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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 GPy
import sys import sys
verbose = True verbose = 0
class Kern_check_model(GPy.core.Model): 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 This function runs on kernels to check the correctness of their
implementation. It checks that the covariance function is positive definite 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): def setUp(self):
self.X = np.random.randn(100,2) self.X = np.random.randn(100,2)
self.X2 = np.random.randn(110,2) self.X2 = np.random.randn(110,2)
@ -220,16 +222,34 @@ class KernelTestsContinuous(unittest.TestCase):
def test_Matern32(self): def test_Matern32(self):
k = GPy.kern.Matern32(2) 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): def test_Matern52(self):
k = GPy.kern.Matern52(2) 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 #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__": if __name__ == "__main__":
print "Running unit tests, please be (very) patient..." 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['.*white'].constrain_fixed(1e-6)
m2['.*rbf.variance'].constrain_bounded(1e-4, 10) m2['.*rbf.variance'].constrain_bounded(1e-4, 10)
m2.randomize() m2.randomize()
if debug: if debug:
print m1 print m1
print m2 print m2
@ -663,7 +663,7 @@ class LaplaceTests(unittest.TestCase):
if debug: if debug:
print m1 print m1
print m2 print m2
m2[:] = m1[:] m2[:] = m1[:]
#Predict for training points to get posterior mean and variance #Predict for training points to get posterior mean and variance
@ -702,7 +702,7 @@ class LaplaceTests(unittest.TestCase):
m1.randomize() m1.randomize()
import ipdb;ipdb.set_trace() import ipdb;ipdb.set_trace()
m2[:] = m1[:] m2[:] = m1[:]
np.testing.assert_almost_equal(m1.log_likelihood(), m2.log_likelihood(), decimal=2) np.testing.assert_almost_equal(m1.log_likelihood(), m2.log_likelihood(), decimal=2)
#Check they are checkgradding #Check they are checkgradding