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Make get_post_fcov methods return posterior covariance matrices of Gaussian Process #66

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Jan 29, 2025
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Make get_post_fcov methods return posterior covariance matrices of Gaussian Process #66

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2 changes: 1 addition & 1 deletion physbo/blm/core/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -224,7 +224,7 @@ def get_post_fcov(self, X, Psi=None, diag=True):
physbo.blm.inf.exact.get_post_fcov
"""
if self.method == "exact":
fcov = inf.exact.get_post_fcov(self, X, Psi, diag=True)
fcov = inf.exact.get_post_fcov(self, X, Psi, diag=diag)
else:
pass
return fcov
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4 changes: 2 additions & 2 deletions physbo/blm/predictor.py
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Expand Up @@ -106,7 +106,7 @@ def get_post_fmean(self, training, test):
self.prepare(training)
return self.blm.get_post_fmean(test.X, test.Z)

def get_post_fcov(self, training, test):
def get_post_fcov(self, training, test, diag=True):
"""
calculates posterior variance-covariance matrix of model

Expand All @@ -123,7 +123,7 @@ def get_post_fcov(self, training, test):
"""
if self.blm.stats is None:
self.prepare(training)
return self.blm.get_post_fcov(test.X, test.Z)
return self.blm.get_post_fcov(test.X, test.Z, diag)

def get_post_params(self, training, test):
"""
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6 changes: 3 additions & 3 deletions physbo/search/discrete/policy.py
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Expand Up @@ -360,18 +360,18 @@ def get_post_fmean(self, xs):
self._update_predictor()
return self.predictor.get_post_fmean(self.training, X)

def get_post_fcov(self, xs):
def get_post_fcov(self, xs, diag=True):
"""Calculate covariance of predictor (post distribution)"""
X = self._make_variable_X(xs)
if self.predictor is None:
self._warn_no_predictor("get_post_fcov()")
predictor = gp_predictor(self.config)
predictor.fit(self.training, 0)
predictor.prepare(self.training)
return predictor.get_post_fcov(self.training, X)
return predictor.get_post_fcov(self.training, X, diag)
else:
self._update_predictor()
return self.predictor.get_post_fcov(self.training, X)
return self.predictor.get_post_fcov(self.training, X, diag)

def get_score(
self,
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