tmap = globaldata->gTreemap;
weightedFile = globaldata->getTreeFile() + ".weighted";
openOutputFile(weightedFile, out);
+ //column headers
+ out << "Group" << '\t' << "Score" << '\t' << "UserFreq" << '\t' << "UserCumul" << '\t' << "RandFreq" << '\t' << "RandCumul" << endl;
+
sumFile = globaldata->getTreeFile() + ".wsummary";
openOutputFile(sumFile, outSum);
//get weighted for users tree
userData.resize(numComp,0); //data[0] = weightedscore AB, data[1] = weightedscore AC...
randomData.resize(numComp,0); //data[0] = weightedscore AB, data[1] = weightedscore AC...
- uscoreFreq.resize(numComp);
- validScores.resize(numComp);
- totalrscoreFreq.resize(numComp);
- uCumul.resize(numComp);
-
+
//create new tree with same num nodes and leaves as users
randT = new Tree();
//get pscores for users trees
for (int i = 0; i < T.size(); i++) {
- rscoreFreq.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
- rCumul.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
-
+ rScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
+ uScores.resize(numComp); //data[0] = weightedscore AB, data[1] = weightedscore AC...
+ validScores.resize(numComp);
+
cout << "Processing tree " << i+1 << endl;
userData = weighted->getValues(T[i]); //userData[0] = weightedscore
//save users score
for (int s=0; s<numComp; s++) {
- //update uscoreFreq
- it = uscoreFreq[s].find(userData[s]);
- if (it == uscoreFreq[s].end()) {//new score
- uscoreFreq[s][userData[s]] = 1;
- }else{ uscoreFreq[s][userData[s]]++; }
+ //add users score to vector of user scores
+ uScores[s].push_back(userData[s]);
- //add user score to valid scores
- validScores[s][userData[s]] = userData[s];
+ //add users score to vector of valid scores
+ validScores[s].push_back(userData[s]);
//save users tree score for summary file
utreeScores.push_back(userData[s]);
}
- //copy T[i]'s info.
- randT->getCopy(T[i]);
-
//get scores for random trees
for (int j = 0; j < iters; j++) {
- //create a random tree with same topology as T[i], but different labels
- randT->assembleRandomUnifracTree();
- //get pscore of random tree
- randomData = weighted->getValues(randT);
-
- //save ramdoms score
- for (int p=0; p<numComp; p++) {
- //add trees weighted score random score freq
- it2 = rscoreFreq[p].find(randomData[p]);
- if (it2 != rscoreFreq[p].end()) {//already have that score
- rscoreFreq[p][randomData[p]]++;
- }else{//first time we have seen this score
- rscoreFreq[p][randomData[p]] = 1;
+ int n = 1;
+ int count = 0;
+ for (int r=0; r<numGroups; r++) {
+ for (int l = n; l < numGroups; l++) {
+ //copy T[i]'s info.
+ randT->getCopy(T[i]);
+
+ if (globaldata->Groups.size() != 0) {
+ //create a random tree with same topology as T[i], but different labels
+ randT->assembleRandomUnifracTree(globaldata->Groups[r], globaldata->Groups[l]);
+ //get wscore of random tree
+ randomData = weighted->getValues(randT, globaldata->Groups[r], globaldata->Groups[l]);
+ }else {
+ //create a random tree with same topology as T[i], but different labels
+ randT->assembleRandomUnifracTree(tmap->namesOfGroups[r], tmap->namesOfGroups[l]);
+ //get wscore of random tree
+ randomData = weighted->getValues(randT, tmap->namesOfGroups[r], tmap->namesOfGroups[l]);
+ }
+
+ //save scores
+ rScores[count].push_back(randomData[0]);
+ validScores[count][randomData[0]] = randomData[0];
+ count++;
}
-
- //add random score to valid scores
- validScores[p][randomData[p]] = randomData[p];
+ n++;
}
}
-
- saveRandomScores(); //save all random scores for weighted file
+
+ removeValidScoresDuplicates();
//find the signifigance of the score for summary file
- for (int t = 0; t < numComp; t++) {
- float rcumul = 1.0000;
- for (it = validScores[t].begin(); it != validScores[t].end(); it++) {
- //make rscoreFreq map and rCumul
- it2 = rscoreFreq[t].find(it->first);
- rCumul[t][it->first] = rcumul;
- //get percentage of random trees with that info
- if (it2 != rscoreFreq[t].end()) { rscoreFreq[t][it->first] /= iters; rcumul-= it2->second; }
- else { rscoreFreq[t][it->first] = 0.0000; } //no random trees with that score
- }
- }
-
- //save the signifigance of the users score for printing later
for (int f = 0; f < numComp; f++) {
- WScoreSig.push_back(rCumul[f][userData[f]]);
- }
+ //sort random scores
+ sort(rScores[f].begin(), rScores[f].end());
+
+ //the index of the score higher than yours is returned
+ //so if you have 1000 random trees the index returned is 100
+ //then there are 900 trees with a score greater then you.
