More work on getting a basic agent implementation to work
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nise.moe
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95650c5ca6
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0067642359
@ -1,96 +1,220 @@
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package com.nisemoe.nise.scheduler
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import com.nisemoe.generated.tables.records.ScoresRecord
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import com.nisemoe.generated.tables.records.UsersRecord
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import com.nisemoe.generated.tables.references.SCORES
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import com.nisemoe.generated.tables.references.USERS
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import com.nisemoe.nise.osu.OsuApi
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import org.jooq.DSLContext
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import org.springframework.context.annotation.Profile
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import org.springframework.scheduling.annotation.Scheduled
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import org.springframework.stereotype.Service
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import java.time.LocalDateTime
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import java.time.temporal.ChronoUnit
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import kotlin.math.roundToInt
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data class UserReport(
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val username: String,
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val susScore: Double,
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val urgencyScore: Double,
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val userId: Long,
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val userScores: List<ScoresRecord>
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)
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val userScores: List<Agent.ScoreMetrics>
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) {
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override fun toString(): String {
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val s = "User: $username (https://nise.moe/u/${username})- Suspiciousness score: ${susScore.roundToInt()} | Urgency score: ${urgencyScore.roundToInt()}"
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val s2 = "Average PP: ${userScores.map { it.pp }.average()} | Average UR: ${userScores.map { it.adjustedUr }.average()} | Average Sliderend Release: ${userScores.map { it.sliderendReleaseStandardDeviationAdjusted }.average()}"
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return s + "\n" + s2 + "\n"
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}
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}
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@Service
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@Profile("agent")
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class Agent(
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private val dslContext: DSLContext
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private val dslContext: DSLContext,
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private val osuApi: OsuApi
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) {
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// 20 minutes to ms = 1200000
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@Scheduled(fixedDelay = 1200000, initialDelay = 0)
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fun buildReports() {
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// Select sus scores
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val susUsers = dslContext.select(
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SCORES.USER_ID,
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SCORES.ADJUSTED_UR,
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SCORES.SLIDEREND_RELEASE_STANDARD_DEVIATION_ADJUSTED,
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SCORES.PP,
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SCORES.EDGE_HITS,
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SCORES.SNAPS,
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SCORES.KEYPRESSES_MEDIAN_ADJUSTED,
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SCORES.ERROR_KURTOSIS
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)
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.from(SCORES)
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.where(SCORES.ADJUSTED_UR.lessOrEqual(10.0))
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.and(SCORES.SLIDEREND_RELEASE_STANDARD_DEVIATION_ADJUSTED.lessOrEqual(8.0))
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.and(SCORES.IS_BANNED.isFalse)
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.and(SCORES.VERSION.greaterOrEqual(4))
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.fetchInto(ScoresRecord::class.java)
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val reports = mutableListOf<UserReport>()
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for(user in susUsers.groupBy { it.userId }) {
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val userId = user.key!!
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val username = dslContext.select(USERS.USERNAME)
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.from(USERS)
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val userIds = dslContext.select(SCORES.USER_ID)
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.from(SCORES)
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.where(SCORES.ADJUSTED_UR.lessOrEqual(256.0))
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.and(SCORES.SLIDEREND_RELEASE_STANDARD_DEVIATION_ADJUSTED.isNotNull)
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.and(SCORES.SLIDEREND_RELEASE_STANDARD_DEVIATION_ADJUSTED.lessOrEqual(16.0))
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.and(SCORES.IS_BANNED.isFalse)
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.and(SCORES.VERSION.greaterOrEqual(4))
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.groupBy(SCORES.USER_ID)
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.fetchInto(Long::class.java)
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println("Found ${userIds.size} users to check.")
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// We check if any of them are banned.
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// val bannedIds = mutableListOf<Long>()
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// for(chunk in userIds.chunked(50)) {
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//
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// val result = osuApi.getUsersBatch(chunk)
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// if(result == null) {
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// println("Failed to get users from osu! api")
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// return
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// }
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//
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// // Compare which userIds aren't in the result and mark them as banned.
