From 878eea8fc10182d53be73bdd9bbd9643d618e139 Mon Sep 17 00:00:00 2001 From: Martin Bubel Date: Tue, 17 Oct 2023 08:30:26 +0200 Subject: [PATCH] fix pytesting kernels --- GPy/testing/test_kernel.py | 24 +++++++++++------------- 1 file changed, 11 insertions(+), 13 deletions(-) diff --git a/GPy/testing/test_kernel.py b/GPy/testing/test_kernel.py index 44aa306f..bae1ed0b 100644 --- a/GPy/testing/test_kernel.py +++ b/GPy/testing/test_kernel.py @@ -517,8 +517,8 @@ class TestKernelGradientContinuous: + GPy.kern.Linear(self.D) ) k.randomize() - with pytest.raises(IndexError): - self.X[:, : self.D] + # with pytest.raises(IndexError): + self.X[:, : self.D] k = ( GPy.kern.Matern32(2, active_dims=[2, self.D - 1]) + GPy.kern.RBF(2, active_dims=[0, 4]) @@ -546,9 +546,7 @@ class TestKernelGradientContinuous: def test_OU(self): k = GPy.kern.OU(self.D - 1, ARD=True) k.randomize() - self.assertTrue( - check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose) - ) + assert check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose) def test_Cosine(self): self.setup() @@ -817,10 +815,8 @@ class TestKernelNonContinuous: self.setup() k = GPy.kern.RBF(self.D, active_dims=range(self.D)) kern = GPy.kern.IndependentOutputs(k, -1, "ind_single") - self.assertTrue( - check_kernel_gradient_functions( - kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1 - ) + assert check_kernel_gradient_functions( + kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1 ) k = [ GPy.kern.RBF(1, active_dims=[1], name="rbf1"), @@ -872,7 +868,7 @@ class TestKernelNonContinuous: @pytest.mark.skipif( not cython_coregionalize_working, - "Cython coregionalize module has not been built on this machine", + reason="Cython coregionalize module has not been built on this machine", ) class TestCoregionalizeCython: """ @@ -936,12 +932,14 @@ class TestKernelProductWithZeroValues: def test_zero_valued_kernel_full(self): self.setup() self.k.update_gradients_full(1, self.X) - assert np.isnan(self.k["linear.variances"].gradient), "Gradient resulted in NaN" + assert not np.isnan( + self.k["linear.variances"].gradient + ), "Gradient resulted in NaN" def test_zero_valued_kernel_gradients_X(self): - self.seutp() + self.setup() target = self.k.gradients_X(1, self.X) - assert np.any(np.isnan(target)), "Gradient resulted in NaN" + assert not np.any(np.isnan(target)), "Gradient resulted in NaN" class TestKernelPsiStatisticsGradient: