This repository holds the custom files needed to run a EFT fit topcoffea datacards.
To quickly install this repo, simply run:
wget -O - https://raw.githubusercontent.com/TopEFT/EFTFit/master/install.sh | sh
NOTE: This will install the TopEFT custom CombineHarvester fork. If you need to use -s -1
as implemented in combine, you'll need to install the main CombineHarvester repo.
In order to run combine, you will need to get the appropriate CMSSW release and to clone several repositories.
Install CMSSW_10_2_13 OUTSIDE OF YOUR TOPCOFFEA DIR AND NOT IN CONDA
export SCRAM_ARCH=slc7_amd64_gcc700
scram project CMSSW CMSSW_10_2_13
cd CMSSW_10_2_13/src
scram b -j8
Currently working with tag v8.2.0
:
git clone [email protected]:cms-analysis/HiggsAnalysis-CombinedLimit.git HiggsAnalysis/CombinedLimit
cd HiggsAnalysis/CombinedLimit/
git checkout v8.2.0
cd -
scram b -j8
cd $CMSSW_BASE/src/
git clone https://github.com/TopEFT/EFTFit.git EFTFit
scram b -j8
This package is designed to be used with the CombineHarvester fork. This might cause errors when compiling, but you can safely ignore them.
git clone [email protected]:cms-analysis/CombineHarvester.git
cd CombineHarvester
git checkout 128e41eb
scram b -j8
Now we can actually run combine to perform the fits.
- Make sure you have done a
cmsenv
inside ofCMSSW_10_2_13/src/
(wherever you have it installed) - Enter
CMSSW_10_2_13/src/EFTFit/Fitter/test
- Copy all .txt and .root files created by
python analysis/topEFT/datacard_maker.py
(in thehistos
directory of your toplevel topcoffea directory) - Run
combineCards.py
to merge them all into one txt file. DO NOT merge multiple variables for the same channel, as this would artifically double the statistics!- E.g.
njets
only:combineCards.py ttx_multileptons-*{b,p,m}.txt > combinedcard.txt
- E.g.
ptbl
for all categories but3l off-shell Z
(usingHT
instead):combineCards.py ttx_multileptons-2lss_*ptbl.txt ttx_multileptons-3l_onZ*ptbl.txt ttx_multileptons-3l_*_offZ_*ht.txt ttx_multileptons-4l_*ptbl.txt > combinedcard.txt
- TOP-22-006 selection (old mehtod):
combineCards.py ttx_multileptons-{2,4}*lj0pt.txt ttx_multileptons-3l_{p,m}_offZ*lj0pt.txt ttx_multileptons-3l_onZ_1b_*ptz.txt ttx_multileptons-3l_onZ_2b_{4,5}j*ptz.txt ttx_multileptons-3l_onZ_2b_{2,3}j*lj0pt.txt > combinedcard.txt
- TOP-22-006 selection (new mehtod): The latest tools should produce the correct lj0pt or ptz datacards for the corresponding categoes. Therefore, you can simply run:
combineCards.py ttx_multileptons-*.txt > combinedcard.txt
- E.g.
- NOTE: combine uses a lot of recursive function calls to create the workspace. When running with systematics, this can cause a segmentation fault. You must run
ulimit -s unlimited
once per session to avoid this. - Run the following command to generate the workspace file:
You can Specify a subset of WCs using
text2workspace.py combinedcard.txt -o wps.root -P EFTFit.Fitter.AnomalousCouplingEFTNegative:analiticAnomalousCouplingEFTNegative --X-allow-no-background --for-fits --no-wrappers --X-pack-asympows --optimize-simpdf-constraints=cms
--PO
, e.g.:text2workspace.py combinedcard.txt -o wps.root -P EFTFit.Fitter.AnomalousCouplingEFTNegative:analiticAnomalousCouplingEFTNegative --X-allow-no-background --PO cpt,ctp,cptb,cQlMi,cQl3i,ctlTi,ctli,cbW,cpQM,cpQ3,ctei,cQei,ctW,ctlSi,ctZ,ctG
- Run combine with our EFTFit tools
- Example:
python -i ../scripts/EFTFitter.py fitter.batch1DScanEFT(basename='.081921.njet.ptbl.Float', batch='condor', workspace='wps.root', other=['-t', '-1'])
- Once all jobs are finished, run the following (again inside
python -i ../scripts/EFTFitter.py
) to collect them in theEFTFit/Fitter/fit_files
folder:fitter.batchRetrieve1DScansEFT(basename='.081921.njet.ptbl.Float', batch='condor')
- Example:
To make simple 1D plots, use:
python -i ../scripts/EFTPlotter.py
plotter.BatchOverlayLLPlot1DEFT(basename1_lst=['.081121.njet.16wc.Float'], basename2_lst=['.EFT.SM.Freeze'], wcs=[], log=False, final=False, titles=['Others profiled', 'Others fixed to SM'])
To make comparison plots (e.g. njets
vs. njets+ptbl
):
python -i ../scripts/EFTPlotter.py
plotter.BestScanPlot(basename_float_lst='.081721.njet.Float', basename_freeze_lst='.081821.njet.ptbl.Float', filename='_float_njet_ptbl', titles=['N_{jet} prof.', 'N_{jet}+p_{T}(b+l) prof.'], printFOM=True)
-
Combine the cards: Inside of the EFTFit repo, copy the relevant cards (
.txt
files) and templates (.root
files) for the categories that you want to make a worksapce for into the same directory. For the TOP-22-006 results, this should correspond to the appropriate mix-and-match combination ofptz
andlj0pt
that can be obtained with thedatacards_post_processing.py
script (as explained in the "To reproduce the TOP-22-006 histograms and datacards" section of thetopcoffea
readme). Then from within this directory (that contains only the relevant cards/templates and no extraneous cards/templates), runcombineCards.py ttx_multileptons-*.txt > combinedcard.txt
to make a combined card. -
Copy your selected WC file that was made with your cards (called
selectedWCs.txt
) to somewhere that is accessible from where you will be running thetext2workspace
step. -
Make the workspace by running the following command. Note that this command can take ~2 hours up to about ~8 hours or more (depending on where it is run).
