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* Hocus → Pattern → Template Pipeline
* Enhanced with Ecosystem Codex Integration
*
* 6-Stage Reality Field Emergence System:
* 1. Pre-form (raw field + noise)
* 2. Feedback + Resonance (delay echo)
* 3. Mode Decomposition (waves → shapes)
* 4. Coherence Measurement (stable pattern check)
* 5. Template Activation (observer node recognition)
* 6. Dominant Template Selection
*
* + Ecosystem Enhancements from JSON codex files
*/
import { ecosystemEnhancements, FrequencyCodexEntry, AurisCodexEntry } from './ecosystemEnhancements';
export interface PipelineConfig {
// Stage 1: Pre-form
noiseAmplitude: number; // η amplitude
// Stage 2: Feedback
alpha: number; // feedback gain (0-1)
tau: number; // delay samples
// Stage 3: Modes
numModes: number; // number of eigenmodes to track
modeFrequencies: number[]; // φₖ base frequencies (Hz)
// Stage 4: Coherence
coherenceWindow: number; // Δ for autocorrelation
// Stage 5: Template
theta: number; // coherence threshold for activation
// Ecosystem enhancement
useCodexEnhancement: boolean;
}
export interface ModeState {
k: number; // mode index
frequency: number; // φₖ frequency
amplitude: number; // aₖ(t) current amplitude
phase: number; // current phase
lambda: number; // growth/decay rate
coherence: number; // Cₖ coherence metric
isTemplate: boolean; // Tₖ = 1 or 0
// Ecosystem enhancements
codexName?: string; // Name from frequency codex
harmonics?: number[]; // Harmonic series from codex
emotionalPhase?: string; // Emotional phase mapping
aurisBoost?: number; // Boost from Auris codex
}
export interface PipelineState {
timestamp: number;
// Stage 1: Raw field
rawField: number;
noise: number;
// Stage 2: Feedback field
feedbackField: number;
echoContribution: number;
// Stage 3-5: Mode states
modes: ModeState[];
// Stage 6: Dominant template
dominantMode: number; // k* = argmax Cₖ
dominantCoherence: number;
// Aggregate metrics
totalCoherence: number; // average across active templates
activeTemplates: number; // count of Tₖ = 1
pipelineStage: 'HOCUS' | 'PATTERN' | 'TEMPLATE';
// Ecosystem enhancement metrics
codexEnhanced: boolean;
dominantEmotionalPhase: string;
harmonicResonance: number;
}
const DEFAULT_CONFIG: PipelineConfig = {
noiseAmplitude: 0.1,
alpha: 0.3,
tau: 10,
numModes: 5,
modeFrequencies: [7.83, 14.1, 20.3, 528, 963], // Schumann + Love + Unity
coherenceWindow: 20,
theta: 0.7,
useCodexEnhancement: true
};
export class HocusPatternPipeline {
private config: PipelineConfig;
private fieldHistory: number[] = [];
private modeHistories: Map<number, number[]> = new Map();
private currentState: PipelineState | null = null;
private stepCount = 0;
private codexLoaded = false;
constructor(config: Partial<PipelineConfig> = {}) {
this.config = { ...DEFAULT_CONFIG, ...config };
this.initializeModeHistories();
this.loadCodexEnhancements();
}
/**
* Load ecosystem enhancements from JSON codex files
*/
private async loadCodexEnhancements(): Promise<void> {
if (!this.config.useCodexEnhancement) return;
try {
await ecosystemEnhancements.loadAll();
this.codexLoaded = ecosystemEnhancements.isLoaded();
// Enhance mode frequencies from codex
if (this.codexLoaded) {
this.enhanceModeFrequenciesFromCodex();
}
console.log('🔮 Pipeline codex enhancement:', this.codexLoaded ? 'ACTIVE' : 'PENDING');
} catch (error) {
console.warn('Pipeline codex enhancement failed:', error);
}
}
/**
* Enhance mode frequencies using frequency codex data
*/
private enhanceModeFrequenciesFromCodex(): void {
const enhancements = ecosystemEnhancements.getEnhancements();
