visualization.ipynb

{
 "metadata": {
  "gist_id": "5223401",
  "name": "visualization"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#this is just for -pi %load_ext gist"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "javascript": [
        "\n",
        "\n",
        "/*\n",
        "Add the contents of this file to your custom.js\n",
        "for it to always be on.\n",
        "*/\n",
        "\n",
        "\n",
        "IPython.ext_update_gist_link = function(gist_id) {\n",
        "    \n",
        "    IPython.notebook.metadata.gist_id = gist_id;\n",
        "    var toolbar = IPython.toolbar.element;\n",
        "    var link = toolbar.find(\"a#nbviewer\");\n",
        "    if ( ! link.length ) {\n",
        "        link = $('<a id=\"nbviewer\" target=\"_blank\"/>');\n",
        "        toolbar.append(\n",
        "            $('<span id=\"nbviewer_span\"/>').append(link)\n",
        "        );\n",
        "    }\n",
        "    \n",
        "    link.attr(\"href\", \"http://nbviewer.ipython.org/\" + gist_id);\n",
        "    link.text(\"http://nbviewer.ipython.org/\" + gist_id);\n",
        "};\n",
        "\n",
        "IPython.ext_handle_gist_output = function(output_type, content) {\n",
        "    if (output_type != 'stream' || content['name'] != 'stdout') {\n",
        "        return;\n",
        "    }\n",
        "    var gist_id = jQuery.trim(content['data']);\n",
        "    if (! gist_id.match(/[A-Za-z0-9]+/g)) {\n",
        "        alert(\"Gist seems to have failed: \" + gist_id);\n",
        "        return;\n",
        "    }\n",
        "    IPython.ext_update_gist_link(gist_id);\n",
        "};\n",
        "\n",
        "IPython.ext_gist_notebook = function () {\n",
        "    var gist_id = IPython.notebook.metadata.gist_id || null;\n",
        "    var cmd = '_nbname = \"' + IPython.notebook.notebook_name + '.ipynb\"';\n",
        "    cmd = cmd + '\\nlines = !jist -p'\n",
        "    if (gist_id) {\n",
        "        cmd = cmd + ' -u ' + gist_id;\n",
        "    }\n",
        "    cmd = cmd + ' \"$_nbname\"';\n",
        "    cmd = cmd + '\\nprint lines[0].replace(\"https://gist.github.com\", \"\").replace(\"/\",\"\")';\n",
        "    IPython.notebook.kernel.execute(cmd, {'output' : IPython.ext_handle_gist_output});\n",
        "};\n",
        "\n",
        "setTimeout(function() {\n",
        "    if ($(\"#gist_notebook\").length == 0) {\n",
        "        IPython.toolbar.add_buttons_group([\n",
        "            {\n",
        "                'label'   : 'Share Notebook as gist',\n",
        "                'icon'    : 'ui-icon-share',\n",
        "                'callback': IPython.ext_gist_notebook,\n",
        "                'id'      : 'gist_notebook'\n",
        "            },\n",
        "        ])\n",
        "    }\n",
        "\n",
        "    if (IPython.notebook.metadata.gist_id) {\n",
        "        IPython.ext_update_gist_link(IPython.notebook.metadata.gist_id);\n",
        "    }\n",
        "}, 1000);\n",
        "\n"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Javascript at 0x1ee6490>"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Visualization\n",
      "==============\n",
      "\n",
      "I (Paul Ivanov) polled the class, and it seemed like people were unfamiliar with just basic plotting, so we started off with that."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Basic Plotting\n",
      "--------------\n",
      "\n",
      "I started off by explaining that, by default, matplotlib's pyplot interface is imported when we enable IPython's %pylab mode."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.kernel.zmq.pylab.backend_inline].\n",
        "For more information, type 'help(pylab)'.\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here's how you can do that in your python scripts (without IPython's pylab mode)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I opened up the Matplotlib website, and in particular, the Matplotlib Gallery...\n",
      "\n",
      "http://matplotlib.org/gallery.html"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<module 'matplotlib.pyplot' from '/home/pi/.local/lib/python2.7/site-packages/matplotlib-1.3.x-py2.7-linux-x86_64.egg/matplotlib/pyplot.pyc'>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We grabbed a link of some example code we found in the gallery, just to play with it interactively\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load http://matplotlib.org/mpl_examples/api/histogram_demo.