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merged with master

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Nicolo Fusi 2013-02-15 11:56:37 +00:00
commit 2abba8cf14
59 changed files with 2845 additions and 1608 deletions
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7
GPy/kern/kern.py
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@ -6,7 +6,7 @@ import numpy as np
from ..core.parameterised import parameterised
from kernpart import kernpart
import itertools
from product_orthogonal import product_orthogonal
from product_orthogonal import product_orthogonal
class kern(parameterised):
def __init__(self,D,parts=[], input_slices=None):
@ -155,7 +155,7 @@ class kern(parameterised):
D = K1.D + K2.D
newkernparts = [product_orthogonal(k1,k2).parts[0] for k1, k2 in itertools.product(K1.parts,K2.parts)]
newkernparts = [product_orthogonal(k1,k2) for k1, k2 in itertools.product(K1.parts,K2.parts)]
slices = []
for sl1, sl2 in itertools.product(K1.input_slices,K2.input_slices):
@ -235,6 +235,8 @@ class kern(parameterised):
X2 = X
target = np.zeros(self.Nparam)
[p.dK_dtheta(partial[s1,s2],X[s1,i_s],X2[s2,i_s],target[ps]) for p,i_s,ps,s1,s2 in zip(self.parts, self.input_slices, self.param_slices, slices1, slices2)]
#TODO: transform the gradients here!
return target
def dK_dX(self,partial,X,X2=None,slices1=None,slices2=None):
@ -324,6 +326,7 @@ class kern(parameterised):
[p.psi2(Z[s2,i_s],mu[s1,i_s],S[s1,i_s],target[s1,s2,s2]) for p,i_s,s1,s2 in zip(self.parts,self.input_slices,slices1,slices2)]
# "crossterms". Here we are recomputing psi1 for white (we don't need to), but it's
# not really expensive, since it's just a matrix of zeroes.
# psi1_matrices = [np.zeros((mu.shape[0], Z.shape[0])) for p in self.parts]