/// <summary>
/// returns the maximum and minimum eigenvalues of the matrix
/// </summary>
/// <returns>Array myeigs =[MaximumEig, MinimumEig]</returns>
public double[] Eigenval()
{
double[] eigenvalues = new double[2];
MultidimensionalArray eigs = MultidimensionalArray.Create(1, 2);
MultidimensionalArray output = MultidimensionalArray.Create(2, 1);
int[] DepVars = this.VarGroup;
double[] DepVars_subvec = this.m_map.GetSubvectorIndices(true, DepVars).Select(i => i + 1.0).ToArray();
using (BatchmodeConnector bmc = new BatchmodeConnector()){
// if Octave should be used instead of Matlab....
//BatchmodeConnector.Flav = BatchmodeConnector.Flavor.Octave;
bmc.PutSparseMatrix(m_OpMtx, "FullMatrix");
bmc.PutVector(DepVars_subvec, "DepVars_subvec");
bmc.Cmd("output = zeros(2,1)");
bmc.Cmd("output(1) = eigs(FullMatrix(DepVars_subvec,DepVars_subvec),1,'lm');");
bmc.Cmd("output(2) = eigs(FullMatrix(DepVars_subvec,DepVars_subvec),1,'sm');");
bmc.GetMatrix(output, "output");
bmc.Execute(false);
}
double[] myeigs = new double[] { output[0, 0], output[1, 0] };
Debug.Assert(output[0, 0].MPIEquals(), "value does not match on procs");
Debug.Assert(output[1, 0].MPIEquals(), "value does not match on procs");
return(myeigs);
}
public static void GetExternalRowsTest(
[Values(XDGusage.none, XDGusage.all)] XDGusage UseXdg,
[Values(2)] int DGOrder,
[Values(4)] int Res)
{
//Matlabaufruf --> gesamte Matrix nach Matlab schreiben
//Teilmatritzen gemäß Globalid extrahieren
//Mit ExternalRows vergleichen
//Die große Frage: funktioniert der batchmode connector parallel? Beim rausschreiben beachten
Utils.TestInit((int)UseXdg, DGOrder);
Console.WriteLine("GetExternalRowsTest({0},{1})", UseXdg, DGOrder);
//Arrange --- setup mgo and mask
MultigridOperator mgo = Utils.CreateTestMGOperator(UseXdg, DGOrder, MatrixShape.laplace, Res);
MultigridMapping map = mgo.Mapping;
BlockMsrMatrix M = mgo.OperatorMatrix;
//Delete this plz ...
//M.SaveToTextFileSparse("M");
//int[] A = Utils.GimmeAllBlocksWithSpec(map, 9);
//int[] B = Utils.GimmeAllBlocksWithSpec(map, 18);
//if (map.MpiRank == 0) {
// A.SaveToTextFileDebug("ACells");
// B.SaveToTextFileDebug("BCells");
//}
var selector = new SubBlockSelector(map);
var dummy = new BlockMsrMatrix(map); // we are only interested in getting indices, so a dummy is sufficient
var mask = new BlockMask(selector, dummy);
//Arrange --- get stuff to put into matlab
int[] GlobalIdx_ext = Utils.GetAllExtCellIdc(map);
double[] GlobIdx = GlobalIdx_ext.Length.ForLoop(i => (double)GlobalIdx_ext[i] + 1.0);
//Arrange --- get external rows by mask
BlockMsrMatrix extrows = BlockMask.GetAllExternalRows(mgo.Mapping, mgo.OperatorMatrix);
//Assert --- idc and rows of extrows have to be the same
Assert.IsTrue(GlobIdx.Length == extrows._RowPartitioning.LocalLength);
//Arrange --- get external rows by matlab
var infNorm = MultidimensionalArray.Create(1, 1);
using (BatchmodeConnector matlab = new BatchmodeConnector()) {
//note: BatchmodeCon maybe working on proc0 but savetotxt file, etc. (I/O) is full mpi parallel
//so concider this as full mpi-parallel
matlab.PutSparseMatrix(M, "M");
matlab.PutSparseMatrix(extrows, "M_test");
matlab.PutVector(GlobIdx, "Idx");
matlab.Cmd(String.Format("M_ext = M(Idx, :);"));
matlab.Cmd("n=norm(M_test-M_ext,inf)");
matlab.GetMatrix(infNorm, "n");
matlab.Execute();
}
//Assert --- test if we actually got the right Matrix corresponding to Index
Assert.IsTrue(infNorm[0, 0] == 0.0);
}
/// <summary>
/// returns the condition number of the full matrix
/// </summary>
public double CondNumMatlab()
{
int[] DepVars = this.VarGroup;
var grd = m_map.GridDat;
int NoOfCells = grd.Grid.NumberOfCells;
int NoOfBdryCells = grd.GetBoundaryCells().NoOfItemsLocally_WithExternal;
var Mtx = m_MultigridOp.OperatorMatrix;
// Blocks and selectors
// ====================
var InnerCellsMask = grd.GetBoundaryCells().Complement();
var FullSel = new SubBlockSelector(m_MultigridOp.Mapping);
FullSel.VariableSelector(this.VarGroup);
// Matlab
// ======
double[] Full_0Vars = (new BlockMask(FullSel)).GlobalIndices.Select(i => i + 1.0).ToArray();
MultidimensionalArray output = MultidimensionalArray.Create(2, 1);
string[] names = new string[] { "Full_0Vars", "Inner_0Vars" };
using (BatchmodeConnector bmc = new BatchmodeConnector()) {
// if Octave should be used instead of Matlab....
// BatchmodeConnector.Flav = BatchmodeConnector.Flavor.Octave;
bmc.PutSparseMatrix(Mtx, "FullMatrix");
bmc.PutVector(Full_0Vars, "Full_0Vars");
bmc.Cmd("output = ones(2,1);");
bmc.Cmd("output(1) = condest(FullMatrix(Full_0Vars,Full_0Vars));");
bmc.GetMatrix(output, "output");
bmc.Execute(false);
double condestFull = output[0, 0];
Debug.Assert(condestFull.MPIEquals(), "value does not match on procs");
Console.WriteLine($"MATLAB condition number: {condestFull:0.###e-00}");
return(condestFull);
}
}
public static IntersectionMesh CreateMesh(MultidimensionalArray nodes)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
IntersectionMesh mesh;
using (var Matlab = new BatchmodeConnector())
{
Matlab.PutMatrix(nodes, "Nodes");
// compute Voronoi diagramm
Matlab.Cmd("[V, C] = voronoin(Nodes);");
// output (export from matlab)
int[][] VocellVertexIndex = new int[nodes.NoOfRows][];
Matlab.GetStaggeredIntArray(VocellVertexIndex, "C");
Matlab.GetMatrix(null, "V");
// run matlab
Matlab.Execute(false);
// Vertices: List<Vertex>
//---------------------------
MultidimensionalArray matlabVertexCoordinates = (MultidimensionalArray)(Matlab.OutputObjects["V"]);
List <Vertex> vertexCoordinates = new List <Vertex>(matlabVertexCoordinates.NoOfRows);
for (int i = 0; i < matlabVertexCoordinates.NoOfRows; ++i)
{
Vertex tmp = new Vertex();
tmp.Position = new Vector(matlabVertexCoordinates.GetRow(i));
tmp.ID = i;
vertexCoordinates.Add(tmp);
}
//Cells: int[][]
//--------------------------------------------
// correct indices (1-based index to 0-based index)
for (int i = 0; i < VocellVertexIndex.Length; ++i)
{
for (int k = 0; k < VocellVertexIndex[i].Length; k++)
{
VocellVertexIndex[i][k]--;
}
}
stopwatch.Stop();
Console.WriteLine(stopwatch.ElapsedMilliseconds);
//Convert to mesh data types
//--------------------------------------------
mesh = new IntersectionMesh(new OrderedMatlabMesh(VocellVertexIndex, vertexCoordinates));
}
return(mesh);
}
public static void SubSelection(
[Values(XDGusage.none, XDGusage.all)] XDGusage UseXdg,
[Values(2)] int DGOrder,
[Values(MatrixShape.full_var_spec, MatrixShape.full_spec, MatrixShape.full_var, MatrixShape.full)] MatrixShape MShape,
[Values(4)] int Res)
{
Utils.TestInit((int)UseXdg, DGOrder, (int)MShape, Res);
Console.WriteLine("SubSelection({0},{1},{2},{3})", UseXdg, DGOrder, MShape, Res);
//Arrange --- create test matrix, MG mapping
MultigridOperator mgo = Utils.CreateTestMGOperator(UseXdg, DGOrder, MShape, Res);
MultigridMapping map = mgo.Mapping;
BlockMsrMatrix M = mgo.OperatorMatrix;
//Arrange --- get mask
int[] cells = Utils.GetCellsOfOverlappingTestBlock(map);
Array.Sort(cells);
var sbs = new SubBlockSelector(map);
sbs.CellSelector(cells, false);
BlockMsrMatrix M_ext = BlockMask.GetAllExternalRows(map, M);
var mask = new BlockMask(sbs, M_ext);
//Arrange --- get GlobalIdxList
int[] idc = Utils.GetIdcOfSubBlock(map, cells);
bool[] coup = Utils.SetCoupling(MShape);
var M_sub = mask.GetSubBlockMatrix(M, false, coup[0], coup[1]);
var infNorm = MultidimensionalArray.Create(4, 1);
int rank = map.MpiRank;
using (BatchmodeConnector matlab = new BatchmodeConnector()) {
double[] GlobIdx = idc.Count().ForLoop(i => (double)idc[i] + 1.0);
Assert.IsTrue(GlobIdx.Length == M_sub.NoOfRows);
matlab.PutSparseMatrix(M, "M");
// note: M_sub lives on Comm_Self, therefore we have to distinguish between procs ...
