Docs build of c0cd944cc456a061ce1deb8d46aa4514b72092af

.buildinfo

@@ -0,0 +1,4 @@
+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: fee21aba0ad35d7353946075a94d4ae9
+tags: 645f666f9bcd5a90fca523b33c5a78b7

_downloads/2dcollections3d.ipynb

@@ -0,0 +1,54 @@
+{
+  "metadata": {
+    "language_info": {
+      "codemirror_mode": {
+        "version": 3,
+        "name": "ipython"
+      },
+      "name": "python",
+      "pygments_lexer": "ipython3",
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "version": "3.5.2"
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3",
+      "language": "python"
+    }
+  },
+  "cells": [
+    {
+      "source": [
+        "%matplotlib inline"
+      ],
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "cell_type": "code",
+      "execution_count": null
+    },
+    {
+      "source": [
+        "\n# Plot 2D data on 3D plot\n\n\nDemonstrates using ax.plot's zdir keyword to plot 2D data on\nselective axes of a 3D plot.\n\n"
+      ],
+      "metadata": {},
+      "cell_type": "markdown"
+    },
+    {
+      "source": [
+        "from mpl_toolkits.mplot3d import Axes3D\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfig = plt.figure()\nax = fig.gca(projection='3d')\n\n# Plot a sin curve using the x and y axes.\nx = np.linspace(0, 1, 100)\ny = np.sin(x * 2 * np.pi) / 2 + 0.5\nax.plot(x, y, zs=0, zdir='z', label='curve in (x,y)')\n\n# Plot scatterplot data (20 2D points per colour) on the x and z axes.\ncolors = ('r', 'g', 'b', 'k')\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)\n\nx = np.random.sample(20 * len(colors))\ny = np.random.sample(20 * len(colors))\nc_list = []\nfor c in colors:\n    c_list.extend([c] * 20)\n# By using zdir='y', the y value of these points is fixed to the zs value 0\n# and the (x,y) points are plotted on the x and z axes.\nax.scatter(x, y, zs=0, zdir='y', c=c_list, label='points in (x,z)')\n\n# Make legend, set axes limits and labels\nax.legend()\nax.set_xlim(0, 1)\nax.set_ylim(0, 1)\nax.set_zlim(0, 1)\nax.set_xlabel('X')\nax.set_ylabel('Y')\nax.set_zlabel('Z')\n\n# Customize the view angle so it's easier to see that the scatter points lie\n# on the plane y=0\nax.view_init(elev=20., azim=-35)\n\nplt.show()"
+      ],
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "cell_type": "code",
+      "execution_count": null
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

_downloads/2dcollections3d.py

@@ -0,0 +1,50 @@
+"""
+=======================
+Plot 2D data on 3D plot
+=======================
+
+Demonstrates using ax.plot's zdir keyword to plot 2D data on
+selective axes of a 3D plot.
+"""
+
+from mpl_toolkits.mplot3d import Axes3D
+import numpy as np
+import matplotlib.pyplot as plt
+
+fig = plt.figure()
+ax = fig.gca(projection='3d')
+
+# Plot a sin curve using the x and y axes.
+x = np.linspace(0, 1, 100)
+y = np.sin(x * 2 * np.pi) / 2 + 0.5
+ax.plot(x, y, zs=0, zdir='z', label='curve in (x,y)')
+
+# Plot scatterplot data (20 2D points per colour) on the x and z axes.
+colors = ('r', 'g', 'b', 'k')
+
+# Fixing random state for reproducibility
+np.random.seed(19680801)
+
+x = np.random.sample(20 * len(colors))
+y = np.random.sample(20 * len(colors))
+c_list = []
+for c in colors:
+    c_list.extend([c] * 20)
+# By using zdir='y', the y value of these points is fixed to the zs value 0
+# and the (x,y) points are plotted on the x and z axes.
+ax.scatter(x, y, zs=0, zdir='y', c=c_list, label='points in (x,z)')
+
+# Make legend, set axes limits and labels
+ax.legend()
+ax.set_xlim(0, 1)
+ax.set_ylim(0, 1)
+ax.set_zlim(0, 1)
+ax.set_xlabel('X')
+ax.set_ylabel('Y')
+ax.set_zlabel('Z')
+
+# Customize the view angle so it's easier to see that the scatter points lie
+# on the plane y=0
+ax.view_init(elev=20., azim=-35)
+
+plt.show()

