fix(guns): per-bin wave queues unbreak GF/DecayGF/KNN learning; fix vbullet drops
Wave queues (guess_factor, decay_gf, knn_gun): predict() stored ONE wave per tick while onResult() popped one per resolved bullet (~4/tick), so the queue drained to empty within a few dozen ticks, ~3 of every 4 resolutions returned without learning, and the survivor paired with a same-tick wave (bearingDelta ~= 0) pinning the histogram at centre. PROOF: GF.vHits == HeadOn.vHits and DecayGF.vHits == HeadOn.vHits byte-for-byte in every one of 50 rounds — the guns had degenerated to HeadOn. Now each gun keeps a per-bin FIFO with an O(1) head cursor. At most one push per (tick, bin) so the fire site's 5th predict() call is a no-op, and onResult pops the oldest wave of its OWN bin via e.bulletPower. Aiming math untouched (it was already correct: 0 deg = East, CCW+). maxBullets 2048 -> 8192: the rack spawns 52 bullets/tick so the ring wrapped every ~39 ticks while a long power-3 shot needs ~90, silently discarding unresolved bullets and biasing every measured hit rate by range. Added a droppedBullets counter so a future overflow is measurable, and wavePushes/ waveStarved counters on the three guns. After the fix: vDropped = 0 and vStarved = 0 across all 48 recorded rounds. fitnessFor is now exported, deterministic (enemies iterated in ascending id order) and shared by the selector and the stats dump, replacing a hand-rolled merge in ModularBot that never advanced its window head. Round lines gain additive keys: vDropped, vStarved.
This commit is contained in:
@@ -199,24 +199,10 @@ method onRoundEnded*(bot: ModularBot, e: RoundEndedEventForBot) =
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## Dump per-gun virtual bullet stats to /tmp/gun_stats.jsonl (one line per round).
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## Dump per-gun virtual bullet stats to /tmp/gun_stats.jsonl (one line per round).
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# Use lastKnownTargetId: currentTargetId is -1 if enemy died before round end
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# Use lastKnownTargetId: currentTargetId is -1 if enemy died before round end
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let targetId = if bot.currentTargetId >= 0: bot.currentTargetId else: bot.lastKnownTargetId
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let targetId = if bot.currentTargetId >= 0: bot.currentTargetId else: bot.lastKnownTargetId
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# Aggregate fitness across all tracked enemies (or just the primary target if known).
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# Per-target fitness when known, else a deterministic recency-weighted aggregate
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# Use aggregate (targetId=-1) so we always have data even if target switched.
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# over all enemies (see VirtualTracker.fitnessFor). Using the shared proc keeps
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let fit = block:
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# this stats dump identical to what the gun selector sees.
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var f: seq[vb.GunFitness]
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let fit = bot.tracker.fitnessFor(targetId)
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if targetId >= 0 and targetId in bot.tracker.fitness:
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f = bot.tracker.fitness[targetId]
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else:
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# aggregate across all enemies
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f = newSeq[vb.GunFitness](bot.tracker.numGuns)
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for perEnemy in bot.tracker.fitness.values:
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for gid in 0..<bot.tracker.numGuns:
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for binIdx in 0..<len(vb.PowerBins):
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let src = perEnemy[gid].bins[binIdx]
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let n = min(src.count, vb.WindowSize)
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for k in 0..<n:
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f[gid].bins[binIdx].hits[(f[gid].bins[binIdx].head + f[gid].bins[binIdx].count) mod vb.WindowSize] = src.hits[k]
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inc f[gid].bins[binIdx].count
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f
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var gunsArr = newJArray()
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var gunsArr = newJArray()
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for gid in 0..<13:
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for gid in 0..<13:
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@@ -251,7 +237,9 @@ method onRoundEnded*(bot: ModularBot, e: RoundEndedEventForBot) =
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"realShots": bot.realShotsFired,
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"realShots": bot.realShotsFired,
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"realHits": bot.realHits,
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"realHits": bot.realHits,
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"score": e.results.totalScore,
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"score": e.results.totalScore,
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"bulletDmg": e.results.bulletDamage
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"bulletDmg": e.results.bulletDamage,
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"vDropped": bot.tracker.droppedBullets,
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"vStarved": bot.guessFactor.waveStarved + bot.decayGF.waveStarved + bot.knnGun.waveStarved
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}
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}
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let f = open("/tmp/gun_stats.jsonl", fmAppend)
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let f = open("/tmp/gun_stats.jsonl", fmAppend)
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f.writeLine($row)
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f.writeLine($row)
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@@ -269,6 +257,15 @@ method onRoundStarted*(bot: ModularBot, e: RoundStartedEvent) =
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bot.gunSelectionCount[i] = 0
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bot.gunSelectionCount[i] = 0
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bot.gunRealShots[i] = 0
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bot.gunRealShots[i] = 0
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bot.gunRealHits[i] = 0
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bot.gunRealHits[i] = 0
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# Reset per-round integrity counters so each /tmp/gun_stats.jsonl line reports
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# that round's numbers (summing the lines gives the session total).
