61e9af1a3757a8b75e86777bdfa341ef112a31d1,pymc3/step_methods/smc.py,SMC,calc_beta,#SMC#,280

Before Change

        while up_beta - low_beta > 1e-6:
            current_beta = (low_beta + up_beta) / 2.
            weights_un = np.exp((current_beta - self.beta) *
                                (self.likelihoods - self.likelihoods.max()))
            sj = np.mean(weights_un)
            cov_temp = np.std(weights_un) / sj
            if cov_temp > self.coef_variation:
                up_beta = current_beta
            else:
                low_beta = current_beta

After Change

            weights_un = np.exp((new_beta - old_beta) * (self.likelihoods - self.likelihoods.max()))

            weights = weights_un / np.sum(weights_un)
            ESS = int(1 / np.sum(weights ** 2))
            //ESS = int(1 / np.max(weights))
            if ESS == rN:
                break
            elif ESS < rN:

Instances