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/* */
/* Copyright 2014 by Thorsten Beier and Ullrich Koethe */
/* */
/* This file is part of the VIGRA computer vision library. */
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/************************************************************************/
/**
* This header provides definitions of graph-related algorithms
*/
#ifndef VIGRA_GRAPH_ALGORITHMS_HXX
#define VIGRA_GRAPH_ALGORITHMS_HXX
/*std*/
#include <algorithm>
#include <vector>
#include <functional>
#include <set>
#include <iomanip>
/*vigra*/
#include "graphs.hxx"
#include "graph_generalization.hxx"
#include "multi_gridgraph.hxx"
#include "priority_queue.hxx"
#include "union_find.hxx"
#include "adjacency_list_graph.hxx"
#include "graph_maps.hxx"
#include "timing.hxx"
//#include "openmp_helper.hxx"
#include "functorexpression.hxx"
#include "array_vector.hxx"
namespace vigra{
/** \addtogroup GraphDataStructures
*/
//@{
namespace detail_graph_algorithms{
template <class GRAPH_MAP,class COMPERATOR>
struct GraphItemCompare
{
GraphItemCompare(const GRAPH_MAP & map,const COMPERATOR & comperator)
: map_(map),
comperator_(comperator){
}
template<class KEY>
bool operator()(const KEY & a, const KEY & b) const{
return comperator_(map_[a],map_[b]);
}
const GRAPH_MAP & map_;
const COMPERATOR & comperator_;
};
} // namespace detail_graph_algorithms
/// \brief get a vector of Edge descriptors
///
/// Sort the Edge descriptors given weights
/// and a comperator
template<class GRAPH,class WEIGHTS,class COMPERATOR>
void edgeSort(
const GRAPH & g,
const WEIGHTS & weights,
const COMPERATOR & comperator,
std::vector<typename GRAPH::Edge> & sortedEdges
){
sortedEdges.resize(g.edgeNum());
size_t c=0;
for(typename GRAPH::EdgeIt e(g);e!=lemon::INVALID;++e){
sortedEdges[c]=*e;
++c;
}
detail_graph_algorithms::GraphItemCompare<WEIGHTS,COMPERATOR> edgeComperator(weights,comperator);
std::sort(sortedEdges.begin(),sortedEdges.end(),edgeComperator);
}
/// \brief copy a lemon node map
template<class G,class A,class B>
void copyNodeMap(const G & g,const A & a ,B & b){
typename G::NodeIt iter(g);
while(iter!=lemon::INVALID){
b[*iter]=a[*iter];
++iter;
}
}
/// \brief copy a lemon edge map
template<class G,class A,class B>
void copyEdgeMap(const G & g,const A & a ,B & b){
typename G::EdgeIt iter(g);
while(iter!=lemon::INVALID){
b[*iter]=a[*iter];
++iter;
}
}
/// \brief fill a lemon node map
template<class G,class A,class T>
void fillNodeMap(const G & g, A & a, const T & value){
typename G::NodeIt iter(g);
while(iter!=lemon::INVALID){
a[*iter]=value;
++iter;
}
}
/// \brief fill a lemon edge map
template<class G,class A,class T>
void fillEdgeMap(const G & g,A & a ,const T & value){
typename G::EdgeIt iter(g);
while(iter!=lemon::INVALID){
a[*iter]=value;
++iter;
}
}
/// \brief make a region adjacency graph from a graph and labels w.r.t. that graph
///
/// \param graphIn : input graph
/// \param labels : labels w.r.t. graphIn
/// \param[out] rag : region adjacency graph
/// \param[out] affiliatedEdges : a vector of edges of graphIn for each edge in rag
/// \param ignoreLabel : optional label to ignore (default: -1 means no label will be ignored)
///
template<
class GRAPH_IN,
class GRAPH_IN_NODE_LABEL_MAP
>
void makeRegionAdjacencyGraph(
GRAPH_IN graphIn,
GRAPH_IN_NODE_LABEL_MAP labels,
AdjacencyListGraph & rag,
typename AdjacencyListGraph:: template EdgeMap< std::vector<typename GRAPH_IN::Edge> > & affiliatedEdges,
const Int64 ignoreLabel=-1
){
rag=AdjacencyListGraph();
typedef typename GraphMapTypeTraits<GRAPH_IN_NODE_LABEL_MAP>::Value LabelType;
typedef GRAPH_IN GraphIn;
typedef AdjacencyListGraph GraphOut;
typedef typename GraphIn::Edge EdgeGraphIn;
typedef typename GraphIn::NodeIt NodeItGraphIn;
typedef typename GraphIn::EdgeIt EdgeItGraphIn;
typedef typename GraphOut::Edge EdgeGraphOut;
for(NodeItGraphIn iter(graphIn);iter!=lemon::INVALID;++iter){
const LabelType l=labels[*iter];
if(ignoreLabel==-1 || static_cast<Int64>(l)!=ignoreLabel)
rag.addNode(l);
}
for(EdgeItGraphIn e(graphIn);e!=lemon::INVALID;++e){
const EdgeGraphIn edge(*e);
const LabelType lu = labels[graphIn.u(edge)];
const LabelType lv = labels[graphIn.v(edge)];
if( lu!=lv && ( ignoreLabel==-1 || (static_cast<Int64>(lu)!=ignoreLabel && static_cast<Int64>(lv)!=ignoreLabel) ) ){
// if there is an edge between lu and lv no new edge will be added
rag.addEdge( rag.nodeFromId(lu),rag.nodeFromId(lv));
}
}
//SET UP HYPEREDGES
affiliatedEdges.assign(rag);
for(EdgeItGraphIn e(graphIn);e!=lemon::INVALID;++e){
const EdgeGraphIn edge(*e);
const LabelType lu = labels[graphIn.u(edge)];
const LabelType lv = labels[graphIn.v(edge)];
//std::cout<<"edge between ?? "<<lu<<" "<<lv<<"\n";
if( lu!=lv && ( ignoreLabel==-1 || (static_cast<Int64>(lu)!=ignoreLabel && static_cast<Int64>(lv)!=ignoreLabel) ) ){
//std::cout<<"find edge between "<<lu<<" "<<lv<<"\n";
EdgeGraphOut ragEdge= rag.findEdge(rag.nodeFromId(lu),rag.nodeFromId(lv));
//std::cout<<"invalid?"<<bool(ragEdge==lemon::INVALID)<<" id "<<rag.id(ragEdge)<<"\n";
affiliatedEdges[ragEdge].push_back(edge);
//std::cout<<"write done\n";
}
}
}
template<unsigned int DIM, class DTAG, class AFF_EDGES>
size_t affiliatedEdgesSerializationSize(
const GridGraph<DIM,DTAG> & gridGraph,
const AdjacencyListGraph & rag,
const AFF_EDGES & affEdges
){
size_t size = 0;
typedef typename AdjacencyListGraph::EdgeIt EdgeIt;
typedef typename AdjacencyListGraph::Edge Edge;
for(EdgeIt iter(rag); iter!=lemon::INVALID; ++iter){
const Edge e(*iter);
size+=1;
size+=affEdges[e].size()*(DIM+1);
}
return size;
}
template<class OUT_ITER, unsigned int DIM, class DTAG, class AFF_EDGES>
void serializeAffiliatedEdges(
const GridGraph<DIM,DTAG> & gridGraph,
const AdjacencyListGraph & rag,
const AFF_EDGES & affEdges,
OUT_ITER outIter
){
typedef typename AdjacencyListGraph::EdgeIt EdgeIt;
typedef typename AdjacencyListGraph::Edge Edge;
typedef typename GridGraph<DIM,DTAG>::Edge GEdge;
for(EdgeIt iter(rag); iter!=lemon::INVALID; ++iter){
const Edge edge = *iter;
const size_t numAffEdge = affEdges[edge].size();
*outIter = numAffEdge; ++outIter;
for(size_t i=0; i<numAffEdge; ++i){
const GEdge gEdge = affEdges[edge][i];
for(size_t d=0; d<DIM+1; ++d){
*outIter = gEdge[d]; ++outIter;
}
}
}
}
template<class IN_ITER, unsigned int DIM, class DTAG, class AFF_EDGES>
void deserializeAffiliatedEdges(
const GridGraph<DIM,DTAG> & gridGraph,
const AdjacencyListGraph & rag,
AFF_EDGES & affEdges,
IN_ITER begin,
IN_ITER end
){
typedef typename AdjacencyListGraph::EdgeIt EdgeIt;
typedef typename AdjacencyListGraph::Edge Edge;
typedef typename GridGraph<DIM,DTAG>::Edge GEdge;
affEdges.assign(rag);
for(EdgeIt iter(rag); iter!=lemon::INVALID; ++iter){
const Edge edge = *iter;
const size_t numAffEdge = *begin; ++begin;
for(size_t i=0; i<numAffEdge; ++i){
GEdge gEdge;
for(size_t d=0; d<DIM+1; ++d){
gEdge[d]=*begin; ++begin;
}
affEdges[edge].push_back(gEdge);
}
}
}
/// \brief shortest path computer
template<class GRAPH,class WEIGHT_TYPE>
class ShortestPathDijkstra{
public:
typedef GRAPH Graph;
typedef typename Graph::Node Node;
typedef typename Graph::NodeIt NodeIt;
typedef typename Graph::Edge Edge;
typedef typename Graph::OutArcIt OutArcIt;
typedef WEIGHT_TYPE WeightType;
typedef ChangeablePriorityQueue<WeightType> PqType;
typedef typename Graph:: template NodeMap<Node> PredecessorsMap;
typedef typename Graph:: template NodeMap<WeightType> DistanceMap;
typedef ArrayVector<Node> DiscoveryOrder;
/// \ brief constructor from graph
ShortestPathDijkstra(const Graph & g)
: graph_(g),
pq_(g.maxNodeId()+1),
predMap_(g),
distMap_(g)
{
}
/// \brief run shortest path given edge weights
///
/// \param weights : edge weights encoding the distance between adjacent nodes (must be non-negative)
/// \param source : source node where shortest path should start
/// \param target : target node where shortest path should stop. If target is not given
/// or <tt>INVALID</tt>, the shortest path from source to all reachable nodes is computed
/// \param maxDistance : path search is terminated when the path length exceeds <tt>maxDistance</tt>
///
/// When a valid \a target is unreachable from \a source (either because the graph is disconnected
/// or \a maxDistance is exceeded), it is set to <tt>lemon::INVALID</tt>. In contrast, if \a target
/// was <tt>lemon::INVALID</tt> at the beginning, it will always be set to the last node
/// visited in the search.
template<class WEIGHTS>
void run(const WEIGHTS & weights, const Node & source,
const Node & target = lemon::INVALID,
WeightType maxDistance=NumericTraits<WeightType>::max())
{
this->initializeMaps(source);
runImpl(weights, target, maxDistance);
}
/// \brief run shortest path in a region of interest of a \ref GridGraph.
///
/// \param start : first point in the desired ROI.
/// \param stop : beyond the last point in the desired ROI (i.e. exclusive)
/// \param weights : edge weights encoding the distance between adjacent nodes (must be non-negative)
/// \param source : source node where shortest path should start
/// \param target : target node where shortest path should stop. If target is not given
/// or <tt>INVALID</tt>, the shortest path from source to all reachable nodes is computed
/// \param maxDistance : path search is terminated when the path length exceeds <tt>maxDistance</tt>
///
/// This version of <tt>run()</tt> restricts the path search to the ROI <tt>[start, stop)</tt> and only
/// works for instances of \ref GridGraph. Otherwise, it is identical to the standard <tt>run()</tt>
/// function.
template<class WEIGHTS>
void run(Node const & start, Node const & stop,
const WEIGHTS & weights, const Node & source,
const Node & target = lemon::INVALID,
WeightType maxDistance=NumericTraits<WeightType>::max())
{
vigra_precondition(allLessEqual(start, source) && allLess(source, stop),
"ShortestPathDijkstra::run(): source is not within ROI");
vigra_precondition(target == lemon::INVALID ||
(allLessEqual(start, target) && allLess(target, stop)),
"ShortestPathDijkstra::run(): target is not within ROI");
this->initializeMaps(source, start, stop);
runImpl(weights, target, maxDistance);
}
/// \brief run shortest path again with given edge weights
///
/// This only differs from standard <tt>run()</tt> by initialization: Instead of resetting
/// the entire graph, this only resets the nodes that have been visited in the
/// previous run, i.e. the contents of the array <tt>discoveryOrder()</tt>.
/// This will be much faster if only a small fraction of the nodes has to be reset.
template<class WEIGHTS>
void reRun(const WEIGHTS & weights, const Node & source,
const Node & target = lemon::INVALID,
WeightType maxDistance=NumericTraits<WeightType>::max())
{
this->reInitializeMaps(source);
runImpl(weights, target, maxDistance);
}
/// \brief run shortest path with given edge weights from multiple sources.
