deploy 3.1.0 docs

Author: tacaswell

3.1.0/Matplotlib.tex

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Scatter Star Poly\n\n\nCreate multiple scatter plots with different\nstar symbols.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\nimport matplotlib.pyplot as plt\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\n\nx = np.random.rand(10)\ny = np.random.rand(10)\nz = np.sqrt(x**2 + y**2)\n\nplt.subplot(321)\nplt.scatter(x, y, s=80, c=z, marker=\">\")\n\nplt.subplot(322)\nplt.scatter(x, y, s=80, c=z, marker=(5, 0))\n\nverts = np.array([[-1, -1], [1, -1], [1, 1], [-1, -1]])\nplt.subplot(323)\nplt.scatter(x, y, s=80, c=z, marker=verts)\n\nplt.subplot(324)\nplt.scatter(x, y, s=80, c=z, marker=(5, 1))\n\nplt.subplot(325)\nplt.scatter(x, y, s=80, c=z, marker='+')\n\nplt.subplot(326)\nplt.scatter(x, y, s=80, c=z, marker=(5, 2))\n\nplt.show()"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.7.3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

3.1.0/_downloads/00092e8501d7b746e7fd736473feb0f6/scatter_star_poly.ipynb

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+"""
+=======================================
+Different ways of specifying error bars
+=======================================
+
+Errors can be specified as a constant value (as shown in
+`errorbar_demo.py`). However, this example demonstrates
+how they vary by specifying arrays of error values.
+
+If the raw ``x`` and ``y`` data have length N, there are two options:
+
+Array of shape (N,):
+    Error varies for each point, but the error values are
+    symmetric (i.e. the lower and upper values are equal).
+
+Array of shape (2, N):
+    Error varies for each point, and the lower and upper limits
+    (in that order) are different (asymmetric case)
+
+In addition, this example demonstrates how to use log
+scale with error bars.
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+# example data
+x = np.arange(0.1, 4, 0.5)
+y = np.exp(-x)
+
+# example error bar values that vary with x-position
+error = 0.1 + 0.2 * x
+
+fig, (ax0, ax1) = plt.subplots(nrows=2, sharex=True)
+ax0.errorbar(x, y, yerr=error, fmt='-o')
+ax0.set_title('variable, symmetric error')
+
+# error bar values w/ different -/+ errors that
+# also vary with the x-position
+lower_error = 0.4 * error
+upper_error = error
+asymmetric_error = [lower_error, upper_error]
+
+ax1.errorbar(x, y, xerr=asymmetric_error, fmt='o')
+ax1.set_title('variable, asymmetric error')
+ax1.set_yscale('log')
+plt.show()

3.1.0/_downloads/0019310e9444a709ad98db6ee976416e/errorbar_features.py

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Agg Buffer\n\n\nUse backend agg to access the figure canvas as an RGB string and then\nconvert it to an array and pass it to Pillow for rendering.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\n\nfrom matplotlib.backends.backend_agg import FigureCanvasAgg\nimport matplotlib.pyplot as plt\n\nplt.plot([1, 2, 3])\n\ncanvas = plt.get_current_fig_manager().canvas\n\nagg = canvas.switch_backends(FigureCanvasAgg)\nagg.draw()\ns, (width, height) = agg.print_to_buffer()\n\n# Convert to a NumPy array.\nX = np.frombuffer(s, np.uint8).reshape((height, width, 4))\n\n# Pass off to PIL.\nfrom PIL import Image\nim = Image.frombytes(\"RGBA\", (width, height), s)\n\n# Uncomment this line to display the image using ImageMagick's `display` tool.\n# im.show()"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.7.3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

3.1.0/_downloads/002dd88353c81f8ead8c49d917e79775/agg_buffer.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Animated line plot\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.animation as animation\n\nfig, ax = plt.subplots()\n\nx = np.arange(0, 2*np.pi, 0.01)\nline, = ax.plot(x, np.sin(x))\n\n\ndef init():  # only required for blitting to give a clean slate.\n    line.set_ydata([np.nan] * len(x))\n    return line,\n\n\ndef animate(i):\n    line.set_ydata(np.sin(x + i / 100))  # update the data.\n    return line,\n\n\nani = animation.FuncAnimation(\n    fig, animate, init_func=init, interval=2, blit=True, save_count=50)\n\n# To save the animation, use e.g.\n#\n# ani.save(\"movie.mp4\")\n#\n# or\n#\n# from matplotlib.animation import FFMpegWriter\n# writer = FFMpegWriter(fps=15, metadata=dict(artist='Me'), bitrate=1800)\n# ani.save(\"movie.mp4\", writer=writer)\n\nplt.show()"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.7.3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

