globaldata = GlobalData::getInstance();
abort = false;
Groups.clear();
-
+
//allow user to run help
if(option == "help") { help(); abort = true; }
else {
//valid paramters for this command
- string Array[] = {"groups","iters","distance","random"};
+ string Array[] = {"groups","iters","distance","random","processors","outputdir","inputdir"};
vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
OptionParser parser(option);
}
if (globaldata->gTree.size() == 0) {//no trees were read
- mothurOut("You must execute the read.tree command, before you may execute the unifrac.weighted command."); mothurOutEndLine(); abort = true; }
-
+ m->mothurOut("You must execute the read.tree command, before you may execute the unifrac.weighted command."); m->mothurOutEndLine(); 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 = "";
+ outputDir += m->hasPath(globaldata->inputFileName); //if user entered a file with a path then preserve it
+ }
+
//check for optional parameter and set defaults
// ...at some point should added some additional type checking...
groups = validParameter.validFile(parameters, "groups", false);
if (groups == "not found") { groups = ""; }
else {
- splitAtDash(groups, Groups);
+ m->splitAtDash(groups, Groups);
globaldata->Groups = Groups;
}
convert(itersString, iters);
string temp = validParameter.validFile(parameters, "distance", false); if (temp == "not found") { temp = "false"; }
- phylip = isTrue(temp);
+ phylip = m->isTrue(temp);
- temp = validParameter.validFile(parameters, "random", false); if (temp == "not found") { temp = "true"; }
- random = isTrue(temp);
+ temp = validParameter.validFile(parameters, "random", false); if (temp == "not found") { temp = "F"; }
+ random = m->isTrue(temp);
+
+ temp = validParameter.validFile(parameters, "processors", false); if (temp == "not found"){ temp = "1"; }
+ convert(temp, processors);
if (!random) { iters = 0; } //turn off random calcs
if (abort == false) {
T = globaldata->gTree;
tmap = globaldata->gTreemap;
- sumFile = globaldata->getTreeFile() + ".wsummary";
- openOutputFile(sumFile, outSum);
+ sumFile = outputDir + m->getSimpleName(globaldata->getTreeFile()) + ".wsummary";
+ m->openOutputFile(sumFile, outSum);
+ outputNames.push_back(sumFile);
util = new SharedUtil();
string s; //to make work with setgroups
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "UnifracWeightedCommand");
+ m->errorOut(e, "UnifracWeightedCommand", "UnifracWeightedCommand");
exit(1);
}
}
void UnifracWeightedCommand::help(){
try {
- mothurOut("The unifrac.weighted command can only be executed after a successful read.tree command.\n");
- mothurOut("The unifrac.weighted command parameters are groups, iters, distance and random. No parameters are required.\n");
- mothurOut("The groups parameter allows you to specify which of the groups in your groupfile you would like analyzed. You must enter at least 2 valid groups.\n");
- mothurOut("The group names are separated by dashes. The iters parameter allows you to specify how many random trees you would like compared to your tree.\n");
- mothurOut("The distance parameter allows you to create a distance file from the results. The default is false.\n");
- mothurOut("The random parameter allows you to shut off the comparison to random trees. The default is true, meaning compare your trees with randomly generated trees.\n");
- mothurOut("The unifrac.weighted command should be in the following format: unifrac.weighted(groups=yourGroups, iters=yourIters).\n");
- mothurOut("Example unifrac.weighted(groups=A-B-C, iters=500).\n");
- mothurOut("The default value for groups is all the groups in your groupfile, and iters is 1000.\n");
- mothurOut("The unifrac.weighted command output two files: .weighted and .wsummary their descriptions are in the manual.\n");
- mothurOut("Note: No spaces between parameter labels (i.e. groups), '=' and parameters (i.e.yourGroups).\n\n");
+ m->mothurOut("The unifrac.weighted command can only be executed after a successful read.tree command.\n");
+ m->mothurOut("The unifrac.weighted command parameters are groups, iters, distance and random. No parameters are required.\n");
+ m->mothurOut("The groups parameter allows you to specify which of the groups in your groupfile you would like analyzed. You must enter at least 2 valid groups.\n");
+ m->mothurOut("The group names are separated by dashes. The iters parameter allows you to specify how many random trees you would like compared to your tree.\n");
+ m->mothurOut("The distance parameter allows you to create a distance file from the results. The default is false.\n");
+ m->mothurOut("The random parameter allows you to shut off the comparison to random trees. The default is false, meaning don't compare your trees with randomly generated trees.\n");
+ m->mothurOut("The unifrac.weighted command should be in the following format: unifrac.weighted(groups=yourGroups, iters=yourIters).\n");
+ m->mothurOut("Example unifrac.weighted(groups=A-B-C, iters=500).\n");
+ m->mothurOut("The default value for groups is all the groups in your groupfile, and iters is 1000.\n");
+ m->mothurOut("The unifrac.weighted command output two files: .weighted and .wsummary their descriptions are in the manual.\n");
+ m->mothurOut("Note: No spaces between parameter labels (i.e. groups), '=' and parameters (i.e.yourGroups).\n\n");
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "help");
+ m->errorOut(e, "UnifracWeightedCommand", "help");
exit(1);
}
}
if (abort == true) { return 0; }
- Progress* reading;
- if (random) { reading = new Progress("Comparing to random:", iters); }
+ int start = time(NULL);
//get weighted for users tree
userData.resize(numComp,0); //data[0] = weightedscore AB, data[1] = weightedscore AC...
