Hi Hans, Sorry, that is actually what I implemented, I just documented it iincorrectly. I have just pushed an update to the README. Thanks for pointing this out!
Martin On Sun, Jul 31, 2011 at 07:57:58AM +0200, Hans Meine wrote: > > Hi Martin, > > I think it would be more useful if isfinite returned true if *all* elements > were finite. (Opposite of isnan and isinf.) > > HTH, > Hans > > PS: did not check the complex dtype, hopefully that one's no different. > > (The above has been typed using a small on-screen keyboard, which may account > for any typos, briefness or bad formatting.) > > Am 16.07.2011 um 16:50 schrieb Martin Ling <martin-nu...@earth.li>: > > > Hi all, > > > > I have just pushed a package to GitHub which adds a quaternion dtype to > > NumPy: https://github.com/martinling/numpy_quaternion > > > > Some backstory: on Wednesday I gave a talk at SciPy 2011 about an > > inertial sensing simulation package I have been working on > > (http://www.imusim.org/). One component I suggested might be reusable > > from that code was the quaternion math implementation, written in > > Cython. One of its features is a wrapper class for Nx4 NumPy arrays that > > supports efficient operations using arrays of quaternion values. > > > > Travis Oliphant suggested that a quaternion dtype would be a better > > solution, and got me talking to Mark Weibe about this. With Mark's help > > I completed this initial version at yesterday's sprint session. > > > > Incidentally, how to do something like this isn't well documented and I > > would have had little hope without both Mark's in-person help and his > > previous code (for adding a half-precision float dtype) to refer to. I > > don't know what the consensus is about whether people writing custom > > dtypes is a desirable thing, but if it is then the process needs to be > > made a lot easier. That said, the fact this is doable without patching > > the numpy core at all is really, really nice. > > > > Example usage: > > > >>>> import numpy as np > >>>> import quaternion > >>>> np.quaternion(1,0,0,0) > > quaternion(1, 0, 0, 0) > >>>> q1 = np.quaternion(1,2,3,4) > >>>> q2 = np.quaternion(5,6,7,8) > >>>> q1 * q2 > > quaternion(-60, 12, 30, 24) > >>>> a = np.array([q1, q2]) > >>>> a > > array([quaternion(1, 2, 3, 4), quaternion(5, 6, 7, 8)], > > dtype=quaternion) > >>>> exp(a) > > array([quaternion(1.69392, -0.78956, -1.18434, -1.57912), > > quaternion(138.909, -25.6861, -29.9671, -34.2481)], > > dtype=quaternion) > > > > The following ufuncs are implemented: > > add, subtract, multiply, divide, log, exp, power, negative, conjugate, > > copysign, equal, not_equal, less, less_equal, isnan, isinf, isfinite, > > absolute > > > > Quaternion components are stored as doubles. The package could be extended > > to support e.g. qfloat, qdouble, qlongdouble > > > > Comparison operations follow the same lexicographic ordering as tuples. > > > > The unary tests isnan, isinf and isfinite return true if they would > > return true for any individual component. > > > > Real types may be cast to quaternions, giving quaternions with zero for > > all three imaginary components. Complex types may also be cast to > > quaternions, with their single imaginary component becoming the first > > imaginary component of the quaternion. Quaternions may not be cast to > > real or complex types. > > > > Comments very welcome. This is my first attempt at NumPy hacking :-) > > > > > > Martin > > _______________________________________________ > > 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
