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edited coregionalize implementation

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This commit is contained in:
James Hensman 2014-09-30 16:44:55 +01:00
parent 9081c8ee96
commit f4718edfb8
2 changed files with 37 additions and 39 deletions
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59
GPy/testing/kernel_tests.py
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@ -360,43 +360,44 @@ class Coregionalize_weave_test(unittest.TestCase):
"""
Make sure that the coregionalize kernel work with and without weave enabled
"""
k = GPy.kern.coregionalize(1, output_dim=12)
N1, N2 = 100, 200
X = np.random.randint(0,12,(N1,1))
X2 = np.random.randint(0,12,(N2,1))
def setUp(self):
self.k = GPy.kern.Coregionalize(1, output_dim=12)
self.N1, self.N2 = 100, 200
self.X = np.random.randint(0,12,(self.N1,1))
self.X2 = np.random.randint(0,12,(self.N2,1))
#symmetric case
dL_dK = np.random.randn(N1, N1)
GPy.util.config.config.set('weave', 'working', True)
K_weave = k.K(X)
k.update_gradients_full(dL_dK, X)
grads_weave = k.gradient.copy()
def test_sym(self):
dL_dK = np.random.randn(self.N1, self.N1)
GPy.util.config.config.set('weave', 'working', 'True')
K_weave = self.k.K(self.X)
self.k.update_gradients_full(dL_dK, self.X)
grads_weave = self.k.gradient.copy()
GPy.util.config.config.set('weave', 'working', False)
K_numpy = k.K(X)
k.update_gradients_full(dL_dK, X)
grads_numpy = k.gradient.copy()
GPy.util.config.config.set('weave', 'working', 'False')
K_numpy = self.k.K(self.X)
self.k.update_gradients_full(dL_dK, self.X)
grads_numpy = self.k.gradient.copy()
self.assertTrue(np.allclose(K_numpy, K_weave))
self.assertTrue(np.allclose(grads_numpy, grads_weave))
self.assertTrue(np.allclose(K_numpy, K_weave))
self.assertTrue(np.allclose(grads_numpy, grads_weave))
#non-symmetric case
dL_dK = np.random.randn(N1, N2)
GPy.util.config.config.set('weave', 'working', True)
K_weave = k.K(X, X2)
k.update_gradients_full(dL_dK, X, X2)
grads_weave = k.gradient.copy()
def test_nonsym(self):
dL_dK = np.random.randn(self.N1, self.N2)
GPy.util.config.config.set('weave', 'working', 'True')
K_weave = self.k.K(self.X, self.X2)
self.k.update_gradients_full(dL_dK, self.X, self.X2)
grads_weave = self.k.gradient.copy()
GPy.util.config.config.set('weave', 'working', False)
K_numpy = k.K(X, X2)
k.update_gradients_full(dL_dK, X, X2)
grads_numpy = k.gradient.copy()
GPy.util.config.config.set('weave', 'working', 'False')
K_numpy = self.k.K(self.X, self.X2)
self.k.update_gradients_full(dL_dK, self.X, self.X2)
grads_numpy = self.k.gradient.copy()
self.assertTrue(np.allclose(K_numpy, K_weave))
self.assertTrue(np.allclose(grads_numpy, grads_weave))
self.assertTrue(np.allclose(K_numpy, K_weave))
self.assertTrue(np.allclose(grads_numpy, grads_weave))
#reset the weave state for any other tests
GPy.util.config.config.set('weave', 'working', False)
GPy.util.config.config.set('weave', 'working', 'False')