本文介绍了比较两个 numpy 二维数组的相似性的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有 2D numpy array1
只包含 0
和 255
值
I have 2D numpy array1
that contains only 0
and 255
values
([[255, 0, 255, 0, 0],
[ 0, 255, 0, 0, 0],
[ 0, 0, 255, 0, 255],
[ 0, 255, 255, 255, 255],
[255, 0, 255, 0, 255]])
和一个 array2
,它的大小和形状与 array1
相同,并且也只包含 0
和 255
值
and an array2
that is identical in size and shape as array1
and also contains only 0
and 255
values
([[255, 0, 255, 0, 255],
[ 0, 255, 0, 0, 0],
[255, 0, 0, 0, 255],
[ 0, 0, 255, 255, 255],
[255, 0, 255, 0, 0]])
如何比较 array1
和 array2
以确定相似度百分比?
How can I compare array1
to array2
to determine a similarity percentage?
推荐答案
由于您只有两个可能的值,我建议使用此算法进行相似性检查:
As you only have two possible values, I would propose this algorithm for similarity-checking:
import numpy as np
A = np.array([[255, 0, 255, 0, 0],
[ 0, 255, 0, 0, 0],
[ 0, 0, 255, 0, 255],
[ 0, 255, 255, 255, 255],
[255, 0, 255, 0, 255]])
B = np.array([[255, 0, 255, 0, 255],
[ 0, 255, 0, 0, 0],
[255, 0, 0, 0, 255],
[ 0, 0, 255, 255, 255],
[255, 0, 255, 0, 0]])
number_of_equal_elements = np.sum(A==B)
total_elements = np.multiply(*A.shape)
percentage = number_of_equal_elements/total_elements
print('total number of elements: \t\t{}'.format(total_elements))
print('number of identical elements: \t\t{}'.format(number_of_equal_elements))
print('number of different elements: \t\t{}'.format(total_elements-number_of_equal_elements))
print('percentage of identical elements: \t{:.2f}%'.format(percentage*100))
计算相等元素并计算相等元素占元素总数的百分比
It counts equal elements and calculates the percentage of the equal elements to the total number of elements
这篇关于比较两个 numpy 二维数组的相似性的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!