Energy economy: the cliff becomes a SLOPE, plus a finishing cap. 11% less energy.
The user's request: "when our bot is low OR enemy is low, it is useless to use high power instead low fast bullets have more chances to finish the enemy. Let's do a math slope: starting from some health down, the power goes down with it." 1. ENERGY SLOPE (`TR_POWER_ENERGY_*`), replacing the old hard step at 50 energy: cap = ENERGY_MAX at/above ENERGY_HI, ENERGY_MIN at/below ENERGY_LO, LINEAR in power between, clamped. Defaults HI=80 LO=20 MIN=0.5 MAX=3.0, so no cap >=80, 0.5 at <=20, and e.g. E=65 -> 2.375, E=50 -> 1.75, E=35 -> 1.125. Rationale: bullet speed is 20-3p, so lower power = FASTER bullet (less lead error, higher hit chance), fires more often (10+2p) and drains slower (p/shot). E[dE] = p(3P-1) => break-even hit probability is 1/3 INDEPENDENT of power, and our measured rates are 5-27%, far below it. 2. FINISHING CAP (`TR_POWER_FINISH_KILL`, default ON): cap power at the SMALLEST bullet that still removes the enemy's remaining energy - `E<=4 -> p=E/4` (min 0.1), `4<E<=16 -> p=(E+2)/6`, `E>16 -> no cap`. Rationale, and it makes the user's instinct stronger than a heuristic: server 1.3.1 caps the damage SCORE at the energy ACTUALLY REMOVED, so overkill is WASTED damage AND ~6x the energy for ZERO extra score. Damage is 4p (p<=1) / 6p-2 (p>1). Both are min-composed with the existing far/below-average caps, may only LOWER power (exhaustively tested), and are exempt while ramming. `TR_POWER_POLICY=0` still returns the uncapped control exactly. MEASURED ENERGY SAVING (offline replay of the DrussGT fixtures, 28,797 ticks): arm shots energy meanP E/1k ticks vs cliff control(uncapped) 1913 4646 2.43 161.4 -90.2% cliff (today) 2363 2443 1.03 84.8 0.0% slope 2404 2178 0.91 75.6 ** 10.9% LESS ** slope+finish 2404 2167 0.90 75.3 ** 11.3% LESS ** So the slope spends ~11% less energy than the cliff AND fires slightly MORE shots (2404 vs 2363) - both directions at once. HONEST NOTE on the finishing rule's reach here: ticks where the enemy is low (0 < E <= 16) are only 2252/28797 = 7.8% of these fixtures, so finishing adds just ~11 energy of saving against DrussGT. It matters in CLOSER fights, not this one. Verification: test_power_policy 58 (was 26) in BOTH the default and TR_POWER_POLICY=0 control arms - slope at E=100/80/65/50/35/20/5, powerToKill across E=0.1..100, the inverse-cover property for E<=16, monotonicity, ram exemption, and an exhaustive sweep proving power <= preference. Guards: test_gun_harness 39, test_vbullet_metric 11, test_power_selection 3, test_adaptive_radar 41, test_tfil_ring_weights 24, test_ram_decision 40, test_rack_membership 48, test_selector_tiebreak 19, test_tm_pattern_registration 20, test_vbullet_admit_gate 12. acceptance 12/12 PASS. ModularBot compiles release. Adds `common_libs/tests/measure_power_policy.nim` (the energy/histogram tool) and updates docs/env_reference.md for the new `energySlope|finishKill` log reasons. NOT MEASURED: the battle/hit-rate effect. The offline figures use the fixture shooter's energy as a proxy, open-loop; the RELATIVE saving is the meaningful part.
This commit is contained in:
@@ -193,6 +193,7 @@ proc shouldFire*(currentGunDir, targetAngle, gunHeat, distPx: float): bool =
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proc selectShotPolicy*(t: var VirtualTracker, targetId = -1, tick = 0,
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dist = 0.0, selfEnergy = 100.0,
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enemyEnergy = 100.0,
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ramming = false,
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rackMode: RackMode = rm1v1,
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membership: openArray[RackMembership] = []
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@@ -200,10 +201,11 @@ proc selectShotPolicy*(t: var VirtualTracker, targetId = -1, tick = 0,
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## `selectShot` plus the energy-aware power-policy decision, so a caller can
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## log the cap and its reason (see `applyPowerPolicy` in virtual_bullets).
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##
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## `dist` is the current distance (px) to the target and `selfEnergy` our own
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## energy; `ramming` exempts the caps (the movement code's `shouldRam` is the
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## single source of truth). The policy is applied identically wherever this is
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## called, so live and any offline caller cannot diverge.
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## `dist` is the current distance (px) to the target, `selfEnergy` our own
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## energy and `enemyEnergy` the target's remaining energy (drives the
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## finishing cap); `ramming` exempts the caps (the movement code's `shouldRam`
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## is the single source of truth). The policy is applied identically wherever
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## this is called, so live and any offline caller cannot diverge.
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##
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## `rackMode` is the server-truth enemy-count mode (`rackMode`); `membership`
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## is the process-wide `TR_RACK_*` table, passed by the live bot. An empty
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@@ -221,21 +223,25 @@ proc selectShotPolicy*(t: var VirtualTracker, targetId = -1, tick = 0,
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let pEst =
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if fit[gunId].bins[prefBin].count == 0: pRef
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else: fit[gunId].bins[prefBin].hitRate()
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let dec = applyPowerPolicy(preferred, dist, selfEnergy, pEst, pRef, ramming)
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let dec = applyPowerPolicy(preferred, dist, selfEnergy, pEst, pRef, ramming,
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enemyEnergy = enemyEnergy)
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result = (gunId, binIndexForPower(dec.power), dec.power, dec)
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proc selectShot*(t: var VirtualTracker, targetId = -1, tick = 0,
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dist = 0.0, selfEnergy = 100.0,
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enemyEnergy = 100.0,
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ramming = false,
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rackMode: RackMode = rm1v1,
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membership: openArray[RackMembership] = []): (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. `tick` drives
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## the minimum-dwell hysteresis (see `selectGun`). `dist`/`selfEnergy`/`ramming`
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## feed the energy-aware power cap (`TR_POWER_POLICY`); defaults keep every
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## existing caller compiling, and `TR_POWER_POLICY=0` reproduces the uncapped
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## `bestPower` preference. Use `selectShotPolicy` when the cap/reason is needed.
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## the minimum-dwell hysteresis (see `selectGun`). `dist`/`selfEnergy`/
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## `enemyEnergy`/`ramming` feed the energy-aware power cap (`TR_POWER_POLICY`);
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## defaults keep every existing caller compiling, and `TR_POWER_POLICY=0`
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## reproduces the uncapped `bestPower` preference. Use `selectShotPolicy` when
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## the cap/reason is needed.
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let (gunId, binIdx, power, _) =
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t.selectShotPolicy(targetId, tick, dist, selfEnergy, ramming,
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t.selectShotPolicy(targetId, tick, dist, selfEnergy,
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enemyEnergy = enemyEnergy, ramming = ramming,
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rackMode = rackMode, membership = membership)
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result = (gunId, binIdx, power)
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@@ -798,40 +798,66 @@ proc bestPower*(t: VirtualTracker, gunId: GunId, targetId: int = -1): (int, floa
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#
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# `bestPower` answers "which power bin does this gun's own virtual data prefer?"
