diff --git a/README.md b/README.md index af4d4230..b15406e6 100644 --- a/README.md +++ b/README.md @@ -495,7 +495,7 @@ The right stick also performs one punch after a center→peak→center gesture. ### Presentation and settings -The committed client renders a real-time 3D broadcast presentation with WebGL (pinned three.js): a procedurally modeled arena, canvas-textured ring, a referee, dynamic lighting and shadows, and GPU particle effects—including deliberately over-the-top, full-mode arcade gore—plus generated Web Audio. The fighters use the realistic “Boxer” rig by Texel, Inc. (CC BY 4.0; source, attribution, and modification notice in `web/hands/assets-src/Boxer.LICENSE.txt`) driven by authored clips retarget-baked from the project's own boxing motion (idle, movement, guards, all punches both hands, reactions, knockdown, get-up), phase-locked to the authoritative simulation via combat-manifest.json. All arena meshes, textures, and sounds remain generated in code. **Blood defaults to graphic `full` mode**; Settings can select `full`, `reduced`, or `off` without changing authoritative trauma or HUD information. Settings also provide master audio volume, haptics on/off, and reduced motion. Audio unlocks only after user interaction and suspends while hidden; haptics are feature-detected and limited to bounded authoritative impact events. Reduced motion removes particles/shake while preserving match state and private get-up information. +The committed client renders a real-time 3D broadcast presentation with WebGL (pinned three.js): a procedurally modeled arena, canvas-textured ring, a referee, dynamic lighting and shadows, and GPU particle effects—including deliberately over-the-top, full-mode arcade gore—plus generated Web Audio. The fighters and the referee use the realistic “Boxer” rig by Texel, Inc. (CC BY 4.0; source, attribution, and modification notice in `web/hands/assets-src/Boxer.LICENSE.txt`) posed at runtime by a two-bone IK solver: planted, stepping feet, punches that extend from the rotated shoulder to the opponent's live head phase-locked to combat-manifest.json timing, spring-damper hit reactions along the incoming punch line, and authored falls and get-ups. Injuries are shaded in object space on the skin materials (bruising, swelling, cuts, flowing blood) and the finishers detach the fighter's actual head or glove mesh. All arena meshes, textures, and sounds remain generated in code. **Blood defaults to graphic `full` mode**; Settings can select `full`, `reduced`, or `off` without changing authoritative trauma or HUD information. Settings also provide master audio volume, haptics on/off, and reduced motion. Coarse-pointer clients (Discord mobile) get on-screen controls: a floating joystick for footwork, punch pads whose left or right half picks the hand, and hold buttons for body, power, and guards. Audio unlocks only after user interaction and suspends while hidden; haptics are feature-detected and limited to bounded authoritative impact events. Reduced motion removes particles/shake while preserving match state and private get-up information. Before a public release, review Discord's current violent-content rules, age rating/restriction controls, store/application disclosures, and regional requirements. Do not add external/borrowed assets, commercial boxing-game UI, audio, animation traces, real-fighter or celebrity likenesses, sanctioning-body/brand marks, logos, or recognizable trade dress. All fighter art, interface, motion, terminology, and sound must remain original. @@ -600,7 +600,7 @@ git diff --exit-code -- src/intelstream/hands/static `npm run build` typechecks, writes exactly `index.html`, `assets/hands.js`, and `assets/hands.css` into `src/intelstream/hands/static`, and runs the scanner. Those generated files are committed so production Python installations do not require Node. Change TypeScript/CSS in `web/hands`, rebuild, inspect the output, commit source and generated files together, and require the final `git diff --exit-code` after a clean rebuild. Never hand-edit the generated bundle. -The fixed three-file deployment contract embeds the Boxer rig and its five source textures in `hands.js`; the resulting production script is intentionally about 5.6 MB (about 2.9 MB gzip). This startup-cost tradeoff keeps the Activity self-contained and avoids runtime asset requests. +The fixed three-file deployment contract embeds the mesh-only Boxer rig and its five source textures (re-encoded as JPEG by the generator) in `hands.js`; the resulting production script is about 2.36 MB (about 1.28 MB gzip). This startup-cost tradeoff keeps the Activity self-contained and avoids runtime asset requests. `scripts/hands_pose_strip.js` renders a pose frozen at a list of times into one frame strip for motion review. `npm run dev` also serves `?model-lab=1&pose=&cam=&trauma=` as a pose lab for reviewing the runtime animation and injury shading without a match (poses include punches, guards, slips, knockdown, seated, celebrate and wave_off), and `?fixture=1` with `&finisher=head|hand`, `&phase=rest`, `&pin=1|corner`, `&blood=reduced|off` or `&platform=mobile` for presentation review. For a standalone presentation fixture, run `npm --prefix web/hands run dev` and open the printed URL with `?fixture=1`. For the real two-process localhost flow, terminal one runs the Python bot/Hands server with valid Discord credentials: @@ -614,6 +614,19 @@ Terminal two runs Vite and proxies HTTP plus WebSocket `/api/hands` requests to HANDS_DEV_BACKEND=http://127.0.0.1:8080 npm --prefix web/hands run dev ``` +### Playing a match locally without Discord + +`scripts/hands_e2e_server.py` runs the Hands server with a development auth backend that skips the Discord OAuth steps but keeps the production ticket, room, websocket, engine and persistence code paths: + +```bash +uv run python scripts/hands_e2e_server.py --port 8091 --rounds 1 --round-seconds 45 +HANDS_DEV_BACKEND=http://127.0.0.1:8091 npm --prefix web/hands run dev -- --port 5174 +``` + +Open `http://localhost:5174/?e2e=1&instance_id=&player=` in two browser windows (different names) to fight. The `e2e` switch only exists in Vite development builds; the development server authenticates anyone who can reach its port, so never expose it. + +`scripts/hands_e2e_scenarios.js` automates this with Playwright: `ko` (power punches until a knockdown, private get-up rhythm, stoppage), `reconnect` (one client drops offline mid-round and resumes), `rest` (two rounds with the corner rest), `spectator` (a third client joins read-only), `touch` (one player on an emulated phone), `mash` (hundreds of key presses per second) `latency` (a TCP proxy delays every frame 110 ms each way, and the clients report their measured input acknowledgement latency, which the fighter HUD also shows) `soak` (a full three-round bout sampling heap size, latency and render scale every twenty seconds) `background` (one player's page is frozen through the DevTools lifecycle state for eight seconds, as a backgrounded phone app would be, then resumed) `rematch` (both players use the Rematch button after the result and fight a second bout in the same instance) `rematchloop` (four bouts back to back while sampling heap size and GPU object counts for leaks) `clinch` (both players close in and one ties up; the harness reads the fighters' separation from the client state through the engine's draw-in, the hold and the referee break) and `response` (key press to first rendered frame for the player's own punch and step, when the opponent sees them, and whether the predicted punch ever jumps back, behind a delay proxy set with `E2E_DELAY_MS`, 60 ms each way by default). It spawns the development server itself and prints the clients' status text plus any client or server errors. The default software renderer keeps runs reproducible on machines without a GPU; set `E2E_GPU=1` to render on the machine's GPU for real frame pacing, input latency and screenshots. + `HANDS_DEV_BACKEND` is a Node/Vite development-process setting, not a browser `VITE_*` value and not a production origin. Real OAuth still needs a valid Activity instance; the fixture is only recorded presentation data. Keep `HANDS_DEV_MODE=false` in production. ### Wheel/package verification diff --git a/docs/hands-lab-architecture.md b/docs/hands-lab-architecture.md index 14a0fa47..6a734b07 100644 --- a/docs/hands-lab-architecture.md +++ b/docs/hands-lab-architecture.md @@ -347,3 +347,13 @@ the palette toward pastel; trauma overlays are scaled for the larger head but their positions are approximate; the knockdown head-fall velocity makes the 0.10 m joint metric read ~0.22 m one tick after contact (filmstrip shows flush contact). + +--- + +# Superseded (2026-09-28) + +The clip-based animation graph, the retarget-baked GLB, the marker export, and +the sphere trauma overlays described above were replaced by the runtime pose +system, object-space injury shading, and mesh-baked gore documented in +`docs/hands-realism-plan.md`. The lab route, the golden replay, and the +acceptance metrics still apply; the protocol is now v3 and the ring is square. diff --git a/docs/hands-realism-plan.md b/docs/hands-realism-plan.md new file mode 100644 index 00000000..d935d0eb --- /dev/null +++ b/docs/hands-realism-plan.md @@ -0,0 +1,87 @@ +# Hands realism overhaul + +Branch `feature/hands-realism`. Goal: make the Hands Discord Activity a realistic, +responsive boxing game with injuries and gore, on the existing authoritative +Python engine, websocket rooms, persistence, and ratings. + +## Baseline findings (2026-09-28) + +Measured against `origin/main` at 992a4f5 with the dev fixture, the model lab, +and the engine source. + +Simulation and protocol + +- Punches only hit along the ring x axis. `_resolve_punch` projects onto the + binary `facing` sign, so fighters offset along ring depth whiff while the + presentation shows them squared up. +- A second punch pressed during the first is dropped. `ACTION_BUFFER_TICKS` + (6) expires before a 13-tick jab clears, so `pending_actions` is cleared + before it can dispatch. There is no recovery cancel, so combos cannot flow. +- Get-up teleports the downed fighter to `x = +-140`, which the client hides + with a 0.85 m slide. + +Presentation and network + +- Movement stutters at 15 Hz. The renderer samples a fixed `latest.tick - 1` + and snapshots arrive every second tick, so the pose holds for about four + frames and jumps. +- Input is polled every 40 ms instead of sent on the key edge, and there is no + local movement prediction, so footwork lags by round trip plus polling. +- Punch, guard, movement, reaction, and knockdown clips are retarget-baked + from a capsule rig through direction-only child aim. Elbow and wrist twist + are uncontrolled and the knockdown never reaches the canvas. +- Injuries are colored spheres and boxes parented to the head bone. They + float beside the textured face. Gibs are red icosahedra; the severed head is + a scaled sphere; the referee is a capsule mannequin. +- Five 105 cd fill spotlights plus bloom wash the image to pastel and blow out + the white rope. The broadcast camera sits 7 m back, so fighters occupy + roughly a third of the frame height. + +## Plan + +1. Simulation feel: continuous facing vector with limited turn rate and a + facing-relative hit test; input buffer that survives the current punch; + late-recovery combo cancels; knockdown separation by the referee instead of + a teleport; protocol v3 carrying `facing_x`, `facing_y`, and the last + processed input sequence. +2. Netcode: continuous render clock with adaptive interpolation delay, + 30 Hz broadcast, edge-triggered action sends, and local movement prediction + for the viewer's fighter. +3. Animation: a runtime pose system on the Texel skeleton (stance, guards, + punches that reach the live target, footwork with planted feet and pivots, + spring-damper hit reactions, keyframed falls and get-ups) replacing the + retarget-baked clips. +4. Injuries and gore: face and body damage painted into the skin textures + (bruising, cuts, swelling displacement, flowing blood), blood on gloves and + canvas, stretched droplet sprites, and mesh-based decapitation and + dismemberment for the arcade finishers. +5. Presentation: closer broadcast framing with impact and knockdown cameras, + corrected lighting and exposure, layered impact audio, and a skinned + referee. + +Every phase lands as its own commits with Python and Vitest coverage, a +rebuilt committed bundle, and screenshots captured through headless Chromium. + +## Status (2026-09-29) + +All five phases landed on `feature/hands-realism` (PR #293). Beyond the plan, the branch also +carries: adaptive render resolution with a no-gain revert, crowd excitement, rest-phase corner +walk with stools and a cutman who climbs in to work the worse eye (engine + client), anti-parallel +facing fix, knockout presentation (slow-motion replay, close-up, held result panel, winner +celebration, referee wave-off), portrait framing with a compact scoreboard, per-round and per-bout +punch stats, rope flex under a pinned fighter, face-down knockdowns after hooks, a real clinch +tie-up (the engine draws the fighters to a hold distance; one hooks over, the other under), a +legible showboat taunt, glove trails on fast punches, a rendered root that follows the engine at a +fixed speed per second, a broken nose under heavy head trauma, a glove touch before the opening +bell, a shadow-boxing waiting screen, rematches, plain-language failure text and a copyable +diagnostics panel. + +Review harnesses: `?model-lab=1&pose=...` (pose lab), `?fixture=1` with `&finisher=head|hand`, +`&phase=rest`, `&pin=1|corner`, `&blood=reduced|off`, `&platform=mobile`, `?lab=1` (golden replay), and the Discord-free +real-stack harness (`scripts/hands_e2e_server.py` plus `scripts/hands_e2e_scenarios.js` with the +ko, reconnect, rest, spectator, touch, mash, latency, soak, background, rematch, rematchloop and +clinch scenarios; see the README). + +Considered and not done: starting round 1 from the corners (the engine tests and the golden +replay schedule assume the centre start). A live Discord Activity launch with the server's players +still has to happen outside this repository's tooling. diff --git a/scripts/hands_e2e_scenarios.js b/scripts/hands_e2e_scenarios.js new file mode 100644 index 00000000..5118421f --- /dev/null +++ b/scripts/hands_e2e_scenarios.js @@ -0,0 +1,625 @@ +/** + * Two-player Hands scenarios through the real client and server, without Discord. + * + * Requires Playwright with Chromium (for example `npm install -g playwright && npx playwright + * install chromium`, then run with NODE_PATH pointing at that global node_modules), a Vite dev + * server started with HANDS_DEV_BACKEND=http://127.0.0.1:8091 (override with E2E_BASE), and uv. + * Each scenario spawns scripts/hands_e2e_server.py on port 8091, drives two headless players with + * keyboard or touch input, reads the client's screen-reader status text, and writes screenshots to + * $TMPDIR/hands-e2e. Set E2E_GPU=1 to render on the machine's GPU instead of the software renderer + * (real frame pacing and input latency). + * + * node scripts/hands_e2e_scenarios.js ko|reconnect|rest|spectator|touch|mash|latency|soak|background|rematch|rematchloop|clinch|response + */ +const { chromium, devices } = require('playwright'); +const { spawn } = require('node:child_process'); +const http = require('node:http'); +const net = require('node:net'); + +const base = process.env.E2E_BASE || 'http://localhost:5174'; +const path = require('node:path'); +const os = require('node:os'); +const fs = require('node:fs'); +const repo = path.resolve(__dirname, '..'); +const out = path.join(os.tmpdir(), 'hands-e2e'); +fs.mkdirSync(out, { recursive: true }); +const scenario = process.argv[2] || 'ko'; +const PORT = Number(process.env.E2E_PORT ?? 8091); +const wait = (ms) => new Promise((r) => setTimeout(r, ms)); + +function healthz() { + return new Promise((resolve) => { + const req = http.get(`http://127.0.0.1:${PORT}/healthz`, (res) => { res.resume(); resolve(res.statusCode === 200); }); + req.on('error', () => resolve(false)); + req.setTimeout(1500, () => { req.destroy(); resolve(false); }); + }); +} + +/** TCP proxy that delays every chunk in both directions, so websocket frames see real latency. */ +function delayProxy(listenPort, targetPort, delayMs) { + const server = net.createServer((client) => { + const upstream = net.connect(targetPort, '127.0.0.1'); + const pipe = (from, to) => { + from.on('data', (chunk) => setTimeout(() => { if (!to.destroyed) to.write(chunk); }, delayMs)); + from.on('end', () => setTimeout(() => to.end(), delayMs)); + from.on('error', () => to.destroy()); + }; + pipe(client, upstream); + pipe(upstream, client); + }); + server.listen(listenPort, '127.0.0.1'); + return server; +} + +async function startServer(args, { oneWayDelayMs = 0 } = {}) { + const backendPort = oneWayDelayMs > 0 ? PORT + 1 : PORT; + const child = spawn('uv', ['run', 'python', 'scripts/hands_e2e_server.py', '--port', String(backendPort), ...args], { cwd: repo, stdio: ['ignore', 'pipe', 'pipe'] }); + const log = []; + child.stdout.on('data', (d) => log.push(String(d))); + child.stderr.on('data', (d) => log.push(String(d))); + const proxy = oneWayDelayMs > 0 ? delayProxy(PORT, backendPort, oneWayDelayMs) : null; + for (let i = 0; i < 60; i += 1) { if (await healthz()) return { child, log, proxy }; await wait(500); } + throw new Error('server did not start: ' + log.join('')); +} + +async function status(page) { + return page.evaluate(() => ({ + status: document.querySelector('[data-status]')?.textContent ?? null, + live: document.querySelector('[data-fight-status]')?.textContent ?? null, + summary: document.querySelector('[data-fight-summary]')?.textContent ?? null, + final: document.querySelector('[data-final]')?.textContent ?? null, + role: document.querySelector('[data-role]')?.hidden === false ? document.querySelector('[data-role]')?.textContent : null, + })); +} + +async function waitFor(page, predicate, timeoutMs, label) { + const started = Date.now(); + while (Date.now() - started < timeoutMs) { + const s = await status(page); + if (predicate(s)) return s; + await wait(250); + } + const s = await status(page); + console.log(`TIMEOUT waiting for ${label}:`, JSON.stringify(s).slice(0, 300)); + return null; +} + +/** + * Counts the WebGL objects alive in the page and the bytes their textures hold. renderer.info cannot + * show a leak across rematches: it starts again at zero with every renderer on the shared context. + */ +function countLiveGlObjects() { + const live = { buffers: 0, textures: 0, programs: 0, shaders: 0, framebuffers: 0, renderbuffers: 0 }; + const proto = WebGL2RenderingContext.prototype; + for (const [create, remove, key] of [['createBuffer', 'deleteBuffer', 'buffers'], ['createTexture', 'deleteTexture', 'textures'], ['createProgram', 'deleteProgram', 'programs'], ['createShader', 'deleteShader', 'shaders'], ['createFramebuffer', 'deleteFramebuffer', 'framebuffers'], ['createRenderbuffer', 'deleteRenderbuffer', 'renderbuffers']]) { + const made = proto[create]; + const gone = proto[remove]; + proto[create] = function (...args) { const object = made.apply(this, args); if (object) live[key] += 1; return object; }; + proto[remove] = function (object) { if (object) live[key] -= 1; return gone.call(this, object); }; + } + const bytes = new Map(); + const bound = new Map(); + let unit = 0; + const activeTexture = proto.activeTexture; + proto.activeTexture = function (value) { unit = value; return activeTexture.call(this, value); }; + const bindTexture = proto.bindTexture; + proto.bindTexture = function (target, texture) { bound.set(`${unit}:${target}`, texture); return bindTexture.call(this, target, texture); }; + const texelBytes = (format) => (format === 0x8814 || format === 0x8D70 ? 16 : format === 0x881A ? 8 : 4); + const texStorage2D = proto.texStorage2D; + proto.texStorage2D = function (target, levels, format, width, height) { + const texture = bound.get(`${unit}:${target}`); + let total = 0; + for (let level = 0, w = width, h = height; level < levels; level += 1, w = Math.max(1, w >> 1), h = Math.max(1, h >> 1)) total += w * h * texelBytes(format); + if (texture) bytes.set(texture, total * (target === 0x8513 ? 6 : 1)); + return texStorage2D.call(this, target, levels, format, width, height); + }; + const texImage2D = proto.texImage2D; + proto.texImage2D = function (...args) { + const texture = bound.get(`${unit}:${args[0]}`); + if (texture && args.length >= 9 && args[1] === 0) bytes.set(texture, args[3] * args[4] * 4); + else if (texture && args.length === 6 && args[1] === 0 && args[5] && args[5].width) bytes.set(texture, args[5].width * args[5].height * 4); + return texImage2D.apply(this, args); + }; + const deleteTexture = proto.deleteTexture; + proto.deleteTexture = function (texture) { bytes.delete(texture); return deleteTexture.call(this, texture); }; + window.__glLive = () => ({ ...live, textureMb: Math.round([...bytes.values()].reduce((a, b) => a + b, 0) / 104857.6) / 10 }); +} + +async function main() { + const gpuArgs = process.env.E2E_GPU === '1' + ? ['--enable-gpu', '--ignore-gpu-blocklist'] + : ['--use-gl=angle', '--use-angle=swiftshader', '--enable-unsafe-swiftshader', '--ignore-gpu-blocklist']; + const browser = await chromium.launch({ args: gpuArgs }); + const instance = `e2e-${scenario}-${Date.now()}`; + const open = async (name, options = {}) => { + const context = await browser.newContext(options.mobile ? { ...devices['Pixel 7'], viewport: { width: 844, height: 390 } } : { viewport: { width: 1280, height: 720 } }); + const page = await context.newPage(); + if (scenario === 'rematchloop') await page.addInitScript(countLiveGlObjects); + if (scenario === 'response') { + // Records when each input frame that carries a press leaves the page, to time press to send. + await page.addInitScript(() => { + const send = WebSocket.prototype.send; + window.__actionSends = []; + WebSocket.prototype.send = function (data) { + if (typeof data === 'string' && data.includes('"actions":[{')) window.__actionSends.push(performance.timeOrigin + performance.now()); + return send.call(this, data); + }; + }); + } + const errors = []; + page.on('pageerror', (e) => errors.push(`${name} pageerror: ${e.message.slice(0, 240)}`)); + page.on('console', (m) => { if (m.type() === 'error') errors.push(`${name} console.error: ${m.text().slice(0, 240)}`); }); + await page.goto(`${base}/?e2e=1&instance_id=${instance}&player=${name}${options.mobile ? '&platform=mobile' : ''}`, { waitUntil: 'load' }); + return { page, context, errors, name }; + }; + const report = { scenario, events: [], errors: [] }; + const note = (...parts) => { const line = parts.join(' '); report.events.push(line); console.log(line); }; + + const serverArgs = { + ko: ['--rounds', '3', '--round-seconds', '90', '--rest-seconds', '5'], + reconnect: ['--rounds', '1', '--round-seconds', '70', '--rest-seconds', '5'], + rest: ['--rounds', '2', '--round-seconds', '14', '--rest-seconds', '9'], + spectator: ['--rounds', '1', '--round-seconds', '30', '--rest-seconds', '5'], + touch: ['--rounds', '1', '--round-seconds', '40', '--rest-seconds', '5'], + mash: ['--rounds', '1', '--round-seconds', '40', '--rest-seconds', '5'], + latency: ['--rounds', '1', '--round-seconds', '45', '--rest-seconds', '5'], + soak: ['--rounds', '3', '--round-seconds', '120', '--rest-seconds', '15'], + background: ['--rounds', '1', '--round-seconds', '60', '--rest-seconds', '5'], + rematch: ['--rounds', '1', '--round-seconds', '25', '--rest-seconds', '5'], + rematchloop: ['--rounds', '1', '--round-seconds', '20', '--rest-seconds', '5'], + clinch: ['--rounds', '1', '--round-seconds', '30', '--rest-seconds', '5'], + response: ['--rounds', '1', '--round-seconds', '40', '--rest-seconds', '5'], + }[scenario]; + const responseDelayMs = Number(process.env.E2E_DELAY_MS ?? 60); + const server = await startServer(serverArgs, { oneWayDelayMs: scenario === 'latency' ? 110 : scenario === 'response' ? responseDelayMs : 0 }); + try { + const A = await open('Alpha'); + const B = await open('Bravo', { mobile: scenario === 'touch' }); + if (scenario === 'latency') note('both clients behind a TCP proxy adding 110 ms each way (220 ms round trip) to every frame'); + const startedState = await waitFor(A.page, (s) => /countdown|fight/.test(s.summary ?? ''), 60000, 'bout start'); + note('bout started:', startedState !== null); + await waitFor(A.page, (s) => /\. fight\./.test(s.summary ?? ''), 20000, 'fight phase'); + // Approach: A right, B left. + await A.page.keyboard.down('d'); await B.page.keyboard.down('a'); await wait(1600); await A.page.keyboard.up('d'); await B.page.keyboard.up('a'); + + if (scenario === 'ko') { + // Records every fighter's punch phase while the knockout replay plays, to catch a stuttering replay. + await A.page.evaluate(() => { + const state = { frames: 0, jumps: 0, worst: 0 }; + window.__replayProbe = state; + const last = [{ id: null, age: 0 }, { id: null, age: 0 }]; + const tick = () => { + const renderer = window.__handsApp?.renderer; + if (renderer?.replay && renderer.graphs) { + state.frames += 1; + renderer.graphs.forEach((graph, index) => { + const id = graph.punchActive ? graph.actionId : null; + const age = graph.punchAgeTicks; + if (id !== null && id === last[index].id && last[index].age - age > 0.5) { state.jumps += 1; state.worst = Math.max(state.worst, last[index].age - age); } + last[index] = { id, age }; + }); + } + requestAnimationFrame(tick); + }; + requestAnimationFrame(tick); + }); + let downSeen = false; let promptsPressed = 0; let final = null; let lastCount = -1; + const started = Date.now(); + await A.page.keyboard.down('Alt'); + while (Date.now() - started < 240000) { + const sB = await status(B.page); + if (sB.final) { final = sB; break; } + const live = sB.live ?? ''; + if (/^Knockdown/.test(live) || /\. knockdown\./.test(sB.summary ?? '')) { + if (!downSeen) { downSeen = true; note('KNOCKDOWN seen at', ((Date.now() - started) / 1000).toFixed(1), 's:', live); await A.page.screenshot({ path: `${out}/e2e-ko-A-down.png` }); await B.page.screenshot({ path: `${out}/e2e-ko-B-down.png` }); } + const count = /Count (\d+)/.exec(live); if (count && Number(count[1]) !== lastCount) { lastCount = Number(count[1]); note('count', lastCount, '|', live); } + if (/Press left now/.test(live)) { await B.page.keyboard.press('ArrowLeft'); promptsPressed += 1; } + else if (/Press right now/.test(live)) { await B.page.keyboard.press('ArrowRight'); promptsPressed += 1; } + await wait(60); + continue; + } + // A keeps pressure: step in, throw power hooks and uppercuts, occasionally straights. + await A.page.keyboard.down('d'); await wait(120); await A.page.keyboard.up('d'); + const key = ['g', 't', 'h', 'y', 'u'][Math.floor(Math.random() * 5)]; + await A.page.keyboard.press(key); + await wait(380); + } + await A.page.keyboard.up('Alt'); + note('get-up presses:', promptsPressed); + note('input latency A:', JSON.stringify(await A.page.evaluate(() => window.__handsApp?.networkStats ?? null)), 'B:', JSON.stringify(await B.page.evaluate(() => window.__handsApp?.networkStats ?? null))); + if (final === null) final = await waitFor(B.page, (s) => Boolean(s.final), 120000, 'final'); + note('FINAL:', JSON.stringify(final?.final ?? null)); + await A.page.screenshot({ path: `${out}/e2e-ko-A-final.png` }); await B.page.screenshot({ path: `${out}/e2e-ko-B-final.png` }); + await wait(8000); + await A.page.screenshot({ path: `${out}/e2e-ko-A-result.png` }); + note('knockout replay:', JSON.stringify(await A.page.evaluate(() => window.__replayProbe))); + } + + if (scenario === 'reconnect') { + for (let i = 0; i < 6; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await wait(400); } + note('before drop A:', (await status(A.page)).status, '| B:', (await status(B.page)).status); + await B.context.setOffline(true); + note('B offline'); + const paused = await waitFor(A.page, (s) => /paused|reconnect/i.test((s.status ?? '') + (s.live ?? '')), 30000, 'opponent pause on A'); + note('A during drop:', paused?.status, '|', paused?.live); + await B.page.screenshot({ path: `${out}/e2e-reconnect-B-offline.png` }); + await wait(3000); + await B.context.setOffline(false); + note('B online'); + const resumed = await waitFor(A.page, (s) => /in progress|fight/i.test((s.status ?? '') + (s.summary ?? '')) && !/paused|reconnect/i.test(s.status ?? ''), 40000, 'resume on A'); + note('A after resume:', resumed?.status, '|', resumed?.live); + const bBack = await waitFor(B.page, (s) => /in progress|fight/i.test((s.status ?? '') + (s.summary ?? '')) && !/Unable|paused|reconnect/i.test(s.status ?? ''), 40000, 'B resumed'); + note('B after resume:', bBack?.status, '|', bBack?.live); + // The server stopped for the drop; the render clock must find it again rather than show only the newest snapshot. + await wait(1500); + for (const [label, page] of [['A', A.page], ['B', B.page]]) { + const clock = await page.evaluate(() => new Promise((resolve) => { + const buffer = window.__handsApp?.renderer?.buffer; + let frames = 0; + let atLatest = 0; + const end = performance.now() + 2000; + const tick = (now) => { + const latest = buffer?.latest?.(); + if (buffer && latest && buffer.offsetTicks !== null) { + frames += 1; + if ((now * 30) / 1000 + buffer.offsetTicks - buffer.interpolationDelayTicks >= latest.tick) atLatest += 1; + } + if (now < end) requestAnimationFrame(tick); + else resolve({ frames, atLatest, delayTicks: buffer?.interpolationDelayTicks ?? null }); + }; + requestAnimationFrame(tick); + })); + note(`${label} render clock after the resume: ${clock.atLatest} of ${clock.frames} frames held on the newest snapshot, delay ${clock.delayTicks} ticks`); + if (clock.frames === 0 || clock.atLatest > clock.frames * 0.2) report.errors.push(`${label} render clock did not recover after the resume (${clock.atLatest} of ${clock.frames} frames at the newest snapshot)`); + } + for (let i = 0; i < 6; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await wait(400); } + note('B summary after resume:', (await status(B.page)).summary?.slice(0, 160)); + const final = await waitFor(A.page, (s) => Boolean(s.final), 120000, 'final'); + note('FINAL A:', JSON.stringify(final?.final ?? null).slice(0, 200)); + note('FINAL B:', JSON.stringify((await status(B.page)).final).slice(0, 200)); + } + + if (scenario === 'rest') { + for (let i = 0; i < 8; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await wait(400); } + const rest = await waitFor(A.page, (s) => /\. rest\./.test(s.summary ?? ''), 40000, 'rest phase'); + note('rest reached:', rest !== null, '|', rest?.status, '|', rest?.live); + await wait(4500); + await A.page.screenshot({ path: `${out}/e2e-rest-A.png` }); await B.page.screenshot({ path: `${out}/e2e-rest-B.png` }); + const round2 = await waitFor(A.page, (s) => /Round 2\. fight/.test(s.summary ?? ''), 40000, 'round 2'); + note('round 2 reached:', round2 !== null, '|', round2?.summary?.slice(0, 60)); + await A.page.keyboard.down('d'); await B.page.keyboard.down('a'); await wait(2500); await A.page.keyboard.up('d'); await B.page.keyboard.up('a'); + await A.page.screenshot({ path: `${out}/e2e-rest-A-round2.png` }); + const final = await waitFor(A.page, (s) => Boolean(s.final), 90000, 'final'); + note('FINAL:', JSON.stringify(final?.final ?? null).slice(0, 200)); + } + + if (scenario === 'spectator') { + const S = await open('Watcher'); + const spec = await waitFor(S.page, (s) => /spectat/i.test((s.status ?? '') + (s.role ?? '')) || Boolean(s.summary), 30000, 'spectator join'); + note('spectator:', spec?.status, '| role:', spec?.role, '| summary:', spec?.summary?.slice(0, 80)); + for (let i = 0; i < 6; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await S.page.keyboard.press('f'); await wait(400); } + await S.page.screenshot({ path: `${out}/e2e-spectator.png` }); + note('spectator after inputs:', (await status(S.page)).status); + const final = await waitFor(S.page, (s) => Boolean(s.final), 90000, 'spectator final'); + note('SPECTATOR FINAL:', JSON.stringify(final?.final ?? null).slice(0, 160)); + report.errors.push(...S.errors); + } + + if (scenario === 'touch') { + const before = await status(A.page); + note('touch controls present on B:', await B.page.evaluate(() => document.querySelectorAll('.touch-pad').length)); + const pad = await B.page.$('.touch-pad[data-punch="jab"]'); + const box = await pad.boundingBox(); + for (let i = 0; i < 10; i += 1) { + await B.page.touchscreen.tap(box.x + box.width * 0.75, box.y + box.height / 2); + await wait(350); + await B.page.touchscreen.tap(box.x + box.width * 0.25, box.y + box.height / 2); + await wait(350); + } + const stick = await B.page.$('.touch-stick'); + const sb = await stick.boundingBox(); + const cdp = await B.context.newCDPSession(B.page); + const sx = sb.x + sb.width / 2, sy = sb.y + sb.height / 2; + await cdp.send('Input.dispatchTouchEvent', { type: 'touchStart', touchPoints: [{ x: sx, y: sy }] }); + await cdp.send('Input.dispatchTouchEvent', { type: 'touchMove', touchPoints: [{ x: sx - 50, y: sy }] }); + await wait(1200); + await cdp.send('Input.dispatchTouchEvent', { type: 'touchEnd', touchPoints: [] }); + await B.page.screenshot({ path: `${out}/e2e-touch-B.png` }); + const after = await status(A.page); + note('A summary before:', before.summary?.slice(0, 200)); + note('A summary after :', after.summary?.slice(0, 200)); + const final = await waitFor(A.page, (s) => Boolean(s.final), 90000, 'final'); + note('FINAL:', JSON.stringify(final?.final ?? null).slice(0, 200)); + } + + if (scenario === 'mash') { + const keys = ['f', 'j', 'r', 'u', 'g', 'h', 't', 'y', 'q', 'e', 'z', 'x', 'c', 'v', 'b', 'm']; + const started = Date.now(); + let presses = 0; + while (Date.now() - started < 15000) { + const key = keys[presses % keys.length]; + await A.page.keyboard.press(key, { delay: 0 }); + presses += 1; + if (presses % 40 === 0) { await A.page.keyboard.down('d'); await wait(40); await A.page.keyboard.up('d'); } + } + note('presses in 15 s:', presses, `(${(presses / 15).toFixed(0)}/s)`); + const after = await status(A.page); + note('A after mash:', after.status, '|', after.summary?.slice(0, 120)); + note('B after mash:', (await status(B.page)).status); + const final = await waitFor(A.page, (s) => Boolean(s.final), 90000, 'final'); + note('FINAL:', JSON.stringify(final?.final ?? null).slice(0, 200)); + } + + if (scenario === 'latency') { + const started = Date.now(); + let step = 0; + const stats = (page) => page.evaluate(() => window.__handsApp?.networkStats?.inputLatencyMs ?? null); + while (Date.now() - started < 25000) { + await A.page.keyboard.press(['f', 'r', 'g'][step % 3]); + await B.page.keyboard.press(['j', 'u', 'h'][step % 3]); + if (step % 4 === 0) { await B.page.keyboard.down('a'); await wait(150); await B.page.keyboard.up('a'); } + await wait(420); + step += 1; + if (step % 8 === 0) note(`t=${((Date.now() - started) / 1000).toFixed(0)}s input latency A: ${Math.round((await stats(A.page)) ?? -1)} ms B: ${Math.round((await stats(B.page)) ?? -1)} ms`); + } + const sA = await status(A.page); const sB = await status(B.page); + note('A:', sA.status, '|', sA.summary?.slice(0, 140)); + note('B:', sB.status, '|', sB.summary?.slice(0, 140)); + note('input latency A:', JSON.stringify(await A.page.evaluate(() => window.__handsApp?.networkStats ?? null)), 'B:', JSON.stringify(await B.page.evaluate(() => window.__handsApp?.networkStats ?? null))); + await B.page.screenshot({ path: `${out}/e2e-latency-B.png` }); + const final = await waitFor(B.page, (s) => Boolean(s.final), 90000, 'final'); + note('FINAL B:', JSON.stringify(final?.final ?? null).slice(0, 200)); + } + + if (scenario === 'background') { + for (let i = 0; i < 6; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await wait(400); } + const clock = (s) => /Clock (\d+:\d+)/.exec(s.summary ?? '')?.[1] ?? null; + note('before freeze A clock', clock(await status(A.page)), 'B clock', clock(await status(B.page))); + const cdp = await B.context.newCDPSession(B.page); + await cdp.send('Page.enable'); + await cdp.send('Page.setWebLifecycleState', { state: 'frozen' }); + note('B frozen (backgrounded)'); + await wait(8000); + for (let i = 0; i < 4; i += 1) { await A.page.keyboard.press('f'); await wait(300); } + note('A during B freeze:', (await status(A.page)).status, '| clock', clock(await status(A.page))); + await cdp.send('Page.setWebLifecycleState', { state: 'active' }); + note('B active again'); + await wait(2500); + const sA = await status(A.page); const sB = await status(B.page); + note('after resume A clock', clock(sA), 'status', sA.status, '| B clock', clock(sB), 'status', sB.status); + for (let i = 0; i < 6; i += 1) { await B.page.keyboard.press('j'); await A.page.keyboard.press('f'); await wait(400); } + const later = await status(B.page); + note('B after inputs:', later.status, '| clock', clock(later), '| latency', JSON.stringify(await B.page.evaluate(() => window.__handsApp?.networkStats ?? null))); + const final = await waitFor(B.page, (s) => Boolean(s.final), 90000, 'final'); + note('FINAL B:', JSON.stringify(final?.final ?? null).slice(0, 200)); + note('FINAL A:', JSON.stringify((await status(A.page)).final).slice(0, 200)); + } + + if (scenario === 'rematch') { + for (let i = 0; i < 4; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await wait(400); } + const first = await waitFor(A.page, (s) => Boolean(s.final), 90000, 'first final'); + note('first final:', JSON.stringify(first?.final ?? null).slice(0, 90)); + const rematchState = (page) => page.evaluate(() => { const b = document.querySelector('[data-rematch]'); return b ? { hidden: b.hidden, disabled: b.disabled, text: b.textContent } : null; }); + note('rematch button right after final:', JSON.stringify(await rematchState(A.page))); + const enabledAt = Date.now(); + for (let i = 0; i < 60; i += 1) { const s = await rematchState(A.page); if (s && !s.hidden && !s.disabled) break; await wait(500); } + note('rematch enabled after', ((Date.now() - enabledAt) / 1000).toFixed(1), 's:', JSON.stringify(await rematchState(A.page)), JSON.stringify(await rematchState(B.page))); + await A.page.click('[data-rematch]'); + await B.page.click('[data-rematch]'); + const second = await waitFor(A.page, (s) => /countdown|\. fight\./.test(s.summary ?? '') && !s.final, 60000, 'second bout start'); + note('second bout started:', second !== null, '|', second?.status, '|', second?.summary?.slice(0, 60)); + await waitFor(A.page, (s) => /\. fight\./.test(s.summary ?? ''), 20000, 'second fight phase'); + for (let i = 0; i < 4; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await wait(400); } + const finalA = await waitFor(A.page, (s) => Boolean(s.final), 90000, 'second final'); + note('second final A:', JSON.stringify(finalA?.final ?? null).slice(0, 120)); + const finalB = await waitFor(B.page, (s) => Boolean(s.final), 15000, 'second final on B'); + note('second final B:', JSON.stringify(finalB?.final ?? null).slice(0, 120)); + } + + if (scenario === 'rematchloop') { + const sample = (page) => page.evaluate(() => ({ heapMb: typeof performance.memory === 'object' && performance.memory ? Math.round(performance.memory.usedJSHeapSize / 1048576) : null, gpu: window.__glLive?.() ?? null })); + const rematchReady = (page) => page.evaluate(() => { const b = document.querySelector('[data-rematch]'); return Boolean(b && !b.hidden && !b.disabled); }); + const samples = []; + for (let bout = 1; bout <= 4; bout += 1) { + await waitFor(A.page, (s) => /\. fight\./.test(s.summary ?? ''), 30000, `bout ${bout} fight phase`); + for (let i = 0; i < 6; i += 1) { await A.page.keyboard.press('f'); await B.page.keyboard.press('j'); await wait(350); } + const final = await waitFor(A.page, (s) => Boolean(s.final), 90000, `bout ${bout} final`); + await waitFor(B.page, (s) => Boolean(s.final), 15000, `bout ${bout} final on B`); + const [a, b] = [await sample(A.page), await sample(B.page)]; + samples.push({ bout, a, b }); + note(`bout ${bout} final: ${JSON.stringify(final?.final ?? null).slice(0, 40)} | heap A ${a.heapMb} MB B ${b.heapMb} MB | gpu A ${JSON.stringify(a.gpu)} B ${JSON.stringify(b.gpu)}`); + if (bout === 4) break; + for (let i = 0; i < 60; i += 1) { if ((await rematchReady(A.page)) && (await rematchReady(B.page))) break; await wait(500); } + await A.page.click('[data-rematch]'); + await B.page.click('[data-rematch]'); + const next = await waitFor(A.page, (s) => /countdown|\. fight\./.test(s.summary ?? '') && !s.final, 60000, `bout ${bout + 1} start`); + note(`bout ${bout + 1} started: ${next !== null}`); + } + if (samples.length >= 2) { + const first = samples[0]; const last = samples.at(-1); + const rebuilds = samples.length - 1; + for (const side of ['a', 'b']) { + const growth = Object.fromEntries(Object.keys(last[side].gpu ?? {}).map((key) => [key, Math.round(((last[side].gpu?.[key] ?? 0) - (first[side].gpu?.[key] ?? 0)) * 10) / 10])); + note(`growth ${side.toUpperCase()} over ${rebuilds} rematches: heap ${last[side].heapMb - first[side].heapMb} MB; live GL objects ${JSON.stringify(growth)}`); + // Each renderer leaves a few small objects inside three.js itself; a leaked model or bloom chain is megabytes. + if ((growth.textureMb ?? 0) > rebuilds * 0.5) report.errors.push(`${side.toUpperCase()} texture memory grew ${growth.textureMb} MB over ${rebuilds} rematches`); + } + } + } + + if (scenario === 'response') { + note(`network delay ${responseDelayMs} ms each way (${responseDelayMs * 2} ms round trip); times are key press to the first rendered frame, within one frame`); + const probe = () => { + const state = { frames: [], keys: [] }; + window.__probe = state; + const epoch = () => performance.timeOrigin + performance.now(); + addEventListener('keydown', (event) => { if (!event.repeat) state.keys.push({ code: event.code, at: epoch() }); }, true); + const tick = () => { + const renderer = window.__handsApp?.renderer; + const graphs = renderer?.graphs; + const latest = renderer?.buffer?.latest?.(); + if (graphs && latest) { + const Vector3 = graphs[0].boxer.root.position.constructor; + const frame = { at: epoch(), viewer: latest.fighters.findIndex((fighter) => fighter.player_id === renderer.viewerId), fighters: [] }; + for (const graph of graphs) { + const left = graph.boxer.rig.bones.gloveL.getWorldPosition(new Vector3()); + const right = graph.boxer.rig.bones.gloveR.getWorldPosition(new Vector3()); + const timing = graph.punchTiming; + const age = graph.punchAgeTicks; + const progress = age < timing.startup ? age / Math.max(1, timing.startup) : age < timing.startup + timing.active ? 1 + (age - timing.startup) / Math.max(1, timing.active) : 2 + Math.min(1, (age - timing.startup - timing.active) / Math.max(1, timing.recovery)); + frame.fighters.push({ active: graph.punchActive === true, age, progress, timing: `${graph.punchClass} ${timing.startup}/${timing.active}/${timing.recovery}`, x: graph.boxer.root.position.x, z: graph.boxer.root.position.z, left: [left.x, left.y, left.z], right: [right.x, right.y, right.z] }); + } + state.frames.push(frame); + if (state.frames.length > 6000) state.frames.shift(); + } + requestAnimationFrame(tick); + }; + requestAnimationFrame(tick); + }; + await A.page.evaluate(probe); await B.page.evaluate(probe); + await wait(600); + const presses = []; + for (const key of ['f', 'f', 'f', 'u', 'u', 'g']) { await wait(1100); await A.page.keyboard.press(key); presses.push(key); } + await wait(1200); + await A.page.keyboard.down('a'); await wait(500); await A.page.keyboard.up('a'); + await wait(900); + const a = await A.page.evaluate(() => window.__probe); + const b = await B.page.evaluate(() => window.__probe); + const distance = (p, q) => Math.hypot(p[0] - q[0], p[1] - q[1], p[2] - q[2]); + const frameAt = (frames, at) => frames.findLast((frame) => frame.at <= at) ?? frames[0]; + const median = (values) => { const sorted = values.filter((v) => v !== null).sort((x, y) => x - y); return sorted.length === 0 ? null : Math.round(sorted[Math.floor(sorted.length / 2)]); }; + const viewerA = a.frames.at(-1).viewer; + const punchKeys = a.keys.filter((key) => ['KeyF', 'KeyU', 'KeyG'].includes(key.code)); + const local = []; const moved = []; const remote = []; + for (const key of punchKeys) { + const hand = key.code === 'KeyU' ? 'right' : 'left'; + const before = frameAt(a.frames, key.at).fighters[viewerA]; + const started = a.frames.find((frame) => frame.at > key.at && frame.fighters[viewerA].active && frame.fighters[viewerA].age < 6); + const glove = a.frames.find((frame) => frame.at > key.at && distance(frame.fighters[viewerA][hand], before[hand]) > 0.03); + const seen = b.frames.find((frame) => frame.at > key.at && frame.fighters[viewerA].active && frame.fighters[viewerA].age < 8); + local.push(started ? started.at - key.at : null); moved.push(glove ? glove.at - key.at : null); remote.push(seen ? seen.at - key.at : null); + } + // Progress through the punch (0 at the press, 1 at contact, 2 at the end of the active phase, 3 when + // recovered), so a change in the server's timing is not mistaken for the glove going back. + const rewinds = punchKeys.map((key) => { + const window = a.frames.filter((frame) => frame.at > key.at && frame.at < key.at + 900 && frame.fighters[viewerA].active); + let worst = 0; let at = null; + for (let index = 1; index < window.length; index += 1) { + const drop = window[index - 1].fighters[viewerA].progress - window[index].fighters[viewerA].progress; + if (drop > worst) { worst = drop; at = Math.round(window[index].at - key.at); } + } + return { progress: Number(worst.toFixed(2)), atMs: at }; + }); + const timings = [...new Set(a.frames.filter((frame) => frame.fighters[viewerA].active).map((frame) => frame.fighters[viewerA].timing))]; + note('punch timings seen on the puncher (startup/active/recovery):', JSON.stringify(timings)); + // Glove-to-hit gap: when the puncher's glove is at full extension versus when the opponent's head reacts on the same screen. + const contacts = punchKeys.map((key) => { + const hand = key.code === 'KeyU' ? 'right' : 'left'; + const window = a.frames.filter((frame) => frame.at > key.at && frame.at < key.at + 900); + if (window.length === 0) return null; + const rest = frameAt(a.frames, key.at).fighters[viewerA][hand]; + let reach = 0; let extended = null; + for (const frame of window) { const d = distance(frame.fighters[viewerA][hand], rest); if (d > reach) { reach = d; extended = frame.at; } } + return extended === null ? null : Math.round(extended - key.at); + }); + note('own glove fully extended, ms after the key:', JSON.stringify(contacts), '| median', median(contacts)); + note('punch keys measured:', punchKeys.length, 'of', presses.length); + const sends = await A.page.evaluate(() => window.__actionSends ?? []); + const sent = punchKeys.map((key) => { const at = sends.find((time) => time >= key.at); return at === undefined ? null : Math.round(at - key.at); }); + note('press leaves the page, ms after the key:', JSON.stringify(sent), '| median', median(sent)); + if (sent.some((ms) => ms === null || ms > 25)) report.errors.push(`a press waited for the periodic input flush: ${JSON.stringify(sent)}`); + note('own punch rewinds (progress the animation went back, and when):', JSON.stringify(rewinds)); + note('own punch starts on screen, ms:', JSON.stringify(local.map((v) => (v === null ? null : Math.round(v)))), '| median', median(local)); + note('own glove has moved 3 cm, ms:', JSON.stringify(moved.map((v) => (v === null ? null : Math.round(v)))), '| median', median(moved)); + note('opponent sees the punch start, ms:', JSON.stringify(remote.map((v) => (v === null ? null : Math.round(v)))), '| median', median(remote)); + const step = a.keys.find((key) => key.code === 'KeyA'); + if (step) { + const before = frameAt(a.frames, step.at).fighters[viewerA]; + const own = a.frames.find((frame) => frame.at > step.at && Math.hypot(frame.fighters[viewerA].x - before.x, frame.fighters[viewerA].z - before.z) > 0.01); + const beforeRemote = frameAt(b.frames, step.at).fighters[viewerA]; + const other = b.frames.find((frame) => frame.at > step.at && Math.hypot(frame.fighters[viewerA].x - beforeRemote.x, frame.fighters[viewerA].z - beforeRemote.z) > 0.01); + note('own step starts on screen, ms:', own ? Math.round(own.at - step.at) : null, '| opponent sees it, ms:', other ? Math.round(other.at - step.at) : null); + } + const gaps = a.frames.slice(1).map((frame, index) => frame.at - a.frames[index].at); + note('frames sampled:', a.frames.length, '| median frame ms:', median(gaps), '| stats', JSON.stringify(await A.page.evaluate(() => window.