The Python package puma provides a plotting API for commonly used plots in flavour tagging.
| ROC curves | Histogram plots | Variable vs efficiency |
|---|---|---|
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puma can be installed from PyPI or using the latest code from this repository.
pip install puma-hepThe installation from PyPI only allows to install tagged releases, meaning you can not
install the latest code from this repo using the above command.
If you just want to use a stable release of puma, this is the way to go.
pip install https://github.com/umami-hep/puma/archive/main.tar.gzThis will install the latest version of puma, i.e. the current version
from the main branch (no matter if it is a release/tagged commit).
If you plan on contributing to puma and/or want the latest version possible, this
is what you want.
The Docker images are built on GitHub and contain the latest version from the main branch.
The container registry with all available tags can be found here.
The puma:latest image is based on python:3.8.15-slim and is meant for users who want to use the latest version of puma. For each release, there is a corresponding tagged image.
You can start an interactive shell in a container with your current working directory
mounted into the container by using one of the commands provided below.
On a machine with Docker installed:
docker run -it --rm -v $PWD:/puma_container -w /puma_container gitlab-registry.cern.ch/atlas-flavor-tagging-tools/training-images/puma-images/puma:latest bashOn a machine/cluster with singularity installed:
singularity shell -B $PWD docker://gitlab-registry.cern.ch/atlas-flavor-tagging-tools/training-images/puma-images/puma:latestFor development, just replace the tag of the image:
latest -> latest-dev
In addition to the minimal requirements that are required to use puma, the
puma:latest-dev image has the requirements.txt from the puma repo installed as
well.
This means that packages like pytest, black, pylint, etc. are installed as well.
However, note that puma itself is not installed in that image such that the dev-version
on your machine can be used/tested.
The images are automatically updated via GitHub and pushed to this repository registry.


