2 * classifyseqscommand.cpp
5 * Created by westcott on 11/2/09.
6 * Copyright 2009 Schloss Lab. All rights reserved.
10 #include "classifyseqscommand.h"
11 #include "sequence.hpp"
13 #include "phylotree.h"
16 //**********************************************************************************************************************
18 ClassifySeqsCommand::ClassifySeqsCommand(string option) {
22 //allow user to run help
23 if(option == "help") { help(); abort = true; }
27 //valid paramters for this command
28 string AlignArray[] = {"template","fasta","name","search","ksize","method","processors","taxonomy","match","mismatch","gapopen","gapextend","numwanted","cutoff","probs","iters", "outputdir","inputdir"};
29 vector<string> myArray (AlignArray, AlignArray+(sizeof(AlignArray)/sizeof(string)));
31 OptionParser parser(option);
32 map<string, string> parameters = parser.getParameters();
34 ValidParameters validParameter;
35 map<string, string>::iterator it;
37 //check to make sure all parameters are valid for command
38 for (it = parameters.begin(); it != parameters.end(); it++) {
39 if (validParameter.isValidParameter(it->first, myArray, it->second) != true) { abort = true; }
42 //if the user changes the output directory command factory will send this info to us in the output parameter
43 outputDir = validParameter.validFile(parameters, "outputdir", false); if (outputDir == "not found"){ outputDir = ""; }
45 //if the user changes the input directory command factory will send this info to us in the output parameter
46 string inputDir = validParameter.validFile(parameters, "inputdir", false);
47 if (inputDir == "not found"){ inputDir = ""; }
50 it = parameters.find("template");
51 //user has given a template file
52 if(it != parameters.end()){
53 path = hasPath(it->second);
54 //if the user has not given a path then, add inputdir. else leave path alone.
55 if (path == "") { parameters["template"] = inputDir + it->second; }
58 it = parameters.find("taxonomy");
59 //user has given a template file
60 if(it != parameters.end()){
61 path = hasPath(it->second);
62 //if the user has not given a path then, add inputdir. else leave path alone.
63 if (path == "") { parameters["taxonomy"] = inputDir + it->second; }
67 //check for required parameters
68 templateFileName = validParameter.validFile(parameters, "template", true);
69 if (templateFileName == "not found") {
70 m->mothurOut("template is a required parameter for the classify.seqs command.");
71 m->mothurOutEndLine();
74 else if (templateFileName == "not open") { abort = true; }
76 fastaFileName = validParameter.validFile(parameters, "fasta", false);
77 if (fastaFileName == "not found") { m->mothurOut("fasta is a required parameter for the classify.seqs command."); m->mothurOutEndLine(); abort = true; }
79 splitAtDash(fastaFileName, fastaFileNames);
81 //go through files and make sure they are good, if not, then disregard them
82 for (int i = 0; i < fastaFileNames.size(); i++) {
84 string path = hasPath(fastaFileNames[i]);
85 //if the user has not given a path then, add inputdir. else leave path alone.
86 if (path == "") { fastaFileNames[i] = inputDir + fastaFileNames[i]; }
93 MPI_Comm_size(MPI_COMM_WORLD, &processors); //set processors to the number of mpi processes running
94 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
100 ableToOpen = openInputFile(fastaFileNames[i], in);
104 for (int j = 1; j < processors; j++) {
105 MPI_Send(&ableToOpen, 1, MPI_INT, j, 2001, MPI_COMM_WORLD);
109 MPI_Recv(&ableToOpen, 1, MPI_INT, 0, 2001, MPI_COMM_WORLD, &status);
114 if (ableToOpen == 1) {
115 m->mothurOut(fastaFileNames[i] + " will be disregarded."); m->mothurOutEndLine();
116 //erase from file list
117 fastaFileNames.erase(fastaFileNames.begin()+i);
123 //make sure there is at least one valid file left
124 if (fastaFileNames.size() == 0) { m->mothurOut("no valid files."); m->mothurOutEndLine(); abort = true; }
128 taxonomyFileName = validParameter.validFile(parameters, "taxonomy", true);
129 if (taxonomyFileName == "not found") {
130 m->mothurOut("taxonomy is a required parameter for the classify.seqs command.");
131 m->mothurOutEndLine();
134 else if (taxonomyFileName == "not open") { abort = true; }
137 namefile = validParameter.validFile(parameters, "name", false);
138 if (namefile == "not found") { namefile = ""; }
141 splitAtDash(namefile, namefileNames);
143 //go through files and make sure they are good, if not, then disregard them
144 for (int i = 0; i < namefileNames.size(); i++) {
145 if (inputDir != "") {
146 string path = hasPath(namefileNames[i]);
147 //if the user has not given a path then, add inputdir. else leave path alone.
148 if (path == "") { namefileNames[i] = inputDir + namefileNames[i]; }
154 MPI_Comm_size(MPI_COMM_WORLD, &processors); //set processors to the number of mpi processes running
155 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
161 ableToOpen = openInputFile(namefileNames[i], in);
165 for (int j = 1; j < processors; j++) {
166 MPI_Send(&ableToOpen, 1, MPI_INT, j, 2001, MPI_COMM_WORLD);
170 MPI_Recv(&ableToOpen, 1, MPI_INT, 0, 2001, MPI_COMM_WORLD, &status);
174 if (ableToOpen == 1) { m->mothurOut("Unable to match name file with fasta file."); m->mothurOutEndLine(); abort = true; }
179 if (namefile != "") {
180 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(); }
183 //check for optional parameter and set defaults
184 // ...at some point should added some additional type checking...
186 temp = validParameter.validFile(parameters, "ksize", false); if (temp == "not found"){ temp = "8"; }
187 convert(temp, kmerSize);
189 temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = "1"; }
190 convert(temp, processors);
192 search = validParameter.validFile(parameters, "search", false); if (search == "not found"){ search = "kmer"; }
194 method = validParameter.validFile(parameters, "method", false); if (method == "not found"){ method = "bayesian"; }
196 temp = validParameter.validFile(parameters, "match", false); if (temp == "not found"){ temp = "1.0"; }
197 convert(temp, match);
199 temp = validParameter.validFile(parameters, "mismatch", false); if (temp == "not found"){ temp = "-1.0"; }
200 convert(temp, misMatch);
202 temp = validParameter.validFile(parameters, "gapopen", false); if (temp == "not found"){ temp = "-2.0"; }
203 convert(temp, gapOpen);
205 temp = validParameter.validFile(parameters, "gapextend", false); if (temp == "not found"){ temp = "-1.0"; }
206 convert(temp, gapExtend);
208 temp = validParameter.validFile(parameters, "numwanted", false); if (temp == "not found"){ temp = "10"; }
209 convert(temp, numWanted);
211 temp = validParameter.validFile(parameters, "cutoff", false); if (temp == "not found"){ temp = "0"; }
212 convert(temp, cutoff);
214 temp = validParameter.validFile(parameters, "probs", false); if (temp == "not found"){ temp = "true"; }
215 probs = isTrue(temp);
217 temp = validParameter.validFile(parameters, "iters", false); if (temp == "not found") { temp = "100"; }
218 convert(temp, iters);
222 if ((method == "bayesian") && (search != "kmer")) {
223 m->mothurOut("The bayesian method requires the kmer search." + search + "will be disregarded." ); m->mothurOutEndLine();
229 catch(exception& e) {
230 m->errorOut(e, "ClassifySeqsCommand", "ClassifySeqsCommand");
235 //**********************************************************************************************************************
237 ClassifySeqsCommand::~ClassifySeqsCommand(){
239 if (abort == false) {
240 for (int i = 0; i < lines.size(); i++) { delete lines[i]; } lines.clear();
244 //**********************************************************************************************************************
246 void ClassifySeqsCommand::help(){
248 m->mothurOut("The classify.seqs command reads a fasta file containing sequences and creates a .taxonomy file and a .tax.summary file.\n");
249 m->mothurOut("The classify.seqs command parameters are template, fasta, name, search, ksize, method, taxonomy, processors, match, mismatch, gapopen, gapextend, numwanted and probs.\n");
250 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");
251 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");
252 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");
253 m->mothurOut("The method parameter allows you to specify classification method to use. Your options are: bayesian and knn. The default is bayesian.\n");
254 m->mothurOut("The ksize parameter allows you to specify the kmer size for finding most similar template to candidate. The default is 8.\n");
255 m->mothurOut("The processors parameter allows you to specify the number of processors to use. The default is 1.\n");
257 m->mothurOut("When using MPI, the processors parameter is set to the number of MPI processes running. \n");
259 m->mothurOut("The match parameter allows you to specify the bonus for having the same base. The default is 1.0.\n");
