unifracweightedcommand.cpp

   1 /*
   2  *  unifracweightedcommand.cpp
   3  *  Mothur
   4  *
   5  *  Created by Sarah Westcott on 2/9/09.
   6  *  Copyright 2009 Schloss Lab UMASS Amherst. All rights reserved.
   7  *
   8  */
   9
  10 #include "unifracweightedcommand.h"
  11
  12 /***********************************************************/
  13 UnifracWeightedCommand::UnifracWeightedCommand(string option) {
  14         try {
  15                 globaldata = GlobalData::getInstance();
  16                 abort = false;
  17                 Groups.clear();
  18
  19                 //allow user to run help
  20                 if(option == "help") { help(); abort = true; }
  21
  22                 else {
  23                         //valid paramters for this command
  24                         string Array[] =  {"groups","iters","distance","random","processors","outputdir","inputdir"};
  25                         vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
  26
  27                         OptionParser parser(option);
  28                         map<string,string> parameters=parser.getParameters();
  29
  30                         ValidParameters validParameter;
  31
  32                         //check to make sure all parameters are valid for command
  33                         for (map<string,string>::iterator it = parameters.begin(); it != parameters.end(); it++) {
  34                                 if (validParameter.isValidParameter(it->first, myArray, it->second) != true) {  abort = true;  }
  35                         }
  36
  37                         if (globaldata->gTree.size() == 0) {//no trees were read
  38                                 m->mothurOut("You must execute the read.tree command, before you may execute the unifrac.weighted command."); m->mothurOutEndLine(); abort = true;  }
  39
  40                         //if the user changes the output directory command factory will send this info to us in the output parameter
  41                         outputDir = validParameter.validFile(parameters, "outputdir", false);           if (outputDir == "not found"){
  42                                 outputDir = "";
  43                                 outputDir += m->hasPath(globaldata->inputFileName); //if user entered a file with a path then preserve it
  44                         }
  45
  46                         //check for optional parameter and set defaults
  47                         // ...at some point should added some additional type checking...
  48                         groups = validParameter.validFile(parameters, "groups", false);
  49                         if (groups == "not found") { groups = ""; }
  50                         else {
  51                                 m->splitAtDash(groups, Groups);
  52                                 globaldata->Groups = Groups;
  53                         }
  54
  55                         itersString = validParameter.validFile(parameters, "iters", false);                     if (itersString == "not found") { itersString = "1000"; }
  56                         convert(itersString, iters);
  57
  58                         string temp = validParameter.validFile(parameters, "distance", false);                  if (temp == "not found") { temp = "false"; }
  59                         phylip = m->isTrue(temp);
  60
  61                         temp = validParameter.validFile(parameters, "random", false);                                   if (temp == "not found") { temp = "F"; }
  62                         random = m->isTrue(temp);
  63
  64                         temp = validParameter.validFile(parameters, "processors", false);       if (temp == "not found"){       temp = "1";                             }
  65                         convert(temp, processors);
  66
  67                         if (!random) {  iters = 0;  } //turn off random calcs
  68
  69
  70                         if (abort == false) {
  71                                 T = globaldata->gTree;
  72                                 tmap = globaldata->gTreemap;
  73                                 sumFile = outputDir + m->getSimpleName(globaldata->getTreeFile()) + ".wsummary";
  74                                 m->openOutputFile(sumFile, outSum);
  75                                 outputNames.push_back(sumFile);
  76
  77                                 util = new SharedUtil();
  78                                 string s; //to make work with setgroups
  79                                 util->setGroups(globaldata->Groups, tmap->namesOfGroups, s, numGroups, "weighted");     //sets the groups the user wants to analyze
  80                                 util->getCombos(groupComb, globaldata->Groups, numComp);
  81
  82                                 weighted = new Weighted(tmap);
  83
  84                         }
  85                 }
  86
  87
  88         }
  89         catch(exception& e) {
