import test from "node:test";
import assert from "node:assert/strict";

import {
  buildDriverActivePracticeStats,
  buildDriverTrainingStats,
  buildDriverTimingChannelStats,
  buildTrainingAchievements,
  buildTrainingHighlights,
  buildTrainingMarkerComparisons,
  buildTrainingMissions,
  buildTrainingPaceBuckets,
  buildTrainingRecommendation,
  buildTrainingStintAnalysis,
  buildTrainingWeekdayStats,
  getBestConsecutiveTrainingLaps,
  getBestTrainingDurationResult,
  getDriverTrainingLaps,
  getNextTrainingMilestone,
  getClubTrainingGoalProgress,
  getTrainingGoalProgress,
  normalizeTrainingState,
  splitTrainingStints,
  syncTrainingLedger,
} from "../src/training_logic.js";
import { getDriverProfileGroups } from "../src/driver_profile_logic.js";

function createUid() {
  let index = 0;
  return (prefix) => `${prefix}_${++index}`;
}

test("normalization removes invalid and duplicate training records", () => {
  const normalized = normalizeTrainingState({
    goals: [
      { id: "goal_1", driverId: "driver_1", targetLaps: 500, title: " Bronze ", reward: " Badge " },
      { id: "goal_invalid", driverId: "", targetLaps: 100 },
    ],
    ledger: [
      { id: "lap_1", sourceKey: "source_1", driverId: "driver_1", lapMs: 16000, timestamp: 1000 },
      { id: "lap_duplicate", sourceKey: "source_1", driverId: "driver_1", lapMs: 17000, timestamp: 2000 },
      { id: "lap_short", sourceKey: "source_2", driverId: "driver_1", lapMs: 500, timestamp: 3000 },
      { id: "lap_anonymous", sourceKey: "source_3", driverId: "", lapMs: 18000, timestamp: 4000 },
    ],
    shares: [
      { driverId: "driver_1", token: "a".repeat(24), enabled: true, visibility: { history: false } },
      { driverId: "driver_1", token: "b".repeat(24), enabled: true },
      { driverId: "driver_2", token: "short", enabled: true },
    ],
    markers: [
      { id: "marker_1", driverId: "driver_1", classId: "class_1", timestamp: 5000, type: "tires", note: " New tires " },
      { id: "marker_invalid", driverId: "", classId: "class_1", timestamp: 5000 },
    ],
    clubGoal: {
      id: "club_goal_1",
      title: " Club to 10000 ",
      reward: " Pizza ",
      targetLaps: 10000,
      baselineLaps: 120,
    },
  }, { uid: createUid() });

  assert.equal(normalized.goals.length, 1);
  assert.equal(normalized.goals[0].title, "Bronze");
  assert.equal(normalized.goals[0].reward, "Badge");
  assert.deepEqual(normalized.ledger.map((lap) => lap.id), ["lap_1"]);
  assert.deepEqual(normalized.shares.map((share) => share.token), ["a".repeat(24)]);
  assert.deepEqual(normalized.shares[0].visibility, { progress: true, achievements: true, performance: true, goals: true, history: false });
  assert.equal(normalized.markers.length, 1);
  assert.equal(normalized.markers[0].note, "New tires");
  assert.equal(normalized.clubGoal.title, "Club to 10000");
  assert.equal(normalized.clubGoal.reward, "Pizza");
  assert.equal(normalized.clubGoal.baselineLaps, 120);
});

test("ledger sync retains archived laps and rebuilds current session laps", () => {
  const training = {
    goals: [{ id: "goal_1", driverId: "driver_1", targetLaps: 100 }],
    shares: [{ driverId: "driver_1", token: "s".repeat(24), enabled: true }],
    ledger: [
      { id: "archived", sourceKey: "old:1", sessionId: "old", driverId: "driver_1", lapMs: 19000, timestamp: 1000 },
      { id: "stale", sourceKey: "live:old", sessionId: "live", driverId: "driver_1", lapMs: 30000, timestamp: 2000 },
    ],
    markers: [{ id: "marker_1", driverId: "driver_1", classId: "class_1", timestamp: 2500, type: "setup" }],
  };
  const state = {
    sessions: [{ id: "live", name: "Free Practice", eventId: "event_1" }],
    events: [{ id: "event_1", name: "Club practice" }],
    resultsBySession: {
      live: {
        passings: [
          { driverId: "driver_1", competitorKey: "driver_1", lapMs: 16500, timestamp: 3000, validLap: true, validationWarning: "above_max_stint", excludedFromPace: true, stintBoundary: true },
          { driverId: "driver_1", competitorKey: "driver_1", lapMs: 9000, timestamp: 4000, validLap: false },
          { driverId: "", competitorKey: "anonymous", lapMs: 17000, timestamp: 5000, validLap: true },
          { driverId: "driver_1", competitorKey: "driver_1", lapMs: 500, timestamp: 6000, validLap: true },
        ],
      },
    },
  };

