mcmc_sampler.py 文件源码

def _sample_weights_precision(self):
        prior_observations = .1 * self.position_size
        shape = prior_observations + self.position_size / 2
        rate = prior_observations / self._weights_precision_value + np.mean(self._weight_norm_ema) / 2

        scale = 1. / rate
        sample = np.clip(np.random.gamma(shape, scale), .1, 10.)
        return sample