# How To’s¶

Below a few examples are given for how to utilize SModelS and some of the SModelS tools as a Python library [*]:

- How to load the database (download the Python code
`here`

, IPython notebook`here`

) - How to obtain experimental upper limits (download the Python code
`here`

, IPython notebook`here`

) - How to obtain experimental efficiencies (download the Python code
`here`

, IPython notebook`here`

) - How to compute leading order cross sections (for MSSM) (download the Python code
`here`

, IPython notebook`here`

) - How to compute next-to-leading order cross sections (for MSSM) (download the Python code
`here`

, IPython notebook`here`

) - How to print decomposition results (download the Python code
`here`

, IPython notebook`here`

) - How to print theory predictions (download the Python code
`here`

, IPython notebook`here`

) - How to compare theory predictions with experimental limits (download the Python code
`here`

, IPython notebook`here`

) - How to compute the likelihood and chi2 for a theory predictions (download the Python code
`here`

, IPython notebook`here`

) - How to find missing topologies (download the Python code
`here`

, IPython notebook`here`

) - How to generate ascii graphs (download the Python code
`here`

, IPython notebook`here`

) - How to marginalize a combined limit instead of profiling it (download the Python code
`here`

, IPython notebook`here`

)

## Examples using the Database Browser¶

- How to obtain upper limits (download the Python code
`here`

, IPython notebook`here`

) - How to select specific results (download the Python code
`here`

, IPython notebook`here`

)

## Examples using the Interactive Plots tool¶

- How to make interactive plots (download the Python code
`here`

, IPython notebook`here`

)

[*] | Some of the output may change depending on the database version used. |