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
# 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) |
Output :
Input list : [100, 200, 300, 400, 500] output array from input list : [ 100. 200. 300. 400. 500.]
Code #2 : Tuple to array
# Python program explaining # numpy.ascontiguousarray() function import numpy as geek my_tuple = ([ 2 , 6 , 10 ], [ 8 , 12 , 16 ]) print ( "Input tuple : " , my_tuple) out_arr = geek.ascontiguousarray(my_tuple, dtype = geek.int32) print ( "output array from input tuple : " , out_arr) |
Output :
Input tuple : ([2, 6, 10], [8, 12, 16]) output array from input tuple : [[ 2 6 10] [ 8 12 16]]
Code #3 : Scalar to array
# 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)) |
Output :
Input scalar : 100 output array from input scalar : [ 100.] class 'numpy.ndarray'