254 lines
12 KiB
C++
254 lines
12 KiB
C++
/*
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* NestedDissection-inl.h
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*
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* Created on: Nov 27, 2010
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* Author: nikai
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* Description:
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*/
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#pragma once
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#include <boost/make_shared.hpp>
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#include "partition/FindSeparator-inl.h"
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#include "OrderedSymbols.h"
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#include "NestedDissection.h"
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using namespace std;
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namespace gtsam { namespace partition {
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/* ************************************************************************* */
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template <class NLG, class SubNLG, class GenericGraph>
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NestedDissection<NLG, SubNLG, GenericGraph>::NestedDissection(
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const NLG& fg, const Ordering& ordering, const int numNodeStopPartition, const int minNodesPerMap, const bool verbose) :
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fg_(fg), ordering_(ordering){
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GenericUnaryGraph unaryFactors;
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GenericGraph gfg;
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boost::tie(unaryFactors, gfg) = fg.createGenericGraph(ordering);
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// build reverse mapping from integer to symbol
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int numNodes = ordering.size();
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int2symbol_.resize(numNodes);
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Ordering::const_iterator it = ordering.begin(), itLast = ordering.end();
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while(it != itLast)
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int2symbol_[it->second] = (it++)->first;
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vector<size_t> keys;
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keys.reserve(numNodes);
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for(int i=0; i<ordering.size(); ++i)
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keys.push_back(i);
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WorkSpace workspace(numNodes);
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root_ = recursivePartition(gfg, unaryFactors, keys, vector<size_t>(), numNodeStopPartition, minNodesPerMap, boost::shared_ptr<SubNLG>(), workspace, verbose);
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}
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/* ************************************************************************* */
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template <class NLG, class SubNLG, class GenericGraph>
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NestedDissection<NLG, SubNLG, GenericGraph>::NestedDissection(
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const NLG& fg, const Ordering& ordering, const boost::shared_ptr<Cuts>& cuts, const bool verbose) : fg_(fg), ordering_(ordering){
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GenericUnaryGraph unaryFactors;
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GenericGraph gfg;
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boost::tie(unaryFactors, gfg) = fg.createGenericGraph(ordering);
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// build reverse mapping from integer to symbol
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int numNodes = ordering.size();
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int2symbol_.resize(numNodes);
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Ordering::const_iterator it = ordering.begin(), itLast = ordering.end();
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while(it != itLast)
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int2symbol_[it->second] = (it++)->first;
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vector<size_t> keys;
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keys.reserve(numNodes);
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for(int i=0; i<ordering.size(); ++i)
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keys.push_back(i);
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WorkSpace workspace(numNodes);
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root_ = recursivePartition(gfg, unaryFactors, keys, vector<size_t>(), cuts, boost::shared_ptr<SubNLG>(), workspace, verbose);
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}
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/* ************************************************************************* */
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template <class NLG, class SubNLG, class GenericGraph>
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boost::shared_ptr<SubNLG> NestedDissection<NLG, SubNLG, GenericGraph>::makeSubNLG(
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const NLG& fg, const vector<size_t>& frontals, const vector<size_t>& sep, const boost::shared_ptr<SubNLG>& parent) const {
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OrderedSymbols frontalKeys;
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BOOST_FOREACH(const size_t index, frontals)
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frontalKeys.push_back(int2symbol_[index]);
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UnorderedSymbols sepKeys;
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BOOST_FOREACH(const size_t index, sep)
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sepKeys.insert(int2symbol_[index]);
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return boost::make_shared<SubNLG>(fg, frontalKeys, sepKeys, parent);
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}
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/* ************************************************************************* */
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template <class NLG, class SubNLG, class GenericGraph>
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void NestedDissection<NLG, SubNLG, GenericGraph>::processFactor(
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const typename GenericGraph::value_type& factor, const std::vector<int>& partitionTable, // input
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vector<GenericGraph>& frontalFactors, NLG& sepFactors, vector<set<size_t> >& childSeps, // output factor graphs
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typename SubNLG::Weeklinks& weeklinks) const { // the links between child cliques
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list<size_t> sep_; // the separator variables involved in the current factor
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int partition1 = partitionTable[factor->key1.index];
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int partition2 = partitionTable[factor->key2.index];
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if (partition1 <= 0 && partition2 <= 0) { // is a factor in the current clique
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sepFactors.push_back(fg_[factor->index]);
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}
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else if (partition1 > 0 && partition2 > 0 && partition1 != partition2) { // is a weeklink (factor between two child cliques)
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weeklinks.push_back(fg_[factor->index]);
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}
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else if (partition1 > 0 && partition2 > 0 && partition1 == partition2) { // is a local factor in one of the child cliques
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frontalFactors[partition1 - 1].push_back(factor);
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}
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else { // is a joint factor in the child clique (involving varaibles in the current clique)
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if (partition1 > 0 && partition2 <= 0) {
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frontalFactors[partition1 - 1].push_back(factor);
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childSeps[partition1 - 1].insert(factor->key2.index);
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} else if (partition1 <= 0 && partition2 > 0) {
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frontalFactors[partition2 - 1].push_back(factor);
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childSeps[partition2 - 1].insert(factor->key1.index);
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} else
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throw runtime_error("processFactor: unexpected entries in the partition table!");
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}
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}
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/* ************************************************************************* */
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/**
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* given a factor graph and its partition {nodeMap}, split the factors between the child cliques ({frontalFactors})
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* and the current clique ({sepFactors}). Also split the variables between the child cliques ({childFrontals})
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* and the current clique ({localFrontals}). Those separator variables involved in {frontalFactors} are put into
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* the correspoding ordering in {childSeps}.
