#184 is started

Author: Hamid Gasmi

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

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

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

@@ -0,0 +1 @@
+0.001544

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

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+xzyyz
+--------
+x y z
+--------
+A B
+--------
+	A	B
+A	0.303	0.697	
+B	0.831	0.169	
+--------
+	x	y	z
+A	0.533	0.065	0.402	
+B	0.342	0.334	0.324

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

@@ -0,0 +1 @@
+0.5

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

@@ -0,0 +1,13 @@
+x
+--------
+x
+--------
+A B
+--------
+	A	B
+A	0.5	0.5
+B	0.5	0.5
+--------
+	x
+A	0.5
+B	0.5

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

@@ -0,0 +1 @@
+0.252

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

@@ -0,0 +1,13 @@
+xy
+--------
+x y
+--------
+A B
+--------
+	A	B
+A	0.4	0.6
+B	0.6	0.4
+--------
+	x	y
+A	0.7	0.3
+B	0.4	0.6

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

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

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

@@ -0,0 +1,15 @@
+xzywyxw
+--------
+w x y z
+--------
+A B C
+--------
+	A	B	C
+A	0.7	0.1	0.2	
+B	0.5	0.3	0.2
+C	0.1	0.4	0.5
+--------
+	w	x	y	z
+A	0.34	0.24	0.42	0
+B	0.17	0.49	0.34	0
+C	0.22	0.22	0.56	0

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

@@ -0,0 +1 @@
+9.17e-09

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

@@ -0,0 +1,15 @@
+xxxxyxxxzz
+--------
+x y z
+--------
+A B C
+--------
+	A	B	C
+A	0.7	0.1	0.2	
+B	0.5	0.3	0.2
+C	0.1	0.4	0.5
+--------
+	x	y	z
+A	0.24	0.41	0.01
+B	0.49	0.33	0.01
+C	0.22	0.55	0.01