/***********************************************************************/
-SingleLinkage::SingleLinkage(RAbundVector* rav, ListVector* lv, SparseMatrix* dm) :
-Cluster(rav, lv, dm)
+SingleLinkage::SingleLinkage(RAbundVector* rav, ListVector* lv, SparseDistanceMatrix* dm, float c, string s) :
+Cluster(rav, lv, dm, c, s)
{}
+
+/***********************************************************************/
+//This function returns the tag of the method.
+string SingleLinkage::getTag() {
+ return("nn");
+}
+
/***********************************************************************/
-//This function clusters based on nearest method.
-void SingleLinkage::update(){
+//This function clusters based on the single linkage method.
+void SingleLinkage::update(double& cutOFF){
try {
- getRowColCells();
+ smallCol = dMatrix->getSmallestCell(smallRow);
+ nColCells = dMatrix->seqVec[smallCol].size();
+ nRowCells = dMatrix->seqVec[smallRow].size();
- for(int i=1;i<nRowCells;i++){
-
- int search;
-
- if(rowCells[i]->row == smallRow){
- search = rowCells[i]->column;
- }
- else{
- search = rowCells[i]->row;
- }
-
- for(int j=1;j<nColCells;j++){
-
- if(colCells[j]->row == search || colCells[j]->column == search){
-
- if(colCells[j]->dist > rowCells[i]->dist){
- colCells[j]->dist = rowCells[i]->dist;
-
- if(colCells[j]->vectorMap != NULL){
- *(colCells[j]->vectorMap) = NULL;
- colCells[j]->vectorMap = NULL;
- }
-
- }
- dMatrix->rmCell(rowCells[i]);
- break;
- }
- }
-
- if(search < smallCol){
- rowCells[i]->row = smallCol;
- rowCells[i]->column = search;
- }
- else{
- rowCells[i]->row = search;
- rowCells[i]->column = smallCol;
- }
-
- }
+ vector<bool> deleted(nRowCells, false);
+ int rowInd;
+ int search;
+ bool changed;
+
+ // The vector has to be traversed in reverse order to preserve the index
+ // for faster removal in removeCell()
+ for (int i=nRowCells-1;i>=0;i--) {
+ if (dMatrix->seqVec[smallRow][i].index == smallCol) {
+ rowInd = i; // The index of the smallest distance cell in rowCells
+ } else {
+ search = dMatrix->seqVec[smallRow][i].index;
+
+ for (int j=0;j<nColCells;j++) {
+ if (dMatrix->seqVec[smallCol][j].index != smallRow) { //if you are not the small cell
+ if (dMatrix->seqVec[smallCol][j].index == search) {
+ changed = updateDistance(dMatrix->seqVec[smallCol][j], dMatrix->seqVec[smallRow][i]);
+ dMatrix->updateCellCompliment(smallCol, j);
+ dMatrix->rmCell(smallRow, i);
+ deleted[i] = true;
+ break;
+ }
+ }
+ }
+ if (!deleted[i]) {
+ // Assign the cell to the new cluster
+ // remove the old cell from seqVec and add the cell
+ // with the new row and column assignment again
+ float distance = dMatrix->seqVec[smallRow][i].dist;
+ dMatrix->rmCell(smallRow, i);
+ if (search < smallCol){
+ PDistCell value(smallCol, distance);
+ dMatrix->addCell(search, value);
+ } else {
+ PDistCell value(search, distance);
+ dMatrix->addCell(smallCol, value);
+ }
+ sort(dMatrix->seqVec[smallCol].begin(), dMatrix->seqVec[smallCol].end(), compareIndexes);
+ sort(dMatrix->seqVec[search].begin(), dMatrix->seqVec[search].end(), compareIndexes);
+ }
+ }
+ }
clusterBins();
clusterNames();
- dMatrix->rmCell(rowCells[0]);
+ // remove also the cell with the smallest distance
+
+ dMatrix->rmCell(smallRow, rowInd);
}
catch(exception& e) {
- errorOut(e, "SingleLinkage", "update");
+ m->errorOut(e, "SingleLinkage", "update");
exit(1);
}
}
+
+/***********************************************************************/
+//This function updates the distance based on the nearest neighbor method.
+bool SingleLinkage::updateDistance(PDistCell& colCell, PDistCell& rowCell) {
+ try {
+ bool changed = false;
+ if (colCell.dist > rowCell.dist) {
+ colCell.dist = rowCell.dist;
+ }
+ return(changed);
+ }
+ catch(exception& e) {
+ m->errorOut(e, "SingleLinkage", "updateDistance");
+ exit(1);
+ }
+}
/***********************************************************************/