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[density] plotting of likelihoods permitted

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mzwiessele 2015-10-02 07:47:57 +01:00
parent d8243383b4
commit fee2f3f727
2 changed files with 13 additions and 17 deletions
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6
GPy/core/gp.py
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@ -272,7 +272,7 @@ class GP(Model):
mean, var = self.likelihood.predictive_values(mu, var, full_cov, Y_metadata=Y_metadata)
return mean, var
def predict_quantiles(self, X, quantiles=(2.5, 97.5), Y_metadata=None, kern=None):
def predict_quantiles(self, X, quantiles=(2.5, 97.5), Y_metadata=None, kern=None, likelihood=None):
"""
Get the predictive quantiles around the prediction at X
@ -288,7 +288,9 @@ class GP(Model):
m, v = self._raw_predict(X, full_cov=False, kern=kern)
if self.normalizer is not None:
m, v = self.normalizer.inverse_mean(m), self.normalizer.inverse_variance(v)
return self.likelihood.predictive_quantiles(m, v, quantiles, Y_metadata=Y_metadata)
if likelihood is None:
likelihood = self.likelihood
return likelihood.predictive_quantiles(m, v, quantiles, Y_metadata=Y_metadata)
def predictive_gradients(self, Xnew):
"""