public static double rhoDinvA(MsrMatrix A, out MsrMatrix DinvA)
{
double rho;
// extract diagonal matrix
double[] Diag = A.GetDiagVector();
int n = Diag.Length;
// % form (D^-1) A
//Diag = spdiags(1./Diag, 0, n, n);
//DinvA = Diag*A;
DinvA = new MsrMatrix(A.RowPartitioning, A.ColPartition);
int i0 = A.RowPartitioning.i0;
int Lr;
int[] ColumnIdx = null;
double[] Values = null;
for (int i = 0; i < n; i++)
{
Lr = A.GetRow(i + i0, ref ColumnIdx, ref Values);
for (int k = 0; k < Lr; k++)
{
Values[k] *= 1.0 / Diag[i];
}
DinvA.SetRow(i + i0, ColumnIdx, Values, Lr);
}
#if DEBUG
for (int i = 0; i < n; i++)
{
Debug.Assert(Math.Abs(1.0 - DinvA[i + i0, i + i0]) < BLAS.MachineEps * 10);
}
#endif
// estimate the largest eigen value from Arnoldi iteration
int kk = 20;
var rand = new Random(0);
double[] v0 = n.ForLoop(i => rand.NextDouble());
double[][] V; double[,] H; int kact;
arnoldi(out V, out H, out kact, DinvA, v0, kk, false);
kk = Math.Min(H.GetLength(0), H.GetLength(1));
H = H.GetSubMatrix(0, kk, 0, kk);
rho = MaxAbsEigen(H);
return(rho);
}
private static void CheckMatrix(MsrMatrix MM, int iRow0, int N, int iRow)
{
int[] Cols = null;
double[] Vals = null;
int LR = MM.GetRow(iRow, ref Cols, ref Vals);
int cMin = int.MaxValue;
int cMax = int.MinValue;
for (int lr = 0; lr < LR; lr++)
{
if (Vals[lr] != 0.0)
{
cMin = Math.Min(cMin, Cols[lr]);
cMax = Math.Max(cMax, Cols[lr]);
}
}
Debug.Assert(cMin >= iRow0);
Debug.Assert(cMax < iRow0 + N);
}
private static MsrMatrix ColumnPermute(MsrMatrix M, int[] ColPerm)
{
MsrMatrix M2;
M2 = new MsrMatrix(M.RowPartitioning, M.ColPartition);
int[] ColIdx = null;
double[] MtxVals = null;
int LR;
for (int i = M2.RowPartitioning.i0; i < M2.RowPartitioning.iE; i++)
{
//var row = M.GetRow(i);
LR = M.GetRow(i, ref ColIdx, ref MtxVals);
for (int lr = 0; lr < LR; lr++)
{
int iCol = ColIdx[lr];
int icol_Targ = ColPerm[iCol];
M2[i, icol_Targ] = MtxVals[lr];
}
}
return(M2);
}
/// <summary>
///
/// </summary>
/// <param name="jCell"></param>
/// <param name="AcceptedMask"></param>
/// <param name="Phi"></param>
/// <param name="gradPhi"></param>
/// <param name="__DiffusionCoeff">Output: if artificial diffusion is turned</param>
/// <param name="MaxAllowedPhi">Input: upper threshold for the values of <paramref name="Phi"/> in cell <see cref="jCell"/>.</param>
/// <param name="MinAllowedPhi">Input: lower threshold for the values of <paramref name="Phi"/> in cell <see cref="jCell"/>.</param>
/// <returns></returns>
public bool LocalSolve_Iterative(int jCell, BitArray AcceptedMask, SinglePhaseField Phi, VectorField <SinglePhaseField> gradPhi, SinglePhaseField __DiffusionCoeff, double MaxAllowedPhi, double MinAllowedPhi)
{
//this.LocalSolve_Geometric(jCell, AcceptedMask, Phi, +1, out MinAllowedPhi, out MaxAllowedPhi);) {
int N = this.LevelSetBasis.GetLength(jCell);
int i0G = this.LevelSetMapping.GlobalUniqueCoordinateIndex(0, jCell, 0);
int i0L = this.LevelSetMapping.LocalUniqueCoordinateIndex(0, jCell, 0);
SinglePhaseField __AcceptedMask = new SinglePhaseField(new Basis(this.GridDat, 0), "accepted");
for (int j = 0; j < AcceptedMask.Length; j++)
{
__AcceptedMask.SetMeanValue(j, AcceptedMask[j] ? 1.0 : 0.0);
}
// subgrid on which we are working, consisting only of one cell
