int MatrixOutputCommand::process(vector<SharedRAbundVector*> thisLookup){
try {
vector< vector< vector<seqDist> > > calcDistsTotals; //each iter, one for each calc, then each groupCombos dists. this will be used to make .dist files
vector< vector<seqDist> > calcDists; calcDists.resize(matrixCalculators.size());
for (int thisIter = 0; thisIter < iters+1; thisIter++) {
map<string, string> variables;
variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(sharedfile));
variables["[distance]"] = thisLookup[0]->getLabel();
variables["[tag2]"] = "";
vector<SharedRAbundVector*> thisItersLookup = thisLookup;
if (subsample && (thisIter != 0)) {
SubSample sample;
vector<string> tempLabels; //dont need since we arent printing the sampled sharedRabunds
//make copy of lookup so we don't get access violations
vector<SharedRAbundVector*> newLookup;
for (int k = 0; k < thisItersLookup.size(); k++) {
SharedRAbundVector* temp = new SharedRAbundVector();
temp->setLabel(thisItersLookup[k]->getLabel());
temp->setGroup(thisItersLookup[k]->getGroup());
newLookup.push_back(temp);
}
//for each bin
for (int k = 0; k < thisItersLookup[0]->getNumBins(); k++) {
if (m->control_pressed) { for (int j = 0; j < newLookup.size(); j++) { delete newLookup[j]; } return 0; }
for (int j = 0; j < thisItersLookup.size(); j++) { newLookup[j]->push_back(thisItersLookup[j]->getAbundance(k), thisItersLookup[j]->getGroup()); }
}
tempLabels = sample.getSample(newLookup, subsampleSize);
thisItersLookup = newLookup;
}
if(processors == 1){
driver(thisItersLookup, 0, numGroups, calcDists);
}else{
int process = 1;
vector<int> processIDS;
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
//loop through and create all the processes you want
while (process != processors) {
pid_t pid = fork();
if (pid > 0) {
processIDS.push_back(pid);
process++;
}else if (pid == 0){
driver(thisItersLookup, lines[process].start, lines[process].end, calcDists);
string tempdistFileName = m->getRootName(m->getSimpleName(sharedfile)) + m->mothurGetpid(process) + ".dist";
ofstream outtemp;
m->openOutputFile(tempdistFileName, outtemp);
for (int i = 0; i < calcDists.size(); i++) {
outtemp << calcDists[i].size() << endl;
for (int j = 0; j < calcDists[i].size(); j++) {
outtemp << calcDists[i][j].seq1 << '\t' << calcDists[i][j].seq2 << '\t' << calcDists[i][j].dist << endl;
}
}
outtemp.close();
exit(0);
}else {
m->mothurOut("[ERROR]: unable to spawn the necessary processes."); m->mothurOutEndLine();
for (int i = 0; i < processIDS.size(); i++) { kill (processIDS[i], SIGINT); }
exit(0);
}
}
//parent do your part
driver(thisItersLookup, lines[0].start, lines[0].end, calcDists);
//force parent to wait until all the processes are done
for (int i = 0; i < processIDS.size(); i++) {
int temp = processIDS[i];
wait(&temp);
}
for (int i = 0; i < processIDS.size(); i++) {
string tempdistFileName = m->getRootName(m->getSimpleName(sharedfile)) + toString(processIDS[i]) + ".dist";
ifstream intemp;
m->openInputFile(tempdistFileName, intemp);
for (int k = 0; k < calcDists.size(); k++) {
int size = 0;
intemp >> size; m->gobble(intemp);
for (int j = 0; j < size; j++) {
int seq1 = 0;
int seq2 = 0;
float dist = 1.0;
intemp >> seq1 >> seq2 >> dist; m->gobble(intemp);
seqDist tempDist(seq1, seq2, dist);
calcDists[k].push_back(tempDist);
}
}
intemp.close();
m->mothurRemove(tempdistFileName);
}
#else
//////////////////////////////////////////////////////////////////////////////////////////////////////
//Windows version shared memory, so be careful when passing variables through the distSharedData struct.
//Above fork() will clone, so memory is separate, but that's not the case with windows,
//Taking advantage of shared memory to pass results vectors.
