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Deploy Aureon OS (deploy/selfhost stack: nginx edge + fusion API x2 + console + HNC organ + redis + postgres; paper mode) (part 18)
f568a4f verified | import { CoherenceDataPoint, DejaVuEvent, HistoricalDataPoint, NexusAnalysisResult } from '@/types'; | |
| const PATTERN_LENGTH = 4; | |
| const SIMILARITY_THRESHOLD = 0.005; // Sum of squared differences for a pattern match | |
| const SEARCH_BACK_DISTANCE = 60; // How many steps back to search for a match | |
| const COOLDOWN_PERIOD = 15; // Minimum steps between detected events | |
| // This function now analyzes the real-time coherence data stream for Déjà Vu events | |
| export const runAnalysis = ( | |
| realtimeData: CoherenceDataPoint[], | |
| historicalData: HistoricalDataPoint[] | |
| ): Omit<NexusAnalysisResult, 'report' | 'aureonData' | 'monitoringEvents'> => { | |
| const dejaVuEvents: DejaVuEvent[] = []; | |
| let lastEventTime = -Infinity; | |
| if (realtimeData.length >= PATTERN_LENGTH + 1) { | |
| // Iterate through the data, looking for repeating patterns | |
| for (let i = PATTERN_LENGTH; i < realtimeData.length - PATTERN_LENGTH; i++) { | |
| if (realtimeData[i].time < lastEventTime + COOLDOWN_PERIOD) continue; | |
| const currentPattern = realtimeData.slice(i, i + PATTERN_LENGTH).map(p => p.cognitiveCapacity); | |
| // Search for a matching pattern in the recent past | |
| const searchStart = Math.max(0, i - SEARCH_BACK_DISTANCE); | |
| for (let j = searchStart; j < i - PATTERN_LENGTH; j++) { | |
| const pastPattern = realtimeData.slice(j, j + PATTERN_LENGTH).map(p => p.cognitiveCapacity); | |
| // Calculate sum of squared differences to find a match | |
| const diff = currentPattern.reduce((sum, val, k) => sum + Math.pow(val - pastPattern[k], 2), 0); | |
| if (diff < SIMILARITY_THRESHOLD) { | |
| // To avoid clustering, check if this is a new event | |
| if (realtimeData[i].time > lastEventTime + COOLDOWN_PERIOD) { | |
| dejaVuEvents.push({ time: realtimeData[i].time, intensity: realtimeData[i].cognitiveCapacity }); | |
| lastEventTime = realtimeData[i].time; | |
| } | |
| break; | |
| } | |
| } | |
| } | |
| } | |
| return { realtimeData, historicalData, dejaVuEvents }; | |
| }; | |
| // This function is now repurposed to provide the historical data for the chart. | |
| // The term "Backtest" is kept to minimize changes in App.tsx, but it now represents a historical simulation. | |
| export const runBacktest = (historicalData: HistoricalDataPoint[]) => { | |
| // FIX: Add a guard to ensure historicalData is an array before mapping. | |
| // This prevents a crash if nexusResult is in an inconsistent state during a render. | |
| if (!Array.isArray(historicalData)) { | |
| return { | |
| performanceData: [], | |
| metrics: { | |
| finalReturn: 0, | |
| sharpeRatio: 0 | |
| } | |
| }; | |
| } | |
| return { | |
| performanceData: historicalData.map(d => ({ | |
| time: d.year, | |
| cumulativeReturn: d.cognitiveCapacity | |
| })), | |
| metrics: { | |
| finalReturn: historicalData.length > 0 ? historicalData[historicalData.length - 1].cognitiveCapacity : 0, | |
| sharpeRatio: 0 // Not applicable in this context | |
| } | |
| } | |
| } | |