bug fix + commit v0.10.2

docs/source/conf.py

@@ -18,11 +18,11 @@
 # -- Project information -----------------------------------------------------
 
 project = 'jajapy'
-copyright = '2022, Raphaël Reynouard'
+copyright = '2023, Raphaël Reynouard'
 author = 'Raphaël Reynouard'
 
 # The full version, including alpha/beta/rc tags
-release = 'v0.10.1'
+release = 'v0.10.2'
 
 
 # -- General configuration ---------------------------------------------------

jajapy/base/BW.py

@@ -196,7 +196,7 @@ def _preparation(self,training_set,initial_model=None, nb_states: int=None,
 				self._computeAlphas = self._computeAlphas_timed
 				self._computeBetas  = self._computeBetas_timed
 			if type(fixed_parameters) == bool:
-				self.fixed_parameters = full(initial_model.matrix.shape,False)
+				self.fixed_parameters = full(self.h.matrix.shape,False)
 			else:
 				self.fixed_parameters = fixed_parameters
 

jajapy/base/Base_MC.py

@@ -58,6 +58,11 @@ def getLabel(self,state: int) -> str:
 		"""
 		self._checkStateIndex(state)
 		return self.labelling[state]
+
+	def b(self,state:int, label:str):
+		if self.getLabel(state) == label:
+			return 1.0
+		return 0.0
 
 	def getAlphabet(self) -> list:
 		"""

jajapy/base/Model.py

@@ -343,7 +343,11 @@ def _logLikelihood_multiproc(self, sequences: Set) -> float:
 		for seq,times in zip(sequences.sequences,sequences.times):
 			tasks.append(p.apply_async(self._computeAlphas, [seq, times,]))
 		temp = [res.get() for res in tasks if res.get() != False]
-		return sum(temp)/sum(sequences.times)
+		s = sum(temp)
+		if s == 0.0:
+			print('WARNING: the model is not able to generate any sequence in the set')
+			return 0.0
+		return s/sum(sequences.times)
 
 	def _computeAlphas(self,sequence: list, times: int) -> float:
 		"""
@@ -369,10 +373,13 @@ def _computeAlphas(self,sequence: list, times: int) -> float:
 				p = array([self.tau(ss,s,sequence[k]) for ss in range(self.nb_states)])
 				new_arr[s] = dot(prev_arr,p)
 			prev_arr = new_arr
-		if prev_arr.sum() == 0.0:
-			return 0.0
 		prev_arr *= (array([self.b(s,sequence[-1]) for s in range(self.nb_states)]))
-		return log(prev_arr.sum())*times
+		try:
+			res = log(prev_arr.sum())*times
+		except ValueError:
+			print("WARNING: this model is not able to generate this sequence")
+			res = False
+		return res
 
 	def _checkStateIndex(self,s:int) -> None:
 		if type(s) != int:

jajapy/ctmc/CTMC.py

@@ -65,6 +65,7 @@ def e(self,s: int) -> float:
 		"""
 		self._checkStateIndex(s)
 		return sum(self.matrix[s])
+
 
 	def l(self, s1:int, s2:int, obs:str) -> float:
 		"""

jajapy/mc/MC.py

@@ -91,11 +91,6 @@ def a(self,s1: int,s2: int) -> float:
 		self._checkStateIndex(s2)
 		return self.matrix[s1][s2]
 
-	def b(self,state:int, label:str):
-		if self.getLabel(state) == label:
-			return 1.0
-		return 0.0
-
 	def next(self,state: int) -> tuple:
 		"""
 		Return a state-observation pair according to the distributions described by `matrix`

setup.py

@@ -13,7 +13,7 @@
     packages=find_packages(),
     install_requires=['numpy', 'scipy', 'alive-progress','sympy'],
     long_description_content_type="text/markdown",
-    version='0.10.1',
+    version='0.10.2',
     url="",
     description='Baum-Welch for all kind of Markov model',
     author='Raphaël Reynouard',