Displaying activity in IPython notebook

gistfile1.txt

{
 "metadata": {
  "name": "Better Activity 2"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import topo"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%run -i ./examples/gcal.ty"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "topo.sim.V1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "LISSOM(allow_skip_non_responding_units=True, apply_output_fns=True, beginning_of_iteration=[], continuous_learning=False, end_of_iteration=[], joint_norm_fn=<function compute_joint_norm_totals_opt at 0x389b758>, layout_location=(300, 100), mask=SheetMask(name='SheetMask00102', print_level=100), mask_init_time=5, measure_maps=True, name='V1', nominal_bounds=BoundingBox(radius=0.5), nominal_density=48.0, output_fns=[HomeostaticResponse(learning_rate=0.01, linear_slope=1.0, name='HomeostaticResponse00100', noise_magnitude=0.10000000000000001, norm_value=None, period=1.0, plastic=True, print_level=100, randomized_init=False, seed=42, smoothing=0.99099999999999999, t_init=0.14999999999999999, target_activity=0.024)], plastic=True, post_initialization_weights_output_fns=[], precedence=0.59999999999999998, print_level=100, row_precedence=0.5, strict_tsettle=None, tsettle=16)"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def imact(objs, size=1.0, show_axes=False, label_name=True, norm_type=0, fig={},\n",
      "              show={'interpolation':'nearest', 'cmap':plt.cm.gray}):\n",
      "    \"\"\"\n",
      "    Displays the activity array of the given list of objects in row format.\n",
      "\n",
      "    size:       An overall size factor.\n",
      "    show_axes:  Whether or not to show axes for each subplot.\n",
      "    label_name: Show the object name above the subplot\n",
      "    norm_type:  0:No normalization, 1:Individually, 2: Together.\n",
      "\n",
      "    fig:  Extra kwargs for the pyplot figure.\n",
      "    show: Extra kwargs for imshow. Note: norm will override norm_type if set.\n",
      "    \"\"\"\n",
      "\n",
      "    fig = plt.figure(*fig)\n",
      "    (width, height) = fig.get_figwidth(), fig.get_figheight()\n",
      "    fig.set_figwidth(width*size)\n",
      "    fig.set_figheight(height*size)\n",
      "    \n",
      "    if norm==1:\n",
      "        show= dict({'norm':matplotlib.colors.Normalize()}, **show)\n",
      "    if norm==2:\n",
      "        activities = [obj.activity for obj in objs]\n",
      "        vmax = min(act.max() for act in activities)\n",
      "        vmin = min(act.min() for act in activities)\n",
      "        show= dict({'norm':matplotlib.colors.Normalize(vmin=vmin, vmax=vmax)}, **show)\n",
      "\n",
      "    plot_num = len(objs)\n",
      "    for (i, obj) in enumerate(objs):\n",
      "        ax = plt.subplot(1,plot_num,i)\n",
      "        if label_name: plt.title(obj.name)\n",
      "        if not show_axes:\n",
      "            ax.yaxis.set_visible(False)\n",
      "            ax.xaxis.set_visible(False)\n",
      "        imshow(obj.activity, **show)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "topo.sim.run(1)\n",
      "imact([topo.sim.V1,topo.sim.Retina])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "topo.sim."
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}