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