///
/// This is otherwise identical to standard <tt>run()</tt>, except that
/// <tt>source()</tt> returns <tt>lemon::INVALID</tt> after path search finishes.
template<class WEIGHTS, class ITER>
void
runMultiSource(const WEIGHTS & weights, ITER source_begin, ITER source_end,
const Node & target = lemon::INVALID,
WeightType maxDistance=NumericTraits<WeightType>::max())
{
this->initializeMapsMultiSource(source_begin, source_end);
runImpl(weights, target, maxDistance);
}
/// \brief run shortest path with given edge weights from multiple sources.
///
/// This is otherwise identical to standard <tt>run()</tt>, except that
/// <tt>source()</tt> returns <tt>lemon::INVALID</tt> after path search finishes.
template<class EFGE_WEIGHTS,class NODE_WEIGHTS, class ITER>
void
runMultiSource(
const EFGE_WEIGHTS & edgeWeights,
const NODE_WEIGHTS & nodeWeights,
ITER source_begin,
ITER source_end,
const Node & target = lemon::INVALID,
WeightType maxDistance = NumericTraits<WeightType>::max())
{
this->initializeMapsMultiSource(source_begin, source_end);
runImplWithNodeWeights(edgeWeights, nodeWeights, target, maxDistance);
}
/// \brief get the graph
const Graph & graph()const{
return graph_;
}
/// \brief get the source node
const Node & source()const{
return source_;
}
/// \brief get the target node
const Node & target()const{
return target_;
}
/// \brief check if explicit target is given
bool hasTarget()const{
return target_!=lemon::INVALID;
}
/// \brief get an array with all visited nodes, sorted by distance from source
const DiscoveryOrder & discoveryOrder() const{
return discoveryOrder_;
}
/// \brief get the predecessors node map (after a call of run)
const PredecessorsMap & predecessors()const{
return predMap_;
}
/// \brief get the distances node map (after a call of run)
const DistanceMap & distances()const{
return distMap_;
}
/// \brief get the distance to a rarget node (after a call of run)
WeightType distance(const Node & target)const{
return distMap_[target];
}
private:
template<class WEIGHTS>
void runImpl(const WEIGHTS & weights,
const Node & target = lemon::INVALID,
WeightType maxDistance=NumericTraits<WeightType>::max())
{
ZeroNodeMap<Graph, WEIGHT_TYPE> zeroNodeMap;
this->runImplWithNodeWeights(weights,zeroNodeMap, target, maxDistance);
}
template<class EDGE_WEIGHTS, class NODE_WEIGHTS>
void runImplWithNodeWeights(
const EDGE_WEIGHTS & edgeWeights,
const NODE_WEIGHTS & nodeWeights,
const Node & target = lemon::INVALID,
WeightType maxDistance=NumericTraits<WeightType>::max())
{
target_ = lemon::INVALID;
while(!pq_.empty() ){ //&& !finished){
const Node topNode(graph_.nodeFromId(pq_.top()));
if(distMap_[topNode] > maxDistance)
break; // distance threshold exceeded
pq_.pop();
discoveryOrder_.push_back(topNode);
if(topNode == target)
break;
// loop over all neigbours
for(OutArcIt outArcIt(graph_,topNode);outArcIt!=lemon::INVALID;++outArcIt){
const Node otherNode = graph_.target(*outArcIt);
const size_t otherNodeId = graph_.id(otherNode);
const WeightType otherNodeWeight = nodeWeights[otherNode];
if(pq_.contains(otherNodeId)){
const Edge edge(*outArcIt);
const WeightType currentDist = distMap_[otherNode];
const WeightType alternativeDist = distMap_[topNode]+edgeWeights[edge]+otherNodeWeight;
if(alternativeDist<currentDist){
pq_.push(otherNodeId,alternativeDist);
distMap_[otherNode]=alternativeDist;
predMap_[otherNode]=topNode;
}
}
else if(predMap_[otherNode]==lemon::INVALID){
const Edge edge(*outArcIt);
const WeightType initialDist = distMap_[topNode]+edgeWeights[edge]+otherNodeWeight;
if(initialDist<=maxDistance)
{
pq_.push(otherNodeId,initialDist);
distMap_[otherNode]=initialDist;
predMap_[otherNode]=topNode;
}
}
}
}
while(!pq_.empty() ){
const Node topNode(graph_.nodeFromId(pq_.top()));
predMap_[topNode]=lemon::INVALID;
pq_.pop();
}
if(target == lemon::INVALID || discoveryOrder_.back() == target)
target_ = discoveryOrder_.back(); // Means that target was reached. If, to the contrary, target
// was unreachable within maxDistance, target_ remains INVALID.
}
void initializeMaps(Node const & source){
for(NodeIt n(graph_); n!=lemon::INVALID; ++n){
const Node node(*n);
predMap_[node]=lemon::INVALID;
}
distMap_[source]=static_cast<WeightType>(0.0);
predMap_[source]=source;
discoveryOrder_.clear();
pq_.push(graph_.id(source),0.0);
source_=source;
}
void initializeMaps(Node const & source,
Node const & start, Node const & stop)
{
Node left_border = min(start, Node(1)),
right_border = min(predMap_.shape()-stop, Node(1)),
DONT_TOUCH = Node(lemon::INVALID) - Node(1);
initMultiArrayBorder(predMap_.subarray(start-left_border, stop+right_border),
left_border, right_border, DONT_TOUCH);
predMap_.subarray(start, stop) = lemon::INVALID;
predMap_[source]=source;
distMap_[source]=static_cast<WeightType>(0.0);
discoveryOrder_.clear();
pq_.push(graph_.id(source),0.0);
source_=source;
}
template <class ITER>
void initializeMapsMultiSource(ITER source, ITER source_end){
for(NodeIt n(graph_); n!=lemon::INVALID; ++n){
const Node node(*n);
predMap_[node]=lemon::INVALID;
}
discoveryOrder_.clear();
for( ; source != source_end; ++source)
{
distMap_[*source]=static_cast<WeightType>(0.0);
predMap_[*source]=*source;
pq_.push(graph_.id(*source),0.0);
}
source_=lemon::INVALID;
}
void reInitializeMaps(Node const & source){
for(unsigned int n=0; n<discoveryOrder_.size(); ++n){
predMap_[discoveryOrder_[n]]=lemon::INVALID;
}
distMap_[source]=static_cast<WeightType>(0.0);
predMap_[source]=source;
discoveryOrder_.clear();
pq_.push(graph_.id(source),0.0);
source_=source;
}
const Graph & graph_;
PqType pq_;
PredecessorsMap predMap_;
DistanceMap distMap_;
DiscoveryOrder discoveryOrder_;
Node source_;
Node target_;
};
/// \brief get the length in node units of a path
template<class NODE,class PREDECESSORS>
size_t pathLength(
const NODE source,
const NODE target,
const PREDECESSORS & predecessors
){
if(predecessors[target]==lemon::INVALID)
return 0;
else{
NODE currentNode = target;
size_t length=1;
while(currentNode!=source){
currentNode=predecessors[currentNode];
length+=1;
}
return length;
}
}
/// \brief Astar Shortest path search
template<class GRAPH,class WEIGHTS,class PREDECESSORS,class DISTANCE,class HEURSTIC>
void shortestPathAStar(
const GRAPH & graph,
const typename GRAPH::Node & source,
const typename GRAPH::Node & target,
const WEIGHTS & weights,
PREDECESSORS & predecessors,
DISTANCE & distance,
const HEURSTIC & heuristic
){
typedef GRAPH Graph;
typedef typename Graph::Edge Edge;
typedef typename Graph::Node Node;
typedef typename Graph::NodeIt NodeIt;
typedef typename Graph::OutArcIt OutArcIt;
typedef typename DISTANCE::value_type DistanceType;
typename GRAPH:: template NodeMap<bool> closedSet(graph);
vigra::ChangeablePriorityQueue<typename WEIGHTS::value_type> estimatedDistanceOpenSet(graph.maxNodeId()+1);
// initialize
for(NodeIt n(graph);n!=lemon::INVALID;++n){
const Node node(*n);
closedSet[node]=false;
distance[node]=std::numeric_limits<DistanceType>::infinity();
predecessors[node]=lemon::INVALID;
}
// distance and estimated distance for start node
distance[source]=static_cast<DistanceType>(0.0);
estimatedDistanceOpenSet.push(graph.id(source),heuristic(source,target));
// while any nodes left in openSet
while(!estimatedDistanceOpenSet.empty()){
// get the node with the lpwest estimated distance in the open set
const Node current = graph.nodeFromId(estimatedDistanceOpenSet.top());
// reached target?
if(current==target)
break;
// remove current from openSet
// add current to closedSet
estimatedDistanceOpenSet.pop();
closedSet[current]=true;
// iterate over neigbours of current
for(OutArcIt outArcIt(graph,current);outArcIt!=lemon::INVALID;++outArcIt){
// get neigbour node and id
const Node neighbour = graph.target(*outArcIt);
const size_t neighbourId = graph.id(neighbour);
// if neighbour is not yet in closedSet
if(!closedSet[neighbour]){
// get edge between current and neigbour
const Edge edge(*outArcIt);
// get tentative score
const DistanceType tenativeScore = distance[current] + weights[edge];
// neighbour NOT in openSet OR tentative score better than the current distance
if(!estimatedDistanceOpenSet.contains(neighbourId) || tenativeScore < distance[neighbour] ){
// set predecessors and distance
predecessors[neighbour]=current;
distance[neighbour]=tenativeScore;
// update the estimated cost from neighbour to target
// ( and neigbour will be (re)-added to openSet)
estimatedDistanceOpenSet.push(neighbourId,distance[neighbour]+heuristic(neighbour,target));
}
}
}
}
}
template<
class GRAPH,
class EDGE_WEIGHTS,
class NODE_WEIGHTS,
class SEED_NODE_MAP,
class WEIGHT_TYPE
>
void shortestPathSegmentation(
const GRAPH & graph,
const EDGE_WEIGHTS & edgeWeights,
const NODE_WEIGHTS & nodeWeights,
SEED_NODE_MAP & seeds
){
typedef GRAPH Graph;
typedef typename Graph::Node Node;
typedef typename Graph::NodeIt NodeIt;
typedef WEIGHT_TYPE WeightType;
// find seeds
std::vector<Node> seededNodes;
for(NodeIt n(graph);n!=lemon::INVALID;++n){
const Node node(*n);
// not a seed
if(seeds[node]!=0){
seededNodes.push_back(node);
}
}
// do shortest path
typedef ShortestPathDijkstra<Graph, WeightType> Sp;
typedef typename Sp::PredecessorsMap PredecessorsMap;
Sp sp(graph);
sp.runMultiSource(edgeWeights, nodeWeights, seededNodes.begin(), seededNodes.end());
const PredecessorsMap & predMap = sp.predecessors();
// do the labeling
for(NodeIt n(graph);n!=lemon::INVALID;++n){
Node node(*n);
if(seeds[node]==0){
int label = 0 ;
Node pred=predMap[node];
while(seeds[pred]==0){
pred=predMap[pred];
}
seeds[node]=seeds[pred];
}
}
}
namespace detail_watersheds_segmentation{
struct RawPriorityFunctor{
template<class L, class T>
T operator()(const L label,const T priority)const{
return priority;
}
};
template<class PRIORITY_TYPE,class LABEL_TYPE>
struct CarvingFunctor{
CarvingFunctor(const LABEL_TYPE backgroundLabel,
const PRIORITY_TYPE & factor,
const PRIORITY_TYPE & noPriorBelow
)
: backgroundLabel_(backgroundLabel),
factor_(factor),
noPriorBelow_(noPriorBelow){
}
PRIORITY_TYPE operator()(const LABEL_TYPE label,const PRIORITY_TYPE priority)const{
if(priority>=noPriorBelow_)
return (label==backgroundLabel_ ? priority*factor_ : priority);
else{
return priority;
}
}
LABEL_TYPE backgroundLabel_;
PRIORITY_TYPE factor_;
PRIORITY_TYPE noPriorBelow_;
};
template<
class GRAPH,
class EDGE_WEIGHTS,
class SEEDS,
class PRIORITY_MANIP_FUNCTOR,
class LABELS
>
void edgeWeightedWatershedsSegmentationImpl(
const GRAPH & g,
const EDGE_WEIGHTS & edgeWeights,
const SEEDS & seeds,
PRIORITY_MANIP_FUNCTOR & priorManipFunctor,
LABELS & labels
){
typedef GRAPH Graph;
typedef typename Graph::Edge Edge;
typedef typename Graph::Node Node;
typedef typename Graph::NodeIt NodeIt;
typedef typename Graph::OutArcIt OutArcIt;
typedef typename EDGE_WEIGHTS::Value WeightType;
typedef typename LABELS::Value LabelType;
//typedef typename Graph:: template EdgeMap<bool> EdgeBoolMap;
typedef PriorityQueue<Edge,WeightType,true> PQ;
PQ pq;
//EdgeBoolMap inPQ(g);
copyNodeMap(g,seeds,labels);
//fillEdgeMap(g,inPQ,false);
// put edges from nodes with seed on pq
for(NodeIt n(g);n!=lemon::INVALID;++n){
const Node node(*n);
if(labels[node]!=static_cast<LabelType>(0)){
for(OutArcIt a(g,node);a!=lemon::INVALID;++a){
const Edge edge(*a);
const Node neigbour=g.target(*a);
//std::cout<<"n- node "<<g.id(neigbour)<<"\n";
if(labels[neigbour]==static_cast<LabelType>(0)){
const WeightType priority = priorManipFunctor(labels[node],edgeWeights[edge]);
pq.push(edge,priority);
//inPQ[edge]=true;
}
}
}
}
while(!pq.empty()){
const Edge edge = pq.top();
pq.pop();
const Node u = g.u(edge);
const Node v = g.v(edge);
const LabelType lU = labels[u];
const LabelType lV = labels[v];
if(lU==0 && lV==0){
throw std::runtime_error("both have no labels");
}
else if(lU!=0 && lV!=0){
// nothing to do
}
else{
const Node unlabeledNode = lU==0 ? u : v;
const LabelType label = lU==0 ? lV : lU;
// assign label to unlabeled node
labels[unlabeledNode] = label;
// iterate over the nodes edges
for(OutArcIt a(g,unlabeledNode);a!=lemon::INVALID;++a){
const Edge otherEdge(*a);
const Node targetNode=g.target(*a);
if(labels[targetNode] == 0){
//if(inPQ[otherEdge] == false && labels[targetNode] == 0){
const WeightType priority = priorManipFunctor(label,edgeWeights[otherEdge]);
pq.push(otherEdge,priority);
// inPQ[otherEdge]=true;
}
}
}
}
}
} // end namespace detail_watersheds_segmentation
/// \brief edge weighted watersheds Segmentataion
///
/// \param g: input graph
/// \param edgeWeights : edge weights / edge indicator
/// \param seeds : seed must be non empty!
