#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","search","ksize","method","processors","taxonomy","match","mismatch","gapopen","gapextend","numwanted","cutoff","probs"};
+ 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);
map<string, string> parameters = parser.getParameters();
ValidParameters validParameter;
+ map<string, string>::iterator it;
//check to make sure all parameters are valid for command
- for (map<string, string>::iterator it = parameters.begin(); it != parameters.end(); it++) {
+ for (it = parameters.begin(); it != parameters.end(); it++) {
if (validParameter.isValidParameter(it->first, myArray, it->second) != true) { abort = true; }
}
+ //if the user changes the output directory command factory will send this info to us in the output parameter
+ outputDir = validParameter.validFile(parameters, "outputdir", false); if (outputDir == "not found"){ outputDir = ""; }
+
+ //if the user changes the input directory command factory will send this info to us in the output parameter
+ string inputDir = validParameter.validFile(parameters, "inputdir", false);
+ if (inputDir == "not found"){ inputDir = ""; }
+ else {
+ string path;
+ it = parameters.find("template");
+ //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["template"] = inputDir + it->second; }
+ }
+
+ it = parameters.find("taxonomy");
+ //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["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", true);
- if (fastaFileName == "not found") {
- mothurOut("fasta is a required parameter for the classify.seqs command.");
- mothurOutEndLine();
- abort = true;
+
+ fastaFileName = validParameter.validFile(parameters, "fasta", false);
+ if (fastaFileName == "not found") { m->mothurOut("fasta is a required parameter for the classify.seqs command."); m->mothurOutEndLine(); abort = true; }
+ else {
+ splitAtDash(fastaFileName, fastaFileNames);
+
+ //go through files and make sure they are good, if not, then disregard them
+ for (int i = 0; i < fastaFileNames.size(); i++) {
+ if (inputDir != "") {
+ string path = hasPath(fastaFileNames[i]);
+ //if the user has not given a path then, add inputdir. else leave path alone.
+ if (path == "") { fastaFileNames[i] = inputDir + fastaFileNames[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(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) {
+ m->mothurOut(fastaFileNames[i] + " will be disregarded."); m->mothurOutEndLine();
+ //erase from file list
+ fastaFileNames.erase(fastaFileNames.begin()+i);
+ i--;
+ }
+
+ }
+
+ //make sure there is at least one valid file left
+ if (fastaFileNames.size() == 0) { m->mothurOut("no valid files."); m->mothurOutEndLine(); abort = true; }
}
- else if (fastaFileName == "not open") { 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; }
+
+
+ namefile = validParameter.validFile(parameters, "name", false);
+ if (namefile == "not found") { namefile = ""; }
+
+ else {
+ splitAtDash(namefile, namefileNames);
+
+ //go through files and make sure they are good, if not, then disregard them
+ for (int i = 0; i < namefileNames.size(); i++) {
+ if (inputDir != "") {
+ string path = hasPath(namefileNames[i]);
+ //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);
+ 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; 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
// ...at some point should added some additional type checking...
temp = validParameter.validFile(parameters, "probs", false); if (temp == "not found"){ temp = "true"; }
probs = isTrue(temp);
+
+ temp = validParameter.validFile(parameters, "iters", false); if (temp == "not found") { temp = "100"; }
+ convert(temp, iters);
+
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, search, ksize, method, taxonomy, processors, match, mismatch, gapopen, gapextend, numwanted and probs.\n");
- mothurOut("The template, fasta and taxonomy parameters are required.\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 -1.0.\n");
- mothurOut("The gapextend parameter allows you to specify the penalty for extending a gap in an alignment. The default is -2.0.\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 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);
}
}
try {
if (abort == true) { return 0; }
- if(method == "bayesian") { classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, probs); }
- else if(method == "knn") { classify = new Knn(taxonomyFileName, templateFileName, search, kmerSize, gapOpen, gapExtend, match, misMatch, numWanted); }
+ 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();
- classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, probs);
+ 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);
}
-
- int numFastaSeqs = 0;
- string newTaxonomyFile = getRootName(fastaFileName) + "taxonomy";
- string tempTaxonomyFile = getRootName(fastaFileName) + "taxonomy.temp";
- string taxSummary = getRootName(fastaFileName) + "tax.summary";
+ if (m->control_pressed) { delete classify; return 0; }
- int start = time(NULL);
-#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
- if(processors == 1){
+ 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
+
+ ifstream inNames;
+ openInputFile(namefileNames[s], inNames);
+
+ string firstCol, secondCol;
+ while(!inNames.eof()) {
+ inNames >> firstCol >> secondCol; gobble(inNames);
+ nameMap[firstCol] = getNumNames(secondCol); //ex. seq1 seq1,seq3,seq5 -> seq1 = 3.
