// Copyright (c) ppy Pty Ltd <contact@ppy.sh>. Licensed under the MIT Licence.
// See the LICENCE file in the repository root for full licence text.

using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using osu.Game.Beatmaps;
using osu.Game.Rulesets.Judgements;
using osu.Game.Rulesets.Scoring;
using osu.Game.Scoring;

namespace osu.Game.Database
{
    public static class StandardisedScoreMigrationTools
    {
        public static long GetNewStandardised(ScoreInfo score)
        {
            var ruleset = score.Ruleset.CreateInstance();
            var processor = ruleset.CreateScoreProcessor();

            var beatmap = new Beatmap();

            HitResult maxRulesetJudgement = ruleset.GetHitResults().First().result;

            var maximumJudgements = score.MaximumStatistics
                                         .Where(kvp => kvp.Key.AffectsCombo())
                                         .OrderByDescending(kvp => Judgement.ToNumericResult(kvp.Key))
                                         .SelectMany(kvp => Enumerable.Repeat(new FakeJudgement(kvp.Key), kvp.Value))
                                         .ToList();

            // This is a list of all results, ordered from best to worst.
            // We are constructing a "best possible" score from the statistics provided because it's the best we can do.
            List<HitResult> sortedHits = score.Statistics
                                              .Where(kvp => kvp.Key.AffectsCombo())
                                              .OrderByDescending(kvp => Judgement.ToNumericResult(kvp.Key))
                                              .SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value))
                                              .ToList();

            if (maximumJudgements.Count != sortedHits.Count)
            {
                // Older scores may not have maximum judgements populated correctly.
                // In this case we need to fill them.
                maximumJudgements = sortedHits
                                    .Select(r => new FakeJudgement(getMaxJudgementFor(r, maxRulesetJudgement)))
                                    .ToList();
            }

            foreach (var judgement in maximumJudgements)
                beatmap.HitObjects.Add(new FakeHit(judgement));

            processor.ApplyBeatmap(beatmap);

            Queue<HitResult> misses = new Queue<HitResult>(score.Statistics
                                                                .Where(kvp => kvp.Key == HitResult.Miss || kvp.Key == HitResult.LargeTickMiss)
                                                                .SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value)));

            int maxJudgementIndex = 0;

            foreach (var result in sortedHits)
            {
                // misses are handled from the queue.
                if (result == HitResult.Miss || result == HitResult.LargeTickMiss)
                    continue;

                if (processor.Combo.Value == score.MaxCombo)
                {
                    if (misses.Count > 0)
                    {
                        processor.ApplyResult(new JudgementResult(null!, maximumJudgements[maxJudgementIndex++])
                        {
                            Type = misses.Dequeue(),
                        });
                    }
                    else
                    {
                        // worst case scenario, insert a miss.
                        processor.ApplyResult(new JudgementResult(null!, new FakeJudgement(getMaxJudgementFor(HitResult.Miss, maxRulesetJudgement)))
                        {
                            Type = HitResult.Miss,
                        });
                    }
                }

                processor.ApplyResult(new JudgementResult(null!, maximumJudgements[maxJudgementIndex++])
                {
                    Type = result
                });
            }

            var bonusHits = score.Statistics
                                 .Where(kvp => kvp.Key.IsBonus())
                                 .SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value));

            foreach (var result in bonusHits)
                processor.ApplyResult(new JudgementResult(null!, new FakeJudgement(result)) { Type = result });

            // Not true for all scores for whatever reason. Oh well.
            // Debug.Assert(processor.HighestCombo.Value == score.MaxCombo);

            return processor.TotalScore.Value;
        }

        private static HitResult getMaxJudgementFor(HitResult hitResult, HitResult max)
        {
            switch (hitResult)
            {
                case HitResult.Miss:
                case HitResult.Meh:
                case HitResult.Ok:
                case HitResult.Good:
                case HitResult.Great:
                case HitResult.Perfect:
                    return max;

                case HitResult.SmallTickMiss:
                case HitResult.SmallTickHit:
                    return HitResult.SmallTickHit;

                case HitResult.LargeTickMiss:
                case HitResult.LargeTickHit:
                    return HitResult.LargeTickHit;
            }

            return HitResult.IgnoreHit;
        }

        public static long GetOldStandardised(ScoreInfo score)
        {
            double accuracyScore =
                (double)score.Statistics.Where(kvp => kvp.Key.AffectsAccuracy()).Sum(kvp => Judgement.ToNumericResult(kvp.Key) * kvp.Value)
                / score.MaximumStatistics.Where(kvp => kvp.Key.AffectsAccuracy()).Sum(kvp => Judgement.ToNumericResult(kvp.Key) * kvp.Value);
            double comboScore = (double)score.MaxCombo / score.MaximumStatistics.Where(kvp => kvp.Key.AffectsCombo()).Sum(kvp => kvp.Value);
            double bonusScore = score.Statistics.Where(kvp => kvp.Key.IsBonus()).Sum(kvp => Judgement.ToNumericResult(kvp.Key) * kvp.Value);

            double accuracyPortion = 0.3;

            switch (score.RulesetID)
            {
                case 1:
                    accuracyPortion = 0.75;
                    break;

                case 3:
                    accuracyPortion = 0.99;
                    break;
            }

            return (long)(1000000 * (accuracyPortion * accuracyScore + (1 - accuracyPortion) * comboScore) + bonusScore);
        }
    }
}