比较 dtype 对象的 numpy 数组

问题描述

我的问题是为什么?:"

My question is "why?:"

aa[0]
array([[405, 162, 414, 0,
        array([list([1, 9, 2]), 18, (405, 18, 207), 64, 'Universal'],
      dtype=object),
        0, 0, 0]], dtype=object)

aaa
array([[405, 162, 414, 0,
        array([list([1, 9, 2]), 18, (405, 18, 207), 64, 'Universal'],
      dtype=object),
        0, 0, 0]], dtype=object)

np.array_equal(aaa,aa[0])
False

那些数组完全相同.

我的最小示例没有重现这一点:

My minimal example doesn't reproduce this:

be=np.array([1],dtype=object)

be
array([1], dtype=object)

ce=np.array([1],dtype=object)

ce
array([1], dtype=object)

np.array_equal(be,ce)
True

这个也没有:

ce=np.array([np.array([1]),'5'],dtype=object)

be=np.array([np.array([1]),'5'],dtype=object)

np.array_equal(be,ce)
True

但是，要重现我的问题，请尝试以下操作:

be=np.array([[405, 162, 414, 0, np.array([list([1, 9, 2]), 18, (405, 18, 207), 64, 'Universal'],dtype=object),0, 0, 0]], dtype=object)

ce=np.array([[405, 162, 414, 0, np.array([list([1, 9, 2]), 18, (405, 18, 207), 64, 'Universal'],dtype=object),0, 0, 0]], dtype=object)

np.array_equal(be,ce)
False

np.array_equal(be[0],ce[0])
False

我不知道为什么它们不相等.还有一个额外的问题，我该如何比较它们?

And I have no idea why those are not equal. And to add the bonus question, how do I compare them?

我需要一种有效的方法来检查 aaa 是否在堆栈 aa 中.

我没有在 aa 中使用 aaa，因为 DeprecationWarning: elementwise == 比较失败；这将在未来引发错误. 并且因为如果有人想知道它仍然返回 False.

I'm not using aaa in aa because of DeprecationWarning: elementwise == comparison failed; this will raise an error in the future. and because it still returns False if anyone is wondering.

np.equal(be,ce)
*** ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

np.all(be,ce)
*** TypeError: only integer scalar arrays can be converted to a scalar index

all(be,ce)
*** TypeError: all() takes exactly one argument (2 given)

all(be==ce)
*** TypeError: 'bool' object is not iterable

np.where(be==ce)
(array([], dtype=int64),)

而这些，我无法在控制台中运行，全部评估为 False，有些给出弃用警告:

And these, which I can't get to run in the console, all evaluate to False, some giving the deprecation warning:

import numpy as np

ce=np.array([[405, 162, 414, 0, np.array([list([1, 9, 2]), 18, (405, 18, 207), 64, 'Universal'],dtype=object),0, 0, 0]], dtype=object)

be=np.array([[405, 162, 414, 0, np.array([list([1, 9, 2]), 18, (405, 18, 207), 64, 'Universal'],dtype=object),0, 0, 0]], dtype=object)

print(np.any([bee in ce for bee in be]))

print(np.any([bee==cee for bee in be for cee in ce]))

print(np.all([bee in ce for bee in be]))

print(np.all([bee==cee for bee in be for cee in ce]))

当然还有其他问题告诉我这应该可行...

And of course other questions telling me this should work...

推荐答案

要在数组之间进行元素比较，您可以使用 numpy.equal() 带有关键字参数 dtype=numpy.object 如:

To make an element-wise comparison between the arrays, you can use numpy.equal() with the keyword argument dtype=numpy.object as in :

In [60]: np.equal(be, ce, dtype=np.object)
Out[60]:
array([[True, True, True, True,
        array([ True,  True,  True,  True,  True]), True, True, True]],
      dtype=object)

P.S. 使用 NumPy 版本 1.15.2 和 Python 3.6.6

P.S. checked using NumPy version 1.15.2 and Python 3.6.6

来自 1.15 的发行说明，

From the release notes for 1.15,

https://docs.scipy.org/doc/numpy-1.15.1/release.html#comparison-ufuncs-accept-dtype-object-overriding-the-default-bool>

Comparison ufuncs accept dtype=object, overriding the default bool

This allows object arrays of symbolic types, which override == and
other operators to return expressions, to be compared elementwise with
np.equal(a, b, dtype=object).

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