*/
#include "clustersplitcommand.h"
-#include "readcluster.h"
-#include "splitmatrix.h"
-#include "readphylip.h"
-#include "readcolumn.h"
-#include "readmatrix.hpp"
-#include "inputdata.h"
//**********************************************************************************************************************
vector<string> ClusterSplitCommand::setParameters(){
try {
- CommandParameter ptaxonomy("taxonomy", "InputTypes", "", "", "none", "none", "FastaTaxName",false,false); parameters.push_back(ptaxonomy);
- CommandParameter pphylip("phylip", "InputTypes", "", "", "PhylipColumnFasta", "PhylipColumnFasta", "none",false,false); parameters.push_back(pphylip);
- CommandParameter pfasta("fasta", "InputTypes", "", "", "PhylipColumnFasta", "PhylipColumnFasta", "FastaTaxName",false,false); parameters.push_back(pfasta);
- CommandParameter pname("name", "InputTypes", "", "", "none", "none", "ColumnName-FastaTaxName",false,false); parameters.push_back(pname);
- CommandParameter pcolumn("column", "InputTypes", "", "", "PhylipColumnFasta", "PhylipColumnFasta", "ColumnName",false,false); parameters.push_back(pcolumn);
- CommandParameter ptaxlevel("taxlevel", "Number", "", "1", "", "", "",false,false); parameters.push_back(ptaxlevel);
- CommandParameter psplitmethod("splitmethod", "Multiple", "classify-fasta-distance", "distance", "", "", "",false,false); parameters.push_back(psplitmethod);
- CommandParameter plarge("large", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(plarge);
- CommandParameter pshowabund("showabund", "Boolean", "", "T", "", "", "",false,false); parameters.push_back(pshowabund);
- CommandParameter ptiming("timing", "Boolean", "", "F", "", "", "",false,false); parameters.push_back(ptiming);
- CommandParameter pprocessors("processors", "Number", "", "1", "", "", "",false,false); parameters.push_back(pprocessors);
- CommandParameter pcutoff("cutoff", "Number", "", "10", "", "", "",false,false); parameters.push_back(pcutoff);
- CommandParameter pprecision("precision", "Number", "", "100", "", "", "",false,false); parameters.push_back(pprecision);
- CommandParameter pmethod("method", "Multiple", "furthest-nearest-average-weighted", "average", "", "", "",false,false); parameters.push_back(pmethod);
- CommandParameter phard("hard", "Boolean", "", "T", "", "", "",false,false); parameters.push_back(phard);
- CommandParameter pinputdir("inputdir", "String", "", "", "", "", "",false,false); parameters.push_back(pinputdir);
- CommandParameter poutputdir("outputdir", "String", "", "", "", "", "",false,false); parameters.push_back(poutputdir);
+ CommandParameter ptaxonomy("taxonomy", "InputTypes", "", "", "none", "none", "FastaTaxName","",false,false,true); parameters.push_back(ptaxonomy);
+ CommandParameter pphylip("phylip", "InputTypes", "", "", "PhylipColumnFasta", "PhylipColumnFasta", "none","list",false,false,true); parameters.push_back(pphylip);
+ CommandParameter pfasta("fasta", "InputTypes", "", "", "PhylipColumnFasta", "PhylipColumnFasta", "FastaTaxName","list",false,false,true); parameters.push_back(pfasta);
+ CommandParameter pname("name", "InputTypes", "", "", "NameCount", "none", "ColumnName-FastaTaxName","rabund-sabund",false,false,true); parameters.push_back(pname);
+ CommandParameter pcount("count", "InputTypes", "", "", "NameCount", "none", "","",false,false,true); parameters.push_back(pcount);
+ CommandParameter pcolumn("column", "InputTypes", "", "", "PhylipColumnFasta", "PhylipColumnFasta", "ColumnName","list",false,false,true); parameters.push_back(pcolumn);
+ CommandParameter ptaxlevel("taxlevel", "Number", "", "3", "", "", "","",false,false,true); parameters.push_back(ptaxlevel);
+ CommandParameter psplitmethod("splitmethod", "Multiple", "classify-fasta-distance", "distance", "", "", "","",false,false,true); parameters.push_back(psplitmethod);
+ CommandParameter plarge("large", "Boolean", "", "F", "", "", "","",false,false); parameters.push_back(plarge);
+ CommandParameter pshowabund("showabund", "Boolean", "", "T", "", "", "","",false,false); parameters.push_back(pshowabund);
+ CommandParameter pcluster("cluster", "Boolean", "", "T", "", "", "","",false,false); parameters.push_back(pcluster);
+ CommandParameter ptiming("timing", "Boolean", "", "F", "", "", "","",false,false); parameters.push_back(ptiming);
+ CommandParameter pprocessors("processors", "Number", "", "1", "", "", "","",false,false,true); parameters.push_back(pprocessors);
+ CommandParameter pcutoff("cutoff", "Number", "", "0.25", "", "", "","",false,false,true); parameters.push_back(pcutoff);
+ CommandParameter pprecision("precision", "Number", "", "100", "", "", "","",false,false); parameters.push_back(pprecision);
+ CommandParameter pmethod("method", "Multiple", "furthest-nearest-average-weighted", "average", "", "", "","",false,false); parameters.push_back(pmethod);
+ CommandParameter phard("hard", "Boolean", "", "T", "", "", "","",false,false); parameters.push_back(phard);
+ CommandParameter pclassic("classic", "Boolean", "", "F", "", "", "","",false,false); parameters.push_back(pclassic);
+ CommandParameter pinputdir("inputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(pinputdir);
+ CommandParameter poutputdir("outputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(poutputdir);
vector<string> myArray;
for (int i = 0; i < parameters.size(); i++) { myArray.push_back(parameters[i].name); }
string ClusterSplitCommand::getHelpString(){
try {
string helpString = "";
- helpString += "The cluster.split command parameter options are fasta, phylip, column, name, cutoff, precision, method, splitmethod, taxonomy, taxlevel, showabund, timing, hard, large, processors. Fasta or Phylip or column and name are required.\n";