if (enhancements.frequencyCodex.length > 0) {
// Add frequencies from codex that aren't already in config
const existingFreqs = new Set(this.config.modeFrequencies);
const codexFreqs = enhancements.frequencyCodex
.map(entry => entry.frequency)
.filter(f => !existingFreqs.has(f))
.slice(0, 3); // Add up to 3 new frequencies
if (codexFreqs.length > 0) {
this.config.modeFrequencies = [...this.config.modeFrequencies, ...codexFreqs];
this.config.numModes = this.config.modeFrequencies.length;
this.initializeModeHistories();
console.log('📊 Pipeline frequencies enhanced:', this.config.modeFrequencies);
}
}
}
private initializeModeHistories(): void {
for (let k = 0; k < this.config.numModes; k++) {
this.modeHistories.set(k, []);
}
}
/**
* Stage 1: Pre-form / "Hocus Pocus"
* x(t+Δt) = x(t) + F(x(t))Δt + η(t)
*/
private computePreform(currentField: number): { rawField: number; noise: number } {
// F(x) - internal dynamics (simple damping toward 0)
const F = -0.1 * currentField;
const dt = 1;
// η(t) - Deterministic noise based on field state (not Math.random)
// Use a hash of the current field and step count for reproducible noise
const seedVal = Math.abs((currentField * 1000 + this.stepCount) % 1);
const u1 = Math.max(0.0001, seedVal || 0.5);
const u2 = Math.max(0.0001, Math.abs((currentField * 7919 + this.stepCount * 13) % 1) || 0.3);
const noise = this.config.noiseAmplitude * Math.sqrt(-2 * Math.log(u1)) * Math.cos(2 * Math.PI * u2);
const rawField = currentField + F * dt + noise;
return { rawField, noise };
}
/**
* Stage 2: Feedback + Resonance
* x(t+Δt) = (1-α)x(t) + αx(t-τ) + η(t)
*/
private computeFeedback(rawField: number, noise: number): { feedbackField: number; echoContribution: number } {
const { alpha, tau } = this.config;
// Get delayed field value (echo)
const delayedField = this.fieldHistory.length >= tau
? this.fieldHistory[this.fieldHistory.length - tau]
: 0;
// Feedback equation
const echoContribution = alpha * delayedField;
const feedbackField = (1 - alpha) * rawField + echoContribution + noise * 0.5;
return { feedbackField, echoContribution };
}
/**
* Stage 3: Mode Decomposition (Enhanced with Ecosystem Codex)
* x(t) = Σₖ aₖ(t)φₖ
* daₖ/dt = λₖaₖ(t) + ξₖ(t)
*/
private decomposeIntoModes(field: number, t: number): ModeState[] {
const modes: ModeState[] = [];
for (let k = 0; k < this.config.numModes; k++) {
const freq = this.config.modeFrequencies[k];
// φₖ - basis function (sinusoidal eigenmode)
const phi = Math.sin(2 * Math.PI * freq * t / 1000);
// Project field onto mode: aₖ ≈ x · φₖ
const amplitude = field * phi;
// λₖ - growth rate (modes near resonance grow)
// Enhanced with codex boost
const { lambda, aurisBoost } = this.computeEnhancedGrowthRate(k, freq);
// ξₖ - projected noise (deterministic based on mode and step)
const xi = ((k * 7 + this.stepCount * 13) % 100 / 100 - 0.5) * 0.05;
// Update amplitude with dynamics
const history = this.modeHistories.get(k) || [];
const prevAmplitude = history.length > 0 ? history[history.length - 1] : 0;
const newAmplitude = prevAmplitude + lambda * prevAmplitude + xi + amplitude * 0.1;
// Store in history
history.push(newAmplitude);
if (history.length > 100) history.shift();
this.modeHistories.set(k, history);
// Compute coherence for this mode (Stage 4)
const coherence = this.computeModeCoherence(k);
// Template activation (Stage 5) - enhanced threshold from codex
const enhancedTheta = this.getEnhancedThreshold(freq);
const isTemplate = coherence >= enhancedTheta;
// Get codex enhancements for this mode
const { codexName, harmonics, emotionalPhase } = this.getCodexEnhancements(freq);
modes.push({
k,
