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feat: refine difficulty calculation and update simulation data

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Grzegorz Kucmierz
2026-02-12 18:51:00 +01:00
parent 27270d6452
commit 934b2a0483
3 changed files with 59 additions and 82 deletions
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71
scripts/simulate_difficulty.js
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@@ -1,75 +1,38 @@
import fs from 'fs';
import path from 'path';
import { generateRandomGrid, calculateHints } from '../src/utils/puzzleUtils.js';
import { solvePuzzle } from '../src/utils/solver.js';
const OUTPUT_FILE = 'difficulty_simulation_results.json';
const CSV_FILE = 'difficulty_simulation_results.csv';
// Configuration
const SIZES = [5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80]; // Steps of 5 up to 50, then 10
const SIZES = [5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80];
const DENSITIES = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9];
const SAMPLES_PER_POINT = 20; // Adjust based on time/accuracy needs
const SAMPLES_SMALL = 100; // For size <= 25
const SAMPLES_LARGE = 30; // For size > 25
console.log('Starting Monte Carlo Simulation for Nonogram Difficulty...');
console.log(`Config: Sizes=${SIZES.length}, Densities=${DENSITIES.length}, Samples=${SAMPLES_PER_POINT}`);
const results = {};
const results = [];
const csvRows = ['size,density,avg_solved_percent,min_solved_percent,max_solved_percent,avg_time_ms'];
console.log('Starting Monte Carlo Simulation...');
const startTime = Date.now();
for (const size of SIZES) {
const samples = size <= 25 ? SAMPLES_SMALL : SAMPLES_LARGE;
const rowData = [];
for (const density of DENSITIES) {
let totalSolved = 0;
let minSolved = 100;
let maxSolved = 0;
let totalTime = 0;
process.stdout.write(`Simulating Size: ${size}x${size}, Density: ${density} ... `);
for (let i = 0; i < SAMPLES_PER_POINT; i++) {
const t0 = performance.now();
// 1. Generate
for (let i = 0; i < samples; i++) {
const grid = generateRandomGrid(size, density);
const { rowHints, colHints } = calculateHints(grid);
// 2. Solve
const { percentSolved } = solvePuzzle(rowHints, colHints);
const t1 = performance.now();
totalSolved += percentSolved;
minSolved = Math.min(minSolved, percentSolved);
maxSolved = Math.max(maxSolved, percentSolved);
totalTime += (t1 - t0);
}
const avgSolved = totalSolved / SAMPLES_PER_POINT;
const avgTime = totalTime / SAMPLES_PER_POINT;
results.push({
size,
density,
avgSolved,
minSolved,
maxSolved,
avgTime
});
csvRows.push(`${size},${density},${avgSolved.toFixed(2)},${minSolved.toFixed(2)},${maxSolved.toFixed(2)},${avgTime.toFixed(2)}`);
console.log(`Avg Solved: ${avgSolved.toFixed(1)}%`);
const avg = Math.round(totalSolved / samples);
rowData.push(avg);
}
results[size] = rowData;
console.log(` Size ${size}: [${rowData.join(', ')}]`);
}
const totalDuration = (Date.now() - startTime) / 1000;
console.log(`Simulation complete in ${totalDuration.toFixed(1)}s`);
// Save results
fs.writeFileSync(OUTPUT_FILE, JSON.stringify(results, null, 2));
fs.writeFileSync(CSV_FILE, csvRows.join('\n'));
console.log(`Results saved to ${OUTPUT_FILE} and ${CSV_FILE}`);
const duration = (Date.now() - startTime) / 1000;
console.log(`\nSimulation Complete in ${duration.toFixed(2)}s. Result JSON:`);
console.log(JSON.stringify(results, null, 4));