Commit 5a303685 authored by Louie's avatar Louie
Browse files

add core systTools files

parent 7dfd1428
#image: lukasheinrich/recast_cvmfs_assisted:20161231
image: atlas/atlas_external_cvmfs
variables:
ATLAS_LOCAL_ROOT_BASE: /cvmfs/atlas.cern.ch/repo/ATLASLocalRootBase
SSH_SERVER_HOSTKEYS: lxplus7 ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDTA/5AzXgbkSapknIPDoEePTM1PzIBSiyDnpZihdDXKzm8UdXxCDJLUVjBwc1JfBjnaXPEeBKZDuozDss/m98m5qQu+s2Dks000V8cUFTU+BFotzRWX0jWSBpmzse0477b40X2XCPqX0Cqfx9yHdkuMlyF0kJRxXgsGTcwzwbmvqNHJdHHYJJz93hGpBhYMREcDN5VOxXz6Ack3X7xfF29xaC91oOAqq75O11LXF5Y4kAeN9kDG8o6Zsqk4c5at5aqWqzZfnnVtGjhkgU2Mt5aKwptaFMe0Z3ys/zZM4SnsE9NfompnnWsiKk2y09UvrbzuYPWLt43Fp3+IFqRJvBX
before_script:
- mkdir -p ~/.ssh
# validate lxplus's SSH key
- 'echo "$SSH_SERVER_HOSTKEYS" > ~/.ssh/known_hosts'
# tell SSH to forward Kerberos credentials so lxplus can access AFS/EOS on behalf of the user
- 'echo -e "Host *\n\tGSSAPIDelegateCredentials yes\n\tGSSAPITrustDNS yes\n\n" > ~/.ssh/config'
- echo "${KRB_PASSWORD}" | kinit ${KRB_USERNAME}@CERN.CH
#- ssh ${KRB_USERNAME}@lxplus7 "ls /eos/user/p/${KRB_USERNAME}/"
- set +e
- source /cvmfs/atlas.cern.ch/repo/ATLASLocalRootBase/user/atlasLocalSetup.sh
- asetup 21.6.33,AthGeneration
- source ${LCG_RELEASE_BASE}/LCG_88/MCGenerators/rivet/${RIVETVER}/${LCG_PLATFORM}/rivetenv.sh
- source data/setupLHAPDF.sh
- export SYSTTOOLSPATH="${PWD}"
- export PATH=/afs/cern.ch/sw/XML/TL2016/bin/x86_64-linux:$PATH
- export PATH="$PWD/local/bin:$PATH"
- export PYTHONPATH="$PWD/local/bin:$PYTHONPATH"
- set -e
- export DATE=`date +%d%m%y`
- export WWW=/eos/user/p/${KRB_USERNAME}//www/PMG/${CI_PROJECT_NAME}/${DATE}_${CI_COMMIT_SHA:1:7}
- ssh ${KRB_USERNAME}@lxplus7 "mkdir -p $WWW"
- xrdcp root://eosuser.cern.ch//eos/user/p/${KRB_USERNAME}/index.php .
stages:
- validate
- download
customMCofficialRivet:
stage: validate
script:
- mkdir inputs
- mkdir outputs
- INPATH=/eos/user/p/${KRB_USERNAME}/SystToolsUnitTests/YodaFormatCustomSample/user.lcorpe.user.mcfayden.evnt.2018-06-26_214326.999999.pp_13TeV.999999.Pv2P8_Zee_EXT0.RIVET.Custom_ZInc_sys_EXT0/
- xrdfs root://eosuser.cern.ch/ ls $INPATH| grep tgz | while read p ; do xrdcp root://eosuser.cern.ch/$p inputs/. ; done
- ./unitTests/customMCofficialRivet.py outputs inputs
- cp ./index.php outputs/.
