diff --git a/GPy/testing/link_function_tests.py b/GPy/testing/link_function_tests.py index 0db85413..d4aeefa6 100644 --- a/GPy/testing/link_function_tests.py +++ b/GPy/testing/link_function_tests.py @@ -20,8 +20,8 @@ from GPy.likelihoods.link_functions import ( ) -class LinkFunctionTests(np.testing.TestCase): - def setUp(self): +class TestLinkFunction: + def setup(self): self.small_f = np.array([[-1e-4]]) self.zero_f = np.array([[1e-4]]) self.mid_f = np.array([[5.0]]) @@ -31,50 +31,50 @@ class LinkFunctionTests(np.testing.TestCase): def check_gradient(self, link_func, lim_of_inf, test_lim=False): grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.mid_f) - self.assertTrue(grad.checkgrad(verbose=True)) + assert grad.checkgrad(verbose=True) grad2 = GradientChecker( link_func.dtransf_df, link_func.d2transf_df2, x0=self.mid_f ) - self.assertTrue(grad2.checkgrad(verbose=True)) + assert grad2.checkgrad(verbose=True) grad3 = GradientChecker( link_func.d2transf_df2, link_func.d3transf_df3, x0=self.mid_f ) - self.assertTrue(grad3.checkgrad(verbose=True)) + assert grad3.checkgrad(verbose=True) grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.small_f) - self.assertTrue(grad.checkgrad(verbose=True)) + assert grad.checkgrad(verbose=True) grad2 = GradientChecker( link_func.dtransf_df, link_func.d2transf_df2, x0=self.small_f ) - self.assertTrue(grad2.checkgrad(verbose=True)) + assert grad2.checkgrad(verbose=True) grad3 = GradientChecker( link_func.d2transf_df2, link_func.d3transf_df3, x0=self.small_f ) - self.assertTrue(grad3.checkgrad(verbose=True)) + assert grad3.checkgrad(verbose=True) grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=self.zero_f) - self.assertTrue(grad.checkgrad(verbose=True)) + assert grad.checkgrad(verbose=True) grad2 = GradientChecker( link_func.dtransf_df, link_func.d2transf_df2, x0=self.zero_f ) - self.assertTrue(grad2.checkgrad(verbose=True)) + assert grad2.checkgrad(verbose=True) grad3 = GradientChecker( link_func.d2transf_df2, link_func.d3transf_df3, x0=self.zero_f ) - self.assertTrue(grad3.checkgrad(verbose=True)) + assert grad3.checkgrad(verbose=True) # Do a limit test if the large f value is too large large_f = np.clip(self.large_f, -np.inf, lim_of_inf - 1e-3) grad = GradientChecker(link_func.transf, link_func.dtransf_df, x0=large_f) - self.assertTrue(grad.checkgrad(verbose=True)) + assert grad.checkgrad(verbose=True) grad2 = GradientChecker( link_func.dtransf_df, link_func.d2transf_df2, x0=large_f ) - self.assertTrue(grad2.checkgrad(verbose=True)) + assert grad2.checkgrad(verbose=True) grad3 = GradientChecker( link_func.d2transf_df2, link_func.d3transf_df3, x0=large_f ) - self.assertTrue(grad3.checkgrad(verbose=True)) + assert grad3.checkgrad(verbose=True) if test_lim: print("Testing limits") @@ -83,29 +83,31 @@ class LinkFunctionTests(np.testing.TestCase): grad = GradientChecker( link_func.transf, link_func.dtransf_df, x0=lim_of_inf ) - self.assertTrue(grad.checkgrad(verbose=True)) + assert grad.checkgrad(verbose=True) grad2 = GradientChecker( link_func.dtransf_df, link_func.d2transf_df2, x0=lim_of_inf ) - self.assertTrue(grad2.checkgrad(verbose=True)) + assert grad2.checkgrad(verbose=True) grad3 = GradientChecker( link_func.d2transf_df2, link_func.d3transf_df3, x0=lim_of_inf ) - self.assertTrue(grad3.checkgrad(verbose=True)) + assert grad3.checkgrad(verbose=True) def