260 m->mothurOut("The mistmatch parameter allows you to specify the penalty for having different bases. The default is -1.0.\n");
261 m->mothurOut("The gapopen parameter allows you to specify the penalty for opening a gap in an alignment. The default is -2.0.\n");
262 m->mothurOut("The gapextend parameter allows you to specify the penalty for extending a gap in an alignment. The default is -1.0.\n");
263 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");
264 m->mothurOut("The cutoff parameter allows you to specify a bootstrap confidence threshold for your taxonomy. The default is 0.\n");
265 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");
266 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");
267 m->mothurOut("The classify.seqs command should be in the following format: \n");
268 m->mothurOut("classify.seqs(template=yourTemplateFile, fasta=yourFastaFile, method=yourClassificationMethod, search=yourSearchmethod, ksize=yourKmerSize, taxonomy=yourTaxonomyFile, processors=yourProcessors) \n");
269 m->mothurOut("Example classify.seqs(fasta=amazon.fasta, template=core.filtered, method=knn, search=gotoh, ksize=8, processors=2)\n");
270 m->mothurOut("The .taxonomy file consists of 2 columns: 1 = your sequence name, 2 = the taxonomy for your sequence. \n");
271 m->mothurOut("The .tax.summary is a summary of the different taxonomies represented in your fasta file. \n");
272 m->mothurOut("Note: No spaces between parameter labels (i.e. fasta), '=' and parameters (i.e.yourFastaFile).\n\n");
274 catch(exception& e) {
275 m->errorOut(e, "ClassifySeqsCommand", "help");
281 //**********************************************************************************************************************
283 int ClassifySeqsCommand::execute(){
285 if (abort == true) { return 0; }
287 if(method == "bayesian"){ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters); }
288 else if(method == "knn"){ classify = new Knn(taxonomyFileName, templateFileName, search, kmerSize, gapOpen, gapExtend, match, misMatch, numWanted); }
290 m->mothurOut(search + " is not a valid method option. I will run the command using bayesian.");
291 m->mothurOutEndLine();
292 classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters);
295 if (m->control_pressed) { delete classify; return 0; }
297 vector<string> outputNames;
299 for (int s = 0; s < fastaFileNames.size(); s++) {
301 m->mothurOut("Classifying sequences from " + fastaFileNames[s] + " ..." ); m->mothurOutEndLine();
303 if (outputDir == "") { outputDir += hasPath(fastaFileNames[s]); }
304 string newTaxonomyFile = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + getRootName(getSimpleName(taxonomyFileName)) + "taxonomy";
305 string tempTaxonomyFile = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + "taxonomy.temp";
306 string taxSummary = outputDir + getRootName(getSimpleName(fastaFileNames[s])) + getRootName(getSimpleName(taxonomyFileName)) + "tax.summary";
308 outputNames.push_back(newTaxonomyFile);
309 outputNames.push_back(taxSummary);
311 int start = time(NULL);
312 int numFastaSeqs = 0;
313 for (int i = 0; i < lines.size(); i++) { delete lines[i]; } lines.clear();
316 int pid, end, numSeqsPerProcessor;
321 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
322 MPI_Comm_size(MPI_COMM_WORLD, &processors);
325 MPI_File outMPINewTax;
326 MPI_File outMPITempTax;
328 int outMode=MPI_MODE_CREATE|MPI_MODE_WRONLY;
329 int inMode=MPI_MODE_RDONLY;
331 //char* outNewTax = new char[newTaxonomyFile.length()];
332 //memcpy(outNewTax, newTaxonomyFile.c_str(), newTaxonomyFile.length());
334 char outNewTax[1024];
335 strcpy(outNewTax, newTaxonomyFile.c_str());
337 //char* outTempTax = new char[tempTaxonomyFile.length()];
338 //memcpy(outTempTax, tempTaxonomyFile.c_str(), tempTaxonomyFile.length());
340 char outTempTax[1024];
341 strcpy(outTempTax, tempTaxonomyFile.c_str());
343 //char* inFileName = new char[fastaFileNames[s].length()];
344 //memcpy(inFileName, fastaFileNames[s].c_str(), fastaFileNames[s].length());
346 char inFileName[1024];
347 strcpy(inFileName, fastaFileNames[s].c_str());
349 MPI_File_open(MPI_COMM_WORLD, inFileName, inMode, MPI_INFO_NULL, &inMPI); //comm, filename, mode, info, filepointer