- ls outputs/*yoda > out.cp
- mkdir yodas
- while read p ; do echo `basename $p` ; cp $p yodas/. ; yodadiff $p unitTests/customMCofficialRivetRefs/`basename $p` | tee diffs.txt ; if [ -s "diffs.txt" ]; then echo "fail" ; cat diffs.txt ; else echo "ok" ; fi ; done < out.cp
- mv outputs customMCofficialRivet
artifacts:
when: always
paths:
- yodas
- yodas/*
- customMCofficialRivet
- customMCofficialRivet/*
expire_in: 1 week
officialMCofficialRivet:
stage: validate
script:
- mkdir inputs
- mkdir outputs
- rsync -mav --include "*MAXHTPTV280_500*/*.tgz" --include='*/' --exclude '*' -e ssh ${KRB_USERNAME}@lxplus7:/eos/user/p/${KRB_USERNAME}/SystToolsUnitTests/YodaFormatJobOutputs/ inputs/
- find inputs
- ./unitTests/officialMCofficialRivet.py outputs inputs
- cp ./index.php outputs/.
- ls Zee_Sherpa_officialMCofficialRivet_/merged_final/*yoda > out.cp
- mkdir yodas
- while read p ; do echo `basename $p` ; cp $p yodas/. ; yodadiff $p unitTests/officialMCofficialRivetRefs/`basename $p` | tee diffs.txt ; if [ -s "diffs.txt" ]; then echo "fail" ; cat diffs.txt ; else echo "ok" ; fi ; done < out.cp
- mv outputs officialMCofficialRivet
artifacts:
when: always
paths:
- yodas
- yodas/*
- officialMCofficialRivet
- officialMCofficialRivet/*
expire_in: 1 week
CxAODOutputExample:
stage: validate
script:
- mkdir inputs
- mkdir outputs
- INPATH=/eos/user/p/${KRB_USERNAME}/SystToolsUnitTests/CxAODReader_VVSemileptonic/
- xrdfs root://eosuser.cern.ch/ ls $INPATH| grep root | while read p ; do xrdcp root://eosuser.cern.ch/$p inputs/. ; done
- ./unitTests/CxAODOutputExample.py outputs inputs
- cp ./index.php outputs/.
- mv outputs CxAODOutputExample
artifacts:
when: always
paths:
- CxAODOutputExample
- CxAODOutputExample/*
expire_in: 1 week
Rivet3Format:
stage: validate
script:
- mkdir inputs
- mkdir outputs
- INPATH=/eos/user/p/${KRB_USERNAME}/SystToolsUnitTests/m4lRivet3.v2/
#- xrdfs root://eosuser.cern.ch/ ls $INPATH | while read p ; do xrdcp root://eosuser.cern.ch/$p inputs/. ; done
- xrdcp -r root://eosuser.cern.ch/$INPATH inputs/.
- ./unitTests/Rivet3Format.py outputs inputs
- cp ./index.php outputs/.
- find | grep yoda | grep wSys_v2 | grep -v gz | grep -v example > out.cp
- mkdir yodas
- while read p ; do echo `basename $p` ; cp $p yodas/. ; yodadiff $p unitTests/Rivet3FormatRefs/`basename $p` | tee diffs.txt ; if [ -s "diffs.txt" ]; then echo "fail" ; cat diffs.txt ; else echo "ok" ; fi ; done < out.cp
- mv outputs Rivet3Format
artifacts:
when: always
paths:
- yodas
- yodas/*
- Rivet3Format
- Rivet3Format/*
expire_in: 1 week
Rivet3FormatTgz:
stage: validate
script:
- mkdir -p inputs/user.jroggel.mc15_13TeV.410470.PhPy8EG_A14_ttbar_hdamp258p75_nonallhad.e6337.RIVET.test2_1406_EXT0
- mkdir outputs
- INPATH=/eos/user/p/${KRB_USERNAME}/SystToolsUnitTests/user.jroggel.mc15_13TeV.410470.PhPy8EG_A14_ttbar_hdamp258p75_nonallhad.e6337.RIVET.test2_1406_EXT0
- xrdcp -r root://eosuser.cern.ch/$INPATH inputs/user.jroggel.mc15_13TeV.410470.PhPy8EG_A14_ttbar_hdamp258p75_nonallhad.e6337.RIVET.test2_1406_EXT0/.
- find inputs/.
- ./unitTests/Rivet3FormatTgz.py outputs inputs
- cp ./index.php outputs/.
- find | grep yoda | grep tgzTest > out.cp
- mkdir yodas
- while read p ; do echo `basename $p` ; cp $p yodas/. ; yodadiff $p unitTests/Rivet3FormatTgzRefs/`basename $p` | tee diffs.txt ; if [ -s "diffs.txt" ]; then echo "fail" ; cat diffs.txt ; else echo "ok" ; fi ; done < out.cp
- mv outputs Rivet3FormatTgz
artifacts:
when: always
paths:
- yodas
- yodas/*
- Rivet3FormatTgz
- Rivet3FormatTgz/*
expire_in: 1 week
RootFormatJobOutputs:
stage: validate
script:
- mkdir inputs
- mkdir outputs
- INPATH=/eos/user/p/${KRB_USERNAME}/SystToolsUnitTests/RootFormatJobOutputs/
- xrdcp -r root://eosuser.cern.ch/$INPATH inputs/.
- find inputs/.
- ./unitTests/RootFormatJobOutputs.py outputs inputs
- cp ./index.php outputs/.
- mv outputs RootFormatJobOutputs
artifacts:
when: always
paths:
- RootFormatJobOutputs
- RootFormatJobOutputs/*
expire_in: 1 week
.readDB2:
stage: validate
script:
- ./unitTests/readDB.py
.readDB1:
stage: validate
script:
- ./unitTests/readDB.sh
copyToEOS:
stage: download
dependencies:
- RootFormatJobOutputs
- Rivet3FormatTgz
- Rivet3Format
- CxAODOutputExample
- officialMCofficialRivet
- customMCofficialRivet
script:
- scp -r ./* ${KRB_USERNAME}@lxplus7:${WWW}/
.submitSampleRivet:
stage: validate
script:
- ./unitTests/submitSampleRivet.sh
################################################################################
# Package: PMGSystematicsTools
################################################################################
# Declare the package name:
atlas_subdir( PMGSystematicsTools )
# Declare the package's dependencies:
atlas_depends_on_subdirs( PUBLIC
Tools/PyCmt )
# External dependencies:
find_package( PythonLibs )
find_package( ROOT COMPONENTS Core PyROOT Tree MathCore Hist RIO pthread )
find_package( Rivet )
find_package( YODA )
# Install files from the package:
atlas_install_python_modules( local/bin/*.py )
atlas_install_scripts(share/*.sh)
atlas_install_scripts( local/bin/*.py )
# Aliases:
atlas_add_alias( PMG_systematicsTool "systematicsTool.py" )
atlas_add_alias( PMG_submissionTool "submissionTool.py" )
# PMG SystematicsTool(s)
Need help to evaluate theory uncertainties?
You are in the right place. I hope this tool helps you save a lot of time.
Before proceeding, please read the caveats below.
Table of Contents:
- [Introduction](#introduction)
- [Installing the systematics tool](#installing-the-systematics-tool)
- [What the tool can and cannot do](#what-the-tool-can-and-cannot-do)
- [Instructions for submissionTool](#instructions-for-submissiontool)
- [Instructions for systematicsTool](#instructions-for-systematicstool)
- [Instructions for covarianceTool](#instructions-for-covariancetool)
<br/>
# Introduction
The three main tools in this package are:
- `submissionTool.py`, which helps to submit `EVNT` samples to the Grid running on `Rivet` analysis, where once instance of `Rivet_i` is run for each matrix-element weight. [Documentation](documentation/UsingTheSubmissionTool.md)
- `systematicsTool.py`, which helps to unpack GRID outputs, merge `yoda` or `root` files across jobs, automatically merge across subsamples/slices with corrected cross-sections for each OTF weight (On-the-fly weight , ie systematics weight), merge OTF weights into systematic variations, and calculate an total uncertainty, and finally to make plots with theory error bands. Can be used as an executable or the individual functions can be imported into a python script like `import systematicsTool as st`. [Documentation](documentation/UsingTheSystematicsTool.md)
- `covarianceTool.py` and `covarianceToolsLibrary.py`, and executable and a library of functions which allow analysts to manipulate and use covariance information. [Documentation](documentation/UsingTheCovarianceTool.md)
- a tool to read the systematics database [Documentation](documentation/QueryingTheSystematicsDatabase.md)
A database of OTF weights and recipes provides the user with the information on how to create the systematic uncertainties from on-the-fly variations stored in a given MC sample (by DSID), and allows the tool to combine OTF-weighted histograms into per-variation histograms automatically.
