*/
#include "classifyseqscommand.h"
-#include "sequence.hpp"
-#include "bayesian.h"
-#include "phylotree.h"
-#include "phylosummary.h"
-#include "knn.h"
CommandParameter pmismatch("mismatch", "Number", "", "-1.0", "", "", "",false,false); parameters.push_back(pmismatch);
CommandParameter pgapopen("gapopen", "Number", "", "-2.0", "", "", "",false,false); parameters.push_back(pgapopen);
CommandParameter pgapextend("gapextend", "Number", "", "-1.0", "", "", "",false,false); parameters.push_back(pgapextend);
+ //CommandParameter pflip("flip", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(pflip);
CommandParameter pcutoff("cutoff", "Number", "", "0", "", "", "",false,true); parameters.push_back(pcutoff);
CommandParameter pprobs("probs", "Boolean", "", "T", "", "", "",false,false); parameters.push_back(pprobs);
CommandParameter piters("iters", "Number", "", "100", "", "", "",false,true); parameters.push_back(piters);
helpString += "The cutoff parameter allows you to specify a bootstrap confidence threshold for your taxonomy. The default is 0.\n";
helpString += "The probs parameter shuts off the bootstrapping results for the bayesian method. The default is true, meaning you want the bootstrapping to be shown.\n";
helpString += "The iters parameter allows you to specify how many iterations to do when calculating the bootstrap confidence score for your taxonomy with the bayesian method. The default is 100.\n";
+ //helpString += "The flip parameter allows you shut off mothur's The default is T.\n";
helpString += "The classify.seqs command should be in the following format: \n";
helpString += "classify.seqs(reference=yourTemplateFile, fasta=yourFastaFile, method=yourClassificationMethod, search=yourSearchmethod, ksize=yourKmerSize, taxonomy=yourTaxonomyFile, processors=yourProcessors) \n";
helpString += "Example classify.seqs(fasta=amazon.fasta, reference=core.filtered, method=knn, search=gotoh, ksize=8, processors=2)\n";
setParameters();
vector<string> tempOutNames;
outputTypes["taxonomy"] = tempOutNames;
+ outputTypes["accnos"] = tempOutNames;
outputTypes["taxsummary"] = tempOutNames;
outputTypes["matchdist"] = tempOutNames;
}
outputTypes["taxonomy"] = tempOutNames;
outputTypes["taxsummary"] = tempOutNames;
outputTypes["matchdist"] = tempOutNames;
+ outputTypes["accnos"] = tempOutNames;
//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 = ""; }
// ...at some point should added some additional type checking...
string temp;
temp = validParameter.validFile(parameters, "ksize", false); if (temp == "not found"){ temp = "8"; }
- convert(temp, kmerSize);
+ m->mothurConvert(temp, kmerSize);
+
+ temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = m->getProcessors(); }
+ m->setProcessors(temp);
+ m->mothurConvert(temp, processors);
temp = validParameter.validFile(parameters, "save", false); if (temp == "not found"){ temp = "f"; }
save = m->isTrue(temp);
}else if (taxonomyFileName == "not open") { abort = true; }
else { if (save) { rdb->setSavedTaxonomy(taxonomyFileName); } }
- temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = m->getProcessors(); }
- m->setProcessors(temp);
- convert(temp, processors);
-
search = validParameter.validFile(parameters, "search", false); if (search == "not found"){ search = "kmer"; }
method = validParameter.validFile(parameters, "method", false); if (method == "not found"){ method = "bayesian"; }
temp = validParameter.validFile(parameters, "match", false); if (temp == "not found"){ temp = "1.0"; }
- convert(temp, match);
+ m->mothurConvert(temp, match);
temp = validParameter.validFile(parameters, "mismatch", false); if (temp == "not found"){ temp = "-1.0"; }
- convert(temp, misMatch);
+ m->mothurConvert(temp, misMatch);
temp = validParameter.validFile(parameters, "gapopen", false); if (temp == "not found"){ temp = "-2.0"; }
- convert(temp, gapOpen);
+ m->mothurConvert(temp, gapOpen);
temp = validParameter.validFile(parameters, "gapextend", false); if (temp == "not found"){ temp = "-1.0"; }
- convert(temp, gapExtend);
+ m->mothurConvert(temp, gapExtend);
temp = validParameter.validFile(parameters, "numwanted", false); if (temp == "not found"){ temp = "10"; }
- convert(temp, numWanted);
+ m->mothurConvert(temp, numWanted);
temp = validParameter.validFile(parameters, "cutoff", false); if (temp == "not found"){ temp = "0"; }
- convert(temp, cutoff);
+ m->mothurConvert(temp, cutoff);
temp = validParameter.validFile(parameters, "probs", false); if (temp == "not found"){ temp = "true"; }
probs = m->isTrue(temp);
+ //temp = validParameter.validFile(parameters, "flip", false); if (temp == "not found"){ temp = "T"; }
+ //flip = m->isTrue(temp);
+ flip = true;
+
temp = validParameter.validFile(parameters, "iters", false); if (temp == "not found") { temp = "100"; }
- convert(temp, iters);
-
+ m->mothurConvert(temp, iters);
if ((method == "bayesian") && (search != "kmer")) {
m->mothurOut("The bayesian method requires the kmer search." + search + "will be disregarded." ); m->mothurOutEndLine();
search = "kmer";
}
+
+ if (namefileNames.size() == 0){
+ vector<string> files; files.push_back(fastaFileNames[fastaFileNames.size()-1]);
+ parser.getNameFile(files);
+ }
+
}
}
try {
if (abort == true) { if (calledHelp) { return 0; } return 2; }
- if(method == "bayesian"){ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters, rand()); }
+ if(method == "bayesian"){ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters, rand(), flip); }
else if(method == "knn"){ classify = new Knn(taxonomyFileName, templateFileName, search, kmerSize, gapOpen, gapExtend, match, misMatch, numWanted, rand()); }
else {
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, rand());
+ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters, rand(), flip);
}
if (m->control_pressed) { delete classify; return 0; }
-
for (int s = 0; s < fastaFileNames.size(); s++) {
if (outputDir == "") { outputDir += m->hasPath(fastaFileNames[s]); }
string newTaxonomyFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + "taxonomy";
+ string newaccnosFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + "flip.accnos";
string tempTaxonomyFile = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + "taxonomy.temp";
string taxSummary = outputDir + m->getRootName(m->getSimpleName(fastaFileNames[s])) + RippedTaxName + "tax.summary";
}
outputNames.push_back(newTaxonomyFile); outputTypes["taxonomy"].push_back(newTaxonomyFile);
+ outputNames.push_back(newaccnosFile); outputTypes["accnos"].push_back(newaccnosFile);
outputNames.push_back(taxSummary); outputTypes["taxsummary"].push_back(taxSummary);
int start = time(NULL);
#ifdef USE_MPI
int pid, numSeqsPerProcessor;
int tag = 2001;
- vector<unsigned long int> MPIPos;
+ vector<unsigned long long> MPIPos;
MPI_Status status;
MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
MPI_File inMPI;
MPI_File outMPINewTax;
MPI_File outMPITempTax;
+ MPI_File outMPIAcc;
int outMode=MPI_MODE_CREATE|MPI_MODE_WRONLY;
int inMode=MPI_MODE_RDONLY;
char outTempTax[1024];
strcpy(outTempTax, tempTaxonomyFile.c_str());
+
+ char outAcc[1024];
+ strcpy(outAcc, newaccnosFile.c_str());
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);
+ MPI_File_open(MPI_COMM_WORLD, outAcc, outMode, MPI_INFO_NULL, &outMPIAcc);
- if (m->control_pressed) { outputTypes.clear(); MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); delete classify; return 0; }
