//**********************************************************************************************************************
ClassifySeqsCommand::ClassifySeqsCommand(){
try {
- abort = true;
- //initialize outputTypes
+ abort = true; calledHelp = true;
vector<string> tempOutNames;
outputTypes["taxonomy"] = tempOutNames;
outputTypes["taxsummary"] = tempOutNames;
//**********************************************************************************************************************
ClassifySeqsCommand::ClassifySeqsCommand(string option) {
try {
- abort = false;
+ abort = false; calledHelp = false;
//allow user to run help
- if(option == "help") { help(); abort = true; }
+ if(option == "help") { help(); abort = true; calledHelp = true; }
else {
int ClassifySeqsCommand::execute(){
try {
- if (abort == true) { return 0; }
+ if (abort == true) { if (calledHelp) { return 0; } return 2; }
if(method == "bayesian"){ classify = new Bayesian(taxonomyFileName, templateFileName, search, kmerSize, cutoff, iters); }
else if(method == "knn"){ classify = new Knn(taxonomyFileName, templateFileName, search, kmerSize, gapOpen, gapExtend, match, misMatch, numWanted); }
for (int i = 0; i < lines.size(); i++) { delete lines[i]; } lines.clear();
#ifdef USE_MPI
- int pid, end, numSeqsPerProcessor;
+ int pid, numSeqsPerProcessor;
int tag = 2001;
vector<unsigned long int> MPIPos;
//get maxLevel from phylotree so you know how many 'unclassified's to add
int maxLevel = taxaSum.getMaxLevel();
-
+
//read taxfile - this reading and rewriting is done to preserve the confidence scores.
string name, taxon;
while (!inTax.eof()) {