This document contains examples for the most common uses of the systematics tool.
Please follow the link for the task you are interested in!
**NB: The `systematicsTool.py` executable relies on `numpy` objects. There is a known problem installing numpy on lxplus machines running CentOS7.
See the discussion here:
https://groups.cern.ch/group/hn-atlas-offlineSWHelp/Lists/Archive/Flat.aspx?RootFolder=%2fgroup%2fhn-atlas-offlineSWHelp%2fLists%2fArchive%2fBroken%20numpy%20in%206%2e14%2e04-x86_64-slc6-gcc62-opt&FolderCTID=0x012002002BD1887D3A9C0D489560C010AA1FE9F4
In the meantime, we suggest to use lxplus6 machines when using `systematicsTool.py` and lxplus7 machines when using `submissionTool.py`**
# Installing the systematics tool
The below are instructions on how to install the tool on lxplus.
```
# for first installation
ssh -Y <username>@lxplus.cern.ch
mkdir PMGTools
cd PMGTools
git clone ssh://git@gitlab.cern.ch:7999/atlas-physics/pmg/tools/systematics-tools.git
cd systematics-tools
source systematics-tools-bootstrap.sh
# the bootstrap will create a setup script called setupSystematicsTool.sh
# which you can use next time to set everything up easily.
# for example, you can copy this to your home directory
cp setupSystematicsTool.sh ~/.
# for subsequent logins:
ssh -Y <username>@lxplus.cern.ch
source setupSystematicsTool.sh
#and you are done!
```
You can test that the loading has happened correctly by calling the executables from anywhere:
```
submissionTool.py -h
systematicsTool.py -h
covarianceTool.py -h
```
And you can test that you are able to import the functions into a custom script like so:
```
lcorpe@lxplus097 systematics-tools]$ python
Type "help", "copyright", "credits" or "license" for more information.
>>> import readDatabase as rdb
>>> import systematicsTool as st
>>> import covarianceToolsLibrary as ct
```
Please see the detailed docuemtenta
## What the tool can and cannot do
***CAN DO***
The tools in this repo can do many things, although for users in PA or CP groups, only a subset of them are likely to be relevant.
The most obvious use is the possibility to automatically combine analysis objects for each on-the-fly (OTF) weight into variations.
For example, one wants to make a plot of jet pT showing the theory uncertainties for PDF, alphaS and Scale.
The tool needs a copy of the jet pT histogram for each OTF-weight (eg 101 copies, one for each PDF weight, two copies, one each for alphaS up and down, and 9 copies for each scale variation) and will look up in a database for a given sample what the relevant uncertainties are, and how they should be combined, and do the combination for you. The output would then be 3 copies of the jet pT histogram (this time as a `TGraph` which is more approrpiate for plotting error bands), one each for PDF uncertainty, alphaS uncertainty and scale uncertainty. (There may be more than three, this is just an example).
In some cases, if there is a PMG prescription to combine the individual uncertainties into a total error band, the tool will do that too.
The tool will make some plots but more importantly the plots for each variation will be stored in `root` files for you to use downstream in your analysis as you please.
The tool can either be used as an exectuable or the individual functions can be imported into your favourite `python` script.
**CANNOT DO**
The tool can only really evaluate uncertainties which can be derived from OTF weights. For example, it cannot evaluate generator choice uncertainties or radiation uncertainties in some ttbar samples. All the information needs to be contained within a single sample.
The tool cannot combine PDF uncertainties "per event". In other words, you cannot use trees as inputs. The uncertainties are not well defined in that way and you need to propagate the OTF weights all the way to your final observables to evaluate them correctly.
The tool also cannot absolve you of understanding what the uncertainties mean: it is just meant to simplify your life. To find out more about how theory uncertainties, in particular PDF uncertainties, are evaluated, we recommend you study https://twiki.cern.ch/twiki/bin/viewauth/AtlasProtected/PdfRecommendations#PDF_uncertainty_prescriptions and https://twiki.cern.ch/twiki/bin/view/AtlasProtected/PmgSystematicUncertaintyRecipes.
