Function rescale_array

monai/transforms/utils.py:232–260

Rescale the values of numpy array `arr` to be from `minv` to `maxv`. If either `minv` or `maxv` is None, it returns `(a - min_a) / (max_a - min_a)`. Args: arr: input array to rescale. minv: minimum value of target rescaled array. maxv: maximum value of target re

(
    arr: NdarrayOrTensor,
    minv: float | None = 0.0,
    maxv: float | None = 1.0,
    dtype: DtypeLike | torch.dtype = np.float32,
)

def rescale_array(
    arr: NdarrayOrTensor,
    minv: float | None = 0.0,
    maxv: float | None = 1.0,
    dtype: DtypeLike | torch.dtype = np.float32,
) -> NdarrayOrTensor:
    """
    Rescale the values of numpy array `arr` to be from `minv` to `maxv`.
    If either `minv` or `maxv` is None, it returns `(a - min_a) / (max_a - min_a)`.

    Args:
        arr: input array to rescale.
        minv: minimum value of target rescaled array.
        maxv: maximum value of target rescaled array.
        dtype: if not None, convert input array to dtype before computation.

    """
    if dtype is not None:
        arr, *_ = convert_data_type(arr, dtype=dtype)
    mina = arr.min()
    maxa = arr.max()

    if mina == maxa:
        return arr * minv if minv is not None else arr

    norm = (arr - mina) / (maxa - mina)  # normalize the array first
    if (minv is None) or (maxv is None):
        return norm
    return (norm * (maxv - minv)) + minv  # rescale by minv and maxv, which is the normalized array by default


def rescale_instance_array(