const rules = [
    {
        id: "death-rate-relief",
        metric: "death-rate",
        changeType: "enemy-damage",
        direction: "above",
        threshold: 0.34,
        multiplier: 0.82,
        target: 0.18,
        reason: "Recent deaths exceed the bounded comfort threshold, so incoming damage is softened."
    },
    {
        id: "slow-completion-timer",
        metric: "completion-time",
        changeType: "timer-multiplier",
        direction: "above",
        threshold: 92,
        multiplier: 1.18,
        target: 72,
        reason: "Completion time is above target, so objective timers are relaxed."
    },
    {
        id: "low-accuracy-resource-support",
        metric: "accuracy",
        changeType: "resource-drop-rate",
        direction: "below",
        threshold: 0.46,
        multiplier: 1.22,
        target: 0.58,
        reason: "Accuracy is below target, so health/ammo resource availability is raised."
    },
    {
        id: "high-skill-enemy-presence",
        metric: "win-rate",
        changeType: "enemy-count",
        direction: "above",
        threshold: 0.72,
        multiplier: 1.1,
        target: 0.58,
        reason: "Win rate is above target, so bounded encounter density can increase."
    },
    {
        id: "resource-efficiency-reward",
        metric: "resource-efficiency",
        changeType: "experience-multiplier",
        direction: "above",
        threshold: 0.68,
        multiplier: 1.08,
        target: 0.56,
        reason: "Resource efficiency is above target, so reward pacing is slightly increased."
    },
    {
        id: "retry-checkpoint-support",
        metric: "retry-count",
        changeType: "checkpoint-frequency",
        direction: "above",
        threshold: 2.4,
        multiplier: 1.2,
        target: 1.4,
        reason: "Retry count is high, so checkpoint spacing is tightened."
    }
];
export function sampleAdaptiveDifficultyFixture(options = {}) {
    const strategy = options.strategy ?? "gradual";
    const seed = integer(options.seed ?? 0x3d2025, "seed");
    const playerSkill = clamp01(finite(options.playerSkill ?? 0.42, "playerSkill"));
    const recentDeaths = clamp(finite(options.recentDeaths ?? 3, "recentDeaths"), 0, 12);
    const completionTimeSeconds = clamp(finite(options.completionTimeSeconds ?? 108, "completionTimeSeconds"), 15, 420);
    const accuracy = clamp01(finite(options.accuracy ?? 0.41, "accuracy"));
    const resourceEfficiency = clamp01(finite(options.resourceEfficiency ?? 0.74, "resourceEfficiency"));
    const progressionRate = clamp01(finite(options.progressionRate ?? 0.52, "progressionRate"));
    const metricSamples = {
        "win-rate": sampleSeries(0.34 + playerSkill * 0.44, 0.06, seed, 0),
        "death-rate": sampleSeries(recentDeaths / 8, 0.09, seed, 11),
        "completion-time": sampleSeries(completionTimeSeconds, 8.5, seed, 23),
        "damage-taken": sampleSeries(0.56 + recentDeaths * 0.045, 0.08, seed, 37),
        "damage-dealt": sampleSeries(0.42 + accuracy * 0.45, 0.06, seed, 41),
        accuracy: sampleSeries(accuracy, 0.045, seed, 53),
        "resource-efficiency": sampleSeries(resourceEfficiency, 0.05, seed, 61),
        "progression-rate": sampleSeries(progressionRate, 0.07, seed, 71),
        "retry-count": sampleSeries(recentDeaths * 0.75, 0.28, seed, 83)
    };
    const metrics = Object.keys(metricSamples).map((type) => summarizeMetric(type, metricSamples[type]));
    const byType = new Map(metrics.map((metric) => [metric.type, metric]));
    const triggeredRules = rules
        .filter((rule) => ruleTriggered(byType.get(rule.metric), rule))
        .map((rule, index) => triggeredRule(rule, strategy, index));
    const adjustment = applyRules(triggeredRules);
    return {
        id: "external-parity-old-branch-adaptive-difficulty-fixture",
        source: "origin-master-ai-balancing-smart-difficulty-adapted",
        strategy,
        metrics,
        triggeredRules,
        adjustment,
        appliedChangeCount: triggeredRules.length,
        blockedClaims: [
            "production dynamic difficulty adjustment service",
            "machine-learning or reinforcement-learning personalization",
            "player-profile telemetry backend",
            "live economy balancing",
            "Unity/Unreal AI middleware parity"
        ],
        hash: stableHash([
            strategy,
            ...metrics.map((metric) => `${metric.type}:${metric.mean}:${metric.recentTrend}`),
            ...triggeredRules.map((rule) => `${rule.id}:${rule.appliedMultiplier}`),
            Object.values(adjustment).join(":")
        ].join("|")),
        claimBoundary: "Deterministic adaptive-difficulty metric/rule telemetry adapted from old balancing and smart difficulty concepts; this is bounded runtime evidence, not production DDA, ML personalization, telemetry backend, live economy balancing, or Unity/Unreal AI middleware parity."