In particular, if you are using your own ntuples, you need to make sure you are normalising the weights correctly, eg, following this prescription:
https://twiki.cern.ch/twiki/bin/view/AtlasProtected/PmgSystematicUncertaintyRecipes#On_the_fly_systematic_variations
Now that we are all on the same page, let's continue, and I hope that the tool saves you lots of time avoid re-inventing the wheel.
For clarifications and feature requests, please contact `lcorpe@cern.ch` or add a git issue to this repo.
# Instructions for submissionTool
See the detailed [Documentation](documentation/UsingTheSubmissionTool.md)
# Instructions for systematicsTool
See the detailed [Documentation](documentation/UsingTheSystematicsTool.md)
# Instructions for covarianceTool
See the detailed [Documentation](documentation/UsingTheCovarianceTool.md)
package PyUtils
author Louie Dartmoor Corpe <lcorpe@cern.ch>
use AtlasPolicy AtlasPolicy-*
use AtlasPython AtlasPython-* External -no_auto_imports
use AtlasPyROOT AtlasPyROOT-* External -no_auto_imports
use AtlasPyFwdBwdPorts AtlasPyFwdBwdPorts-* External -no_auto_imports
use PyCmt PyCmt-* Tools -no_auto_imports
use Rivet Rivet-* External
use YODA YODA-* External
branches python bin
## some handy aliases
alias systematicsTool systematicsTool.py
private
apply_pattern declare_python_modules files="*.py AthFile scripts"
apply_pattern declare_scripts files="\
-s=$(PMGSystematicsTools_root)/bin \
systematicsTool.py \
"
end_private
This diff is collapsed.
# BEGIN PLOT /ExclusivePlusInclusive/d.
LeftMargin=1.9
LegendXPos=0.54
YLabelSep=8.0
RatioPlotYMin=0.4
RatioPlotYMax=1.6
RatioPlotYLabel=MC/Data
#RatioPlotYLabel=RIVET/ParticleLevel
Title=combined lepton channels
RatioPlotErrorBandColor=lightgray
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d01-x01-y01
RatioPlotYMin=0.7
RatioPlotYMax=1.3
XLabel=$p_{\text{T}}^{t,\text{had}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}}^{t,\text{had}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d01-x01-y02
RatioPlotYMin=0.65
RatioPlotYMax=1.35
XLabel=$p_{\text{T}}^{t\bar{t}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}^{t\bar{t}}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d01-x01-y03
RatioPlotYMin=0.75
RatioPlotYMax=1.25
XLabel=$|y_{t,\text{had}}|$
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}|y_{t,\text{had}}|}$ [pb]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d01-x01-y04
RatioPlotYMin=0.75
RatioPlotYMax=1.25
XLabel=$|y_{t\bar{t}}|$
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}|y_{t\bar{t}}|}$ [pb]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d01-x01-y05
RatioPlotYMin=0.475
RatioPlotYMax=1.525
XLabel=$m_{t\bar{t}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}m_{t\bar{t}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d02.
XLabel=$p_{\text{T}}^{t\bar{t}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}^{t\bar{t}}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d03
XLabel=$|p_{\text{out}}^{t\bar{t}}|$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}|p_{\text{out}}^{t\bar{t}}|}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d04
XLabel=$p_{\text{T}}^{t,\text{had}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}}^{t,\text{had}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d05
XLabel=$p_{\text{T}}^{t\bar{t}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}^{t\bar{t}}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d06
XLabel=$|p_{\text{out}}^{t\bar{t}}|$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}|p_{\text{out}}^{t\bar{t}}|}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d07
XLabel=$p_{\text{T}}^{t,\text{had}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}}^{t,\text{had}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d08
XLabel=$p_{\text{T}}^{t\bar{t}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}^{t\bar{t}}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d09
XLabel=$|p_{\text{out}}^{t\bar{t}}|$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}|p_{\text{out}}^{t\bar{t}}|}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d10
XLabel=$p_{\text{T}}^{t,\text{had}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}}^{t,\text{had}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d11
XLabel=$p_{\text{T}}^{t\bar{t}}$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}p_{\text{T}^{t\bar{t}}}}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
# BEGIN PLOT /ExclusivePlusInclusive/d12
XLabel=$|p_{\text{out}}^{t\bar{t}}|$ [GeV]
YLabel=$\dfrac{\text{d}\sigma^\text{fid}}{\text{d}|p_{\text{out}}^{t\bar{t}}|}$ [$\dfrac{\text{pb}}{\text{GeV}}$]
# END PLOT
This diff is collapsed.