//////////////////////////////////////////////////////////////////////////////////////////////////////
vector<distSharedData*> pDataArray;
DWORD dwThreadIdArray[processors-1];
HANDLE hThreadArray[processors-1];
//Create processor worker threads.
for( int i=1; i<processors; i++ ){
//make copy of lookup so we don't get access violations
vector<SharedRAbundVector*> newLookup;
for (int k = 0; k < thisItersLookup.size(); k++) {
SharedRAbundVector* temp = new SharedRAbundVector();
temp->setLabel(thisItersLookup[k]->getLabel());
temp->setGroup(thisItersLookup[k]->getGroup());
newLookup.push_back(temp);
}
//for each bin
for (int k = 0; k < thisItersLookup[0]->getNumBins(); k++) {
if (m->control_pressed) { for (int j = 0; j < newLookup.size(); j++) { delete newLookup[j]; } return 0; }
for (int j = 0; j < thisItersLookup.size(); j++) { newLookup[j]->push_back(thisItersLookup[j]->getAbundance(k), thisItersLookup[j]->getGroup()); }
}
// Allocate memory for thread data.
distSharedData* tempSum = new distSharedData(m, lines[i].start, lines[i].end, Estimators, newLookup);
pDataArray.push_back(tempSum);
processIDS.push_back(i);
hThreadArray[i-1] = CreateThread(NULL, 0, MyDistSharedThreadFunction, pDataArray[i-1], 0, &dwThreadIdArray[i-1]);
}
//parent do your part
driver(thisItersLookup, lines[0].start, lines[0].end, calcDists);
//Wait until all threads have terminated.
WaitForMultipleObjects(processors-1, hThreadArray, TRUE, INFINITE);
//Close all thread handles and free memory allocations.
for(int i=0; i < pDataArray.size(); i++){
if (pDataArray[i]->count != (pDataArray[i]->end-pDataArray[i]->start)) {
m->mothurOut("[ERROR]: process " + toString(i) + " only processed " + toString(pDataArray[i]->count) + " of " + toString(pDataArray[i]->end-pDataArray[i]->start) + " groups assigned to it, quitting. \n"); m->control_pressed = true;
}
for (int j = 0; j < pDataArray[i]->thisLookup.size(); j++) { delete pDataArray[i]->thisLookup[j]; }
for (int k = 0; k < calcDists.size(); k++) {
int size = pDataArray[i]->calcDists[k].size();
for (int j = 0; j < size; j++) { calcDists[k].push_back(pDataArray[i]->calcDists[k][j]); }
}
CloseHandle(hThreadArray[i]);
delete pDataArray[i];
}
#endif
}
if (subsample && (thisIter != 0)) {
if((thisIter) % 100 == 0){ m->mothurOutJustToScreen(toString(thisIter)+"\n"); }
calcDistsTotals.push_back(calcDists);
for (int i = 0; i < calcDists.size(); i++) {
for (int j = 0; j < calcDists[i].size(); j++) {
if (m->debug) { m->mothurOut("[DEBUG]: Results: iter = " + toString(thisIter) + ", " + thisLookup[calcDists[i][j].seq1]->getGroup() + " - " + thisLookup[calcDists[i][j].seq2]->getGroup() + " distance = " + toString(calcDists[i][j].dist) + ".\n"); }
}
}
//clean up memory
for (int i = 0; i < thisItersLookup.size(); i++) { delete thisItersLookup[i]; }
thisItersLookup.clear();
}else { //print results for whole dataset
for (int i = 0; i < calcDists.size(); i++) {
if (m->control_pressed) { break; }
//initialize matrix
vector< vector<double> > matrix; //square matrix to represent the distance
matrix.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
for (int j = 0; j < calcDists[i].size(); j++) {
int row = calcDists[i][j].seq1;
int column = calcDists[i][j].seq2;
double dist = calcDists[i][j].dist;
matrix[row][column] = dist;
matrix[column][row] = dist;
}
variables["[outputtag]"] = output;
variables["[calc]"] = matrixCalculators[i]->getName();
string distFileName = getOutputFileName("phylip",variables);
outputNames.push_back(distFileName); outputTypes["phylip"].push_back(distFileName);
ofstream outDist;
m->openOutputFile(distFileName, outDist);
outDist.setf(ios::fixed, ios::floatfield); outDist.setf(ios::showpoint);
printSims(outDist, matrix);
outDist.close();
}
}
for (int i = 0; i < calcDists.size(); i++) { calcDists[i].clear(); }
}
if (iters != 0) {
//we need to find the average distance and standard deviation for each groups distance
vector< vector<seqDist> > calcAverages = m->getAverages(calcDistsTotals, mode);
//find standard deviation
vector< vector<seqDist> > stdDev = m->getStandardDeviation(calcDistsTotals, calcAverages);
//print results
for (int i = 0; i < calcDists.size(); i++) {
vector< vector<double> > matrix; //square matrix to represent the distance
matrix.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
vector< vector<double> > stdmatrix; //square matrix to represent the stdDev
stdmatrix.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { stdmatrix[k].resize(thisLookup.size(), 0.0); }
for (int j = 0; j < calcAverages[i].size(); j++) {
int row = calcAverages[i][j].seq1;
int column = calcAverages[i][j].seq2;
float dist = calcAverages[i][j].dist;
float stdDist = stdDev[i][j].dist;
matrix[row][column] = dist;
matrix[column][row] = dist;
stdmatrix[row][column] = stdDist;
stdmatrix[column][row] = stdDist;
}
map<string, string> variables;
variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(sharedfile));
variables["[distance]"] = thisLookup[0]->getLabel();
variables["[outputtag]"] = output;
variables["[tag2]"] = "ave";
variables["[calc]"] = matrixCalculators[i]->getName();
string distFileName = getOutputFileName("phylip",variables);
outputNames.push_back(distFileName); outputTypes["phylip"].push_back(distFileName);
//set current phylip file to average distance matrix
m->setPhylipFile(distFileName);
ofstream outAve;
m->openOutputFile(distFileName, outAve);
outAve.setf(ios::fixed, ios::floatfield); outAve.setf(ios::showpoint);
printSims(outAve, matrix);
outAve.close();
variables["[tag2]"] = "std";
distFileName = getOutputFileName("phylip",variables);
outputNames.push_back(distFileName); outputTypes["phylip"].push_back(distFileName);
ofstream outSTD;
m->openOutputFile(distFileName, outSTD);
outSTD.setf(ios::fixed, ios::floatfield); outSTD.setf(ios::showpoint);
printSims(outSTD, stdmatrix);
outSTD.close();
}
}
return 0;
}
catch(exception& e) {
m->errorOut(e, "MatrixOutputCommand", "process");
exit(1);
}
}
int TreeGroupCommand::process(vector<SharedRAbundVector*> thisLookup) {
try{
vector< vector< vector<seqDist> > > calcDistsTotals; //each iter, one for each calc, then each groupCombos dists. this will be used to make .dist files
vector< vector<seqDist> > calcDists; calcDists.resize(treeCalculators.size());
for (int thisIter = 0; thisIter < iters; thisIter++) {
vector<SharedRAbundVector*> thisItersLookup = thisLookup;
if (subsample) {
SubSample sample;
vector<string> tempLabels; //dont need since we arent printing the sampled sharedRabunds
//make copy of lookup so we don't get access violations
vector<SharedRAbundVector*> newLookup;
for (int k = 0; k < thisItersLookup.size(); k++) {
SharedRAbundVector* temp = new SharedRAbundVector();
temp->setLabel(thisItersLookup[k]->getLabel());
temp->setGroup(thisItersLookup[k]->getGroup());
newLookup.push_back(temp);
}
//for each bin
for (int k = 0; k < thisItersLookup[0]->getNumBins(); k++) {
if (m->control_pressed) { for (int j = 0; j < newLookup.size(); j++) { delete newLookup[j]; } return 0; }
for (int j = 0; j < thisItersLookup.size(); j++) { newLookup[j]->push_back(thisItersLookup[j]->getAbundance(k), thisItersLookup[j]->getGroup()); }
}
tempLabels = sample.getSample(newLookup, subsampleSize);
thisItersLookup = newLookup;
}
if(processors == 1){
driver(thisItersLookup, 0, numGroups, calcDists);
}else{
int process = 1;
vector<int> processIDS;
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
//loop through and create all the processes you want
while (process != processors) {
pid_t pid = fork();
if (pid > 0) {
processIDS.push_back(pid);
process++;
}else if (pid == 0){
driver(thisItersLookup, lines[process].start, lines[process].end, calcDists);
string tempdistFileName = m->getRootName(m->getSimpleName(sharedfile)) + m->mothurGetpid(process) + ".dist";
ofstream outtemp;
m->openOutputFile(tempdistFileName, outtemp);
for (int i = 0; i < calcDists.size(); i++) {
outtemp << calcDists[i].size() << endl;
for (int j = 0; j < calcDists[i].size(); j++) {
outtemp << calcDists[i][j].seq1 << '\t' << calcDists[i][j].seq2 << '\t' << calcDists[i][j].dist << endl;
}
}
outtemp.close();
exit(0);
}else {
m->mothurOut("[ERROR]: unable to spawn the necessary processes."); m->mothurOutEndLine();
for (int i = 0; i < processIDS.size(); i++) { kill (processIDS[i], SIGINT); }
exit(0);
}
}
//parent do your part
driver(thisItersLookup, lines[0].start, lines[0].end, calcDists);
//force parent to wait until all the processes are done
for (int i = 0; i < processIDS.size(); i++) {
int temp = processIDS[i];
wait(&temp);
}
for (int i = 0; i < processIDS.size(); i++) {
string tempdistFileName = m->getRootName(m->getSimpleName(sharedfile)) + toString(processIDS[i]) + ".dist";
ifstream intemp;
m->openInputFile(tempdistFileName, intemp);
for (int k = 0; k < calcDists.size(); k++) {
int size = 0;
intemp >> size; m->gobble(intemp);
for (int j = 0; j < size; j++) {
int seq1 = 0;
int seq2 = 0;
float dist = 1.0;
intemp >> seq1 >> seq2 >> dist; m->gobble(intemp);
seqDist tempDist(seq1, seq2, dist);
calcDists[k].push_back(tempDist);
}
}
intemp.close();
m->mothurRemove(tempdistFileName);
}
#else
//////////////////////////////////////////////////////////////////////////////////////////////////////
//Windows version shared memory, so be careful when passing variables through the treeSharedData struct.
//Above fork() will clone, so memory is separate, but that's not the case with windows,
//Taking advantage of shared memory to pass results vectors.
//////////////////////////////////////////////////////////////////////////////////////////////////////
vector<treeSharedData*> pDataArray;
DWORD dwThreadIdArray[processors-1];
HANDLE hThreadArray[processors-1];
//Create processor worker threads.
for( int i=1; i<processors; i++ ){
//make copy of lookup so we don't get access violations
vector<SharedRAbundVector*> newLookup;
for (int k = 0; k < thisItersLookup.size(); k++) {
SharedRAbundVector* temp = new SharedRAbundVector();
temp->setLabel(thisItersLookup[k]->getLabel());
temp->setGroup(thisItersLookup[k]->getGroup());
newLookup.push_back(temp);
}
//for each bin
for (int k = 0; k < thisItersLookup[0]->getNumBins(); k++) {
if (m->control_pressed) { for (int j = 0; j < newLookup.size(); j++) { delete newLookup[j]; } return 0; }
for (int j = 0; j < thisItersLookup.size(); j++) { newLookup[j]->push_back(thisItersLookup[j]->getAbundance(k), thisItersLookup[j]->getGroup()); }
}
// Allocate memory for thread data.
treeSharedData* tempSum = new treeSharedData(m, lines[i].start, lines[i].end, Estimators, newLookup);
pDataArray.push_back(tempSum);
processIDS.push_back(i);
hThreadArray[i-1] = CreateThread(NULL, 0, MyTreeSharedThreadFunction, pDataArray[i-1], 0, &dwThreadIdArray[i-1]);
}
//parent do your part
driver(thisItersLookup, lines[0].start, lines[0].end, calcDists);
//Wait until all threads have terminated.
