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1 changed files with 51 additions and 50 deletions
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@ -5,6 +5,7 @@ import unittest
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import numpy as np
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import numpy as np
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import GPy
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import GPy
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class PriorTests(unittest.TestCase):
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class PriorTests(unittest.TestCase):
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def test_studentT(self):
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def test_studentT(self):
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xmin, xmax = 1, 2.5 * np.pi
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xmin, xmax = 1, 2.5 * np.pi
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@ -23,7 +24,7 @@ class PriorTests(unittest.TestCase):
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self.assertRaises(AssertionError, m.rbf.set_prior, studentT)
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self.assertRaises(AssertionError, m.rbf.set_prior, studentT)
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# The gradients need to be checked
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# The gradients need to be checked
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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# Check the singleton pattern:
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# Check the singleton pattern:
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self.assertIs(studentT, GPy.priors.StudentT(1, 2, 4))
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self.assertIs(studentT, GPy.priors.StudentT(1, 2, 4))
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@ -40,7 +41,7 @@ class PriorTests(unittest.TestCase):
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lognormal = GPy.priors.LogGaussian(1, 2)
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lognormal = GPy.priors.LogGaussian(1, 2)
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m.rbf.set_prior(lognormal)
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m.rbf.set_prior(lognormal)
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m.randomize()
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m.randomize()
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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def test_Gamma(self):
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def test_Gamma(self):
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xmin, xmax = 1, 2.5 * np.pi
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xmin, xmax = 1, 2.5 * np.pi
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@ -53,7 +54,7 @@ class PriorTests(unittest.TestCase):
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Gamma = GPy.priors.Gamma(1, 1)
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Gamma = GPy.priors.Gamma(1, 1)
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m.rbf.set_prior(Gamma)
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m.rbf.set_prior(Gamma)
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m.randomize()
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m.randomize()
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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def test_InverseGamma(self):
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def test_InverseGamma(self):
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# Test that this prior object can be instantiated and performs its basic functions
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# Test that this prior object can be instantiated and performs its basic functions
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@ -68,7 +69,7 @@ class PriorTests(unittest.TestCase):
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InverseGamma = GPy.priors.InverseGamma(1, 1)
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InverseGamma = GPy.priors.InverseGamma(1, 1)
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m.rbf.set_prior(InverseGamma)
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m.rbf.set_prior(InverseGamma)
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m.randomize()
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m.randomize()
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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def test_incompatibility(self):
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def test_incompatibility(self):
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xmin, xmax = 1, 2.5 * np.pi
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xmin, xmax = 1, 2.5 * np.pi
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@ -109,23 +110,23 @@ class PriorTests(unittest.TestCase):
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uniform = GPy.priors.Uniform(0, 2)
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uniform = GPy.priors.Uniform(0, 2)
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m.rbf.set_prior(uniform)
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m.rbf.set_prior(uniform)
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m.randomize()
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m.randomize()
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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m.Z.set_prior(uniform)
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m.Z.set_prior(uniform)
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m.randomize()
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m.randomize()
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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m.Z.unconstrain()
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m.Z.unconstrain()
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uniform = GPy.priors.Uniform(-1, 10)
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uniform = GPy.priors.Uniform(-1, 10)
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m.Z.set_prior(uniform)
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m.Z.set_prior(uniform)
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m.randomize()
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m.randomize()
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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m.Z.constrain_negative()
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m.Z.constrain_negative()
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uniform = GPy.priors.Uniform(-1, 0)
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uniform = GPy.priors.Uniform(-1, 0)
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m.Z.set_prior(uniform)
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m.Z.set_prior(uniform)
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m.randomize()
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m.randomize()
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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def test_set_gaussian_for_reals(self):
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def test_set_gaussian_for_reals(self):
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xmin, xmax = 1, 2.5 * np.pi
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xmin, xmax = 1, 2.5 * np.pi
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@ -141,8 +142,7 @@ class PriorTests(unittest.TestCase):
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# setting a Gaussian prior on non-negative parameters
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# setting a Gaussian prior on non-negative parameters
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# should raise an assertionerror.
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# should raise an assertionerror.
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# self.assertRaises(AssertionError, m.Z.set_prior, gaussian)
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# self.assertRaises(AssertionError, m.Z.set_prior, gaussian)
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self.assertTrue(m.checkgrad())
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assert m.checkgrad()
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def test_fixed_domain_check(self):
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def test_fixed_domain_check(self):
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xmin, xmax = 1, 2.5 * np.pi
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xmin, xmax = 1, 2.5 * np.pi
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@ -174,6 +174,7 @@ class PriorTests(unittest.TestCase):
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# should raise an assertionerror.
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# should raise an assertionerror.
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self.assertRaises(AssertionError, m.rbf.set_prior, gaussian)
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self.assertRaises(AssertionError, m.rbf.set_prior, gaussian)
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if __name__ == "__main__":
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if __name__ == "__main__":
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print("Running unit tests, please be (very) patient...")
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print("Running unit tests, please be (very) patient...")
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unittest.main()
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unittest.main()
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