numpy.clip

numpy.clip(a, a_min, a_max, out=None)

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

Minimum value.

a_max : scalar or array_like

Maximum value. If a_min or a_max are array_like, then they will be broadcasted to the shape of a.

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.

Returns:

clipped_array : ndarray

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

See also

numpy.doc.ufuncs

Section “Output arguments”

Examples

>>> a = np.arange(10)
>>> np.clip(a, 1, 8)
array([1, 1, 2, 3, 4, 5, 6, 7, 8, 8])
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.clip(a, 3, 6, out=a)
array([3, 3, 3, 3, 4, 5, 6, 6, 6, 6])
>>> a = np.arange(10)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.clip(a, [3,4,1,1,1,4,4,4,4,4], 8)
array([3, 4, 2, 3, 4, 5, 6, 7, 8, 8])