numpy.ones_like () in Python



numpy.ones_like (array, dtype = None, order = & # 39; K & # 39 ;, subok = True): return an array of the given shape and type as a given array with ones,
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-rise 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 (byDeafult)] Data type of returned array. 

Returns :

 ndarray of ones having given shape, order and datatype. 

# Python Illustrative Programming
# numpy.ones_like method

  

import numpy as geek

 

array = geek. arange ( 10 ). reshape ( 5 , 2 )

print ( " Original array: " , array)

  

  

b = geek.ones_like (array, float )

print ( "Matrix b:" , b)

 

array = geek.arange ( 8 )

c = geek.ones_like (array)

print ( "Matrix c:" , c)

Exit :

 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] 

Links:
https:// docs.scipy.org/doc/numpy-dev/reference/generated/numpy.ones_like.html
Notes:
Also, these codes will not work to an online ID. Please run them on your systems to see how they work

This article is courtesy of Mohit Gupta_OMG