{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", "

Introduction to Python for Data Sciences

Franck Iutzeler
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Chap. 2 - Numpy and co.
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\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 1- Packages\n", "\n", "\n", "\n", "Python has a large standard library, commonly cited as one of Python's greatest strengths, providing tools suited to many tasks. As of May, 2017, the official repository containing third-party software for Python, contains over 107,000 packages.\n", "\n", "A *package* is a collection of *modules* i.e. groups of functions, classes, constants, types, etc." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Built-in modules\n", "\n", "To use a module, you have to *import* it using the command `import`." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import math" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can now use it in the code by using its name as a prefix. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.0\n" ] } ], "source": [ "x = math.cos(2 * math.pi)\n", "\n", "print(x)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To explore the function and other content of the module/library:\n", " * Use the web documentation (e.g. for the `math` library Doc for Python 3)\n", " * Use the built-in`help`" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on built-in module math:\n", "\n", "NAME\n", " math\n", "\n", "DESCRIPTION\n", " This module provides access to the mathematical functions\n", " defined by the C standard.\n", "\n", "FUNCTIONS\n", " acos(x, /)\n", " Return the arc cosine (measured in radians) of x.\n", " \n", " acosh(x, /)\n", " Return the inverse hyperbolic cosine of x.\n", " \n", " asin(x, /)\n", " Return the arc sine (measured in radians) of x.\n", " \n", " asinh(x, /)\n", " Return the inverse hyperbolic sine of x.\n", " \n", " atan(x, /)\n", " Return the arc tangent (measured in radians) of x.\n", " \n", " atan2(y, x, /)\n", " Return the arc tangent (measured in radians) of y/x.\n", " \n", " Unlike atan(y/x), the signs of both x and y are considered.\n", " \n", " atanh(x, /)\n", " Return the inverse hyperbolic tangent of x.\n", " \n", " ceil(x, /)\n", " Return the ceiling of x as an Integral.\n", " \n", " This is the smallest integer >= x.\n", " \n", " comb(n, k, /)\n", " Number of ways to choose k items from n items without repetition and without order.\n", " \n", " Evaluates to n! / (k! * (n - k)!) when k <= n and evaluates\n", " to zero when k > n.\n", " \n", " Also called the binomial coefficient because it is equivalent\n", " to the coefficient of k-th term in polynomial expansion of the\n", " expression (1 + x)**n.\n", " \n", " Raises TypeError if either of the arguments are not integers.\n", " Raises ValueError if either of the arguments are negative.\n", " \n", " copysign(x, y, /)\n", " Return a float with the magnitude (absolute value) of x but the sign of y.\n", " \n", " On platforms that support signed zeros, copysign(1.0, -0.0)\n", " returns -1.0.\n", " \n", " cos(x, /)\n", " Return the cosine of x (measured in radians).\n", " \n", " cosh(x, /)\n", " Return the hyperbolic cosine of x.\n", " \n", " degrees(x, /)\n", " Convert angle x from radians to degrees.\n", " \n", " dist(p, q, /)\n", " Return the Euclidean distance between two points p and q.\n", " \n", " The points should be specified as sequences (or iterables) of\n", " coordinates. Both inputs must have the same dimension.\n", " \n", " Roughly equivalent to:\n", " sqrt(sum((px - qx) ** 2.0 for px, qx in zip(p, q)))\n", " \n", " erf(x, /)\n", " Error function at x.\n", " \n", " erfc(x, /)\n", " Complementary error function at x.\n", " \n", " exp(x, /)\n", " Return e raised to the power of x.\n", " \n", " expm1(x, /)\n", " Return exp(x)-1.\n", " \n", " This function avoids the loss of precision involved in the direct evaluation of exp(x)-1 for small x.\n", " \n", " fabs(x, /)\n", " Return the absolute value of the float x.\n", " \n", " factorial(x, /)\n", " Find x!.\n", " \n", " Raise a ValueError if x is negative or non-integral.\n", " \n", " floor(x, /)\n", " Return the floor of x as an Integral.\n", " \n", " This is the largest integer <= x.\n", " \n", " fmod(x, y, /)\n", " Return fmod(x, y), according to platform C.\n", " \n", " x % y may differ.\n", " \n", " frexp(x, /)\n", " Return the mantissa and exponent of x, as pair (m, e).\n", " \n", " m is a float and e is an int, such that x = m * 2.**e.\n", " If x is 0, m and e are both 0. Else 0.5 <= abs(m) < 1.0.\n", " \n", " fsum(seq, /)\n", " Return an accurate floating point sum of values in the iterable seq.\n", " \n", " Assumes IEEE-754 floating point arithmetic.\n", " \n", " gamma(x, /)\n", " Gamma function at x.\n", " \n", " gcd(x, y, /)\n", " greatest common divisor of x and y\n", " \n", " hypot(...)\n", " hypot(*coordinates) -> value\n", " \n", " Multidimensional Euclidean distance from the origin to a point.\n", " \n", " Roughly equivalent to:\n", " sqrt(sum(x**2 for x in coordinates))\n", " \n", " For a two dimensional point (x, y), gives the hypotenuse\n", " using the Pythagorean theorem: sqrt(x*x + y*y).\n", " \n", " For example, the hypotenuse of a 3/4/5 right triangle is:\n", " \n", " >>> hypot(3.0, 4.0)\n", " 5.0\n", " \n", " isclose(a, b, *, rel_tol=1e-09, abs_tol=0.0)\n", " Determine whether two floating point numbers are close in value.\n", " \n", " rel_tol\n", " maximum difference for being considered \"close\", relative to the\n", " magnitude of the input values\n", " abs_tol\n", " maximum difference for being considered \"close\", regardless of the\n", " magnitude of the input values\n", " \n", " Return True if a is close in value to b, and False otherwise.\n", " \n", " For the values to be considered close, the difference between them\n", " must be smaller than at least one of the tolerances.\n", " \n", " -inf, inf and NaN behave similarly to the IEEE 754 Standard. That\n", " is, NaN is not close to anything, even itself. inf and -inf are\n", " only close to themselves.\n", " \n", " isfinite(x, /)\n", " Return True if x is neither an infinity nor a NaN, and False otherwise.\n", " \n", " isinf(x, /)\n", " Return True if x is a positive or negative infinity, and False otherwise.\n", " \n", " isnan(x, /)\n", " Return True if x is a NaN (not a number), and False otherwise.\n", " \n", " isqrt(n, /)\n", " Return the integer part of the square root of the input.\n", " \n", " ldexp(x, i, /)\n", " Return x * (2**i).\n", " \n", " This is essentially the inverse of frexp().\n", " \n", " lgamma(x, /)\n", " Natural logarithm of absolute value of Gamma function at x.\n", " \n", " log(...)\n", " log(x, [base=math.e])\n", " Return the logarithm of x to the given base.\n", " \n", " If the base not specified, returns the natural logarithm (base e) of x.\n", " \n", " log10(x, /)\n", " Return the base 10 logarithm of x.\n", " \n", " log1p(x, /)\n", " Return the natural logarithm of 1+x (base e).\n", " \n", " The result is computed in a way which is accurate for x near zero.\n", " \n", " log2(x, /)\n", " Return the base 2 logarithm of x.\n", " \n", " modf(x, /)\n", " Return the fractional and integer parts of x.\n", " \n", " Both results carry the sign of x and are floats.\n", " \n", " perm(n, k=None, /)\n", " Number of ways to choose k items from n items without repetition and with order.\n", " \n", " Evaluates to n! / (n - k)! when k <= n and evaluates\n", " to zero when k > n.\n", " \n", " If k is not specified or is None, then k defaults to n\n", " and the function returns n!.\n", " \n", " Raises TypeError if either of the arguments are not integers.\n", " Raises ValueError if either of the arguments are negative.\n", " \n", " pow(x, y, /)\n", " Return x**y (x to the power of y).\n", " \n", " prod(iterable, /, *, start=1)\n", " Calculate the product of all the elements in the input iterable.\n", " \n", " The default start value for the product is 1.\n", " \n", " When the iterable is empty, return the start value. This function is\n", " intended specifically for use with numeric values and may reject\n", " non-numeric types.\n", " \n", " radians(x, /)\n", " Convert angle x from degrees to radians.\n", " \n", " remainder(x, y, /)\n", " Difference between x and the closest integer multiple of y.\n", " \n", " Return x - n*y where n*y is the closest integer multiple of y.\n", " In the case where x is exactly halfway between two multiples of\n", " y, the nearest even value of n is used. The result is always exact.\n", " \n", " sin(x, /)\n", " Return the sine of x (measured in radians).\n", " \n", " sinh(x, /)\n", " Return the hyperbolic sine of x.\n", " \n", " sqrt(x, /)\n", " Return the square root of x.\n", " \n", " tan(x, /)\n", " Return the tangent of x (measured in radians).\n", " \n", " tanh(x, /)\n", " Return the hyperbolic tangent of x.\n", " \n", " trunc(x, /)\n", " Truncates the Real x to the nearest Integral toward 0.\n", " \n", " Uses the __trunc__ magic method.\n", "\n", "DATA\n", " e = 2.718281828459045\n", " inf = inf\n", " nan = nan\n", " pi = 3.141592653589793\n", " tau = 6.283185307179586\n", "\n", "FILE\n", " (built-in)\n", "\n", "\n" ] } ], "source": [ "help(math)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on built-in function sqrt in module math:\n", "\n", "sqrt(x, /)\n", " Return the square root of x.\n", "\n" ] } ], "source": [ "help(math.sqrt)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the name prefix can make the code obfuscated as it can get quite verbose (e.g. `scipy.optimize.minimize`) so Python provides simpler ways to import:\n", "* `import name as nickname`: the prefix to call is now `nickname`" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3.141592653589793\n" ] } ], "source": [ "import math as m\n", "\n", "print(m.pi)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* `from name import function1,constant1` : `function1` `constant1` can now be called directly. You can even import all contents with `from name import *` but this may be dangerous as names may conflict or override former ones, it is thus not advised except on user-generated modules." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "4.0\n" ] } ], "source": [ "from math import e,log\n", "\n", "print(log(e**4))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## Installing packages\n", "\n", "\n", "Python comes with a lot a lot of packages (ie. functions and small programs), provided by the community. To install a package `SomePackage`, the recommended way is know to use `pip` :\n", "\n", "`python -m pip install SomePackage` or simply `pip install SomePackage`\n", "\n", "\n", "See https://docs.python.org/3.9/installing/index.html for details on installing packages (and if you do not have `pip` installed, see https://packaging.python.org/tutorials/installing-packages/#requirements-for-installing-packages )\n", "\n", "\n", "*Warning:* this is the preferred way, however:\n", "* if you are using Anaconda, it is preferrable to install packages directly using the Anaconda interface, see https://docs.anaconda.com/anaconda/navigator/tutorials/manage-packages/ \n", "* If you don't have administrator rights on the machine (eg. at university), use `pip --user install SomePackage` to install a package locally." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once installed, you can import the packages as above. " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "import scipy" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on package scipy:\n", "\n", "NAME\n", " scipy\n", "\n", "DESCRIPTION\n", " SciPy: A scientific computing package for Python\n", " ================================================\n", " \n", " Documentation is available in the docstrings and\n", " online at https://docs.scipy.org.\n", " \n", " Contents\n", " --------\n", " SciPy imports all the functions from the NumPy namespace, and in\n", " addition provides:\n", " \n", " Subpackages\n", " -----------\n", " Using any of these subpackages requires an explicit import. For example,\n", " ``import scipy.cluster``.\n", " \n", " ::\n", " \n", " cluster --- Vector Quantization / Kmeans\n", " fft --- Discrete Fourier transforms\n", " fftpack --- Legacy discrete Fourier transforms\n", " integrate --- Integration routines\n", " interpolate --- Interpolation Tools\n", " io --- Data input and output\n", " linalg --- Linear algebra routines\n", " linalg.blas --- Wrappers to BLAS library\n", " linalg.lapack --- Wrappers to LAPACK library\n", " misc --- Various utilities that don't have\n", " another home.\n", " ndimage --- N-D image package\n", " odr --- Orthogonal Distance Regression\n", " optimize --- Optimization Tools\n", " signal --- Signal Processing Tools\n", " signal.windows --- Window functions\n", " sparse --- Sparse Matrices\n", " sparse.linalg --- Sparse Linear Algebra\n", " sparse.linalg.dsolve --- Linear Solvers\n", " sparse.linalg.dsolve.umfpack --- :Interface to the UMFPACK library:\n", " Conjugate Gradient Method (LOBPCG)\n", " sparse.linalg.eigen --- Sparse Eigenvalue Solvers\n", " sparse.linalg.eigen.lobpcg --- Locally Optimal Block Preconditioned\n", " Conjugate Gradient Method (LOBPCG)\n", " spatial --- Spatial data structures and algorithms\n", " special --- Special functions\n", " stats --- Statistical Functions\n", " \n", " Utility tools\n", " -------------\n", " ::\n", " \n", " test --- Run scipy unittests\n", " show_config --- Show scipy build configuration\n", " show_numpy_config --- Show numpy build configuration\n", " __version__ --- SciPy version string\n", " __numpy_version__ --- Numpy version string\n", "\n", "PACKAGE CONTENTS\n", " __config__\n", " _build_utils (package)\n", " _distributor_init\n", " _lib (package)\n", " cluster (package)\n", " conftest\n", " constants (package)\n", " fft (package)\n", " fftpack (package)\n", " integrate (package)\n", " interpolate (package)\n", " io (package)\n", " linalg (package)\n", " misc (package)\n", " ndimage (package)\n", " odr (package)\n", " optimize (package)\n", " setup\n", " signal (package)\n", " sparse (package)\n", " spatial (package)\n", " special (package)\n", " stats (package)\n", " version\n", "\n", "CLASSES\n", " builtins.DeprecationWarning(builtins.Warning)\n", " numpy.ModuleDeprecationWarning\n", " builtins.IndexError(builtins.LookupError)\n", " numpy.AxisError(builtins.ValueError, builtins.IndexError)\n", " builtins.RuntimeError(builtins.Exception)\n", " numpy.TooHardError\n", " builtins.RuntimeWarning(builtins.Warning)\n", " numpy.ComplexWarning\n", " builtins.UserWarning(builtins.Warning)\n", " numpy.RankWarning\n", " numpy.VisibleDeprecationWarning\n", " builtins.ValueError(builtins.Exception)\n", " numpy.AxisError(builtins.ValueError, builtins.IndexError)\n", " builtins.bytes(builtins.object)\n", " numpy.bytes_(builtins.bytes, numpy.character)\n", " builtins.object\n", " numpy.DataSource\n", " numpy.MachAr\n", " numpy.broadcast\n", " numpy.busdaycalendar\n", " numpy.dtype\n", " numpy.finfo\n", " numpy.flatiter\n", " numpy.format_parser\n", " numpy.generic\n", " numpy.bool_\n", " numpy.datetime64\n", " numpy.flexible\n", " numpy.character\n", " numpy.bytes_(builtins.bytes, numpy.character)\n", " numpy.str_(builtins.str, numpy.character)\n", " numpy.void\n", " numpy.record\n", " numpy.number\n", " numpy.inexact\n", " numpy.complexfloating\n", " numpy.complex128(numpy.complexfloating, builtins.complex)\n", " numpy.complex256\n", " numpy.complex64\n", " numpy.floating\n", " numpy.float128\n", " numpy.float16\n", " numpy.float32\n", " numpy.float64(numpy.floating, builtins.float)\n", " numpy.integer\n", " numpy.signedinteger\n", " numpy.int16\n", " numpy.int32\n", " numpy.int64\n", " numpy.int8\n", " numpy.longlong\n", " numpy.timedelta64\n", " numpy.unsignedinteger\n", " numpy.uint16\n", " numpy.uint32\n", " numpy.uint64\n", " numpy.uint8\n", " numpy.ulonglong\n", " numpy.object_\n", " numpy.iinfo\n", " numpy.ndarray\n", " numpy.chararray\n", " numpy.matrix\n", " numpy.memmap\n", " numpy.recarray\n", " numpy.ndenumerate\n", " numpy.ndindex\n", " numpy.nditer\n", " numpy.poly1d\n", " numpy.ufunc\n", " numpy.vectorize\n", " builtins.str(builtins.object)\n", " numpy.str_(builtins.str, numpy.character)\n", " contextlib.ContextDecorator(builtins.object)\n", " numpy.errstate\n", " \n", " class AxisError(builtins.ValueError, builtins.IndexError)\n", " | AxisError(axis, ndim=None, msg_prefix=None)\n", " | \n", " | Axis supplied was invalid.\n", " | \n", " | Method resolution order:\n", " | AxisError\n", " | builtins.ValueError\n", " | builtins.IndexError\n", " | builtins.LookupError\n", " | builtins.Exception\n", " | builtins.BaseException\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __init__(self, axis, ndim=None, msg_prefix=None)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.ValueError:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.BaseException:\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __repr__(self, /)\n", " | Return repr(self).\n", " | \n", " | __setattr__(self, name, value, /)\n", " | Implement setattr(self, name, value).\n", " | \n", " | __setstate__(...)\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | with_traceback(...)\n", " | Exception.with_traceback(tb) --\n", " | set self.__traceback__ to tb and return self.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from builtins.BaseException:\n", " | \n", " | __cause__\n", " | exception cause\n", " | \n", " | __context__\n", " | exception context\n", " | \n", " | __dict__\n", " | \n", " | __suppress_context__\n", " | \n", " | __traceback__\n", " | \n", " | args\n", " \n", " class ComplexWarning(builtins.RuntimeWarning)\n", " | The warning raised when casting a complex dtype to a real dtype.\n", " | \n", " | As implemented, casting a complex number to a real discards its imaginary\n", " | part, but this behavior may not be what the user actually wants.\n", " | \n", " | Method resolution order:\n", " | ComplexWarning\n", " | builtins.RuntimeWarning\n", " | builtins.Warning\n", " | builtins.Exception\n", " | builtins.BaseException\n", " | builtins.object\n", " | \n", " | Data descriptors defined here:\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.RuntimeWarning:\n", " | \n", " | __init__(self, /, *args, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.RuntimeWarning:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.BaseException:\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __repr__(self, /)\n", " | Return repr(self).\n", " | \n", " | __setattr__(self, name, value, /)\n", " | Implement setattr(self, name, value).\n", " | \n", " | __setstate__(...)\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | with_traceback(...)\n", " | Exception.with_traceback(tb) --\n", " | set self.__traceback__ to tb and return self.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from builtins.BaseException:\n", " | \n", " | __cause__\n", " | exception cause\n", " | \n", " | __context__\n", " | exception context\n", " | \n", " | __dict__\n", " | \n", " | __suppress_context__\n", " | \n", " | __traceback__\n", " | \n", " | args\n", " \n", " class DataSource(builtins.object)\n", " | DataSource(destpath='.')\n", " | \n", " | DataSource(destpath='.')\n", " | \n", " | A generic data source file (file, http, ftp, ...).\n", " | \n", " | DataSources can be local files or remote files/URLs. The files may\n", " | also be compressed or uncompressed. DataSource hides some of the\n", " | low-level details of downloading the file, allowing you to simply pass\n", " | in a valid file path (or URL) and obtain a file object.\n", " | \n", " | Parameters\n", " | ----------\n", " | destpath : str or None, optional\n", " | Path to the directory where the source file gets downloaded to for\n", " | use. If `destpath` is None, a temporary directory will be created.\n", " | The default path is the current directory.\n", " | \n", " | Notes\n", " | -----\n", " | URLs require a scheme string (``http://``) to be used, without it they\n", " | will fail::\n", " | \n", " | >>> repos = np.DataSource()\n", " | >>> repos.exists('www.google.com/index.html')\n", " | False\n", " | >>> repos.exists('http://www.google.com/index.html')\n", " | True\n", " | \n", " | Temporary directories are deleted when the DataSource is deleted.\n", " | \n", " | Examples\n", " | --------\n", " | ::\n", " | \n", " | >>> ds = np.DataSource('/home/guido')\n", " | >>> urlname = 'http://www.google.com/'\n", " | >>> gfile = ds.open('http://www.google.com/')\n", " | >>> ds.abspath(urlname)\n", " | '/home/guido/www.google.com/index.html'\n", " | \n", " | >>> ds = np.DataSource(None) # use with temporary file\n", " | >>> ds.open('/home/guido/foobar.txt')\n", " | \n", " | >>> ds.abspath('/home/guido/foobar.txt')\n", " | '/tmp/.../home/guido/foobar.txt'\n", " | \n", " | Methods defined here:\n", " | \n", " | __del__(self)\n", " | \n", " | __init__(self, destpath='.')\n", " | Create a DataSource with a local path at destpath.\n", " | \n", " | abspath(self, path)\n", " | Return absolute path of file in the DataSource directory.\n", " | \n", " | If `path` is an URL, then `abspath` will return either the location\n", " | the file exists locally or the location it would exist when opened\n", " | using the `open` method.\n", " | \n", " | Parameters\n", " | ----------\n", " | path : str\n", " | Can be a local file or a remote URL.\n", " | \n", " | Returns\n", " | -------\n", " | out : str\n", " | Complete path, including the `DataSource` destination directory.\n", " | \n", " | Notes\n", " | -----\n", " | The functionality is based on `os.path.abspath`.\n", " | \n", " | exists(self, path)\n", " | Test if path exists.\n", " | \n", " | Test if `path` exists as (and in this order):\n", " | \n", " | - a local file.\n", " | - a remote URL that has been downloaded and stored locally in the\n", " | `DataSource` directory.\n", " | - a remote URL that has not been downloaded, but is valid and\n", " | accessible.\n", " | \n", " | Parameters\n", " | ----------\n", " | path : str\n", " | Can be a local file or a remote URL.\n", " | \n", " | Returns\n", " | -------\n", " | out : bool\n", " | True if `path` exists.\n", " | \n", " | Notes\n", " | -----\n", " | When `path` is an URL, `exists` will return True if it's either\n", " | stored locally in the `DataSource` directory, or is a valid remote\n", " | URL. `DataSource` does not discriminate between the two, the file\n", " | is accessible if it exists in either location.\n", " | \n", " | open(self, path, mode='r', encoding=None, newline=None)\n", " | Open and return file-like object.\n", " | \n", " | If `path` is an URL, it will be downloaded, stored in the\n", " | `DataSource` directory and opened from there.\n", " | \n", " | Parameters\n", " | ----------\n", " | path : str\n", " | Local file path or URL to open.\n", " | mode : {'r', 'w', 'a'}, optional\n", " | Mode to open `path`. Mode 'r' for reading, 'w' for writing,\n", " | 'a' to append. Available modes depend on the type of object\n", " | specified by `path`. Default is 'r'.\n", " | encoding : {None, str}, optional\n", " | Open text file with given encoding. The default encoding will be\n", " | what `io.open` uses.\n", " | newline : {None, str}, optional\n", " | Newline to use when reading text file.\n", " | \n", " | Returns\n", " | -------\n", " | out : file object\n", " | File object.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class MachAr(builtins.object)\n", " | MachAr(float_conv=, int_conv=, float_to_float=, float_to_str= at 0x7f99240989d0>, title='Python floating point number')\n", " | \n", " | Diagnosing machine parameters.\n", " | \n", " | Attributes\n", " | ----------\n", " | ibeta : int\n", " | Radix in which numbers are represented.\n", " | it : int\n", " | Number of base-`ibeta` digits in the floating point mantissa M.\n", " | machep : int\n", " | Exponent of the smallest (most negative) power of `ibeta` that,\n", " | added to 1.0, gives something different from 1.0\n", " | eps : float\n", " | Floating-point number ``beta**machep`` (floating point precision)\n", " | negep : int\n", " | Exponent of the smallest power of `ibeta` that, subtracted\n", " | from 1.0, gives something different from 1.0.\n", " | epsneg : float\n", " | Floating-point number ``beta**negep``.\n", " | iexp : int\n", " | Number of bits in the exponent (including its sign and bias).\n", " | minexp : int\n", " | Smallest (most negative) power of `ibeta` consistent with there\n", " | being no leading zeros in the mantissa.\n", " | xmin : float\n", " | Floating point number ``beta**minexp`` (the smallest [in\n", " | magnitude] usable floating value).\n", " | maxexp : int\n", " | Smallest (positive) power of `ibeta` that causes overflow.\n", " | xmax : float\n", " | ``(1-epsneg) * beta**maxexp`` (the largest [in magnitude]\n", " | usable floating value).\n", " | irnd : int\n", " | In ``range(6)``, information on what kind of rounding is done\n", " | in addition, and on how underflow is handled.\n", " | ngrd : int\n", " | Number of 'guard digits' used when truncating the product\n", " | of two mantissas to fit the representation.\n", " | epsilon : float\n", " | Same as `eps`.\n", " | tiny : float\n", " | Same as `xmin`.\n", " | huge : float\n", " | Same as `xmax`.\n", " | precision : float\n", " | ``- int(-log10(eps))``\n", " | resolution : float\n", " | ``- 10**(-precision)``\n", " | \n", " | Parameters\n", " | ----------\n", " | float_conv : function, optional\n", " | Function that converts an integer or integer array to a float\n", " | or float array. Default is `float`.\n", " | int_conv : function, optional\n", " | Function that converts a float or float array to an integer or\n", " | integer array. Default is `int`.\n", " | float_to_float : function, optional\n", " | Function that converts a float array to float. Default is `float`.\n", " | Note that this does not seem to do anything useful in the current\n", " | implementation.\n", " | float_to_str : function, optional\n", " | Function that converts a single float to a string. Default is\n", " | ``lambda v:'%24.16e' %v``.\n", " | title : str, optional\n", " | Title that is printed in the string representation of `MachAr`.\n", " | \n", " | See Also\n", " | --------\n", " | finfo : Machine limits for floating point types.\n", " | iinfo : Machine limits for integer types.\n", " | \n", " | References\n", " | ----------\n", " | .. [1] Press, Teukolsky, Vetterling and Flannery,\n", " | \"Numerical Recipes in C++,\" 2nd ed,\n", " | Cambridge University Press, 2002, p. 31.\n", " | \n", " | Methods defined here:\n", " | \n", " | __init__(self, float_conv=, int_conv=, float_to_float=, float_to_str= at 0x7f99240989d0>, title='Python floating point number')\n", " | float_conv - convert integer to float (array)\n", " | int_conv - convert float (array) to integer\n", " | float_to_float - convert float array to float\n", " | float_to_str - convert array float to str\n", " | title - description of used floating point numbers\n", " | \n", " | __str__(self)\n", " | Return str(self).\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class ModuleDeprecationWarning(builtins.DeprecationWarning)\n", " | Module deprecation warning.\n", " | \n", " | The nose tester turns ordinary Deprecation warnings into test failures.\n", " | That makes it hard to deprecate whole modules, because they get\n", " | imported by default. So this is a special Deprecation warning that the\n", " | nose tester will let pass without making tests fail.\n", " | \n", " | Method resolution order:\n", " | ModuleDeprecationWarning\n", " | builtins.DeprecationWarning\n", " | builtins.Warning\n", " | builtins.Exception\n", " | builtins.BaseException\n", " | builtins.object\n", " | \n", " | Data descriptors defined here:\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.DeprecationWarning:\n", " | \n", " | __init__(self, /, *args, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.DeprecationWarning:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.BaseException:\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __repr__(self, /)\n", " | Return repr(self).\n", " | \n", " | __setattr__(self, name, value, /)\n", " | Implement setattr(self, name, value).\n", " | \n", " | __setstate__(...)\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | with_traceback(...)\n", " | Exception.with_traceback(tb) --\n", " | set self.__traceback__ to tb and return self.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from builtins.BaseException:\n", " | \n", " | __cause__\n", " | exception cause\n", " | \n", " | __context__\n", " | exception context\n", " | \n", " | __dict__\n", " | \n", " | __suppress_context__\n", " | \n", " | __traceback__\n", " | \n", " | args\n", " \n", " class RankWarning(builtins.UserWarning)\n", " | Issued by `polyfit` when the Vandermonde matrix is rank deficient.\n", " | \n", " | For more information, a way to suppress the warning, and an example of\n", " | `RankWarning` being issued, see `polyfit`.\n", " | \n", " | Method resolution order:\n", " | RankWarning\n", " | builtins.UserWarning\n", " | builtins.Warning\n", " | builtins.Exception\n", " | builtins.BaseException\n", " | builtins.object\n", " | \n", " | Data descriptors defined here:\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.UserWarning:\n", " | \n", " | __init__(self, /, *args, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.UserWarning:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.BaseException:\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __repr__(self, /)\n", " | Return repr(self).\n", " | \n", " | __setattr__(self, name, value, /)\n", " | Implement setattr(self, name, value).\n", " | \n", " | __setstate__(...)\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | with_traceback(...)\n", " | Exception.with_traceback(tb) --\n", " | set self.__traceback__ to tb and return self.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from builtins.BaseException:\n", " | \n", " | __cause__\n", " | exception cause\n", " | \n", " | __context__\n", " | exception context\n", " | \n", " | __dict__\n", " | \n", " | __suppress_context__\n", " | \n", " | __traceback__\n", " | \n", " | args\n", " \n", " class TooHardError(builtins.RuntimeError)\n", " | Unspecified run-time error.\n", " | \n", " | Method resolution order:\n", " | TooHardError\n", " | builtins.RuntimeError\n", " | builtins.Exception\n", " | builtins.BaseException\n", " | builtins.object\n", " | \n", " | Data descriptors defined here:\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.RuntimeError:\n", " | \n", " | __init__(self, /, *args, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.RuntimeError:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.BaseException:\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __repr__(self, /)\n", " | Return repr(self).\n", " | \n", " | __setattr__(self, name, value, /)\n", " | Implement setattr(self, name, value).\n", " | \n", " | __setstate__(...)\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | with_traceback(...)\n", " | Exception.with_traceback(tb) --\n", " | set self.__traceback__ to tb and return self.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from builtins.BaseException:\n", " | \n", " | __cause__\n", " | exception cause\n", " | \n", " | __context__\n", " | exception context\n", " | \n", " | __dict__\n", " | \n", " | __suppress_context__\n", " | \n", " | __traceback__\n", " | \n", " | args\n", " \n", " class VisibleDeprecationWarning(builtins.UserWarning)\n", " | Visible deprecation warning.\n", " | \n", " | By default, python will not show deprecation warnings, so this class\n", " | can be used when a very visible warning is helpful, for example because\n", " | the usage is most likely a user bug.\n", " | \n", " | Method resolution order:\n", " | VisibleDeprecationWarning\n", " | builtins.UserWarning\n", " | builtins.Warning\n", " | builtins.Exception\n", " | builtins.BaseException\n", " | builtins.object\n", " | \n", " | Data descriptors defined here:\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.UserWarning:\n", " | \n", " | __init__(self, /, *args, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.UserWarning:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.BaseException:\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __repr__(self, /)\n", " | Return repr(self).\n", " | \n", " | __setattr__(self, name, value, /)\n", " | Implement setattr(self, name, value).\n", " | \n", " | __setstate__(...)\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | with_traceback(...)\n", " | Exception.with_traceback(tb) --\n", " | set self.__traceback__ to tb and return self.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from builtins.BaseException:\n", " | \n", " | __cause__\n", " | exception cause\n", " | \n", " | __context__\n", " | exception context\n", " | \n", " | __dict__\n", " | \n", " | __suppress_context__\n", " | \n", " | __traceback__\n", " | \n", " | args\n", " \n", " bool8 = class bool_(generic)\n", " | Boolean type (True or False), stored as a byte.\n", " | Character code: ``'?'``.\n", " | Alias: ``np.bool8``.\n", " | \n", " | Method resolution order:\n", " | bool_\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class bool_(generic)\n", " | Boolean type (True or False), stored as a byte.\n", " | Character code: ``'?'``.\n", " | Alias: ``np.bool8``.\n", " | \n", " | Method resolution order:\n", " | bool_\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class broadcast(builtins.object)\n", " | Produce an object that mimics broadcasting.\n", " | \n", " | Parameters\n", " | ----------\n", " | in1, in2, ... : array_like\n", " | Input parameters.\n", " | \n", " | Returns\n", " | -------\n", " | b : broadcast object\n", " | Broadcast the input parameters against one another, and\n", " | return an object that encapsulates the result.\n", " | Amongst others, it has ``shape`` and ``nd`` properties, and\n", " | may be used as an iterator.\n", " | \n", " | See Also\n", " | --------\n", " | broadcast_arrays\n", " | broadcast_to\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | Manually adding two vectors, using broadcasting:\n", " | \n", " | >>> x = np.array([[1], [2], [3]])\n", " | >>> y = np.array([4, 5, 6])\n", " | >>> b = np.broadcast(x, y)\n", " | \n", " | >>> out = np.empty(b.shape)\n", " | >>> out.flat = [u+v for (u,v) in b]\n", " | >>> out\n", " | array([[5., 6., 7.],\n", " | [6., 7., 8.],\n", " | [7., 8., 9.]])\n", " | \n", " | Compare against built-in broadcasting:\n", " | \n", " | >>> x + y\n", " | array([[5, 6, 7],\n", " | [6, 7, 8],\n", " | [7, 8, 9]])\n", " | \n", " | Methods defined here:\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __next__(self, /)\n", " | Implement next(self).\n", " | \n", " | reset(...)\n", " | reset()\n", " | \n", " | Reset the broadcasted result's iterator(s).\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> y = np.array([[4], [5], [6]])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> b.index\n", " | 0\n", " | >>> next(b), next(b), next(b)\n", " | ((1, 4), (2, 4), (3, 4))\n", " | >>> b.index\n", " | 3\n", " | >>> b.reset()\n", " | >>> b.index\n", " | 0\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | index\n", " | current index in broadcasted result\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([[1], [2], [3]])\n", " | >>> y = np.array([4, 5, 6])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> b.index\n", " | 0\n", " | >>> next(b), next(b), next(b)\n", " | ((1, 4), (1, 5), (1, 6))\n", " | >>> b.index\n", " | 3\n", " | \n", " | iters\n", " | tuple of iterators along ``self``'s \"components.\"\n", " | \n", " | Returns a tuple of `numpy.flatiter` objects, one for each \"component\"\n", " | of ``self``.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> y = np.array([[4], [5], [6]])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> row, col = b.iters\n", " | >>> next(row), next(col)\n", " | (1, 4)\n", " | \n", " | nd\n", " | Number of dimensions of broadcasted result. For code intended for NumPy\n", " | 1.12.0 and later the more consistent `ndim` is preferred.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> y = np.array([[4], [5], [6]])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> b.nd\n", " | 2\n", " | \n", " | ndim\n", " | Number of dimensions of broadcasted result. Alias for `nd`.\n", " | \n", " | .. versionadded:: 1.12.0\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> y = np.array([[4], [5], [6]])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> b.ndim\n", " | 2\n", " | \n", " | numiter\n", " | Number of iterators possessed by the broadcasted result.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> y = np.array([[4], [5], [6]])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> b.numiter\n", " | 2\n", " | \n", " | shape\n", " | Shape of broadcasted result.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> y = np.array([[4], [5], [6]])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> b.shape\n", " | (3, 3)\n", " | \n", " | size\n", " | Total size of broadcasted result.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> y = np.array([[4], [5], [6]])\n", " | >>> b = np.broadcast(x, y)\n", " | >>> b.size\n", " | 9\n", " \n", " class busdaycalendar(builtins.object)\n", " | busdaycalendar(weekmask='1111100', holidays=None)\n", " | \n", " | A business day calendar object that efficiently stores information\n", " | defining valid days for the busday family of functions.\n", " | \n", " | The default valid days are Monday through Friday (\"business days\").\n", " | A busdaycalendar object can be specified with any set of weekly\n", " | valid days, plus an optional \"holiday\" dates that always will be invalid.\n", " | \n", " | Once a busdaycalendar object is created, the weekmask and holidays\n", " | cannot be modified.\n", " | \n", " | .. versionadded:: 1.7.0\n", " | \n", " | Parameters\n", " | ----------\n", " | weekmask : str or array_like of bool, optional\n", " | A seven-element array indicating which of Monday through Sunday are\n", " | valid days. May be specified as a length-seven list or array, like\n", " | [1,1,1,1,1,0,0]; a length-seven string, like '1111100'; or a string\n", " | like \"Mon Tue Wed Thu Fri\", made up of 3-character abbreviations for\n", " | weekdays, optionally separated by white space. Valid abbreviations\n", " | are: Mon Tue Wed Thu Fri Sat Sun\n", " | holidays : array_like of datetime64[D], optional\n", " | An array of dates to consider as invalid dates, no matter which\n", " | weekday they fall upon. Holiday dates may be specified in any\n", " | order, and NaT (not-a-time) dates are ignored. This list is\n", " | saved in a normalized form that is suited for fast calculations\n", " | of valid days.\n", " | \n", " | Returns\n", " | -------\n", " | out : busdaycalendar\n", " | A business day calendar object containing the specified\n", " | weekmask and holidays values.\n", " | \n", " | See Also\n", " | --------\n", " | is_busday : Returns a boolean array indicating valid days.\n", " | busday_offset : Applies an offset counted in valid days.\n", " | busday_count : Counts how many valid days are in a half-open date range.\n", " | \n", " | Attributes\n", " | ----------\n", " | Note: once a busdaycalendar object is created, you cannot modify the\n", " | weekmask or holidays. The attributes return copies of internal data.\n", " | weekmask : (copy) seven-element array of bool\n", " | holidays : (copy) sorted array of datetime64[D]\n", " | \n", " | Examples\n", " | --------\n", " | >>> # Some important days in July\n", " | ... bdd = np.busdaycalendar(\n", " | ... holidays=['2011-07-01', '2011-07-04', '2011-07-17'])\n", " | >>> # Default is Monday to Friday weekdays\n", " | ... bdd.weekmask\n", " | array([ True, True, True, True, True, False, False])\n", " | >>> # Any holidays already on the weekend are removed\n", " | ... bdd.holidays\n", " | array(['2011-07-01', '2011-07-04'], dtype='datetime64[D]')\n", " | \n", " | Methods defined here:\n", " | \n", " | __init__(self, /, *args, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | holidays\n", " | A copy of the holiday array indicating additional invalid days.\n", " | \n", " | weekmask\n", " | A copy of the seven-element boolean mask indicating valid days.\n", " \n", " byte = class int8(signedinteger)\n", " | Signed integer type, compatible with C ``char``.\n", " | Character code: ``'b'``.\n", " | Canonical name: ``np.byte``.\n", " | Alias *on this platform*: ``np.int8``: 8-bit signed integer (-128 to 127).\n", " | \n", " | Method resolution order:\n", " | int8\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " bytes0 = class bytes_(builtins.bytes, character)\n", " | bytes(iterable_of_ints) -> bytes\n", " | bytes(string, encoding[, errors]) -> bytes\n", " | bytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\n", " | bytes(int) -> bytes object of size given by the parameter initialized with null bytes\n", " | bytes() -> empty bytes object\n", " | \n", " | Construct an immutable array of bytes from:\n", " | - an iterable yielding integers in range(256)\n", " | - a text string encoded using the specified encoding\n", " | - any object implementing the buffer API.\n", " | - an integer\n", " | \n", " | Method resolution order:\n", " | bytes_\n", " | builtins.bytes\n", " | character\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self copy of B\n", " | \n", " | Return a copy of B with only its first character capitalized (ASCII)\n", " | and the rest lower-cased.\n", " | \n", " | center(self, width, fillchar=b' ', /)\n", " | Return a centered string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | count(...)\n", " | B.count(sub[, start[, end]]) -> int\n", " | \n", " | Return the number of non-overlapping occurrences of subsection sub in\n", " | bytes B[start:end]. Optional arguments start and end are interpreted\n", " | as in slice notation.\n", " | \n", " | decode(self, /, encoding='utf-8', errors='strict')\n", " | Decode the bytes using the codec registered for encoding.\n", " | \n", " | encoding\n", " | The encoding with which to decode the bytes.\n", " | errors\n", " | The error handling scheme to use for the handling of decoding errors.\n", " | The default is 'strict' meaning that decoding errors raise a\n", " | UnicodeDecodeError. Other possible values are 'ignore' and 'replace'\n", " | as well as any other name registered with codecs.register_error that\n", " | can handle UnicodeDecodeErrors.\n", " | \n", " | endswith(...)\n", " | B.endswith(suffix[, start[, end]]) -> bool\n", " | \n", " | Return True if B ends with the specified suffix, False otherwise.\n", " | With optional start, test B beginning at that position.\n", " | With optional end, stop comparing B at that position.\n", " | suffix can also be a tuple of bytes to try.\n", " | \n", " | expandtabs(self, /, tabsize=8)\n", " | Return a copy where all tab characters are expanded using spaces.\n", " | \n", " | If tabsize is not given, a tab size of 8 characters is assumed.\n", " | \n", " | find(...)\n", " | B.find(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | hex(...)\n", " | Create a str of hexadecimal numbers from a bytes object.\n", " | \n", " | sep\n", " | An optional single character or byte to separate hex bytes.\n", " | bytes_per_sep\n", " | How many bytes between separators. Positive values count from the\n", " | right, negative values count from the left.\n", " | \n", " | Example:\n", " | >>> value = b'\\xb9\\x01\\xef'\n", " | >>> value.hex()\n", " | 'b901ef'\n", " | >>> value.hex(':')\n", " | 'b9:01:ef'\n", " | >>> value.hex(':', 2)\n", " | 'b9:01ef'\n", " | >>> value.hex(':', -2)\n", " | 'b901:ef'\n", " | \n", " | index(...)\n", " | B.index(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the subsection is not found.\n", " | \n", " | isalnum(...)\n", " | B.isalnum() -> bool\n", " | \n", " | Return True if all characters in B are alphanumeric\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | isalpha(...)\n", " | B.isalpha() -> bool\n", " | \n", " | Return True if all characters in B are alphabetic\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | isascii(...)\n", " | B.isascii() -> bool\n", " | \n", " | Return True if B is empty or all characters in B are ASCII,\n", " | False otherwise.\n", " | \n", " | isdigit(...)\n", " | B.isdigit() -> bool\n", " | \n", " | Return True if all characters in B are digits\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | islower(...)\n", " | B.islower() -> bool\n", " | \n", " | Return True if all cased characters in B are lowercase and there is\n", " | at least one cased character in B, False otherwise.\n", " | \n", " | isspace(...)\n", " | B.isspace() -> bool\n", " | \n", " | Return True if all characters in B are whitespace\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | istitle(...)\n", " | B.istitle() -> bool\n", " | \n", " | Return True if B is a titlecased string and there is at least one\n", " | character in B, i.e. uppercase characters may only follow uncased\n", " | characters and lowercase characters only cased ones. Return False\n", " | otherwise.\n", " | \n", " | isupper(...)\n", " | B.isupper() -> bool\n", " | \n", " | Return True if all cased characters in B are uppercase and there is\n", " | at least one cased character in B, False otherwise.\n", " | \n", " | join(self, iterable_of_bytes, /)\n", " | Concatenate any number of bytes objects.\n", " | \n", " | The bytes whose method is called is inserted in between each pair.\n", " | \n", " | The result is returned as a new bytes object.\n", " | \n", " | Example: b'.'.join([b'ab', b'pq', b'rs']) -> b'ab.pq.rs'.\n", " | \n", " | ljust(self, width, fillchar=b' ', /)\n", " | Return a left-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | lower(...)\n", " | B.lower() -> copy of B\n", " | \n", " | Return a copy of B with all ASCII characters converted to lowercase.\n", " | \n", " | lstrip(self, bytes=None, /)\n", " | Strip leading bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip leading ASCII whitespace.\n", " | \n", " | partition(self, sep, /)\n", " | Partition the bytes into three parts using the given separator.\n", " | \n", " | This will search for the separator sep in the bytes. If the separator is found,\n", " | returns a 3-tuple containing the part before the separator, the separator\n", " | itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing the original bytes\n", " | object and two empty bytes objects.\n", " | \n", " | replace(self, old, new, count=-1, /)\n", " | Return a copy with all occurrences of substring old replaced by new.\n", " | \n", " | count\n", " | Maximum number of occurrences to replace.\n", " | -1 (the default value) means replace all occurrences.\n", " | \n", " | If the optional argument count is given, only the first count occurrences are\n", " | replaced.\n", " | \n", " | rfind(...)\n", " | B.rfind(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | rindex(...)\n", " | B.rindex(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raise ValueError when the subsection is not found.\n", " | \n", " | rjust(self, width, fillchar=b' ', /)\n", " | Return a right-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | rpartition(self, sep, /)\n", " | Partition the bytes into three parts using the given separator.\n", " | \n", " | This will search for the separator sep in the bytes, starting at the end. If\n", " | the separator is found, returns a 3-tuple containing the part before the\n", " | separator, the separator itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing two empty bytes\n", " | objects and the original bytes object.\n", " | \n", " | rsplit(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the sections in the bytes, using sep as the delimiter.\n", " | \n", " | sep\n", " | The delimiter according which to split the bytes.\n", " | None (the default value) means split on ASCII whitespace characters\n", " | (space, tab, return, newline, formfeed, vertical tab).\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | Splitting is done starting at the end of the bytes and working to the front.\n", " | \n", " | rstrip(self, bytes=None, /)\n", " | Strip trailing bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip trailing ASCII whitespace.\n", " | \n", " | split(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the sections in the bytes, using sep as the delimiter.\n", " | \n", " | sep\n", " | The delimiter according which to split the bytes.\n", " | None (the default value) means split on ASCII whitespace characters\n", " | (space, tab, return, newline, formfeed, vertical tab).\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | splitlines(self, /, keepends=False)\n", " | Return a list of the lines in the bytes, breaking at line boundaries.\n", " | \n", " | Line breaks are not included in the resulting list unless keepends is given and\n", " | true.\n", " | \n", " | startswith(...)\n", " | B.startswith(prefix[, start[, end]]) -> bool\n", " | \n", " | Return True if B starts with the specified prefix, False otherwise.\n", " | With optional start, test B beginning at that position.\n", " | With optional end, stop comparing B at that position.\n", " | prefix can also be a tuple of bytes to try.\n", " | \n", " | strip(self, bytes=None, /)\n", " | Strip leading and trailing bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip leading and trailing ASCII whitespace.\n", " | \n", " | swapcase(...)\n", " | B.swapcase() -> copy of B\n", " | \n", " | Return a copy of B with uppercase ASCII characters converted\n", " | to lowercase ASCII and vice versa.\n", " | \n", " | title(...)\n", " | B.title() -> copy of B\n", " | \n", " | Return a titlecased version of B, i.e. ASCII words start with uppercase\n", " | characters, all remaining cased characters have lowercase.\n", " | \n", " | translate(self, table, /, delete=b'')\n", " | Return a copy with each character mapped by the given translation table.\n", " | \n", " | table\n", " | Translation table, which must be a bytes object of length 256.\n", " | \n", " | All characters occurring in the optional argument delete are removed.\n", " | The remaining characters are mapped through the given translation table.\n", " | \n", " | upper(...)\n", " | B.upper() -> copy of B\n", " | \n", " | Return a copy of B with all ASCII characters converted to uppercase.\n", " | \n", " | zfill(self, width, /)\n", " | Pad a numeric string with zeros on the left, to fill a field of the given width.\n", " | \n", " | The original string is never truncated.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Class methods inherited from builtins.bytes:\n", " | \n", " | fromhex(string, /) from builtins.type\n", " | Create a bytes object from a string of hexadecimal numbers.\n", " | \n", " | Spaces between two numbers are accepted.\n", " | Example: bytes.fromhex('B9 01EF') -> b'\\\\xb9\\\\x01\\\\xef'.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.bytes:\n", " | \n", " | maketrans(frm, to, /)\n", " | Return a translation table useable for the bytes or bytearray translate method.\n", " | \n", " | The returned table will be one where each byte in frm is mapped to the byte at\n", " | the same position in to.\n", " | \n", " | The bytes objects frm and to must be of the same length.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class bytes_(builtins.bytes, character)\n", " | bytes(iterable_of_ints) -> bytes\n", " | bytes(string, encoding[, errors]) -> bytes\n", " | bytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\n", " | bytes(int) -> bytes object of size given by the parameter initialized with null bytes\n", " | bytes() -> empty bytes object\n", " | \n", " | Construct an immutable array of bytes from:\n", " | - an iterable yielding integers in range(256)\n", " | - a text string encoded using the specified encoding\n", " | - any object implementing the buffer API.\n", " | - an integer\n", " | \n", " | Method resolution order:\n", " | bytes_\n", " | builtins.bytes\n", " | character\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self copy of B\n", " | \n", " | Return a copy of B with only its first character capitalized (ASCII)\n", " | and the rest lower-cased.\n", " | \n", " | center(self, width, fillchar=b' ', /)\n", " | Return a centered string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | count(...)\n", " | B.count(sub[, start[, end]]) -> int\n", " | \n", " | Return the number of non-overlapping occurrences of subsection sub in\n", " | bytes B[start:end]. Optional arguments start and end are interpreted\n", " | as in slice notation.\n", " | \n", " | decode(self, /, encoding='utf-8', errors='strict')\n", " | Decode the bytes using the codec registered for encoding.\n", " | \n", " | encoding\n", " | The encoding with which to decode the bytes.\n", " | errors\n", " | The error handling scheme to use for the handling of decoding errors.\n", " | The default is 'strict' meaning that decoding errors raise a\n", " | UnicodeDecodeError. Other possible values are 'ignore' and 'replace'\n", " | as well as any other name registered with codecs.register_error that\n", " | can handle UnicodeDecodeErrors.\n", " | \n", " | endswith(...)\n", " | B.endswith(suffix[, start[, end]]) -> bool\n", " | \n", " | Return True if B ends with the specified suffix, False otherwise.\n", " | With optional start, test B beginning at that position.\n", " | With optional end, stop comparing B at that position.\n", " | suffix can also be a tuple of bytes to try.\n", " | \n", " | expandtabs(self, /, tabsize=8)\n", " | Return a copy where all tab characters are expanded using spaces.\n", " | \n", " | If tabsize is not given, a tab size of 8 characters is assumed.\n", " | \n", " | find(...)\n", " | B.find(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | hex(...)\n", " | Create a str of hexadecimal numbers from a bytes object.\n", " | \n", " | sep\n", " | An optional single character or byte to separate hex bytes.\n", " | bytes_per_sep\n", " | How many bytes between separators. Positive values count from the\n", " | right, negative values count from the left.\n", " | \n", " | Example:\n", " | >>> value = b'\\xb9\\x01\\xef'\n", " | >>> value.hex()\n", " | 'b901ef'\n", " | >>> value.hex(':')\n", " | 'b9:01:ef'\n", " | >>> value.hex(':', 2)\n", " | 'b9:01ef'\n", " | >>> value.hex(':', -2)\n", " | 'b901:ef'\n", " | \n", " | index(...)\n", " | B.index(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the subsection is not found.\n", " | \n", " | isalnum(...)\n", " | B.isalnum() -> bool\n", " | \n", " | Return True if all characters in B are alphanumeric\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | isalpha(...)\n", " | B.isalpha() -> bool\n", " | \n", " | Return True if all characters in B are alphabetic\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | isascii(...)\n", " | B.isascii() -> bool\n", " | \n", " | Return True if B is empty or all characters in B are ASCII,\n", " | False otherwise.\n", " | \n", " | isdigit(...)\n", " | B.isdigit() -> bool\n", " | \n", " | Return True if all characters in B are digits\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | islower(...)\n", " | B.islower() -> bool\n", " | \n", " | Return True if all cased characters in B are lowercase and there is\n", " | at least one cased character in B, False otherwise.\n", " | \n", " | isspace(...)\n", " | B.isspace() -> bool\n", " | \n", " | Return True if all characters in B are whitespace\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | istitle(...)\n", " | B.istitle() -> bool\n", " | \n", " | Return True if B is a titlecased string and there is at least one\n", " | character in B, i.e. uppercase characters may only follow uncased\n", " | characters and lowercase characters only cased ones. Return False\n", " | otherwise.\n", " | \n", " | isupper(...)\n", " | B.isupper() -> bool\n", " | \n", " | Return True if all cased characters in B are uppercase and there is\n", " | at least one cased character in B, False otherwise.\n", " | \n", " | join(self, iterable_of_bytes, /)\n", " | Concatenate any number of bytes objects.\n", " | \n", " | The bytes whose method is called is inserted in between each pair.\n", " | \n", " | The result is returned as a new bytes object.\n", " | \n", " | Example: b'.'.join([b'ab', b'pq', b'rs']) -> b'ab.pq.rs'.\n", " | \n", " | ljust(self, width, fillchar=b' ', /)\n", " | Return a left-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | lower(...)\n", " | B.lower() -> copy of B\n", " | \n", " | Return a copy of B with all ASCII characters converted to lowercase.\n", " | \n", " | lstrip(self, bytes=None, /)\n", " | Strip leading bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip leading ASCII whitespace.\n", " | \n", " | partition(self, sep, /)\n", " | Partition the bytes into three parts using the given separator.\n", " | \n", " | This will search for the separator sep in the bytes. If the separator is found,\n", " | returns a 3-tuple containing the part before the separator, the separator\n", " | itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing the original bytes\n", " | object and two empty bytes objects.\n", " | \n", " | replace(self, old, new, count=-1, /)\n", " | Return a copy with all occurrences of substring old replaced by new.\n", " | \n", " | count\n", " | Maximum number of occurrences to replace.\n", " | -1 (the default value) means replace all occurrences.\n", " | \n", " | If the optional argument count is given, only the first count occurrences are\n", " | replaced.\n", " | \n", " | rfind(...)\n", " | B.rfind(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | rindex(...)\n", " | B.rindex(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raise ValueError when the subsection is not found.\n", " | \n", " | rjust(self, width, fillchar=b' ', /)\n", " | Return a right-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | rpartition(self, sep, /)\n", " | Partition the bytes into three parts using the given separator.\n", " | \n", " | This will search for the separator sep in the bytes, starting at the end. If\n", " | the separator is found, returns a 3-tuple containing the part before the\n", " | separator, the separator itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing two empty bytes\n", " | objects and the original bytes object.\n", " | \n", " | rsplit(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the sections in the bytes, using sep as the delimiter.\n", " | \n", " | sep\n", " | The delimiter according which to split the bytes.\n", " | None (the default value) means split on ASCII whitespace characters\n", " | (space, tab, return, newline, formfeed, vertical tab).\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | Splitting is done starting at the end of the bytes and working to the front.\n", " | \n", " | rstrip(self, bytes=None, /)\n", " | Strip trailing bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip trailing ASCII whitespace.\n", " | \n", " | split(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the sections in the bytes, using sep as the delimiter.\n", " | \n", " | sep\n", " | The delimiter according which to split the bytes.\n", " | None (the default value) means split on ASCII whitespace characters\n", " | (space, tab, return, newline, formfeed, vertical tab).\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | splitlines(self, /, keepends=False)\n", " | Return a list of the lines in the bytes, breaking at line boundaries.\n", " | \n", " | Line breaks are not included in the resulting list unless keepends is given and\n", " | true.\n", " | \n", " | startswith(...)\n", " | B.startswith(prefix[, start[, end]]) -> bool\n", " | \n", " | Return True if B starts with the specified prefix, False otherwise.\n", " | With optional start, test B beginning at that position.\n", " | With optional end, stop comparing B at that position.\n", " | prefix can also be a tuple of bytes to try.\n", " | \n", " | strip(self, bytes=None, /)\n", " | Strip leading and trailing bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip leading and trailing ASCII whitespace.\n", " | \n", " | swapcase(...)\n", " | B.swapcase() -> copy of B\n", " | \n", " | Return a copy of B with uppercase ASCII characters converted\n", " | to lowercase ASCII and vice versa.\n", " | \n", " | title(...)\n", " | B.title() -> copy of B\n", " | \n", " | Return a titlecased version of B, i.e. ASCII words start with uppercase\n", " | characters, all remaining cased characters have lowercase.\n", " | \n", " | translate(self, table, /, delete=b'')\n", " | Return a copy with each character mapped by the given translation table.\n", " | \n", " | table\n", " | Translation table, which must be a bytes object of length 256.\n", " | \n", " | All characters occurring in the optional argument delete are removed.\n", " | The remaining characters are mapped through the given translation table.\n", " | \n", " | upper(...)\n", " | B.upper() -> copy of B\n", " | \n", " | Return a copy of B with all ASCII characters converted to uppercase.\n", " | \n", " | zfill(self, width, /)\n", " | Pad a numeric string with zeros on the left, to fill a field of the given width.\n", " | \n", " | The original string is never truncated.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Class methods inherited from builtins.bytes:\n", " | \n", " | fromhex(string, /) from builtins.type\n", " | Create a bytes object from a string of hexadecimal numbers.\n", " | \n", " | Spaces between two numbers are accepted.\n", " | Example: bytes.fromhex('B9 01EF') -> b'\\\\xb9\\\\x01\\\\xef'.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.bytes:\n", " | \n", " | maketrans(frm, to, /)\n", " | Return a translation table useable for the bytes or bytearray translate method.\n", " | \n", " | The returned table will be one where each byte in frm is mapped to the byte at\n", " | the same position in to.\n", " | \n", " | The bytes objects frm and to must be of the same length.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " cdouble = class complex128(complexfloating, builtins.complex)\n", " | cdouble(real=0, imag=0)\n", " | \n", " | Complex number type composed of two double-precision floating-point\n", " | numbers, compatible with Python `complex`.\n", " | Character code: ``'D'``.\n", " | Canonical name: ``np.cdouble``.\n", " | Alias: ``np.cfloat``.\n", " | Alias: ``np.complex_``.\n", " | Alias *on this platform*: ``np.complex128``: Complex number type composed of 2 64-bit-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex128\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.complex\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.complex:\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getnewargs__(...)\n", " \n", " cfloat = class complex128(complexfloating, builtins.complex)\n", " | cfloat(real=0, imag=0)\n", " | \n", " | Complex number type composed of two double-precision floating-point\n", " | numbers, compatible with Python `complex`.\n", " | Character code: ``'D'``.\n", " | Canonical name: ``np.cdouble``.\n", " | Alias: ``np.cfloat``.\n", " | Alias: ``np.complex_``.\n", " | Alias *on this platform*: ``np.complex128``: Complex number type composed of 2 64-bit-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex128\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.complex\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.complex:\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getnewargs__(...)\n", " \n", " class character(flexible)\n", " | Abstract base class of all character string scalar types.\n", " | \n", " | Method resolution order:\n", " | character\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " class chararray(ndarray)\n", " | chararray(shape, itemsize=1, unicode=False, buffer=None, offset=0, strides=None, order='C')\n", " | \n", " | chararray(shape, itemsize=1, unicode=False, buffer=None, offset=0,\n", " | strides=None, order=None)\n", " | \n", " | Provides a convenient view on arrays of string and unicode values.\n", " | \n", " | .. note::\n", " | The `chararray` class exists for backwards compatibility with\n", " | Numarray, it is not recommended for new development. Starting from numpy\n", " | 1.4, if one needs arrays of strings, it is recommended to use arrays of\n", " | `dtype` `object_`, `string_` or `unicode_`, and use the free functions\n", " | in the `numpy.char` module for fast vectorized string operations.\n", " | \n", " | Versus a regular NumPy array of type `str` or `unicode`, this\n", " | class adds the following functionality:\n", " | \n", " | 1) values automatically have whitespace removed from the end\n", " | when indexed\n", " | \n", " | 2) comparison operators automatically remove whitespace from the\n", " | end when comparing values\n", " | \n", " | 3) vectorized string operations are provided as methods\n", " | (e.g. `.endswith`) and infix operators (e.g. ``\"+\", \"*\", \"%\"``)\n", " | \n", " | chararrays should be created using `numpy.char.array` or\n", " | `numpy.char.asarray`, rather than this constructor directly.\n", " | \n", " | This constructor creates the array, using `buffer` (with `offset`\n", " | and `strides`) if it is not ``None``. If `buffer` is ``None``, then\n", " | constructs a new array with `strides` in \"C order\", unless both\n", " | ``len(shape) >= 2`` and ``order='F'``, in which case `strides`\n", " | is in \"Fortran order\".\n", " | \n", " | Methods\n", " | -------\n", " | astype\n", " | argsort\n", " | copy\n", " | count\n", " | decode\n", " | dump\n", " | dumps\n", " | encode\n", " | endswith\n", " | expandtabs\n", " | fill\n", " | find\n", " | flatten\n", " | getfield\n", " | index\n", " | isalnum\n", " | isalpha\n", " | isdecimal\n", " | isdigit\n", " | islower\n", " | isnumeric\n", " | isspace\n", " | istitle\n", " | isupper\n", " | item\n", " | join\n", " | ljust\n", " | lower\n", " | lstrip\n", " | nonzero\n", " | put\n", " | ravel\n", " | repeat\n", " | replace\n", " | reshape\n", " | resize\n", " | rfind\n", " | rindex\n", " | rjust\n", " | rsplit\n", " | rstrip\n", " | searchsorted\n", " | setfield\n", " | setflags\n", " | sort\n", " | split\n", " | splitlines\n", " | squeeze\n", " | startswith\n", " | strip\n", " | swapaxes\n", " | swapcase\n", " | take\n", " | title\n", " | tofile\n", " | tolist\n", " | tostring\n", " | translate\n", " | transpose\n", " | upper\n", " | view\n", " | zfill\n", " | \n", " | Parameters\n", " | ----------\n", " | shape : tuple\n", " | Shape of the array.\n", " | itemsize : int, optional\n", " | Length of each array element, in number of characters. Default is 1.\n", " | unicode : bool, optional\n", " | Are the array elements of type unicode (True) or string (False).\n", " | Default is False.\n", " | buffer : object exposing the buffer interface or str, optional\n", " | Memory address of the start of the array data. Default is None,\n", " | in which case a new array is created.\n", " | offset : int, optional\n", " | Fixed stride displacement from the beginning of an axis?\n", " | Default is 0. Needs to be >=0.\n", " | strides : array_like of ints, optional\n", " | Strides for the array (see `ndarray.strides` for full description).\n", " | Default is None.\n", " | order : {'C', 'F'}, optional\n", " | The order in which the array data is stored in memory: 'C' ->\n", " | \"row major\" order (the default), 'F' -> \"column major\"\n", " | (Fortran) order.\n", " | \n", " | Examples\n", " | --------\n", " | >>> charar = np.chararray((3, 3))\n", " | >>> charar[:] = 'a'\n", " | >>> charar\n", " | chararray([[b'a', b'a', b'a'],\n", " | [b'a', b'a', b'a'],\n", " | [b'a', b'a', b'a']], dtype='|S1')\n", " | \n", " | >>> charar = np.chararray(charar.shape, itemsize=5)\n", " | >>> charar[:] = 'abc'\n", " | >>> charar\n", " | chararray([[b'abc', b'abc', b'abc'],\n", " | [b'abc', b'abc', b'abc'],\n", " | [b'abc', b'abc', b'abc']], dtype='|S5')\n", " | \n", " | Method resolution order:\n", " | chararray\n", " | ndarray\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __add__(self, other)\n", " | Return (self + other), that is string concatenation,\n", " | element-wise for a pair of array_likes of str or unicode.\n", " | \n", " | See also\n", " | --------\n", " | add\n", " | \n", " | __array_finalize__(self, obj)\n", " | None.\n", " | \n", " | __eq__(self, other)\n", " | Return (self == other) element-wise.\n", " | \n", " | See also\n", " | --------\n", " | equal\n", " | \n", " | __ge__(self, other)\n", " | Return (self >= other) element-wise.\n", " | \n", " | See also\n", " | --------\n", " | greater_equal\n", " | \n", " | __getitem__(self, obj)\n", " | Return self[key].\n", " | \n", " | __gt__(self, other)\n", " | Return (self > other) element-wise.\n", " | \n", " | See also\n", " | --------\n", " | greater\n", " | \n", " | __le__(self, other)\n", " | Return (self <= other) element-wise.\n", " | \n", " | See also\n", " | --------\n", " | less_equal\n", " | \n", " | __lt__(self, other)\n", " | Return (self < other) element-wise.\n", " | \n", " | See also\n", " | --------\n", " | less\n", " | \n", " | __mod__(self, i)\n", " | Return (self % i), that is pre-Python 2.6 string formatting\n", " | (interpolation), element-wise for a pair of array_likes of `string_`\n", " | or `unicode_`.\n", " | \n", " | See also\n", " | --------\n", " | mod\n", " | \n", " | __mul__(self, i)\n", " | Return (self * i), that is string multiple concatenation,\n", " | element-wise.\n", " | \n", " | See also\n", " | --------\n", " | multiply\n", " | \n", " | __ne__(self, other)\n", " | Return (self != other) element-wise.\n", " | \n", " | See also\n", " | --------\n", " | not_equal\n", " | \n", " | __radd__(self, other)\n", " | Return (other + self), that is string concatenation,\n", " | element-wise for a pair of array_likes of `string_` or `unicode_`.\n", " | \n", " | See also\n", " | --------\n", " | add\n", " | \n", " | __rmod__(self, other)\n", " | Return value%self.\n", " | \n", " | __rmul__(self, i)\n", " | Return (self * i), that is string multiple concatenation,\n", " | element-wise.\n", " | \n", " | See also\n", " | --------\n", " | multiply\n", " | \n", " | argsort(self, axis=-1, kind=None, order=None)\n", " | a.argsort(axis=-1, kind=None, order=None)\n", " | \n", " | Returns the indices that would sort this array.\n", " | \n", " | Refer to `numpy.argsort` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argsort : equivalent function\n", " | \n", " | capitalize(self)\n", " | Return a copy of `self` with only the first character of each element\n", " | capitalized.\n", " | \n", " | See also\n", " | --------\n", " | char.capitalize\n", " | \n", " | center(self, width, fillchar=' ')\n", " | Return a copy of `self` with its elements centered in a\n", " | string of length `width`.\n", " | \n", " | See also\n", " | --------\n", " | center\n", " | \n", " | count(self, sub, start=0, end=None)\n", " | Returns an array with the number of non-overlapping occurrences of\n", " | substring `sub` in the range [`start`, `end`].\n", " | \n", " | See also\n", " | --------\n", " | char.count\n", " | \n", " | decode(self, encoding=None, errors=None)\n", " | Calls `str.decode` element-wise.\n", " | \n", " | See also\n", " | --------\n", " | char.decode\n", " | \n", " | encode(self, encoding=None, errors=None)\n", " | Calls `str.encode` element-wise.\n", " | \n", " | See also\n", " | --------\n", " | char.encode\n", " | \n", " | endswith(self, suffix, start=0, end=None)\n", " | Returns a boolean array which is `True` where the string element\n", " | in `self` ends with `suffix`, otherwise `False`.\n", " | \n", " | See also\n", " | --------\n", " | char.endswith\n", " | \n", " | expandtabs(self, tabsize=8)\n", " | Return a copy of each string element where all tab characters are\n", " | replaced by one or more spaces.\n", " | \n", " | See also\n", " | --------\n", " | char.expandtabs\n", " | \n", " | find(self, sub, start=0, end=None)\n", " | For each element, return the lowest index in the string where\n", " | substring `sub` is found.\n", " | \n", " | See also\n", " | --------\n", " | char.find\n", " | \n", " | index(self, sub, start=0, end=None)\n", " | Like `find`, but raises `ValueError` when the substring is not found.\n", " | \n", " | See also\n", " | --------\n", " | char.index\n", " | \n", " | isalnum(self)\n", " | Returns true for each element if all characters in the string\n", " | are alphanumeric and there is at least one character, false\n", " | otherwise.\n", " | \n", " | See also\n", " | --------\n", " | char.isalnum\n", " | \n", " | isalpha(self)\n", " | Returns true for each element if all characters in the string\n", " | are alphabetic and there is at least one character, false\n", " | otherwise.\n", " | \n", " | See also\n", " | --------\n", " | char.isalpha\n", " | \n", " | isdecimal(self)\n", " | For each element in `self`, return True if there are only\n", " | decimal characters in the element.\n", " | \n", " | See also\n", " | --------\n", " | char.isdecimal\n", " | \n", " | isdigit(self)\n", " | Returns true for each element if all characters in the string are\n", " | digits and there is at least one character, false otherwise.\n", " | \n", " | See also\n", " | --------\n", " | char.isdigit\n", " | \n", " | islower(self)\n", " | Returns true for each element if all cased characters in the\n", " | string are lowercase and there is at least one cased character,\n", " | false otherwise.\n", " | \n", " | See also\n", " | --------\n", " | char.islower\n", " | \n", " | isnumeric(self)\n", " | For each element in `self`, return True if there are only\n", " | numeric characters in the element.\n", " | \n", " | See also\n", " | --------\n", " | char.isnumeric\n", " | \n", " | isspace(self)\n", " | Returns true for each element if there are only whitespace\n", " | characters in the string and there is at least one character,\n", " | false otherwise.\n", " | \n", " | See also\n", " | --------\n", " | char.isspace\n", " | \n", " | istitle(self)\n", " | Returns true for each element if the element is a titlecased\n", " | string and there is at least one character, false otherwise.\n", " | \n", " | See also\n", " | --------\n", " | char.istitle\n", " | \n", " | isupper(self)\n", " | Returns true for each element if all cased characters in the\n", " | string are uppercase and there is at least one character, false\n", " | otherwise.\n", " | \n", " | See also\n", " | --------\n", " | char.isupper\n", " | \n", " | join(self, seq)\n", " | Return a string which is the concatenation of the strings in the\n", " | sequence `seq`.\n", " | \n", " | See also\n", " | --------\n", " | char.join\n", " | \n", " | ljust(self, width, fillchar=' ')\n", " | Return an array with the elements of `self` left-justified in a\n", " | string of length `width`.\n", " | \n", " | See also\n", " | --------\n", " | char.ljust\n", " | \n", " | lower(self)\n", " | Return an array with the elements of `self` converted to\n", " | lowercase.\n", " | \n", " | See also\n", " | --------\n", " | char.lower\n", " | \n", " | lstrip(self, chars=None)\n", " | For each element in `self`, return a copy with the leading characters\n", " | removed.\n", " | \n", " | See also\n", " | --------\n", " | char.lstrip\n", " | \n", " | partition(self, sep)\n", " | Partition each element in `self` around `sep`.\n", " | \n", " | See also\n", " | --------\n", " | partition\n", " | \n", " | replace(self, old, new, count=None)\n", " | For each element in `self`, return a copy of the string with all\n", " | occurrences of substring `old` replaced by `new`.\n", " | \n", " | See also\n", " | --------\n", " | char.replace\n", " | \n", " | rfind(self, sub, start=0, end=None)\n", " | For each element in `self`, return the highest index in the string\n", " | where substring `sub` is found, such that `sub` is contained\n", " | within [`start`, `end`].\n", " | \n", " | See also\n", " | --------\n", " | char.rfind\n", " | \n", " | rindex(self, sub, start=0, end=None)\n", " | Like `rfind`, but raises `ValueError` when the substring `sub` is\n", " | not found.\n", " | \n", " | See also\n", " | --------\n", " | char.rindex\n", " | \n", " | rjust(self, width, fillchar=' ')\n", " | Return an array with the elements of `self`\n", " | right-justified in a string of length `width`.\n", " | \n", " | See also\n", " | --------\n", " | char.rjust\n", " | \n", " | rpartition(self, sep)\n", " | Partition each element in `self` around `sep`.\n", " | \n", " | See also\n", " | --------\n", " | rpartition\n", " | \n", " | rsplit(self, sep=None, maxsplit=None)\n", " | For each element in `self`, return a list of the words in\n", " | the string, using `sep` as the delimiter string.\n", " | \n", " | See also\n", " | --------\n", " | char.rsplit\n", " | \n", " | rstrip(self, chars=None)\n", " | For each element in `self`, return a copy with the trailing\n", " | characters removed.\n", " | \n", " | See also\n", " | --------\n", " | char.rstrip\n", " | \n", " | split(self, sep=None, maxsplit=None)\n", " | For each element in `self`, return a list of the words in the\n", " | string, using `sep` as the delimiter string.\n", " | \n", " | See also\n", " | --------\n", " | char.split\n", " | \n", " | splitlines(self, keepends=None)\n", " | For each element in `self`, return a list of the lines in the\n", " | element, breaking at line boundaries.\n", " | \n", " | See also\n", " | --------\n", " | char.splitlines\n", " | \n", " | startswith(self, prefix, start=0, end=None)\n", " | Returns a boolean array which is `True` where the string element\n", " | in `self` starts with `prefix`, otherwise `False`.\n", " | \n", " | See also\n", " | --------\n", " | char.startswith\n", " | \n", " | strip(self, chars=None)\n", " | For each element in `self`, return a copy with the leading and\n", " | trailing characters removed.\n", " | \n", " | See also\n", " | --------\n", " | char.strip\n", " | \n", " | swapcase(self)\n", " | For each element in `self`, return a copy of the string with\n", " | uppercase characters converted to lowercase and vice versa.\n", " | \n", " | See also\n", " | --------\n", " | char.swapcase\n", " | \n", " | title(self)\n", " | For each element in `self`, return a titlecased version of the\n", " | string: words start with uppercase characters, all remaining cased\n", " | characters are lowercase.\n", " | \n", " | See also\n", " | --------\n", " | char.title\n", " | \n", " | translate(self, table, deletechars=None)\n", " | For each element in `self`, return a copy of the string where\n", " | all characters occurring in the optional argument\n", " | `deletechars` are removed, and the remaining characters have\n", " | been mapped through the given translation table.\n", " | \n", " | See also\n", " | --------\n", " | char.translate\n", " | \n", " | upper(self)\n", " | Return an array with the elements of `self` converted to\n", " | uppercase.\n", " | \n", " | See also\n", " | --------\n", " | char.upper\n", " | \n", " | zfill(self, width)\n", " | Return the numeric string left-filled with zeros in a string of\n", " | length `width`.\n", " | \n", " | See also\n", " | --------\n", " | char.zfill\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(subtype, shape, itemsize=1, unicode=False, buffer=None, offset=0, strides=None, order='C')\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes defined here:\n", " | \n", " | __hash__ = None\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from ndarray:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | a.__array__([dtype], /) -> reference if type unchanged, copy otherwise.\n", " | \n", " | Returns either a new reference to self if dtype is not given or a new array\n", " | of provided data type if dtype is different from the current dtype of the\n", " | array.\n", " | \n", " | __array_function__(...)\n", " | \n", " | __array_prepare__(...)\n", " | a.__array_prepare__(obj) -> Object of same type as ndarray object obj.\n", " | \n", " | __array_ufunc__(...)\n", " | \n", " | __array_wrap__(...)\n", " | a.__array_wrap__(obj) -> Object of same type as ndarray object a.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __contains__(self, key, /)\n", " | Return key in self.