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bot.tracker.droppedBullets = 0
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bot.guessFactor.wavePushes = 0
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bot.guessFactor.waveStarved = 0
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bot.decayGF.wavePushes = 0
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bot.decayGF.waveStarved = 0
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bot.knnGun.wavePushes = 0
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bot.knnGun.waveStarved = 0
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setAdjustGunForBodyTurn(true)
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setAdjustGunForBodyTurn(true)
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setAdjustRadarForBodyTurn(true)
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setAdjustRadarForBodyTurn(true)
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setAdjustRadarForGunTurn(true)
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setAdjustRadarForGunTurn(true)
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@@ -6,12 +6,16 @@
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import std/math
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import std/math
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import std/tables
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import std/tables
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import std/random
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import std/random
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import std/algorithm
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import gun_interface
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import gun_interface
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const
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const
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PowerBins* = [1.0, 1.5, 2.0, 3.0] ## 4 bins; ponytail: fixed array, add runtime config if needed
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PowerBins* = [1.0, 1.5, 2.0, 3.0] ## 4 bins; ponytail: fixed array, add runtime config if needed
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WindowSize* = 100 ## rolling window ticks for fitness
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WindowSize* = 100 ## rolling window ticks for fitness
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MaxBullets* = 2048 ## hard cap; ponytail: ring buffer, resize if more guns added
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MaxBullets* = 8192 ## hard cap; ring buffer. 52 spawns/tick and a
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## full-map long shot (~90 ticks) need ~4700 slots;
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## 8192 wraps only after ~157 ticks. Each VirtualBullet
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## is 88 bytes, so this array costs ~704 KiB.
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MinHitRate* = 0.40 ## 40% threshold for acceptable power selection
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MinHitRate* = 0.40 ## 40% threshold for acceptable power selection
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MinObsBeforeCompete* = 50 ## min observations before a gun×bin enters competition
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MinObsBeforeCompete* = 50 ## min observations before a gun×bin enters competition
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TieMargin* = 0.02 ## guns within this hit-rate margin of best are tied
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TieMargin* = 0.02 ## guns within this hit-rate margin of best are tied
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@@ -45,6 +49,7 @@ type
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head*: int ## ring buffer head
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head*: int ## ring buffer head
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numGuns*: int
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numGuns*: int
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fitness*: Table[int, seq[GunFitness]] ## keyed by enemy bot ID, indexed by GunId
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fitness*: Table[int, seq[GunFitness]] ## keyed by enemy bot ID, indexed by GunId
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droppedBullets*: int ## unresolved bullets clobbered by the ring buffer (should stay 0)
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proc initTracker*(numGuns: int): VirtualTracker =
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proc initTracker*(numGuns: int): VirtualTracker =
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result.numGuns = numGuns
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result.numGuns = numGuns
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@@ -75,6 +80,11 @@ proc spawnBullets*(t: var VirtualTracker, gunId: GunId,
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let pred = predictions[binIdx]
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let pred = predictions[binIdx]
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let fireDist = hypot(pred.x - state.selfX, pred.y - state.selfY)
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let fireDist = hypot(pred.x - state.selfX, pred.y - state.selfY)
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let slot = t.head mod MaxBullets
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let slot = t.head mod MaxBullets
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# Measurement integrity: if the slot we are about to overwrite still holds an
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# unresolved bullet, that bullet will never be scored. Count it instead of
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# silently dropping it (non-zero after a battle means MaxBullets is too small).
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if t.bullets[slot].active:
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inc t.droppedBullets
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t.bullets[slot] = VirtualBullet(
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t.bullets[slot] = VirtualBullet(
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gunId: gunId,
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gunId: gunId,
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powerBin: binIdx,
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powerBin: binIdx,
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@@ -140,20 +150,30 @@ proc tickBullets*(t: var VirtualTracker, state: WorldState,
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onResolved(b.gunId, b.powerBin, fe)
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onResolved(b.gunId, b.powerBin, fe)
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b.active = false
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b.active = false
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proc fitnessFor(t: VirtualTracker, targetId: int): seq[GunFitness] =
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proc fitnessFor*(t: VirtualTracker, targetId: int): seq[GunFitness] =
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## Returns fitness seq for targetId, or merges all enemies as fallback.
