assign_out.print("\t" + ranks[i]);
}
assign_out.println();
}
for (MCSample sample : samples) {
Sequence seq;
while ((seq = sample.getNextSeq()) != null) {
try {
ClassificationResult result = classifier.classify(new ClassifierSequence(seq), min_bootstrap_words);
if ( !format.equals(ClassificationResultFormatter.FORMAT.biom)){
printClassificationResult(result, assign_out, format, confidence);
}else {
seqClassificationMap.put(result.getSequence().getSeqName(), ClassificationResultFormatter.getOutput(result, format, confidence, ranks));
}
processClassificationResult(result, sample, root, confidence, seqCountMap);
sample.addRankCount(result);
} catch (ShortSequenceException e) {
badSequences.add(seq.getSeqName());
}
}
}