numpy.clip#

numpy.clip(a,a_min=<novalue>,a_max=<novalue>,out=None,*,min=<novalue>,max=<novalue>,**kwargs)[source]#

Clip (limit) the values in an array.

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

Equivalent to but faster thannp.minimum(a_max,np.maximum(a,a_min)).

No check is performed to ensurea_min<a_max.

Parameters:
aarray_like

Array containing elements to clip.

a_min, a_maxarray_like or None

Minimum and maximum value. IfNone, clipping is not performed onthe corresponding edge. If botha_min anda_max areNone,the elements of the returned array stay the same. Both are broadcastedagainsta.

outndarray, optional

The results will be placed in this array. It may be the inputarray for in-place clipping.out must be of the right shapeto hold the output. Its type is preserved.

min, maxarray_like or None

Array API compatible alternatives fora_min anda_maxarguments. Eithera_min anda_max ormin andmaxcan be passed at the same time. Default:None.

New in version 2.1.0.

**kwargs

For other keyword-only arguments, see theufunc docs.

Returns:
clipped_arrayndarray

An array with the elements ofa, but where values<a_min are replaced witha_min, and those >a_maxwitha_max.

Notes

Whena_min is greater thana_max,clip returns anarray in which all values are equal toa_max,as shown in the second example.

Examples

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