AliceMazzoleni99 e795310b16
All checks were successful
Build on RHEL8 / build (push) Successful in 3m11s
Build on RHEL9 / build (push) Successful in 3m46s
fixed tests (#252)
- fixed failed tests 
- removed import of pickle, scipy 
- still requires boost_histogram, pytest_check

Co-authored-by: Erik Fröjdh <erik.frojdh@psi.ch>
2025-11-28 11:28:13 +01:00
2025-04-22 16:41:48 +02:00
fix
2024-11-18 15:33:38 +01:00
2025-11-21 14:44:54 +01:00
2025-11-21 14:52:54 +01:00
2025-11-26 20:00:03 +01:00
2025-11-24 12:29:08 +01:00
2025-04-01 15:15:54 +02:00
2025-11-28 11:28:13 +01:00
2025-11-25 11:25:44 +01:00
2025-11-21 10:14:14 +01:00
WIP
2024-11-11 17:13:48 +01:00
2025-03-20 12:52:04 +01:00
2025-04-22 16:41:48 +02:00
2025-11-20 09:01:28 +01:00
2025-11-20 09:01:28 +01:00
2025-11-21 14:44:54 +01:00
2025-11-21 16:17:04 +01:00
2025-11-21 16:14:05 +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

#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 form other folders either add the path to your conda environment using conda-build or add it to your PYTHONPATH

Install using conda/mamba

#enable your env first!
conda install aare=2024.10.29.dev0 -c slsdetectorgroup

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]}"
Description
Mirrored from github
Readme MPL-2.0 111 MiB
Languages
Jupyter Notebook 72.7%
C++ 23.9%
Python 2.4%
CMake 1%