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global gradient test done and some parameterized fixes

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Max Zwiessele 2014-02-28 16:58:24 +00:00
parent eae3c28dc0
commit 20e02e63a9
7 changed files with 39 additions and 93 deletions
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8
GPy/core/model.py
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@ -226,6 +226,11 @@ class Model(Parameterized):
TODO: valid args
"""
if self.is_fixed:
raise RuntimeError, "Cannot optimize, when everything is fixed"
if self.size == 0:
raise RuntimeError, "Model without parameters cannot be minimized"
if optimizer is None:
optimizer = self.preferred_optimizer
@ -294,9 +299,8 @@ class Model(Parameterized):
dx = dx[transformed_index]
gradient = gradient[transformed_index]
numerical_gradient = (f1 - f2) / (2 * dx)
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)
return (np.abs(1. - global_ratio) < tolerance)
else:
# check the gradient of each parameter individually, and do some pretty printing
try: