public void Init(MultigridOperator op)
{
var Mtx = op.OperatorMatrix;
var MgMap = op.Mapping;
this.m_mgop = op;
if (!Mtx.RowPartitioning.EqualsPartition(MgMap.Partitioning))
{
throw new ArgumentException("Row partitioning mismatch.");
}
if (!Mtx.ColPartition.EqualsPartition(MgMap.Partitioning))
{
throw new ArgumentException("Column partitioning mismatch.");
}
this.Matrix = Mtx;
if (Precond != null)
{
Precond.Init(op);
}
}
public override void SolverDriver <S>(CoordinateVector SolutionVec, S RHS)
{
using (var tr = new FuncTrace()) {
m_SolutionVec = SolutionVec;
int itc;
itc = 0;
double[] x, xt, xOld, f0, deltaX, ft;
double rat;
double alpha = 1E-4, sigma0 = 0.1, sigma1 = 0.5, maxarm = 20, gamma = 0.9;
// Eval_F0
base.Init(SolutionVec, RHS, out x, out f0);
Console.WriteLine("Residual base.init: " + f0.L2NormPow2().MPISum().Sqrt());
deltaX = new double[x.Length];
xt = new double[x.Length];
ft = new double[x.Length];
this.CurrentLin.TransformSolFrom(SolutionVec, x);
base.EvalResidual(x, ref f0);
// fnorm
double fnorm = f0.L2NormPow2().MPISum().Sqrt();
double fNormo = 1;
double errstep;
double[] step = new double[x.Length];
double[] stepOld = new double[x.Length];
MsrMatrix CurrentJac;
Console.WriteLine("Start residuum for nonlinear iteration: " + fnorm);
OnIterationCallback(itc, x.CloneAs(), f0.CloneAs(), this.CurrentLin);
while (fnorm > ConvCrit && itc < MaxIter)
{
rat = fnorm / fNormo;
fNormo = fnorm;
itc++;
// How should the inverse of the Jacobian be approximated?
if (ApproxJac == ApproxInvJacobianOptions.GMRES)
{
CurrentJac = new MsrMatrix(x.Length);
if (Precond != null)
{
Precond.Init(CurrentLin);
}
step = Krylov(SolutionVec, x, f0, out errstep);
}
else if (ApproxJac == ApproxInvJacobianOptions.DirectSolver)
{
CurrentJac = diffjac(SolutionVec, x, f0);
var solver = new ilPSP.LinSolvers.MUMPS.MUMPSSolver();
solver.DefineMatrix(CurrentJac);
step.ClearEntries();
solver.Solve(step, f0);
}
else
{
throw new NotImplementedException("Your approximation option for the jacobian seems not to be existent.");
}
// Start line search
xOld = x;
double lambda = 1;
double lamm = 1;
double lamc = lambda;
double iarm = 0;
xt = x.CloneAs();
xt.AccV(lambda, step);
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
var nft = ft.L2NormPow2().MPISum().Sqrt(); var nf0 = f0.L2NormPow2().MPISum().Sqrt(); var ff0 = nf0 * nf0; var ffc = nft * nft; var ffm = nft * nft;
// Control of the the step size
while (nft >= (1 - alpha * lambda) * nf0 && iarm < maxStep)
{
// Line search starts here
if (iarm == 0)
{
lambda = sigma1 * lambda;
}
else
{
lambda = parab3p(lamc, lamm, ff0, ffc, ffm);
}
// Update x;
xt = x.CloneAs();
xt.AccV(lambda, step);
lamm = lamc;
lamc = lambda;
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
nft = ft.L2NormPow2().MPISum().Sqrt();
ffm = ffc;
ffc = nft * nft;
iarm++;
#if DEBUG
Console.WriteLine("Step size: " + lambda + "with Residuum: " + nft);
#endif
}
// transform solution back to 'original domain'
// to perform the linearization at the new point...
// (and for Level-Set-Updates ...)
