kopecna/EWP-BplusToKstMuMu-AngAna
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Update 'Selection code'

Renata Kopecná 2022-01-24 11:18:25 +01:00
parent df84a3f137
commit 500049b7ec
1 changed files with 28 additions and 28 deletions
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Selection-code.md

@ -3,46 +3,46 @@ The selection code is a set of C++ scripts. First, the running of the code is in
# Running the code # Running the code
When re-running everything, do the following When re-running everything, do the following
First, compile and run the preselection First, compile and run the preselection. It is defined in [[BDTSelection.cpp|BDTSelection]] .
``` ```
.L BDTSelection.cpp+ .L BDTSelection.cpp+
runAllSignalData(1); runAllSignalData(2); runAllSignalData(1); runAllSignalData(2);
runAllSignalMC(1); runAllSignalMC(2); runAllSignalMC(1); runAllSignalMC(2);
runAllRefMC(1); runAllRefMC(2); runAllRefMC(1); runAllRefMC(2);
runAllPHSPMC(1); runAllPHSPMC(2); runAllPHSPMC(1); runAllPHSPMC(2);
``` ```
Then,run a python script performing the Kstar MacGyver DTF Then,run a python script performing the Kstar MacGyver DTF
``` ```
lb-conda default python Rescale_pi0momentum.py lb-conda default python Rescale_pi0momentum.py
``` ```
Next step is to compile and perform the MC Truth-Matching Next step is to compile and perform the MC Truth-Matching
``` ```
.L MCtruthmatching.cpp+ .L MCtruthmatching.cpp+
TruthMatchAllAll(1); TruthMatchAllAll(2); TruthMatchAllAll(1); TruthMatchAllAll(2);
``` ```
Then, we need to add the XMuMu mass variable and apply the KplusMuMu veto Then, we need to add the XMuMu mass variable and apply the KplusMuMu veto
``` ```
.L CodeForTests/AddVariable.cpp+ .L CodeForTests/AddVariable.cpp+
addAllXMuMuMass(true,true,1); addAllXMuMuMass(false,true,1); applyAllVetoKplusMuMuMass(1); addAllXMuMuMass(true,true,1); addAllXMuMuMass(false,true,1); applyAllVetoKplusMuMuMass(1);
addAllXMuMuMass(true,true,2); addAllXMuMuMass(false,true,2); applyAllVetoKplusMuMuMass(2); addAllXMuMuMass(true,true,2); addAllXMuMuMass(false,true,2); applyAllVetoKplusMuMuMass(2);
``` ```
We have all the preselection finished. Now we will need to fit the reconstructed B mass peak. For the instructions how to compile the code and make RooFit use double-sided Crystal Ball or ExpGauss, see [B mass model section](https://git.physi.uni-heidelberg.de/kopecna/EWP-BplusToKstMuMu-AngAna/wiki/B-mass-model). We have all the preselection finished. Now we will need to fit the reconstructed B mass peak. For the instructions how to compile the code and make RooFit use double-sided Crystal Ball or ExpGauss, see [B mass model section](https://git.physi.uni-heidelberg.de/kopecna/EWP-BplusToKstMuMu-AngAna/wiki/B-mass-model).
Now the peaking background is removed, we can proceed to reweighting Now the peaking background is removed, we can proceed to reweighting
``` ```
.L nTrackWeights.cpp+ .L nTrackWeights.cpp+
WeightAll(true,1,true); ReweightReferenceMC(true,1,true); ReweightPHSPMC(true,1,true); WeightAll(true,1,true); ReweightReferenceMC(true,1,true); ReweightPHSPMC(true,1,true);
WeightAll(true,2,true); ReweightReferenceMC(true,2,true); ReweightPHSPMC(true,2,true); WeightAll(true,2,true); ReweightReferenceMC(true,2,true); ReweightPHSPMC(true,2,true);
``` ```
Check the MVA variables are agreeing after weighting them with sWeights Check the MVA variables are agreeing after weighting them with sWeights
``` ```
.L CodeForTests/compareVariables.cc+ .L CodeForTests/compareVariables.cc+
compareAll(1); compareAll(2); compareAll(1); compareAll(2);
``` ```
Reweighted Data and Monte Carlo can be used for the MVA training Reweighted Data and Monte Carlo can be used for the MVA training
@ -54,7 +54,7 @@ Reweighted Data and Monte Carlo can be used for the MVA training
Apply the MVA to all the MC and Data Apply the MVA to all the MC and Data
``` ```
.L TMVAClassApp.cpp+ .L TMVAClassApp.cpp+
TMVAClassAppAll(1); TMVAClassAppAll(2); TMVAClassAppAll(1); TMVAClassAppAll(2);
``` ```
Remove all multiple candidates Remove all multiple candidates
@ -65,8 +65,8 @@ python RemoveMultipleCandidates.py -all
We have to rerun the weights and therefore also the MVA: the shape of the B mass peak is fixed to the one after MVA. We have to rerun the weights and therefore also the MVA: the shape of the B mass peak is fixed to the one after MVA.
``` ```
.L nTrackWeights.cpp+ .L nTrackWeights.cpp+
WeightAll(true,1,true); ReweightReferenceMC(true,1,true); ReweightPHSPMC(true,1,true); WeightAll(true,1,true); ReweightReferenceMC(true,1,true); ReweightPHSPMC(true,1,true);
WeightAll(true,2,true); ReweightReferenceMC(true,2,true); ReweightPHSPMC(true,2,true); WeightAll(true,2,true); ReweightReferenceMC(true,2,true); ReweightPHSPMC(true,2,true);
``` ```
Check the variables again Check the variables again
@ -94,14 +94,14 @@ python RemoveMultipleCandidates.py -all
Add variables to the MC samples **TODO** Add variables to the MC samples **TODO**
``` ```
.L CodeForTests/AddVariable.cpp+ .L CodeForTests/AddVariable.cpp+
addAllVariablesAllMCSamples(1); addAllVariablesAllMCSamples(2); addAllVariablesAllMCSamples(1); addAllVariablesAllMCSamples(2);
``` ```
Get the eficiencies needed for the estimation of the best MVA response cut Get the eficiencies needed for the estimation of the best MVA response cut
``` ```
.L Efficiency.cpp+ .L Efficiency.cpp+
runAllEff(); runAllEff();
``` ```
Scan the significance in the MVA cut. Don't mind the 2012 and 2016 tags, they are just dummies Scan the significance in the MVA cut. Don't mind the 2012 and 2016 tags, they are just dummies
@ -121,11 +121,11 @@ python ReorganizeTGraph.py
Use the MVA scan to plot the signal yields, apply the MVA cut and compare the yields to the CMS results. Use the MVA scan to plot the signal yields, apply the MVA cut and compare the yields to the CMS results.
``` ```
.L SignalStudy.cpp+ .L SignalStudy.cpp+
plotYieldInQ2(true); plotYieldInQ2(false); plotYieldInQ2(true); plotYieldInQ2(false);
ApplyCutPerYearAll(1); ApplyCutPerYearAll(2); ApplyCutPerYearAll(1); ApplyCutPerYearAll(2);
printYileds(false); printYileds(true) printYileds(false); printYileds(true)
yieldComparison(1,getTMVAcut(1)); yieldComparison(1,getTMVAcut(1));
yieldComparison(2,getTMVAcut(2)); yieldComparison(2,getTMVAcut(2));
``` ```