__handsApp?.networkStats?.inputLatencyMs ?? null))); + const final = await waitFor(A.page, (s) => Boolean(s.final), 90000, 'final'); + note('FINAL:', JSON.stringify(final?.final ?? null).slice(0, 200)); + } + + if (scenario === 'clinch') { + const fighters = (page) => page.evaluate(() => (window.__handsApp?.state?.snapshot?.fighters ?? []).map((f) => ({ id: f.player_id, x: f.x, y: f.y, clinch: f.clinch_ticks }))); + const gap = (list) => (list.length === 2 ? Math.round(Math.hypot(list[1].x - list[0].x, list[1].y - list[0].y)) : null); + let started = Date.now(); + while (Date.now() - started < 15000) { + const g = gap(await fighters(A.page)); + if (g !== null && g <= 95) break; + await A.page.keyboard.down('d'); await B.page.keyboard.down('a'); await wait(150); await A.page.keyboard.up('d'); await B.page.keyboard.up('a'); + } + note('gap before clinch:', gap(await fighters(A.page))); + // Page evaluation and screenshots are slow under SwiftShader, so the page records the hold itself. + await B.page.evaluate(() => { + window.__clinchLog = []; + window.__clinchTimer = setInterval(() => { + const snapshot = window.__handsApp?.state?.snapshot; + const f = snapshot?.fighters ?? []; + if (f.length === 2) window.__clinchLog.push({ tick: snapshot.tick, gap: Math.round(Math.hypot(f[1].x - f[0].x, f[1].y - f[0].y)), clinch: f[0].clinch_ticks }); + }, 40); + }); + await A.page.keyboard.press('b'); + await wait(600); + for (let i = 0; i < 4; i += 1) await A.page.screenshot({ path: `${out}/e2e-clinch-A-${i}.png` }); + await wait(2000); + const log = await B.page.evaluate(() => { clearInterval(window.__clinchTimer); return window.__clinchLog; }); + const firstHeld = log.findIndex((s) => s.clinch > 0); + const held = log.filter((s) => s.clinch > 0); + const afterBreak = firstHeld < 0 ? null : log.slice(firstHeld).find((s) => s.clinch === 0); + note('clinch seen:', firstHeld >= 0, '| samples during hold:', held.length, '| gap on entry:', held[0]?.gap, '| min gap:', held.length ? Math.min(...held.map((s) => s.gap)) : null, '| last held gap:', held.at(-1)?.gap, '| gap after break:', afterBreak?.gap ?? null); + note('status A:', (await status(A.page)).status, '| B:', (await status(B.page)).status); + const final = await waitFor(A.page, (s) => Boolean(s.final), 90000, 'final'); + note('FINAL:', JSON.stringify(final?.final ?? null).slice(0, 200)); + } + + if (scenario === 'soak') { + const sample = (page) => page.evaluate(() => ({ + heapMb: typeof performance.memory === 'object' && performance.memory ? Math.round(performance.memory.usedJSHeapSize / 1048576) : null, + stats: window.__handsApp?.networkStats ?? null, + })); + const started = Date.now(); + const samples = []; + let step = 0; + let final = null; + while (Date.now() - started < 8 * 60 * 1000) { + const sA = await status(A.page); + if (sA.final) { final = sA; break; } + // A measured pace: a jab every few seconds behind a held guard keeps the bout going for three rounds. + if (step % 4 === 0) await A.page.keyboard.press('f'); + if (step % 4 === 2) await B.page.keyboard.press('j'); + await A.page.keyboard.down('q'); await B.page.keyboard.down('q'); await wait(700); await A.page.keyboard.up('q'); await B.page.keyboard.up('q'); + if (step % 6 === 0) { await A.page.keyboard.down('d'); await B.page.keyboard.down('a'); await wait(200); await A.page.keyboard.up('d'); await B.page.keyboard.up('a'); } + if (step % 7 === 3) { await A.page.keyboard.down('a'); await B.page.keyboard.down('d'); await wait(300); await A.page.keyboard.up('a'); await B.page.keyboard.up('d'); } + await wait(400); + step += 1; + if (step % 18 === 0) { + const [a, b] = [await sample(A.page), await sample(B.page)]; + samples.push({ t: Math.round((Date.now() - started) / 1000), a, b }); + note(`t=${samples.at(-1).t}s heap A ${a.heapMb} MB B ${b.heapMb} MB | latency A ${Math.round(a.stats?.inputLatencyMs ?? -1)} B ${Math.round(b.stats?.inputLatencyMs ?? -1)} | scale A ${a.stats?.resolutionScale} B ${b.stats?.resolutionScale} | ${sA.summary?.slice(0, 40)}`); + } + } + if (final === null) final = await waitFor(A.page, (s) => Boolean(s.final), 60000, 'final'); + note('FINAL:', JSON.stringify(final?.final ?? null).slice(0, 220)); + if (samples.length >= 2) note('heap growth A:', samples.at(-1).a.heapMb - samples[0].a.heapMb, 'MB; B:', samples.at(-1).b.heapMb - samples[0].b.heapMb, 'MB over', samples.at(-1).t - samples[0].t, 's'); + await A.page.screenshot({ path: `${out}/e2e-soak-A-final.png` }); + } + + report.errors.push(...A.errors, ...B.errors); + } finally { + server.child.kill('SIGTERM'); + server.proxy?.close(); + await browser.close(); + } + const serverErrors = server.log.join('').split('\n').filter((l) => /error|warning|Traceback/i.test(l) && !/healthz/.test(l)); + console.log('client errors:', JSON.stringify(report.errors.filter((e) => !/GL Driver/.test(e)).slice(0, 20), null, 1)); + console.log('server log lines of interest:', JSON.stringify(serverErrors.slice(0, 20), null, 1)); +} + +main().catch((e) => { console.error('ERR', e.stack || e.message); process.exit(1); }); diff --git a/scripts/hands_e2e_server.py b/scripts/hands_e2e_server.py new file mode 100644 index 00000000..f052933f --- /dev/null +++ b/scripts/hands_e2e_server.py @@ -0,0 +1,117 @@ +"""Run the Hands server locally without Discord so the real client can be played end to end. + +The real ``HandsAuth`` is subclassed so the OAuth ``begin``/``exchange`` steps become a local +handshake (``code`` is ``dev:``), while tickets, rooms, the websocket protocol, +the engine and persistence stay on the production code paths. The Vite dev server proxies +``/api/hands`` to this process (``HANDS_DEV_BACKEND``), and ``?e2e=1&instance_id=...&player=...`` +in the client selects the development authorizer. This authenticates anyone who can reach the +port: run it only on a local development machine. +""" + +from __future__ import annotations + +import argparse +import asyncio +import contextlib +import secrets +import signal +import zlib + +from intelstream.database.repository import Repository +from intelstream.hands.auth import ( + ActivityInstance, + AuthenticatedPlayer, + AuthExchange, + HandsAuth, + HandsAuthError, + validate_instance_id, +) +from intelstream.hands.engine import EngineConfig +from intelstream.hands.rooms import HandsRoomManager, RoomConfig +from intelstream.hands.server import HandsServer + +APPLICATION_ID = "100000000000000001" +GUILD_ID = "100000000000000002" +MAX_NAME_LENGTH = 32 + + +class DevAuth(HandsAuth): + def __init__(self) -> None: + super().__init__( + application_id=APPLICATION_ID, + guild_id=GUILD_ID, + client_secret="dev", + bot_token="dev", + ) + self._dev_states: dict[str, str] = {} + + async def begin(self, instance_id: object) -> tuple[str, ActivityInstance]: + instance = validate_instance_id(instance_id) + state = secrets.token_urlsafe(16) + self._dev_states[state] = instance + return state, ActivityInstance(instance, self.guild_id, "0", frozenset()) + + async def exchange(self, *, code: object, state: object) -> AuthExchange: + instance = self._dev_states.pop(state, None) if isinstance(state, str) else None + if instance is None: + raise HandsAuthError("invalid_state") + if not isinstance(code, str) or not code.startswith("dev:"): + raise HandsAuthError("invalid_request") + display_name = code[len("dev:") :].strip()[:MAX_NAME_LENGTH] or "Player" + user_id = str(10**17 + zlib.crc32(display_name.encode())) + player = AuthenticatedPlayer(user_id, self.guild_id, instance, display_name, None) + return AuthExchange("dev-access-token", self.issue_ticket(player), player) + + +async def run(args: argparse.Namespace) -> None: + repository = Repository("sqlite+aiosqlite:///:memory:") + await repository.initialize() + engine_config = EngineConfig( + rounds=args.rounds, + round_ticks=args.round_seconds * 30, + rest_ticks=args.rest_seconds * 30, + ) + server = HandsServer( + repository=repository, + application_id=APPLICATION_ID, + guild_id=GUILD_ID, + client_secret="dev", + bot_token="dev", + host="127.0.0.1", + port=args.port, + dev_mode=True, + auth=DevAuth(), + rooms=HandsRoomManager(repository, config=RoomConfig(engine_config=engine_config)), + ) + await server.start() + try: + print(f"hands e2e server listening on http://127.0.0.1:{server.bound_port}", flush=True) + stop = asyncio.Event() + loop = asyncio.get_running_loop() + for signal_number in (signal.SIGINT, signal.SIGTERM): + # Windows event loops have no signal handlers; Ctrl+C cancels the run there instead. + with contextlib.suppress(NotImplementedError): + loop.add_signal_handler(signal_number, stop.set) + await stop.wait() + finally: + await server.close() + await repository.close() + + +def parse_args(argv: list[str] | None = None) -> argparse.Namespace: + parser = argparse.ArgumentParser(description=__doc__.splitlines()[0]) + # Not 8080: that is the production server's port, which a live tunnel may forward. + parser.add_argument("--port", type=int, default=8091) + parser.add_argument("--rounds", type=int, default=3) + parser.add_argument("--round-seconds", type=int, default=120) + parser.add_argument("--rest-seconds", type=int, default=15) + return parser.parse_args(argv) + + +def main() -> None: + with contextlib.suppress(KeyboardInterrupt): + asyncio.run(run(parse_args())) + + +if __name__ == "__main__": + main() diff --git a/scripts/hands_pose_strip.js b/scripts/hands_pose_strip.js new file mode 100644 index 00000000..11734d49 --- /dev/null +++ b/scripts/hands_pose_strip.js @@ -0,0 +1,32 @@ +/** + * Frame strips from the pose lab for reviewing motion, not just single poses. + * + * Requires Playwright with Chromium and pngjs on NODE_PATH (web/hands/node_modules has pngjs), + * and the Vite dev server on http://localhost:5173. Renders the given pose frozen at each time + * and writes the frames side by side. + * + * node scripts/hands_pose_strip.js hook_left "0.15,0.27,0.37,0.45,0.52,0.6,0.72,0.9" strip.png "&cam=top" + */ +const { chromium } = require('playwright'); +const { PNG } = require('pngjs'); +const fs = require('node:fs'); +const [,, pose, timesCsv, out, extra = ''] = process.argv; +const times = timesCsv.split(',').map(Number); +const SIZE = 420; +(async () => { + const browser = await chromium.launch({ args: ['--use-gl=angle', '--use-angle=swiftshader', '--enable-unsafe-swiftshader', '--ignore-gpu-blocklist'] }); + const page = await browser.newPage({ viewport: { width: SIZE, height: SIZE } }); + const strip = new PNG({ width: SIZE * times.length, height: SIZE }); + const debug = []; + for (const [index, t] of times.entries()) { + await page.goto(`http://localhost:5173/?model-lab=1&pose=${pose}&freeze=${t}${extra}`, { waitUntil: 'load' }); + await page.waitForTimeout(2600); + const frame = PNG.sync.read(await page.screenshot({ type: 'png' })); + for (let y = 0; y < SIZE; y += 1) frame.data.copy(strip.data, (y * strip.width + index * SIZE) * 4, y * frame.width * 4, (y * frame.width + SIZE) * 4); + const info = await page.evaluate(() => window.__poseLab ?? null); + debug.push({ t, gloveL: info?.gloveL, gloveR: info?.gloveR }); + } + fs.writeFileSync(out, PNG.sync.write(strip)); + console.log(JSON.stringify(debug)); + await browser.close(); +})().catch((e) => { console.error('ERR', e.message); process.exit(1); }); diff --git a/src/intelstream/database/repository.py b/src/intelstream/database/repository.py index f0feab7a..df896b56 100644 --- a/src/intelstream/database/repository.py +++ b/src/intelstream/database/repository.py @@ -37,7 +37,12 @@ SourceType, SuckBoobsStats, ) -from intelstream.hands.rating import DEFAULT_RATING, calculate_elo +from intelstream.hands.rating import ( + DEFAULT_RATING, + REPEAT_PAIRING_WINDOW, + calculate_elo, + repeat_pairing_k_factor, +) from intelstream.hands.types import FinishMethod, MatchResult logger = structlog.get_logger() @@ -976,7 +981,30 @@ async def _record_hands_match_locked(self, match_result: MatchResult) -> HandsMa if match_result.winner_id is None else (1.0 if match_result.winner_id == one.user_id else 0.0) ) - elo = calculate_elo(one.rating, two.rating, one_score) + earlier_bouts = await session.scalar( + select(func.count()) + .select_from(HandsMatch) + .where( + HandsMatch.guild_id == match_result.guild_id, + HandsMatch.created_at >= datetime.now(UTC) - REPEAT_PAIRING_WINDOW, + or_( + and_( + HandsMatch.player_one_id == one.user_id, + HandsMatch.player_two_id == two.user_id, + ), + and_( + HandsMatch.player_one_id == two.user_id, + HandsMatch.player_two_id == one.user_id, + ), + ), + ) + ) + elo = calculate_elo( + one.rating, + two.rating, + one_score, + k_factor=repeat_pairing_k_factor(int(earlier_bouts or 0)), + ) scorecard_json = json.dumps( [ { diff --git a/src/intelstream/hands/combat-manifest.json b/src/intelstream/hands/combat-manifest.json index aa08d456..68610775 100644 --- a/src/intelstream/hands/combat-manifest.json +++ b/src/intelstream/hands/combat-manifest.json @@ -1,9 +1,9 @@ { - "format": 1, + "format": 2, "tick_rate": 30, "ring": { "half_width": 500, - "half_height": 330, + "half_height": 500, "fighter_radius": 38 }, "limits": { @@ -13,6 +13,39 @@ "max_poise": 600 }, "action_buffer_ticks": 6, + "facing": { + "scale": 1000, + "turn_percent_per_update": 35 + }, + "combos": { + "recovery_cancel_percent": 50, + "chains": [ + [ + "jab", + "straight" + ], + [ + "jab", + "hook" + ], + [ + "straight", + "hook" + ], + [ + "hook", + "uppercut" + ], + [ + "uppercut", + "hook" + ] + ] + }, + "knockdown": { + "neutral_separation": 230, + "referee_walk_speed": 4 + }, "hitstop_ms": { "hit": 78, "block": 45 @@ -118,8 +151,29 @@ } }, "hurtboxes": { - "head": { "radius": 0.13, "length": 0.16, "joint": "head", "offset_y": 0.12 }, - "torso": { "radius": 0.21, "length": 0.34, "joint": "chest", "offset_y": 0.16 } + "head": { + "radius": 0.13, + "length": 0.16, + "joint": "head", + "offset_y": 0.12 + }, + "torso": { + "radius": 0.21, + "length": 0.34, + "joint": "chest", + "offset_y": 0.16 + } + }, + "corners": { + "reach": 733 + }, + "rest": { + "corner_offset": 365, + "walk_speed": 5 + }, + "clinch": { + "hold_distance": 60, + "draw_speed": 6 }, "hitbox": { "glove_radius": 0.11 diff --git a/src/intelstream/hands/engine.py b/src/intelstream/hands/engine.py index 805ad4d7..778379f1 100644 --- a/src/intelstream/hands/engine.py +++ b/src/intelstream/hands/engine.py @@ -9,18 +9,28 @@ from typing import Final from intelstream.hands.rules import ( + CLINCH_DRAW_SPEED, + CLINCH_HOLD_DISTANCE, COMPATIBLE_COMBO_CHAINS, COUNTDOWN_TICKS, DEFAULT_ROUNDS, + FACING_SCALE, + FACING_TURN_PERCENT, FIGHTER_RADIUS, JUDGE_PROFILES, + KNOCKDOWN_NEUTRAL_SEPARATION, MAX_CONDITIONING, MAX_GUARD, MAX_POISE, MAX_STAMINA, MINIMUM_SEPARATION, PUNCH_RULES, + RECOVERY_CANCEL_PERCENT, + REFEREE_WALK_SPEED, + REST_CORNER_OFFSET, REST_TICKS, + REST_WALK_SPEED, + RING_CORNER_REACH, RING_HALF_HEIGHT, RING_HALF_WIDTH, ROUND_TICKS, @@ -56,6 +66,27 @@ PERFECT_BLOCK_TICKS: Final = 4 EVASION_TICKS: Final = 10 COUNTER_WINDOW_TICKS: Final = 18 +ROPE_OVERLAP_PASSES: Final = 8 +ROPE_OVERLAP_STEP: Final = 8 +NEUTRAL_WALK_MARGIN: Final = 6 +_COMPASS: Final = ( + (1000, 0), + (924, 383), + (707, 707), + (383, 924), + (0, 1000), + (-383, 924), + (-707, 707), + (-924, 383), + (-1000, 0), + (-924, -383), + (-707, -707), + (-383, -924), + (0, -1000), + (383, -924), + (707, -707), + (924, -383), +) CLINCH_STARTUP_TICKS: Final = 8 CLINCH_TICKS: Final = 45 FOUL_RECOVERY_TICKS: Final = 60 @@ -105,6 +136,7 @@ class AttackState: rule: PunchRule age: int = 0 resolved: bool = False + landed: bool = False combo_bonus: int = 0 start_tick: int = 0 contact_tick: int = 0 @@ -113,6 +145,14 @@ class AttackState: def total_ticks(self) -> int: return self.rule.startup + self.rule.active + self.rule.recovery + @property + def cancel_age(self) -> int: + return ( + self.rule.startup + + self.rule.active + + self.rule.recovery * RECOVERY_CANCEL_PERCENT // 100 + ) + @dataclass(slots=True) class RoundPerformance: @@ -132,6 +172,8 @@ class FighterState: y: int facing: int stance: Stance + facing_x: int = 0 + facing_y: int = 0 velocity_x: int = 0 velocity_y: int = 0 velocity_fixed_x: int = 0 @@ -179,6 +221,10 @@ class FighterState: damage_dealt: int = 0 movement_load: int = 0 + def __post_init__(self) -> None: + if self.facing_x == 0 and self.facing_y == 0: + self.facing_x = FACING_SCALE if self.facing >= 0 else -FACING_SCALE + @property def maximum_stamina(self) -> int: return fatigue_max_stamina(self.conditioning, self.trauma.body) @@ -233,6 +279,24 @@ def _symmetric_divide(numerator: int, denominator: int) -> int: return magnitude if numerator >= 0 else -magnitude +def _separation_along_axis(across: int) -> int: + """Distance to open along one axis so two fighters `across` apart on the other just clear. + + Opening the full separation on one axis regardless of the other threw fighters who met at an + angle well apart, so they closed and were thrown apart again for as long as they pressed. + """ + needed = MINIMUM_SEPARATION * MINIMUM_SEPARATION - across * across + if needed <= 0: + return 0 + root = isqrt(needed) + return root if root * root == needed else root + 1 + + +def _away_divide(numerator: int, denominator: int) -> int: + magnitude = -(-abs(numerator) // denominator) + return magnitude if numerator >= 0 else -magnitude + + def _normalize_move_vector(move_x: int, move_y: int) -> tuple[int, int]: squared_magnitude = move_x * move_x + move_y * move_y if squared_magnitude <= 1_000_000: @@ -268,6 +332,32 @@ def _consume_fixed_position(velocity: int, remainder: int) -> tuple[int, int]: return delta, total - delta * MOVEMENT_FIXED_SCALE +def _ring_point(x: int, y: int) -> tuple[int, int, bool, bool, bool]: + """Nearest point inside the ropes and corner pads. + + Also reports which of the x rope, the y rope and the corner cut stopped the point. At the end + of a cut, where it meets a rope, both are reported. + """ + limit_x = RING_HALF_WIDTH - FIGHTER_RADIUS + limit_y = RING_HALF_HEIGHT - FIGHTER_RADIUS + sign_x = -1 if x < 0 else 1 + sign_y = -1 if y < 0 else 1 + reach_x, reach_y = abs(x), abs(y) + inside_x, inside_y = min(reach_x, limit_x), min(reach_y, limit_y) + if inside_x + inside_y <= RING_CORNER_REACH: + return sign_x * inside_x, sign_y * inside_y, reach_x > limit_x, reach_y > limit_y, False + excess = reach_x + reach_y - RING_CORNER_REACH + if reach_x >= reach_y: + cut_x, cut_y = reach_x - (excess + 1) // 2, reach_y - excess // 2 + else: + cut_x, cut_y = reach_x - excess // 2, reach_y - (excess + 1) // 2 + if cut_y > limit_y: + return sign_x * (RING_CORNER_REACH - limit_y), sign_y * limit_y, False, True, True + if cut_x > limit_x: + return sign_x * limit_x, sign_y * (RING_CORNER_REACH - limit_x), True, False, True + return sign_x * cut_x, sign_y * cut_y, False, False, True + + def _canonical(value: object) -> object: if isinstance(value, Enum): return value.value @@ -343,6 +433,10 @@ def clear_action_buffers(self) -> None: fighter.pending_actions.clear() fighter.pending_action_expires_tick = 0 + def clear_held_input(self) -> None: + for fighter in self._fighters.values(): + fighter.held_input = InputCommand(0, 0) + def submit_input(self, player_id: str, command: InputCommand) -> bool: fighter = self.fighter(player_id) if self.result is not None or self.phase is MatchPhase.COMPLETE: @@ -413,6 +507,8 @@ def _advance_fight(self) -> None: two = self._fighters[self._player_ids[1]] one.movement_load = 0 two.movement_load = 0 + # The facing blends toward the opponent here and again after each fighter's footwork + # (`_move_fighter`), so in the fight phase it turns about 58% of the way per tick. self._update_facing(one, two) self._update_facing(two, one) @@ -474,7 +570,11 @@ def _process_fighter(self, fighter: FighterState, opponent: FighterState) -> Non fighter.defense_started_tick = self.tick fighter.defense = fighter.held_input.defense - if fighter.pending_actions and self.tick > fighter.pending_action_expires_tick: + if ( + fighter.pending_actions + and fighter.attack is None + and self.tick > fighter.pending_action_expires_tick + ): fighter.pending_actions.clear() fighter.pending_action_expires_tick = 0 @@ -489,7 +589,10 @@ def _process_fighter(self, fighter: FighterState, opponent: FighterState) -> Non self._resolve_punch(fighter, opponent, attack) if fighter.stunned_ticks > 0 or attack.age >= attack.total_ticks: self._retain_action(fighter) - return + return + if not self._can_cancel_recovery(fighter, opponent, attack): + return + self._retain_action(fighter) if fighter.taunt_ticks > 0: fighter.taunt_ticks -= 1 @@ -517,6 +620,25 @@ def _attack_lands_next_tick(attack: AttackState) -> bool: and attack.rule.startup <= next_age < attack.rule.startup + attack.rule.active ) + @staticmethod + def _can_cancel_recovery( + fighter: FighterState, opponent: FighterState, attack: AttackState + ) -> bool: + if not attack.landed or attack.age < attack.cancel_age or not fighter.pending_actions: + return False + if opponent.stunned_ticks > 0: + # A stunned man is already open. Cutting the recovery short would only chain stun + # into stun before he has a tick to answer. + return False + follow_up = fighter.pending_actions[0] + return ( + isinstance(follow_up, PunchAction) + and (attack.action.punch_class, follow_up.punch_class) in COMPATIBLE_COMBO_CHAINS + # `_start_punch` refuses a punch the fighter cannot pay for in full. + and fighter.stamina + >= PUNCH_RULES[(follow_up.punch_class, follow_up.target, follow_up.power)].stamina_cost + ) + def _start_punch(self, fighter: FighterState, action: PunchAction) -> bool: base_rule = PUNCH_RULES[(action.punch_class, action.target, action.power)] cost = base_rule.stamina_cost @@ -589,6 +711,8 @@ def _retain_action(self, fighter: FighterState) -> None: fighter.last_action_contact_tick = attack.contact_tick if attack.resolved else 0 fighter.last_action_until_tick = self.tick + 15 fighter.attack = None + if fighter.pending_actions: + fighter.pending_action_expires_tick = self.tick + ACTION_BUFFER_TICKS def _resolve_punch( self, attacker: FighterState, defender: FighterState, attack: AttackState @@ -604,13 +728,13 @@ def _resolve_punch( ) effective_reach = rule.reach * (100 - vision_penalty) // 100 effective_arc = rule.lateral_arc * (100 - vision_penalty) // 100 - forward_distance = dx * attacker.facing + forward_distance, lateral_distance = self._facing_components(attacker, dx, dy) in_front = forward_distance > FIGHTER_RADIUS // 3 if ( not in_front or forward_distance > effective_reach or distance_squared > effective_reach**2 - or abs(dy) > effective_arc + or lateral_distance > effective_arc ): attacker.stamina = max(0, attacker.stamina - rule.whiff_cost) attacker.conditioning = max(0, attacker.conditioning - max(2, rule.whiff_cost // 10)) @@ -623,7 +747,10 @@ def _resolve_punch( ) return - if self._evades(defender, action, distance_squared, rule.reach, abs(dy)): + # The facing holds still through a punch, so this is how far the defender is off the line + # the punch was thrown along. Only off that line can he weave a body hook or slip a body + # uppercut. + if self._evades(defender, action, distance_squared, rule.reach, lateral_distance): defender.performance.evasions += 1 defender.counter_ticks = COUNTER_WINDOW_TICKS self._emit( @@ -636,6 +763,8 @@ def _resolve_punch( ) or (action.target is Target.BODY and defender.defense is DefensivePose.GUARD_LOW) perfect = guarding and self.tick - defender.defense_started_tick <= PERFECT_BLOCK_TICKS counter = attacker.counter_ticks > 0 or self._counter_vulnerable(defender.attack) + # A combination flows through a blocked punch but not a parried one. + attack.landed = not perfect fatigue = attacker.fatigue counter_multiplier = 128 if counter else 100 impact = ( @@ -729,7 +858,9 @@ def _resolve_punch( action.target is Target.HEAD and defender.trauma.head > 850 and damage >= 40 ): self._knock_down(defender, attacker) - elif action.target is Target.HEAD and damage >= 36: + elif action.target is Target.HEAD and damage >= 36 and defender.stunned_ticks == 0: + # A punch on a man who is still stunned does not start his stun again, so a run of + # punches cannot hold him past the first stun. defender.stunned_ticks = min(90, 8 + damage // 2) defender.stunned_at_tick = self.tick defender.taunt_ticks = 0 @@ -855,6 +986,12 @@ def _advance_clinch_attempt(self, fighter: FighterState, opponent: FighterState) opponent.clinch_startup_ticks = 0 fighter.clinch_ticks = CLINCH_TICKS opponent.clinch_ticks = CLINCH_TICKS + for held in (fighter, opponent): + # Tied up, neither walks on. Only the draw moves them now, and the speed they came in + # with must not count as pressure or carry their feet through the hold. + held.velocity_x = held.velocity_y = 0 + held.velocity_fixed_x = held.velocity_fixed_y = 0 + held.position_remainder_x = held.position_remainder_y = 0 self._retain_action(fighter) self._retain_action(opponent) fighter.pending_actions.clear() @@ -911,14 +1048,35 @@ def _advance_clinch(self, one: FighterState, two: FighterState) -> None: two.stamina = min(two.maximum_stamina, two.stamina + 1) one.conditioning = max(0, one.conditioning - (1 if self.tick % 10 == 0 else 0)) two.conditioning = max(0, two.conditioning - (1 if self.tick % 10 == 0 else 0)) + if remaining > 0: + self._draw_clinch_together(one, two) if remaining == 0: - one.x -= one.facing * 45 - two.x -= two.facing * 45 + for fighter in (one, two): + fighter.x -= _symmetric_divide(fighter.facing_x * 45, FACING_SCALE) + fighter.y -= _symmetric_divide(fighter.facing_y * 45, FACING_SCALE) self._clamp_to_ring(one) self._clamp_to_ring(two) self._separate_fighters(one, two) self._emit("referee_break", one.player_id, two.player_id) + def _draw_clinch_together(self, one: FighterState, two: FighterState) -> None: + dx = two.x - one.x + dy = two.y - one.y + distance = isqrt(dx * dx + dy * dy) + if distance <= CLINCH_HOLD_DISTANCE: + return + step = min(CLINCH_DRAW_SPEED, (distance - CLINCH_HOLD_DISTANCE) // 2) + if step == 0: + return + move_x = _symmetric_divide(dx * step, distance) + move_y = _symmetric_divide(dy * step, distance) + one.x += move_x + one.y += move_y + two.x -= move_x + two.y -= move_y + self._clamp_to_ring(one) + self._clamp_to_ring(two) + def _move_fighter(self, fighter: FighterState, opponent: FighterState) -> None: move_x = fighter.held_input.move_x move_y = fighter.held_input.move_y @@ -995,33 +1153,48 @@ def _move_fighter(self, fighter: FighterState, opponent: FighterState) -> None: @staticmethod def _clamp_to_ring(fighter: FighterState) -> None: - minimum_x = -RING_HALF_WIDTH + FIGHTER_RADIUS - maximum_x = RING_HALF_WIDTH - FIGHTER_RADIUS - minimum_y = -RING_HALF_HEIGHT + FIGHTER_RADIUS - maximum_y = RING_HALF_HEIGHT - FIGHTER_RADIUS - clamped_x = min(maximum_x, max(minimum_x, fighter.x)) - clamped_y = min(maximum_y, max(minimum_y, fighter.y)) - if clamped_x != fighter.x: - fighter.velocity_x = 0 - fighter.velocity_fixed_x = 0 - fighter.position_remainder_x = 0 - if clamped_y != fighter.y: - fighter.velocity_y = 0 - fighter.velocity_fixed_y = 0 - fighter.position_remainder_y = 0 - fighter.x = clamped_x - fighter.y = clamped_y + x, y, rope_x, rope_y, corner = _ring_point(fighter.x, fighter.y) + if corner and (rope_x or rope_y): + # Wedged where the corner pad meets a rope: nowhere left to slide. + fighter.velocity_x = fighter.velocity_y = 0 + fighter.velocity_fixed_x = fighter.velocity_fixed_y = 0 + fighter.position_remainder_x = fighter.position_remainder_y = 0 + elif corner: + # Against the corner pad: lose the speed into it, keep the speed along it. + sign_x = -1 if x < 0 else 1 + sign_y = -1 if y < 0 else 1 + outward = sign_x * fighter.velocity_fixed_x + sign_y * fighter.velocity_fixed_y + if outward > 0: + half = (outward + 1) // 2 + fighter.velocity_fixed_x -= sign_x * half + fighter.velocity_fixed_y -= sign_y * half + fighter.velocity_x = _rounded_fixed_velocity(fighter.velocity_fixed_x) + fighter.velocity_y = _rounded_fixed_velocity(fighter.velocity_fixed_y) + fighter.position_remainder_x = fighter.position_remainder_y = 0 + else: + if rope_x: + fighter.velocity_x = 0 + fighter.velocity_fixed_x = 0 + fighter.position_remainder_x = 0 + if rope_y: + fighter.velocity_y = 0 + fighter.velocity_fixed_y = 0 + fighter.position_remainder_y = 0 + fighter.x = x + fighter.y = y def _separate_fighters(self, one: FighterState, two: FighterState) -> None: dx = two.x - one.x dy = two.y - one.y if dx * dx + dy * dy >= MINIMUM_SEPARATION**2: return + before = (one.x, one.y, two.x, two.y) if abs(dx) >= abs(dy): direction = 1 if dx > 0 or (dx == 0 and one.player_id < two.player_id) else -1 center = (one.x + two.x) // 2 - one.x = center - direction * (MINIMUM_SEPARATION // 2) - two.x = center + direction * (MINIMUM_SEPARATION // 2) + apart = _separation_along_axis(dy) + one.x = center - direction * (apart // 2) + two.x = center + direction * (apart - apart // 2) minimum = -RING_HALF_WIDTH + FIGHTER_RADIUS maximum = RING_HALF_WIDTH - FIGHTER_RADIUS shift = max(0, minimum - min(one.x, two.x)) - max(0, max(one.x, two.x) - maximum) @@ -1030,19 +1203,99 @@ def _separate_fighters(self, one: FighterState, two: FighterState) -> None: else: direction = 1 if dy > 0 or (dy == 0 and one.player_id < two.player_id) else -1 center = (one.y + two.y) // 2 - one.y = center - direction * (MINIMUM_SEPARATION // 2) - two.y = center + direction * (MINIMUM_SEPARATION // 2) + apart = _separation_along_axis(dx) + one.y = center - direction * (apart // 2) + two.y = center + direction * (apart - apart // 2) minimum = -RING_HALF_HEIGHT + FIGHTER_RADIUS maximum = RING_HALF_HEIGHT - FIGHTER_RADIUS shift = max(0, minimum - min(one.y, two.y)) - max(0, max(one.y, two.y) - maximum) one.y += shift two.y += shift + pushed = (one.x, one.y, two.x, two.y) self._clamp_to_ring(one) self._clamp_to_ring(two) + if (one.x, one.y, two.x, two.y) != pushed: + # A corner pad refused part of the push. Start again from where they met, so the + # same fighter gives way by the same amount every tick they keep pressing. + one.x, one.y, two.x, two.y = before + self._clamp_to_ring(one) + self._clamp_to_ring(two) + self._resolve_rope_overlap(one, two) + + def _resolve_rope_overlap(self, one: FighterState, two: FighterState) -> None: + """Parts two fighters the ropes pushed back together. + + The fighter nearer the ring centre has room, so he gives way along the line between them + by exactly the distance that is missing. + """ + for _ in range(ROPE_OVERLAP_PASSES): + dx = two.x - one.x + dy = two.y - one.y + squared = dx * dx + dy * dy + if squared >= MINIMUM_SEPARATION**2: + return + if squared == 0: + dx, dy, squared = (1 if one.player_id < two.player_id else -1), 0, 1 + distance = isqrt(squared) + missing = MINIMUM_SEPARATION - distance + push_x = _away_divide(dx * missing, distance) + push_y = _away_divide(dy * missing, distance) + if abs(one.x) + abs(one.y) <= abs(two.x) + abs(two.y): + one.x -= push_x + one.y -= push_y + else: + two.x += push_x + two.y += push_y + self._clamp_to_ring(one) + self._clamp_to_ring(two) + for _ in range(ROPE_OVERLAP_PASSES): + dx = two.x - one.x + dy = two.y - one.y + if dx * dx + dy * dy >= MINIMUM_SEPARATION**2: + return + inner = one if abs(one.x) + abs(one.y) <= abs(two.x) + abs(two.y) else two + inner.x -= ROPE_OVERLAP_STEP if inner.x > 0 else -ROPE_OVERLAP_STEP + inner.y -= ROPE_OVERLAP_STEP if inner.y > 0 else -ROPE_OVERLAP_STEP + self._clamp_to_ring(one) + self._clamp_to_ring(two) def _update_facing(self, fighter: FighterState, opponent: FighterState) -> None: - if fighter.attack is None and fighter.clinch_startup_ticks == 0: - fighter.facing = 1 if opponent.x >= fighter.x else -1 + if fighter.attack is not None or fighter.clinch_startup_ticks: + return + dx = opponent.x - fighter.x + dy = opponent.y - fighter.y + distance = isqrt(dx * dx + dy * dy) + if distance == 0: + return + desired_x = _symmetric_divide(dx * FACING_SCALE, distance) + desired_y = _symmetric_divide(dy * FACING_SCALE, distance) + if fighter.facing_x * desired_x + fighter.facing_y * desired_y < -( + FACING_SCALE * FACING_SCALE * 9 // 10 + ): + # Anti-parallel facings would blend through the origin; turn via the perpendicular. + fighter.facing_x, fighter.facing_y = ( + fighter.facing_x - _symmetric_divide(fighter.facing_y * FACING_TURN_PERCENT, 100), + fighter.facing_y + _symmetric_divide(fighter.facing_x * FACING_TURN_PERCENT, 100), + ) + fighter.facing_x += _symmetric_divide( + (desired_x - fighter.facing_x) * FACING_TURN_PERCENT, 100 + ) + fighter.facing_y += _symmetric_divide( + (desired_y - fighter.facing_y) * FACING_TURN_PERCENT, 100 + ) + length = isqrt(fighter.facing_x**2 + fighter.facing_y**2) + if length == 0: + fighter.facing_x, fighter.facing_y = desired_x, desired_y + else: + fighter.facing_x = _symmetric_divide(fighter.facing_x * FACING_SCALE, length) + fighter.facing_y = _symmetric_divide(fighter.facing_y * FACING_SCALE, length) + fighter.facing = 1 if fighter.facing_x >= 0 else -1 + + @staticmethod + def _facing_components(fighter: FighterState, dx: int, dy: int) -> tuple[int, int]: + forward = _symmetric_divide(dx * fighter.facing_x + dy * fighter.facing_y, FACING_SCALE) + lateral = abs(dx * fighter.facing_y - dy * fighter.facing_x) // FACING_SCALE + return forward, lateral def _recover_resources(self, fighter: FighterState) -> None: active = ( @@ -1067,7 +1320,10 @@ def _ring_control(fighter: FighterState, opponent: FighterState) -> int: fighter_center = abs(fighter.x) + abs(fighter.y) opponent_center = abs(opponent.x) + abs(opponent.y) position = 1 if fighter_center + 30 < opponent_center else 0 - forward_motion = fighter.velocity_x * fighter.facing + forward_motion = _symmetric_divide( + fighter.velocity_x * fighter.facing_x + fighter.velocity_y * fighter.facing_y, + FACING_SCALE, + ) effective_pressure = 1 if forward_motion > 1 and fighter.attack is None else 0 return position + effective_pressure @@ -1188,6 +1444,7 @@ def _advance_knockdown(self) -> None: winner.pending_actions.clear() self.phase_ticks_remaining -= 1 self._knockdown_count_ticks += 1 + self._walk_to_neutral_corner(winner, downed) while downed.pending_actions: action = downed.pending_actions.pop(0) if isinstance(action, MovementAction): @@ -1200,8 +1457,7 @@ def _advance_knockdown(self) -> None: downed.poise = MAX_POISE // 2 downed.stamina = min(downed.maximum_stamina, 350) downed.stunned_ticks = 20 - downed.x = -140 if downed.facing == 1 else 140 - self._clamp_to_ring(downed) + self._separate_fighters(downed, winner) self.phase = MatchPhase.FIGHT self.phase_ticks_remaining = max(1, self._paused_fight_ticks) self._downed_id = None @@ -1212,6 +1468,96 @@ def _advance_knockdown(self) -> None: elif self._knockdown_count_ticks % COUNT_TICK_INTERVAL == 0: self._emit("count", target_id=downed.player_id, amount=count) + def _walk_to_neutral_corner(self, winner: FighterState, downed: FighterState) -> None: + dx = winner.x - downed.x + dy = winner.y - downed.y + distance = isqrt(dx * dx + dy * dy) + if distance >= KNOCKDOWN_NEUTRAL_SEPARATION: + winner.velocity_x = winner.velocity_y = 0 + winner.velocity_fixed_x = winner.velocity_fixed_y = 0 + winner.position_remainder_x = winner.position_remainder_y = 0 + self._update_facing(winner, downed) + return + if distance == 0: + step_x, step_y = winner.facing_x, winner.facing_y + else: + step_x = _symmetric_divide(dx * FACING_SCALE, distance) + step_y = _symmetric_divide(dy * FACING_SCALE, distance) + step_x, step_y = self._neutral_walk_step(winner, downed, step_x, step_y) + winner.velocity_fixed_x = step_x * REFEREE_WALK_SPEED + winner.velocity_fixed_y = step_y * REFEREE_WALK_SPEED + winner.velocity_x = _rounded_fixed_velocity(winner.velocity_fixed_x) + winner.velocity_y = _rounded_fixed_velocity(winner.velocity_fixed_y) + delta_x, winner.position_remainder_x = _consume_fixed_position( + winner.velocity_fixed_x, winner.position_remainder_x + ) + delta_y, winner.position_remainder_y = _consume_fixed_position( + winner.velocity_fixed_y, winner.position_remainder_y + ) + winner.x += delta_x + winner.y += delta_y + self._clamp_to_ring(winner) + self._update_facing(winner, downed) + + @staticmethod + def _neutral_walk_step( + winner: FighterState, downed: FighterState, step_x: int, step_y: int + ) -> tuple[int, int]: + """Direction for the walk to neutral distance. + + Straight away from the downed fighter while the spot that leads to is inside the ropes. + A winner with his back to the ropes or a corner walks to the nearest open spot at that + distance instead, by a line that does not take him over the man on the canvas. + """ + radius = KNOCKDOWN_NEUTRAL_SEPARATION + NEUTRAL_WALK_MARGIN + + def spot(direction_x: int, direction_y: int) -> tuple[int, int]: + return ( + downed.x + _symmetric_divide(direction_x * radius, FACING_SCALE), + downed.y + _symmetric_divide(direction_y * radius, FACING_SCALE), + ) + + def is_open(point: tuple[int, int]) -> bool: + x, y, _, _, _ = _ring_point(point[0], point[1]) + return (x, y) == point + + def clears_downed(point: tuple[int, int]) -> bool: + path_x, path_y = point[0] - winner.x, point[1] - winner.y + length_squared = path_x * path_x + path_y * path_y + if length_squared == 0: + return True + along = (downed.x - winner.x) * path_x + (downed.y - winner.y) * path_y + along = min(max(along, 0), length_squared) + nearest_x = winner.x + _symmetric_divide(path_x * along, length_squared) + nearest_y = winner.y + _symmetric_divide(path_y * along, length_squared) + gap = (nearest_x - downed.x) ** 2 + (nearest_y - downed.y) ** 2 + return gap >= (MINIMUM_SEPARATION - NEUTRAL_WALK_MARGIN) ** 2 + + if is_open(spot(step_x, step_y)): + return step_x, step_y + chosen: tuple[int, int] | None = None + nearest = 0 + for clear_path in (True, False): + for direction_x, direction_y in _COMPASS: + point = spot(direction_x, direction_y) + if not is_open(point) or (clear_path and not clears_downed(point)): + continue + gap = (point[0] - winner.x) ** 2 + (point[1] - winner.y) ** 2 + if chosen is None or gap < nearest: + chosen, nearest = point, gap + if chosen is not None: + break + if chosen is None: + return step_x, step_y + path_x, path_y = chosen[0] - winner.x, chosen[1] - winner.y + length = isqrt(path_x * path_x + path_y * path_y) + if length == 0: + return 0, 0 + return ( + _symmetric_divide(path_x * FACING_SCALE, length), + _symmetric_divide(path_y * FACING_SCALE, length), + ) + def _finish_round(self) -> None: one = self._fighters[self._player_ids[0]] two = self._fighters[self._player_ids[1]] @@ -1224,14 +1570,31 @@ def _finish_round(self) -> None: if self.round_number >= self.config.rounds: self._finish_decision() return + for fighter in self._fighters.values(): + # The bell ends whatever was held. Clients stop sending between rounds, so a walk or a + # guard held at the bell would otherwise carry the fighter into the next round. + fighter.held_input = InputCommand(0, 0) if self.config.rest_ticks == 0: self._start_next_round() else: self.phase = MatchPhase.REST self.phase_ticks_remaining = self.config.rest_ticks + for fighter in self._fighters.values(): + fighter.attack = None + fighter.pending_actions.clear() + fighter.clinch_startup_ticks = 0 + fighter.clinch_ticks = 0 + fighter.stunned_ticks = 0 + fighter.taunt_ticks = 0 + fighter.defense = DefensivePose.NONE def _advance_rest(self) -> None: self.phase_ticks_remaining -= 1 + one = self._fighters[self._player_ids[0]] + two = self._fighters[self._player_ids[1]] + self._walk_to_corner(one, -REST_CORNER_OFFSET, -REST_CORNER_OFFSET, two) + self._walk_to_corner(two, REST_CORNER_OFFSET, REST_CORNER_OFFSET, one) + self._separate_fighters(one, two) for fighter in self._fighters.values(): fighter.stamina = min(fighter.maximum_stamina, fighter.stamina + 3) fighter.guard = min(MAX_GUARD, fighter.guard + 2) @@ -1241,6 +1604,37 @@ def _advance_rest(self) -> None: if self.phase_ticks_remaining <= 0: self._start_next_round() + def _walk_to_corner( + self, fighter: FighterState, corner_x: int, corner_y: int, opponent: FighterState + ) -> None: + dx = corner_x - fighter.x + dy = corner_y - fighter.y + distance = isqrt(dx * dx + dy * dy) + if distance <= REST_WALK_SPEED: + fighter.x, fighter.y = corner_x, corner_y + fighter.velocity_x = fighter.velocity_y = 0 + fighter.velocity_fixed_x = fighter.velocity_fixed_y = 0 + fighter.position_remainder_x = fighter.position_remainder_y = 0 + self._update_facing(fighter, opponent) + return + step_x = _symmetric_divide(dx * FACING_SCALE, distance) + step_y = _symmetric_divide(dy * FACING_SCALE, distance) + fighter.velocity_fixed_x = step_x * REST_WALK_SPEED + fighter.velocity_fixed_y = step_y * REST_WALK_SPEED + fighter.velocity_x = _rounded_fixed_velocity(fighter.velocity_fixed_x) + fighter.velocity_y = _rounded_fixed_velocity(fighter.velocity_fixed_y) + delta_x, fighter.position_remainder_x = _consume_fixed_position( + fighter.velocity_fixed_x, fighter.position_remainder_x + ) + delta_y, fighter.position_remainder_y = _consume_fixed_position( + fighter.velocity_fixed_y, fighter.position_remainder_y + ) + fighter.x += delta_x + fighter.y += delta_y + self._clamp_to_ring(fighter) + fighter.facing_x, fighter.facing_y = step_x, step_y + fighter.facing = 1 if fighter.facing_x >= 0 else -1 + def _start_next_round(self) -> None: self.round_number += 1 for fighter in self._fighters.values(): @@ -1250,6 +1644,9 @@ def _start_next_round(self) -> None: fighter.clinch_startup_ticks = 0 fighter.stunned_ticks = 0 fighter.taunt_ticks = 0 + fighter.evasion_ticks = 0 + fighter.counter_ticks = 0 + fighter.combo_ticks = 0 fighter.last_action_until_tick = -1 self.phase = MatchPhase.FIGHT self.phase_ticks_remaining = self.config.round_ticks @@ -1417,6 +1814,8 @@ def _fighter_snapshot(self, fighter: FighterState) -> FighterSnapshot: x=fighter.x, y=fighter.y, facing=fighter.facing, + facing_x=fighter.facing_x, + facing_y=fighter.facing_y, velocity_x=fighter.velocity_x, velocity_y=fighter.velocity_y, stance=fighter.stance, @@ -1463,6 +1862,7 @@ def _fighter_snapshot(self, fighter: FighterState) -> FighterSnapshot: get_up_count=self._knockdown_count_ticks // COUNT_TICK_INTERVAL, get_up_window_start_tick=fighter.get_up_window_start_tick, get_up_window_end_tick=fighter.get_up_window_end_tick, + last_input_sequence=fighter.last_sequence, ) def _checksum(self, _fighters: tuple[FighterSnapshot, FighterSnapshot]) -> str: @@ -1473,7 +1873,7 @@ def _checksum(self, _fighters: tuple[FighterSnapshot, FighterSnapshot]) -> str: { "player_id": fighter.player_id, "position": [fighter.x, fighter.y], - "facing": fighter.facing, + "facing": [fighter.facing, fighter.facing_x, fighter.facing_y], "velocity": [fighter.velocity_x, fighter.velocity_y], "movement_fixed": [ fighter.velocity_fixed_x, diff --git a/src/intelstream/hands/protocol.py b/src/intelstream/hands/protocol.py index 1f57c479..b53c46b6 100644 --- a/src/intelstream/hands/protocol.py +++ b/src/intelstream/hands/protocol.py @@ -21,7 +21,7 @@ Target, ) -PROTOCOL_VERSION = 2 +PROTOCOL_VERSION = 3 MAX_FRAME_BYTES = 4096 MAX_ACTIONS_PER_INPUT = 4 MAX_SERVER_FRAME_BYTES = 65_536 @@ -145,10 +145,11 @@ def parse_client_input( if sequence <= last_sequence: raise ProtocolError("stale input sequence") client_tick = _integer(envelope.get("client_tick"), "client_tick", 0, MAX_SEQUENCE) - if client_tick < max(0, server_tick - MAX_TICK_LAG): - raise ProtocolError("client tick is too old") - if client_tick > server_tick + MAX_TICK_LEAD: - raise ProtocolError("client tick is too far ahead") + # The client tick is informational; a stalled or lagging client must keep playing, so the + # value is clamped into the plausible window instead of ending the connection. + client_tick = min( + max(client_tick, max(0, server_tick - MAX_TICK_LAG)), server_tick + MAX_TICK_LEAD + ) move = _object(envelope.get("move"), "move") _exact_fields(move, {"x", "y"}, "move") @@ -266,6 +267,7 @@ def snapshot_for_viewer(snapshot: EngineSnapshot, viewer_id: str | None) -> Engi get_up_required=0, get_up_window_start_tick=0, get_up_window_end_tick=0, + last_input_sequence=-1, ) for fighter in snapshot.fighters ) diff --git a/src/intelstream/hands/rating.py b/src/intelstream/hands/rating.py index 6e348382..a5e7a892 100644 --- a/src/intelstream/hands/rating.py +++ b/src/intelstream/hands/rating.py @@ -1,8 +1,17 @@ import math from dataclasses import dataclass +from datetime import timedelta DEFAULT_RATING = 1000 ELO_K_FACTOR = 32 +# A rematch is one click, so bouts between the same two fighters are damped: each earlier rated +# bout between them inside the window halves K. A pair exchanges about one bout's worth of rating +# a day however often it fights, which takes the point out of farming rating with an alt. +REPEAT_PAIRING_WINDOW = timedelta(hours=24) + + +def repeat_pairing_k_factor(earlier_bouts: int) -> float: + return ELO_K_FACTOR * 0.5 ** min(earlier_bouts, 64) @dataclass(frozen=True, slots=True) @@ -19,6 +28,8 @@ def calculate_elo( player_one_rating: int, player_two_rating: int, player_one_score: float, + *, + k_factor: float = ELO_K_FACTOR, ) -> EloChange: if player_one_rating < 0 or player_two_rating < 0: raise ValueError("ratings cannot be negative") @@ -26,7 +37,7 @@ def calculate_elo( raise ValueError("player_one_score must be 0, 0.5, or 1") expected = 1.0 / (1.0 + 10.0 ** ((player_two_rating - player_one_rating) / 400.0)) - raw_delta = ELO_K_FACTOR * (player_one_score - expected) + raw_delta = k_factor * (player_one_score - expected) delta = math.floor(raw_delta + 0.5) if raw_delta >= 0 else math.ceil(raw_delta - 0.5) player_one_after = max(0, player_one_rating + delta) applied_delta = player_one_after - player_one_rating diff --git a/src/intelstream/hands/rooms.py b/src/intelstream/hands/rooms.py index 143facb6..fa51cbb4 100644 --- a/src/intelstream/hands/rooms.py +++ b/src/intelstream/hands/rooms.py @@ -6,8 +6,8 @@ import secrets import time from collections import deque -from dataclasses import dataclass, field -from typing import TYPE_CHECKING, Literal, Protocol +from dataclasses import dataclass, field, replace +from typing import TYPE_CHECKING, Literal, Never, Protocol from uuid import uuid4 import structlog @@ -27,10 +27,22 @@ from intelstream.database.models import HandsMatch from intelstream.database.repository import Repository from intelstream.hands.auth import AuthenticatedPlayer - from intelstream.hands.types import MatchResult + from intelstream.hands.types import CombatEvent, EngineSnapshot, MatchResult logger = structlog.get_logger(__name__) +JOIN_ATTEMPTS = 3 +# A stalled uplink delivers its backlog in one burst. Frames past the per-second limit are dropped; +# the bout only ends for a flood that lasts this long or one this many times past the limit. +FLOOD_GRACE_SECONDS = 3.0 +FLOOD_HARD_LIMIT_FACTOR = 4 +# A connection is only ever sent its newest snapshot, and not while its transport already holds +# more than about two frames: a slow client sees the fight late instead of an ever older fight. +SNAPSHOT_BACKLOG_BYTES = 4096 +# The events of snapshots a connection never got ride on the next one, newest kept, well inside +# the client's limit of 256 per snapshot. +MAX_CARRIED_EVENTS = 128 + ConnectionRole = Literal["fighter", "spectator"] @@ -40,8 +52,16 @@ def closed(self) -> bool: ... async def send_str(self, data: str) -> object: ... + async def send_uncompressed(self, data: str) -> object: + """Sends a frame that carries a secret and must never share a compression context.""" + ... + + def write_buffer_size(self) -> int: ... + async def close(self, *, code: int = 1000, message: bytes = b"") -> object: ... + def abort(self) -> None: ... + class RoomError(Exception): def __init__(self, code: str) -> None: @@ -49,15 +69,26 @@ def __init__(self, code: str) -> None: self.code = code +class _RoomRetiredError(RoomError): + """The room a join found finished and was retired while the join was being admitted.""" + + def __init__(self) -> None: + super().__init__("room_closed") + + @dataclass(frozen=True, slots=True) class RoomConfig: tick_interval_seconds: float = 1 / 30 - broadcast_every_ticks: int = 2 + broadcast_every_ticks: int = 1 reconnect_grace_seconds: float = 20.0 result_hold_seconds: float = 10.0 final_delivery_timeout_seconds: float = 1.0 + close_timeout_seconds: float = 1.0 max_catch_up_ticks: int = 4 max_inputs_per_second: int = 60 + max_input_frames_per_second: int = 180 + # A connection is dropped as a slow consumer once this many control updates wait unsent, or + # this many snapshots in a row were replaced before it could be sent one. outbound_queue_size: int = 16 max_spectators: int = 20 engine_config: EngineConfig = field(default_factory=EngineConfig) @@ -79,10 +110,13 @@ def __post_init__(self) -> None: self.reconnect_grace_seconds <= 0 or self.result_hold_seconds < 0 or self.final_delivery_timeout_seconds <= 0 + or self.close_timeout_seconds <= 0 ): raise ValueError("room durations are invalid") if self.max_spectators < 0: raise ValueError("spectator bound must not be negative") + if self.max_input_frames_per_second < self.max_inputs_per_second: + raise ValueError("input frame bound must not be below the accepted input bound") @dataclass(frozen=True, slots=True) @@ -90,6 +124,16 @@ class _OutboundMessage: message: str | None = None bounded_update: bool = False ticket_refresh: bool = False + snapshot: bool = False + uncompressed: bool = False + + +@dataclass(frozen=True, slots=True) +class _PendingSnapshot: + snapshot: EngineSnapshot + viewer_id: str | None + message: str + carried_events: tuple[CombatEvent, ...] = () @dataclass(slots=True) @@ -101,6 +145,9 @@ class PlayerConnection: slow_drop_task: asyncio.Task[None] | None = None ticket_refresh_queued: bool = False latest_ticket_refresh: str | None = None + pending_snapshot: _PendingSnapshot | None = None + snapshot_queued: bool = False + missed_snapshots: int = 0 writer_task: asyncio.Task[None] | None = None @@ -111,7 +158,11 @@ class PlayerSlot: connection: PlayerConnection | None grace_remaining: float last_sequence: int = -1 - input_times: deque[float] = field(default_factory=deque) + input_budget: float | None = None + input_budget_at: float = 0.0 + deferred_frame: str | bytes | None = None + frame_times: deque[float] = field(default_factory=deque) + flood_started: float | None = None reconnect_deadline: float | None = None pre_match_grace_event: asyncio.Event = field(default_factory=asyncio.Event) pre_match_grace_task: asyncio.Task[None] | None = None @@ -172,6 +223,7 @@ def __init__( self._cleanup_task: asyncio.Task[None] | None = None self._closed = False self._finished = False + self._retired = False self._accepting_reconnects = True self._final_payload: str | None = None self._lock = asyncio.Lock() @@ -202,6 +254,10 @@ def member_ids(self) -> tuple[str, ...]: def finished(self) -> bool: return self._finished + def retire(self) -> None: + """The manager no longer routes joins here; a join already on its way must not land.""" + self._retired = True + async def add( self, identity: AuthenticatedPlayer, @@ -226,7 +282,7 @@ async def add( or self._persistence_task is not None or self._finished ) - if self._closed or (final_recovery and not self._accepting_reconnects): + if self._closed or self._retired or (final_recovery and not self._accepting_reconnects): raise RoomError("room_closed") if final_recovery and existing is None: raise RoomError("room_closed") @@ -254,21 +310,20 @@ async def add( if len(self._spectators) >= self.config.max_spectators: raise RoomError("room_full") - if existing is not None and existing.connection is not None: - await self._stop_connection(existing.connection, code=4001, reason=b"replaced") - final_recovery = self._engine is not None and ( - self._engine.result is not None - or self._persistence_task is not None - or self._finished - ) - if final_recovery and not self._accepting_reconnects: - raise RoomError("room_closed") if reconnect_ticket_factory is not None: reconnect_ticket = reconnect_ticket_factory() connection = self._new_connection(identity.user_id, role, socket) + if existing is not None and existing.connection is not None: + # The replaced socket may belong to a phone that stopped reading, so it is closed + # in the background; the new connection takes its place below, under the lock. + self._spawn( + self._stop_connection(existing.connection, code=4001, reason=b"replaced"), + name=f"hands-replace-{role}-{identity.user_id}", + ) if role == "fighter": if existing_fighter is not None: + self._forget_connection_input(existing_fighter) existing_fighter.connection = connection existing_fighter.identity = identity existing_fighter.grace_remaining = self.config.reconnect_grace_seconds @@ -308,7 +363,7 @@ async def add( if reconnect_ticket is not None: welcome["reconnect_ticket"] = reconnect_ticket - self._enqueue(connection, self._message("welcome", **welcome)) + self._enqueue(connection, self._message("welcome", **welcome), uncompressed=True) if (existing is not None and self._engine is not None) or role == "spectator": assert self._engine is not None self._enqueue( @@ -427,15 +482,24 @@ async def _writer( outbound = await connection.outbox.get() try: message = outbound.message - if outbound.ticket_refresh: + uncompressed = outbound.uncompressed + if outbound.snapshot: + message = await self._take_snapshot(connection) + if message is None: + continue + elif outbound.ticket_refresh: message = connection.latest_ticket_refresh connection.latest_ticket_refresh = None connection.ticket_refresh_queued = False if message is None: continue + uncompressed = True elif message is None: return - await connection.socket.send_str(message) + if uncompressed: + await connection.socket.send_uncompressed(message) + else: + await connection.socket.send_str(message) finally: if outbound.bounded_update: connection.pending_updates -= 1 @@ -474,22 +538,73 @@ def _public_players(self) -> list[dict[str, object]]: ] def _enqueue( - self, connection: PlayerConnection, message: str, *, bounded_update: bool = False + self, + connection: PlayerConnection, + message: str, + *, + bounded_update: bool = False, + uncompressed: bool = False, ) -> None: if bounded_update: if connection.pending_updates >= self.config.outbound_queue_size: - if not connection.slow_drop_started: - connection.slow_drop_started = True - connection.slow_drop_task = self._spawn( - self._drop_slow_connection(connection), - name=f"hands-slow-drop-{self.instance_id}", - ) + self._suspect_slow_connection(connection) return connection.pending_updates += 1 connection.outbox.put_nowait( - _OutboundMessage(message=message, bounded_update=bounded_update) + _OutboundMessage( + message=message, bounded_update=bounded_update, uncompressed=uncompressed + ) ) + def _offer_snapshot( + self, + connection: PlayerConnection, + snapshot: EngineSnapshot, + viewer_id: str | None, + message: str, + ) -> None: + pending = connection.pending_snapshot + carried: tuple[CombatEvent, ...] = () + if pending is not None: + # The snapshot this one replaces is never sent, so its events travel on. + carried = (*pending.carried_events, *pending.snapshot.events)[-MAX_CARRIED_EVENTS:] + connection.missed_snapshots += 1 + if connection.missed_snapshots >= self.config.outbound_queue_size: + self._suspect_slow_connection(connection) + connection.pending_snapshot = _PendingSnapshot(snapshot, viewer_id, message, carried) + if not connection.snapshot_queued: + connection.snapshot_queued = True + connection.outbox.put_nowait(_OutboundMessage(snapshot=True)) + + async def _take_snapshot(self, connection: PlayerConnection) -> str | None: + # Newer snapshots replace the pending one while the transport drains. A transport only + # signals at its own watermarks, so the backlog is checked once a tick instead. + while connection.socket.write_buffer_size() > SNAPSHOT_BACKLOG_BYTES: # noqa: ASYNC110 + await asyncio.sleep(self.config.tick_interval_seconds) + pending = connection.pending_snapshot + connection.pending_snapshot = None + connection.snapshot_queued = False + if pending is None: + return None + connection.missed_snapshots = 0 + if not pending.carried_events: + return pending.message + events = (*pending.carried_events, *pending.snapshot.events) + try: + return encode_snapshot( + replace(pending.snapshot, events=events), viewer_id=pending.viewer_id + ) + except ProtocolError: + return pending.message + + def _suspect_slow_connection(self, connection: PlayerConnection) -> None: + if not connection.slow_drop_started: + connection.slow_drop_started = True + connection.slow_drop_task = self._spawn( + self._drop_slow_connection(connection), + name=f"hands-slow-drop-{self.instance_id}", + ) + def _connected_members(self) -> list[tuple[str, ConnectionRole, PlayerConnection]]: members: list[tuple[str, ConnectionRole, PlayerConnection]] = [ (player_id, "fighter", slot.connection) @@ -505,7 +620,10 @@ def _connected_members(self) -> list[tuple[str, ConnectionRole, PlayerConnection async def _drop_slow_connection(self, connection: PlayerConnection) -> None: try: await asyncio.sleep(self.config.tick_interval_seconds) - if connection.pending_updates < self.config.outbound_queue_size: + if ( + connection.pending_updates < self.config.outbound_queue_size + and connection.missed_snapshots < self.config.outbound_queue_size + ): connection.slow_drop_started = False return for player_id, role, current in self._connected_members(): @@ -562,20 +680,42 @@ async def submit_frame( or self._persistence_task is not None or (self._engine is not None and self._engine.result is not None) ): - raise RoomError("match_complete") + # Inputs already in flight when the bout ends arrive after the result on any + # real connection; dropping them keeps the final on the player's screen. + return slot = self._slots.get(player_id) if slot is None or slot.connection is not connection: raise RoomError("connection_replaced") engine = self._engine if engine is None: raise RoomError("match_not_started") + paused = any(current.connection is None for current in self._slots.values()) + # A paused bout drops inputs; none is held back to fire once it resumes. + held = None if paused else frame now = self._clock() - while slot.input_times and slot.input_times[0] <= now - 1.0: - slot.input_times.popleft() - if len(slot.input_times) >= self.config.max_inputs_per_second: - raise RoomError("rate_limited") - if any(current.connection is None for current in self._slots.values()): - slot.input_times.append(now) + while slot.frame_times and slot.frame_times[0] <= now - 1.0: + slot.frame_times.popleft() + slot.frame_times.append(now) + limit = self.config.max_input_frames_per_second + if len(slot.frame_times) > limit: + if slot.flood_started is None: + slot.flood_started = now + if ( + len(slot.frame_times) > FLOOD_HARD_LIMIT_FACTOR * limit + or now - slot.flood_started >= FLOOD_GRACE_SECONDS + ): + raise RoomError("rate_limited") + slot.deferred_frame = held + return + slot.flood_started = None + if not self._spend_input_budget(slot, now): + # A stalled connection delivers its backlog in one burst. The frames past the + # budget are not applied, but the newest is kept and goes in as soon as there is + # room, so the player's latest input is never the one that is lost. + slot.deferred_frame = held + return + slot.deferred_frame = None + if paused: return try: command = parse_client_input( @@ -585,11 +725,51 @@ async def submit_frame( ) except ProtocolError as exc: raise RoomError("invalid_input") from exc - slot.input_times.append(now) slot.last_sequence = command.sequence if not engine.submit_input(player_id, command): raise RoomError("input_queue_full") + @staticmethod + def _forget_connection_input(slot: PlayerSlot) -> None: + """Input pacing belongs to a connection: a new one starts with a full allowance.""" + slot.deferred_frame = None + slot.frame_times.clear() + slot.flood_started = None + slot.input_budget = None + + def _spend_input_budget(self, slot: PlayerSlot, now: float) -> bool: + limit = float(self.config.max_inputs_per_second) + if slot.input_budget is None: + slot.input_budget = limit + else: + elapsed = max(0.0, now - slot.input_budget_at) + slot.input_budget = min(limit, slot.input_budget + elapsed * limit) + slot.input_budget_at = now + if slot.input_budget < 1.0: + return False + slot.input_budget -= 1.0 + return True + + def _apply_deferred_inputs(self, now: float) -> None: + engine = self._engine + if engine is None or any(slot.connection is None for slot in self._slots.values()): + return + for player_id, slot in self._slots.items(): + frame = slot.deferred_frame + if frame is None or not self._spend_input_budget(slot, now): + continue + slot.deferred_frame = None + try: + command = parse_client_input( + frame, + last_sequence=slot.last_sequence, + server_tick=engine.tick, + ) + except ProtocolError: + continue + slot.last_sequence = command.sequence + engine.submit_input(player_id, command) + async def disconnect( self, player_id: str, role: ConnectionRole, connection: PlayerConnection ) -> None: @@ -599,34 +779,40 @@ async def disconnect( if spectator is None or spectator.connection is not connection: return self._spectators.pop(player_id, None) - await self._stop_connection(connection, code=1001, reason=b"disconnected") - return - - slot = self._slots.get(player_id) - if slot is None or slot.connection is not connection: - return - slot.connection = None - await self._stop_connection(connection, code=1001, reason=b"disconnected") - slot.grace_remaining = self.config.reconnect_grace_seconds - slot.reconnect_deadline = self._clock() + self.config.reconnect_grace_seconds - if self._engine is not None: - self._engine.clear_action_buffers() - if self._engine is None: - if slot.pre_match_grace_task is None or slot.pre_match_grace_task.done(): - slot.pre_match_grace_task = self._spawn( - self._expire_pre_match_fighter(player_id, slot), - name=f"hands-waiting-grace-{player_id}", + else: + slot = self._slots.get(player_id) + if slot is None or slot.connection is not connection: + return + # The pause and its deadline are settled before the socket is touched: closing + # a stalled socket can wait or fail, and the bout must not depend on it. + slot.connection = None + slot.grace_remaining = self.config.reconnect_grace_seconds + slot.reconnect_deadline = self._clock() + self.config.reconnect_grace_seconds + # Nothing queued before the pause fires after it, including a frame either + # fighter had held back by the input budget, and nobody keeps walking or + # guarding on what he held when it began: inputs during the pause are dropped. + if self._engine is not None: + self._engine.clear_action_buffers() + self._engine.clear_held_input() + for current in self._slots.values(): + current.deferred_frame = None + if self._engine is None: + if slot.pre_match_grace_task is None or slot.pre_match_grace_task.done(): + slot.pre_match_grace_task = self._spawn( + self._expire_pre_match_fighter(player_id, slot), + name=f"hands-waiting-grace-{player_id}", + ) + slot.pre_match_grace_event.set() + elif not self._finished: + self._enqueue_all( + self._message( + "paused", + player_id=player_id, + grace_ms=max(0, int(slot.grace_remaining * 1000)), + ), + bounded_update=True, ) - slot.pre_match_grace_event.set() - elif not self._finished: - self._enqueue_all( - self._message( - "paused", - player_id=player_id, - grace_ms=max(0, int(slot.grace_remaining * 1000)), - ), - bounded_update=True, - ) + await self._stop_connection(connection, code=1001, reason=b"disconnected") async def _wait_for_pre_match_change( self, @@ -718,6 +904,7 @@ async def _run_match(self) -> None: if ticks_due > self.config.max_catch_up_ticks: ticks_due = self.config.max_catch_up_ticks next_tick = now - (ticks_due - 1) * interval + self._apply_deferred_inputs(now) for _ in range(ticks_due): snapshot = engine.step() next_tick += interval @@ -732,12 +919,24 @@ async def _run_match(self) -> None: break if engine.result is None: await self._sleep(max(0.0, next_tick - self._clock())) + except Exception as exc: + logger.exception( + "Hands match failed", + instance_id=self.instance_id, + match_id=engine.match_id, + error_type=type(exc).__name__, + ) + # A result the engine had already reached stands; otherwise the bout is void. + if engine.result is not None: + self._ensure_finish_task(engine.result) + elif self._finish_task is None: + self._finish_task = asyncio.create_task( + self._finish_failed(), name=f"hands-failed-{self.instance_id}" + ) - finish_task = self._finish_task - if finish_task is not None and finish_task is not asyncio.current_task(): - await asyncio.shield(finish_task) - except asyncio.CancelledError: - raise + finish_task = self._finish_task + if finish_task is not None and finish_task is not asyncio.current_task(): + await asyncio.shield(finish_task) def _broadcast_snapshot(self, snapshot: object) -> None: from intelstream.hands.types import EngineSnapshot @@ -745,19 +944,16 @@ def _broadcast_snapshot(self, snapshot: object) -> None: assert isinstance(snapshot, EngineSnapshot) for player_id, slot in self._slots.items(): if slot.connection is not None: - self._enqueue( + self._offer_snapshot( slot.connection, + snapshot, + player_id, encode_snapshot(snapshot, viewer_id=player_id), - bounded_update=True, ) if self._spectators: message = encode_snapshot(snapshot, viewer_id=None) for spectator in self._spectators.values(): - self._enqueue( - spectator.connection, - message, - bounded_update=True, - ) + self._offer_snapshot(spectator.connection, snapshot, None, message) def _ensure_finish_task(self, result: MatchResult | None) -> asyncio.Task[None] | None: if result is None: @@ -786,6 +982,16 @@ async def _finish_abandoned(self) -> None: await self._close_now(code=1001, reason=b"match abandoned") await self._on_finished(self) + async def _finish_failed(self) -> None: + """The bout cannot go on: it ends as a no contest, nothing is recorded or rated.""" + async with self._lock: + self._finished = True + self._accepting_reconnects = False + self._enqueue_all(self._message("error", code="internal_error")) + await self._drain_outboxes() + await self._close_now(code=1011, reason=b"match failed") + await self._on_finished(self) + async def _finish_result(self, result: MatchResult) -> None: assert self._persistence_task is not None try: @@ -812,6 +1018,8 @@ async def _finish_result(self, result: MatchResult) -> None: await self._drain_outboxes() if self.config.result_hold_seconds: await self._sleep(self.config.result_hold_seconds) + # Closing can wait on a stalled member; a rematch from here starts a new room instead. + await self._on_finished(self) async with self._lock: self._accepting_reconnects = False await self._drain_outboxes() @@ -859,23 +1067,49 @@ async def _stop_connection( self, connection: PlayerConnection, *, code: int, reason: bytes ) -> None: current = asyncio.current_task() - slow_drop_task = connection.slow_drop_task - connection.slow_drop_task = None - if slow_drop_task is not None and slow_drop_task is not current: - slow_drop_task.cancel() - with contextlib.suppress(asyncio.CancelledError): - await slow_drop_task - connection.latest_ticket_refresh = None - connection.ticket_refresh_queued = False - connection.outbox.put_nowait(_OutboundMessage()) - writer_task = connection.writer_task - if writer_task is not None and writer_task is not current: - writer_task.cancel() - with contextlib.suppress(asyncio.CancelledError): - await writer_task - if not connection.socket.closed: - with contextlib.suppress(ConnectionError, RuntimeError): - await connection.socket.close(code=code, message=reason[:120]) + try: + slow_drop_task = connection.slow_drop_task + connection.slow_drop_task = None + if slow_drop_task is not None and slow_drop_task is not current: + await self._cancel_and_wait(slow_drop_task) + connection.latest_ticket_refresh = None + connection.ticket_refresh_queued = False + connection.outbox.put_nowait(_OutboundMessage()) + writer_task = connection.writer_task + if writer_task is not None and writer_task is not current: + await self._cancel_and_wait(writer_task) + if not connection.socket.closed: + await self._close_socket(connection.socket, code=code, reason=reason) + except asyncio.CancelledError: + connection.socket.abort() + raise + + @staticmethod + async def _cancel_and_wait(task: asyncio.Task[None]) -> None: + task.cancel() + try: + await task + except asyncio.CancelledError: + current = asyncio.current_task() + if current is not None and current.cancelling(): + raise + + async def _close_socket(self, socket: SocketLike, *, code: int, reason: bytes) -> None: + current = asyncio.current_task() + try: + async with asyncio.timeout(self.config.close_timeout_seconds): + await socket.close(code=code, message=reason[:120]) + return + except asyncio.CancelledError: + if current is not None and current.cancelling(): + raise + # aiohttp parks every write on one drain waiter per transport. Cancelling a writer + # parked there cancels that waiter, and close() then fails on it: that cancellation + # belongs to the writer, not to this task. + except (ConnectionError, RuntimeError, TimeoutError): + pass + # A peer that stopped reading never lets a graceful close finish. + socket.abort() async def _close_now(self, *, code: int, reason: bytes) -> None: async with self._lock: @@ -889,8 +1123,12 @@ async def _close_now(self, *, code: int, reason: bytes) -> None: for slot in self._slots.values(): slot.connection = None self._spectators.clear() - for connection in connections: - await self._stop_connection(connection, code=code, reason=reason) + await asyncio.gather( + *( + self._stop_connection(connection, code=code, reason=reason) + for connection in connections + ) + ) tick_task = self._tick_task if tick_task is not None and tick_task is not asyncio.current_task(): tick_task.cancel() @@ -951,6 +1189,26 @@ async def join( *, reconnect_ticket: str | None = None, reconnect_ticket_factory: Callable[[], str] | None = None, + ) -> RoomMembership: + for _attempt in range(JOIN_ATTEMPTS): + try: + return await self._join_once( + player, + socket, + reconnect_ticket=reconnect_ticket, + reconnect_ticket_factory=reconnect_ticket_factory, + ) + except _RoomRetiredError: + continue + raise RoomError("room_closed") + + async def _join_once( + self, + player: AuthenticatedPlayer, + socket: SocketLike, + *, + reconnect_ticket: str | None, + reconnect_ticket_factory: Callable[[], str] | None, ) -> RoomMembership: owner = object() async with self._lock: @@ -991,8 +1249,10 @@ async def join( and reservation.owner is owner ) if not valid: - rejection = "server_shutting_down" if self._closed else "room_closed" - raise RoomError(rejection) + self._raise_unavailable(player, room) + # Admission into one room never holds up joins anywhere else; the room's own + # admission lock still orders joins into it. + try: membership = await room.add( player, socket, @@ -1000,19 +1260,39 @@ async def join( reconnect_ticket=reconnect_ticket, reconnect_ticket_factory=reconnect_ticket_factory, ) - reservation.established = True - reservation.connection = membership.connection + except RoomError as exc: + if exc.code != "room_closed": + raise + # The room may have finished and been retired after the check above. + async with self._lock: + self._raise_unavailable(player, room) + async with self._lock: + if self._user_rooms.get(player.user_id) is reservation: + reservation.established = True + reservation.connection = membership.connection except BaseException: async with self._lock: current = self._user_rooms.get(player.user_id) if current is reservation and reservation.owner is owner: if not reservation.established: self._user_rooms.pop(player.user_id, None) - if not room.member_ids and self._rooms.get(player.instance_id) is room: - self._rooms.pop(player.instance_id, None) + if not room.member_ids: + self._retire_room(room) raise return membership + def _raise_unavailable(self, player: AuthenticatedPlayer, room: HandsRoom) -> Never: + if self._closed: + raise RoomError("server_shutting_down") + if room.finished and self._rooms.get(player.instance_id) is not room: + raise _RoomRetiredError + raise RoomError("room_closed") + + def _retire_room(self, room: HandsRoom) -> None: + if self._rooms.get(room.instance_id) is room: + self._rooms.pop(room.instance_id, None) + room.retire() + async def _room_finished(self, room: HandsRoom) -> None: async with self._lock: active_member_ids = set(room.member_ids) @@ -1024,8 +1304,7 @@ async def _room_finished(self, room: HandsRoom) -> None: for player_id, reservation in list(self._user_rooms.items()): if reservation.room is room: self._user_rooms.pop(player_id, None) - if self._rooms.get(room.instance_id) is room: - self._rooms.pop(room.instance_id, None) + self._retire_room(room) async def leave(self, membership: RoomMembership) -> None: await membership.room.disconnect( @@ -1042,13 +1321,11 @@ async def leave(self, membership: RoomMembership) -> None: reservation is not None and reservation.room is membership.room and reservation.connection is membership.connection + and membership.player_id not in membership.room.member_ids ): self._user_rooms.pop(membership.player_id, None) - if ( - not membership.room.member_ids - and self._rooms.get(membership.room.instance_id) is membership.room - ): - self._rooms.pop(membership.room.instance_id, None) + if not membership.room.member_ids: + self._retire_room(membership.room) async def close(self) -> None: async with self._lock: diff --git a/src/intelstream/hands/rules.py b/src/intelstream/hands/rules.py index 17565ae1..8f7b91d2 100644 --- a/src/intelstream/hands/rules.py +++ b/src/intelstream/hands/rules.py @@ -15,7 +15,7 @@ def _load_manifest() -> dict[str, Any]: TICKS_PER_SECOND = 30 RING_HALF_WIDTH = 500 -RING_HALF_HEIGHT = 330 +RING_HALF_HEIGHT = 500 FIGHTER_RADIUS = 38 MINIMUM_SEPARATION = FIGHTER_RADIUS * 2 ROUND_TICKS = 120 * TICKS_PER_SECOND @@ -26,6 +26,19 @@ def _load_manifest() -> dict[str, Any]: MAX_CONDITIONING = 1000 MAX_GUARD = 700 MAX_POISE = 600 +FACING_SCALE: int = _MANIFEST["facing"]["scale"] +# Share of the remaining turn toward the opponent taken per facing update. A fight tick makes two +# updates (before the exchange and after footwork), about 58% per tick; knockdown and rest walks +# make one. +FACING_TURN_PERCENT: int = _MANIFEST["facing"]["turn_percent_per_update"] +RECOVERY_CANCEL_PERCENT: int = _MANIFEST["combos"]["recovery_cancel_percent"] +KNOCKDOWN_NEUTRAL_SEPARATION: int = _MANIFEST["knockdown"]["neutral_separation"] +REFEREE_WALK_SPEED: int = _MANIFEST["knockdown"]["referee_walk_speed"] +RING_CORNER_REACH: int = _MANIFEST["corners"]["reach"] +REST_CORNER_OFFSET: int = _MANIFEST["rest"]["corner_offset"] +CLINCH_HOLD_DISTANCE: int = _MANIFEST["clinch"]["hold_distance"] +CLINCH_DRAW_SPEED: int = _MANIFEST["clinch"]["draw_speed"] +REST_WALK_SPEED: int = _MANIFEST["rest"]["walk_speed"] def _manifest_check() -> None: @@ -42,6 +55,12 @@ def _manifest_check() -> None: raise RuntimeError("combat-manifest.json limits mismatch with rules.py") if limits["max_guard"] != MAX_GUARD or limits["max_poise"] != MAX_POISE: raise RuntimeError("combat-manifest.json limits mismatch with rules.py") + # Not a tunable: the engine's fixed-point movement and compass, which the knockdown and rest + # walks feed facing vectors into, and the client's snapshot checks all count a unit as 1000. + if FACING_SCALE != 1000: + raise RuntimeError("combat-manifest.json facing.scale must stay 1000") + if REST_CORNER_OFFSET * 2 > RING_CORNER_REACH: + raise RuntimeError("combat-manifest.json rest.corner_offset is past the corner pads") _manifest_check() @@ -126,13 +145,7 @@ def _punch_variant(base: PunchRule, target: Target, power: Power) -> PunchRule: } COMPATIBLE_COMBO_CHAINS: frozenset[tuple[PunchClass, PunchClass]] = frozenset( - { - (PunchClass.JAB, PunchClass.STRAIGHT), - (PunchClass.JAB, PunchClass.HOOK), - (PunchClass.STRAIGHT, PunchClass.HOOK), - (PunchClass.HOOK, PunchClass.UPPERCUT), - (PunchClass.UPPERCUT, PunchClass.HOOK), - } + (PunchClass(first), PunchClass(second)) for first, second in _MANIFEST["combos"]["chains"] ) diff --git a/src/intelstream/hands/server.py b/src/intelstream/hands/server.py index 01a9f9ec..b4d937b7 100644 --- a/src/intelstream/hands/server.py +++ b/src/intelstream/hands/server.py @@ -6,6 +6,7 @@ import math import mimetypes import secrets +import struct import time from collections import OrderedDict, deque from dataclasses import dataclass, field @@ -25,7 +26,7 @@ ProtocolError, parse_ticket_ack, ) -from intelstream.hands.rooms import HandsRoomManager, RoomError, RoomMembership +from intelstream.hands.rooms import HandsRoomManager, RoomError, RoomMembership, SocketLike from intelstream.hands.rules import RING_HALF_HEIGHT, RING_HALF_WIDTH, TICKS_PER_SECOND if TYPE_CHECKING: @@ -206,6 +207,63 @@ def confirm(self) -> None: self.acknowledged.set() +def _text_frame(payload: bytes) -> bytes: + """One final, unmasked and uncompressed websocket text frame (RFC 6455 section 5.2).""" + length = len(payload) + if length < 126: + header = struct.pack("!BB", 0x81, length) + elif length < 1 << 16: + header = struct.pack("!BBH", 0x81, 126, length) + else: + header = struct.pack("!BBQ", 0x81, 127, length) + return header + payload + + +class _RoomSocket: + """The room's handle on one websocket, with the transport underneath it. + + Room traffic is deflated through aiohttp with the connection's shared context when the client + negotiated permessage-deflate. A frame that carries a reconnect ticket is written uncompressed, + which RFC 7692 allows per message, so the ticket never shares a context with player-chosen + text such as display names. aiohttp cannot send it that way itself: its per-message option + deflates with a fresh context, which the client's inflater cannot follow. + """ + + __slots__ = ("_request", "_websocket") + + def __init__(self, request: web.Request, websocket: web.WebSocketResponse) -> None: + self._request = request + self._websocket = websocket + + @property + def closed(self) -> bool: + return self._websocket.closed + + async def send_str(self, data: str) -> None: + await self._websocket.send_str(data) + + async def send_uncompressed(self, data: str) -> None: + if not self._websocket.compress: + await self._websocket.send_str(data) + return + transport = self._request.transport + if self._websocket.closed or transport is None or transport.is_closing(): + raise ConnectionResetError("websocket is closed") + transport.write(_text_frame(data.encode())) + + def write_buffer_size(self) -> int: + transport = self._request.transport + return 0 if transport is None else transport.get_write_buffer_size() + + async def close(self, *, code: int = 1000, message: bytes = b"") -> None: + await self._websocket.close(code=code, message=message) + + def abort(self) -> None: + transport = self._request.transport + if transport is not None: + transport.abort() + + class AuthBackend(Protocol): application_id: str @@ -229,7 +287,7 @@ class RoomsBackend(Protocol): async def join( self, player: AuthenticatedPlayer, - socket: web.WebSocketResponse, + socket: SocketLike, *, reconnect_ticket: str | None = None, reconnect_ticket_factory: Callable[[], str] | None = None, @@ -282,6 +340,20 @@ def _unique_object(pairs: list[tuple[str, object]]) -> dict[str, object]: return result +def _authentication_version(raw: bytes) -> int | None: + """The protocol version an authentication frame claims, before its shape is checked.""" + try: + value = json.loads(raw) + except (json.JSONDecodeError, UnicodeDecodeError, ValueError): + return None + if not isinstance(value, dict) or value.get("type") != "authenticate": + return None + version = value.get("version") + if isinstance(version, bool) or not isinstance(version, int) or not 0 < version < 2**31: + return None + return version + + def _strict_object(raw: bytes, *, fields: set[str]) -> dict[str, object]: if len(raw) > MAX_HTTP_BODY_BYTES: raise web.HTTPRequestEntityTooLarge( @@ -655,7 +727,7 @@ async def _websocket(self, request: web.Request) -> web.StreamResponse: autoping=True, heartbeat=15.0, max_msg_size=MAX_FRAME_BYTES, - compress=False, + compress=True, ) try: await websocket.prepare(request) @@ -665,6 +737,7 @@ async def _websocket(self, request: web.Request) -> web.StreamResponse: membership: RoomMembership | None = None ticket_refresh_state: _TicketRefreshState | None = None ticket_refresh_task: asyncio.Task[None] | None = None + reply_version = PROTOCOL_VERSION try: try: async with asyncio.timeout(self.auth_timeout_seconds): @@ -674,6 +747,12 @@ async def _websocket(self, request: web.Request) -> web.StreamResponse: encoded = first.data.encode() if isinstance(first.data, str) else first.data if not isinstance(encoded, bytes) or len(encoded) > MAX_AUTH_FRAME_BYTES: raise HandsAuthError("authentication_required") + client_version = _authentication_version(encoded) + if client_version is not None and client_version != PROTOCOL_VERSION: + # A window still running an older build after a deploy: it must reload, + # and is told so in its own version, which its decoder still reads. + reply_version = client_version + raise HandsAuthError("client_outdated") payload = _strict_object(encoded, fields={"version", "type", "ticket"}) if payload["version"] != PROTOCOL_VERSION or payload["type"] != "authenticate": raise HandsAuthError("invalid_ticket") @@ -682,7 +761,7 @@ async def _websocket(self, request: web.Request) -> web.StreamResponse: await self._ws_error(websocket, "authentication_timeout", close_code=4003) return websocket except HandsAuthError as exc: - await self._ws_error(websocket, exc.code, close_code=4003) + await self._ws_error(websocket, exc.code, close_code=4003, version=reply_version) return websocket except web.HTTPException: await self._ws_error(websocket, "invalid_request", close_code=4004) @@ -693,7 +772,7 @@ async def _websocket(self, request: web.Request) -> web.StreamResponse: try: membership = await self.rooms.join( player, - websocket, + _RoomSocket(request, websocket), reconnect_ticket_factory=lambda: self.auth.issue_ticket(player), ) except (HandsAuthError, RoomError) as exc: @@ -780,12 +859,18 @@ async def _refresh_reconnect_ticket( logger.error("Hands ticket refresh failed", error_type=type(exc).__name__) @staticmethod - async def _ws_error(websocket: web.WebSocketResponse, code: str, *, close_code: int) -> None: + async def _ws_error( + websocket: web.WebSocketResponse, + code: str, + *, + close_code: int, + version: int = PROTOCOL_VERSION, + ) -> None: if not websocket.closed: with contextlib.suppress(ConnectionError, RuntimeError): await websocket.send_str( json.dumps( - {"version": PROTOCOL_VERSION, "type": "error", "code": code}, + {"version": version, "type": "error", "code": code}, separators=(",", ":"), sort_keys=True, ) diff --git a/src/intelstream/hands/static/assets/hands.css b/src/intelstream/hands/static/assets/hands.css index 1a74ef28..78363974 100644 --- a/src/intelstream/hands/static/assets/hands.css +++ b/src/intelstream/hands/static/assets/hands.css @@ -1,2 +1,2 @@ -:root{color:#f2f6ff;font-synthesis:none;background:#07090e;font-family:Inter,ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,Segoe 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`},{name:`dismember_right`,sampleRate:12e3,frames:6960,wav:`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`}],r={jab:{from:520,to:1500,duration:.09},straight:{from:420,to:1150,duration:.12},hook:{from:300,to:880,duration:.14},uppercut:{from:240,to:820,duration:.15}},i=class{settings;context=null;master=null;noiseBuffer=null;injuryBuffers=new Map;crowdGain=null;unlocked=!1;unlockPromise=null;crowdStarted=!1;destroyed=!1;timers=new Set;lastBreathTick=-300;lastHeartbeatTick=-300;unlockListener=()=>{this.unlock().catch(()=>void 0)};visibility=()=>{let e=this.context;if(e===null)return;let t=document.hidden?e.suspend():this.unlocked?e.resume():null;t!==null&&t.catch(()=>void 0)};constructor(e){this.settings=e,window.addEventListener(`pointerdown`,this.unlockListener),window.addEventListener(`keydown`,this.unlockListener),document.addEventListener(`visibilitychange`,this.visibility)}unlock(){return this.destroyed||this.unlocked?Promise.resolve():(this.unlockPromise===null&&(this.unlockPromise=this.performUnlock().finally(()=>{this.unlockPromise=null})),this.unlockPromise)}async performUnlock(){let e=this.context;if(e===null){e=new AudioContext;let t=e.createGain();t.gain.value=Math.min(.8,Math.max(0,this.settings().volume)),t.connect(e.destination),this.context=e,this.master=t}if(e.state===`suspended`&&await e.resume(),this.destroyed||this.context!==e)return;let t=await this.decodeInjuryBuffers(e);this.destroyed||this.context!==e||(this.injuryBuffers=t,this.unlocked=!0,window.removeEventListener(`pointerdown`,this.unlockListener),window.removeEventListener(`keydown`,this.unlockListener),this.crowdStarted||(this.crowdStarted=!0,this.crowdBed()))}setVolume(){this.master!==null&&(this.master.gain.value=Math.min(.8,Math.max(0,this.settings().volume)))}event(e){if(this.unlocked)switch(e.kind){case`punch_start`:{let t=r[e.detail.split(`:`)[1]??`jab`]??r.jab;this.noise({duration:t.duration,frequency:t.from,sweepTo:t.to,gain:.1,type:`bandpass`,q:1.2});break}case`whiff`:this.noise({duration:.11,frequency:850,sweepTo:320,gain:.07,type:`bandpass`,q:1.1});break;case`hit`:case`counter_hit`:{let t=e.detail.endsWith(`body`),n=Math.min(.34,.16+e.amount/1400)*(e.kind===`counter_hit`?1.3:1);this.tone({from:t?120:150,to:42,duration:.13,type:`sine`,gain:n}),this.noise({duration:.06,frequency:t?420:1650,gain:n*.85,type:`bandpass`,q:.9}),this.noise({duration:.16,frequency:t?190:300,gain:n*.6}),e.kind===`counter_hit`&&this.crowdSwell(.5);break}case`block`:this.noise({duration:.05,frequency:900,gain:.15,type:`bandpass`,q:1.4}),this.tone({from:170,to:120,duration:.05,type:`triangle`,gain:.06});break;case`perfect_block`:this.noise({duration:.05,frequency:1450,gain:.16,type:`bandpass`,q:1.6}),this.tone({from:260,to:200,duration:.06,type:`triangle`,gain:.07});break;case`guard_break`:this.noise({duration:.18,frequency:520,gain:.24}),this.tone({from:230,to:78,duration:.2,type:`sawtooth`,gain:.1}),this.crowdSwell(.4);break;case`stun`:this.tone({from:96,to:74,duration:.22,type:`sine`,gain:.1});break;case`knockdown`:this.tone({from:68,to:32,duration:.34,type:`sine`,gain:.3}),this.noise({duration:.22,frequency:260,gain:.26}),this.crowdSwell(1);break;case`bell`:{let t=e.detail===`round_start`?3:1;for(let e=0;e.55&&e-this.lastBreathTick>=75&&(this.lastBreathTick=e,this.noise({duration:.18,frequency:420,gain:.045+i*.04})),(i>.72||r>500)&&e-this.lastHeartbeatTick>=24&&(this.lastHeartbeatTick=e,this.tone({from:52,duration:.09,type:`sine`,gain:.055}))}result(e){if(!this.unlocked)return;this.crowdSwell(1),this.tone({from:e.winner_id===null?280:520,duration:.45,type:`triangle`,gain:.18});let t=window.setTimeout(()=>{this.timers.delete(t),this.tone({from:650,duration:.5,type:`triangle`,gain:.14})},160);this.timers.add(t)}injury(e){let t=this.context,n=this.master,r=this.injuryBuffers.get(e),i=this.settings();if(!this.unlocked||t===null||n===null||r===void 0||i.blood!==`full`||i.reducedMotion)return;let a=t.createBufferSource(),o=t.createGain();a.buffer=r,o.gain.value=.16,a.connect(o).connect(n),a.start()}async decodeInjuryBuffers(e){let t=await Promise.all(n.map(async t=>{let n=atob(t.wav),r=new Uint8Array(n.length);for(let e=0;evoid 0)}},a=class extends 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t=u(e,`fighter`);d(t,`player_id.x.y.facing.velocity_x.velocity_y.stance.defense.stamina.maximum_stamina.conditioning.guard.poise.trauma.knockdowns.warnings.deductions.stunned_ticks.is_downed.action.action_hand.action_target.action_power.action_id.action_key.action_start_tick.action_startup_ticks.action_active_ticks.action_recovery_ticks.action_contact_tick.queued_actions.clinch_startup_ticks.clinch_ticks.is_foul_recovery_target.taunt_ticks.get_up_prompt.get_up_meter.get_up_required.get_up_count.get_up_window_start_tick.get_up_window_end_tick`.split(`.`));let n=t.action===null?null:g(t.action,y,`action`),r=t.action_hand===null?null:g(t.action_hand,v,`action hand`),i=t.action_target===null?null:g(t.action_target,b,`action target`),o=t.action_power===null?null:g(t.action_power,x,`action power`);if([n,r,i,o].some(e=>e===null)&&[n,r,i,o].some(e=>e!==null))throw new a(`partial punch action`);let 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isCUID2(){return!!this._def.checks.find(e=>e.kind===`cuid2`)}get isULID(){return!!this._def.checks.find(e=>e.kind===`ulid`)}get isIP(){return!!this._def.checks.find(e=>e.kind===`ip`)}get isBase64(){return!!this._def.checks.find(e=>e.kind===`base64`)}get minLength(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e}get maxLength(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuenew ut({checks:[],typeName:en.ZodString,coerce:e?.coerce??!1,...We(e)});function dt(e,t){let n=(e.toString().split(`.`)[1]||``).length,r=(t.toString().split(`.`)[1]||``).length,i=n>r?n:r;return parseInt(e.toFixed(i).replace(`.`,``))%parseInt(t.toFixed(i).replace(`.`,``))/10**i}var ft=class e extends Ge{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte,this.step=this.multipleOf}_parse(e){if(this._def.coerce&&(e.data=Number(e.data)),this._getType(e)!==P.number){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.number,received:t.parsedType}),z}let t,n=new je;for(let r of this._def.checks)r.kind===`int`?N.isInteger(e.data)||(t=this._getOrReturnCtx(e,t),R(t,{code:F.invalid_type,expected:`integer`,received:`float`,message:r.message}),n.dirty()):r.kind===`min`?(r.inclusive?e.datar.value:e.data>=r.value)&&(t=this._getOrReturnCtx(e,t),R(t,{code:F.too_big,maximum:r.value,type:`number`,inclusive:r.inclusive,exact:!1,message:r.message}),n.dirty()):r.kind===`multipleOf`?dt(e.data,r.value)!==0&&(t=this._getOrReturnCtx(e,t),R(t,{code:F.not_multiple_of,multipleOf:r.value,message:r.message}),n.dirty()):r.kind===`finite`?Number.isFinite(e.data)||(t=this._getOrReturnCtx(e,t),R(t,{code:F.not_finite,message:r.message}),n.dirty()):N.assertNever(r);return{status:n.value,value:e.data}}gte(e,t){return this.setLimit(`min`,e,!0,B.toString(t))}gt(e,t){return this.setLimit(`min`,e,!1,B.toString(t))}lte(e,t){return this.setLimit(`max`,e,!0,B.toString(t))}lt(e,t){return this.setLimit(`max`,e,!1,B.toString(t))}setLimit(t,n,r,i){return new e({...this._def,checks:[...this._def.checks,{kind:t,value:n,inclusive:r,message:B.toString(i)}]})}_addCheck(t){return new e({...this._def,checks:[...this._def.checks,t]})}int(e){return this._addCheck({kind:`int`,message:B.toString(e)})}positive(e){return this._addCheck({kind:`min`,value:0,inclusive:!1,message:B.toString(e)})}negative(e){return this._addCheck({kind:`max`,value:0,inclusive:!1,message:B.toString(e)})}nonpositive(e){return this._addCheck({kind:`max`,value:0,inclusive:!0,message:B.toString(e)})}nonnegative(e){return this._addCheck({kind:`min`,value:0,inclusive:!0,message:B.toString(e)})}multipleOf(e,t){return this._addCheck({kind:`multipleOf`,value:e,message:B.toString(t)})}finite(e){return this._addCheck({kind:`finite`,message:B.toString(e)})}safe(e){return this._addCheck({kind:`min`,inclusive:!0,value:-(2**53-1),message:B.toString(e)})._addCheck({kind:`max`,inclusive:!0,value:2**53-1,message:B.toString(e)})}get minValue(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuee.kind===`int`||e.kind===`multipleOf`&&N.isInteger(e.value))}get isFinite(){let e=null,t=null;for(let n of this._def.checks)if(n.kind===`finite`||n.kind===`int`||n.kind===`multipleOf`)return!0;else n.kind===`min`?(t===null||n.value>t)&&(t=n.value):n.kind===`max`&&(e===null||n.valuenew ft({checks:[],typeName:en.ZodNumber,coerce:e?.coerce||!1,...We(e)});var pt=class e extends Ge{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte}_parse(e){if(this._def.coerce&&(e.data=BigInt(e.data)),this._getType(e)!==P.bigint){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.bigint,received:t.parsedType}),z}let t,n=new je;for(let r of this._def.checks)r.kind===`min`?(r.inclusive?e.datar.value:e.data>=r.value)&&(t=this._getOrReturnCtx(e,t),R(t,{code:F.too_big,type:`bigint`,maximum:r.value,inclusive:r.inclusive,message:r.message}),n.dirty()):r.kind===`multipleOf`?e.data%r.value!==BigInt(0)&&(t=this._getOrReturnCtx(e,t),R(t,{code:F.not_multiple_of,multipleOf:r.value,message:r.message}),n.dirty()):N.assertNever(r);return{status:n.value,value:e.data}}gte(e,t){return this.setLimit(`min`,e,!0,B.toString(t))}gt(e,t){return this.setLimit(`min`,e,!1,B.toString(t))}lte(e,t){return this.setLimit(`max`,e,!0,B.toString(t))}lt(e,t){return this.setLimit(`max`,e,!1,B.toString(t))}setLimit(t,n,r,i){return new e({...this._def,checks:[...this._def.checks,{kind:t,value:n,inclusive:r,message:B.toString(i)}]})}_addCheck(t){return new e({...this._def,checks:[...this._def.checks,t]})}positive(e){return this._addCheck({kind:`min`,value:BigInt(0),inclusive:!1,message:B.toString(e)})}negative(e){return this._addCheck({kind:`max`,value:BigInt(0),inclusive:!1,message:B.toString(e)})}nonpositive(e){return this._addCheck({kind:`max`,value:BigInt(0),inclusive:!0,message:B.toString(e)})}nonnegative(e){return this._addCheck({kind:`min`,value:BigInt(0),inclusive:!0,message:B.toString(e)})}multipleOf(e,t){return this._addCheck({kind:`multipleOf`,value:e,message:B.toString(t)})}get minValue(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuenew pt({checks:[],typeName:en.ZodBigInt,coerce:e?.coerce??!1,...We(e)});var mt=class extends Ge{_parse(e){if(this._def.coerce&&(e.data=!!e.data),this._getType(e)!==P.boolean){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.boolean,received:t.parsedType}),z}return Ne(e.data)}};mt.create=e=>new mt({typeName:en.ZodBoolean,coerce:e?.coerce||!1,...We(e)});var ht=class e extends Ge{_parse(e){if(this._def.coerce&&(e.data=new Date(e.data)),this._getType(e)!==P.date){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.date,received:t.parsedType}),z}if(isNaN(e.data.getTime()))return R(this._getOrReturnCtx(e),{code:F.invalid_date}),z;let t=new je,n;for(let r of this._def.checks)r.kind===`min`?e.data.getTime()r.value&&(n=this._getOrReturnCtx(e,n),R(n,{code:F.too_big,message:r.message,inclusive:!0,exact:!1,maximum:r.value,type:`date`}),t.dirty()):N.assertNever(r);return{status:t.value,value:new Date(e.data.getTime())}}_addCheck(t){return new e({...this._def,checks:[...this._def.checks,t]})}min(e,t){return this._addCheck({kind:`min`,value:e.getTime(),message:B.toString(t)})}max(e,t){return this._addCheck({kind:`max`,value:e.getTime(),message:B.toString(t)})}get minDate(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e==null?null:new Date(e)}get maxDate(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuenew ht({checks:[],coerce:e?.coerce||!1,typeName:en.ZodDate,...We(e)});var gt=class extends Ge{_parse(e){if(this._getType(e)!==P.symbol){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.symbol,received:t.parsedType}),z}return Ne(e.data)}};gt.create=e=>new gt({typeName:en.ZodSymbol,...We(e)});var _t=class extends Ge{_parse(e){if(this._getType(e)!==P.undefined){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.undefined,received:t.parsedType}),z}return Ne(e.data)}};_t.create=e=>new _t({typeName:en.ZodUndefined,...We(e)});var vt=class extends Ge{_parse(e){if(this._getType(e)!==P.null){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.null,received:t.parsedType}),z}return Ne(e.data)}};vt.create=e=>new vt({typeName:en.ZodNull,...We(e)});var yt=class extends Ge{constructor(){super(...arguments),this._any=!0}_parse(e){return Ne(e.data)}};yt.create=e=>new yt({typeName:en.ZodAny,...We(e)});var bt=class extends Ge{constructor(){super(...arguments),this._unknown=!0}_parse(e){return Ne(e.data)}};bt.create=e=>new bt({typeName:en.ZodUnknown,...We(e)});var xt=class extends Ge{_parse(e){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.never,received:t.parsedType}),z}};xt.create=e=>new xt({typeName:en.ZodNever,...We(e)});var St=class extends Ge{_parse(e){if(this._getType(e)!==P.undefined){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.void,received:t.parsedType}),z}return Ne(e.data)}};St.create=e=>new St({typeName:en.ZodVoid,...We(e)});var Ct=class e extends Ge{_parse(e){let{ctx:t,status:n}=this._processInputParams(e),r=this._def;if(t.parsedType!==P.array)return R(t,{code:F.invalid_type,expected:P.array,received:t.parsedType}),z;if(r.exactLength!==null){let e=t.data.length>r.exactLength.value,i=t.data.lengthr.maxLength.value&&(R(t,{code:F.too_big,maximum:r.maxLength.value,type:`array`,inclusive:!0,exact:!1,message:r.maxLength.message}),n.dirty()),t.common.async)return Promise.all([...t.data].map((e,n)=>r.type._parseAsync(new He(t,e,t.path,n)))).then(e=>je.mergeArray(n,e));let i=[...t.data].map((e,n)=>r.type._parseSync(new He(t,e,t.path,n)));return je.mergeArray(n,i)}get element(){return this._def.type}min(t,n){return new e({...this._def,minLength:{value:t,message:B.toString(n)}})}max(t,n){return new e({...this._def,maxLength:{value:t,message:B.toString(n)}})}length(t,n){return new e({...this._def,exactLength:{value:t,message:B.toString(n)}})}nonempty(e){return this.min(1,e)}};Ct.create=(e,t)=>new Ct({type:e,minLength:null,maxLength:null,exactLength:null,typeName:en.ZodArray,...We(t)});function wt(e){if(e instanceof Tt){let t={};for(let n in e.shape){let r=e.shape[n];t[n]=Ut.create(wt(r))}return new Tt({...e._def,shape:()=>t})}else if(e instanceof Ct)return new Ct({...e._def,type:wt(e.element)});else if(e instanceof Ut)return Ut.create(wt(e.unwrap()));else if(e instanceof Wt)return Wt.create(wt(e.unwrap()));else if(e instanceof jt)return jt.create(e.items.map(e=>wt(e)));else return e}var Tt=class e extends Ge{constructor(){super(...arguments),this._cached=null,this.nonstrict=this.passthrough,this.augment=this.extend}_getCached(){if(this._cached!==null)return this._cached;let e=this._def.shape(),t=N.objectKeys(e);return this._cached={shape:e,keys:t}}_parse(e){if(this._getType(e)!==P.object){let t=this._getOrReturnCtx(e);return R(t,{code:F.invalid_type,expected:P.object,received:t.parsedType}),z}let{status:t,ctx:n}=this._processInputParams(e),{shape:r,keys:i}=this._getCached(),a=[];if(!(this._def.catchall instanceof xt&&this._def.unknownKeys===`strip`))for(let e in n.data)i.includes(e)||a.push(e);let o=[];for(let e of i){let t=r[e],i=n.data[e];o.push({key:{status:`valid`,value:e},value:t._parse(new He(n,i,n.path,e)),alwaysSet:e in n.data})}if(this._def.catchall instanceof xt){let e=this._def.unknownKeys;if(e===`passthrough`)for(let e of a)o.push({key:{status:`valid`,value:e},value:{status:`valid`,value:n.data[e]}});else if(e===`strict`)a.length>0&&(R(n,{code:F.unrecognized_keys,keys:a}),t.dirty());else if(e!==`strip`)throw Error(`Internal ZodObject error: invalid unknownKeys value.`)}else{let e=this._def.catchall;for(let t of a){let r=n.data[t];o.push({key:{status:`valid`,value:t},value:e._parse(new He(n,r,n.path,t)),alwaysSet:t in n.data})}}return n.common.async?Promise.resolve().then(async()=>{let e=[];for(let t of o){let n=await t.key,r=await t.value;e.push({key:n,value:r,alwaysSet:t.alwaysSet})}return e}).then(e=>je.mergeObjectSync(t,e)):je.mergeObjectSync(t,o)}get shape(){return this._def.shape()}strict(t){return B.errToObj,new e({...this._def,unknownKeys:`strict`,...t===void 0?{}:{errorMap:(e,n)=>{var r;let i=(r=this._def).errorMap?.call(r,e,n).message??n.defaultError;return e.code===`unrecognized_keys`?{message:B.errToObj(t).message??i}:{message:i}}}})}strip(){return new e({...this._def,unknownKeys:`strip`})}passthrough(){return new e({...this._def,unknownKeys:`passthrough`})}extend(t){return new e({...this._def,shape:()=>({...this._def.shape(),...t})})}merge(t){return new e({unknownKeys:t._def.unknownKeys,catchall:t._def.catchall,shape:()=>({...this._def.shape(),...t._def.shape()}),typeName:en.ZodObject})}setKey(e,t){return this.augment({[e]:t})}catchall(t){return new e({...this._def,catchall:t})}pick(t){let n={};return N.objectKeys(t).forEach(e=>{t[e]&&this.shape[e]&&(n[e]=this.shape[e])}),new e({...this._def,shape:()=>n})}omit(t){let n={};return N.objectKeys(this.shape).forEach(e=>{t[e]||(n[e]=this.shape[e])}),new e({...this._def,shape:()=>n})}deepPartial(){return wt(this)}partial(t){let n={};return N.objectKeys(this.shape).forEach(e=>{let r=this.shape[e];t&&!t[e]?n[e]=r:n[e]=r.optional()}),new e({...this._def,shape:()=>n})}required(t){let n={};return N.objectKeys(this.shape).forEach(e=>{if(t&&!t[e])n[e]=this.shape[e];else{let t=this.shape[e];for(;t instanceof Ut;)t=t._def.innerType;n[e]=t}}),new e({...this._def,shape:()=>n})}keyof(){return Rt(N.objectKeys(this.shape))}};Tt.create=(e,t)=>new Tt({shape:()=>e,unknownKeys:`strip`,catchall:xt.create(),typeName:en.ZodObject,...We(t)}),Tt.strictCreate=(e,t)=>new Tt({shape:()=>e,unknownKeys:`strict`,catchall:xt.create(),typeName:en.ZodObject,...We(t)}),Tt.lazycreate=(e,t)=>new Tt({shape:e,unknownKeys:`strip`,catchall:xt.create(),typeName:en.ZodObject,...We(t)});var Et=class extends Ge{_parse(e){let{ctx:t}=this._processInputParams(e),n=this._def.options;function r(e){for(let t of e)if(t.result.status===`valid`)return t.result;for(let n of e)if(n.result.status===`dirty`)return t.common.issues.push(...n.ctx.common.issues),n.result;let n=e.map(e=>new I(e.ctx.common.issues));return R(t,{code:F.invalid_union,unionErrors:n}),z}if(t.common.async)return Promise.all(n.map(async e=>{let n={...t,common:{...t.common,issues:[]},parent:null};return{result:await e._parseAsync({data:t.data,path:t.path,parent:n}),ctx:n}})).then(r);{let e,r=[];for(let i of n){let n={...t,common:{...t.common,issues:[]},parent:null},a=i._parseSync({data:t.data,path:t.path,parent:n});if(a.status===`valid`)return a;a.status===`dirty`&&!e&&(e={result:a,ctx:n}),n.common.issues.length&&r.push(n.common.issues)}if(e)return t.common.issues.push(...e.ctx.common.issues),e.result;let i=r.map(e=>new I(e));return R(t,{code:F.invalid_union,unionErrors:i}),z}}get options(){return this._def.options}};Et.create=(e,t)=>new Et({options:e,typeName:en.ZodUnion,...We(t)});var Dt=e=>e instanceof It?Dt(e.schema):e instanceof Ht?Dt(e.innerType()):e instanceof Lt?[e.value]:e instanceof zt?e.options:e instanceof Bt?N.objectValues(e.enum):e instanceof Gt?Dt(e._def.innerType):e instanceof _t?[void 0]:e instanceof vt?[null]:e instanceof Ut?[void 0,...Dt(e.unwrap())]:e instanceof Wt?[null,...Dt(e.unwrap())]:e instanceof Yt||e instanceof Zt?Dt(e.unwrap()):e instanceof Kt?Dt(e._def.innerType):[],Ot=class e extends Ge{_parse(e){let{ctx:t}=this._processInputParams(e);if(t.parsedType!==P.object)return R(t,{code:F.invalid_type,expected:P.object,received:t.parsedType}),z;let n=this.discriminator,r=t.data[n],i=this.optionsMap.get(r);return i?t.common.async?i._parseAsync({data:t.data,path:t.path,parent:t}):i._parseSync({data:t.data,path:t.path,parent:t}):(R(t,{code:F.invalid_union_discriminator,options:Array.from(this.optionsMap.keys()),path:[n]}),z)}get discriminator(){return this._def.discriminator}get options(){return this._def.options}get optionsMap(){return this._def.optionsMap}static create(t,n,r){let i=new Map;for(let e of n){let n=Dt(e.shape[t]);if(!n.length)throw Error(`A discriminator value for key \`${t}\` could not be extracted from all schema options`);for(let r of n){if(i.has(r))throw Error(`Discriminator property ${String(t)} has duplicate value ${String(r)}`);i.set(r,e)}}return new e({typeName:en.ZodDiscriminatedUnion,discriminator:t,options:n,optionsMap:i,...We(r)})}};function kt(e,t){let n=we(e),r=we(t);if(e===t)return{valid:!0,data:e};if(n===P.object&&r===P.object){let n=N.objectKeys(t),r=N.objectKeys(e).filter(e=>n.indexOf(e)!==-1),i={...e,...t};for(let n of r){let r=kt(e[n],t[n]);if(!r.valid)return{valid:!1};i[n]=r.data}return{valid:!0,data:i}}else if(n===P.array&&r===P.array){if(e.length!==t.length)return{valid:!1};let n=[];for(let r=0;r{if(Pe(e)||Pe(r))return z;let i=kt(e.value,r.value);return i.valid?((Fe(e)||Fe(r))&&t.dirty(),{status:t.value,value:i.data}):(R(n,{code:F.invalid_intersection_types}),z)};return n.common.async?Promise.all([this._def.left._parseAsync({data:n.data,path:n.path,parent:n}),this._def.right._parseAsync({data:n.data,path:n.path,parent:n})]).then(([e,t])=>r(e,t)):r(this._def.left._parseSync({data:n.data,path:n.path,parent:n}),this._def.right._parseSync({data:n.data,path:n.path,parent:n}))}};At.create=(e,t,n)=>new At({left:e,right:t,typeName:en.ZodIntersection,...We(n)});var jt=class e extends Ge{_parse(e){let{status:t,ctx:n}=this._processInputParams(e);if(n.parsedType!==P.array)return R(n,{code:F.invalid_type,expected:P.array,received:n.parsedType}),z;if(n.data.lengththis._def.items.length&&(R(n,{code:F.too_big,maximum:this._def.items.length,inclusive:!0,exact:!1,type:`array`}),t.dirty());let r=[...n.data].map((e,t)=>{let r=this._def.items[t]||this._def.rest;return r?r._parse(new He(n,e,n.path,t)):null}).filter(e=>!!e);return n.common.async?Promise.all(r).then(e=>je.mergeArray(t,e)):je.mergeArray(t,r)}get items(){return this._def.items}rest(t){return new e({...this._def,rest:t})}};jt.create=(e,t)=>{if(!Array.isArray(e))throw Error(`You must pass an array of schemas to z.tuple([ ... ])`);return new jt({items:e,typeName:en.ZodTuple,rest:null,...We(t)})};var Mt=class e extends Ge{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:n}=this._processInputParams(e);if(n.parsedType!==P.object)return R(n,{code:F.invalid_type,expected:P.object,received:n.parsedType}),z;let r=[],i=this._def.keyType,a=this._def.valueType;for(let e in n.data)r.push({key:i._parse(new He(n,e,n.path,e)),value:a._parse(new He(n,n.data[e],n.path,e)),alwaysSet:e in n.data});return n.common.async?je.mergeObjectAsync(t,r):je.mergeObjectSync(t,r)}get element(){return this._def.valueType}static create(t,n,r){return n instanceof Ge?new e({keyType:t,valueType:n,typeName:en.ZodRecord,...We(r)}):new e({keyType:ut.create(),valueType:t,typeName:en.ZodRecord,...We(n)})}},Nt=class extends Ge{get keySchema(){return 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Command`),vr=W.object({command:W.string(),options:W.array(W.object({name:W.string(),value:W.string()})).optional(),content:W.string().max(2e3).optional(),require_launch_channel:W.boolean().optional(),preview_image:W.object({height:W.number(),url:W.string(),width:W.number()}).optional(),components:W.array(W.object({type:W.literal(1),components:W.array(W.object({type:W.literal(2),style:W.number().gte(1).lte(5),label:W.string().max(80).optional(),custom_id:W.string().max(100).describe(`Developer-defined identifier for the button; max 100 characters`).optional()})).max(5).optional()})).optional(),pid:W.number().optional()}).describe(`Request for "SHARE_INTERACTION" Command`),yr=W.object({success:W.boolean()}).describe(`Response for "SHARE_INTERACTION" Command`),br=W.object({custom_id:W.string().max(64).optional(),message:W.string().max(1e3),link_id:W.string().max(64).optional()}).describe(`Request for "SHARE_LINK" Command`),xr=W.object({success:W.boolean(),didCopyLink:W.boolean(),didSendMessage:W.boolean()}).describe(`Response for "SHARE_LINK" Command`),Sr=W.object({relationships:W.array(W.object({type:W.number(),user:W.object({id:W.string(),username:W.string(),global_name:W.union([W.string(),W.null()]).optional(),discriminator:W.string(),avatar:W.union([W.string(),W.null()]).optional(),flags:W.number(),bot:W.boolean(),avatar_decoration_data:W.union([W.object({asset:W.union([W.string(),W.null()]).optional(),skuId:W.string().optional(),expiresAt:W.number().optional()}),W.null()]).optional(),premium_type:W.union([W.number(),W.null()]).optional()}),presence:W.object({status:W.string(),activity:W.union([W.object({session_id:W.string().optional(),type:W.number().optional(),name:W.string(),url:W.union([W.string(),W.null()]).optional(),application_id:W.string().optional(),status_display_type:W.number().optional(),state:W.string().optional(),state_url:W.string().optional(),details:W.string().optional(),details_url:W.string().optional(),emoji:W.union([W.object({name:W.string(),id:W.union([W.string(),W.null()]).optional(),animated:W.union([W.boolean(),W.null()]).optional()}),W.null()]).optional(),assets:W.object({large_image:W.string().optional(),large_text:W.string().optional(),large_url:W.string().optional(),small_image:W.string().optional(),small_text:W.string().optional(),small_url:W.string().optional()}).optional(),timestamps:W.object({start:W.number().optional(),end:W.number().optional()}).optional(),party:W.object({id:W.string().optional(),size:W.array(W.number()).min(2).max(2).optional(),privacy:W.number().optional()}).optional(),secrets:W.object({match:W.string().optional(),join:W.string().optional()}).optional(),sync_id:W.string().optional(),created_at:W.number().optional(),instance:W.boolean().optional(),flags:W.number().optional(),metadata:W.object({}).optional(),platform:W.string().optional(),supported_platforms:W.array(W.string()).optional(),buttons:W.array(W.string()).optional(),hangStatus:W.string().optional()}),W.null()]).optional()}).optional()}))}).describe(`Response for "GET_RELATIONSHIPS" Command`),Cr=W.object({user_id:W.string(),content:W.string().min(0).max(1024).optional()}).describe(`Request for "INVITE_USER_EMBEDDED" Command`),wr=W.object({id:W.string().max(64)}).describe(`Request for "GET_USER" Command`),Tr=W.union([W.object({id:W.string(),username:W.string(),global_name:W.union([W.string(),W.null()]).optional(),discriminator:W.string(),avatar:W.union([W.string(),W.null()]).optional(),flags:W.number(),bot:W.boolean(),avatar_decoration_data:W.union([W.object({asset:W.union([W.string(),W.null()]).optional(),skuId:W.string().optional(),expiresAt:W.number().optional()}),W.null()]).optional(),premium_type:W.union([W.number(),W.null()]).optional()}),W.null()]),Er=W.object({quest_id:W.string()}).describe(`Request for "GET_QUEST_ENROLLMENT_STATUS" Command`),Dr=W.object({quest_id:W.string(),is_enrolled:W.boolean(),enrolled_at:W.union([W.string(),W.null()]).optional()}).describe(`Response for "GET_QUEST_ENROLLMENT_STATUS" Command`),Or=W.object({quest_id:W.string()}).describe(`Request for "QUEST_START_TIMER" Command`),kr=W.object({success:W.boolean()}).describe(`Response for "QUEST_START_TIMER" Command`),Ar=W.object({quest_id:W.string(),enrolled_at:W.union([W.string(),W.null()]).optional(),completed_at:W.union([W.string(),W.null()]).optional(),external_cta_url:W.string()}).describe(`Response for "GET_QUEST" Command`),jr=W.object({ticket:W.string()}).describe(`Response for "REQUEST_PROXY_TICKET_REFRESH" Command`),Mr;(function(e){e.INITIATE_IMAGE_UPLOAD=`INITIATE_IMAGE_UPLOAD`,e.OPEN_SHARE_MOMENT_DIALOG=`OPEN_SHARE_MOMENT_DIALOG`,e.AUTHENTICATE=`AUTHENTICATE`,e.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS=`GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS`,e.SHARE_INTERACTION=`SHARE_INTERACTION`,e.SHARE_LINK=`SHARE_LINK`,e.GET_RELATIONSHIPS=`GET_RELATIONSHIPS`,e.INVITE_USER_EMBEDDED=`INVITE_USER_EMBEDDED`,e.GET_USER=`GET_USER`,e.GET_QUEST_ENROLLMENT_STATUS=`GET_QUEST_ENROLLMENT_STATUS`,e.QUEST_START_TIMER=`QUEST_START_TIMER`,e.GET_QUEST=`GET_QUEST`,e.REQUEST_PROXY_TICKET_REFRESH=`REQUEST_PROXY_TICKET_REFRESH`})(Mr||={});var Nr=W.object({}).optional().nullable(),Pr=W.void(),Fr={[Mr.INITIATE_IMAGE_UPLOAD]:{request:Pr,response:pr},[Mr.OPEN_SHARE_MOMENT_DIALOG]:{request:mr,response:Nr},[Mr.AUTHENTICATE]:{request:hr,response:gr},[Mr.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS]:{request:Pr,response:_r},[Mr.SHARE_INTERACTION]:{request:vr,response:yr},[Mr.SHARE_LINK]:{request:br,response:xr},[Mr.GET_RELATIONSHIPS]:{request:Pr,response:Sr},[Mr.INVITE_USER_EMBEDDED]:{request:Cr,response:Nr},[Mr.GET_USER]:{request:wr,response:Tr},[Mr.GET_QUEST_ENROLLMENT_STATUS]:{request:Er,response:Dr},[Mr.QUEST_START_TIMER]:{request:Or,response:kr},[Mr.GET_QUEST]:{request:Pr,response:Ar},[Mr.REQUEST_PROXY_TICKET_REFRESH]:{request:Pr,response:jr}},Ir=t({Activity:()=>Xr,Attachment:()=>ai,CertifiedDevice:()=>Ti,CertifiedDeviceTypeObject:()=>wi,Channel:()=>ei,ChannelMention:()=>ii,ChannelTypesObject:()=>$r,Commands:()=>G,DISPATCH:()=>Lr,Embed:()=>fi,EmbedAuthor:()=>ui,EmbedField:()=>di,EmbedFooter:()=>oi,EmbedProvider:()=>li,Emoji:()=>Gr,Entitlement:()=>ki,EntitlementTypesObject:()=>Oi,Guild:()=>ri,GuildMember:()=>Ur,GuildMemberRPC:()=>Wr,Image:()=>si,KeyTypesObject:()=>yi,LayoutMode:()=>Li,LayoutModeTypeObject:()=>Ii,Message:()=>_i,MessageActivity:()=>mi,MessageApplication:()=>hi,MessageReference:()=>gi,Orientation:()=>Fi,OrientationLockState:()=>ji,OrientationLockStateTypeObject:()=>Ai,OrientationTypeObject:()=>Pi,PermissionOverwrite:()=>Qr,PermissionOverwriteTypeObject:()=>Zr,PresenceUpdate:()=>ti,Reaction:()=>pi,ReceiveFramePayload:()=>Rr,Relationship:()=>Vr,Role:()=>ni,Scopes:()=>Br,ScopesObject:()=>zr,ShortcutKey:()=>bi,Sku:()=>Di,SkuTypeObject:()=>Ei,Status:()=>Yr,StatusObject:()=>Jr,ThermalState:()=>Ni,ThermalStateTypeObject:()=>Mi,User:()=>Hr,UserVoiceState:()=>qr,Video:()=>ci,VoiceDevice:()=>vi,VoiceSettingModeTypeObject:()=>xi,VoiceSettingsIO:()=>Ci,VoiceSettingsMode:()=>Si,VoiceState:()=>Kr}),Lr=`DISPATCH`,G;(function(e){e.AUTHORIZE=`AUTHORIZE`,e.GET_GUILDS=`GET_GUILDS`,e.GET_GUILD=`GET_GUILD`,e.GET_CHANNEL=`GET_CHANNEL`,e.GET_CHANNELS=`GET_CHANNELS`,e.SELECT_VOICE_CHANNEL=`SELECT_VOICE_CHANNEL`,e.SELECT_TEXT_CHANNEL=`SELECT_TEXT_CHANNEL`,e.SUBSCRIBE=`SUBSCRIBE`,e.UNSUBSCRIBE=`UNSUBSCRIBE`,e.CAPTURE_SHORTCUT=`CAPTURE_SHORTCUT`,e.SET_CERTIFIED_DEVICES=`SET_CERTIFIED_DEVICES`,e.SET_ACTIVITY=`SET_ACTIVITY`,e.GET_SKUS=`GET_SKUS`,e.GET_ENTITLEMENTS=`GET_ENTITLEMENTS`,e.GET_SKUS_EMBEDDED=`GET_SKUS_EMBEDDED`,e.GET_ENTITLEMENTS_EMBEDDED=`GET_ENTITLEMENTS_EMBEDDED`,e.START_PURCHASE=`START_PURCHASE`,e.SET_CONFIG=`SET_CONFIG`,e.SEND_ANALYTICS_EVENT=`SEND_ANALYTICS_EVENT`,e.USER_SETTINGS_GET_LOCALE=`USER_SETTINGS_GET_LOCALE`,e.OPEN_EXTERNAL_LINK=`OPEN_EXTERNAL_LINK`,e.ENCOURAGE_HW_ACCELERATION=`ENCOURAGE_HW_ACCELERATION`,e.CAPTURE_LOG=`CAPTURE_LOG`,e.SET_ORIENTATION_LOCK_STATE=`SET_ORIENTATION_LOCK_STATE`,e.OPEN_INVITE_DIALOG=`OPEN_INVITE_DIALOG`,e.GET_PLATFORM_BEHAVIORS=`GET_PLATFORM_BEHAVIORS`,e.GET_CHANNEL_PERMISSIONS=`GET_CHANNEL_PERMISSIONS`,e.AUTHENTICATE=`AUTHENTICATE`,e.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS=`GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS`,e.GET_QUEST=`GET_QUEST`,e.GET_QUEST_ENROLLMENT_STATUS=`GET_QUEST_ENROLLMENT_STATUS`,e.GET_RELATIONSHIPS=`GET_RELATIONSHIPS`,e.GET_USER=`GET_USER`,e.INITIATE_IMAGE_UPLOAD=`INITIATE_IMAGE_UPLOAD`,e.INVITE_USER_EMBEDDED=`INVITE_USER_EMBEDDED`,e.OPEN_SHARE_MOMENT_DIALOG=`OPEN_SHARE_MOMENT_DIALOG`,e.QUEST_START_TIMER=`QUEST_START_TIMER`,e.REQUEST_PROXY_TICKET_REFRESH=`REQUEST_PROXY_TICKET_REFRESH`,e.SHARE_INTERACTION=`SHARE_INTERACTION`,e.SHARE_LINK=`SHARE_LINK`})(G||={});var Rr=U({cmd:V(),data:dn(),evt:ln(),nonce:V()}).passthrough(),zr=Object.assign(Object.assign({},gr.shape.scopes.element.overlayType._def.innerType.options[0].Values),{UNHANDLED:-1}),Br=dr(zr),Vr=Sr.shape.relationships.element,Hr=U({id:V(),username:V(),discriminator:V(),global_name:V().optional().nullable(),avatar:V().optional().nullable(),avatar_decoration_data:U({asset:V(),sku_id:V().optional()}).nullable(),bot:an(),flags:H().optional().nullable(),premium_type:H().optional().nullable()}),Ur=U({user:Hr,nick:V().optional().nullable(),roles:mn(V()),joined_at:V(),deaf:an(),mute:an()}),Wr=U({user_id:V(),nick:V().optional().nullable(),guild_id:V(),avatar:V().optional().nullable(),avatar_decoration_data:U({asset:V(),sku_id:V().optional().nullable()}).optional().nullable(),color_string:V().optional().nullable()}),Gr=U({id:V(),name:V().optional().nullable(),roles:mn(V()).optional().nullable(),user:Hr.optional().nullable(),require_colons:an().optional().nullable(),managed:an().optional().nullable(),animated:an().optional().nullable(),available:an().optional().nullable()}),Kr=U({mute:an(),deaf:an(),self_mute:an(),self_deaf:an(),suppress:an()}),qr=U({mute:an(),nick:V(),user:Hr,voice_state:Kr,volume:H()}),Jr={UNHANDLED:-1,IDLE:`idle`,DND:`dnd`,ONLINE:`online`,OFFLINE:`offline`},Yr=dr(Jr),Xr=U({name:V(),type:H(),url:V().optional().nullable(),created_at:H().optional().nullable(),timestamps:U({start:H(),end:H()}).partial().optional().nullable(),application_id:V().optional().nullable(),details:V().optional().nullable(),details_url:V().url().optional().nullable(),state:V().optional().nullable(),state_url:V().url().optional().nullable(),emoji:Gr.optional().nullable(),party:U({id:V().optional().nullable(),size:mn(H()).optional().nullable()}).optional().nullable(),assets:U({large_image:V().nullable(),large_text:V().nullable(),large_url:V().url().optional().nullable(),small_image:V().nullable(),small_text:V().nullable(),small_url:V().url().optional().nullable()}).partial().optional().nullable(),secrets:U({join:V(),match:V()}).partial().optional().nullable(),instance:an().optional().nullable(),flags:H().optional().nullable()}),Zr={UNHANDLED:-1,ROLE:0,MEMBER:1},Qr=U({id:V(),type:dr(Zr),allow:V(),deny:V()}),$r={UNHANDLED:-1,DM:1,GROUP_DM:3,GUILD_TEXT:0,GUILD_VOICE:2,GUILD_CATEGORY:4,GUILD_ANNOUNCEMENT:5,GUILD_STORE:6,ANNOUNCEMENT_THREAD:10,PUBLIC_THREAD:11,PRIVATE_THREAD:12,GUILD_STAGE_VOICE:13,GUILD_DIRECTORY:14,GUILD_FORUM:15},ei=U({id:V(),type:dr($r),guild_id:V().optional().nullable(),position:H().optional().nullable(),permission_overwrites:mn(Qr).optional().nullable(),name:V().optional().nullable(),topic:V().optional().nullable(),nsfw:an().optional().nullable(),last_message_id:V().optional().nullable(),bitrate:H().optional().nullable(),user_limit:H().optional().nullable(),rate_limit_per_user:H().optional().nullable(),recipients:mn(Hr).optional().nullable(),icon:V().optional().nullable(),owner_id:V().optional().nullable(),application_id:V().optional().nullable(),parent_id:V().optional().nullable(),last_pin_timestamp:V().optional().nullable()}),ti=U({user:Hr,guild_id:V(),status:Yr,activities:mn(Xr),client_status:U({desktop:Yr,mobile:Yr,web:Yr}).partial()}),ni=U({id:V(),name:V(),color:H(),hoist:an(),position:H(),permissions:V(),managed:an(),mentionable:an()}),ri=U({id:V(),name:V(),owner_id:V(),icon:V().nullable(),icon_hash:V().optional().nullable(),splash:V().nullable(),discovery_splash:V().nullable(),owner:an().optional().nullable(),permissions:V().optional().nullable(),region:V(),afk_channel_id:V().nullable(),afk_timeout:H(),widget_enabled:an().optional().nullable(),widget_channel_id:V().optional().nullable(),verification_level:H(),default_message_notifications:H(),explicit_content_filter:H(),roles:mn(ni),emojis:mn(Gr),features:mn(V()),mfa_level:H(),application_id:V().nullable(),system_channel_id:V().nullable(),system_channel_flags:H(),rules_channel_id:V().nullable(),joined_at:V().optional().nullable(),large:an().optional().nullable(),unavailable:an().optional().nullable(),member_count:H().optional().nullable(),voice_states:mn(Kr).optional().nullable(),members:mn(Ur).optional().nullable(),channels:mn(ei).optional().nullable(),presences:mn(ti).optional().nullable(),max_presences:H().optional().nullable(),max_members:H().optional().nullable(),vanity_url_code:V().nullable(),description:V().nullable(),banner:V().nullable(),premium_tier:H(),premium_subscription_count:H().optional().nullable(),preferred_locale:V(),public_updates_channel_id:V().nullable(),max_video_channel_users:H().optional().nullable(),approximate_member_count:H().optional().nullable(),approximate_presence_count:H().optional().nullable()}),ii=U({id:V(),guild_id:V(),type:H(),name:V()}),ai=U({id:V(),filename:V(),size:H(),url:V(),proxy_url:V(),height:H().optional().nullable(),width:H().optional().nullable()}),oi=U({text:V(),icon_url:V().optional().nullable(),proxy_icon_url:V().optional().nullable()}),si=U({url:V().optional().nullable(),proxy_url:V().optional().nullable(),height:H().optional().nullable(),width:H().optional().nullable()}),ci=si.omit({proxy_url:!0}),li=U({name:V().optional().nullable(),url:V().optional().nullable()}),ui=U({name:V().optional().nullable(),url:V().optional().nullable(),icon_url:V().optional().nullable(),proxy_icon_url:V().optional().nullable()}),di=U({name:V(),value:V(),inline:an()}),fi=U({title:V().optional().nullable(),type:V().optional().nullable(),description:V().optional().nullable(),url:V().optional().nullable(),timestamp:V().optional().nullable(),color:H().optional().nullable(),footer:oi.optional().nullable(),image:si.optional().nullable(),thumbnail:si.optional().nullable(),video:ci.optional().nullable(),provider:li.optional().nullable(),author:ui.optional().nullable(),fields:mn(di).optional().nullable()}),pi=U({count:H(),me:an(),emoji:Gr}),mi=U({type:H(),party_id:V().optional().nullable()}),hi=U({id:V(),cover_image:V().optional().nullable(),description:V(),icon:V().optional().nullable(),name:V()}),gi=U({message_id:V().optional().nullable(),channel_id:V().optional().nullable(),guild_id:V().optional().nullable()}),_i=U({id:V(),channel_id:V(),guild_id:V().optional().nullable(),author:Hr.optional().nullable(),member:Ur.optional().nullable(),content:V(),timestamp:V(),edited_timestamp:V().optional().nullable(),tts:an(),mention_everyone:an(),mentions:mn(Hr),mention_roles:mn(V()),mention_channels:mn(ii),attachments:mn(ai),embeds:mn(fi),reactions:mn(pi).optional().nullable(),nonce:gn([V(),H()]).optional().nullable(),pinned:an(),webhook_id:V().optional().nullable(),type:H(),activity:mi.optional().nullable(),application:hi.optional().nullable(),message_reference:gi.optional().nullable(),flags:H().optional().nullable(),stickers:mn(dn()).optional().nullable(),referenced_message:dn().optional().nullable()}),vi=U({id:V(),name:V()}),yi={UNHANDLED:-1,KEYBOARD_KEY:0,MOUSE_BUTTON:1,KEYBOARD_MODIFIER_KEY:2,GAMEPAD_BUTTON:3},bi=U({type:dr(yi),code:H(),name:V()}),xi={UNHANDLED:-1,PUSH_TO_TALK:`PUSH_TO_TALK`,VOICE_ACTIVITY:`VOICE_ACTIVITY`},Si=U({type:dr(xi),auto_threshold:an(),threshold:H(),shortcut:mn(bi),delay:H()}),Ci=U({device_id:V(),volume:H(),available_devices:mn(vi)}),wi={UNHANDLED:-1,AUDIO_INPUT:`AUDIO_INPUT`,AUDIO_OUTPUT:`AUDIO_OUTPUT`,VIDEO_INPUT:`VIDEO_INPUT`},Ti=U({type:dr(wi),id:V(),vendor:U({name:V(),url:V()}),model:U({name:V(),url:V()}),related:mn(V()),echo_cancellation:an().optional().nullable(),noise_suppression:an().optional().nullable(),automatic_gain_control:an().optional().nullable(),hardware_mute:an().optional().nullable()}),Ei={UNHANDLED:-1,APPLICATION:1,DLC:2,CONSUMABLE:3,BUNDLE:4,SUBSCRIPTION:5},Di=U({id:V(),name:V(),type:dr(Ei),price:U({amount:H(),currency:V()}),application_id:V(),flags:H(),release_date:V().nullable()}),Oi={UNHANDLED:-1,PURCHASE:1,PREMIUM_SUBSCRIPTION:2,DEVELOPER_GIFT:3,TEST_MODE_PURCHASE:4,FREE_PURCHASE:5,USER_GIFT:6,PREMIUM_PURCHASE:7},ki=U({id:V(),sku_id:V(),application_id:V(),user_id:V(),gift_code_flags:H(),type:dr(Oi),gifter_user_id:V().optional().nullable(),branches:mn(V()).optional().nullable(),starts_at:V().optional().nullable(),ends_at:V().optional().nullable(),parent_id:V().optional().nullable(),consumed:an().optional().nullable(),deleted:an().optional().nullable(),gift_code_batch_id:V().optional().nullable()}),Ai={UNHANDLED:-1,UNLOCKED:1,PORTRAIT:2,LANDSCAPE:3},ji=dr(Ai),Mi={UNHANDLED:-1,NOMINAL:0,FAIR:1,SERIOUS:2,CRITICAL:3},Ni=dr(Mi),Pi={UNHANDLED:-1,PORTRAIT:0,LANDSCAPE:1},Fi=dr(Pi),Ii={UNHANDLED:-1,FOCUSED:0,PIP:1,GRID:2},Li=dr(Ii),Ri=`ERROR`,zi;(function(e){e.READY=`READY`,e.VOICE_STATE_UPDATE=`VOICE_STATE_UPDATE`,e.SPEAKING_START=`SPEAKING_START`,e.SPEAKING_STOP=`SPEAKING_STOP`,e.ACTIVITY_LAYOUT_MODE_UPDATE=`ACTIVITY_LAYOUT_MODE_UPDATE`,e.ORIENTATION_UPDATE=`ORIENTATION_UPDATE`,e.CURRENT_USER_UPDATE=`CURRENT_USER_UPDATE`,e.CURRENT_GUILD_MEMBER_UPDATE=`CURRENT_GUILD_MEMBER_UPDATE`,e.ENTITLEMENT_CREATE=`ENTITLEMENT_CREATE`,e.THERMAL_STATE_UPDATE=`THERMAL_STATE_UPDATE`,e.ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE=`ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE`,e.RELATIONSHIP_UPDATE=`RELATIONSHIP_UPDATE`,e.ACTIVITY_JOIN=`ACTIVITY_JOIN`,e.QUEST_ENROLLMENT_STATUS_UPDATE=`QUEST_ENROLLMENT_STATUS_UPDATE`})(zi||={});var Bi=Rr.extend({evt:Dn(zi),nonce:V().nullable(),cmd:Tn(Lr),data:U({}).passthrough()}),Vi=Rr.extend({evt:Tn(Ri),data:U({code:H(),message:V().optional()}).passthrough(),cmd:Dn(G),nonce:V().nullable()}),Hi=gn([Bi,Bi.extend({evt:V()}),Vi]);function Ui(e){let t=e.evt;if(!(t in zi))throw Error(`Unrecognized event type ${e.evt}`);return Wi[t].payload.parse(e)}var Wi={[zi.READY]:{payload:Bi.extend({evt:Tn(zi.READY),data:U({v:H(),config:U({cdn_host:V().optional(),api_endpoint:V(),environment:V()}),user:U({id:V(),username:V(),discriminator:V(),avatar:V().optional()}).optional()})})},[zi.VOICE_STATE_UPDATE]:{payload:Bi.extend({evt:Tn(zi.VOICE_STATE_UPDATE),data:qr}),subscribeArgs:U({channel_id:V()})},[zi.SPEAKING_START]:{payload:Bi.extend({evt:Tn(zi.SPEAKING_START),data:U({lobby_id:V().optional(),channel_id:V().optional(),user_id:V()})}),subscribeArgs:U({lobby_id:V().nullable().optional(),channel_id:V().nullable().optional()})},[zi.SPEAKING_STOP]:{payload:Bi.extend({evt:Tn(zi.SPEAKING_STOP),data:U({lobby_id:V().optional(),channel_id:V().optional(),user_id:V()})}),subscribeArgs:U({lobby_id:V().nullable().optional(),channel_id:V().nullable().optional()})},[zi.ACTIVITY_LAYOUT_MODE_UPDATE]:{payload:Bi.extend({evt:Tn(zi.ACTIVITY_LAYOUT_MODE_UPDATE),data:U({layout_mode:dr(Ii)})})},[zi.ORIENTATION_UPDATE]:{payload:Bi.extend({evt:Tn(zi.ORIENTATION_UPDATE),data:U({screen_orientation:dr(Pi),orientation:Dn(lr)})})},[zi.CURRENT_USER_UPDATE]:{payload:Bi.extend({evt:Tn(zi.CURRENT_USER_UPDATE),data:Hr})},[zi.CURRENT_GUILD_MEMBER_UPDATE]:{payload:Bi.extend({evt:Tn(zi.CURRENT_GUILD_MEMBER_UPDATE),data:Wr}),subscribeArgs:U({guild_id:V()})},[zi.ENTITLEMENT_CREATE]:{payload:Bi.extend({evt:Tn(zi.ENTITLEMENT_CREATE),data:U({entitlement:ki})})},[zi.THERMAL_STATE_UPDATE]:{payload:Bi.extend({evt:Tn(zi.THERMAL_STATE_UPDATE),data:U({thermal_state:Ni})})},[zi.ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE]:{payload:Bi.extend({evt:Tn(zi.ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE),data:U({participants:_r.shape.participants})})},[zi.RELATIONSHIP_UPDATE]:{payload:Bi.extend({evt:Tn(zi.RELATIONSHIP_UPDATE),data:Vr})},[zi.ACTIVITY_JOIN]:{payload:Bi.extend({evt:Tn(zi.ACTIVITY_JOIN),data:U({applicationId:V(),secret:V()})})},[zi.QUEST_ENROLLMENT_STATUS_UPDATE]:{payload:Bi.extend({evt:Tn(zi.QUEST_ENROLLMENT_STATUS_UPDATE),data:U({quest_id:V(),is_enrolled:an(),enrolled_at:V().date()})})}};function Gi(e,t){throw t}var Ki=U({}).nullable(),qi=U({code:V()}),Ji=U({guilds:mn(U({id:V(),name:V()}))}),Yi=U({id:V(),name:V(),icon_url:V().optional(),members:mn(Ur)}),Xi=U({id:V(),type:dr($r),guild_id:V().optional().nullable(),name:V().optional().nullable(),topic:V().optional().nullable(),bitrate:H().optional().nullable(),user_limit:H().optional().nullable(),position:H().optional().nullable(),voice_states:mn(qr),messages:mn(_i)}),Zi=U({channels:mn(ei)});Xi.nullable();var Qi=Xi.nullable(),$i=Xi.nullable();U({input:Ci,output:Ci,mode:Si,automatic_gain_control:an(),echo_cancellation:an(),noise_suppression:an(),qos:an(),silence_warning:an(),deaf:an(),mute:an()});var ea=U({evt:V()}),ta=U({shortcut:bi}),na=Xr,ra=U({skus:mn(Di)}),ia=U({entitlements:mn(ki)}),aa=mn(ki).nullable(),oa=U({use_interactive_pip:an()}),sa=U({locale:V()}),ca=U({enabled:an()}),la=U({permissions:rn().or(V())}),ua=fr(U({opened:an().or(ln())}).default({opened:null})),da=U({iosKeyboardResizesView:An(an())}),fa=Rr.extend({cmd:Dn(G),evt:ln()});function pa({cmd:e,data:t}){switch(e){case G.AUTHORIZE:return qi.parse(t);case G.CAPTURE_SHORTCUT:return ta.parse(t);case G.ENCOURAGE_HW_ACCELERATION:return ca.parse(t);case G.GET_CHANNEL:return Xi.parse(t);case G.GET_CHANNELS:return Zi.parse(t);case G.GET_CHANNEL_PERMISSIONS:return la.parse(t);case G.GET_GUILD:return Yi.parse(t);case G.GET_GUILDS:return Ji.parse(t);case G.GET_PLATFORM_BEHAVIORS:return da.parse(t);case G.GET_CHANNEL:return Xi.parse(t);case G.SELECT_TEXT_CHANNEL:return $i.parse(t);case G.SELECT_VOICE_CHANNEL:return Qi.parse(t);case G.SET_ACTIVITY:return na.parse(t);case G.GET_SKUS_EMBEDDED:return ra.parse(t);case G.GET_ENTITLEMENTS_EMBEDDED:return ia.parse(t);case G.SET_CONFIG:return oa.parse(t);case G.START_PURCHASE:return aa.parse(t);case G.SUBSCRIBE:case G.UNSUBSCRIBE:return ea.parse(t);case G.USER_SETTINGS_GET_LOCALE:return sa.parse(t);case G.OPEN_EXTERNAL_LINK:return ua.parse(t);case G.SET_ORIENTATION_LOCK_STATE:case G.SET_CERTIFIED_DEVICES:case G.SEND_ANALYTICS_EVENT:case G.OPEN_INVITE_DIALOG:case G.CAPTURE_LOG:case G.GET_SKUS:case G.GET_ENTITLEMENTS:return Ki.parse(t);case G.AUTHENTICATE:case G.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS:case G.GET_QUEST:case G.GET_QUEST_ENROLLMENT_STATUS:case G.GET_RELATIONSHIPS:case G.GET_USER:case G.INITIATE_IMAGE_UPLOAD:case G.INVITE_USER_EMBEDDED:case G.OPEN_SHARE_MOMENT_DIALOG:case G.QUEST_START_TIMER:case G.REQUEST_PROXY_TICKET_REFRESH:case G.SHARE_INTERACTION:case G.SHARE_LINK:let{response:n}=Fr[e];return n.parse(t);default:Gi(e,Error(`Unrecognized command ${e}`))}}function ma(e){return 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ba=e=>va(e,G.AUTHORIZE,qi),xa=e=>va(e,G.CAPTURE_LOG,Ki),Sa=e=>va(e,G.ENCOURAGE_HW_ACCELERATION,ca),Ca=e=>va(e,G.GET_CHANNEL,Xi),wa=e=>va(e,G.GET_ENTITLEMENTS_EMBEDDED,ia),Ta=e=>va(e,G.GET_SKUS_EMBEDDED,ra),Ea=e=>va(e,G.GET_CHANNEL_PERMISSIONS,la),Da=e=>va(e,G.GET_PLATFORM_BEHAVIORS,da),Oa=e=>va(e,G.OPEN_EXTERNAL_LINK,ua),ka=e=>va(e,G.OPEN_INVITE_DIALOG,Ki);Xr.pick({state:!0,state_url:!0,details:!0,details_url:!0,timestamps:!0,assets:!0,party:!0,secrets:!0,instance:!0,type:!0}).extend({type:Xr.shape.type.optional(),instance:Xr.shape.instance.optional()}).nullable();var Aa=e=>va(e,G.SET_ACTIVITY,na),ja=e=>va(e,G.SET_CONFIG,oa);function Ma({sendCommand:e,cmd:t,response:n,fallbackTransform:r,transferTransform:i=()=>void 0}){let a=Rr.extend({cmd:Tn(t),data:n});return async n=>{try{let r=await e({cmd:t,args:n,transfer:i(n)});return a.parse(r).data}catch(o){if(o.code===cr.INVALID_PAYLOAD){let o=r(n),s=await e({cmd:t,args:o,transfer:i(o)});return a.parse(s).data}else throw o}}}var Na=e=>({lock_state:e.lock_state,picture_in_picture_lock_state:e.picture_in_picture_lock_state}),Pa=e=>Ma({sendCommand:e,cmd:G.SET_ORIENTATION_LOCK_STATE,response:Ki,fallbackTransform:Na}),Fa=e=>va(e,G.START_PURCHASE,aa),Ia=e=>va(e,G.USER_SETTINGS_GET_LOCALE,sa),La=ya(Mr.AUTHENTICATE),Ra=ya(Mr.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS),za=ya(Mr.GET_QUEST),Ba=ya(Mr.GET_QUEST_ENROLLMENT_STATUS),Va=ya(Mr.GET_RELATIONSHIPS),Ha=ya(Mr.GET_USER),Ua=ya(Mr.INITIATE_IMAGE_UPLOAD),Wa=ya(Mr.INVITE_USER_EMBEDDED),Ga=ya(Mr.OPEN_SHARE_MOMENT_DIALOG),Ka=ya(Mr.QUEST_START_TIMER),qa=ya(Mr.REQUEST_PROXY_TICKET_REFRESH),Ja=ya(Mr.SHARE_INTERACTION),Ya=ya(Mr.SHARE_LINK);function 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s=n[r+0],c=n[r+1],l=n[r+2],u=n[r+3],d=i[a+0],f=i[a+1],p=i[a+2],m=i[a+3];if(u!==m||s!==d||c!==f||l!==p){let e=s*d+c*f+l*p+u*m;e<0&&(d=-d,f=-f,p=-p,m=-m,e=-e);let t=1-o;if(e<.9995){let n=Math.acos(e),r=Math.sin(n);t=Math.sin(t*n)/r,o=Math.sin(o*n)/r,s=s*t+d*o,c=c*t+f*o,l=l*t+p*o,u=u*t+m*o}else{s=s*t+d*o,c=c*t+f*o,l=l*t+p*o,u=u*t+m*o;let e=1/Math.sqrt(s*s+c*c+l*l+u*u);s*=e,c*=e,l*=e,u*=e}}e[t]=s,e[t+1]=c,e[t+2]=l,e[t+3]=u}static multiplyQuaternionsFlat(e,t,n,r,i,a){let o=n[r],s=n[r+1],c=n[r+2],l=n[r+3],u=i[a],d=i[a+1],f=i[a+2],p=i[a+3];return e[t]=o*p+l*u+s*f-c*d,e[t+1]=s*p+l*d+c*u-o*f,e[t+2]=c*p+l*f+o*d-s*u,e[t+3]=l*p-o*u-s*d-c*f,e}get x(){return this._x}set x(e){this._x=e,this._onChangeCallback()}get y(){return this._y}set y(e){this._y=e,this._onChangeCallback()}get z(){return this._z}set z(e){this._z=e,this._onChangeCallback()}get w(){return this._w}set w(e){this._w=e,this._onChangeCallback()}set(e,t,n,r){return 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t=0;t.025?(c.inputState.pinching=!1,this.dispatchEvent({type:`pinchend`,handedness:e.handedness,target:this})):!c.inputState.pinching&&o<=.015&&(c.inputState.pinching=!0,this.dispatchEvent({type:`pinchstart`,handedness:e.handedness,target:this}))}else s!==null&&e.gripSpace&&(i=t.getPose(e.gripSpace,n),i!==null&&(s.matrix.fromArray(i.transform.matrix),s.matrix.decompose(s.position,s.rotation,s.scale),s.matrixWorldNeedsUpdate=!0,i.linearVelocity?(s.hasLinearVelocity=!0,s.linearVelocity.copy(i.linearVelocity)):s.hasLinearVelocity=!1,i.angularVelocity?(s.hasAngularVelocity=!0,s.angularVelocity.copy(i.angularVelocity)):s.hasAngularVelocity=!1,s.eventsEnabled&&s.dispatchEvent({type:`gripUpdated`,data:e,target:this})));o!==null&&(r=t.getPose(e.targetRaySpace,n),r===null&&i!==null&&(r=i),r!==null&&(o.matrix.fromArray(r.transform.matrix),o.matrix.decompose(o.position,o.rotation,o.scale),o.matrixWorldNeedsUpdate=!0,r.linearVelocity?(o.hasLinearVelocity=!0,o.linearVelocity.copy(r.linearVelocity)):o.hasLinearVelocity=!1,r.angularVelocity?(o.hasAngularVelocity=!0,o.angularVelocity.copy(r.angularVelocity)):o.hasAngularVelocity=!1,this.dispatchEvent(Xu)))}return o!==null&&(o.visible=r!==null),s!==null&&(s.visible=i!==null),c!==null&&(c.visible=a!==null),this}_getHandJoint(e,t){if(e.joints[t.jointName]===void 0){let n=new Yu;n.matrixAutoUpdate=!1,n.visible=!1,e.joints[t.jointName]=n,e.add(n)}return 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td(e,t,n){return n<0&&(n+=1),n>1&&--n,n<1/6?e+(t-e)*6*n:n<1/2?t:n<2/3?e+(t-e)*6*(2/3-n):e}var Z=class{constructor(e,t,n){return this.isColor=!0,this.r=1,this.g=1,this.b=1,this.set(e,t,n)}set(e,t,n){if(t===void 0&&n===void 0){let t=e;t&&t.isColor?this.copy(t):typeof t==`number`?this.setHex(t):typeof t==`string`&&this.setStyle(t)}else this.setRGB(e,t,n);return this}setScalar(e){return this.r=e,this.g=e,this.b=e,this}setHex(e,t=il){return e=Math.floor(e),this.r=(e>>16&255)/255,this.g=(e>>8&255)/255,this.b=(e&255)/255,au.colorSpaceToWorking(this,t),this}setRGB(e,t,n,r=au.workingColorSpace){return this.r=e,this.g=t,this.b=n,au.colorSpaceToWorking(this,r),this}setHSL(e,t,n,r=au.workingColorSpace){if(e=Al(e,1),t=kl(t,0,1),n=kl(n,0,1),t===0)this.r=this.g=this.b=n;else{let r=n<=.5?n*(1+t):n+t-n*t,i=2*n-r;this.r=td(i,r,e+1/3),this.g=td(i,r,e),this.b=td(i,r,e-1/3)}return au.colorSpaceToWorking(this,r),this}setStyle(e,t=il){function n(t){t!==void 0&&parseFloat(t)<1&&J(`Color: Alpha component of 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this.setRGB(parseInt(n.charAt(0),16)/15,parseInt(n.charAt(1),16)/15,parseInt(n.charAt(2),16)/15,t);if(i===6)return this.setHex(parseInt(n,16),t);J(`Color: Invalid hex color `+e)}else if(e&&e.length>0)return this.setColorName(e,t);return this}setColorName(e,t=il){let n=Qu[e.toLowerCase()];return n===void 0?J(`Color: Unknown color `+e):this.setHex(n,t),this}clone(){return new this.constructor(this.r,this.g,this.b)}copy(e){return this.r=e.r,this.g=e.g,this.b=e.b,this}copySRGBToLinear(e){return this.r=ou(e.r),this.g=ou(e.g),this.b=ou(e.b),this}copyLinearToSRGB(e){return this.r=su(e.r),this.g=su(e.g),this.b=su(e.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(e=il){return au.workingToColorSpace(nd.copy(this),e),Math.round(kl(nd.r*255,0,255))*65536+Math.round(kl(nd.g*255,0,255))*256+Math.round(kl(nd.b*255,0,255))}getHexString(e=il){return(`000000`+this.getHex(e).toString(16)).slice(-6)}getHSL(e,t=au.workingColorSpace){au.workingToColorSpace(nd.copy(this),t);let n=nd.r,r=nd.g,i=nd.b,a=Math.max(n,r,i),o=Math.min(n,r,i),s,c,l=(o+a)/2;if(o===a)s=0,c=0;else{let e=a-o;switch(c=l<=.5?e/(a+o):e/(2-a-o),a){case n:s=(r-i)/e+(r0&&(t.object.backgroundBlurriness=this.backgroundBlurriness),this.backgroundIntensity!==1&&(t.object.backgroundIntensity=this.backgroundIntensity),t.object.backgroundRotation=this.backgroundRotation.toArray(),this.environmentIntensity!==1&&(t.object.environmentIntensity=this.environmentIntensity),t.object.environmentRotation=this.environmentRotation.toArray(),t}},ad=new X,od=new X,sd=new X,cd=new X,ld=new X,ud=new X,dd=new X,fd=new X,pd=new X,md=new X,hd=new gu,gd=new gu,_d=new gu,vd=class e{constructor(e=new X,t=new X,n=new 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e.isEmpty()?this:this.isEmpty()?(this.copy(e),this):(this.center.equals(e.center)===!0?this.radius=Math.max(this.radius,e.radius):(Ud.subVectors(e.center,this.center).setLength(e.radius),this.expandByPoint(Hd.copy(e.center).add(Ud)),this.expandByPoint(Hd.copy(e.center).sub(Ud))),this)}equals(e){return e.center.equals(this.center)&&e.radius===this.radius}clone(){return new this.constructor().copy(this)}toJSON(){return{radius:this.radius,center:this.center.toArray()}}fromJSON(e){return this.radius=e.radius,this.center.fromArray(e.center),this}},Gd=0,Kd=new xu,qd=new Ju,Jd=new X,Yd=new yd,Xd=new yd,Zd=new X,Qd=class e extends Cl{constructor(){super(),this.isBufferGeometry=!0,Object.defineProperty(this,"id",{value:Gd++}),this.uuid=Ol(),this.name=``,this.type=`BufferGeometry`,this.index=null,this.indirect=null,this.indirectOffset=0,this.attributes={},this.morphAttributes={},this.morphTargetsRelative=!1,this.groups=[],this.boundingBox=null,this.boundingSphere=null,this.drawRange={start:0,count:1/0},this.userData={},this._transformed=!1}getIndex(){return this.index}setIndex(e){return Array.isArray(e)?this.index=new(fl(e)?zd:Rd)(e,1):this.index=e,this}setIndirect(e,t=0){return this.indirect=e,this.indirectOffset=t,this}getIndirect(){return this.indirect}getAttribute(e){return this.attributes[e]}setAttribute(e,t){return this.attributes[e]=t,this}deleteAttribute(e){return delete this.attributes[e],this}hasAttribute(e){return this.attributes[e]!==void 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Kd.makeScale(e,t,n),this.applyMatrix4(Kd),this}lookAt(e){return qd.lookAt(e),qd.updateMatrix(),this.applyMatrix4(qd.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(Jd).negate(),this.translate(Jd.x,Jd.y,Jd.z),this}setFromPoints(e){let t=this.getAttribute(`position`);if(t===void 0){let t=[];for(let n=0,r=e.length;nt.count&&J(`BufferGeometry: Buffer size too small for points data. 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t=0,r=n.length;t0&&(r[t]=a,i=!0)}i&&(e.data.morphAttributes=r,e.data.morphTargetsRelative=this.morphTargetsRelative);let a=this.groups;a.length>0&&(e.data.groups=JSON.parse(JSON.stringify(a)));let o=this.boundingSphere;return o!==null&&(e.data.boundingSphere=o.toJSON()),e}clone(){return new this.constructor().copy(this)}copy(e){this.index=null,this.attributes={},this.morphAttributes={},this.groups=[],this.boundingBox=null,this.boundingSphere=null;let t={};this.name=e.name;let n=e.index;n!==null&&this.setIndex(n.clone());let r=e.attributes;for(let e in r){let n=r[e];this.setAttribute(e,n.clone(t))}let i=e.morphAttributes;for(let e in i){let n=[],r=i[e];for(let e=0,i=r.length;e0!=e>0&&this.version++,this._alphaTest=e}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(e){if(e!==void 0)for(let t in e){let n=e[t];if(n===void 0){J(`Material: parameter '${t}' has value of undefined.`);continue}let r=this[t];if(r===void 0){J(`Material: 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0&&this.emissiveIntensity!==1&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),this.specularIntensity!==void 0&&(n.specularIntensity=this.specularIntensity),this.specularColor&&this.specularColor.isColor&&(n.specularColor=this.specularColor.getHex()),this.shininess!==void 0&&(n.shininess=this.shininess),this.clearcoat!==void 0&&(n.clearcoat=this.clearcoat),this.clearcoatRoughness!==void 0&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(e).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(e).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(e).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.sheenColorMap&&this.sheenColorMap.isTexture&&(n.sheenColorMap=this.sheenColorMap.toJSON(e).uuid),this.sheenRoughnessMap&&this.sheenRoughnessMap.isTexture&&(n.sheenRoughnessMap=this.sheenRoughnessMap.toJSON(e).uuid),this.dispersion!==void 0&&(n.dispersion=this.dispersion),this.iridescence!==void 0&&(n.iridescence=this.iridescence),this.iridescenceIOR!==void 0&&(n.iridescenceIOR=this.iridescenceIOR),this.iridescenceThicknessRange!==void 0&&(n.iridescenceThicknessRange=this.iridescenceThicknessRange),this.iridescenceMap&&this.iridescenceMap.isTexture&&(n.iridescenceMap=this.iridescenceMap.toJSON(e).uuid),this.iridescenceThicknessMap&&this.iridescenceThicknessMap.isTexture&&(n.iridescenceThicknessMap=this.iridescenceThicknessMap.toJSON(e).uuid),this.anisotropy!==void 0&&(n.anisotropy=this.anisotropy),this.anisotropyRotation!==void 0&&(n.anisotropyRotation=this.anisotropyRotation),this.anisotropyMap&&this.anisotropyMap.isTexture&&(n.anisotropyMap=this.anisotropyMap.toJSON(e).uuid),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(e).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(e).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(e).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(e).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(e).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(e).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(e).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(e).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(e).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(e).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(e).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(e).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(e).uuid),this.specularColorMap&&this.specularColorMap.isTexture&&(n.specularColorMap=this.specularColorMap.toJSON(e).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(e).uuid,this.combine!==void 0&&(n.combine=this.combine)),this.envMapRotation!==void 0&&(n.envMapRotation=this.envMapRotation.toArray()),this.envMapIntensity!==void 0&&(n.envMapIntensity=this.envMapIntensity),this.reflectivity!==void 0&&(n.reflectivity=this.reflectivity),this.refractionRatio!==void 0&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(e).uuid),this.transmission!==void 0&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(e).uuid),this.thickness!==void 0&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(e).uuid),this.attenuationDistance!==void 0&&this.attenuationDistance!==1/0&&(n.attenuationDistance=this.attenuationDistance),this.attenuationColor!==void 0&&(n.attenuationColor=this.attenuationColor.getHex()),this.size!==void 0&&(n.size=this.size),this.shadowSide!==null&&(n.shadowSide=this.shadowSide),this.sizeAttenuation!==void 0&&(n.sizeAttenuation=this.sizeAttenuation),this.blending!==1&&(n.blending=this.blending),this.side!==0&&(n.side=this.side),this.vertexColors===!0&&(n.vertexColors=!0),this.opacity<1&&(n.opacity=this.opacity),this.transparent===!0&&(n.transparent=!0),this.blendSrc!==204&&(n.blendSrc=this.blendSrc),this.blendDst!==205&&(n.blendDst=this.blendDst),this.blendEquation!==100&&(n.blendEquation=this.blendEquation),this.blendSrcAlpha!==null&&(n.blendSrcAlpha=this.blendSrcAlpha),this.blendDstAlpha!==null&&(n.blendDstAlpha=this.blendDstAlpha),this.blendEquationAlpha!==null&&(n.blendEquationAlpha=this.blendEquationAlpha),this.blendColor&&this.blendColor.isColor&&(n.blendColor=this.blendColor.getHex()),this.blendAlpha!==0&&(n.blendAlpha=this.blendAlpha),this.depthFunc!==3&&(n.depthFunc=this.depthFunc),this.depthTest===!1&&(n.depthTest=this.depthTest),this.depthWrite===!1&&(n.depthWrite=this.depthWrite),this.colorWrite===!1&&(n.colorWrite=this.colorWrite),this.stencilWriteMask!==255&&(n.stencilWriteMask=this.stencilWriteMask),this.stencilFunc!==519&&(n.stencilFunc=this.stencilFunc),this.stencilRef!==0&&(n.stencilRef=this.stencilRef),this.stencilFuncMask!==255&&(n.stencilFuncMask=this.stencilFuncMask),this.stencilFail!==7680&&(n.stencilFail=this.stencilFail),this.stencilZFail!==7680&&(n.stencilZFail=this.stencilZFail),this.stencilZPass!==7680&&(n.stencilZPass=this.stencilZPass),this.stencilWrite===!0&&(n.stencilWrite=this.stencilWrite),this.rotation!==void 0&&this.rotation!==0&&(n.rotation=this.rotation),this.polygonOffset===!0&&(n.polygonOffset=!0),this.polygonOffsetFactor!==0&&(n.polygonOffsetFactor=this.polygonOffsetFactor),this.polygonOffsetUnits!==0&&(n.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth!==void 0&&this.linewidth!==1&&(n.linewidth=this.linewidth),this.dashSize!==void 0&&(n.dashSize=this.dashSize),this.gapSize!==void 0&&(n.gapSize=this.gapSize),this.scale!==void 0&&(n.scale=this.scale),this.dithering===!0&&(n.dithering=!0),this.alphaTest>0&&(n.alphaTest=this.alphaTest),this.alphaHash===!0&&(n.alphaHash=!0),this.alphaToCoverage===!0&&(n.alphaToCoverage=!0),this.premultipliedAlpha===!0&&(n.premultipliedAlpha=!0),this.forceSinglePass===!0&&(n.forceSinglePass=!0),this.allowOverride===!1&&(n.allowOverride=!1),this.wireframe===!0&&(n.wireframe=!0),this.wireframeLinewidth>1&&(n.wireframeLinewidth=this.wireframeLinewidth),this.wireframeLinecap!==`round`&&(n.wireframeLinecap=this.wireframeLinecap),this.wireframeLinejoin!==`round`&&(n.wireframeLinejoin=this.wireframeLinejoin),this.flatShading===!0&&(n.flatShading=!0),this.visible===!1&&(n.visible=!1),this.toneMapped===!1&&(n.toneMapped=!1),this.fog===!1&&(n.fog=!1),Object.keys(this.userData).length>0&&(n.userData=this.userData);function r(e){let t=[];for(let n in e){let r=e[n];delete r.metadata,t.push(r)}return t}if(t){let t=r(e.textures),i=r(e.images);t.length>0&&(n.textures=t),i.length>0&&(n.images=i)}return n}fromJSON(e,t){if(e.uuid!==void 0&&(this.uuid=e.uuid),e.name!==void 0&&(this.name=e.name),e.color!==void 0&&this.color!==void 0&&this.color.setHex(e.color),e.roughness!==void 0&&(this.roughness=e.roughness),e.metalness!==void 0&&(this.metalness=e.metalness),e.sheen!==void 0&&(this.sheen=e.sheen),e.sheenColor!==void 0&&(this.sheenColor=new Z().setHex(e.sheenColor)),e.sheenRoughness!==void 0&&(this.sheenRoughness=e.sheenRoughness),e.emissive!==void 0&&this.emissive!==void 0&&this.emissive.setHex(e.emissive),e.specular!==void 0&&this.specular!