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# and is deliberately left untouched. The policy below CAPS that preference using
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# only cheap, always-available state — range, our own energy, and the gun's own
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# rate — so a long-range or low-energy shot trades single-hit damage for a
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# faster bullet (speed = 20-3p, so LOW power is FASTER and needs less lead) and a
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# shorter fire interval (10+2p, so LOW power = MORE shots). It never RAISES
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# power, so the shipped behaviour is exactly the `cap = 3.0` case, which is also
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# the control arm (`TR_POWER_POLICY=0`).
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# only cheap, always-available state — range, our own energy, the ENEMY's energy,
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# and the gun's own rate. It never RAISES power, so the shipped behaviour is
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# exactly the `cap = 3.0` case, which is also the control arm
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# (`TR_POWER_POLICY=0`). Every rule is an ADDITIONAL cap: the applied cap is the
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# minimum of all of them.
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#
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# Two rules are the energy-economy improvement:
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#
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# 1. ENERGY SLOPE (replaces the old `TR_POWER_LOW_ENERGY` CLIFF at 50): cap our
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# power as a LINEAR function of OUR energy — `TR_POWER_ENERGY_MAX` at/above
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# `TR_POWER_ENERGY_HI`, `TR_POWER_ENERGY_MIN` at/below `TR_POWER_ENERGY_LO`,
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# linear in between. A lower power is a FASTER bullet (speed = 20-3p, so less
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# lead error -> higher hit chance), fires more often (interval 10+2p) and
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# drains energy more slowly (cost p/shot). Energy math: E[dE] = p(3P-1), so
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# the break-even hit probability is 1/3 INDEPENDENT of power; our measured
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# hit rates are 5-27%, far below 1/3, so every point of power above the
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# minimum costs more than it returns. Below HI the old code was a hard step.
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#
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# 2. FINISHING SLOPE (`TR_POWER_FINISH_KILL`): when the ENEMY is low, cap power
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# at the SMALLEST bullet that still removes its remaining energy. Server
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# 1.3.1 caps the `bulletDamage` score at the energy ACTUALLY REMOVED, so
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# overkill is WASTED damage AND ~6x the energy for ZERO extra score. Damage
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# is `4p` for p<=1 and `6p-2` for p>1, so the minimum power that covers `E`
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# is `E/4` (clamped to >=0.1) for E<=4, `(E+2)/6` for 4<E<=16, and no cap
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# above 16 (even p=3.0 removes only 16).
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#
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# Measured basis (real shots vs DrussGT, 8-16 runs): hit rate 21.6% at 0-100px,
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# 27.1% at 100-200, then 19.3% at 200-300, 10.9% at 300-400, 6.8% at 400-600 and
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# 5.4% at 600-800. Energy math: E[dE] = p(3P-1), so the break-even hit
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# probability is 1/3 INDEPENDENT of power; at range/low energy the extra speed
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# and shots of p=1.0 dominate. Damage is 4p (p<=1) / 6p-2 (p>1).
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# 5.4% at 600-800. Damage is 4p (p<=1) / 6p-2 (p>1).
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const
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PowerPolicyEnvVar* = "TR_POWER_POLICY" ## 0 = control arm (uncapped)
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PowerFarDistEnvVar* = "TR_POWER_FAR_DIST" ## px; beyond this = bad-chances zone
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PowerLowEnergyEnvVar* = "TR_POWER_LOW_ENERGY" ## self energy below this = conserve
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PowerFarCapEnvVar* = "TR_POWER_FAR_CAP" ## cap for far / low-energy
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PowerFarCapEnvVar* = "TR_POWER_FAR_CAP" ## cap for far
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PowerMidCapEnvVar* = "TR_POWER_MID_CAP" ## cap when close+healthy but not above avg
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PowerRefEnvVar* = "TR_POWER_REF" ## 0 = gun's own mean; >0 = fixed P_ref
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PowerEnergyHiEnvVar* = "TR_POWER_ENERGY_HI" ## self energy at/above which = no slope cap
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PowerEnergyLoEnvVar* = "TR_POWER_ENERGY_LO" ## self energy at/below which = ENERGY_MIN
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PowerEnergyMinEnvVar* = "TR_POWER_ENERGY_MIN" ## the cap at/below ENERGY_LO
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PowerEnergyMaxEnvVar* = "TR_POWER_ENERGY_MAX" ## the cap at/above ENERGY_HI (3.0 = uncapped)
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PowerFinishKillEnvVar* = "TR_POWER_FINISH_KILL" ## 1 = cap to the smallest killing bullet
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let PowerPolicyEnabled* = envBool(PowerPolicyEnvVar, true)
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let PowerFarDist* = envFloat(PowerFarDistEnvVar, 200.0)
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let PowerLowEnergy* = envFloat(PowerLowEnergyEnvVar, 50.0)
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let PowerFarCap* = envFloat(PowerFarCapEnvVar, 1.0)
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let PowerMidCap* = envFloat(PowerMidCapEnvVar, 2.0)
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let PowerRefFixed* = envFloat(PowerRefEnvVar, 0.0)
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let PowerEnergyHi* = envFloat(PowerEnergyHiEnvVar, 80.0)
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let PowerEnergyLo* = envFloat(PowerEnergyLoEnvVar, 20.0)
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let PowerEnergyMin* = envFloat(PowerEnergyMinEnvVar, 0.5)
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let PowerEnergyMax* = envFloat(PowerEnergyMaxEnvVar, 3.0)
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let PowerFinishKill* = envBool(PowerFinishKillEnvVar, true)
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type
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PowerReason* = enum
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prFull ## above-average chances, close, healthy -> full power
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prFar ## beyond TR_POWER_FAR_DIST -> bad-chances zone
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prLowEnergy ## self energy below TR_POWER_LOW_ENERGY -> conserve
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prBelowAvg ## chances not above the gun's own average -> no power 3.0
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prRam ## ramming: exempt (at contact P->1, so 3.0 is correct)
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prFull ## no cap binds -> the gun's own preference
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prFar ## beyond TR_POWER_FAR_DIST -> bad-chances zone
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prEnergySlope ## OUR energy below TR_POWER_ENERGY_HI -> linear conserve cap
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prFinishKill ## ENEMY energy low -> smallest bullet that still finishes it
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prBelowAvg ## chances not above the gun's own average -> no power 3.0
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prRam ## ramming: exempt (at contact P->1, so 3.0 is correct)
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PowerCap* = object
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power*: float ## the power to fire (<= the gun's preference)
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@@ -840,11 +866,52 @@ type
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proc powerReasonName*(r: PowerReason): string =
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case r
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of prFull: "full"
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of prFar: "far"
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of prLowEnergy: "lowEnergy"
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of prBelowAvg: "belowAvg"
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of prRam: "ram"
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of prFull: "full"
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of prFar: "far"
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of prEnergySlope: "energySlope"
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of prFinishKill: "finishKill"
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of prBelowAvg: "belowAvg"
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of prRam: "ram"
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proc bulletDamageAtPower*(power: float): float =
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## Energy the server removes for a bullet of `power`: `4p` for `p <= 1` and
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## `6p - 2` for `p > 1` (and 0 for `p <= 0`), mirroring the server's
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## `rules/math.kt calcBulletDamage`. Kept local so `gun_harness` has no
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## dependency on the movement modules (which define the same `bulletDamage`).
