Files
SirRoboGarage/tools/ab
SirStone 140fe2519a HeadOn (no-lead) vs Pattern LIVE at long range: clean negative, offline ruler killed
2 arms x 15 runs x 7 rounds, one frozen binary from HEAD a82c864, real DrussGT,
server-side events sidecar. Shipped rack is onlyPattern, so control=Pattern-only
and headon=HeadOn-only (TR_RACK_PATTERN=off TR_RACK_HEADON=both).

  arm      dmg/run  dmgtk/run  round wins  shots/run
  control      279        211     48/105       785
  headon        14        228      0/105       580

Round wins and dmg/run both separate at p<0.0001 (MC permutation, se 0.0000),
~7x the damage MDE (35.8). Per range band (pooled, 15 runs):
  300-450: Pattern 12.3% (4590 shots) vs HeadOn 0.6% (3701)  p<0.0001, MDE 2.0pp
  450+   : Pattern  9.2% (6671)       vs HeadOn 0.4% (4177)  p<0.0001, MDE 1.1pp
HeadOn loses EVERY long-range band by 20-23x, so the whole-battle loss is not a
close-range artefact.

The offline ruler (prediction_quality_results.txt) predicted the opposite: HeadOn
meanAbs 14.61 vs Pattern 17.53 at 300-450 and 12.33 vs 16.19 at 450+, hitProxy
.105/.104 and .098/.077 (+27%). That is an open-loop replay of a FIXED enemy
track, so it cannot see that a different bullet makes the surfer dodge
differently; live, the static gun does not lead at all.

TR_PATTERN_RAD_SCALE arms were skipped: applyRadial scales aim DISTANCE along an
unchanged bearing, so it cannot express 'less lead' (bearing is what firing uses).
HeadOn confirmed to ignore bulletSpeed (head_on.nim:9), liveness OK 15/15.

Adds the range-band analyzer tools/ab/ab_range_bands.py (reuses the lead-capture
Run alignment) and the captured fixtures. Does not touch bitbrain_gun.nim /
bitbrain_campaign.md (job-100).
2026-09-24 23:52:49 +02:00
..

tools/ab — reusable A/B harness

Two tools, built once and reused for every variant test. Adding an arm costs nothing: the frozen bot is built once per session and every arm reuses it.

1. Run a session

tools/ab/ab_run.sh --arms tools/ab/arms.example.txt --runs 7 --outdir /tmp/ab/power --conc 7
  • builds ONE frozen ModularBot from current HEAD (git archive HEAD + nim c -d:release) and reuses that binary for every arm — a dirty tree cannot leak into the measurement;
  • runs arm × run battles vs real DrussGT in parallel (ephemeral ports, one DrussGT botdir/data per run, one ModularBot botdir per run);
  • writes session.json (commit, binary sha256, arms, runs/rounds, timestamp) and <outdir>/<arm>/run<N>.{jsonl,jsonl.rounds.json,jsonl.results.json,events.jsonl,battle.log,bot.stdout.log}.

Options: --arms FILE (required) --runs N (default 7) --outdir DIR (required) --conc K (default 7) --rounds R (default 7).

It kills its own children (own process group + outdir-tagged backstop) on EXIT/INT/TERM, so a Ctrl-C does not leave orphan battles.

Prerequisites (fails loudly if any is missing): /tmp/robocode/install/libs/robocode.jar, /tmp/drussgt/DrussGT.jar, the Tank Royale runner jar, the bot-API jar, nim, and the shim out/ classes. /tmp/tr_bots/DrussGT is recreated via make_botdir.sh if absent (the actual battles still use per-run copies).

2. Analyze a session

python3 tools/ab/ab_analyze.py /tmp/ab/power [--reference control]

Prints per-arm damage/run, damage taken/run, round wins, shots/run, hits taken/run, the per-run values, and for every pair of arms:

  • a two-sided permutation test on per-run damage and wins. Full enumeration when C(n, na) <= 20,000,000 (7v7 -> C(14,7)=3432, always exact); otherwise a Monte-Carlo permutation test with MC_DRAWS = 1,000,000 fixed draws and the fixed seed MC_SEED = 0x5eed5eed, reported with its Monte-Carlo standard error (p = (cnt+1)/(B+1), se = sqrt(p(1-p)/(B+1))). Each row says which method produced its p-value;
  • a tie-corrected, continuity-corrected Mann-Whitney U cross-check;

plus the minimum detectable effect for the reference arm's n and observed per-run SD (alpha=0.05 two-sided, 80% power), a round-level Fisher test (labelled anti-conservative), a liveness OK/FAIL line, a [bb] applied-shift check (needs TR_BITBRAIN_LOG=1; a zero-shift placebo emits no [bb] lines), and a round-win attribution cross-check.

Round wins come from the events sidecar (the bot that does not die wins) and are cross-checked against the runner's firstPlaces. The per-round lines in *.results.json are cumulative standings — not round winners.

Arm file

See arms.example.txt:

name | ENV_VAR=value ENV_VAR2=value2 | optional label

Known gotchas

  • Ports: the runner picks ephemeral ports itself; nothing to configure.
  • Races: never share a DrussGT botdir/data or a ModularBot stdout log across parallel runs — ab_run.sh already gives every run its own.
  • pkill -f run_bridge_battle matches the pkill command itself; use the [r]un_bridge_battle trick (as ab_run.sh does).
  • Liveness reads the bot's [env] boot report from <arm>/run<N>.bot.stdout.log; if an arm's variable is missing there it is a FAIL, not a measurement.