matlab.PutSparseMatrixRankExclusive(M_sub, "M_sub");
matlab.PutVectorRankExclusive(GlobIdx, "Idx");
matlab.Cmd("M_0 = full(M(Idx_0, Idx_0));");
matlab.Cmd("M_1 = full(M(Idx_1, Idx_1));");
matlab.Cmd("M_2 = full(M(Idx_2, Idx_2));");
matlab.Cmd("M_3 = full(M(Idx_3, Idx_3));");
matlab.Cmd("n=[0; 0; 0; 0];");
matlab.Cmd("n(1,1)=norm(M_0-M_sub_0,inf);");
matlab.Cmd("n(2,1)=norm(M_1-M_sub_1,inf);");
matlab.Cmd("n(3,1)=norm(M_2-M_sub_2,inf);");
matlab.Cmd("n(4,1)=norm(M_3-M_sub_3,inf);");
matlab.GetMatrix(infNorm, "n");
matlab.Execute();
}
Assert.IsTrue(infNorm[rank, 0] == 0.0);
}
private void OperatorAnalysis()
{
AggregationGridBasis[][] XAggB = AggregationGridBasis.CreateSequence(base.MultigridSequence, u.Mapping.BasisS);
XAggB.UpdateXdgAggregationBasis(this.Op_Agglomeration);
var MultigridOp = new MultigridOperator(XAggB, this.u.Mapping,
this.Op_Matrix,
this.Op_mass.GetMassMatrix(new UnsetteledCoordinateMapping(this.u.Basis), false),
OpConfig);
var PcOpMatrix = MultigridOp.OperatorMatrix;
//PcOpMatrix.SaveToTextFileSparse("C:\\temp\\Xpoisson.txt");
MultidimensionalArray ret = MultidimensionalArray.Create(1, 4);
using (BatchmodeConnector bmc = new BatchmodeConnector()) {
bmc.PutSparseMatrix(PcOpMatrix, "OpMtx");
bmc.Cmd("OpMtxSym = 0.5*(OpMtx + OpMtx');");
bmc.Cmd("condNo = condest(OpMtxSym);");
bmc.Cmd("eigMaxi = eigs(OpMtxSym,1,'lm')");
bmc.Cmd("eigMini = eigs(OpMtxSym,1,'sm')");
bmc.Cmd("lasterr");
bmc.Cmd("[V,r]=chol(OpMtxSym);");
bmc.Cmd("ret = [condNo, eigMaxi, eigMini, r]");
bmc.GetMatrix(ret, "ret");
bmc.Execute(false);
}
double condNo = ret[0, 0];
double eigMaxi = ret[0, 1];
double eigMini = ret[0, 2];
double posDef = ret[0, 3] == 0 ? 1 : 0;
Console.WriteLine("Condition number: {0:0.####E-00}", condNo);
if (posDef == 0.0)
{
Console.WriteLine("WARNING: Operator matrix is not positive definite.");
}
base.QueryHandler.ValueQuery("condNo", condNo, false);
base.QueryHandler.ValueQuery("eigMaxi", eigMaxi, false);
base.QueryHandler.ValueQuery("eigMini", eigMini, false);
base.QueryHandler.ValueQuery("posDef", posDef, false);
}
/// <summary>
///
/// </summary>
public void AnalyzeOperators(out MultidimensionalArray ret)
{
ret = MultidimensionalArray.Create(1, 7);
// MultidimensionalArray ret = MultidimensionalArray.Create(1, 4);
Console.WriteLine("Calling MATLAB/Octave...");
using (BatchmodeConnector bmc = new BatchmodeConnector()) {
bmc.PutSparseMatrix(OpMatrix, "OpMatrix");
bmc.Cmd("condNoOpMatrix = condest(OpMatrix)");
bmc.Cmd("OpRank = rank(full(OpMatrix))");
bmc.Cmd("OpSize = size(OpMatrix)");
bmc.Cmd("eigiMaxi = eigs(OpMatrix,1,'lm')");
bmc.Cmd("eigiMini = eigs(OpMatrix,1,'sm')");
bmc.Cmd("lasterr");
bmc.Cmd("[V,r]=chol(OpMatrix);");
bmc.Cmd("ret = [condNoOpMatrix, eigiMaxi, eigiMini, r, OpRank, OpSize]");
bmc.GetMatrix(ret, "ret");
bmc.Execute(true);
}
double condNoOpMatrix = ret[0, 0];
double eigiMaxi = ret[0, 1];
double eigiMini = ret[0, 2];
double posDef = ret[0, 3] == 0 ? 1 : 0;
Console.WriteLine("Condition number operator: {0:0.####E-00}", condNoOpMatrix);
if (posDef == 0.0)
{
Console.WriteLine("WARNING: Operator matrix is not positive definite.");
}
else
{
Console.WriteLine("Good news: Operator matrix seems to be positive definite.");
}
}
public static void SpMVTest(
[Values(XDGusage.none, XDGusage.mixed1, XDGusage.mixed2, XDGusage.all)] XDGusage UseXdg,
[Values(1, 3)] int DGOrder,
[Values(false, true)] bool compressL1,
[Values(false, true)] bool compressL2)
{
unsafe
{
int[] Params = new int[8], ParamsGlob = new int[8];
fixed(int *pParams = Params, pParamsGlob = ParamsGlob)
{
pParams[0] = (int)UseXdg;
pParams[1] = DGOrder;
pParams[2] = compressL1 ? 1 : 0;
pParams[3] = compressL2 ? 1 : 0;
pParams[4] = -pParams[0];
pParams[5] = -pParams[1];
pParams[6] = -pParams[2];
pParams[7] = -pParams[3];
csMPI.Raw.Allreduce((IntPtr)pParams, (IntPtr)pParamsGlob, 8, csMPI.Raw._DATATYPE.INT, csMPI.Raw._OP.MIN, csMPI.Raw._COMM.WORLD);
}
int[] ParamsMin = ParamsGlob.GetSubVector(0, 4);
int[] ParamsMax = ParamsGlob.GetSubVector(4, 4);
for (int i = 0; i < 4; i++)
{
if (Params[i] != ParamsMin[i])
{
throw new ApplicationException();
}
if (Params[i] != -ParamsMax[i])
{
throw new ApplicationException();
}
}
Console.WriteLine("SpMVTest({0},{1},{2},{3})", UseXdg, DGOrder, compressL1, compressL2);
}
using (var solver = new Matrix_MPItestMain()
{
m_UseXdg = UseXdg, m_DGorder = DGOrder
}) {
// create the test data
// ====================
BoSSS.Solution.Application.CommandLineOptions opts = null;
//opts = new BoSSS.Solution.Application.CommandLineOptions();
solver.Init(null, opts);
solver.RunSolverMode();
Stopwatch stw = new Stopwatch();
stw.Reset();
BlockMsrMatrix M = solver.OperatorMatrix;
double[] B = new double[M.RowPartitioning.LocalLength];
double[] X = new double[M.ColPartition.LocalLength];
Random R = new Random();
for (int i = 0; i < X.Length; i++)
{
X[i] = R.NextDouble();
}
for (int i = 0; i < B.Length; i++)
{
B[i] = R.NextDouble();
}
double[] Bb4 = B.CloneAs();
double RefNorm = B.L2NormPow2().MPISum().Sqrt() * 1e-10;
stw.Start();
M.SpMV(1.6, X, 0.5, B);
stw.Stop();
//M.SaveToTextFileSparse(@"C:\tmp\M.txt");
//M11.SaveToTextFileSparse(@"C:\tmp\M11.txt");
//M12.SaveToTextFileSparse(@"C:\tmp\M12.txt");
//M21.SaveToTextFileSparse(@"C:\tmp\M21.txt");
//M22.SaveToTextFileSparse(@"C:\tmp\M22.txt");
//M22xM21.SaveToTextFileSparse(@"C:\tmp\M22xM21.txt");
using (var MatlabRef = new BatchmodeConnector()) {
MultidimensionalArray CheckRes = MultidimensionalArray.Create(1, 1);
MatlabRef.PutSparseMatrix(M, "M");
MatlabRef.PutVector(Bb4, "Bref");
MatlabRef.PutVector(B, "B");
MatlabRef.PutVector(X, "X");
MatlabRef.Cmd("Bref = Bref*0.5 + M*X*1.6;");
MatlabRef.Cmd("errB = norm(B - Bref, 2);");
MatlabRef.Cmd("CheckRes = [errB];");
MatlabRef.GetMatrix(CheckRes, "CheckRes");
MatlabRef.Execute();
Console.WriteLine("Matlab check SpMV: " + CheckRes[0, 0]);
Assert.LessOrEqual(CheckRes[0, 0], RefNorm, "Error in SpMV");
}
Console.WriteLine("Time spend in matrix operations: " + stw.Elapsed.TotalSeconds + " sec.");
TotTime_MatrixOp += stw.Elapsed;
}
}
public static void SubMatrixTest(
[Values(XDGusage.none, XDGusage.mixed1, XDGusage.mixed2, XDGusage.all)] XDGusage UseXdg,
[Values(1, 3)] int DGOrder,
[Values(false, true)] bool compressL1,
[Values(false, true)] bool compressL2)
{
unsafe
{
int[] Params = new int[8], ParamsGlob = new int[8];
fixed(int *pParams = Params, pParamsGlob = ParamsGlob)
{
pParams[0] = (int)UseXdg;
pParams[1] = DGOrder;
pParams[2] = compressL1 ? 1 : 0;
pParams[3] = compressL2 ? 1 : 0;
pParams[4] = -pParams[0];
pParams[5] = -pParams[1];
pParams[6] = -pParams[2];
pParams[7] = -pParams[3];
csMPI.Raw.Allreduce((IntPtr)pParams, (IntPtr)pParamsGlob, 8, csMPI.Raw._DATATYPE.INT, csMPI.Raw._OP.MIN, csMPI.Raw._COMM.WORLD);
}
int[] ParamsMin = ParamsGlob.GetSubVector(0, 4);
int[] ParamsMax = ParamsGlob.GetSubVector(4, 4);
for (int i = 0; i < 4; i++)
{
if (Params[i] != ParamsMin[i])
{
throw new ApplicationException();
}
if (Params[i] != -ParamsMax[i])
{
throw new ApplicationException();
}
}
Console.WriteLine("SubMatrixTest({0},{1},{2},{3})", UseXdg, DGOrder, compressL1, compressL2);
}
using (var solver = new Matrix_MPItestMain()
{
m_UseXdg = UseXdg, m_DGorder = DGOrder
}) {
// create the test data
// ====================
BoSSS.Solution.Application.CommandLineOptions opts = null;
//opts = new BoSSS.Solution.Application.CommandLineOptions();
solver.Init(null, opts);
solver.RunSolverMode();
Stopwatch stw = new Stopwatch();
stw.Reset();
stw.Start();
BlockMsrMatrix M = solver.OperatorMatrix;
int[] Ilist1 = solver.ProblemMapping.GetSubvectorIndices(false, 0);
int[] Ilist2 = solver.ProblemMapping.GetSubvectorIndices(false, 1);
foreach (int i in Ilist1)
{
Assert.IsTrue(solver.ProblemMapping.IsInLocalRange(i));
}
foreach (int i in Ilist2)
{
Assert.IsTrue(solver.ProblemMapping.IsInLocalRange(i));
}
var Blk1 = solver.ProblemMapping.GetSubBlocking(Ilist1, csMPI.Raw._COMM.WORLD, compressL1 ? -1 : 0);
var Blk2 = solver.ProblemMapping.GetSubBlocking(Ilist2, csMPI.Raw._COMM.WORLD, compressL2 ? -1 : 0);
int[] Tlist1 = compressL1 ? default(int[]) : Blk1.GetOccupiedIndicesList();
int[] Tlist2 = compressL2 ? default(int[]) : Blk2.GetOccupiedIndicesList();
if (Tlist1 != null)
{
Assert.AreEqual(Tlist1.Length, Ilist1.Length);
foreach (int i in Tlist1)
{
Assert.IsTrue(Blk1.IsInLocalRange(i));
}
}
if (Tlist2 != null)
{
Assert.AreEqual(Tlist2.Length, Ilist2.Length);
foreach (int i in Tlist2)
{
Assert.IsTrue(Blk2.IsInLocalRange(i));
}
}
BlockMsrMatrix M11 = new BlockMsrMatrix(Blk1, Blk1);
BlockMsrMatrix M12 = new BlockMsrMatrix(Blk1, Blk2);
BlockMsrMatrix M21 = new BlockMsrMatrix(Blk2, Blk1);
BlockMsrMatrix M22 = new BlockMsrMatrix(Blk2, Blk2);
M.AccSubMatrixTo(1.0, M11, Ilist1, Tlist1, Ilist1, Tlist1);
M.AccSubMatrixTo(1.0, M12, Ilist1, Tlist1, Ilist2, Tlist2);
M.AccSubMatrixTo(1.0, M21, Ilist2, Tlist2, Ilist1, Tlist1);
M.AccSubMatrixTo(1.0, M22, Ilist2, Tlist2, Ilist2, Tlist2);
BlockMsrMatrix restored_M = new BlockMsrMatrix(M._RowPartitioning, M._ColPartitioning);
int[] Idx1 = compressL1 ? Blk1.LocalLength.ForLoop(i => i + Blk1.i0) : Tlist1;
int[] Idx2 = compressL2 ? Blk2.LocalLength.ForLoop(i => i + Blk2.i0) : Tlist2;
M11.AccSubMatrixTo(1.0, restored_M, Idx1, Ilist1, Idx1, Ilist1);
M12.AccSubMatrixTo(1.0, restored_M, Idx1, Ilist1, Idx2, Ilist2);
M21.AccSubMatrixTo(1.0, restored_M, Idx2, Ilist2, Idx1, Ilist1);
M22.AccSubMatrixTo(1.0, restored_M, Idx2, Ilist2, Idx2, Ilist2);
// test transpose-operator
var M_TT = M.Transpose().Transpose();
var M11_TT = M11.Transpose().Transpose();
var M12_TT = M12.Transpose().Transpose();
var M21_TT = M21.Transpose().Transpose();
var M22_TT = M22.Transpose().Transpose();
M_TT.Acc(-1.0, M);
M11_TT.Acc(-1.0, M11);
M12_TT.Acc(-1.0, M12);
M21_TT.Acc(-1.0, M21);
M22_TT.Acc(-1.0, M22);
double M_TT_norm = M_TT.InfNorm();
