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Merge branch 'devel' of github.com:SheffieldML/GPy into devel

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Zhenwen Dai 2015-08-27 17:05:01 +01:00
commit 81cdc8b49d
1 changed files with 7 additions and 6 deletions
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13
GPy/testing/model_tests.py
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@ -352,8 +352,8 @@ class GradientTests(np.testing.TestCase):
self.check_model(rbf, model_type='SparseGPRegression', dimension=2)
def test_SparseGPRegression_rbf_linear_white_kern_1D(self):
''' Testing the sparse GP regression with rbf kernel on 2d data '''
rbflin = GPy.kern.RBF(1) + GPy.kern.Linear(1)
''' Testing the sparse GP regression with rbf kernel on 1d data '''
rbflin = GPy.kern.RBF(1) + GPy.kern.Linear(1) + GPy.kern.White(1, 1e-5)
self.check_model(rbflin, model_type='SparseGPRegression', dimension=1)
def test_SparseGPRegression_rbf_linear_white_kern_2D(self):
@ -472,6 +472,7 @@ class GradientTests(np.testing.TestCase):
self.assertTrue(m.checkgrad())
def test_gp_kronecker_gaussian(self):
np.random.seed(0)
N1, N2 = 30, 20
X1 = np.random.randn(N1, 1)
X2 = np.random.randn(N2, 1)
@ -492,16 +493,16 @@ class GradientTests(np.testing.TestCase):
m.randomize()
mm[:] = m[:]
assert np.allclose(m.log_likelihood(), mm.log_likelihood())
assert np.allclose(m.gradient, mm.gradient)
self.assertTrue(np.allclose(m.log_likelihood(), mm.log_likelihood()))
self.assertTrue(np.allclose(m.gradient, mm.gradient))
X1test = np.random.randn(100, 1)
X2test = np.random.randn(100, 1)
mean1, var1 = m.predict(X1test, X2test)
yy, xx = np.meshgrid(X2test, X1test)
Xgrid = np.vstack((xx.flatten(order='F'), yy.flatten(order='F'))).T
mean2, var2 = mm.predict(Xgrid)
assert np.allclose(mean1, mean2)
assert np.allclose(var1, var2)
self.assertTrue( np.allclose(mean1, mean2) )
self.assertTrue( np.allclose(var1, var2) )
def test_gp_VGPC(self):
num_obs = 25