void plotSteps()
{
//checkInputs(); return;
TFile fin("/mnt/sdc/andriusj/DY13TeV/DYanalysis-20160817/ElectronNtupler/test/Analysis_Codes/AccEff/dyee_preFSR_forAccEff_v1steps.root");
TH1D *h1effPass_new= loadHisto(fin,"h1_eff_sumPass","h1effPass_new",1,h1dummy);
TH1D *h1effPass_noPU= loadHisto(fin,"h1_eff_sumPass_noPU","h1effPass_noPU",1,h1dummy);
TH1D *h1effPass_noTrigObjMatching= loadHisto(fin,"h1_eff_sumPass_noTrigObjMatching","h1effPass_noTrigObjMatching",1,h1dummy);
TH1D *h1effPass_matchDR3= loadHisto(fin,"h1_eff_sumPass_matchDR3","h1effPass_matchDR3",1,h1dummy);
TH1D *h1effPass_noTrig= loadHisto(fin,"h1_eff_sumPass_noTrig","h1effPass_noTrig",1,h1dummy);
TH1D *h1effPass_noTrigNoPU= loadHisto(fin,"h1_eff_sumPass_noTrigNoPU","h1effPass_noTrigNoPU",1,h1dummy);
//TH1D *h1effTot_new= loadHisto(fin, "h1_eff_sumTot", "h1effTot_new",1,h1dummy);
fin.Close();
if (!h1effPass_new || !h1effPass_noPU || !h1effPass_noTrigObjMatching ||
!h1effPass_matchDR3 || !h1effPass_noTrig || !h1effPass_noTrigNoPU) {
std::cout << "null ptr\n";
return;
}
std::vector<TH1D*> h1InfoV;
std::vector<TString> infoLabelV;
histoStyle(h1effPass_noPU,kRed,5,1);
histoStyle(h1effPass_noTrig,kBlue,7,2);
histoStyle(h1effPass_matchDR3,kGreen+1,5,1);
histoStyle(h1effPass_noTrigObjMatching,kOrange,20,2);
std::cout << "\nwPU effect on new effPass distribution\n";
plotHisto(h1effPass_new,"cPUnew",1,0,"LPE1","new wPU");
plotHistoSame(h1effPass_noPU,"cPUnew","LPE1","new noPU");
printRatio(h1effPass_new,h1effPass_noPU);
addRatio(h1effPass_noPU,h1effPass_new,"no PU rew.",h1InfoV,infoLabelV);
std::cout << "\nwPU effect on old effPass distribution\n";
plotHisto(h1effPass_noTrig,"cPUold",1,0,"LPE1","old wPU");
plotHistoSame(h1effPass_noTrigNoPU,"cPUold","LPE1","old noPU");
printRatio(h1effPass_noTrig,h1effPass_noTrigNoPU);
std::cout << "\ntriggering\n";
plotHisto(h1effPass_new,"cTrig",1,0,"LPE1","new wPU");
plotHistoSame(h1effPass_noTrig,"cTrig","LPE1","no event trigger");
printRatio(h1effPass_new,h1effPass_noTrig);
addRatio(h1effPass_noTrig,h1effPass_new,"no trigger",h1InfoV,infoLabelV);
std::cout << "\ntrigger object matching\n";
plotHisto(h1effPass_new,"cTrigObjMatch",1,0,"LPE1","new wPU");
plotHistoSame(h1effPass_noTrigObjMatching,"cTrigObjMatch","LPE1","new, noTrigObjMatch");
printRatio(h1effPass_new,h1effPass_noTrigObjMatching);
addRatio(h1effPass_noTrigObjMatching,h1effPass_new,"no trig.obj.match.",h1InfoV,infoLabelV);
std::cout << "\nDR effect on new effPass distribution\n";
plotHisto(h1effPass_new,"cDR",1,0,"LPE1","new wPU, match DR1");
plotHistoSame(h1effPass_matchDR3,"cDR","LPE1","new wPU, match DR3");
printRatio(h1effPass_new,h1effPass_matchDR3);
addRatio(h1effPass_matchDR3,h1effPass_new,"#DeltaR<0.3",h1InfoV,infoLabelV);
//printLatex("effPassSteps.tex",h1InfoV,infoLabelV,1);
plotRatios(h1InfoV,infoLabelV);
}
void MLScale::setDefaultScale()
{
clear();
setName("12-equal");
setDescription("The chromatic equal-tempered scale.");
// make 12-ET scale
for(int i=1; i<=12; ++i)
{
addRatio(100.0 * i);
}
}
// Return true if we successfully read a tuning file, false otherwise
boolean Tuning::read() {
scalaFile = SD.open(_filename);
char character;
boolean inComment = false;
int numEntries = 0;
ratios[0] = 1.0;
numRatios = 1;
int DESCRIPTION_STATE = 1;
int ENTRIES_STATE = 2;
int RATIO_STATE = 3;
int state = DESCRIPTION_STATE;
String currentLine = "";
String description;
while (scalaFile.available()) {
character = scalaFile.read();
// If we're in a comment just keep reading until we hit the next line
if(inComment) {
if(character == '\n') {
inComment = false;
}
continue;
}
if(character == '!') {
// Line is a comment, ignore until end
inComment = true;
if(state == RATIO_STATE && currentLine.length() > 1) {
// If a comment has started on a ratio line, we can process the ratio
if(addRatio(¤tLine)) {
break;
}
currentLine = "";
}
continue;
} else {
inComment = false;
}
if(state == DESCRIPTION_STATE) {
if(character == '\n') {
state = ENTRIES_STATE;
if(currentLine.length() == 0) {
description = "No Info";
} else {
description = currentLine;
}
#ifdef DEBUG_TUNING
Serial.println("End description");
Serial.println(description);
#endif
currentLine = "";
} else {
currentLine += character;
}
} else if(state == ENTRIES_STATE) {
if(character == '\n') {
state = RATIO_STATE;
numEntries = currentLine.toInt();
if(numEntries == 0) {
return false;
}
#ifdef DEBUG_TUNING
Serial.print("End num entries: ");
Serial.println(numEntries);
#endif
currentLine = "";
} else {
currentLine += character;
}
} else if(state == RATIO_STATE) {
if(character == '\n') {
#ifdef DEBUG_TUNING
Serial.print("Got ratio");
Serial.println(currentLine);
#endif
if(addRatio(¤tLine)) {
break;
}
currentLine = "";
} else {
currentLine += character;
}
}
}
scalaFile.close();
#ifdef DEBUG_TUNING
if(numEntries != numRatios) {
Serial.print("Entries and Ratio Count not equal. ");
Serial.print(numEntries);
Serial.print(" vs ");
Serial.println(numRatios);
}
#endif
if(numRatios > 1) {
return true;
}
return false;
}
void Job::evaluate(Brain * brain)
{
//
addRatio(brain->getRatio());
addBalance(brain->getBalance());
addError(brain->getError());
QString fileName = saveDirectory + "/" +
QString::number(brain->getBalance(),'f',2) + " | " +
QString::number(brain->getRatio(),'f',4) + " | " +
QString::number(brain->getError(),'f',2) +".brain";
//
if(evaluationMode == BALANCE)
{
mutexAverageBalance.lock();
float averageBalanceTmp = averageBalance;
mutexAverageBalance.unlock();
if(brain->getBalance() > averageBalanceTmp)
{
copyToBestBrain(brain);
}
if(brain->getBalance() > bestBalanceEver)
{
copyToBestBrainEver(brain);
bestBalanceEver = brain->getBalance();
saveBestBrain(fileName);
}
}
else if(evaluationMode == RATIO)
{
mutexAverageRatio.lock();
float averageRatioTmp = averageRatio;
mutexAverageRatio.unlock();
if(brain->getRatio() > averageRatioTmp)
{
copyToBestBrain(brain);
}
/*if(brain->getRatio() > bestRatioEver)
{
copyToBestBrainEver(brain);
bestRatioEver = brain->getRatio();
saveBestBrain(fileName);
}*/
}
else if(evaluationMode == ERROR)
{
mutexAverageError.lock();
float averageErrorTmp = averageError;
mutexAverageError.unlock();
if(brain->getError() < averageErrorTmp)
{
copyToBestBrain(brain);
}
if(brain->getError() < bestErrorEver)
{
copyToBestBrainEver(brain);
bestErrorEver = brain->getError();
saveBestBrain(fileName);
}
}
//
copyFromBestBrain(brain);
brain->mutate(mutationFrequency, mutationIntensity);
}
void MLScale::clear()
{
mRatioList.clear();
addRatio(0.0);
}
