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[merge] devel and plotting tests from meanfunc

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mzwiessele 2016-08-03 08:55:26 +01:00
commit 52567d7732
6 changed files with 44 additions and 4 deletions
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GPy/testing/baseline/bayesian_gplvm_magnification.npz
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GPy/testing/meanfunc_tests.py
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@ -28,10 +28,49 @@ class MFtests(unittest.TestCase):
A linear mean function with parameters that we'll learn alongside the kernel
"""
X = np.linspace(-1,10,50).reshape(-1,1)
Y = 3-np.abs((X-6))
Y += .5*np.cos(3*X) + 0.3*np.random.randn(*X.shape)
mf = GPy.mappings.PiecewiseLinear(1, 1, [-1,1], [9,2])
k =GPy.kern.RBF(1)
lik = GPy.likelihoods.Gaussian()
m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf)
self.assertTrue(m.checkgrad())
def test_parametric_mean_function_composition(self):
"""
A linear mean function with parameters that we'll learn alongside the kernel
"""
X = np.linspace(0,10,50).reshape(-1,1)
Y = np.sin(X) + 0.5*np.cos(3*X) + 0.1*np.random.randn(*X.shape) + 3*X
mf = GPy.mappings.Linear(1,1)
mf = GPy.mappings.Compound(GPy.mappings.Linear(1,1),
GPy.mappings.Kernel(1, 1, np.random.normal(0,1,(1,1)),
GPy.kern.RBF(1))
)
k =GPy.kern.RBF(1)
lik = GPy.likelihoods.Gaussian()
m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf)
self.assertTrue(m.checkgrad())
def test_parametric_mean_function_additive(self):
"""
A linear mean function with parameters that we'll learn alongside the kernel
"""
X = np.linspace(0,10,50).reshape(-1,1)
Y = np.sin(X) + 0.5*np.cos(3*X) + 0.1*np.random.randn(*X.shape) + 3*X
mf = GPy.mappings.Additive(GPy.mappings.Constant(1,1,3),
GPy.mappings.Additive(GPy.mappings.MLP(1,1),
GPy.mappings.Identity(1,1)
)
)
k =GPy.kern.RBF(1)
lik = GPy.likelihoods.Gaussian()