+ helpString += "The cluster.split command parameter options are fasta, phylip, column, name, count, cutoff, precision, method, splitmethod, taxonomy, taxlevel, showabund, timing, hard, large, cluster, processors. Fasta or Phylip or column and name are required.\n";
helpString += "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";
helpString += "For the distance file method, you need only provide your distance file and mothur will split the file into distinct groups. \n";
helpString += "For the classification method, you need to provide your distance file and taxonomy file, and set the splitmethod to classify. \n";
helpString += "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";
helpString += "The phylip and column parameter allow you to enter your distance file. \n";
helpString += "The fasta parameter allows you to enter your aligned fasta file. \n";
- helpString += "The name parameter allows you to enter your name file and is required if your distance file is in column format. \n";
- helpString += "The cutoff parameter allow you to set the distance you want to cluster to, default is 10.0. \n";
+ helpString += "The name parameter allows you to enter your name file. \n";
+ helpString += "The count parameter allows you to enter your count file. \n A count or name file is required if your distance file is in column format";
+ helpString += "The cluster parameter allows you to indicate whether you want to run the clustering or just split the distance matrix, default=t";
+ helpString += "The cutoff parameter allow you to set the distance you want to cluster to, default is 0.25. \n";
helpString += "The precision parameter allows you specify the precision of the precision of the distances outputted, default=100, meaning 2 decimal places. \n";
- helpString += "The method allows you to specify what clustering algorythm you want to use, default=average, option furthest, nearest, or average. \n";
+ helpString += "The method allows you to specify what clustering algorithm you want to use, default=average, option furthest, nearest, or average. \n";
helpString += "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";
helpString += "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";
- helpString += "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";
+ helpString += "The taxlevel parameter allows you to specify the taxonomy level you want to use to split the distance file, default=3, meaning use the first taxon in each list. \n";
helpString += "The large parameter allows you to indicate that your distance matrix is too large to fit in RAM. The default value is false.\n";
+ helpString += "The classic parameter allows you to indicate that you want to run your files with cluster.classic. It is only valid with splitmethod=fasta. Default=f.\n";
#ifdef USE_MPI
helpString += "When using MPI, the processors parameter is set to the number of MPI processes running. \n";
#endif
}
}
//**********************************************************************************************************************
+string ClusterSplitCommand::getOutputPattern(string type) {
+ try {
+ string pattern = "";
+
+ if (type == "list") { pattern = "[filename],[clustertag],list-[filename],[clustertag],[tag2],list"; }
+ else if (type == "rabund") { pattern = "[filename],[clustertag],rabund"; }
+ else if (type == "sabund") { pattern = "[filename],[clustertag],sabund"; }
+ else if (type == "column") { pattern = "[filename],dist"; }
+ else { m->mothurOut("[ERROR]: No definition for type " + type + " output pattern.\n"); m->control_pressed = true; }
+
+ return pattern;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "ClusterSplitCommand", "getOutputPattern");
+ exit(1);
+ }
+}
+//**********************************************************************************************************************
ClusterSplitCommand::ClusterSplitCommand(){
try {
abort = true; calledHelp = true;
//if the user has not given a path then, add inputdir. else leave path alone.
if (path == "") { parameters["fasta"] = inputDir + it->second; }
}
+
+ it = parameters.find("count");
+ //user has given a template file
+ if(it != parameters.end()){
+ path = m->hasPath(it->second);
+ //if the user has not given a path then, add inputdir. else leave path alone.
+ if (path == "") { parameters["count"] = inputDir + it->second; }
+ }
}
//check for required parameters
else { distfile = columnfile; format = "column"; m->setColumnFile(columnfile); }
namefile = validParameter.validFile(parameters, "name", true);
- if (namefile == "not open") { abort = true; }
+ if (namefile == "not open") { abort = true; namefile = "";}
else if (namefile == "not found") { namefile = ""; }
else { m->setNameFile(namefile); }
+
+ countfile = validParameter.validFile(parameters, "count", true);
+ if (countfile == "not open") { abort = true; countfile = "";}
+ else if (countfile == "not found") { countfile = ""; }
+ else { m->setCountTableFile(countfile); }
fastafile = validParameter.validFile(parameters, "fasta", true);
if (fastafile == "not open") { abort = true; }
else { distfile = fastafile; splitmethod = "fasta"; m->setFastaFile(fastafile); }
taxFile = validParameter.validFile(parameters, "taxonomy", true);
- if (taxFile == "not open") { abort = true; }
+ if (taxFile == "not open") { taxFile = ""; abort = true; }
else if (taxFile == "not found") { taxFile = ""; }
- else { m->setTaxonomyFile(taxFile); }
+ else { m->setTaxonomyFile(taxFile); if (splitmethod != "fasta") { splitmethod = "classify"; } }
if ((phylipfile == "") && (columnfile == "") && (fastafile == "")) {
//is there are current file available for either of these?
}
}
else if ((phylipfile != "") && (columnfile != "") && (fastafile != "")) { m->mothurOut("When executing a cluster.split command you must enter ONLY ONE of the following: fasta, phylip or column."); m->mothurOutEndLine(); abort = true; }
-
+
+ if ((countfile != "") && (namefile != "")) { m->mothurOut("When executing a cluster.split command you must enter ONLY ONE of the following: count or name."); m->mothurOutEndLine(); abort = true; }
+
if (columnfile != "") {
- if (namefile == "") {
+ if ((namefile == "") && (countfile == "")) {
namefile = m->getNameFile();
if (namefile != "") { m->mothurOut("Using " + namefile + " as input file for the name parameter."); m->mothurOutEndLine(); }
else {
- m->mothurOut("You need to provide a namefile if you are going to use the column format."); m->mothurOutEndLine();
- abort = true;
+ countfile = m->getCountTableFile();
+ if (countfile != "") { m->mothurOut("Using " + countfile + " as input file for the count parameter."); m->mothurOutEndLine(); }
+ else {
+ m->mothurOut("You need to provide a namefile or countfile if you are going to use the column format."); m->mothurOutEndLine();
+ abort = true;
+ }
}
}
}
}
}
- if (namefile == "") {
+ if ((namefile == "") && (countfile == "")) {
namefile = m->getNameFile();
if (namefile != "") { m->mothurOut("Using " + namefile + " as input file for the name parameter."); m->mothurOutEndLine(); }
else {
- m->mothurOut("You need to provide a namefile if you are if you are using a fasta file to generate the split."); m->mothurOutEndLine();
- abort = true;
+ countfile = m->getCountTableFile();
+ if (countfile != "") { m->mothurOut("Using " + countfile + " as input file for the count parameter."); m->mothurOutEndLine(); }
+ else {
+ m->mothurOut("You need to provide a namefile or countfile if you are going to use the fasta file to generate the split."); m->mothurOutEndLine();
+ abort = true;
+ }
}
}
}
if (temp == "not found") { temp = "100"; }
//saves precision legnth for formatting below
length = temp.length();
- convert(temp, precision);
+ m->mothurConvert(temp, precision);
temp = validParameter.validFile(parameters, "hard", false); if (temp == "not found") { temp = "T"; }
hard = m->isTrue(temp);
temp = validParameter.validFile(parameters, "large", false); if (temp == "not found") { temp = "F"; }
large = m->isTrue(temp);
-
+
temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = m->getProcessors(); }
m->setProcessors(temp);
- convert(temp, processors);
+ m->mothurConvert(temp, processors);
temp = validParameter.validFile(parameters, "splitmethod", false);
- if (splitmethod != "fasta") {
+ if ((splitmethod != "fasta") && (splitmethod != "classify")) {
if (temp == "not found") { splitmethod = "distance"; }
else { splitmethod = temp; }
}
- temp = validParameter.validFile(parameters, "cutoff", false); if (temp == "not found") { temp = "10"; }
- convert(temp, cutoff);
+ temp = validParameter.validFile(parameters, "classic", false); if (temp == "not found") { temp = "F"; }
+ classic = m->isTrue(temp);
+
+ if ((splitmethod != "fasta") && classic) { m->mothurOut("splitmethod must be fasta to use cluster.classic.\n"); abort=true; }
+
+ temp = validParameter.validFile(parameters, "cutoff", false); if (temp == "not found") { temp = "0.25"; }
+ m->mothurConvert(temp, cutoff);
cutoff += (5 / (precision * 10.0));
- temp = validParameter.validFile(parameters, "taxlevel", false); if (temp == "not found") { temp = "1"; }
- convert(temp, taxLevelCutoff);
+ temp = validParameter.validFile(parameters, "taxlevel", false); if (temp == "not found") { temp = "3"; }
+ m->mothurConvert(temp, taxLevelCutoff);
method = validParameter.validFile(parameters, "method", false); if (method == "not found") { method = "average"; }
- if ((method == "furthest") || (method == "nearest") || (method == "average")) { }
+ if ((method == "furthest") || (method == "nearest") || (method == "average")) { m->mothurOut("Using splitmethod " + splitmethod + ".\n"); }
else { m->mothurOut("Not a valid clustering method. Valid clustering algorithms are furthest, nearest or average."); m->mothurOutEndLine(); abort = true; }
if ((splitmethod == "distance") || (splitmethod == "classify") || (splitmethod == "fasta")) { }
showabund = validParameter.validFile(parameters, "showabund", false);
if (showabund == "not found") { showabund = "T"; }
+
+ temp = validParameter.validFile(parameters, "cluster", false); if (temp == "not found") { temp = "T"; }
+ runCluster = m->isTrue(temp);
timing = validParameter.validFile(parameters, "timing", false);
if (timing == "not found") { timing = "F"; }
//if no names file given with phylip file, create it
ListVector* listToMakeNameFile = convert->getListVector();
- if (namefile == "") { //you need to make a namefile for split matrix
+ if ((namefile == "") && (countfile == "")) { //you need to make a namefile for split matrix
ofstream out;
namefile = phylipfile + ".names";
m->openOutputFile(namefile, out);
//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, cutoff, splitmethod, processors, outputDir); }
+ if (splitmethod == "distance") { split = new SplitMatrix(distfile, namefile, countfile, taxFile, cutoff, splitmethod, large); }
+ else if (splitmethod == "classify") { split = new SplitMatrix(distfile, namefile, countfile, taxFile, taxLevelCutoff, splitmethod, large); }
+ else if (splitmethod == "fasta") { split = new SplitMatrix(fastafile, namefile, countfile, taxFile, taxLevelCutoff, cutoff, splitmethod, processors, classic, outputDir); }
else { m->mothurOut("Not a valid splitting method. Valid splitting algorithms are distance, classify or fasta."); m->mothurOutEndLine(); return 0; }
split->split();
vector< map<string, string> > distName = split->getDistanceFiles(); //returns map of distance files -> namefile sorted by distance file size
delete split;
+ if (m->debug) { m->mothurOut("[DEBUG]: distName.size() = " + toString(distName.size()) + ".\n"); }
+
//output a merged distance file
- if (splitmethod == "fasta") { createMergedDistanceFile(distName); }
-
+ //if (splitmethod == "fasta") { createMergedDistanceFile(distName); }
if (m->control_pressed) { return 0; }
m->mothurOut("It took " + toString(time(NULL) - estart) + " seconds to split the distance file."); m->mothurOutEndLine();
estart = time(NULL);
-
+
+ if (!runCluster) {
+
+ m->mothurOutEndLine();
+ m->mothurOut("Output File Names: "); m->mothurOutEndLine();
+ for (int i = 0; i < distName.size(); i++) { m->mothurOut(distName[i].begin()->first); m->mothurOutEndLine(); m->mothurOut(distName[i].begin()->second); m->mothurOutEndLine(); }
+ m->mothurOutEndLine();
+ return 0;
+
+ }
+
//****************** break up files between processes and cluster each file set ******************************//
#ifdef USE_MPI
////you are process 0 from above////
MPI_Barrier(MPI_COMM_WORLD);
#else
-
- #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
+ ///////////////////// WINDOWS CAN ONLY USE 1 PROCESSORS ACCESS VIOLATION UNRESOLVED ///////////////////////
+ //sanity check
+ if (processors > distName.size()) { processors = distName.size(); }
+
+ #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
if(processors == 1){
listFileNames = cluster(distName, labels); //clusters individual files and returns names of list files
}else{
- 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
- 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()); }
- }
-
- createProcesses(dividedNames);
-
- if (m->control_pressed) { return 0; }
-
- //get list of list file names from each process
- for(int i=0;i<processors;i++){
- string filename = toString(processIDS[i]) + ".temp";
- ifstream in;
- m->openInputFile(filename, in);
-
- in >> tag; m->gobble(in);
-
- while(!in.eof()) {
- string tempName;
- in >> tempName; m->gobble(in);
- listFileNames.push_back(tempName);
- }
- in.close();
- m->mothurRemove((toString(processIDS[i]) + ".temp"));
-
- //get labels
- filename = toString(processIDS[i]) + ".temp.labels";
- ifstream in2;
- m->openInputFile(filename, in2);
-
- float tempCutoff;
- in2 >> tempCutoff; m->gobble(in2);
- if (tempCutoff < cutoff) { cutoff = tempCutoff; }
-
- while(!in2.eof()) {
- string tempName;
- in2 >> tempName; m->gobble(in2);
- if (labels.count(tempName) == 0) { labels.insert(tempName); }
- }
- in2.close();
- m->mothurRemove((toString(processIDS[i]) + ".temp.labels"));
- }
- }
+ listFileNames = createProcesses(distName, labels);
+ }
#else
listFileNames = cluster(distName, labels); //clusters individual files and returns names of list files
#endif
//read in singletons
if (singleton != "none") {
- ifstream in;
- m->openInputFile(singleton, in);
+
+ ifstream in;
+ m->openInputFile(singleton, in);
string firstCol, secondCol;
listSingle = new ListVector();
+
+ if (countfile != "") { m->getline(in); m->gobble(in); }
+
while (!in.eof()) {
- in >> firstCol >> secondCol; m->gobble(in);
- listSingle->push_back(secondCol);
+ in >> firstCol >> secondCol; m->getline(in); m->gobble(in);
+ if (countfile == "") { listSingle->push_back(secondCol); }
+ else { listSingle->push_back(firstCol); }
}
+
in.close();
m->mothurRemove(singleton);
if (outputDir == "") { outputDir += m->hasPath(distfile); }
fileroot = outputDir + m->getRootName(m->getSimpleName(distfile));
- m->openOutputFile(fileroot+ tag + ".sabund", outSabund);
- m->openOutputFile(fileroot+ tag + ".rabund", outRabund);
- m->openOutputFile(fileroot+ tag + ".list", outList);
-
- outputNames.push_back(fileroot+ tag + ".sabund"); outputTypes["list"].push_back(fileroot+ tag + ".list");
- outputNames.push_back(fileroot+ tag + ".rabund"); outputTypes["rabund"].push_back(fileroot+ tag + ".rabund");
- outputNames.push_back(fileroot+ tag + ".list"); outputTypes["sabund"].push_back(fileroot+ tag + ".sabund");
+ map<string, string> variables;
+ variables["[filename]"] = fileroot;
+ variables["[clustertag]"] = tag;
+ string sabundFileName = getOutputFileName("sabund", variables);
+ string rabundFileName = getOutputFileName("rabund", variables);
+ if (countfile != "") { variables["[tag2]"] = "unique_list"; }
+ string listFileName = getOutputFileName("list", variables);
+
+ if (countfile == "") {
+ m->openOutputFile(sabundFileName, outSabund);
+ m->openOutputFile(rabundFileName, outRabund);
+ outputNames.push_back(sabundFileName); outputTypes["sabund"].push_back(sabundFileName);
+ outputNames.push_back(rabundFileName); outputTypes["rabund"].push_back(rabundFileName);
+
+ }
+ m->openOutputFile(listFileName, outList);
+ outputNames.push_back(listFileName); outputTypes["list"].push_back(listFileName);