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## Returns fitness seq for targetId, or merges all enemies as fallback.
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## ponytail: merge is O(enemies*guns*bins), fine for small counts
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##
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## The fallback is a RECENCY-WEIGHTED AGGREGATE over the last WindowSize
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## samples, NOT a pooled rate: each per-enemy window is replayed into one fresh
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## window, so once the total exceeds WindowSize the earliest samples are
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## overwritten by later ones. Enemies are visited in ascending target-id order
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## so the result is identical on every run (std/tables iteration order is hash
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## order and therefore nondeterministic).
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## ponytail: merge is O(enemies*guns*bins*WindowSize), fine for small counts
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if targetId >= 0 and targetId in t.fitness:
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if targetId >= 0 and targetId in t.fitness:
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return t.fitness[targetId]
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return t.fitness[targetId]
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# Aggregate across all enemies
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# Aggregate across all enemies, deterministically ordered.
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result = newSeq[GunFitness](t.numGuns)
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result = newSeq[GunFitness](t.numGuns)
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for perEnemy in t.fitness.values:
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var enemyIds: seq[int]
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for id in t.fitness.keys: enemyIds.add id
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enemyIds.sort()
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for id in enemyIds:
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let perEnemy = t.fitness[id]
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for gunId in 0..<t.numGuns:
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for gunId in 0..<t.numGuns:
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for binIdx in 0..<len(PowerBins):
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for binIdx in 0..<len(PowerBins):
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let src = perEnemy[gunId].bins[binIdx]
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let src = perEnemy[gunId].bins[binIdx]
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var dst = addr result[gunId].bins[binIdx]
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for k in 0..<min(src.count, WindowSize):
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for k in 0..<min(src.count, WindowSize):
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dst[].record(src.hits[k])
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result[gunId].bins[binIdx].record(src.hits[k])
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proc bestPower*(t: VirtualTracker, gunId: GunId, targetId: int = -1): (int, float) =
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proc bestPower*(t: VirtualTracker, gunId: GunId, targetId: int = -1): (int, float) =
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## Returns (binIdx, power) with highest power that has >= MinHitRate.
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## Returns (binIdx, power) with highest power that has >= MinHitRate.
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@@ -1,14 +1,16 @@
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## Recency-weighted GF gun: exponential decay on histogram bins.
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## Recency-weighted GF gun: exponential decay on histogram bins.
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## decay=0.998/tick gives ~350-tick half-life — adapts to mid-battle strategy shifts.
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## decay=0.998/tick gives ~350-tick half-life — adapts to mid-battle strategy shifts.
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## Everything else identical to guess_factor.nim.
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## Everything else identical to guess_factor.nim, including per-power-bin wave queues.
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import std/math
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import std/math
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import gun_harness/gun_interface
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import gun_harness/gun_interface
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import gun_harness/virtual_bullets as vb # PowerBins
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const
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const
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GFBins = 31
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GFBins = 31
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GFPrior = 0.1
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GFPrior = 0.1
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DecayRate = 0.998 # ponytail: single global decay, tune if adaptation too slow/fast
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DecayRate = 0.998 # ponytail: single global decay, tune if adaptation too slow/fast
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DecayWaveCompactAt = 64
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type
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type
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DWave = object
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DWave = object
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@@ -17,14 +19,21 @@ type
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DecayGFGun* = object
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DecayGFGun* = object
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bins: array[GFBins, float]
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bins: array[GFBins, float]
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waves: seq[DWave]
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# One wave queue per power bin; a resolved bullet only learns from a wave
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cachedTick: int
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# queued for its own bin (matched on bulletSpeed / bulletPower).
