From 56d50e0469e3ef0c530d560ce2bfca59f5e23591 Mon Sep 17 00:00:00 2001 From: Alan Saul Date: Fri, 22 May 2015 21:16:38 +0100 Subject: [PATCH] Reshaped log predictive density to have D outputs --- GPy/likelihoods/likelihood.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py index 7a6721f9..31f5dffd 100644 --- a/GPy/likelihoods/likelihood.py +++ b/GPy/likelihoods/likelihood.py @@ -143,7 +143,7 @@ class Likelihood(Parameterized): p_ystar, _ = zip(*[quad(integral_generator(yi, mi, vi, yi_m), -np.inf, np.inf) for yi, mi, vi, yi_m in zipped_values]) - p_ystar = np.array(p_ystar).reshape(-1, 1) + p_ystar = np.array(p_ystar).reshape(*y_test.shape) return np.log(p_ystar) def log_predictive_density_sampling(self, y_test, mu_star, var_star, Y_metadata=None, num_samples=1000): @@ -173,6 +173,7 @@ class Likelihood(Parameterized): from scipy.misc import logsumexp log_p_ystar = -np.log(num_samples) + logsumexp(self.logpdf(fi_samples, y_test, Y_metadata=Y_metadata), axis=1) + log_p_ystar = np.array(log_p_ystar).reshape(*y_test.shape) return log_p_ystar