==void 0&&this.specular.setHex(e.specular),e.specularIntensity!==void 0&&(this.specularIntensity=e.specularIntensity),e.specularColor!==void 0&&this.specularColor!==void 0&&this.specularColor.setHex(e.specularColor),e.shininess!==void 0&&(this.shininess=e.shininess),e.clearcoat!==void 0&&(this.clearcoat=e.clearcoat),e.clearcoatRoughness!==void 0&&(this.clearcoatRoughness=e.clearcoatRoughness),e.dispersion!==void 0&&(this.dispersion=e.dispersion),e.iridescence!==void 0&&(this.iridescence=e.iridescence),e.iridescenceIOR!==void 0&&(this.iridescenceIOR=e.iridescenceIOR),e.iridescenceThicknessRange!==void 0&&(this.iridescenceThicknessRange=e.iridescenceThicknessRange),e.transmission!==void 0&&(this.transmission=e.transmission),e.thickness!==void 0&&(this.thickness=e.thickness),e.attenuationDistance!==void 0&&(this.attenuationDistance=e.attenuationDistance),e.attenuationColor!==void 0&&this.attenuationColor!==void 0&&this.attenuationColor.setHex(e.attenuationColor),e.anisotropy!==void 0&&(this.anisotropy=e.anisotropy),e.anisotropyRotation!==void 0&&(this.anisotropyRotation=e.anisotropyRotation),e.fog!==void 0&&(this.fog=e.fog),e.flatShading!==void 0&&(this.flatShading=e.flatShading),e.blending!==void 0&&(this.blending=e.blending),e.combine!==void 0&&(this.combine=e.combine),e.side!==void 0&&(this.side=e.side),e.shadowSide!==void 0&&(this.shadowSide=e.shadowSide),e.opacity!==void 0&&(this.opacity=e.opacity),e.transparent!==void 0&&(this.transparent=e.transparent),e.alphaTest!==void 0&&(this.alphaTest=e.alphaTest),e.alphaHash!==void 0&&(this.alphaHash=e.alphaHash),e.depthFunc!==void 0&&(this.depthFunc=e.depthFunc),e.depthTest!==void 0&&(this.depthTest=e.depthTest),e.depthWrite!==void 0&&(this.depthWrite=e.depthWrite),e.colorWrite!==void 0&&(this.colorWrite=e.colorWrite),e.blendSrc!==void 0&&(this.blendSrc=e.blendSrc),e.blendDst!==void 0&&(this.blendDst=e.blendDst),e.blendEquation!==void 0&&(this.blendEquation=e.blendEquation),e.blendSrcAlpha!==void 0&&(this.blendSrcAlpha=e.blendSrcAlpha),e.blendDstAlpha!==void 0&&(this.blendDstAlpha=e.blendDstAlpha),e.blendEquationAlpha!==void 0&&(this.blendEquationAlpha=e.blendEquationAlpha),e.blendColor!==void 0&&this.blendColor!==void 0&&this.blendColor.setHex(e.blendColor),e.blendAlpha!==void 0&&(this.blendAlpha=e.blendAlpha),e.stencilWriteMask!==void 0&&(this.stencilWriteMask=e.stencilWriteMask),e.stencilFunc!==void 0&&(this.stencilFunc=e.stencilFunc),e.stencilRef!==void 0&&(this.stencilRef=e.stencilRef),e.stencilFuncMask!==void 0&&(this.stencilFuncMask=e.stencilFuncMask),e.stencilFail!==void 0&&(this.stencilFail=e.stencilFail),e.stencilZFail!==void 0&&(this.stencilZFail=e.stencilZFail),e.stencilZPass!==void 0&&(this.stencilZPass=e.stencilZPass),e.stencilWrite!==void 0&&(this.stencilWrite=e.stencilWrite),e.wireframe!==void 0&&(this.wireframe=e.wireframe),e.wireframeLinewidth!==void 0&&(this.wireframeLinewidth=e.wireframeLinewidth),e.wireframeLinecap!==void 0&&(this.wireframeLinecap=e.wireframeLinecap),e.wireframeLinejoin!==void 0&&(this.wireframeLinejoin=e.wireframeLinejoin),e.rotation!==void 0&&(this.rotation=e.rotation),e.linewidth!==void 0&&(this.linewidth=e.linewidth),e.dashSize!==void 0&&(this.dashSize=e.dashSize),e.gapSize!==void 0&&(this.gapSize=e.gapSize),e.scale!==void 0&&(this.scale=e.scale),e.polygonOffset!==void 0&&(this.polygonOffset=e.polygonOffset),e.polygonOffsetFactor!==void 0&&(this.polygonOffsetFactor=e.polygonOffsetFactor),e.polygonOffsetUnits!==void 0&&(this.polygonOffsetUnits=e.polygonOffsetUnits),e.dithering!==void 0&&(this.dithering=e.dithering),e.alphaToCoverage!==void 0&&(this.alphaToCoverage=e.alphaToCoverage),e.premultipliedAlpha!==void 0&&(this.premultipliedAlpha=e.premultipliedAlpha),e.forceSinglePass!==void 0&&(this.forceSinglePass=e.forceSinglePass),e.allowOverride!==void 0&&(this.allowOverride=e.allowOverride),e.visible!==void 0&&(this.visible=e.visible),e.toneMapped!==void 0&&(this.toneMapped=e.toneMapped),e.userData!==void 0&&(this.userData=e.userData),e.vertexColors!==void 0&&(typeof e.vertexColors==`number`?this.vertexColors=e.vertexColors>0:this.vertexColors=e.vertexColors),e.size!==void 0&&(this.size=e.size),e.sizeAttenuation!==void 0&&(this.sizeAttenuation=e.sizeAttenuation),e.map!==void 0&&(this.map=t[e.map]||null),e.matcap!==void 0&&(this.matcap=t[e.matcap]||null),e.alphaMap!==void 0&&(this.alphaMap=t[e.alphaMap]||null),e.bumpMap!==void 0&&(this.bumpMap=t[e.bumpMap]||null),e.bumpScale!==void 0&&(this.bumpScale=e.bumpScale),e.normalMap!==void 0&&(this.normalMap=t[e.normalMap]||null),e.normalMapType!==void 0&&(this.normalMapType=e.normalMapType),e.normalScale!==void 0){let t=e.normalScale;Array.isArray(t)===!1&&(t=[t,t]),this.normalScale=new Y().fromArray(t)}return e.displacementMap!==void 0&&(this.displacementMap=t[e.displacementMap]||null),e.displacementScale!==void 0&&(this.displacementScale=e.displacementScale),e.displacementBias!==void 0&&(this.displacementBias=e.displacementBias),e.roughnessMap!==void 0&&(this.roughnessMap=t[e.roughnessMap]||null),e.metalnessMap!==void 0&&(this.metalnessMap=t[e.metalnessMap]||null),e.emissiveMap!==void 0&&(this.emissiveMap=t[e.emissiveMap]||null),e.emissiveIntensity!==void 0&&(this.emissiveIntensity=e.emissiveIntensity),e.specularMap!==void 0&&(this.specularMap=t[e.specularMap]||null),e.specularIntensityMap!==void 0&&(this.specularIntensityMap=t[e.specularIntensityMap]||null),e.specularColorMap!==void 0&&(this.specularColorMap=t[e.specularColorMap]||null),e.envMap!==void 0&&(this.envMap=t[e.envMap]||null),e.envMapRotation!==void 0&&this.envMapRotation.fromArray(e.envMapRotation),e.envMapIntensity!==void 0&&(this.envMapIntensity=e.envMapIntensity),e.reflectivity!==void 0&&(this.reflectivity=e.reflectivity),e.refractionRatio!==void 0&&(this.refractionRatio=e.refractionRatio),e.lightMap!==void 0&&(this.lightMap=t[e.lightMap]||null),e.lightMapIntensity!==void 0&&(this.lightMapIntensity=e.lightMapIntensity),e.aoMap!==void 0&&(this.aoMap=t[e.aoMap]||null),e.aoMapIntensity!==void 0&&(this.aoMapIntensity=e.aoMapIntensity),e.gradientMap!==void 0&&(this.gradientMap=t[e.gradientMap]||null),e.clearcoatMap!==void 0&&(this.clearcoatMap=t[e.clearcoatMap]||null),e.clearcoatRoughnessMap!==void 0&&(this.clearcoatRoughnessMap=t[e.clearcoatRoughnessMap]||null),e.clearcoatNormalMap!==void 0&&(this.clearcoatNormalMap=t[e.clearcoatNormalMap]||null),e.clearcoatNormalScale!==void 0&&(this.clearcoatNormalScale=new Y().fromArray(e.clearcoatNormalScale)),e.iridescenceMap!==void 0&&(this.iridescenceMap=t[e.iridescenceMap]||null),e.iridescenceThicknessMap!==void 0&&(this.iridescenceThicknessMap=t[e.iridescenceThicknessMap]||null),e.transmissionMap!==void 0&&(this.transmissionMap=t[e.transmissionMap]||null),e.thicknessMap!==void 0&&(this.thicknessMap=t[e.thicknessMap]||null),e.anisotropyMap!==void 0&&(this.anisotropyMap=t[e.anisotropyMap]||null),e.sheenColorMap!==void 0&&(this.sheenColorMap=t[e.sheenColorMap]||null),e.sheenRoughnessMap!==void 0&&(this.sheenRoughnessMap=t[e.sheenRoughnessMap]||null),this}clone(){return new this.constructor().copy(this)}copy(e){this.name=e.name,this.blending=e.blending,this.side=e.side,this.vertexColors=e.vertexColors,this.opacity=e.opacity,this.transparent=e.transparent,this.blendSrc=e.blendSrc,this.blendDst=e.blendDst,this.blendEquation=e.blendEquation,this.blendSrcAlpha=e.blendSrcAlpha,this.blendDstAlpha=e.blendDstAlpha,this.blendEquationAlpha=e.blendEquationAlpha,this.blendColor.copy(e.blendColor),this.blendAlpha=e.blendAlpha,this.depthFunc=e.depthFunc,this.depthTest=e.depthTest,this.depthWrite=e.depthWrite,this.stencilWriteMask=e.stencilWriteMask,this.stencilFunc=e.stencilFunc,this.stencilRef=e.stencilRef,this.stencilFuncMask=e.stencilFuncMask,this.stencilFail=e.stencilFail,this.stencilZFail=e.stencilZFail,this.stencilZPass=e.stencilZPass,this.stencilWrite=e.stencilWrite;let t=e.clippingPlanes,n=null;if(t!==null){let e=t.length;n=Array(e);for(let r=0;r!==e;++r)n[r]=t[r].clone()}return this.clippingPlanes=n,this.clipIntersection=e.clipIntersection,this.clipShadows=e.clipShadows,this.shadowSide=e.shadowSide,this.colorWrite=e.colorWrite,this.precision=e.precision,this.polygonOffset=e.polygonOffset,this.polygonOffsetFactor=e.polygonOffsetFactor,this.polygonOffsetUnits=e.polygonOffsetUnits,this.dithering=e.dithering,this.alphaTest=e.alphaTest,this.alphaHash=e.alphaHash,this.alphaToCoverage=e.alphaToCoverage,this.premultipliedAlpha=e.premultipliedAlpha,this.forceSinglePass=e.forceSinglePass,this.allowOverride=e.allowOverride,this.visible=e.visible,this.toneMapped=e.toneMapped,this.userData=JSON.parse(JSON.stringify(e.userData)),this}dispose(){this.dispatchEvent({type:`dispose`})}set needsUpdate(e){e===!0&&this.version++}},af=new X,of=new X,sf=new X,cf=new X,lf=new X,uf=new X,df=new X,ff=class{constructor(e=new X,t=new X(0,0,-1)){this.origin=e,this.direction=t}set(e,t){return this.origin.copy(e),this.direction.copy(t),this}copy(e){return this.origin.copy(e.origin),this.direction.copy(e.direction),this}at(e,t){return t.copy(this.origin).addScaledVector(this.direction,e)}lookAt(e){return this.direction.copy(e).sub(this.origin).normalize(),this}recast(e){return this.origin.copy(this.at(e,af)),this}closestPointToPoint(e,t){t.subVectors(e,this.origin);let n=t.dot(this.direction);return n<0?t.copy(this.origin):t.copy(this.origin).addScaledVector(this.direction,n)}distanceToPoint(e){return Math.sqrt(this.distanceSqToPoint(e))}distanceSqToPoint(e){let t=af.subVectors(e,this.origin).dot(this.direction);return t<0?this.origin.distanceToSquared(e):(af.copy(this.origin).addScaledVector(this.direction,t),af.distanceToSquared(e))}distanceSqToSegment(e,t,n,r){of.copy(e).add(t).multiplyScalar(.5),sf.copy(t).sub(e).normalize(),cf.copy(this.origin).sub(of);let i=e.distanceTo(t)*.5,a=-this.direction.dot(sf),o=cf.dot(this.direction),s=-cf.dot(sf),c=cf.lengthSq(),l=Math.abs(1-a*a),u,d,f,p;if(l>0)if(u=a*s-o,d=a*o-s,p=i*l,u>=0)if(d>=-p)if(d<=p){let e=1/l;u*=e,d*=e,f=u*(u+a*d+2*o)+d*(a*u+d+2*s)+c}else d=i,u=Math.max(0,-(a*d+o)),f=-u*u+d*(d+2*s)+c;else d=-i,u=Math.max(0,-(a*d+o)),f=-u*u+d*(d+2*s)+c;else d<=-p?(u=Math.max(0,-(-a*i+o)),d=u>0?-i:Math.min(Math.max(-i,-s),i),f=-u*u+d*(d+2*s)+c):d<=p?(u=0,d=Math.min(Math.max(-i,-s),i),f=d*(d+2*s)+c):(u=Math.max(0,-(a*i+o)),d=u>0?i:Math.min(Math.max(-i,-s),i),f=-u*u+d*(d+2*s)+c);else d=a>0?-i:i,u=Math.max(0,-(a*d+o)),f=-u*u+d*(d+2*s)+c;return n&&n.copy(this.origin).addScaledVector(this.direction,u),r&&r.copy(of).addScaledVector(sf,d),f}intersectSphere(e,t){af.subVectors(e.center,this.origin);let n=af.dot(this.direction),r=af.dot(af)-n*n,i=e.radius*e.radius;if(r>i)return null;let a=Math.sqrt(i-r),o=n-a,s=n+a;return s<0?null:o<0?this.at(s,t):this.at(o,t)}intersectsSphere(e){return e.radius<0?!1:this.distanceSqToPoint(e.center)<=e.radius*e.radius}distanceToPlane(e){let t=e.normal.dot(this.direction);if(t===0)return e.distanceToPoint(this.origin)===0?0:null;let n=-(this.origin.dot(e.normal)+e.constant)/t;return n>=0?n:null}intersectPlane(e,t){let n=this.distanceToPlane(e);return n===null?null:this.at(n,t)}intersectsPlane(e){let t=e.distanceToPoint(this.origin);return t===0||e.normal.dot(this.direction)*t<0}intersectBox(e,t){let n,r,i,a,o,s,c=1/this.direction.x,l=1/this.direction.y,u=1/this.direction.z,d=this.origin;return c>=0?(n=(e.min.x-d.x)*c,r=(e.max.x-d.x)*c):(n=(e.max.x-d.x)*c,r=(e.min.x-d.x)*c),l>=0?(i=(e.min.y-d.y)*l,a=(e.max.y-d.y)*l):(i=(e.max.y-d.y)*l,a=(e.min.y-d.y)*l),n>a||i>r||((i>n||isNaN(n))&&(n=i),(a=0?(o=(e.min.z-d.z)*u,s=(e.max.z-d.z)*u):(o=(e.max.z-d.z)*u,s=(e.min.z-d.z)*u),n>s||o>r)||((o>n||n!==n)&&(n=o),(s=0?n:r,t)}intersectsBox(e){return this.intersectBox(e,af)!==null}intersectTriangle(e,t,n,r,i){lf.subVectors(t,e),uf.subVectors(n,e),df.crossVectors(lf,uf);let a=this.direction.dot(df),o;if(a>0){if(r)return null;o=1}else if(a<0)o=-1,a=-a;else return null;cf.subVectors(this.origin,e);let s=o*this.direction.dot(uf.crossVectors(cf,uf));if(s<0)return null;let c=o*this.direction.dot(lf.cross(cf));if(c<0||s+c>a)return null;let l=-o*cf.dot(df);return l<0?null:this.at(l/a,i)}applyMatrix4(e){return this.origin.applyMatrix4(e),this.direction.transformDirection(e),this}equals(e){return e.origin.equals(this.origin)&&e.direction.equals(this.direction)}clone(){return new this.constructor().copy(this)}},pf=class extends rf{constructor(e){super(),this.isMeshBasicMaterial=!0,this.type=`MeshBasicMaterial`,this.color=new Z(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ju,this.combine=0,this.reflectivity=1,this.refractionRatio=.98,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=`round`,this.wireframeLinejoin=`round`,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.combine=e.combine,this.reflectivity=e.reflectivity,this.refractionRatio=e.refractionRatio,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.fog=e.fog,this}},mf=new xu,hf=new ff,gf=new Wd,_f=new X,vf=new X,yf=new X,bf=new X,xf=new X,Sf=new X,Cf=new X,wf=new X,Q=class extends Ju{constructor(e=new Qd,t=new pf){super(),this.isMesh=!0,this.type=`Mesh`,this.geometry=e,this.material=t,this.morphTargetDictionary=void 0,this.morphTargetInfluences=void 0,this.count=1,this.updateMorphTargets()}copy(e,t){return super.copy(e,t),e.morphTargetInfluences!==void 0&&(this.morphTargetInfluences=e.morphTargetInfluences.slice()),e.morphTargetDictionary!==void 0&&(this.morphTargetDictionary=Object.assign({},e.morphTargetDictionary)),this.material=Array.isArray(e.material)?e.material.slice():e.material,this.geometry=e.geometry,this}updateMorphTargets(){let e=this.geometry.morphAttributes,t=Object.keys(e);if(t.length>0){let n=e[t[0]];if(n!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,t=n.length;e(e.far-e.near)**2))&&(mf.copy(i).invert(),hf.copy(e.ray).applyMatrix4(mf),!(n.boundingBox!==null&&hf.intersectsBox(n.boundingBox)===!1)&&this._computeIntersections(e,t,hf)))}_computeIntersections(e,t,n){let r,i=this.geometry,a=this.material,o=i.index,s=i.attributes.position,c=i.attributes.uv,l=i.attributes.uv1,u=i.attributes.normal,d=i.groups,f=i.drawRange;if(o!==null)if(Array.isArray(a))for(let i=0,s=d.length;in.far?null:{distance:l,point:wf.clone(),object:e}}function Ef(e,t,n,r,i,a,o,s,c,l){e.getVertexPosition(s,vf),e.getVertexPosition(c,yf),e.getVertexPosition(l,bf);let u=Tf(e,t,n,r,vf,yf,bf,Cf);if(u){let e=new X;vd.getBarycoord(Cf,vf,yf,bf,e),i&&(u.uv=vd.getInterpolatedAttribute(i,s,c,l,e,new Y)),a&&(u.uv1=vd.getInterpolatedAttribute(a,s,c,l,e,new Y)),o&&(u.normal=vd.getInterpolatedAttribute(o,s,c,l,e,new X),u.normal.dot(r.direction)>0&&u.normal.multiplyScalar(-1));let t={a:s,b:c,c:l,normal:new X,materialIndex:0};vd.getNormal(vf,yf,bf,t.normal),u.face=t,u.barycoord=e}return u}var Df=new gu,Of=new gu,kf=new gu,Af=new gu,jf=new xu,Mf=new X,Nf=new Wd,Pf=new xu,Ff=new ff,If=class extends Q{constructor(e,t){super(e,t),this.isSkinnedMesh=!0,this.type=`SkinnedMesh`,this.bindMode=As,this.bindMatrix=new xu,this.bindMatrixInverse=new xu,this.boundingBox=null,this.boundingSphere=null}computeBoundingBox(){let e=this.geometry;this.boundingBox===null&&(this.boundingBox=new yd),this.boundingBox.makeEmpty();let t=e.getAttribute(`position`);for(let e=0;e1)?null:t.copy(e.start).addScaledVector(r,a)}intersectsLine(e){let t=this.distanceToPoint(e.start),n=this.distanceToPoint(e.end);return t<0&&n>0||n<0&&t>0}intersectsBox(e){return e.intersectsPlane(this)}intersectsSphere(e){return e.intersectsPlane(this)}coplanarPoint(e){return e.copy(this.normal).multiplyScalar(-this.constant)}applyMatrix4(e,t){let n=t||$f.getNormalMatrix(e),r=this.coplanarPoint(Zf).applyMatrix4(e),i=this.normal.applyMatrix3(n).normalize();return this.constant=-r.dot(i),this}translate(e){return this.constant-=e.dot(this.normal),this}equals(e){return e.normal.equals(this.normal)&&e.constant===this.constant}clone(){return new this.constructor().copy(this)}},tp=new Wd,np=new Y(.5,.5),rp=new X,ip=class{constructor(e=new ep,t=new ep,n=new ep,r=new ep,i=new ep,a=new ep){this.planes=[e,t,n,r,i,a]}set(e,t,n,r,i,a){let o=this.planes;return o[0].copy(e),o[1].copy(t),o[2].copy(n),o[3].copy(r),o[4].copy(i),o[5].copy(a),this}copy(e){let t=this.planes;for(let n=0;n<6;n++)t[n].copy(e.planes[n]);return this}setFromProjectionMatrix(e,t=dl,n=!1){let r=this.planes,i=e.elements,a=i[0],o=i[1],s=i[2],c=i[3],l=i[4],u=i[5],d=i[6],f=i[7],p=i[8],m=i[9],h=i[10],g=i[11],_=i[12],v=i[13],y=i[14],b=i[15];if(r[0].setComponents(c-a,f-l,g-p,b-_).normalize(),r[1].setComponents(c+a,f+l,g+p,b+_).normalize(),r[2].setComponents(c+o,f+u,g+m,b+v).normalize(),r[3].setComponents(c-o,f-u,g-m,b-v).normalize(),n)r[4].setComponents(s,d,h,y).normalize(),r[5].setComponents(c-s,f-d,g-h,b-y).normalize();else if(r[4].setComponents(c-s,f-d,g-h,b-y).normalize(),t===2e3)r[5].setComponents(c+s,f+d,g+h,b+y).normalize();else if(t===2001)r[5].setComponents(s,d,h,y).normalize();else throw Error(`THREE.Frustum.setFromProjectionMatrix(): Invalid coordinate system: `+t);return this}intersectsObject(e){if(e.boundingSphere!==void 0)e.boundingSphere===null&&e.computeBoundingSphere(),tp.copy(e.boundingSphere).applyMatrix4(e.matrixWorld);else{let t=e.geometry;t.boundingSphere===null&&t.computeBoundingSphere(),tp.copy(t.boundingSphere).applyMatrix4(e.matrixWorld)}return this.intersectsSphere(tp)}intersectsSprite(e){return tp.center.set(0,0,0),tp.radius=.7071067811865476+np.distanceTo(e.center),tp.applyMatrix4(e.matrixWorld),this.intersectsSphere(tp)}intersectsSphere(e){let t=this.planes,n=e.center,r=-e.radius;for(let e=0;e<6;e++)if(t[e].distanceToPoint(n)0?e.max.x:e.min.x,rp.y=r.normal.y>0?e.max.y:e.min.y,rp.z=r.normal.z>0?e.max.z:e.min.z,r.distanceToPoint(rp)<0)return!1}return!0}containsPoint(e){let t=this.planes;for(let n=0;n<6;n++)if(t[n].distanceToPoint(e)<0)return!1;return!0}clone(){return new this.constructor().copy(this)}},ap=class extends rf{constructor(e){super(),this.isLineBasicMaterial=!0,this.type=`LineBasicMaterial`,this.color=new Z(16777215),this.map=null,this.linewidth=1,this.linecap=`round`,this.linejoin=`round`,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.linewidth=e.linewidth,this.linecap=e.linecap,this.linejoin=e.linejoin,this.fog=e.fog,this}},op=new X,sp=new X,cp=new xu,lp=new ff,up=new Wd,dp=new X,fp=new X,pp=class extends Ju{constructor(e=new Qd,t=new ap){super(),this.isLine=!0,this.type=`Line`,this.geometry=e,this.material=t,this.morphTargetDictionary=void 0,this.morphTargetInfluences=void 0,this.updateMorphTargets()}copy(e,t){return super.copy(e,t),this.material=Array.isArray(e.material)?e.material.slice():e.material,this.geometry=e.geometry,this}computeLineDistances(){let e=this.geometry;if(e.index===null){let t=e.attributes.position,n=[0];for(let e=1,r=t.count;e0){let n=e[t[0]];if(n!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,t=n.length;er)return;dp.applyMatrix4(e.matrixWorld);let c=t.ray.origin.distanceTo(dp);if(!(ct.far))return{distance:c,point:fp.clone().applyMatrix4(e.matrixWorld),index:o,face:null,faceIndex:null,barycoord:null,object:e}}var hp=new X,gp=new X,_p=class extends pp{constructor(e,t){super(e,t),this.isLineSegments=!0,this.type=`LineSegments`}computeLineDistances(){let e=this.geometry;if(e.index===null){let t=e.attributes.position,n=[];for(let e=0,r=t.count;e0){let n=e[t[0]];if(n!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let e=0,t=n.length;ei.far)return;a.push({distance:c,distanceToRay:Math.sqrt(s),point:n,index:t,face:null,faceIndex:null,barycoord:null,object:o})}}var Ep=class extends 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`},{name:`dismember_right`,sampleRate:12e3,frames:6960,wav:`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isCUID2(){return!!this._def.checks.find(e=>e.kind===`cuid2`)}get isULID(){return!!this._def.checks.find(e=>e.kind===`ulid`)}get isIP(){return!!this._def.checks.find(e=>e.kind===`ip`)}get isBase64(){return!!this._def.checks.find(e=>e.kind===`base64`)}get minLength(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e}get maxLength(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuenew At({checks:[],typeName:xn.ZodString,coerce:e?.coerce??!1,...ut(e)});function jt(e,t){let n=(e.toString().split(`.`)[1]||``).length,r=(t.toString().split(`.`)[1]||``).length,i=n>r?n:r;return parseInt(e.toFixed(i).replace(`.`,``))%parseInt(t.toFixed(i).replace(`.`,``))/10**i}var Mt=class e extends dt{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte,this.step=this.multipleOf}_parse(e){if(this._def.coerce&&(e.data=Number(e.data)),this._getType(e)!==B.number){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.number,received:t.parsedType}),Ze}let t,n=new Xe;for(let r of this._def.checks)r.kind===`int`?ze.isInteger(e.data)||(t=this._getOrReturnCtx(e,t),H(t,{code:V.invalid_type,expected:`integer`,received:`float`,message:r.message}),n.dirty()):r.kind===`min`?(r.inclusive?e.datar.value:e.data>=r.value)&&(t=this._getOrReturnCtx(e,t),H(t,{code:V.too_big,maximum:r.value,type:`number`,inclusive:r.inclusive,exact:!1,message:r.message}),n.dirty()):r.kind===`multipleOf`?jt(e.data,r.value)!==0&&(t=this._getOrReturnCtx(e,t),H(t,{code:V.not_multiple_of,multipleOf:r.value,message:r.message}),n.dirty()):r.kind===`finite`?Number.isFinite(e.data)||(t=this._getOrReturnCtx(e,t),H(t,{code:V.not_finite,message:r.message}),n.dirty()):ze.assertNever(r);return{status:n.value,value:e.data}}gte(e,t){return this.setLimit(`min`,e,!0,U.toString(t))}gt(e,t){return this.setLimit(`min`,e,!1,U.toString(t))}lte(e,t){return this.setLimit(`max`,e,!0,U.toString(t))}lt(e,t){return this.setLimit(`max`,e,!1,U.toString(t))}setLimit(t,n,r,i){return new e({...this._def,checks:[...this._def.checks,{kind:t,value:n,inclusive:r,message:U.toString(i)}]})}_addCheck(t){return new e({...this._def,checks:[...this._def.checks,t]})}int(e){return this._addCheck({kind:`int`,message:U.toString(e)})}positive(e){return this._addCheck({kind:`min`,value:0,inclusive:!1,message:U.toString(e)})}negative(e){return this._addCheck({kind:`max`,value:0,inclusive:!1,message:U.toString(e)})}nonpositive(e){return this._addCheck({kind:`max`,value:0,inclusive:!0,message:U.toString(e)})}nonnegative(e){return this._addCheck({kind:`min`,value:0,inclusive:!0,message:U.toString(e)})}multipleOf(e,t){return this._addCheck({kind:`multipleOf`,value:e,message:U.toString(t)})}finite(e){return this._addCheck({kind:`finite`,message:U.toString(e)})}safe(e){return this._addCheck({kind:`min`,inclusive:!0,value:-(2**53-1),message:U.toString(e)})._addCheck({kind:`max`,inclusive:!0,value:2**53-1,message:U.toString(e)})}get minValue(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuee.kind===`int`||e.kind===`multipleOf`&&ze.isInteger(e.value))}get isFinite(){let e=null,t=null;for(let n of this._def.checks)if(n.kind===`finite`||n.kind===`int`||n.kind===`multipleOf`)return!0;else n.kind===`min`?(t===null||n.value>t)&&(t=n.value):n.kind===`max`&&(e===null||n.valuenew Mt({checks:[],typeName:xn.ZodNumber,coerce:e?.coerce||!1,...ut(e)});var Nt=class e extends dt{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte}_parse(e){if(this._def.coerce&&(e.data=BigInt(e.data)),this._getType(e)!==B.bigint){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.bigint,received:t.parsedType}),Ze}let t,n=new Xe;for(let r of this._def.checks)r.kind===`min`?(r.inclusive?e.datar.value:e.data>=r.value)&&(t=this._getOrReturnCtx(e,t),H(t,{code:V.too_big,type:`bigint`,maximum:r.value,inclusive:r.inclusive,message:r.message}),n.dirty()):r.kind===`multipleOf`?e.data%r.value!==BigInt(0)&&(t=this._getOrReturnCtx(e,t),H(t,{code:V.not_multiple_of,multipleOf:r.value,message:r.message}),n.dirty()):ze.assertNever(r);return{status:n.value,value:e.data}}gte(e,t){return this.setLimit(`min`,e,!0,U.toString(t))}gt(e,t){return this.setLimit(`min`,e,!1,U.toString(t))}lte(e,t){return this.setLimit(`max`,e,!0,U.toString(t))}lt(e,t){return this.setLimit(`max`,e,!1,U.toString(t))}setLimit(t,n,r,i){return new e({...this._def,checks:[...this._def.checks,{kind:t,value:n,inclusive:r,message:U.toString(i)}]})}_addCheck(t){return new e({...this._def,checks:[...this._def.checks,t]})}positive(e){return this._addCheck({kind:`min`,value:BigInt(0),inclusive:!1,message:U.toString(e)})}negative(e){return this._addCheck({kind:`max`,value:BigInt(0),inclusive:!1,message:U.toString(e)})}nonpositive(e){return this._addCheck({kind:`max`,value:BigInt(0),inclusive:!0,message:U.toString(e)})}nonnegative(e){return this._addCheck({kind:`min`,value:BigInt(0),inclusive:!0,message:U.toString(e)})}multipleOf(e,t){return this._addCheck({kind:`multipleOf`,value:e,message:U.toString(t)})}get minValue(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuenew Nt({checks:[],typeName:xn.ZodBigInt,coerce:e?.coerce??!1,...ut(e)});var Pt=class extends dt{_parse(e){if(this._def.coerce&&(e.data=!!e.data),this._getType(e)!==B.boolean){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.boolean,received:t.parsedType}),Ze}return $e(e.data)}};Pt.create=e=>new Pt({typeName:xn.ZodBoolean,coerce:e?.coerce||!1,...ut(e)});var Ft=class e extends dt{_parse(e){if(this._def.coerce&&(e.data=new Date(e.data)),this._getType(e)!==B.date){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.date,received:t.parsedType}),Ze}if(isNaN(e.data.getTime()))return H(this._getOrReturnCtx(e),{code:V.invalid_date}),Ze;let t=new Xe,n;for(let r of this._def.checks)r.kind===`min`?e.data.getTime()r.value&&(n=this._getOrReturnCtx(e,n),H(n,{code:V.too_big,message:r.message,inclusive:!0,exact:!1,maximum:r.value,type:`date`}),t.dirty()):ze.assertNever(r);return{status:t.value,value:new Date(e.data.getTime())}}_addCheck(t){return new e({...this._def,checks:[...this._def.checks,t]})}min(e,t){return this._addCheck({kind:`min`,value:e.getTime(),message:U.toString(t)})}max(e,t){return this._addCheck({kind:`max`,value:e.getTime(),message:U.toString(t)})}get minDate(){let e=null;for(let t of this._def.checks)t.kind===`min`&&(e===null||t.value>e)&&(e=t.value);return e==null?null:new Date(e)}get maxDate(){let e=null;for(let t of this._def.checks)t.kind===`max`&&(e===null||t.valuenew Ft({checks:[],coerce:e?.coerce||!1,typeName:xn.ZodDate,...ut(e)});var It=class extends dt{_parse(e){if(this._getType(e)!==B.symbol){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.symbol,received:t.parsedType}),Ze}return $e(e.data)}};It.create=e=>new It({typeName:xn.ZodSymbol,...ut(e)});var Lt=class extends dt{_parse(e){if(this._getType(e)!==B.undefined){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.undefined,received:t.parsedType}),Ze}return $e(e.data)}};Lt.create=e=>new Lt({typeName:xn.ZodUndefined,...ut(e)});var Rt=class extends dt{_parse(e){if(this._getType(e)!==B.null){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.null,received:t.parsedType}),Ze}return $e(e.data)}};Rt.create=e=>new Rt({typeName:xn.ZodNull,...ut(e)});var zt=class extends dt{constructor(){super(...arguments),this._any=!0}_parse(e){return $e(e.data)}};zt.create=e=>new zt({typeName:xn.ZodAny,...ut(e)});var Bt=class extends dt{constructor(){super(...arguments),this._unknown=!0}_parse(e){return $e(e.data)}};Bt.create=e=>new Bt({typeName:xn.ZodUnknown,...ut(e)});var Vt=class extends dt{_parse(e){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.never,received:t.parsedType}),Ze}};Vt.create=e=>new Vt({typeName:xn.ZodNever,...ut(e)});var Ht=class extends dt{_parse(e){if(this._getType(e)!==B.undefined){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.void,received:t.parsedType}),Ze}return $e(e.data)}};Ht.create=e=>new Ht({typeName:xn.ZodVoid,...ut(e)});var Ut=class e extends dt{_parse(e){let{ctx:t,status:n}=this._processInputParams(e),r=this._def;if(t.parsedType!==B.array)return H(t,{code:V.invalid_type,expected:B.array,received:t.parsedType}),Ze;if(r.exactLength!==null){let e=t.data.length>r.exactLength.value,i=t.data.lengthr.maxLength.value&&(H(t,{code:V.too_big,maximum:r.maxLength.value,type:`array`,inclusive:!0,exact:!1,message:r.maxLength.message}),n.dirty()),t.common.async)return Promise.all([...t.data].map((e,n)=>r.type._parseAsync(new ct(t,e,t.path,n)))).then(e=>Xe.mergeArray(n,e));let i=[...t.data].map((e,n)=>r.type._parseSync(new ct(t,e,t.path,n)));return Xe.mergeArray(n,i)}get element(){return this._def.type}min(t,n){return new e({...this._def,minLength:{value:t,message:U.toString(n)}})}max(t,n){return new e({...this._def,maxLength:{value:t,message:U.toString(n)}})}length(t,n){return new e({...this._def,exactLength:{value:t,message:U.toString(n)}})}nonempty(e){return this.min(1,e)}};Ut.create=(e,t)=>new Ut({type:e,minLength:null,maxLength:null,exactLength:null,typeName:xn.ZodArray,...ut(t)});function Wt(e){if(e instanceof Gt){let t={};for(let n in e.shape){let r=e.shape[n];t[n]=un.create(Wt(r))}return new Gt({...e._def,shape:()=>t})}else if(e instanceof Ut)return new Ut({...e._def,type:Wt(e.element)});else if(e instanceof un)return un.create(Wt(e.unwrap()));else if(e instanceof dn)return dn.create(Wt(e.unwrap()));else if(e instanceof Zt)return Zt.create(e.items.map(e=>Wt(e)));else return e}var Gt=class e extends dt{constructor(){super(...arguments),this._cached=null,this.nonstrict=this.passthrough,this.augment=this.extend}_getCached(){if(this._cached!==null)return this._cached;let e=this._def.shape(),t=ze.objectKeys(e);return this._cached={shape:e,keys:t}}_parse(e){if(this._getType(e)!==B.object){let t=this._getOrReturnCtx(e);return H(t,{code:V.invalid_type,expected:B.object,received:t.parsedType}),Ze}let{status:t,ctx:n}=this._processInputParams(e),{shape:r,keys:i}=this._getCached(),a=[];if(!(this._def.catchall instanceof Vt&&this._def.unknownKeys===`strip`))for(let e in n.data)i.includes(e)||a.push(e);let o=[];for(let e of i){let t=r[e],i=n.data[e];o.push({key:{status:`valid`,value:e},value:t._parse(new ct(n,i,n.path,e)),alwaysSet:e in n.data})}if(this._def.catchall instanceof Vt){let e=this._def.unknownKeys;if(e===`passthrough`)for(let e of a)o.push({key:{status:`valid`,value:e},value:{status:`valid`,value:n.data[e]}});else if(e===`strict`)a.length>0&&(H(n,{code:V.unrecognized_keys,keys:a}),t.dirty());else if(e!==`strip`)throw Error(`Internal ZodObject error: invalid unknownKeys value.`)}else{let e=this._def.catchall;for(let t of a){let r=n.data[t];o.push({key:{status:`valid`,value:t},value:e._parse(new ct(n,r,n.path,t)),alwaysSet:t in n.data})}}return n.common.async?Promise.resolve().then(async()=>{let e=[];for(let t of o){let n=await t.key,r=await t.value;e.push({key:n,value:r,alwaysSet:t.alwaysSet})}return e}).then(e=>Xe.mergeObjectSync(t,e)):Xe.mergeObjectSync(t,o)}get shape(){return this._def.shape()}strict(t){return U.errToObj,new e({...this._def,unknownKeys:`strict`,...t===void 0?{}:{errorMap:(e,n)=>{var r;let i=(r=this._def).errorMap?.call(r,e,n).message??n.defaultError;return e.code===`unrecognized_keys`?{message:U.errToObj(t).message??i}:{message:i}}}})}strip(){return new e({...this._def,unknownKeys:`strip`})}passthrough(){return new e({...this._def,unknownKeys:`passthrough`})}extend(t){return new e({...this._def,shape:()=>({...this._def.shape(),...t})})}merge(t){return new e({unknownKeys:t._def.unknownKeys,catchall:t._def.catchall,shape:()=>({...this._def.shape(),...t._def.shape()}),typeName:xn.ZodObject})}setKey(e,t){return this.augment({[e]:t})}catchall(t){return new e({...this._def,catchall:t})}pick(t){let n={};return ze.objectKeys(t).forEach(e=>{t[e]&&this.shape[e]&&(n[e]=this.shape[e])}),new e({...this._def,shape:()=>n})}omit(t){let n={};return ze.objectKeys(this.shape).forEach(e=>{t[e]||(n[e]=this.shape[e])}),new e({...this._def,shape:()=>n})}deepPartial(){return Wt(this)}partial(t){let n={};return ze.objectKeys(this.shape).forEach(e=>{let r=this.shape[e];t&&!t[e]?n[e]=r:n[e]=r.optional()}),new e({...this._def,shape:()=>n})}required(t){let n={};return ze.objectKeys(this.shape).forEach(e=>{if(t&&!t[e])n[e]=this.shape[e];else{let t=this.shape[e];for(;t instanceof un;)t=t._def.innerType;n[e]=t}}),new e({...this._def,shape:()=>n})}keyof(){return an(ze.objectKeys(this.shape))}};Gt.create=(e,t)=>new Gt({shape:()=>e,unknownKeys:`strip`,catchall:Vt.create(),typeName:xn.ZodObject,...ut(t)}),Gt.strictCreate=(e,t)=>new Gt({shape:()=>e,unknownKeys:`strict`,catchall:Vt.create(),typeName:xn.ZodObject,...ut(t)}),Gt.lazycreate=(e,t)=>new Gt({shape:e,unknownKeys:`strip`,catchall:Vt.create(),typeName:xn.ZodObject,...ut(t)});var Kt=class extends dt{_parse(e){let{ctx:t}=this._processInputParams(e),n=this._def.options;function r(e){for(let t of e)if(t.result.status===`valid`)return t.result;for(let n of e)if(n.result.status===`dirty`)return t.common.issues.push(...n.ctx.common.issues),n.result;let n=e.map(e=>new Ue(e.ctx.common.issues));return H(t,{code:V.invalid_union,unionErrors:n}),Ze}if(t.common.async)return Promise.all(n.map(async e=>{let n={...t,common:{...t.common,issues:[]},parent:null};return{result:await e._parseAsync({data:t.data,path:t.path,parent:n}),ctx:n}})).then(r);{let e,r=[];for(let i of n){let n={...t,common:{...t.common,issues:[]},parent:null},a=i._parseSync({data:t.data,path:t.path,parent:n});if(a.status===`valid`)return a;a.status===`dirty`&&!e&&(e={result:a,ctx:n}),n.common.issues.length&&r.push(n.common.issues)}if(e)return t.common.issues.push(...e.ctx.common.issues),e.result;let i=r.map(e=>new Ue(e));return H(t,{code:V.invalid_union,unionErrors:i}),Ze}}get options(){return this._def.options}};Kt.create=(e,t)=>new Kt({options:e,typeName:xn.ZodUnion,...ut(t)});var qt=e=>e instanceof nn?qt(e.schema):e instanceof ln?qt(e.innerType()):e instanceof rn?[e.value]:e instanceof on?e.options:e instanceof sn?ze.objectValues(e.enum):e instanceof fn?qt(e._def.innerType):e instanceof Lt?[void 0]:e instanceof Rt?[null]:e instanceof un?[void 0,...qt(e.unwrap())]:e instanceof dn?[null,...qt(e.unwrap())]:e instanceof gn||e instanceof vn?qt(e.unwrap()):e instanceof pn?qt(e._def.innerType):[],Jt=class e extends dt{_parse(e){let{ctx:t}=this._processInputParams(e);if(t.parsedType!==B.object)return H(t,{code:V.invalid_type,expected:B.object,received:t.parsedType}),Ze;let n=this.discriminator,r=t.data[n],i=this.optionsMap.get(r);return i?t.common.async?i._parseAsync({data:t.data,path:t.path,parent:t}):i._parseSync({data:t.data,path:t.path,parent:t}):(H(t,{code:V.invalid_union_discriminator,options:Array.from(this.optionsMap.keys()),path:[n]}),Ze)}get discriminator(){return this._def.discriminator}get options(){return this._def.options}get optionsMap(){return this._def.optionsMap}static create(t,n,r){let i=new Map;for(let e of n){let n=qt(e.shape[t]);if(!n.length)throw Error(`A discriminator value for key \`${t}\` could not be extracted from all schema options`);for(let r of n){if(i.has(r))throw Error(`Discriminator property ${String(t)} has duplicate value ${String(r)}`);i.set(r,e)}}return new e({typeName:xn.ZodDiscriminatedUnion,discriminator:t,options:n,optionsMap:i,...ut(r)})}};function Yt(e,t){let n=Ve(e),r=Ve(t);if(e===t)return{valid:!0,data:e};if(n===B.object&&r===B.object){let n=ze.objectKeys(t),r=ze.objectKeys(e).filter(e=>n.indexOf(e)!==-1),i={...e,...t};for(let n of r){let r=Yt(e[n],t[n]);if(!r.valid)return{valid:!1};i[n]=r.data}return{valid:!0,data:i}}else if(n===B.array&&r===B.array){if(e.length!==t.length)return{valid:!1};let n=[];for(let r=0;r{if(et(e)||et(r))return Ze;let i=Yt(e.value,r.value);return i.valid?((tt(e)||tt(r))&&t.dirty(),{status:t.value,value:i.data}):(H(n,{code:V.invalid_intersection_types}),Ze)};return n.common.async?Promise.all([this._def.left._parseAsync({data:n.data,path:n.path,parent:n}),this._def.right._parseAsync({data:n.data,path:n.path,parent:n})]).then(([e,t])=>r(e,t)):r(this._def.left._parseSync({data:n.data,path:n.path,parent:n}),this._def.right._parseSync({data:n.data,path:n.path,parent:n}))}};Xt.create=(e,t,n)=>new Xt({left:e,right:t,typeName:xn.ZodIntersection,...ut(n)});var Zt=class e extends dt{_parse(e){let{status:t,ctx:n}=this._processInputParams(e);if(n.parsedType!==B.array)return H(n,{code:V.invalid_type,expected:B.array,received:n.parsedType}),Ze;if(n.data.lengththis._def.items.length&&(H(n,{code:V.too_big,maximum:this._def.items.length,inclusive:!0,exact:!1,type:`array`}),t.dirty());let r=[...n.data].map((e,t)=>{let r=this._def.items[t]||this._def.rest;return r?r._parse(new ct(n,e,n.path,t)):null}).filter(e=>!!e);return n.common.async?Promise.all(r).then(e=>Xe.mergeArray(t,e)):Xe.mergeArray(t,r)}get items(){return this._def.items}rest(t){return new e({...this._def,rest:t})}};Zt.create=(e,t)=>{if(!Array.isArray(e))throw Error(`You must pass an array of schemas to z.tuple([ ... ])`);return new Zt({items:e,typeName:xn.ZodTuple,rest:null,...ut(t)})};var Qt=class e extends dt{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:n}=this._processInputParams(e);if(n.parsedType!==B.object)return H(n,{code:V.invalid_type,expected:B.object,received:n.parsedType}),Ze;let r=[],i=this._def.keyType,a=this._def.valueType;for(let e in n.data)r.push({key:i._parse(new ct(n,e,n.path,e)),value:a._parse(new ct(n,n.data[e],n.path,e)),alwaysSet:e in n.data});return n.common.async?Xe.mergeObjectAsync(t,r):Xe.mergeObjectSync(t,r)}get element(){return this._def.valueType}static create(t,n,r){return n instanceof dt?new e({keyType:t,valueType:n,typeName:xn.ZodRecord,...ut(r)}):new e({keyType:At.create(),valueType:t,typeName:xn.ZodRecord,...ut(n)})}},$t=class extends dt{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:n}=this._processInputParams(e);if(n.parsedType!==B.map)return H(n,{code:V.invalid_type,expected:B.map,received:n.parsedType}),Ze;let r=this._def.keyType,i=this._def.valueType,a=[...n.data.entries()].map(([e,t],a)=>({key:r._parse(new ct(n,e,n.path,[a,`key`])),value:i._parse(new ct(n,t,n.path,[a,`value`]))}));if(n.common.async){let e=new Map;return Promise.resolve().then(async()=>{for(let n of a){let r=await n.key,i=await n.value;if(r.status===`aborted`||i.status===`aborted`)return Ze;(r.status===`dirty`||i.status===`dirty`)&&t.dirty(),e.set(r.value,i.value)}return{status:t.value,value:e}})}else{let e=new Map;for(let n of a){let r=n.key,i=n.value;if(r.status===`aborted`||i.status===`aborted`)return Ze;(r.status===`dirty`||i.status===`dirty`)&&t.dirty(),e.set(r.value,i.value)}return{status:t.value,value:e}}}};$t.create=(e,t,n)=>new $t({valueType:t,keyType:e,typeName:xn.ZodMap,...ut(n)});var en=class 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Command`),zr=K.object({command:K.string(),options:K.array(K.object({name:K.string(),value:K.string()})).optional(),content:K.string().max(2e3).optional(),require_launch_channel:K.boolean().optional(),preview_image:K.object({height:K.number(),url:K.string(),width:K.number()}).optional(),components:K.array(K.object({type:K.literal(1),components:K.array(K.object({type:K.literal(2),style:K.number().gte(1).lte(5),label:K.string().max(80).optional(),custom_id:K.string().max(100).describe(`Developer-defined identifier for the button; max 100 characters`).optional()})).max(5).optional()})).optional(),pid:K.number().optional()}).describe(`Request for "SHARE_INTERACTION" Command`),Br=K.object({success:K.boolean()}).describe(`Response for "SHARE_INTERACTION" Command`),Vr=K.object({custom_id:K.string().max(64).optional(),message:K.string().max(1e3),link_id:K.string().max(64).optional()}).describe(`Request for "SHARE_LINK" Command`),Hr=K.object({success:K.boolean(),didCopyLink:K.boolean(),didSendMessage:K.boolean()}).describe(`Response for "SHARE_LINK" Command`),Ur=K.object({relationships:K.array(K.object({type:K.number(),user:K.object({id:K.string(),username:K.string(),global_name:K.union([K.string(),K.null()]).optional(),discriminator:K.string(),avatar:K.union([K.string(),K.null()]).optional(),flags:K.number(),bot:K.boolean(),avatar_decoration_data:K.union([K.object({asset:K.union([K.string(),K.null()]).optional(),skuId:K.string().optional(),expiresAt:K.number().optional()}),K.null()]).optional(),premium_type:K.union([K.number(),K.null()]).optional()}),presence:K.object({status:K.string(),activity:K.union([K.object({session_id:K.string().optional(),type:K.number().optional(),name:K.string(),url:K.union([K.string(),K.null()]).optional(),application_id:K.string().optional(),status_display_type:K.number().optional(),state:K.string().optional(),state_url:K.string().optional(),details:K.string().optional(),details_url:K.string().optional(),emoji:K.union([K.object({name:K.string(),id:K.union([K.string(),K.null()]).optional(),animated:K.union([K.boolean(),K.null()]).optional()}),K.null()]).optional(),assets:K.object({large_image:K.string().optional(),large_text:K.string().optional(),large_url:K.string().optional(),small_image:K.string().optional(),small_text:K.string().optional(),small_url:K.string().optional()}).optional(),timestamps:K.object({start:K.number().optional(),end:K.number().optional()}).optional(),party:K.object({id:K.string().optional(),size:K.array(K.number()).min(2).max(2).optional(),privacy:K.number().optional()}).optional(),secrets:K.object({match:K.string().optional(),join:K.string().optional()}).optional(),sync_id:K.string().optional(),created_at:K.number().optional(),instance:K.boolean().optional(),flags:K.number().optional(),metadata:K.object({}).optional(),platform:K.string().optional(),supported_platforms:K.array(K.string()).optional(),buttons:K.array(K.string()).optional(),hangStatus:K.string().optional()}),K.null()]).optional()}).optional()}))}).describe(`Response for "GET_RELATIONSHIPS" Command`),Wr=K.object({user_id:K.string(),content:K.string().min(0).max(1024).optional()}).describe(`Request for "INVITE_USER_EMBEDDED" Command`),Gr=K.object({id:K.string().max(64)}).describe(`Request for "GET_USER" Command`),Kr=K.union([K.object({id:K.string(),username:K.string(),global_name:K.union([K.string(),K.null()]).optional(),discriminator:K.string(),avatar:K.union([K.string(),K.null()]).optional(),flags:K.number(),bot:K.boolean(),avatar_decoration_data:K.union([K.object({asset:K.union([K.string(),K.null()]).optional(),skuId:K.string().optional(),expiresAt:K.number().optional()}),K.null()]).optional(),premium_type:K.union([K.number(),K.null()]).optional()}),K.null()]),qr=K.object({quest_id:K.string()}).describe(`Request for "GET_QUEST_ENROLLMENT_STATUS" Command`),Jr=K.object({quest_id:K.string(),is_enrolled:K.boolean(),enrolled_at:K.union([K.string(),K.null()]).optional()}).describe(`Response for "GET_QUEST_ENROLLMENT_STATUS" Command`),Yr=K.object({quest_id:K.string()}).describe(`Request for "QUEST_START_TIMER" Command`),Xr=K.object({success:K.boolean()}).describe(`Response for "QUEST_START_TIMER" Command`),Zr=K.object({quest_id:K.string(),enrolled_at:K.union([K.string(),K.null()]).optional(),completed_at:K.union([K.string(),K.null()]).optional(),external_cta_url:K.string()}).describe(`Response for "GET_QUEST" Command`),Qr=K.object({ticket:K.string()}).describe(`Response for "REQUEST_PROXY_TICKET_REFRESH" Command`),$r;(function(e){e.INITIATE_IMAGE_UPLOAD=`INITIATE_IMAGE_UPLOAD`,e.OPEN_SHARE_MOMENT_DIALOG=`OPEN_SHARE_MOMENT_DIALOG`,e.AUTHENTICATE=`AUTHENTICATE`,e.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS=`GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS`,e.SHARE_INTERACTION=`SHARE_INTERACTION`,e.SHARE_LINK=`SHARE_LINK`,e.GET_RELATIONSHIPS=`GET_RELATIONSHIPS`,e.INVITE_USER_EMBEDDED=`INVITE_USER_EMBEDDED`,e.GET_USER=`GET_USER`,e.GET_QUEST_ENROLLMENT_STATUS=`GET_QUEST_ENROLLMENT_STATUS`,e.QUEST_START_TIMER=`QUEST_START_TIMER`,e.GET_QUEST=`GET_QUEST`,e.REQUEST_PROXY_TICKET_REFRESH=`REQUEST_PROXY_TICKET_REFRESH`})($r||={});var ei=K.object({}).optional().nullable(),ti=K.void(),ni={[$r.INITIATE_IMAGE_UPLOAD]:{request:ti,response:Pr},[$r.OPEN_SHARE_MOMENT_DIALOG]:{request:Fr,response:ei},[$r.AUTHENTICATE]:{request:Ir,response:Lr},[$r.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS]:{request:ti,response:Rr},[$r.SHARE_INTERACTION]:{request:zr,response:Br},[$r.SHARE_LINK]:{request:Vr,response:Hr},[$r.GET_RELATIONSHIPS]:{request:ti,response:Ur},[$r.INVITE_USER_EMBEDDED]:{request:Wr,response:ei},[$r.GET_USER]:{request:Gr,response:Kr},[$r.GET_QUEST_ENROLLMENT_STATUS]:{request:qr,response:Jr},[$r.QUEST_START_TIMER]:{request:Yr,response:Xr},[$r.GET_QUEST]:{request:ti,response:Zr},[$r.REQUEST_PROXY_TICKET_REFRESH]:{request:ti,response:Qr}},ri=t({Activity:()=>_i,Attachment:()=>Ei,CertifiedDevice:()=>Ki,CertifiedDeviceTypeObject:()=>Gi,Channel:()=>xi,ChannelMention:()=>Ti,ChannelTypesObject:()=>bi,Commands:()=>q,DISPATCH:()=>ii,Embed:()=>Ni,EmbedAuthor:()=>ji,EmbedField:()=>Mi,EmbedFooter:()=>Di,EmbedProvider:()=>Ai,Emoji:()=>fi,Entitlement:()=>Xi,EntitlementTypesObject:()=>Yi,Guild:()=>wi,GuildMember:()=>ui,GuildMemberRPC:()=>di,Image:()=>Oi,KeyTypesObject:()=>Bi,LayoutMode:()=>ia,LayoutModeTypeObject:()=>ra,Message:()=>Ri,MessageActivity:()=>Fi,MessageApplication:()=>Ii,MessageReference:()=>Li,Orientation:()=>na,OrientationLockState:()=>Qi,OrientationLockStateTypeObject:()=>Zi,OrientationTypeObject:()=>ta,PermissionOverwrite:()=>yi,PermissionOverwriteTypeObject:()=>vi,PresenceUpdate:()=>Si,Reaction:()=>Pi,ReceiveFramePayload:()=>ai,Relationship:()=>ci,Role:()=>Ci,Scopes:()=>si,ScopesObject:()=>oi,ShortcutKey:()=>Vi,Sku:()=>Ji,SkuTypeObject:()=>qi,Status:()=>gi,StatusObject:()=>hi,ThermalState:()=>ea,ThermalStateTypeObject:()=>$i,User:()=>li,UserVoiceState:()=>mi,Video:()=>ki,VoiceDevice:()=>zi,VoiceSettingModeTypeObject:()=>Hi,VoiceSettingsIO:()=>Wi,VoiceSettingsMode:()=>Ui,VoiceState:()=>pi}),ii=`DISPATCH`,q;(function(e){e.AUTHORIZE=`AUTHORIZE`,e.GET_GUILDS=`GET_GUILDS`,e.GET_GUILD=`GET_GUILD`,e.GET_CHANNEL=`GET_CHANNEL`,e.GET_CHANNELS=`GET_CHANNELS`,e.SELECT_VOICE_CHANNEL=`SELECT_VOICE_CHANNEL`,e.SELECT_TEXT_CHANNEL=`SELECT_TEXT_CHANNEL`,e.SUBSCRIBE=`SUBSCRIBE`,e.UNSUBSCRIBE=`UNSUBSCRIBE`,e.CAPTURE_SHORTCUT=`CAPTURE_SHORTCUT`,e.SET_CERTIFIED_DEVICES=`SET_CERTIFIED_DEVICES`,e.SET_ACTIVITY=`SET_ACTIVITY`,e.GET_SKUS=`GET_SKUS`,e.GET_ENTITLEMENTS=`GET_ENTITLEMENTS`,e.GET_SKUS_EMBEDDED=`GET_SKUS_EMBEDDED`,e.GET_ENTITLEMENTS_EMBEDDED=`GET_ENTITLEMENTS_EMBEDDED`,e.START_PURCHASE=`START_PURCHASE`,e.SET_CONFIG=`SET_CONFIG`,e.SEND_ANALYTICS_EVENT=`SEND_ANALYTICS_EVENT`,e.USER_SETTINGS_GET_LOCALE=`USER_SETTINGS_GET_LOCALE`,e.OPEN_EXTERNAL_LINK=`OPEN_EXTERNAL_LINK`,e.ENCOURAGE_HW_ACCELERATION=`ENCOURAGE_HW_ACCELERATION`,e.CAPTURE_LOG=`CAPTURE_LOG`,e.SET_ORIENTATION_LOCK_STATE=`SET_ORIENTATION_LOCK_STATE`,e.OPEN_INVITE_DIALOG=`OPEN_INVITE_DIALOG`,e.GET_PLATFORM_BEHAVIORS=`GET_PLATFORM_BEHAVIORS`,e.GET_CHANNEL_PERMISSIONS=`GET_CHANNEL_PERMISSIONS`,e.AUTHENTICATE=`AUTHENTICATE`,e.