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() ?
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 email@example.com wrote:
On Fri, Jan 30, 2009 at 13:18, Christopher Barker Chris.Barker@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 Numpyfirstname.lastname@example.org http://projects.scipy.org/mailman/listinfo/numpy-discussion