X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=clustersplitcommand.cpp;h=874eb6d7b535e9e400cca8f22593280ecd959b42;hb=6b32d112bb60e9f7eb6d4407a4eed4c49b67bced;hp=270ea6208d8ead0683d8cf46fb8d7a417469c243;hpb=ac663461b19ad1436a06aa63f97221d1ff105482;p=mothur.git

diff --git a/clustersplitcommand.cpp b/clustersplitcommand.cpp
index 270ea62..874eb6d 100644
--- a/clustersplitcommand.cpp
+++ b/clustersplitcommand.cpp
@@ -61,7 +61,7 @@ string ClusterSplitCommand::getHelpString(){
         helpString += "The cluster parameter allows you to indicate whether you want to run the clustering or just split the distance matrix, default=t";
 		helpString += "The cutoff parameter allow you to set the distance you want to cluster to, default is 0.25. \n";
 		helpString += "The precision parameter allows you specify the precision of the precision of the distances outputted, default=100, meaning 2 decimal places. \n";
-		helpString += "The method allows you to specify what clustering algorythm you want to use, default=average, option furthest, nearest, or average. \n";
+		helpString += "The method allows you to specify what clustering algorithm you want to use, default=average, option furthest, nearest, or average. \n";
 		helpString += "The splitmethod parameter allows you to specify how you want to split your distance file before you cluster, default=distance, options distance, classify or fasta. \n";
 		helpString += "The taxonomy parameter allows you to enter the taxonomy file for your sequences, this is only valid if you are using splitmethod=classify. Be sure your taxonomy file does not include the probability scores. \n";
 		helpString += "The taxlevel parameter allows you to specify the taxonomy level you want to use to split the distance file, default=3, meaning use the first taxon in each list. \n";
@@ -833,8 +833,10 @@ int ClusterSplitCommand::mergeLists(vector<string> listNames, map<float, int> us
 		m->openOutputFile(listFileName,	outList);
         outputNames.push_back(listFileName); outputTypes["list"].push_back(listFileName);
 		
-		
 		map<float, int>::iterator itLabel;
+        
+        //clears out junk for autocompleting of list files above.  Perhaps there is a beter way to handle this from within the data structure?
+        m->printedListHeaders = false;
 
 		//for each label needed
 		for(itLabel = userLabels.begin(); itLabel != userLabels.end(); itLabel++) {
@@ -890,6 +892,8 @@ int ClusterSplitCommand::mergeLists(vector<string> listNames, map<float, int> us
                 rabund->print(outRabund);
             }
 			//outList << endl;
+            if (!m->printedListHeaders) { 
+                m->listBinLabelsInFile.clear(); completeList.printHeaders(outList); }
             completeList.print(outList);
 			
 			if (rabund != NULL) { delete rabund; }
@@ -1174,7 +1178,7 @@ string ClusterSplitCommand::clusterClassicFile(string thisDistFile, string thisN
             cluster->readPhylipFile(thisDistFile, nameMap);
 		}else if (countfile != "") {
             ct = new CountTable();
-            ct->readTable(thisNamefile, false);
+            ct->readTable(thisNamefile, false, false);
             cluster->readPhylipFile(thisDistFile, ct);
         }
         tag = cluster->getTag();
@@ -1302,7 +1306,7 @@ string ClusterSplitCommand::clusterFile(string thisDistFile, string thisNamefile
             read->read(nameMap);
 		}else if (countfile != "") {
             ct = new CountTable();
-            ct->readTable(thisNamefile, false);
+            ct->readTable(thisNamefile, false, false);
             read->read(ct);
         }else { read->read(nameMap); }
 		
@@ -1330,9 +1334,10 @@ string ClusterSplitCommand::clusterFile(string thisDistFile, string thisNamefile
         m->mothurOutEndLine(); m->mothurOut("Clustering " + thisDistFile); m->mothurOutEndLine();
 		
         //create cluster
-        if (method == "furthest")	{	cluster = new CompleteLinkage(rabund, list, matrix, cutoff, method); }
-        else if(method == "nearest"){	cluster = new SingleLinkage(rabund, list, matrix, cutoff, method); }
-        else if(method == "average"){	cluster = new AverageLinkage(rabund, list, matrix, cutoff, method);	}
+        float adjust = -1.0;
+        if (method == "furthest")	{	cluster = new CompleteLinkage(rabund, list, matrix, cutoff, method, adjust); }
+        else if(method == "nearest"){	cluster = new SingleLinkage(rabund, list, matrix, cutoff, method, adjust); }
+        else if(method == "average"){	cluster = new AverageLinkage(rabund, list, matrix, cutoff, method, adjust);	}
         tag = cluster->getTag();
 		
         if (outputDir == "") { outputDir += m->hasPath(thisDistFile); }