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, bool f, bool sh) :
  16 Classify(), kmerSize(ksize), confidenceThreshold(cutoff), iters(i) {
  17         try {
  18                 ReferenceDB* rdb = ReferenceDB::getInstance();
  19
  20                 threadID = tid;
  21                 flip = f;
  22         shortcuts = sh;
  23                 string baseName = tempFile;
  24
  25                 if (baseName == "saved") { baseName = rdb->getSavedReference(); }
  26
  27                 string baseTName = tfile;
  28                 if (baseTName == "saved") { baseTName = rdb->getSavedTaxonomy(); }
  29
  30                 /************calculate the probablity that each word will be in a specific taxonomy*************/
  31                 string tfileroot = m->getFullPathName(baseTName.substr(0,baseTName.find_last_of(".")+1));
  32                 string tempfileroot = m->getRootName(m->getSimpleName(baseName));
  33                 string phyloTreeName = tfileroot + "tree.train";
  34                 string phyloTreeSumName = tfileroot + "tree.sum";
  35                 string probFileName = tfileroot + tempfileroot + char('0'+ kmerSize) + "mer.prob";
  36                 string probFileName2 = tfileroot + tempfileroot + char('0'+ kmerSize) + "mer.numNonZero";
  37
  38                 ofstream out;
  39                 ofstream out2;
  40
  41                 ifstream phyloTreeTest(phyloTreeName.c_str());
  42                 ifstream probFileTest2(probFileName2.c_str());
  43                 ifstream probFileTest(probFileName.c_str());
  44                 ifstream probFileTest3(phyloTreeSumName.c_str());
  45
  46                 int start = time(NULL);
  47
  48                 //if they are there make sure they were created after this release date
  49                 bool FilesGood = false;
  50                 if(probFileTest && probFileTest2 && phyloTreeTest && probFileTest3){
  51                         FilesGood = checkReleaseDate(probFileTest, probFileTest2, phyloTreeTest, probFileTest3);
  52                 }
  53
  54                 //if you want to save, but you dont need to calculate then just read
  55                 if (rdb->save && probFileTest && probFileTest2 && phyloTreeTest && probFileTest3 && FilesGood && (tempFile != "saved")) {
  56                         ifstream saveIn;
  57                         m->openInputFile(tempFile, saveIn);
  58
  59                         while (!saveIn.eof()) {
  60                                 Sequence temp(saveIn);
  61                                 m->gobble(saveIn);
  62
  63                                 rdb->referenceSeqs.push_back(temp);
  64                         }
  65                         saveIn.close();
  66                 }
  67 FilesGood = false;
  68                 if(probFileTest && probFileTest2 && phyloTreeTest && probFileTest3 && FilesGood){
  69                         if (tempFile == "saved") { m->mothurOutEndLine();  m->mothurOut("Using sequences from " + rdb->getSavedReference() + " that are saved in memory.");     m->mothurOutEndLine(); }
  70
  71                         m->mothurOut("Reading template taxonomy...     "); cout.flush();
  72
  73                         phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
  74
  75                         m->mothurOut("DONE."); m->mothurOutEndLine();
  76
  77                         genusNodes = phyloTree->getGenusNodes();
  78                         genusTotals = phyloTree->getGenusTotals();
  79
  80                         if (tfile == "saved") {
  81                                 m->mothurOutEndLine();  m->mothurOut("Using probabilties from " + rdb->getSavedTaxonomy() + " that are saved in memory...    ");        cout.flush();;
  82                                 wordGenusProb = rdb->wordGenusProb;
  83                                 WordPairDiffArr = rdb->WordPairDiffArr;
  84                         }else {
  85                                 m->mothurOut("Reading template probabilities...     "); cout.flush();
  86                                 readProbFile(probFileTest, probFileTest2, probFileName, probFileName2);
  87                         }
  88
  89                         //save probabilities
  90                         if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
  91                 }else{
  92
  93                         //create search database and names vector
  94                         generateDatabaseAndNames(tfile, tempFile, method, ksize, 0.0, 0.0, 0.0, 0.0);
  95
  96                         //prevents errors caused by creating shortcut files if you had an error in the sanity check.
