X-Git-Url: https://git.donarmstrong.com/?p=mothur.git;a=blobdiff_plain;f=unifracweightedcommand.cpp;h=3b0c53b7437111cfe5045663a8c78370274b939e;hp=633cb643a213044e4f7e92c108ad012690deff09;hb=c48d91112209b841444923670dca5454da0e2a4d;hpb=3116a941ad720952df651d84aab8c3a9bd6a7c78 diff --git a/unifracweightedcommand.cpp b/unifracweightedcommand.cpp index 633cb64..3b0c53b 100644 --- a/unifracweightedcommand.cpp +++ b/unifracweightedcommand.cpp @@ -15,19 +15,20 @@ //********************************************************************************************************************** vector UnifracWeightedCommand::setParameters(){ try { - CommandParameter ptree("tree", "InputTypes", "", "", "none", "none", "none",false,true); parameters.push_back(ptree); - CommandParameter pgroup("group", "InputTypes", "", "", "none", "none", "none",false,false); parameters.push_back(pgroup); - CommandParameter pname("name", "InputTypes", "", "", "none", "none", "none",false,false); parameters.push_back(pname); - CommandParameter pgroups("groups", "String", "", "", "", "", "",false,false); parameters.push_back(pgroups); - CommandParameter piters("iters", "Number", "", "1000", "", "", "",false,false); parameters.push_back(piters); - CommandParameter pprocessors("processors", "Number", "", "1", "", "", "",false,false); parameters.push_back(pprocessors); - CommandParameter psubsample("subsample", "String", "", "", "", "", "",false,false); parameters.push_back(psubsample); - CommandParameter pconsensus("consensus", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(pconsensus); - CommandParameter prandom("random", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(prandom); - CommandParameter pdistance("distance", "Multiple", "column-lt-square", "column", "", "", "",false,false); parameters.push_back(pdistance); - CommandParameter proot("root", "Boolean", "F", "", "", "", "",false,false); parameters.push_back(proot); - CommandParameter pinputdir("inputdir", "String", "", "", "", "", "",false,false); parameters.push_back(pinputdir); - CommandParameter poutputdir("outputdir", "String", "", "", "", "", "",false,false); parameters.push_back(poutputdir); + CommandParameter ptree("tree", "InputTypes", "", "", "none", "none", "none","weighted-wsummary",false,true,true); parameters.push_back(ptree); + CommandParameter pname("name", "InputTypes", "", "", "NameCount", "none", "none","",false,false,true); parameters.push_back(pname); + CommandParameter pcount("count", "InputTypes", "", "", "NameCount-CountGroup", "none", "none","",false,false,true); parameters.push_back(pcount); + CommandParameter pgroup("group", "InputTypes", "", "", "CountGroup", "none", "none","",false,false,true); parameters.push_back(pgroup); + CommandParameter pgroups("groups", "String", "", "", "", "", "","",false,false); parameters.push_back(pgroups); + CommandParameter piters("iters", "Number", "", "1000", "", "", "","",false,false); parameters.push_back(piters); + CommandParameter pprocessors("processors", "Number", "", "1", "", "", "","",false,false,true); parameters.push_back(pprocessors); + CommandParameter psubsample("subsample", "String", "", "", "", "", "","",false,false); parameters.push_back(psubsample); + CommandParameter pconsensus("consensus", "Boolean", "", "F", "", "", "","tree",false,false); parameters.push_back(pconsensus); + CommandParameter prandom("random", "Boolean", "", "F", "", "", "","",false,false); parameters.push_back(prandom); + CommandParameter pdistance("distance", "Multiple", "column-lt-square-phylip", "column", "", "", "","phylip-column",false,false); parameters.push_back(pdistance); + CommandParameter proot("root", "Boolean", "F", "", "", "", "","",false,false); parameters.push_back(proot); + CommandParameter pinputdir("inputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(pinputdir); + CommandParameter poutputdir("outputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(poutputdir); vector myArray; for (int i = 0; i < parameters.size(); i++) { myArray.push_back(parameters[i].name); } @@ -42,7 +43,7 @@ vector UnifracWeightedCommand::setParameters(){ string UnifracWeightedCommand::getHelpString(){ try { string helpString = ""; - helpString += "The unifrac.weighted command parameters are tree, group, name, groups, iters, distance, processors, root, subsample, consensus and random. tree parameter is required unless you have valid current tree file.