/// \param[out] labels : resulting nodeLabeling (not necessarily dense)
template<class GRAPH,class EDGE_WEIGHTS,class SEEDS,class LABELS>
void edgeWeightedWatershedsSegmentation(
const GRAPH & g,
const EDGE_WEIGHTS & edgeWeights,
const SEEDS & seeds,
LABELS & labels
){
detail_watersheds_segmentation::RawPriorityFunctor fPriority;
detail_watersheds_segmentation::edgeWeightedWatershedsSegmentationImpl(g,edgeWeights,seeds,fPriority,labels);
}
/// \brief edge weighted watersheds Segmentataion
///
/// \param g: input graph
/// \param edgeWeights : edge weights / edge indicator
/// \param seeds : seed must be non empty!
/// \param backgroundLabel : which label is background
/// \param backgroundBias : bias for background
/// \param noPriorBelow : don't bias the background if edge indicator is below this value
/// \param[out] labels : resulting nodeLabeling (not necessarily dense)
template<class GRAPH,class EDGE_WEIGHTS,class SEEDS,class LABELS>
void carvingSegmentation(
const GRAPH & g,
const EDGE_WEIGHTS & edgeWeights,
const SEEDS & seeds,
const typename LABELS::Value backgroundLabel,
const typename EDGE_WEIGHTS::Value backgroundBias,
const typename EDGE_WEIGHTS::Value noPriorBelow,
LABELS & labels
){
typedef typename EDGE_WEIGHTS::Value WeightType;
typedef typename LABELS::Value LabelType;
detail_watersheds_segmentation::CarvingFunctor<WeightType,LabelType> fPriority(backgroundLabel,backgroundBias, noPriorBelow);
detail_watersheds_segmentation::edgeWeightedWatershedsSegmentationImpl(g,edgeWeights,seeds,fPriority,labels);
}
/// \brief edge weighted watersheds Segmentataion
///
/// \param graph: input graph
/// \param edgeWeights : edge weights / edge indicator
/// \param nodeSizes : size of each node
/// \param k : free parameter of felzenszwalb algorithm
/// \param[out] nodeLabeling : nodeLabeling (not necessarily dense)
/// \param nodeNumStopCond : optional stopping condition
template< class GRAPH , class EDGE_WEIGHTS, class NODE_SIZE,class NODE_LABEL_MAP>
void felzenszwalbSegmentation(
const GRAPH & graph,
const EDGE_WEIGHTS & edgeWeights,
const NODE_SIZE & nodeSizes,
float k,
NODE_LABEL_MAP & nodeLabeling,
const int nodeNumStopCond = -1
){
typedef GRAPH Graph;
typedef typename Graph::Edge Edge;
typedef typename Graph::Node Node;
typedef typename EDGE_WEIGHTS::Value WeightType;
typedef typename EDGE_WEIGHTS::Value NodeSizeType;
typedef typename Graph:: template NodeMap<WeightType> NodeIntDiffMap;
typedef typename Graph:: template NodeMap<NodeSizeType> NodeSizeAccMap;
// initalize node size map and internal diff map
NodeIntDiffMap internalDiff(graph);
NodeSizeAccMap nodeSizeAcc(graph);
copyNodeMap(graph,nodeSizes,nodeSizeAcc);
fillNodeMap(graph,internalDiff,static_cast<WeightType>(0.0));
// initlaize internal node diff map
// sort the edges by their weights
std::vector<Edge> sortedEdges;
std::less<WeightType> comperator;
edgeSort(graph,edgeWeights,comperator,sortedEdges);
// make the ufd
UnionFindArray<UInt64> ufdArray(graph.maxNodeId()+1);
size_t nodeNum = graph.nodeNum();
while(true){
// iterate over edges is the sorted order
for(size_t i=0;i<sortedEdges.size();++i){
const Edge e = sortedEdges[i];
const size_t rui = ufdArray.findIndex(graph.id(graph.u(e)));
const size_t rvi = ufdArray.findIndex(graph.id(graph.v(e)));
const Node ru = graph.nodeFromId(rui);
const Node rv = graph.nodeFromId(rvi);
if(rui!=rvi){
//check if to merge or not ?
