Getting Started#

Installation#

Git clone the project and work with the v0.0.1

git clone https://github.com/giorgiopizz/mkShapesRDF.git
git checkout v0.0.1

Lxplus is currently the suggested machine to work with. In general one should need cvmfs with sft.cern.ch and cms.cern.ch.

Automatic installation#

mkShapesRDF has its own install script: install.sh: it first sources the correct python environment (it should contain a recent python3 and ROOT bindings) and then proceeds with the creation of a virtual environment myenv where all the needed packages and the framework scripts will be installed.

You’re free to change the environment with conda/mamba insted of a LCG release inside install.sh.

When you’re ready just run:

./install.sh

It will create a start.sh script that should be run everytime to activate the environment.

Manual installation#

In order to install the package it’s first necessary to source the right LCG release:

source /cvmfs/sft.cern.ch/lcg/views/LCG_103/x86_64-centos7-gcc11-opt/setup.sh

now the right python version (3.9) and it’s bindings with ROOT are setup. It’s highly reccomended to create a virtual environment for the installation:

python -m venv --system-site-packages myenv

and of course activate it:

source myenv/bin/activate

Now you can proceed to the simple installation:

pip install -e .[docs,dev]

Now to work with mkShapes.processor one should also install correctionlib and compile it:

python -m pip install --no-binary=correctionlib correctionlib

From now on, when you will login again on that machine you will just have to run the setup command:

source start.sh

Another step needed when using the processor is to download the jsonpog-integration folder:

wget https://gpizzati.web.cern.ch/mkShapesRDF/jsonpog-integration.tar.gz
tar -xzvf jsonpog-integration.tar.gz
rm -r jsonpog-integration.tar.gz
mv jsonpog-integration mkShapesRDF/processor/data/

Shape analysis: Run the analysis with the provided example#

Configure the configuration folder (e.g. `examples/2016Real`)#

Documentation on the configuration folder structure at the configuration folder structure.

Compile the configuration folder#

Inside a configuration folder one can compile it into .json and .pkl. The compiled version are used across all the operating modes of mkShapesRDF

mkShapesRDF -c 1

Run the analysis#

mkShapesRDF -o 0 -f . -b 1

-o indicates the operationMode: - 0 run analysis - 1 check batch output and errs - 2 merge root files

For the provided example (2016Real) it’s estimated an execution time of ~ 10 mins running on lxbatch (condor on lxplus) @ CERN when disabling nuisances.

It’s highly recommended to limit input ROOT files at the first run to check for errors. The following command will only take 1 event for each sample type:

mkShapesRDF -o 0 -f . -l 1

Check for errors#

After all the jobs finished (or most of them did) you can run mkShapesRDF -o 1 -f . to know which jobs failed and why.

One can resubmit failed jobs with mkShapesRDF -o 1 -f . -r 1.

While if one wants to resubmit jobs that are still running, the option -r 2 should be used.

Merge files#

If all the jobs succeeded run the merger with the option:

mkShapesRDF -o 2 -f .

Plots#

Plot with

mkPlot

which will create the plots to the specified paths provided in configuration.py

Processor: run the post processing#

Coming soon