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cb87d6ce50
This subtle detail was messing with server-side score import flows. Server-side, legacy total score will *already* be in `LegacyTotalScore` from the start, and `TotalScore` will be zero until recomputed via `StandardisedScoreMigrationTools.UpdateFromLegacy()` - so in that context, attempting to move it across is incorrect.
677 lines
35 KiB
C#
677 lines
35 KiB
C#
// Copyright (c) ppy Pty Ltd <contact@ppy.sh>. Licensed under the MIT Licence.
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// See the LICENCE file in the repository root for full licence text.
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using System;
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using System.Collections.Generic;
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using System.Diagnostics;
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using System.Linq;
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using osu.Framework.Logging;
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using osu.Game.Beatmaps;
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using osu.Game.Extensions;
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using osu.Game.IO.Legacy;
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using osu.Game.Rulesets;
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using osu.Game.Rulesets.Judgements;
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using osu.Game.Rulesets.Mods;
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using osu.Game.Rulesets.Objects;
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using osu.Game.Rulesets.Scoring;
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using osu.Game.Rulesets.Scoring.Legacy;
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using osu.Game.Scoring;
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namespace osu.Game.Database
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{
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public static class StandardisedScoreMigrationTools
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{
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public static bool ShouldMigrateToNewStandardised(ScoreInfo score)
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{
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if (score.IsLegacyScore)
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return false;
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if (score.TotalScoreVersion > 30000002)
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return false;
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// Recalculate the old-style standardised score to see if this was an old lazer score.
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bool oldScoreMatchesExpectations = GetOldStandardised(score) == score.TotalScore;
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// Some older scores don't have correct statistics populated, so let's give them benefit of doubt.
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bool scoreIsVeryOld = score.Date < new DateTime(2023, 1, 1, 0, 0, 0);
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return oldScoreMatchesExpectations || scoreIsVeryOld;
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}
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public static long GetNewStandardised(ScoreInfo score)
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{
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int maxJudgementIndex = 0;
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// Avoid retrieving from realm inside loops.
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int maxCombo = score.MaxCombo;
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var ruleset = score.Ruleset.CreateInstance();
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var processor = ruleset.CreateScoreProcessor();
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processor.TrackHitEvents = false;
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var beatmap = new Beatmap();
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HitResult maxRulesetJudgement = ruleset.GetHitResults().First().result;
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// This is a list of all results, ordered from best to worst.
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// We are constructing a "best possible" score from the statistics provided because it's the best we can do.
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List<HitResult> sortedHits = score.Statistics
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.Where(kvp => kvp.Key.AffectsCombo())
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.OrderByDescending(kvp => processor.GetBaseScoreForResult(kvp.Key))
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.SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value))
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.ToList();
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// Attempt to use maximum statistics from the database.
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var maximumJudgements = score.MaximumStatistics
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.Where(kvp => kvp.Key.AffectsCombo())
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.OrderByDescending(kvp => processor.GetBaseScoreForResult(kvp.Key))
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.SelectMany(kvp => Enumerable.Repeat(new FakeJudgement(kvp.Key), kvp.Value))
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.ToList();
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// Some older scores may not have maximum statistics populated correctly.
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// In this case we need to fill them with best-known-defaults.
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if (maximumJudgements.Count != sortedHits.Count)
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{
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maximumJudgements = sortedHits
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.Select(r => new FakeJudgement(getMaxJudgementFor(r, maxRulesetJudgement)))
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.ToList();
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}
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// This is required to get the correct maximum combo portion.
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foreach (var judgement in maximumJudgements)
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beatmap.HitObjects.Add(new FakeHit(judgement));
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processor.ApplyBeatmap(beatmap);
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processor.Mods.Value = score.Mods;
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// Insert all misses into a queue.
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// These will be nibbled at whenever we need to reset the combo.
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Queue<HitResult> misses = new Queue<HitResult>(score.Statistics
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.Where(kvp => kvp.Key == HitResult.Miss || kvp.Key == HitResult.LargeTickMiss)
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.SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value)));
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foreach (var result in sortedHits)
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{
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// For the main part of this loop, ignore all misses, as they will be inserted from the queue.
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if (result == HitResult.Miss || result == HitResult.LargeTickMiss)
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continue;
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// Reset combo if required.
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if (processor.Combo.Value == maxCombo)
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insertMiss();
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processor.ApplyResult(new JudgementResult(null!, maximumJudgements[maxJudgementIndex++])
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{
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Type = result
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});
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}
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// Ensure we haven't forgotten any misses.
