我如何使用链式比较对数组进行布尔化掩盖? [英] How do I boolean mask an array using chained comparisons?

问题描述

如何使用一对不等式来过滤一个numpy数组，例如:

How can I filter a numpy array using a pair of inequalities, such as:

>>> a = np.arange(10)
>>> a[a <= 6]
array([0, 1, 2, 3, 4, 5, 6])
>>> a[3 < a]
array([4, 5, 6, 7, 8, 9])
>>>
>>> a[3 < a <= 6]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: The truth value of an array with more than one element is ambiguous.
 Use a.any() or a.all()

如果我尝试a.all(3 < a <= 6)

np.array([x for x in a if 3 < x <= 6])可以工作，但是看起来很讨厌.什么是正确的方法?

np.array([x for x in a if 3 < x <= 6]) works, but it seems nasty. What's the right way to do this?

推荐答案

您需要这样做:

a[(3 < a) & (a <= 6)]

这是python中的疣".在python中，(3 < a <=6)被翻译为((3 < a) and (a <= 6)).但是numpy数组不适用于and操作，因为python不允许and和or运算符重载.因此，numpy使用&和|.大约一年前，有一些关于解决此问题的讨论，但是自那以后，我对此似乎没有多少关注.

It's a "wart" in python. In python (3 < a <=6) is translated to ((3 < a) and (a <= 6)). However numpy arrays don't work with the and operation because python doesn't allow overloading of the and and or operators. Because of that numpy uses & and |. There was some discussion about fixing this about a year ago, but I haven't seem much about it since.

http://mail.python.org/pipermail/python-dev/2012-March/117510.html

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