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cachedWaveStored: bool
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waves: array[len(vb.PowerBins), seq[DWave]]
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waveHead: array[len(vb.PowerBins), int] # O(1) pop cursor
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waveStoredTick: array[len(vb.PowerBins), int] # last tick a wave was queued for this bin
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cachedTick: int # last tick bins were decayed
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wavePushes*: int
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waveStarved*: int
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debugGraphics*: bool
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debugGraphics*: bool
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proc initDecayGFGun*(): DecayGFGun =
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proc initDecayGFGun*(): DecayGFGun =
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result.cachedTick = -1
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result.cachedTick = -1
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result.debugGraphics = false
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result.debugGraphics = false
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for b in 0..<len(vb.PowerBins):
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result.waveStoredTick[b] = -1
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let center = (GFBins - 1) div 2
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let center = (GFBins - 1) div 2
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for i in 0..<GFBins:
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for i in 0..<GFBins:
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let d = abs(i - center)
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let d = abs(i - center)
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@@ -43,6 +52,28 @@ proc peakBin(g: DecayGFGun): int =
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best = i
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best = i
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best
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best
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proc binForSpeed(spd: float): int {.inline.} =
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for i in 0..<len(vb.PowerBins):
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if abs(spd - bulletSpeed(vb.PowerBins[i])) < 1e-6:
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return i
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-1
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proc binForPower(power: float): int {.inline.} =
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for i in 0..<len(vb.PowerBins):
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if abs(power - vb.PowerBins[i]) < 1e-6:
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return i
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-1
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proc takeOldestWave(g: var DecayGFGun, binIdx: int): (bool, DWave) =
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if binIdx < 0 or g.waveHead[binIdx] >= g.waves[binIdx].len:
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return (false, DWave())
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result = (true, g.waves[binIdx][g.waveHead[binIdx]])
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inc g.waveHead[binIdx]
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if g.waveHead[binIdx] >= DecayWaveCompactAt and
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g.waveHead[binIdx] * 2 >= g.waves[binIdx].len:
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g.waves[binIdx] = g.waves[binIdx][g.waveHead[binIdx] .. g.waves[binIdx].high]
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g.waveHead[binIdx] = 0
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proc predict*(g: var DecayGFGun, state: WorldState, bulletSpeed: float): GunPrediction =
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proc predict*(g: var DecayGFGun, state: WorldState, bulletSpeed: float): GunPrediction =
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if bulletSpeed <= 0.0:
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if bulletSpeed <= 0.0:
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return GunPrediction(x: state.enemyX, y: state.enemyY)
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return GunPrediction(x: state.enemyX, y: state.enemyY)
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@@ -57,12 +88,15 @@ proc predict*(g: var DecayGFGun, state: WorldState, bulletSpeed: float): GunPred
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# Decay all bins once per tick
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# Decay all bins once per tick
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for i in 0..<GFBins:
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for i in 0..<GFBins:
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g.bins[i] *= DecayRate
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g.bins[i] *= DecayRate
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g.cachedTick = state.tick
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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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# Queue at most one wave per (tick, power bin); the fire site's extra predict()
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g.waves.add DWave(fireX: state.selfX, fireY: state.selfY, fireBearing: bearing)
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# call for the selected bin lands on the same tick and reuses the queued wave.
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g.cachedWaveStored = true
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let binIdx = binForSpeed(bulletSpeed)
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if binIdx >= 0 and g.waveStoredTick[binIdx] != state.tick:
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g.waves[binIdx].add DWave(fireX: state.selfX, fireY: state.selfY, fireBearing: bearing)
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g.waveStoredTick[binIdx] = state.tick
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inc g.wavePushes
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let peak = g.peakBin()
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let peak = g.peakBin()
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let peakGF = indexToGF(peak)
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let peakGF = indexToGF(peak)
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@@ -76,10 +110,13 @@ proc predict*(g: var DecayGFGun, state: WorldState, bulletSpeed: float): GunPred
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)
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)
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proc onResult*(g: var DecayGFGun, e: FeedbackEvent) =
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proc onResult*(g: var DecayGFGun, e: FeedbackEvent) =
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if g.waves.len == 0: return
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let binIdx = binForPower(e.bulletPower)
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if binIdx < 0: return
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let w = g.waves[0]
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let (found, w) = g.takeOldestWave(binIdx)
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g.waves.delete(0)
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if not found:
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inc g.waveStarved
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return
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let speed = bulletSpeed(e.bulletPower)
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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 mea = arcsin(clamp(8.0 / speed, -1.0, 1.0))
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@@ -1,14 +1,16 @@
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## Guess-factor gun: statistical targeting via GF histogram.
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## Guess-factor gun: statistical targeting via GF histogram.
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## Bins: 31, ranging GF -1 (max CW escape) to +1 (max CCW escape).
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## Bins: 31, ranging GF -1 (max CW escape) to +1 (max CCW escape).
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## Learns from virtual bullet outcomes; caches wave state per-tick.
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## Learns from virtual bullet outcomes; queues one wave per (tick, power bin).
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import std/[math, strformat]
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import std/[math, strformat]
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import gun_harness/gun_interface
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import gun_harness/gun_interface
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import gun_harness/virtual_bullets as vb # PowerBins: the four power bins the harness spawns
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const
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const
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GFBins = 31
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GFBins = 31
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GFPrior = 0.1
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GFPrior = 0.1
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DebugGF* = false
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DebugGF* = false
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WaveCompactAt = 64 ## compact a bin's wave seq once this many entries are consumed
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type
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type
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Wave = object
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Wave = object
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@@ -18,15 +20,20 @@ type
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GFGun* = object
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GFGun* = object
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bins: array[GFBins, float]
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bins: array[GFBins, float]
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waves: seq[Wave] # pending unresolved waves
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# One wave queue per power bin. The owning bin is fixed at push time (from the
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# per-tick cache: store wave only once across multiple power-bin calls
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# bulletSpeed argument) and at pop time (from FeedbackEvent.bulletPower), so a
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cachedTick: int
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# resolved bullet is always paired with a wave from its own bin.
