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/*
* distsharedcommand.cpp
* Mothur
*
* Created by Sarah Westcott on 5/20/09.
* Copyright 2009 Schloss Lab UMASS Amherst. All rights reserved.
*
*/
#include "distsharedcommand.h"
#include "subsample.h"
//**********************************************************************************************************************
vector<string> DistSharedCommand::setParameters(){
try {
CommandParameter pshared("shared", "InputTypes", "", "", "none", "none", "none","phylip",false,true,true); parameters.push_back(pshared);
CommandParameter plabel("label", "String", "", "", "", "", "","",false,false); parameters.push_back(plabel);
CommandParameter psubsample("subsample", "String", "", "", "", "", "","",false,false); parameters.push_back(psubsample);
CommandParameter pgroups("groups", "String", "", "", "", "", "","",false,false); parameters.push_back(pgroups);
CommandParameter pcalc("calc", "Multiple", "sharedsobs-sharedchao-sharedace-jabund-sorabund-jclass-sorclass-jest-sorest-thetayc-thetan-kstest-sharednseqs-ochiai-anderberg-kulczynski-kulczynskicody-lennon-morisitahorn-braycurtis-whittaker-odum-canberra-structeuclidean-structchord-hellinger-manhattan-structpearson-soergel-spearman-structkulczynski-speciesprofile-hamming-structchi2-gower-memchi2-memchord-memeuclidean-mempearson-jsd-rjsd", "jclass-thetayc", "", "", "","",true,false,true); parameters.push_back(pcalc);
CommandParameter poutput("output", "Multiple", "lt-square-column", "lt", "", "", "","",false,false); parameters.push_back(poutput);
CommandParameter pmode("mode", "Multiple", "average-median", "average", "", "", "","",false,false); parameters.push_back(pmode);
CommandParameter pprocessors("processors", "Number", "", "1", "", "", "","",false,false,true); parameters.push_back(pprocessors);
CommandParameter piters("iters", "Number", "", "1000", "", "", "","",false,false); parameters.push_back(piters);
CommandParameter pwithreplacement("withreplacement", "Boolean", "", "F", "", "", "","",false,false,true); parameters.push_back(pwithreplacement);
CommandParameter pseed("seed", "Number", "", "0", "", "", "","",false,false); parameters.push_back(pseed);
CommandParameter pinputdir("inputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(pinputdir);
CommandParameter poutputdir("outputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(poutputdir);
vector<string> tempOutNames;
outputTypes["phylip"] = tempOutNames;
abort = false; calledHelp = false; allLines = true;
vector<string> myArray;
for (int i = 0; i < parameters.size(); i++) { myArray.push_back(parameters[i].name); }
return myArray;
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "setParameters");
exit(1);
}
}
//**********************************************************************************************************************
string DistSharedCommand::getHelpString(){
try {
string helpString = "";
ValidCalculators validCalculator;
helpString += "The dist.shared command parameters are shared, groups, calc, output, processors, subsample, iters, mode, and label. shared is a required, unless you have a valid current file.\n";
helpString += "The groups parameter allows you to specify which of the groups in your groupfile you would like included used.\n";
helpString += "The group names are separated by dashes. The label parameter allows you to select what distance levels you would like distance matrices created for, and is also separated by dashes.\n";
helpString += "The iters parameter allows you to choose the number of times you would like to run the subsample.\n";
helpString += "The subsample parameter allows you to enter the size pergroup of the sample or you can set subsample=T and mothur will use the size of your smallest group.\n";
helpString += "The withreplacement parameter allows you to indicate you want to subsample your data allowing for the same read to be included multiple times. Default=f. \n";