+
map<float, int>::iterator itLabel;
if (itLabel->first == -1) { thisLabel = "unique"; }
else { thisLabel = toString(itLabel->first, length-1); }
- outList << thisLabel << '\t' << itLabel->second << '\t';
-
- RAbundVector* rabund = new RAbundVector();
- rabund->setLabel(thisLabel);
+ //outList << thisLabel << '\t' << itLabel->second << '\t';
+
+ RAbundVector* rabund = NULL;
+ ListVector completeList;
+ completeList.setLabel(thisLabel);
+
+ if (countfile == "") {
+ rabund = new RAbundVector();
+ rabund->setLabel(thisLabel);
+ }
//add in singletons
if (listSingle != NULL) {
for (int j = 0; j < listSingle->getNumBins(); j++) {
- outList << listSingle->get(j) << '\t';
- rabund->push_back(m->getNumNames(listSingle->get(j)));
+ //outList << listSingle->get(j) << '\t';
+ completeList.push_back(listSingle->get(j));
+ if (countfile == "") { rabund->push_back(m->getNumNames(listSingle->get(j))); }
}
}
//get the list info from each file
for (int k = 0; k < listNames.size(); k++) {
- if (m->control_pressed) { if (listSingle != NULL) { delete listSingle; } for (int i = 0; i < listNames.size(); i++) { m->mothurRemove(listNames[i]); } delete rabund; return 0; }
+ if (m->control_pressed) { if (listSingle != NULL) { delete listSingle; } for (int i = 0; i < listNames.size(); i++) { m->mothurRemove(listNames[i]); } if (rabund != NULL) { delete rabund; } return 0; }
InputData* input = new InputData(listNames[k], "list");
ListVector* list = input->getListVector(thisLabel);
if (list == NULL) { m->mothurOut("Error merging listvectors in file " + listNames[k]); m->mothurOutEndLine(); }
else {
for (int j = 0; j < list->getNumBins(); j++) {
- outList << list->get(j) << '\t';
- rabund->push_back(m->getNumNames(list->get(j)));
+ //outList << list->get(j) << '\t';
+ completeList.push_back(list->get(j));
+ if (countfile == "") { rabund->push_back(m->getNumNames(list->get(j))); }
}
delete list;
}
delete input;
}
- SAbundVector sabund = rabund->getSAbundVector();
-
- sabund.print(outSabund);
- rabund->print(outRabund);
- outList << endl;
+ if (countfile == "") {
+ SAbundVector sabund = rabund->getSAbundVector();
+ sabund.print(outSabund);
+ rabund->print(outRabund);
+ }
+ //outList << endl;
+ completeList.print(outList);
- delete rabund;
+ if (rabund != NULL) { delete rabund; }
}
outList.close();
- outRabund.close();
- outSabund.close();
-
+ if (countfile == "") {
+ outRabund.close();
+ outSabund.close();
+ }
if (listSingle != NULL) { delete listSingle; }
for (int i = 0; i < listNames.size(); i++) { m->mothurRemove(listNames[i]); }
}
}
//**********************************************************************************************************************
-int ClusterSplitCommand::createProcesses(vector < vector < map<string, string> > > dividedNames){
+vector<string> ClusterSplitCommand::createProcesses(vector< map<string, string> > distName, set<string>& labels){
try {
+
+ vector<string> listFiles;
+ 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
+ for (int i = 0; i < distName.size(); i++) {
+ //cout << i << endl;
+ int processToAssign = (i+1) % processors;
+ if (processToAssign == 0) { processToAssign = processors; }
+
+ dividedNames[(processToAssign-1)].push_back(distName[i]);
+ if ((processToAssign-1) == 1) { m->mothurOut(distName[i].begin()->first + "\n"); }
+ }
+
+ //now lets reverse the order of ever other process, so we balance big files running with little ones
+ for (int i = 0; i < processors; i++) {
+ //cout << i << endl;
+ int remainder = ((i+1) % processors);
+ if (remainder) { reverse(dividedNames[i].begin(), dividedNames[i].end()); }
+ }
+
+ if (m->control_pressed) { return listFiles; }
- #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
- int process = 0;
- int exitCommand = 1;
+ #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
+ int process = 1;
processIDS.clear();
//loop through and create all the processes you want
}
}
+ //do your part
+ listFiles = cluster(dividedNames[0], labels);
+
//force parent to wait until all the processes are done
- for (int i=0;i<processors;i++) {
+ for (int i=0;i< processIDS.size();i++) {
int temp = processIDS[i];
wait(&temp);
}
+
+ //get list of list file names from each process
+ for(int i=0;i<processIDS.size();i++){
+ string filename = toString(processIDS[i]) + ".temp";
+ ifstream in;
+ m->openInputFile(filename, in);
+
+ in >> tag; m->gobble(in);
+
+ while(!in.eof()) {
+ string tempName;
+ in >> tempName; m->gobble(in);
+ listFiles.push_back(tempName);
+ }
+ in.close();
+ m->mothurRemove((toString(processIDS[i]) + ".temp"));
+
+ //get labels
+ filename = toString(processIDS[i]) + ".temp.labels";
+ ifstream in2;
+ m->openInputFile(filename, in2);
+
+ float tempCutoff;
+ in2 >> tempCutoff; m->gobble(in2);
+ if (tempCutoff < cutoff) { cutoff = tempCutoff; }
+
+ while(!in2.eof()) {
+ string tempName;
+ in2 >> tempName; m->gobble(in2);
+ if (labels.count(tempName) == 0) { labels.insert(tempName); }
+ }
+ in2.close();
+ m->mothurRemove((toString(processIDS[i]) + ".temp.labels"));
+ }
+
+
+ #else
+
+ //////////////////////////////////////////////////////////////////////////////////////////////////////
+ //Windows version shared memory, so be careful when passing variables through the clusterData struct.
