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more edits for variational expectations in likelihoods

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This commit is contained in:
James Hensman 2014-10-16 16:26:15 +01:00
parent 30343f5e53
commit 6983751420
1 changed files with 12 additions and 2 deletions
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14
GPy/likelihoods/likelihood.py
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@ -145,7 +145,7 @@ class Likelihood(Parameterized):
""" """
if gh_points is None: if gh_points is None:
gh_x, gh_w = np.polynomial.hermite.hermgauss(20) gh_x, gh_w = np.polynomial.hermite.hermgauss(12)
else: else:
gh_x, gh_w = gh_points gh_x, gh_w = gh_points
@ -161,12 +161,22 @@ class Likelihood(Parameterized):
dlogp_dx = self.dlogpdf_df(X, Y[:,None]) dlogp_dx = self.dlogpdf_df(X, Y[:,None])
d2logp_dx2 = self.d2logpdf_df2(X, Y[:,None]) d2logp_dx2 = self.d2logpdf_df2(X, Y[:,None])
#clipping for numerical stability
logp = np.clip(logp,-1e6,1e6)
dlogp_dx = np.clip(dlogp_dx,-1e6,1e6)
d2logp_dx2 = np.clip(d2logp_dx2,-1e6,1e6)
#average over the gird to get derivatives of the Gaussian's parameters #average over the gird to get derivatives of the Gaussian's parameters
F = np.dot(logp, gh_w) F = np.dot(logp, gh_w)
dF_dm = np.dot(dlogp_dx, gh_w) dF_dm = np.dot(dlogp_dx, gh_w)
dF_dv = np.dot(d2logp_dx2, gh_w)/2. dF_dv = np.dot(d2logp_dx2, gh_w)/2.
return F, dF_dm, dF_dv if np.any(np.isnan(dF_dv)) or np.any(np.isinf(dF_dv)):
stop
if np.any(np.isnan(dF_dm)) or np.any(np.isinf(dF_dm)):
stop
return F.reshape(*shape), dF_dm.reshape(*shape), dF_dv.reshape(*shape)