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renaming: posterior_variationa -> variational_posterior

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James Hensman 2014-02-24 19:31:13 +00:00
parent 17f9764a55
commit da4686dd3c
9 changed files with 58 additions and 63 deletions
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34
GPy/kern/_src/rbf.py
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@ -40,27 +40,27 @@ class RBF(Stationary):
self._Z, self._mu, self._S = np.empty(shape=(3, 1)) # cached versions of Z,mu,S
def psi0(self, Z, posterior_variational):
return self.Kdiag(posterior_variational.mean)
def psi0(self, Z, variational_posterior):
return self.Kdiag(variational_posterior.mean)
def psi1(self, Z, posterior_variational):
mu = posterior_variational.mean
S = posterior_variational.variance
def psi1(self, Z, variational_posterior):
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)
return self._psi1
def psi2(self, Z, posterior_variational):
mu = posterior_variational.mean
S = posterior_variational.variance
def psi2(self, Z, variational_posterior):
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)
return self._psi2
def update_gradients_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, posterior_variational):
def update_gradients_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
#contributions from Kmm
sself.update_gradients_full(dL_dKmm, Z)
mu = posterior_variational.mean
S = posterior_variational.variance
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)
l2 = self.lengthscale **2
@ -87,9 +87,9 @@ class RBF(Stationary):
else:
self.lengthscale.gradient += dpsi2_dlength.sum(0).sum(0).sum(0)
def gradients_Z_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, posterior_variational):
mu = posterior_variational.mean
S = posterior_variational.variance
def gradients_Z_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)
l2 = self.lengthscale **2
@ -108,9 +108,9 @@ class RBF(Stationary):
return grad
def gradients_q_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, posterior_variational):
mu = posterior_variational.mean
S = posterior_variational.variance
def gradients_q_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)
l2 = self.lengthscale **2
#psi1