added modify names parameter to set.dir

[mothur.git] / singlelinkage.cpp

diff --git a/singlelinkage.cpp b/singlelinkage.cpp
index 9f015db7359879be53da5e6001889117c7e5f7c6..3af1ea0c346030eb6f8eda3527ffc7a882c1b950 100644 (file)
--- a/singlelinkage.cpp
+++ b/singlelinkage.cpp
@@ -5,8 +5,8 @@
 
 /***********************************************************************/
 
-SingleLinkage::SingleLinkage(RAbundVector* rav, ListVector* lv, SparseMatrix* dm, float c) :
-Cluster(rav, lv, dm, c)
+SingleLinkage::SingleLinkage(RAbundVector* rav, ListVector* lv, SparseDistanceMatrix* dm, float c, string s) :
+Cluster(rav, lv, dm, c, s)
 {}
 
 
@@ -18,9 +18,11 @@ string SingleLinkage::getTag() {
 
 /***********************************************************************/
 //This function clusters based on the single linkage method.
-void  SingleLinkage::update(){
+void SingleLinkage::update(double& cutOFF){
        try {
-               getRowColCells();       
+               smallCol = dMatrix->getSmallestCell(smallRow);
+        nColCells = dMatrix->seqVec[smallCol].size();
+        nRowCells = dMatrix->seqVec[smallRow].size();  
        
                vector<bool> deleted(nRowCells, false);
                int rowInd;
@@ -30,57 +32,48 @@ void  SingleLinkage::update(){
                // 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 ((rowCells[i]->row == smallRow) && (rowCells[i]->column == smallCol)) {
-                               rowInd = i;   // The index of the smallest distance cell in rowCells
-                       } else {
-                               if (rowCells[i]->row == smallRow) {
-                                       search = rowCells[i]->column;
-                               } else {
-                                       search = rowCells[i]->row;
-                               }
-               
-                               for (int j=0;j<nColCells;j++) {
-                                       if (!((colCells[j]->row == smallRow) && (colCells[j]->column == smallCol))) {
-                                               if (colCells[j]->row == search || colCells[j]->column == search) {
-                                                       changed = updateDistance(colCells[j], rowCells[i]);
-                                                       // If the cell's distance changed and it had the same distance as 
-                                                       // the smallest distance, invalidate the mins vector in SparseMatrix
-                                                       if (changed) {
-                                                               if (colCells[j]->vectorMap != NULL) {
-                                                                       *(colCells[j]->vectorMap) = NULL;
-                                                                       colCells[j]->vectorMap = NULL;
-                                                               }
-                                                       }
-                                                       removeCell(rowCells[i], i , -1);
-                                                       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
-                                       removeCell(rowCells[i], i , -1, false);
-                                       if (search < smallCol){
-                                               rowCells[i]->row = smallCol;
-                                               rowCells[i]->column = search;
-                                       } else {
-                                               rowCells[i]->row = search;
-                                               rowCells[i]->column = smallCol;
-                                       }
-                                       seqVec[rowCells[i]->row].push_back(rowCells[i]);
-                                       seqVec[rowCells[i]->column].push_back(rowCells[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();
                // remove also the cell with the smallest distance
-               removeCell(rowCells[rowInd], -1 , -1);
+
+               dMatrix->rmCell(smallRow, rowInd);
        }
        catch(exception& e) {
-               errorOut(e, "SingleLinkage", "update");
+               m->errorOut(e, "SingleLinkage", "update");
                exit(1);
        }
 }
@@ -88,16 +81,16 @@ void  SingleLinkage::update(){
 
 /***********************************************************************/
 //This function updates the distance based on the nearest neighbor method.
-bool SingleLinkage::updateDistance(MatData& colCell, MatData& rowCell) {
+bool SingleLinkage::updateDistance(PDistCell& colCell, PDistCell& rowCell) {
        try {
                bool changed = false;
-               if (colCell->dist > rowCell->dist) {
-                       colCell->dist = rowCell->dist;
+               if (colCell.dist > rowCell.dist) {
+                       colCell.dist = rowCell.dist;
                }
                return(changed);
        }
        catch(exception& e) {
-               errorOut(e, "SingleLinkage", "updateDistance");
+               m->errorOut(e, "SingleLinkage", "updateDistance");
                exit(1);
        }
 }