#!/usr/bin/env node
/**
 * VMD 动作文件诊断工具。
 *
 * 用途：拿到一个 .vmd 后，先看服务端会怎么解析它——骨骼名认不认、腿部是 IK 还是 FK、
 * 重定向成 MediaPipe 33 点后是否正常。上传前先跑一遍可以避免"传上去才发现预处理失败"。
 *
 * 用法（在 web-server 目录下，先 npm run build）：
 *   node scripts/inspect-vmd.mjs 动作.vmd
 *   node scripts/inspect-vmd.mjs 动作.vmd --frames 300      # 只采样前 300 帧
 *   node scripts/inspect-vmd.mjs 动作.vmd --json out.json   # 导出关键点序列
 *
 * 只读：不写数据库、不访问网络。
 */
import { createRequire } from 'node:module';
import { existsSync, readFileSync, writeFileSync } from 'node:fs';
import { basename, join, resolve } from 'node:path';

const require = createRequire(import.meta.url);

const args = process.argv.slice(2);
const file = args.find((a) => !a.startsWith('--'));
if (!file) {
  console.error('用法：node scripts/inspect-vmd.mjs <文件.vmd> [--frames N] [--json out.json]');
  process.exit(2);
}
const readFlag = (name, fallback) => {
  const index = args.indexOf(name);
  return index >= 0 && args[index + 1] ? args[index + 1] : fallback;
};
const maxFrames = Number(readFlag('--frames', 0)) || undefined;
const jsonOut = readFlag('--json', null);

const distDir = join(process.cwd(), 'dist', 'preprocess');
if (!existsSync(distDir)) {
  console.error('未找到 dist/preprocess，请先执行：npm run build');
  process.exit(2);
}
const { parseVmd, trackHasPositionMotion, trackHasRotationMotion, VMD_FPS } = require(
  join(distDir, 'vmd-parser.js'),
);
const { vmdToWorldFrames, legIkDriven } = require(join(distDir, 'mmd-pose.js'));
const { worldFramesToKeypointFrames } = require(join(distDir, 'retarget.js'));
const { LEG_LENGTHS, REST_HEIGHTS, MMD_SKELETON } = require(join(distDir, 'mmd-skeleton.js'));
const { ANGLE_TRIPLETS } = require(join(distDir, 'mediapipe33.js'));

const path = resolve(file);
const buffer = readFileSync(path);
const started = Date.now();
const vmd = parseVmd(buffer);
const tParse = Date.now() - started;

console.log(`文件：${basename(path)}（${(buffer.length / 1024 / 1024).toFixed(2)} MiB）`);
console.log(`头部：${vmd.header}`);
console.log(`模型名：${vmd.modelName || '（空）'}`);
console.log(`帧数：${vmd.maxFrame + 1}（${((vmd.maxFrame + 1) / VMD_FPS).toFixed(1)} 秒 @ ${VMD_FPS}fps）`);
console.log(`骨骼轨道：${vmd.tracks.size} 条 / 标准骨架共 ${MMD_SKELETON.length} 根`);
console.log(`morph 关键帧：${vmd.morphCount}`);
console.log(`解析耗时：${tParse} ms`);

const missing = MMD_SKELETON.filter((b) => !vmd.tracks.has(b.name)).map((b) => b.name);
console.log(
  `\n未出现在文件中的标准骨骼（按静止姿态处理）：${missing.length === 0 ? '（无，全部有键）' : missing.join('、')}`,
);
if (vmd.unknownBones.length > 0) {
  const preview = vmd.unknownBones.slice(0, 12).join('、');
  console.log(
    `未纳入标准骨架的骨骼：${vmd.unknownBones.length} 种（裙摆/物理/表情等，会被忽略）` +
      `\n  例如：${preview}${vmd.unknownBones.length > 12 ? ' …' : ''}`,
  );
}

const ik = legIkDriven(vmd);
console.log(
  `\n腿部驱动：左=${ik.左 ? 'IK（足ＩＫ 有位移）' : 'FK（烘焙旋转）'}  右=${ik.右 ? 'IK' : 'FK'}`,
);
const fingerBones = vmd.unknownBones.filter((n) => n.includes('親指') || n.includes('小指'));
console.log(
  `手指骨骼：${fingerBones.length > 0 ? `文件里有（${fingerBones.length} 种，当前不使用）` : '无'}`,
);
console.log(
  `IK 段落：${trackHasRotationMotion(vmd.tracks.get('左足ＩＫ')) ? '足ＩＫ 带旋转' : '足ＩＫ 仅位移'}`,
);

const t0 = Date.now();
const { frames: world, fps } = vmdToWorldFrames(vmd, { fps: VMD_FPS, maxFrames });
const tFk = Date.now() - t0;
const t1 = Date.now();
const frames = worldFramesToKeypointFrames(world, fps);
const tRt = Date.now() - t1;

let nan = 0;
let outOfRange = 0;
const knee = [];
const elbow = [];
let shoulderGap = 0;
for (const frame of frames) {
  for (const p of frame.points) {
    if (!p.every(Number.isFinite)) nan += 1;
    if (p[0] < 0 || p[0] > 1 || p[1] < 0 || p[1] > 1 || p[2] < -1 || p[2] > 1) outOfRange += 1;
  }
  knee.push(frame.angles[6], frame.angles[7]);
  elbow.push(frame.angles[2], frame.angles[3]);
  shoulderGap += frame.points[11][0] - frame.points[12][0];
}
const stats = (values) => {
  const sorted = [...values].sort((a, b) => a - b);
  const q = (p) => sorted[Math.min(sorted.length - 1, Math.floor((sorted.length - 1) * p))];
  return `min=${q(0).toFixed(3)} 中位=${q(0.5).toFixed(3)} max=${q(1).toFixed(3)}`;
};

console.log(`\n关键点序列：${frames.length} 帧`);
console.log(`  耗时：FK ${tFk} ms + 重定向 ${tRt} ms`);
console.log(`  异常：NaN ${nan} 处 / 越界 ${outOfRange} 处`);
console.log(`  膝角余弦（-1=伸直）：${stats(knee)}`);
console.log(`  肘角余弦：${stats(elbow)}`);
console.log(
  `  左肩x-右肩x 均值 ${(shoulderGap / frames.length).toFixed(3)}（>0 表示左肩在画面右侧，自拍视角）`,
);

const rig = {
  足首: REST_HEIGHTS.ankle,
  膝: REST_HEIGHTS.knee,
  髋: REST_HEIGHTS.hip,
  首: REST_HEIGHTS.neck,
  頭: REST_HEIGHTS.head,
  大腿: LEG_LENGTHS.thigh,
  小腿: LEG_LENGTHS.shin,
};
console.log(`\n标准骨架比例（静止，MMD 单位）：`);
console.log(
  `  足首 ${rig.足首.toFixed(2)} / 膝 ${rig.膝.toFixed(2)} / 髋 ${rig.髋.toFixed(2)} / ` +
    `首 ${rig.首.toFixed(2)} / 頭 ${rig.頭.toFixed(2)}`,
);
console.log(`  大腿 ${rig.大腿.toFixed(2)} + 小腿 ${rig.小腿.toFixed(2)}（腿长 ${(rig.大腿 + rig.小腿).toFixed(2)}）`);
console.log(`  关节角数量：${ANGLE_TRIPLETS.length}`);

if (jsonOut) {
  writeFileSync(jsonOut, JSON.stringify({ fps, frames }, null, 0));
  console.log(`\n已导出关键点序列：${jsonOut}`);
}
console.log('\n结论：解析与重定向均正常，可上传（.vmd → format=vmd）。');