OptionParser parser(option);
map<string,string> parameters = parser.getParameters();
- ValidParameters validParameter;
+ ValidParameters validParameter("cluster.split");
//check to make sure all parameters are valid for command
map<string,string>::iterator it;
it = parameters.find("phylip");
//user has given a template file
if(it != parameters.end()){
- path = hasPath(it->second);
+ path = m->hasPath(it->second);
//if the user has not given a path then, add inputdir. else leave path alone.
if (path == "") { parameters["phylip"] = inputDir + it->second; }
}
it = parameters.find("column");
//user has given a template file
if(it != parameters.end()){
- path = hasPath(it->second);
+ path = m->hasPath(it->second);
//if the user has not given a path then, add inputdir. else leave path alone.
if (path == "") { parameters["column"] = inputDir + it->second; }
}
it = parameters.find("name");
//user has given a template file
if(it != parameters.end()){
- path = hasPath(it->second);
+ path = m->hasPath(it->second);
//if the user has not given a path then, add inputdir. else leave path alone.
if (path == "") { parameters["name"] = inputDir + it->second; }
}
it = parameters.find("taxonomy");
//user has given a template file
if(it != parameters.end()){
- path = hasPath(it->second);
+ path = m->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("fasta");
//user has given a template file
if(it != parameters.end()){
- path = hasPath(it->second);
+ path = m->hasPath(it->second);
//if the user has not given a path then, add inputdir. else leave path alone.
if (path == "") { parameters["fasta"] = inputDir + it->second; }
}
fastafile = validParameter.validFile(parameters, "fasta", true);
if (fastafile == "not open") { abort = true; }
else if (fastafile == "not found") { fastafile = ""; }
- else { splitmethod = "fasta"; }
+ else { distfile = fastafile; splitmethod = "fasta"; }
taxFile = validParameter.validFile(parameters, "taxonomy", true);
if (taxFile == "not open") { abort = true; }
convert(temp, precision);
temp = validParameter.validFile(parameters, "hard", false); if (temp == "not found") { temp = "F"; }
- hard = isTrue(temp);
+ hard = m->isTrue(temp);
temp = validParameter.validFile(parameters, "large", false); if (temp == "not found") { temp = "F"; }
- large = isTrue(temp);
+ large = m->isTrue(temp);
temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = "1"; }
convert(temp, processors);
m->mothurOut("The cluster.split command can split your files in 3 ways. Splitting by distance file, by classification, or by classification also using a fasta file. \n");
m->mothurOut("For the distance file method, you need only provide your distance file and mothur will split the file into distinct groups. \n");
m->mothurOut("For the classification method, you need to provide your distance file and taxonomy file, and set the splitmethod to classify. \n");
- m->mothurOut("You will also need to set the taxlevel you want to split by. mothur will split the sequence into distinct taxonomy groups, and split the distance file based on those groups. \n");
+ m->mothurOut("You will also need to set the taxlevel you want to split by. mothur will split the sequences into distinct taxonomy groups, and split the distance file based on those groups. \n");
m->mothurOut("For the classification method using a fasta file, you need to provide your fasta file, names file and taxonomy file. \n");
m->mothurOut("You will also need to set the taxlevel you want to split by. mothur will split the sequence into distinct taxonomy groups, and create distance files for each grouping. \n");
m->mothurOut("The phylip and column parameter allow you to enter your distance file. \n");
m->mothurOut("The method allows you to specify what clustering algorythm you want to use, default=furthest, option furthest, nearest, or average. \n");
m->mothurOut("The splitmethod parameter allows you to specify how you want to split your distance file before you cluster, default=distance, options distance, classify or fasta. \n");
m->mothurOut("The taxonomy parameter allows you to enter the taxonomy file for your sequences, this is only valid if you are using splitmethod=classify. Be sure your taxonomy file does not include the probability scores. \n");
- m->mothurOut("The taxlevel parameter allows you to specify the taxonomy level you want to use to split the distance file, default=1. \n");
+ m->mothurOut("The taxlevel parameter allows you to specify the taxonomy level you want to use to split the distance file, default=1, meaning use the first taxon in each list. \n");
m->mothurOut("The large parameter allows you to indicate that your distance matrix is too large to fit in RAM. The default value is false.\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 cluster.split command should be in the following format: \n");
m->mothurOut("cluster.split(column=youDistanceFile, name=yourNameFile, method=yourMethod, cutoff=yourCutoff, precision=yourPrecision, splitmethod=yourSplitmethod, taxonomy=yourTaxonomyfile, taxlevel=yourtaxlevel) \n");
m->mothurOut("Example: cluster.split(column=abrecovery.dist, name=abrecovery.names, method=furthest, cutoff=0.10, precision=1000, splitmethod=classify, taxonomy=abrecovery.silva.slv.taxonomy, taxlevel=5) \n");
try {
if (abort == true) { return 0; }
+
time_t estart;
+ vector<string> listFileNames;
+ set<string> labels;
+ string singletonName = "";
+ double saveCutoff = cutoff;
+
//****************** file prep work ******************************//
+ #ifdef USE_MPI
+ int pid;
+ int tag = 2001;
+ MPI_Status status;
+ 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) { //only process 0 converts and splits
+
+ #endif
//if user gave a phylip file convert to column file
if (format == "phylip") {
if (namefile == "") { //you need to make a namefile for split matrix
ofstream out;
namefile = phylipfile + ".names";
- openOutputFile(namefile, out);
+ m->openOutputFile(namefile, out);
for (int i = 0; i < listToMakeNameFile->getNumBins(); i++) {
string bin = listToMakeNameFile->get(i);
out << bin << '\t' << bin << endl;
//split matrix into non-overlapping groups
SplitMatrix* split;
- if (splitmethod == "distance") { split = new SplitMatrix(distfile, namefile, taxFile, cutoff, splitmethod, large); }
- else if (splitmethod == "classify") { split = new SplitMatrix(distfile, namefile, taxFile, taxLevelCutoff, splitmethod, large); }
- else if (splitmethod == "fasta") { split = new SplitMatrix(fastafile, namefile, taxFile, taxLevelCutoff, splitmethod, processors); }
- else { m->mothurOut("Not a valid splitting method. Valid splitting algorithms are distance, classify or fasta."); m->mothurOutEndLine(); return 0; }
+ if (splitmethod == "distance") { split = new SplitMatrix(distfile, namefile, taxFile, cutoff, splitmethod, large); }
+ else if (splitmethod == "classify") { split = new SplitMatrix(distfile, namefile, taxFile, taxLevelCutoff, splitmethod, large); }
+ else if (splitmethod == "fasta") { split = new SplitMatrix(fastafile, namefile, taxFile, taxLevelCutoff, splitmethod, processors, outputDir); }
+ else { m->mothurOut("Not a valid splitting method. Valid splitting algorithms are distance, classify or fasta."); m->mothurOutEndLine(); return 0; }
split->split();
if (m->control_pressed) { delete split; return 0; }
- string singletonName = split->getSingletonNames();
+ singletonName = split->getSingletonNames();
vector< map<string, string> > distName = split->getDistanceFiles(); //returns map of distance files -> namefile sorted by distance file size
delete split;
estart = time(NULL);
//****************** break up files between processes and cluster each file set ******************************//
- vector<string> listFileNames;
- set<string> labels;
+ #ifdef USE_MPI
+ ////you are process 0 from above////
+
+ vector < vector < map<string, string> > > dividedNames; //distNames[1] = vector of filenames for process 1...
+ dividedNames.resize(processors);
+
+ //for each file group figure out which process will complete it
+ //want to divide the load intelligently so the big files are spread between processes
+ int count = 1;
+ for (int i = 0; i < distName.size(); i++) {
+ int processToAssign = (i+1) % processors;
+ if (processToAssign == 0) { processToAssign = processors; }
