boxed indicator added

min max history with relative coordinates adding

--HG--
branch : aspn

src/viterbi.py

@@ -0,0 +1,66 @@
+# See http://en.wikipedia.org/wiki/Viterbi_algorithm
+
+""" Viterbi algorithm 
+"""
+
+
+
+states = ('Rainy', 'Sunny')
+ 
+observations = ('walk', 'shop', 'clean')
+ 
+start_probability = {'Rainy': 0.6, 'Sunny': 0.4}
+ 
+transition_probability = {
+   'Rainy' : {'Rainy': 0.7, 'Sunny': 0.3},
+   'Sunny' : {'Rainy': 0.4, 'Sunny': 0.6},
+   }
+ 
+emission_probability = {
+   'Rainy' : {'walk': 0.1, 'shop': 0.4, 'clean': 0.5},
+   'Sunny' : {'walk': 0.6, 'shop': 0.3, 'clean': 0.1},
+   }
+
+
+def forward_viterbi(obs, states, start_p, trans_p, emit_p):
+    T = {}
+    for state in states:
+        ##          prob.           V. path  V. prob.
+        T[state] = (start_p[state], [state], start_p[state])
+    for output in obs:
+        U = {}
+        for next_state in states:
+            total = 0
+            argmax = None
+            valmax = 0
+            for source_state in states:
+                (prob, v_path, v_prob) = T[source_state]
+                p = emit_p[source_state][output] * trans_p[source_state][next_state]
+                prob *= p
+                v_prob *= p
+                total += prob
+                if v_prob > valmax:
+                    argmax = v_path + [next_state]
+                    valmax = v_prob
+            U[next_state] = (total, argmax, valmax)
+        T = U
+    ## apply sum/max to the final states:
+    total = 0
+    argmax = None
+    valmax = 0
+    for state in states:
+        (prob, v_path, v_prob) = T[state]
+        total += prob
+        if v_prob > valmax:
+            argmax = v_path
+            valmax = v_prob
+    return (total, argmax, valmax)
+
+
+def example():
+    return forward_viterbi(observations,
+                           states,
+                           start_probability,
+                           transition_probability,
+                           emission_probability)
+print example()