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x, y = np.arange(10), np.sin(np.arange(10))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(x, y, 'ro')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "[<matplotlib.lines.Line2D at 0x5971c90>]"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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BwNDYtjuPKTNMFSwtAlNYY23tsBKTpJpAQE1er02JgPuPIgOmMOfAQNjxhP7+SU4CTByK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\ngg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x4cd1c90>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.scatter(x, y, s=np.cos(x)*100, c=)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "<matplotlib.collections.PathCollection at 0x6223490>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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pS/rr6+s1a9Ys/fWvf9Xu3bt10003SZKOHz+uO+64Q7/61a/8B+HyIwDgNHxJKADAGHxJ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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x5ac8c10>"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p = patches[0]\n",
      "p.get_facecolor()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 38,
       "text": [
        "(0.0, 0.0, 1.0, 1.0)"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "R, G, B, A"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p.set_facecolor('g')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "counts, locs, patches = plt.hist(np.random.randn(5000), bins=100)\n",
      "\n",
      "for x in range(25, 75):\n",
      "    p = patches[x]\n",
      "    p.set_facecolor('g')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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qr9c77vU1NTX+rx0OhxwORyRlAAAM5XK55HK5wr4uotD69NNP1dnZqSeffFLLli3T1q1b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\n/wB/SnVzKrlHhQAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x72da8d0>"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 42,
       "text": [
        "<matplotlib.patches.Rectangle at 0x7abcd90>"
       ]
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Paging through data\n",
      "--------"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This example shows us how to make changes to a plot based on keyboard input. This does not work if our matplotlib backend is set to inline, since that just generates static images. Set the backend to an interactive one (qt, tk, wx, or macosx)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab qt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Welcome to pylab, a matplotlib-based Python environment [backend: Qt4Agg].\n",
        "For more information, type 'help(pylab)'.\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load http://matplotlib.sourceforge.net/examples/event_handling/keypress_demo.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#!/usr/bin/env python\n",
      "\n",
      "\"\"\"\n",
      "Show how to connect to keypress events\n",
      "\"\"\"\n",
      "from __future__ import print_function\n",
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "import sys\n",
      "\n",
      "\n",
      "def press(event):\n",
      "    print('press', event.key)\n",
      "    sys.stdout.flush()\n",
      "    if event.key=='x':\n",
      "        visible = xl.get_visible()\n",
      "        xl.set_visible(not visible)\n",
      "        fig.canvas.draw()\n",
      "\n",
      "fig = plt.figure()\n",
      "ax = fig.add_subplot(111)\n",
      "\n",
      "fig.canvas.mpl_connect('key_press_event', press)\n",
      "\n",
      "ax.plot(np.random.rand(12), np.random.rand(12), 'go')\n",
      "xl = ax.set_xlabel('easy come, easy go')\n",
      "\n",
      "plt.show()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " x\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press alt\n",
        "press"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " alt\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press a\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press a\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press a\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press a\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press a\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press b\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press b\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press p\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press p\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press x\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press x\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press x\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press x\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "press alt\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now modify the example above to pan left and right the width of the current view using `,` and `.` keys"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(np.sin(np.arange(100)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "[<matplotlib.lines.Line2D at 0x3dc0d10>]"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load http://matplotlib.sourceforge.net/examples/event_handling/keypress_demo.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax = plt.gca()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax.get_xlim()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "(7.5219586089047414, 12.161979327136788)"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax.set_xlim(7, 20)\n",
      "plt.draw()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#!/usr/bin/env python\n",
      "\n",
      "\"\"\"\n",
      "Show how to connect to keypress events\n",
      "\"\"\"\n",
      "from __future__ import print_function\n",
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "\n",
      "\n",
      "def press(event):\n",
      "    x0, x1 = ax.get_xlim()\n",
      "    dx = x1 - x0\n",
      "    if event.key==',':\n",
      "        ax.set_xlim(x0-dx, x1-dx)\n",
      "        plt.draw()\n",
      "    if event.key=='.':\n",
      "        ax.set_xlim(x0+dx, x1+dx)\n",
      "        plt.draw()\n",
      "\n",
      "fig = plt.figure()\n",
      "ax = fig.add_subplot(111)\n",
      "\n",
      "fig.canvas.mpl_connect('key_press_event', press)\n",
      "\n",
      "ax.plot(np.sin(np.arange(100)), 'go--')\n",
      "\n",
      "\n",
      "plt.show()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "3D Slicer\n",
      "---------\n",
      "\n",
      "Here's some code I (pi) wrote to do basic, interactive orthogonal slicer.\n",
      "\n",
      "We will go through the code to understand the individual parts, running the next cell will create a file called `orthoslicer.py` on your machine. If you get an error, you are using at older version of IPython where the `%%file` magic was not available"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%file orthoslicer.py\n",
      "import matplotlib\n",
      "import matplotlib.pyplot as plt\n",
      "from matplotlib.image import AxesImage\n",
      "\n",
      "import numpy as np\n",
      "\n",
      "#  assuming the following layout\n",
      "#   <--  y  -->     <--  z  -->\n",
      "# ^ +---------+   ^ +---------+\n",
      "# | |         |   | |         |\n",
      "#   |         |     |         |\n",
      "# x |         |   x |         |\n",
      "#   |         |     |         |\n",
      "# | |         |   | |         |\n",
      "# v +---------+   v +---------+\n",
      "#\n",
      "#                   <--  z  -->\n",
      "#                 ^ +---------+\n",
      "#                 | |         |\n",
      "#                   |         |\n",
      "#                 y |         |\n",
      "#                   |         |\n",
      "#                 | |         |\n",
      "#                 v +---------+\n",
      "#\n",
      "\n",
      "class OrthoSlicer3D(object):\n",
      "    \"\"\"Orthogonal-plane slicer.\n",
      "\n",
      "    OrthoSlicer3d expects 3-dimensional data, and creates a figure with 3\n",
      "    axes for each slice orientation. Moving the mouse in any one axes will\n",
      "    select out the corresponding slices in the other two. Clicking the right\n",
      "    mouse button toggles mouse following and triggers a full redraw (to update\n",
      "    the ticks, for example). Scrolling up and down moves that slice up and\n",
      "    down. \n",
      "\n",
      "    Example\n",
      "    -------\n",
      "    import numpy as np\n",
      "    a = np.sin(np.linspace(0,np.pi,20))\n",
      "    b = np.sin(np.linspace(0,np.pi*5,20))\n",
      "    data = np.outer(a,b)[..., np.newaxis]*a\n",
      "\n",
      "    OrthoSlicer3D(data)\n",
      "\n",
      "    \"\"\"\n",
      "    def __init__(self, data, axes=None, aspect_ratio=np.array((1,1,1))):\n",
      "        \"\"\"\n",
      "        Parameters\n",
      "        ----------\n",
      "        data : ndarray (3d)\n",
      "            The data that will be displaced by the slicer\n",
      "        axes : mpl.Axes (3)\n",
      "            3 axes instances for the Z, Y, and X slices, or None (default)\n",
      "        aspect_ratio : ndarray (length 3)\n",
      "            stretch factors for X,Y,Z directions (default: 1,1,1)\n",
      "        \"\"\"\n",
      "        if axes is None:\n",
      "            fig = plt.figure()\n",
      "            x,y,z = data.shape  * aspect_ratio\n",
      "\n",
      "            maxw = float(z+y)\n",
      "            maxh = float(y+x)\n",
      "            zw = y / maxw\n",
      "            zh = x / maxh\n",
      "            yw = z / maxw\n",
      "\n",
      "            ax1 = fig.add_axes((0,  1.0-zh, zw,     zh))\n",
      "            ax2 = fig.add_axes((zw, 1.0-zh, yw,     zh))\n",
      "            ax3 = fig.add_axes((zw, 0.0   , yw, 1.0-zh))\n",
      "            axes = (ax1, ax2, ax3)\n",
      "        else:\n",
