Python Numpy MaskedArray.atleast_2d()函数

Python Numpy MaskedArray.atleast_2d()函数

numpy.MaskedArray.atleast_2d()函数用于将输入转换为至少有两个维度的掩码数组。标量和一维数组被转换为二维数组,而高维输入则被保留。

语法: numpy.ma.atleast_2d(*arys)

参数:
arys: [ array_like] 一个或多个输入数组。

返回 : [ ndarray] 一个数组,或数组列表,每个数组都有 arr.ndim >= 2。

代码#1:

# Python program explaining
# numpy.MaskedArray.atleast_2d() method 
    
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
    
# creating input arrays  
in_arr1 = geek.array([ 3, -1, 5, -3])
print ("1st Input array : ", in_arr1)
  
in_arr2 = geek.array(2)
print ("2nd Input array : ", in_arr2)
    
# Now we are creating  masked array. 
# by making  entry as invalid.  
mask_arr1 = ma.masked_array(in_arr1, mask =[ 1, 0, 1, 0]) 
print ("1st Masked array : ", mask_arr1)
  
mask_arr2 = ma.masked_array(in_arr2, mask = 0) 
print ("2nd Masked array : ", mask_arr2)
    
# applying MaskedArray.atleast_2d methods 
# to masked array 
out_arr = ma.atleast_2d(mask_arr1, mask_arr2) 
print ("Output masked array : ", out_arr) 

输出:

1st Input array :  [ 3 -1  5 -3]
2nd Input array :  2
1st Masked array :  [-- -1 -- -3]
2nd Masked array :  2
Output masked array :  [masked_array(data=[[--, -1, --, -3]],
             mask=[[ True, False,  True, False]],
       fill_value=999999), masked_array(data=[[2]],
             mask=[[False]],
       fill_value=999999)]


代码#2:

# Python program explaining
# numpy.MaskedArray.atleast_2d() 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.atleast_2d methods 
# to masked array
out_arr = ma.atleast_2d(mask_arr) 
print ("Output masked array : ", out_arr)

输出:

Input array :  [[[ 2.0e+08  3.0e-05]]

 [[-4.5e+01  2.0e+05]]]
3D Masked array :  [[[-- 3e-05]]

 [[-45.0 200000.0]]]
Output masked array :  [[[-- 3e-05]]

 [[-45.0 200000.0]]]

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Numpy 数组操作