C++ DenseMatrix::numCols方法代码示例

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);

}

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;
}

NOX::Abstract::Group::ReturnType
LOCA::MultiContinuation::CompositeConstraint::multiplyDX(
		      double alpha, 
		      const NOX::Abstract::MultiVector& input_x,
	              NOX::Abstract::MultiVector::DenseMatrix& result_p) const
{
  std::string callingFunction = 
    "LOCA::MultiContinuation::CompositeConstraint::multiplyDX()";
  NOX::Abstract::Group::ReturnType status;
  NOX::Abstract::Group::ReturnType finalStatus = NOX::Abstract::Group::Ok;

  // If dg/dx is zero for every constraint, result_p is zero
  if (isDXZero()) {
    result_p.putScalar(0.0);
    return finalStatus;
  }

  Teuchos::RCP<NOX::Abstract::MultiVector::DenseMatrix> result_p_sub;
  int num_rows;
  int num_cols = result_p.numCols();
  for (int i=0; i<numConstraintObjects; i++) {

    num_rows = constraintPtrs[i]->numConstraints();

    // if dg/dx is zero for this constraint, set corresponding entries of
    // result_p to zero
    if (constraintPtrs[i]->isDXZero()) {
      for (int j=0; j<num_rows; j++)
	for (int k=0; k<num_cols; k++)
	  result_p(indices[i][j],k) = 0.0;
    }
    else {

      // Create a sub view of rows indices[i][0] -- indices[i][end] 
      // of result_p 
      result_p_sub = 
	Teuchos::rcp(new NOX::Abstract::MultiVector::DenseMatrix(Teuchos::View,
								 result_p,
								 num_rows,
								 num_cols,
								 indices[i][0],
								 0));

      status = constraintPtrs[i]->multiplyDX(alpha, input_x, 
					     *result_p_sub);
      finalStatus = 
	globalData->locaErrorCheck->combineAndCheckReturnTypes(
							     status, 
							     finalStatus,
							     callingFunction);
    }

  }

  return finalStatus;
}

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);
}

// =============================================================================
// Compute result_p = alpha * dg/dx * input_x.
NOX::Abstract::Group::ReturnType
Ginla::FDM::Constraint::MinDist::
multiplyDX ( double                                    alpha,
             const NOX::Abstract::MultiVector        & input_x,
             NOX::Abstract::MultiVector::DenseMatrix & result_p
           ) const
{ 
  TEUCHOS_ASSERT( komplex_.is_valid_ptr() && !komplex_.is_null() );
  
  TEUCHOS_ASSERT_EQUALITY( result_p.numCols(), input_x.numVectors() );
  
  for ( int k=0; k<input_x.numVectors(); k++ )
  {
      const Epetra_Vector & xE =
              Teuchos::dyn_cast<const NOX::Epetra::Vector>( input_x[0] ).getEpetraVector();
      Teuchos::RCP<ComplexVector> xPsi = komplex_->real2complex( xE );

      result_p(0,k) = alpha * std::imag( psiRef_->dot(*xPsi) );
  }
  
  return NOX::Abstract::Group::Ok;
}

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;
}