double M11_TT_norm = M11_TT.InfNorm();
double M12_TT_norm = M12_TT.InfNorm();
double M21_TT_norm = M21_TT.InfNorm();
double M22_TT_norm = M22_TT.InfNorm();
Assert.IsTrue(M_TT_norm == 0.0, "Transpose^2 is not identity.");
Assert.IsTrue(M11_TT_norm == 0.0, "Transpose^2 is not identity.");
Assert.IsTrue(M12_TT_norm == 0.0, "Transpose^2 is not identity.");
Assert.IsTrue(M21_TT_norm == 0.0, "Transpose^2 is not identity.");
Assert.IsTrue(M22_TT_norm == 0.0, "Transpose^2 is not identity.");
//M.SaveToTextFileSparse(@"C:\tmp\M.txt");
//M11.SaveToTextFileSparse(@"C:\tmp\M11.txt");
//M12.SaveToTextFileSparse(@"C:\tmp\M12.txt");
//M21.SaveToTextFileSparse(@"C:\tmp\M21.txt");
//M22.SaveToTextFileSparse(@"C:\tmp\M22.txt");
//restored_M.SaveToTextFileSparse(@"C:\tmp\Mr.txt");
stw.Stop();
using (var MatlabRef = new BatchmodeConnector()) {
MatlabRef.PutVector(Ilist1.Select(i => (double)i + 1.0).ToArray(), "Ilist1");
MatlabRef.PutVector(Ilist2.Select(i => (double)i + 1.0).ToArray(), "Ilist2");
MatlabRef.PutVector(Tlist1 == null ? Ilist1.Length.ForLoop(i => (double)i + 1.0 + Blk1.i0) : Tlist1.Select(i => (double)i + 1.0).ToArray(), "Tlist1");
MatlabRef.PutVector(Tlist2 == null ? Ilist2.Length.ForLoop(i => (double)i + 1.0 + Blk2.i0) : Tlist2.Select(i => (double)i + 1.0).ToArray(), "Tlist2");
MultidimensionalArray CheckRes = MultidimensionalArray.Create(1, 4);
MatlabRef.PutSparseMatrix(M, "M");
MatlabRef.PutSparseMatrix(M11, "M11");
MatlabRef.PutSparseMatrix(M12, "M12");
MatlabRef.PutSparseMatrix(M21, "M21");
MatlabRef.PutSparseMatrix(M22, "M22");
MatlabRef.Cmd("L1 = {0};", Blk1.TotalLength);
MatlabRef.Cmd("L2 = {0};", Blk2.TotalLength);
MatlabRef.Cmd("refM11 = sparse(L1, L1);");
MatlabRef.Cmd("refM12 = sparse(L1, L2);");
MatlabRef.Cmd("refM21 = sparse(L2, L1);");
MatlabRef.Cmd("refM22 = sparse(L2, L2);");
MatlabRef.Cmd("refM11(Tlist1, Tlist1) = M(Ilist1, Ilist1);");
MatlabRef.Cmd("refM12(Tlist1, Tlist2) = M(Ilist1, Ilist2);");
MatlabRef.Cmd("refM21(Tlist2, Tlist1) = M(Ilist2, Ilist1);");
MatlabRef.Cmd("refM22(Tlist2, Tlist2) = M(Ilist2, Ilist2);");
MatlabRef.Cmd("err11 = norm(refM11 - M11, inf);");
MatlabRef.Cmd("err12 = norm(refM12 - M12, inf);");
MatlabRef.Cmd("err21 = norm(refM21 - M21, inf);");
MatlabRef.Cmd("err22 = norm(refM22 - M22, inf);");
MatlabRef.Cmd("CheckRes = [err11, err12, err21, err22];");
MatlabRef.GetMatrix(CheckRes, "CheckRes");
MatlabRef.Execute();
Console.WriteLine("Matlab check 11: " + CheckRes[0, 0]);
Console.WriteLine("Matlab check 12: " + CheckRes[0, 1]);
Console.WriteLine("Matlab check 21: " + CheckRes[0, 2]);
Console.WriteLine("Matlab check 22: " + CheckRes[0, 3]);
Assert.IsTrue(CheckRes[0, 0] == 0.0);
Assert.IsTrue(CheckRes[0, 1] == 0.0);
Assert.IsTrue(CheckRes[0, 2] == 0.0);
Assert.IsTrue(CheckRes[0, 3] == 0.0);
}
stw.Start();
restored_M.Acc(-1.0, M);
double err = restored_M.InfNorm();
Console.WriteLine("Submatrix operations error: " + err);
Assert.IsTrue(err == 0.0);
restored_M.Clear();
restored_M.Acc(1.0, M);
IMutuableMatrixEx_Extensions.Acc(restored_M, -1.0, M);
double err2 = restored_M.InfNorm();
Console.WriteLine("Submatrix operations error: " + err2);
Assert.IsTrue(err2 == 0.0);
stw.Stop();
Console.WriteLine("Time spend in matrix operations: " + stw.Elapsed.TotalSeconds + " sec.");
TotTime_MatrixOp += stw.Elapsed;
}
}
/// <summary>
///
/// </summary>
public void AnalyzeOperators(out MultidimensionalArray ret)
{
int length = OpMatrix.NoOfRows / Extension.Basis.Length;
//int[,] PatternMatrix = new int[length, length]; // lässt sich besser anschauen?
MsrMatrix PatternMatrix = new MsrMatrix(length);
for (int i = 0; i < length; i++)
{
for (int j = 0; j < length; j++)
{
if (OpMatrix[i * Extension.Basis.Length, j *Extension.Basis.Length] != 0)
{
PatternMatrix[i, j] = 1;
}
}
}
ret = MultidimensionalArray.Create(1, 4);
Console.WriteLine("Calling MATLAB/Octave...");
MultidimensionalArray L = MultidimensionalArray.Create(PatternMatrix.NoOfRows, PatternMatrix.NoOfRows);
MultidimensionalArray U = MultidimensionalArray.Create(PatternMatrix.NoOfRows, PatternMatrix.NoOfRows);
MultidimensionalArray P = MultidimensionalArray.Create(PatternMatrix.NoOfRows, PatternMatrix.NoOfRows);
using (BatchmodeConnector bmc = new BatchmodeConnector()) {
bmc.PutSparseMatrix(PatternMatrix, "PatternMatrix");
bmc.Cmd("[L, U, P] = lu(PatternMatrix);");
bmc.PutSparseMatrix(OpMatrix, "OpMatrix");
bmc.Cmd("condNoOpMatrix = condest(OpMatrix);");
bmc.Cmd("eigiMaxi = eigs(OpMatrix,1,'lm')");
bmc.Cmd("eigiMini = eigs(OpMatrix,1,'sm')");
bmc.Cmd("lasterr");
bmc.Cmd("[V,r]=chol(OpMatrix);");
bmc.Cmd("ret = [condNoOpMatrix, eigiMaxi, eigiMini, r]");
bmc.GetMatrix(L, "full(L)");
bmc.GetMatrix(U, "full(U)");
bmc.GetMatrix(P, "full(P)");
bmc.GetMatrix(ret, "ret");
bmc.Execute(true);
}
//PatternMatrix.SaveToTextFile("Patternmatrix.txt");
//PatternMatrix.SaveToTextFileSparse("PatternmatrixSparse.txt");
double condNoOpMatrix = ret[0, 0];
double eigiMaxi = ret[0, 1];
double eigiMini = ret[0, 2];
double posDef = ret[0, 3] == 0 ? 1 : 0;
Console.WriteLine("Condition number operator: {0:0.####E-00}", condNoOpMatrix);
if (posDef == 0.0)
{
Console.WriteLine("WARNING: Operator matrix is not positive definite.");
}
else
{
Console.WriteLine("Good news: Operator matrix seems to be positive definite.");
}
}
public static void MultiplyTest(
[Values(XDGusage.none, XDGusage.mixed1, XDGusage.mixed2, XDGusage.all)] XDGusage UseXdg,
[Values(1, 3)] int DGOrder,
[Values(false, true)] bool compressL1,
[Values(false, true)] bool compressL2)
{
unsafe
{
int[] Params = new int[8], ParamsGlob = new int[8];
fixed(int *pParams = Params, pParamsGlob = ParamsGlob)
{
pParams[0] = (int)UseXdg;
pParams[1] = DGOrder;
pParams[2] = compressL1 ? 1 : 0;
pParams[3] = compressL2 ? 1 : 0;
pParams[4] = -pParams[0];
pParams[5] = -pParams[1];
pParams[6] = -pParams[2];
pParams[7] = -pParams[3];
csMPI.Raw.Allreduce((IntPtr)pParams, (IntPtr)pParamsGlob, 8, csMPI.Raw._DATATYPE.INT, csMPI.Raw._OP.MIN, csMPI.Raw._COMM.WORLD);
}
int[] ParamsMin = ParamsGlob.GetSubVector(0, 4);
int[] ParamsMax = ParamsGlob.GetSubVector(4, 4);
for (int i = 0; i < 4; i++)
{
if (Params[i] != ParamsMin[i])
{
throw new ApplicationException();
}
if (Params[i] != -ParamsMax[i])
{
throw new ApplicationException();
}
}
Console.WriteLine("MultiplyTest({0},{1},{2},{3})", UseXdg, DGOrder, compressL1, compressL2);
}
using (var solver = new Matrix_MPItestMain()
{
m_UseXdg = UseXdg, m_DGorder = DGOrder
}) {
// create the test data
// ====================
solver.Init(null);
solver.RunSolverMode();
Stopwatch stw = new Stopwatch();
stw.Reset();
stw.Start();
BlockMsrMatrix M = solver.OperatorMatrix;
int[] Ilist1 = solver.ProblemMapping.GetSubvectorIndices(false, 0);
int[] Ilist2 = solver.ProblemMapping.GetSubvectorIndices(false, 1);
foreach (int i in Ilist1)
{
Assert.IsTrue(solver.ProblemMapping.IsInLocalRange(i));
}
foreach (int i in Ilist2)
{
Assert.IsTrue(solver.ProblemMapping.IsInLocalRange(i));
}
var Blk1 = solver.ProblemMapping.GetSubBlocking(Ilist1, csMPI.Raw._COMM.WORLD, compressL1 ? -1 : 0);
var Blk2 = solver.ProblemMapping.GetSubBlocking(Ilist2, csMPI.Raw._COMM.WORLD, compressL2 ? -1 : 0);
int[] Tlist1 = compressL1 ? default(int[]) : Blk1.GetOccupiedIndicesList();
int[] Tlist2 = compressL2 ? default(int[]) : Blk2.GetOccupiedIndicesList();
if (Tlist1 != null)
{
Assert.AreEqual(Tlist1.Length, Ilist1.Length);
foreach (int i in Tlist1)
{
Assert.IsTrue(Blk1.IsInLocalRange(i));
}
}
if (Tlist2 != null)
{
Assert.AreEqual(Tlist2.Length, Ilist2.Length);
foreach (int i in Tlist2)
{
Assert.IsTrue(Blk2.IsInLocalRange(i));
}
}
BlockMsrMatrix M11 = new BlockMsrMatrix(Blk1, Blk1);
BlockMsrMatrix M12 = new BlockMsrMatrix(Blk1, Blk2);
BlockMsrMatrix M21 = new BlockMsrMatrix(Blk2, Blk1);
BlockMsrMatrix M22 = new BlockMsrMatrix(Blk2, Blk2);
M.AccSubMatrixTo(1.0, M11, Ilist1, Tlist1, Ilist1, Tlist1);
M.AccSubMatrixTo(1.0, M12, Ilist1, Tlist1, Ilist2, Tlist2);
M.AccSubMatrixTo(1.0, M21, Ilist2, Tlist2, Ilist1, Tlist1);
M.AccSubMatrixTo(1.0, M22, Ilist2, Tlist2, Ilist2, Tlist2);
/*
* MultidimensionalArray CheckRes2 = MultidimensionalArray.Create(1, 4);
* using (var MatlabRef = new BatchmodeConnector()) {
*
* MatlabRef.PutVector(Ilist1.Select(i => (double)i + 1.0).ToArray(), "Ilist1");
* MatlabRef.PutVector(Ilist2.Select(i => (double)i + 1.0).ToArray(), "Ilist2");
* MatlabRef.PutVector(Tlist1 == null ? Ilist1.Length.ForLoop(i => (double)i + 1.0 + Blk1.i0) : Tlist1.Select(i => (double)i + 1.0).ToArray(), "Tlist1");
* MatlabRef.PutVector(Tlist2 == null ? Ilist2.Length.ForLoop(i => (double)i + 1.0 + Blk2.i0) : Tlist2.Select(i => (double)i + 1.0).ToArray(), "Tlist2");
*
* MatlabRef.PutSparseMatrix(solver.AltOperatorMatrix, "M");
*
*
* MatlabRef.Cmd("L1 = {0};", Blk1.TotalLength);
* MatlabRef.Cmd("L2 = {0};", Blk2.TotalLength);
* //MatlabRef.Cmd("refM11 = sparse(L1, L1);");
* //MatlabRef.Cmd("refM12 = sparse(L1, L2);");
* MatlabRef.Cmd("refM21 = sparse(L2, L1);");
* //MatlabRef.Cmd("refM22 = sparse(L2, L2);");
*
* //MatlabRef.Cmd("refM11(Tlist1, Tlist1) = M(Ilist1, Ilist1);");
* //MatlabRef.Cmd("refM12(Tlist1, Tlist2) = M(Ilist1, Ilist2);");
* MatlabRef.Cmd("refM21(Tlist2, Tlist1) = M(Ilist2, Ilist1);");
* //MatlabRef.Cmd("refM22(Tlist2, Tlist2) = M(Ilist2, Ilist2);");
*
* //MatlabRef.Cmd("err11 = norm(refM11 - M11, inf);");
* //MatlabRef.Cmd("err12 = norm(refM12 - M12, inf);");
* //MatlabRef.Cmd("err21 = norm(refM21 - M21, inf);");
* //MatlabRef.Cmd("err22 = norm(refM22 - M22, inf);");
*
* MatlabRef.Cmd("CheckRes = [refM21(1339, 1321), 0.0, 1.567, 0 ];");
* MatlabRef.GetMatrix(CheckRes2, "CheckRes");
*
* MatlabRef.Execute();
* }
*/
// test multipliation (later verified by matlab)
BlockMsrMatrix M11xM12 = new BlockMsrMatrix(M11._RowPartitioning, M12._ColPartitioning);
M11xM12.Acc(1.0, M12);
BlockMsrMatrix.Multiply(M11xM12, M11, M12);
