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Solved incorrect parameter assignments (causing test faillure)

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Joachim van der Herten 2017-07-15 00:35:39 +02:00
parent 394d3ea236
commit 4af1f017ec
3 changed files with 3 additions and 5 deletions
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1
GPy/inference/latent_function_inference/posterior.py
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@ -318,7 +318,6 @@ class StudentTPosterior(PosteriorExact):
self.nu = deg_free
def _raw_predict(self, kern, Xnew, pred_var, full_cov=False):
print(self.nu)
mu, var = super(StudentTPosterior, self)._raw_predict(kern, Xnew, pred_var, full_cov)
beta = np.sum(self.woodbury_vector * self.mean)
N = self.woodbury_vector.shape[0]

1
GPy/testing/gp_tests.py
View file

@ -92,7 +92,6 @@ class Test(unittest.TestCase):
Y = p.f(X) + np.random.multivariate_normal(np.zeros(X.shape[0]), k.K(X)+np.eye(X.shape[0])*1e-8)[:,None] + np.random.normal(0, .1, (X.shape[0], 1))
m = GPy.models.GPRegression(X, Y, mean_function=p)
m.randomize()
print(m)
assert(m.checkgrad())
_ = m.predict(m.X)

6
GPy/testing/tp_tests.py
View file

@ -131,11 +131,11 @@ class Test(unittest.TestCase):
k = GPy.kern.RBF(1)
m = GPy.models.GPRegression(self.X, self.Y, kernel=k)
m.optimize()
k1 = GPy.kern.RBF(1, variance=k.variance, lengthscale=k.lengthscale)
mu1, var1 = m.predict(self.X)
k1 = GPy.kern.RBF(1)
k1[:] = k[:]
k2 = GPy.kern.White(1, variance=m.likelihood.variance)
m2 = GPy.models.TPRegression(self.X, self.Y, kernel=k1 + k2, deg_free=1e6)
mu1, var1 = m.predict(self.X)
mu2, var2 = m2.predict(self.X)
np.testing.assert_allclose(mu1, mu2)
np.testing.assert_allclose(var1, var2)