bayesian.cpp

   1 /*
   2  *  bayesian.cpp
   3  *  Mothur
   4  *
   5  *  Created by westcott on 11/3/09.
   6  *  Copyright 2009 Schloss Lab. All rights reserved.
   7  *
   8  */
   9
  10 #include "bayesian.h"
  11 #include "kmer.hpp"
  12 #include "phylosummary.h"
  13 #include "referencedb.h"
  14 /**************************************************************************************************/
  15 Bayesian::Bayesian(string tfile, string tempFile, string method, int ksize, int cutoff, int i, int tid) :
  16 Classify(), kmerSize(ksize), confidenceThreshold(cutoff), iters(i)  {
  17         try {
  18                 ReferenceDB* rdb = ReferenceDB::getInstance();
  19
  20                 threadID = tid;
  21                 string baseName = tempFile;
  22                 if (baseName == "saved") { baseName = rdb->getSavedReference(); }
  23
  24                 string baseTName = tfile;
  25                 if (baseTName == "saved") { baseTName = rdb->getSavedTaxonomy(); }
  26
  27                 /************calculate the probablity that each word will be in a specific taxonomy*************/
  28                 string tfileroot = baseTName.substr(0,baseTName.find_last_of(".")+1);
  29                 string tempfileroot = m->getRootName(m->getSimpleName(baseName));
  30                 string phyloTreeName = tfileroot + "tree.train";
  31                 string phyloTreeSumName = tfileroot + "tree.sum";
  32                 string probFileName = tfileroot + tempfileroot + char('0'+ kmerSize) + "mer.prob";
  33                 string probFileName2 = tfileroot + tempfileroot + char('0'+ kmerSize) + "mer.numNonZero";
  34
  35                 ofstream out;
  36                 ofstream out2;
  37
  38                 ifstream phyloTreeTest(phyloTreeName.c_str());
  39                 ifstream probFileTest2(probFileName2.c_str());
  40                 ifstream probFileTest(probFileName.c_str());
  41                 ifstream probFileTest3(phyloTreeSumName.c_str());
  42
  43                 int start = time(NULL);
  44
  45                 //if they are there make sure they were created after this release date
  46                 bool FilesGood = false;
  47                 if(probFileTest && probFileTest2 && phyloTreeTest && probFileTest3){
  48                         FilesGood = checkReleaseDate(probFileTest, probFileTest2, phyloTreeTest, probFileTest3);
  49                 }
  50
  51                 //if you want to save, but you dont need to calculate then just read
  52                 if (rdb->save && probFileTest && probFileTest2 && phyloTreeTest && probFileTest3 && FilesGood) {
  53                         ifstream saveIn;
  54                         m->openInputFile(tempFile, saveIn);
  55
  56                         while (!saveIn.eof()) {
  57                                 Sequence temp(saveIn);
  58                                 m->gobble(saveIn);
  59
  60                                 rdb->referenceSeqs.push_back(temp);
  61                         }
  62                         saveIn.close();
  63                 }
  64
  65                 if(probFileTest && probFileTest2 && phyloTreeTest && probFileTest3 && FilesGood){
  66                         if (tempFile == "saved") { m->mothurOutEndLine();  m->mothurOut("Using sequences from " + rdb->getSavedReference() + " that are saved in memory.");     m->mothurOutEndLine(); }
  67
  68                         m->mothurOut("Reading template taxonomy...     "); cout.flush();
  69
  70                         phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
  71
  72                         m->mothurOut("DONE."); m->mothurOutEndLine();
  73
  74                         genusNodes = phyloTree->getGenusNodes();
  75                         genusTotals = phyloTree->getGenusTotals();
  76
  77                         if (tfile == "saved") {
  78                                 m->mothurOutEndLine();  m->mothurOut("Using probabilties from " + rdb->getSavedTaxonomy() + " that are saved in memory...    ");        cout.flush();;
  79                                 wordGenusProb = rdb->wordGenusProb;
  80                         }else {
  81                                 m->mothurOut("Reading template probabilities...     "); cout.flush();
  82                                 readProbFile(probFileTest, probFileTest2, probFileName, probFileName2);
  83                         }
  84
  85                         //save probabilities
  86                         if (rdb->save) { rdb->wordGenusProb = wordGenusProb; }
  87                 }else{
  88
  89                         //create search database and names vector
  90                         generateDatabaseAndNames(tfile, tempFile, method, ksize, 0.0, 0.0, 0.0, 0.0);
  91
  92                         //prevents errors caused by creating shortcut files if you had an error in the sanity check.