  97                         if (m->control_pressed) {  m->mothurRemove(phyloTreeName);  m->mothurRemove(probFileName); m->mothurRemove(probFileName2); }
  98                         else{
  99                                 genusNodes = phyloTree->getGenusNodes();
 100                                 genusTotals = phyloTree->getGenusTotals();
 101
 102                                 m->mothurOut("Calculating template taxonomy tree...     "); cout.flush();
 103
 104                                 phyloTree->printTreeNodes(phyloTreeName);
 105
 106                                 m->mothurOut("DONE."); m->mothurOutEndLine();
 107
 108                                 m->mothurOut("Calculating template probabilities...     "); cout.flush();
 109
 110                                 numKmers = database->getMaxKmer() + 1;
 111
 112                                 //initialze probabilities
 113                                 wordGenusProb.resize(numKmers);
 114                                 WordPairDiffArr.resize(numKmers);
 115
 116                                 for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 117                 ofstream out;
 118                                 ofstream out2;
 119
 120                                 #ifdef USE_MPI
 121                                         int pid;
 122                                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 123
 124                                         if (pid == 0) {
 125                                 #endif
 126
 127
 128                 if (shortcuts) {
 129                     m->openOutputFile(probFileName, out);
 130
 131                     //output mothur version
 132                     out << "#" << m->getVersion() << endl;
 133
 134                     out << numKmers << endl;
 135
 136                     m->openOutputFile(probFileName2, out2);
 137
 138                     //output mothur version
 139                     out2 << "#" << m->getVersion() << endl;
 140                 }
 141
 142                                 #ifdef USE_MPI
 143                                         }
 144                                 #endif
 145
 146
 147                                 //for each word
 148                                 for (int i = 0; i < numKmers; i++) {
 149                                         if (m->control_pressed) {  break; }
 150
 151                                         #ifdef USE_MPI
 152                                                 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 153
 154                                                 if (pid == 0) {
 155                                         #endif
 156
 157                     if (shortcuts) {  out << i << '\t'; }
 158
 159                                         #ifdef USE_MPI
 160                                                 }
 161                                         #endif
 162
 163                                         vector<int> seqsWithWordi = database->getSequencesWithKmer(i);
 164
 165                                         map<int, int> count;
 166                                         for (int k = 0; k < genusNodes.size(); k++) {  count[genusNodes[k]] = 0;  }
 167
 168                                         //for each sequence with that word
 169                                         for (int j = 0; j < seqsWithWordi.size(); j++) {
 170                                                 int temp = phyloTree->getIndex(names[seqsWithWordi[j]]);
 171                                                 count[temp]++;  //increment count of seq in this genus who have this word
 172                                         }
 173
 174                                         //probabilityInTemplate = (# of seqs with that word in template + 0.50) / (total number of seqs in template + 1);
 175                                         float probabilityInTemplate = (seqsWithWordi.size() + 0.50) / (float) (names.size() + 1);
 176                                         diffPair tempProb(log(probabilityInTemplate), 0.0);
 177                                         WordPairDiffArr[i] = tempProb;
 178
 179                                         int numNotZero = 0;
 180                                         for (int k = 0; k < genusNodes.size(); k++) {
 181                                                 //probabilityInThisTaxonomy = (# of seqs with that word in this taxonomy + probabilityInTemplate) / (total number of seqs in this taxonomy + 1);
 182
 183
 184                                                 wordGenusProb[i][k] = log((count[genusNodes[k]] + probabilityInTemplate) / (float) (genusTotals[k] + 1));
 185
 186                                                 if (count[genusNodes[k]] != 0) {
 187                                                         #ifdef USE_MPI
 188                                                                 int pid;
 189                                                                 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 190
 191                                                                 if (pid == 0) {
 192                                                         #endif
 193
 194                             if (shortcuts) { out << k << '\t' << wordGenusProb[i][k] << '\t' ; }
 195
 196                                                         #ifdef USE_MPI
