double HCluster::update(int row, int col, float distance){
try {
bool cluster = false;
smallRow = row;
smallCol = col;
smallDist = distance;
//find upmost parent of row and col
smallRow = getUpmostParent(smallRow);
smallCol = getUpmostParent(smallCol);
//you don't want to cluster with yourself
if (smallRow != smallCol) {
if ((method == "furthest") || (method == "nearest")) {
//can we cluster???
if (method == "nearest") { cluster = true; }
else{ //assume furthest
//are they active in the link table
int linkValue = makeActive(); //after this point this nodes info is active in linkTable
if (linkValue == (clusterArray[smallRow].numSeq * clusterArray[smallCol].numSeq)) { cluster = true; }
}
if (cluster) {
updateArrayandLinkTable();
clusterBins();
clusterNames();
}
}else {
cluster = true;
updateArrayandLinkTable();
clusterBins();
clusterNames();
combineFile();
}
}
return cutoff;
//printInfo();
}
catch(exception& e) {
m->errorOut(e, "HCluster", "update");
exit(1);
}
}
//This function clusters based on the single linkage method.
void SingleLinkage::update(double& cutOFF){
try {
getRowColCells();
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 ((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]);
}
}
}
clusterBins();
clusterNames();
// remove also the cell with the smallest distance
removeCell(rowCells[rowInd], -1 , -1);
}
catch(exception& e) {
m->errorOut(e, "SingleLinkage", "update");
exit(1);
}
}
void Cluster::update(double& cutOFF){
try {
smallCol = dMatrix->getSmallestCell(smallRow);
nColCells = dMatrix->seqVec[smallCol].size();
nRowCells = dMatrix->seqVec[smallRow].size();
vector<int> foundCol(nColCells, 0);
//cout << dMatrix->getNNodes() << " small cell: " << smallRow << '\t' << smallCol << endl;
int search;
bool changed;
for (int i=nRowCells-1;i>=0;i--) {
if (m->control_pressed) { break; }
//if you are not the smallCell
if (dMatrix->seqVec[smallRow][i].index != smallCol) {
search = dMatrix->seqVec[smallRow][i].index;
bool merged = false;
for (int j=0;j<nColCells;j++) {
if (dMatrix->seqVec[smallCol][j].index != smallRow) { //if you are not the smallest distance
if (dMatrix->seqVec[smallCol][j].index == search) {
foundCol[j] = 1;
merged = true;
changed = updateDistance(dMatrix->seqVec[smallCol][j], dMatrix->seqVec[smallRow][i]);
dMatrix->updateCellCompliment(smallCol, j);
break;
}else if (dMatrix->seqVec[smallCol][j].index < search) { j+=nColCells; } //we don't have a distance for this cell
}
}
//if not merged it you need it for warning
if ((!merged) && (method == "average" || method == "weighted")) {
if (cutOFF > dMatrix->seqVec[smallRow][i].dist) {
cutOFF = dMatrix->seqVec[smallRow][i].dist;
//cout << "changing cutoff to " << cutOFF << endl;
}
}
dMatrix->rmCell(smallRow, i);
}
}
clusterBins();
clusterNames();
// Special handling for singlelinkage case, not sure whether this
// could be avoided
for (int i=nColCells-1;i>=0;i--) {
if (foundCol[i] == 0) {
if (method == "average" || method == "weighted") {
if (dMatrix->seqVec[smallCol][i].index != smallRow) { //if you are not hte smallest distance
if (cutOFF > dMatrix->seqVec[smallCol][i].dist) {
cutOFF = dMatrix->seqVec[smallCol][i].dist;
}
}
}
dMatrix->rmCell(smallCol, i);
}
}
}
catch(exception& e) {
m->errorOut(e, "Cluster", "update");
exit(1);
}
}
