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cmm_creation

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beiwang 2016-11-11 19:59:45 +00:00
parent 567601344c
commit fbb55a3998
2 changed files with 0 additions and 10 deletions
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4
GPy/core/parameterization/variational.py
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@ -63,10 +63,6 @@ class GmmNormalPrior(VariationalPrior):
def KL_divergence(self, variational_posterior):
# Lagrange multiplier maybe also needed here
# var_mean = np.square(variational_posterior.mean).sum()
# var_S = (variational_posterior.variance - np.log(variational_posterior.variance)).sum()
# return 0.5 * (var_mean + var_S) - 0.5 * variational_posterior.input_dim * variational_posterior.num_data
mu = variational_posterior.mean
S = variational_posterior.variance
pi = self.variational_pi

6
GPy/models/gmm_bayesian_gplvm.py
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@ -61,12 +61,6 @@ class GmmBayesianGPLVM(SparseGP_MPI):
px_mu[i] = np.zeros(X_variance.shape)
px_var[i] = np.ones(X_variance.shape)
# print("Should print")
# print(pi)
# print(px_mu)
# print(px_var)
# print(variational_pi)
# print("Didnt print")
self.variational_prior = GmmNormalPrior(px_mu=px_mu, px_var=px_var, pi=pi,
n_component=n_component, variational_pi=variational_pi)