#include "inputdata.h"
#include "groupmap.h"
#include "validcalculator.h"
+#include "sharedsobscollectsummary.h"
+#include "sharedchao1.h"
+#include "sharedace.h"
+#include "sharednseqs.h"
+#include "sharedjabund.h"
+#include "sharedsorabund.h"
+#include "sharedjclass.h"
+#include "sharedsorclass.h"
+#include "sharedjest.h"
+#include "sharedsorest.h"
+#include "sharedthetayc.h"
+#include "sharedthetan.h"
+#include "sharedkstest.h"
+#include "whittaker.h"
+#include "sharedochiai.h"
+#include "sharedanderbergs.h"
+#include "sharedkulczynski.h"
+#include "sharedkulczynskicody.h"
+#include "sharedlennon.h"
+#include "sharedmorisitahorn.h"
+#include "sharedbraycurtis.h"
+#include "sharedjackknife.h"
+#include "whittaker.h"
+#include "odum.h"
+#include "canberra.h"
+#include "structeuclidean.h"
+#include "structchord.h"
+#include "hellinger.h"
+#include "manhattan.h"
+#include "structpearson.h"
+#include "soergel.h"
+#include "spearman.h"
+#include "structkulczynski.h"
+#include "structchi2.h"
+#include "speciesprofile.h"
+#include "hamming.h"
+#include "gower.h"
+#include "memchi2.h"
+#include "memchord.h"
+#include "memeuclidean.h"
+#include "mempearson.h"
+
// aka. dist.shared()
vector<string> setParameters();
string getCommandName() { return "dist.shared"; }
string getCommandCategory() { return "OTU-Based Approaches"; }
+
string getHelpString();
+ string getOutputPattern(string);
string getCitation() { return "http://www.mothur.org/wiki/Dist.shared"; }
+ string getDescription() { return "generate a distance matrix that describes the dissimilarity among multiple groups"; }
+
int execute();
void help() { m->mothurOut(getHelpString()); }
private:
- void printSims(ostream&);
+ struct linePair {
+ int start;
+ int end;
+ };
+ vector<linePair> lines;
+
+ void printSims(ostream&, vector< vector<double> >&);
int process(vector<SharedRAbundVector*>);
vector<Calculator*> matrixCalculators;
- vector< vector<float> > simMatrix;
+ //vector< vector<float> > simMatrix;
InputData* input;
vector<SharedRAbundVector*> lookup;
string exportFileName, output, sharedfile;
- int numGroups;
+ int numGroups, processors, iters, subsampleSize;
ofstream out;
- bool abort, allLines;
+ bool abort, allLines, subsample;
set<string> labels; //holds labels to be used
- string outputFile, calc, groups, label, outputDir;
+ string outputFile, calc, groups, label, outputDir, mode;
vector<string> Estimators, Groups, outputNames; //holds estimators to be used
+ int process(vector<SharedRAbundVector*>, string, string);
+ int driver(vector<SharedRAbundVector*>, int, int, vector< vector<seqDist> >&);
+
};
+/**************************************************************************************************/
+//custom data structure for threads to use.
+// This is passed by void pointer so it can be any data type
+// that can be passed using a single void pointer (LPVOID).
+struct distSharedData {
+ vector<SharedRAbundVector*> thisLookup;
+ vector< vector<seqDist> > calcDists;
+ vector<string> Estimators;
+ unsigned long long start;
+ unsigned long long end;
+ MothurOut* m;
+ int count;
+
+ distSharedData(){}
+ distSharedData(MothurOut* mout, unsigned long long st, unsigned long long en, vector<string> est, vector<SharedRAbundVector*> lu) {
+ m = mout;
+ start = st;
+ end = en;
+ Estimators = est;
+ thisLookup = lu;
+ count = 0;
+ }
+};
+/**************************************************************************************************/
+#if defined (__APPLE__) || (__MACH__) || (linux) || (__linux) || (__linux__) || (__unix__) || (__unix)
+#else
+static DWORD WINAPI MyDistSharedThreadFunction(LPVOID lpParam){
+ distSharedData* pDataArray;
+ pDataArray = (distSharedData*)lpParam;
+
+ try {
+
+ vector<Calculator*> matrixCalculators;
+ ValidCalculators validCalculator;
+ for (int i=0; i<pDataArray->Estimators.size(); i++) {
+ if (validCalculator.isValidCalculator("matrix", pDataArray->Estimators[i]) == true) {
+ if (pDataArray->Estimators[i] == "sharedsobs") {
+ matrixCalculators.push_back(new SharedSobsCS());
+ }else if (pDataArray->Estimators[i] == "sharedchao") {
+ matrixCalculators.push_back(new SharedChao1());
+ }else if (pDataArray->Estimators[i] == "sharedace") {
+ matrixCalculators.push_back(new SharedAce());
+ }else if (pDataArray->Estimators[i] == "jabund") {
+ matrixCalculators.push_back(new JAbund());
+ }else if (pDataArray->Estimators[i] == "sorabund") {
+ matrixCalculators.push_back(new SorAbund());
+ }else if (pDataArray->Estimators[i] == "jclass") {
+ matrixCalculators.push_back(new Jclass());
+ }else if (pDataArray->Estimators[i] == "sorclass") {
+ matrixCalculators.push_back(new SorClass());
+ }else if (pDataArray->Estimators[i] == "jest") {