  const synced = syncTrainingLedger(training, state, { uid: createUid() });

  assert.equal(synced.ledger.length, 2);
  assert.equal(synced.ledger.some((lap) => lap.id === "archived"), true);
  assert.equal(synced.ledger.some((lap) => lap.id === "stale"), false);
  const liveLap = synced.ledger.find((lap) => lap.sessionId === "live");
  assert.equal(liveLap.lapMs, 16500);
  assert.equal(liveLap.sessionName, "Free Practice");
  assert.equal(liveLap.eventName, "Club practice");
  assert.equal(liveLap.excludedFromPace, true);
  assert.equal(liveLap.stintBoundary, true);
  assert.equal(synced.goals.length, 1);
  assert.equal(synced.shares.length, 1);
  assert.equal(synced.markers.length, 1);
});

test("driver statistics remain isolated and aggregate days and sessions", () => {
  const firstDay = new Date(2026, 0, 10, 12, 0, 0).getTime();
  const secondDay = new Date(2026, 0, 11, 12, 0, 0).getTime();
  const state = {
    training: {
      ledger: [
        { driverId: "driver_1", sessionId: "practice_1", timestamp: firstDay, lapMs: 18000 },
        { driverId: "driver_1", sessionId: "practice_1", timestamp: firstDay + 20000, lapMs: 16500 },
        { driverId: "driver_1", sessionId: "practice_2", timestamp: secondDay, lapMs: 17000 },
        { driverId: "driver_2", sessionId: "practice_2", timestamp: secondDay + 20000, lapMs: 12000 },
      ],
    },
  };

  assert.equal(getDriverTrainingLaps(state, "driver_1").length, 3);
  const stats = buildDriverTrainingStats(state, "driver_1");
  assert.equal(stats.totalLaps, 3);
  assert.equal(stats.totalSessions, 2);
  assert.equal(stats.trainingDays, 2);
  assert.equal(stats.bestLapMs, 16500);
  assert.equal(stats.averageLapMs, 17167);
  // A flow streak never carries over into another session or stint.
  assert.equal(stats.controlledLapStreak, 1);
  assert.equal(stats.dailySummaries[0].laps, 1);
  assert.equal(stats.dailySummaries[1].laps, 2);
});

test("counted stint-boundary laps do not distort driver pace averages", () => {
  const state = {
    training: {
      ledger: [
        { driverId: "driver_1", sourceId: "tp_1", sessionId: "practice", timestamp: 37_000, lapMs: 37_000 },
        { driverId: "driver_1", sourceId: "tp_1", sessionId: "practice", timestamp: 74_000, lapMs: 37_000 },
        { driverId: "driver_1", sourceId: "tp_1", sessionId: "practice", timestamp: 164_000, lapMs: 90_000, excludedFromPace: true, stintBoundary: true },
      ],
    },
  };

  const stats = buildDriverTrainingStats(state, "driver_1");
  assert.equal(stats.totalLaps, 3);
  assert.equal(stats.bestLapMs, 37_000);
  assert.equal(stats.averageLapMs, 37_000);
  assert.equal(stats.stintCount, 2);
});