\n"; + helpString += "The unifrac.weighted command parameters are tree, group, name, count, groups, iters, distance, processors, root, subsample, consensus and random. tree parameter is required unless you have valid current tree file.\n"; helpString += "The groups parameter allows you to specify which of the groups in your groupfile you would like analyzed. You must enter at least 2 valid groups.\n"; helpString += "The group names are separated by dashes. The iters parameter allows you to specify how many random trees you would like compared to your tree.\n"; helpString += "The distance parameter allows you to create a distance file from the results. The default is false.\n"; @@ -64,6 +65,24 @@ string UnifracWeightedCommand::getHelpString(){ } } //********************************************************************************************************************** +string UnifracWeightedCommand::getOutputPattern(string type) { + try { + string pattern = ""; + if (type == "weighted") { pattern = "[filename],weighted-[filename],[tag],weighted"; } + else if (type == "wsummary") { pattern = "[filename],wsummary"; } + else if (type == "phylip") { pattern = "[filename],[tag],[tag2],dist"; } + else if (type == "column") { pattern = "[filename],[tag],[tag2],dist"; } + else if (type == "tree") { pattern = "[filename],[tag],[tag2],tre"; } + else { m->mothurOut("[ERROR]: No definition for type " + type + " output pattern.\n"); m->control_pressed = true; } + + return pattern; + } + catch(exception& e) { + m->errorOut(e, "UnifracWeightedCommand", "getOutputPattern"); + exit(1); + } +} +//********************************************************************************************************************** UnifracWeightedCommand::UnifracWeightedCommand(){ try { abort = true; calledHelp = true; @@ -140,6 +159,14 @@ UnifracWeightedCommand::UnifracWeightedCommand(string option) { //if the user has not given a path then, add inputdir. else leave path alone. if (path == "") { parameters["name"] = inputDir + it->second; } } + + it = parameters.find("count"); + //user has given a template file + if(it != parameters.end()){ + path = m->hasPath(it->second); + //if the user has not given a path then, add inputdir. else leave path alone. + if (path == "") { parameters["count"] = inputDir + it->second; } + } } //check for required parameters @@ -162,6 +189,19 @@ UnifracWeightedCommand::UnifracWeightedCommand(string option) { else if (namefile == "not found") { namefile = ""; } else { m->setNameFile(namefile); } + countfile = validParameter.validFile(parameters, "count", true); + if (countfile == "not open") { countfile = ""; abort = true; } + else if (countfile == "not found") { countfile = ""; } + else { m->setCountTableFile(countfile); } + + if ((namefile != "") && (countfile != "")) { + m->mothurOut("[ERROR]: you may only use one of the following: name or count."); m->mothurOutEndLine(); abort = true; + } + + if ((groupfile != "") && (countfile != "")) { + m->mothurOut("[ERROR]: you may only use one of the following: group or count."); m->mothurOutEndLine(); abort=true; + } + outputDir = validParameter.validFile(parameters, "outputdir", false); if (outputDir == "not found"){ outputDir = m->hasPath(treefile); } @@ -180,6 +220,7 @@ UnifracWeightedCommand::UnifracWeightedCommand(string option) { string temp = validParameter.validFile(parameters, "distance", false); if (temp == "not found") { phylip = false; outputForm = ""; } else{ + if (temp=="phylip") { temp = "lt"; } if ((temp == "lt") || (temp == "column") || (temp == "square")) { phylip = true; outputForm = temp; } else { m->mothurOut("Options for distance are: lt, square, or column. Using lt."); m->mothurOutEndLine(); phylip = true; outputForm = "lt"; } } @@ -208,14 +249,22 @@ UnifracWeightedCommand::UnifracWeightedCommand(string option) { consensus = m->isTrue(temp); if (subsample && random) { m->mothurOut("[ERROR]: random must be false, if subsample=t.