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if power <= 0.0: return 0.0
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var p = power
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if p < 0.1: p = 0.1
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elif p > 3.0: p = 3.0
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result = 4.0 * p
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if p > 1.0: result += 2.0 * (p - 1.0)
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proc powerToKill*(enemyEnergy: float): float =
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## The SMALLEST power whose bullet damage covers `enemyEnergy`, i.e. the
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## inverse of `bulletDamageAtPower`:
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## E <= 4 -> p = E/4 (clamped to >= 0.1)
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## E > 4 -> p = (E+2)/6
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## E > 16 -> 3.0 (no cap: even p=3.0 removes only 16, so nothing smaller
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## helps and the normal rules decide)
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## Exactly covers E in the first two branches (`4p = E` and `6p-2 = E`); the
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## clamp makes it cover E <= 0.4 too. PURE, exposed for testing.
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if enemyEnergy > 16.0: return 3.0
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if enemyEnergy <= 4.0: return max(0.1, enemyEnergy / 4.0)
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(enemyEnergy + 2.0) / 6.0
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proc energySlopeCap*(selfEnergy: float,
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hi = PowerEnergyHi,
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lo = PowerEnergyLo,
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capMin = PowerEnergyMin,
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capMax = PowerEnergyMax): float =
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## Linear power cap vs OUR energy: `capMax` at/above `hi`, `capMin` at/below
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## `lo`, linear in POWER in between, clamped to `[capMin, capMax]`. The
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## shipped defaults (3.0 at 80, 0.5 at 20) mean "no cap above 80, half-power at
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## or below 20". `capMax` is the value at/above HI; at its default 3.0 that is
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## exactly "no cap from this rule". PURE, exposed for testing.
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if selfEnergy >= hi: return capMax
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if selfEnergy <= lo: return capMin
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let t = (selfEnergy - lo) / (hi - lo)
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clamp(capMin + t * (capMax - capMin), capMin, capMax)
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proc binIndexForPower*(power: float): int =
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## Index of `power` in `PowerBins`; if it is not an exact bin value, the
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@@ -857,38 +924,51 @@ proc binIndexForPower*(power: float): int =
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proc applyPowerPolicy*(preferredPower, dist, selfEnergy, pEst, pRef: float,
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ramming: bool,
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enemyEnergy = 100.0,
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enabled = PowerPolicyEnabled,
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farDist = PowerFarDist,
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lowEnergy = PowerLowEnergy,
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energyHi = PowerEnergyHi,
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energyLo = PowerEnergyLo,
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energyMin = PowerEnergyMin,
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energyMax = PowerEnergyMax,
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finishKill = PowerFinishKill,
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farCap = PowerFarCap,
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midCap = PowerMidCap): PowerCap =
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## PURE cap core — no tracker, no battle. `power = min(preferredPower, cap)`,
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## so the result can only ever LOWER the gun's own preference. Order of
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## precedence: ram (exempt) > far > low energy > below average > full.
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## so the result can only ever LOWER the gun's own preference. Each rule is an
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## additional cap; the applied cap is the MINIMUM of all of them, and `reason`
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## names the rule that set it (ties resolved by the order below, which is also
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## the precedence order): ram (exempt) > far > energy slope > below average >
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## finishing. `prFull` means nothing capped.
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##
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## `pEst` is the gun's rate for the bin it chose (or its aggregate when that
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## bin is empty); `pRef` is the gun's aggregate mean (or the fixed
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## `TR_POWER_REF`). A cold gun has no data, so `pEst <= pRef` is vacuously
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## true and it gets the mid cap — deliberately conservative until it has
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## evidence its chances are above average.
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##
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## `enemyEnergy` drives the finishing rule; its default (100) means "no
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## finishing cap", so every pre-existing caller is unchanged. The finishing
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## rule is skipped for `enemyEnergy <= 0` (a dead/unknown target), so a zero
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## energy reading cannot collapse power to 0.1.
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if ramming:
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return PowerCap(power: preferredPower, cap: 3.0, reason: prRam)
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if not enabled:
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return PowerCap(power: preferredPower, cap: 3.0, reason: prFull)
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var cap: float
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var reason: PowerReason
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if dist > farDist:
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cap = farCap
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reason = prFar
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elif selfEnergy < lowEnergy:
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cap = farCap
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reason = prLowEnergy
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elif pEst <= pRef:
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cap = midCap
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reason = prBelowAvg
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else:
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cap = 3.0
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reason = prFull
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var cap = 3.0
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var reason = prFull
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template noteCap(c: float, r: PowerReason) =
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## Adopt `c` as the cap only when it is STRICTLY smaller, so ties keep the
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## higher-precedence rule's reason (the order of the calls below).
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if c < cap:
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cap = c
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reason = r
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if dist > farDist: noteCap(farCap, prFar)
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noteCap(energySlopeCap(selfEnergy, energyHi, energyLo, energyMin, energyMax),
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prEnergySlope)
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if pEst <= pRef: noteCap(midCap, prBelowAvg)
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if finishKill and enemyEnergy > 0.0:
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noteCap(powerToKill(enemyEnergy), prFinishKill)
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PowerCap(power: min(preferredPower, cap), cap: cap, reason: reason)
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proc chooseFromFit*(fit: seq[GunFitness], diag: ptr SelectorDiag = nil,
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@@ -0,0 +1,210 @@
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## Offline energy-economy measurement for the power policy (TR_POWER_*).
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##
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## Replays the committed DrussGT movement fixtures through the real VirtualTracker
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## (same path the range/acceptance tests use) and, per tick, computes the power
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## the SHIPPED rack's only gun (Pattern, id 5) would prefer (`bestPower`). It then
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## simulates four policy arms against that SAME preference sequence:
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##
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## control : uncapped (TR_POWER_POLICY=0) — the baseline
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## cliff : TODAY's shipped rule (far 1.0, self energy < 50 -> 1.0, belowAvg 2.0)
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## slope : the new linear self-energy cap (finishing OFF)
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## finish : slope + the new smallest-killing-bullet cap (finishing ON)
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##
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## The fire schedule uses the server's gun heat: a shot adds `1 + p/5` heat and
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## the gun cools `0.1`/tick, so the interval is `10 + 2p` ticks — LOWER power fires
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## more often. `energySpent` sums the fired power over shots; the histogram counts
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## shots at each 0.1-wide power bucket.
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##
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## IMPORTANT (labelled in the output): the trajectory is recorded (open-loop,
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## perfect-information) so this is NOT a closed-loop hit-rate A/B. What is
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## MEASURED is the policy's energy draw over real recorded movement; what is
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## INFERRED is the resulting battle outcome. Hit rates are NOT modelled here.
