本文整理汇总了C++中Epetra_RowMatrix::NormOne方法的典型用法代码示例。如果您正苦于以下问题：C++ Epetra_RowMatrix::NormOne方法的具体用法？C++ Epetra_RowMatrix::NormOne怎么用？C++ Epetra_RowMatrix::NormOne使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Epetra_RowMatrix的用法示例。
在下文中一共展示了Epetra_RowMatrix::NormOne方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: solve
int SchwarzSolver::solve()
{
// compute some statistics for the original problem
double condest = -1;
Epetra_LinearProblem problem(_stiffnessMatrix.get(), _lhs.get(), _rhs.get());
AztecOO solverForConditionEstimate(problem);
solverForConditionEstimate.SetAztecOption(AZ_solver, AZ_cg_condnum);
solverForConditionEstimate.ConstructPreconditioner(condest);
Epetra_RowMatrix *A = problem.GetMatrix();
double norminf = A->NormInf();
double normone = A->NormOne();
if (_printToConsole)
{
cout << "\n Inf-norm of stiffness matrix before scaling = " << norminf;
cout << "\n One-norm of stiffness matrix before scaling = " << normone << endl << endl;
cout << "Condition number estimate: " << condest << endl;
}
AztecOO solver(problem);
int otherRows = A->NumGlobalRows() - A->NumMyRows();
int overlapLevel = std::min(otherRows,_overlapLevel);
solver.SetAztecOption(AZ_precond, AZ_dom_decomp); // additive schwarz
solver.SetAztecOption(AZ_overlap, overlapLevel); // level of overlap for schwarz
solver.SetAztecOption(AZ_type_overlap, AZ_symmetric);
solver.SetAztecOption(AZ_solver, AZ_cg_condnum); // more expensive than AZ_cg, but allows estimate of condition #
solver.SetAztecOption(AZ_subdomain_solve, AZ_ilut); // TODO: look these up (copied from example)
solver.SetAztecParam(AZ_ilut_fill, 1.0); // TODO: look these up (copied from example)
solver.SetAztecParam(AZ_drop, 0.0); // TODO: look these up (copied from example)
int solveResult = solver.Iterate(_maxIters,_tol);
// int solveResult = solver.AdaptiveIterate(_maxIters,1,_tol); // an experiment (was Iterate())
norminf = A->NormInf();
normone = A->NormOne();
condest = solver.Condest();
int numIters = solver.NumIters();
if (_printToConsole)
{
cout << "\n Inf-norm of stiffness matrix after scaling = " << norminf;
cout << "\n One-norm of stiffness matrix after scaling = " << normone << endl << endl;
cout << "Condition number estimate: " << condest << endl;
cout << "Num iterations: " << numIters << endl;
}
return solveResult;
}示例2: check
int check(Epetra_RowMatrix& A, Epetra_RowMatrix & B, bool verbose) {
int ierr = 0;
EPETRA_TEST_ERR(!A.Comm().NumProc()==B.Comm().NumProc(),ierr);
EPETRA_TEST_ERR(!A.Comm().MyPID()==B.Comm().MyPID(),ierr);
EPETRA_TEST_ERR(!A.Filled()==B.Filled(),ierr);
EPETRA_TEST_ERR(!A.HasNormInf()==B.HasNormInf(),ierr);
EPETRA_TEST_ERR(!A.LowerTriangular()==B.LowerTriangular(),ierr);
EPETRA_TEST_ERR(!A.Map().SameAs(B.Map()),ierr);
EPETRA_TEST_ERR(!A.MaxNumEntries()==B.MaxNumEntries(),ierr);
EPETRA_TEST_ERR(!A.NumGlobalCols64()==B.NumGlobalCols64(),ierr);
EPETRA_TEST_ERR(!A.NumGlobalDiagonals64()==B.NumGlobalDiagonals64(),ierr);
EPETRA_TEST_ERR(!A.NumGlobalNonzeros64()==B.NumGlobalNonzeros64(),ierr);
EPETRA_TEST_ERR(!A.NumGlobalRows64()==B.NumGlobalRows64(),ierr);
EPETRA_TEST_ERR(!A.NumMyCols()==B.NumMyCols(),ierr);
EPETRA_TEST_ERR(!A.NumMyDiagonals()==B.NumMyDiagonals(),ierr);
