#include "unifracweightedcommand.h"
+//**********************************************************************************************************************
+vector<string> UnifracWeightedCommand::getValidParameters(){
+ try {
+ string Array[] = {"groups","iters","distance","random","processors","outputdir","inputdir"};
+ vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
+ return myArray;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "UnifracWeightedCommand", "getValidParameters");
+ exit(1);
+ }
+}
+//**********************************************************************************************************************
+UnifracWeightedCommand::UnifracWeightedCommand(){
+ try {
+ abort = true;
+ //initialize outputTypes
+ vector<string> tempOutNames;
+ outputTypes["weighted"] = tempOutNames;
+ outputTypes["wsummary"] = tempOutNames;
+ outputTypes["phylip"] = tempOutNames;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "UnifracWeightedCommand", "UnifracWeightedCommand");
+ exit(1);
+ }
+}
+//**********************************************************************************************************************
+vector<string> UnifracWeightedCommand::getRequiredParameters(){
+ try {
+ vector<string> myArray;
+ return myArray;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "UnifracWeightedCommand", "getRequiredParameters");
+ exit(1);
+ }
+}
+//**********************************************************************************************************************
+vector<string> UnifracWeightedCommand::getRequiredFiles(){
+ try {
+ string Array[] = {"tree","group"};
+ vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
+
+ return myArray;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "UnifracWeightedCommand", "getRequiredFiles");
+ exit(1);
+ }
+}
/***********************************************************/
UnifracWeightedCommand::UnifracWeightedCommand(string option) {
try {
if (validParameter.isValidParameter(it->first, myArray, it->second) != true) { abort = true; }
}
+ //initialize outputTypes
+ vector<string> tempOutNames;
+ outputTypes["weighted"] = tempOutNames;
+ outputTypes["wsummary"] = tempOutNames;
+ outputTypes["phylip"] = tempOutNames;
+
if (globaldata->gTree.size() == 0) {//no trees were read
m->mothurOut("You must execute the read.tree command, before you may execute the unifrac.weighted command."); m->mothurOutEndLine(); abort = true; }
tmap = globaldata->gTreemap;
sumFile = outputDir + m->getSimpleName(globaldata->getTreeFile()) + ".wsummary";
m->openOutputFile(sumFile, outSum);
- outputNames.push_back(sumFile);
+ outputNames.push_back(sumFile); outputTypes["wsummary"].push_back(sumFile);
util = new SharedUtil();
string s; //to make work with setgroups
void UnifracWeightedCommand::help(){
try {
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 unifrac.weighted command parameters are groups, iters, distance, processors 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 processors parameter allows you to specify the number of processors to use. The default is 1.\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");
userData.resize(numComp,0); //data[0] = weightedscore AB, data[1] = weightedscore AC...
randomData.resize(numComp,0); //data[0] = weightedscore AB, data[1] = weightedscore AC...
- //create new tree with same num nodes and leaves as users
- randT = new Tree();
-
//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; }
+ if (m->control_pressed) { 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...
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");
+ outputTypes["weighted"].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;
- }
-
+ if (m->control_pressed) { if (random) { delete output; } outSum.close(); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } return 0; }
//save users score
for (int s=0; s<numComp; s++) {
}
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++) {
+ for (int l = 0; l < a; l++) {
vector<string> groups; groups.push_back(globaldata->Groups[a]); groups.push_back(globaldata->Groups[l]);
namesOfGroupCombos.push_back(groups);
}
}
-
+
+ lines.clear();
+
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
if(processors != 1){
int numPairs = namesOfGroupCombos.size();
if(i == processors - 1){
numPairsPerProcessor = numPairs - i * numPairsPerProcessor;
}
- lines.push_back(new linePair(startPos, numPairsPerProcessor));
+ lines.push_back(linePair(startPos, numPairsPerProcessor));
}
}
#endif
//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);
+ driver(T[i], namesOfGroupCombos, 0, namesOfGroupCombos.size(), rScores);
}else{
- createProcesses(T[i], randT, namesOfGroupCombos, sums, rScores);
- for (int i = 0; i < lines.size(); i++) { delete lines[i]; } lines.clear();
+ createProcesses(T[i], namesOfGroupCombos, rScores);
}
#else
- driver(T[i], randT, namesOfGroupCombos, 0, namesOfGroupCombos.size(), sums, rScores);
+ driver(T[i], namesOfGroupCombos, 0, namesOfGroupCombos.size(), 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; }
+
+ //report progress
+ m->mothurOut("Iter: " + toString(j+1)); m->mothurOutEndLine();
}
-
-
+ lines.clear();
+
//find the signifigance of the score for summary file
for (int f = 0; f < numComp; f++) {