SubGrid jCellGrid = new SubGrid(new CellMask(this.GridDat, Chunk.GetSingleElementChunk(jCell)));
// create spatial operator
IEvaluatorNonLin evo;
{
SpatialOperator op = new SpatialOperator(1, 2, 1, QuadOrderFunc.NonLinear(2), "Phi", "dPhi_dx0", "dPhi_dx1", "cod1");
op.EquationComponents["cod1"].Add(new ReinitOperator());
op.EdgeQuadraturSchemeProvider = g => (new EdgeQuadratureScheme(domain: EdgeMask.GetEmptyMask(g)));
op.VolumeQuadraturSchemeProvider = g => (new CellQuadratureScheme(domain: jCellGrid.VolumeMask));
op.Commit();
evo = op.GetEvaluatorEx(Phi.Mapping.Fields, gradPhi.Mapping.Fields, Phi.Mapping);
evo.ActivateSubgridBoundary(jCellGrid.VolumeMask, subGridBoundaryTreatment: SubGridBoundaryModes.InnerEdge);
}
// create artificial diffusion operator
MultidimensionalArray DiffMtx;
double[] DiffRhs;
SpatialOperator dop;
{
double penaltyBase = this.LevelSetBasis.Degree + 2;
penaltyBase = penaltyBase.Pow2();
dop = (new ArtificialViscosity(AcceptedMask, penaltyBase, GridDat.Cells.h_min, jCell, -1.0)).Operator(1);
MsrMatrix _DiffMtx = new MsrMatrix(this.LevelSetMapping, this.LevelSetMapping);
double[] _DiffRhs = new double[this.LevelSetMapping.LocalLength];
dop.ComputeMatrixEx(this.LevelSetMapping, new DGField[] { Phi, null, null }, this.LevelSetMapping,
_DiffMtx, _DiffRhs, OnlyAffine: false,
edgeQuadScheme: (new EdgeQuadratureScheme(domain: jCellGrid.AllEdgesMask)),
volQuadScheme: (new CellQuadratureScheme(domain: jCellGrid.VolumeMask)));
// extract matrix for 'jCell'
DiffMtx = MultidimensionalArray.Create(N, N);
DiffRhs = new double[N];
for (int n = 0; n < N; n++)
{
#if DEBUG
int Lr;
int[] row_cols = null;
double[] row_vals = null;
Lr = _DiffMtx.GetRow(i0G + n, ref row_cols, ref row_vals);
for (int lr = 0; lr < Lr; lr++)
{
int ColIndex = row_cols[lr];
double Value = row_vals[lr];
Debug.Assert((ColIndex >= i0G && ColIndex < i0G + N) || (Value == 0.0), "Matrix is expected to be block-diagonal.");
}
#endif
for (int m = 0; m < N; m++)
{
DiffMtx[n, m] = _DiffMtx[i0G + n, i0G + m];
}
DiffRhs[n] = _DiffRhs[i0L + n];
}
#if DEBUG
var Test = DiffMtx.Transpose();
Test.Acc(-1.0, DiffMtx);
Debug.Assert(Test.InfNorm() <= 1.0e-8);
#endif
}
// find 'good' initial value by geometric solve AND
// thresholds for the maximum an minimal value of Phi
double Range = MaxAllowedPhi - MinAllowedPhi;
MinAllowedPhi -= 0.1 * Range;
MaxAllowedPhi += 0.1 * Range;
// timestep for pseudo-timestepping
double dt = 0.5 * this.GridDat.Cells.h_min[jCell] / (((double)(this.LevelSetBasis.Degree)).Pow2());
DGField[] PlotFields = new DGField[] { Phi, gradPhi[0], gradPhi[1], __DiffusionCoeff, __AcceptedMask };
//Tecplot.Tecplot.PlotFields(Params, "itt_0", "EllipicReinit", 0, 3);
double[] PrevVal = new double[N];
double[] NextVal = new double[N];
Phi.Coordinates.GetRow(jCell, PrevVal);
// pseudo-timestepping
//if(jCell == 80)
// Tecplot.Tecplot.PlotFields(PlotFields, "itt_0", "EllipicReinit", 0, 3);
//Console.Write(" Local solve cell " + jCell + " ... ");
bool converged = false;
double DiffusionCoeff = 0;
int IterGrowCount = 0; // number of iterations in which the residual grew
double LastResi = double.NaN;
for (int iIter = 0; iIter < 1000; iIter++)
{
//Console.Write(" Local solve iteration " + iIter + " ... ");
PerformRKstep(dt, jCell, AcceptedMask, Phi, gradPhi, evo);