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*/
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// TODO: frontalFactors and localFrontals should be generated in findSeparator
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template <class NLG, class SubNLG, class GenericGraph>
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void NestedDissection<NLG, SubNLG, GenericGraph>::partitionFactorsAndVariables(
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const GenericGraph& fg, const GenericUnaryGraph& unaryFactors, const std::vector<size_t>& keys, //input
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const std::vector<int>& partitionTable, const int numSubmaps, // input
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vector<GenericGraph>& frontalFactors, vector<GenericUnaryGraph>& frontalUnaryFactors, NLG& sepFactors, // output factor graphs
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vector<vector<size_t> >& childFrontals, vector<vector<size_t> >& childSeps, vector<size_t>& localFrontals, // output sub-orderings
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typename SubNLG::Weeklinks& weeklinks) const { // the links between child cliques
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// make three lists of variables A, B, and C
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int partition;
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childFrontals.resize(numSubmaps);
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BOOST_FOREACH(const size_t key, keys){
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partition = partitionTable[key];
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switch (partition) {
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case -1: break; // the separator of the separator variables
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case 0: localFrontals.push_back(key); break; // the separator variables
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default: childFrontals[partition-1].push_back(key); // the frontal variables
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}
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}
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// group the factors to {frontalFactors} and {sepFactors},and find the joint variables
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vector<set<size_t> > childSeps_;
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childSeps_.resize(numSubmaps);
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childSeps.reserve(numSubmaps);
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frontalFactors.resize(numSubmaps);
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frontalUnaryFactors.resize(numSubmaps);
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BOOST_FOREACH(typename GenericGraph::value_type factor, fg)
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processFactor(factor, partitionTable, frontalFactors, sepFactors, childSeps_, weeklinks);
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BOOST_FOREACH(const set<size_t>& childSep, childSeps_)
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childSeps.push_back(vector<size_t>(childSep.begin(), childSep.end()));
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// add unary factor to the current cluster or pass it to one of the child clusters
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BOOST_FOREACH(const sharedGenericUnaryFactor& unaryFactor_, unaryFactors) {
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partition = partitionTable[unaryFactor_->key.index];
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if (!partition) sepFactors.push_back(fg_[unaryFactor_->index]);
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else frontalUnaryFactors[partition-1].push_back(unaryFactor_);
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}
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}
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/* ************************************************************************* */
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template <class NLG, class SubNLG, class GenericGraph>
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NLG NestedDissection<NLG, SubNLG, GenericGraph>::collectOriginalFactors(
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const GenericGraph& gfg, const GenericUnaryGraph& unaryFactors) const {
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NLG sepFactors;
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typename GenericGraph::const_iterator it = gfg.begin(), itLast = gfg.end();
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while(it!=itLast) sepFactors.push_back(fg_[(*it++)->index]);
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BOOST_FOREACH(const sharedGenericUnaryFactor& unaryFactor_, unaryFactors)
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sepFactors.push_back(fg_[unaryFactor_->index]);
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return sepFactors;
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}
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/* ************************************************************************* */
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template <class NLG, class SubNLG, class GenericGraph>
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boost::shared_ptr<SubNLG> NestedDissection<NLG, SubNLG, GenericGraph>::recursivePartition(
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const GenericGraph& gfg, const GenericUnaryGraph& unaryFactors, const vector<size_t>& frontals, const vector<size_t>& sep,
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const int numNodeStopPartition, const int minNodesPerMap, const boost::shared_ptr<SubNLG>& parent, WorkSpace& workspace, const bool verbose) const {
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// if no split needed
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NLG sepFactors; // factors that should remain in the current cluster
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if (frontals.size() <= numNodeStopPartition || gfg.size() <= numNodeStopPartition) {
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sepFactors = collectOriginalFactors(gfg, unaryFactors);
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return makeSubNLG(sepFactors, frontals, sep, parent);
