def _check(self): # super(GaussianHMM, self)._check() self.means_ = np.asarray(self.means_) self.n_features = self.means_.shape[1] if self.covariance_type not in COVARIANCE_TYPES: raise ValueError( 'covariance_type must be one of {0}'.format(COVARIANCE_TYPES)) _validate_covars(self._covars_, self.covariance_type, self.n_components)
def _check(self): super(GaussianHMM, self)._check() self.means_ = np.asarray(self.means_) self.n_features = self.means_.shape[1] if self.covariance_type not in COVARIANCE_TYPES: raise ValueError('covariance_type must be one of {0}' .format(COVARIANCE_TYPES)) _validate_covars(self._covars_, self.covariance_type, self.n_components)
def _set_covars(self, covars): covars = np.asarray(covars) _validate_covars(covars, self._covariance_type, self.n_components) self._covars_ = covars.copy()