Function create_shear

monai/transforms/utils.py:947–983

create a shearing matrix Args: spatial_dims: spatial rank coefs: shearing factors, a tuple of 2 floats for 2D, a tuple of 6 floats for 3D). Individual single-axis shear matrices are composed (multiplied) in coefficient order so that the result is a p

(
    spatial_dims: int,
    coefs: Sequence[float] | float,
    device: torch.device | None = None,
    backend=TransformBackends.NUMPY,
)

def create_shear(
    spatial_dims: int,
    coefs: Sequence[float] | float,
    device: torch.device | None = None,
    backend=TransformBackends.NUMPY,
) -> NdarrayOrTensor:
    """
    create a shearing matrix

    Args:
        spatial_dims: spatial rank
        coefs: shearing factors, a tuple of 2 floats for 2D, a tuple of 6 floats for 3D).
            Individual single-axis shear matrices are composed (multiplied) in
            coefficient order so that the result is a proper shear with determinant 1.
            For 2D with coefs ``(Sx, Sy)`` the composed matrix is::

                [
                    [1.0,  Sx,          0.0],
                    [Sy,   1.0 + Sx*Sy, 0.0],
                    [0.0,  0.0,         1.0],
                ]

        device: device to compute and store the output (when the backend is "torch").
        backend: APIs to use, ``numpy`` or ``torch``.

    Raises:
        NotImplementedError: When ``spatial_dims`` is not one of [2, 3].

    """
    _backend = look_up_option(backend, TransformBackends)
    if _backend == TransformBackends.NUMPY:
        return _create_shear(spatial_dims=spatial_dims, coefs=coefs, eye_func=np.eye)
    if _backend == TransformBackends.TORCH:
        return _create_shear(
            spatial_dims=spatial_dims, coefs=coefs, eye_func=lambda rank: torch.eye(rank, device=device)
        )
    raise ValueError(f"backend {backend} is not supported")


def _create_shear(spatial_dims: int, coefs: Sequence[float] | float, eye_func=np.eye) -> NdarrayOrTensor: