public int SearchMaxDist()
{
Stack <HClusterNode> st = new Stack <HClusterNode>();
HClusterNode current = null;
int kMax;
kMax = -(int)this.levelDist;
kMin = (int)this.levelDist;
st.Push(this);
while (st.Count != 0)
{
current = st.Pop();
if (current.levelDist > kMax)
{
kMax = (int)current.levelDist;
}
if (current.levelDist < kMin)
{
kMin = (int)current.levelDist;
}
if (current.joined != null)
{
foreach (var item in current.joined)
{
st.Push(item);
}
}
}
return(kMax);
}
public Dictionary <double, List <HClusterNode> > GetClustersByLevels()
{
Dictionary <double, List <HClusterNode> > dic = new Dictionary <double, List <HClusterNode> >();
Stack <HClusterNode> st = new Stack <HClusterNode>();
HClusterNode current = null;
st.Push(this);
while (st.Count != 0)
{
current = st.Pop();
if (!dic.ContainsKey(current.levelDist))
{
dic.Add(current.levelDist, new List <HClusterNode>());
}
dic[current.levelDist].Add(current);
if (current.joined != null)
{
foreach (var item in current.joined)
{
st.Push(item);
}
}
}
return(dic);
}
public Dictionary <HClusterNode, System.Drawing.Color> MarkNodes(List <string> toMark, System.Drawing.Color color)
{
Dictionary <HClusterNode, System.Drawing.Color> returnList = new Dictionary <HClusterNode, System.Drawing.Color>();
Stack <HClusterNode> st = new Stack <HClusterNode>();
HClusterNode current = null;
st.Push(this);
while (st.Count != 0)
{
current = st.Pop();
if (current.joined == null || current.joined.Count == 0)
{
foreach (var item in toMark)
{
if (current.setStruct.Contains(item))
{
returnList.Add(current, color);
break;
}
}
}
else
if (current.joined != null)
{
foreach (var item in current.joined)
{
st.Push(item);
}
}
}
return(returnList);
}
public bool IsVisible(HClusterNode node)
{
Stack <HClusterNode> st = new Stack <HClusterNode>();
HClusterNode current = null;
if (this == node)
{
return(true);
}
st.Push(this);
while (st.Count != 0)
{
current = st.Pop();
if (current.joined != null)
{
foreach (var item in current.joined)
{
if (item == node)
{
return(true);
}
st.Push(item);
}
}
}
return(false);
}
public List <HClusterNode> GetLeaves()
{
List <HClusterNode> listH = new List <HClusterNode>();
Stack <HClusterNode> st = new Stack <HClusterNode>();
HClusterNode current = null;
st.Push(this);
while (st.Count != 0)
{
current = st.Pop();
if (current.joined != null)
{
foreach (var item in current.joined)
{
st.Push(item);
}
}
else
{
listH.Add(current);
}
}
return(listH);
}
public Dictionary <HClusterNode, System.Drawing.Color> CutDendrog(int distThreshold)
{
Dictionary <HClusterNode, System.Drawing.Color> returnList = new Dictionary <HClusterNode, System.Drawing.Color>();
Stack <HClusterNode> st = new Stack <HClusterNode>();
HClusterNode current = null;
st.Push(this);
while (st.Count != 0)
{
current = st.Pop();
if (current.levelDist < distThreshold)
{
returnList.Add(current, System.Drawing.Color.Red);
}
else
if (current.joined != null)
{
foreach (var item in current.joined)
{
st.Push(item);
}
}
}
return(returnList);
}
public ClusterOutput HierarchicalClustering(List <string> structures)
{
List<List<HClusterNode>> level =new List<List<HClusterNode>>();
List<HClusterNode> levelNodes=new List<HClusterNode>();
List<HClusterNode> rowNodes=new List<HClusterNode>();
ClusterOutput outCl = new ClusterOutput();
int levelCount = 0;
bool end=false;
HClusterNode node;
if (structures.Count <= 1)
{
outCl.hNode = new HClusterNode();
outCl.hNode.setStruct = structures;
outCl.hNode.refStructure = structures[0];
outCl.hNode.levelDist = 0;
outCl.hNode.joined = null;
return outCl;
}
dMeasure.CalcDistMatrix(structures);
for(int i=0;i<structures.Count;i++)
{
node=new HClusterNode();
node.refStructure=structures[i];
node.joined=null;
node.setStruct.Add(structures[i]);
node.levelNum = levelCount;
node.levelDist = dMeasure.maxSimilarity;
node.realDist = dMeasure.GetRealValue(node.levelDist);
levelNodes.Add(node);
}
level.Add(levelNodes);
while(!end)
{
levelNodes=new List<HClusterNode>();
List<List<HClusterNode>> rowList = LevelMinimalDist(level[level.Count - 1]);
if (rowList.Count > 0)
{
foreach (var item in rowList)
{
node=new HClusterNode();
node.joined=item;
node.levelDist = min;
node.realDist = dMeasure.GetRealValue(min);
node.levelNum = level.Count;
for(int m=0;m<item.Count;m++)
{
node.setStruct.AddRange(item[m].setStruct);
item[m].fNode = true;
}
//node.refStructure = dMeasure.GetReferenceStructure(node.setStruct);
List<string> refList = new List<string>();
foreach (var itemJoined in node.joined)
refList.Add(itemJoined.refStructure);
node.refStructure = null;
if (mustRefStructure != null)
foreach (var itemRef in refList)
if (itemRef == mustRefStructure)
