apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-24 14:15:14 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

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

Browse source 
Conflicts:
	GPy/examples/regression.py
	GPy/kern/constructors.py
	GPy/testing/kernel_tests.py
	GPy/util/multioutput.py
This commit is contained in:
Ricardo 2013-09-16 12:32:42 +01:00
commit 603aa18482
25 changed files with 400 additions and 72 deletions
Download patch file Download diff file Expand all files Collapse all files

8
GPy/core/model.py
View file

@ -1,4 +1,4 @@
# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
# Copyright (c) 2012, 2013, GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
@ -459,8 +459,8 @@ class Model(Parameterized):
gradient = self.objective_function_gradients(x)
numerical_gradient = (f1 - f2) / (2 * dx)
global_ratio = (f1 - f2) / (2 * np.dot(dx, gradient))
global_ratio = (f1 - f2) / (2 * np.dot(dx, np.where(gradient==0, 1e-32, gradient)))
return (np.abs(1. - global_ratio) < tolerance) or (np.abs(gradient - numerical_gradient).mean() < tolerance)
else:
# check the gradient of each parameter individually, and do some pretty printing
@ -499,7 +499,7 @@ class Model(Parameterized):
gradient = self.objective_function_gradients(x)[i]
numerical_gradient = (f1 - f2) / (2 * step)
ratio = (f1 - f2) / (2 * step * gradient)
ratio = (f1 - f2) / (2 * step * np.where(gradient==0, 1e-312, gradient))
difference = np.abs((f1 - f2) / 2 / step - gradient)
if (np.abs(1. - ratio) < tolerance) or np.abs(difference) < tolerance: