diff --git a/DataQuality/dqm_algorithms/src/L1Calo_BinsDiffFromStripMedian.cxx b/DataQuality/dqm_algorithms/src/L1Calo_BinsDiffFromStripMedian.cxx
index 2b8f018d16e423d5272bc771f6b6ed05d5e6f268..4b1e36d58e66b4f1a7b894e4f7343ad4fc339749 100644
--- a/DataQuality/dqm_algorithms/src/L1Calo_BinsDiffFromStripMedian.cxx
+++ b/DataQuality/dqm_algorithms/src/L1Calo_BinsDiffFromStripMedian.cxx
@@ -60,7 +60,7 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
throw dqm_core::BadConfig( ERS_HERE, name, "does not inherit from TH1" );
}
- const double minstat = dqm_algorithms::tools::GetFirstFromMap( "MinStat", config.getParameters(), -1);
+ const double minstat = dqm_algorithms::tools::GetFirstFromMap( "MinStat", config.getParameters(), 100);
const double ignoreBelow = dqm_algorithms::tools::GetFirstFromMap( "IgnoreBelow", config.getParameters(), 0);
const double probThreshold = dqm_algorithms::tools::GetFirstFromMap( "ProbThreshold", config.getParameters(), 0.01);
const int publishDetail = dqm_algorithms::tools::GetFirstFromMap( "PublishDetail", config.getParameters(), 0x10/*publish status code - since saw some inconsistencies in webdisplay on local testing. Should plan to set to 0 in future*/);
@@ -102,6 +102,7 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
if ( histogram->GetEntries() < minstat ) {
dqm_core::Result *result = new dqm_core::Result(dqm_core::Result::Undefined);
+ result->status_ = dqm_core::Result::Yellow; // will treat almost-empty histograms as a warning .... shifter should think if this is expected
result->tags_["InsufficientEntries"] = histogram->GetEntries();
return result;
}
@@ -109,6 +110,8 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
std::vector<int> range=dqm_algorithms::tools::GetBinRange(histogram, config.getParameters());
+ std::set<int> filledRows; // will only look for dead strips once all rows are filled
+
// compute medians, means, variances, k-test probabilities
std::vector<double> stripsMedian;
std::vector<double> stripsAvg;
@@ -122,6 +125,7 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
for ( int j = range[2]; j <= range[3]; ++j ) {
if (histogram->GetBinContent(i,j) < ignoreBelow) continue;
float binvalue = histogram->GetBinContent(i,j);
+ if(binvalue>0) filledRows.insert(j); // used to veto running deadstrip tests on sparsely populated plots
onestrip.push_back(binvalue);
stripSum += binvalue;
stripSum2 += binvalue*binvalue;
@@ -140,8 +144,15 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
// also compute Kolmogorov test probability vs a same-size dataset generated from a gaussian with the strip mean and variance
if(stripsVariance.back() > 0) {
std::vector<double> stripRef;
- for (size_t i = 0; i < onestrip.size(); i++)
- stripRef.push_back(r.Gaus(stripsAvg.back(), std::sqrt(stripsVariance.back())));
+ for (size_t i = 0; i < onestrip.size(); i++) {
+ // use possion for variances less than 100 (corresponding ~ to averages fewer than 100)
+ // otherwise switch to gaussian
+ double nextVal = 0;
+ do {
+ nextVal = (stripsVariance.back()>=100) ? r.Gaus(stripsAvg.back(), std::sqrt(stripsVariance.back())) : r.Poisson(stripsAvg.back());
+ } while(nextVal<ignoreBelow);
+ stripRef.push_back(nextVal);
+ }
std::sort(stripRef.begin(),stripRef.end());
stripsProb.push_back( TMath::KolmogorovTest(onestrip.size(),&onestrip[0],stripRef.size(),&stripRef[0],"") );
} else {
@@ -164,10 +175,12 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
}
+ bool testDeadStrips = (filledRows.size() == size_t(range[3]-range[2]+1));
+
std::map<std::string,int> counts;
// ensure all counts defined, even if will end up being 0
- counts["NDeadStrip"]=0;
+ counts["NDeadStrip"]= (testDeadStrips) ? 0 : -1; // use -1 to flag not running this test
counts["NDead"]=0;
counts["NWrongKnown"]=0;
counts["NConsecUnlikelyStrip"]=0;
@@ -178,12 +191,16 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
// publish deadstrips (whole strip is 0), and unlikely strips
int nUnlikelyStrips = 0;
for(size_t i = 0;i<stripsVariance.size();i++) {
- if (stripsN.at(i) > 0 && stripsVariance.at(i) == 0 && stripsAvg.at(i) == 0) {
- result->tags_[TString::Format("_DeadStrip%02ld", i+1).Data()] = histogram->GetXaxis()->GetBinCenter(range[0] + i);
