numpy.MaskedArray.swapaxes() function is used to Return a view of the masked array with axis1 and axis2 interchanged.
Syntax :
numpy.ma.swapaxes(axis1, axis2)Parameters:
axis1 :[int] First axis.
axis2 : [int] Second axis.Return : [ swapped_array] Resultant array.
Code #1 :
# Python program explaining # numpy.MaskedArray.swapaxes() 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.swapaxes methods # to masked array out_arr = mask_arr.swapaxes(0, 1) print ("Output swapped masked array : ", out_arr) |
Output:
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [3 --] [5 -3]] Output swapped masked array : [[-- 3 5] [2 -- -3]]
Code #2 :
# Python program explaining # numpy.MaskedArray.swapaxes() 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.swapaxes methods # to masked array out_arr = mask_arr.swapaxes(0, 2) print ("Output swapped 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 swapped masked array : [[[-- -45.0]] [[3e-05 200000.0]]]
