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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
// 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.
// * Neither the name of Google Inc. nor the names of its contributors may be
// used to endorse or promote products derived from this software without
// specific prior written permission.
//
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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_PARAMETER_BLOCK_ORDERING_H_
#define CERES_INTERNAL_PARAMETER_BLOCK_ORDERING_H_
#include <vector>
#include "ceres/ordered_groups.h"
#include "ceres/graph.h"
#include "ceres/types.h"
namespace ceres {
namespace internal {
class Program;
class ParameterBlock;
// Uses an approximate independent set ordering to order the parameter
// blocks of a problem so that it is suitable for use with Schur
// complement based solvers. The output variable ordering contains an
// ordering of the parameter blocks and the return value is size of
// the independent set or the number of e_blocks (see
// schur_complement_solver.h for an explanation). Constant parameters
// are added to the end.
//
// The ordering vector has the structure
//
// ordering = [independent set,
// complement of the independent set,
// fixed blocks]
int ComputeSchurOrdering(const Program& program,
std::vector<ParameterBlock* >* ordering);
// Same as above, except that ties while computing the independent set
// ordering are resolved in favour of the order in which the parameter
// blocks occur in the program.
int ComputeStableSchurOrdering(const Program& program,
std::vector<ParameterBlock* >* ordering);
// Use an approximate independent set ordering to decompose the
// parameter blocks of a problem in a sequence of independent
// sets. The ordering covers all the non-constant parameter blocks in
// the program.
void ComputeRecursiveIndependentSetOrdering(const Program& program,
ParameterBlockOrdering* ordering);
// Builds a graph on the parameter blocks of a Problem, whose
// structure reflects the sparsity structure of the Hessian. Each
// vertex corresponds to a parameter block in the Problem except for
// parameter blocks that are marked constant. An edge connects two
// parameter blocks, if they co-occur in a residual block.
Graph<ParameterBlock*>* CreateHessianGraph(const Program& program);
// Iterate over each of the groups in order of their priority and fill
// summary with their sizes.
void OrderingToGroupSizes(const ParameterBlockOrdering* ordering,
std::vector<int>* group_sizes);
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_PARAMETER_BLOCK_ORDERING_H_