An amortized variational inference model to integrate diffraction data.
The installation requires a python environment manager. I use micromamba, and the following instructions assume it. Another popular manager is conda, but I do not use it nor have experience with it.
The project depends on DIALS and laue-DIALS alongside PyTorch. DIALS (and dxtbx/cctbx) and PyTorch are installed from conda-forge. Pick the environment file that matches your machine:
| File | Env | For |
|---|---|---|
environment.yml |
integrator |
CPU runtime (local, non-CUDA) |
environment-cuda.yml |
integrator-cuda |
CUDA / GPU runtime (cluster, linux-64) |
environment-dev.yml |
integrator-dev |
CPU + test/lint/logging tooling (development) |
environment-cuda-dev.yml |
integrator-cuda-dev |
CUDA / GPU + dev tooling (development on GPU) |
# CPU runtime
micromamba env create -f environment.yml
micromamba activate integrator
# CUDA runtime (GPU machine)
micromamba env create -f environment-cuda.yml
micromamba activate integrator-cuda
# Development (tests, ruff, mypy)
micromamba env create -f environment-dev.yml
micromamba activate integrator-dev
# Development on a GPU machine
micromamba env create -f environment-cuda-dev.yml
micromamba activate integrator-cuda-devEach installs DIALS, laue-DIALS, PyTorch, the integrator package (editable), and the upstream reciprocalspaceship build required to read DIALS .refl files.