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C++ DenseMatrix::numRows方法代码示例

本文整理汇总了C++中nox::abstract::multivector::DenseMatrix::numRows方法的典型用法代码示例。如果您正苦于以下问题：C++ DenseMatrix::numRows方法的具体用法？C++ DenseMatrix::numRows怎么用？C++ DenseMatrix::numRows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nox::abstract::multivector::DenseMatrix的用法示例。


在下文中一共展示了DenseMatrix::numRows方法的7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: tmp

void 
LOCA::Extended::MultiVector::multiply(
			    double alpha, 
			    const LOCA::Extended::MultiVector& y,
			    NOX::Abstract::MultiVector::DenseMatrix& b) const
{
  // Verify dimensions are consistent
  if (y.numMultiVecRows != numMultiVecRows || y.numColumns != b.numRows() ||
      y.numScalarRows != numScalarRows || numColumns != b.numCols()) 
    globalData->locaErrorCheck->throwError(
  "LOCA::Extended::MultiVector::multiply()",
  "Size of supplied multivector/matrix is incompatible with this multivector");

  // Zero out b
  b.putScalar(0.0);

  // Create temporary matrix to hold product for each multivec
  NOX::Abstract::MultiVector::DenseMatrix tmp(b);

  // Compute and sum products for each multivec
  for (int i=0; i<numMultiVecRows; i++) {
    multiVectorPtrs[i]->multiply(alpha, *(y.multiVectorPtrs[i]), tmp);
    b += tmp;
  }

  // Compute and add in product for scalars
  if (numScalarRows > 0)
    b.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, alpha, *y.scalarsPtr,
	       *scalarsPtr, 1.0);

}
开发者ID:gitter-badger，项目名称:quinoa，代码行数:31，代码来源:LOCA_Extended_MultiVector.C

示例2: tmp

int 
NOX::TestCompare::testMatrix(
		 const NOX::Abstract::MultiVector::DenseMatrix& mat, 
		 const NOX::Abstract::MultiVector::DenseMatrix& mat_expected, 
		 double rtol, double atol, 
		 const std::string& name)
{
  bool passed;

  NOX::Abstract::MultiVector::DenseMatrix tmp(mat_expected.numRows(),
					      mat_expected.numCols());

  for (int j=0; j<mat_expected.numCols(); j++)
    for (int i=0; i<mat_expected.numRows(); i++)
      tmp(i,j) = fabs(mat(i,j)-mat_expected(i,j)) / 
	(atol + rtol * fabs(mat_expected(i,j)));
 
  double inf_norm = tmp.normInf();

  if (inf_norm < 1)
    passed = true;
  else
    passed = false;

  if (utils.isPrintType(NOX::Utils::TestDetails)) {
    os << std::endl
	 << "\tChecking " << name << ":  ";
    if (passed)
      os << "Passed." << std::endl;
    else
      os << "Failed." << std::endl;
    os << "\t\tComputed norm:        " << utils.sciformat(inf_norm) 
       << std::endl
       << "\t\tRelative Tolerance:   " << utils.sciformat(rtol) 
       << std::endl
       << "\t\tAbsolute Tolerance:   " << utils.sciformat(rtol) 
       << std::endl;
  }

  if (passed)
    return 0;
  else
    return 1;
}
开发者ID:gitter-badger，项目名称:quinoa，代码行数:44，代码来源:NOX_TestCompare.C

示例3: if

void
LOCA::BorderedSolver::HouseholderQR::applyCompactWY(
                const NOX::Abstract::MultiVector::DenseMatrix& Y1,
                const NOX::Abstract::MultiVector& Y2,
                const NOX::Abstract::MultiVector::DenseMatrix& T,
                NOX::Abstract::MultiVector::DenseMatrix& X1,
                NOX::Abstract::MultiVector& X2,
                bool isZeroX1, bool isZeroX2,
                bool useTranspose) const
{
  if (isZeroX1 && isZeroX2) {
    X1.putScalar(0.0);
    X2.init(0.0);
    return;
  }

  int m = Y2.numVectors();

  Teuchos::ETransp T_flag;
  if (useTranspose)
    T_flag = Teuchos::TRANS;
  else
    T_flag = Teuchos::NO_TRANS;

  NOX::Abstract::MultiVector::DenseMatrix tmp(m, X2.numVectors());

  // Compute Y1^T*X1 + Y2^T*X2
  if (!isZeroX2)
    X2.multiply(1.0, Y2, tmp);

  // Opportunity for optimization here since Y1 is a lower-triangular
  // matrix with unit diagonal
  if (!isZeroX2 && !isZeroX1)
    tmp.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, Y1, X1, 1.0);
  else if (!isZeroX1)
    tmp.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, Y1, X1, 0.0);

  // Compute op(T)*(Y1^T*X1 + Y2^T*X2)
  dblas.TRMM(Teuchos::LEFT_SIDE, Teuchos::UPPER_TRI, T_flag,
         Teuchos::NON_UNIT_DIAG, tmp.numRows(), tmp.numCols(), 1.0,
         T.values(), T.numRows(), tmp.values(), tmp.numRows());

  // Compute X1 = X1 + Y1*op(T)*(Y1^T*X1 + Y2^T*X2)
  // Opportunity for optimization here since Y1 is a lower-triangular
  // matrix with unit diagonal
  if (isZeroX1)
    X1.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, Y1, tmp, 0.0);
  else
    X1.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, Y1, tmp, 1.0);

  // Compute X2 = X2 + Y1*op(T)*(Y1^T*X1 + Y2^T*X2)
  if (isZeroX2)
    X2.update(Teuchos::NO_TRANS, 1.0, Y2, tmp, 0.0);
  else
    X2.update(Teuchos::NO_TRANS, 1.0, Y2, tmp, 1.0);
}
开发者ID:00liujj，项目名称:trilinos，代码行数:56，代码来源:LOCA_BorderedSolver_HouseholderQR.C

示例4: 

LOCA::MultiContinuation::ExtendedMultiVector::ExtendedMultiVector(
		     const Teuchos::RCP<LOCA::GlobalData>& global_data,
		     const NOX::Abstract::MultiVector& xVec,
		     const NOX::Abstract::MultiVector::DenseMatrix& params) :
  LOCA::Extended::MultiVector(global_data, xVec.numVectors(), 1, 
			      params.numRows())
{
  LOCA::Extended::MultiVector::setMultiVectorPtr(0, xVec.clone(NOX::DeepCopy));
  LOCA::Extended::MultiVector::getScalars()->assign(params);
}
开发者ID:haripandey，项目名称:trilinos，代码行数:10，代码来源:LOCA_MultiContinuation_ExtendedMultiVector.C

示例5: sqrt

void
LOCA::BorderedSolver::HouseholderQR::computeHouseholderVector(
              int col,
              const NOX::Abstract::MultiVector::DenseMatrix& A1,
              const NOX::Abstract::MultiVector& A2,
              NOX::Abstract::MultiVector::DenseMatrix& V1,
              NOX::Abstract::MultiVector& V2,
              double& beta)
{
  double houseP = A1(col,col);

  V1(0,0) = 1.0;
  V2[0] = A2[col];

  double sigma = A2[col].innerProduct(A2[col]);
  for (int i=col+1; i<A1.numRows(); i++)
    sigma += A1(i,col)*A1(i,col);

  if (sigma == 0.0)
    beta = 0.0;
  else {
    double mu = sqrt(houseP*houseP + sigma);
    if (houseP <= 0.0)
      houseP = houseP - mu;
    else
      houseP = -sigma / (houseP + mu);
    beta = 2.0*houseP*houseP/(sigma + houseP*houseP);

    V2.scale(1.0/houseP);
    for (int i=1; i<V1.numRows(); i++)
      V1(i,0) = A1(i+col,col) / houseP;
  }


  return;
}
开发者ID:00liujj，项目名称:trilinos，代码行数:36，代码来源:LOCA_BorderedSolver_HouseholderQR.C

