*/
#include "treegroupscommand.h"
-#include "sharedsobscollectsummary.h"
-#include "sharedchao1.h"
-#include "sharedace.h"
-#include "sharednseqs.h"
-#include "sharedjabund.h"
-#include "sharedsorabund.h"
-#include "sharedjclass.h"
-#include "sharedsorclass.h"
-#include "sharedjest.h"
-#include "sharedsorest.h"
-#include "sharedthetayc.h"
-#include "sharedthetan.h"
-#include "sharedkstest.h"
-#include "whittaker.h"
-#include "sharedochiai.h"
-#include "sharedanderbergs.h"
-#include "sharedkulczynski.h"
-#include "sharedkulczynskicody.h"
-#include "sharedlennon.h"
-#include "sharedmorisitahorn.h"
-#include "sharedbraycurtis.h"
-#include "sharedjackknife.h"
-#include "whittaker.h"
-#include "odum.h"
-#include "canberra.h"
-#include "structeuclidean.h"
-#include "structchord.h"
-#include "hellinger.h"
-#include "manhattan.h"
-#include "structpearson.h"
-#include "soergel.h"
-#include "spearman.h"
-#include "structkulczynski.h"
-#include "structchi2.h"
-#include "speciesprofile.h"
-#include "hamming.h"
-#include "gower.h"
-#include "memchi2.h"
-#include "memchord.h"
-#include "memeuclidean.h"
-#include "mempearson.h"
+#include "subsample.h"
+#include "consensus.h"
//**********************************************************************************************************************
vector<string> TreeGroupCommand::setParameters(){
CommandParameter pshared("shared", "InputTypes", "", "", "PhylipColumnShared", "PhylipColumnShared", "none",false,false); parameters.push_back(pshared);
CommandParameter pphylip("phylip", "InputTypes", "", "", "PhylipColumnShared", "PhylipColumnShared", "none",false,false); parameters.push_back(pphylip);
CommandParameter pname("name", "InputTypes", "", "", "none", "none", "ColumnName",false,false); parameters.push_back(pname);
- CommandParameter pcolumn("column", "InputTypes", "", "", "PhylipColumnShared", "PhylipColumnShared", "ColumnName",false,false); parameters.push_back(pcolumn);
- CommandParameter pcutoff("cutoff", "Number", "", "10", "", "", "",false,false); parameters.push_back(pcutoff);
+ CommandParameter pcolumn("column", "InputTypes", "", "", "PhylipColumnShared", "PhylipColumnShared", "ColumnName",false,false); parameters.push_back(pcolumn);
+ CommandParameter piters("iters", "Number", "", "1000", "", "", "",false,false); parameters.push_back(piters);
+ CommandParameter psubsample("subsample", "String", "", "", "", "", "",false,false); parameters.push_back(psubsample);
+ CommandParameter pcutoff("cutoff", "Number", "", "10", "", "", "",false,false); parameters.push_back(pcutoff);
CommandParameter pprecision("precision", "Number", "", "100", "", "", "",false,false); parameters.push_back(pprecision);
CommandParameter plabel("label", "String", "", "", "", "", "",false,false); parameters.push_back(plabel);
CommandParameter pgroups("groups", "String", "", "", "", "", "",false,false); parameters.push_back(pgroups);
CommandParameter pcalc("calc", "Multiple", "sharedsobs-sharedchao-sharedace-jabund-sorabund-jclass-sorclass-jest-sorest-thetayc-thetan-kstest-sharednseqs-ochiai-anderberg-kulczynski-kulczynskicody-lennon-morisitahorn-braycurtis-whittaker-odum-canberra-structeuclidean-structchord-hellinger-manhattan-structpearson-soergel-spearman-structkulczynski-speciesprofile-hamming-structchi2-gower-memchi2-memchord-memeuclidean-mempearson", "jclass-thetayc", "", "", "",true,false); parameters.push_back(pcalc);
- CommandParameter poutput("output", "Multiple", "lt-square", "lt", "", "", "",false,false); parameters.push_back(poutput);
+
+ CommandParameter pprocessors("processors", "Number", "", "1", "", "", "",false,false); parameters.push_back(pprocessors);
+ CommandParameter poutput("output", "Multiple", "lt-square", "lt", "", "", "",false,false); parameters.push_back(poutput);
CommandParameter pinputdir("inputdir", "String", "", "", "", "", "",false,false); parameters.push_back(pinputdir);
