X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=classifyseqscommand.h;h=bfc42a9b81c6406caabea9eac68c00eeab5f30ff;hb=f6a58db15cdc7b90a601f8bf9c9d3b69d642f85d;hp=f8a820dcf6347aa39432d461c78f6f8613ae6acf;hpb=14cddf859d97118481161bf3e85a647976020758;p=mothur.git

diff --git a/classifyseqscommand.h b/classifyseqscommand.h
index f8a820d..bfc42a9 100644
--- a/classifyseqscommand.h
+++ b/classifyseqscommand.h
@@ -77,7 +77,7 @@ private:
 	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, hasName, hasCount, writeShortcuts;
+	bool abort, probs, save, flip, hasName, hasCount, writeShortcuts, relabund;
 	
 	int driver(linePair*, string, string, string, string);
 	int createProcesses(string, string, string, string); 
@@ -166,7 +166,7 @@ static DWORD WINAPI MyClassThreadFunction(LPVOID lpParam){
 		//make classify
 		Classify* myclassify;
         string outputMethodTag = pDataArray->method + ".";
-		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);		}
+		if(pDataArray->method == "wang"){	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 if(pDataArray->method == "zap"){	
             outputMethodTag = pDataArray->search + "_" + outputMethodTag;
@@ -174,7 +174,7 @@ static DWORD WINAPI MyClassThreadFunction(LPVOID lpParam){
             else {  myclassify = new AlignTree(pDataArray->templateFileName, pDataArray->taxonomyFileName, pDataArray->cutoff);  }
         }
 		else {
-			pDataArray->m->mothurOut(pDataArray->search + " is not a valid method option. I will run the command using bayesian.");
+			pDataArray->m->mothurOut(pDataArray->method + " is not a valid method option. I will run the command using wang.");
 			pDataArray->m->mothurOutEndLine();
 			myclassify = new Bayesian(pDataArray->taxonomyFileName, pDataArray->templateFileName, pDataArray->search, pDataArray->kmerSize, pDataArray->cutoff, pDataArray->iters, pDataArray->threadID, pDataArray->flip, pDataArray->writeShortcuts);	
 		}
@@ -211,11 +211,11 @@ static DWORD WINAPI MyClassThreadFunction(LPVOID lpParam){
 			}
 			delete candidateSeq;
 			//report progress
-			if((pDataArray->count) % 100 == 0){	pDataArray->m->mothurOut("Processing sequence: " + toString(pDataArray->count)); pDataArray->m->mothurOutEndLine();		}
+			if((pDataArray->count) % 100 == 0){	pDataArray->m->mothurOutJustToScreen("Processing sequence: " + toString(pDataArray->count)+"\n"); 	}
 			
 		}
 		//report progress
-		if((pDataArray->count) % 100 != 0){	pDataArray->m->mothurOut("Processing sequence: " + toString(pDataArray->count)); pDataArray->m->mothurOutEndLine();		}
+		if((pDataArray->count) % 100 != 0){	pDataArray->m->mothurOutJustToScreen("Processing sequence: " + toString(pDataArray->count)+"\n"); 		}
 		
 		delete myclassify;
 		inFASTA.close();