def _log_wishart_const(num_features, nws_dof, nws_scale_matrix):
"""Compute `log_wishart_const_init` """
if nws_scale_matrix.ndim == 2:
ld = logdet(nws_scale_matrix)
else:
ld = [logdet(nws_scale_matrix[k, :, :]) for k in range(nws_scale_matrix.shape[0])]
log_wishart_const = (
(nws_dof / 2) * ld - (nws_dof * num_features / 2) * log(2) - mvt_gamma_ln(num_features, nws_dof / 2)
)
return log_wishart_const
def _log_wishart_const(num_features, nws_dof,
nws_scale_matrix):
"""Compute `log_wishart_const_init` """
log_wishart_const = ((nws_dof / 2) * logdet(nws_scale_matrix) -
(nws_dof * num_features / 2) * log(2) -
mvt_gamma_ln(num_features, nws_dof / 2))
return log_wishart_const
def _update_log_det_precision(num_features, num_comp, posterior_nws_dof,
posterior_nws_scale_matrix):
""" Update `log_det_precision` """
update = lambda k: (np.sum(psi((posterior_nws_dof[k] +
1 - range(1, num_features + 1)) / 2)) +
num_features * log(2) -
logdet(posterior_nws_scale_matrix[k, :, :]))
log_det_precision = [update(k) for k in range(num_comp)]
return log_det_precision