__DiffusionCoeff.SetMeanValue(jCell, DiffusionCoeff);
if (jCell == 80)
{
DiffusionCoeff = 0.1;
}
if (DiffusionCoeff > 0)
{
//Console.WriteLine(" Diffusion on.");
double[] _DiffRhs = new double[this.LevelSetMapping.LocalLength];
dop.ComputeMatrixEx(this.LevelSetMapping, new DGField[] { Phi, gradPhi[0], gradPhi[1] }, this.LevelSetMapping,
default(MsrMatrix), _DiffRhs, OnlyAffine: true,
edgeQuadScheme: (new EdgeQuadratureScheme(domain: jCellGrid.AllEdgesMask)),
volQuadScheme: (new CellQuadratureScheme(domain: CellMask.GetEmptyMask(this.GridDat))));
// extract matrix for 'jCell'
for (int n = 0; n < N; n++)
{
DiffRhs[n] = _DiffRhs[i0L + n];
}
PerformArtificialDiffusion(dt * DiffusionCoeff, jCell, Phi, DiffMtx, DiffRhs);
}
Phi.Coordinates.GetRow(jCell, NextVal);
double resi = Math.Sqrt(GenericBlas.L2DistPow2(NextVal, PrevVal) / GenericBlas.L2NormPow2(PrevVal));
double[] A = NextVal;
NextVal = PrevVal;
PrevVal = A;
if (iIter > 0 && resi > LastResi)
{
IterGrowCount++;
}
else
{
IterGrowCount = 0;
}
LastResi = resi;
if (resi < 1.0e-10)
{
converged = true;
break;
}
double maxPhi, minPhi;
Phi.GetExtremalValuesInCell(out minPhi, out maxPhi, jCell);
bool MinAlarm = minPhi < MinAllowedPhi;
bool Maxalarm = maxPhi > MaxAllowedPhi;
bool GrowAlarm = IterGrowCount > 4;
bool IterAlarm = iIter >= 50;
if (MinAlarm || Maxalarm || GrowAlarm)
{
// Diffusion coefficient should be increased
if (DiffusionCoeff == 0)
{
DiffusionCoeff = 1.0e-2;
}
else
{
if (DiffusionCoeff < 1.0e3)
{
DiffusionCoeff *= 2;
}
}
//Console.WriteLine(" increasing Diffusion: {0}, Alarms : {1}{2}{3}{4}", DiffusionCoeff, MinAlarm ? 1 : 0, Maxalarm ? 1 : 0, GrowAlarm ? 1 : 0, IterAlarm ? 1 : 0);
}
//if(jCell == 80 && iIter < 100)
// Tecplot.Tecplot.PlotFields(PlotFields, "itt_" + (iIter + 1), "EllipicReinit", iIter + 1, 3);
}
return(converged);
}
private void ApproximationMatrix()
{
this.Aapprox = null;
this.AapproxInverse = null;
//MsrMatrix AapproxComp = null;
/*
* switch(m_SIMPLEOptions.Option_Approximation_Predictor) {
* case ApproxPredictor.MassMatrix:
* case ApproxPredictor.LocalizedOperator: { break; }
* default: {
* Aapprox = ConvDiff.CloneAs();
* //switch (m_SIMPLEOptions.Option_Timestepper) {
* // case Timestepper.Steady: break;
* // case Timestepper.ImplicitEuler: {
* // Aapprox.Acc(1.0 / dt, MassMatrix);
* // break;
* // }
* // default: {
* // throw new NotImplementedException("Unknown Timestepper");
* // }
* //}
* AapproxComp = new MsrMatrix(USubMatrixIdx.Length, USubMatrixIdx.Length, MassMatrix.RowPartitioning.BlockSize / (2 * D), MassMatrix.ColPartition.BlockSize / (2 * D));
* Aapprox.WriteSubMatrixTo(AapproxComp, USubMatrixIdx, default(int[]), USubMatrixIdx, default(int[]));
* break;
* }
* }
*/
switch (m_SIMPLEOptions.Option_Approximation_Predictor)
{
case ApproxPredictor.MassMatrix: {
BlockMsrMatrix MM;
if (!double.IsPositiveInfinity(this.m_SIMPLEOptions.dt))
{
// instationary SIMPLE
//MM = this.m_MgOp.MassMatrix.CloneAs();
// hier muss ich mir nochmal was überlegen --
// für einige Präkond.-Optionen
// (genau jene, welche die XDG-Basen für beide Phasen in Cut-Zellen mischen),
// wie etwa
// MultigridOperator.Mode.SymPart_DiagBlockEquilib
// ist eine Block-Skalierung mit rho_A und rho_B
// inkonsistent!