\n", " | \n", " | __copy__(...)\n", " | a.__copy__()\n", " | \n", " | Used if :func:`copy.copy` is called on an array. Returns a copy of the array.\n", " | \n", " | Equivalent to ``a.copy(order='K')``.\n", " | \n", " | __deepcopy__(...)\n", " | a.__deepcopy__(memo, /) -> Deep copy of array.\n", " | \n", " | Used if :func:`copy.deepcopy` is called on an array.\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | Default object formatter.\n", " | \n", " | __iadd__(self, value, /)\n", " | Return self+=value.\n", " | \n", " | __iand__(self, value, /)\n", " | Return self&=value.\n", " | \n", " | __ifloordiv__(self, value, /)\n", " | Return self//=value.\n", " | \n", " | __ilshift__(self, value, /)\n", " | Return self<<=value.\n", " | \n", " | __imatmul__(self, value, /)\n", " | Return self@=value.\n", " | \n", " | __imod__(self, value, /)\n", " | Return self%=value.\n", " | \n", " | __imul__(self, value, /)\n", " | Return self*=value.\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __ior__(self, value, /)\n", " | Return self|=value.\n", " | \n", " | __ipow__(self, value, /)\n", " | Return self**=value.\n", " | \n", " | __irshift__(self, value, /)\n", " | Return self>>=value.\n", " | \n", " | __isub__(self, value, /)\n", " | Return self-=value.\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __itruediv__(self, value, /)\n", " | Return self/=value.\n", " | \n", " | __ixor__(self, value, /)\n", " | Return self^=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setitem__(self, key, value, /)\n", " | Set self[key] to value.\n", " | \n", " | __setstate__(...)\n", " | a.__setstate__(state, /)\n", " | \n", " | For unpickling.\n", " | \n", " | The `state` argument must be a sequence that contains the following\n", " | elements:\n", " | \n", " | Parameters\n", " | ----------\n", " | version : int\n", " | optional pickle version. If omitted defaults to 0.\n", " | shape : tuple\n", " | dtype : data-type\n", " | isFortran : bool\n", " | rawdata : string or list\n", " | a binary string with the data (or a list if 'a' is an object array)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | a.all(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if all elements evaluate to True.\n", " | \n", " | Refer to `numpy.all` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.all : equivalent function\n", " | \n", " | any(...)\n", " | a.any(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if any of the elements of `a` evaluate to True.\n", " | \n", " | Refer to `numpy.any` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.any : equivalent function\n", " | \n", " | argmax(...)\n", " | a.argmax(axis=None, out=None)\n", " | \n", " | Return indices of the maximum values along the given axis.\n", " | \n", " | Refer to `numpy.argmax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmax : equivalent function\n", " | \n", " | argmin(...)\n", " | a.argmin(axis=None, out=None)\n", " | \n", " | Return indices of the minimum values along the given axis of `a`.\n", " | \n", " | Refer to `numpy.argmin` for detailed documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmin : equivalent function\n", " | \n", " | argpartition(...)\n", " | a.argpartition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Returns the indices that would partition this array.\n", " | \n", " | Refer to `numpy.argpartition` for full documentation.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argpartition : equivalent function\n", " | \n", " | astype(...)\n", " | a.astype(dtype, order='K', casting='unsafe', subok=True, copy=True)\n", " | \n", " | Copy of the array, cast to a specified type.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | Typecode or data-type to which the array is cast.\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout order of the result.\n", " | 'C' means C order, 'F' means Fortran order, 'A'\n", " | means 'F' order if all the arrays are Fortran contiguous,\n", " | 'C' order otherwise, and 'K' means as close to the\n", " | order the array elements appear in memory as possible.\n", " | Default is 'K'.\n", " | casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n", " | Controls what kind of data casting may occur. Defaults to 'unsafe'\n", " | for backwards compatibility.\n", " | \n", " | * 'no' means the data types should not be cast at all.\n", " | * 'equiv' means only byte-order changes are allowed.\n", " | * 'safe' means only casts which can preserve values are allowed.\n", " | * 'same_kind' means only safe casts or casts within a kind,\n", " | like float64 to float32, are allowed.\n", " | * 'unsafe' means any data conversions may be done.\n", " | subok : bool, optional\n", " | If True, then sub-classes will be passed-through (default), otherwise\n", " | the returned array will be forced to be a base-class array.\n", " | copy : bool, optional\n", " | By default, astype always returns a newly allocated array. If this\n", " | is set to false, and the `dtype`, `order`, and `subok`\n", " | requirements are satisfied, the input array is returned instead\n", " | of a copy.\n", " | \n", " | Returns\n", " | -------\n", " | arr_t : ndarray\n", " | Unless `copy` is False and the other conditions for returning the input\n", " | array are satisfied (see description for `copy` input parameter), `arr_t`\n", " | is a new array of the same shape as the input array, with dtype, order\n", " | given by `dtype`, `order`.\n", " | \n", " | Notes\n", " | -----\n", " | .. versionchanged:: 1.17.0\n", " | Casting between a simple data type and a structured one is possible only\n", " | for \"unsafe\" casting. Casting to multiple fields is allowed, but\n", " | casting from multiple fields is not.\n", " | \n", " | .. versionchanged:: 1.9.0\n", " | Casting from numeric to string types in 'safe' casting mode requires\n", " | that the string dtype length is long enough to store the max\n", " | integer/float value converted.\n", " | \n", " | Raises\n", " | ------\n", " | ComplexWarning\n", " | When casting from complex to float or int. To avoid this,\n", " | one should use ``a.real.astype(t)``.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 2.5])\n", " | >>> x\n", " | array([1. , 2. , 2.5])\n", " | \n", " | >>> x.astype(int)\n", " | array([1, 2, 2])\n", " | \n", " | byteswap(...)\n", " | a.byteswap(inplace=False)\n", " | \n", " | Swap the bytes of the array elements\n", " | \n", " | Toggle between low-endian and big-endian data representation by\n", " | returning a byteswapped array, optionally swapped in-place.\n", " | Arrays of byte-strings are not swapped. The real and imaginary\n", " | parts of a complex number are swapped individually.\n", " | \n", " | Parameters\n", " | ----------\n", " | inplace : bool, optional\n", " | If ``True``, swap bytes in-place, default is ``False``.\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | The byteswapped array. If `inplace` is ``True``, this is\n", " | a view to self.\n", " | \n", " | Examples\n", " | --------\n", " | >>> A = np.array([1, 256, 8755], dtype=np.int16)\n", " | >>> list(map(hex, A))\n", " | ['0x1', '0x100', '0x2233']\n", " | >>> A.byteswap(inplace=True)\n", " | array([ 256, 1, 13090], dtype=int16)\n", " | >>> list(map(hex, A))\n", " | ['0x100', '0x1', '0x3322']\n", " | \n", " | Arrays of byte-strings are not swapped\n", " | \n", " | >>> A = np.array([b'ceg', b'fac'])\n", " | >>> A.byteswap()\n", " | array([b'ceg', b'fac'], dtype='|S3')\n", " | \n", " | ``A.newbyteorder().byteswap()`` produces an array with the same values\n", " | but different representation in memory\n", " | \n", " | >>> A = np.array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,\n", " | 0, 0], dtype=uint8)\n", " | >>> A.newbyteorder().byteswap(inplace=True)\n", " | array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0,\n", " | 0, 3], dtype=uint8)\n", " | \n", " | choose(...)\n", " | a.choose(choices, out=None, mode='raise')\n", " | \n", " | Use an index array to construct a new array from a set of choices.\n", " | \n", " | Refer to `numpy.choose` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.choose : equivalent function\n", " | \n", " | clip(...)\n", " | a.clip(min=None, max=None, out=None, **kwargs)\n", " | \n", " | Return an array whose values are limited to ``[min, max]``.\n", " | One of max or min must be given.\n", " | \n", " | Refer to `numpy.clip` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.clip : equivalent function\n", " | \n", " | compress(...)\n", " | a.compress(condition, axis=None, out=None)\n", " | \n", " | Return selected slices of this array along given axis.\n", " | \n", " | Refer to `numpy.compress` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.compress : equivalent function\n", " | \n", " | conj(...)\n", " | a.conj()\n", " | \n", " | Complex-conjugate all elements.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | conjugate(...)\n", " | a.conjugate()\n", " | \n", " | Return the complex conjugate, element-wise.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | copy(...)\n", " | a.copy(order='C')\n", " | \n", " | Return a copy of the array.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout of the copy. 'C' means C-order,\n", " | 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,\n", " | 'C' otherwise. 'K' means match the layout of `a` as closely\n", " | as possible. (Note that this function and :func:`numpy.copy` are very\n", " | similar, but have different default values for their order=\n", " | arguments.)\n", " | \n", " | See also\n", " | --------\n", " | numpy.copy\n", " | numpy.copyto\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([[1,2,3],[4,5,6]], order='F')\n", " | \n", " | >>> y = x.copy()\n", " | \n", " | >>> x.fill(0)\n", " | \n", " | >>> x\n", " | array([[0, 0, 0],\n", " | [0, 0, 0]])\n", " | \n", " | >>> y\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | \n", " | >>> y.flags['C_CONTIGUOUS']\n", " | True\n", " | \n", " | cumprod(...)\n", " | a.cumprod(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative product of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumprod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumprod : equivalent function\n", " | \n", " | cumsum(...)\n", " | a.cumsum(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative sum of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumsum` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumsum : equivalent function\n", " | \n", " | diagonal(...)\n", " | a.diagonal(offset=0, axis1=0, axis2=1)\n", " | \n", " | Return specified diagonals. In NumPy 1.9 the returned array is a\n", " | read-only view instead of a copy as in previous NumPy versions. In\n", " | a future version the read-only restriction will be removed.\n", " | \n", " | Refer to :func:`numpy.diagonal` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.diagonal : equivalent function\n", " | \n", " | dot(...)\n", " | a.dot(b, out=None)\n", " | \n", " | Dot product of two arrays.\n", " | \n", " | Refer to `numpy.dot` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dot : equivalent function\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.eye(2)\n", " | >>> b = np.ones((2, 2)) * 2\n", " | >>> a.dot(b)\n", " | array([[2., 2.],\n", " | [2., 2.]])\n", " | \n", " | This array method can be conveniently chained:\n", " | \n", " | >>> a.dot(b).dot(b)\n", " | array([[8., 8.],\n", " | [8., 8.]])\n", " | \n", " | dump(...)\n", " | a.dump(file)\n", " | \n", " | Dump a pickle of the array to the specified file.\n", " | The array can be read back with pickle.load or numpy.load.\n", " | \n", " | Parameters\n", " | ----------\n", " | file : str or Path\n", " | A string naming the dump file.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | dumps(...)\n", " | a.dumps()\n", " | \n", " | Returns the pickle of the array as a string.\n", " | pickle.loads or numpy.loads will convert the string back to an array.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | fill(...)\n", " | a.fill(value)\n", " | \n", " | Fill the array with a scalar value.\n", " | \n", " | Parameters\n", " | ----------\n", " | value : scalar\n", " | All elements of `a` will be assigned this value.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([1, 2])\n", " | >>> a.fill(0)\n", " | >>> a\n", " | array([0, 0])\n", " | >>> a = np.empty(2)\n", " | >>> a.fill(1)\n", " | >>> a\n", " | array([1., 1.])\n", " | \n", " | flatten(...)\n", " | a.flatten(order='C')\n", " | \n", " | Return a copy of the array collapsed into one dimension.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | 'C' means to flatten in row-major (C-style) order.\n", " | 'F' means to flatten in column-major (Fortran-\n", " | style) order. 'A' means to flatten in column-major\n", " | order if `a` is Fortran *contiguous* in memory,\n", " | row-major order otherwise. 'K' means to flatten\n", " | `a` in the order the elements occur in memory.\n", " | The default is 'C'.\n", " | \n", " | Returns\n", " | -------\n", " | y : ndarray\n", " | A copy of the input array, flattened to one dimension.\n", " | \n", " | See Also\n", " | --------\n", " | ravel : Return a flattened array.\n", " | flat : A 1-D flat iterator over the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,2], [3,4]])\n", " | >>> a.flatten()\n", " | array([1, 2, 3, 4])\n", " | >>> a.flatten('F')\n", " | array([1, 3, 2, 4])\n", " | \n", " | getfield(...)\n", " | a.getfield(dtype, offset=0)\n", " | \n", " | Returns a field of the given array as a certain type.\n", " | \n", " | A field is a view of the array data with a given data-type. The values in\n", " | the view are determined by the given type and the offset into the current\n", " | array in bytes. The offset needs to be such that the view dtype fits in the\n", " | array dtype; for example an array of dtype complex128 has 16-byte elements.\n", " | If taking a view with a 32-bit integer (4 bytes), the offset needs to be\n", " | between 0 and 12 bytes.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | The data type of the view. The dtype size of the view can not be larger\n", " | than that of the array itself.\n", " | offset : int\n", " | Number of bytes to skip before beginning the element view.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.diag([1.+1.j]*2)\n", " | >>> x[1, 1] = 2 + 4.j\n", " | >>> x\n", " | array([[1.+1.j, 0.+0.j],\n", " | [0.+0.j, 2.+4.j]])\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0.],\n", " | [0., 2.]])\n", " | \n", " | By choosing an offset of 8 bytes we can select the complex part of the\n", " | array for our view:\n", " | \n", " | >>> x.getfield(np.float64, offset=8)\n", " | array([[1., 0.],\n", " | [0., 4.]])\n", " | \n", " | item(...)\n", " | a.item(*args)\n", " | \n", " | Copy an element of an array to a standard Python scalar and return it.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments (variable number and type)\n", " | \n", " | * none: in this case, the method only works for arrays\n", " | with one element (`a.size == 1`), which element is\n", " | copied into a standard Python scalar object and returned.\n", " | \n", " | * int_type: this argument is interpreted as a flat index into\n", " | the array, specifying which element to copy and return.\n", " | \n", " | * tuple of int_types: functions as does a single int_type argument,\n", " | except that the argument is interpreted as an nd-index into the\n", " | array.\n", " | \n", " | Returns\n", " | -------\n", " | z : Standard Python scalar object\n", " | A copy of the specified element of the array as a suitable\n", " | Python scalar\n", " | \n", " | Notes\n", " | -----\n", " | When the data type of `a` is longdouble or clongdouble, item() returns\n", " | a scalar array object because there is no available Python scalar that\n", " | would not lose information. Void arrays return a buffer object for item(),\n", " | unless fields are defined, in which case a tuple is returned.\n", " | \n", " | `item` is very similar to a[args], except, instead of an array scalar,\n", " | a standard Python scalar is returned. This can be useful for speeding up\n", " | access to elements of the array and doing arithmetic on elements of the\n", " | array using Python's optimized math.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.item(3)\n", " | 1\n", " | >>> x.item(7)\n", " | 0\n", " | >>> x.item((0, 1))\n", " | 2\n", " | >>> x.item((2, 2))\n", " | 1\n", " | \n", " | itemset(...)\n", " | a.itemset(*args)\n", " | \n", " | Insert scalar into an array (scalar is cast to array's dtype, if possible)\n", " | \n", " | There must be at least 1 argument, and define the last argument\n", " | as *item*. Then, ``a.itemset(*args)`` is equivalent to but faster\n", " | than ``a[args] = item``. The item should be a scalar value and `args`\n", " | must select a single item in the array `a`.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments\n", " | If one argument: a scalar, only used in case `a` is of size 1.\n", " | If two arguments: the last argument is the value to be set\n", " | and must be a scalar, the first argument specifies a single array\n", " | element location. It is either an int or a tuple.\n", " | \n", " | Notes\n", " | -----\n", " | Compared to indexing syntax, `itemset` provides some speed increase\n", " | for placing a scalar into a particular location in an `ndarray`,\n", " | if you must do this. However, generally this is discouraged:\n", " | among other problems, it complicates the appearance of the code.\n", " | Also, when using `itemset` (and `item`) inside a loop, be sure\n", " | to assign the methods to a local variable to avoid the attribute\n", " | look-up at each loop iteration.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.itemset(4, 0)\n", " | >>> x.itemset((2, 2), 9)\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 0, 6],\n", " | [1, 0, 9]])\n", " | \n", " | max(...)\n", " | a.max(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the maximum along a given axis.\n", " | \n", " | Refer to `numpy.amax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amax : equivalent function\n", " | \n", " | mean(...)\n", " | a.mean(axis=None, dtype=None, out=None, keepdims=False)\n", " | \n", " | Returns the average of the array elements along given axis.\n", " | \n", " | Refer to `numpy.mean` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.mean : equivalent function\n", " | \n", " | min(...)\n", " | a.min(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the minimum along a given axis.\n", " | \n", " | Refer to `numpy.amin` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amin : equivalent function\n", " | \n", " | newbyteorder(...)\n", " | arr.newbyteorder(new_order='S')\n", " | \n", " | Return the array with the same data viewed with a different byte order.\n", " | \n", " | Equivalent to::\n", " | \n", " | arr.view(arr.dtype.newbytorder(new_order))\n", " | \n", " | Changes are also made in all fields and sub-arrays of the array data\n", " | type.\n", " | \n", " | \n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : string, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | below. `new_order` codes can be any of:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_arr : array\n", " | New array object with the dtype reflecting given change to the\n", " | byte order.\n", " | \n", " | nonzero(...)\n", " | a.nonzero()\n", " | \n", " | Return the indices of the elements that are non-zero.\n", " | \n", " | Refer to `numpy.nonzero` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.nonzero : equivalent function\n", " | \n", " | prod(...)\n", " | a.prod(axis=None, dtype=None, out=None, keepdims=False, initial=1, where=True)\n", " | \n", " | Return the product of the array elements over the given axis\n", " | \n", " | Refer to `numpy.prod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.prod : equivalent function\n", " | \n", " | ptp(...)\n", " | a.ptp(axis=None, out=None, keepdims=False)\n", " | \n", " | Peak to peak (maximum - minimum) value along a given axis.\n", " | \n", " | Refer to `numpy.ptp` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ptp : equivalent function\n", " | \n", " | put(...)\n", " | a.put(indices, values, mode='raise')\n", " | \n", " | Set ``a.flat[n] = values[n]`` for all `n` in indices.\n", " | \n", " | Refer to `numpy.put` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.put : equivalent function\n", " | \n", " | ravel(...)\n", " | a.ravel([order])\n", " | \n", " | Return a flattened array.\n", " | \n", " | Refer to `numpy.ravel` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ravel : equivalent function\n", " | \n", " | ndarray.flat : a flat iterator on the array.\n", " | \n", " | repeat(...)\n", " | a.repeat(repeats, axis=None)\n", " | \n", " | Repeat elements of an array.\n", " | \n", " | Refer to `numpy.repeat` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.repeat : equivalent function\n", " | \n", " | reshape(...)\n", " | a.reshape(shape, order='C')\n", " | \n", " | Returns an array containing the same data with a new shape.\n", " | \n", " | Refer to `numpy.reshape` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : equivalent function\n", " | \n", " | Notes\n", " | -----\n", " | Unlike the free function `numpy.reshape`, this method on `ndarray` allows\n", " | the elements of the shape parameter to be passed in as separate arguments.\n", " | For example, ``a.reshape(10, 11)`` is equivalent to\n", " | ``a.reshape((10, 11))``.\n", " | \n", " | resize(...)\n", " | a.resize(new_shape, refcheck=True)\n", " | \n", " | Change shape and size of array in-place.\n", " | \n", " | Parameters\n", " | ----------\n", " | new_shape : tuple of ints, or `n` ints\n", " | Shape of resized array.\n", " | refcheck : bool, optional\n", " | If False, reference count will not be checked. Default is True.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | Raises\n", " | ------\n", " | ValueError\n", " | If `a` does not own its own data or references or views to it exist,\n", " | and the data memory must be changed.\n", " | PyPy only: will always raise if the data memory must be changed, since\n", " | there is no reliable way to determine if references or views to it\n", " | exist.\n", " | \n", " | SystemError\n", " | If the `order` keyword argument is specified. This behaviour is a\n", " | bug in NumPy.\n", " | \n", " | See Also\n", " | --------\n", " | resize : Return a new array with the specified shape.\n", " | \n", " | Notes\n", " | -----\n", " | This reallocates space for the data area if necessary.\n", " | \n", " | Only contiguous arrays (data elements consecutive in memory) can be\n", " | resized.\n", " | \n", " | The purpose of the reference count check is to make sure you\n", " | do not use this array as a buffer for another Python object and then\n", " | reallocate the memory. However, reference counts can increase in\n", " | other ways so if you are sure that you have not shared the memory\n", " | for this array with another Python object, then you may safely set\n", " | `refcheck` to False.\n", " | \n", " | Examples\n", " | --------\n", " | Shrinking an array: array is flattened (in the order that the data are\n", " | stored in memory), resized, and reshaped:\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='C')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [1]])\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='F')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [2]])\n", " | \n", " | Enlarging an array: as above, but missing entries are filled with zeros:\n", " | \n", " | >>> b = np.array([[0, 1], [2, 3]])\n", " | >>> b.resize(2, 3) # new_shape parameter doesn't have to be a tuple\n", " | >>> b\n", " | array([[0, 1, 2],\n", " | [3, 0, 0]])\n", " | \n", " | Referencing an array prevents resizing...\n", " | \n", " | >>> c = a\n", " | >>> a.resize((1, 1))\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: cannot resize an array that references or is referenced ...\n", " | \n", " | Unless `refcheck` is False:\n", " | \n", " | >>> a.resize((1, 1), refcheck=False)\n", " | >>> a\n", " | array([[0]])\n", " | >>> c\n", " | array([[0]])\n", " | \n", " | round(...)\n", " | a.round(decimals=0, out=None)\n", " | \n", " | Return `a` with each element rounded to the given number of decimals.\n", " | \n", " | Refer to `numpy.around` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.around : equivalent function\n", " | \n", " | searchsorted(...)\n", " | a.searchsorted(v, side='left', sorter=None)\n", " | \n", " | Find indices where elements of v should be inserted in a to maintain order.\n", " | \n", " | For full documentation, see `numpy.searchsorted`\n", " | \n", " | See Also\n", " | --------\n", " | numpy.searchsorted : equivalent function\n", " | \n", " | setfield(...)\n", " | a.setfield(val, dtype, offset=0)\n", " | \n", " | Put a value into a specified place in a field defined by a data-type.\n", " | \n", " | Place `val` into `a`'s field defined by `dtype` and beginning `offset`\n", " | bytes into the field.\n", " | \n", " | Parameters\n", " | ----------\n", " | val : object\n", " | Value to be placed in field.\n", " | dtype : dtype object\n", " | Data-type of the field in which to place `val`.\n", " | offset : int, optional\n", " | The number of bytes into the field at which to place `val`.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | See Also\n", " | --------\n", " | getfield\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.eye(3)\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | >>> x.setfield(3, np.int32)\n", " | >>> x.getfield(np.int32)\n", " | array([[3, 3, 3],\n", " | [3, 3, 3],\n", " | [3, 3, 3]], dtype=int32)\n", " | >>> x\n", " | array([[1.0e+000, 1.5e-323, 1.5e-323],\n", " | [1.5e-323, 1.0e+000, 1.5e-323],\n", " | [1.5e-323, 1.5e-323, 1.0e+000]])\n", " | >>> x.setfield(np.eye(3), np.int32)\n", " | >>> x\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | \n", " | setflags(...)\n", " | a.setflags(write=None, align=None, uic=None)\n", " | \n", " | Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY),\n", " | respectively.\n", " | \n", " | These Boolean-valued flags affect how numpy interprets the memory\n", " | area used by `a` (see Notes below). The ALIGNED flag can only\n", " | be set to True if the data is actually aligned according to the type.\n", " | The WRITEBACKIFCOPY and (deprecated) UPDATEIFCOPY flags can never be set\n", " | to True. The flag WRITEABLE can only be set to True if the array owns its\n", " | own memory, or the ultimate owner of the memory exposes a writeable buffer\n", " | interface, or is a string. (The exception for string is made so that\n", " | unpickling can be done without copying memory.)\n", " | \n", " | Parameters\n", " | ----------\n", " | write : bool, optional\n", " | Describes whether or not `a` can be written to.\n", " | align : bool, optional\n", " | Describes whether or not `a` is aligned properly for its type.\n", " | uic : bool, optional\n", " | Describes whether or not `a` is a copy of another \"base\" array.\n", " | \n", " | Notes\n", " | -----\n", " | Array flags provide information about how the memory area used\n", " | for the array is to be interpreted. There are 7 Boolean flags\n", " | in use, only four of which can be changed by the user:\n", " | WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED.\n", " | \n", " | WRITEABLE (W) the data area can be written to;\n", " | \n", " | ALIGNED (A) the data and strides are aligned appropriately for the hardware\n", " | (as determined by the compiler);\n", " | \n", " | UPDATEIFCOPY (U) (deprecated), replaced by WRITEBACKIFCOPY;\n", " | \n", " | WRITEBACKIFCOPY (X) this array is a copy of some other array (referenced\n", " | by .base). When the C-API function PyArray_ResolveWritebackIfCopy is\n", " | called, the base array will be updated with the contents of this array.\n", " | \n", " | All flags can be accessed using the single (upper case) letter as well\n", " | as the full name.\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.array([[3, 1, 7],\n", " | ... [2, 0, 0],\n", " | ... [8, 5, 9]])\n", " | >>> y\n", " | array([[3, 1, 7],\n", " | [2, 0, 0],\n", " | [8, 5, 9]])\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : True\n", " | ALIGNED : True\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(write=0, align=0)\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : False\n", " | ALIGNED : False\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(uic=1)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: cannot set WRITEBACKIFCOPY flag to True\n", " | \n", " | sort(...)\n", " | a.sort(axis=-1, kind=None, order=None)\n", " | \n", " | Sort an array in-place. Refer to `numpy.sort` for full documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional\n", " | Sorting algorithm. The default is 'quicksort'. Note that both 'stable'\n", " | and 'mergesort' use timsort under the covers and, in general, the\n", " | actual implementation will vary with datatype. The 'mergesort' option\n", " | is retained for backwards compatibility.\n", " | \n", " | .. versionchanged:: 1.15.0.\n", " | The 'stable' option was added.\n", " | \n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.sort : Return a sorted copy of an array.\n", " | numpy.argsort : Indirect sort.\n", " | numpy.lexsort : Indirect stable sort on multiple keys.\n", " | numpy.searchsorted : Find elements in sorted array.\n", " | numpy.partition: Partial sort.\n", " | \n", " | Notes\n", " | -----\n", " | See `numpy.sort` for notes on the different sorting algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,4], [3,1]])\n", " | >>> a.sort(axis=1)\n", " | >>> a\n", " | array([[1, 4],\n", " | [1, 3]])\n", " | >>> a.sort(axis=0)\n", " | >>> a\n", " | array([[1, 3],\n", " | [1, 4]])\n", " | \n", " | Use the `order` keyword to specify a field to use when sorting a\n", " | structured array:\n", " | \n", " | >>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])\n", " | >>> a.sort(order='y')\n", " | >>> a\n", " | array([(b'c', 1), (b'a', 2)],\n", " | dtype=[('x', 'S1'), ('y', '>> x = np.array([[0, 1], [2, 3]], dtype='>> x.tobytes()\n", " | b'\\x00\\x00\\x01\\x00\\x02\\x00\\x03\\x00'\n", " | >>> x.tobytes('C') == x.tobytes()\n", " | True\n", " | >>> x.tobytes('F')\n", " | b'\\x00\\x00\\x02\\x00\\x01\\x00\\x03\\x00'\n", " | \n", " | tofile(...)\n", " | a.tofile(fid, sep=\"\", format=\"%s\")\n", " | \n", " | Write array to a file as text or binary (default).\n", " | \n", " | Data is always written in 'C' order, independent of the order of `a`.\n", " | The data produced by this method can be recovered using the function\n", " | fromfile().\n", " | \n", " | Parameters\n", " | ----------\n", " | fid : file or str or Path\n", " | An open file object, or a string containing a filename.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | sep : str\n", " | Separator between array items for text output.\n", " | If \"\" (empty), a binary file is written, equivalent to\n", " | ``file.write(a.tobytes())``.\n", " | format : str\n", " | Format string for text file output.\n", " | Each entry in the array is formatted to text by first converting\n", " | it to the closest Python type, and then using \"format\" % item.\n", " | \n", " | Notes\n", " | -----\n", " | This is a convenience function for quick storage of array data.\n", " | Information on endianness and precision is lost, so this method is not a\n", " | good choice for files intended to archive data or transport data between\n", " | machines with different endianness. Some of these problems can be overcome\n", " | by outputting the data as text files, at the expense of speed and file\n", " | size.\n", " | \n", " | When fid is a file object, array contents are directly written to the\n", " | file, bypassing the file object's ``write`` method. As a result, tofile\n", " | cannot be used with files objects supporting compression (e.g., GzipFile)\n", " | or file-like objects that do not support ``fileno()`` (e.g., BytesIO).\n", " | \n", " | tolist(...)\n", " | a.tolist()\n", " | \n", " | Return the array as an ``a.ndim``-levels deep nested list of Python scalars.\n", " | \n", " | Return a copy of the array data as a (nested) Python list.\n", " | Data items are converted to the nearest compatible builtin Python type, via\n", " | the `~numpy.ndarray.item` function.\n", " | \n", " | If ``a.ndim`` is 0, then since the depth of the nested list is 0, it will\n", " | not be a list at all, but a simple Python scalar.\n", " | \n", " | Parameters\n", " | ----------\n", " | none\n", " | \n", " | Returns\n", " | -------\n", " | y : object, or list of object, or list of list of object, or ...\n", " | The possibly nested list of array elements.\n", " | \n", " | Notes\n", " | -----\n", " | The array may be recreated via ``a = np.array(a.tolist())``, although this\n", " | may sometimes lose precision.\n", " | \n", " | Examples\n", " | --------\n", " | For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``,\n", " | except that ``tolist`` changes numpy scalars to Python scalars:\n", " | \n", " | >>> a = np.uint32([1, 2])\n", " | >>> a_list = list(a)\n", " | >>> a_list\n", " | [1, 2]\n", " | >>> type(a_list[0])\n", " | \n", " | >>> a_tolist = a.tolist()\n", " | >>> a_tolist\n", " | [1, 2]\n", " | >>> type(a_tolist[0])\n", " | \n", " | \n", " | Additionally, for a 2D array, ``tolist`` applies recursively:\n", " | \n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> list(a)\n", " | [array([1, 2]), array([3, 4])]\n", " | >>> a.tolist()\n", " | [[1, 2], [3, 4]]\n", " | \n", " | The base case for this recursion is a 0D array:\n", " | \n", " | >>> a = np.array(1)\n", " | >>> list(a)\n", " | Traceback (most recent call last):\n", " | ...\n", " | TypeError: iteration over a 0-d array\n", " | >>> a.tolist()\n", " | 1\n", " | \n", " | tostring(...)\n", " | a.tostring(order='C')\n", " | \n", " | A compatibility alias for `tobytes`, with exactly the same behavior.\n", " | \n", " | Despite its name, it returns `bytes` not `str`\\ s.\n", " | \n", " | .. deprecated:: 1.19.0\n", " | \n", " | trace(...)\n", " | a.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)\n", " | \n", " | Return the sum along diagonals of the array.\n", " | \n", " | Refer to `numpy.trace` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.trace : equivalent function\n", " | \n", " | transpose(...)\n", " | a.transpose(*axes)\n", " | \n", " | Returns a view of the array with axes transposed.\n", " | \n", " | For a 1-D array this has no effect, as a transposed vector is simply the\n", " | same vector. To convert a 1-D array into a 2D column vector, an additional\n", " | dimension must be added. `np.atleast2d(a).T` achieves this, as does\n", " | `a[:, np.newaxis]`.\n", " | For a 2-D array, this is a standard matrix transpose.\n", " | For an n-D array, if axes are given, their order indicates how the\n", " | axes are permuted (see Examples). If axes are not provided and\n", " | ``a.shape = (i[0], i[1], ... i[n-2], i[n-1])``, then\n", " | ``a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])``.\n", " | \n", " | Parameters\n", " | ----------\n", " | axes : None, tuple of ints, or `n` ints\n", " | \n", " | * None or no argument: reverses the order of the axes.\n", " | \n", " | * tuple of ints: `i` in the `j`-th place in the tuple means `a`'s\n", " | `i`-th axis becomes `a.transpose()`'s `j`-th axis.\n", " | \n", " | * `n` ints: same as an n-tuple of the same ints (this form is\n", " | intended simply as a \"convenience\" alternative to the tuple form)\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | View of `a`, with axes suitably permuted.\n", " | \n", " | See Also\n", " | --------\n", " | ndarray.T : Array property returning the array transposed.\n", " | ndarray.reshape : Give a new shape to an array without changing its data.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> a\n", " | array([[1, 2],\n", " | [3, 4]])\n", " | >>> a.transpose()\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose((1, 0))\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose(1, 0)\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | \n", " | var(...)\n", " | a.var(axis=None, dtype=None, out=None, ddof=0, keepdims=False)\n", " | \n", " | Returns the variance of the array elements, along given axis.\n", " | \n", " | Refer to `numpy.var` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.var : equivalent function\n", " | \n", " | view(...)\n", " | a.view([dtype][, type])\n", " | \n", " | New view of array with the same data.\n", " | \n", " | .. note::\n", " | Passing None for ``dtype`` is different from omitting the parameter,\n", " | since the former invokes ``dtype(None)`` which is an alias for\n", " | ``dtype('float_')``.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : data-type or ndarray sub-class, optional\n", " | Data-type descriptor of the returned view, e.g., float32 or int16.\n", " | Omitting it results in the view having the same data-type as `a`.\n", " | This argument can also be specified as an ndarray sub-class, which\n", " | then specifies the type of the returned object (this is equivalent to\n", " | setting the ``type`` parameter).\n", " | type : Python type, optional\n", " | Type of the returned view, e.g., ndarray or matrix. Again, omission\n", " | of the parameter results in type preservation.\n", " | \n", " | Notes\n", " | -----\n", " | ``a.view()`` is used two different ways:\n", " | \n", " | ``a.view(some_dtype)`` or ``a.view(dtype=some_dtype)`` constructs a view\n", " | of the array's memory with a different data-type. This can cause a\n", " | reinterpretation of the bytes of memory.\n", " | \n", " | ``a.view(ndarray_subclass)`` or ``a.view(type=ndarray_subclass)`` just\n", " | returns an instance of `ndarray_subclass` that looks at the same array\n", " | (same shape, dtype, etc.) This does not cause a reinterpretation of the\n", " | memory.\n", " | \n", " | For ``a.view(some_dtype)``, if ``some_dtype`` has a different number of\n", " | bytes per entry than the previous dtype (for example, converting a\n", " | regular array to a structured array), then the behavior of the view\n", " | cannot be predicted just from the superficial appearance of ``a`` (shown\n", " | by ``print(a)``). It also depends on exactly how ``a`` is stored in\n", " | memory. Therefore if ``a`` is C-ordered versus fortran-ordered, versus\n", " | defined as a slice or transpose, etc., the view may give different\n", " | results.\n", " | \n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | \n", " | Viewing array data using a different type and dtype:\n", " | \n", " | >>> y = x.view(dtype=np.int16, type=np.matrix)\n", " | >>> y\n", " | matrix([[513]], dtype=int16)\n", " | >>> print(type(y))\n", " | \n", " | \n", " | Creating a view on a structured array so it can be used in calculations\n", " | \n", " | >>> x = np.array([(1, 2),(3,4)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | >>> xv = x.view(dtype=np.int8).reshape(-1,2)\n", " | >>> xv\n", " | array([[1, 2],\n", " | [3, 4]], dtype=int8)\n", " | >>> xv.mean(0)\n", " | array([2., 3.])\n", " | \n", " | Making changes to the view changes the underlying array\n", " | \n", " | >>> xv[0,1] = 20\n", " | >>> x\n", " | array([(1, 20), (3, 4)], dtype=[('a', 'i1'), ('b', 'i1')])\n", " | \n", " | Using a view to convert an array to a recarray:\n", " | \n", " | >>> z = x.view(np.recarray)\n", " | >>> z.a\n", " | array([1, 3], dtype=int8)\n", " | \n", " | Views share data:\n", " | \n", " | >>> x[0] = (9, 10)\n", " | >>> z[0]\n", " | (9, 10)\n", " | \n", " | Views that change the dtype size (bytes per entry) should normally be\n", " | avoided on arrays defined by slices, transposes, fortran-ordering, etc.:\n", " | \n", " | >>> x = np.array([[1,2,3],[4,5,6]], dtype=np.int16)\n", " | >>> y = x[:, 0:2]\n", " | >>> y\n", " | array([[1, 2],\n", " | [4, 5]], dtype=int16)\n", " | >>> y.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: To change to a dtype of a different size, the array must be C-contiguous\n", " | >>> z = y.copy()\n", " | >>> z.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | array([[(1, 2)],\n", " | [(4, 5)]], dtype=[('width', '>> x = np.array([[1.,2.],[3.,4.]])\n", " | >>> x\n", " | array([[ 1., 2.],\n", " | [ 3., 4.]])\n", " | >>> x.T\n", " | array([[ 1., 3.],\n", " | [ 2., 4.]])\n", " | >>> x = np.array([1.,2.,3.,4.])\n", " | >>> x\n", " | array([ 1., 2., 3., 4.])\n", " | >>> x.T\n", " | array([ 1., 2., 3., 4.])\n", " | \n", " | See Also\n", " | --------\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side.\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: C-struct side.\n", " | \n", " | base\n", " | Base object if memory is from some other object.\n", " | \n", " | Examples\n", " | --------\n", " | The base of an array that owns its memory is None:\n", " | \n", " | >>> x = np.array([1,2,3,4])\n", " | >>> x.base is None\n", " | True\n", " | \n", " | Slicing creates a view, whose memory is shared with x:\n", " | \n", " | >>> y = x[2:]\n", " | >>> y.base is x\n", " | True\n", " | \n", " | ctypes\n", " | An object to simplify the interaction of the array with the ctypes\n", " | module.\n", " | \n", " | This attribute creates an object that makes it easier to use arrays\n", " | when calling shared libraries with the ctypes module. The returned\n", " | object has, among others, data, shape, and strides attributes (see\n", " | Notes below) which themselves return ctypes objects that can be used\n", " | as arguments to a shared library.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | c : Python object\n", " | Possessing attributes data, shape, strides, etc.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ctypeslib\n", " | \n", " | Notes\n", " | -----\n", " | Below are the public attributes of this object which were documented\n", " | in \"Guide to NumPy\" (we have omitted undocumented public attributes,\n", " | as well as documented private attributes):\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.data\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.shape\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.strides\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.data_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.shape_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.strides_as\n", " | :noindex:\n", " | \n", " | If the ctypes module is not available, then the ctypes attribute\n", " | of array objects still returns something useful, but ctypes objects\n", " | are not returned and errors may be raised instead. In particular,\n", " | the object will still have the ``as_parameter`` attribute which will\n", " | return an integer equal to the data attribute.\n", " | \n", " | Examples\n", " | --------\n", " | >>> import ctypes\n", " | >>> x = np.array([[0, 1], [2, 3]], dtype=np.int32)\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]], dtype=int32)\n", " | >>> x.ctypes.data\n", " | 31962608 # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32))\n", " | <__main__.LP_c_uint object at 0x7ff2fc1fc200> # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32)).contents\n", " | c_uint(0)\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint64)).contents\n", " | c_ulong(4294967296)\n", " | >>> x.ctypes.shape\n", " | # may vary\n", " | >>> x.ctypes.strides\n", " | # may vary\n", " | \n", " | data\n", " | Python buffer object pointing to the start of the array's data.\n", " | \n", " | dtype\n", " | Data-type of the array's elements.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | d : numpy dtype object\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dtype\n", " | \n", " | Examples\n", " | --------\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]])\n", " | >>> x.dtype\n", " | dtype('int32')\n", " | >>> type(x.dtype)\n", " | \n", " | \n", " | flags\n", " | Information about the memory layout of the array.\n", " | \n", " | Attributes\n", " | ----------\n", " | C_CONTIGUOUS (C)\n", " | The data is in a single, C-style contiguous segment.\n", " | F_CONTIGUOUS (F)\n", " | The data is in a single, Fortran-style contiguous segment.\n", " | OWNDATA (O)\n", " | The array owns the memory it uses or borrows it from another object.\n", " | WRITEABLE (W)\n", " | The data area can be written to. Setting this to False locks\n", " | the data, making it read-only. A view (slice, etc.) inherits WRITEABLE\n", " | from its base array at creation time, but a view of a writeable\n", " | array may be subsequently locked while the base array remains writeable.\n", " | (The opposite is not true, in that a view of a locked array may not\n", " | be made writeable. However, currently, locking a base object does not\n", " | lock any views that already reference it, so under that circumstance it\n", " | is possible to alter the contents of a locked array via a previously\n", " | created writeable view onto it.) Attempting to change a non-writeable\n", " | array raises a RuntimeError exception.\n", " | ALIGNED (A)\n", " | The data and all elements are aligned appropriately for the hardware.\n", " | WRITEBACKIFCOPY (X)\n", " | This array is a copy of some other array. The C-API function\n", " | PyArray_ResolveWritebackIfCopy must be called before deallocating\n", " | to the base array will be updated with the contents of this array.\n", " | UPDATEIFCOPY (U)\n", " | (Deprecated, use WRITEBACKIFCOPY) This array is a copy of some other array.\n", " | When this array is\n", " | deallocated, the base array will be updated with the contents of\n", " | this array.\n", " | FNC\n", " | F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | FORC\n", " | F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).\n", " | BEHAVED (B)\n", " | ALIGNED and WRITEABLE.\n", " | CARRAY (CA)\n", " | BEHAVED and C_CONTIGUOUS.\n", " | FARRAY (FA)\n", " | BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | \n", " | Notes\n", " | -----\n", " | The `flags` object can be accessed dictionary-like (as in ``a.flags['WRITEABLE']``),\n", " | or by using lowercased attribute names (as in ``a.flags.writeable``). Short flag\n", " | names are only supported in dictionary access.\n", " | \n", " | Only the WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be\n", " | changed by the user, via direct assignment to the attribute or dictionary\n", " | entry, or by calling `ndarray.setflags`.\n", " | \n", " | The array flags cannot be set arbitrarily:\n", " | \n", " | - UPDATEIFCOPY can only be set ``False``.\n", " | - WRITEBACKIFCOPY can only be set ``False``.\n", " | - ALIGNED can only be set ``True`` if the data is truly aligned.\n", " | - WRITEABLE can only be set ``True`` if the array owns its own memory\n", " | or the ultimate owner of the memory exposes a writeable buffer\n", " | interface or is a string.\n", " | \n", " | Arrays can be both C-style and Fortran-style contiguous simultaneously.\n", " | This is clear for 1-dimensional arrays, but can also be true for higher\n", " | dimensional arrays.\n", " | \n", " | Even for contiguous arrays a stride for a given dimension\n", " | ``arr.strides[dim]`` may be *arbitrary* if ``arr.shape[dim] == 1``\n", " | or the array has no elements.\n", " | It does *not* generally hold that ``self.strides[-1] == self.itemsize``\n", " | for C-style contiguous arrays or ``self.strides[0] == self.itemsize`` for\n", " | Fortran-style contiguous arrays is true.\n", " | \n", " | flat\n", " | A 1-D iterator over the array.\n", " | \n", " | This is a `numpy.flatiter` instance, which acts similarly to, but is not\n", " | a subclass of, Python's built-in iterator object.\n", " | \n", " | See Also\n", " | --------\n", " | flatten : Return a copy of the array collapsed into one dimension.\n", " | \n", " | flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(1, 7).reshape(2, 3)\n", " | >>> x\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | >>> x.flat[3]\n", " | 4\n", " | >>> x.T\n", " | array([[1, 4],\n", " | [2, 5],\n", " | [3, 6]])\n", " | >>> x.T.flat[3]\n", " | 5\n", " | >>> type(x.flat)\n", " | \n", " | \n", " | An assignment example:\n", " | \n", " | >>> x.flat = 3; x\n", " | array([[3, 3, 3],\n", " | [3, 3, 3]])\n", " | >>> x.flat[[1,4]] = 1; x\n", " | array([[3, 1, 3],\n", " | [3, 1, 3]])\n", " | \n", " | imag\n", " | The imaginary part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.imag\n", " | array([ 0. , 0.70710678])\n", " | >>> x.imag.dtype\n", " | dtype('float64')\n", " | \n", " | itemsize\n", " | Length of one array element in bytes.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1,2,3], dtype=np.float64)\n", " | >>> x.itemsize\n", " | 8\n", " | >>> x = np.array([1,2,3], dtype=np.complex128)\n", " | >>> x.itemsize\n", " | 16\n", " | \n", " | nbytes\n", " | Total bytes consumed by the elements of the array.\n", " | \n", " | Notes\n", " | -----\n", " | Does not include memory consumed by non-element attributes of the\n", " | array object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3,5,2), dtype=np.complex128)\n", " | >>> x.nbytes\n", " | 480\n", " | >>> np.prod(x.shape) * x.itemsize\n", " | 480\n", " | \n", " | ndim\n", " | Number of array dimensions.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> x.ndim\n", " | 1\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.ndim\n", " | 3\n", " | \n", " | real\n", " | The real part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.real\n", " | array([ 1. , 0.70710678])\n", " | >>> x.real.dtype\n", " | dtype('float64')\n", " | \n", " | See Also\n", " | --------\n", " | numpy.real : equivalent function\n", " | \n", " | shape\n", " | Tuple of array dimensions.\n", " | \n", " | The shape property is usually used to get the current shape of an array,\n", " | but may also be used to reshape the array in-place by assigning a tuple of\n", " | array dimensions to it. As with `numpy.reshape`, one of the new shape\n", " | dimensions can be -1, in which case its value is inferred from the size of\n", " | the array and the remaining dimensions. Reshaping an array in-place will\n", " | fail if a copy is required.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3, 4])\n", " | >>> x.shape\n", " | (4,)\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.shape\n", " | (2, 3, 4)\n", " | >>> y.shape = (3, 8)\n", " | >>> y\n", " | array([[ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.]])\n", " | >>> y.shape = (3, 6)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: total size of new array must be unchanged\n", " | >>> np.zeros((4,2))[::2].shape = (-1,)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | AttributeError: Incompatible shape for in-place modification. Use\n", " | `.reshape()` to make a copy with the desired shape.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : similar function\n", " | ndarray.reshape : similar method\n", " | \n", " | size\n", " | Number of elements in the array.\n", " | \n", " | Equal to ``np.prod(a.shape)``, i.e., the product of the array's\n", " | dimensions.\n", " | \n", " | Notes\n", " | -----\n", " | `a.size` returns a standard arbitrary precision Python integer. This\n", " | may not be the case with other methods of obtaining the same value\n", " | (like the suggested ``np.prod(a.shape)``, which returns an instance\n", " | of ``np.int_``), and may be relevant if the value is used further in\n", " | calculations that may overflow a fixed size integer type.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3, 5, 2), dtype=np.complex128)\n", " | >>> x.size\n", " | 30\n", " | >>> np.prod(x.shape)\n", " | 30\n", " | \n", " | strides\n", " | Tuple of bytes to step in each dimension when traversing an array.\n", " | \n", " | The byte offset of element ``(i[0], i[1], ..., i[n])`` in an array `a`\n", " | is::\n", " | \n", " | offset = sum(np.array(i) * a.strides)\n", " | \n", " | A more detailed explanation of strides can be found in the\n", " | \"ndarray.rst\" file in the NumPy reference guide.\n", " | \n", " | Notes\n", " | -----\n", " | Imagine an array of 32-bit integers (each 4 bytes)::\n", " | \n", " | x = np.array([[0, 1, 2, 3, 4],\n", " | [5, 6, 7, 8, 9]], dtype=np.int32)\n", " | \n", " | This array is stored in memory as 40 bytes, one after the other\n", " | (known as a contiguous block of memory). The strides of an array tell\n", " | us how many bytes we have to skip in memory to move to the next position\n", " | along a certain axis. For example, we have to skip 4 bytes (1 value) to\n", " | move to the next column, but 20 bytes (5 values) to get to the same\n", " | position in the next row. As such, the strides for the array `x` will be\n", " | ``(20, 4)``.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.lib.stride_tricks.as_strided\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.reshape(np.arange(2*3*4), (2,3,4))\n", " | >>> y\n", " | array([[[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]],\n", " | [[12, 13, 14, 15],\n", " | [16, 17, 18, 19],\n", " | [20, 21, 22, 23]]])\n", " | >>> y.strides\n", " | (48, 16, 4)\n", " | >>> y[1,1,1]\n", " | 17\n", " | >>> offset=sum(y.strides * np.array((1,1,1)))\n", " | >>> offset/y.itemsize\n", " | 17\n", " | \n", " | >>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0)\n", " | >>> x.strides\n", " | (32, 4, 224, 1344)\n", " | >>> i = np.array([3,5,2,2])\n", " | >>> offset = sum(i * x.strides)\n", " | >>> x[3,5,2,2]\n", " | 813\n", " | >>> offset / x.itemsize\n", " | 813\n", " \n", " clongdouble = class complex256(complexfloating)\n", " | Complex number type composed of two extended-precision floating-point\n", " | numbers.\n", " | Character code: ``'G'``.\n", " | Canonical name: ``np.clongdouble``.\n", " | Alias: ``np.clongfloat``.\n", " | Alias: ``np.longcomplex``.\n", " | Alias *on this platform*: ``np.complex256``: Complex number type composed of 2 128-bit extended-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex256\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " clongfloat = class complex256(complexfloating)\n", " | Complex number type composed of two extended-precision floating-point\n", " | numbers.\n", " | Character code: ``'G'``.\n", " | Canonical name: ``np.clongdouble``.\n", " | Alias: ``np.clongfloat``.\n", " | Alias: ``np.longcomplex``.\n", " | Alias *on this platform*: ``np.complex256``: Complex number type composed of 2 128-bit extended-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex256\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class complex128(complexfloating, builtins.complex)\n", " | complex128(real=0, imag=0)\n", " | \n", " | Complex number type composed of two double-precision floating-point\n", " | numbers, compatible with Python `complex`.\n", " | Character code: ``'D'``.\n", " | Canonical name: ``np.cdouble``.\n", " | Alias: ``np.cfloat``.\n", " | Alias: ``np.complex_``.\n", " | Alias *on this platform*: ``np.complex128``: Complex number type composed of 2 64-bit-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex128\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.complex\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.complex:\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getnewargs__(...)\n", " \n", " class complex256(complexfloating)\n", " | Complex number type composed of two extended-precision floating-point\n", " | numbers.\n", " | Character code: ``'G'``.\n", " | Canonical name: ``np.clongdouble``.\n", " | Alias: ``np.clongfloat``.\n", " | Alias: ``np.longcomplex``.\n", " | Alias *on this platform*: ``np.complex256``: Complex number type composed of 2 128-bit extended-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex256\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class complex64(complexfloating)\n", " | Complex number type composed of two single-precision floating-point\n", " | numbers.\n", " | Character code: ``'F'``.\n", " | Canonical name: ``np.csingle``.\n", " | Alias: ``np.singlecomplex``.\n", " | Alias *on this platform*: ``np.complex64``: Complex number type composed of 2 32-bit-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex64\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " complex_ = class complex128(complexfloating, builtins.complex)\n", " | complex_(real=0, imag=0)\n", " | \n", " | Complex number type composed of two double-precision floating-point\n", " | numbers, compatible with Python `complex`.\n", " | Character code: ``'D'``.\n", " | Canonical name: ``np.cdouble``.\n", " | Alias: ``np.cfloat``.\n", " | Alias: ``np.complex_``.\n", " | Alias *on this platform*: ``np.complex128``: Complex number type composed of 2 64-bit-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex128\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.complex\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.complex:\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getnewargs__(...)\n", " \n", " class complexfloating(inexact)\n", " | Abstract base class of all complex number scalar types that are made up of\n", " | floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " csingle = class complex64(complexfloating)\n", " | Complex number type composed of two single-precision floating-point\n", " | numbers.\n", " | Character code: ``'F'``.\n", " | Canonical name: ``np.csingle``.\n", " | Alias: ``np.singlecomplex``.\n", " | Alias *on this platform*: ``np.complex64``: Complex number type composed of 2 32-bit-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex64\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class datetime64(generic)\n", " | Base class for numpy scalar types.\n", " | \n", " | Class from which most (all?) numpy scalar types are derived. For\n", " | consistency, exposes the same API as `ndarray`, despite many\n", " | consequent attributes being either \"get-only,\" or completely irrelevant.\n", " | This is the class from which it is strongly suggested users should derive\n", " | custom scalar types.\n", " | \n", " | Method resolution order:\n", " | datetime64\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " double = class float64(floating, builtins.float)\n", " | double(x=0, /)\n", " | \n", " | Double-precision floating-point number type, compatible with Python `float`\n", " | and C ``double``.\n", " | Character code: ``'d'``.\n", " | Canonical name: ``np.double``.\n", " | Alias: ``np.float_``.\n", " | Alias *on this platform*: ``np.float64``: 64-bit precision floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa.\n", " | \n", " | Method resolution order:\n", " | float64\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.float\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.double(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.double(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.double(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.float:\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getnewargs__(self, /)\n", " | \n", " | __trunc__(self, /)\n", " | Return the Integral closest to x between 0 and x.\n", " | \n", " | hex(self, /)\n", " | Return a hexadecimal representation of a floating-point number.\n", " | \n", " | >>> (-0.1).hex()\n", " | '-0x1.999999999999ap-4'\n", " | >>> 3.14159.hex()\n", " | '0x1.921f9f01b866ep+1'\n", " | \n", " | is_integer(self, /)\n", " | Return True if the float is an integer.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Class methods inherited from builtins.float:\n", " | \n", " | __getformat__(typestr, /) from builtins.type\n", " | You probably don't want to use this function.\n", " | \n", " | typestr\n", " | Must be 'double' or 'float'.\n", " | \n", " | It exists mainly to be used in Python's test suite.\n", " | \n", " | This function returns whichever of 'unknown', 'IEEE, big-endian' or 'IEEE,\n", " | little-endian' best describes the format of floating point numbers used by the\n", " | C type named by typestr.\n", " | \n", " | __set_format__(typestr, fmt, /) from builtins.type\n", " | You probably don't want to use this function.\n", " | \n", " | typestr\n", " | Must be 'double' or 'float'.\n", " | fmt\n", " | Must be one of 'unknown', 'IEEE, big-endian' or 'IEEE, little-endian',\n", " | and in addition can only be one of the latter two if it appears to\n", " | match the underlying C reality.\n", " | \n", " | It exists mainly to be used in Python's test suite.\n", " | \n", " | Override the automatic determination of C-level floating point type.\n", " | This affects how floats are converted to and from binary strings.\n", " | \n", " | fromhex(string, /) from builtins.type\n", " | Create a floating-point number from a hexadecimal string.\n", " | \n", " | >>> float.fromhex('0x1.ffffp10')\n", " | 2047.984375\n", " | >>> float.fromhex('-0x1p-1074')\n", " | -5e-324\n", " \n", " class dtype(builtins.object)\n", " | dtype(obj, align=False, copy=False)\n", " | \n", " | Create a data type object.\n", " | \n", " | A numpy array is homogeneous, and contains elements described by a\n", " | dtype object. A dtype object can be constructed from different\n", " | combinations of fundamental numeric types.\n", " | \n", " | Parameters\n", " | ----------\n", " | obj\n", " | Object to be converted to a data type object.\n", " | align : bool, optional\n", " | Add padding to the fields to match what a C compiler would output\n", " | for a similar C-struct. Can be ``True`` only if `obj` is a dictionary\n", " | or a comma-separated string. If a struct dtype is being created,\n", " | this also sets a sticky alignment flag ``isalignedstruct``.\n", " | copy : bool, optional\n", " | Make a new copy of the data-type object. If ``False``, the result\n", " | may just be a reference to a built-in data-type object.\n", " | \n", " | See also\n", " | --------\n", " | result_type\n", " | \n", " | Examples\n", " | --------\n", " | Using array-scalar type:\n", " | \n", " | >>> np.dtype(np.int16)\n", " | dtype('int16')\n", " | \n", " | Structured type, one field name 'f1', containing int16:\n", " | \n", " | >>> np.dtype([('f1', np.int16)])\n", " | dtype([('f1', '>> np.dtype([('f1', [('f1', np.int16)])])\n", " | dtype([('f1', [('f1', '>> np.dtype([('f1', np.uint64), ('f2', np.int32)])\n", " | dtype([('f1', '>> np.dtype([('a','f8'),('b','S10')])\n", " | dtype([('a', '>> np.dtype(\"i4, (2,3)f8\")\n", " | dtype([('f0', '>> np.dtype([('hello',(np.int64,3)),('world',np.void,10)])\n", " | dtype([('hello', '>> np.dtype((np.int16, {'x':(np.int8,0), 'y':(np.int8,1)}))\n", " | dtype((numpy.int16, [('x', 'i1'), ('y', 'i1')]))\n", " | \n", " | Using dictionaries. Two fields named 'gender' and 'age':\n", " | \n", " | >>> np.dtype({'names':['gender','age'], 'formats':['S1',np.uint8]})\n", " | dtype([('gender', 'S1'), ('age', 'u1')])\n", " | \n", " | Offsets in bytes, here 0 and 25:\n", " | \n", " | >>> np.dtype({'surname':('S25',0),'age':(np.uint8,25)})\n", " | dtype([('surname', 'S25'), ('age', 'u1')])\n", " | \n", " | Methods defined here:\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lt__(self, value, /)\n", " | Return self', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | The code does a case-insensitive check on the first letter of\n", " | `new_order` for these alternatives. For example, any of '>'\n", " | or 'B' or 'b' or 'brian' are valid to specify big-endian.\n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New dtype object with the given change to the byte order.\n", " | \n", " | Notes\n", " | -----\n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | Examples\n", " | --------\n", " | >>> import sys\n", " | >>> sys_is_le = sys.byteorder == 'little'\n", " | >>> native_code = sys_is_le and '<' or '>'\n", " | >>> swapped_code = sys_is_le and '>' or '<'\n", " | >>> native_dt = np.dtype(native_code+'i2')\n", " | >>> swapped_dt = np.dtype(swapped_code+'i2')\n", " | >>> native_dt.newbyteorder('S') == swapped_dt\n", " | True\n", " | >>> native_dt.newbyteorder() == swapped_dt\n", " | True\n", " | >>> native_dt == swapped_dt.newbyteorder('S')\n", " | True\n", " | >>> native_dt == swapped_dt.newbyteorder('=')\n", " | True\n", " | >>> native_dt == swapped_dt.newbyteorder('N')\n", " | True\n", " | >>> native_dt == native_dt.newbyteorder('|')\n", " | True\n", " | >>> np.dtype('>> np.dtype('>> np.dtype('>i2') == native_dt.newbyteorder('>')\n", " | True\n", " | >>> np.dtype('>i2') == native_dt.newbyteorder('B')\n", " | True\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | alignment\n", " | The required alignment (bytes) of this data-type according to the compiler.\n", " | \n", " | More information is available in the C-API section of the manual.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> x = np.dtype('i4')\n", " | >>> x.alignment\n", " | 4\n", " | \n", " | >>> x = np.dtype(float)\n", " | >>> x.alignment\n", " | 8\n", " | \n", " | base\n", " | Returns dtype for the base element of the subarrays,\n", " | regardless of their dimension or shape.\n", " | \n", " | See Also\n", " | --------\n", " | dtype.subdtype\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = numpy.dtype('8f')\n", " | >>> x.base\n", " | dtype('float32')\n", " | \n", " | >>> x = numpy.dtype('i2')\n", " | >>> x.base\n", " | dtype('int16')\n", " | \n", " | byteorder\n", " | A character indicating the byte-order of this data-type object.\n", " | \n", " | One of:\n", " | \n", " | === ==============\n", " | '=' native\n", " | '<' little-endian\n", " | '>' big-endian\n", " | '|' not applicable\n", " | === ==============\n", " | \n", " | All built-in data-type objects have byteorder either '=' or '|'.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> dt = np.dtype('i2')\n", " | >>> dt.byteorder\n", " | '='\n", " | >>> # endian is not relevant for 8 bit numbers\n", " | >>> np.dtype('i1').byteorder\n", " | '|'\n", " | >>> # or ASCII strings\n", " | >>> np.dtype('S2').byteorder\n", " | '|'\n", " | >>> # Even if specific code is given, and it is native\n", " | >>> # '=' is the byteorder\n", " | >>> import sys\n", " | >>> sys_is_le = sys.byteorder == 'little'\n", " | >>> native_code = sys_is_le and '<' or '>'\n", " | >>> swapped_code = sys_is_le and '>' or '<'\n", " | >>> dt = np.dtype(native_code + 'i2')\n", " | >>> dt.byteorder\n", " | '='\n", " | >>> # Swapped code shows up as itself\n", " | >>> dt = np.dtype(swapped_code + 'i2')\n", " | >>> dt.byteorder == swapped_code\n", " | True\n", " | \n", " | char\n", " | A unique character code for each of the 21 different built-in types.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> x = np.dtype(float)\n", " | >>> x.char\n", " | 'd'\n", " | \n", " | descr\n", " | `__array_interface__` description of the data-type.\n", " | \n", " | The format is that required by the 'descr' key in the\n", " | `__array_interface__` attribute.\n", " | \n", " | Warning: This attribute exists specifically for `__array_interface__`,\n", " | and passing it directly to `np.dtype` will not accurately reconstruct\n", " | some dtypes (e.g., scalar and subarray dtypes).\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> x = np.dtype(float)\n", " | >>> x.descr\n", " | [('', '>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])\n", " | >>> dt.descr\n", " | [('name', '>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])\n", " | >>> print(dt.fields)\n", " | {'grades': (dtype(('float64',(2,))), 16), 'name': (dtype('|S16'), 0)}\n", " | \n", " | flags\n", " | Bit-flags describing how this data type is to be interpreted.\n", " | \n", " | Bit-masks are in `numpy.core.multiarray` as the constants\n", " | `ITEM_HASOBJECT`, `LIST_PICKLE`, `ITEM_IS_POINTER`, `NEEDS_INIT`,\n", " | `NEEDS_PYAPI`, `USE_GETITEM`, `USE_SETITEM`. A full explanation\n", " | of these flags is in C-API documentation; they are largely useful\n", " | for user-defined data-types.\n", " | \n", " | The following example demonstrates that operations on this particular\n", " | dtype requires Python C-API.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> x = np.dtype([('a', np.int32, 8), ('b', np.float64, 6)])\n", " | >>> x.flags\n", " | 16\n", " | >>> np.core.multiarray.NEEDS_PYAPI\n", " | 16\n", " | \n", " | hasobject\n", " | Boolean indicating whether this dtype contains any reference-counted\n", " | objects in any fields or sub-dtypes.\n", " | \n", " | Recall that what is actually in the ndarray memory representing\n", " | the Python object is the memory address of that object (a pointer).\n", " | Special handling may be required, and this attribute is useful for\n", " | distinguishing data types that may contain arbitrary Python objects\n", " | and data-types that won't.\n", " | \n", " | isalignedstruct\n", " | Boolean indicating whether the dtype is a struct which maintains\n", " | field alignment. This flag is sticky, so when combining multiple\n", " | structs together, it is preserved and produces new dtypes which\n", " | are also aligned.\n", " | \n", " | isbuiltin\n", " | Integer indicating how this dtype relates to the built-in dtypes.\n", " | \n", " | Read-only.\n", " | \n", " | = ========================================================================\n", " | 0 if this is a structured array type, with fields\n", " | 1 if this is a dtype compiled into numpy (such as ints, floats etc)\n", " | 2 if the dtype is for a user-defined numpy type\n", " | A user-defined type uses the numpy C-API machinery to extend\n", " | numpy to handle a new array type. See\n", " | :ref:`user.user-defined-data-types` in the NumPy manual.\n", " | = ========================================================================\n", " | \n", " | Examples\n", " | --------\n", " | >>> dt = np.dtype('i2')\n", " | >>> dt.isbuiltin\n", " | 1\n", " | >>> dt = np.dtype('f8')\n", " | >>> dt.isbuiltin\n", " | 1\n", " | >>> dt = np.dtype([('field1', 'f8')])\n", " | >>> dt.isbuiltin\n", " | 0\n", " | \n", " | isnative\n", " | Boolean indicating whether the byte order of this dtype is native\n", " | to the platform.\n", " | \n", " | itemsize\n", " | The element size of this data-type object.\n", " | \n", " | For 18 of the 21 types this number is fixed by the data-type.\n", " | For the flexible data-types, this number can be anything.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> arr = np.array([[1, 2], [3, 4]])\n", " | >>> arr.dtype\n", " | dtype('int64')\n", " | >>> arr.itemsize\n", " | 8\n", " | \n", " | >>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])\n", " | >>> dt.itemsize\n", " | 80\n", " | \n", " | kind\n", " | A character code (one of 'biufcmMOSUV') identifying the general kind of data.\n", " | \n", " | = ======================\n", " | b boolean\n", " | i signed integer\n", " | u unsigned integer\n", " | f floating-point\n", " | c complex floating-point\n", " | m timedelta\n", " | M datetime\n", " | O object\n", " | S (byte-)string\n", " | U Unicode\n", " | V void\n", " | = ======================\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> dt = np.dtype('i4')\n", " | >>> dt.kind\n", " | 'i'\n", " | >>> dt = np.dtype('f8')\n", " | >>> dt.kind\n", " | 'f'\n", " | >>> dt = np.dtype([('field1', 'f8')])\n", " | >>> dt.kind\n", " | 'V'\n", " | \n", " | metadata\n", " | \n", " | name\n", " | A bit-width name for this data-type.\n", " | \n", " | Un-sized flexible data-type objects do not have this attribute.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> x = np.dtype(float)\n", " | >>> x.name\n", " | 'float64'\n", " | >>> x = np.dtype([('a', np.int32, 8), ('b', np.float64, 6)])\n", " | >>> x.name\n", " | 'void640'\n", " | \n", " | names\n", " | Ordered list of field names, or ``None`` if there are no fields.\n", " | \n", " | The names are ordered according to increasing byte offset. This can be\n", " | used, for example, to walk through all of the named fields in offset order.\n", " | \n", " | Examples\n", " | --------\n", " | >>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))])\n", " | >>> dt.names\n", " | ('name', 'grades')\n", " | \n", " | ndim\n", " | Number of dimensions of the sub-array if this data type describes a\n", " | sub-array, and ``0`` otherwise.\n", " | \n", " | .. versionadded:: 1.13.0\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.dtype(float)\n", " | >>> x.ndim\n", " | 0\n", " | \n", " | >>> x = np.dtype((float, 8))\n", " | >>> x.ndim\n", " | 1\n", " | \n", " | >>> x = np.dtype(('i4', (3, 4)))\n", " | >>> x.ndim\n", " | 2\n", " | \n", " | num\n", " | A unique number for each of the 21 different built-in types.\n", " | \n", " | These are roughly ordered from least-to-most precision.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> dt = np.dtype(str)\n", " | >>> dt.num\n", " | 19\n", " | \n", " | >>> dt = np.dtype(float)\n", " | >>> dt.num\n", " | 12\n", " | \n", " | shape\n", " | Shape tuple of the sub-array if this data type describes a sub-array,\n", " | and ``()`` otherwise.\n", " | \n", " | Examples\n", " | --------\n", " | \n", " | >>> dt = np.dtype(('i4', 4))\n", " | >>> dt.shape\n", " | (4,)\n", " | \n", " | >>> dt = np.dtype(('i4', (2, 3)))\n", " | >>> dt.shape\n", " | (2, 3)\n", " | \n", " | str\n", " | The array-protocol typestring of this data-type object.\n", " | \n", " | subdtype\n", " | Tuple ``(item_dtype, shape)`` if this `dtype` describes a sub-array, and\n", " | None otherwise.\n", " | \n", " | The *shape* is the fixed shape of the sub-array described by this\n", " | data type, and *item_dtype* the data type of the array.\n", " | \n", " | If a field whose dtype object has this attribute is retrieved,\n", " | then the extra dimensions implied by *shape* are tacked on to\n", " | the end of the retrieved array.\n", " | \n", " | See Also\n", " | --------\n", " | dtype.base\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = numpy.dtype('8f')\n", " | >>> x.subdtype\n", " | (dtype('float32'), (8,))\n", " | \n", " | >>> x = numpy.dtype('i2')\n", " | >>> x.subdtype\n", " | >>>\n", " | \n", " | type\n", " | The type object used to instantiate a scalar of this data-type.\n", " \n", " class errstate(contextlib.ContextDecorator)\n", " | errstate(*, call=, **kwargs)\n", " | \n", " | errstate(**kwargs)\n", " | \n", " | Context manager for floating-point error handling.\n", " | \n", " | Using an instance of `errstate` as a context manager allows statements in\n", " | that context to execute with a known error handling behavior. Upon entering\n", " | the context the error handling is set with `seterr` and `seterrcall`, and\n", " | upon exiting it is reset to what it was before.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `errstate` is also usable as a function decorator, saving\n", " | a level of indentation if an entire function is wrapped.\n", " | See :py:class:`contextlib.ContextDecorator` for more information.\n", " | \n", " | Parameters\n", " | ----------\n", " | kwargs : {divide, over, under, invalid}\n", " | Keyword arguments. The valid keywords are the possible floating-point\n", " | exceptions. Each keyword should have a string value that defines the\n", " | treatment for the particular error. Possible values are\n", " | {'ignore', 'warn', 'raise', 'call', 'print', 'log'}.\n", " | \n", " | See Also\n", " | --------\n", " | seterr, geterr, seterrcall, geterrcall\n", " | \n", " | Notes\n", " | -----\n", " | For complete documentation of the types of floating-point exceptions and\n", " | treatment options, see `seterr`.\n", " | \n", " | Examples\n", " | --------\n", " | >>> from collections import OrderedDict\n", " | >>> olderr = np.seterr(all='ignore') # Set error handling to known state.\n", " | \n", " | >>> np.arange(3) / 0.\n", " | array([nan, inf, inf])\n", " | >>> with np.errstate(divide='warn'):\n", " | ... np.arange(3) / 0.\n", " | array([nan, inf, inf])\n", " | \n", " | >>> np.sqrt(-1)\n", " | nan\n", " | >>> with np.errstate(invalid='raise'):\n", " | ... np.sqrt(-1)\n", " | Traceback (most recent call last):\n", " | File \"\", line 2, in \n", " | FloatingPointError: invalid value encountered in sqrt\n", " | \n", " | Outside the context the error handling behavior has not changed:\n", " | \n", " | >>> OrderedDict(sorted(np.geterr().items()))\n", " | OrderedDict([('divide', 'ignore'), ('invalid', 'ignore'), ('over', 'ignore'), ('under', 'ignore')])\n", " | \n", " | Method resolution order:\n", " | errstate\n", " | contextlib.ContextDecorator\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __enter__(self)\n", " | \n", " | __exit__(self, *exc_info)\n", " | \n", " | __init__(self, *, call=, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from contextlib.ContextDecorator:\n", " | \n", " | __call__(self, func)\n", " | Call self as a function.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from contextlib.ContextDecorator:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class finfo(builtins.object)\n", " | finfo(dtype)\n", " | \n", " | finfo(dtype)\n", " | \n", " | Machine limits for floating point types.\n", " | \n", " | Attributes\n", " | ----------\n", " | bits : int\n", " | The number of bits occupied by the type.\n", " | eps : float\n", " | The difference between 1.0 and the next smallest representable float\n", " | larger than 1.0. For example, for 64-bit binary floats in the IEEE-754\n", " | standard, ``eps = 2**-52``, approximately 2.22e-16.\n", " | epsneg : float\n", " | The difference between 1.0 and the next smallest representable float\n", " | less than 1.0. For example, for 64-bit binary floats in the IEEE-754\n", " | standard, ``epsneg = 2**-53``, approximately 1.11e-16.\n", " | iexp : int\n", " | The number of bits in the exponent portion of the floating point\n", " | representation.\n", " | machar : MachAr\n", " | The object which calculated these parameters and holds more\n", " | detailed information.\n", " | machep : int\n", " | The exponent that yields `eps`.\n", " | max : floating point number of the appropriate type\n", " | The largest representable number.\n", " | maxexp : int\n", " | The smallest positive power of the base (2) that causes overflow.\n", " | min : floating point number of the appropriate type\n", " | The smallest representable number, typically ``-max``.\n", " | minexp : int\n", " | The most negative power of the base (2) consistent with there\n", " | being no leading 0's in the mantissa.\n", " | negep : int\n", " | The exponent that yields `epsneg`.\n", " | nexp : int\n", " | The number of bits in the exponent including its sign and bias.\n", " | nmant : int\n", " | The number of bits in the mantissa.\n", " | precision : int\n", " | The approximate number of decimal digits to which this kind of\n", " | float is precise.\n", " | resolution : floating point number of the appropriate type\n", " | The approximate decimal resolution of this type, i.e.,\n", " | ``10**-precision``.\n", " | tiny : float\n", " | The smallest positive usable number. Type of `tiny` is an\n", " | appropriate floating point type.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : float, dtype, or instance\n", " | Kind of floating point data-type about which to get information.\n", " | \n", " | See Also\n", " | --------\n", " | MachAr : The implementation of the tests that produce this information.\n", " | iinfo : The equivalent for integer data types.\n", " | spacing : The distance between a value and the nearest adjacent number\n", " | nextafter : The next floating point value after x1 towards x2\n", " | \n", " | Notes\n", " | -----\n", " | For developers of NumPy: do not instantiate this at the module level.\n", " | The initial calculation of these parameters is expensive and negatively\n", " | impacts import times. These objects are cached, so calling ``finfo()``\n", " | repeatedly inside your functions is not a problem.\n", " | \n", " | Methods defined here:\n", " | \n", " | __repr__(self)\n", " | Return repr(self).\n", " | \n", " | __str__(self)\n", " | Return str(self).\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(cls, dtype)\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class flatiter(builtins.object)\n", " | Flat iterator object to iterate over arrays.\n", " | \n", " | A `flatiter` iterator is returned by ``x.flat`` for any array `x`.\n", " | It allows iterating over the array as if it were a 1-D array,\n", " | either in a for-loop or by calling its `next` method.\n", " | \n", " | Iteration is done in row-major, C-style order (the last\n", " | index varying the fastest). The iterator can also be indexed using\n", " | basic slicing or advanced indexing.