287 lines
9.7 KiB
TypeScript
287 lines
9.7 KiB
TypeScript
import { Elysia, t } from "elysia"
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import { db } from "@/lib/db/index"
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import {
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games,
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gameVersions,
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performanceEntries,
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hardware,
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} from "@/lib/db/schema"
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import { eq, and, sql } from "drizzle-orm"
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export const gameStatsRoutes = new Elysia({ prefix: "/games" }).get(
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"/:gameId/stats",
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async ({ params, set }) => {
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const { gameId } = params
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// Verify game exists
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const [game] = await db
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.select({ id: games.id, steamAppId: games.steamAppId })
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.from(games)
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.where(eq(games.id, gameId))
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.limit(1)
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if (!game) {
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set.status = 404
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return { error: "Game not found" }
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}
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// ── 1. All non-removed entries with joins ──────────────────────
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const entries = await db
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.select({
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id: performanceEntries.id,
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hardwareSlug: performanceEntries.hardwareSlug,
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hardwareName: hardware.name,
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fpsAvg: performanceEntries.fpsAvg,
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fpsLow: performanceEntries.fpsLow,
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fpsHigh: performanceEntries.fpsHigh,
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fpsOnePercentLow: performanceEntries.fpsOnePercentLow,
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upscalerType: performanceEntries.upscalerType,
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upscalerVersion: performanceEntries.upscalerVersion,
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frameGenMethod: performanceEntries.frameGenMethod,
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protonVersion: performanceEntries.protonVersion,
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osVersion: performanceEntries.osVersion,
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upvotes: performanceEntries.upvotes,
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downvotes: performanceEntries.downvotes,
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verifiedAt: performanceEntries.verifiedAt,
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userNotes: performanceEntries.userNotes,
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createdAt: performanceEntries.createdAt,
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versionId: performanceEntries.versionId,
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})
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.from(performanceEntries)
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.innerJoin(
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gameVersions,
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eq(performanceEntries.versionId, gameVersions.id),
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)
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.innerJoin(hardware, eq(performanceEntries.hardwareSlug, hardware.slug))
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.where(
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and(
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eq(gameVersions.gameId, gameId),
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eq(performanceEntries.isRemoved, false),
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),
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)
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if (entries.length === 0) {
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return {
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summary: {
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totalEntries: 0,
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avgFps: null,
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bestDevice: null,
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verifiedCount: 0,
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versionCount: 0,
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},
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isRawPerformer: false,
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boxplot: [],
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historical: [],
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upscalerStats: [],
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fpsRange: [],
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deviceBreakdown: [],
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filterOptions: { protonVersions: [], osVersions: [] },
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}
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}
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// ── 2. Summary stats ──────────────────────────────────────────
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const totalEntries = entries.length
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const avgFps =
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entries.reduce((sum, e) => sum + (e.fpsAvg ?? 0), 0) / totalEntries
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const verifiedCount = entries.filter((e) => e.verifiedAt !== null).length
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// Best device by mean fpsAvg
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const deviceFpsMap = new Map<string, number[]>()
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for (const e of entries) {
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const arr = deviceFpsMap.get(e.hardwareSlug) || []
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arr.push(e.fpsAvg ?? 0)
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deviceFpsMap.set(e.hardwareSlug, arr)
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}
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let bestDevice: string | null = null
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let bestDeviceAvg = 0
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for (const [slug, fpsArr] of deviceFpsMap) {
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const mean = fpsArr.reduce((a, b) => a + b, 0) / fpsArr.length
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if (mean > bestDeviceAvg) {
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bestDeviceAvg = mean
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bestDevice = slug
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}
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}
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// Version count
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const [versionRow] = await db
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.select({ count: sql<number>`count(*)::int` })
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.from(gameVersions)
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.where(eq(gameVersions.gameId, gameId))
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const versionCount = versionRow?.count ?? 0
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// ── 3. Raw Performer check ────────────────────────────────────
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const isRawPerformer = entries.some(
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(e) =>
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(e.fpsAvg ?? 0) >= 60 &&
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e.upscalerType === "none" &&
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e.frameGenMethod === "none",
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)
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// ── 3b. Poor Performance check ─────────────────────────────────
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const isPoorPerformance = entries.some((e) => (e.fpsAvg ?? 0) < 30)
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// ── 4. Boxplot per device ─────────────────────────────────────
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const boxplotMap = new Map<
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string,
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{ hardwareName: string; values: number[] }
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>()
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for (const e of entries) {
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const existing = boxplotMap.get(e.hardwareSlug) || {
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hardwareName: e.hardwareName,
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values: [],
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}
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existing.values.push(e.fpsAvg ?? 0)
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boxplotMap.set(e.hardwareSlug, existing)
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}
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const boxplot = Array.from(boxplotMap.entries()).map(
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([slug, { hardwareName, values }]) => {
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const sorted = [...values].sort((a, b) => a - b)
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const n = sorted.length
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const q1Idx = Math.floor(n * 0.25)
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const medIdx = Math.floor(n * 0.5)
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const q3Idx = Math.floor(n * 0.75)
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const onePercentLow = sorted.length > 0 ? sorted[Math.max(0, Math.floor(sorted.length * 0.01))] : sorted[0]
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return {
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hardwareSlug: slug,
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hardwareName,
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min: sorted[0],
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q1: sorted[q1Idx],
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median: sorted[medIdx],
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onePercentLow,
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q3: sorted[q3Idx],
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max: sorted[n - 1],
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}
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},
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)
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// ── 5. Historical (group by month + device) ───────────────────
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const histMap = new Map<
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string,
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Map<string, { sum: number; count: number }>
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>()
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for (const e of entries) {
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const date = e.createdAt
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const month = `${date.getFullYear()}-${String(date.getMonth() + 1).padStart(2, "0")}`
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if (!histMap.has(month)) histMap.set(month, new Map())
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const deviceMap = histMap.get(month)!