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}
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// find the nested dissection separator
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int numSubmaps = findSeparator(gfg, frontals, minNodesPerMap, workspace, verbose, int2symbol_, NLG::reduceGraph(),
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NLG::minNrConstraintsPerCamera(),NLG::minNrConstraintsPerLandmark());
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partition::PartitionTable& partitionTable = workspace.partitionTable;
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if (numSubmaps == 0) throw runtime_error("recursivePartition: get zero submap after ND!");
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// split the factors between child cliques and the current clique
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vector<GenericGraph> frontalFactors; vector<GenericUnaryGraph> frontalUnaryFactors; typename SubNLG::Weeklinks weeklinks;
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vector<size_t> localFrontals; vector<vector<size_t> > childFrontals, childSeps;
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partitionFactorsAndVariables(gfg, unaryFactors, frontals, partitionTable, numSubmaps,
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frontalFactors, frontalUnaryFactors, sepFactors, childFrontals, childSeps, localFrontals, weeklinks);
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// make a new cluster
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boost::shared_ptr<SubNLG> current = makeSubNLG(sepFactors, localFrontals, sep, parent);
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current->setWeeklinks(weeklinks);
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// check whether all the submaps are fully constrained
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for (int i=0; i<numSubmaps; i++) {
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checkSingularity(frontalFactors[i], childFrontals[i], workspace, NLG::minNrConstraintsPerCamera(),NLG::minNrConstraintsPerLandmark());
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}
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// create child clusters
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for (int i=0; i<numSubmaps; i++) {
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boost::shared_ptr<SubNLG> child = recursivePartition(frontalFactors[i], frontalUnaryFactors[i], childFrontals[i], childSeps[i],
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numNodeStopPartition, minNodesPerMap, current, workspace, verbose);
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current->addChild(child);
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}
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return current;
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}
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/* ************************************************************************* */
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template <class NLG, class SubNLG, class GenericGraph>
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boost::shared_ptr<SubNLG> NestedDissection<NLG, SubNLG, GenericGraph>::recursivePartition(
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const GenericGraph& gfg, const GenericUnaryGraph& unaryFactors, const vector<size_t>& frontals, const vector<size_t>& sep,
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const boost::shared_ptr<Cuts>& cuts, const boost::shared_ptr<SubNLG>& parent, WorkSpace& workspace, const bool verbose) const {
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// if there is no need to cut any more
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NLG sepFactors; // factors that should remain in the current cluster
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if (!cuts.get()) {
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sepFactors = collectOriginalFactors(gfg, unaryFactors);
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return makeSubNLG(sepFactors, frontals, sep, parent);
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}
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// retrieve the current partitioning info
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int numSubmaps = 2;
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partition::PartitionTable& partitionTable = cuts->partitionTable;
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// split the factors between child cliques and the current clique
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vector<GenericGraph> frontalFactors; vector<GenericUnaryGraph> frontalUnaryFactors; typename SubNLG::Weeklinks weeklinks;
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vector<size_t> localFrontals; vector<vector<size_t> > childFrontals, childSeps;
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partitionFactorsAndVariables(gfg, unaryFactors, frontals, partitionTable, numSubmaps,
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frontalFactors, frontalUnaryFactors, sepFactors, childFrontals, childSeps, localFrontals, weeklinks);
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// make a new cluster
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boost::shared_ptr<SubNLG> current = makeSubNLG(sepFactors, localFrontals, sep, parent);
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current->setWeeklinks(weeklinks);
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// create child clusters
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for (int i=0; i<2; i++) {
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boost::shared_ptr<SubNLG> child = recursivePartition(frontalFactors[i], frontalUnaryFactors[i], childFrontals[i], childSeps[i],
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cuts->children.empty() ? boost::shared_ptr<Cuts>() : cuts->children[i], current, workspace, verbose);
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current->addChild(child);
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}
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return current;
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}
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}} //namespace
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