Function create_rotate

monai/transforms/utils.py:862–897

create a 2D or 3D rotation matrix Args: spatial_dims: {``2``, ``3``} spatial rank radians: rotation radians when spatial_dims == 3, the `radians` sequence corresponds to rotation in the 1st, 2nd, and 3rd dim respectively. device: device to co

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

def create_rotate(
    spatial_dims: int,
    radians: Sequence[float] | float,
    device: torch.device | None = None,
    backend: str = TransformBackends.NUMPY,
) -> NdarrayOrTensor:
    """
    create a 2D or 3D rotation matrix

    Args:
        spatial_dims: {``2``, ``3``} spatial rank
        radians: rotation radians
            when spatial_dims == 3, the `radians` sequence corresponds to
            rotation in the 1st, 2nd, and 3rd dim respectively.
        device: device to compute and store the output (when the backend is "torch").
        backend: APIs to use, ``numpy`` or ``torch``.

    Raises:
        ValueError: When ``radians`` is empty.
        ValueError: When ``spatial_dims`` is not one of [2, 3].

    """
    _backend = look_up_option(backend, TransformBackends)
    if _backend == TransformBackends.NUMPY:
        return _create_rotate(
            spatial_dims=spatial_dims, radians=radians, sin_func=np.sin, cos_func=np.cos, eye_func=np.eye
        )
    if _backend == TransformBackends.TORCH:
        return _create_rotate(
            spatial_dims=spatial_dims,
            radians=radians,
            sin_func=lambda th: torch.sin(torch.as_tensor(th, dtype=torch.float32, device=device)),
            cos_func=lambda th: torch.cos(torch.as_tensor(th, dtype=torch.float32, device=device)),
            eye_func=lambda rank: torch.eye(rank, device=device),
        )
    raise ValueError(f"backend {backend} is not supported")


def _create_rotate(