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS=`GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS`,e.GET_QUEST=`GET_QUEST`,e.GET_QUEST_ENROLLMENT_STATUS=`GET_QUEST_ENROLLMENT_STATUS`,e.GET_RELATIONSHIPS=`GET_RELATIONSHIPS`,e.GET_USER=`GET_USER`,e.INITIATE_IMAGE_UPLOAD=`INITIATE_IMAGE_UPLOAD`,e.INVITE_USER_EMBEDDED=`INVITE_USER_EMBEDDED`,e.OPEN_SHARE_MOMENT_DIALOG=`OPEN_SHARE_MOMENT_DIALOG`,e.QUEST_START_TIMER=`QUEST_START_TIMER`,e.REQUEST_PROXY_TICKET_REFRESH=`REQUEST_PROXY_TICKET_REFRESH`,e.SHARE_INTERACTION=`SHARE_INTERACTION`,e.SHARE_LINK=`SHARE_LINK`})(q||={});var ai=G({cmd:W(),data:Mn(),evt:An(),nonce:W()}).passthrough(),oi=Object.assign(Object.assign({},Lr.shape.scopes.element.overlayType._def.innerType.options[0].Values),{UNHANDLED:-1}),si=Mr(oi),ci=Ur.shape.relationships.element,li=G({id:W(),username:W(),discriminator:W(),global_name:W().optional().nullable(),avatar:W().optional().nullable(),avatar_decoration_data:G({asset:W(),sku_id:W().optional()}).nullable(),bot:En(),flags:Cn().optional().nullable(),premium_type:Cn().optional().nullable()}),ui=G({user:li,nick:W().optional().nullable(),roles:Fn(W()),joined_at:W(),deaf:En(),mute:En()}),di=G({user_id:W(),nick:W().optional().nullable(),guild_id:W(),avatar:W().optional().nullable(),avatar_decoration_data:G({asset:W(),sku_id:W().optional().nullable()}).optional().nullable(),color_string:W().optional().nullable()}),fi=G({id:W(),name:W().optional().nullable(),roles:Fn(W()).optional().nullable(),user:li.optional().nullable(),require_colons:En().optional().nullable(),managed:En().optional().nullable(),animated:En().optional().nullable(),available:En().optional().nullable()}),pi=G({mute:En(),deaf:En(),self_mute:En(),self_deaf:En(),suppress:En()}),mi=G({mute:En(),nick:W(),user:li,voice_state:pi,volume:Cn()}),hi={UNHANDLED:-1,IDLE:`idle`,DND:`dnd`,ONLINE:`online`,OFFLINE:`offline`},gi=Mr(hi),_i=G({name:W(),type:Cn(),url:W().optional().nullable(),created_at:Cn().optional().nullable(),timestamps:G({start:Cn(),end:Cn()}).partial().optional().nullable(),application_id:W().optional().nullable(),details:W().optional().nullable(),details_url:W().url().optional().nullable(),state:W().optional().nullable(),state_url:W().url().optional().nullable(),emoji:fi.optional().nullable(),party:G({id:W().optional().nullable(),size:Fn(Cn()).optional().nullable()}).optional().nullable(),assets:G({large_image:W().nullable(),large_text:W().nullable(),large_url:W().url().optional().nullable(),small_image:W().nullable(),small_text:W().nullable(),small_url:W().url().optional().nullable()}).partial().optional().nullable(),secrets:G({join:W(),match:W()}).partial().optional().nullable(),instance:En().optional().nullable(),flags:Cn().optional().nullable()}),vi={UNHANDLED:-1,ROLE:0,MEMBER:1},yi=G({id:W(),type:Mr(vi),allow:W(),deny:W()}),bi={UNHANDLED:-1,DM:1,GROUP_DM:3,GUILD_TEXT:0,GUILD_VOICE:2,GUILD_CATEGORY:4,GUILD_ANNOUNCEMENT:5,GUILD_STORE:6,ANNOUNCEMENT_THREAD:10,PUBLIC_THREAD:11,PRIVATE_THREAD:12,GUILD_STAGE_VOICE:13,GUILD_DIRECTORY:14,GUILD_FORUM:15},xi=G({id:W(),type:Mr(bi),guild_id:W().optional().nullable(),position:Cn().optional().nullable(),permission_overwrites:Fn(yi).optional().nullable(),name:W().optional().nullable(),topic:W().optional().nullable(),nsfw:En().optional().nullable(),last_message_id:W().optional().nullable(),bitrate:Cn().optional().nullable(),user_limit:Cn().optional().nullable(),rate_limit_per_user:Cn().optional().nullable(),recipients:Fn(li).optional().nullable(),icon:W().optional().nullable(),owner_id:W().optional().nullable(),application_id:W().optional().nullable(),parent_id:W().optional().nullable(),last_pin_timestamp:W().optional().nullable()}),Si=G({user:li,guild_id:W(),status:gi,activities:Fn(_i),client_status:G({desktop:gi,mobile:gi,web:gi}).partial()}),Ci=G({id:W(),name:W(),color:Cn(),hoist:En(),position:Cn(),permissions:W(),managed:En(),mentionable:En()}),wi=G({id:W(),name:W(),owner_id:W(),icon:W().nullable(),icon_hash:W().optional().nullable(),splash:W().nullable(),discovery_splash:W().nullable(),owner:En().optional().nullable(),permissions:W().optional().nullable(),region:W(),afk_channel_id:W().nullable(),afk_timeout:Cn(),widget_enabled:En().optional().nullable(),widget_channel_id:W().optional().nullable(),verification_level:Cn(),default_message_notifications:Cn(),explicit_content_filter:Cn(),roles:Fn(Ci),emojis:Fn(fi),features:Fn(W()),mfa_level:Cn(),application_id:W().nullable(),system_channel_id:W().nullable(),system_channel_flags:Cn(),rules_channel_id:W().nullable(),joined_at:W().optional().nullable(),large:En().optional().nullable(),unavailable:En().optional().nullable(),member_count:Cn().optional().nullable(),voice_states:Fn(pi).optional().nullable(),members:Fn(ui).optional().nullable(),channels:Fn(xi).optional().nullable(),presences:Fn(Si).optional().nullable(),max_presences:Cn().optional().nullable(),max_members:Cn().optional().nullable(),vanity_url_code:W().nullable(),description:W().nullable(),banner:W().nullable(),premium_tier:Cn(),premium_subscription_count:Cn().optional().nullable(),preferred_locale:W(),public_updates_channel_id:W().nullable(),max_video_channel_users:Cn().optional().nullable(),approximate_member_count:Cn().optional().nullable(),approximate_presence_count:Cn().optional().nullable()}),Ti=G({id:W(),guild_id:W(),type:Cn(),name:W()}),Ei=G({id:W(),filename:W(),size:Cn(),url:W(),proxy_url:W(),height:Cn().optional().nullable(),width:Cn().optional().nullable()}),Di=G({text:W(),icon_url:W().optional().nullable(),proxy_icon_url:W().optional().nullable()}),Oi=G({url:W().optional().nullable(),proxy_url:W().optional().nullable(),height:Cn().optional().nullable(),width:Cn().optional().nullable()}),ki=Oi.omit({proxy_url:!0}),Ai=G({name:W().optional().nullable(),url:W().optional().nullable()}),ji=G({name:W().optional().nullable(),url:W().optional().nullable(),icon_url:W().optional().nullable(),proxy_icon_url:W().optional().nullable()}),Mi=G({name:W(),value:W(),inline:En()}),Ni=G({title:W().optional().nullable(),type:W().optional().nullable(),description:W().optional().nullable(),url:W().optional().nullable(),timestamp:W().optional().nullable(),color:Cn().optional().nullable(),footer:Di.optional().nullable(),image:Oi.optional().nullable(),thumbnail:Oi.optional().nullable(),video:ki.optional().nullable(),provider:Ai.optional().nullable(),author:ji.optional().nullable(),fields:Fn(Mi).optional().nullable()}),Pi=G({count:Cn(),me:En(),emoji:fi}),Fi=G({type:Cn(),party_id:W().optional().nullable()}),Ii=G({id:W(),cover_image:W().optional().nullable(),description:W(),icon:W().optional().nullable(),name:W()}),Li=G({message_id:W().optional().nullable(),channel_id:W().optional().nullable(),guild_id:W().optional().nullable()}),Ri=G({id:W(),channel_id:W(),guild_id:W().optional().nullable(),author:li.optional().nullable(),member:ui.optional().nullable(),content:W(),timestamp:W(),edited_timestamp:W().optional().nullable(),tts:En(),mention_everyone:En(),mentions:Fn(li),mention_roles:Fn(W()),mention_channels:Fn(Ti),attachments:Fn(Ei),embeds:Fn(Ni),reactions:Fn(Pi).optional().nullable(),nonce:Ln([W(),Cn()]).optional().nullable(),pinned:En(),webhook_id:W().optional().nullable(),type:Cn(),activity:Fi.optional().nullable(),application:Ii.optional().nullable(),message_reference:Li.optional().nullable(),flags:Cn().optional().nullable(),stickers:Fn(Mn()).optional().nullable(),referenced_message:Mn().optional().nullable()}),zi=G({id:W(),name:W()}),Bi={UNHANDLED:-1,KEYBOARD_KEY:0,MOUSE_BUTTON:1,KEYBOARD_MODIFIER_KEY:2,GAMEPAD_BUTTON:3},Vi=G({type:Mr(Bi),code:Cn(),name:W()}),Hi={UNHANDLED:-1,PUSH_TO_TALK:`PUSH_TO_TALK`,VOICE_ACTIVITY:`VOICE_ACTIVITY`},Ui=G({type:Mr(Hi),auto_threshold:En(),threshold:Cn(),shortcut:Fn(Vi),delay:Cn()}),Wi=G({device_id:W(),volume:Cn(),available_devices:Fn(zi)}),Gi={UNHANDLED:-1,AUDIO_INPUT:`AUDIO_INPUT`,AUDIO_OUTPUT:`AUDIO_OUTPUT`,VIDEO_INPUT:`VIDEO_INPUT`},Ki=G({type:Mr(Gi),id:W(),vendor:G({name:W(),url:W()}),model:G({name:W(),url:W()}),related:Fn(W()),echo_cancellation:En().optional().nullable(),noise_suppression:En().optional().nullable(),automatic_gain_control:En().optional().nullable(),hardware_mute:En().optional().nullable()}),qi={UNHANDLED:-1,APPLICATION:1,DLC:2,CONSUMABLE:3,BUNDLE:4,SUBSCRIPTION:5},Ji=G({id:W(),name:W(),type:Mr(qi),price:G({amount:Cn(),currency:W()}),application_id:W(),flags:Cn(),release_date:W().nullable()}),Yi={UNHANDLED:-1,PURCHASE:1,PREMIUM_SUBSCRIPTION:2,DEVELOPER_GIFT:3,TEST_MODE_PURCHASE:4,FREE_PURCHASE:5,USER_GIFT:6,PREMIUM_PURCHASE:7},Xi=G({id:W(),sku_id:W(),application_id:W(),user_id:W(),gift_code_flags:Cn(),type:Mr(Yi),gifter_user_id:W().optional().nullable(),branches:Fn(W()).optional().nullable(),starts_at:W().optional().nullable(),ends_at:W().optional().nullable(),parent_id:W().optional().nullable(),consumed:En().optional().nullable(),deleted:En().optional().nullable(),gift_code_batch_id:W().optional().nullable()}),Zi={UNHANDLED:-1,UNLOCKED:1,PORTRAIT:2,LANDSCAPE:3},Qi=Mr(Zi),$i={UNHANDLED:-1,NOMINAL:0,FAIR:1,SERIOUS:2,CRITICAL:3},ea=Mr($i),ta={UNHANDLED:-1,PORTRAIT:0,LANDSCAPE:1},na=Mr(ta),ra={UNHANDLED:-1,FOCUSED:0,PIP:1,GRID:2},ia=Mr(ra),aa=`ERROR`,oa;(function(e){e.READY=`READY`,e.VOICE_STATE_UPDATE=`VOICE_STATE_UPDATE`,e.SPEAKING_START=`SPEAKING_START`,e.SPEAKING_STOP=`SPEAKING_STOP`,e.ACTIVITY_LAYOUT_MODE_UPDATE=`ACTIVITY_LAYOUT_MODE_UPDATE`,e.ORIENTATION_UPDATE=`ORIENTATION_UPDATE`,e.CURRENT_USER_UPDATE=`CURRENT_USER_UPDATE`,e.CURRENT_GUILD_MEMBER_UPDATE=`CURRENT_GUILD_MEMBER_UPDATE`,e.ENTITLEMENT_CREATE=`ENTITLEMENT_CREATE`,e.THERMAL_STATE_UPDATE=`THERMAL_STATE_UPDATE`,e.ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE=`ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE`,e.RELATIONSHIP_UPDATE=`RELATIONSHIP_UPDATE`,e.ACTIVITY_JOIN=`ACTIVITY_JOIN`,e.QUEST_ENROLLMENT_STATUS_UPDATE=`QUEST_ENROLLMENT_STATUS_UPDATE`})(oa||={});var sa=ai.extend({evt:Jn(oa),nonce:W().nullable(),cmd:Kn(ii),data:G({}).passthrough()}),ca=ai.extend({evt:Kn(aa),data:G({code:Cn(),message:W().optional()}).passthrough(),cmd:Jn(q),nonce:W().nullable()}),la=Ln([sa,sa.extend({evt:W()}),ca]);function ua(e){let t=e.evt;if(!(t in oa))throw Error(`Unrecognized event type ${e.evt}`);return da[t].payload.parse(e)}var da={[oa.READY]:{payload:sa.extend({evt:Kn(oa.READY),data:G({v:Cn(),config:G({cdn_host:W().optional(),api_endpoint:W(),environment:W()}),user:G({id:W(),username:W(),discriminator:W(),avatar:W().optional()}).optional()})})},[oa.VOICE_STATE_UPDATE]:{payload:sa.extend({evt:Kn(oa.VOICE_STATE_UPDATE),data:mi}),subscribeArgs:G({channel_id:W()})},[oa.SPEAKING_START]:{payload:sa.extend({evt:Kn(oa.SPEAKING_START),data:G({lobby_id:W().optional(),channel_id:W().optional(),user_id:W()})}),subscribeArgs:G({lobby_id:W().nullable().optional(),channel_id:W().nullable().optional()})},[oa.SPEAKING_STOP]:{payload:sa.extend({evt:Kn(oa.SPEAKING_STOP),data:G({lobby_id:W().optional(),channel_id:W().optional(),user_id:W()})}),subscribeArgs:G({lobby_id:W().nullable().optional(),channel_id:W().nullable().optional()})},[oa.ACTIVITY_LAYOUT_MODE_UPDATE]:{payload:sa.extend({evt:Kn(oa.ACTIVITY_LAYOUT_MODE_UPDATE),data:G({layout_mode:Mr(ra)})})},[oa.ORIENTATION_UPDATE]:{payload:sa.extend({evt:Kn(oa.ORIENTATION_UPDATE),data:G({screen_orientation:Mr(ta),orientation:Jn(Ar)})})},[oa.CURRENT_USER_UPDATE]:{payload:sa.extend({evt:Kn(oa.CURRENT_USER_UPDATE),data:li})},[oa.CURRENT_GUILD_MEMBER_UPDATE]:{payload:sa.extend({evt:Kn(oa.CURRENT_GUILD_MEMBER_UPDATE),data:di}),subscribeArgs:G({guild_id:W()})},[oa.ENTITLEMENT_CREATE]:{payload:sa.extend({evt:Kn(oa.ENTITLEMENT_CREATE),data:G({entitlement:Xi})})},[oa.THERMAL_STATE_UPDATE]:{payload:sa.extend({evt:Kn(oa.THERMAL_STATE_UPDATE),data:G({thermal_state:ea})})},[oa.ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE]:{payload:sa.extend({evt:Kn(oa.ACTIVITY_INSTANCE_PARTICIPANTS_UPDATE),data:G({participants:Rr.shape.participants})})},[oa.RELATIONSHIP_UPDATE]:{payload:sa.extend({evt:Kn(oa.RELATIONSHIP_UPDATE),data:ci})},[oa.ACTIVITY_JOIN]:{payload:sa.extend({evt:Kn(oa.ACTIVITY_JOIN),data:G({applicationId:W(),secret:W()})})},[oa.QUEST_ENROLLMENT_STATUS_UPDATE]:{payload:sa.extend({evt:Kn(oa.QUEST_ENROLLMENT_STATUS_UPDATE),data:G({quest_id:W(),is_enrolled:En(),enrolled_at:W().date()})})}};function fa(e,t){throw t}var pa=G({}).nullable(),ma=G({code:W()}),ha=G({guilds:Fn(G({id:W(),name:W()}))}),ga=G({id:W(),name:W(),icon_url:W().optional(),members:Fn(ui)}),_a=G({id:W(),type:Mr(bi),guild_id:W().optional().nullable(),name:W().optional().nullable(),topic:W().optional().nullable(),bitrate:Cn().optional().nullable(),user_limit:Cn().optional().nullable(),position:Cn().optional().nullable(),voice_states:Fn(mi),messages:Fn(Ri)}),va=G({channels:Fn(xi)});_a.nullable();var ya=_a.nullable(),ba=_a.nullable();G({input:Wi,output:Wi,mode:Ui,automatic_gain_control:En(),echo_cancellation:En(),noise_suppression:En(),qos:En(),silence_warning:En(),deaf:En(),mute:En()});var xa=G({evt:W()}),Sa=G({shortcut:Vi}),Ca=_i,wa=G({skus:Fn(Ji)}),Ta=G({entitlements:Fn(Xi)}),Ea=Fn(Xi).nullable(),Da=G({use_interactive_pip:En()}),Oa=G({locale:W()}),ka=G({enabled:En()}),Aa=G({permissions:Tn().or(W())}),ja=Nr(G({opened:En().or(An())}).default({opened:null})),Ma=G({iosKeyboardResizesView:Zn(En())}),Na=ai.extend({cmd:Jn(q),evt:An()});function Pa({cmd:e,data:t}){switch(e){case q.AUTHORIZE:return ma.parse(t);case q.CAPTURE_SHORTCUT:return Sa.parse(t);case q.ENCOURAGE_HW_ACCELERATION:return ka.parse(t);case q.GET_CHANNEL:return _a.parse(t);case q.GET_CHANNELS:return va.parse(t);case q.GET_CHANNEL_PERMISSIONS:return Aa.parse(t);case q.GET_GUILD:return ga.parse(t);case q.GET_GUILDS:return ha.parse(t);case q.GET_PLATFORM_BEHAVIORS:return Ma.parse(t);case q.GET_CHANNEL:return _a.parse(t);case q.SELECT_TEXT_CHANNEL:return ba.parse(t);case q.SELECT_VOICE_CHANNEL:return ya.parse(t);case q.SET_ACTIVITY:return Ca.parse(t);case q.GET_SKUS_EMBEDDED:return wa.parse(t);case q.GET_ENTITLEMENTS_EMBEDDED:return Ta.parse(t);case q.SET_CONFIG:return Da.parse(t);case q.START_PURCHASE:return Ea.parse(t);case q.SUBSCRIBE:case q.UNSUBSCRIBE:return xa.parse(t);case q.USER_SETTINGS_GET_LOCALE:return Oa.parse(t);case q.OPEN_EXTERNAL_LINK:return ja.parse(t);case q.SET_ORIENTATION_LOCK_STATE:case q.SET_CERTIFIED_DEVICES:case q.SEND_ANALYTICS_EVENT:case q.OPEN_INVITE_DIALOG:case q.CAPTURE_LOG:case q.GET_SKUS:case q.GET_ENTITLEMENTS:return pa.parse(t);case q.AUTHENTICATE:case q.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS:case q.GET_QUEST:case q.GET_QUEST_ENROLLMENT_STATUS:case q.GET_RELATIONSHIPS:case q.GET_USER:case q.INITIATE_IMAGE_UPLOAD:case q.INVITE_USER_EMBEDDED:case q.OPEN_SHARE_MOMENT_DIALOG:case q.QUEST_START_TIMER:case q.REQUEST_PROXY_TICKET_REFRESH:case q.SHARE_INTERACTION:case q.SHARE_LINK:let{response:n}=ni[e];return n.parse(t);default:fa(e,Error(`Unrecognized command ${e}`))}}function Fa(e){return 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Va=e=>za(e,q.AUTHORIZE,ma),Ha=e=>za(e,q.CAPTURE_LOG,pa),Ua=e=>za(e,q.ENCOURAGE_HW_ACCELERATION,ka),Wa=e=>za(e,q.GET_CHANNEL,_a),Ga=e=>za(e,q.GET_ENTITLEMENTS_EMBEDDED,Ta),Ka=e=>za(e,q.GET_SKUS_EMBEDDED,wa),qa=e=>za(e,q.GET_CHANNEL_PERMISSIONS,Aa),Ja=e=>za(e,q.GET_PLATFORM_BEHAVIORS,Ma),Ya=e=>za(e,q.OPEN_EXTERNAL_LINK,ja),Xa=e=>za(e,q.OPEN_INVITE_DIALOG,pa);_i.pick({state:!0,state_url:!0,details:!0,details_url:!0,timestamps:!0,assets:!0,party:!0,secrets:!0,instance:!0,type:!0}).extend({type:_i.shape.type.optional(),instance:_i.shape.instance.optional()}).nullable();var Za=e=>za(e,q.SET_ACTIVITY,Ca),Qa=e=>za(e,q.SET_CONFIG,Da);function $a({sendCommand:e,cmd:t,response:n,fallbackTransform:r,transferTransform:i=()=>void 0}){let a=ai.extend({cmd:Kn(t),data:n});return async n=>{try{let r=await e({cmd:t,args:n,transfer:i(n)});return a.parse(r).data}catch(o){if(o.code===kr.INVALID_PAYLOAD){let o=r(n),s=await e({cmd:t,args:o,transfer:i(o)});return a.parse(s).data}else throw o}}}var eo=e=>({lock_state:e.lock_state,picture_in_picture_lock_state:e.picture_in_picture_lock_state}),to=e=>$a({sendCommand:e,cmd:q.SET_ORIENTATION_LOCK_STATE,response:pa,fallbackTransform:eo}),no=e=>za(e,q.START_PURCHASE,Ea),ro=e=>za(e,q.USER_SETTINGS_GET_LOCALE,Oa),io=Ba($r.AUTHENTICATE),ao=Ba($r.GET_ACTIVITY_INSTANCE_CONNECTED_PARTICIPANTS),oo=Ba($r.GET_QUEST),so=Ba($r.GET_QUEST_ENROLLMENT_STATUS),co=Ba($r.GET_RELATIONSHIPS),lo=Ba($r.GET_USER),uo=Ba($r.INITIATE_IMAGE_UPLOAD),fo=Ba($r.INVITE_USER_EMBEDDED),po=Ba($r.OPEN_SHARE_MOMENT_DIALOG),mo=Ba($r.QUEST_START_TIMER),ho=Ba($r.REQUEST_PROXY_TICKET_REFRESH),go=Ba($r.SHARE_INTERACTION),_o=Ba($r.SHARE_LINK);function 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this.root.querySelectorAll(`.pressed`))e.classList.remove(`pressed`);this.sharedActions.clearSource(`touch`)}destroy(){this.reset(),this.root.remove()}},As={block:[55,.12,.22],hit:[85,.3,.42],counter_hit:[105,.38,.5],stun:[125,.42,.55],knockdown:[180,.62,.65]},js=class{settings;constructor(e){this.settings=e}event(e){if(!this.settings().haptics)return;let t=As[e.kind];if(t===void 0)return;let n=this.padActuator();if(n===null){this.vibrate(t[0]);return}try{Promise.resolve(n.playEffect(`dual-rumble`,{duration:Math.min(180,Math.max(0,t[0])),strongMagnitude:Math.min(.65,Math.max(0,t[1])),weakMagnitude:Math.min(.65,Math.max(0,t[2]))})).catch(()=>void 0)}catch{}}padActuator(){if(typeof navigator.getGamepads!=`function`)return null;let e;try{e=[...navigator.getGamepads.call(navigator)]}catch{return null}let t=e.find(e=>e!==null&&e.connected&&`vibrationActuator`in e)?.vibrationActuator;return t==null||typeof t.playEffect!=`function`?null:t}vibrate(e){if(!(!Es()||typeof navigator.vibrate!=`function`))try{navigator.vibrate(Math.min(180,Math.max(0,e)))}catch{}}},Ms={KeyF:[`left`,`jab`],KeyJ:[`right`,`jab`],KeyR:[`left`,`straight`],KeyU:[`right`,`straight`],KeyG:[`left`,`hook`],KeyH:[`right`,`hook`],KeyT:[`left`,`uppercut`],KeyY:[`right`,`uppercut`]},Ns={KeyZ:{kind:`slip_left`},KeyX:{kind:`slip_right`},KeyC:{kind:`weave`},KeyV:{kind:`pull`},KeyB:{kind:`clinch`},KeyN:{kind:`switch_stance`},KeyM:{kind:`taunt`},Digit1:{kind:`foul`,foul:`low_blow`},Digit2:{kind:`foul`,foul:`headbutt`},ArrowLeft:{kind:`get_up_left`},ArrowRight:{kind:`get_up_right`}},Ps=new Set([...Object.keys(Ms),...Object.keys(Ns),`KeyW`,`KeyA`,`KeyS`,`KeyD`,`KeyQ`,`KeyE`,`ShiftLeft`,`ShiftRight`,`AltLeft`,`AltRight`]),Fs=[`Move: W up · S down · A left · D right`,`High / low guard: Q / E`,`Left/right jab: F / J`,`Left/right straight: R / U`,`Left/right hook: G / H`,`Left/right uppercut: T / Y`,`Body: Shift · Power: Alt`,`Slip: Z / X · Weave: C · Pull: V`,`Clinch: B · Stance: N · Taunt: M · Fouls: 1 / 2`,`Get-up rhythm: ← / →`,`Controller move: left stick. High / low guard: left / right shoulder (independent of punches).`,`Controller face classes: bottom jab · right straight · left hook · top uppercut.`,`Controller face hand: hold D-pad left for left hand or D-pad right for right hand, then press a face punch; otherwise punches use the right hand. A direction used for a punch is consumed and does not evade.`,`Controller modifiers: left trigger body · right trigger power.`,`Controller actions: left stick press clinch · right stick press switch stance · hold right trigger + right stick press to taunt · D-pad up weave · D-pad down pull · tap and release D-pad left/right to slip; while down, D-pad left/right performs the private get-up rhythm immediately.`,`Controller fouls: View/Back low blow · Menu/Start headbutt.`,`Right-stick gesture: horizontal 0–22.5° hook · 22.5–45° jab · 45–70° straight · 70–90° uppercut; left/right direction selects hand.`,`Touch: drag the left side to move · tap a punch pad's left or right half for that hand · hold BODY, POWER, GUARD or LOW · tap ◀ SLIP, SLIP ▶, WEAVE, PULL or CLINCH.`];function Is(e,t){return e.kind===t.kind?e.kind===`punch`&&t.kind===`punch`?e.hand===t.hand&&e.class===t.class&&e.target===t.target&&e.power===t.power:e.kind===`foul`&&t.kind===`foul`?e.foul===t.foul:!0:!1}function Ls(e,t,n){if(n<1||e.length>0&&Is(e.at(-1),t))return;let r=e.length-n+1;r>0&&e.splice(0,r),e.push(t)}var Rs=class{maximum;queue=[];counter=0;listener=null;constructor(e=1){this.maximum=e}setListener(e){this.listener=e}push(e,t){if(this.maximum<1)return;let n=this.queue.at(-1);if(n!==void 0&&Is(n.action,t)){n.source=e;return}let r={...t,id:`c${this.counter+=1}`},i=this.queue.length-this.maximum+1;i>0&&this.queue.splice(0,i),this.queue.push({action:r,source:e}),this.listener?.(r)}clear(){this.queue.length=0}clearSource(e){let t=this.queue.filter(t=>t.source!==e);this.queue.splice(0,this.queue.length,...t)}drain(e){return this.queue.splice(0,e).map(e=>e.action)}};function zs(e,t,n=.18){let r=Math.hypot(e,t);if(!Number.isFinite(r)||r<=n)return{x:0,y:0};let i=(Math.min(1,r)-n)/(1-n);return{x:e/r*i,y:t/r*i}}var Bs=(e,t)=>{let n=Math.atan2(Math.abs(t),Math.abs(e))*180/Math.PI;return n<22.5?`hook`:n<45?`jab`:n<70?`straight`:`uppercut`},Vs=class{active=!1;hand=`right`;target=`head`;power=`normal`;peak={x:0,y:0};peakMagnitude=0;update(e,t,n,r){let i=Math.hypot(e,t);if(!this.active&&i>=.55&&Math.abs(e)>=.12)return this.active=!0,this.hand=e<0?`left`:`right`,this.target=n?`body`:`head`,this.power=r?`power`:`normal`,this.peak={x:e,y:t},this.peakMagnitude=i,null;if(!this.active)return null;if(i>this.peakMagnitude&&(this.peak={x:e,y:t},this.peakMagnitude=i),i<=.25){let e={kind:`punch`,hand:this.hand,class:Bs(this.peak.x,this.peak.y),target:this.target,power:this.power};return this.reset(),e}return null}reset(){this.active=!1,this.peak={x:0,y:0},this.peakMagnitude=0}},Hs=[`jab`,`straight`,`hook`,`uppercut`],Us=(e,t)=>e.buttons[t]?.pressed===!0;function Ws(){let e=navigator.getGamepads;if(typeof e!=`function`)return null;try{return[...e.call(navigator)].find(e=>e!==null&&e.connected&&e.mapping===`standard`)??null}catch{return null}}var Gs=class{maximumQueue;sharedActions;gesture=new Vs;queue=[];previous=new Set;selectorConsumed=new Map;raf=0;currentId=null;moveX=0;moveY=0;defense=`none`;knockdown=!1;enabled=!0;disconnect=e=>{e.gamepad.id===this.currentId&&this.reset()};constructor(e=1,t){this.maximumQueue=e,this.sharedActions=t,window.addEventListener(`gamepaddisconnected`,this.disconnect),this.raf=requestAnimationFrame(()=>this.poll())}push(e){this.sharedActions===void 0?Ls(this.queue,e,this.maximumQueue):this.sharedActions.push(`gamepad`,e)}clearActions(){this.queue.length=0,this.sharedActions?.clear()}poll(){if(!this.enabled){this.reset(),this.schedulePoll();return}let e=Ws();if(e===null){this.currentId!==null&&this.reset(),this.schedulePoll();return}this.currentId!==null&&this.currentId!==e.id&&this.reset(),this.currentId=e.id;let t=zs(e.axes[0]??0,e.axes[1]??0);this.moveX=Math.round(t.x*1e3),this.moveY=Math.round(-t.y*1e3);let n=Us(e,4)?`guard_high`:Us(e,5)?`guard_low`:`none`;n!==`none`&&n!==this.defense&&this.clearActions(),this.defense=n;let r=this.gesture.update(e.axes[2]??0,e.axes[3]??0,Us(e,6),Us(e,7));r!==null&&this.push(r);let i=Hs.some((t,n)=>Us(e,n)&&!this.previous.has(n));for(let t of[14,15]){let n=Us(e,t),r=this.previous.has(t);this.knockdown?(n&&!r&&this.push({kind:t===14?`get_up_left`:`get_up_right`}),this.selectorConsumed.delete(t)):n?(r||this.selectorConsumed.set(t,!1),i&&this.selectorConsumed.set(t,!0)):r&&(this.selectorConsumed.get(t)===!1&&this.push({kind:t===14?`slip_left`:`slip_right`}),this.selectorConsumed.delete(t))}for(let t=0;tthis.poll())}setKnockdown(e){this.knockdown=e}setEnabled(e){this.enabled=e,e||this.reset()}frame(e=4){let t=this.sharedActions===void 0?this.queue.splice(0,e):[];return{moveX:this.moveX,moveY:this.moveY,defense:this.defense,actions:t}}reset(){this.currentId=null,this.moveX=this.moveY=0,this.defense=`none`,this.queue.length=0,this.sharedActions?.clearSource(`gamepad`),this.previous.clear(),this.selectorConsumed.clear(),this.gesture.reset()}destroy(){cancelAnimationFrame(this.raf),window.removeEventListener(`gamepaddisconnected`,this.disconnect),this.reset()}},Ks=class{target;maximumQueue;sharedActions;held=new Set;queue=[];enabled=!0;keydown=e=>{if(!Ps.has(e.code))return;if(!this.enabled){this.held.add(e.code);return}if(e.preventDefault(),e.repeat){this.held.add(e.code);return}this.held.add(e.code),(e.code===`KeyQ`||e.code===`KeyE`)&&this.clearActions();let t=Ms[e.code];if(t!==void 0)this.push({kind:`punch`,hand:t[0],class:t[1],target:this.hasShift()?`body`:`head`,power:this.hasAlt()?`power`:`normal`});else{let t=Ns[e.code];t!==void 0&&this.push(t)}};keyup=e=>{Ps.has(e.code)&&(this.enabled&&e.preventDefault(),this.held.delete(e.code))};visibility=()=>{document.hidden&&this.reset()};blur=()=>this.reset();constructor(e=window,t=1,n){this.target=e,this.maximumQueue=t,this.sharedActions=n,e.addEventListener(`keydown`,this.keydown),e.addEventListener(`keyup`,this.keyup),e.addEventListener(`blur`,this.blur),document.addEventListener(`visibilitychange`,this.visibility)}hasShift(){return this.held.has(`ShiftLeft`)||this.held.has(`ShiftRight`)}hasAlt(){return this.held.has(`AltLeft`)||this.held.has(`AltRight`)}push(e){this.sharedActions===void 0?Ls(this.queue,e,this.maximumQueue):this.sharedActions.push(`keyboard`,e)}clearActions(){this.queue.length=0,this.sharedActions?.clear()}setEnabled(e){this.enabled=e,e||(this.queue.length=0,this.sharedActions?.clearSource(`keyboard`))}frame(e=4){if(!this.enabled)return{moveX:0,moveY:0,defense:`none`,actions:[]};let t=(this.held.has(`KeyD`)?1e3:0)-(this.held.has(`KeyA`)?1e3:0),n=(this.held.has(`KeyW`)?1e3:0)-(this.held.has(`KeyS`)?1e3:0);t!==0&&n!==0&&(t=Math.sign(t)*707,n=Math.sign(n)*707);let r=this.held.has(`KeyQ`)?`guard_high`:this.held.has(`KeyE`)?`guard_low`:`none`;return{moveX:t,moveY:n,defense:r,actions:this.sharedActions===void 0?this.queue.splice(0,e):[]}}reset(){this.held.clear(),this.queue.length=0,this.sharedActions?.clearSource(`keyboard`)}destroy(){this.reset(),this.target.removeEventListener(`keydown`,this.keydown),this.target.removeEventListener(`keyup`,this.keyup),this.target.removeEventListener(`blur`,this.blur),document.removeEventListener(`visibilitychange`,this.visibility)}},qs=class{actions=new Rs(1);keyboard;gamepad;touch=null;reset=()=>{this.keyboard.reset(),this.gamepad.reset(),this.touch?.reset(),this.actions.clear(),this.gamepad.setKnockdown(!1)};constructor(){this.keyboard=new Ks(window,1,this.actions),this.gamepad=new Gs(1,this.actions),window.addEventListener(`blur`,this.reset),document.addEventListener(`visibilitychange`,this.visibility)}visibility=()=>{document.hidden&&this.reset()};attachTouch(e,t=Es()){this.touch!==null||!t||(this.touch=new ks(e,this.actions))}setActive(e,t=e){this.keyboard.setEnabled(e),this.gamepad.setEnabled(e),this.touch?.setEnabled(e,t)}setKnockdown(e){this.gamepad.setKnockdown(e),this.touch?.setKnockdown(e)}onAction(e){this.actions.setListener(e)}held(){let e=this.keyboard.frame(0),t=this.gamepad.frame(0),n=this.touch?.frame()??null;return{moveX:t.moveX===0?n!==null&&n.moveX!==0?n.moveX:e.moveX:t.moveX,moveY:t.moveY===0?n!==null&&n.moveY!==0?n.moveY:e.moveY:t.moveY,defense:t.defense===`none`?n!==null&&n.defense!==`none`?n.defense:e.defense:t.defense}}frame(){return{...this.held(),actions:this.actions.drain(4)}}destroy(){window.removeEventListener(`blur`,this.reset),document.removeEventListener(`visibilitychange`,this.visibility),this.keyboard.destroy(),this.gamepad.destroy(),this.touch?.destroy()}},Js=(e,t,n)=>e+(t-e)*n,Ys=(e,t,n)=>({...t,x:Js(e.x,t.x,n),y:Js(e.y,t.y,n),facing:Js(e.facing,t.facing,n),facing_x:Js(e.facing_x,t.facing_x,n),facing_y:Js(e.facing_y,t.facing_y,n),velocity_x:Js(e.velocity_x,t.velocity_x,n),velocity_y:Js(e.velocity_y,t.velocity_y,n),stamina:Js(e.stamina,t.stamina,n),maximum_stamina:Js(e.maximum_stamina,t.maximum_stamina,n),conditioning:Js(e.conditioning,t.conditioning,n),guard:Js(e.guard,t.guard,n),poise:Js(e.poise,t.poise,n)}),Xs=1.5,Zs=6,Qs=.5,$s=2500,ec=1,tc=.04,nc=100,rc=.01,ic=4,ac=class{maximum;tickRate;initialDelayTicks;snapshots=[];offsetTicks=null;delayTicks;lastStarvationMs=-1/0;lastFrameMs=null;behindPushes=0;needs=[];constructor(e=8,t=30,n=2){this.maximum=e,this.tickRate=t,this.initialDelayTicks=n,this.delayTicks=n}get interpolationDelayTicks(){return this.delayTicks}push(e,t){let n=this.snapshots.at(-1);if(n!==void 0&&e.tick<=n.tick)return!1;if(this.snapshots.push(e),this.snapshots.length>this.maximum&&this.snapshots.shift(),t!==void 0&&Number.isFinite(t)){let n=e.tick-t*this.tickRate/1e3;this.offsetTicks!==null&&n=ic&&this.restartClock(),this.offsetTicks===null?(this.offsetTicks=n,this.need(t,this.initialDelayTicks)):this.offsetTicks=Math.max(n,this.offsetTicks-rc),this.need(t,this.offsetTicks-n+ec)}return!0}resync(){this.restartClock()}restartClock(){this.offsetTicks=null,this.delayTicks=this.initialDelayTicks,this.lastStarvationMs=-1/0,this.behindPushes=0,this.needs.length=0}need(e,t){for(;this.needs.length>0&&this.needs.at(-1).ticks<=t;)this.needs.pop();this.needs.push({atMs:e,ticks:t})}recentNeed(e){for(;this.needs.length>0&&this.needs[0].atMs<=e-$s;)this.needs.shift();return this.needs[0]?.ticks??0}latest(){return this.snapshots.at(-1)??null}renderTick(e){let t=this.latest();if(t===null)return 0;let n=this.snapshots[0].tick;if(this.offsetTicks===null)return Math.max(n,t.tick-1);let r=this.lastFrameMs===null?0:Math.min(nc,Math.max(0,e-this.lastFrameMs));this.lastFrameMs=e;let i=e*this.tickRate/1e3+this.offsetTicks-this.delayTicks;if(i>t.tick+.25)e-this.lastStarvationMs>250&&(this.lastStarvationMs=e,this.delayTicks=Math.min(Zs,this.delayTicks+Qs),this.need(e,this.delayTicks));else{let t=Math.max(Xs,this.recentNeed(e));this.delayTicks>t&&(this.delayTicks=Math.max(t,this.delayTicks-tc*r*this.tickRate/1e3))}return Math.min(t.tick,Math.max(n,i))}sample(e){let t=this.snapshots.findIndex(t=>t.tick>=e);if(t<=0)return this.snapshots[Math.max(0,t)]??this.latest();let n=this.snapshots[t-1],r=this.snapshots[t];if(n.phase!==r.phase||n.fighters.some((e,t)=>e.knockdowns!==r.fighters[t]?.knockdowns))return r;let i=Math.max(0,Math.min(1,(e-n.tick)/Math.max(1,r.tick-n.tick)));return{...r,fighters:[Ys(n.fighters[0],r.fighters[0],i),Ys(n.fighters[1],r.fighters[1],i)]}}clear(){this.snapshots.length=0,this.offsetTicks=null}},oc=class{highest=-1;accept(e){let t=new Set,n=e.filter(e=>e.event_id<=this.highest||t.has(e.event_id)?!1:(t.add(e.event_id),!0)).sort((e,t)=>e.event_id-t.event_id);for(let e of n)this.highest=Math.max(this.highest,e.event_id);return n}reset(){this.highest=-1}};function sc(e=window.location){let t=new URL(`/api/hands/ws`,e.origin);if(e.protocol===`https:`)t.protocol=`wss:`;else if(e.protocol===`http:`&&[`localhost`,`127.0.0.1`,`::1`].includes(e.hostname))t.protocol=`ws:`;else throw Error(`insecure_websocket_origin`);return t.search=``,t.hash=``,t.toString()}var cc=1,lc={moveX:0,moveY:0,defense:`none`,actions:[]},uc=33,dc=8,fc=50,pc=20,mc=2048;function hc(e){try{return Se(e)}catch(t){let n;try{let t=A(e);n=typeof t==`object`&&t&&`version`in t?t.version:void 0}catch{}throw typeof n==`number`&&n!==3?new Ee(`client_outdated`,!0):t}}var gc=class{getInput;callbacks;makeSocket;now;socket=null;reconnectTicket;reconnectTimer=null;opponentPauseTimer=null;inputTimer=null;reconnectDeadline=0;opponentPauseDeadline=0;opponentPaused=!1;attempts=0;nextSequence=0;playerId=null;sentAt=new Map;actionSequences=new Map;latencyMs=null;serverTick=0;role=null;active=!1;boutStarted=!1;disposed=!1;terminal=!1;inputSuppressed=!1;pointerFocus=!1;listenersBound=!1;lastInputSentAt=-1/0;sendTimes=[];edgeSendTimes=[];constructor(e,t,n,r=e=>new WebSocket(e),i=()=>performance.now()){this.getInput=t,this.callbacks=n,this.makeSocket=r,this.now=i,this.reconnectTicket=e}start(){this.disposed||this.listenersBound||(this.listenersBound=!0,window.addEventListener(`blur`,this.onInputLoss),window.addEventListener(`focus`,this.onInputRegain),window.addEventListener(`pointerdown`,this.onPagePointer,!0),document.addEventListener(`visibilitychange`,this.onVisibilityChange),this.connect(),!this.disposed&&!this.terminal&&(this.inputTimer=window.setInterval(()=>this.flushInput(),uc)))}setActive(e){this.setInputActive(e)}setInputActive(e){let t=this.active;this.active=e,e?this.boutStarted=!0:t&&this.sendInput(lc,!0)}notifyAction(){this.now()-(this.edgeSendTimes.at(-1)??-1/0)=pc||this.flushInput()&&this.edgeSendTimes.push(this.lastInputSentAt)}sendsInLastSecond(){return this.withinLastSecond(this.sendTimes)}withinLastSecond(e){let t=this.now()-1e3;for(;e.length>0&&e[0]<=t;)e.shift();return e.length}onInputLoss=()=>{this.inputSuppressed||(this.sendInput(lc,this.boutStarted),this.inputSuppressed=!0,this.pointerFocus=!1)};onInputRegain=()=>{!document.hidden&&document.hasFocus()&&(this.inputSuppressed=!1)};onPagePointer=()=>{if(!document.hidden&&(this.pointerFocus=!0,this.inputSuppressed=!1,!document.hasFocus()))try{window.focus()}catch{}};onVisibilityChange=()=>{document.hidden?this.onInputLoss():this.onInputRegain()};connect(){if(this.disposed||this.terminal)return;let e=this.reconnectTicket;if(e===null){this.terminal=!0,this.stopInputLifecycle(),this.callbacks.onFreshAuth();return}let t;try{t=this.makeSocket(sc())}catch{this.terminal=!0,this.stopInputLifecycle(),this.callbacks.onFatal(`network_unavailable`);return}this.socket=t,t.binaryType=`arraybuffer`,t.onopen=()=>{if(!(this.socket!==t||this.disposed))try{t.send(JSON.stringify({version:3,type:`authenticate`,ticket:e})),this.reconnectTicket=null}catch{this.handleClose(t)}},t.onmessage=e=>this.handleMessage(t,e),t.onerror=()=>void 0,t.onclose=()=>this.handleClose(t)}handleMessage(e,t){if(!(this.socket!==e||this.disposed||this.terminal))try{if(typeof t.data!=`string`&&!(t.data instanceof ArrayBuffer))throw Error(`unsupported_frame`);let n=hc(t.data);if(this.applyMessage(n),n.type===`ticket`){try{e.send(JSON.stringify({version:3,type:`ticket_ack`,refresh_id:n.refresh_id}))}catch{this.handleClose(e)}return}this.callbacks.onMessage(n),n.type===`error`?this.terminate(n.code,e):n.type===`final`&&(this.terminal=!0,this.clearTransportReconnect(!0),this.clearOpponentPause(!0),this.stopInputLifecycle(),this.socket===e&&(this.socket=null),e.onopen=e.onmessage=e.onclose=e.onerror=null,e.close(1e3,`complete`))}catch(e){this.callbacks.onFatal(Me(e)),this.dispose()}}applyMessage(e){if(e.type===`welcome`){if(e.reconnect_ticket===void 0)throw Error(`missing_reconnect_ticket`);this.reconnectTicket=e.reconnect_ticket,this.serverTick=e.server_tick,this.role=e.role,this.playerId=e.role===`fighter`?e.player_id:null,this.sentAt.clear(),e.role===`fighter`?this.nextSequence=Math.max(this.nextSequence,e.next_sequence):this.stopInputLifecycle(),this.attempts=0,this.clearTransportReconnect(!0)}else e.type===`ticket`?this.reconnectTicket=e.reconnect_ticket:e.type===`snapshot`?(this.serverTick=Math.max(this.serverTick,e.payload.tick),this.setInputActive([`countdown`,`fight`,`knockdown`,`foul_recovery`].includes(e.payload.phase)),this.observeAcknowledgement(e.payload)):e.type===`paused`?(this.setInputActive(!1),this.startOpponentPause(e.grace_ms)):e.type===`resumed`?(this.setInputActive(!0),this.attempts=0,this.clearOpponentPause(!0)):e.type===`ready`?this.setInputActive(!0):e.type===`waiting`?this.setInputActive(!1):(e.type===`final`||e.type===`error`)&&(this.active=!1,this.clearOpponentPause(!0))}terminate(e,t){this.terminal=!0,this.active=!1,this.clearTransportReconnect(!0),this.clearOpponentPause(!0),this.stopInputLifecycle(),this.callbacks.onFatal(e),this.socket===t&&(this.socket=null,t.onopen=t.onmessage=t.onclose=t.onerror=null,t.close(1e3,`terminal`))}handleClose(e){if(this.socket!==e||(this.socket=null,this.active=!1,this.disposed||this.terminal))return;if(this.reconnectTicket===null){this.terminal=!0,this.stopInputLifecycle(),this.callbacks.onFreshAuth();return}this.clearOpponentPause(!1),this.reconnectDeadline===0&&(this.reconnectDeadline=this.now()+2e4);let t=Math.max(0,this.reconnectDeadline-this.now());if(this.callbacks.onReconnect(t),t<=0){this.terminal=!0,this.stopInputLifecycle(),this.callbacks.onFreshAuth();return}let n=Math.min(3e3,250*2**Math.min(this.attempts,4),t);this.attempts+=1,this.reconnectTimer=window.setTimeout(()=>{this.reconnectTimer=null,this.callbacks.onReconnect(Math.max(0,this.reconnectDeadline-this.now())),this.connect()},n)}get inputLatencyMs(){return this.latencyMs}sequenceOf(e){return this.actionSequences.get(e)??null}observeAcknowledgement(e){if(this.playerId===null)return;let t=e.fighters.find(e=>e.player_id===this.playerId);if(t===void 0||t.last_input_sequence<0)return;let n=this.sentAt.get(t.last_input_sequence);if(n!==void 0){let e=Math.max(0,this.now()-n);this.latencyMs=this.latencyMs===null?e:this.latencyMs*.8+e*.2}for(let e of this.sentAt.keys())e<=t.last_input_sequence&&this.sentAt.delete(e)}sendInput(e,t=!1){let n=this.socket;if(this.role!==`fighter`||!this.active&&!t||this.disposed||this.terminal||n?.readyState!==cc)return!1;try{let t=e.actions.slice(0,4);n.send(Ce(this.nextSequence,this.serverTick,{...e,actions:t})),this.sentAt.set(this.nextSequence,this.now()),this.sentAt.size>128&&this.sentAt.delete(this.sentAt.keys().next().value);for(let e of t)e.id!==void 0&&this.actionSequences.set(e.id,this.nextSequence);for(;this.actionSequences.size>64;)this.actionSequences.delete(this.actionSequences.keys().next().value);return this.nextSequence+=1,this.lastInputSentAt=this.now(),this.sendTimes.push(this.lastInputSentAt),!0}catch{return this.handleClose(n),!1}}flushInput(){return this.inputSuppressed||document.hidden||!(this.pointerFocus||document.hasFocus())||this.sendsInLastSecond()>=fc||(this.socket?.bufferedAmount??0)>mc?!1:this.sendInput(this.getInput())}startOpponentPause(e){this.clearOpponentPause(!1),this.opponentPaused=!0,this.opponentPauseDeadline=this.now()+e,this.callbacks.onReconnect(e),e>0&&this.scheduleOpponentPauseTick()}scheduleOpponentPauseTick(){let e=Math.max(0,this.opponentPauseDeadline-this.now());if(e<=0){this.opponentPauseDeadline=0,this.callbacks.onReconnect(0);return}this.opponentPauseTimer=window.setTimeout(()=>{this.opponentPauseTimer=null;let e=Math.max(0,this.opponentPauseDeadline-this.now());this.callbacks.onReconnect(e),e>0?this.scheduleOpponentPauseTick():this.opponentPauseDeadline=0},Math.min(250,e))}clearOpponentPause(e){let t=this.opponentPaused;this.opponentPaused=!1,this.opponentPauseDeadline=0,this.opponentPauseTimer!==null&&(clearTimeout(this.opponentPauseTimer),this.opponentPauseTimer=null),e&&t&&this.callbacks.onReconnect(0)}cancelReconnect(){this.reconnectTimer!==null&&(clearTimeout(this.reconnectTimer),this.reconnectTimer=null)}clearTransportReconnect(e){let t=this.reconnectDeadline!==0;this.reconnectDeadline=0,this.cancelReconnect(),e&&t&&this.callbacks.onReconnect(0)}stopInputLifecycle(){this.inputTimer!==null&&(clearInterval(this.inputTimer),this.inputTimer=null),this.listenersBound&&=(window.removeEventListener(`blur`,this.onInputLoss),window.removeEventListener(`focus`,this.onInputRegain),window.removeEventListener(`pointerdown`,this.onPagePointer,!0),document.removeEventListener(`visibilitychange`,this.onVisibilityChange),!1)}dispose(){if(this.disposed)return;this.disposed=!0,this.active=!1,this.reconnectTicket=null,this.clearTransportReconnect(!0),this.clearOpponentPause(!0),this.stopInputLifecycle();let 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s!==null&&e.gripSpace&&(i=t.getPose(e.gripSpace,n),i!==null&&(s.matrix.fromArray(i.transform.matrix),s.matrix.decompose(s.position,s.rotation,s.scale),s.matrixWorldNeedsUpdate=!0,i.linearVelocity?(s.hasLinearVelocity=!0,s.linearVelocity.copy(i.linearVelocity)):s.hasLinearVelocity=!1,i.angularVelocity?(s.hasAngularVelocity=!0,s.angularVelocity.copy(i.angularVelocity)):s.hasAngularVelocity=!1,s.eventsEnabled&&s.dispatchEvent({type:`gripUpdated`,data:e,target:this})));o!==null&&(r=t.getPose(e.targetRaySpace,n),r===null&&i!==null&&(r=i),r!==null&&(o.matrix.fromArray(r.transform.matrix),o.matrix.decompose(o.position,o.rotation,o.scale),o.matrixWorldNeedsUpdate=!0,r.linearVelocity?(o.hasLinearVelocity=!0,o.linearVelocity.copy(r.linearVelocity)):o.hasLinearVelocity=!1,r.angularVelocity?(o.hasAngularVelocity=!0,o.angularVelocity.copy(r.angularVelocity)):o.hasAngularVelocity=!1,this.dispatchEvent(Pd)))}return o!==null&&(o.visible=r!==null),s!==null&&(s.visible=i!==null),c!==null&&(c.visible=a!==null),this}_getHandJoint(e,t){if(e.joints[t.jointName]===void 0){let n=new Nd;n.matrixAutoUpdate=!1,n.visible=!1,e.joints[t.jointName]=n,e.add(n)}return e.joints[t.jointName]}},Id={aliceblue:15792383,antiquewhite:16444375,aqua:65535,aquamarine:8388564,azure:15794175,beige:16119260,bisque:16770244,black:0,blanchedalmond:16772045,blue:255,blueviolet:9055202,brown:10824234,burlywood:14596231,cadetblue:6266528,chartreuse:8388352,chocolate:13789470,coral:16744272,cornflowerblue:6591981,cornsilk:16775388,crimson:14423100,cyan:65535,darkblue:139,darkcyan:35723,darkgoldenrod:12092939,darkgray:11119017,darkgreen:25600,darkgrey:11119017,darkkhaki:12433259,darkmagenta:9109643,darkolivegreen:5597999,darkorange:16747520,darkorchid:10040012,darkred:9109504,darksalmon:15308410,darkseagreen:9419919,darkslateblue:4734347,darkslategray:3100495,darkslategrey:3100495,darkturquoise:52945,darkviolet:9699539,deeppink:16716947,deepskyblue:49151,dimgray:6908265,dimgrey:6908265,dodgerblue:2003199,firebrick:11674146,floralwhite:16775920,forestgreen:2263842,fuchsia:16711935,gainsboro:14474460,ghostwhite:16316671,gold:16766720,goldenrod:14329120,gray:8421504,green:32768,greenyellow:11403055,grey:8421504,honeydew:15794160,hotpink:16738740,indianred:13458524,indigo:4915330,ivory:16777200,khaki:15787660,lavender:15132410,lavenderblush:16773365,lawngreen:8190976,lemonchiffon:16775885,lightblue:11393254,lightcoral:15761536,lightcyan:14745599,lightgoldenrodyellow:16448210,lightgray:13882323,lightgreen:9498256,lightgrey:13882323,lightpink:16758465,lightsalmon:16752762,lightseagreen:2142890,lightskyblue:8900346,lightslategray:7833753,lightslategrey:7833753,lightsteelblue:11584734,lightyellow:16777184,lime:65280,limegreen:3329330,linen:16445670,magenta:16711935,maroon:8388608,mediumaquamarine:6737322,mediumblue:205,mediumorchid:12211667,mediumpurple:9662683,mediumseagreen:3978097,mediumslateblue:8087790,mediumspringgreen:64154,mediumturquoise:4772300,mediumvioletred:13047173,midnightblue:1644912,mintcream:16121850,mistyrose:16770273,moccasin:16770229,navajowhite:16768685,navy:128,oldlace:16643558,olive:8421376,olivedrab:7048739,orange:16753920,orangered:16729344,orchid:14315734,palegoldenrod:15657130,palegreen:10025880,paleturquoise:11529966,palevioletred:14381203,papayawhip:16773077,peachpuff:16767673,peru:13468991,pink:16761035,plum:14524637,powderblue:11591910,purple:8388736,rebeccapurple:6697881,red:16711680,rosybrown:12357519,royalblue:4286945,saddlebrown:9127187,salmon:16416882,sandybrown:16032864,seagreen:3050327,seashell:16774638,sienna:10506797,silver:12632256,skyblue:8900331,slateblue:6970061,slategray:7372944,slategrey:7372944,snow:16775930,springgreen:65407,steelblue:4620980,tan:13808780,teal:32896,thistle:14204888,tomato:16737095,turquoise:4251856,violet:15631086,wheat:16113331,white:16777215,whitesmoke:16119285,yellow:16776960,yellowgreen:10145074},Ld={h:0,s:0,l:0},Rd={h:0,s:0,l:0};function zd(e,t,n){return n<0&&(n+=1),n>1&&--n,n<1/6?e+(t-e)*6*n:n<1/2?t:n<2/3?e+(t-e)*6*(2/3-n):e}var Q=class{constructor(e,t,n){return this.isColor=!0,this.r=1,this.g=1,this.b=1,this.set(e,t,n)}set(e,t,n){if(t===void 0&&n===void 0){let t=e;t&&t.isColor?this.copy(t):typeof t==`number`?this.setHex(t):typeof t==`string`&&this.setStyle(t)}else this.setRGB(e,t,n);return this}setScalar(e){return this.r=e,this.g=e,this.b=e,this}setHex(e,t=Vl){return e=Math.floor(e),this.r=(e>>16&255)/255,this.g=(e>>8&255)/255,this.b=(e&255)/255,Uu.colorSpaceToWorking(this,t),this}setRGB(e,t,n,r=Uu.workingColorSpace){return this.r=e,this.g=t,this.b=n,Uu.colorSpaceToWorking(this,r),this}setHSL(e,t,n,r=Uu.workingColorSpace){if(e=mu(e,1),t=pu(t,0,1),n=pu(n,0,1),t===0)this.r=this.g=this.b=n;else{let r=n<=.5?n*(1+t):n+t-n*t,i=2*n-r;this.r=zd(i,r,e+1/3),this.g=zd(i,r,e),this.b=zd(i,r,e-1/3)}return Uu.colorSpaceToWorking(this,r),this}setStyle(e,t=Vl){function n(t){t!==void 0&&parseFloat(t)<1&&nu(`Color: Alpha component of 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0&&(n.roughness=this.roughness),this.metalness!==void 0&&(n.metalness=this.metalness),this.sheen!==void 0&&(n.sheen=this.sheen),this.sheenColor&&this.sheenColor.isColor&&(n.sheenColor=this.sheenColor.getHex()),this.sheenRoughness!==void 0&&(n.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(n.emissive=this.emissive.getHex()),this.emissiveIntensity!==void 0&&(n.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(n.specular=this.specular.getHex()),this.specularIntensity!==void 0&&(n.specularIntensity=this.specularIntensity),this.specularColor&&this.specularColor.isColor&&(n.specularColor=this.specularColor.getHex()),this.shininess!==void 0&&(n.shininess=this.shininess),this.clearcoat!==void 0&&(n.clearcoat=this.clearcoat),this.clearcoatRoughness!==void 0&&(n.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(n.clearcoatMap=this.clearcoatMap.toJSON(e).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(n.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(e).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(n.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(e).uuid,n.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.sheenColorMap&&this.sheenColorMap.isTexture&&(n.sheenColorMap=this.sheenColorMap.toJSON(e).uuid),this.sheenRoughnessMap&&this.sheenRoughnessMap.isTexture&&(n.sheenRoughnessMap=this.sheenRoughnessMap.toJSON(e).uuid),this.dispersion!==void 0&&(n.dispersion=this.dispersion),this.retroreflectivity!==void 0&&(n.retroreflectivity=this.retroreflectivity),this.iridescence!==void 0&&(n.iridescence=this.iridescence),this.iridescenceIOR!==void 0&&(n.iridescenceIOR=this.iridescenceIOR),this.iridescenceThicknessRange!==void 0&&(n.iridescenceThicknessRange=this.iridescenceThicknessRange),this.iridescenceMap&&this.iridescenceMap.isTexture&&(n.iridescenceMap=this.iridescenceMap.toJSON(e).uuid),this.iridescenceThicknessMap&&this.iridescenceThicknessMap.isTexture&&(n.iridescenceThicknessMap=this.iridescenceThicknessMap.toJSON(e).uuid),this.anisotropy!==void 0&&(n.anisotropy=this.anisotropy),this.anisotropyRotation!==void 0&&(n.anisotropyRotation=this.anisotropyRotation),this.anisotropyMap&&this.anisotropyMap.isTexture&&(n.anisotropyMap=this.anisotropyMap.toJSON(e).uuid),this.map&&this.map.isTexture&&(n.map=this.map.toJSON(e).uuid),this.matcap&&this.matcap.isTexture&&(n.matcap=this.matcap.toJSON(e).uuid),this.alphaMap&&this.alphaMap.isTexture&&(n.alphaMap=this.alphaMap.toJSON(e).uuid),this.lightMap&&this.lightMap.isTexture&&(n.lightMap=this.lightMap.toJSON(e).uuid,n.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(n.aoMap=this.aoMap.toJSON(e).uuid,n.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(n.bumpMap=this.bumpMap.toJSON(e).uuid,n.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(n.normalMap=this.normalMap.toJSON(e).uuid,n.normalMapType=this.normalMapType,n.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(n.displacementMap=this.displacementMap.toJSON(e).uuid,n.displacementScale=this.displacementScale,n.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(n.roughnessMap=this.roughnessMap.toJSON(e).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(n.metalnessMap=this.metalnessMap.toJSON(e).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(n.emissiveMap=this.emissiveMap.toJSON(e).uuid),this.specularMap&&this.specularMap.isTexture&&(n.specularMap=this.specularMap.toJSON(e).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(n.specularIntensityMap=this.specularIntensityMap.toJSON(e).uuid),this.specularColorMap&&this.specularColorMap.isTexture&&(n.specularColorMap=this.specularColorMap.toJSON(e).uuid),this.envMap&&this.envMap.isTexture&&(n.envMap=this.envMap.toJSON(e).uuid,this.combine!==void 0&&(n.combine=this.combine)),this.envMapRotation!==void 0&&(n.envMapRotation=this.envMapRotation.toArray()),this.envMapIntensity!==void 0&&(n.envMapIntensity=this.envMapIntensity),this.reflectivity!==void 0&&(n.reflectivity=this.reflectivity),this.refractionRatio!==void 0&&(n.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(n.gradientMap=this.gradientMap.toJSON(e).uuid),this.transmission!==void 0&&(n.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(n.transmissionMap=this.transmissionMap.toJSON(e).uuid),this.thickness!==void 0&&(n.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(n.thicknessMap=this.thicknessMap.toJSON(e).uuid),this.attenuationDistance!==void 0&&(n.attenuationDistance=this.attenuationDistance),this.attenuationColor!==void 0&&(n.attenuationColor=this.attenuationColor.getHex()),this.size!==void 0&&(n.size=this.size),this.sizeAttenuation!==void 0&&(n.sizeAttenuation=this.sizeAttenuation),Array.isArray(this.clippingPlanes)&&this.clippingPlanes.length>0&&(n.clippingPlanes=this.clippingPlanes.map(e=>e.toJSON())),this.rotation!==void 0&&(n.rotation=this.rotation),this.depthPacking!==void 0&&(n.depthPacking=this.depthPacking),this.linewidth!==void 0&&(n.linewidth=this.linewidth),this.linecap!==void 0&&(n.linecap=this.linecap),this.linejoin!==void 0&&(n.linejoin=this.linejoin),this.dashSize!==void 0&&(n.dashSize=this.dashSize),this.gapSize!==void 0&&(n.gapSize=this.gapSize),this.scale!==void 0&&(n.scale=this.scale),this.wireframe!==void 0&&(n.wireframe=this.wireframe),this.wireframeLinewidth!==void 0&&(n.wireframeLinewidth=this.wireframeLinewidth),this.wireframeLinecap!==void 0&&(n.wireframeLinecap=this.wireframeLinecap),this.wireframeLinejoin!==void 0&&(n.wireframeLinejoin=this.wireframeLinejoin),this.flatShading!==void 0&&(n.flatShading=this.flatShading),this.fog!==void 0&&(n.fog=this.fog),Object.keys(this.userData).length>0&&(n.userData=this.userData);function r(e){let t=[];for(let n in e){let r=e[n];delete r.metadata,t.push(r)}return t}if(t){let t=r(e.textures),i=r(e.images);t.length>0&&(n.textures=t),i.length>0&&(n.images=i)}return n}fromJSON(e,t){if(e.uuid!==void 0&&(this.uuid=e.uuid),e.name!==void 0&&(this.name=e.name),e.color!==void 0&&this.color!==void 0&&this.color.setHex(e.color),e.roughness!==void 0&&(this.roughness=e.roughness),e.metalness!==void 0&&(this.metalness=e.metalness),e.sheen!==void 0&&(this.sheen=e.sheen),e.sheenColor!==void 0&&(this.sheenColor=new Q().setHex(e.sheenColor)),e.sheenRoughness!==void 0&&(this.sheenRoughness=e.sheenRoughness),e.emissive!==void 0&&this.emissive!==void 0&&this.emissive.setHex(e.emissive),e.specular!==void 0&&this.specular!==void 0&&this.specular.setHex(e.specular),e.specularIntensity!==void 0&&(this.specularIntensity=e.specularIntensity),e.specularColor!==void 0&&this.specularColor!==void 0&&this.specularColor.setHex(e.specularColor),e.shininess!==void 0&&(this.shininess=e.shininess),e.clearcoat!==void 0&&(this.clearcoat=e.clearcoat),e.clearcoatRoughness!==void 0&&(this.clearcoatRoughness=e.clearcoatRoughness),e.dispersion!==void 0&&(this.dispersion=e.dispersion),e.retroreflectivity!