helpString += "The dist.shared command should be in the following format: dist.shared(groups=yourGroups, calc=yourCalcs, label=yourLabels).\n";
helpString += "The output parameter allows you to specify format of your distance matrix. Options are lt, column and square. The default is lt.\n";
helpString += "The mode parameter allows you to specify if you want the average or the median values reported when subsampling. Options are average, and median. The default is average.\n";
helpString += "Example dist.shared(groups=A-B-C, calc=jabund-sorabund).\n";
helpString += "The default value for groups is all the groups in your groupfile.\n";
helpString += "The default value for calc is jclass and thetayc.\n";
helpString += validCalculator.printCalc("matrix");
helpString += "The dist.shared command outputs a .dist file for each calculator you specify at each distance you choose.\n";
return helpString;
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "getHelpString");
exit(1);
}
}
//**********************************************************************************************************************
string DistSharedCommand::getOutputPattern(string type) {
try {
string pattern = "";
if (type == "phylip") { pattern = "[filename],[calc],[distance],[outputtag],dist-[filename],[calc],[distance],[outputtag],[tag2],dist"; }
else { m->mothurOut("[ERROR]: No definition for type " + type + " output pattern.\n"); m->setControl_pressed(true); }
return pattern;
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "getOutputPattern");
exit(1);
}
}
//**********************************************************************************************************************
DistSharedCommand::DistSharedCommand(string option) : Command() {
try {
if(option == "help") { help(); abort = true; calledHelp = true; }
else if(option == "citation") { citation(); abort = true; calledHelp = true;}
else if(option == "category") { abort = true; calledHelp = true; }
else {
OptionParser parser(option, setParameters());
map<string,string> parameters = parser.getParameters();
ValidParameters validParameter;
sharedfile = validParameter.validFile(parameters, "shared");
if (sharedfile == "not found") {
//if there is a current shared file, use it
sharedfile = current->getSharedFile();
if (sharedfile != "") { m->mothurOut("Using " + sharedfile + " as input file for the shared parameter.\n"); }
else { m->mothurOut("You have no current sharedfile and the shared parameter is required.\n"); abort = true; }
}else if (sharedfile == "not open") { sharedfile = ""; abort = true; }
else { current->setSharedFile(sharedfile); }
if (outputdir == ""){ outputdir += util.hasPath(sharedfile); }
//check for optional parameter and set defaults
// ...at some point should added some additional type checking...
label = validParameter.valid(parameters, "label");
if (label == "not found") { label = ""; }
else {
if(label != "all") { util.splitAtDash(label, labels); allLines = false; }
else { allLines = true; }
}
output = validParameter.valid(parameters, "output"); if(output == "not found"){ output = "lt"; }
if ((output != "lt") && (output != "square") && (output != "column")) { m->mothurOut(output + " is not a valid output form. Options are lt, column and square. I will use lt.\n"); output = "lt"; }
mode = validParameter.valid(parameters, "mode"); if(mode == "not found"){ mode = "average"; }
if ((mode != "average") && (mode != "median")) { m->mothurOut(mode + " is not a valid mode. Options are average and medina. I will use average.\n"); output = "average"; }
groups = validParameter.valid(parameters, "groups");
if (groups == "not found") { groups = ""; }
else {
util.splitAtDash(groups, Groups);
if (Groups.size() != 0) { if (Groups[0]== "all") { Groups.clear(); } }
}
string temp = validParameter.valid(parameters, "processors"); if (temp == "not found"){ temp = current->getProcessors(); }
processors = current->setProcessors(temp);
calc = validParameter.valid(parameters, "calc");
if (calc == "not found") { calc = "jclass-thetayc"; }
else {
if (calc == "default") { calc = "jclass-thetayc"; }
