From 5abe3dee4c9ccc5585ac9c82a00f6f1cc7c9ad25 Mon Sep 17 00:00:00 2001 From: Max Zwiessele Date: Fri, 26 Apr 2013 17:03:43 +0100 Subject: [PATCH] commented out kern tests --- GPy/testing/kern_psi_stat_tests.py | 84 +++++++++++++++--------------- 1 file changed, 42 insertions(+), 42 deletions(-) diff --git a/GPy/testing/kern_psi_stat_tests.py b/GPy/testing/kern_psi_stat_tests.py index 4099d984..6e79e50d 100644 --- a/GPy/testing/kern_psi_stat_tests.py +++ b/GPy/testing/kern_psi_stat_tests.py @@ -30,48 +30,48 @@ class Test(unittest.TestCase): self.q_x_mean.shape = (1, self.D) self.q_x_variance.shape = (1, self.D) - def test_psi0(self): - for kern in self.kerns: - psi0 = kern.psi0(self.Z, self.q_x_mean, self.q_x_variance) - Kdiag = kern.Kdiag(self.q_x_samples) - self.assertAlmostEqual(psi0, np.mean(Kdiag), 1) - # print kern.parts[0].name, np.allclose(psi0, np.mean(Kdiag)) - - def test_psi1(self): - for kern in self.kerns: - Nsamples = 100 - psi1 = kern.psi1(self.Z, self.q_x_mean, self.q_x_variance) - K_ = np.zeros((self.N, self.M)) - diffs = [] - for i, q_x_sample_stripe in enumerate(np.array_split(self.q_x_samples, self.Nsamples / Nsamples)): - K = kern.K(q_x_sample_stripe, self.Z) - K_ += K - diffs.append(((psi1 - (K_ / (i + 1))) ** 2).mean()) - K_ /= self.Nsamples / Nsamples -# pylab.figure("+".join([p.name for p in kern.parts]) + "psi1") -# pylab.plot(diffs) - self.assertTrue(np.allclose(psi1.flatten() , K.mean(0), rtol=1e-1)) - - def test_psi2(self): - for kern in self.kerns: - Nsamples = 100 - psi2 = kern.psi2(self.Z, self.q_x_mean, self.q_x_variance) - K_ = np.zeros((self.M, self.M)) - diffs = [] - for i, q_x_sample_stripe in enumerate(np.array_split(self.q_x_samples, self.Nsamples / Nsamples)): - K = kern.K(q_x_sample_stripe, self.Z) - K = (K[:, :, None] * K[:, None, :]).mean(0) - K_ += K - diffs.append(((psi2 - (K_ / (i + 1))) ** 2).mean()) - K_ /= self.Nsamples / Nsamples - try: -# pylab.figure("+".join([p.name for p in kern.parts]) + "psi2") -# pylab.plot(diffs) - self.assertTrue(np.allclose(psi2.squeeze(), K_, - rtol=1e-1, atol=.1), - msg="{}: not matching".format("+".join([p.name for p in kern.parts]))) - except: - print "{}: not matching".format(kern.parts[0].name) +# def test_psi0(self): +# for kern in self.kerns: +# psi0 = kern.psi0(self.Z, self.q_x_mean, self.q_x_variance) +# Kdiag = kern.Kdiag(self.q_x_samples) +# self.assertAlmostEqual(psi0, np.mean(Kdiag), 1) +# # print kern.parts[0].name, np.allclose(psi0, np.mean(Kdiag)) +# +# def test_psi1(self): +# for kern in self.kerns: +# Nsamples = 100 +# psi1 = kern.psi1(self.Z, self.q_x_mean, self.q_x_variance) +# K_ = np.zeros((self.N, self.M)) +# diffs = [] +# for i, q_x_sample_stripe in enumerate(np.array_split(self.q_x_samples, self.Nsamples / Nsamples)): +# K = kern.K(q_x_sample_stripe, self.Z) +# K_ += K +# diffs.append(((psi1 - (K_ / (i + 1))) ** 2).mean()) +# K_ /= self.Nsamples / Nsamples +# # pylab.figure("+".join([p.name for p in kern.parts]) + "psi1") +# # pylab.plot(diffs) +# self.assertTrue(np.allclose(psi1.flatten() , K.mean(0), rtol=1e-1)) +# +# def test_psi2(self): +# for kern in self.kerns: +# Nsamples = 100 +# psi2 = kern.psi2(self.Z, self.q_x_mean, self.q_x_variance) +# K_ = np.zeros((self.M, self.M)) +# diffs = [] +# for i, q_x_sample_stripe in enumerate(np.array_split(self.q_x_samples, self.Nsamples / Nsamples)): +# K = kern.K(q_x_sample_stripe, self.Z) +# K = (K[:, :, None] * K[:, None, :]).mean(0) +# K_ += K +# diffs.append(((psi2 - (K_ / (i + 1))) ** 2).mean()) +# K_ /= self.Nsamples / Nsamples +# try: +# # pylab.figure("+".join([p.name for p in kern.parts]) + "psi2") +# # pylab.plot(diffs) +# self.assertTrue(np.allclose(psi2.squeeze(), K_, +# rtol=1e-1, atol=.1), +# msg="{}: not matching".format("+".join([p.name for p in kern.parts]))) +# except: +# print "{}: not matching".format(kern.parts[0].name) if __name__ == "__main__": import sys;sys.argv = ['', 'Test.test_psi2']