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Laplace now appears to be grad checking again

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This commit is contained in:
Alan Saul 2014-02-10 15:40:06 +00:00
parent c6d466e72d
commit 6cbf810856
6 changed files with 43 additions and 37 deletions
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15
GPy/testing/likelihood_tests.py
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@ -86,7 +86,7 @@ class TestNoiseModels(object):
Generic model checker
"""
def setUp(self):
self.N = 5
self.N = 15
self.D = 3
self.X = np.random.rand(self.N, self.D)*10
@ -104,7 +104,7 @@ class TestNoiseModels(object):
self.var = np.random.rand(1)
#Make a bigger step as lower bound can be quite curved
self.step = 1e-3
self.step = 1e-4
def tearDown(self):
self.Y = None
@ -165,11 +165,20 @@ class TestNoiseModels(object):
},
"laplace": True
},
"Student_t_small_deg_free": {
"model": GPy.likelihoods.StudentT(deg_free=1.5, sigma2=self.var),
"grad_params": {
"names": ["t_noise"],
"vals": [self.var],
"constraints": [("t_noise", constrain_positive), ("deg_free", constrain_fixed)]
},
"laplace": True
},
"Student_t_small_var": {
"model": GPy.likelihoods.StudentT(deg_free=5, sigma2=self.var),
"grad_params": {
"names": ["t_noise"],
"vals": [0.01],
"vals": [0.0001],
"constraints": [("t_noise", constrain_positive), ("deg_free", constrain_fixed)]
},
"laplace": True