CommandParameter poutputdir("outputdir", "String", "", "", "", "", "",false,false); parameters.push_back(poutputdir);
string helpString = "";
ValidCalculators validCalculator;
helpString += "The tree.shared command creates a .tre to represent the similiarity between groups or sequences.\n";
- helpString += "The tree.shared command parameters are shared, groups, calc, phylip, column, name, cutoff, precision and label.\n";
+ helpString += "The tree.shared command parameters are shared, groups, calc, phylip, column, name, cutoff, precision, processors, subsample, iters and label.\n";
helpString += "The groups parameter allows you to specify which of the groups in your groupfile you would like included used.\n";
helpString += "The group names are separated by dashes. The label allow you to select what distance levels you would like trees created for, and are also separated by dashes.\n";
helpString += "The phylip or column parameter are required if you do not provide a sharedfile, and only one may be used. If you use a column file the name filename is required. \n";
helpString += "If you do not provide a cutoff value 10.00 is assumed. If you do not provide a precision value then 100 is assumed.\n";
helpString += "The tree.shared command should be in the following format: tree.shared(groups=yourGroups, calc=yourCalcs, label=yourLabels).\n";
+ helpString += "The iters parameter allows you to choose the number of times you would like to run the subsample.\n";
+ helpString += "The subsample parameter allows you to enter the size pergroup of the sample or you can set subsample=T and mothur will use the size of your smallest group. The subsample parameter may only be used with a shared file.\n";
helpString += "Example tree.shared(groups=A-B-C, calc=jabund-sorabund).\n";
helpString += "The default value for groups is all the groups in your groupfile.\n";
helpString += "The default value for calc is jclass-thetayc.\n";
m->mothurConvert(temp, cutoff);
cutoff += (5 / (precision * 10.0));
+ temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = m->getProcessors(); }
+ m->setProcessors(temp);
+ m->mothurConvert(temp, processors);
+
+ temp = validParameter.validFile(parameters, "iters", false); if (temp == "not found") { temp = "1000"; }
+ m->mothurConvert(temp, iters);
+
+ temp = validParameter.validFile(parameters, "subsample", false); if (temp == "not found") { temp = "F"; }
+ if (m->isNumeric1(temp)) { m->mothurConvert(temp, subsampleSize); subsample = true; }
+ else {
+ if (m->isTrue(temp)) { subsample = true; subsampleSize = -1; } //we will set it to smallest group later
+ else { subsample = false; }
+ }
+
+ if (subsample == false) { iters = 1; }
+
+ if (subsample && (format != "sharedfile")) { m->mothurOut("[ERROR]: the subsample parameter can only be used with a shared file.\n"); 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 (m->control_pressed) { return 0; }
- makeSimsDist();
+ vector< vector<double> > matrix = makeSimsDist();
if (m->control_pressed) { return 0; }
//create a new filename
- outputFile = outputDir + m->getRootName(m->getSimpleName(inputfile)) + "tre";
+ string outputFile = outputDir + m->getRootName(m->getSimpleName(inputfile)) + "tre";
outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
- createTree();
+ Tree* newTree = createTree(matrix);
+
+ if (newTree != NULL) { writeTree(outputFile, newTree); delete newTree; }
if (m->control_pressed) { return 0; }
}
//**********************************************************************************************************************
-int TreeGroupCommand::createTree(){
+Tree* TreeGroupCommand::createTree(vector< vector<double> >& simMatrix){
try {
//create tree
t = new Tree(tmap);
+
+ //initialize index
+ map<int, int> index; //maps row in simMatrix to vector index in the tree
+ for (int g = 0; g < numGroups; g++) { index[g] = g; }