//
throw new NotImplementedException("todo");
}
else
{
MM = this.m_MgOp.MassMatrix;
}
Aapprox = new MsrMatrix(this.ConvDiff.RowPartitioning);
this.m_MgOp.MassMatrix.WriteSubMatrixTo(Aapprox, this.USubMatrixIdx_Row, default(int[]), this.USubMatrixIdx_Row, default(int[]));
//AapproxInverse = MassMatrixInv._ToMsrMatrix();// Aapprox.Invert();
//switch(m_SIMPLEOptions.Option_Timestepper) {
// case Timestepper.Steady: break;
// case Timestepper.ImplicitEuler: {
// Aapprox.Scale(1 + 1.0 / dt);
// AapproxInverse.Scale(1 / (1 + 1.0 / dt));
// /*#if DEBUG
// var CheckMX = AapproxInverse * Aapprox;
// foreach (int i in USubMatrixIdx) {
// if (Math.Abs(CheckMX.GetDiagonalElement(i) - 1.0) > 1e-10) throw new ArithmeticException("AapproxInverse is not the Inverse of the Aapprox-Matrix");
// }
// #endif*/
// break;
// }
// default: {
// throw new NotImplementedException("Unknown Timestepper");
// }
//}
break;
}
case ApproxPredictor.Exact: {
if (this.LsTrk.GridDat.CellPartitioning.MpiSize > 1)
{
throw new NotSupportedException("Not implemented for MPI-parallel runs.");
}
//RowIdx = VelocityMapping.GetSubvectorIndices(this.LsTrk, D.ForLoop(d => d), _SpcIds: this.LsTrk.SpeciesIdS, drk: this.TransportAgglomerator);
//ColIdx = RowIdx;
if (USubMatrixIdx_Row.Length > 4500)
{
Console.WriteLine(string.Format("WARNING: you don't really want to invert a {0}x{0} matrix.", USubMatrixIdx_Row.Length));
}
this.Aapprox = this.ConvDiff;
MultidimensionalArray AapproxFull = Aapprox.ToFullMatrixOnProc0();
MultidimensionalArray AapproxInverseFull = AapproxFull.GetInverse();
this.AapproxInverse = new MsrMatrix(new Partitioning(USubMatrixIdx_Row.Length));
this.AapproxInverse.AccDenseMatrix(1.0, AapproxInverseFull);
break;
}
case ApproxPredictor.Diagonal: {
/*
* Aapprox = new MsrMatrix(ConvDiff.RowPartitioning, ConvDiff.ColPartition);
* AapproxInverse = new MsrMatrix(ConvDiff.RowPartitioning, ConvDiff.ColPartition);
* foreach(int i in USubMatrixIdx) {
* int[] j = new int[] { i };
* double Value = ConvDiff.GetValues(i, j)[0];
* //Value += MassMatrix.GetValues(i, j)[0];
* Aapprox.SetDiagonalElement(i, Value);
* if(Value == 0) {
* AapproxInverse.SetDiagonalElement(i, 0);
* } else {
* AapproxInverse.SetDiagonalElement(i, 1 / Value);
* }
* }
#if DEBUG
* Aapprox.VerifyDataStructure();
* AapproxInverse.VerifyDataStructure();
* var CheckMX = AapproxInverse * Aapprox;
* foreach(int i in USubMatrixIdx) {
* if(Math.Abs(CheckMX.GetDiagonalElement(i) - 1.0) > 1e-13) throw new ArithmeticException("AapproxInverse is not the Inverse of the Operator Matrix");
* }
#endif
* break;
*/
throw new NotImplementedException("todo");
}
case ApproxPredictor.BlockDiagonal: {
/*
* AapproxInverse = new MsrMatrix(Aapprox.RowPartitioning, Aapprox.ColPartition);
* var AapproxCompBD = new BlockDiagonalMatrix(AapproxComp);
* var AapproxCompInvBD = AapproxCompBD.Invert();
* AapproxCompBD._ToMsrMatrix().WriteSubMatrixTo(Aapprox, default(int[]), USubMatrixIdx, default(int[]), USubMatrixIdx);
* AapproxCompInvBD._ToMsrMatrix().WriteSubMatrixTo(AapproxInverse, default(int[]), USubMatrixIdx, default(int[]), USubMatrixIdx);
* //#if DEBUG
* Aapprox.VerifyDataStructure();
* AapproxInverse.VerifyDataStructure();