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// val bannedUsers = chunk.filter { it !in result.users.map { it.id } }
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// bannedIds.addAll(bannedUsers)
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// }
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//
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// if(bannedIds.isNotEmpty()) {
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// // Remove all banned users from the list
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// susUsers.removeIf { it.userId in bannedIds }
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//
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// // Mark all their scores as banned
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// dslContext.update(SCORES)
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// .set(SCORES.IS_BANNED, true)
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// .where(SCORES.USER_ID.`in`(bannedIds))
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// .execute()
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//
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// println("Marked ${bannedIds.size} users as banned: $bannedIds")
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// }
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for(userId in userIds) {
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val userDetails = dslContext.selectFrom(USERS)
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.where(USERS.USER_ID.eq(userId))
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.fetchOne(USERS.USERNAME) ?: continue
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.fetchOneInto(UsersRecord::class.java) ?: continue
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val userScores = user.value
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val susScore = calculateSuspiciousnessScore(userScores)
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val username = userDetails.username!!
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val userScores = dslContext.select(
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SCORES.DATE,
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SCORES.ADJUSTED_UR,
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SCORES.SLIDEREND_RELEASE_STANDARD_DEVIATION_ADJUSTED,
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SCORES.PP,
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SCORES.EDGE_HITS,
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SCORES.SNAPS,
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SCORES.KEYPRESSES_MEDIAN_ADJUSTED,
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SCORES.ERROR_KURTOSIS
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)
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.from(SCORES)
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.where(SCORES.ADJUSTED_UR.lessOrEqual(256.0))
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.and(SCORES.SLIDEREND_RELEASE_STANDARD_DEVIATION_ADJUSTED.isNotNull)
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.and(SCORES.SLIDEREND_RELEASE_STANDARD_DEVIATION_ADJUSTED.lessOrEqual(16.0))
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.and(SCORES.IS_BANNED.isFalse)
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.and(SCORES.VERSION.greaterOrEqual(4))
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.and(SCORES.USER_ID.eq(userId))
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.fetchInto(ScoresRecord::class.java)
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reports.add(UserReport(userId = userId, username = username, userScores = userScores, susScore = susScore))
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if(areMetricsBlatant(userScores.map { mapScoreToMetrics(userDetails, it) }))
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continue
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val susScore = calculateSuspiciousnessScore(userScores.map { mapScoreToMetrics(userDetails, it) })
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val newReport = UserReport(
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userId = userId,
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username = username,
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userScores = userScores.map { mapScoreToMetrics(userDetails, it) },
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susScore = susScore.first,
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urgencyScore = susScore.second
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)
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reports.add(newReport)
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println(newReport)
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}
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reports.sortByDescending { it.susScore }
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println(reports)
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reports.sortByDescending { it.urgencyScore }
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}
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fun calculateSuspiciousnessScore(scores: List<ScoresRecord>): Double {
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if (scores.isEmpty()) return 0.0
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fun mapScoreToMetrics(user: UsersRecord, score: ScoresRecord): ScoreMetrics {
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return ScoreMetrics(
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date = score.date!!,
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country = user.country!!,
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pp = score.pp!!,
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adjustedUr = score.adjustedUr!!,
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sliderendReleaseStandardDeviationAdjusted = score.sliderendReleaseStandardDeviationAdjusted!!,
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edgeHits = score.edgeHits!!,
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snaps = score.snaps!!,
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keypressesMedianAdjusted = score.keypressesMedianAdjusted!!,
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errorKurtosis = score.errorKurtosis!!
