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‎3.6.0/Matplotlib.pdf

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‎3.6.0/_downloads/0017d0c84e03d6c5e463e23d8e570671/line_collection.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n# Line Collection\n\nPlotting lines with Matplotlib.\n\n`~matplotlib.collections.LineCollection` allows one to plot multiple\nlines on a figure. Below we show off some of its properties.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\nfrom matplotlib.collections import LineCollection\nfrom matplotlib import colors as mcolors\n\nimport numpy as np\n\n# In order to efficiently plot many lines in a single set of axes,\n# Matplotlib has the ability to add the lines all at once. Here is a\n# simple example showing how it is done.\n\nx = np.arange(100)\n# Here are many sets of y to plot vs. x\nys = x[:50, np.newaxis] + x[np.newaxis, :]\n\nsegs = np.zeros((50, 100, 2))\nsegs[:, :, 1] = ys\nsegs[:, :, 0] = x\n\n# Mask some values to test masked array support:\nsegs = np.ma.masked_where((segs > 50) & (segs < 60), segs)\n\n# We need to set the plot limits.\nfig, ax = plt.subplots()\nax.set_xlim(x.min(), x.max())\nax.set_ylim(ys.min(), ys.max())\n\n# *colors* is sequence of rgba tuples.\n# *linestyle* is a string or dash tuple. Legal string values are\n# solid|dashed|dashdot|dotted. The dash tuple is (offset, onoffseq) where\n# onoffseq is an even length tuple of on and off ink in points. If linestyle\n# is omitted, 'solid' is used.\n# See `matplotlib.collections.LineCollection` for more information.\ncolors = [mcolors.to_rgba(c)\n for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]\n\nline_segments = LineCollection(segs, linewidths=(0.5, 1, 1.5, 2),\n colors=colors, linestyle='solid')\nax.add_collection(line_segments)\nax.set_title('Line collection with masked arrays')\nplt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In order to efficiently plot many lines in a single set of axes,\nMatplotlib has the ability to add the lines all at once. Here is a\nsimple example showing how it is done.\n\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"N = 50\nx = np.arange(N)\n# Here are many sets of y to plot vs. x\nys = [x + i for i in x]\n\n# We need to set the plot limits, they will not autoscale\nfig, ax = plt.subplots()\nax.set_xlim(np.min(x), np.max(x))\nax.set_ylim(np.min(ys), np.max(ys))\n\n# colors is sequence of rgba tuples\n# linestyle is a string or dash tuple. Legal string values are\n# solid|dashed|dashdot|dotted. The dash tuple is (offset, onoffseq)\n# where onoffseq is an even length tuple of on and off ink in points.\n# If linestyle is omitted, 'solid' is used\n# See `matplotlib.collections.LineCollection` for more information\n\n# Make a sequence of (x, y) pairs.\nline_segments = LineCollection([np.column_stack([x, y]) for y in ys],\n linewidths=(0.5, 1, 1.5, 2),\n linestyles='solid')\nline_segments.set_array(x)\nax.add_collection(line_segments)\naxcb = fig.colorbar(line_segments)\naxcb.set_label('Line Number')\nax.set_title('Line Collection with mapped colors')\nplt.sci(line_segments) # This allows interactive changing of the colormap.\nplt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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".. admonition:: References\n\n The use of the following functions, methods, classes and modules is shown\n in this example:\n\n - `matplotlib.collections`\n - `matplotlib.collections.LineCollection`\n - `matplotlib.cm.ScalarMappable.set_array`\n - `matplotlib.axes.Axes.add_collection`\n - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`\n - `matplotlib.pyplot.sci`\n\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