text2workspace.py combinedcard.txt -o yourworkspacename.root -P EFTFit.Fitter.AnomalousCouplingEFTNegative:analiticAnomalousCouplingEFTNegative --X-allow-no-background --for-fits --no-wrappers --X-pack-asympows --optimize-simpdf-constraints=cms --PO selectedWCs=/path/to/your/selectedWCs.txt
Impact plots must be done in three stages:
Run
fitter.ImpactInitialFit(workspace='ptz-lj0pt_fullR2_anatest17_noAutostats_withSys.root', wcs=[])
to produce the initial fits. A blank wcs
will run over all WCs.
Run
fitter.ImpactNuisance(workspace='ptz-lj0pt_fullR2_anatest17_noAutostats_withSys.root', wcs=[])
to fit each NP. A blank wcs
will run over all WCs.
Run
fitter.ImpactCollect(workspace='ptz-lj0pt_fullR2_anatest17_noAutostats_withSys.root', wcs=[])
to collect all jobs and create the final pdf plots. A blank wcs
will run over all WCs.
Note: If you are making Asimov data postfit, the best way to approach this is to simply create a seperate Asimov workspace with only Asimov datacards and perform the exact same steps in this section. (For topeft analysis group, turn off --unblind
option to obtain Asimov datacards)
- Copy your workspace into
/Fitter/test
directory, make sure you activatecmsenv
- In
Fitter/test
runMultidimFit
to make postfit for the workspacewsp.root
with the following command:
time combine --algo none --cminPreScan --cminDefaultMinimizerStrategy=0 -P ctW --trackParameters ctW,ctZ,ctp,cpQM,ctG,cbW,cpQ3,cptb,cpt,cQl3i,cQlMi,cQei,ctli,ctei,ctlSi,ctlTi,cQq13,cQq83,cQq11,ctq1,cQq81,ctq8,ctt1,cQQ1,cQt8,cQt1 --floatOtherPOIs 1 --setParameters ctW=0,ctZ=0,ctp=0,cpQM=0,ctG=0,cbW=0,cpQ3=0,cptb=0,cpt=0,cQl3i=0,cQlMi=0,cQei=0,ctli=0,ctei=0,ctlSi=0,ctlTi=0,cQq13=0,cQq83=0,cQq11=0,ctq1=0,cQq81=0,ctq8=0,ctt1=0,cQQ1=0,cQt8=0,cQt1=0 -M MultiDimFit -d wsp.root -v 2 --saveFitResult -n multidimfit
A file named multidimfit.root
will be made in the Fitter/test
directory.
- Add the file
multidimfit.root
to../../script/structMaker.C
, and change optiondo_postfit
totrue
in the script. - Open
../../condor/submit
script then queue the corresponding number of signal regions, which is 11 for top22-006. (Make sure all the necessary scripts to run condor have the correct directory to eventually point to your../../script/structMaker.C
.) - In
Fitter/test
directory, make a new directory calledfit_results
, and inside, makeSR_postfit
andSR_sum_postfit
two directories. (The scripts are set already to read these directories otherwise it would fail the command.) - Make a directory in
fit_results
calledcondor/logs
. - Run the condor jobs through:
condor_submit ../../condor/submit
- When the jobs are finished, there will be 11 (or whatever number of signal regions your analysis has) SR files in
SR_postfit
, and the same number of files inSR_sum_postfit
. (Note that file naming would start from zero)
- Go into
test/fit_results
directory, and run:
root -b -l -q '../../scripts/plot_maker.C("")'
The corresponding plots will be made in fit_results/plots
For step 2. the command is used to fit all WCs = 0 case. If you want to set certain WC value to non-zero, simply change --setParameters
option.