frequency: freq,
amplitude: newAmplitude,
phase: (2 * Math.PI * freq * t / 1000) % (2 * Math.PI),
lambda,
coherence,
isTemplate,
codexName,
harmonics,
emotionalPhase,
aurisBoost
});
}
return modes;
}
/**
* Get codex enhancements for a frequency
*/
private getCodexEnhancements(freq: number): {
codexName: string;
harmonics: number[];
emotionalPhase: string
} {
if (!this.codexLoaded) {
return { codexName: 'Unknown', harmonics: [], emotionalPhase: 'neutral' };
}
const freqEnhancement = ecosystemEnhancements.getFrequencyEnhancement(freq);
const { harmonics: codexHarmonics, name } = ecosystemEnhancements.applyFrequencyHarmonics(freq);
// Map frequency to emotional phase
let emotionalPhase = 'neutral';
if (freq < 100) emotionalPhase = 'grounding';
else if (freq < 300) emotionalPhase = 'growth';
else if (freq < 600) emotionalPhase = 'love';
else emotionalPhase = 'transcendence';
return {
codexName: name || freqEnhancement?.name || 'Mode-' + Math.round(freq),
harmonics: codexHarmonics,
emotionalPhase
};
}
/**
* Get enhanced coherence threshold from codex
*/
private getEnhancedThreshold(freq: number): number {
if (!this.codexLoaded) return this.config.theta;
// Sacred frequencies get lower threshold (easier to activate)
const sacredFreqs = [7.83, 528, 963, 432];
const isSacred = sacredFreqs.some(sf => Math.abs(freq - sf) < 10);
return isSacred ? this.config.theta * 0.85 : this.config.theta;
}
/**
* Compute enhanced growth rate λₖ for mode k with Auris codex boost
* Modes that resonate with the system's natural frequencies grow
*/
private computeEnhancedGrowthRate(k: number, freq: number): { lambda: number; aurisBoost: number } {
// Base resonant frequencies grow (528 Hz Love frequency has highest growth)
const resonanceFreqs = [7.83, 528, 963];
let lambda = -0.01; // default decay
let aurisBoost = 1.0;
for (const resFreq of resonanceFreqs) {
const distance = Math.abs(freq - resFreq) / resFreq;
if (distance < 0.1) {
lambda = 0.05 * (1 - distance * 10); // grow if close to resonance
}
}
// Apply Auris codex enhancement
if (this.codexLoaded) {
const enhancements = ecosystemEnhancements.getEnhancements();
// Check if frequency matches any Auris node (with null check)
if (Array.isArray(enhancements.aurisCodex)) {
for (const aurisNode of enhancements.aurisCodex) {
if (aurisNode.frequency && Math.abs(freq - aurisNode.frequency) < 50) {
aurisBoost = ecosystemEnhancements.applyAurisBoost(aurisNode.name, 1.0);
lambda *= (1 + (aurisBoost - 1) * 0.5); // Apply weighted boost to growth
break;
}
}
}
// Symbolic compiler trigger check
const symbolic = ecosystemEnhancements.getSymbolicTriggers('BUY');
if (symbolic && freq >= 500 && freq <= 600) {
// Love frequency range gets extra boost from symbolic layer
lambda *= 1.15;
aurisBoost *= 1.1;
}
}
return { lambda, aurisBoost };
}
/**
* Stage 4: Pattern Coherence
* Cₖ = |⟨aₖ(t)aₖ*(t+Δ)⟩| / ⟨|aₖ(t)|²⟩
*/
private computeModeCoherence(k: number): number {
const history = this.modeHistories.get(k) || [];
const delta = Math.min(this.config.coherenceWindow, Math.floor(history.length / 2));
if (history.length < delta + 5) return 0;
// Compute autocorrelation
let numerator = 0;
let denominator = 0;
const n = history.length - delta;
for (let i = 0; i < n; i++) {
const a_t = history[i];
const a_tplusdelta = history[i + delta];
numerator += a_t * a_tplusdelta;
denominator += a_t * a_t;
}
if (denominator === 0) return 0;
// Coherence = |autocorrelation| normalized
const coherence = Math.abs(numerator / denominator);
return Math.min(1, Math.max(0, coherence));
}
/**
* Stage 6: Dominant Template Selection
* k* = argmax_k Cₖ
*/