\n", " | \n", " | See Also\n", " | --------\n", " | ndarray.flat : Return a flat iterator over an array.\n", " | ndarray.flatten : Returns a flattened copy of an array.\n", " | \n", " | Notes\n", " | -----\n", " | A `flatiter` iterator can not be constructed directly from Python code\n", " | by calling the `flatiter` constructor.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(6).reshape(2, 3)\n", " | >>> fl = x.flat\n", " | >>> type(fl)\n", " | \n", " | >>> for item in fl:\n", " | ... print(item)\n", " | ...\n", " | 0\n", " | 1\n", " | 2\n", " | 3\n", " | 4\n", " | 5\n", " | \n", " | >>> fl[2:4]\n", " | array([2, 3])\n", " | \n", " | Methods defined here:\n", " | \n", " | __array__(...)\n", " | __array__(type=None) Get array from iterator\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>> x = np.arange(6).reshape(2, 3)\n", " | >>> x\n", " | array([[0, 1, 2],\n", " | [3, 4, 5]])\n", " | >>> fl = x.flat\n", " | >>> fl.copy()\n", " | array([0, 1, 2, 3, 4, 5])\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | base\n", " | A reference to the array that is iterated over.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(5)\n", " | >>> fl = x.flat\n", " | >>> fl.base is x\n", " | True\n", " | \n", " | coords\n", " | An N-dimensional tuple of current coordinates.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(6).reshape(2, 3)\n", " | >>> fl = x.flat\n", " | >>> fl.coords\n", " | (0, 0)\n", " | >>> next(fl)\n", " | 0\n", " | >>> fl.coords\n", " | (0, 1)\n", " | \n", " | index\n", " | Current flat index into the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(6).reshape(2, 3)\n", " | >>> fl = x.flat\n", " | >>> fl.index\n", " | 0\n", " | >>> next(fl)\n", " | 0\n", " | >>> fl.index\n", " | 1\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes defined here:\n", " | \n", " | __hash__ = None\n", " \n", " class flexible(generic)\n", " | Abstract base class of all scalar types without predefined length.\n", " | The actual size of these types depends on the specific `np.dtype`\n", " | instantiation.\n", " | \n", " | Method resolution order:\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " class float128(floating)\n", " | Extended-precision floating-point number type, compatible with C\n", " | ``long double`` but not necessarily with IEEE 754 quadruple-precision.\n", " | Character code: ``'g'``.\n", " | Canonical name: ``np.longdouble``.\n", " | Alias: ``np.longfloat``.\n", " | Alias *on this platform*: ``np.float128``: 128-bit extended-precision floating-point number type.\n", " | \n", " | Method resolution order:\n", " | float128\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.longdouble(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.longdouble(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.longdouble(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class float16(floating)\n", " | Half-precision floating-point number type.\n", " | Character code: ``'e'``.\n", " | Canonical name: ``np.half``.\n", " | Alias *on this platform*: ``np.float16``: 16-bit-precision floating-point number type: sign bit, 5 bits exponent, 10 bits mantissa.\n", " | \n", " | Method resolution order:\n", " | float16\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.half(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.half(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.half(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class float32(floating)\n", " | Single-precision floating-point number type, compatible with C ``float``.\n", " | Character code: ``'f'``.\n", " | Canonical name: ``np.single``.\n", " | Alias *on this platform*: ``np.float32``: 32-bit-precision floating-point number type: sign bit, 8 bits exponent, 23 bits mantissa.\n", " | \n", " | Method resolution order:\n", " | float32\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.single(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.single(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.single(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class float64(floating, builtins.float)\n", " | float64(x=0, /)\n", " | \n", " | Double-precision floating-point number type, compatible with Python `float`\n", " | and C ``double``.\n", " | Character code: ``'d'``.\n", " | Canonical name: ``np.double``.\n", " | Alias: ``np.float_``.\n", " | Alias *on this platform*: ``np.float64``: 64-bit precision floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa.\n", " | \n", " | Method resolution order:\n", " | float64\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.float\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.double(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.double(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.double(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.float:\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getnewargs__(self, /)\n", " | \n", " | __trunc__(self, /)\n", " | Return the Integral closest to x between 0 and x.\n", " | \n", " | hex(self, /)\n", " | Return a hexadecimal representation of a floating-point number.\n", " | \n", " | >>> (-0.1).hex()\n", " | '-0x1.999999999999ap-4'\n", " | >>> 3.14159.hex()\n", " | '0x1.921f9f01b866ep+1'\n", " | \n", " | is_integer(self, /)\n", " | Return True if the float is an integer.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Class methods inherited from builtins.float:\n", " | \n", " | __getformat__(typestr, /) from builtins.type\n", " | You probably don't want to use this function.\n", " | \n", " | typestr\n", " | Must be 'double' or 'float'.\n", " | \n", " | It exists mainly to be used in Python's test suite.\n", " | \n", " | This function returns whichever of 'unknown', 'IEEE, big-endian' or 'IEEE,\n", " | little-endian' best describes the format of floating point numbers used by the\n", " | C type named by typestr.\n", " | \n", " | __set_format__(typestr, fmt, /) from builtins.type\n", " | You probably don't want to use this function.\n", " | \n", " | typestr\n", " | Must be 'double' or 'float'.\n", " | fmt\n", " | Must be one of 'unknown', 'IEEE, big-endian' or 'IEEE, little-endian',\n", " | and in addition can only be one of the latter two if it appears to\n", " | match the underlying C reality.\n", " | \n", " | It exists mainly to be used in Python's test suite.\n", " | \n", " | Override the automatic determination of C-level floating point type.\n", " | This affects how floats are converted to and from binary strings.\n", " | \n", " | fromhex(string, /) from builtins.type\n", " | Create a floating-point number from a hexadecimal string.\n", " | \n", " | >>> float.fromhex('0x1.ffffp10')\n", " | 2047.984375\n", " | >>> float.fromhex('-0x1p-1074')\n", " | -5e-324\n", " \n", " float_ = class float64(floating, builtins.float)\n", " | float_(x=0, /)\n", " | \n", " | Double-precision floating-point number type, compatible with Python `float`\n", " | and C ``double``.\n", " | Character code: ``'d'``.\n", " | Canonical name: ``np.double``.\n", " | Alias: ``np.float_``.\n", " | Alias *on this platform*: ``np.float64``: 64-bit precision floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa.\n", " | \n", " | Method resolution order:\n", " | float64\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.float\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.double(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.double(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.double(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from builtins.float:\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getnewargs__(self, /)\n", " | \n", " | __trunc__(self, /)\n", " | Return the Integral closest to x between 0 and x.\n", " | \n", " | hex(self, /)\n", " | Return a hexadecimal representation of a floating-point number.\n", " | \n", " | >>> (-0.1).hex()\n", " | '-0x1.999999999999ap-4'\n", " | >>> 3.14159.hex()\n", " | '0x1.921f9f01b866ep+1'\n", " | \n", " | is_integer(self, /)\n", " | Return True if the float is an integer.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Class methods inherited from builtins.float:\n", " | \n", " | __getformat__(typestr, /) from builtins.type\n", " | You probably don't want to use this function.\n", " | \n", " | typestr\n", " | Must be 'double' or 'float'.\n", " | \n", " | It exists mainly to be used in Python's test suite.\n", " | \n", " | This function returns whichever of 'unknown', 'IEEE, big-endian' or 'IEEE,\n", " | little-endian' best describes the format of floating point numbers used by the\n", " | C type named by typestr.\n", " | \n", " | __set_format__(typestr, fmt, /) from builtins.type\n", " | You probably don't want to use this function.\n", " | \n", " | typestr\n", " | Must be 'double' or 'float'.\n", " | fmt\n", " | Must be one of 'unknown', 'IEEE, big-endian' or 'IEEE, little-endian',\n", " | and in addition can only be one of the latter two if it appears to\n", " | match the underlying C reality.\n", " | \n", " | It exists mainly to be used in Python's test suite.\n", " | \n", " | Override the automatic determination of C-level floating point type.\n", " | This affects how floats are converted to and from binary strings.\n", " | \n", " | fromhex(string, /) from builtins.type\n", " | Create a floating-point number from a hexadecimal string.\n", " | \n", " | >>> float.fromhex('0x1.ffffp10')\n", " | 2047.984375\n", " | >>> float.fromhex('-0x1p-1074')\n", " | -5e-324\n", " \n", " class floating(inexact)\n", " | Abstract base class of all floating-point scalar types.\n", " | \n", " | Method resolution order:\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " class format_parser(builtins.object)\n", " | format_parser(formats, names, titles, aligned=False, byteorder=None)\n", " | \n", " | Class to convert formats, names, titles description to a dtype.\n", " | \n", " | After constructing the format_parser object, the dtype attribute is\n", " | the converted data-type:\n", " | ``dtype = format_parser(formats, names, titles).dtype``\n", " | \n", " | Attributes\n", " | ----------\n", " | dtype : dtype\n", " | The converted data-type.\n", " | \n", " | Parameters\n", " | ----------\n", " | formats : str or list of str\n", " | The format description, either specified as a string with\n", " | comma-separated format descriptions in the form ``'f8, i4, a5'``, or\n", " | a list of format description strings in the form\n", " | ``['f8', 'i4', 'a5']``.\n", " | names : str or list/tuple of str\n", " | The field names, either specified as a comma-separated string in the\n", " | form ``'col1, col2, col3'``, or as a list or tuple of strings in the\n", " | form ``['col1', 'col2', 'col3']``.\n", " | An empty list can be used, in that case default field names\n", " | ('f0', 'f1', ...) are used.\n", " | titles : sequence\n", " | Sequence of title strings. An empty list can be used to leave titles\n", " | out.\n", " | aligned : bool, optional\n", " | If True, align the fields by padding as the C-compiler would.\n", " | Default is False.\n", " | byteorder : str, optional\n", " | If specified, all the fields will be changed to the\n", " | provided byte-order. Otherwise, the default byte-order is\n", " | used. For all available string specifiers, see `dtype.newbyteorder`.\n", " | \n", " | See Also\n", " | --------\n", " | dtype, typename, sctype2char\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.format_parser(['>> np.format_parser(['f8', 'i4', 'a5'], ['col1', 'col2', 'col3'],\n", " | ... []).dtype\n", " | dtype([('col1', '>> np.format_parser(['=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes defined here:\n", " | \n", " | __hash__ = None\n", " \n", " half = class float16(floating)\n", " | Half-precision floating-point number type.\n", " | Character code: ``'e'``.\n", " | Canonical name: ``np.half``.\n", " | Alias *on this platform*: ``np.float16``: 16-bit-precision floating-point number type: sign bit, 5 bits exponent, 10 bits mantissa.\n", " | \n", " | Method resolution order:\n", " | float16\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.half(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.half(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.half(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class iinfo(builtins.object)\n", " | iinfo(int_type)\n", " | \n", " | iinfo(type)\n", " | \n", " | Machine limits for integer types.\n", " | \n", " | Attributes\n", " | ----------\n", " | bits : int\n", " | The number of bits occupied by the type.\n", " | min : int\n", " | The smallest integer expressible by the type.\n", " | max : int\n", " | The largest integer expressible by the type.\n", " | \n", " | Parameters\n", " | ----------\n", " | int_type : integer type, dtype, or instance\n", " | The kind of integer data type to get information about.\n", " | \n", " | See Also\n", " | --------\n", " | finfo : The equivalent for floating point data types.\n", " | \n", " | Examples\n", " | --------\n", " | With types:\n", " | \n", " | >>> ii16 = np.iinfo(np.int16)\n", " | >>> ii16.min\n", " | -32768\n", " | >>> ii16.max\n", " | 32767\n", " | >>> ii32 = np.iinfo(np.int32)\n", " | >>> ii32.min\n", " | -2147483648\n", " | >>> ii32.max\n", " | 2147483647\n", " | \n", " | With instances:\n", " | \n", " | >>> ii32 = np.iinfo(np.int32(10))\n", " | >>> ii32.min\n", " | -2147483648\n", " | >>> ii32.max\n", " | 2147483647\n", " | \n", " | Methods defined here:\n", " | \n", " | __init__(self, int_type)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | __repr__(self)\n", " | Return repr(self).\n", " | \n", " | __str__(self)\n", " | String representation.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Readonly properties defined here:\n", " | \n", " | max\n", " | Maximum value of given dtype.\n", " | \n", " | min\n", " | Minimum value of given dtype.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class inexact(number)\n", " | Abstract base class of all numeric scalar types with a (potentially)\n", " | inexact representation of the values in its range, such as\n", " | floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " int0 = class int64(signedinteger)\n", " | Signed integer type, compatible with Python `int` anc C ``long``.\n", " | Character code: ``'l'``.\n", " | Canonical name: ``np.int_``.\n", " | Alias *on this platform*: ``np.int64``: 64-bit signed integer (-9223372036854775808 to 9223372036854775807).\n", " | Alias *on this platform*: ``np.intp``: Signed integer large enough to fit pointer, compatible with C ``intptr_t``.\n", " | \n", " | Method resolution order:\n", " | int64\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class int16(signedinteger)\n", " | Signed integer type, compatible with C ``short``.\n", " | Character code: ``'h'``.\n", " | Canonical name: ``np.short``.\n", " | Alias *on this platform*: ``np.int16``: 16-bit signed integer (-32768 to 32767).\n", " | \n", " | Method resolution order:\n", " | int16\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class int32(signedinteger)\n", " | Signed integer type, compatible with C ``int``.\n", " | Character code: ``'i'``.\n", " | Canonical name: ``np.intc``.\n", " | Alias *on this platform*: ``np.int32``: 32-bit signed integer (-2147483648 to 2147483647).\n", " | \n", " | Method resolution order:\n", " | int32\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class int64(signedinteger)\n", " | Signed integer type, compatible with Python `int` anc C ``long``.\n", " | Character code: ``'l'``.\n", " | Canonical name: ``np.int_``.\n", " | Alias *on this platform*: ``np.int64``: 64-bit signed integer (-9223372036854775808 to 9223372036854775807).\n", " | Alias *on this platform*: ``np.intp``: Signed integer large enough to fit pointer, compatible with C ``intptr_t``.\n", " | \n", " | Method resolution order:\n", " | int64\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class int8(signedinteger)\n", " | Signed integer type, compatible with C ``char``.\n", " | Character code: ``'b'``.\n", " | Canonical name: ``np.byte``.\n", " | Alias *on this platform*: ``np.int8``: 8-bit signed integer (-128 to 127).\n", " | \n", " | Method resolution order:\n", " | int8\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " int_ = class int64(signedinteger)\n", " | Signed integer type, compatible with Python `int` anc C ``long``.\n", " | Character code: ``'l'``.\n", " | Canonical name: ``np.int_``.\n", " | Alias *on this platform*: ``np.int64``: 64-bit signed integer (-9223372036854775808 to 9223372036854775807).\n", " | Alias *on this platform*: ``np.intp``: Signed integer large enough to fit pointer, compatible with C ``intptr_t``.\n", " | \n", " | Method resolution order:\n", " | int64\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " intc = class int32(signedinteger)\n", " | Signed integer type, compatible with C ``int``.\n", " | Character code: ``'i'``.\n", " | Canonical name: ``np.intc``.\n", " | Alias *on this platform*: ``np.int32``: 32-bit signed integer (-2147483648 to 2147483647).\n", " | \n", " | Method resolution order:\n", " | int32\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class integer(number)\n", " | Abstract base class of all integer scalar types.\n", " | \n", " | Method resolution order:\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " intp = class int64(signedinteger)\n", " | Signed integer type, compatible with Python `int` anc C ``long``.\n", " | Character code: ``'l'``.\n", " | Canonical name: ``np.int_``.\n", " | Alias *on this platform*: ``np.int64``: 64-bit signed integer (-9223372036854775808 to 9223372036854775807).\n", " | Alias *on this platform*: ``np.intp``: Signed integer large enough to fit pointer, compatible with C ``intptr_t``.\n", " | \n", " | Method resolution order:\n", " | int64\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " longcomplex = class complex256(complexfloating)\n", " | Complex number type composed of two extended-precision floating-point\n", " | numbers.\n", " | Character code: ``'G'``.\n", " | Canonical name: ``np.clongdouble``.\n", " | Alias: ``np.clongfloat``.\n", " | Alias: ``np.longcomplex``.\n", " | Alias *on this platform*: ``np.complex256``: Complex number type composed of 2 128-bit extended-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex256\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " longdouble = class float128(floating)\n", " | Extended-precision floating-point number type, compatible with C\n", " | ``long double`` but not necessarily with IEEE 754 quadruple-precision.\n", " | Character code: ``'g'``.\n", " | Canonical name: ``np.longdouble``.\n", " | Alias: ``np.longfloat``.\n", " | Alias *on this platform*: ``np.float128``: 128-bit extended-precision floating-point number type.\n", " | \n", " | Method resolution order:\n", " | float128\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.longdouble(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.longdouble(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.longdouble(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " longfloat = class float128(floating)\n", " | Extended-precision floating-point number type, compatible with C\n", " | ``long double`` but not necessarily with IEEE 754 quadruple-precision.\n", " | Character code: ``'g'``.\n", " | Canonical name: ``np.longdouble``.\n", " | Alias: ``np.longfloat``.\n", " | Alias *on this platform*: ``np.float128``: 128-bit extended-precision floating-point number type.\n", " | \n", " | Method resolution order:\n", " | float128\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.longdouble(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.longdouble(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.longdouble(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class longlong(signedinteger)\n", " | Signed integer type, compatible with C ``long long``.\n", " | Character code: ``'q'``.\n", " | \n", " | Method resolution order:\n", " | longlong\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class matrix(ndarray)\n", " | matrix(data, dtype=None, copy=True)\n", " | \n", " | matrix(data, dtype=None, copy=True)\n", " | \n", " | .. note:: It is no longer recommended to use this class, even for linear\n", " | algebra. Instead use regular arrays. The class may be removed\n", " | in the future.\n", " | \n", " | Returns a matrix from an array-like object, or from a string of data.\n", " | A matrix is a specialized 2-D array that retains its 2-D nature\n", " | through operations. It has certain special operators, such as ``*``\n", " | (matrix multiplication) and ``**`` (matrix power).\n", " | \n", " | Parameters\n", " | ----------\n", " | data : array_like or string\n", " | If `data` is a string, it is interpreted as a matrix with commas\n", " | or spaces separating columns, and semicolons separating rows.\n", " | dtype : data-type\n", " | Data-type of the output matrix.\n", " | copy : bool\n", " | If `data` is already an `ndarray`, then this flag determines\n", " | whether the data is copied (the default), or whether a view is\n", " | constructed.\n", " | \n", " | See Also\n", " | --------\n", " | array\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.matrix('1 2; 3 4')\n", " | >>> a\n", " | matrix([[1, 2],\n", " | [3, 4]])\n", " | \n", " | >>> np.matrix([[1, 2], [3, 4]])\n", " | matrix([[1, 2],\n", " | [3, 4]])\n", " | \n", " | Method resolution order:\n", " | matrix\n", " | ndarray\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __array_finalize__(self, obj)\n", " | None.\n", " | \n", " | __getitem__(self, index)\n", " | Return self[key].\n", " | \n", " | __imul__(self, other)\n", " | Return self*=value.\n", " | \n", " | __ipow__(self, other)\n", " | Return self**=value.\n", " | \n", " | __mul__(self, other)\n", " | Return self*value.\n", " | \n", " | __pow__(self, other)\n", " | Return pow(self, value, mod).\n", " | \n", " | __rmul__(self, other)\n", " | Return value*self.\n", " | \n", " | __rpow__(self, other)\n", " | Return pow(value, self, mod).\n", " | \n", " | all(self, axis=None, out=None)\n", " | Test whether all matrix elements along a given axis evaluate to True.\n", " | \n", " | Parameters\n", " | ----------\n", " | See `numpy.all` for complete descriptions\n", " | \n", " | See Also\n", " | --------\n", " | numpy.all\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.all`, but it returns a `matrix` object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> y = x[0]; y\n", " | matrix([[0, 1, 2, 3]])\n", " | >>> (x == y)\n", " | matrix([[ True, True, True, True],\n", " | [False, False, False, False],\n", " | [False, False, False, False]])\n", " | >>> (x == y).all()\n", " | False\n", " | >>> (x == y).all(0)\n", " | matrix([[False, False, False, False]])\n", " | >>> (x == y).all(1)\n", " | matrix([[ True],\n", " | [False],\n", " | [False]])\n", " | \n", " | any(self, axis=None, out=None)\n", " | Test whether any array element along a given axis evaluates to True.\n", " | \n", " | Refer to `numpy.any` for full documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | axis : int, optional\n", " | Axis along which logical OR is performed\n", " | out : ndarray, optional\n", " | Output to existing array instead of creating new one, must have\n", " | same shape as expected output\n", " | \n", " | Returns\n", " | -------\n", " | any : bool, ndarray\n", " | Returns a single bool if `axis` is ``None``; otherwise,\n", " | returns `ndarray`\n", " | \n", " | argmax(self, axis=None, out=None)\n", " | Indexes of the maximum values along an axis.\n", " | \n", " | Return the indexes of the first occurrences of the maximum values\n", " | along the specified axis. If axis is None, the index is for the\n", " | flattened matrix.\n", " | \n", " | Parameters\n", " | ----------\n", " | See `numpy.argmax` for complete descriptions\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmax\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.argmax`, but returns a `matrix` object\n", " | where `ndarray.argmax` would return an `ndarray`.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.argmax()\n", " | 11\n", " | >>> x.argmax(0)\n", " | matrix([[2, 2, 2, 2]])\n", " | >>> x.argmax(1)\n", " | matrix([[3],\n", " | [3],\n", " | [3]])\n", " | \n", " | argmin(self, axis=None, out=None)\n", " | Indexes of the minimum values along an axis.\n", " | \n", " | Return the indexes of the first occurrences of the minimum values\n", " | along the specified axis. If axis is None, the index is for the\n", " | flattened matrix.\n", " | \n", " | Parameters\n", " | ----------\n", " | See `numpy.argmin` for complete descriptions.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmin\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.argmin`, but returns a `matrix` object\n", " | where `ndarray.argmin` would return an `ndarray`.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = -np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, -1, -2, -3],\n", " | [ -4, -5, -6, -7],\n", " | [ -8, -9, -10, -11]])\n", " | >>> x.argmin()\n", " | 11\n", " | >>> x.argmin(0)\n", " | matrix([[2, 2, 2, 2]])\n", " | >>> x.argmin(1)\n", " | matrix([[3],\n", " | [3],\n", " | [3]])\n", " | \n", " | flatten(self, order='C')\n", " | Return a flattened copy of the matrix.\n", " | \n", " | All `N` elements of the matrix are placed into a single row.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | 'C' means to flatten in row-major (C-style) order. 'F' means to\n", " | flatten in column-major (Fortran-style) order. 'A' means to\n", " | flatten in column-major order if `m` is Fortran *contiguous* in\n", " | memory, row-major order otherwise. 'K' means to flatten `m` in\n", " | the order the elements occur in memory. The default is 'C'.\n", " | \n", " | Returns\n", " | -------\n", " | y : matrix\n", " | A copy of the matrix, flattened to a `(1, N)` matrix where `N`\n", " | is the number of elements in the original matrix.\n", " | \n", " | See Also\n", " | --------\n", " | ravel : Return a flattened array.\n", " | flat : A 1-D flat iterator over the matrix.\n", " | \n", " | Examples\n", " | --------\n", " | >>> m = np.matrix([[1,2], [3,4]])\n", " | >>> m.flatten()\n", " | matrix([[1, 2, 3, 4]])\n", " | >>> m.flatten('F')\n", " | matrix([[1, 3, 2, 4]])\n", " | \n", " | getA = A(self)\n", " | Return `self` as an `ndarray` object.\n", " | \n", " | Equivalent to ``np.asarray(self)``.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : ndarray\n", " | `self` as an `ndarray`\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.getA()\n", " | array([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | \n", " | getA1 = A1(self)\n", " | Return `self` as a flattened `ndarray`.\n", " | \n", " | Equivalent to ``np.asarray(x).ravel()``\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : ndarray\n", " | `self`, 1-D, as an `ndarray`\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.getA1()\n", " | array([ 0, 1, 2, ..., 9, 10, 11])\n", " | \n", " | getH = H(self)\n", " | Returns the (complex) conjugate transpose of `self`.\n", " | \n", " | Equivalent to ``np.transpose(self)`` if `self` is real-valued.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : matrix object\n", " | complex conjugate transpose of `self`\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4)))\n", " | >>> z = x - 1j*x; z\n", " | matrix([[ 0. +0.j, 1. -1.j, 2. -2.j, 3. -3.j],\n", " | [ 4. -4.j, 5. -5.j, 6. -6.j, 7. -7.j],\n", " | [ 8. -8.j, 9. -9.j, 10.-10.j, 11.-11.j]])\n", " | >>> z.getH()\n", " | matrix([[ 0. -0.j, 4. +4.j, 8. +8.j],\n", " | [ 1. +1.j, 5. +5.j, 9. +9.j],\n", " | [ 2. +2.j, 6. +6.j, 10.+10.j],\n", " | [ 3. +3.j, 7. +7.j, 11.+11.j]])\n", " | \n", " | getI = I(self)\n", " | Returns the (multiplicative) inverse of invertible `self`.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : matrix object\n", " | If `self` is non-singular, `ret` is such that ``ret * self`` ==\n", " | ``self * ret`` == ``np.matrix(np.eye(self[0,:].size))`` all return\n", " | ``True``.\n", " | \n", " | Raises\n", " | ------\n", " | numpy.linalg.LinAlgError: Singular matrix\n", " | If `self` is singular.\n", " | \n", " | See Also\n", " | --------\n", " | linalg.inv\n", " | \n", " | Examples\n", " | --------\n", " | >>> m = np.matrix('[1, 2; 3, 4]'); m\n", " | matrix([[1, 2],\n", " | [3, 4]])\n", " | >>> m.getI()\n", " | matrix([[-2. , 1. ],\n", " | [ 1.5, -0.5]])\n", " | >>> m.getI() * m\n", " | matrix([[ 1., 0.], # may vary\n", " | [ 0., 1.]])\n", " | \n", " | getT = T(self)\n", " | Returns the transpose of the matrix.\n", " | \n", " | Does *not* conjugate! For the complex conjugate transpose, use ``.H``.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : matrix object\n", " | The (non-conjugated) transpose of the matrix.\n", " | \n", " | See Also\n", " | --------\n", " | transpose, getH\n", " | \n", " | Examples\n", " | --------\n", " | >>> m = np.matrix('[1, 2; 3, 4]')\n", " | >>> m\n", " | matrix([[1, 2],\n", " | [3, 4]])\n", " | >>> m.getT()\n", " | matrix([[1, 3],\n", " | [2, 4]])\n", " | \n", " | max(self, axis=None, out=None)\n", " | Return the maximum value along an axis.\n", " | \n", " | Parameters\n", " | ----------\n", " | See `amax` for complete descriptions\n", " | \n", " | See Also\n", " | --------\n", " | amax, ndarray.max\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.max`, but returns a `matrix` object\n", " | where `ndarray.max` would return an ndarray.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.max()\n", " | 11\n", " | >>> x.max(0)\n", " | matrix([[ 8, 9, 10, 11]])\n", " | >>> x.max(1)\n", " | matrix([[ 3],\n", " | [ 7],\n", " | [11]])\n", " | \n", " | mean(self, axis=None, dtype=None, out=None)\n", " | Returns the average of the matrix elements along the given axis.\n", " | \n", " | Refer to `numpy.mean` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.mean\n", " | \n", " | Notes\n", " | -----\n", " | Same as `ndarray.mean` except that, where that returns an `ndarray`,\n", " | this returns a `matrix` object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3, 4)))\n", " | >>> x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.mean()\n", " | 5.5\n", " | >>> x.mean(0)\n", " | matrix([[4., 5., 6., 7.]])\n", " | >>> x.mean(1)\n", " | matrix([[ 1.5],\n", " | [ 5.5],\n", " | [ 9.5]])\n", " | \n", " | min(self, axis=None, out=None)\n", " | Return the minimum value along an axis.\n", " | \n", " | Parameters\n", " | ----------\n", " | See `amin` for complete descriptions.\n", " | \n", " | See Also\n", " | --------\n", " | amin, ndarray.min\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.min`, but returns a `matrix` object\n", " | where `ndarray.min` would return an ndarray.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = -np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, -1, -2, -3],\n", " | [ -4, -5, -6, -7],\n", " | [ -8, -9, -10, -11]])\n", " | >>> x.min()\n", " | -11\n", " | >>> x.min(0)\n", " | matrix([[ -8, -9, -10, -11]])\n", " | >>> x.min(1)\n", " | matrix([[ -3],\n", " | [ -7],\n", " | [-11]])\n", " | \n", " | prod(self, axis=None, dtype=None, out=None)\n", " | Return the product of the array elements over the given axis.\n", " | \n", " | Refer to `prod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | prod, ndarray.prod\n", " | \n", " | Notes\n", " | -----\n", " | Same as `ndarray.prod`, except, where that returns an `ndarray`, this\n", " | returns a `matrix` object instead.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.prod()\n", " | 0\n", " | >>> x.prod(0)\n", " | matrix([[ 0, 45, 120, 231]])\n", " | >>> x.prod(1)\n", " | matrix([[ 0],\n", " | [ 840],\n", " | [7920]])\n", " | \n", " | ptp(self, axis=None, out=None)\n", " | Peak-to-peak (maximum - minimum) value along the given axis.\n", " | \n", " | Refer to `numpy.ptp` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ptp\n", " | \n", " | Notes\n", " | -----\n", " | Same as `ndarray.ptp`, except, where that would return an `ndarray` object,\n", " | this returns a `matrix` object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.ptp()\n", " | 11\n", " | >>> x.ptp(0)\n", " | matrix([[8, 8, 8, 8]])\n", " | >>> x.ptp(1)\n", " | matrix([[3],\n", " | [3],\n", " | [3]])\n", " | \n", " | ravel(self, order='C')\n", " | Return a flattened matrix.\n", " | \n", " | Refer to `numpy.ravel` for more documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | The elements of `m` are read using this index order. 'C' means to\n", " | index the elements in C-like order, with the last axis index\n", " | changing fastest, back to the first axis index changing slowest.\n", " | 'F' means to index the elements in Fortran-like index order, with\n", " | the first index changing fastest, and the last index changing\n", " | slowest. Note that the 'C' and 'F' options take no account of the\n", " | memory layout of the underlying array, and only refer to the order\n", " | of axis indexing. 'A' means to read the elements in Fortran-like\n", " | index order if `m` is Fortran *contiguous* in memory, C-like order\n", " | otherwise. 'K' means to read the elements in the order they occur\n", " | in memory, except for reversing the data when strides are negative.\n", " | By default, 'C' index order is used.\n", " | \n", " | Returns\n", " | -------\n", " | ret : matrix\n", " | Return the matrix flattened to shape `(1, N)` where `N`\n", " | is the number of elements in the original matrix.\n", " | A copy is made only if necessary.\n", " | \n", " | See Also\n", " | --------\n", " | matrix.flatten : returns a similar output matrix but always a copy\n", " | matrix.flat : a flat iterator on the array.\n", " | numpy.ravel : related function which returns an ndarray\n", " | \n", " | squeeze(self, axis=None)\n", " | Return a possibly reshaped matrix.\n", " | \n", " | Refer to `numpy.squeeze` for more documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | axis : None or int or tuple of ints, optional\n", " | Selects a subset of the single-dimensional entries in the shape.\n", " | If an axis is selected with shape entry greater than one,\n", " | an error is raised.\n", " | \n", " | Returns\n", " | -------\n", " | squeezed : matrix\n", " | The matrix, but as a (1, N) matrix if it had shape (N, 1).\n", " | \n", " | See Also\n", " | --------\n", " | numpy.squeeze : related function\n", " | \n", " | Notes\n", " | -----\n", " | If `m` has a single column then that column is returned\n", " | as the single row of a matrix. Otherwise `m` is returned.\n", " | The returned matrix is always either `m` itself or a view into `m`.\n", " | Supplying an axis keyword argument will not affect the returned matrix\n", " | but it may cause an error to be raised.\n", " | \n", " | Examples\n", " | --------\n", " | >>> c = np.matrix([[1], [2]])\n", " | >>> c\n", " | matrix([[1],\n", " | [2]])\n", " | >>> c.squeeze()\n", " | matrix([[1, 2]])\n", " | >>> r = c.T\n", " | >>> r\n", " | matrix([[1, 2]])\n", " | >>> r.squeeze()\n", " | matrix([[1, 2]])\n", " | >>> m = np.matrix([[1, 2], [3, 4]])\n", " | >>> m.squeeze()\n", " | matrix([[1, 2],\n", " | [3, 4]])\n", " | \n", " | std(self, axis=None, dtype=None, out=None, ddof=0)\n", " | Return the standard deviation of the array elements along the given axis.\n", " | \n", " | Refer to `numpy.std` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.std\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.std`, except that where an `ndarray` would\n", " | be returned, a `matrix` object is returned instead.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3, 4)))\n", " | >>> x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.std()\n", " | 3.4520525295346629 # may vary\n", " | >>> x.std(0)\n", " | matrix([[ 3.26598632, 3.26598632, 3.26598632, 3.26598632]]) # may vary\n", " | >>> x.std(1)\n", " | matrix([[ 1.11803399],\n", " | [ 1.11803399],\n", " | [ 1.11803399]])\n", " | \n", " | sum(self, axis=None, dtype=None, out=None)\n", " | Returns the sum of the matrix elements, along the given axis.\n", " | \n", " | Refer to `numpy.sum` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.sum\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.sum`, except that where an `ndarray` would\n", " | be returned, a `matrix` object is returned instead.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix([[1, 2], [4, 3]])\n", " | >>> x.sum()\n", " | 10\n", " | >>> x.sum(axis=1)\n", " | matrix([[3],\n", " | [7]])\n", " | >>> x.sum(axis=1, dtype='float')\n", " | matrix([[3.],\n", " | [7.]])\n", " | >>> out = np.zeros((2, 1), dtype='float')\n", " | >>> x.sum(axis=1, dtype='float', out=np.asmatrix(out))\n", " | matrix([[3.],\n", " | [7.]])\n", " | \n", " | tolist(self)\n", " | Return the matrix as a (possibly nested) list.\n", " | \n", " | See `ndarray.tolist` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | ndarray.tolist\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.tolist()\n", " | [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]\n", " | \n", " | var(self, axis=None, dtype=None, out=None, ddof=0)\n", " | Returns the variance of the matrix elements, along the given axis.\n", " | \n", " | Refer to `numpy.var` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.var\n", " | \n", " | Notes\n", " | -----\n", " | This is the same as `ndarray.var`, except that where an `ndarray` would\n", " | be returned, a `matrix` object is returned instead.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3, 4)))\n", " | >>> x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.var()\n", " | 11.916666666666666\n", " | >>> x.var(0)\n", " | matrix([[ 10.66666667, 10.66666667, 10.66666667, 10.66666667]]) # may vary\n", " | >>> x.var(1)\n", " | matrix([[1.25],\n", " | [1.25],\n", " | [1.25]])\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(subtype, data, dtype=None, copy=True)\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Readonly properties defined here:\n", " | \n", " | A\n", " | Return `self` as an `ndarray` object.\n", " | \n", " | Equivalent to ``np.asarray(self)``.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : ndarray\n", " | `self` as an `ndarray`\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.getA()\n", " | array([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | \n", " | A1\n", " | Return `self` as a flattened `ndarray`.\n", " | \n", " | Equivalent to ``np.asarray(x).ravel()``\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : ndarray\n", " | `self`, 1-D, as an `ndarray`\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4))); x\n", " | matrix([[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]])\n", " | >>> x.getA1()\n", " | array([ 0, 1, 2, ..., 9, 10, 11])\n", " | \n", " | H\n", " | Returns the (complex) conjugate transpose of `self`.\n", " | \n", " | Equivalent to ``np.transpose(self)`` if `self` is real-valued.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : matrix object\n", " | complex conjugate transpose of `self`\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.matrix(np.arange(12).reshape((3,4)))\n", " | >>> z = x - 1j*x; z\n", " | matrix([[ 0. +0.j, 1. -1.j, 2. -2.j, 3. -3.j],\n", " | [ 4. -4.j, 5. -5.j, 6. -6.j, 7. -7.j],\n", " | [ 8. -8.j, 9. -9.j, 10.-10.j, 11.-11.j]])\n", " | >>> z.getH()\n", " | matrix([[ 0. -0.j, 4. +4.j, 8. +8.j],\n", " | [ 1. +1.j, 5. +5.j, 9. +9.j],\n", " | [ 2. +2.j, 6. +6.j, 10.+10.j],\n", " | [ 3. +3.j, 7. +7.j, 11.+11.j]])\n", " | \n", " | I\n", " | Returns the (multiplicative) inverse of invertible `self`.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : matrix object\n", " | If `self` is non-singular, `ret` is such that ``ret * self`` ==\n", " | ``self * ret`` == ``np.matrix(np.eye(self[0,:].size))`` all return\n", " | ``True``.\n", " | \n", " | Raises\n", " | ------\n", " | numpy.linalg.LinAlgError: Singular matrix\n", " | If `self` is singular.\n", " | \n", " | See Also\n", " | --------\n", " | linalg.inv\n", " | \n", " | Examples\n", " | --------\n", " | >>> m = np.matrix('[1, 2; 3, 4]'); m\n", " | matrix([[1, 2],\n", " | [3, 4]])\n", " | >>> m.getI()\n", " | matrix([[-2. , 1. ],\n", " | [ 1.5, -0.5]])\n", " | >>> m.getI() * m\n", " | matrix([[ 1., 0.], # may vary\n", " | [ 0., 1.]])\n", " | \n", " | T\n", " | Returns the transpose of the matrix.\n", " | \n", " | Does *not* conjugate! For the complex conjugate transpose, use ``.H``.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | ret : matrix object\n", " | The (non-conjugated) transpose of the matrix.\n", " | \n", " | See Also\n", " | --------\n", " | transpose, getH\n", " | \n", " | Examples\n", " | --------\n", " | >>> m = np.matrix('[1, 2; 3, 4]')\n", " | >>> m\n", " | matrix([[1, 2],\n", " | [3, 4]])\n", " | >>> m.getT()\n", " | matrix([[1, 3],\n", " | [2, 4]])\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes defined here:\n", " | \n", " | __array_priority__ = 10.0\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from ndarray:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | a.__array__([dtype], /) -> reference if type unchanged, copy otherwise.\n", " | \n", " | Returns either a new reference to self if dtype is not given or a new array\n", " | of provided data type if dtype is different from the current dtype of the\n", " | array.\n", " | \n", " | __array_function__(...)\n", " | \n", " | __array_prepare__(...)\n", " | a.__array_prepare__(obj) -> Object of same type as ndarray object obj.\n", " | \n", " | __array_ufunc__(...)\n", " | \n", " | __array_wrap__(...)\n", " | a.__array_wrap__(obj) -> Object of same type as ndarray object a.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __contains__(self, key, /)\n", " | Return key in self.\n", " | \n", " | __copy__(...)\n", " | a.__copy__()\n", " | \n", " | Used if :func:`copy.copy` is called on an array. Returns a copy of the array.\n", " | \n", " | Equivalent to ``a.copy(order='K')``.\n", " | \n", " | __deepcopy__(...)\n", " | a.__deepcopy__(memo, /) -> Deep copy of array.\n", " | \n", " | Used if :func:`copy.deepcopy` is called on an array.\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | Default object formatter.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __iadd__(self, value, /)\n", " | Return self+=value.\n", " | \n", " | __iand__(self, value, /)\n", " | Return self&=value.\n", " | \n", " | __ifloordiv__(self, value, /)\n", " | Return self//=value.\n", " | \n", " | __ilshift__(self, value, /)\n", " | Return self<<=value.\n", " | \n", " | __imatmul__(self, value, /)\n", " | Return self@=value.\n", " | \n", " | __imod__(self, value, /)\n", " | Return self%=value.\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __ior__(self, value, /)\n", " | Return self|=value.\n", " | \n", " | __irshift__(self, value, /)\n", " | Return self>>=value.\n", " | \n", " | __isub__(self, value, /)\n", " | Return self-=value.\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __itruediv__(self, value, /)\n", " | Return self/=value.\n", " | \n", " | __ixor__(self, value, /)\n", " | Return self^=value.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setitem__(self, key, value, /)\n", " | Set self[key] to value.\n", " | \n", " | __setstate__(...)\n", " | a.__setstate__(state, /)\n", " | \n", " | For unpickling.\n", " | \n", " | The `state` argument must be a sequence that contains the following\n", " | elements:\n", " | \n", " | Parameters\n", " | ----------\n", " | version : int\n", " | optional pickle version. If omitted defaults to 0.\n", " | shape : tuple\n", " | dtype : data-type\n", " | isFortran : bool\n", " | rawdata : string or list\n", " | a binary string with the data (or a list if 'a' is an object array)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | argpartition(...)\n", " | a.argpartition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Returns the indices that would partition this array.\n", " | \n", " | Refer to `numpy.argpartition` for full documentation.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argpartition : equivalent function\n", " | \n", " | argsort(...)\n", " | a.argsort(axis=-1, kind=None, order=None)\n", " | \n", " | Returns the indices that would sort this array.\n", " | \n", " | Refer to `numpy.argsort` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argsort : equivalent function\n", " | \n", " | astype(...)\n", " | a.astype(dtype, order='K', casting='unsafe', subok=True, copy=True)\n", " | \n", " | Copy of the array, cast to a specified type.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | Typecode or data-type to which the array is cast.\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout order of the result.\n", " | 'C' means C order, 'F' means Fortran order, 'A'\n", " | means 'F' order if all the arrays are Fortran contiguous,\n", " | 'C' order otherwise, and 'K' means as close to the\n", " | order the array elements appear in memory as possible.\n", " | Default is 'K'.\n", " | casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n", " | Controls what kind of data casting may occur. Defaults to 'unsafe'\n", " | for backwards compatibility.\n", " | \n", " | * 'no' means the data types should not be cast at all.\n", " | * 'equiv' means only byte-order changes are allowed.\n", " | * 'safe' means only casts which can preserve values are allowed.\n", " | * 'same_kind' means only safe casts or casts within a kind,\n", " | like float64 to float32, are allowed.\n", " | * 'unsafe' means any data conversions may be done.\n", " | subok : bool, optional\n", " | If True, then sub-classes will be passed-through (default), otherwise\n", " | the returned array will be forced to be a base-class array.\n", " | copy : bool, optional\n", " | By default, astype always returns a newly allocated array. If this\n", " | is set to false, and the `dtype`, `order`, and `subok`\n", " | requirements are satisfied, the input array is returned instead\n", " | of a copy.\n", " | \n", " | Returns\n", " | -------\n", " | arr_t : ndarray\n", " | Unless `copy` is False and the other conditions for returning the input\n", " | array are satisfied (see description for `copy` input parameter), `arr_t`\n", " | is a new array of the same shape as the input array, with dtype, order\n", " | given by `dtype`, `order`.\n", " | \n", " | Notes\n", " | -----\n", " | .. versionchanged:: 1.17.0\n", " | Casting between a simple data type and a structured one is possible only\n", " | for \"unsafe\" casting. Casting to multiple fields is allowed, but\n", " | casting from multiple fields is not.\n", " | \n", " | .. versionchanged:: 1.9.0\n", " | Casting from numeric to string types in 'safe' casting mode requires\n", " | that the string dtype length is long enough to store the max\n", " | integer/float value converted.\n", " | \n", " | Raises\n", " | ------\n", " | ComplexWarning\n", " | When casting from complex to float or int. To avoid this,\n", " | one should use ``a.real.astype(t)``.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 2.5])\n", " | >>> x\n", " | array([1. , 2. , 2.5])\n", " | \n", " | >>> x.astype(int)\n", " | array([1, 2, 2])\n", " | \n", " | byteswap(...)\n", " | a.byteswap(inplace=False)\n", " | \n", " | Swap the bytes of the array elements\n", " | \n", " | Toggle between low-endian and big-endian data representation by\n", " | returning a byteswapped array, optionally swapped in-place.\n", " | Arrays of byte-strings are not swapped. The real and imaginary\n", " | parts of a complex number are swapped individually.\n", " | \n", " | Parameters\n", " | ----------\n", " | inplace : bool, optional\n", " | If ``True``, swap bytes in-place, default is ``False``.\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | The byteswapped array. If `inplace` is ``True``, this is\n", " | a view to self.\n", " | \n", " | Examples\n", " | --------\n", " | >>> A = np.array([1, 256, 8755], dtype=np.int16)\n", " | >>> list(map(hex, A))\n", " | ['0x1', '0x100', '0x2233']\n", " | >>> A.byteswap(inplace=True)\n", " | array([ 256, 1, 13090], dtype=int16)\n", " | >>> list(map(hex, A))\n", " | ['0x100', '0x1', '0x3322']\n", " | \n", " | Arrays of byte-strings are not swapped\n", " | \n", " | >>> A = np.array([b'ceg', b'fac'])\n", " | >>> A.byteswap()\n", " | array([b'ceg', b'fac'], dtype='|S3')\n", " | \n", " | ``A.newbyteorder().byteswap()`` produces an array with the same values\n", " | but different representation in memory\n", " | \n", " | >>> A = np.array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,\n", " | 0, 0], dtype=uint8)\n", " | >>> A.newbyteorder().byteswap(inplace=True)\n", " | array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0,\n", " | 0, 3], dtype=uint8)\n", " | \n", " | choose(...)\n", " | a.choose(choices, out=None, mode='raise')\n", " | \n", " | Use an index array to construct a new array from a set of choices.\n", " | \n", " | Refer to `numpy.choose` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.choose : equivalent function\n", " | \n", " | clip(...)\n", " | a.clip(min=None, max=None, out=None, **kwargs)\n", " | \n", " | Return an array whose values are limited to ``[min, max]``.\n", " | One of max or min must be given.\n", " | \n", " | Refer to `numpy.clip` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.clip : equivalent function\n", " | \n", " | compress(...)\n", " | a.compress(condition, axis=None, out=None)\n", " | \n", " | Return selected slices of this array along given axis.\n", " | \n", " | Refer to `numpy.compress` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.compress : equivalent function\n", " | \n", " | conj(...)\n", " | a.conj()\n", " | \n", " | Complex-conjugate all elements.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | conjugate(...)\n", " | a.conjugate()\n", " | \n", " | Return the complex conjugate, element-wise.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | copy(...)\n", " | a.copy(order='C')\n", " | \n", " | Return a copy of the array.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout of the copy. 'C' means C-order,\n", " | 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,\n", " | 'C' otherwise. 'K' means match the layout of `a` as closely\n", " | as possible. (Note that this function and :func:`numpy.copy` are very\n", " | similar, but have different default values for their order=\n", " | arguments.)\n", " | \n", " | See also\n", " | --------\n", " | numpy.copy\n", " | numpy.copyto\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([[1,2,3],[4,5,6]], order='F')\n", " | \n", " | >>> y = x.copy()\n", " | \n", " | >>> x.fill(0)\n", " | \n", " | >>> x\n", " | array([[0, 0, 0],\n", " | [0, 0, 0]])\n", " | \n", " | >>> y\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | \n", " | >>> y.flags['C_CONTIGUOUS']\n", " | True\n", " | \n", " | cumprod(...)\n", " | a.cumprod(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative product of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumprod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumprod : equivalent function\n", " | \n", " | cumsum(...)\n", " | a.cumsum(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative sum of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumsum` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumsum : equivalent function\n", " | \n", " | diagonal(...)\n", " | a.diagonal(offset=0, axis1=0, axis2=1)\n", " | \n", " | Return specified diagonals. In NumPy 1.9 the returned array is a\n", " | read-only view instead of a copy as in previous NumPy versions. In\n", " | a future version the read-only restriction will be removed.\n", " | \n", " | Refer to :func:`numpy.diagonal` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.diagonal : equivalent function\n", " | \n", " | dot(...)\n", " | a.dot(b, out=None)\n", " | \n", " | Dot product of two arrays.\n", " | \n", " | Refer to `numpy.dot` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dot : equivalent function\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.eye(2)\n", " | >>> b = np.ones((2, 2)) * 2\n", " | >>> a.dot(b)\n", " | array([[2., 2.],\n", " | [2., 2.]])\n", " | \n", " | This array method can be conveniently chained:\n", " | \n", " | >>> a.dot(b).dot(b)\n", " | array([[8., 8.],\n", " | [8., 8.]])\n", " | \n", " | dump(...)\n", " | a.dump(file)\n", " | \n", " | Dump a pickle of the array to the specified file.\n", " | The array can be read back with pickle.load or numpy.load.\n", " | \n", " | Parameters\n", " | ----------\n", " | file : str or Path\n", " | A string naming the dump file.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | dumps(...)\n", " | a.dumps()\n", " | \n", " | Returns the pickle of the array as a string.\n", " | pickle.loads or numpy.loads will convert the string back to an array.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | fill(...)\n", " | a.fill(value)\n", " | \n", " | Fill the array with a scalar value.\n", " | \n", " | Parameters\n", " | ----------\n", " | value : scalar\n", " | All elements of `a` will be assigned this value.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([1, 2])\n", " | >>> a.fill(0)\n", " | >>> a\n", " | array([0, 0])\n", " | >>> a = np.empty(2)\n", " | >>> a.fill(1)\n", " | >>> a\n", " | array([1., 1.])\n", " | \n", " | getfield(...)\n", " | a.getfield(dtype, offset=0)\n", " | \n", " | Returns a field of the given array as a certain type.\n", " | \n", " | A field is a view of the array data with a given data-type. The values in\n", " | the view are determined by the given type and the offset into the current\n", " | array in bytes. The offset needs to be such that the view dtype fits in the\n", " | array dtype; for example an array of dtype complex128 has 16-byte elements.\n", " | If taking a view with a 32-bit integer (4 bytes), the offset needs to be\n", " | between 0 and 12 bytes.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | The data type of the view. The dtype size of the view can not be larger\n", " | than that of the array itself.\n", " | offset : int\n", " | Number of bytes to skip before beginning the element view.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.diag([1.+1.j]*2)\n", " | >>> x[1, 1] = 2 + 4.j\n", " | >>> x\n", " | array([[1.+1.j, 0.+0.j],\n", " | [0.+0.j, 2.+4.j]])\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0.],\n", " | [0., 2.]])\n", " | \n", " | By choosing an offset of 8 bytes we can select the complex part of the\n", " | array for our view:\n", " | \n", " | >>> x.getfield(np.float64, offset=8)\n", " | array([[1., 0.],\n", " | [0., 4.]])\n", " | \n", " | item(...)\n", " | a.item(*args)\n", " | \n", " | Copy an element of an array to a standard Python scalar and return it.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments (variable number and type)\n", " | \n", " | * none: in this case, the method only works for arrays\n", " | with one element (`a.size == 1`), which element is\n", " | copied into a standard Python scalar object and returned.\n", " | \n", " | * int_type: this argument is interpreted as a flat index into\n", " | the array, specifying which element to copy and return.\n", " | \n", " | * tuple of int_types: functions as does a single int_type argument,\n", " | except that the argument is interpreted as an nd-index into the\n", " | array.\n", " | \n", " | Returns\n", " | -------\n", " | z : Standard Python scalar object\n", " | A copy of the specified element of the array as a suitable\n", " | Python scalar\n", " | \n", " | Notes\n", " | -----\n", " | When the data type of `a` is longdouble or clongdouble, item() returns\n", " | a scalar array object because there is no available Python scalar that\n", " | would not lose information. Void arrays return a buffer object for item(),\n", " | unless fields are defined, in which case a tuple is returned.\n", " | \n", " | `item` is very similar to a[args], except, instead of an array scalar,\n", " | a standard Python scalar is returned. This can be useful for speeding up\n", " | access to elements of the array and doing arithmetic on elements of the\n", " | array using Python's optimized math.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.item(3)\n", " | 1\n", " | >>> x.item(7)\n", " | 0\n", " | >>> x.item((0, 1))\n", " | 2\n", " | >>> x.item((2, 2))\n", " | 1\n", " | \n", " | itemset(...)\n", " | a.itemset(*args)\n", " | \n", " | Insert scalar into an array (scalar is cast to array's dtype, if possible)\n", " | \n", " | There must be at least 1 argument, and define the last argument\n", " | as *item*. Then, ``a.itemset(*args)`` is equivalent to but faster\n", " | than ``a[args] = item``. The item should be a scalar value and `args`\n", " | must select a single item in the array `a`.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments\n", " | If one argument: a scalar, only used in case `a` is of size 1.\n", " | If two arguments: the last argument is the value to be set\n", " | and must be a scalar, the first argument specifies a single array\n", " | element location. It is either an int or a tuple.\n", " | \n", " | Notes\n", " | -----\n", " | Compared to indexing syntax, `itemset` provides some speed increase\n", " | for placing a scalar into a particular location in an `ndarray`,\n", " | if you must do this. However, generally this is discouraged:\n", " | among other problems, it complicates the appearance of the code.\n", " | Also, when using `itemset` (and `item`) inside a loop, be sure\n", " | to assign the methods to a local variable to avoid the attribute\n", " | look-up at each loop iteration.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.itemset(4, 0)\n", " | >>> x.itemset((2, 2), 9)\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 0, 6],\n", " | [1, 0, 9]])\n", " | \n", " | newbyteorder(...)\n", " | arr.newbyteorder(new_order='S')\n", " | \n", " | Return the array with the same data viewed with a different byte order.\n", " | \n", " | Equivalent to::\n", " | \n", " | arr.view(arr.dtype.newbytorder(new_order))\n", " | \n", " | Changes are also made in all fields and sub-arrays of the array data\n", " | type.\n", " | \n", " | \n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : string, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | below. `new_order` codes can be any of:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_arr : array\n", " | New array object with the dtype reflecting given change to the\n", " | byte order.\n", " | \n", " | nonzero(...)\n", " | a.nonzero()\n", " | \n", " | Return the indices of the elements that are non-zero.\n", " | \n", " | Refer to `numpy.nonzero` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.nonzero : equivalent function\n", " | \n", " | partition(...)\n", " | a.partition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Rearranges the elements in the array in such a way that the value of the\n", " | element in kth position is in the position it would be in a sorted array.\n", " | All elements smaller than the kth element are moved before this element and\n", " | all equal or greater are moved behind it. The ordering of the elements in\n", " | the two partitions is undefined.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | Parameters\n", " | ----------\n", " | kth : int or sequence of ints\n", " | Element index to partition by. The kth element value will be in its\n", " | final sorted position and all smaller elements will be moved before it\n", " | and all equal or greater elements behind it.\n", " | The order of all elements in the partitions is undefined.\n", " | If provided with a sequence of kth it will partition all elements\n", " | indexed by kth of them into their sorted position at once.\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'introselect'}, optional\n", " | Selection algorithm. Default is 'introselect'.\n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need to be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.partition : Return a parititioned copy of an array.\n", " | argpartition : Indirect partition.\n", " | sort : Full sort.\n", " | \n", " | Notes\n", " | -----\n", " | See ``np.partition`` for notes on the different algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([3, 4, 2, 1])\n", " | >>> a.partition(3)\n", " | >>> a\n", " | array([2, 1, 3, 4])\n", " | \n", " | >>> a.partition((1, 3))\n", " | >>> a\n", " | array([1, 2, 3, 4])\n", " | \n", " | put(...)\n", " | a.put(indices, values, mode='raise')\n", " | \n", " | Set ``a.flat[n] = values[n]`` for all `n` in indices.\n", " | \n", " | Refer to `numpy.put` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.put : equivalent function\n", " | \n", " | repeat(...)\n", " | a.repeat(repeats, axis=None)\n", " | \n", " | Repeat elements of an array.\n", " | \n", " | Refer to `numpy.repeat` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.repeat : equivalent function\n", " | \n", " | reshape(...)\n", " | a.reshape(shape, order='C')\n", " | \n", " | Returns an array containing the same data with a new shape.\n", " | \n", " | Refer to `numpy.reshape` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : equivalent function\n", " | \n", " | Notes\n", " | -----\n", " | Unlike the free function `numpy.reshape`, this method on `ndarray` allows\n", " | the elements of the shape parameter to be passed in as separate arguments.\n", " | For example, ``a.reshape(10, 11)`` is equivalent to\n", " | ``a.reshape((10, 11))``.\n", " | \n", " | resize(...)\n", " | a.resize(new_shape, refcheck=True)\n", " | \n", " | Change shape and size of array in-place.\n", " | \n", " | Parameters\n", " | ----------\n", " | new_shape : tuple of ints, or `n` ints\n", " | Shape of resized array.\n", " | refcheck : bool, optional\n", " | If False, reference count will not be checked. Default is True.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | Raises\n", " | ------\n", " | ValueError\n", " | If `a` does not own its own data or references or views to it exist,\n", " | and the data memory must be changed.\n", " | PyPy only: will always raise if the data memory must be changed, since\n", " | there is no reliable way to determine if references or views to it\n", " | exist.\n", " | \n", " | SystemError\n", " | If the `order` keyword argument is specified. This behaviour is a\n", " | bug in NumPy.\n", " | \n", " | See Also\n", " | --------\n", " | resize : Return a new array with the specified shape.\n", " | \n", " | Notes\n", " | -----\n", " | This reallocates space for the data area if necessary.\n", " | \n", " | Only contiguous arrays (data elements consecutive in memory) can be\n", " | resized.\n", " | \n", " | The purpose of the reference count check is to make sure you\n", " | do not use this array as a buffer for another Python object and then\n", " | reallocate the memory. However, reference counts can increase in\n", " | other ways so if you are sure that you have not shared the memory\n", " | for this array with another Python object, then you may safely set\n", " | `refcheck` to False.\n", " | \n", " | Examples\n", " | --------\n", " | Shrinking an array: array is flattened (in the order that the data are\n", " | stored in memory), resized, and reshaped:\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='C')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [1]])\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='F')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [2]])\n", " | \n", " | Enlarging an array: as above, but missing entries are filled with zeros:\n", " | \n", " | >>> b = np.array([[0, 1], [2, 3]])\n", " | >>> b.resize(2, 3) # new_shape parameter doesn't have to be a tuple\n", " | >>> b\n", " | array([[0, 1, 2],\n", " | [3, 0, 0]])\n", " | \n", " | Referencing an array prevents resizing...\n", " | \n", " | >>> c = a\n", " | >>> a.resize((1, 1))\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: cannot resize an array that references or is referenced ...\n", " | \n", " | Unless `refcheck` is False:\n", " | \n", " | >>> a.resize((1, 1), refcheck=False)\n", " | >>> a\n", " | array([[0]])\n", " | >>> c\n", " | array([[0]])\n", " | \n", " | round(...)\n", " | a.round(decimals=0, out=None)\n", " | \n", " | Return `a` with each element rounded to the given number of decimals.\n", " | \n", " | Refer to `numpy.around` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.around : equivalent function\n", " | \n", " | searchsorted(...)\n", " | a.searchsorted(v, side='left', sorter=None)\n", " | \n", " | Find indices where elements of v should be inserted in a to maintain order.\n", " | \n", " | For full documentation, see `numpy.searchsorted`\n", " | \n", " | See Also\n", " | --------\n", " | numpy.searchsorted : equivalent function\n", " | \n", " | setfield(...)\n", " | a.setfield(val, dtype, offset=0)\n", " | \n", " | Put a value into a specified place in a field defined by a data-type.\n", " | \n", " | Place `val` into `a`'s field defined by `dtype` and beginning `offset`\n", " | bytes into the field.\n", " | \n", " | Parameters\n", " | ----------\n", " | val : object\n", " | Value to be placed in field.\n", " | dtype : dtype object\n", " | Data-type of the field in which to place `val`.\n", " | offset : int, optional\n", " | The number of bytes into the field at which to place `val`.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | See Also\n", " | --------\n", " | getfield\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.eye(3)\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | >>> x.setfield(3, np.int32)\n", " | >>> x.getfield(np.int32)\n", " | array([[3, 3, 3],\n", " | [3, 3, 3],\n", " | [3, 3, 3]], dtype=int32)\n", " | >>> x\n", " | array([[1.0e+000, 1.5e-323, 1.5e-323],\n", " | [1.5e-323, 1.0e+000, 1.5e-323],\n", " | [1.5e-323, 1.5e-323, 1.0e+000]])\n", " | >>> x.setfield(np.eye(3), np.int32)\n", " | >>> x\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | \n", " | setflags(...)\n", " | a.setflags(write=None, align=None, uic=None)\n", " | \n", " | Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY),\n", " | respectively.\n", " | \n", " | These Boolean-valued flags affect how numpy interprets the memory\n", " | area used by `a` (see Notes below). The ALIGNED flag can only\n", " | be set to True if the data is actually aligned according to the type.\n", " | The WRITEBACKIFCOPY and (deprecated) UPDATEIFCOPY flags can never be set\n", " | to True. The flag WRITEABLE can only be set to True if the array owns its\n", " | own memory, or the ultimate owner of the memory exposes a writeable buffer\n", " | interface, or is a string. (The exception for string is made so that\n", " | unpickling can be done without copying memory.)\n", " | \n", " | Parameters\n", " | ----------\n", " | write : bool, optional\n", " | Describes whether or not `a` can be written to.\n", " | align : bool, optional\n", " | Describes whether or not `a` is aligned properly for its type.\n", " | uic : bool, optional\n", " | Describes whether or not `a` is a copy of another \"base\" array.\n", " | \n", " | Notes\n", " | -----\n", " | Array flags provide information about how the memory area used\n", " | for the array is to be interpreted. There are 7 Boolean flags\n", " | in use, only four of which can be changed by the user:\n", " | WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED.\n", " | \n", " | WRITEABLE (W) the data area can be written to;\n", " | \n", " | ALIGNED (A) the data and strides are aligned appropriately for the hardware\n", " | (as determined by the compiler);\n", " | \n", " | UPDATEIFCOPY (U) (deprecated), replaced by WRITEBACKIFCOPY;\n", " | \n", " | WRITEBACKIFCOPY (X) this array is a copy of some other array (referenced\n", " | by .base). When the C-API function PyArray_ResolveWritebackIfCopy is\n", " | called, the base array will be updated with the contents of this array.\n", " | \n", " | All flags can be accessed using the single (upper case) letter as well\n", " | as the full name.\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.array([[3, 1, 7],\n", " | ... [2, 0, 0],\n", " | ... [8, 5, 9]])\n", " | >>> y\n", " | array([[3, 1, 7],\n", " | [2, 0, 0],\n", " | [8, 5, 9]])\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : True\n", " | ALIGNED : True\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(write=0, align=0)\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : False\n", " | ALIGNED : False\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(uic=1)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: cannot set WRITEBACKIFCOPY flag to True\n", " | \n", " | sort(...)\n", " | a.sort(axis=-1, kind=None, order=None)\n", " | \n", " | Sort an array in-place. Refer to `numpy.sort` for full documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional\n", " | Sorting algorithm. The default is 'quicksort'. Note that both 'stable'\n", " | and 'mergesort' use timsort under the covers and, in general, the\n", " | actual implementation will vary with datatype. The 'mergesort' option\n", " | is retained for backwards compatibility.\n", " | \n", " | .. versionchanged:: 1.15.0.\n", " | The 'stable' option was added.\n", " | \n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.sort : Return a sorted copy of an array.\n", " | numpy.argsort : Indirect sort.\n", " | numpy.lexsort : Indirect stable sort on multiple keys.\n", " | numpy.searchsorted : Find elements in sorted array.\n", " | numpy.partition: Partial sort.\n", " | \n", " | Notes\n", " | -----\n", " | See `numpy.sort` for notes on the different sorting algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,4], [3,1]])\n", " | >>> a.sort(axis=1)\n", " | >>> a\n", " | array([[1, 4],\n", " | [1, 3]])\n", " | >>> a.sort(axis=0)\n", " | >>> a\n", " | array([[1, 3],\n", " | [1, 4]])\n", " | \n", " | Use the `order` keyword to specify a field to use when sorting a\n", " | structured array:\n", " | \n", " | >>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])\n", " | >>> a.sort(order='y')\n", " | >>> a\n", " | array([(b'c', 1), (b'a', 2)],\n", " | dtype=[('x', 'S1'), ('y', '>> x = np.array([[0, 1], [2, 3]], dtype='>> x.tobytes()\n", " | b'\\x00\\x00\\x01\\x00\\x02\\x00\\x03\\x00'\n", " | >>> x.tobytes('C') == x.tobytes()\n", " | True\n", " | >>> x.tobytes('F')\n", " | b'\\x00\\x00\\x02\\x00\\x01\\x00\\x03\\x00'\n", " | \n", " | tofile(...)\n", " | a.tofile(fid, sep=\"\", format=\"%s\")\n", " | \n", " | Write array to a file as text or binary (default).\n", " | \n", " | Data is always written in 'C' order, independent of the order of `a`.\n", " | The data produced by this method can be recovered using the function\n", " | fromfile().\n", " | \n", " | Parameters\n", " | ----------\n", " | fid : file or str or Path\n", " | An open file object, or a string containing a filename.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | sep : str\n", " | Separator between array items for text output.\n", " | If \"\" (empty), a binary file is written, equivalent to\n", " | ``file.write(a.tobytes())``.\n", " | format : str\n", " | Format string for text file output.\n", " | Each entry in the array is formatted to text by first converting\n", " | it to the closest Python type, and then using \"format\" % item.\n", " | \n", " | Notes\n", " | -----\n", " | This is a convenience function for quick storage of array data.\n", " | Information on endianness and precision is lost, so this method is not a\n", " | good choice for files intended to archive data or transport data between\n", " | machines with different endianness. Some of these problems can be overcome\n", " | by outputting the data as text files, at the expense of speed and file\n", " | size.\n", " | \n", " | When fid is a file object, array contents are directly written to the\n", " | file, bypassing the file object's ``write`` method. As a result, tofile\n", " | cannot be used with files objects supporting compression (e.g., GzipFile)\n", " | or file-like objects that do not support ``fileno()`` (e.g., BytesIO).\n", " | \n", " | tostring(...)\n", " | a.tostring(order='C')\n", " | \n", " | A compatibility alias for `tobytes`, with exactly the same behavior.\n", " | \n", " | Despite its name, it returns `bytes` not `str`\\ s.\n", " | \n", " | .. deprecated:: 1.19.0\n", " | \n", " | trace(...)\n", " | a.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)\n", " | \n", " | Return the sum along diagonals of the array.\n", " | \n", " | Refer to `numpy.trace` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.trace : equivalent function\n", " | \n", " | transpose(...)\n", " | a.transpose(*axes)\n", " | \n", " | Returns a view of the array with axes transposed.\n", " | \n", " | For a 1-D array this has no effect, as a transposed vector is simply the\n", " | same vector. To convert a 1-D array into a 2D column vector, an additional\n", " | dimension must be added. `np.atleast2d(a).T` achieves this, as does\n", " | `a[:, np.newaxis]`.\n", " | For a 2-D array, this is a standard matrix transpose.\n", " | For an n-D array, if axes are given, their order indicates how the\n", " | axes are permuted (see Examples). If axes are not provided and\n", " | ``a.shape = (i[0], i[1], ... i[n-2], i[n-1])``, then\n", " | ``a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])``.\n", " | \n", " | Parameters\n", " | ----------\n", " | axes : None, tuple of ints, or `n` ints\n", " | \n", " | * None or no argument: reverses the order of the axes.\n", " | \n", " | * tuple of ints: `i` in the `j`-th place in the tuple means `a`'s\n", " | `i`-th axis becomes `a.transpose()`'s `j`-th axis.\n", " | \n", " | * `n` ints: same as an n-tuple of the same ints (this form is\n", " | intended simply as a \"convenience\" alternative to the tuple form)\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | View of `a`, with axes suitably permuted.\n", " | \n", " | See Also\n", " | --------\n", " | ndarray.T : Array property returning the array transposed.\n", " | ndarray.reshape : Give a new shape to an array without changing its data.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> a\n", " | array([[1, 2],\n", " | [3, 4]])\n", " | >>> a.transpose()\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose((1, 0))\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose(1, 0)\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | \n", " | view(...)\n", " | a.view([dtype][, type])\n", " | \n", " | New view of array with the same data.\n", " | \n", " | .. note::\n", " | Passing None for ``dtype`` is different from omitting the parameter,\n", " | since the former invokes ``dtype(None)`` which is an alias for\n", " | ``dtype('float_')``.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : data-type or ndarray sub-class, optional\n", " | Data-type descriptor of the returned view, e.g., float32 or int16.\n", " | Omitting it results in the view having the same data-type as `a`.\n", " | This argument can also be specified as an ndarray sub-class, which\n", " | then specifies the type of the returned object (this is equivalent to\n", " | setting the ``type`` parameter).\n", " | type : Python type, optional\n", " | Type of the returned view, e.g., ndarray or matrix. Again, omission\n", " | of the parameter results in type preservation.\n", " | \n", " | Notes\n", " | -----\n", " | ``a.view()`` is used two different ways:\n", " | \n", " | ``a.view(some_dtype)`` or ``a.view(dtype=some_dtype)`` constructs a view\n", " | of the array's memory with a different data-type. This can cause a\n", " | reinterpretation of the bytes of memory.\n", " | \n", " | ``a.view(ndarray_subclass)`` or ``a.view(type=ndarray_subclass)`` just\n", " | returns an instance of `ndarray_subclass` that looks at the same array\n", " | (same shape, dtype, etc.) This does not cause a reinterpretation of the\n", " | memory.\n", " | \n", " | For ``a.view(some_dtype)``, if ``some_dtype`` has a different number of\n", " | bytes per entry than the previous dtype (for example, converting a\n", " | regular array to a structured array), then the behavior of the view\n", " | cannot be predicted just from the superficial appearance of ``a`` (shown\n", " | by ``print(a)``). It also depends on exactly how ``a`` is stored in\n", " | memory. Therefore if ``a`` is C-ordered versus fortran-ordered, versus\n", " | defined as a slice or transpose, etc., the view may give different\n", " | results.\n", " | \n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | \n", " | Viewing array data using a different type and dtype:\n", " | \n", " | >>> y = x.view(dtype=np.int16, type=np.matrix)\n", " | >>> y\n", " | matrix([[513]], dtype=int16)\n", " | >>> print(type(y))\n", " | \n", " | \n", " | Creating a view on a structured array so it can be used in calculations\n", " | \n", " | >>> x = np.array([(1, 2),(3,4)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | >>> xv = x.view(dtype=np.int8).reshape(-1,2)\n", " | >>> xv\n", " | array([[1, 2],\n", " | [3, 4]], dtype=int8)\n", " | >>> xv.mean(0)\n", " | array([2., 3.])\n", " | \n", " | Making changes to the view changes the underlying array\n", " | \n", " | >>> xv[0,1] = 20\n", " | >>> x\n", " | array([(1, 20), (3, 4)], dtype=[('a', 'i1'), ('b', 'i1')])\n", " | \n", " | Using a view to convert an array to a recarray:\n", " | \n", " | >>> z = x.view(np.recarray)\n", " | >>> z.a\n", " | array([1, 3], dtype=int8)\n", " | \n", " | Views share data:\n", " | \n", " | >>> x[0] = (9, 10)\n", " | >>> z[0]\n", " | (9, 10)\n", " | \n", " | Views that change the dtype size (bytes per entry) should normally be\n", " | avoided on arrays defined by slices, transposes, fortran-ordering, etc.:\n", " | \n", " | >>> x = np.array([[1,2,3],[4,5,6]], dtype=np.int16)\n", " | >>> y = x[:, 0:2]\n", " | >>> y\n", " | array([[1, 2],\n", " | [4, 5]], dtype=int16)\n", " | >>> y.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: To change to a dtype of a different size, the array must be C-contiguous\n", " | >>> z = y.copy()\n", " | >>> z.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | array([[(1, 2)],\n", " | [(4, 5)]], dtype=[('width', '>> x = np.array([1,2,3,4])\n", " | >>> x.base is None\n", " | True\n", " | \n", " | Slicing creates a view, whose memory is shared with x:\n", " | \n", " | >>> y = x[2:]\n", " | >>> y.base is x\n", " | True\n", " | \n", " | ctypes\n", " | An object to simplify the interaction of the array with the ctypes\n", " | module.\n", " | \n", " | This attribute creates an object that makes it easier to use arrays\n", " | when calling shared libraries with the ctypes module. The returned\n", " | object has, among others, data, shape, and strides attributes (see\n", " | Notes below) which themselves return ctypes objects that can be used\n", " | as arguments to a shared library.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | c : Python object\n", " | Possessing attributes data, shape, strides, etc.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ctypeslib\n", " | \n", " | Notes\n", " | -----\n", " | Below are the public attributes of this object which were documented\n", " | in \"Guide to NumPy\" (we have omitted undocumented public attributes,\n", " | as well as documented private attributes):\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.data\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.shape\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.strides\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.data_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.shape_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.strides_as\n", " | :noindex:\n", " | \n", " | If the ctypes module is not available, then the ctypes attribute\n", " | of array objects still returns something useful, but ctypes objects\n", " | are not returned and errors may be raised instead. In particular,\n", " | the object will still have the ``as_parameter`` attribute which will\n", " | return an integer equal to the data attribute.\n", " | \n", " | Examples\n", " | --------\n", " | >>> import ctypes\n", " | >>> x = np.array([[0, 1], [2, 3]], dtype=np.int32)\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]], dtype=int32)\n", " | >>> x.ctypes.data\n", " | 31962608 # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32))\n", " | <__main__.LP_c_uint object at 0x7ff2fc1fc200> # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32)).contents\n", " | c_uint(0)\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint64)).contents\n", " | c_ulong(4294967296)\n", " | >>> x.ctypes.shape\n", " | # may vary\n", " | >>> x.ctypes.strides\n", " | # may vary\n", " | \n", " | data\n", " | Python buffer object pointing to the start of the array's data.\n", " | \n", " | dtype\n", " | Data-type of the array's elements.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | d : numpy dtype object\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dtype\n", " | \n", " | Examples\n", " | --------\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]])\n", " | >>> x.dtype\n", " | dtype('int32')\n", " | >>> type(x.dtype)\n", " | \n", " | \n", " | flags\n", " | Information about the memory layout of the array.\n", " | \n", " | Attributes\n", " | ----------\n", " | C_CONTIGUOUS (C)\n", " | The data is in a single, C-style contiguous segment.\n", " | F_CONTIGUOUS (F)\n", " | The data is in a single, Fortran-style contiguous segment.\n", " | OWNDATA (O)\n", " | The array owns the memory it uses or borrows it from another object.\n", " | WRITEABLE (W)\n", " | The data area can be written to. Setting this to False locks\n", " | the data, making it read-only. A view (slice, etc.) inherits WRITEABLE\n", " | from its base array at creation time, but a view of a writeable\n", " | array may be subsequently locked while the base array remains writeable.\n", " | (The opposite is not true, in that a view of a locked array may not\n", " | be made writeable. However, currently, locking a base object does not\n", " | lock any views that already reference it, so under that circumstance it\n", " | is possible to alter the contents of a locked array via a previously\n", " | created writeable view onto it.) Attempting to change a non-writeable\n", " | array raises a RuntimeError exception.\n", " | ALIGNED (A)\n", " | The data and all elements are aligned appropriately for the hardware.\n", " | WRITEBACKIFCOPY (X)\n", " | This array is a copy of some other array. The C-API function\n", " | PyArray_ResolveWritebackIfCopy must be called before deallocating\n", " | to the base array will be updated with the contents of this array.\n", " | UPDATEIFCOPY (U)\n", " | (Deprecated, use WRITEBACKIFCOPY) This array is a copy of some other array.\n", " | When this array is\n", " | deallocated, the base array will be updated with the contents of\n", " | this array.\n", " | FNC\n", " | F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | FORC\n", " | F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).\n", " | BEHAVED (B)\n", " | ALIGNED and WRITEABLE.\n", " | CARRAY (CA)\n", " | BEHAVED and C_CONTIGUOUS.\n", " | FARRAY (FA)\n", " | BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | \n", " | Notes\n", " | -----\n", " | The `flags` object can be accessed dictionary-like (as in ``a.flags['WRITEABLE']``),\n", " | or by using lowercased attribute names (as in ``a.flags.writeable``). Short flag\n", " | names are only supported in dictionary access.\n", " | \n", " | Only the WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be\n", " | changed by the user, via direct assignment to the attribute or dictionary\n", " | entry, or by calling `ndarray.setflags`.\n", " | \n", " | The array flags cannot be set arbitrarily:\n", " | \n", " | - UPDATEIFCOPY can only be set ``False``.\n", " | - WRITEBACKIFCOPY can only be set ``False``.\n", " | - ALIGNED can only be set ``True`` if the data is truly aligned.\n", " | - WRITEABLE can only be set ``True`` if the array owns its own memory\n", " | or the ultimate owner of the memory exposes a writeable buffer\n", " | interface or is a string.\n", " | \n", " | Arrays can be both C-style and Fortran-style contiguous simultaneously.\n", " | This is clear for 1-dimensional arrays, but can also be true for higher\n", " | dimensional arrays.\n", " | \n", " | Even for contiguous arrays a stride for a given dimension\n", " | ``arr.strides[dim]`` may be *arbitrary* if ``arr.shape[dim] == 1``\n", " | or the array has no elements.\n", " | It does *not* generally hold that ``self.strides[-1] == self.itemsize``\n", " | for C-style contiguous arrays or ``self.strides[0] == self.itemsize`` for\n", " | Fortran-style contiguous arrays is true.\n", " | \n", " | flat\n", " | A 1-D iterator over the array.\n", " | \n", " | This is a `numpy.flatiter` instance, which acts similarly to, but is not\n", " | a subclass of, Python's built-in iterator object.\n", " | \n", " | See Also\n", " | --------\n", " | flatten : Return a copy of the array collapsed into one dimension.\n", " | \n", " | flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(1, 7).reshape(2, 3)\n", " | >>> x\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | >>> x.flat[3]\n", " | 4\n", " | >>> x.T\n", " | array([[1, 4],\n", " | [2, 5],\n", " | [3, 6]])\n", " | >>> x.T.flat[3]\n", " | 5\n", " | >>> type(x.flat)\n", " | \n", " | \n", " | An assignment example:\n", " | \n", " | >>> x.flat = 3; x\n", " | array([[3, 3, 3],\n", " | [3, 3, 3]])\n", " | >>> x.flat[[1,4]] = 1; x\n", " | array([[3, 1, 3],\n", " | [3, 1, 3]])\n", " | \n", " | imag\n", " | The imaginary part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.imag\n", " | array([ 0. , 0.70710678])\n", " | >>> x.imag.dtype\n", " | dtype('float64')\n", " | \n", " | itemsize\n", " | Length of one array element in bytes.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1,2,3], dtype=np.float64)\n", " | >>> x.itemsize\n", " | 8\n", " | >>> x = np.array([1,2,3], dtype=np.complex128)\n", " | >>> x.itemsize\n", " | 16\n", " | \n", " | nbytes\n", " | Total bytes consumed by the elements of the array.\n", " | \n", " | Notes\n", " | -----\n", " | Does not include memory consumed by non-element attributes of the\n", " | array object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3,5,2), dtype=np.complex128)\n", " | >>> x.nbytes\n", " | 480\n", " | >>> np.prod(x.shape) * x.itemsize\n", " | 480\n", " | \n", " | ndim\n", " | Number of array dimensions.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> x.ndim\n", " | 1\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.ndim\n", " | 3\n", " | \n", " | real\n", " | The real part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.real\n", " | array([ 1. , 0.70710678])\n", " | >>> x.real.dtype\n", " | dtype('float64')\n", " | \n", " | See Also\n", " | --------\n", " | numpy.real : equivalent function\n", " | \n", " | shape\n", " | Tuple of array dimensions.\n", " | \n", " | The shape property is usually used to get the current shape of an array,\n", " | but may also be used to reshape the array in-place by assigning a tuple of\n", " | array dimensions to it. As with `numpy.reshape`, one of the new shape\n", " | dimensions can be -1, in which case its value is inferred from the size of\n", " | the array and the remaining dimensions. Reshaping an array in-place will\n", " | fail if a copy is required.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3, 4])\n", " | >>> x.shape\n", " | (4,)\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.shape\n", " | (2, 3, 4)\n", " | >>> y.shape = (3, 8)\n", " | >>> y\n", " | array([[ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.]])\n", " | >>> y.shape = (3, 6)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: total size of new array must be unchanged\n", " | >>> np.zeros((4,2))[::2].shape = (-1,)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | AttributeError: Incompatible shape for in-place modification. Use\n", " | `.reshape()` to make a copy with the desired shape.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : similar function\n", " | ndarray.reshape : similar method\n", " | \n", " | size\n", " | Number of elements in the array.\n", " | \n", " | Equal to ``np.prod(a.shape)``, i.e., the product of the array's\n", " | dimensions.\n", " | \n", " | Notes\n", " | -----\n", " | `a.size` returns a standard arbitrary precision Python integer. This\n", " | may not be the case with other methods of obtaining the same value\n", " | (like the suggested ``np.prod(a.shape)``, which returns an instance\n", " | of ``np.int_``), and may be relevant if the value is used further in\n", " | calculations that may overflow a fixed size integer type.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3, 5, 2), dtype=np.complex128)\n", " | >>> x.size\n", " | 30\n", " | >>> np.prod(x.shape)\n", " | 30\n", " | \n", " | strides\n", " | Tuple of bytes to step in each dimension when traversing an array.\n", " | \n", " | The byte offset of element ``(i[0], i[1], ..., i[n])`` in an array `a`\n", " | is::\n", " | \n", " | offset = sum(np.array(i) * a.strides)\n", " | \n", " | A more detailed explanation of strides can be found in the\n", " | \"ndarray.rst\" file in the NumPy reference guide.\n", " | \n", " | Notes\n", " | -----\n", " | Imagine an array of 32-bit integers (each 4 bytes)::\n", " | \n", " | x = np.array([[0, 1, 2, 3, 4],\n", " | [5, 6, 7, 8, 9]], dtype=np.int32)\n", " | \n", " | This array is stored in memory as 40 bytes, one after the other\n", " | (known as a contiguous block of memory). The strides of an array tell\n", " | us how many bytes we have to skip in memory to move to the next position\n", " | along a certain axis. For example, we have to skip 4 bytes (1 value) to\n", " | move to the next column, but 20 bytes (5 values) to get to the same\n", " | position in the next row. As such, the strides for the array `x` will be\n", " | ``(20, 4)``.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.lib.stride_tricks.as_strided\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.reshape(np.arange(2*3*4), (2,3,4))\n", " | >>> y\n", " | array([[[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]],\n", " | [[12, 13, 14, 15],\n", " | [16, 17, 18, 19],\n", " | [20, 21, 22, 23]]])\n", " | >>> y.strides\n", " | (48, 16, 4)\n", " | >>> y[1,1,1]\n", " | 17\n", " | >>> offset=sum(y.strides * np.array((1,1,1)))\n", " | >>> offset/y.itemsize\n", " | 17\n", " | \n", " | >>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0)\n", " | >>> x.strides\n", " | (32, 4, 224, 1344)\n", " | >>> i = np.array([3,5,2,2])\n", " | >>> offset = sum(i * x.strides)\n", " | >>> x[3,5,2,2]\n", " | 813\n", " | >>> offset / x.itemsize\n", " | 813\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from ndarray:\n", " | \n", " | __hash__ = None\n", " \n", " class memmap(ndarray)\n", " | memmap(filename, dtype=, mode='r+', offset=0, shape=None, order='C')\n", " | \n", " | Create a memory-map to an array stored in a *binary* file on disk.\n", " | \n", " | Memory-mapped files are used for accessing small segments of large files\n", " | on disk, without reading the entire file into memory. NumPy's\n", " | memmap's are array-like objects. This differs from Python's ``mmap``\n", " | module, which uses file-like objects.\n", " | \n", " | This subclass of ndarray has some unpleasant interactions with\n", " | some operations, because it doesn't quite fit properly as a subclass.\n", " | An alternative to using this subclass is to create the ``mmap``\n", " | object yourself, then create an ndarray with ndarray.__new__ directly,\n", " | passing the object created in its 'buffer=' parameter.\n", " | \n", " | This class may at some point be turned into a factory function\n", " | which returns a view into an mmap buffer.\n", " | \n", " | Delete the memmap instance to close the memmap file.\n", " | \n", " | \n", " | Parameters\n", " | ----------\n", " | filename : str, file-like object, or pathlib.Path instance\n", " | The file name or file object to be used as the array data buffer.\n", " | dtype : data-type, optional\n", " | The data-type used to interpret the file contents.\n", " | Default is `uint8`.\n", " | mode : {'r+', 'r', 'w+', 'c'}, optional\n", " | The file is opened in this mode:\n", " | \n", " | +------+-------------------------------------------------------------+\n", " | | 'r' | Open existing file for reading only. |\n", " | +------+-------------------------------------------------------------+\n", " | | 'r+' | Open existing file for reading and writing. |\n", " | +------+-------------------------------------------------------------+\n", " | | 'w+' | Create or overwrite existing file for reading and writing. |\n", " | +------+-------------------------------------------------------------+\n", " | | 'c' | Copy-on-write: assignments affect data in memory, but |\n", " | | | changes are not saved to disk. The file on disk is |\n", " | | | read-only. |\n", " | +------+-------------------------------------------------------------+\n", " | \n", " | Default is 'r+'.\n", " | offset : int, optional\n", " | In the file, array data starts at this offset. Since `offset` is\n", " | measured in bytes, it should normally be a multiple of the byte-size\n", " | of `dtype`. When ``mode != 'r'``, even positive offsets beyond end of\n", " | file are valid; The file will be extended to accommodate the\n", " | additional data. By default, ``memmap`` will start at the beginning of\n", " | the file, even if ``filename`` is a file pointer ``fp`` and\n", " | ``fp.tell() != 0``.\n", " | shape : tuple, optional\n", " | The desired shape of the array. If ``mode == 'r'`` and the number\n", " | of remaining bytes after `offset` is not a multiple of the byte-size\n", " | of `dtype`, you must specify `shape`. By default, the returned array\n", " | will be 1-D with the number of elements determined by file size\n", " | and data-type.\n", " | order : {'C', 'F'}, optional\n", " | Specify the order of the ndarray memory layout:\n", " | :term:`row-major`, C-style or :term:`column-major`,\n", " | Fortran-style. This only has an effect if the shape is\n", " | greater than 1-D. The default order is 'C'.\n", " | \n", " | Attributes\n", " | ----------\n", " | filename : str or pathlib.Path instance\n", " | Path to the mapped file.\n", " | offset : int\n", " | Offset position in the file.\n", " | mode : str\n", " | File mode.\n", " | \n", " | Methods\n", " | -------\n", " | flush\n", " | Flush any changes in memory to file on disk.\n", " | When you delete a memmap object, flush is called first to write\n", " | changes to disk before removing the object.\n", " | \n", " | \n", " | See also\n", " | --------\n", " | lib.format.open_memmap : Create or load a memory-mapped ``.npy`` file.\n", " | \n", " | Notes\n", " | -----\n", " | The memmap object can be used anywhere an ndarray is accepted.\n", " | Given a memmap ``fp``, ``isinstance(fp, numpy.ndarray)`` returns\n", " | ``True``.\n", " | \n", " | Memory-mapped files cannot be larger than 2GB on 32-bit systems.\n", " | \n", " | When a memmap causes a file to be created or extended beyond its\n", " | current size in the filesystem, the contents of the new part are\n", " | unspecified. On systems with POSIX filesystem semantics, the extended\n", " | part will be filled with zero bytes.\n", " | \n", " | Examples\n", " | --------\n", " | >>> data = np.arange(12, dtype='float32')\n", " | >>> data.resize((3,4))\n", " | \n", " | This example uses a temporary file so that doctest doesn't write\n", " | files to your directory. You would use a 'normal' filename.\n", " | \n", " | >>> from tempfile import mkdtemp\n", " | >>> import os.path as path\n", " | >>> filename = path.join(mkdtemp(), 'newfile.dat')\n", " | \n", " | Create a memmap with dtype and shape that matches our data:\n", " | \n", " | >>> fp = np.memmap(filename, dtype='float32', mode='w+', shape=(3,4))\n", " | >>> fp\n", " | memmap([[0., 0., 0., 0.],\n", " | [0., 0., 0., 0.],\n", " | [0., 0., 0., 0.]], dtype=float32)\n", " | \n", " | Write data to memmap array:\n", " | \n", " | >>> fp[:] = data[:]\n", " | >>> fp\n", " | memmap([[ 0., 1., 2., 3.],\n", " | [ 4., 5., 6., 7.],\n", " | [ 8., 9., 10., 11.]], dtype=float32)\n", " | \n", " | >>> fp.filename == path.abspath(filename)\n", " | True\n", " | \n", " | Deletion flushes memory changes to disk before removing the object:\n", " | \n", " | >>> del fp\n", " | \n", " | Load the memmap and verify data was stored:\n", " | \n", " | >>> newfp = np.memmap(filename, dtype='float32', mode='r', shape=(3,4))\n", " | >>> newfp\n", " | memmap([[ 0., 1., 2., 3.],\n", " | [ 4., 5., 6., 7.],\n", " | [ 8., 9., 10., 11.]], dtype=float32)\n", " | \n", " | Read-only memmap:\n", " | \n", " | >>> fpr = np.memmap(filename, dtype='float32', mode='r', shape=(3,4))\n", " | >>> fpr.flags.writeable\n", " | False\n", " | \n", " | Copy-on-write memmap:\n", " | \n", " | >>> fpc = np.memmap(filename, dtype='float32', mode='c', shape=(3,4))\n", " | >>> fpc.flags.writeable\n", " | True\n", " | \n", " | It's possible to assign to copy-on-write array, but values are only\n", " | written into the memory copy of the array, and not written to disk:\n", " | \n", " | >>> fpc\n", " | memmap([[ 0., 1., 2., 3.],\n", " | [ 4., 5., 6., 7.],\n", " | [ 8., 9., 10., 11.]], dtype=float32)\n", " | >>> fpc[0,:] = 0\n", " | >>> fpc\n", " | memmap([[ 0., 0., 0., 0.],\n", " | [ 4., 5., 6., 7.],\n", " | [ 8., 9., 10., 11.]], dtype=float32)\n", " | \n", " | File on disk is unchanged:\n", " | \n", " | >>> fpr\n", " | memmap([[ 0., 1., 2., 3.],\n", " | [ 4., 5., 6., 7.],\n", " | [ 8., 9., 10., 11.]], dtype=float32)\n", " | \n", " | Offset into a memmap:\n", " | \n", " | >>> fpo = np.memmap(filename, dtype='float32', mode='r', offset=16)\n", " | >>> fpo\n", " | memmap([ 4., 5., 6., 7., 8., 9., 10., 11.], dtype=float32)\n", " | \n", " | Method resolution order:\n", " | memmap\n", " | ndarray\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __array_finalize__(self, obj)\n", " | None.\n", " | \n", " | __array_wrap__(self, arr, context=None)\n", " | a.__array_wrap__(obj) -> Object of same type as ndarray object a.\n", " | \n", " | __getitem__(self, index)\n", " | Return self[key].\n", " | \n", " | flush(self)\n", " | Write any changes in the array to the file on disk.\n", " | \n", " | For further information, see `memmap`.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | See Also\n", " | --------\n", " | memmap\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(subtype, filename, dtype=, mode='r+', offset=0, shape=None, order='C')\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes defined here:\n", " | \n", " | __array_priority__ = -100.0\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from ndarray:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | a.__array__([dtype], /) -> reference if type unchanged, copy otherwise.\n", " | \n", " | Returns either a new reference to self if dtype is not given or a new array\n", " | of provided data type if dtype is different from the current dtype of the\n", " | array.\n", " | \n", " | __array_function__(...)\n", " | \n", " | __array_prepare__(...)\n", " | a.__array_prepare__(obj) -> Object of same type as ndarray object obj.\n", " | \n", " | __array_ufunc__(...)\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __contains__(self, key, /)\n", " | Return key in self.\n", " | \n", " | __copy__(...)\n", " | a.__copy__()\n", " | \n", " | Used if :func:`copy.copy` is called on an array. Returns a copy of the array.\n", " | \n", " | Equivalent to ``a.copy(order='K')``.\n", " | \n", " | __deepcopy__(...)\n", " | a.__deepcopy__(memo, /) -> Deep copy of array.\n", " | \n", " | Used if :func:`copy.deepcopy` is called on an array.\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | Default object formatter.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __iadd__(self, value, /)\n", " | Return self+=value.\n", " | \n", " | __iand__(self, value, /)\n", " | Return self&=value.\n", " | \n", " | __ifloordiv__(self, value, /)\n", " | Return self//=value.\n", " | \n", " | __ilshift__(self, value, /)\n", " | Return self<<=value.\n", " | \n", " | __imatmul__(self, value, /)\n", " | Return self@=value.\n", " | \n", " | __imod__(self, value, /)\n", " | Return self%=value.\n", " | \n", " | __imul__(self, value, /)\n", " | Return self*=value.\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __ior__(self, value, /)\n", " | Return self|=value.\n", " | \n", " | __ipow__(self, value, /)\n", " | Return self**=value.\n", " | \n", " | __irshift__(self, value, /)\n", " | Return self>>=value.\n", " | \n", " | __isub__(self, value, /)\n", " | Return self-=value.\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __itruediv__(self, value, /)\n", " | Return self/=value.\n", " | \n", " | __ixor__(self, value, /)\n", " | Return self^=value.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setitem__(self, key, value, /)\n", " | Set self[key] to value.\n", " | \n", " | __setstate__(...)\n", " | a.__setstate__(state, /)\n", " | \n", " | For unpickling.\n", " | \n", " | The `state` argument must be a sequence that contains the following\n", " | elements:\n", " | \n", " | Parameters\n", " | ----------\n", " | version : int\n", " | optional pickle version. If omitted defaults to 0.\n", " | shape : tuple\n", " | dtype : data-type\n", " | isFortran : bool\n", " | rawdata : string or list\n", " | a binary string with the data (or a list if 'a' is an object array)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | a.all(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if all elements evaluate to True.\n", " | \n", " | Refer to `numpy.all` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.all : equivalent function\n", " | \n", " | any(...)\n", " | a.any(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if any of the elements of `a` evaluate to True.\n", " | \n", " | Refer to `numpy.any` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.any : equivalent function\n", " | \n", " | argmax(...)\n", " | a.argmax(axis=None, out=None)\n", " | \n", " | Return indices of the maximum values along the given axis.\n", " | \n", " | Refer to `numpy.argmax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmax : equivalent function\n", " | \n", " | argmin(...)\n", " | a.argmin(axis=None, out=None)\n", " | \n", " | Return indices of the minimum values along the given axis of `a`.\n", " | \n", " | Refer to `numpy.argmin` for detailed documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmin : equivalent function\n", " | \n", " | argpartition(...)\n", " | a.argpartition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Returns the indices that would partition this array.\n", " | \n", " | Refer to `numpy.argpartition` for full documentation.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argpartition : equivalent function\n", " | \n", " | argsort(...)\n", " | a.argsort(axis=-1, kind=None, order=None)\n", " | \n", " | Returns the indices that would sort this array.\n", " | \n", " | Refer to `numpy.argsort` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argsort : equivalent function\n", " | \n", " | astype(...)\n", " | a.astype(dtype, order='K', casting='unsafe', subok=True, copy=True)\n", " | \n", " | Copy of the array, cast to a specified type.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | Typecode or data-type to which the array is cast.\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout order of the result.\n", " | 'C' means C order, 'F' means Fortran order, 'A'\n", " | means 'F' order if all the arrays are Fortran contiguous,\n", " | 'C' order otherwise, and 'K' means as close to the\n", " | order the array elements appear in memory as possible.\n", " | Default is 'K'.\n", " | casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n", " | Controls what kind of data casting may occur. Defaults to 'unsafe'\n", " | for backwards compatibility.\n", " | \n", " | * 'no' means the data types should not be cast at all.\n", " | * 'equiv' means only byte-order changes are allowed.\n", " | * 'safe' means only casts which can preserve values are allowed.\n", " | * 'same_kind' means only safe casts or casts within a kind,\n", " | like float64 to float32, are allowed.\n", " | * 'unsafe' means any data conversions may be done.\n", " | subok : bool, optional\n", " | If True, then sub-classes will be passed-through (default), otherwise\n", " | the returned array will be forced to be a base-class array.\n", " | copy : bool, optional\n", " | By default, astype always returns a newly allocated array. If this\n", " | is set to false, and the `dtype`, `order`, and `subok`\n", " | requirements are satisfied, the input array is returned instead\n", " | of a copy.\n", " | \n", " | Returns\n", " | -------\n", " | arr_t : ndarray\n", " | Unless `copy` is False and the other conditions for returning the input\n", " | array are satisfied (see description for `copy` input parameter), `arr_t`\n", " | is a new array of the same shape as the input array, with dtype, order\n", " | given by `dtype`, `order`.\n", " | \n", " | Notes\n", " | -----\n", " | .. versionchanged:: 1.17.0\n", " | Casting between a simple data type and a structured one is possible only\n", " | for \"unsafe\" casting. Casting to multiple fields is allowed, but\n", " | casting from multiple fields is not.\n", " | \n", " | .. versionchanged:: 1.9.0\n", " | Casting from numeric to string types in 'safe' casting mode requires\n", " | that the string dtype length is long enough to store the max\n", " | integer/float value converted.\n", " | \n", " | Raises\n", " | ------\n", " | ComplexWarning\n", " | When casting from complex to float or int. To avoid this,\n", " | one should use ``a.real.astype(t)``.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 2.5])\n", " | >>> x\n", " | array([1. , 2. , 2.5])\n", " | \n", " | >>> x.astype(int)\n", " | array([1, 2, 2])\n", " | \n", " | byteswap(...)\n", " | a.byteswap(inplace=False)\n", " | \n", " | Swap the bytes of the array elements\n", " | \n", " | Toggle between low-endian and big-endian data representation by\n", " | returning a byteswapped array, optionally swapped in-place.\n", " | Arrays of byte-strings are not swapped. The real and imaginary\n", " | parts of a complex number are swapped individually.\n", " | \n", " | Parameters\n", " | ----------\n", " | inplace : bool, optional\n", " | If ``True``, swap bytes in-place, default is ``False``.\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | The byteswapped array. If `inplace` is ``True``, this is\n", " | a view to self.\n", " | \n", " | Examples\n", " | --------\n", " | >>> A = np.array([1, 256, 8755], dtype=np.int16)\n", " | >>> list(map(hex, A))\n", " | ['0x1', '0x100', '0x2233']\n", " | >>> A.byteswap(inplace=True)\n", " | array([ 256, 1, 13090], dtype=int16)\n", " | >>> list(map(hex, A))\n", " | ['0x100', '0x1', '0x3322']\n", " | \n", " | Arrays of byte-strings are not swapped\n", " | \n", " | >>> A = np.array([b'ceg', b'fac'])\n", " | >>> A.byteswap()\n", " | array([b'ceg', b'fac'], dtype='|S3')\n", " | \n", " | ``A.newbyteorder().byteswap()`` produces an array with the same values\n", " | but different representation in memory\n", " | \n", " | >>> A = np.array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,\n", " | 0, 0], dtype=uint8)\n", " | >>> A.newbyteorder().byteswap(inplace=True)\n", " | array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0,\n", " | 0, 3], dtype=uint8)\n", " | \n", " | choose(...)\n", " | a.choose(choices, out=None, mode='raise')\n", " | \n", " | Use an index array to construct a new array from a set of choices.\n", " | \n", " | Refer to `numpy.choose` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.choose : equivalent function\n", " | \n", " | clip(...)\n", " | a.clip(min=None, max=None, out=None, **kwargs)\n", " | \n", " | Return an array whose values are limited to ``[min, max]``.\n", " | One of max or min must be given.\n", " | \n", " | Refer to `numpy.clip` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.clip : equivalent function\n", " | \n", " | compress(...)\n", " | a.compress(condition, axis=None, out=None)\n", " | \n", " | Return selected slices of this array along given axis.\n", " | \n", " | Refer to `numpy.compress` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.compress : equivalent function\n", " | \n", " | conj(...)\n", " | a.conj()\n", " | \n", " | Complex-conjugate all elements.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | conjugate(...)\n", " | a.conjugate()\n", " | \n", " | Return the complex conjugate, element-wise.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | copy(...)\n", " | a.copy(order='C')\n", " | \n", " | Return a copy of the array.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout of the copy. 'C' means C-order,\n", " | 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,\n", " | 'C' otherwise. 'K' means match the layout of `a` as closely\n", " | as possible. (Note that this function and :func:`numpy.copy` are very\n", " | similar, but have different default values for their order=\n", " | arguments.)\n", " | \n", " | See also\n", " | --------\n", " | numpy.copy\n", " | numpy.copyto\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([[1,2,3],[4,5,6]], order='F')\n", " | \n", " | >>> y = x.copy()\n", " | \n", " | >>> x.fill(0)\n", " | \n", " | >>> x\n", " | array([[0, 0, 0],\n", " | [0, 0, 0]])\n", " | \n", " | >>> y\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | \n", " | >>> y.flags['C_CONTIGUOUS']\n", " | True\n", " | \n", " | cumprod(...)\n", " | a.cumprod(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative product of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumprod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumprod : equivalent function\n", " | \n", " | cumsum(...)\n", " | a.cumsum(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative sum of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumsum` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumsum : equivalent function\n", " | \n", " | diagonal(...)\n", " | a.diagonal(offset=0, axis1=0, axis2=1)\n", " | \n", " | Return specified diagonals. In NumPy 1.9 the returned array is a\n", " | read-only view instead of a copy as in previous NumPy versions. In\n", " | a future version the read-only restriction will be removed.\n", " | \n", " | Refer to :func:`numpy.diagonal` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.diagonal : equivalent function\n", " | \n", " | dot(...)\n", " | a.dot(b, out=None)\n", " | \n", " | Dot product of two arrays.\n", " | \n", " | Refer to `numpy.dot` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dot : equivalent function\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.eye(2)\n", " | >>> b = np.ones((2, 2)) * 2\n", " | >>> a.dot(b)\n", " | array([[2., 2.],\n", " | [2., 2.]])\n", " | \n", " | This array method can be conveniently chained:\n", " | \n", " | >>> a.dot(b).dot(b)\n", " | array([[8., 8.],\n", " | [8., 8.]])\n", " | \n", " | dump(...)\n", " | a.dump(file)\n", " | \n", " | Dump a pickle of the array to the specified file.\n", " | The array can be read back with pickle.load or numpy.load.\n", " | \n", " | Parameters\n", " | ----------\n", " | file : str or Path\n", " | A string naming the dump file.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | dumps(...)\n", " | a.dumps()\n", " | \n", " | Returns the pickle of the array as a string.\n", " | pickle.loads or numpy.loads will convert the string back to an array.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | fill(...)\n", " | a.fill(value)\n", " | \n", " | Fill the array with a scalar value.\n", " | \n", " | Parameters\n", " | ----------\n", " | value : scalar\n", " | All elements of `a` will be assigned this value.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([1, 2])\n", " | >>> a.fill(0)\n", " | >>> a\n", " | array([0, 0])\n", " | >>> a = np.empty(2)\n", " | >>> a.fill(1)\n", " | >>> a\n", " | array([1., 1.])\n", " | \n", " | flatten(...)\n", " | a.flatten(order='C')\n", " | \n", " | Return a copy of the array collapsed into one dimension.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | 'C' means to flatten in row-major (C-style) order.\n", " | 'F' means to flatten in column-major (Fortran-\n", " | style) order. 'A' means to flatten in column-major\n", " | order if `a` is Fortran *contiguous* in memory,\n", " | row-major order otherwise. 'K' means to flatten\n", " | `a` in the order the elements occur in memory.\n", " | The default is 'C'.\n", " | \n", " | Returns\n", " | -------\n", " | y : ndarray\n", " | A copy of the input array, flattened to one dimension.\n", " | \n", " | See Also\n", " | --------\n", " | ravel : Return a flattened array.\n", " | flat : A 1-D flat iterator over the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,2], [3,4]])\n", " | >>> a.flatten()\n", " | array([1, 2, 3, 4])\n", " | >>> a.flatten('F')\n", " | array([1, 3, 2, 4])\n", " | \n", " | getfield(...)\n", " | a.getfield(dtype, offset=0)\n", " | \n", " | Returns a field of the given array as a certain type.\n", " | \n", " | A field is a view of the array data with a given data-type. The values in\n", " | the view are determined by the given type and the offset into the current\n", " | array in bytes. The offset needs to be such that the view dtype fits in the\n", " | array dtype; for example an array of dtype complex128 has 16-byte elements.\n", " | If taking a view with a 32-bit integer (4 bytes), the offset needs to be\n", " | between 0 and 12 bytes.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | The data type of the view. The dtype size of the view can not be larger\n", " | than that of the array itself.\n", " | offset : int\n", " | Number of bytes to skip before beginning the element view.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.diag([1.+1.j]*2)\n", " | >>> x[1, 1] = 2 + 4.j\n", " | >>> x\n", " | array([[1.+1.j, 0.+0.j],\n", " | [0.+0.j, 2.+4.j]])\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0.],\n", " | [0., 2.]])\n", " | \n", " | By choosing an offset of 8 bytes we can select the complex part of the\n", " | array for our view:\n", " | \n", " | >>> x.getfield(np.float64, offset=8)\n", " | array([[1., 0.],\n", " | [0., 4.]])\n", " | \n", " | item(...)\n", " | a.item(*args)\n", " | \n", " | Copy an element of an array to a standard Python scalar and return it.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments (variable number and type)\n", " | \n", " | * none: in this case, the method only works for arrays\n", " | with one element (`a.size == 1`), which element is\n", " | copied into a standard Python scalar object and returned.\n", " | \n", " | * int_type: this argument is interpreted as a flat index into\n", " | the array, specifying which element to copy and return.\n", " | \n", " | * tuple of int_types: functions as does a single int_type argument,\n", " | except that the argument is interpreted as an nd-index into the\n", " | array.\n", " | \n", " | Returns\n", " | -------\n", " | z : Standard Python scalar object\n", " | A copy of the specified element of the array as a suitable\n", " | Python scalar\n", " | \n", " | Notes\n", " | -----\n", " | When the data type of `a` is longdouble or clongdouble, item() returns\n", " | a scalar array object because there is no available Python scalar that\n", " | would not lose information. Void arrays return a buffer object for item(),\n", " | unless fields are defined, in which case a tuple is returned.\n", " | \n", " | `item` is very similar to a[args], except, instead of an array scalar,\n", " | a standard Python scalar is returned. This can be useful for speeding up\n", " | access to elements of the array and doing arithmetic on elements of the\n", " | array using Python's optimized math.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.item(3)\n", " | 1\n", " | >>> x.item(7)\n", " | 0\n", " | >>> x.item((0, 1))\n", " | 2\n", " | >>> x.item((2, 2))\n", " | 1\n", " | \n", " | itemset(...)\n", " | a.itemset(*args)\n", " | \n", " | Insert scalar into an array (scalar is cast to array's dtype, if possible)\n", " | \n", " | There must be at least 1 argument, and define the last argument\n", " | as *item*. Then, ``a.itemset(*args)`` is equivalent to but faster\n", " | than ``a[args] = item``. The item should be a scalar value and `args`\n", " | must select a single item in the array `a`.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments\n", " | If one argument: a scalar, only used in case `a` is of size 1.\n", " | If two arguments: the last argument is the value to be set\n", " | and must be a scalar, the first argument specifies a single array\n", " | element location. It is either an int or a tuple.\n", " | \n", " | Notes\n", " | -----\n", " | Compared to indexing syntax, `itemset` provides some speed increase\n", " | for placing a scalar into a particular location in an `ndarray`,\n", " | if you must do this. However, generally this is discouraged:\n", " | among other problems, it complicates the appearance of the code.\n", " | Also, when using `itemset` (and `item`) inside a loop, be sure\n", " | to assign the methods to a local variable to avoid the attribute\n", " | look-up at each loop iteration.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.itemset(4, 0)\n", " | >>> x.itemset((2, 2), 9)\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 0, 6],\n", " | [1, 0, 9]])\n", " | \n", " | max(...)\n", " | a.max(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the maximum along a given axis.\n", " | \n", " | Refer to `numpy.amax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amax : equivalent function\n", " | \n", " | mean(...)\n", " | a.mean(axis=None, dtype=None, out=None, keepdims=False)\n", " | \n", " | Returns the average of the array elements along given axis.\n", " | \n", " | Refer to `numpy.mean` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.mean : equivalent function\n", " | \n", " | min(...)\n", " | a.min(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the minimum along a given axis.\n", " | \n", " | Refer to `numpy.amin` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amin : equivalent function\n", " | \n", " | newbyteorder(...)\n", " | arr.newbyteorder(new_order='S')\n", " | \n", " | Return the array with the same data viewed with a different byte order.\n", " | \n", " | Equivalent to::\n", " | \n", " | arr.view(arr.dtype.newbytorder(new_order))\n", " | \n", " | Changes are also made in all fields and sub-arrays of the array data\n", " | type.\n", " | \n", " | \n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : string, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | below. `new_order` codes can be any of:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_arr : array\n", " | New array object with the dtype reflecting given change to the\n", " | byte order.\n", " | \n", " | nonzero(...)\n", " | a.nonzero()\n", " | \n", " | Return the indices of the elements that are non-zero.\n", " | \n", " | Refer to `numpy.nonzero` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.nonzero : equivalent function\n", " | \n", " | partition(...)\n", " | a.partition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Rearranges the elements in the array in such a way that the value of the\n", " | element in kth position is in the position it would be in a sorted array.\n", " | All elements smaller than the kth element are moved before this element and\n", " | all equal or greater are moved behind it. The ordering of the elements in\n", " | the two partitions is undefined.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | Parameters\n", " | ----------\n", " | kth : int or sequence of ints\n", " | Element index to partition by. The kth element value will be in its\n", " | final sorted position and all smaller elements will be moved before it\n", " | and all equal or greater elements behind it.\n", " | The order of all elements in the partitions is undefined.\n", " | If provided with a sequence of kth it will partition all elements\n", " | indexed by kth of them into their sorted position at once.\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'introselect'}, optional\n", " | Selection algorithm. Default is 'introselect'.\n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need to be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.partition : Return a parititioned copy of an array.\n", " | argpartition : Indirect partition.\n", " | sort : Full sort.\n", " | \n", " | Notes\n", " | -----\n", " | See ``np.partition`` for notes on the different algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([3, 4, 2, 1])\n", " | >>> a.partition(3)\n", " | >>> a\n", " | array([2, 1, 3, 4])\n", " | \n", " | >>> a.partition((1, 3))\n", " | >>> a\n", " | array([1, 2, 3, 4])\n", " | \n", " | prod(...)\n", " | a.prod(axis=None, dtype=None, out=None, keepdims=False, initial=1, where=True)\n", " | \n", " | Return the product of the array elements over the given axis\n", " | \n", " | Refer to `numpy.prod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.prod : equivalent function\n", " | \n", " | ptp(...)\n", " | a.ptp(axis=None, out=None, keepdims=False)\n", " | \n", " | Peak to peak (maximum - minimum) value along a given axis.\n", " | \n", " | Refer to `numpy.ptp` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ptp : equivalent function\n", " | \n", " | put(...)\n", " | a.put(indices, values, mode='raise')\n", " | \n", " | Set ``a.flat[n] = values[n]`` for all `n` in indices.\n", " | \n", " | Refer to `numpy.put` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.put : equivalent function\n", " | \n", " | ravel(...)\n", " | a.ravel([order])\n", " | \n", " | Return a flattened array.\n", " | \n", " | Refer to `numpy.ravel` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ravel : equivalent function\n", " | \n", " | ndarray.flat : a flat iterator on the array.\n", " | \n", " | repeat(...)\n", " | a.repeat(repeats, axis=None)\n", " | \n", " | Repeat elements of an array.\n", " | \n", " | Refer to `numpy.repeat` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.repeat : equivalent function\n", " | \n", " | reshape(...)\n", " | a.reshape(shape, order='C')\n", " | \n", " | Returns an array containing the same data with a new shape.\n", " | \n", " | Refer to `numpy.reshape` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : equivalent function\n", " | \n", " | Notes\n", " | -----\n", " | Unlike the free function `numpy.reshape`, this method on `ndarray` allows\n", " | the elements of the shape parameter to be passed in as separate arguments.\n", " | For example, ``a.reshape(10, 11)`` is equivalent to\n", " | ``a.reshape((10, 11))``.\n", " | \n", " | resize(...)\n", " | a.resize(new_shape, refcheck=True)\n", " | \n", " | Change shape and size of array in-place.\n", " | \n", " | Parameters\n", " | ----------\n", " | new_shape : tuple of ints, or `n` ints\n", " | Shape of resized array.\n", " | refcheck : bool, optional\n", " | If False, reference count will not be checked. Default is True.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | Raises\n", " | ------\n", " | ValueError\n", " | If `a` does not own its own data or references or views to it exist,\n", " | and the data memory must be changed.\n", " | PyPy only: will always raise if the data memory must be changed, since\n", " | there is no reliable way to determine if references or views to it\n", " | exist.\n", " | \n", " | SystemError\n", " | If the `order` keyword argument is specified. This behaviour is a\n", " | bug in NumPy.\n", " | \n", " | See Also\n", " | --------\n", " | resize : Return a new array with the specified shape.\n", " | \n", " | Notes\n", " | -----\n", " | This reallocates space for the data area if necessary.\n", " | \n", " | Only contiguous arrays (data elements consecutive in memory) can be\n", " | resized.\n", " | \n", " | The purpose of the reference count check is to make sure you\n", " | do not use this array as a buffer for another Python object and then\n", " | reallocate the memory. However, reference counts can increase in\n", " | other ways so if you are sure that you have not shared the memory\n", " | for this array with another Python object, then you may safely set\n", " | `refcheck` to False.\n", " | \n", " | Examples\n", " | --------\n", " | Shrinking an array: array is flattened (in the order that the data are\n", " | stored in memory), resized, and reshaped:\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='C')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [1]])\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='F')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [2]])\n", " | \n", " | Enlarging an array: as above, but missing entries are filled with zeros:\n", " | \n", " | >>> b = np.array([[0, 1], [2, 3]])\n", " | >>> b.resize(2, 3) # new_shape parameter doesn't have to be a tuple\n", " | >>> b\n", " | array([[0, 1, 2],\n", " | [3, 0, 0]])\n", " | \n", " | Referencing an array prevents resizing...\n", " | \n", " | >>> c = a\n", " | >>> a.resize((1, 1))\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: cannot resize an array that references or is referenced ...\n", " | \n", " | Unless `refcheck` is False:\n", " | \n", " | >>> a.resize((1, 1), refcheck=False)\n", " | >>> a\n", " | array([[0]])\n", " | >>> c\n", " | array([[0]])\n", " | \n", " | round(...)\n", " | a.round(decimals=0, out=None)\n", " | \n", " | Return `a` with each element rounded to the given number of decimals.\n", " | \n", " | Refer to `numpy.around` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.around : equivalent function\n", " | \n", " | searchsorted(...)\n", " | a.searchsorted(v, side='left', sorter=None)\n", " | \n", " | Find indices where elements of v should be inserted in a to maintain order.\n", " | \n", " | For full documentation, see `numpy.searchsorted`\n", " | \n", " | See Also\n", " | --------\n", " | numpy.searchsorted : equivalent function\n", " | \n", " | setfield(...)\n", " | a.setfield(val, dtype, offset=0)\n", " | \n", " | Put a value into a specified place in a field defined by a data-type.\n", " | \n", " | Place `val` into `a`'s field defined by `dtype` and beginning `offset`\n", " | bytes into the field.\n", " | \n", " | Parameters\n", " | ----------\n", " | val : object\n", " | Value to be placed in field.\n", " | dtype : dtype object\n", " | Data-type of the field in which to place `val`.\n", " | offset : int, optional\n", " | The number of bytes into the field at which to place `val`.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | See Also\n", " | --------\n", " | getfield\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.eye(3)\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | >>> x.setfield(3, np.int32)\n", " | >>> x.getfield(np.int32)\n", " | array([[3, 3, 3],\n", " | [3, 3, 3],\n", " | [3, 3, 3]], dtype=int32)\n", " | >>> x\n", " | array([[1.0e+000, 1.5e-323, 1.5e-323],\n", " | [1.5e-323, 1.0e+000, 1.5e-323],\n", " | [1.5e-323, 1.5e-323, 1.0e+000]])\n", " | >>> x.setfield(np.eye(3), np.int32)\n", " | >>> x\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | \n", " | setflags(...)\n", " | a.setflags(write=None, align=None, uic=None)\n", " | \n", " | Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY),\n", " | respectively.\n", " | \n", " | These Boolean-valued flags affect how numpy interprets the memory\n", " | area used by `a` (see Notes below). The ALIGNED flag can only\n", " | be set to True if the data is actually aligned according to the type.\n", " | The WRITEBACKIFCOPY and (deprecated) UPDATEIFCOPY flags can never be set\n", " | to True. The flag WRITEABLE can only be set to True if the array owns its\n", " | own memory, or the ultimate owner of the memory exposes a writeable buffer\n", " | interface, or is a string. (The exception for string is made so that\n", " | unpickling can be done without copying memory.)\n", " | \n", " | Parameters\n", " | ----------\n", " | write : bool, optional\n", " | Describes whether or not `a` can be written to.\n", " | align : bool, optional\n", " | Describes whether or not `a` is aligned properly for its type.\n", " | uic : bool, optional\n", " | Describes whether or not `a` is a copy of another \"base\" array.\n", " | \n", " | Notes\n", " | -----\n", " | Array flags provide information about how the memory area used\n", " | for the array is to be interpreted. There are 7 Boolean flags\n", " | in use, only four of which can be changed by the user:\n", " | WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED.\n", " | \n", " | WRITEABLE (W) the data area can be written to;\n", " | \n", " | ALIGNED (A) the data and strides are aligned appropriately for the hardware\n", " | (as determined by the compiler);\n", " | \n", " | UPDATEIFCOPY (U) (deprecated), replaced by WRITEBACKIFCOPY;\n", " | \n", " | WRITEBACKIFCOPY (X) this array is a copy of some other array (referenced\n", " | by .base). When the C-API function PyArray_ResolveWritebackIfCopy is\n", " | called, the base array will be updated with the contents of this array.\n", " | \n", " | All flags can be accessed using the single (upper case) letter as well\n", " | as the full name.\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.array([[3, 1, 7],\n", " | ... [2, 0, 0],\n", " | ... [8, 5, 9]])\n", " | >>> y\n", " | array([[3, 1, 7],\n", " | [2, 0, 0],\n", " | [8, 5, 9]])\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : True\n", " | ALIGNED : True\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(write=0, align=0)\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : False\n", " | ALIGNED : False\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(uic=1)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: cannot set WRITEBACKIFCOPY flag to True\n", " | \n", " | sort(...)\n", " | a.sort(axis=-1, kind=None, order=None)\n", " | \n", " | Sort an array in-place. Refer to `numpy.sort` for full documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional\n", " | Sorting algorithm. The default is 'quicksort'. Note that both 'stable'\n", " | and 'mergesort' use timsort under the covers and, in general, the\n", " | actual implementation will vary with datatype. The 'mergesort' option\n", " | is retained for backwards compatibility.\n", " | \n", " | .. versionchanged:: 1.15.0.\n", " | The 'stable' option was added.\n", " | \n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.sort : Return a sorted copy of an array.\n", " | numpy.argsort : Indirect sort.\n", " | numpy.lexsort : Indirect stable sort on multiple keys.\n", " | numpy.searchsorted : Find elements in sorted array.\n", " | numpy.partition: Partial sort.\n", " | \n", " | Notes\n", " | -----\n", " | See `numpy.sort` for notes on the different sorting algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,4], [3,1]])\n", " | >>> a.sort(axis=1)\n", " | >>> a\n", " | array([[1, 4],\n", " | [1, 3]])\n", " | >>> a.sort(axis=0)\n", " | >>> a\n", " | array([[1, 3],\n", " | [1, 4]])\n", " | \n", " | Use the `order` keyword to specify a field to use when sorting a\n", " | structured array:\n", " | \n", " | >>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])\n", " | >>> a.sort(order='y')\n", " | >>> a\n", " | array([(b'c', 1), (b'a', 2)],\n", " | dtype=[('x', 'S1'), ('y', '>> x = np.array([[0, 1], [2, 3]], dtype='>> x.tobytes()\n", " | b'\\x00\\x00\\x01\\x00\\x02\\x00\\x03\\x00'\n", " | >>> x.tobytes('C') == x.tobytes()\n", " | True\n", " | >>> x.tobytes('F')\n", " | b'\\x00\\x00\\x02\\x00\\x01\\x00\\x03\\x00'\n", " | \n", " | tofile(...)\n", " | a.tofile(fid, sep=\"\", format=\"%s\")\n", " | \n", " | Write array to a file as text or binary (default).\n", " | \n", " | Data is always written in 'C' order, independent of the order of `a`.\n", " | The data produced by this method can be recovered using the function\n", " | fromfile().\n", " | \n", " | Parameters\n", " | ----------\n", " | fid : file or str or Path\n", " | An open file object, or a string containing a filename.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | sep : str\n", " | Separator between array items for text output.\n", " | If \"\" (empty), a binary file is written, equivalent to\n", " | ``file.write(a.tobytes())``.\n", " | format : str\n", " | Format string for text file output.\n", " | Each entry in the array is formatted to text by first converting\n", " | it to the closest Python type, and then using \"format\" % item.\n", " | \n", " | Notes\n", " | -----\n", " | This is a convenience function for quick storage of array data.\n", " | Information on endianness and precision is lost, so this method is not a\n", " | good choice for files intended to archive data or transport data between\n", " | machines with different endianness. Some of these problems can be overcome\n", " | by outputting the data as text files, at the expense of speed and file\n", " | size.\n", " | \n", " | When fid is a file object, array contents are directly written to the\n", " | file, bypassing the file object's ``write`` method. As a result, tofile\n", " | cannot be used with files objects supporting compression (e.g., GzipFile)\n", " | or file-like objects that do not support ``fileno()`` (e.g., BytesIO).\n", " | \n", " | tolist(...)\n", " | a.tolist()\n", " | \n", " | Return the array as an ``a.ndim``-levels deep nested list of Python scalars.\n", " | \n", " | Return a copy of the array data as a (nested) Python list.\n", " | Data items are converted to the nearest compatible builtin Python type, via\n", " | the `~numpy.ndarray.item` function.\n", " | \n", " | If ``a.ndim`` is 0, then since the depth of the nested list is 0, it will\n", " | not be a list at all, but a simple Python scalar.\n", " | \n", " | Parameters\n", " | ----------\n", " | none\n", " | \n", " | Returns\n", " | -------\n", " | y : object, or list of object, or list of list of object, or ...\n", " | The possibly nested list of array elements.\n", " | \n", " | Notes\n", " | -----\n", " | The array may be recreated via ``a = np.array(a.tolist())``, although this\n", " | may sometimes lose precision.\n", " | \n", " | Examples\n", " | --------\n", " | For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``,\n", " | except that ``tolist`` changes numpy scalars to Python scalars:\n", " | \n", " | >>> a = np.uint32([1, 2])\n", " | >>> a_list = list(a)\n", " | >>> a_list\n", " | [1, 2]\n", " | >>> type(a_list[0])\n", " | \n", " | >>> a_tolist = a.tolist()\n", " | >>> a_tolist\n", " | [1, 2]\n", " | >>> type(a_tolist[0])\n", " | \n", " | \n", " | Additionally, for a 2D array, ``tolist`` applies recursively:\n", " | \n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> list(a)\n", " | [array([1, 2]), array([3, 4])]\n", " | >>> a.tolist()\n", " | [[1, 2], [3, 4]]\n", " | \n", " | The base case for this recursion is a 0D array:\n", " | \n", " | >>> a = np.array(1)\n", " | >>> list(a)\n", " | Traceback (most recent call last):\n", " | ...\n", " | TypeError: iteration over a 0-d array\n", " | >>> a.tolist()\n", " | 1\n", " | \n", " | tostring(...)\n", " | a.tostring(order='C')\n", " | \n", " | A compatibility alias for `tobytes`, with exactly the same behavior.\n", " | \n", " | Despite its name, it returns `bytes` not `str`\\ s.\n", " | \n", " | .. deprecated:: 1.19.0\n", " | \n", " | trace(...)\n", " | a.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)\n", " | \n", " | Return the sum along diagonals of the array.\n", " | \n", " | Refer to `numpy.trace` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.trace : equivalent function\n", " | \n", " | transpose(...)\n", " | a.transpose(*axes)\n", " | \n", " | Returns a view of the array with axes transposed.\n", " | \n", " | For a 1-D array this has no effect, as a transposed vector is simply the\n", " | same vector. To convert a 1-D array into a 2D column vector, an additional\n", " | dimension must be added. `np.atleast2d(a).T` achieves this, as does\n", " | `a[:, np.newaxis]`.\n", " | For a 2-D array, this is a standard matrix transpose.\n", " | For an n-D array, if axes are given, their order indicates how the\n", " | axes are permuted (see Examples). If axes are not provided and\n", " | ``a.shape = (i[0], i[1], ... i[n-2], i[n-1])``, then\n", " | ``a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])``.\n", " | \n", " | Parameters\n", " | ----------\n", " | axes : None, tuple of ints, or `n` ints\n", " | \n", " | * None or no argument: reverses the order of the axes.\n", " | \n", " | * tuple of ints: `i` in the `j`-th place in the tuple means `a`'s\n", " | `i`-th axis becomes `a.transpose()`'s `j`-th axis.\n", " | \n", " | * `n` ints: same as an n-tuple of the same ints (this form is\n", " | intended simply as a \"convenience\" alternative to the tuple form)\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | View of `a`, with axes suitably permuted.\n", " | \n", " | See Also\n", " | --------\n", " | ndarray.T : Array property returning the array transposed.\n", " | ndarray.reshape : Give a new shape to an array without changing its data.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> a\n", " | array([[1, 2],\n", " | [3, 4]])\n", " | >>> a.transpose()\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose((1, 0))\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose(1, 0)\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | \n", " | var(...)\n", " | a.var(axis=None, dtype=None, out=None, ddof=0, keepdims=False)\n", " | \n", " | Returns the variance of the array elements, along given axis.\n", " | \n", " | Refer to `numpy.var` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.var : equivalent function\n", " | \n", " | view(...)\n", " | a.view([dtype][, type])\n", " | \n", " | New view of array with the same data.\n", " | \n", " | .. note::\n", " | Passing None for ``dtype`` is different from omitting the parameter,\n", " | since the former invokes ``dtype(None)`` which is an alias for\n", " | ``dtype('float_')``.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : data-type or ndarray sub-class, optional\n", " | Data-type descriptor of the returned view, e.g., float32 or int16.\n", " | Omitting it results in the view having the same data-type as `a`.\n", " | This argument can also be specified as an ndarray sub-class, which\n", " | then specifies the type of the returned object (this is equivalent to\n", " | setting the ``type`` parameter).\n", " | type : Python type, optional\n", " | Type of the returned view, e.g., ndarray or matrix. Again, omission\n", " | of the parameter results in type preservation.\n", " | \n", " | Notes\n", " | -----\n", " | ``a.view()`` is used two different ways:\n", " | \n", " | ``a.view(some_dtype)`` or ``a.view(dtype=some_dtype)`` constructs a view\n", " | of the array's memory with a different data-type. This can cause a\n", " | reinterpretation of the bytes of memory.\n", " | \n", " | ``a.view(ndarray_subclass)`` or ``a.view(type=ndarray_subclass)`` just\n", " | returns an instance of `ndarray_subclass` that looks at the same array\n", " | (same shape, dtype, etc.) This does not cause a reinterpretation of the\n", " | memory.\n", " | \n", " | For ``a.view(some_dtype)``, if ``some_dtype`` has a different number of\n", " | bytes per entry than the previous dtype (for example, converting a\n", " | regular array to a structured array), then the behavior of the view\n", " | cannot be predicted just from the superficial appearance of ``a`` (shown\n", " | by ``print(a)``). It also depends on exactly how ``a`` is stored in\n", " | memory. Therefore if ``a`` is C-ordered versus fortran-ordered, versus\n", " | defined as a slice or transpose, etc., the view may give different\n", " | results.\n", " | \n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | \n", " | Viewing array data using a different type and dtype:\n", " | \n", " | >>> y = x.view(dtype=np.int16, type=np.matrix)\n", " | >>> y\n", " | matrix([[513]], dtype=int16)\n", " | >>> print(type(y))\n", " | \n", " | \n", " | Creating a view on a structured array so it can be used in calculations\n", " | \n", " | >>> x = np.array([(1, 2),(3,4)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | >>> xv = x.view(dtype=np.int8).reshape(-1,2)\n", " | >>> xv\n", " | array([[1, 2],\n", " | [3, 4]], dtype=int8)\n", " | >>> xv.mean(0)\n", " | array([2., 3.])\n", " | \n", " | Making changes to the view changes the underlying array\n", " | \n", " | >>> xv[0,1] = 20\n", " | >>> x\n", " | array([(1, 20), (3, 4)], dtype=[('a', 'i1'), ('b', 'i1')])\n", " | \n", " | Using a view to convert an array to a recarray:\n", " | \n", " | >>> z = x.view(np.recarray)\n", " | >>> z.a\n", " | array([1, 3], dtype=int8)\n", " | \n", " | Views share data:\n", " | \n", " | >>> x[0] = (9, 10)\n", " | >>> z[0]\n", " | (9, 10)\n", " | \n", " | Views that change the dtype size (bytes per entry) should normally be\n", " | avoided on arrays defined by slices, transposes, fortran-ordering, etc.:\n", " | \n", " | >>> x = np.array([[1,2,3],[4,5,6]], dtype=np.int16)\n", " | >>> y = x[:, 0:2]\n", " | >>> y\n", " | array([[1, 2],\n", " | [4, 5]], dtype=int16)\n", " | >>> y.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: To change to a dtype of a different size, the array must be C-contiguous\n", " | >>> z = y.copy()\n", " | >>> z.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | array([[(1, 2)],\n", " | [(4, 5)]], dtype=[('width', '>> x = np.array([[1.,2.],[3.,4.]])\n", " | >>> x\n", " | array([[ 1., 2.],\n", " | [ 3., 4.]])\n", " | >>> x.T\n", " | array([[ 1., 3.],\n", " | [ 2., 4.]])\n", " | >>> x = np.array([1.,2.,3.,4.])\n", " | >>> x\n", " | array([ 1., 2., 3., 4.])\n", " | >>> x.T\n", " | array([ 1., 2., 3., 4.])\n", " | \n", " | See Also\n", " | --------\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side.\n", " | \n", " | __array_struct__\n", " | Array protocol: C-struct side.\n", " | \n", " | base\n", " | Base object if memory is from some other object.\n", " | \n", " | Examples\n", " | --------\n", " | The base of an array that owns its memory is None:\n", " | \n", " | >>> x = np.array([1,2,3,4])\n", " | >>> x.base is None\n", " | True\n", " | \n", " | Slicing creates a view, whose memory is shared with x:\n", " | \n", " | >>> y = x[2:]\n", " | >>> y.base is x\n", " | True\n", " | \n", " | ctypes\n", " | An object to simplify the interaction of the array with the ctypes\n", " | module.\n", " | \n", " | This attribute creates an object that makes it easier to use arrays\n", " | when calling shared libraries with the ctypes module. The returned\n", " | object has, among others, data, shape, and strides attributes (see\n", " | Notes below) which themselves return ctypes objects that can be used\n", " | as arguments to a shared library.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | c : Python object\n", " | Possessing attributes data, shape, strides, etc.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ctypeslib\n", " | \n", " | Notes\n", " | -----\n", " | Below are the public attributes of this object which were documented\n", " | in \"Guide to NumPy\" (we have omitted undocumented public attributes,\n", " | as well as documented private attributes):\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.data\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.shape\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.strides\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.data_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.shape_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.strides_as\n", " | :noindex:\n", " | \n", " | If the ctypes module is not available, then the ctypes attribute\n", " | of array objects still returns something useful, but ctypes objects\n", " | are not returned and errors may be raised instead. In particular,\n", " | the object will still have the ``as_parameter`` attribute which will\n", " | return an integer equal to the data attribute.\n", " | \n", " | Examples\n", " | --------\n", " | >>> import ctypes\n", " | >>> x = np.array([[0, 1], [2, 3]], dtype=np.int32)\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]], dtype=int32)\n", " | >>> x.ctypes.data\n", " | 31962608 # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32))\n", " | <__main__.LP_c_uint object at 0x7ff2fc1fc200> # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32)).contents\n", " | c_uint(0)\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint64)).contents\n", " | c_ulong(4294967296)\n", " | >>> x.ctypes.shape\n", " | # may vary\n", " | >>> x.ctypes.strides\n", " | # may vary\n", " | \n", " | data\n", " | Python buffer object pointing to the start of the array's data.\n", " | \n", " | dtype\n", " | Data-type of the array's elements.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | d : numpy dtype object\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dtype\n", " | \n", " | Examples\n", " | --------\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]])\n", " | >>> x.dtype\n", " | dtype('int32')\n", " | >>> type(x.dtype)\n", " | \n", " | \n", " | flags\n", " | Information about the memory layout of the array.\n", " | \n", " | Attributes\n", " | ----------\n", " | C_CONTIGUOUS (C)\n", " | The data is in a single, C-style contiguous segment.\n", " | F_CONTIGUOUS (F)\n", " | The data is in a single, Fortran-style contiguous segment.\n", " | OWNDATA (O)\n", " | The array owns the memory it uses or borrows it from another object.\n", " | WRITEABLE (W)\n", " | The data area can be written to. Setting this to False locks\n", " | the data, making it read-only. A view (slice, etc.) inherits WRITEABLE\n", " | from its base array at creation time, but a view of a writeable\n", " | array may be subsequently locked while the base array remains writeable.\n", " | (The opposite is not true, in that a view of a locked array may not\n", " | be made writeable. However, currently, locking a base object does not\n", " | lock any views that already reference it, so under that circumstance it\n", " | is possible to alter the contents of a locked array via a previously\n", " | created writeable view onto it.) Attempting to change a non-writeable\n", " | array raises a RuntimeError exception.\n", " | ALIGNED (A)\n", " | The data and all elements are aligned appropriately for the hardware.\n", " | WRITEBACKIFCOPY (X)\n", " | This array is a copy of some other array. The C-API function\n", " | PyArray_ResolveWritebackIfCopy must be called before deallocating\n", " | to the base array will be updated with the contents of this array.\n", " | UPDATEIFCOPY (U)\n", " | (Deprecated, use WRITEBACKIFCOPY) This array is a copy of some other array.\n", " | When this array is\n", " | deallocated, the base array will be updated with the contents of\n", " | this array.\n", " | FNC\n", " | F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | FORC\n", " | F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).\n", " | BEHAVED (B)\n", " | ALIGNED and WRITEABLE.\n", " | CARRAY (CA)\n", " | BEHAVED and C_CONTIGUOUS.\n", " | FARRAY (FA)\n", " | BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | \n", " | Notes\n", " | -----\n", " | The `flags` object can be accessed dictionary-like (as in ``a.flags['WRITEABLE']``),\n", " | or by using lowercased attribute names (as in ``a.flags.writeable``). Short flag\n", " | names are only supported in dictionary access.\n", " | \n", " | Only the WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be\n", " | changed by the user, via direct assignment to the attribute or dictionary\n", " | entry, or by calling `ndarray.setflags`.\n", " | \n", " | The array flags cannot be set arbitrarily:\n", " | \n", " | - UPDATEIFCOPY can only be set ``False``.\n", " | - WRITEBACKIFCOPY can only be set ``False``.\n", " | - ALIGNED can only be set ``True`` if the data is truly aligned.\n", " | - WRITEABLE can only be set ``True`` if the array owns its own memory\n", " | or the ultimate owner of the memory exposes a writeable buffer\n", " | interface or is a string.\n", " | \n", " | Arrays can be both C-style and Fortran-style contiguous simultaneously.\n", " | This is clear for 1-dimensional arrays, but can also be true for higher\n", " | dimensional arrays.\n", " | \n", " | Even for contiguous arrays a stride for a given dimension\n", " | ``arr.strides[dim]`` may be *arbitrary* if ``arr.shape[dim] == 1``\n", " | or the array has no elements.\n", " | It does *not* generally hold that ``self.strides[-1] == self.itemsize``\n", " | for C-style contiguous arrays or ``self.strides[0] == self.itemsize`` for\n", " | Fortran-style contiguous arrays is true.\n", " | \n", " | flat\n", " | A 1-D iterator over the array.\n", " | \n", " | This is a `numpy.flatiter` instance, which acts similarly to, but is not\n", " | a subclass of, Python's built-in iterator object.\n", " | \n", " | See Also\n", " | --------\n", " | flatten : Return a copy of the array collapsed into one dimension.\n", " | \n", " | flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(1, 7).reshape(2, 3)\n", " | >>> x\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | >>> x.flat[3]\n", " | 4\n", " | >>> x.T\n", " | array([[1, 4],\n", " | [2, 5],\n", " | [3, 6]])\n", " | >>> x.T.flat[3]\n", " | 5\n", " | >>> type(x.flat)\n", " | \n", " | \n", " | An assignment example:\n", " | \n", " | >>> x.flat = 3; x\n", " | array([[3, 3, 3],\n", " | [3, 3, 3]])\n", " | >>> x.flat[[1,4]] = 1; x\n", " | array([[3, 1, 3],\n", " | [3, 1, 3]])\n", " | \n", " | imag\n", " | The imaginary part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.imag\n", " | array([ 0. , 0.70710678])\n", " | >>> x.imag.dtype\n", " | dtype('float64')\n", " | \n", " | itemsize\n", " | Length of one array element in bytes.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1,2,3], dtype=np.float64)\n", " | >>> x.itemsize\n", " | 8\n", " | >>> x = np.array([1,2,3], dtype=np.complex128)\n", " | >>> x.itemsize\n", " | 16\n", " | \n", " | nbytes\n", " | Total bytes consumed by the elements of the array.\n", " | \n", " | Notes\n", " | -----\n", " | Does not include memory consumed by non-element attributes of the\n", " | array object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3,5,2), dtype=np.complex128)\n", " | >>> x.nbytes\n", " | 480\n", " | >>> np.prod(x.shape) * x.itemsize\n", " | 480\n", " | \n", " | ndim\n", " | Number of array dimensions.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> x.ndim\n", " | 1\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.ndim\n", " | 3\n", " | \n", " | real\n", " | The real part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.real\n", " | array([ 1. , 0.70710678])\n", " | >>> x.real.dtype\n", " | dtype('float64')\n", " | \n", " | See Also\n", " | --------\n", " | numpy.real : equivalent function\n", " | \n", " | shape\n", " | Tuple of array dimensions.\n", " | \n", " | The shape property is usually used to get the current shape of an array,\n", " | but may also be used to reshape the array in-place by assigning a tuple of\n", " | array dimensions to it. As with `numpy.reshape`, one of the new shape\n", " | dimensions can be -1, in which case its value is inferred from the size of\n", " | the array and the remaining dimensions. Reshaping an array in-place will\n", " | fail if a copy is required.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3, 4])\n", " | >>> x.shape\n", " | (4,)\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.shape\n", " | (2, 3, 4)\n", " | >>> y.shape = (3, 8)\n", " | >>> y\n", " | array([[ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.]])\n", " | >>> y.shape = (3, 6)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: total size of new array must be unchanged\n", " | >>> np.zeros((4,2))[::2].shape = (-1,)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | AttributeError: Incompatible shape for in-place modification. Use\n", " | `.reshape()` to make a copy with the desired shape.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : similar function\n", " | ndarray.reshape : similar method\n", " | \n", " | size\n", " | Number of elements in the array.\n", " | \n", " | Equal to ``np.prod(a.shape)``, i.e., the product of the array's\n", " | dimensions.\n", " | \n", " | Notes\n", " | -----\n", " | `a.size` returns a standard arbitrary precision Python integer. This\n", " | may not be the case with other methods of obtaining the same value\n", " | (like the suggested ``np.prod(a.shape)``, which returns an instance\n", " | of ``np.int_``), and may be relevant if the value is used further in\n", " | calculations that may overflow a fixed size integer type.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3, 5, 2), dtype=np.complex128)\n", " | >>> x.size\n", " | 30\n", " | >>> np.prod(x.shape)\n", " | 30\n", " | \n", " | strides\n", " | Tuple of bytes to step in each dimension when traversing an array.\n", " | \n", " | The byte offset of element ``(i[0], i[1], ..., i[n])`` in an array `a`\n", " | is::\n", " | \n", " | offset = sum(np.array(i) * a.strides)\n", " | \n", " | A more detailed explanation of strides can be found in the\n", " | \"ndarray.rst\" file in the NumPy reference guide.\n", " | \n", " | Notes\n", " | -----\n", " | Imagine an array of 32-bit integers (each 4 bytes)::\n", " | \n", " | x = np.array([[0, 1, 2, 3, 4],\n", " | [5, 6, 7, 8, 9]], dtype=np.int32)\n", " | \n", " | This array is stored in memory as 40 bytes, one after the other\n", " | (known as a contiguous block of memory). The strides of an array tell\n", " | us how many bytes we have to skip in memory to move to the next position\n", " | along a certain axis. For example, we have to skip 4 bytes (1 value) to\n", " | move to the next column, but 20 bytes (5 values) to get to the same\n", " | position in the next row. As such, the strides for the array `x` will be\n", " | ``(20, 4)``.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.lib.stride_tricks.as_strided\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.reshape(np.arange(2*3*4), (2,3,4))\n", " | >>> y\n", " | array([[[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]],\n", " | [[12, 13, 14, 15],\n", " | [16, 17, 18, 19],\n", " | [20, 21, 22, 23]]])\n", " | >>> y.strides\n", " | (48, 16, 4)\n", " | >>> y[1,1,1]\n", " | 17\n", " | >>> offset=sum(y.strides * np.array((1,1,1)))\n", " | >>> offset/y.itemsize\n", " | 17\n", " | \n", " | >>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0)\n", " | >>> x.strides\n", " | (32, 4, 224, 1344)\n", " | >>> i = np.array([3,5,2,2])\n", " | >>> offset = sum(i * x.strides)\n", " | >>> x[3,5,2,2]\n", " | 813\n", " | >>> offset / x.itemsize\n", " | 813\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from ndarray:\n", " | \n", " | __hash__ = None\n", " \n", " class ndarray(builtins.object)\n", " | ndarray(shape, dtype=float, buffer=None, offset=0,\n", " | strides=None, order=None)\n", " | \n", " | An array object represents a multidimensional, homogeneous array\n", " | of fixed-size items. An associated data-type object describes the\n", " | format of each element in the array (its byte-order, how many bytes it\n", " | occupies in memory, whether it is an integer, a floating point number,\n", " | or something else, etc.)\n", " | \n", " | Arrays should be constructed using `array`, `zeros` or `empty` (refer\n", " | to the See Also section below). The parameters given here refer to\n", " | a low-level method (`ndarray(...)`) for instantiating an array.\n", " | \n", " | For more information, refer to the `numpy` module and examine the\n", " | methods and attributes of an array.\n", " | \n", " | Parameters\n", " | ----------\n", " | (for the __new__ method; see Notes below)\n", " | \n", " | shape : tuple of ints\n", " | Shape of created array.\n", " | dtype : data-type, optional\n", " | Any object that can be interpreted as a numpy data type.\n", " | buffer : object exposing buffer interface, optional\n", " | Used to fill the array with data.\n", " | offset : int, optional\n", " | Offset of array data in buffer.\n", " | strides : tuple of ints, optional\n", " | Strides of data in memory.\n", " | order : {'C', 'F'}, optional\n", " | Row-major (C-style) or column-major (Fortran-style) order.\n", " | \n", " | Attributes\n", " | ----------\n", " | T : ndarray\n", " | Transpose of the array.\n", " | data : buffer\n", " | The array's elements, in memory.\n", " | dtype : dtype object\n", " | Describes the format of the elements in the array.\n", " | flags : dict\n", " | Dictionary containing information related to memory use, e.g.,\n", " | 'C_CONTIGUOUS', 'OWNDATA', 'WRITEABLE', etc.\n", " | flat : numpy.flatiter object\n", " | Flattened version of the array as an iterator. The iterator\n", " | allows assignments, e.g., ``x.flat = 3`` (See `ndarray.flat` for\n", " | assignment examples; TODO).\n", " | imag : ndarray\n", " | Imaginary part of the array.\n", " | real : ndarray\n", " | Real part of the array.\n", " | size : int\n", " | Number of elements in the array.\n", " | itemsize : int\n", " | The memory use of each array element in bytes.\n", " | nbytes : int\n", " | The total number of bytes required to store the array data,\n", " | i.e., ``itemsize * size``.\n", " | ndim : int\n", " | The array's number of dimensions.\n", " | shape : tuple of ints\n", " | Shape of the array.\n", " | strides : tuple of ints\n", " | The step-size required to move from one element to the next in\n", " | memory. For example, a contiguous ``(3, 4)`` array of type\n", " | ``int16`` in C-order has strides ``(8, 2)``. This implies that\n", " | to move from element to element in memory requires jumps of 2 bytes.\n", " | To move from row-to-row, one needs to jump 8 bytes at a time\n", " | (``2 * 4``).\n", " | ctypes : ctypes object\n", " | Class containing properties of the array needed for interaction\n", " | with ctypes.\n", " | base : ndarray\n", " | If the array is a view into another array, that array is its `base`\n", " | (unless that array is also a view). The `base` array is where the\n", " | array data is actually stored.\n", " | \n", " | See Also\n", " | --------\n", " | array : Construct an array.\n", " | zeros : Create an array, each element of which is zero.\n", " | empty : Create an array, but leave its allocated memory unchanged (i.e.,\n", " | it contains \"garbage\").\n", " | dtype : Create a data-type.\n", " | \n", " | Notes\n", " | -----\n", " | There are two modes of creating an array using ``__new__``:\n", " | \n", " | 1. If `buffer` is None, then only `shape`, `dtype`, and `order`\n", " | are used.\n", " | 2. If `buffer` is an object exposing the buffer interface, then\n", " | all keywords are interpreted.\n", " | \n", " | No ``__init__`` method is needed because the array is fully initialized\n", " | after the ``__new__`` method.\n", " | \n", " | Examples\n", " | --------\n", " | These examples illustrate the low-level `ndarray` constructor. Refer\n", " | to the `See Also` section above for easier ways of constructing an\n", " | ndarray.\n", " | \n", " | First mode, `buffer` is None:\n", " | \n", " | >>> np.ndarray(shape=(2,2), dtype=float, order='F')\n", " | array([[0.0e+000, 0.0e+000], # random\n", " | [ nan, 2.5e-323]])\n", " | \n", " | Second mode:\n", " | \n", " | >>> np.ndarray((2,), buffer=np.array([1,2,3]),\n", " | ... offset=np.int_().itemsize,\n", " | ... dtype=int) # offset = 1*itemsize, i.e. skip first element\n", " | array([2, 3])\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | a.__array__([dtype], /) -> reference if type unchanged, copy otherwise.\n", " | \n", " | Returns either a new reference to self if dtype is not given or a new array\n", " | of provided data type if dtype is different from the current dtype of the\n", " | array.\n", " | \n", " | __array_function__(...)\n", " | \n", " | __array_prepare__(...)\n", " | a.__array_prepare__(obj) -> Object of same type as ndarray object obj.\n", " | \n", " | __array_ufunc__(...)\n", " | \n", " | __array_wrap__(...)\n", " | a.__array_wrap__(obj) -> Object of same type as ndarray object a.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __contains__(self, key, /)\n", " | Return key in self.\n", " | \n", " | __copy__(...)\n", " | a.__copy__()\n", " | \n", " | Used if :func:`copy.copy` is called on an array. Returns a copy of the array.\n", " | \n", " | Equivalent to ``a.copy(order='K')``.\n", " | \n", " | __deepcopy__(...)\n", " | a.__deepcopy__(memo, /) -> Deep copy of array.\n", " | \n", " | Used if :func:`copy.deepcopy` is called on an array.\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | Default object formatter.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __iadd__(self, value, /)\n", " | Return self+=value.\n", " | \n", " | __iand__(self, value, /)\n", " | Return self&=value.