+
+ dividedNames[(processToAssign-1)].push_back(distName[i]);
+ }
+
+ //not lets reverse the order of ever other process, so we balance big files running with little ones
+ for (int i = 0; i < processors; i++) {
+ int remainder = ((i+1) % processors);
+ if (remainder) { reverse(dividedNames[i].begin(), dividedNames[i].end()); }
+ }
+
+
+ //send each child the list of files it needs to process
+ for(int i = 1; i < processors; i++) {
+ //send number of file pairs
+ int num = dividedNames[i].size();
+ MPI_Send(&num, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
+
+ for (int j = 0; j < num; j++) { //send filenames to process i
+ char tempDistFileName[1024];
+ strcpy(tempDistFileName, (dividedNames[i][j].begin()->first).c_str());
+ int lengthDist = (dividedNames[i][j].begin()->first).length();
+
+ MPI_Send(&lengthDist, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
+ MPI_Send(tempDistFileName, 1024, MPI_CHAR, i, tag, MPI_COMM_WORLD);
+
+ char tempNameFileName[1024];
+ strcpy(tempNameFileName, (dividedNames[i][j].begin()->second).c_str());
+ int lengthName = (dividedNames[i][j].begin()->second).length();
+
+ MPI_Send(&lengthName, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
+ MPI_Send(tempNameFileName, 1024, MPI_CHAR, i, tag, MPI_COMM_WORLD);
+ }
+ }
+
+ //process your share
+ listFileNames = cluster(dividedNames[0], labels);
+
+ //receive the other processes info
+ for(int i = 1; i < processors; i++) {
+ int num = dividedNames[i].size();
+
+ double tempCutoff;
+ MPI_Recv(&tempCutoff, 1, MPI_DOUBLE, i, tag, MPI_COMM_WORLD, &status);
+ if (tempCutoff < cutoff) { cutoff = tempCutoff; }
+
+ //send list filenames to root process
+ for (int j = 0; j < num; j++) {
+ int lengthList = 0;
+ char tempListFileName[1024];
+
+ MPI_Recv(&lengthList, 1, MPI_INT, i, tag, MPI_COMM_WORLD, &status);
+ MPI_Recv(tempListFileName, 1024, MPI_CHAR, i, tag, MPI_COMM_WORLD, &status);
+
+ string myListFileName = tempListFileName;
+ myListFileName = myListFileName.substr(0, lengthList);
+
+ listFileNames.push_back(myListFileName);
+ }
+
+ //send Labels to root process
+ int numLabels = 0;
+ MPI_Recv(&numLabels, 1, MPI_INT, i, tag, MPI_COMM_WORLD, &status);
+
+ for (int j = 0; j < numLabels; j++) {
+ int lengthLabel = 0;
+ char tempLabel[100];
+
+ MPI_Recv(&lengthLabel, 1, MPI_INT, i, tag, MPI_COMM_WORLD, &status);
+ MPI_Recv(tempLabel, 100, MPI_CHAR, i, tag, MPI_COMM_WORLD, &status);
+
+ string myLabel = tempLabel;
+ myLabel = myLabel.substr(0, lengthLabel);
+
+ if (labels.count(myLabel) == 0) { labels.insert(myLabel); }
+ }
+ }
+
+ }else { //you are a child process
+ vector < map<string, string> > myNames;
+
+ //recieve the files you need to process
+ //receive number of file pairs
+ int num = 0;
+ MPI_Recv(&num, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
+
+ myNames.resize(num);
+
+ for (int j = 0; j < num; j++) { //receive filenames to process
+ int lengthDist = 0;
+ char tempDistFileName[1024];
+
+ MPI_Recv(&lengthDist, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
+ MPI_Recv(tempDistFileName, 1024, MPI_CHAR, 0, tag, MPI_COMM_WORLD, &status);
+
+ string myDistFileName = tempDistFileName;
+ myDistFileName = myDistFileName.substr(0, lengthDist);
+
+ int lengthName = 0;
+ char tempNameFileName[1024];
+
+ MPI_Recv(&lengthName, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
+ MPI_Recv(tempNameFileName, 1024, MPI_CHAR, 0, tag, MPI_COMM_WORLD, &status);
+
+ string myNameFileName = tempNameFileName;
+ myNameFileName = myNameFileName.substr(0, lengthName);
+
+ //save file name
+ myNames[j][myDistFileName] = myNameFileName;
+ }
+
+ //process them
+ listFileNames = cluster(myNames, labels);
+
+ //send cutoff
+ MPI_Send(&cutoff, 1, MPI_DOUBLE, 0, tag, MPI_COMM_WORLD);
+
+ //send list filenames to root process
+ for (int j = 0; j < num; j++) {
+ char tempListFileName[1024];
+ strcpy(tempListFileName, listFileNames[j].c_str());
+ int lengthList = listFileNames[j].length();
+
+ MPI_Send(&lengthList, 1, MPI_INT, 0, tag, MPI_COMM_WORLD);
+ MPI_Send(tempListFileName, 1024, MPI_CHAR, 0, tag, MPI_COMM_WORLD);
+ }
+
+ //send Labels to root process
