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https://github.com/slsdetectorgroup/aare.git
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cbefbc43e945f52a7becbc8d3be770a3cca41545
Issue from Jonathan. - writing to output queue did not check if queue is full - such that frames were dropped. ## Dataset to recreata issue: data overf 10G interface can be accessed on pc: pc-highz-02 raw frames: /mnt/sls_det_storage_10G/highZ_data/JMulvey/Calibration_From_HZ02/2025Jan_m343/Zr15800eV/250129_CZTsolo_Xray_Tp_15C_tint_100_master_0.json pedestal frames: /mnt/sls_det_storage_10G/highZ_data/JMulvey/Calibration_From_HZ02/2025Jan_m343/Zr15800eV/250129_CZTsolo_Pedestal_Tp_15C_tint_100_master_0.json --------- Co-authored-by: Erik Fröjdh <erik.frojdh@psi.ch>
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
71.6%
C++
25%
Python
2.4%
CMake
1%