//get weighted scores for users trees
for (int i = 0; i < T.size(); i++) {
+
+ if (m->control_pressed) { delete randT; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } return 0; }
+
counter = 0;
rScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
uScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
- if (random) { output = new ColumnFile(globaldata->getTreeFile() + toString(i+1) + ".weighted", itersString); }
+ if (random) {
+ output = new ColumnFile(outputDir + m->getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted", itersString);
+ outputNames.push_back(outputDir + m->getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted");
+ }
+
+ userData = weighted->getValues(T[i], processors, outputDir); //userData[0] = weightedscore
+
+ if (m->control_pressed) {
+ delete randT;
+ if (random) { delete output; }
+ outSum.close();
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
- userData = weighted->getValues(T[i]); //userData[0] = weightedscore
//save users score
for (int s=0; s<numComp; s++) {
utreeScores.push_back(userData[s]);
}
- //get scores for random trees
- for (int j = 0; j < iters; j++) {
- int count = 0;
- for (int r=0; r<numGroups; r++) {
- for (int l = r+1; l < numGroups; l++) {
- //copy T[i]'s info.
- randT->getCopy(T[i]);
-
- //create a random tree with same topology as T[i], but different labels
- randT->assembleRandomUnifracTree(globaldata->Groups[r], globaldata->Groups[l]);
- //get wscore of random tree
- randomData = weighted->getValues(randT, globaldata->Groups[r], globaldata->Groups[l]);
-
- //save scores
- rScores[count].push_back(randomData[0]);
- count++;
+ if (random) {
+ vector<double> sums = weighted->getBranchLengthSums(T[i]);
+
+ //calculate number of comparisons i.e. with groups A,B,C = AB, AC, BC = 3;
+ vector< vector<string> > namesOfGroupCombos;
+ for (int a=0; a<numGroups; a++) {
+ for (int l = a+1; l < numGroups; l++) {
+ vector<string> groups; groups.push_back(globaldata->Groups[a]); groups.push_back(globaldata->Groups[l]);
+ namesOfGroupCombos.push_back(groups);
}
}
-
- //update progress bar
- reading->update(j);
-
- }
+
+ #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
+ if(processors != 1){
+ int numPairs = namesOfGroupCombos.size();
+ int numPairsPerProcessor = numPairs / processors;
+
+ for (int i = 0; i < processors; i++) {
+ int startPos = i * numPairsPerProcessor;
+ if(i == processors - 1){
+ numPairsPerProcessor = numPairs - i * numPairsPerProcessor;
+ }
+ lines.push_back(new linePair(startPos, numPairsPerProcessor));
+ }
+ }
+ #endif
- //removeValidScoresDuplicates();
- //find the signifigance of the score for summary file
- if (random) {
+
+ //get scores for random trees
+ for (int j = 0; j < iters; j++) {
+ int count = 0;
+
+ #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
+ if(processors == 1){
+ driver(T[i], randT, namesOfGroupCombos, 0, namesOfGroupCombos.size(), sums, rScores);
+ }else{
+ createProcesses(T[i], randT, namesOfGroupCombos, sums, rScores);
+ for (int i = 0; i < lines.size(); i++) { delete lines[i]; } lines.clear();
+ }
+ #else
+ driver(T[i], randT, namesOfGroupCombos, 0, namesOfGroupCombos.size(), sums, rScores);
+ #endif
+
+ if (m->control_pressed) { delete output; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } return 0; }
+ }
+
+
+ //find the signifigance of the score for summary file
for (int f = 0; f < numComp; f++) {
//sort random scores
sort(rScores[f].begin(), rScores[f].end());
//so if you have 1000 random trees the index returned is 100
//then there are 900 trees with a score greater then you.