示例6: 

void
NOX::Thyra::MultiVector::
multiply(double alpha,
     const NOX::Abstract::MultiVector& y,
     NOX::Abstract::MultiVector::DenseMatrix& b) const
{
  const NOX::Thyra::MultiVector& yy =
    dynamic_cast<const NOX::Thyra::MultiVector&>(y);

  int m = b.numRows();
  int n = b.numCols();
  Teuchos::RCP< ::Thyra::MultiVectorBase<double> > bb =
    ::Thyra::createMembersView(
      yy.thyraMultiVec->domain(),
      RTOpPack::SubMultiVectorView<double>(0, m, 0, n,
        Teuchos::arcp(b.values(), 0, b.stride()*b.numCols(), false),
        b.stride()
        )
      );

  ::Thyra::apply(*yy.thyraMultiVec, ::Thyra::CONJTRANS, *thyraMultiVec,
                   bb.ptr(), alpha, 0.0);
}
开发者ID:ChiahungTai，项目名称:Trilinos，代码行数:23，代码来源:NOX_Thyra_MultiVector.C

示例7: T

NOX::Abstract::Group::ReturnType 
LOCA::BorderedSolver::LowerTriangularBlockElimination::
solve(Teuchos::ParameterList& params,
      const LOCA::BorderedSolver::AbstractOperator& op,
      const LOCA::MultiContinuation::ConstraintInterface& B,
      const NOX::Abstract::MultiVector::DenseMatrix& C,
      const NOX::Abstract::MultiVector* F,
      const NOX::Abstract::MultiVector::DenseMatrix* G,
      NOX::Abstract::MultiVector& X,
      NOX::Abstract::MultiVector::DenseMatrix& Y) const
{
  string callingFunction = 
    "LOCA::BorderedSolver::LowerTriangularBlockElimination::solve()";
  NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;
  NOX::Abstract::Group::ReturnType status;

  // Determine if X or Y is zero
  bool isZeroF = (F == NULL);
  bool isZeroG = (G == NULL);
  bool isZeroB = B.isDXZero();
  bool isZeroX = isZeroF;
  bool isZeroY = isZeroG && (isZeroB  || isZeroX);

  // First compute X
  if (isZeroX)
    X.init(0.0);
  else {
    // Solve X = J^-1 F, note F must be nonzero
    status = op.applyInverse(params, *F, X);
    finalStatus = 
      globalData->locaErrorCheck->combineAndCheckReturnTypes(status, 
							     finalStatus,
							     callingFunction);
  }

  // Now compute Y
  if (isZeroY)
    Y.putScalar(0.0);
  else {
    // Compute G - B^T*X and store in Y
    if (isZeroG) 
      B.multiplyDX(-1.0, X, Y);
    else {
      Y.assign(*G);
      if (!isZeroB && !isZeroX) {
	NOX::Abstract::MultiVector::DenseMatrix T(Y.numRows(),Y.numCols());
	B.multiplyDX(1.0, X, T);
	Y -= T;
      }
    }

    // Overwrite Y with Y = C^-1 * (G - B^T*X)
    NOX::Abstract::MultiVector::DenseMatrix M(C);
    int *ipiv = new int[M.numRows()];
    Teuchos::LAPACK<int,double> L;
    int info;
    L.GETRF(M.numRows(), M.numCols(), M.values(), M.stride(), ipiv, &info);
    if (info != 0) {
      status = NOX::Abstract::Group::Failed;
      finalStatus = 
	globalData->locaErrorCheck->combineAndCheckReturnTypes(
							      status, 
							      finalStatus,
							      callingFunction);
    }
    L.GETRS('N', M.numRows(), Y.numCols(), M.values(), M.stride(), ipiv, 
	    Y.values(), Y.stride(), &info);
    delete [] ipiv;
    if (info != 0) {
      status = NOX::Abstract::Group::Failed;
      finalStatus = 
	globalData->locaErrorCheck->combineAndCheckReturnTypes(
							     status, 
							     finalStatus,
							     callingFunction);
    }
  }

  return finalStatus;
}
开发者ID:haripandey，项目名称:trilinos，代码行数:80，代码来源:LOCA_BorderedSolver_LowerTriangularBlockElimination.C


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