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https://github.com/slsdetectorgroup/aare.git
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7f3123d68f85c24921629ab3aae2b1b489891998
- New aare:to_string/string_to similar to what we have in slsDetectorPackage - Added members period and exptime to RawMasterFile - Parsing exposure time and period for json and raw master file formats - Parsing of RawMasterFile from string stream to enable test without files Comments: - to_string is at the moment not a public header. Can make it later if needed. This gives us full freedom with the API - FileConfig should probably be deprecated need to look into it. Meanwhile removed python bindings and string conv
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]}"
Languages
Jupyter Notebook
70.7%
C++
25.9%
Python
2.4%
CMake
1%