UNPKG

@uor-foundation/operators

Version:

Layer 3: Arithmetic operators - operations as chemical reactions between numbers

151 lines 6.19 kB
"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); exports.DenormalizationEngine = void 0; const field_substrate_1 = require("@uor-foundation/field-substrate"); const carry_1 = require("./carry"); /** * Tracks and analyzes denormalization artifacts during arithmetic operations * These artifacts are the universe's way of creating/destroying information */ class DenormalizationEngine { constructor(substrate, resonance) { this.substrate = substrate; this.resonance = resonance; this.carryOperator = new carry_1.CarryOperator(substrate); } /** * Track artifacts during multiplication */ trackMultiplication(a, b) { const artifacts = this.carryOperator.analyzeArtifacts(a, b); const product = a * b; // Analyze field evolution const patternA = this.substrate.getFieldPattern(a); const patternB = this.substrate.getFieldPattern(b); const patternProduct = this.substrate.getFieldPattern(product); // Calculate resonance changes const resonanceA = this.resonance.calculateResonance(a); const resonanceB = this.resonance.calculateResonance(b); const resonanceProduct = this.resonance.calculateResonance(product); // Field statistics const vanishingFields = artifacts.filter((a) => a.type === 'vanishing'); const emergentFields = artifacts.filter((a) => a.type === 'emergent'); return { operands: { a: Number(a), b: Number(b) }, product: Number(product), artifacts, fieldEvolution: { before: { activeInA: patternA.filter(Boolean).length, activeInB: patternB.filter(Boolean).length, totalActive: this.countUniqueActiveFields(patternA, patternB), }, after: { activeInProduct: patternProduct.filter(Boolean).length, }, vanished: vanishingFields.length, emerged: emergentFields.length, }, resonanceEvolution: { before: { a: resonanceA, b: resonanceB }, after: resonanceProduct, energyChange: resonanceProduct - resonanceA * resonanceB, }, }; } /** * Predict artifacts for a multiplication without performing it */ predictArtifacts(a, b) { // This is a simplified prediction based on field patterns const patternA = this.substrate.getFieldPattern(a); const patternB = this.substrate.getFieldPattern(b); const predictions = []; // Analyze each field for (let i = 0; i < field_substrate_1.FIELD_COUNT; i++) { const activeInA = patternA[i]; const activeInB = patternB[i]; if (activeInA && activeInB) { // Both active - high chance of vanishing predictions.push({ field: i, likelihood: 0.7, type: 'vanishing', }); } else if (!activeInA && !activeInB) { // Both inactive - chance of emergence predictions.push({ field: i, likelihood: 0.3, type: 'emergent', }); } } return { operands: { a: Number(a), b: Number(b) }, predictions: predictions.sort((a, b) => b.likelihood - a.likelihood), }; } /** * Find multiplication pairs that produce specific artifacts */ findArtifactProducers(targetField, artifactType, searchRange) { const producers = []; // This is a simplified search - in practice would be optimized for (let a = searchRange.min; a <= searchRange.max; a++) { for (let b = a; b <= searchRange.max; b++) { const artifacts = this.carryOperator.analyzeArtifacts(a, b); const hasTargetArtifact = artifacts.some((art) => art.field === targetField && art.type === artifactType); if (hasTargetArtifact) { producers.push({ factors: [Number(a), Number(b)], product: Number(a * b), targetField, artifactType, }); } } } return producers; } /** * Analyze artifact patterns in a number sequence */ analyzeSequence(numbers) { const artifactCounts = new Map(); const fieldTransitions = new Map(); for (let i = 1; i < numbers.length; i++) { const artifacts = this.trackMultiplication(numbers[i - 1], numbers[i]); // Count artifact types artifacts.artifacts.forEach((art) => { const key = `${art.type}-${art.field}`; artifactCounts.set(key, (artifactCounts.get(key) ?? 0) + 1); }); // Track field transitions artifacts.artifacts.forEach((art) => { fieldTransitions.set(art.field, (fieldTransitions.get(art.field) ?? 0) + 1); }); } return { sequence: numbers.map((n) => Number(n)), totalArtifacts: Array.from(artifactCounts.values()).reduce((a, b) => a + b, 0), artifactDistribution: Object.fromEntries(artifactCounts), mostActiveField: Array.from(fieldTransitions.entries()).sort((a, b) => b[1] - a[1])[0]?.[0] || -1, averageArtifactsPerOperation: Array.from(artifactCounts.values()).reduce((a, b) => a + b, 0) / (numbers.length - 1), }; } /** * Count unique active fields across patterns */ countUniqueActiveFields(patternA, patternB) { let count = 0; for (let i = 0; i < field_substrate_1.FIELD_COUNT; i++) { if (patternA[i] || patternB[i]) count++; } return count; } } exports.DenormalizationEngine = DenormalizationEngine; //# sourceMappingURL=denormalization.js.map