class BaumWelchIterate(unittest.TestCase): """ Tester la reussite des reestimations """ def setUp(self): self.listState = ['A', 'B'] self.listObservables = ["je", "ne", "suis", "pas", "un", "hero"] self.hmm = HMM_BW(self.listObservables, self.listState, 5) def test_setAlpha(self): ''' Test de l'instanciation des alpha ''' alpha_0 = self.hmm.alpha[1]['A'] self.hmm.setAlpha() alpha_1 = self.hmm.alpha[1]['A'] assert(not alpha_0 == alpha_1) def test_setBeta(self): ''' Test de l'instanciation des beta ''' beta_0 = self.hmm.beta[0]['A'] self.hmm.setBeta() beta_1 = self.hmm.beta[0]['A'] assert(not beta_0 == beta_1) def test_setGamma(self): ''' Test de l'instanciation des gamma ''' gamma_0 = self.hmm.gamma[0]['A'] self.hmm.setGamma() gamma_1 = self.hmm.gamma[0]['A'] assert(not gamma_0 == gamma_1) def test_iterations(self): ''' Test du bon fonctionnement d'une iteration ''' E_0 = self.hmm.emissions[self.listObservables[0]][self.listState[0]] self.hmm.iterate() E_1 = self.hmm.emissions[self.listObservables[0]][self.listState[0]] assert(not E_0 == E_1)
class BaumWelchIterate(unittest.TestCase): """ Tester la reussite des reestimations """ def setUp(self): listObservables = ["je", "ne", "suis", "pas", "un", "hero"] self.hmm = HMM_BW(listObservables, 5) def test_setAlpha(self): alpha_0 = self.hmm.alpha[1]['A'] self.hmm.setAlpha() alpha_1 = self.hmm.alpha[1]['A'] assert(not alpha_0 == alpha_1) def test_setBeta(self): beta_0 = self.hmm.beta[0]['A'] self.hmm.setBeta() beta_1 = self.hmm.beta[0]['A'] assert(not beta_0 == beta_1) def test_iterations(self): self.hmm.iterate() assert(1==2)
def setUp(self): self.listState = ['A', 'B'] self.listObservables = ["je", "ne", "suis", "pas", "un", "hero"] self.hmm = HMM_BW(self.listObservables, self.listState, 5)
def setUp(self): listObservables = ["je", "ne", "suis", "pas", "un", "hero"] self.hmm = HMM_BW(listObservables, 5)
listObservables = range(len(test_table))
for k in range(len(test_table)):
listObservables[k] = test_table[k][0]
### On construit un hmm avec le fichier d'apprentissage ###
S = app.get_Pi_T_E()
I = S[0]
T = S[1]
E = S[2]
if perturbation:
for obs in listObservables:
for state in listState:
if obs in E and not state=="":
E[obs][state]+=(random.random()-0.5)*coef
###########################################################
hmm = HMM_BW(listObservables, listState, 1)
if hmm_determine:
hmm.Pi = I
hmm.Pi[""] = 0.0
T[""] = hmm.Pi
for state in hmm.Pi:
T[state][""] = 0.01
hmm.transitions = T
hmm.transitions[""] = {}
E[""] = hmm.Pi
for obs in hmm.listObservables:
E[obs][""] = 0.0
E[""][""] = 1.0
hmm.emissions = E
