many important updates and fixes

Author: Qwlouse

Create Animations.ipynb

@@ -0,0 +1,117 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import h5py\n",
+    "import pickle\n",
+    "from matplotlib.colors import hsv_to_rgb\n",
+    "import numpy as np\n",
+    "from dae import ex\n",
+    "import os.path"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# run a longer (30 iterations) evaluation for visualization\n",
+    "datasets = {\n",
+    "    'bars': 12, \n",
+    "    'corners': 5,\n",
+    "    'shapes': 3,\n",
+    "    'multi_mnist': 3,\n",
+    "    'mnist_shape': 2,\n",
+    "    'simple_superpos':2\n",
+    "}\n",
+    "nr_iters = 30\n",
+    "nrows = 10\n",
+    "ncols = 12\n",
+    "\n",
+    "\n",
+    "\n",
+    "for ds, k in datasets.items():\n",
+    "    results_filename = 'Results/{}_{}_{}.pickle'.format(ds, nr_iters, k)\n",
+    "    animation_dir = 'animations/{}'.format(ds)\n",
+    "    if not os.path.exists(animation_dir):\n",
+    "        os.makedirs(animation_dir)\n",
+    "    \n",
+    "    ex.run_command('evaluate', config_updates={\n",
+    "               'dataset.name': ds,\n",
+    "               'net_filename': 'Networks/best_{}_dae.h5'.format(ds),\n",
+    "               'em.k': k,\n",
+    "               'em.nr_iters': 30,\n",
+    "               'em.dump_results': results_filename,\n",
+    "               'seed': 42})    \n",
+    "    \n",
+    "    with h5py.File('/home/greff/Datasets/{}.h5'.format(ds)) as f:\n",
+    "        true_groups = f['test']['groups'][:]\n",
+    "    with open(results_filename, 'rb') as f:\n",
+    "        scores, likelihoods, results = pickle.load(f)\n",
+    "    \n",
+    "    if results.shape[-1] != 3:\n",
+    "        nr_colors = results.shape[-1]\n",
+    "        hsv_colors = np.ones((nr_colors, 3))\n",
+    "        hsv_colors[:, 0] = (np.linspace(0, 1, nr_colors, endpoint=False) + 2/3) % 1.0\n",
+    "        color_conv = hsv_to_rgb(hsv_colors)\n",
+    "        results = results.reshape(-1, nr_colors).dot(color_conv).reshape(results.shape[:-1] + (3,))\n",
+    "    \n",
+    "    for it in range(nr_iters+1):\n",
+    "        fig, axes = plt.subplots(nrows=nrows, ncols=ncols, figsize=(ncols, nrows))\n",
+    "        for r in range(nrows):\n",
+    "            for c in range(ncols):\n",
+    "                axes[r, c].imshow(results[ncols*r + c, it, 0, :, :, 0, :], interpolation='nearest')\n",
+    "                axes[r, c].set_xticks([])\n",
+    "                axes[r, c].set_yticks([])\n",
+    "        plt.subplots_adjust(wspace=0, hspace=0)\n",
+    "        fig.savefig(animation_dir + '/img_{:02d}.png'.format(it), bbox_inches='tight', pad_inches=0, dpi=72.26)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from subprocess import call\n",
+    "\n",
+    "for ds in datasets:\n",
+    "    call(['convert', '-delay', '10', '-loop', '0', 'animations/{}/*.png'.format(ds), 'animations/{}.gif'.format(ds)])\n"
+   ]
+  }
+ ],
+ "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": "3.4.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}