const WeightType w = edgeWeights[e];
const NodeSizeType sizeRu = nodeSizeAcc[ru];
const NodeSizeType sizeRv = nodeSizeAcc[rv];
const WeightType tauRu = static_cast<WeightType>(k)/static_cast<WeightType>(sizeRu);
const WeightType tauRv = static_cast<WeightType>(k)/static_cast<WeightType>(sizeRv);
const WeightType minIntDiff = std::min(internalDiff[ru]+tauRu,internalDiff[rv]+tauRv);
if(w<=minIntDiff){
// do merge
ufdArray.makeUnion(rui,rvi);
--nodeNum;
// update size and internal difference
const size_t newRepId = ufdArray.findIndex(rui);
const Node newRepNode = graph.nodeFromId(newRepId);
internalDiff[newRepNode]=w;
nodeSizeAcc[newRepNode] = sizeRu+sizeRv;
}
}
if(nodeNum==nodeNumStopCond){
break;
}
}
if(nodeNumStopCond==-1){
break;
}
else{
if(nodeNum>nodeNumStopCond){
k *= 1.2f;
}
else{
break;
}
}
}
ufdArray.makeContiguous();
for(typename GRAPH::NodeIt n(graph);n!=lemon::INVALID;++n){
const Node node(*n);
nodeLabeling[node]=ufdArray.findLabel(graph.id(node));
}
}
namespace detail_graph_smoothing{
template<
class GRAPH,
class NODE_FEATURES_IN,
class EDGE_WEIGHTS,
class WEIGHTS_TO_SMOOTH_FACTOR,
class NODE_FEATURES_OUT
>
void graphSmoothingImpl(
const GRAPH & g,
const NODE_FEATURES_IN & nodeFeaturesIn,
const EDGE_WEIGHTS & edgeWeights,
WEIGHTS_TO_SMOOTH_FACTOR & weightsToSmoothFactor,
NODE_FEATURES_OUT & nodeFeaturesOut
){
typedef GRAPH Graph;
typedef typename Graph::Edge Edge;
typedef typename Graph::Node Node;
typedef typename Graph::NodeIt NodeIt;
typedef typename Graph::OutArcIt OutArcIt;
typedef typename NODE_FEATURES_IN::Value NodeFeatureInValue;
typedef typename NODE_FEATURES_OUT::Reference NodeFeatureOutRef;
typedef typename EDGE_WEIGHTS::ConstReference SmoothFactorType;
//fillNodeMap(g, nodeFeaturesOut, typename NODE_FEATURES_OUT::value_type(0.0));
for(NodeIt n(g);n!=lemon::INVALID;++n){
const Node node(*n);
NodeFeatureInValue featIn = nodeFeaturesIn[node];
NodeFeatureOutRef featOut = nodeFeaturesOut[node];
featOut=0;
float weightSum = 0.0;
size_t degree = 0;
for(OutArcIt a(g,node);a!=lemon::INVALID;++a){
const Edge edge(*a);
const Node neigbour(g.target(*a));
SmoothFactorType smoothFactor= weightsToSmoothFactor(edgeWeights[edge]);
NodeFeatureInValue neighbourFeat = nodeFeaturesIn[neigbour];
neighbourFeat*=smoothFactor;
if(degree==0)
featOut = neighbourFeat;
else
featOut += neighbourFeat;
weightSum+=smoothFactor;
++degree;
}
// fixme..set me to right type
featIn*=static_cast<float>(degree);
weightSum+=static_cast<float>(degree);
featOut+=featIn;
featOut/=weightSum;
}
}
template<class T>
struct ExpSmoothFactor{
ExpSmoothFactor(const T lambda,const T edgeThreshold,const T scale)
: lambda_(lambda),
edgeThreshold_(edgeThreshold),
scale_(scale){
}
T operator()(const T weight){
return weight> edgeThreshold_ ? 0 : std::exp(-1.0*lambda_*weight)*scale_;
}
T lambda_;
T edgeThreshold_;
T scale_;
};
} // namespace detail_graph_smoothing
/// \brief smooth node features of a graph
///
/// \param g : input graph
/// \param nodeFeaturesIn : input node features which should be smoothed
/// \param edgeIndicator : edge indicator to indicate over which edges one should smooth
/// \param lambda : scale edge indicator by lambda before taking negative exponent
/// \param edgeThreshold : edge threshold
/// \param scale : how much smoothing should be applied
/// \param[out] nodeFeaturesOut : smoothed node features
template<class GRAPH, class NODE_FEATURES_IN,class EDGE_INDICATOR,class NODE_FEATURES_OUT>
void graphSmoothing(
const GRAPH & g,
const NODE_FEATURES_IN & nodeFeaturesIn,
const EDGE_INDICATOR & edgeIndicator,
const float lambda,
const float edgeThreshold,
const float scale,
NODE_FEATURES_OUT & nodeFeaturesOut
){
detail_graph_smoothing::ExpSmoothFactor<float> functor(lambda,edgeThreshold,scale);
detail_graph_smoothing::graphSmoothingImpl(g,nodeFeaturesIn,edgeIndicator,functor,nodeFeaturesOut);
}
/// \brief smooth node features of a graph
///
/// \param g : input graph
/// \param nodeFeaturesIn : input node features which should be smoothed
/// \param edgeIndicator : edge indicator to indicate over which edges one should smooth
/// \param lambda : scale edge indicator by lambda before taking negative exponent
/// \param edgeThreshold : edge threshold
/// \param scale : how much smoothing should be applied
/// \param iterations : how often should this algorithm be called recursively
/// \param[out] nodeFeaturesBuffer : preallocated(!) buffer to store node features temp.
/// \param[out] nodeFeaturesOut : smoothed node features
template<class GRAPH, class NODE_FEATURES_IN,class EDGE_INDICATOR,class NODE_FEATURES_OUT>
void recursiveGraphSmoothing(
const GRAPH & g,
const NODE_FEATURES_IN & nodeFeaturesIn,
const EDGE_INDICATOR & edgeIndicator,
const float lambda,
const float edgeThreshold,
const float scale,
size_t iterations,
NODE_FEATURES_OUT & nodeFeaturesBuffer,
NODE_FEATURES_OUT & nodeFeaturesOut
){
iterations = std::max(size_t(1),iterations);
// initial run
graphSmoothing(g,nodeFeaturesIn,edgeIndicator,lambda,edgeThreshold,scale,nodeFeaturesOut);
iterations -=1;
bool outAsIn=true;
for(size_t i=0;i<iterations;++i){
if(outAsIn){
graphSmoothing(g,nodeFeaturesOut,edgeIndicator,lambda,edgeThreshold,scale,nodeFeaturesBuffer);
outAsIn=false;
}
else{
graphSmoothing(g,nodeFeaturesBuffer,edgeIndicator,lambda,edgeThreshold,scale,nodeFeaturesOut);
outAsIn=true;
}
}
if(!outAsIn){
copyNodeMap(g,nodeFeaturesBuffer,nodeFeaturesOut);
}
}
template<class GRAPH, class NODE_MAP, class EDGE_MAP>
void nodeGtToEdgeGt(
const GRAPH & g,
const NODE_MAP & nodeGt,
const Int64 ignoreLabel,
EDGE_MAP & edgeGt
){
typedef typename GRAPH::Node Node;
typedef typename GRAPH::EdgeIt EdgeIt;
typedef typename GRAPH::Edge Edge;
for(EdgeIt edgeIt(g); edgeIt!=lemon::INVALID; ++edgeIt){
const Edge edge(*edgeIt);
const Node u = g.u(edge);
const Node v = g.v(edge);
const Int64 lU = static_cast<Int64>(nodeGt[u]);
const Int64 lV = static_cast<Int64>(nodeGt[v]);
if(ignoreLabel==-1 || (lU!=ignoreLabel || lV!=ignoreLabel)){
edgeGt[edge] = lU == lV ? 0 : 1;
}
else{
edgeGt[edge] = 2;
}
}
}
/// project ground truth from a base graph, to a region adjacency graph.
