X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=classifyseqscommand.h;h=bfc42a9b81c6406caabea9eac68c00eeab5f30ff;hb=f6a58db15cdc7b90a601f8bf9c9d3b69d642f85d;hp=a3328d8dcea09eebe63c641e04e1b816fc92fee1;hpb=deba0af0ccdcb6005ed5b2b82649b137c63fbdf7;p=mothur.git diff --git a/classifyseqscommand.h b/classifyseqscommand.h index a3328d8..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); @@ -163,12 +163,10 @@ static DWORD WINAPI MyClassThreadFunction(LPVOID lpParam){ inFASTA.seekg(pDataArray->start-1); pDataArray->m->gobble(inFASTA); } - pDataArray->count = pDataArray->end; - //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; @@ -176,14 +174,14 @@ 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); } if (pDataArray->m->control_pressed) { delete myclassify; return 0; } - int count = 0; + pDataArray->count = 0; for(int i = 0; i < pDataArray->end; i++){ //end is the number of sequences to process if (pDataArray->m->control_pressed) { delete myclassify; return 0; } @@ -209,15 +207,15 @@ static DWORD WINAPI MyClassThreadFunction(LPVOID lpParam){ if (myclassify->getFlipped()) { outAcc << candidateSeq->getName() << endl; } - count++; + pDataArray->count++; } delete candidateSeq; //report progress - if((count) % 100 == 0){ pDataArray->m->mothurOut("Processing sequence: " + toString(count)); pDataArray->m->mothurOutEndLine(); } + if((pDataArray->count) % 100 == 0){ pDataArray->m->mothurOutJustToScreen("Processing sequence: " + toString(pDataArray->count)+"\n"); } } //report progress - if((count) % 100 != 0){ pDataArray->m->mothurOut("Processing sequence: " + toString(count)); pDataArray->m->mothurOutEndLine(); } + if((pDataArray->count) % 100 != 0){ pDataArray->m->mothurOutJustToScreen("Processing sequence: " + toString(pDataArray->count)+"\n"); } delete myclassify; inFASTA.close();