SirStone
254c7dc997
- Gun harness: virtual bullet tracker, rolling fitness, auto-selector - Guns: head-on, linear (extrapolation), circular (integrated formula), tsetlin machine (learning) - Movement: phantom meteor gravity engine (danger histograms, phantom bullets, fire detection) - Radar: harness + radar_lock adapter - Color-coded modules: turret/bullet color per gun, body per movement, scan per radar - Beats Target, SpinBot, Crazy, TrackFire in 10-round battles
51 lines
1.7 KiB
Nim
51 lines
1.7 KiB
Nim
import std/math
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import binary_encoding
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const
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N_SECTORS = 8
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N_BANDS = 3
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LEARNING_RATE = 0.2
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BAND_THR_LO = 33.0
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BAND_THR_HI = 66.0
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type
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ResidualTable* = object
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corrections*: array[N_SECTORS * N_BANDS, tuple[cx, cy: float]]
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proc initPredictor*(): ResidualTable = discard # zero-init is correct
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proc getSector*(headingSin, headingCos: int): int =
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let s = headingSin.float / 199.0 * 2.0 - 1.0
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let c = headingCos.float / 199.0 * 2.0 - 1.0
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var deg = radToDeg(arctan2(s, c))
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if deg < 0.0: deg += 360.0
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int(deg / 45.0) mod N_SECTORS
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proc getBand*(distance: int): int =
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if distance.float < BAND_THR_LO: 0
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elif distance.float < BAND_THR_HI: 1
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else: 2
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proc predict*(table: ResidualTable,
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f0, f1: array[NUM_FRAME_FIELDS, int],
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power: float): tuple[predX, predY: float] =
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# field indices: 2=distance, 4=heading_sin, 5=heading_cos, 6=enemy_x, 7=enemy_y
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let bulletSpd = 20.0 - 3.0 * power
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let distancePx = f0[2].float / 99.0 * 1414.0
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let ticks = distancePx / bulletSpd
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let vx = float(f0[6] - f1[6])
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let vy = float(f0[7] - f1[7])
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let sector = getSector(f0[4], f0[5])
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let band = getBand(f0[2])
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let corr = table.corrections[sector * N_BANDS + band]
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result.predX = f0[6].float + vx * ticks + corr.cx
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result.predY = f0[7].float + vy * ticks + corr.cy
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proc sectorBand*(f0: array[NUM_FRAME_FIELDS, int]): tuple[sector, band: int] =
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(getSector(f0[4], f0[5]), getBand(f0[2]))
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proc learn*(table: var ResidualTable, sector, band: int,
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residualX, residualY: float) =
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table.corrections[sector * N_BANDS + band].cx += LEARNING_RATE * residualX
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table.corrections[sector * N_BANDS + band].cy += LEARNING_RATE * residualY
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