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parameters.ini
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parameters.ini
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#Select running mode
[options]
checkInput = True ;Set True to check the input file for possible errors
doInvisible = True ;Set True if invisible compression should be performed, False elsewise
doCompress = True ;Set True if mass compression should be performed, False elsewise
testCoverage = True ;Set True if topologies not covered by experiments (missing topologies) should be identified, False otherwise
computeStatistics = True ;Set True to compute the likelihoods L_BSM, L_SM and L_max for EM-type results.
combineSRs = True ;Set True to combine signal regions when covariance matrix or pyhf JSON likelihood is available. Caution, increases runtime! False uses only best SR (faster).
#combineAnas = ATLAS-SUSY-2019-08,ATLAS-SUSY-2019-09 ; list of statistically independent analyses to combine. Works for EM-type results only. Use with care!
pyhfbackend = pytorch ;Define pyhf backend used, one of: numpy (default), pytorch, tensorflow, jax. WARNING: if backend specified is not found, we fall back to numpy!
reportAllSRs = False ;Set True to report all signal regions, instead of best signal region only.
experimentalFeatures = False ;Set True to enable experimental features that are not yet considered part of SModelS proper. Use only if you know what you are doing!!
[particles]
model=share.models.mssm ; path to the BSM model file. It can be a python module with definition of BSM particles or a SLHA file with QNUMBERS blocks. If omitted, we search in the current working directory as well as "smodels/share/models". MSSM is the default.
promptWidth = 1e-11 ; All particles with widths (in GeV) above this value are considered prompt
stableWidth = 1e-25 ; All particles with widths (in GeV) below this value are considered stable
#ignorePromptQNumbers = spin,eCharge,colordim ; Quantum numbers to be erased for promptly decaying particles (more inclusive results, but not always valid)
#Select input parameters
[parameters]
sigmacut = 0.005 ;Give minimum cross section value [fb] considered in SLHA decomposition (relevant for SLHA decomposition and detection of missing topologies)
minmassgap = 5. ;Give minimum mass gap [GeV] for mass compression
maxcond = 0.2 ;Maximum relative violation of conditions for valid results
ncpus = 1 ;Give number of cores used when running in parallel (integer, -1 means all available CPUs are used). Warning: do not change unless you know what you are doing!
#Select database analyses
[database]
path = official ; URL to the database pickle file (it will be downloaded)
#can be extended by: +fastlim (adds fastlim results), +superseded (adds superseded results), +nonaggregated (adds results with non-aggregated SRs in addition to the aggregated results), +full_llhds (replaces simplified HistFactory likelihoods by full ones).
# examples: path = official+nonaggregated, path = official+full_llhds
analyses = all ;Set all to use all analyses included in the database
#to use only specific analyses, give a list of the names separated by comma
# analyses = CMS-PAS-SUS-13-008, CMS-SUS-13-013,ATLAS-CONF-2013-024,ATLAS-SUSY-2013-04
# Wildcards are understood as in shell-expansion of file names: * ? [<list of letters>]
# Filter centre-of-mass energy with suffix beginning with a colon, in unum-style, like :13*TeV
# Note that the asterisk in the suffix is not a wildcard.
txnames= all ;Set all to use all constraints included in the database
#to use only specific constraints, give a list of the names separated by comma
#txnames = T2,T1,TChiWZ
# Wildcards are understood as in shell-expansion of file names: * ? [<list of letters>]
dataselector= all ; Set all to use all upper limit and efficiency maps results in the database. Set to upperLimit (efficiencyMap) to use only UL (EM) results:
#dataselector = efficiencyMap
#It can also be used to select specific datasets (signal regions) from efficiency map results. For the latter provide a list of the desired dataset ids
#dataselector = SRA mCT150,SRA mCT200
# Wildcards are understood as in shell-expansion of file names: * ? [<list of letters>]
#Settings for result printout
[printer]
outputType = summary, python ;Define the output formats
#available output formats: summary, stdout, log, python, xml, slha (type log redirects stdout in *.log output file)
outputFormat = version3 ; Define output format
#available output formats: current (latest format), version2 (SModelS 2.x format using bracket notation)
#options for stdout and log format
[stdout-printer]
printDatabase = False ;Set True to print the list of selected experimental results to stdout, False elsewise
addAnaInfo = False ;Set True to add detailed information about each experimental result selected, False elsewise. Only used if printDatabase = True
printDecomp = False ;Set True to print a table of all topologies generated by decomposition, False elsewise
addSMSInfo = False ;Set True to print a list of all SMS generated by decomposition, False elsewise. Note that not all the SMS appearing in this table are constrained by experiments. Only used if printDecomp = True
printExtendedResults = False ;Set True to print detailed information about the experimental constraints, False to print a shorter version
addCoverageID = False ;Set True to print the ID of the SMS not constrained by the experimental constraints. Only used if testCoverage=True
#options for summary printer
[summary-printer]
expandedSummary = True ;Set True to print to file all applicable analyses, False for only the strongest result
#options for slha printer
[slha-printer]
expandedOutput = True ; Set True to print the full list of results. If False will only print the most constraining result for non-excluded points or all the excluding results for excluded points.
#options for python printer
[python-printer]
addSMSList = False ;Set True to print full list of SMS to python and xml format, False elsewise. Note that these are all SMS after decomposition and the list can be very long.
addTxWeights = False ; Set True to print the contribution from individual topologies to each theory prediction.
#options for xml printer
[xml-printer]
addSMSList = False ;Set True to print full list of SMS to python and xml format, False elsewise. Note that these are all SMS after decomposition and the list can be very long.
addTxWeights = False ; Set True to print the contribution from individual topologies to each theory prediction.