#
mc15_13TeV:mc15_13TeV.363123.MGPy8EG_N30NLO_Zmumu_Ht0_70_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363124.MGPy8EG_N30NLO_Zmumu_Ht0_70_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363125.MGPy8EG_N30NLO_Zmumu_Ht0_70_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363127.MGPy8EG_N30NLO_Zmumu_Ht70_140_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363128.MGPy8EG_N30NLO_Zmumu_Ht70_140_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363126.MGPy8EG_N30NLO_Zmumu_Ht70_140_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363131.MGPy8EG_N30NLO_Zmumu_Ht140_280_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363129.MGPy8EG_N30NLO_Zmumu_Ht140_280_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363130.MGPy8EG_N30NLO_Zmumu_Ht140_280_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363134.MGPy8EG_N30NLO_Zmumu_Ht280_500_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363133.MGPy8EG_N30NLO_Zmumu_Ht280_500_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363132.MGPy8EG_N30NLO_Zmumu_Ht280_500_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363137.MGPy8EG_N30NLO_Zmumu_Ht500_700_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363136.MGPy8EG_N30NLO_Zmumu_Ht500_700_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363135.MGPy8EG_N30NLO_Zmumu_Ht500_700_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363138.MGPy8EG_N30NLO_Zmumu_Ht700_1000_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363140.MGPy8EG_N30NLO_Zmumu_Ht700_1000_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363139.MGPy8EG_N30NLO_Zmumu_Ht700_1000_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363142.MGPy8EG_N30NLO_Zmumu_Ht1000_2000_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363141.MGPy8EG_N30NLO_Zmumu_Ht1000_2000_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363143.MGPy8EG_N30NLO_Zmumu_Ht1000_2000_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363144.MGPy8EG_N30NLO_Zmumu_Ht2000_E_CMS_CVetoBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363145.MGPy8EG_N30NLO_Zmumu_Ht2000_E_CMS_CFilterBVeto.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363146.MGPy8EG_N30NLO_Zmumu_Ht2000_E_CMS_BFilter.evgen.EVNT.e4649
mc15_13TeV:mc15_13TeV.363150.MGPy8EG_N30NLO_Zee_Ht70_140_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363160.MGPy8EG_N30NLO_Zee_Ht500_700_CFilterBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363157.MGPy8EG_N30NLO_Zee_Ht280_500_CFilterBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363158.MGPy8EG_N30NLO_Zee_Ht280_500_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363152.MGPy8EG_N30NLO_Zee_Ht70_140_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363155.MGPy8EG_N30NLO_Zee_Ht140_280_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363163.MGPy8EG_N30NLO_Zee_Ht700_1000_CFilterBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363166.MGPy8EG_N30NLO_Zee_Ht1000_2000_CFilterBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363149.MGPy8EG_N30NLO_Zee_Ht0_70_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363148.MGPy8EG_N30NLO_Zee_Ht0_70_CFilterBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363167.MGPy8EG_N30NLO_Zee_Ht1000_2000_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363168.MGPy8EG_N30NLO_Zee_Ht2000_E_CMS_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363161.MGPy8EG_N30NLO_Zee_Ht500_700_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363151.MGPy8EG_N30NLO_Zee_Ht70_140_CFilterBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363170.MGPy8EG_N30NLO_Zee_Ht2000_E_CMS_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363162.MGPy8EG_N30NLO_Zee_Ht700_1000_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363164.MGPy8EG_N30NLO_Zee_Ht700_1000_BFilter.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363169.MGPy8EG_N30NLO_Zee_Ht2000_E_CMS_CFilterBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363165.MGPy8EG_N30NLO_Zee_Ht1000_2000_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363156.MGPy8EG_N30NLO_Zee_Ht280_500_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363153.MGPy8EG_N30NLO_Zee_Ht140_280_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363159.MGPy8EG_N30NLO_Zee_Ht500_700_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363147.MGPy8EG_N30NLO_Zee_Ht0_70_CVetoBVeto.evgen.EVNT.e4866
