cooccurrencecommand.cpp

   1 /*
   2  *  cooccurrencecommand.cpp
   3  *  Mothur
   4  *
   5  *  Created by kiverson on 1/2/12.
   6  *  Copyright 2012 Schloss Lab. All rights reserved.
   7  *
   8  */
   9
  10 #include "cooccurrencecommand.h"
  11
  12 //**********************************************************************************************************************
  13 vector<string> CooccurrenceCommand::setParameters() {
  14         try {
  15                 CommandParameter pshared("shared", "InputTypes", "", "", "none", "none", "none","summary",false,true,true); parameters.push_back(pshared);
  16                 CommandParameter pmetric("metric", "Multiple", "cscore-checker-combo-vratio", "cscore", "", "", "","",false,false); parameters.push_back(pmetric);
  17                 CommandParameter pmatrix("matrixmodel", "Multiple", "sim1-sim2-sim3-sim4-sim5-sim6-sim7-sim8-sim9", "sim2", "", "", "","",false,false); parameters.push_back(pmatrix);
  18         CommandParameter pruns("iters", "Number", "", "1000", "", "", "","",false,false); parameters.push_back(pruns);
  19                 CommandParameter pinputdir("inputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(pinputdir);
  20                 CommandParameter poutputdir("outputdir", "String", "", "", "", "", "","",false,false); parameters.push_back(poutputdir);
  21                 CommandParameter plabel("label", "String", "", "", "", "", "","",false,false); parameters.push_back(plabel);
  22         CommandParameter pgroups("groups", "String", "", "", "", "", "","",false,false); parameters.push_back(pgroups);
  23
  24                 vector<string> myArray;
  25                 for (int i = 0; i < parameters.size(); i++) {   myArray.push_back(parameters[i].name);          }
  26                 return myArray;
  27         }
  28         catch(exception& e) {
  29                 m->errorOut(e, "CooccurrenceCommand", "setParameters");
  30                 exit(1);
  31         }
  32 }
  33 //**********************************************************************************************************************
  34 string CooccurrenceCommand::getHelpString(){
  35         try {
  36                 string helpString = "The cooccurrence command calculates four metrics and tests their significance to assess whether presence-absence patterns are different than what one would expect by chance.";
  37         helpString += "The cooccurrence command parameters are shared, metric, matrixmodel, iters, label and groups.";
  38         helpString += "The matrixmodel parameter options are sim1, sim2, sim3, sim4, sim5, sim6, sim7, sim8 and sim9. Default=sim2";
  39         helpString += "The metric parameter options are cscore, checker, combo and vratio. Default=cscore";
  40         helpString += "The label parameter is used to analyze specific labels in your input.\n";
  41                 helpString += "The groups parameter allows you to specify which of the groups you would like analyzed.\n";
  42         helpString += "The cooccurrence command should be in the following format: \n";
  43                 helpString += "cooccurrence(shared=yourSharedFile) \n";
  44                 helpString += "Example cooccurrence(shared=final.an.shared).\n";
  45                 helpString += "Note: No spaces between parameter labels (i.e. shared), '=' and parameters (i.e.yourShared).\n";
  46                 return helpString;
  47         }
  48         catch(exception& e) {
  49                 m->errorOut(e, "CooccurrenceCommand", "getHelpString");
  50                 exit(1);
  51         }
  52 }
  53 //**********************************************************************************************************************
  54 string CooccurrenceCommand::getOutputPattern(string type) {
  55     try {
  56         string pattern = "";
  57
  58         if (type == "summary") {  pattern = "[filename],cooccurence.summary"; }
  59         else { m->mothurOut("[ERROR]: No definition for type " + type + " output pattern.\n"); m->control_pressed = true;  }
  60
  61         return pattern;
  62     }
  63     catch(exception& e) {
  64         m->errorOut(e, "CooccurrenceCommand", "getOutputPattern");
  65         exit(1);
  66     }
  67 }
  68 //**********************************************************************************************************************
  69 CooccurrenceCommand::CooccurrenceCommand(){
  70         try {
  71                 abort = true; calledHelp = true;
  72                 setParameters();
  73         vector<string> tempOutNames;
