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Changed kern.py so that X2 is correctly passed as None to the kern parts for dK_dX. Modified several kern parts so that dK_dX is correctly computed (factors of 2 missing). Removed spurious factors of 2 from gplvm, bcgplvm, sparse_gp and fitc code.

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This commit is contained in:
Neil Lawrence 2013-09-14 20:02:40 +01:00
parent 2e6cac0d34
commit 00d335444d
20 changed files with 259 additions and 68 deletions
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59
GPy/testing/kernel_tests.py
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@ -5,7 +5,7 @@ import unittest
import numpy as np
import GPy
verbose = False
class KernelTests(unittest.TestCase):
def test_kerneltie(self):
@ -19,25 +19,54 @@ class KernelTests(unittest.TestCase):
self.assertTrue(m.checkgrad())
def test_rbfkernel(self):
verbose = False
kern = GPy.kern.rbf(5)
self.assertTrue(GPy.kern.Kern_check_model(kern).is_positive_definite())
self.assertTrue(GPy.kern.Kern_check_dK_dtheta(kern).checkgrad(verbose=verbose))
self.assertTrue(GPy.kern.Kern_check_dKdiag_dtheta(kern).checkgrad(verbose=verbose))
self.assertTrue(GPy.kern.Kern_check_dK_dX(kern).checkgrad(verbose=verbose))
kern = GPy.kern.rbf(5)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_rbf_invkernel(self):
kern = GPy.kern.rbf_inv(5)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_Matern32kernel(self):
kern = GPy.kern.Matern32(5)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_Matern52kernel(self):
kern = GPy.kern.Matern52(5)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_linearkernel(self):
kern = GPy.kern.linear(5)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_periodic_exponentialkernel(self):
kern = GPy.kern.periodic_exponential(1)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_periodic_Matern32kernel(self):
kern = GPy.kern.periodic_Matern32(1)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_periodic_Matern52kernel(self):
kern = GPy.kern.periodic_Matern52(1)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_rational_quadratickernel(self):
kern = GPy.kern.rational_quadratic(1)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_gibbskernel(self):
verbose = False
kern = GPy.kern.gibbs(5, mapping=GPy.mappings.Linear(5, 1))
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_heterokernel(self):
kern = GPy.kern.hetero(5, mapping=GPy.mappings.Linear(5, 1), transform=GPy.core.transformations.logexp())
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_mlpkernel(self):
verbose = False
kern = GPy.kern.mlp(5)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_polykernel(self):
verbose = False
kern = GPy.kern.poly(5, degree=4)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
@ -48,9 +77,8 @@ class KernelTests(unittest.TestCase):
X = np.random.rand(30, 4)
K = np.dot(X, X.T)
kernel = GPy.kern.fixed(4, K)
Y = np.ones((30,1))
m = GPy.models.GPRegression(X,Y,kernel=kernel)
self.assertTrue(m.checkgrad())
kern = GPy.kern.poly(5, degree=4)
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))
def test_coregionalisation(self):
X1 = np.random.rand(50,1)*8
@ -63,9 +91,8 @@ class KernelTests(unittest.TestCase):
k1 = GPy.kern.rbf(1) + GPy.kern.bias(1)
k2 = GPy.kern.coregionalise(2,1)
k = k1.prod(k2,tensor=True)
m = GPy.models.GPRegression(X,Y,kernel=k)
self.assertTrue(m.checkgrad())
kern = k1**k2
self.assertTrue(GPy.kern.kern_test(kern, verbose=verbose))