def _compute_log_p_kappa(self):
log_p_prior = sum([
compute_e_log_p_dirichlet(x, self.kappa_prior)
for x in self.kappa.values()
])
log_p_posterior = self._compute_e_log_p_kappa_posterior()
return log_p_prior + log_p_posterior
def _compute_e_log_p(self):
gamma_prior = 0
gamma_posterior = 0
for data_type in self.data_types:
for k in range(self.K):
for m in range(self.M[data_type]):
gamma_prior += compute_e_log_p_dirichlet(self.gamma[data_type][:, k, m],
self.gamma_prior[data_type])
gamma_posterior += self._compute_e_log_p_gamma_posterior(data_type)
kappa_prior = compute_e_log_p_dirichlet(self.kappa, self.kappa_prior)
kappa_posterior = self._compute_e_log_p_kappa_posterior()
return sum([gamma_prior,
gamma_posterior,
kappa_prior,
kappa_posterior])
def _compute_log_p_gamma(self):
log_p_prior = 0
log_p_posterior = 0
for data_type in self.data_types:
if self.use_position_specific_gamma:
for m in range(self.M[data_type]):
log_p_prior += sum([
compute_e_log_p_dirichlet(x, y)
for x, y in zip(self.gamma[data_type][:, :, m],
self.gamma_prior[data_type])
])
else:
log_p_prior += sum([
compute_e_log_p_dirichlet(x, y) for x, y in zip(
self.gamma[data_type], self.gamma_prior[data_type])
])
log_p_posterior += self._compute_e_log_p_gamma_posterior(data_type)
return log_p_prior + log_p_posterior
def _compute_log_p_alpha(self):
log_p_prior = compute_e_log_p_dirichlet(self.alpha, self.alpha_prior)
log_p_posterior = self._compute_e_log_p_alpha_posterior()
return log_p_prior + log_p_posterior