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# FLASHgg Final Fits (lite) | ||
# Final Fits (lite) | ||
Welcome to the new Final Fits package. Here lies a a series of scripts which are used to run the final stages of the CMS Hgg analysis: signal modelling, background modelling, datacard creation and final statistical interpretation and final result plots. | ||
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## Download and setup instructions | ||
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# Install the GBRLikelihood package which contains the RooDoubleCBFast implementation | ||
git clone [email protected]:jonathon-langford/HiggsAnalysis.git | ||
# Install Combine as per the documentation here: cms-analysis.github.io/HiggsAnalysis-CombinedLimit/ | ||
git clone [email protected]:cms-analysis/HiggsAnalysis-CombinedLimit.git HiggsAnalysis/CombinedLimit | ||
# Install Combine Harvester for parallelizing fits | ||
git clone https://github.com/cms-analysis/CombineHarvester.git CombineHarvester | ||
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scram b -j 9 | ||
# Install Flashgg Final Fit packages | ||
git clone -b dev_runII_102x [email protected]:cms-analysis/flashggFinalFit.git | ||
git clone -b dev_fggfinalfits_lite [email protected]:cms-analysis/flashggFinalFit.git | ||
cd flashggFinalFit/ | ||
``` | ||
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In every new shell run the following to add `tools/commonTools` and `tools/commonObjects` to your `${PYTHONPATH}`: | ||
``` | ||
./setup.sh | ||
cmsenv | ||
source setup.sh | ||
``` | ||
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## Contents | ||
The FLASHgg Finals Fits package contains several subfolders which are used for the following steps: | ||
The Finals Fits package contains several subfolders which are used for the following steps: | ||
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* Create the Signal Model (see `Signal` dir) | ||
* Create the Background Model (see `Background` dir) | ||
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# Signal Scripts | ||
# Signal modelling | ||
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Add some intro details here. | ||
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There are a number of steps to perform when constructing the signal model (described below). It is recommended to construct a signal model for each year separately. This allows to keep track of both the year-dependent resolution effects and the year-dependent systematic uncertainties. Each step up to the packaging is ran using the `RunSignalScripts.py` script, which takes as input a config file to specify the options for the signal modelling. | ||
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For example: this config file corresponds to running over 2016 signal workspaces: | ||
``` | ||
# Config file: options for signal fitting | ||
signalScriptCfg = { | ||
# Setup | ||
'inputWSDir':'/vols/cms/jl2117/hgg/ws/UL/Sept20/MC_final/signal_2016', # dir storing flashgg workspaces | ||
'procs':'auto', # if auto: inferred automatically from filenames | ||
'cats':'auto', # if auto: inferred automatically from (0) workspace | ||
'ext':'test_2016', # output directory extension | ||
'analysis':'example', # To specify replacement dataset and XS*BR mapping (defined in ./tools/replacementMap.py and ./tools/XSBRMap.py respectively) | ||
'year':'2016', # Use 'combined' if merging all years: not recommended | ||
'massPoints':'120,125,130', | ||
#Photon shape systematics | ||
'scales':'HighR9EB,HighR9EE,LowR9EB,LowR9EE,Gain1EB,Gain6EB', # separate nuisance per year | ||
'scalesCorr':'MaterialCentralBarrel,MaterialOuterBarrel,MaterialForward,FNUFEE,FNUFEB,ShowerShapeHighR9EE,ShowerShapeHighR9EB,ShowerShapeLowR9EE,ShowerShapeLowR9EB', # correlated across years | ||
'scalesGlobal':'NonLinearity,Geant4', # affect all processes equally, correlated across years | ||
'smears':'HighR9EBPhi,HighR9EBRho,HighR9EEPhi,HighR9EERho,LowR9EBPhi,LowR9EBRho,LowR9EEPhi,LowR9EERho', # separate nuisance per year | ||
# Job submission options | ||
'batch':'condor', # ['condor','SGE','IC','local'] | ||
'queue':'espresso' # use hep.q for IC | ||
} | ||
``` | ||
The basic command for using `RunSignalScripts.py` is the following: | ||
``` | ||
python RunSignalScripts.py --inputConfig config_{}.py --mode {mode} --modeOpts "{list of options for specific mode}" --jobOpts "{list of options for job submission}" | ||
``` | ||
The available modes are: | ||
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* fTest | ||
* calcPhotonSyst | ||
* getDiagProc | ||
* getEffAcc | ||
* signalFit | ||
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## Signal F-test | ||
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Test for determining the optimal number of gaussians to use in signal model. If using Double Crystall Ball + Gaussian function for model then you can skip the F-test. | ||
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``` | ||
python RunSignalScripts.py | ||
## Photon systematics | ||
## Extracting the efficiency x acceptance | ||
## Extracting the diagonal process for a given category | ||
## Final model construction | ||
Add details about replacementMap and XSBRMap | ||
## Packaging the output | ||
## Signal model plots |
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