Numpy MaskedArray.flatten() function | Python
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 :
# 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 :
# 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]
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