Class ScaleIntensityRanged

monai/transforms/intensity/dictionary.py:867–903

Dictionary-based wrapper of :py:class:`monai.transforms.ScaleIntensityRange`. Args: keys: keys of the corresponding items to be transformed. See also: monai.transforms.MapTransform a_min: intensity original range min. a_max: intensity original range max.

class ScaleIntensityRanged(MapTransform):
    """
    Dictionary-based wrapper of :py:class:`monai.transforms.ScaleIntensityRange`.

    Args:
        keys: keys of the corresponding items to be transformed.
            See also: monai.transforms.MapTransform
        a_min: intensity original range min.
        a_max: intensity original range max.
        b_min: intensity target range min.
        b_max: intensity target range max.
        clip: whether to perform clip after scaling.
        dtype: output data type, if None, same as input image. defaults to float32.
        allow_missing_keys: don't raise exception if key is missing.
    """

    backend = ScaleIntensityRange.backend

    def __init__(
        self,
        keys: KeysCollection,
        a_min: float,
        a_max: float,
        b_min: float | None = None,
        b_max: float | None = None,
        clip: bool = False,
        dtype: DtypeLike = np.float32,
        allow_missing_keys: bool = False,
    ) -> None:
        super().__init__(keys, allow_missing_keys)
        self.scaler = ScaleIntensityRange(a_min, a_max, b_min, b_max, clip, dtype)

    def __call__(self, data: Mapping[Hashable, NdarrayOrTensor]) -> dict[Hashable, NdarrayOrTensor]:
        d = dict(data)
        for key in self.key_iterator(d):
            d[key] = self.scaler(d[key])
        return d


class ClipIntensityPercentilesd(MapTransform):