fgmm.py 文件源码

def log_marg(self):
        """Return log marginal of data and component assignments: p(X, z)"""

        # Log probability of component assignment, (24.24) in Murphy, p. 842
        log_prob_z = (
            gammaln(self.kalpha)
            - gammaln(self.kalpha + np.sum(self.components.counts))
            + np.sum(
                gammaln(
                    self.components.counts
                    + float(self.kalpha)/self.components.K_max
                    )
                - gammaln(self.kalpha/self.components.K_max)
                )
            )

        # Log probability of data in each component
        log_prob_X_given_z = self.components.log_marg()

        return log_prob_z + log_prob_X_given_z