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 可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试):
问题:
回答1:
Numpy.all does not understands generator expressions.
From the documentation
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. 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 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
From the documentation of 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. It is well documented about the various types of Input data thats accepted which is definitely not generator expression
Finally, trying
>>> np.asarray(0 for i in range(10)) array(<generator object <genexpr> at 0x42740828>, dtype=object) 回答2:
Strange. When I try that I get:
>>> np.all(i for i in xrange(10)) <generator object <genexpr> at 0x7f6e04c64500> Hmm.
I don't think numpy understands generator expressions. Try using a list comprehension and you get this:
>>> np.all([i for i in xrange(10)]) False