Python Numpy MaskedArray.transpose()用法及代碼示例

numpy.MaskedArray.transpose()函數用於置換蒙版數組的尺寸。

用法： numpy.ma.transpose(axis)

參數：
axis:[整數列表，可選]默認情況下，反轉尺寸，否則根據給定的值對軸進行排列。

Return :[ndarray]結果數組，其軸已置換。

代碼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)

輸出：

Input array: [[ 1  2]
 [ 3 -1]
 [ 5 -3]]
Masked array: [[-- 2]
 [3 --]
 [5 -3]]
Output transposed masked array: [[-- 3 5]

代碼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)

輸出：

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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注：本文由純淨天空篩選整理自jana_sayantan大神的英文原創作品 Numpy MaskedArray.transpose() function | Python。非經特殊聲明，原始代碼版權歸原作者所有，本譯文未經允許或授權，請勿轉載或複製。