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cachedWaveStored: bool
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waves: array[len(vb.PowerBins), seq[Wave]]
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waveHead: array[len(vb.PowerBins), int] # O(1) pop cursor into waves[bin]
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||||||
|
waveStoredTick: array[len(vb.PowerBins), int] # last tick a wave was queued for this bin
|
||||||
|
wavePushes*: int # total waves enqueued (== one per (tick, bin))
|
||||||
|
waveStarved*: int # onResult found an empty queue for its own bin
|
||||||
debugGraphics*: bool
|
debugGraphics*: bool
|
||||||
|
|
||||||
proc initGFGun*(): GFGun =
|
proc initGFGun*(): GFGun =
|
||||||
result.cachedTick = -1
|
|
||||||
result.debugGraphics = false
|
result.debugGraphics = false
|
||||||
|
for b in 0..<len(vb.PowerBins):
|
||||||
|
result.waveStoredTick[b] = -1
|
||||||
# Seed with a head-on prior: triangular bump at bin 15 (GF=0).
|
# Seed with a head-on prior: triangular bump at bin 15 (GF=0).
|
||||||
# Prevents the cold-start tie-break to GF=-1 (bin 0) that poisons early fitness.
|
# Prevents the cold-start tie-break to GF=-1 (bin 0) that poisons early fitness.
|
||||||
let center = (GFBins - 1) div 2 # = 15
|
let center = (GFBins - 1) div 2 # = 15
|
||||||
@@ -47,6 +54,34 @@ proc peakBin(g: GFGun): int =
|
|||||||
best = i
|
best = i
|
||||||
best
|
best
|
||||||
|
|
||||||
|
proc binForSpeed(spd: float): int {.inline.} =
|
||||||
|
## Map a virtual-bullet speed back to its power-bin index. All four bin speeds
|
||||||
|
## are exactly representable floats; the epsilon is belt-and-braces only.
|
||||||
|
for i in 0..<len(vb.PowerBins):
|
||||||
|
if abs(spd - bulletSpeed(vb.PowerBins[i])) < 1e-6:
|
||||||
|
return i
|
||||||
|
-1
|
||||||
|
|
||||||
|
proc binForPower(power: float): int {.inline.} =
|
||||||
|
## Map a FeedbackEvent.bulletPower back to its power-bin index.
|
||||||
|
for i in 0..<len(vb.PowerBins):
|
||||||
|
if abs(power - vb.PowerBins[i]) < 1e-6:
|
||||||
|
return i
|
||||||
|
-1
|
||||||
|
|
||||||
|
proc takeOldestWave(g: var GFGun, binIdx: int): (bool, Wave) =
|
||||||
|
## Pop the oldest unresolved wave for this bin (O(1) amortized via waveHead).
|
||||||
|
## Returns (false, default) when the bin's queue is empty.
|
||||||
|
if binIdx < 0 or g.waveHead[binIdx] >= g.waves[binIdx].len:
|
||||||
|
return (false, Wave())
|
||||||
|
result = (true, g.waves[binIdx][g.waveHead[binIdx]])
|
||||||
|
inc g.waveHead[binIdx]
|
||||||
|
# Amortized O(1): drop the consumed prefix once it dominates the queue.
|
||||||
|
if g.waveHead[binIdx] >= WaveCompactAt and
|
||||||
|
g.waveHead[binIdx] * 2 >= g.waves[binIdx].len:
|
||||||
|
g.waves[binIdx] = g.waves[binIdx][g.waveHead[binIdx] .. g.waves[binIdx].high]
|
||||||
|
g.waveHead[binIdx] = 0
|
||||||
|
|
||||||
proc predict*(g: var GFGun, state: WorldState, bulletSpeed: float): GunPrediction =
|
proc predict*(g: var GFGun, state: WorldState, bulletSpeed: float): GunPrediction =
|
||||||
if bulletSpeed <= 0.0:
|
if bulletSpeed <= 0.0:
|
||||||
return GunPrediction(x: state.enemyX, y: state.enemyY)
|
return GunPrediction(x: state.enemyX, y: state.enemyY)
|
||||||
@@ -57,18 +92,17 @@ proc predict*(g: var GFGun, state: WorldState, bulletSpeed: float): GunPredictio
|
|||||||
let bearing = arctan2(dy, dx)
|
let bearing = arctan2(dy, dx)
|
||||||
let mea = arcsin(clamp(8.0 / bulletSpeed, -1.0, 1.0))
|
let mea = arcsin(clamp(8.0 / bulletSpeed, -1.0, 1.0))
|
||||||
|
|
||||||
# Store one wave per tick regardless of how many power bins call us
|
# Queue at most one wave per (tick, power bin). The fire site's extra predict()
|
||||||
if state.tick != g.cachedTick:
