#NEWLINE# def test_fit( self , params = 'ste' , n_iter = 5 ) : #NEWLINE# #INDENT# h = self . h #NEWLINE# h . params = params #NEWLINE# lengths = np . array ( ( [ 10 ] * 10 ) ) #NEWLINE# ( X , _state_sequence ) = h . sample ( lengths . sum ( ) ) #NEWLINE# h . startprob_ = normalized ( np . random . random ( self . n_components ) ) #NEWLINE# h . transmat_ = normalized ( np . random . random ( ( self . n_components , self . n_components ) ) , axis = 1 ) #NEWLINE# h . emissionprob_ = normalized ( np . random . random ( ( self . n_components , self . n_features ) ) , axis = 1 ) #NEWLINE# assert log_likelihood_increasing ( h , X , lengths , n_iter )