numpy都与内置所有不同

Question

numpy的这种奇怪之处是什么原因all？

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

Answer 1

Numpy.all不了解生成器表达式.

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.

好的,不是很明确,所以让我们看看代码

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

作为发电机表达式不具有all的方法,它结束调用_wrapit 在_wrapit为,它首先检查__array_wrap__方法,其generates AttributeError最后结束了呼叫asarray在发电机表达

从文档中 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.

有关所接受的各种类型的输入数据的详细记录,绝对不是生成器表达式

最后,尝试

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