bool videoFormatToGL(const VideoFormat& fmt, GLint* internal_format, GLenum* data_format, GLenum* data_type, QMatrix4x4* mat)
{
typedef struct fmt_entry {
VideoFormat::PixelFormat pixfmt;
GLint internal_format;
GLenum format;
GLenum type;
} fmt_entry;
static const fmt_entry pixfmt_to_gles[] = {
{VideoFormat::Format_BGRA32, GL_BGRA, GL_BGRA, GL_UNSIGNED_BYTE }, //tested for angle
{VideoFormat::Format_RGB32, GL_BGRA, GL_BGRA, GL_UNSIGNED_BYTE },
{VideoFormat::Format_Invalid, 0, 0, 0}
};
Q_UNUSED(pixfmt_to_gles);
static const fmt_entry pixfmt_to_desktop[] = {
{VideoFormat::Format_BGRA32, GL_RGBA, GL_BGRA, GL_UNSIGNED_BYTE }, //bgra bgra works on win but not osx
{VideoFormat::Format_RGB32, GL_RGBA, GL_BGRA, GL_UNSIGNED_BYTE }, //FIXMEL endian check
//{VideoFormat::Format_BGRA32, GL_RGBA, GL_RGBA, GL_UNSIGNED_BYTE }, //{2,1,0,3}
//{VideoFormat::Format_BGR24, GL_RGB, GL_BGR, GL_UNSIGNED_BYTE }, //{0,1,2,3}
#ifdef GL_UNSIGNED_SHORT_5_6_5_REV
{VideoFormat::Format_BGR565, GL_RGB, GL_RGB, GL_UNSIGNED_SHORT_5_6_5_REV}, // es error, use channel map
#endif
#ifdef GL_UNSIGNED_SHORT_1_5_5_5_REV
{VideoFormat::Format_RGB555, GL_RGBA, GL_BGRA, GL_UNSIGNED_SHORT_1_5_5_5_REV},
#endif
#ifdef GL_UNSIGNED_SHORT_1_5_5_5_REV
{VideoFormat::Format_BGR555, GL_RGBA, GL_RGBA, GL_UNSIGNED_SHORT_1_5_5_5_REV},
#endif
// TODO: BE formats not implemeted
{VideoFormat::Format_RGB48, GL_RGB, GL_RGB, GL_UNSIGNED_SHORT }, //TODO: they are not work for ANGLE, and rgb16 works on desktop gl, so remove these lines to use rgb16?
{VideoFormat::Format_RGB48LE, GL_RGB, GL_RGB, GL_UNSIGNED_SHORT },
{VideoFormat::Format_RGB48BE, GL_RGB, GL_RGB, GL_UNSIGNED_SHORT },
{VideoFormat::Format_BGR48, GL_RGB, GL_BGR, GL_UNSIGNED_SHORT }, //RGB16?
{VideoFormat::Format_BGR48LE, GL_RGB, GL_BGR, GL_UNSIGNED_SHORT },
{VideoFormat::Format_BGR48BE, GL_RGB, GL_BGR, GL_UNSIGNED_SHORT },
{VideoFormat::Format_RGBA64LE, GL_RGBA, GL_RGBA, GL_UNSIGNED_SHORT },
{VideoFormat::Format_RGBA64BE, GL_RGBA, GL_RGBA, GL_UNSIGNED_SHORT },
{VideoFormat::Format_BGRA64LE, GL_RGBA, GL_BGRA, GL_UNSIGNED_SHORT },
{VideoFormat::Format_BGRA64BE, GL_RGBA, GL_BGRA, GL_UNSIGNED_SHORT },
{VideoFormat::Format_Invalid, 0, 0, 0}
};
Q_UNUSED(pixfmt_to_desktop);
const fmt_entry *pixfmt_gl_entry = pixfmt_to_desktop;
if (OpenGLHelper::isOpenGLES())
pixfmt_gl_entry = pixfmt_to_gles;
// Very special formats, for which OpenGL happens to have direct support
static const fmt_entry pixfmt_gl_base[] = {
{VideoFormat::Format_RGBA32, GL_RGBA, GL_RGBA, GL_UNSIGNED_BYTE }, // only tested for osx, win, angle
{VideoFormat::Format_RGB24, GL_RGB, GL_RGB, GL_UNSIGNED_BYTE },
{VideoFormat::Format_RGB565, GL_RGB, GL_RGB, GL_UNSIGNED_SHORT_5_6_5},
{VideoFormat::Format_BGR32, GL_BGRA, GL_BGRA, GL_UNSIGNED_BYTE }, //rgba(tested) or abgr, depending on endian
};
const VideoFormat::PixelFormat pixfmt = fmt.pixelFormat();
// can not use array size because pixfmt_gl_entry is set on runtime
for (const fmt_entry* e = pixfmt_gl_entry; e->pixfmt != VideoFormat::Format_Invalid; ++e) {
if (e->pixfmt == pixfmt) {
*internal_format = e->internal_format;
*data_format = e->format;
*data_type = e->type;
if (mat)
*mat = QMatrix4x4();
return true;
}
}
for (size_t i = 0; i < ARRAY_SIZE(pixfmt_gl_base); ++i) {
const fmt_entry& e = pixfmt_gl_base[i];
if (e.pixfmt == pixfmt) {
*internal_format = e.internal_format;
*data_format = e.format;
*data_type = e.type;
if (mat)
*mat = QMatrix4x4();
return true;
}
}
static const fmt_entry pixfmt_to_gl_swizzele[] = {
{VideoFormat::Format_UYVY, GL_RGBA, GL_RGBA, GL_UNSIGNED_BYTE },
{VideoFormat::Format_YUYV, GL_RGBA, GL_RGBA, GL_UNSIGNED_BYTE },
{VideoFormat::Format_VYUY, GL_RGBA, GL_RGBA, GL_UNSIGNED_BYTE },
{VideoFormat::Format_YVYU, GL_RGBA, GL_RGBA, GL_UNSIGNED_BYTE },
{VideoFormat::Format_BGR565, GL_RGB, GL_RGB, GL_UNSIGNED_SHORT_5_6_5}, //swizzle
{VideoFormat::Format_RGB555, GL_RGBA, GL_RGBA, GL_UNSIGNED_SHORT_5_5_5_1}, //not working
{VideoFormat::Format_BGR555, GL_RGBA, GL_RGBA, GL_UNSIGNED_SHORT_5_5_5_1}, //not working
};
for (size_t i = 0; i < ARRAY_SIZE(pixfmt_to_gl_swizzele); ++i) {
const fmt_entry& e = pixfmt_to_gl_swizzele[i];
if (e.pixfmt == pixfmt) {
*internal_format = e.internal_format;
*data_format = e.format;
*data_type = e.type;
if (mat)
*mat = channelMap(fmt);
return true;
}
}
GLint *i_f = internal_format;
GLenum *d_f = data_format;
GLenum *d_t = data_type;
gl_param_t* gp = (gl_param_t*)get_gl_param();
if (gp == gl_param_desktop && (
fmt.planeCount() == 2 // nv12 UV plane is 16bit, but we use rg
|| (OpenGLHelper::depth16BitTexture() == 16 && OpenGLHelper::has16BitTexture() && fmt.isBigEndian() && fmt.bitsPerComponent() > 8) // 16bit texture does not support be channel now
)) {
gp = (gl_param_t*)gl_param_desktop_fallback;
qDebug("desktop_fallback for %s", fmt.planeCount() == 2 ? "bi-plane format" : "16bit big endian channel");
}
for (int p = 0; p < fmt.planeCount(); ++p) {
// for packed rgb(swizzle required) and planar formats
const int c = (fmt.channels(p)-1) + 4*((fmt.bitsPerComponent() + 7)/8 - 1);
if (gp[c].format == 0)
return false;
const gl_param_t& f = gp[c];
*(i_f++) = f.internal_format;
*(d_f++) = f.format;
*(d_t++) = f.type;
}
if (mat)
*mat = channelMap(fmt);
return true;
}
void plotPedestalAnalysis(string inputFileName, string outputDIR, bool testDoubleGaussianChannels){
system(("mkdir -p "+outputDIR).c_str());
setTDRStyle();
gROOT->SetBatch(kTRUE);
TFile* inputFile = TFile::Open(inputFileName.c_str(),"READ");
inputFile->cd();
TTree* tree = (TTree*) inputFile->Get("pedestalFullNoise");
uint32_t detid,fedKey;
uint16_t fecCrate,fecSlot, fecRing, ccuAdd, ccuChan, lldChannel, fedId, fedCh, apvId, stripId;
float fitChi2Probab, kSProbab, jBProbab, aDProbab, fitChi2;
float noiseSkewness, noiseKurtosis;
float fitGausMean, fitGausSigma, fitGausNormalization;
float fitGausMeanError, fitGausSigmaError, fitGausNormalizationError;
vector<float>* noiseDistribution = 0;
vector<float>* noiseDistributionError = 0;
float nBin, xMin, xMax;
tree->SetBranchStatus("*",kFALSE);
tree->SetBranchStatus("detid",kTRUE);
tree->SetBranchStatus("fedKey",kTRUE);
tree->SetBranchStatus("fecCrate",kTRUE);
tree->SetBranchStatus("fecSlot",kTRUE);
tree->SetBranchStatus("fecRing",kTRUE);
tree->SetBranchStatus("ccuAdd",kTRUE);
tree->SetBranchStatus("ccuChan",kTRUE);
tree->SetBranchStatus("lldChannel",kTRUE);
tree->SetBranchStatus("fedId",kTRUE);
tree->SetBranchStatus("fedCh",kTRUE);
tree->SetBranchStatus("apvId",kTRUE);
tree->SetBranchStatus("stripId",kTRUE);
tree->SetBranchStatus("fitChi2",kTRUE);
tree->SetBranchStatus("fitChi2Probab",kTRUE);
tree->SetBranchStatus("kSProbab",kTRUE);
tree->SetBranchStatus("jBProbab",kTRUE);
tree->SetBranchStatus("aDProbab",kTRUE);
tree->SetBranchStatus("fitGausNormalization",kTRUE);
tree->SetBranchStatus("fitGausMean",kTRUE);
tree->SetBranchStatus("fitGausSigma",kTRUE);
tree->SetBranchStatus("fitGausNormalizationError",kTRUE);
tree->SetBranchStatus("fitGausMeanError",kTRUE);
tree->SetBranchStatus("fitGausSigmaError",kTRUE);
tree->SetBranchStatus("noiseSkewness",kTRUE);
tree->SetBranchStatus("noiseKurtosis",kTRUE);
tree->SetBranchStatus("noiseDistribution",kTRUE);
tree->SetBranchStatus("noiseDistributionError",kTRUE);
tree->SetBranchStatus("nBin",kTRUE);
tree->SetBranchStatus("xMin",kTRUE);
tree->SetBranchStatus("xMax",kTRUE);
tree->SetBranchAddress("detid",&detid);
tree->SetBranchAddress("fedKey",&fedKey);
tree->SetBranchAddress("fecCrate",&fecCrate);
tree->SetBranchAddress("fecSlot",&fecSlot);
tree->SetBranchAddress("fecRing",&fecRing);
tree->SetBranchAddress("ccuAdd",&ccuAdd);
tree->SetBranchAddress("ccuChan",&ccuChan);
tree->SetBranchAddress("lldChannel",&lldChannel);
tree->SetBranchAddress("fedId",&fedId);
tree->SetBranchAddress("fedCh",&fedCh);
tree->SetBranchAddress("apvId",&apvId);
tree->SetBranchAddress("stripId",&stripId);
tree->SetBranchAddress("fitGausNormalization",&fitGausNormalization);
tree->SetBranchAddress("fitGausMean",&fitGausMean);
tree->SetBranchAddress("fitGausSigma",&fitGausSigma);
tree->SetBranchAddress("fitGausNormalizationError",&fitGausNormalizationError);
tree->SetBranchAddress("fitGausMeanError",&fitGausMeanError);
tree->SetBranchAddress("fitGausSigmaError",&fitGausSigmaError);
tree->SetBranchAddress("fitChi2",&fitChi2);
tree->SetBranchAddress("fitChi2Probab",&fitChi2Probab);
tree->SetBranchAddress("noiseSkewness",&noiseSkewness);
tree->SetBranchAddress("noiseKurtosis",&noiseKurtosis);
tree->SetBranchAddress("kSProbab",&kSProbab);
tree->SetBranchAddress("aDProbab",&aDProbab);
tree->SetBranchAddress("jBProbab",&jBProbab);
tree->SetBranchAddress("noiseDistribution",&noiseDistribution);
tree->SetBranchAddress("noiseDistributionError",&noiseDistributionError);
tree->SetBranchAddress("nBin",&nBin);
tree->SetBranchAddress("xMin",&xMin);
tree->SetBranchAddress("xMax",&xMax);
TFile* badStripsNFilledBins = new TFile((outputDIR+"/badStripsNFilledBins.root").c_str(),"RECREATE");
TFile* badKsTest = new TFile((outputDIR+"/badStripsKsTest.root").c_str(),"RECREATE");
TFile* badjBTest = new TFile((outputDIR+"/badStripsjBTest.root").c_str(),"RECREATE");
TFile* badChi2Test = new TFile((outputDIR+"/badStripsChi2Test.root").c_str(),"RECREATE");
TFile* badaDTest = new TFile((outputDIR+"/badStripsaDTest.root").c_str(),"RECREATE");
TFile* badCombinedTest = new TFile((outputDIR+"/badStripsCombined.root").c_str(),"RECREATE");
TFile* badJBNotKSTest = new TFile((outputDIR+"/badStripsjBNotKS.root").c_str(),"RECREATE");
TFile* badaDNotKSandjBTest = new TFile((outputDIR+"/badStripaDNotKSNotjB.root").c_str(),"RECREATE");
TFile* badChi2NotKSandjBandaDTest = new TFile((outputDIR+"/badStripsChi2NotKsandjBandaD.root").c_str(),"RECREATE");
long int nbadNFilledBins = 0;
long int nbadKsTest = 0;
long int nbadjBTest = 0;
long int nbadaDTest = 0;
long int nbadChi2Test = 0;
long int nbadCombinedTest = 0;
long int nbadJBNotKSTest = 0;
long int nbadaDNotKSandjBTest = 0;
long int nbadChi2NotKSandjBandaDTest = 0;
long int nbadDoublePeakDistance = 0;
long int nbadDoublePeakAshman = 0;
long int nbadDoublePeakChi2 = 0;
long int nbadDoublePeakAmplitude = 0;
long int nbadDoublePeakBimodality = 0;
long int nbadDoublePeakCombined = 0;
TCanvas* canvas = new TCanvas("canvas","canvas",600,650);
map<uint32_t,uint32_t> moduleDenominator;
map<uint32_t,uint32_t> moduleNumerator;
// map<uint32_t,uint32_t> moduleNonEdgeNumerator;
// map<uint32_t,uint32_t> moduleAPVEdgeNumerator;
map<uint32_t,uint32_t> moduleNumeratorFilledBins;
map<uint32_t,uint32_t> moduleNumeratorKS;
map<uint32_t,uint32_t> moduleNumeratorJB;
map<uint32_t,uint32_t> moduleNumeratorDoublePeak;
vector<TrackerStrip> badStrip;
TH1F* noiseHist = NULL;
TF1* noiseFit = NULL;
TF1* noiseFit2Gaus = NULL;
TFitResultPtr result;
TH1F* chi2Distance = new TH1F("chi2Distance","",100,0,1);
chi2Distance->Sumw2();
TH1F* peakDistance = new TH1F("peakDistance","",100,0,3);
peakDistance->Sumw2();
TH1F* ashmanDistance = new TH1F("ashmanDistance","",100,0,5);
ashmanDistance->Sumw2();
TH1F* bimodalityDistance = new TH1F("bimodalityDistance","",100,0,1);
bimodalityDistance->Sumw2();
TH1F* amplitudeRatioDistance = new TH1F("amplitudeRatioDistance","",100,0,3);
amplitudeRatioDistance->Sumw2();
TFile* multiPeakChannelsChi2 = new TFile((outputDIR+"/multiPeakChannelsChi2.root").c_str(),"RECREATE");
TFile* multiPeakChannelsDistance = new TFile((outputDIR+"/multiPeakChannelsDistance.root").c_str(),"RECREATE");
TFile* multiPeakChannelsAshman = new TFile((outputDIR+"/multiPeakChannelsAshman.root").c_str(),"RECREATE");
TFile* multiPeakChannelsAmplitude = new TFile((outputDIR+"/multiPeakChannelsAmplitude.root").c_str(),"RECREATE");
TFile* multiPeakChannelsBimodality = new TFile((outputDIR+"/multiPeakChannelsBimodality.root").c_str(),"RECREATE");
TFile* multiPeakChannelsCombined = new TFile((outputDIR+"/multiPeakChannelsCombined.root").c_str(),"RECREATE");
int nonNullBins = 0;
float chi2Ratio = 0;
float distance = 0;
float ashman = 0;
float bimodality = 0;
float amplitudeRatio = 0;
bool isfound = false;
string fedKeyStr ;
TString name ;
std::map<string,string> fitParam;
for(long int iChannel = 0; iChannel < tree->GetEntries(); iChannel++){
tree->GetEntry(iChannel);
cout.flush();
if(iChannel %10000 == 0) cout<<"\r"<<"iChannel "<<100*double(iChannel)/(tree->GetEntries()/reductionFactor)<<" % ";
if(iChannel > double(tree->GetEntries())/reductionFactor) break;
// skip problematic fed id
isfound = false;
for(auto skipfed : skipFEDid){
if(fedId == skipfed) isfound = true;
}
if(isfound) continue;
// make selections to identify bad noisy channels (not gaussian ones)
std::stringstream stream;
stream << std::hex << fedKey;
fedKeyStr = stream.str();
if(fedKeyStr.size() == 4)
name = Form("fecCrate%d_fecSlot%d_fecRing%d_ccuAdd%d_ccuCh%d_fedKey0x0000%s_lldCh%d_apv%d_strip%d",fecCrate,fecSlot,fecRing,ccuAdd,ccuChan,fedKeyStr.c_str(),lldChannel,apvId,stripId);
else if(fedKeyStr.size() == 5)
name = Form("fecCrate%d_fecSlot%d_fecRing%d_ccuAdd%d_ccuCh%d_fedKey0x000%s_lldCh%d_apv%d_strip%d",fecCrate,fecSlot,fecRing,ccuAdd,ccuChan,fedKeyStr.c_str(),lldChannel,apvId,stripId);
fitParam.clear();
stringstream sMean;
sMean << std::scientific << fitGausMean;
fitParam["fitGausMean"] = sMean.str();
stringstream sSigma;
sSigma << std::scientific << fitGausSigma;
fitParam["fitGausSigma"] = sSigma.str();
stringstream sSkew;
sSkew << std::scientific << noiseSkewness;
fitParam["noiseSkewness"] = sSkew.str();
stringstream sKurt;
sKurt << std::scientific << noiseKurtosis;
fitParam["noiseKurtosis"] = sKurt.str();
stringstream sKS;
sKS << std::scientific << kSProbab;
fitParam["kSProbab"] = sKS.str();
stringstream sJB;
sJB << std::scientific << jBProbab;
fitParam["jBProbab"] = sJB.str();
stringstream sChi2;
sChi2 << std::scientific << fitChi2Probab;
fitParam["fitChi2Probab"] = sChi2.str();
stringstream sAD;
sAD << std::scientific << aDProbab;
fitParam["aDProbab"] = sAD.str();
moduleDenominator[detid] = moduleDenominator[detid]+1;
if(noiseHist == NULL){
noiseHist = new TH1F ("noiseHist","",nBin,xMin,xMax);
noiseHist->Sumw2();
}
noiseHist->Reset();
for(int iBin = 0; iBin < noiseDistribution->size(); iBin++){
noiseHist->SetBinContent(iBin+1,noiseDistribution->at(iBin));
noiseHist->SetBinError(iBin+1,noiseDistributionError->at(iBin));
}
if(noiseFit == NULL)
noiseFit = new TF1 ("noiseFist","gaus(0)",xMin,xMax);
noiseFit->SetRange(xMin,xMax);
noiseFit->SetParameters(fitGausNormalization,fitGausMean,fitGausSigma);
noiseFit->SetParError(0,fitGausNormalizationError);
noiseFit->SetParError(1,fitGausMeanError);
noiseFit->SetParError(2,fitGausSigmaError);
nonNullBins = 0;
for(int iBin = 0; iBin < noiseHist->GetNbinsX(); iBin++){
if(noiseHist->GetBinContent(iBin+1) != 0) nonNullBins++;
}
if(nonNullBins < nFilledBinSelection or noiseHist->GetRMS() < minimumRMS){
badStripsNFilledBins->cd();
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
nbadNFilledBins++;
moduleNumeratorFilledBins[detid] +=1;
continue;
}
if(kSProbab < quantile3sigma){
badKsTest->cd();
nbadKsTest++;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
moduleNumeratorKS[detid] += 1;
}
if(jBProbab < quantile5sigma){
badjBTest->cd();
nbadjBTest++;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
}
if(fitChi2Probab < quantile4sigma){
badChi2Test->cd();
nbadChi2Test++;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
}
if(aDProbab < quantile3sigma){
badaDTest->cd();
nbadaDTest++;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
}
if(jBProbab < quantile5sigma and kSProbab > quantile3sigma and kSProbab < quantile){
badJBNotKSTest->cd();
nbadJBNotKSTest++;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
moduleNumeratorJB[detid] += 1;
}
if(aDProbab < quantile3sigma and jBProbab > quantile5sigma and kSProbab > quantile3sigma and kSProbab < quantile){
badaDNotKSandjBTest->cd();
nbadaDNotKSandjBTest++;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
}
if(fitChi2Probab < quantile4sigma and jBProbab > quantile5sigma and kSProbab > quantile3sigma and kSProbab < quantile and aDProbab > quantile3sigma){
badChi2NotKSandjBandaDTest->cd();
nbadChi2NotKSandjBandaDTest++;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
}
if(kSProbab < quantile3sigma or (kSProbab > quantile3sigma and kSProbab < quantile and jBProbab < quantile5sigma) or (kSProbab > quantile3sigma and kSProbab < quantile and jBProbab > quantile5sigma and aDProbab < quantile3sigma) or (kSProbab > quantile3sigma and kSProbab < quantile and jBProbab > quantile5sigma and aDProbab > quantile3sigma and fitChi2Probab < quantile4sigma)){
badCombinedTest->cd();
nbadCombinedTest++;
moduleNumerator[detid] = moduleNumerator[detid]+1;
//if(stripId == 1 or stripId == 128)
// moduleAPVEdgeNumerator[detid] = moduleAPVEdgeNumerator[detid]+1;
//else
// moduleNonEdgeNumerator[detid] = moduleNonEdgeNumerator[detid]+1;
storeOutputCanvas(canvas,noiseHist,noiseFit,name,fitParam);
name = Form("fecCrate%d_fecSlot%d_fecRing%d_ccuAdd%d_ccuCh%d_fedKey0x0000%s_lldCh%d_apv%d_strip%d",fecCrate,fecSlot,fecRing,ccuAdd,ccuChan,fedKeyStr.c_str(),lldChannel,apvId,stripId);
badStrip.push_back(TrackerStrip(fecCrate,fecSlot,fecRing,ccuAdd,ccuChan,uint32_t(atoi(fedKeyStr.c_str())),lldChannel,apvId,stripId));
//try to identify double peaked channels
if(testDoubleGaussianChannels){
if(noiseFit2Gaus == NULL)
// double gaussian in which the sigma is constrained to be the same --> identifing clear two peak channels
noiseFit2Gaus = new TF1("dgaus","[0]*exp(-((x-[1])*(x-[1]))/(2*[2]*[2]))+[3]*exp(-((x-[4])*(x-[4]))/(2*[5]*[5]))",xMin,xMax);
noiseFit2Gaus->SetRange(xMin,xMax);
noiseFit2Gaus->SetParameter(0,fitGausNormalization/2);
noiseFit2Gaus->SetParameter(3,fitGausNormalization/2);
noiseFit2Gaus->SetParameter(1,1.);
noiseFit2Gaus->SetParameter(4,-1.);
noiseFit2Gaus->SetParameter(2,fitGausSigma);
noiseFit2Gaus->SetParameter(5,fitGausSigma);
noiseFit2Gaus->SetParLimits(1,0.,xMax);
noiseFit2Gaus->SetParLimits(4,xMin,0);
result = noiseHist->Fit(noiseFit2Gaus,"QSR");
chi2Ratio = 0;
distance = 0;
ashman = 0;
bimodality = 0;
amplitudeRatio = 0;
if(result.Get() or noiseHist->Integral() == 0){
//compute the chi2 ratio
chi2Ratio = 0.5*ROOT::Math::chisquared_cdf_c((fitChi2/(result->Ndf()+3))/(result->Chi2()/result->Ndf()),1);
chi2Distance->Fill(chi2Ratio);
distance = fabs(noiseFit2Gaus->GetParameter(1)-noiseFit2Gaus->GetParameter(4))/(2*sqrt(noiseFit2Gaus->GetParameter(2)*noiseFit2Gaus->GetParameter(5)));
peakDistance->Fill(distance);
ashman = TMath::Power(2,0.5)*abs(noiseFit2Gaus->GetParameter(1)-noiseFit2Gaus->GetParameter(4))/(sqrt(pow(noiseFit2Gaus->GetParameter(2),2)+pow(noiseFit2Gaus->GetParameter(5),2)));
ashmanDistance->Fill(ashman);
if(nonNullBins > 3)
bimodality = (noiseHist->GetSkewness()*noiseHist->GetSkewness()+1)/(noiseHist->GetKurtosis()+3*(nonNullBins-1)*(nonNullBins-1)/((nonNullBins-2)*(nonNullBins-3)));
else
bimodality = (noiseHist->GetSkewness()*noiseHist->GetSkewness()+1)/(noiseHist->GetKurtosis());
bimodalityDistance->Fill(bimodality);
amplitudeRatio = std::min(noiseFit2Gaus->GetParameter(0),noiseFit2Gaus->GetParameter(3))/std::max(noiseFit2Gaus->GetParameter(0),noiseFit2Gaus->GetParameter(3));
amplitudeRatioDistance->Fill(amplitudeRatio);
if(distance > 1){
multiPeakChannelsDistance->cd();
storeOutputCanvas(canvas,noiseHist,noiseFit,noiseFit2Gaus,name);