//do merges and create tree structure by setting parents and children
//there are numGroups - 1 merges to do
for (int i = 0; i < (numGroups - 1); i++) {
float largest = -1000.0;
- if (m->control_pressed) { delete t; return 1; }
+ if (m->control_pressed) { delete t; t = NULL; return t; }
int row, column;
//find largest value in sims matrix by searching lower triangle
//assemble tree
t->assembleTree();
- if (m->control_pressed) { delete t; return 1; }
-
- //print newick file
- t->createNewickFile(outputFile);
-
- //delete tree
- delete t;
+ if (m->control_pressed) { delete t; t = NULL; return t; }
- if (m->control_pressed) { m->mothurRemove(outputFile); outputNames.pop_back(); return 1; }
-
- return 0;
+ return t;
}
catch(exception& e) {
}
}
/***********************************************************/
-void TreeGroupCommand::printSims(ostream& out) {
+int TreeGroupCommand::writeTree(string out, Tree* T) {
try {
- //output column headers
- //out << '\t';
- //for (int i = 0; i < lookup.size(); i++) { out << lookup[i]->getGroup() << '\t'; }
- //out << endl;
+ //print newick file
+ t->createNewickFile(out);
+ if (m->control_pressed) { m->mothurRemove(out); outputNames.pop_back(); return 1; }
+
+ return 0;
+
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TreeGroupCommand", "printSims");
+ exit(1);
+ }
+}
+
+/***********************************************************/
+void TreeGroupCommand::printSims(ostream& out, vector< vector<double> >& simMatrix) {
+ try {
- for (int m = 0; m < simMatrix.size(); m++) {
+ for (int m = 0; m < simMatrix.size(); m++) {
//out << lookup[m]->getGroup() << '\t';
for (int n = 0; n < simMatrix.size(); n++) {
out << simMatrix[m][n] << '\t';
}
}
/***********************************************************/
-int TreeGroupCommand::makeSimsDist() {
+vector< vector<double> > TreeGroupCommand::makeSimsDist() {
try {
numGroups = list->size();
- //initialize index
- index.clear();
- for (int g = 0; g < numGroups; g++) { index[g] = g; }
-
//initialize simMatrix
- simMatrix.clear();
+ vector< vector<double> > simMatrix;
simMatrix.resize(numGroups);
for (int k = 0; k < simMatrix.size(); k++) {
for (int j = 0; j < simMatrix.size(); j++) {
simMatrix[currentCell->row][currentCell->column] = -(currentCell->dist -1.0);
simMatrix[currentCell->column][currentCell->row] = -(currentCell->dist -1.0);
- if (m->control_pressed) { return 1; }
+ if (m->control_pressed) { return simMatrix; }
}
- return 0;
+ return simMatrix;
}
catch(exception& e) {
m->errorOut(e, "TreeGroupCommand", "makeSimsDist");
/***********************************************************/
int TreeGroupCommand::makeSimsShared() {
try {
+
+ numGroups = lookup.size();
+ lines.resize(processors);
+ for (int i = 0; i < processors; i++) {
+ lines[i].start = int (sqrt(float(i)/float(processors)) * numGroups);
+ lines[i].end = int (sqrt(float(i+1)/float(processors)) * numGroups);
+ }
+
+ if (subsample) {
+ if (subsampleSize == -1) { //user has not set size, set size = smallest samples size
+ subsampleSize = lookup[0]->getNumSeqs();
+ for (int i = 1; i < lookup.size(); i++) {
+ int thisSize = lookup[i]->getNumSeqs();
+
+ if (thisSize < subsampleSize) { subsampleSize = thisSize; }
+ }
+ }else {
+ m->clearGroups();
+ Groups.clear();
+ vector<SharedRAbundVector*> temp;
+ for (int i = 0; i < lookup.size(); i++) {
+ if (lookup[i]->getNumSeqs() < subsampleSize) {
+ m->mothurOut(lookup[i]->getGroup() + " contains " + toString(lookup[i]->getNumSeqs()) + ". Eliminating."); m->mothurOutEndLine();
+ delete lookup[i];
+ }else {
+ Groups.push_back(lookup[i]->getGroup());
+ temp.push_back(lookup[i]);
+ }
+ }
+ lookup = temp;
+ m->setGroups(Groups);
+ }
+ }
+
set<string> processedLabels;
set<string> userLabels = labels;
/***********************************************************/
int TreeGroupCommand::process(vector<SharedRAbundVector*> thisLookup) {
