numpy.clip() in Python

numpy.clip() in Python

Last Updated : 29 Nov, 2018

numpy.clip() function is used to 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.

Syntax : numpy.clip(a, a_min, a_max, out=None) Parameters : a : Array containing elements to clip. a_min : 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 : 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 : 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. Return : clipped_array

Code #1 :

Python3

# Python3 code demonstrate clip() function

# importing the numpy
import numpy as np

in_array = [1, 2, 3, 4, 5, 6, 7, 8 ]
print ("Input array : ", in_array)

out_array = np.clip(in_array, a_min = 2, a_max = 6)
print ("Output array : ", out_array)

Output :

Input array :  [1, 2, 3, 4, 5, 6, 7, 8]
Output array :  [2 2 3 4 5 6 6 6]

Code #2 :

Python3

# Python3 code demonstrate clip() function

# importing the numpy
import numpy as np

in_array = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
print ("Input array : ", in_array)

out_array = np.clip(in_array, a_min =[3, 4, 1, 1, 1, 4, 4, 4, 4, 4],
                                                         a_max = 9)
print ("Output array : ", out_array)

Output :

Input array :  [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Output array :  [3 4 3 4 5 6 7 8 9 9]

numpy.clip() in Python

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