_downloads/3D.ipynb

@@ -0,0 +1,54 @@
+{
+  "metadata": {
+    "language_info": {
+      "codemirror_mode": {
+        "version": 3,
+        "name": "ipython"
+      },
+      "name": "python",
+      "pygments_lexer": "ipython3",
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "nbconvert_exporter": "python",
+      "version": "3.5.2"
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3",
+      "language": "python"
+    }
+  },
+  "cells": [
+    {
+      "source": [
+        "%matplotlib inline"
+      ],
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "cell_type": "code",
+      "execution_count": null
+    },
+    {
+      "source": [
+        "\n# Frontpage 3D example\n\n\nThis example reproduces the frontpage 3D example.\n\n\n"
+      ],
+      "metadata": {},
+      "cell_type": "markdown"
+    },
+    {
+      "source": [
+        "from mpl_toolkits.mplot3d import Axes3D\nfrom matplotlib import cbook\nfrom matplotlib import cm\nfrom matplotlib.colors import LightSource\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfilename = cbook.get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)\nwith np.load(filename) as dem:\n    z = dem['elevation']\n    nrows, ncols = z.shape\n    x = np.linspace(dem['xmin'], dem['xmax'], ncols)\n    y = np.linspace(dem['ymin'], dem['ymax'], nrows)\n    x, y = np.meshgrid(x, y)\n\nregion = np.s_[5:50, 5:50]\nx, y, z = x[region], y[region], z[region]\n\nfig, ax = plt.subplots(subplot_kw=dict(projection='3d'))\n\nls = LightSource(270, 45)\n# To use a custom hillshading mode, override the built-in shading and pass\n# in the rgb colors of the shaded surface calculated from \"shade\".\nrgb = ls.shade(z, cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')\nsurf = ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolors=rgb,\n                       linewidth=0, antialiased=False, shade=False)\nax.set_xticks([])\nax.set_yticks([])\nax.set_zticks([])\nfig.savefig(\"surface3d_frontpage.png\", dpi=25)  # results in 160x120 px image"
+      ],
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "cell_type": "code",
+      "execution_count": null
+    }
+  ],
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

_downloads/3D.py

@@ -0,0 +1,38 @@
+"""
+====================
+Frontpage 3D example
+====================
+
+This example reproduces the frontpage 3D example.
+
+"""
+from mpl_toolkits.mplot3d import Axes3D
+from matplotlib import cbook
+from matplotlib import cm
+from matplotlib.colors import LightSource
+import matplotlib.pyplot as plt
+import numpy as np
+
+filename = cbook.get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
+with np.load(filename) as dem:
+    z = dem['elevation']
+    nrows, ncols = z.shape
+    x = np.linspace(dem['xmin'], dem['xmax'], ncols)
+    y = np.linspace(dem['ymin'], dem['ymax'], nrows)
+    x, y = np.meshgrid(x, y)
+
+region = np.s_[5:50, 5:50]
+x, y, z = x[region], y[region], z[region]
+
+fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+
+ls = LightSource(270, 45)
+# To use a custom hillshading mode, override the built-in shading and pass
+# in the rgb colors of the shaded surface calculated from "shade".
+rgb = ls.shade(z, cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')
+surf = ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolors=rgb,
+                       linewidth=0, antialiased=False, shade=False)
+ax.set_xticks([])
+ax.set_yticks([])
+ax.set_zticks([])
+fig.savefig("surface3d_frontpage.png", dpi=25)  # results in 160x120 px image

_downloads/3d_bars.ipynb

@@ -0,0 +1,54 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "source": [
+        "%matplotlib inline"
+      ],
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Demo of 3D bar charts\n\n\nA basic demo of how to plot 3D bars with and without\nshading.\n\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "source": [
+        "import numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\n\n\n# setup the figure and axes\nfig = plt.figure(figsize=(8, 3))\nax1 = fig.add_subplot(121, projection='3d')\nax2 = fig.add_subplot(122, projection='3d')\n\n# fake data\n_x = np.arange(4)\n_y = np.arange(5)\n_xx, _yy = np.meshgrid(_x, _y)\nx, y = _xx.ravel(), _yy.ravel()\n\ntop = x + y\nbottom = np.zeros_like(top)\nwidth = depth = 1\n\nax1.bar3d(x, y, bottom, width, depth, top, shade=True)\nax1.set_title('Shaded')\n\nax2.bar3d(x, y, bottom, width, depth, top, shade=False)\nax2.set_title('Not Shaded')\n\nplt.show()"
+      ],
+      "outputs": []
+    }
+  ],
+  "nbformat_minor": 0,
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "version": "3.5.2",
+      "nbconvert_exporter": "python",
+      "mimetype": "text/x-python",
+      "codemirror_mode": {
+        "version": 3,
+        "name": "ipython"
+      },
+      "file_extension": ".py",
+      "pygments_lexer": "ipython3",
+      "name": "python"
+    }
+  },
+  "nbformat": 4
+}