WaitForMultipleObjects(processors-1, hThreadArray, TRUE, INFINITE);
//Close all thread handles and free memory allocations.
for(int i=0; i < pDataArray.size(); i++){
if (pDataArray[i]->count != (pDataArray[i]->end-pDataArray[i]->start)) {
m->mothurOut("[ERROR]: process " + toString(i) + " only processed " + toString(pDataArray[i]->count) + " of " + toString(pDataArray[i]->end-pDataArray[i]->start) + " groups assigned to it, quitting. \n"); m->control_pressed = true;
}
for (int j = 0; j < pDataArray[i]->thisLookup.size(); j++) { delete pDataArray[i]->thisLookup[j]; }
for (int k = 0; k < calcDists.size(); k++) {
int size = pDataArray[i]->calcDists[k].size();
for (int j = 0; j < size; j++) { calcDists[k].push_back(pDataArray[i]->calcDists[k][j]); }
}
CloseHandle(hThreadArray[i]);
delete pDataArray[i];
}
#endif
}
calcDistsTotals.push_back(calcDists);
if (subsample) {
//clean up memory
for (int i = 0; i < thisItersLookup.size(); i++) { delete thisItersLookup[i]; }
thisItersLookup.clear();
for (int i = 0; i < calcDists.size(); i++) { calcDists[i].clear(); }
}
if (m->debug) { m->mothurOut("[DEBUG]: iter = " + toString(thisIter) + ".\n"); }
}
if (m->debug) { m->mothurOut("[DEBUG]: done with iters.\n"); }
if (iters != 1) {
//we need to find the average distance and standard deviation for each groups distance
vector< vector<seqDist> > calcAverages = m->getAverages(calcDistsTotals);
if (m->debug) { m->mothurOut("[DEBUG]: found averages.\n"); }
//create average tree for each calc
for (int i = 0; i < calcDists.size(); i++) {
vector< vector<double> > matrix; //square matrix to represent the distance
matrix.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
for (int j = 0; j < calcAverages[i].size(); j++) {
int row = calcAverages[i][j].seq1;
int column = calcAverages[i][j].seq2;
float dist = calcAverages[i][j].dist;
matrix[row][column] = dist;
matrix[column][row] = dist;
}
//create a new filename
map<string, string> variables;
variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(inputfile));
variables["[calc]"] = treeCalculators[i]->getName();
variables["[distance]"] = thisLookup[0]->getLabel();
variables["[tag]"] = "ave";
string outputFile = getOutputFileName("tree",variables);
outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
//creates tree from similarity matrix and write out file
Tree* newTree = createTree(matrix);
if (newTree != NULL) { writeTree(outputFile, newTree); }
}
if (m->debug) { m->mothurOut("[DEBUG]: done averages trees.\n"); }
//create all trees for each calc and find their consensus tree
for (int i = 0; i < calcDists.size(); i++) {
if (m->control_pressed) { break; }
//create a new filename
//create a new filename
map<string, string> variables;
variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(inputfile));
variables["[calc]"] = treeCalculators[i]->getName();
variables["[distance]"] = thisLookup[0]->getLabel();
variables["[tag]"] = "all";
string outputFile = getOutputFileName("tree",variables);
outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
ofstream outAll;
m->openOutputFile(outputFile, outAll);
vector<Tree*> trees;
for (int myIter = 0; myIter < iters; myIter++) {
if(m->control_pressed) { break; }
//initialize matrix
vector< vector<double> > matrix; //square matrix to represent the distance
matrix.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
for (int j = 0; j < calcDistsTotals[myIter][i].size(); j++) {
int row = calcDistsTotals[myIter][i][j].seq1;
int column = calcDistsTotals[myIter][i][j].seq2;
double dist = calcDistsTotals[myIter][i][j].dist;
matrix[row][column] = dist;
matrix[column][row] = dist;
}
//creates tree from similarity matrix and write out file
Tree* newTree = createTree(matrix);
if (newTree != NULL) {
newTree->print(outAll);
trees.push_back(newTree);
}
}
outAll.close();
if (m->control_pressed) { for (int k = 0; k < trees.size(); k++) { delete trees[k]; } }
if (m->debug) { m->mothurOut("[DEBUG]: done all trees.\n"); }
Consensus consensus;
//clear old tree names if any
m->Treenames.clear(); m->Treenames = m->getGroups(); //may have changed if subsample eliminated groups
Tree* conTree = consensus.getTree(trees);
if (m->debug) { m->mothurOut("[DEBUG]: done cons tree.\n"); }
//create a new filename
variables["[tag]"] = "cons";
string conFile = getOutputFileName("tree",variables);