+ }
+ inNames.close();
+ }
+
+ #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
+ if(processors == 1){
+ ifstream inFASTA;
+ openInputFile(fastaFileNames[s], inFASTA);
+ numFastaSeqs=count(istreambuf_iterator<char>(inFASTA),istreambuf_iterator<char>(), '>');
+ inFASTA.close();
+
+ lines.push_back(new linePair(0, numFastaSeqs));
+
+ driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
+ }
+ else{
+ vector<int> positions;
+ processIDS.resize(0);
+
+ ifstream inFASTA;
+ openInputFile(fastaFileNames[s], inFASTA);
+
+ string input;
+ while(!inFASTA.eof()){
+ input = getline(inFASTA);
+ if (input.length() != 0) {
+ if(input[0] == '>'){ int pos = inFASTA.tellg(); positions.push_back(pos - input.length() - 1); }
+ }
+ }
+ inFASTA.close();
+
+ numFastaSeqs = positions.size();
+
+ int numSeqsPerProcessor = numFastaSeqs / processors;
+
+ for (int i = 0; i < processors; i++) {
+ int startPos = positions[ i * numSeqsPerProcessor ];
+ if(i == processors - 1){
+ numSeqsPerProcessor = numFastaSeqs - i * numSeqsPerProcessor;
+ }
+ lines.push_back(new linePair(startPos, numSeqsPerProcessor));
+ }
+ createProcesses(newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
+
+ rename((newTaxonomyFile + toString(processIDS[0]) + ".temp").c_str(), newTaxonomyFile.c_str());
+ rename((tempTaxonomyFile + toString(processIDS[0]) + ".temp").c_str(), tempTaxonomyFile.c_str());
+
+ for(int i=1;i<processors;i++){
+ appendTaxFiles((newTaxonomyFile + toString(processIDS[i]) + ".temp"), newTaxonomyFile);
+ appendTaxFiles((tempTaxonomyFile + toString(processIDS[i]) + ".temp"), tempTaxonomyFile);
+ remove((newTaxonomyFile + toString(processIDS[i]) + ".temp").c_str());
+ remove((tempTaxonomyFile + toString(processIDS[i]) + ".temp").c_str());
+ }
+
+ }
+ #else
ifstream inFASTA;
- openInputFile(fastaFileName, inFASTA);
+ openInputFile(fastaFileNames[s], inFASTA);
numFastaSeqs=count(istreambuf_iterator<char>(inFASTA),istreambuf_iterator<char>(), '>');
inFASTA.close();
lines.push_back(new linePair(0, numFastaSeqs));
-
- driver(lines[0], newTaxonomyFile, tempTaxonomyFile);
- }
- else{
- vector<int> positions;
- processIDS.resize(0);
- ifstream inFASTA;
- openInputFile(fastaFileName, inFASTA);
+ driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
+ #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]);
- string input;
- while(!inFASTA.eof()){
- input = getline(inFASTA);
- if (input.length() != 0) {
- if(input[0] == '>'){ int pos = inFASTA.tellg(); positions.push_back(pos - input.length() - 1); }
+ 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);
+
+ //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()) {
+ m->mothurOut(name + " is not in your name file please correct."); m->mothurOutEndLine(); exit(1);
+ }else{
+ for (int i = 0; i < itNames->second; i++) {
+ taxaSum.addSeqToTree(name, taxon); //add it as many times as there are identical seqs
+ }
+ }
}
+ in.close();
}
- inFASTA.close();
+ remove(tempTaxonomyFile.c_str());
- numFastaSeqs = positions.size();
+ if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } delete classify; return 0; }
- int numSeqsPerProcessor = numFastaSeqs / processors;
+ //print summary file
+ ofstream outTaxTree;
+ openOutputFile(taxSummary, outTaxTree);
+ taxaSum.print(outTaxTree);
+ outTaxTree.close();
- for (int i = 0; i < processors; i++) {
- int startPos = positions[ i * numSeqsPerProcessor ];
- if(i == processors - 1){
- numSeqsPerProcessor = numFastaSeqs - i * numSeqsPerProcessor;
- }
- lines.push_back(new linePair(startPos, numSeqsPerProcessor));
- }
- createProcesses(newTaxonomyFile, tempTaxonomyFile);
+ //output taxonomy with the unclassified bins added
+ ifstream inTax;
+ openInputFile(newTaxonomyFile, inTax);
+
+ ofstream outTax;
+ string unclass = newTaxonomyFile + ".unclass.temp";
+ openOutputFile(unclass, outTax);
- rename((newTaxonomyFile + toString(processIDS[0]) + ".temp").c_str(), newTaxonomyFile.c_str());
- rename((tempTaxonomyFile + toString(processIDS[0]) + ".temp").c_str(), tempTaxonomyFile.c_str());
+ //get maxLevel from phylotree so you know how many 'unclassified's to add
+ int maxLevel = taxaSum.getMaxLevel();
- for(int i=1;i<processors;i++){
- appendTaxFiles((newTaxonomyFile + toString(processIDS[i]) + ".temp"), newTaxonomyFile);
- appendTaxFiles((tempTaxonomyFile + toString(processIDS[i]) + ".temp"), tempTaxonomyFile);
