numpy的所有不同于内置所有 [英] numpy all differing from builtin all

问题描述

numpy的all出现这种怪异的原因是什么?

What is the reason for this weirdness in numpy's all?

>>> import numpy as np
>>> np.all(xrange(10))
False
>>> np.all(i for i in xrange(10))
True

推荐答案

Numpy.all不理解生成器表达式.

Numpy.all does not understands generator expressions.

从文档中

 numpy.all(a, axis=None, out=None)

    Test whether all array elements along a given axis evaluate to True.
    Parameters :    

    a : array_like

        Input array or object that can be converted to an array.

好吧，不是很明确，所以让我们看一下代码

Ok, not very explicit, so lets look at the code

def all(a,axis=None, out=None):
    try:
        all = a.all
    except AttributeError:
        return _wrapit(a, 'all', axis, out)
    return all(axis, out)

def _wrapit(obj, method, *args, **kwds):
    try:
        wrap = obj.__array_wrap__
    except AttributeError:
        wrap = None
    result = getattr(asarray(obj),method)(*args, **kwds)
    if wrap:
        if not isinstance(result, mu.ndarray):
            result = asarray(result)
        result = wrap(result)
    return result

由于生成器表达式没有all方法，因此最终调用_wrapit 在_wrapit中，它首先检查__array_wrap__方法，该方法generates AttributeError最后结束在生成器表达式上调用asarray

As generator expression doesn't have all method, it ends up calling _wrapit In _wrapit, it first checks for __array_wrap__ method which generates AttributeError finally ending up calling asarray on the generator expression

来自numpy.asarray

 numpy.asarray(a, dtype=None, order=None)

    Convert the input to an array.
    Parameters :    

    a : array_like

        Input data, in any form that can be converted to an array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays.

关于接受的各种输入数据的文献充分记录，这绝对不是生成器表达式

It is well documented about the various types of Input data thats accepted which is definitely not generator expression

最后，尝试

>>> np.asarray(0 for i in range(10))
array(<generator object <genexpr> at 0x42740828>, dtype=object)

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