}
util.splitAtDash(calc, Estimators);
if (util.inUsersGroups("citation", Estimators)) {
ValidCalculators validCalc; validCalc.printCitations(Estimators);
//remove citation from list of calcs
for (int i = 0; i < Estimators.size(); i++) { if (Estimators[i] == "citation") { Estimators.erase(Estimators.begin()+i); break; } }
}
temp = validParameter.valid(parameters, "iters"); if (temp == "not found") { temp = "1000"; }
util.mothurConvert(temp, iters);
temp = validParameter.valid(parameters, "subsample"); if (temp == "not found") { temp = "F"; }
if (util.isNumeric1(temp)) { util.mothurConvert(temp, subsampleSize); subsample = true; }
else {
if (util.isTrue(temp)) { subsample = true; subsampleSize = -1; } //we will set it to smallest group later
else { subsample = false; }
}
if (subsample == false) { iters = 1; }
temp = validParameter.valid(parameters, "withreplacement"); if (temp == "not found"){ temp = "f"; }
withReplacement = util.isTrue(temp);
}
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "DistSharedCommand");
exit(1);
}
}
//**********************************************************************************************************************
DistSharedCommand::~DistSharedCommand(){}
//**********************************************************************************************************************
int DistSharedCommand::execute(){
try {
if (abort) { if (calledHelp) { return 0; } return 2; }
time_t start = time(nullptr);
InputData input(sharedfile, "sharedfile", Groups);
set<string> processedLabels;
set<string> userLabels = labels;
string lastLabel = "";
SharedRAbundVectors* lookup = util.getNextShared(input, allLines, userLabels, processedLabels, lastLabel);
Groups = lookup->getNamesGroups();
if (lookup->size() < 2) { m->mothurOut("[ERROR]: You have not provided enough valid groups. I cannot run the command.\n"); delete lookup; return 0;}
if (subsample) {
if (subsampleSize == -1) { //user has not set size, set size = smallest samples size
subsampleSize = lookup->getNumSeqsSmallestGroup();
m->mothurOut("\nSetting sample size to " + toString(subsampleSize) + ".\n\n");
}else {
lookup->removeGroups(subsampleSize);
Groups = lookup->getNamesGroups();
}
if (lookup->size() < 2) { m->mothurOut("[ERROR]: You have not provided enough valid groups. I cannot run the command.\n"); m->setControl_pressed(true); return 0; }
}
numGroups = lookup->size();
if (m->getControl_pressed()) { delete lookup; return 0; }
while (lookup != nullptr) {
if (m->getControl_pressed()) { delete lookup; break; }
createProcesses(lookup); delete lookup;
lookup = util.getNextShared(input, allLines, userLabels, processedLabels, lastLabel);
}
if (m->getControl_pressed()) { outputTypes.clear(); for (int i = 0; i < outputNames.size(); i++) { util.mothurRemove(outputNames[i]); } return 0; }
//set phylip file as new current phylipfile
string currentName = "";
itTypes = outputTypes.find("phylip");
if (itTypes != outputTypes.end()) {
if ((itTypes->second).size() != 0) { currentName = (itTypes->second)[0]; current->setPhylipFile(currentName); }
}
m->mothurOut("\nIt took " + toString(time(nullptr) - start) + " seconds to run dist.shared.\n");
m->mothurOut("\nOutput File Names: \n");
for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i] +"\n"); } m->mothurOutEndLine();
return 0;
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "execute");
exit(1);
}
}
/***********************************************************/
void DistSharedCommand::printDists(ostream& out, vector< vector<double> >& simMatrix, vector<string> groupNames) {
try {
out.setf(ios::fixed, ios::floatfield); out.setf(ios::showpoint);
if (output == "lt") {
out << simMatrix.size() << endl;
for (int b = 0; b < simMatrix.size(); b++) {
out << groupNames[b];
for (int n = 0; n < b; n++) {
out << '\t' << simMatrix[b][n];
}
out << endl;
}
}else if (output == "column") {
for (int b = 0; b < simMatrix.size(); b++) {
for (int n = 0; n < b; n++) {
out << groupNames[b] << '\t' << groupNames[n] << '\t' << simMatrix[b][n] << endl;
