def METHOD_NAME():
    # Small streamline
    streamline = [[1, 2, 3], [4, 5, 3], [5, 6, 3]]
    # Non-default eigenvalues:
    evals = [0.0012, 0.0006, 0.0004]
    streamline_tensors = life.streamline_tensors(streamline, evals=evals)
    npt.assert_array_almost_equal(streamline_tensors[0],
                                  np.array([[0.0009, 0.0003, 0.],
                                            [0.0003, 0.0009, 0.],
                                            [0., 0., 0.0004]]))
    # Get the eigenvalues/eigenvectors:
    eigvals, eigvecs = la.eig(streamline_tensors[0])
    eigvecs = eigvecs[np.argsort(eigvals)[::-1]]
    eigvals = eigvals[np.argsort(eigvals)[::-1]]
    npt.assert_array_almost_equal(eigvals,
                                  np.array([0.0012, 0.0006, 0.0004]))
    npt.assert_array_almost_equal(eigvecs[0],
                                  np.array([0.70710678, -0.70710678, 0.]))
    # Another small streamline
    streamline = [[1, 0, 0], [2, 0, 0], [3, 0, 0]]
    streamline_tensors = life.streamline_tensors(streamline, evals=evals)
    for t in streamline_tensors:
        eigvals, eigvecs = la.eig(t)
        eigvecs = eigvecs[np.argsort(eigvals)[::-1]]
        # This one has no rotations - all tensors are simply the canonical:
        npt.assert_almost_equal(np.rad2deg(np.arccos(
            np.dot(eigvecs[0], [1, 0, 0]))), 0)
        npt.assert_almost_equal(np.rad2deg(np.arccos(
            np.dot(eigvecs[1], [0, 1, 0]))), 0)
        npt.assert_almost_equal(np.rad2deg(np.arccos(
            np.dot(eigvecs[2], [0, 0, 1]))), 0)