numpy.ma.asarray() function is used when we want to convert input to a masked array of the given data-type.
No copy is performed if the input is already a ndarray. If arr is a subclass of MaskedArray, a base class MaskedArray is returned.
Syntax : numpy.ma.asarray(arr, dtype=None, order=None)
Parameters :
arr : [array_like] Input data, in any form that can be converted to a masked array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists, ndarrays and masked arrays.
dtype : [data-type, optional] By default, the data-type is inferred from the input data.
order : Whether to use row-major (C-style) or column-major (Fortran-style) memory representation. Defaults to ‘C’.Return : [MaskedArray] Masked array interpretation of arr.
Code #1 :
# Python program explaining # numpy.ma.asarray() function import numpy as geek my_list = [1, 4, 8, 7, 2, 5] print ("Input list : ", my_list) out_arr = geek.ma.asarray(my_list) print ("output array from input list : ", out_arr) |
Output :
Input list : [1, 4, 8, 7, 2, 5] output array from input list : [1 4 8 7 2 5]
Code #2 :
# Python program explaining # numpy.ma.asarray() function import numpy as geek my_tuple = ([1, 4, 8], [7, 2, 5]) print ("Input tuple : ", my_tuple) out_arr = geek.ma.asarray(my_tuple) print ("output array from input tuple : ", out_arr) |
Output :
Input tuple : ([1, 4, 8], [7, 2, 5]) output array from input tuple : [[1 4 8] [7 2 5]]