}
}
}else{
out << simMatrix.size() << endl;
for (int b = 0; b < simMatrix.size(); b++) {
out << groupNames[b];
for (int n = 0; n < simMatrix[b].size(); n++) {
out << '\t' << simMatrix[b][n];
}
out << endl;
}
}
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "printSims");
exit(1);
}
}
/**************************************************************************************************/
int driver(vector<SharedRAbundVector*>& thisLookup, vector< vector<seqDist> >& calcDists, vector<Calculator*> matrixCalculators, MothurOut* m) {
try {
vector<SharedRAbundVector*> subset;
for (int k = 0; k < thisLookup.size(); k++) { // pass cdd each set of groups to compare
for (int l = 0; l < k; l++) {
if (k != l) { //we dont need to similarity of a groups to itself
subset.clear(); //clear out old pair of sharedrabunds
//add new pair of sharedrabunds
subset.push_back(thisLookup[k]); subset.push_back(thisLookup[l]);
for(int i=0;i<matrixCalculators.size();i++) {
//if this calc needs all groups to calculate the pair load all groups
if (matrixCalculators[i]->getNeedsAll()) {
//load subset with rest of lookup for those calcs that need everyone to calc for a pair
for (int w = 0; w < thisLookup.size(); w++) {
if ((w != k) && (w != l)) { subset.push_back(thisLookup[w]); }
}
}
vector<double> tempdata = matrixCalculators[i]->getValues(subset); //saves the calculator outputs
if (m->getControl_pressed()) { return 1; }
seqDist temp(l, k, tempdata[0]);
calcDists[i].push_back(temp);
}
}
}
}
return 0;
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "driver");
exit(1);
}
}
/***********************************************************/
int process(distSharedData* params){
try {
vector<Calculator*> matrixCalculators;
ValidCalculators validCalculator;
for (int i=0; i<params->Estimators.size(); i++) {
if (validCalculator.isValidCalculator("matrix", params->Estimators[i]) ) {
if (params->Estimators[i] == "sharedsobs") {
matrixCalculators.push_back(new SharedSobsCS());
}else if (params->Estimators[i] == "sharedchao") {
matrixCalculators.push_back(new SharedChao1());
}else if (params->Estimators[i] == "sharedace") {
matrixCalculators.push_back(new SharedAce());
}else if (params->Estimators[i] == "jabund") {
matrixCalculators.push_back(new JAbund());
}else if (params->Estimators[i] == "sorabund") {
matrixCalculators.push_back(new SorAbund());
}else if (params->Estimators[i] == "jclass") {
matrixCalculators.push_back(new Jclass());
}else if (params->Estimators[i] == "sorclass") {
matrixCalculators.push_back(new SorClass());
}else if (params->Estimators[i] == "jest") {
matrixCalculators.push_back(new Jest());
}else if (params->Estimators[i] == "sorest") {
matrixCalculators.push_back(new SorEst());
}else if (params->Estimators[i] == "thetayc") {
matrixCalculators.push_back(new ThetaYC());
}else if (params->Estimators[i] == "thetan") {
matrixCalculators.push_back(new ThetaN());
}else if (params->Estimators[i] == "kstest") {
matrixCalculators.push_back(new KSTest());
}else if (params->Estimators[i] == "sharednseqs") {
matrixCalculators.push_back(new SharedNSeqs());
}else if (params->Estimators[i] == "ochiai") {
matrixCalculators.push_back(new Ochiai());
}else if (params->Estimators[i] == "anderberg") {
matrixCalculators.push_back(new Anderberg());
}else if (params->Estimators[i] == "kulczynski") {
matrixCalculators.push_back(new Kulczynski());
}else if (params->Estimators[i] == "kulczynskicody") {
matrixCalculators.push_back(new KulczynskiCody());
}else if (params->Estimators[i] == "lennon") {
matrixCalculators.push_back(new Lennon());
}else if (params->Estimators[i] == "morisitahorn") {
matrixCalculators.push_back(new MorHorn());
}else if (params->Estimators[i] == "braycurtis") {
matrixCalculators.push_back(new BrayCurtis());
}else if (params->Estimators[i] == "whittaker") {
matrixCalculators.push_back(new Whittaker());
}else if (params->Estimators[i] == "odum") {
matrixCalculators.push_back(new Odum());
}else if (params->Estimators[i] == "canberra") {