  90                 m->errorOut(e, "UnifracWeightedCommand", "UnifracWeightedCommand");
  91                 exit(1);
  92         }
  93 }
  94 //**********************************************************************************************************************
  95
  96 void UnifracWeightedCommand::help(){
  97         try {
  98                 m->mothurOut("The unifrac.weighted command can only be executed after a successful read.tree command.\n");
  99                 m->mothurOut("The unifrac.weighted command parameters are groups, iters, distance and random.  No parameters are required.\n");
 100                 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");
 101                 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");
 102                 m->mothurOut("The distance parameter allows you to create a distance file from the results. The default is false.\n");
 103                 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");
 104                 m->mothurOut("The unifrac.weighted command should be in the following format: unifrac.weighted(groups=yourGroups, iters=yourIters).\n");
 105                 m->mothurOut("Example unifrac.weighted(groups=A-B-C, iters=500).\n");
 106                 m->mothurOut("The default value for groups is all the groups in your groupfile, and iters is 1000.\n");
 107                 m->mothurOut("The unifrac.weighted command output two files: .weighted and .wsummary their descriptions are in the manual.\n");
 108                 m->mothurOut("Note: No spaces between parameter labels (i.e. groups), '=' and parameters (i.e.yourGroups).\n\n");
 109         }
 110         catch(exception& e) {
 111                 m->errorOut(e, "UnifracWeightedCommand", "help");
 112                 exit(1);
 113         }
 114 }
 115
 116 /***********************************************************/
 117 int UnifracWeightedCommand::execute() {
 118         try {
 119
 120                 if (abort == true) { return 0; }
 121
 122                 int start = time(NULL);
 123
 124                 //get weighted for users tree
 125                 userData.resize(numComp,0);  //data[0] = weightedscore AB, data[1] = weightedscore AC...
 126                 randomData.resize(numComp,0); //data[0] = weightedscore AB, data[1] = weightedscore AC...
 127
 128                 //create new tree with same num nodes and leaves as users
 129                 randT = new Tree();
 130
 131                 //get weighted scores for users trees
 132                 for (int i = 0; i < T.size(); i++) {
 133
 134                         if (m->control_pressed) { delete randT; outSum.close(); for (int i = 0; i < outputNames.size(); i++) {  remove(outputNames[i].c_str());  } return 0; }
 135
 136                         counter = 0;
 137                         rScores.resize(numComp);  //data[0] = weightedscore AB, data[1] = weightedscore AC...
 138                         uScores.resize(numComp);  //data[0] = weightedscore AB, data[1] = weightedscore AC...
 139
 140                         if (random) {
 141                                 output = new ColumnFile(outputDir + m->getSimpleName(globaldata->getTreeFile())  + toString(i+1) + ".weighted", itersString);
 142                                 outputNames.push_back(outputDir + m->getSimpleName(globaldata->getTreeFile())  + toString(i+1) + ".weighted");
 143                         }
 144
 145                         userData = weighted->getValues(T[i], processors, outputDir);  //userData[0] = weightedscore
 146
 147                         if (m->control_pressed) {
 148                                 delete randT;
 149                                 if (random) { delete output; }
 150                                 outSum.close();
 151                                 for (int i = 0; i < outputNames.size(); i++) {  remove(outputNames[i].c_str());  }
 152                                 return 0;
 153                         }
 154
 155
 156                         //save users score
 157                         for (int s=0; s<numComp; s++) {
 158                                 //add users score to vector of user scores
 159                                 uScores[s].push_back(userData[s]);
 160
 161                                 //save users tree score for summary file
 162                                 utreeScores.push_back(userData[s]);
 163                         }
 164
 165                         if (random) {
 166                                 vector<double> sums = weighted->getBranchLengthSums(T[i]);
 167
 168                                 //calculate number of comparisons i.e. with groups A,B,C = AB, AC, BC = 3;
 169                                 vector< vector<string> > namesOfGroupCombos;
 170                                 for (int a=0; a<numGroups; a++) {
 171                                         for (int l = a+1; l < numGroups; l++) {
