Wouldn't it be nice to have numpy a little more generic? All that would be needed was a little check of the arguments.
If I do: numpy.trace(4) shouldn't numpy be smart enough to regard the 4 as a 1x1 array? numpy.sin(4) works! and if x = my_class(4) wouldn't it be nice if numpy.trace(x) would call x.trace() ? numpy.sin(my_class(4)) works! Wouldn't it be nice if numpy worked a little more consistent. Is this worth a ticket? Or am I missing something here? On Fri, Jan 30, 2009 at 10:05 PM, Robert Kern <robert.k...@gmail.com> wrote: > On Fri, Jan 30, 2009 at 13:18, Christopher Barker <chris.bar...@noaa.gov> > wrote: >> I think you want to subclass an ndarray here. It's a bit tricky to so, >> but if you look in the wiki and these mailing list archives, you'll find >> advise on how to do it. > > That still won't work. numpy.linalg.inv() simply does a particular > algorithm on float and complex arrays and nothing else. > > -- > Robert Kern > > "I have come to believe that the whole world is an enigma, a harmless > enigma that is made terrible by our own mad attempt to interpret it as > though it had an underlying truth." > -- Umberto Eco > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
