// Ceres Solver - A fast non-linear least squares minimizer
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// http://code.google.com/p/ceres-solver/
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// Author: sameeragarwal@google.com (Sameer Agarwal)
//
// Class for loading and holding in memory bundle adjustment problems
// from the BAL (Bundle Adjustment in the Large) dataset from the
// University of Washington.
//
// For more details see http://grail.cs.washington.edu/projects/bal/

#ifndef CERES_EXAMPLES_BAL_PROBLEM_H_
#define CERES_EXAMPLES_BAL_PROBLEM_H_

#include <string>

namespace ceres {
namespace examples {

class BALProblem {
 public:
  explicit BALProblem(const std::string filename, bool use_quaternions);
  ~BALProblem();

  int camera_block_size()      const { return use_quaternions_ ? 10 : 9; }
  int point_block_size()       const { return 3;                         }
  int num_cameras()            const { return num_cameras_;              }
  int num_points()             const { return num_points_;               }
  int num_observations()       const { return num_observations_;         }
  int num_parameters()         const { return num_parameters_;           }
  const int* point_index()     const { return point_index_;              }
  const int* camera_index()    const { return camera_index_;             }
  const double* observations() const { return observations_;             }
  const double* parameters()   const { return parameters_;               }
  double* mutable_cameras()          { return parameters_;               }
  double* mutable_points() {
    return parameters_  + camera_block_size() * num_cameras_;
  }

 private:
  int num_cameras_;
  int num_points_;
  int num_observations_;
  int num_parameters_;
  bool use_quaternions_;

  int* point_index_;
  int* camera_index_;
  double* observations_;
  // The parameter vector is laid out as follows
  // [camera_1, ..., camera_n, point_1, ..., point_m]
  double* parameters_;
};

}  // namespace examples
}  // namespace ceres

#endif  // CERES_EXAMPLES_BAL_PROBLEM_H_