dwmoreau/mlindex-models

MLINDEX models

Machine-learning models used by MLINDEX, a powder diffraction indexing program. Given a list of observed diffraction peaks, MLINDEX returns candidate unit cells ranked by the de Wolff M20 figure of merit. These models initialize the candidate unit cells for each Bravais lattice; the candidates are then refined by least-squares optimization.

Contents

One directory per lattice system, each holding the trained components for its Bravais lattices and split groups:

Directory	Bravais lattices
cubic_1/	cF, cI, cP
hexagonal_1/	hP
rhombohedral_1/	hR
tetragonal_1/	tI, tP
orthorhombic_1/	oC, oF, oI, oP
monoclinic_1/	mC, mP
triclinic_1/	aP

Within each, random_forest/ and random/ hold random-forest volume predictors, template/ holds the Miller-index template libraries and their calibrators, abnn/ holds the quantized ONNX ABNN networks (an attention-based network that predicts unit cells from the peak list), and data/ holds the hkl_ref_*.npy reference sets and training parameters.

Total: 739 files, 465 MB.

Usage

pip install mlindex
mlindex.download_models

mlindex.download_models fetches this repository at the revision pinned by your installed mlindex version. No git or git-lfs required.

To fetch it directly:

from huggingface_hub import snapshot_download
snapshot_download("dwmoreau/mlindex-models", revision="v2", local_dir="models")

Revisions

Releases of mlindex pin a specific tag, so a given version always gets the exact weights it was tested against.

• v2 removes the 43 per-peak Miller-index assignment networks (104.7 MB), which a closed-form posterior replaced, and renames integral_filter/ to abnn/. It needs an mlindex that looks for abnn/.
• v1 corresponds to the models released with mlindex 0.1.x, which keep working against it.

Citation

Please check the GitHub repository for the current citation.

License

MIT, matching the MLINDEX source.