numpy.MaskedArray.transpose() function is used to permute the dimensions of an masked array.
Syntax :
numpy.ma.transpose(axis)Parameters:
axis :[list of ints, optional] By default, reverse the dimensions, otherwise permute the axes according to the values given.Return : [ ndarray] Resultant array with its axes permuted..
Code #1 :
# Python program explaining # numpy.MaskedArray.transpose() 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([[1, 2], [ 3, -1], [ 5, -3]]) print ("Input array : ", in_arr)     # Now we are creating a masked array. # by making entry as invalid.  mask_arr = ma.masked_array(in_arr, mask =[[ 1, 0], [ 0, 1], [ 0, 0]]) print ("Masked array : ", mask_arr)     # applying MaskedArray.transpose methods # to masked array out_arr = mask_arr.transpose() print ("Output transposed masked array : ", out_arr) |
Output:
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [3 --] [5 -3]] Output transposed masked array : [[-- 3 5]
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Code #2 :
# Python program explaining # numpy.MaskedArray.transpose() 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]], [[ -45.0, 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 ("3D Masked array : ", mask_arr)      # applying MaskedArray.transpose methods # to masked array out_arr = mask_arr.transpose() print ("Output transposed masked array : ", out_arr) |
Output:
Input array : [[[ 2.0e+08 3.0e-05]] [[-4.5e+01 2.0e+05]]] 3D Masked array : [[[-- 3e-05]] [[-45.0 200000.0]]] Output transposed masked array : [[[-- -45.0]] [[3e-05 200000.0]]]
