Class Spacingd

monai/transforms/spatial/dictionary.py:367–540

Dictionary-based wrapper of :py:class:`monai.transforms.Spacing`. This transform assumes the ``data`` dictionary has a key for the input data's metadata and contains `affine` field. The key is formed by ``key_{meta_key_postfix}``. After resampling the input array, this transform

class Spacingd(MapTransform, InvertibleTransform, LazyTransform):
    """
    Dictionary-based wrapper of :py:class:`monai.transforms.Spacing`.

    This transform assumes the ``data`` dictionary has a key for the input
    data's metadata and contains `affine` field.  The key is formed by ``key_{meta_key_postfix}``.

    After resampling the input array, this transform will write the new affine
    to the `affine` field of metadata which is formed by ``key_{meta_key_postfix}``.

    This transform is capable of lazy execution. See the :ref:`Lazy Resampling topic<lazy_resampling>`
    for more information.

    see also:
        :py:class:`monai.transforms.Spacing`
    """

    backend = Spacing.backend

    def __init__(
        self,
        keys: KeysCollection,
        pixdim: Sequence[float] | float,
        diagonal: bool = False,
        mode: SequenceStr = GridSampleMode.BILINEAR,
        padding_mode: SequenceStr = GridSamplePadMode.BORDER,
        align_corners: Sequence[bool] | bool = False,
        dtype: Sequence[DtypeLike] | DtypeLike = np.float64,
        scale_extent: bool = False,
        recompute_affine: bool = False,
        min_pixdim: Sequence[float] | float | None = None,
        max_pixdim: Sequence[float] | float | None = None,
        ensure_same_shape: bool = True,
        allow_missing_keys: bool = False,
        lazy: bool = False,
    ) -> None:
        """
        Args:
            pixdim: output voxel spacing. if providing a single number, will use it for the first dimension.
                items of the pixdim sequence map to the spatial dimensions of input image, if length
                of pixdim sequence is longer than image spatial dimensions, will ignore the longer part,
                if shorter, will pad with `1.0`.
                if the components of the `pixdim` are non-positive values, the transform will use the
                corresponding components of the original pixdim, which is computed from the `affine`
                matrix of input image.
            diagonal: whether to resample the input to have a diagonal affine matrix.
                If True, the input data is resampled to the following affine::

                    np.diag((pixdim_0, pixdim_1, pixdim_2, 1))

                This effectively resets the volume to the world coordinate system (RAS+ in nibabel).
                The original orientation, rotation, shearing are not preserved.

                If False, the axes orientation, orthogonal rotation and
                translations components from the original affine will be
                preserved in the target affine. This option will not flip/swap
                axes against the original ones.
            mode: {``"bilinear"``, ``"nearest"``} or spline interpolation order 0-5 (integers).