outputNames.push_back(conFile); outputTypes["tree"].push_back(conFile);
ofstream outTree;
m->openOutputFile(conFile, outTree);
if (conTree != NULL) { conTree->print(outTree, "boot"); delete conTree; }
}
}else {
for (int i = 0; i < calcDists.size(); i++) {
if (m->control_pressed) { break; }
//initialize matrix
vector< vector<double> > matrix; //square matrix to represent the distance
matrix.resize(thisLookup.size());
for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
for (int j = 0; j < calcDists[i].size(); j++) {
int row = calcDists[i][j].seq1;
int column = calcDists[i][j].seq2;
double dist = calcDists[i][j].dist;
matrix[row][column] = dist;
matrix[column][row] = dist;
}
//create a new filename
map<string, string> variables;
variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(inputfile));
variables["[calc]"] = treeCalculators[i]->getName();
variables["[distance]"] = thisLookup[0]->getLabel();
variables["[tag]"] = "";
string outputFile = getOutputFileName("tree",variables);
outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
//creates tree from similarity matrix and write out file
Tree* newTree = createTree(matrix);
if (newTree != NULL) { writeTree(outputFile, newTree); delete newTree; }
}
}
return 0;
}
catch(exception& e) {
m->errorOut(e, "TreeGroupCommand", "process");
exit(1);
}
}
//**********************************************************************************************************************
int SummaryCommand::process(SAbundVector*& sabund, ofstream& outputFileHandle, ofstream& outAve) {
try {
//calculator -> data -> values
vector< vector< vector<double> > > results;
results.resize(sumCalculators.size());
outputFileHandle << sabund->getLabel();
SubSample sample;
for (int thisIter = 0; thisIter < iters+1; thisIter++) {
SAbundVector* thisIterSabund = sabund;
//we want the summary results for the whole dataset, then the subsampling
if ((thisIter > 0) && subsample) { //subsample sabund and run it
//copy sabund since getSample destroys it
RAbundVector rabund = sabund->getRAbundVector();
SAbundVector* newSabund = new SAbundVector();
*newSabund = rabund.getSAbundVector();
sample.getSample(newSabund, subsampleSize);
thisIterSabund = newSabund;
}
for(int i=0; i<sumCalculators.size(); i++) {
vector<double> data = sumCalculators[i]->getValues(thisIterSabund);
if (m->control_pressed) {
return 0;
}
if (thisIter == 0) {
outputFileHandle << '\t';
sumCalculators[i]->print(outputFileHandle);
} else {
//some of the calc have hci and lci need to make room for that
if (results[i].size() == 0) {
results[i].resize(data.size());
}
//save results for ave and std.
for (int j = 0; j < data.size(); j++) {
if (m->control_pressed) {
return 0;
}
results[i][j].push_back(data[j]);
}
}
}
//cleanup memory
if ((thisIter > 0) && subsample) {
delete thisIterSabund;
}
}
outputFileHandle << endl;
if (subsample) {
outAve << sabund->getLabel() << '\t' << "ave\t";
//find ave and std for this label and output
//will need to modify the createGroupSummary to combine results and not mess with the .summary file.
//calcs -> values
vector< vector<double> > calcAverages;
calcAverages.resize(sumCalculators.size());
for (int i = 0; i < calcAverages.size(); i++) {
calcAverages[i].resize(results[i].size(), 0);
}
for (int thisIter = 0; thisIter < iters; thisIter++) { //sum all groups dists for each calculator
for (int i = 0; i < calcAverages.size(); i++) { //initialize sums to zero.
for (int j = 0; j < calcAverages[i].size(); j++) {
calcAverages[i][j] += results[i][j][thisIter];
}
}
}
for (int i = 0; i < calcAverages.size(); i++) { //finds average.
for (int j = 0; j < calcAverages[i].size(); j++) {
calcAverages[i][j] /= (float) iters;
outAve << calcAverages[i][j] << '\t';
}
}
//find standard deviation
vector< vector<double> > stdDev;
stdDev.resize(sumCalculators.size());
for (int i = 0; i < stdDev.size(); i++) {
stdDev[i].resize(results[i].size(), 0);
}
for (int thisIter = 0; thisIter < iters; thisIter++) { //compute the difference of each dist from the mean, and square the result of each
for (int i = 0; i < stdDev.size(); i++) {
for (int j = 0; j < stdDev[i].size(); j++) {
stdDev[i][j] += ((results[i][j][thisIter] - calcAverages[i][j]) * (results[i][j][thisIter] - calcAverages[i][j]));
}
}
}
outAve << endl << sabund->getLabel() << '\t' << "std\t";
for (int i = 0; i < stdDev.size(); i++) { //finds average.
