Utilities to combine correlated physics measurement results
Project description
Combination Code
This is a generic averaging code to combine an arbitrary set of (experimental) results under consideration of the statistical errors and their correlations, and systematic errors and correlations, both between the parameters of one measurement and different measurements. The code documentation providing detailed instructions to the example code is available here.
A tutorial is available here
Installation
Install with `pip in a virtual environment
python3 -m venv coco-env
cd coco-env
source bin/activate
python -m pip install combination-code
Doucumentation and examples are available in share/combination-code
The Python package is exposed as:
from combination_code import ResultList, ResultSet, readResultListJSON
Development
Install the package in editable mode with development tooling:
python3 -m venv coco-env
cd coco-env
source bin/activate
git clone ssh://git@gitlab.cern.ch:7999/hflav/shared/combination-code.git
cd combination-code
pip install -e .[dev]
Run all tests (unit + system):
pytest
Test Suite
The repository includes two test layers:
- Unit tests in
tests/unit/for core APIs inResultSet,ResultList, andIntercorrelationMaps. - System tests in
tests/system/that execute tutorial examples fromtutorial/Example1,tutorial/Example2, andtutorial/Example3and validate expected output artifacts.
System tests force a non-interactive Matplotlib backend (Agg) so they run reliably in CI.
Continuous Integration
GitHub Actions workflow build.yml now:
- Runs the test suite on Python 3.10 and 3.14.
- Produces coverage output via
pytest-cov. - Uploads
coverage.xmlas a CI artifact.
Build and release (PyPI)
This is done via Gitlab CI. Simply create a new release with the for vX.Y.Z format following semantic versioning.
Project details
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