nbadDoublePeakDistance++;
}
if(ashman > 2){
multiPeakChannelsAshman->cd();
storeOutputCanvas(canvas,noiseHist,noiseFit,noiseFit2Gaus,name);
nbadDoublePeakAshman++;
}
if(chi2Ratio < 0.05){
multiPeakChannelsChi2->cd();
storeOutputCanvas(canvas,noiseHist,noiseFit,noiseFit2Gaus,name);
nbadDoublePeakChi2++;
}
if(amplitudeRatio > 0.85){
multiPeakChannelsAmplitude->cd();
storeOutputCanvas(canvas,noiseHist,noiseFit,noiseFit2Gaus,name);
nbadDoublePeakAmplitude++;
}
if(bimodality > 0.55){
multiPeakChannelsBimodality->cd();
storeOutputCanvas(canvas,noiseHist,noiseFit,noiseFit2Gaus,name);
nbadDoublePeakBimodality++;
}
if(ashman > 2 && amplitudeRatio > 0.85){
multiPeakChannelsCombined->cd();
storeOutputCanvas(canvas,noiseHist,noiseFit,noiseFit2Gaus,name);
nbadDoublePeakCombined++;
moduleNumeratorDoublePeak[detid]++;
}
}
}
}
}
// plot the chi2 and peak distance
if(testDoubleGaussianChannels){
storeOutputCanvas(canvas,chi2Distance,"chi2TestStatistics",outputDIR);
storeOutputCanvas(canvas,peakDistance,"peakDistanceTestStatistics",outputDIR);
storeOutputCanvas(canvas,ashmanDistance,"ashmanTestStatistics",outputDIR);
storeOutputCanvas(canvas,amplitudeRatioDistance,"amplitudeRatioDistance",outputDIR);
storeOutputCanvas(canvas,bimodalityDistance,"bimodalityDistance",outputDIR);
}
std::cout<<std::endl;
badStripsNFilledBins->Close();
badKsTest->Close();
badaDTest->Close();
badjBTest->Close();
badChi2Test->Close();
badCombinedTest->Close();
badJBNotKSTest->Close();
badaDNotKSandjBTest->Close();
badChi2NotKSandjBandaDTest->Close();
multiPeakChannelsCombined->Close();
//////
multiPeakChannelsChi2->Close();
multiPeakChannelsDistance->Close();
multiPeakChannelsAshman->Close();
multiPeakChannelsAmplitude->Close();
multiPeakChannelsBimodality->Close();
cout<<"#### Bad Nfilled bins "<<nbadNFilledBins<<" --> "<<double(nbadNFilledBins)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad KS Test Channels "<<nbadKsTest<<" ---> "<<double(nbadKsTest)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad JB Test Channels "<<nbadjBTest<<" ---> "<<double(nbadjBTest)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad AD Test Channels "<<nbadaDTest<<" ---> "<<double(nbadaDTest)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad Chi2 Test Channels "<<nbadChi2Test<<" ---> "<<double(nbadChi2Test)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad JB but not KS Test Channels "<<nbadJBNotKSTest<<" ---> "<<double(nbadJBNotKSTest)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad AD but not KS and not JB Test Channels "<<nbadaDNotKSandjBTest<<" ---> "<<double(nbadaDNotKSandjBTest)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad Chi2 but not KS and JB and AD Test Channels "<<nbadChi2NotKSandjBandaDTest<<" ---> "<<double(nbadChi2NotKSandjBandaDTest)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"#### Bad Combined Test Channels "<<nbadCombinedTest<<" ---> "<<double(nbadCombinedTest)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
if(testDoubleGaussianChannels){
cout<<"###############################"<<endl;
cout<<"#### Multiple peak finder ####"<<endl;
cout<<"##############################"<<endl;