test("split and pit statistics aggregate by personal profile and selected class", () => {
  const state = {
    drivers: [
      { id: "driver_2wd_a", name: "Driver", profileId: "profile_1", classId: "class_2wd" },
      { id: "driver_2wd_b", name: "Driver", profileId: "profile_1", classId: "class_2wd" },
      { id: "driver_4wd", name: "Driver", profileId: "profile_1", classId: "class_4wd" },
    ],
    sessions: [
      { id: "session_1", name: "Practice", eventId: "event_1" },
      { id: "session_2", name: "Endurance", eventId: "event_1" },
    ],
    events: [{ id: "event_1", name: "Club day" }],
    resultsBySession: {
      session_1: {
        splits: [
          { driverId: "driver_2wd_a", splitMs: 8100, timestamp: 1000 },
          { driverId: "driver_2wd_b", splitMs: 7900, timestamp: 2000 },
          { driverId: "driver_4wd", splitMs: 6500, timestamp: 3000 },
        ],
        pitStops: [],
      },
      session_2: {
        splits: [],
        pitStops: [
          { driverId: "driver_2wd_a", pitStopMs: 12500, enteredAt: 4000 },
          { driverId: "driver_2wd_b", pitStopMs: 9500, enteredAt: 5000 },
          { driverId: "driver_4wd", pitStopMs: 7000, enteredAt: 6000 },
        ],
      },
    },
  };

  const stats = buildDriverTimingChannelStats(state, "profile_1", "class_2wd");
  assert.equal(stats.splitCount, 2);
  assert.equal(stats.bestSplitMs, 7900);
  assert.equal(stats.averageSplitMs, 8000);
  assert.equal(stats.latestSplitGainMs, 200);
  assert.equal(stats.pitStopCount, 2);
  assert.equal(stats.totalPitMs, 22000);
  assert.equal(stats.bestPitStopMs, 9500);
  assert.equal(stats.recentPitStops[0].sessionName, "Endurance");
});

test("one driver profile combines transponders within a class but keeps 2WD and 4WD separate", () => {
  const state = {
    drivers: [
      { id: "driver_2wd_a", name: "Same Driver", profileId: "profile_same", classId: "class_2wd" },
      { id: "driver_2wd_b", name: "Same Driver", profileId: "profile_same", classId: "class_2wd" },
      { id: "driver_4wd", name: "Same Driver", profileId: "profile_same", classId: "class_4wd" },
    ],
    training: {
      ledger: [
        { driverId: "driver_2wd_a", sessionId: "practice", timestamp: 10_000, lapMs: 18_000 },
        { driverId: "driver_2wd_b", sessionId: "practice", timestamp: 30_000, lapMs: 17_500 },
        { driverId: "driver_4wd", sessionId: "practice", timestamp: 50_000, lapMs: 15_000 },
      ],
    },
  };

  const twoWheelDrive = buildDriverTrainingStats(state, "profile_same", "class_2wd");
  const fourWheelDrive = buildDriverTrainingStats(state, "profile_same", "class_4wd");

  assert.equal(twoWheelDrive.totalLaps, 2);
  assert.equal(twoWheelDrive.bestLapMs, 17_500);
  assert.equal(fourWheelDrive.totalLaps, 1);
  assert.equal(fourWheelDrive.bestLapMs, 15_000);
});

test("legacy same-name entries share a profile while an explicit profile can remain separate", () => {
  const groups = getDriverProfileGroups({
    drivers: [
      { id: "legacy_2wd", name: "Test Driver", classId: "2wd", club: "JMK RB", country: "Sverige" },
      { id: "legacy_4wd", name: " test   driver ", classId: "4wd" },
      { id: "separate", name: "Test Driver", profileId: "profile_other", classId: "2wd" },
    ],
  });

  assert.equal(groups.length, 2);
  assert.equal(groups.find((group) => group.id.startsWith("legacy:"))?.drivers.length, 2);
  assert.equal(groups.find((group) => group.id.startsWith("legacy:"))?.club, "JMK RB");
  assert.equal(groups.find((group) => group.id.startsWith("legacy:"))?.country, "Sverige");
  assert.equal(groups.find((group) => group.id === "profile_other")?.drivers.length, 1);
});

