Removes unused imports and an ambiguous variable name, narrows
Optional types before use so ty's flow analysis is satisfied, swaps
sum() over polars expressions for pl.sum_horizontal to avoid the
Literal[0] fallback type, and converts numpy bin edges to plain lists
before passing to matplotlib's hist (whose stub only accepts
Sequence[float]). Also applies ruff format across the repo, which had
drifted out of sync with the formatter.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
- energy_simplex_encode: warn when clipping post_E to pre_E discards
recorded edep/e_sec instead of silently zeroing them
- local/inv_local_frame_rotation: validate and normalize pre_dir instead
of silently assuming unit norm; raise on near-zero-norm rows
- train(): make --lr authoritative on resume instead of being silently
overwritten by the checkpoint's optimizer/scheduler state; print and
exit cleanly instead of silently training zero epochs when the
checkpoint already meets --epochs; truncate metrics.csv on a fresh
run instead of always appending
- dwarf update-manifest: check file existence for every manifest line,
not just ones whose gen/schema actually changed
- pyproject.toml: dev extra now pulls in convert+analysis so the
documented `uv sync --extra cpu --extra dev` + `pytest` actually
passes collection
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Replaces the independent log_delta_e/log_edep targets with 2 additive-log-ratio
coordinates over the deposit/secondary/post-energy simplex (fractions of pre_E
summing to 1), so edep + e_sec + post_E == pre_E holds by construction after
decoding (softmax) rather than being learned approximately. Requires e_sec
(secondary energy) as a new conditioning input and a steps_to_parquet.py pass
to derive it from child track first-step energies.
ruff removed unused imports across analysis.py and several test files.
ty caught a wrong dict[int, int] annotation on StreamingStepsDataset's
mat_map (materials are strings) and a real bug in steps_to_parquet.py
where --compression none passed None to polars' write_parquet, which
only accepts the literal "uncompressed". Also narrows a few
Optional-typed attributes (ddpm_schedule, Normalizer.mean/std) with
asserts and aligns __getitem__'s parameter name with torch's Dataset
base class.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
step_length already encodes |post_pos - pre_pos| by definition, so a raw
post_pos target would duplicate that magnitude and could drift inconsistent
with step_length during sampling. Instead add travel_dir, a unit vector
(local frame) giving only the direction of pre_pos->post_pos; post_pos is
reconstructed at inference as pre_pos + step_length * travel_dir, keeping
the two self-consistent. Target grows from 6D to 9D.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
lars