# 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>`.