numpy.place() in Python (original) (raw)

Last Updated : 08 Mar, 2024

The numpy.place() method makes changes in the array according the parameters – conditions and value(uses first N-values to put into array as per the mask being set by the user). It works opposite to numpy.extract().

Syntax:

numpy.place(array, mask, vals)

Parameters :

array : [ndarray] Input array, we need to make changes into mask : [array_like]Boolean that must have same size as that of the input array value : Values to put into the array. Based on the mask condition it adds only N-elements to the array. If in case values in val are smaller than the mask, same values get repeated.

Return :

Array with change elements i.e. new elements being put

Python

import numpy as geek

array = geek.arange( 12 ).reshape( 3 , 4 )

print ( "Original array : \n" , array)

a = geek.place(array, array > 5 , [ 15 , 25 , 35 ])

print ( "\nPutting up elements to array: \n" , array)

array1 = geek.arange( 6 ).reshape( 2 , 3 )

print ( "\n\nOriginal array1 : \n" , array)

a = geek.place(array1, array1> 2 , [ 44 , 55 ])

print ( "\nPutting new elements to array1 : \n" , array1)

Output :

Original array : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]]

Putting up elements to array: [[ 0 1 2 3] [ 4 5 15 25] [35 15 25 35]]

Original array1 : [[ 0 1 2 3] [ 4 5 15 25] [35 15 25 35]]

Putting new elements to array1 : [[ 0 1 2] [44 55 44]]

Note :
These codes won’t run on online IDE’s. So please, run them on your systems to explore the working.