+ //giving you a signifigance of 0.900
+ int index = findIndex(userData[f]); if (index == -1) { cout << "error in UnifracWeightedCommand" << endl; exit(1); } //error code
+ //the signifigance is the number of trees with the users score or higher
+ WScoreSig.push_back((iters-index)/(float)iters);
+ }
- //clear random data
- rscoreFreq.clear();
- rCumul.clear();
- }
-
- rCumul.resize(numComp);
- for (int b = 0; b < numComp; b++) {
- 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[b].begin(); it != validScores[b].end(); it++) {
- it2 = uscoreFreq[b].find(it->first);
- //make uCumul map
- uCumul[b][it->first] = ucumul;
- //user data has that score
- if (it2 != uscoreFreq[b].end()) { uscoreFreq[b][it->first] /= T.size(); ucumul-= it2->second; }
- else { uscoreFreq[b][it->first] = 0.0000; } //no user trees with that score
+ out << "Tree# " << i << endl;
+ //printWeightedFile();
- //make rscoreFreq map and rCumul
- it2 = totalrscoreFreq[b].find(it->first);
- rCumul[b][it->first] = rcumul;
- //get percentage of random trees with that info
- if (it2 != totalrscoreFreq[b].end()) { totalrscoreFreq[b][it->first] /= (iters * T.size()); rcumul-= it2->second; }
- else { totalrscoreFreq[b][it->first] = 0.0000; } //no random trees with that score
- }
+ //clear data
+ rScores.clear();
+ uScores.clear();
+ validScores.clear();
}
- printWeightedFile();
printWSummaryFile();
//clear out users groups
exit(1);
}
}
-/***********************************************************/
+/***********************************************************
void UnifracWeightedCommand::printWeightedFile() {
try {
- //column headers
-
- out << "Group" << '\t' << "Score" << '\t' << "UserFreq" << '\t' << "UserCumul" << '\t' << "RandFreq" << '\t' << "RandCumul" << endl;
-
+
//format output
out.setf(ios::fixed, ios::floatfield); out.setf(ios::showpoint);
//for each group
for (int e = 0; e < numComp; e++) {
//print each line in that group
- for (it = validScores[e].begin(); it != validScores[e].end(); it++) {
- out << setprecision(6) << groupComb[e] << '\t' << it->first << '\t' << '\t' << uscoreFreq[e][it->first] << '\t' << uCumul[e][it->first] << '\t' << totalrscoreFreq[e][it->first] << '\t' << rCumul[e][it->first] << endl;
+ for (i = 0; i < validScores[e].size(); i++) {
+ out << setprecision(6) << groupComb[e] << '\t' << validScores[e][i] << '\t' << '\t' << uscoreFreq[e][it->first] << '\t' << uCumul[e][it->first] << '\t' << rscoreFreq[e][it->first] << '\t' << rCumul[e][it->first] << endl;
}
}
}
/***********************************************************/
-void UnifracWeightedCommand::saveRandomScores() {
+void UnifracWeightedCommand::removeValidScoresDuplicates() {
try {
for (int e = 0; e < numComp; e++) {
- //update total map with new random scores
- for (it = rscoreFreq[e].begin(); it != rscoreFreq[e].end(); it++) {
- //does this score already exist in the total map
- it2 = totalrscoreFreq[e].find(it->first);
- //if yes then add them
- if (it2 != totalrscoreFreq[e].end()) {
- totalrscoreFreq[e][it->first] += rscoreFreq[e][it->first];
- }else{ //its a new score
- totalrscoreFreq[e][it->first] = rscoreFreq[e][it->first];
- }
+ //sort valid scores
+ sort(validScores[e].begin(), validScores[e].end());
+
+ for (int i = 0; i< validScores[e].size()-1; i++) {
+ if (validScores[e][i] == validScores[e][i+1]) { validScores[e].erase(validScores[e].begin()+i); }
+ }
+ }
+ }
+ catch(exception& e) {
+ cout << "Standard Error: " << e.what() << " has occurred in the UnifracWeightedCommand class Function removeValidScoresDuplicates. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
+ exit(1);
+ }
+ catch(...) {
+ cout << "An unknown error has occurred in the UnifracWeightedCommand class function removeValidScoresDuplicates. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
+ exit(1);
+ }
+}
+
+/***********************************************************/
+int UnifracWeightedCommand::findIndex(float score) {
+ try{
+ for (int e = 0; e < numComp; e++) {
+ for (int i = 0; i < rScores[e].size(); i++) {
+//cout << rScores[e][i] << " number " << i << endl;
+ if (rScores[e][i] >= score) { return i; }
}
}
+ return -1;
}
catch(exception& e) {
- cout << "Standard Error: " << e.what() << " has occurred in the UnifracWeightedCommand class Function saveRandomScores. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
+ cout << "Standard Error: " << e.what() << " has occurred in the UnifracWeightedCommand class Function findIndex. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
exit(1);
}
catch(...) {
- cout << "An unknown error has occurred in the UnifracWeightedCommand class function saveRandomScores. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
+ cout << "An unknown error has occurred in the UnifracWeightedCommand class function findIndex. Please contact Pat Schloss at pschloss@microbio.umass.edu." << "\n";
exit(1);
}
}
projects / mothur.git / blobdiff