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import not relative in tests

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This commit is contained in:
James Hensman 2014-03-13 10:23:07 +00:00
parent b87e25d031
commit 4d00b9db03
2 changed files with 10 additions and 10 deletions
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14
GPy/kern/_src/independent_outputs.py
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@ -73,7 +73,7 @@ class IndependentOutputs(Kern):
slices = index_to_slices(X[:,self.index_dim])
if X2 is None:
[[collate_grads(dL_dK[s,s], X[s], None) for s in slices_i] for slices_i in slices]
[[collate_grads(dL_dK[s,ss], X[s], X[ss]) for s,ss in itertools.product(slices_i, slices_i)] for slices_i in slices]
else:
slices2 = index_to_slices(X2[:,self.index_dim])
[[[collate_grads(dL_dK[s,s2],X[s],X2[s2]) for s in slices_i] for s2 in slices_j] for slices_i,slices_j in zip(slices,slices2)]
@ -83,10 +83,10 @@ class IndependentOutputs(Kern):
target = np.zeros_like(X)
slices = index_to_slices(X[:,self.index_dim])
if X2 is None:
[[np.copyto(target[s,:-1], self.kern.gradients_X(dL_dK[s,s],X[s],None)) for s in slices_i] for slices_i in slices]
[[np.copyto(target[s,self.kern.active_dims], self.kern.gradients_X(dL_dK[s,s],X[s],X[ss])) for s, ss in product(slices_i, slices_i)] for slices_i in slices]
else:
X2,slices2 = X2[:,:-1],index_to_slices(X2[:,-1])
[[[np.copyto(target[s,:-1], self.kern.gradients_X(dL_dK[s,s2], X[s], X2[s2])) for s in slices_i] for s2 in slices_j] for slices_i,slices_j in zip(slices,slices2)]
X2,slices2 = X2[:,:self.index_dim],index_to_slices(X2[:,-1])
[[[np.copyto(target[s,:self.index_dim], self.kern.gradients_X(dL_dK[s,s2], X[s], X2[s2])) for s in slices_i] for s2 in slices_j] for slices_i,slices_j in zip(slices,slices2)]
return target
def gradients_X_diag(self, dL_dKdiag, X):
@ -95,12 +95,12 @@ class IndependentOutputs(Kern):
[[np.copyto(target[s,:-1], self.kern.gradients_X_diag(dL_dKdiag[s],X[s])) for s in slices_i] for slices_i in slices]
return target
def update_gradients_diag(self,dL_dKdiag,X,target):
def update_gradients_diag(self, dL_dKdiag, X):
target = np.zeros(self.kern.size)
def collate_grads(dL, X):
self.kern.update_gradients_diag(dL,X)
self.target += self.kern.gradient
X,slices = X[:,:-1],index_to_slices(X[:,-1])
target[:] += self.kern.gradient
slices = index_to_slices(X[:,self.index_dim])
[[collate_grads(dL_dKdiag[s], X[s,:]) for s in slices_i] for slices_i in slices]
self.kern.gradient = target

6
GPy/testing/likelihood_tests.py
View file

@ -1,11 +1,11 @@
import numpy as np
import unittest
import GPy
from ..models import GradientChecker
from GPy.models import GradientChecker
import functools
import inspect
from ..likelihoods import link_functions
from ..core.parameterization import Param
from GPy.likelihoods import link_functions
from GPy.core.parameterization import Param
from functools import partial
#np.random.seed(300)
#np.random.seed(7)