povm_test.py 文件源码

def test_povm_normalization_ic(dim):
    for name, constructor in ALL_POVMS.items():
        # Check that the POVM is normalized: elements must sum to the identity
        current_povm = constructor(dim)
        element_sum = sum(iter(current_povm))
        assert_array_almost_equal(element_sum, np.eye(dim))

        # Check that the attribute that says whether the POVM is IC is correct.
        linear_inversion_recons = np.dot(current_povm.linear_inversion_map,
                                         current_povm.probability_map)
        if current_povm.informationally_complete:
            assert_array_almost_equal(
                linear_inversion_recons, np.eye(dim**2),
                err_msg='POVM {} is not informationally complete'.format(name))
        else:
            assert np.abs(linear_inversion_recons - np.eye(dim**2)).max() > 0.1, \
                'POVM {} is informationally complete'.format(name)