//giving you a signifigance of 0.900
- int index = findIndex(userData[f], f); if (index == -1) { mothurOut("error in UnifracWeightedCommand"); mothurOutEndLine(); exit(1); } //error code
+ int index = findIndex(userData[f], f); if (index == -1) { m->mothurOut("error in UnifracWeightedCommand"); m->mothurOutEndLine(); exit(1); } //error code
//the signifigance is the number of trees with the users score or higher
WScoreSig.push_back((iters-index)/(float)iters);
printWeightedFile();
delete output;
+
}
//clear data
validScores.clear();
}
- //finish progress bar
- if (random) { reading->finish(); delete reading; }
+
+ if (m->control_pressed) { delete randT; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } return 0; }
printWSummaryFile();
delete randT;
+ if (m->control_pressed) {
+ for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
+ return 0;
+ }
+
+ m->mothurOut("It took " + toString(time(NULL) - start) + " secs to run unifrac.weighted."); m->mothurOutEndLine();
+
+ m->mothurOutEndLine();
+ m->mothurOut("Output File Names: "); m->mothurOutEndLine();
+ for (int i = 0; i < outputNames.size(); i++) { m->mothurOut(outputNames[i]); m->mothurOutEndLine(); }
+ m->mothurOutEndLine();
+
+ return 0;
+
+ }
+ catch(exception& e) {
+ m->errorOut(e, "UnifracWeightedCommand", "execute");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
+
+int UnifracWeightedCommand::createProcesses(Tree* t, Tree* randT, vector< vector<string> > namesOfGroupCombos, vector<double>& sums, vector< vector<double> >& scores) {
+ try {
+#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
+ int process = 1;
+ int num = 0;
+ vector<int> processIDS;
+
+ EstOutput results;
+
+ //loop through and create all the processes you want
+ while (process != processors) {
+ int pid = fork();
+
+ if (pid > 0) {
+ processIDS.push_back(pid); //create map from line number to pid so you can append files in correct order later
+ process++;
+ }else if (pid == 0){
+ driver(t, randT, namesOfGroupCombos, lines[process]->start, lines[process]->num, sums, scores);
+
+ m->mothurOut("Merging results."); m->mothurOutEndLine();
+
+ //pass numSeqs to parent
+ ofstream out;
+ string tempFile = outputDir + toString(getpid()) + ".weightedcommand.results.temp";
+ m->openOutputFile(tempFile, out);
+ for (int i = lines[process]->start; i < (lines[process]->start + lines[process]->num); i++) { out << scores[i][0] << '\t'; } out << endl;
+ out.close();
+
+ exit(0);
+ }else { m->mothurOut("unable to spawn the necessary processes."); m->mothurOutEndLine(); exit(0); }
+ }
+
+ driver(t, randT, namesOfGroupCombos, lines[0]->start, lines[0]->num, sums, scores);
+
+ //force parent to wait until all the processes are done
+ for (int i=0;i<(processors-1);i++) {
+ int temp = processIDS[i];
+ wait(&temp);
+ }
+
+ //get data created by processes
+ for (int i=0;i<(processors-1);i++) {
+ ifstream in;
+ string s = outputDir + toString(processIDS[i]) + ".weightedcommand.results.temp";
+ m->openInputFile(s, in);
+
+ for (int i = lines[process]->start; i < (lines[process]->start + lines[process]->num); i++) { in >> scores[i][0]; }
+ in.close();
+ remove(s.c_str());
+ }
+
+ m->mothurOut("DONE."); m->mothurOutEndLine(); m->mothurOutEndLine();
+
return 0;
+#endif
+ }
+ catch(exception& e) {
+ m->errorOut(e, "UnifracWeightedCommand", "createProcesses");
+ exit(1);
+ }
+}
+
+/**************************************************************************************************/
+int UnifracWeightedCommand::driver(Tree* t, Tree* randT, vector< vector<string> > namesOfGroupCombos, int start, int num, vector<double>& sums, vector< vector<double> >& scores) {
+ try {
+ int count = 0;
+ int total = num;
+ int twentyPercent = (total * 0.20);
+
+ for (int h = start; h < (start+num); h++) {
+
+ if (m->control_pressed) { return 0; }
+ //initialize weighted score
+ string groupA = namesOfGroupCombos[h][0];
+ string groupB = namesOfGroupCombos[h][1];
+
+ //copy T[i]'s info.
