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psi_stat tests renamed

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Max Zwiessele 2013-05-22 12:39:49 +01:00
parent b7de50b5b3
commit 1f5a7d0053
3 changed files with 33 additions and 21 deletions
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2
GPy/testing/__init__.py
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@ -7,6 +7,6 @@ import unittest
import sys import sys
def deepTest(reason): def deepTest(reason):
if 'deep' in sys.argv: if 'deep' in reason:
return lambda x:x return lambda x:x
return unittest.skip("Not deep scanning, enable deepscan by adding 'deep' argument") return unittest.skip("Not deep scanning, enable deepscan by adding 'deep' argument")

52
GPy/testing/kern_psi_stat_tests.py → GPy/testing/psi_stat_expactation_tests.py
View file

@ -6,10 +6,9 @@ Created on 26 Apr 2013
import unittest import unittest
import GPy import GPy
import numpy as np import numpy as np
import sys from GPy import testing
from .. import testing
__test__ = True __test__ = False
np.random.seed(0) np.random.seed(0)
def ard(p): def ard(p):
@ -20,7 +19,7 @@ def ard(p):
pass pass
return "" return ""
@testing.deepTest @testing.deepTest(__test__)
class Test(unittest.TestCase): class Test(unittest.TestCase):
D = 9 D = 9
M = 4 M = 4
@ -29,13 +28,22 @@ class Test(unittest.TestCase):
def setUp(self): def setUp(self):
self.kerns = ( self.kerns = (
GPy.kern.rbf(self.D), GPy.kern.rbf(self.D, ARD=True), # (GPy.kern.rbf(self.D, ARD=True) +
GPy.kern.linear(self.D, ARD=False), GPy.kern.linear(self.D, ARD=True), # GPy.kern.linear(self.D, ARD=True) +
GPy.kern.linear(self.D) + GPy.kern.bias(self.D), # GPy.kern.bias(self.D) +
GPy.kern.rbf(self.D) + GPy.kern.bias(self.D), # GPy.kern.white(self.D)),
GPy.kern.linear(self.D) + GPy.kern.bias(self.D) + GPy.kern.white(self.D), (GPy.kern.rbf(self.D, np.random.rand(), np.random.rand(self.D), ARD=True) +
GPy.kern.rbf(self.D) + GPy.kern.bias(self.D) + GPy.kern.white(self.D), GPy.kern.rbf(self.D, np.random.rand(), np.random.rand(self.D), ARD=True) +
GPy.kern.bias(self.D), GPy.kern.white(self.D), GPy.kern.linear(self.D, np.random.rand(self.D), ARD=True) +
GPy.kern.bias(self.D) +
GPy.kern.white(self.D)),
# GPy.kern.rbf(self.D), GPy.kern.rbf(self.D, ARD=True),
# GPy.kern.linear(self.D, ARD=False), GPy.kern.linear(self.D, ARD=True),
# GPy.kern.linear(self.D) + GPy.kern.bias(self.D),
# GPy.kern.rbf(self.D) + GPy.kern.bias(self.D),
# GPy.kern.linear(self.D) + GPy.kern.bias(self.D) + GPy.kern.white(self.D),
# GPy.kern.rbf(self.D) + GPy.kern.bias(self.D) + GPy.kern.white(self.D),
# GPy.kern.bias(self.D), GPy.kern.white(self.D),
) )
self.q_x_mean = np.random.randn(self.D) self.q_x_mean = np.random.randn(self.D)
self.q_x_variance = np.exp(np.random.randn(self.D)) self.q_x_variance = np.exp(np.random.randn(self.D))
@ -64,8 +72,9 @@ class Test(unittest.TestCase):
K_ /= self.Nsamples / Nsamples K_ /= self.Nsamples / Nsamples
msg = "psi1: " + "+".join([p.name + ard(p) for p in kern.parts]) msg = "psi1: " + "+".join([p.name + ard(p) for p in kern.parts])
try: try:
# pylab.figure(msg) import pylab
# pylab.plot(diffs) pylab.figure(msg)
pylab.plot(diffs)
self.assertTrue(np.allclose(psi1.squeeze(), K_, self.assertTrue(np.allclose(psi1.squeeze(), K_,
rtol=1e-1, atol=.1), rtol=1e-1, atol=.1),
msg=msg + ": not matching") msg=msg + ": not matching")
@ -90,8 +99,9 @@ class Test(unittest.TestCase):
K_ /= self.Nsamples / Nsamples K_ /= self.Nsamples / Nsamples
msg = "psi2: {}".format("+".join([p.name + ard(p) for p in kern.parts])) msg = "psi2: {}".format("+".join([p.name + ard(p) for p in kern.parts]))
try: try:
# pylab.figure(msg) import pylab
# pylab.plot(diffs) pylab.figure(msg)
pylab.plot(diffs)
self.assertTrue(np.allclose(psi2.squeeze(), K_, self.assertTrue(np.allclose(psi2.squeeze(), K_,
rtol=1e-1, atol=.1), rtol=1e-1, atol=.1),
msg=msg + ": not matching") msg=msg + ": not matching")
@ -104,9 +114,11 @@ class Test(unittest.TestCase):
pass pass
if __name__ == "__main__": if __name__ == "__main__":
import sys;sys.argv = ['', import sys
'Test.test_psi0', __test__ = 'deep' in sys.argv
'Test.test_psi1', sys.argv = ['',
'Test.test_psi2', 'Test.test_psi0',
] 'Test.test_psi1',
'Test.test_psi2',
]
unittest.main() unittest.main()

0
GPy/testing/psi_stat_tests.py → GPy/testing/psi_stat_gradient_tests.py
View file