changed unweighted and weighted score cumulatives to be that score or higher instead...

[mothur.git] / unifracunweightedcommand.cpp

diff --git a/unifracunweightedcommand.cpp b/unifracunweightedcommand.cpp
index 77069443c2fd26a0cebbabf4dd661e1d37288030..3eedb2ecd99ff2a68342c23ab617639c3c82e312 100644 (file)
--- a/unifracunweightedcommand.cpp
+++ b/unifracunweightedcommand.cpp
@@ -113,12 +113,13 @@ int UnifracUnweightedCommand::execute() {
                        saveRandomScores(); //save all random scores for unweighted file
                        
                        //find the signifigance of the score
-                       float rcumul = 0.0000;
+                       float rcumul = 1.0000;
                        for (it = rscoreFreq.begin(); it != rscoreFreq.end(); it++) { 
+                               rCumul[it->first] = rcumul;
                                //get percentage of random trees with that info
                                rscoreFreq[it->first] /= iters; 
-                               rcumul+= it->second;  
-                               rCumul[it->first] = rcumul;
+                               rcumul-= it->second;  
+                               
                        }
                        
                        //save the signifigance of the users score for printing later
@@ -130,31 +131,29 @@ int UnifracUnweightedCommand::execute() {
                        rCumul.clear();
                }
                
-               float ucumul = 0.0000;
-               float rcumul = 0.0000;
+               float ucumul = 1.0000;
+               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 (it = validScores.begin(); it != validScores.end(); it++) { 
                        it2 = uscoreFreq.find(it->first);
-                       //user data has that score 
-                       if (it2 != uscoreFreq.end()) { uscoreFreq[it->first] /= T.size(); ucumul+= it2->second;  }
-                       else { uscoreFreq[it->first] = 0.0000; } //no user trees with that score
                        //make uCumul map
                        uCumul[it->first] = ucumul;
-                       
+                       //user data has that score 
+                       if (it2 != uscoreFreq.end()) { uscoreFreq[it->first] /= T.size(); ucumul-= it2->second;  }
+                       else { uscoreFreq[it->first] = 0.0000; } //no user trees with that score
+                                               
                        //make rscoreFreq map and rCumul
                        it2 = totalrscoreFreq.find(it->first);
+                       rCumul[it->first] = rcumul;
                        //get percentage of random trees with that info
-                       if (it2 != totalrscoreFreq.end()) {  totalrscoreFreq[it->first] /= (iters*T.size()); rcumul+= it2->second;  }
+                       if (it2 != totalrscoreFreq.end()) {  totalrscoreFreq[it->first] /= (iters*T.size()); rcumul-= it2->second;  }
                        else { totalrscoreFreq[it->first] = 0.0000; } //no random trees with that score
-                       rCumul[it->first] = rcumul;
+                       
                }
                
                printUnweightedFile();
                printUWSummaryFile();
                
-               //reset randomTree parameter to 0
-               globaldata->setRandomTree("0");
-               
                delete randT;
                
                return 0;