  74                 outputTypes["summary"] = tempOutNames;
  75
  76         }
  77         catch(exception& e) {
  78                 m->errorOut(e, "CooccurrenceCommand", "CooccurrenceCommand");
  79                 exit(1);
  80         }
  81 }
  82 //**********************************************************************************************************************
  83 CooccurrenceCommand::CooccurrenceCommand(string option) {
  84         try {
  85                 abort = false; calledHelp = false;
  86                 allLines = 1;
  87
  88                 //allow user to run help
  89                 if(option == "help") { help(); abort = true; calledHelp = true; }
  90                 else if(option == "citation") { citation(); abort = true; calledHelp = true;}
  91
  92                 else {
  93                         vector<string> myArray = setParameters();
  94
  95                         OptionParser parser(option);
  96                         map<string,string> parameters = parser.getParameters();
  97                         map<string,string>::iterator it;
  98
  99                         ValidParameters validParameter;
 100
 101                         //check to make sure all parameters are valid for command
 102                         for (it = parameters.begin(); it != parameters.end(); it++) {
 103                                 if (validParameter.isValidParameter(it->first, myArray, it->second) != true) {  abort = true;  }
 104                         }
 105
 106
 107                         //if the user changes the input directory command factory will send this info to us in the output parameter
 108                         string inputDir = validParameter.validFile(parameters, "inputdir", false);
 109                         if (inputDir == "not found"){   inputDir = "";          }
 110                         else {
 111                                 string path;
 112                                 it = parameters.find("shared");
 113                                 //user has given a template file
 114                                 if(it != parameters.end()){
 115                                         path = m->hasPath(it->second);
 116                                         //if the user has not given a path then, add inputdir. else leave path alone.
 117                                         if (path == "") {       parameters["shared"] = inputDir + it->second;           }
 118                                 }
 119                         }
 120
 121             vector<string> tempOutNames;
 122             outputTypes["summary"] = tempOutNames;
 123
 124                 //check for optional parameter and set defaults
 125                         // ...at some point should added some additional type checking...
 126                         label = validParameter.validFile(parameters, "label", false);
 127                         if (label == "not found") { label = ""; }
 128                         else {
 129                                 if(label != "all") {  m->splitAtDash(label, labels);  allLines = 0;  }
 130                                 else { allLines = 1;  }
 131                         }
 132
 133                         //get shared file
 134                         sharedfile = validParameter.validFile(parameters, "shared", true);
 135                         if (sharedfile == "not open") { sharedfile = ""; abort = true; }
 136                         else if (sharedfile == "not found") {
 137                                 //if there is a current shared file, use it
 138                                 sharedfile = m->getSharedFile();
 139                                 if (sharedfile != "") { m->mothurOut("Using " + sharedfile + " as input file for the shared parameter."); m->mothurOutEndLine(); }
 140                                 else {  m->mothurOut("You have no current sharedfile and the shared parameter is required."); m->mothurOutEndLine(); abort = true; }
 141                         }else { m->setSharedFile(sharedfile); }
 142
 143
 144                         //if the user changes the output directory command factory will send this info to us in the output parameter
 145                         outputDir = validParameter.validFile(parameters, "outputdir", false);           if (outputDir == "not found"){  outputDir = m->hasPath(sharedfile);             }
 146
 147
 148                         metric = validParameter.validFile(parameters, "metric", false);                         if (metric == "not found") { metric = "cscore"; }
