{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
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Title
Path Element
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Dependencies
Bokeh
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Backends
Bokeh
Matplotlib
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" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import holoviews as hv\n", "from holoviews import opts\n", "\n", "hv.extension('bokeh')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A ``Path`` element represents one more lines, connecting arbitrary points in two-dimensional space. ``Path`` supports plotting an individual line or multiple subpaths, which should be supplied as a list. Each path should be defined in a columnar format such as NumPy arrays, DataFrames or dictionaries for each column. For a full description of the path geometry data model see the [Geometry Data User Guide](../user_guide/Geometry_Data.ipynb).\n", "\n", "In this example we will create a Lissajous curve, which describe complex harmonic motion:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "lin = np.linspace(0, np.pi*2, 200)\n", "\n", "def lissajous(t, a, b, delta):\n", " return (np.sin(a * t + delta), np.sin(b * t), t)\n", "\n", "path = hv.Path([lissajous(lin, 3, 5, np.pi/2)])\n", "path.opts(color='black', line_width=4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "If you looked carefully the ``lissajous`` function actually returns three columns, respectively for the x, y columns and a third column describing the point in time. By declaring a value dimension for that third column we can also color the Path by time. Since the value is cyclical we will also use a cyclic colormap (``'hsv'``) to represent this variable:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "path = hv.Path([lissajous(lin, 3, 5, np.pi/2)], vdims='time')\n", "path.opts(cmap='hsv', color='time', line_width=4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we do not provide a ``color`` overlaid ``Path`` elements will cycle colors just like other elements do unlike ``Curve`` a single ``Path`` element can contain multiple lines that are disconnected from each other. A ``Path`` can therefore often useful to draw arbitrary annotations on top of an existing plot.\n", "\n", "A ``Path`` Element accepts multiple formats for specifying the paths, the simplest of which is passing a list of ``Nx2`` arrays of the x- and y-coordinates, alternative we can pass lists of coordinates. In this example we will create some coordinates representing rectangles and ellipses annotating an ``RGB`` image:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "angle = np.linspace(0, 2*np.pi, 100)\n", "baby = list(zip(0.15*np.sin(angle), 0.2*np.cos(angle)-0.2))\n", "\n", "adultR = [(0.25, 0.45), (0.35,0.35), (0.25, 0.25), (0.15, 0.35), (0.25, 0.45)]\n", "adultL = [(-0.3, 0.4), (-0.3, 0.3), (-0.2, 0.3), (-0.2, 0.4),(-0.3, 0.4)]\n", "scene = hv.RGB.load_image('../assets/penguins.png')\n", "\n", "overlay = (scene * hv.Path([adultL, adultR, baby]) * hv.Path([baby]))\n", "overlay.opts(opts.Path(line_width=4))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A ``Path`` can also be used as a means to display a number of lines with the same sampling along the x-axis at once. If we initialize the ``Path`` with a tuple of x-coordinates and stacked y-coordinates, we can quickly view a number of lines at once. Here we will generate a number of random traces each slightly offset along the y-axis:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "N, NLINES = 100, 10\n", "paths = hv.Path((np.arange(N), np.random.rand(N, NLINES) + np.arange(NLINES)[np.newaxis, :]))\n", "paths2 = hv.Path((np.arange(N), np.random.rand(N, NLINES) + np.arange(NLINES)[np.newaxis, :]))\n", "\n", "overlay = paths * paths2\n", "overlay.opts(width=600)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For full documentation and the available style and plot options, use ``hv.help(hv.Path).``" ] } ], "metadata": { "language_info": { "name": "python", "pygments_lexer": "ipython3" } }, "nbformat": 4, "nbformat_minor": 2 }