On 13 Mar 2014, at 15:17, Ondřej Čertík wrote:
It's really up to us how we design CSymPy. But I would try to reuse as
much
as we can from other libraries where it makes sense rather than
reimplementing stuff ourselves. So in particular, I would use Flint,
Eigen,
Armadillo etc., as those are well tested libraries with wide usage.
The problem I see with this approach is that there could be a lot of
conversions between the different types used in the specific libraries.
Plus, there's the situations like with linear algebra. There's numeric
linear algebra libraries, but they're useless for symbolic linear
algebra. For numeric linear algebra, why don't we just defer to NumPy,
as that's their area of expertise?
I had the library conversion problem in trying to implement my Master's
thesis in C++ as the linear algebra libraries and the ODE solvers all
used different vector/matrix types. I gave up and went to Fortran.
If we're going to use additional libraries, we should make a careful
decisions as to when to use them. Otherwise, I can see CSymPy becoming
Sage.
Cheers,
Tim.
---
Tim Lahey, Ph.D.
Post-Doctoral Fellow
Systems Design Engineering
University of Waterloo
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