Merge remote-tracking branch 'origin/ScalaEvaluator'
* origin/ScalaEvaluator: Allow games with 40 turns UI and determinations Weigh positive matches more heavily UI, Mark/Report Conds. and DateTime entry Update scalachess Improve display of report card
This commit is contained in:
Thibault Duplessis
commit
cfccb2f455
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@ -12,6 +12,7 @@ import lila.rating.PerfType
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import lila.security.Permission
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import lila.user.tube.userTube
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import lila.user.{ User => UserModel, UserRepo }
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import lila.evaluation.PlayerAggregateAssessment
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import views._
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object User extends LilaController {
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@ -147,7 +148,7 @@ object User extends LilaController {
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def mod(username: String) = Secure(_.UserSpy) { implicit ctx =>
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me => OptionFuOk(UserRepo named username) { user =>
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(Env.evaluation.evaluator find user) zip (Env.security userSpy user.id) zip (Env.mod.assessApi.getResultsByUserId(user.id, 25)) map {
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case ((eval, spy), gameResults) => html.user.mod(user, spy, eval, gameResults)
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case ((eval, spy), gameResults) => html.user.mod(user, spy, eval, PlayerAggregateAssessment(gameResults))
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}
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}
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}
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@ -2,7 +2,7 @@
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@(game: Game, results: GameResults)(implicit ctx: Context)
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<br />
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@if(isGranted(_.MarkEngine) && game.analysable && !game.isCorrespondence && game.turns > 40) {
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@if(isGranted(_.MarkEngine) && game.analysable && !game.isCorrespondence && game.turns >= 40) {
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@game.players.map { p =>
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<table class="modAssessment">
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<tr>
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@ -1,4 +1,6 @@
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@(u: User, spy: lila.security.UserSpy, eval: Option[lila.evaluation.Evaluation], gameResults: List[lila.evaluation.GameGroupResult])(implicit ctx: Context)
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@(u: User, spy: lila.security.UserSpy, eval: Option[lila.evaluation.Evaluation], aggregateAssessment: lila.evaluation.PlayerAggregateAssessment)(implicit ctx: Context)
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@import lila.evaluation.Display
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<div class="actions clearfix">
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@if(isGranted(_.UserEvaluate)) {
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@ -75,9 +77,52 @@
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}
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</div>
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}
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@if(gameResults.nonEmpty) {
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<div class="evaluation">
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<table class="slist hint--top">
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@if(aggregateAssessment.gameGroupResults.nonEmpty) {
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<div class="evaluation results">
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<table class="reportCard">
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<thead>
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<tr>
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<th>
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<span class="@(if(aggregateAssessment.markPri) "mark" else "noMark")">Cheating</span>
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</th>
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<th>
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<span class="@(if(aggregateAssessment.markSec) "mark" else "noMark")">Cheating</span>
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</th>
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<th>
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<span class="@(if(aggregateAssessment.reportPri) "report" else "noReport")">Report</span>
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</th>
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<th>
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<span class="@(if(aggregateAssessment.reportSec) "report" else "noReport")">Report</span>
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</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>
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<span class="sig_5">@aggregateAssessment.cheatingSum</span> / 2
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</td>
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<td>
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<span class="sig_5">@aggregateAssessment.cheatingSum</span> +
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<span class="sig_4">@aggregateAssessment.likelyCheatingSum</span> / 4
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</td>
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<td>
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<span class="sig_5">@aggregateAssessment.cheatingSum</span> +
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<span class="sig_4">@aggregateAssessment.likelyCheatingSum</span> / 2
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</td>
