Exp std estimate from advi.

Author: twiecki

pymc3/examples/advi.ipynb

@@ -80,8 +80,8 @@
     {
      "data": {
       "text/plain": [
-       "({'mu': array(-0.04257040855843567), 'sd_log': array(0.04718829740487737)},\n",
-       " {'mu': array(-2.1597198585453112), 'sd_log': array(-2.5448566614228585)})"
+       "({'mu': array(-0.00185745477891906), 'sd_log': array(0.08483499873770008)},\n",
+       " {'mu': 0.11968501081096175, 'sd_log': 0.078377195440148151})"
       ]
      },
      "execution_count": 4,
@@ -95,7 +95,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -107,6 +107,14 @@
       "\r",
       " [-----------------100%-----------------] 500 of 500 complete in 0.2 sec"
      ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/wiecki/envs/pymc3/local/lib/python2.7/site-packages/theano/scan_module/scan_perform_ext.py:133: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility\n",
+      "  from scan_perform.scan_perform import *\n"
+     ]
     }
    ],
    "source": [
@@ -117,7 +125,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
@@ -126,19 +134,28 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "-0.0670183517618\n",
-      "0.0498948596914\n",
-      "-2.17277976734\n",
-      "-2.68756925176\n"
+      "-0.0234951954338\n",
+      "0.084690267036\n",
+      "0.117815331104\n",
+      "0.0747069952536\n"
      ]
     }
    ],
    "source": [
     "print trace['mu'].mean()\n",
     "print trace['sd_log'].mean()\n",
-    "print np.log(trace['mu'].std())\n",
-    "print np.log(trace['sd_log'].std())"
+    "print trace['mu'].std()\n",
+    "print trace['sd_log'].std()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

pymc3/variational/ADVI.py

@@ -42,6 +42,9 @@ def advi(vars=None, start=None, model=None, n=5000):
 
     u = bij.rmap(result[:l])
     w = bij.rmap(result[l:])
+    # w is in log space
+    for var in w.keys():
+        w[var] = np.exp(w[var])
     return u, w
 
 def run_adagrad(uw, grad, inarray, n):