‎3.6.0/_downloads/00c94fd2ec27d6cef4b040acefbf730d/hyperlinks_sgskip.py

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"""
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==========
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Hyperlinks
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==========
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This example demonstrates how to set a hyperlinks on various kinds of elements.
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This currently only works with the SVG backend.
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"""
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import numpy as np
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import matplotlib.cm as cm
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import matplotlib.pyplot as plt
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###############################################################################
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fig = plt.figure()
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s = plt.scatter([1, 2, 3], [4, 5, 6])
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s.set_urls(['https://www.bbc.com/news', 'https://www.google.com/', None])
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fig.savefig('scatter.svg')
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###############################################################################
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fig = plt.figure()
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delta = 0.025
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x = y = np.arange(-3.0, 3.0, delta)
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X, Y = np.meshgrid(x, y)
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Z1 = np.exp(-X**2 - Y**2)
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Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
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Z = (Z1 - Z2) * 2
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im = plt.imshow(Z, interpolation='bilinear', cmap=cm.gray,
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origin='lower', extent=[-3, 3, -3, 3])
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im.set_url('https://www.google.com/')
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fig.savefig('image.svg')

‎3.6.0/_downloads/00f7f20b47c4afdb8cf00a246bc6af53/animation_demo.py

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"""
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================
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pyplot animation
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================
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Generating an animation by calling `~.pyplot.pause` between plotting commands.
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The method shown here is only suitable for simple, low-performance use. For
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more demanding applications, look at the :mod:`.animation` module and the
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examples that use it.
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Note that calling `time.sleep` instead of `~.pyplot.pause` would *not* work.
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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np.random.seed(19680801)
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data = np.random.random((50, 50, 50))
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fig, ax = plt.subplots()
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for i, img in enumerate(data):
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ax.clear()
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ax.imshow(img)
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ax.set_title(f"frame {i}")
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# Note that using time.sleep does *not* work here!
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plt.pause(0.1)

‎3.6.0/_downloads/00fb9b6278ae3996d0eda53a7198ae42/hatch_style_reference.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n# Hatch style reference\n\nHatches can be added to most polygons in Matplotlib, including `~.Axes.bar`,\n`~.Axes.fill_between`, `~.Axes.contourf`, and children of `~.patches.Polygon`.\nThey are currently supported in the PS, PDF, SVG, OSX, and Agg backends. The WX\nand Cairo backends do not currently support hatching.\n\nSee also :doc:`/gallery/images_contours_and_fields/contourf_hatching` for\nan example using `~.Axes.contourf`, and\n:doc:`/gallery/shapes_and_collections/hatch_demo` for more usage examples.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\nfrom matplotlib.patches import Rectangle\n\nfig, axs = plt.subplots(2, 5, constrained_layout=True, figsize=(6.4, 3.2))\n\nhatches = ['/', '\\\\', '|', '-', '+', 'x', 'o', 'O', '.', '*']\n\n\ndef hatches_plot(ax, h):\n ax.add_patch(Rectangle((0, 0), 2, 2, fill=False, hatch=h))\n ax.text(1, -0.5, f\"' {h} '\", size=15, ha=\"center\")\n ax.axis('equal')\n ax.axis('off')\n\nfor ax, h in zip(axs.flat, hatches):\n hatches_plot(ax, h)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Hatching patterns can be repeated to increase the density.\n\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"fig, axs = plt.subplots(2, 5, constrained_layout=True, figsize=(6.4, 3.2))\n\nhatches = ['//', '\\\\\\\\', '||', '--', '++', 'xx', 'oo', 'OO', '..', '**']\n\nfor ax, h in zip(axs.flat, hatches):\n hatches_plot(ax, h)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Hatching patterns can be combined to create additional patterns.\n\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"fig, axs = plt.subplots(2, 5, constrained_layout=True, figsize=(6.4, 3.2))\n\nhatches = ['/o', '\\\\|', '|*', '-\\\\', '+o', 'x*', 'o-', 'O|', 'O.', '*-']\n\nfor ax, h in zip(axs.flat, hatches):\n hatches_plot(ax, h)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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".. admonition:: References\n\n The use of the following functions, methods, classes and modules is shown\n in this example:\n\n - `matplotlib.patches`\n - `matplotlib.patches.Rectangle`\n - `matplotlib.axes.Axes.add_patch`\n - `matplotlib.axes.Axes.text`\n\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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