3.1.0/_downloads/0030ea2ba073910bfaeee3324b663fd9/simple_anim.ipynb

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+"""
+=================
+Fancytextbox Demo
+=================
+
+"""
+import matplotlib.pyplot as plt
+
+plt.text(0.6, 0.7, "eggs", size=50, rotation=30.,
+         ha="center", va="center",
+         bbox=dict(boxstyle="round",
+                   ec=(1., 0.5, 0.5),
+                   fc=(1., 0.8, 0.8),
+                   )
+         )
+
+plt.text(0.55, 0.6, "spam", size=50, rotation=-25.,
+         ha="right", va="top",
+         bbox=dict(boxstyle="square",
+                   ec=(1., 0.5, 0.5),
+                   fc=(1., 0.8, 0.8),
+                   )
+         )
+
+plt.show()

3.1.0/_downloads/01d2d618b11a1582ce766e85ecc828ee/fancytextbox_demo.py

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+"""
+===============================
+Resizing axes with tight layout
+===============================
+
+`~.figure.Figure.tight_layout` attempts to resize subplots in
+a figure so that there are no overlaps between axes objects and labels
+on the axes.
+
+See :doc:`/tutorials/intermediate/tight_layout_guide` for more details and
+:doc:`/tutorials/intermediate/constrainedlayout_guide` for an alternative.
+
+"""
+
+import matplotlib.pyplot as plt
+import itertools
+import warnings
+
+
+fontsizes = itertools.cycle([8, 16, 24, 32])
+
+
+def example_plot(ax):
+    ax.plot([1, 2])
+    ax.set_xlabel('x-label', fontsize=next(fontsizes))
+    ax.set_ylabel('y-label', fontsize=next(fontsizes))
+    ax.set_title('Title', fontsize=next(fontsizes))
+
+
+###############################################################################
+
+fig, ax = plt.subplots()
+example_plot(ax)
+plt.tight_layout()
+
+###############################################################################
+
+fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(nrows=2, ncols=2)
+example_plot(ax1)
+example_plot(ax2)
+example_plot(ax3)
+example_plot(ax4)
+plt.tight_layout()
+
+###############################################################################
+
+fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1)
+example_plot(ax1)
+example_plot(ax2)
+plt.tight_layout()
+
+###############################################################################
+
+fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)
+example_plot(ax1)
+example_plot(ax2)
+plt.tight_layout()
+
+###############################################################################
+
+fig, axes = plt.subplots(nrows=3, ncols=3)
+for row in axes:
+    for ax in row:
+        example_plot(ax)
+plt.tight_layout()
+
+###############################################################################
+
+fig = plt.figure()
+
+ax1 = plt.subplot(221)
+ax2 = plt.subplot(223)
+ax3 = plt.subplot(122)
+
+example_plot(ax1)
+example_plot(ax2)
+example_plot(ax3)
+
+plt.tight_layout()
+
+###############################################################################
+
+fig = plt.figure()
+
+ax1 = plt.subplot2grid((3, 3), (0, 0))
+ax2 = plt.subplot2grid((3, 3), (0, 1), colspan=2)
+ax3 = plt.subplot2grid((3, 3), (1, 0), colspan=2, rowspan=2)
+ax4 = plt.subplot2grid((3, 3), (1, 2), rowspan=2)
+
+example_plot(ax1)
+example_plot(ax2)
+example_plot(ax3)
+example_plot(ax4)
+
+plt.tight_layout()
+
+plt.show()
+
+###############################################################################
+
+fig = plt.figure()
+
+gs1 = fig.add_gridspec(3, 1)
+ax1 = fig.add_subplot(gs1[0])
+ax2 = fig.add_subplot(gs1[1])
+ax3 = fig.add_subplot(gs1[2])
+
+example_plot(ax1)
+example_plot(ax2)
+example_plot(ax3)
+
+gs1.tight_layout(fig, rect=[None, None, 0.45, None])
+
+gs2 = fig.add_gridspec(2, 1)
+ax4 = fig.add_subplot(gs2[0])
+ax5 = fig.add_subplot(gs2[1])
+
+example_plot(ax4)
+example_plot(ax5)
+
+with warnings.catch_warnings():
+    # gs2.tight_layout cannot handle the subplots from the first gridspec
+    # (gs1), so it will raise a warning. We are going to match the gridspecs
+    # manually so we can filter the warning away.
+    warnings.simplefilter("ignore", UserWarning)
+    gs2.tight_layout(fig, rect=[0.45, None, None, None])
+
+# now match the top and bottom of two gridspecs.
+top = min(gs1.top, gs2.top)
+bottom = max(gs1.bottom, gs2.bottom)
+
+gs1.update(top=top, bottom=bottom)
+gs2.update(top=top, bottom=bottom)
+
+plt.show()
+
+#############################################################################
+#
+# ------------
+#
+# References
+# """"""""""
+#
+# The use of the following functions and methods is shown in this example:
+
+import matplotlib
+matplotlib.pyplot.tight_layout
+matplotlib.figure.Figure.tight_layout
+matplotlib.figure.Figure.add_gridspec
+matplotlib.figure.Figure.add_subplot
+matplotlib.pyplot.subplot2grid