 197                                                                 }
 198                                                         #endif
 199
 200                                                         numNotZero++;
 201                                                 }
 202                                         }
 203
 204                                         #ifdef USE_MPI
 205                                                 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 206
 207                                                 if (pid == 0) {
 208                                         #endif
 209
 210                             if (shortcuts) {
 211                                 out << endl;
 212                                 out2 << probabilityInTemplate << '\t' << numNotZero << '\t' << log(probabilityInTemplate) << endl;
 213                             }
 214
 215                                         #ifdef USE_MPI
 216                                                 }
 217                                         #endif
 218                                 }
 219
 220                                 #ifdef USE_MPI
 221                                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 222
 223                                         if (pid == 0) {
 224                                 #endif
 225
 226                         if (shortcuts) {
 227                             out.close();
 228                             out2.close();
 229                         }
 230                                 #ifdef USE_MPI
 231                                         }
 232                                 #endif
 233
 234                                 //read in new phylotree with less info. - its faster
 235                                 ifstream phyloTreeTest(phyloTreeName.c_str());
 236                                 delete phyloTree;
 237
 238                                 phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
 239
 240                                 //save probabilities
 241                                 if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
 242                         }
 243                 }
 244
 245                 generateWordPairDiffArr();
 246
 247                 //save probabilities
 248                 if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
 249
 250                 m->mothurOut("DONE."); m->mothurOutEndLine();
 251                 m->mothurOut("It took " + toString(time(NULL) - start) + " seconds get probabilities. "); m->mothurOutEndLine();
 252         }
 253         catch(exception& e) {
 254                 m->errorOut(e, "Bayesian", "Bayesian");
 255                 exit(1);
 256         }
 257 }
 258 /**************************************************************************************************/
 259 Bayesian::~Bayesian() {
 260         try {
 261
 262                  delete phyloTree;
 263                  if (database != NULL) {  delete database; }
 264         }
 265         catch(exception& e) {
 266                 m->errorOut(e, "Bayesian", "~Bayesian");
 267                 exit(1);
 268         }
 269 }
 270
 271 /**************************************************************************************************/
 272 string Bayesian::getTaxonomy(Sequence* seq) {
 273         try {
 274                 string tax = "";
 275                 Kmer kmer(kmerSize);
 276                 flipped = false;
 277
 278                 //get words contained in query
 279                 //getKmerString returns a string where the index in the string is hte kmer number
 280                 //and the character at that index can be converted to be the number of times that kmer was seen
 281                 string queryKmerString = kmer.getKmerString(seq->getUnaligned());
 282
 283                 vector<int> queryKmers;
 284                 for (int i = 0; i < queryKmerString.length()-1; i++) {  // the -1 is to ignore any kmer with an N in it
 285                         if (queryKmerString[i] != '!') { //this kmer is in the query
 286                                 queryKmers.push_back(i);
 287                         }
 288                 }
 289
 290                 //if user wants to test reverse compliment and its reversed use that instead
 291                 if (flip) {
 292                         if (isReversed(queryKmers)) {
 293                                 flipped = true;
 294                                 seq->reverseComplement();
 295                                 queryKmerString = kmer.getKmerString(seq->getUnaligned());
 296                                 queryKmers.clear();
 297                                 for (int i = 0; i < queryKmerString.length()-1; i++) {  // the -1 is to ignore any kmer with an N in it
 298                                         if (queryKmerString[i] != '!') { //this kmer is in the query
 299                                                 queryKmers.push_back(i);
 300                                         }
 301                                 }
 302                         }
 303                 }
 304
 305                 if (queryKmers.size() == 0) {  m->mothurOut(seq->getName() + "is bad."); m->mothurOutEndLine(); simpleTax = "unknown;";  return "unknown;"; }
 306
 307
 308                 int index = getMostProbableTaxonomy(queryKmers);
 309
 310                 if (m->control_pressed) { return tax; }
 311
 312                 //bootstrap - to set confidenceScore
 313                 int numToSelect = queryKmers.size() / 8;
 314
 315                 tax = bootstrapResults(queryKmers, index, numToSelect);
 316
 317                 return tax;
 318         }
 319         catch(exception& e) {
 320                 m->errorOut(e, "Bayesian", "getTaxonomy");
 321                 exit(1);
 322         }
 323 }
 324 /**************************************************************************************************/
 325 string Bayesian::bootstrapResults(vector<int> kmers, int tax, int numToSelect) {
 326         try {
 327
 328                 map<int, int> confidenceScores;
 329
 330                 //initialize confidences to 0
 331                 int seqIndex = tax;
 332                 TaxNode seq = phyloTree->get(tax);
 333                 confidenceScores[tax] = 0;
 334
 335                 while (seq.level != 0) { //while you are not at the root
 336                         seqIndex = seq.parent;
 337                         confidenceScores[seqIndex] = 0;
 338                         seq = phyloTree->get(seq.parent);
 339                 }
 340
 341                 map<int, int>::iterator itBoot;
 342                 map<int, int>::iterator itBoot2;
 343                 map<int, int>::iterator itConvert;
 344
 345                 for (int i = 0; i < iters; i++) {
 346                         if (m->control_pressed) { return "control"; }
 347
 348                         vector<int> temp;
 349                         for (int j = 0; j < numToSelect; j++) {
 350                                 int index = int(rand() % kmers.size());
 351
 352                                 //add word to temp
 353                                 temp.push_back(kmers[index]);
 354                         }
 355
 356                         //get taxonomy
 357                         int newTax = getMostProbableTaxonomy(temp);
 358                         //int newTax = 1;
 359                         TaxNode taxonomyTemp = phyloTree->get(newTax);
 360
 361                         //add to confidence results
 362                         while (taxonomyTemp.level != 0) { //while you are not at the root
 363                                 itBoot2 = confidenceScores.find(newTax); //is this a classification we already have a count on
 364
 365                                 if (itBoot2 != confidenceScores.end()) { //this is a classification we need a confidence for
 366                                         (itBoot2->second)++;
 367                                 }
 368
 369                                 newTax = taxonomyTemp.parent;
 370                                 taxonomyTemp = phyloTree->get(newTax);
 371                         }
 372
 373                 }
 374
 375                 string confidenceTax = "";
 376                 simpleTax = "";
 377
 378                 int seqTaxIndex = tax;
 379                 TaxNode seqTax = phyloTree->get(tax);
 380
 381                 while (seqTax.level != 0) { //while you are not at the root
 382
 383                                 itBoot2 = confidenceScores.find(seqTaxIndex); //is this a classification we already have a count on
 384
 385                                 int confidence = 0;
 386                                 if (itBoot2 != confidenceScores.end()) { //already in confidence scores
 387                                         confidence = itBoot2->second;
 388                                 }
 389
 390                                 if (((confidence/(float)iters) * 100) >= confidenceThreshold) {
 391                                         confidenceTax = seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");" + confidenceTax;
 392                                         simpleTax = seqTax.name + ";" + simpleTax;
 393                                 }
 394
 395                                 seqTaxIndex = seqTax.parent;
 396                                 seqTax = phyloTree->get(seqTax.parent);
 397                 }
 398
 399                 if (confidenceTax == "") { confidenceTax = "unknown;"; simpleTax = "unknown;";  }
 400
 401                 return confidenceTax;
 402
 403         }
 404         catch(exception& e) {
 405                 m->errorOut(e, "Bayesian", "bootstrapResults");
 406                 exit(1);
 407         }
 408 }
 409 /**************************************************************************************************/
 410 int Bayesian::getMostProbableTaxonomy(vector<int> queryKmer) {
 411         try {
 412                 int indexofGenus = 0;
 413
 414                 double maxProbability = -1000000.0;
 415                 //find taxonomy with highest probability that this sequence is from it
 416
 417
 418 //              cout << genusNodes.size() << endl;
 419
 420
 421                 for (int k = 0; k < genusNodes.size(); k++) {
 422                         //for each taxonomy calc its probability
 423
 424                         double prob = 0.0000;
 425                         for (int i = 0; i < queryKmer.size(); i++) {
 426                                 prob += wordGenusProb[queryKmer[i]][k];
 427                         }
 428
 429 //                      cout << phyloTree->get(genusNodes[k]).name << '\t' << prob << endl;
 430
 431                         //is this the taxonomy with the greatest probability?
 432                         if (prob > maxProbability) {
 433                                 indexofGenus = genusNodes[k];
 434                                 maxProbability = prob;
 435                         }
 436                 }
 437
 438
 439                 return indexofGenus;
 440         }
 441         catch(exception& e) {
 442                 m->errorOut(e, "Bayesian", "getMostProbableTaxonomy");
 443                 exit(1);
 444         }
 445 }
 446 //********************************************************************************************************************
 447 //if it is more probable that the reverse compliment kmers are in the template, then we assume the sequence is reversed.
 448 bool Bayesian::isReversed(vector<int>& queryKmers){
 449         try{
 450                 bool reversed = false;
 451                 float prob = 0;
 452                 float reverseProb = 0;
 453
 454         for (int i = 0; i < queryKmers.size(); i++){
 455             int kmer = queryKmers[i];
 456             if (kmer >= 0){
 457                 prob += WordPairDiffArr[kmer].prob;
 458                                 reverseProb += WordPairDiffArr[kmer].reverseProb;
 459             }
 460         }
 461
 462         if (reverseProb > prob){ reversed = true; }
 463
 464                 return reversed;
 465         }
 466         catch(exception& e) {
 467                 m->errorOut(e, "Bayesian", "isReversed");
 468                 exit(1);
 469         }
 470 }
 471 //********************************************************************************************************************
 472 int Bayesian::generateWordPairDiffArr(){
 473         try{
 474                 Kmer kmer(kmerSize);
 475                 for (int i = 0; i < WordPairDiffArr.size(); i++) {
 476                         int reversedWord = kmer.getReverseKmerNumber(i);
 477                         WordPairDiffArr[i].reverseProb = WordPairDiffArr[reversedWord].prob;
 478                 }
 479
 480                 return 0;
 481         }catch(exception& e) {
 482                 m->errorOut(e, "Bayesian", "generateWordPairDiffArr");
 483                 exit(1);
 484         }
 485 }
 486 /*************************************************************************************************
 487 map<string, int> Bayesian::parseTaxMap(string newTax) {
 488         try{
 489
 490                 map<string, int> parsed;
 491
 492                 newTax = newTax.substr(0, newTax.length()-1);  //get rid of last ';'
 493
 494                 //parse taxonomy
 495                 string individual;
 496                 while (newTax.find_first_of(';') != -1) {
 497                         individual = newTax.substr(0,newTax.find_first_of(';'));
 498                         newTax = newTax.substr(newTax.find_first_of(';')+1, newTax.length());
 499                         parsed[individual] = 1;
 500                 }
 501
 502                 //get last one
 503                 parsed[newTax] = 1;
 504
 505                 return parsed;
 506
 507         }
 508         catch(exception& e) {
 509                 m->errorOut(e, "Bayesian", "parseTax");
 510                 exit(1);
 511         }
 512 }
 513 **************************************************************************************************/
 514 void Bayesian::readProbFile(ifstream& in, ifstream& inNum, string inName, string inNumName) {
 515         try{
 516
 517                 #ifdef USE_MPI
 518
 519                         int pid, num, num2, processors;
 520                         vector<unsigned long long> positions;
 521                         vector<unsigned long long> positions2;
 522
 523                         MPI_Status status;
 524                         MPI_File inMPI;
 525                         MPI_File inMPI2;
 526                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 527                         MPI_Comm_size(MPI_COMM_WORLD, &processors);
 528                         int tag = 2001;
 529
 530                         char inFileName[1024];
 531                         strcpy(inFileName, inNumName.c_str());
 532
 533                         char inFileName2[1024];
 534                         strcpy(inFileName2, inName.c_str());
 535
 536                         MPI_File_open(MPI_COMM_WORLD, inFileName, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI);  //comm, filename, mode, info, filepointer
 537                         MPI_File_open(MPI_COMM_WORLD, inFileName2, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI2);  //comm, filename, mode, info, filepointer
 538
 539                         if (pid == 0) {
 540                                 positions = m->setFilePosEachLine(inNumName, num);
 541                                 positions2 = m->setFilePosEachLine(inName, num2);
 542
 543                                 for(int i = 1; i < processors; i++) {
 544                                         MPI_Send(&num, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
 545                                         MPI_Send(&positions[0], (num+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
 546
 547                                         MPI_Send(&num2, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
 548                                         MPI_Send(&positions2[0], (num2+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
 549                                 }
 550
 551                         }else{