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
// update linearization
base.Update(SolutionVec.Mapping.Fields, ref xt);
// residual evaluation & callback
base.EvalResidual(xt, ref ft);
// EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
//base.Init(SolutionVec, RHS, out x, out f0);
fnorm = ft.L2NormPow2().MPISum().Sqrt();
x = xt;
f0 = ft.CloneAs();
OnIterationCallback(itc, x.CloneAs(), f0.CloneAs(), this.CurrentLin);
}
SolutionVec = m_SolutionVec;
}
}
//bool solveVelocity = true;
//double VelocitySolver_ConvergenceCriterion = 1e-5;
//double StressSolver_ConvergenceCriterion = 1e-5;
public override void SolverDriver <S>(CoordinateVector SolutionVec, S RHS)
{
using (var tr = new FuncTrace()) {
m_SolutionVec = SolutionVec;
int itc;
itc = 0;
double[] x, xt, xOld, f0, deltaX, ft;
double rat;
double alpha = 1E-4;
//double sigma0 = 0.1;
double sigma1 = 0.5;
//double maxarm = 20;
//double gamma = 0.9;
// Eval_F0
using (new BlockTrace("Slv Init", tr)) {
base.Init(SolutionVec, RHS, out x, out f0);
};
//Console.WriteLine("Residual base.init: " + f0.L2NormPow2().MPISum().Sqrt());
deltaX = new double[x.Length];
xt = new double[x.Length];
ft = new double[x.Length];
this.CurrentLin.TransformSolFrom(SolutionVec, x);
EvaluateOperator(1, SolutionVec.Mapping.ToArray(), f0);
Console.WriteLine("Residual base.init: " + f0.L2NormPow2().MPISum().Sqrt());
//base.EvalResidual(x, ref f0);
// fnorm
double fnorm = f0.L2NormPow2().MPISum().Sqrt();
double fNormo = 1;
double errstep;
double[] step = new double[x.Length];
double[] stepOld = new double[x.Length];
//BlockMsrMatrix CurrentJac;
OnIterationCallback(itc, x.CloneAs(), f0.CloneAs(), this.CurrentLin);
using (new BlockTrace("Slv Iter", tr)) {
while ((fnorm > ConvCrit * fNormo * 0 + ConvCrit && itc < MaxIter) || itc < MinIter)
{
rat = fnorm / fNormo;
fNormo = fnorm;
itc++;
// How should the inverse of the Jacobian be approximated?
if (ApproxJac == ApproxInvJacobianOptions.GMRES)
{
if (Precond != null)
{
Precond.Init(CurrentLin);
}
//base.EvalResidual(x, ref f0);
f0.ScaleV(-1.0);
step = Krylov(SolutionVec, x, f0, out errstep);
}
else if (ApproxJac == ApproxInvJacobianOptions.DirectSolver)
{
/*
* double[] _step = step.ToArray();
* double[] _f0 = f0.ToArray();
* double _check_norm;
* {
* var CurrentJac = CurrentLin.OperatorMatrix;
* var _solver = new ilPSP.LinSolvers.PARDISO.PARDISOSolver(); // .MUMPS.MUMPSSolver();
* _solver.DefineMatrix(CurrentJac);
* _step.ClearEntries();
* var _check = _f0.CloneAs();
* _f0.ScaleV(-1.0);
* _solver.Solve(_step, _f0);
*
* CurrentLin.OperatorMatrix.SpMV(-1.0, _step, -1.0, _check);
* _check_norm = _check.L2Norm();
* }
*/
var solver = linsolver;
//var mgo = new MultigridOperator(m_AggBasisSeq, SolutionVec.Mapping, CurrentJac, null, m_MultigridOperatorConfig);
solver.Init(CurrentLin);
step.ClearEntries();
var check = f0.CloneAs();
f0.ScaleV(-1.0);
solver.ResetStat();
solver.Solve(step, f0);
/*
* double check_norm;
* {
* CurrentLin.OperatorMatrix.SpMV(-1.0, step, -1.0, check);
* check_norm = check.L2Norm();
* }
*
*
* double dist = GenericBlas.L2Dist(step, _step);
*
*
* Console.WriteLine(" conv: " + solver.Converged + " /iter = " + solver.ThisLevelIterations + " /dist = " + dist + " /resNrm = " + check_norm + " /parresNrm = " + _check_norm);
