SparseLUSolverTraits.h

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 *
 *  Copyright NumFOCUS
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         https://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
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 *=========================================================================*/
#ifndef SparseLUSolverTraits_h
#define SparseLUSolverTraits_h
 
#include "itk_eigen.h"
#include ITK_EIGEN(Sparse)
#include ITK_EIGEN(SparseLU)

template <typename T = double>
class SparseLUSolverTraits
{
public:
  using ValueType = T;
  using MatrixType = Eigen::SparseMatrix<ValueType>;
  using VectorType = Eigen::Matrix<ValueType, Eigen::Dynamic, 1>;
  using SolverType = Eigen::SparseLU<MatrixType>;
 
  static bool
  IsDirectSolver()
  {
    return true;
  }

  static MatrixType
  InitializeSparseMatrix(const unsigned int & iN)
  {
    return MatrixType(iN, iN);
  }

  static MatrixType
  InitializeSparseMatrix(const unsigned int & iRow, const unsigned int & iCol)
  {
    return MatrixType(iRow, iCol);
  }

  static VectorType
  InitializeVector(const unsigned int & iN)
  {
    return VectorType(iN);
  }

  static void
  FillMatrix(MatrixType & iA, const unsigned int & iR, const unsigned int & iC, const ValueType & iV)
  {
    iA.coeffRef(iR, iC) = iV;
  }

  static void
  AddToMatrix(MatrixType & iA, const unsigned int & iR, const unsigned int & iC, const ValueType & iV)
  {
    iA.coeffRef(iR, iC) += iV;
  }

  static void
  MatVecMult(const MatrixType & iA, const VectorType & iB, VectorType & oX)
  {
    oX = iA * iB;
  }

  static bool
  Solve(const MatrixType & iA, const VectorType & iB, VectorType & oX)
  {
    // Eigen::SparseLU copies and compresses the matrix internally
    // (analyzePattern), so no manual copy/compress is needed here.
    SolverType solver(iA);
    oX = solver.solve(iB);
    return solver.info() == Eigen::Success;
  }

  static bool
  Solve(const MatrixType & iA,
        const VectorType & iBx,
        const VectorType & iBy,
        const VectorType & iBz,
        VectorType &       oX,
        VectorType &       oY,
        VectorType &       oZ)
  {
    // Eigen::SparseLU copies and compresses the matrix internally.
    SolverType solver(iA);
    Solve(solver, iBx, iBy, iBz, oX, oY, oZ);
    return solver.info() == Eigen::Success;
  }

  static bool
  Solve(const MatrixType & iA, const VectorType & iBx, const VectorType & iBy, VectorType & oX, VectorType & oY)
  {
    // Eigen::SparseLU copies and compresses the matrix internally.
    SolverType solver(iA);
    Solve(solver, iBx, iBy, oX, oY);
    return solver.info() == Eigen::Success;
  }

  static void
  Solve(SolverType & solver, const VectorType & iB, VectorType & oX)
  {
    oX = solver.solve(iB);
  }

  static void
  Solve(SolverType &       solver,
        const VectorType & iBx,
        const VectorType & iBy,
        const VectorType & iBz,
        VectorType &       oX,
        VectorType &       oY,
        VectorType &       oZ)
  {
    oX = solver.solve(iBx);
    oY = solver.solve(iBy);
    oZ = solver.solve(iBz);
  }

  static void
  Solve(SolverType & solver, const VectorType & iBx, const VectorType & iBy, VectorType & oX, VectorType & oY)
  {
    oX = solver.solve(iBx);
    oY = solver.solve(iBy);
  }
};
 
#endif