inFASTA.close();
lines.push_back(new linePair(0, numFastaSeqs));
-
+
driver(lines[0], newTaxonomyFile, tempTaxonomyFile);
-
}
else{
vector<int> positions;
}
#else
ifstream inFASTA;
- openInputFile(candidateFileName, inFASTA);
+ openInputFile(fastaFileName, inFASTA);
numFastaSeqs=count(istreambuf_iterator<char>(inFASTA),istreambuf_iterator<char>(), '>');
inFASTA.close();
lines.push_back(new linePair(0, numFastaSeqs));
driver(lines[0], newTaxonomyFile, tempTaxonomyFile);
-#endif
-
+#endif
delete classify;
//make taxonomy tree from new taxonomy file
taxonomy = classify->getTaxonomy(candidateSeq);
if (taxonomy != "bad seq") {
- //if (method != "bayesian") {
- outTax << candidateSeq->getName() << '\t' << taxonomy << endl;
- outTaxSimple << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
- //}else{
- //vector<string> pTax = classify->parseTax(taxonomy);
- //map<string, int> confidence = classify->getConfidenceScores();
-
- //outTax << candidateSeq->getName() << '\t';
- //for (int j = 0; j < pTax.size(); j++) {
- //if (confidence[pTax[j]] > cutoff) {
- // outTax << pTax[j] << "(" << confidence[pTax[j]] << ");";
- //}else{ break; }
- //}
- //outTax << endl;
- //}
+ outTax << candidateSeq->getName() << '\t' << taxonomy << endl;
+ outTaxSimple << candidateSeq->getName() << '\t' << classify->getSimpleTax() << endl;
}
delete candidateSeq;
- if(i % 100 == 0){
- mothurOut("Classifying sequence " + toString(i)); mothurOutEndLine();
+ if((i+1) % 100 == 0){
+ mothurOut("Classifying sequence " + toString(i+1)); mothurOutEndLine();
}
}