 149
 150                         if ((metric != "cscore") && (metric != "checker") && (metric != "combo") && (metric != "vratio")) {
 151                                 m->mothurOut("[ERROR]: " + metric + " is not a valid metric option for the cooccurrence command. Choices are cscore, checker, combo, vratio."); m->mothurOutEndLine(); abort = true;
 152                         }
 153
 154                         matrix = validParameter.validFile(parameters, "matrixmodel", false);                            if (matrix == "not found") { matrix = "sim2"; }
 155
 156                         if ((matrix != "sim1") && (matrix != "sim2") && (matrix != "sim3") && (matrix != "sim4") && (matrix != "sim5" ) && (matrix != "sim6" ) && (matrix != "sim7" ) && (matrix != "sim8" ) && (matrix != "sim9" )) {
 157                                 m->mothurOut("[ERROR]: " + matrix + " is not a valid matrix option for the cooccurrence command. Choices are sim1, sim2, sim3, sim4, sim5, sim6, sim7, sim8, sim9."); m->mothurOutEndLine(); abort = true;
 158                         }
 159
 160             groups = validParameter.validFile(parameters, "groups", false);
 161                         if (groups == "not found") { groups = "";   }
 162                         else {
 163                                 m->splitAtDash(groups, Groups);
 164                         }
 165                         m->setGroups(Groups);
 166
 167             string temp = validParameter.validFile(parameters, "iters", false);                 if (temp == "not found") { temp = "1000"; }
 168                         m->mothurConvert(temp, runs);
 169
 170                 }
 171
 172         }
 173         catch(exception& e) {
 174                 m->errorOut(e, "CooccurrenceCommand", "CooccurrenceCommand");
 175                 exit(1);
 176         }
 177 }
 178 //**********************************************************************************************************************
 179
 180 int CooccurrenceCommand::execute(){
 181         try {
 182
 183                 if (abort == true) { if (calledHelp) { return 0; }  return 2;   }
 184
 185                 InputData* input = new InputData(sharedfile, "sharedfile");
 186                 vector<SharedRAbundVector*> lookup = input->getSharedRAbundVectors();
 187                 string lastLabel = lookup[0]->getLabel();
 188
 189                 //if the users enters label "0.06" and there is no "0.06" in their file use the next lowest label.
 190                 set<string> processedLabels;
 191                 set<string> userLabels = labels;
 192
 193         ofstream out;
 194         map<string, string> variables;
 195         variables["[filename]"] = outputDir + m->getRootName(m->getSimpleName(sharedfile));
 196                 string outputFileName = getOutputFileName("summary", variables);
 197         m->openOutputFile(outputFileName, out);
 198         outputNames.push_back(outputFileName);  outputTypes["summary"].push_back(outputFileName);
 199         out.setf(ios::fixed, ios::floatfield); out.setf(ios::showpoint);
 200         out << "metric\tlabel\tScore\tzScore\tstandardDeviation\tnp_Pvalue\n";
 201
 202                 //as long as you are not at the end of the file or done wih the lines you want
 203                 while((lookup[0] != NULL) && ((allLines == 1) || (userLabels.size() != 0))) {
 204
 205                         if (m->control_pressed) { for (int i = 0; i < lookup.size(); i++) {  delete lookup[i];  } delete input; out.close(); m->mothurRemove(outputFileName); return 0; }
 206
 207                         if(allLines == 1 || labels.count(lookup[0]->getLabel()) == 1){
 208
 209                                 m->mothurOut(lookup[0]->getLabel()); m->mothurOutEndLine();
 210
 211                                 getCooccurrence(lookup, out);
 212
 213                                 processedLabels.insert(lookup[0]->getLabel());
 214                                 userLabels.erase(lookup[0]->getLabel());
 215                         }
 216
 217                         if ((m->anyLabelsToProcess(lookup[0]->getLabel(), userLabels, "") == true) && (processedLabels.count(lastLabel) != 1)) {
 218                                 string saveLabel = lookup[0]->getLabel();
 219
 220                                 for (int i = 0; i < lookup.size(); i++) {  delete lookup[i];  }
 221                                 lookup = input->getSharedRAbundVectors(lastLabel);
 222                                 m->mothurOut(lookup[0]->getLabel()); m->mothurOutEndLine();