test("active practice profile statistics include only linked entries in the selected class", () => {
  const state = {
    activeSessionId: "practice",
    drivers: [
      { id: "two_a", name: "Driver", profileId: "profile", classId: "2wd" },
      { id: "two_b", name: "Driver", profileId: "profile", classId: "2wd" },
      { id: "four", name: "Driver", profileId: "profile", classId: "4wd" },
    ],
    sessions: [{ id: "practice", name: "Open", type: "open_practice", status: "running", startedAt: 1_000 }],
    resultsBySession: {
      practice: {
        passings: [
          { driverId: "two_a", timestamp: 20_000, lapMs: 18_000, validLap: true },
          { driverId: "two_b", timestamp: 39_000, lapMs: 17_500, validLap: true },
          { driverId: "four", timestamp: 55_000, lapMs: 15_000, validLap: true },
        ],
      },
    },
  };

  const stats = buildDriverActivePracticeStats(state, "profile", 60_000, "2wd");
  assert.equal(stats.laps, 2);
  assert.equal(stats.bestLapMs, 17_500);
});

test("active practice stats include only the selected driver's current valid laps", () => {
  const startedAt = 10_000;
  const state = {
    activeSessionId: "practice_1",
    sessions: [{ id: "practice_1", name: "Wednesday Open Practice", type: "open_practice", status: "running", startedAt }],
    resultsBySession: {
      practice_1: {
        passings: [
          { driverId: "driver_1", timestamp: 9_000, lapMs: 15_000, validLap: true },
          { driverId: "driver_1", timestamp: 20_000, lapMs: 16_000, validLap: true },
          { driverId: "driver_1", timestamp: 37_000, lapMs: 17_000, validLap: true },
          { driverId: "driver_1", timestamp: 45_000, lapMs: 8_000, validLap: false },
          { driverId: "driver_2", timestamp: 54_000, lapMs: 16_500, validLap: true },
        ],
      },
    },
  };

  assert.deepEqual(buildDriverActivePracticeStats(state, "driver_1", 70_000), {
    sessionId: "practice_1",
    sessionName: "Wednesday Open Practice",
    startedAt,
    elapsedMs: 60_000,
    laps: 2,
    bestLapMs: 16_000,
    averageLapMs: 16_500,
    lastLapMs: 17_000,
    controlZoneMinMs: 16_000,
    controlZoneMaxMs: 17_280,
    controlledLapStreak: 2,
  });
});

test("active practice stats ignore races and stopped practice sessions", () => {
  const base = { activeSessionId: "session_1", resultsBySession: {} };
  assert.equal(buildDriverActivePracticeStats({ ...base, sessions: [{ id: "session_1", type: "final", status: "running" }] }, "driver_1"), null);
  assert.equal(buildDriverActivePracticeStats({ ...base, sessions: [{ id: "session_1", type: "free_practice", status: "finished" }] }, "driver_1"), null);
});

test("training stints split after a break over two minutes or a session change", () => {
  const laps = [
    { sessionId: "practice_1", timestamp: 18_000, lapMs: 18_000 },
    { sessionId: "practice_1", timestamp: 36_000, lapMs: 18_000 },
    { sessionId: "practice_1", timestamp: 200_001, lapMs: 164_001 },
    { sessionId: "practice_2", timestamp: 218_001, lapMs: 18_000 },
  ];
  const stints = splitTrainingStints(laps);

  assert.equal(stints.length, 3);
  assert.equal(stints[0].laps.length, 2);
  assert.equal(stints[1].laps.length, 1);
  assert.equal(stints[1].laps[0].excludedFromPace, true);
  assert.equal(stints[1].durationMs, 0);
  assert.equal(stints[1].startedAt, 200_001);
  assert.equal(stints[2].sessionId, "practice_2");
});

test("configured maximum lap time creates a new pace stint below the fallback break", () => {
  const stints = splitTrainingStints([
    { sessionId: "practice_1", sourceId: "tp_1", timestamp: 37_000, lapMs: 37_000 },
    { sessionId: "practice_1", sourceId: "tp_1", timestamp: 74_000, lapMs: 37_000 },
    { sessionId: "practice_1", sourceId: "tp_1", timestamp: 164_000, lapMs: 90_000, excludedFromPace: true, stintBoundary: true },
    { sessionId: "practice_1", sourceId: "tp_1", timestamp: 201_000, lapMs: 37_000 },
  ]);

  assert.equal(stints.length, 2);
  assert.equal(stints[1].startedAt, 164_000);
  assert.equal(stints[1].durationMs, 37_000);
  assert.equal(stints[1].laps.filter((lap) => !lap.excludedFromPace).length, 1);
});

