On Wed, 2013-02-06 at 10:18 +0100, Dag Sverre Seljebotn wrote: > On 02/06/2013 08:41 AM, Charles R Harris wrote: > > > > > > On Tue, Feb 5, 2013 at 11:50 PM, Jason Grout > > <jason-s...@creativetrax.com <mailto:jason-s...@creativetrax.com>> wrote: > > > > On 2/6/13 12:46 AM, Charles R Harris wrote: > > > if we decide to do so > > > > I should mention that we don't really depend on either behavior (we > > probably should have a better doctest testing for an array of None > > values anyway), but we noticed the oddity and thought we ought to > > mention it. So it doesn't matter to us which way the decision goes. > > > > > > More Python craziness > > > > In [6]: print None or 0 > > 0 > > > > In [7]: print 0 or None > > None > > To me this seems natural and is just how Python works? I think the rule > for "or" is simply "evaluate __nonzero__ of left operand, if it is > False, return right operand". > > The reason is so that you can use it like this: >
Yes, but any() and all() functions in python return forcibly a bool as one would expect. So probably logical_and.reduce and all should simply not be the same thing, at least for objects. Though it is a bit weird that objects do something different from other types, so maybe it would be OK to say that numpy just differs from python here, since I am not sure if you can easily change it for the other types. Regards, Sebastian > x = get_foo() or get_bar() # if get_foo() returns None > # use result of get_bar > > or > > def f(x=None): > x = x or create_default_x() > ... > > I guess that after the "a if expr else b" was introduced this has become > less common. > > Dag Sverre > > > > > Numpy any is consistent with python when considered as logical_or.reduce > > > > In [13]: print array([0, None]).any() > > None > > > > In [14]: print array([None, 0]).any() > > 0 > > > > This appears to be an __ror__, __or__ inconsistency in python. Note that > > None possesses neither of those operators. > > > > Chuck > > > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > http://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
