Package Overview

The repository is now organized around a modern src/ layout with the package root at src/mltsa.

Package areas

• mltsa.io provides reusable HDF5 helpers and schema utilities.

• mltsa.synthetic provides deterministic benchmark datasets with save, load, rebuild, and append support.

• mltsa.models provides sklearn and PyTorch model wrappers through a small shared factory.

• mltsa.explain provides native, permutation, and global-mean importance methods with HDF5 persistence.

• mltsa.md provides labeling, featurization, analysis, and export helpers for MD workflows.

• mltsa.cli provides thin command-line wrappers around the Python API.

Repository state

The historical research modules remain in the repository during the migration, but they are no longer the preferred public API for new work.

New development should target mltsa directly.

Storage model

The package uses a small HDF5 schema designed for incremental workflows:

• /md/replicas/<replica_id> for lightweight per-replica metadata

• /md/feature_sets/<feature_set_id> for appendable MD feature sets

• /results/experiments/<experiment_id> for saved analyses and diagnostics

This keeps metadata scans fast and avoids loading large numeric arrays just to check whether a result already exists.