 223                                 getCooccurrence(lookup, out);
 224
 225                                 processedLabels.insert(lookup[0]->getLabel());
 226                                 userLabels.erase(lookup[0]->getLabel());
 227
 228                                 //restore real lastlabel to save below
 229                                 lookup[0]->setLabel(saveLabel);
 230                         }
 231
 232                         lastLabel = lookup[0]->getLabel();
 233                         //prevent memory leak
 234                         for (int i = 0; i < lookup.size(); i++) {  delete lookup[i]; lookup[i] = NULL; }
 235
 236                         if (m->control_pressed) {  outputTypes.clear(); delete input; out.close(); m->mothurRemove(outputFileName); return 0; }
 237
 238                         //get next line to process
 239                         lookup = input->getSharedRAbundVectors();
 240                 }
 241
 242                 if (m->control_pressed) { delete input; out.close(); m->mothurRemove(outputFileName); return 0; }
 243
 244                 //output error messages about any remaining user labels
 245                 set<string>::iterator it;
 246                 bool needToRun = false;
 247                 for (it = userLabels.begin(); it != userLabels.end(); it++) {
 248                         m->mothurOut("Your file does not include the label " + *it);
 249                         if (processedLabels.count(lastLabel) != 1) {
 250                                 m->mothurOut(". I will use " + lastLabel + "."); m->mothurOutEndLine();
 251                                 needToRun = true;
 252                         }else {
 253                                 m->mothurOut(". Please refer to " + lastLabel + "."); m->mothurOutEndLine();
 254                         }
 255                 }
 256
 257                 //run last label if you need to
 258                 if (needToRun == true)  {
 259                         for (int i = 0; i < lookup.size(); i++) { if (lookup[i] != NULL) { delete lookup[i]; } }
 260                         lookup = input->getSharedRAbundVectors(lastLabel);
 261
 262                         m->mothurOut(lookup[0]->getLabel()); m->mothurOutEndLine();
 263
 264                         getCooccurrence(lookup, out);
 265
 266                         for (int i = 0; i < lookup.size(); i++) {  delete lookup[i];  }
 267                 }
 268
 269         out.close();
 270
 271                 //reset groups parameter
 272                 delete input;
 273         m->clearGroups();
 274
 275         m->mothurOutEndLine();
 276                 m->mothurOut("Output File Names: "); m->mothurOutEndLine();
 277                 m->mothurOut(outputFileName); m->mothurOutEndLine();
 278                 m->mothurOutEndLine();
 279
 280                 return 0;
 281         }
 282         catch(exception& e) {
 283                 m->errorOut(e, "CooccurrenceCommand", "execute");
 284                 exit(1);
 285         }
 286 }
 287 //**********************************************************************************************************************
 288
 289 int CooccurrenceCommand::getCooccurrence(vector<SharedRAbundVector*>& thisLookUp, ofstream& out){
 290     try {
 291         int numOTUS = thisLookUp[0]->getNumBins();
 292
 293         if(numOTUS < 2) {
 294             m->mothurOut("Not enough OTUs for co-occurrence analysis, skipping"); m->mothurOutEndLine();
 295             return 0;
 296         }
 297
 298         vector< vector<int> > co_matrix; co_matrix.resize(thisLookUp[0]->getNumBins());
 299         for (int i = 0; i < thisLookUp[0]->getNumBins(); i++) { co_matrix[i].resize((thisLookUp.size()), 0); }
 300         vector<int> columntotal; columntotal.resize(thisLookUp.size(), 0);
 301         vector<int> rowtotal; rowtotal.resize(numOTUS, 0);
 302
 303         for (int i = 0; i < thisLookUp.size(); i++) { //nrows in the shared file
 304             for (int j = 0; j < thisLookUp[i]->getNumBins(); j++) { //cols of original shared file
 305                 if (m->control_pressed) { return 0; }
 306                 int abund = thisLookUp[i]->getAbundance(j);
 307
 308                 if(abund > 0) {
 309                     co_matrix[j][i] = 1;
 310                     rowtotal[j]++;
 311                     columntotal[i]++;
 312                 }
 313             }
 314         }
 315
 316         //nrows is ncols of inital matrix. All the functions need this value. They assume the transposition has already taken place and nrows and ncols refer to that matrix.
