X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=unifracweightedcommand.h;h=e1ebd16c6151e373eb86971f53295d2036b4e4c2;hb=03dca3b32a903c3f29fbcf5b410b19d6ab6dae63;hp=fe5d76c700a130848c9f5f3eef657a3094cda177;hpb=8f7f4fc08b8c70d9ef0f79607813dba4e926e102;p=mothur.git

diff --git a/unifracweightedcommand.h b/unifracweightedcommand.h
index fe5d76c..e1ebd16 100644
--- a/unifracweightedcommand.h
+++ b/unifracweightedcommand.h
@@ -30,7 +30,8 @@ class UnifracWeightedCommand : public Command {
 		string getCommandCategory()		{ return "Hypothesis Testing";		}
 		string getHelpString();	
 		string getCitation() { return "Lozupone CA, Hamady M, Kelley ST, Knight R (2007). Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol 73: 1576-85. \nhttp://www.mothur.org/wiki/Unifrac.weighted"; }
-	
+		string getDescription()		{ return "generic tests that describes whether two or more communities have the same structure"; }
+
 		int execute();
 		void help() { m->mothurOut(getHelpString()); }
 	
@@ -50,21 +51,18 @@ class UnifracWeightedCommand : public Command {
 		vector<double> WScoreSig;  //tree weighted score signifigance when compared to random trees - percentage of random trees with that score or lower.
 		vector<string> groupComb; // AB. AC, BC...
 		TreeMap* tmap;
-		Weighted* weighted;
 		string sumFile, outputDir;
 		int iters, numGroups, numComp, counter;
-		EstOutput userData;			//weighted score info for user tree
-		EstOutput randomData;		//weighted score info for random trees
 		vector< vector<double> > rScores;  //vector<weighted scores for random trees.> each group comb has an entry
 		vector< vector<double> > uScores;  //vector<weighted scores for user trees.> each group comb has an entry
 		vector< map<float, float> > rScoreFreq;  //map <weighted score, number of random trees with that score.> -vector entry for each combination.
 		vector< map<float, float> > rCumul;  //map <weighted score, cumulative percentage of number of random trees with that score or higher.> -vector entry for each c								
 		map<float, float>  validScores;  //map contains scores from random
 		
-		bool abort, phylip, random, includeRoot;
+		bool abort, phylip, random, includeRoot, subsample, consensus;
 		string groups, itersString, outputForm, treefile, groupfile, namefile;
 		vector<string> Groups, outputNames; //holds groups to be used
-		int processors, numUniquesInName;
+		int processors, numUniquesInName, subsampleSize, subsampleIters;
 		ofstream outSum;
 		map<string, string> nameMap;
 		
@@ -77,6 +75,11 @@ class UnifracWeightedCommand : public Command {
 		int createProcesses(Tree*,  vector< vector<string> >,  vector< vector<double> >&);
 		int driver(Tree*, vector< vector<string> >, int, int,  vector< vector<double> >&);
 		int readNamesFile();
+        int runRandomCalcs(Tree*, vector<double>);
+        int readTrees();
+        vector<Tree*> buildTrees(vector< vector<double> >&, int, TreeMap*);
+        int getConsensusTrees(vector< vector<double> >&, int);
+        int getAverageSTDMatrices(vector< vector<double> >&, int);
 		
 };