mc15_13TeV:mc15_13TeV.363154.MGPy8EG_N30NLO_Zee_Ht140_280_CFilterBVeto.evgen.EVNT.e4866
#
mc15_13TeV:mc15_13TeV.361513.MadGraphPythia8EvtGen_A14NNPDF23LO_Ztautau_Np3.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361510.MadGraphPythia8EvtGen_A14NNPDF23LO_Ztautau_Np0.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361511.MadGraphPythia8EvtGen_A14NNPDF23LO_Ztautau_Np1.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361514.MadGraphPythia8EvtGen_A14NNPDF23LO_Ztautau_Np4.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361512.MadGraphPythia8EvtGen_A14NNPDF23LO_Ztautau_Np2.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361516.MadGraphPythia8EvtGen_A14NNPDF23LO_Znunu_Np1.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361518.MadGraphPythia8EvtGen_A14NNPDF23LO_Znunu_Np3.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361515.MadGraphPythia8EvtGen_A14NNPDF23LO_Znunu_Np0.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361519.MadGraphPythia8EvtGen_A14NNPDF23LO_Znunu_Np4.evgen.EVNT.e3898
mc15_13TeV:mc15_13TeV.361517.MadGraphPythia8EvtGen_A14NNPDF23LO_Znunu_Np2.evgen.EVNT.e3898
#
mc15_13TeV:mc15_13TeV.363607.MGPy8EG_N30NLO_Wenu_Ht140_280_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363605.MGPy8EG_N30NLO_Wenu_Ht70_140_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363620.MGPy8EG_N30NLO_Wenu_Ht1000_2000_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363610.MGPy8EG_N30NLO_Wenu_Ht280_500_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363614.MGPy8EG_N30NLO_Wenu_Ht500_700_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363623.MGPy8EG_N30NLO_Wenu_Ht2000_E_CMS_BFilter.evgen.EVNT.e4835
mc15_13TeV:mc15_13TeV.363613.MGPy8EG_N30NLO_Wenu_Ht500_700_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363606.MGPy8EG_N30NLO_Wenu_Ht140_280_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363615.MGPy8EG_N30NLO_Wenu_Ht700_1000_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363618.MGPy8EG_N30NLO_Wenu_Ht1000_2000_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363622.MGPy8EG_N30NLO_Wenu_Ht2000_E_CMS_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363619.MGPy8EG_N30NLO_Wenu_Ht1000_2000_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363616.MGPy8EG_N30NLO_Wenu_Ht700_1000_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363602.MGPy8EG_N30NLO_Wenu_Ht0_70_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363611.MGPy8EG_N30NLO_Wenu_Ht280_500_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363608.MGPy8EG_N30NLO_Wenu_Ht140_280_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363609.MGPy8EG_N30NLO_Wenu_Ht280_500_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363604.MGPy8EG_N30NLO_Wenu_Ht70_140_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363617.MGPy8EG_N30NLO_Wenu_Ht700_1000_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363612.MGPy8EG_N30NLO_Wenu_Ht500_700_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363621.MGPy8EG_N30NLO_Wenu_Ht2000_E_CMS_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363600.MGPy8EG_N30NLO_Wenu_Ht0_70_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363603.MGPy8EG_N30NLO_Wenu_Ht70_140_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363623.MGPy8EG_N30NLO_Wenu_Ht2000_E_CMS_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363601.MGPy8EG_N30NLO_Wenu_Ht0_70_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363629.MGPy8EG_N30NLO_Wmunu_Ht70_140_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363642.MGPy8EG_N30NLO_Wmunu_Ht1000_2000_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363632.MGPy8EG_N30NLO_Wmunu_Ht140_280_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363638.MGPy8EG_N30NLO_Wmunu_Ht500_700_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363645.MGPy8EG_N30NLO_Wmunu_Ht2000_E_CMS_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363634.MGPy8EG_N30NLO_Wmunu_Ht280_500_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363641.MGPy8EG_N30NLO_Wmunu_Ht700_1000_