for (int j = 0; j < stdDev[i].size(); j++) {
stdDev[i][j] /= (float) iters;
stdDev[i][j] = sqrt(stdDev[i][j]);
outAve << stdDev[i][j] << '\t';
}
}
outAve << endl;
}
return 0;
}
catch(exception& e) {
m->errorOut(e, "SummaryCommand", "process");
exit(1);
}
}
int process(treeSharedData* params) {
try{
ValidCalculators validCalculator;
vector<Calculator*> treeCalculators;
for (int i=0; i<params->Estimators.size(); i++) {
if (validCalculator.isValidCalculator("treegroup", params->Estimators[i]) ) {
if (params->Estimators[i] == "sharedsobs") {
treeCalculators.push_back(new SharedSobsCS());
}else if (params->Estimators[i] == "sharedchao") {
treeCalculators.push_back(new SharedChao1());
}else if (params->Estimators[i] == "sharedace") {
treeCalculators.push_back(new SharedAce());
}else if (params->Estimators[i] == "jabund") {
treeCalculators.push_back(new JAbund());
}else if (params->Estimators[i] == "sorabund") {
treeCalculators.push_back(new SorAbund());
}else if (params->Estimators[i] == "jclass") {
treeCalculators.push_back(new Jclass());
}else if (params->Estimators[i] == "sorclass") {
treeCalculators.push_back(new SorClass());
}else if (params->Estimators[i] == "jest") {
treeCalculators.push_back(new Jest());
}else if (params->Estimators[i] == "sorest") {
treeCalculators.push_back(new SorEst());
}else if (params->Estimators[i] == "thetayc") {
treeCalculators.push_back(new ThetaYC());
}else if (params->Estimators[i] == "thetan") {
treeCalculators.push_back(new ThetaN());
}else if (params->Estimators[i] == "kstest") {
treeCalculators.push_back(new KSTest());
}else if (params->Estimators[i] == "sharednseqs") {
treeCalculators.push_back(new SharedNSeqs());
}else if (params->Estimators[i] == "ochiai") {
treeCalculators.push_back(new Ochiai());
}else if (params->Estimators[i] == "anderberg") {
treeCalculators.push_back(new Anderberg());
}else if (params->Estimators[i] == "kulczynski") {
treeCalculators.push_back(new Kulczynski());
}else if (params->Estimators[i] == "kulczynskicody") {
treeCalculators.push_back(new KulczynskiCody());
}else if (params->Estimators[i] == "lennon") {
treeCalculators.push_back(new Lennon());
}else if (params->Estimators[i] == "morisitahorn") {
treeCalculators.push_back(new MorHorn());
}else if (params->Estimators[i] == "braycurtis") {
treeCalculators.push_back(new BrayCurtis());
}else if (params->Estimators[i] == "whittaker") {
treeCalculators.push_back(new Whittaker());
}else if (params->Estimators[i] == "odum") {
treeCalculators.push_back(new Odum());
}else if (params->Estimators[i] == "canberra") {
treeCalculators.push_back(new Canberra());
}else if (params->Estimators[i] == "structeuclidean") {
treeCalculators.push_back(new StructEuclidean());
}else if (params->Estimators[i] == "structchord") {
treeCalculators.push_back(new StructChord());
}else if (params->Estimators[i] == "hellinger") {
treeCalculators.push_back(new Hellinger());
}else if (params->Estimators[i] == "manhattan") {
treeCalculators.push_back(new Manhattan());
}else if (params->Estimators[i] == "structpearson") {
treeCalculators.push_back(new StructPearson());
}else if (params->Estimators[i] == "soergel") {
treeCalculators.push_back(new Soergel());
}else if (params->Estimators[i] == "spearman") {
treeCalculators.push_back(new Spearman());
}else if (params->Estimators[i] == "structkulczynski") {
treeCalculators.push_back(new StructKulczynski());
}else if (params->Estimators[i] == "speciesprofile") {
treeCalculators.push_back(new SpeciesProfile());
}else if (params->Estimators[i] == "hamming") {
treeCalculators.push_back(new Hamming());