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<td>
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<span class="sig_5">@aggregateAssessment.cheatingSum</span> +
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<span class="sig_4">@aggregateAssessment.likelyCheatingSum</span> +
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<span class="sig_3">@aggregateAssessment.unclearSum</span> / 4
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</td>
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</tr>
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</tbody>
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</table>
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<p class="legend">
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@Range(1, 6).map { i =>
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<span class="sig_@i">@Display.assessmentString(i)</span>
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}
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</p>
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<table class="slist">
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<thead>
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<tr>
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<th>Assessed game</th>
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@ -91,15 +136,16 @@
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</th>
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<th>Blurs</th>
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<th>Bot</th>
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<th><span data-hint="Primary match">1</span></th>
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<th><span data-hint="Secondary match">2</span></th>
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<th><span data-hint="Tertiary match">3</span></th>
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<th><span data-hint="Quaternary match">4</span></th>
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<th><span data-hint="Quinary match">5</span></th>
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<th><span class="hint--top-left" data-hint="Aggregate match">Σ</span></th>
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<th><span class="hint--top-left" data-hint="Primary match">1</span></th>
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<th><span class="hint--top-left" data-hint="Secondary match">2</span></th>
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<th><span class="hint--top-left" data-hint="Tertiary match">3</span></th>
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<th><span class="hint--top-left" data-hint="Quaternary match">4</span></th>
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<th><span class="hint--top-left" data-hint="Quinary match">5</span></th>
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</tr>
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</thead>
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<tbody>
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@gameResults.map { result =>
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@aggregateAssessment.gameGroupResults.map { result =>
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<tr>
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<td><a href="@routes.Round.watcher(result.gameId, result.color.name)">@routes.Round.watcher(result.gameId, result.color.name)</a></td>
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<td>@result.sfAvg ± @result.sfSd</td>
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@ -107,18 +153,23 @@
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<td>@(result.blur)%</td>
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<td>@if(result.hold){Yes} else {No}</td>
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<td>
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<a href="@routes.Round.watcher(result.bestMatch.gameId, result.bestMatch.color.name)" class="peerLink hint--top" data-hint="@result.bestMatch.explanation">
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<span class="assessment sig_@(result.bestMatch.assessment)">@result.bestMatch.assessmentString</span>
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<br /><span class="@if(result.bestMatch.positiveMatch) {match} else {partial}">@(result.bestMatch.matchPercentage)%</span>
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<span class="aggregate hint--top-left" data-hint="@result.aggregate.explanation">
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<span class="sig_@(result.aggregate.assessment)" data-icon="@Display.dataIcon(result.aggregate)"></span>
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</span>
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</td>
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<td>
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<a href="@routes.Round.watcher(result.bestMatch.gameId, result.bestMatch.color.name)" class="peerLink hint--top-left" data-hint="@result.bestMatch.explanation">
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<span class="sig_@(result.bestMatch.assessment)" data-icon="@Display.dataIcon(result.bestMatch)"> </span>
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<br /><span class="percentage">@(result.bestMatch.matchPercentage)%</span>
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</a>
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</td>
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@Range(0, 4).map { i =>
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@result.secondaryMatches.lift(i) match {
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case Some(peer) => {
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<td>
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<a href="@routes.Round.watcher(peer.gameId, peer.color.name)" class="peerLink hint--top" data-hint="@peer.explanation">
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<span class="assessment sig_@(peer.assessment)">@peer.assessmentString</span>
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<br /><span class="@if(peer.positiveMatch) {match} else {partial}">@(peer.matchPercentage)%</span>
