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Refactor EP and EPDTC

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Moreno 2017-06-07 16:37:40 +01:00 • committed by Akash Kumar Dhaka
parent 7c4e2f21f8
commit 255d97a917
2 changed files with 233 additions and 209 deletions
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8
GPy/testing/inference_tests.py
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@ -73,11 +73,11 @@ class InferenceGPEP(unittest.TestCase):
inference_method=inf,
likelihood=lik)
K = self.model.kern.K(X)
mu, Sigma, mu_tilde, tau_tilde, log_Z_tilde = self.model.inference_method.expectation_propagation(K, ObsAr(Y), lik, None)
post_params, ga_approx, log_Z_tilde = self.model.inference_method.expectation_propagation(K, ObsAr(Y), lik, None)
v_tilde = mu_tilde * tau_tilde
p, m, d = self.model.inference_method._inference(K, tau_tilde, v_tilde, lik, Y_metadata=None, Z_tilde=log_Z_tilde.sum())
p0, m0, d0 = super(GPy.inference.latent_function_inference.expectation_propagation.EP, inf).inference(k, X,lik ,mu_tilde[:,None], mean_function=None, variance=1./tau_tilde, K=K, Z_tilde=log_Z_tilde.sum() + np.sum(- 0.5*np.log(tau_tilde) + 0.5*(v_tilde*v_tilde*1./tau_tilde)))
mu_tilde = ga_approx.v / ga_approx.tau.astype(float)
p, m, d = self.model.inference_method._inference(K, ga_approx, lik, Y_metadata=None, Z_tilde=log_Z_tilde)
p0, m0, d0 = super(GPy.inference.latent_function_inference.expectation_propagation.EP, inf).inference(k, X,lik ,mu_tilde[:,None], mean_function=None, variance=1./ga_approx.tau, K=K, Z_tilde=log_Z_tilde + np.sum(- 0.5*np.log(ga_approx.tau) + 0.5*(ga_approx.v*ga_approx.v*1./ga_approx.tau)))
assert (np.sum(np.array([m - m0,
np.sum(d['dL_dK'] - d0['dL_dK']),