    };
}
function summarizeMetric(type, values) {
    const sorted = [...values].sort((left, right) => left - right);
    const mean = values.reduce((sum, value) => sum + value, 0) / values.length;
    const variance = values.reduce((sum, value) => sum + (value - mean) ** 2, 0) / values.length;
    const firstHalf = values.slice(0, Math.max(1, Math.floor(values.length / 2)));
    const secondHalf = values.slice(Math.floor(values.length / 2));
    const firstMean = firstHalf.reduce((sum, value) => sum + value, 0) / firstHalf.length;
    const secondMean = secondHalf.reduce((sum, value) => sum + value, 0) / secondHalf.length;
    const trendDelta = secondMean - firstMean;
    return {
        type,
        count: values.length,
        mean: round(mean),
        median: round(sorted[Math.floor(sorted.length / 2)] ?? mean),
        standardDeviation: round(Math.sqrt(variance)),
        min: round(sorted[0] ?? mean),
        max: round(sorted[sorted.length - 1] ?? mean),
        recentTrend: Math.abs(trendDelta) < 0.025 ? "stable" : isLowerBetter(type) ? trendDelta < 0 ? "improving" : "declining" : trendDelta > 0 ? "improving" : "declining"
    };
}
function triggeredRule(rule, strategy, index) {
    const smoothing = strategy === "immediate" ? 1 : strategy === "predictive" ? 0.72 : strategy === "manual" ? 0 : 0.55;
    const appliedMultiplier = strategy === "manual" ? 1 : 1 + (rule.multiplier - 1) * smoothing;
    return {
        id: rule.id,
        metric: rule.metric,
        strategy,
        changeType: rule.changeType,
        target: rule.target,
        threshold: rule.threshold,
        rawMultiplier: rule.multiplier,
        appliedMultiplier: round(appliedMultiplier),
        cooldownSeconds: 12 + index * 4,
        reason: rule.reason
    };
}
function applyRules(triggeredRules) {
    const adjustment = {
        enemyHealth: 1,
        enemyDamage: 1,
        enemyCount: 1,
        resourceDropRate: 1,
        experienceMultiplier: 1,
        timerMultiplier: 1,
        checkpointMultiplier: 1
    };
    const mutable = { ...adjustment };
    for (const rule of triggeredRules) {
        if (rule.changeType === "enemy-health")
            mutable.enemyHealth *= rule.appliedMultiplier;
        else if (rule.changeType === "enemy-damage")
            mutable.enemyDamage *= rule.appliedMultiplier;
        else if (rule.changeType === "enemy-count")
            mutable.enemyCount *= rule.appliedMultiplier;
        else if (rule.changeType === "resource-drop-rate")
            mutable.resourceDropRate *= rule.appliedMultiplier;
        else if (rule.changeType === "experience-multiplier")
            mutable.experienceMultiplier *= rule.appliedMultiplier;
        else if (rule.changeType === "timer-multiplier")
            mutable.timerMultiplier *= rule.appliedMultiplier;
        else
            mutable.checkpointMultiplier *= rule.appliedMultiplier;
    }
    return {
        enemyHealth: round(mutable.enemyHealth),
        enemyDamage: round(mutable.enemyDamage),
        enemyCount: round(mutable.enemyCount),
        resourceDropRate: round(mutable.resourceDropRate),
        experienceMultiplier: round(mutable.experienceMultiplier),
        timerMultiplier: round(mutable.timerMultiplier),
        checkpointMultiplier: round(mutable.checkpointMultiplier)
    };
}
function ruleTriggered(metric, rule) {
    if (!metric)
        return false;
    return rule.direction === "above" ? metric.mean > rule.threshold : metric.mean < rule.threshold;
}
function sampleSeries(center, amplitude, seed, salt) {
    return Array.from({ length: 9 }, (_, index) => {
        const wave = Math.sin((seed + salt + index * 17) * 0.37) * amplitude;
        const drift = (index - 4) * amplitude * 0.08;
        return round(Math.max(0, center + wave + drift));
    });
}
function isLowerBetter(type) {
    return type === "death-rate" || type === "completion-time" || type === "damage-taken" || type === "retry-count";
}
function stableHash(value) {
    let hash = 0x811c9dc5;
    for (let index = 0; index < value.length; index += 1) {
        hash ^= value.charCodeAt(index);
        hash = Math.imul(hash, 0x01000193);
    }
    return (hash >>> 0).toString(16).padStart(8, "0");
}
function integer(value, label) {
    if (!Number.isInteger(value))
        throw new RangeError(`Adaptive difficulty fixture ${label} must be an integer.`);
    return value;
}
function finite(value, label) {
    if (!Number.isFinite(value))
        throw new RangeError(`Adaptive difficulty fixture ${label} must be finite.`);
    return value;
}
function clamp(value, min, max) {
    return Math.max(min, Math.min(max, value));
}
function clamp01(value) {
    return clamp(value, 0, 1);
}
function round(value) {
    return Number(value.toFixed(4));
}
//# sourceMappingURL=AdaptiveDifficultyFixtures.js.map