BlockMsrMatrix M22xM21 = new BlockMsrMatrix(M22._RowPartitioning, M21._ColPartitioning);
BlockMsrMatrix.Multiply(M22xM21, M22, M21);
double ProdNorm = M22xM21.InfNorm();
stw.Stop();
//M.SaveToTextFileSparse(@"C:\tmp\M.txt");
//M11.SaveToTextFileSparse(@"C:\tmp\M11.txt");
//M12.SaveToTextFileSparse(@"C:\tmp\M12.txt");
//M21.SaveToTextFileSparse(@"C:\tmp\M21.txt");
//M22.SaveToTextFileSparse(@"C:\tmp\M22.txt");
//M22xM21.SaveToTextFileSparse(@"C:\tmp\M22xM21.txt");
using (var MatlabRef = new BatchmodeConnector()) {
MultidimensionalArray CheckRes = MultidimensionalArray.Create(1, 4);
MatlabRef.PutSparseMatrix(M11, "M11");
MatlabRef.PutSparseMatrix(M12, "M12");
MatlabRef.PutSparseMatrix(M21, "M21");
MatlabRef.PutSparseMatrix(M22, "M22");
MatlabRef.PutSparseMatrix(M11xM12, "M11xM12");
MatlabRef.PutSparseMatrix(M22xM21, "M22xM21");
MatlabRef.Cmd("refM11xM12 = M12 + M11*M12;");
MatlabRef.Cmd("refM22xM21 = M22*M21;");
MatlabRef.Cmd("err1112 = norm(refM11xM12 - M11xM12, inf);");
MatlabRef.Cmd("err2221 = norm(refM22xM21 - M22xM21, inf);");
MatlabRef.Cmd("CheckRes = [err1112, err2221, 0, 0];");
MatlabRef.GetMatrix(CheckRes, "CheckRes");
MatlabRef.Execute();
Console.WriteLine("Matlab check M11*M12: " + CheckRes[0, 0]);
Console.WriteLine("Matlab check M22*M21: " + CheckRes[0, 1]);
Assert.IsTrue(CheckRes[0, 0] == 0.0);
Assert.IsTrue(CheckRes[0, 1] < 1.0e-10 * ProdNorm);
//Assert.IsTrue(CheckRes[0, 2] == 0.0);
//Assert.IsTrue(CheckRes[0, 3] == 0.0);
}
Console.WriteLine("Time spend in matrix operations: " + stw.Elapsed.TotalSeconds + " sec.");
TotTime_MatrixOp += stw.Elapsed;
}
}
/// <summary>
/// Spatial operator matrix analysis method
/// </summary>
public void SpatialOperatorMatrixAnalysis(bool CheckAssertions, int AnalysisLevel)
{
using (var solver = new Rheology()) {
int D = solver.Grid.SpatialDimension;
if (AnalysisLevel < 0 || AnalysisLevel > 2)
{
throw new ArgumentException();
}
BlockMsrMatrix OpMatrix;
double[] OpAffine;
solver.AssembleMatrix(out OpMatrix, out OpAffine, solver.CurrentSolution.Mapping.ToArray(), true);
// =============================
// AnalysisLevel 0
// =============================
{
var OpMatrixT = OpMatrix.Transpose();
CoordinateVector TestVec = new CoordinateVector(solver.CurrentSolution.Mapping.Fields.Select(f => f.CloneAs()).ToArray());
double testsumPos = 0.0;
double testsumNeg = 0.0;
for (int rnd_seed = 0; rnd_seed < 20; rnd_seed++)
{
// fill the pressure components of the test vector
TestVec.Clear();
Random rnd = new Random(rnd_seed);
DGField Pressack = TestVec.Mapping.Fields[D] as DGField;
int J = solver.GridData.iLogicalCells.NoOfLocalUpdatedCells;
for (int j = 0; j < J; j++)
{
int N = Pressack.Basis.GetLength(j);
for (int n = 0; n < N; n++)
{
Pressack.Coordinates[j, n] = rnd.NextDouble();
}
}
// Gradient times P:
double[] R1 = new double[TestVec.Count];
OpMatrix.SpMV(1.0, TestVec, 0.0, R1); // R1 = Grad * P
//Console.WriteLine("L2 of 'Grad * P': " + R1.L2Norm());
// transpose of Divergence times P:
double[] R2 = new double[TestVec.Count];
OpMatrix.SpMV(1.0, TestVec, 0.0, R2); // R2 = divT * P
//Console.WriteLine("L2 of 'divT * P': " + R2.L2Norm());
TestVec.Clear();
TestVec.Acc(1.0, R1);
TestVec.Acc(1.0, R2);
// analyze!
testsumNeg += GenericBlas.L2Dist(R1, R2);
R2.ScaleV(-1.0);
testsumPos += GenericBlas.L2Dist(R1, R2);
}
Console.WriteLine("Pressure/Divergence Symmetry error in all tests (+): " + testsumPos);
Console.WriteLine("Pressure/Divergence Symmetry error in all tests (-): " + testsumNeg);
if (CheckAssertions)
{
Assert.LessOrEqual(Math.Abs(testsumNeg), testsumPos * 1.0e-13);
}
}
// =============================
// AnalysisLevel 1 and 2
// =============================
if (AnalysisLevel > 0)
{
AggregationGridBasis[][] MgBasis = AggregationGridBasis.CreateSequence(solver.MultigridSequence, solver.CurrentSolution.Mapping.BasisS);
MultigridOperator mgOp = new MultigridOperator(MgBasis, solver.CurrentSolution.Mapping, OpMatrix, null, solver.MultigridOperatorConfig);
// extract
////////////
MsrMatrix FullMatrix = mgOp.OperatorMatrix.ToMsrMatrix();
MsrMatrix DiffMatrix;
{
int[] VelVarIdx = D.ForLoop(d => d);
int[] USubMatrixIdx_Row = mgOp.Mapping.GetSubvectorIndices(VelVarIdx);
int[] USubMatrixIdx_Col = mgOp.Mapping.GetSubvectorIndices(VelVarIdx);
int L = USubMatrixIdx_Row.Length;
DiffMatrix = new MsrMatrix(L, L, 1, 1);
FullMatrix.WriteSubMatrixTo(DiffMatrix, USubMatrixIdx_Row, default(int[]), USubMatrixIdx_Col, default(int[]));
double DiffMatrix_sd = DiffMatrix.SymmetryDeviation();
Console.WriteLine("Diffusion assymetry:" + DiffMatrix_sd);
}
MsrMatrix SaddlePointMatrix;
{
int[] VelPVarIdx = new int[] { 0, 1, 2 };
int[] VelPSubMatrixIdx_Row = mgOp.Mapping.GetSubvectorIndices(VelPVarIdx);
int[] VelPSubMatrixIdx_Col = mgOp.Mapping.GetSubvectorIndices(VelPVarIdx);
int L = VelPSubMatrixIdx_Row.Length;
SaddlePointMatrix = new MsrMatrix(L, L, 1, 1);
FullMatrix.WriteSubMatrixTo(SaddlePointMatrix, VelPSubMatrixIdx_Row, default(int[]), VelPSubMatrixIdx_Col, default(int[]));
}
//SaddlePointMatrix.SaveToTextFileSparse("C:\\Users\\kikker\\Documents\\MATLAB\\spm.txt");
MsrMatrix ConstitutiveMatrix;
{
int[] StressVarIdx = new int[] { 3, 4, 5 };
int[] StressSubMatrixIdx_Row = mgOp.Mapping.GetSubvectorIndices(StressVarIdx);
int[] StressSubMatrixIdx_Col = mgOp.Mapping.GetSubvectorIndices(StressVarIdx);
int L = StressSubMatrixIdx_Row.Length;
ConstitutiveMatrix = new MsrMatrix(L, L, 1, 1);
FullMatrix.WriteSubMatrixTo(ConstitutiveMatrix, StressSubMatrixIdx_Row, default(int[]), StressSubMatrixIdx_Col, default(int[]));
}
// operator analysis
//////////////////////
bool posDef;
if (AnalysisLevel > 1)
{
// +++++++++++++++++++++++++++++++
// check condition number, etc
// +++++++++++++++++++++++++++++++
MultidimensionalArray ret = MultidimensionalArray.Create(1, 5);
Console.WriteLine("Calling MATLAB/Octave...");
using (BatchmodeConnector bmc = new BatchmodeConnector()) {
bmc.PutSparseMatrix(FullMatrix, "FullMatrix");
bmc.PutSparseMatrix(SaddlePointMatrix, "SaddlePointMatrix");
bmc.PutSparseMatrix(ConstitutiveMatrix, "ConstitutiveMatrix");
bmc.PutSparseMatrix(DiffMatrix, "DiffMatrix");
bmc.Cmd("DiffMatrix = 0.5*(DiffMatrix + DiffMatrix');");
bmc.Cmd("condNoFullMatrix = condest(FullMatrix);");
bmc.Cmd("condNoSaddlePointMatrix = condest(SaddlePointMatrix);");
bmc.Cmd("condNoConstitutiveMatrix = condest(ConstitutiveMatrix);");
bmc.Cmd("condNoDiffMatrix = condest(DiffMatrix);");
//bmc.Cmd("eigiMaxiSaddle = 1.0; % eigs(SaddlePointMatrix,1,'lm')");
//bmc.Cmd("eigiMiniSaddle = 1.0; % eigs(SaddlePointMatrix,1,'sm')");
//bmc.Cmd("eigiMaxiConst = 1.0; % eigs(ConstitutiveMatrix,1,'lm')");
//bmc.Cmd("eigiMiniConst = 1.0; % eigs(ConstitutiveMatrix,1,'sm')");
//bmc.Cmd("eigiMaxiDiff = 1.0; % eigs(DiffMatrix,1,'lm')");
//bmc.Cmd("eigiMiniDiff = 1.0; % eigs(DiffMatrix,1,'sm')");
bmc.Cmd("lasterr");
bmc.Cmd("[V,r]=chol(SaddlePointMatrix);");
bmc.Cmd("[V,r]=chol(ConstitutiveMatrix);");
bmc.Cmd("ret = [condNoFullMatrix, condNoSaddlePointMatrix, condNoConstitutiveMatrix, condNoDiffMatrix, r]"); //eigiMaxiSaddle, eigiMiniSaddle, eigiMaxiConst, eigiMiniConst, eigiMaxiDiff, eigiMiniDiff,
bmc.GetMatrix(ret, "ret");
bmc.Execute(false);
}
double condNoFullMatrix = ret[0, 0];
double condNoSaddlePMatrix = ret[0, 1];
double condNoConstitutiveMatrix = ret[0, 2];
double condNoDiffMatrix = ret[0, 3];
//double eigiMaxiSaddle = ret[0, 4];
//double eigiMiniSaddle = ret[0, 5];
//double eigiMaxiConst = ret[0, 6];
//double eigiMiniConst = ret[0, 7];
//double eigiMaxiDiff = ret[0, 8];
//double eigiMiniDiff = ret[0, 9];
posDef = ret[0, 4] == 0;
//Console.WriteLine("Eigenvalue range of saddle point matrix: {0} to {1}", eigiMiniSaddle, eigiMaxiSaddle);
//Console.WriteLine("Eigenvalue range of constitutive matrix: {0} to {1}", eigiMiniConst, eigiMaxiConst);
//Console.WriteLine("Eigenvalue range of diffusion matrix: {0} to {1}", eigiMiniDiff, eigiMaxiDiff);
Console.WriteLine("Condition number full operator: {0:0.####E-00}", condNoFullMatrix);
Console.WriteLine("Condition number saddle point operator: {0:0.####E-00}", condNoSaddlePMatrix);
Console.WriteLine("Condition number constitutive operator: {0:0.####E-00}", condNoConstitutiveMatrix);
Console.WriteLine("Condition number diffusion operator: {0:0.####E-00}", condNoDiffMatrix);
//base.QueryHandler.ValueQuery("ConditionNumber", condNoFullMatrix);
}
else
{
// +++++++++++++++++++++++++++++++++++++++
// test only for positive definiteness
// +++++++++++++++++++++++++++++++++++++++
var SaddlePMatrixFull = SaddlePointMatrix.ToFullMatrixOnProc0();
var ConstMatrixFull = ConstitutiveMatrix.ToFullMatrixOnProc0();
posDef = true;
try {
SaddlePMatrixFull.Cholesky();
} catch (ArithmeticException) {
posDef = false;
}
posDef = true;
try {
ConstMatrixFull.Cholesky();
} catch (ArithmeticException) {
posDef = false;
}
}
double SaddlePSymm = SaddlePointMatrix.SymmetryDeviation();
Console.WriteLine("Symmetry deviation of saddle point matrix: " + SaddlePSymm);
if (posDef)
{
Console.WriteLine("Good news: Saddle point operator matrix seems to be positive definite.");
}
else
{
Console.WriteLine("WARNING: Saddle point operator matrix is not positive definite.");
}
double ConstSymm = ConstitutiveMatrix.SymmetryDeviation();
Console.WriteLine("Symmetry deviation of constitutive matrix: " + ConstSymm);
if (posDef)
{
Console.WriteLine("Good news: constitutive operator matrix seems to be positive definite.");
}
else
{
Console.WriteLine("WARNING: constitutive operator matrix is not positive definite.");
}
//if (CheckAssertions) {
// if (Control.AdvancedDiscretizationOptions.ViscosityMode == ViscosityMode.FullySymmetric && Control.PhysicalParameters.IncludeConvection == false) {
// Assert.IsTrue(posDef, "Positive definiteness test failed.");
// double compVal = DiffMatrix.InfNorm() * 1e-13;
