90 lines
2.5 KiB
C++
90 lines
2.5 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file MetisIndex.h
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* @author Andrew Melim
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* @date Oct. 10, 2014
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*/
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#pragma once
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#include <vector>
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#include <boost/foreach.hpp>
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#include <gtsam/base/FastList.h>
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#include <gtsam/base/types.h>
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#include <gtsam/base/timing.h>
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#include <gtsam/inference/Key.h>
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#include <gtsam/inference/FactorGraph.h>
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#include <gtsam/3rdparty/metis/include/metis.h>
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#include <boost/bimap.hpp>
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namespace gtsam {
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/**
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* The MetisIndex class converts a factor graph into the Compressed Sparse Row format for use in
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* METIS algorithms. Specifically, two vectors store the adjacency structure of the graph. It is built
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* from a factor graph prior to elimination, and stores the list of factors
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* that involve each variable.
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* \nosubgrouping
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*/
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class GTSAM_EXPORT MetisIndex
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{
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public:
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typedef boost::shared_ptr<MetisIndex> shared_ptr;
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typedef boost::bimap<Key, idx_t> bm_type;
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private:
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FastVector<idx_t> xadj_; // Index of node's adjacency list in adj
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FastVector<idx_t> adj_; // Stores ajacency lists of all nodes, appended into a single vector
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FastVector<idx_t> iadj_; // Integer keys for passing into metis. One to one mapping with adj_;
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boost::bimap<Key, idx_t> intKeyBMap_; // Stores Key <-> integer value relationship
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size_t nFactors_; // Number of factors in the original factor graph
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size_t nKeys_;
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public:
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/// @name Standard Constructors
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/// @{
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/** Default constructor, creates empty MetisIndex */
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MetisIndex() : nFactors_(0), nKeys_(0) {}
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template<class FG>
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MetisIndex(const FG& factorGraph) : nFactors_(0), nKeys_(0) {
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augment(factorGraph); }
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~MetisIndex(){}
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/// @}
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/// @name Advanced Interface
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/// @{
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/**
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* Augment the variable index with new factors. This can be used when
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* solving problems incrementally.
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*/
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template<class FACTOR>
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void augment(const FactorGraph<FACTOR>& factors);
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std::vector<idx_t> xadj() const { return xadj_; }
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std::vector<idx_t> adj() const { return adj_; }
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size_t nValues() const { return nKeys_; }
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Key intToKey(idx_t value) const {
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assert(value >= 0);
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return intKeyBMap_.right.find(value)->second;
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}
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/// @}
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};
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}
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#include <gtsam/inference/MetisIndex-inl.h>
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