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reduce the number of 'PRunSingleHisto::CalcMaxLikelihood: **WARNING** NEGATIVE theorygit status -uno' messages.
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suter_a
2026-09-12 18:12:11 +02:00
parent a95318dc9f
commit 915e7552b2
2 changed files with 18 additions and 6 deletions
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src/classes/PRunMuMinus.cpp
+6 -2
View File
@@ -372,6 +372,7 @@ Double_t PRunMuMinus::CalcMaxLikelihood(const std::vector<Double_t>& par)
Double_t theo;
Double_t data;
Double_t time(1.0);
Bool_t post_msg(true);
Int_t i;
// Calculate the theory function once to ensure one function evaluation for the current set of parameters.
@@ -384,7 +385,7 @@ Double_t PRunMuMinus::CalcMaxLikelihood(const std::vector<Double_t>& par)
Int_t chunk = (fEndTimeBin - fStartTimeBin)/omp_get_num_procs();
if (chunk < 10)
chunk = 10;
#pragma omp parallel for default(shared) private(i,time,theo,data) schedule(dynamic,chunk) reduction(+:mllh)
#pragma omp parallel for default(shared) private(i,time,theo,data,post_msg) schedule(dynamic,chunk) reduction(+:mllh)
#endif
for (i=fStartTimeBin; i < fEndTimeBin; ++i) {
time = fData.GetDataTimeStart() + static_cast<Double_t>(i)*fData.GetDataTimeStep();
@@ -394,7 +395,10 @@ Double_t PRunMuMinus::CalcMaxLikelihood(const std::vector<Double_t>& par)
data = fData.GetValue()->at(i);
if (theo <= 0.0) {
std::cerr << ">> PRunMuMinus::CalcMaxLikelihood: **WARNING** NEGATIVE theory!!" << std::endl;
if (post_msg) {
post_msg = false;
std::cerr << ">> PRunMuMinus::CalcMaxLikelihood: **WARNING** NEGATIVE theory!!" << std::endl;
}
continue;
}
src/classes/PRunSingleHisto.cpp
+12 -4
View File
@@ -498,6 +498,7 @@ Double_t PRunSingleHisto::CalcMaxLikelihood(const std::vector<Double_t>& par)
Double_t theo;
Double_t data;
Double_t time(1.0);
Bool_t post_msg(true);
Int_t i;
// norm is needed since there is no simple scaling like in chisq case to get the correct Max.Log.Likelihood value when normlizing N(t) to 1/ns
@@ -516,7 +517,7 @@ Double_t PRunSingleHisto::CalcMaxLikelihood(const std::vector<Double_t>& par)
Int_t chunk = (fEndTimeBin - fStartTimeBin)/omp_get_num_procs();
if (chunk < 10)
chunk = 10;
#pragma omp parallel for default(shared) private(i,time,theo,data) schedule(dynamic,chunk) reduction(+:mllh)
#pragma omp parallel for default(shared) private(i,time,theo,data,post_msg) schedule(dynamic,chunk) reduction(+:mllh)
#endif
for (i=fStartTimeBin; i<fEndTimeBin; ++i) {
time = fData.GetDataTimeStart() + static_cast<Double_t>(i)*fData.GetDataTimeStep();
@@ -526,7 +527,10 @@ Double_t PRunSingleHisto::CalcMaxLikelihood(const std::vector<Double_t>& par)
data = fData.GetValue()->at(i);
if (theo <= 0.0) {
std::cerr << ">> PRunSingleHisto::CalcMaxLikelihood: **WARNING** NEGATIVE theory!!" << std::endl;
if (post_msg) {
post_msg = false;
std::cerr << ">> PRunSingleHisto::CalcMaxLikelihood: **WARNING** NEGATIVE theory!!" << std::endl;
}
continue;
}
@@ -633,6 +637,7 @@ Double_t PRunSingleHisto::CalcMaxLikelihoodExpected(const std::vector<Double_t>&
Double_t theo;
Double_t data;
Double_t time(1.0);
Bool_t post_msg(true);
Int_t i;
// norm is needed since there is no simple scaling like in chisq case to get the correct Max.Log.Likelihood value when normlizing N(t) to 1/ns
@@ -651,7 +656,7 @@ Double_t PRunSingleHisto::CalcMaxLikelihoodExpected(const std::vector<Double_t>&
Int_t chunk = (fEndTimeBin - fStartTimeBin)/omp_get_num_procs();
if (chunk < 10)
chunk = 10;
#pragma omp parallel for default(shared) private(i,time,theo,data) schedule(dynamic,chunk) reduction(+:mllh)
#pragma omp parallel for default(shared) private(i,time,theo,data,post_msg) schedule(dynamic,chunk) reduction(+:mllh)
#endif
for (i=fStartTimeBin; i<fEndTimeBin; ++i) {
time = fData.GetDataTimeStart() + static_cast<Double_t>(i)*fData.GetDataTimeStep();
@@ -661,7 +666,10 @@ Double_t PRunSingleHisto::CalcMaxLikelihoodExpected(const std::vector<Double_t>&
data = fData.GetValue()->at(i);
if (theo <= 0.0) {
std::cerr << ">> PRunSingleHisto::CalcMaxLikelihood: **WARNING** NEGATIVE theory!!" << std::endl;
if (post_msg) {
post_msg = false;
std::cerr << ">> PRunSingleHisto::CalcMaxLikelihood: **WARNING** NEGATIVE theory!!" << std::endl;
}
continue;
}