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* TrcfDetector — wraps @beshu-tech/trcf-ts with attribution and drift detection.
*
* Supports both univariate and multivariate scenarios. Multivariate mode is
* auto-detected when DataPoint.dimensions is present AND non-empty.
*
* @module detect/trcf-detector
*/
import {
createTimeSeriesDetector,
createMultiVariateDetector,
} from '@beshu-tech/trcf-ts'
import type { AnomalyDetector } from '@beshu-tech/trcf-ts'
import type {
DataPoint,
DetectionResult,
DimensionAttribution,
IDetector,
} from '../types.js'
import { DimensionAttributor } from './attribution.js'
import { DriftDetector } from './drift.js'
export interface TrcfDetectorConfig {
windowSize: number
anomalyRate: number
numberOfTrees: number
normalize: boolean
attributionEnabled: boolean
driftEnabled: boolean
driftDetector: 'adwin' | 'kswin'
}
const DEFAULT_CONFIG: TrcfDetectorConfig = {
windowSize: 256,
anomalyRate: 0.005,
numberOfTrees: 30,
normalize: true,
attributionEnabled: true,
driftEnabled: true,
driftDetector: 'adwin',
}
export class TrcfDetector implements IDetector {
private detector: AnomalyDetector
private config: TrcfDetectorConfig
private attributor: DimensionAttributor | null
private driftDetector: DriftDetector | null
private dimensionNames: string[] = []
private isMultivariate = false
constructor(config?: Partial<TrcfDetectorConfig>) {
this.config = { ...DEFAULT_CONFIG, ...config }
const trcfConfig = {
anomalyRate: this.config.anomalyRate,
windowSize: this.config.windowSize,
numberOfTrees: this.config.numberOfTrees,
normalize: this.config.normalize,
}
this.detector = createTimeSeriesDetector(trcfConfig)
this.attributor = this.config.attributionEnabled ? new DimensionAttributor() : null
this.driftDetector = this.config.driftEnabled
? new DriftDetector(this.config.driftDetector)
: null
}
detect(point: DataPoint, _context: DataPoint[]): DetectionResult {
this.ensureDetectorType(point)
const inputArray = this.toInputArray(point)
const raw = this.detector.detect(inputArray, point.timestamp)
let driftDetected = false
let driftDetails = undefined
if (this.driftDetector) {
const driftResult = this.driftDetector.update(point.value)
driftDetected = driftResult.detected
driftDetails = driftResult.detected ? driftResult.info : undefined
}
// Compute attribution for multivariate only
const attribution = this.computeAttribution(point, inputArray, raw.score)
return {
isAnomaly: raw.isAnomaly,
grade: raw.grade,
score: raw.score,
threshold: raw.threshold,
confidence: raw.confidence,
attribution,
driftDetected,
driftDetails,
detectedAt: Date.now(),
}
}
getState(): Uint8Array {
const state = {
config: this.config,
isMultivariate: this.isMultivariate,
dimensionNames: this.dimensionNames,
trcfState: this.detector.getState(),
driftState: this.driftDetector?.getState() ?? null,
}
return new TextEncoder().encode(JSON.stringify(state))
}
setState(state: Uint8Array): void {
const parsed = JSON.parse(new TextDecoder().decode(state))
this.config = { ...DEFAULT_CONFIG, ...parsed.config }
this.isMultivariate = parsed.isMultivariate ?? false
this.dimensionNames = parsed.dimensionNames ?? []
this.attributor = this.config.attributionEnabled ? new DimensionAttributor() : null
this.recreateDetector()
this.driftDetector = this.config.driftEnabled
? (parsed.driftState ? DriftDetector.fromState(parsed.driftState) : new DriftDetector(this.config.driftDetector))
: null
}
reset(): void {
this.isMultivariate = false
this.dimensionNames = []
this.recreateDetector()
this.driftDetector?.reset()
this.attributor = this.config.attributionEnabled ? new DimensionAttributor() : null
}
private recreateDetector(): void {
const tc = {
anomalyRate: this.config.anomalyRate,
windowSize: this.config.windowSize,
numberOfTrees: this.config.numberOfTrees,
normalize: this.config.normalize,
}
if (this.isMultivariate && this.dimensionNames.length > 0) {
this.detector = createMultiVariateDetector({ ...tc, dimensions: this.dimensionNames.length } as any)
} else {
this.detector = createTimeSeriesDetector(tc)
}
}
private ensureDetectorType(point: DataPoint): void {
const dims = point.dimensions
const hasDims = dims !== undefined && Object.keys(dims).length > 0
if (hasDims && !this.isMultivariate) {
this.dimensionNames = Object.keys(dims)
this.isMultivariate = true
this.recreateDetector()
}
}
private toInputArray(point: DataPoint): number[] {
if (!this.isMultivariate || this.dimensionNames.length === 0) return [point.value]
return this.dimensionNames.map((name) => {
const val = point.dimensions?.[name]
return typeof val === 'number' && Number.isFinite(val) ? val : 0
})
}
private computeAttribution(
point: DataPoint,
inputArray: number[],
baselineScore: number
): DimensionAttribution[] {
if (!this.attributor || !this.isMultivariate) return []
return this.attributor.compute(
point,
[] as DataPoint[],
inputArray,
baselineScore,
(arr, ts) => this.detector.detect(arr, ts).score
)
}
}
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