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Merge branch 'devel' of github.com:SheffieldML/GPy into devel

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mzwiessele 2015-04-24 11:02:05 +02:00
commit be40318e0b
1 changed files with 7 additions and 5 deletions
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12
GPy/likelihoods/likelihood.py
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@ -170,9 +170,9 @@ class Likelihood(Parameterized):
#only compute gh points if required
__gh_points = None
def _gh_points(self):
def _gh_points(self, T=20):
if self.__gh_points is None:
self.__gh_points = np.polynomial.hermite.hermgauss(20)
self.__gh_points = np.polynomial.hermite.hermgauss(T)
return self.__gh_points
def variational_expectations(self, Y, m, v, gh_points=None, Y_metadata=None):
@ -211,9 +211,11 @@ class Likelihood(Parameterized):
#d2logp_dx2 = np.clip(d2logp_dx2,-1e9,1e9)
#average over the gird to get derivatives of the Gaussian's parameters
F = np.dot(logp, gh_w)
dF_dm = np.dot(dlogp_dx, gh_w)
dF_dv = np.dot(d2logp_dx2, gh_w)/2.
#division by pi comes from fact that for each quadrature we need to scale by 1/sqrt(pi)
F = np.dot(logp, gh_w)/np.sqrt(np.pi)
dF_dm = np.dot(dlogp_dx, gh_w)/np.sqrt(np.pi)
dF_dv = np.dot(d2logp_dx2, gh_w)/np.sqrt(np.pi)
dF_dv /= 2.
if np.any(np.isnan(dF_dv)) or np.any(np.isinf(dF_dv)):
stop