为什么“不是数字"?在Python/Numpy中转换为布尔值时，值是否等于True? [英] Why do "Not a Number" values equal True when cast as boolean in Python/Numpy?
问题描述
将NumPy非数字值转换为布尔值时，它变为True，例如如下.
When casting a NumPy Not-a-Number value as a boolean, it becomes True, e.g. as follows.
>>> import numpy as np
>>> bool(np.nan)
True
这与我的直觉期望完全相反.这种行为是否有合理的原则?
This is the exact opposite to what I would intuitively expect. Is there a sound principle underlying this behaviour?
(我怀疑八度音阶中可能会出现相同的行为.)
(I suspect there might be as the same behaviour seems to occur in Octave.)
推荐答案
这绝不是NumPy特有的，但与Python处理NaN的方式是一致的:
This is in no way NumPy-specific, but is consistent with how Python treats NaNs:
In [1]: bool(float('nan'))
Out[1]: True
The rules are spelled out in the documentation.
我认为可以合理地认为NaN的真值应为False.但是，这不是该语言目前的工作方式.
I think it could be reasonably argued that the truth value of NaN should be False. However, this is not how the language works right now.
这篇关于为什么“不是数字"?在Python/Numpy中转换为布尔值时，值是否等于True?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IT屋！