*/
//step.SetV(step);
//if (solver.Converged == false)
// Debugger.Launch();
}
else
{
throw new NotImplementedException("Your approximation option for the jacobian seems not to be existent.");
}
// Start line search
xOld = x;
double lambda = 1;
double lamm = 1;
double lamc = lambda;
double iarm = 0;
xt = x.CloneAs();
xt.AccV(lambda, step);
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
double nft = ft.L2NormPow2().MPISum().Sqrt();
double nf0 = f0.L2NormPow2().MPISum().Sqrt();
double ff0 = nf0 * nf0;
double ffc = nft * nft;
double ffm = nft * nft;
// Console.WriteLine(" Residuum 0:" + nf0);
// Control of the the step size
while (nft >= (1 - alpha * lambda) * nf0 && iarm < maxStep)
{
// Line search starts here
if (iarm == 0)
{
lambda = sigma1 * lambda;
}
else
{
lambda = parab3p(lamc, lamm, ff0, ffc, ffm);
}
// Update x;
xt = x.CloneAs();
xt.AccV(lambda, step);
lamm = lamc;
lamc = lambda;
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
nft = ft.L2NormPow2().MPISum().Sqrt();
ffm = ffc;
ffc = nft * nft;
iarm++;
#if DEBUG
Console.WriteLine(" Residuum: " + nft + " lambda = " + lambda);
#endif
}
// transform solution back to 'original domain'
// to perform the linearization at the new point...
// (and for Level-Set-Updates ...)
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
// update linearization
if (itc % constant_newton_it == 0)
{
base.Update(SolutionVec.Mapping.Fields, ref xt);
if (constant_newton_it != 1)
{
Console.WriteLine("Jacobian is updated: it {0}", itc);
}
}
// residual evaluation & callback
base.EvalResidual(xt, ref ft);
EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
fnorm = ft.L2NormPow2().MPISum().Sqrt();
x = xt;
f0 = ft.CloneAs();
OnIterationCallback(itc, x.CloneAs(), f0.CloneAs(), this.CurrentLin);
}
}
SolutionVec = m_SolutionVec;
}
}
public override void SolverDriver <S>(CoordinateVector SolutionVec, S RHS)
{
using (var tr = new FuncTrace()) {
m_SolutionVec = SolutionVec;
int itc;
itc = 0;
double[] x, xt, xOld, f0, deltaX, ft;
double rat;
double alpha = 1E-4, sigma0 = 0.1, sigma1 = 0.5, maxarm = 20, gamma = 0.9;
// Eval_F0
using (new BlockTrace("Slv Init", tr)) {
base.Init(SolutionVec, RHS, out x, out f0);
};
Console.WriteLine("Residual base.init: " + f0.L2NormPow2().MPISum().Sqrt());
deltaX = new double[x.Length];
xt = new double[x.Length];
ft = new double[x.Length];
this.CurrentLin.TransformSolFrom(SolutionVec, x);
base.EvalResidual(x, ref f0);
// fnorm
double fnorm = f0.L2NormPow2().MPISum().Sqrt();
double fNormo = 1;
double errstep;
double[] step = new double[x.Length];
double[] stepOld = new double[x.Length];
MsrMatrix CurrentJac;
Console.WriteLine("Start residuum for nonlinear iteration: " + fnorm);
OnIterationCallback(itc, x.CloneAs(), f0.CloneAs(), this.CurrentLin);
//int[] Velocity_idx = SolutionVec.Mapping.GetSubvectorIndices(false, 0, 1, 2);
//int[] Stresses_idx = SolutionVec.Mapping.GetSubvectorIndices(false, 3, 4, 5);
//int[] Velocity_fields = new int[] { 0, 1, 2 };
//int[] Stress_fields = new int[] { 3, 4, 5 };
//int NoCoupledIterations = 1;
using (new BlockTrace("Slv Iter", tr)) {
while (fnorm > ConvCrit && itc < MaxIter)
{
rat = fnorm / fNormo;
fNormo = fnorm;
itc++;
// How should the inverse of the Jacobian be approximated?