\n"); abort=true; } - if (subsample && (groupfile == "")) { m->mothurOut("[ERROR]: if subsample=t, a group file must be provided.\n"); abort=true; } + if (countfile == "") { if (subsample && (groupfile == "")) { m->mothurOut("[ERROR]: if subsample=t, a group file must be provided.\n"); abort=true; } } + else { + CountTable testCt; + if ((!testCt.testGroups(countfile)) && (subsample)) { + m->mothurOut("[ERROR]: if subsample=t, a count file with group info must be provided.\n"); abort=true; + } + } if (subsample && (!phylip)) { phylip=true; outputForm = "lt"; } if (consensus && (!subsample)) { m->mothurOut("[ERROR]: you cannot use consensus without subsample.\n"); abort=true; } - if (namefile == "") { - vector files; files.push_back(treefile); - parser.getNameFile(files); - } + if (countfile=="") { + if (namefile == "") { + vector files; files.push_back(treefile); + parser.getNameFile(files); + } + } } @@ -233,26 +282,30 @@ int UnifracWeightedCommand::execute() { m->setTreeFile(treefile); - TreeReader* reader = new TreeReader(treefile, groupfile, namefile); + TreeReader* reader; + if (countfile == "") { reader = new TreeReader(treefile, groupfile, namefile); } + else { reader = new TreeReader(treefile, countfile); } T = reader->getTrees(); - tmap = T[0]->getTreeMap(); - map nameMap = reader->getNames(); + ct = T[0]->getCountTable(); delete reader; - - if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; } return 0; } - - sumFile = outputDir + m->getSimpleName(treefile) + ".wsummary"; + + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } return 0; } + + map variables; + variables["[filename]"] = outputDir + m->getSimpleName(treefile); + sumFile = getOutputFileName("wsummary",variables); m->openOutputFile(sumFile, outSum); outputNames.push_back(sumFile); outputTypes["wsummary"].push_back(sumFile); SharedUtil util; string s; //to make work with setgroups Groups = m->getGroups(); - vector nameGroups = tmap->getNamesOfGroups(); - util.setGroups(Groups, nameGroups, s, numGroups, "weighted"); //sets the groups the user wants to analyze + vector nameGroups = ct->getNamesOfGroups(); + if (nameGroups.size() < 2) { m->mothurOut("[ERROR]: You cannot run unifrac.weighted with less than 2 groups, aborting.\n"); delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } return 0; } + util.setGroups(Groups, nameGroups, s, numGroups, "weighted"); //sets the groups the user wants to analyze m->setGroups(Groups); - if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; } return 0; } + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } return 0; } Weighted weighted(includeRoot); @@ -263,10 +316,9 @@ int UnifracWeightedCommand::execute() { //user has not set size, set size = smallest samples size if (subsampleSize == -1) { vector temp; temp.push_back(Groups[0]); - subsampleSize = (tmap->getNamesSeqs(temp)).size(); //num in first group + subsampleSize = ct->getGroupCount(Groups[0]); //num in first group for (int i = 1; i < Groups.size(); i++) { - temp.clear(); temp.push_back(Groups[i]); - int thisSize = (tmap->getNamesSeqs(temp)).size(); + int thisSize = ct->getGroupCount(Groups[i]); if (thisSize < subsampleSize) { subsampleSize = thisSize; } } m->mothurOut("\nSetting subsample size to " + toString(subsampleSize) + ".