feat(ModularBot): anti-surfer gun + wave-surf movement module
- Anti-surfer gun: inverse GF targeting for wave-surfing enemies - Wave-surf movement: danger histogram dodge (not wired yet, needs movement selector) - 7 guns total, battle-tested Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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## Anti-surfer gun: inverse of GF histogram — aim at the VALLEY bin.
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## Wave surfers dodge to where they predict bullets won't be (the GF peak).
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## They congregate at the valley → aim there to punish their dodge.
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## Bins: 31, same as GFGun. Learns from virtual bullet outcomes.
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import std/[math, strformat]
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import gun_harness/gun_interface
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const
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ASBins = 31
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ASPrior = 0.1
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DebugAS* = false
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type
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ASWave = object
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fireX, fireY: float
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fireBearing: float
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AntiSurferGun* = object
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bins: array[ASBins, float]
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waves: seq[ASWave]
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cachedTick: int
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cachedWaveStored: bool
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proc initAntiSurferGun*(): AntiSurferGun =
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result.cachedTick = -1
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# Same triangular head-on prior as GFGun — cold-start aims head-on.
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let center = (ASBins - 1) div 2 # = 15
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for i in 0..<ASBins:
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let d = abs(i - center)
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result.bins[i] = ASPrior + 0.5 / float(1 + d)
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proc asToIndex(gf: float): int {.inline.} =
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clamp(int(round((gf + 1.0) * 0.5 * float(ASBins - 1))), 0, ASBins - 1)
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proc indexToAS(idx: int): float {.inline.} =
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float(idx) / float(ASBins - 1) * 2.0 - 1.0
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proc valleyBin(g: AntiSurferGun): int =
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## Find the bin with MINIMUM value — where the surfer thinks is safe.
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var best = 0
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for i in 1..<ASBins:
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if g.bins[i] < g.bins[best]:
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best = i
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best
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proc predict*(g: var AntiSurferGun, state: WorldState, bulletSpeed: float): GunPrediction =
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if bulletSpeed <= 0.0:
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return GunPrediction(x: state.enemyX, y: state.enemyY)
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let dx = state.enemyX - state.selfX
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let dy = state.enemyY - state.selfY
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let dist = sqrt(dx*dx + dy*dy)
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let bearing = arctan2(dy, dx)
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let mea = arcsin(clamp(8.0 / bulletSpeed, -1.0, 1.0))
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if state.tick != g.cachedTick:
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g.cachedTick = state.tick
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g.cachedWaveStored = false
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if not g.cachedWaveStored:
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g.waves.add ASWave(
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fireX: state.selfX,
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fireY: state.selfY,
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fireBearing: bearing,
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)
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g.cachedWaveStored = true
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let valley = g.valleyBin()
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let valleyGF = indexToAS(valley)
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let gfAngle = bearing + valleyGF * mea
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let px = state.selfX + cos(gfAngle) * dist
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let py = state.selfY + sin(gfAngle) * dist
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when DebugAS:
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echo fmt"[as-dbg] predict: valleyGF={valleyGF:.2f} valleyBin={valley} mea={radToDeg(mea):.1f}° aimAngle={radToDeg(gfAngle):.1f}°"
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GunPrediction(
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x: clamp(px, BotRadius, state.arenaWidth - BotRadius),
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y: clamp(py, BotRadius, state.arenaHeight - BotRadius),
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)
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proc onResult*(g: var AntiSurferGun, e: FeedbackEvent) =
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## Same learning as GFGun — track where the enemy actually goes.
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## ponytail: O(n) scan over waves; stays tiny (< a dozen at a time)
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if g.waves.len == 0:
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return
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let w = g.waves[0]
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g.waves.delete(0)
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let speed = bulletSpeed(e.bulletPower)
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let mea = arcsin(clamp(8.0 / speed, -1.0, 1.0))
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let actualDx = e.actualX - w.fireX
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let actualDy = e.actualY - w.fireY
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let actualBearing = arctan2(actualDy, actualDx)
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var bearingDelta = actualBearing - w.fireBearing
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while bearingDelta > PI: bearingDelta -= 2.0*PI
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while bearingDelta < -PI: bearingDelta += 2.0*PI
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let gf = if mea > 1e-10: clamp(bearingDelta / mea, -1.0, 1.0) else: 0.0
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let centerIdx = asToIndex(gf)
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when DebugAS:
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echo fmt"[as-dbg] onResult: delta={radToDeg(bearingDelta):.1f}° MEA={radToDeg(mea):.1f}° GF={gf:.2f} bin={centerIdx}"
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for i in 0..<ASBins:
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let dist = abs(i - centerIdx)
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g.bins[i] += 1.0 / float(1 + dist)
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