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##
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## Run: nim c -r common_libs/tests/measure_power_policy.nim
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import std/[os, strformat, strutils, math, tables, algorithm]
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import gun_harness/offline_range
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import gun_harness/virtual_bullets
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import range_guns
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const
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repoRoot = currentSourcePath().parentDir.parentDir.parentDir
|
||||
fixturesDir = repoRoot / "tools" / "fixtures"
|
||||
ShippedGunId = 5 ## Pattern — the only gun in the shipped rack
|
||||
CoolRate = 0.1 ## gun heat lost per tick (server config)
|
||||
OldCliffEnergy = 50.0 ## TR_POWER_LOW_ENERGY's old hard threshold
|
||||
|
||||
const FixtureNames = [
|
||||
"drussgt_vs_spinbot.jsonl",
|
||||
"drussgt_vs_ramfire.jsonl",
|
||||
"drussgt_vs_crazy.jsonl",
|
||||
"drussgt_vs_corners.jsonl",
|
||||
"drussgt_vs_drussgt.jsonl",
|
||||
]
|
||||
|
||||
type
|
||||
Arm* = enum
|
||||
aControl ## uncapped — the control arm
|
||||
aCliff ## today's shipped cliff
|
||||
aSlope ## new energy slope only
|
||||
aFinish ## energy slope + finishing
|
||||
|
||||
TickRec = object
|
||||
dist, selfE, enemyE: float
|
||||
prefPower: float
|
||||
pEst, pRef: float
|
||||
|
||||
SimResult = object
|
||||
shots: int
|
||||
energy: float
|
||||
hist: Table[int, int] ## key = round(power*10)
|
||||
|
||||
proc armName(a: Arm): string =
|
||||
case a
|
||||
of aControl: "control"
|
||||
of aCliff: "cliff "
|
||||
of aSlope: "slope "
|
||||
of aFinish: "finish "
|
||||
|
||||
proc firedPower(arm: Arm, r: TickRec): float =
|
||||
## The power this arm would fire given the gun's own preference and the
|
||||
## per-tick state. `applyPowerPolicy` already returns `min(preference, cap)`.
|
||||
case arm
|
||||
of aControl:
|
||||
r.prefPower
|
||||
of aCliff:
|
||||
var cap = 3.0
|
||||
if r.dist > PowerFarDist: cap = PowerFarCap
|
||||
elif r.selfE < OldCliffEnergy: cap = PowerFarCap
|
||||
elif r.pEst <= r.pRef: cap = PowerMidCap
|
||||
min(r.prefPower, cap)
|
||||
of aSlope:
|
||||
applyPowerPolicy(r.prefPower, r.dist, r.selfE, r.pEst, r.pRef, false,
|
||||
enemyEnergy = r.enemyE, enabled = true,
|
||||
finishKill = false).power
|
||||
of aFinish:
|
||||
applyPowerPolicy(r.prefPower, r.dist, r.selfE, r.pEst, r.pRef, false,
|
||||
enemyEnergy = r.enemyE, enabled = true,
|
||||
finishKill = true).power
|
||||
|
||||
proc collect(fx: Fixture): seq[TickRec] =
|
||||
## One pass through the real tracker, recording the per-tick preference and
|
||||
## policy inputs. The preference sequence is arm-INDEPENDENT (virtual bullets
|
||||
## are spawned for every bin regardless of what we fire), so all four arms are
|
||||
## compared against the exact same sequence.
|
||||
var recs: seq[TickRec]
|
||||
var tickIdx = 0
|
||||
let drivers = buildAllGunDrivers(seed = 1)
|
||||
let cb = proc(t: ptr VirtualTracker) =
|
||||
let si = tickIdx
|
||||
inc tickIdx
|
||||
if si >= fx.states.len: return
|
||||
let st = fx.states[si]
|
||||
let tid = fx.enemyId
|
||||
let (prefBin, prefPower) = t[].bestPower(ShippedGunId, tid)
|
||||
let fit = t[].fitnessFor(tid)
|
||||
let pRef = gunRate(fit[ShippedGunId], pooled = true)
|
||||
let pEst =
|
||||
if fit[ShippedGunId].bins[prefBin].count == 0: pRef
|
||||
else: fit[ShippedGunId].bins[prefBin].hitRate()
|
||||
recs.add TickRec(
|
||||
dist: hypot(st.enemyX - st.selfX, st.enemyY - st.selfY),
|
||||
selfE: st.selfEnergy,
|
||||
enemyE: st.enemyEnergy,
|
||||
prefPower: prefPower,
|
||||
pEst: pEst, pRef: pRef)
|
||||
discard replayFixture(fx, drivers, metric = bmPath, tickCb = cb)
|
||||
recs
|
||||
|
||||
proc simulate(recs: seq[TickRec], arm: Arm): SimResult =
|
||||
## Fire whenever the gun is cool (heat <= 0), drawing `power` energy per shot
|
||||
## and adding `1 + p/5` heat. Mirrors the live `setFire` + `getEnergy() > power`
|
||||
## guard, so a shot is skipped if our energy cannot cover it.
|
||||
var heat = 0.0
|
||||
for r in recs:
|
||||
heat = max(0.0, heat - CoolRate)
|
||||
if heat > 1e-9: continue
|
||||
let p = firedPower(arm, r)
|
||||
if r.selfE <= p: continue
|
||||
result.energy += p
|
||||
inc result.shots
|
||||
let key = int(round(p * 10.0))
|
||||
result.hist[key] = result.hist.getOrDefault(key) + 1
|
||||
heat = 1.0 + p / 5.0
|
||||
|
||||
proc addHist(dst: var Table[int, int], src: Table[int, int]) =
|
||||
for k, v in src: dst[k] = dst.getOrDefault(k) + v
|
||||
|
||||
proc histLine(h: Table[int, int]): string =
|
||||
var keys: seq[int]
|
||||
for k in h.keys: keys.add k
|
||||
keys.sort()
|
||||
for k in keys:
|
||||
if result.len > 0: result.add " "
|
||||
result.add fmt"p={k.float/10.0:.1f}:{h[k]}"
|
||||
|
||||
proc main() =
|
||||
echo "=== offline energy-economy measurement (power policy) ==="
|
||||
echo "fixtures: ", FixtureNames.len, " gun: Pattern(id=", ShippedGunId, ")"
|
||||
echo "heat model: +1+p/5 per shot, -0.1/tick => interval 10+2p ticks"
|
||||
echo ""
|
||||
|
||||
var totalTicks = 0
|
||||
var lowEnemyTicks = 0
|
||||
var agg: array[Arm, SimResult]
|
||||
|
||||
echo "fixture ticks arm shots energy meanP"
|
||||
echo "-".repeat(72)
|
||||
for name in FixtureNames:
|
||||
let path = fixturesDir / name
|
||||
if not fileExists(path):
|
||||
echo " (missing: ", path, ")"
|
||||
continue
|
||||
let fx = loadFixture(path)
|
||||
let recs = collect(fx)
|
||||
totalTicks += recs.len
|
||||
for r in recs:
|
||||
if r.enemyE > 0.0 and r.enemyE <= 16.0: inc lowEnemyTicks
|
||||
for arm in Arm:
|
||||
let s = simulate(recs, arm)
|
||||
agg[arm].shots += s.shots
|
||||
agg[arm].energy += s.energy
|
||||
agg[arm].hist.addHist(s.hist)
|
||||
let meanP = if s.shots > 0: s.energy / s.shots.float else: 0.0
|
||||
echo fmt"{name:<26} {recs.len:>6} {armName(arm):<8} {s.shots:>6} " &
|
||||
fmt"{s.energy:>8.0f} {meanP:>6.2f}"
|
||||
echo ""
|
||||
|
||||
echo "=== AGGREGATE over all fixtures (", totalTicks, " ticks) ==="
|
||||
echo "arm shots energy meanP E/1k ticks vs control vs cliff"
|
||||
echo "-".repeat(72)
|
||||
let base = agg[aControl].energy
|
||||
let cliff = agg[aCliff].energy
|
||||
for arm in Arm:
|
||||
let s = agg[arm]
|
||||
let meanP = if s.shots > 0: s.energy / s.shots.float else: 0.0
|
||||
let per1k = if totalTicks > 0: s.energy / totalTicks.float * 1000.0 else: 0.0
|
||||
let vsControl = if base > 0: (base - s.energy) / base * 100.0 else: 0.0
|
||||
let vsCliff = if cliff > 0: (cliff - s.energy) / cliff * 100.0 else: 0.0
|
||||
echo fmt"{armName(arm):<8} {s.shots:>7} {s.energy:>9.0f} {meanP:>7.2f} " &
|
||||
fmt"{per1k:>11.1f} {vsControl:>10.1f}% {vsCliff:>9.1f}%"
|
||||
|
||||
echo ""
|
||||
echo fmt"low-enemy ticks (0 < E <= 16, where the finishing rule can bind): " &
|
||||
fmt"{lowEnemyTicks}/{totalTicks} ({lowEnemyTicks.float/max(1,totalTicks).float*100.0:.1f}%)"
|
||||
echo ""
|
||||
echo "=== POWER HISTOGRAM (shots per 0.1-wide power bucket, all fixtures) ==="
|
||||
for arm in Arm:
|
||||
echo armName(arm), ": ", histLine(agg[arm].hist)
|
||||
|
||||
echo ""
|
||||
echo "=== HIT-CHANCE / BREAK-EVEN REASONING (INFERRED, not measured here) ==="
|
||||
echo "E[dE] = p(3P-1): the break-even hit probability is 1/3 INDEPENDENT of power."