\n", " | \n", " | __ifloordiv__(self, value, /)\n", " | Return self//=value.\n", " | \n", " | __ilshift__(self, value, /)\n", " | Return self<<=value.\n", " | \n", " | __imatmul__(self, value, /)\n", " | Return self@=value.\n", " | \n", " | __imod__(self, value, /)\n", " | Return self%=value.\n", " | \n", " | __imul__(self, value, /)\n", " | Return self*=value.\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __ior__(self, value, /)\n", " | Return self|=value.\n", " | \n", " | __ipow__(self, value, /)\n", " | Return self**=value.\n", " | \n", " | __irshift__(self, value, /)\n", " | Return self>>=value.\n", " | \n", " | __isub__(self, value, /)\n", " | Return self-=value.\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __itruediv__(self, value, /)\n", " | Return self/=value.\n", " | \n", " | __ixor__(self, value, /)\n", " | Return self^=value.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setitem__(self, key, value, /)\n", " | Set self[key] to value.\n", " | \n", " | __setstate__(...)\n", " | a.__setstate__(state, /)\n", " | \n", " | For unpickling.\n", " | \n", " | The `state` argument must be a sequence that contains the following\n", " | elements:\n", " | \n", " | Parameters\n", " | ----------\n", " | version : int\n", " | optional pickle version. If omitted defaults to 0.\n", " | shape : tuple\n", " | dtype : data-type\n", " | isFortran : bool\n", " | rawdata : string or list\n", " | a binary string with the data (or a list if 'a' is an object array)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | a.all(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if all elements evaluate to True.\n", " | \n", " | Refer to `numpy.all` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.all : equivalent function\n", " | \n", " | any(...)\n", " | a.any(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if any of the elements of `a` evaluate to True.\n", " | \n", " | Refer to `numpy.any` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.any : equivalent function\n", " | \n", " | argmax(...)\n", " | a.argmax(axis=None, out=None)\n", " | \n", " | Return indices of the maximum values along the given axis.\n", " | \n", " | Refer to `numpy.argmax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmax : equivalent function\n", " | \n", " | argmin(...)\n", " | a.argmin(axis=None, out=None)\n", " | \n", " | Return indices of the minimum values along the given axis of `a`.\n", " | \n", " | Refer to `numpy.argmin` for detailed documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmin : equivalent function\n", " | \n", " | argpartition(...)\n", " | a.argpartition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Returns the indices that would partition this array.\n", " | \n", " | Refer to `numpy.argpartition` for full documentation.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argpartition : equivalent function\n", " | \n", " | argsort(...)\n", " | a.argsort(axis=-1, kind=None, order=None)\n", " | \n", " | Returns the indices that would sort this array.\n", " | \n", " | Refer to `numpy.argsort` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argsort : equivalent function\n", " | \n", " | astype(...)\n", " | a.astype(dtype, order='K', casting='unsafe', subok=True, copy=True)\n", " | \n", " | Copy of the array, cast to a specified type.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | Typecode or data-type to which the array is cast.\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout order of the result.\n", " | 'C' means C order, 'F' means Fortran order, 'A'\n", " | means 'F' order if all the arrays are Fortran contiguous,\n", " | 'C' order otherwise, and 'K' means as close to the\n", " | order the array elements appear in memory as possible.\n", " | Default is 'K'.\n", " | casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n", " | Controls what kind of data casting may occur. Defaults to 'unsafe'\n", " | for backwards compatibility.\n", " | \n", " | * 'no' means the data types should not be cast at all.\n", " | * 'equiv' means only byte-order changes are allowed.\n", " | * 'safe' means only casts which can preserve values are allowed.\n", " | * 'same_kind' means only safe casts or casts within a kind,\n", " | like float64 to float32, are allowed.\n", " | * 'unsafe' means any data conversions may be done.\n", " | subok : bool, optional\n", " | If True, then sub-classes will be passed-through (default), otherwise\n", " | the returned array will be forced to be a base-class array.\n", " | copy : bool, optional\n", " | By default, astype always returns a newly allocated array. If this\n", " | is set to false, and the `dtype`, `order`, and `subok`\n", " | requirements are satisfied, the input array is returned instead\n", " | of a copy.\n", " | \n", " | Returns\n", " | -------\n", " | arr_t : ndarray\n", " | Unless `copy` is False and the other conditions for returning the input\n", " | array are satisfied (see description for `copy` input parameter), `arr_t`\n", " | is a new array of the same shape as the input array, with dtype, order\n", " | given by `dtype`, `order`.\n", " | \n", " | Notes\n", " | -----\n", " | .. versionchanged:: 1.17.0\n", " | Casting between a simple data type and a structured one is possible only\n", " | for \"unsafe\" casting. Casting to multiple fields is allowed, but\n", " | casting from multiple fields is not.\n", " | \n", " | .. versionchanged:: 1.9.0\n", " | Casting from numeric to string types in 'safe' casting mode requires\n", " | that the string dtype length is long enough to store the max\n", " | integer/float value converted.\n", " | \n", " | Raises\n", " | ------\n", " | ComplexWarning\n", " | When casting from complex to float or int. To avoid this,\n", " | one should use ``a.real.astype(t)``.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 2.5])\n", " | >>> x\n", " | array([1. , 2. , 2.5])\n", " | \n", " | >>> x.astype(int)\n", " | array([1, 2, 2])\n", " | \n", " | byteswap(...)\n", " | a.byteswap(inplace=False)\n", " | \n", " | Swap the bytes of the array elements\n", " | \n", " | Toggle between low-endian and big-endian data representation by\n", " | returning a byteswapped array, optionally swapped in-place.\n", " | Arrays of byte-strings are not swapped. The real and imaginary\n", " | parts of a complex number are swapped individually.\n", " | \n", " | Parameters\n", " | ----------\n", " | inplace : bool, optional\n", " | If ``True``, swap bytes in-place, default is ``False``.\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | The byteswapped array. If `inplace` is ``True``, this is\n", " | a view to self.\n", " | \n", " | Examples\n", " | --------\n", " | >>> A = np.array([1, 256, 8755], dtype=np.int16)\n", " | >>> list(map(hex, A))\n", " | ['0x1', '0x100', '0x2233']\n", " | >>> A.byteswap(inplace=True)\n", " | array([ 256, 1, 13090], dtype=int16)\n", " | >>> list(map(hex, A))\n", " | ['0x100', '0x1', '0x3322']\n", " | \n", " | Arrays of byte-strings are not swapped\n", " | \n", " | >>> A = np.array([b'ceg', b'fac'])\n", " | >>> A.byteswap()\n", " | array([b'ceg', b'fac'], dtype='|S3')\n", " | \n", " | ``A.newbyteorder().byteswap()`` produces an array with the same values\n", " | but different representation in memory\n", " | \n", " | >>> A = np.array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,\n", " | 0, 0], dtype=uint8)\n", " | >>> A.newbyteorder().byteswap(inplace=True)\n", " | array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0,\n", " | 0, 3], dtype=uint8)\n", " | \n", " | choose(...)\n", " | a.choose(choices, out=None, mode='raise')\n", " | \n", " | Use an index array to construct a new array from a set of choices.\n", " | \n", " | Refer to `numpy.choose` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.choose : equivalent function\n", " | \n", " | clip(...)\n", " | a.clip(min=None, max=None, out=None, **kwargs)\n", " | \n", " | Return an array whose values are limited to ``[min, max]``.\n", " | One of max or min must be given.\n", " | \n", " | Refer to `numpy.clip` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.clip : equivalent function\n", " | \n", " | compress(...)\n", " | a.compress(condition, axis=None, out=None)\n", " | \n", " | Return selected slices of this array along given axis.\n", " | \n", " | Refer to `numpy.compress` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.compress : equivalent function\n", " | \n", " | conj(...)\n", " | a.conj()\n", " | \n", " | Complex-conjugate all elements.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | conjugate(...)\n", " | a.conjugate()\n", " | \n", " | Return the complex conjugate, element-wise.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | copy(...)\n", " | a.copy(order='C')\n", " | \n", " | Return a copy of the array.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout of the copy. 'C' means C-order,\n", " | 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,\n", " | 'C' otherwise. 'K' means match the layout of `a` as closely\n", " | as possible. (Note that this function and :func:`numpy.copy` are very\n", " | similar, but have different default values for their order=\n", " | arguments.)\n", " | \n", " | See also\n", " | --------\n", " | numpy.copy\n", " | numpy.copyto\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([[1,2,3],[4,5,6]], order='F')\n", " | \n", " | >>> y = x.copy()\n", " | \n", " | >>> x.fill(0)\n", " | \n", " | >>> x\n", " | array([[0, 0, 0],\n", " | [0, 0, 0]])\n", " | \n", " | >>> y\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | \n", " | >>> y.flags['C_CONTIGUOUS']\n", " | True\n", " | \n", " | cumprod(...)\n", " | a.cumprod(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative product of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumprod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumprod : equivalent function\n", " | \n", " | cumsum(...)\n", " | a.cumsum(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative sum of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumsum` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumsum : equivalent function\n", " | \n", " | diagonal(...)\n", " | a.diagonal(offset=0, axis1=0, axis2=1)\n", " | \n", " | Return specified diagonals. In NumPy 1.9 the returned array is a\n", " | read-only view instead of a copy as in previous NumPy versions. In\n", " | a future version the read-only restriction will be removed.\n", " | \n", " | Refer to :func:`numpy.diagonal` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.diagonal : equivalent function\n", " | \n", " | dot(...)\n", " | a.dot(b, out=None)\n", " | \n", " | Dot product of two arrays.\n", " | \n", " | Refer to `numpy.dot` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dot : equivalent function\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.eye(2)\n", " | >>> b = np.ones((2, 2)) * 2\n", " | >>> a.dot(b)\n", " | array([[2., 2.],\n", " | [2., 2.]])\n", " | \n", " | This array method can be conveniently chained:\n", " | \n", " | >>> a.dot(b).dot(b)\n", " | array([[8., 8.],\n", " | [8., 8.]])\n", " | \n", " | dump(...)\n", " | a.dump(file)\n", " | \n", " | Dump a pickle of the array to the specified file.\n", " | The array can be read back with pickle.load or numpy.load.\n", " | \n", " | Parameters\n", " | ----------\n", " | file : str or Path\n", " | A string naming the dump file.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | dumps(...)\n", " | a.dumps()\n", " | \n", " | Returns the pickle of the array as a string.\n", " | pickle.loads or numpy.loads will convert the string back to an array.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | fill(...)\n", " | a.fill(value)\n", " | \n", " | Fill the array with a scalar value.\n", " | \n", " | Parameters\n", " | ----------\n", " | value : scalar\n", " | All elements of `a` will be assigned this value.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([1, 2])\n", " | >>> a.fill(0)\n", " | >>> a\n", " | array([0, 0])\n", " | >>> a = np.empty(2)\n", " | >>> a.fill(1)\n", " | >>> a\n", " | array([1., 1.])\n", " | \n", " | flatten(...)\n", " | a.flatten(order='C')\n", " | \n", " | Return a copy of the array collapsed into one dimension.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | 'C' means to flatten in row-major (C-style) order.\n", " | 'F' means to flatten in column-major (Fortran-\n", " | style) order. 'A' means to flatten in column-major\n", " | order if `a` is Fortran *contiguous* in memory,\n", " | row-major order otherwise. 'K' means to flatten\n", " | `a` in the order the elements occur in memory.\n", " | The default is 'C'.\n", " | \n", " | Returns\n", " | -------\n", " | y : ndarray\n", " | A copy of the input array, flattened to one dimension.\n", " | \n", " | See Also\n", " | --------\n", " | ravel : Return a flattened array.\n", " | flat : A 1-D flat iterator over the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,2], [3,4]])\n", " | >>> a.flatten()\n", " | array([1, 2, 3, 4])\n", " | >>> a.flatten('F')\n", " | array([1, 3, 2, 4])\n", " | \n", " | getfield(...)\n", " | a.getfield(dtype, offset=0)\n", " | \n", " | Returns a field of the given array as a certain type.\n", " | \n", " | A field is a view of the array data with a given data-type. The values in\n", " | the view are determined by the given type and the offset into the current\n", " | array in bytes. The offset needs to be such that the view dtype fits in the\n", " | array dtype; for example an array of dtype complex128 has 16-byte elements.\n", " | If taking a view with a 32-bit integer (4 bytes), the offset needs to be\n", " | between 0 and 12 bytes.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | The data type of the view. The dtype size of the view can not be larger\n", " | than that of the array itself.\n", " | offset : int\n", " | Number of bytes to skip before beginning the element view.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.diag([1.+1.j]*2)\n", " | >>> x[1, 1] = 2 + 4.j\n", " | >>> x\n", " | array([[1.+1.j, 0.+0.j],\n", " | [0.+0.j, 2.+4.j]])\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0.],\n", " | [0., 2.]])\n", " | \n", " | By choosing an offset of 8 bytes we can select the complex part of the\n", " | array for our view:\n", " | \n", " | >>> x.getfield(np.float64, offset=8)\n", " | array([[1., 0.],\n", " | [0., 4.]])\n", " | \n", " | item(...)\n", " | a.item(*args)\n", " | \n", " | Copy an element of an array to a standard Python scalar and return it.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments (variable number and type)\n", " | \n", " | * none: in this case, the method only works for arrays\n", " | with one element (`a.size == 1`), which element is\n", " | copied into a standard Python scalar object and returned.\n", " | \n", " | * int_type: this argument is interpreted as a flat index into\n", " | the array, specifying which element to copy and return.\n", " | \n", " | * tuple of int_types: functions as does a single int_type argument,\n", " | except that the argument is interpreted as an nd-index into the\n", " | array.\n", " | \n", " | Returns\n", " | -------\n", " | z : Standard Python scalar object\n", " | A copy of the specified element of the array as a suitable\n", " | Python scalar\n", " | \n", " | Notes\n", " | -----\n", " | When the data type of `a` is longdouble or clongdouble, item() returns\n", " | a scalar array object because there is no available Python scalar that\n", " | would not lose information. Void arrays return a buffer object for item(),\n", " | unless fields are defined, in which case a tuple is returned.\n", " | \n", " | `item` is very similar to a[args], except, instead of an array scalar,\n", " | a standard Python scalar is returned. This can be useful for speeding up\n", " | access to elements of the array and doing arithmetic on elements of the\n", " | array using Python's optimized math.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.item(3)\n", " | 1\n", " | >>> x.item(7)\n", " | 0\n", " | >>> x.item((0, 1))\n", " | 2\n", " | >>> x.item((2, 2))\n", " | 1\n", " | \n", " | itemset(...)\n", " | a.itemset(*args)\n", " | \n", " | Insert scalar into an array (scalar is cast to array's dtype, if possible)\n", " | \n", " | There must be at least 1 argument, and define the last argument\n", " | as *item*. Then, ``a.itemset(*args)`` is equivalent to but faster\n", " | than ``a[args] = item``. The item should be a scalar value and `args`\n", " | must select a single item in the array `a`.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments\n", " | If one argument: a scalar, only used in case `a` is of size 1.\n", " | If two arguments: the last argument is the value to be set\n", " | and must be a scalar, the first argument specifies a single array\n", " | element location. It is either an int or a tuple.\n", " | \n", " | Notes\n", " | -----\n", " | Compared to indexing syntax, `itemset` provides some speed increase\n", " | for placing a scalar into a particular location in an `ndarray`,\n", " | if you must do this. However, generally this is discouraged:\n", " | among other problems, it complicates the appearance of the code.\n", " | Also, when using `itemset` (and `item`) inside a loop, be sure\n", " | to assign the methods to a local variable to avoid the attribute\n", " | look-up at each loop iteration.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.itemset(4, 0)\n", " | >>> x.itemset((2, 2), 9)\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 0, 6],\n", " | [1, 0, 9]])\n", " | \n", " | max(...)\n", " | a.max(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the maximum along a given axis.\n", " | \n", " | Refer to `numpy.amax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amax : equivalent function\n", " | \n", " | mean(...)\n", " | a.mean(axis=None, dtype=None, out=None, keepdims=False)\n", " | \n", " | Returns the average of the array elements along given axis.\n", " | \n", " | Refer to `numpy.mean` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.mean : equivalent function\n", " | \n", " | min(...)\n", " | a.min(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the minimum along a given axis.\n", " | \n", " | Refer to `numpy.amin` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amin : equivalent function\n", " | \n", " | newbyteorder(...)\n", " | arr.newbyteorder(new_order='S')\n", " | \n", " | Return the array with the same data viewed with a different byte order.\n", " | \n", " | Equivalent to::\n", " | \n", " | arr.view(arr.dtype.newbytorder(new_order))\n", " | \n", " | Changes are also made in all fields and sub-arrays of the array data\n", " | type.\n", " | \n", " | \n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : string, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | below. `new_order` codes can be any of:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_arr : array\n", " | New array object with the dtype reflecting given change to the\n", " | byte order.\n", " | \n", " | nonzero(...)\n", " | a.nonzero()\n", " | \n", " | Return the indices of the elements that are non-zero.\n", " | \n", " | Refer to `numpy.nonzero` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.nonzero : equivalent function\n", " | \n", " | partition(...)\n", " | a.partition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Rearranges the elements in the array in such a way that the value of the\n", " | element in kth position is in the position it would be in a sorted array.\n", " | All elements smaller than the kth element are moved before this element and\n", " | all equal or greater are moved behind it. The ordering of the elements in\n", " | the two partitions is undefined.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | Parameters\n", " | ----------\n", " | kth : int or sequence of ints\n", " | Element index to partition by. The kth element value will be in its\n", " | final sorted position and all smaller elements will be moved before it\n", " | and all equal or greater elements behind it.\n", " | The order of all elements in the partitions is undefined.\n", " | If provided with a sequence of kth it will partition all elements\n", " | indexed by kth of them into their sorted position at once.\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'introselect'}, optional\n", " | Selection algorithm. Default is 'introselect'.\n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need to be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.partition : Return a parititioned copy of an array.\n", " | argpartition : Indirect partition.\n", " | sort : Full sort.\n", " | \n", " | Notes\n", " | -----\n", " | See ``np.partition`` for notes on the different algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([3, 4, 2, 1])\n", " | >>> a.partition(3)\n", " | >>> a\n", " | array([2, 1, 3, 4])\n", " | \n", " | >>> a.partition((1, 3))\n", " | >>> a\n", " | array([1, 2, 3, 4])\n", " | \n", " | prod(...)\n", " | a.prod(axis=None, dtype=None, out=None, keepdims=False, initial=1, where=True)\n", " | \n", " | Return the product of the array elements over the given axis\n", " | \n", " | Refer to `numpy.prod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.prod : equivalent function\n", " | \n", " | ptp(...)\n", " | a.ptp(axis=None, out=None, keepdims=False)\n", " | \n", " | Peak to peak (maximum - minimum) value along a given axis.\n", " | \n", " | Refer to `numpy.ptp` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ptp : equivalent function\n", " | \n", " | put(...)\n", " | a.put(indices, values, mode='raise')\n", " | \n", " | Set ``a.flat[n] = values[n]`` for all `n` in indices.\n", " | \n", " | Refer to `numpy.put` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.put : equivalent function\n", " | \n", " | ravel(...)\n", " | a.ravel([order])\n", " | \n", " | Return a flattened array.\n", " | \n", " | Refer to `numpy.ravel` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ravel : equivalent function\n", " | \n", " | ndarray.flat : a flat iterator on the array.\n", " | \n", " | repeat(...)\n", " | a.repeat(repeats, axis=None)\n", " | \n", " | Repeat elements of an array.\n", " | \n", " | Refer to `numpy.repeat` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.repeat : equivalent function\n", " | \n", " | reshape(...)\n", " | a.reshape(shape, order='C')\n", " | \n", " | Returns an array containing the same data with a new shape.\n", " | \n", " | Refer to `numpy.reshape` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : equivalent function\n", " | \n", " | Notes\n", " | -----\n", " | Unlike the free function `numpy.reshape`, this method on `ndarray` allows\n", " | the elements of the shape parameter to be passed in as separate arguments.\n", " | For example, ``a.reshape(10, 11)`` is equivalent to\n", " | ``a.reshape((10, 11))``.\n", " | \n", " | resize(...)\n", " | a.resize(new_shape, refcheck=True)\n", " | \n", " | Change shape and size of array in-place.\n", " | \n", " | Parameters\n", " | ----------\n", " | new_shape : tuple of ints, or `n` ints\n", " | Shape of resized array.\n", " | refcheck : bool, optional\n", " | If False, reference count will not be checked. Default is True.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | Raises\n", " | ------\n", " | ValueError\n", " | If `a` does not own its own data or references or views to it exist,\n", " | and the data memory must be changed.\n", " | PyPy only: will always raise if the data memory must be changed, since\n", " | there is no reliable way to determine if references or views to it\n", " | exist.\n", " | \n", " | SystemError\n", " | If the `order` keyword argument is specified. This behaviour is a\n", " | bug in NumPy.\n", " | \n", " | See Also\n", " | --------\n", " | resize : Return a new array with the specified shape.\n", " | \n", " | Notes\n", " | -----\n", " | This reallocates space for the data area if necessary.\n", " | \n", " | Only contiguous arrays (data elements consecutive in memory) can be\n", " | resized.\n", " | \n", " | The purpose of the reference count check is to make sure you\n", " | do not use this array as a buffer for another Python object and then\n", " | reallocate the memory. However, reference counts can increase in\n", " | other ways so if you are sure that you have not shared the memory\n", " | for this array with another Python object, then you may safely set\n", " | `refcheck` to False.\n", " | \n", " | Examples\n", " | --------\n", " | Shrinking an array: array is flattened (in the order that the data are\n", " | stored in memory), resized, and reshaped:\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='C')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [1]])\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='F')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [2]])\n", " | \n", " | Enlarging an array: as above, but missing entries are filled with zeros:\n", " | \n", " | >>> b = np.array([[0, 1], [2, 3]])\n", " | >>> b.resize(2, 3) # new_shape parameter doesn't have to be a tuple\n", " | >>> b\n", " | array([[0, 1, 2],\n", " | [3, 0, 0]])\n", " | \n", " | Referencing an array prevents resizing...\n", " | \n", " | >>> c = a\n", " | >>> a.resize((1, 1))\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: cannot resize an array that references or is referenced ...\n", " | \n", " | Unless `refcheck` is False:\n", " | \n", " | >>> a.resize((1, 1), refcheck=False)\n", " | >>> a\n", " | array([[0]])\n", " | >>> c\n", " | array([[0]])\n", " | \n", " | round(...)\n", " | a.round(decimals=0, out=None)\n", " | \n", " | Return `a` with each element rounded to the given number of decimals.\n", " | \n", " | Refer to `numpy.around` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.around : equivalent function\n", " | \n", " | searchsorted(...)\n", " | a.searchsorted(v, side='left', sorter=None)\n", " | \n", " | Find indices where elements of v should be inserted in a to maintain order.\n", " | \n", " | For full documentation, see `numpy.searchsorted`\n", " | \n", " | See Also\n", " | --------\n", " | numpy.searchsorted : equivalent function\n", " | \n", " | setfield(...)\n", " | a.setfield(val, dtype, offset=0)\n", " | \n", " | Put a value into a specified place in a field defined by a data-type.\n", " | \n", " | Place `val` into `a`'s field defined by `dtype` and beginning `offset`\n", " | bytes into the field.\n", " | \n", " | Parameters\n", " | ----------\n", " | val : object\n", " | Value to be placed in field.\n", " | dtype : dtype object\n", " | Data-type of the field in which to place `val`.\n", " | offset : int, optional\n", " | The number of bytes into the field at which to place `val`.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | See Also\n", " | --------\n", " | getfield\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.eye(3)\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | >>> x.setfield(3, np.int32)\n", " | >>> x.getfield(np.int32)\n", " | array([[3, 3, 3],\n", " | [3, 3, 3],\n", " | [3, 3, 3]], dtype=int32)\n", " | >>> x\n", " | array([[1.0e+000, 1.5e-323, 1.5e-323],\n", " | [1.5e-323, 1.0e+000, 1.5e-323],\n", " | [1.5e-323, 1.5e-323, 1.0e+000]])\n", " | >>> x.setfield(np.eye(3), np.int32)\n", " | >>> x\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | \n", " | setflags(...)\n", " | a.setflags(write=None, align=None, uic=None)\n", " | \n", " | Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY),\n", " | respectively.\n", " | \n", " | These Boolean-valued flags affect how numpy interprets the memory\n", " | area used by `a` (see Notes below). The ALIGNED flag can only\n", " | be set to True if the data is actually aligned according to the type.\n", " | The WRITEBACKIFCOPY and (deprecated) UPDATEIFCOPY flags can never be set\n", " | to True. The flag WRITEABLE can only be set to True if the array owns its\n", " | own memory, or the ultimate owner of the memory exposes a writeable buffer\n", " | interface, or is a string. (The exception for string is made so that\n", " | unpickling can be done without copying memory.)\n", " | \n", " | Parameters\n", " | ----------\n", " | write : bool, optional\n", " | Describes whether or not `a` can be written to.\n", " | align : bool, optional\n", " | Describes whether or not `a` is aligned properly for its type.\n", " | uic : bool, optional\n", " | Describes whether or not `a` is a copy of another \"base\" array.\n", " | \n", " | Notes\n", " | -----\n", " | Array flags provide information about how the memory area used\n", " | for the array is to be interpreted. There are 7 Boolean flags\n", " | in use, only four of which can be changed by the user:\n", " | WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED.\n", " | \n", " | WRITEABLE (W) the data area can be written to;\n", " | \n", " | ALIGNED (A) the data and strides are aligned appropriately for the hardware\n", " | (as determined by the compiler);\n", " | \n", " | UPDATEIFCOPY (U) (deprecated), replaced by WRITEBACKIFCOPY;\n", " | \n", " | WRITEBACKIFCOPY (X) this array is a copy of some other array (referenced\n", " | by .base). When the C-API function PyArray_ResolveWritebackIfCopy is\n", " | called, the base array will be updated with the contents of this array.\n", " | \n", " | All flags can be accessed using the single (upper case) letter as well\n", " | as the full name.\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.array([[3, 1, 7],\n", " | ... [2, 0, 0],\n", " | ... [8, 5, 9]])\n", " | >>> y\n", " | array([[3, 1, 7],\n", " | [2, 0, 0],\n", " | [8, 5, 9]])\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : True\n", " | ALIGNED : True\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(write=0, align=0)\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : False\n", " | ALIGNED : False\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(uic=1)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: cannot set WRITEBACKIFCOPY flag to True\n", " | \n", " | sort(...)\n", " | a.sort(axis=-1, kind=None, order=None)\n", " | \n", " | Sort an array in-place. Refer to `numpy.sort` for full documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional\n", " | Sorting algorithm. The default is 'quicksort'. Note that both 'stable'\n", " | and 'mergesort' use timsort under the covers and, in general, the\n", " | actual implementation will vary with datatype. The 'mergesort' option\n", " | is retained for backwards compatibility.\n", " | \n", " | .. versionchanged:: 1.15.0.\n", " | The 'stable' option was added.\n", " | \n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.sort : Return a sorted copy of an array.\n", " | numpy.argsort : Indirect sort.\n", " | numpy.lexsort : Indirect stable sort on multiple keys.\n", " | numpy.searchsorted : Find elements in sorted array.\n", " | numpy.partition: Partial sort.\n", " | \n", " | Notes\n", " | -----\n", " | See `numpy.sort` for notes on the different sorting algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,4], [3,1]])\n", " | >>> a.sort(axis=1)\n", " | >>> a\n", " | array([[1, 4],\n", " | [1, 3]])\n", " | >>> a.sort(axis=0)\n", " | >>> a\n", " | array([[1, 3],\n", " | [1, 4]])\n", " | \n", " | Use the `order` keyword to specify a field to use when sorting a\n", " | structured array:\n", " | \n", " | >>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])\n", " | >>> a.sort(order='y')\n", " | >>> a\n", " | array([(b'c', 1), (b'a', 2)],\n", " | dtype=[('x', 'S1'), ('y', '>> x = np.array([[0, 1], [2, 3]], dtype='>> x.tobytes()\n", " | b'\\x00\\x00\\x01\\x00\\x02\\x00\\x03\\x00'\n", " | >>> x.tobytes('C') == x.tobytes()\n", " | True\n", " | >>> x.tobytes('F')\n", " | b'\\x00\\x00\\x02\\x00\\x01\\x00\\x03\\x00'\n", " | \n", " | tofile(...)\n", " | a.tofile(fid, sep=\"\", format=\"%s\")\n", " | \n", " | Write array to a file as text or binary (default).\n", " | \n", " | Data is always written in 'C' order, independent of the order of `a`.\n", " | The data produced by this method can be recovered using the function\n", " | fromfile().\n", " | \n", " | Parameters\n", " | ----------\n", " | fid : file or str or Path\n", " | An open file object, or a string containing a filename.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | sep : str\n", " | Separator between array items for text output.\n", " | If \"\" (empty), a binary file is written, equivalent to\n", " | ``file.write(a.tobytes())``.\n", " | format : str\n", " | Format string for text file output.\n", " | Each entry in the array is formatted to text by first converting\n", " | it to the closest Python type, and then using \"format\" % item.\n", " | \n", " | Notes\n", " | -----\n", " | This is a convenience function for quick storage of array data.\n", " | Information on endianness and precision is lost, so this method is not a\n", " | good choice for files intended to archive data or transport data between\n", " | machines with different endianness. Some of these problems can be overcome\n", " | by outputting the data as text files, at the expense of speed and file\n", " | size.\n", " | \n", " | When fid is a file object, array contents are directly written to the\n", " | file, bypassing the file object's ``write`` method. As a result, tofile\n", " | cannot be used with files objects supporting compression (e.g., GzipFile)\n", " | or file-like objects that do not support ``fileno()`` (e.g., BytesIO).\n", " | \n", " | tolist(...)\n", " | a.tolist()\n", " | \n", " | Return the array as an ``a.ndim``-levels deep nested list of Python scalars.\n", " | \n", " | Return a copy of the array data as a (nested) Python list.\n", " | Data items are converted to the nearest compatible builtin Python type, via\n", " | the `~numpy.ndarray.item` function.\n", " | \n", " | If ``a.ndim`` is 0, then since the depth of the nested list is 0, it will\n", " | not be a list at all, but a simple Python scalar.\n", " | \n", " | Parameters\n", " | ----------\n", " | none\n", " | \n", " | Returns\n", " | -------\n", " | y : object, or list of object, or list of list of object, or ...\n", " | The possibly nested list of array elements.\n", " | \n", " | Notes\n", " | -----\n", " | The array may be recreated via ``a = np.array(a.tolist())``, although this\n", " | may sometimes lose precision.\n", " | \n", " | Examples\n", " | --------\n", " | For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``,\n", " | except that ``tolist`` changes numpy scalars to Python scalars:\n", " | \n", " | >>> a = np.uint32([1, 2])\n", " | >>> a_list = list(a)\n", " | >>> a_list\n", " | [1, 2]\n", " | >>> type(a_list[0])\n", " | \n", " | >>> a_tolist = a.tolist()\n", " | >>> a_tolist\n", " | [1, 2]\n", " | >>> type(a_tolist[0])\n", " | \n", " | \n", " | Additionally, for a 2D array, ``tolist`` applies recursively:\n", " | \n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> list(a)\n", " | [array([1, 2]), array([3, 4])]\n", " | >>> a.tolist()\n", " | [[1, 2], [3, 4]]\n", " | \n", " | The base case for this recursion is a 0D array:\n", " | \n", " | >>> a = np.array(1)\n", " | >>> list(a)\n", " | Traceback (most recent call last):\n", " | ...\n", " | TypeError: iteration over a 0-d array\n", " | >>> a.tolist()\n", " | 1\n", " | \n", " | tostring(...)\n", " | a.tostring(order='C')\n", " | \n", " | A compatibility alias for `tobytes`, with exactly the same behavior.\n", " | \n", " | Despite its name, it returns `bytes` not `str`\\ s.\n", " | \n", " | .. deprecated:: 1.19.0\n", " | \n", " | trace(...)\n", " | a.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)\n", " | \n", " | Return the sum along diagonals of the array.\n", " | \n", " | Refer to `numpy.trace` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.trace : equivalent function\n", " | \n", " | transpose(...)\n", " | a.transpose(*axes)\n", " | \n", " | Returns a view of the array with axes transposed.\n", " | \n", " | For a 1-D array this has no effect, as a transposed vector is simply the\n", " | same vector. To convert a 1-D array into a 2D column vector, an additional\n", " | dimension must be added. `np.atleast2d(a).T` achieves this, as does\n", " | `a[:, np.newaxis]`.\n", " | For a 2-D array, this is a standard matrix transpose.\n", " | For an n-D array, if axes are given, their order indicates how the\n", " | axes are permuted (see Examples). If axes are not provided and\n", " | ``a.shape = (i[0], i[1], ... i[n-2], i[n-1])``, then\n", " | ``a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])``.\n", " | \n", " | Parameters\n", " | ----------\n", " | axes : None, tuple of ints, or `n` ints\n", " | \n", " | * None or no argument: reverses the order of the axes.\n", " | \n", " | * tuple of ints: `i` in the `j`-th place in the tuple means `a`'s\n", " | `i`-th axis becomes `a.transpose()`'s `j`-th axis.\n", " | \n", " | * `n` ints: same as an n-tuple of the same ints (this form is\n", " | intended simply as a \"convenience\" alternative to the tuple form)\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | View of `a`, with axes suitably permuted.\n", " | \n", " | See Also\n", " | --------\n", " | ndarray.T : Array property returning the array transposed.\n", " | ndarray.reshape : Give a new shape to an array without changing its data.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> a\n", " | array([[1, 2],\n", " | [3, 4]])\n", " | >>> a.transpose()\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose((1, 0))\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose(1, 0)\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | \n", " | var(...)\n", " | a.var(axis=None, dtype=None, out=None, ddof=0, keepdims=False)\n", " | \n", " | Returns the variance of the array elements, along given axis.\n", " | \n", " | Refer to `numpy.var` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.var : equivalent function\n", " | \n", " | view(...)\n", " | a.view([dtype][, type])\n", " | \n", " | New view of array with the same data.\n", " | \n", " | .. note::\n", " | Passing None for ``dtype`` is different from omitting the parameter,\n", " | since the former invokes ``dtype(None)`` which is an alias for\n", " | ``dtype('float_')``.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : data-type or ndarray sub-class, optional\n", " | Data-type descriptor of the returned view, e.g., float32 or int16.\n", " | Omitting it results in the view having the same data-type as `a`.\n", " | This argument can also be specified as an ndarray sub-class, which\n", " | then specifies the type of the returned object (this is equivalent to\n", " | setting the ``type`` parameter).\n", " | type : Python type, optional\n", " | Type of the returned view, e.g., ndarray or matrix. Again, omission\n", " | of the parameter results in type preservation.\n", " | \n", " | Notes\n", " | -----\n", " | ``a.view()`` is used two different ways:\n", " | \n", " | ``a.view(some_dtype)`` or ``a.view(dtype=some_dtype)`` constructs a view\n", " | of the array's memory with a different data-type. This can cause a\n", " | reinterpretation of the bytes of memory.\n", " | \n", " | ``a.view(ndarray_subclass)`` or ``a.view(type=ndarray_subclass)`` just\n", " | returns an instance of `ndarray_subclass` that looks at the same array\n", " | (same shape, dtype, etc.) This does not cause a reinterpretation of the\n", " | memory.\n", " | \n", " | For ``a.view(some_dtype)``, if ``some_dtype`` has a different number of\n", " | bytes per entry than the previous dtype (for example, converting a\n", " | regular array to a structured array), then the behavior of the view\n", " | cannot be predicted just from the superficial appearance of ``a`` (shown\n", " | by ``print(a)``). It also depends on exactly how ``a`` is stored in\n", " | memory. Therefore if ``a`` is C-ordered versus fortran-ordered, versus\n", " | defined as a slice or transpose, etc., the view may give different\n", " | results.\n", " | \n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | \n", " | Viewing array data using a different type and dtype:\n", " | \n", " | >>> y = x.view(dtype=np.int16, type=np.matrix)\n", " | >>> y\n", " | matrix([[513]], dtype=int16)\n", " | >>> print(type(y))\n", " | \n", " | \n", " | Creating a view on a structured array so it can be used in calculations\n", " | \n", " | >>> x = np.array([(1, 2),(3,4)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | >>> xv = x.view(dtype=np.int8).reshape(-1,2)\n", " | >>> xv\n", " | array([[1, 2],\n", " | [3, 4]], dtype=int8)\n", " | >>> xv.mean(0)\n", " | array([2., 3.])\n", " | \n", " | Making changes to the view changes the underlying array\n", " | \n", " | >>> xv[0,1] = 20\n", " | >>> x\n", " | array([(1, 20), (3, 4)], dtype=[('a', 'i1'), ('b', 'i1')])\n", " | \n", " | Using a view to convert an array to a recarray:\n", " | \n", " | >>> z = x.view(np.recarray)\n", " | >>> z.a\n", " | array([1, 3], dtype=int8)\n", " | \n", " | Views share data:\n", " | \n", " | >>> x[0] = (9, 10)\n", " | >>> z[0]\n", " | (9, 10)\n", " | \n", " | Views that change the dtype size (bytes per entry) should normally be\n", " | avoided on arrays defined by slices, transposes, fortran-ordering, etc.:\n", " | \n", " | >>> x = np.array([[1,2,3],[4,5,6]], dtype=np.int16)\n", " | >>> y = x[:, 0:2]\n", " | >>> y\n", " | array([[1, 2],\n", " | [4, 5]], dtype=int16)\n", " | >>> y.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: To change to a dtype of a different size, the array must be C-contiguous\n", " | >>> z = y.copy()\n", " | >>> z.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | array([[(1, 2)],\n", " | [(4, 5)]], dtype=[('width', '>> x = np.array([[1.,2.],[3.,4.]])\n", " | >>> x\n", " | array([[ 1., 2.],\n", " | [ 3., 4.]])\n", " | >>> x.T\n", " | array([[ 1., 3.],\n", " | [ 2., 4.]])\n", " | >>> x = np.array([1.,2.,3.,4.])\n", " | >>> x\n", " | array([ 1., 2., 3., 4.])\n", " | >>> x.T\n", " | array([ 1., 2., 3., 4.])\n", " | \n", " | See Also\n", " | --------\n", " | transpose\n", " | \n", " | __array_finalize__\n", " | None.\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side.\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: C-struct side.\n", " | \n", " | base\n", " | Base object if memory is from some other object.\n", " | \n", " | Examples\n", " | --------\n", " | The base of an array that owns its memory is None:\n", " | \n", " | >>> x = np.array([1,2,3,4])\n", " | >>> x.base is None\n", " | True\n", " | \n", " | Slicing creates a view, whose memory is shared with x:\n", " | \n", " | >>> y = x[2:]\n", " | >>> y.base is x\n", " | True\n", " | \n", " | ctypes\n", " | An object to simplify the interaction of the array with the ctypes\n", " | module.\n", " | \n", " | This attribute creates an object that makes it easier to use arrays\n", " | when calling shared libraries with the ctypes module. The returned\n", " | object has, among others, data, shape, and strides attributes (see\n", " | Notes below) which themselves return ctypes objects that can be used\n", " | as arguments to a shared library.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | c : Python object\n", " | Possessing attributes data, shape, strides, etc.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ctypeslib\n", " | \n", " | Notes\n", " | -----\n", " | Below are the public attributes of this object which were documented\n", " | in \"Guide to NumPy\" (we have omitted undocumented public attributes,\n", " | as well as documented private attributes):\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.data\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.shape\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.strides\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.data_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.shape_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.strides_as\n", " | :noindex:\n", " | \n", " | If the ctypes module is not available, then the ctypes attribute\n", " | of array objects still returns something useful, but ctypes objects\n", " | are not returned and errors may be raised instead. In particular,\n", " | the object will still have the ``as_parameter`` attribute which will\n", " | return an integer equal to the data attribute.\n", " | \n", " | Examples\n", " | --------\n", " | >>> import ctypes\n", " | >>> x = np.array([[0, 1], [2, 3]], dtype=np.int32)\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]], dtype=int32)\n", " | >>> x.ctypes.data\n", " | 31962608 # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32))\n", " | <__main__.LP_c_uint object at 0x7ff2fc1fc200> # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32)).contents\n", " | c_uint(0)\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint64)).contents\n", " | c_ulong(4294967296)\n", " | >>> x.ctypes.shape\n", " | # may vary\n", " | >>> x.ctypes.strides\n", " | # may vary\n", " | \n", " | data\n", " | Python buffer object pointing to the start of the array's data.\n", " | \n", " | dtype\n", " | Data-type of the array's elements.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | d : numpy dtype object\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dtype\n", " | \n", " | Examples\n", " | --------\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]])\n", " | >>> x.dtype\n", " | dtype('int32')\n", " | >>> type(x.dtype)\n", " | \n", " | \n", " | flags\n", " | Information about the memory layout of the array.\n", " | \n", " | Attributes\n", " | ----------\n", " | C_CONTIGUOUS (C)\n", " | The data is in a single, C-style contiguous segment.\n", " | F_CONTIGUOUS (F)\n", " | The data is in a single, Fortran-style contiguous segment.\n", " | OWNDATA (O)\n", " | The array owns the memory it uses or borrows it from another object.\n", " | WRITEABLE (W)\n", " | The data area can be written to. Setting this to False locks\n", " | the data, making it read-only. A view (slice, etc.) inherits WRITEABLE\n", " | from its base array at creation time, but a view of a writeable\n", " | array may be subsequently locked while the base array remains writeable.\n", " | (The opposite is not true, in that a view of a locked array may not\n", " | be made writeable. However, currently, locking a base object does not\n", " | lock any views that already reference it, so under that circumstance it\n", " | is possible to alter the contents of a locked array via a previously\n", " | created writeable view onto it.) Attempting to change a non-writeable\n", " | array raises a RuntimeError exception.\n", " | ALIGNED (A)\n", " | The data and all elements are aligned appropriately for the hardware.\n", " | WRITEBACKIFCOPY (X)\n", " | This array is a copy of some other array. The C-API function\n", " | PyArray_ResolveWritebackIfCopy must be called before deallocating\n", " | to the base array will be updated with the contents of this array.\n", " | UPDATEIFCOPY (U)\n", " | (Deprecated, use WRITEBACKIFCOPY) This array is a copy of some other array.\n", " | When this array is\n", " | deallocated, the base array will be updated with the contents of\n", " | this array.\n", " | FNC\n", " | F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | FORC\n", " | F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).\n", " | BEHAVED (B)\n", " | ALIGNED and WRITEABLE.\n", " | CARRAY (CA)\n", " | BEHAVED and C_CONTIGUOUS.\n", " | FARRAY (FA)\n", " | BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | \n", " | Notes\n", " | -----\n", " | The `flags` object can be accessed dictionary-like (as in ``a.flags['WRITEABLE']``),\n", " | or by using lowercased attribute names (as in ``a.flags.writeable``). Short flag\n", " | names are only supported in dictionary access.\n", " | \n", " | Only the WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be\n", " | changed by the user, via direct assignment to the attribute or dictionary\n", " | entry, or by calling `ndarray.setflags`.\n", " | \n", " | The array flags cannot be set arbitrarily:\n", " | \n", " | - UPDATEIFCOPY can only be set ``False``.\n", " | - WRITEBACKIFCOPY can only be set ``False``.\n", " | - ALIGNED can only be set ``True`` if the data is truly aligned.\n", " | - WRITEABLE can only be set ``True`` if the array owns its own memory\n", " | or the ultimate owner of the memory exposes a writeable buffer\n", " | interface or is a string.\n", " | \n", " | Arrays can be both C-style and Fortran-style contiguous simultaneously.\n", " | This is clear for 1-dimensional arrays, but can also be true for higher\n", " | dimensional arrays.\n", " | \n", " | Even for contiguous arrays a stride for a given dimension\n", " | ``arr.strides[dim]`` may be *arbitrary* if ``arr.shape[dim] == 1``\n", " | or the array has no elements.\n", " | It does *not* generally hold that ``self.strides[-1] == self.itemsize``\n", " | for C-style contiguous arrays or ``self.strides[0] == self.itemsize`` for\n", " | Fortran-style contiguous arrays is true.\n", " | \n", " | flat\n", " | A 1-D iterator over the array.\n", " | \n", " | This is a `numpy.flatiter` instance, which acts similarly to, but is not\n", " | a subclass of, Python's built-in iterator object.\n", " | \n", " | See Also\n", " | --------\n", " | flatten : Return a copy of the array collapsed into one dimension.\n", " | \n", " | flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(1, 7).reshape(2, 3)\n", " | >>> x\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | >>> x.flat[3]\n", " | 4\n", " | >>> x.T\n", " | array([[1, 4],\n", " | [2, 5],\n", " | [3, 6]])\n", " | >>> x.T.flat[3]\n", " | 5\n", " | >>> type(x.flat)\n", " | \n", " | \n", " | An assignment example:\n", " | \n", " | >>> x.flat = 3; x\n", " | array([[3, 3, 3],\n", " | [3, 3, 3]])\n", " | >>> x.flat[[1,4]] = 1; x\n", " | array([[3, 1, 3],\n", " | [3, 1, 3]])\n", " | \n", " | imag\n", " | The imaginary part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.imag\n", " | array([ 0. , 0.70710678])\n", " | >>> x.imag.dtype\n", " | dtype('float64')\n", " | \n", " | itemsize\n", " | Length of one array element in bytes.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1,2,3], dtype=np.float64)\n", " | >>> x.itemsize\n", " | 8\n", " | >>> x = np.array([1,2,3], dtype=np.complex128)\n", " | >>> x.itemsize\n", " | 16\n", " | \n", " | nbytes\n", " | Total bytes consumed by the elements of the array.\n", " | \n", " | Notes\n", " | -----\n", " | Does not include memory consumed by non-element attributes of the\n", " | array object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3,5,2), dtype=np.complex128)\n", " | >>> x.nbytes\n", " | 480\n", " | >>> np.prod(x.shape) * x.itemsize\n", " | 480\n", " | \n", " | ndim\n", " | Number of array dimensions.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> x.ndim\n", " | 1\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.ndim\n", " | 3\n", " | \n", " | real\n", " | The real part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.real\n", " | array([ 1. , 0.70710678])\n", " | >>> x.real.dtype\n", " | dtype('float64')\n", " | \n", " | See Also\n", " | --------\n", " | numpy.real : equivalent function\n", " | \n", " | shape\n", " | Tuple of array dimensions.\n", " | \n", " | The shape property is usually used to get the current shape of an array,\n", " | but may also be used to reshape the array in-place by assigning a tuple of\n", " | array dimensions to it. As with `numpy.reshape`, one of the new shape\n", " | dimensions can be -1, in which case its value is inferred from the size of\n", " | the array and the remaining dimensions. Reshaping an array in-place will\n", " | fail if a copy is required.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3, 4])\n", " | >>> x.shape\n", " | (4,)\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.shape\n", " | (2, 3, 4)\n", " | >>> y.shape = (3, 8)\n", " | >>> y\n", " | array([[ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.]])\n", " | >>> y.shape = (3, 6)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: total size of new array must be unchanged\n", " | >>> np.zeros((4,2))[::2].shape = (-1,)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | AttributeError: Incompatible shape for in-place modification. Use\n", " | `.reshape()` to make a copy with the desired shape.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : similar function\n", " | ndarray.reshape : similar method\n", " | \n", " | size\n", " | Number of elements in the array.\n", " | \n", " | Equal to ``np.prod(a.shape)``, i.e., the product of the array's\n", " | dimensions.\n", " | \n", " | Notes\n", " | -----\n", " | `a.size` returns a standard arbitrary precision Python integer. This\n", " | may not be the case with other methods of obtaining the same value\n", " | (like the suggested ``np.prod(a.shape)``, which returns an instance\n", " | of ``np.int_``), and may be relevant if the value is used further in\n", " | calculations that may overflow a fixed size integer type.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3, 5, 2), dtype=np.complex128)\n", " | >>> x.size\n", " | 30\n", " | >>> np.prod(x.shape)\n", " | 30\n", " | \n", " | strides\n", " | Tuple of bytes to step in each dimension when traversing an array.\n", " | \n", " | The byte offset of element ``(i[0], i[1], ..., i[n])`` in an array `a`\n", " | is::\n", " | \n", " | offset = sum(np.array(i) * a.strides)\n", " | \n", " | A more detailed explanation of strides can be found in the\n", " | \"ndarray.rst\" file in the NumPy reference guide.\n", " | \n", " | Notes\n", " | -----\n", " | Imagine an array of 32-bit integers (each 4 bytes)::\n", " | \n", " | x = np.array([[0, 1, 2, 3, 4],\n", " | [5, 6, 7, 8, 9]], dtype=np.int32)\n", " | \n", " | This array is stored in memory as 40 bytes, one after the other\n", " | (known as a contiguous block of memory). The strides of an array tell\n", " | us how many bytes we have to skip in memory to move to the next position\n", " | along a certain axis. For example, we have to skip 4 bytes (1 value) to\n", " | move to the next column, but 20 bytes (5 values) to get to the same\n", " | position in the next row. As such, the strides for the array `x` will be\n", " | ``(20, 4)``.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.lib.stride_tricks.as_strided\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.reshape(np.arange(2*3*4), (2,3,4))\n", " | >>> y\n", " | array([[[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]],\n", " | [[12, 13, 14, 15],\n", " | [16, 17, 18, 19],\n", " | [20, 21, 22, 23]]])\n", " | >>> y.strides\n", " | (48, 16, 4)\n", " | >>> y[1,1,1]\n", " | 17\n", " | >>> offset=sum(y.strides * np.array((1,1,1)))\n", " | >>> offset/y.itemsize\n", " | 17\n", " | \n", " | >>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0)\n", " | >>> x.strides\n", " | (32, 4, 224, 1344)\n", " | >>> i = np.array([3,5,2,2])\n", " | >>> offset = sum(i * x.strides)\n", " | >>> x[3,5,2,2]\n", " | 813\n", " | >>> offset / x.itemsize\n", " | 813\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes defined here:\n", " | \n", " | __hash__ = None\n", " \n", " class ndenumerate(builtins.object)\n", " | ndenumerate(arr)\n", " | \n", " | Multidimensional index iterator.\n", " | \n", " | Return an iterator yielding pairs of array coordinates and values.\n", " | \n", " | Parameters\n", " | ----------\n", " | arr : ndarray\n", " | Input array.\n", " | \n", " | See Also\n", " | --------\n", " | ndindex, flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> for index, x in np.ndenumerate(a):\n", " | ... print(index, x)\n", " | (0, 0) 1\n", " | (0, 1) 2\n", " | (1, 0) 3\n", " | (1, 1) 4\n", " | \n", " | Methods defined here:\n", " | \n", " | __init__(self, arr)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | __iter__(self)\n", " | \n", " | __next__(self)\n", " | Standard iterator method, returns the index tuple and array value.\n", " | \n", " | Returns\n", " | -------\n", " | coords : tuple of ints\n", " | The indices of the current iteration.\n", " | val : scalar\n", " | The array element of the current iteration.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class ndindex(builtins.object)\n", " | ndindex(*shape)\n", " | \n", " | An N-dimensional iterator object to index arrays.\n", " | \n", " | Given the shape of an array, an `ndindex` instance iterates over\n", " | the N-dimensional index of the array. At each iteration a tuple\n", " | of indices is returned, the last dimension is iterated over first.\n", " | \n", " | Parameters\n", " | ----------\n", " | `*args` : ints\n", " | The size of each dimension of the array.\n", " | \n", " | See Also\n", " | --------\n", " | ndenumerate, flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> for index in np.ndindex(3, 2, 1):\n", " | ... print(index)\n", " | (0, 0, 0)\n", " | (0, 1, 0)\n", " | (1, 0, 0)\n", " | (1, 1, 0)\n", " | (2, 0, 0)\n", " | (2, 1, 0)\n", " | \n", " | Methods defined here:\n", " | \n", " | __init__(self, *shape)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | __iter__(self)\n", " | \n", " | __next__(self)\n", " | Standard iterator method, updates the index and returns the index\n", " | tuple.\n", " | \n", " | Returns\n", " | -------\n", " | val : tuple of ints\n", " | Returns a tuple containing the indices of the current\n", " | iteration.\n", " | \n", " | ndincr(self)\n", " | Increment the multi-dimensional index by one.\n", " | \n", " | This method is for backward compatibility only: do not use.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class nditer(builtins.object)\n", " | nditer(op, flags=None, op_flags=None, op_dtypes=None, order='K', casting='safe', op_axes=None, itershape=None, buffersize=0)\n", " | \n", " | Efficient multi-dimensional iterator object to iterate over arrays.\n", " | To get started using this object, see the\n", " | :ref:`introductory guide to array iteration `.\n", " | \n", " | Parameters\n", " | ----------\n", " | op : ndarray or sequence of array_like\n", " | The array(s) to iterate over.\n", " | \n", " | flags : sequence of str, optional\n", " | Flags to control the behavior of the iterator.\n", " | \n", " | * ``buffered`` enables buffering when required.\n", " | * ``c_index`` causes a C-order index to be tracked.\n", " | * ``f_index`` causes a Fortran-order index to be tracked.\n", " | * ``multi_index`` causes a multi-index, or a tuple of indices\n", " | with one per iteration dimension, to be tracked.\n", " | * ``common_dtype`` causes all the operands to be converted to\n", " | a common data type, with copying or buffering as necessary.\n", " | * ``copy_if_overlap`` causes the iterator to determine if read\n", " | operands have overlap with write operands, and make temporary\n", " | copies as necessary to avoid overlap. False positives (needless\n", " | copying) are possible in some cases.\n", " | * ``delay_bufalloc`` delays allocation of the buffers until\n", " | a reset() call is made. Allows ``allocate`` operands to\n", " | be initialized before their values are copied into the buffers.\n", " | * ``external_loop`` causes the ``values`` given to be\n", " | one-dimensional arrays with multiple values instead of\n", " | zero-dimensional arrays.\n", " | * ``grow_inner`` allows the ``value`` array sizes to be made\n", " | larger than the buffer size when both ``buffered`` and\n", " | ``external_loop`` is used.\n", " | * ``ranged`` allows the iterator to be restricted to a sub-range\n", " | of the iterindex values.\n", " | * ``refs_ok`` enables iteration of reference types, such as\n", " | object arrays.\n", " | * ``reduce_ok`` enables iteration of ``readwrite`` operands\n", " | which are broadcasted, also known as reduction operands.\n", " | * ``zerosize_ok`` allows `itersize` to be zero.\n", " | op_flags : list of list of str, optional\n", " | This is a list of flags for each operand. At minimum, one of\n", " | ``readonly``, ``readwrite``, or ``writeonly`` must be specified.\n", " | \n", " | * ``readonly`` indicates the operand will only be read from.\n", " | * ``readwrite`` indicates the operand will be read from and written to.\n", " | * ``writeonly`` indicates the operand will only be written to.\n", " | * ``no_broadcast`` prevents the operand from being broadcasted.\n", " | * ``contig`` forces the operand data to be contiguous.\n", " | * ``aligned`` forces the operand data to be aligned.\n", " | * ``nbo`` forces the operand data to be in native byte order.\n", " | * ``copy`` allows a temporary read-only copy if required.\n", " | * ``updateifcopy`` allows a temporary read-write copy if required.\n", " | * ``allocate`` causes the array to be allocated if it is None\n", " | in the ``op`` parameter.\n", " | * ``no_subtype`` prevents an ``allocate`` operand from using a subtype.\n", " | * ``arraymask`` indicates that this operand is the mask to use\n", " | for selecting elements when writing to operands with the\n", " | 'writemasked' flag set. The iterator does not enforce this,\n", " | but when writing from a buffer back to the array, it only\n", " | copies those elements indicated by this mask.\n", " | * ``writemasked`` indicates that only elements where the chosen\n", " | ``arraymask`` operand is True will be written to.\n", " | * ``overlap_assume_elementwise`` can be used to mark operands that are\n", " | accessed only in the iterator order, to allow less conservative\n", " | copying when ``copy_if_overlap`` is present.\n", " | op_dtypes : dtype or tuple of dtype(s), optional\n", " | The required data type(s) of the operands. If copying or buffering\n", " | is enabled, the data will be converted to/from their original types.\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the iteration order. 'C' means C order, 'F' means\n", " | Fortran order, 'A' means 'F' order if all the arrays are Fortran\n", " | contiguous, 'C' order otherwise, and 'K' means as close to the\n", " | order the array elements appear in memory as possible. This also\n", " | affects the element memory order of ``allocate`` operands, as they\n", " | are allocated to be compatible with iteration order.\n", " | Default is 'K'.\n", " | casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n", " | Controls what kind of data casting may occur when making a copy\n", " | or buffering. Setting this to 'unsafe' is not recommended,\n", " | as it can adversely affect accumulations.\n", " | \n", " | * 'no' means the data types should not be cast at all.\n", " | * 'equiv' means only byte-order changes are allowed.\n", " | * 'safe' means only casts which can preserve values are allowed.\n", " | * 'same_kind' means only safe casts or casts within a kind,\n", " | like float64 to float32, are allowed.\n", " | * 'unsafe' means any data conversions may be done.\n", " | op_axes : list of list of ints, optional\n", " | If provided, is a list of ints or None for each operands.\n", " | The list of axes for an operand is a mapping from the dimensions\n", " | of the iterator to the dimensions of the operand. A value of\n", " | -1 can be placed for entries, causing that dimension to be\n", " | treated as `newaxis`.\n", " | itershape : tuple of ints, optional\n", " | The desired shape of the iterator. This allows ``allocate`` operands\n", " | with a dimension mapped by op_axes not corresponding to a dimension\n", " | of a different operand to get a value not equal to 1 for that\n", " | dimension.\n", " | buffersize : int, optional\n", " | When buffering is enabled, controls the size of the temporary\n", " | buffers. Set to 0 for the default value.\n", " | \n", " | Attributes\n", " | ----------\n", " | dtypes : tuple of dtype(s)\n", " | The data types of the values provided in `value`. This may be\n", " | different from the operand data types if buffering is enabled.\n", " | Valid only before the iterator is closed.\n", " | finished : bool\n", " | Whether the iteration over the operands is finished or not.\n", " | has_delayed_bufalloc : bool\n", " | If True, the iterator was created with the ``delay_bufalloc`` flag,\n", " | and no reset() function was called on it yet.\n", " | has_index : bool\n", " | If True, the iterator was created with either the ``c_index`` or\n", " | the ``f_index`` flag, and the property `index` can be used to\n", " | retrieve it.\n", " | has_multi_index : bool\n", " | If True, the iterator was created with the ``multi_index`` flag,\n", " | and the property `multi_index` can be used to retrieve it.\n", " | index\n", " | When the ``c_index`` or ``f_index`` flag was used, this property\n", " | provides access to the index. Raises a ValueError if accessed\n", " | and ``has_index`` is False.\n", " | iterationneedsapi : bool\n", " | Whether iteration requires access to the Python API, for example\n", " | if one of the operands is an object array.\n", " | iterindex : int\n", " | An index which matches the order of iteration.\n", " | itersize : int\n", " | Size of the iterator.\n", " | itviews\n", " | Structured view(s) of `operands` in memory, matching the reordered\n", " | and optimized iterator access pattern. Valid only before the iterator\n", " | is closed.\n", " | multi_index\n", " | When the ``multi_index`` flag was used, this property\n", " | provides access to the index. Raises a ValueError if accessed\n", " | accessed and ``has_multi_index`` is False.\n", " | ndim : int\n", " | The dimensions of the iterator.\n", " | nop : int\n", " | The number of iterator operands.\n", " | operands : tuple of operand(s)\n", " | The array(s) to be iterated over. Valid only before the iterator is\n", " | closed.\n", " | shape : tuple of ints\n", " | Shape tuple, the shape of the iterator.\n", " | value\n", " | Value of ``operands`` at current iteration. Normally, this is a\n", " | tuple of array scalars, but if the flag ``external_loop`` is used,\n", " | it is a tuple of one dimensional arrays.\n", " | \n", " | Notes\n", " | -----\n", " | `nditer` supersedes `flatiter`. The iterator implementation behind\n", " | `nditer` is also exposed by the NumPy C API.\n", " | \n", " | The Python exposure supplies two iteration interfaces, one which follows\n", " | the Python iterator protocol, and another which mirrors the C-style\n", " | do-while pattern. The native Python approach is better in most cases, but\n", " | if you need the coordinates or index of an iterator, use the C-style pattern.\n", " | \n", " | Examples\n", " | --------\n", " | Here is how we might write an ``iter_add`` function, using the\n", " | Python iterator protocol:\n", " | \n", " | >>> def iter_add_py(x, y, out=None):\n", " | ... addop = np.add\n", " | ... it = np.nditer([x, y, out], [],\n", " | ... [['readonly'], ['readonly'], ['writeonly','allocate']])\n", " | ... with it:\n", " | ... for (a, b, c) in it:\n", " | ... addop(a, b, out=c)\n", " | ... return it.operands[2]\n", " | \n", " | Here is the same function, but following the C-style pattern:\n", " | \n", " | >>> def iter_add(x, y, out=None):\n", " | ... addop = np.add\n", " | ... it = np.nditer([x, y, out], [],\n", " | ... [['readonly'], ['readonly'], ['writeonly','allocate']])\n", " | ... with it:\n", " | ... while not it.finished:\n", " | ... addop(it[0], it[1], out=it[2])\n", " | ... it.iternext()\n", " | ... return it.operands[2]\n", " | \n", " | Here is an example outer product function:\n", " | \n", " | >>> def outer_it(x, y, out=None):\n", " | ... mulop = np.multiply\n", " | ... it = np.nditer([x, y, out], ['external_loop'],\n", " | ... [['readonly'], ['readonly'], ['writeonly', 'allocate']],\n", " | ... op_axes=[list(range(x.ndim)) + [-1] * y.ndim,\n", " | ... [-1] * x.ndim + list(range(y.ndim)),\n", " | ... None])\n", " | ... with it:\n", " | ... for (a, b, c) in it:\n", " | ... mulop(a, b, out=c)\n", " | ... return it.operands[2]\n", " | \n", " | >>> a = np.arange(2)+1\n", " | >>> b = np.arange(3)+1\n", " | >>> outer_it(a,b)\n", " | array([[1, 2, 3],\n", " | [2, 4, 6]])\n", " | \n", " | Here is an example function which operates like a \"lambda\" ufunc:\n", " | \n", " | >>> def luf(lamdaexpr, *args, **kwargs):\n", " | ... '''luf(lambdaexpr, op1, ..., opn, out=None, order='K', casting='safe', buffersize=0)'''\n", " | ... nargs = len(args)\n", " | ... op = (kwargs.get('out',None),) + args\n", " | ... it = np.nditer(op, ['buffered','external_loop'],\n", " | ... [['writeonly','allocate','no_broadcast']] +\n", " | ... [['readonly','nbo','aligned']]*nargs,\n", " | ... order=kwargs.get('order','K'),\n", " | ... casting=kwargs.get('casting','safe'),\n", " | ... buffersize=kwargs.get('buffersize',0))\n", " | ... while not it.finished:\n", " | ... it[0] = lamdaexpr(*it[1:])\n", " | ... it.iternext()\n", " | ... return it.operands[0]\n", " | \n", " | >>> a = np.arange(5)\n", " | >>> b = np.ones(5)\n", " | >>> luf(lambda i,j:i*i + j/2, a, b)\n", " | array([ 0.5, 1.5, 4.5, 9.5, 16.5])\n", " | \n", " | If operand flags `\"writeonly\"` or `\"readwrite\"` are used the\n", " | operands may be views into the original data with the\n", " | `WRITEBACKIFCOPY` flag. In this case `nditer` must be used as a\n", " | context manager or the `nditer.close` method must be called before\n", " | using the result. The temporary data will be written back to the\n", " | original data when the `__exit__` function is called but not before:\n", " | \n", " | >>> a = np.arange(6, dtype='i4')[::-2]\n", " | >>> with np.nditer(a, [],\n", " | ... [['writeonly', 'updateifcopy']],\n", " | ... casting='unsafe',\n", " | ... op_dtypes=[np.dtype('f4')]) as i:\n", " | ... x = i.operands[0]\n", " | ... x[:] = [-1, -2, -3]\n", " | ... # a still unchanged here\n", " | >>> a, x\n", " | (array([-1, -2, -3], dtype=int32), array([-1., -2., -3.], dtype=float32))\n", " | \n", " | It is important to note that once the iterator is exited, dangling\n", " | references (like `x` in the example) may or may not share data with\n", " | the original data `a`. If writeback semantics were active, i.e. if\n", " | `x.base.flags.writebackifcopy` is `True`, then exiting the iterator\n", " | will sever the connection between `x` and `a`, writing to `x` will\n", " | no longer write to `a`. If writeback semantics are not active, then\n", " | `x.data` will still point at some part of `a.data`, and writing to\n", " | one will affect the other.\n", " | \n", " | Context management and the `close` method appeared in version 1.15.0.\n", " | \n", " | Methods defined here:\n", " | \n", " | __copy__(...)\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __enter__(...)\n", " | \n", " | __exit__(...)\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __init__(self, /, *args, **kwargs)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __next__(self, /)\n", " | Implement next(self).\n", " | \n", " | __setitem__(self, key, value, /)\n", " | Set self[key] to value.\n", " | \n", " | close(...)\n", " | close()\n", " | \n", " | Resolve all writeback semantics in writeable operands.\n", " | \n", " | .. versionadded:: 1.15.0\n", " | \n", " | See Also\n", " | --------\n", " | \n", " | :ref:`nditer-context-manager`\n", " | \n", " | copy(...)\n", " | copy()\n", " | \n", " | Get a copy of the iterator in its current state.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(10)\n", " | >>> y = x + 1\n", " | >>> it = np.nditer([x, y])\n", " | >>> next(it)\n", " | (array(0), array(1))\n", " | >>> it2 = it.copy()\n", " | >>> next(it2)\n", " | (array(1), array(2))\n", " | \n", " | debug_print(...)\n", " | debug_print()\n", " | \n", " | Print the current state of the `nditer` instance and debug info to stdout.\n", " | \n", " | enable_external_loop(...)\n", " | enable_external_loop()\n", " | \n", " | When the \"external_loop\" was not used during construction, but\n", " | is desired, this modifies the iterator to behave as if the flag\n", " | was specified.\n", " | \n", " | iternext(...)\n", " | iternext()\n", " | \n", " | Check whether iterations are left, and perform a single internal iteration\n", " | without returning the result. Used in the C-style pattern do-while\n", " | pattern. For an example, see `nditer`.\n", " | \n", " | Returns\n", " | -------\n", " | iternext : bool\n", " | Whether or not there are iterations left.\n", " | \n", " | remove_axis(...)\n", " | remove_axis(i)\n", " | \n", " | Removes axis `i` from the iterator. Requires that the flag \"multi_index\"\n", " | be enabled.\n", " | \n", " | remove_multi_index(...)\n", " | remove_multi_index()\n", " | \n", " | When the \"multi_index\" flag was specified, this removes it, allowing\n", " | the internal iteration structure to be optimized further.\n", " | \n", " | reset(...)\n", " | reset()\n", " | \n", " | Reset the iterator to its initial state.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | dtypes\n", " | \n", " | finished\n", " | \n", " | has_delayed_bufalloc\n", " | \n", " | has_index\n", " | \n", " | has_multi_index\n", " | \n", " | index\n", " | \n", " | iterationneedsapi\n", " | \n", " | iterindex\n", " | \n", " | iterrange\n", " | \n", " | itersize\n", " | \n", " | itviews\n", " | \n", " | multi_index\n", " | \n", " | ndim\n", " | \n", " | nop\n", " | \n", " | operands\n", " | operands[`Slice`]\n", " | \n", " | The array(s) to be iterated over. Valid only before the iterator is closed.\n", " | \n", " | shape\n", " | \n", " | value\n", " \n", " class number(generic)\n", " | Abstract base class of all numeric scalar types.\n", " | \n", " | Method resolution order:\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " object0 = class object_(generic)\n", " | Any Python object.\n", " | Character code: ``'O'``.\n", " | \n", " | Method resolution order:\n", " | object_\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __call__(self, /, *args, **kwargs)\n", " | Call self as a function.\n", " | \n", " | __contains__(self, key, /)\n", " | Return key in self.\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __iadd__(self, value, /)\n", " | Implement self+=value.\n", " | \n", " | __imul__(self, value, /)\n", " | Implement self*=value.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class object_(generic)\n", " | Any Python object.\n", " | Character code: ``'O'``.\n", " | \n", " | Method resolution order:\n", " | object_\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __call__(self, /, *args, **kwargs)\n", " | Call self as a function.\n", " | \n", " | __contains__(self, key, /)\n", " | Return key in self.\n", " | \n", " | __delattr__(self, name, /)\n", " | Implement delattr(self, name).\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getattribute__(self, name, /)\n", " | Return getattr(self, name).\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __iadd__(self, value, /)\n", " | Implement self+=value.\n", " | \n", " | __imul__(self, value, /)\n", " | Implement self*=value.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class poly1d(builtins.object)\n", " | poly1d(c_or_r, r=False, variable=None)\n", " | \n", " | A one-dimensional polynomial class.\n", " | \n", " | A convenience class, used to encapsulate \"natural\" operations on\n", " | polynomials so that said operations may take on their customary\n", " | form in code (see Examples).\n", " | \n", " | Parameters\n", " | ----------\n", " | c_or_r : array_like\n", " | The polynomial's coefficients, in decreasing powers, or if\n", " | the value of the second parameter is True, the polynomial's\n", " | roots (values where the polynomial evaluates to 0). For example,\n", " | ``poly1d([1, 2, 3])`` returns an object that represents\n", " | :math:`x^2 + 2x + 3`, whereas ``poly1d([1, 2, 3], True)`` returns\n", " | one that represents :math:`(x-1)(x-2)(x-3) = x^3 - 6x^2 + 11x -6`.\n", " | r : bool, optional\n", " | If True, `c_or_r` specifies the polynomial's roots; the default\n", " | is False.\n", " | variable : str, optional\n", " | Changes the variable used when printing `p` from `x` to `variable`\n", " | (see Examples).\n", " | \n", " | Examples\n", " | --------\n", " | Construct the polynomial :math:`x^2 + 2x + 3`:\n", " | \n", " | >>> p = np.poly1d([1, 2, 3])\n", " | >>> print(np.poly1d(p))\n", " | 2\n", " | 1 x + 2 x + 3\n", " | \n", " | Evaluate the polynomial at :math:`x = 0.5`:\n", " | \n", " | >>> p(0.5)\n", " | 4.25\n", " | \n", " | Find the roots:\n", " | \n", " | >>> p.r\n", " | array([-1.+1.41421356j, -1.-1.41421356j])\n", " | >>> p(p.r)\n", " | array([ -4.44089210e-16+0.j, -4.44089210e-16+0.j]) # may vary\n", " | \n", " | These numbers in the previous line represent (0, 0) to machine precision\n", " | \n", " | Show the coefficients:\n", " | \n", " | >>> p.c\n", " | array([1, 2, 3])\n", " | \n", " | Display the order (the leading zero-coefficients are removed):\n", " | \n", " | >>> p.order\n", " | 2\n", " | \n", " | Show the coefficient of the k-th power in the polynomial\n", " | (which is equivalent to ``p.c[-(i+1)]``):\n", " | \n", " | >>> p[1]\n", " | 2\n", " | \n", " | Polynomials can be added, subtracted, multiplied, and divided\n", " | (returns quotient and remainder):\n", " | \n", " | >>> p * p\n", " | poly1d([ 1, 4, 10, 12, 9])\n", " | \n", " | >>> (p**3 + 4) / p\n", " | (poly1d([ 1., 4., 10., 12., 9.]), poly1d([4.]))\n", " | \n", " | ``asarray(p)`` gives the coefficient array, so polynomials can be\n", " | used in all functions that accept arrays:\n", " | \n", " | >>> p**2 # square of polynomial\n", " | poly1d([ 1, 4, 10, 12, 9])\n", " | \n", " | >>> np.square(p) # square of individual coefficients\n", " | array([1, 4, 9])\n", " | \n", " | The variable used in the string representation of `p` can be modified,\n", " | using the `variable` parameter:\n", " | \n", " | >>> p = np.poly1d([1,2,3], variable='z')\n", " | >>> print(p)\n", " | 2\n", " | 1 z + 2 z + 3\n", " | \n", " | Construct a polynomial from its roots:\n", " | \n", " | >>> np.poly1d([1, 2], True)\n", " | poly1d([ 1., -3., 2.])\n", " | \n", " | This is the same polynomial as obtained by:\n", " | \n", " | >>> np.poly1d([1, -1]) * np.poly1d([1, -2])\n", " | poly1d([ 1, -3, 2])\n", " | \n", " | Methods defined here:\n", " | \n", " | __add__(self, other)\n", " | \n", " | __array__(self, t=None)\n", " | \n", " | __call__(self, val)\n", " | Call self as a function.\n", " | \n", " | __div__(self, other)\n", " | \n", " | __eq__(self, other)\n", " | Return self==value.\n", " | \n", " | __getitem__(self, val)\n", " | \n", " | __init__(self, c_or_r, r=False, variable=None)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | __iter__(self)\n", " | \n", " | __len__(self)\n", " | \n", " | __mul__(self, other)\n", " | \n", " | __ne__(self, other)\n", " | Return self!=value.\n", " | \n", " | __neg__(self)\n", " | \n", " | __pos__(self)\n", " | \n", " | __pow__(self, val)\n", " | \n", " | __radd__(self, other)\n", " | \n", " | __rdiv__(self, other)\n", " | \n", " | __repr__(self)\n", " | Return repr(self).\n", " | \n", " | __rmul__(self, other)\n", " | \n", " | __rsub__(self, other)\n", " | \n", " | __rtruediv__ = __rdiv__(self, other)\n", " | \n", " | __setitem__(self, key, val)\n", " | \n", " | __str__(self)\n", " | Return str(self).\n", " | \n", " | __sub__(self, other)\n", " | \n", " | __truediv__ = __div__(self, other)\n", " | \n", " | deriv(self, m=1)\n", " | Return a derivative of this polynomial.\n", " | \n", " | Refer to `polyder` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | polyder : equivalent function\n", " | \n", " | integ(self, m=1, k=0)\n", " | Return an antiderivative (indefinite integral) of this polynomial.\n", " | \n", " | Refer to `polyint` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | polyint : equivalent function\n", " | \n", " | ----------------------------------------------------------------------\n", " | Readonly properties defined here:\n", " | \n", " | o\n", " | The order or degree of the polynomial\n", " | \n", " | order\n", " | The order or degree of the polynomial\n", " | \n", " | r\n", " | The roots of the polynomial, where self(x) == 0\n", " | \n", " | roots\n", " | The roots of the polynomial, where self(x) == 0\n", " | \n", " | variable\n", " | The name of the polynomial variable\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | c\n", " | The polynomial coefficients\n", " | \n", " | coef\n", " | The polynomial coefficients\n", " | \n", " | coefficients\n", " | The polynomial coefficients\n", " | \n", " | coeffs\n", " | The polynomial coefficients\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes defined here:\n", " | \n", " | __hash__ = None\n", " \n", " class recarray(ndarray)\n", " | recarray(shape, dtype=None, buf=None, offset=0, strides=None, formats=None, names=None, titles=None, byteorder=None, aligned=False, order='C')\n", " | \n", " | Construct an ndarray that allows field access using attributes.