+ int numLabels = labels.size();
+ MPI_Send(&numLabels, 1, MPI_INT, 0, tag, MPI_COMM_WORLD);
+
+ for(set<string>::iterator it = labels.begin(); it != labels.end(); ++it) {
+ char tempLabel[100];
+ strcpy(tempLabel, (*it).c_str());
+ int lengthLabel = (*it).length();
+
+ MPI_Send(&lengthLabel, 1, MPI_INT, 0, tag, MPI_COMM_WORLD);
+ MPI_Send(tempLabel, 100, MPI_CHAR, 0, tag, MPI_COMM_WORLD);
+ }
+ }
+
+ //make everyone wait
+ MPI_Barrier(MPI_COMM_WORLD);
+
+ #else
+
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
if(processors == 1){
listFileNames = cluster(distName, labels); //clusters individual files and returns names of list files
for(int i=0;i<processors;i++){
string filename = toString(processIDS[i]) + ".temp";
ifstream in;
- openInputFile(filename, in);
+ m->openInputFile(filename, in);
- in >> tag; gobble(in);
+ in >> tag; m->gobble(in);
while(!in.eof()) {
string tempName;
- in >> tempName; gobble(in);
+ in >> tempName; m->gobble(in);
listFileNames.push_back(tempName);
}
in.close();
//get labels
filename = toString(processIDS[i]) + ".temp.labels";
ifstream in2;
- openInputFile(filename, in2);
+ m->openInputFile(filename, in2);
+
+ float tempCutoff;
+ in2 >> tempCutoff; m->gobble(in2);
+ if (tempCutoff < cutoff) { cutoff = tempCutoff; }
while(!in2.eof()) {
string tempName;
- in2 >> tempName; gobble(in2);
+ in2 >> tempName; m->gobble(in2);
if (labels.count(tempName) == 0) { labels.insert(tempName); }
}
in2.close();
#else
listFileNames = cluster(distName, labels); //clusters individual files and returns names of list files
#endif
-
+ #endif
if (m->control_pressed) { for (int i = 0; i < listFileNames.size(); i++) { remove(listFileNames[i].c_str()); } return 0; }
+ if (saveCutoff != cutoff) { m->mothurOut("Cutoff was " + toString(saveCutoff) + " changed cutoff to " + toString(cutoff)); m->mothurOutEndLine(); }
+
m->mothurOut("It took " + toString(time(NULL) - estart) + " seconds to cluster"); m->mothurOutEndLine();
//****************** merge list file and create rabund and sabund files ******************************//
estart = time(NULL);
m->mothurOut("Merging the clustered files..."); m->mothurOutEndLine();
+ #ifdef USE_MPI
+ if (pid == 0) { //only process 0 merges
+ #endif
+
ListVector* listSingle;
map<float, int> labelBins = completeListFile(listFileNames, singletonName, labels, listSingle); //returns map of label to numBins
m->mothurOut("Output File Names: "); m->mothurOutEndLine();
for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); }
m->mothurOutEndLine();
+
+ #ifdef USE_MPI
+ } //only process 0 merges
+
+ //make everyone wait
+ MPI_Barrier(MPI_COMM_WORLD);
+ #endif
return 0;
}
//read in singletons
if (singleton != "none") {
ifstream in;
- openInputFile(singleton, in);
+ m->openInputFile(singleton, in);
string firstCol, secondCol;
listSingle = new ListVector();
while (!in.eof()) {
- in >> firstCol >> secondCol; gobble(in);
+ in >> firstCol >> secondCol; m->gobble(in);
listSingle->push_back(secondCol);
}
in.close();
if ((*it != "unique") && (convertTestFloat(*it, temp) == true)) { convert(*it, temp); }
else if (*it == "unique") { temp = -1.0; }
-
- orderFloat.push_back(temp);
- labelBin[temp] = numSingleBins; //initialize numbins
+
+ if (temp <= cutoff) {
+ orderFloat.push_back(temp);
+ labelBin[temp] = numSingleBins; //initialize numbins
+ }
}
//sort order
string filledInList = listNames[k] + "filledInTemp";
ofstream outFilled;
- openOutputFile(filledInList, outFilled);
+ m->openOutputFile(filledInList, outFilled);
//for each label needed
for(int l = 0; l < orderFloat.size(); l++){
//**********************************************************************************************************************
int ClusterSplitCommand::mergeLists(vector<string> listNames, map<float, int> userLabels, ListVector* listSingle){
try {
- if (outputDir == "") { outputDir += hasPath(distfile); }
- fileroot = outputDir + getRootName(getSimpleName(distfile));
+ if (outputDir == "") { outputDir += m->hasPath(distfile); }
+ fileroot = outputDir + m->getRootName(m->getSimpleName(distfile));
- openOutputFile(fileroot+ tag + ".sabund", outSabund);
