#include "bayesian.h"
#include "kmer.hpp"
-
+#include "phylosummary.h"
+#include "referencedb.h"
/**************************************************************************************************/
-Bayesian::Bayesian(string tfile, string tempFile, string method, int ksize, int cutoff, int i) :
-Classify(tfile, tempFile, method, ksize, 0.0, 0.0, 0.0, 0.0), kmerSize(ksize), confidenceThreshold(cutoff), iters(i) {
+Bayesian::Bayesian(string tfile, string tempFile, string method, int ksize, int cutoff, int i, int tid, bool f, bool sh) :
+Classify(), kmerSize(ksize), confidenceThreshold(cutoff), iters(i) {
try {
-
- numKmers = database->getMaxKmer() + 1;
-
- //initialze probabilities
- wordGenusProb.resize(numKmers);
-
- genusNodes = phyloTree->getGenusNodes();
+ ReferenceDB* rdb = ReferenceDB::getInstance();
- for (int j = 0; j < wordGenusProb.size(); j++) { wordGenusProb[j].resize(genusNodes.size()); }
+ threadID = tid;
+ flip = f;
+ shortcuts = sh;
+ string baseName = tempFile;
- //reset counts because we are on a new word
- for (int j = 0; j < genusNodes.size(); j++) {
- TaxNode temp = phyloTree->get(genusNodes[j]);
- genusTotals.push_back(temp.accessions.size());
- }
-
+ if (baseName == "saved") { baseName = rdb->getSavedReference(); }
+
+ string baseTName = tfile;
+ if (baseTName == "saved") { baseTName = rdb->getSavedTaxonomy(); }
/************calculate the probablity that each word will be in a specific taxonomy*************/
- ofstream out;
- string probFileName = tempFile.substr(0,tempFile.find_last_of(".")+1) + char('0'+ kmerSize) + "mer.prob";
- ifstream probFileTest(probFileName.c_str());
+ string tfileroot = m->getFullPathName(baseTName.substr(0,baseTName.find_last_of(".")+1));
+ string tempfileroot = m->getRootName(m->getSimpleName(baseName));
+ string phyloTreeName = tfileroot + "tree.train";
+ string phyloTreeSumName = tfileroot + "tree.sum";
+ string probFileName = tfileroot + tempfileroot + char('0'+ kmerSize) + "mer.prob";
+ string probFileName2 = tfileroot + tempfileroot + char('0'+ kmerSize) + "mer.numNonZero";
+ ofstream out;
ofstream out2;
- string probFileName2 = tempFile.substr(0,tempFile.find_last_of(".")+1) + char('0'+ kmerSize) + "mer.numNonZero";
+
+ ifstream phyloTreeTest(phyloTreeName.c_str());
ifstream probFileTest2(probFileName2.c_str());
+ ifstream probFileTest(probFileName.c_str());
+ ifstream probFileTest3(phyloTreeSumName.c_str());
int start = time(NULL);
- if(probFileTest && probFileTest2){
- m->mothurOut("Reading template probabilities... "); cout.flush();
- readProbFile(probFileTest, probFileTest2);
- }else{
- m->mothurOut("Calculating template probabilities... "); cout.flush();
+ //if they are there make sure they were created after this release date
+ bool FilesGood = false;
+ if(probFileTest && probFileTest2 && phyloTreeTest && probFileTest3){
+ FilesGood = checkReleaseDate(probFileTest, probFileTest2, phyloTreeTest, probFileTest3);
+ }
+
+ //if you want to save, but you dont need to calculate then just read
+ if (rdb->save && probFileTest && probFileTest2 && phyloTreeTest && probFileTest3 && FilesGood && (tempFile != "saved")) {
+ ifstream saveIn;
+ m->openInputFile(tempFile, saveIn);
+
+ while (!saveIn.eof()) {
+ Sequence temp(saveIn);
+ m->gobble(saveIn);
+
+ rdb->referenceSeqs.push_back(temp);
+ }
+ saveIn.close();
+ }
- ofstream out;
- openOutputFile(probFileName, out);
+ if(probFileTest && probFileTest2 && phyloTreeTest && probFileTest3 && FilesGood){
+ if (tempFile == "saved") { m->mothurOutEndLine(); m->mothurOut("Using sequences from " + rdb->getSavedReference() + " that are saved in memory."); m->mothurOutEndLine(); }
- ofstream out2;
- openOutputFile(probFileName2, out2);
+ m->mothurOut("Reading template taxonomy... "); cout.flush();
- //for each word
- for (int i = 0; i < numKmers; i++) {
+ phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
+
+ m->mothurOut("DONE."); m->mothurOutEndLine();
+
+ genusNodes = phyloTree->getGenusNodes();
+ genusTotals = phyloTree->getGenusTotals();
+
+ if (tfile == "saved") {
+ m->mothurOutEndLine(); m->mothurOut("Using probabilties from " + rdb->getSavedTaxonomy() + " that are saved in memory... "); cout.flush();;
+ wordGenusProb = rdb->wordGenusProb;
+ WordPairDiffArr = rdb->WordPairDiffArr;
+ }else {
+ m->mothurOut("Reading template probabilities... "); cout.flush();
+ readProbFile(probFileTest, probFileTest2, probFileName, probFileName2);
+ }
+
+ //save probabilities
+ if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
+ }else{
+
+ //create search database and names vector
+ generateDatabaseAndNames(tfile, tempFile, method, ksize, 0.0, 0.0, 0.0, 0.0);
+
+ //prevents errors caused by creating shortcut files if you had an error in the sanity check.
+ if (m->control_pressed) { m->mothurRemove(phyloTreeName); m->mothurRemove(probFileName); m->mothurRemove(probFileName2); }
+ else{
+ genusNodes = phyloTree->getGenusNodes();
+ genusTotals = phyloTree->getGenusTotals();
+
+ m->mothurOut("Calculating template taxonomy tree... "); cout.flush();
+
+ phyloTree->printTreeNodes(phyloTreeName);
+
+ m->mothurOut("DONE."); m->mothurOutEndLine();
+
+ m->mothurOut("Calculating template probabilities... "); cout.flush();
+
+ numKmers = database->getMaxKmer() + 1;
+
+ //initialze probabilities
+ wordGenusProb.resize(numKmers);
+ WordPairDiffArr.resize(numKmers);
+
+ for (int j = 0; j < wordGenusProb.size(); j++) { wordGenusProb[j].resize(genusNodes.size()); }
+ ofstream out;
+ ofstream out2;
+
+ #ifdef USE_MPI
+ int pid;
+ MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
+
+ if (pid == 0) {
+ #endif
+
+
+ if (shortcuts) {
+ m->openOutputFile(probFileName, out);
+
+ //output mothur version
+ out << "#" << m->getVersion() << endl;
- out << i << '\t';
+ out << numKmers << endl;
- vector<int> seqsWithWordi = database->getSequencesWithKmer(i);
+ m->openOutputFile(probFileName2, out2);
- map<int, int> count;
- for (int k = 0; k < genusNodes.size(); k++) { count[genusNodes[k]] = 0; }
+ //output mothur version
+ out2 << "#" << m->getVersion() << endl;
+ }
+
+ #ifdef USE_MPI
+ }
+ #endif
+
+ //for each word
+ for (int i = 0; i < numKmers; i++) {
+ //m->mothurOut("[DEBUG]: kmer = " + toString(i) + "\n");
+
+ if (m->control_pressed) { break; }
+
+ #ifdef USE_MPI
+ MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
+
+ if (pid == 0) {
+ #endif
+
+ if (shortcuts) { out << i << '\t'; }
+
+ #ifdef USE_MPI
+ }
+ #endif
+
+ vector<int> seqsWithWordi = database->getSequencesWithKmer(i);
+
+ //for each sequence with that word
+ vector<int> count; count.resize(genusNodes.size(), 0);
+ for (int j = 0; j < seqsWithWordi.size(); j++) {
+ int temp = phyloTree->getGenusIndex(names[seqsWithWordi[j]]);
+ count[temp]++; //increment count of seq in this genus who have this word
+ }
+
+ //probabilityInTemplate = (# of seqs with that word in template + 0.50) / (total number of seqs in template + 1);
+ float probabilityInTemplate = (seqsWithWordi.size() + 0.50) / (float) (names.size() + 1);
+ diffPair tempProb(log(probabilityInTemplate), 0.0);
+ WordPairDiffArr[i] = tempProb;
+
+ int numNotZero = 0;
+ for (int k = 0; k < genusNodes.size(); k++) {
+ //probabilityInThisTaxonomy = (# of seqs with that word in this taxonomy + probabilityInTemplate) / (total number of seqs in this taxonomy + 1);
+
+
+ wordGenusProb[i][k] = log((count[k] + probabilityInTemplate) / (float) (genusTotals[k] + 1));
+
+ if (count[k] != 0) {
+ #ifdef USE_MPI
+ int pid;
+ MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
- //for each sequence with that word
- for (int j = 0; j < seqsWithWordi.size(); j++) {
- int temp = phyloTree->getIndex(names[seqsWithWordi[j]]);
- count[temp]++; //increment count of seq in this genus who have this word
+ if (pid == 0) {
+ #endif
+
+ if (shortcuts) { out << k << '\t' << wordGenusProb[i][k] << '\t' ; }
+
+ #ifdef USE_MPI
+ }
+ #endif
+
+ numNotZero++;
+ }
+ }
+
+ #ifdef USE_MPI
+ MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
+
+ if (pid == 0) {
+ #endif
+
+ if (shortcuts) {
+ out << endl;
+ out2 << probabilityInTemplate << '\t' << numNotZero << '\t' << log(probabilityInTemplate) << endl;
+ }
+
+ #ifdef USE_MPI
+ }
+ #endif
}
- //probabilityInTemplate = (# of seqs with that word in template + 0.05) / (total number of seqs in template + 1);
- float probabilityInTemplate = (seqsWithWordi.size() + 0.50) / (float) (names.size() + 1);
+ #ifdef USE_MPI
+ MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
- int numNotZero = 0;
- for (int k = 0; k < genusNodes.size(); k++) {
- //probabilityInThisTaxonomy = (# of seqs with that word in this taxonomy + probabilityInTemplate) / (total number of seqs in this taxonomy + 1);
- wordGenusProb[i][k] = log((count[genusNodes[k]] + probabilityInTemplate) / (float) (genusTotals[k] + 1));
- if (count[genusNodes[k]] != 0) { out << k << '\t' << wordGenusProb[i][k] << '\t'; numNotZero++; }
- }
- out << endl;
- out2 << probabilityInTemplate << '\t' << numNotZero << endl;
+ if (pid == 0) {
+ #endif
+
+ if (shortcuts) {
+ out.close();
+ out2.close();
+ }
+ #ifdef USE_MPI
+ }
+ #endif
+
+ //read in new phylotree with less info. - its faster
+ ifstream phyloTreeTest(phyloTreeName.c_str());
+ delete phyloTree;
+
+ phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
+
+ //save probabilities
+ if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
}
-
- out.close();
- out2.close();
}
+ if (m->debug) { m->mothurOut("[DEBUG]: about to generateWordPairDiffArr\n"); }
+ generateWordPairDiffArr();
+ if (m->debug) { m->mothurOut("[DEBUG]: done generateWordPairDiffArr\n"); }
+
+ //save probabilities
+ if (rdb->save) { rdb->wordGenusProb = wordGenusProb; rdb->WordPairDiffArr = WordPairDiffArr; }
m->mothurOut("DONE."); m->mothurOutEndLine();
m->mothurOut("It took " + toString(time(NULL) - start) + " seconds get probabilities. "); m->mothurOutEndLine();
exit(1);
}
}
+/**************************************************************************************************/
+Bayesian::~Bayesian() {
+ try {
+ if (phyloTree != NULL) { delete phyloTree; }
+ if (database != NULL) { delete database; }
+ }
+ catch(exception& e) {
+ m->errorOut(e, "Bayesian", "~Bayesian");
+ exit(1);
+ }
+}
+
/**************************************************************************************************/
string Bayesian::getTaxonomy(Sequence* seq) {
try {
string tax = "";
Kmer kmer(kmerSize);
+ flipped = false;
//get words contained in query
//getKmerString returns a string where the index in the string is hte kmer number
//and the character at that index can be converted to be the number of times that kmer was seen
string queryKmerString = kmer.getKmerString(seq->getUnaligned());
+
vector<int> queryKmers;
- for (int i = 0; i < queryKmerString.length(); i++) {
+ for (int i = 0; i < queryKmerString.length()-1; i++) { // the -1 is to ignore any kmer with an N in it
if (queryKmerString[i] != '!') { //this kmer is in the query
queryKmers.push_back(i);
}
}
-
+
+ //if user wants to test reverse compliment and its reversed use that instead
+ if (flip) {
+ if (isReversed(queryKmers)) {
+ flipped = true;
+ seq->reverseComplement();
+ queryKmerString = kmer.getKmerString(seq->getUnaligned());
+ queryKmers.clear();
+ for (int i = 0; i < queryKmerString.length()-1; i++) { // the -1 is to ignore any kmer with an N in it
+ if (queryKmerString[i] != '!') { //this kmer is in the query
+ queryKmers.push_back(i);
+ }
+ }
+ }
+ }
+
+ if (queryKmers.size() == 0) { m->mothurOut(seq->getName() + " is bad. It has no kmers of length " + toString(kmerSize) + "."); m->mothurOutEndLine(); simpleTax = "unknown;"; return "unknown;"; }
+
+
int index = getMostProbableTaxonomy(queryKmers);
+
+ if (m->control_pressed) { return tax; }
//bootstrap - to set confidenceScore
int numToSelect = queryKmers.size() / 8;
+
+ if (m->debug) { m->mothurOut(seq->getName() + "\t"); }
+
tax = bootstrapResults(queryKmers, index, numToSelect);
-
+
+ if (m->debug) { m->mothurOut("\n"); }
+
return tax;
}
catch(exception& e) {
/**************************************************************************************************/
string Bayesian::bootstrapResults(vector<int> kmers, int tax, int numToSelect) {
try {
-
- //taxConfidenceScore.clear(); //clear out previous seqs scores
- vector< map<string, int> > confidenceScores; //you need the added vector level of confusion to account for the level that name is seen since they can be the same
- //map of classification to confidence for all areas seen
- //ie. Bacteria;Alphaproteobacteria;Rhizobiales;Azorhizobium_et_rel.;Methylobacterium_et_rel.;Bosea;
- //ie. Bacteria -> 100, Alphaproteobacteria -> 100, Rhizobiales -> 87, Azorhizobium_et_rel. -> 78, Methylobacterium_et_rel. -> 70, Bosea -> 50
- confidenceScores.resize(100); //if you have more than 100 levels of classification...
+ map<int, int> confidenceScores;
- map<string, int>::iterator itBoot;
- map<string, int>::iterator itBoot2;
- map<int, int>::iterator itConvert;
+ //initialize confidences to 0
+ int seqIndex = tax;
+ TaxNode seq = phyloTree->get(tax);
+ confidenceScores[tax] = 0;
+ while (seq.level != 0) { //while you are not at the root
+ seqIndex = seq.parent;
+ confidenceScores[seqIndex] = 0;
+ seq = phyloTree->get(seq.parent);
+ }
+
+ map<int, int>::iterator itBoot;
+ map<int, int>::iterator itBoot2;
+ map<int, int>::iterator itConvert;
+
for (int i = 0; i < iters; i++) {
+ if (m->control_pressed) { return "control"; }
+
vector<int> temp;
-
for (int j = 0; j < numToSelect; j++) {
int index = int(rand() % kmers.size());
//get taxonomy
int newTax = getMostProbableTaxonomy(temp);
- TaxNode taxonomy = phyloTree->get(newTax);
+ //int newTax = 1;
+ TaxNode taxonomyTemp = phyloTree->get(newTax);
//add to confidence results
- while (taxonomy.level != 0) { //while you are not at the root
+ while (taxonomyTemp.level != 0) { //while you are not at the root
+ itBoot2 = confidenceScores.find(newTax); //is this a classification we already have a count on
- itBoot2 = confidenceScores[taxonomy.level].find(taxonomy.name); //is this a classification we already have a count on
-
- if (itBoot2 == confidenceScores[taxonomy.level].end()) { //not already in confidence scores
- confidenceScores[taxonomy.level][taxonomy.name] = 1;
- }else{
- confidenceScores[taxonomy.level][taxonomy.name]++;
+ if (itBoot2 != confidenceScores.end()) { //this is a classification we need a confidence for
+ (itBoot2->second)++;
}
-
- taxonomy = phyloTree->get(taxonomy.parent);
+
+ newTax = taxonomyTemp.parent;
+ taxonomyTemp = phyloTree->get(newTax);
}
+
}
string confidenceTax = "";
simpleTax = "";
+
+ int seqTaxIndex = tax;
TaxNode seqTax = phyloTree->get(tax);
+
while (seqTax.level != 0) { //while you are not at the root
-
- itBoot2 = confidenceScores[seqTax.level].find(seqTax.name); //is this a classification we already have a count on
+
+ itBoot2 = confidenceScores.find(seqTaxIndex); //is this a classification we already have a count on
int confidence = 0;
- if (itBoot2 != confidenceScores[seqTax.level].end()) { //not already in confidence scores
- confidence = confidenceScores[seqTax.level][seqTax.name];
+ if (itBoot2 != confidenceScores.end()) { //already in confidence scores
+ confidence = itBoot2->second;
}
- if (confidence >= confidenceThreshold) {
+ if (m->debug) { m->mothurOut(seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");"); }
+
+ if (((confidence/(float)iters) * 100) >= confidenceThreshold) {
confidenceTax = seqTax.name + "(" + toString(((confidence/(float)iters) * 100)) + ");" + confidenceTax;
simpleTax = seqTax.name + ";" + simpleTax;
}
-
+
+ seqTaxIndex = seqTax.parent;
seqTax = phyloTree->get(seqTax.parent);
}
+ if (confidenceTax == "") { confidenceTax = "unknown;"; simpleTax = "unknown;"; }
+
return confidenceTax;
}
/**************************************************************************************************/
int Bayesian::getMostProbableTaxonomy(vector<int> queryKmer) {
try {
- int indexofGenus;
+ int indexofGenus = 0;
double maxProbability = -1000000.0;
//find taxonomy with highest probability that this sequence is from it
- for (int k = 0; k < genusNodes.size(); k++) {
+
+// cout << genusNodes.size() << endl;
+
+
+ for (int k = 0; k < genusNodes.size(); k++) {
//for each taxonomy calc its probability
- double prob = 1.0;
+
+ double prob = 0.0000;
for (int i = 0; i < queryKmer.size(); i++) {
prob += wordGenusProb[queryKmer[i]][k];
}
-
+
+// cout << phyloTree->get(genusNodes[k]).name << '\t' << prob << endl;
+
//is this the taxonomy with the greatest probability?
if (prob > maxProbability) {
indexofGenus = genusNodes[k];
maxProbability = prob;
}
}
-
+
+
return indexofGenus;
}
catch(exception& e) {
exit(1);
}
}
+//********************************************************************************************************************
+//if it is more probable that the reverse compliment kmers are in the template, then we assume the sequence is reversed.
+bool Bayesian::isReversed(vector<int>& queryKmers){
+ try{
+ bool reversed = false;
+ float prob = 0;
+ float reverseProb = 0;
+
+ for (int i = 0; i < queryKmers.size(); i++){
+ int kmer = queryKmers[i];
+ if (kmer >= 0){
+ prob += WordPairDiffArr[kmer].prob;
+ reverseProb += WordPairDiffArr[kmer].reverseProb;
+ }
+ }
+
+ if (reverseProb > prob){ reversed = true; }
+
+ return reversed;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "Bayesian", "isReversed");
+ exit(1);
+ }
+}
+//********************************************************************************************************************
+int Bayesian::generateWordPairDiffArr(){
+ try{
+ Kmer kmer(kmerSize);
+ for (int i = 0; i < WordPairDiffArr.size(); i++) {
+ int reversedWord = kmer.getReverseKmerNumber(i);
+ WordPairDiffArr[i].reverseProb = WordPairDiffArr[reversedWord].prob;
+ }
+
+ return 0;
+ }catch(exception& e) {
+ m->errorOut(e, "Bayesian", "generateWordPairDiffArr");
+ exit(1);
+ }
+}
/*************************************************************************************************
map<string, int> Bayesian::parseTaxMap(string newTax) {
try{
exit(1);
}
}
-/**************************************************************************************************/
-void Bayesian::readProbFile(ifstream& in, ifstream& inNum) {
+**************************************************************************************************/
+void Bayesian::readProbFile(ifstream& in, ifstream& inNum, string inName, string inNumName) {
try{
- int kmer, name, count; count = 0;
- vector<int> num; num.resize(numKmers);
- float prob;
- vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
-
- while (inNum) {
- inNum >> zeroCountProb[count] >> num[count];
- count++;
- gobble(inNum);
- }
- inNum.close();
-
- while(in) {
- in >> kmer;
+ #ifdef USE_MPI
+
+ int pid, num, num2, processors;
+ vector<unsigned long long> positions;
+ vector<unsigned long long> positions2;
+
+ MPI_Status status;
+ MPI_File inMPI;
+ MPI_File inMPI2;
+ MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
+ MPI_Comm_size(MPI_COMM_WORLD, &processors);
+ int tag = 2001;
+
+ char inFileName[1024];
+ strcpy(inFileName, inNumName.c_str());
+
+ char inFileName2[1024];
+ strcpy(inFileName2, inName.c_str());
+
+ MPI_File_open(MPI_COMM_WORLD, inFileName, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI); //comm, filename, mode, info, filepointer
+ MPI_File_open(MPI_COMM_WORLD, inFileName2, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI2); //comm, filename, mode, info, filepointer
+
+ if (pid == 0) {
+ positions = m->setFilePosEachLine(inNumName, num);
+ positions2 = m->setFilePosEachLine(inName, num2);
+
+ for(int i = 1; i < processors; i++) {
+ MPI_Send(&num, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
+ MPI_Send(&positions[0], (num+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
+
+ MPI_Send(&num2, 1, MPI_INT, i, tag, MPI_COMM_WORLD);
+ MPI_Send(&positions2[0], (num2+1), MPI_LONG, i, tag, MPI_COMM_WORLD);
+ }
+
+ }else{
+ MPI_Recv(&num, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
+ positions.resize(num+1);
+ MPI_Recv(&positions[0], (num+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
+
+ MPI_Recv(&num2, 1, MPI_INT, 0, tag, MPI_COMM_WORLD, &status);
+ positions2.resize(num2+1);
+ MPI_Recv(&positions2[0], (num2+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
+ }
+
+ //read version
+ int length = positions2[1] - positions2[0];
+ char* buf5 = new char[length];
+
+ MPI_File_read_at(inMPI2, positions2[0], buf5, length, MPI_CHAR, &status);
+ delete buf5;
+
+ //read numKmers
+ length = positions2[2] - positions2[1];
+ char* buf = new char[length];
+
+ MPI_File_read_at(inMPI2, positions2[1], buf, length, MPI_CHAR, &status);
+
+ string tempBuf = buf;
+ if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
+ delete buf;
+
+ istringstream iss (tempBuf,istringstream::in);
+ iss >> numKmers;
- //set them all to zero value
- for (int i = 0; i < genusNodes.size(); i++) {
- wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
+ //initialze probabilities
+ wordGenusProb.resize(numKmers);
+
+ for (int j = 0; j < wordGenusProb.size(); j++) { wordGenusProb[j].resize(genusNodes.size()); }
+
+ int kmer, name;
+ vector<int> numbers; numbers.resize(numKmers);
+ float prob;
+ vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
+ WordPairDiffArr.resize(numKmers);
+
+ //read version
+ length = positions[1] - positions[0];
+ char* buf6 = new char[length];
+
+ MPI_File_read_at(inMPI2, positions[0], buf6, length, MPI_CHAR, &status);
+ delete buf6;
+
+ //read file
+ for(int i=1;i<num;i++){
+ //read next sequence
+ length = positions[i+1] - positions[i];
+ char* buf4 = new char[length];
+
+ MPI_File_read_at(inMPI, positions[i], buf4, length, MPI_CHAR, &status);
+
+ tempBuf = buf4;
+ if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
+ delete buf4;
+
+ istringstream iss (tempBuf,istringstream::in);
+ float probTemp;
+ iss >> zeroCountProb[i] >> numbers[i] >> probTemp;
+ WordPairDiffArr[i].prob = probTemp;
+
}
- //get probs for nonzero values
- for (int i = 0; i < num[kmer]; i++) {
- in >> name >> prob;
- wordGenusProb[kmer][name] = prob;
+ MPI_File_close(&inMPI);
+
+ for(int i=2;i<num2;i++){
+ //read next sequence
+ length = positions2[i+1] - positions2[i];
+ char* buf4 = new char[length];
+
+ MPI_File_read_at(inMPI2, positions2[i], buf4, length, MPI_CHAR, &status);
+
+ tempBuf = buf4;
+ if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
+ delete buf4;
+
+ istringstream iss (tempBuf,istringstream::in);
+
+ iss >> kmer;
+
+ //set them all to zero value
+ for (int i = 0; i < genusNodes.size(); i++) {
+ wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
+ }
+
+ //get probs for nonzero values
+ for (int i = 0; i < numbers[kmer]; i++) {
+ iss >> name >> prob;
+ wordGenusProb[kmer][name] = prob;
+ }
+
}
+ MPI_File_close(&inMPI2);
