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Merge branch 'devel' of github.com:SheffieldML/GPy into devel

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Ricardo 2013-09-16 15:46:26 +01:00
commit 2a6c638707
2 changed files with 4 additions and 2 deletions
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2
GPy/kern/parts/prod.py
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@ -90,6 +90,8 @@ class Prod(Kernpart):
def dK_dX(self,dL_dK,X,X2,target): def dK_dX(self,dL_dK,X,X2,target):
"""derivative of the covariance matrix with respect to X.""" """derivative of the covariance matrix with respect to X."""
self._K_computations(X,X2) self._K_computations(X,X2)
if X2 is None:
X2 = X
self.k1.dK_dX(dL_dK*self._K2, X[:,self.slice1], X2[:,self.slice1], target[:,self.slice1]) self.k1.dK_dX(dL_dK*self._K2, X[:,self.slice1], X2[:,self.slice1], target[:,self.slice1])
self.k2.dK_dX(dL_dK*self._K1, X[:,self.slice2], X2[:,self.slice2], target[:,self.slice2]) self.k2.dK_dX(dL_dK*self._K1, X[:,self.slice2], X2[:,self.slice2], target[:,self.slice2])

4
GPy/kern/parts/rational_quadratic.py
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@ -57,7 +57,7 @@ class RationalQuadratic(Kernpart):
dist2 = np.square((X-X2.T)/self.lengthscale) dist2 = np.square((X-X2.T)/self.lengthscale)
dvar = (1 + dist2/2.)**(-self.power) dvar = (1 + dist2/2.)**(-self.power)
dl = self.power * self.variance * dist2 * self.lengthscale**(-3) * (1 + dist2/2./self.power)**(-self.power-1) dl = self.power * self.variance * dist2 / self.lengthscale * (1 + dist2/2.)**(-self.power-1)
dp = - self.variance * np.log(1 + dist2/2.) * (1 + dist2/2.)**(-self.power) dp = - self.variance * np.log(1 + dist2/2.) * (1 + dist2/2.)**(-self.power)
target[0] += np.sum(dvar*dL_dK) target[0] += np.sum(dvar*dL_dK)
@ -70,7 +70,7 @@ class RationalQuadratic(Kernpart):
def dK_dX(self,dL_dK,X,X2,target): def dK_dX(self,dL_dK,X,X2,target):
"""derivative of the covariance matrix with respect to X.""" """derivative of the covariance matrix with respect to X."""
if X2 is None: if X2 is None:
dist2 = np.square((X-X.T)/self.lengthscale) dist2 = np.square((X-X.T)/self.lengthscale)
dX = -2.*self.variance*self.power * (X-X.T)/self.lengthscale**2 * (1 + dist2/2./self.lengthscale)**(-self.power-1) dX = -2.*self.variance*self.power * (X-X.T)/self.lengthscale**2 * (1 + dist2/2./self.lengthscale)**(-self.power-1)
else: else: