From ffd05027cbdc4213a670c337859cd783001278ba Mon Sep 17 00:00:00 2001 From: Nicolas Date: Fri, 18 Jan 2013 16:14:13 +0000 Subject: [PATCH] More tests in unit_tests --- GPy/kern/rbf.py | 1 + GPy/testing/unit_tests.py | 41 ++++++++++++++++++++++++++------------- 2 files changed, 29 insertions(+), 13 deletions(-) diff --git a/GPy/kern/rbf.py b/GPy/kern/rbf.py index 62a9c46d..1e9b4379 100644 --- a/GPy/kern/rbf.py +++ b/GPy/kern/rbf.py @@ -24,6 +24,7 @@ class rbf(kernpart): :type lengthscale: np.ndarray od size (1,) or (D,) depending on ARD :param ARD: Auto Relevance Determination. If equal to "False", the kernel is isotropic (ie. one single lengthscale parameter \ell), otherwise there is one lengthscale parameter per dimension. :type ARD: Boolean + :rtype: kernel object """ diff --git a/GPy/testing/unit_tests.py b/GPy/testing/unit_tests.py index d2ef87f7..c5db80bd 100644 --- a/GPy/testing/unit_tests.py +++ b/GPy/testing/unit_tests.py @@ -42,51 +42,66 @@ class GradientTests(unittest.TestCase): # contrain all parameters to be positive self.assertTrue(m.checkgrad()) - def test_gp_regression_rbf_white_kern_1d(self): + def test_gp_regression_rbf_1d(self): ''' Testing the GP regression with rbf kernel with white kernel on 1d data ''' rbf = GPy.kern.rbf(1) self.check_model_with_white(rbf, model_type='GP_regression', dimension=1) - def test_GP_regression_rbf_ARD_white_kern_2D(self): - ''' Testing the GP regression with rbf and white kernel on 2d data ''' - k = GPy.kern.rbf_ARD(2) - self.check_model_with_white(k, model_type='GP_regression', dimension=2) - - def test_GP_regression_rbf_white_kern_2D(self): + def test_GP_regression_rbf_2D(self): ''' Testing the GP regression with rbf and white kernel on 2d data ''' rbf = GPy.kern.rbf(2) self.check_model_with_white(rbf, model_type='GP_regression', dimension=2) - def test_GP_regression_matern52_kern_1D(self): + def test_GP_regression_rbf_ARD_2D(self): + ''' Testing the GP regression with rbf and white kernel on 2d data ''' + k = GPy.kern.rbf(2,ARD=True) + self.check_model_with_white(k, model_type='GP_regression', dimension=2) + + def test_GP_regression_matern52_1D(self): ''' Testing the GP regression with matern52 kernel on 1d data ''' matern52 = GPy.kern.Matern52(1) self.check_model_with_white(matern52, model_type='GP_regression', dimension=1) - def test_GP_regression_matern52_kern_2D(self): + def test_GP_regression_matern52_2D(self): ''' Testing the GP regression with matern52 kernel on 2d data ''' matern52 = GPy.kern.Matern52(2) self.check_model_with_white(matern52, model_type='GP_regression', dimension=2) - def test_GP_regression_matern32_kern_1D(self): + def test_GP_regression_matern52_ARD_2D(self): + ''' Testing the GP regression with matern52 kernel on 2d data ''' + matern52 = GPy.kern.Matern52(2,ARD=True) + self.check_model_with_white(matern52, model_type='GP_regression', dimension=2) + + def test_GP_regression_matern32_1D(self): ''' Testing the GP regression with matern32 kernel on 1d data ''' matern32 = GPy.kern.Matern32(1) self.check_model_with_white(matern32, model_type='GP_regression', dimension=1) - def test_GP_regression_matern32_kern_2D(self): + def test_GP_regression_matern32_2D(self): ''' Testing the GP regression with matern32 kernel on 2d data ''' matern32 = GPy.kern.Matern32(2) self.check_model_with_white(matern32, model_type='GP_regression', dimension=2) - def test_GP_regression_exponential_kern_1D(self): + def test_GP_regression_matern32_ARD_2D(self): + ''' Testing the GP regression with matern32 kernel on 2d data ''' + matern32 = GPy.kern.Matern32(2,ARD=True) + self.check_model_with_white(matern32, model_type='GP_regression', dimension=2) + + def test_GP_regression_exponential_1D(self): ''' Testing the GP regression with exponential kernel on 1d data ''' exponential = GPy.kern.exponential(1) self.check_model_with_white(exponential, model_type='GP_regression', dimension=1) - def test_GP_regression_exponential_kern_2D(self): + def test_GP_regression_exponential_2D(self): ''' Testing the GP regression with exponential kernel on 2d data ''' exponential = GPy.kern.exponential(2) self.check_model_with_white(exponential, model_type='GP_regression', dimension=2) + def test_GP_regression_exponential_ARD_2D(self): + ''' Testing the GP regression with exponential kernel on 2d data ''' + exponential = GPy.kern.exponential(2,ARD=True) + self.check_model_with_white(exponential, model_type='GP_regression', dimension=2) + def test_GP_regression_bias_kern_1D(self): ''' Testing the GP regression with bias kernel on 1d data ''' bias = GPy.kern.bias(1)