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Changed the order of the operations, ensuring that the covariance matrix is symmetric despite numerical precision issues.

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Suggested by Alan.
This commit is contained in:
Teo de Campos 2016-12-06 11:01:45 -02:00
parent b1935292d9
commit a2f67febb4
1 changed files with 1 additions and 1 deletions
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GPy/kern/src/stationary.py
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@ -135,7 +135,7 @@ class Stationary(Kern):
#X2, = self._slice_X(X2) #X2, = self._slice_X(X2)
X1sq = np.sum(np.square(X),1) X1sq = np.sum(np.square(X),1)
X2sq = np.sum(np.square(X2),1) X2sq = np.sum(np.square(X2),1)
r2 = -2.*np.dot(X, X2.T) + X1sq[:,None] + X2sq[None,:] r2 = -2.*np.dot(X, X2.T) + (X1sq[:,None] + X2sq[None,:])
r2 = np.clip(r2, 0, np.inf) r2 = np.clip(r2, 0, np.inf)
return np.sqrt(r2) return np.sqrt(r2)