INSTRUCTIONS FOR TUTORIAL 1
===========================

** Assuming you have followed the Pre-tutorial steps **

Requirements
------------

* Modules: FlavBit
* Scanners: diver
* Backends: SuperIso, HEPLike (Root)

Model
-----

* WC_lite.yaml (already in the yaml_files directory)
  Parameters: Re_DeltaC7, Re_Delta10
  Likelihoods: b2sgamma_LogLikelihood, B2mumu_LogLikelihood_Atlas, B2mumu_LogLikelihood_CMS, B2mumu_LogLikelihood_LHCb

Running scan
------------

* Run scan with various MPI process for speed

    mpirun -np 4 ./gambit -f yaml_files/WC_lite.yaml

  And just wait...

Check results
-------------

* Results are written in the "output" directory (e.g. runs/WC_lite/samples)

    h5ls runs/WC_lite/samples/WC.hdf5/WC

Plotting results
----------------

* To generate plots we use pippi
  Pippi file: WC_lite.pip

    ./pippi/pippi WC_lite.pip

* Best fit point is printed in the parse directory (e.g. runs/WC_lite/parse)

    less runs/WC_lite/parse/WC.best_all

* Plots are generated in the selected plots directory (e.g runs/WC_lite/plots)

    okular runs/WC_lite/plots/*