try{
- EstOutput data;
- vector<SharedRAbundVector*> subset;
- numGroups = thisLookup.size();
-
- //for each calculator
- for(int i = 0 ; i < treeCalculators.size(); i++) {
- //initialize simMatrix
- simMatrix.clear();
- simMatrix.resize(numGroups);
- for (int k = 0; k < simMatrix.size(); k++) {
- for (int j = 0; j < simMatrix.size(); j++) {
- simMatrix[k].push_back(0.0);
- }
- }
+ vector< vector< vector<seqDist> > > calcDistsTotals; //each iter, one for each calc, then each groupCombos dists. this will be used to make .dist files
+ vector< vector<seqDist> > calcDists; calcDists.resize(treeCalculators.size());
+
+ for (int thisIter = 0; thisIter < iters; thisIter++) {
+
+ vector<SharedRAbundVector*> thisItersLookup = thisLookup;
+
+ if (subsample) {
+ SubSample sample;
+ vector<string> tempLabels; //dont need since we arent printing the sampled sharedRabunds
+
+ //make copy of lookup so we don't get access violations
+ vector<SharedRAbundVector*> newLookup;
+ for (int k = 0; k < thisItersLookup.size(); k++) {
+ SharedRAbundVector* temp = new SharedRAbundVector();
+ temp->setLabel(thisItersLookup[k]->getLabel());
+ temp->setGroup(thisItersLookup[k]->getGroup());
+ newLookup.push_back(temp);
+ }
+
+ //for each bin
+ for (int k = 0; k < thisItersLookup[0]->getNumBins(); k++) {
+ if (m->control_pressed) { for (int j = 0; j < newLookup.size(); j++) { delete newLookup[j]; } return 0; }
+ for (int j = 0; j < thisItersLookup.size(); j++) { newLookup[j]->push_back(thisItersLookup[j]->getAbundance(k), thisItersLookup[j]->getGroup()); }
+ }
+
+ tempLabels = sample.getSample(newLookup, subsampleSize);
+ thisItersLookup = newLookup;
+ }
+
+ if(processors == 1){
+ driver(thisItersLookup, 0, numGroups, calcDists);
+ }else{
+ int process = 1;
+ vector<int> processIDS;
+
+#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
+ //loop through and create all the processes you want
+ while (process != processors) {
+ int pid = fork();
+
+ if (pid > 0) {
+ processIDS.push_back(pid);
+ process++;
+ }else if (pid == 0){
+
+ driver(thisItersLookup, lines[process].start, lines[process].end, calcDists);
+
+ string tempdistFileName = m->getRootName(m->getSimpleName(sharedfile)) + toString(getpid()) + ".dist";
+ ofstream outtemp;
+ m->openOutputFile(tempdistFileName, outtemp);
+
+ for (int i = 0; i < calcDists.size(); i++) {
+ outtemp << calcDists[i].size() << endl;
+
+ for (int j = 0; j < calcDists[i].size(); j++) {
+ outtemp << calcDists[i][j].seq1 << '\t' << calcDists[i][j].seq2 << '\t' << calcDists[i][j].dist << endl;
+ }
+ }
+ outtemp.close();
+
+ exit(0);
+ }else {
+ m->mothurOut("[ERROR]: unable to spawn the necessary processes."); m->mothurOutEndLine();
+ for (int i = 0; i < processIDS.size(); i++) { kill (processIDS[i], SIGINT); }
+ exit(0);
+ }
+ }
+
+ //parent do your part
+ driver(thisItersLookup, lines[0].start, lines[0].end, calcDists);
+
+ //force parent to wait until all the processes are done
+ for (int i = 0; i < processIDS.size(); i++) {
+ int temp = processIDS[i];
+ wait(&temp);
+ }
+
+ for (int i = 0; i < processIDS.size(); i++) {
+ string tempdistFileName = m->getRootName(m->getSimpleName(sharedfile)) + toString(processIDS[i]) + ".dist";
+ ifstream intemp;
+ m->openInputFile(tempdistFileName, intemp);
+
+ for (int k = 0; k < calcDists.size(); k++) {
+ int size = 0;
+ intemp >> size; m->gobble(intemp);
+
+ for (int j = 0; j < size; j++) {
+ int seq1 = 0;
+ int seq2 = 0;
+ float dist = 1.0;
+
+ intemp >> seq1 >> seq2 >> dist; m->gobble(intemp);
+
+ seqDist tempDist(seq1, seq2, dist);
+ calcDists[k].push_back(tempDist);
+ }
+ }
+ intemp.close();
+ m->mothurRemove(tempdistFileName);
+ }
+#else
+ //////////////////////////////////////////////////////////////////////////////////////////////////////
+ //Windows version shared memory, so be careful when passing variables through the treeSharedData struct.
