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fixed unnecessary warnings when using periodic kernels

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durrande 2014-06-08 18:37:07 +02:00
parent ec1b9190f5
commit 1dfe7ed0a8
1 changed files with 2 additions and 1 deletions
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GPy/kern/_src/periodic.py
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@ -101,6 +101,7 @@ class PeriodicExponential(Periodic):
Flower = np.array(self._cos(self.basis_alpha,self.basis_omega,self.basis_phi)(self.lower))[:,None] Flower = np.array(self._cos(self.basis_alpha,self.basis_omega,self.basis_phi)(self.lower))[:,None]
return(self.lengthscale/(2*self.variance) * Gint + 1./self.variance*np.dot(Flower,Flower.T)) return(self.lengthscale/(2*self.variance) * Gint + 1./self.variance*np.dot(Flower,Flower.T))
@silence_errors
def update_gradients_full(self, dL_dK, X, X2=None): def update_gradients_full(self, dL_dK, X, X2=None):
"""derivative of the covariance matrix with respect to the parameters (shape is N x num_inducing x num_params)""" """derivative of the covariance matrix with respect to the parameters (shape is N x num_inducing x num_params)"""
if X2 is None: X2 = X if X2 is None: X2 = X
@ -213,7 +214,7 @@ class PeriodicMatern32(Periodic):
return(self.lengthscale**3/(12*np.sqrt(3)*self.variance) * Gint + 1./self.variance*np.dot(Flower,Flower.T) + self.lengthscale**2/(3.*self.variance)*np.dot(F1lower,F1lower.T)) return(self.lengthscale**3/(12*np.sqrt(3)*self.variance) * Gint + 1./self.variance*np.dot(Flower,Flower.T) + self.lengthscale**2/(3.*self.variance)*np.dot(F1lower,F1lower.T))
#@silence_errors @silence_errors
def update_gradients_full(self,dL_dK,X,X2): def update_gradients_full(self,dL_dK,X,X2):
"""derivative of the covariance matrix with respect to the parameters (shape is num_data x num_inducing x num_params)""" """derivative of the covariance matrix with respect to the parameters (shape is num_data x num_inducing x num_params)"""
if X2 is None: X2 = X if X2 is None: X2 = X