X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=classifyseqscommand.cpp;h=7f262bf9019de7e26d611e9d8b6c37c9f47e7cc6;hb=5c5c0428f6d548c28a8b903ac80efed4f92d59db;hp=c76b047cbd064a5b7b967ab388109bb4e46cc0cc;hpb=49d2b7459c5027557564b21e9487dadafbbbdc96;p=mothur.git diff --git a/classifyseqscommand.cpp b/classifyseqscommand.cpp index c76b047..7f262bf 100644 --- a/classifyseqscommand.cpp +++ b/classifyseqscommand.cpp @@ -17,11 +17,13 @@ vector ClassifySeqsCommand::setParameters(){ CommandParameter ptaxonomy("taxonomy", "InputTypes", "", "", "none", "none", "none",false,true); parameters.push_back(ptaxonomy); CommandParameter ptemplate("reference", "InputTypes", "", "", "none", "none", "none",false,true); parameters.push_back(ptemplate); CommandParameter pfasta("fasta", "InputTypes", "", "", "none", "none", "none",false,true); parameters.push_back(pfasta); - CommandParameter pname("name", "InputTypes", "", "", "none", "none", "none",false,false); parameters.push_back(pname); - CommandParameter pgroup("group", "InputTypes", "", "", "none", "none", "none",false,false); parameters.push_back(pgroup); - CommandParameter psearch("search", "Multiple", "kmer-blast-suffix-distance", "kmer", "", "", "",false,false); parameters.push_back(psearch); + CommandParameter pname("name", "InputTypes", "", "", "NameCount", "none", "none",false,false); parameters.push_back(pname); + CommandParameter pcount("count", "InputTypes", "", "", "NameCount-CountGroup", "none", "none",false,false); parameters.push_back(pcount); + CommandParameter pgroup("group", "InputTypes", "", "", "CountGroup", "none", "none",false,false); parameters.push_back(pgroup); + + CommandParameter psearch("search", "Multiple", "kmer-blast-suffix-distance-align", "kmer", "", "", "",false,false); parameters.push_back(psearch); CommandParameter pksize("ksize", "Number", "", "8", "", "", "",false,false); parameters.push_back(pksize); - CommandParameter pmethod("method", "Multiple", "bayesian-knn", "bayesian", "", "", "",false,false); parameters.push_back(pmethod); + CommandParameter pmethod("method", "Multiple", "wang-knn-zap", "wang", "", "", "",false,false); parameters.push_back(pmethod); CommandParameter pprocessors("processors", "Number", "", "1", "", "", "",false,false); parameters.push_back(pprocessors); CommandParameter pmatch("match", "Number", "", "1.0", "", "", "",false,false); parameters.push_back(pmatch); CommandParameter pmismatch("mismatch", "Number", "", "-1.0", "", "", "",false,false); parameters.push_back(pmismatch); @@ -32,6 +34,7 @@ vector ClassifySeqsCommand::setParameters(){ CommandParameter pprobs("probs", "Boolean", "", "T", "", "", "",false,false); parameters.push_back(pprobs); CommandParameter piters("iters", "Number", "", "100", "", "", "",false,true); parameters.push_back(piters); CommandParameter psave("save", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(psave); + CommandParameter pshortcuts("shortcuts", "Boolean", "", "T", "", "", "",false,false); parameters.push_back(pshortcuts); CommandParameter pnumwanted("numwanted", "Number", "", "10", "", "", "",false,true); parameters.push_back(pnumwanted); CommandParameter pinputdir("inputdir", "String", "", "", "", "", "",false,false); parameters.push_back(pinputdir); CommandParameter poutputdir("outputdir", "String", "", "", "", "", "",false,false); parameters.push_back(poutputdir); @@ -50,12 +53,13 @@ string ClassifySeqsCommand::getHelpString(){ try { string helpString = ""; helpString += "The classify.seqs command reads a fasta file containing sequences and creates a .taxonomy file and a .tax.summary file.\n"; - helpString += "The classify.seqs command parameters are reference, fasta, name, search, ksize, method, taxonomy, processors, match, mismatch, gapopen, gapextend, numwanted and probs.\n"; + helpString += "The classify.seqs command parameters are reference, fasta, name, group, count, search, ksize, method, taxonomy, processors, match, mismatch, gapopen, gapextend, numwanted and probs.