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363640.MGPy8EG_N30NLO_Wmunu_Ht700_1000_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363633.MGPy8EG_N30NLO_Wmunu_Ht280_500_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363628.MGPy8EG_N30NLO_Wmunu_Ht70_140_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363646.MGPy8EG_N30NLO_Wmunu_Ht2000_E_CMS_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363626.MGPy8EG_N30NLO_Wmunu_Ht0_70_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363624.MGPy8EG_N30NLO_Wmunu_Ht0_70_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363644.MGPy8EG_N30NLO_Wmunu_Ht1000_2000_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363647.MGPy8EG_N30NLO_Wmunu_Ht2000_E_CMS_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363639.MGPy8EG_N30NLO_Wmunu_Ht700_1000_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363627.MGPy8EG_N30NLO_Wmunu_Ht70_140_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363625.MGPy8EG_N30NLO_Wmunu_Ht0_70_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363630.MGPy8EG_N30NLO_Wmunu_Ht140_280_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363635.MGPy8EG_N30NLO_Wmunu_Ht280_500_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363643.MGPy8EG_N30NLO_Wmunu_Ht1000_2000_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363637.MGPy8EG_N30NLO_Wmunu_Ht500_700_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363636.MGPy8EG_N30NLO_Wmunu_Ht500_700_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363631.MGPy8EG_N30NLO_Wmunu_Ht140_280_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363659.MGPy8EG_N30NLO_Wtaunu_Ht280_500_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363660.MGPy8EG_N30NLO_Wtaunu_Ht500_700_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363652.MGPy8EG_N30NLO_Wtaunu_Ht70_140_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363658.MGPy8EG_N30NLO_Wtaunu_Ht280_500_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363653.MGPy8EG_N30NLO_Wtaunu_Ht70_140_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363661.MGPy8EG_N30NLO_Wtaunu_Ht500_700_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363651.MGPy8EG_N30NLO_Wtaunu_Ht70_140_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363670.MGPy8EG_N30NLO_Wtaunu_Ht2000_E_CMS_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363664.MGPy8EG_N30NLO_Wtaunu_Ht700_1000_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363663.MGPy8EG_N30NLO_Wtaunu_Ht700_1000_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363669.MGPy8EG_N30NLO_Wtaunu_Ht2000_E_CMS_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363655.MGPy8EG_N30NLO_Wtaunu_Ht140_280_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363648.MGPy8EG_N30NLO_Wtaunu_Ht0_70_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363671.MGPy8EG_N30NLO_Wtaunu_Ht2000_E_CMS_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363662.MGPy8EG_N30NLO_Wtaunu_Ht500_700_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363668.MGPy8EG_N30NLO_Wtaunu_Ht1000_2000_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363667.MGPy8EG_N30NLO_Wtaunu_Ht1000_2000_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363650.MGPy8EG_N30NLO_Wtaunu_Ht0_70_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363649.MGPy8EG_N30NLO_Wtaunu_Ht0_70_CFilterBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363654.MGPy8EG_N30NLO_Wtaunu_Ht140_280_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363665.MGPy8EG_N30NLO_Wtaunu_Ht700_1000_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363656.MGPy8EG_N30NLO_Wtaunu_Ht140_280_BFilter.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363657.MGPy8EG_N30NLO_Wtaunu_Ht280_500_CVetoBVeto.evgen.EVNT.e4944
mc15_13TeV:mc15_13TeV.363666.MGPy8EG_N30NLO_Wtaunu_Ht1000_2000_CVetoBVeto.evgen.EVNT.e4944
dataset_number/I:physics_short/C:crossSection/D:genFiltEff/D:kFactor/D:relUncert/D:generator_name/C
300000 Pythia8BPhotospp_A14_CTEQ6L1_pp_Jpsimu2p5mu2p5 3498900.0 1.0000E+00 1.0 0.0 Pythia8B+Photospp
410646 PowhegPythia8EvtGen_A14_Wt_DR_inclusive_top 0.037937 1.0000E+00 1.0 0.0 PowhegPythia8
410659 PhPy8EG_A14_tchan_BW50_lept_antitop 0.022175 1.0000E+00 1.0 0.0 PowhegPythia8