\n\n"); @@ -274,12 +326,10 @@ int UnifracWeightedCommand::execute() { vector newGroups = Groups; Groups.clear(); for (int i = 0; i < newGroups.size(); i++) { - vector thisGroup; thisGroup.push_back(newGroups[i]); - vector thisGroupsSeqs = tmap->getNamesSeqs(thisGroup); - int thisSize = thisGroupsSeqs.size(); + int thisSize = ct->getGroupCount(newGroups[i]); if (thisSize >= subsampleSize) { Groups.push_back(newGroups[i]); } - else { m->mothurOut("You have selected a size that is larger than "+newGroups[i]+" number of sequences, removing "+newGroups[i]+".\n"); } + else { m->mothurOut("You have selected a size that is larger than "+newGroups[i]+" number of sequences, removing "+newGroups[i]+".\n"); } } m->setGroups(Groups); } @@ -295,7 +345,7 @@ int UnifracWeightedCommand::execute() { //get weighted scores for users trees for (int i = 0; i < T.size(); i++) { - if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } counter = 0; rScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC... @@ -305,13 +355,15 @@ int UnifracWeightedCommand::execute() { vector randomData; randomData.resize(numComp,0); //weighted score info for random trees. data[0] = weightedscore AB, data[1] = weightedscore AC... if (random) { - output = new ColumnFile(outputDir + m->getSimpleName(treefile) + toString(i+1) + ".weighted", itersString); - outputNames.push_back(outputDir + m->getSimpleName(treefile) + toString(i+1) + ".weighted"); - outputTypes["weighted"].push_back(outputDir + m->getSimpleName(treefile) + toString(i+1) + ".weighted"); + variables["[filename]"] = outputDir + m->getSimpleName(treefile); + variables["[tag]"] = toString(i+1); + string wFileName = getOutputFileName("weighted", variables); + output = new ColumnFile(wFileName, itersString); + outputNames.push_back(wFileName); outputTypes["wweighted"].push_back(wFileName); } userData = weighted.getValues(T[i], processors, outputDir); //userData[0] = weightedscore - if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; } if (random) { delete output; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } if (random) { delete output; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } //save users score for (int s=0; s > calcDistsTotals; //each iter, each groupCombos dists. this will be used to make .dist files for (int thisIter = 0; thisIter < subsampleIters; thisIter++) { //subsampleIters=0, if subsample=f. - if (m->control_pressed) { break; } //copy to preserve old one - would do this in subsample but memory cleanup becomes messy. - TreeMap* newTmap = new TreeMap(); - newTmap->getCopy(*tmap); + CountTable* newCt = new CountTable(); + + int sampleTime = 0; + if (m->debug) { sampleTime = time(NULL); } + //uses method of setting groups to doNotIncludeMe SubSample sample; - Tree* subSampleTree = sample.getSample(T[i], newTmap, nameMap, subsampleSize); - + Tree* subSampleTree = sample.getSample(T[i], ct, newCt, subsampleSize); + + if (m->debug) { m->mothurOut("[DEBUG]: iter " + toString(thisIter) + " took " + toString(time(NULL) - sampleTime) + " seconds to sample tree.\n"); } + //call new weighted function vector iterData; iterData.resize(numComp,0); Weighted thisWeighted(includeRoot); @@ -349,20 +405,20 @@ int UnifracWeightedCommand::execute() { //save data to make ave dist, std dist calcDistsTotals.push_back(iterData); - delete newTmap; + delete newCt; delete subSampleTree; - if((thisIter+1) % 100 == 0){ m->mothurOut(toString(thisIter+1)); m->mothurOutEndLine(); } + if((thisIter+1) % 100 == 0){ m->mothurOutJustToScreen(toString(thisIter+1)+"\n"); } } - if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; } if (random) { delete output; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } if (random) { delete output; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } if (subsample) { getAverageSTDMatrices(calcDistsTotals, i); } if (consensus) { getConsensusTrees(calcDistsTotals, i); } } - if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } if (phylip) { createPhylipFile(); } @@ -370,7 +426,7 @@ int UnifracWeightedCommand::execute() { //clear