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migrate link_function_tests to pytest
This commit is contained in:
Martin Bubel
parent
393f9938ea
commit
7340cf7f7f
1 changed files with 38 additions and 26 deletions
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@ -20,8 +20,8 @@ from GPy.likelihoods.link_functions import (
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)
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class LinkFunctionTests(np.testing.TestCase):
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def setUp(self):
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class TestLinkFunction:
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def setup(self):
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self.small_f = np.array([[-1e-4]])
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self.zero_f = np.array([[1e-4]])
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self.mid_f = np.array([[5.0]])
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@ -31,50 +31,50 @@ class LinkFunctionTests(np.testing.TestCase):
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def check_gradient(self, link_func, lim_of_inf, test_lim=False):
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grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.mid_f)
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self.assertTrue(grad.checkgrad(verbose=True))
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assert grad.checkgrad(verbose=True)
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grad2 = GradientChecker(
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link_func.dtransf_df, link_func.d2transf_df2, x0=self.mid_f
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)
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self.assertTrue(grad2.checkgrad(verbose=True))
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assert grad2.checkgrad(verbose=True)
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grad3 = GradientChecker(
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link_func.d2transf_df2, link_func.d3transf_df3, x0=self.mid_f
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)
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self.assertTrue(grad3.checkgrad(verbose=True))
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assert grad3.checkgrad(verbose=True)
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grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.small_f)
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self.assertTrue(grad.checkgrad(verbose=True))
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assert grad.checkgrad(verbose=True)
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grad2 = GradientChecker(
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link_func.dtransf_df, link_func.d2transf_df2, x0=self.small_f
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)
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self.assertTrue(grad2.checkgrad(verbose=True))
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assert grad2.checkgrad(verbose=True)
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grad3 = GradientChecker(
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link_func.d2transf_df2, link_func.d3transf_df3, x0=self.small_f
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)
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self.assertTrue(grad3.checkgrad(verbose=True))
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assert grad3.checkgrad(verbose=True)
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grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.zero_f)
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self.assertTrue(grad.checkgrad(verbose=True))
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assert grad.checkgrad(verbose=True)
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grad2 = GradientChecker(
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link_func.dtransf_df, link_func.d2transf_df2, x0=self.zero_f
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)
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self.assertTrue(grad2.checkgrad(verbose=True))
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assert grad2.checkgrad(verbose=True)
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grad3 = GradientChecker(
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link_func.d2transf_df2, link_func.d3transf_df3, x0=self.zero_f
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)
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self.assertTrue(grad3.checkgrad(verbose=True))
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assert grad3.checkgrad(verbose=True)
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# Do a limit test if the large f value is too large
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large_f = np.clip(self.large_f, -np.inf, lim_of_inf - 1e-3)
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grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=large_f)
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self.assertTrue(grad.checkgrad(verbose=True))
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assert grad.checkgrad(verbose=True)
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grad2 = GradientChecker(
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link_func.dtransf_df, link_func.d2transf_df2, x0=large_f
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)
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self.assertTrue(grad2.checkgrad(verbose=True))
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assert grad2.checkgrad(verbose=True)
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grad3 = GradientChecker(
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link_func.d2transf_df2, link_func.d3transf_df3, x0=large_f
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)
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self.assertTrue(grad3.checkgrad(verbose=True))
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assert grad3.checkgrad(verbose=True)
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if test_lim:
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print("Testing limits")
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@ -83,29 +83,31 @@ class LinkFunctionTests(np.testing.TestCase):
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grad = GradientChecker(
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link_func.transf, link_func.dtransf_df, x0=lim_of_inf
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)
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self.assertTrue(grad.checkgrad(verbose=True))
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assert grad.checkgrad(verbose=True)
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grad2 = GradientChecker(
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link_func.dtransf_df, link_func.d2transf_df2, x0=lim_of_inf
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)
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self.assertTrue(grad2.checkgrad(verbose=True))
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assert grad2.checkgrad(verbose=True)
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grad3 = GradientChecker(
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link_func.d2transf_df2, link_func.d3transf_df3, x0=lim_of_inf
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)
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self.assertTrue(grad3.checkgrad(verbose=True))
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assert grad3.checkgrad(verbose=True)
