SModelS stores all the information about the experimental results in the Database. The Database is organized as files in an ordinary (UNIX) directory hierarchy, with a thin Python layer serving as the access to the database. The overall structure of the directory hierarchy and its contents is depicted in the scheme below:
The complete list of analyses and results included in the database can be consulted at https://smodels.github.io/docs/ListOfAnalyses. We note that all the results in the official database release have been carefully validated and the validation material can be found at https://smodels.github.io/docs/Validation.
The database can conveniently be updated independently from SModelS code updates. It suffices to download or clone this repository to a local folder and correctly set the SModelS database path when running SModelS. Alternatively, from SModelS v1.1.3 onwards, the database path can be specified as an URL, e.g. https://smodels.github.io/database/official300, and the binary database file will be automatically downloaded and used. This is often faster than building the binary file from the database folder and avoids possible machine dependencies. The database URLs can be found in the releases page. For more information check the SModelS online manual.
For some efficiency map results with a large number of signal regions, the official SModelS database is shipped with a reduced number of (aggregated) signal regions. However, the non-aggregated versions of the results are stored as a tarball on the top level of the database folder; for v3.0.0 this is nonaggregated300.tar.gz. To use them, simply expand this tarball in the directory:
cd <smodels-database folder> tar -xzvf nonaggregated300.tar.gz
The database will then be re-built accordingly upon first usage and include the non-aggregated results. The user has to be aware, however, that both the aggregated and non-aggregated results will be displayed in the output.
The official SModelS database can be augmented with data from the fastlim results. For using SModelS with the text database, a tarball with the properly converted fastlim-1.0 efficiency maps can be found in the smodels-database folder. The tarball then needs to be exploded in the top level directory of the database:
cd <smodels-database folder> tar -xzvf smodels-v1.1-fastlim-1.0.tgz rm smodels-v1.1-fastlim-1.0.tgz
Once the fastlim folders have been added to the database, SModelS auto-detects fastlim results and issues an acknowledgement.
As mentioned above, from SModelS v1.1.3 onwards it is also possible to directly download the database binary file using the URLs provided in the releases page . Separate URLs are provided for the database including the Fastlim maps, so the user can choose which database to use.
When using fastlim results, please properly cite the fastlim paper; for convenience, a bibtex file is provided in the smodels-fastlim tarball.
Adding additional experimental results is a matter of copying and editing text files. Once the new folders and files have been added following the database structure format, SModelS automatically rebuilds the binary (Pickle) database file. The added results will then be available for use with SModelS.
For citing the experimental analyses in the database, you can use database.bib.