Fixed the number of samples in the np.random.random call to match tha…

…t in the np.random.choice call in posterior_moments function.
LoLab-MSM · Apr 7, 2020 · 2cf2cfb · 2cf2cfb
1 parent 2bcd8c4
commit 2cf2cfb
Showing 1 changed file with 1 addition and 1 deletion.
diff --git a/gleipnir/nsbase.py b/gleipnir/nsbase.py
@@ -76,7 +76,7 @@ def posterior_moments(self):
             marginal, edges, centers = post[parm]
             width = edges[1] - edges[0]
             # resample from the distribution
-            samples = np.random.choice(centers, size=1000000, p=marginal/(marginal.sum())) + (width*(np.random.random(10000)-0.5))
+            samples = np.random.choice(centers, size=1000000, p=marginal/(marginal.sum())) + (width*(np.random.random(1000000)-0.5))
             mean = np.mean(samples)
             var = np.var(samples)
             skew = scipy.stats.skew(samples)