On Sat, May 5, 2012 at 12:55 PM, Charles R Harris <charlesr.har...@gmail.com> wrote: > > > On Sat, May 5, 2012 at 5:27 AM, Tom Aldcroft <aldcr...@head.cfa.harvard.edu> > wrote: >> >> On Fri, May 4, 2012 at 11:44 PM, Ilan Schnell <ischn...@enthought.com> >> wrote: >> > Hi Chuck, >> > >> > thanks for the prompt reply. I as curious because because >> > someone was interested in adding http://pypi.python.org/pypi/Quaternion >> > to EPD, but Martin and Mark's implementation of quaternions >> > looks much better. >> >> Hi - >> >> I'm a co-author of the above mentioned Quaternion package. I agree >> the numpy_quaternion version would be better, but if there is no >> expectation that it will move forward I can offer to improve our >> Quaternion. A few months ago I played around with making it accept >> arbitrary array inputs (with similar shape of course) to essentially >> vectorize the transformations. We never got around to putting this in >> a release because of a perceived lack of interest / priorities... If >> this would be useful then let me know. >> > > Would you be interested in carrying Martin's package forward? I'm not > opposed to having quaternions in numpy/scipy but there needs to be someone > to push it and deal with problems if they come up. Martin's package > disappeared in large part because Martin disappeared. I'd also like to hear > from Mark about other aspects, as there was also a simple rational user type > proposed that we were looking to put in as an extension 'test' type. IIRC, > there were some needed fixes to Numpy, some of which were postponed in favor > of larger changes. User types is one of the things we want ot get fixed up.
It would be great to have a quaternion dtype available in numpy, so I would be interested in carrying this package if nobody else steps forward. I don't have any experience with numpy internals, but it looks like most the heavy lifting is done already. On a related note the AstroPy project has been discussing a time class suitable for astronomy (with different conversions, time systems, an option to use 128-bit precision, etc). We have recently talked about a numpy dtype analogous to datetime64. This might be an opportunity to understand a bit the mechanics of making a new dtype. Cheers, Tom > 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