// End-of-term review: a score from the whole term (not just the last day), a letter
// grade, the historian's title and the decisions that mattered most.
// Pure: works for a finished term and for a game that ended early.

import { clamp } from "./state.js";
import { indexCards } from "./cards.js";

// Names usable in the `min` / `max` conditions of endgame.json titles.
export const METRIC_IDS = [
  "order", "stability", "civilRights", "opinion", "economy", "hardPower", "softPower", "unrest", "armyLoyalty",
  "growth", "unemployment", "inflation", "debt", "score", "years",
];

const mean = (xs) => (xs.length ? xs.reduce((a, b) => a + b, 0) / xs.length : 0);

const AVERAGED = ["order", "stability", "civilRights", "opinion", "economy", "hardPower", "softPower", "unrest", "armyLoyalty", "growth", "unemployment", "inflation"];

// Averages over the whole term, plus the final debt ratio. With `lastYearShare` the average
// leans on the last 52 weekly samples: the historian judges what you leave behind, so a
// boom bought on credit does not pay for itself.
function termAverages(state, lastYearShare = 0) {
  const s = state.history.series;
  const m = {};
  for (const id of AVERAGED) {
    const all = s[id] ?? [];
    m[id] = lastYearShare > 0 ? (1 - lastYearShare) * mean(all) + lastYearShare * mean(all.slice(-52)) : mean(all);
  }
  m.debt = s.debtRatio?.at(-1) ?? 0;
  m.years = state.day / 365;
  return m;
}

function computeScore(m, bal) {
  const sc = bal.score;
  let base = 0;
  for (const [id, w] of Object.entries(sc.weights)) base += w * (id === "calm" ? 100 - m.unrest : m[id]);
  const bonus = (cfg, value) => clamp((cfg.ref - value) * cfg.per, cfg.min, cfg.max);
  const total = base
    + bonus(sc.debt, m.debt)
    + clamp((m.growth - sc.growth.ref) * sc.growth.per, sc.growth.min, sc.growth.max)
    + bonus(sc.unemployment, m.unemployment);
  return clamp(total, 0, 100);
}

const gradeOf = (score, bal) => bal.score.grades.find(([min]) => score >= min)?.[1] ?? "F";

// How strongly one effect moves the country, in rough "points". Used to rank decisions.
export function effectImpact(e) {
  const d = Math.abs(e.delta ?? 0);
  if (e.stat !== undefined || e.sector !== undefined) {
    if (e.bias) return d * clamp((e.days ?? 365) / 90, 1, 8);
    return d;
  }
  if (e.revenue !== undefined) return d * (e.revenue === "other" ? 8 : 2);
  if (e.oneOff !== undefined) return Math.abs(e.oneOff) * 5;
  if (e.extraSpending !== undefined) return Math.abs(e.extraSpending) * 8;
  return 0;
}

export const optionImpact = (option) => (option.effects ?? []).reduce((sum, e) => sum + effectImpact(e), 0);

function topDecisions(state, cards, count) {
  const byId = indexCards(cards);
  return state.cardHistory
    .map((h) => {
      const card = byId.get(h.id);
      return card ? { id: h.id, day: h.day, choice: h.choice, impact: optionImpact(card[h.choice]) } : null;
    })
    .filter(Boolean)
    .sort((a, b) => b.impact - a.impact || a.day - b.day)
    .slice(0, count);
}

function meets(entry, m) {
  const c = entry.conditions ?? {};
  for (const [k, v] of Object.entries(c.min ?? {})) if (!(m[k] >= v)) return false;
  for (const [k, v] of Object.entries(c.max ?? {})) if (!(m[k] <= v)) return false;
  return true;
}

// endgame: the parsed data/endgame.json (its `titles` list is in priority order).
export function buildReview(state, bal, cards, endgame) {
  const metrics = termAverages(state);
  let score = computeScore(termAverages(state, bal.score.lastYearShare ?? 0), bal);
  if (state.over && state.over.type !== "term") score = Math.min(score, bal.score.overCap);
  metrics.score = score;

  const earlyEnd = state.over && state.over.type !== "term" ? state.over.type : null;
  const title = endgame.titles.find((t) => (t.over ?? null) === earlyEnd && (earlyEnd || meets(t, metrics)));
  return {
    over: state.over,
    metrics,
    score,
    grade: earlyEnd ? "F" : gradeOf(score, bal),
    titleId: title?.id ?? null,
    topDecisions: topDecisions(state, cards, bal.score.topDecisions),
  };
}