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Author SHA1 Message Date
5d8320fe8a fix/mathc_collector: fix splitting of boots and first backs
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2026-04-30 20:15:44 +02:00
c7d0d929be fix/match_collector: change region tagging logic 2026-04-30 17:51:14 +02:00
8ee981b949 fix: fix cdragon cache directory 2026-04-30 16:31:25 +02:00
5 changed files with 74 additions and 21 deletions

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@@ -9,13 +9,18 @@ const readFileAsync = promisify(readFile)
const CDRAGON_BASE = 'https://raw.communitydragon.org/'
// Cache directory - can be configured via environment variable
// Default to dev/cdragon for development
// In development, use dev/data/cdragon relative to project root
// In production, use /cdragon (shared volume)
const getCacheDir = () => {
if (process.env.CDRAGON_CACHE_DIR) {
return process.env.CDRAGON_CACHE_DIR
}
// Default to dev/cdragon relative to project root
return join(process.cwd(), '..', 'dev', 'data', 'cdragon')
// Check if we're in development mode (explicitly set)
if (process.env.NODE_ENV === 'development') {
return join(process.cwd(), '..', 'dev', 'data', 'cdragon')
}
// Default to /cdragon for production (Docker)
return '/cdragon'
}
/**

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@@ -46,7 +46,8 @@ async function downloadCDragonAssets(patch: string) {
console.log(`\n=== Downloading CDragon assets for patch ${cdragonPatch} ===`)
// Get cache directory from environment or use default
// In development, use a local directory relative to project root; in production (Docker), use /cdragon
// In development, use a local directory relative to project root
// In production (Docker), use /cdragon (shared volume with frontend)
const defaultCacheDir =
process.env.NODE_ENV === 'development'
? resolve(__dirname, '../../dev/data/cdragon')

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@@ -177,7 +177,7 @@ function handleMatchBuilds(
participantIndex: number,
builds: Builds,
platform?: string
): Build {
): { build: Build; startItemId: number | undefined } {
const timeline: Timeline = match.timeline
// Find or create the build for this participant's rune configuration
@@ -185,6 +185,7 @@ function handleMatchBuilds(
build.count += 1
const items: Array<{ itemId: number; goldAdvantage: GoldAdvantageTag; platform?: string }> = []
let startItemId: number | undefined = undefined
for (const frame of timeline.info.frames) {
for (const event of frame.events) {
if (event.participantId != participantIndex) continue
@@ -267,9 +268,11 @@ function handleMatchBuilds(
// This tree includes start item as the root, then branching paths
if (items.length > 0) {
treeMerge(build.items, items)
// The first item is the starter item
startItemId = items[0].itemId
}
return build
return { build, startItemId }
}
function handleMatch(match: Match, champions: Map<number, ChampionData>, platform?: string) {
@@ -365,14 +368,22 @@ function handleMatch(match: Match, champions: Map<number, ChampionData>, platfor
}
// Items and runes (builds)
const build = handleMatchBuilds(match, participant, participantIndex, lane.builds, platform)
const { build, startItemId } = handleMatchBuilds(
match,
participant,
participantIndex,
lane.builds,
platform
)
// First back data - store at build level
// First back data - store at build level with start item tracking
const firstBackData = extractFirstBackFromMatch(match, participantIndex)
if (firstBackData) {
if (!build.firstBacksRaw) {
build.firstBacksRaw = []
}
// Include the starter item ID for proper filtering when splitting builds
firstBackData.startItemId = startItemId
build.firstBacksRaw.push(firstBackData)
}
}
@@ -445,16 +456,44 @@ function splitMergeOnStarterItem(build: Build, championName: string): BuildWithS
console.log(`Warning: for champion ${championName}, start item splits build variant.`)
const builds = []
for (const c of build.items.children) {
// Calculate the ratio for proportional distribution
const ratio = c.count / build.count
// Proportionally distribute boots counts
const scaledBoots = build.boots.map(b => ({
data: b.data,
count: Math.round(b.count * ratio)
}))
// Proportionally distribute suppItems counts
const scaledSuppItems = build.suppItems.map(s => ({
data: s.data,
count: Math.round(s.count * ratio)
}))
// Proportionally distribute bootsFirstCount
const scaledBootsFirstCount = Math.round(build.bootsFirstCount * ratio)
// Filter firstBacksRaw by starter item
let filteredFirstBacksRaw: FirstBackData[] | undefined
if (build.firstBacksRaw && build.firstBacksRaw.length > 0) {
// Filter by the starter item ID that was tracked when storing firstBacksRaw
filteredFirstBacksRaw = build.firstBacksRaw.filter(fb => fb.startItemId === c.data)
if (filteredFirstBacksRaw.length === 0) {
filteredFirstBacksRaw = undefined
}
}
builds.push({
runeKeystone: build.runeKeystone,
runes: build.runes,
items: c,
bootsFirstCount: build.bootsFirstCount,
bootsFirstCount: scaledBootsFirstCount,
count: c.count,
startItems: [{ data: c.data!, count: c.count }],
suppItems: build.suppItems,
boots: build.boots,
firstBacksRaw: build.firstBacksRaw
suppItems: scaledSuppItems,
boots: scaledBoots,
firstBacksRaw: filteredFirstBacksRaw
})
c.data = undefined
}

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@@ -264,12 +264,8 @@ function deriveTags(node: ItemTree, expectedRegionDistribution?: PlatformCounts)
const totalExpected = REGION_KEYS.reduce((sum, key) => sum + expectedRegionDistribution[key], 0)
if (totalExpected > 0) {
// Tag if the item is significantly more popular in a region (>= 1.5x expected rate)
// and has a minimum absolute percentage (>= 10%)
const SIGNIFICANCE_THRESHOLD = 1.5
const MINIMUM_PCT = 0.1
// Loop through all regions to derive tags
// Tag if one region accounts for >= 60% of the normalized distribution
// Normalized value = actual percentage / expected percentage ratio
const regionTags: Array<{ key: keyof PlatformCounts; tag: ItemTag }> = [
{ key: 'euw', tag: 'region_euw' },
{ key: 'eun', tag: 'region_eun' },
@@ -277,12 +273,23 @@ function deriveTags(node: ItemTree, expectedRegionDistribution?: PlatformCounts)
{ key: 'kr', tag: 'region_kr' }
]
for (const { key, tag } of regionTags) {
// Calculate normalized values (actual/expected ratio) for each region
const normalizedValues = regionTags.map(({ key, tag }) => {
const expectedPct = expectedRegionDistribution[key] / totalExpected
const actualPct = node.platformCount[key] / totalRegionCount
const normalizedValue = expectedPct > 0 ? actualPct / expectedPct : 0
return { tag, value: normalizedValue }
})
if (actualPct >= expectedPct * SIGNIFICANCE_THRESHOLD && actualPct >= MINIMUM_PCT) {
tags.push(tag)
const totalNormalized = normalizedValues.reduce((sum, { value }) => sum + value, 0)
// Tag the region if it accounts for >= 60% of the normalized distribution
if (totalNormalized > 0) {
for (const { tag, value } of normalizedValues) {
if (value / totalNormalized >= 0.6) {
tags.push(tag)
break // Only tag the most dominant region
}
}
}
}

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@@ -82,6 +82,7 @@ export interface ItemSet {
export interface FirstBackData {
timestamp: number
itemSet: ItemSet
startItemId?: number
}
/**