X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;ds=sidebyside;f=classifyseqscommand.cpp;h=26df57ffbb56d6ddd0cc3532013c2be65fe5e3f8;hb=e189982e0a9b7352ad57cc38ccee675f128be22e;hp=0d9e797a00c226ba2e2eea219d041fa1143d03fa;hpb=315e38cf393c82be238da5b32574f225a020d25c;p=mothur.git diff --git a/classifyseqscommand.cpp b/classifyseqscommand.cpp index 0d9e797..26df57f 100644 --- a/classifyseqscommand.cpp +++ b/classifyseqscommand.cpp @@ -15,7 +15,7 @@ //********************************************************************************************************************** -ClassifySeqsCommand::ClassifySeqsCommand(string option){ +ClassifySeqsCommand::ClassifySeqsCommand(string option) { try { abort = false; @@ -67,14 +67,14 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option){ //check for required parameters templateFileName = validParameter.validFile(parameters, "template", true); if (templateFileName == "not found") { - mothurOut("template is a required parameter for the classify.seqs command."); - mothurOutEndLine(); + m->mothurOut("template is a required parameter for the classify.seqs command."); + m->mothurOutEndLine(); abort = true; } else if (templateFileName == "not open") { abort = true; } fastaFileName = validParameter.validFile(parameters, "fasta", false); - if (fastaFileName == "not found") { mothurOut("fasta is a required parameter for the classify.seqs command."); mothurOutEndLine(); abort = true; } + if (fastaFileName == "not found") { m->mothurOut("fasta is a required parameter for the classify.seqs command."); m->mothurOutEndLine(); abort = true; } else { splitAtDash(fastaFileName, fastaFileNames); @@ -87,26 +87,48 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option){ } int ableToOpen; + + #ifdef USE_MPI + int pid; + MPI_Comm_size(MPI_COMM_WORLD, &processors); //set processors to the number of mpi processes running + MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are + + if (pid == 0) { + #endif + ifstream in; ableToOpen = openInputFile(fastaFileNames[i], in); + in.close(); + + #ifdef USE_MPI + for (int j = 1; j < processors; j++) { + MPI_Send(&ableToOpen, 1, MPI_INT, j, 2001, MPI_COMM_WORLD); + } + }else{ + MPI_Status status; + MPI_Recv(&ableToOpen, 1, MPI_INT, 0, 2001, MPI_COMM_WORLD, &status); + } + + #endif + if (ableToOpen == 1) { - mothurOut(fastaFileNames[i] + " will be disregarded."); mothurOutEndLine(); + m->mothurOut(fastaFileNames[i] + " will be disregarded."); m->mothurOutEndLine(); //erase from file list fastaFileNames.erase(fastaFileNames.begin()+i); i--; } - in.close(); + } //make sure there is at least one valid file left - if (fastaFileNames.size() == 0) { mothurOut("no valid files."); mothurOutEndLine(); abort = true; } + if (fastaFileNames.size() == 0) { m->mothurOut("no valid files."); m->mothurOutEndLine(); abort = true; } } taxonomyFileName = validParameter.validFile(parameters, "taxonomy", true); if (taxonomyFileName == "not found") { - mothurOut("taxonomy is a required parameter for the classify.seqs command."); - mothurOutEndLine(); + m->mothurOut("taxonomy is a required parameter for the classify.seqs command."); + m->mothurOutEndLine(); abort = true; } else if (taxonomyFileName == "not open") { abort = true; } @@ -125,17 +147,37 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option){ //if the user has not given a path then, add inputdir. else leave path alone. if (path == "") { namefileNames[i] = inputDir + namefileNames[i]; } } - int ableToOpen; + + #ifdef USE_MPI + int pid; + MPI_Comm_size(MPI_COMM_WORLD, &processors); //set processors to the number of mpi processes running + MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are + + if (pid == 0) { + #endif + ifstream in; ableToOpen = openInputFile(namefileNames[i], in); - if (ableToOpen == 1) { mothurOut("Unable to match name file with fasta file."); mothurOutEndLine(); abort = true; } in.close(); + + #ifdef USE_MPI + for (int j = 1; j < processors; j++) { + MPI_Send(&ableToOpen, 1, MPI_INT, j, 2001, MPI_COMM_WORLD); + } + }else{ + MPI_Status status; + MPI_Recv(&ableToOpen, 1, MPI_INT, 0, 2001, MPI_COMM_WORLD, &status); + } + + #endif + if (ableToOpen == 1) { m->mothurOut("Unable to match name file with fasta file."); m->mothurOutEndLine(); abort = true; } + } } if (namefile != "") { - if (namefileNames.size() != fastaFileNames.size()) { abort = true; mothurOut("If you provide a name file, you must have one for each fasta file."); mothurOutEndLine(); } + 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 optional parameter and set defaults @@ -178,14 +220,14 @@ ClassifySeqsCommand::ClassifySeqsCommand(string option){ if ((method == "bayesian") && (search != "kmer")) { - mothurOut("The bayesian method requires the kmer search." + search + "will be disregarded." ); mothurOutEndLine(); + m->mothurOut("The bayesian method requires the kmer search." + search + "will be disregarded." ); m->mothurOutEndLine(); search = "kmer"; } } } catch(exception& e) { - errorOut(e, "ClassifySeqsCommand", "ClassifySeqsCommand"); + m->errorOut(e, "ClassifySeqsCommand", "ClassifySeqsCommand"); exit(1); } } @@ -203,30 +245,34 @@ ClassifySeqsCommand::~ClassifySeqsCommand(){ void ClassifySeqsCommand::help(){ try { - mothurOut("The classify.seqs command reads a fasta file containing sequences and creates a .taxonomy file and a .tax.summary file.\n"); - mothurOut("The classify.seqs command parameters are template, fasta, search, ksize, method, taxonomy, processors, match, mismatch, gapopen, gapextend, numwanted and probs.\n"); - mothurOut("The template, 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"); - mothurOut("The search parameter allows you to specify the method to find most similar template. Your options are: suffix, kmer and blast. The default is kmer.\n"); - mothurOut("The method parameter allows you to specify classification method to use. Your options are: bayesian and knn. The default is bayesian.\n"); - mothurOut("The ksize parameter allows you to specify the kmer size for finding most similar template to candidate. The default is 8.\n"); - mothurOut("The processors parameter allows you to specify the number of processors to use. The default is 1.\n"); - mothurOut("The match parameter allows you to specify the bonus for having the same base. The default is 1.0.\n"); - mothurOut("The mistmatch parameter allows you to specify the penalty for having different bases. The default is -1.0.\n"); - mothurOut("The gapopen parameter allows you to specify the penalty for opening a gap in an alignment. The default is -2.0.\n"); - mothurOut("The gapextend parameter allows you to specify the penalty for extending a gap in an alignment. The default is -1.0.\n"); - mothurOut("The numwanted parameter allows you to specify the number of sequence matches you want with the knn method. The default is 10.\n"); - mothurOut("The cutoff parameter allows you to specify a bootstrap confidence threshold for your taxonomy. The default is 0.\n"); - mothurOut("The probs parameter shut off the bootstrapping results for the bayesian method. The default is true, meaning you want the bootstrapping to be run.\n"); - mothurOut("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"); - mothurOut("The classify.seqs command should be in the following format: \n"); - mothurOut("classify.seqs(template=yourTemplateFile, fasta=yourFastaFile, method=yourClassificationMethod, search=yourSearchmethod, ksize=yourKmerSize, taxonomy=yourTaxonomyFile, processors=yourProcessors) \n"); - mothurOut("Example classify.seqs(fasta=amazon.fasta, template=core.filtered, method=knn, search=gotoh, ksize=8, processors=2)\n"); - mothurOut("The .taxonomy file consists of 2 columns: 1 = your sequence name, 2 = the taxonomy for your sequence. \n"); - mothurOut("The .tax.summary is a summary of the different taxonomies represented in your fasta file. \n"); - mothurOut("Note: No spaces between parameter labels (i.e. fasta), '=' and parameters (i.e.yourFastaFile).\n\n"); + m->mothurOut("The classify.seqs command reads a fasta file containing sequences and creates a .taxonomy file and a .tax.summary file.\n"); + m->mothurOut("The classify.seqs command parameters are template, fasta, name, search, ksize, method, taxonomy, processors, match, mismatch, gapopen, gapextend, numwanted and probs.\n"); + m->mothurOut("The template, 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"); + m->mothurOut("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"); + m->mothurOut("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"); + m->mothurOut("The method parameter allows you to specify classification method to use. Your options are: bayesian and knn. The default is bayesian.