 317         //comatrix and initmatrix are still vectors of vectors of ints as in the original script. The abundancevector is only what was read in ie not a co-occurrence matrix!
 318         int nrows = numOTUS;//rows of inital matrix
 319         int ncols = thisLookUp.size();//groups
 320         double initscore = 0.0;
 321
 322         vector<double> stats;
 323         vector<double> probabilityMatrix; probabilityMatrix.resize(ncols * nrows, 0);
 324         vector<vector<int> > nullmatrix(nrows, vector<int>(ncols, 0));
 325
 326         TrialSwap2 trial;
 327
 328         int n = accumulate( columntotal.begin(), columntotal.end(), 0 );
 329
 330         //============================================================
 331
 332         //generate a probability matrix. Only do this once.
 333         float start = 0.0;
 334
 335         if (matrix == "sim1") {
 336             for(int i=0;i<nrows;i++) {
 337                 for(int j=0;j<ncols;j++) {
 338                     probabilityMatrix[ncols * i + j] = start + 1/double(nrows*ncols);
 339                     start = start + 1/double(nrows*ncols);
 340                 }
 341             }
 342         }
 343         //don't need a prob matrix because we just shuffle the rows, may use this in the future
 344         else if (matrix == "sim2") { }
 345 //            for(int i=0;i<nrows;i++) {
 346 //                start = 0.0;
 347 //                for(int j=0;j<ncols;j++) {
 348 //                    probabilityMatrix[ncols * i + j] = start + 1/double(ncols);
 349 //                    start = start + 1/double(ncols);
 350 //                }
 351 //            }
 352 //        }
 353
 354         else if (matrix == "sim3") {
 355             for(int j=0;j<ncols;j++) {
 356                 start = 0.0;
 357                 for(int i=0;i<nrows;i++) {
 358                     probabilityMatrix[ncols * i + j] = start + 1/double(nrows);
 359                     start = start + 1/double(nrows);
 360                 }
 361             }
 362         }
 363
 364         else if (matrix == "sim4") {
 365             for(int i=0;i<nrows;i++) {
 366                 start = 0.0;
 367                 for(int j=0;j<ncols;j++) {
 368                     probabilityMatrix[ncols * i + j] = start + columntotal[j]/double(n);
 369                     start = start + columntotal[j]/double(n);
 370                 }
 371             }
 372         }
 373
 374         else if (matrix == "sim5") {
 375             for(int j=0;j<ncols;j++) {
 376                 start = 0.0;
 377                 for(int i=0;i<nrows;i++) {
 378                     probabilityMatrix[ncols * i + j] = start + rowtotal[i]/double(n);
 379                     start = start + rowtotal[i]/double(n);
 380                 }
 381             }
 382         }
 383
 384         else if (matrix == "sim6") {
 385             for(int i=0;i<nrows;i++) {
 386                 for(int j=0;j<ncols;j++) {
 387                     probabilityMatrix[ncols * i + j] = start + columntotal[j]/double(n*nrows);
 388                     start = start + columntotal[j]/double(n*nrows);
 389                 }
 390             }
 391         }
 392
 393
 394         else if (matrix == "sim7") {
 395             for(int i=0;i<nrows;i++) {
 396                 for(int j=0;j<ncols;j++) {
 397                     probabilityMatrix[ncols * i + j] = start + rowtotal[i]/double(n*ncols);
 398                     start = start + rowtotal[i]/double(n*ncols);
 399                 }
 400             }
 401         }
 402
 403         else if (matrix == "sim8") {
 404             for(int i=0;i<nrows;i++) {
 405                 for(int j=0;j<ncols;j++) {
 406                     probabilityMatrix[ncols * i + j] = start + (rowtotal[i]*columntotal[j])/double(n*n);
 407                     start = start + (rowtotal[i]*columntotal[j])/double(n*n);
 408                 }
 409             }
 410         }
 411         else if (matrix == "sim9" || matrix == "sim2") { }