node.refStructure = mustRefStructure;
if(node.refStructure==null)
node.refStructure = dMeasure.GetReferenceStructure(node.setStruct,refList);
levelNodes.Add(node);
}
}
if(levelNodes.Count>0)
{
level.Add(levelNodes);
for(int i=0;i<level[level.Count-2].Count;i++)
{
if(!level[level.Count-2][i].fNode)
level[level.Count-1].Add(level[level.Count-2][i]);
}
}
if(level[level.Count-1].Count==1)
end=true;
}
outCl.hNode = level[level.Count - 1][0];
outCl.hNode.levelNum = 0;
//At the end level num must be set properly
Queue<HClusterNode> qq = new Queue<HClusterNode>();
HClusterNode h;
for (int i = 0; i < level.Count; i++)
for (int j = 0; j < level[i].Count; j++)
level[i][j].fNode = true;
for (int i = 0; i < level.Count; i++)
for (int j = 0; j < level[i].Count; j++)
if (level[i][j].fNode)
{
level[i][j].levelDist = Math.Abs(level[i][j].levelDist - dMeasure.maxSimilarity);
level[i][j].realDist = dMeasure.GetRealValue(level[i][j].levelDist);
level[i][j].fNode = false;
}
qq.Enqueue(level[level.Count - 1][0]);
while (qq.Count != 0)
{
h = qq.Dequeue();
if (h.joined != null)
foreach (var item in h.joined)
{
item.levelNum = h.levelNum + 1;
qq.Enqueue(item);
}
}
outCl.hNode.dirName = dirName;
outCl.clusters = null;
outCl.juryLike = null;
return outCl;
}
public bool IsVisible(HClusterNode node)
{
Stack<HClusterNode> st = new Stack<HClusterNode>();
HClusterNode current = null;
if (this == node)
return true;
st.Push(this);
while (st.Count != 0)
{
current = st.Pop();
if (current.joined != null)
foreach (var item in current.joined)
{
if (item == node)
return true;
st.Push(item);
}
}
return false;
}
public ClusterOutput HierarchicalClustering(List <string> structures)
{
List <List <HClusterNode> > level = new List <List <HClusterNode> >();
List <HClusterNode> levelNodes = new List <HClusterNode>();
List <HClusterNode> rowNodes = new List <HClusterNode>();
ClusterOutput outCl = new ClusterOutput();
int levelCount = 0;
bool end = false;
HClusterNode node;
if (structures.Count <= 1)
{
outCl.hNode = new HClusterNode();
outCl.hNode.setStruct = structures;
outCl.hNode.refStructure = structures[0];
outCl.hNode.levelDist = 0;
outCl.hNode.joined = null;
return(outCl);
}
dMeasure.CalcDistMatrix(structures);
for (int i = 0; i < structures.Count; i++)
{
node = new HClusterNode();
node.refStructure = structures[i];
node.joined = null;
node.setStruct.Add(structures[i]);
node.levelNum = levelCount;
node.levelDist = dMeasure.maxSimilarity;
node.realDist = dMeasure.GetRealValue(node.levelDist);
levelNodes.Add(node);
}
level.Add(levelNodes);
while (!end)
{
levelNodes = new List <HClusterNode>();
List <List <HClusterNode> > rowList = LevelMinimalDist(level[level.Count - 1]);
if (rowList.Count > 0)
{
foreach (var item in rowList)
{
node = new HClusterNode();
node.joined = item;
node.levelDist = min;
node.realDist = dMeasure.GetRealValue(min);
node.levelNum = level.Count;
for (int m = 0; m < item.Count; m++)
{
node.setStruct.AddRange(item[m].setStruct);
item[m].fNode = true;
}
//node.refStructure = dMeasure.GetReferenceStructure(node.setStruct);
List <string> refList = new List <string>();
foreach (var itemJoined in node.joined)
{
refList.Add(itemJoined.refStructure);
}
node.refStructure = null;
if (mustRefStructure != null)
{
foreach (var itemRef in refList)
{
if (itemRef == mustRefStructure)
{
node.refStructure = mustRefStructure;
}
}
}
if (node.refStructure == null)
{
node.refStructure = dMeasure.GetReferenceStructure(node.setStruct, refList);
}
levelNodes.Add(node);
}
}
if (levelNodes.Count > 0)
{
level.Add(levelNodes);
for (int i = 0; i < level[level.Count - 2].Count; i++)
{
if (!level[level.Count - 2][i].fNode)
{
level[level.Count - 1].Add(level[level.Count - 2][i]);
}
}
}
if (level[level.Count - 1].Count == 1)
{
end = true;
}
}
outCl.hNode = level[level.Count - 1][0];
outCl.hNode.levelNum = 0;
//At the end level num must be set properly
Queue <HClusterNode> qq = new Queue <HClusterNode>();
HClusterNode h;
for (int i = 0; i < level.Count; i++)
{
for (int j = 0; j < level[i].Count; j++)
{
level[i][j].fNode = true;
}
}
for (int i = 0; i < level.Count; i++)
{
for (int j = 0; j < level[i].Count; j++)
{
if (level[i][j].fNode)
{
level[i][j].levelDist = Math.Abs(level[i][j].levelDist - dMeasure.maxSimilarity);
level[i][j].realDist = dMeasure.GetRealValue(level[i][j].levelDist);
level[i][j].fNode = false;
}
}
}
qq.Enqueue(level[level.Count - 1][0]);
while (qq.Count != 0)
{
h = qq.Dequeue();
if (h.joined != null)
{
foreach (var item in h.joined)
{
item.levelNum = h.levelNum + 1;
qq.Enqueue(item);
}
}
}
outCl.hNode.dirName = dirName;
outCl.clusters = null;
outCl.juryLike = null;
return(outCl);
}
