Files
SirRoboGarage/common_libs/guns/decay_gf.nim
T
SirStone 0cc682152d 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.
2026-09-20 22:27:52 +02:00

136 lines
4.5 KiB
Nim

## Recency-weighted GF gun: exponential decay on histogram bins.
## decay=0.998/tick gives ~350-tick half-life — adapts to mid-battle strategy shifts.
## Everything else identical to guess_factor.nim, including per-power-bin wave queues.
import std/math
import gun_harness/gun_interface
import gun_harness/virtual_bullets as vb # PowerBins
const
GFBins = 31
GFPrior = 0.1
DecayRate = 0.998 # ponytail: single global decay, tune if adaptation too slow/fast
DecayWaveCompactAt = 64
type
DWave = object
fireX, fireY: float
fireBearing: float
DecayGFGun* = object
bins: array[GFBins, float]
# One wave queue per power bin; a resolved bullet only learns from a wave
# queued for its own bin (matched on bulletSpeed / bulletPower).
waves: array[len(vb.PowerBins), seq[DWave]]
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
cachedTick: int # last tick bins were decayed
wavePushes*: int
waveStarved*: int
debugGraphics*: bool
proc initDecayGFGun*(): DecayGFGun =
result.cachedTick = -1
result.debugGraphics = false
for b in 0..<len(vb.PowerBins):
result.waveStoredTick[b] = -1
let center = (GFBins - 1) div 2
for i in 0..<GFBins:
let d = abs(i - center)
result.bins[i] = GFPrior + 0.5 / float(1 + d)
proc gfToIndex(gf: float): int {.inline.} =
clamp(int(round((gf + 1.0) * 0.5 * float(GFBins - 1))), 0, GFBins - 1)
proc indexToGF(idx: int): float {.inline.} =
float(idx) / float(GFBins - 1) * 2.0 - 1.0
proc peakBin(g: DecayGFGun): int =
var best = 0
for i in 1..<GFBins:
if g.bins[i] > g.bins[best]:
best = i
best
proc binForSpeed(spd: float): int {.inline.} =
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.} =
for i in 0..<len(vb.PowerBins):
if abs(power - vb.PowerBins[i]) < 1e-6:
return i
-1
proc takeOldestWave(g: var DecayGFGun, binIdx: int): (bool, DWave) =
if binIdx < 0 or g.waveHead[binIdx] >= g.waves[binIdx].len:
return (false, DWave())
result = (true, g.waves[binIdx][g.waveHead[binIdx]])
inc g.waveHead[binIdx]
if g.waveHead[binIdx] >= DecayWaveCompactAt 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 DecayGFGun, state: WorldState, bulletSpeed: float): GunPrediction =
if bulletSpeed <= 0.0:
return GunPrediction(x: state.enemyX, y: state.enemyY)
let dx = state.enemyX - state.selfX
let dy = state.enemyY - state.selfY
let dist = sqrt(dx*dx + dy*dy)
let bearing = arctan2(dy, dx)
let mea = arcsin(clamp(8.0 / bulletSpeed, -1.0, 1.0))
if state.tick != g.cachedTick:
# Decay all bins once per tick
for i in 0..<GFBins:
g.bins[i] *= DecayRate
g.cachedTick = state.tick
# 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(bulletSpeed)
if binIdx >= 0 and g.waveStoredTick[binIdx] != state.tick:
g.waves[binIdx].add DWave(fireX: state.selfX, fireY: state.selfY, fireBearing: bearing)
g.waveStoredTick[binIdx] = state.tick
inc g.wavePushes
let peak = g.peakBin()
let peakGF = indexToGF(peak)
let gfAngle = bearing + peakGF * mea
let px = state.selfX + cos(gfAngle) * dist
let py = state.selfY + sin(gfAngle) * dist
GunPrediction(
x: clamp(px, BotRadius, state.arenaWidth - BotRadius),
y: clamp(py, BotRadius, state.arenaHeight - BotRadius),
)
proc onResult*(g: var DecayGFGun, e: FeedbackEvent) =
let binIdx = binForPower(e.bulletPower)
if binIdx < 0: return
let (found, w) = g.takeOldestWave(binIdx)
if not found:
inc g.waveStarved
return
let speed = bulletSpeed(e.bulletPower)
let mea = arcsin(clamp(8.0 / speed, -1.0, 1.0))
let actualDx = e.actualX - w.fireX
let actualDy = e.actualY - w.fireY
let actualBearing = arctan2(actualDy, actualDx)
var bearingDelta = actualBearing - w.fireBearing
while bearingDelta > PI: bearingDelta -= 2.0*PI
while bearingDelta < -PI: bearingDelta += 2.0*PI
let gf = if mea > 1e-10: clamp(bearingDelta / mea, -1.0, 1.0) else: 0.0
let centerIdx = gfToIndex(gf)
for i in 0..<GFBins:
let d = abs(i - centerIdx)
g.bins[i] += 1.0 / float(1 + d)