{
 "metadata": {
  "name": "05_other"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Doctest"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Often we need both: document our function and test that it's working properly, one of the easiest way to do both is using the [doctest](http://docs.python.org/2/library/doctest.html)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def multiply(a, b):\n",
      "    \"\"\"Return the moltiplication of two values. ::\n",
      "\n",
      "    Example\n",
      "    --------\n",
      "    \n",
      "    ::\n",
      "\n",
      "        >>> multiply(1, 2)\n",
      "        2\n",
      "        >>> multiply(1, 2.)\n",
      "        2.0\n",
      "        >>> multiply('a', 4)\n",
      "        'aaaa'\n",
      "    \"\"\"\n",
      "    pass\n",
      "\n",
      "import doctest\n",
      "doctest.run_docstring_examples(multiply, globals(), verbose=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Exercise 13"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Modify the above function to pass all the tests. After that modify the class Bbox contained in bbox.py to pass all the following tests:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%bash\n",
      "python2 bbox.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "file, write, open and print"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "More info: http://docs.python.org/2/tutorial/inputoutput.html#reading-and-writing-files and http://docs.python.org/2/library/stdtypes.html#file-objects"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#\n",
      "# generate random data\n",
      "#\n",
      "import random\n",
      "\n",
      "def get_random(num, upto=100):\n",
      "    \"\"\"Return a list of random numbers:\n",
      "\n",
      "    >>> get_random(3)   # doctest: +ELLIPSIS\n",
      "    [...]\n",
      "    \"\"\"\n",
      "    random_number = []\n",
      "    for _ in xrange(num):\n",
      "        random_number.append(random.random() * upto)\n",
      "    return random_number\n",
      "\n",
      "#\n",
      "# write random data\n",
      "#\n",
      "NROWS = 10\n",
      "NCOLS = 3\n",
      "\n",
      "def write_random(rows, cols, filename, upto=100):\n",
      "    # open a file in write mode\n",
      "    data = open(filename, mode='w+')\n",
      "    for row in xrange(rows):\n",
      "        data.write(';'.join([str(num) for num in get_random(cols)]) + '\\n')\n",
      "    data.close()\n",
      "    \n",
      "write_random(NROWS, NCOLS, 'data.csv')\n",
      "\n",
      "#\n",
      "# read data from file\n",
      "#\n",
      "def read(filename):\n",
      "    # open a file in read mode\n",
      "    data = open(filename, mode='r')\n",
      "    for row in data:\n",
      "        print row\n",
      "    data.close()\n",
      "        \n",
      "read('data.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Exercise 14"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Define a function that using the numpy library, allow user to compute: average, std, min, max [5 min]. "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Before to start, numpy have several mathematical and statistical functions"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy\n",
      "\n",
      "numpy.average([0, 1, 2, 3, 4, 5, 6])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def compute_from_file(filename, function, sep=';'):\n",
      "    \"\"\"Do some mathematical operations for each row in a file\n",
      "    \n",
      "    >>> compute_from_file('data.csv', numpy.average)\n",
      "    [...]\n",
      "    >>> compute_from_file('data.csv', numpy.median)\n",
      "    [...]\n",
      "    >>> compute_from_file('data.csv', numpy.min)\n",
      "    \"\"\"\n",
      "    pass"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A possible solution is:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "os"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import os"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "os.listdir('.')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "LIMIT = 10\n",
      "count = 0\n",
      "for f in sorted(os.listdir('.')):\n",
      "    count += 1\n",
      "    if count > LIMIT:\n",
      "        break\n",
      "    if os.path.isfile(f):\n",
      "        print 'is a file: %s' % f\n",
      "    elif os.path.islink(f):\n",
      "        print 'is a link: %s' % f\n",
      "    elif os.path.isdir(f):\n",
      "        print 'is a directory: %s' % f"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import os\n",
      "\n",
      "from take_time import timeit\n",
      "\n",
      "class Finder(object):\n",
      "    def __init__(self, dirpath, extension, verbose=False):\n",
      "        self.found = 0\n",
      "        self.analyzed = 0\n",
      "        self.dirpath = dirpath\n",
      "        self.extension = extension\n",
      "        self.verbose = verbose\n",
      "\n",
      "    @timeit\n",
      "    def __call__(self):\n",
      "        self.looking_for(self.dirpath)\n",
      "        print \"Analyzed: %d filse\\nFound: %d files\" % (self.analyzed, self.found)\n",
      "\n",
      "    def looking_for(self, dirpath):\n",
      "        for f in sorted(os.listdir(dirpath)):\n",
      "            self.analyzed += 1\n",
      "            abspath = os.path.join(dirpath, f)\n",
      "            if os.path.isfile(abspath):\n",
      "                fname, fext = os.path.splitext(abspath)\n",
      "                if fext == self.extension:\n",
      "                    self.found += 1\n",
      "                    if self.verbose:\n",
      "                        print 'found: %s' % abspath\n",
      "            if os.path.isdir(abspath):\n",
      "                self.looking_for(abspath)\n",
      "\n",
      "Finder('solutions/', '.py')()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "When we need to copy, remove, move directories the right tool is: [shutil](http://docs.python.org/2/library/shutil.html)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from shutil import copytree, ignore_patterns\n",
      "\n",
      "copytree(source, destination, ignore=ignore_patterns('*.pyc', 'tmp*'))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "fnmatch"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import fnmatch\n",
      "\n",
      "for file in os.listdir('.'):\n",
      "    if fnmatch.fnmatch(file, '*.py'):\n",
      "        print file"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Exercise 15"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Modify the Find class using fnmatch. [5 min]"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "numpy"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "even = np.arange(0, 10, 2, dtype=np.float)\n",
      "even"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "odd = np.arange(1, 10, 2, dtype=np.float)\n",
      "odd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "even + odd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "odd - even"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "even / odd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "array2d = np.arange(10000).reshape(100,100)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "array2d"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "array2d.T"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "array2d / 2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And much much more features... start from the [Numpy Tutorial](http://www.scipy.org/Tentative_NumPy_Tutorial)"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "matplotlib"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = np.arange(0, 2*np.pi, 0.01)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(x, np.sin(x), 'r-', x, np.cos(x), 'b-')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.grid()\n",
      "plt.plot(x, np.sin(x), 'r-', x, np.cos(x), 'b-')\n",
      "plt.title(r'Comparison between sin and cos')\n",
      "plt.xlabel(r'x')\n",
      "plt.ylabel(r\"y\")\n",
      "plt.savefig(\"comparison_sin_cos.png\", dpi=200,\n",
      "            format='png', transparent=True, bbox_inches='tight')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.core.display import Image"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image(filename=\"comparison_sin_cos.png\")  # load the figure that we create with plt.savefig"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}