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BGPLVM working with rbf+white

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This commit is contained in:
Nicolo Fusi 2013-01-29 14:02:41 +00:00
parent 8b6e244cf1
commit 936d08723e
5 changed files with 105 additions and 32 deletions
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16
GPy/kern/rbf.py
View file

@ -95,7 +95,7 @@ class rbf(kernpart):
target += self.variance
def dpsi0_dtheta(self,partial,Z,mu,S,target):
target[0] += 1.
target[0] += np.sum(partial)
def dpsi0_dmuS(self,partial,Z,mu,S,target_mu,target_S):
pass
@ -113,7 +113,9 @@ class rbf(kernpart):
def dpsi1_dZ(self,partial,Z,mu,S,target):
self._psi_computations(Z,mu,S)
target += np.sum(partial[:,:,None]*-self._psi1[:,:,None]*self._psi1_dist/self.lengthscale2/self._psi1_denom,0)
denominator = (self.lengthscale2*(self._psi1_denom))
dpsi1_dZ = - self._psi1[:,:,None] * ((self._psi1_dist/denominator))
target += np.sum(partial.T[:,:,None] * dpsi1_dZ, 0)
def dpsi1_dmuS(self,partial,Z,mu,S,target_mu,target_S):
self._psi_computations(Z,mu,S)
@ -132,13 +134,14 @@ class rbf(kernpart):
d_length = self._psi2[:,:,:,None]*(0.5*self._psi2_Zdist_sq*self._psi2_denom + 2.*self._psi2_mudist_sq + 2.*S[:,None,None,:]/self.lengthscale2)/(self.lengthscale*self._psi2_denom)
d_length = d_length.sum(0)
target[0] += np.sum(partial*d_var)
target[1] += np.sum(d_length*partial)
target[1] += np.sum(d_length*partial[:,:,None])
def dpsi2_dZ(self,partial,Z,mu,S,target):
"""Returns shape N,M,M,Q"""
self._psi_computations(Z,mu,S)
dZ = self._psi2[:,:,:,None]/self.lengthscale2*(-0.5*self._psi2_Zdist + self._psi2_mudist/self._psi2_denom)
target += np.sum(partial[None,:,:,None]*dZ,0).sum(1)
term1 = 0.5*self._psi2_Zdist/self.lengthscale2 # M, M, Q
term2 = self._psi2_mudist/self._psi2_denom/self.lengthscale2 # N, M, M, Q
dZ = self._psi2[:,:,:,None] * (term1[None] + term2)
target += (partial[None,:,:,None]*dZ).sum(0).sum(0)
def dpsi2_dmuS(self,partial,Z,mu,S,target_mu,target_S):
"""Think N,M,M,Q """
@ -175,4 +178,3 @@ class rbf(kernpart):
self._psi2 = np.square(self.variance)*np.exp(self._psi2_exponent) # N,M,M
self._Z, self._mu, self._S = Z, mu,S

14
GPy/kern/rbf_ARD.py
View file

@ -74,7 +74,7 @@ class rbf_ARD(kernpart):
target += self.variance
def dpsi0_dtheta(self,partial,Z,mu,S,target):
target[0] += 1.
target[0] += np.sum(partial)
def dpsi0_dmuS(self,partial,Z,mu,S,target_mu,target_S):
pass
@ -93,7 +93,9 @@ class rbf_ARD(kernpart):
def dpsi1_dZ(self,partial,Z,mu,S,target):
self._psi_computations(Z,mu,S)
# np.add(target,-self._psi1[:,:,None]*self._psi1_dist/self.lengthscales2/self._psi1_denom,target)
target += np.sum(partial[:,:,None]*-self._psi1[:,:,None]*self._psi1_dist/self.lengthscales2/self._psi1_denom,0)
denominator = (self.lengthscales2*(self._psi1_denom))
dpsi1_dZ = - self._psi1[:,:,None] * ((self._psi1_dist/denominator))
target += np.sum(partial.T[:,:,None] * dpsi1_dZ, 0)
def dpsi1_dmuS(self,partial,Z,mu,S,target_mu,target_S):
"""return shapes are N,M,Q"""
@ -118,8 +120,10 @@ class rbf_ARD(kernpart):
def dpsi2_dZ(self,partial,Z,mu,S,target):
"""Returns shape N,M,M,Q"""
self._psi_computations(Z,mu,S)
dZ = self._psi2[:,:,:,None]/self.lengthscales2*(-0.5*self._psi2_Zdist + self._psi2_mudist/self._psi2_denom)
target += np.sum(partial[None,:,:,None]*dZ,0).sum(1)
term1 = 0.5*self._psi2_Zdist/self.lengthscales2 # M, M, Q
term2 = self._psi2_mudist/self._psi2_denom/self.lengthscales2 # N, M, M, Q
dZ = self._psi2[:,:,:,None] * (term1[None] + term2)
target += (partial[None,:,:,None]*dZ).sum(0).sum(0)
def dpsi2_dmuS(self,partial,Z,mu,S,target_mu,target_S):
"""Think N,M,M,Q """
@ -247,5 +251,3 @@ if __name__=='__main__':
return f,df
print "psi2_theta_test"
checkgrad(psi2_theta_test,np.random.rand(1+Q),args=(k,))