numpy.ones_like() in Python
The one_like() method of Python numpy class returns an array of ones with the same shape and type as the specified array.
Syntax
numpy.ones_like(a, dtype=None, order='K', subok=True)
Parameter
The numpy.ones_like() method consists of four parameters, which are as follows:
arrray : It indicates the array_like input.
subok : It is an optional Boolean argument that is used to make a subclass of type ‘a’ or not. By default, it is true.
order : The order parameter can be either C_contiguous or F_contiguous. C order means that operating row-rise on the array will be slightly quicker
FORTRAN-contiguous order in memory (the first index varies the fastest). F order means that column-wise operations will be faster.
dtype : It is an optional parameter. It depicts the data type of returned array, and by default, it is a float.
Return
This method returns the array with the specified shape, order and datatype.
Example 1
# Python Programming giving an example for
# numpy.ones_like() method
import numpy as numpy
array = numpy.arange(10).reshape(5, 2)
print("Original array : \n", array)
a = numpy.ones_like(array, float)
print("\nMatrix : \n", a)
array = numpy.arange(8)
b = numpy.ones_like(array)
print("\nMatrix : \n", b)
Output
Original array :
[[0 1]
[2 3]
[4 5]
[6 7]
[8 9]]
Matrix :
[[ 1. 1.]
[ 1. 1.]
[ 1. 1.]
[ 1. 1.]
[ 1. 1.]]
Matrix :
[1 1 1 1 1 1 1 1]