* var CheckMX = AapproxInverse * Aapprox;
* foreach(int i in USubMatrixIdx) {
* if(Math.Abs(CheckMX.GetDiagonalElement(i) - 1.0) > 1e-12) throw new ArithmeticException("AapproxInverse is not the Inverse of the Operator Matrix");
* }
* //#endif
*
* break;
*/
throw new NotImplementedException("todo");
}
case ApproxPredictor.BlockSum: {
/*
* Console.WriteLine("BlockSum is not properly tested yet and did not work in previous tests");
* int AccdBlockSize = ConvDiff.RowPartitioning.BlockSize / (2 * D);
* var AapproxBD = new BlockDiagonalMatrix(ConvDiff.RowPartitioning);
* var Aapprox = new MsrMatrix(ConvDiff.RowPartitioning);
* int[] indexer = new int[AccdBlockSize];
* for(int i = 0; i < indexer.Length; i++) {
* indexer[i] = i;
* }
* int[] rowindexer = indexer.CloneAs();
*
*
* for(int i = 0; i < ConvDiff.NoOfRows / AccdBlockSize; i++) {
* int[] colindexer = indexer.CloneAs();
* for(int j = 0; j < ConvDiff.NoOfCols / AccdBlockSize; j++) {
* ConvDiff.AccSubMatrixTo(1.0, Aapprox, rowindexer, rowindexer, colindexer, rowindexer);
* for(int r = 0; r < indexer.Length; r++) {
* colindexer[r] += AccdBlockSize;
* }
* }
* for(int r = 0; r < indexer.Length; r++) {
* rowindexer[r] += AccdBlockSize;
* }
* }
* //if (m_SIMPLEOptions.Option_Timestepper == Timestepper.ImplicitEuler) {
* // Aapprox.Acc(1 / dt, MassMatrix);
* //}
* AapproxComp = new MsrMatrix(USubMatrixIdx.Length, USubMatrixIdx.Length, AccdBlockSize, AccdBlockSize);
* Aapprox.WriteSubMatrixTo(AapproxComp, USubMatrixIdx, default(int[]), USubMatrixIdx, default(int[]));
* AapproxInverse = new MsrMatrix(Aapprox.RowPartitioning, Aapprox.ColPartition);
* var AapproxCompBD = new BlockDiagonalMatrix(AapproxComp);
* var AapproxCompInvBD = AapproxCompBD.Invert();
* AapproxCompInvBD._ToMsrMatrix().WriteSubMatrixTo(AapproxInverse, default(int[]), USubMatrixIdx, default(int[]), USubMatrixIdx);
#if DEBUG
* Aapprox.VerifyDataStructure();
* AapproxInverse.VerifyDataStructure();
*
* // Check copying back and forth
* var CheckAapproxComp = new MsrMatrix(Aapprox.RowPartitioning, Aapprox.ColPartition);
* AapproxComp.WriteSubMatrixTo(CheckAapproxComp, default(int[]), USubMatrixIdx, default(int[]), USubMatrixIdx);
* CheckAapproxComp.Acc(-1.0, Aapprox);
* if(CheckAapproxComp.InfNorm() > 1e-14) throw new ArithmeticException("Something went wrong while copying the Aapprox Matrix");
*
* //Check Transformation to BlockdiagonalMatrix
* var CheckAapproxCompBD = new MsrMatrix(Aapprox.RowPartitioning, Aapprox.ColPartition);
* AapproxCompBD._ToMsrMatrix().WriteSubMatrixTo(CheckAapproxCompBD, default(int[]), USubMatrixIdx, default(int[]), USubMatrixIdx);
* CheckAapproxCompBD.Acc(-1.0, Aapprox);
* if(CheckAapproxCompBD.InfNorm() > 1e-14) throw new ArithmeticException("Something went wrong while copying the Aapprox Matrix");
*
* //Check Matrix Inversion
* var CheckMX = AapproxInverse * Aapprox;
* foreach(int i in USubMatrixIdx) {
* if(Math.Abs(CheckMX.GetDiagonalElement(i) - 1.0) > 1e-12) throw new ArithmeticException("AapproxInverse is not the Inverse of the Operator Matrix");
* }
#endif
* break;
*/
throw new NotImplementedException("todo");
}
case ApproxPredictor.Neumann: {
/*
* Console.WriteLine("Neumann did not work in previous Tests, Series does typically not converge");
