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
  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                                 //for each word
 147                                 for (int i = 0; i < numKmers; i++) {
 148                                         if (m->control_pressed) {  break; }
 149
 150                                         #ifdef USE_MPI
 151                                                 MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 152
 153                                                 if (pid == 0) {
 154                                         #endif
 155
 156                     if (shortcuts) {  out << i << '\t'; }
 157
 158                                         #ifdef USE_MPI
 159                                                 }
 160                                         #endif
 161
 162                                         vector<int> seqsWithWordi = database->getSequencesWithKmer(i);
 163
 164                                         //for each sequence with that word
 165                     vector<int> count; count.resize(genusNodes.size(), 0);
 166                                         for (int j = 0; j < seqsWithWordi.size(); j++) {
 167                                                 int temp = phyloTree->getGenusIndex(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[k] + probabilityInTemplate) / (float) (genusTotals[k] + 1));
 182
 183                                                 if (count[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                             if (shortcuts) { 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                             if (shortcuts) {
 208                                 out << endl;
 209                                 out2 << probabilityInTemplate << '\t' << numNotZero << '\t' << log(probabilityInTemplate) << endl;
 210                             }
 211
 212                                         #ifdef USE_MPI
 213                                                 }
 214                                         #endif
 215                                 }
 216
 217                                 #ifdef USE_MPI
 218                                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 219
 220                                         if (pid == 0) {
 221                                 #endif
 222
 223                         if (shortcuts) {
 224                             out.close();
 225                             out2.close();
 226                         }
 227                                 #ifdef USE_MPI
 228                                         }
 229                                 #endif
 230
 231                                 //read in new phylotree with less info. - its faster
 232                                 ifstream phyloTreeTest(phyloTreeName.c_str());
 233                                 delete phyloTree;
 234
 235                                 phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
 236
 237                                 //save probabilities
 238                                 if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
 239                         }
 240                 }
 241
 242                 generateWordPairDiffArr();
 243
 244                 //save probabilities
 245                 if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
 246
 247                 m->mothurOut("DONE."); m->mothurOutEndLine();
 248                 m->mothurOut("It took " + toString(time(NULL) - start) + " seconds get probabilities. "); m->mothurOutEndLine();
 249         }
 250         catch(exception& e) {
 251                 m->errorOut(e, "Bayesian", "Bayesian");
 252                 exit(1);
 253         }
 254 }
 255 /**************************************************************************************************/
 256 Bayesian::~Bayesian() {
 257         try {
 258         if (phyloTree != NULL) { delete phyloTree; }
 259         if (database != NULL) {  delete database; }
 260         }
 261         catch(exception& e) {
 262                 m->errorOut(e, "Bayesian", "~Bayesian");
 263                 exit(1);
 264         }
 265 }
 266
 267 /**************************************************************************************************/
 268 string Bayesian::getTaxonomy(Sequence* seq) {
 269         try {
 270                 string tax = "";
 271                 Kmer kmer(kmerSize);
 272                 flipped = false;
 273
 274                 //get words contained in query
 275                 //getKmerString returns a string where the index in the string is hte kmer number
 276                 //and the character at that index can be converted to be the number of times that kmer was seen
 277                 string queryKmerString = kmer.getKmerString(seq->getUnaligned());
 278
 279                 vector<int> queryKmers;
 280                 for (int i = 0; i < queryKmerString.length()-1; i++) {  // the -1 is to ignore any kmer with an N in it
 281                         if (queryKmerString[i] != '!') { //this kmer is in the query
 282                                 queryKmers.push_back(i);
 283                         }
 284                 }
 285
 286                 //if user wants to test reverse compliment and its reversed use that instead
 287                 if (flip) {
 288                         if (isReversed(queryKmers)) {
 289                                 flipped = true;
 290                                 seq->reverseComplement();
 291                                 queryKmerString = kmer.getKmerString(seq->getUnaligned());
 292                                 queryKmers.clear();
 293                                 for (int i = 0; i < queryKmerString.length()-1; i++) {  // the -1 is to ignore any kmer with an N in it
 294                                         if (queryKmerString[i] != '!') { //this kmer is in the query
 295                                                 queryKmers.push_back(i);
 296                                         }
 297                                 }
 298                         }
 299                 }
 300
 301                 if (queryKmers.size() == 0) {  m->mothurOut(seq->getName() + " is bad. It has no kmers of length " + toString(kmerSize) + "."); m->mothurOutEndLine(); simpleTax = "unknown;";  return "unknown;"; }
 302
 303
 304                 int index = getMostProbableTaxonomy(queryKmers);
 305
 306                 if (m->control_pressed) { return tax; }
 307
 308                 //bootstrap - to set confidenceScore
 309                 int numToSelect = queryKmers.size() / 8;
 310
 311         if (m->debug) {  m->mothurOut(seq->getName() + "\t"); }
 312
 313                 tax = bootstrapResults(queryKmers, index, numToSelect);
 314
 315         if (m->debug) {  m->mothurOut("\n"); }
 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
 382                 while (seqTax.level != 0) { //while you are not at the root
 383
 384                                 itBoot2 = confidenceScores.find(seqTaxIndex); //is this a classification we already have a count on
 385
 386                                 int confidence = 0;
 387                                 if (itBoot2 != confidenceScores.end()) { //already in confidence scores
 388                                         confidence = itBoot2->second;
 389                                 }
 390
 391                 if (m->debug) { m->mothurOut(seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");"); }
 392
 393                                 if (((confidence/(float)iters) * 100) >= confidenceThreshold) {
 394                                         confidenceTax = seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");" + confidenceTax;
 395                                         simpleTax = seqTax.name + ";" + simpleTax;
 396                                 }
 397
 398                                 seqTaxIndex = seqTax.parent;
 399                                 seqTax = phyloTree->get(seqTax.parent);
 400                 }
 401
 402                 if (confidenceTax == "") { confidenceTax = "unknown;"; simpleTax = "unknown;";  }
 403
 404                 return confidenceTax;
 405
 406         }
 407         catch(exception& e) {
 408                 m->errorOut(e, "Bayesian", "bootstrapResults");
 409                 exit(1);
 410         }
 411 }
 412 /**************************************************************************************************/
 413 int Bayesian::getMostProbableTaxonomy(vector<int> queryKmer) {
 414         try {
 415                 int indexofGenus = 0;
 416
 417                 double maxProbability = -1000000.0;
 418                 //find taxonomy with highest probability that this sequence is from it
 419
 420
 421 //              cout << genusNodes.size() << endl;
 422
 423
 424                 for (int k = 0; k < genusNodes.size(); k++) {
 425                         //for each taxonomy calc its probability
 426
 427                         double prob = 0.0000;
 428                         for (int i = 0; i < queryKmer.size(); i++) {
 429                                 prob += wordGenusProb[queryKmer[i]][k];
 430                         }
 431
 432 //                      cout << phyloTree->get(genusNodes[k]).name << '\t' << prob << endl;
 433
 434                         //is this the taxonomy with the greatest probability?
 435                         if (prob > maxProbability) {
 436                                 indexofGenus = genusNodes[k];
 437                                 maxProbability = prob;
 438                         }
 439                 }
 440
 441
 442                 return indexofGenus;
 443         }
 444         catch(exception& e) {
 445                 m->errorOut(e, "Bayesian", "getMostProbableTaxonomy");
 446                 exit(1);
 447         }
 448 }
 449 //********************************************************************************************************************
 450 //if it is more probable that the reverse compliment kmers are in the template, then we assume the sequence is reversed.
 451 bool Bayesian::isReversed(vector<int>& queryKmers){
 452         try{
 453                 bool reversed = false;
 454                 float prob = 0;
 455                 float reverseProb = 0;
 456
 457         for (int i = 0; i < queryKmers.size(); i++){
 458             int kmer = queryKmers[i];
 459             if (kmer >= 0){
 460                 prob += WordPairDiffArr[kmer].prob;
 461                                 reverseProb += WordPairDiffArr[kmer].reverseProb;
 462             }
 463         }
 464
 465         if (reverseProb > prob){ reversed = true; }
 466
 467                 return reversed;
 468         }
 469         catch(exception& e) {
 470                 m->errorOut(e, "Bayesian", "isReversed");
 471                 exit(1);
 472         }
 473 }
 474 //********************************************************************************************************************
 475 int Bayesian::generateWordPairDiffArr(){
 476         try{
 477                 Kmer kmer(kmerSize);
 478                 for (int i = 0; i < WordPairDiffArr.size(); i++) {
 479                         int reversedWord = kmer.getReverseKmerNumber(i);
 480                         WordPairDiffArr[i].reverseProb = WordPairDiffArr[reversedWord].prob;
 481                 }
 482
 483                 return 0;
 484         }catch(exception& e) {
 485                 m->errorOut(e, "Bayesian", "generateWordPairDiffArr");
 486                 exit(1);
 487         }
 488 }
 489 /*************************************************************************************************
 490 map<string, int> Bayesian::parseTaxMap(string newTax) {
 491         try{
 492
 493                 map<string, int> parsed;
 494
 495                 newTax = newTax.substr(0, newTax.length()-1);  //get rid of last ';'
 496
 497                 //parse taxonomy
 498                 string individual;
 499                 while (newTax.find_first_of(';') != -1) {
 500                         individual = newTax.substr(0,newTax.find_first_of(';'));
 501                         newTax = newTax.substr(newTax.find_first_of(';')+1, newTax.length());
 502                         parsed[individual] = 1;
 503                 }
 504
 505                 //get last one
 506                 parsed[newTax] = 1;
 507
 508                 return parsed;
 509
 510         }
 511         catch(exception& e) {
 512                 m->errorOut(e, "Bayesian", "parseTax");
 513                 exit(1);
 514         }
 515 }
 516 **************************************************************************************************/
 517 void Bayesian::readProbFile(ifstream& in, ifstream& inNum, string inName, string inNumName) {
 518         try{
 519
 520                 #ifdef USE_MPI
 521
 522                         int pid, num, num2, processors;
 523                         vector<unsigned long long> positions;
 524                         vector<unsigned long long> positions2;
 525
 526                         MPI_Status status;
 527                         MPI_File inMPI;
 528                         MPI_File inMPI2;
 529                         MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
 530                         MPI_Comm_size(MPI_COMM_WORLD, &processors);
 531                         int tag = 2001;
 532
 533                         char inFileName[1024];
 534                         strcpy(inFileName, inNumName.c_str());
 535
 536                         char inFileName2[1024];
 537                         strcpy(inFileName2, inName.c_str());
 538
 539                         MPI_File_open(MPI_COMM_WORLD, inFileName, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI);  //comm, filename, mode, info, filepointer
 540                         MPI_File_open(MPI_COMM_WORLD, inFileName2, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI2);  //comm, filename, mode, info, filepointer
 541
 542                         if (pid == 0) {
 543                                 positions = m->setFilePosEachLine(inNumName, num);
 544                                 positions2 = m->setFilePosEachLine(inName, num2);
 545
 546                                 for(int i = 1; i < processors; i++) {
 547                                         MPI_Send(&num, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
 548                                         MPI_Send(&positions[0], (num+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
 549
 550                                         MPI_Send(&num2, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
 551                                         MPI_Send(&positions2[0], (num2+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
 552                                 }
 553
 554                         }else{
 555                                 MPI_Recv(&num, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
 556                                 positions.resize(num+1);
 557                                 MPI_Recv(&positions[0], (num+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
 558
 559                                 MPI_Recv(&num2, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
 560                                 positions2.resize(num2+1);
 561                                 MPI_Recv(&positions2[0], (num2+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
 562                         }
 563
 564                         //read version
 565                         int length = positions2[1] - positions2[0];
 566                         char* buf5 = new char[length];
 567
 568                         MPI_File_read_at(inMPI2, positions2[0], buf5, length, MPI_CHAR, &status);
 569                         delete buf5;
 570
 571                         //read numKmers
 572                         length = positions2[2] - positions2[1];
 573                         char* buf = new char[length];
 574
 575                         MPI_File_read_at(inMPI2, positions2[1], buf, length, MPI_CHAR, &status);
 576
 577                         string tempBuf = buf;
 578                         if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 579                         delete buf;
 580
 581                         istringstream iss (tempBuf,istringstream::in);
 582                         iss >> numKmers;
 583
 584                         //initialze probabilities
 585                         wordGenusProb.resize(numKmers);
 586
 587                         for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 588
 589                         int kmer, name;
 590                         vector<int> numbers; numbers.resize(numKmers);
 591                         float prob;
 592                         vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
 593                         WordPairDiffArr.resize(numKmers);
 594
 595                         //read version
 596                         length = positions[1] - positions[0];
 597                         char* buf6 = new char[length];
 598
 599                         MPI_File_read_at(inMPI2, positions[0], buf6, length, MPI_CHAR, &status);
 600                         delete buf6;
 601
 602                         //read file
 603                         for(int i=1;i<num;i++){
 604                                 //read next sequence
 605                                 length = positions[i+1] - positions[i];
 606                                 char* buf4 = new char[length];
 607
 608                                 MPI_File_read_at(inMPI, positions[i], buf4, length, MPI_CHAR, &status);
 609
 610                                 tempBuf = buf4;
 611                                 if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 612                                 delete buf4;
 613
 614                                 istringstream iss (tempBuf,istringstream::in);
 615                                 float probTemp;
 616                                 iss >> zeroCountProb[i] >> numbers[i] >> probTemp;
 617                                 WordPairDiffArr[i].prob = probTemp;
 618
 619                         }
 620
 621                         MPI_File_close(&inMPI);
 622
 623                         for(int i=2;i<num2;i++){
 624                                 //read next sequence
 625                                 length = positions2[i+1] - positions2[i];
 626                                 char* buf4 = new char[length];
 627
 628                                 MPI_File_read_at(inMPI2, positions2[i], buf4, length, MPI_CHAR, &status);
 629
 630                                 tempBuf = buf4;
 631                                 if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
 632                                 delete buf4;
 633
 634                                 istringstream iss (tempBuf,istringstream::in);
 635
 636                                 iss >> kmer;
 637
 638                                 //set them all to zero value
 639                                 for (int i = 0; i < genusNodes.size(); i++) {
 640                                         wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
 641                                 }
 642
 643                                 //get probs for nonzero values
 644                                 for (int i = 0; i < numbers[kmer]; i++) {
 645                                         iss >> name >> prob;
 646                                         wordGenusProb[kmer][name] = prob;
 647                                 }
 648
 649                         }
 650                         MPI_File_close(&inMPI2);
 651                         MPI_Barrier(MPI_COMM_WORLD); //make everyone wait - just in case
 652                 #else
 653                         //read version
 654                         string line = m->getline(in); m->gobble(in);
 655
 656                         in >> numKmers; m->gobble(in);
 657                         //cout << threadID << '\t' << line << '\t' << numKmers << &in << '\t' << &inNum << '\t' << genusNodes.size() << endl;
 658                         //initialze probabilities
 659                         wordGenusProb.resize(numKmers);
 660
 661                         for (int j = 0; j < wordGenusProb.size(); j++) {        wordGenusProb[j].resize(genusNodes.size());             }
 662
 663                         int kmer, name, count;  count = 0;
 664                         vector<int> num; num.resize(numKmers);
 665                         float prob;
 666                         vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