private selectDominantTemplate(modes: ModeState[]): { dominantMode: number; dominantCoherence: number } {
let maxCoherence = 0;
let dominantMode = 0;
for (const mode of modes) {
if (mode.coherence > maxCoherence) {
maxCoherence = mode.coherence;
dominantMode = mode.k;
}
}
return { dominantMode, dominantCoherence: maxCoherence };
}
/**
* Determine pipeline stage based on system state
*/
private determinePipelineStage(modes: ModeState[]): 'HOCUS' | 'PATTERN' | 'TEMPLATE' {
const activeTemplates = modes.filter(m => m.isTemplate).length;
const avgCoherence = modes.reduce((sum, m) => sum + m.coherence, 0) / modes.length;
if (avgCoherence < 0.3) return 'HOCUS'; // Still noise
if (activeTemplates === 0) return 'PATTERN'; // Patterns forming
return 'TEMPLATE'; // Templates locked
}
/**
* Main pipeline step - runs all 6 stages with ecosystem enhancement
*/
public step(externalInput: number = 0): PipelineState {
this.stepCount++;
const t = this.stepCount;
// Get current field from history or start at 0
const currentField = this.fieldHistory.length > 0
? this.fieldHistory[this.fieldHistory.length - 1]
: 0;
// Stage 1: Pre-form
const { rawField, noise } = this.computePreform(currentField + externalInput);
// Stage 2: Feedback + Resonance
const { feedbackField, echoContribution } = this.computeFeedback(rawField, noise);
// Store in field history
this.fieldHistory.push(feedbackField);
if (this.fieldHistory.length > 200) this.fieldHistory.shift();
// Stage 3-5: Mode decomposition, coherence, template activation (enhanced)
const modes = this.decomposeIntoModes(feedbackField, t);
// Stage 6: Dominant template
const { dominantMode, dominantCoherence } = this.selectDominantTemplate(modes);
// Aggregate metrics
const activeTemplates = modes.filter(m => m.isTemplate).length;
const totalCoherence = activeTemplates > 0
? modes.filter(m => m.isTemplate).reduce((sum, m) => sum + m.coherence, 0) / activeTemplates
: 0;
const pipelineStage = this.determinePipelineStage(modes);
// Ecosystem enhancement metrics
const dominantEmotionalPhase = modes[dominantMode]?.emotionalPhase || 'neutral';
const harmonicResonance = this.computeHarmonicResonance(modes);
this.currentState = {
timestamp: Date.now(),
rawField,
noise,
feedbackField,
echoContribution,
modes,
dominantMode,
dominantCoherence,
totalCoherence,
activeTemplates,
pipelineStage,
codexEnhanced: this.codexLoaded,
dominantEmotionalPhase,
harmonicResonance
};
return this.currentState;
}
/**
* Compute harmonic resonance across all modes using codex harmonics
*/
private computeHarmonicResonance(modes: ModeState[]): number {
if (!this.codexLoaded || modes.length === 0) return 0;
let resonanceSum = 0;
let count = 0;
for (const mode of modes) {
if (mode.harmonics && mode.harmonics.length > 0) {
// Check how many harmonics are reinforcing
const harmonicStrength = mode.harmonics.reduce((sum, h, i) => {
return sum + h / (i + 1); // Weight earlier harmonics more
}, 0) / mode.harmonics.length;
resonanceSum += mode.coherence * harmonicStrength * (mode.aurisBoost || 1);
count++;
}
}
return count > 0 ? resonanceSum / count : 0;
}
public getState(): PipelineState | null {
return this.currentState;
}
public getFieldHistory(): number[] {
return [...this.fieldHistory];
}
public getModeHistory(k: number): number[] {
return [...(this.modeHistories.get(k) || [])];
}
public reset(): void {
this.fieldHistory = [];
this.modeHistories.clear();
this.initializeModeHistories();
this.currentState = null;
this.stepCount = 0;
}
}
// Singleton instance
export const hocusPatternPipeline = new HocusPatternPipeline();
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