* int serieslength = 10;
*
* Aapprox = ConvDiff.CloneAs();
* //if (m_SIMPLEOptions.Option_Timestepper != Timestepper.Steady) {
* // Aapprox.Acc(1.0 / dt, MassMatrix);
* //}
* var B = Aapprox.CloneAs();
* double ScalingFactor = Aapprox.InfNorm();
* B.Scale((-1.0 / ScalingFactor.Pow(0))); //Scaling Power up to 4 tried
* B.AccEyeSp(1.0);
* AapproxInverse = B;
* AapproxInverse.AccEyeSp(1.0);
* MsrMatrix OldMoment = B;
* for(int i = 0; i <= serieslength; i++) {
* var NewMoment = OldMoment * B;
* AapproxInverse.Acc(1.0, NewMoment);
* //Debug
* Console.WriteLine("MomentNumber #{0}, InfNormOf Inverse #{1}", i, NewMoment.InfNorm());
* OldMoment = NewMoment;
* }
* AapproxInverse.Scale((1.0 / ScalingFactor.Pow(0))); //Scaling Power up to 4 tried
* break;
*/
throw new NotImplementedException("todo");
}
case ApproxPredictor.LocalizedOperator: {
/*
* Console.WriteLine("Localized Operator did not work in previous Tests");
* double[] LocalizedOpAffine;
* MultiphaseCellAgglomerator LocalizedAgglomerator;
* Aapprox = new MsrMatrix(MassMatrix.RowPartitioning, MassMatrix.ColPartition);
* TransportOpLocalized.AssembleMatrix(
* out Aapprox, out LocalizedOpAffine,
* out LocalizedAgglomerator, out TransportMassFact,
* this.Velocity.Current, null,
* this.LevSet, null, Curv,
* VelocityMapping, VelocityMapping);
* if(Option_Timestepper == Timestepper.ImplicitEuler) {
* Aapprox.Acc(1 / dt, MassMatrix);
* }
*
* var DiagAverage = Aapprox.GetDiagVector().Average();
* foreach(int i in RowIdx) {
* if(Aapprox.GetDiagonalElement(i) == 0.0) {
* //Aapprox.SetDiagonalElement(i, MassMatrix.GetDiagonalElement(i));
* Aapprox.SetDiagonalElement(i, DiagAverage);
* }
* }
* AapproxComp = new MsrMatrix(RowIdx.Length, RowIdx.Length, MassMatrix.RowPartitioning.BlockSize / (2 * D), MassMatrix.ColPartition.BlockSize / (2 * D));
* Aapprox.WriteSubMatrixTo(AapproxComp, RowIdx, default(int[]), ColIdx, default(int[]));
* AapproxInverse = new MsrMatrix(Aapprox.RowPartitioning, Aapprox.ColPartition);
* var AapproxCompBD = new BlockDiagonalMatrix(AapproxComp);
* var AapproxCompInvBD = AapproxCompBD.Invert();
* AapproxCompInvBD._ToMsrMatrix().WriteSubMatrixTo(AapproxInverse, default(int[]), RowIdx, default(int[]), ColIdx);
* //AapproxComp._ToMsrMatrix().WriteSubMatrixTo(Aapprox, default(int[]), RowIdx, default(int[]), ColIdx);
*
*
#if DEBUG
* Aapprox.VerifyDataStructure();
* AapproxInverse.VerifyDataStructure();
* var CheckAapproxCompBD = new MsrMatrix(Aapprox.RowPartitioning, Aapprox.ColPartition);
* AapproxCompBD._ToMsrMatrix().WriteSubMatrixTo(CheckAapproxCompBD, default(int[]), RowIdx, default(int[]), ColIdx);
* CheckAapproxCompBD.Acc(-1.0, Aapprox);
* if(CheckAapproxCompBD.InfNorm() > 1e-14) throw new ArithmeticException("Something went wrong while copying the Aapprox Matrix");
* var CheckMX = AapproxInverse * Aapprox;
* foreach(int i in RowIdx) {
* if(Math.Abs(CheckMX.GetDiagonalElement(i) - 1.0) > 1e-12) throw new ArithmeticException("AapproxInverse is not the Inverse of the Operator Matrix");
* }
#endif
* break;
*/
throw new NotImplementedException("todo");
}
default:
throw new NotImplementedException("todo");
}
if (this.AapproxInverse == null)
{
// block-inversion is required.
