Numpy maskearray . allequal()函数| Python
原文:https://www . geeksforgeeks . org/numpy-masked array-allequal-function-python/
在许多情况下，数据集可能是不完整的，或者被无效数据污染。例如，传感器可能未能记录数据，或者记录了无效值。numpy.ma模块通过引入屏蔽数组提供了一种解决这个问题的便捷方法。屏蔽数组是指可能缺少条目或条目无效的数组。
numpy.MaskedArray.allequal() 如果 a 和 b 的所有条目都相等，函数返回真，使用 fill_value 作为真值，其中一个或两个都被屏蔽。
语法:
numpy.ma.allequal(arr1, arr2, fill_value=True)参数: arr1、arr 2:【array _ like】输入数组进行比较。 fill _ value:【bool，可选】arr1 或 arr2 中的屏蔽值是否被视为相等(真)或不相等(假)。
返回:【bool】如果两个数组在给定容差内相等，则返回真，否则返回假。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)
Output:
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)
Output:
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
