import { describe, it, expect, vi, beforeEach, type MockInstance } from "vitest";
import { AutoRacingSimulator } from "../auto-racing-simulator";

vi.mock("~/database/context", () => ({
  database: vi.fn(),
}));

vi.mock("~/models/participant-season-result", () => ({
  getSeasonResults: vi.fn(),
}));

vi.mock("~/models/participant-expected-value", () => ({
  getAllParticipantEVsForSeason: vi.fn(),
}));

// ─── F1 race points (positions 1–10) ─────────────────────────────────────────
const F1_RACE_POINTS: Record<number, number> = {
  1: 25, 2: 18, 3: 15, 4: 12, 5: 10, 6: 8, 7: 6, 8: 4, 9: 2, 10: 1,
};

// ─── Fixtures ─────────────────────────────────────────────────────────────────

const DRIVERS = ["d1", "d2", "d3", "d4", "d5"].map((id) => ({ id }));

function makeEvent(isComplete: boolean, eventType = "race") {
  return { isComplete, eventType };
}

function makeSeasonResult(participantId: string, currentPoints: string) {
  return { participant: { id: participantId }, currentPoints };
}

function makeEv(participantId: string, sourceOdds: number | null) {
  return { participantId, sourceOdds };
}

function mockDb(events: ReturnType<typeof makeEvent>[]) {
  return {
    query: {
      seasonParticipants: {
        findMany: vi.fn().mockResolvedValue(DRIVERS),
      },
      scoringEvents: {
        findMany: vi.fn().mockResolvedValue(events),
      },
    },
  };
}

// ─── Setup ────────────────────────────────────────────────────────────────────

let db: ReturnType<typeof mockDb>;

beforeEach(async () => {
  const { database } = await import("~/database/context");
  const { getSeasonResults } = await import("~/models/participant-season-result");
  const { getAllParticipantEVsForSeason } = await import("~/models/participant-expected-value");

  db = mockDb([]);
  (database as unknown as MockInstance).mockReturnValue(db);
  (getSeasonResults as unknown as MockInstance).mockResolvedValue([]);
  (getAllParticipantEVsForSeason as unknown as MockInstance).mockResolvedValue([]);
});

// ─── Tests ────────────────────────────────────────────────────────────────────

describe("AutoRacingSimulator", () => {
  it("throws when no participants are found", async () => {
    db.query.seasonParticipants.findMany.mockResolvedValue([]);
    await expect(
      new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1")
    ).rejects.toThrow(/No participants found/);
  });

  describe("pre-season path (remainingRaces === 0)", () => {
    beforeEach(async () => {
      const { getAllParticipantEVsForSeason } = await import("~/models/participant-expected-value");
      // No scoring events → remainingRaces = 0
      db = mockDb([]);
      const { database } = await import("~/database/context");
      (database as unknown as MockInstance).mockReturnValue(db);
      // Heavy favourite: d1 at −500, all others at +1000
      (getAllParticipantEVsForSeason as unknown as MockInstance).mockResolvedValue([
        makeEv("d1", -500),
        makeEv("d2", 1000),
        makeEv("d3", 1000),
        makeEv("d4", 1000),
        makeEv("d5", 1000),
      ]);
    });

    it("returns one result per driver", async () => {
      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      expect(results).toHaveLength(5);
    });

    it("normalizes each position column to sum to 1.0", async () => {
      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      const keys = [
        "probFirst", "probSecond", "probThird", "probFourth",
        "probFifth", "probSixth", "probSeventh", "probEighth",
      ] as const;
      for (const key of keys) {
        const sum = results.reduce((s, r) => s + r.probabilities[key], 0);
        expect(sum, `${key} column sum`).toBeCloseTo(1.0, 6);
      }
    });

    it("heavy favourite ranks first more often than long shots", async () => {
      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      const favourite = results.find((r) => r.participantId === "d1");
      const longShot = results.find((r) => r.participantId === "d2");
      expect(favourite).toBeDefined();
      expect(longShot).toBeDefined();
      if (!favourite || !longShot) return;
      expect(favourite.probabilities.probFirst).toBeGreaterThan(longShot.probabilities.probFirst);
    });

    it("drivers without odds get equal fallback probability", async () => {
      const { getAllParticipantEVsForSeason } = await import("~/models/participant-expected-value");
      (getAllParticipantEVsForSeason as unknown as MockInstance).mockResolvedValue([]);
      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      // With equal weights all 5 drivers should finish 1st roughly equally
      for (const r of results) {
        expect(r.probabilities.probFirst).toBeGreaterThan(0.1);
        expect(r.probabilities.probFirst).toBeLessThan(0.3);
      }
    });
  });

  describe("in-season path (remainingRaces > 0)", () => {
    beforeEach(async () => {
      const { database } = await import("~/database/context");
      // 10 completed races, 5 remaining
      db = mockDb([
        ...Array.from({ length: 10 }, () => makeEvent(true)),
        ...Array.from({ length: 5 }, () => makeEvent(false)),
      ]);
      (database as unknown as MockInstance).mockReturnValue(db);
    });

    it("normalizes each position column to sum to 1.0", async () => {
      const { getSeasonResults } = await import("~/models/participant-season-result");
      (getSeasonResults as unknown as MockInstance).mockResolvedValue(
        DRIVERS.map((d, i) => makeSeasonResult(d.id, String((5 - i) * 50)))
      );
      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      const keys = [
        "probFirst", "probSecond", "probThird", "probFourth",
        "probFifth", "probSixth", "probSeventh", "probEighth",
      ] as const;
      for (const key of keys) {
        const sum = results.reduce((s, r) => s + r.probabilities[key], 0);
        expect(sum, `${key} column sum`).toBeCloseTo(1.0, 6);
      }
    });

