def test_cross_validation_fit_02(self):
np.random.seed(42)
inputs = np.random.uniform(-1, 1, 15).reshape(5, -1)
outputs = np.random.uniform(0, 5, 10).reshape(5, -1)
gradients = np.random.uniform(-1, 1, 30).reshape(5, 2, 3)
ss = ActiveSubspaces(dim=1)
csv = CrossValidation(inputs=inputs,
outputs=outputs,
gradients=gradients,
folds=3,
subspace=ss)
csv.fit(inputs, gradients, outputs)
self.assertIsNotNone(csv.gp)
def test_cross_validation_fit_01(self):
np.random.seed(42)
inputs = np.random.uniform(-1, 1, 15).reshape(5, -1)
outputs = np.random.uniform(0, 5, 10).reshape(5, -1)
gradients = np.random.uniform(-1, 1, 30).reshape(5, 2, 3)
ss = ActiveSubspaces(dim=2, method='exact')
csv = CrossValidation(inputs=inputs,
outputs=outputs,
gradients=gradients,
folds=3,
subspace=ss)
csv.fit(inputs, gradients, outputs)
self.assertEqual(csv.gp.X.shape[1], 2)