///
///
///
///
template<class RAG, class BASE_GRAPH, class BASE_GRAPH_RAG_LABELS,
class BASE_GRAPH_GT, class RAG_GT, class RAG_GT_QT>
void projectGroundTruth(
const RAG & rag,
const BASE_GRAPH & baseGraph,
const BASE_GRAPH_RAG_LABELS & baseGraphRagLabels,
const BASE_GRAPH_GT & baseGraphGt,
RAG_GT & ragGt,
RAG_GT_QT & ragGtQt
){
typedef typename BASE_GRAPH::Node BaseGraphNode;
typedef typename BASE_GRAPH::NodeIt BaseGraphNodeIt;
typedef typename RAG::NodeIt RagNodeIt;
typedef typename RAG::Node RagNode;
typedef typename BASE_GRAPH_RAG_LABELS::Value BaseRagLabelType;
typedef typename BASE_GRAPH_GT::Value GtLabelType;
typedef typename RAG_GT::Value RagGtLabelType;
// overlap map
typedef std::map<GtLabelType,UInt32> MapType;
typedef typename MapType::const_iterator MapIter;
typedef typename RAG:: template NodeMap<MapType> Overlap;
Overlap overlap(rag);
size_t i=0;
//::cout<<"\n";
for(BaseGraphNodeIt baseNodeIter(baseGraph); baseNodeIter!=lemon::INVALID; ++baseNodeIter , ++i ){
//if (i%2000 == 0){
// std::cout<<"\r"<<std::setw(10)<< float(i)/float(baseGraph.nodeNum())<<std::flush;
//}
const BaseGraphNode baseNode = *baseNodeIter;
// get gt label
const GtLabelType gtLabel = baseGraphGt[baseNode];
// get the label which generated rag
// (node mapping from bg-node to rag-node-id)
const BaseRagLabelType bgRagLabel = baseGraphRagLabels[baseNode];
const RagNode ragNode = rag.nodeFromId(bgRagLabel);
// fill overlap
overlap[ragNode][gtLabel]+=1;
}
//std::cout<<"\n";
// select label with max overlap
for(RagNodeIt ragNodeIter(rag); ragNodeIter!=lemon::INVALID; ++ragNodeIter ){
const RagNode ragNode = *ragNodeIter;
const MapType olMap = overlap[ragNode];
UInt32 olSize=0;
RagGtLabelType bestLabel = 0;
for(MapIter olIter = olMap.begin(); olIter!=olMap.end(); ++olIter ){
if(olIter->second > olSize){
olSize = olIter->second;
bestLabel = olIter->first;
}
}
ragGt[ragNode]=bestLabel;
}
}
/// \brief Find indices of points on the edges
///
/// \param rag : Region adjacency graph of the labels array
/// \param graph : Graph of labels array
/// \param affiliatedEdges : The affiliated edges of the region adjacency graph
/// \param labelsArray : The label image
/// \param node : The node (of the region adjacency graph), whose edges shall be found
template<class RAGGRAPH, class GRAPH, class RAGEDGES, unsigned int N, class T>
MultiArray<2, MultiArrayIndex> ragFindEdges(
const RAGGRAPH & rag,
const GRAPH & graph,
const RAGEDGES & affiliatedEdges,
MultiArrayView<N, T> labelsArray,
const typename RAGGRAPH::Node & node
){
typedef typename GRAPH::Node Node;
typedef typename GRAPH::Edge Edge;
typedef typename RAGGRAPH::OutArcIt RagOutArcIt;
typedef typename RAGGRAPH::Edge RagEdge;
typedef typename GraphDescriptorToMultiArrayIndex<GRAPH>::IntrinsicNodeMapShape NodeCoordinate;
T nodeLabel = rag.id(node);
// Find edges and write them into a set.
std::set< NodeCoordinate > edgeCoordinates;
for (RagOutArcIt iter(rag, node); iter != lemon::INVALID; ++iter)
{
const RagEdge ragEdge(*iter);
const std::vector<Edge> & affEdges = affiliatedEdges[ragEdge];
for (int i=0; i<affEdges.size(); ++i)
{
Node u = graph.u(affEdges[i]);
Node v = graph.v(affEdges[i]);
T uLabel = labelsArray[u];
T vLabel = labelsArray[v];
NodeCoordinate coords;
if (uLabel == nodeLabel)
{
coords = GraphDescriptorToMultiArrayIndex<GRAPH>::intrinsicNodeCoordinate(graph, u);
}
else if (vLabel == nodeLabel)
{
coords = GraphDescriptorToMultiArrayIndex<GRAPH>::intrinsicNodeCoordinate(graph, v);
}
else
{
vigra_precondition(false, "You should not come to this part of the code.");
}
edgeCoordinates.insert(coords);
}
}
// Fill the return array.
