Numpy MaskedArray.masked_where()函数| Python

在许多情况下，数据集可能不完整或因存在无效数据而受到污染。例如，传感器可能无法记录数据，或记录无效值。 numpy.ma模块通过引入掩码数组提供了解决此问题的便捷方法。掩码数组是可能缺少或无效条目的数组。

numpy.MaskedArray.masked_where()函数用于屏蔽满足条件的数组。它返回 arr 作为屏蔽条件为 True 的数组。 arr 或 condition 的任何屏蔽值也会在输出中屏蔽。

Syntax : numpy.ma.masked_where(condition, arr, copy=True)

Parameters:
condition : [array_like] Masking condition. When condition tests floating point values for equality, consider using masked_values instead.
arr : [ndarray] Input array which we want to mask.
copy : [bool] If True (default) make a copy of arr in the result. If False modify arr in place and return a view.

Return : [ MaskedArray] The result of masking arr where condition is True..

代码#1：

# Python program explaining
# numpy.MaskedArray.masked_where() 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, 2])
print ("Input array : ", in_arr)
  
# applying MaskedArray.masked_where methods 
# to input array where value<= 1
mask_arr = ma.masked_where(in_arr<= 1, in_arr)
print ("Masked array : ", mask_arr)

输出：

Input array :  [ 1  2  3 -1  2]
Masked array :  [-- 2 3 -- 2]

代码#2：

# Python program explaining
# numpy.MaskedArray.masked_where() method 
  
# importing numpy as geek 
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
  
# creating input array in_arr1 
in_arr1 = geek.arange(4)
print ("1st Input array : ", in_arr1)
  
# applying MaskedArray.masked_where methods 
# to input array in_arr1 where value = 1
mask_arr1 = ma.masked_where(in_arr1 == 1, in_arr1)
print ("1st Masked array : ", mask_arr1)
  
# creating input array in_arr2 
in_arr2 = geek.arange(4)
print ("2nd Input array : ", in_arr2)
  
# applying MaskedArray.masked_where methods 
# to input array in_arr2 where value = 1
mask_arr2 = ma.masked_where(in_arr2 == 3, in_arr2)
print ("2nd Masked array : ", mask_arr2)
  
# applying MaskedArray.masked_where methods 
# to 1st masked array where second masked array
# is used as condition
res_arr = ma.masked_where(mask_arr1 == 3, mask_arr2)
print("Resultant Masked array : ", res_arr)

输出：

1st Input array :  [0 1 2 3]
1st Masked array :  [0 -- 2 3]
2nd Input array :  [0 1 2 3]
2nd Masked array :  [0 1 2 --]
Resultant Masked array :  [0 -- 2 --]