elliptical_slice_sampler.py 文件源码

def sample(self, model):
        if not model.has_data:
            return np.zeros(0) # TODO this should be a sample from the prior...

        prior_cov      = model.noiseless_kernel.cov(model.inputs)
        prior_cov_chol = spla.cholesky(prior_cov, lower=True)
        # Here get the Cholesky from model

        params_array = hyperparameter_utils.params_to_array(self.params)
        for i in xrange(self.thinning + 1):
            params_array, current_ll = elliptical_slice(
                params_array,
                self.logprob,
                prior_cov_chol,
                model.mean.value,
                model,
                **self.sampler_options
            )
            hyperparameter_utils.set_params_from_array(self.params, params_array)
        self.current_ll = current_ll # for diagnostics


# xx: the initial point
# sample_nu: a function that samples from the multivariate Gaussian prior
# log_like_fn: a function that computes the log likelihood of an input
# cur_log_like (optional): the current log likelihood
# angle_range: not sure