 552                                 MPI_Recv(&num, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
 553                                 positions.resize(num+1);
 554                                 MPI_Recv(&positions[0], (num+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
 555
 556                                 MPI_Recv(&num2, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
 557                                 positions2.resize(num2+1);
 558                                 MPI_Recv(&positions2[0], (num2+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
 559                         }
 560
 561                         //read version
 562                         int length = positions2[1] - positions2[0];
 563                         char* buf5 = new char[length];
 564
 565                         MPI_File_read_at(inMPI2, positions2[0], buf5, length, MPI_CHAR, &status);
 566                         delete buf5;
 567
 568                         //read numKmers
 569                         length = positions2[2] - positions2[1];
 570                         char* buf = new char[length];
 571
 572                         MPI_File_read_at(inMPI2, positions2[1], buf, length, MPI_CHAR, &status);
 573
 574                         string tempBuf = buf;
 575                         if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 576                         delete buf;
 577
 578                         istringstream iss (tempBuf,istringstream::in);
 579                         iss >> numKmers;
 580
 581                         //initialze probabilities
 582                         wordGenusProb.resize(numKmers);
 583
 584                         for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 585
 586                         int kmer, name;
 587                         vector<int> numbers; numbers.resize(numKmers);
 588                         float prob;
 589                         vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
 590                         WordPairDiffArr.resize(numKmers);
 591
 592                         //read version
 593                         length = positions[1] - positions[0];
 594                         char* buf6 = new char[length];
 595
 596                         MPI_File_read_at(inMPI2, positions[0], buf6, length, MPI_CHAR, &status);
 597                         delete buf6;
 598
 599                         //read file
 600                         for(int i=1;i<num;i++){
 601                                 //read next sequence
 602                                 length = positions[i+1] - positions[i];
 603                                 char* buf4 = new char[length];
 604
 605                                 MPI_File_read_at(inMPI, positions[i], buf4, length, MPI_CHAR, &status);
 606
 607                                 tempBuf = buf4;
 608                                 if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 609                                 delete buf4;
 610
 611                                 istringstream iss (tempBuf,istringstream::in);
 612                                 float probTemp;
 613                                 iss >> zeroCountProb[i] >> numbers[i] >> probTemp;
 614                                 WordPairDiffArr[i].prob = probTemp;
 615
 616                         }
 617
 618                         MPI_File_close(&inMPI);
 619
 620                         for(int i=2;i<num2;i++){
 621                                 //read next sequence
 622                                 length = positions2[i+1] - positions2[i];
 623                                 char* buf4 = new char[length];
 624
 625                                 MPI_File_read_at(inMPI2, positions2[i], buf4, length, MPI_CHAR, &status);
 626
 627                                 tempBuf = buf4;
 628                                 if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 629                                 delete buf4;
 630
 631                                 istringstream iss (tempBuf,istringstream::in);
 632
 633                                 iss >> kmer;
 634
 635                                 //set them all to zero value
 636                                 for (int i = 0; i < genusNodes.size(); i++) {
 637                                         wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
 638                                 }
 639
 640                                 //get probs for nonzero values
 641                                 for (int i = 0; i < numbers[kmer]; i++) {
 642                                         iss >> name >> prob;
 643                                         wordGenusProb[kmer][name] = prob;
 644                                 }
 645
 646                         }
 647                         MPI_File_close(&inMPI2);
 648                         MPI_Barrier(MPI_COMM_WORLD); //make everyone wait - just in case
 649                 #else
 650                         //read version
 651                         string line = m->getline(in); m->gobble(in);
 652
 653                         in >> numKmers; m->gobble(in);
 654                         //cout << threadID << '\t' << line << '\t' << numKmers << &in << '\t' << &inNum << '\t' << genusNodes.size() << endl;
 655                         //initialze probabilities
 656                         wordGenusProb.resize(numKmers);
 657
 658                         for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 659