==void 0&&(this.retroreflectivity=e.retroreflectivity),e.iridescence!==void 0&&(this.iridescence=e.iridescence),e.iridescenceIOR!==void 0&&(this.iridescenceIOR=e.iridescenceIOR),e.iridescenceThicknessRange!==void 0&&(this.iridescenceThicknessRange=e.iridescenceThicknessRange),e.transmission!==void 0&&(this.transmission=e.transmission),e.thickness!==void 0&&(this.thickness=e.thickness),e.attenuationDistance!==void 0&&(this.attenuationDistance=e.attenuationDistance),e.attenuationColor!==void 0&&this.attenuationColor!==void 0&&this.attenuationColor.setHex(e.attenuationColor),e.anisotropy!==void 0&&(this.anisotropy=e.anisotropy),e.anisotropyRotation!==void 0&&(this.anisotropyRotation=e.anisotropyRotation),e.fog!==void 0&&(this.fog=e.fog),e.flatShading!==void 0&&(this.flatShading=e.flatShading),e.blending!==void 0&&(this.blending=e.blending),e.combine!==void 0&&(this.combine=e.combine),e.side!==void 0&&(this.side=e.side),e.shadowSide!==void 0&&(this.shadowSide=e.shadowSide),e.opacity!==void 0&&(this.opacity=e.opacity),e.transparent!==void 0&&(this.transparent=e.transparent),e.alphaTest!==void 0&&(this.alphaTest=e.alphaTest),e.alphaHash!==void 0&&(this.alphaHash=e.alphaHash),e.depthFunc!==void 0&&(this.depthFunc=e.depthFunc),e.depthTest!==void 0&&(this.depthTest=e.depthTest),e.depthWrite!==void 0&&(this.depthWrite=e.depthWrite),e.colorWrite!==void 0&&(this.colorWrite=e.colorWrite),e.clippingPlanes!==void 0&&(this.clippingPlanes=e.clippingPlanes.map(e=>new Wf().fromJSON(e))),e.clipIntersection!==void 0&&(this.clipIntersection=e.clipIntersection),e.clipShadows!==void 0&&(this.clipShadows=e.clipShadows),e.depthPacking!==void 0&&(this.depthPacking=e.depthPacking),e.blendSrc!==void 0&&(this.blendSrc=e.blendSrc),e.blendDst!==void 0&&(this.blendDst=e.blendDst),e.blendEquation!==void 0&&(this.blendEquation=e.blendEquation),e.blendSrcAlpha!==void 0&&(this.blendSrcAlpha=e.blendSrcAlpha),e.blendDstAlpha!==void 0&&(this.blendDstAlpha=e.blendDstAlpha),e.blendEquationAlpha!==void 0&&(this.blendEquationAlpha=e.blendEquationAlpha),e.blendColor!==void 0&&this.blendColor!==void 0&&this.blendColor.setHex(e.blendColor),e.blendAlpha!==void 0&&(this.blendAlpha=e.blendAlpha),e.stencilWriteMask!==void 0&&(this.stencilWriteMask=e.stencilWriteMask),e.stencilFunc!==void 0&&(this.stencilFunc=e.stencilFunc),e.stencilRef!==void 0&&(this.stencilRef=e.stencilRef),e.stencilFuncMask!==void 0&&(this.stencilFuncMask=e.stencilFuncMask),e.stencilFail!==void 0&&(this.stencilFail=e.stencilFail),e.stencilZFail!==void 0&&(this.stencilZFail=e.stencilZFail),e.stencilZPass!==void 0&&(this.stencilZPass=e.stencilZPass),e.stencilWrite!==void 0&&(this.stencilWrite=e.stencilWrite),e.wireframe!==void 0&&(this.wireframe=e.wireframe),e.wireframeLinewidth!==void 0&&(this.wireframeLinewidth=e.wireframeLinewidth),e.wireframeLinecap!==void 0&&(this.wireframeLinecap=e.wireframeLinecap),e.wireframeLinejoin!==void 0&&(this.wireframeLinejoin=e.wireframeLinejoin),e.rotation!==void 0&&(this.rotation=e.rotation),e.linewidth!==void 0&&(this.linewidth=e.linewidth),e.linecap!==void 0&&(this.linecap=e.linecap),e.linejoin!==void 0&&(this.linejoin=e.linejoin),e.dashSize!==void 0&&(this.dashSize=e.dashSize),e.gapSize!==void 0&&(this.gapSize=e.gapSize),e.scale!==void 0&&(this.scale=e.scale),e.polygonOffset!==void 0&&(this.polygonOffset=e.polygonOffset),e.polygonOffsetFactor!==void 0&&(this.polygonOffsetFactor=e.polygonOffsetFactor),e.polygonOffsetUnits!==void 0&&(this.polygonOffsetUnits=e.polygonOffsetUnits),e.dithering!==void 0&&(this.dithering=e.dithering),e.alphaToCoverage!==void 0&&(this.alphaToCoverage=e.alphaToCoverage),e.premultipliedAlpha!==void 0&&(this.premultipliedAlpha=e.premultipliedAlpha),e.forceSinglePass!==void 0&&(this.forceSinglePass=e.forceSinglePass),e.allowOverride!==void 0&&(this.allowOverride=e.allowOverride),e.visible!==void 0&&(this.visible=e.visible),e.toneMapped!==void 0&&(this.toneMapped=e.toneMapped),e.userData!==void 0&&(this.userData=e.userData),e.vertexColors!==void 0&&(typeof e.vertexColors==`number`?this.vertexColors=e.vertexColors>0:this.vertexColors=e.vertexColors),e.size!==void 0&&(this.size=e.size),e.sizeAttenuation!==void 0&&(this.sizeAttenuation=e.sizeAttenuation),e.map!==void 0&&(this.map=t[e.map]||null),e.matcap!==void 0&&(this.matcap=t[e.matcap]||null),e.alphaMap!==void 0&&(this.alphaMap=t[e.alphaMap]||null),e.bumpMap!==void 0&&(this.bumpMap=t[e.bumpMap]||null),e.bumpScale!==void 0&&(this.bumpScale=e.bumpScale),e.normalMap!==void 0&&(this.normalMap=t[e.normalMap]||null),e.normalMapType!==void 0&&(this.normalMapType=e.normalMapType),e.normalScale!==void 0){let t=e.normalScale;Array.isArray(t)===!1&&(t=[t,t]),this.normalScale=new X().fromArray(t)}return e.displacementMap!==void 0&&(this.displacementMap=t[e.displacementMap]||null),e.displacementScale!==void 0&&(this.displacementScale=e.displacementScale),e.displacementBias!==void 0&&(this.displacementBias=e.displacementBias),e.roughnessMap!==void 0&&(this.roughnessMap=t[e.roughnessMap]||null),e.metalnessMap!==void 0&&(this.metalnessMap=t[e.metalnessMap]||null),e.emissiveMap!==void 0&&(this.emissiveMap=t[e.emissiveMap]||null),e.emissiveIntensity!==void 0&&(this.emissiveIntensity=e.emissiveIntensity),e.specularMap!==void 0&&(this.specularMap=t[e.specularMap]||null),e.specularIntensityMap!==void 0&&(this.specularIntensityMap=t[e.specularIntensityMap]||null),e.specularColorMap!==void 0&&(this.specularColorMap=t[e.specularColorMap]||null),e.envMap!==void 0&&(this.envMap=t[e.envMap]||null),e.envMapRotation!==void 0&&this.envMapRotation.fromArray(e.envMapRotation),e.envMapIntensity!==void 0&&(this.envMapIntensity=e.envMapIntensity),e.reflectivity!==void 0&&(this.reflectivity=e.reflectivity),e.refractionRatio!==void 0&&(this.refractionRatio=e.refractionRatio),e.lightMap!==void 0&&(this.lightMap=t[e.lightMap]||null),e.lightMapIntensity!==void 0&&(this.lightMapIntensity=e.lightMapIntensity),e.aoMap!==void 0&&(this.aoMap=t[e.aoMap]||null),e.aoMapIntensity!==void 0&&(this.aoMapIntensity=e.aoMapIntensity),e.gradientMap!==void 0&&(this.gradientMap=t[e.gradientMap]||null),e.clearcoatMap!==void 0&&(this.clearcoatMap=t[e.clearcoatMap]||null),e.clearcoatRoughnessMap!==void 0&&(this.clearcoatRoughnessMap=t[e.clearcoatRoughnessMap]||null),e.clearcoatNormalMap!==void 0&&(this.clearcoatNormalMap=t[e.clearcoatNormalMap]||null),e.clearcoatNormalScale!==void 0&&(this.clearcoatNormalScale=new X().fromArray(e.clearcoatNormalScale)),e.iridescenceMap!==void 0&&(this.iridescenceMap=t[e.iridescenceMap]||null),e.iridescenceThicknessMap!==void 0&&(this.iridescenceThicknessMap=t[e.iridescenceThicknessMap]||null),e.transmissionMap!==void 0&&(this.transmissionMap=t[e.transmissionMap]||null),e.thicknessMap!==void 0&&(this.thicknessMap=t[e.thicknessMap]||null),e.anisotropyMap!==void 0&&(this.anisotropyMap=t[e.anisotropyMap]||null),e.sheenColorMap!==void 0&&(this.sheenColorMap=t[e.sheenColorMap]||null),e.sheenRoughnessMap!==void 0&&(this.sheenRoughnessMap=t[e.sheenRoughnessMap]||null),this}clone(){return new this.constructor().copy(this)}copy(e){this.name=e.name,this.blending=e.blending,this.side=e.side,this.vertexColors=e.vertexColors,this.opacity=e.opacity,this.transparent=e.transparent,this.blendSrc=e.blendSrc,this.blendDst=e.blendDst,this.blendEquation=e.blendEquation,this.blendSrcAlpha=e.blendSrcAlpha,this.blendDstAlpha=e.blendDstAlpha,this.blendEquationAlpha=e.blendEquationAlpha,this.blendColor.copy(e.blendColor),this.blendAlpha=e.blendAlpha,this.depthFunc=e.depthFunc,this.depthTest=e.depthTest,this.depthWrite=e.depthWrite,this.stencilWriteMask=e.stencilWriteMask,this.stencilFunc=e.stencilFunc,this.stencilRef=e.stencilRef,this.stencilFuncMask=e.stencilFuncMask,this.stencilFail=e.stencilFail,this.stencilZFail=e.stencilZFail,this.stencilZPass=e.stencilZPass,this.stencilWrite=e.stencilWrite;let t=e.clippingPlanes,n=null;if(t!==null){let e=t.length;n=Array(e);for(let r=0;r!==e;++r)n[r]=t[r].clone()}return this.clippingPlanes=n,this.clipIntersection=e.clipIntersection,this.clipShadows=e.clipShadows,this.shadowSide=e.shadowSide,this.colorWrite=e.colorWrite,this.precision=e.precision,this.polygonOffset=e.polygonOffset,this.polygonOffsetFactor=e.polygonOffsetFactor,this.polygonOffsetUnits=e.polygonOffsetUnits,this.dithering=e.dithering,this.alphaTest=e.alphaTest,this.alphaHash=e.alphaHash,this.alphaToCoverage=e.alphaToCoverage,this.premultipliedAlpha=e.premultipliedAlpha,this.forceSinglePass=e.forceSinglePass,this.allowOverride=e.allowOverride,this.visible=e.visible,this.toneMapped=e.toneMapped,this.userData=JSON.parse(JSON.stringify(e.userData)),this}dispose(){this.dispatchEvent({type:`dispose`})}set needsUpdate(e){e===!0&&this.version++}},qf=new Z,Jf=new Z,Yf=new Z,Xf=new Z,Zf=class{constructor(e=new Z,t=new Z(0,0,-1)){this.origin=e,this.direction=t}set(e,t){return this.origin.copy(e),this.direction.copy(t),this}copy(e){return this.origin.copy(e.origin),this.direction.copy(e.direction),this}at(e,t){return t.copy(this.origin).addScaledVector(this.direction,e)}lookAt(e){return this.direction.copy(e).sub(this.origin).normalize(),this}recast(e){return this.origin.copy(this.at(e,qf)),this}closestPointToPoint(e,t){t.subVectors(e,this.origin);let n=t.dot(this.direction);return n<0?t.copy(this.origin):t.copy(this.origin).addScaledVector(this.direction,n)}distanceToPoint(e){return Math.sqrt(this.distanceSqToPoint(e))}distanceSqToPoint(e){let t=qf.subVectors(e,this.origin).dot(this.direction);return t<0?this.origin.distanceToSquared(e):(qf.copy(this.origin).addScaledVector(this.direction,t),qf.distanceToSquared(e))}distanceSqToSegment(e,t,n,r){Jf.copy(e).add(t).multiplyScalar(.5),Yf.copy(t).sub(e).normalize(),Xf.copy(this.origin).sub(Jf);let i=e.distanceTo(t)*.5,a=-this.direction.dot(Yf),o=Xf.dot(this.direction),s=-Xf.dot(Yf),c=Xf.lengthSq(),l=Math.abs(1-a*a),u,d,f,p;if(l>0)if(u=a*s-o,d=a*o-s,p=i*l,u>=0)if(d>=-p)if(d<=p){let e=1/l;u*=e,d*=e,f=u*(u+a*d+2*o)+d*(a*u+d+2*s)+c}else d=i,u=Math.max(0,-(a*d+o)),f=-u*u+d*(d+2*s)+c;else d=-i,u=Math.max(0,-(a*d+o)),f=-u*u+d*(d+2*s)+c;else d<=-p?(u=Math.max(0,-(-a*i+o)),d=u>0?-i:Math.min(Math.max(-i,-s),i),f=-u*u+d*(d+2*s)+c):d<=p?(u=0,d=Math.min(Math.max(-i,-s),i),f=d*(d+2*s)+c):(u=Math.max(0,-(a*i+o)),d=u>0?i:Math.min(Math.max(-i,-s),i),f=-u*u+d*(d+2*s)+c);else d=a>0?-i:i,u=Math.max(0,-(a*d+o)),f=-u*u+d*(d+2*s)+c;return n&&n.copy(this.origin).addScaledVector(this.direction,u),r&&r.copy(Jf).addScaledVector(Yf,d),f}intersectSphere(e,t){if(e.radius<0)return null;qf.subVectors(e.center,this.origin);let n=qf.dot(this.direction),r=qf.dot(qf)-n*n,i=e.radius*e.radius;if(r>i)return null;let a=Math.sqrt(i-r),o=n-a,s=n+a;return s<0?null:o<0?this.at(s,t):this.at(o,t)}intersectsSphere(e){return e.radius<0?!1:this.distanceSqToPoint(e.center)<=e.radius*e.radius}distanceToPlane(e){let t=e.normal.dot(this.direction);if(t===0)return e.distanceToPoint(this.origin)===0?0:null;let n=-(this.origin.dot(e.normal)+e.constant)/t;return n>=0?n:null}intersectPlane(e,t){let n=this.distanceToPlane(e);return n===null?null:this.at(n,t)}intersectsPlane(e){let t=e.distanceToPoint(this.origin);return t===0||e.normal.dot(this.direction)*t<0}intersectBox(e,t){let n,r,i,a,o,s,c=1/this.direction.x,l=1/this.direction.y,u=1/this.direction.z,d=this.origin;return c>=0?(n=(e.min.x-d.x)*c,r=(e.max.x-d.x)*c):(n=(e.max.x-d.x)*c,r=(e.min.x-d.x)*c),l>=0?(i=(e.min.y-d.y)*l,a=(e.max.y-d.y)*l):(i=(e.max.y-d.y)*l,a=(e.min.y-d.y)*l),n>a||i>r||((i>n||isNaN(n))&&(n=i),(a=0?(o=(e.min.z-d.z)*u,s=(e.max.z-d.z)*u):(o=(e.max.z-d.z)*u,s=(e.min.z-d.z)*u),n>s||o>r)||((o>n||n!==n)&&(n=o),(s=0?n:r,t)}intersectsBox(e){return this.intersectBox(e,qf)!==null}intersectTriangle(e,t,n,r,i){let 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ym{constructor(e=[],t=!1,n=`centripetal`,r=.5){super(),this.isCatmullRomCurve3=!0,this.type=`CatmullRomCurve3`,this.points=e,this.closed=t,this.curveType=n,this.tension=r}getPoint(e,t=new Z){let n=t,r=this.points,i=r.length,a=(i-+!this.closed)*e,o=Math.floor(a),s=a-o;this.closed?o+=o>0?0:(Math.floor(Math.abs(o)/i)+1)*i:s===0&&o===i-1&&(o=i-2,s=1);let c,l;this.closed||o>0?c=r[(o-1)%i]:(wm.subVectors(r[0],r[1]).add(r[0]),c=wm);let u=r[o%i],d=r[(o+1)%i];if(this.closed||o+2r.length-2?r.length-1:a+1],u=r[a>r.length-3?r.length-1:a+2];return n.set(km(o,s.x,c.x,l.x,u.x),km(o,s.y,c.y,l.y,u.y)),n}copy(e){super.copy(e),this.points=[];for(let t=0,n=e.points.length;t0)&&f.push(t,i,c),(e!==n-1||s0&&(t.defines=this.defines),t.vertexShader=this.vertexShader,t.fragmentShader=this.fragmentShader,t.lights=this.lights,t.clipping=this.clipping;let n={};for(let e in this.extensions)this.extensions[e]===!0&&(n[e]=!0);return Object.keys(n).length>0&&(t.extensions=n),t}fromJSON(e,t){if(super.fromJSON(e,t),e.uniforms!==void 0)for(let n in e.uniforms){let r=e.uniforms[n];switch(this.uniforms[n]={},r.type){case`t`:this.uniforms[n].value=t[r.value]||null;break;case`c`:this.uniforms[n].value=new Z().setHex(r.value);break;case`v2`:this.uniforms[n].value=new Y().fromArray(r.value);break;case`v3`:this.uniforms[n].value=new X().fromArray(r.value);break;case`v4`:this.uniforms[n].value=new gu().fromArray(r.value);break;case`m3`:this.uniforms[n].value=new eu().fromArray(r.value);break;case`m4`:this.uniforms[n].value=new xu().fromArray(r.value);break;default:this.uniforms[n].value=r.value}}if(e.defines!==void 0&&(this.defines=e.defines),e.vertexShader!==void 0&&(this.vertexShader=e.vertexShader),e.fragmentShader!==void 0&&(this.fragmentShader=e.fragmentShader),e.glslVersion!==void 0&&(this.glslVersion=e.glslVersion),e.extensions!==void 0)for(let t in e.extensions)this.extensions[t]=e.extensions[t];return e.lights!==void 0&&(this.lights=e.lights),e.clipping!==void 0&&(this.clipping=e.clipping),this}},Tm=class extends wm{constructor(e){super(e),this.isRawShaderMaterial=!0,this.type=`RawShaderMaterial`}},Em=class extends rf{constructor(e){super(),this.isMeshStandardMaterial=!0,this.type=`MeshStandardMaterial`,this.defines={STANDARD:``},this.color=new Z(16777215),this.roughness=1,this.metalness=0,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new Z(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new Y(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.roughnessMap=null,this.metalnessMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new ju,this.envMapIntensity=1,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=`round`,this.wireframeLinejoin=`round`,this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.defines={STANDARD:``},this.color.copy(e.color),this.roughness=e.roughness,this.metalness=e.metalness,this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.roughnessMap=e.roughnessMap,this.metalnessMap=e.metalnessMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.envMapIntensity=e.envMapIntensity,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}},Dm=class extends Em{constructor(e){super(),this.isMeshPhysicalMaterial=!0,this.defines={STANDARD:``,PHYSICAL:``},this.type=`MeshPhysicalMaterial`,this.anisotropyRotation=0,this.anisotropyMap=null,this.clearcoatMap=null,this.clearcoatRoughness=0,this.clearcoatRoughnessMap=null,this.clearcoatNormalScale=new Y(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,"reflectivity",{get:function(){return kl(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(e){this.ior=(1+.4*e)/(1-.4*e)}}),this.iridescenceMap=null,this.iridescenceIOR=1.3,this.iridescenceThicknessRange=[100,400],this.iridescenceThicknessMap=null,this.sheenColor=new Z(0),this.sheenColorMap=null,this.sheenRoughness=1,this.sheenRoughnessMap=null,this.transmissionMap=null,this.thickness=0,this.thicknessMap=null,this.attenuationDistance=1/0,this.attenuationColor=new Z(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularColor=new Z(1,1,1),this.specularColorMap=null,this._anisotropy=0,this._clearcoat=0,this._dispersion=0,this._iridescence=0,this._sheen=0,this._transmission=0,this.setValues(e)}get anisotropy(){return this._anisotropy}set anisotropy(e){this._anisotropy>0!=e>0&&this.version++,this._anisotropy=e}get clearcoat(){return this._clearcoat}set clearcoat(e){this._clearcoat>0!=e>0&&this.version++,this._clearcoat=e}get iridescence(){return this._iridescence}set iridescence(e){this._iridescence>0!=e>0&&this.version++,this._iridescence=e}get dispersion(){return this._dispersion}set dispersion(e){this._dispersion>0!=e>0&&this.version++,this._dispersion=e}get sheen(){return this._sheen}set sheen(e){this._sheen>0!=e>0&&this.version++,this._sheen=e}get transmission(){return this._transmission}set transmission(e){this._transmission>0!=e>0&&this.version++,this._transmission=e}copy(e){return super.copy(e),this.defines={STANDARD:``,PHYSICAL:``},this.anisotropy=e.anisotropy,this.anisotropyRotation=e.anisotropyRotation,this.anisotropyMap=e.anisotropyMap,this.clearcoat=e.clearcoat,this.clearcoatMap=e.clearcoatMap,this.clearcoatRoughness=e.clearcoatRoughness,this.clearcoatRoughnessMap=e.clearcoatRoughnessMap,this.clearcoatNormalMap=e.clearcoatNormalMap,this.clearcoatNormalScale.copy(e.clearcoatNormalScale),this.dispersion=e.dispersion,this.ior=e.ior,this.iridescence=e.iridescence,this.iridescenceMap=e.iridescenceMap,this.iridescenceIOR=e.iridescenceIOR,this.iridescenceThicknessRange=[...e.iridescenceThicknessRange],this.iridescenceThicknessMap=e.iridescenceThicknessMap,this.sheen=e.sheen,this.sheenColor.copy(e.sheenColor),this.sheenColorMap=e.sheenColorMap,this.sheenRoughness=e.sheenRoughness,this.sheenRoughnessMap=e.sheenRoughnessMap,this.transmission=e.transmission,this.transmissionMap=e.transmissionMap,this.thickness=e.thickness,this.thicknessMap=e.thicknessMap,this.attenuationDistance=e.attenuationDistance,this.attenuationColor.copy(e.attenuationColor),this.specularIntensity=e.specularIntensity,this.specularIntensityMap=e.specularIntensityMap,this.specularColor.copy(e.specularColor),this.specularColorMap=e.specularColorMap,this}},Om=class extends rf{constructor(e){super(),this.isMeshDepthMaterial=!0,this.type=`MeshDepthMaterial`,this.depthPacking=rl,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.setValues(e)}copy(e){return super.copy(e),this.depthPacking=e.depthPacking,this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this}},km=class extends rf{constructor(e){super(),this.isMeshDistanceMaterial=!0,this.type=`MeshDistanceMaterial`,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.setValues(e)}copy(e){return super.copy(e),this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this}};function Am(e,t){return!e||e.constructor===t?e:typeof t.BYTES_PER_ELEMENT==`number`?new t(e):Array.prototype.slice.call(e)}function jm(e){function t(t,n){return e[t]-e[n]}let n=e.length,r=Array(n);for(let e=0;e!==n;++e)r[e]=e;return r.sort(t),r}function Mm(e,t,n){let r=e.length,i=new e.constructor(r);for(let a=0,o=0;o!==r;++a){let r=n[a]*t;for(let n=0;n!==t;++n)i[o++]=e[r+n]}return i}function Nm(e,t,n,r){let i=1,a=e[0];for(;a!==void 0&&a[r]===void 0;)a=e[i++];if(a===void 0)return;let o=a[r];if(o!==void 0)if(Array.isArray(o))do o=a[r],o!==void 0&&(t.push(a.time),n.push(...o)),a=e[i++];while(a!==void 0);else if(o.toArray!==void 0)do o=a[r],o!==void 0&&(t.push(a.time),o.toArray(n,n.length)),a=e[i++];while(a!==void 0);else do o=a[r],o!==void 0&&(t.push(a.time),n.push(o)),a=e[i++];while(a!==void 0)}var 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t)this.add(e),e.updateMatrixWorld()}update(e,t){this.parent===null&&this.updateMatrixWorld();let{renderTarget:n,activeMipmapLevel:r}=this;this.coordinateSystem!==e.coordinateSystem&&(this.coordinateSystem=e.coordinateSystem,this.updateCoordinateSystem());let[i,a,o,s,c,l]=this.children,u=e.getRenderTarget(),d=e.getActiveCubeFace(),f=e.getActiveMipmapLevel(),p=e.xr.enabled;e.xr.enabled=!1;let m=n.texture.generateMipmaps;n.texture.generateMipmaps=!1;let h=!1;h=e.isWebGLRenderer===!0?e.state.buffers.depth.getReversed():e.reversedDepthBuffer,e.setRenderTarget(n,0,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,i),e.setRenderTarget(n,1,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,a),e.setRenderTarget(n,2,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,o),e.setRenderTarget(n,3,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,s),e.setRenderTarget(n,4,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,c),n.texture.generateMipmaps=m,e.setRenderTarget(n,5,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,l),e.setRenderTarget(u,d,f),e.xr.enabled=p,n.texture.needsPMREMUpdate=!0}},Ph=class extends yh{constructor(e=[]){super(),this.isArrayCamera=!0,this.isMultiViewCamera=!1,this.cameras=e}},Fh=class{constructor(){this._previousTime=0,this._currentTime=0,this._startTime=performance.now(),this._delta=0,this._elapsed=0,this._timescale=1,this._document=null,this._pageVisibilityHandler=null}connect(e){this._document=e,e.hidden!==void 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t=this.buffer,n=this.valueSize,r=n*this._addIndex;this.cumulativeWeightAdditive===0&&this._setIdentity(),this._mixBufferRegionAdditive(t,r,0,e,n),this.cumulativeWeightAdditive+=e}apply(e){let t=this.valueSize,n=this.buffer,r=e*t+t,i=this.cumulativeWeight,a=this.cumulativeWeightAdditive,o=this.binding;if(this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,i<1){let e=t*this._origIndex;this._mixBufferRegion(n,r,e,1-i,t)}a>0&&this._mixBufferRegionAdditive(n,r,this._addIndex*t,1,t);for(let e=t,i=t+t;e!==i;++e)if(n[e]!==n[e+t]){o.setValue(n,r);break}}saveOriginalState(){let e=this.binding,t=this.buffer,n=this.valueSize,r=n*this._origIndex;e.getValue(t,r);for(let e=n,i=r;e!==i;++e)t[e]=t[r+e%n];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){let e=this.valueSize*3;this.binding.setValue(this.buffer,e)}_setAdditiveIdentityNumeric(){let e=this._addIndex*this.valueSize,t=e+this.valueSize;for(let n=e;n=.5)for(let 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Cl{constructor(e){super(),this._root=e,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1,typeof __THREE_DEVTOOLS__<`u`&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent(`observe`,{detail:this}))}_bindAction(e,t){let n=e._localRoot||this._root,r=e._clip.tracks,i=r.length,a=e._propertyBindings,o=e._interpolants,s=n.uuid,c=this._bindingsByRootAndName,l=c[s];l===void 0&&(l={},c[s]=l);for(let e=0;e!==i;++e){let i=r[e],c=i.name,u=l[c];if(u!==void 0)++u.referenceCount,a[e]=u;else{if(u=a[e],u!==void 0){u._cacheIndex===null&&(++u.referenceCount,this._addInactiveBinding(u,s,c));continue}let r=t&&t._propertyBindings[e].binding.parsedPath;u=new Lh(Yh.create(n,c,r),i.ValueTypeName,i.getValueSize()),++u.referenceCount,this._addInactiveBinding(u,s,c),a[e]=u}o[e].resultBuffer=u.buffer}}_activateAction(e){if(!this._isActiveAction(e)){if(e._cacheIndex===null){let t=(e._localRoot||this._root).uuid,n=e._clip.uuid,r=this._actionsByClip[n];this._bindAction(e,r&&r.knownActions[0]),this._addInactiveAction(e,n,t)}let t=e._propertyBindings;for(let e=0,n=t.length;e!==n;++e){let n=t[e];n.useCount++===0&&(this._lendBinding(n),n.saveOriginalState())}this._lendAction(e)}}_deactivateAction(e){if(this._isActiveAction(e)){let t=e._propertyBindings;for(let e=0,n=t.length;e!==n;++e){let n=t[e];--n.useCount===0&&(n.restoreOriginalState(),this._takeBackBinding(n))}this._takeBackAction(e)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;let e=this;this.stats={actions:{get total(){return e._actions.length},get inUse(){return e._nActiveActions}},bindings:{get total(){return e._bindings.length},get inUse(){return e._nActiveBindings}},controlInterpolants:{get total(){return 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Kf{constructor(e){super(),this.isMeshStandardMaterial=!0,this.type=`MeshStandardMaterial`,this.defines={STANDARD:``},this.color=new Q(16777215),this.roughness=1,this.metalness=0,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new Q(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=0,this.normalScale=new X(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.roughnessMap=null,this.metalnessMap=null,this.alphaMap=null,this.envMap=null,this.envMapRotation=new hd,this.envMapIntensity=1,this.wireframe=!1,this.wireframeLinewidth=1,this.wireframeLinecap=`round`,this.wireframeLinejoin=`round`,this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.defines={STANDARD:``},this.color.copy(e.color),this.roughness=e.roughness,this.metalness=e.metalness,this.map=e.map,this.lightMap=e.lightMap,this.lightMapIntensity=e.lightMapIntensity,this.aoMap=e.aoMap,this.aoMapIntensity=e.aoMapIntensity,this.emissive.copy(e.emissive),this.emissiveMap=e.emissiveMap,this.emissiveIntensity=e.emissiveIntensity,this.bumpMap=e.bumpMap,this.bumpScale=e.bumpScale,this.normalMap=e.normalMap,this.normalMapType=e.normalMapType,this.normalScale.copy(e.normalScale),this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.roughnessMap=e.roughnessMap,this.metalnessMap=e.metalnessMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,this.envMapRotation.copy(e.envMapRotation),this.envMapIntensity=e.envMapIntensity,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.flatShading=e.flatShading,this.fog=e.fog,this}},ch=class extends sh{constructor(e){super(),this.isMeshPhysicalMaterial=!0,this.defines={STANDARD:``,PHYSICAL:``},this.type=`MeshPhysicalMaterial`,this.anisotropyRotation=0,this.anisotropyMap=null,this.clearcoatMap=null,this.clearcoatRoughness=0,this.clearcoatRoughnessMap=null,this.clearcoatNormalScale=new X(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,"reflectivity",{get:function(){return pu(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(e){this.ior=(1+.4*e)/(1-.4*e)}}),this.iridescenceMap=null,this.iridescenceIOR=1.3,this.iridescenceThicknessRange=[100,400],this.iridescenceThicknessMap=null,this.sheenColor=new Q(0),this.sheenColorMap=null,this.sheenRoughness=1,this.sheenRoughnessMap=null,this.transmissionMap=null,this.thickness=0,this.thicknessMap=null,this.attenuationDistance=1/0,this.attenuationColor=new Q(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularColor=new Q(1,1,1),this.specularColorMap=null,this._anisotropy=0,this._clearcoat=0,this._dispersion=0,this._iridescence=0,this._retroreflectivity=0,this._sheen=0,this._transmission=0,this.setValues(e)}get anisotropy(){return this._anisotropy}set anisotropy(e){this._anisotropy>0!=e>0&&this.version++,this._anisotropy=e}get clearcoat(){return this._clearcoat}set clearcoat(e){this._clearcoat>0!=e>0&&this.version++,this._clearcoat=e}get iridescence(){return this._iridescence}set iridescence(e){this._iridescence>0!=e>0&&this.version++,this._iridescence=e}get dispersion(){return this._dispersion}set dispersion(e){this._dispersion>0!=e>0&&this.version++,this._dispersion=e}get retroreflectivity(){return this._retroreflectivity}set retroreflectivity(e){this._retroreflectivity>0!=e>0&&this.version++,this._retroreflectivity=e}get sheen(){return this._sheen}set sheen(e){this._sheen>0!=e>0&&this.version++,this._sheen=e}get transmission(){return this._transmission}set transmission(e){this._transmission>0!=e>0&&this.version++,this._transmission=e}copy(e){return super.copy(e),this.defines={STANDARD:``,PHYSICAL:``},this.anisotropy=e.anisotropy,this.anisotropyRotation=e.anisotropyRotation,this.anisotropyMap=e.anisotropyMap,this.clearcoat=e.clearcoat,this.clearcoatMap=e.clearcoatMap,this.clearcoatRoughness=e.clearcoatRoughness,this.clearcoatRoughnessMap=e.clearcoatRoughnessMap,this.clearcoatNormalMap=e.clearcoatNormalMap,this.clearcoatNormalScale.copy(e.clearcoatNormalScale),this.dispersion=e.dispersion,this.ior=e.ior,this.iridescence=e.iridescence,this.iridescenceMap=e.iridescenceMap,this.iridescenceIOR=e.iridescenceIOR,this.iridescenceThicknessRange=[...e.iridescenceThicknessRange],this.iridescenceThicknessMap=e.iridescenceThicknessMap,this.retroreflectivity=e.retroreflectivity,this.sheen=e.sheen,this.sheenColor.copy(e.sheenColor),this.sheenColorMap=e.sheenColorMap,this.sheenRoughness=e.sheenRoughness,this.sheenRoughnessMap=e.sheenRoughnessMap,this.transmission=e.transmission,this.transmissionMap=e.transmissionMap,this.thickness=e.thickness,this.thicknessMap=e.thicknessMap,this.attenuationDistance=e.attenuationDistance,this.attenuationColor.copy(e.attenuationColor),this.specularIntensity=e.specularIntensity,this.specularIntensityMap=e.specularIntensityMap,this.specularColor.copy(e.specularColor),this.specularColorMap=e.specularColorMap,this}},lh=class extends Kf{constructor(e){super(),this.isMeshDepthMaterial=!0,this.type=`MeshDepthMaterial`,this.depthPacking=Bl,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.setValues(e)}copy(e){return super.copy(e),this.depthPacking=e.depthPacking,this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this}},uh=class extends Kf{constructor(e){super(),this.isMeshDistanceMaterial=!0,this.type=`MeshDistanceMaterial`,this.map=null,this.alphaMap=null,this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.setValues(e)}copy(e){return super.copy(e),this.map=e.map,this.alphaMap=e.alphaMap,this.displacementMap=e.displacementMap,this.displacementScale=e.displacementScale,this.displacementBias=e.displacementBias,this}};function dh(e,t){return!e||e.constructor===t?e:typeof t.BYTES_PER_ELEMENT==`number`?new t(e):Array.prototype.slice.call(e)}function fh(e){return e!==void 0&&e.inTangents!==void 0&&e.outTangents!==void 0}function ph(e){function t(t,n){return e[t]-e[n]}let n=e.length,r=Array(n);for(let e=0;e!==n;++e)r[e]=e;return r.sort(t),r}function mh(e,t,n){let r=e.length,i=new e.constructor(r);for(let a=0,o=0;o!==r;++a){let r=n[a]*t;for(let n=0;n!==t;++n)i[o++]=e[r+n]}return i}function hh(e,t,n,r){let i=1,a=e[0];for(;a!==void 0&&a[r]===void 0;)a=e[i++];if(a===void 0)return;let o=a[r];if(o!==void 0)if(Array.isArray(o))do o=a[r],o!==void 0&&(t.push(a.time),n.push(...o)),a=e[i++];while(a!==void 0);else if(o.toArray!==void 0)do o=a[r],o!==void 0&&(t.push(a.time),o.toArray(n,n.length)),a=e[i++];while(a!==void 0);else do o=a[r],o!==void 0&&(t.push(a.time),n.push(o)),a=e[i++];while(a!==void 0)}var gh=class{constructor(e,t,n,r){this.parameterPositions=e,this._cachedIndex=0,this.resultBuffer=r===void 0?new t.constructor(n):r,this.sampleValues=t,this.valueSize=n,this.settings=null,this.DefaultSettings_={}}evaluate(e){let t=this.parameterPositions,n=this._cachedIndex,r=t[n],i=t[n-1];validate_interval:{seek:{let a;linear_scan:{forward_scan:if(!(e=i)){let o=t[1];e=i)break seek}a=n,n=0;break linear_scan}break validate_interval}for(;n>>1;et;)--a;if(++a,i!==0||a!==r){i>=a&&(a=Math.max(a,1),i=a-1);let e=this.getValueSize();this.times=n.slice(i,a),this.values=this.values.slice(i*e,a*e)}return this}validate(){let e=!0,t=this.getValueSize();t-Math.floor(t)!==0&&(ru(`KeyframeTrack: Invalid value size in track.`,this),e=!1);let n=this.times,r=this.values,i=n.length;i===0&&(ru(`KeyframeTrack: Track is empty.`,this),e=!1);let a=null;for(let t=0;t!==i;t++){let r=n[t];if(typeof r==`number`&&isNaN(r)){ru(`KeyframeTrack: 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n=0,r=e.length;n!==r;n+=2)e[n]*=t}wh.prototype.ValueTypeName=``,wh.prototype.TimeBufferType=Float32Array,wh.prototype.ValueBufferType=Float32Array,wh.prototype.DefaultInterpolation=Nl;var Eh=class extends wh{constructor(e,t,n){super(e,t,n)}};Eh.prototype.ValueTypeName=`bool`,Eh.prototype.ValueBufferType=Array,Eh.prototype.DefaultInterpolation=Ml,Eh.prototype.InterpolantFactoryMethodLinear=void 0,Eh.prototype.InterpolantFactoryMethodSmooth=void 0;var Dh=class extends wh{constructor(e,t,n,r){super(e,t,n,r)}};Dh.prototype.ValueTypeName=`color`;var Oh=class extends wh{constructor(e,t,n,r){super(e,t,n,r)}};Oh.prototype.ValueTypeName=`number`;var kh=class extends gh{constructor(e,t,n,r){super(e,t,n,r)}interpolate_(e,t,n,r){let i=this.resultBuffer,a=this.sampleValues,o=this.valueSize,s=(n-t)/(r-t),c=e*o;for(let e=c+o;c!==e;c+=4)Fu.slerpFlat(i,0,a,c-o,a,c,s);return i}},Ah=class extends wh{constructor(e,t,n,r){super(e,t,n,r)}InterpolantFactoryMethodLinear(e){return new kh(this.times,this.values,this.getValueSize(),e)}};Ah.prototype.ValueTypeName=`quaternion`,Ah.prototype.InterpolantFactoryMethodSmooth=void 0;var jh=class extends wh{constructor(e,t,n){super(e,t,n)}};jh.prototype.ValueTypeName=`string`,jh.prototype.ValueBufferType=Array,jh.prototype.DefaultInterpolation=Ml,jh.prototype.InterpolantFactoryMethodLinear=void 0,jh.prototype.InterpolantFactoryMethodSmooth=void 0;var Mh=class extends wh{constructor(e,t,n,r){super(e,t,n,r)}};Mh.prototype.ValueTypeName=`vector`;var Nh=class{constructor(e=``,t=-1,n=[],r=zl){this.name=e,this.tracks=n,this.duration=t,this.blendMode=r,this.uuid=fu(),this.userData={},this.duration<0&&this.resetDuration()}static parse(e){let t=[],n=e.tracks,r=1/(e.fps||1);for(let e=0,i=n.length;e!==i;++e)t.push(Fh(n[e]).scale(r));let i=new this(e.name,e.duration,t,e.blendMode);return i.uuid=e.uuid,i.userData=JSON.parse(e.userData||`{}`),i}static toJSON(e){let t=[],n=e.tracks,r={name:e.name,duration:e.duration,tracks:t,uuid:e.uuid,blendMode:e.blendMode,userData:JSON.stringify(e.userData)};for(let e=0,r=n.length;e!==r;++e)t.push(wh.toJSON(n[e]));return r}static CreateFromMorphTargetSequence(e,t,n,r){let i=t.length,a=[];for(let e=0;e1){let e=a[1],t=r[e];t||(r[e]=t=[]),t.push(n)}}let a=[];for(let e in r)a.push(this.CreateFromMorphTargetSequence(e,r[e],t,n));return a}resetDuration(){let e=this.tracks,t=0;for(let n=0,r=e.length;n!==r;++n){let e=this.tracks[n];t=Math.max(t,e.times[e.times.length-1])}return this.duration=t,this}trim(){for(let e=0;e{t&&t(i),this.manager.itemEnd(e)},0);return}if(Bh[e]!==void 0){Bh[e].push({onLoad:t,onProgress:n,onError:r});return}Bh[e]=[],Bh[e].push({onLoad:t,onProgress:n,onError:r});let a=new Request(e,{headers:new Headers(this.requestHeader),credentials:this.withCredentials?`include`:`same-origin`,signal:typeof AbortSignal.any==`function`?AbortSignal.any([this._abortController.signal,this.manager.abortController.signal]):this._abortController.signal}),o=this.mimeType,s=this.responseType;fetch(a).then(t=>{if(t.status===200||t.status===0){if(t.status===0&&nu(`FileLoader: HTTP Status 0 received.`),typeof ReadableStream>`u`||t.body===void 0||t.body.getReader===void 0)return t;let n=Bh[e],r=t.body.getReader(),i=t.headers.get(`X-File-Size`)||t.headers.get(`Content-Length`),a=i?parseInt(i):0,o=a!==0,s=0,c=new ReadableStream({start(e){t();function t(){r.read().then(({done:r,value:i})=>{if(r)e.close();else{s+=i.byteLength;let r=new ProgressEvent(`progress`,{lengthComputable:o,loaded:s,total:a});for(let e=0,t=n.length;e{e.error(t)})}}});return new Response(c)}else throw new Vh(`fetch for "${t.url}" responded with ${t.status}: ${t.statusText}`,t)}).then(e=>{switch(s){case`arraybuffer`:return e.arrayBuffer();case`blob`:return e.blob();case`document`:return e.text().then(e=>new DOMParser().parseFromString(e,o));case`json`:return e.json();default:if(o===``)return e.text();{let t=/charset="?([^;"\s]*)"?/i.exec(o),n=t&&t[1]?t[1].toLowerCase():void 0,r=new TextDecoder(n);return e.arrayBuffer().then(e=>r.decode(e))}}}).then(t=>{Ih.add(`file:${e}`,t);let n=Bh[e];delete Bh[e];for(let e=0,r=n.length;e{let n=Bh[e];if(n===void 0)throw this.manager.itemError(e),t;delete Bh[e];for(let e=0,r=n.length;e{this.manager.itemEnd(e)}),this.manager.itemStart(e)}setResponseType(e){return this.responseType=e,this}setMimeType(e){return this.mimeType=e,this}abort(){return this._abortController.abort(),this._abortController=new AbortController,this}},Uh=new WeakMap,Wh=class extends zh{constructor(e){super(e)}load(e,t,n,r){this.path!==void 0&&(e=this.path+e),e=this.manager.resolveURL(e);let i=this,a=Ih.get(`image:${e}`);if(a!==void 0){if(a.complete===!0)i.manager.itemStart(e),setTimeout(function(){t&&t(a),i.manager.itemEnd(e)},0);else{let e=Uh.get(a);e===void 0&&(e=[],Uh.set(a,e)),e.push({onLoad:t,onError:r})}return a}let o=Zl(`img`);function s(){l(),t&&t(this);let n=Uh.get(this)||[];for(let e=0;e`u`&&nu(`ImageBitmapLoader: createImageBitmap() not supported.`),typeof fetch>`u`&&nu(`ImageBitmapLoader: fetch() not supported.`),this.options={premultiplyAlpha:`none`},this._abortController=new AbortController}setOptions(e){return this.options=e,this}load(e,t,n,r){e===void 0&&(e=``),this.path!==void 0&&(e=this.path+e),e=this.manager.resolveURL(e);let i=this,a=Ih.get(`image-bitmap:${e}`);if(a!==void 0){if(i.manager.itemStart(e),a.then){a.then(n=>{mg.has(a)===!0?(r&&r(mg.get(a)),i.manager.itemError(e),i.manager.itemEnd(e)):(t&&t(n),i.manager.itemEnd(e))});return}setTimeout(function(){t&&t(a),i.manager.itemEnd(e)},0);return}let o={};o.credentials=this.crossOrigin===`anonymous`?`same-origin`:`include`,o.headers=this.requestHeader,o.signal=typeof AbortSignal.any==`function`?AbortSignal.any([this._abortController.signal,this.manager.abortController.signal]):this._abortController.signal;let s=fetch(e,o).then(function(e){return e.blob()}).then(function(e){return createImageBitmap(e,Object.assign({},i.options,{colorSpaceConversion:`none`}))}).then(function(n){return Ih.add(`image-bitmap:${e}`,n),t&&t(n),i.manager.itemEnd(e),n}).catch(function(t){r&&r(t),mg.set(s,t),Ih.remove(`image-bitmap:${e}`),i.manager.itemError(e),i.manager.itemEnd(e)});Ih.add(`image-bitmap:${e}`,s),i.manager.itemStart(e)}abort(){return this._abortController.abort(),this._abortController=new AbortController,this}},gg=-90,_g=1,vg=class extends Md{constructor(e,t,n){super(),this.type=`CubeCamera`,this.renderTarget=n,this.coordinateSystem=null,this.activeMipmapLevel=0;let r=new ag(gg,_g,e,t);r.layers=this.layers,this.add(r);let i=new ag(gg,_g,e,t);i.layers=this.layers,this.add(i);let a=new ag(gg,_g,e,t);a.layers=this.layers,this.add(a);let o=new ag(gg,_g,e,t);o.layers=this.layers,this.add(o);let s=new ag(gg,_g,e,t);s.layers=this.layers,this.add(s);let c=new ag(gg,_g,e,t);c.layers=this.layers,this.add(c)}updateCoordinateSystem(){let e=this.coordinateSystem,t=this.children.concat(),[n,r,i,a,o,s]=t;for(let e of t)this.remove(e);if(e===2e3)n.up.set(0,1,0),n.lookAt(1,0,0),r.up.set(0,1,0),r.lookAt(-1,0,0),i.up.set(0,0,-1),i.lookAt(0,1,0),a.up.set(0,0,1),a.lookAt(0,-1,0),o.up.set(0,1,0),o.lookAt(0,0,1),s.up.set(0,1,0),s.lookAt(0,0,-1);else if(e===2001)n.up.set(0,-1,0),n.lookAt(-1,0,0),r.up.set(0,-1,0),r.lookAt(1,0,0),i.up.set(0,0,1),i.lookAt(0,1,0),a.up.set(0,0,-1),a.lookAt(0,-1,0),o.up.set(0,-1,0),o.lookAt(0,0,1),s.up.set(0,-1,0),s.lookAt(0,0,-1);else throw Error(`THREE.CubeCamera.updateCoordinateSystem(): Invalid coordinate system: `+e);for(let e of t)this.add(e),e.updateMatrixWorld()}update(e,t){this.parent===null&&this.updateMatrixWorld();let{renderTarget:n,activeMipmapLevel:r}=this;this.coordinateSystem!==e.coordinateSystem&&(this.coordinateSystem=e.coordinateSystem,this.updateCoordinateSystem());let[i,a,o,s,c,l]=this.children,u=e.getRenderTarget(),d=e.getActiveCubeFace(),f=e.getActiveMipmapLevel(),p=e.xr.enabled;e.xr.enabled=!1;let m=n.texture.generateMipmaps;n.texture.generateMipmaps=!1;let h=!1;h=e.isWebGLRenderer===!0?e.state.buffers.depth.getReversed():e.reversedDepthBuffer,e.setRenderTarget(n,0,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,i),e.setRenderTarget(n,1,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,a),e.setRenderTarget(n,2,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,o),e.setRenderTarget(n,3,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,s),e.setRenderTarget(n,4,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,c),n.texture.generateMipmaps=m,e.setRenderTarget(n,5,r),h&&e.autoClear===!1&&e.clearDepth(),e.render(t,l),e.setRenderTarget(u,d,f),e.xr.enabled=p,n.texture.needsPMREMUpdate=!0}},yg=class extends ag{constructor(e=[]){super(),this.isArrayCamera=!0,this.isMultiViewCamera=!1,this.cameras=e}},bg=class{constructor(){this._previousTime=0,this._currentTime=0,this._startTime=performance.now(),this._delta=0,this._elapsed=0,this._timescale=1,this._document=null,this._pageVisibilityHandler=null}connect(e){this._document=e,e.hidden!==void 0&&(this._pageVisibilityHandler=xg.bind(this),e.addEventListener(`visibilitychange`,this._pageVisibilityHandler,!1))}disconnect(){this._pageVisibilityHandler!==null&&(this._document.removeEventListener(`visibilitychange`,this._pageVisibilityHandler),this._pageVisibilityHandler=null),this._document=null}getDelta(){return this._delta/1e3}getElapsed(){return this._elapsed/1e3}getTimescale(){return this._timescale}setTimescale(e){return this._timescale=e,this}reset(){return this._currentTime=performance.now()-this._startTime,this}dispose(){this.disconnect()}update(e){return this._pageVisibilityHandler!==null&&this._document.hidden===!0?this._delta=0:(this._previousTime=this._currentTime,this._currentTime=(e===void 0?performance.now():e)-this._startTime,this._delta=(this._currentTime-this._previousTime)*this._timescale,this._elapsed+=this._delta),this}};function xg(){this._document.hidden===!1&&this.reset()}var Sg=`\\[\\]\\.:\\/`,Cg=RegExp(`[\\[\\]\\.:\\/]`,`g`),wg=`[^\\[\\]\\.:\\/]`,Tg=`[^`+Sg.replace(`\\.`,``)+`]`,Eg=`((?:WC+[\\/:])*)`.replace(`WC`,wg),Dg=`(WCOD+)?`.replace(`WCOD`,Tg),Og=`(?:\\.(WC+)(?:\\[(.+)\\])?)?`.replace(`WC`,wg),kg=`\\.(WC+)(?:\\[(.+)\\])?`.replace(`WC`,wg),Ag=RegExp(`^`+Eg+Dg+Og+kg+`$`),jg=[`material`,`materials`,`bones`,`map`],Mg=class{constructor(e,t,n){let r=n||Ng.parseTrackName(t);this._targetGroup=e,this._bindings=e.subscribe_(t,r)}getValue(e,t){this.bind();let n=this._targetGroup.nCachedObjects_,r=this._bindings[n];r!==void 0&&r.getValue(e,t)}setValue(e,t){let n=this._bindings;for(let r=this._targetGroup.nCachedObjects_,i=n.length;r!==i;++r)n[r].setValue(e,t)}bind(){let e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,n=e.length;t!==n;++t)e[t].bind()}unbind(){let e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,n=e.length;t!==n;++t)e[t].unbind()}},Ng=class e{constructor(t,n,r){this.path=n,this.parsedPath=r||e.parseTrackName(n),this.node=e.findNode(t,this.parsedPath.nodeName),this.rootNode=t,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}static create(t,n,r){return t&&t.isAnimationObjectGroup?new e.Composite(t,n,r):new e(t,n,r)}static sanitizeNodeName(e){return e.replace(/\s/g,`_`).replace(Cg,``)}static parseTrackName(e){let t=Ag.exec(e);if(t===null)throw Error(`THREE.PropertyBinding: Cannot parse trackName: `+e);let n={nodeName:t[2],objectName:t[3],objectIndex:t[4],propertyName:t[5],propertyIndex:t[6]},r=n.nodeName&&n.nodeName.lastIndexOf(`.`);if(r!==void 0&&r!==-1){let e=n.nodeName.substring(r+1);jg.indexOf(e)!==-1&&(n.nodeName=n.nodeName.substring(0,r),n.objectName=e)}if(n.propertyName===null||n.propertyName.length===0)throw Error(`THREE.PropertyBinding: can not parse propertyName from trackName: `+e);return n}static findNode(e,t){if(t===void 0||t===``||t===`.`||t===-1||t===e.name||t===e.uuid)return e;if(e.skeleton){let n=e.skeleton.getBoneByName(t);if(n!