numpy.ndarray.view() helps to get a new view of array with the same data.
Syntax: ndarray.view(dtype=None, type=None)
Parameters:
dtype : Data-type descriptor of the returned view, e.g., float32 or int16. The default, None, results in the view having the same data-type as a.
type : Python type, optional
Returns : ndarray or matrix.
Code #1:
Python3
# Python program explaining # numpy.ndarray.view() function import numpy as geek a = geek.arange( 10 , dtype = 'int16' ) print ( "a is: \n" , a) # using view() method v = a.view( 'int32' ) print ( "\n After using view() with dtype = 'int32' a is : \n" , a) v + = 1 # addition of 1 to each element of v print ( "\n After using view() with dtype = 'int32' and adding 1 a is : \n" , a) |
a is: [0 1 2 3 4 5 6 7 8 9] After using view() with dtype = 'int32' a is : [0 1 2 3 4 5 6 7 8 9] After using view() with dtype = 'int32' and adding 1 a is : [1 1 3 3 5 5 7 7 9 9]
Code #2:
Python3
# Python program explaining # numpy.ndarray.view() function import numpy as geek a = geek.arange( 10 , dtype = 'int16' ) print ( "a is:" , a) # Using view() method v = a.view( 'int16' ) print ( "\n After using view() with dtype = 'int16' a is :\n" , a) v + = 1 # addition of 1 to each element of v print ( "\n After using view() with dtype = 'int16' and adding 1 a is : \n" , a) |
a is: [0 1 2 3 4 5 6 7 8 9] After using view() with dtype = 'int16' a is : [0 1 2 3 4 5 6 7 8 9] After using view() with dtype = 'int16' and adding 1 a is : [ 1 2 3 4 5 6 7 8 9 10]
Code #3:
Python3
# Python program explaining # numpy.ndarray.view() function import numpy as geek a = geek.arange( 10 , dtype = 'int16' ) print ( "a is: \n" , a) v = a.view( 'int8' ) print ( "\n After using view() with dtype = 'int8' a is : \n" , a) v + = 1 # addition of 1 to each element of v print ( "\n After using view() with dtype = 'int8' and adding 1 a is : \n" , a) |