 667                         WordPairDiffArr.resize(numKmers);
 668
 669                         //read version
 670                         string line2 = m->getline(inNum); m->gobble(inNum);
 671                         float probTemp;
 672                 //cout << threadID << '\t' << line2 << '\t' << this << endl;
 673                         while (inNum) {
 674                                 inNum >> zeroCountProb[count] >> num[count] >> probTemp;
 675                                 WordPairDiffArr[count].prob = probTemp;
 676                                 count++;
 677                                 m->gobble(inNum);
 678                                 //cout << threadID << '\t' << count << endl;
 679                         }
 680                         inNum.close();
 681                 //cout << threadID << '\t' << "here1 " << &wordGenusProb << '\t' << &num << endl; //
 682                 //cout << threadID << '\t' << &genusTotals << '\t' << endl;
 683                 //cout << threadID << '\t' << genusNodes.size() << endl;
 684                         while(in) {
 685                                 in >> kmer;
 686                         //cout << threadID << '\t' << kmer << endl;
 687                                 //set them all to zero value
 688                                 for (int i = 0; i < genusNodes.size(); i++) {
 689                                         wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
 690                                 }
 691                         //cout << threadID << '\t' << num[kmer] << "here" << endl;
 692                                 //get probs for nonzero values
 693                                 for (int i = 0; i < num[kmer]; i++) {
 694                                         in >> name >> prob;
 695                                         wordGenusProb[kmer][name] = prob;
 696                                 }
 697
 698                                 m->gobble(in);
 699                         }
 700                         in.close();
 701                 //cout << threadID << '\t' << "here" << endl;
 702                 #endif
 703         }
 704         catch(exception& e) {
 705                 m->errorOut(e, "Bayesian", "readProbFile");
 706                 exit(1);
 707         }
 708 }
 709 /**************************************************************************************************/
 710 bool Bayesian::checkReleaseDate(ifstream& file1, ifstream& file2, ifstream& file3, ifstream& file4) {
 711         try {
 712
 713                 bool good = true;
 714
 715                 vector<string> lines;
 716                 lines.push_back(m->getline(file1));
 717                 lines.push_back(m->getline(file2));
 718                 lines.push_back(m->getline(file3));
 719                 lines.push_back(m->getline(file4));
 720
 721                 //before we added this check
 722                 if ((lines[0][0] != '#') || (lines[1][0] != '#') || (lines[2][0] != '#') || (lines[3][0] != '#')) {  good = false;  }
 723                 else {
 724                         //rip off #
 725                         for (int i = 0; i < lines.size(); i++) { lines[i] = lines[i].substr(1);  }
 726
 727                         //get mothurs current version
 728                         string version = m->getVersion();
 729
 730                         vector<string> versionVector;
 731                         m->splitAtChar(version, versionVector, '.');
 732
 733                         //check each files version
 734                         for (int i = 0; i < lines.size(); i++) {
 735                                 vector<string> linesVector;
 736                                 m->splitAtChar(lines[i], linesVector, '.');
 737
 738                                 if (versionVector.size() != linesVector.size()) { good = false; break; }
 739                                 else {
 740                                         for (int j = 0; j < versionVector.size(); j++) {
 741                                                 int num1, num2;
 742                                                 convert(versionVector[j], num1);
 743                                                 convert(linesVector[j], num2);
 744
 745                                                 //if mothurs version is newer than this files version, then we want to remake it
 746                                                 if (num1 > num2) {  good = false; break;  }
 747                                         }
 748                                 }
 749
 750                                 if (!good) { break; }
 751                         }
 752                 }
 753
 754                 if (!good) {  file1.close(); file2.close(); file3.close(); file4.close();  }
 755                 else { file1.seekg(0);  file2.seekg(0);  file3.seekg(0);  file4.seekg(0);  }
 756
 757                 return good;
 758         }
 759         catch(exception& e) {
 760                 m->errorOut(e, "Bayesian", "checkReleaseDate");
 761                 exit(1);
 762         }
 763 }
 764 /**************************************************************************************************/
 765
 766
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