      "            ax1, ax2, ax3 = axes\n",
      "\n",
      "        self.data = data\n",
      "\n",
      "        kw = dict(vmin=data.min(), vmax=data.max(), picker=True,\n",
      "                aspect='auto')\n",
      "        im1 = ax1.imshow(data[...,0], **kw)\n",
      "        im2 = ax2.imshow(data[:,0,:], **kw)\n",
      "        im3 = ax3.imshow(data[0,...], **kw)\n",
      "\n",
      "        # idx will be used to slice in to the data with the appropriate\n",
      "        # slicing scheme\n",
      "        im1.idx = im2.idx = im3.idx = 0\n",
      "\n",
      "        # set the maximum dimensions for i%dim indexing\n",
      "        im1.size = data.shape[-1]\n",
      "        im2.size = data.shape[-2]\n",
      "        im3.size = data.shape[-3]\n",
      "\n",
      "        im1.get_slice = lambda i: (slice(None), slice(None), i)\n",
      "        im2.get_slice = lambda i: (slice(None), i, slice(None))\n",
      "        im3.get_slice = lambda i: (i, slice(None), slice(None))\n",
      "\n",
      "        # setup pairwise connections between the slice dimensions\n",
      "        im1.imx = im2\n",
      "        im1.imy = im3\n",
      "        im2.imx = im1\n",
      "        im2.imy = im3\n",
      "        im3.imx = im1\n",
      "        im3.imy = im2\n",
      "\n",
      "        self.toggle_update = True\n",
      "        self.figs = set([ax.figure for ax in axes])\n",
      "        for fig in self.figs:\n",
      "            #fig.canvas.mpl_connect('pick_event', self.on_pick)\n",
      "            fig.canvas.mpl_connect('motion_notify_event', self.on_pick)\n",
      "        plt.show()\n",
      "\n",
      "\n",
      "    def on_pick(self, event):\n",
      "        # Here we do a bit of a hack to make mousemovement events fit the mold\n",
      "        # of a pick event\n",
      "        if hasattr(event,'inaxes') and event.inaxes:\n",
      "            artist = event.inaxes.images[0]\n",
      "            me = event\n",
      "            me.button = 1 if self.toggle_update else 0\n",
      "        elif hasattr(event, 'artist'):\n",
      "            artist = event.artist\n",
      "            me = event.mouseevent\n",
      "        else:\n",
      "            return\n",
      "        if isinstance(artist, AxesImage):\n",
      "            im = artist\n",
      "            ax = artist.axes\n",
      "            imx,imy = im.imx, im.imy\n",
      "            if me.button == 1: # or self.toggle_update:\n",
      "                #if me.button == 1:\n",
      "                #    self.toggle_update = not self.toggle_update\n",
      "                x,y = np.round((me.xdata, me.ydata)).astype(int)\n",
      "                imx.set_data(self.data[imx.get_slice(x)])\n",
      "                imy.set_data(self.data[imy.get_slice(y)])\n",
      "                imx.idx = x\n",
      "                imy.idx = y\n",
      "                for i in imx, imy:\n",
      "                    ax = i.axes\n",
      "                    ax.draw_artist(i)\n",
      "                    ax.figure.canvas.blit(ax.bbox)\n",
      "                return\n",
      "            if me.button == 3:\n",
      "                self.toggle_update = not self.toggle_update\n",
      "                # the axes might be in different figures, redraw all of them\n",
      "                #for fig in self.figs:\n",
      "                #    fig.canvas.draw() # redraw the ticks which don't get blitted\n",
      "                plt.draw()\n",
      "                return\n",
      "            if me.button not in ('up', 'down'):\n",
      "                return\n",
      "            if me.button == 'up':\n",
      "                im.idx += 1\n",
      "            elif me.button == 'down':\n",
      "                im.idx -= 1\n",
      "            im.idx %= im.size\n",
      "            im.set_data(self.data[im.get_slice(im.idx)])\n",
      "            ax.draw_artist(im)\n",
      "            ax.figure.canvas.blit(ax.bbox)\n",
      "\n",
      "if __name__ == '__main__':\n",
      "    import numpy as np\n",
      "    a = np.sin(np.linspace(0,np.pi,20))\n",
      "    b = np.sin(np.linspace(0,np.pi*5,20))\n",
      "    data = np.outer(a,b)[..., np.newaxis]*a\n",
      "    # all slices\n",
      "    OrthoSlicer3D(data)\n",
      "\n",
      "    # broken out into three separate figures\n",
      "    f, ax1 = plt.subplots()\n",
      "    f, ax2 = plt.subplots()\n",
      "    f, ax3 = plt.subplots()\n",
      "    OrthoSlicer3D(data, axes=(ax1, ax2, ax3))\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Overwriting orthoslicer.py\n"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "run orthoslicer.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    }
   ],
   "metadata": {}
  }
 ]
}