whitened_prior_slice_sampler.py 文件源码

def sample_fun(self, model, **sampler_options):
        params_array = hyperparameter_utils.params_to_array(self.params)

        if model.has_data:
            K_XX      = model.noiseless_kernel.cov(model.inputs)
            current_L = spla.cholesky(K_XX, lower=True)
            nu        = spla.solve_triangular(current_L, model.latent_values.value-model.mean.value, lower=True)
        else:
            nu = None # if no data

        new_params, current_ll = slice_sample(params_array, self.logprob, model, nu, **sampler_options)

        new_latent_values = self._compute_implied_y(model, nu)

        return new_params, new_latent_values, current_ll