+ //Above fork() will clone, so memory is separate, but that's not the case with windows,
+ //Taking advantage of shared memory to allow both threads to add labels.
+ //////////////////////////////////////////////////////////////////////////////////////////////////////
+ /*
+ vector<clusterData*> pDataArray;
+ DWORD dwThreadIdArray[processors-1];
+ HANDLE hThreadArray[processors-1];
- return exitCommand;
+ //Create processor worker threads.
+ for( int i=1; i<processors; i++ ){
+ // Allocate memory for thread data.
+ clusterData* tempCluster = new clusterData(dividedNames[i], m, cutoff, method, outputDir, hard, precision, length, i);
+ pDataArray.push_back(tempCluster);
+ processIDS.push_back(i);
+
+ //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-1] = CreateThread(NULL, 0, MyClusterThreadFunction, pDataArray[i-1], 0, &dwThreadIdArray[i-1]);
+
+ }
+
+ //do your part
+ listFiles = cluster(dividedNames[0], labels);
+
+ //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++){
+ //get tag
+ tag = pDataArray[i]->tag;
+ //get listfiles created
+ for(int j=0; j < pDataArray[i]->listFiles.size(); j++){ listFiles.push_back(pDataArray[i]->listFiles[j]); }
+ //get labels
+ set<string>::iterator it;
+ for(it = pDataArray[i]->labels.begin(); it != pDataArray[i]->labels.end(); it++){ labels.insert(*it); }
+ //check cutoff
+ if (pDataArray[i]->cutoff < cutoff) { cutoff = pDataArray[i]->cutoff; }
+ CloseHandle(hThreadArray[i]);
+ delete pDataArray[i];
+ }
+*/
#endif
+
+ return listFiles;
}
catch(exception& e) {
vector<string> ClusterSplitCommand::cluster(vector< map<string, string> > distNames, set<string>& labels){
try {
- Cluster* cluster;
- SparseMatrix* matrix;
- ListVector* list;
- ListVector oldList;
- RAbundVector* rabund;
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;
-
- #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);
- read->setCutoff(cutoff);
-
- NameAssignment* nameMap = new NameAssignment(thisNamefile);
- nameMap->readMap();
- read->read(nameMap);
- if (m->control_pressed) { delete read; delete nameMap; return listFileNames; }
-
- list = read->getListVector();
- oldList = *list;
- matrix = read->getMatrix();
-
- 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());
-
- //create cluster
- if (method == "furthest") { cluster = new CompleteLinkage(rabund, list, matrix, cutoff, method); }
- else if(method == "nearest"){ cluster = new SingleLinkage(rabund, list, matrix, cutoff, method); }
- else if(method == "average"){ cluster = new AverageLinkage(rabund, list, matrix, cutoff, method); }
- tag = cluster->getTag();
-
- if (outputDir == "") { outputDir += m->hasPath(thisDistFile); }
- fileroot = outputDir + m->getRootName(m->getSimpleName(thisDistFile));
-
- ofstream listFile;
- m->openOutputFile(fileroot+ tag + ".list", listFile);
-
- listFileNames.push_back(fileroot+ tag + ".list");
-
- float previousDist = 0.00000;
- float rndPreviousDist = 0.00000;
-
- oldList = *list;
-
- print_start = true;
- start = time(NULL);
- double saveCutoff = cutoff;
-
- while (matrix->getSmallDist() < cutoff && matrix->getNNodes() > 0){
-
- if (m->control_pressed) { //clean up
- delete matrix; delete list; delete cluster; delete rabund;
- listFile.close();
- for (int i = 0; i < listFileNames.size(); i++) { m->mothurRemove(listFileNames[i]); }
- listFileNames.clear(); return listFileNames;
- }
-
- cluster->update(saveCutoff);
-
- float dist = matrix->getSmallDist();
- float rndDist;
- if (hard) {
- rndDist = m->ceilDist(dist, precision);
- }else{
- rndDist = m->roundDist(dist, precision);
- }
-
- if(previousDist <= 0.0000 && dist != previousDist){
- oldList.setLabel("unique");
- oldList.print(listFile);
- if (labels.count("unique") == 0) { labels.insert("unique"); }
- }
- else if(rndDist != rndPreviousDist){
- oldList.setLabel(toString(rndPreviousDist, length-1));
- oldList.print(listFile);
- if (labels.count(toString(rndPreviousDist, length-1)) == 0) { labels.insert(toString(rndPreviousDist, length-1)); }
- }
-
- previousDist = dist;
- rndPreviousDist = rndDist;
- oldList = *list;
- }
+ string listFileName = "";
+ if (classic) { listFileName = clusterClassicFile(thisDistFile, thisNamefile, labels, smallestCutoff); }
+ else { listFileName = clusterFile(thisDistFile, thisNamefile, labels, smallestCutoff); }
-
- if(previousDist <= 0.0000){
- oldList.setLabel("unique");
- oldList.print(listFile);
- if (labels.count("unique") == 0) { labels.insert("unique"); }
- }
- else if(rndPreviousDist<cutoff){
- oldList.setLabel(toString(rndPreviousDist, length-1));
- oldList.print(listFile);
- if (labels.count(toString(rndPreviousDist, length-1)) == 0) { labels.insert(toString(rndPreviousDist, length-1)); }
- }
-
- delete matrix; delete list; delete cluster; delete rabund;
- listFile.close();
