X-Git-Url: https://git.donarmstrong.com/?p=mothur.git;a=blobdiff_plain;f=unifracweightedcommand.h;h=a5507cdb6cc2d95152eec0241f386acd66de1aab;hp=ea2c41814ac1940a61bd8c48995ecebcff30f324;hb=b206f634aae1b4ce13978d203247fb64757d5482;hpb=f18d75f9c996cb619a5051a7664620c0c5ae05fb

diff --git a/unifracweightedcommand.h b/unifracweightedcommand.h
index ea2c418..a5507cd 100644
--- a/unifracweightedcommand.h
+++ b/unifracweightedcommand.h
@@ -12,56 +12,145 @@
 
 #include "command.hpp"
 #include "weighted.h"
-#include "treemap.h"
+#include "counttable.h"
 #include "progress.hpp"
-
-using namespace std;
-
-class GlobalData;
+#include "sharedutilities.h"
+#include "fileoutput.h"
+#include "readtree.h"
 
 class UnifracWeightedCommand : public Command {
 	
 	public:
-		UnifracWeightedCommand();	
-		~UnifracWeightedCommand() { delete weighted; }
-		int execute();	
+		UnifracWeightedCommand(string);
+		UnifracWeightedCommand();
+		~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:
-		GlobalData* globaldata;
+		struct linePair {
+			int start;
+			int num;
+			linePair(int i, int j) : start(i), num(j) {}
+		};
+		vector<linePair> lines;
+        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...
-		Tree* randT;  //random tree
-		TreeMap* tmap;
-		Weighted* weighted;
-		string weightedFile, weightedFileout, sumFile;
+		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
-		map<float, float>::iterator it2;
-		map<float, float>::iterator it;
+		vector< map<double, double> > rScoreFreq;  //map <weighted score, number of random trees with that score.> -vector entry for each combination.
+		vector< map<double, double> > rCumul;  //map <weighted score, cumulative percentage of number of random trees with that score or higher.> -vector entry for each c								
+		map<double, double>  validScores;  //map contains scores from random
 		
-		ofstream outSum, out;
-		ifstream inFile;
+		bool abort, phylip, random, includeRoot, subsample, consensus;
+		string groups, itersString, outputForm, treefile, groupfile, namefile, countfile;
+		vector<string> Groups, outputNames; //holds groups to be used
+		int processors, subsampleSize, subsampleIters;
+		ofstream outSum;
+		map<string, string> nameMap;
 		
 		void printWSummaryFile();
 		void printWeightedFile();  
+		void createPhylipFile();
 		//void removeValidScoresDuplicates();
 		int findIndex(float, int);
-		void setGroups(); 
 		void calculateFreqsCumuls();
-		void initFile(string);
-		void output(vector<double>);
-		void resetFile();
+		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);
+		
+};
 
+/***********************************************************************/
+struct weightedRandomData {
+    int start;
+	int num;
+	MothurOut* m;
+    vector< vector<double> > scores;
+    vector< vector<string> > namesOfGroupCombos;
+    Tree* t;
+    CountTable* ct;
+    bool includeRoot;
+	
+	weightedRandomData(){}
+	weightedRandomData(MothurOut* mout, int st, int en, vector< vector<string> > ngc, Tree* tree, CountTable* count, bool ir, vector< vector<double> > sc) {
+        m = mout;
+		start = st;
+		num = en;
+        namesOfGroupCombos = ngc;
+        t = tree;
+        ct = count;
+        includeRoot = ir;
+        scores = sc;
+	}
 };
 
+/**************************************************************************************************/
+#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
+#else
+static DWORD WINAPI MyWeightedRandomThreadFunction(LPVOID lpParam){
+	weightedRandomData* pDataArray;
+	pDataArray = (weightedRandomData*)lpParam;
+	try {
+        
+        Tree* randT = new Tree(pDataArray->ct);
+        
+        Weighted weighted(pDataArray->includeRoot);
+        
+		for (int h = pDataArray->start; h < (pDataArray->start+pDataArray->num); h++) {
+            
+			if (pDataArray->m->control_pressed) { return 0; }
+            
+			//initialize weighted score
+			string groupA = pDataArray->namesOfGroupCombos[h][0];
+			string groupB = pDataArray->namesOfGroupCombos[h][1];
+			
+			//copy T[i]'s info.
+			randT->getCopy(pDataArray->t);
+            
+			//create a random tree with same topology as T[i], but different labels
+			randT->assembleRandomUnifracTree(groupA, groupB);
+			
+			if (pDataArray->m->control_pressed) { delete randT;  return 0;  }
+            
+			//get wscore of random tree
+			EstOutput randomData = weighted.getValues(randT, groupA, groupB);
+            
+			if (pDataArray->m->control_pressed) { delete randT;  return 0;  }
+            
+			//save scores
+			pDataArray->scores[h].push_back(randomData[0]);
+		}
+        
+		delete randT;
+        
+        return 0;
+    }
+	catch(exception& e) {
+		pDataArray->m->errorOut(e, "Weighted", "MyWeightedRandomThreadFunction");
+		exit(1);
+	}
+}
+#endif
 
 
 #endif