cunumeric.clip#

cunumeric.clip(a: ndarray, a_min: int | float | npt.ArrayLike | None, a_max: int | float | npt.ArrayLike | None, out: npt.NDArray[Any] | ndarray | None = None) ndarray#

Clip (limit) the values in an array.

Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1.

Parameters:
  • a (array_like) – Array containing elements to clip.

  • a_min (scalar or array_like or None) – Minimum value. If None, clipping is not performed on lower interval edge. Not more than one of a_min and a_max may be None.

  • a_max (scalar or array_like or None) – Maximum value. If None, clipping is not performed on upper interval edge. Not more than one of a_min and a_max may be None. If a_min or a_max are array_like, then the three arrays will be broadcasted to match their shapes.

  • out (ndarray, optional) – The results will be placed in this array. It may be the input array for in-place clipping. out must be of the right shape to hold the output. Its type is preserved.

  • **kwargs – For other keyword-only arguments, see the ufunc docs.

Returns:

clipped_array – An array with the elements of a, but where values < a_min are replaced with a_min, and those > a_max with a_max.

Return type:

ndarray

See also

numpy.clip

Availability:

Multiple GPUs, Multiple CPUs