  93                         if (m->control_pressed) {  m->mothurRemove(phyloTreeName);  m->mothurRemove(probFileName); m->mothurRemove(probFileName2); }
  94                         else{
  95                                 genusNodes = phyloTree->getGenusNodes();
  96                                 genusTotals = phyloTree->getGenusTotals();
  97
  98                                 m->mothurOut("Calculating template taxonomy tree...     "); cout.flush();
  99
 100                                 phyloTree->printTreeNodes(phyloTreeName);
 101
 102                                 m->mothurOut("DONE."); m->mothurOutEndLine();
 103
 104                                 m->mothurOut("Calculating template probabilities...     "); cout.flush();
 105
 106                                 numKmers = database->getMaxKmer() + 1;
 107
 108                                 //initialze probabilities
 109                                 wordGenusProb.resize(numKmers);
 110                         //cout << numKmers << '\t' << genusNodes.size() << endl;
 111                                 for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 112                         //cout << numKmers << '\t' << genusNodes.size() << endl;
 113                                 ofstream out;
 114                                 ofstream out2;
 115
 116                                 #ifdef USE_MPI
 117                                         int pid;
 118                                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 119
 120                                         if (pid == 0) {
 121                                 #endif
 122
 123
 124                                 m->openOutputFile(probFileName, out);
 125
 126                                 //output mothur version
 127                                 out << "#" << m->getVersion() << endl;
 128
 129                                 out << numKmers << endl;
 130
 131                                 m->openOutputFile(probFileName2, out2);
 132
 133                                 //output mothur version
 134                                 out2 << "#" << m->getVersion() << endl;
 135
 136                                 #ifdef USE_MPI
 137                                         }
 138                                 #endif
 139
 140
 141                                 //for each word
 142                                 for (int i = 0; i < numKmers; i++) {
 143                                         if (m->control_pressed) {  break; }
 144
 145                                         #ifdef USE_MPI
 146                                                 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 147
 148                                                 if (pid == 0) {
 149                                         #endif
 150
 151                                         out << i << '\t';
 152
 153                                         #ifdef USE_MPI
 154                                                 }
 155                                         #endif
 156
 157                                         vector<int> seqsWithWordi = database->getSequencesWithKmer(i);
 158
 159                                         map<int, int> count;
 160                                         for (int k = 0; k < genusNodes.size(); k++) {  count[genusNodes[k]] = 0;  }
 161
 162                                         //for each sequence with that word
 163                                         for (int j = 0; j < seqsWithWordi.size(); j++) {
 164                                                 int temp = phyloTree->getIndex(names[seqsWithWordi[j]]);
 165                                                 count[temp]++;  //increment count of seq in this genus who have this word
 166                                         }
 167
 168                                         //probabilityInTemplate = (# of seqs with that word in template + 0.50) / (total number of seqs in template + 1);
 169                                         float probabilityInTemplate = (seqsWithWordi.size() + 0.50) / (float) (names.size() + 1);
 170
 171                                         int numNotZero = 0;
 172                                         for (int k = 0; k < genusNodes.size(); k++) {
 173                                                 //probabilityInThisTaxonomy = (# of seqs with that word in this taxonomy + probabilityInTemplate) / (total number of seqs in this taxonomy + 1);
 174
 175
 176                                                 wordGenusProb[i][k] = log((count[genusNodes[k]] + probabilityInTemplate) / (float) (genusTotals[k] + 1));
 177
 178                                                 if (count[genusNodes[k]] != 0) {
 179                                                         #ifdef USE_MPI
 180                                                                 int pid;
 181                                                                 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 182