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const existing = deviceMap.get(e.hardwareSlug) || {
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sum: 0,
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count: 0,
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}
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existing.sum += e.fpsAvg ?? 0
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existing.count++
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deviceMap.set(e.hardwareSlug, existing)
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}
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const historical = Array.from(histMap.entries())
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.sort(([a], [b]) => a.localeCompare(b))
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.map(([month, deviceMap]) => ({
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period: month,
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entries: Array.from(deviceMap.entries()).map(([slug, data]) => ({
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hardwareSlug: slug,
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avgFps: Math.round((data.sum / data.count) * 10) / 10,
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count: data.count,
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})),
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}))
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// ── 6. Upscaler/framegen stats ────────────────────────────────
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const upscalerMap = new Map<
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string,
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{ hardwareSlug: string; sum: number; count: number }
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>()
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for (const e of entries) {
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const key = `${e.upscalerType}|${e.upscalerVersion ?? ''}|${e.frameGenMethod}|${e.hardwareSlug}`
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const existing = upscalerMap.get(key) || {
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hardwareSlug: e.hardwareSlug,
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sum: 0,
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count: 0,
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}
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existing.sum += e.fpsAvg ?? 0
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existing.count++
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upscalerMap.set(key, existing)
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}
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const upscalerStats = Array.from(upscalerMap.entries()).map(
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([key, data]) => {
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const [upscalerType, upscalerVersion, frameGenMethod] = key.split("|")
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return {
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upscalerType,
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upscalerVersion: upscalerVersion || null,
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frameGenMethod,
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hardwareSlug: data.hardwareSlug,
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avgFps: Math.round((data.sum / data.count) * 10) / 10,
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count: data.count,
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}
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},
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)
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// ── 7. FPS range per entry ────────────────────────────────────
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const fpsRange = entries
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.filter((e) => e.fpsLow !== null && e.fpsHigh !== null)
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.map((e) => ({
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id: e.id,
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hardwareSlug: e.hardwareSlug,
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fpsLow: e.fpsLow!,
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fpsAvg: e.fpsAvg ?? 0,
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fpsHigh: e.fpsHigh!,
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fpsOnePercentLow: e.fpsOnePercentLow ?? null,
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isRawPerformer:
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(e.fpsAvg ?? 0) >= 60 &&
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e.upscalerType === "none" &&
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e.frameGenMethod === "none",
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isPoorPerformer: (e.fpsAvg ?? 0) < 30,
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}))
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// Stability score computation
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const stabilityScores = entries
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.filter(e => e.fpsOnePercentLow != null && (e.fpsAvg ?? 0) > 0)
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.map(e => Math.min(1, e.fpsOnePercentLow! / (e.fpsAvg ?? 1)))
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const avgStability = stabilityScores.length > 0
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? Math.round((stabilityScores.reduce((a, b) => a + b, 0) / stabilityScores.length) * 100) / 100
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: null
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const bestOnePercentLow = entries.reduce((best, e) =>
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e.fpsOnePercentLow != null && e.fpsOnePercentLow > (best ?? 0) ? e.fpsOnePercentLow : best, null as number | null)
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// ── 8. Device breakdown ───────────────────────────────────────
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const deviceBreakdown = Array.from(boxplotMap.entries()).map(
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([slug, { hardwareName, values }]) => ({
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hardwareSlug: slug,
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hardwareName,
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count: values.length,
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}),
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)
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// ── 9. Filter options ────────────────────────────────────────
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const protonVersions = [
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...new Set(entries.map((e) => e.protonVersion).filter(Boolean)),
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] as string[]
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const osVersions = [
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...new Set(entries.map((e) => e.osVersion).filter(Boolean)),
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] as string[]
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return {
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summary: {
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totalEntries,
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avgFps: Math.round(avgFps * 10) / 10,
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bestDevice,
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verifiedCount,
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versionCount,
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avgStability,
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bestOnePercentLow,
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},
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isRawPerformer,
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isPoorPerformance,
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boxplot,
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historical,
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upscalerStats,
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fpsRange,
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deviceBreakdown,
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filterOptions: { protonVersions, osVersions },
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}
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},
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{
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params: t.Object({ gameId: t.String() }),
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},
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)
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