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last changes for mrd stability

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Max Zwiessele 2013-05-08 16:47:56 +01:00
parent f39afb9ea5
commit 18117bba81
4 changed files with 8 additions and 7 deletions
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6
GPy/models/sparse_GP.py
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@ -81,7 +81,7 @@ class sparse_GP(GP):
# psi2_beta_scaled = (self.psi2 * (self.likelihood.precision.flatten().reshape(self.N, 1, 1) / sf2)).sum(0)
psi2_beta_scaled = (self.psi2 * (self.likelihood.precision.flatten().reshape(self.N, 1, 1))).sum(0)
evals, evecs = linalg.eigh(psi2_beta_scaled)
clipped_evals = np.clip(evals, 0., 1e6) # TODO: make clipping configurable
clipped_evals = np.clip(evals, 0., 1e15) # TODO: make clipping configurable
if not np.allclose(evals, clipped_evals):
print "Warning: clipping posterior eigenvalues"
tmp = evecs * np.sqrt(clipped_evals)
@ -97,7 +97,7 @@ class sparse_GP(GP):
# psi2_beta_scaled = (self.psi2 * (self.likelihood.precision / sf2)).sum(0)
psi2_beta_scaled = (self.psi2 * (self.likelihood.precision)).sum(0)
evals, evecs = linalg.eigh(psi2_beta_scaled)
clipped_evals = np.clip(evals, 0., 1e6) # TODO: make clipping configurable
clipped_evals = np.clip(evals, 0., 1e15) # TODO: make clipping configurable
if not np.allclose(evals, clipped_evals):
print "Warning: clipping posterior eigenvalues"
tmp = evecs * np.sqrt(clipped_evals)
@ -259,7 +259,7 @@ class sparse_GP(GP):
Kmmi_LmiBLmi = backsub_both_sides(self.Lm, np.eye(self.M) - Bi)
Kx = self.kern.K(self.Z, Xnew, which_parts=which_parts)
mu = np.dot(Kx.T, self.Cpsi1V / self.scale_factor)
mu = np.dot(Kx.T, self.Cpsi1V) # / self.scale_factor)
if full_cov:
Kxx = self.kern.K(Xnew, which_parts=which_parts)
var = Kxx - mdot(Kx.T, Kmmi_LmiBLmi, Kx) # NOTE this won't work for plotting