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fix: pkg: added tests for multioutput regression with normalizer

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mzwiessele 2018-02-12 17:14:53 +01:00
parent 56696ced27
commit eac941f534
1 changed files with 35 additions and 8 deletions
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43
GPy/testing/model_tests.py
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@ -124,17 +124,44 @@ class MiscTests(unittest.TestCase):
""" """
# Create test inputs # Create test inputs
X1 = (np.random.rand(50, 1) * 8) X = self.X
Y1 = np.sin(X1) + np.random.randn(*X1.shape) * 0.05 Y1 = np.sin(X) + np.random.randn(*X.shape) * 0.2
Y2 = -np.sin(X1) + np.random.randn(*X1.shape) * 0.05 Y2 = -np.sin(X) + np.random.randn(*X.shape) * 0.05
Y = np.hstack((Y1, Y2)) Y = np.hstack((Y1, Y2))
m = GPy.models.GPRegression(X1, Y, normalizer=True) mu, std = Y.mean(0), Y.std(0)
m = GPy.models.GPRegression(X, Y, normalizer=True)
m.optimize(messages=True)
assert(m.checkgrad())
k = GPy.kern.RBF(1)
m2 = GPy.models.GPRegression(X, (Y-mu)/std, normalizer=False)
m2[:] = m[:]
n_test_point = 10 mu1, var1 = m.predict(m.X, full_cov=True)
mean, covaraince = m.predict(np.random.rand(n_test_point, 1), mu2, var2 = m2.predict(m2.X, full_cov=True)
full_cov=True) np.testing.assert_allclose(mu1, (mu2*std)+mu)
self.assertTrue(covaraince.shape == (n_test_point, n_test_point, 2)) np.testing.assert_allclose(var1, var2[:, :, None]*std[None, None, :]**2)
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*std[None, :]**2)
q50n = m.predict_quantiles(m.X, (50,))
q50 = m2.predict_quantiles(m2.X, (50,))
np.testing.assert_allclose(q50n[0], (q50[0]*std)+mu)
# Test variance component:
qs = np.array([2.5, 97.5])
# The quantiles get computed before unormalization
# And transformed using the mean transformation:
c = np.random.choice(X.shape[0])
q95 = m2.predict_quantiles(X[[c]], qs)
mu, var = m2.predict(X[[c]])
from scipy.stats import norm
np.testing.assert_allclose((mu.T+(norm.ppf(qs/100.)*np.sqrt(var))).T.flatten(), np.array(q95).flatten())
def check_jacobian(self): def check_jacobian(self):
try: try: