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[coverage] added normalizer tests

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Max Zwiessele 2015-09-04 13:28:22 +01:00
parent 296e4b078d
commit eddebd2ad9
1 changed files with 20 additions and 0 deletions
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20
GPy/testing/model_tests.py
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@ -36,6 +36,26 @@ class MiscTests(unittest.TestCase):
np.testing.assert_almost_equal(np.diag(K_hat)[:, None], var) np.testing.assert_almost_equal(np.diag(K_hat)[:, None], var)
np.testing.assert_almost_equal(mu_hat, mu) np.testing.assert_almost_equal(mu_hat, mu)
def test_normalizer(self):
k = GPy.kern.RBF(1)
Y = self.Y
mu, std = Y.mean(0), Y.std(0)
m = GPy.models.GPRegression(self.X, Y, kernel=k, normalizer=True)
m.optimize()
assert(m.checkgrad())
k = GPy.kern.RBF(1)
m2 = GPy.models.GPRegression(self.X, (Y-mu)/std, kernel=k, normalizer=False)
m2[:] = m[:]
mu1, var1 = m.predict(m.X, full_cov=True)
mu2, var2 = m2.predict(m2.X, full_cov=True)
np.testing.assert_allclose(mu1, (mu2*std)+mu)
np.testing.assert_allclose(var1, var2)
mu1, var1 = m.predict(m.X, full_cov=False)
mu2, var2 = m2.predict(m2.X, full_cov=False)
np.testing.assert_allclose(mu1, (mu2*std)+mu)
np.testing.assert_allclose(var1, var2)
def test_sparse_raw_predict(self): def test_sparse_raw_predict(self):
k = GPy.kern.RBF(1) k = GPy.kern.RBF(1)
m = GPy.models.SparseGPRegression(self.X, self.Y, kernel=k) m = GPy.models.SparseGPRegression(self.X, self.Y, kernel=k)