+ //Above fork() will clone, so memory is separate, but that's not the case with windows,
+ //Taking advantage of shared memory to pass results vectors.
+ //////////////////////////////////////////////////////////////////////////////////////////////////////
+
+ vector<treeSharedData*> pDataArray;
+ DWORD dwThreadIdArray[processors-1];
+ HANDLE hThreadArray[processors-1];
+
+ //Create processor worker threads.
+ for( int i=1; i<processors; i++ ){
+
+ //make copy of lookup so we don't get access violations
+ vector<SharedRAbundVector*> newLookup;
+ for (int k = 0; k < thisItersLookup.size(); k++) {
+ SharedRAbundVector* temp = new SharedRAbundVector();
+ temp->setLabel(thisItersLookup[k]->getLabel());
+ temp->setGroup(thisItersLookup[k]->getGroup());
+ newLookup.push_back(temp);
+ }
+
+ //for each bin
+ for (int k = 0; k < thisItersLookup[0]->getNumBins(); k++) {
+ if (m->control_pressed) { for (int j = 0; j < newLookup.size(); j++) { delete newLookup[j]; } return 0; }
+ for (int j = 0; j < thisItersLookup.size(); j++) { newLookup[j]->push_back(thisItersLookup[j]->getAbundance(k), thisItersLookup[j]->getGroup()); }
+ }
+
+ // Allocate memory for thread data.
+ treeSharedData* tempSum = new treeSharedData(m, lines[i].start, lines[i].end, Estimators, newLookup);
+ pDataArray.push_back(tempSum);
+ processIDS.push_back(i);
+
+ hThreadArray[i-1] = CreateThread(NULL, 0, MyTreeSharedThreadFunction, pDataArray[i-1], 0, &dwThreadIdArray[i-1]);
+ }
+
+ //parent do your part
+ driver(thisItersLookup, lines[0].start, lines[0].end, calcDists);
+
+ //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++){
+ for (int j = 0; j < pDataArray[i]->thisLookup.size(); j++) { delete pDataArray[i]->thisLookup[j]; }
+
+ for (int k = 0; k < calcDists.size(); k++) {
+ int size = pDataArray[i]->calcDists[k].size();
+ for (int j = 0; j < size; j++) { calcDists[k].push_back(pDataArray[i]->calcDists[k][j]); }
+ }
+
+ CloseHandle(hThreadArray[i]);
+ delete pDataArray[i];
+ }
+
+#endif
+ }
+
+ calcDistsTotals.push_back(calcDists);
+
+ if (subsample) {
+
+ //clean up memory
+ for (int i = 0; i < thisItersLookup.size(); i++) { delete thisItersLookup[i]; }
+ thisItersLookup.clear();
+ for (int i = 0; i < calcDists.size(); i++) { calcDists[i].clear(); }
+ }
+ }
- //initialize index
- index.clear();
- for (int g = 0; g < numGroups; g++) { index[g] = g; }
-
- //create a new filename
- outputFile = outputDir + m->getRootName(m->getSimpleName(inputfile)) + treeCalculators[i]->getName() + "." + thisLookup[0]->getLabel() + ".tre";
- outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
-
- for (int k = 0; k < thisLookup.size(); k++) {
- for (int l = k; l < thisLookup.size(); l++) {
- if (k != l) { //we dont need to similiarity of a groups to itself
- //get estimated similarity between 2 groups
-
- subset.clear(); //clear out old pair of sharedrabunds
- //add new pair of sharedrabunds
- subset.push_back(thisLookup[k]); subset.push_back(thisLookup[l]);
-
- //if this calc needs all groups to calculate the pair load all groups
- if (treeCalculators[i]->getNeedsAll()) {
- //load subset with rest of lookup for those calcs that need everyone to calc for a pair
- for (int w = 0; w < thisLookup.size(); w++) {
- if ((w != k) && (w != l)) { subset.push_back(thisLookup[w]); }
- }
- }
-
- data = treeCalculators[i]->getValues(subset); //saves the calculator outputs
- //cout << thisLookup[k]->getGroup() << '\t' << thisLookup[l]->getGroup() << '\t' << (1.0 - data[0]) << endl;
- if (m->control_pressed) { return 1; }
-
- //save values in similarity matrix
- simMatrix[k][l] = -(data[0]-1.0);
- simMatrix[l][k] = -(data[0]-1.0);
- }
- }
- }
+ if (iters != 1) {
+ //we need to find the average distance and standard deviation for each groups distance
+
+ vector< vector<seqDist> > calcAverages; calcAverages.resize(treeCalculators.size());
+ for (int i = 0; i < calcAverages.size(); i++) { //initialize sums to zero.
