numpy.ascontiguousarray() in Python

numpy.ascontiguousarray()function is used when we want to return a contiguous array in memory (C order).

Syntax : numpy.ascontiguousarray(arr, dtype=None)

Parameters :
arr : [array_like] Input data, in any form that can be converted to an array. This includes scalars, lists, lists of tuples, tuples, tuples of tuples, tuples of lists, and ndarrays.
dtype : [str or dtype object, optional] Data-type of returned array.

Return : ndarray Contiguous array of same shape and content as arr, with type dtype if specified.

Code #1 : List to array

filter_none

edit
close

play_arrow

link
brightness_4
code

# Python program explaining
# numpy.ascontiguousarray() function
  
import numpy as geek
my_list = [100, 200, 300, 400, 500]
  
print ("Input  list : ", my_list)
   
    
out_arr = geek.ascontiguousarray(my_list, dtype = geek.float32)
print ("output array from input list : ", out_arr) 

chevron_right


Output :

Input  list :  [100, 200, 300, 400, 500]
output array from input list :  [ 100.  200.  300.  400.  500.]

 
Code #2 : Tuple to array

filter_none

edit
close

play_arrow

link
brightness_4
code

# Python program explaining
# numpy.ascontiguousarray() function
  
import numpy as geek
  
my_tuple = ([2, 6, 10], [8, 12, 16])
   
print ("Input  touple : ", my_tuple)
    
out_arr = geek.ascontiguousarray(my_tuple, dtype = geek.int32) 
print ("output array from input touple : ", out_arr) 

chevron_right


Output :

Input  touple :  ([2, 6, 10], [8, 12, 16])
output array from input touple :  [[ 2  6 10]
 [ 8 12 16]]

 
Code #3 : Scalar to array

filter_none

edit
close

play_arrow

link
brightness_4
code

# Python program explaining
# numpy.ascontiguousarray() function
  
import numpy as geek
  
my_scalar = 100
   
print ("Input  scalar : ", my_scalar)
    
out_arr = geek.ascontiguousarray(my_scalar, dtype = geek.float32) 
print ("output array from input scalar : ", out_arr) 
print(type(out_arr))

chevron_right


Output :

Input  scalar :  100
output array from input scalar :  [ 100.]
class 'numpy.ndarray'


My Personal Notes arrow_drop_up

Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.