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https://github.com/slsdetectorgroup/aare.git
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06670a7e247a233a6f1144ee6c3677de0d48d2e6
Modified read_n to return the number of frames available if less than
the number of frames requested.
```python
#f is a CtbRawFile containing 10 frames
f.read_n(7) # you get 7 frames
f.read_n(7) # you get 3 frames
f.read_n(7) # RuntimeError
```
Also added support for chunk_size when iterating over a file:
```python
# The file contains 10 frames
with CtbRawFile(fname, chunk_size = 7) as f:
for headers, frames in f:
#do something with the data
# 1 iteration 7 frames
# 2 iteration 3 frames
# 3 iteration stops
```
aare
Data analysis library for PSI hybrid detectors
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
71.7%
C++
25%
Python
2.3%
CMake
1%