+ calcAverages[i].resize(calcDistsTotals[0][i].size());
+
+ for (int j = 0; j < calcAverages[i].size(); j++) {
+ calcAverages[i][j].seq1 = calcDists[i][j].seq1;
+ calcAverages[i][j].seq2 = calcDists[i][j].seq2;
+ calcAverages[i][j].dist = 0.0;
+ }
+ }
+
+ for (int thisIter = 0; thisIter < iters; thisIter++) { //sum all groups dists for each calculator
+ for (int i = 0; i < calcAverages.size(); i++) { //initialize sums to zero.
+ for (int j = 0; j < calcAverages[i].size(); j++) {
+ calcAverages[i][j].dist += calcDistsTotals[thisIter][i][j].dist;
+ }
+ }
+ }
+
+ for (int i = 0; i < calcAverages.size(); i++) { //finds average.
+ for (int j = 0; j < calcAverages[i].size(); j++) {
+ calcAverages[i][j].dist /= (float) iters;
+ }
+ }
+
+ //create average tree for each calc
+ for (int i = 0; i < calcDists.size(); i++) {
+ vector< vector<double> > matrix; //square matrix to represent the distance
+ matrix.resize(thisLookup.size());
+ for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
+
+ for (int j = 0; j < calcAverages[i].size(); j++) {
+ int row = calcAverages[i][j].seq1;
+ int column = calcAverages[i][j].seq2;
+ float dist = calcAverages[i][j].dist;
+
+ matrix[row][column] = dist;
+ matrix[column][row] = dist;
+ }
+
+ //create a new filename
+ string outputFile = outputDir + m->getRootName(m->getSimpleName(inputfile)) + treeCalculators[i]->getName() + "." + thisLookup[0]->getLabel() + ".ave.tre";
+ outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
+
+ //creates tree from similarity matrix and write out file
+ Tree* newTree = createTree(matrix);
+ if (newTree != NULL) { writeTree(outputFile, newTree); }
+ }
+
+ //create all trees for each calc and find their consensus tree
+ for (int i = 0; i < calcDists.size(); i++) {
+ if (m->control_pressed) { break; }
+
+ //create a new filename
+ string outputFile = outputDir + m->getRootName(m->getSimpleName(inputfile)) + treeCalculators[i]->getName() + "." + thisLookup[0]->getLabel() + ".all.tre";
+ outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
+
+ ofstream outAll;
+ m->openOutputFile(outputFile, outAll);
+
+ vector<Tree*> trees;
+ for (int myIter = 0; myIter < iters; myIter++) {
+
+ if(m->control_pressed) { break; }
+
+ //initialize matrix
+ vector< vector<double> > matrix; //square matrix to represent the distance
+ matrix.resize(thisLookup.size());
+ for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
+
+ for (int j = 0; j < calcDistsTotals[myIter][i].size(); j++) {
+ int row = calcDistsTotals[myIter][i][j].seq1;
+ int column = calcDistsTotals[myIter][i][j].seq2;
+ double dist = calcDistsTotals[myIter][i][j].dist;
+
+ matrix[row][column] = dist;
+ matrix[column][row] = dist;
+ }
+
+ //creates tree from similarity matrix and write out file
+ Tree* newTree = createTree(matrix);
+ if (newTree != NULL) {
+ newTree->print(outAll);
+ trees.push_back(newTree);
+ }
+ }
+ outAll.close();
+ if (m->control_pressed) { for (int k = 0; k < trees.size(); k++) { delete trees[k]; } }
+
+ Consensus consensus;
+ Tree* conTree = consensus.getTree(trees, tmap);
+
+ //create a new filename
+ string conFile = outputDir + m->getRootName(m->getSimpleName(inputfile)) + treeCalculators[i]->getName() + "." + thisLookup[0]->getLabel() + ".cons.tre";
+ outputNames.push_back(conFile); outputTypes["tree"].push_back(outputFile);