// Assert.LessOrEqual(DiffSymm, compVal, "Diffusion matrix seems to be non-symmetric.");
// }
//}
}
}
}
public void Solve <U, V>(U X, V B)
where U : IList <double>
where V : IList <double>
{
var Bu = new double[Uidx.Length];
var Xu = Bu.CloneAs();
Bu = B.GetSubVector(Uidx, default(int[]));
var Bp = new double[Pidx.Length];
var Xp = Bp.CloneAs();
Bp = B.GetSubVector(Pidx, default(int[]));
Xu = X.GetSubVector(Uidx, default(int[]));
Xp = X.GetSubVector(Pidx, default(int[]));
P = new BlockMsrMatrix(null, null);// Pidx.Length, Pidx.Length); //
MultidimensionalArray Schur = MultidimensionalArray.Create(Pidx.Length, Pidx.Length);
using (BatchmodeConnector bmc = new BatchmodeConnector()) {
bmc.PutSparseMatrix(LocalMatrix, "LocalMatrix");
bmc.PutSparseMatrix(divVel, "divVel");
bmc.PutSparseMatrix(pGrad, "pGrad");
bmc.Cmd("invLocalMatrix = inv(full(LocalMatrix))");
bmc.Cmd("Poisson = invLocalMatrix*pGrad");
bmc.Cmd("Schur= divVel*Poisson");
bmc.GetMatrix(Schur, "Schur");
bmc.Execute(false);
}
P = null; // Schur.ToMsrMatrix();
//P.SaveToTextFileSparse("LocalSchur");
using (var solver = new ilPSP.LinSolvers.MUMPS.MUMPSSolver()) {
solver.DefineMatrix(P);
solver.Solve(Xp, Bp);
}
//var temp2 = Xp.CloneAs();
//LocalMatrix.SpMV(1, Xp, 0, temp2);
//using (var solver = new ilPSP.LinSolvers.MUMPS.MUMPSSolver())
//{
// solver.DefineMatrix(divVel);
// solver.Solve(Xp, temp2);
//}
// Solve ConvD iff*w=v-q*pGrad
pGrad.SpMV(-1, Xp, 1, Bu);
using (var solver = new ilPSP.LinSolvers.MUMPS.MUMPSSolver()) {
solver.DefineMatrix(ConvDiff);
solver.Solve(Xu, Bu);
}
var temp = new double[Uidx.Length + Pidx.Length];
for (int i = 0; i < Uidx.Length; i++)
{
temp[Uidx[i]] = Xu[i];
}
for (int i = 0; i < Pidx.Length; i++)
{
temp[Pidx[i]] = Xp[i];
}
X.SetV(temp);
m_ThisLevelIterations++;
}
/// <summary>
/// According to the Rouché-Capelli theorem, the system is inconsistent if rank(augMatrix) > rank(Matrix).
/// If rank(augMatrix) == rank(Matrix), the system has at least one solution.
/// Additionally, if the rank is equal to the number of variables, the solution of the system is unique.
/// Remark: This requires the whole RHS not only local!!!
/// </summary>
/// <param name="OpMatrix"></param>
/// <param name="RHS"></param>
public void rankAnalysis(BlockMsrMatrix OpMatrix, double[] RHS)
{
int RHSlen = this.localRHS.Length;
Debug.Assert(RHSlen == m_OpMtx.RowPartitioning.LocalLength);
MultidimensionalArray outputArray = MultidimensionalArray.Create(2, 1); // The two rank values
//At this point OpMatrix and RHS are local, they are collected within bmc on proc rank==0
using (var bmc = new BatchmodeConnector()){
bmc.PutSparseMatrix(OpMatrix, "OpMatrix");
bmc.PutVector(RHS, "RHS");
bmc.Cmd("output = zeros(2,1)"); // First value is rank(OpMatrix), second the rank of the augmented matrix = rank([Matrix|RHS])
bmc.Cmd("");
bmc.Cmd("fullMtx = full(OpMatrix);");
bmc.Cmd("augmentedMtx = [fullMtx RHS];");
bmc.Cmd("output(1) = rank(fullMtx)");
bmc.Cmd("output(2) = rank(augmentedMtx)");
bmc.GetMatrix(outputArray, "output");
bmc.Execute(false);
}
double[] output = new double[2];
output[0] = outputArray[0, 0]; //Rank matrix
output[1] = outputArray[1, 0]; //Rank augmented matrix ( [Matrix|RHS])
double rnkMtx = output[0];
double rnkAugmentedMtx = output[1];
// Some tests
Console.WriteLine("==================================================================");
//Output
{
Console.WriteLine("Results of rank analysis:");
if (rnkAugmentedMtx > rnkMtx)
{
//throw new Exception("The rank of the augmented matrix shouldn't be greater than the one of the original matrix!!");
Console.WriteLine("======================================================");
Console.WriteLine("WARNING!!!!!!! The rank of the augmented matrix shouldn't be greater than the one of the original matrix!!");
Console.WriteLine("This means that the system doesnt have a solution!");
}
if (rnkAugmentedMtx == rnkMtx)
{
Console.WriteLine("The system has at least a solution");
}
//RHS and OpMatrix will be collected in Bmc, so total length has to be considered for RHS: RHS.length will lead to errors in parallel execution
if (rnkMtx < RHSlen)
{
Console.WriteLine("The rank of the matrix is smaller than the number of variables. There are {0} free parameters", (RHS.Length - rnkMtx));
}
else if (rnkMtx == RHSlen)
{
Console.WriteLine("The system has a unique solution :) ");
}
else
{
throw new Exception("what? should not happen");
}
Console.WriteLine("Rank of the matrix : {0} \n" + "Rank of the augmented matrix : {1} \n" + "Number of variables: {2}", output[0], output[1], RHS.Length);
Console.WriteLine("==================================================================");
}
Debug.Assert(output[0].MPIEquals(), "value does not match on procs");
Debug.Assert(output[1].MPIEquals(), "value does not match on procs");
}
/// <summary>
/// Test on a 2D Voronoi mesh
/// </summary>
/// <param name="Res">
/// number of randomly chosen Delaunay vertices
/// </param>
/// <param name="deg">
/// polynomial degree
/// </param>
/// <param name="solver_name">
/// Name of solver to use.
/// </param>
public static SipControl TestVoronoi(int Res, SolverCodes solver_name = SolverCodes.classic_pardiso, int deg = 3)
{
if (System.Environment.MachineName.ToLowerInvariant().EndsWith("rennmaschin")
//|| System.Environment.MachineName.ToLowerInvariant().Contains("jenkins")
)
{
// This is Florians Laptop;
// he is to poor to afford MATLAB, so he uses OCTAVE
BatchmodeConnector.Flav = BatchmodeConnector.Flavor.Octave;
BatchmodeConnector.MatlabExecuteable = "C:\\cygwin64\\bin\\bash.exe";
}
var R = new SipControl();
R.ProjectName = "SipPoisson-Voronoi";
R.SessionName = "testrun";
R.savetodb = false;
R.FieldOptions.Add("T", new FieldOpts()
{
Degree = deg, SaveToDB = FieldOpts.SaveToDBOpt.TRUE
});
R.FieldOptions.Add("Tex", new FieldOpts()
{
Degree = deg * 2
});
R.InitialValues_Evaluators.Add("RHS", X => 1.0);
R.InitialValues_Evaluators.Add("Tex", X => 0.0);
R.ExactSolution_provided = false;
R.NoOfMultigridLevels = int.MaxValue;
R.solver_name = solver_name;
//R.TargetBlockSize = 100;
bool IsIn(params double[] X)
{
Debug.Assert(X.Length == 2);
double xi = X[0];
double yi = X[1];
//for(int l = 0; l < bndys.Length; l++) {
// Debug.Assert(bndys[l].Normal.Length == 2);
// if (bndys[l].PointDistance(xi, yi) > 0.0)
// return false;
//}
if (xi > 1.0)
{
return(false);
}
if (yi > 1.0)
{
return(false);
}
if (xi < 0 && yi < 0)
{
return(false);
}
if (xi < -1)
{
return(false);
}
if (yi < -1)
{
return(false);
}
return(true);
}
int Mirror(ref double[] _x, ref double[] _y, AffineManifold[] bndys)
{
if (_x.Length != _y.Length)
{
throw new ArgumentException();
}
var x = _x.ToList();
var y = _y.ToList();
int N = _x.Length;
// filter all points that are outside of the domain
for (int n = 0; n < N; n++)
{
if (!IsIn(x[n], y[n]))
{
x.RemoveAt(n);
y.RemoveAt(n);
N--;
n--;
}
}
Debug.Assert(x.Count == N);
Debug.Assert(y.Count == N);
for (int n = 0; n < N; n++)
{
Debug.Assert(IsIn(x[n], y[n]));
}
// mirror each point
for (int n = 0; n < N; n++)
{
double xn = x[n];
double yn = y[n];
for (int l = 0; l < bndys.Length; l++)
{
var bndy_l = bndys[l];
double dist = bndy_l.PointDistance(xn, yn);
if (dist < 0)
{
double xMirr = xn - bndy_l.Normal[0] * dist * 2;
double yMirr = yn - bndy_l.Normal[1] * dist * 2;
Debug.Assert(bndy_l.PointDistance(xMirr, yMirr) > 0);
if (!IsIn(xMirr, yMirr))
{
x.Add(xMirr);
y.Add(yMirr);
}
}
}
}
// return
_x = x.ToArray();
_y = y.ToArray();
return(N);
}
GridCommons GridFunc()
{
GridCommons grd = null;
var Matlab = new BatchmodeConnector();
// boundaries for L-domain
AffineManifold[] Boundaries = new AffineManifold[6];
Boundaries[0] = new AffineManifold(new[] { 0.0, 1.0 }, new[] { 0.0, 1.0 });
Boundaries[1] = new AffineManifold(new[] { 1.0, 0.0 }, new[] { 1.0, 0.0 });
Boundaries[2] = new AffineManifold(new[] { -1.0, 0.0 }, new[] { -1.0, 0.0 });
Boundaries[3] = new AffineManifold(new[] { -1.0, 0.0 }, new[] { 0.0, 0.0 });
Boundaries[4] = new AffineManifold(new[] { 0.0, -1.0 }, new[] { 0.0, -1.0 });
Boundaries[5] = new AffineManifold(new[] { 0.0, -1.0 }, new[] { 0.0, 0.0 });
// generate Delaunay vertices
Random rnd = new Random(0);
double[] xNodes = Res.ForLoop(idx => rnd.NextDouble() * 2 - 1);
double[] yNodes = Res.ForLoop(idx => rnd.NextDouble() * 2 - 1);
int ResFix = Mirror(ref xNodes, ref yNodes, Boundaries);
var Nodes = MultidimensionalArray.Create(xNodes.Length, 2);
Nodes.SetColumn(0, xNodes);
Nodes.SetColumn(1, yNodes);
Matlab.PutMatrix(Nodes, "Nodes");
// compute Voronoi diagramm
Matlab.Cmd("[V, C] = voronoin(Nodes);");
// output (export from matlab)
int[][] OutputVertexIndex = new int[Nodes.NoOfRows][];
Matlab.GetStaggeredIntArray(OutputVertexIndex, "C");
Matlab.GetMatrix(null, "V");
// run matlab
Matlab.Execute(false);
// import here
MultidimensionalArray VertexCoordinates = (MultidimensionalArray)(Matlab.OutputObjects["V"]);
// correct indices (1-based index to 0-based index)
foreach (int[] cell in OutputVertexIndex)
{
int K = cell.Length;
for (int k = 0; k < K; k++)
{
cell[k]--;
}
}
// tessellation
List <Cell> cells = new List <Cell>();
List <int[]> aggregation = new List <int[]>();
for (int jV = 0; jV < ResFix; jV++) // loop over Voronoi Cells
{
Debug.Assert(IsIn(Nodes.GetRow(jV)));
int[] iVtxS = OutputVertexIndex[jV];
int NV = iVtxS.Length;
List <int> Agg2Pt = new List <int>();
for (int iTri = 0; iTri < NV - 2; iTri++) // loop over triangles of voronoi cell
{
int iV0 = iVtxS[0];
int iV1 = iVtxS[iTri + 1];
int iV2 = iVtxS[iTri + 2];
double[] V0 = VertexCoordinates.GetRow(iV0);
double[] V1 = VertexCoordinates.GetRow(iV1);
double[] V2 = VertexCoordinates.GetRow(iV2);
double[] D1 = V1.Minus(V0);
double[] D2 = V2.Minus(V0);
Debug.Assert(D1.CrossProduct2D(D2).Abs() > 1.0e-8);
if (D1.CrossProduct2D(D2) < 0)
{
double[] T = V2;
int t = iV2;
