> o Will make your suggested mods and try them on the demos and then our model. > Thanks very much, James, for the insight into FiPy's innards. > > Regards, > +jtg+
Also, on another quick note: the modifications for eliminating preconditioners and matching residual norms that I've detailed are kind of hacky as they have you modifying internal FiPy code. With Trilinos, you can currently instantiate a solver from the top level with the parameter ``precon=None'' passed to disable the preconditioner. However, when I began working on this problem, doing the same thing using PySparse yielded no change, as the preconditioner was hardwired in for PySparse solvers. That's why I had you modifying source directly. In light of all this, I've written up a quick patch that'll let you specify one (or None) of two preconditioners (JacobiPreconditioner() or SsorPreconditioner()) for PySparse solvers. Selection works in exactly the same way that it does for Trilinos; simply pass in ``precon=Foo'' when you instantiate a PySparse solver. These changes will be committed to branch momentarily. NB: You are still going to need to modify internal FiPy code to match the residual norms. James