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def check_overflow(self, link_func, lim_of_inf):
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# Check that it does something sensible beyond this limit,
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# note this is not checking the value is correct, just that it isn't nan
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beyond_lim_of_inf = lim_of_inf + 100.0
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self.assertFalse(np.isinf(link_func.transf(beyond_lim_of_inf)))
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self.assertFalse(np.isinf(link_func.dtransf_df(beyond_lim_of_inf)))
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self.assertFalse(np.isinf(link_func.d2transf_df2(beyond_lim_of_inf)))
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assert np.isinf(link_func.transf(beyond_lim_of_inf))
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assert np.isinf(link_func.dtransf_df(beyond_lim_of_inf))
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assert np.isinf(link_func.d2transf_df2(beyond_lim_of_inf))
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self.assertFalse(np.isnan(link_func.transf(beyond_lim_of_inf)))
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self.assertFalse(np.isnan(link_func.dtransf_df(beyond_lim_of_inf)))
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self.assertFalse(np.isnan(link_func.d2transf_df2(beyond_lim_of_inf)))
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assert np.isnan(link_func.transf(beyond_lim_of_inf))
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assert np.isnan(link_func.dtransf_df(beyond_lim_of_inf))
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assert np.isnan(link_func.d2transf_df2(beyond_lim_of_inf))
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def test_log_overflow(self):
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self.setup()
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link = Log()
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lim_of_inf = _lim_val_exp
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@ -113,16 +115,18 @@ class LinkFunctionTests(np.testing.TestCase):
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assert np.isinf(np.exp(np.log(self.f_upper_lim)))
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# Check the clipping works
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np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5)
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self.assertTrue(np.isfinite(link.transf(self.f_upper_lim)))
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assert np.isfinite(link.transf(self.f_upper_lim))
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self.check_overflow(link, lim_of_inf)
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# Check that it would otherwise fail
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beyond_lim_of_inf = lim_of_inf + 10.0
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old_err_state = np.seterr(over="ignore")
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self.assertTrue(np.isinf(np.exp(beyond_lim_of_inf)))
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assert np.isinf(np.exp(beyond_lim_of_inf))
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np.seterr(**old_err_state)
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def test_log_ex_1_overflow(self):
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self.setup()
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link = Log_ex_1()
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lim_of_inf = _lim_val_exp
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@ -141,43 +145,51 @@ class LinkFunctionTests(np.testing.TestCase):
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# Check that it would otherwise fail
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beyond_lim_of_inf = lim_of_inf + 10.0
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old_err_state = np.seterr(over="ignore")
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self.assertTrue(np.isinf(scipy.special.log1p(np.exp(beyond_lim_of_inf))))
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assert np.isinf(scipy.special.log1p(np.exp(beyond_lim_of_inf)))
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np.seterr(**old_err_state)
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def test_log_gradients(self):
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# transf dtransf_df d2transf_df2 d3transf_df3
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self.setup()
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link = Log()
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lim_of_inf = _lim_val_exp
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self.check_gradient(link, lim_of_inf, test_lim=True)
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def test_identity_gradients(self):
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self.setup()
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link = Identity()
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lim_of_inf = _lim_val
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# FIXME: Should be able to think of a way to test the limits of this
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self.check_gradient(link, lim_of_inf, test_lim=False)
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def test_probit_gradients(self):
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self.setup()
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link = Probit()
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lim_of_inf = _lim_val
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self.check_gradient(link, lim_of_inf, test_lim=True)
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def test_scaledprobit_gradients(self):
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self.setup()
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link = ScaledProbit(nu=random.random())
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lim_of_inf = _lim_val
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self.check_gradient(link, lim_of_inf, test_lim=True)
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def test_Cloglog_gradients(self):
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self.setup()
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link = Cloglog()
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lim_of_inf = _lim_val_exp
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self.check_gradient(link, lim_of_inf, test_lim=True)
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def test_Log_ex_1_gradients(self):
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self.setup()
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link = Log_ex_1()
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lim_of_inf = _lim_val_exp
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self.check_gradient(link, lim_of_inf, test_lim=True)
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self.check_overflow(link, lim_of_inf)
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def test_reciprocal_gradients(self):
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self.setup()
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link = Reciprocal()
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lim_of_inf = _lim_val
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# Does not work with much smaller values, and values closer to zero than 1e-5
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