 412         else {
 413             m->mothurOut("[ERROR]: No model selected! \n");
 414             m->control_pressed = true;
 415         }
 416
 417
 418         //co_matrix is the transposed shared file, initmatrix is the original shared file
 419         if (metric == "cscore") { initscore = trial.calc_c_score(co_matrix, rowtotal, ncols, nrows); }
 420         else if (metric == "checker") { initscore = trial.calc_checker(co_matrix, rowtotal, ncols, nrows); }
 421         else if (metric == "vratio") { initscore = trial.calc_vratio(nrows, ncols, rowtotal, columntotal); }
 422         else if (metric == "combo") { initscore = trial.calc_combo(nrows, ncols, co_matrix); }
 423         else { m->mothurOut("[ERROR]: No metric selected!\n"); m->control_pressed = true; return 1; }
 424
 425         m->mothurOut("Initial c score: " + toString(initscore)); m->mothurOutEndLine();
 426
 427         double previous;
 428         double current;
 429         double randnum;
 430         int count;
 431
 432         //burn-in for sim9
 433         if(matrix == "sim9") {
 434             for(int i=0;i<10000;i++) trial.swap_checkerboards (co_matrix, ncols, nrows);
 435         }
 436
 437         //populate null matrix from probability matrix, do this a lot.
 438         for(int k=0;k<runs;k++){
 439             nullmatrix.clear();
 440             //zero-fill the null matrix
 441             nullmatrix.assign(nrows, vector<int>(ncols, 0));
 442
 443             if(matrix == "sim1" || matrix == "sim6" || matrix == "sim8" || matrix == "sim7") {
 444                 count = 0;
 445                 while(count < n) {
 446                     if (m->control_pressed) { return 0; }
 447                 nextnum2:
 448                     previous = 0.0;
 449                     randnum = rand() / double(RAND_MAX);
 450                     for(int i=0;i<nrows;i++) {
 451                         for(int j=0;j<ncols;j++) {
 452                             current = probabilityMatrix[ncols * i + j];
 453                             if(randnum <= current && randnum > previous) {
 454                                 nullmatrix[i][j] = 1;
 455                                 count++;
 456                                 if (count > n) break;
 457                                 else
 458                                     goto nextnum2;
 459                             }
 460                             previous = current;
 461                         }
 462                     }
 463                 }
 464             }
 465
 466             else if (matrix == "sim2") {
 467                 for(int i=0;i<nrows;i++) {
 468                     random_shuffle( co_matrix[i].begin(), co_matrix[i].end() );
 469                 }
 470                 //do this for the scoring since those all have nullmatrix as a parameter
 471                 //nullmatrix gets cleared at the begining of each run
 472                 nullmatrix = co_matrix;
 473             }
 474
 475             else if(matrix == "sim4") {
 476                 for(int i=0;i<nrows;i++) {
 477                     count = 0;
 478                     while(count < rowtotal[i]) {
 479                         previous = 0.0;
 480                         if (m->control_pressed) { return 0; }
 481                         randnum = rand() / double(RAND_MAX);
 482                         for(int j=0;j<ncols;j++) {
 483                             current = probabilityMatrix[ncols * i + j];
 484                             if(randnum <= current && randnum > previous && nullmatrix[i][j] != 1) {
 485                                 nullmatrix[i][j] = 1;
 486                                 count++;
 487                                 previous = 0.0;
 488                                 break;
 489                             }
 490                             previous = current;
 491                         }
 492                     }
 493                 }
 494             }
 495
 496             else if(matrix == "sim3" || matrix == "sim5") {
