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[Kent-Andre Mardal <question149919@xxxxxxxxxxxxxxxxxxxxx>]

Question #149919 on DOLFIN changed:
https://answers.launchpad.net/dolfin/+question/149919

Kent-Andre Mardal proposed the following answer:
The SWIG wizard!

Kent

On 23 March 2011 22:01, Johan Hake <johan.hake@xxxxxxxxx> wrote:

> This should be fixed now.
>
> Johan
>
> On Monday March 21 2011 10:12:52 Christian Clason wrote:
> > New question #149919 on DOLFIN:
> > https://answers.launchpad.net/dolfin/+question/149919
> >
> > I am trying to solve a nonlinear pde-constrained optimization problem
> with
> > a reduced Newton method, where instead of constructing the full Hessian,
> I
> > compute the action of the Hessian on a function for use in a Krylov
> solver
> > such as CG.
> >
> > I assume that this can be done by constructing a PETScKrylovMatrix and
> > defining a suitable mult function. (If there is a more high-level way of
> > doing this, I'd be grateful for a hint.) However, I'm a bit stumped by
> the
> > interface between PETSc and Dolfin here. The core step in the matrix
> > multiplication would be something like
> >
> > def mult(self, *args) :
> >     du = Function(V,args[0])
> >     L = du*v*dx
> >     problem = VariationalProblem(a, L, bc)
> >     y = problem.solve()
> >     args[1] = y.vector()
> >
> > (assume that the function space V, test function v, boundary conditions
> bc
> > and bilinear form a have all been defined previously). This however
> > doesn't work, since args[0] and args[1] are not of proper type. How do I
> > need to massage args[0] and args[1] to make this work? Any hints would be
> > appreciated, especially a template for the use of PETScKrylovMatrix in
> > Python.
> >
> > (If I can get this working, I'd be happy to turn this into a documented
> > demo. I'm sure there are more people interested in using FEniCS as a
> > framework for pde-constrained optimization.)
>
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