+ randT->getCopy(t);
+
+ //create a random tree with same topology as T[i], but different labels
+ randT->assembleRandomUnifracTree(groupA, groupB);
+
+ if (m->control_pressed) { delete randT; return 0; }
+
+
+ //get wscore of random tree
+ EstOutput randomData = weighted->getValues(randT, groupA, groupB, sums);
+
+ if (m->control_pressed) { delete randT; return 0; }
+
+ //save scores
+ scores[h].push_back(randomData[0]);
+
+ count++;
+
+ //report progress
+ if((count) % twentyPercent == 0){ m->mothurOut("Random comparison percentage complete: " + toString(int((count / (float)total) * 100.0))); m->mothurOutEndLine(); }
+ }
+
+ m->mothurOut("Random comparison percentage complete: 100"); m->mothurOutEndLine();
+
+ return 0;
+
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "execute");
+ m->errorOut(e, "UnifracWeightedCommand", "driver");
exit(1);
}
}
}
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "printWeightedFile");
+ m->errorOut(e, "UnifracWeightedCommand", "printWeightedFile");
exit(1);
}
}
try {
//column headers
outSum << "Tree#" << '\t' << "Groups" << '\t' << "WScore" << '\t' << "WSig" << endl;
- mothurOut("Tree#\tGroups\tWScore\tWSig"); mothurOutEndLine();
+ m->mothurOut("Tree#\tGroups\tWScore\tWSig"); m->mothurOutEndLine();
//format output
outSum.setf(ios::fixed, ios::floatfield); outSum.setf(ios::showpoint);
if (WScoreSig[count] > (1/(float)iters)) {
outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count])); mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count])); m->mothurOutEndLine();
}else{
outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters)))); mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters)))); m->mothurOutEndLine();
}
}else{
outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
- mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00"); mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00"); m->mothurOutEndLine();
}
count++;
}
outSum.close();
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "printWSummaryFile");
+ m->errorOut(e, "UnifracWeightedCommand", "printWSummaryFile");
exit(1);
}
}
//for each tree
for (int i = 0; i < T.size(); i++) {
- string phylipFileName = globaldata->getTreeFile() + toString(i+1) + ".weighted.dist";
+ string phylipFileName = outputDir + m->getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted.dist";
+ outputNames.push_back(phylipFileName);
ofstream out;
- openOutputFile(phylipFileName, out);
+ m->openOutputFile(phylipFileName, out);
//output numSeqs
out << globaldata->Groups.size() << endl;
//flip it so you can print it
for (int r=0; r<globaldata->Groups.size(); r++) {
for (int l = r+1; l < globaldata->Groups.size(); l++) {
- dists[r][l] = (1.0 - utreeScores[count]);
- dists[l][r] = (1.0 - utreeScores[count]);
+ dists[r][l] = utreeScores[count];
+ dists[l][r] = utreeScores[count];
count++;
}
}
//output to file
for (int r=0; r<globaldata->Groups.size(); r++) {
//output name
- out << globaldata->Groups[r] << '\t';
+ string name = globaldata->Groups[r];
+ if (name.length() < 10) { //pad with spaces to make compatible
+ while (name.length() < 10) { name += " "; }
+ }
+ out << name << '\t';
//output distances
for (int l = 0; l < r; l++) { out << dists[r][l] << '\t'; }
}
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "createPhylipFile");
+ m->errorOut(e, "UnifracWeightedCommand", "createPhylipFile");
exit(1);
}
}
return rScores[index].size();
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "findIndex");
+ m->errorOut(e, "UnifracWeightedCommand", "findIndex");
exit(1);
}
}
}
catch(exception& e) {
- errorOut(e, "UnifracWeightedCommand", "calculateFreqsCums");
+ m->errorOut(e, "UnifracWeightedCommand", "calculateFreqsCums");
exit(1);
}
}
projects / mothur.git / blobdiff