adds tests for element_wise_product and forward_backward

SnShine · SnShine · commit 4c64a2c3007f · 2016-03-16T23:49:54.000+05:30
diff --git a/probability.py b/probability.py
@@ -524,15 +524,7 @@ def markov_blanket_sample(X, e, bn):
 
 # _________________________________________________________________________
 
-"""
-umbrella_evidence = [T, T, F, T, T]
-umbrella_prior = [0.5, 0.5]
-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)
-
-print(forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior))
-"""
+# Umbrella Example [Fig. 15.2]
 
 class HiddenMarkovModel:
 
@@ -568,7 +560,19 @@ def backward(HMM, b, ev):
 
 
 def forward_backward(HMM, ev, prior):
-    """[Fig. 15.4]"""
+    """[Fig. 15.4]
+    Forward-Backward algorithm for smoothing. Computes posterior probabilities
+    of a sequence of states given a sequence of observations.
+
+    umbrella_evidence = [T, T, F, T, T]
+    umbrella_prior = [0.5, 0.5]
+    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)
+
+    >>> forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior)
+    [[0.6469, 0.3531], [0.8673, 0.1327], [0.8204, 0.1796], [0.3075, 0.6925], [0.8204, 0.1796], [0.8673, 0.1327]]
+    """
     t = len(ev)
     ev.insert(0, None)  # to make the code look similar to pseudo code
 
@@ -587,6 +591,7 @@ def forward_backward(HMM, ev, prior):
         bv.append(b)
 
     sv = sv[::-1]
+    # to have only 4 digits after decimal point
     for i in range(len(sv)):
         for j in range(len(sv[i])):
             sv[i][j] = float("{0:.4f}".format(sv[i][j]))
diff --git a/tests/test_probability.py b/tests/test_probability.py
@@ -102,5 +102,21 @@ def test_likelihood_weighting():
             'Burglary', dict(JohnCalls=T, MaryCalls=T),
             burglary, 10000).show_approx() == 'False: 0.702, True: 0.298'
 
+
+def test_forward_backward():
+    umbrella_prior = [0.5, 0.5]
+    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)
+
+    umbrella_evidence = [T, T, F, T, T]
+    assert forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior) == [[0.6469, 0.3531],
+                [0.8673, 0.1327], [0.8204, 0.1796], [0.3075, 0.6925], [0.8204, 0.1796], [0.8673, 0.1327]]
+
+    umbrella_evidence = [T, F, T, F, T]
+    assert forward_backward(umbrellaHMM, umbrella_evidence, umbrella_prior) == [[0.5871, 0.4129],
+                 [0.7177, 0.2823], [0.2324, 0.7676], [0.6072, 0.3928], [0.2324, 0.7676], [0.7177, 0.2823]]
+
+
 if __name__ == '__main__':
     pytest.main()
diff --git a/tests/test_utils.py b/tests/test_utils.py
@@ -15,8 +15,7 @@ def test_removeall_list():
 
 def test_removeall_string():
     assert removeall('s', '') == ''
-    assert removeall(
-        's', 'This is a test. Was a test.') == 'Thi i a tet. Wa a tet.'
+    assert removeall('s', 'This is a test. Was a test.') == 'Thi i a tet. Wa a tet.'
 
 
 def test_unique():
@@ -86,6 +85,10 @@ def test_histogram():
 def test_dotproduct():
     assert dotproduct([1, 2, 3], [1000, 100, 10]) == 1230
 
+def test_element_wise_product():
+    assert element_wise_product([1, 2, 5], [7, 10, 0]) == [7, 20, 0]
+    assert element_wise_product([1, 6, 3, 0], [9, 12, 0, 0]) == [9, 72, 0, 0]
+
 
 def test_vector_add():
     assert vector_add((0, 1), (8, 9)) == (8, 10)
