-
- //save the signifigance of the users score for printing later
- UWScoreSig.push_back(rCumul[userData[0]]);
-
-
- //clear random data
- rscoreFreq.clear(); //you clear this because in the summary file you want the unweighted signifinance to be relative to these 1000 trees.
- rCumul.clear();
- }
-
- 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);
- //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; }
- else { totalrscoreFreq[it->first] = 0.0000; } //no random trees with that score
-