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[testing] updated tests wrt normalization

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mzwiessele 2014-09-05 12:40:00 +01:00
parent d06f8b9272
commit 32469e0461
1 changed files with 5 additions and 2 deletions
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7
GPy/testing/model_tests.py
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@ -19,9 +19,10 @@ class MiscTests(unittest.TestCase):
k = GPy.kern.RBF(1)
m = GPy.models.GPRegression(self.X, self.Y, kernel=k)
m.randomize()
Kinv = np.linalg.pinv(k.K(self.X) + np.eye(self.N)*m.Gaussian_noise.variance)
m.likelihood.variance = .5
Kinv = np.linalg.pinv(k.K(self.X) + np.eye(self.N)*m.likelihood.variance)
K_hat = k.K(self.X_new) - k.K(self.X_new, self.X).dot(Kinv).dot(k.K(self.X, self.X_new))
mu_hat = k.K(self.X_new, self.X).dot(Kinv).dot(self.Y)
mu_hat = k.K(self.X_new, self.X).dot(Kinv).dot(m.Y_normalized)
mu, covar = m._raw_predict(self.X_new, full_cov=True)
self.assertEquals(mu.shape, (self.N_new, self.D))
@ -431,6 +432,8 @@ class GradientTests(np.testing.TestCase):
k1 = GPy.kern.RBF(1) # + GPy.kern.White(1)
k2 = GPy.kern.RBF(1) # + GPy.kern.White(1)
Y = np.random.randn(N1, N2)
Y = Y-Y.mean(0)
Y = Y/Y.std(0)
m = GPy.models.GPKroneckerGaussianRegression(X1, X2, Y, k1, k2)
# build the model the dumb way