// Copyright (c) ppy Pty Ltd . Licensed under the MIT Licence. // See the LICENCE file in the repository root for full licence text. using System; using System.Collections.Generic; using System.Diagnostics; using System.Linq; using osu.Framework.Logging; using osu.Game.Beatmaps; using osu.Game.Extensions; using osu.Game.IO.Legacy; using osu.Game.Rulesets; using osu.Game.Rulesets.Judgements; using osu.Game.Rulesets.Mods; using osu.Game.Rulesets.Objects; using osu.Game.Rulesets.Scoring; using osu.Game.Rulesets.Scoring.Legacy; using osu.Game.Scoring; namespace osu.Game.Database { public static class StandardisedScoreMigrationTools { public static bool ShouldMigrateToNewStandardised(ScoreInfo score) { if (score.IsLegacyScore) return false; if (score.TotalScoreVersion > 30000002) return false; // Recalculate the old-style standardised score to see if this was an old lazer score. bool oldScoreMatchesExpectations = GetOldStandardised(score) == score.TotalScore; // Some older scores don't have correct statistics populated, so let's give them benefit of doubt. bool scoreIsVeryOld = score.Date < new DateTime(2023, 1, 1, 0, 0, 0); return oldScoreMatchesExpectations || scoreIsVeryOld; } public static long GetNewStandardised(ScoreInfo score) { int maxJudgementIndex = 0; // Avoid retrieving from realm inside loops. int maxCombo = score.MaxCombo; var ruleset = score.Ruleset.CreateInstance(); var processor = ruleset.CreateScoreProcessor(); processor.TrackHitEvents = false; var beatmap = new Beatmap(); HitResult maxRulesetJudgement = ruleset.GetHitResults().First().result; // 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 sortedHits = score.Statistics .Where(kvp => kvp.Key.AffectsCombo()) .OrderByDescending(kvp => processor.GetBaseScoreForResult(kvp.Key)) .SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value)) .ToList(); // Attempt to use maximum statistics from the database. var maximumJudgements = score.MaximumStatistics .Where(kvp => kvp.Key.AffectsCombo()) .OrderByDescending(kvp => processor.GetBaseScoreForResult(kvp.Key)) .SelectMany(kvp => Enumerable.Repeat(new FakeJudgement(kvp.Key), kvp.Value)) .ToList(); // Some older scores may not have maximum statistics populated correctly. // In this case we need to fill them with best-known-defaults. if (maximumJudgements.Count != sortedHits.Count) { maximumJudgements = sortedHits .Select(r => new FakeJudgement(getMaxJudgementFor(r, maxRulesetJudgement))) .ToList(); } // This is required to get the correct maximum combo portion. foreach (var judgement in maximumJudgements) beatmap.HitObjects.Add(new FakeHit(judgement)); processor.ApplyBeatmap(beatmap); processor.Mods.Value = score.Mods; // Insert all misses into a queue. // These will be nibbled at whenever we need to reset the combo. Queue misses = new Queue(score.Statistics .Where(kvp => kvp.Key == HitResult.Miss || kvp.Key == HitResult.LargeTickMiss) .SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value))); foreach (var result in sortedHits) { // For the main part of this loop, ignore all misses, as they will be inserted from the queue. if (result == HitResult.Miss || result == HitResult.LargeTickMiss) continue; // Reset combo if required. if (processor.Combo.Value == maxCombo) insertMiss(); processor.ApplyResult(new JudgementResult(null!, maximumJudgements[maxJudgementIndex++]) { Type = result }); } // Ensure we haven't forgotten any misses. while (misses.Count > 0) insertMiss(); 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; void insertMiss() { if (misses.Count > 0) { processor.ApplyResult(new JudgementResult(null!, maximumJudgements[maxJudgementIndex++]) { Type = misses.Dequeue(), }); } else { // We ran out of misses. But we can't let max combo increase beyond the known value, // so let's forge a miss. processor.ApplyResult(new JudgementResult(null!, new FakeJudgement(getMaxJudgementFor(HitResult.Miss, maxRulesetJudgement))) { Type = HitResult.Miss, }); } } } 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 => numericScoreFor(kvp.Key) * kvp.Value) / score.MaximumStatistics.Where(kvp => kvp.Key.AffectsAccuracy()).Sum(kvp => numericScoreFor(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 => numericScoreFor(kvp.Key) * kvp.Value); double accuracyPortion = 0.3; switch (score.RulesetID) { case 1: accuracyPortion = 0.75; break; case 3: accuracyPortion = 0.99; break; } double modMultiplier = 1; foreach (var mod in score.Mods) modMultiplier *= mod.ScoreMultiplier; return (long)Math.Round((1000000 * (accuracyPortion * accuracyScore + (1 - accuracyPortion) * comboScore) + bonusScore) * modMultiplier); static int numericScoreFor(HitResult result) { switch (result) { default: return 0; case HitResult.SmallTickHit: return 10; case HitResult.LargeTickHit: return 30; case HitResult.Meh: return 50; case HitResult.Ok: return 100; case HitResult.Good: return 200; case HitResult.Great: return 300; case HitResult.Perfect: return 315; case HitResult.SmallBonus: return 10; case HitResult.LargeBonus: return 50; } } } /// /// Updates a to standardised scoring. /// This will recompite the score's (always), (always), /// and (if the score comes from stable). /// The total score from stable - if any applicable - will be stored to . /// /// The score to update. /// The applicable for this score. public static void UpdateFromLegacy(ScoreInfo score, WorkingBeatmap beatmap) { var ruleset = score.Ruleset.CreateInstance(); var scoreProcessor = ruleset.CreateScoreProcessor(); // warning: ordering is important here - both total score and ranks are dependent on accuracy! score.Accuracy = computeAccuracy(score, scoreProcessor); score.Rank = computeRank(score, scoreProcessor); score.TotalScore = convertFromLegacyTotalScore(score, ruleset, beatmap); } /// /// Updates a to standardised scoring. /// This will recompute the score's (always), (always), /// and (if the score comes from stable). /// The total score from stable - if any applicable - will be stored to . /// /// /// This overload is intended for server-side flows. /// See: https://github.com/ppy/osu-queue-score-statistics/blob/3681e92ac91c6c61922094bdbc7e92e6217dd0fc/osu.Server.Queues.ScoreStatisticsProcessor/Commands/Queue/BatchInserter.cs /// /// The score to update. /// The in which the score was set. /// The beatmap difficulty. /// The legacy scoring attributes for the beatmap which the score was set on. public static void UpdateFromLegacy(ScoreInfo score, Ruleset ruleset, LegacyBeatmapConversionDifficultyInfo difficulty, LegacyScoreAttributes attributes) { var scoreProcessor = ruleset.CreateScoreProcessor(); // warning: ordering is important here - both total score and ranks are dependent on accuracy! score.Accuracy = computeAccuracy(score, scoreProcessor); score.Rank = computeRank(score, scoreProcessor); score.TotalScore = convertFromLegacyTotalScore(score, ruleset, difficulty, attributes); } /// /// Converts from to the new standardised scoring of . /// /// The score to convert the total score of. /// The in which the score was set. /// The applicable for this score. /// The standardised total score. private static long convertFromLegacyTotalScore(ScoreInfo score, Ruleset ruleset, WorkingBeatmap beatmap) { if (!score.IsLegacyScore) return score.TotalScore; if (ruleset is not ILegacyRuleset legacyRuleset) return score.TotalScore; var mods = score.Mods; if (mods.Any(mod => mod is ModScoreV2)) return score.TotalScore; var playableBeatmap = beatmap.GetPlayableBeatmap(ruleset.RulesetInfo, score.Mods); if (playableBeatmap.HitObjects.Count == 0) throw new InvalidOperationException("Beatmap contains no hit objects!"); ILegacyScoreSimulator sv1Simulator = legacyRuleset.CreateLegacyScoreSimulator(); LegacyScoreAttributes attributes = sv1Simulator.Simulate(beatmap, playableBeatmap); return convertFromLegacyTotalScore(score, ruleset, LegacyBeatmapConversionDifficultyInfo.FromBeatmap(beatmap.Beatmap), attributes); } /// /// Converts from to the new standardised scoring of . /// /// The score to convert the total score of. /// The in which the score was set. /// The beatmap difficulty. /// The legacy scoring attributes for the beatmap which the score was set on. /// The standardised total score. private static long convertFromLegacyTotalScore(ScoreInfo score, Ruleset ruleset, LegacyBeatmapConversionDifficultyInfo difficulty, LegacyScoreAttributes attributes) { if (!score.IsLegacyScore) return score.TotalScore; Debug.Assert(score.LegacyTotalScore != null); if (ruleset is not ILegacyRuleset legacyRuleset) return score.TotalScore; double legacyModMultiplier = legacyRuleset.CreateLegacyScoreSimulator().GetLegacyScoreMultiplier(score.Mods, difficulty); int maximumLegacyAccuracyScore = attributes.AccuracyScore; long maximumLegacyComboScore = (long)Math.Round(attributes.ComboScore * legacyModMultiplier); double maximumLegacyBonusRatio = attributes.BonusScoreRatio; long maximumLegacyBonusScore = attributes.BonusScore; double legacyAccScore = maximumLegacyAccuracyScore * score.Accuracy; double comboProportion; if (maximumLegacyComboScore + maximumLegacyBonusScore > 0) { // We can not separate the ComboScore from the BonusScore, so we keep the bonus in the ratio. comboProportion = Math.Max((double)score.LegacyTotalScore - legacyAccScore, 0) / (maximumLegacyComboScore + maximumLegacyBonusScore); } else { // Two possible causes: // the beatmap has no bonus objects *AND* // either the active mods have a zero mod multiplier, in which case assume 0, // or the *beatmap* has a zero `difficultyPeppyStars` (or just no combo-giving objects), in which case assume 1. comboProportion = legacyModMultiplier == 0 ? 0 : 1; } // We assume the bonus proportion only makes up the rest of the score that exceeds maximumLegacyBaseScore. long maximumLegacyBaseScore = maximumLegacyAccuracyScore + maximumLegacyComboScore; double bonusProportion = Math.Max(0, ((long)score.LegacyTotalScore - maximumLegacyBaseScore) * maximumLegacyBonusRatio); double modMultiplier = score.Mods.Select(m => m.ScoreMultiplier).Aggregate(1.0, (c, n) => c * n); long convertedTotalScore; switch (score.Ruleset.OnlineID) { case 0: if (score.MaxCombo == 0 || score.Accuracy == 0) { return (long)Math.Round(( 0 + 500000 * Math.Pow(score.Accuracy, 5) + bonusProportion) * modMultiplier); } // see similar check above. // if there is no legacy combo score, all combo conversion operations below // are either pointless or wildly wrong. if (maximumLegacyComboScore + maximumLegacyBonusScore == 0) { return (long)Math.Round(( 500000 * comboProportion // as above, zero if mods result in zero multiplier, one otherwise + 500000 * Math.Pow(score.Accuracy, 5) + bonusProportion) * modMultiplier); } // Assumptions: // - sliders and slider ticks are uniformly distributed in the beatmap, and thus can be ignored without losing much precision. // We thus consider a map of hit-circles only, which gives objectCount == maximumCombo. // - the Ok/Meh hit results are uniformly spread in the score, and thus can be ignored without losing much precision. // We simplify and consider each hit result to have the same hit value of `300 * score.Accuracy` // (which represents the average hit value over the entire play), // which allows us to isolate the accuracy multiplier. // This is a very ballpark estimate of the maximum magnitude of the combo portion in score V1. // It is derived by assuming a full combo play and summing up the contribution to combo portion from each individual object. // Because each object's combo contribution is proportional to the current combo at the time of judgement, // this can be roughly represented by summing / integrating f(combo) = combo. // All mod- and beatmap-dependent multipliers and constants are not included here, // as we will only be using the magnitude of this to compute ratios. int maximumLegacyCombo = attributes.MaxCombo; double maximumAchievableComboPortionInScoreV1 = Math.Pow(maximumLegacyCombo, 2); // Similarly, estimate the maximum magnitude of the combo portion in standardised score. // Roughly corresponds to integrating f(combo) = combo ^ COMBO_EXPONENT (omitting constants) double maximumAchievableComboPortionInStandardisedScore = Math.Pow(maximumLegacyCombo, 1 + ScoreProcessor.COMBO_EXPONENT); // This is - roughly - how much score, in the combo portion, the longest combo on this particular play would gain in score V1. double comboPortionFromLongestComboInScoreV1 = Math.Pow(score.MaxCombo, 2); // Same for standardised score. double comboPortionFromLongestComboInStandardisedScore = Math.Pow(score.MaxCombo, 1 + ScoreProcessor.COMBO_EXPONENT); // We estimate the combo portion of the score in score V1 terms. // The division by accuracy is supposed to lessen the impact of accuracy on the combo portion, // but in some edge cases it cannot sanely undo it. // Therefore the resultant value is clamped from both sides for sanity. // The clamp from below to `comboPortionFromLongestComboInScoreV1` targets near-FC scores wherein // the player had bad accuracy at the end of their longest combo, which causes the division by accuracy // to underestimate the combo portion. // Ideally, this would be clamped from above to `maximumAchievableComboPortionInScoreV1` too, // but in practice this appears to fail for some scores (https://github.com/ppy/osu/pull/25876#issuecomment-1862248413). // TODO: investigate the above more closely double comboPortionInScoreV1 = Math.Max(maximumAchievableComboPortionInScoreV1 * comboProportion / score.Accuracy, comboPortionFromLongestComboInScoreV1); // Calculate how many times the longest combo the user has achieved in the play can repeat // without exceeding the combo portion in score V1 as achieved by the player. // This is a pessimistic estimate; it intentionally does not operate on object count and uses only score instead. double maximumOccurrencesOfLongestCombo = Math.Floor(comboPortionInScoreV1 / comboPortionFromLongestComboInScoreV1); double comboPortionFromRepeatedLongestCombosInScoreV1 = maximumOccurrencesOfLongestCombo * comboPortionFromLongestComboInScoreV1; double remainingComboPortionInScoreV1 = comboPortionInScoreV1 - comboPortionFromRepeatedLongestCombosInScoreV1; // `remainingComboPortionInScoreV1` is in the "score ballpark" realm, which means it's proportional to combo squared. // To convert that back to a raw combo length, we need to take the square root... double remainingCombo = Math.Sqrt(remainingComboPortionInScoreV1); // ...and then based on that raw combo length, we calculate how much this last combo is worth in standardised score. double remainingComboPortionInStandardisedScore = Math.Pow(remainingCombo, 1 + ScoreProcessor.COMBO_EXPONENT); double lowerEstimateOfComboPortionInStandardisedScore = maximumOccurrencesOfLongestCombo * comboPortionFromLongestComboInStandardisedScore + remainingComboPortionInStandardisedScore; // Compute approximate upper estimate new score for that play. // This time, divide the remaining combo among remaining objects equally to achieve longest possible combo lengths. // There is no rigorous proof that doing this will yield a correct upper bound, but it seems to work out in practice. remainingComboPortionInScoreV1 = comboPortionInScoreV1 - comboPortionFromLongestComboInScoreV1; double remainingCountOfObjectsGivingCombo = maximumLegacyCombo - score.MaxCombo - score.Statistics.GetValueOrDefault(HitResult.Miss); // Because we assumed all combos were equal, `remainingComboPortionInScoreV1` // can be approximated by n * x^2, wherein n is the assumed number of equal combos, // and x is the assumed length of every one of those combos. // The remaining count of objects giving combo is, using those terms, equal to n * x. // Therefore, dividing the two will result in x, i.e. the assumed length of the remaining combos. double lengthOfRemainingCombos = remainingCountOfObjectsGivingCombo > 0 ? remainingComboPortionInScoreV1 / remainingCountOfObjectsGivingCombo : 0; // In standardised scoring, each combo yields a score proportional to combo length to the power 1 + COMBO_EXPONENT. // Using the symbols introduced above, that would be x ^ 1.5 per combo, n times (because there are n assumed equal-length combos). // However, because `remainingCountOfObjectsGivingCombo` - using the symbols introduced above - is assumed to be equal to n * x, // we can skip adding the 1 and just multiply by x ^ 0.5. remainingComboPortionInStandardisedScore = remainingCountOfObjectsGivingCombo * Math.Pow(lengthOfRemainingCombos, ScoreProcessor.COMBO_EXPONENT); double upperEstimateOfComboPortionInStandardisedScore = comboPortionFromLongestComboInStandardisedScore + remainingComboPortionInStandardisedScore; // Approximate by combining lower and upper estimates. // As the lower-estimate is very pessimistic, we use a 30/70 ratio // and cap it with 1.2 times the middle-point to avoid overestimates. double estimatedComboPortionInStandardisedScore = Math.Min( 0.3 * lowerEstimateOfComboPortionInStandardisedScore + 0.7 * upperEstimateOfComboPortionInStandardisedScore, 1.2 * (lowerEstimateOfComboPortionInStandardisedScore + upperEstimateOfComboPortionInStandardisedScore) / 2 ); double newComboScoreProportion = estimatedComboPortionInStandardisedScore / maximumAchievableComboPortionInStandardisedScore; convertedTotalScore = (long)Math.Round(( 500000 * newComboScoreProportion * score.Accuracy + 500000 * Math.Pow(score.Accuracy, 5) + bonusProportion) * modMultiplier); break; case 1: convertedTotalScore = (long)Math.Round(( 250000 * comboProportion + 750000 * Math.Pow(score.Accuracy, 3.6) + bonusProportion) * modMultiplier); break; case 2: // compare logic in `CatchScoreProcessor`. // this could technically be slightly incorrect in the case of stable scores. // because large droplet misses are counted as full misses in stable scores, // `score.MaximumStatistics.GetValueOrDefault(Great)` will be equal to the count of fruits *and* large droplets // rather than just fruits (which was the intent). // this is not fixable without introducing an extra legacy score attribute dedicated for catch, // and this is a ballpark conversion process anyway, so attempt to trudge on. int fruitTinyScaleDivisor = score.MaximumStatistics.GetValueOrDefault(HitResult.SmallTickHit) + score.MaximumStatistics.GetValueOrDefault(HitResult.Great); double fruitTinyScale = fruitTinyScaleDivisor == 0 ? 0 : (double)score.MaximumStatistics.GetValueOrDefault(HitResult.SmallTickHit) / fruitTinyScaleDivisor; const int max_tiny_droplets_portion = 400000; double comboPortion = 1000000 - max_tiny_droplets_portion + max_tiny_droplets_portion * (1 - fruitTinyScale); double dropletsPortion = max_tiny_droplets_portion * fruitTinyScale; double dropletsHit = score.MaximumStatistics.GetValueOrDefault(HitResult.SmallTickHit) == 0 ? 0 : (double)score.Statistics.GetValueOrDefault(HitResult.SmallTickHit) / score.MaximumStatistics.GetValueOrDefault(HitResult.SmallTickHit); convertedTotalScore = (long)Math.Round(( comboPortion * estimateComboProportionForCatch(attributes.MaxCombo, score.MaxCombo, score.Statistics.GetValueOrDefault(HitResult.Miss)) + dropletsPortion * dropletsHit + bonusProportion) * modMultiplier); break; case 3: convertedTotalScore = (long)Math.Round(( 850000 * comboProportion + 150000 * Math.Pow(score.Accuracy, 2 + 2 * score.Accuracy) + bonusProportion) * modMultiplier); break; default: convertedTotalScore = score.TotalScore; break; } if (convertedTotalScore < 0) throw new InvalidOperationException($"Total score conversion operation returned invalid total of {convertedTotalScore}"); return convertedTotalScore; } /// /// /// For catch, the general method of calculating the combo proportion used for other rulesets is generally useless. /// This is because in stable score V1, catch has quadratic score progression, /// while in stable score V2, score progression is logarithmic up to 200 combo and then linear. /// /// /// This means that applying the naive rescale method to scores with lots of short combos (think 10x 100-long combos on a 1000-object map) /// by linearly rescaling the combo portion as given by score V1 leads to horribly underestimating it. /// Therefore this method attempts to counteract this by calculating the best case estimate for the combo proportion that takes all of the above into account. /// /// /// The general idea is that aside from the which the player is known to have hit, /// the remaining misses are evenly distributed across the rest of the objects that give combo. /// This is therefore a worst-case estimate. /// /// private static double estimateComboProportionForCatch(int beatmapMaxCombo, int scoreMaxCombo, int scoreMissCount) { if (beatmapMaxCombo == 0) return 1; if (scoreMaxCombo == 0) return 0; if (beatmapMaxCombo == scoreMaxCombo) return 1; double estimatedBestCaseTotal = estimateBestCaseComboTotal(beatmapMaxCombo); int remainingCombo = beatmapMaxCombo - (scoreMaxCombo + scoreMissCount); double totalDroppedScore = 0; int assumedLengthOfRemainingCombos = (int)Math.Floor((double)remainingCombo / scoreMissCount); if (assumedLengthOfRemainingCombos > 0) { int assumedCombosCount = (int)Math.Floor((double)remainingCombo / assumedLengthOfRemainingCombos); totalDroppedScore += assumedCombosCount * estimateDroppedComboScoreAfterMiss(assumedLengthOfRemainingCombos); remainingCombo -= assumedCombosCount * assumedLengthOfRemainingCombos; if (remainingCombo > 0) totalDroppedScore += estimateDroppedComboScoreAfterMiss(remainingCombo); } else { // there are so many misses that attempting to evenly divide remaining combo results in 0 length per combo, // i.e. all remaining judgements are combo breaks. // in that case, presume every single remaining object is a miss and did not give any combo score. totalDroppedScore = estimatedBestCaseTotal - estimateBestCaseComboTotal(scoreMaxCombo); } return estimatedBestCaseTotal == 0 ? 1 : 1 - Math.Clamp(totalDroppedScore / estimatedBestCaseTotal, 0, 1); double estimateBestCaseComboTotal(int maxCombo) { if (maxCombo == 0) return 1; double estimatedTotal = 0.5 * Math.Min(maxCombo, 2); if (maxCombo <= 2) return estimatedTotal; // int_2^x log_4(t) dt estimatedTotal += (Math.Min(maxCombo, 200) * (Math.Log(Math.Min(maxCombo, 200)) - 1) + 2 - Math.Log(4)) / Math.Log(4); if (maxCombo <= 200) return estimatedTotal; estimatedTotal += (maxCombo - 200) * Math.Log(200) / Math.Log(4); return estimatedTotal; } double estimateDroppedComboScoreAfterMiss(int lengthOfComboAfterMiss) { if (lengthOfComboAfterMiss >= 200) lengthOfComboAfterMiss = 200; // int_0^x (log_4(200) - log_4(t)) dt // note that this is an pessimistic estimate, i.e. it may subtract too much if the miss happened before reaching 200 combo return lengthOfComboAfterMiss * (1 + Math.Log(200) - Math.Log(lengthOfComboAfterMiss)) / Math.Log(4); } } private static double computeAccuracy(ScoreInfo scoreInfo, ScoreProcessor scoreProcessor) { int baseScore = scoreInfo.Statistics.Where(kvp => kvp.Key.AffectsAccuracy()) .Sum(kvp => kvp.Value * scoreProcessor.GetBaseScoreForResult(kvp.Key)); int maxBaseScore = scoreInfo.MaximumStatistics.Where(kvp => kvp.Key.AffectsAccuracy()) .Sum(kvp => kvp.Value * scoreProcessor.GetBaseScoreForResult(kvp.Key)); return maxBaseScore == 0 ? 1 : baseScore / (double)maxBaseScore; } public static ScoreRank ComputeRank(ScoreInfo scoreInfo) => computeRank(scoreInfo, scoreInfo.Ruleset.CreateInstance().CreateScoreProcessor()); private static ScoreRank computeRank(ScoreInfo scoreInfo, ScoreProcessor scoreProcessor) { var rank = scoreProcessor.RankFromScore(scoreInfo.Accuracy, scoreInfo.Statistics); foreach (var mod in scoreInfo.Mods.OfType()) rank = mod.AdjustRank(rank, scoreInfo.Accuracy); return rank; } /// /// Used to populate the model using data parsed from its corresponding replay file. /// /// The score to run population from replay for. /// A instance to use for fetching replay. /// /// Delegate describing the population to execute. /// The delegate's argument is a instance which permits to read data from the replay stream. /// public static void PopulateFromReplay(this ScoreInfo score, RealmFileStore files, Action populationFunc) { string? replayFilename = score.Files.FirstOrDefault(f => f.Filename.EndsWith(@".osr", StringComparison.InvariantCultureIgnoreCase))?.File.GetStoragePath(); if (replayFilename == null) return; try { using (var stream = files.Store.GetStream(replayFilename)) { if (stream == null) return; using (SerializationReader sr = new SerializationReader(stream)) populationFunc.Invoke(sr); } } catch (Exception e) { Logger.Error(e, $"Failed to read replay {replayFilename} during score migration", LoggingTarget.Database); } } private class FakeHit : HitObject { private readonly Judgement judgement; public override Judgement CreateJudgement() => judgement; public FakeHit(Judgement judgement) { this.judgement = judgement; } } private class FakeJudgement : Judgement { public override HitResult MaxResult { get; } public FakeJudgement(HitResult maxResult) { MaxResult = maxResult; } } } }