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<a href="@routes.Round.watcher(peer.gameId, peer.color.name)" class="peerLink hint--top-left" data-hint="@peer.explanation">
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<span class="sig_@(peer.assessment)" data-icon="@Display.dataIcon(peer)"></span>
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<br /><span class="percentage">@(peer.matchPercentage)%</span>
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</a>
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</td>
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}
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@ -1,6 +1,6 @@
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package lila.evaluation
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import Math.{pow, E, PI, log, sqrt, abs, exp}
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import Math.{pow, E, PI, log, sqrt, abs, exp, round}
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import org.joda.time.DateTime
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import scalaz.NonEmptyList
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import chess.{ Color }
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@ -26,16 +26,6 @@ case class PeerGame(
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) {
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val color = Color(white)
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val assessmentString: String =
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assessment match {
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case 1 => "NC" // Not cheating
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case 2 => "UC" // Unlikely Cheating
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case 3 => "NA" // Unclear
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case 4 => "LC" // Likely Cheating
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case 5 => "CH" // Cheating
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case _ => "Undef"
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}
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val explanation: String =
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(if (positiveMatch) "Matches " else "Partially matches ") + "with " +
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(assessment match {
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@ -48,6 +38,43 @@ case class PeerGame(
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}) + " game at " + matchPercentage + "% confidence"
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}
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case class PlayerAggregateAssessment(
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gameGroupResults: List[GameGroupResult]
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) {
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import Statistics.listSum
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def sumAssessment(x: Int): Int =
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listSum(gameGroupResults.map { result =>
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if (result.aggregate.assessment == x && (result.aggregate.positiveMatch || result.aggregate.confidence > 80)) 1
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else 0
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})
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val cheatingSum: Int = sumAssessment(5)
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val likelyCheatingSum: Int = sumAssessment(4)
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val unclearSum: Int = sumAssessment(3)
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val markPri: Boolean = cheatingSum >= 2
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val markSec: Boolean = cheatingSum + likelyCheatingSum >= 4
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val reportPri: Boolean = cheatingSum + likelyCheatingSum >= 2
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val reportSec: Boolean = cheatingSum + likelyCheatingSum + unclearSum >= 4
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}
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case class AggregateAssessment(
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assessment: Int,
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confidence: Int,
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positiveMatch: Boolean
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) {
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val explanation: String =
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(if (positiveMatch) "Matches " else "Partially matches ") +
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(assessment match {
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case 1 => "Not Cheating"
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case 2 => "Unlikely Cheating"
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case 3 => "Unclear"
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case 4 => "Likely Cheating"
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case 5 => "Cheating"
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case _ => "Undefined"
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}) + " at " + confidence + "% confidence"
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}
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case class GameGroupResult(
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_id: String, // sourceGameId + "/" + sourceGameColor
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userId: String, // The userId of the player being evaluated
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@ -55,6 +82,7 @@ case class GameGroupResult(
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white: Boolean, // The side of the game being talked about
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bestMatch: PeerGame,
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secondaryMatches: List[PeerGame],
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date: DateTime,
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// Meta infos
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sfAvg: Int,
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sfSd: Int,
