numpy.ndarray.view() in Python

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)

Output

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)

Output

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

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)

Output:

a is: 
 [0 1 2 3 4 5 6 7 8 9]

 After using view() with dtype = 'int8' a is : 
 [0 1 2 3 4 5 6 7 8 9]

 After using view() with dtype = 'int8' and adding 1 a is : 
 [257 258 259 260 261 262 263 264 265 266]