#182 is completed

Author: Hamid Gasmi

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability.py

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+import sys
+
+def outcome_probability(x, sigma, pi, states, emission):
+    if len(pi) == 0:
+        return 0.0
+
+    probability = 1
+    for p in range(len(pi)):
+       probability *= emission[ pi[p] ][ x[p] ]
+
+    return probability
+
+if __name__ == "__main__":
+    x = sys.stdin.readline().strip()
+    sys.stdin.readline() # delimiter
+
+    sigma = sys.stdin.readline().strip().split()
+    sys.stdin.readline() # delimiter
+
+    pi = sys.stdin.readline().strip()
+    sys.stdin.readline() # delimiter
+
+    states = sys.stdin.readline().strip().split()
+    sys.stdin.readline() # delimiter
+
+    chars = sys.stdin.readline().strip().split() 
+    emission = [sys.stdin.readline().strip().split() for _ in range(len(states))]
+    emission = {line[0]:dict(zip(chars, map(float,line[1:]))) for line in emission}
+
+    print(outcome_probability(x,sigma,pi,states,emission))

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/01.exp

@@ -0,0 +1 @@
+0.001106941474

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/01.in

@@ -0,0 +1,11 @@
+zzzyx
+--------
+x y z
+--------
+BAAAA
+--------
+A B
+--------
+	x	y	z
+A	0.176	0.596	0.228
+B	0.225	0.572	0.203

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/02.exp

@@ -0,0 +1 @@
+1.0

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/02.in

@@ -0,0 +1,11 @@
+x
+--------
+x
+--------
+A
+--------
+A B
+--------
+	x
+A	1
+B	1

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/03.exp

@@ -0,0 +1 @@
+0.18

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/03.in

@@ -0,0 +1,11 @@
+xx
+--------
+x y
+--------
+AB
+--------
+A B
+--------
+	x	y
+A	0.6	0.4
+B	0.3	0.7

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/04.exp

@@ -0,0 +1 @@
+0.24

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/04.in

@@ -0,0 +1,11 @@
+xy
+--------
+x y
+--------
+AA
+--------
+A B
+--------
+	x	y
+A	0.6	0.4
+B	0.3	0.7

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/05.exp

@@ -0,0 +1 @@
+9.70e-15

06-dynamic-programming-applications-in-machine-learning-and-genomics/3-hidden-markov-models-for-sequence-alignment-1/outcome_probability_tests/05.in

@@ -0,0 +1,11 @@
+xxxxxyxyyx
+--------
+x y
+--------
+AABBABABBA
+--------
+A B
+--------
+	x	y
+A	0.01	0.99
+B	0.01	0.99