//sort random scores
}
- if (m->control_pressed) { delete randT; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } return 0; }
+ if (m->control_pressed) { outSum.close(); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); } return 0; }
printWSummaryFile();
//clear out users groups
globaldata->Groups.clear();
- delete randT;
if (m->control_pressed) {
for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str()); }
}
/**************************************************************************************************/
-int UnifracWeightedCommand::createProcesses(Tree* t, Tree* randT, vector< vector<string> > namesOfGroupCombos, vector<double>& sums, vector< vector<double> >& scores) {
+int UnifracWeightedCommand::createProcesses(Tree* t, vector< vector<string> > namesOfGroupCombos, vector< vector<double> >& scores) {
try {
#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
- int process = 0;
+ int process = 1;
int num = 0;
vector<int> processIDS;
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();
-
+ driver(t, namesOfGroupCombos, lines[process].start, lines[process].num, scores);
+
//pass numSeqs to parent
ofstream out;
- string tempFile = outputDir + toString(getpid()) + ".results.temp";
+ string tempFile = outputDir + toString(getpid()) + ".weightedcommand.results.temp";
m->openOutputFile(tempFile, out);
- out << results.size() << endl;
- for (int i = lines[process]->start; i < (lines[process]->start + lines[process]->num); i++) { out << results[i] << '\t'; } out << endl;
+ for (int i = lines[process].start; i < (lines[process].start + lines[process].num); i++) { out << scores[i][(scores[i].size()-1)] << '\t'; } out << endl;
out.close();
exit(0);
- }else { m->mothurOut("unable to spawn the necessary processes."); m->mothurOutEndLine(); 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);
+ }
}
+ driver(t, namesOfGroupCombos, lines[0].start, lines[0].num, scores);
+
//force parent to wait until all the processes are done
- for (int i=0;i<processors;i++) {
+ 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;i++) {
+ for (int i=0;i<(processors-1);i++) {
+
ifstream in;
- string s = outputDir + toString(processIDS[i]) + ".results.temp";
+ string s = outputDir + toString(processIDS[i]) + ".weightedcommand.results.temp";
m->openInputFile(s, in);
- vector<double> r;
-
- //get quantiles
- while (!in.eof()) {
- int num;
- in >> num;
-
- m->gobble(in);
-
- double w;
- for (int j = 0; j < num; j++) {
- in >> w;
- r.push_back(w);
- }
- m->gobble(in);
- }
+ double tempScore;
+ for (int j = lines[(i+1)].start; j < (lines[(i+1)].start + lines[(i+1)].num); j++) { in >> tempScore; scores[j].push_back(tempScore); }
in.close();
remove(s.c_str());
-
- //save quan in quantiles
- for (int j = 0; j < r.size(); j++) {
- //put all values of r into results
- results.push_back(r[j]);
- }
}
- m->mothurOut("DONE."); m->mothurOutEndLine(); m->mothurOutEndLine();
-
return 0;
#endif
}
}
/**************************************************************************************************/
-int UnifracWeightedCommand::driver(Tree* t, Tree* randT, vector< vector<string> > namesOfGroupCombos, int start, int num, vector<double>& sums, vector< vector<double> >& scores) {
+int UnifracWeightedCommand::driver(Tree* t, vector< vector<string> > namesOfGroupCombos, int start, int num, vector< vector<double> >& scores) {
try {
- int count = 0;
- int total = start+num;
- int twentyPercent = (total * 0.20);
+ Tree* randT = new Tree();
for (int h = start; h < (start+num); h++) {
-
+
if (m->control_pressed) { return 0; }
//initialize weighted score
if (m->control_pressed) { delete randT; return 0; }
-
//get wscore of random tree
- EstOutput randomData = weighted->getValues(randT, groupA, groupB, sums);
-
+ EstOutput randomData = weighted->getValues(randT, groupA, groupB);
+
if (m->control_pressed) { delete randT; return 0; }
//save scores
scores[h].push_back(randomData[0]);
-
- count++;
-
- //report progress
- if((h) % twentyPercent == 0){ m->mothurOut("Random comparison percentage complete: " + toString(int((h / (float)total) * 100.0))); m->mothurOutEndLine(); }
}
-
- m->mothurOut("Random comparison percentage complete: 100"); m->mothurOutEndLine();
-
+
+ delete randT;
+
return 0;
}
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;
- m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count])); m->mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" + toString(WScoreSig[count]) + "\n");
}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;
- m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters)))); m->mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" + toString((1/float(iters))) + "\n");
}
}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;
- m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00"); m->mothurOutEndLine();
+ m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00\n");
}
count++;
}
string phylipFileName = outputDir + m->getSimpleName(globaldata->getTreeFile()) + toString(i+1) + ".weighted.dist";
outputNames.push_back(phylipFileName);
+ outputTypes["phylip"].push_back(phylipFileName);
ofstream out;
m->openOutputFile(phylipFileName, out);
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