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