X-Git-Url: https://git.donarmstrong.com/?a=blobdiff_plain;f=unifracweightedcommand.h;h=1c67c32f81afb2535943934ab82d66629bbc05b2;hb=67ea6ccd74dbd64828d31b952808255f206364ff;hp=2eee7c44e674073420c217f1b4d49aa4dc769497;hpb=fca3f55d5ded10c3dc77856f3cc4a1c53b02bb6f;p=mothur.git

diff --git a/unifracweightedcommand.h b/unifracweightedcommand.h
index 2eee7c4..1c67c32 100644
--- a/unifracweightedcommand.h
+++ b/unifracweightedcommand.h
@@ -12,26 +12,30 @@
 
 #include "command.hpp"
 #include "weighted.h"
-#include "treemap.h"
+#include "counttable.h"
 #include "progress.hpp"
 #include "sharedutilities.h"
 #include "fileoutput.h"
-
-
-class GlobalData;
+#include "readtree.h"
 
 class UnifracWeightedCommand : public Command {
 	
 	public:
 		UnifracWeightedCommand(string);
 		UnifracWeightedCommand();
-		~UnifracWeightedCommand() { if (abort == false) {  delete weighted; delete util; } }
-		vector<string> getRequiredParameters();
-		vector<string> getValidParameters();
-		vector<string> getRequiredFiles();
-		map<string, vector<string> > getOutputFiles() { return outputTypes; }
-		int execute();	
-		void help();
+		~UnifracWeightedCommand() {}
+	
+		vector<string> setParameters();
+		string getCommandName()			{ return "unifrac.weighted";		}
+		string getCommandCategory()		{ return "Hypothesis Testing";		}
+		
+	string getHelpString();	
+    string getOutputPattern(string);	
+		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()); }
 	
 	private:
 		struct linePair {
@@ -40,34 +44,26 @@ class UnifracWeightedCommand : public Command {
 			linePair(int i, int j) : start(i), num(j) {}
 		};
 		vector<linePair> lines;
-		
-		GlobalData* globaldata;
-		SharedUtil* util;
+        CountTable* ct;
 		FileOutput* output;
 		vector<Tree*> T;	   //user trees
 		vector<double> utreeScores;  //user tree unweighted scores
 		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;
-		string groups, itersString, outputForm;
+		bool abort, phylip, random, includeRoot, subsample, consensus;
+		string groups, itersString, outputForm, treefile, groupfile, namefile, countfile;
 		vector<string> Groups, outputNames; //holds groups to be used
-		map<string, vector<string> > outputTypes;
-		int processors;
-
-		
+		int processors, subsampleSize, subsampleIters;
 		ofstream outSum;
+		map<string, string> nameMap;
 		
 		void printWSummaryFile();
 		void printWeightedFile();  
@@ -77,6 +73,10 @@ class UnifracWeightedCommand : public Command {
 		void calculateFreqsCumuls();
 		int createProcesses(Tree*,  vector< vector<string> >,  vector< vector<double> >&);
 		int driver(Tree*, vector< vector<string> >, int, int,  vector< vector<double> >&);
+        int runRandomCalcs(Tree*, vector<double>);
+        vector<Tree*> buildTrees(vector< vector<double> >&, int, CountTable&);
+        int getConsensusTrees(vector< vector<double> >&, int);
+        int getAverageSTDMatrices(vector< vector<double> >&, int);
 		
 };