|
||||
echo "Our measured real hit rates are 5-27% (far below 1/3), so every point of"
|
||||
echo "power costs more energy than it returns. A smaller bullet needs MORE hits"
|
||||
echo "(ceil(E/damage)) but each hit is MORE LIKELY (speed 20-3p => less lead"
|
||||
echo "error) and shots come FASTER (interval 10+2p). This tool measures only the"
|
||||
echo "ENERGY side; which effect wins for hit rate needs the battle A/B."
|
||||
|
||||
when isMainModule:
|
||||
main()
|
||||
@@ -1,10 +1,16 @@
|
||||
## Unit guard for the energy-aware power policy (TR_POWER_*).
|
||||
##
|
||||
## The policy is a CAP on the gun's own preferred bin: at long range or low
|
||||
## energy it trades single-hit damage for a faster bullet and more shots, and it
|
||||
## withholds power 3.0 unless the gun's own chances for the chosen bin are above
|
||||
## that gun's average. It must NEVER raise power, and `TR_POWER_POLICY=0` must
|
||||
## reproduce the uncapped preference exactly (the control arm).
|
||||
## The policy is a CAP on the gun's own preferred bin. Every rule can only LOWER
|
||||
## power; `power = min(preference, min(all caps))`. The two energy-economy rules
|
||||
## under test here are:
|
||||
##
|
||||
## * the ENERGY SLOPE — a linear cap on OUR energy (`energySlopeCap`), replacing
|
||||
## the old hard cliff at `TR_POWER_LOW_ENERGY` (50);
|
||||
## * the FINISHING SLOPE — cap power at the smallest bullet that still removes
|
||||
## the ENEMY's remaining energy (`powerToKill`), because server 1.3.1 caps the
|
||||
## `bulletDamage` score at the energy actually removed, so overkill is wasted.
|
||||
##
|
||||
## `TR_POWER_POLICY=0` must reproduce the uncapped preference exactly (control).
|
||||
##
|
||||
## Pure: no Java, no battle. Run:
|
||||
## nim c -r common_libs/tests/test_power_policy.nim
|
||||
@@ -20,6 +26,8 @@ proc check(name: string, ok: bool) =
|
||||
if ok: echo "PASS: ", name
|
||||
else: echo "FAIL: ", name; inc failures
|
||||
|
||||
proc close(a, b: float, eps = 1e-9): bool = abs(a - b) < eps
|
||||
|
||||
proc recordHit(fw: var FitnessWindow, hit: bool) =
|
||||
fw.hits[fw.head] = hit
|
||||
fw.head = (fw.head + 1) mod WindowSize
|
||||
@@ -32,7 +40,92 @@ proc seedWindow(t: var VirtualTracker, targetId, gunId, binIdx, hits, misses: in
|
||||
for _ in 0..<hits: recordHit(fw[], true)
|
||||
for _ in 0..<misses: recordHit(fw[], false)
|
||||
|
||||
# ── pure cap core ────────────────────────────────────────────────────────────
|
||||
# ── CHANGE 1: the energy slope (pure formula) ────────────────────────────────
|
||||
# Defaults: capMax 3.0 at/above 80, capMin 0.5 at/below 20, linear between.
|
||||
|
||||
proc testEnergySlope() =
|
||||
# Above / at HI: no cap from this rule.
|
||||
check "energy slope: selfE=100 -> cap 3.0 (no cap)",
|
||||
close(energySlopeCap(100.0, 80.0, 20.0, 0.5, 3.0), 3.0)
|
||||
check "energy slope: selfE=80 (HI) -> cap 3.0",
|
||||
close(energySlopeCap(80.0, 80.0, 20.0, 0.5, 3.0), 3.0)
|
||||
# At/below LO: the floor cap.
|
||||
check "energy slope: selfE=20 (LO) -> cap 0.5",
|
||||
close(energySlopeCap(20.0, 80.0, 20.0, 0.5, 3.0), 0.5)
|
||||
check "energy slope: selfE=5 -> cap 0.5 (clamped at LO)",
|
||||
close(energySlopeCap(5.0, 80.0, 20.0, 0.5, 3.0), 0.5)
|
||||
# Linear interpolation in POWER.
|
||||
check "energy slope: selfE=50 -> cap 1.75 (halfway 0.5..3.0)",
|
||||
close(energySlopeCap(50.0, 80.0, 20.0, 0.5, 3.0), 1.75)
|
||||
check "energy slope: selfE=65 -> cap 2.375 (t=0.75)",
|
||||
close(energySlopeCap(65.0, 80.0, 20.0, 0.5, 3.0), 2.375)
|
||||
check "energy slope: selfE=35 -> cap 1.125 (t=0.25)",
|
||||
close(energySlopeCap(35.0, 80.0, 20.0, 0.5, 3.0), 1.125)
|
||||
# A non-default top: the interpolation endpoint is capMax, not hardcoded 3.0.
|
||||
check "energy slope: custom capMax=2.0 at HI",
|
||||
close(energySlopeCap(80.0, 80.0, 20.0, 0.5, 2.0), 2.0)
