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allow passing mask to clustervector (#304)
- passing mask to ClusterVector 
- creates a copy of the ClusterVector

Co-authored-by: Erik Fröjdh <erik.frojdh@psi.ch>
2026-04-17 17:13:02 +02:00
2026-01-20 17:20:48 +01:00
2024-11-11 19:59:55 +01:00
2025-03-20 12:52:04 +01:00
2025-11-20 09:01:28 +01:00

aare

Data analysis library for PSI hybrid detectors

Documentation

Detailed documentation including installation can be found in Documentation

License

This project is licensed under the MPL-2.0 license. See the LICENSE file or https://www.mozilla.org/en-US/MPL/ for details.

Build and install

Prerequisites

  • cmake >= 3.14
  • C++17 compiler (gcc >= 8)
  • python >= 3.10

Development install (for Python)

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

Install using conda/mamba

#enable your env first!
conda install aare -c slsdetectorgroup # installs latest version

Install to a custom location and use in your project

Working 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_PATH

Local build of conda pkgs

conda build . --variants="{python: [3.11, 3.12, 3.13]}"

Developer's guide

We are looking forward to your contributions via pull requests!

If you want to fix an existing bug or propose a new feature:

  1. Install pre-commit python package and setup it pre-commit install
  2. Create a new branch with git branch branch_name
  3. Implement your changes and make a commit (pre-commit will check your code automatically)
  4. Push your commit and open a pull request if needed
Description
Mirrored from github
Readme MPL-2.0 120 MiB
Languages
Jupyter Notebook 76.4%
C++ 20.8%
Python 2%
CMake 0.8%