matrixCalculators.push_back(new Canberra());
}else if (params->Estimators[i] == "structeuclidean") {
matrixCalculators.push_back(new StructEuclidean());
}else if (params->Estimators[i] == "structchord") {
matrixCalculators.push_back(new StructChord());
}else if (params->Estimators[i] == "hellinger") {
matrixCalculators.push_back(new Hellinger());
}else if (params->Estimators[i] == "manhattan") {
matrixCalculators.push_back(new Manhattan());
}else if (params->Estimators[i] == "structpearson") {
matrixCalculators.push_back(new StructPearson());
}else if (params->Estimators[i] == "soergel") {
matrixCalculators.push_back(new Soergel());
}else if (params->Estimators[i] == "spearman") {
matrixCalculators.push_back(new Spearman());
}else if (params->Estimators[i] == "structkulczynski") {
matrixCalculators.push_back(new StructKulczynski());
}else if (params->Estimators[i] == "speciesprofile") {
matrixCalculators.push_back(new SpeciesProfile());
}else if (params->Estimators[i] == "hamming") {
matrixCalculators.push_back(new Hamming());
}else if (params->Estimators[i] == "structchi2") {
matrixCalculators.push_back(new StructChi2());
}else if (params->Estimators[i] == "gower") {
matrixCalculators.push_back(new Gower());
}else if (params->Estimators[i] == "memchi2") {
matrixCalculators.push_back(new MemChi2());
}else if (params->Estimators[i] == "memchord") {
matrixCalculators.push_back(new MemChord());
}else if (params->Estimators[i] == "memeuclidean") {
matrixCalculators.push_back(new MemEuclidean());
}else if (params->Estimators[i] == "mempearson") {
matrixCalculators.push_back(new MemPearson());
}else if (params->Estimators[i] == "jsd") {
matrixCalculators.push_back(new JSD());
}else if (params->Estimators[i] == "rjsd") {
matrixCalculators.push_back(new RJSD());
}
}
}
//if the users entered no valid calculators don't execute command
if (matrixCalculators.size() == 0) { params->m->mothurOut("No valid calculators.\n"); return 0; }
params->Estimators.clear();
for (int i=0; i<matrixCalculators.size(); i++) { params->Estimators.push_back(matrixCalculators[i]->getName()); }
vector< vector<seqDist> > calcDists; calcDists.resize(matrixCalculators.size());
SubSample sample;
for (int thisIter = 0; thisIter < params->numIters; thisIter++) {
SharedRAbundVectors* thisItersLookup = new SharedRAbundVectors(*params->thisLookup);
vector<string> namesOfGroups = thisItersLookup->getNamesGroups();
time_t start = time(nullptr);
if (params->subsample) {
if (params->withReplacement) { sample.getSampleWithReplacement(thisItersLookup, params->subsampleSize); }
else { sample.getSample(thisItersLookup, params->subsampleSize); }
}
if (params->m->getDebug()) { params->m->mothurOut("\nIt took " + toString(time(nullptr) - start) + " seconds to subsample the shared file.\n"); }
//params->m->mothurOut(toString(thisIter) + " It took " + toString(time(nullptr) - start) + " seconds to subsample the shared file.\n");
vector<SharedRAbundVector*> thisItersRabunds = thisItersLookup->getSharedRAbundVectors();
vector<string> thisItersGroupNames = params->thisLookup->getNamesGroups();
start = time(nullptr);
driver(thisItersRabunds, calcDists, matrixCalculators, params->m);
if (params->m->getDebug()) { params->m->mothurOut("\nIt took " + toString(time(nullptr) - start) + " seconds to calc dist for shared file.\n"); }
//params->m->mothurOut(toString(thisIter) + " It took " + toString(time(nullptr) - start) + " seconds to calc dist for shared file.\n");
for (int i = 0; i < thisItersRabunds.size(); i++) { delete thisItersRabunds[i]; }
if (params->subsample){
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;
matrix[column][row] = dist;
}
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"); }
return 0;
}
catch(exception& e) {
params->m->errorOut(e, "DistSharedCommand", "process");
exit(1);
}
}
/***********************************************************/
int DistSharedCommand::createProcesses(SharedRAbundVectors*& thisLookup){
try {
vector<string> groupNames = thisLookup->getNamesGroups();
