Add rollout-quality distance, confusion, containment and router plots (gitea #76) #79

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lars merged 1 commits from fix/issue-76 into master 2026-08-24 11:22:13 +02:00

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lars commented 2026-08-24 11:14:05 +02:00

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Picks 4 of the 7 catalog additions the issue proposed (the smaller-lift
ones; 2D joint plots, PIT calibration, and the throughput/accuracy scatter
are left for follow-up issues):

• marginal_distance_summary: a var x grouping-axis KS-statistic heatmap,
  reusing the existing marginal hist1d compute and just adding a finalize —
  a single at-a-glance regression scorecard instead of N overlay plots.
• n_sec_confusion: predicted (rollout) vs true (reference) secondary count
  per event, paired by event_id since a rollout is seeded from the same
  events as its reference file. Needed a new zero-filling primitive
  (reduce.sec_count_by_event) since a plain group_by over secondary rows
  silently drops zero-secondary events.
• shower_containment_depth_{90,95}: per-event depth containing 90%/95% of
  deposited energy, derived from the same per-event depth-bin matrix the
  longitudinal profile already computes.
• router_specialization: max gate weight vs energy per side, summarizing
  router_gating's full stacked area into the one trend line the roadmap's
  MoE writeup describes (the ~60-65% ceiling), to make a future
  lambda_balance>0 retrain's effect on specialization checkable at a glance.

Both new heatmap-shaped plots (distance summary, confusion matrix) share one
new "heatmap" Reduced kind/renderer rather than two near-identical ones.

Co-Authored-By: Claude Sonnet 5 noreply@anthropic.com

Picks 4 of the 7 catalog additions the issue proposed (the smaller-lift ones; 2D joint plots, PIT calibration, and the throughput/accuracy scatter are left for follow-up issues): - marginal_distance_summary: a var x grouping-axis KS-statistic heatmap, reusing the existing marginal hist1d compute and just adding a finalize — a single at-a-glance regression scorecard instead of N overlay plots. - n_sec_confusion: predicted (rollout) vs true (reference) secondary count per event, paired by event_id since a rollout is seeded from the same events as its reference file. Needed a new zero-filling primitive (reduce.sec_count_by_event) since a plain group_by over secondary rows silently drops zero-secondary events. - shower_containment_depth_{90,95}: per-event depth containing 90%/95% of deposited energy, derived from the same per-event depth-bin matrix the longitudinal profile already computes. - router_specialization: max gate weight vs energy per side, summarizing router_gating's full stacked area into the one trend line the roadmap's MoE writeup describes (the ~60-65% ceiling), to make a future lambda_balance>0 retrain's effect on specialization checkable at a glance. Both new heatmap-shaped plots (distance summary, confusion matrix) share one new "heatmap" Reduced kind/renderer rather than two near-identical ones. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

lars added 1 commit 2026-08-24 11:14:06 +02:00

Add rollout-quality distance, confusion, containment and router plots (gitea #76) ... ffb7c0cc2a

Picks 4 of the 7 catalog additions the issue proposed (the smaller-lift
ones; 2D joint plots, PIT calibration, and the throughput/accuracy scatter
are left for follow-up issues):

- marginal_distance_summary: a var x grouping-axis KS-statistic heatmap,
  reusing the existing marginal hist1d compute and just adding a finalize —
  a single at-a-glance regression scorecard instead of N overlay plots.
- n_sec_confusion: predicted (rollout) vs true (reference) secondary count
  per event, paired by event_id since a rollout is seeded from the same
  events as its reference file. Needed a new zero-filling primitive
  (reduce.sec_count_by_event) since a plain group_by over secondary rows
  silently drops zero-secondary events.
- shower_containment_depth_{90,95}: per-event depth containing 90%/95% of
  deposited energy, derived from the same per-event depth-bin matrix the
  longitudinal profile already computes.
- router_specialization: max gate weight vs energy per side, summarizing
  router_gating's full stacked area into the one trend line the roadmap's
  MoE writeup describes (the ~60-65% ceiling), to make a future
  lambda_balance>0 retrain's effect on specialization checkable at a glance.

Both new heatmap-shaped plots (distance summary, confusion matrix) share one
new "heatmap" Reduced kind/renderer rather than two near-identical ones.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

lars merged commit 1b6c8b33b7 into master 2026-08-24 11:22:13 +02:00

lars deleted branch fix/issue-76 2026-08-24 11:22:13 +02:00

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Reference: lars/giant#79