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[Anders Logg <question149919@xxxxxxxxxxxxxxxxxxxxx>]

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

Anders Logg proposed the following answer:
On Wed, Mar 23, 2011 at 02:24:45PM -0700, Johan Hake wrote:
> On Wednesday March 23 2011 14:20:16 Kent-Andre Mardal wrote:
> > The SWIG wizard!
>
> Well... copy/paste mostly :)

But you copy/paste from your own magic SWIG code which still qualifies
and magic. :-)

--
Anders


> Johan
>
> > 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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>
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