Commit Graph

4 Commits

Author SHA1 Message Date
lars 8cebc4809d Apply ruff format and document lint/type tooling in CLAUDE.md
First repo-wide ruff format pass, plus a note in CLAUDE.md to run
ruff and ty periodically.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 17:40:27 +02:00
lars 53fd2e4405 Add ruff and ty as dev dependencies, fix lint/type findings
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>
2026-06-18 17:38:40 +02:00
lars 80b198c1a5 Add lazy polars I/O and duplicate KL/constraint checks for giant.analysis
load_predicted_local now reads predict parquet via a lazy polars scan with
column projection pushed into the reader, instead of materializing the
whole file as a pandas DataFrame. Also adds marginal_table_pl and
constraint_report_pl, polars-native duplicates that read straight from a
predict parquet path/LazyFrame and stay lazy per (group, dim) pair, so
peak memory is one column slice rather than the whole SampleCollection.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 17:06:58 +02:00
lars a867fc4aae Add giant.analysis module for notebook-based model quality diagnostics
Provides stratified marginal comparisons, joint-structure checks (correlation
matrices, physically-coupled pairwise plots, direction alignment), and
physical-constraint validation (unit-norm directions, non-negative raw
targets) for a trained model's generated samples, building on the aggregate
marginal/KL check already in giant.validate.

Supports two entry points: live sampling against a checkpoint + val data
(load_model_bundle/collect_samples), or loading a precomputed
`giant predict --coord local` parquet directly (load_predicted_local) without
needing the checkpoint at all. Predict output is now tagged with parquet
schema metadata so the loader can verify a file's format and reject
coord=global or untagged files with a clear error instead of guessing from
column names.

Also extends the config git-hash mismatch warning (added for --config
loading) to checkpoint loading: both `giant predict` and
analysis.load_model_bundle now look for a config.toml next to the checkpoint
and warn (without failing) if it was generated from a different git commit.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-18 16:36:19 +02:00