Re: IVP for Parabolic-Elliptic 1D Queries

[c.]

On 7 Mar 2014, at 15:38, prao <address@hidden> wrote:

> fgnievinski wrote
>> Any insight from how Scilab, Freemat, Julia, SciPy, or R handle this?
>> -F.
> 
> Hi Felipe,
> 
> Thanks for the reply. Different packages have different ways to handle it,
> and the methods have their own pros and cons. I compiled a list of some of
> the packages including the ones you suggested:
> 
> 1. R 
> Uses finite difference (mainly a combination of Runge-Kutta and multistep
> methods like BDF and Adams)
> 
> 2. Netlib 
> It has subroutines employing different methods
> -PDECOL (B-splines collocation)
> -EPDCOL (B- splines)
> -PDEONE ( finite difference)
> -PDECHEB (C0 collocation)
> 
> 3. Julia
> It doesn't have a PDE solver but it does have an ODE solver that interfaces
> with Sundials(finite difference, multi step methods)
> 
> 4. DUNE
> It has a bunch of solvers. Apparently their hybrid Galerkin has very good
> performance.
> 
> 5. SciPy doesn't have a PDE solver but FiPy(finite volume) and StePy(finite
> element) do.
> 
> 6. Freemat
> Couldn't find anything related to pde solvers
> 
> I am leaning towards finite difference methods using Runge-Kutta type
> methods. My preference is based on my familiarity and relative use of their
> implementation and their high performance. I am doing some more paper
> reading to figure out exactly what RK methods would be appropriate.
> 
> Does anyone have any ideas, comments or suggestions? Thanks!
> 

Octave is missing in this list.
Do you know what are currently the options for solving PDEs available in Octave?

> Best,
> Pooja

c.