350 MPI_File_open(MPI_COMM_WORLD, outNewTax, outMode, MPI_INFO_NULL, &outMPINewTax);
351 MPI_File_open(MPI_COMM_WORLD, outTempTax, outMode, MPI_INFO_NULL, &outMPITempTax);
357 if (m->control_pressed) { MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); delete classify; return 0; }
359 if(namefile != "") { MPIReadNamesFile(namefileNames[s]); }
361 if (pid == 0) { //you are the root process
363 MPIPos = setFilePosFasta(fastaFileNames[s], numFastaSeqs); //fills MPIPos, returns numSeqs
365 //send file positions to all processes
366 MPI_Bcast(&numFastaSeqs, 1, MPI_INT, 0, MPI_COMM_WORLD); //send numSeqs
367 MPI_Bcast(&MPIPos[0], (numFastaSeqs+1), MPI_LONG, 0, MPI_COMM_WORLD); //send file pos
369 //figure out how many sequences you have to align
370 numSeqsPerProcessor = numFastaSeqs / processors;
371 if(pid == (processors - 1)){ numSeqsPerProcessor = numFastaSeqs - pid * numSeqsPerProcessor; }
372 int startIndex = pid * numSeqsPerProcessor;
375 driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, MPIPos);
377 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; }
379 for (int i = 1; i < processors; i++) {
381 MPI_Recv(&done, 1, MPI_INT, i, tag, MPI_COMM_WORLD, &status);
383 }else{ //you are a child process
384 MPI_Bcast(&numFastaSeqs, 1, MPI_INT, 0, MPI_COMM_WORLD); //get numSeqs
385 MPIPos.resize(numFastaSeqs+1);
386 MPI_Bcast(&MPIPos[0], (numFastaSeqs+1), MPI_LONG, 0, MPI_COMM_WORLD); //get file positions
388 //figure out how many sequences you have to align
389 numSeqsPerProcessor = numFastaSeqs / processors;
390 if(pid == (processors - 1)){ numSeqsPerProcessor = numFastaSeqs - pid * numSeqsPerProcessor; }
391 int startIndex = pid * numSeqsPerProcessor;
394 driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, MPIPos);
396 if (m->control_pressed) { MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); delete classify; return 0; }
399 MPI_Send(&done, 1, MPI_INT, 0, tag, MPI_COMM_WORLD);
403 MPI_File_close(&inMPI);
404 MPI_File_close(&outMPINewTax);
405 MPI_File_close(&outMPITempTax);
410 nameMap.clear(); //remove old names
413 openInputFile(namefileNames[s], inNames);
415 string firstCol, secondCol;
416 while(!inNames.eof()) {
417 inNames >> firstCol >> secondCol; gobble(inNames);
418 nameMap[firstCol] = getNumNames(secondCol); //ex. seq1 seq1,seq3,seq5 -> seq1 = 3.
423 #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
426 openInputFile(fastaFileNames[s], inFASTA);
427 numFastaSeqs=count(istreambuf_iterator<char>(inFASTA),istreambuf_iterator<char>(), '>');
430 lines.push_back(new linePair(0, numFastaSeqs));
432 driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
435 vector<int> positions;
436 processIDS.resize(0);
439 openInputFile(fastaFileNames[s], inFASTA);
442 while(!inFASTA.eof()){
443 input = getline(inFASTA);
444 if (input.length() != 0) {
445 if(input[0] == '>'){ int pos = inFASTA.tellg(); positions.push_back(pos - input.length() - 1); }
450 numFastaSeqs = positions.size();
452 int numSeqsPerProcessor = numFastaSeqs / processors;
454 for (int i = 0; i < processors; i++) {
455 int startPos = positions[ i * numSeqsPerProcessor ];
456 if(i == processors - 1){
457 numSeqsPerProcessor = numFastaSeqs - i * numSeqsPerProcessor;
459 lines.push_back(new linePair(startPos, numSeqsPerProcessor));
461 createProcesses(newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
463 rename((newTaxonomyFile + toString(processIDS[0]) + ".temp").c_str(), newTaxonomyFile.c_str());
464 rename((tempTaxonomyFile + toString(processIDS[0]) + ".temp").c_str(), tempTaxonomyFile.c_str());
466 for(int i=1;i<processors;i++){
467 appendTaxFiles((newTaxonomyFile + toString(processIDS[i]) + ".temp"), newTaxonomyFile);
468 appendTaxFiles((tempTaxonomyFile + toString(processIDS[i]) + ".temp"), tempTaxonomyFile);
469 remove((newTaxonomyFile + toString(processIDS[i]) + ".temp").c_str());
470 remove((tempTaxonomyFile + toString(processIDS[i]) + ".temp").c_str());
476 openInputFile(fastaFileNames[s], inFASTA);
477 numFastaSeqs=count(istreambuf_iterator<char>(inFASTA),istreambuf_iterator<char>(), '>');
480 lines.push_back(new linePair(0, numFastaSeqs));
482 driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
487 if (pid == 0) { //this part does not need to be paralellized