out users groups m->clearGroups(); - delete tmap; + delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } @@ -409,40 +465,28 @@ int UnifracWeightedCommand::getAverageSTDMatrices(vector< vector >& dist //we need to find the average distance and standard deviation for each groups distance //finds sum - vector averages; averages.resize(numComp, 0); - for (int thisIter = 0; thisIter < subsampleIters; thisIter++) { - for (int i = 0; i < dists[thisIter].size(); i++) { - averages[i] += dists[thisIter][i]; - } - } - - //finds average. - for (int i = 0; i < averages.size(); i++) { averages[i] /= (float) subsampleIters; } + vector averages = m->getAverages(dists); //find standard deviation - vector stdDev; stdDev.resize(numComp, 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 j = 0; j < dists[thisIter].size(); j++) { - stdDev[j] += ((dists[thisIter][j] - averages[j]) * (dists[thisIter][j] - averages[j])); - } - } - for (int i = 0; i < stdDev.size(); i++) { - stdDev[i] /= (float) subsampleIters; - stdDev[i] = sqrt(stdDev[i]); - } + vector stdDev = m->getStandardDeviation(dists, averages); //make matrix with scores in it - vector< vector > avedists; avedists.resize(m->getNumGroups()); + vector< vector > avedists; //avedists.resize(m->getNumGroups()); for (int i = 0; i < m->getNumGroups(); i++) { - avedists[i].resize(m->getNumGroups(), 0.0); + vector temp; + for (int j = 0; j < m->getNumGroups(); j++) { temp.push_back(0.0); } + avedists.push_back(temp); } //make matrix with scores in it - vector< vector > stddists; stddists.resize(m->getNumGroups()); + vector< vector > stddists; //stddists.resize(m->getNumGroups()); for (int i = 0; i < m->getNumGroups(); i++) { - stddists[i].resize(m->getNumGroups(), 0.0); + vector temp; + for (int j = 0; j < m->getNumGroups(); j++) { temp.push_back(0.0); } + //stddists[i].resize(m->getNumGroups(), 0.0); + stddists.push_back(temp); } + //flip it so you can print it int count = 0; @@ -456,15 +500,20 @@ int UnifracWeightedCommand::getAverageSTDMatrices(vector< vector >& dist } } - string aveFileName = outputDir + m->getSimpleName(treefile) + toString(treeNum+1) + ".weighted.ave.dist"; - outputNames.push_back(aveFileName); outputTypes["phylip"].push_back(aveFileName); - + map variables; + variables["[filename]"] = outputDir + m->getSimpleName(treefile); + variables["[tag]"] = toString(treeNum+1); + variables["[tag2]"] = "weighted.ave"; + string aveFileName = getOutputFileName("phylip",variables); + if (outputForm != "column") { outputNames.push_back(aveFileName); outputTypes["phylip"].push_back(aveFileName); } + else { outputNames.push_back(aveFileName); outputTypes["column"].push_back(aveFileName); } ofstream out; m->openOutputFile(aveFileName, out); - string stdFileName = outputDir + m->getSimpleName(treefile) + toString(treeNum+1) + ".weighted.std.dist"; - outputNames.push_back(stdFileName); outputTypes["phylip"].push_back(stdFileName); - + variables["[tag2]"] = "weighted.std"; + string stdFileName = getOutputFileName("phylip",variables); + if (outputForm != "column") { outputNames.push_back(stdFileName); outputTypes["phylip"].push_back(stdFileName); } + else { outputNames.push_back(stdFileName); outputTypes["column"].push_back(stdFileName); } ofstream outStd; m->openOutputFile(stdFileName, outStd); @@ -527,9 +576,17 @@ int UnifracWeightedCommand::getConsensusTrees(vector< vector >& dists, i //used in tree constructor m->runParse = false; - //create treemap class from groupmap for tree class to use - TreeMap newTmap; - newTmap.makeSim(m->getGroups()); + ///create treemap class from groupmap for tree class to use + CountTable newCt; + set nameMap; + map groupMap; + set gps; + for (int i = 0; i < m->getGroups().size(); i++) { + nameMap.insert(m->getGroups()[i]); + gps.insert(m->getGroups()[i]); + groupMap[m->getGroups()[i]] = m->getGroups()[i]; + } + newCt.createTable(nameMap, groupMap, gps); //clear