EPETRA_TEST_ERR(!A.NumMyNonzeros()==B.NumMyNonzeros(),ierr);
for (int i=0; i<A.NumMyRows(); i++) {
int nA, nB;
A.NumMyRowEntries(i,nA); B.NumMyRowEntries(i,nB);
EPETRA_TEST_ERR(!nA==nB,ierr);
}
EPETRA_TEST_ERR(!A.NumMyRows()==B.NumMyRows(),ierr);
EPETRA_TEST_ERR(!A.OperatorDomainMap().SameAs(B.OperatorDomainMap()),ierr);
EPETRA_TEST_ERR(!A.OperatorRangeMap().SameAs(B.OperatorRangeMap()),ierr);
EPETRA_TEST_ERR(!A.RowMatrixColMap().SameAs(B.RowMatrixColMap()),ierr);
EPETRA_TEST_ERR(!A.RowMatrixRowMap().SameAs(B.RowMatrixRowMap()),ierr);
EPETRA_TEST_ERR(!A.UpperTriangular()==B.UpperTriangular(),ierr);
EPETRA_TEST_ERR(!A.UseTranspose()==B.UseTranspose(),ierr);
int NumVectors = 5;
{ // No transpose case
Epetra_MultiVector X(A.OperatorDomainMap(), NumVectors);
Epetra_MultiVector YA1(A.OperatorRangeMap(), NumVectors);
Epetra_MultiVector YA2(YA1);
Epetra_MultiVector YB1(YA1);
Epetra_MultiVector YB2(YA1);
X.Random();
bool transA = false;
A.SetUseTranspose(transA);
B.SetUseTranspose(transA);
A.Apply(X,YA1);
A.Multiply(transA, X, YA2);
EPETRA_TEST_ERR(checkMultiVectors(YA1,YA2,"A Multiply and A Apply", verbose),ierr);
B.Apply(X,YB1);
EPETRA_TEST_ERR(checkMultiVectors(YA1,YB1,"A Multiply and B Multiply", verbose),ierr);
B.Multiply(transA, X, YB2);
EPETRA_TEST_ERR(checkMultiVectors(YA1,YB2,"A Multiply and B Apply", verbose), ierr);
}
{// transpose case
Epetra_MultiVector X(A.OperatorRangeMap(), NumVectors);
Epetra_MultiVector YA1(A.OperatorDomainMap(), NumVectors);
Epetra_MultiVector YA2(YA1);
Epetra_MultiVector YB1(YA1);
Epetra_MultiVector YB2(YA1);
X.Random();
bool transA = true;
A.SetUseTranspose(transA);
B.SetUseTranspose(transA);
A.Apply(X,YA1);
A.Multiply(transA, X, YA2);
EPETRA_TEST_ERR(checkMultiVectors(YA1,YA2, "A Multiply and A Apply (transpose)", verbose),ierr);
B.Apply(X,YB1);
EPETRA_TEST_ERR(checkMultiVectors(YA1,YB1, "A Multiply and B Multiply (transpose)", verbose),ierr);
B.Multiply(transA, X,YB2);
EPETRA_TEST_ERR(checkMultiVectors(YA1,YB2, "A Multiply and B Apply (transpose)", verbose),ierr);
}
Epetra_Vector diagA(A.RowMatrixRowMap());
EPETRA_TEST_ERR(A.ExtractDiagonalCopy(diagA),ierr);
Epetra_Vector diagB(B.RowMatrixRowMap());
EPETRA_TEST_ERR(B.ExtractDiagonalCopy(diagB),ierr);
EPETRA_TEST_ERR(checkMultiVectors(diagA,diagB, "ExtractDiagonalCopy", verbose),ierr);
Epetra_Vector rowA(A.RowMatrixRowMap());
EPETRA_TEST_ERR(A.InvRowSums(rowA),ierr);
Epetra_Vector rowB(B.RowMatrixRowMap());
EPETRA_TEST_ERR(B.InvRowSums(rowB),ierr)
EPETRA_TEST_ERR(checkMultiVectors(rowA,rowB, "InvRowSums", verbose),ierr);
Epetra_Vector colA(A.RowMatrixColMap());
EPETRA_TEST_ERR(A.InvColSums(colA),ierr);
Epetra_Vector colB(B.RowMatrixColMap());
EPETRA_TEST_ERR(B.InvColSums(colB),ierr);
EPETRA_TEST_ERR(checkMultiVectors(colA,colB, "InvColSums", verbose),ierr);
EPETRA_TEST_ERR(checkValues(A.NormInf(), B.NormInf(), "NormInf before scaling", verbose), ierr);
EPETRA_TEST_ERR(checkValues(A.NormOne(), B.NormOne(), "NormOne before scaling", verbose),ierr);
EPETRA_TEST_ERR(A.RightScale(colA),ierr);
EPETRA_TEST_ERR(B.RightScale(colB),ierr);
EPETRA_TEST_ERR(A.LeftScale(rowA),ierr);
EPETRA_TEST_ERR(B.LeftScale(rowB),ierr);
//.........这里部分代码省略.........
