[SciPy-dev] Generic polynomials class (was Re: Volunteer for Scipy Project)
Charles R Harris
Thu Oct 15 20:36:32 CDT 2009
On Thu, Oct 15, 2009 at 4:35 PM, Fernando Perez <email@example.com>wrote:
> Hi all,
> On Wed, Oct 14, 2009 at 8:08 AM, Charles R Harris
> <firstname.lastname@example.org> wrote:
> > One reason for the low level functions is that they are short and can be
> > easily converted to cython functions or be library functions written in
> > fortran or whatever. The z series could be done that way, but at the
> > level they could probably be dispensed with and the underlying Cheybyshev
> > series used instead, that's one reason they are private functions. What
> > brought to the python case was some vectorization of the algorithms.
> > way to look at them is as symbolic Fourier transforms.
> I don't know if this will genuinely add anything to this (very
> interesting discussion), but Ariel, Mike and I thought a lot about
> fairly similar problems in the nitime package, and went for an
> approach with:
> - a purely functional library (even if the functions end up having
> long signatures and don't cache things they could),
> - very simple data cointainers whose design evolves very conservatively
> - analysis objects that expose a nice, high-level interface and manage
> the containers and library functions. These are what users should use
> 90% of the time, but if we get their design wrong, little is lost
> because most of the complexities are in the functional library.
How did you build the analysis objects? Part of what we have been discussing
it the easiest way to expose a consistent interface while reusing the
maximum amount of code.
And thanks for the links.
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