+ if (m->control_pressed) { outputTypes.clear(); MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPIAcc); MPI_File_close(&outMPITempTax); delete classify; return 0; }
if (pid == 0) { //you are the root process
//align your part
- driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, MPIPos);
+ driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, outMPIAcc, MPIPos);
- if (m->control_pressed) { outputTypes.clear(); MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } delete classify; return 0; }
+ if (m->control_pressed) { outputTypes.clear(); MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPIAcc); MPI_File_close(&outMPITempTax); for (int i = 0; i < outputNames.size(); i++) { m->mothurRemove(outputNames[i]); } delete classify; return 0; }
for (int i = 1; i < processors; i++) {
int done;
//align your part
- driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, MPIPos);
+ driverMPI(startIndex, numSeqsPerProcessor, inMPI, outMPINewTax, outMPITempTax, outMPIAcc, MPIPos);
- if (m->control_pressed) { outputTypes.clear(); MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPITempTax); delete classify; return 0; }
+ if (m->control_pressed) { outputTypes.clear(); MPI_File_close(&inMPI); MPI_File_close(&outMPINewTax); MPI_File_close(&outMPIAcc); MPI_File_close(&outMPITempTax); delete classify; return 0; }
int done = 0;
MPI_Send(&done, 1, MPI_INT, 0, tag, MPI_COMM_WORLD);
MPI_File_close(&inMPI);
MPI_File_close(&outMPINewTax);
MPI_File_close(&outMPITempTax);
+ MPI_File_close(&outMPIAcc);
MPI_Barrier(MPI_COMM_WORLD); //make everyone wait - just in case
#else
- vector<unsigned long int> positions = m->divideFile(fastaFileNames[s], processors);
+ vector<unsigned long long> positions;
+#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
+ positions = m->divideFile(fastaFileNames[s], processors);
+ for (int i = 0; i < (positions.size()-1); i++) { lines.push_back(new linePair(positions[i], positions[(i+1)])); }
+#else
+ if (processors == 1) {
+ lines.push_back(new linePair(0, 1000));
+ }else {
+ positions = m->setFilePosFasta(fastaFileNames[s], numFastaSeqs);
- for (int i = 0; i < (positions.size()-1); i++) {
- lines.push_back(new linePair(positions[i], positions[(i+1)]));
- }
-
- #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
- if(processors == 1){
- numFastaSeqs = driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
+ //figure out how many sequences you have to process
+ int numSeqsPerProcessor = numFastaSeqs / processors;
+ for (int i = 0; i < processors; i++) {
+ int startIndex = i * numSeqsPerProcessor;
+ if(i == (processors - 1)){ numSeqsPerProcessor = numFastaSeqs - i * numSeqsPerProcessor; }
+ lines.push_back(new linePair(positions[startIndex], numSeqsPerProcessor));
+ }
}
- else{
- processIDS.resize(0);
-
- numFastaSeqs = createProcesses(newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
-
+#endif
+ if(processors == 1){
+ numFastaSeqs = driver(lines[0], newTaxonomyFile, tempTaxonomyFile, newaccnosFile, fastaFileNames[s]);
+ }else{
+ numFastaSeqs = createProcesses(newTaxonomyFile, tempTaxonomyFile, newaccnosFile, fastaFileNames[s]);
}
- #else
- numFastaSeqs = driver(lines[0], newTaxonomyFile, tempTaxonomyFile, fastaFileNames[s]);
- #endif
#endif
+
+ if (!m->isBlank(newaccnosFile)) { m->mothurOutEndLine(); m->mothurOut("[WARNING]: mothur suspects some of your sequences may be reversed, please check " + newaccnosFile + " for the list of the sequences."); m->mothurOutEndLine(); }
m->mothurOutEndLine();
m->mothurOut("It took " + toString(time(NULL) - start) + " secs to classify " + toString(numFastaSeqs) + " sequences."); m->mothurOutEndLine(); m->mothurOutEndLine();