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)
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}
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return scores.sumOf { score ->
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var suspiciousnessScore = 0.0
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data class ScoreMetrics(
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val date: LocalDateTime,
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val country: String,
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val pp: Double,
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val adjustedUr: Double,
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val sliderendReleaseStandardDeviationAdjusted: Double,
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val edgeHits: Int,
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val snaps: Int,
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val keypressesMedianAdjusted: Double,
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val errorKurtosis: Double
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)
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suspiciousnessScore += score.pp!! * 1.0
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val ppWeight = 1.0
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val urWeight = 2.0
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val sliderendReleaseWeight = 2.0
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val edgeHitsWeight = 2.0
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val snapsWeight = 2.0
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val keypressesWeight = 2.0
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val errorKurtosisWeight = 1.0
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val recencyBoost = 10.0
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val spreadBoost = 5.0
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suspiciousnessScore += if (score.adjustedUr!! < 6.0) 5.0 else 0.0
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fun areMetricsBlatant(metrics: List<ScoreMetrics>): Boolean {
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return metrics.map { it.adjustedUr }.average() < 24.0
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}
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suspiciousnessScore += if (score.sliderendReleaseStandardDeviationAdjusted!! < 6) 5.0 else 0.0
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fun calculateSuspiciousnessScore(scores: List<ScoreMetrics>): Pair<Double, Double> {
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if (scores.isEmpty()) return Pair(0.0, 0.0)
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suspiciousnessScore += when {
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score.edgeHits!! > 4 -> (score.edgeHits!! - 4) * 2.0
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val currentDate = LocalDateTime.now()
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val mostRecentScoreDate = scores.maxByOrNull { it.date }?.date ?: return Pair(0.0, 0.0)
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val daysSinceMostRecentScore = ChronoUnit.DAYS.between(mostRecentScoreDate, currentDate)
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val recencyScore = if (daysSinceMostRecentScore <= 30) recencyBoost else 0.0
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val dateSpread = scores.map { score -> ChronoUnit.MONTHS.between(score.date, currentDate) }.average()
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val spreadScore = if (dateSpread > 12) spreadBoost else 0.0
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val (suspiciousnessScore, ppTotal) = scores.fold(Pair(0.0, 0.0)) { acc, score ->
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var suspiciousness = acc.first
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var ppSum = acc.second
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suspiciousness += score.pp * ppWeight
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if (score.adjustedUr < 6.0) {
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suspiciousness += (6.0 - score.adjustedUr) * urWeight
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}
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if (score.sliderendReleaseStandardDeviationAdjusted < 6.0) {
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suspiciousness += (6.0 - score.sliderendReleaseStandardDeviationAdjusted) * sliderendReleaseWeight
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}
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suspiciousness += when {
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score.edgeHits > 4 -> (score.edgeHits - 4) * edgeHitsWeight
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else -> 0.0
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}
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suspiciousnessScore += when {
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score.snaps!! > 4 -> (score.snaps!! - 4) * 2.0
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suspiciousness += when {
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score.snaps > 4 -> (score.snaps - 4) * snapsWeight
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else -> 0.0
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}
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suspiciousnessScore += if (score.keypressesMedianAdjusted!! < 6) 5.0 else 0.0
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if (score.keypressesMedianAdjusted < 6) {
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suspiciousness += (6.0 - score.keypressesMedianAdjusted) * keypressesWeight
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}
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suspiciousnessScore += if (score.errorKurtosis!! < 6) 5.0 else 0.0
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if (score.errorKurtosis <= 0.0) {
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suspiciousness += (6.0 - score.errorKurtosis) * errorKurtosisWeight
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}
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suspiciousnessScore
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ppSum += score.pp
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Pair(suspiciousness, ppSum)
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}
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val averageSuspiciousnessScore = suspiciousnessScore / scores.size
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val urgencyScore = ppTotal / scores.size + recencyScore + spreadScore
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return Pair(averageSuspiciousnessScore, urgencyScore)
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}
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}
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@ -0,0 +1,28 @@
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package com.nisemoe.nise.scheduler
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import com.nisemoe.nise.database.UserService
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import com.nisemoe.nise.osu.OsuApi
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import com.nisemoe.nise.osu.TokenService
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import com.nisemoe.nise.service.CacheService
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import org.junit.jupiter.api.Test
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import org.springframework.beans.factory.annotation.Autowired
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import org.springframework.boot.test.context.SpringBootTest
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import org.springframework.boot.test.mock.mockito.MockBean
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import org.springframework.context.annotation.Import
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import org.springframework.test.context.ActiveProfiles
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@SpringBootTest
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@ActiveProfiles("postgres", "agent")
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@MockBean(GlobalCache::class, UserService::class)
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@Import(Agent::class, OsuApi::class, TokenService::class, CacheService::class)
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class AgentTest {
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@Autowired
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lateinit var agent: Agent
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@Test
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fun buildReports() {
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agent.buildReports()
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}
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}
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