 183                                                                 if (pid == 0) {
 184                                                         #endif
 185
 186                                                         out << k << '\t' << wordGenusProb[i][k] << '\t';
 187
 188                                                         #ifdef USE_MPI
 189                                                                 }
 190                                                         #endif
 191
 192                                                         numNotZero++;
 193                                                 }
 194                                         }
 195
 196                                         #ifdef USE_MPI
 197                                                 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 198
 199                                                 if (pid == 0) {
 200                                         #endif
 201
 202                                         out << endl;
 203                                         out2 << probabilityInTemplate << '\t' << numNotZero << endl;
 204
 205                                         #ifdef USE_MPI
 206                                                 }
 207                                         #endif
 208                                 }
 209
 210                                 #ifdef USE_MPI
 211                                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 212
 213                                         if (pid == 0) {
 214                                 #endif
 215
 216                                 out.close();
 217                                 out2.close();
 218
 219                                 #ifdef USE_MPI
 220                                         }
 221                                 #endif
 222
 223                                 //read in new phylotree with less info. - its faster
 224                                 ifstream phyloTreeTest(phyloTreeName.c_str());
 225                                 delete phyloTree;
 226
 227                                 phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
 228
 229                                 //save probabilities
 230                                 if (rdb->save) { rdb->wordGenusProb = wordGenusProb; }
 231                         }
 232                 }
 233
 234                 m->mothurOut("DONE."); m->mothurOutEndLine();
 235                 m->mothurOut("It took " + toString(time(NULL) - start) + " seconds get probabilities. "); m->mothurOutEndLine();
 236         }
 237         catch(exception& e) {
 238                 m->errorOut(e, "Bayesian", "Bayesian");
 239                 exit(1);
 240         }
 241 }
 242 /**************************************************************************************************/
 243 Bayesian::~Bayesian() {
 244         try {
 245
 246                  delete phyloTree;
 247                  if (database != NULL) {  delete database; }
 248         }
 249         catch(exception& e) {
 250                 m->errorOut(e, "Bayesian", "~Bayesian");
 251                 exit(1);
 252         }
 253 }
 254
 255 /**************************************************************************************************/
 256 string Bayesian::getTaxonomy(Sequence* seq) {
 257         try {
 258                 string tax = "";
 259                 Kmer kmer(kmerSize);
 260
 261                 //get words contained in query
 262                 //getKmerString returns a string where the index in the string is hte kmer number
 263                 //and the character at that index can be converted to be the number of times that kmer was seen
 264
 265                 string queryKmerString = kmer.getKmerString(seq->getUnaligned());
 266
 267                 vector<int> queryKmers;
 268                 for (int i = 0; i < queryKmerString.length()-1; i++) {  // the -1 is to ignore any kmer with an N in it
 269                         if (queryKmerString[i] != '!') { //this kmer is in the query
 270                                 queryKmers.push_back(i);
 271                         }
 272                 }
 273
 274                 if (queryKmers.size() == 0) {  m->mothurOut(seq->getName() + "is bad."); m->mothurOutEndLine(); return "bad seq"; }
 275
 276
 277                 int index = getMostProbableTaxonomy(queryKmers);
 278
 279                 if (m->control_pressed) { return tax; }
 280
 281                 //bootstrap - to set confidenceScore
 282                 int numToSelect = queryKmers.size() / 8;
 283
 284                 tax = bootstrapResults(queryKmers, index, numToSelect);
 285
 286                 return tax;
 287         }
 288         catch(exception& e) {
 289                 m->errorOut(e, "Bayesian", "getTaxonomy");
 290                 exit(1);
 291         }
 292 }
