2008/7/3 Zbyszek Szmek <[EMAIL PROTECTED]>: > On Wed, Jul 02, 2008 at 10:55:12PM +0200, Stéfan van der Walt wrote: >> 2008/7/2 Zbyszek Szmek <[EMAIL PROTECTED]>: >> >> That's Ticket #709 <http://projects.scipy.org/scipy/numpy/ticket/709>: >> >> >> >> > I'm faily sure that: >> >> > numpy.isnan(datetime.datetime.now() >> >> > ...should just return False and not raise an exception. >> > IMHO numpy.isnan() makes no sense for non-numerical types. >> >> I agree with Chuck's rationale [if someone asks me whether a peanut >> butter sandwhich is a Koala bear, then I'd say no, without trying to >> cast the sandwhich to a mammal], and it seems that other ufuncs try to >> be general this way, e.g. np.add handles arbitrary classes with >> __add__ methods. > Exactly, you can add things only when they are numerical or when you have > defined __add__, otherwise it's a TypeError. > If it was important and general enough, we could add an attribute __isnan__, > and extend isnan-iness to other things, but it probably isn't. > > The operator 'is' makes sense for both mammals and sandwiches, so the > statement > 'a butter sandwich is a Koala' makes sense. > I would compare isnan-iness to asking if > 'a butter sandwich is even-toed'? It is defined for some mammals, and doesn't > have a definite value for other things.
We may be talking about two different things here: - NaN: the IEEE floating point number - Not a number: anything that is not a number The `isnan`-function specifically aims to identify the first case. > Defining isnan for arbitrary objects seems a workaround for passing > objects to a wrong place function and pollution of code with a kludge for > a special case. Sure, this can be done. Then the function will simply become: Return False unless the input object is a NumPy floating-point scalar (or a Python float) that matches the IEEE NaN bit-pattern. Long live even-toed peanut-butter eating Koalas! Stéfan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
