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

Last Updated : 08 Mar, 2024

The numpy.one_like() function returns an array of given shape and type as a given array, with ones.

Syntax: numpy.ones_like(array, dtype = None, order = 'K', subok = True)

Parameters :

array : array_like input subok : [optional, boolean]If true, then newly created array will be sub-class of array; otherwise, a base-class array order : C_contiguous or F_contiguous C-contiguous order in memory(last index varies the fastest) C order means that operating row-wise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster. dtype : [optional, float(byDefault)] Data type of returned array.

Returns :

ndarray of ones having given shape, order and datatype.

Python `

Python Programming illustrating

numpy.ones_like method

import numpy as geek

array = geek.arange(10).reshape(5, 2) print("Original array : \n", array)

b = geek.ones_like(array, float) print("\nMatrix b : \n", b)

array = geek.arange(8) c = geek.ones_like(array) print("\nMatrix c : \n", c)

`

Output:

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

Matrix b : [[ 1. 1.] [ 1. 1.] [ 1. 1.] [ 1. 1.] [ 1. 1.]]

Matrix c : [1 1 1 1 1 1 1 1]

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