|
# call for the selected bin lands on the same tick and reuses the queued wave.
|
||||||
g.cachedTick = state.tick
|
let binIdx = binForSpeed(bulletSpeed)
|
||||||
g.cachedWaveStored = false
|
if binIdx >= 0 and g.waveStoredTick[binIdx] != state.tick:
|
||||||
|
g.waves[binIdx].add Wave(
|
||||||
if not g.cachedWaveStored:
|
|
||||||
g.waves.add Wave(
|
|
||||||
fireX: state.selfX,
|
fireX: state.selfX,
|
||||||
fireY: state.selfY,
|
fireY: state.selfY,
|
||||||
fireBearing: bearing,
|
fireBearing: bearing,
|
||||||
)
|
)
|
||||||
g.cachedWaveStored = true
|
g.waveStoredTick[binIdx] = state.tick
|
||||||
|
inc g.wavePushes
|
||||||
|
|
||||||
let peak = g.peakBin()
|
let peak = g.peakBin()
|
||||||
let peakGF = indexToGF(peak)
|
let peakGF = indexToGF(peak)
|
||||||
@@ -78,7 +112,7 @@ proc predict*(g: var GFGun, state: WorldState, bulletSpeed: float): GunPredictio
|
|||||||
let py = state.selfY + sin(gfAngle) * dist
|
let py = state.selfY + sin(gfAngle) * dist
|
||||||
|
|
||||||
when DebugGF:
|
when DebugGF:
|
||||||
echo fmt"[gf-dbg] predict: peakGF={peakGF:.2f} peakBin={peak} mea={radToDeg(mea):.1f}° aimAngle={radToDeg(gfAngle):.1f}° waves={g.waves.len}"
|
echo fmt"[gf-dbg] predict: peakGF={peakGF:.2f} peakBin={peak} mea={radToDeg(mea):.1f}° aimAngle={radToDeg(gfAngle):.1f}° waves={g.waves[binIdx].len}"
|
||||||
|
|
||||||
GunPrediction(
|
GunPrediction(
|
||||||
x: clamp(px, BotRadius, state.arenaWidth - BotRadius),
|
x: clamp(px, BotRadius, state.arenaWidth - BotRadius),
|
||||||
@@ -86,17 +120,15 @@ proc predict*(g: var GFGun, state: WorldState, bulletSpeed: float): GunPredictio
|
|||||||
)
|
)
|
||||||
|
|
||||||
proc onResult*(g: var GFGun, e: FeedbackEvent) =
|
proc onResult*(g: var GFGun, e: FeedbackEvent) =
|
||||||
## Called when a virtual bullet resolves. Match the wave by predicted point,
|
## Called when a virtual bullet resolves. Pop the OLDEST unresolved wave from
|
||||||
## compute actual GF, and increment the histogram with a smoothing kernel.
|
## this bullet's own power-bin queue, compute the actual GF, and smooth-add it.
|
||||||
## We don't have the original wave tick here, so we use the prediction coords
|
let binIdx = binForPower(e.bulletPower)
|
||||||
## to identify and remove the matching wave.
|
if binIdx < 0: return
|
||||||
## ponytail: O(n) scan over waves; waves list stays tiny (< a dozen at a time)
|
|
||||||
if g.waves.len == 0:
|
|
||||||
return
|
|
||||||
|
|
||||||
# Pop the oldest wave (FIFO matches bullet resolution order)
|
let (found, w) = g.takeOldestWave(binIdx)
|
||||||
let w = g.waves[0]
|
if not found:
|
||||||
g.waves.delete(0)
|
inc g.waveStarved
|
||||||
|
return
|
||||||
|
|
||||||
# Recompute mea from the actual bullet power (correct per-bin, not the cached first-bin mea)
|
# Recompute mea from the actual bullet power (correct per-bin, not the cached first-bin mea)
|
||||||
let speed = bulletSpeed(e.bulletPower)
|
let speed = bulletSpeed(e.bulletPower)
|
||||||
|
|||||||
@@ -5,6 +5,7 @@
|
|||||||
|
|
||||||
import std/[math]
|
import std/[math]
|
||||||
import gun_harness/gun_interface
|
import gun_harness/gun_interface
|
||||||
|
import gun_harness/virtual_bullets as vb # PowerBins
|
||||||
|
|
||||||
const
|
const
|
||||||
MaxObs = 2000 # ring-buffer cap
|
MaxObs = 2000 # ring-buffer cap
|
||||||
@@ -25,10 +26,14 @@ type
|
|||||||
KNNGun* = object
|
KNNGun* = object
|
||||||
obs: seq[Obs]
|
obs: seq[Obs]
|
||||||
obsHead: int # ring-buffer write index
|
obsHead: int # ring-buffer write index
|
||||||
waves: seq[KNNWave]