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@ -63,9 +91,48 @@ case class GameGroupResult(
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blur: Int,
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hold: Boolean
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) {
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import Statistics.{listSum, listAverage}
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val color = Color(white)
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val aggregate: AggregateAssessment = {
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val peers = bestMatch :: secondaryMatches
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AggregateAssessment(
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round(listSum(peers.map {
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case a if (a.positiveMatch) => 4 * a.matchPercentage * a.assessment
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case a => a.matchPercentage * a.assessment
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}).toDouble / listSum(peers.map {
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case a if (a.positiveMatch) => 4 * a.matchPercentage
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case a => a.matchPercentage
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})).toInt,
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bestMatch.matchPercentage,
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peers.exists(_.positiveMatch)
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)
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}
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}
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object Display {
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def assessmentString(x: Int): String =
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x match {
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case 1 => "Not Cheating" // Not cheating
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case 2 => "Unlikely Cheating" // Unlikely Cheating
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case 3 => "Unclear" // Unclear
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case 4 => "Likely Cheating" // Likely Cheating
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case 5 => "Cheating" // Cheating
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case _ => "Undef"
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}
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def dataIcon(positiveMatch: Boolean, confidence: Int): String = {
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(positiveMatch, confidence) match {
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case (true, _) => "J"
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case (_, a) if (a >= 80) => "l"
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case _ => "K"
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}
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}
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def dataIcon(x: AggregateAssessment): String = dataIcon(x.positiveMatch, x.confidence)
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def dataIcon(x: PeerGame): String = dataIcon(x.positiveMatch, x.matchPercentage)
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}
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case class GameResults(
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white: Option[GameGroupResult],
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black: Option[GameGroupResult]
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@ -100,17 +167,18 @@ case class GameGroup(analysed: Analysed, color: Color, assessment: Option[Int] =
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def groupedDiffList(game: Game, color: Color, analysis: Analysis, size: Int = 5): List[List[Int]] =
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Accuracy.diffsList(Pov(game, color), analysis).grouped(size).toList
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// Insist that is greater than this (so this can be compared in full saturation)
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if (that.analysed.game.turns < this.analysed.game.turns) return (Similarity(0), Similarity(0))
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val thisPlayerDiffs = groupedDiffList(this.analysed.game, this.color, this.analysed.analysis)
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val thatPlayerDiffs = groupedDiffList(that.analysed.game, that.color, that.analysed.analysis)
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if (thisPlayerDiffs.size != thatPlayerDiffs.size) return (Similarity(0), Similarity(0))
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else {
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(
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(groupedDiffList(this.analysed.game, this.color, this.analysed.analysis) zip
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groupedDiffList(that.analysed.game, that.color, that.analysed.analysis)) map {
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thisPlayerDiffs zip thatPlayerDiffs map {
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a => listToListSimilarity(a._1, a._2, 0.8)
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}
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,
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(groupedDiffList(this.analysed.game, !this.color, this.analysed.analysis) zip
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groupedDiffList(that.analysed.game, !that.color, that.analysed.analysis)) map {
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a => listToListSimilarity(a._1, a._2, 0.8)
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a => listToListSimilarity(a._1, a._2, 0.6)
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}
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) match {
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case (Nil, Nil) => (Similarity(0), Similarity(0)) // Both empty
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@ -266,6 +334,12 @@ object Statistics {
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def skip[A](l: List[A], n: Int) =
