distributions.py 文件源码

def resample(self,data=[],temperature=1.,stats=None):
        stats = self._get_statistics(data) if stats is None else stats

        alphas_n, betas_n, mu_n, nus_n = self._natural_to_standard(
                self.natural_hypparam + stats / temperature)

        D = mu_n.shape[0]
        self.sigmas = 1/np.random.gamma(alphas_n,scale=1/betas_n)
        self.mu = np.sqrt(self.sigmas/nus_n)*np.random.randn(D) + mu_n

        assert not np.isnan(self.mu).any()
        assert not np.isnan(self.sigmas).any()

        # NOTE: next line is to use Gibbs sampling to initialize mean field
        self.mf_mu = self.mu

        assert self.sigmas.ndim == 1
        return self