 293 /**************************************************************************************************/
 294 string Bayesian::bootstrapResults(vector<int> kmers, int tax, int numToSelect) {
 295         try {
 296
 297                 map<int, int> confidenceScores;
 298
 299                 //initialize confidences to 0
 300                 int seqIndex = tax;
 301                 TaxNode seq = phyloTree->get(tax);
 302                 confidenceScores[tax] = 0;
 303
 304                 while (seq.level != 0) { //while you are not at the root
 305                         seqIndex = seq.parent;
 306                         confidenceScores[seqIndex] = 0;
 307                         seq = phyloTree->get(seq.parent);
 308                 }
 309
 310                 map<int, int>::iterator itBoot;
 311                 map<int, int>::iterator itBoot2;
 312                 map<int, int>::iterator itConvert;
 313
 314                 for (int i = 0; i < iters; i++) {
 315                         if (m->control_pressed) { return "control"; }
 316
 317                         vector<int> temp;
 318                         for (int j = 0; j < numToSelect; j++) {
 319                                 int index = int(rand() % kmers.size());
 320
 321                                 //add word to temp
 322                                 temp.push_back(kmers[index]);
 323                         }
 324
 325                         //get taxonomy
 326                         int newTax = getMostProbableTaxonomy(temp);
 327                         //int newTax = 1;
 328                         TaxNode taxonomyTemp = phyloTree->get(newTax);
 329
 330                         //add to confidence results
 331                         while (taxonomyTemp.level != 0) { //while you are not at the root
 332                                 itBoot2 = confidenceScores.find(newTax); //is this a classification we already have a count on
 333
 334                                 if (itBoot2 != confidenceScores.end()) { //this is a classification we need a confidence for
 335                                         (itBoot2->second)++;
 336                                 }
 337
 338                                 newTax = taxonomyTemp.parent;
 339                                 taxonomyTemp = phyloTree->get(newTax);
 340                         }
 341
 342                 }
 343
 344                 string confidenceTax = "";
 345                 simpleTax = "";
 346
 347                 int seqTaxIndex = tax;
 348                 TaxNode seqTax = phyloTree->get(tax);
 349
 350                 while (seqTax.level != 0) { //while you are not at the root
 351
 352                                 itBoot2 = confidenceScores.find(seqTaxIndex); //is this a classification we already have a count on
 353
 354                                 int confidence = 0;
 355                                 if (itBoot2 != confidenceScores.end()) { //already in confidence scores
 356                                         confidence = itBoot2->second;
 357                                 }
 358
 359                                 if (((confidence/(float)iters) * 100) >= confidenceThreshold) {
 360                                         confidenceTax = seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");" + confidenceTax;
 361                                         simpleTax = seqTax.name + ";" + simpleTax;
 362                                 }
 363
 364                                 seqTaxIndex = seqTax.parent;
 365                                 seqTax = phyloTree->get(seqTax.parent);
 366                 }
 367
 368                 if (confidenceTax == "") { confidenceTax = "unclassified;"; simpleTax = "unclassified;"; }
 369                 return confidenceTax;
 370
 371         }
 372         catch(exception& e) {
 373                 m->errorOut(e, "Bayesian", "bootstrapResults");
 374                 exit(1);
 375         }
 376 }
 377 /**************************************************************************************************/
 378 int Bayesian::getMostProbableTaxonomy(vector<int> queryKmer) {
 379         try {
 380                 int indexofGenus = 0;
 381
 382                 double maxProbability = -1000000.0;
 383                 //find taxonomy with highest probability that this sequence is from it
 384
 385
 386 //              cout << genusNodes.size() << endl;
 387
 388
 389                 for (int k = 0; k < genusNodes.size(); k++) {
 390                         //for each taxonomy calc its probability
 391
 392                         double prob = 0.0000;
 393                         for (int i = 0; i < queryKmer.size(); i++) {
 394                                 prob += wordGenusProb[queryKmer[i]][k];
 395                         }
 396
 397 //                      cout << phyloTree->get(genusNodes[k]).name << '\t' << prob << endl;
 398
 399                         //is this the taxonomy with the greatest probability?
