On 20. okt. 2010 21:20, Johan Hake wrote: > On Wednesday October 20 2010 10:39:11 Marie Rognes wrote: > >> A while back (in connection with the blueprint >> https://blueprints.launchpad.net/dolfin/+spec/solver-interfaces) there >> was a discussion regarding the interface to VariationalProblem. Anders >> and Marie have discussed this a bit further, in particular with regard >> to the adaptive solution of variational problems, and suggest the >> interface outlined below. (This suggestion involves a change in the >> interface, and hence the double post to both the dolfin and >> fenics-mailinglists) >> > I guess this discussion comes on top of the previous one? Because that > blueprint mentioned a lot more than what is mentioned here. > >
Yes. > I also assume this is limited to the Python interface as doing stuff like > derivative behind the scene is limited to PyDOLFIN? > > Yes and no. Using derivative is limited to Python (for now...). However, the suggested change allows a clean common interface for c++ and Python, incorporating the desired implicit derivative for Python users. >> >From Marie's perspective, the main reasons for changing the interface are >> >> (a) The current "nonlinear=true" variable seems superfluous and >> suboptimal >> (b) We should allow for automated computation of the Jacobian (when >> needed). >> >> For (nonlinear) variational problems, the interface should read >> >> pde = VariationalProblem(Form F, Form jacobian=None, ...) >> pde.solve(u) >> >> where "F" is a Form of rank 1, "jacobian" is a Form of rank 2, and "u" >> is a Function. Such a pde will be treated as a nonlinear variational >> problem. The "jacobian" would be an optional argument. If not given, >> >> jacobian = derivative(F, u) >> >> will be used for the nonlinear solve if needed (for instance as the >> left-hand side of the Newton iteration). >> >> Additionally, we have the interface for linear problems (as before) >> >> pde = VariationalProblem(Form a, Form L, ...) >> pde.solve(u) / u = pde.solve() >> >> where "a" is a Form of rank 2 and "L" is a form of rank 1. Such as pde >> will be treated as a linear variational problem. >> > Some wild thoughts... > > Couldn't we just lump a and L into one form F, and let VariationalProblem > then > figure out what kindoff problem the user would like to solve? Basically > VariationalProblem then solve F=0. > > Differentiate F if the form is of rank 1, (or take an optional Jacobian), or > split it into a linear problem using lhs and rhs? > > This is possible in the Python interface with the model suggested above. (Just implies adding a bit more intelligence than indicated) However, for the sake of the c++ interface (and many application codes), not removing the (a, L) option seems like a good idea to me. >> Philosophical question: Should u be given as an argument to the >> VariationalProblem instead of to the call to solve? >> > It is more natural to give u to solve, as that is what you solve for. Then > you > can differentiate wrt to u in the solve function. However, it makes it more > difficult to make u an optional argument to solve. > > I'm rather flexible at this point. Note that u is only an optional argument if the problem is linear, right. For my purposes, no differentiation is needed in such cases (and hence u can be created and not given). -- Marie _______________________________________________ Mailing list: https://launchpad.net/~dolfin Post to : [email protected] Unsubscribe : https://launchpad.net/~dolfin More help : https://help.launchpad.net/ListHelp
