Python Numpy MaskedArray.allequal()用法及代码示例

在许多情况下，数据集可能不完整或被无效数据污染。例如，传感器可能无法记录数据或记录了无效值。的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条目或无效条目的数组。

如果a和b的所有条目都相等，则numpy.MaskedArray.allequal()函数将true填充为真值(其中一个或两个都被屏蔽)时返回True。

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

参数：
arr1，arr2：[数组]要比较的输入数组。
fill_value :[bool，可选]是否将arr1或arr2中的掩码值视为相等(真)或不相等(假)。

Return :[bool]如果两个数组在给定的公差范围内相等，则返回True，否则返回False。如果任一数组包含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

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注：本文由纯净天空筛选整理自jana_sayantan大神的英文原创作品 Numpy MaskedArray.allequal() function | Python。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。