[英]How to compare two arrays of arrays 'array-elementwise' in Numpy?
Given two arrays of arrays A and B, I need to test the equality of each subarray from A (ai) to its corresponding subarray in B (bi): 给定数组A和B的两个数组,我需要测试从A(ai)到B中的相应子数组(bi)的相等性:
import numpy as np
a1 = np.array([1, 2, 3])
a2 = np.array([3, 4, 5])
a3 = np.array([2, 4, 6])
A = np.array([a1, a2, a3])
b1 = np.array([3, 2, 1])
b2 = np.array([3, 4, 5])
b3 = np.array([6, 4, 2])
B = np.array([b1, b2, b3])
def compare_arrays(A, B):
#ret = A == B
#ret = np.array_equal(A, B)
return ret
print(compare_arrays(A, B))
Unsurprisingly, the output I get with A == B
: [[False True False][ True True True][False True False]]
. 毫不奇怪,我通过
A == B
获得的输出: [[False True False][ True True True][False True False]]
。
Unsurprisingly, the output I get with np.array_equal(A, B)
: False
. 毫不奇怪,我通过
np.array_equal(A, B)
获得的输出: False
。
The output I would like to get: [[False, True, False]]
. 我想得到的输出:
[[False, True, False]]
。
I would like to know if there exists an off-the-shelf solution that I have not found or if I should implement my own. 我想知道是否存在尚未找到的现成解决方案,或者是否应该实施自己的解决方案。
You can get logical and results along axis=1 from A == B. 您可以从A == B获得沿轴= 1的逻辑和结果。
def compare_arrays(A, B):
ret = np.equal(A, B).all(axis=1)
return ret
You can use something like this: 您可以使用如下形式:
def compare_arrays(A, B):
return map(lambda item: not False in item, A==B)
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