From c22249be99331e69a705b4a2bf261f91435d991b Mon Sep 17 00:00:00 2001
From: Shawn Tan <shawn@wtf.sg>
Date: Wed, 19 Jun 2013 15:28:27 +0800
Subject: [PATCH] Modified crf

---
 crf.py  | 33 ++++++++++++++++++++++++++++++---
 test.py | 13 +++++++++----
 2 files changed, 39 insertions(+), 7 deletions(-)

diff --git a/crf.py b/crf.py
index eaab611..20261ad 100644
--- a/crf.py
+++ b/crf.py
@@ -138,11 +138,38 @@ def predict(self,x_vec, debug=False):
 		"""
 		all_features  = self.all_features(x_vec)
 		log_potential = np.dot(all_features,self.theta)
-		N = len(x_vec)
-		return self.log_predict(log_potential,N,K)
+		return [ self.labels[i] for i in self._predict(log_potential,len(x_vec),len(self.labels)) ]
+	
+	def _predict(self,log_potential,N,K,debug=False):
+		"""
+		Find the most likely assignment to labels given parameters using the
+		Viterbi algorithm.
+		"""
+		g0 = log_potential[0,0]
+		g  = log_potential[1:]
+
+		B = np.ones((N,K), dtype=np.int32) * -1
+		# compute max-marginals and backtrace matrix
+		V = g0
+		for t in xrange(1,N):
+			U = np.empty(K)
+			for y in xrange(K):
+				w = V + g[t-1,:,y]
+				B[t,y] = b = w.argmax()
+				U[y] = w[b]
+			V = U
+		# extract the best path by brack-tracking
+		y = V.argmax()
+		trace = []
+		for t in reversed(xrange(N)):
+			trace.append(y)
+			y = B[t, y]
+		trace.reverse()
+		return trace
+
 
 
-	def log_predict(self,log_potential,N,K):
+	def log_predict(self,log_potential,N,K,debug=False):
 		if debug:
 			print
 			print
diff --git a/test.py b/test.py
index 1b393f6..4b30d41 100644
--- a/test.py
+++ b/test.py
@@ -108,7 +108,7 @@ class TestCRF(unittest.TestCase):
 	def setUp(self):
 		self.matrix = 0.001 + np.random.poisson(lam=1.5, size=(3,3)).astype(np.float)
 		self.vector = 0.001 + np.random.poisson(lam=1.5, size=(3,)).astype(np.float)
-		self.M = 0.001 + np.random.poisson(lam=1.5, size=(3,3,3)).astype(np.float)
+		self.M = 0.001 + np.random.poisson(lam=1.5, size=(10,3,3)).astype(np.float)
 		self.crf = crf.CRF([],[])
 
 	def test_log_dot_mv(self):
@@ -138,9 +138,14 @@ def test_forward(self):
 		self.assertTrue((res == res_true).all())
 
 	def test_predict(self):
-		print self.log_predict(self.M,self.M.shape[0],self.M.shape[1])
-		print argmax(self.M)
+		label_pred = self.crf.log_predict(self.M,self.M.shape[0],self.M.shape[1])
+		label_act  = argmax(self.M)
+		print label_pred
+		print label_act
+		self.assertTrue(label_pred == label_act)
+
 
 if __name__ == '__main__':
-	unittest.main()
+	for i in range(10):
+		unittest.main()