+ matrixCalculators.push_back(new Jest());
+ }else if (pDataArray->Estimators[i] == "sorest") {
+ matrixCalculators.push_back(new SorEst());
+ }else if (pDataArray->Estimators[i] == "thetayc") {
+ matrixCalculators.push_back(new ThetaYC());
+ }else if (pDataArray->Estimators[i] == "thetan") {
+ matrixCalculators.push_back(new ThetaN());
+ }else if (pDataArray->Estimators[i] == "kstest") {
+ matrixCalculators.push_back(new KSTest());
+ }else if (pDataArray->Estimators[i] == "sharednseqs") {
+ matrixCalculators.push_back(new SharedNSeqs());
+ }else if (pDataArray->Estimators[i] == "ochiai") {
+ matrixCalculators.push_back(new Ochiai());
+ }else if (pDataArray->Estimators[i] == "anderberg") {
+ matrixCalculators.push_back(new Anderberg());
+ }else if (pDataArray->Estimators[i] == "kulczynski") {
+ matrixCalculators.push_back(new Kulczynski());
+ }else if (pDataArray->Estimators[i] == "kulczynskicody") {
+ matrixCalculators.push_back(new KulczynskiCody());
+ }else if (pDataArray->Estimators[i] == "lennon") {
+ matrixCalculators.push_back(new Lennon());
+ }else if (pDataArray->Estimators[i] == "morisitahorn") {
+ matrixCalculators.push_back(new MorHorn());
+ }else if (pDataArray->Estimators[i] == "braycurtis") {
+ matrixCalculators.push_back(new BrayCurtis());
+ }else if (pDataArray->Estimators[i] == "whittaker") {
+ matrixCalculators.push_back(new Whittaker());
+ }else if (pDataArray->Estimators[i] == "odum") {
+ matrixCalculators.push_back(new Odum());
+ }else if (pDataArray->Estimators[i] == "canberra") {
+ matrixCalculators.push_back(new Canberra());
+ }else if (pDataArray->Estimators[i] == "structeuclidean") {
+ matrixCalculators.push_back(new StructEuclidean());
+ }else if (pDataArray->Estimators[i] == "structchord") {
+ matrixCalculators.push_back(new StructChord());
+ }else if (pDataArray->Estimators[i] == "hellinger") {
+ matrixCalculators.push_back(new Hellinger());
+ }else if (pDataArray->Estimators[i] == "manhattan") {
+ matrixCalculators.push_back(new Manhattan());
+ }else if (pDataArray->Estimators[i] == "structpearson") {
+ matrixCalculators.push_back(new StructPearson());
+ }else if (pDataArray->Estimators[i] == "soergel") {
+ matrixCalculators.push_back(new Soergel());
+ }else if (pDataArray->Estimators[i] == "spearman") {
+ matrixCalculators.push_back(new Spearman());
+ }else if (pDataArray->Estimators[i] == "structkulczynski") {
+ matrixCalculators.push_back(new StructKulczynski());
+ }else if (pDataArray->Estimators[i] == "speciesprofile") {
+ matrixCalculators.push_back(new SpeciesProfile());
+ }else if (pDataArray->Estimators[i] == "hamming") {
+ matrixCalculators.push_back(new Hamming());
+ }else if (pDataArray->Estimators[i] == "structchi2") {
+ matrixCalculators.push_back(new StructChi2());
+ }else if (pDataArray->Estimators[i] == "gower") {
+ matrixCalculators.push_back(new Gower());
+ }else if (pDataArray->Estimators[i] == "memchi2") {
+ matrixCalculators.push_back(new MemChi2());
+ }else if (pDataArray->Estimators[i] == "memchord") {
+ matrixCalculators.push_back(new MemChord());
+ }else if (pDataArray->Estimators[i] == "memeuclidean") {
+ matrixCalculators.push_back(new MemEuclidean());
+ }else if (pDataArray->Estimators[i] == "mempearson") {
+ matrixCalculators.push_back(new MemPearson());
+ }
+ }
+ }
+
+ pDataArray->calcDists.resize(matrixCalculators.size());
+
+ vector<SharedRAbundVector*> subset;
+ for (int k = pDataArray->start; k < pDataArray->end; k++) { // pass cdd each set of groups to compare
+ pDataArray->count++;
+ for (int l = 0; l < k; l++) {
+
+ if (k != l) { //we dont need to similiarity of a groups to itself
+ subset.clear(); //clear out old pair of sharedrabunds
+ //add new pair of sharedrabunds
+ subset.push_back(pDataArray->thisLookup[k]); subset.push_back(pDataArray->thisLookup[l]);
+
+ for(int i=0;i<matrixCalculators.size();i++) {
+
+ //if this calc needs all groups to calculate the pair load all groups
+ if (matrixCalculators[i]->getNeedsAll()) {
+ //load subset with rest of lookup for those calcs that need everyone to calc for a pair
+ for (int w = 0; w < pDataArray->thisLookup.size(); w++) {
+ if ((w != k) && (w != l)) { subset.push_back(pDataArray->thisLookup[w]); }
+ }
+ }
+
+ vector<double> tempdata = matrixCalculators[i]->getValues(subset); //saves the calculator outputs
+
+ if (pDataArray->m->control_pressed) { return 1; }
+
+ seqDist temp(l, k, tempdata[0]);
+ pDataArray->calcDists[i].push_back(temp);
+ }
+ }
+ }
+ }
+
+ for(int i=0;i<matrixCalculators.size();i++){ delete matrixCalculators[i]; }
+
+ return 0;
+
+ }
+ catch(exception& e) {
+ pDataArray->m->errorOut(e, "MatrixOutputCommand", "MyDistSharedThreadFunction");
+ exit(1);
+ }
+}
+#endif
#endif
projects / mothur.git / blobdiff