[Numpy-discussion] Quaternion data type

Tom Aldcroft aldcroft at head.cfa.harvard.edu
Sat May 5 21:15:34 EDT 2012


On Sat, May 5, 2012 at 12:55 PM, Charles R Harris
<charlesr.harris at gmail.com> wrote:
>
>
> On Sat, May 5, 2012 at 5:27 AM, Tom Aldcroft <aldcroft at head.cfa.harvard.edu>
> wrote:
>>
>> On Fri, May 4, 2012 at 11:44 PM, Ilan Schnell <ischnell at 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 at scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>



More information about the NumPy-Discussion mailing list