if (ApproxJac == ApproxInvJacobianOptions.GMRES)
{
CurrentJac = new MsrMatrix(x.Length);
if (Precond != null)
{
Precond.Init(CurrentLin);
}
step = Krylov(SolutionVec, x, f0, out errstep);
}
else if (ApproxJac == ApproxInvJacobianOptions.DirectSolver)
{
CurrentJac = diffjac(SolutionVec, x, f0);
CurrentJac.SaveToTextFileSparse("Jacobi");
CurrentLin.OperatorMatrix.SaveToTextFileSparse("OpMatrix");
var solver = new ilPSP.LinSolvers.MUMPS.MUMPSSolver();
solver.DefineMatrix(CurrentJac);
step.ClearEntries();
solver.Solve(step, f0);
}
else if (ApproxJac == ApproxInvJacobianOptions.DirectSolverHybrid)
{
//EXPERIMENTAL_____________________________________________________________________
MultidimensionalArray OpMatrixMatl = MultidimensionalArray.Create(x.Length, x.Length);
CurrentJac = diffjac(SolutionVec, x, f0);
//Console.WriteLine("Calling MATLAB/Octave...");
using (BatchmodeConnector bmc = new BatchmodeConnector())
{
bmc.PutSparseMatrix(CurrentJac, "Jacobi");
bmc.PutSparseMatrix(CurrentLin.OperatorMatrix, "OpMatrix");
bmc.Cmd("Jacobi(abs(Jacobi) < 10^-6)=0; dim = length(OpMatrix);");
bmc.Cmd("dim = length(OpMatrix);");
bmc.Cmd(@"for i=1:dim
if (i >= 16) && (i <= 33) && (i + 6 <= 33) && (i + 12 <= 33)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 49) && (i <= 66) && (i + 6 <= 66) && (i + 12 <= 66)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 82) && (i <= 99) && (i + 6 <= 99) && (i + 12 <= 99)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 115) && (i <= 132) && (i + 6 <= 132) && (i + 12 <= 132)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 148) && (i <= 165) && (i + 6 <= 165) && (i + 12 <= 165)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 181) && (i <= 198) && (i + 6 <= 198) && (i + 12 <= 198)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 214) && (i <= 231) && (i + 6 <= 231) && (i + 12 <= 231)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 247) && (i <= 264) && (i + 6 <= 264) && (i + 12 <= 264)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 280) && (i <= 297) && (i + 6 <= 297) && (i + 12 <= 297)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 313) && (i <= 330) && (i + 6 <= 330) && (i + 12 <= 330)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 346) && (i <= 363) && (i + 6 <= 363) && (i + 12 <= 363)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 379) && (i <= 396) && (i + 6 <= 396) && (i + 12 <= 396)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 412) && (i <= 429) && (i + 6 <= 429) && (i + 12 <= 429)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 445) && (i <= 462) && (i + 6 <= 462) && (i + 12 <= 462)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 478) && (i <= 495) && (i + 6 <= 495) && (i + 12 <= 495)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
if (i >= 511) && (i <= 528) && (i + 6 <= 528) && (i + 12 <= 528)
OpMatrix(i, i) = Jacobi(i, i);
OpMatrix(i, i + 6) = Jacobi(i, i + 6);
OpMatrix(i + 6, i) = Jacobi(i + 6, i);
OpMatrix(i + 12, i + 6) = Jacobi(i + 12, i + 6);
OpMatrix(i + 6, i + 12) = Jacobi(i + 6, i + 12);
end
end");
bmc.Cmd("OpMatrix = full(OpMatrix)");
bmc.GetMatrix(OpMatrixMatl, "OpMatrix");
bmc.Execute(false);
}
MsrMatrix OpMatrix = OpMatrixMatl.ToMsrMatrix();