 172                                                 vector<string> groups; groups.push_back(globaldata->Groups[a]); groups.push_back(globaldata->Groups[l]);
 173                                                 namesOfGroupCombos.push_back(groups);
 174                                         }
 175                                 }
 176
 177                                 #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
 178                                         if(processors != 1){
 179                                                 int numPairs = namesOfGroupCombos.size();
 180                                                 int numPairsPerProcessor = numPairs / processors;
 181
 182                                                 for (int i = 0; i < processors; i++) {
 183                                                         int startPos = i * numPairsPerProcessor;
 184                                                         if(i == processors - 1){
 185                                                                 numPairsPerProcessor = numPairs - i * numPairsPerProcessor;
 186                                                         }
 187                                                         lines.push_back(new linePair(startPos, numPairsPerProcessor));
 188                                                 }
 189                                         }
 190                                 #endif
 191
 192
 193                                 //get scores for random trees
 194                                 for (int j = 0; j < iters; j++) {
 195                                         int count = 0;
 196
 197                                         #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
 198                                                 if(processors == 1){
 199                                                         driver(T[i], randT, namesOfGroupCombos, 0, namesOfGroupCombos.size(), sums, rScores);
 200                                                 }else{
 201                                                         createProcesses(T[i], randT, namesOfGroupCombos, sums, rScores);
 202                                                         for (int i = 0; i < lines.size(); i++) {  delete lines[i];  }  lines.clear();
 203                                                 }
 204                                         #else
 205                                                 driver(T[i], randT, namesOfGroupCombos, 0, namesOfGroupCombos.size(), sums, rScores);
 206                                         #endif
 207
 208                                         if (m->control_pressed) { delete output; outSum.close(); for (int i = 0; i < outputNames.size(); i++) { remove(outputNames[i].c_str());  } return 0; }
 209                                 }
 210
 211
 212                                 //find the signifigance of the score for summary file
 213                                 for (int f = 0; f < numComp; f++) {
 214                                         //sort random scores
 215                                         sort(rScores[f].begin(), rScores[f].end());
 216
 217                                         //the index of the score higher than yours is returned
 218                                         //so if you have 1000 random trees the index returned is 100
 219                                         //then there are 900 trees with a score greater then you.
 220                                         //giving you a signifigance of 0.900
 221                                         int index = findIndex(userData[f], f);    if (index == -1) { m->mothurOut("error in UnifracWeightedCommand"); m->mothurOutEndLine(); exit(1); } //error code
 222
 223                                         //the signifigance is the number of trees with the users score or higher
 224                                         WScoreSig.push_back((iters-index)/(float)iters);
 225                                 }
 226
 227                                 //out << "Tree# " << i << endl;
 228                                 calculateFreqsCumuls();
 229                                 printWeightedFile();
 230
 231                                 delete output;
 232
 233                         }
 234
 235                         //clear data
 236                         rScores.clear();
 237                         uScores.clear();
 238                         validScores.clear();
 239                 }
 240
 241
 242                 if (m->control_pressed) { delete randT; outSum.close(); for (int i = 0; i < outputNames.size(); i++) {  remove(outputNames[i].c_str());  } return 0;  }
 243
 244                 printWSummaryFile();
 245
 246                 if (phylip) {   createPhylipFile();             }
 247
 248                 //clear out users groups
 249                 globaldata->Groups.clear();
 250
 251                 delete randT;
 252
 253                 if (m->control_pressed) {
 254                         for (int i = 0; i < outputNames.size(); i++) {  remove(outputNames[i].c_str());  }
 255                         return 0;
 256                 }
 257
 258                 m->mothurOut("It took " + toString(time(NULL) - start) + " secs to run unifrac.weighted."); m->mothurOutEndLine();
 259
 260                 m->mothurOutEndLine();
 261                 m->mothurOut("Output File Names: "); m->mothurOutEndLine();
 262                 for (int i = 0; i < outputNames.size(); i++) {  m->mothurOut(outputNames[i]); m->mothurOutEndLine();    }
 263                 m->mothurOutEndLine();
 264
 265                 return 0;
 266
 267         }
 268         catch(exception& e) {
 269                 m->errorOut(e, "UnifracWeightedCommand", "execute");
 270                 exit(1);
 271         }
 272 }
 273 /**************************************************************************************************/
 274
 275 int UnifracWeightedCommand::createProcesses(Tree* t, Tree* randT, vector< vector<string> > namesOfGroupCombos, vector<double>& sums, vector< vector<double> >& scores) {
 276         try {
 277 #if defined (__APPLE__) || (__MACH__) || (linux) || (__linux)
 278                 int process = 1;
 279                 int num = 0;
 280                 vector<int> processIDS;
 281
 282                 EstOutput results;
 283
 284                 //loop through and create all the processes you want
 285                 while (process != processors) {
 286                         int pid = fork();
 287
 288                         if (pid > 0) {
 289                                 processIDS.push_back(pid);  //create map from line number to pid so you can append files in correct order later
 290                                 process++;
 291                         }else if (pid == 0){
 292                                 driver(t, randT, namesOfGroupCombos, lines[process]->start, lines[process]->num, sums, scores);
 293
 294                                 m->mothurOut("Merging results."); m->mothurOutEndLine();
 295
 296                                 //pass numSeqs to parent
 297                                 ofstream out;
 298                                 string tempFile = outputDir + toString(getpid()) + ".weightedcommand.results.temp";
 299                                 m->openOutputFile(tempFile, out);
 300                                 for (int i = lines[process]->start; i < (lines[process]->start + lines[process]->num); i++) {  out << scores[i][0] << '\t';  } out << endl;
 301                                 out.close();
 302
 303                                 exit(0);
 304                         }else { m->mothurOut("unable to spawn the necessary processes."); m->mothurOutEndLine(); exit(0); }
 305                 }
 306
 307                 driver(t, randT, namesOfGroupCombos, lines[0]->start, lines[0]->num, sums, scores);
 308
 309                 //force parent to wait until all the processes are done
 310                 for (int i=0;i<(processors-1);i++) {
 311                         int temp = processIDS[i];
 312                         wait(&temp);
 313                 }
 314
 315                 //get data created by processes
 316                 for (int i=0;i<(processors-1);i++) {
 317                         ifstream in;
 318                         string s = outputDir + toString(processIDS[i]) + ".weightedcommand.results.temp";
 319                         m->openInputFile(s, in);
 320
 321                         for (int i = lines[process]->start; i < (lines[process]->start + lines[process]->num); i++) { in >> scores[i][0]; }
 322                         in.close();
 323                         remove(s.c_str());
 324                 }
 325
 326                 m->mothurOut("DONE."); m->mothurOutEndLine(); m->mothurOutEndLine();
 327
 328                 return 0;
 329 #endif
 330         }
 331         catch(exception& e) {
 332                 m->errorOut(e, "UnifracWeightedCommand", "createProcesses");
 333                 exit(1);
 334         }
 335 }
 336
 337 /**************************************************************************************************/
 338 int UnifracWeightedCommand::driver(Tree* t, Tree* randT, vector< vector<string> > namesOfGroupCombos, int start, int num, vector<double>& sums, vector< vector<double> >& scores) {
 339  try {
 340                 int count = 0;
 341                 int total = num;
 342                 int twentyPercent = (total * 0.20);
 343
 344                 for (int h = start; h < (start+num); h++) {
 345
 346                         if (m->control_pressed) { return 0; }
 347
 348                         //initialize weighted score
 349                         string groupA = namesOfGroupCombos[h][0];
 350                         string groupB = namesOfGroupCombos[h][1];
 351
 352                         //copy T[i]'s info.