start = time(NULL);
-
+
+
#ifdef USE_MPI
if (pid == 0) { //this part does not need to be paralellized
if ((itTypes->second).size() != 0) { current = (itTypes->second)[0]; m->setTaxonomyFile(current); }
}
+ current = "";
+ itTypes = outputTypes.find("accnos");
+ if (itTypes != outputTypes.end()) {
+ if ((itTypes->second).size() != 0) { current = (itTypes->second)[0]; m->setAccnosFile(current); }
+ }
+
delete classify;
+
return 0;
}
catch(exception& e) {
/**************************************************************************************************/
-int ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile, string filename) {
+int ClassifySeqsCommand::createProcesses(string taxFileName, string tempTaxFile, string accnos, string filename) {
try {
+
+ int num = 0;
+ processIDS.clear();
+
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
int process = 1;
- int num = 0;
//loop through and create all the processes you want
while (process != processors) {
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){
- num = driver(lines[process], taxFileName + toString(getpid()) + ".temp", tempTaxFile + toString(getpid()) + ".temp", filename);
+ num = driver(lines[process], taxFileName + toString(getpid()) + ".temp", tempTaxFile + toString(getpid()) + ".temp", accnos + toString(getpid()) + ".temp", filename);
//pass numSeqs to parent
ofstream out;
}
//parent does its part
- num = driver(lines[0], taxFileName, tempTaxFile, filename);
+ num = driver(lines[0], taxFileName, tempTaxFile, accnos, filename);
//force parent to wait until all the processes are done
for (int i=0;i<processIDS.size();i++) {
if (!in.eof()) { int tempNum = 0; in >> tempNum; num += tempNum; }
in.close(); m->mothurRemove(m->getFullPathName(tempFile));
}
+#else
+ //////////////////////////////////////////////////////////////////////////////////////////////////////
+ //Windows version shared memory, so be careful when passing variables through the alignData struct.
+ //Above fork() will clone, so memory is separate, but that's not the case with windows,
+ //////////////////////////////////////////////////////////////////////////////////////////////////////
+
+ vector<classifyData*> pDataArray;
+ DWORD dwThreadIdArray[processors-1];
+ HANDLE hThreadArray[processors-1];
+
+ //Create processor worker threads.
+ for( int i=0; i<processors-1; i++ ){
+ // Allocate memory for thread data.
+ string extension = "";
+ if (i != 0) { extension = toString(i) + ".temp"; processIDS.push_back(i); }
+
+ classifyData* tempclass = new classifyData((accnos + extension), probs, method, templateFileName, taxonomyFileName, (taxFileName + extension), (tempTaxFile + extension), filename, search, kmerSize, iters, numWanted, m, lines[i]->start, lines[i]->end, match, misMatch, gapOpen, gapExtend, cutoff, i, flipThreshold);
+ pDataArray.push_back(tempclass);
+
+ //MySeqSumThreadFunction is in header. It must be global or static to work with the threads.
+ //default security attributes, thread function name, argument to thread function, use default creation flags, returns the thread identifier
+ hThreadArray[i] = CreateThread(NULL, 0, MyClassThreadFunction, pDataArray[i], 0, &dwThreadIdArray[i]);
+
+ }
+
+ //parent does its part
+ num = driver(lines[processors-1], taxFileName + toString(processors-1) + ".temp", tempTaxFile + toString(processors-1) + ".temp", accnos + toString(processors-1) + ".temp", filename);
+ processIDS.push_back((processors-1));
+
+ //Wait until all threads have terminated.
+ WaitForMultipleObjects(processors-1, hThreadArray, TRUE, INFINITE);
+
+ //Close all thread handles and free memory allocations.