\n", " | \n", " | Arrays may have a data-types containing fields, analogous\n", " | to columns in a spread sheet. An example is ``[(x, int), (y, float)]``,\n", " | where each entry in the array is a pair of ``(int, float)``. Normally,\n", " | these attributes are accessed using dictionary lookups such as ``arr['x']``\n", " | and ``arr['y']``. Record arrays allow the fields to be accessed as members\n", " | of the array, using ``arr.x`` and ``arr.y``.\n", " | \n", " | Parameters\n", " | ----------\n", " | shape : tuple\n", " | Shape of output array.\n", " | dtype : data-type, optional\n", " | The desired data-type. By default, the data-type is determined\n", " | from `formats`, `names`, `titles`, `aligned` and `byteorder`.\n", " | formats : list of data-types, optional\n", " | A list containing the data-types for the different columns, e.g.\n", " | ``['i4', 'f8', 'i4']``. `formats` does *not* support the new\n", " | convention of using types directly, i.e. ``(int, float, int)``.\n", " | Note that `formats` must be a list, not a tuple.\n", " | Given that `formats` is somewhat limited, we recommend specifying\n", " | `dtype` instead.\n", " | names : tuple of str, optional\n", " | The name of each column, e.g. ``('x', 'y', 'z')``.\n", " | buf : buffer, optional\n", " | By default, a new array is created of the given shape and data-type.\n", " | If `buf` is specified and is an object exposing the buffer interface,\n", " | the array will use the memory from the existing buffer. In this case,\n", " | the `offset` and `strides` keywords are available.\n", " | \n", " | Other Parameters\n", " | ----------------\n", " | titles : tuple of str, optional\n", " | Aliases for column names. For example, if `names` were\n", " | ``('x', 'y', 'z')`` and `titles` is\n", " | ``('x_coordinate', 'y_coordinate', 'z_coordinate')``, then\n", " | ``arr['x']`` is equivalent to both ``arr.x`` and ``arr.x_coordinate``.\n", " | byteorder : {'<', '>', '='}, optional\n", " | Byte-order for all fields.\n", " | aligned : bool, optional\n", " | Align the fields in memory as the C-compiler would.\n", " | strides : tuple of ints, optional\n", " | Buffer (`buf`) is interpreted according to these strides (strides\n", " | define how many bytes each array element, row, column, etc.\n", " | occupy in memory).\n", " | offset : int, optional\n", " | Start reading buffer (`buf`) from this offset onwards.\n", " | order : {'C', 'F'}, optional\n", " | Row-major (C-style) or column-major (Fortran-style) order.\n", " | \n", " | Returns\n", " | -------\n", " | rec : recarray\n", " | Empty array of the given shape and type.\n", " | \n", " | See Also\n", " | --------\n", " | rec.fromrecords : Construct a record array from data.\n", " | record : fundamental data-type for `recarray`.\n", " | format_parser : determine a data-type from formats, names, titles.\n", " | \n", " | Notes\n", " | -----\n", " | This constructor can be compared to ``empty``: it creates a new record\n", " | array but does not fill it with data. To create a record array from data,\n", " | use one of the following methods:\n", " | \n", " | 1. Create a standard ndarray and convert it to a record array,\n", " | using ``arr.view(np.recarray)``\n", " | 2. Use the `buf` keyword.\n", " | 3. Use `np.rec.fromrecords`.\n", " | \n", " | Examples\n", " | --------\n", " | Create an array with two fields, ``x`` and ``y``:\n", " | \n", " | >>> x = np.array([(1.0, 2), (3.0, 4)], dtype=[('x', '>> x\n", " | array([(1., 2), (3., 4)], dtype=[('x', '>> x['x']\n", " | array([1., 3.])\n", " | \n", " | View the array as a record array:\n", " | \n", " | >>> x = x.view(np.recarray)\n", " | \n", " | >>> x.x\n", " | array([1., 3.])\n", " | \n", " | >>> x.y\n", " | array([2, 4])\n", " | \n", " | Create a new, empty record array:\n", " | \n", " | >>> np.recarray((2,),\n", " | ... dtype=[('x', int), ('y', float), ('z', int)]) #doctest: +SKIP\n", " | rec.array([(-1073741821, 1.2249118382103472e-301, 24547520),\n", " | (3471280, 1.2134086255804012e-316, 0)],\n", " | dtype=[('x', ' reference if type unchanged, copy otherwise.\n", " | \n", " | Returns either a new reference to self if dtype is not given or a new array\n", " | of provided data type if dtype is different from the current dtype of the\n", " | array.\n", " | \n", " | __array_function__(...)\n", " | \n", " | __array_prepare__(...)\n", " | a.__array_prepare__(obj) -> Object of same type as ndarray object obj.\n", " | \n", " | __array_ufunc__(...)\n", " | \n", " | __array_wrap__(...)\n", " | a.__array_wrap__(obj) -> Object of same type as ndarray object a.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __contains__(self, key, /)\n", " | Return key in self.\n", " | \n", " | __copy__(...)\n", " | a.__copy__()\n", " | \n", " | Used if :func:`copy.copy` is called on an array. Returns a copy of the array.\n", " | \n", " | Equivalent to ``a.copy(order='K')``.\n", " | \n", " | __deepcopy__(...)\n", " | a.__deepcopy__(memo, /) -> Deep copy of array.\n", " | \n", " | Used if :func:`copy.deepcopy` is called on an array.\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | Default object formatter.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __iadd__(self, value, /)\n", " | Return self+=value.\n", " | \n", " | __iand__(self, value, /)\n", " | Return self&=value.\n", " | \n", " | __ifloordiv__(self, value, /)\n", " | Return self//=value.\n", " | \n", " | __ilshift__(self, value, /)\n", " | Return self<<=value.\n", " | \n", " | __imatmul__(self, value, /)\n", " | Return self@=value.\n", " | \n", " | __imod__(self, value, /)\n", " | Return self%=value.\n", " | \n", " | __imul__(self, value, /)\n", " | Return self*=value.\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __ior__(self, value, /)\n", " | Return self|=value.\n", " | \n", " | __ipow__(self, value, /)\n", " | Return self**=value.\n", " | \n", " | __irshift__(self, value, /)\n", " | Return self>>=value.\n", " | \n", " | __isub__(self, value, /)\n", " | Return self-=value.\n", " | \n", " | __iter__(self, /)\n", " | Implement iter(self).\n", " | \n", " | __itruediv__(self, value, /)\n", " | Return self/=value.\n", " | \n", " | __ixor__(self, value, /)\n", " | Return self^=value.\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setitem__(self, key, value, /)\n", " | Set self[key] to value.\n", " | \n", " | __setstate__(...)\n", " | a.__setstate__(state, /)\n", " | \n", " | For unpickling.\n", " | \n", " | The `state` argument must be a sequence that contains the following\n", " | elements:\n", " | \n", " | Parameters\n", " | ----------\n", " | version : int\n", " | optional pickle version. If omitted defaults to 0.\n", " | shape : tuple\n", " | dtype : data-type\n", " | isFortran : bool\n", " | rawdata : string or list\n", " | a binary string with the data (or a list if 'a' is an object array)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | a.all(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if all elements evaluate to True.\n", " | \n", " | Refer to `numpy.all` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.all : equivalent function\n", " | \n", " | any(...)\n", " | a.any(axis=None, out=None, keepdims=False)\n", " | \n", " | Returns True if any of the elements of `a` evaluate to True.\n", " | \n", " | Refer to `numpy.any` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.any : equivalent function\n", " | \n", " | argmax(...)\n", " | a.argmax(axis=None, out=None)\n", " | \n", " | Return indices of the maximum values along the given axis.\n", " | \n", " | Refer to `numpy.argmax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmax : equivalent function\n", " | \n", " | argmin(...)\n", " | a.argmin(axis=None, out=None)\n", " | \n", " | Return indices of the minimum values along the given axis of `a`.\n", " | \n", " | Refer to `numpy.argmin` for detailed documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argmin : equivalent function\n", " | \n", " | argpartition(...)\n", " | a.argpartition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Returns the indices that would partition this array.\n", " | \n", " | Refer to `numpy.argpartition` for full documentation.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argpartition : equivalent function\n", " | \n", " | argsort(...)\n", " | a.argsort(axis=-1, kind=None, order=None)\n", " | \n", " | Returns the indices that would sort this array.\n", " | \n", " | Refer to `numpy.argsort` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.argsort : equivalent function\n", " | \n", " | astype(...)\n", " | a.astype(dtype, order='K', casting='unsafe', subok=True, copy=True)\n", " | \n", " | Copy of the array, cast to a specified type.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | Typecode or data-type to which the array is cast.\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout order of the result.\n", " | 'C' means C order, 'F' means Fortran order, 'A'\n", " | means 'F' order if all the arrays are Fortran contiguous,\n", " | 'C' order otherwise, and 'K' means as close to the\n", " | order the array elements appear in memory as possible.\n", " | Default is 'K'.\n", " | casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional\n", " | Controls what kind of data casting may occur. Defaults to 'unsafe'\n", " | for backwards compatibility.\n", " | \n", " | * 'no' means the data types should not be cast at all.\n", " | * 'equiv' means only byte-order changes are allowed.\n", " | * 'safe' means only casts which can preserve values are allowed.\n", " | * 'same_kind' means only safe casts or casts within a kind,\n", " | like float64 to float32, are allowed.\n", " | * 'unsafe' means any data conversions may be done.\n", " | subok : bool, optional\n", " | If True, then sub-classes will be passed-through (default), otherwise\n", " | the returned array will be forced to be a base-class array.\n", " | copy : bool, optional\n", " | By default, astype always returns a newly allocated array. If this\n", " | is set to false, and the `dtype`, `order`, and `subok`\n", " | requirements are satisfied, the input array is returned instead\n", " | of a copy.\n", " | \n", " | Returns\n", " | -------\n", " | arr_t : ndarray\n", " | Unless `copy` is False and the other conditions for returning the input\n", " | array are satisfied (see description for `copy` input parameter), `arr_t`\n", " | is a new array of the same shape as the input array, with dtype, order\n", " | given by `dtype`, `order`.\n", " | \n", " | Notes\n", " | -----\n", " | .. versionchanged:: 1.17.0\n", " | Casting between a simple data type and a structured one is possible only\n", " | for \"unsafe\" casting. Casting to multiple fields is allowed, but\n", " | casting from multiple fields is not.\n", " | \n", " | .. versionchanged:: 1.9.0\n", " | Casting from numeric to string types in 'safe' casting mode requires\n", " | that the string dtype length is long enough to store the max\n", " | integer/float value converted.\n", " | \n", " | Raises\n", " | ------\n", " | ComplexWarning\n", " | When casting from complex to float or int. To avoid this,\n", " | one should use ``a.real.astype(t)``.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 2.5])\n", " | >>> x\n", " | array([1. , 2. , 2.5])\n", " | \n", " | >>> x.astype(int)\n", " | array([1, 2, 2])\n", " | \n", " | byteswap(...)\n", " | a.byteswap(inplace=False)\n", " | \n", " | Swap the bytes of the array elements\n", " | \n", " | Toggle between low-endian and big-endian data representation by\n", " | returning a byteswapped array, optionally swapped in-place.\n", " | Arrays of byte-strings are not swapped. The real and imaginary\n", " | parts of a complex number are swapped individually.\n", " | \n", " | Parameters\n", " | ----------\n", " | inplace : bool, optional\n", " | If ``True``, swap bytes in-place, default is ``False``.\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | The byteswapped array. If `inplace` is ``True``, this is\n", " | a view to self.\n", " | \n", " | Examples\n", " | --------\n", " | >>> A = np.array([1, 256, 8755], dtype=np.int16)\n", " | >>> list(map(hex, A))\n", " | ['0x1', '0x100', '0x2233']\n", " | >>> A.byteswap(inplace=True)\n", " | array([ 256, 1, 13090], dtype=int16)\n", " | >>> list(map(hex, A))\n", " | ['0x100', '0x1', '0x3322']\n", " | \n", " | Arrays of byte-strings are not swapped\n", " | \n", " | >>> A = np.array([b'ceg', b'fac'])\n", " | >>> A.byteswap()\n", " | array([b'ceg', b'fac'], dtype='|S3')\n", " | \n", " | ``A.newbyteorder().byteswap()`` produces an array with the same values\n", " | but different representation in memory\n", " | \n", " | >>> A = np.array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0,\n", " | 0, 0], dtype=uint8)\n", " | >>> A.newbyteorder().byteswap(inplace=True)\n", " | array([1, 2, 3])\n", " | >>> A.view(np.uint8)\n", " | array([0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0,\n", " | 0, 3], dtype=uint8)\n", " | \n", " | choose(...)\n", " | a.choose(choices, out=None, mode='raise')\n", " | \n", " | Use an index array to construct a new array from a set of choices.\n", " | \n", " | Refer to `numpy.choose` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.choose : equivalent function\n", " | \n", " | clip(...)\n", " | a.clip(min=None, max=None, out=None, **kwargs)\n", " | \n", " | Return an array whose values are limited to ``[min, max]``.\n", " | One of max or min must be given.\n", " | \n", " | Refer to `numpy.clip` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.clip : equivalent function\n", " | \n", " | compress(...)\n", " | a.compress(condition, axis=None, out=None)\n", " | \n", " | Return selected slices of this array along given axis.\n", " | \n", " | Refer to `numpy.compress` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.compress : equivalent function\n", " | \n", " | conj(...)\n", " | a.conj()\n", " | \n", " | Complex-conjugate all elements.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | conjugate(...)\n", " | a.conjugate()\n", " | \n", " | Return the complex conjugate, element-wise.\n", " | \n", " | Refer to `numpy.conjugate` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.conjugate : equivalent function\n", " | \n", " | copy(...)\n", " | a.copy(order='C')\n", " | \n", " | Return a copy of the array.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | Controls the memory layout of the copy. 'C' means C-order,\n", " | 'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,\n", " | 'C' otherwise. 'K' means match the layout of `a` as closely\n", " | as possible. (Note that this function and :func:`numpy.copy` are very\n", " | similar, but have different default values for their order=\n", " | arguments.)\n", " | \n", " | See also\n", " | --------\n", " | numpy.copy\n", " | numpy.copyto\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([[1,2,3],[4,5,6]], order='F')\n", " | \n", " | >>> y = x.copy()\n", " | \n", " | >>> x.fill(0)\n", " | \n", " | >>> x\n", " | array([[0, 0, 0],\n", " | [0, 0, 0]])\n", " | \n", " | >>> y\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | \n", " | >>> y.flags['C_CONTIGUOUS']\n", " | True\n", " | \n", " | cumprod(...)\n", " | a.cumprod(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative product of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumprod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumprod : equivalent function\n", " | \n", " | cumsum(...)\n", " | a.cumsum(axis=None, dtype=None, out=None)\n", " | \n", " | Return the cumulative sum of the elements along the given axis.\n", " | \n", " | Refer to `numpy.cumsum` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.cumsum : equivalent function\n", " | \n", " | diagonal(...)\n", " | a.diagonal(offset=0, axis1=0, axis2=1)\n", " | \n", " | Return specified diagonals. In NumPy 1.9 the returned array is a\n", " | read-only view instead of a copy as in previous NumPy versions. In\n", " | a future version the read-only restriction will be removed.\n", " | \n", " | Refer to :func:`numpy.diagonal` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.diagonal : equivalent function\n", " | \n", " | dot(...)\n", " | a.dot(b, out=None)\n", " | \n", " | Dot product of two arrays.\n", " | \n", " | Refer to `numpy.dot` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dot : equivalent function\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.eye(2)\n", " | >>> b = np.ones((2, 2)) * 2\n", " | >>> a.dot(b)\n", " | array([[2., 2.],\n", " | [2., 2.]])\n", " | \n", " | This array method can be conveniently chained:\n", " | \n", " | >>> a.dot(b).dot(b)\n", " | array([[8., 8.],\n", " | [8., 8.]])\n", " | \n", " | dump(...)\n", " | a.dump(file)\n", " | \n", " | Dump a pickle of the array to the specified file.\n", " | The array can be read back with pickle.load or numpy.load.\n", " | \n", " | Parameters\n", " | ----------\n", " | file : str or Path\n", " | A string naming the dump file.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | dumps(...)\n", " | a.dumps()\n", " | \n", " | Returns the pickle of the array as a string.\n", " | pickle.loads or numpy.loads will convert the string back to an array.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | fill(...)\n", " | a.fill(value)\n", " | \n", " | Fill the array with a scalar value.\n", " | \n", " | Parameters\n", " | ----------\n", " | value : scalar\n", " | All elements of `a` will be assigned this value.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([1, 2])\n", " | >>> a.fill(0)\n", " | >>> a\n", " | array([0, 0])\n", " | >>> a = np.empty(2)\n", " | >>> a.fill(1)\n", " | >>> a\n", " | array([1., 1.])\n", " | \n", " | flatten(...)\n", " | a.flatten(order='C')\n", " | \n", " | Return a copy of the array collapsed into one dimension.\n", " | \n", " | Parameters\n", " | ----------\n", " | order : {'C', 'F', 'A', 'K'}, optional\n", " | 'C' means to flatten in row-major (C-style) order.\n", " | 'F' means to flatten in column-major (Fortran-\n", " | style) order. 'A' means to flatten in column-major\n", " | order if `a` is Fortran *contiguous* in memory,\n", " | row-major order otherwise. 'K' means to flatten\n", " | `a` in the order the elements occur in memory.\n", " | The default is 'C'.\n", " | \n", " | Returns\n", " | -------\n", " | y : ndarray\n", " | A copy of the input array, flattened to one dimension.\n", " | \n", " | See Also\n", " | --------\n", " | ravel : Return a flattened array.\n", " | flat : A 1-D flat iterator over the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,2], [3,4]])\n", " | >>> a.flatten()\n", " | array([1, 2, 3, 4])\n", " | >>> a.flatten('F')\n", " | array([1, 3, 2, 4])\n", " | \n", " | getfield(...)\n", " | a.getfield(dtype, offset=0)\n", " | \n", " | Returns a field of the given array as a certain type.\n", " | \n", " | A field is a view of the array data with a given data-type. The values in\n", " | the view are determined by the given type and the offset into the current\n", " | array in bytes. The offset needs to be such that the view dtype fits in the\n", " | array dtype; for example an array of dtype complex128 has 16-byte elements.\n", " | If taking a view with a 32-bit integer (4 bytes), the offset needs to be\n", " | between 0 and 12 bytes.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : str or dtype\n", " | The data type of the view. The dtype size of the view can not be larger\n", " | than that of the array itself.\n", " | offset : int\n", " | Number of bytes to skip before beginning the element view.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.diag([1.+1.j]*2)\n", " | >>> x[1, 1] = 2 + 4.j\n", " | >>> x\n", " | array([[1.+1.j, 0.+0.j],\n", " | [0.+0.j, 2.+4.j]])\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0.],\n", " | [0., 2.]])\n", " | \n", " | By choosing an offset of 8 bytes we can select the complex part of the\n", " | array for our view:\n", " | \n", " | >>> x.getfield(np.float64, offset=8)\n", " | array([[1., 0.],\n", " | [0., 4.]])\n", " | \n", " | item(...)\n", " | a.item(*args)\n", " | \n", " | Copy an element of an array to a standard Python scalar and return it.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments (variable number and type)\n", " | \n", " | * none: in this case, the method only works for arrays\n", " | with one element (`a.size == 1`), which element is\n", " | copied into a standard Python scalar object and returned.\n", " | \n", " | * int_type: this argument is interpreted as a flat index into\n", " | the array, specifying which element to copy and return.\n", " | \n", " | * tuple of int_types: functions as does a single int_type argument,\n", " | except that the argument is interpreted as an nd-index into the\n", " | array.\n", " | \n", " | Returns\n", " | -------\n", " | z : Standard Python scalar object\n", " | A copy of the specified element of the array as a suitable\n", " | Python scalar\n", " | \n", " | Notes\n", " | -----\n", " | When the data type of `a` is longdouble or clongdouble, item() returns\n", " | a scalar array object because there is no available Python scalar that\n", " | would not lose information. Void arrays return a buffer object for item(),\n", " | unless fields are defined, in which case a tuple is returned.\n", " | \n", " | `item` is very similar to a[args], except, instead of an array scalar,\n", " | a standard Python scalar is returned. This can be useful for speeding up\n", " | access to elements of the array and doing arithmetic on elements of the\n", " | array using Python's optimized math.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.item(3)\n", " | 1\n", " | >>> x.item(7)\n", " | 0\n", " | >>> x.item((0, 1))\n", " | 2\n", " | >>> x.item((2, 2))\n", " | 1\n", " | \n", " | itemset(...)\n", " | a.itemset(*args)\n", " | \n", " | Insert scalar into an array (scalar is cast to array's dtype, if possible)\n", " | \n", " | There must be at least 1 argument, and define the last argument\n", " | as *item*. Then, ``a.itemset(*args)`` is equivalent to but faster\n", " | than ``a[args] = item``. The item should be a scalar value and `args`\n", " | must select a single item in the array `a`.\n", " | \n", " | Parameters\n", " | ----------\n", " | \\*args : Arguments\n", " | If one argument: a scalar, only used in case `a` is of size 1.\n", " | If two arguments: the last argument is the value to be set\n", " | and must be a scalar, the first argument specifies a single array\n", " | element location. It is either an int or a tuple.\n", " | \n", " | Notes\n", " | -----\n", " | Compared to indexing syntax, `itemset` provides some speed increase\n", " | for placing a scalar into a particular location in an `ndarray`,\n", " | if you must do this. However, generally this is discouraged:\n", " | among other problems, it complicates the appearance of the code.\n", " | Also, when using `itemset` (and `item`) inside a loop, be sure\n", " | to assign the methods to a local variable to avoid the attribute\n", " | look-up at each loop iteration.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.random.seed(123)\n", " | >>> x = np.random.randint(9, size=(3, 3))\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 3, 6],\n", " | [1, 0, 1]])\n", " | >>> x.itemset(4, 0)\n", " | >>> x.itemset((2, 2), 9)\n", " | >>> x\n", " | array([[2, 2, 6],\n", " | [1, 0, 6],\n", " | [1, 0, 9]])\n", " | \n", " | max(...)\n", " | a.max(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the maximum along a given axis.\n", " | \n", " | Refer to `numpy.amax` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amax : equivalent function\n", " | \n", " | mean(...)\n", " | a.mean(axis=None, dtype=None, out=None, keepdims=False)\n", " | \n", " | Returns the average of the array elements along given axis.\n", " | \n", " | Refer to `numpy.mean` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.mean : equivalent function\n", " | \n", " | min(...)\n", " | a.min(axis=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Return the minimum along a given axis.\n", " | \n", " | Refer to `numpy.amin` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.amin : equivalent function\n", " | \n", " | newbyteorder(...)\n", " | arr.newbyteorder(new_order='S')\n", " | \n", " | Return the array with the same data viewed with a different byte order.\n", " | \n", " | Equivalent to::\n", " | \n", " | arr.view(arr.dtype.newbytorder(new_order))\n", " | \n", " | Changes are also made in all fields and sub-arrays of the array data\n", " | type.\n", " | \n", " | \n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : string, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | below. `new_order` codes can be any of:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_arr : array\n", " | New array object with the dtype reflecting given change to the\n", " | byte order.\n", " | \n", " | nonzero(...)\n", " | a.nonzero()\n", " | \n", " | Return the indices of the elements that are non-zero.\n", " | \n", " | Refer to `numpy.nonzero` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.nonzero : equivalent function\n", " | \n", " | partition(...)\n", " | a.partition(kth, axis=-1, kind='introselect', order=None)\n", " | \n", " | Rearranges the elements in the array in such a way that the value of the\n", " | element in kth position is in the position it would be in a sorted array.\n", " | All elements smaller than the kth element are moved before this element and\n", " | all equal or greater are moved behind it. The ordering of the elements in\n", " | the two partitions is undefined.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | Parameters\n", " | ----------\n", " | kth : int or sequence of ints\n", " | Element index to partition by. The kth element value will be in its\n", " | final sorted position and all smaller elements will be moved before it\n", " | and all equal or greater elements behind it.\n", " | The order of all elements in the partitions is undefined.\n", " | If provided with a sequence of kth it will partition all elements\n", " | indexed by kth of them into their sorted position at once.\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'introselect'}, optional\n", " | Selection algorithm. Default is 'introselect'.\n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need to be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.partition : Return a parititioned copy of an array.\n", " | argpartition : Indirect partition.\n", " | sort : Full sort.\n", " | \n", " | Notes\n", " | -----\n", " | See ``np.partition`` for notes on the different algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([3, 4, 2, 1])\n", " | >>> a.partition(3)\n", " | >>> a\n", " | array([2, 1, 3, 4])\n", " | \n", " | >>> a.partition((1, 3))\n", " | >>> a\n", " | array([1, 2, 3, 4])\n", " | \n", " | prod(...)\n", " | a.prod(axis=None, dtype=None, out=None, keepdims=False, initial=1, where=True)\n", " | \n", " | Return the product of the array elements over the given axis\n", " | \n", " | Refer to `numpy.prod` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.prod : equivalent function\n", " | \n", " | ptp(...)\n", " | a.ptp(axis=None, out=None, keepdims=False)\n", " | \n", " | Peak to peak (maximum - minimum) value along a given axis.\n", " | \n", " | Refer to `numpy.ptp` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ptp : equivalent function\n", " | \n", " | put(...)\n", " | a.put(indices, values, mode='raise')\n", " | \n", " | Set ``a.flat[n] = values[n]`` for all `n` in indices.\n", " | \n", " | Refer to `numpy.put` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.put : equivalent function\n", " | \n", " | ravel(...)\n", " | a.ravel([order])\n", " | \n", " | Return a flattened array.\n", " | \n", " | Refer to `numpy.ravel` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ravel : equivalent function\n", " | \n", " | ndarray.flat : a flat iterator on the array.\n", " | \n", " | repeat(...)\n", " | a.repeat(repeats, axis=None)\n", " | \n", " | Repeat elements of an array.\n", " | \n", " | Refer to `numpy.repeat` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.repeat : equivalent function\n", " | \n", " | reshape(...)\n", " | a.reshape(shape, order='C')\n", " | \n", " | Returns an array containing the same data with a new shape.\n", " | \n", " | Refer to `numpy.reshape` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : equivalent function\n", " | \n", " | Notes\n", " | -----\n", " | Unlike the free function `numpy.reshape`, this method on `ndarray` allows\n", " | the elements of the shape parameter to be passed in as separate arguments.\n", " | For example, ``a.reshape(10, 11)`` is equivalent to\n", " | ``a.reshape((10, 11))``.\n", " | \n", " | resize(...)\n", " | a.resize(new_shape, refcheck=True)\n", " | \n", " | Change shape and size of array in-place.\n", " | \n", " | Parameters\n", " | ----------\n", " | new_shape : tuple of ints, or `n` ints\n", " | Shape of resized array.\n", " | refcheck : bool, optional\n", " | If False, reference count will not be checked. Default is True.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | Raises\n", " | ------\n", " | ValueError\n", " | If `a` does not own its own data or references or views to it exist,\n", " | and the data memory must be changed.\n", " | PyPy only: will always raise if the data memory must be changed, since\n", " | there is no reliable way to determine if references or views to it\n", " | exist.\n", " | \n", " | SystemError\n", " | If the `order` keyword argument is specified. This behaviour is a\n", " | bug in NumPy.\n", " | \n", " | See Also\n", " | --------\n", " | resize : Return a new array with the specified shape.\n", " | \n", " | Notes\n", " | -----\n", " | This reallocates space for the data area if necessary.\n", " | \n", " | Only contiguous arrays (data elements consecutive in memory) can be\n", " | resized.\n", " | \n", " | The purpose of the reference count check is to make sure you\n", " | do not use this array as a buffer for another Python object and then\n", " | reallocate the memory. However, reference counts can increase in\n", " | other ways so if you are sure that you have not shared the memory\n", " | for this array with another Python object, then you may safely set\n", " | `refcheck` to False.\n", " | \n", " | Examples\n", " | --------\n", " | Shrinking an array: array is flattened (in the order that the data are\n", " | stored in memory), resized, and reshaped:\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='C')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [1]])\n", " | \n", " | >>> a = np.array([[0, 1], [2, 3]], order='F')\n", " | >>> a.resize((2, 1))\n", " | >>> a\n", " | array([[0],\n", " | [2]])\n", " | \n", " | Enlarging an array: as above, but missing entries are filled with zeros:\n", " | \n", " | >>> b = np.array([[0, 1], [2, 3]])\n", " | >>> b.resize(2, 3) # new_shape parameter doesn't have to be a tuple\n", " | >>> b\n", " | array([[0, 1, 2],\n", " | [3, 0, 0]])\n", " | \n", " | Referencing an array prevents resizing...\n", " | \n", " | >>> c = a\n", " | >>> a.resize((1, 1))\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: cannot resize an array that references or is referenced ...\n", " | \n", " | Unless `refcheck` is False:\n", " | \n", " | >>> a.resize((1, 1), refcheck=False)\n", " | >>> a\n", " | array([[0]])\n", " | >>> c\n", " | array([[0]])\n", " | \n", " | round(...)\n", " | a.round(decimals=0, out=None)\n", " | \n", " | Return `a` with each element rounded to the given number of decimals.\n", " | \n", " | Refer to `numpy.around` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.around : equivalent function\n", " | \n", " | searchsorted(...)\n", " | a.searchsorted(v, side='left', sorter=None)\n", " | \n", " | Find indices where elements of v should be inserted in a to maintain order.\n", " | \n", " | For full documentation, see `numpy.searchsorted`\n", " | \n", " | See Also\n", " | --------\n", " | numpy.searchsorted : equivalent function\n", " | \n", " | setfield(...)\n", " | a.setfield(val, dtype, offset=0)\n", " | \n", " | Put a value into a specified place in a field defined by a data-type.\n", " | \n", " | Place `val` into `a`'s field defined by `dtype` and beginning `offset`\n", " | bytes into the field.\n", " | \n", " | Parameters\n", " | ----------\n", " | val : object\n", " | Value to be placed in field.\n", " | dtype : dtype object\n", " | Data-type of the field in which to place `val`.\n", " | offset : int, optional\n", " | The number of bytes into the field at which to place `val`.\n", " | \n", " | Returns\n", " | -------\n", " | None\n", " | \n", " | See Also\n", " | --------\n", " | getfield\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.eye(3)\n", " | >>> x.getfield(np.float64)\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | >>> x.setfield(3, np.int32)\n", " | >>> x.getfield(np.int32)\n", " | array([[3, 3, 3],\n", " | [3, 3, 3],\n", " | [3, 3, 3]], dtype=int32)\n", " | >>> x\n", " | array([[1.0e+000, 1.5e-323, 1.5e-323],\n", " | [1.5e-323, 1.0e+000, 1.5e-323],\n", " | [1.5e-323, 1.5e-323, 1.0e+000]])\n", " | >>> x.setfield(np.eye(3), np.int32)\n", " | >>> x\n", " | array([[1., 0., 0.],\n", " | [0., 1., 0.],\n", " | [0., 0., 1.]])\n", " | \n", " | setflags(...)\n", " | a.setflags(write=None, align=None, uic=None)\n", " | \n", " | Set array flags WRITEABLE, ALIGNED, (WRITEBACKIFCOPY and UPDATEIFCOPY),\n", " | respectively.\n", " | \n", " | These Boolean-valued flags affect how numpy interprets the memory\n", " | area used by `a` (see Notes below). The ALIGNED flag can only\n", " | be set to True if the data is actually aligned according to the type.\n", " | The WRITEBACKIFCOPY and (deprecated) UPDATEIFCOPY flags can never be set\n", " | to True. The flag WRITEABLE can only be set to True if the array owns its\n", " | own memory, or the ultimate owner of the memory exposes a writeable buffer\n", " | interface, or is a string. (The exception for string is made so that\n", " | unpickling can be done without copying memory.)\n", " | \n", " | Parameters\n", " | ----------\n", " | write : bool, optional\n", " | Describes whether or not `a` can be written to.\n", " | align : bool, optional\n", " | Describes whether or not `a` is aligned properly for its type.\n", " | uic : bool, optional\n", " | Describes whether or not `a` is a copy of another \"base\" array.\n", " | \n", " | Notes\n", " | -----\n", " | Array flags provide information about how the memory area used\n", " | for the array is to be interpreted. There are 7 Boolean flags\n", " | in use, only four of which can be changed by the user:\n", " | WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED.\n", " | \n", " | WRITEABLE (W) the data area can be written to;\n", " | \n", " | ALIGNED (A) the data and strides are aligned appropriately for the hardware\n", " | (as determined by the compiler);\n", " | \n", " | UPDATEIFCOPY (U) (deprecated), replaced by WRITEBACKIFCOPY;\n", " | \n", " | WRITEBACKIFCOPY (X) this array is a copy of some other array (referenced\n", " | by .base). When the C-API function PyArray_ResolveWritebackIfCopy is\n", " | called, the base array will be updated with the contents of this array.\n", " | \n", " | All flags can be accessed using the single (upper case) letter as well\n", " | as the full name.\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.array([[3, 1, 7],\n", " | ... [2, 0, 0],\n", " | ... [8, 5, 9]])\n", " | >>> y\n", " | array([[3, 1, 7],\n", " | [2, 0, 0],\n", " | [8, 5, 9]])\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : True\n", " | ALIGNED : True\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(write=0, align=0)\n", " | >>> y.flags\n", " | C_CONTIGUOUS : True\n", " | F_CONTIGUOUS : False\n", " | OWNDATA : True\n", " | WRITEABLE : False\n", " | ALIGNED : False\n", " | WRITEBACKIFCOPY : False\n", " | UPDATEIFCOPY : False\n", " | >>> y.setflags(uic=1)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: cannot set WRITEBACKIFCOPY flag to True\n", " | \n", " | sort(...)\n", " | a.sort(axis=-1, kind=None, order=None)\n", " | \n", " | Sort an array in-place. Refer to `numpy.sort` for full documentation.\n", " | \n", " | Parameters\n", " | ----------\n", " | axis : int, optional\n", " | Axis along which to sort. Default is -1, which means sort along the\n", " | last axis.\n", " | kind : {'quicksort', 'mergesort', 'heapsort', 'stable'}, optional\n", " | Sorting algorithm. The default is 'quicksort'. Note that both 'stable'\n", " | and 'mergesort' use timsort under the covers and, in general, the\n", " | actual implementation will vary with datatype. The 'mergesort' option\n", " | is retained for backwards compatibility.\n", " | \n", " | .. versionchanged:: 1.15.0.\n", " | The 'stable' option was added.\n", " | \n", " | order : str or list of str, optional\n", " | When `a` is an array with fields defined, this argument specifies\n", " | which fields to compare first, second, etc. A single field can\n", " | be specified as a string, and not all fields need be specified,\n", " | but unspecified fields will still be used, in the order in which\n", " | they come up in the dtype, to break ties.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.sort : Return a sorted copy of an array.\n", " | numpy.argsort : Indirect sort.\n", " | numpy.lexsort : Indirect stable sort on multiple keys.\n", " | numpy.searchsorted : Find elements in sorted array.\n", " | numpy.partition: Partial sort.\n", " | \n", " | Notes\n", " | -----\n", " | See `numpy.sort` for notes on the different sorting algorithms.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1,4], [3,1]])\n", " | >>> a.sort(axis=1)\n", " | >>> a\n", " | array([[1, 4],\n", " | [1, 3]])\n", " | >>> a.sort(axis=0)\n", " | >>> a\n", " | array([[1, 3],\n", " | [1, 4]])\n", " | \n", " | Use the `order` keyword to specify a field to use when sorting a\n", " | structured array:\n", " | \n", " | >>> a = np.array([('a', 2), ('c', 1)], dtype=[('x', 'S1'), ('y', int)])\n", " | >>> a.sort(order='y')\n", " | >>> a\n", " | array([(b'c', 1), (b'a', 2)],\n", " | dtype=[('x', 'S1'), ('y', '>> x = np.array([[0, 1], [2, 3]], dtype='>> x.tobytes()\n", " | b'\\x00\\x00\\x01\\x00\\x02\\x00\\x03\\x00'\n", " | >>> x.tobytes('C') == x.tobytes()\n", " | True\n", " | >>> x.tobytes('F')\n", " | b'\\x00\\x00\\x02\\x00\\x01\\x00\\x03\\x00'\n", " | \n", " | tofile(...)\n", " | a.tofile(fid, sep=\"\", format=\"%s\")\n", " | \n", " | Write array to a file as text or binary (default).\n", " | \n", " | Data is always written in 'C' order, independent of the order of `a`.\n", " | The data produced by this method can be recovered using the function\n", " | fromfile().\n", " | \n", " | Parameters\n", " | ----------\n", " | fid : file or str or Path\n", " | An open file object, or a string containing a filename.\n", " | \n", " | .. versionchanged:: 1.17.0\n", " | `pathlib.Path` objects are now accepted.\n", " | \n", " | sep : str\n", " | Separator between array items for text output.\n", " | If \"\" (empty), a binary file is written, equivalent to\n", " | ``file.write(a.tobytes())``.\n", " | format : str\n", " | Format string for text file output.\n", " | Each entry in the array is formatted to text by first converting\n", " | it to the closest Python type, and then using \"format\" % item.\n", " | \n", " | Notes\n", " | -----\n", " | This is a convenience function for quick storage of array data.\n", " | Information on endianness and precision is lost, so this method is not a\n", " | good choice for files intended to archive data or transport data between\n", " | machines with different endianness. Some of these problems can be overcome\n", " | by outputting the data as text files, at the expense of speed and file\n", " | size.\n", " | \n", " | When fid is a file object, array contents are directly written to the\n", " | file, bypassing the file object's ``write`` method. As a result, tofile\n", " | cannot be used with files objects supporting compression (e.g., GzipFile)\n", " | or file-like objects that do not support ``fileno()`` (e.g., BytesIO).\n", " | \n", " | tolist(...)\n", " | a.tolist()\n", " | \n", " | Return the array as an ``a.ndim``-levels deep nested list of Python scalars.\n", " | \n", " | Return a copy of the array data as a (nested) Python list.\n", " | Data items are converted to the nearest compatible builtin Python type, via\n", " | the `~numpy.ndarray.item` function.\n", " | \n", " | If ``a.ndim`` is 0, then since the depth of the nested list is 0, it will\n", " | not be a list at all, but a simple Python scalar.\n", " | \n", " | Parameters\n", " | ----------\n", " | none\n", " | \n", " | Returns\n", " | -------\n", " | y : object, or list of object, or list of list of object, or ...\n", " | The possibly nested list of array elements.\n", " | \n", " | Notes\n", " | -----\n", " | The array may be recreated via ``a = np.array(a.tolist())``, although this\n", " | may sometimes lose precision.\n", " | \n", " | Examples\n", " | --------\n", " | For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``,\n", " | except that ``tolist`` changes numpy scalars to Python scalars:\n", " | \n", " | >>> a = np.uint32([1, 2])\n", " | >>> a_list = list(a)\n", " | >>> a_list\n", " | [1, 2]\n", " | >>> type(a_list[0])\n", " | \n", " | >>> a_tolist = a.tolist()\n", " | >>> a_tolist\n", " | [1, 2]\n", " | >>> type(a_tolist[0])\n", " | \n", " | \n", " | Additionally, for a 2D array, ``tolist`` applies recursively:\n", " | \n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> list(a)\n", " | [array([1, 2]), array([3, 4])]\n", " | >>> a.tolist()\n", " | [[1, 2], [3, 4]]\n", " | \n", " | The base case for this recursion is a 0D array:\n", " | \n", " | >>> a = np.array(1)\n", " | >>> list(a)\n", " | Traceback (most recent call last):\n", " | ...\n", " | TypeError: iteration over a 0-d array\n", " | >>> a.tolist()\n", " | 1\n", " | \n", " | tostring(...)\n", " | a.tostring(order='C')\n", " | \n", " | A compatibility alias for `tobytes`, with exactly the same behavior.\n", " | \n", " | Despite its name, it returns `bytes` not `str`\\ s.\n", " | \n", " | .. deprecated:: 1.19.0\n", " | \n", " | trace(...)\n", " | a.trace(offset=0, axis1=0, axis2=1, dtype=None, out=None)\n", " | \n", " | Return the sum along diagonals of the array.\n", " | \n", " | Refer to `numpy.trace` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.trace : equivalent function\n", " | \n", " | transpose(...)\n", " | a.transpose(*axes)\n", " | \n", " | Returns a view of the array with axes transposed.\n", " | \n", " | For a 1-D array this has no effect, as a transposed vector is simply the\n", " | same vector. To convert a 1-D array into a 2D column vector, an additional\n", " | dimension must be added. `np.atleast2d(a).T` achieves this, as does\n", " | `a[:, np.newaxis]`.\n", " | For a 2-D array, this is a standard matrix transpose.\n", " | For an n-D array, if axes are given, their order indicates how the\n", " | axes are permuted (see Examples). If axes are not provided and\n", " | ``a.shape = (i[0], i[1], ... i[n-2], i[n-1])``, then\n", " | ``a.transpose().shape = (i[n-1], i[n-2], ... i[1], i[0])``.\n", " | \n", " | Parameters\n", " | ----------\n", " | axes : None, tuple of ints, or `n` ints\n", " | \n", " | * None or no argument: reverses the order of the axes.\n", " | \n", " | * tuple of ints: `i` in the `j`-th place in the tuple means `a`'s\n", " | `i`-th axis becomes `a.transpose()`'s `j`-th axis.\n", " | \n", " | * `n` ints: same as an n-tuple of the same ints (this form is\n", " | intended simply as a \"convenience\" alternative to the tuple form)\n", " | \n", " | Returns\n", " | -------\n", " | out : ndarray\n", " | View of `a`, with axes suitably permuted.\n", " | \n", " | See Also\n", " | --------\n", " | ndarray.T : Array property returning the array transposed.\n", " | ndarray.reshape : Give a new shape to an array without changing its data.\n", " | \n", " | Examples\n", " | --------\n", " | >>> a = np.array([[1, 2], [3, 4]])\n", " | >>> a\n", " | array([[1, 2],\n", " | [3, 4]])\n", " | >>> a.transpose()\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose((1, 0))\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | >>> a.transpose(1, 0)\n", " | array([[1, 3],\n", " | [2, 4]])\n", " | \n", " | var(...)\n", " | a.var(axis=None, dtype=None, out=None, ddof=0, keepdims=False)\n", " | \n", " | Returns the variance of the array elements, along given axis.\n", " | \n", " | Refer to `numpy.var` for full documentation.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.var : equivalent function\n", " | \n", " | view(...)\n", " | a.view([dtype][, type])\n", " | \n", " | New view of array with the same data.\n", " | \n", " | .. note::\n", " | Passing None for ``dtype`` is different from omitting the parameter,\n", " | since the former invokes ``dtype(None)`` which is an alias for\n", " | ``dtype('float_')``.\n", " | \n", " | Parameters\n", " | ----------\n", " | dtype : data-type or ndarray sub-class, optional\n", " | Data-type descriptor of the returned view, e.g., float32 or int16.\n", " | Omitting it results in the view having the same data-type as `a`.\n", " | This argument can also be specified as an ndarray sub-class, which\n", " | then specifies the type of the returned object (this is equivalent to\n", " | setting the ``type`` parameter).\n", " | type : Python type, optional\n", " | Type of the returned view, e.g., ndarray or matrix. Again, omission\n", " | of the parameter results in type preservation.\n", " | \n", " | Notes\n", " | -----\n", " | ``a.view()`` is used two different ways:\n", " | \n", " | ``a.view(some_dtype)`` or ``a.view(dtype=some_dtype)`` constructs a view\n", " | of the array's memory with a different data-type. This can cause a\n", " | reinterpretation of the bytes of memory.\n", " | \n", " | ``a.view(ndarray_subclass)`` or ``a.view(type=ndarray_subclass)`` just\n", " | returns an instance of `ndarray_subclass` that looks at the same array\n", " | (same shape, dtype, etc.) This does not cause a reinterpretation of the\n", " | memory.\n", " | \n", " | For ``a.view(some_dtype)``, if ``some_dtype`` has a different number of\n", " | bytes per entry than the previous dtype (for example, converting a\n", " | regular array to a structured array), then the behavior of the view\n", " | cannot be predicted just from the superficial appearance of ``a`` (shown\n", " | by ``print(a)``). It also depends on exactly how ``a`` is stored in\n", " | memory. Therefore if ``a`` is C-ordered versus fortran-ordered, versus\n", " | defined as a slice or transpose, etc., the view may give different\n", " | results.\n", " | \n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([(1, 2)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | \n", " | Viewing array data using a different type and dtype:\n", " | \n", " | >>> y = x.view(dtype=np.int16, type=np.matrix)\n", " | >>> y\n", " | matrix([[513]], dtype=int16)\n", " | >>> print(type(y))\n", " | \n", " | \n", " | Creating a view on a structured array so it can be used in calculations\n", " | \n", " | >>> x = np.array([(1, 2),(3,4)], dtype=[('a', np.int8), ('b', np.int8)])\n", " | >>> xv = x.view(dtype=np.int8).reshape(-1,2)\n", " | >>> xv\n", " | array([[1, 2],\n", " | [3, 4]], dtype=int8)\n", " | >>> xv.mean(0)\n", " | array([2., 3.])\n", " | \n", " | Making changes to the view changes the underlying array\n", " | \n", " | >>> xv[0,1] = 20\n", " | >>> x\n", " | array([(1, 20), (3, 4)], dtype=[('a', 'i1'), ('b', 'i1')])\n", " | \n", " | Using a view to convert an array to a recarray:\n", " | \n", " | >>> z = x.view(np.recarray)\n", " | >>> z.a\n", " | array([1, 3], dtype=int8)\n", " | \n", " | Views share data:\n", " | \n", " | >>> x[0] = (9, 10)\n", " | >>> z[0]\n", " | (9, 10)\n", " | \n", " | Views that change the dtype size (bytes per entry) should normally be\n", " | avoided on arrays defined by slices, transposes, fortran-ordering, etc.:\n", " | \n", " | >>> x = np.array([[1,2,3],[4,5,6]], dtype=np.int16)\n", " | >>> y = x[:, 0:2]\n", " | >>> y\n", " | array([[1, 2],\n", " | [4, 5]], dtype=int16)\n", " | >>> y.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: To change to a dtype of a different size, the array must be C-contiguous\n", " | >>> z = y.copy()\n", " | >>> z.view(dtype=[('width', np.int16), ('length', np.int16)])\n", " | array([[(1, 2)],\n", " | [(4, 5)]], dtype=[('width', '>> x = np.array([[1.,2.],[3.,4.]])\n", " | >>> x\n", " | array([[ 1., 2.],\n", " | [ 3., 4.]])\n", " | >>> x.T\n", " | array([[ 1., 3.],\n", " | [ 2., 4.]])\n", " | >>> x = np.array([1.,2.,3.,4.])\n", " | >>> x\n", " | array([ 1., 2., 3., 4.])\n", " | >>> x.T\n", " | array([ 1., 2., 3., 4.])\n", " | \n", " | See Also\n", " | --------\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side.\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: C-struct side.\n", " | \n", " | base\n", " | Base object if memory is from some other object.\n", " | \n", " | Examples\n", " | --------\n", " | The base of an array that owns its memory is None:\n", " | \n", " | >>> x = np.array([1,2,3,4])\n", " | >>> x.base is None\n", " | True\n", " | \n", " | Slicing creates a view, whose memory is shared with x:\n", " | \n", " | >>> y = x[2:]\n", " | >>> y.base is x\n", " | True\n", " | \n", " | ctypes\n", " | An object to simplify the interaction of the array with the ctypes\n", " | module.\n", " | \n", " | This attribute creates an object that makes it easier to use arrays\n", " | when calling shared libraries with the ctypes module. The returned\n", " | object has, among others, data, shape, and strides attributes (see\n", " | Notes below) which themselves return ctypes objects that can be used\n", " | as arguments to a shared library.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | c : Python object\n", " | Possessing attributes data, shape, strides, etc.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ctypeslib\n", " | \n", " | Notes\n", " | -----\n", " | Below are the public attributes of this object which were documented\n", " | in \"Guide to NumPy\" (we have omitted undocumented public attributes,\n", " | as well as documented private attributes):\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.data\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.shape\n", " | :noindex:\n", " | \n", " | .. autoattribute:: numpy.core._internal._ctypes.strides\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.data_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.shape_as\n", " | :noindex:\n", " | \n", " | .. automethod:: numpy.core._internal._ctypes.strides_as\n", " | :noindex:\n", " | \n", " | If the ctypes module is not available, then the ctypes attribute\n", " | of array objects still returns something useful, but ctypes objects\n", " | are not returned and errors may be raised instead. In particular,\n", " | the object will still have the ``as_parameter`` attribute which will\n", " | return an integer equal to the data attribute.\n", " | \n", " | Examples\n", " | --------\n", " | >>> import ctypes\n", " | >>> x = np.array([[0, 1], [2, 3]], dtype=np.int32)\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]], dtype=int32)\n", " | >>> x.ctypes.data\n", " | 31962608 # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32))\n", " | <__main__.LP_c_uint object at 0x7ff2fc1fc200> # may vary\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint32)).contents\n", " | c_uint(0)\n", " | >>> x.ctypes.data_as(ctypes.POINTER(ctypes.c_uint64)).contents\n", " | c_ulong(4294967296)\n", " | >>> x.ctypes.shape\n", " | # may vary\n", " | >>> x.ctypes.strides\n", " | # may vary\n", " | \n", " | data\n", " | Python buffer object pointing to the start of the array's data.\n", " | \n", " | dtype\n", " | Data-type of the array's elements.\n", " | \n", " | Parameters\n", " | ----------\n", " | None\n", " | \n", " | Returns\n", " | -------\n", " | d : numpy dtype object\n", " | \n", " | See Also\n", " | --------\n", " | numpy.dtype\n", " | \n", " | Examples\n", " | --------\n", " | >>> x\n", " | array([[0, 1],\n", " | [2, 3]])\n", " | >>> x.dtype\n", " | dtype('int32')\n", " | >>> type(x.dtype)\n", " | \n", " | \n", " | flags\n", " | Information about the memory layout of the array.\n", " | \n", " | Attributes\n", " | ----------\n", " | C_CONTIGUOUS (C)\n", " | The data is in a single, C-style contiguous segment.\n", " | F_CONTIGUOUS (F)\n", " | The data is in a single, Fortran-style contiguous segment.\n", " | OWNDATA (O)\n", " | The array owns the memory it uses or borrows it from another object.\n", " | WRITEABLE (W)\n", " | The data area can be written to. Setting this to False locks\n", " | the data, making it read-only. A view (slice, etc.) inherits WRITEABLE\n", " | from its base array at creation time, but a view of a writeable\n", " | array may be subsequently locked while the base array remains writeable.\n", " | (The opposite is not true, in that a view of a locked array may not\n", " | be made writeable. However, currently, locking a base object does not\n", " | lock any views that already reference it, so under that circumstance it\n", " | is possible to alter the contents of a locked array via a previously\n", " | created writeable view onto it.) Attempting to change a non-writeable\n", " | array raises a RuntimeError exception.\n", " | ALIGNED (A)\n", " | The data and all elements are aligned appropriately for the hardware.\n", " | WRITEBACKIFCOPY (X)\n", " | This array is a copy of some other array. The C-API function\n", " | PyArray_ResolveWritebackIfCopy must be called before deallocating\n", " | to the base array will be updated with the contents of this array.\n", " | UPDATEIFCOPY (U)\n", " | (Deprecated, use WRITEBACKIFCOPY) This array is a copy of some other array.\n", " | When this array is\n", " | deallocated, the base array will be updated with the contents of\n", " | this array.\n", " | FNC\n", " | F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | FORC\n", " | F_CONTIGUOUS or C_CONTIGUOUS (one-segment test).\n", " | BEHAVED (B)\n", " | ALIGNED and WRITEABLE.\n", " | CARRAY (CA)\n", " | BEHAVED and C_CONTIGUOUS.\n", " | FARRAY (FA)\n", " | BEHAVED and F_CONTIGUOUS and not C_CONTIGUOUS.\n", " | \n", " | Notes\n", " | -----\n", " | The `flags` object can be accessed dictionary-like (as in ``a.flags['WRITEABLE']``),\n", " | or by using lowercased attribute names (as in ``a.flags.writeable``). Short flag\n", " | names are only supported in dictionary access.\n", " | \n", " | Only the WRITEBACKIFCOPY, UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be\n", " | changed by the user, via direct assignment to the attribute or dictionary\n", " | entry, or by calling `ndarray.setflags`.\n", " | \n", " | The array flags cannot be set arbitrarily:\n", " | \n", " | - UPDATEIFCOPY can only be set ``False``.\n", " | - WRITEBACKIFCOPY can only be set ``False``.\n", " | - ALIGNED can only be set ``True`` if the data is truly aligned.\n", " | - WRITEABLE can only be set ``True`` if the array owns its own memory\n", " | or the ultimate owner of the memory exposes a writeable buffer\n", " | interface or is a string.\n", " | \n", " | Arrays can be both C-style and Fortran-style contiguous simultaneously.\n", " | This is clear for 1-dimensional arrays, but can also be true for higher\n", " | dimensional arrays.\n", " | \n", " | Even for contiguous arrays a stride for a given dimension\n", " | ``arr.strides[dim]`` may be *arbitrary* if ``arr.shape[dim] == 1``\n", " | or the array has no elements.\n", " | It does *not* generally hold that ``self.strides[-1] == self.itemsize``\n", " | for C-style contiguous arrays or ``self.strides[0] == self.itemsize`` for\n", " | Fortran-style contiguous arrays is true.\n", " | \n", " | flat\n", " | A 1-D iterator over the array.\n", " | \n", " | This is a `numpy.flatiter` instance, which acts similarly to, but is not\n", " | a subclass of, Python's built-in iterator object.\n", " | \n", " | See Also\n", " | --------\n", " | flatten : Return a copy of the array collapsed into one dimension.\n", " | \n", " | flatiter\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.arange(1, 7).reshape(2, 3)\n", " | >>> x\n", " | array([[1, 2, 3],\n", " | [4, 5, 6]])\n", " | >>> x.flat[3]\n", " | 4\n", " | >>> x.T\n", " | array([[1, 4],\n", " | [2, 5],\n", " | [3, 6]])\n", " | >>> x.T.flat[3]\n", " | 5\n", " | >>> type(x.flat)\n", " | \n", " | \n", " | An assignment example:\n", " | \n", " | >>> x.flat = 3; x\n", " | array([[3, 3, 3],\n", " | [3, 3, 3]])\n", " | >>> x.flat[[1,4]] = 1; x\n", " | array([[3, 1, 3],\n", " | [3, 1, 3]])\n", " | \n", " | imag\n", " | The imaginary part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.imag\n", " | array([ 0. , 0.70710678])\n", " | >>> x.imag.dtype\n", " | dtype('float64')\n", " | \n", " | itemsize\n", " | Length of one array element in bytes.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1,2,3], dtype=np.float64)\n", " | >>> x.itemsize\n", " | 8\n", " | >>> x = np.array([1,2,3], dtype=np.complex128)\n", " | >>> x.itemsize\n", " | 16\n", " | \n", " | nbytes\n", " | Total bytes consumed by the elements of the array.\n", " | \n", " | Notes\n", " | -----\n", " | Does not include memory consumed by non-element attributes of the\n", " | array object.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3,5,2), dtype=np.complex128)\n", " | >>> x.nbytes\n", " | 480\n", " | >>> np.prod(x.shape) * x.itemsize\n", " | 480\n", " | \n", " | ndim\n", " | Number of array dimensions.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3])\n", " | >>> x.ndim\n", " | 1\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.ndim\n", " | 3\n", " | \n", " | real\n", " | The real part of the array.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.sqrt([1+0j, 0+1j])\n", " | >>> x.real\n", " | array([ 1. , 0.70710678])\n", " | >>> x.real.dtype\n", " | dtype('float64')\n", " | \n", " | See Also\n", " | --------\n", " | numpy.real : equivalent function\n", " | \n", " | shape\n", " | Tuple of array dimensions.\n", " | \n", " | The shape property is usually used to get the current shape of an array,\n", " | but may also be used to reshape the array in-place by assigning a tuple of\n", " | array dimensions to it. As with `numpy.reshape`, one of the new shape\n", " | dimensions can be -1, in which case its value is inferred from the size of\n", " | the array and the remaining dimensions. Reshaping an array in-place will\n", " | fail if a copy is required.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.array([1, 2, 3, 4])\n", " | >>> x.shape\n", " | (4,)\n", " | >>> y = np.zeros((2, 3, 4))\n", " | >>> y.shape\n", " | (2, 3, 4)\n", " | >>> y.shape = (3, 8)\n", " | >>> y\n", " | array([[ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.],\n", " | [ 0., 0., 0., 0., 0., 0., 0., 0.]])\n", " | >>> y.shape = (3, 6)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | ValueError: total size of new array must be unchanged\n", " | >>> np.zeros((4,2))[::2].shape = (-1,)\n", " | Traceback (most recent call last):\n", " | File \"\", line 1, in \n", " | AttributeError: Incompatible shape for in-place modification. Use\n", " | `.reshape()` to make a copy with the desired shape.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.reshape : similar function\n", " | ndarray.reshape : similar method\n", " | \n", " | size\n", " | Number of elements in the array.\n", " | \n", " | Equal to ``np.prod(a.shape)``, i.e., the product of the array's\n", " | dimensions.\n", " | \n", " | Notes\n", " | -----\n", " | `a.size` returns a standard arbitrary precision Python integer. This\n", " | may not be the case with other methods of obtaining the same value\n", " | (like the suggested ``np.prod(a.shape)``, which returns an instance\n", " | of ``np.int_``), and may be relevant if the value is used further in\n", " | calculations that may overflow a fixed size integer type.\n", " | \n", " | Examples\n", " | --------\n", " | >>> x = np.zeros((3, 5, 2), dtype=np.complex128)\n", " | >>> x.size\n", " | 30\n", " | >>> np.prod(x.shape)\n", " | 30\n", " | \n", " | strides\n", " | Tuple of bytes to step in each dimension when traversing an array.\n", " | \n", " | The byte offset of element ``(i[0], i[1], ..., i[n])`` in an array `a`\n", " | is::\n", " | \n", " | offset = sum(np.array(i) * a.strides)\n", " | \n", " | A more detailed explanation of strides can be found in the\n", " | \"ndarray.rst\" file in the NumPy reference guide.\n", " | \n", " | Notes\n", " | -----\n", " | Imagine an array of 32-bit integers (each 4 bytes)::\n", " | \n", " | x = np.array([[0, 1, 2, 3, 4],\n", " | [5, 6, 7, 8, 9]], dtype=np.int32)\n", " | \n", " | This array is stored in memory as 40 bytes, one after the other\n", " | (known as a contiguous block of memory). The strides of an array tell\n", " | us how many bytes we have to skip in memory to move to the next position\n", " | along a certain axis. For example, we have to skip 4 bytes (1 value) to\n", " | move to the next column, but 20 bytes (5 values) to get to the same\n", " | position in the next row. As such, the strides for the array `x` will be\n", " | ``(20, 4)``.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.lib.stride_tricks.as_strided\n", " | \n", " | Examples\n", " | --------\n", " | >>> y = np.reshape(np.arange(2*3*4), (2,3,4))\n", " | >>> y\n", " | array([[[ 0, 1, 2, 3],\n", " | [ 4, 5, 6, 7],\n", " | [ 8, 9, 10, 11]],\n", " | [[12, 13, 14, 15],\n", " | [16, 17, 18, 19],\n", " | [20, 21, 22, 23]]])\n", " | >>> y.strides\n", " | (48, 16, 4)\n", " | >>> y[1,1,1]\n", " | 17\n", " | >>> offset=sum(y.strides * np.array((1,1,1)))\n", " | >>> offset/y.itemsize\n", " | 17\n", " | \n", " | >>> x = np.reshape(np.arange(5*6*7*8), (5,6,7,8)).transpose(2,3,1,0)\n", " | >>> x.strides\n", " | (32, 4, 224, 1344)\n", " | >>> i = np.array([3,5,2,2])\n", " | >>> offset = sum(i * x.strides)\n", " | >>> x[3,5,2,2]\n", " | 813\n", " | >>> offset / x.itemsize\n", " | 813\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from ndarray:\n", " | \n", " | __hash__ = None\n", " \n", " class record(void)\n", " | A data-type scalar that allows field access as attribute lookup.\n", " | \n", " | Method resolution order:\n", " | record\n", " | void\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __getattribute__(self, attr)\n", " | Return getattr(self, name).\n", " | \n", " | __getitem__(self, indx)\n", " | Return self[key].\n", " | \n", " | __repr__(self)\n", " | Return repr(self).\n", " | \n", " | __setattr__(self, attr, val)\n", " | Implement setattr(self, name, value).\n", " | \n", " | __str__(self)\n", " | Return str(self).\n", " | \n", " | pprint(self)\n", " | Pretty-print all fields.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from void:\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " short = class int16(signedinteger)\n", " | Signed integer type, compatible with C ``short``.\n", " | Character code: ``'h'``.\n", " | Canonical name: ``np.short``.\n", " | Alias *on this platform*: ``np.int16``: 16-bit signed integer (-32768 to 32767).\n", " | \n", " | Method resolution order:\n", " | int16\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class signedinteger(integer)\n", " | Abstract base class of all signed integer scalar types.\n", " | \n", " | Method resolution order:\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " single = class float32(floating)\n", " | Single-precision floating-point number type, compatible with C ``float``.\n", " | Character code: ``'f'``.\n", " | Canonical name: ``np.single``.\n", " | Alias *on this platform*: ``np.float32``: 32-bit-precision floating-point number type: sign bit, 8 bits exponent, 23 bits mantissa.\n", " | \n", " | Method resolution order:\n", " | float32\n", " | floating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self (int, int)\n", " | \n", " | Return a pair of integers, whose ratio is exactly equal to the original\n", " | floating point number, and with a positive denominator.\n", " | Raise OverflowError on infinities and a ValueError on NaNs.\n", " | \n", " | >>> np.single(10.0).as_integer_ratio()\n", " | (10, 1)\n", " | >>> np.single(0.0).as_integer_ratio()\n", " | (0, 1)\n", " | >>> np.single(-.25).as_integer_ratio()\n", " | (-1, 4)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from floating:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " singlecomplex = class complex64(complexfloating)\n", " | Complex number type composed of two single-precision floating-point\n", " | numbers.\n", " | Character code: ``'F'``.\n", " | Canonical name: ``np.csingle``.\n", " | Alias: ``np.singlecomplex``.\n", " | Alias *on this platform*: ``np.complex64``: Complex number type composed of 2 32-bit-precision floating-point numbers.\n", " | \n", " | Method resolution order:\n", " | complex64\n", " | complexfloating\n", " | inexact\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __complex__(...)\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " str0 = class str_(builtins.str, character)\n", " | str(object='') -> str\n", " | str(bytes_or_buffer[, encoding[, errors]]) -> str\n", " | \n", " | Create a new string object from the given object. If encoding or\n", " | errors is specified, then the object must expose a data buffer\n", " | that will be decoded using the given encoding and error handler.\n", " | Otherwise, returns the result of object.__str__() (if defined)\n", " | or repr(object).\n", " | encoding defaults to sys.getdefaultencoding().\n", " | errors defaults to 'strict'.\n", " | \n", " | Method resolution order:\n", " | str_\n", " | builtins.str\n", " | character\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self int\n", " | \n", " | Return the number of non-overlapping occurrences of substring sub in\n", " | string S[start:end]. Optional arguments start and end are\n", " | interpreted as in slice notation.\n", " | \n", " | encode(self, /, encoding='utf-8', errors='strict')\n", " | Encode the string using the codec registered for encoding.\n", " | \n", " | encoding\n", " | The encoding in which to encode the string.\n", " | errors\n", " | The error handling scheme to use for encoding errors.\n", " | The default is 'strict' meaning that encoding errors raise a\n", " | UnicodeEncodeError. Other possible values are 'ignore', 'replace' and\n", " | 'xmlcharrefreplace' as well as any other name registered with\n", " | codecs.register_error that can handle UnicodeEncodeErrors.\n", " | \n", " | endswith(...)\n", " | S.endswith(suffix[, start[, end]]) -> bool\n", " | \n", " | Return True if S ends with the specified suffix, False otherwise.\n", " | With optional start, test S beginning at that position.\n", " | With optional end, stop comparing S at that position.\n", " | suffix can also be a tuple of strings to try.\n", " | \n", " | expandtabs(self, /, tabsize=8)\n", " | Return a copy where all tab characters are expanded using spaces.\n", " | \n", " | If tabsize is not given, a tab size of 8 characters is assumed.\n", " | \n", " | find(...)\n", " | S.find(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | format(...)\n", " | S.format(*args, **kwargs) -> str\n", " | \n", " | Return a formatted version of S, using substitutions from args and kwargs.\n", " | The substitutions are identified by braces ('{' and '}').\n", " | \n", " | format_map(...)\n", " | S.format_map(mapping) -> str\n", " | \n", " | Return a formatted version of S, using substitutions from mapping.\n", " | The substitutions are identified by braces ('{' and '}').\n", " | \n", " | index(...)\n", " | S.index(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the substring is not found.\n", " | \n", " | isalnum(self, /)\n", " | Return True if the string is an alpha-numeric string, False otherwise.\n", " | \n", " | A string is alpha-numeric if all characters in the string are alpha-numeric and\n", " | there is at least one character in the string.\n", " | \n", " | isalpha(self, /)\n", " | Return True if the string is an alphabetic string, False otherwise.\n", " | \n", " | A string is alphabetic if all characters in the string are alphabetic and there\n", " | is at least one character in the string.\n", " | \n", " | isascii(self, /)\n", " | Return True if all characters in the string are ASCII, False otherwise.\n", " | \n", " | ASCII characters have code points in the range U+0000-U+007F.\n", " | Empty string is ASCII too.\n", " | \n", " | isdecimal(self, /)\n", " | Return True if the string is a decimal string, False otherwise.\n", " | \n", " | A string is a decimal string if all characters in the string are decimal and\n", " | there is at least one character in the string.\n", " | \n", " | isdigit(self, /)\n", " | Return True if the string is a digit string, False otherwise.\n", " | \n", " | A string is a digit string if all characters in the string are digits and there\n", " | is at least one character in the string.\n", " | \n", " | isidentifier(self, /)\n", " | Return True if the string is a valid Python identifier, False otherwise.\n", " | \n", " | Call keyword.iskeyword(s) to test whether string s is a reserved identifier,\n", " | such as \"def\" or \"class\".\n", " | \n", " | islower(self, /)\n", " | Return True if the string is a lowercase string, False otherwise.\n", " | \n", " | A string is lowercase if all cased characters in the string are lowercase and\n", " | there is at least one cased character in the string.\n", " | \n", " | isnumeric(self, /)\n", " | Return True if the string is a numeric string, False otherwise.\n", " | \n", " | A string is numeric if all characters in the string are numeric and there is at\n", " | least one character in the string.\n", " | \n", " | isprintable(self, /)\n", " | Return True if the string is printable, False otherwise.\n", " | \n", " | A string is printable if all of its characters are considered printable in\n", " | repr() or if it is empty.\n", " | \n", " | isspace(self, /)\n", " | Return True if the string is a whitespace string, False otherwise.\n", " | \n", " | A string is whitespace if all characters in the string are whitespace and there\n", " | is at least one character in the string.\n", " | \n", " | istitle(self, /)\n", " | Return True if the string is a title-cased string, False otherwise.\n", " | \n", " | In a title-cased string, upper- and title-case characters may only\n", " | follow uncased characters and lowercase characters only cased ones.\n", " | \n", " | isupper(self, /)\n", " | Return True if the string is an uppercase string, False otherwise.\n", " | \n", " | A string is uppercase if all cased characters in the string are uppercase and\n", " | there is at least one cased character in the string.\n", " | \n", " | join(self, iterable, /)\n", " | Concatenate any number of strings.\n", " | \n", " | The string whose method is called is inserted in between each given string.\n", " | The result is returned as a new string.\n", " | \n", " | Example: '.'.join(['ab', 'pq', 'rs']) -> 'ab.pq.rs'\n", " | \n", " | ljust(self, width, fillchar=' ', /)\n", " | Return a left-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character (default is a space).\n", " | \n", " | lower(self, /)\n", " | Return a copy of the string converted to lowercase.\n", " | \n", " | lstrip(self, chars=None, /)\n", " | Return a copy of the string with leading whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | partition(self, sep, /)\n", " | Partition the string into three parts using the given separator.\n", " | \n", " | This will search for the separator in the string. If the separator is found,\n", " | returns a 3-tuple containing the part before the separator, the separator\n", " | itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing the original string\n", " | and two empty strings.\n", " | \n", " | replace(self, old, new, count=-1, /)\n", " | Return a copy with all occurrences of substring old replaced by new.\n", " | \n", " | count\n", " | Maximum number of occurrences to replace.\n", " | -1 (the default value) means replace all occurrences.\n", " | \n", " | If the optional argument count is given, only the first count occurrences are\n", " | replaced.\n", " | \n", " | rfind(...)\n", " | S.rfind(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | rindex(...)\n", " | S.rindex(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the substring is not found.\n", " | \n", " | rjust(self, width, fillchar=' ', /)\n", " | Return a right-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character (default is a space).\n", " | \n", " | rpartition(self, sep, /)\n", " | Partition the string into three parts using the given separator.\n", " | \n", " | This will search for the separator in the string, starting at the end. If\n", " | the separator is found, returns a 3-tuple containing the part before the\n", " | separator, the separator itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing two empty strings\n", " | and the original string.\n", " | \n", " | rsplit(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the words in the string, using sep as the delimiter string.\n", " | \n", " | sep\n", " | The delimiter according which to split the string.\n", " | None (the default value) means split according to any whitespace,\n", " | and discard empty strings from the result.\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | Splits are done starting at the end of the string and working to the front.\n", " | \n", " | rstrip(self, chars=None, /)\n", " | Return a copy of the string with trailing whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | split(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the words in the string, using sep as the delimiter string.\n", " | \n", " | sep\n", " | The delimiter according which to split the string.\n", " | None (the default value) means split according to any whitespace,\n", " | and discard empty strings from the result.\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | splitlines(self, /, keepends=False)\n", " | Return a list of the lines in the string, breaking at line boundaries.\n", " | \n", " | Line breaks are not included in the resulting list unless keepends is given and\n", " | true.\n", " | \n", " | startswith(...)\n", " | S.startswith(prefix[, start[, end]]) -> bool\n", " | \n", " | Return True if S starts with the specified prefix, False otherwise.\n", " | With optional start, test S beginning at that position.\n", " | With optional end, stop comparing S at that position.\n", " | prefix can also be a tuple of strings to try.\n", " | \n", " | strip(self, chars=None, /)\n", " | Return a copy of the string with leading and trailing whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | swapcase(self, /)\n", " | Convert uppercase characters to lowercase and lowercase characters to uppercase.\n", " | \n", " | title(self, /)\n", " | Return a version of the string where each word is titlecased.\n", " | \n", " | More specifically, words start with uppercased characters and all remaining\n", " | cased characters have lower case.\n", " | \n", " | translate(self, table, /)\n", " | Replace each character in the string using the given translation table.\n", " | \n", " | table\n", " | Translation table, which must be a mapping of Unicode ordinals to\n", " | Unicode ordinals, strings, or None.\n", " | \n", " | The table must implement lookup/indexing via __getitem__, for instance a\n", " | dictionary or list. If this operation raises LookupError, the character is\n", " | left untouched. Characters mapped to None are deleted.\n", " | \n", " | upper(self, /)\n", " | Return a copy of the string converted to uppercase.\n", " | \n", " | zfill(self, width, /)\n", " | Pad a numeric string with zeros on the left, to fill a field of the given width.\n", " | \n", " | The string is never truncated.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.str:\n", " | \n", " | maketrans(...)\n", " | Return a translation table usable for str.translate().\n", " | \n", " | If there is only one argument, it must be a dictionary mapping Unicode\n", " | ordinals (integers) or characters to Unicode ordinals, strings or None.\n", " | Character keys will be then converted to ordinals.\n", " | If there are two arguments, they must be strings of equal length, and\n", " | in the resulting dictionary, each character in x will be mapped to the\n", " | character at the same position in y. If there is a third argument, it\n", " | must be a string, whose characters will be mapped to None in the result.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class str_(builtins.str, character)\n", " | str(object='') -> str\n", " | str(bytes_or_buffer[, encoding[, errors]]) -> str\n", " | \n", " | Create a new string object from the given object. If encoding or\n", " | errors is specified, then the object must expose a data buffer\n", " | that will be decoded using the given encoding and error handler.\n", " | Otherwise, returns the result of object.__str__() (if defined)\n", " | or repr(object).\n", " | encoding defaults to sys.getdefaultencoding().\n", " | errors defaults to 'strict'.\n", " | \n", " | Method resolution order:\n", " | str_\n", " | builtins.str\n", " | character\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self int\n", " | \n", " | Return the number of non-overlapping occurrences of substring sub in\n", " | string S[start:end]. Optional arguments start and end are\n", " | interpreted as in slice notation.\n", " | \n", " | encode(self, /, encoding='utf-8', errors='strict')\n", " | Encode the string using the codec registered for encoding.\n", " | \n", " | encoding\n", " | The encoding in which to encode the string.\n", " | errors\n", " | The error handling scheme to use for encoding errors.\n", " | The default is 'strict' meaning that encoding errors raise a\n", " | UnicodeEncodeError. Other possible values are 'ignore', 'replace' and\n", " | 'xmlcharrefreplace' as well as any other name registered with\n", " | codecs.register_error that can handle UnicodeEncodeErrors.\n", " | \n", " | endswith(...)\n", " | S.endswith(suffix[, start[, end]]) -> bool\n", " | \n", " | Return True if S ends with the specified suffix, False otherwise.\n", " | With optional start, test S beginning at that position.\n", " | With optional end, stop comparing S at that position.\n", " | suffix can also be a tuple of strings to try.\n", " | \n", " | expandtabs(self, /, tabsize=8)\n", " | Return a copy where all tab characters are expanded using spaces.\n", " | \n", " | If tabsize is not given, a tab size of 8 characters is assumed.\n", " | \n", " | find(...)\n", " | S.find(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | format(...)\n", " | S.format(*args, **kwargs) -> str\n", " | \n", " | Return a formatted version of S, using substitutions from args and kwargs.\n", " | The substitutions are identified by braces ('{' and '}').\n", " | \n", " | format_map(...)\n", " | S.format_map(mapping) -> str\n", " | \n", " | Return a formatted version of S, using substitutions from mapping.\n", " | The substitutions are identified by braces ('{' and '}').\n", " | \n", " | index(...)\n", " | S.index(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the substring is not found.\n", " | \n", " | isalnum(self, /)\n", " | Return True if the string is an alpha-numeric string, False otherwise.\n", " | \n", " | A string is alpha-numeric if all characters in the string are alpha-numeric and\n", " | there is at least one character in the string.\n", " | \n", " | isalpha(self, /)\n", " | Return True if the string is an alphabetic string, False otherwise.\n", " | \n", " | A string is alphabetic if all characters in the string are alphabetic and there\n", " | is at least one character in the string.\n", " | \n", " | isascii(self, /)\n", " | Return True if all characters in the string are ASCII, False otherwise.\n", " | \n", " | ASCII characters have code points in the range U+0000-U+007F.\n", " | Empty string is ASCII too.