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Merge branch 'devel' into esiivola-feature-multioutput

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mzwiessele 2018-09-02 16:49:59 +01:00
commit 270b90857c
10 changed files with 255 additions and 67 deletions
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14
GPy/testing/kernel_tests.py
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@ -482,7 +482,19 @@ class KernelGradientTestsContinuous(unittest.TestCase):
k = GPy.kern.StdPeriodic(self.D)
k.randomize()
self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose))
def test_symmetric_even(self):
k_base = GPy.kern.Linear(1) + GPy.kern.RBF(1)
transform = -np.array([[1.0]])
k = GPy.kern.Symmetric(k_base, transform, 'even')
self.assertTrue(check_kernel_gradient_functions(k))
def test_symmetric_odd(self):
k_base = GPy.kern.Linear(1) + GPy.kern.RBF(1)
transform = -np.array([[1.0]])
k = GPy.kern.Symmetric(k_base, transform, 'odd')
self.assertTrue(check_kernel_gradient_functions(k))
def test_MultioutputKern(self):
k1 = GPy.kern.RBF(self.D, ARD=True)
k1.randomize()

4
GPy/testing/serialization_tests.py
View file

@ -237,7 +237,9 @@ class Test(unittest.TestCase):
m.save_model("temp_test_gp_classifier_with_data.json", compress=True, save_data=True)
m.save_model("temp_test_gp_classifier_without_data.json", compress=True, save_data=False)
m1_r = GPy.models.GPClassification.load_model("temp_test_gp_classifier_with_data.json.zip")
self.assertTrue(type(m) == type(m1_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r)))
m2_r = GPy.models.GPClassification.load_model("temp_test_gp_classifier_without_data.json.zip", (X,Y))
self.assertTrue(type(m) == type(m2_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r)))
os.remove("temp_test_gp_classifier_with_data.json.zip")
os.remove("temp_test_gp_classifier_without_data.json.zip")
@ -259,7 +261,9 @@ class Test(unittest.TestCase):
m.save_model("temp_test_sparse_gp_classifier_with_data.json", compress=True, save_data=True)
m.save_model("temp_test_sparse_gp_classifier_without_data.json", compress=True, save_data=False)
m1_r = GPy.models.SparseGPClassification.load_model("temp_test_sparse_gp_classifier_with_data.json.zip")
self.assertTrue(type(m) == type(m1_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r)))
m2_r = GPy.models.SparseGPClassification.load_model("temp_test_sparse_gp_classifier_without_data.json.zip", (X,Y))
self.assertTrue(type(m) == type(m2_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r)))
os.remove("temp_test_sparse_gp_classifier_with_data.json.zip")
os.remove("temp_test_sparse_gp_classifier_without_data.json.zip")