}else if (params->Estimators[i] == "structchi2") {
treeCalculators.push_back(new StructChi2());
}else if (params->Estimators[i] == "gower") {
treeCalculators.push_back(new Gower());
}else if (params->Estimators[i] == "memchi2") {
treeCalculators.push_back(new MemChi2());
}else if (params->Estimators[i] == "memchord") {
treeCalculators.push_back(new MemChord());
}else if (params->Estimators[i] == "memeuclidean") {
treeCalculators.push_back(new MemEuclidean());
}else if (params->Estimators[i] == "mempearson") {
treeCalculators.push_back(new MemPearson());
}else if (params->Estimators[i] == "jsd") {
treeCalculators.push_back(new JSD());
}else if (params->Estimators[i] == "rjsd") {
treeCalculators.push_back(new RJSD());
}
}
}
//if the users entered no valid calculators don't execute command
if (treeCalculators.size() == 0) { params->m->mothurOut("You have given no valid calculators.\n"); return 0; }
params->Estimators.clear();
for (int i=0; i<treeCalculators.size(); i++) { params->Estimators.push_back(treeCalculators[i]->getName()); }
vector< vector<seqDist> > calcDists; calcDists.resize(treeCalculators.size());
SubSample sample;
for (int thisIter = 0; thisIter < params->numIters; thisIter++) {
SharedRAbundVectors* thisItersLookup = new SharedRAbundVectors(*params->thisLookup);
vector<string> namesOfGroups = thisItersLookup->getNamesGroups();
if ((params->subsample && (!params->mainThread)) || (params->mainThread && (thisIter != 0) ) ) {
if (params->withReplacement) { sample.getSampleWithReplacement(thisItersLookup, params->subsampleSize); }
else { sample.getSample(thisItersLookup, params->subsampleSize); }
}
vector<SharedRAbundVector*> thisItersRabunds = thisItersLookup->getSharedRAbundVectors();
vector<string> thisItersGroupNames = params->thisLookup->getNamesGroups();
driverTreeShared(thisItersRabunds, calcDists, treeCalculators, params->m);
for (int i = 0; i < thisItersRabunds.size(); i++) { delete thisItersRabunds[i]; }
if ((params->subsample && (!params->mainThread)) || (params->mainThread && (thisIter != 0) ) ){
if((thisIter+1) % 100 == 0){ params->m->mothurOutJustToScreen(toString(thisIter+1)+"\n"); }
params->calcDistsTotals.push_back(calcDists);
for (int i = 0; i < calcDists.size(); i++) {
for (int j = 0; j < calcDists[i].size(); j++) {
if (params->m->getDebug()) { params->m->mothurOut("[DEBUG]: Results: iter = " + toString(thisIter) + ", " + thisItersGroupNames[calcDists[i][j].seq1] + " - " + thisItersGroupNames[calcDists[i][j].seq2] + " distance = " + toString(calcDists[i][j].dist) + ".\n"); }
}
}
}else { //print results for whole dataset
for (int i = 0; i < calcDists.size(); i++) {
if (params->m->getControl_pressed()) { break; }
//initialize matrix
vector< vector<double> > matrix; //square matrix to represent the distance
matrix.resize(thisItersLookup->size());
for (int k = 0; k < thisItersLookup->size(); k++) { matrix[k].resize(thisItersLookup->size(), 0.0); }
for (int j = 0; j < calcDists[i].size(); j++) {
int row = calcDists[i][j].seq1;
int column = calcDists[i][j].seq2;
double dist = calcDists[i][j].dist;
matrix[row][column] = -(dist-1.0);
matrix[column][row] = -(dist-1.0);
}
params->matrices.push_back(matrix);
}
}
for (int i = 0; i < calcDists.size(); i++) { calcDists[i].clear(); }
delete thisItersLookup;
}
if((params->numIters) % 100 != 0){ params->m->mothurOutJustToScreen(toString(params->numIters)+"\n"); }
for (int i=0; i<treeCalculators.size(); i++) { delete treeCalculators[i]; }
return 0;
}
catch(exception& e) {
params->m->errorOut(e, "TreeGroupCommand", "process");
exit(1);
}
}