 353                         randT->getCopy(t);
 354
 355                         //create a random tree with same topology as T[i], but different labels
 356                         randT->assembleRandomUnifracTree(groupA, groupB);
 357
 358                         if (m->control_pressed) { delete randT;  return 0;  }
 359
 360
 361                         //get wscore of random tree
 362                         EstOutput randomData = weighted->getValues(randT, groupA, groupB, sums);
 363
 364                         if (m->control_pressed) { delete randT;  return 0;  }
 365
 366                         //save scores
 367                         scores[h].push_back(randomData[0]);
 368
 369                         count++;
 370
 371                         //report progress
 372                         if((count) % twentyPercent == 0){       m->mothurOut("Random comparison percentage complete: " + toString(int((count / (float)total) * 100.0))); m->mothurOutEndLine();         }
 373                 }
 374
 375                 m->mothurOut("Random comparison percentage complete: 100"); m->mothurOutEndLine();
 376
 377                 return 0;
 378
 379         }
 380         catch(exception& e) {
 381                 m->errorOut(e, "UnifracWeightedCommand", "driver");
 382                 exit(1);
 383         }
 384 }
 385 /***********************************************************/
 386 void UnifracWeightedCommand::printWeightedFile() {
 387         try {
 388                 vector<double> data;
 389                 vector<string> tags;
 390                 tags.push_back("Score"); tags.push_back("RandFreq"); tags.push_back("RandCumul");
 391
 392                 for(int a = 0; a < numComp; a++) {
 393                         output->initFile(groupComb[a], tags);
 394                         //print each line
 395                         for (map<float,float>::iterator it = validScores.begin(); it != validScores.end(); it++) {
 396                                 data.push_back(it->first);  data.push_back(rScoreFreq[a][it->first]); data.push_back(rCumul[a][it->first]);
 397                                 output->output(data);
 398                                 data.clear();
 399                         }
 400                         output->resetFile();
 401                 }
 402         }
 403         catch(exception& e) {
 404                 m->errorOut(e, "UnifracWeightedCommand", "printWeightedFile");
 405                 exit(1);
 406         }
 407 }
 408
 409
 410 /***********************************************************/
 411 void UnifracWeightedCommand::printWSummaryFile() {
 412         try {
 413                 //column headers
 414                 outSum << "Tree#" << '\t' << "Groups" << '\t' << "WScore" << '\t' << "WSig" <<  endl;
 415                 m->mothurOut("Tree#\tGroups\tWScore\tWSig"); m->mothurOutEndLine();
 416
 417                 //format output
 418                 outSum.setf(ios::fixed, ios::floatfield); outSum.setf(ios::showpoint);
 419
 420                 //print each line
 421                 int count = 0;
 422                 for (int i = 0; i < T.size(); i++) {
 423                         for (int j = 0; j < numComp; j++) {
 424                                 if (random) {
 425                                         if (WScoreSig[count] > (1/(float)iters)) {
 426                                                 outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
 427                                                 cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << WScoreSig[count] << endl;
 428                                                 m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t" +  toString(WScoreSig[count])); m->mothurOutEndLine();
 429                                         }else{
 430                                                 outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
 431                                                 cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << setprecision(itersString.length()) << "<" << (1/float(iters)) << endl;
 432                                                 m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t<" +  toString((1/float(iters)))); m->mothurOutEndLine();
 433                                         }
 434                                 }else{
 435                                         outSum << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
 436                                         cout << setprecision(6) << i+1 << '\t' << groupComb[j] << '\t' << utreeScores[count] << '\t' << "0.00" << endl;
 437                                         m->mothurOutJustToLog(toString(i+1) +"\t" + groupComb[j] +"\t" + toString(utreeScores[count]) +"\t0.00"); m->mothurOutEndLine();
 438                                 }
 439                                 count++;
 440                         }
 441                 }
 442                 outSum.close();
 443         }
 444         catch(exception& e) {
 445                 m->errorOut(e, "UnifracWeightedCommand", "printWSummaryFile");
 446                 exit(1);
 447         }
 448 }
 449 /***********************************************************/
 450 void UnifracWeightedCommand::createPhylipFile() {
 451         try {
 452                 int count = 0;
 453                 //for each tree
 454                 for (int i = 0; i < T.size(); i++) {
 455
