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Numpy MaskedArray.transpose() function | Python

  • Last Updated : 13 Oct, 2019

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]

 

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]]]


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