|
||||
|
||||
proc testEnergySlopeMonotone() =
|
||||
# The cap must be non-decreasing in our energy (more energy never caps lower).
|
||||
var mono = true
|
||||
var prev = -1.0
|
||||
for i in 0..20:
|
||||
let e = i.float * 5.0
|
||||
let c = energySlopeCap(e, 80.0, 20.0, 0.5, 3.0)
|
||||
if c < prev - 1e-12: mono = false
|
||||
prev = c
|
||||
check "energy slope: cap is non-decreasing in self energy", mono
|
||||
|
||||
# ── CHANGE 2: the finishing slope (pure formula) ─────────────────────────────
|
||||
|
||||
proc testPowerToKill() =
|
||||
# E <= 4: p = E/4, clamped to >= 0.1.
|
||||
check "finish: E=0.1 -> p=0.1 (clamp)",
|
||||
close(powerToKill(0.1), 0.1)
|
||||
check "finish: E=0.4 -> p=0.1 (clamp)",
|
||||
close(powerToKill(0.4), 0.1)
|
||||
check "finish: E=1 -> p=0.25",
|
||||
close(powerToKill(1.0), 0.25)
|
||||
check "finish: E=2 -> p=0.5",
|
||||
close(powerToKill(2.0), 0.5)
|
||||
check "finish: E=4 -> p=1.0 (branch seam)",
|
||||
close(powerToKill(4.0), 1.0)
|
||||
# E > 4: p = (E+2)/6.
|
||||
check "finish: E=6 -> p=4/3",
|
||||
close(powerToKill(6.0), 4.0 / 3.0)
|
||||
check "finish: E=10 -> p=2.0",
|
||||
close(powerToKill(10.0), 2.0)
|
||||
check "finish: E=16 -> p=3.0",
|
||||
close(powerToKill(16.0), 3.0)
|
||||
# E > 16: no cap (p=3.0 removes only 16).
|
||||
check "finish: E=17 -> p=3.0 (no cap)",
|
||||
close(powerToKill(17.0), 3.0)
|
||||
check "finish: E=20 -> p=3.0 (no cap)",
|
||||
close(powerToKill(20.0), 3.0)
|
||||
check "finish: E=100 -> p=3.0 (no cap)",
|
||||
close(powerToKill(100.0), 3.0)
|
||||
|
||||
proc testPowerToKillCovers() =
|
||||
# The formula must be a TRUE inverse for the range it can cover (E <= 16);
|
||||
# above 16 even p=3.0 removes only 16, so there is no cap to find.
|
||||
var covers = true
|
||||
for i in 0..159:
|
||||
let e = 0.1 + i.float * 0.1 # 0.1 .. 16.0
|
||||
if bulletDamageAtPower(powerToKill(e)) < e - 1e-9: covers = false
|
||||
check "finish: powerToKill(E) always removes at least E (E in 0.1..16.0)",
|
||||
covers
|
||||
|
||||
proc testPowerToKillMonotone() =
|
||||
var mono = true
|
||||
var prev = -1.0
|
||||
for i in 0..200:
|
||||
let e = i.float * 0.1
|
||||
let p = powerToKill(e)
|
||||
if p < prev - 1e-12: mono = false
|
||||
prev = p
|
||||
check "finish: powerToKill is non-decreasing in enemy energy", mono
|
||||
|
||||
# ── the combined cap core ────────────────────────────────────────────────────
|
||||
|
||||
proc testFar() =
|
||||
let d = applyPowerPolicy(preferredPower = 3.0, dist = 250.0, selfEnergy = 100.0,
|
||||
@@ -40,17 +133,50 @@ proc testFar() =
|
||||
check "distance > TR_POWER_FAR_DIST -> cap 1.0 (far)",
|
||||
d.power == 1.0 and d.cap == 1.0 and d.reason == prFar
|
||||
|
||||
proc testLowEnergy() =
|
||||
let d = applyPowerPolicy(3.0, 100.0, 30.0, 0.9, 0.1, false, enabled = true)
|
||||
check "self energy < TR_POWER_LOW_ENERGY -> cap 1.0 (lowEnergy)",
|
||||
d.power == 1.0 and d.cap == 1.0 and d.reason == prLowEnergy
|
||||
proc testEnergySlopeCap() =
|
||||
# Close, above average, healthy enemy: only the energy slope binds.
|
||||
let d = applyPowerPolicy(3.0, 100.0, 50.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 100.0, enabled = true)
|
||||
check "selfE=50 -> cap 1.75 (energySlope)",
|
||||
close(d.power, 1.75) and close(d.cap, 1.75) and d.reason == prEnergySlope
|
||||
let e = applyPowerPolicy(3.0, 100.0, 20.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 100.0, enabled = true)
|
||||
check "selfE=20 -> cap 0.5 (energySlope)",
|
||||
close(e.power, 0.5) and e.reason == prEnergySlope
|
||||
let f = applyPowerPolicy(3.0, 100.0, 80.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 100.0, enabled = true)
|
||||
check "selfE=80 -> no energy cap, full power", f.power == 3.0
|
||||
|
||||
proc testFinishingCap() =
|
||||
# Close, healthy self, above average, low enemy: only finishing binds.
|
||||
let d = applyPowerPolicy(3.0, 100.0, 100.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 2.0, enabled = true, finishKill = true)
|
||||
check "enemyE=2 -> smallest killing bullet p=0.5 (finishKill)",
|
||||
close(d.power, 0.5) and close(d.cap, 0.5) and d.reason == prFinishKill
|
||||
let e = applyPowerPolicy(3.0, 100.0, 100.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 10.0, enabled = true, finishKill = true)
|
||||
check "enemyE=10 -> p=2.0 (finishKill)",
|
||||
close(e.power, 2.0) and e.reason == prFinishKill
|
||||
let f = applyPowerPolicy(3.0, 100.0, 100.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 16.0, enabled = true, finishKill = true)
|
||||
check "enemyE=16 -> p=3.0 (finish cap does not bite)", f.power == 3.0
|
||||
let g = applyPowerPolicy(3.0, 100.0, 100.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 20.0, enabled = true, finishKill = true)
|
||||
check "enemyE=20 -> no finish cap", g.power == 3.0
|
||||
# Disabled finishing leaves power alone.
|
||||
let h = applyPowerPolicy(3.0, 100.0, 100.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 2.0, enabled = true, finishKill = false)
|
||||
check "enemyE=2 with finishKill=false -> uncapped", h.power == 3.0
|
||||
# A dead/unknown target (energy 0) must NOT collapse power to 0.1.
|
||||
let i = applyPowerPolicy(3.0, 100.0, 100.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 0.0, enabled = true, finishKill = true)
|
||||
check "enemyE=0 (dead) -> finish rule skipped, no collapse", i.power == 3.0
|
||||
|
||||
proc testBelowAverage() =
|
||||
# pEst == pRef is "not above average": withhold power 3.0 -> cap 2.0.
|
||||
let d = applyPowerPolicy(3.0, 100.0, 100.0, 0.2, 0.2, false, enabled = true)