 660                         int kmer, name, count;  count = 0;
 661                         vector<int> num; num.resize(numKmers);
 662                         float prob;
 663                         vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
 664                         WordPairDiffArr.resize(numKmers);
 665
 666                         //read version
 667                         string line2 = m->getline(inNum); m->gobble(inNum);
 668                         float probTemp;
 669                 //cout << threadID << '\t' << line2 << '\t' << this << endl;
 670                         while (inNum) {
 671                                 inNum >> zeroCountProb[count] >> num[count] >> probTemp;
 672                                 WordPairDiffArr[count].prob = probTemp;
 673                                 count++;
 674                                 m->gobble(inNum);
 675                                 //cout << threadID << '\t' << count << endl;
 676                         }
 677                         inNum.close();
 678                 //cout << threadID << '\t' << "here1 " << &wordGenusProb << '\t' << &num << endl; //
 679                 //cout << threadID << '\t' << &genusTotals << '\t' << endl;
 680                 //cout << threadID << '\t' << genusNodes.size() << endl;
 681                         while(in) {
 682                                 in >> kmer;
 683                         //cout << threadID << '\t' << kmer << endl;
 684                                 //set them all to zero value
 685                                 for (int i = 0; i < genusNodes.size(); i++) {
 686                                         wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
 687                                 }
 688                         //cout << threadID << '\t' << num[kmer] << "here" << endl;
 689                                 //get probs for nonzero values
 690                                 for (int i = 0; i < num[kmer]; i++) {
 691                                         in >> name >> prob;
 692                                         wordGenusProb[kmer][name] = prob;
 693                                 }
 694
 695                                 m->gobble(in);
 696                         }
 697                         in.close();
 698                 //cout << threadID << '\t' << "here" << endl;
 699                 #endif
 700         }
 701         catch(exception& e) {
 702                 m->errorOut(e, "Bayesian", "readProbFile");
 703                 exit(1);
 704         }
 705 }
 706 /**************************************************************************************************/
 707 bool Bayesian::checkReleaseDate(ifstream& file1, ifstream& file2, ifstream& file3, ifstream& file4) {
 708         try {
 709
 710                 bool good = true;
 711
 712                 vector<string> lines;
 713                 lines.push_back(m->getline(file1));
 714                 lines.push_back(m->getline(file2));
 715                 lines.push_back(m->getline(file3));
 716                 lines.push_back(m->getline(file4));
 717
 718                 //before we added this check
 719                 if ((lines[0][0] != '#') || (lines[1][0] != '#') || (lines[2][0] != '#') || (lines[3][0] != '#')) {  good = false;  }
 720                 else {
 721                         //rip off #
 722                         for (int i = 0; i < lines.size(); i++) { lines[i] = lines[i].substr(1);  }
 723
 724                         //get mothurs current version
 725                         string version = m->getVersion();
 726
 727                         vector<string> versionVector;
 728                         m->splitAtChar(version, versionVector, '.');
 729
 730                         //check each files version
 731                         for (int i = 0; i < lines.size(); i++) {
 732                                 vector<string> linesVector;
 733                                 m->splitAtChar(lines[i], linesVector, '.');
 734
 735                                 if (versionVector.size() != linesVector.size()) { good = false; break; }
 736                                 else {
 737                                         for (int j = 0; j < versionVector.size(); j++) {
 738                                                 int num1, num2;
 739                                                 convert(versionVector[j], num1);
 740                                                 convert(linesVector[j], num2);
 741
 742                                                 //if mothurs version is newer than this files version, then we want to remake it
 743                                                 if (num1 > num2) {  good = false; break;  }
 744                                         }
 745                                 }
 746
 747                                 if (!good) { break; }
 748                         }
 749                 }
 750
 751                 if (!good) {  file1.close(); file2.close(); file3.close(); file4.close();  }
 752                 else { file1.seekg(0);  file2.seekg(0);  file3.seekg(0);  file4.seekg(0);  }
 753
 754                 return good;
 755         }
 756         catch(exception& e) {
 757                 m->errorOut(e, "Bayesian", "checkReleaseDate");
 758                 exit(1);
 759         }
 760 }
 761 /**************************************************************************************************/
 762
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