cout<<"Two peak by Chi2 "<<nbadDoublePeakChi2<<" --> "<<double(nbadDoublePeakChi2)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"Two peak by Distance "<<nbadDoublePeakDistance<<" --> "<<double(nbadDoublePeakDistance)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"Two peak by Ashman "<<nbadDoublePeakAshman<<" --> "<<double(nbadDoublePeakAshman)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"Two peak by Amplitude "<<nbadDoublePeakAmplitude<<" --> "<<double(nbadDoublePeakAmplitude)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"Two peak by Bimodality "<<nbadDoublePeakBimodality<<" --> "<<double(nbadDoublePeakBimodality)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
cout<<"Two peak by Combibed "<<nbadDoublePeakCombined<<" ---> "<<double(nbadDoublePeakCombined)/(tree->GetEntries()/reductionFactor)<<" % "<<endl;
}
/// ------->
ofstream channelMap ((outputDIR+"/fractionOfGoodChannels.txt").c_str());
for(auto module : moduleDenominator)
channelMap << module.first <<" "<< 1. - double(moduleNumerator[module.first])/double(moduleDenominator[module.first]) << "\n";
channelMap.close();
/// ------->
ofstream nchannelMapFilledBins ((outputDIR+"/numberBadChannelsFilledBins.txt").c_str());
for(auto module : moduleNumeratorFilledBins)
nchannelMapFilledBins << module.first <<" "<< moduleNumeratorFilledBins[module.first] << "\n";
nchannelMapFilledBins.close();
/// ------->
ofstream nchannelMap ((outputDIR+"/numberBadChannels.txt").c_str());
for(auto module : moduleNumerator)
nchannelMap << module.first <<" "<< moduleNumerator[module.first] << "\n";
nchannelMap.close();
/// ------->
// ofstream nNonEdgechannelMap ((outputDIR+"/numberBadChannelsNonEdge.txt").c_str());
// for(auto module : moduleNonEdgeNumerator)
// nNonEdgechannelMap << module.first <<" "<< moduleNonEdgeNumerator[module.first] << "\n";
// nNonEdgechannelMap.close();
/// ------->
// ofstream nAPVEdgechannelMap ((outputDIR+"/numberBadChannelsAPVEdge.txt").c_str());
// for(auto module : moduleAPVEdgeNumerator)
// nAPVEdgechannelMap << module.first <<" "<< moduleAPVEdgeNumerator[module.first] << "\n";
// nAPVEdgechannelMap.close();
/// ------->
ofstream nchannelMapKS ((outputDIR+"/numberBadChannelsKS.txt").c_str());
for(auto module : moduleNumeratorKS)
nchannelMapKS << module.first <<" "<< moduleNumeratorKS[module.first] << "\n";
nchannelMapKS.close();
/// ------->
ofstream nchannelMapJB ((outputDIR+"/numberBadChannelsJB.txt").c_str());
for(auto module : moduleNumeratorJB)
nchannelMapJB << module.first <<" "<< moduleNumeratorKS[module.first] << "\n";
nchannelMapJB.close();
/// ------->
ofstream nchannelMapDoublePeak ((outputDIR+"/numberBadChannelsDoublePeak.txt").c_str());
for(auto module : moduleNumeratorDoublePeak)
nchannelMapDoublePeak << module.first <<" "<< moduleNumeratorDoublePeak[module.first] << "\n";
nchannelMapDoublePeak.close();
// ------> detailed info of bad strips
ofstream badStripDump ((outputDIR+"/badStripDump.txt").c_str());
for(auto badstrip : badStrip){
badStripDump<< badstrip.fecCrate_<<" "<<badstrip.fecSlot_<<" "<<badstrip.fecRing_<<" "<<badstrip.ccuAdd_<<" "<<badstrip.ccuCh_<<" "<<badstrip.fedKey_<<" "<<badstrip.lldCh_<<" "<<badstrip.apvid_<<" "<<badstrip.stripid_<<" \n";
}
badStripDump.close();
}
