Delete redundant (and buggy) weighted_sample_with_replacement; add a little testing for it.

Author: darius

probability.py

@@ -650,23 +650,5 @@ def particle_filtering(e, N, HMM):
         w[i] = float("{0:.4f}".format(w[i]))
 
     # STEP 2
-    s = weighted_sample_with_replacement(N, s, w)
+    s = weighted_sample_with_replacement(s, w, N)
     return s
-
-
-def weighted_sample_with_replacement(N, s, w):
-    """
-    Performs Weighted sampling over the paricles given weights of each particle.
-    We keep on picking random states unitll we fill N number states in new distribution
-    """
-    s_wtd = []
-    cnt = 0
-    while (cnt <= N):
-        # Generate a random number from 0 to N-1
-        i = random.randint(0, N-1)
-        if (probability(w[i])):
-            s_wtd.append(s[i])
-            cnt += 1
-    return s_wtd
-
-

tests/test_probability.py

@@ -146,8 +146,11 @@ def test_particle_filtering():
     umbrella_transition = [[0.7, 0.3], [0.3, 0.7]]
     umbrella_sensor = [[0.9, 0.2], [0.1, 0.8]]
     umbrellaHMM = HiddenMarkovModel(umbrella_transition, umbrella_sensor)
+    s = particle_filtering(umbrella_evidence, N, umbrellaHMM)
+    assert len(s) == N
+    assert all(state in 'AB' for state in s)
+    # XXX 'A' and 'B' are really arbitrary names, but I'm letting it stand for now
 
-    assert particle_filtering(umbrella_evidence, N, umbrellaHMM)
 
 # The following should probably go in .ipynb: