// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// modification, are permitted provided that the following conditions are met:
//
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//   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.
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//   used to endorse or promote products derived from this software without
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//
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// Author: sameeragarwal@google.com (Sameer Agarwal)

#ifndef CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_
#define CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_

#include <string>
#include <vector>

#include "ceres/evaluator.h"
#include "ceres/minimizer.h"
#include "ceres/problem_impl.h"
#include "ceres/solver.h"

namespace ceres {
namespace internal {

class Program;
class LinearSolver;

// Given a Program, and a ParameterBlockOrdering which partitions
// (non-exhaustively) the Hessian matrix into independent sets,
// perform coordinate descent on the parameter blocks in the
// ordering. The independent set structure allows for all parameter
// blocks in the same independent set to be optimized in parallel, and
// the order of the independent set determines the order in which the
// parameter block groups are optimized.
//
// The minimizer assumes that none of the parameter blocks in the
// program are constant.
class CoordinateDescentMinimizer : public Minimizer {
 public:
  bool Init(const Program& program,
            const ProblemImpl::ParameterMap& parameter_map,
            const ParameterBlockOrdering& ordering,
            std::string* error);

  // Minimizer interface.
  virtual ~CoordinateDescentMinimizer();
  virtual void Minimize(const Minimizer::Options& options,
                        double* parameters,
                        Solver::Summary* summary);

  // Verify that each group in the ordering forms an independent set.
  static bool IsOrderingValid(const Program& program,
                              const ParameterBlockOrdering& ordering,
                              std::string* message);

  // Find a recursive decomposition of the Hessian matrix as a set
  // of independent sets of decreasing size and invert it. This
  // seems to work better in practice, i.e., Cameras before
  // points.
  static ParameterBlockOrdering* CreateOrdering(const Program& program);

 private:
  void Solve(Program* program,
             LinearSolver* linear_solver,
             double* parameters,
             Solver::Summary* summary);

  std::vector<ParameterBlock*> parameter_blocks_;
  std::vector<std::vector<ResidualBlock*> > residual_blocks_;
  // The optimization is performed in rounds. In each round all the
  // parameter blocks that form one independent set are optimized in
  // parallel. This array, marks the boundaries of the independent
  // sets in parameter_blocks_.
  std::vector<int> independent_set_offsets_;

  Evaluator::Options evaluator_options_;
};

}  // namespace internal
}  // namespace ceres

#endif  // CERES_INTERNAL_COORDINATE_DESCENT_MINIMIZER_H_
