public override void UpdateClusters()
{
CurrentClusters.Clear();
//Get unit objects only!
List <CacheUnit> listObjectUnits = Bot.Targeting.Cache.ValidObjects.OfType <CacheUnit>().Where(u =>
Bot.Targeting.Cache.Environment.UnitRAGUIDs.Contains(u.RAGUID) &&
u.CentreDistance <= this.clusterConditions.MaximumDistance &&
(!this.clusterConditions.IgnoreNonTargetable || u.IsTargetable.HasValue && u.IsTargetable.Value)).ToList();
//Logger.DBLog.InfoFormat("Total Units {0}", listObjectUnits.Count.ToString());
if (listObjectUnits.Count > 0)
{
CurrentClusters = cluster.RunKmeans(listObjectUnits, this.clusterConditions.ClusterDistance).Where(c => c.ListUnits.Count >= this.clusterConditions.MinimumUnits && (this.clusterConditions.DOTDPSRatio == 0.00d || c.Info.DotDPSRatio <= this.clusterConditions.DOTDPSRatio)).ToList();
//Sort by distance -- reverse to get nearest unit First
if (CurrentClusters.Count > 0)
{
CurrentClusters = CurrentClusters.OrderBy(o => o.NearestMonsterDistance).ToList();
CurrentClusters.First().ListUnits.Sort();
CurrentClusters.First().ListUnits.Reverse();
}
}
lastClusterComputed = DateTime.Now;
}
///<summary>
///Updates the Cluster List!
///</summary>
public virtual void UpdateClusters()
{
CurrentClusters.Clear();
//Get unit objects only!
List <CacheUnit> listObjectUnits;
//(radius or centre)
if (!clusterConditions.UseRadiusDistance)
{
listObjectUnits = FunkyGame.Targeting.Cache.ValidObjects.OfType <CacheUnit>().Where(u =>
FunkyGame.Targeting.Cache.Environment.UnitRAGUIDs.Contains(u.RAGUID) &&
u.CentreDistance <= clusterConditions.MaximumDistance &&
u.CentreDistance >= clusterConditions.MinimumDistance &&
(!clusterConditions.IgnoreNonTargetable || u.IsTargetable.HasValue && u.IsTargetable.Value)).ToList();
}
else
{
listObjectUnits = FunkyGame.Targeting.Cache.ValidObjects.OfType <CacheUnit>().Where(u =>
FunkyGame.Targeting.Cache.Environment.UnitRAGUIDs.Contains(u.RAGUID) &&
u.RadiusDistance <= clusterConditions.MaximumDistance &&
u.RadiusDistance >= clusterConditions.MinimumDistance &&
(!clusterConditions.IgnoreNonTargetable || u.IsTargetable.HasValue && u.IsTargetable.Value)).ToList();
}
//Logger.DBLog.InfoFormat("Total Units {0}", listObjectUnits.Count.ToString());
if (listObjectUnits.Count > 0)
{
CurrentClusters = cluster.RunKmeans(listObjectUnits, clusterConditions.ClusterDistance)
.Where(c => c.Info.Properties.HasFlag(clusterConditions.ClusterFlags) && c.ListUnits.Count >= clusterConditions.MinimumUnits && (clusterConditions.DOTDPSRatio == 0.00d || c.Info.DotDPSRatio <= clusterConditions.DOTDPSRatio)).ToList();
//Sort by distance -- reverse to get nearest unit First
if (CurrentClusters.Count > 0)
{
CurrentClusters = CurrentClusters.OrderBy(o => o.NearestMonsterDistance).ToList();
CurrentClusters.First().ListUnits.Sort();
CurrentClusters.First().ListUnits.Reverse();
}
}
lastClusterComputed = DateTime.Now;
}
///<summary>
///Iterates thru the cluster list and calls the update method on each.
///</summary>
public virtual void RefreshClusters()
{
if (DateTime.Now.Subtract(lastClusterRefresh).TotalMilliseconds < this.RefreshRate)
{
return;
}
if (CurrentClusters.Count > 0)
{
foreach (var item in CurrentClusters)
{
item.UpdateUnitPointLists(clusterConditions);
}
CurrentClusters = CurrentClusters.Where(c => c.ListUnits.Count >= clusterConditions.MinimumUnits && (clusterConditions.DOTDPSRatio == 0.00d || c.Info.DotDPSRatio <= clusterConditions.DOTDPSRatio)).ToList();
}
lastClusterRefresh = DateTime.Now;
}
private void MergeClusters(string linkageMethod, string distanceMethod)
{
double minDist = double.MaxValue;
Cluster minClust1 = null, minClust2 = null;
bool buildInitialMatrix = false;
if (distanceMatrix.Count == 0)
{
buildInitialMatrix = true;
}
for (int i = 0; i < CurrentClusters.Count; ++i)
{
Cluster c1 = CurrentClusters[i];
if (buildInitialMatrix)
{
distanceMatrix[c1] = new Dictionary <Cluster, double>();
}
for (int j = i + 1; j < CurrentClusters.Count; ++j)
{
Cluster c2 = CurrentClusters[j];
double dist;
if (buildInitialMatrix)
{
dist = distanceMatrix[c1][c2] = ClusterDistance(CurrentClusters[i], CurrentClusters[j], linkageMethod, distanceMethod);
}
else
{
dist = distanceMatrix[CurrentClusters[i]][CurrentClusters[j]];
}
if (dist < minDist)
{
minDist = dist;
minClust1 = CurrentClusters[i];
minClust2 = CurrentClusters[j];
}
}
}
if (minClust1 == null || minClust2 == null)
{
Console.WriteLine("[WARNING] Could not find clusters to merge");
return;
}
Cluster newCluster = new Cluster(minClust1, minClust2);
FinalClusters.Add(minClust1);
FinalClusters.Add(minClust2);
CurrentClusters.Remove(minClust1);
CurrentClusters.Remove(minClust2);
// update distance matrix and add new cluster to current clusters
distanceMatrix.Remove(minClust1);
distanceMatrix.Remove(minClust2);
foreach (Cluster c in CurrentClusters)
{
distanceMatrix[c][newCluster] = ClusterDistance(c, newCluster, linkageMethod, distanceMethod);
}
distanceMatrix[newCluster] = new Dictionary <Cluster, double>();
CurrentClusters.Add(newCluster);
}