// ++++++++++++++++++++++++++++
int D = this.LsTrk.GridDat.SpatialDimension;
this.AapproxInverse = new MsrMatrix(this.Aapprox.RowPartitioning, this.Aapprox.ColPartition);
//int N = this.m_MgOp.Mapping.AggBasis.GetMinimalLength(this.m_MgOp.Mapping.DgDegree[0]);
//Debug.Assert(this.Aapprox.RowPartitioning.LocalLength % N == 0);
MultidimensionalArray Block = new MultidimensionalArray(2);
MultidimensionalArray InvBlock = new MultidimensionalArray(2);
int iRow0 = this.Aapprox.RowPartitioning.i0;
int JAGG = this.m_MgOp.Mapping.AggGrid.iLogicalCells.NoOfLocalUpdatedCells;
int[] DegreeS = this.m_MgOp.Mapping.DgDegree;
for (int jagg = 0; jagg < JAGG; jagg++) // loop over aggregate cells...
{
for (int d = 0; d < D; d++) // loop over velocity components...
{
int N = this.m_MgOp.Mapping.AggBasis[d].GetLength(jagg, DegreeS[d]);
if (Block.GetLength(0) != N)
{
Block.Allocate(N, N);
InvBlock.Allocate(N, N);
}
for (int n = 0; n < N; n++)
{
#if DEBUG
int iRow = iRow0 + n;
{
int[] Cols = null;
double[] Vals = null;
int LR = Aapprox.GetRow(iRow, ref Cols, ref Vals);
int cMin = int.MaxValue;
int cMax = int.MinValue;
for (int lr = 0; lr < LR; lr++)
{
if (Vals[lr] != 0.0)
{
cMin = Math.Min(cMin, Cols[lr]);
cMax = Math.Max(cMax, Cols[lr]);
}
}
Debug.Assert(cMin >= iRow0);
Debug.Assert(cMax < iRow0 + N);
}
#endif
for (int m = 0; m < N; m++)
{
Block[n, m] = this.Aapprox[iRow0 + n, iRow0 + m];
}
}
Block.InvertTo(InvBlock);
for (int n = 0; n < N; n++)
{
for (int m = 0; m < N; m++)
{
this.AapproxInverse[iRow0 + n, iRow0 + m] = InvBlock[n, m];
}
}
iRow0 += N;
}
}
Debug.Assert(iRow0 == this.Aapprox.RowPartitioning.iE);
}
#if DEBUG
var CheckMX = AapproxInverse * Aapprox;
double TRESH = Math.Max(AapproxInverse.InfNorm(), Aapprox.InfNorm()) * 1.0e-10;
for (int iRow = CheckMX.RowPartitioning.i0; iRow < CheckMX.RowPartitioning.iE; iRow++)
{
if (Math.Abs(CheckMX.GetDiagonalElement(iRow) - 1.0) > TRESH)
{
throw new ArithmeticException("AapproxInverse is not the Inverse of the Aapprox-Matrix");
}
}
#endif
}
void ExtractMatrices()
{
// dispose old solver, if required
// ===============================
if (this.m_PressureSolver != null)
{
this.m_PressureSolver.Dispose();
this.m_PressureSolver = null;
}
// sub-matrices for the Potential Solver
// =====================================
int VelocityLength = this.USubMatrixIdx_Row.Length;
int PressureLength = this.PSubMatrixIdx_Row.Length;
this.PressureGrad = new MsrMatrix(VelocityLength, PressureLength, 1, 1);
this.VelocityDiv = new MsrMatrix(PressureLength, VelocityLength, 1, 1);
this.Stab = new MsrMatrix(PressureLength, PressureLength, 1, 1);