-
if (m->control_pressed) { //clean up
for (int i = 0; i < listFileNames.size(); i++) { m->mothurRemove(listFileNames[i]); }
listFileNames.clear(); return listFileNames;
}
-
- m->mothurRemove(thisDistFile);
- m->mothurRemove(thisNamefile);
-
- 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; }
- }
+
+ listFileNames.push_back(listFileName);
+ }
cutoff = smallestCutoff;
}
//**********************************************************************************************************************
+string ClusterSplitCommand::clusterClassicFile(string thisDistFile, string thisNamefile, set<string>& labels, double& smallestCutoff){
+ try {
+ string listFileName = "";
+
+ ListVector* list = NULL;
+ ListVector oldList;
+ RAbundVector* rabund = NULL;
+
+#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();
+
+ //reads phylip file storing data in 2D vector, also fills list and rabund
+ bool sim = false;
+ ClusterClassic* cluster = new ClusterClassic(cutoff, method, sim);
+
+ NameAssignment* nameMap = NULL;
+ CountTable* ct = NULL;
+ if(namefile != ""){
+ nameMap = new NameAssignment(thisNamefile);
+ nameMap->readMap();
+ cluster->readPhylipFile(thisDistFile, nameMap);
+ }else if (countfile != "") {
+ ct = new CountTable();
+ ct->readTable(thisNamefile, false);
+ cluster->readPhylipFile(thisDistFile, ct);
+ }
+ tag = cluster->getTag();
+
+ if (m->control_pressed) { if(namefile != ""){ delete nameMap; }
+ else { delete ct; } delete cluster; return 0; }
+
+ list = cluster->getListVector();
+ rabund = cluster->getRAbundVector();
+
+ if (outputDir == "") { outputDir += m->hasPath(thisDistFile); }
+ fileroot = outputDir + m->getRootName(m->getSimpleName(thisDistFile));
+ listFileName = fileroot+ tag + ".list";
+
+ ofstream listFile;
+ m->openOutputFile(fileroot+ tag + ".list", listFile);
+
+ float previousDist = 0.00000;
+ float rndPreviousDist = 0.00000;
+ oldList = *list;
+
+#ifdef USE_MPI
+ //output your files too
+ if (pid != 0) {
+ cout << endl << "Clustering " << thisDistFile << endl;
+ }
+#endif
+
+ m->mothurOutEndLine(); m->mothurOut("Clustering " + thisDistFile); m->mothurOutEndLine();
+
+ while ((cluster->getSmallDist() < cutoff) && (cluster->getNSeqs() > 1)){
+ if (m->control_pressed) { delete cluster; delete list; delete rabund; listFile.close(); if(namefile != ""){ delete nameMap; }
+ else { delete ct; } return listFileName; }
+
+ cluster->update(cutoff);
+
+ float dist = cluster->getSmallDist();
+ float rndDist;
+ if (hard) {
+ rndDist = m->ceilDist(dist, precision);
+ }else{
+ rndDist = m->roundDist(dist, precision);
+ }
+
+ if(previousDist <= 0.0000 && dist != previousDist){
+ oldList.setLabel("unique");
+ oldList.print(listFile);
+ if (labels.count("unique") == 0) { labels.insert("unique"); }
+ }
+ else if(rndDist != rndPreviousDist){
+ oldList.setLabel(toString(rndPreviousDist, length-1));
+ oldList.print(listFile);
+ if (labels.count(toString(rndPreviousDist, length-1)) == 0) { labels.insert(toString(rndPreviousDist, length-1)); }
+ }
+
+
+ previousDist = dist;
+ rndPreviousDist = rndDist;
+ oldList = *list;
+ }
+
+ if(previousDist <= 0.0000){
+ oldList.setLabel("unique");
+ oldList.print(listFile);
+ if (labels.count("unique") == 0) { labels.insert("unique"); }
+ }
+ else if(rndPreviousDist<cutoff){
+ oldList.setLabel(toString(rndPreviousDist, length-1));
+ oldList.print(listFile);
+ if (labels.count(toString(rndPreviousDist, length-1)) == 0) { labels.insert(toString(rndPreviousDist, length-1)); }
+ }
+
+
+ listFile.close();
+
+ delete cluster; delete list; delete rabund;
+ if(namefile != ""){ delete nameMap; }
+ else { delete ct; }
+
+ m->mothurRemove(thisDistFile);
+ m->mothurRemove(thisNamefile);
+
+ return listFileName;
+
+ }
+ catch(exception& e) {
+ m->errorOut(e, "ClusterSplitCommand", "clusterClassicFile");
+ exit(1);
+ }
+}
+
+//**********************************************************************************************************************
+string ClusterSplitCommand::clusterFile(string thisDistFile, string thisNamefile, set<string>& labels, double& smallestCutoff){
+ try {
+ string listFileName = "";
+
+ Cluster* cluster = NULL;
+ SparseDistanceMatrix* matrix = NULL;
+ ListVector* list = NULL;
+ ListVector oldList;
+ RAbundVector* rabund = NULL;
+
+ if (m->control_pressed) { return listFileName; }
+
+#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);
+ read->setCutoff(cutoff);
+
+ NameAssignment* nameMap = NULL;
+ CountTable* ct = NULL;
+ if(namefile != ""){
+ nameMap = new NameAssignment(thisNamefile);
+ nameMap->readMap();
+ read->read(nameMap);
+ }else if (countfile != "") {
+ ct = new CountTable();
+ ct->readTable(thisNamefile, false);
+ read->read(ct);
+ }else { read->read(nameMap); }
+
+ list = read->getListVector();
+ oldList = *list;