var solver = new ilPSP.LinSolvers.MUMPS.MUMPSSolver();
//Console.WriteLine("USING HIGH EXPERIMENTAL OPMATRIX WITH JAC! only for p=1, GridLevel=2");
solver.DefineMatrix(OpMatrix);
//______________________________________________________________________________________________________
step.ClearEntries();
solver.Solve(step, f0);
}
else if (ApproxJac == ApproxInvJacobianOptions.DirectSolverOpMatrix)
{
CurrentJac = new MsrMatrix(x.Length);
CurrentJac = CurrentLin.OperatorMatrix.ToMsrMatrix();
var solver = new ilPSP.LinSolvers.MUMPS.MUMPSSolver();
solver.DefineMatrix(CurrentJac);
step.ClearEntries();
solver.Solve(step, f0);
}
else
{
throw new NotImplementedException("Your approximation option for the jacobian seems not to be existent.");
}
//if (itc > NoCoupledIterations)
//{
// if (solveVelocity)
// {
// Console.WriteLine("stress correction = 0");
// foreach (int idx in Stresses_idx)
// {
// step[idx] = 0.0;
// }
// }
// else
// {
// Console.WriteLine("velocity correction = 0");
// foreach (int idx in Velocity_idx)
// {
// step[idx] = 0.0;
// }
// }
//}
// Start line search
xOld = x;
double lambda = 1;
double lamm = 1;
double lamc = lambda;
double iarm = 0;
xt = x.CloneAs();
xt.AccV(lambda, step);
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
var nft = ft.L2NormPow2().MPISum().Sqrt(); var nf0 = f0.L2NormPow2().MPISum().Sqrt(); var ff0 = nf0 * nf0; var ffc = nft * nft; var ffm = nft * nft;
// Control of the the step size
while (nft >= (1 - alpha * lambda) * nf0 && iarm < maxStep)
{
// Line search starts here
if (iarm == 0)
{
lambda = sigma1 * lambda;
}
else
{
lambda = parab3p(lamc, lamm, ff0, ffc, ffm);
}
// Update x;
xt = x.CloneAs();
xt.AccV(lambda, step);
lamm = lamc;
lamc = lambda;
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
nft = ft.L2NormPow2().MPISum().Sqrt();
ffm = ffc;
ffc = nft * nft;
iarm++;
#if DEBUG
Console.WriteLine("Step size: " + lambda + "with Residuum: " + nft);
#endif
}
// transform solution back to 'original domain'
// to perform the linearization at the new point...
// (and for Level-Set-Updates ...)
this.CurrentLin.TransformSolFrom(SolutionVec, xt);
// update linearization
base.Update(SolutionVec.Mapping.Fields, ref xt);
// residual evaluation & callback
base.EvalResidual(xt, ref ft);
// EvaluateOperator(1, SolutionVec.Mapping.Fields, ft);
//base.Init(SolutionVec, RHS, out x, out f0);
fnorm = ft.L2NormPow2().MPISum().Sqrt();
x = xt;
f0 = ft.CloneAs();
//if (itc > NoCoupledIterations)
//{
// double coupledL2Res = 0.0;
// if (solveVelocity)
// {
// foreach (int idx in Velocity_idx)
// {
// coupledL2Res += f0[idx].Pow2();
// }
// }
// else
// {
// foreach (int idx in Stresses_idx)
// {
// coupledL2Res += f0[idx].Pow2();
// }
// }
// coupledL2Res = coupledL2Res.Sqrt();
// Console.WriteLine("coupled residual = {0}", coupledL2Res);
// if (solveVelocity && coupledL2Res < this.VelocitySolver_ConvergenceCriterion)
// {
// Console.WriteLine("SolveVelocity = false");
// this.solveVelocity = false;
// }
// else if (!solveVelocity && coupledL2Res < this.StressSolver_ConvergenceCriterion)
// {
// Console.WriteLine("SolveVelocity = true");
// this.solveVelocity = true;
// }
//}
OnIterationCallback(itc, x.CloneAs(), f0.CloneAs(), this.CurrentLin);
}
}
SolutionVec = m_SolutionVec;
}
}