|
# One wave queue per power bin; matched on bulletSpeed / bulletPower so a
|
||||||
|
# resolved bullet only ever learns from a wave fired with the same power.
|
||||||
|
waves: array[len(vb.PowerBins), seq[KNNWave]]
|
||||||
|
waveHead: array[len(vb.PowerBins), int] # O(1) pop cursor
|
||||||
|
waveStoredTick: array[len(vb.PowerBins), int] # last tick a wave was queued for this bin
|
||||||
# per-tick cache
|
# per-tick cache
|
||||||
cachedTick: int
|
cachedTick: int
|
||||||
cachedWaveStored: bool
|
tickWave: KNNWave # wave template for the current tick (features computed once)
|
||||||
# rolling normalization ranges
|
# rolling normalization ranges
|
||||||
featMin: array[7, float]
|
featMin: array[7, float]
|
||||||
featMax: array[7, float]
|
featMax: array[7, float]
|
||||||
@@ -36,12 +41,16 @@ type
|
|||||||
lastSpeed: float
|
lastSpeed: float
|
||||||
lastDirection: float # +1 or -1
|
lastDirection: float # +1 or -1
|
||||||
timeSinceDirChange: int
|
timeSinceDirChange: int
|
||||||
|
wavePushes*: int
|
||||||
|
waveStarved*: int
|
||||||
debugGraphics*: bool
|
debugGraphics*: bool
|
||||||
|
|
||||||
proc initKNNGun*(): KNNGun =
|
proc initKNNGun*(): KNNGun =
|
||||||
result.cachedTick = -1
|
result.cachedTick = -1
|
||||||
result.lastDirection = 1.0
|
result.lastDirection = 1.0
|
||||||
result.debugGraphics = false
|
result.debugGraphics = false
|
||||||
|
for b in 0..<len(vb.PowerBins):
|
||||||
|
result.waveStoredTick[b] = -1
|
||||||
for i in 0..6:
|
for i in 0..6:
|
||||||
result.featMin[i] = 1e18
|
result.featMin[i] = 1e18
|
||||||
result.featMax[i] = -1e18
|
result.featMax[i] = -1e18
|
||||||
@@ -105,6 +114,32 @@ proc euclidean(a, b: array[7, float]): float {.inline.} =
|
|||||||
result += d * d
|
result += d * d
|
||||||
result = sqrt(result)
|
result = sqrt(result)
|
||||||
|
|
||||||
|
proc binForSpeed(spd: float): int {.inline.} =
|
||||||
|
## Map a virtual-bullet speed back to its power-bin index. All four bin speeds
|
||||||
|
## are exactly representable floats; the epsilon is belt-and-braces only.
|
||||||
|
for i in 0..<len(vb.PowerBins):
|
||||||
|
if abs(spd - bulletSpeed(vb.PowerBins[i])) < 1e-6:
|
||||||
|
return i
|
||||||
|
-1
|
||||||
|
|
||||||
|
proc binForPower(power: float): int {.inline.} =
|
||||||
|
## Map a FeedbackEvent.bulletPower back to its power-bin index.
|
||||||
|
for i in 0..<len(vb.PowerBins):
|
||||||
|
if abs(power - vb.PowerBins[i]) < 1e-6:
