void findStatistics(){
float sumInCluster=0, sumBetweenCluster=0;
int countInCluster=0, countBetweenCluster=0, temp=0;
edge TempEdge;
while(temp<(vertexNum)){ /*iterating on all the vertices*/
findDiameter(temp);
TempEdge = vertices[temp]->edges->head;
while(TempEdge!=NULL){ /*iterating on all the edges bounded to this vertex*/
/*in the following sections weight is divided by 2 because each edge is added twice*/
if((TempEdge->inCluster==1)){
sumInCluster+=(TempEdge->weight);
(clusters[vertices[temp]->ClusterBelonging-1]->score)+=(TempEdge->weight/2);
countInCluster++;
}
else if((TempEdge->inCluster==3)){
sumBetweenCluster+=(TempEdge->weight);
countBetweenCluster++;
}
TempEdge=TempEdge->next;
}
temp++;
}
if(countInCluster!=0){
avgInClusters = Calculate(sumInCluster,countInCluster);
}
if(countBetweenCluster!=0){
avgBetweenClusters = Calculate(sumBetweenCluster,countBetweenCluster);
}
sort();
setClusters();
}
/**
* @brief AgentCluster::assignmentPhase Runs the assignment phase of the AgentSwarm algorithm.
*/
void AgentCluster::assignmentPhase() {
for (unsigned int i = 0; i < m_agents.size(); i++) {
Agent* agent = m_agents[i];
if (agent->visited)
continue;
agent->visited = true;
Cluster* cluster = new Cluster();
cluster->id = m_clusters.size();
m_clusters.push_back(cluster);
std::vector<Agent*> neighbors = agentsWithinRange(agent, agent->foragingRange * 2.0);
addToCluster(cluster, agent, neighbors);
}
for (unsigned int i = 0; i < m_clusters.size(); i++) {
Cluster* cluster = m_clusters[i];
for (unsigned int j = 0; j < cluster->agents.size(); j++) {
Agent* agent = cluster->agents[j];
std::vector<ClusterItem*> items = dataWithinForagingRange(agent);
for (unsigned int k = 0; k < items.size(); k++) {
ClusterItem* item = items[k];
if (item->group != -1)
continue;
item->group = cluster->id;
cluster->points.push_back(item);
}
}
}
for (unsigned int i = 0; i < m_data.size(); i++) { //assign unassigned points to the closest groups
ClusterItem* item = m_data[i];
if (item->group != -1)
continue;
Agent* closestAgent = 0;
double closestDistance = -1;
for (unsigned int j = 0; j < m_agents.size(); j++) {
Agent* current = m_agents[j];
double dist = pointDistance(current->x, item->x, current->y, item->y);
if (dist < closestDistance || closestDistance == -1) {
closestAgent = current;
closestDistance = dist;
}
}
item->group = closestAgent->cluster;
for (unsigned int j = 0; j < m_clusters.size(); j++) {
Cluster* cluster = m_clusters[j];
if (cluster->id == item->group)
cluster->points.push_back(item);
}
}
emit setClusters(&m_clusters);
}
AlgMultiArranque::AlgMultiArranque(vector<Cluster*>& clusters, vector<Objeto*>& objetos) {
setNombreAlgoritmo(" Técnica MultiArranque ");
setObjetos(objetos);
setClusters(clusters);
setDimension(getClusters()[0]->getDimension());
int* sol = new int [getObjetos().size()];
_solActual = new int [getObjetos().size()];
_mejorSol = new int [getObjetos().size()];
for (unsigned int i = 0; i < getObjetos().size(); ++i) {
sol[i] = -1;
}
setSolucion(sol);
delete [] sol;
_tecnicaLocal = NULL;
_centroidesFin = new int *[getClusters().size()];
for (unsigned int i = 0; i < getClusters().size(); ++i)
_centroidesFin[i] = new int[getDimension()];
}
void ProcessingCallback(const geometry_msgs::PoseArray msg)
{
//Reinitialize image to zeros
image.setTo(cv::Scalar(255, 255, 255));
//Reset Points and Cluster
LeftCluster.clear();
RightCluster.clear();
//Set valid points
setClusters(msg);
//Evaluates cluster
evaluateCluster();
//Show Image
cv::imshow(OPENCV_WINDOW, image);
cvWaitKey(1);
}
int findClusters(){
int iter;
clus *tmp, newCluster;
edge tempEdge;
clusterList cl;
element e;
int *checked = (int *)calloc(vertexNum,sizeof(int));
clusters=(clus *)malloc(sizeof(clus)*vertexNum); /*we will realoc it later to fit the cluster number*/
if (clusters==NULL){
allFail(0);
if (checked!=NULL){
free(checked);
}
return -1;
}
if (checked==NULL){
allFail(1);
return -1;
}
for(iter=0;iter<vertexNum;iter++){
if(checked[iter]==0){
cl = (clusterList) malloc(sizeof(struct s_clusterList));
if (cl==NULL){
allFail(0);
free(checked);
return -1;
}
newCluster=(clus)malloc(sizeof(struct s_clust));
clusters[clusterNum]=newCluster;
clusters[clusterNum]->clustVertices = cl;
clusters[clusterNum]->size=1;
clusters[clusterNum]->score=0;
clusters[clusterNum]->diameter=0;
clusterNum++;
tempEdge=vertices[iter]->edges->head;
e = (element) malloc(sizeof(struct s_element));
if (e==NULL){
allFail(0);
free(checked);
return -1;
}
e->vertex = iter; /*Adding the first vertex in the cluster to the Cluster list*/
cl->headl = e;
e->next=NULL;
checked[tempEdge->vertexBelong]=1;
while(tempEdge!=NULL){
if((tempEdge->inCluster==1) || (tempEdge->inCluster==2)){
if (checked[tempEdge->id_vertex]==0){
checked[tempEdge->id_vertex]=1;
e = (element) malloc(sizeof(struct s_element));
if (e==NULL){
perror("Problem in function: 'findClusters'\n");
allFail(0);
free(checked);
return -1;
}
e->vertex = tempEdge->id_vertex;
e->next = cl->headl;
cl->headl = e;
clusters[clusterNum-1]->size++;
}
}
tempEdge=tempEdge->next;
}
}
}
tmp=(clus*)realloc(clusters,sizeof(clus)*clusterNum);
if(tmp==NULL){
free(clusters);
free(checked);
return -1;
}
clusters=tmp;
setClusters();
free(checked);
return 0;
}
