Data analysis library for PSI hybrid detectors
Detailed documentation including installation can be found in Documentation
This project is licensed under the MPL-2.0 license. See the LICENSE file or https://www.mozilla.org/en-US/MPL/ for details.
Prerequisites
- cmake >= 3.14
- C++17 compiler (gcc >= 8)
- python >= 3.10
git clone git@github.com:slsdetectorgroup/aare.git --branch=v1 #or using http...
mkdir build
cd build
#configure using cmake
cmake ../aare -DAARE_PYTHON_BINDINGS=ON
#build (replace 4 with the number of threads you want to use)
make -j4 Now you can use the Python module from your build directory
import aare
f = aare.File('Some/File/I/Want_to_open_master_0.json')To run from other folders either add the path to your conda environment using conda-build or add the module to your PYTHONPATH
export PYTHONPATH=path_to_aare/aare/build:$PYTHONPATH#enable your env first!
conda install aare -c slsdetectorgroup # installs latest versionWorking example in: https://github.com/slsdetectorgroup/aare-examples
#build and install aare
git clone git@github.com:slsdetectorgroup/aare.git --branch=v1 #or using http...
mkdir build
cd build
#configure using cmake
cmake ../aare -DCMAKE_INSTALL_PREFIX=/where/to/put/aare
#build (replace 4 with the number of threads you want to use)
make -j4
#install
make install
#Now configure your project
cmake .. -DCMAKE_PREFIX_PATH=SOME_PATHconda build . --variants="{python: [3.11, 3.12, 3.13]}"We are looking forward to your contributions via pull requests!
If you want to fix an existing bug or propose a new feature:
- Install
pre-commitpython package and setup itpre-commit install - Create a new branch with
git branch branch_name - Implement your changes and make a commit (
pre-commitwill check your code automatically) - Push your commit and open a pull request if needed