numpy.ndarray.view() in Python
Last Updated :
01 Mar, 2024
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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:
# 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:
# 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:
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]