|
||||
check "chances not above average -> cap 2.0 (belowAvg)",
|
||||
d.power == 2.0 and d.cap == 2.0 and d.reason == prBelowAvg
|
||||
# Strictly below also caps.
|
||||
let e = applyPowerPolicy(3.0, 100.0, 100.0, 0.1, 0.2, false, enabled = true)
|
||||
check "chances strictly below average -> cap 2.0 (belowAvg)",
|
||||
e.power == 2.0 and e.reason == prBelowAvg
|
||||
@@ -61,36 +187,58 @@ proc testAboveAverageFull() =
|
||||
d.power == 3.0 and d.cap == 3.0 and d.reason == prFull
|
||||
|
||||
proc testRamExempt() =
|
||||
# Far, low energy, no chance data: still full power because we are ramming.
|
||||
let d = applyPowerPolicy(3.0, 500.0, 5.0, 0.0, 0.9, true)
|
||||
check "ramming exempts the caps even far + low energy",
|
||||
# Far, low self energy, low enemy energy, no chance data: still full power.
|
||||
let d = applyPowerPolicy(3.0, 500.0, 5.0, 0.0, 0.9, true,
|
||||
enemyEnergy = 1.0, enabled = true, finishKill = true)
|
||||
check "ramming exempts far + energy slope + finishing",
|
||||
d.power == 3.0 and d.reason == prRam
|
||||
# Ram beats far even with the policy on.
|
||||
let e = applyPowerPolicy(3.0, 500.0, 5.0, 0.0, 0.9, true, enabled = true)
|
||||
check "ram exemption takes precedence over the far cap", e.power == 3.0
|
||||
|
||||
proc testCapNeverRaises() =
|
||||
# Preferred below every cap must pass through untouched.
|
||||
let a = applyPowerPolicy(1.0, 500.0, 5.0, 0.0, 0.9, false, enabled = true)
|
||||
check "far cap does not raise a preferred p=1.0", a.power == 1.0
|
||||
let b = applyPowerPolicy(1.5, 100.0, 100.0, 0.1, 0.2, false, enabled = true)
|
||||
check "mid cap does not raise a preferred p=1.5", b.power == 1.5
|
||||
let c = applyPowerPolicy(1.5, 100.0, 100.0, 0.9, 0.2, false, enabled = true)
|
||||
check "full cap does not raise a preferred p=1.5", c.power == 1.5
|
||||
# Caps may LOWER a preference (the new slope does exactly that here) but must
|
||||
# never raise it: power is always min(preference, cap).
|
||||
let a = applyPowerPolicy(1.0, 500.0, 5.0, 0.0, 0.9, false,
|
||||
enemyEnergy = 1.0, enabled = true, finishKill = true)
|
||||
check "all caps never raise a preferred p=1.0 (power = min(pref, cap))",
|
||||
a.power <= 1.0 and close(a.power, min(1.0, a.cap))
|
||||
let b = applyPowerPolicy(1.5, 100.0, 100.0, 0.1, 0.2, false,
|
||||
enemyEnergy = 20.0, enabled = true, finishKill = true)
|
||||
check "belowAvg cap does not raise a preferred p=1.5", b.power == 1.5
|
||||
# Exhaustive: for every cap combination, power <= preference.
|
||||
var never = true
|
||||
for pref in [0.5, 1.0, 1.5, 2.0, 3.0]:
|
||||
for selfE in [5.0, 20.0, 50.0, 80.0, 100.0]:
|
||||
for enemyE in [0.0, 0.5, 2.0, 10.0, 20.0]:
|
||||
for d in [50.0, 250.0]:
|
||||
let r = applyPowerPolicy(pref, d, selfE, 0.1, 0.2, false,
|
||||
enemyEnergy = enemyE, enabled = true,
|
||||
finishKill = true)
|
||||
if r.power > pref + 1e-12: never = false
|
||||
check "cap never raises power (exhaustive sweep)", never
|
||||
|
||||
proc testPrecedence() =
|
||||
# far beats low energy, and low energy beats belowAvg.
|
||||
let a = applyPowerPolicy(3.0, 500.0, 5.0, 0.0, 0.9, false, enabled = true)
|
||||
check "far takes precedence over low energy", a.reason == prFar
|
||||
let b = applyPowerPolicy(3.0, 100.0, 5.0, 0.0, 0.9, false, enabled = true)
|
||||
check "low energy takes precedence over belowAvg", b.reason == prLowEnergy
|
||||
# far (1.0) beats the energy slope (1.75 at selfE=50).
|
||||
let a = applyPowerPolicy(3.0, 500.0, 50.0, 0.0, 0.9, false,
|
||||
enemyEnergy = 100.0, enabled = true)
|
||||
check "far takes precedence over the energy slope", a.reason == prFar
|
||||
# the energy slope (1.75) beats belowAvg (2.0).
|
||||
let b = applyPowerPolicy(3.0, 100.0, 50.0, 0.0, 0.9, false,
|
||||
enemyEnergy = 100.0, enabled = true)
|
||||
check "energy slope takes precedence over belowAvg",
|
||||
b.reason == prEnergySlope
|
||||
# finishing (0.5 at enemyE=2) is smaller than far (1.0), so it wins.
|
||||
let c = applyPowerPolicy(3.0, 500.0, 100.0, 0.9, 0.1, false,
|
||||
enemyEnergy = 2.0, enabled = true, finishKill = true)