- counts["NDeadStrip"]++;
+ if (testDeadStrips && stripsVariance.at(i) == 0 && stripsAvg.at(i) == 0) {
+ // only dead if at least one of the neighbour strips has enough entries in it
+ if( (i>0 && (stripsAvg.at(i-1)*stripsN.at(i-1))>=minstat) || (i<stripsVariance.size()-1 && (stripsAvg.at(i+1)*stripsN.at(i+1))>=minstat)) {
+ result->tags_[TString::Format("_DeadStrip%02ld", i+1).Data()] = histogram->GetXaxis()->GetBinCenter(range[0] + i);
+ counts["NDeadStrip"]++;
+ }
+
}
if (stripsProb.at(i) < probThreshold) {
- result->tags_[TString::Format("_UnlikelyStrip%02ld", i+1).Data()] = stripsProb.at(i);
+ result->tags_[TString::Format("_UnlikelyStrip%02ld", i+1).Data()] = -log(stripsProb.at(i));
nUnlikelyStrips++;
if(nUnlikelyStrips > counts["NConsecUnlikelyStrip"]) counts["NConsecUnlikelyStrip"] = nUnlikelyStrips;
} else {
@@ -220,7 +237,7 @@ dqm_algorithms::L1Calo_BinsDiffFromStripMedian::execute(const std::string & nam
// loop through cuts, assign bin to one of the ranges, and report if not a known bin
double classCut = 0;
for(auto& [cut,k] : orderedCuts) {
- if( (cut < 0 && bin.m_outstandingRatio < cut) || (cut > 0 && bin.m_outstandingRatio > cut) ) {
+ if( (cut < 0 && bin.m_outstandingRatio < cut) || (cut > 0 && bin.m_outstandingRatio > cut && bin.m_value>=minstat) ) {
classCut = cut;
if(knownBins[k].find({bin.m_ix,bin.m_iy})==knownBins[k].end()) {
result->tags_[TString::Format("_%s(%d,%d)", k.c_str(), bin.m_ix,
@@ -291,10 +308,10 @@ void dqm_algorithms::L1Calo_BinsDiffFromStripMedian::printDescription(std::ostre
out<<"L1Calo_BinsDiffFromStripMedian: Calculates strip median and then find out bins which are aliens "<<std::endl;
out<<"Specify cuts with parameters named <cutName>Cut will generate a result of form Nxxx" << std::endl;
out<<"Specify known anomalies with Known<cutName> string argument - note any leading non-numeric char will be stripped" << std::endl;
- out<<"Special results are: NDead (number of 0 bins below most negative cut), NDeadStrip (strips that are all 0), NConsecUnlikelyStrip (most consecutive strips that are below ProbThreshold)" << std::endl;
+ out<<"Special results are: NDead (number of 0 bins below most negative cut), NDeadStrip (strips that are all 0 .. will be -1 if not got an entry in every row of plot), NConsecUnlikelyStrip (most consecutive strips that are below ProbThreshold)" << std::endl;
out<<"Thresholds can be set on any of the results\n"<<std::endl;
- out<<"Optional Parameter: MinStat: Minimum histogram statistics needed to perform Algorithm"<<std::endl;
+ out<<"Optional Parameter: MinStat: Minimum histogram statistics needed to perform Algorithm, also min entries for warm/hot spots (cuts > 0), and min entries in neighbour strip to declare a strip dead"<<std::endl;
out<<"Optional Parameter: IgnoreBelow: values below which the bins wont be considered (default 0)"<<std::endl;
out<<"Optional Parameter: ProbThreshold: cutoff for strip k-test probabilities for strip to be considered unlikely (default 0.05)"<<std::endl;
out<<"Optional Parameter: PublishDetail: Bitmask of what extra info to publish about strips. Starting with MSB: AlgStatusCode,Zeros,Noise,Prob,StdDev,Median (default 000000)"<<std::endl;
diff --git a/Trigger/TrigT1/TrigT1CaloMonitoring/python/EfexInputMonitorAlgorithm.py b/Trigger/TrigT1/TrigT1CaloMonitoring/python/EfexInputMonitorAlgorithm.py
index 32353b2d3da4e313ef3d41524ef129c37abfb46a..9928d783bd0dcbe26157b110ecff296ba07ddbc8 100644
--- a/Trigger/TrigT1/TrigT1CaloMonitoring/python/EfexInputMonitorAlgorithm.py
+++ b/Trigger/TrigT1/TrigT1CaloMonitoring/python/EfexInputMonitorAlgorithm.py
@@ -95,7 +95,7 @@ def EfexInputMonitoringConfig(flags):
for layer in ["ecal","hcal"]:
helper.defineHistogram(f'TowerEta,TowerPhi;h_dataTowers_{layer}_hot_EtaPhiMap',title=f'{layer.upper()} SuperCells >= 500MeV;#eta;#phi',
cutmask="AboveCut",
- path="Expert/Inputs/eFEX",
+ paths=["Expert/Inputs/eFEX","Shifter/Inputs/eFEX"],
hanConfig={"algorithm":f"Efex_{layer}_hot_etaPhiMapOutliers","description":f"Check <a href='./detail/h_dataTowers_{layer}_hot_posVsLBN'>detail plot</a> to get timeseries for each location"},
fillGroup=layer,
type='TH2I',