// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, W. Burgard
// All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are
// met:
//
// * Redistributions of source code must retain the above copyright notice,
//   this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
//   notice, this list of conditions and the following disclaimer in the
//   documentation and/or other materials provided with the distribution.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS
// IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
// TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
// PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
// HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

#ifndef G2O_SOLVER_H
#define G2O_SOLVER_H

#include "hyper_graph.h"
#include "batch_stats.h"
#include "sparse_block_matrix.h"
#include "g2o_core_api.h"
#include <cstddef>

namespace g2o {


  class SparseOptimizer;

  /**
   * \brief Generic interface for a sparse solver operating on a graph which solves one iteration of the linearized objective function
   */
  class G2O_CORE_API Solver
  {
    public:
      Solver();
      virtual ~Solver();

    public:
      /**
       * initialize the solver, called once before the first iteration
       */
      virtual bool init(SparseOptimizer* optimizer, bool online = false) = 0;

      /**
       * build the structure of the system
       */
      virtual bool buildStructure(bool zeroBlocks = false) = 0;
      /**
       * update the structures for online processing
       */
      virtual bool updateStructure(const std::vector<HyperGraph::Vertex*>& vset, const HyperGraph::EdgeSet& edges) = 0;
      /**
       * build the current system
       */
      virtual bool buildSystem() = 0;

      /**
       * solve Ax = b
       */
      virtual bool solve() = 0;

      /**
       * computes the block diagonal elements of the pattern specified in the input
       * and stores them in given SparseBlockMatrix
       */
      virtual bool computeMarginals(SparseBlockMatrix<Eigen::MatrixXd>& spinv, const std::vector<std::pair<int, int> >& blockIndices) = 0;

      /**
       * update the system while performing Levenberg, i.e., modifying the diagonal
       * components of A by doing += lambda along the main diagonal of the Matrix.
       * Note that this function may be called with a positive and a negative lambda.
       * The latter is used to undo a former modification.
       * If backup is true, then the solver should store a backup of the diagonal, which
       * can be restored by restoreDiagonal()
       */
      virtual bool setLambda(double lambda, bool backup = false) = 0;

      /**
       * restore a previosly made backup of the diagonal
       */
      virtual void restoreDiagonal() = 0;

      //! return x, the solution vector
      double* x() { return _x;}
      const double* x() const { return _x;}
      //! return b, the right hand side of the system
      double* b() { return _b;}
      const double* b() const { return _b;}

      //! return the size of the solution vector (x) and b
      size_t vectorSize() const { return _xSize;}

      //! the optimizer (graph) on which the solver works
      SparseOptimizer* optimizer() const { return _optimizer;}
      void setOptimizer(SparseOptimizer* optimizer);

      //! the system is Levenberg-Marquardt
      bool levenberg() const { return _isLevenberg;}
      void setLevenberg(bool levenberg);

      /**
       * does this solver support the Schur complement for solving a system consisting of poses and
       * landmarks. Re-implemement in a derived solver, if your solver supports it.
       */
      virtual bool supportsSchur() {return false;}

      //! should the solver perform the schur complement or not
      virtual bool schur()=0;
      virtual void setSchur(bool s)=0;

      size_t additionalVectorSpace() const { return _additionalVectorSpace;}
      void setAdditionalVectorSpace(size_t s);

      /**
       * write debug output of the Hessian if system is not positive definite
       */
      virtual void setWriteDebug(bool) = 0;
      virtual bool writeDebug() const = 0;

      //! write the hessian to disk using the specified file name
      virtual bool saveHessian(const std::string& /*fileName*/) const = 0;

    protected:
      SparseOptimizer* _optimizer;
      double* _x;
      double* _b;
      size_t _xSize, _maxXSize;
      bool _isLevenberg; ///< the system we gonna solve is a Levenberg-Marquardt system
      size_t _additionalVectorSpace;

      void resizeVector(size_t sx);

    private:
      // Disable the copy constructor and assignment operator
      Solver(const Solver&) { }
      Solver& operator= (const Solver&) { return *this; }
  };
} // end namespace

#endif