 400                         if (prob > maxProbability) {
 401                                 indexofGenus = genusNodes[k];
 402                                 maxProbability = prob;
 403                         }
 404                 }
 405
 406
 407                 return indexofGenus;
 408         }
 409         catch(exception& e) {
 410                 m->errorOut(e, "Bayesian", "getMostProbableTaxonomy");
 411                 exit(1);
 412         }
 413 }
 414 /*************************************************************************************************
 415 map<string, int> Bayesian::parseTaxMap(string newTax) {
 416         try{
 417
 418                 map<string, int> parsed;
 419
 420                 newTax = newTax.substr(0, newTax.length()-1);  //get rid of last ';'
 421
 422                 //parse taxonomy
 423                 string individual;
 424                 while (newTax.find_first_of(';') != -1) {
 425                         individual = newTax.substr(0,newTax.find_first_of(';'));
 426                         newTax = newTax.substr(newTax.find_first_of(';')+1, newTax.length());
 427                         parsed[individual] = 1;
 428                 }
 429
 430                 //get last one
 431                 parsed[newTax] = 1;
 432
 433                 return parsed;
 434
 435         }
 436         catch(exception& e) {
 437                 m->errorOut(e, "Bayesian", "parseTax");
 438                 exit(1);
 439         }
 440 }
 441 /**************************************************************************************************/
 442 void Bayesian::readProbFile(ifstream& in, ifstream& inNum, string inName, string inNumName) {
 443         try{
 444
 445                 #ifdef USE_MPI
 446
 447                         int pid, num, num2, processors;
 448                         vector<unsigned long int> positions;
 449                         vector<unsigned long int> positions2;
 450
 451                         MPI_Status status;
 452                         MPI_File inMPI;
 453                         MPI_File inMPI2;
 454                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 455                         MPI_Comm_size(MPI_COMM_WORLD, &processors);
 456                         int tag = 2001;
 457
 458                         char inFileName[1024];
 459                         strcpy(inFileName, inNumName.c_str());
 460
 461                         char inFileName2[1024];
 462                         strcpy(inFileName2, inName.c_str());
 463
 464                         MPI_File_open(MPI_COMM_WORLD, inFileName, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI);  //comm, filename, mode, info, filepointer
 465                         MPI_File_open(MPI_COMM_WORLD, inFileName2, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI2);  //comm, filename, mode, info, filepointer
 466
 467                         if (pid == 0) {
 468                                 positions = m->setFilePosEachLine(inNumName, num);
 469                                 positions2 = m->setFilePosEachLine(inName, num2);
 470
 471                                 for(int i = 1; i < processors; i++) {
 472                                         MPI_Send(&num, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
 473                                         MPI_Send(&positions[0], (num+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
 474
 475                                         MPI_Send(&num2, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
 476                                         MPI_Send(&positions2[0], (num2+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
 477                                 }
 478
 479                         }else{
 480                                 MPI_Recv(&num, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
 481                                 positions.resize(num+1);
 482                                 MPI_Recv(&positions[0], (num+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
 483
 484                                 MPI_Recv(&num2, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
 485                                 positions2.resize(num2+1);
 486                                 MPI_Recv(&positions2[0], (num2+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
 487                         }
 488
 489                         //read version
 490                         int length = positions2[1] - positions2[0];
 491                         char* buf5 = new char[length];
 492
 493                         MPI_File_read_at(inMPI2, positions2[0], buf5, length, MPI_CHAR, &status);
 494                         delete buf5;
 495
 496                         //read numKmers
 497                         length = positions2[2] - positions2[1];
 498                         char* buf = new char[length];
 499
 500                         MPI_File_read_at(inMPI2, positions2[1], buf, length, MPI_CHAR, &status);
 501
 502                         string tempBuf = buf;
 503                         if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 504                         delete buf;
 505
 506                         istringstream iss (tempBuf,istringstream::in);
 507                         iss >> numKmers;
 508
 509                         //initialze probabilities
 510                         wordGenusProb.resize(numKmers);
 511
 512                         for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 513
 514                         int kmer, name;
 515                         vector<int> numbers; numbers.resize(numKmers);
 516                         float prob;
 517                         vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
 518
 519                         //read version
 520                         length = positions[1] - positions[0];
 521                         char* buf6 = new char[length];
 522
 523                         MPI_File_read_at(inMPI2, positions[0], buf6, length, MPI_CHAR, &status);
 524                         delete buf6;
 525
 526                         //read file
 527                         for(int i=1;i<num;i++){
 528                                 //read next sequence
 529                                 length = positions[i+1] - positions[i];
 530                                 char* buf4 = new char[length];
 531
 532                                 MPI_File_read_at(inMPI, positions[i], buf4, length, MPI_CHAR, &status);
 533
 534                                 tempBuf = buf4;
 535                                 if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 536                                 delete buf4;
 537
 538                                 istringstream iss (tempBuf,istringstream::in);
