From d2d9ab7ba51f2cc382a2676aaacecbf75bcfadc8 Mon Sep 17 00:00:00 2001
From: Thibaut Horel <thibaut.horel@gmail.com>
Date: Mon, 30 Nov 2015 20:11:09 -0500
Subject: Fix mle.py

---
 simulation/mle.py | 33 +++++++++++++++++----------------
 1 file changed, 17 insertions(+), 16 deletions(-)

(limited to 'simulation')

diff --git a/simulation/mle.py b/simulation/mle.py
index c6b2e85..21b50b5 100644
--- a/simulation/mle.py
+++ b/simulation/mle.py
@@ -1,5 +1,6 @@
 import numpy as np
 from scipy.optimize import minimize
+import utils
 
 
 def likelihood(p, x, y):
@@ -53,20 +54,20 @@ def confidence_interval(counts, bins):
     return bins[len(bins)/2-k], bins[len(bins)/2+k]
 
 
-def build_matrix(cascades, node):
-
-    def aux(cascade, node):
-        xlist, slist = zip(*cascade)
-        indices = [i for i, s in enumerate(slist) if s[node] and i >= 1]
-        if indices:
-            x = np.vstack(xlist[i-1] for i in indices)
-            y = np.array([xlist[i][node] for i in indices])
-            return x, y
-        else:
-            return None
-
-    pairs = (aux(cascade, node) for cascade in cascades)
-    xs, ys = zip(*(pair for pair in pairs if pair))
-    x = np.vstack(xs)
-    y = np.concatenate(ys)
+def build_matrix(x_obs, s_obs, node):
+    ind = s_obs[:, node]
+    ind_bis = np.zeros(x_obs.shape[0], dtype=bool)
+    ind_bis[:-1] = ind[1:]
+    ind_bis[-1] = False
+    y = x_obs[ind, node]
+    x = x_obs[ind_bis]
     return x, y
+
+if __name__ == "__main__":
+    n_obs = 10000
+    graph = utils.create_wheel(10)
+    source = lambda graph: utils.constant_source(graph, 0)
+    x, s = utils.simulate_cascades(n_obs, graph, source)
+    x, y = build_matrix(x, s, 1)
+    print x, y
+    print infer(x, y)[0]
-- 
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