+ ofstream outTree;
+ m->openOutputFile(conFile, outTree);
+
+ if (conTree != NULL) { conTree->print(outTree, "boot"); delete conTree; }
+ }
+
+ }else {
+
+ for (int i = 0; i < calcDists.size(); i++) {
+ if (m->control_pressed) { break; }
+
+ //initialize matrix
+ vector< vector<double> > matrix; //square matrix to represent the distance
+ matrix.resize(thisLookup.size());
+ for (int k = 0; k < thisLookup.size(); k++) { matrix[k].resize(thisLookup.size(), 0.0); }
+
+ for (int j = 0; j < calcDists[i].size(); j++) {
+ int row = calcDists[i][j].seq1;
+ int column = calcDists[i][j].seq2;
+ double dist = calcDists[i][j].dist;
+
+ matrix[row][column] = dist;
+ matrix[column][row] = dist;
+ }
+
+ //create a new filename
+ string outputFile = outputDir + m->getRootName(m->getSimpleName(inputfile)) + treeCalculators[i]->getName() + "." + thisLookup[0]->getLabel() + ".tre";
+ outputNames.push_back(outputFile); outputTypes["tree"].push_back(outputFile);
+
+ //creates tree from similarity matrix and write out file
+ Tree* newTree = createTree(matrix);
+ if (newTree != NULL) { writeTree(outputFile, newTree); delete newTree; }
+ }
+ }
+
+ return 0;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "TreeGroupCommand", "process");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+int TreeGroupCommand::driver(vector<SharedRAbundVector*> thisLookup, int start, int end, vector< vector<seqDist> >& calcDists) {
+ try {
+ vector<SharedRAbundVector*> subset;
+ for (int k = start; k < end; k++) { // pass cdd each set of groups to compare
+
+ for (int l = 0; l < k; l++) {
+
+ if (k != l) { //we dont need to similiarity of a groups to itself
+ subset.clear(); //clear out old pair of sharedrabunds
+ //add new pair of sharedrabunds
+ subset.push_back(thisLookup[k]); subset.push_back(thisLookup[l]);
- //createdistance file from simMatrix
- /*string o = outputDir + m->getRootName(m->getSimpleName(globaldata->inputFileName)) + treeCalculators[i]->getName() + "." + thisLookup[0]->getLabel() + ".dist";
- ofstream outDist;
- m->openOutputFile(o, outDist);
- outDist << simMatrix.size() << endl;
- for (int k = 0; k < simMatrix.size(); k++) {
- outDist << thisLookup[k]->getGroup() << '\t';
- for (int l = 0; l < k; l++) {
- outDist << (1.0-simMatrix[k][l]) << '\t';
+ for(int i=0;i<treeCalculators.size();i++) {
+
+ //if this calc needs all groups to calculate the pair load all groups
+ if (treeCalculators[i]->getNeedsAll()) {
+ //load subset with rest of lookup for those calcs that need everyone to calc for a pair
+ for (int w = 0; w < thisLookup.size(); w++) {
+ if ((w != k) && (w != l)) { subset.push_back(thisLookup[w]); }
+ }
}
- outDist << endl;
+
+ vector<double> tempdata = treeCalculators[i]->getValues(subset); //saves the calculator outputs
+
+ if (m->control_pressed) { return 1; }
+
+ seqDist temp(l, k, -(tempdata[0]-1.0));
+ calcDists[i].push_back(temp);
}
- outDist.close();*/
-
-
- if (m->control_pressed) { return 1; }
- //creates tree from similarity matrix and write out file
- createTree();
-
- if (m->control_pressed) { return 1; }
}
-
- return 0;
-
+ }
+ }
+
+ return 0;
}
catch(exception& e) {
- m->errorOut(e, "TreeGroupCommand", "process");
+ m->errorOut(e, "TreeGroupCommand", "driver");
exit(1);
}
}
projects / mothur.git / blobdiff