V2 = V1;
iV2 = iV1;
V1 = T;
iV1 = t;
}
double[] Center = V0.Plus(V1).Plus(V2).Mul(1.0 / 3.0);
//Debug.Assert(IsIn(Center[0], Center[1]));
Cell Cj = new Cell();
Cj.GlobalID = cells.Count;
Cj.Type = CellType.Triangle_3;
Cj.TransformationParams = MultidimensionalArray.Create(3, 2);
Cj.NodeIndices = new int[] { iV0, iV1, iV2 };
Cj.TransformationParams.SetRow(0, V0);
Cj.TransformationParams.SetRow(1, V1);
Cj.TransformationParams.SetRow(2, V2);
Agg2Pt.Add(cells.Count);
cells.Add(Cj);
}
aggregation.Add(Agg2Pt.ToArray());
}
// return grid
grd = new Grid2D(Triangle.Instance);
grd.Cells = cells.ToArray();
grd.EdgeTagNames.Add(1, BoundaryType.Dirichlet.ToString());
grd.DefineEdgeTags(X => (byte)1);
//grd.Plot2DGrid();
// create aggregation grid
//var agrd = new AggregationGrid(grd, aggregation.ToArray());
return(grd);
};
R.GridFunc = GridFunc;
R.AddBoundaryValue(BoundaryType.Dirichlet.ToString(), "T",
delegate(double[] X) {
//double x = X[0], y = X[1];
return(0.0);
//if(Math.Abs(X[0] - (0.0)) < 1.0e-8)
// return 0.0;
//
//throw new ArgumentOutOfRangeException();
});
return(R);
}
/// <summary>
/// returns the condition number of the full matrix and the inner matrix without boundary terms
/// </summary>
/// <returns>Array condestOut=[ConditionNumberFullOp, ConditionNumberInnerOp]</returns>
public double[] CondNum()
{
int[] DepVars = this.VarGroup;
var grd = m_map.GridDat;
int NoOfCells = grd.Grid.NumberOfCells;
int NoOfBdryCells = grd.GetBoundaryCells().NoOfItemsLocally_WithExternal;
// only for full matrix, if there are no inner cells
if (NoOfCells == NoOfBdryCells)
{
Console.WriteLine("");
Console.WriteLine("Since there are only boundary cells, the condest of the non-existing inner matrix is set to zero!");
double[] Full_0Vars = this.m_map.GetSubvectorIndices(true, DepVars).Select(i => i + 1.0).ToArray();
MultidimensionalArray output = MultidimensionalArray.Create(1, 1);
using (BatchmodeConnector bmc = new BatchmodeConnector()){
// if Octave should be used instead of Matlab....
//BatchmodeConnector.Flav = BatchmodeConnector.Flavor.Octave;
bmc.PutSparseMatrix(m_OpMtx, "FullMatrix");
bmc.PutVector(Full_0Vars, "Full_0Vars");
bmc.Cmd("output = zeros(1,1)");
bmc.Cmd("output = condest(FullMatrix(Full_0Vars,Full_0Vars));");
bmc.GetMatrix(output, "output");
bmc.Execute(false);
}
double condestFull = output[0, 0];
double condestInner = 0;
double[] condestOut = new double[] { condestFull, condestInner };
return(condestOut);
}
// for full and inner matrix
else
{
CellMask InnerCellsMask = grd.GetBoundaryCells().Complement();
SubGrid InnerCells = new SubGrid(InnerCellsMask);
double[] Full_0Vars = this.m_map.GetSubvectorIndices(true, DepVars).Select(i => i + 1.0).ToArray();
double[] Inner_0Vars = this.m_map.GetSubvectorIndices(InnerCells, true, DepVars).Select(i => i + 1.0).ToArray();
MultidimensionalArray output = MultidimensionalArray.Create(2, 1);
string[] names = new string[] { "Full_0Vars", "Inner_0Vars" };
using (BatchmodeConnector bmc = new BatchmodeConnector()){
// if Octave should be used instead of Matlab....
// BatchmodeConnector.Flav = BatchmodeConnector.Flavor.Octave;
bmc.PutSparseMatrix(m_OpMtx, "FullMatrix");
bmc.PutVector(Inner_0Vars, "Inner_0Vars");
bmc.PutVector(Full_0Vars, "Full_0Vars");
bmc.Cmd("output = zeros(2,1)");
int k = 1;
foreach (var s in names)
{
bmc.Cmd("output({1}) = condest(FullMatrix({0},{0}));", s, k);
k++;
}
bmc.GetMatrix(output, "output");
bmc.Execute(false);
double condestFull = output[0, 0];
double condestInner = output[1, 0];
double[] condestOut = new double[] { condestFull, condestInner };
Debug.Assert(condestOut[0].MPIEquals(), "value does not match on procs");
Debug.Assert(condestOut[1].MPIEquals(), "value does not match on procs");
return(condestOut);
}
}
}
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;
}
}
public void CreateWithMatlab()
{
// ================================
// generate voronoi graph in matlab
// ================================
int J = this.DelaunayVertices.NoOfRows;
int D = this.DelaunayVertices.NoOfCols;
if (D != 2)
{
throw new NotSupportedException("todo");
}
int[][] OutputVertexIndex = new int[J * 5][];
MultidimensionalArray VertexCoordinates;
{
var Matlab = new BatchmodeConnector();
Matlab.PutMatrix(this.DelaunayVertices, "X");
// create mirror points
Matlab.Cmd("[J, D] = size(X);");
Matlab.Cmd("Xneg = [-X(:, 1), X(:, 2)];");
Matlab.Cmd("Yneg = [X(:, 1), -X(:, 2)];");
Matlab.Cmd("X2 = [ones(J, 1) * 2, zeros(J, 1)];");
Matlab.Cmd("Y2 = [zeros(J, 1), ones(J, 1) * 2];");
Matlab.Cmd("Xm = X;");
Matlab.Cmd("Xm = [Xm; Xneg]; % mirror at x = 0");
Matlab.Cmd("Xm = [Xm; X2 + Xneg]; % mirror at x = 1");
Matlab.Cmd("Xm = [Xm; Yneg]; % mirror at x = 0");
Matlab.Cmd("Xm = [Xm; Y2 + Yneg]; % mirror at x = 1");
// compute Voronoi diagramm
Matlab.Cmd("[V, C] = voronoin(Xm);");
// output (export from matlab)
Matlab.GetStaggeredIntArray(OutputVertexIndex, "C");
Matlab.GetMatrix(null, "V");
// run matlab
Matlab.Execute(false);
// import here
VertexCoordinates = (MultidimensionalArray)(Matlab.OutputObjects["V"]);
// correct indices (1-based index to 0-based index)
foreach (int[] cell in OutputVertexIndex)
{
int K = cell.Length;
for (int k = 0; k < K; k++)
{
cell[k]--;
}
}
}
// ===============
// record internal
// ===============
{
// define Cell data
{
this.m_CellData = new CellData();
this.m_CellData.m_Owner = this;
this.m_VertexData = new VertexData();
this.m_LogEdges = new LogEdgeData();
this.m_VertexData.Coordinates = VertexCoordinates;
this.m_CellData.CellVertices = OutputVertexIndex.GetSubVector(0, J);
this.m_CellData.InfoFlags = new CellInfo[J];
ArrayTools.SetAll(this.m_CellData.InfoFlags, CellInfo.CellIsAffineLinear | CellInfo.IsAggregate);
}
// decomposition of Voronoi cells to triangles/tetrahedrons
{
m_CellData.AggregateCellToParts = new int[J][];
if (D == 2)
{
var Tri = RefElements.Triangle.Instance;
m_CellData.RefElements = new RefElement[] { Tri };
int cnt = 0;
for (int j = 0; j < J; j++)
{
int[] VtxIndices = m_CellData.CellVertices[j];
int[] PartIdx = new int[VtxIndices.Length - 2];
for (int i = 0; i < PartIdx.Length; i++)
{
PartIdx[i] = cnt;
cnt++;
}
m_CellData.AggregateCellToParts[j] = PartIdx;
}
int NoOfParts = cnt;
m_CellData.PartTransformation = MultidimensionalArray.Create(NoOfParts, D, D);
m_CellData.PartCenter = MultidimensionalArray.Create(NoOfParts, D);
MultidimensionalArray TriangleVtx = MultidimensionalArray.Create(3, D);
for (int j = 0; j < J; j++)
{
int[] VtxIndices = m_CellData.CellVertices[j];
int[] PartIdx = m_CellData.AggregateCellToParts[j];
for (int i = 0; i < PartIdx.Length; i++)
{
int iV0 = VtxIndices[0];
int iV1 = VtxIndices[i + 1];
int iV2 = VtxIndices[i + 2];
TriangleVtx[0, 0] = m_VertexData.Coordinates[iV0, 0];
TriangleVtx[0, 1] = m_VertexData.Coordinates[iV0, 1];
TriangleVtx[1, 0] = m_VertexData.Coordinates[iV1, 0];
TriangleVtx[1, 1] = m_VertexData.Coordinates[iV1, 1];
TriangleVtx[2, 0] = m_VertexData.Coordinates[iV2, 0];
TriangleVtx[2, 1] = m_VertexData.Coordinates[iV2, 1];
var TR = AffineTrafo.FromPoints(Tri.Vertices, TriangleVtx);
m_CellData.PartTransformation.ExtractSubArrayShallow(PartIdx[i], -1, -1).Set(TR.Matrix);
m_CellData.PartCenter.ExtractSubArrayShallow(PartIdx[i], -1).SetVector(TR.Affine);
}
}
}
else if (D == 3)
{
throw new NotImplementedException("todo");
}
else
{
throw new NotSupportedException("Unknown spatial dimension.");
}
}
// bounding boxes, transformations
{
BoundingBox BB = new BoundingBox(D);
m_CellData.BoundingBoxTransformation = MultidimensionalArray.Create(J, D, D);
m_CellData.BoundingBoxCenter = MultidimensionalArray.Create(J, D);
for (int j = 0; j < J; j++)
{
m_CellData.GetCellBoundingBox(j, BB);
for (int d = 0; d < D; d++)
{
double lo = BB.Min[d];
double hi = BB.Max[d];
m_CellData.BoundingBoxCenter[j, d] = 0.5 * (lo + hi);
m_CellData.BoundingBoxTransformation[j, d, d] = 0.5 * (hi - lo);
}
}
}
// mapping: vertex to cell
{
List <int>[] VertexToCell = new List <int> [VertexCoordinates.Length];
for (int j = 0; j < J; j++)
{
foreach (int iVtx in OutputVertexIndex[j])
{
if (VertexToCell[iVtx] == null)
{
VertexToCell[iVtx] = new List <int>();
}
if (!VertexToCell[iVtx].Contains(j))
{
VertexToCell[iVtx].Add(j);
}
}
}
m_VertexData.VerticeToCell = new int[VertexToCell.Length][];
for (int i = 0; i < VertexToCell.Length; i++)
{
if (VertexToCell[i] == null)
{
m_VertexData.VerticeToCell[i] = new int[0];
}
else
{
m_VertexData.VerticeToCell[i] = VertexToCell[i].ToArray();
}
}
VertexToCell = null;
}
// cell neighbors, edges
{
m_CellData.CellNeighbours = new int[J][];
var tmpCells2Edges = new List <int> [J];
Dictionary <int, int> ShareCount = new Dictionary <int, int>(); // key: cell index; value: number of vertices shared with this cell
var EdgesTemp = new List <EdgeTemp>();
List <int> Neighs = new List <int>();
List <int> EdgeVtx = new List <int>();
List <int> IdedEdgsAtOneCell = new List <int>();
for (int jCell = 0; jCell < J; jCell++) // loop over cells
{
ShareCount.Clear();
Neighs.Clear();
IdedEdgsAtOneCell.Clear();
// determine how many vertices 'jCell' shares with other cells
foreach (int iVtx in m_CellData.CellVertices[jCell])
{
foreach (int jOtherCell in m_VertexData.VerticeToCell[iVtx])
{
if (jOtherCell != jCell)
{
if (!ShareCount.ContainsKey(jOtherCell))
{
ShareCount.Add(jOtherCell, 1);
}
else
{
ShareCount[jOtherCell]++;
}
}
}
}
// find faces
int[][] FaceIdx = ConvexHullFaces(m_VertexData.Coordinates, m_CellData.CellVertices[jCell]);
// determine cell neighbors and edges
int NoOfFacesFound = 0;
foreach (var kv in ShareCount)
{
int jCellNeigh = kv.Key;
int NoOfSharedVtx = kv.Value;
if (NoOfSharedVtx >= D)
{
// +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
// cells 'jCell' and 'jCellNeigh' share more than 'D' vertices - this is an edge to another cell,
// resp. a face of 'jCell'.