 456                         string phylipFileName = outputDir + m->getSimpleName(globaldata->getTreeFile())  + toString(i+1) + ".weighted.dist";
 457                         outputNames.push_back(phylipFileName);
 458                         ofstream out;
 459                         m->openOutputFile(phylipFileName, out);
 460
 461                         //output numSeqs
 462                         out << globaldata->Groups.size() << endl;
 463
 464                         //make matrix with scores in it
 465                         vector< vector<float> > dists;  dists.resize(globaldata->Groups.size());
 466                         for (int i = 0; i < globaldata->Groups.size(); i++) {
 467                                 dists[i].resize(globaldata->Groups.size(), 0.0);
 468                         }
 469
 470                         //flip it so you can print it
 471                         for (int r=0; r<globaldata->Groups.size(); r++) {
 472                                 for (int l = r+1; l < globaldata->Groups.size(); l++) {
 473                                         dists[r][l] = utreeScores[count];
 474                                         dists[l][r] = utreeScores[count];
 475                                         count++;
 476                                 }
 477                         }
 478
 479                         //output to file
 480                         for (int r=0; r<globaldata->Groups.size(); r++) {
 481                                 //output name
 482                                 string name = globaldata->Groups[r];
 483                                 if (name.length() < 10) { //pad with spaces to make compatible
 484                                         while (name.length() < 10) {  name += " ";  }
 485                                 }
 486                                 out << name << '\t';
 487
 488                                 //output distances
 489                                 for (int l = 0; l < r; l++) {   out  << dists[r][l] << '\t';  }
 490                                 out << endl;
 491                         }
 492                         out.close();
 493                 }
 494         }
 495         catch(exception& e) {
 496                 m->errorOut(e, "UnifracWeightedCommand", "createPhylipFile");
 497                 exit(1);
 498         }
 499 }
 500 /***********************************************************/
 501 int UnifracWeightedCommand::findIndex(float score, int index) {
 502         try{
 503                 for (int i = 0; i < rScores[index].size(); i++) {
 504                         if (rScores[index][i] >= score) {       return i;       }
 505                 }
 506                 return rScores[index].size();
 507         }
 508         catch(exception& e) {
 509                 m->errorOut(e, "UnifracWeightedCommand", "findIndex");
 510                 exit(1);
 511         }
 512 }
 513
 514 /***********************************************************/
 515
 516 void UnifracWeightedCommand::calculateFreqsCumuls() {
 517         try {
 518                 //clear out old tree values
 519                 rScoreFreq.clear();
 520                 rScoreFreq.resize(numComp);
 521                 rCumul.clear();
 522                 rCumul.resize(numComp);
 523                 validScores.clear();
 524
 525                 //calculate frequency
 526                 for (int f = 0; f < numComp; f++) {
 527                         for (int i = 0; i < rScores[f].size(); i++) { //looks like 0,0,1,1,1,2,4,7...  you want to make a map that say rScoreFreq[0] = 2, rScoreFreq[1] = 3...
 528                                 validScores[rScores[f][i]] = rScores[f][i];
 529                                 map<float,float>::iterator it = rScoreFreq[f].find(rScores[f][i]);
 530                                 if (it != rScoreFreq[f].end()) {
 531                                         rScoreFreq[f][rScores[f][i]]++;
 532                                 }else{
 533                                         rScoreFreq[f][rScores[f][i]] = 1;
 534                                 }
 535                         }
 536                 }
 537
 538                 //calculate rcumul
 539                 for(int a = 0; a < numComp; a++) {
 540                         float rcumul = 1.0000;
 541                         //this loop fills the cumulative maps and put 0.0000 in the score freq map to make it easier to print.
 542                         for (map<float,float>::iterator it = validScores.begin(); it != validScores.end(); it++) {
 543                                 //make rscoreFreq map and rCumul
 544                                 map<float,float>::iterator it2 = rScoreFreq[a].find(it->first);
 545                                 rCumul[a][it->first] = rcumul;
 546                                 //get percentage of random trees with that info
 547                                 if (it2 != rScoreFreq[a].end()) {  rScoreFreq[a][it->first] /= iters; rcumul-= it2->second;  }
 548                                 else { rScoreFreq[a][it->first] = 0.0000; } //no random trees with that score
 549                         }
 550                 }
 551
 552         }
 553         catch(exception& e) {
 554                 m->errorOut(e, "UnifracWeightedCommand", "calculateFreqsCums");
 555                 exit(1);
 556         }
 557 }
 558
 559 /***********************************************************/
 560
 561
 562
 563
 564