\n"); + m->mothurOut("The ksize parameter allows you to specify the kmer size for finding most similar template to candidate. The default is 8.\n"); + m->mothurOut("The processors parameter allows you to specify the number of processors to use. The default is 1.\n"); + #ifdef USE_MPI + m->mothurOut("When using MPI, the processors parameter is set to the number of MPI processes running. \n"); + #endif + m->mothurOut("The match parameter allows you to specify the bonus for having the same base. The default is 1.0.\n"); + m->mothurOut("The mistmatch parameter allows you to specify the penalty for having different bases. The default is -1.0.\n"); + m->mothurOut("The gapopen parameter allows you to specify the penalty for opening a gap in an alignment. The default is -2.0.\n"); + m->mothurOut("The gapextend parameter allows you to specify the penalty for extending a gap in an alignment. The default is -1.0.\n"); + m->mothurOut("The numwanted parameter allows you to specify the number of sequence matches you want with the knn method. The default is 10.\n"); + m->mothurOut("The cutoff parameter allows you to specify a bootstrap confidence threshold for your taxonomy. The default is 0.\n"); + m->mothurOut("The probs parameter shut off the bootstrapping results for the bayesian method. The default is true, meaning you want the bootstrapping to be run.\n"); + m->mothurOut("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"); + m->mothurOut("The classify.seqs command should be in the following format: \n"); + m->mothurOut("classify.seqs(template=yourTemplateFile, fasta=yourFastaFile, method=yourClassificationMethod, search=yourSearchmethod, ksize=yourKmerSize, taxonomy=yourTaxonomyFile, processors=yourProcessors) \n"); + m->mothurOut("Example classify.seqs(fasta=amazon.fasta, template=core.filtered, method=knn, search=gotoh, ksize=8, processors=2)\n"); + m->mothurOut("The .taxonomy file consists of 2 columns: 1 = your sequence name, 2 = the taxonomy for your sequence. \n"); + m->mothurOut("The .tax.summary is a summary of the different taxonomies represented in your fasta file. \n"); + m->mothurOut("Note: No spaces between parameter labels (i.e. fasta), '=' and parameters (i.e.yourFastaFile).\n\n"); } catch(exception& e) { - errorOut(e, "ClassifySeqsCommand", "help"); + m->errorOut(e, "ClassifySeqsCommand", "help"); exit(1); } } @@ -241,14 +287,113 @@ int ClassifySeqsCommand::execute(){ if(method == "bayesian"){ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters); } else if(method == "knn"){ classify = new Knn(taxonomyFileName, templateFileName, search, kmerSize, gapOpen, gapExtend, match, misMatch, numWanted); } else { - mothurOut(search + " is not a valid method option. I will run the command using bayesian."); - mothurOutEndLine(); + m->mothurOut(search + " is not a valid method option. I will run the command using bayesian."); + m->mothurOutEndLine(); classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters); } - + + if (m->control_pressed) { delete classify; return 0; } + + vector outputNames; for (int s = 0; s < fastaFileNames.size(); s++) { + m->mothurOut("Classifying sequences from " + fastaFileNames[s] + " ..." ); m->mothurOutEndLine(); + + if (outputDir == "") { outputDir += hasPath(fastaFileNames[s]); } + string newTaxonomyFile = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + getRootName(getSimpleName(taxonomyFileName)) + "taxonomy"; + string tempTaxonomyFile = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + "taxonomy.temp"; + string taxSummary = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + getRootName(getSimpleName(taxonomyFileName)) + "tax.summary"; + + outputNames.push_back(newTaxonomyFile); + outputNames.push_back(taxSummary); + + int start = time(NULL); + int numFastaSeqs = 0; + for (int i = 0; i < lines.size(); i++) { delete lines[i]; } lines.clear(); + +#ifdef USE_MPI + + int pid, end, numSeqsPerProcessor; + int tag = 2001; + vector MPIPos; + + MPI_Status status; + MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are + MPI_Comm_size(MPI_COMM_WORLD, &processors); + + MPI_File inMPI; + MPI_File outMPINewTax; + MPI_File outMPITempTax; + + int outMode=MPI_MODE_CREATE|MPI_MODE_WRONLY; + int inMode=MPI_MODE_RDONLY; + + char outNewTax[newTaxonomyFile.length()]; + strcpy(outNewTax, newTaxonomyFile.c_str()); + + char outTempTax[tempTaxonomyFile.length()]; + strcpy(outTempTax, tempTaxonomyFile.c_str()); + + char inFileName[fastaFileNames[s].length()]; + strcpy(inFileName, fastaFileNames[s].c_str()); + + MPI_File_open(MPI_COMM_WORLD, inFileName, inMode, MPI_INFO_NULL, &inMPI); //comm, filename, mode, info, filepointer + MPI_File_open(MPI_COMM_WORLD, outNewTax, outMode, MPI_INFO_NULL, &outMPINewTax); + MPI_File_open(MPI_COMM_WORLD, outTempTax, outMode, MPI_INFO_NULL, &outMPITempTax); + + if (m->control_pressed) { MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); delete classify; return 0; } + + if(namefile != "") { MPIReadNamesFile(namefileNames[s]); } + + if (pid == 0) { //you are the root process + + MPIPos = setFilePosFasta(fastaFileNames[s], numFastaSeqs); //fills MPIPos, returns numSeqs + + //send file positions to all processes + MPI_Bcast(&numFastaSeqs, 1, MPI_INT, 0, MPI_COMM_WORLD); //send numSeqs + MPI_Bcast(&MPIPos[0], (numFastaSeqs+1), MPI_LONG, 0, MPI_COMM_WORLD); //send file pos + + //figure out how many sequences you have to align + numSeqsPerProcessor = numFastaSeqs / processors; + if(pid == (processors - 1)){ numSeqsPerProcessor = numFastaSeqs - pid * numSeqsPerProcessor; } + int startIndex = pid * numSeqsPerProcessor; + + //align your part + driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, MPIPos); + + if (m->control_pressed) { MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } delete classify; return 0; } + + for (int i = 1; i < processors; i++) { + int done; + MPI_Recv(&done, 1, MPI_INT, i, tag, MPI_COMM_WORLD, &status); + } + }else{ //you are a child process + MPI_Bcast(&numFastaSeqs, 1, MPI_INT, 0, MPI_COMM_WORLD); //get numSeqs + MPIPos.resize(numFastaSeqs+1); + MPI_Bcast(&MPIPos[0], (numFastaSeqs+1), MPI_LONG, 0, MPI_COMM_WORLD); //get file positions + + //figure out how many sequences you have to align + numSeqsPerProcessor = numFastaSeqs / processors; + if(pid == (processors - 1)){ numSeqsPerProcessor = numFastaSeqs - pid * numSeqsPerProcessor; } + int startIndex = pid * numSeqsPerProcessor; + + //align your part + driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, MPIPos); + + if (m->control_pressed) { MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); delete classify; return 0; } + + int done = 0; + MPI_Send(&done, 1, MPI_INT, 0, tag, MPI_COMM_WORLD); + } + + //close files + MPI_File_close(&inMPI); + MPI_File_close(&outMPINewTax); + MPI_File_close(&outMPITempTax); + +#else + //read namefile if(namefile != "") { nameMap.clear(); //remove old names @@ -263,19 +408,8 @@ int ClassifySeqsCommand::execute(){ } inNames.close(); } - - mothurOut("Classifying sequences from " + fastaFileNames[s] + " ..." ); mothurOutEndLine(); - - if (outputDir == "") { outputDir += hasPath(fastaFileNames[s]); } - string newTaxonomyFile = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + getRootName(getSimpleName(taxonomyFileName)) + "taxonomy"; - string tempTaxonomyFile = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + "taxonomy.temp"; - string taxSummary = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + getRootName(getSimpleName(taxonomyFileName)) + "tax.summary"; - - int start = time(NULL); - int numFastaSeqs = 0; - for (int i = 0; i < lines.size(); i++) { delete lines[i]; } lines.clear(); - -#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) + + #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) if(processors == 1){ ifstream inFASTA; openInputFile(fastaFileNames[s], inFASTA); @@ -326,7 +460,7 @@ int ClassifySeqsCommand::execute(){ } } -#else + #else ifstream inFASTA; openInputFile(fastaFileNames[s], inFASTA); numFastaSeqs=count(istreambuf_iterator(inFASTA),istreambuf_iterator(), '>'); @@ -335,23 +469,36 @@ int ClassifySeqsCommand::execute(){ lines.push_back(new linePair(0, numFastaSeqs)); driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]); -#endif + #endif +#endif + + delete classify; + + #ifdef USE_MPI + if (pid == 0) { //this part does