Python Numpy MaskedArray.allequal()函数

在许多情况下，数据集可能是不完整的，或因存在无效数据而受到污染。例如，一个传感器可能未能记录一个数据，或者记录了一个无效的值。numpy.ma模块通过引入掩码数组，为解决这个问题提供了一个方便的方法。掩码数组是可能存在缺失或无效项的数组。

numpy.MaskedArray.allequal()函数如果a和b的所有条目都相等，则返回True，使用fill_value作为真值，其中任何一个或两个都被屏蔽。

语法: numpy.ma.allequal(arr1, arr2, fill_value=True)

参数:
arr1, arr2 : [array_like] 要比较的输入数组。
fill_value : [ bool, optional] arr1或arr2中的屏蔽值是否被视为相等（True）或不相等（False）。

返回 : [ bool]如果两个数组在给定的公差内相等，则返回True，否则返回False。如果任何一个数组包含NaN，则返回False。

代码#1：

# Python program explaining
# numpy.MaskedArray.allequal() method 
  
# importing numpy as geek 
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
  
# creating 1st input array 
in_arr1 = geek.array([1e8, 1e-5, -15.0])
print ("1st Input array : ", in_arr1)
  
# Now we are creating 1st masked array by making third entry as invalid. 
mask_arr1 = ma.masked_array(in_arr1, mask =[0, 0, 1])
print ("1st Masked array : ", mask_arr1)
  
# creating 2nd input array 
in_arr2 = geek.array([1e8, 1e-5, 15.0])
print ("2nd Input array : ", in_arr2)
  
# Now we are creating 2nd masked array by making third entry as invalid. 
mask_arr2 = ma.masked_array(in_arr2, mask =[0, 0, 1])
print ("2nd Masked array : ", mask_arr2)
  
# applying MaskedArray.allequal method
out_arr = ma.allequal(mask_arr1, mask_arr2, fill_value = False)
print ("Output array : ", out_arr)

输出:

1st Input array :  [ 1.0e+08  1.0e-05 -1.5e+01]
1st Masked array :  [100000000.0 1e-05 --]
2nd Input array :  [1.0e+08 1.0e-05 1.5e+01]
2nd Masked array :  [100000000.0 1e-05 --]
Output array :  False

代码#2：

# importing numpy as geek 
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
  
# creating 1st input array 
in_arr1 = geek.array([2e8, 3e-5, -45.0])
print ("1st Input array : ", in_arr1)
  
# Now we are creating 1st masked array by making third entry as invalid. 
mask_arr1 = ma.masked_array(in_arr1, mask =[0, 0, 1])
print ("1st Masked array : ", mask_arr1)
  
# creating 2nd input array 
in_arr2 = geek.array([2e8, 3e-5, 15.0])
print ("2nd Input array : ", in_arr2)
  
# Now we are creating 2nd masked array by making third entry as invalid. 
mask_arr2 = ma.masked_array(in_arr2, mask =[0, 0, 1])
print ("2nd Masked array : ", mask_arr2)
# applying MaskedArray.allequal method
out_arr = ma.allequal(mask_arr1, mask_arr2, fill_value = True)
print ("Output  array : ", out_arr)

输出:

1st Input array :  [ 2.0e+08  3.0e-05 -4.5e+01]
1st Masked array :  [200000000.0 3e-05 --]
2nd Input array :  [2.0e+08 3.0e-05 1.5e+01]
2nd Masked array :  [200000000.0 3e-05 --]
Output  array :  True