示例3: AZOO_iterate
void AZOO_iterate(double * xsolve, double * b,
int * options, double * params,
double * status, int *proc_config,
AZ_MATRIX * Amat,
AZ_PRECOND *precond, struct AZ_SCALING *scaling)
{
(void)precond;
(void)scaling;
bool verbose = (options[AZ_output]!=AZ_none); // Print info unless all output is turned off
Epetra_Comm * comm;
Epetra_BlockMap * map;
Epetra_RowMatrix * A;
Epetra_Vector * px;
Epetra_Vector * pb;
int * global_indices;
int ierr = Aztec2Petra(proc_config, Amat, xsolve, b, comm, map, A, px, pb, &global_indices);
if (ierr!=0) {
cerr << "Error detected in Aztec2Petra. Value = " << ierr << endl;
exit(1);
}
Epetra_LinearProblem problem(A, px, pb);
Epetra_Vector * leftScaleVec = 0;
Epetra_Vector * rightScaleVec = 0;
bool doRowScaling = false;
bool doColScaling = false;
if ((options[AZ_scaling]==AZ_Jacobi) || options[AZ_scaling]==AZ_BJacobi) {
doRowScaling = true;
leftScaleVec = new Epetra_Vector(*map);
A->ExtractDiagonalCopy(*leftScaleVec); // Extract diagonal of matrix
leftScaleVec->Reciprocal(*leftScaleVec); // invert it
}
else if (options[AZ_scaling]==AZ_row_sum) {
doRowScaling = true;
leftScaleVec = new Epetra_Vector(*map);
A->InvRowSums(*leftScaleVec);
}
else if (options[AZ_scaling]==AZ_sym_diag) {
doRowScaling = true;
doColScaling = true;
leftScaleVec = new Epetra_Vector(*map);
A->ExtractDiagonalCopy(*leftScaleVec); // Extract diagonal of matrix
int length = leftScaleVec->MyLength();
for (int i=0; i<length; i++) (*leftScaleVec)[i] = sqrt(fabs((*leftScaleVec)[i])); // Take its sqrt
rightScaleVec = leftScaleVec; // symmetric, so left and right the same
leftScaleVec->Reciprocal(*leftScaleVec); // invert it
}
else if (options[AZ_scaling]==AZ_sym_row_sum) {
doRowScaling = true;
doColScaling = true;
leftScaleVec = new Epetra_Vector(*map);
A->InvRowSums(*leftScaleVec);
int length = leftScaleVec->MyLength();
for (int i=0; i<length; i++) (*leftScaleVec)[i] = sqrt(fabs((*leftScaleVec)[i])); // Take its sqrt
rightScaleVec = leftScaleVec; // symmetric, so left and right the same
}
if ((doRowScaling || doColScaling) && verbose) {
double norminf = A->NormInf();
double normone = A->NormOne();
if (comm->MyPID()==0)
cout << "\n Inf-norm of A before scaling = " << norminf
<< "\n One-norm of A before scaling = " << normone<< endl << endl;
}
if (doRowScaling) problem.LeftScale(*leftScaleVec);
if (doColScaling) problem.RightScale(*rightScaleVec);
if ((doRowScaling || doColScaling) && verbose) {
double norminf = A->NormInf();
double normone = A->NormOne();
if (comm->MyPID()==0)
cout << "\n Inf-norm of A after scaling = " << norminf
<< "\n One-norm of A after scaling = " << normone << endl << endl;
}
AztecOO solver(problem);
solver.SetAllAztecParams(params); // set all AztecOO params with user-provided params
solver.SetAllAztecOptions(options); // set all AztecOO options with user-provided options
solver.CheckInput();
solver.SetAztecOption(AZ_scaling, AZ_none); // Always must have scaling off
solver.Iterate(options[AZ_max_iter], params[AZ_tol]);
solver.GetAllAztecStatus(status);
if (doColScaling) {
rightScaleVec->Reciprocal(*rightScaleVec);
problem.RightScale(*rightScaleVec);
}
if (doRowScaling) {
//.........这里部分代码省略.........
