This is a Python wrapper of RooUnfold, plus a toolkit for bias, toy test, and converter for dataframe etc. which are commonly used in Python.
- Please make sure RooUnfold has been installed before using PyRooUnfold.
If not, please first follow the steps to install RooUnfold https://gitlab.cern.ch/RooUnfold/RooUnfold/-/blob/master/README.md
or, use a pre-installed RooUnfold (e.g. from CVMFS).
- After installing RooUnfold, please set the environment variable for your RooUnfold libary as
export ROOUNFOLD_PATH="/path/for/your/libRooUnfold.so"
e.g. in my case
export ROOUNFOLD_PATH="/Users/caolu/Workspace/RooUnfold/libRooUnfold.so"
or using CVMFS version provided as externals of Belle-II software
export ROOUNFOLD_PATH="/cvmfs/belle.cern.ch/el9/externals/v02-02-01/Linux_x86_64/common/lib/libRooUnfold.so"
- To install PyRooUnfold, you can first check out the needed version, e.g.
git checkout -b v2.0.0
and then install the package via
pip install .
If install via setup.py, you need to include the package into your python library
export PYTHONPATH=$PYTHONPATH:<path-of-PyrooUnfold>
- A hands-on introduction and a simple demo Jupyter notebook can be found in ./example folder.
- v1.0.0: compatible with RooUnfold 2.0.1
- v2.0.0: compatible with RooUnfold 3.0.0
Details of RooUnfold can be found at https://gitlab.cern.ch/RooUnfold/RooUnfold and an older version at http://hepunx.rl.ac.uk/~adye/software/unfold/RooUnfold.html
This project has been set up using PyScaffold 3.1. For details and usage information on PyScaffold see https://pyscaffold.org/.