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slicing tests and ipdb delete

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This commit is contained in:
Max Zwiessele 2014-03-11 10:24:30 +00:00
parent 2d8246d33f
commit 81d35686d9
2 changed files with 28 additions and 8 deletions
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30
GPy/testing/kernel_tests.py
View file

@ -6,7 +6,9 @@ import numpy as np
import GPy
import sys
verbose = True
verbose = 0
class Kern_check_model(GPy.core.Model):
"""
@ -91,7 +93,7 @@ class Kern_check_dKdiag_dX(Kern_check_dK_dX):
def kern_test(kern, X=None, X2=None, output_ind=None, verbose=False):
def check_kernel_gradient_functions(kern, X=None, X2=None, output_ind=None, verbose=False):
"""
This function runs on kernels to check the correctness of their
implementation. It checks that the covariance function is positive definite
@ -210,7 +212,7 @@ def kern_test(kern, X=None, X2=None, output_ind=None, verbose=False):
class KernelTestsContinuous(unittest.TestCase):
class KernelGradientTestsContinuous(unittest.TestCase):
def setUp(self):
self.X = np.random.randn(100,2)
self.X2 = np.random.randn(110,2)
@ -220,16 +222,34 @@ class KernelTestsContinuous(unittest.TestCase):
def test_Matern32(self):
k = GPy.kern.Matern32(2)
self.assertTrue(kern_test(k, X=self.X, X2=self.X2, verbose=verbose))
self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
def test_Matern52(self):
k = GPy.kern.Matern52(2)
self.assertTrue(kern_test(k, X=self.X, X2=self.X2, verbose=verbose))
self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
#TODO: turn off grad checkingwrt X for indexed kernels liek coregionalize
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.rbf = GPy.kern.RBF(range(2))
self.linear = GPy.kern.Linear((3,5,6))
self.matern = GPy.kern.Matern32(np.array([2,4,7]))
self.sumkern = self.rbf + self.linear
self.sumkern += self.matern
self.sumkern.randomize()
def test_active_dims(self):
self.assertListEqual(self.sumkern.active_dims.tolist(), range(8))
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)))
self.assertTrue(np.allclose(self.sumkern.K(self.X, which_parts=[self.linear, self.rbf]), self.linear.K(self.X)+self.rbf.K(self.X)))
self.assertTrue(np.allclose(self.sumkern.K(self.X, which_parts=self.sumkern.parts[0]), self.rbf.K(self.X)))
if __name__ == "__main__":
print "Running unit tests, please be (very) patient..."

6
GPy/testing/likelihood_tests.py
View file

@ -651,7 +651,7 @@ class LaplaceTests(unittest.TestCase):
m2['.*white'].constrain_fixed(1e-6)
m2['.*rbf.variance'].constrain_bounded(1e-4, 10)
m2.randomize()
if debug:
print m1
print m2
@ -663,7 +663,7 @@ class LaplaceTests(unittest.TestCase):
if debug:
print m1
print m2
m2[:] = m1[:]
#Predict for training points to get posterior mean and variance
@ -702,7 +702,7 @@ class LaplaceTests(unittest.TestCase):
m1.randomize()
import ipdb;ipdb.set_trace()
m2[:] = m1[:]
np.testing.assert_almost_equal(m1.log_likelihood(), m2.log_likelihood(), decimal=2)
#Check they are checkgradding