\n", " | \n", " | isdecimal(self, /)\n", " | Return True if the string is a decimal string, False otherwise.\n", " | \n", " | A string is a decimal string if all characters in the string are decimal and\n", " | there is at least one character in the string.\n", " | \n", " | isdigit(self, /)\n", " | Return True if the string is a digit string, False otherwise.\n", " | \n", " | A string is a digit string if all characters in the string are digits and there\n", " | is at least one character in the string.\n", " | \n", " | isidentifier(self, /)\n", " | Return True if the string is a valid Python identifier, False otherwise.\n", " | \n", " | Call keyword.iskeyword(s) to test whether string s is a reserved identifier,\n", " | such as \"def\" or \"class\".\n", " | \n", " | islower(self, /)\n", " | Return True if the string is a lowercase string, False otherwise.\n", " | \n", " | A string is lowercase if all cased characters in the string are lowercase and\n", " | there is at least one cased character in the string.\n", " | \n", " | isnumeric(self, /)\n", " | Return True if the string is a numeric string, False otherwise.\n", " | \n", " | A string is numeric if all characters in the string are numeric and there is at\n", " | least one character in the string.\n", " | \n", " | isprintable(self, /)\n", " | Return True if the string is printable, False otherwise.\n", " | \n", " | A string is printable if all of its characters are considered printable in\n", " | repr() or if it is empty.\n", " | \n", " | isspace(self, /)\n", " | Return True if the string is a whitespace string, False otherwise.\n", " | \n", " | A string is whitespace if all characters in the string are whitespace and there\n", " | is at least one character in the string.\n", " | \n", " | istitle(self, /)\n", " | Return True if the string is a title-cased string, False otherwise.\n", " | \n", " | In a title-cased string, upper- and title-case characters may only\n", " | follow uncased characters and lowercase characters only cased ones.\n", " | \n", " | isupper(self, /)\n", " | Return True if the string is an uppercase string, False otherwise.\n", " | \n", " | A string is uppercase if all cased characters in the string are uppercase and\n", " | there is at least one cased character in the string.\n", " | \n", " | join(self, iterable, /)\n", " | Concatenate any number of strings.\n", " | \n", " | The string whose method is called is inserted in between each given string.\n", " | The result is returned as a new string.\n", " | \n", " | Example: '.'.join(['ab', 'pq', 'rs']) -> 'ab.pq.rs'\n", " | \n", " | ljust(self, width, fillchar=' ', /)\n", " | Return a left-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character (default is a space).\n", " | \n", " | lower(self, /)\n", " | Return a copy of the string converted to lowercase.\n", " | \n", " | lstrip(self, chars=None, /)\n", " | Return a copy of the string with leading whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | partition(self, sep, /)\n", " | Partition the string into three parts using the given separator.\n", " | \n", " | This will search for the separator in the string. If the separator is found,\n", " | returns a 3-tuple containing the part before the separator, the separator\n", " | itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing the original string\n", " | and two empty strings.\n", " | \n", " | replace(self, old, new, count=-1, /)\n", " | Return a copy with all occurrences of substring old replaced by new.\n", " | \n", " | count\n", " | Maximum number of occurrences to replace.\n", " | -1 (the default value) means replace all occurrences.\n", " | \n", " | If the optional argument count is given, only the first count occurrences are\n", " | replaced.\n", " | \n", " | rfind(...)\n", " | S.rfind(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | rindex(...)\n", " | S.rindex(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the substring is not found.\n", " | \n", " | rjust(self, width, fillchar=' ', /)\n", " | Return a right-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character (default is a space).\n", " | \n", " | rpartition(self, sep, /)\n", " | Partition the string into three parts using the given separator.\n", " | \n", " | This will search for the separator in the string, starting at the end. If\n", " | the separator is found, returns a 3-tuple containing the part before the\n", " | separator, the separator itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing two empty strings\n", " | and the original string.\n", " | \n", " | rsplit(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the words in the string, using sep as the delimiter string.\n", " | \n", " | sep\n", " | The delimiter according which to split the string.\n", " | None (the default value) means split according to any whitespace,\n", " | and discard empty strings from the result.\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | Splits are done starting at the end of the string and working to the front.\n", " | \n", " | rstrip(self, chars=None, /)\n", " | Return a copy of the string with trailing whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | split(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the words in the string, using sep as the delimiter string.\n", " | \n", " | sep\n", " | The delimiter according which to split the string.\n", " | None (the default value) means split according to any whitespace,\n", " | and discard empty strings from the result.\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | splitlines(self, /, keepends=False)\n", " | Return a list of the lines in the string, breaking at line boundaries.\n", " | \n", " | Line breaks are not included in the resulting list unless keepends is given and\n", " | true.\n", " | \n", " | startswith(...)\n", " | S.startswith(prefix[, start[, end]]) -> bool\n", " | \n", " | Return True if S starts with the specified prefix, False otherwise.\n", " | With optional start, test S beginning at that position.\n", " | With optional end, stop comparing S at that position.\n", " | prefix can also be a tuple of strings to try.\n", " | \n", " | strip(self, chars=None, /)\n", " | Return a copy of the string with leading and trailing whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | swapcase(self, /)\n", " | Convert uppercase characters to lowercase and lowercase characters to uppercase.\n", " | \n", " | title(self, /)\n", " | Return a version of the string where each word is titlecased.\n", " | \n", " | More specifically, words start with uppercased characters and all remaining\n", " | cased characters have lower case.\n", " | \n", " | translate(self, table, /)\n", " | Replace each character in the string using the given translation table.\n", " | \n", " | table\n", " | Translation table, which must be a mapping of Unicode ordinals to\n", " | Unicode ordinals, strings, or None.\n", " | \n", " | The table must implement lookup/indexing via __getitem__, for instance a\n", " | dictionary or list. If this operation raises LookupError, the character is\n", " | left untouched. Characters mapped to None are deleted.\n", " | \n", " | upper(self, /)\n", " | Return a copy of the string converted to uppercase.\n", " | \n", " | zfill(self, width, /)\n", " | Pad a numeric string with zeros on the left, to fill a field of the given width.\n", " | \n", " | The string is never truncated.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.str:\n", " | \n", " | maketrans(...)\n", " | Return a translation table usable for str.translate().\n", " | \n", " | If there is only one argument, it must be a dictionary mapping Unicode\n", " | ordinals (integers) or characters to Unicode ordinals, strings or None.\n", " | Character keys will be then converted to ordinals.\n", " | If there are two arguments, they must be strings of equal length, and\n", " | in the resulting dictionary, each character in x will be mapped to the\n", " | character at the same position in y. If there is a third argument, it\n", " | must be a string, whose characters will be mapped to None in the result.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " string_ = class bytes_(builtins.bytes, character)\n", " | bytes(iterable_of_ints) -> bytes\n", " | bytes(string, encoding[, errors]) -> bytes\n", " | bytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\n", " | bytes(int) -> bytes object of size given by the parameter initialized with null bytes\n", " | bytes() -> empty bytes object\n", " | \n", " | Construct an immutable array of bytes from:\n", " | - an iterable yielding integers in range(256)\n", " | - a text string encoded using the specified encoding\n", " | - any object implementing the buffer API.\n", " | - an integer\n", " | \n", " | Method resolution order:\n", " | bytes_\n", " | builtins.bytes\n", " | character\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self copy of B\n", " | \n", " | Return a copy of B with only its first character capitalized (ASCII)\n", " | and the rest lower-cased.\n", " | \n", " | center(self, width, fillchar=b' ', /)\n", " | Return a centered string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | count(...)\n", " | B.count(sub[, start[, end]]) -> int\n", " | \n", " | Return the number of non-overlapping occurrences of subsection sub in\n", " | bytes B[start:end]. Optional arguments start and end are interpreted\n", " | as in slice notation.\n", " | \n", " | decode(self, /, encoding='utf-8', errors='strict')\n", " | Decode the bytes using the codec registered for encoding.\n", " | \n", " | encoding\n", " | The encoding with which to decode the bytes.\n", " | errors\n", " | The error handling scheme to use for the handling of decoding errors.\n", " | The default is 'strict' meaning that decoding errors raise a\n", " | UnicodeDecodeError. Other possible values are 'ignore' and 'replace'\n", " | as well as any other name registered with codecs.register_error that\n", " | can handle UnicodeDecodeErrors.\n", " | \n", " | endswith(...)\n", " | B.endswith(suffix[, start[, end]]) -> bool\n", " | \n", " | Return True if B ends with the specified suffix, False otherwise.\n", " | With optional start, test B beginning at that position.\n", " | With optional end, stop comparing B at that position.\n", " | suffix can also be a tuple of bytes to try.\n", " | \n", " | expandtabs(self, /, tabsize=8)\n", " | Return a copy where all tab characters are expanded using spaces.\n", " | \n", " | If tabsize is not given, a tab size of 8 characters is assumed.\n", " | \n", " | find(...)\n", " | B.find(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | hex(...)\n", " | Create a str of hexadecimal numbers from a bytes object.\n", " | \n", " | sep\n", " | An optional single character or byte to separate hex bytes.\n", " | bytes_per_sep\n", " | How many bytes between separators. Positive values count from the\n", " | right, negative values count from the left.\n", " | \n", " | Example:\n", " | >>> value = b'\\xb9\\x01\\xef'\n", " | >>> value.hex()\n", " | 'b901ef'\n", " | >>> value.hex(':')\n", " | 'b9:01:ef'\n", " | >>> value.hex(':', 2)\n", " | 'b9:01ef'\n", " | >>> value.hex(':', -2)\n", " | 'b901:ef'\n", " | \n", " | index(...)\n", " | B.index(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the subsection is not found.\n", " | \n", " | isalnum(...)\n", " | B.isalnum() -> bool\n", " | \n", " | Return True if all characters in B are alphanumeric\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | isalpha(...)\n", " | B.isalpha() -> bool\n", " | \n", " | Return True if all characters in B are alphabetic\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | isascii(...)\n", " | B.isascii() -> bool\n", " | \n", " | Return True if B is empty or all characters in B are ASCII,\n", " | False otherwise.\n", " | \n", " | isdigit(...)\n", " | B.isdigit() -> bool\n", " | \n", " | Return True if all characters in B are digits\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | islower(...)\n", " | B.islower() -> bool\n", " | \n", " | Return True if all cased characters in B are lowercase and there is\n", " | at least one cased character in B, False otherwise.\n", " | \n", " | isspace(...)\n", " | B.isspace() -> bool\n", " | \n", " | Return True if all characters in B are whitespace\n", " | and there is at least one character in B, False otherwise.\n", " | \n", " | istitle(...)\n", " | B.istitle() -> bool\n", " | \n", " | Return True if B is a titlecased string and there is at least one\n", " | character in B, i.e. uppercase characters may only follow uncased\n", " | characters and lowercase characters only cased ones. Return False\n", " | otherwise.\n", " | \n", " | isupper(...)\n", " | B.isupper() -> bool\n", " | \n", " | Return True if all cased characters in B are uppercase and there is\n", " | at least one cased character in B, False otherwise.\n", " | \n", " | join(self, iterable_of_bytes, /)\n", " | Concatenate any number of bytes objects.\n", " | \n", " | The bytes whose method is called is inserted in between each pair.\n", " | \n", " | The result is returned as a new bytes object.\n", " | \n", " | Example: b'.'.join([b'ab', b'pq', b'rs']) -> b'ab.pq.rs'.\n", " | \n", " | ljust(self, width, fillchar=b' ', /)\n", " | Return a left-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | lower(...)\n", " | B.lower() -> copy of B\n", " | \n", " | Return a copy of B with all ASCII characters converted to lowercase.\n", " | \n", " | lstrip(self, bytes=None, /)\n", " | Strip leading bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip leading ASCII whitespace.\n", " | \n", " | partition(self, sep, /)\n", " | Partition the bytes into three parts using the given separator.\n", " | \n", " | This will search for the separator sep in the bytes. If the separator is found,\n", " | returns a 3-tuple containing the part before the separator, the separator\n", " | itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing the original bytes\n", " | object and two empty bytes objects.\n", " | \n", " | replace(self, old, new, count=-1, /)\n", " | Return a copy with all occurrences of substring old replaced by new.\n", " | \n", " | count\n", " | Maximum number of occurrences to replace.\n", " | -1 (the default value) means replace all occurrences.\n", " | \n", " | If the optional argument count is given, only the first count occurrences are\n", " | replaced.\n", " | \n", " | rfind(...)\n", " | B.rfind(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | rindex(...)\n", " | B.rindex(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in B where subsection sub is found,\n", " | such that sub is contained within B[start,end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raise ValueError when the subsection is not found.\n", " | \n", " | rjust(self, width, fillchar=b' ', /)\n", " | Return a right-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character.\n", " | \n", " | rpartition(self, sep, /)\n", " | Partition the bytes into three parts using the given separator.\n", " | \n", " | This will search for the separator sep in the bytes, starting at the end. If\n", " | the separator is found, returns a 3-tuple containing the part before the\n", " | separator, the separator itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing two empty bytes\n", " | objects and the original bytes object.\n", " | \n", " | rsplit(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the sections in the bytes, using sep as the delimiter.\n", " | \n", " | sep\n", " | The delimiter according which to split the bytes.\n", " | None (the default value) means split on ASCII whitespace characters\n", " | (space, tab, return, newline, formfeed, vertical tab).\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | Splitting is done starting at the end of the bytes and working to the front.\n", " | \n", " | rstrip(self, bytes=None, /)\n", " | Strip trailing bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip trailing ASCII whitespace.\n", " | \n", " | split(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the sections in the bytes, using sep as the delimiter.\n", " | \n", " | sep\n", " | The delimiter according which to split the bytes.\n", " | None (the default value) means split on ASCII whitespace characters\n", " | (space, tab, return, newline, formfeed, vertical tab).\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | splitlines(self, /, keepends=False)\n", " | Return a list of the lines in the bytes, breaking at line boundaries.\n", " | \n", " | Line breaks are not included in the resulting list unless keepends is given and\n", " | true.\n", " | \n", " | startswith(...)\n", " | B.startswith(prefix[, start[, end]]) -> bool\n", " | \n", " | Return True if B starts with the specified prefix, False otherwise.\n", " | With optional start, test B beginning at that position.\n", " | With optional end, stop comparing B at that position.\n", " | prefix can also be a tuple of bytes to try.\n", " | \n", " | strip(self, bytes=None, /)\n", " | Strip leading and trailing bytes contained in the argument.\n", " | \n", " | If the argument is omitted or None, strip leading and trailing ASCII whitespace.\n", " | \n", " | swapcase(...)\n", " | B.swapcase() -> copy of B\n", " | \n", " | Return a copy of B with uppercase ASCII characters converted\n", " | to lowercase ASCII and vice versa.\n", " | \n", " | title(...)\n", " | B.title() -> copy of B\n", " | \n", " | Return a titlecased version of B, i.e. ASCII words start with uppercase\n", " | characters, all remaining cased characters have lowercase.\n", " | \n", " | translate(self, table, /, delete=b'')\n", " | Return a copy with each character mapped by the given translation table.\n", " | \n", " | table\n", " | Translation table, which must be a bytes object of length 256.\n", " | \n", " | All characters occurring in the optional argument delete are removed.\n", " | The remaining characters are mapped through the given translation table.\n", " | \n", " | upper(...)\n", " | B.upper() -> copy of B\n", " | \n", " | Return a copy of B with all ASCII characters converted to uppercase.\n", " | \n", " | zfill(self, width, /)\n", " | Pad a numeric string with zeros on the left, to fill a field of the given width.\n", " | \n", " | The original string is never truncated.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Class methods inherited from builtins.bytes:\n", " | \n", " | fromhex(string, /) from builtins.type\n", " | Create a bytes object from a string of hexadecimal numbers.\n", " | \n", " | Spaces between two numbers are accepted.\n", " | Example: bytes.fromhex('B9 01EF') -> b'\\\\xb9\\\\x01\\\\xef'.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.bytes:\n", " | \n", " | maketrans(frm, to, /)\n", " | Return a translation table useable for the bytes or bytearray translate method.\n", " | \n", " | The returned table will be one where each byte in frm is mapped to the byte at\n", " | the same position in to.\n", " | \n", " | The bytes objects frm and to must be of the same length.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class timedelta64(signedinteger)\n", " | Abstract base class of all signed integer scalar types.\n", " | \n", " | Method resolution order:\n", " | timedelta64\n", " | signedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " ubyte = class uint8(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned char``.\n", " | Character code: ``'B'``.\n", " | Canonical name: ``np.ubyte``.\n", " | Alias *on this platform*: ``np.uint8``: 8-bit unsigned integer (0 to 255).\n", " | \n", " | Method resolution order:\n", " | uint8\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class ufunc(builtins.object)\n", " | Functions that operate element by element on whole arrays.\n", " | \n", " | To see the documentation for a specific ufunc, use `info`. For\n", " | example, ``np.info(np.sin)``. Because ufuncs are written in C\n", " | (for speed) and linked into Python with NumPy's ufunc facility,\n", " | Python's help() function finds this page whenever help() is called\n", " | on a ufunc.\n", " | \n", " | A detailed explanation of ufuncs can be found in the docs for :ref:`ufuncs`.\n", " | \n", " | Calling ufuncs:\n", " | ===============\n", " | \n", " | op(*x[, out], where=True, **kwargs)\n", " | Apply `op` to the arguments `*x` elementwise, broadcasting the arguments.\n", " | \n", " | The broadcasting rules are:\n", " | \n", " | * Dimensions of length 1 may be prepended to either array.\n", " | * Arrays may be repeated along dimensions of length 1.\n", " | \n", " | Parameters\n", " | ----------\n", " | *x : array_like\n", " | Input arrays.\n", " | out : ndarray, None, or tuple of ndarray and None, optional\n", " | Alternate array object(s) in which to put the result; if provided, it\n", " | must have a shape that the inputs broadcast to. A tuple of arrays\n", " | (possible only as a keyword argument) must have length equal to the\n", " | number of outputs; use None for uninitialized outputs to be\n", " | allocated by the ufunc.\n", " | where : array_like, optional\n", " | This condition is broadcast over the input. At locations where the\n", " | condition is True, the `out` array will be set to the ufunc result.\n", " | Elsewhere, the `out` array will retain its original value.\n", " | Note that if an uninitialized `out` array is created via the default\n", " | ``out=None``, locations within it where the condition is False will\n", " | remain uninitialized.\n", " | **kwargs\n", " | For other keyword-only arguments, see the :ref:`ufunc docs `.\n", " | \n", " | Returns\n", " | -------\n", " | r : ndarray or tuple of ndarray\n", " | `r` will have the shape that the arrays in `x` broadcast to; if `out` is\n", " | provided, it will be returned. If not, `r` will be allocated and\n", " | may contain uninitialized values. If the function has more than one\n", " | output, then the result will be a tuple of arrays.\n", " | \n", " | Methods defined here:\n", " | \n", " | __call__(self, /, *args, **kwargs)\n", " | Call self as a function.\n", " | \n", " | __repr__(self, /)\n", " | Return repr(self).\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | accumulate(...)\n", " | accumulate(array, axis=0, dtype=None, out=None)\n", " | \n", " | Accumulate the result of applying the operator to all elements.\n", " | \n", " | For a one-dimensional array, accumulate produces results equivalent to::\n", " | \n", " | r = np.empty(len(A))\n", " | t = op.identity # op = the ufunc being applied to A's elements\n", " | for i in range(len(A)):\n", " | t = op(t, A[i])\n", " | r[i] = t\n", " | return r\n", " | \n", " | For example, add.accumulate() is equivalent to np.cumsum().\n", " | \n", " | For a multi-dimensional array, accumulate is applied along only one\n", " | axis (axis zero by default; see Examples below) so repeated use is\n", " | necessary if one wants to accumulate over multiple axes.\n", " | \n", " | Parameters\n", " | ----------\n", " | array : array_like\n", " | The array to act on.\n", " | axis : int, optional\n", " | The axis along which to apply the accumulation; default is zero.\n", " | dtype : data-type code, optional\n", " | The data-type used to represent the intermediate results. Defaults\n", " | to the data-type of the output array if such is provided, or the\n", " | the data-type of the input array if no output array is provided.\n", " | out : ndarray, None, or tuple of ndarray and None, optional\n", " | A location into which the result is stored. If not provided or None,\n", " | a freshly-allocated array is returned. For consistency with\n", " | ``ufunc.__call__``, if given as a keyword, this may be wrapped in a\n", " | 1-element tuple.\n", " | \n", " | .. versionchanged:: 1.13.0\n", " | Tuples are allowed for keyword argument.\n", " | \n", " | Returns\n", " | -------\n", " | r : ndarray\n", " | The accumulated values. If `out` was supplied, `r` is a reference to\n", " | `out`.\n", " | \n", " | Examples\n", " | --------\n", " | 1-D array examples:\n", " | \n", " | >>> np.add.accumulate([2, 3, 5])\n", " | array([ 2, 5, 10])\n", " | >>> np.multiply.accumulate([2, 3, 5])\n", " | array([ 2, 6, 30])\n", " | \n", " | 2-D array examples:\n", " | \n", " | >>> I = np.eye(2)\n", " | >>> I\n", " | array([[1., 0.],\n", " | [0., 1.]])\n", " | \n", " | Accumulate along axis 0 (rows), down columns:\n", " | \n", " | >>> np.add.accumulate(I, 0)\n", " | array([[1., 0.],\n", " | [1., 1.]])\n", " | >>> np.add.accumulate(I) # no axis specified = axis zero\n", " | array([[1., 0.],\n", " | [1., 1.]])\n", " | \n", " | Accumulate along axis 1 (columns), through rows:\n", " | \n", " | >>> np.add.accumulate(I, 1)\n", " | array([[1., 1.],\n", " | [0., 1.]])\n", " | \n", " | at(...)\n", " | at(a, indices, b=None)\n", " | \n", " | Performs unbuffered in place operation on operand 'a' for elements\n", " | specified by 'indices'. For addition ufunc, this method is equivalent to\n", " | ``a[indices] += b``, except that results are accumulated for elements that\n", " | are indexed more than once. For example, ``a[[0,0]] += 1`` will only\n", " | increment the first element once because of buffering, whereas\n", " | ``add.at(a, [0,0], 1)`` will increment the first element twice.\n", " | \n", " | .. versionadded:: 1.8.0\n", " | \n", " | Parameters\n", " | ----------\n", " | a : array_like\n", " | The array to perform in place operation on.\n", " | indices : array_like or tuple\n", " | Array like index object or slice object for indexing into first\n", " | operand. If first operand has multiple dimensions, indices can be a\n", " | tuple of array like index objects or slice objects.\n", " | b : array_like\n", " | Second operand for ufuncs requiring two operands. Operand must be\n", " | broadcastable over first operand after indexing or slicing.\n", " | \n", " | Examples\n", " | --------\n", " | Set items 0 and 1 to their negative values:\n", " | \n", " | >>> a = np.array([1, 2, 3, 4])\n", " | >>> np.negative.at(a, [0, 1])\n", " | >>> a\n", " | array([-1, -2, 3, 4])\n", " | \n", " | Increment items 0 and 1, and increment item 2 twice:\n", " | \n", " | >>> a = np.array([1, 2, 3, 4])\n", " | >>> np.add.at(a, [0, 1, 2, 2], 1)\n", " | >>> a\n", " | array([2, 3, 5, 4])\n", " | \n", " | Add items 0 and 1 in first array to second array,\n", " | and store results in first array:\n", " | \n", " | >>> a = np.array([1, 2, 3, 4])\n", " | >>> b = np.array([1, 2])\n", " | >>> np.add.at(a, [0, 1], b)\n", " | >>> a\n", " | array([2, 4, 3, 4])\n", " | \n", " | outer(...)\n", " | outer(A, B, **kwargs)\n", " | \n", " | Apply the ufunc `op` to all pairs (a, b) with a in `A` and b in `B`.\n", " | \n", " | Let ``M = A.ndim``, ``N = B.ndim``. Then the result, `C`, of\n", " | ``op.outer(A, B)`` is an array of dimension M + N such that:\n", " | \n", " | .. math:: C[i_0, ..., i_{M-1}, j_0, ..., j_{N-1}] =\n", " | op(A[i_0, ..., i_{M-1}], B[j_0, ..., j_{N-1}])\n", " | \n", " | For `A` and `B` one-dimensional, this is equivalent to::\n", " | \n", " | r = empty(len(A),len(B))\n", " | for i in range(len(A)):\n", " | for j in range(len(B)):\n", " | r[i,j] = op(A[i], B[j]) # op = ufunc in question\n", " | \n", " | Parameters\n", " | ----------\n", " | A : array_like\n", " | First array\n", " | B : array_like\n", " | Second array\n", " | kwargs : any\n", " | Arguments to pass on to the ufunc. Typically `dtype` or `out`.\n", " | \n", " | Returns\n", " | -------\n", " | r : ndarray\n", " | Output array\n", " | \n", " | See Also\n", " | --------\n", " | numpy.outer : A less powerful version of ``np.multiply.outer``\n", " | that `ravel`\\ s all inputs to 1D. This exists\n", " | primarily for compatibility with old code.\n", " | \n", " | tensordot : ``np.tensordot(a, b, axes=((), ()))`` and\n", " | ``np.multiply.outer(a, b)`` behave same for all\n", " | dimensions of a and b.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.multiply.outer([1, 2, 3], [4, 5, 6])\n", " | array([[ 4, 5, 6],\n", " | [ 8, 10, 12],\n", " | [12, 15, 18]])\n", " | \n", " | A multi-dimensional example:\n", " | \n", " | >>> A = np.array([[1, 2, 3], [4, 5, 6]])\n", " | >>> A.shape\n", " | (2, 3)\n", " | >>> B = np.array([[1, 2, 3, 4]])\n", " | >>> B.shape\n", " | (1, 4)\n", " | >>> C = np.multiply.outer(A, B)\n", " | >>> C.shape; C\n", " | (2, 3, 1, 4)\n", " | array([[[[ 1, 2, 3, 4]],\n", " | [[ 2, 4, 6, 8]],\n", " | [[ 3, 6, 9, 12]]],\n", " | [[[ 4, 8, 12, 16]],\n", " | [[ 5, 10, 15, 20]],\n", " | [[ 6, 12, 18, 24]]]])\n", " | \n", " | reduce(...)\n", " | reduce(a, axis=0, dtype=None, out=None, keepdims=False, initial=, where=True)\n", " | \n", " | Reduces `a`'s dimension by one, by applying ufunc along one axis.\n", " | \n", " | Let :math:`a.shape = (N_0, ..., N_i, ..., N_{M-1})`. Then\n", " | :math:`ufunc.reduce(a, axis=i)[k_0, ..,k_{i-1}, k_{i+1}, .., k_{M-1}]` =\n", " | the result of iterating `j` over :math:`range(N_i)`, cumulatively applying\n", " | ufunc to each :math:`a[k_0, ..,k_{i-1}, j, k_{i+1}, .., k_{M-1}]`.\n", " | For a one-dimensional array, reduce produces results equivalent to:\n", " | ::\n", " | \n", " | r = op.identity # op = ufunc\n", " | for i in range(len(A)):\n", " | r = op(r, A[i])\n", " | return r\n", " | \n", " | For example, add.reduce() is equivalent to sum().\n", " | \n", " | Parameters\n", " | ----------\n", " | a : array_like\n", " | The array to act on.\n", " | axis : None or int or tuple of ints, optional\n", " | Axis or axes along which a reduction is performed.\n", " | The default (`axis` = 0) is perform a reduction over the first\n", " | dimension of the input array. `axis` may be negative, in\n", " | which case it counts from the last to the first axis.\n", " | \n", " | .. versionadded:: 1.7.0\n", " | \n", " | If this is None, a reduction is performed over all the axes.\n", " | If this is a tuple of ints, a reduction is performed on multiple\n", " | axes, instead of a single axis or all the axes as before.\n", " | \n", " | For operations which are either not commutative or not associative,\n", " | doing a reduction over multiple axes is not well-defined. The\n", " | ufuncs do not currently raise an exception in this case, but will\n", " | likely do so in the future.\n", " | dtype : data-type code, optional\n", " | The type used to represent the intermediate results. Defaults\n", " | to the data-type of the output array if this is provided, or\n", " | the data-type of the input array if no output array is provided.\n", " | out : ndarray, None, or tuple of ndarray and None, optional\n", " | A location into which the result is stored. If not provided or None,\n", " | a freshly-allocated array is returned. For consistency with\n", " | ``ufunc.__call__``, if given as a keyword, this may be wrapped in a\n", " | 1-element tuple.\n", " | \n", " | .. versionchanged:: 1.13.0\n", " | Tuples are allowed for keyword argument.\n", " | keepdims : bool, optional\n", " | If this is set to True, the axes which are reduced are left\n", " | in the result as dimensions with size one. With this option,\n", " | the result will broadcast correctly against the original `arr`.\n", " | \n", " | .. versionadded:: 1.7.0\n", " | initial : scalar, optional\n", " | The value with which to start the reduction.\n", " | If the ufunc has no identity or the dtype is object, this defaults\n", " | to None - otherwise it defaults to ufunc.identity.\n", " | If ``None`` is given, the first element of the reduction is used,\n", " | and an error is thrown if the reduction is empty.\n", " | \n", " | .. versionadded:: 1.15.0\n", " | \n", " | where : array_like of bool, optional\n", " | A boolean array which is broadcasted to match the dimensions\n", " | of `a`, and selects elements to include in the reduction. Note\n", " | that for ufuncs like ``minimum`` that do not have an identity\n", " | defined, one has to pass in also ``initial``.\n", " | \n", " | .. versionadded:: 1.17.0\n", " | \n", " | Returns\n", " | -------\n", " | r : ndarray\n", " | The reduced array. If `out` was supplied, `r` is a reference to it.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.multiply.reduce([2,3,5])\n", " | 30\n", " | \n", " | A multi-dimensional array example:\n", " | \n", " | >>> X = np.arange(8).reshape((2,2,2))\n", " | >>> X\n", " | array([[[0, 1],\n", " | [2, 3]],\n", " | [[4, 5],\n", " | [6, 7]]])\n", " | >>> np.add.reduce(X, 0)\n", " | array([[ 4, 6],\n", " | [ 8, 10]])\n", " | >>> np.add.reduce(X) # confirm: default axis value is 0\n", " | array([[ 4, 6],\n", " | [ 8, 10]])\n", " | >>> np.add.reduce(X, 1)\n", " | array([[ 2, 4],\n", " | [10, 12]])\n", " | >>> np.add.reduce(X, 2)\n", " | array([[ 1, 5],\n", " | [ 9, 13]])\n", " | \n", " | You can use the ``initial`` keyword argument to initialize the reduction\n", " | with a different value, and ``where`` to select specific elements to include:\n", " | \n", " | >>> np.add.reduce([10], initial=5)\n", " | 15\n", " | >>> np.add.reduce(np.ones((2, 2, 2)), axis=(0, 2), initial=10)\n", " | array([14., 14.])\n", " | >>> a = np.array([10., np.nan, 10])\n", " | >>> np.add.reduce(a, where=~np.isnan(a))\n", " | 20.0\n", " | \n", " | Allows reductions of empty arrays where they would normally fail, i.e.\n", " | for ufuncs without an identity.\n", " | \n", " | >>> np.minimum.reduce([], initial=np.inf)\n", " | inf\n", " | >>> np.minimum.reduce([[1., 2.], [3., 4.]], initial=10., where=[True, False])\n", " | array([ 1., 10.])\n", " | >>> np.minimum.reduce([])\n", " | Traceback (most recent call last):\n", " | ...\n", " | ValueError: zero-size array to reduction operation minimum which has no identity\n", " | \n", " | reduceat(...)\n", " | reduceat(a, indices, axis=0, dtype=None, out=None)\n", " | \n", " | Performs a (local) reduce with specified slices over a single axis.\n", " | \n", " | For i in ``range(len(indices))``, `reduceat` computes\n", " | ``ufunc.reduce(a[indices[i]:indices[i+1]])``, which becomes the i-th\n", " | generalized \"row\" parallel to `axis` in the final result (i.e., in a\n", " | 2-D array, for example, if `axis = 0`, it becomes the i-th row, but if\n", " | `axis = 1`, it becomes the i-th column). There are three exceptions to this:\n", " | \n", " | * when ``i = len(indices) - 1`` (so for the last index),\n", " | ``indices[i+1] = a.shape[axis]``.\n", " | * if ``indices[i] >= indices[i + 1]``, the i-th generalized \"row\" is\n", " | simply ``a[indices[i]]``.\n", " | * if ``indices[i] >= len(a)`` or ``indices[i] < 0``, an error is raised.\n", " | \n", " | The shape of the output depends on the size of `indices`, and may be\n", " | larger than `a` (this happens if ``len(indices) > a.shape[axis]``).\n", " | \n", " | Parameters\n", " | ----------\n", " | a : array_like\n", " | The array to act on.\n", " | indices : array_like\n", " | Paired indices, comma separated (not colon), specifying slices to\n", " | reduce.\n", " | axis : int, optional\n", " | The axis along which to apply the reduceat.\n", " | dtype : data-type code, optional\n", " | The type used to represent the intermediate results. Defaults\n", " | to the data type of the output array if this is provided, or\n", " | the data type of the input array if no output array is provided.\n", " | out : ndarray, None, or tuple of ndarray and None, optional\n", " | A location into which the result is stored. If not provided or None,\n", " | a freshly-allocated array is returned. For consistency with\n", " | ``ufunc.__call__``, if given as a keyword, this may be wrapped in a\n", " | 1-element tuple.\n", " | \n", " | .. versionchanged:: 1.13.0\n", " | Tuples are allowed for keyword argument.\n", " | \n", " | Returns\n", " | -------\n", " | r : ndarray\n", " | The reduced values. If `out` was supplied, `r` is a reference to\n", " | `out`.\n", " | \n", " | Notes\n", " | -----\n", " | A descriptive example:\n", " | \n", " | If `a` is 1-D, the function `ufunc.accumulate(a)` is the same as\n", " | ``ufunc.reduceat(a, indices)[::2]`` where `indices` is\n", " | ``range(len(array) - 1)`` with a zero placed\n", " | in every other element:\n", " | ``indices = zeros(2 * len(a) - 1)``, ``indices[1::2] = range(1, len(a))``.\n", " | \n", " | Don't be fooled by this attribute's name: `reduceat(a)` is not\n", " | necessarily smaller than `a`.\n", " | \n", " | Examples\n", " | --------\n", " | To take the running sum of four successive values:\n", " | \n", " | >>> np.add.reduceat(np.arange(8),[0,4, 1,5, 2,6, 3,7])[::2]\n", " | array([ 6, 10, 14, 18])\n", " | \n", " | A 2-D example:\n", " | \n", " | >>> x = np.linspace(0, 15, 16).reshape(4,4)\n", " | >>> x\n", " | array([[ 0., 1., 2., 3.],\n", " | [ 4., 5., 6., 7.],\n", " | [ 8., 9., 10., 11.],\n", " | [12., 13., 14., 15.]])\n", " | \n", " | ::\n", " | \n", " | # reduce such that the result has the following five rows:\n", " | # [row1 + row2 + row3]\n", " | # [row4]\n", " | # [row2]\n", " | # [row3]\n", " | # [row1 + row2 + row3 + row4]\n", " | \n", " | >>> np.add.reduceat(x, [0, 3, 1, 2, 0])\n", " | array([[12., 15., 18., 21.],\n", " | [12., 13., 14., 15.],\n", " | [ 4., 5., 6., 7.],\n", " | [ 8., 9., 10., 11.],\n", " | [24., 28., 32., 36.]])\n", " | \n", " | ::\n", " | \n", " | # reduce such that result has the following two columns:\n", " | # [col1 * col2 * col3, col4]\n", " | \n", " | >>> np.multiply.reduceat(x, [0, 3], 1)\n", " | array([[ 0., 3.],\n", " | [ 120., 7.],\n", " | [ 720., 11.],\n", " | [2184., 15.]])\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | identity\n", " | The identity value.\n", " | \n", " | Data attribute containing the identity element for the ufunc, if it has one.\n", " | If it does not, the attribute value is None.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.add.identity\n", " | 0\n", " | >>> np.multiply.identity\n", " | 1\n", " | >>> np.power.identity\n", " | 1\n", " | >>> print(np.exp.identity)\n", " | None\n", " | \n", " | nargs\n", " | The number of arguments.\n", " | \n", " | Data attribute containing the number of arguments the ufunc takes, including\n", " | optional ones.\n", " | \n", " | Notes\n", " | -----\n", " | Typically this value will be one more than what you might expect because all\n", " | ufuncs take the optional \"out\" argument.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.add.nargs\n", " | 3\n", " | >>> np.multiply.nargs\n", " | 3\n", " | >>> np.power.nargs\n", " | 3\n", " | >>> np.exp.nargs\n", " | 2\n", " | \n", " | nin\n", " | The number of inputs.\n", " | \n", " | Data attribute containing the number of arguments the ufunc treats as input.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.add.nin\n", " | 2\n", " | >>> np.multiply.nin\n", " | 2\n", " | >>> np.power.nin\n", " | 2\n", " | >>> np.exp.nin\n", " | 1\n", " | \n", " | nout\n", " | The number of outputs.\n", " | \n", " | Data attribute containing the number of arguments the ufunc treats as output.\n", " | \n", " | Notes\n", " | -----\n", " | Since all ufuncs can take output arguments, this will always be (at least) 1.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.add.nout\n", " | 1\n", " | >>> np.multiply.nout\n", " | 1\n", " | >>> np.power.nout\n", " | 1\n", " | >>> np.exp.nout\n", " | 1\n", " | \n", " | ntypes\n", " | The number of types.\n", " | \n", " | The number of numerical NumPy types - of which there are 18 total - on which\n", " | the ufunc can operate.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ufunc.types\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.add.ntypes\n", " | 18\n", " | >>> np.multiply.ntypes\n", " | 18\n", " | >>> np.power.ntypes\n", " | 17\n", " | >>> np.exp.ntypes\n", " | 7\n", " | >>> np.remainder.ntypes\n", " | 14\n", " | \n", " | signature\n", " | Definition of the core elements a generalized ufunc operates on.\n", " | \n", " | The signature determines how the dimensions of each input/output array\n", " | are split into core and loop dimensions:\n", " | \n", " | 1. Each dimension in the signature is matched to a dimension of the\n", " | corresponding passed-in array, starting from the end of the shape tuple.\n", " | 2. Core dimensions assigned to the same label in the signature must have\n", " | exactly matching sizes, no broadcasting is performed.\n", " | 3. The core dimensions are removed from all inputs and the remaining\n", " | dimensions are broadcast together, defining the loop dimensions.\n", " | \n", " | Notes\n", " | -----\n", " | Generalized ufuncs are used internally in many linalg functions, and in\n", " | the testing suite; the examples below are taken from these.\n", " | For ufuncs that operate on scalars, the signature is None, which is\n", " | equivalent to '()' for every argument.\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.core.umath_tests.matrix_multiply.signature\n", " | '(m,n),(n,p)->(m,p)'\n", " | >>> np.linalg._umath_linalg.det.signature\n", " | '(m,m)->()'\n", " | >>> np.add.signature is None\n", " | True # equivalent to '(),()->()'\n", " | \n", " | types\n", " | Returns a list with types grouped input->output.\n", " | \n", " | Data attribute listing the data-type \"Domain-Range\" groupings the ufunc can\n", " | deliver. The data-types are given using the character codes.\n", " | \n", " | See Also\n", " | --------\n", " | numpy.ufunc.ntypes\n", " | \n", " | Examples\n", " | --------\n", " | >>> np.add.types\n", " | ['??->?', 'bb->b', 'BB->B', 'hh->h', 'HH->H', 'ii->i', 'II->I', 'll->l',\n", " | 'LL->L', 'qq->q', 'QQ->Q', 'ff->f', 'dd->d', 'gg->g', 'FF->F', 'DD->D',\n", " | 'GG->G', 'OO->O']\n", " | \n", " | >>> np.multiply.types\n", " | ['??->?', 'bb->b', 'BB->B', 'hh->h', 'HH->H', 'ii->i', 'II->I', 'll->l',\n", " | 'LL->L', 'qq->q', 'QQ->Q', 'ff->f', 'dd->d', 'gg->g', 'FF->F', 'DD->D',\n", " | 'GG->G', 'OO->O']\n", " | \n", " | >>> np.power.types\n", " | ['bb->b', 'BB->B', 'hh->h', 'HH->H', 'ii->i', 'II->I', 'll->l', 'LL->L',\n", " | 'qq->q', 'QQ->Q', 'ff->f', 'dd->d', 'gg->g', 'FF->F', 'DD->D', 'GG->G',\n", " | 'OO->O']\n", " | \n", " | >>> np.exp.types\n", " | ['f->f', 'd->d', 'g->g', 'F->F', 'D->D', 'G->G', 'O->O']\n", " | \n", " | >>> np.remainder.types\n", " | ['bb->b', 'BB->B', 'hh->h', 'HH->H', 'ii->i', 'II->I', 'll->l', 'LL->L',\n", " | 'qq->q', 'QQ->Q', 'ff->f', 'dd->d', 'gg->g', 'OO->O']\n", " \n", " uint = class uint64(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned long``.\n", " | Character code: ``'L'``.\n", " | Canonical name: ``np.uint``.\n", " | Alias *on this platform*: ``np.uint64``: 64-bit unsigned integer (0 to 18446744073709551615).\n", " | Alias *on this platform*: ``np.uintp``: Unsigned integer large enough to fit pointer, compatible with C ``uintptr_t``.\n", " | \n", " | Method resolution order:\n", " | uint64\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " uint0 = class uint64(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned long``.\n", " | Character code: ``'L'``.\n", " | Canonical name: ``np.uint``.\n", " | Alias *on this platform*: ``np.uint64``: 64-bit unsigned integer (0 to 18446744073709551615).\n", " | Alias *on this platform*: ``np.uintp``: Unsigned integer large enough to fit pointer, compatible with C ``uintptr_t``.\n", " | \n", " | Method resolution order:\n", " | uint64\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class uint16(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned short``.\n", " | Character code: ``'H'``.\n", " | Canonical name: ``np.ushort``.\n", " | Alias *on this platform*: ``np.uint16``: 16-bit unsigned integer (0 to 65535).\n", " | \n", " | Method resolution order:\n", " | uint16\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class uint32(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned int``.\n", " | Character code: ``'I'``.\n", " | Canonical name: ``np.uintc``.\n", " | Alias *on this platform*: ``np.uint32``: 32-bit unsigned integer (0 to 4294967295).\n", " | \n", " | Method resolution order:\n", " | uint32\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class uint64(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned long``.\n", " | Character code: ``'L'``.\n", " | Canonical name: ``np.uint``.\n", " | Alias *on this platform*: ``np.uint64``: 64-bit unsigned integer (0 to 18446744073709551615).\n", " | Alias *on this platform*: ``np.uintp``: Unsigned integer large enough to fit pointer, compatible with C ``uintptr_t``.\n", " | \n", " | Method resolution order:\n", " | uint64\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class uint8(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned char``.\n", " | Character code: ``'B'``.\n", " | Canonical name: ``np.ubyte``.\n", " | Alias *on this platform*: ``np.uint8``: 8-bit unsigned integer (0 to 255).\n", " | \n", " | Method resolution order:\n", " | uint8\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " uintc = class uint32(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned int``.\n", " | Character code: ``'I'``.\n", " | Canonical name: ``np.uintc``.\n", " | Alias *on this platform*: ``np.uint32``: 32-bit unsigned integer (0 to 4294967295).\n", " | \n", " | Method resolution order:\n", " | uint32\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " uintp = class uint64(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned long``.\n", " | Character code: ``'L'``.\n", " | Canonical name: ``np.uint``.\n", " | Alias *on this platform*: ``np.uint64``: 64-bit unsigned integer (0 to 18446744073709551615).\n", " | Alias *on this platform*: ``np.uintp``: Unsigned integer large enough to fit pointer, compatible with C ``uintptr_t``.\n", " | \n", " | Method resolution order:\n", " | uint64\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class ulonglong(unsignedinteger)\n", " | Signed integer type, compatible with C ``unsigned long long``.\n", " | Character code: ``'Q'``.\n", " | \n", " | Method resolution order:\n", " | ulonglong\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " unicode_ = class str_(builtins.str, character)\n", " | str(object='') -> str\n", " | str(bytes_or_buffer[, encoding[, errors]]) -> str\n", " | \n", " | Create a new string object from the given object. If encoding or\n", " | errors is specified, then the object must expose a data buffer\n", " | that will be decoded using the given encoding and error handler.\n", " | Otherwise, returns the result of object.__str__() (if defined)\n", " | or repr(object).\n", " | encoding defaults to sys.getdefaultencoding().\n", " | errors defaults to 'strict'.\n", " | \n", " | Method resolution order:\n", " | str_\n", " | builtins.str\n", " | character\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lt__(self, value, /)\n", " | Return self int\n", " | \n", " | Return the number of non-overlapping occurrences of substring sub in\n", " | string S[start:end]. Optional arguments start and end are\n", " | interpreted as in slice notation.\n", " | \n", " | encode(self, /, encoding='utf-8', errors='strict')\n", " | Encode the string using the codec registered for encoding.\n", " | \n", " | encoding\n", " | The encoding in which to encode the string.\n", " | errors\n", " | The error handling scheme to use for encoding errors.\n", " | The default is 'strict' meaning that encoding errors raise a\n", " | UnicodeEncodeError. Other possible values are 'ignore', 'replace' and\n", " | 'xmlcharrefreplace' as well as any other name registered with\n", " | codecs.register_error that can handle UnicodeEncodeErrors.\n", " | \n", " | endswith(...)\n", " | S.endswith(suffix[, start[, end]]) -> bool\n", " | \n", " | Return True if S ends with the specified suffix, False otherwise.\n", " | With optional start, test S beginning at that position.\n", " | With optional end, stop comparing S at that position.\n", " | suffix can also be a tuple of strings to try.\n", " | \n", " | expandtabs(self, /, tabsize=8)\n", " | Return a copy where all tab characters are expanded using spaces.\n", " | \n", " | If tabsize is not given, a tab size of 8 characters is assumed.\n", " | \n", " | find(...)\n", " | S.find(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | format(...)\n", " | S.format(*args, **kwargs) -> str\n", " | \n", " | Return a formatted version of S, using substitutions from args and kwargs.\n", " | The substitutions are identified by braces ('{' and '}').\n", " | \n", " | format_map(...)\n", " | S.format_map(mapping) -> str\n", " | \n", " | Return a formatted version of S, using substitutions from mapping.\n", " | The substitutions are identified by braces ('{' and '}').\n", " | \n", " | index(...)\n", " | S.index(sub[, start[, end]]) -> int\n", " | \n", " | Return the lowest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the substring is not found.\n", " | \n", " | isalnum(self, /)\n", " | Return True if the string is an alpha-numeric string, False otherwise.\n", " | \n", " | A string is alpha-numeric if all characters in the string are alpha-numeric and\n", " | there is at least one character in the string.\n", " | \n", " | isalpha(self, /)\n", " | Return True if the string is an alphabetic string, False otherwise.\n", " | \n", " | A string is alphabetic if all characters in the string are alphabetic and there\n", " | is at least one character in the string.\n", " | \n", " | isascii(self, /)\n", " | Return True if all characters in the string are ASCII, False otherwise.\n", " | \n", " | ASCII characters have code points in the range U+0000-U+007F.\n", " | Empty string is ASCII too.\n", " | \n", " | isdecimal(self, /)\n", " | Return True if the string is a decimal string, False otherwise.\n", " | \n", " | A string is a decimal string if all characters in the string are decimal and\n", " | there is at least one character in the string.\n", " | \n", " | isdigit(self, /)\n", " | Return True if the string is a digit string, False otherwise.\n", " | \n", " | A string is a digit string if all characters in the string are digits and there\n", " | is at least one character in the string.\n", " | \n", " | isidentifier(self, /)\n", " | Return True if the string is a valid Python identifier, False otherwise.\n", " | \n", " | Call keyword.iskeyword(s) to test whether string s is a reserved identifier,\n", " | such as \"def\" or \"class\".\n", " | \n", " | islower(self, /)\n", " | Return True if the string is a lowercase string, False otherwise.\n", " | \n", " | A string is lowercase if all cased characters in the string are lowercase and\n", " | there is at least one cased character in the string.\n", " | \n", " | isnumeric(self, /)\n", " | Return True if the string is a numeric string, False otherwise.\n", " | \n", " | A string is numeric if all characters in the string are numeric and there is at\n", " | least one character in the string.\n", " | \n", " | isprintable(self, /)\n", " | Return True if the string is printable, False otherwise.\n", " | \n", " | A string is printable if all of its characters are considered printable in\n", " | repr() or if it is empty.\n", " | \n", " | isspace(self, /)\n", " | Return True if the string is a whitespace string, False otherwise.\n", " | \n", " | A string is whitespace if all characters in the string are whitespace and there\n", " | is at least one character in the string.\n", " | \n", " | istitle(self, /)\n", " | Return True if the string is a title-cased string, False otherwise.\n", " | \n", " | In a title-cased string, upper- and title-case characters may only\n", " | follow uncased characters and lowercase characters only cased ones.\n", " | \n", " | isupper(self, /)\n", " | Return True if the string is an uppercase string, False otherwise.\n", " | \n", " | A string is uppercase if all cased characters in the string are uppercase and\n", " | there is at least one cased character in the string.\n", " | \n", " | join(self, iterable, /)\n", " | Concatenate any number of strings.\n", " | \n", " | The string whose method is called is inserted in between each given string.\n", " | The result is returned as a new string.\n", " | \n", " | Example: '.'.join(['ab', 'pq', 'rs']) -> 'ab.pq.rs'\n", " | \n", " | ljust(self, width, fillchar=' ', /)\n", " | Return a left-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character (default is a space).\n", " | \n", " | lower(self, /)\n", " | Return a copy of the string converted to lowercase.\n", " | \n", " | lstrip(self, chars=None, /)\n", " | Return a copy of the string with leading whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | partition(self, sep, /)\n", " | Partition the string into three parts using the given separator.\n", " | \n", " | This will search for the separator in the string. If the separator is found,\n", " | returns a 3-tuple containing the part before the separator, the separator\n", " | itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing the original string\n", " | and two empty strings.\n", " | \n", " | replace(self, old, new, count=-1, /)\n", " | Return a copy with all occurrences of substring old replaced by new.\n", " | \n", " | count\n", " | Maximum number of occurrences to replace.\n", " | -1 (the default value) means replace all occurrences.\n", " | \n", " | If the optional argument count is given, only the first count occurrences are\n", " | replaced.\n", " | \n", " | rfind(...)\n", " | S.rfind(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Return -1 on failure.\n", " | \n", " | rindex(...)\n", " | S.rindex(sub[, start[, end]]) -> int\n", " | \n", " | Return the highest index in S where substring sub is found,\n", " | such that sub is contained within S[start:end]. Optional\n", " | arguments start and end are interpreted as in slice notation.\n", " | \n", " | Raises ValueError when the substring is not found.\n", " | \n", " | rjust(self, width, fillchar=' ', /)\n", " | Return a right-justified string of length width.\n", " | \n", " | Padding is done using the specified fill character (default is a space).\n", " | \n", " | rpartition(self, sep, /)\n", " | Partition the string into three parts using the given separator.\n", " | \n", " | This will search for the separator in the string, starting at the end. If\n", " | the separator is found, returns a 3-tuple containing the part before the\n", " | separator, the separator itself, and the part after it.\n", " | \n", " | If the separator is not found, returns a 3-tuple containing two empty strings\n", " | and the original string.\n", " | \n", " | rsplit(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the words in the string, using sep as the delimiter string.\n", " | \n", " | sep\n", " | The delimiter according which to split the string.\n", " | None (the default value) means split according to any whitespace,\n", " | and discard empty strings from the result.\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | Splits are done starting at the end of the string and working to the front.\n", " | \n", " | rstrip(self, chars=None, /)\n", " | Return a copy of the string with trailing whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | split(self, /, sep=None, maxsplit=-1)\n", " | Return a list of the words in the string, using sep as the delimiter string.\n", " | \n", " | sep\n", " | The delimiter according which to split the string.\n", " | None (the default value) means split according to any whitespace,\n", " | and discard empty strings from the result.\n", " | maxsplit\n", " | Maximum number of splits to do.\n", " | -1 (the default value) means no limit.\n", " | \n", " | splitlines(self, /, keepends=False)\n", " | Return a list of the lines in the string, breaking at line boundaries.\n", " | \n", " | Line breaks are not included in the resulting list unless keepends is given and\n", " | true.\n", " | \n", " | startswith(...)\n", " | S.startswith(prefix[, start[, end]]) -> bool\n", " | \n", " | Return True if S starts with the specified prefix, False otherwise.\n", " | With optional start, test S beginning at that position.\n", " | With optional end, stop comparing S at that position.\n", " | prefix can also be a tuple of strings to try.\n", " | \n", " | strip(self, chars=None, /)\n", " | Return a copy of the string with leading and trailing whitespace removed.\n", " | \n", " | If chars is given and not None, remove characters in chars instead.\n", " | \n", " | swapcase(self, /)\n", " | Convert uppercase characters to lowercase and lowercase characters to uppercase.\n", " | \n", " | title(self, /)\n", " | Return a version of the string where each word is titlecased.\n", " | \n", " | More specifically, words start with uppercased characters and all remaining\n", " | cased characters have lower case.\n", " | \n", " | translate(self, table, /)\n", " | Replace each character in the string using the given translation table.\n", " | \n", " | table\n", " | Translation table, which must be a mapping of Unicode ordinals to\n", " | Unicode ordinals, strings, or None.\n", " | \n", " | The table must implement lookup/indexing via __getitem__, for instance a\n", " | dictionary or list. If this operation raises LookupError, the character is\n", " | left untouched. Characters mapped to None are deleted.\n", " | \n", " | upper(self, /)\n", " | Return a copy of the string converted to uppercase.\n", " | \n", " | zfill(self, width, /)\n", " | Pad a numeric string with zeros on the left, to fill a field of the given width.\n", " | \n", " | The string is never truncated.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods inherited from builtins.str:\n", " | \n", " | maketrans(...)\n", " | Return a translation table usable for str.translate().\n", " | \n", " | If there is only one argument, it must be a dictionary mapping Unicode\n", " | ordinals (integers) or characters to Unicode ordinals, strings or None.\n", " | Character keys will be then converted to ordinals.\n", " | If there are two arguments, they must be strings of equal length, and\n", " | in the resulting dictionary, each character in x will be mapped to the\n", " | character at the same position in y. If there is a third argument, it\n", " | must be a string, whose characters will be mapped to None in the result.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class unsignedinteger(integer)\n", " | Abstract base class of all unsigned integer scalar types.\n", " | \n", " | Method resolution order:\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data and other attributes inherited from generic:\n", " | \n", " | __hash__ = None\n", " \n", " ushort = class uint16(unsignedinteger)\n", " | Unsigned integer type, compatible with C ``unsigned short``.\n", " | Character code: ``'H'``.\n", " | Canonical name: ``np.ushort``.\n", " | Alias *on this platform*: ``np.uint16``: 16-bit unsigned integer (0 to 65535).\n", " | \n", " | Method resolution order:\n", " | uint16\n", " | unsignedinteger\n", " | integer\n", " | number\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __abs__(self, /)\n", " | abs(self)\n", " | \n", " | __add__(self, value, /)\n", " | Return self+value.\n", " | \n", " | __and__(self, value, /)\n", " | Return self&value.\n", " | \n", " | __bool__(self, /)\n", " | self != 0\n", " | \n", " | __divmod__(self, value, /)\n", " | Return divmod(self, value).\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __float__(self, /)\n", " | float(self)\n", " | \n", " | __floordiv__(self, value, /)\n", " | Return self//value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __index__(self, /)\n", " | Return self converted to an integer, if self is suitable for use as an index into a list.\n", " | \n", " | __int__(self, /)\n", " | int(self)\n", " | \n", " | __invert__(self, /)\n", " | ~self\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __lshift__(self, value, /)\n", " | Return self<>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __str__(self, /)\n", " | Return str(self).\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Static methods defined here:\n", " | \n", " | __new__(*args, **kwargs) from builtins.type\n", " | Create and return a new object. See help(type) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from integer:\n", " | \n", " | __round__(...)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from integer:\n", " | \n", " | denominator\n", " | denominator of value (1)\n", " | \n", " | numerator\n", " | numerator of value (the value itself)\n", " | \n", " | ----------------------------------------------------------------------\n", " | Methods inherited from generic:\n", " | \n", " | __array__(...)\n", " | sc.__array__(dtype) return 0-dim array from scalar with specified dtype\n", " | \n", " | __array_wrap__(...)\n", " | sc.__array_wrap__(obj) return scalar from array\n", " | \n", " | __copy__(...)\n", " | \n", " | __deepcopy__(...)\n", " | \n", " | __format__(...)\n", " | NumPy array scalar formatter\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __reduce__(...)\n", " | Helper for pickle.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | getfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setfield(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | base\n", " | base object\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | dtype\n", " | get array data-descriptor\n", " | \n", " | flags\n", " | integer value of flags\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " class vectorize(builtins.object)\n", " | vectorize(pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None)\n", " | \n", " | vectorize(pyfunc, otypes=None, doc=None, excluded=None, cache=False,\n", " | signature=None)\n", " | \n", " | Generalized function class.\n", " | \n", " | Define a vectorized function which takes a nested sequence of objects or\n", " | numpy arrays as inputs and returns a single numpy array or a tuple of numpy\n", " | arrays. The vectorized function evaluates `pyfunc` over successive tuples\n", " | of the input arrays like the python map function, except it uses the\n", " | broadcasting rules of numpy.\n", " | \n", " | The data type of the output of `vectorized` is determined by calling\n", " | the function with the first element of the input. This can be avoided\n", " | by specifying the `otypes` argument.\n", " | \n", " | Parameters\n", " | ----------\n", " | pyfunc : callable\n", " | A python function or method.\n", " | otypes : str or list of dtypes, optional\n", " | The output data type. It must be specified as either a string of\n", " | typecode characters or a list of data type specifiers. There should\n", " | be one data type specifier for each output.\n", " | doc : str, optional\n", " | The docstring for the function. If None, the docstring will be the\n", " | ``pyfunc.__doc__``.\n", " | excluded : set, optional\n", " | Set of strings or integers representing the positional or keyword\n", " | arguments for which the function will not be vectorized. These will be\n", " | passed directly to `pyfunc` unmodified.\n", " | \n", " | .. versionadded:: 1.7.0\n", " | \n", " | cache : bool, optional\n", " | If `True`, then cache the first function call that determines the number\n", " | of outputs if `otypes` is not provided.\n", " | \n", " | .. versionadded:: 1.7.0\n", " | \n", " | signature : string, optional\n", " | Generalized universal function signature, e.g., ``(m,n),(n)->(m)`` for\n", " | vectorized matrix-vector multiplication. If provided, ``pyfunc`` will\n", " | be called with (and expected to return) arrays with shapes given by the\n", " | size of corresponding core dimensions. By default, ``pyfunc`` is\n", " | assumed to take scalars as input and output.\n", " | \n", " | .. versionadded:: 1.12.0\n", " | \n", " | Returns\n", " | -------\n", " | vectorized : callable\n", " | Vectorized function.\n", " | \n", " | See Also\n", " | --------\n", " | frompyfunc : Takes an arbitrary Python function and returns a ufunc\n", " | \n", " | Notes\n", " | -----\n", " | The `vectorize` function is provided primarily for convenience, not for\n", " | performance. The implementation is essentially a for loop.\n", " | \n", " | If `otypes` is not specified, then a call to the function with the\n", " | first argument will be used to determine the number of outputs. The\n", " | results of this call will be cached if `cache` is `True` to prevent\n", " | calling the function twice. However, to implement the cache, the\n", " | original function must be wrapped which will slow down subsequent\n", " | calls, so only do this if your function is expensive.\n", " | \n", " | The new keyword argument interface and `excluded` argument support\n", " | further degrades performance.\n", " | \n", " | References\n", " | ----------\n", " | .. [1] NumPy Reference, section `Generalized Universal Function API\n", " | `_.\n", " | \n", " | Examples\n", " | --------\n", " | >>> def myfunc(a, b):\n", " | ... \"Return a-b if a>b, otherwise return a+b\"\n", " | ... if a > b:\n", " | ... return a - b\n", " | ... else:\n", " | ... return a + b\n", " | \n", " | >>> vfunc = np.vectorize(myfunc)\n", " | >>> vfunc([1, 2, 3, 4], 2)\n", " | array([3, 4, 1, 2])\n", " | \n", " | The docstring is taken from the input function to `vectorize` unless it\n", " | is specified:\n", " | \n", " | >>> vfunc.__doc__\n", " | 'Return a-b if a>b, otherwise return a+b'\n", " | >>> vfunc = np.vectorize(myfunc, doc='Vectorized `myfunc`')\n", " | >>> vfunc.__doc__\n", " | 'Vectorized `myfunc`'\n", " | \n", " | The output type is determined by evaluating the first element of the input,\n", " | unless it is specified:\n", " | \n", " | >>> out = vfunc([1, 2, 3, 4], 2)\n", " | >>> type(out[0])\n", " | \n", " | >>> vfunc = np.vectorize(myfunc, otypes=[float])\n", " | >>> out = vfunc([1, 2, 3, 4], 2)\n", " | >>> type(out[0])\n", " | \n", " | \n", " | The `excluded` argument can be used to prevent vectorizing over certain\n", " | arguments. This can be useful for array-like arguments of a fixed length\n", " | such as the coefficients for a polynomial as in `polyval`:\n", " | \n", " | >>> def mypolyval(p, x):\n", " | ... _p = list(p)\n", " | ... res = _p.pop(0)\n", " | ... while _p:\n", " | ... res = res*x + _p.pop(0)\n", " | ... return res\n", " | >>> vpolyval = np.vectorize(mypolyval, excluded=['p'])\n", " | >>> vpolyval(p=[1, 2, 3], x=[0, 1])\n", " | array([3, 6])\n", " | \n", " | Positional arguments may also be excluded by specifying their position:\n", " | \n", " | >>> vpolyval.excluded.add(0)\n", " | >>> vpolyval([1, 2, 3], x=[0, 1])\n", " | array([3, 6])\n", " | \n", " | The `signature` argument allows for vectorizing functions that act on\n", " | non-scalar arrays of fixed length. For example, you can use it for a\n", " | vectorized calculation of Pearson correlation coefficient and its p-value:\n", " | \n", " | >>> import scipy.stats\n", " | >>> pearsonr = np.vectorize(scipy.stats.pearsonr,\n", " | ... signature='(n),(n)->(),()')\n", " | >>> pearsonr([[0, 1, 2, 3]], [[1, 2, 3, 4], [4, 3, 2, 1]])\n", " | (array([ 1., -1.]), array([ 0., 0.]))\n", " | \n", " | Or for a vectorized convolution:\n", " | \n", " | >>> convolve = np.vectorize(np.convolve, signature='(n),(m)->(k)')\n", " | >>> convolve(np.eye(4), [1, 2, 1])\n", " | array([[1., 2., 1., 0., 0., 0.],\n", " | [0., 1., 2., 1., 0., 0.],\n", " | [0., 0., 1., 2., 1., 0.],\n", " | [0., 0., 0., 1., 2., 1.]])\n", " | \n", " | Methods defined here:\n", " | \n", " | __call__(self, *args, **kwargs)\n", " | Return arrays with the results of `pyfunc` broadcast (vectorized) over\n", " | `args` and `kwargs` not in `excluded`.\n", " | \n", " | __init__(self, pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors defined here:\n", " | \n", " | __dict__\n", " | dictionary for instance variables (if defined)\n", " | \n", " | __weakref__\n", " | list of weak references to the object (if defined)\n", " \n", " class void(flexible)\n", " | Abstract base class of all scalar types without predefined length.\n", " | The actual size of these types depends on the specific `np.dtype`\n", " | instantiation.\n", " | \n", " | Method resolution order:\n", " | void\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", " \n", " void0 = class void(flexible)\n", " | Abstract base class of all scalar types without predefined length.\n", " | The actual size of these types depends on the specific `np.dtype`\n", " | instantiation.\n", " | \n", " | Method resolution order:\n", " | void\n", " | flexible\n", " | generic\n", " | builtins.object\n", " | \n", " | Methods defined here:\n", " | \n", " | __delitem__(self, key, /)\n", " | Delete self[key].\n", " | \n", " | __eq__(self, value, /)\n", " | Return self==value.\n", " | \n", " | __ge__(self, value, /)\n", " | Return self>=value.\n", " | \n", " | __getitem__(self, key, /)\n", " | Return self[key].\n", " | \n", " | __gt__(self, value, /)\n", " | Return self>value.\n", " | \n", " | __hash__(self, /)\n", " | Return hash(self).\n", " | \n", " | __le__(self, value, /)\n", " | Return self<=value.\n", " | \n", " | __len__(self, /)\n", " | Return len(self).\n", " | \n", " | __lt__(self, value, /)\n", " | Return self>self.\n", " | \n", " | __rshift__(self, value, /)\n", " | Return self>>value.\n", " | \n", " | __rsub__(self, value, /)\n", " | Return value-self.\n", " | \n", " | __rtruediv__(self, value, /)\n", " | Return value/self.\n", " | \n", " | __rxor__(self, value, /)\n", " | Return value^self.\n", " | \n", " | __setstate__(...)\n", " | \n", " | __sizeof__(...)\n", " | Size of object in memory, in bytes.\n", " | \n", " | __sub__(self, value, /)\n", " | Return self-value.\n", " | \n", " | __truediv__(self, value, /)\n", " | Return self/value.\n", " | \n", " | __xor__(self, value, /)\n", " | Return self^value.\n", " | \n", " | all(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | any(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmax(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argmin(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | argsort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | astype(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | byteswap(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | choose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | clip(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | compress(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | conj(...)\n", " | \n", " | conjugate(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | copy(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumprod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | cumsum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | diagonal(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dump(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | dumps(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | fill(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | flatten(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | item(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | itemset(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | max(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | mean(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | min(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | newbyteorder(...)\n", " | newbyteorder(new_order='S')\n", " | \n", " | Return a new `dtype` with a different byte order.\n", " | \n", " | Changes are also made in all fields and sub-arrays of the data type.\n", " | \n", " | The `new_order` code can be any from the following:\n", " | \n", " | * 'S' - swap dtype from current to opposite endian\n", " | * {'<', 'L'} - little endian\n", " | * {'>', 'B'} - big endian\n", " | * {'=', 'N'} - native order\n", " | * {'|', 'I'} - ignore (no change to byte order)\n", " | \n", " | Parameters\n", " | ----------\n", " | new_order : str, optional\n", " | Byte order to force; a value from the byte order specifications\n", " | above. The default value ('S') results in swapping the current\n", " | byte order. The code does a case-insensitive check on the first\n", " | letter of `new_order` for the alternatives above. For example,\n", " | any of 'B' or 'b' or 'biggish' are valid to specify big-endian.\n", " | \n", " | \n", " | Returns\n", " | -------\n", " | new_dtype : dtype\n", " | New `dtype` object with the given change to the byte order.\n", " | \n", " | nonzero(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | prod(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ptp(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | put(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ravel(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | repeat(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | reshape(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | resize(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | round(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | searchsorted(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | setflags(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class so as to\n", " | provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sort(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | squeeze(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | std(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | sum(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | swapaxes(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | take(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tobytes(...)\n", " | \n", " | tofile(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tolist(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | tostring(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | trace(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | transpose(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | var(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | view(...)\n", " | Not implemented (virtual attribute)\n", " | \n", " | Class generic exists solely to derive numpy scalars from, and possesses,\n", " | albeit unimplemented, all the attributes of the ndarray class\n", " | so as to provide a uniform API.\n", " | \n", " | See also the corresponding attribute of the derived class of interest.\n", " | \n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from generic:\n", " | \n", " | T\n", " | transpose\n", " | \n", " | __array_interface__\n", " | Array protocol: Python side\n", " | \n", " | __array_priority__\n", " | Array priority.\n", " | \n", " | __array_struct__\n", " | Array protocol: struct\n", " | \n", " | data\n", " | pointer to start of data\n", " | \n", " | flat\n", " | a 1-d view of scalar\n", " | \n", " | imag\n", " | imaginary part of scalar\n", " | \n", " | itemsize\n", " | length of one element in bytes\n", " | \n", " | nbytes\n", " | length of item in bytes\n", " | \n", " | ndim\n", " | number of array dimensions\n", " | \n", " | real\n", " | real part of scalar\n", " | \n", " | shape\n", " | tuple of array dimensions\n", " | \n", " | size\n", " | number of elements in the gentype\n", " | \n", " | strides\n", " | tuple of bytes steps in each dimension\n", "\n", "FUNCTIONS\n", " _add_newdoc_ufunc(...)\n", " scipy._add_newdoc_ufunc is deprecated and will be removed in SciPy 2.0.0, use numpy._add_newdoc_ufunc instead\n", " \n", " absolute(...)\n", " scipy.absolute is deprecated and will be removed in SciPy 2.0.0, use numpy.absolute instead\n", " \n", " add(...)\n", " scipy.add is deprecated and will be removed in SciPy 2.0.0, use numpy.add instead\n", " \n", " add_docstring(...)\n", " scipy.add_docstring is deprecated and will be removed in SciPy 2.0.0, use numpy.add_docstring instead\n", " \n", " add_newdoc(place, obj, doc, warn_on_python=True)\n", " scipy.add_newdoc is deprecated and will be removed in SciPy 2.0.0, use numpy.add_newdoc instead\n", " \n", " add_newdoc_ufunc = _add_newdoc_ufunc(...)\n", " scipy.add_newdoc_ufunc is deprecated and will be removed in SciPy 2.0.0, use numpy.add_newdoc_ufunc instead\n", " \n", " alen(a)\n", " scipy.alen is deprecated and will be removed in SciPy 2.0.0, use numpy.alen instead\n", " \n", " all(a, axis=None, out=None, keepdims=)\n", " scipy.all is deprecated and will be removed in SciPy 2.0.0, use numpy.all instead\n", " \n", " allclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)\n", " scipy.allclose is deprecated and will be removed in SciPy 2.0.0, use numpy.allclose instead\n", " \n", " alltrue(*args, **kwargs)\n", " scipy.alltrue is deprecated and will be removed in SciPy 2.0.0, use numpy.alltrue instead\n", " \n", " amax(a, axis=None, out=None, keepdims=, initial=, where=)\n", " scipy.amax is deprecated and will be removed in SciPy 2.0.0, use numpy.amax instead\n", " \n", " amin(a, axis=None, out=None, keepdims=, initial=, where=)\n", " scipy.amin is deprecated and will be removed in SciPy 2.0.0, use numpy.amin instead\n", " \n", " angle(z, deg=False)\n", " scipy.angle is deprecated and will be removed in SciPy 2.0.0, use numpy.angle instead\n", " \n", " any(a, axis=None, out=None, keepdims=)\n", " scipy.any is deprecated and will be removed in SciPy 2.0.0, use numpy.any instead\n", " \n", " append(arr, values, axis=None)\n", " scipy.append is deprecated and will be removed in SciPy 2.0.0, use numpy.append instead\n", " \n", " apply_along_axis(func1d, axis, arr, *args, **kwargs)\n", " scipy.apply_along_axis is deprecated and will be removed in SciPy 2.0.0, use numpy.apply_along_axis instead\n", " \n", " apply_over_axes(func, a, axes)\n", " scipy.apply_over_axes is deprecated and will be removed in SciPy 2.0.0, use numpy.apply_over_axes instead\n", " \n", " arange(...)\n", " scipy.arange is deprecated and will be removed in SciPy 2.0.0, use numpy.arange instead\n", " \n", " arccos(x)\n", " scipy.arccos is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.arccos instead\n", " \n", " arccosh(...)\n", " scipy.arccosh is deprecated and will be removed in SciPy 2.0.0, use numpy.arccosh instead\n", " \n", " arcsin(x)\n", " scipy.arcsin is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.arcsin instead\n", " \n", " arcsinh(...)\n", " scipy.arcsinh is deprecated and will be removed in SciPy 2.0.0, use numpy.arcsinh instead\n", " \n", " arctan(...)\n", " scipy.arctan is deprecated and will be removed in SciPy 2.0.0, use numpy.arctan instead\n", " \n", " arctan2(...)\n", " scipy.arctan2 is deprecated and will be removed in SciPy 2.0.0, use numpy.arctan2 instead\n", " \n", " arctanh(x)\n", " scipy.arctanh is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.arctanh instead\n", " \n", " argmax(a, axis=None, out=None)\n", " scipy.argmax is deprecated and will be removed in SciPy 2.0.0, use numpy.argmax instead\n", " \n", " argmin(a, axis=None, out=None)\n", " scipy.argmin is deprecated and will be removed in SciPy 2.0.0, use numpy.argmin instead\n", " \n", " argpartition(a, kth, axis=-1, kind='introselect', order=None)\n", " scipy.argpartition is deprecated and will be removed in SciPy 2.0.0, use numpy.argpartition instead\n", " \n", " argsort(a, axis=-1, kind=None, order=None)\n", " scipy.argsort is deprecated and will be removed in SciPy 2.0.0, use numpy.argsort instead\n", " \n", " argwhere(a)\n", " scipy.argwhere is deprecated and will be removed in SciPy 2.0.0, use numpy.argwhere instead\n", " \n", " around(a, decimals=0, out=None)\n", " scipy.around is deprecated and will be removed in SciPy 2.0.0, use numpy.around instead\n", " \n", " array(...)