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Update model.py

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Max Zwiessele 2015-09-13 08:42:58 +01:00
parent 61c972fbd5
commit 3a72634149
1 changed files with 4 additions and 4 deletions
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8
GPy/core/model.py
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@ -368,9 +368,9 @@ class Model(Parameterized):
for nind, xind in zip(param_index, transformed_index): for nind, xind in zip(param_index, transformed_index):
xx = x.copy() xx = x.copy()
xx[xind] += step xx[xind] += step
f1 = self._objective(xx) f1 = float(self._objective(xx))
xx[xind] -= 2.*step xx[xind] -= 2.*step
f2 = self._objective(xx) f2 = float(self._objective(xx))
#Avoid divide by zero, if any of the values are above 1e-15, otherwise both values are essentiall #Avoid divide by zero, if any of the values are above 1e-15, otherwise both values are essentiall
#the same #the same
if f1 > 1e-15 or f1 < -1e-15 or f2 > 1e-15 or f2 < -1e-15: if f1 > 1e-15 or f1 < -1e-15 or f2 > 1e-15 or f2 < -1e-15:
@ -378,9 +378,9 @@ class Model(Parameterized):
else: else:
df_ratio = 1.0 df_ratio = 1.0
df_unstable = df_ratio < df_tolerance df_unstable = df_ratio < df_tolerance
numerical_gradient = (f1 - f2) / (2 * step) numerical_gradient = (f1 - f2) / (2. * step)
if np.all(gradient[xind] == 0): ratio = (f1 - f2) == gradient[xind] if np.all(gradient[xind] == 0): ratio = (f1 - f2) == gradient[xind]
else: ratio = (f1 - f2) / (2 * step * gradient[xind]) else: ratio = (f1 - f2) / (2. * step * gradient[xind])
difference = np.abs(numerical_gradient - gradient[xind]) difference = np.abs(numerical_gradient - gradient[xind])
if (np.abs(1. - ratio) < tolerance) or np.abs(difference) < tolerance: if (np.abs(1. - ratio) < tolerance) or np.abs(difference) < tolerance: