#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(), 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 {
-
+ ReferenceDB* rdb = ReferenceDB::getInstance();
+
+ threadID = tid;
+ flip = f;
+ shortcuts = sh;
+ string baseName = tempFile;
+
+ 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*************/
- string tfileroot = tfile.substr(0,tfile.find_last_of(".")+1);
- string tempfileroot = getRootName(getSimpleName(tempFile));
+ 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";
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 && phyloTreeTest){
+ //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();
+ }
+
+ 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(); }
+
m->mothurOut("Reading template taxonomy... "); cout.flush();
phyloTree = new PhyloTree(phyloTreeTest, phyloTreeName);
genusNodes = phyloTree->getGenusNodes();
genusTotals = phyloTree->getGenusTotals();
-
- m->mothurOut("Reading template probabilities... "); cout.flush();
- readProbFile(probFileTest, probFileTest2, probFileName, probFileName2);
+ 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);
- 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);
-
- for (int j = 0; j < wordGenusProb.size(); j++) { wordGenusProb[j].resize(genusNodes.size()); }
-
-
- #ifdef USE_MPI
- int pid;
- MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
-
- if (pid == 0) {
- #endif
-
- ofstream out;
- openOutputFile(probFileName, out);
-
- out << numKmers << endl;
-
- ofstream out2;
- openOutputFile(probFileName2, out2);
+ //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;
- #ifdef USE_MPI
- }
- #endif
-
+ //initialze probabilities
+ wordGenusProb.resize(numKmers);
+ WordPairDiffArr.resize(numKmers);
- //for each word
- for (int i = 0; i < numKmers; i++) {
- if (m->control_pressed) { break; }
+ 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
- out << i << '\t';
- #ifdef USE_MPI
- }
- #endif
+ if (shortcuts) {
+ m->openOutputFile(probFileName, out);
- vector<int> seqsWithWordi = database->getSequencesWithKmer(i);
+ //output mothur version
+ out << "#" << m->getVersion() << endl;
- map<int, int> count;
- for (int k = 0; k < genusNodes.size(); k++) { count[genusNodes[k]] = 0; }
-
- //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
- }
+ out << numKmers << endl;
- //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);
+ m->openOutputFile(probFileName2, out2);
- 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) {
- #ifdef USE_MPI
- MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
- if (pid == 0) {
- #endif
+ //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
- out << k << '\t' << wordGenusProb[i][k] << '\t';
+ 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;
- #ifdef USE_MPI
- }
- #endif
+ 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
+
+ if (pid == 0) {
+ #endif
- numNotZero++;
+ 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
}
#ifdef USE_MPI
MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
+
if (pid == 0) {
#endif
- out << endl;
- out2 << probabilityInTemplate << '\t' << numNotZero << endl;
-
+ 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; }
}
-
- #ifdef USE_MPI
- MPI_Comm_rank(MPI_COMM_WORLD, &pid); //find out who we are
- if (pid == 0) {
- #endif
-
- 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);
}
-
+
+ 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();
}
/**************************************************************************************************/
Bayesian::~Bayesian() {
try {
- delete phyloTree;
- if (database != NULL) { delete database; }
+ if (phyloTree != NULL) { delete phyloTree; }
+ if (database != NULL) { delete database; }
}
catch(exception& e) {
m->errorOut(e, "Bayesian", "~Bayesian");
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 (queryKmers.size() == 0) { m->mothurOut(seq->getName() + "is bad."); m->mothurOutEndLine(); return "bad seq"; }
+ //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; }
-//cout << seq->getName() << '\t' << index << endl;
+
//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) {