|
||||
check "finishing beats far when it is the smaller cap",
|
||||
close(c.power, 0.5) and c.reason == prFinishKill
|
||||
|
||||
proc testDisabledUncapped() =
|
||||
# enabled=false is the code path TR_POWER_POLICY=0 drives.
|
||||
for p in [1.0, 1.5, 2.0, 3.0]:
|
||||
let d = applyPowerPolicy(p, 500.0, 5.0, 0.0, 0.9, false, enabled = false)
|
||||
let d = applyPowerPolicy(p, 500.0, 5.0, 0.0, 0.9, false,
|
||||
enemyEnergy = 1.0, enabled = false, finishKill = true)
|
||||
check fmt"policy off reproduces the uncapped preference p={p:.1f}",
|
||||
d.power == p and d.cap == 3.0
|
||||
d.power == p and d.cap == 3.0 and d.reason == prFull
|
||||
|
||||
proc testEnvFlag() =
|
||||
# The flag is read once at module init, so the active branch is selected by
|
||||
@@ -98,9 +246,13 @@ proc testEnvFlag() =
|
||||
if PowerPolicyEnabled:
|
||||
check "TR_POWER_POLICY default (on): far shot is capped to 1.0",
|
||||
applyPowerPolicy(3.0, 300.0, 100.0, 0.5, 0.2, false).power == 1.0
|
||||
check "TR_POWER_POLICY default (on): low self energy is capped by the slope",
|
||||
applyPowerPolicy(3.0, 100.0, 20.0, 0.5, 0.2, false).power == 0.5
|
||||
else:
|
||||
check "TR_POWER_POLICY=0: far shot is NOT capped (control arm)",
|
||||
applyPowerPolicy(3.0, 300.0, 100.0, 0.5, 0.2, false).power == 3.0
|
||||
check "TR_POWER_POLICY=0: low self energy is NOT capped (control arm)",
|
||||
applyPowerPolicy(3.0, 100.0, 20.0, 0.5, 0.2, false).power == 3.0
|
||||
|
||||
proc testBinIndex() =
|
||||
check "binIndexForPower maps the shipped bins exactly",
|
||||
@@ -112,7 +264,8 @@ proc testBinIndex() =
|
||||
proc testReasonNames() =
|
||||
check "reason names match the documented log vocabulary",
|
||||
powerReasonName(prFar) == "far" and
|
||||
powerReasonName(prLowEnergy) == "lowEnergy" and
|
||||
powerReasonName(prEnergySlope) == "energySlope" and
|
||||
powerReasonName(prFinishKill) == "finishKill" and
|
||||
powerReasonName(prBelowAvg) == "belowAvg" and
|
||||
powerReasonName(prFull) == "full" and
|
||||
powerReasonName(prRam) == "ram"
|
||||
@@ -129,7 +282,8 @@ proc testTrackerAboveAverage() =
|
||||
seedWindow(t, 7, 0, 2, 10, 90)
|
||||
seedWindow(t, 7, 0, 3, 50, 50)
|
||||
let (g, _, p, d) = t.selectShotPolicy(7, tick = 0, dist = 100.0,
|
||||
selfEnergy = 100.0, ramming = false)
|
||||
selfEnergy = 100.0, enemyEnergy = 100.0,
|
||||
ramming = false)
|
||||
if PowerPolicyEnabled:
|
||||
check "tracker: above-average bin + close + healthy -> power 3.0",
|
||||
g == 0 and p == 3.0 and d.reason == prFull
|
||||
@@ -137,36 +291,61 @@ proc testTrackerAboveAverage() =
|
||||
check "tracker (control): above-average bin still fires power 3.0",
|
||||
g == 0 and p == 3.0
|
||||
|
||||
proc testTrackerEnergySlope() =
|
||||
var t = initTracker(1)
|
||||
seedWindow(t, 7, 0, 3, 50, 50)
|
||||
let (_, _, p, d) = t.selectShotPolicy(7, tick = 0, dist = 100.0,
|
||||
selfEnergy = 50.0, enemyEnergy = 100.0,
|
||||
ramming = false)
|
||||
if PowerPolicyEnabled:
|
||||
check "tracker: selfE=50 -> power 1.75 (energySlope)",
|
||||
close(p, 1.75) and d.reason == prEnergySlope
|
||||
else:
|
||||
check "tracker (control): selfE=50 keeps the uncapped preference (3.0)",
|
||||
p == 3.0
|
||||
|
||||
proc testTrackerFinishing() =
|
||||
var t = initTracker(1)
|
||||
seedWindow(t, 7, 0, 3, 50, 50)
|
||||
let (_, _, p, d) = t.selectShotPolicy(7, tick = 0, dist = 100.0,
|
||||
selfEnergy = 100.0, enemyEnergy = 2.0,
|
||||
ramming = false)
|
||||
if PowerPolicyEnabled and PowerFinishKill:
|
||||
check "tracker: enemyE=2 -> power 0.5 (finishKill)",
|
||||
close(p, 0.5) and d.reason == prFinishKill
|
||||
else:
|
||||
check "tracker (control/finish off): enemyE=2 keeps preference (3.0)",
|
||||
p == 3.0
|
||||
|
||||
proc testTrackerBelowAverage() =
|
||||
var t = initTracker(1)
|
||||
for b in 0..<len(PowerBins):
|
||||
seedWindow(t, 7, 0, b, 20, 80) # all bins equal: chosen bin not above mean
|
||||
let (_, _, p, d) = t.selectShotPolicy(7, tick = 0, dist = 100.0,
|
||||
selfEnergy = 100.0, ramming = false)
|
||||
selfEnergy = 100.0, enemyEnergy = 100.0,
|
||||
ramming = false)
|
||||
if PowerPolicyEnabled:
|
||||
check "tracker: flat gun -> cap 2.0 (belowAvg)", p == 2.0 and d.reason == prBelowAvg
|
||||
else:
|
||||
check "tracker (control): flat gun keeps its uncapped preference (power 3.0)",
|
||||
p == 3.0
|
||||
|
||||
proc testTrackerFarAndLowEnergy() =
|
||||
proc testTrackerFar() =
|
||||
var t = initTracker(1)
|
||||
seedWindow(t, 7, 0, 3, 50, 50)
|
||||
let (_, _, pFar, dFar) = t.selectShotPolicy(7, 0, dist = 250.0,
|
||||
selfEnergy = 100.0, ramming = false)
|
||||
let (_, _, pLow, dLow) = t.selectShotPolicy(7, 0, dist = 100.0,
|
||||
selfEnergy = 30.0, ramming = false)
|
||||
selfEnergy = 100.0, enemyEnergy = 100.0,
|
||||
ramming = false)
|
||||
if PowerPolicyEnabled:
|
||||
check "tracker: far -> power 1.0", pFar == 1.0 and dFar.reason == prFar
|
||||
check "tracker: low energy -> power 1.0", pLow == 1.0 and dLow.reason == prLowEnergy
|
||||
else:
|
||||
check "tracker (control): far does NOT cap (uncapped preference)", pFar == 3.0
|
||||
check "tracker (control): low energy does NOT cap (uncapped preference)", pLow == 3.0
|
||||
|
||||
proc testTrackerColdAndEmptyBin() =
|
||||
var t = initTracker(1)
|
||||
let (_, _, pCold, dCold) = t.selectShotPolicy(7, 0, dist = 100.0,
|
||||
selfEnergy = 100.0, ramming = false)
|
||||
selfEnergy = 100.0, enemyEnergy = 100.0,
|
||||
ramming = false)
|
||||
if PowerPolicyEnabled:
|
||||
# Cold gun: no data at all -> pEst <= pRef vacuously -> mid cap, but the
|
||||
# preferred bin is already 1.0, so the fired power stays 1.0.
|
||||
@@ -179,13 +358,20 @@ proc testTrackerRamExempt() =
|
||||
var t = initTracker(1)
|
||||
seedWindow(t, 7, 0, 3, 50, 50)
|
||||
let (_, _, p, d) = t.selectShotPolicy(7, 0, dist = 500.0,
|
||||
selfEnergy = 5.0, ramming = true)
|
||||
selfEnergy = 5.0, enemyEnergy = 1.0,
|
||||
ramming = true)
|
||||
check "tracker: ramming exempts the caps", p == 3.0 and d.reason == prRam
|
||||
|
||||
# ── driver ───────────────────────────────────────────────────────────────────
|
||||
|
||||
testEnergySlope()
|
||||
testEnergySlopeMonotone()
|
||||
testPowerToKill()
|
||||
testPowerToKillCovers()
|
||||
testPowerToKillMonotone()
|
||||
testFar()
|
||||
testLowEnergy()
|
||||
testEnergySlopeCap()
|
||||
testFinishingCap()
|
||||
testBelowAverage()
|
||||
testAboveAverageFull()
|
||||
testRamExempt()
|
||||
@@ -196,8 +382,10 @@ testEnvFlag()
|
||||
testBinIndex()
|
||||
testReasonNames()
|
||||
testTrackerAboveAverage()
|
||||
testTrackerEnergySlope()
|
||||
testTrackerFinishing()
|
||||
testTrackerBelowAverage()
|
||||
testTrackerFarAndLowEnergy()
|
||||
testTrackerFar()
|
||||
testTrackerColdAndEmptyBin()
|
||||
testTrackerRamExempt()
|
||||
|
||||
|
||||
Reference in New Issue
Block a user