+ for(int i=0; i < pDataArray.size(); i++){
+ num += pDataArray[i]->count;
+ CloseHandle(hThreadArray[i]);
+ delete pDataArray[i];
+ }
+
+ #endif
for(int i=0;i<processIDS.size();i++){
appendTaxFiles((taxFileName + toString(processIDS[i]) + ".temp"), taxFileName);
appendTaxFiles((tempTaxFile + toString(processIDS[i]) + ".temp"), tempTaxFile);
+ appendTaxFiles((accnos + toString(processIDS[i]) + ".temp"), accnos);
m->mothurRemove((m->getFullPathName(taxFileName) + toString(processIDS[i]) + ".temp"));
m->mothurRemove((m->getFullPathName(tempTaxFile) + toString(processIDS[i]) + ".temp"));
+ m->mothurRemove((m->getFullPathName(accnos) + toString(processIDS[i]) + ".temp"));
}
return num;
-#endif
+
}
catch(exception& e) {
m->errorOut(e, "ClassifySeqsCommand", "createProcesses");
//**********************************************************************************************************************
-int ClassifySeqsCommand::driver(linePair* filePos, string taxFName, string tempTFName, string filename){
+int ClassifySeqsCommand::driver(linePair* filePos, string taxFName, string tempTFName, string accnos, string filename){
try {
ofstream outTax;
m->openOutputFile(taxFName, outTax);
ofstream outTaxSimple;
m->openOutputFile(tempTFName, outTaxSimple);
+
+ ofstream outAcc;
+ m->openOutputFile(accnos, outAcc);
ifstream inFASTA;
m->openInputFile(filename, inFASTA);
int count = 0;
while (!done) {
- if (m->control_pressed) { return 0; }
+ if (m->control_pressed) {
+ inFASTA.close();
+ outTax.close();
+ outTaxSimple.close();
+ outAcc.close(); return 0; }
Sequence* candidateSeq = new Sequence(inFASTA); m->gobble(inFASTA);
taxonomy = classify->getTaxonomy(candidateSeq);
if (m->control_pressed) { delete candidateSeq; return 0; }
-
- if (taxonomy != "bad seq") {
- //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;
+
+ if (taxonomy == "unknown;") { m->mothurOut("[WARNING]: " + candidateSeq->getName() + " could not be classified. You can use the remove.lineage command with taxon=unknown; to remove such sequences."); m->mothurOutEndLine(); }
+
+ //output confidence scores or not
+ if (probs) {
+ outTax << candidateSeq->getName() << '\t' << taxonomy << endl;
+ }else{
+ outTax << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
}
+
+ if (classify->getFlipped()) { outAcc << candidateSeq->getName() << endl; }
+
+ outTaxSimple << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
+
count++;
}
delete candidateSeq;
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
- unsigned long int pos = inFASTA.tellg();
+ unsigned long long pos = inFASTA.tellg();
if ((pos == -1) || (pos >= filePos->end)) { break; }
#else
if (inFASTA.eof()) { break; }
inFASTA.close();
outTax.close();
outTaxSimple.close();
+ outAcc.close();
return count;
}
}
//**********************************************************************************************************************
#ifdef USE_MPI
-int ClassifySeqsCommand::driverMPI(int start, int num, MPI_File& inMPI, MPI_File& newFile, MPI_File& tempFile, vector<unsigned long int>& MPIPos){
+int ClassifySeqsCommand::driverMPI(int start, int num, MPI_File& inMPI, MPI_File& newFile, MPI_File& tempFile, MPI_File& accFile, vector<unsigned long long>& MPIPos){
try {
MPI_Status statusNew;
MPI_Status statusTemp;
+ MPI_Status statusAcc;
MPI_Status status;
int pid;
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);
+ if (taxonomy == "unknown;") { m->mothurOut("[WARNING]: " + candidateSeq->getName() + " could not be classified. You can use the remove.lineage command with taxon=unknown; to remove such sequences."); m->mothurOutEndLine(); }
- MPI_File_write_shared(newFile, buf2, length, MPI_CHAR, &statusNew);
- delete buf2;
-
+ //output confidence scores or not
+ if (probs) {
+ outputString = candidateSeq->getName() + "\t" + taxonomy + "\n";
+ }else{
outputString = candidateSeq->getName() + "\t" + classify->getSimpleTax() + "\n";
- length = outputString.length();
- char* buf = new char[length];
- memcpy(buf, outputString.c_str(), length);
+ }
+
+ 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;
+ MPI_File_write_shared(tempFile, buf, length, MPI_CHAR, &statusTemp);
+ delete buf;
+
+ if (classify->getFlipped()) {
+ outputString = candidateSeq->getName() + "\n";
+ length = outputString.length();
+ char* buf3 = new char[length];
+ memcpy(buf3, outputString.c_str(), length);
+
+ MPI_File_write_shared(accFile, buf3, length, MPI_CHAR, &statusAcc);
+ delete buf3;
}
+
}
delete candidateSeq;
projects / mothur.git / blobdiff