try {
map<int, int> confidenceScores;
+
+ //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);
+ //int newTax = 1;
TaxNode taxonomyTemp = phyloTree->get(newTax);
-
+
//add to confidence results
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
- if (itBoot2 == confidenceScores.end()) { //not already in confidence scores
- confidenceScores[newTax] = 1;
- }else{
- confidenceScores[newTax]++;
+ if (itBoot2 != confidenceScores.end()) { //this is a classification we need a confidence for
+ (itBoot2->second)++;
}
newTax = taxonomyTemp.parent;
int seqTaxIndex = tax;
TaxNode seqTax = phyloTree->get(tax);
+
while (seqTax.level != 0) { //while you are not at the root
itBoot2 = confidenceScores.find(seqTaxIndex); //is this a classification we already have a count on
int confidence = 0;
if (itBoot2 != confidenceScores.end()) { //already in confidence scores
- confidence = confidenceScores[seqTaxIndex];
+ confidence = itBoot2->second;
}
+ 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 = "unclassified;"; simpleTax = "unclassified;"; }
+ if (confidenceTax == "") { confidenceTax = "unknown;"; simpleTax = "unknown;"; }
+
return confidenceTax;
}
double maxProbability = -1000000.0;
//find taxonomy with highest probability that this sequence is from it
+
+
+// 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, string inName, string inNumName) {
try{
#ifdef USE_MPI
int pid, num, num2, processors;
- vector<long> positions;
- vector<long> positions2;
+ vector<unsigned long long> positions;
+ vector<unsigned long long> positions2;
MPI_Status status;
MPI_File inMPI;
MPI_File_open(MPI_COMM_WORLD, inFileName2, MPI_MODE_RDONLY, MPI_INFO_NULL, &inMPI2); //comm, filename, mode, info, filepointer
if (pid == 0) {
- positions = setFilePosEachLine(inNumName, num);
- positions2 = setFilePosEachLine(inName, num2);
+ 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);
positions2.resize(num2+1);
MPI_Recv(&positions2[0], (num2+1), MPI_LONG, 0, tag, MPI_COMM_WORLD, &status);
}
-
- //read numKmers
+
+ //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[0], buf, length, MPI_CHAR, &status);
+ MPI_File_read_at(inMPI2, positions2[1], buf, length, MPI_CHAR, &status);
string tempBuf = buf;
if (tempBuf.length() > length) { tempBuf = tempBuf.substr(0, length); }
int kmer, name;
vector<int> numbers; numbers.resize(numKmers);
float prob;
- vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
+ 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=0;i<num;i++){
+ for(int i=1;i<num;i++){
//read next sequence
length = positions[i+1] - positions[i];
char* buf4 = new char[length];
delete buf4;
istringstream iss (tempBuf,istringstream::in);
- iss >> zeroCountProb[i] >> numbers[i];
+ float probTemp;
+ iss >> zeroCountProb[i] >> numbers[i] >> probTemp;
+ WordPairDiffArr[i].prob = probTemp;
+
}
MPI_File_close(&inMPI);
- for(int i=1;i<num2;i++){
+ for(int i=2;i<num2;i++){
//read next sequence
length = positions2[i+1] - positions2[i];
char* buf4 = new char[length];
MPI_File_close(&inMPI2);
MPI_Barrier(MPI_COMM_WORLD); //make everyone wait - just in case
#else
-
- in >> numKmers; gobble(in);
+ //read version
+ string line = m->getline(in); m->gobble(in);
+ in >> numKmers; m->gobble(in);
+ //cout << threadID << '\t' << line << '\t' << numKmers << &in << '\t' << &inNum << '\t' << genusNodes.size() << endl;
//initialze probabilities
wordGenusProb.resize(numKmers);
int kmer, name, count; count = 0;
vector<int> num; num.resize(numKmers);
float prob;
- vector<float> zeroCountProb; zeroCountProb.resize(numKmers);
-
+ 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];
+ inNum >> zeroCountProb[count] >> num[count] >> probTemp;
+ WordPairDiffArr[count].prob = probTemp;
count++;
- gobble(inNum);
+ 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;
}
- gobble(in);
+ m->gobble(in);
}
in.close();
-
+ //cout << threadID << '\t' << "here" << endl;
#endif
}
catch(exception& e) {
}
}
/**************************************************************************************************/
+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