// +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Debug.Assert(jCellNeigh != jCell);
Debug.Assert(!Neighs.Contains(jCellNeigh));
Neighs.Add(jCellNeigh);
NoOfFacesFound++;
EdgeVtx.Clear();
foreach (int iVtx in m_CellData.CellVertices[jCell])
{
if (Array.IndexOf(m_VertexData.VerticeToCell[iVtx], jCellNeigh) >= 0)
{
EdgeVtx.Add(iVtx);
}
}
if (jCell < jCellNeigh)
{
// the pairing 'jCell'/'jCellNeigh' will be discovered twice;
// we only want to record once
var Etmp = new EdgeTemp()
{
jCell1 = jCell,
jCell2 = jCellNeigh,
Vertices = EdgeVtx.ToArray()
};
EdgesTemp.Add(Etmp);
IdedEdgsAtOneCell.Add(EdgesTemp.Count - 1);
if (tmpCells2Edges[jCell] == null)
{
tmpCells2Edges[jCell] = new List <int>();
}
if (tmpCells2Edges[jCellNeigh] == null)
{
tmpCells2Edges[jCellNeigh] = new List <int>();
}
tmpCells2Edges[jCell].Add(EdgesTemp.Count); // the funky convention for edges-to-cell: the index is
tmpCells2Edges[jCellNeigh].Add(-EdgesTemp.Count); // shifted by 1, out-cell is negative
}
else
{
Debug.Assert(jCellNeigh < jCell);
int MatchCount = 0;
foreach (int i in tmpCells2Edges[jCellNeigh])
{
int iEdge = Math.Abs(i) - 1;
if (EdgesTemp[iEdge].jCell1 == jCellNeigh && EdgesTemp[iEdge].jCell2 == jCell)
{
MatchCount++;
IdedEdgsAtOneCell.Add(iEdge);
}
}
Debug.Assert(MatchCount == 1);
}
#if DEBUG
if (D == 2)
{
Debug.Assert(EdgeVtx.Count == 2);
}
else if (D == 3)
{
// verify that all vertices of the edge are geometrically in one plane
Debug.Assert(EdgeVtx.Count >= 3);
var FacePlane = AffineManifold.FromPoints(
m_VertexData.Coordinates.GetRowPt(EdgeVtx[0]),
m_VertexData.Coordinates.GetRowPt(EdgeVtx[1]),
m_VertexData.Coordinates.GetRowPt(EdgeVtx[2])
);
BoundingBox BB = new BoundingBox(D);
m_CellData.GetCellBoundingBox(jCell, BB);
double h = BB.Diameter;
foreach (int iVtx in EdgeVtx)
{
double dist = Math.Abs(FacePlane.PointDistance(m_VertexData.Coordinates.GetRow(iVtx)));
Debug.Assert(dist < h * 1e-8);
}
}
else
{
throw new NotSupportedException("Unknown spatial dimension.");
}
#endif
}
}
m_CellData.CellNeighbours[jCell] = Neighs.ToArray();
Debug.Assert(NoOfFacesFound <= FaceIdx.Length);
Debug.Assert(NoOfFacesFound == IdedEdgsAtOneCell.Count);
// boundary edges
if (NoOfFacesFound == FaceIdx.Length)
{
// nothing to do - all faces/edges identified
#if DEBUG
for (int i = 0; i < NoOfFacesFound; i++)
{
int Matches = 0;
for (int l = 0; l < NoOfFacesFound; l++)
{
if (FaceIdx[i].SetEquals(EdgesTemp[IdedEdgsAtOneCell[l]].Vertices))
{
Matches++;
}
}
Debug.Assert(Matches == 1);
}
#endif
}
else
{
// missing boundary
for (int i = 0; i < FaceIdx.Length; i++)
{
int Matches = 0;
for (int l = 0; l < NoOfFacesFound; l++)
{
if (FaceIdx[i].SetEquals(EdgesTemp[IdedEdgsAtOneCell[l]].Vertices))
{
Matches++;
}
}
Debug.Assert(Matches <= 1);
if (Matches == 0)
{
// boundary edge found
var Etmp = new EdgeTemp()
{
jCell1 = jCell,
jCell2 = int.MinValue,
Vertices = EdgeVtx.ToArray()
};
EdgesTemp.Add(Etmp);
tmpCells2Edges[jCell].Add(EdgesTemp.Count); // index shifted by 1
}
}
}
}
// convert temporary data structures to the final ones
m_CellData.Cells2Edges = new int[J][];
var C2E = m_CellData.Cells2Edges;
for (int j = 0; j < J; j++)
{
C2E[j] = tmpCells2Edges[j] != null ? tmpCells2Edges[j].ToArray() : new int[0];
}
m_GeomEdges = new GeomEdgeData();
int NoOfEdges = EdgesTemp.Count;
m_GeomEdges.Info = new EdgeInfo[NoOfEdges];
m_LogEdges.CellIndices = new int[NoOfEdges, 2];
m_GeomEdges.VertexIndices = new int[NoOfEdges][];
var Evtx = m_GeomEdges.VertexIndices;
var E2C = m_LogEdges.CellIndices;
var Einf = m_GeomEdges.Info;
for (int iEdge = 0; iEdge < NoOfEdges; iEdge++)
{
var Etmp = EdgesTemp[iEdge];
E2C[iEdge, 0] = Etmp.jCell1;
E2C[iEdge, 1] = Etmp.jCell2;
Einf[iEdge] = EdgeInfo.EdgeIsAffineLinear | EdgeInfo.IsAggregate;
if (Etmp.jCell2 < 0)
{
Einf[iEdge] |= EdgeInfo.Boundary;
}
Evtx[iEdge] = Etmp.Vertices;
}
}
// edge metrics
{
if (D == 2)
{
m_GeomEdges.EdgeRefElements = new RefElement[] { Line.Instance };
}
else if (D == 3)
{
m_GeomEdges.EdgeRefElements = new RefElement[] { Triangle.Instance };
}
else
{
throw new NotSupportedException("Unknown spatial dimension.");
}
int[][] Evtx = m_GeomEdges.VertexIndices;
int NoOfParts = 0;
int NoOfEdges = m_GeomEdges.Count;
for (int iEdge = 0; iEdge < NoOfEdges; iEdge++)
{
NoOfParts += Evtx[iEdge].Length - D + 1;
}
Debug.Assert(D != 2 || NoOfParts == NoOfEdges);
m_GeomEdges.Edge2CellTrafoIndex = new int[NoOfParts, 2];
var tmpEdg2CellTrafo = new Dictionary <int, Tuple <int, AffineTrafo> >();
// unsolved problem:
// (D-1) -- dimensional tesselation of edge is given by D -- dimensional tesselation of adjacent cells
// * case D == 2: trivial
// * case D == 3: the problem is that two adjacent cells will induce _two different_ tesselations, which
// wont match in the general case.
MultidimensionalArray PreImage = m_GeomEdges.EdgeRefElements[0].Vertices;
MultidimensionalArray Image = MultidimensionalArray.Create(PreImage.NoOfRows, D);
//for(int iEdge )
}
}
}
public static void FastSubMatrixExtraction(
[Values(XDGusage.none, XDGusage.all)] XDGusage UseXdg,
[Values(2)] int DGOrder,
[Values(MatrixShape.laplace)] MatrixShape MShape,
[Values(4)] int Res
)
{
Utils.TestInit((int)UseXdg, DGOrder, (int)MShape);
Console.WriteLine("FastSubMatrixExtraction({0},{1},{2})", UseXdg, DGOrder, MShape);
//Arrange ---
MultigridOperator mgo = Utils.CreateTestMGOperator(UseXdg, DGOrder, MShape, Res);
MultigridMapping map = mgo.Mapping;
BlockMsrMatrix M = mgo.OperatorMatrix;
var sbs = new SubBlockSelector(map);
int[] extcells = sbs.AllExternalCellsSelection();
var M_ext = BlockMask.GetAllExternalRows(map, M);
var mask = new BlockMask(sbs, M_ext);
//Arrange --- get index list of all external cells
int[] idc = Utils.GetAllExtCellIdc(map);
double[] GlobIdx = idc.Count().ForLoop(i => (double)idc[i] + 1.0);
//Arrange --- stopwatch
var stw = new Stopwatch();
stw.Reset();
//Act --- Extract SubMatrix
stw.Start();
BlockMsrMatrix subM = mask.GetSubBlockMatrix(M);
stw.Stop();
//Arrange --- Extract Blocks in Matlab and substract
var infNorm = MultidimensionalArray.Create(4, 1);
int rank = map.MpiRank;
using (BatchmodeConnector matlab = new BatchmodeConnector()) {
matlab.PutSparseMatrix(M, "M");
// note: M_sub lives on Comm_Self, therefore we have to distinguish between procs ...
