From e74bfd81c6139206fe2cd1f686db19397f865398 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Wed, 25 Mar 2015 14:22:39 +0000 Subject: [PATCH] added some clarifying comments with NDL --- .../latent_function_inference/expectation_propagation.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/GPy/inference/latent_function_inference/expectation_propagation.py b/GPy/inference/latent_function_inference/expectation_propagation.py index 26144974..647823bd 100644 --- a/GPy/inference/latent_function_inference/expectation_propagation.py +++ b/GPy/inference/latent_function_inference/expectation_propagation.py @@ -40,8 +40,11 @@ class EP(LatentFunctionInference): K = kern.K(X) if self._ep_approximation is None: + + #if we don't yet have the results of runnign EP, run EP and store the computed factors in self._ep_approximation mu, Sigma, mu_tilde, tau_tilde, Z_hat = self._ep_approximation = self.expectation_propagation(K, Y, likelihood, Y_metadata) else: + #if we've already run EP, just use the existing approximation stored in self._ep_approximation mu, Sigma, mu_tilde, tau_tilde, Z_hat = self._ep_approximation Wi, LW, LWi, W_logdet = pdinv(K + np.diag(1./tau_tilde))