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bug fix: slicing can now be turned of by passing None as active_dims

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This commit is contained in:
Max Zwiessele 2014-04-16 09:49:35 +01:00
parent d2f73f13ec
commit a57ca26c89
3 changed files with 34 additions and 52 deletions
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46
GPy/testing/kernel_tests.py
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@ -260,7 +260,6 @@ class KernelGradientTestsContinuous(unittest.TestCase):
self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
def test_Prod3(self):
k = GPy.kern.Matern32(2, active_dims=[2,3]) * (GPy.kern.RBF(2, active_dims=[0,4]) + GPy.kern.Linear(self.D))
k = (GPy.kern.RBF(2, active_dims=[0,4]) * GPy.kern.Linear(self.D))
k.randomize()
self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
@ -274,7 +273,7 @@ class KernelGradientTestsContinuous(unittest.TestCase):
def test_Add_dims(self):
k = GPy.kern.Matern32(2, active_dims=[2,self.D]) + GPy.kern.RBF(2, active_dims=[0,4]) + GPy.kern.Linear(self.D)
k.randomize()
self.assertRaises(AssertionError, k.K, self.X)
self.assertRaises(IndexError, k.K, self.X)
k = GPy.kern.Matern32(2, active_dims=[2,self.D-1]) + GPy.kern.RBF(2, active_dims=[0,4]) + GPy.kern.Linear(self.D)
k.randomize()
# assert it runs:
@ -303,46 +302,25 @@ class KernelGradientTestsContinuous(unittest.TestCase):
k.randomize()
self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
#TODO: turn off grad checkingwrt X for indexed kernels like coregionalize
# class KernelGradientTestsContinuous1D(unittest.TestCase):
# def setUp(self):
# self.N, self.D = 100, 1
# self.X = np.random.randn(self.N,self.D)
# self.X2 = np.random.randn(self.N+10,self.D)
#
# continuous_kerns = ['RBF', 'Linear']
# self.kernclasses = [getattr(GPy.kern, s) for s in continuous_kerns]
#
# def test_PeriodicExponential(self):
# k = GPy.kern.PeriodicExponential(self.D)
# k.randomize()
# self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
#
# def test_PeriodicMatern32(self):
# k = GPy.kern.PeriodicMatern32(self.D)
# k.randomize()
# self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
#
# def test_PeriodicMatern52(self):
# k = GPy.kern.PeriodicMatern52(self.D)
# k.randomize()
# self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
class KernelTestsMiscellaneous(unittest.TestCase):
def setUp(self):
N, D = 100, 10
self.X = np.linspace(-np.pi, +np.pi, N)[:,None] * np.ones(D)
self.X = np.linspace(-np.pi, +np.pi, N)[:,None] * np.random.uniform(-10,10,D)
self.rbf = GPy.kern.RBF(2, active_dims=slice(0,4,2))
self.linear = GPy.kern.Linear(2, active_dims=(3,9))
self.matern = GPy.kern.Matern32(3, active_dims=np.array([2,4,9]))
self.matern = GPy.kern.Matern32(3, active_dims=np.array([1,7,9]))
self.sumkern = self.rbf + self.linear
self.sumkern += self.matern
self.sumkern.randomize()
def test_active_dims(self):
self.assertEqual(self.sumkern.input_dim, 10)
self.assertEqual(self.sumkern.active_dims, slice(0, 10, 1))
#self.assertEqual(self.sumkern.input_dim, 10)
#self.assertEqual(list(self.sumkern.active_dims), [0,1,2,3,7,9])
# test the automatic dim detection expression for slices:
start, stop = 0, 277
for i in range(start,stop,7):
for j in range(1,4):
GPy.kern.Kern(int(np.round((i+1)/j)), slice(0, i+1, j), "testkern")
def test_which_parts(self):
self.assertTrue(np.allclose(self.sumkern.K(self.X, which_parts=[self.linear, self.matern]), self.linear.K(self.X)+self.matern.K(self.X)))
@ -365,7 +343,7 @@ class KernelTestsNonContinuous(unittest.TestCase):
self.X2 = np.random.randn((N0+N1)*2, self.D+1)
self.X2[:(N0*2), -1] = 0
self.X2[(N0*2):, -1] = 1
def test_IndependentOutputs(self):
k = GPy.kern.RBF(self.D)
kern = GPy.kern.IndependentOutputs(k, -1, 'ind_single')
@ -373,7 +351,7 @@ class KernelTestsNonContinuous(unittest.TestCase):
k = [GPy.kern.RBF(1, active_dims=[1], name='rbf1'), GPy.kern.RBF(self.D, name='rbf012'), GPy.kern.RBF(2, active_dims=[0,2], name='rbf02')]
kern = GPy.kern.IndependentOutputs(k, -1, name='ind_split')
self.assertTrue(check_kernel_gradient_functions(kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1))
def test_ODE_UY(self):
kern = GPy.kern.ODE_UY(2, active_dims=[0, self.D])
X = self.X[self.X[:,-1]!=2]