matlab.PutSparseMatrixRankExclusive(subM, "M_sub");
matlab.PutVectorRankExclusive(GlobIdx, "Idx");
matlab.Cmd("M_0 = M(Idx_0, Idx_0);");
matlab.Cmd("M_1 = M(Idx_1, Idx_1);");
matlab.Cmd("M_2 = M(Idx_2, Idx_2);");
matlab.Cmd("M_3 = M(Idx_3, Idx_3);");
matlab.Cmd("n=[0; 0; 0; 0];");
matlab.Cmd("n(1,1)=norm(M_0-M_sub_0,inf);");
matlab.Cmd("n(2,1)=norm(M_1-M_sub_1,inf);");
matlab.Cmd("n(3,1)=norm(M_2-M_sub_2,inf);");
matlab.Cmd("n(4,1)=norm(M_3-M_sub_3,inf);");
matlab.GetMatrix(infNorm, "n");
matlab.Execute();
}
//Assert --- mask blocks and extracted blocks are the same
Assert.IsTrue(infNorm[rank, 0] == 0.0);
}
public void Init(MultigridOperator op)
{
int D = op.Mapping.GridData.SpatialDimension;
var M = op.OperatorMatrix;
var MgMap = op.Mapping;
this.m_mgop = op;
if (!M.RowPartitioning.EqualsPartition(MgMap.Partitioning))
{
throw new ArgumentException("Row partitioning mismatch.");
}
if (!M.ColPartition.EqualsPartition(MgMap.Partitioning))
{
throw new ArgumentException("Column partitioning mismatch.");
}
Uidx = MgMap.ProblemMapping.GetSubvectorIndices(true, D.ForLoop(i => i));
Pidx = MgMap.ProblemMapping.GetSubvectorIndices(true, D);
int Upart = Uidx.Length;
int Ppart = Pidx.Length;
ConvDiff = new MsrMatrix(Upart, Upart, 1, 1);
pGrad = new MsrMatrix(Upart, Ppart, 1, 1);
divVel = new MsrMatrix(Ppart, Upart, 1, 1);
var PxP = new MsrMatrix(Ppart, Ppart, 1, 1);
M.AccSubMatrixTo(1.0, ConvDiff, Uidx, default(int[]), Uidx, default(int[]));
M.AccSubMatrixTo(1.0, pGrad, Uidx, default(int[]), Pidx, default(int[]));
M.AccSubMatrixTo(1.0, divVel, Pidx, default(int[]), Uidx, default(int[]));
M.AccSubMatrixTo(1.0, PxP, Pidx, default(int[]), Pidx, default(int[]));
Mtx = M;
int L = M.RowPartitioning.LocalLength;
int i0 = Mtx.RowPartitioning.i0;
P = new MsrMatrix(Mtx);
P.Clear();
// Debugging output
//ConvDiff.SaveToTextFileSparse("ConvDiff");
//divVel.SaveToTextFileSparse("divVel");
//pGrad.SaveToTextFileSparse("pGrad");
//PxP.SaveToTextFileSparse("PxP");
velMassMatrix = new MsrMatrix(Upart, Upart, 1, 1);
op.MassMatrix.AccSubMatrixTo(1.0, velMassMatrix, Uidx, default(int[]), Uidx, default(int[]));
switch (SchurOpt)
{
case SchurOptions.exact:
{
// Building complete Schur and Approximate Schur
MultidimensionalArray Poisson = MultidimensionalArray.Create(Pidx.Length, Pidx.Length);
MultidimensionalArray SchurConvPart = MultidimensionalArray.Create(Pidx.Length, Pidx.Length);
MultidimensionalArray Schur = MultidimensionalArray.Create(Pidx.Length, Pidx.Length);
using (BatchmodeConnector bmc = new BatchmodeConnector())
{
bmc.PutSparseMatrix(ConvDiff, "ConvDiff");
bmc.PutSparseMatrix(velMassMatrix, "MassMatrix");
bmc.PutSparseMatrix(divVel, "divVel");
bmc.PutSparseMatrix(pGrad, "pGrad");
bmc.Cmd("Qdiag = diag(diag(MassMatrix))");
bmc.Cmd("invT= inv(Qdiag)");
bmc.Cmd("Poisson = full(invT)*pGrad");
bmc.Cmd("ConvPart = ConvDiff*Poisson");
bmc.Cmd("ConvPart= full(invT)*ConvPart");
bmc.Cmd("ConvPart= divVel*ConvPart");
bmc.Cmd("Poisson = divVel*Poisson");
bmc.Cmd("ConvDiffInv = inv(full(ConvDiff))");
bmc.Cmd("Schur = divVel*ConvDiffInv");
bmc.Cmd("Schur = Schur*pGrad");
bmc.GetMatrix(Poisson, "Poisson");
bmc.GetMatrix(SchurConvPart, "ConvPart");
bmc.GetMatrix(Schur, "-Schur");
bmc.Execute(false);
}
PoissonMtx_T = Poisson.ToMsrMatrix();
PoissonMtx_H = Poisson.ToMsrMatrix();
SchurConvMtx = SchurConvPart.ToMsrMatrix();
SchurMtx = Schur.ToMsrMatrix();
SchurMtx.Acc(PxP, 1);
ConvDiff.AccSubMatrixTo(1.0, P, default(int[]), Uidx, default(int[]), Uidx);
pGrad.AccSubMatrixTo(1.0, P, default(int[]), Uidx, default(int[]), Pidx);
SchurMtx.AccSubMatrixTo(1.0, P, default(int[]), Pidx, default(int[]), Pidx);
return;
}
case SchurOptions.decoupledApprox:
{
// Do assembly for approximate Schur inverse
invVelMassMatrix = velMassMatrix.CloneAs();
invVelMassMatrix.Clear();
invVelMassMatrixSqrt = invVelMassMatrix.CloneAs();
for (int i = velMassMatrix.RowPartitioning.i0; i < velMassMatrix.RowPartitioning.iE; i++)
{
if (ApproxScaling)
{
invVelMassMatrix.SetDiagonalElement(i, 1 / (velMassMatrix[i, i]));
invVelMassMatrixSqrt.SetDiagonalElement(i, 1 / (Math.Sqrt(velMassMatrix[i, i])));
}
else
{
invVelMassMatrix.SetDiagonalElement(i, 1);
invVelMassMatrixSqrt.SetDiagonalElement(i, 1);
}
}
//invVelMassMatrix.SaveToTextFileSparse("invVelMassMatrix");
//velMassMatrix.SaveToTextFileSparse("velMassMatrix");
//ConvDiffPoissonMtx = MsrMatrix.Multiply(ConvDiff, pGrad);
//ConvDiffPoissonMtx = MsrMatrix.Multiply(divVel, ConvDiffPoissonMtx);
// Inverse of mass matrix in Matlab
//MultidimensionalArray temp = MultidimensionalArray.Create(Uidx.Length, Uidx.Length);
//using (BatchmodeConnector bmc = new BatchmodeConnector())
//{
// bmc.PutSparseMatrix(velMassMatrix, "velMassMatrix");
// bmc.Cmd("invVelMassMatrix = inv(full(velMassMatrix))");
// bmc.GetMatrix(temp, "invVelMassMatrix");
// bmc.Execute(false);
//}
//invVelMassMatrix = temp.ToMsrMatrix();
//ConvDiffPoissonMtx = MsrMatrix.Multiply(ConvDiffPoissonMtx, PoissonMtx);
//ConvDiffPoissonMtx = MsrMatrix.Multiply(PoissonMtx, ConvDiffPoissonMtx);
//ConvDiff.AccSubMatrixTo(1.0, P, default(int[]), Uidx, default(int[]), Uidx);
//pGrad.AccSubMatrixTo(1.0, P, default(int[]), Uidx, default(int[]), Pidx);
//ConvDiffPoissonMtx.AccSubMatrixTo(1.0, P, default(int[]), Pidx, default(int[]), Pidx);
//op.MassMatrix.SaveToTextFileSparse("MassMatrix");
//velMassMatrix.SaveToTextFileSparse("velMassMatrix2");
// Possion scaled by inverse of the velocity mass matrix
PoissonMtx_T = MsrMatrix.Multiply(invVelMassMatrix, pGrad);
PoissonMtx_T = MsrMatrix.Multiply(divVel, PoissonMtx_T);
////PoissonMtx_T.Acc(PxP, 1); // p.379
// Poisson scaled by sqrt of inverse of velocity mass matrix
PoissonMtx_H = MsrMatrix.Multiply(invVelMassMatrixSqrt, pGrad);
PoissonMtx_H = MsrMatrix.Multiply(divVel, PoissonMtx_H);
//PoissonMtx_H.Acc(PxP, 1); // p.379
return;
}
case SchurOptions.SIMPLE:
{
var invdiag_ConvDiff = ConvDiff.CloneAs();
invdiag_ConvDiff.Clear();
for (int i = ConvDiff.RowPartitioning.i0; i < ConvDiff.RowPartitioning.iE; i++)
{
invdiag_ConvDiff[i, i] = 1 / ConvDiff[i, i];
}
simpleSchur = MsrMatrix.Multiply(invdiag_ConvDiff, pGrad);
simpleSchur = MsrMatrix.Multiply(divVel, simpleSchur);
return;
}
default:
throw new NotImplementedException("SchurOption");
}
//var ConvDiffInvMtx = ConvDiffInv.ToMsrMatrix();
//// x= inv(P)*b !!!!! To be done with approximate Inverse
// P.SpMV(1, B, 0, X);
}
public static void SubBlockExtraction(
[Values(XDGusage.none, XDGusage.all)] XDGusage UseXdg,
[Values(2)] int DGOrder,
[Values(MatrixShape.diagonal_var_spec, MatrixShape.diagonal_spec, MatrixShape.diagonal_var, MatrixShape.diagonal)] MatrixShape MShape,
[Values(4)] int Res
)
{
Utils.TestInit((int)UseXdg, DGOrder, (int)MShape);
Console.WriteLine("SubMatrixIgnoreCoupling({0},{1},{2})", UseXdg, DGOrder, MShape);
//Arrange --- create test matrix and MG mapping
MultigridOperator mgo = Utils.CreateTestMGOperator(UseXdg, DGOrder, MShape, Res);
MultigridMapping map = mgo.Mapping;
BlockMsrMatrix M = mgo.OperatorMatrix;
//Arrange --- masking of all external cells
var sbs = new SubBlockSelector(map);
sbs.AllExternalCellsSelection();
var M_ext = BlockMask.GetAllExternalRows(map, M);
var mask = new BlockMask(sbs, M_ext);
//bool[] coup = Utils.SetCoupling(MShape);
//Arrange --- get index dictonary of all external cell indices
Dictionary <int, int[]> Didc = Utils.GetDictOfAllExtCellIdc(map);
//Arrange --- stopwatch
var stw = new Stopwatch();
stw.Reset();
//Act --- Extract subblocks
stw.Start();
//var eblocks = mask.GetSubBlocks(M,coup[0],coup[1],coup[2]);
var eblocks = mask.GetDiagonalBlocks(M, false, false);
stw.Stop();
//Assert --- same number of blocks?
Assert.IsTrue(eblocks.Length == M_ext._RowPartitioning.LocalNoOfBlocks);
bool test = eblocks.Length.MPIEquals();
Debug.Assert(test);
for (int iBlock = 0; iBlock < eblocks.Length; iBlock++)
{
var infNorm = MultidimensionalArray.Create(4, 1);
int rank = map.MpiRank;
int ExtBlockIdx = iBlock + map.AggGrid.iLogicalCells.NoOfLocalUpdatedCells;
Didc.TryGetValue(ExtBlockIdx, out int[] idc);
using (BatchmodeConnector matlab = new BatchmodeConnector()) {
double[] GlobIdx = idc.Count().ForLoop(i => (double)idc[i] + 1.0);
Assert.IsTrue(GlobIdx.Length == eblocks[iBlock].Lengths[0]);
MsrMatrix M_sub = eblocks[iBlock].ConvertToMsr();
matlab.PutSparseMatrix(M, "M");
// note: M_sub lives on Comm_Self, therefore we have to distinguish between procs ...
matlab.PutSparseMatrixRankExclusive(M_sub, "M_sub");
matlab.PutVectorRankExclusive(GlobIdx, "Idx");
matlab.Cmd("M_0 = full(M(Idx_0, Idx_0));");
matlab.Cmd("M_1 = full(M(Idx_1, Idx_1));");
matlab.Cmd("M_2 = full(M(Idx_2, Idx_2));");
matlab.Cmd("M_3 = full(M(Idx_3, Idx_3));");
matlab.Cmd("n=[0; 0; 0; 0];");
matlab.Cmd("n(1,1)=norm(M_0-M_sub_0,inf);");
matlab.Cmd("n(2,1)=norm(M_1-M_sub_1,inf);");
matlab.Cmd("n(3,1)=norm(M_2-M_sub_2,inf);");
matlab.Cmd("n(4,1)=norm(M_3-M_sub_3,inf);");
matlab.GetMatrix(infNorm, "n");
matlab.Execute();
}
Assert.IsTrue(infNorm[rank, 0] == 0.0); //
}
}