working on parallelizing unifrac.unweighted.

[mothur.git] / unifracunweightedcommand.cpp

diff --git a/unifracunweightedcommand.cpp b/unifracunweightedcommand.cpp
index 848c85c9d20f14f2ede20987026666ab2cd62181..7836eb682f19d444ae2ffb7f82fe538efdb7d933 100644 (file)
--- a/unifracunweightedcommand.cpp
+++ b/unifracunweightedcommand.cpp
@@ -21,7 +21,7 @@ UnifracUnweightedCommand::UnifracUnweightedCommand(string option)  {
                
                else {
                        //valid paramters for this command
-                       string Array[] =  {"groups","iters","distance","random", "outputdir","inputdir"};
+                       string Array[] =  {"groups","iters","distance","random", "processors","outputdir","inputdir"};
                        vector<string> myArray (Array, Array+(sizeof(Array)/sizeof(string)));
                        
                        OptionParser parser(option);
@@ -58,9 +58,12 @@ UnifracUnweightedCommand::UnifracUnweightedCommand(string option)  {
                        string temp = validParameter.validFile(parameters, "distance", false);                  if (temp == "not found") { temp = "false"; }
                        phylip = m->isTrue(temp);
                        
-                       temp = validParameter.validFile(parameters, "random", false);                                   if (temp == "not found") { temp = "true"; }
+                       temp = validParameter.validFile(parameters, "random", false);                                   if (temp == "not found") { temp = "f"; }
                        random = m->isTrue(temp);
                        
+                       temp = validParameter.validFile(parameters, "processors", false);       if (temp == "not found"){       temp = "1";                             }
+                       convert(temp, processors); 
+                       
                        if (!random) {  iters = 0;  } //turn off random calcs
                        
                        //if user selects distance = true and no groups it won't calc the pairwise
@@ -105,7 +108,7 @@ void UnifracUnweightedCommand::help(){
                m->mothurOut("The groups parameter allows you to specify which of the groups in your groupfile you would like analyzed.  You must enter at least 1 valid group.\n");
                m->mothurOut("The group names are separated by dashes.  The iters parameter allows you to specify how many random trees you would like compared to your tree.\n");
                m->mothurOut("The distance parameter allows you to create a distance file from the results. The default is false.\n");
-               m->mothurOut("The random parameter allows you to shut off the comparison to random trees. The default is true, meaning compare your trees with randomly generated trees.\n");
+               m->mothurOut("The random parameter allows you to shut off the comparison to random trees. The default is false, meaning compare don't your trees with randomly generated trees.\n");
                m->mothurOut("The unifrac.unweighted command should be in the following format: unifrac.unweighted(groups=yourGroups, iters=yourIters).\n");
                m->mothurOut("Example unifrac.unweighted(groups=A-B-C, iters=500).\n");
                m->mothurOut("The default value for groups is all the groups in your groupfile, and iters is 1000.\n");
@@ -125,6 +128,8 @@ int UnifracUnweightedCommand::execute() {
                
                if (abort == true) { return 0; }
                
+               int start = time(NULL);
+               
                userData.resize(numComp,0);  //data[0] = unweightedscore 
                randomData.resize(numComp,0); //data[0] = unweightedscore
                //create new tree with same num nodes and leaves as users
@@ -154,14 +159,9 @@ int UnifracUnweightedCommand::execute() {
                        utreeScores.resize(numComp);  
                        UWScoreSig.resize(numComp); 
 
-                       userData = unweighted->getValues(T[i]);  //userData[0] = unweightedscore
+                       userData = unweighted->getValues(T[i], processors, outputDir);  //userData[0] = unweightedscore
                        
-                       if (m->control_pressed) { 
-                               if (random) { delete output;  }
-                               outSum.close();
-                               for (int i = 0; i < outputNames.size(); i++) {  remove(outputNames[i].c_str());  }
-                               return 0; 
-                       }
+                       if (m->control_pressed) { if (random) { delete output;  } outSum.close();  for (int i = 0; i < outputNames.size(); i++) {       remove(outputNames[i].c_str());  }return 0; }
                        
                        //output scores for each combination
                        for(int k = 0; k < numComp; k++) {
@@ -197,21 +197,23 @@ int UnifracUnweightedCommand::execute() {
                                        validScores[randomData[k]] = randomData[k];
                                }
                        }
-               
+       
                        for(int a = 0; a < numComp; a++) {
                                float rcumul = 1.0000;
-                               //this loop fills the cumulative maps and put 0.0000 in the score freq map to make it easier to print.
-                               for (map<float,float>::iterator it = validScores.begin(); it != validScores.end(); it++) { 
-                                       //make rscoreFreq map and rCumul
-                                       map<float,float>::iterator it2 = rscoreFreq[a].find(it->first);
-                                       rCumul[a][it->first] = rcumul;
-                                       //get percentage of random trees with that info
-                                       if (it2 != rscoreFreq[a].end()) {  rscoreFreq[a][it->first] /= iters; rcumul-= it2->second;  }
-                                       else { rscoreFreq[a][it->first] = 0.0000; } //no random trees with that score
-                               }
                                
-                               if (random) {   UWScoreSig[a].push_back(rCumul[a][userData[a]]);        }
-                               else            {       UWScoreSig[a].push_back(0.0);                                           }
+                               if (random) {
+                                       //this loop fills the cumulative maps and put 0.0000 in the score freq map to make it easier to print.
+                                       for (map<float,float>::iterator it = validScores.begin(); it != validScores.end(); it++) { 
+                                               //make rscoreFreq map and rCumul
+                                               map<float,float>::iterator it2 = rscoreFreq[a].find(it->first);
+                                               rCumul[a][it->first] = rcumul;
+                                               //get percentage of random trees with that info
+                                               if (it2 != rscoreFreq[a].end()) {  rscoreFreq[a][it->first] /= iters; rcumul-= it2->second;  }
+                                               else { rscoreFreq[a][it->first] = 0.0000; } //no random trees with that score
+                                       }
+                                       UWScoreSig[a].push_back(rCumul[a][userData[a]]);
+                               }else           {       UWScoreSig[a].push_back(0.0);                                           }
+       
                        }
                        
                        
@@ -239,6 +241,8 @@ int UnifracUnweightedCommand::execute() {
                
                if (m->control_pressed) { for (int i = 0; i < outputNames.size(); i++) {        remove(outputNames[i].c_str());  }      return 0; }
                
+               m->mothurOut("It took " + toString(time(NULL) - start) + " secs to run unifrac.unweighted."); m->mothurOutEndLine();
+               
                m->mothurOutEndLine();
                m->mothurOut("Output File Names: "); m->mothurOutEndLine();
                for (int i = 0; i < outputNames.size(); i++) {  m->mothurOut(outputNames[i]); m->mothurOutEndLine();    }