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STEP 1
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To run this set of tutorial examples, you need data-science python libraries installed
on your computers. You have two options

1) if you have a CERN account + CERNbox you can move all files on your CERNbox area
and use SWAN 

2) if you don't (or if you want to run locally), you need to have python installed, 
with a python library manager and install the following 

jupyter
numpy
glob
h5py
matplotlib
scikit-learn
keras
tensorflow (see below)

FOR TENSORFLOW: there are two versions of tensorflow. If your computer has an nvidia  GPU,
you should install tensorflow-gpu. For this to work ok, you need to have cuda drivers installed
(you can check this running the command 

nvidia-smi

If the command gives anything other than an error (e.g., command not found), this means that
you have a working GPU and you are ready to go)

Otherwise, just install plain tensorflow (i.e., no -gpu)

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STEP 2
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To start running the software, get a copy of the directory at this URL

https://www.dropbox.com/s/vxdz9x8lrf6of0p/CHIPP_19_EPISODE_I.tar.gz?dl=0

Then you can do

tar -xzf CHIPP_19_EPISODE_I.tar.gz 
cd CHIPP_19_EPISODE_I

and start the jupyer notebook

jupyter-notebook

Open the .ipynb file in the jupyer/ folder, by clicking on it

To execute a cell in the notebook, you need to do shift+enter