|
||||||
|
return i
|
||||||
|
-1
|
||||||
|
|
||||||
|
proc takeOldestWave(g: var KNNGun, binIdx: int): (bool, KNNWave) =
|
||||||
|
## Pop the oldest unresolved wave for this bin (O(1) amortized via waveHead).
|
||||||
|
if binIdx < 0 or g.waveHead[binIdx] >= g.waves[binIdx].len:
|
||||||
|
return (false, KNNWave())
|
||||||
|
result = (true, g.waves[binIdx][g.waveHead[binIdx]])
|
||||||
|
inc g.waveHead[binIdx]
|
||||||
|
if g.waveHead[binIdx] >= 64 and
|
||||||
|
g.waveHead[binIdx] * 2 >= g.waves[binIdx].len:
|
||||||
|
g.waves[binIdx] = g.waves[binIdx][g.waveHead[binIdx] .. g.waves[binIdx].high]
|
||||||
|
g.waveHead[binIdx] = 0
|
||||||
|
|
||||||
# ── Gun interface ─────────────────────────────────────────────────────────────
|
# ── Gun interface ─────────────────────────────────────────────────────────────
|
||||||
|
|
||||||
proc predict*(g: var KNNGun, state: WorldState, bulletSpd: float): GunPrediction =
|
proc predict*(g: var KNNGun, state: WorldState, bulletSpd: float): GunPrediction =
|
||||||
@@ -119,8 +154,7 @@ proc predict*(g: var KNNGun, state: WorldState, bulletSpd: float): GunPrediction
|
|||||||
|
|
||||||
# Track direction change — update state once per tick
|
# Track direction change — update state once per tick
|
||||||
if state.tick != g.cachedTick:
|
if state.tick != g.cachedTick:
|
||||||
g.cachedTick = state.tick
|
g.cachedTick = state.tick
|
||||||
g.cachedWaveStored = false
|
|
||||||
|
|
||||||
let relHead = state.enemyHeading - bearing
|
let relHead = state.enemyHeading - bearing
|
||||||
let latVel = state.enemySpeed * sin(relHead)
|
let latVel = state.enemySpeed * sin(relHead)
|
||||||
@@ -131,18 +165,26 @@ proc predict*(g: var KNNGun, state: WorldState, bulletSpd: float): GunPrediction
|
|||||||
else:
|
else:
|
||||||
inc g.timeSinceDirChange
|
inc g.timeSinceDirChange
|
||||||
|
|
||||||
# Store wave once per tick
|
# Compute the tick's feature vector ONCE, before lastSpeed is advanced, so
|
||||||
if not g.cachedWaveStored:
|
# every power bin fired this tick shares identical features. lastSpeed is
|
||||||
|
# only advanced here (once/tick), not once per bin.
|
||||||
let feat = buildFeatures(state, g.lastSpeed, g.lastDirection, g.timeSinceDirChange)
|
let feat = buildFeatures(state, g.lastSpeed, g.lastDirection, g.timeSinceDirChange)
|
||||||
g.updateMinMax(feat)
|
g.updateMinMax(feat)
|
||||||
g.waves.add KNNWave(
|
g.tickWave = KNNWave(
|
||||||
fireX: state.selfX,
|
fireX: state.selfX,
|
||||||
fireY: state.selfY,
|
fireY: state.selfY,
|
||||||
fireBearing: bearing,
|
fireBearing: bearing,
|
||||||
feat: feat,
|
feat: feat,
|
||||||
)
|
)
|
||||||
g.lastSpeed = state.enemySpeed
|
g.lastSpeed = state.enemySpeed
|
||||||
g.cachedWaveStored = true
|
|
||||||
|
# Queue at most one wave per (tick, power bin). The fire site's extra predict()
|
||||||
|
# call for the selected bin lands on the same tick and reuses the queued wave.
|
||||||
|
let binIdx = binForSpeed(bulletSpd)
|
||||||
|
if binIdx >= 0 and g.waveStoredTick[binIdx] != state.tick:
|
||||||
|
g.waves[binIdx].add g.tickWave
|
||||||
|
g.waveStoredTick[binIdx] = state.tick
|
||||||
|
inc g.wavePushes
|
||||||
|
|
||||||
# Cold start — no data yet
|
# Cold start — no data yet
|
||||||
if g.obs.len == 0:
|
if g.obs.len == 0:
|
||||||
@@ -236,10 +278,12 @@ proc predict*(g: var KNNGun, state: WorldState, bulletSpd: float): GunPrediction
|
|||||||
)
|
)
|
||||||
|
|
||||||
proc onResult*(g: var KNNGun, e: FeedbackEvent) =
|
proc onResult*(g: var KNNGun, e: FeedbackEvent) =
|
||||||
if g.waves.len == 0: return
|
let binIdx = binForPower(e.bulletPower)
|
||||||
|
if binIdx < 0: return
|
||||||
let w = g.waves[0]
|
let (found, w) = g.takeOldestWave(binIdx)
|
||||||
g.waves.delete(0)
|
if not found:
|
||||||
|
inc g.waveStarved
|
||||||
|
return
|
||||||
|
|
||||||
let speed = bulletSpeed(e.bulletPower)
|
let speed = bulletSpeed(e.bulletPower)
|
||||||
let mea = arcsin(clamp(8.0 / speed, -1.0, 1.0))
|
let mea = arcsin(clamp(8.0 / speed, -1.0, 1.0))
|
||||||
|
|||||||
Reference in New Issue
Block a user