vector<int> lines;
if (processors > (iters)) { processors = iters; }
//figure out how many sequences you have to process
int numItersPerProcessor = (iters) / processors;
for (int i = 0; i < processors; i++) {
if(i == (processors - 1)){ numItersPerProcessor = (iters) - i * numItersPerProcessor; }
lines.push_back(numItersPerProcessor);
}
//create array of worker threads
vector<std::thread*> workerThreads;
vector<distSharedData*> data;
//Lauch worker threads
for (int i = 0; i < processors-1; i++) {
//make copy of lookup so we don't get access violations
SharedRAbundVectors* newLookup = new SharedRAbundVectors(*thisLookup);
distSharedData* dataBundle = new distSharedData(lines[i+1], false, subsample, subsampleSize, withReplacement, Estimators, newLookup);
data.push_back(dataBundle);
workerThreads.push_back(new std::thread(process, dataBundle));
}
//make copy of lookup so we don't get access violations
SharedRAbundVectors* newLookup = new SharedRAbundVectors(*thisLookup);
distSharedData* dataBundle = new distSharedData(lines[0], true, subsample, subsampleSize, withReplacement, Estimators, newLookup);
process(dataBundle);
delete newLookup;
Estimators.clear(); Estimators = dataBundle->Estimators;
if (!subsample) {
map<string, string> variables;
variables["[filename]"] = outputdir + util.getRootName(util.getSimpleName(sharedfile));
variables["[distance]"] = thisLookup->getLabel();
variables["[tag2]"] = "";
variables["[outputtag]"] = output;
/// fix to print out matrices for each calc - only main does this
for (int i = 0; i < Estimators.size(); i++) {
variables["[calc]"] = Estimators[i];
string distFileName = getOutputFileName("phylip",variables);
outputNames.push_back(distFileName); outputTypes["phylip"].push_back(distFileName);
ofstream outDist; util.openOutputFile(distFileName, outDist);
outDist.setf(ios::fixed, ios::floatfield); outDist.setf(ios::showpoint);
printDists(outDist, dataBundle->matrices[i], groupNames); outDist.close();
}
}
vector< vector< vector<seqDist> > > calcDistsTotals = dataBundle->calcDistsTotals;
for (int i = 0; i < processors-1; i++) {
workerThreads[i]->join();
//get calcDistsTotal info - one entry per iter
for (int j = 0; j < data[i]->calcDistsTotals.size(); j++) { calcDistsTotals.push_back(data[i]->calcDistsTotals[j]); }
delete data[i]->thisLookup;
delete data[i];
delete workerThreads[i];
}
delete dataBundle;
if (subsample) {
//we need to find the average distance and standard deviation for each groups distance
vector< vector<seqDist> > calcAverages = util.getAverages(calcDistsTotals, mode);
//find standard deviation
vector< vector<seqDist> > stdDev = util.getStandardDeviation(calcDistsTotals, calcAverages);
//print results
for (int i = 0; i < Estimators.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 + util.getRootName(util.getSimpleName(sharedfile));
variables["[distance]"] = thisLookup->getLabel();
variables["[outputtag]"] = output;
variables["[tag2]"] = "ave";
variables["[calc]"] = Estimators[i];
string distFileName = getOutputFileName("phylip",variables);
outputNames.push_back(distFileName); outputTypes["phylip"].push_back(distFileName);
//set current phylip file to average distance matrix
current->setPhylipFile(distFileName);
ofstream outAve;
util.openOutputFile(distFileName, outAve);
outAve.setf(ios::fixed, ios::floatfield); outAve.setf(ios::showpoint);
printDists(outAve, matrix, groupNames);
outAve.close();
variables["[tag2]"] = "std";
distFileName = getOutputFileName("phylip",variables);
outputNames.push_back(distFileName); outputTypes["phylip"].push_back(distFileName);
ofstream outSTD;
util.openOutputFile(distFileName, outSTD);
outSTD.setf(ios::fixed, ios::floatfield); outSTD.setf(ios::showpoint);
printDists(outSTD, stdmatrix, thisLookup->getNamesGroups());
outSTD.close();
}
}
return 0;
}
catch(exception& e) {
m->errorOut(e, "DistSharedCommand", "createProcesses");
exit(1);
}
}
/***********************************************************/
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