99 lines
4.0 KiB
JavaScript
99 lines
4.0 KiB
JavaScript
// End-of-term review: a score from the whole term (not just the last day), a letter
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// grade, the historian's title and the decisions that mattered most.
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// Pure: works for a finished term and for a game that ended early.
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import { clamp } from "./state.js";
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import { indexCards } from "./cards.js";
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// Names usable in the `min` / `max` conditions of endgame.json titles.
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export const METRIC_IDS = [
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"order", "stability", "civilRights", "opinion", "economy", "hardPower", "softPower", "unrest", "armyLoyalty",
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"growth", "unemployment", "inflation", "debt", "score", "years",
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];
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const mean = (xs) => (xs.length ? xs.reduce((a, b) => a + b, 0) / xs.length : 0);
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const AVERAGED = ["order", "stability", "civilRights", "opinion", "economy", "hardPower", "softPower", "unrest", "armyLoyalty", "growth", "unemployment", "inflation"];
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// Averages over the whole term, plus the final debt ratio. With `lastYearShare` the average
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// leans on the last 52 weekly samples: the historian judges what you leave behind, so a
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// boom bought on credit does not pay for itself.
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function termAverages(state, lastYearShare = 0) {
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const s = state.history.series;
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const m = {};
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for (const id of AVERAGED) {
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const all = s[id] ?? [];
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m[id] = lastYearShare > 0 ? (1 - lastYearShare) * mean(all) + lastYearShare * mean(all.slice(-52)) : mean(all);
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}
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m.debt = s.debtRatio?.at(-1) ?? 0;
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m.years = state.day / 365;
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return m;
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}
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function computeScore(m, bal) {
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const sc = bal.score;
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let base = 0;
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for (const [id, w] of Object.entries(sc.weights)) base += w * (id === "calm" ? 100 - m.unrest : m[id]);
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const bonus = (cfg, value) => clamp((cfg.ref - value) * cfg.per, cfg.min, cfg.max);
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const total = base
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+ bonus(sc.debt, m.debt)
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+ clamp((m.growth - sc.growth.ref) * sc.growth.per, sc.growth.min, sc.growth.max)
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+ bonus(sc.unemployment, m.unemployment);
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return clamp(total, 0, 100);
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}
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const gradeOf = (score, bal) => bal.score.grades.find(([min]) => score >= min)?.[1] ?? "F";
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// How strongly one effect moves the country, in rough "points". Used to rank decisions.
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export function effectImpact(e) {
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const d = Math.abs(e.delta ?? 0);
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if (e.stat !== undefined || e.sector !== undefined) {
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if (e.bias) return d * clamp((e.days ?? 365) / 90, 1, 8);
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return d;
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}
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if (e.revenue !== undefined) return d * (e.revenue === "other" ? 8 : 2);
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if (e.oneOff !== undefined) return Math.abs(e.oneOff) * 5;
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if (e.extraSpending !== undefined) return Math.abs(e.extraSpending) * 8;
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return 0;
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}
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export const optionImpact = (option) => (option.effects ?? []).reduce((sum, e) => sum + effectImpact(e), 0);
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function topDecisions(state, cards, count) {
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const byId = indexCards(cards);
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return state.cardHistory
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.map((h) => {
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const card = byId.get(h.id);
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return card ? { id: h.id, day: h.day, choice: h.choice, impact: optionImpact(card[h.choice]) } : null;
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})
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.filter(Boolean)
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.sort((a, b) => b.impact - a.impact || a.day - b.day)
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.slice(0, count);
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}
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function meets(entry, m) {
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const c = entry.conditions ?? {};
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for (const [k, v] of Object.entries(c.min ?? {})) if (!(m[k] >= v)) return false;
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for (const [k, v] of Object.entries(c.max ?? {})) if (!(m[k] <= v)) return false;
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return true;
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}
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// endgame: the parsed data/endgame.json (its `titles` list is in priority order).
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export function buildReview(state, bal, cards, endgame) {
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const metrics = termAverages(state);
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let score = computeScore(termAverages(state, bal.score.lastYearShare ?? 0), bal);
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if (state.over && state.over.type !== "term") score = Math.min(score, bal.score.overCap);
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metrics.score = score;
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const earlyEnd = state.over && state.over.type !== "term" ? state.over.type : null;
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const title = endgame.titles.find((t) => (t.over ?? null) === earlyEnd && (earlyEnd || meets(t, metrics)));
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return {
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over: state.over,
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metrics,
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score,
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grade: earlyEnd ? "F" : gradeOf(score, bal),
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titleId: title?.id ?? null,
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topDecisions: topDecisions(state, cards, bal.score.topDecisions),
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};
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}
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