示例4: Ifpack_Analyze
//.........这里部分代码省略.........
MyLowerNonzeros++;
else if (GCID > GRID)
MyUpperNonzeros++;
long long b = GCID - GRID;
if (b < 0) b = -b;
if (b > MyBandwidth)
MyBandwidth = b;
}
if (Diag[i] > RowSum[i])
MyDiagonallyDominant++;
if (Diag[i] >= RowSum[i])
MyWeaklyDiagonallyDominant++;
RowSum[i] += Diag[i];
}
// ======================== //
// summing up global values //
// ======================== //
A.Comm().SumAll(&MyDiagonallyDominant,&GlobalDiagonallyDominant,1);
A.Comm().SumAll(&MyWeaklyDiagonallyDominant,&GlobalWeaklyDiagonallyDominant,1);
A.Comm().SumAll(&NumMyActualNonzeros, &NumGlobalActualNonzeros, 1);
A.Comm().SumAll(&NumMyEmptyRows, &NumGlobalEmptyRows, 1);
A.Comm().SumAll(&NumMyDirichletRows, &NumGlobalDirichletRows, 1);
A.Comm().SumAll(&MyBandwidth, &GlobalBandwidth, 1);
A.Comm().SumAll(&MyLowerNonzeros, &GlobalLowerNonzeros, 1);
A.Comm().SumAll(&MyUpperNonzeros, &GlobalUpperNonzeros, 1);
A.Comm().SumAll(&MyDiagonallyDominant, &GlobalDiagonallyDominant, 1);
A.Comm().SumAll(&MyWeaklyDiagonallyDominant, &GlobalWeaklyDiagonallyDominant, 1);
double NormOne = A.NormOne();
double NormInf = A.NormInf();
double NormF = Ifpack_FrobeniusNorm(A);
if (verbose) {
print();
print<long long>("Actual nonzeros", NumGlobalActualNonzeros);
print<long long>("Nonzeros in strict lower part", GlobalLowerNonzeros);
print<long long>("Nonzeros in strict upper part", GlobalUpperNonzeros);
print();
print<long long>("Empty rows", NumGlobalEmptyRows,
100.0 * NumGlobalEmptyRows / NumGlobalRows);
print<long long>("Dirichlet rows", NumGlobalDirichletRows,
100.0 * NumGlobalDirichletRows / NumGlobalRows);
print<long long>("Diagonally dominant rows", GlobalDiagonallyDominant,
100.0 * GlobalDiagonallyDominant / NumGlobalRows);
print<long long>("Weakly diag. dominant rows",
GlobalWeaklyDiagonallyDominant,
100.0 * GlobalWeaklyDiagonallyDominant / NumGlobalRows);
print();
print<long long>("Maximum bandwidth", GlobalBandwidth);
print();
print("", "one-norm", "inf-norm", "Frobenius", false);
print("", "========", "========", "=========", false);
print();
print<double>("A", NormOne, NormInf, NormF);
}
if (Cheap == false) {
// create A + A^T and A - A^T