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cms-ptmiss-ml

Setup

Requires miniconda (Python 3.7). Install as follows:

curl -OL https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

After installation, install the environment using environment.yml included in this repository:

conda env create --file=environment.yml

For recurrent setup, also do the following or add the equivalent lines in a setup.sh script:

conda init <shell>

Activate the environment before running:

conda activate tf_gpu

Running

Example training command (mind that using inputs from eos can be very slow):

python -i train_ptmiss.py -i /eos/user/s/steggema/ptmiss/dy_pf_chunk56.h5 --embedding

In order to run over a large number of samples, mixing different processes, create a "virtual hdf5" index file, and then run it with the command above:

python create_virtual_hd5.py -i /tmp/${USER}/dy_pf_chunk60.h5,/tmp/${USER}/tt_pf_chunk240.h5,/tmp/${USER}/dy_pf_chunk59.h5,/tmp/${USER}/tt_pf_chunk249.h5 -o out_20190930_v1.h5 -d X,X_c_0,X_c_1,X_c_2,Y,Z

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Original keras-based DeepMET training code

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