update code to work with python3

facebookresearch · Mar 18, 2017 · 1f976fa · 1f976fa
1 parent ef74076
commit 1f976fa
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Showing 6 changed files with 137 additions and 124 deletions.
diff --git a/examples/dense_matrix.ipynb b/examples/dense_matrix.ipynb
@@ -46,7 +46,7 @@
    "outputs": [],
    "source": [
     "# make sure you run 'python setup.py install' first!\n",
-    "import pysparnn\n",
+    "import pysparnn.cluster_index as ci\n",
     "import pysparnn.matrix_distance"
    ]
   },
@@ -63,7 +63,7 @@
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
@@ -94,25 +94,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/spencebeecher/anaconda2/lib/python2.7/site-packages/pysparnn/matrix_distance.py:189: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "  magnitude = 1.0 / (a_root_sum_square * self.matrix_root_sum_square)\n"
+     ]
+    }
+   ],
    "source": [
-    "cp = pysparnn.MultiClusterIndex(train_features, data_to_return)"
+    "cp = ci.MultiClusterIndex(train_features, data_to_return)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/spencebeecher/anaconda2/lib/python2.7/site-packages/pysparnn/matrix_distance.py:334: RuntimeWarning: divide by zero encountered in true_divide\n",
+      "  magnitude = 1.0 / (a_root_sum_square * self.matrix_root_sum_square)\n",
+      "/Users/spencebeecher/anaconda2/lib/python2.7/site-packages/pysparnn/matrix_distance.py:336: RuntimeWarning: invalid value encountered in multiply\n",
+      "  return 1 - (dprod * magnitude)\n",
+      "/Users/spencebeecher/anaconda2/lib/python2.7/site-packages/pysparnn/matrix_distance.py:108: RuntimeWarning: invalid value encountered in less_equal\n",
+      "  dist_filter = (dist_matrix <= max_distance)\n"
+     ]
+    }
+   ],
    "source": [
-    "dense_cp = pysparnn.MultiClusterIndex(train_features, data_to_return, \n",
-    "                                      distance_type=pysparnn.matrix_distance.DenseCosineDistance)"
+    "dense_cp = ci.MultiClusterIndex(train_features, data_to_return, \n",
+    "                                distance_type=pysparnn.matrix_distance.DenseCosineDistance)"
    ]
   },
   {
@@ -124,7 +146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
@@ -135,7 +157,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {
     "collapsed": true
    },
@@ -160,7 +182,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
@@ -169,7 +191,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Percent of time sparse returns a top 3 result: 0.2384\n"
+      "Percent of time sparse returns a top 3 result: 0.2498\n"
      ]
     }
    ],
@@ -178,14 +200,14 @@
     "\n",
     "results = cp.search(test_features, return_distance=False)\n",
     "\n",
-    "print('Percent of time sparse returns a top 3 result:', pysparnn_utils.recall(answers, results).mean())\n",
+    "print('Percent of time sparse returns a top 3 result: {}'.format(pysparnn_utils.recall(answers, results).mean()))\n",
     "\n",
     "cp_time = time.time() - t0"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
@@ -194,7 +216,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Percent of time dense returns a top 3 result: 0.2318\n"
+      "Percent of time dense returns a top 3 result: 0.2458\n"
      ]
     }
    ],
@@ -203,25 +225,25 @@
     "\n",
     "results = dense_cp.search(test_features, return_distance=False)\n",
     "\n",
-    "print('Percent of time dense returns a top 3 result:', pysparnn_utils.recall(answers, results).mean())\n",
+    "print('Percent of time dense returns a top 3 result: {}'.format(pysparnn_utils.recall(answers, results).mean()))\n",
     "\n",
     "dense_cp_time = time.time() - t0"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "4.370408034254829"
+       "4.979948311566905"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -242,21 +264,21 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 2",
    "language": "python",
-   "name": "python3"
+   "name": "python2"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 3
+    "version": 2
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.0"
+   "pygments_lexer": "ipython2",
+   "version": "2.7.12"
   }
  },
  "nbformat": 4,