test("best consecutive laps never cross a stint boundary", () => {
  const stints = splitTrainingStints([
    { sessionId: "practice_1", timestamp: 18_000, lapMs: 18_000 },
    { sessionId: "practice_1", timestamp: 35_000, lapMs: 17_000 },
    { sessionId: "practice_1", timestamp: 51_000, lapMs: 16_000 },
    { sessionId: "practice_1", timestamp: 66_000, lapMs: 15_000 },
    { sessionId: "practice_1", timestamp: 201_001, lapMs: 15_000 },
  ]);
  const best = getBestConsecutiveTrainingLaps(stints, 3);

  assert.equal(best.totalMs, 48_000);
  assert.equal(best.averageLapMs, 16_000);
  assert.equal(best.startedAt, 18_000);
});

test("best five-minute result counts a final lap started before the cutoff and reports its pace", () => {
  const laps = Array.from({ length: 16 }, (_, index) => ({
    sessionId: "practice_1",
    timestamp: (index + 1) * 18_000,
    lapMs: 18_000,
  }));
  laps.push({ sessionId: "practice_1", timestamp: 314_123, lapMs: 26_123 });
  const result = getBestTrainingDurationResult(splitTrainingStints(laps), 300_000);

  assert.equal(result.lapCount, 17);
  assert.equal(result.totalMs, 314_123);
  assert.equal(result.averageLapMs, 18_478);
  assert.equal(result.startedAt, 0);
  assert.equal(result.endedAt, 314_123);
});

test("best five-minute result never combines simultaneous transponder sources", () => {
  const laps = ["transponder_a", "transponder_b"].flatMap((sourceId) => (
    Array.from({ length: 9 }, (_, index) => ({
      driverId: sourceId,
      sourceId,
      sessionId: "practice_1",
      timestamp: (index + 1) * 37_000,
      lapMs: 37_000,
    }))
  ));
  const stints = splitTrainingStints(laps);
  const result = getBestTrainingDurationResult(stints, 300_000);

  assert.equal(stints.length, 2);
  assert.equal(result.lapCount, 9);
  assert.equal(result.totalMs, 333_000);
  assert.ok(result.totalMs <= result.targetMs + 37_000);
});

test("a stint shorter than the target duration has no five-minute result", () => {
  const stints = splitTrainingStints([
    { sessionId: "practice_1", timestamp: 18_000, lapMs: 18_000 },
    { sessionId: "practice_1", timestamp: 36_000, lapMs: 18_000 },
  ]);
  assert.equal(getBestTrainingDurationResult(stints, 300_000), null);
});

test("training progress recognizes a clean five-minute stint and strong finish", () => {
  const ledger = Array.from({ length: 16 }, (_, index) => ({
    driverId: "driver_1",
    sourceId: "transponder_1",
    sessionId: "practice_1",
    timestamp: (index + 1) * 20_000,
    lapMs: 20_000,
  }));
  const state = { training: { ledger } };
  const stats = buildDriverTrainingStats(state, "driver_1");
  const analysis = buildTrainingStintAnalysis(state, "driver_1");

  assert.equal(stats.controlZoneMinMs, 20_000);
  assert.equal(stats.controlZoneMaxMs, 21_600);
  assert.equal(stats.controlledLapStreak, 16);
  assert.equal(stats.outlierLaps, 0);
  assert.equal(stats.strongFinishStints, 1);
  assert.equal(stats.cleanFiveMinuteStints, 1);
  assert.equal(stats.achievements.find((item) => item.id === "strong_finish").unlocked, true);
  assert.equal(stats.achievements.find((item) => item.id === "clean_five_minute").unlocked, true);
  assert.equal(analysis.rows[0].strongFinish, true);
  assert.equal(analysis.rows[0].fiveMinuteResult.lapCount, 15);
  assert.equal(analysis.rows[0].fiveMinuteResult.totalMs, 300_000);
});

