def METHOD_NAME():
    data = np.ones((10, 10, 10))
    bundle = Streamlines()
    bundle.extend(np.array([[[0, 0., 0],
                             [1, 0., 0.],
                             [2, 0., 0.]]]))
    bundle.extend(np.array([[[0, 0., 0.],
                             [1, 0., 0],
                             [2, 0,  0.]]]))
    profile = afq_profile(data, bundle, np.eye(4))
    npt.assert_equal(profile, np.ones(100))
    profile = afq_profile(data, bundle, np.eye(4), n_points=10,
                          weights=None)
    npt.assert_equal(profile, np.ones(10))
    profile = afq_profile(data, bundle, np.eye(4),
                          weights=gaussian_weights, stat=np.median)
    npt.assert_equal(profile, np.ones(100))
    profile = afq_profile(data, bundle, np.eye(4), orient_by=bundle[0],
                          weights=gaussian_weights, stat=np.median)
    npt.assert_equal(profile, np.ones(100))
    profile = afq_profile(data, bundle, np.eye(4), n_points=10,
                          weights=None)
    npt.assert_equal(profile, np.ones(10))
    profile = afq_profile(data, bundle, np.eye(4), n_points=10,
                          weights=np.ones((2, 10)) * 0.5)
    npt.assert_equal(profile, np.ones(10))
    profile = afq_profile(data, bundle, np.eye(4), n_points=10,
                          stat=np.median)
    npt.assert_equal(profile, np.ones(10))
    # Disallow setting weights that don't sum to 1 across fibers/nodes:
    npt.assert_raises(ValueError, afq_profile,
                      data, bundle, np.eye(4),
                      n_points=10, weights=np.ones((2, 10)) * 0.6)
    # Test using an affine:
    affine = np.eye(4)
    affine[:, 3] = [-1, 100, -20, 1]
    # Transform the streamlines:
    bundle._data = bundle._data + affine[:3, 3]
    profile = afq_profile(data,
                          bundle,
                          affine,
                          n_points=10,
                          weights=None)
    npt.assert_equal(profile, np.ones(10))
    # Test for error-handling:
    empty_bundle = Streamlines([])
    npt.assert_raises(ValueError, afq_profile, data, empty_bundle, np.eye(4))