On Fri, Nov 22, 2013 at 03:34:45PM +0100, Corrado Maurini wrote:
>
>
> Le 22 nov. 2013 à 10:25, Anders Logg <[email protected]> a écrit :
> >
> >
> >> However, the issue is larger than that.
> >> Many other parameters are not passed, although existing in snes and
> >> newton_solver.
> >>
> >> For example it is not possible to set the tolerance or the max iterations
> >> of the krylov_solver used in the newton or snes iterations, which is very
> >> bad in my opinion.
> >> I proposed a (ugly) fix some time ago which was declined (
> >> https://bitbucket.org/fenics-project/dolfin/pull-request/34/updating-of-ksp-parameters-in/diff
> >> ).
> >> However I think that something must be done, because many parameters are
> >> shown and modifiable, but they are not taken into account.
> >
> > Are you sure? These lines from NewtonSolver.cpp should take care of that:
> >
> > // Set parameters for linear solver
> > if (solver_type == "direct" || solver_type == "lu")
> > _solver->update_parameters(parameters("lu_solver"));
> > else if (solver_type == "iterative")
> > _solver->update_parameters(parameters("krylov_solver"));
> > else
> > warning("Unable to set parameters for linear solver type \"%s\".",
> > solver_type.c_str());
> >
> As a matter of fact when you try to set the options of the krylov solver they
> do not work.
> Please, check with the example of demo_hyperelasticity reported in the
> previous message.
> For example with par_new.krylov_solver["monitor_convergence"] = True one
> expects the output of the krylov solver iterations.
>
> I agree that the lines you cite are supposed to do the
> work. However, in practice, it is not evident to track what
> _solver->update_parameters(parameters("krylov_solver")) does:
> _solver is a GenericLinearSolver and there are several wrapping
> before arriving to KrylovSolver. I suspect that there is a problem
> in one of those passages.
Yes, something happens with the parameters. They don't seem to
propagate all the way down. I'll try to find the problem.
--
Anders
> >
> >> To test on newton_solver, consider the following modify version of
> >> demo_hyperelasticity, where par_new.krylov_solver are ignored:
> >>
> >> from dolfin import *
> >>
> >> # Optimization options for the form compiler
> >> parameters["form_compiler"]["cpp_optimize"] = True
> >> ffc_options = {"optimize": True, \
> >> "eliminate_zeros": True, \
> >> "precompute_basis_const": True, \
> >> "precompute_ip_const": True}
> >>
> >> # Create mesh and define function space
> >> mesh = UnitCubeMesh(24, 16, 16)
> >> V = VectorFunctionSpace(mesh, "Lagrange", 1)
> >>
> >> # Mark boundary subdomians
> >> left = CompiledSubDomain("near(x[0], side) && on_boundary", side = 0.0)
> >> right = CompiledSubDomain("near(x[0], side) && on_boundary", side = 1.0)
> >>
> >> # Define Dirichlet boundary (x = 0 or x = 1)
> >> c = Expression(("0.0", "0.0", "0.0"))
> >> r = Expression(("scale*0.0",
> >> "scale*(y0 + (x[1] - y0)*cos(theta) - (x[2] -
> >> z0)*sin(theta) - x[1])",
> >> "scale*(z0 + (x[1] - y0)*sin(theta) + (x[2] -
> >> z0)*cos(theta) - x[2])"),
> >> scale = 0.5, y0 = 0.5, z0 = 0.5, theta = pi/3)
> >>
> >> bcl = DirichletBC(V, c, left)
> >> bcr = DirichletBC(V, r, right)
> >> bcs = [bcl, bcr]
> >>
> >> # Define functions
> >> du = TrialFunction(V) # Incremental displacement
> >> v = TestFunction(V) # Test function
> >> u = Function(V) # Displacement from previous iteration
> >> B = Constant((0.0, -0.5, 0.0)) # Body force per unit volume
> >> T = Constant((0.1, 0.0, 0.0)) # Traction force on the boundary
> >>
> >> # Kinematics
> >> I = Identity(V.cell().d) # Identity tensor
> >> F = I + grad(u) # Deformation gradient
> >> C = F.T*F # Right Cauchy-Green tensor
> >>
> >> # Invariants of deformation tensors
> >> Ic = tr(C)
> >> J = det(F)
> >>
> >> # Elasticity parameters
> >> E, nu = 10.0, 0.3
> >> mu, lmbda = Constant(E/(2*(1 + nu))), Constant(E*nu/((1 + nu)*(1 - 2*nu)))
> >>
> >> # Stored strain energy density (compressible neo-Hookean model)
> >> psi = (mu/2)*(Ic - 3) - mu*ln(J) + (lmbda/2)*(ln(J))**2
> >>
> >> # Total potential energy
> >> Pi = psi*dx - dot(B, u)*dx - dot(T, u)*ds
> >>
> >> # Compute first variation of Pi (directional derivative about u in the
> >> direction of v)
> >> F = derivative(Pi, u, v)
> >>
> >> # Compute Jacobian of F
> >> J = derivative(F, u, du)
> >>
> >> # Solve variational problem
> >> problem =
> >> NonlinearVariationalProblem(F,u,bcs,J,form_compiler_parameters=ffc_options)
> >> solver = NonlinearVariationalSolver(problem)
> >> par_new = solver.parameters.newton_solver
> >> par_new.linear_solver = "gmres"
> >> par_new.preconditioner = "amg"
> >> par_new.krylov_solver["report"] = True
> >> par_new.krylov_solver["monitor_convergence"] = True
> >> par_new.krylov_solver["maximum_iterations"] = 5
> >> info(par_new, True)
> >> solver.solve()
> >>
> >>
> >>
> >>
> >>
> >> Corrado Maurini
> >> [email protected]
> >>
> >>
> >>
> >> _______________________________________________
> >> fenics mailing list
> >> [email protected]
> >> http://fenicsproject.org/mailman/listinfo/fenics
>
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