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
Upstream recommends a fresh conda env, but repo.anaconda.com is not
reachable from Ra, so the build uses uv instead: it fetches a standalone
Python 3.12 into $PREFIX/python (upstream supports >=3.9,<3.13), creates
$PREFIX/venv, and runs uv pip install careless[cuda]==<version> into
it. The [cuda] extra pulls the NVIDIA libraries as pip wheels, so the
same install works on GPU and CPU-only Ra nodes.
uv must be on PATH on the build host (e.g. pip install --user uv).
Loading the module puts the venv's bin/ on PATH (the careless
command is directly available, no activation needed) and sets
CARELESS_ENV to the venv path.
Adding a new version
Add the version under versions: in files/config.yaml, then on a Ra
login node: modbuild build <version> (modbuild/2.1.2).