 539                                 iss >> zeroCountProb[i] >> numbers[i];
 540                         }
 541
 542                         MPI_File_close(&inMPI);
 543
 544                         for(int i=2;i<num2;i++){
 545                                 //read next sequence
 546                                 length = positions2[i+1] - positions2[i];
 547                                 char* buf4 = new char[length];
 548
 549                                 MPI_File_read_at(inMPI2, positions2[i], buf4, length, MPI_CHAR, &status);
 550
 551                                 tempBuf = buf4;
 552                                 if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 553                                 delete buf4;
 554
 555                                 istringstream iss (tempBuf,istringstream::in);
 556
 557                                 iss >> kmer;
 558
 559                                 //set them all to zero value
 560                                 for (int i = 0; i < genusNodes.size(); i++) {
 561                                         wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
 562                                 }
 563
 564                                 //get probs for nonzero values
 565                                 for (int i = 0; i < numbers[kmer]; i++) {
 566                                         iss >> name >> prob;
 567                                         wordGenusProb[kmer][name] = prob;
 568                                 }
 569
 570                         }
 571                         MPI_File_close(&inMPI2);
 572                         MPI_Barrier(MPI_COMM_WORLD); //make everyone wait - just in case
 573                 #else
 574                         //read version
 575                         string line = m->getline(in); m->gobble(in);
 576
 577                         in >> numKmers; m->gobble(in);
 578
 579                         //initialze probabilities
 580                         wordGenusProb.resize(numKmers);
 581
 582                         for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 583
 584                         int kmer, name, count;  count = 0;
 585                         vector<int> num; num.resize(numKmers);
 586                         float prob;
 587                         vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
 588
 589                         //read version
 590                         string line2 = m->getline(inNum); m->gobble(inNum);
 591
 592                         while (inNum) {
 593                                 inNum >> zeroCountProb[count] >> num[count];
 594                                 count++;
 595                                 m->gobble(inNum);
 596                         }
 597                         inNum.close();
 598
 599                         while(in) {
 600                                 in >> kmer;
 601
 602                                 //set them all to zero value
 603                                 for (int i = 0; i < genusNodes.size(); i++) {
 604                                         wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
 605                                 }
 606
 607                                 //get probs for nonzero values
 608                                 for (int i = 0; i < num[kmer]; i++) {
 609                                         in >> name >> prob;
 610                                         wordGenusProb[kmer][name] = prob;
 611                                 }
 612
 613                                 m->gobble(in);
 614                         }
 615                         in.close();
 616
 617                 #endif
 618         }
 619         catch(exception& e) {
 620                 m->errorOut(e, "Bayesian", "readProbFile");
 621                 exit(1);
 622         }
 623 }
 624 /**************************************************************************************************/
 625 bool Bayesian::checkReleaseDate(ifstream& file1, ifstream& file2, ifstream& file3, ifstream& file4) {
 626         try {
 627
 628                 bool good = true;
 629
 630                 vector<string> lines;
 631                 lines.push_back(m->getline(file1));
 632                 lines.push_back(m->getline(file2));
 633                 lines.push_back(m->getline(file3));
 634                 lines.push_back(m->getline(file4));
 635
 636                 //before we added this check
 637                 if ((lines[0][0] != '#') || (lines[1][0] != '#') || (lines[2][0] != '#') || (lines[3][0] != '#')) {  good = false;  }
 638                 else {
 639                         //rip off #
 640                         for (int i = 0; i < lines.size(); i++) { lines[i] = lines[i].substr(1);  }
 641
 642                         //get mothurs current version
 643                         string version = m->getVersion();
 644
 645                         vector<string> versionVector;
 646                         m->splitAtChar(version, versionVector, '.');
 647
 648                         //check each files version
 649                         for (int i = 0; i < lines.size(); i++) {
 650                                 vector<string> linesVector;
 651                                 m->splitAtChar(lines[i], linesVector, '.');
 652
 653                                 if (versionVector.size() != linesVector.size()) { good = false; break; }
 654                                 else {
 655                                         for (int j = 0; j < versionVector.size(); j++) {
 656                                                 int num1, num2;
 657                                                 convert(versionVector[j], num1);
 658                                                 convert(linesVector[j], num2);
 659
 660                                                 //if mothurs version is newer than this files version, then we want to remake it
 661                                                 if (num1 > num2) {  good = false; break;  }
 662                                         }
 663                                 }
 664
 665                                 if (!good) { break; }
 666                         }
 667                 }
 668
 669                 if (!good) {  file1.close(); file2.close(); file3.close(); file4.close();  }
 670                 else { file1.seekg(0);  file2.seekg(0);  file3.seekg(0);  file4.seekg(0);  }
 671
 672                 return good;
 673         }
 674         catch(exception& e) {
 675                 m->errorOut(e, "Bayesian", "checkReleaseDate");
 676                 exit(1);
 677         }
 678 }
 679 /**************************************************************************************************/
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