test("recommendations select baseline, consistency, and progression", () => {
  assert.equal(buildTrainingRecommendation({ totalLaps: 9 }).level, "baseline");
  assert.deepEqual(
    buildTrainingRecommendation({ totalLaps: 30, recentLapCount: 30, consistencySpreadPct: 9, bestLapMs: 16000 }),
    {
      level: "consistency",
      titleKey: "training.plan_consistency_title",
      bodyKey: "training.plan_consistency_body",
      targetLapMs: 17280,
    }
  );
  assert.equal(buildTrainingRecommendation({ totalLaps: 30, recentLapCount: 30, consistencySpreadPct: 4, bestLapMs: 16000 }).level, "progression");
});

test("goal and automatic milestone progress are bounded", () => {
  assert.deepEqual(getTrainingGoalProgress({ targetLaps: 500 }, { totalLaps: 125 }), {
    currentLaps: 125,
    targetLaps: 500,
    remainingLaps: 375,
    percent: 25,
    reached: false,
  });
  assert.equal(getTrainingGoalProgress({ targetLaps: 100 }, { totalLaps: 150 }).percent, 100);
  assert.equal(getTrainingGoalProgress({ targetLaps: 100 }, { totalLaps: 150 }).reached, true);
  assert.equal(getNextTrainingMilestone({ totalLaps: 250 }).targetLaps, 500);
  assert.equal(getNextTrainingMilestone({ totalLaps: 5200 }).targetLaps, 6000);
});

test("development trend compares the latest 30 laps with the preceding 30", () => {
  const start = new Date(2026, 0, 10, 12, 0, 0).getTime();
  const ledger = Array.from({ length: 60 }, (_, index) => ({
    driverId: "driver_1",
    sessionId: "practice_1",
    timestamp: start + ((index + 1) * 18_000),
    lapMs: index < 30 ? 18_000 : 17_000,
  }));
  const stats = buildDriverTrainingStats({ training: { ledger } }, "driver_1");

  assert.equal(stats.trendSampleReady, true);
  assert.equal(stats.previousRecentAverageMs, 18_000);
  assert.equal(stats.recentAverageMs, 17_000);
  assert.equal(stats.averageTrendMs, 1_000);
  assert.equal(stats.consistencyTrendPct, 0);
});

test("automatic achievements expose unlocked and upcoming personal goals", () => {
  const achievements = buildTrainingAchievements({
    totalSessions: 2,
    totalLaps: 520,
    trainingDays: 4,
    controlledLapStreak: 7,
    bestFiveMinuteResult: { lapCount: 17 },
  });

  assert.equal(achievements.find((item) => item.id === "first_session").unlocked, true);
  assert.equal(achievements.find((item) => item.id === "laps_500").unlocked, true);
  assert.equal(achievements.find((item) => item.id === "laps_1000").percent, 52);
  assert.equal(achievements.find((item) => item.id === "days_10").unlocked, false);
  assert.equal(achievements.find((item) => item.id === "five_minute").unlocked, true);
  assert.equal(achievements.find((item) => item.id === "laps_250").unlocked, true);
  assert.equal(achievements.find((item) => item.id === "controlled_10").unlocked, false);
});

test("daily missions recognize volume, control, and completed five-minute stints", () => {
  const missions = buildTrainingMissions({
    todayLaps: 12,
    todayControlledLapStreak: 5,
    todayCompletedFiveMinuteStints: 1,
  });

  assert.equal(missions.find((item) => item.id === "laps_today").percent, 60);
  assert.equal(missions.find((item) => item.id === "controlled_today").completed, true);
  assert.equal(missions.find((item) => item.id === "five_minute_today").completed, true);
});

test("training highlights prioritize current personal progress", () => {
  const highlights = buildTrainingHighlights({
    totalLaps: 600,
    todayLaps: 24,
    personalBestGainMs: 320,
    trendSampleReady: true,
    averageTrendMs: 180,
    consistencyTrendPct: 1.4,
    todayControlledLapStreak: 6,
  });

  assert.deepEqual(highlights.map((item) => item.id), ["today_laps", "personal_best", "pace_gain"]);
});

test("club goal progress starts at its saved baseline and is bounded", () => {
  const progress = getClubTrainingGoalProgress({
    ledger: Array.from({ length: 175 }, (_, index) => ({ id: `lap_${index}` })),
    clubGoal: { targetLaps: 100, baselineLaps: 125 },
  });

