// Validate the JS LightGBM evaluator against LightGBM's own predictions.
// Run: node tools/blockbench-uv-packer/ml/validate_js_eval.mjs

import fs from 'node:fs';
import path from 'node:path';

const ROOT = path.dirname(new URL(import.meta.url).pathname.replace(/^\//, ''));
const model = JSON.parse(fs.readFileSync(path.join(ROOT, 'share_model.json'), 'utf8'));
const tests = JSON.parse(fs.readFileSync(path.join(ROOT, 'inference_test_cases.json'), 'utf8'));

function evalTree(node, x) {
  while (!('v' in node)) {
    const val = x[node.f];
    let goLeft;
    if (val === undefined || val === null || (typeof val === 'number' && isNaN(val))) {
      goLeft = node.default_left;
    } else if (node.d === '==') {
      const cats = String(node.t).split('||').map(Number);
      goLeft = cats.includes(val);
    } else {
      goLeft = val <= node.t;
    }
    node = goLeft ? node.l : node.r;
  }
  return node.v;
}

function predict(features) {
  const x = new Array(model.feature_names.length);
  for (let i = 0; i < model.feature_names.length; i++) {
    x[i] = features[model.feature_names[i]];
  }
  let raw = 0;
  for (const tree of model.trees) raw += evalTree(tree.root, x);
  return 1 / (1 + Math.exp(-raw));
}

let maxErr = 0;
let worstCase = null;
for (const tc of tests) {
  const got = predict(tc.features);
  const err = Math.abs(got - tc.expected_prob);
  if (err > maxErr) { maxErr = err; worstCase = { tc, got }; }
}

console.log(`tests: ${tests.length}`);
console.log(`max abs error: ${maxErr.toExponential(4)}`);
if (worstCase) {
  console.log(`worst: expected=${worstCase.tc.expected_prob.toFixed(6)} got=${worstCase.got.toFixed(6)}`);
}
if (maxErr > 0.005) {
  console.error('FAIL — JS evaluator disagrees with LightGBM');
  process.exit(1);
}
console.log('PASS');