careless
Scaling and merging of X-ray diffraction data with approximate Bayesian inference (variational merging), built on TensorFlow.
- Upstream: https://github.com/rs-station/careless
- License: MIT
How it is built
The build installs a private miniconda into $PREFIX/miniconda, creates a
careless_<version> env with Python 3.12 (upstream supports >=3.9,<3.13),
and runs pip install careless[cuda]==<version> inside it. The [cuda]
extra pulls the NVIDIA libraries as pip wheels, so the same install works
on GPU and CPU-only Ra nodes.
Loading the module puts the env's bin/ on PATH (the careless command
is directly available, no conda activate needed) and sets CARELESS_ENV
to the conda env path.
Adding a new version
Add the version under versions: in files/config.yaml, then on a Ra
login node: ./build <version>.