_downloads/3d_bars.py

@@ -0,0 +1,37 @@
+"""
+=====================
+Demo of 3D bar charts
+=====================
+
+A basic demo of how to plot 3D bars with and without
+shading.
+
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+
+# setup the figure and axes
+fig = plt.figure(figsize=(8, 3))
+ax1 = fig.add_subplot(121, projection='3d')
+ax2 = fig.add_subplot(122, projection='3d')
+
+# fake data
+_x = np.arange(4)
+_y = np.arange(5)
+_xx, _yy = np.meshgrid(_x, _y)
+x, y = _xx.ravel(), _yy.ravel()
+
+top = x + y
+bottom = np.zeros_like(top)
+width = depth = 1
+
+ax1.bar3d(x, y, bottom, width, depth, top, shade=True)
+ax1.set_title('Shaded')
+
+ax2.bar3d(x, y, bottom, width, depth, top, shade=False)
+ax2.set_title('Not Shaded')
+
+plt.show()

_downloads/accented_text.ipynb

@@ -0,0 +1,54 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "source": [
+        "%matplotlib inline"
+      ],
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Using accented text in matplotlib\n\n\nMatplotlib supports accented characters via TeX mathtext or unicode.\n\nUsing mathtext, the following accents are provided: \\hat, \\breve, \\grave, \\bar,\n\\acute, \\tilde, \\vec, \\dot, \\ddot.  All of them have the same syntax,\ne.g., to make an overbar you do \\bar{o} or to make an o umlaut you do\n\\ddot{o}.  The shortcuts are also provided, e.g.,: \\\"o \\'e \\`e \\~n \\.x\n\\^y\n\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "source": [
+        "from __future__ import unicode_literals\nimport matplotlib.pyplot as plt\n\n# Mathtext demo\nfig, ax = plt.subplots()\nax.plot(range(10))\nax.set_title(r'$\\ddot{o}\\acute{e}\\grave{e}\\hat{O}'\n             r'\\breve{i}\\bar{A}\\tilde{n}\\vec{q}$', fontsize=20)\n\n# Shorthand is also supported and curly braces are optional\nax.set_xlabel(r\"\"\"$\\\"o\\ddot o \\'e\\`e\\~n\\.x\\^y$\"\"\", fontsize=20)\nax.text(4, 0.5, r\"$F=m\\ddot{x}$\")\nfig.tight_layout()\n\n# Unicode demo\nfig, ax = plt.subplots()\nax.set_title(\"GISCARD CHAHUT\u00c9 \u00c0 L'ASSEMBL\u00c9E\")\nax.set_xlabel(\"LE COUP DE D\u00c9 DE DE GAULLE\")\nax.set_ylabel('Andr\u00e9 was here!')\nax.text(0.2, 0.8, 'Institut f\u00fcr Festk\u00f6rperphysik', rotation=45)\nax.text(0.4, 0.2, 'AVA (check kerning)')\n\nplt.show()"
+      ],
+      "outputs": []
+    }
+  ],
+  "nbformat_minor": 0,
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "version": "3.5.2",
+      "nbconvert_exporter": "python",
+      "mimetype": "text/x-python",
+      "codemirror_mode": {
+        "version": 3,
+        "name": "ipython"
+      },
+      "file_extension": ".py",
+      "pygments_lexer": "ipython3",
+      "name": "python"
+    }
+  },
+  "nbformat": 4
+}

_downloads/accented_text.py

@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+r"""
+=================================
+Using accented text in matplotlib
+=================================
+
+Matplotlib supports accented characters via TeX mathtext or unicode.
+
+Using mathtext, the following accents are provided: \hat, \breve, \grave, \bar,
+\acute, \tilde, \vec, \dot, \ddot.  All of them have the same syntax,
+e.g., to make an overbar you do \bar{o} or to make an o umlaut you do
+\ddot{o}.  The shortcuts are also provided, e.g.,: \"o \'e \`e \~n \.x
+\^y
+
+"""
+from __future__ import unicode_literals
+import matplotlib.pyplot as plt
+
+# Mathtext demo
+fig, ax = plt.subplots()
+ax.plot(range(10))
+ax.set_title(r'$\ddot{o}\acute{e}\grave{e}\hat{O}'
+             r'\breve{i}\bar{A}\tilde{n}\vec{q}$', fontsize=20)
+
+# Shorthand is also supported and curly braces are optional
+ax.set_xlabel(r"""$\"o\ddot o \'e\`e\~n\.x\^y$""", fontsize=20)
+ax.text(4, 0.5, r"$F=m\ddot{x}$")
+fig.tight_layout()
+
+# Unicode demo
+fig, ax = plt.subplots()
+ax.set_title("GISCARD CHAHUTÉ À L'ASSEMBLÉE")
+ax.set_xlabel("LE COUP DE DÉ DE DE GAULLE")
+ax.set_ylabel('André was here!')
+ax.text(0.2, 0.8, 'Institut für Festkörperphysik', rotation=45)
+ax.text(0.4, 0.2, 'AVA (check kerning)')
+
+plt.show()