  assert.equal(progress.currentLaps, 50);
  assert.equal(progress.remainingLaps, 50);
  assert.equal(progress.percent, 50);
  assert.equal(progress.reached, false);
  assert.equal(getClubTrainingGoalProgress({ ledger: [] }), null);
});

test("pace buckets use a trimmed average and keep classes isolated", () => {
  const start = new Date(2026, 7, 23, 12, 0, 0).getTime();
  const twoWheelLaps = [10_000, ...Array.from({ length: 10 }, () => 20_000), 60_000];
  const state = {
    drivers: [
      { id: "driver_2wd", profileId: "profile", classId: "2wd" },
      { id: "driver_4wd", profileId: "profile", classId: "4wd" },
    ],
    training: {
      ledger: [
        ...twoWheelLaps.map((lapMs, index) => ({ driverId: "driver_2wd", sessionId: "practice", timestamp: start + index * 60_000, lapMs })),
        { driverId: "driver_4wd", sessionId: "practice", timestamp: start + 60_000, lapMs: 14_000 },
      ],
      markers: [],
    },
  };
  const buckets = buildTrainingPaceBuckets(state, "profile", "2wd", 30);
  const weekdays = buildTrainingWeekdayStats(state, "profile", "2wd");

  assert.equal(buckets.length, 1);
  assert.equal(buckets[0].lapCount, 12);
  assert.equal(buckets[0].paceMs, 20_000);
  assert.equal(weekdays.find((day) => day.weekday === 0).lapCount, 12);
});

test("setup markers compare only the selected class before and after the change", () => {
  const markerAt = new Date(2026, 7, 23, 13, 0, 0).getTime();
  const state = {
    drivers: [
      { id: "driver_2wd", profileId: "profile", classId: "2wd" },
      { id: "driver_4wd", profileId: "profile", classId: "4wd" },
    ],
    training: {
      ledger: [
        ...[25, 20, 15].map((minutes, index) => ({ driverId: "driver_2wd", timestamp: markerAt - minutes * 60_000, lapMs: 20_000 + index * 100 })),
        ...[5, 10, 15].map((minutes, index) => ({ driverId: "driver_2wd", timestamp: markerAt + minutes * 60_000, lapMs: 18_000 + index * 100 })),
        { driverId: "driver_4wd", timestamp: markerAt + 60_000, lapMs: 12_000 },
      ],
      markers: [{ id: "marker", driverId: "driver_2wd", classId: "2wd", timestamp: markerAt, type: "tires" }],
    },
  };
  const [comparison] = buildTrainingMarkerComparisons(state, "profile", "2wd", 30);

  assert.equal(comparison.beforeLapCount, 3);
  assert.equal(comparison.afterLapCount, 3);
  assert.equal(comparison.beforePaceMs, 20_100);
  assert.equal(comparison.afterPaceMs, 18_100);
  assert.equal(comparison.improvementMs, 2_000);
});

test("stint analysis hides race pace 10 for short stints and flags slow laps", () => {
  const firstStart = new Date(2026, 7, 23, 12, 0, 0).getTime();
  const firstLaps = [...Array.from({ length: 10 }, () => 18_000), 30_000];
  let timestamp = firstStart;
  const ledger = firstLaps.map((lapMs) => {
    timestamp += lapMs;
    return { driverId: "driver", sessionId: "practice", timestamp, lapMs };
  });
  ledger.push({ driverId: "driver", sessionId: "practice", timestamp: timestamp + 180_001, lapMs: 18_000 });
  ledger.push({ driverId: "driver", sessionId: "practice", timestamp: timestamp + 198_001, lapMs: 18_000 });
  const analysis = buildTrainingStintAnalysis({ training: { ledger } }, "driver");

  assert.equal(analysis.rows.length, 2);
  const longStint = analysis.rows.find((row) => row.lapCount === 11);
  const shortStint = analysis.rows.find((row) => row.lapCount === 2);
  assert.equal(longStint.racePace10Ms, 18_000);
  assert.equal(longStint.mistakes, 1);
  assert.equal(shortStint.racePace10Ms, 0);
  assert.equal(shortStint.consistencyPct, null);
  assert.equal(shortStint.insufficient, true);
});