6 Commits

Include renames

Author	SHA1	Message	Date
larsandClaude Sonnet 5	8d46f27d1b	Reformat rollout_validation.ipynb with ruff format ... Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-07-23 14:38:49 +02:00
larsandClaude Sonnet 5	0d2967fa6b	Add router gating diagnostic for MoE checkpoints ... plot_router_gating visualizes soft expert gate weights vs. a continuous routing axis (e.g. pre-step energy), binned into equal-population quantiles and stacked to show the router's soft decision boundaries. Wired into rollout_validation.ipynb as a new notebook-only section that loads a checkpoint's Router directly, since gate weights aren't present in rollout/predict parquet output. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-07-23 14:15:39 +02:00
larsandClaude Sonnet 5	81ec225b86	Reimplement rollout-vs-truth comparison on the streaming analysis module ... Merged in every non-analysis change from the MoE-prototype branch (routing, training, data pipeline, streaming rollout output), keeping this branch's lean streaming giant/analysis.py and rebuilding the rollout-vs-truth feature natively on it instead of resurrecting the old numpy SampleCollection path. - Add RolloutVsTruth, accepted anywhere Tier 1-3 functions take a predict-parquet source: decodes a giant rollout file and a held-out truth file into RAW_TARGET_NAMES space via a polars port of the forward local-frame rotation, fully streaming (no SampleCollection, no eager materialization). - Add compute_rollout_vs_truth_observables_pl for Tier 4, reusing EventObservables (now backed by independent real_table/gen_table to support unequal rollout/truth event counts) so every existing shower-observable plot function works unchanged for both one-step and full-rollout comparisons. - Update analysis/rollout_validation.ipynb to the new API and CLAUDE.md's architecture description; add test coverage for the new source type. - Fix a pre-existing return-type mismatch in giant.rollout.rollout() (found by `ty check`): the on_chunk summary-dict branch didn't match the declared dict[str, np.ndarray] return type, now expressed as a RolloutSummary TypedDict. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-07-17 12:32:30 +02:00
lars	ea22b85df9	Run full rollout validation.	2026-07-13 14:32:36 +02:00
larsandClaude Sonnet 5	4c1250e246	Fix rollout edep mismatch and add truth overlay to Tier 4 observables ... load_rollout_vs_truth was including rollout.py's synthetic termination- bookkeeping rows (escaped/unknown_pdg/energy_cutoff/max_steps) unfiltered: these carry step_length=0 and edep=pre_E dumped in one row for shower-level energy conservation, not a real per-step value, and nearly doubled the apparent mean edep in a repro. _load_world_frame_side now drops them, keeping only real generated steps (continuing or natural_end). Also documents the remaining, unfixable difference: rollout's edep on real steps absorbs any secondary-energy budget Stage 2 didn't allocate, which truth's edep never does. Adds compute_truth_observables, the truth-schema counterpart to compute_rollout_observables, so the Tier 4 event-level plots (plot_rollout_longitudinal/transverse/total_energy) can overlay a real reference computed directly from load_rollout_vs_truth's own truth file, without needing a separate paired giant predict --coord local file. Shares the depth/transverse binning core with compute_rollout_observables via a new _event_axis_depth_transverse helper. Updates rollout_validation.ipynb's Tier 4 section to use this reference and points ROLLOUT_FILE/TRUTH_FILE at a real prediction/shard pair. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-07-13 12:38:44 +02:00
larsandClaude Sonnet 5	36bdbf7cc1	Add load_rollout_vs_truth to compare rollouts against held-out truth data ... Extends the Tier 1-3 SampleCollection diagnostics (marginals, correlations, pairwise, direction alignment, constraints) to work on a full autoregressive giant rollout shower checked against an independent ground-truth steps file, rather than only paired giant predict --coord local output. The two files are unpaired (different lengths, own conditioning), so SampleCollection gains optional *_gen fields and _group_labels/marginal_table/plot_marginals/ plot_pairwise build independent real/gen masks instead of assuming one. Adds analysis/rollout_validation.ipynb, a sibling of validation.ipynb built around this workflow. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>	2026-07-13 10:58:42 +02:00