/// <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 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>
/// 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>
/// 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);
}
}
}