MultiArray<2, MultiArrayIndex> edgePoints(Shape2(edgeCoordinates.size(), N));
edgePoints.init(0);
int next = 0;
typedef typename std::set< NodeCoordinate >::iterator setIter;
for (setIter iter = edgeCoordinates.begin(); iter!=edgeCoordinates.end(); ++iter)
{
NodeCoordinate coords = *iter;
for (int k=0; k<coords.size(); ++k)
{
edgePoints(next, k) = coords[k];
}
next++;
}
return edgePoints;
}
/// \brief create edge weights from node weights
///
/// \param g : input graph
/// \param nodeWeights : node property map holding node weights
/// \param[out] edgeWeights : resulting edge weights
/// \param euclidean : if 'true', multiply the computed weights with the Euclidean
/// distance between the edge's end nodes (default: 'false')
/// \param func : binary function that computes the edge weight from the
/// weights of the edge's end nodes (default: take the average)
template<unsigned int N, class DirectedTag,
class NODEMAP, class EDGEMAP, class FUNCTOR>
void
edgeWeightsFromNodeWeights(
const GridGraph<N, DirectedTag> & g,
const NODEMAP & nodeWeights,
EDGEMAP & edgeWeights,
bool euclidean,
FUNCTOR const & func)
{
typedef GridGraph<N, DirectedTag> Graph;
typedef typename Graph::Edge Edge;
typedef typename Graph::EdgeIt EdgeIt;
typedef typename MultiArrayShape<N>::type CoordType;
vigra_precondition(nodeWeights.shape() == g.shape(),
"edgeWeightsFromNodeWeights(): shape mismatch between graph and nodeWeights.");
for (EdgeIt iter(g); iter!=lemon::INVALID; ++iter)
{
const Edge edge(*iter);
const CoordType uCoord(g.u(edge));
const CoordType vCoord(g.v(edge));
if (euclidean)
{
edgeWeights[edge] = norm(uCoord-vCoord) * func(nodeWeights[uCoord], nodeWeights[vCoord]);
}
else
{
edgeWeights[edge] = func(nodeWeights[uCoord], nodeWeights[vCoord]);
}
}
}
template<unsigned int N, class DirectedTag,
class NODEMAP, class EDGEMAP>
inline void
edgeWeightsFromNodeWeights(
const GridGraph<N, DirectedTag> & g,
const NODEMAP & nodeWeights,
EDGEMAP & edgeWeights,
bool euclidean=false)
{
using namespace vigra::functor;
edgeWeightsFromNodeWeights(g, nodeWeights, edgeWeights, euclidean, Param(0.5)*(Arg1()+Arg2()));
}
/// \brief create edge weights from an interpolated image
///
/// \param g : input graph
/// \param interpolatedImage : interpolated image
/// \param[out] edgeWeights : edge weights
/// \param euclidean : if 'true', multiply the weights with the Euclidean
/// distance between the edge's end nodes (default: 'false')
///
/// For each edge, the function reads the weight from <tt>interpolatedImage[u+v]</tt>,
/// where <tt>u</tt> and <tt>v</tt> are the coordinates of the edge's end points.
template<unsigned int N, class DirectedTag,
class T, class EDGEMAP>
void
edgeWeightsFromInterpolatedImage(
const GridGraph<N, DirectedTag> & g,
const MultiArrayView<N, T> & interpolatedImage,
EDGEMAP & edgeWeights,
bool euclidean = false)
{
typedef GridGraph<N, DirectedTag> Graph;
typedef typename Graph::Edge Edge;
typedef typename Graph::EdgeIt EdgeIt;
typedef typename MultiArrayShape<N>::type CoordType;
vigra_precondition(interpolatedImage.shape() == 2*g.shape()-CoordType(1),
"edgeWeightsFromInterpolatedImage(): interpolated shape must be shape*2-1");
for (EdgeIt iter(g); iter!=lemon::INVALID; ++iter)
{
const Edge edge(*iter);
const CoordType uCoord(g.u(edge));
const CoordType vCoord(g.v(edge));
if (euclidean)
{
edgeWeights[edge] = norm(uCoord-vCoord) * interpolatedImage[uCoord+vCoord];
}
else
{
edgeWeights[edge] = interpolatedImage[uCoord+vCoord];
}
}
}
template<class GRAPH>
struct ThreeCycle{
typedef typename GRAPH::Node Node;
ThreeCycle(const Node & a, const Node & b, const Node c){
nodes_[0] = a;
nodes_[1] = b;
nodes_[2] = c;
std::sort(nodes_, nodes_+3);
}
bool operator < (const ThreeCycle & other)const{
if(nodes_[0] < other.nodes_[0]){
return true;
}
else if(nodes_[0] == other.nodes_[0]){
if(nodes_[1] < other.nodes_[1]){
return true;
}
else if(nodes_[1] == other.nodes_[1]){
if(nodes_[2] < other.nodes_[2]){
return true;
}
else{
return false;
}
}
else{
return false;
}
}
else{
return false;
}
}
Node nodes_[3];
};
template<class GRAPH>
void find3Cycles(
const GRAPH & g,
MultiArray<1, TinyVector<Int32, 3> > & cyclesArray
){
typedef typename GRAPH::Node Node;
typedef typename GRAPH::Edge Edge;
typedef typename GRAPH::EdgeIt EdgeIt;
typedef typename GRAPH::OutArcIt OutArcIt;
typedef ThreeCycle<GRAPH> Cycle;
std::set< Cycle > cycles;
typedef typename std::set<Cycle>::const_iterator SetIter;
for (EdgeIt iter(g); iter!=lemon::INVALID; ++iter){
const Edge edge(*iter);
const Node u = g.u(edge);
const Node v = g.v(edge);
// find a node n which is connected to u and v
for(OutArcIt outArcIt(g,u); outArcIt!=lemon::INVALID;++outArcIt){
const Node w = g.target(*outArcIt);
if(w != v){
const Edge e = g.findEdge(w,v);
if(e != lemon::INVALID){
// found cycle
cycles.insert(Cycle(u, v, w));
}
}
}
}
cyclesArray.reshape(TinyVector<UInt32,1>(cycles.size()));
UInt32 i=0;
for(SetIter iter=cycles.begin(); iter!=cycles.end(); ++iter){
const Cycle & c = *iter;
for(size_t j=0;j<3; ++j){
cyclesArray(i)[j] = g.id(c.nodes_[j]);
}
++i;
}
}
template<class GRAPH>
void find3CyclesEdges(
const GRAPH & g,
MultiArray<1, TinyVector<Int32, 3> > & cyclesArray
){
typedef typename GRAPH::Node Node;
typedef typename GRAPH::Edge Edge;
typedef typename GRAPH::EdgeIt EdgeIt;
typedef typename GRAPH::OutArcIt OutArcIt;
typedef ThreeCycle<GRAPH> Cycle;
std::set< Cycle > cycles;
typedef typename std::set<Cycle>::const_iterator SetIter;
for (EdgeIt iter(g); iter!=lemon::INVALID; ++iter){
const Edge edge(*iter);
const Node u = g.u(edge);
const Node v = g.v(edge);
// find a node n which is connected to u and v
for(OutArcIt outArcIt(g,u); outArcIt!=lemon::INVALID;++outArcIt){
const Node w = g.target(*outArcIt);
if(w != v){
const Edge e = g.findEdge(w,v);
if(e != lemon::INVALID){
// found cycle
cycles.insert(Cycle(u, v, w));
}
}
}
}
cyclesArray.reshape(TinyVector<UInt32,1>(cycles.size()));
UInt32 i=0;
for(SetIter iter=cycles.begin(); iter!=cycles.end(); ++iter){
const Cycle & c = *iter;
const Node u = c.nodes_[0];
const Node v = c.nodes_[1];
const Node w = c.nodes_[2];
cyclesArray(i)[0] = g.id(g.findEdge(u, v));
cyclesArray(i)[1] = g.id(g.findEdge(u, w));
cyclesArray(i)[2] = g.id(g.findEdge(v, w));
++i;
}
}
//@}
} // namespace vigra
#endif // VIGRA_GRAPH_ALGORITHMS_HXX
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