added 2.2.5 docs

Author: tacaswell

2.2.5/Matplotlib.pdf

@@ -0,0 +1,54 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "%matplotlib inline"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Axis Direction Demo Step01\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\nimport mpl_toolkits.axisartist as axisartist\n\n\ndef setup_axes(fig, rect):\n    ax = axisartist.Subplot(fig, rect)\n    fig.add_axes(ax)\n\n    ax.set_ylim(-0.1, 1.5)\n    ax.set_yticks([0, 1])\n\n    ax.axis[:].set_visible(False)\n\n    ax.axis[\"x\"] = ax.new_floating_axis(1, 0.5)\n    ax.axis[\"x\"].set_axisline_style(\"->\", size=1.5)\n\n    return ax\n\n\nfig = plt.figure(figsize=(3, 2.5))\nfig.subplots_adjust(top=0.8)\nax1 = setup_axes(fig, \"111\")\n\nax1.axis[\"x\"].set_axis_direction(\"left\")\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": "3.8.1"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

2.2.5/_downloads/001a0398aba5436bf44cc545a5581e7d/axis_direction_demo_step01.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# Simple Axesgrid2\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1 import ImageGrid\n\n\ndef get_demo_image():\n    import numpy as np\n    from matplotlib.cbook import get_sample_data\n    f = get_sample_data(\"axes_grid/bivariate_normal.npy\", asfileobj=False)\n    z = np.load(f)\n    # z is a numpy array of 15x15\n    return z, (-3, 4, -4, 3)\n\nF = plt.figure(1, (5.5, 3.5))\ngrid = ImageGrid(F, 111,  # similar to subplot(111)\n                 nrows_ncols=(1, 3),\n                 axes_pad=0.1,\n                 add_all=True,\n                 label_mode=\"L\",\n                 )\n\nZ, extent = get_demo_image()  # demo image\n\nim1 = Z\nim2 = Z[:, :10]\nim3 = Z[:, 10:]\nvmin, vmax = Z.min(), Z.max()\nfor i, im in enumerate([im1, im2, im3]):\n    ax = grid[i]\n    ax.imshow(im, origin=\"lower\", vmin=vmin,\n              vmax=vmax, interpolation=\"nearest\")\n\nplt.draw()\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": "3.8.1"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

2.2.5/_downloads/005513053d53651f2ffe511840ceece5/simple_axesgrid2.ipynb

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+"""
+=======================================
+Custom hillshading in a 3D surface plot
+=======================================
+
+Demonstrates using custom hillshading in a 3D surface plot.
+"""
+
+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
+
+# Load and format data
+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]
+
+# Set up plot
+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)
+
+plt.show()

2.2.5/_downloads/009bf417d97f3090a82134095e2af059/custom_shaded_3d_surface.py

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+"""
+=============
+QuadMesh Demo
+=============
+
+`~.axes.Axes.pcolormesh` uses a `~matplotlib.collections.QuadMesh`,
+a faster generalization of `~.axes.Axes.pcolor`, but with some restrictions.
+
+This demo illustrates a bug in quadmesh with masked data.
+"""
+
+import copy
+
+from matplotlib import cm, colors, pyplot as plt
+import numpy as np
+
+n = 12
+x = np.linspace(-1.5, 1.5, n)
+y = np.linspace(-1.5, 1.5, n * 2)
+X, Y = np.meshgrid(x, y)
+Qx = np.cos(Y) - np.cos(X)
+Qz = np.sin(Y) + np.sin(X)
+Z = np.sqrt(X**2 + Y**2) / 5
+Z = (Z - Z.min()) / (Z.max() - Z.min())
+
+# The color array can include masked values.
+Zm = np.ma.masked_where(np.abs(Qz) < 0.5 * np.max(Qz), Z)
+
+fig, axs = plt.subplots(nrows=1, ncols=3)
+axs[0].pcolormesh(Qx, Qz, Z, shading='gouraud')
+axs[0].set_title('Without masked values')
+
+# You can control the color of the masked region. We copy the default colormap
+# before modifying it.
+cmap = copy.copy(cm.get_cmap(plt.rcParams['image.cmap']))
+cmap.set_bad('y', 1.0)
+axs[1].pcolormesh(Qx, Qz, Zm, shading='gouraud', cmap=cmap)
+axs[1].set_title('With masked values')
+
+# Or use the default, which is transparent.
+axs[2].pcolormesh(Qx, Qz, Zm, shading='gouraud')
+axs[2].set_title('With masked values')
+
+fig.tight_layout()
+plt.show()
+
+#############################################################################
+#
+# ------------
+#
+# References
+# """"""""""
+#
+# The use of the following functions and methods is shown in this example:
+
+import matplotlib
+matplotlib.axes.Axes.pcolormesh
+matplotlib.pyplot.pcolormesh

2.2.5/_downloads/00d16fb53a414217c5b2c46c5561d6dd/quadmesh_demo.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# Filling the area between lines\n\n\nThis example shows how to use ``fill_between`` to color between lines based on\nuser-defined logic.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\nimport numpy as np\n\nx = np.arange(0.0, 2, 0.01)\ny1 = np.sin(2 * np.pi * x)\ny2 = 1.2 * np.sin(4 * np.pi * x)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "fig, (ax1, ax2, ax3) = plt.subplots(3, 1, sharex=True)\n\nax1.fill_between(x, 0, y1)\nax1.set_ylabel('between y1 and 0')\n\nax2.fill_between(x, y1, 1)\nax2.set_ylabel('between y1 and 1')\n\nax3.fill_between(x, y1, y2)\nax3.set_ylabel('between y1 and y2')\nax3.set_xlabel('x')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Now fill between y1 and y2 where a logical condition is met.  Note\nthis is different than calling\n``fill_between(x[where], y1[where], y2[where] ...)``\nbecause of edge effects over multiple contiguous regions.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "fig, (ax, ax1) = plt.subplots(2, 1, sharex=True)\nax.plot(x, y1, x, y2, color='black')\nax.fill_between(x, y1, y2, where=y2 >= y1, facecolor='green', interpolate=True)\nax.fill_between(x, y1, y2, where=y2 <= y1, facecolor='red', interpolate=True)\nax.set_title('fill between where')\n\n# Test support for masked arrays.\ny2 = np.ma.masked_greater(y2, 1.0)\nax1.plot(x, y1, x, y2, color='black')\nax1.fill_between(x, y1, y2, where=y2 >= y1,\n                 facecolor='green', interpolate=True)\nax1.fill_between(x, y1, y2, where=y2 <= y1,\n                 facecolor='red', interpolate=True)\nax1.set_title('Now regions with y2>1 are masked')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "This example illustrates a problem; because of the data\ngridding, there are undesired unfilled triangles at the crossover\npoints.  A brute-force solution would be to interpolate all\narrays to a very fine grid before plotting.\n\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Use transforms to create axes spans where a certain condition is satisfied:\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "fig, ax = plt.subplots()\ny = np.sin(4 * np.pi * x)\nax.plot(x, y, color='black')\n\n# use data coordinates for the x-axis and the axes coordinates for the y-axis\nimport matplotlib.transforms as mtransforms\ntrans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes)\ntheta = 0.9\nax.axhline(theta, color='green', lw=2, alpha=0.5)\nax.axhline(-theta, color='red', lw=2, alpha=0.5)\nax.fill_between(x, 0, 1, where=y > theta,\n                facecolor='green', alpha=0.5, transform=trans)\nax.fill_between(x, 0, 1, where=y < -theta,\n                facecolor='red', alpha=0.5, transform=trans)\n\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": "3.8.1"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}