Ticket #3773: sage-3773-part2.patch

a/sage/stats/hmm/hmm.pyx

@@ -544 +544 @@
-            sage: a.log_likelihood([1,1])
-            -1.3862943611198906
-        """
+        if self._emission_symbols_dict:
+            seq = [self._emission_symbols_dict[z] for z in seq]
-        cdef double log_p
-        cdef int* O = to_int_array(seq)
-        cdef int ret = ghmm_dmodel_logp(self.m, O, len(seq), &log_p)
@@ -587 +589 @@
-            sage: a.viterbi([3/4, 'abc', 'abc'] + [3/4]*10)
-            ([0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], -25.299405845367794)
-        """
+        if len(seq) == 0:
+            return [], 0.0
-        if self._emission_symbols_dict:
-            seq = [self._emission_symbols_dict[z] for z in seq]
-        cdef int* path
@@ -615 +619 @@
-        Baum-Welch algorithm to increase the probability of observing O.
-
-        INPUT:
-
+ (or a single list)
-            nsteps -- integer or None (default: None) maximum number
-                      of Baum-Welch steps to take
-            log_likehood_cutoff -- positive float or None (default:
@@ -675 +679 @@
-            Applications in Speech Recognition"', Proceedings of the IEEE,
-            77, no 2, 1989, pp 257--285. 
-        """
+        if len(training_seqs) > 0 and not isinstance(training_seqs[0], (list, tuple)):
+            training_seqs = [training_seqs]
+            
-        if self._emission_symbols_dict:
-            seqs = [[self._emission_symbols_dict[z] for z in x] for x in training_seqs]
-        else: