def _do_backward_pass(self, framelogprob):
n_samples, n_components = framelogprob.shape
bwdlattice = np.zeros((n_samples, n_components))
_hmmc._backward(n_samples, n_components,
log_mask_zero(self.startprob_),
log_mask_zero(self.transmat_), framelogprob,
bwdlattice)
return bwdlattice
def _accumulate_sufficient_statistics(self, stats, X, framelogprob,
posteriors, fwdlattice, bwdlattice):
"""Updates sufficient statistics from a given sample.
Parameters
----------
stats : dict
Sufficient statistics as returned by
:meth:`~base._BaseHMM._initialize_sufficient_statistics`.
X : array, shape (n_samples, n_features)
Sample sequence.
framelogprob : array, shape (n_samples, n_components)
Log-probabilities of each sample under each of the model states.
posteriors : array, shape (n_samples, n_components)
Posterior probabilities of each sample being generated by each
of the model states.
fwdlattice, bwdlattice : array, shape (n_samples, n_components)
Log-forward and log-backward probabilities.
"""
stats['nobs'] += 1
if 's' in self.params:
stats['start'] += posteriors[0]
if 't' in self.params:
n_samples, n_components = framelogprob.shape
# when the sample is of length 1, it contains no transitions
# so there is no reason to update our trans. matrix estimate
if n_samples <= 1:
return
log_xi_sum = np.full((n_components, n_components), -np.inf)
_hmmc._compute_log_xi_sum(n_samples, n_components, fwdlattice,
log_mask_zero(self.transmat_),
bwdlattice, framelogprob, log_xi_sum)
stats['trans'] += np.exp(log_xi_sum)
def _do_forward_pass(self, framelogprob):
n_samples, n_components = framelogprob.shape
fwdlattice = np.zeros((n_samples, n_components))
_hmmc._forward(n_samples, n_components, log_mask_zero(self.startprob_),
log_mask_zero(self.transmat_), framelogprob, fwdlattice)
return logsumexp(fwdlattice[-1]), fwdlattice
def _do_viterbi_pass(self, framelogprob):
n_samples, n_components = framelogprob.shape
state_sequence, logprob = _hmmc._viterbi(
n_samples, n_components, log_mask_zero(self.startprob_),
log_mask_zero(self.transmat_), framelogprob)
return logprob, state_sequence