No problem. I figured it out somehow. I worked out an example and posted
that in my proposal too.
Also, this is the only proposal that I submitted to Google.


On Apr 4, 2017 2:44 AM, "Ondřej Čertík" <[email protected]> wrote:

> Arif, Vedarth,
>
> Please make sure you submit your proposal. Try to do your best
> regarding the example, I am busy today at work, my apologies for that.
> I'll try to find time in the next few days to work it out (or ask
> prof. Sukumar or his student), unless you can figure it out in the
> meantime.
>
> Ondrej
>
> On Sun, Apr 2, 2017 at 5:30 PM, Arif Ahmed
> <[email protected]> wrote:
> > I have written a proposal as well. Can you please take the time to
> review it
> > ? :
> > https://docs.google.com/document/d/1pIH-HXoAesl34_
> Qs41Mfmwxa8-2ExYvhVHh9bfS4ijQ/edit
> >
> > Also , is it necessary to add this content to the SymPy wiki ?
> >
> >
> > On Thursday, March 30, 2017 at 3:56:11 AM UTC+5:30, Ondřej Čertík wrote:
> >>
> >> Hi,
> >>
> >> Here is another GSoC idea from my collaborator at UC Davis, prof.
> >> Sukumar [1]. His student Eric Chin gave me his permission to post the
> >> project here, see the attached project description and his poster with
> >> more details.
> >>
> >> The general idea is to implement a module in SymPy to help integrate
> >> homogeneous functions over arbitrary 2D and 3D polytopes (triangles,
> >> quads, polygons, hexahedra, and more complicated 3D elements). The
> >> applications are in extended finite elements which requires an
> >> efficient quadrature of a 3D function over the finite element (say a
> >> hexahedron). Other applications are computer graphics (ridid body
> >> simulations of solids) and to devise cubature rules on arbitrary
> >> polytopes.
> >>
> >> See the references in the attached document. They use the Stokes
> >> theorem and Euler theorem to transform the 3D integral (which
> >> otherwise would require a 3D quadrature --- very expensive) to
> >> integral over faces and eventually edges, and so it becomes much
> >> faster. Features needed from SymPy:
> >>
> >> * exact handling of integers and rationals
> >> * symbolic representation of homogeneous functions
> >> * symbolic derivatives
> >> * numerical evaluation
> >>
> >> At first it sounds technical, but this would be extremely useful even
> >> for my own work. The spirit is roughly in line of this module that I
> >> started and others finished:
> >>
> >>
> >> https://github.com/sympy/sympy/blob/8800fd2ab1553cd768ad743c44b3ed
> 00c111c368/sympy/integrals/quadrature.py
> >>
> >> The ultimate application of this sympy.integrals.quadrature module are
> >> double precision floating point numbers in Fortran, C or C++ programs,
> >> however the reason it's in SymPy is that one can use SymPy to get
> >> guaranteed accuracy to arbitrary precision. In principle
> >> sympy.integrals.quadrature could also be implemented using libraries
> >> like Arb (https://github.com/fredrik-johansson/arb), but Arb didn't
> >> exist when I wrote quadrature.py, and the code of quadrature.py is
> >> very simple, using regular SymPy, so there is still value in having
> >> it.
> >>
> >> The module proposed by this project would require symbolic features
> >> from SymPy as well, such as the symbolic derivatives, as well as the
> >> ability for the user to input the expression to integrate
> >> symbolically.
> >>
> >> The above project could also lead to a publication if there is interest.
> >>
> >> If there are any interested students, please let me know. I can mentor
> >> as well as help with the proposal.
> >>
> >> Ondrej
> >>
> >> [1] http://dilbert.engr.ucdavis.edu/~suku/
> >
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