\n"; helpString += "The reference, fasta and taxonomy parameters are required. You may enter multiple fasta files by separating their names with dashes. ie. fasta=abrecovery.fasta-amzon.fasta \n"; - helpString += "The search parameter allows you to specify the method to find most similar template. Your options are: suffix, kmer, blast and distance. The default is kmer.\n"; + helpString += "The search parameter allows you to specify the method to find most similar template. Your options are: suffix, kmer, blast, align and distance. The default is kmer.\n"; helpString += "The name parameter allows you add a names file with your fasta file, if you enter multiple fasta files, you must enter matching names files for them.\n"; helpString += "The group parameter allows you add a group file so you can have the summary totals broken up by group.\n"; - helpString += "The method parameter allows you to specify classification method to use. Your options are: bayesian and knn. The default is bayesian.\n"; + helpString += "The count parameter allows you add a count file so you can have the summary totals broken up by group.\n"; + helpString += "The method parameter allows you to specify classification method to use. Your options are: wang, knn and zap. The default is wang.\n"; helpString += "The ksize parameter allows you to specify the kmer size for finding most similar template to candidate. The default is 8.\n"; helpString += "The processors parameter allows you to specify the number of processors to use. The default is 1.\n"; #ifdef USE_MPI @@ -68,8 +72,8 @@ string ClassifySeqsCommand::getHelpString(){ helpString += "The gapextend parameter allows you to specify the penalty for extending a gap in an alignment. The default is -1.0.\n"; helpString += "The numwanted parameter allows you to specify the number of sequence matches you want with the knn method. The default is 10.\n"; helpString += "The cutoff parameter allows you to specify a bootstrap confidence threshold for your taxonomy. The default is 0.\n"; - helpString += "The probs parameter shuts off the bootstrapping results for the bayesian method. The default is true, meaning you want the bootstrapping to be shown.\n"; - helpString += "The iters parameter allows you to specify how many iterations to do when calculating the bootstrap confidence score for your taxonomy with the bayesian method. The default is 100.\n"; + helpString += "The probs parameter shuts off the bootstrapping results for the wang and zap method. The default is true, meaning you want the bootstrapping to be shown.\n"; + helpString += "The iters parameter allows you to specify how many iterations to do when calculating the bootstrap confidence score for your taxonomy with the wang method. The default is 100.\n"; //helpString += "The flip parameter allows you shut off mothur's The default is T.\n"; helpString += "The classify.seqs command should be in the following format: \n"; helpString += "classify.seqs(reference=yourTemplateFile, fasta=yourFastaFile, method=yourClassificationMethod, search=yourSearchmethod, ksize=yourKmerSize, taxonomy=yourTaxonomyFile, processors=yourProcessors) \n"; @@ -127,7 +131,7 @@ ClassifySeqsCommand::ClassifySeqsCommand(){ ClassifySeqsCommand::ClassifySeqsCommand(string option) { try { abort = false; calledHelp = false; - rdb = ReferenceDB::getInstance(); + rdb = ReferenceDB::getInstance(); hasName = false; hasCount=false; //allow user to run help if(option == "help") { help(); abort = true; calledHelp = true; } @@ -185,6 +189,14 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option) { //if the user has not given a path then, add inputdir. else leave path alone. if (path == "") { parameters["group"] = 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; } + } } fastaFileName = validParameter.validFile(parameters, "fasta", false); @@ -333,11 +345,90 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option) { } } } - + + if (namefileNames.size() != 0) { hasName = true; } + if (namefile != "") { if (namefileNames.size() != fastaFileNames.size()) { abort = true; m->mothurOut("If you provide a name file, you must have one for each fasta file."); m->mothurOutEndLine(); } } + //check for required parameters + countfile = validParameter.validFile(parameters, "count", false); + if (countfile == "not found") { + countfile = ""; + }else { + m->splitAtDash(countfile, countfileNames); + + //go through files and make sure they are good, if not, then disregard them + for (int i = 0; i < countfileNames.size(); i++) { + + bool ignore = false; + if (countfileNames[i] == "current") { + countfileNames[i] = m->getCountTableFile(); + if (countfileNames[i] != "") { m->mothurOut("Using " + countfileNames[i] + " as input file for the count parameter where you had given current."); m->mothurOutEndLine(); } + else { + m->mothurOut("You have no current count file, ignoring current."); m->mothurOutEndLine(); ignore=true; + //erase from file list + countfileNames.erase(countfileNames.begin()+i); + i--; + } + } + + if (!ignore) { + + if (inputDir != "") { + string path = m->hasPath(countfileNames[i]); + //if the user has not given a path then, add inputdir. else leave path alone. + if (path == "") { countfileNames[i] = inputDir + countfileNames[i]; } + } + + int ableToOpen; + ifstream in; + + ableToOpen = m->openInputFile(countfileNames[i], in, "noerror"); + + //if you can't open it, try default location + if (ableToOpen == 1) { + if (m->getDefaultPath() != "") { //default path is set + string tryPath = m->getDefaultPath() + m->getSimpleName(countfileNames[i]); + m->mothurOut("Unable to open " + countfileNames[i] + ". Trying default " + tryPath); m->mothurOutEndLine(); + ifstream in2; + ableToOpen = m->openInputFile(tryPath, in2, "noerror"); + in2.close(); + countfileNames[i] = tryPath; + } + } + + if (ableToOpen == 1) { + if (m->getOutputDir() != "") { //default path is set + string tryPath = m->getOutputDir() + m->getSimpleName(countfileNames[i]); + m->mothurOut("Unable to open " + countfileNames[i] + ". Trying output directory " + tryPath); m->mothurOutEndLine(); + ifstream in2; + ableToOpen = m->openInputFile(tryPath, in2, "noerror"); + in2.close(); + countfileNames[i] = tryPath; + } + } + + in.close(); + + if (ableToOpen == 1) { + m->mothurOut("Unable to open " + countfileNames[i] + ". It will be disregarded."); m->mothurOutEndLine(); + //erase from file list + countfileNames.erase(countfileNames.begin()+i); + i--; + }else { + m->setCountTableFile(countfileNames[i]); + } + } + } + } + + if (countfileNames.size() != 0) { hasCount = true; if (countfileNames.size() != fastaFileNames.size()) {m->mothurOut("If you provide a count file, you must have one for each fasta file."); m->mothurOutEndLine(); } } + + //make sure there is at least one valid file left + if (hasName && hasCount) { m->mothurOut("[ERROR]: You must enter ONLY ONE of the following: count or name."); m->mothurOutEndLine(); abort = true; } + groupfile = validParameter.validFile(parameters, "group", false); if (groupfile == "not found") { groupfile = ""; } else { @@ -393,6 +484,7 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option) { if (groupfile != "") { if (groupfileNames.size() != fastaFileNames.size()) { abort = true; m->mothurOut("If you provide a group file, you must have one for each fasta file."); m->mothurOutEndLine(); } + if (hasCount) { m->mothurOut("[ERROR]: You must enter ONLY ONE of the following: count or group."); m->mothurOutEndLine(); abort = true; } }else { for (int i = 0; i < fastaFileNames.size(); i++) { groupfileNames.push_back(""); } } @@ -400,9 +492,6 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option) { //check for optional parameter and set defaults // ...at some point should added some additional type checking... string temp; - temp = validParameter.validFile(parameters, "ksize", false); if (temp == "not found"){ temp = "8"; } - m->mothurConvert(temp, kmerSize); - temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = m->getProcessors(); } m->setProcessors(temp); m->mothurConvert(temp, processors); @@ -444,7 +533,13 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option) { search = validParameter.validFile(parameters, "search", false); if (search == "not found"){ search = "kmer"; } - method = validParameter.validFile(parameters, "method", false); if (method == "not found"){ method = "bayesian"; } + method = validParameter.validFile(parameters, "method", false); if (method == "not found"){ method = "wang"; } + + temp = validParameter.validFile(parameters, "ksize", false); if (temp == "not found"){ + temp = "8"; + if (method == "zap") { temp = "7"; } + } + m->mothurConvert(temp, kmerSize); temp = validParameter.validFile(parameters, "match", false); if (temp == "not found"){ temp = "1.0"; } m->mothurConvert(temp, match); @@ -466,6 +561,9 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option) { temp = validParameter.validFile(parameters, "probs", false); if (temp == "not found"){ temp = "true"; } probs = m->isTrue(temp); + + temp = validParameter.validFile(parameters, "shortcuts", false); if (temp == "not found"){ temp = "true"; } + writeShortcuts = m->isTrue(temp); //temp = validParameter.validFile(parameters, "flip", false); if (temp == "not found"){ temp = "T"; } //flip = m->isTrue(temp); @@ -475,16 +573,23 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option) { m->mothurConvert(temp, iters); - if ((method == "bayesian") && (search != "kmer")) { - m->mothurOut("The bayesian method requires the kmer search." + search + "will be disregarded." ); m->mothurOutEndLine(); + if ((method == "wang") && (search != "kmer")) { + m->mothurOut("The wang method requires the kmer search. " + search + " will be disregarded, and kmer will be used." ); m->mothurOutEndLine(); + search = "kmer"; + } + + if ((method == "zap") && ((search != "kmer") && (search != "align"))) { + m->mothurOut("The zap method requires the kmer or align search. " + search + " will be disregarded, and kmer will be used." ); m->mothurOutEndLine(); search = "kmer"; } if (!abort) { - if (namefileNames.size() == 0){ - if (fastaFileNames.size() != 0) { - vector files; files.push_back(fastaFileNames[fastaFileNames.size()-1]); - parser.getNameFile(files); + if (!hasCount) { + if (namefileNames.size() == 0){ + if (fastaFileNames.size() != 0) { + vector files; files.push_back(fastaFileNames[fastaFileNames.size()-1]); + parser.getNameFile(files); + } } } } @@ -508,12 +613,18 @@ int ClassifySeqsCommand::execute(){ try { if (abort == true) { if (calledHelp) { return 0; } return 2; } - if(method == "bayesian"){ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters, rand(), flip); } + string outputMethodTag = method + "."; + if(method == "wang"){ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters, rand(), flip, writeShortcuts); } else if(method == "knn"){ classify = new Knn(taxonomyFileName, templateFileName, search, kmerSize, gapOpen, gapExtend, match, misMatch, numWanted, rand()); } + else if(method == "zap"){ + outputMethodTag = search + "_" + outputMethodTag; + if (search == "kmer") { classify = new KmerTree(templateFileName, taxonomyFileName, kmerSize, cutoff); } + else { classify = new AlignTree(templateFileName, taxonomyFileName, cutoff); } + } else { - m->mothurOut(search + " is not a valid method option. I will run the command using bayesian."); + m->mothurOut(search + " is not a valid method option. I will run the command using wang."); m->mothurOutEndLine(); - classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters, rand(), flip); + classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters, rand(), flip, writeShortcuts); } if (m->control_pressed) { delete classify; return 0; } @@ -522,7 +633,7 @@ int ClassifySeqsCommand::execute(){ m->mothurOut("Classifying sequences from " + fastaFileNames[s] + " ..." ); m->mothurOutEndLine(); - string baseTName = taxonomyFileName; + string baseTName = m->getSimpleName(taxonomyFileName); if (taxonomyFileName == "saved") {baseTName = rdb->getSavedTaxonomy(); } //set rippedTaxName to @@ -536,10 +647,10 @@ int