X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=classifyseqscommand.h;h=6d11d9236778028e326c6f4fdd4925dd6430fd50;hb=035f86272c776e1cccaa47021e26782e49cd41e7;hp=acee70c5cb474dee4e25eea4a6dcf6b5bd55fa06;hpb=91a27e0483827c06c21c4fe89558923bbfe86573;p=mothur.git

diff --git a/classifyseqscommand.h b/classifyseqscommand.h
index acee70c..6d11d92 100644
--- a/classifyseqscommand.h
+++ b/classifyseqscommand.h
@@ -41,6 +41,7 @@ public:
 	vector<string> setParameters();
 	string getCommandName()			{ return "classify.seqs";		}
 	string getCommandCategory()		{ return "Phylotype Analysis";	}
+	string getOutputFileNameTag(string, string);
 	string getHelpString();	
 	string getCitation() { return "Wang Q, Garrity GM, Tiedje JM, Cole JR (2007). Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73: 5261-7. [ for Bayesian classifier ] \nAltschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389-402. [ for BLAST ] \nDeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL (2006). Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72: 5069-72. [ for kmer ] \nhttp://www.mothur.org/wiki/Classify.seqs"; }
 	string getDescription()		{ return "classify sequences"; }
@@ -61,6 +62,7 @@ private:
 	vector<linePair*> lines;
 	vector<string> fastaFileNames;
 	vector<string> namefileNames;
+    vector<string> countfileNames;
 	vector<string> groupfileNames;
 	vector<string> outputNames;
 	map<string, vector<string> > nameMap;
@@ -69,13 +71,12 @@ private:
 	Classify* classify;
 	ReferenceDB* rdb;
 	
-	string fastaFileName, templateFileName, distanceFileName, namefile, search, method, taxonomyFileName, outputDir, groupfile;
+	string fastaFileName, templateFileName, countfile, distanceFileName, namefile, search, method, taxonomyFileName, outputDir, groupfile;
 	int processors, kmerSize, numWanted, cutoff, iters;
 	float match, misMatch, gapOpen, gapExtend;
-	bool abort, probs, save, flip;
+	bool abort, probs, save, flip, hasName, hasCount, writeShortcuts;
 	
 	int driver(linePair*, string, string, string, string);
-	void appendTaxFiles(string, string);
 	int createProcesses(string, string, string, string); 
 	string addUnclassifieds(string, int);
 	
@@ -99,10 +100,10 @@ struct classifyData {
 	MothurOut* m;
 	float match, misMatch, gapOpen, gapExtend;
 	int count, kmerSize, threadID, cutoff, iters, numWanted;
-	bool probs, flip;
+	bool probs, flip, writeShortcuts;
 	 
 	classifyData(){}
-	classifyData(string acc, bool p, string me, string te, string tx, string a, string r, string f, string se, int ks, int i, int numW, MothurOut* mout, unsigned long long st, unsigned long long en, float ma, float misMa, float gapO, float gapE, int cut, int tid, bool fli) {
+	classifyData(string acc, bool p, string me, string te, string tx, string a, string r, string f, string se, int ks, int i, int numW, MothurOut* mout, unsigned long long st, unsigned long long en, float ma, float misMa, float gapO, float gapE, int cut, int tid, bool fli, bool wsh) {
 		accnos = acc;
 		taxonomyFileName = tx;
 		templateFileName = te;
@@ -126,6 +127,7 @@ struct classifyData {
 		probs = p;
 		count = 0;
 		flip = fli;
+        writeShortcuts = wsh;
 	}
 };
 
@@ -162,12 +164,12 @@ static DWORD WINAPI MyClassThreadFunction(LPVOID lpParam){
 		
 		//make classify
 		Classify* myclassify;
-		if(pDataArray->method == "bayesian"){	myclassify = new Bayesian(pDataArray->taxonomyFileName, pDataArray->templateFileName, pDataArray->search, pDataArray->kmerSize, pDataArray->cutoff, pDataArray->iters, pDataArray->threadID, pDataArray->flip);		}
+		if(pDataArray->method == "bayesian"){	myclassify = new Bayesian(pDataArray->taxonomyFileName, pDataArray->templateFileName, pDataArray->search, pDataArray->kmerSize, pDataArray->cutoff, pDataArray->iters, pDataArray->threadID, pDataArray->flip, pDataArray->writeShortcuts);		}
 		else if(pDataArray->method == "knn"){	myclassify = new Knn(pDataArray->taxonomyFileName, pDataArray->templateFileName, pDataArray->search, pDataArray->kmerSize, pDataArray->gapOpen, pDataArray->gapExtend, pDataArray->match, pDataArray->misMatch, pDataArray->numWanted, pDataArray->threadID);				}
 		else {
 			pDataArray->m->mothurOut(pDataArray->search + " is not a valid method option. I will run the command using bayesian.");
 			pDataArray->m->mothurOutEndLine();
-			myclassify = new Bayesian(pDataArray->taxonomyFileName, pDataArray->templateFileName, pDataArray->search, pDataArray->kmerSize, pDataArray->cutoff, pDataArray->iters, pDataArray->threadID, pDataArray->flip);	
+			myclassify = new Bayesian(pDataArray->taxonomyFileName, pDataArray->templateFileName, pDataArray->search, pDataArray->kmerSize, pDataArray->cutoff, pDataArray->iters, pDataArray->threadID, pDataArray->flip, pDataArray->writeShortcuts);	
 		}
 		
 		if (pDataArray->m->control_pressed) { delete myclassify; return 0; }