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while (misses.Count > 0)
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insertMiss();
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var bonusHits = score.Statistics
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.Where(kvp => kvp.Key.IsBonus())
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.SelectMany(kvp => Enumerable.Repeat(kvp.Key, kvp.Value));
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foreach (var result in bonusHits)
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processor.ApplyResult(new JudgementResult(null!, new FakeJudgement(result)) { Type = result });
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// Not true for all scores for whatever reason. Oh well.
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// Debug.Assert(processor.HighestCombo.Value == score.MaxCombo);
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return processor.TotalScore.Value;
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void insertMiss()
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{
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if (misses.Count > 0)
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{
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processor.ApplyResult(new JudgementResult(null!, maximumJudgements[maxJudgementIndex++])
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{
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Type = misses.Dequeue(),
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});
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}
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else
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{
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// We ran out of misses. But we can't let max combo increase beyond the known value,
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// so let's forge a miss.
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processor.ApplyResult(new JudgementResult(null!, new FakeJudgement(getMaxJudgementFor(HitResult.Miss, maxRulesetJudgement)))
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{
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Type = HitResult.Miss,
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});
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}
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}
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}
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private static HitResult getMaxJudgementFor(HitResult hitResult, HitResult max)
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{
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switch (hitResult)
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{
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case HitResult.Miss:
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case HitResult.Meh:
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case HitResult.Ok:
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case HitResult.Good:
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case HitResult.Great:
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case HitResult.Perfect:
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return max;
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case HitResult.SmallTickMiss:
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case HitResult.SmallTickHit:
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return HitResult.SmallTickHit;
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case HitResult.LargeTickMiss:
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case HitResult.LargeTickHit:
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return HitResult.LargeTickHit;
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}
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return HitResult.IgnoreHit;
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}
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public static long GetOldStandardised(ScoreInfo score)
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{
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double accuracyScore =
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(double)score.Statistics.Where(kvp => kvp.Key.AffectsAccuracy()).Sum(kvp => numericScoreFor(kvp.Key) * kvp.Value)
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/ score.MaximumStatistics.Where(kvp => kvp.Key.AffectsAccuracy()).Sum(kvp => numericScoreFor(kvp.Key) * kvp.Value);
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double comboScore = (double)score.MaxCombo / score.MaximumStatistics.Where(kvp => kvp.Key.AffectsCombo()).Sum(kvp => kvp.Value);
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double bonusScore = score.Statistics.Where(kvp => kvp.Key.IsBonus()).Sum(kvp => numericScoreFor(kvp.Key) * kvp.Value);
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double accuracyPortion = 0.3;
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switch (score.RulesetID)
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{
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case 1:
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accuracyPortion = 0.75;
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break;
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case 3:
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accuracyPortion = 0.99;
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break;
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}
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double modMultiplier = 1;
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foreach (var mod in score.Mods)
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modMultiplier *= mod.ScoreMultiplier;
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return (long)Math.Round((1000000 * (accuracyPortion * accuracyScore + (1 - accuracyPortion) * comboScore) + bonusScore) * modMultiplier);
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static int numericScoreFor(HitResult result)
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{
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switch (result)
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{
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default:
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return 0;
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case HitResult.SmallTickHit:
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return 10;
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case HitResult.LargeTickHit:
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return 30;
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case HitResult.Meh:
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return 50;
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case HitResult.Ok:
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return 100;
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case HitResult.Good:
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return 200;
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case HitResult.Great:
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return 300;
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case HitResult.Perfect:
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return 315;
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case HitResult.SmallBonus:
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return 10;
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case HitResult.LargeBonus:
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return 50;
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}
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}
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}
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/// <summary>
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/// Updates a <see cref="ScoreInfo"/> to standardised scoring.
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/// This will recompite the score's <see cref="ScoreInfo.Accuracy"/> (always), <see cref="ScoreInfo.Rank"/> (always),
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/// and <see cref="ScoreInfo.TotalScore"/> (if the score comes from stable).
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/// The total score from stable - if any applicable - will be stored to <see cref="ScoreInfo.LegacyTotalScore"/>.
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/// </summary>
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/// <param name="score">The score to update.</param>
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/// <param name="beatmap">The <see cref="WorkingBeatmap"/> applicable for this score.</param>
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public static void UpdateFromLegacy(ScoreInfo score, WorkingBeatmap beatmap)
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{
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var ruleset = score.Ruleset.CreateInstance();
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var scoreProcessor = ruleset.CreateScoreProcessor();
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// warning: ordering is important here - both total score and ranks are dependent on accuracy!
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score.Accuracy = computeAccuracy(score, scoreProcessor);
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score.Rank = computeRank(score, scoreProcessor);
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score.TotalScore = convertFromLegacyTotalScore(score, ruleset, beatmap);
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}
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/// <summary>
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/// Updates a <see cref="ScoreInfo"/> to standardised scoring.
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/// This will recompute the score's <see cref="ScoreInfo.Accuracy"/> (always), <see cref="ScoreInfo.Rank"/> (always),
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/// and <see cref="ScoreInfo.TotalScore"/> (if the score comes from stable).
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/// The total score from stable - if any applicable - will be stored to <see cref="ScoreInfo.LegacyTotalScore"/>.
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/// </summary>
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/// <remarks>
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/// This overload is intended for server-side flows.
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/// See: https://github.com/ppy/osu-queue-score-statistics/blob/3681e92ac91c6c61922094bdbc7e92e6217dd0fc/osu.Server.Queues.ScoreStatisticsProcessor/Commands/Queue/BatchInserter.cs
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/// </remarks>
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/// <param name="score">The score to update.</param>
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/// <param name="ruleset">The <see cref="Ruleset"/> in which the score was set.</param>
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/// <param name="difficulty">The beatmap difficulty.</param>
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/// <param name="attributes">The legacy scoring attributes for the beatmap which the score was set on.</param>
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public static void UpdateFromLegacy(ScoreInfo score, Ruleset ruleset, LegacyBeatmapConversionDifficultyInfo difficulty, LegacyScoreAttributes attributes)
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{
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var scoreProcessor = ruleset.CreateScoreProcessor();
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// warning: ordering is important here - both total score and ranks are dependent on accuracy!
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score.Accuracy = computeAccuracy(score, scoreProcessor);
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score.Rank = computeRank(score, scoreProcessor);
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score.TotalScore = convertFromLegacyTotalScore(score, ruleset, difficulty, attributes);
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}
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/// <summary>
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/// Converts from <see cref="ScoreInfo.LegacyTotalScore"/> to the new standardised scoring of <see cref="ScoreProcessor"/>.
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/// </summary>
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/// <param name="score">The score to convert the total score of.</param>
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/// <param name="ruleset">The <see cref="Ruleset"/> in which the score was set.</param>
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/// <param name="beatmap">The <see cref="WorkingBeatmap"/> applicable for this score.</param>
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/// <returns>The standardised total score.</returns>
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private static long convertFromLegacyTotalScore(ScoreInfo score, Ruleset ruleset, WorkingBeatmap beatmap)
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{
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if (!score.IsLegacyScore)
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return score.TotalScore;
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if (ruleset is not ILegacyRuleset legacyRuleset)
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return score.TotalScore;
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var mods = score.Mods;
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if (mods.Any(mod => mod is ModScoreV2))
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return score.TotalScore;
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var playableBeatmap = beatmap.GetPlayableBeatmap(ruleset.RulesetInfo, score.Mods);
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if (playableBeatmap.HitObjects.Count == 0)
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throw new InvalidOperationException("Beatmap contains no hit objects!");
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ILegacyScoreSimulator sv1Simulator = legacyRuleset.CreateLegacyScoreSimulator();
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LegacyScoreAttributes attributes = sv1Simulator.Simulate(beatmap, playableBeatmap);
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return convertFromLegacyTotalScore(score, ruleset, LegacyBeatmapConversionDifficultyInfo.FromBeatmap(beatmap.Beatmap), attributes);
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}
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/// <summary>
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/// Converts from <see cref="ScoreInfo.LegacyTotalScore"/> to the new standardised scoring of <see cref="ScoreProcessor"/>.
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/// </summary>
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/// <param name="score">The score to convert the total score of.</param>
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/// <param name="ruleset">The <see cref="Ruleset"/> in which the score was set.</param>
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/// <param name="difficulty">The beatmap difficulty.</param>
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/// <param name="attributes">The legacy scoring attributes for the beatmap which the score was set on.</param>
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/// <returns>The standardised total score.</returns>
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private static long convertFromLegacyTotalScore(ScoreInfo score, Ruleset ruleset, LegacyBeatmapConversionDifficultyInfo difficulty, LegacyScoreAttributes attributes)
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{
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if (!score.IsLegacyScore)
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return score.TotalScore;
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Debug.Assert(score.LegacyTotalScore != null);
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if (ruleset is not ILegacyRuleset legacyRuleset)
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return score.TotalScore;
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double legacyModMultiplier = legacyRuleset.CreateLegacyScoreSimulator().GetLegacyScoreMultiplier(score.Mods, difficulty);
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int maximumLegacyAccuracyScore = attributes.AccuracyScore;
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long maximumLegacyComboScore = (long)Math.Round(attributes.ComboScore * legacyModMultiplier);
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double maximumLegacyBonusRatio = attributes.BonusScoreRatio;
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long maximumLegacyBonusScore = attributes.BonusScore;
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double legacyAccScore = maximumLegacyAccuracyScore * score.Accuracy;
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double comboProportion;
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if (maximumLegacyComboScore + maximumLegacyBonusScore > 0)
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{
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// We can not separate the ComboScore from the BonusScore, so we keep the bonus in the ratio.
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comboProportion = Math.Max((double)score.LegacyTotalScore - legacyAccScore, 0) / (maximumLegacyComboScore + maximumLegacyBonusScore);
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}
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else
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{
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// Two possible causes:
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// the beatmap has no bonus objects *AND*
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// either the active mods have a zero mod multiplier, in which case assume 0,
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// or the *beatmap* has a zero `difficultyPeppyStars` (or just no combo-giving objects), in which case assume 1.
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comboProportion = legacyModMultiplier == 0 ? 0 : 1;
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}
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// We assume the bonus proportion only makes up the rest of the score that exceeds maximumLegacyBaseScore.
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long maximumLegacyBaseScore = maximumLegacyAccuracyScore + maximumLegacyComboScore;
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double bonusProportion = Math.Max(0, ((long)score.LegacyTotalScore - maximumLegacyBaseScore) * maximumLegacyBonusRatio);
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double modMultiplier = score.Mods.Select(m => m.ScoreMultiplier).Aggregate(1.0, (c, n) => c * n);
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long convertedTotalScore;
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switch (score.Ruleset.OnlineID)
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{
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case 0:
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if (score.MaxCombo == 0 || score.Accuracy == 0)
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{
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return (long)Math.Round((
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0
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+ 500000 * Math.Pow(score.Accuracy, 5)
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+ bonusProportion) * modMultiplier);
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}
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// Assumptions:
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// - sliders and slider ticks are uniformly distributed in the beatmap, and thus can be ignored without losing much precision.
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// We thus consider a map of hit-circles only, which gives objectCount == maximumCombo.
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// - the Ok/Meh hit results are uniformly spread in the score, and thus can be ignored without losing much precision.
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// We simplify and consider each hit result to have the same hit value of `300 * score.Accuracy`
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// (which represents the average hit value over the entire play),
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// which allows us to isolate the accuracy multiplier.
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// This is a very ballpark estimate of the maximum magnitude of the combo portion in score V1.
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// It is derived by assuming a full combo play and summing up the contribution to combo portion from each individual object.
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// Because each object's combo contribution is proportional to the current combo at the time of judgement,
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// this can be roughly represented by summing / integrating f(combo) = combo.
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// All mod- and beatmap-dependent multipliers and constants are not included here,
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// as we will only be using the magnitude of this to compute ratios.
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int maximumLegacyCombo = attributes.MaxCombo;
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double maximumAchievableComboPortionInScoreV1 = Math.Pow(maximumLegacyCombo, 2);
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// Similarly, estimate the maximum magnitude of the combo portion in standardised score.
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// Roughly corresponds to integrating f(combo) = combo ^ COMBO_EXPONENT (omitting constants)
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double maximumAchievableComboPortionInStandardisedScore = Math.Pow(maximumLegacyCombo, 1 + ScoreProcessor.COMBO_EXPONENT);
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// This is - roughly - how much score, in the combo portion, the longest combo on this particular play would gain in score V1.
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double comboPortionFromLongestComboInScoreV1 = Math.Pow(score.MaxCombo, 2);
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// Same for standardised score.
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double comboPortionFromLongestComboInStandardisedScore = Math.Pow(score.MaxCombo, 1 + ScoreProcessor.COMBO_EXPONENT);
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// We estimate the combo portion of the score in score V1 terms.
