#include "sequence.hpp"
#include "bayesian.h"
#include "phylotree.h"
+#include "phylosummary.h"
#include "knn.h"
//**********************************************************************************************************************
-ClassifySeqsCommand::ClassifySeqsCommand(string option){
+ClassifySeqsCommand::ClassifySeqsCommand(string option) {
try {
abort = false;
else {
//valid paramters for this command
- string AlignArray[] = {"template","fasta","name","search","ksize","method","processors","taxonomy","match","mismatch","gapopen","gapextend","numwanted","cutoff","probs","iters", "outputdir","inputdir"};
+ string AlignArray[] = {"template","fasta","name","group","search","ksize","method","processors","taxonomy","match","mismatch","gapopen","gapextend","numwanted","cutoff","probs","iters", "outputdir","inputdir"};
vector<string> myArray (AlignArray, AlignArray+(sizeof(AlignArray)/sizeof(string)));
OptionParser parser(option);
//if the user has not given a path then, add inputdir. else leave path alone.
if (path == "") { parameters["taxonomy"] = inputDir + it->second; }
}
+
+ it = parameters.find("group");
+ //user has given a template file
+ if(it != parameters.end()){
+ path = hasPath(it->second);
+ //if the user has not given a path then, add inputdir. else leave path alone.
+ if (path == "") { parameters["group"] = inputDir + it->second; }
+ }
}
//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);
}
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; }
//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(); }
+ }
+
+ groupfile = validParameter.validFile(parameters, "group", false);
+ if (groupfile == "not found") { groupfile = ""; }
+ else {
+ splitAtDash(groupfile, groupfileNames);
+
+ //go through files and make sure they are good, if not, then disregard them
+ for (int i = 0; i < groupfileNames.size(); i++) {
+ if (inputDir != "") {
+ string path = hasPath(groupfileNames[i]);
+ //if the user has not given a path then, add inputdir. else leave path alone.
+ if (path == "") { groupfileNames[i] = inputDir + groupfileNames[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(groupfileNames[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) { m->mothurOut("Unable to match group file with fasta file."); m->mothurOutEndLine(); abort = true; }
+
+ }
+ }
+
+ 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(); }
+ }else {
+ for (int i = 0; i < fastaFileNames.size(); i++) { groupfileNames.push_back(""); }
}
//check for optional parameter and set defaults
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);
}
}
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, name, 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, blast and distance. The default is kmer.\n");
- 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");
- 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 group parameter allows you add a group file so you can have the summary totals broken up by group.\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);
}
}
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<string> 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<long> 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 = new char[newTaxonomyFile.length()];
+ //memcpy(outNewTax, newTaxonomyFile.c_str(), newTaxonomyFile.length());
+
+ char outNewTax[1024];
+ strcpy(outNewTax, newTaxonomyFile.c_str());
+
+ //char* outTempTax = new char[tempTaxonomyFile.length()];
+ //memcpy(outTempTax, tempTaxonomyFile.c_str(), tempTaxonomyFile.length());
+
+ char outTempTax[1024];
+ strcpy(outTempTax, tempTaxonomyFile.c_str());
+
+ //char* inFileName = new char[fastaFileNames[s].length()];
+ //memcpy(inFileName, fastaFileNames[s].c_str(), fastaFileNames[s].length());
+
+ char inFileName[1024];
+ 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);
+
+ //delete outNewTax;
+ //delete outTempTax;
+ //delete inFileName;
+
+ 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;
+ int startIndex = pid * numSeqsPerProcessor;
+ if(pid == (processors - 1)){ numSeqsPerProcessor = numFastaSeqs - 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;
+ int startIndex = pid * numSeqsPerProcessor;
+ if(pid == (processors - 1)){ numSeqsPerProcessor = numFastaSeqs - 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
}
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);
}
}
-#else
+ #else
ifstream inFASTA;
openInputFile(fastaFileNames[s], inFASTA);
numFastaSeqs=count(istreambuf_iterator<char>(inFASTA),istreambuf_iterator<char>(), '>');
lines.push_back(new linePair(0, numFastaSeqs));
driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
