Examples.rst

How To's

How To's

Below we provide a few examples for using SModelS and some of the SModelS tools <smodelsTools> as a Python library¹.

To try out the examples in interactive mode:

Main examples:

• How to run SModelS using a parameter file (download the Python code here <recipes/runWithParameterFile.py>, IPython notebook here <recipes/runWithParameterFile.ipynb>)
• How to run SModelS as a python library (download the Python code here <recipes/runAsLibrary.py>, IPython notebook here <recipes/runAsLibrary.ipynb>)

Examples displaying several functionalities:

• How to load the database (download the Python code here <recipes/load_database.py>, IPython notebook here <recipes/load_database.ipynb>)
• How to obtain experimental upper limits (download the Python code here <recipes/lookup_upper_limit.py>, IPython notebook here <recipes/lookup_upper_limit.ipynb>)
• How to obtain experimental efficiencies (download the Python code here <recipes/lookup_efficiency.py>, IPython notebook here <recipes/lookup_efficiency.ipynb>)
• How to print decomposition results (download the Python code here <recipes/print_decomposition.py>, IPython notebook here <recipes/print_decomposition.ipynb>)
• How to print theory predictions (download the Python code here <recipes/print_theoryPrediction.py>, IPython notebook here <recipes/print_theoryPrediction.ipynb>)
• How to compare theory predictions with experimental limits (download the Python code here <recipes/compareUL.py>, IPython notebook here <recipes/compareUL.ipynb>)
• How to compute the likelihood and chi2 for a theory predictions (download the Python code here <recipes/compute_likelihood.py>, IPython notebook here <recipes/compute_likelihood.ipynb>)
• How to find missing topologies (download the Python code here <recipes/missingTopologies.py>, IPython notebook here <recipes/missingTopologies.ipynb>)
• How to generate ascii graphs (download the Python code here <recipes/ascii_graph_from_lhe.py>, IPython notebook here <recipes/ascii_graph_from_lhe.ipynb>)
• How to marginalize a combined limit instead of profiling it (download the Python code here <recipes/marginalize.py>, IPython notebook here <recipes/marginalize.ipynb>)

Examples using the cross-section computer:

• How to compute leading order cross sections (for MSSM) (download the Python code here <recipes/lo_xsecs_from_slha.py>, IPython notebook here <recipes/lo_xsecs_from_slha.ipynb>)
• How to compute next-to-leading order cross sections (for MSSM) (download the Python code here <recipes/nll_xsecs_from_slha.py>, IPython notebook here <recipes/nll_xsecs_from_slha.ipynb>)

Examples using the Database Browser

• How to obtain upper limits (download the Python code here <recipes/browserExample2.py>, IPython notebook here <recipes/browserExample2.ipynb>)
• How to select specific results (download the Python code here <recipes/browserExample3.py>, IPython notebook here <recipes/browserExample3.ipynb>)

Examples using the Interactive Plots tool

• How to make interactive plots (download the Python code here <recipes/interactivePlotsExample.py>, IPython notebook here <recipes/interactivePlotsExample.ipynb>)

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1. Some of the output may change depending on the database version used.↩