check_overflow(self, link_func, lim_of_inf): # Check that it does something sensible beyond this limit, # note this is not checking the value is correct, just that it isn't nan beyond_lim_of_inf = lim_of_inf + 100.0 - self.assertFalse(np.isinf(link_func.transf(beyond_lim_of_inf))) - self.assertFalse(np.isinf(link_func.dtransf_df(beyond_lim_of_inf))) - self.assertFalse(np.isinf(link_func.d2transf_df2(beyond_lim_of_inf))) + assert np.isinf(link_func.transf(beyond_lim_of_inf)) + assert np.isinf(link_func.dtransf_df(beyond_lim_of_inf)) + assert np.isinf(link_func.d2transf_df2(beyond_lim_of_inf)) - self.assertFalse(np.isnan(link_func.transf(beyond_lim_of_inf))) - self.assertFalse(np.isnan(link_func.dtransf_df(beyond_lim_of_inf))) - self.assertFalse(np.isnan(link_func.d2transf_df2(beyond_lim_of_inf))) + assert np.isnan(link_func.transf(beyond_lim_of_inf)) + assert np.isnan(link_func.dtransf_df(beyond_lim_of_inf)) + assert np.isnan(link_func.d2transf_df2(beyond_lim_of_inf)) def test_log_overflow(self): + self.setup() + link = Log() lim_of_inf = _lim_val_exp @@ -113,16 +115,18 @@ class LinkFunctionTests(np.testing.TestCase): assert np.isinf(np.exp(np.log(self.f_upper_lim))) # Check the clipping works np.testing.assert_almost_equal(link.transf(self.f_lower_lim), 0, decimal=5) - self.assertTrue(np.isfinite(link.transf(self.f_upper_lim))) + assert np.isfinite(link.transf(self.f_upper_lim)) self.check_overflow(link, lim_of_inf) # Check that it would otherwise fail beyond_lim_of_inf = lim_of_inf + 10.0 old_err_state = np.seterr(over="ignore") - self.assertTrue(np.isinf(np.exp(beyond_lim_of_inf))) + assert np.isinf(np.exp(beyond_lim_of_inf)) np.seterr(**old_err_state) def test_log_ex_1_overflow(self): + self.setup() + link = Log_ex_1() lim_of_inf = _lim_val_exp @@ -141,43 +145,51 @@ class LinkFunctionTests(np.testing.TestCase): # Check that it would otherwise fail beyond_lim_of_inf = lim_of_inf + 10.0 old_err_state = np.seterr(over="ignore") - self.assertTrue(np.isinf(scipy.special.log1p(np.exp(beyond_lim_of_inf)))) + assert np.isinf(scipy.special.log1p(np.exp(beyond_lim_of_inf))) np.seterr(**old_err_state) def test_log_gradients(self): # transf dtransf_df d2transf_df2 d3transf_df3 + self.setup() + link = Log() lim_of_inf = _lim_val_exp self.check_gradient(link, lim_of_inf, test_lim=True) def test_identity_gradients(self): + self.setup() link = Identity() lim_of_inf = _lim_val # FIXME: Should be able to think of a way to test the limits of this self.check_gradient(link, lim_of_inf, test_lim=False) def test_probit_gradients(self): + self.setup() link = Probit() lim_of_inf = _lim_val self.check_gradient(link, lim_of_inf, test_lim=True) def test_scaledprobit_gradients(self): + self.setup() link = ScaledProbit(nu=random.random()) lim_of_inf = _lim_val self.check_gradient(link, lim_of_inf, test_lim=True) def test_Cloglog_gradients(self): + self.setup() link = Cloglog() lim_of_inf = _lim_val_exp self.check_gradient(link, lim_of_inf, test_lim=True) def test_Log_ex_1_gradients(self): + self.setup() link = Log_ex_1() lim_of_inf = _lim_val_exp self.check_gradient(link, lim_of_inf, test_lim=True) self.check_overflow(link, lim_of_inf) def test_reciprocal_gradients(self): + self.setup() link = Reciprocal() lim_of_inf = _lim_val # Does not work with much smaller values, and values closer to zero than 1e-5