def test_covariance_inverse_generator_02(self, array_type):
input_array = array_type(self.training_data)
KrigingClass = KrigingModel(input_array[0:3], regularization=True)
cov_matrix = np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
inverse_x = KrigingClass.covariance_inverse_generator(cov_matrix)
np.testing.assert_array_equal(np.round(inverse_x, 7),
np.round(cov_matrix, 7))
def test_covariance_inverse_generator_01(self, array_type):
input_array = array_type(self.training_data)
KrigingClass = KrigingModel(input_array[0:3], regularization=True)
cov_matrix = np.array([[1.000001, 0.60653066, 0.13533528],
[0.60653066, 1.000001, 0.60653066],
[0.13533528, 0.60653066, 1.000001]])
cov_matrix_inv_exp = np.array([[1.82957788, -1.51792604, 0.67306158],
[-1.51792604, 2.84133453, -1.51792604],
[0.67306158, -1.51792604, 1.82957788]])
inverse_x = KrigingClass.covariance_inverse_generator(cov_matrix)
np.testing.assert_array_equal(np.round(inverse_x, 7), np.round(cov_matrix_inv_exp, 7))