X-Git-Url: https://git.donarmstrong.com/?p=mothur.git;a=blobdiff_plain;f=unifracunweightedcommand.cpp;h=db5cf90cf56ad18ad1f5fd80cb6ee5b79c1aaa32;hp=dbdee2ad942db51860cb0a7f403662a895def1bf;hb=e98d56be8369a799e61a411bc13d3bd1fa3451e5;hpb=0caf3fbabaa3ece404f8ce77f4c883dc5b1bf1dc

diff --git a/unifracunweightedcommand.cpp b/unifracunweightedcommand.cpp
index dbdee2a..db5cf90 100644
--- a/unifracunweightedcommand.cpp
+++ b/unifracunweightedcommand.cpp
@@ -245,6 +245,7 @@ int UnifracUnweightedCommand::execute() {
         T = reader->getTrees();
         tmap = T[0]->getTreeMap();
         map<string, string> nameMap = reader->getNames();
+        map<string, string> unique2Dup = reader->getNameMap();
         delete reader;	
         
 		sumFile = outputDir + m->getSimpleName(treefile) + ".uwsummary";
@@ -281,7 +282,7 @@ int UnifracUnweightedCommand::execute() {
                     int thisSize = thisGroupsSeqs.size();
                     
                     if (thisSize >= subsampleSize) {    Groups.push_back(newGroups[i]);	}
-                    else {  m->mothurOut("You have selected a size that is larger than "+newGroups[i]+" number of sequences, removing "+newGroups[i]+".\n"); }
+                    else {   m->mothurOut("You have selected a size that is larger than "+newGroups[i]+" number of sequences, removing "+newGroups[i]+".\n"); }
                 } 
                 m->setGroups(Groups);
             }
@@ -305,7 +306,7 @@ int UnifracUnweightedCommand::execute() {
 		for (int i = 0; i < T.size(); i++) {
 			if (m->control_pressed) { delete tmap; for (int i = 0; i < T.size(); i++) { delete T[i]; }outSum.close(); for (int i = 0; i < outputNames.size(); i++) {	m->mothurRemove(outputNames[i]);  } return 0; }
 			
-			counter = 0;
+            counter = 0;
 			
 			if (random)  {  
 				output = new ColumnFile(outputDir + m->getSimpleName(treefile)  + toString(i+1) + ".unweighted", itersString);
@@ -354,6 +355,11 @@ int UnifracUnweightedCommand::execute() {
                 SubSample sample;
                 Tree* subSampleTree = sample.getSample(T[i], newTmap, nameMap, subsampleSize);
                 
+                //uses method of setting groups to doNotIncludeMe
+                //SubSample sample;
+                //Tree* newTree2 = sample.getSample(T[i], newTmap, nameMap, subsampleSize, unique2Dup);
+                // newTree2->print(cout);
+                
                 //call new weighted function
                 vector<double> iterData; iterData.resize(numComp,0);
                 Unweighted thisUnweighted(includeRoot);