-#endif
- //make taxonomy tree from new taxonomy file
- PhyloTree taxaBrowser;
-
- 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);
+ #endif
+#endif
+
+ #ifdef USE_MPI
+ if (pid == 0) { //this part does not need to be paralellized
+ #endif
+
+ m->mothurOutEndLine();
+ m->mothurOut("It took " + toString(time(NULL) - start) + " secs to classify " + toString(numFastaSeqs) + " sequences."); m->mothurOutEndLine(); m->mothurOutEndLine();
+ start = time(NULL);
+
+ PhyloSummary taxaSum(taxonomyFileName, groupfileNames[s]);
+
+ if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } delete classify; return 0; }
+
+ if (namefile == "") { taxaSum.summarize(tempTaxonomyFile); }
+ else {
+ ifstream in;
+ openInputFile(tempTaxonomyFile, in);
- if (namefile != "") {
+ //read in users taxonomy file and add sequences to tree
+ string name, taxon;
+ while(!in.eof()){
+ in >> name >> taxon; gobble(in);
+
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
+ taxaSum.addSeqToTree(name, taxon); //add it as many times as there are identical seqs
}
}
- }else { taxaBrowser.addSeqToTree(name, taxon); } //add it once
+ }
+ in.close();
}
- in.close();
-
- taxaBrowser.assignHeirarchyIDs(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);
- taxaBrowser.print(outTaxTree);
+ taxaSum.print(outTaxTree);
outTaxTree.close();
//output taxonomy with the unclassified bins added
openOutputFile(unclass, outTax);
//get maxLevel from phylotree so you know how many 'unclassified's to add
- int maxLevel = taxaBrowser.getMaxLevel();
+ int maxLevel = taxaSum.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.
+ string name, taxon;
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);
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();
+ m->mothurOutEndLine();
+ m->mothurOut("It took " + toString(time(NULL) - start) + " secs to create the summary file for " + toString(numFastaSeqs) + " sequences."); m->mothurOutEndLine(); m->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();
}
delete classify;
return 0;
}
catch(exception& e) {
- errorOut(e, "ClassifySeqsCommand", "execute");
+ m->errorOut(e, "ClassifySeqsCommand", "execute");
exit(1);
}
}
return newTax;
}
catch(exception& e) {
- errorOut(e, "ClassifySeqsCommand", "addUnclassifieds");
+ m->errorOut(e, "ClassifySeqsCommand", "addUnclassifieds");
exit(1);
}
}
}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
#endif
}
catch(exception& e) {
- errorOut(e, "ClassifySeqsCommand", "createProcesses");
+ m->errorOut(e, "ClassifySeqsCommand", "createProcesses");
exit(1);
}
}
output.close();
}
catch(exception& e) {
- errorOut(e, "ClassifySeqsCommand", "appendTaxFiles");
+ m->errorOut(e, "ClassifySeqsCommand", "appendTaxFiles");
exit(1);
}
}
string taxonomy;
for(int i=0;i<line->numSeqs;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") {
//output confidence scores or not
delete candidateSeq;
if((i+1) % 100 == 0){
- mothurOut("Classifying sequence " + toString(i+1)); mothurOutEndLine();
+ m->mothurOut("Classifying sequence " + toString(i+1)); m->mothurOutEndLine();
}
}
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<long>& 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;i<num;i++){
+
+ if (m->control_pressed) { return 0; }
+
+ //read next sequence
+ int length = MPIPos[start+i+1] - MPIPos[start+i];
+ char* buf4 = new char[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);
+ delete buf4;
+
+ Sequence* candidateSeq = new Sequence(iss);
+
+ if (candidateSeq->getName() != "") {
+ taxonomy = classify->getTaxonomy(candidateSeq);
+
+ if (taxonomy != "bad seq") {
+ //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 = new char[length];
+ memcpy(buf2, outputString.c_str(), length);
+
+ MPI_File_write_shared(newFile, buf2, length, MPI_CHAR, &statusNew);
+ delete buf2;
+
+ outputString = candidateSeq->getName() + "\t" + classify->getSimpleTax() + "\n";
+ length = outputString.length();
+ char* buf = new char[length];
+ memcpy(buf, outputString.c_str(), length);
+
+ MPI_File_write_shared(tempFile, buf, length, MPI_CHAR, &statusTemp);
+ delete buf;
+ }
+ }
+ 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 = new char[nameFilename.length()];
+ //memcpy(inFileName, nameFilename.c_str(), nameFilename.length());
+
+ char inFileName[1024];
+ 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);
+ //delete inFileName;
+
+ char* buffer = new char[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);
+ delete buffer;
+
+ 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
/**************************************************************************************************/