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// The division by accuracy is supposed to lessen the impact of accuracy on the combo portion,
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// but in some edge cases it cannot sanely undo it.
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// Therefore the resultant value is clamped from both sides for sanity.
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// The clamp from below to `comboPortionFromLongestComboInScoreV1` targets near-FC scores wherein
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// the player had bad accuracy at the end of their longest combo, which causes the division by accuracy
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// to underestimate the combo portion.
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// Ideally, this would be clamped from above to `maximumAchievableComboPortionInScoreV1` too,
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// but in practice this appears to fail for some scores (https://github.com/ppy/osu/pull/25876#issuecomment-1862248413).
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// TODO: investigate the above more closely
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double comboPortionInScoreV1 = Math.Max(maximumAchievableComboPortionInScoreV1 * comboProportion / score.Accuracy, comboPortionFromLongestComboInScoreV1);
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// Calculate how many times the longest combo the user has achieved in the play can repeat
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// without exceeding the combo portion in score V1 as achieved by the player.
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// This is a pessimistic estimate; it intentionally does not operate on object count and uses only score instead.
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double maximumOccurrencesOfLongestCombo = Math.Floor(comboPortionInScoreV1 / comboPortionFromLongestComboInScoreV1);
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double comboPortionFromRepeatedLongestCombosInScoreV1 = maximumOccurrencesOfLongestCombo * comboPortionFromLongestComboInScoreV1;
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double remainingComboPortionInScoreV1 = comboPortionInScoreV1 - comboPortionFromRepeatedLongestCombosInScoreV1;
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// `remainingComboPortionInScoreV1` is in the "score ballpark" realm, which means it's proportional to combo squared.
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// To convert that back to a raw combo length, we need to take the square root...
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double remainingCombo = Math.Sqrt(remainingComboPortionInScoreV1);
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// ...and then based on that raw combo length, we calculate how much this last combo is worth in standardised score.
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double remainingComboPortionInStandardisedScore = Math.Pow(remainingCombo, 1 + ScoreProcessor.COMBO_EXPONENT);
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double lowerEstimateOfComboPortionInStandardisedScore
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= maximumOccurrencesOfLongestCombo * comboPortionFromLongestComboInStandardisedScore
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+ remainingComboPortionInStandardisedScore;
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// Compute approximate upper estimate new score for that play.
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// This time, divide the remaining combo among remaining objects equally to achieve longest possible combo lengths.
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// There is no rigorous proof that doing this will yield a correct upper bound, but it seems to work out in practice.
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remainingComboPortionInScoreV1 = comboPortionInScoreV1 - comboPortionFromLongestComboInScoreV1;
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double remainingCountOfObjectsGivingCombo = maximumLegacyCombo - score.MaxCombo - score.Statistics.GetValueOrDefault(HitResult.Miss);
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// Because we assumed all combos were equal, `remainingComboPortionInScoreV1`
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// can be approximated by n * x^2, wherein n is the assumed number of equal combos,
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// and x is the assumed length of every one of those combos.
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// The remaining count of objects giving combo is, using those terms, equal to n * x.
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// Therefore, dividing the two will result in x, i.e. the assumed length of the remaining combos.
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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;
|
|
}
|
|
|
|
/// <summary>
|
|
/// <para>
|
|
/// 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.
|
|
/// </para>
|
|
/// <para>
|
|
/// 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.
|
|
/// </para>
|
|
/// <para>
|
|
/// The general idea is that aside from the <paramref name="scoreMaxCombo"/> 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.
|
|
/// </para>
|
|
/// </summary>
|
|
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<IApplicableToScoreProcessor>())
|
|
rank = mod.AdjustRank(rank, scoreInfo.Accuracy);
|
|
|
|
return rank;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Used to populate the <paramref name="score"/> model using data parsed from its corresponding replay file.
|
|
/// </summary>
|
|
/// <param name="score">The score to run population from replay for.</param>
|
|
/// <param name="files">A <see cref="RealmFileStore"/> instance to use for fetching replay.</param>
|
|
/// <param name="populationFunc">
|
|
/// Delegate describing the population to execute.
|
|
/// The delegate's argument is a <see cref="SerializationReader"/> instance which permits to read data from the replay stream.
|
|
/// </param>
|
|
public static void PopulateFromReplay(this ScoreInfo score, RealmFileStore files, Action<SerializationReader> 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;
|
|
}
|
|
}
|
|
}
|
|
}
|