+ MPI_Barrier(MPI_COMM_WORLD); //make everyone wait - just in case
+ #else
+ //read version
+ string line = m->getline(in); m->gobble(in);
- gobble(in);
- }
- in.close();
+ in >> numKmers; m->gobble(in);
+ //cout << threadID << '\t' << line << '\t' << numKmers << &in << '\t' << &inNum << '\t' << genusNodes.size() << endl;
+ //initialze probabilities
+ wordGenusProb.resize(numKmers);
+
+ for (int j = 0; j < wordGenusProb.size(); j++) { wordGenusProb[j].resize(genusNodes.size()); }
+
+ int kmer, name, count; count = 0;
+ vector<int> num; num.resize(numKmers);
+ float prob;
+ vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
+ WordPairDiffArr.resize(numKmers);
+
+ //read version
+ string line2 = m->getline(inNum); m->gobble(inNum);
+ float probTemp;
+ //cout << threadID << '\t' << line2 << '\t' << this << endl;
+ while (inNum) {
+ inNum >> zeroCountProb[count] >> num[count] >> probTemp;
+ WordPairDiffArr[count].prob = probTemp;
+ count++;
+ m->gobble(inNum);
+ //cout << threadID << '\t' << count << endl;
+ }
+ inNum.close();
+ //cout << threadID << '\t' << "here1 " << &wordGenusProb << '\t' << &num << endl; //
+ //cout << threadID << '\t' << &genusTotals << '\t' << endl;
+ //cout << threadID << '\t' << genusNodes.size() << endl;
+ while(in) {
+ in >> kmer;
+ //cout << threadID << '\t' << kmer << endl;
+ //set them all to zero value
+ for (int i = 0; i < genusNodes.size(); i++) {
+ wordGenusProb[kmer][i] = log(zeroCountProb[kmer] / (float) (genusTotals[i]+1));
+ }
+ //cout << threadID << '\t' << num[kmer] << "here" << endl;
+ //get probs for nonzero values
+ for (int i = 0; i < num[kmer]; i++) {
+ in >> name >> prob;
+ wordGenusProb[kmer][name] = prob;
+ }
+
+ m->gobble(in);
+ }
+ in.close();
+ //cout << threadID << '\t' << "here" << endl;
+ #endif
}
catch(exception& e) {
m->errorOut(e, "Bayesian", "readProbFile");
}
}
/**************************************************************************************************/
+bool Bayesian::checkReleaseDate(ifstream& file1, ifstream& file2, ifstream& file3, ifstream& file4) {
+ try {
+
+ bool good = true;
+
+ vector<string> lines;
+ lines.push_back(m->getline(file1));
+ lines.push_back(m->getline(file2));
+ lines.push_back(m->getline(file3));
+ lines.push_back(m->getline(file4));
+
+ //before we added this check
+ if ((lines[0][0] != '#') || (lines[1][0] != '#') || (lines[2][0] != '#') || (lines[3][0] != '#')) { good = false; }
+ else {
+ //rip off #
+ for (int i = 0; i < lines.size(); i++) { lines[i] = lines[i].substr(1); }
+
+ //get mothurs current version
+ string version = m->getVersion();
+
+ vector<string> versionVector;
+ m->splitAtChar(version, versionVector, '.');
+
+ //check each files version
+ for (int i = 0; i < lines.size(); i++) {
+ vector<string> linesVector;
+ m->splitAtChar(lines[i], linesVector, '.');
+
+ if (versionVector.size() != linesVector.size()) { good = false; break; }
+ else {
+ for (int j = 0; j < versionVector.size(); j++) {
+ int num1, num2;
+ convert(versionVector[j], num1);
+ convert(linesVector[j], num2);
+
+ //if mothurs version is newer than this files version, then we want to remake it
+ if (num1 > num2) { good = false; break; }
+ }
+ }
+
+ if (!good) { break; }
+ }
+ }
+
+ if (!good) { file1.close(); file2.close(); file3.close(); file4.close(); }
+ else { file1.seekg(0); file2.seekg(0); file3.seekg(0); file4.seekg(0); }
+
+ return good;
+ }
+ catch(exception& e) {
+ m->errorOut(e, "Bayesian", "checkReleaseDate");
+ exit(1);
+ }
+}
+/**************************************************************************************************/
projects / mothur.git / blobdiff