490 //make taxonomy tree from new taxonomy file
491 PhyloTree taxaBrowser;
493 if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } delete classify; return 0; }
496 openInputFile(tempTaxonomyFile, in);
498 //read in users taxonomy file and add sequences to tree
501 in >> name >> taxon; gobble(in);
503 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; }
505 if (namefile != "") {
506 itNames = nameMap.find(name);
508 if (itNames == nameMap.end()) {
509 m->mothurOut(name + " is not in your name file please correct."); m->mothurOutEndLine(); exit(1);
511 for (int i = 0; i < itNames->second; i++) {
512 taxaBrowser.addSeqToTree(name+toString(i), taxon); //add it as many times as there are identical seqs
515 }else { taxaBrowser.addSeqToTree(name, taxon); } //add it once
519 taxaBrowser.assignHeirarchyIDs(0);
521 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; }
523 taxaBrowser.binUnclassified();
525 remove(tempTaxonomyFile.c_str());
527 if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } delete classify; return 0; }
532 openOutputFile(taxSummary, outTaxTree);
533 taxaBrowser.print(outTaxTree);
536 //output taxonomy with the unclassified bins added
538 openInputFile(newTaxonomyFile, inTax);
541 string unclass = newTaxonomyFile + ".unclass.temp";
542 openOutputFile(unclass, outTax);
544 //get maxLevel from phylotree so you know how many 'unclassified's to add
545 int maxLevel = taxaBrowser.getMaxLevel();
547 //read taxfile - this reading and rewriting is done to preserve the confidence scores.
548 while (!inTax.eof()) {
549 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; }
551 inTax >> name >> taxon; gobble(inTax);
553 string newTax = addUnclassifieds(taxon, maxLevel);
555 outTax << name << '\t' << newTax << endl;
560 remove(newTaxonomyFile.c_str());
561 rename(unclass.c_str(), newTaxonomyFile.c_str());
567 m->mothurOutEndLine();
568 m->mothurOut("Output File Names: "); m->mothurOutEndLine();
569 for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); }
570 m->mothurOutEndLine();
573 m->mothurOutEndLine();
574 m->mothurOut("It took " + toString(time(NULL) - start) + " secs to classify " + toString(numFastaSeqs) + " sequences."); m->mothurOutEndLine(); m->mothurOutEndLine();
580 catch(exception& e) {
581 m->errorOut(e, "ClassifySeqsCommand", "execute");
586 /**************************************************************************************************/
587 string ClassifySeqsCommand::addUnclassifieds(string tax, int maxlevel) {
589 string newTax, taxon;
592 //keep what you have counting the levels
593 while (tax.find_first_of(';') != -1) {
595 taxon = tax.substr(0,tax.find_first_of(';'))+';';
596 tax = tax.substr(tax.find_first_of(';')+1, tax.length());
601 //add "unclassified" until you reach maxLevel
602 while (level < maxlevel) {
603 newTax += "unclassified;";
609 catch(exception& e) {
610 m->errorOut(e, "ClassifySeqsCommand", "addUnclassifieds");
615 /**************************************************************************************************/
617 void ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile, string filename) {
619 #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
621 // processIDS.resize(0);
623 //loop through and create all the processes you want
624 while (process != processors) {
628 processIDS.push_back(pid); //create map from line number to pid so you can append files in correct order later
631 driver(lines[process], taxFileName + toString(getpid()) + ".temp", tempTaxFile + toString(getpid()) + ".temp", filename);
633 }else { m->mothurOut("unable to spawn the necessary processes."); m->mothurOutEndLine(); exit(0); }
636 //force parent to wait until all the processes are done
637 for (int i=0;i<processors;i++) {
638 int temp = processIDS[i];
643 catch(exception& e) {
644 m->errorOut(e, "ClassifySeqsCommand", "createProcesses");
648 /**************************************************************************************************/
650 void ClassifySeqsCommand::appendTaxFiles(string temp, string filename) {
655 openOutputFileAppend(filename, output);
656 openInputFile(temp, input);
658 while(char c = input.get()){
659 if(input.eof()) { break; }
660 else { output << c; }
666 catch(exception& e) {
667 m->errorOut(e, "ClassifySeqsCommand", "appendTaxFiles");