var WholeSystemMatrix = this.m_MgOp.OperatorMatrix;
WholeSystemMatrix.WriteSubMatrixTo(PressureGrad, USubMatrixIdx_Row, default(int[]), PSubMatrixIdx_Row, default(int[]));
WholeSystemMatrix.WriteSubMatrixTo(VelocityDiv, PSubMatrixIdx_Row, default(int[]), USubMatrixIdx_Row, default(int[]));
WholeSystemMatrix.WriteSubMatrixTo(Stab, PSubMatrixIdx_Row, default(int[]), PSubMatrixIdx_Row, default(int[]));
// inverse mass matrix
// ===================
if (this.m_SIMPLEOptions.PotentialSolver_UseMassMatrix)
{
// extract the mass-matrix block for the velocity part
// ---------------------------------------------------
MsrMatrix MM = new MsrMatrix(this.PressureGrad.RowPartitioning, this.VelocityDiv.ColPartition);
this.m_MgOp.MassMatrix.WriteSubMatrixTo(MM, this.USubMatrixIdx_Row, default(int[]), this.USubMatrixIdx_Row, default(int[]));
// invert mass matrix
// ------------------
int D = this.LsTrk.GridDat.SpatialDimension;
this.invMM = new MsrMatrix(MM.RowPartitioning, MM.ColPartition);
MultidimensionalArray Block = new MultidimensionalArray(2);
MultidimensionalArray InvBlock = new MultidimensionalArray(2);
int iRow0 = MM.RowPartitioning.i0;
int JAGG = this.m_MgOp.Mapping.AggGrid.iLogicalCells.NoOfLocalUpdatedCells;
int[] DegreeS = this.m_MgOp.Mapping.DgDegree;
for (int jagg = 0; jagg < JAGG; jagg++) // loop over aggregate cells...
{
for (int d = 0; d < D; d++) // loop over velocity components...
{
int N = this.m_MgOp.Mapping.AggBasis[d].GetLength(jagg, DegreeS[d]);
if (Block.GetLength(0) != N)
{
Block.Allocate(N, N);
InvBlock.Allocate(N, N);
}
for (int n = 0; n < N; n++)
{
#if DEBUG
int iRow = iRow0 + n;
{
int[] Cols = null;
double[] Vals = null;
int LR = MM.GetRow(iRow, ref Cols, ref Vals);
int cMin = int.MaxValue;
int cMax = int.MinValue;
for (int lr = 0; lr < LR; lr++)
{
if (Vals[lr] != 0.0)
{
cMin = Math.Min(cMin, Cols[lr]);
cMax = Math.Max(cMax, Cols[lr]);
}
}
Debug.Assert(cMin >= iRow0);
Debug.Assert(cMax < iRow0 + N);
}
#endif
for (int m = 0; m < N; m++)
{
Block[n, m] = MM[iRow0 + n, iRow0 + m];
}
}
Block.InvertTo(InvBlock);
for (int n = 0; n < N; n++)
{
for (int m = 0; m < N; m++)
{
this.invMM[iRow0 + n, iRow0 + m] = InvBlock[n, m];
}
}
iRow0 += N;
}
}
Debug.Assert(iRow0 == MM.RowPartitioning.iE);
#if DEBUG
var CheckMX = MM * invMM;
double TRESH = Math.Max(MM.InfNorm(), invMM.InfNorm()) * 1.0e-10;
for (int iRow = CheckMX.RowPartitioning.i0; iRow < CheckMX.RowPartitioning.iE; iRow++)
{
if (Math.Abs(CheckMX.GetDiagonalElement(iRow) - 1.0) > TRESH)
{
throw new ArithmeticException("AapproxInverse is not the Inverse of the Aapprox-Matrix");
}
}
#endif
}
}