+ matrix = read->getDMatrix();
+
+ if(countfile != "") {
+ rabund = new RAbundVector();
+ createRabund(ct, list, rabund); //creates an rabund that includes the counts for the unique list
+ delete ct;
+ }else { rabund = new RAbundVector(list->getRAbundVector()); }
+
+ delete read; read = NULL;
+ if (namefile != "") { delete nameMap; nameMap = NULL; }
+
+
+#ifdef USE_MPI
+ //output your files too
+ if (pid != 0) {
+ cout << endl << "Clustering " << thisDistFile << endl;
+ }
+#endif
+
+ m->mothurOutEndLine(); m->mothurOut("Clustering " + thisDistFile); m->mothurOutEndLine();
+
+ //create cluster
+ float adjust = -1.0;
+ if (method == "furthest") { cluster = new CompleteLinkage(rabund, list, matrix, cutoff, method, adjust); }
+ else if(method == "nearest"){ cluster = new SingleLinkage(rabund, list, matrix, cutoff, method, adjust); }
+ else if(method == "average"){ cluster = new AverageLinkage(rabund, list, matrix, cutoff, method, adjust); }
+ tag = cluster->getTag();
+
+ if (outputDir == "") { outputDir += m->hasPath(thisDistFile); }
+ fileroot = outputDir + m->getRootName(m->getSimpleName(thisDistFile));
+
+ ofstream listFile;
+ m->openOutputFile(fileroot+ tag + ".list", listFile);
+
+ listFileName = fileroot+ tag + ".list";
+
+ float previousDist = 0.00000;
+ float rndPreviousDist = 0.00000;
+
+ oldList = *list;
+
+ print_start = true;
+ start = time(NULL);
+ double saveCutoff = cutoff;
+
+ while (matrix->getSmallDist() < cutoff && matrix->getNNodes() > 0){
+
+ if (m->control_pressed) { //clean up
+ delete matrix; delete list; delete cluster; delete rabund;
+ listFile.close();
+ m->mothurRemove(listFileName);
+ return listFileName;
+ }
+
+ cluster->update(saveCutoff);
+
+ float dist = matrix->getSmallDist();
+ float rndDist;
+ if (hard) {
+ rndDist = m->ceilDist(dist, precision);
+ }else{
+ rndDist = m->roundDist(dist, precision);
+ }
+
+ if(previousDist <= 0.0000 && dist != previousDist){
+ oldList.setLabel("unique");
+ oldList.print(listFile);
+ if (labels.count("unique") == 0) { labels.insert("unique"); }
+ }
+ else if(rndDist != rndPreviousDist){
+ oldList.setLabel(toString(rndPreviousDist, length-1));
+ oldList.print(listFile);
+ if (labels.count(toString(rndPreviousDist, length-1)) == 0) { labels.insert(toString(rndPreviousDist, length-1)); }
+ }
+
+ previousDist = dist;
+ rndPreviousDist = rndDist;
+ oldList = *list;
+ }
+
+
+ if(previousDist <= 0.0000){
+ oldList.setLabel("unique");
+ oldList.print(listFile);
+ if (labels.count("unique") == 0) { labels.insert("unique"); }
+ }
+ else if(rndPreviousDist<cutoff){
+ oldList.setLabel(toString(rndPreviousDist, length-1));
+ oldList.print(listFile);
+ if (labels.count(toString(rndPreviousDist, length-1)) == 0) { labels.insert(toString(rndPreviousDist, length-1)); }
+ }
+
+ delete matrix; delete list; delete cluster; delete rabund;
+ matrix = NULL; list = NULL; cluster = NULL; rabund = NULL;
+ listFile.close();
+
+ if (m->control_pressed) { //clean up
+ m->mothurRemove(listFileName);
+ return listFileName;
+ }
+
+ m->mothurRemove(thisDistFile);
+ m->mothurRemove(thisNamefile);
+
+ 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; }
+
+ return listFileName;
+
+ }
+ catch(exception& e) {
+ m->errorOut(e, "ClusterSplitCommand", "clusterFile");
+ exit(1);
+ }
+}
+//**********************************************************************************************************************
int ClusterSplitCommand::createMergedDistanceFile(vector< map<string, string> > distNames) {
try{
string thisOutputDir = outputDir;
if (outputDir == "") { thisOutputDir = m->hasPath(fastafile); }
- string outputFileName = thisOutputDir + m->getRootName(m->getSimpleName(fastafile)) + "dist";
+ map<string, string> variables;
+ variables["[filename]"] = thisOutputDir + m->getRootName(m->getSimpleName(fastafile));
+ string outputFileName = getOutputFileName("column", variables);
m->mothurRemove(outputFileName);
}
}
//**********************************************************************************************************************
+int ClusterSplitCommand::createRabund(CountTable*& ct, ListVector*& list, RAbundVector*& rabund){
+ try {
+ rabund->setLabel(list->getLabel());
+ for(int i = 0; i < list->getNumBins(); i++) {
+ if (m->control_pressed) { break; }
+ vector<string> binNames;
+ string bin = list->get(i);
+ m->splitAtComma(bin, binNames);
+ int total = 0;
+ for (int j = 0; j < binNames.size(); j++) { total += ct->getNumSeqs(binNames[j]); }
+ rabund->push_back(total);
+ }
+ return 0;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "ClusterCommand", "createRabund");
+ exit(1);
+ }
+
+}
+//**********************************************************************************************************************
projects / mothur.git / blobdiff