问题描述
我正在玩numpy并仔细阅读文档，我遇到了一些魔术.即我在说numpy.where():
I am playing with numpy and digging through documentation and I have come across some magic. Namely I am talking about numpy.where():
>>> x = np.arange(9.).reshape(3, 3)
>>> np.where( x > 5 )
(array([2, 2, 2]), array([0, 1, 2]))
它们如何在内部实现您能够将类似x > 5的内容传递给方法的功能?我想这可能与__gt__有关，但我正在寻找详细的解释.
How do they achieve internally that you are able to pass something like x > 5 into a method? I guess it has something to do with __gt__ but I am looking for a detailed explanation.
推荐答案
简短的答案是他们没有.
The short answer is that they don't.
对numpy数组进行任何逻辑运算都会返回一个布尔数组. (即__gt__，__lt__等都返回给定条件为true的布尔数组).
Any sort of logical operation on a numpy array returns a boolean array. (i.e. __gt__, __lt__, etc all return boolean arrays where the given condition is true).
例如
x = np.arange(9).reshape(3,3)
print x > 5
产量:
array([[False, False, False],
[False, False, False],
[ True, True, True]], dtype=bool)
这就是为什么如果x是一个numpy数组，类似if x > 5:的对象会引发ValueError的相同原因.这是一个True/False值数组，而不是单个值.
This is the same reason why something like if x > 5: raises a ValueError if x is a numpy array. It's an array of True/False values, not a single value.
此外，可以用布尔数组对numpy数组进行索引.例如.在这种情况下，x[x>5]产生[6 7 8].
Furthermore, numpy arrays can be indexed by boolean arrays. E.g. x[x>5] yields [6 7 8], in this case.
老实说，您实际上需要numpy.where的情况很少见，但它只返回布尔数组为True的索引.通常，您可以通过简单的布尔索引来完成所需的工作.
Honestly, it's fairly rare that you actually need numpy.where but it just returns the indicies where a boolean array is True. Usually you can do what you need with simple boolean indexing.
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