X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=cluster.cpp;h=a766e08d47b4af7a46d8093323cb795d57d6aa78;hb=6e8fce385a566f51350274309503d7405e5b9f35;hp=e2d307e1bfbce54162b55a7368b58180205f87e5;hpb=fdc1f6eaf544f695fc1511f24bddd7e6069c33ba;p=mothur.git

diff --git a/cluster.cpp b/cluster.cpp
index e2d307e..a766e08 100644
--- a/cluster.cpp
+++ b/cluster.cpp
@@ -17,6 +17,7 @@
 Cluster::Cluster(RAbundVector* rav, ListVector* lv, SparseMatrix* dm, float c, string f) :
 rabund(rav), list(lv), dMatrix(dm), method(f)
 {
+	try {
 /*
 	cout << "sizeof(MatData): " << sizeof(MatData) << endl;
 	cout << "sizeof(PCell*): " << sizeof(PCell*) << endl;
@@ -50,19 +51,28 @@ rabund(rav), list(lv), dMatrix(dm), method(f)
 	// a list contains pointers (iterators) to the all distances related
 	// to a certain sequence. The Vector is accessed via the index of a 
 	// sequence in the distance matrix.
-	
-
+//ofstream outtemp;
+//string temp = "temp";
+//openOutputFile(temp, outtemp);	
+//cout << lv->size() << endl;
 	seqVec = vector<MatVec>(lv->size());
 	for (MatData currentCell = dMatrix->begin(); currentCell != dMatrix->end(); currentCell++) {
+//outtemp << currentCell->row << '\t' << currentCell->column  << '\t' << currentCell->dist << endl;
 		seqVec[currentCell->row].push_back(currentCell);
 		seqVec[currentCell->column].push_back(currentCell);
 	}
-
+//outtemp.close();
 	mapWanted = false;  //set to true by mgcluster to speed up overlap merge
 	
 	//save so you can modify as it changes in average neighbor
 	cutoff = c;
 	m = MothurOut::getInstance();
+	
+	}
+	catch(exception& e) {
+		m->errorOut(e, "Cluster", "Cluster");
+		exit(1);
+	}
 }
 
 /***********************************************************************/
@@ -74,11 +84,16 @@ void Cluster::getRowColCells() {
 		smallRow = smallCell->row;		// get its row
 		smallCol = smallCell->column;	// get its column
 		smallDist = smallCell->dist;	// get the smallest distance
-	
+	//cout << "small row = " << smallRow << "small col = " << smallCol << "small dist = " << smallDist << endl;
+	 
 		rowCells = seqVec[smallRow];    // all distances related to the row index
 		colCells = seqVec[smallCol];    // all distances related to the column index
 		nRowCells = rowCells.size();
 		nColCells = colCells.size();
+//cout << "num rows = " << nRowCells << "num col = " << nColCells << endl;
+		
+		//for (int i = 0; i < nColCells; i++) { cout << colCells[i]->row << '\t' << colCells[i]->column << endl;  }
+		//for (int i = 0; i < nRowCells; i++) { cout << rowCells[i]->row << '\t' << rowCells[i]->column << endl;  }
 	}
 	catch(exception& e) {
 		m->errorOut(e, "Cluster", "getRowColCells");
@@ -132,7 +147,9 @@ void Cluster::removeCell(const MatData& cell, int vrow, int vcol, bool rmMatrix)
 			seqVec[dcol].erase(seqVec[dcol].begin()+vcol);
 		
 			if (rmMatrix) {
+			//cout << " removing = " << cell->row << '\t' << cell->column  << '\t' << cell->dist << endl;
 				dMatrix->rmCell(cell);
+		//	cout << "done" << endl;
 			}
 		
 	}
@@ -224,7 +241,7 @@ void Cluster::update(double& cutOFF){
 					}		
 				}
 				//if not merged it you need it for warning 
-				if ((!merged) && (method == "average")) {  
+				if ((!merged) && (method == "average" || method == "weighted")) {  
 					//m->mothurOut("Warning: trying to merge cell " + toString(rowCells[i]->row+1) + " " + toString(rowCells[i]->column+1) + " distance " + toString(rowCells[i]->dist) + " with value above cutoff. Results may vary from using cutoff at cluster command instead of read.dist."); m->mothurOutEndLine(); 
 					if (cutOFF > rowCells[i]->dist) {  
 						cutOFF = rowCells[i]->dist;  
@@ -243,7 +260,7 @@ void Cluster::update(double& cutOFF){
 		// could be avoided
 		for (int i=nColCells-1;i>=0;i--) {
 			if (foundCol[i] == 0) {
-				if (method == "average") {
+				if (method == "average" || method == "weighted") {
 					if (!((colCells[i]->row == smallRow) && (colCells[i]->column == smallCol))) {
 						//m->mothurOut("Warning: merging cell " + toString(colCells[i]->row+1) + " " + toString(colCells[i]->column+1) + " distance " + toString(colCells[i]->dist) + " value above cutoff. Results may vary from using cutoff at cluster command instead of read.dist."); m->mothurOutEndLine();
 						if (cutOFF > colCells[i]->dist) {