ClassifySeqsCommand::execute(){ if (RippedTaxName != "") { RippedTaxName += "."; } if (outputDir == "") { outputDir += m->hasPath(fastaFileNames[s]); } - string newTaxonomyFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + getOutputFileNameTag("taxonomy"); - string newaccnosFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + getOutputFileNameTag("accnos"); + string newTaxonomyFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + outputMethodTag + getOutputFileNameTag("taxonomy"); + string newaccnosFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + outputMethodTag +getOutputFileNameTag("accnos"); string tempTaxonomyFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + "taxonomy.temp"; - string taxSummary = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + getOutputFileNameTag("taxsummary"); + string taxSummary = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + outputMethodTag + getOutputFileNameTag("taxsummary"); if ((method == "knn") && (search == "distance")) { string DistName = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + getOutputFileNameTag("matchdist"); @@ -547,7 +658,6 @@ int ClassifySeqsCommand::execute(){ } outputNames.push_back(newTaxonomyFile); outputTypes["taxonomy"].push_back(newTaxonomyFile); - outputNames.push_back(newaccnosFile); outputTypes["accnos"].push_back(newaccnosFile); outputNames.push_back(taxSummary); outputTypes["taxsummary"].push_back(taxSummary); int start = time(NULL); @@ -671,7 +781,9 @@ int ClassifySeqsCommand::execute(){ } #endif - if (!m->isBlank(newaccnosFile)) { m->mothurOutEndLine(); m->mothurOut("[WARNING]: mothur suspects some of your sequences may be reversed, please check " + newaccnosFile + " for the list of the sequences."); m->mothurOutEndLine(); } + if (!m->isBlank(newaccnosFile)) { m->mothurOutEndLine(); m->mothurOut("[WARNING]: mothur suspects some of your sequences may be reversed, please check " + newaccnosFile + " for the list of the sequences."); m->mothurOutEndLine(); + outputNames.push_back(newaccnosFile); outputTypes["accnos"].push_back(newaccnosFile); + }else { m->mothurRemove(newaccnosFile); } m->mothurOutEndLine(); m->mothurOut("It took " + toString(time(NULL) - start) + " secs to classify " + toString(numFastaSeqs) + " sequences."); m->mothurOutEndLine(); m->mothurOutEndLine(); @@ -694,46 +806,58 @@ int ClassifySeqsCommand::execute(){ } #endif - string group = ""; - if (groupfile != "") { group = groupfileNames[s]; } - - PhyloSummary taxaSum(baseTName, group); - - if (m->control_pressed) { outputTypes.clear(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } delete classify; return 0; } - - if (namefile == "") { taxaSum.summarize(tempTaxonomyFile); } - else { - ifstream in; - m->openInputFile(tempTaxonomyFile, in); - - //read in users taxonomy file and add sequences to tree - string name, taxon; - - while(!in.eof()){ - in >> name >> taxon; m->gobble(in); - - itNames = nameMap.find(name); - - if (itNames == nameMap.end()) { - m->mothurOut(name + " is not in your name file please correct."); m->mothurOutEndLine(); exit(1); - }else{ - for (int i = 0; i < itNames->second.size(); i++) { - taxaSum.addSeqToTree(itNames->second[i], taxon); //add it as many times as there are identical seqs - } - itNames->second.clear(); - nameMap.erase(itNames->first); - } - } - in.close(); - } + string group = ""; + GroupMap* groupMap = NULL; + CountTable* ct = NULL; + PhyloSummary* taxaSum; + if (hasCount) { + ct = new CountTable(); + ct->readTable(countfileNames[s]); + taxaSum = new PhyloSummary(taxonomyFileName, ct); + taxaSum->summarize(tempTaxonomyFile); + }else { + if (groupfile != "") { group = groupfileNames[s]; groupMap = new GroupMap(group); groupMap->readMap(); } + + taxaSum = new PhyloSummary(taxonomyFileName, groupMap); + + if (m->control_pressed) { outputTypes.clear(); if (ct != NULL) { delete ct; } if (groupMap != NULL) { delete groupMap; } delete taxaSum; for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } delete classify; return 0; } + + if (namefile == "") { taxaSum->summarize(tempTaxonomyFile); } + else { + ifstream in; + m->openInputFile(tempTaxonomyFile, in); + + //read in users taxonomy file and add sequences to tree + string name, taxon; + + while(!in.eof()){ + if (m->control_pressed) { outputTypes.clear(); if (ct != NULL) { delete ct; } if (groupMap != NULL) { delete groupMap; } delete taxaSum; for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } delete classify; return 0; } + + in >> name >> taxon; m->gobble(in); + + itNames = nameMap.find(name); + + if (itNames == nameMap.end()) { + m->mothurOut(name + " is not in your name file please correct."); m->mothurOutEndLine(); exit(1); + }else{ + for (int i = 0; i < itNames->second.size(); i++) { + taxaSum->addSeqToTree(itNames->second[i], taxon); //add it as many times as there are identical seqs + } + itNames->second.clear(); + nameMap.erase(itNames->first); + } + } + in.close(); + } + } m->mothurRemove(tempTaxonomyFile); - if (m->control_pressed) { outputTypes.clear(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } delete classify; return 0; } + if (m->control_pressed) { outputTypes.clear(); if (ct != NULL) { delete ct; } if (groupMap != NULL) { delete groupMap; } for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } delete classify; return 0; } //print summary file ofstream outTaxTree; m->openOutputFile(taxSummary, outTaxTree); - taxaSum.print(outTaxTree); + taxaSum->print(outTaxTree); outTaxTree.close(); //output taxonomy with the unclassified bins added @@ -745,12 +869,12 @@ int ClassifySeqsCommand::execute(){ m->openOutputFile(unclass, outTax); //get maxLevel from phylotree so you know how many 'unclassified's to add - int maxLevel = taxaSum.getMaxLevel(); + int maxLevel = taxaSum->getMaxLevel(); //read taxfile - this reading and rewriting is done to preserve the confidence scores. string name, taxon; while (!inTax.eof()) { - if (m->control_pressed) { outputTypes.clear(); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } m->mothurRemove(unclass); delete classify; return 0; } + if (m->control_pressed) { outputTypes.clear(); if (ct != NULL) { delete ct; } if (groupMap != NULL) { delete groupMap; } delete taxaSum; for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } m->mothurRemove(unclass); delete classify; return 0; } inTax >> name >> taxon; m->gobble(inTax); @@ -761,6 +885,8 @@ int ClassifySeqsCommand::execute(){ inTax.close(); outTax.close(); + if (ct != NULL) { delete ct; } + if (groupMap != NULL) { delete groupMap; } delete taxaSum; m->mothurRemove(newTaxonomyFile); rename(unclass.c_str(), newTaxonomyFile.c_str()); @@ -770,12 +896,12 @@ int ClassifySeqsCommand::execute(){ #ifdef USE_MPI } #endif - - m->mothurOutEndLine(); - m->mothurOut("Output File Names: "); m->mothurOutEndLine(); - for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); } - m->mothurOutEndLine(); } + + m->mothurOutEndLine(); + m->mothurOut("Output File Names: "); m->mothurOutEndLine(); + for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); } + m->mothurOutEndLine(); //set taxonomy file as new current taxonomyfile string current = ""; @@ -897,7 +1023,7 @@ int ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile, string extension = ""; if (i != 0) { extension = toString(i) + ".temp"; processIDS.push_back(i); } - classifyData* tempclass = new classifyData((accnos + extension), probs, method, templateFileName, taxonomyFileName, (taxFileName + extension), (tempTaxFile + extension), filename, search, kmerSize, iters, numWanted, m, lines[i]->start, lines[i]->end, match, misMatch, gapOpen, gapExtend, cutoff, i, flip); + classifyData* tempclass = new classifyData((accnos + extension), probs, method, templateFileName, taxonomyFileName, (taxFileName + extension), (tempTaxFile + extension), filename, search, kmerSize, iters, numWanted, m, lines[i]->start, lines[i]->end, match, misMatch, gapOpen, gapExtend, cutoff, i, flip, writeShortcuts); pDataArray.push_back(tempclass); //MySeqSumThreadFunction is in header. It must be global or static to work with the threads.