    it("standings leader ranks higher than a driver far behind when standings dominate", async () => {
      // 20/25 races done → seasonProgress = 0.8 → standings weighted 80%
      const { database } = await import("~/database/context");
      db = mockDb([
        ...Array.from({ length: 20 }, () => makeEvent(true)),
        ...Array.from({ length: 5 }, () => makeEvent(false)),
      ]);
      (database as unknown as MockInstance).mockReturnValue(db);

      const { getSeasonResults } = await import("~/models/participant-season-result");
      const { getAllParticipantEVsForSeason } = await import("~/models/participant-expected-value");
      // d1 leads with 400 pts; d2 is a distant 2nd with 50 pts
      (getSeasonResults as unknown as MockInstance).mockResolvedValue([
        makeSeasonResult("d1", "400"),
        makeSeasonResult("d2", "50"),
        makeSeasonResult("d3", "40"),
        makeSeasonResult("d4", "30"),
        makeSeasonResult("d5", "20"),
      ]);
      // Futures odds heavily favour d2 (pretend markets disagree)
      (getAllParticipantEVsForSeason as unknown as MockInstance).mockResolvedValue([
        makeEv("d1", 5000),  // very long shot per futures
        makeEv("d2", -500),  // heavy favourite per futures
      ]);

      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      const leader = results.find((r) => r.participantId === "d1");
      const distant = results.find((r) => r.participantId === "d2");
      expect(leader).toBeDefined();
      expect(distant).toBeDefined();
      if (!leader || !distant) return;
      // Standings signal should dominate: d1's massive points lead wins out
      expect(leader.probabilities.probFirst).toBeGreaterThan(distant.probabilities.probFirst);
    });

    it("falls back to odds for all drivers when no standings data exists", async () => {
      // totalCurrentPoints = 0 → standings signal disabled, odds take over
      const { getAllParticipantEVsForSeason } = await import("~/models/participant-expected-value");
      (getAllParticipantEVsForSeason as unknown as MockInstance).mockResolvedValue([
        makeEv("d1", -500),
        makeEv("d2", 1000),
      ]);
      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      const fav = results.find((r) => r.participantId === "d1");
      const longShot = results.find((r) => r.participantId === "d2");
      expect(fav).toBeDefined();
      expect(longShot).toBeDefined();
      if (!fav || !longShot) return;
      // Without standings, odds-favoured driver should still rank higher
      expect(fav.probabilities.probFirst).toBeGreaterThan(longShot.probabilities.probFirst);
    });

    it("a driver with 0 points mid-season is not penalized beyond their odds weight", async () => {
      // Use 2 completed / 20 remaining → early season, standings gap is small
      const { database } = await import("~/database/context");
      db = mockDb([
        ...Array.from({ length: 2 }, () => makeEvent(true)),
        ...Array.from({ length: 20 }, () => makeEvent(false)),
      ]);
      (database as unknown as MockInstance).mockReturnValue(db);

      const { getSeasonResults } = await import("~/models/participant-season-result");
      // d1-d4 have a modest lead; d5 is absent (0 pts, new entry)
      (getSeasonResults as unknown as MockInstance).mockResolvedValue([
        makeSeasonResult("d1", "10"),
        makeSeasonResult("d2", "8"),
        makeSeasonResult("d3", "6"),
        makeSeasonResult("d4", "4"),
        // d5 intentionally absent → falls back to odds weight
      ]);
      const { getAllParticipantEVsForSeason } = await import("~/models/participant-expected-value");
      (getAllParticipantEVsForSeason as unknown as MockInstance).mockResolvedValue([
        makeEv("d5", -500), // strong odds favourite despite 0 pts
      ]);

      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      // d5 should win championships at a non-trivial rate given their strong odds weight
      const d5 = results.find((r) => r.participantId === "d5");
      expect(d5).toBeDefined();
      if (!d5) return;
      expect(d5.probabilities.probFirst).toBeGreaterThan(0.1);
    });

    it("emits a warning when participants are missing from standings", async () => {
      const warnSpy = vi.spyOn(console, "warn").mockImplementation(() => {});
      const { getSeasonResults } = await import("~/models/participant-season-result");
      // Only 3 of 5 drivers have standings rows
      (getSeasonResults as unknown as MockInstance).mockResolvedValue([
        makeSeasonResult("d1", "100"),
        makeSeasonResult("d2", "80"),
        makeSeasonResult("d3", "60"),
      ]);
      await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      expect(warnSpy).toHaveBeenCalledWith(
        expect.stringContaining("2 participant(s) missing from standings")
      );
      warnSpy.mockRestore();
    });

    it("schedule_event entries are excluded from race counts", async () => {
      const { database } = await import("~/database/context");
      // 5 real races + 3 schedule_events (should be ignored)
      db = mockDb([
        ...Array.from({ length: 5 }, () => makeEvent(true)),
        ...Array.from({ length: 3 }, () => makeEvent(false, "schedule_event")),
        makeEvent(false), // 1 real remaining
      ]);
      (database as unknown as MockInstance).mockReturnValue(db);
      // Should not throw and should use seasonProgress = 5/6
      const results = await new AutoRacingSimulator(F1_RACE_POINTS, "f1").simulate("s1");
      expect(results).toHaveLength(5);
    });
  });
});