\n", " scipy.array is deprecated and will be removed in SciPy 2.0.0, use numpy.array instead\n", " \n", " array2string(a, max_line_width=None, precision=None, suppress_small=None, separator=' ', prefix='', style=, formatter=None, threshold=None, edgeitems=None, sign=None, floatmode=None, suffix='', *, legacy=None)\n", " scipy.array2string is deprecated and will be removed in SciPy 2.0.0, use numpy.array2string instead\n", " \n", " array_equal(a1, a2, equal_nan=False)\n", " scipy.array_equal is deprecated and will be removed in SciPy 2.0.0, use numpy.array_equal instead\n", " \n", " array_equiv(a1, a2)\n", " scipy.array_equiv is deprecated and will be removed in SciPy 2.0.0, use numpy.array_equiv instead\n", " \n", " array_repr(arr, max_line_width=None, precision=None, suppress_small=None)\n", " scipy.array_repr is deprecated and will be removed in SciPy 2.0.0, use numpy.array_repr instead\n", " \n", " array_split(ary, indices_or_sections, axis=0)\n", " scipy.array_split is deprecated and will be removed in SciPy 2.0.0, use numpy.array_split instead\n", " \n", " array_str(a, max_line_width=None, precision=None, suppress_small=None)\n", " scipy.array_str is deprecated and will be removed in SciPy 2.0.0, use numpy.array_str instead\n", " \n", " asanyarray(a, dtype=None, order=None)\n", " scipy.asanyarray is deprecated and will be removed in SciPy 2.0.0, use numpy.asanyarray instead\n", " \n", " asarray(a, dtype=None, order=None)\n", " scipy.asarray is deprecated and will be removed in SciPy 2.0.0, use numpy.asarray instead\n", " \n", " asarray_chkfinite(a, dtype=None, order=None)\n", " scipy.asarray_chkfinite is deprecated and will be removed in SciPy 2.0.0, use numpy.asarray_chkfinite instead\n", " \n", " ascontiguousarray(a, dtype=None)\n", " scipy.ascontiguousarray is deprecated and will be removed in SciPy 2.0.0, use numpy.ascontiguousarray instead\n", " \n", " asfarray(a, dtype=)\n", " scipy.asfarray is deprecated and will be removed in SciPy 2.0.0, use numpy.asfarray instead\n", " \n", " asfortranarray(a, dtype=None)\n", " scipy.asfortranarray is deprecated and will be removed in SciPy 2.0.0, use numpy.asfortranarray instead\n", " \n", " asmatrix(data, dtype=None)\n", " scipy.asmatrix is deprecated and will be removed in SciPy 2.0.0, use numpy.asmatrix instead\n", " \n", " asscalar(a)\n", " scipy.asscalar is deprecated and will be removed in SciPy 2.0.0, use numpy.asscalar instead\n", " \n", " atleast_1d(*arys)\n", " scipy.atleast_1d is deprecated and will be removed in SciPy 2.0.0, use numpy.atleast_1d instead\n", " \n", " atleast_2d(*arys)\n", " scipy.atleast_2d is deprecated and will be removed in SciPy 2.0.0, use numpy.atleast_2d instead\n", " \n", " atleast_3d(*arys)\n", " scipy.atleast_3d is deprecated and will be removed in SciPy 2.0.0, use numpy.atleast_3d instead\n", " \n", " average(a, axis=None, weights=None, returned=False)\n", " scipy.average is deprecated and will be removed in SciPy 2.0.0, use numpy.average instead\n", " \n", " bartlett(M)\n", " scipy.bartlett is deprecated and will be removed in SciPy 2.0.0, use numpy.bartlett instead\n", " \n", " base_repr(number, base=2, padding=0)\n", " scipy.base_repr is deprecated and will be removed in SciPy 2.0.0, use numpy.base_repr instead\n", " \n", " binary_repr(num, width=None)\n", " scipy.binary_repr is deprecated and will be removed in SciPy 2.0.0, use numpy.binary_repr instead\n", " \n", " bincount(...)\n", " scipy.bincount is deprecated and will be removed in SciPy 2.0.0, use numpy.bincount instead\n", " \n", " bitwise_and(...)\n", " scipy.bitwise_and is deprecated and will be removed in SciPy 2.0.0, use numpy.bitwise_and instead\n", " \n", " bitwise_not = invert(...)\n", " scipy.bitwise_not is deprecated and will be removed in SciPy 2.0.0, use numpy.bitwise_not instead\n", " \n", " bitwise_or(...)\n", " scipy.bitwise_or is deprecated and will be removed in SciPy 2.0.0, use numpy.bitwise_or instead\n", " \n", " bitwise_xor(...)\n", " scipy.bitwise_xor is deprecated and will be removed in SciPy 2.0.0, use numpy.bitwise_xor instead\n", " \n", " blackman(M)\n", " scipy.blackman is deprecated and will be removed in SciPy 2.0.0, use numpy.blackman instead\n", " \n", " block(arrays)\n", " scipy.block is deprecated and will be removed in SciPy 2.0.0, use numpy.block instead\n", " \n", " bmat(obj, ldict=None, gdict=None)\n", " scipy.bmat is deprecated and will be removed in SciPy 2.0.0, use numpy.bmat instead\n", " \n", " broadcast_arrays(*args, subok=False)\n", " scipy.broadcast_arrays is deprecated and will be removed in SciPy 2.0.0, use numpy.broadcast_arrays instead\n", " \n", " broadcast_to(array, shape, subok=False)\n", " scipy.broadcast_to is deprecated and will be removed in SciPy 2.0.0, use numpy.broadcast_to instead\n", " \n", " busday_count(...)\n", " scipy.busday_count is deprecated and will be removed in SciPy 2.0.0, use numpy.busday_count instead\n", " \n", " busday_offset(...)\n", " scipy.busday_offset is deprecated and will be removed in SciPy 2.0.0, use numpy.busday_offset instead\n", " \n", " byte_bounds(a)\n", " scipy.byte_bounds is deprecated and will be removed in SciPy 2.0.0, use numpy.byte_bounds instead\n", " \n", " can_cast(...)\n", " scipy.can_cast is deprecated and will be removed in SciPy 2.0.0, use numpy.can_cast instead\n", " \n", " cbrt(...)\n", " scipy.cbrt is deprecated and will be removed in SciPy 2.0.0, use numpy.cbrt instead\n", " \n", " ceil(...)\n", " scipy.ceil is deprecated and will be removed in SciPy 2.0.0, use numpy.ceil instead\n", " \n", " choose(a, choices, out=None, mode='raise')\n", " scipy.choose is deprecated and will be removed in SciPy 2.0.0, use numpy.choose instead\n", " \n", " clip(a, a_min, a_max, out=None, **kwargs)\n", " scipy.clip is deprecated and will be removed in SciPy 2.0.0, use numpy.clip instead\n", " \n", " column_stack(tup)\n", " scipy.column_stack is deprecated and will be removed in SciPy 2.0.0, use numpy.column_stack instead\n", " \n", " common_type(*arrays)\n", " scipy.common_type is deprecated and will be removed in SciPy 2.0.0, use numpy.common_type instead\n", " \n", " compare_chararrays(...)\n", " scipy.compare_chararrays is deprecated and will be removed in SciPy 2.0.0, use numpy.compare_chararrays instead\n", " \n", " compress(condition, a, axis=None, out=None)\n", " scipy.compress is deprecated and will be removed in SciPy 2.0.0, use numpy.compress instead\n", " \n", " concatenate(...)\n", " scipy.concatenate is deprecated and will be removed in SciPy 2.0.0, use numpy.concatenate instead\n", " \n", " conj = conjugate(...)\n", " scipy.conj is deprecated and will be removed in SciPy 2.0.0, use numpy.conj instead\n", " \n", " conjugate(...)\n", " scipy.conjugate is deprecated and will be removed in SciPy 2.0.0, use numpy.conjugate instead\n", " \n", " convolve(a, v, mode='full')\n", " scipy.convolve is deprecated and will be removed in SciPy 2.0.0, use numpy.convolve instead\n", " \n", " copy(a, order='K', subok=False)\n", " scipy.copy is deprecated and will be removed in SciPy 2.0.0, use numpy.copy instead\n", " \n", " copysign(...)\n", " scipy.copysign is deprecated and will be removed in SciPy 2.0.0, use numpy.copysign instead\n", " \n", " copyto(...)\n", " scipy.copyto is deprecated and will be removed in SciPy 2.0.0, use numpy.copyto instead\n", " \n", " corrcoef(x, y=None, rowvar=True, bias=, ddof=)\n", " scipy.corrcoef is deprecated and will be removed in SciPy 2.0.0, use numpy.corrcoef instead\n", " \n", " correlate(a, v, mode='valid')\n", " scipy.correlate is deprecated and will be removed in SciPy 2.0.0, use numpy.correlate instead\n", " \n", " cos(...)\n", " scipy.cos is deprecated and will be removed in SciPy 2.0.0, use numpy.cos instead\n", " \n", " cosh(...)\n", " scipy.cosh is deprecated and will be removed in SciPy 2.0.0, use numpy.cosh instead\n", " \n", " count_nonzero(a, axis=None, *, keepdims=False)\n", " scipy.count_nonzero is deprecated and will be removed in SciPy 2.0.0, use numpy.count_nonzero instead\n", " \n", " cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, aweights=None)\n", " scipy.cov is deprecated and will be removed in SciPy 2.0.0, use numpy.cov instead\n", " \n", " cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None)\n", " scipy.cross is deprecated and will be removed in SciPy 2.0.0, use numpy.cross instead\n", " \n", " cumprod(a, axis=None, dtype=None, out=None)\n", " scipy.cumprod is deprecated and will be removed in SciPy 2.0.0, use numpy.cumprod instead\n", " \n", " cumproduct(*args, **kwargs)\n", " scipy.cumproduct is deprecated and will be removed in SciPy 2.0.0, use numpy.cumproduct instead\n", " \n", " cumsum(a, axis=None, dtype=None, out=None)\n", " scipy.cumsum is deprecated and will be removed in SciPy 2.0.0, use numpy.cumsum instead\n", " \n", " datetime_as_string(...)\n", " scipy.datetime_as_string is deprecated and will be removed in SciPy 2.0.0, use numpy.datetime_as_string instead\n", " \n", " datetime_data(...)\n", " scipy.datetime_data is deprecated and will be removed in SciPy 2.0.0, use numpy.datetime_data instead\n", " \n", " deg2rad(...)\n", " scipy.deg2rad is deprecated and will be removed in SciPy 2.0.0, use numpy.deg2rad instead\n", " \n", " degrees(...)\n", " scipy.degrees is deprecated and will be removed in SciPy 2.0.0, use numpy.degrees instead\n", " \n", " delete(arr, obj, axis=None)\n", " scipy.delete is deprecated and will be removed in SciPy 2.0.0, use numpy.delete instead\n", " \n", " deprecate(*args, **kwargs)\n", " scipy.deprecate is deprecated and will be removed in SciPy 2.0.0, use numpy.deprecate instead\n", " \n", " deprecate_with_doc lambda msg\n", " scipy.deprecate_with_doc is deprecated and will be removed in SciPy 2.0.0, use numpy.deprecate_with_doc instead\n", " \n", " diag(v, k=0)\n", " scipy.diag is deprecated and will be removed in SciPy 2.0.0, use numpy.diag instead\n", " \n", " diag_indices(n, ndim=2)\n", " scipy.diag_indices is deprecated and will be removed in SciPy 2.0.0, use numpy.diag_indices instead\n", " \n", " diag_indices_from(arr)\n", " scipy.diag_indices_from is deprecated and will be removed in SciPy 2.0.0, use numpy.diag_indices_from instead\n", " \n", " diagflat(v, k=0)\n", " scipy.diagflat is deprecated and will be removed in SciPy 2.0.0, use numpy.diagflat instead\n", " \n", " diagonal(a, offset=0, axis1=0, axis2=1)\n", " scipy.diagonal is deprecated and will be removed in SciPy 2.0.0, use numpy.diagonal instead\n", " \n", " diff(a, n=1, axis=-1, prepend=, append=)\n", " scipy.diff is deprecated and will be removed in SciPy 2.0.0, use numpy.diff instead\n", " \n", " digitize(x, bins, right=False)\n", " scipy.digitize is deprecated and will be removed in SciPy 2.0.0, use numpy.digitize instead\n", " \n", " disp(mesg, device=None, linefeed=True)\n", " scipy.disp is deprecated and will be removed in SciPy 2.0.0, use numpy.disp instead\n", " \n", " divide = true_divide(...)\n", " scipy.divide is deprecated and will be removed in SciPy 2.0.0, use numpy.divide instead\n", " \n", " divmod(...)\n", " scipy.divmod is deprecated and will be removed in SciPy 2.0.0, use numpy.divmod instead\n", " \n", " dot(...)\n", " scipy.dot is deprecated and will be removed in SciPy 2.0.0, use numpy.dot instead\n", " \n", " dsplit(ary, indices_or_sections)\n", " scipy.dsplit is deprecated and will be removed in SciPy 2.0.0, use numpy.dsplit instead\n", " \n", " dstack(tup)\n", " scipy.dstack is deprecated and will be removed in SciPy 2.0.0, use numpy.dstack instead\n", " \n", " ediff1d(ary, to_end=None, to_begin=None)\n", " scipy.ediff1d is deprecated and will be removed in SciPy 2.0.0, use numpy.ediff1d instead\n", " \n", " einsum(*operands, out=None, optimize=False, **kwargs)\n", " scipy.einsum is deprecated and will be removed in SciPy 2.0.0, use numpy.einsum instead\n", " \n", " einsum_path(*operands, optimize='greedy', einsum_call=False)\n", " scipy.einsum_path is deprecated and will be removed in SciPy 2.0.0, use numpy.einsum_path instead\n", " \n", " empty(...)\n", " scipy.empty is deprecated and will be removed in SciPy 2.0.0, use numpy.empty instead\n", " \n", " empty_like(...)\n", " scipy.empty_like is deprecated and will be removed in SciPy 2.0.0, use numpy.empty_like instead\n", " \n", " equal(...)\n", " scipy.equal is deprecated and will be removed in SciPy 2.0.0, use numpy.equal instead\n", " \n", " exp(...)\n", " scipy.exp is deprecated and will be removed in SciPy 2.0.0, use numpy.exp instead\n", " \n", " exp2(...)\n", " scipy.exp2 is deprecated and will be removed in SciPy 2.0.0, use numpy.exp2 instead\n", " \n", " expand_dims(a, axis)\n", " scipy.expand_dims is deprecated and will be removed in SciPy 2.0.0, use numpy.expand_dims instead\n", " \n", " expm1(...)\n", " scipy.expm1 is deprecated and will be removed in SciPy 2.0.0, use numpy.expm1 instead\n", " \n", " extract(condition, arr)\n", " scipy.extract is deprecated and will be removed in SciPy 2.0.0, use numpy.extract instead\n", " \n", " eye(N, M=None, k=0, dtype=, order='C')\n", " scipy.eye is deprecated and will be removed in SciPy 2.0.0, use numpy.eye instead\n", " \n", " fabs(...)\n", " scipy.fabs is deprecated and will be removed in SciPy 2.0.0, use numpy.fabs instead\n", " \n", " fastCopyAndTranspose = _fastCopyAndTranspose(...)\n", " scipy.fastCopyAndTranspose is deprecated and will be removed in SciPy 2.0.0, use numpy.fastCopyAndTranspose instead\n", " \n", " fill_diagonal(a, val, wrap=False)\n", " scipy.fill_diagonal is deprecated and will be removed in SciPy 2.0.0, use numpy.fill_diagonal instead\n", " \n", " find_common_type(array_types, scalar_types)\n", " scipy.find_common_type is deprecated and will be removed in SciPy 2.0.0, use numpy.find_common_type instead\n", " \n", " fix(x, out=None)\n", " scipy.fix is deprecated and will be removed in SciPy 2.0.0, use numpy.fix instead\n", " \n", " flatnonzero(a)\n", " scipy.flatnonzero is deprecated and will be removed in SciPy 2.0.0, use numpy.flatnonzero instead\n", " \n", " flip(m, axis=None)\n", " scipy.flip is deprecated and will be removed in SciPy 2.0.0, use numpy.flip instead\n", " \n", " fliplr(m)\n", " scipy.fliplr is deprecated and will be removed in SciPy 2.0.0, use numpy.fliplr instead\n", " \n", " flipud(m)\n", " scipy.flipud is deprecated and will be removed in SciPy 2.0.0, use numpy.flipud instead\n", " \n", " float_power(...)\n", " scipy.float_power is deprecated and will be removed in SciPy 2.0.0, use numpy.float_power instead\n", " \n", " floor(...)\n", " scipy.floor is deprecated and will be removed in SciPy 2.0.0, use numpy.floor instead\n", " \n", " floor_divide(...)\n", " scipy.floor_divide is deprecated and will be removed in SciPy 2.0.0, use numpy.floor_divide instead\n", " \n", " fmax(...)\n", " scipy.fmax is deprecated and will be removed in SciPy 2.0.0, use numpy.fmax instead\n", " \n", " fmin(...)\n", " scipy.fmin is deprecated and will be removed in SciPy 2.0.0, use numpy.fmin instead\n", " \n", " fmod(...)\n", " scipy.fmod is deprecated and will be removed in SciPy 2.0.0, use numpy.fmod instead\n", " \n", " format_float_positional(x, precision=None, unique=True, fractional=True, trim='k', sign=False, pad_left=None, pad_right=None)\n", " scipy.format_float_positional is deprecated and will be removed in SciPy 2.0.0, use numpy.format_float_positional instead\n", " \n", " format_float_scientific(x, precision=None, unique=True, trim='k', sign=False, pad_left=None, exp_digits=None)\n", " scipy.format_float_scientific is deprecated and will be removed in SciPy 2.0.0, use numpy.format_float_scientific instead\n", " \n", " frexp(...)\n", " scipy.frexp is deprecated and will be removed in SciPy 2.0.0, use numpy.frexp instead\n", " \n", " frombuffer(...)\n", " scipy.frombuffer is deprecated and will be removed in SciPy 2.0.0, use numpy.frombuffer instead\n", " \n", " fromfile(...)\n", " scipy.fromfile is deprecated and will be removed in SciPy 2.0.0, use numpy.fromfile instead\n", " \n", " fromfunction(function, shape, *, dtype=, **kwargs)\n", " scipy.fromfunction is deprecated and will be removed in SciPy 2.0.0, use numpy.fromfunction instead\n", " \n", " fromiter(...)\n", " scipy.fromiter is deprecated and will be removed in SciPy 2.0.0, use numpy.fromiter instead\n", " \n", " frompyfunc(...)\n", " scipy.frompyfunc is deprecated and will be removed in SciPy 2.0.0, use numpy.frompyfunc instead\n", " \n", " fromregex(file, regexp, dtype, encoding=None)\n", " scipy.fromregex is deprecated and will be removed in SciPy 2.0.0, use numpy.fromregex instead\n", " \n", " fromstring(...)\n", " scipy.fromstring is deprecated and will be removed in SciPy 2.0.0, use numpy.fromstring instead\n", " \n", " full(shape, fill_value, dtype=None, order='C')\n", " scipy.full is deprecated and will be removed in SciPy 2.0.0, use numpy.full instead\n", " \n", " full_like(a, fill_value, dtype=None, order='K', subok=True, shape=None)\n", " scipy.full_like is deprecated and will be removed in SciPy 2.0.0, use numpy.full_like instead\n", " \n", " fv(rate, nper, pmt, pv, when='end')\n", " scipy.fv is deprecated and will be removed in SciPy 2.0.0, use numpy.fv instead\n", " \n", " gcd(...)\n", " scipy.gcd is deprecated and will be removed in SciPy 2.0.0, use numpy.gcd instead\n", " \n", " genfromtxt(fname, dtype=, comments='#', delimiter=None, skip_header=0, skip_footer=0, converters=None, missing_values=None, filling_values=None, usecols=None, names=None, excludelist=None, deletechars=\" !#$%&'()*+,-./:;<=>?@[\\\\]^{|}~\", replace_space='_', autostrip=False, case_sensitive=True, defaultfmt='f%i', unpack=None, usemask=False, loose=True, invalid_raise=True, max_rows=None, encoding='bytes')\n", " scipy.genfromtxt is deprecated and will be removed in SciPy 2.0.0, use numpy.genfromtxt instead\n", " \n", " geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0)\n", " scipy.geomspace is deprecated and will be removed in SciPy 2.0.0, use numpy.geomspace instead\n", " \n", " get_array_wrap(*args)\n", " scipy.get_array_wrap is deprecated and will be removed in SciPy 2.0.0, use numpy.get_array_wrap instead\n", " \n", " get_include()\n", " scipy.get_include is deprecated and will be removed in SciPy 2.0.0, use numpy.get_include instead\n", " \n", " get_printoptions()\n", " scipy.get_printoptions is deprecated and will be removed in SciPy 2.0.0, use numpy.get_printoptions instead\n", " \n", " getbufsize()\n", " scipy.getbufsize is deprecated and will be removed in SciPy 2.0.0, use numpy.getbufsize instead\n", " \n", " geterr()\n", " scipy.geterr is deprecated and will be removed in SciPy 2.0.0, use numpy.geterr instead\n", " \n", " geterrcall()\n", " scipy.geterrcall is deprecated and will be removed in SciPy 2.0.0, use numpy.geterrcall instead\n", " \n", " geterrobj(...)\n", " scipy.geterrobj is deprecated and will be removed in SciPy 2.0.0, use numpy.geterrobj instead\n", " \n", " gradient(f, *varargs, axis=None, edge_order=1)\n", " scipy.gradient is deprecated and will be removed in SciPy 2.0.0, use numpy.gradient instead\n", " \n", " greater(...)\n", " scipy.greater is deprecated and will be removed in SciPy 2.0.0, use numpy.greater instead\n", " \n", " greater_equal(...)\n", " scipy.greater_equal is deprecated and will be removed in SciPy 2.0.0, use numpy.greater_equal instead\n", " \n", " hamming(M)\n", " scipy.hamming is deprecated and will be removed in SciPy 2.0.0, use numpy.hamming instead\n", " \n", " hanning(M)\n", " scipy.hanning is deprecated and will be removed in SciPy 2.0.0, use numpy.hanning instead\n", " \n", " heaviside(...)\n", " scipy.heaviside is deprecated and will be removed in SciPy 2.0.0, use numpy.heaviside instead\n", " \n", " histogram(a, bins=10, range=None, normed=None, weights=None, density=None)\n", " scipy.histogram is deprecated and will be removed in SciPy 2.0.0, use numpy.histogram instead\n", " \n", " histogram2d(x, y, bins=10, range=None, normed=None, weights=None, density=None)\n", " scipy.histogram2d is deprecated and will be removed in SciPy 2.0.0, use numpy.histogram2d instead\n", " \n", " histogram_bin_edges(a, bins=10, range=None, weights=None)\n", " scipy.histogram_bin_edges is deprecated and will be removed in SciPy 2.0.0, use numpy.histogram_bin_edges instead\n", " \n", " histogramdd(sample, bins=10, range=None, normed=None, weights=None, density=None)\n", " scipy.histogramdd is deprecated and will be removed in SciPy 2.0.0, use numpy.histogramdd instead\n", " \n", " hsplit(ary, indices_or_sections)\n", " scipy.hsplit is deprecated and will be removed in SciPy 2.0.0, use numpy.hsplit instead\n", " \n", " hstack(tup)\n", " scipy.hstack is deprecated and will be removed in SciPy 2.0.0, use numpy.hstack instead\n", " \n", " hypot(...)\n", " scipy.hypot is deprecated and will be removed in SciPy 2.0.0, use numpy.hypot instead\n", " \n", " i0(x)\n", " scipy.i0 is deprecated and will be removed in SciPy 2.0.0, use numpy.i0 instead\n", " \n", " identity(n, dtype=None)\n", " scipy.identity is deprecated and will be removed in SciPy 2.0.0, use numpy.identity instead\n", " \n", " ifft(a, n=None, axis=-1, norm=None)\n", " scipy.ifft is deprecated and will be removed in SciPy 2.0.0, use scipy.fft.ifft instead\n", " \n", " imag(val)\n", " scipy.imag is deprecated and will be removed in SciPy 2.0.0, use numpy.imag instead\n", " \n", " in1d(ar1, ar2, assume_unique=False, invert=False)\n", " scipy.in1d is deprecated and will be removed in SciPy 2.0.0, use numpy.in1d instead\n", " \n", " indices(dimensions, dtype=, sparse=False)\n", " scipy.indices is deprecated and will be removed in SciPy 2.0.0, use numpy.indices instead\n", " \n", " info(object=None, maxwidth=76, output=, toplevel='numpy')\n", " scipy.info is deprecated and will be removed in SciPy 2.0.0, use numpy.info instead\n", " \n", " inner(...)\n", " scipy.inner is deprecated and will be removed in SciPy 2.0.0, use numpy.inner instead\n", " \n", " insert(arr, obj, values, axis=None)\n", " scipy.insert is deprecated and will be removed in SciPy 2.0.0, use numpy.insert instead\n", " \n", " interp(x, xp, fp, left=None, right=None, period=None)\n", " scipy.interp is deprecated and will be removed in SciPy 2.0.0, use numpy.interp instead\n", " \n", " intersect1d(ar1, ar2, assume_unique=False, return_indices=False)\n", " scipy.intersect1d is deprecated and will be removed in SciPy 2.0.0, use numpy.intersect1d instead\n", " \n", " invert(...)\n", " scipy.invert is deprecated and will be removed in SciPy 2.0.0, use numpy.invert instead\n", " \n", " ipmt(rate, per, nper, pv, fv=0, when='end')\n", " scipy.ipmt is deprecated and will be removed in SciPy 2.0.0, use numpy.ipmt instead\n", " \n", " irr(values)\n", " scipy.irr is deprecated and will be removed in SciPy 2.0.0, use numpy.irr instead\n", " \n", " is_busday(...)\n", " scipy.is_busday is deprecated and will be removed in SciPy 2.0.0, use numpy.is_busday instead\n", " \n", " isclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)\n", " scipy.isclose is deprecated and will be removed in SciPy 2.0.0, use numpy.isclose instead\n", " \n", " iscomplex(x)\n", " scipy.iscomplex is deprecated and will be removed in SciPy 2.0.0, use numpy.iscomplex instead\n", " \n", " iscomplexobj(x)\n", " scipy.iscomplexobj is deprecated and will be removed in SciPy 2.0.0, use numpy.iscomplexobj instead\n", " \n", " isfinite(...)\n", " scipy.isfinite is deprecated and will be removed in SciPy 2.0.0, use numpy.isfinite instead\n", " \n", " isfortran(a)\n", " scipy.isfortran is deprecated and will be removed in SciPy 2.0.0, use numpy.isfortran instead\n", " \n", " isin(element, test_elements, assume_unique=False, invert=False)\n", " scipy.isin is deprecated and will be removed in SciPy 2.0.0, use numpy.isin instead\n", " \n", " isinf(...)\n", " scipy.isinf is deprecated and will be removed in SciPy 2.0.0, use numpy.isinf instead\n", " \n", " isnan(...)\n", " scipy.isnan is deprecated and will be removed in SciPy 2.0.0, use numpy.isnan instead\n", " \n", " isnat(...)\n", " scipy.isnat is deprecated and will be removed in SciPy 2.0.0, use numpy.isnat instead\n", " \n", " isneginf(x, out=None)\n", " scipy.isneginf is deprecated and will be removed in SciPy 2.0.0, use numpy.isneginf instead\n", " \n", " isposinf(x, out=None)\n", " scipy.isposinf is deprecated and will be removed in SciPy 2.0.0, use numpy.isposinf instead\n", " \n", " isreal(x)\n", " scipy.isreal is deprecated and will be removed in SciPy 2.0.0, use numpy.isreal instead\n", " \n", " isrealobj(x)\n", " scipy.isrealobj is deprecated and will be removed in SciPy 2.0.0, use numpy.isrealobj instead\n", " \n", " isscalar(element)\n", " scipy.isscalar is deprecated and will be removed in SciPy 2.0.0, use numpy.isscalar instead\n", " \n", " issctype(rep)\n", " scipy.issctype is deprecated and will be removed in SciPy 2.0.0, use numpy.issctype instead\n", " \n", " issubclass_(arg1, arg2)\n", " scipy.issubclass_ is deprecated and will be removed in SciPy 2.0.0, use numpy.issubclass_ instead\n", " \n", " issubdtype(arg1, arg2)\n", " scipy.issubdtype is deprecated and will be removed in SciPy 2.0.0, use numpy.issubdtype instead\n", " \n", " issubsctype(arg1, arg2)\n", " scipy.issubsctype is deprecated and will be removed in SciPy 2.0.0, use numpy.issubsctype instead\n", " \n", " iterable(y)\n", " scipy.iterable is deprecated and will be removed in SciPy 2.0.0, use numpy.iterable instead\n", " \n", " ix_(*args)\n", " scipy.ix_ is deprecated and will be removed in SciPy 2.0.0, use numpy.ix_ instead\n", " \n", " kaiser(M, beta)\n", " scipy.kaiser is deprecated and will be removed in SciPy 2.0.0, use numpy.kaiser instead\n", " \n", " kron(a, b)\n", " scipy.kron is deprecated and will be removed in SciPy 2.0.0, use numpy.kron instead\n", " \n", " lcm(...)\n", " scipy.lcm is deprecated and will be removed in SciPy 2.0.0, use numpy.lcm instead\n", " \n", " ldexp(...)\n", " scipy.ldexp is deprecated and will be removed in SciPy 2.0.0, use numpy.ldexp instead\n", " \n", " left_shift(...)\n", " scipy.left_shift is deprecated and will be removed in SciPy 2.0.0, use numpy.left_shift instead\n", " \n", " less(...)\n", " scipy.less is deprecated and will be removed in SciPy 2.0.0, use numpy.less instead\n", " \n", " less_equal(...)\n", " scipy.less_equal is deprecated and will be removed in SciPy 2.0.0, use numpy.less_equal instead\n", " \n", " lexsort(...)\n", " scipy.lexsort is deprecated and will be removed in SciPy 2.0.0, use numpy.lexsort instead\n", " \n", " linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)\n", " scipy.linspace is deprecated and will be removed in SciPy 2.0.0, use numpy.linspace instead\n", " \n", " load(file, mmap_mode=None, allow_pickle=False, fix_imports=True, encoding='ASCII')\n", " scipy.load is deprecated and will be removed in SciPy 2.0.0, use numpy.load instead\n", " \n", " loads(*args, **kwargs)\n", " scipy.loads is deprecated and will be removed in SciPy 2.0.0, use numpy.loads instead\n", " \n", " loadtxt(fname, dtype=, comments='#', delimiter=None, converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0, encoding='bytes', max_rows=None)\n", " scipy.loadtxt is deprecated and will be removed in SciPy 2.0.0, use numpy.loadtxt instead\n", " \n", " log(x)\n", " scipy.log is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.log instead\n", " \n", " log10(x)\n", " scipy.log10 is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.log10 instead\n", " \n", " log1p(...)\n", " scipy.log1p is deprecated and will be removed in SciPy 2.0.0, use numpy.log1p instead\n", " \n", " log2(x)\n", " scipy.log2 is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.log2 instead\n", " \n", " logaddexp(...)\n", " scipy.logaddexp is deprecated and will be removed in SciPy 2.0.0, use numpy.logaddexp instead\n", " \n", " logaddexp2(...)\n", " scipy.logaddexp2 is deprecated and will be removed in SciPy 2.0.0, use numpy.logaddexp2 instead\n", " \n", " logical_and(...)\n", " scipy.logical_and is deprecated and will be removed in SciPy 2.0.0, use numpy.logical_and instead\n", " \n", " logical_not(...)\n", " scipy.logical_not is deprecated and will be removed in SciPy 2.0.0, use numpy.logical_not instead\n", " \n", " logical_or(...)\n", " scipy.logical_or is deprecated and will be removed in SciPy 2.0.0, use numpy.logical_or instead\n", " \n", " logical_xor(...)\n", " scipy.logical_xor is deprecated and will be removed in SciPy 2.0.0, use numpy.logical_xor instead\n", " \n", " logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0)\n", " scipy.logspace is deprecated and will be removed in SciPy 2.0.0, use numpy.logspace instead\n", " \n", " lookfor(what, module=None, import_modules=True, regenerate=False, output=None)\n", " scipy.lookfor is deprecated and will be removed in SciPy 2.0.0, use numpy.lookfor instead\n", " \n", " mafromtxt(fname, **kwargs)\n", " scipy.mafromtxt is deprecated and will be removed in SciPy 2.0.0, use numpy.mafromtxt instead\n", " \n", " mask_indices(n, mask_func, k=0)\n", " scipy.mask_indices is deprecated and will be removed in SciPy 2.0.0, use numpy.mask_indices instead\n", " \n", " mat = asmatrix(data, dtype=None)\n", " scipy.mat is deprecated and will be removed in SciPy 2.0.0, use numpy.mat instead\n", " \n", " matmul(...)\n", " scipy.matmul is deprecated and will be removed in SciPy 2.0.0, use numpy.matmul instead\n", " \n", " maximum(...)\n", " scipy.maximum is deprecated and will be removed in SciPy 2.0.0, use numpy.maximum instead\n", " \n", " maximum_sctype(t)\n", " scipy.maximum_sctype is deprecated and will be removed in SciPy 2.0.0, use numpy.maximum_sctype instead\n", " \n", " may_share_memory(...)\n", " scipy.may_share_memory is deprecated and will be removed in SciPy 2.0.0, use numpy.may_share_memory instead\n", " \n", " mean(a, axis=None, dtype=None, out=None, keepdims=)\n", " scipy.mean is deprecated and will be removed in SciPy 2.0.0, use numpy.mean instead\n", " \n", " median(a, axis=None, out=None, overwrite_input=False, keepdims=False)\n", " scipy.median is deprecated and will be removed in SciPy 2.0.0, use numpy.median instead\n", " \n", " meshgrid(*xi, copy=True, sparse=False, indexing='xy')\n", " scipy.meshgrid is deprecated and will be removed in SciPy 2.0.0, use numpy.meshgrid instead\n", " \n", " min_scalar_type(...)\n", " scipy.min_scalar_type is deprecated and will be removed in SciPy 2.0.0, use numpy.min_scalar_type instead\n", " \n", " minimum(...)\n", " scipy.minimum is deprecated and will be removed in SciPy 2.0.0, use numpy.minimum instead\n", " \n", " mintypecode(typechars, typeset='GDFgdf', default='d')\n", " scipy.mintypecode is deprecated and will be removed in SciPy 2.0.0, use numpy.mintypecode instead\n", " \n", " mirr(values, finance_rate, reinvest_rate)\n", " scipy.mirr is deprecated and will be removed in SciPy 2.0.0, use numpy.mirr instead\n", " \n", " mod = remainder(...)\n", " scipy.mod is deprecated and will be removed in SciPy 2.0.0, use numpy.mod instead\n", " \n", " modf(...)\n", " scipy.modf is deprecated and will be removed in SciPy 2.0.0, use numpy.modf instead\n", " \n", " moveaxis(a, source, destination)\n", " scipy.moveaxis is deprecated and will be removed in SciPy 2.0.0, use numpy.moveaxis instead\n", " \n", " msort(a)\n", " scipy.msort is deprecated and will be removed in SciPy 2.0.0, use numpy.msort instead\n", " \n", " multiply(...)\n", " scipy.multiply is deprecated and will be removed in SciPy 2.0.0, use numpy.multiply instead\n", " \n", " nan_to_num(x, copy=True, nan=0.0, posinf=None, neginf=None)\n", " scipy.nan_to_num is deprecated and will be removed in SciPy 2.0.0, use numpy.nan_to_num instead\n", " \n", " nanargmax(a, axis=None)\n", " scipy.nanargmax is deprecated and will be removed in SciPy 2.0.0, use numpy.nanargmax instead\n", " \n", " nanargmin(a, axis=None)\n", " scipy.nanargmin is deprecated and will be removed in SciPy 2.0.0, use numpy.nanargmin instead\n", " \n", " nancumprod(a, axis=None, dtype=None, out=None)\n", " scipy.nancumprod is deprecated and will be removed in SciPy 2.0.0, use numpy.nancumprod instead\n", " \n", " nancumsum(a, axis=None, dtype=None, out=None)\n", " scipy.nancumsum is deprecated and will be removed in SciPy 2.0.0, use numpy.nancumsum instead\n", " \n", " nanmax(a, axis=None, out=None, keepdims=)\n", " scipy.nanmax is deprecated and will be removed in SciPy 2.0.0, use numpy.nanmax instead\n", " \n", " nanmean(a, axis=None, dtype=None, out=None, keepdims=)\n", " scipy.nanmean is deprecated and will be removed in SciPy 2.0.0, use numpy.nanmean instead\n", " \n", " nanmedian(a, axis=None, out=None, overwrite_input=False, keepdims=)\n", " scipy.nanmedian is deprecated and will be removed in SciPy 2.0.0, use numpy.nanmedian instead\n", " \n", " nanmin(a, axis=None, out=None, keepdims=)\n", " scipy.nanmin is deprecated and will be removed in SciPy 2.0.0, use numpy.nanmin instead\n", " \n", " nanpercentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=)\n", " scipy.nanpercentile is deprecated and will be removed in SciPy 2.0.0, use numpy.nanpercentile instead\n", " \n", " nanprod(a, axis=None, dtype=None, out=None, keepdims=)\n", " scipy.nanprod is deprecated and will be removed in SciPy 2.0.0, use numpy.nanprod instead\n", " \n", " nanquantile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=)\n", " scipy.nanquantile is deprecated and will be removed in SciPy 2.0.0, use numpy.nanquantile instead\n", " \n", " nanstd(a, axis=None, dtype=None, out=None, ddof=0, keepdims=)\n", " scipy.nanstd is deprecated and will be removed in SciPy 2.0.0, use numpy.nanstd instead\n", " \n", " nansum(a, axis=None, dtype=None, out=None, keepdims=)\n", " scipy.nansum is deprecated and will be removed in SciPy 2.0.0, use numpy.nansum instead\n", " \n", " nanvar(a, axis=None, dtype=None, out=None, ddof=0, keepdims=)\n", " scipy.nanvar is deprecated and will be removed in SciPy 2.0.0, use numpy.nanvar instead\n", " \n", " ndfromtxt(fname, **kwargs)\n", " scipy.ndfromtxt is deprecated and will be removed in SciPy 2.0.0, use numpy.ndfromtxt instead\n", " \n", " ndim(a)\n", " scipy.ndim is deprecated and will be removed in SciPy 2.0.0, use numpy.ndim instead\n", " \n", " negative(...)\n", " scipy.negative is deprecated and will be removed in SciPy 2.0.0, use numpy.negative instead\n", " \n", " nested_iters(...)\n", " scipy.nested_iters is deprecated and will be removed in SciPy 2.0.0, use numpy.nested_iters instead\n", " \n", " nextafter(...)\n", " scipy.nextafter is deprecated and will be removed in SciPy 2.0.0, use numpy.nextafter instead\n", " \n", " nonzero(a)\n", " scipy.nonzero is deprecated and will be removed in SciPy 2.0.0, use numpy.nonzero instead\n", " \n", " not_equal(...)\n", " scipy.not_equal is deprecated and will be removed in SciPy 2.0.0, use numpy.not_equal instead\n", " \n", " nper(rate, pmt, pv, fv=0, when='end')\n", " scipy.nper is deprecated and will be removed in SciPy 2.0.0, use numpy.nper instead\n", " \n", " npv(rate, values)\n", " scipy.npv is deprecated and will be removed in SciPy 2.0.0, use numpy.npv instead\n", " \n", " obj2sctype(rep, default=None)\n", " scipy.obj2sctype is deprecated and will be removed in SciPy 2.0.0, use numpy.obj2sctype instead\n", " \n", " ones(shape, dtype=None, order='C')\n", " scipy.ones is deprecated and will be removed in SciPy 2.0.0, use numpy.ones instead\n", " \n", " ones_like(a, dtype=None, order='K', subok=True, shape=None)\n", " scipy.ones_like is deprecated and will be removed in SciPy 2.0.0, use numpy.ones_like instead\n", " \n", " outer(a, b, out=None)\n", " scipy.outer is deprecated and will be removed in SciPy 2.0.0, use numpy.outer instead\n", " \n", " packbits(...)\n", " scipy.packbits is deprecated and will be removed in SciPy 2.0.0, use numpy.packbits instead\n", " \n", " pad(array, pad_width, mode='constant', **kwargs)\n", " scipy.pad is deprecated and will be removed in SciPy 2.0.0, use numpy.pad instead\n", " \n", " partition(a, kth, axis=-1, kind='introselect', order=None)\n", " scipy.partition is deprecated and will be removed in SciPy 2.0.0, use numpy.partition instead\n", " \n", " percentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=False)\n", " scipy.percentile is deprecated and will be removed in SciPy 2.0.0, use numpy.percentile instead\n", " \n", " piecewise(x, condlist, funclist, *args, **kw)\n", " scipy.piecewise is deprecated and will be removed in SciPy 2.0.0, use numpy.piecewise instead\n", " \n", " place(arr, mask, vals)\n", " scipy.place is deprecated and will be removed in SciPy 2.0.0, use numpy.place instead\n", " \n", " pmt(rate, nper, pv, fv=0, when='end')\n", " scipy.pmt is deprecated and will be removed in SciPy 2.0.0, use numpy.pmt instead\n", " \n", " poly(seq_of_zeros)\n", " scipy.poly is deprecated and will be removed in SciPy 2.0.0, use numpy.poly instead\n", " \n", " polyadd(a1, a2)\n", " scipy.polyadd is deprecated and will be removed in SciPy 2.0.0, use numpy.polyadd instead\n", " \n", " polyder(p, m=1)\n", " scipy.polyder is deprecated and will be removed in SciPy 2.0.0, use numpy.polyder instead\n", " \n", " polydiv(u, v)\n", " scipy.polydiv is deprecated and will be removed in SciPy 2.0.0, use numpy.polydiv instead\n", " \n", " polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False)\n", " scipy.polyfit is deprecated and will be removed in SciPy 2.0.0, use numpy.polyfit instead\n", " \n", " polyint(p, m=1, k=None)\n", " scipy.polyint is deprecated and will be removed in SciPy 2.0.0, use numpy.polyint instead\n", " \n", " polymul(a1, a2)\n", " scipy.polymul is deprecated and will be removed in SciPy 2.0.0, use numpy.polymul instead\n", " \n", " polysub(a1, a2)\n", " scipy.polysub is deprecated and will be removed in SciPy 2.0.0, use numpy.polysub instead\n", " \n", " polyval(p, x)\n", " scipy.polyval is deprecated and will be removed in SciPy 2.0.0, use numpy.polyval instead\n", " \n", " positive(...)\n", " scipy.positive is deprecated and will be removed in SciPy 2.0.0, use numpy.positive instead\n", " \n", " power(x, p)\n", " scipy.power is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.power instead\n", " \n", " ppmt(rate, per, nper, pv, fv=0, when='end')\n", " scipy.ppmt is deprecated and will be removed in SciPy 2.0.0, use numpy.ppmt instead\n", " \n", " printoptions(*args, **kwargs)\n", " scipy.printoptions is deprecated and will be removed in SciPy 2.0.0, use numpy.printoptions instead\n", " \n", " prod(a, axis=None, dtype=None, out=None, keepdims=, initial=, where=)\n", " scipy.prod is deprecated and will be removed in SciPy 2.0.0, use numpy.prod instead\n", " \n", " product(*args, **kwargs)\n", " scipy.product is deprecated and will be removed in SciPy 2.0.0, use numpy.product instead\n", " \n", " promote_types(...)\n", " scipy.promote_types is deprecated and will be removed in SciPy 2.0.0, use numpy.promote_types instead\n", " \n", " ptp(a, axis=None, out=None, keepdims=)\n", " scipy.ptp is deprecated and will be removed in SciPy 2.0.0, use numpy.ptp instead\n", " \n", " put(a, ind, v, mode='raise')\n", " scipy.put is deprecated and will be removed in SciPy 2.0.0, use numpy.put instead\n", " \n", " put_along_axis(arr, indices, values, axis)\n", " scipy.put_along_axis is deprecated and will be removed in SciPy 2.0.0, use numpy.put_along_axis instead\n", " \n", " putmask(...)\n", " scipy.putmask is deprecated and will be removed in SciPy 2.0.0, use numpy.putmask instead\n", " \n", " pv(rate, nper, pmt, fv=0, when='end')\n", " scipy.pv is deprecated and will be removed in SciPy 2.0.0, use numpy.pv instead\n", " \n", " quantile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear', keepdims=False)\n", " scipy.quantile is deprecated and will be removed in SciPy 2.0.0, use numpy.quantile instead\n", " \n", " rad2deg(...)\n", " scipy.rad2deg is deprecated and will be removed in SciPy 2.0.0, use numpy.rad2deg instead\n", " \n", " radians(...)\n", " scipy.radians is deprecated and will be removed in SciPy 2.0.0, use numpy.radians instead\n", " \n", " rand(...)\n", " scipy.rand is deprecated and will be removed in SciPy 2.0.0, use numpy.random.rand instead\n", " \n", " randn(...)\n", " scipy.randn is deprecated and will be removed in SciPy 2.0.0, use numpy.random.randn instead\n", " \n", " rate(nper, pmt, pv, fv, when='end', guess=None, tol=None, maxiter=100)\n", " scipy.rate is deprecated and will be removed in SciPy 2.0.0, use numpy.rate instead\n", " \n", " ravel(a, order='C')\n", " scipy.ravel is deprecated and will be removed in SciPy 2.0.0, use numpy.ravel instead\n", " \n", " ravel_multi_index(...)\n", " scipy.ravel_multi_index is deprecated and will be removed in SciPy 2.0.0, use numpy.ravel_multi_index instead\n", " \n", " real(val)\n", " scipy.real is deprecated and will be removed in SciPy 2.0.0, use numpy.real instead\n", " \n", " real_if_close(a, tol=100)\n", " scipy.real_if_close is deprecated and will be removed in SciPy 2.0.0, use numpy.real_if_close instead\n", " \n", " recfromcsv(fname, **kwargs)\n", " scipy.recfromcsv is deprecated and will be removed in SciPy 2.0.0, use numpy.recfromcsv instead\n", " \n", " recfromtxt(fname, **kwargs)\n", " scipy.recfromtxt is deprecated and will be removed in SciPy 2.0.0, use numpy.recfromtxt instead\n", " \n", " reciprocal(...)\n", " scipy.reciprocal is deprecated and will be removed in SciPy 2.0.0, use numpy.reciprocal instead\n", " \n", " remainder(...)\n", " scipy.remainder is deprecated and will be removed in SciPy 2.0.0, use numpy.remainder instead\n", " \n", " repeat(a, repeats, axis=None)\n", " scipy.repeat is deprecated and will be removed in SciPy 2.0.0, use numpy.repeat instead\n", " \n", " require(a, dtype=None, requirements=None)\n", " scipy.require is deprecated and will be removed in SciPy 2.0.0, use numpy.require instead\n", " \n", " reshape(a, newshape, order='C')\n", " scipy.reshape is deprecated and will be removed in SciPy 2.0.0, use numpy.reshape instead\n", " \n", " resize(a, new_shape)\n", " scipy.resize is deprecated and will be removed in SciPy 2.0.0, use numpy.resize instead\n", " \n", " result_type(...)\n", " scipy.result_type is deprecated and will be removed in SciPy 2.0.0, use numpy.result_type instead\n", " \n", " right_shift(...)\n", " scipy.right_shift is deprecated and will be removed in SciPy 2.0.0, use numpy.right_shift instead\n", " \n", " rint(...)\n", " scipy.rint is deprecated and will be removed in SciPy 2.0.0, use numpy.rint instead\n", " \n", " roll(a, shift, axis=None)\n", " scipy.roll is deprecated and will be removed in SciPy 2.0.0, use numpy.roll instead\n", " \n", " rollaxis(a, axis, start=0)\n", " scipy.rollaxis is deprecated and will be removed in SciPy 2.0.0, use numpy.rollaxis instead\n", " \n", " roots(p)\n", " scipy.roots is deprecated and will be removed in SciPy 2.0.0, use numpy.roots instead\n", " \n", " rot90(m, k=1, axes=(0, 1))\n", " scipy.rot90 is deprecated and will be removed in SciPy 2.0.0, use numpy.rot90 instead\n", " \n", " round_(a, decimals=0, out=None)\n", " scipy.round_ is deprecated and will be removed in SciPy 2.0.0, use numpy.round_ instead\n", " \n", " row_stack = vstack(tup)\n", " scipy.row_stack is deprecated and will be removed in SciPy 2.0.0, use numpy.row_stack instead\n", " \n", " safe_eval(source)\n", " scipy.safe_eval is deprecated and will be removed in SciPy 2.0.0, use numpy.safe_eval instead\n", " \n", " save(file, arr, allow_pickle=True, fix_imports=True)\n", " scipy.save is deprecated and will be removed in SciPy 2.0.0, use numpy.save instead\n", " \n", " savetxt(fname, X, fmt='%.18e', delimiter=' ', newline='\\n', header='', footer='', comments='# ', encoding=None)\n", " scipy.savetxt is deprecated and will be removed in SciPy 2.0.0, use numpy.savetxt instead\n", " \n", " savez(file, *args, **kwds)\n", " scipy.savez is deprecated and will be removed in SciPy 2.0.0, use numpy.savez instead\n", " \n", " savez_compressed(file, *args, **kwds)\n", " scipy.savez_compressed is deprecated and will be removed in SciPy 2.0.0, use numpy.savez_compressed instead\n", " \n", " sctype2char(sctype)\n", " scipy.sctype2char is deprecated and will be removed in SciPy 2.0.0, use numpy.sctype2char instead\n", " \n", " searchsorted(a, v, side='left', sorter=None)\n", " scipy.searchsorted is deprecated and will be removed in SciPy 2.0.0, use numpy.searchsorted instead\n", " \n", " select(condlist, choicelist, default=0)\n", " scipy.select is deprecated and will be removed in SciPy 2.0.0, use numpy.select instead\n", " \n", " set_numeric_ops(...)\n", " scipy.set_numeric_ops is deprecated and will be removed in SciPy 2.0.0, use numpy.set_numeric_ops instead\n", " \n", " set_printoptions(precision=None, threshold=None, edgeitems=None, linewidth=None, suppress=None, nanstr=None, infstr=None, formatter=None, sign=None, floatmode=None, *, legacy=None)\n", " scipy.set_printoptions is deprecated and will be removed in SciPy 2.0.0, use numpy.set_printoptions instead\n", " \n", " set_string_function(f, repr=True)\n", " scipy.set_string_function is deprecated and will be removed in SciPy 2.0.0, use numpy.set_string_function instead\n", " \n", " setbufsize(size)\n", " scipy.setbufsize is deprecated and will be removed in SciPy 2.0.0, use numpy.setbufsize instead\n", " \n", " setdiff1d(ar1, ar2, assume_unique=False)\n", " scipy.setdiff1d is deprecated and will be removed in SciPy 2.0.0, use numpy.setdiff1d instead\n", " \n", " seterr(all=None, divide=None, over=None, under=None, invalid=None)\n", " scipy.seterr is deprecated and will be removed in SciPy 2.0.0, use numpy.seterr instead\n", " \n", " seterrcall(func)\n", " scipy.seterrcall is deprecated and will be removed in SciPy 2.0.0, use numpy.seterrcall instead\n", " \n", " seterrobj(...)\n", " scipy.seterrobj is deprecated and will be removed in SciPy 2.0.0, use numpy.seterrobj instead\n", " \n", " setxor1d(ar1, ar2, assume_unique=False)\n", " scipy.setxor1d is deprecated and will be removed in SciPy 2.0.0, use numpy.setxor1d instead\n", " \n", " shape(a)\n", " scipy.shape is deprecated and will be removed in SciPy 2.0.0, use numpy.shape instead\n", " \n", " shares_memory(...)\n", " scipy.shares_memory is deprecated and will be removed in SciPy 2.0.0, use numpy.shares_memory instead\n", " \n", " show_config = show()\n", " \n", " sign(...)\n", " scipy.sign is deprecated and will be removed in SciPy 2.0.0, use numpy.sign instead\n", " \n", " signbit(...)\n", " scipy.signbit is deprecated and will be removed in SciPy 2.0.0, use numpy.signbit instead\n", " \n", " sin(...)\n", " scipy.sin is deprecated and will be removed in SciPy 2.0.0, use numpy.sin instead\n", " \n", " sinc(x)\n", " scipy.sinc is deprecated and will be removed in SciPy 2.0.0, use numpy.sinc instead\n", " \n", " sinh(...)\n", " scipy.sinh is deprecated and will be removed in SciPy 2.0.0, use numpy.sinh instead\n", " \n", " size(a, axis=None)\n", " scipy.size is deprecated and will be removed in SciPy 2.0.0, use numpy.size instead\n", " \n", " sometrue(*args, **kwargs)\n", " scipy.sometrue is deprecated and will be removed in SciPy 2.0.0, use numpy.sometrue instead\n", " \n", " sort(a, axis=-1, kind=None, order=None)\n", " scipy.sort is deprecated and will be removed in SciPy 2.0.0, use numpy.sort instead\n", " \n", " sort_complex(a)\n", " scipy.sort_complex is deprecated and will be removed in SciPy 2.0.0, use numpy.sort_complex instead\n", " \n", " source(object, output=)\n", " scipy.source is deprecated and will be removed in SciPy 2.0.0, use numpy.source instead\n", " \n", " spacing(...)\n", " scipy.spacing is deprecated and will be removed in SciPy 2.0.0, use numpy.spacing instead\n", " \n", " split(ary, indices_or_sections, axis=0)\n", " scipy.split is deprecated and will be removed in SciPy 2.0.0, use numpy.split instead\n", " \n", " sqrt(x)\n", " scipy.sqrt is deprecated and will be removed in SciPy 2.0.0, use numpy.lib.scimath.sqrt instead\n", " \n", " square(...)\n", " scipy.square is deprecated and will be removed in SciPy 2.0.0, use numpy.square instead\n", " \n", " squeeze(a, axis=None)\n", " scipy.squeeze is deprecated and will be removed in SciPy 2.0.0, use numpy.squeeze instead\n", " \n", " stack(arrays, axis=0, out=None)\n", " scipy.stack is deprecated and will be removed in SciPy 2.0.0, use numpy.stack instead\n", " \n", " std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=)\n", " scipy.std is deprecated and will be removed in SciPy 2.0.0, use numpy.std instead\n", " \n", " subtract(...)\n", " scipy.subtract is deprecated and will be removed in SciPy 2.0.0, use numpy.subtract instead\n", " \n", " sum(a, axis=None, dtype=None, out=None, keepdims=, initial=, where=)\n", " scipy.sum is deprecated and will be removed in SciPy 2.0.0, use numpy.sum instead\n", " \n", " swapaxes(a, axis1, axis2)\n", " scipy.swapaxes is deprecated and will be removed in SciPy 2.0.0, use numpy.swapaxes instead\n", " \n", " take(a, indices, axis=None, out=None, mode='raise')\n", " scipy.take is deprecated and will be removed in SciPy 2.0.0, use numpy.take instead\n", " \n", " take_along_axis(arr, indices, axis)\n", " scipy.take_along_axis is deprecated and will be removed in SciPy 2.0.0, use numpy.take_along_axis instead\n", " \n", " tan(...)\n", " scipy.tan is deprecated and will be removed in SciPy 2.0.0, use numpy.tan instead\n", " \n", " tanh(...)\n", " scipy.tanh is deprecated and will be removed in SciPy 2.0.0, use numpy.tanh instead\n", " \n", " tensordot(a, b, axes=2)\n", " scipy.tensordot is deprecated and will be removed in SciPy 2.0.0, use numpy.tensordot instead\n", " \n", " tile(A, reps)\n", " scipy.tile is deprecated and will be removed in SciPy 2.0.0, use numpy.tile instead\n", " \n", " trace(a, offset=0, axis1=0, axis2=1, dtype=None, out=None)\n", " scipy.trace is deprecated and will be removed in SciPy 2.0.0, use numpy.trace instead\n", " \n", " transpose(a, axes=None)\n", " scipy.transpose is deprecated and will be removed in SciPy 2.0.0, use numpy.transpose instead\n", " \n", " trapz(y, x=None, dx=1.0, axis=-1)\n", " scipy.trapz is deprecated and will be removed in SciPy 2.0.0, use numpy.trapz instead\n", " \n", " tri(N, M=None, k=0, dtype=)\n", " scipy.tri is deprecated and will be removed in SciPy 2.0.0, use numpy.tri instead\n", " \n", " tril(m, k=0)\n", " scipy.tril is deprecated and will be removed in SciPy 2.0.0, use numpy.tril instead\n", " \n", " tril_indices(n, k=0, m=None)\n", " scipy.tril_indices is deprecated and will be removed in SciPy 2.0.0, use numpy.tril_indices instead\n", " \n", " tril_indices_from(arr, k=0)\n", " scipy.tril_indices_from is deprecated and will be removed in SciPy 2.0.0, use numpy.tril_indices_from instead\n", " \n", " trim_zeros(filt, trim='fb')\n", " scipy.trim_zeros is deprecated and will be removed in SciPy 2.0.0, use numpy.trim_zeros instead\n", " \n", " triu(m, k=0)\n", " scipy.triu is deprecated and will be removed in SciPy 2.0.0, use numpy.triu instead\n", " \n", " triu_indices(n, k=0, m=None)\n", " scipy.triu_indices is deprecated and will be removed in SciPy 2.0.0, use numpy.triu_indices instead\n", " \n", " triu_indices_from(arr, k=0)\n", " scipy.triu_indices_from is deprecated and will be removed in SciPy 2.0.0, use numpy.triu_indices_from instead\n", " \n", " true_divide(...)\n", " scipy.true_divide is deprecated and will be removed in SciPy 2.0.0, use numpy.true_divide instead\n", " \n", " trunc(...)\n", " scipy.trunc is deprecated and will be removed in SciPy 2.0.0, use numpy.trunc instead\n", " \n", " typename(char)\n", " scipy.typename is deprecated and will be removed in SciPy 2.0.0, use numpy.typename instead\n", " \n", " union1d(ar1, ar2)\n", " scipy.union1d is deprecated and will be removed in SciPy 2.0.0, use numpy.union1d instead\n", " \n", " unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None)\n", " scipy.unique is deprecated and will be removed in SciPy 2.0.0, use numpy.unique instead\n", " \n", " unpackbits(...)\n", " scipy.unpackbits is deprecated and will be removed in SciPy 2.0.0, use numpy.unpackbits instead\n", " \n", " unravel_index(...)\n", " scipy.unravel_index is deprecated and will be removed in SciPy 2.0.0, use numpy.unravel_index instead\n", " \n", " unwrap(p, discont=3.141592653589793, axis=-1)\n", " scipy.unwrap is deprecated and will be removed in SciPy 2.0.0, use numpy.unwrap instead\n", " \n", " vander(x, N=None, increasing=False)\n", " scipy.vander is deprecated and will be removed in SciPy 2.0.0, use numpy.vander instead\n", " \n", " var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=)\n", " scipy.var is deprecated and will be removed in SciPy 2.0.0, use numpy.var instead\n", " \n", " vdot(...)\n", " scipy.vdot is deprecated and will be removed in SciPy 2.0.0, use numpy.vdot instead\n", " \n", " vsplit(ary, indices_or_sections)\n", " scipy.vsplit is deprecated and will be removed in SciPy 2.0.0, use numpy.vsplit instead\n", " \n", " vstack(tup)\n", " scipy.vstack is deprecated and will be removed in SciPy 2.0.0, use numpy.vstack instead\n", " \n", " where(...)\n", " scipy.where is deprecated and will be removed in SciPy 2.0.0, use numpy.where instead\n", " \n", " who(vardict=None)\n", " scipy.who is deprecated and will be removed in SciPy 2.0.0, use numpy.who instead\n", " \n", " zeros(...)\n", " scipy.zeros is deprecated and will be removed in SciPy 2.0.0, use numpy.zeros instead\n", " \n", " zeros_like(a, dtype=None, order='K', subok=True, shape=None)\n", " scipy.zeros_like is deprecated and will be removed in SciPy 2.0.0, use numpy.zeros_like instead\n", "\n", "DATA\n", " ALLOW_THREADS = 1\n", " BUFSIZE = 8192\n", " CLIP = 0\n", " ERR_CALL = 3\n", " ERR_DEFAULT = 521\n", " ERR_IGNORE = 0\n", " ERR_LOG = 5\n", " ERR_PRINT = 4\n", " ERR_RAISE = 2\n", " ERR_WARN = 1\n", " FLOATING_POINT_SUPPORT = 1\n", " FPE_DIVIDEBYZERO = 1\n", " FPE_INVALID = 8\n", " FPE_OVERFLOW = 2\n", " FPE_UNDERFLOW = 4\n", " False_ = False\n", " Inf = inf\n", " Infinity = inf\n", " MAXDIMS = 32\n", " MAY_SHARE_BOUNDS = 0\n", " MAY_SHARE_EXACT = -1\n", " NAN = nan\n", " NINF = -inf\n", " NZERO = -0.0\n", " NaN = nan\n", " PINF = inf\n", " PZERO = 0.0\n", " RAISE = 2\n", " SHIFT_DIVIDEBYZERO = 0\n", " SHIFT_INVALID = 9\n", " SHIFT_OVERFLOW = 3\n", " SHIFT_UNDERFLOW = 6\n", " ScalarType = (, , , \n", " __SCIPY_SETUP__ = False\n", " __all__ = ['test', 'ModuleDeprecationWarning', 'VisibleDeprecationWarn...\n", " __numpy_version__ = '1.19.5'\n", " c_ = \n", " cast = {: at ...py.int8'>: <...\n", " e = 2.718281828459045\n", " euler_gamma = 0.5772156649015329\n", " index_exp = \n", " inf = inf\n", " infty = inf\n", " little_endian = True\n", " mgrid = \n", " nan = nan\n", " nbytes = {: 1, :....datetime6...\n", " newaxis = None\n", " ogrid = \n", " pi = 3.141592653589793\n", " r_ = \n", " s_ = \n", " sctypeDict = {'?': , 0: , 'b...\n", " sctypeNA = {'Bool': , , , \n", " tracemalloc_domain = 389047\n", " typeDict = {'?': , 0: , 'byt...\n", " typeNA = {'Bool': , , \n" ] } ], "source": [ "x = np.array([1, 2.5, 5, 10])\n", "print(x,type(x))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0.0749064 0.22495348 0.22248318 0.04446907] \n" ] } ], "source": [ "y = np.random.rand(4)\n", "print(y,type(y))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plotting\n", "\n", "Visualizing the data is quite simple with pyplot:\n", "* Initialize a figure with `plt.figure()`\n", "* Plot something with ... `plt.plot` (see the [documentation](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.html?highlight=pyplot#module-matplotlib.pyplot) )\n", "* Fix labels, titles, axes\n", "* Eventually save the result with `plt.savefig`\n", "* Show the figure with `plt.show()`" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "\n", "plt.plot(x,y, 'bd--', label='y(x)')\n", "\n", "plt.legend(loc='lower right')\n", "plt.xlabel('x')\n", "plt.ylabel('y')\n", "plt.title('Sample Figure')\n", "plt.xlim([0, 10])\n", "plt.ylim([0, 1])\n", "plt.savefig('img/sample.png')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Matrices\n", "\n", "Matrices are simply 2D arrays. Since vectors and matrices share the same type, the notion of *shape* is very important." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0.25 6.2 1. 10. ]\n", " [12. 6.2 6. -5.3 ]] \n" ] } ], "source": [ "M = np.array([[0.25, 6.2, 1, 10],[12, 6.2, 6, -5.3]])\n", "print(M,type(M))" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 1. 2.5 5. 10. ] \n" ] } ], "source": [ "print(x,type(x))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* The `size` of an array is the number of elements while the `shape` gives how they are arranged." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "4\n", "8\n" ] } ], "source": [ "print(x.size) # or equivalently np.size(x)\n", "print(M.size)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(4,)\n", "(2, 4)\n" ] } ], "source": [ "print(x.shape) # or equivalently np.shape(x)\n", "print(M.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* The element access, assignment, type, copy is common and similar to the list type." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 1. 2.5 5. 10. ]\n", "5.0 10.0\n", "[10. 5. 2.5 1. ]\n", "[ 6.1554 2.5 5. 10. ]\n" ] } ], "source": [ "print(x)\n", "print(x[2],x[-1])\n", "print(x[::-1])\n", "x[0] = 6.1554\n", "print(x)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 6.1554 2.5 5. 10. ]\n", "[ 1. 2.5 5. 10. ]\n", "[ 6.1554 2.5 5. 10. ]\n" ] } ], "source": [ "v = x\n", "w = np.copy(x) \n", "print(v)\n", "x[0]=1\n", "print(v)\n", "print(w)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0.25 6.2 1. 10. ]\n", " [12. 6.2 6. -5.3 ]]\n", "6.0 \n", "[12. 6.2 6. -5.3] (4,)\n", "[12. 6.2 6. -5.3]\n", "[ 0.25 12. ]\n" ] } ], "source": [ "print(M)\n", "print(M[1,2],type(M[1,2]))\n", "print(M[1,:],type(M[1,:]),M[1,:].shape)\n", "print(M[1])\n", "print(M[:,0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Advanced access to content and modification is possible" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 1. 5. 10.]\n" ] } ], "source": [ "x = np.array([1, 2.5, 5, 10])\n", "ind = [0,2,3]\n", "print(x[ind])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Advanced array properties [*]\n", "\n", "\n", "An array has a *type* that can be accessed with dtype, it the combination of a base type (int, float, complex, bool, object, etc.) and a precision in bits (int64, int16, float128, complex128)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "float64\n" ] } ], "source": [ "print(x.dtype)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Array only accept they casting to their own type. However, the type of an array can be changed." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "can't convert complex to float\n" ] } ], "source": [ "try:\n", " x[0] = 1 + 2.0j\n", "except Exception as e:\n", " print(e)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 1. +2.j 2.5+0.j 5. +0.j 10. +0.j] complex128\n" ] } ], "source": [ "y = x.astype(complex)\n", "y[0] = 1 + 2.0j\n", "print(y,type(y),y.dtype)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Numpy array generation\n", "\n", "See the corresponding [documentation](https://numpy.org/doc/stable/user/basics.creation.html)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Number sequences\n", "\n", "\n", "`arange` returns an array of evenly spaced number from `start` to (at most) `stop` with a fixed jump `step` \n", "\n", "\n", "`linspace` returns an array of evenly spaced number from `start` to (exactly) `stop` with a fixed number of points `num`" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0. 1.5 3. 4.5 6. 7.5 9. ] \n" ] } ], "source": [ "x = np.arange(0, 10, 1.5)\n", "print(x,type(x))" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0. 0.41666667 0.83333333 1.25 1.66666667 2.08333333\n", " 2.5 2.91666667 3.33333333 3.75 4.16666667 4.58333333\n", " 5. 5.41666667 5.83333333 6.25 6.66666667 7.08333333\n", " 7.5 7.91666667 8.33333333 8.75 9.16666667 9.58333333\n", " 10. ] \n" ] } ], "source": [ "y = np.linspace(0, 10, 25)\n", "print(y,type(y))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Zeros and Ones\n", "\n", "\n", "`zeros` returns an array (of floats) of zeros of the precised `shape`\n", "\n", "`ones` returns an array (of floats) of ones of the precised `shape`\n", "\n", "`eye` returns a square 2D-array (of floats) with ones on the diagonal and zeros elsewhere " ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0. 0. 0.] (3,) float64\n", "[0. 0. 0.] (3,) float64\n" ] } ], "source": [ "x = np.zeros(3)\n", "print(x,x.shape,type(x),x.dtype)\n", "\n", "x = np.zeros((3,))\n", "print(x,x.shape,type(x),x.dtype)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cannot interpret '3' as a data type\n", "[0. 0. 0.] (3,) float64\n" ] } ], "source": [ "try:\n", " x = np.zeros(3,3) # This causes an error as 3,3 is not a shape, it is (3,3) -> double parentheses\n", "except Exception as error:\n", " print(error)\n", "\n", "print(x,x.shape,type(x),x.dtype)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[0. 0. 0.]\n", " [0. 0. 0.]\n", " [0. 0. 0.]] (3, 3) float64\n" ] } ], "source": [ "x = np.zeros((3,3))\n", "print(x,x.shape,type(x),x.dtype)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([1., 1.])" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y = np.ones(2)\n", "y" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[1. 0. 0.]\n", " [0. 1. 0.]\n", " [0. 0. 1.]] (3, 3) float64\n" ] } ], "source": [ "M = np.eye(3)\n", "print(M,M.shape,type(M),M.dtype)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Random data\n", "\n", "\n", "Random arrays can be generated by Numpy's [random](https://numpy.org/doc/stable/reference/random/index.html) module.\n", "\n", "\n", "`rand` returns an array (of floats) of uniformly distributed numbers in [0,1) of the precised dimension\n", "\n", "`randn` returns an array (of floats) of numbers from the normal distribution of the precised dimension\n", "\n", "`randint` returns an array (of floats) of integers from the discrete uniform distribution" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0.09708256, 0.28084182, 0.03623694, 0.83693802, 0.89064811])" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.random.rand(5) " ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[-0.13167876, 0.53288997],\n", " [ 1.94922176, -0.55397441],\n", " [-0.8463868 , -1.96584426],\n", " [ 0.23209953, 0.58799903],\n", " [-0.08861985, 0.27334093]])" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.random.randn(5,2)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([88, 6, 78, 3, 18, 17, 96, 13, 13, 90])" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.random.randint(0,100,size=(10,))" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "a = np.random.randn(10000)\n", "plt.figure()\n", "plt.hist(a,40) # histogram of a with 40 bins\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Operations on Matrices and vectors \n" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0 1 2 3 4]\n" ] } ], "source": [ "v = np.arange(0, 5)\n", "print(v)" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0, 2, 4, 6, 8])" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "v * 2" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([2.5, 3.5, 4.5, 5.5, 6.5])" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "v + 2.5" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0 1 4 9 16] [0. 1. 1.41421356 1.73205081 2. ]\n" ] } ], "source": [ "square = v**2\n", "root = np.sqrt(v)\n", "print(square,root)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "plt.subplot(1,2,1)\n", "plt.plot(square,'g--', label='$y = x^2$')\n", "plt.legend(loc=0)\n", "plt.subplot(1,2,2)\n", "plt.plot(root, 'r*-', label='$y = \\sqrt{x}$')\n", "plt.legend(loc=2)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0 1 2 3 4]\n", " [10 11 12 13 14]\n", " [20 21 22 23 24]\n", " [30 31 32 33 34]]\n" ] } ], "source": [ "A = np.array([[n+m*10 for n in range(5)] for m in range(4)])\n", "print(A)" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 0, 2, 4, 6, 8],\n", " [20, 22, 24, 26, 28],\n", " [40, 42, 44, 46, 48],\n", " [60, 62, 64, 66, 68]])" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A*2" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 2.5, 3.5, 4.5, 5.5, 6.5],\n", " [12.5, 13.5, 14.5, 15.5, 16.5],\n", " [22.5, 23.5, 24.5, 25.5, 26.5],\n", " [32.5, 33.5, 34.5, 35.5, 36.5]])" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A+2.5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Matrices can be visualized as images." ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "C = np.random.randn(100,100)\n", "plt.figure()\n", "plt.imshow(C)\n", "plt.colorbar()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Matrix and vector operations\n", "\n", "\n", "\n", "*Warning:* Operation symbols `+ - * /` correspond to *elementwise* operations! To perform, matrix/vector multiplication, dedicated function must be used. \n", "\n", "### Elementwise operations" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0 1 2 3 4]\n", " [10 11 12 13 14]\n", " [20 21 22 23 24]\n", " [30 31 32 33 34]] [4 3 2 3 3]\n" ] } ], "source": [ "A = np.array([[n+m*10 for n in range(5)] for m in range(4)])\n", "v = np.random.randint(0,5,5)\n", "print(A,v)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 0, 1, 4, 9, 16],\n", " [ 100, 121, 144, 169, 196],\n", " [ 400, 441, 484, 529, 576],\n", " [ 900, 961, 1024, 1089, 1156]])" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A*A" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([16, 9, 4, 9, 9])" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "v*v" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 0, 3, 4, 9, 12],\n", " [ 40, 33, 24, 39, 42],\n", " [ 80, 63, 44, 69, 72],\n", " [120, 93, 64, 99, 102]])" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A*v" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Transposition\n", "\n", "It can be useful to transpose, it is simply done by suffixing `.T` (or equivalently using the function `np.transpose`). Similarly `.H` is the Hermitian conjugate, `.imag` `.real` are the real and imaginary parts and `.abs` the modulus (their *full* versions are respectively `np.conjugate`, `np.imag`, etc.)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0 1 2 3 4]\n", " [10 11 12 13 14]\n", " [20 21 22 23 24]\n", " [30 31 32 33 34]] (4, 5)\n", "[[ 0 10 20 30]\n", " [ 1 11 21 31]\n", " [ 2 12 22 32]\n", " [ 3 13 23 33]\n", " [ 4 14 24 34]] (5, 4)\n" ] } ], "source": [ "print(A,A.shape)\n", "print(A.T,A.T.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Matrix/vector operations\n", "\n", "$y=Av$ can be obtained by `y = A.dot(v)` (or equivalently `y = np.dot(A,v)`). This methods works for array with *compatible shape* (matrix-matrix, matrix-vector, vector-matrix, vector-vector, etc).\n" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0 1 2 3 4]\n", " [10 11 12 13 14]\n", " [20 21 22 23 24]\n", " [30 31 32 33 34]] (4, 5) [4 3 2 3 3] (5,)\n", "[ 28 178 328 478] (4,)\n" ] } ], "source": [ "y = np.dot(A,v)\n", "print(A,A.shape,v,v.shape)\n", "print(y,type(y),y.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Example of vector-vector multiplication i.e. a scalar product" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[4 3 2 3 3] 47 \n" ] } ], "source": [ "s = v.dot(v)\n", "print(v, s, type(s))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Example of non-compatible shapes" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "shapes (4,5) and (4,5) not aligned: 5 (dim 1) != 4 (dim 0)\n" ] } ], "source": [ "try:\n", " A2 = np.dot(A,A)\n", "except Exception as error:\n", " print(error)" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 30 130 230 330]\n", " [ 130 730 1330 1930]\n", " [ 230 1330 2430 3530]\n", " [ 330 1930 3530 5130]] (4, 4)\n" ] } ], "source": [ "A3 = np.dot(A,A.T)\n", "print(A3,A3.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From a vector $v$, one can form the matrix $P=v v^T$ by `A=v.outer(v)` (or equivalently `np.outer(v,v)`)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[16 12 8 12 12]\n", " [12 9 6 9 9]\n", " [ 8 6 4 6 6]\n", " [12 9 6 9 9]\n", " [12 9 6 9 9]]\n" ] } ], "source": [ "P = np.outer(v,v)\n", "print(P)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Useful Functions\n", "\n", "See the Documentation on [arrays](https://numpy.org/doc/stable/reference/arrays.ndarray.html) and [array creation](https://numpy.org/doc/stable/reference/routines.array-creation.html).\n", "\n", "*Warning:* Modificators such as transpose, reshape, etc. do not modify the matrix, if you want to keep the result of the operation, you have to assign a variable to it. The notable exceptions are precised as *in-place* in the documentation." ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 0, 1, 2, 3, 4, 10, 11, 12, 13, 14],\n", " [20, 21, 22, 23, 24, 30, 31, 32, 33, 34]])" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A.reshape((2,10))" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 0 1 2 3 4]\n", " [10 11 12 13 14]\n", " [20 21 22 23 24]\n", " [30 31 32 33 34]]\n" ] } ], "source": [ "print(A)" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0 1 2 3 4 10 11 12 13 14 20 21 22 23 24 30 31 32 33 34]\n" ] } ], "source": [ "B = A.flatten()\n", "print(B)" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "66 34 19\n" ] } ], "source": [ "print(A.trace(),A.max(),A.argmax())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Some functions may be taken with respects to the columns with axis=0 or lines with axis=1." ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "17.0 [15. 16. 17. 18. 19.] [ 2. 12. 22. 32.]\n" ] } ], "source": [ "print(A.mean(),A.mean(axis=0),A.mean(axis=1))" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "127.0 [125. 125. 125. 125. 125.] [1.41421356 1.41421356 1.41421356 1.41421356]\n" ] } ], "source": [ "print(A.var(),A.var(axis=0),A.std(axis=1))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Repetition, concatenation" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1, 2],\n", " [3, 4]])" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a = np.array([[1, 2], [3, 4]])\n", "a" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[5, 6]])" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "b = np.array([[5, 6]])\n", "b" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1, 2],\n", " [3, 4],\n", " [5, 6]])" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.concatenate((a, b), axis=0)" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1, 2, 5],\n", " [3, 4, 6]])" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.concatenate((a, b.T), axis=1)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1, 2],\n", " [3, 4],\n", " [5, 6]])" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.vstack((a,b))" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1, 2, 5],\n", " [3, 4, 6]])" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.hstack((a,b.T))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Iterating on arrays" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1\n", "2\n", "3\n", "4\n" ] } ], "source": [ "v = np.array([1,2,3,4])\n", "\n", "for element in v:\n", " print(element)" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "row [1 2]\n", "1\n", "2\n", "row [3 4]\n", "3\n", "4\n" ] } ], "source": [ "a = np.array([[1,2], [3,4]])\n", "\n", "for row in a:\n", " print(\"row\", row)\n", " \n", " for element in row:\n", " print(element)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "enumerate can be used to get indexes along with elements." ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "row_idx 0 row [1 2]\n", "col_idx 0 element 1\n", "col_idx 1 element 2\n", "row_idx 1 row [3 4]\n", "col_idx 0 element 3\n", "col_idx 1 element 4\n" ] } ], "source": [ "for row_idx, row in enumerate(a):\n", " print(\"row_idx\", row_idx, \"row\", row)\n", " \n", " for col_idx, element in enumerate(row):\n", " print(\"col_idx\", col_idx, \"element\", element)\n", " \n", " # update the matrix a: square each element\n", " a[row_idx, col_idx] = element ** 2" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 1, 4],\n", " [ 9, 16]])" ] }, "execution_count": 72, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 3- Linear Algebra \n", "\n", "\n", "Numpy comes with an efficient linear algebra module named `linalg` (see the [documentation](https://numpy.org/doc/stable/reference/routines.linalg.html) ). As in many languages, the more vectorized the operations are, the more efficient.\n", "\n", "## Decompositions\n", "\n", "\n", "* *QR:* `linalg.qr` Factor the matrix $A$ as $QR$, where $Q$ is orthonormal and $R$ is upper-triangular.\n", "* *Cholesky:* `linalg.cholesky` Return the Cholesky decomposition, $L L^H$, of the square matrix $A$, where $L$ is lower-triangular. $A$ must be Hermitian and positive-definite. Only $L$ is actually returned.\n", "* *SVD:* `linalg.svd` Factors the matrix $A$ as $U \\text{diag}(s) V$, where $U$ and $V$ are unitary and $s$ is a 1-d array of $A$‘s singular values.\n", "\n" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [], "source": [ "A = np.random.randn(3,2)" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[-0.19169683 -0.06738807]\n", " [ 0.73213885 0.09261738]\n", " [ 0.05779475 0.20352188]]\n", "[[-0.2525575 -0.18377434]\n", " [ 0.96458118 -0.12508222]\n", " [ 0.07614366 0.97497766]]\n", "[[0.75902253 0.12185325]\n", " [0. 0.19922869]]\n" ] } ], "source": [ "Q, R = np.linalg.qr(A)\n", "print(A)\n", "print(Q)\n", "print(R)" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.allclose(A, np.dot(Q, R)) # check that A=QR" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(3, 3) (2, 2) (2,)\n" ] } ], "source": [ "U, s, V = np.linalg.svd(A)\n", "print(U.shape, V.shape, s.shape)" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "S = np.zeros(A.shape)\n", "S[:A.shape[1], :A.shape[1]] = np.diag(s)\n", "np.allclose(A, np.dot(U, np.dot(S, V)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By default, $U$ and $V$ have the shapes $(M, M)$ and $(N, N)$ respectively if $A$ is $(M,N)$. If `full_matrices=False` is passed, the shapes are $(M, K)$ and $(K, N)$, respectively, where $K = min(M, N)$." ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(3, 2) (2, 2) (2,)\n" ] } ], "source": [ "U, s, V = np.linalg.svd(A, full_matrices=False)\n", "print(U.shape, V.shape, s.shape)" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "S = np.diag(s)\n", "np.allclose(A, np.dot(U, np.dot(S, V)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Eigenvalues\n", "\n", "`linalg.eig` compute the eigenvalues and right eigenvectors of a square array and is the main function (`linalg.eigvals` computes eigenvalues of a non-symmetric array, `linalg.eigh` returns eigenvalues and eigenvectors of a symmetric or Hermitian array)." ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 1 -1]\n", " [ 1 1]]\n", "[1.+1.j 1.-1.j]\n", "[[0.70710678+0.j 0.70710678-0.j ]\n", " [0. -0.70710678j 0. +0.70710678j]]\n" ] } ], "source": [ "A = np.array([[1, -1], [1, 1]])\n", "print(A)\n", "l, v = np.linalg.eig(A)\n", "print(l); print(v)" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0.70710678+0.70710678j, 0.70710678-0.70710678j])" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A.dot(v[:,0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can check that $Ax= \\lambda x$." ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 82, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.allclose(A.dot(v[:,0]),l[0]*v[:,0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Norms and other numbers\n", "\n", "The function `linalg.norm` is able to return one of eight different matrix norms, or one of an infinite number of vector norms (described below), depending on the value of the `ord` parameter.\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
ordnorm for matricesnorm for vectors
NoneFrobenius norm2-norm
‘fro’Frobenius norm–
‘nuc’nuclear norm–
infmax(sum(abs(x), axis=1))max(abs(x))
-infmin(sum(abs(x), axis=1))min(abs(x))
0–sum(x != 0)
1max(sum(abs(x), axis=0))as below
-1min(sum(abs(x), axis=0))as below
22-norm (largest sing. value)as below
-2smallest singular valueas below
other–sum(abs(x)$^{ord}$)$^{(1./ord)}$
" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [], "source": [ "a = np.arange(9) - 4\n", "B = a.reshape((3, 3))" ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[-4 -3 -2 -1 0 1 2 3 4]\n", "none \t 7.745966692414834\n", "2 \t 7.745966692414834\n", "1 \t 20.0\n", "inf \t 4.0\n", "0 \t 8.0\n" ] } ], "source": [ "print(a)\n", "print(\"none \\t\",np.linalg.norm(a))\n", "print(\"2 \\t\",np.linalg.norm(a,ord=2))\n", "print(\"1 \\t\",np.linalg.norm(a,ord=1))\n", "print(\"inf \\t\",np.linalg.norm(a,ord=np.inf))\n", "print(\"0 \\t\",np.linalg.norm(a,ord=0))" ] }, { "cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[-4 -3 -2]\n", " [-1 0 1]\n", " [ 2 3 4]]\n", "none \t 7.745966692414834\n", "2 \t 7.348469228349533\n", "1 \t 7.0\n", "inf \t 9.0\n", "fro \t 7.745966692414834\n" ] } ], "source": [ "print(B)\n", "print(\"none \\t\",np.linalg.norm(B))\n", "print(\"2 \\t\",np.linalg.norm(B,ord=2))\n", "print(\"1 \\t\",np.linalg.norm(B,ord=1))\n", "print(\"inf \\t\",np.linalg.norm(B,ord=np.inf))\n", "print(\"fro \\t\",np.linalg.norm(B,ord='fro'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Other useful function include the condition number `linalg.cond`, or rank `linalg.matrix_rank` ." ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [], "source": [ "A = np.array([[1, 0, -1], [0, 1, 0], [1, 0, 1]]) # some matrix\n", "I = np.eye(4) # identity\n", "Def = np.eye(4); Def[0,0]=0 # rank deficient" ] }, { "cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.4142135623730951 1.0\n" ] } ], "source": [ "print(np.linalg.cond(A), np.linalg.cond(I))" ] }, { "cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "inf" ] }, "execution_count": 88, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.linalg.cond(Def)" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3 4 3\n" ] } ], "source": [ "print(np.linalg.matrix_rank(A), np.linalg.matrix_rank(I), np.linalg.matrix_rank(Def))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Solving equations and inverting matrices\n", "\n", "When $A$ is full-rank, finding $x$ such that $Ax=b$ can be done efficiently using `linalg.solve` (as a general remark it is in general bad to invert $A$ for solving such equations, although this can be done by `linalg.inv`). " ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[3 1]\n", " [1 2]]\n", "[9 8]\n" ] } ], "source": [ "A = np.array([[3,1], [1,2]])\n", "b = np.array([9,8])\n", "print(A)\n", "print(b)" ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2. 3.] True\n" ] } ], "source": [ "x_sol = np.linalg.solve(A,b)\n", "\n", "print(x_sol , np.allclose(A.dot(x_sol),b))" ] }, { "cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2. 3.] True\n" ] } ], "source": [ "A_inv = np.linalg.inv(A)\n", "x_sol2 = A_inv.dot(b)\n", "\n", "print(x_sol2 , np.allclose(A.dot(x_sol2),b))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Why you don't want to invert a matrix except if really needed:" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [], "source": [ "N= 100\n", "A = np.random.randn(N,N)\n", "b = np.random.randn(N)" ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "209 µs ± 68.7 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n" ] } ], "source": [ "%timeit x_sol = np.linalg.solve(A,b)" ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "295 µs ± 28.3 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n" ] } ], "source": [ "%timeit A_inv = np.linalg.inv(A) ; x_sol2 = A_inv.dot(b)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If $A$ is not full-rank, the least squares solution of $Ax=b$ (i.e $x$ that minimizes $\\|Ax-b\\|_2$) can be obtained by `linalg.lstsq` and `linalg.pinv` give the Moore-Penrose pseudo inverse." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 4- Exercises" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "> **Exercise 1:** In polynomial regression, we are given $n$ points $(x_i,y_i)$ and fit a size-$m$ polynome $f(x) = c_0 + c_1 x + c_2 x^2 + .. + c_m x^m$ so that $f(x_i)\\approx y_i$ for all $i=1,..n$.\n", "> \n", "> In this exercise, we want to find the $m+1$ coefficients $(c_j)$ that minimize the least square error\n", "> $$ \\left\\| ~~~ \\underbrace{ \\left[ \\begin{array}{ccccc} 1 & x_1 & x_1^2 & .. & x_1^m \\\\ 1 & x_2 & x_2^2 & .. & x_2^m \\\\ \\vdots & \\vdots & \\vdots & \\vdots & \\vdots \\\\ 1 & x_n & x_n^2 & .. & x_n^m \\end{array} \\right] }_{X} ~ \\underbrace{ \\left[ \\begin{array}{c} c_0 \\\\ c_1 \\\\ c_2 \\\\ \\vdots \\\\ c_m \\end{array} \\right] }_{c} - \\underbrace{ \\left[ \\begin{array}{c} y_1 \\\\ y_2 \\\\ \\vdots \\\\ y_n \\end{array} \\right] }_{y} \\right\\|^2 $$\n", "> 1. Construct the matrix $X$ from the given vector $x$ below with $m=3$.\n", "> * Find the optimal $c$ by solving the least square problem $\\min_c \\|Xc-y\\|^2$ using Numpy (`lstsq` and `solve`). Is the result exact (no error)?\n", "> * Plot the obtained polynome on the scatter plot.\n", "> * Redo questions 2-3 by varying the relative sizes of $n$ and $m$. What do you observe?" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "\n", "n = 30 # Number of sample points\n", "\n", "x = (np.random.rand(n)-0.5)*6\n", "y = np.sign(x)*np.maximum(np.abs(x)-1.0,0.0)" ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 97, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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