- openOutputFile(fileroot+ tag + ".rabund", outRabund);
- openOutputFile(fileroot+ tag + ".list", outList);
+ m->openOutputFile(fileroot+ tag + ".sabund", outSabund);
+ m->openOutputFile(fileroot+ tag + ".rabund", outRabund);
+ m->openOutputFile(fileroot+ tag + ".list", outList);
outputNames.push_back(fileroot+ tag + ".sabund");
outputNames.push_back(fileroot+ tag + ".rabund");
if (listSingle != NULL) {
for (int j = 0; j < listSingle->getNumBins(); j++) {
outList << listSingle->get(j) << '\t';
- rabund->push_back(getNumNames(listSingle->get(j)));
+ rabund->push_back(m->getNumNames(listSingle->get(j)));
}
}
else {
for (int j = 0; j < list->getNumBins(); j++) {
outList << list->get(j) << '\t';
- rabund->push_back(getNumNames(list->get(j)));
+ rabund->push_back(m->getNumNames(list->get(j)));
}
delete list;
}
RAbundVector oldRAbund = oldList->getRAbundVector();
oldRAbund.setLabel(label);
- if (isTrue(showabund)) {
+ if (m->isTrue(showabund)) {
oldRAbund.getSAbundVector().print(cout);
}
oldRAbund.print(outRabund);
//write out names to file
string filename = toString(getpid()) + ".temp";
ofstream out;
- openOutputFile(filename, out);
+ m->openOutputFile(filename, out);
out << tag << endl;
for (int j = 0; j < listFileNames.size(); j++) { out << listFileNames[j] << endl; }
out.close();
//print out labels
ofstream outLabels;
filename = toString(getpid()) + ".temp.labels";
- openOutputFile(filename, outLabels);
-
+ m->openOutputFile(filename, outLabels);
+
+ outLabels << cutoff << endl;
for (set<string>::iterator it = labels.begin(); it != labels.end(); it++) {
outLabels << (*it) << endl;
}
vector<string> listFileNames;
+ double smallestCutoff = cutoff;
+
//cluster each distance file
for (int i = 0; i < distNames.size(); i++) {
+ if (m->control_pressed) { return listFileNames; }
string thisNamefile = distNames[i].begin()->second;
string thisDistFile = distNames[i].begin()->first;
globaldata->setNameFile(thisNamefile);
globaldata->setColumnFile(thisDistFile); globaldata->setFormat("column");
+ #ifdef USE_MPI
+ int pid;
+ MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
+
+ //output your files too
+ if (pid != 0) {
+ cout << endl << "Reading " << thisDistFile << endl;
+ }
+ #endif
+
m->mothurOutEndLine(); m->mothurOut("Reading " + thisDistFile); m->mothurOutEndLine();
ReadMatrix* read = new ReadColumnMatrix(thisDistFile);
delete read;
delete nameMap;
+
+ #ifdef USE_MPI
+ //output your files too
+ if (pid != 0) {
+ cout << endl << "Clustering " << thisDistFile << endl;
+ }
+ #endif
+
m->mothurOutEndLine(); m->mothurOut("Clustering " + thisDistFile); m->mothurOutEndLine();
rabund = new RAbundVector(list->getRAbundVector());
else if(method == "average"){ cluster = new AverageLinkage(rabund, list, matrix, cutoff, method); }
tag = cluster->getTag();
- if (outputDir == "") { outputDir += hasPath(thisDistFile); }
- fileroot = outputDir + getRootName(getSimpleName(thisDistFile));
+ if (outputDir == "") { outputDir += m->hasPath(thisDistFile); }
+ fileroot = outputDir + m->getRootName(m->getSimpleName(thisDistFile));
ofstream listFile;
- openOutputFile(fileroot+ tag + ".list", listFile);
+ m->openOutputFile(fileroot+ tag + ".list", listFile);
listFileNames.push_back(fileroot+ tag + ".list");
listFileNames.clear(); return listFileNames;
}
- cluster->update(cutoff);
+ cluster->update(saveCutoff);
float dist = matrix->getSmallDist();
float rndDist;
if (hard) {
- rndDist = ceilDist(dist, precision);
+ rndDist = m->ceilDist(dist, precision);
}else{
- rndDist = roundDist(dist, precision);
+ rndDist = m->roundDist(dist, precision);
}
if(previousDist <= 0.0000 && dist != previousDist){
remove(thisDistFile.c_str());
remove(thisNamefile.c_str());
+
+ if (saveCutoff != cutoff) {
+ if (hard) { saveCutoff = m->ceilDist(saveCutoff, precision); }
+ else { saveCutoff = m->roundDist(saveCutoff, precision); }
+
+ m->mothurOut("Cutoff was " + toString(cutoff) + " changed cutoff to " + toString(saveCutoff)); m->mothurOutEndLine();
+ }
+
+ if (saveCutoff < smallestCutoff) { smallestCutoff = saveCutoff; }
}
+ cutoff = smallestCutoff;
return listFileNames;
projects / mothur.git / blobdiff