 497                 //columns
 498                 for(int j=0;j<ncols;j++) {
 499                     count = 0;
 500                     while(count < columntotal[j]) {
 501                         if (m->control_pressed) { return 0; }
 502                         randnum = rand() / double(RAND_MAX);
 503                         for(int i=0;i<nrows;i++) {
 504                             current = probabilityMatrix[ncols * i + j];
 505                             if(randnum <= current && randnum > previous && nullmatrix[i][j] != 1) {
 506                                 nullmatrix[i][j] = 1;
 507                                 count++;
 508                                 previous = 0.0;
 509                                 break;
 510                             }
 511                             previous = current;
 512                         }
 513                     }
 514                 }
 515             }
 516
 517             //swap_checkerboards takes the original matrix and swaps checkerboards
 518             else if(matrix == "sim9") {
 519                 trial.swap_checkerboards (co_matrix, ncols, nrows);
 520                 nullmatrix = co_matrix;
 521             }
 522             else {
 523                 m->mothurOut("[ERROR]: No null model selected!\n\n"); m->control_pressed = true;
 524                 return 1;
 525             }
 526
 527             //run metric on null matrix and add score to the stats vector
 528             if (metric == "cscore"){
 529                 stats.push_back(trial.calc_c_score(nullmatrix, rowtotal, ncols, nrows));
 530             }
 531             else if (metric == "checker") {
 532                 stats.push_back(trial.calc_checker(nullmatrix, rowtotal, ncols, nrows));
 533             }
 534             else if (metric == "vratio") {
 535                 stats.push_back(trial.calc_vratio(nrows, ncols, rowtotal, columntotal));
 536             }
 537             else if (metric == "combo") {
 538                 stats.push_back(trial.calc_combo(nrows, ncols, nullmatrix));
 539             }
 540             else {
 541                 m->mothurOut("[ERROR]: No metric selected!\n\n"); m->control_pressed = true;
 542                 return 1;
 543             }
 544
 545         }
 546
 547
 548
 549         double total = 0.0;
 550         for (int i=0; i<stats.size();i++) { total+=stats[i]; }
 551
 552         double nullMean = double (total/(double)stats.size());
 553
 554         m->mothurOutEndLine(); m->mothurOut("average metric score: " + toString(nullMean)); m->mothurOutEndLine();
 555
 556         //calc_p_value is not a statistical p-value, it's just the average that are either > or < the initscore.
 557         //All it does is show what is expected in a competitively structured community
 558         //zscore is output so p-value can be looked up in a ztable
 559         double pvalue = 0.0;
 560         if (metric == "cscore" || metric == "checker") { pvalue = trial.calc_pvalue_greaterthan (stats, initscore); }
 561         else{ pvalue = trial.calc_pvalue_lessthan (stats, initscore); }
 562
 563         double sd = trial.getSD(runs, stats, nullMean);
 564
 565         double zscore = trial.get_zscore(sd, nullMean, initscore);
 566
 567         m->mothurOut("zscore: " + toString(zscore)); m->mothurOutEndLine();
 568         m->mothurOut("standard deviation: " + toString(sd)); m->mothurOutEndLine();
 569         m->mothurOut("non-parametric p-value: " + toString(pvalue)); m->mothurOutEndLine();
 570         out << metric << '\t' << thisLookUp[0]->getLabel() << '\t' << nullMean << '\t' << zscore << '\t' << sd << '\t' << pvalue << endl;
 571
 572         return 0;
 573     }
 574     catch(exception& e) {
 575         m->errorOut(e, "CooccurrenceCommand", "Cooccurrence");
 576         exit(1);
 577     }
 578 }
 579 //**********************************************************************************************************************
 580
 581