#include "command.hpp"
#include "weighted.h"
-#include "treemap.h"
-
-using namespace std;
-
-class GlobalData;
+#include "counttable.h"
+#include "progress.hpp"
+#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<float> utreeScores; //user tree unweighted scores
- vector<float> WScoreSig; //tree weighted score signifigance when compared to random trees - percentage of random trees with that score or lower.
+ 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, sumFile;
- int iters, numGroups, numComp;
- EstOutput userData; //weighted score info for user tree
- EstOutput randomData; //weighted score info for random trees
- vector< map<float, float> > validScores; //vector<contains scores from both user and random> each group comb has an entry
- vector< map<float, float> > rscoreFreq; //vector<weighted score, number of random trees with that score.> each group comb has an entry
- vector< map<float, float> > uscoreFreq; //vector<weighted, number of user trees with that score.> each group comb has an entry
- vector< map<float, float> > totalrscoreFreq; //vector<weighted score, number of random trees with that score.> each group comb has an entry
- vector< map<float, float> > rCumul; //vector<weighted score, number of random trees with that score or higher.> each group comb has an entry
- vector< map<float, float> > uCumul; //vector<weighted, cumulative percentage of number of user trees with that score or higher.> each group comb has an entry
- map<float, float>::iterator it;
- map<float, float>::iterator it2;
+ string sumFile, outputDir;
+ int iters, numGroups, numComp, counter;
+ 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<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;
+ 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 saveRandomScores();
- void setGroups();
+ void createPhylipFile();
+ //void removeValidScoresDuplicates();
+ int findIndex(float, int);
+ 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);
+
};
+/***********************************************************************/
+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