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Fixed white variance

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This commit is contained in:
Alan Saul 2013-10-02 13:37:48 +01:00
parent 2c419d2f48
commit c4715b2f5b
1 changed files with 6 additions and 2 deletions
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8
GPy/testing/laplace_tests.py
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@ -236,11 +236,13 @@ class LaplaceTests(unittest.TestCase):
def test_studentt_rbf(self):
print "\n{}".format(inspect.stack()[0][3])
self.Y = self.Y/self.Y.max()
kernel = GPy.kern.rbf(self.X.shape[1]) + GPy.kern.white(self.X.shape[1], variance=2.0)
white_var = 3.0
kernel = GPy.kern.rbf(self.X.shape[1]) + GPy.kern.white(self.X.shape[1])
stu_t_laplace = GPy.likelihoods.Laplace(self.Y.copy(), self.stu_t, opt='rasm')
m = GPy.models.GPRegression(self.X, self.Y.copy(), kernel, likelihood=stu_t_laplace)
m.ensure_default_constraints()
m.constrain_positive('t_noise')
m.constrain_fixed('white', white_var)
m.randomize()
m.checkgrad(verbose=1)
print m
@ -249,11 +251,13 @@ class LaplaceTests(unittest.TestCase):
def test_studentt_rbf_smallvar(self):
print "\n{}".format(inspect.stack()[0][3])
self.Y = self.Y/self.Y.max()
kernel = GPy.kern.rbf(self.X.shape[1]) + GPy.kern.white(self.X.shape[1], variance=2.0)
white_var = 3.0
kernel = GPy.kern.rbf(self.X.shape[1]) + GPy.kern.white(self.X.shape[1])
stu_t_laplace = GPy.likelihoods.Laplace(self.Y.copy(), self.stu_t, opt='rasm')
m = GPy.models.GPRegression(self.X, self.Y.copy(), kernel, likelihood=stu_t_laplace)
m.ensure_default_constraints()
m.constrain_positive('t_noise')
m.constrain_fixed('white', white_var)
m['t_noise'] = 0.01
m.checkgrad(verbose=1)
print m