old tree names if any m->Treenames.clear(); @@ -537,7 +594,7 @@ int UnifracWeightedCommand::getConsensusTrees(vector< vector >& dists, i //fills globaldatas tree names m->Treenames = m->getGroups(); - vector newTrees = buildTrees(dists, treeNum, newTmap); //also creates .all.tre file containing the trees created + vector newTrees = buildTrees(dists, treeNum, newCt); //also creates .all.tre file containing the trees created if (m->control_pressed) { return 0; } @@ -545,7 +602,11 @@ int UnifracWeightedCommand::getConsensusTrees(vector< vector >& dists, i Tree* conTree = con.getTree(newTrees); //create a new filename - string conFile = outputDir + m->getRootName(m->getSimpleName(treefile)) + toString(treeNum+1) + ".weighted.cons.tre"; + map variables; + variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(treefile)); + variables["[tag]"] = toString(treeNum+1); + variables["[tag2]"] = "weighted.cons"; + string conFile = getOutputFileName("tree",variables); outputNames.push_back(conFile); outputTypes["tree"].push_back(conFile); ofstream outTree; m->openOutputFile(conFile, outTree); @@ -563,13 +624,17 @@ int UnifracWeightedCommand::getConsensusTrees(vector< vector >& dists, i } /**************************************************************************************************/ -vector UnifracWeightedCommand::buildTrees(vector< vector >& dists, int treeNum, TreeMap& mytmap) { +vector UnifracWeightedCommand::buildTrees(vector< vector >& dists, int treeNum, CountTable& myct) { try { vector trees; //create a new filename - string outputFile = outputDir + m->getRootName(m->getSimpleName(treefile)) + toString(treeNum+1) + ".weighted.all.tre"; + map variables; + variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(treefile)); + variables["[tag]"] = toString(treeNum+1); + variables["[tag2]"] = "weighted.all"; + string outputFile = getOutputFileName("tree",variables); outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile); ofstream outAll; @@ -597,9 +662,8 @@ vector UnifracWeightedCommand::buildTrees(vector< vector >& dists } //create tree - Tree* tempTree = new Tree(&mytmap, sims); - map empty; - tempTree->assembleTree(empty); + Tree* tempTree = new Tree(&myct, sims); + tempTree->assembleTree(); trees.push_back(tempTree); @@ -634,39 +698,32 @@ int UnifracWeightedCommand::runRandomCalcs(Tree* thisTree, vector usersS lines.clear(); -#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) - if(processors != 1){ - int numPairs = namesOfGroupCombos.size(); - int numPairsPerProcessor = numPairs / processors; - - for (int i = 0; i < processors; i++) { - int startPos = i * numPairsPerProcessor; - if(i == processors - 1){ - numPairsPerProcessor = numPairs - i * numPairsPerProcessor; - } - lines.push_back(linePair(startPos, numPairsPerProcessor)); - } + //breakdown work between processors + int numPairs = namesOfGroupCombos.size(); + int numPairsPerProcessor = numPairs / processors; + + for (int i = 0; i < processors; i++) { + int startPos = i * numPairsPerProcessor; + if(i == processors - 1){ numPairsPerProcessor = numPairs - i * numPairsPerProcessor; } + lines.push_back(linePair(startPos, numPairsPerProcessor)); } -#endif //get scores for random trees for (int j = 0; j < iters; j++) { - -#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) - if(processors == 1){ - driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); - }else{ +//#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) + //if(processors == 1){ + // driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); + // }else{ createProcesses(thisTree, namesOfGroupCombos, rScores); - } -#else - driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); -#endif + // } +//#else + //driver(thisTree, namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores); +//#endif + - if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; } delete output; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } + if (m->control_pressed) { delete ct; for (int i = 0; i < T.size(); i++) { delete T[i]; } delete output; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } return 0; } - //report progress - // m->mothurOut("Iter: " + toString(j+1)); m->mothurOutEndLine(); } lines.clear(); @@ -702,12 +759,11 @@ int UnifracWeightedCommand::runRandomCalcs(Tree* thisTree, vector usersS int UnifracWeightedCommand::createProcesses(Tree* t, vector< vector > namesOfGroupCombos, vector< vector >& scores) { try { -#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) - int process = 1; + int process = 1; vector processIDS; - EstOutput results; - + +#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix) //loop through and create all the processes you want while (process != processors) { int pid = fork(); @@ -753,9 +809,53 @@ int UnifracWeightedCommand::createProcesses(Tree* t, vector< vector > na in.close(); m->mothurRemove(s); } +#else + //fill in functions + vector pDataArray; + DWORD dwThreadIdArray[processors-1]; + HANDLE hThreadArray[processors-1]; + vector cts; + vector trees; - return 0; -#endif + //Create processor worker threads. + for( int i=1; icopy(ct); + Tree* copyTree = new Tree(copyCount); + copyTree->getCopy(t); + + cts.push_back(copyCount); + trees.push_back(copyTree); + + vector< vector > copyScores = rScores; + + weightedRandomData* tempweighted = new weightedRandomData(m, lines[i].start, lines[i].num, namesOfGroupCombos, copyTree, copyCount, includeRoot, copyScores); + pDataArray.push_back(tempweighted); + processIDS.push_back(i); + + hThreadArray[i-1] = CreateThread(NULL, 0, MyWeightedRandomThreadFunction, pDataArray[i-1], 0, &dwThreadIdArray[i-1]); + } + + driver(t, namesOfGroupCombos, lines[0].start, lines[0].num, scores); + + //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++){ + for (int j = pDataArray[i]->start; j < (pDataArray[i]->start+pDataArray[i]->num); j++) { + scores[j].push_back(pDataArray[i]->scores[j][pDataArray[i]->scores[j].size()-1]); + } + delete cts[i]; + delete trees[i]; + CloseHandle(hThreadArray[i]); + delete pDataArray[i]; + } + + +#endif + + return 0; } catch(exception& e) { m->errorOut(e, "UnifracWeightedCommand", "createProcesses"); @@ -766,7 +866,7 @@ int UnifracWeightedCommand::createProcesses(Tree* t, vector< vector > na /**************************************************************************************************/ int UnifracWeightedCommand::driver(Tree* t, vector< vector > namesOfGroupCombos, int start, int num, vector< vector >& scores) { try { - Tree* randT = new Tree(tmap); + Tree* randT = new Tree(ct); Weighted weighted(includeRoot); @@ -878,14 +978,20 @@ void UnifracWeightedCommand::createPhylipFile() { //for each tree for (int i = 0; i < T.size(); i++) { - string phylipFileName; - if ((outputForm == "lt") || (outputForm == "square")) { - phylipFileName = outputDir + m->getSimpleName(treefile) + toString(i+1) + ".weighted.phylip.dist"; - outputNames.push_back(phylipFileName); outputTypes["phylip"].push_back(phylipFileName); - }else { //column - phylipFileName = outputDir + m->getSimpleName(treefile) + toString(i+1) + ".weighted.column.dist"; - outputNames.push_back(phylipFileName); outputTypes["column"].push_back(phylipFileName); - } + string phylipFileName; + map variables; + variables["[filename]"] = outputDir + m->getSimpleName(treefile); + variables["[tag]"] = toString(i+1); + if ((outputForm == "lt") || (outputForm == "square")) { + variables["[tag2]"] = "weighted.phylip"; + phylipFileName = getOutputFileName("phylip",variables); + outputNames.push_back(phylipFileName); outputTypes["phylip"].push_back(phylipFileName); + }else { //column + variables["[tag2]"] = "weighted.column"; + phylipFileName = getOutputFileName("column",variables); + outputNames.push_back(phylipFileName); outputTypes["column"].push_back(phylipFileName); + } + ofstream out; m->openOutputFile(phylipFileName, out);