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l.zipWithIndex.collect {case (e,i) if ((i+n) % 2) == 0 => e} // (i+1) because zipWithIndex is 0-based
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def listSum(xs: List[Int]): Int = xs match {
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case Nil => 0
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case x :: tail => x + listSum(tail)
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}
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def listAverage[T](x: List[T])(implicit n: Numeric[T]): Double = x match {
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case Nil => 0
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case a :: Nil => n.toDouble(a)
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|
|
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|
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@ -6,6 +6,7 @@ import lila.db.BSON.BSONJodaDateTimeHandler
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import lila.evaluation.{ PlayerAssessment, GameGroupResult, GameResults, GameGroup, Analysed, PeerGame, MatchAndSig }
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import lila.game.Game
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import lila.game.{ Game, GameRepo }
|
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import org.joda.time.DateTime
|
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import reactivemongo.bson._
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import scala.concurrent._
|
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|
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@ -55,7 +56,7 @@ final class AssessApi(collRef: Coll, collRes: Coll, logApi: ModlogApi) {
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def onAnalysisReady(game: Game, analysis: Analysis): Funit = {
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def playerAssessmentGameGroups: Fu[List[GameGroup]] =
|
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getPlayerAssessments(200) flatMap { assessments =>
|
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getPlayerAssessments(400) flatMap { assessments =>
|
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GameRepo.gameOptions(assessments.map(_.gameId)) flatMap { games =>
|
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AnalysisRepo.doneByIds(assessments.map(_.gameId)) map { analyses =>
|
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assessments zip games zip analyses flatMap {
|
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|
|
@ -86,6 +87,7 @@ final class AssessApi(collRef: Coll, collRes: Coll, logApi: ModlogApi) {
|
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white = source.color.white,
|
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bestMatch = a,
|
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secondaryMatches = b,
|
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date = DateTime.now,
|
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sfAvg = source.sfAvg,
|
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sfSd = source.sfSd,
|
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mtAvg = source.mtAvg,
|
||||
|
|
@ -96,7 +98,7 @@ final class AssessApi(collRef: Coll, collRes: Coll, logApi: ModlogApi) {
|
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case _ => None
|
||||
}
|
||||
|
||||
if (!game.isCorrespondence && game.turns > 40 && game.mode.rated) {
|
||||
if (!game.isCorrespondence && game.turns >= 40 && game.mode.rated) {
|
||||
val whiteGameGroup = GameGroup(Analysed(game, analysis), Color.White)
|
||||
val blackGameGroup = GameGroup(Analysed(game, analysis), Color.Black)
|
||||
|
||||
|
|
|
|||
|
|
@ -228,32 +228,37 @@ div.user_show .evaluation strong {
|
|||
display: inline;
|
||||
text-transform: uppercase;
|
||||
}
|
||||
div.user_show .evaluation .assessment {
|
||||
text-align: right;
|
||||
div.user_show .evaluation .percentage {
|
||||
font-size: 0.9em;
|
||||
}
|
||||
div.user_show .evaluation .legend {
|
||||
text-align: center;
|
||||
font-weight: bold;
|
||||
margin-bottom: 10px;
|
||||
}
|
||||
div.user_show .evaluation .legend span {
|
||||
padding: 10px;
|
||||
}
|
||||
div.user_show .evaluation .sig_1 {
|
||||
color: #99d531;
|
||||
color: #388922; /* green */
|
||||
}
|
||||
div.user_show .evaluation .sig_2 {
|
||||
color: #b8d531;
|
||||
color: #83ab23; /* appricot */
|
||||
}
|
||||
div.user_show .evaluation .sig_3 {
|
||||
color: #d3d531;
|
||||
color: #B8AA1A; /* yellow */
|
||||
}
|
||||
div.user_show .evaluation .sig_4 {
|
||||
font-weight: bold;
|
||||
color: #d59931;
|
||||
color: #C36A2A; /* orange */
|
||||
}
|
||||
div.user_show .evaluation .sig_5 {
|
||||
font-weight: bold;
|
||||
color: #de6039;
|
||||
color: #dc322f; /* red */
|
||||
}
|
||||
div.user_show .evaluation .match {
|
||||
font-weight: bold;
|
||||
color: #759900;
|
||||
}
|
||||
div.user_show .evaluation .partial {
|
||||
color: #d59120;
|
||||
}
|
||||
div.user_show div.content_box_inter.tabs {
|
||||
margin-left: -8px;
|
||||
|
|
@ -265,5 +270,42 @@ div.user_show #crosstable {
|
|||
margin: 25px auto 15px auto;
|
||||
}
|
||||
div.user_show .evaluation .peerLink {
|
||||
text-align: center;
|
||||
text-decoration: none;
|
||||
}
|
||||
div.user_show .results table.slist th {
|
||||
text-align: center;
|
||||
}
|
||||
div.user_show .results table.slist td {
|
||||
text-align: center;
|
||||
}
|
||||
div.user_show .reportCard {
|
||||
margin: 0 auto 10px auto;
|
||||
}
|
||||
div.user_show .reportCard th {
|
||||
text-align: center;
|
||||
font-weight: bold;
|
||||
font-size: 2em;
|
||||
padding: 0 20px 5px 20px;
|
||||
}
|
||||
div.user_show .reportCard td {
|
||||
text-align: center;
|
||||
font-weight: bold;
|
||||
font-size: 1.2em;
|
||||
}
|
||||
div.user_show .results .aggregate {
|
||||
font-size: 2.2em;
|
||||
margin-top: -5px;
|
||||
}
|
||||
div.user_show .reportCard .mark {
|
||||
color: #dc322f; /* red */
|
||||
}
|
||||
div.user_show .reportCard .noMark {
|
||||
/*color: #dc322f;*/ /* red */
|
||||
}
|
||||
div.user_show .reportCard .report {
|
||||
color: #B8AA1A; /* red */
|
||||
}
|
||||
div.user_show .reportCard .noReport {
|
||||
/*color: #dc322f;*/ /* red */
|
||||
}
|
||||
Loading…
Reference in a new issue