672 //**********************************************************************************************************************
674 int ClassifySeqsCommand::driver(linePair* line, string taxFName, string tempTFName, string filename){
677 openOutputFile(taxFName, outTax);
679 ofstream outTaxSimple;
680 openOutputFile(tempTFName, outTaxSimple);
683 openInputFile(filename, inFASTA);
685 inFASTA.seekg(line->start);
689 for(int i=0;i<line->numSeqs;i++){
690 if (m->control_pressed) { return 0; }
692 Sequence* candidateSeq = new Sequence(inFASTA);
694 if (candidateSeq->getName() != "") {
695 taxonomy = classify->getTaxonomy(candidateSeq);
697 if (m->control_pressed) { delete candidateSeq; return 0; }
699 if (taxonomy != "bad seq") {
700 //output confidence scores or not
702 outTax << candidateSeq->getName() << '\t' << taxonomy << endl;
704 outTax << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
707 outTaxSimple << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
712 if((i+1) % 100 == 0){
713 m->mothurOut("Classifying sequence " + toString(i+1)); m->mothurOutEndLine();
719 outTaxSimple.close();
723 catch(exception& e) {
724 m->errorOut(e, "ClassifySeqsCommand", "driver");
728 //**********************************************************************************************************************
730 int ClassifySeqsCommand::driverMPI(int start, int num, MPI_File& inMPI, MPI_File& newFile, MPI_File& tempFile, vector<long>& MPIPos){
732 MPI_Status statusNew;
733 MPI_Status statusTemp;
737 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
742 for(int i=0;i<num;i++){
744 if (m->control_pressed) { return 0; }
747 int length = MPIPos[start+i+1] - MPIPos[start+i];
748 char* buf4 = new char[length];
749 MPI_File_read_at(inMPI, MPIPos[start+i], buf4, length, MPI_CHAR, &status);
751 string tempBuf = buf4;
752 if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
753 istringstream iss (tempBuf,istringstream::in);
756 Sequence* candidateSeq = new Sequence(iss);
758 if (candidateSeq->getName() != "") {
759 taxonomy = classify->getTaxonomy(candidateSeq);
761 if (taxonomy != "bad seq") {
762 //output confidence scores or not
764 outputString = candidateSeq->getName() + "\t" + taxonomy + "\n";
766 outputString = candidateSeq->getName() + "\t" + classify->getSimpleTax() + "\n";
769 int length = outputString.length();
770 char* buf2 = new char[length];
771 memcpy(buf2, outputString.c_str(), length);
773 MPI_File_write_shared(newFile, buf2, length, MPI_CHAR, &statusNew);
776 outputString = candidateSeq->getName() + "\t" + classify->getSimpleTax() + "\n";
777 length = outputString.length();
778 char* buf = new char[length];
779 memcpy(buf, outputString.c_str(), length);
781 MPI_File_write_shared(tempFile, buf, length, MPI_CHAR, &statusTemp);
787 if((i+1) % 100 == 0){ cout << "Classifying sequence " << (i+1) << endl; }
790 if(num % 100 != 0){ cout << "Classifying sequence " << (num) << endl; }
795 catch(exception& e) {
796 m->errorOut(e, "ClassifySeqsCommand", "driverMPI");
801 //**********************************************************************************************************************
802 int ClassifySeqsCommand::MPIReadNamesFile(string nameFilename){
805 nameMap.clear(); //remove old names
811 //char* inFileName = new char[nameFilename.length()];
812 //memcpy(inFileName, nameFilename.c_str(), nameFilename.length());
814 char inFileName[1024];
815 strcpy(inFileName, nameFilename.c_str());
817 MPI_File_open(MPI_COMM_WORLD, inFileName, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI);
818 MPI_File_get_size(inMPI, &size);
821 char* buffer = new char[size];
822 MPI_File_read(inMPI, buffer, size, MPI_CHAR, &status);
824 string tempBuf = buffer;
825 if (tempBuf.length() > size) { tempBuf = tempBuf.substr(0, size); }
826 istringstream iss (tempBuf,istringstream::in);
829 string firstCol, secondCol;
831 iss >> firstCol >> secondCol; gobble(iss);
832 nameMap[firstCol] = getNumNames(secondCol); //ex. seq1 seq1,seq3,seq5 -> seq1 = 3.
835 MPI_File_close(&inMPI);
839 catch(exception& e) {
840 m->errorOut(e, "ClassifySeqsCommand", "MPIReadNamesFile");
845 /**************************************************************************************************/