- remove((newTaxonomyFile + toString(processIDS[i]) + ".temp").c_str());
- remove((tempTaxonomyFile + toString(processIDS[i]) + ".temp").c_str());
+ //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);
+
+ outTax << name << '\t' << newTax << endl;
}
+ inTax.close();
+ outTax.close();
- }
-#else
- ifstream inFASTA;
- openInputFile(fastaFileName, inFASTA);
- numFastaSeqs=count(istreambuf_iterator<char>(inFASTA),istreambuf_iterator<char>(), '>');
- inFASTA.close();
-
- lines.push_back(new linePair(0, numFastaSeqs));
-
- driver(lines[0], newTaxonomyFile, tempTaxonomyFile);
-#endif
- delete classify;
-
- //make taxonomy tree from new taxonomy file
- ifstream inTaxonomy;
- openInputFile(tempTaxonomyFile, inTaxonomy);
-
- string accession, taxaList;
- PhyloTree taxaBrowser;
-
- //read in users taxonomy file and add sequences to tree
- while(!inTaxonomy.eof()){
- inTaxonomy >> accession >> taxaList;
+ remove(newTaxonomyFile.c_str());
+ rename(unclass.c_str(), newTaxonomyFile.c_str());
- taxaBrowser.addSeqToTree(accession, taxaList);
+ m->mothurOutEndLine();
+ m->mothurOut("It took " + toString(time(NULL) - start) + " secs to create the summary file for " + toString(numFastaSeqs) + " sequences."); m->mothurOutEndLine(); m->mothurOutEndLine();
- gobble(inTaxonomy);
+ #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();
}
- inTaxonomy.close();
- remove(tempTaxonomyFile.c_str());
- taxaBrowser.assignHeirarchyIDs(0);
-
- ofstream outTaxTree;
- openOutputFile(taxSummary, outTaxTree);
+ delete classify;
+ return 0;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "ClassifySeqsCommand", "execute");
+ exit(1);
+ }
+}
+
+/**************************************************************************************************/
+string ClassifySeqsCommand::addUnclassifieds(string tax, int maxlevel) {
+ try{
+ string newTax, taxon;
+ int level = 0;
- taxaBrowser.print(outTaxTree);
+ //keep what you have counting the levels
+ while (tax.find_first_of(';') != -1) {
+ //get taxon
+ taxon = tax.substr(0,tax.find_first_of(';'))+';';
+ tax = tax.substr(tax.find_first_of(';')+1, tax.length());
+ newTax += taxon;
+ level++;
+ }
- mothurOutEndLine();
- mothurOut("It took " + toString(time(NULL) - start) + " secs to classify " + toString(numFastaSeqs) + " sequences.");
- mothurOutEndLine();
- mothurOutEndLine();
+ //add "unclassified" until you reach maxLevel
+ while (level < maxlevel) {
+ newTax += "unclassified;";
+ level++;
+ }
- return 0;
+ return newTax;
}
catch(exception& e) {
- errorOut(e, "ClassifySeqsCommand", "execute");
+ m->errorOut(e, "ClassifySeqsCommand", "addUnclassifieds");
exit(1);
}
}
+
/**************************************************************************************************/
-void ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile) {
+void ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile, string filename) {
try {
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
int process = 0;
processIDS.push_back(pid); //create map from line number to pid so you can append files in correct order later
process++;
}else if (pid == 0){
- driver(lines[process], taxFileName + toString(getpid()) + ".temp", tempTaxFile + toString(getpid()) + ".temp");
+ 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);
}
}
//**********************************************************************************************************************
-int ClassifySeqsCommand::driver(linePair* line, string taxFName, string tempTFName){
+int ClassifySeqsCommand::driver(linePair* line, string taxFName, string tempTFName, string filename){
try {
ofstream outTax;
openOutputFile(taxFName, outTax);
openOutputFile(tempTFName, outTaxSimple);
ifstream inFASTA;
- openInputFile(fastaFileName, inFASTA);
+ openInputFile(filename, inFASTA);
inFASTA.seekg(line->start);
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") {
- outTax << candidateSeq->getName() << '\t' << taxonomy << endl;
+ //output confidence scores or not
+ if (probs) {
+ outTax << candidateSeq->getName() << '\t' << taxonomy << endl;
+ }else{
+ outTax << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
+ }
+
outTaxSimple << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
}
}
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
/**************************************************************************************************/