not need to be paralellized + #endif + //make taxonomy tree from new taxonomy file PhyloTree taxaBrowser; - + + if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } delete classify; return 0; } + ifstream in; openInputFile(tempTaxonomyFile, in); //read in users taxonomy file and add sequences to tree string name, taxon; + while(!in.eof()){ in >> name >> taxon; gobble(in); + if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } remove(tempTaxonomyFile.c_str()); delete classify; return 0; } + if (namefile != "") { itNames = nameMap.find(name); if (itNames == nameMap.end()) { - mothurOut(name + " is not in your name file please correct."); mothurOutEndLine(); exit(1); + m->mothurOut(name + " is not in your name file please correct."); m->mothurOutEndLine(); exit(1); }else{ for (int i = 0; i < itNames->second; i++) { taxaBrowser.addSeqToTree(name+toString(i), taxon); //add it as many times as there are identical seqs @@ -362,11 +509,16 @@ int ClassifySeqsCommand::execute(){ in.close(); taxaBrowser.assignHeirarchyIDs(0); + + if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } remove(tempTaxonomyFile.c_str()); delete classify; return 0; } taxaBrowser.binUnclassified(); remove(tempTaxonomyFile.c_str()); + if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } delete classify; return 0; } + + //print summary file ofstream outTaxTree; openOutputFile(taxSummary, outTaxTree); @@ -384,8 +536,10 @@ int ClassifySeqsCommand::execute(){ //get maxLevel from phylotree so you know how many 'unclassified's to add int maxLevel = taxaBrowser.getMaxLevel(); - //read taxfile - this reading and rewriting is done to preserve the confidence sscores. + //read taxfile - this reading and rewriting is done to preserve the confidence scores. while (!inTax.eof()) { + if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } remove(unclass.c_str()); delete classify; return 0; } + inTax >> name >> taxon; gobble(inTax); string newTax = addUnclassifieds(taxon, maxLevel); @@ -398,15 +552,24 @@ int ClassifySeqsCommand::execute(){ remove(newTaxonomyFile.c_str()); rename(unclass.c_str(), newTaxonomyFile.c_str()); - mothurOutEndLine(); - mothurOut("It took " + toString(time(NULL) - start) + " secs to classify " + toString(numFastaSeqs) + " sequences."); mothurOutEndLine(); mothurOutEndLine(); + #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("It took " + toString(time(NULL) - start) + " secs to classify " + toString(numFastaSeqs) + " sequences."); m->mothurOutEndLine(); m->mothurOutEndLine(); } - delete classify; return 0; } catch(exception& e) { - errorOut(e, "ClassifySeqsCommand", "execute"); + m->errorOut(e, "ClassifySeqsCommand", "execute"); exit(1); } } @@ -435,7 +598,7 @@ string ClassifySeqsCommand::addUnclassifieds(string tax, int maxlevel) { return newTax; } catch(exception& e) { - errorOut(e, "ClassifySeqsCommand", "addUnclassifieds"); + m->errorOut(e, "ClassifySeqsCommand", "addUnclassifieds"); exit(1); } } @@ -458,7 +621,7 @@ void ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile }else if (pid == 0){ driver(lines[process], taxFileName + toString(getpid()) + ".temp", tempTaxFile + toString(getpid()) + ".temp", filename); exit(0); - }else { mothurOut("unable to spawn the necessary processes."); mothurOutEndLine(); exit(0); } + }else { m->mothurOut("unable to spawn the necessary processes."); m->mothurOutEndLine(); exit(0); } } //force parent to wait until all the processes are done @@ -469,7 +632,7 @@ void ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile #endif } catch(exception& e) { - errorOut(e, "ClassifySeqsCommand", "createProcesses"); + m->errorOut(e, "ClassifySeqsCommand", "createProcesses"); exit(1); } } @@ -492,7 +655,7 @@ void ClassifySeqsCommand::appendTaxFiles(string temp, string filename) { output.close(); } catch(exception& e) { - errorOut(e, "ClassifySeqsCommand", "appendTaxFiles"); + m->errorOut(e, "ClassifySeqsCommand", "appendTaxFiles"); exit(1); } } @@ -515,28 +678,30 @@ int ClassifySeqsCommand::driver(linePair* line, string taxFName, string tempTFNa string taxonomy; for(int i=0;inumSeqs;i++){ + if (m->control_pressed) { return 0; } Sequence* candidateSeq = new Sequence(inFASTA); - + if (candidateSeq->getName() != "") { taxonomy = classify->getTaxonomy(candidateSeq); + + if (m->control_pressed) { delete candidateSeq; return 0; } - if (taxonomy != "bad seq") { + if ((taxonomy != "bad seq") && (taxonomy != "")) { //output confidence scores or not if (probs) { outTax << candidateSeq->getName() << '\t' << taxonomy << endl; }else{ outTax << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl; - cout << classify->getSimpleTax() << endl; } outTaxSimple << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl; - } + }else{ m->mothurOut("Sequence: " + candidateSeq->getName() + " is bad."); m->mothurOutEndLine(); } } delete candidateSeq; if((i+1) % 100 == 0){ - mothurOut("Classifying sequence " + toString(i+1)); mothurOutEndLine(); + m->mothurOut("Classifying sequence " + toString(i+1)); m->mothurOutEndLine(); } } @@ -547,9 +712,117 @@ int ClassifySeqsCommand::driver(linePair* line, string taxFName, string tempTFNa return 1; } catch(exception& e) { - errorOut(e, "ClassifySeqsCommand", "driver"); + m->errorOut(e, "ClassifySeqsCommand", "driver"); exit(1); } } +//********************************************************************************************************************** +#ifdef USE_MPI +int ClassifySeqsCommand::driverMPI(int start, int num, MPI_File& inMPI, MPI_File& newFile, MPI_File& tempFile, vector& MPIPos){ + try { + MPI_Status statusNew; + MPI_Status statusTemp; + MPI_Status status; + + int pid; + MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are + + string taxonomy; + string outputString; + + for(int i=0;icontrol_pressed) { return 0; } + + //read next sequence + int length = MPIPos[start+i+1] - MPIPos[start+i]; + char buf4[length]; + MPI_File_read_at(inMPI, MPIPos[start+i], buf4, length, MPI_CHAR, &status); + + string tempBuf = buf4; + if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); } + istringstream iss (tempBuf,istringstream::in); + Sequence* candidateSeq = new Sequence(iss); + + if (candidateSeq->getName() != "") { + taxonomy = classify->getTaxonomy(candidateSeq); + + if ((taxonomy != "bad seq") && (taxonomy != "")) { + //output confidence scores or not + if (probs) { + outputString = candidateSeq->getName() + "\t" + taxonomy + "\n"; + }else{ + outputString = candidateSeq->getName() + "\t" + classify->getSimpleTax() + "\n"; + } + + int length = outputString.length(); + char buf2[length]; + strcpy(buf2, outputString.c_str()); + + MPI_File_write_shared(newFile, buf2, length, MPI_CHAR, &statusNew); + + outputString = candidateSeq->getName() + "\t" + classify->getSimpleTax() + "\n"; + length = outputString.length(); + char buf[length]; + strcpy(buf, outputString.c_str()); + + MPI_File_write_shared(tempFile, buf, length, MPI_CHAR, &statusTemp); + }else{ cout << "Sequence: " << candidateSeq->getName() << " is bad." << endl; } + } + delete candidateSeq; + + if((i+1) % 100 == 0){ cout << "Classifying sequence " << (i+1) << endl; } + } + + if(num % 100 != 0){ cout << "Classifying sequence " << (num) << endl; } + + + return 1; + } + catch(exception& e) { + m->errorOut(e, "ClassifySeqsCommand", "driverMPI"); + exit(1); + } +} + +//********************************************************************************************************************** +int ClassifySeqsCommand::MPIReadNamesFile(string nameFilename){ + try { + + nameMap.clear(); //remove old names + + MPI_File inMPI; + MPI_Offset size; + MPI_Status status; + + char inFileName[nameFilename.length()]; + strcpy(inFileName, nameFilename.c_str()); + + MPI_File_open(MPI_COMM_WORLD, inFileName, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI); + MPI_File_get_size(inMPI, &size); + + char buffer[size]; + MPI_File_read(inMPI, buffer, size, MPI_CHAR, &status); + + string tempBuf = buffer; + if (tempBuf.length() > size) { tempBuf = tempBuf.substr(0, size); } + istringstream iss (tempBuf,istringstream::in); + + string firstCol, secondCol; + while(!iss.eof()) { + iss >> firstCol >> secondCol; gobble(iss); + nameMap[firstCol] = getNumNames(secondCol); //ex. seq1 seq1,seq3,seq5 -> seq1 = 3. + } + + MPI_File_close(&inMPI); + + return 1; + } + catch(exception& e) { + m->errorOut(e, "ClassifySeqsCommand", "MPIReadNamesFile"); + exit(1); + } +} +#endif /**************************************************************************************************/