X-Git-Url: https://git.donarmstrong.com/?p=mothur.git;a=blobdiff_plain;f=singlelinkage.cpp;h=3af1ea0c346030eb6f8eda3527ffc7a882c1b950;hp=3c2697714f4e252a7e2aa0ee06002ba4a8a6fa46;hb=a8e2df1b96a57f5f29576b08361b86a96a8eff4f;hpb=20a2d0350a737a434c89f303662d64a8eeea7b05

diff --git a/singlelinkage.cpp b/singlelinkage.cpp
index 3c26977..3af1ea0 100644
--- a/singlelinkage.cpp
+++ b/singlelinkage.cpp
@@ -1,70 +1,97 @@
 
+#include "mothur.h"
 #include "cluster.hpp"
-#include <exception>
+
 
 /***********************************************************************/
 
-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) {
-		cout << "Standard Error: " << e.what() << " has occurred in the SingleLinkage class Function update. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
+		m->errorOut(e, "SingleLinkage", "update");
 		exit(1);
 	}
-	catch(...) {
-		cout << "An unknown error has occurred in the SingleLinkage class function update. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
-		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);
+	}
+}
 /***********************************************************************/