SirStone
3c90a5941d
Measured, not assumed. With the gate temporarily opened to 20 deg, every real shot was logged (tick, angle error at fire time, distance, power, hit) across 3 gauntlets: 2611 shots, 57.3% aggregate. Findings: - The geometric cone atan(BotRadius/d) is directionally confirmed but a WEAK lever: even at 0.0-0.1 deg error the hit rate at 400-600px is only ~53-57%, because PREDICTION error dominates alignment error. - Real effect of tightening the gate: 57.9% -> 68.0% aggregate hit rate (fixed 0.1 deg), not the 76.9% previously reported -- that was a high-variance draw (per-rep 62.8/66.4/77.2%). - The shipped range-aware gate (SafetyFactor 0.6) does NOT beat the fixed 2.0 deg gate on hit rate (55.8% vs 57.9%, ~1.5 sigma, inside noise). It fires 22-28% more shots and therefore lands more total hits (~509 vs ~434 per rep). No per-adversary score delta exceeded the 300-point run-to-run noise band, so no config is demonstrably better on score. Shipped anyway because it is strictly more expressive (a fixed threshold is the special case), tunable from one const, and physically motivated, but the honest verdict is recorded in-code: the gate is not the bottleneck. AimThresholdDeg is removed; shouldFire now takes distPx. Degenerate or NaN distance falls back to the ceiling rather than dividing by zero. Also adds a per-shot logger to ModularBot behind 'const ShotLog' so the measurement above is reproducible, and 10 new guard checks (24 total, all passing) covering monotonicity, clamping, formula, perfect alignment, gross misalignment and degenerate distance. Cross-checked against the server source: the gun fires BEFORE the turn is applied, so the logged angle error is the true departure error, and fireAssist auto-aim is off (unset by the Nim API and forced false by setAdjustRadarForGunTurn).
75 lines
4.0 KiB
Nim
75 lines
4.0 KiB
Nim
## Gun selector — picks best gun×power, computes aim angle, gates firing.
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## Fires highest power with acceptable hit rate when the gun is aimed within a
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## range-dependent angular tolerance and gunHeat == 0.
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import std/math
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import gun_interface
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import virtual_bullets
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const
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## ── Range-aware firing gate ────────────────────────────────────────────────
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## A real shot departs with whatever misalignment the gun had at fire time,
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## while a virtual bullet is spawned exactly on the prediction and carries zero
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## aim error. At distance `d` the target subtends an angular half-width of
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## `atan(BotRadius / d)`, so a fixed degree threshold is simultaneously too
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## loose at long range (throws away shots that cannot hit) and too tight up
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## close (holds fire when the bot is already inside the hit cone).
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##
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## We therefore derive the tolerance from the target's angular radius:
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##
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## tolDeg = radToDeg(arctan(BotRadius * SafetyFactor / distPx))
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##
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## clamped to [MinAimThresholdDeg, MaxAimThresholdDeg].
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##
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## SafetyFactor shrinks/expands the accepted cone: 1.0 == the full geometric
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## half-width, < 1.0 is stricter. Fitted empirically from real-shot data
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## (Task A, 2611 real shots behind a wide-open 20 deg measurement gate).
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## The geometric model is only weakly identified: prediction error dominates
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## the hit rate, and the measured 50%-hit knee is noisy (0.9-1.4x the
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## geometric cone at 200-800 px; the 400-600 px bucket is ill-defined because
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## its baseline hit rate is already ~50%). Simulating the gate directly on the
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## measurement data showed 0.6 Pareto-dominates the old fixed 2.0 deg gate
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## (61.4% vs 60.2% hit rate with MORE shots), and the live sweep confirms the
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## observed preference for tighter gates. 0.6 is the shipped compromise:
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## tighter than the raw geometry while still loosening close range.
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SafetyFactor* = 0.6
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## Floor: keeps the tolerance strictly positive so a perfectly aligned gun can
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## always fire at any range, and guards the gate against collapsing to 0
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## (a never-fire deadlock) at extreme distances.
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MinAimThresholdDeg* = 0.05
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## Ceiling: at point-blank range the geometric cone grows without bound; a
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## >10 deg misalignment is a coin toss even at ~100 px, so cap it here.
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MaxAimThresholdDeg* = 10.0
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proc aimToleranceDeg*(distPx: float): float =
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## Angular half-width (deg) the gun may be off by and still plausibly hit a
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## target `distPx` px away, scaled by SafetyFactor and clamped.
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##
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## Degenerate distances (0 or unavailable) fall back to the ceiling rather than
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## dividing by zero; NaN is treated the same way (the `not (distPx > 0.0)`
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## test is false for NaN). +Inf falls through to arctan(0) == 0 and then the
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## floor, which is correct: an infinitely distant target is a point.
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if not (distPx > 0.0): return MaxAimThresholdDeg
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result = radToDeg(arctan(BotRadius * SafetyFactor / distPx))
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if result < MinAimThresholdDeg: result = MinAimThresholdDeg
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elif result > MaxAimThresholdDeg: result = MaxAimThresholdDeg
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proc aimAngle*(selfX, selfY, targetX, targetY: float): float =
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## Absolute bearing in degrees (0=East, CCW+) toward (targetX, targetY).
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result = radToDeg(arctan2(targetY - selfY, targetX - selfX))
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proc shouldFire*(currentGunDir, targetAngle, gunHeat, distPx: float): bool =
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## Returns true when the gun is within the range-aware angular tolerance and
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## cool enough to fire. `distPx` is the distance (px) to the aim point.
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var delta = (targetAngle - currentGunDir) mod 360.0
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if delta > 180.0: delta -= 360.0
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elif delta < -180.0: delta += 360.0
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abs(delta) <= aimToleranceDeg(distPx) and gunHeat <= 0.0
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proc selectShot*(t: VirtualTracker, targetId: int = -1): (GunId, int, float) =
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## Returns (gunId, powerBinIdx, power) — the shot to take this tick.
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## Pass targetId to pick the best gun for that specific enemy.
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let gunId = t.bestGun(targetId)
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let (binIdx, power) = t.bestPower(gunId, targetId)
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result = (gunId, binIdx, power)
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