Numpy MaskedArray.flatten() function | Python (original) (raw)

Last Updated : 03 Oct, 2019

numpy.MaskedArray.flatten() function is used to return a copy of the input masked array collapsed into one dimension.

Syntax : numpy.ma.flatten(order='C') Parameters: order : [‘C’, ‘F’, ‘A’, ‘K’, optional] Whether to flatten in C (row-major), Fortran (column-major) order, or preserve the C/Fortran ordering from a. The default is ‘C’.Return : [ ndarray] A copy of the input array, flattened to one dimension.

Code #1 :

Python3 `

Python program explaining

numpy.MaskedArray.flatten() method

importing numpy as geek

and numpy.ma module as ma

import numpy as geek import numpy.ma as ma

creating input array of 2 * 2

in_arr = geek.array([[10, 20], [-10, 40]]) print ("Input array : ", in_arr)

Now we are creating a masked array

by making one entry as invalid.

mask_arr = ma.masked_array(in_arr, mask =[[ 1, 0], [ 0, 0]]) print ("Masked array : ", mask_arr)

applying MaskedArray.flatten methods to make

it a 1D flattened array

out_arr = mask_arr.flatten() print ("Output flattened masked array : ", out_arr)

`

Output:

Input array : [[ 10 20] [-10 40]] Masked array : [[-- 20] [-10 40]] Output flattened masked array : [-- 20 -10 40]

Code #2 :

Python3 `

Python program explaining

numpy.MaskedArray.flatten() method

importing numpy as geek

and numpy.ma module as ma

import numpy as geek import numpy.ma as ma

creating input array

in_arr = geek.array([[[ 2e8, 3e-5]], [[ -4e-6, 2e5]]]) print ("Input array : ", in_arr)

Now we are creating a masked array

by making one entry as invalid.

mask_arr = ma.masked_array(in_arr, mask =[[[ 1, 0]], [[ 0, 0]]]) print ("Masked array : ", mask_arr)

applying MaskedArray.flatten methods to make

it a 1D masked array

out_arr = mask_arr.flatten(order ='F') print ("Output flattened masked array : ", out_arr)

`

Output:

Input array : [[[ 2.e+08 3.e-05]]

[[-4.e-06 2.e+05]]] Masked array : [[[-- 3e-05]]

[[-4e-06 200000.0]]] Output flattened masked array : [-- -4e-06 3e-05 200000.0]