order 0.1.17

Pythonic class collection that helps you structure external data from LHC / HEP experiments.

If you're designing a high-energy physics analysis (e.g. with data recorded with an LHC experiment at CERN), manual bookkeeping of external data can get complicated quite fast. order provides a Python class collection that helps you structuring

• analyses,
• MC campaigns,
• datasets,
• cross sections,
• channels,
• categories,
• systematics, and
• models for statistical inference.

Getting started

See the intro.ipynb notebook for an introduction to the most important classes and an example setup of a small analysis.

You can find the full API documentation on readthedocs..

Installation and dependencies

Via pip:

pip install order

Currently, the only dependencies of the core classes are scinum and six, which are also installed with the above command.

Contributing

If you like to contribute, I'm happy to receive pull requests. Just make sure to add a new test cases and run them via:

> python -m unittest tests

Testing

In general, tests should be run for different environments:

• Python 2.7
• Python 3.5
• Python 3.6

Docker

To run tests in a docker container, do:

git clone https://github.com/riga/order.git
cd order

docker run --rm -v `pwd`:/root/order -w /root/order python:3.6 /bin/bash -c "\
	pip install -r requirements.txt; python -m unittest tests"

Development

• Source hosted at GitHub
• Report issues, questions, feature requests on GitHub Issues

Authors

• Marcel R.

License

The MIT License (MIT)

Copyright (c) 2018 Marcel R.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.