==void 0)return n}if(e.children){let n=function(e){for(let r=0;re.start-t.start);let t=0;for(let e=1;e 0 + struct SunLight { + vec3 direction; + vec3 color; + }; + uniform SunLight sunLights[ NUM_SUN_LIGHTS ]; + void getSunLightInfo( const in SunLight sunLight, out IncidentLight light ) { + light.color = sunLight.color; + light.direction = sunLight.direction; + light.visible = true; + } +#endif #if NUM_DIR_LIGHTS > 0 struct DirectionalLight { vec3 direction; @@ -851,6 +897,9 @@ material.roughness = min( material.roughness, 1.0 ); #ifdef USE_DISPERSION material.dispersion = dispersion; #endif +#ifdef USE_RETROREFLECTION + material.retroreflectivity = retroreflectivity; +#endif #ifdef USE_IRIDESCENCE material.iridescence = iridescence; material.iridescenceIOR = iridescenceIOR; @@ -901,6 +950,11 @@ struct PhysicalMaterial { float metalness; float specularF90; float dispersion; + vec2 dfg; + vec3 multiScatteringCompensation; + #ifdef USE_RETROREFLECTION + float retroreflectivity; + #endif #ifdef USE_CLEARCOAT float clearcoat; float clearcoatRoughness; @@ -912,9 +966,8 @@ struct PhysicalMaterial { float iridescenceIOR; float iridescenceThickness; vec3 iridescenceFresnel; - vec3 iridescenceF0; - vec3 iridescenceFresnelDielectric; - vec3 iridescenceFresnelMetallic; + vec3 iridescenceF0Dielectric; + vec3 iridescenceF0Metallic; #endif #ifdef USE_SHEEN vec3 sheenColor; @@ -1102,12 +1155,10 @@ vec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 return specularColor * fab.x + specularF90 * fab.y; } #ifdef USE_IRIDESCENCE -void computeMultiscatteringIridescence( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float iridescence, const in vec3 iridescenceF0, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) { +void computeMultiscatteringIridescence( const in vec2 fab, const in vec3 specularColor, const in float specularF90, const in float iridescence, const in vec3 iridescenceF0, inout vec3 singleScatter, inout vec3 multiScatter ) { #else -void computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness, inout vec3 singleScatter, inout vec3 multiScatter ) { +void computeMultiscattering( const in vec2 fab, const in vec3 specularColor, const in float specularF90, inout vec3 singleScatter, inout vec3 multiScatter ) { #endif - float dotNV = saturate( dot( normal, viewDir ) ); - vec2 fab = texture2D( dfgLUT, vec2( roughness, dotNV ) ).rg; #ifdef USE_IRIDESCENCE vec3 Fr = mix( specularColor, iridescenceF0, iridescence ); #else @@ -1120,24 +1171,6 @@ void computeMultiscattering( const in vec3 normal, const in vec3 viewDir, const singleScatter += FssEss; multiScatter += Fms * Ems; } -vec3 BRDF_GGX_Multiscatter( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material ) { - vec3 singleScatter = BRDF_GGX( lightDir, viewDir, normal, material ); - float dotNL = saturate( dot( normal, lightDir ) ); - float dotNV = saturate( dot( normal, viewDir ) ); - vec2 dfgV = texture2D( dfgLUT, vec2( material.roughness, dotNV ) ).rg; - vec2 dfgL = texture2D( dfgLUT, vec2( material.roughness, dotNL ) ).rg; - vec3 FssEss_V = material.specularColorBlended * dfgV.x + material.specularF90 * dfgV.y; - vec3 FssEss_L = material.specularColorBlended * dfgL.x + material.specularF90 * dfgL.y; - float Ess_V = dfgV.x + dfgV.y; - float Ess_L = dfgL.x + dfgL.y; - float Ems_V = 1.0 - Ess_V; - float Ems_L = 1.0 - Ess_L; - vec3 Favg = material.specularColorBlended + ( 1.0 - material.specularColorBlended ) * 0.047619; - vec3 Fms = FssEss_V * FssEss_L * Favg / ( 1.0 - Ems_V * Ems_L * Favg + EPSILON ); - float compensationFactor = Ems_V * Ems_L; - vec3 multiScatter = Fms * compensationFactor; - return singleScatter + multiScatter; -} #if NUM_RECT_AREA_LIGHTS > 0 void RE_Direct_RectArea_Physical( const in RectAreaLight rectAreaLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) { vec3 normal = geometryNormal; @@ -1198,13 +1231,36 @@ void RE_Direct_Physical( const in IncidentLight directLight, const in vec3 geome irradiance *= sheenEnergyComp; #endif - reflectedLight.directSpecular += irradiance * BRDF_GGX_Multiscatter( directLight.direction, geometryViewDir, geometryNormal, material ); - reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseContribution ); + vec3 specularBRDF = BRDF_GGX( directLight.direction, geometryViewDir, geometryNormal, material ); + #ifdef USE_RETROREFLECTION + vec3 retroViewDir = reflect( - geometryViewDir, geometryNormal ); + vec3 retroSpecularBRDF = BRDF_GGX( directLight.direction, retroViewDir, geometryNormal, material ); + specularBRDF = mix( specularBRDF, retroSpecularBRDF, saturate( material.retroreflectivity ) ); + #endif + reflectedLight.directSpecular += irradiance * specularBRDF * material.multiScatteringCompensation; + vec3 halfDir = normalize( directLight.direction + geometryViewDir ); + float dotVH = saturate( dot( geometryViewDir, halfDir ) ); + vec3 F = F_Schlick( material.specularColor, material.specularF90, dotVH ); + #ifdef USE_RETROREFLECTION + vec3 retroHalfDir = normalize( directLight.direction + retroViewDir ); + float dotRetroVH = saturate( dot( retroViewDir, retroHalfDir ) ); + vec3 retroF = F_Schlick( material.specularColor, material.specularF90, dotRetroVH ); + F = mix( F, retroF, saturate( material.retroreflectivity ) ); + #endif + reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseContribution ) * ( 1.0 - F ); } void RE_IndirectDiffuse_Physical( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) { - vec3 diffuse = irradiance * BRDF_Lambert( material.diffuseContribution ); + vec3 singleScattering = vec3( 0.0 ); + vec3 multiScattering = vec3( 0.0 ); + #ifdef USE_IRIDESCENCE + computeMultiscatteringIridescence( material.dfg, material.specularColor, material.specularF90, material.iridescence, material.iridescenceF0Dielectric, singleScattering, multiScattering ); + #else + computeMultiscattering( material.dfg, material.specularColor, material.specularF90, singleScattering, multiScattering ); + #endif + vec3 diffuse = irradiance * BRDF_Lambert( material.diffuseContribution ) * ( 1.0 - singleScattering - multiScattering ); #ifdef USE_SHEEN float sheenAlbedo = IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness ); + sheenSpecularIndirect += irradiance * material.sheenColor * sheenAlbedo * RECIPROCAL_PI; float sheenEnergyComp = 1.0 - max3( material.sheenColor ) * sheenAlbedo; diffuse *= sheenEnergyComp; #endif @@ -1222,11 +1278,11 @@ void RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradia vec3 singleScatteringMetallic = vec3( 0.0 ); vec3 multiScatteringMetallic = vec3( 0.0 ); #ifdef USE_IRIDESCENCE - computeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnelDielectric, material.roughness, singleScatteringDielectric, multiScatteringDielectric ); - computeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.diffuseColor, material.specularF90, material.iridescence, material.iridescenceFresnelMetallic, material.roughness, singleScatteringMetallic, multiScatteringMetallic ); + computeMultiscatteringIridescence( material.dfg, material.specularColor, material.specularF90, material.iridescence, material.iridescenceF0Dielectric, singleScatteringDielectric, multiScatteringDielectric ); + computeMultiscatteringIridescence( material.dfg, material.diffuseColor, material.specularF90, material.iridescence, material.iridescenceF0Metallic, singleScatteringMetallic, multiScatteringMetallic ); #else - computeMultiscattering( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.roughness, singleScatteringDielectric, multiScatteringDielectric ); - computeMultiscattering( geometryNormal, geometryViewDir, material.diffuseColor, material.specularF90, material.roughness, singleScatteringMetallic, multiScatteringMetallic ); + computeMultiscattering( material.dfg, material.specularColor, material.specularF90, singleScatteringDielectric, multiScatteringDielectric ); + computeMultiscattering( material.dfg, material.diffuseColor, material.specularF90, singleScatteringMetallic, multiScatteringMetallic ); #endif vec3 singleScattering = mix( singleScatteringDielectric, singleScatteringMetallic, material.metalness ); vec3 multiScattering = mix( multiScatteringDielectric, multiScatteringMetallic, material.metalness ); @@ -1267,12 +1323,21 @@ vec3 geometryClearcoatNormal = vec3( 0.0 ); material.iridescence = saturate( material.iridescence ); } if ( material.iridescence > 0.0 ) { - material.iridescenceFresnelDielectric = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor ); - material.iridescenceFresnelMetallic = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.diffuseColor ); - material.iridescenceFresnel = mix( material.iridescenceFresnelDielectric, material.iridescenceFresnelMetallic, material.metalness ); - material.iridescenceF0 = Schlick_to_F0( material.iridescenceFresnel, 1.0, dotNVi ); + vec3 iridescenceFresnelDielectric = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor ); + vec3 iridescenceFresnelMetallic = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.diffuseColor ); + material.iridescenceFresnel = mix( iridescenceFresnelDielectric, iridescenceFresnelMetallic, material.metalness ); + material.iridescenceF0Dielectric = Schlick_to_F0( iridescenceFresnelDielectric, 1.0, dotNVi ); + material.iridescenceF0Metallic = Schlick_to_F0( iridescenceFresnelMetallic, 1.0, dotNVi ); } #endif +#ifdef STANDARD + float dotNVms = saturate( dot( geometryNormal, geometryViewDir ) ); + material.dfg = texture2D( dfgLUT, vec2( material.roughness, dotNVms ) ).rg; + #if ( NUM_SUN_LIGHTS > 0 || NUM_DIR_LIGHTS > 0 || NUM_POINT_LIGHTS > 0 || NUM_SPOT_LIGHTS > 0 ) + float EssMs = material.dfg.x + material.dfg.y; + material.multiScatteringCompensation = 1.0 + material.specularColorBlended * ( 1.0 / EssMs - 1.0 ); + #endif +#endif IncidentLight directLight; #if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct ) PointLight pointLight; @@ -1325,6 +1390,23 @@ IncidentLight directLight; } #pragma unroll_loop_end #endif +#if ( NUM_SUN_LIGHTS > 0 ) && defined( RE_Direct ) + SunLight sunLight; + #if defined( USE_SHADOWMAP ) && NUM_SUN_LIGHT_SHADOWS > 0 + SunLightShadow sunLightShadow; + #endif + #pragma unroll_loop_start + for ( int i = 0; i < NUM_SUN_LIGHTS; i ++ ) { + sunLight = sunLights[ i ]; + getSunLightInfo( sunLight, directLight ); + #if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SUN_LIGHT_SHADOWS ) + sunLightShadow = sunLightShadows[ i ]; + directLight.color *= ( directLight.visible && receiveShadow ) ? getSunShadow( sunShadowMap[ i ], sunLightShadow, UNROLLED_LOOP_INDEX ) : 1.0; + #endif + RE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight ); + } + #pragma unroll_loop_end +#endif #if ( NUM_DIR_LIGHTS > 0 ) && defined( RE_Direct ) DirectionalLight directionalLight; #if defined( USE_SHADOWMAP ) && NUM_DIR_LIGHT_SHADOWS > 0 @@ -1387,10 +1469,19 @@ IncidentLight directLight; #endif #if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular ) #ifdef USE_ANISOTROPY - radiance += getIBLAnisotropyRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy ); + vec3 iblRadiance = getIBLAnisotropyRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy ); #else - radiance += getIBLRadiance( geometryViewDir, geometryNormal, material.roughness ); + vec3 iblRadiance = getIBLRadiance( geometryViewDir, geometryNormal, material.roughness ); #endif + #ifdef USE_RETROREFLECTION + #ifdef USE_ANISOTROPY + vec3 retroIBLRadiance = getIBLAnisotropyRetroRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy ); + #else + vec3 retroIBLRadiance = getIBLRetroRadiance( geometryViewDir, geometryNormal, material.roughness ); + #endif + iblRadiance = mix( iblRadiance, retroIBLRadiance, saturate( material.retroreflectivity ) ); + #endif + radiance += iblRadiance; #ifdef USE_CLEARCOAT clearcoatRadiance += getIBLRadiance( geometryViewDir, geometryClearcoatNormal, material.clearcoatRoughness ); #endif @@ -1775,6 +1866,26 @@ gl_Position = projectionMatrix * mvPosition;`,dithering_fragment:`#ifdef DITHERI uniform sampler2D spotLightMap[ NUM_SPOT_LIGHT_MAPS ]; #endif #ifdef USE_SHADOWMAP + #if NUM_SUN_LIGHT_SHADOWS > 0 + #define SUN_LIGHT_CASCADES 2 + #if defined( SHADOWMAP_TYPE_PCF ) + uniform sampler2DShadow sunShadowMap[ NUM_SUN_LIGHT_SHADOWS ]; + #else + uniform sampler2D sunShadowMap[ NUM_SUN_LIGHT_SHADOWS ]; + #endif + uniform mat4 sunShadowMatrix[ NUM_SUN_LIGHT_SHADOWS * SUN_LIGHT_CASCADES ]; + uniform vec4 sunShadowCascade[ NUM_SUN_LIGHT_SHADOWS * SUN_LIGHT_CASCADES ]; + varying vec4 vSunShadowWorldPosition; + varying vec3 vSunShadowWorldNormal; + struct SunLightShadow { + float shadowIntensity; + float shadowBias; + float shadowNormalBias; + float shadowRadius; + vec2 shadowMapSize; + }; + uniform SunLightShadow sunLightShadows[ NUM_SUN_LIGHT_SHADOWS ]; + #endif #if NUM_DIR_LIGHT_SHADOWS > 0 #if defined( SHADOWMAP_TYPE_PCF ) uniform sampler2DShadow directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ]; @@ -1911,6 +2022,37 @@ gl_Position = projectionMatrix * mvPosition;`,dithering_fragment:`#ifdef DITHERI return mix( 1.0, shadow, shadowIntensity ); } #endif + #if NUM_SUN_LIGHT_SHADOWS > 0 + float getSunShadow( + #if defined( SHADOWMAP_TYPE_PCF ) + sampler2DShadow shadowMap, + #else + sampler2D shadowMap, + #endif + SunLightShadow sunLightShadow, + int shadowIndex + ) { + vec4 shadowWorldPosition = vec4( vSunShadowWorldPosition.xyz + vSunShadowWorldNormal * sunLightShadow.shadowNormalBias, 1.0 ); + float viewDepth = vSunShadowWorldPosition.w; + int cascadeOffset = shadowIndex * SUN_LIGHT_CASCADES; + float shadow = 1.0; + for ( int i = SUN_LIGHT_CASCADES - 1; i >= 0; i -- ) { + vec4 cascade = sunShadowCascade[ cascadeOffset + i ]; + if ( viewDepth >= cascade.x && viewDepth < cascade.y ) { + float cascadeShadow = getShadow( + shadowMap, + sunLightShadow.shadowMapSize, + sunLightShadow.shadowIntensity, + sunLightShadow.shadowBias, + sunLightShadow.shadowRadius, + sunShadowMatrix[ cascadeOffset + i ] * shadowWorldPosition + ); + shadow = mix( cascadeShadow, shadow, smoothstep( cascade.z, cascade.y, viewDepth ) ); + } + } + return shadow; + } + #endif #if NUM_POINT_LIGHT_SHADOWS > 0 #if defined( SHADOWMAP_TYPE_PCF ) float getPointShadow( samplerCubeShadow shadowMap, vec2 shadowMapSize, float shadowIntensity, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) { @@ -1973,6 +2115,10 @@ gl_Position = projectionMatrix * mvPosition;`,dithering_fragment:`#ifdef DITHERI varying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ]; #endif #ifdef USE_SHADOWMAP + #if NUM_SUN_LIGHT_SHADOWS > 0 + varying vec4 vSunShadowWorldPosition; + varying vec3 vSunShadowWorldNormal; + #endif #if NUM_DIR_LIGHT_SHADOWS > 0 uniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ]; varying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ]; @@ -2009,7 +2155,7 @@ gl_Position = projectionMatrix * mvPosition;`,dithering_fragment:`#ifdef DITHERI }; uniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ]; #endif -#endif`,shadowmap_vertex:`#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 ) +#endif`,shadowmap_vertex:`#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_SUN_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 ) #ifdef HAS_NORMAL vec3 shadowWorldNormal = transformNormalByInverseViewMatrix( transformedNormal, viewMatrix ); #else @@ -2018,6 +2164,10 @@ gl_Position = projectionMatrix * mvPosition;`,dithering_fragment:`#ifdef DITHERI vec4 shadowWorldPosition; #endif #if defined( USE_SHADOWMAP ) + #if NUM_SUN_LIGHT_SHADOWS > 0 + vSunShadowWorldPosition = vec4( worldPosition.xyz, - mvPosition.z ); + vSunShadowWorldNormal = shadowWorldNormal; + #endif #if NUM_DIR_LIGHT_SHADOWS > 0 #pragma unroll_loop_start for ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) { @@ -2048,6 +2198,15 @@ gl_Position = projectionMatrix * mvPosition;`,dithering_fragment:`#ifdef DITHERI #endif`,shadowmask_pars_fragment:`float getShadowMask() { float shadow = 1.0; #ifdef USE_SHADOWMAP + #if NUM_SUN_LIGHT_SHADOWS > 0 + SunLightShadow sunLight; + #pragma unroll_loop_start + for ( int i = 0; i < NUM_SUN_LIGHT_SHADOWS; i ++ ) { + sunLight = sunLightShadows[ i ]; + shadow *= receiveShadow ? getSunShadow( sunShadowMap[ i ], sunLight, UNROLLED_LOOP_INDEX ) : 1.0; + } + #pragma unroll_loop_end + #endif #if NUM_DIR_LIGHT_SHADOWS > 0 DirectionalLightShadow directionalLight; #pragma unroll_loop_start @@ -3340,6 +3499,9 @@ uniform float opacity; #ifdef USE_DISPERSION uniform float dispersion; #endif +#ifdef USE_RETROREFLECTION + uniform float retroreflectivity; +#endif #ifdef USE_IRIDESCENCE uniform float 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i=t,r=e.length,n},this.beginShadows=function(){a=!0,u(null)},this.endShadows=function(){a=!1},this.setGlobalState=function(e,t){n=u(e,t,0)},this.setState=function(t,o,s){let d=t.clippingPlanes,f=t.clipIntersection,p=t.clipShadows,m=e.get(t);if(!i||d===null||d.length===0||a&&!p)a?u(null):l();else{let e=a?0:r,t=e*4,i=m.clippingState||null;c.value=i,i=u(d,o,t,s);for(let e=0;e!==t;++e)i[e]=n[e];m.clippingState=i,this.numIntersection=f?this.numPlanes:0,this.numPlanes+=e}};function l(){c.value!==n&&(c.value=n,c.needsUpdate=r>0),t.numPlanes=r,t.numIntersection=0}function u(e,n,r,i){let a=e===null?0:e.length,l=null;if(a!==0){if(l=c.value,i!==!0||l===null){let t=r+a*4,i=n.matrixWorldInverse;s.getNormalMatrix(i),(l===null||l.length0&&this._blur(s,0,0,t),this._applyPMREM(s),this._cleanup(s),s}fromEquirectangular(e,t=null){return this._fromTexture(e,t)}fromCubemap(e,t=null){return 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n=this._renderer,r=e.mapping===301||e.mapping===302;r?(this._cubemapMaterial===null&&(this._cubemapMaterial=y_()),this._cubemapMaterial.uniforms.flipEnvMap.value=e.isRenderTargetTexture===!1?-1:1):this._equirectMaterial===null&&(this._equirectMaterial=v_());let i=r?this._cubemapMaterial:this._equirectMaterial,a=this._lodMeshes[0];a.material=i;let o=i.uniforms;o.envMap.value=e;let s=this._cubeSize;h_(t,0,0,3*s,2*s),n.setRenderTarget(t),n.render(a,i_)}_applyPMREM(e){let t=this._renderer,n=t.autoClear;t.autoClear=!1;let r=this._lodMeshes.length;for(let t=1;td-e_?n-d+e_:0),m=4*(this._cubeSize-f);s.envMap.value=e.texture,s.roughness.value=u,s.mipInt.value=d-t,h_(i,p,m,3*f,2*f),r.setRenderTarget(i),r.render(o,i_),s.envMap.value=i.texture,s.roughness.value=0,s.mipInt.value=d-n,h_(e,p,m,3*f,2*f),r.setRenderTarget(e),r.render(o,i_)}_blur(e,t,n,r){let i=this._pingPongRenderTarget,a=Math.min(r,Math.PI)/Math.SQRT2;this._blurPass(e,i,t,n,a),this._blurPass(i,e,n,n,a)}_blurPass(e,t,n,r,i){let a=this._renderer,o=this._blurMaterial,s=this._lodMeshes[r];s.material=o;let c=o.uniforms;c.envMap.value=e.texture,c.sigma.value=i,c.mipInt.value=this._lodMax-n;let l=this._sizeLods[r];h_(t,3*l*(r>this._lodMax-e_?r-this._lodMax+e_:0),4*(this._cubeSize-l),3*l,2*l),a.setRenderTarget(t),a.render(s,i_)}};function p_(e){let t=[],n=[],r=e,i=e-e_+1+t_;for(let e=0;e2?0:-1,r=[t,n,0,t+2/3,n,0,t+2/3,n+1,0,t,n,0,t+2/3,n+1,0,t,n+1,0];c.set(r,18*e);for(let t=0;t<6;t++){let n=s[t*2]*2-1,r=s[t*2+1]*2-1;e===0?d_.set(1,r,n):e===1?d_.set(-n,1,-r):e===2?d_.set(-n,r,1):e===3?d_.set(-1,r,-n):e===4?d_.set(-n,-1,r):d_.set(n,r,-1),d_.toArray(l,(e*6+t)*3)}}let u=new Lf;u.setAttribute(`position`,new Sf(c,3)),u.setAttribute(`outputDirection`,new Sf(l,3)),n.push(new up(u,null)),r>e_&&r--}return{lodMeshes:n,sizeLods:t}}function m_(e,t,n){let r=new nd(e,t,n);return r.texture.mapping=306,r.texture.name=`PMREM.cubeUv`,r.scissorTest=!0,r}function h_(e,t,n,r,i){e.viewport.set(t,n,r,i),e.scissor.set(t,n,r,i)}function g_(e,t,n){return new ah({name:`PMREMGGXConvolution`,defines:{GGX_SAMPLES:r_,CUBEUV_TEXEL_WIDTH:1/t,CUBEUV_TEXEL_HEIGHT:1/n,CUBEUV_MAX_MIP:`${e}.0`},uniforms:{envMap:{value:null},roughness:{value:0},mipInt:{value:0}},vertexShader:b_(),fragmentShader:` precision highp float; precision highp int; @@ -3772,67 +3934,67 @@ void main() { gl_FragColor = vec4(prefilteredColor, 1.0); } - `,blending:0,depthTest:!1,depthWrite:!1})}function Pg(e,t,n){let r=new Float32Array(bg),i=new X(0,1,0);return new wm({name:`SphericalGaussianBlur`,defines:{n:bg,CUBEUV_TEXEL_WIDTH:1/t,CUBEUV_TEXEL_HEIGHT:1/n,CUBEUV_MAX_MIP:`${e}.0`},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:r},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:i}},vertexShader:Lg(),fragmentShader:` + `,blending:0,depthTest:!1,depthWrite:!1})}function __(e,t,n){return new ah({name:`SphericalGaussianBlur`,defines:{SAMPLES:n_,CUBEUV_TEXEL_WIDTH:1/t,CUBEUV_TEXEL_HEIGHT:1/n,CUBEUV_MAX_MIP:`${e}.0`},uniforms:{envMap:{value:null},sigma:{value:0},mipInt:{value:0}},vertexShader:b_(),fragmentShader:` - precision mediump float; - precision mediump int; + precision highp float; + precision highp int; varying vec3 vOutputDirection; uniform sampler2D envMap; - uniform int samples; - uniform float weights[ n ]; - uniform bool latitudinal; - uniform float dTheta; + uniform float sigma; uniform float mipInt; - uniform vec3 poleAxis; #define ENVMAP_TYPE_CUBE_UV #include - vec3 getSample( float theta, vec3 axis ) { - - float cosTheta = cos( theta ); - // Rodrigues' axis-angle rotation - vec3 sampleDirection = vOutputDirection * cosTheta - + cross( axis, vOutputDirection ) * sin( theta ) - + axis * dot( axis, vOutputDirection ) * ( 1.0 - cosTheta ); - - return bilinearCubeUV( envMap, sampleDirection, mipInt ); - - } + #define PI 3.14159265359 + #define GOLDEN_ANGLE 2.39996322973 void main() { - vec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection ); - - if ( all( equal( axis, vec3( 0.0 ) ) ) ) { + if ( sigma == 0.0 ) { - axis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x ); + gl_FragColor = vec4( bilinearCubeUV( envMap, vOutputDirection, mipInt ), 1.0 ); + return; } - axis = normalize( axis ); + vec3 outputDirection = normalize( vOutputDirection ); - gl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 ); - gl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis ); + vec3 up = abs( outputDirection.z ) < 0.999 ? vec3( 0.0, 0.0, 1.0 ) : vec3( 1.0, 0.0, 0.0 ); + vec3 tangent = normalize( cross( up, outputDirection ) ); + vec3 bitangent = cross( outputDirection, tangent ); - for ( int i = 1; i < n; i++ ) { + // Truncate the kernel at three standard deviations or at the antipode. + float thetaMax = min( 3.0 * sigma, PI ); + float truncation = 1.0 - exp( - 0.5 * thetaMax * thetaMax / ( sigma * sigma ) ); - if ( i >= samples ) { + vec3 accumColor = vec3( 0.0 ); + float accumWeight = 0.0; - break; + for ( int i = 0; i < SAMPLES; i ++ ) { - } + // Stratified inverse-CDF sampling of the Gaussian, placed on a golden-angle spiral. + float stratum = ( float( i ) + 0.5 ) / float( SAMPLES ); + float theta = sigma * sqrt( - 2.0 * log( 1.0 - stratum * truncation ) ); + float phi = float( i ) * GOLDEN_ANGLE; + + vec3 offset = cos( phi ) * tangent + sin( phi ) * bitangent; + vec3 sampleDirection = cos( theta ) * outputDirection + sin( theta ) * offset; - float theta = dTheta * float( i ); - gl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis ); - gl_FragColor.rgb += weights[ i ] * getSample( theta, axis ); + // Correct the planar sample density to solid angle. + float weight = sin( theta ) / theta; + + accumColor += weight * bilinearCubeUV( envMap, sampleDirection, mipInt ); + accumWeight += weight; } + gl_FragColor = vec4( accumColor / accumWeight, 1.0 ); + } - `,blending:0,depthTest:!1,depthWrite:!1})}function Fg(){return new wm({name:`EquirectangularToCubeUV`,uniforms:{envMap:{value:null}},vertexShader:Lg(),fragmentShader:` + `,blending:0,depthTest:!1,depthWrite:!1})}function v_(){return new ah({name:`EquirectangularToCubeUV`,uniforms:{envMap:{value:null}},vertexShader:b_(),fragmentShader:` precision mediump float; precision mediump int; @@ -3851,7 +4013,7 @@ void main() { gl_FragColor = vec4( texture2D ( envMap, uv ).rgb, 1.0 ); } - `,blending:0,depthTest:!1,depthWrite:!1})}function Ig(){return new wm({name:`CubemapToCubeUV`,uniforms:{envMap:{value:null},flipEnvMap:{value:-1}},vertexShader:Lg(),fragmentShader:` + `,blending:0,depthTest:!1,depthWrite:!1})}function y_(){return new ah({name:`CubemapToCubeUV`,uniforms:{envMap:{value:null},flipEnvMap:{value:-1}},vertexShader:b_(),fragmentShader:` precision mediump float; precision mediump int; @@ -3867,62 +4029,22 @@ void main() { gl_FragColor = textureCube( envMap, vec3( flipEnvMap * vOutputDirection.x, vOutputDirection.yz ) ); } - `,blending:0,depthTest:!1,depthWrite:!1})}function Lg(){return` + `,blending:0,depthTest:!1,depthWrite:!1})}function b_(){return` precision mediump float; precision mediump int; - attribute float faceIndex; + attribute vec3 outputDirection; varying vec3 vOutputDirection; - // RH coordinate system; PMREM face-indexing convention - vec3 getDirection( vec2 uv, float face ) { - - uv = 2.0 * uv - 1.0; - - vec3 direction = vec3( uv, 1.0 ); - - if ( face == 0.0 ) { - - direction = direction.zyx; // ( 1, v, u ) pos x - - } else if ( face == 1.0 ) { - - direction = direction.xzy; - direction.xz *= -1.0; // ( -u, 1, -v ) pos y - - } else if ( face == 2.0 ) { - - direction.x *= -1.0; // ( -u, v, 1 ) pos z - - } else if ( face == 3.0 ) { - - direction = direction.zyx; - direction.xz *= -1.0; // ( -1, v, -u ) neg x - - } else if ( face == 4.0 ) { - - direction = direction.xzy; - direction.xy *= -1.0; // ( -u, -1, v ) neg y - - } else if ( face == 5.0 ) { - - direction.z *= -1.0; // ( u, v, -1 ) neg z - - } - - return direction; - - } - void main() { - vOutputDirection = getDirection( uv, faceIndex ); + vOutputDirection = outputDirection; gl_Position = vec4( position, 1.0 ); } - `}var Rg=class extends vu{constructor(e=1,t={}){super(e,e,t),this.isWebGLCubeRenderTarget=!0;let n={width:e,height:e,depth:1},r=[n,n,n,n,n,n];this.texture=new Ep(r),this._setTextureOptions(t),this.texture.isRenderTargetTexture=!0}fromEquirectangularTexture(e,t){this.texture.type=t.type,this.texture.colorSpace=t.colorSpace,this.texture.generateMipmaps=t.generateMipmaps,this.texture.minFilter=t.minFilter,this.texture.magFilter=t.magFilter;let n={uniforms:{tEquirect:{value:null}},vertexShader:` + `}var x_=class extends nd{constructor(e=1,t={}){super(e,e,t),this.isWebGLCubeRenderTarget=!0;let n={width:e,height:e,depth:1},r=[n,n,n,n,n,n];this.texture=new 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USE_FOG`:``,n.useFog&&n.fogExp2?`#define FOG_EXP2`:``,n.map?`#define USE_MAP`:``,n.envMap?`#define USE_ENVMAP`:``,n.envMap?`#define `+u:``,n.lightMap?`#define USE_LIGHTMAP`:``,n.aoMap?`#define USE_AOMAP`:``,n.bumpMap?`#define USE_BUMPMAP`:``,n.normalMap?`#define USE_NORMALMAP`:``,n.normalMapObjectSpace?`#define USE_NORMALMAP_OBJECTSPACE`:``,n.normalMapTangentSpace?`#define USE_NORMALMAP_TANGENTSPACE`:``,n.displacementMap?`#define USE_DISPLACEMENTMAP`:``,n.emissiveMap?`#define USE_EMISSIVEMAP`:``,n.anisotropy?`#define USE_ANISOTROPY`:``,n.anisotropyMap?`#define USE_ANISOTROPYMAP`:``,n.clearcoatMap?`#define USE_CLEARCOATMAP`:``,n.clearcoatRoughnessMap?`#define USE_CLEARCOAT_ROUGHNESSMAP`:``,n.clearcoatNormalMap?`#define USE_CLEARCOAT_NORMALMAP`:``,n.iridescenceMap?`#define USE_IRIDESCENCEMAP`:``,n.iridescenceThicknessMap?`#define USE_IRIDESCENCE_THICKNESSMAP`:``,n.specularMap?`#define USE_SPECULARMAP`:``,n.specularColorMap?`#define USE_SPECULAR_COLORMAP`:``,n.specularIntensityMap?`#define USE_SPECULAR_INTENSITYMAP`:``,n.roughnessMap?`#define USE_ROUGHNESSMAP`:``,n.metalnessMap?`#define USE_METALNESSMAP`:``,n.alphaMap?`#define USE_ALPHAMAP`:``,n.alphaHash?`#define USE_ALPHAHASH`:``,n.transmission?`#define USE_TRANSMISSION`:``,n.transmissionMap?`#define USE_TRANSMISSIONMAP`:``,n.thicknessMap?`#define USE_THICKNESSMAP`:``,n.sheenColorMap?`#define USE_SHEEN_COLORMAP`:``,n.sheenRoughnessMap?`#define USE_SHEEN_ROUGHNESSMAP`:``,n.mapUv?`#define MAP_UV `+n.mapUv:``,n.alphaMapUv?`#define ALPHAMAP_UV `+n.alphaMapUv:``,n.lightMapUv?`#define LIGHTMAP_UV `+n.lightMapUv:``,n.aoMapUv?`#define AOMAP_UV `+n.aoMapUv:``,n.emissiveMapUv?`#define EMISSIVEMAP_UV `+n.emissiveMapUv:``,n.bumpMapUv?`#define BUMPMAP_UV `+n.bumpMapUv:``,n.normalMapUv?`#define NORMALMAP_UV `+n.normalMapUv:``,n.displacementMapUv?`#define DISPLACEMENTMAP_UV `+n.displacementMapUv:``,n.metalnessMapUv?`#define METALNESSMAP_UV `+n.metalnessMapUv:``,n.roughnessMapUv?`#define ROUGHNESSMAP_UV `+n.roughnessMapUv:``,n.anisotropyMapUv?`#define ANISOTROPYMAP_UV `+n.anisotropyMapUv:``,n.clearcoatMapUv?`#define CLEARCOATMAP_UV `+n.clearcoatMapUv:``,n.clearcoatNormalMapUv?`#define CLEARCOAT_NORMALMAP_UV `+n.clearcoatNormalMapUv:``,n.clearcoatRoughnessMapUv?`#define CLEARCOAT_ROUGHNESSMAP_UV `+n.clearcoatRoughnessMapUv:``,n.iridescenceMapUv?`#define IRIDESCENCEMAP_UV `+n.iridescenceMapUv:``,n.iridescenceThicknessMapUv?`#define IRIDESCENCE_THICKNESSMAP_UV `+n.iridescenceThicknessMapUv:``,n.sheenColorMapUv?`#define SHEEN_COLORMAP_UV `+n.sheenColorMapUv:``,n.sheenRoughnessMapUv?`#define SHEEN_ROUGHNESSMAP_UV `+n.sheenRoughnessMapUv:``,n.specularMapUv?`#define SPECULARMAP_UV `+n.specularMapUv:``,n.specularColorMapUv?`#define SPECULAR_COLORMAP_UV `+n.specularColorMapUv:``,n.specularIntensityMapUv?`#define SPECULAR_INTENSITYMAP_UV `+n.specularIntensityMapUv:``,n.transmissionMapUv?`#define TRANSMISSIONMAP_UV `+n.transmissionMapUv:``,n.thicknessMapUv?`#define THICKNESSMAP_UV `+n.thicknessMapUv:``,n.vertexTangents&&n.flatShading===!1?`#define USE_TANGENT`:``,n.vertexNormals?`#define HAS_NORMAL`:``,n.vertexColors?`#define USE_COLOR`:``,n.vertexAlphas?`#define USE_COLOR_ALPHA`:``,n.vertexUv1s?`#define USE_UV1`:``,n.vertexUv2s?`#define USE_UV2`:``,n.vertexUv3s?`#define USE_UV3`:``,n.pointsUvs?`#define USE_POINTS_UV`:``,n.flatShading?`#define FLAT_SHADED`:``,n.skinning?`#define USE_SKINNING`:``,n.morphTargets?`#define USE_MORPHTARGETS`:``,n.morphNormals&&n.flatShading===!1?`#define USE_MORPHNORMALS`:``,n.morphColors?`#define USE_MORPHCOLORS`:``,n.morphTargetsCount>0?`#define MORPHTARGETS_TEXTURE_STRIDE `+n.morphTextureStride:``,n.morphTargetsCount>0?`#define MORPHTARGETS_COUNT `+n.morphTargetsCount:``,n.doubleSided?`#define DOUBLE_SIDED`:``,n.flipSided?`#define FLIP_SIDED`:``,n.shadowMapEnabled?`#define USE_SHADOWMAP`:``,n.shadowMapEnabled?`#define `+c:``,n.sizeAttenuation?`#define USE_SIZEATTENUATION`:``,n.numLightProbes>0?`#define USE_LIGHT_PROBES`:``,n.logarithmicDepthBuffer?`#define USE_LOGARITHMIC_DEPTH_BUFFER`:``,n.reversedDepthBuffer?`#define USE_REVERSED_DEPTH_BUFFER`:``,`uniform mat4 modelMatrix;`,`uniform mat4 modelViewMatrix;`,`uniform mat4 projectionMatrix;`,`uniform mat4 viewMatrix;`,`uniform mat3 normalMatrix;`,`uniform vec3 cameraPosition;`,`uniform bool isOrthographic;`,`#ifdef USE_INSTANCING`,` attribute mat4 instanceMatrix;`,`#endif`,`#ifdef USE_INSTANCING_COLOR`,` attribute vec3 instanceColor;`,`#endif`,`#ifdef USE_INSTANCING_MORPH`,` uniform sampler2D morphTexture;`,`#endif`,`attribute vec3 position;`,`attribute vec3 normal;`,`attribute vec2 uv;`,`#ifdef USE_UV1`,` attribute vec2 uv1;`,`#endif`,`#ifdef USE_UV2`,` attribute vec2 uv2;`,`#endif`,`#ifdef USE_UV3`,` attribute vec2 uv3;`,`#endif`,`#ifdef USE_TANGENT`,` attribute vec4 tangent;`,`#endif`,`#if defined( USE_COLOR_ALPHA )`,` attribute vec4 color;`,`#elif defined( USE_COLOR )`,` attribute vec3 color;`,`#endif`,`#ifdef USE_SKINNING`,` attribute vec4 skinIndex;`,` attribute vec4 skinWeight;`,`#endif`,` -`].filter(gv).join(` -`),_=[Ev(n),`#define SHADER_TYPE `+n.shaderType,`#define SHADER_NAME `+n.shaderName,m,n.useFog&&n.fog?`#define USE_FOG`:``,n.useFog&&n.fogExp2?`#define FOG_EXP2`:``,n.alphaToCoverage?`#define ALPHA_TO_COVERAGE`:``,n.map?`#define USE_MAP`:``,n.matcap?`#define USE_MATCAP`:``,n.envMap?`#define USE_ENVMAP`:``,n.envMap?`#define `+l:``,n.envMap?`#define `+u:``,n.envMap?`#define `+d:``,f?`#define CUBEUV_TEXEL_WIDTH `+f.texelWidth:``,f?`#define CUBEUV_TEXEL_HEIGHT `+f.texelHeight:``,f?`#define CUBEUV_MAX_MIP `+f.maxMip+`.0`:``,n.lightMap?`#define USE_LIGHTMAP`:``,n.aoMap?`#define USE_AOMAP`:``,n.bumpMap?`#define USE_BUMPMAP`:``,n.normalMap?`#define USE_NORMALMAP`:``,n.normalMapObjectSpace?`#define USE_NORMALMAP_OBJECTSPACE`:``,n.normalMapTangentSpace?`#define USE_NORMALMAP_TANGENTSPACE`:``,n.packedNormalMap?`#define USE_PACKED_NORMALMAP`:``,n.emissiveMap?`#define USE_EMISSIVEMAP`:``,n.anisotropy?`#define USE_ANISOTROPY`:``,n.anisotropyMap?`#define USE_ANISOTROPYMAP`:``,n.clearcoat?`#define USE_CLEARCOAT`:``,n.clearcoatMap?`#define USE_CLEARCOATMAP`:``,n.clearcoatRoughnessMap?`#define USE_CLEARCOAT_ROUGHNESSMAP`:``,n.clearcoatNormalMap?`#define USE_CLEARCOAT_NORMALMAP`:``,n.dispersion?`#define USE_DISPERSION`:``,n.iridescence?`#define USE_IRIDESCENCE`:``,n.iridescenceMap?`#define USE_IRIDESCENCEMAP`:``,n.iridescenceThicknessMap?`#define USE_IRIDESCENCE_THICKNESSMAP`:``,n.specularMap?`#define USE_SPECULARMAP`:``,n.specularColorMap?`#define USE_SPECULAR_COLORMAP`:``,n.specularIntensityMap?`#define USE_SPECULAR_INTENSITYMAP`:``,n.roughnessMap?`#define USE_ROUGHNESSMAP`:``,n.metalnessMap?`#define USE_METALNESSMAP`:``,n.alphaMap?`#define USE_ALPHAMAP`:``,n.alphaTest?`#define USE_ALPHATEST`:``,n.alphaHash?`#define USE_ALPHAHASH`:``,n.sheen?`#define USE_SHEEN`:``,n.sheenColorMap?`#define USE_SHEEN_COLORMAP`:``,n.sheenRoughnessMap?`#define USE_SHEEN_ROUGHNESSMAP`:``,n.transmission?`#define USE_TRANSMISSION`:``,n.transmissionMap?`#define USE_TRANSMISSIONMAP`:``,n.thicknessMap?`#define USE_THICKNESSMAP`:``,n.vertexTangents&&n.flatShading===!1?`#define USE_TANGENT`:``,n.vertexColors||n.instancingColor?`#define USE_COLOR`:``,n.vertexAlphas||n.batchingColor?`#define USE_COLOR_ALPHA`:``,n.vertexUv1s?`#define USE_UV1`:``,n.vertexUv2s?`#define USE_UV2`:``,n.vertexUv3s?`#define USE_UV3`:``,n.pointsUvs?`#define USE_POINTS_UV`:``,n.gradientMap?`#define USE_GRADIENTMAP`:``,n.flatShading?`#define FLAT_SHADED`:``,n.doubleSided?`#define DOUBLE_SIDED`:``,n.flipSided?`#define FLIP_SIDED`:``,n.shadowMapEnabled?`#define USE_SHADOWMAP`:``,n.shadowMapEnabled?`#define `+c:``,n.premultipliedAlpha?`#define PREMULTIPLIED_ALPHA`:``,n.numLightProbes>0?`#define USE_LIGHT_PROBES`:``,n.numLightProbeGrids>0?`#define USE_LIGHT_PROBES_GRID`:``,n.decodeVideoTexture?`#define DECODE_VIDEO_TEXTURE`:``,n.decodeVideoTextureEmissive?`#define DECODE_VIDEO_TEXTURE_EMISSIVE`:``,n.logarithmicDepthBuffer?`#define USE_LOGARITHMIC_DEPTH_BUFFER`:``,n.reversedDepthBuffer?`#define USE_REVERSED_DEPTH_BUFFER`:``,`uniform mat4 viewMatrix;`,`uniform vec3 cameraPosition;`,`uniform bool isOrthographic;`,n.toneMapping===0?``:`#define TONE_MAPPING`,n.toneMapping===0?``:cg.tonemapping_pars_fragment,n.toneMapping===0?``:uv(`toneMapping`,n.toneMapping),n.dithering?`#define DITHERING`:``,n.opaque?`#define OPAQUE`:``,cg.colorspace_pars_fragment,cv(`linearToOutputTexel`,n.outputColorSpace),fv(),n.useDepthPacking?`#define DEPTH_PACKING `+n.depthPacking:``,` -`].filter(gv).join(` -`)),o=bv(o),o=_v(o,n),o=vv(o,n),s=bv(s),s=_v(s,n),s=vv(s,n),o=wv(o),s=wv(s),n.isRawShaderMaterial!==!0&&(v=`#version 300 es +`)):(g=[ly(n),`#define SHADER_TYPE `+n.shaderType,`#define SHADER_NAME `+n.shaderName,m,n.extensionClipCullDistance?`#define USE_CLIP_DISTANCE`:``,n.batching?`#define USE_BATCHING`:``,n.batchingColor?`#define USE_BATCHING_COLOR`:``,n.instancing?`#define USE_INSTANCING`:``,n.instancingColor?`#define USE_INSTANCING_COLOR`:``,n.instancingMorph?`#define USE_INSTANCING_MORPH`:``,n.useFog&&n.fog?`#define USE_FOG`:``,n.useFog&&n.fogExp2?`#define FOG_EXP2`:``,n.map?`#define USE_MAP`:``,n.envMap?`#define USE_ENVMAP`:``,n.envMap?`#define `+u:``,n.lightMap?`#define USE_LIGHTMAP`:``,n.aoMap?`#define USE_AOMAP`:``,n.bumpMap?`#define USE_BUMPMAP`:``,n.normalMap?`#define USE_NORMALMAP`:``,n.normalMapObjectSpace?`#define USE_NORMALMAP_OBJECTSPACE`:``,n.normalMapTangentSpace?`#define USE_NORMALMAP_TANGENTSPACE`:``,n.displacementMap?`#define USE_DISPLACEMENTMAP`:``,n.emissiveMap?`#define USE_EMISSIVEMAP`:``,n.anisotropy?`#define USE_ANISOTROPY`:``,n.anisotropyMap?`#define USE_ANISOTROPYMAP`:``,n.clearcoatMap?`#define USE_CLEARCOATMAP`:``,n.clearcoatRoughnessMap?`#define USE_CLEARCOAT_ROUGHNESSMAP`:``,n.clearcoatNormalMap?`#define USE_CLEARCOAT_NORMALMAP`:``,n.iridescenceMap?`#define USE_IRIDESCENCEMAP`:``,n.iridescenceThicknessMap?`#define USE_IRIDESCENCE_THICKNESSMAP`:``,n.specularMap?`#define USE_SPECULARMAP`:``,n.specularColorMap?`#define USE_SPECULAR_COLORMAP`:``,n.specularIntensityMap?`#define USE_SPECULAR_INTENSITYMAP`:``,n.roughnessMap?`#define USE_ROUGHNESSMAP`:``,n.metalnessMap?`#define USE_METALNESSMAP`:``,n.alphaMap?`#define USE_ALPHAMAP`:``,n.alphaHash?`#define USE_ALPHAHASH`:``,n.transmission?`#define USE_TRANSMISSION`:``,n.transmissionMap?`#define USE_TRANSMISSIONMAP`:``,n.thicknessMap?`#define USE_THICKNESSMAP`:``,n.sheenColorMap?`#define USE_SHEEN_COLORMAP`:``,n.sheenRoughnessMap?`#define USE_SHEEN_ROUGHNESSMAP`:``,n.mapUv?`#define MAP_UV `+n.mapUv:``,n.alphaMapUv?`#define ALPHAMAP_UV `+n.alphaMapUv:``,n.lightMapUv?`#define LIGHTMAP_UV `+n.lightMapUv:``,n.aoMapUv?`#define AOMAP_UV `+n.aoMapUv:``,n.emissiveMapUv?`#define EMISSIVEMAP_UV `+n.emissiveMapUv:``,n.bumpMapUv?`#define BUMPMAP_UV `+n.bumpMapUv:``,n.normalMapUv?`#define NORMALMAP_UV `+n.normalMapUv:``,n.displacementMapUv?`#define DISPLACEMENTMAP_UV `+n.displacementMapUv:``,n.metalnessMapUv?`#define METALNESSMAP_UV `+n.metalnessMapUv:``,n.roughnessMapUv?`#define ROUGHNESSMAP_UV `+n.roughnessMapUv:``,n.anisotropyMapUv?`#define ANISOTROPYMAP_UV `+n.anisotropyMapUv:``,n.clearcoatMapUv?`#define CLEARCOATMAP_UV `+n.clearcoatMapUv:``,n.clearcoatNormalMapUv?`#define CLEARCOAT_NORMALMAP_UV `+n.clearcoatNormalMapUv:``,n.clearcoatRoughnessMapUv?`#define CLEARCOAT_ROUGHNESSMAP_UV `+n.clearcoatRoughnessMapUv:``,n.iridescenceMapUv?`#define IRIDESCENCEMAP_UV `+n.iridescenceMapUv:``,n.iridescenceThicknessMapUv?`#define IRIDESCENCE_THICKNESSMAP_UV `+n.iridescenceThicknessMapUv:``,n.sheenColorMapUv?`#define SHEEN_COLORMAP_UV `+n.sheenColorMapUv:``,n.sheenRoughnessMapUv?`#define SHEEN_ROUGHNESSMAP_UV `+n.sheenRoughnessMapUv:``,n.specularMapUv?`#define SPECULARMAP_UV `+n.specularMapUv:``,n.specularColorMapUv?`#define SPECULAR_COLORMAP_UV `+n.specularColorMapUv:``,n.specularIntensityMapUv?`#define SPECULAR_INTENSITYMAP_UV `+n.specularIntensityMapUv:``,n.transmissionMapUv?`#define TRANSMISSIONMAP_UV `+n.transmissionMapUv:``,n.thicknessMapUv?`#define THICKNESSMAP_UV `+n.thicknessMapUv:``,n.vertexTangents&&n.flatShading===!1?`#define USE_TANGENT`:``,n.vertexNormals?`#define HAS_NORMAL`:``,n.vertexColors?`#define USE_COLOR`:``,n.vertexAlphas?`#define USE_COLOR_ALPHA`:``,n.vertexUv1s?`#define USE_UV1`:``,n.vertexUv2s?`#define USE_UV2`:``,n.vertexUv3s?`#define USE_UV3`:``,n.pointsUvs?`#define USE_POINTS_UV`:``,n.flatShading?`#define FLAT_SHADED`:``,n.skinning?`#define USE_SKINNING`:``,n.morphTargets?`#define USE_MORPHTARGETS`:``,n.morphNormals&&n.flatShading===!1?`#define USE_MORPHNORMALS`:``,n.morphColors?`#define USE_MORPHCOLORS`:``,n.morphTargetsCount>0?`#define MORPHTARGETS_TEXTURE_STRIDE `+n.morphTextureStride:``,n.morphTargetsCount>0?`#define MORPHTARGETS_COUNT `+n.morphTargetsCount:``,n.doubleSided?`#define DOUBLE_SIDED`:``,n.flipSided?`#define FLIP_SIDED`:``,n.shadowMapEnabled?`#define USE_SHADOWMAP`:``,n.shadowMapEnabled?`#define `+c:``,n.sizeAttenuation?`#define USE_SIZEATTENUATION`:``,n.numLightProbes>0?`#define USE_LIGHT_PROBES`:``,n.logarithmicDepthBuffer?`#define USE_LOGARITHMIC_DEPTH_BUFFER`:``,n.reversedDepthBuffer?`#define USE_REVERSED_DEPTH_BUFFER`:``,`uniform mat4 modelMatrix;`,`uniform mat4 modelViewMatrix;`,`uniform mat4 projectionMatrix;`,`uniform mat4 viewMatrix;`,`uniform mat3 normalMatrix;`,`uniform vec3 cameraPosition;`,`uniform bool isOrthographic;`,`#ifdef USE_INSTANCING`,` attribute mat4 instanceMatrix;`,`#endif`,`#ifdef USE_INSTANCING_COLOR`,` attribute vec3 instanceColor;`,`#endif`,`#ifdef USE_INSTANCING_MORPH`,` uniform sampler2D morphTexture;`,`#endif`,`attribute vec3 position;`,`attribute vec3 normal;`,`attribute vec2 uv;`,`#ifdef USE_UV1`,` attribute vec2 uv1;`,`#endif`,`#ifdef USE_UV2`,` attribute vec2 uv2;`,`#endif`,`#ifdef USE_UV3`,` attribute vec2 uv3;`,`#endif`,`#ifdef USE_TANGENT`,` attribute vec4 tangent;`,`#endif`,`#if defined( USE_COLOR_ALPHA )`,` attribute vec4 color;`,`#elif defined( USE_COLOR )`,` attribute vec3 color;`,`#endif`,`#ifdef USE_SKINNING`,` attribute vec4 skinIndex;`,` attribute vec4 skinWeight;`,`#endif`,` +`].filter($v).join(` +`),_=[ly(n),`#define SHADER_TYPE `+n.shaderType,`#define SHADER_NAME `+n.shaderName,m,n.useFog&&n.fog?`#define USE_FOG`:``,n.useFog&&n.fogExp2?`#define FOG_EXP2`:``,n.alphaToCoverage?`#define ALPHA_TO_COVERAGE`:``,n.map?`#define USE_MAP`:``,n.matcap?`#define USE_MATCAP`:``,n.envMap?`#define USE_ENVMAP`:``,n.envMap?`#define `+l:``,n.envMap?`#define `+u:``,n.envMap?`#define `+d:``,f?`#define CUBEUV_TEXEL_WIDTH `+f.texelWidth:``,f?`#define CUBEUV_TEXEL_HEIGHT `+f.texelHeight:``,f?`#define CUBEUV_MAX_MIP `+f.maxMip+`.0`:``,n.lightMap?`#define USE_LIGHTMAP`:``,n.aoMap?`#define USE_AOMAP`:``,n.bumpMap?`#define USE_BUMPMAP`:``,n.normalMap?`#define USE_NORMALMAP`:``,n.normalMapObjectSpace?`#define USE_NORMALMAP_OBJECTSPACE`:``,n.normalMapTangentSpace?`#define USE_NORMALMAP_TANGENTSPACE`:``,n.packedNormalMap?`#define USE_PACKED_NORMALMAP`:``,n.emissiveMap?`#define USE_EMISSIVEMAP`:``,n.anisotropy?`#define USE_ANISOTROPY`:``,n.anisotropyMap?`#define USE_ANISOTROPYMAP`:``,n.clearcoat?`#define USE_CLEARCOAT`:``,n.clearcoatMap?`#define USE_CLEARCOATMAP`:``,n.clearcoatRoughnessMap?`#define USE_CLEARCOAT_ROUGHNESSMAP`:``,n.clearcoatNormalMap?`#define USE_CLEARCOAT_NORMALMAP`:``,n.dispersion?`#define USE_DISPERSION`:``,n.retroreflection?`#define USE_RETROREFLECTION`:``,n.iridescence?`#define USE_IRIDESCENCE`:``,n.iridescenceMap?`#define USE_IRIDESCENCEMAP`:``,n.iridescenceThicknessMap?`#define USE_IRIDESCENCE_THICKNESSMAP`:``,n.specularMap?`#define USE_SPECULARMAP`:``,n.specularColorMap?`#define USE_SPECULAR_COLORMAP`:``,n.specularIntensityMap?`#define USE_SPECULAR_INTENSITYMAP`:``,n.roughnessMap?`#define USE_ROUGHNESSMAP`:``,n.metalnessMap?`#define USE_METALNESSMAP`:``,n.alphaMap?`#define USE_ALPHAMAP`:``,n.alphaTest?`#define USE_ALPHATEST`:``,n.alphaHash?`#define USE_ALPHAHASH`:``,n.sheen?`#define USE_SHEEN`:``,n.sheenColorMap?`#define USE_SHEEN_COLORMAP`:``,n.sheenRoughnessMap?`#define USE_SHEEN_ROUGHNESSMAP`:``,n.transmission?`#define USE_TRANSMISSION`:``,n.transmissionMap?`#define USE_TRANSMISSIONMAP`:``,n.thicknessMap?`#define USE_THICKNESSMAP`:``,n.vertexTangents&&n.flatShading===!1?`#define USE_TANGENT`:``,n.vertexColors||n.instancingColor?`#define USE_COLOR`:``,n.vertexAlphas||n.batchingColor?`#define USE_COLOR_ALPHA`:``,n.vertexUv1s?`#define USE_UV1`:``,n.vertexUv2s?`#define USE_UV2`:``,n.vertexUv3s?`#define USE_UV3`:``,n.pointsUvs?`#define USE_POINTS_UV`:``,n.gradientMap?`#define USE_GRADIENTMAP`:``,n.flatShading?`#define FLAT_SHADED`:``,n.doubleSided?`#define DOUBLE_SIDED`:``,n.flipSided?`#define FLIP_SIDED`:``,n.shadowMapEnabled?`#define USE_SHADOWMAP`:``,n.shadowMapEnabled?`#define `+c:``,n.premultipliedAlpha?`#define PREMULTIPLIED_ALPHA`:``,n.numLightProbes>0?`#define USE_LIGHT_PROBES`:``,n.numLightProbeGrids>0?`#define USE_LIGHT_PROBES_GRID`:``,n.decodeVideoTexture?`#define DECODE_VIDEO_TEXTURE`:``,n.decodeVideoTextureEmissive?`#define DECODE_VIDEO_TEXTURE_EMISSIVE`:``,n.logarithmicDepthBuffer?`#define USE_LOGARITHMIC_DEPTH_BUFFER`:``,n.reversedDepthBuffer?`#define USE_REVERSED_DEPTH_BUFFER`:``,`uniform mat4 viewMatrix;`,`uniform vec3 cameraPosition;`,`uniform bool isOrthographic;`,n.toneMapping===0?``:`#define TONE_MAPPING`,n.toneMapping===0?``:Wg.tonemapping_pars_fragment,n.toneMapping===0?``:qv(`toneMapping`,n.toneMapping),n.dithering?`#define DITHERING`:``,n.opaque?`#define OPAQUE`:``,Wg.colorspace_pars_fragment,Gv(`linearToOutputTexel`,n.outputColorSpace),Yv(),n.useDepthPacking?`#define DEPTH_PACKING `+n.depthPacking:``,` +`].filter($v).join(` +`)),o=ry(o),o=ey(o,n),o=ty(o,n),s=ry(s),s=ey(s,n),s=ty(s,n),o=sy(o),s=sy(s),n.isRawShaderMaterial!==!0&&(v=`#version 300 es `,g=[p,`#define attribute in`,`#define varying out`,`#define texture2D texture`].join(` `)+` `+g,_=[`#define varying in`,n.glslVersion===`300 es`?``:`layout(location = 0) out highp vec4 pc_fragColor;`,n.glslVersion===`300 es`?``:`#define gl_FragColor pc_fragColor`,`#define gl_FragDepthEXT gl_FragDepth`,`#define texture2D texture`,`#define textureCube texture`,`#define texture2DProj textureProj`,`#define texture2DLodEXT textureLod`,`#define texture2DProjLodEXT textureProjLod`,`#define textureCubeLodEXT textureLod`,`#define texture2DGradEXT textureGrad`,`#define texture2DProjGradEXT textureProjGrad`,`#define textureCubeGradEXT textureGrad`].join(` `)+` -`+_);let y=v+g+o,b=v+_+s,x=tv(i,i.VERTEX_SHADER,y),S=tv(i,i.FRAGMENT_SHADER,b);i.attachShader(h,x),i.attachShader(h,S),n.index0AttributeName===void 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p(e,t,r){e.ior.value=t.ior,t.sheen>0&&(e.sheenColor.value.copy(t.sheenColor).multiplyScalar(t.sheen),e.sheenRoughness.value=t.sheenRoughness,t.sheenColorMap&&(e.sheenColorMap.value=t.sheenColorMap,n(t.sheenColorMap,e.sheenColorMapTransform)),t.sheenRoughnessMap&&(e.sheenRoughnessMap.value=t.sheenRoughnessMap,n(t.sheenRoughnessMap,e.sheenRoughnessMapTransform))),t.clearcoat>0&&(e.clearcoat.value=t.clearcoat,e.clearcoatRoughness.value=t.clearcoatRoughness,t.clearcoatMap&&(e.clearcoatMap.value=t.clearcoatMap,n(t.clearcoatMap,e.clearcoatMapTransform)),t.clearcoatRoughnessMap&&(e.clearcoatRoughnessMap.value=t.clearcoatRoughnessMap,n(t.clearcoatRoughnessMap,e.clearcoatRoughnessMapTransform)),t.clearcoatNormalMap&&(e.clearcoatNormalMap.value=t.clearcoatNormalMap,n(t.clearcoatNormalMap,e.clearcoatNormalMapTransform),e.clearcoatNormalScale.value.copy(t.clearcoatNormalScale),t.side===1&&e.clearcoatNormalScale.value.negate())),t.dispersion>0&&(e.dispersion.value=t.dispersion),t.iridescence>0&&(e.iridescence.value=t.iridescence,e.iridescenceIOR.value=t.iridescenceIOR,e.iridescenceThicknessMinimum.value=t.iridescenceThicknessRange[0],e.iridescenceThicknessMaximum.value=t.iridescenceThicknessRange[1],t.iridescenceMap&&(e.iridescenceMap.value=t.iridescenceMap,n(t.iridescenceMap,e.iridescenceMapTransform)),t.iridescenceThicknessMap&&(e.iridescenceThicknessMap.value=t.iridescenceThicknessMap,n(t.iridescenceThicknessMap,e.iridescenceThicknessMapTransform))),t.transmission>0&&(e.transmission.value=t.transmission,e.transmissionSamplerMap.value=r.texture,e.transmissionSamplerSize.value.set(r.width,r.height),t.transmissionMap&&(e.transmissionMap.value=t.transmissionMap,n(t.transmissionMap,e.transmissionMapTransform)),e.thickness.value=t.thickness,t.thicknessMap&&(e.thicknessMap.value=t.thicknessMap,n(t.thicknessMap,e.thicknessMapTransform)),e.attenuationDistance.value=t.attenuationDistance,e.attenuationColor.value.copy(t.attenuationColor)),t.anisotropy>0&&(e.anisotropyVector.value.set(t.anisotropy*Math.cos(t.anisotropyRotation),t.anisotropy*Math.sin(t.anisotropyRotation)),t.anisotropyMap&&(e.anisotropyMap.value=t.anisotropyMap,n(t.anisotropyMap,e.anisotropyMapTransform))),e.specularIntensity.value=t.specularIntensity,e.specularColor.value.copy(t.specularColor),t.specularColorMap&&(e.specularColorMap.value=t.specularColorMap,n(t.specularColorMap,e.specularColorMapTransform)),t.specularIntensityMap&&(e.specularIntensityMap.value=t.specularIntensityMap,n(t.specularIntensityMap,e.specularIntensityMapTransform))}function 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n=L.get(e),r=L.get(t),h=L.get(n.__renderTarget),g=L.get(r.__renderTarget);I.bindFramebuffer(P.READ_FRAMEBUFFER,h.__webglFramebuffer),I.bindFramebuffer(P.DRAW_FRAMEBUFFER,g.__webglFramebuffer);for(let n=0;n=0&&(x[r]=null,b[r].disconnect(n))}for(let t=0;t=x.length){x.push(n),r=e;break}else if(x[e]===null){x[e]=n,r=e;break}if(r===-1)break}let i=b[r];i&&i.connect(n)}}let M=new Z,ne=new Z;function N(e,t,n){M.setFromMatrixPosition(t.matrixWorld),ne.setFromMatrixPosition(n.matrixWorld);let r=M.distanceTo(ne),i=t.projectionMatrix.elements,a=n.projectionMatrix.elements,o=i[14]/(i[10]-1),s=i[14]/(i[10]+1),c=(i[9]+1)/i[5],l=(i[9]-1)/i[5],u=(i[8]-1)/i[0],d=(a[8]+1)/a[0],f=o*u,p=o*d,m=r/(-u+d),h=m*-u;if(t.matrixWorld.decompose(e.position,e.quaternion,e.scale),e.translateX(h),e.translateZ(m),e.matrixWorld.compose(e.position,e.quaternion,e.scale),e.matrixWorldInverse.copy(e.matrixWorld).invert(),i[10]===-1)e.projectionMatrix.copy(t.projectionMatrix),e.projectionMatrixInverse.copy(t.projectionMatrixInverse);else{let t=o+m,n=s+m,i=f-h,a=p+(r-h),u=c*s/n*t,d=l*s/n*t;e.projectionMatrix.makePerspective(i,a,u,d,t,n),e.projectionMatrixInverse.copy(e.projectionMatrix).invert()}}function P(e,t){t===null?e.matrixWorld.copy(e.matrix):e.matrixWorld.multiplyMatrices(t.matrixWorld,e.matrix),e.matrixWorldInverse.copy(e.matrixWorld).invert()}this.updateCamera=function(e){if(r===null)return;let 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h=Jy(.05,l,t,10,8);h.scale.set(.95,.62,1),h.position.set(0,-.055,.2),p.add(h);let g=new Q(new Pp(.052,.058,.08,10),l);return t.push(g.geometry),g.position.y=.01,g.castShadow=!0,p.add(g),{hip:r,knee:u,ankle:p}},Ve=Be(1),He=Be(-1);return{root:D,hips:O,spine:te,chest:A,head:j,shoulderL:ze.shoulder,elbowL:ze.elbow,gloveL:ze.glove,shoulderR:B.shoulder,elbowR:B.elbow,gloveR:B.glove,hipL:Ve.hip,kneeL:Ve.knee,ankleL:Ve.ankle,hipR:He.hip,kneeR:He.knee,ankleR:He.ankle,chestMesh:re,headMesh:pe,browL:xe,browR:Se,bruiseL:Ee,bruiseR:L,bodyBruise:le,cutL:De,cutR:Oe,swellL:ke,swellR:Ae,cheekL:R,cheekR:je,streakL:z,streakR:Me,noseStreak:Ne,mouthBlood:Pe,ribL:Fe,ribR:Ie,bodyStreak:Le,gloveLMesh:ze.gloveMesh,gloveRMesh:B.gloveMesh,gloveLMaterial:o,gloveRMaterial:o,gloveBaseColor:new Z(e.glove),skinMaterial:n,chestDetails:ce,materials:E,geometries:t}}var $y=new X,eb=new X,tb=new X,nb=new X,rb=new X,ib=new X,ab=new X(0,-1,0),ob=new X;function sb(e,t,n,r,i=.6449999999999999){let 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wb=(e,t,n,r)=>e+(t-e)*(1-Math.exp(-n*r)),Tb=(e,t,n,r)=>e+(((t-e+Math.PI)%(Math.PI*2)+Math.PI*2)%(Math.PI*2)-Math.PI)*(1-Math.exp(-n*r)),Eb=(e,t,n)=>{let r=Math.max(0,Math.min(1,(n-e)/(t-e)));return r*r*(3-2*r)},Db=new X,Ob=new X,kb=new X,Ab={elbowWorld:new X,targetWorld:new X},jb=new X,Mb=new X,Nb=new X,Pb=new X,Fb=new X,Ib=new X,Lb=new X,Rb=new X,zb=new Zl,Bb={full:1,reduced:.35,off:0},Vb=new Z(6031886),Hb=class{rig;mapping;yaw=0;punchT=1;punchKind=null;punchHand=`left`;punchTargetKind=`head`;punchPower=`normal`;actionId=null;actionStartTick=0;actionTotalTicks=1;actionStartupFrac=.33;actionActiveFrac=.1;completedActionId=null;opponentDrop=0;frozenTicks=0;lastAgeTicks=0;predictedId=null;predictedAtSeconds=-1;predictedTotalTicks=1;predictionExpiredTicks=0;downAmount=0;rootX=null;rootZ=0;reactionT=1;reactionDirection=1;reactionPower=0;reactionTarget=`head`;walkPhase=0;gloveLCurrent=new X().copy(vb);gloveRCurrent=new X().copy(yb);hipsRoll=0;spinePitch=0;spineTwist=0;drop=0;kinStep=0;kinHipYaw=0;kinDrop=0;kinHeelR=0;kinPivotL=0;kinHeadTuck=0;hitstop=0;prevVelocityX=0;prevVelocityY=0;inertiaPitch=0;inertiaRoll=0;prevDown=0;landingSpring=0;landingVelocity=0;constructor(e,t){this.rig=e,this.mapping=t}get landingOffset(){return this.landingSpring}impact(e){(e.amount>this.reactionPower||this.reactionT>.4)&&(this.reactionT=0,this.reactionDirection=e.direction,this.reactionPower=Math.max(this.reactionPower*.4,e.amount),this.reactionTarget=e.target??`head`)}landedHit(e){this.hitstop=Math.max(this.hitstop,e?.045:.078)}predict(e,t,n){if(e.kind!==`punch`||e.id===void 0)return;this.predictedId=e.id,this.predictedAtSeconds=t,this.predictionExpiredTicks=0,this.punchKind=e.class,this.punchHand=e.hand,this.punchTargetKind=e.target,this.punchPower=e.power;let r=Uy(e.class,e.target,e.power);this.predictedTotalTicks=Wy(r),this.actionStartupFrac=r.startup/this.predictedTotalTicks,this.actionActiveFrac=r.active/this.predictedTotalTicks,(this.actionId===null||this.punchT>.45)&&(this.punchT=0,this.frozenTicks=0,this.lastAgeTicks=0)}beginAuthoritative(e,t,n){let r=this.predictedId!==null&&e.action_id===this.predictedId;if(this.actionId=e.action_id,this.actionStartTick=e.action_start_tick,this.actionTotalTicks=Math.max(1,e.action_startup_ticks+e.action_active_ticks+e.action_recovery_ticks),this.actionStartupFrac=e.action_startup_ticks/this.actionTotalTicks,this.actionActiveFrac=e.action_active_ticks/this.actionTotalTicks,this.punchKind=e.action,this.punchHand=e.action_hand??(e.stance===`orthodox`?`left`:`right`),this.punchTargetKind=e.action_target??`head`,this.punchPower=e.action_power??`normal`,r){let r=(n-this.predictedAtSeconds)*30,i=t-e.action_start_tick,a=r-i;Math.abs(a)>1&&(this.punchT=Math.max(0,Math.min(1,i/this.actionTotalTicks)),this.frozenTicks=0),this.predictedId=null}else this.punchT=Math.max(0,Math.min(1,(t-e.action_start_tick)/this.actionTotalTicks)),this.frozenTicks=0,this.lastAgeTicks=this.punchT*this.actionTotalTicks}update(e,t,n,r,i,a=`full`,o=0){let s=this.rig,c=e.stance===`orthodox`?1:-1,l=this.mapping.x(e.x),u=this.mapping.z(e.y);this.rootX===null&&(this.rootX=l,this.rootZ=u);let d=.05,f=Xl.clamp(l-this.rootX,-.05,d),p=Xl.clamp(u-this.rootZ,-.05,d);this.rootX+=f,this.rootZ+=p;let m=Math.atan2(this.mapping.x(t.x)-l,(this.mapping.z(t.y)-u)*.45);this.yaw=Tb(this.yaw,m,7,n),e.action_id!==null&&e.action_id!==this.actionId&&e.action_id!==this.completedActionId&&this.beginAuthoritative(e,o,r),e.action_id===null&&(this.actionId=null,this.completedActionId=null),this.predictedId!==null&&(this.predictionExpiredTicks+=n*30,this.predictionExpiredTicks>10&&(this.predictedId=null,this.punchT=1));let h=this.predictedId!==null&&this.actionId===null,g=0,_=1;h?(g=(r-this.predictedAtSeconds)*30-this.frozenTicks,_=this.predictedTotalTicks):this.actionId!==null&&(g=o-this.actionStartTick-this.frozenTicks,_=this.actionTotalTicks),this.hitstop>0&&(this.hitstop=Math.max(0,this.hitstop-n),this.frozenTicks+=n*30),h||this.actionId!==null?(this.punchT=Math.max(0,Math.min(1,g/_)),this.punchT>=1&&this.actionId!==null&&(this.completedActionId=this.actionId,this.actionId=null)):this.punchT=1;let v=1-e.stamina/Math.max(1,e.maximum_stamina),y=Xl.clamp((v-.1)/.9,0,1),b=this.mapping.x(e.velocity_x)*By,x=this.mapping.z(e.velocity_y)*By,S=Math.hypot(b,x),C=Math.min(1,S/1.1),w=Xl.clamp(e.velocity_x*e.facing/7,-1,1),T=Xl.clamp(e.velocity_y/7,-1,1);this.walkPhase+=S*n*5.72;let E=(e.velocity_x-this.prevVelocityX)/Math.max(.001,n),D=(e.velocity_y-this.prevVelocityY)/Math.max(.001,n);this.prevVelocityX=e.velocity_x,this.prevVelocityY=e.velocity_y;let O=(Math.sin(this.yaw)*this.mapping.x(E)+Math.cos(this.yaw)*this.mapping.z(D))*.12,ee=(Math.cos(this.yaw)*this.mapping.x(E)-Math.sin(this.yaw)*this.mapping.z(D))*.12;this.inertiaPitch=wb(this.inertiaPitch,Xl.clamp(-O,-.16,.16),6,n),this.inertiaRoll=wb(this.inertiaRoll,Xl.clamp(ee,-.12,.12),6,n);let k=+!!e.is_downed,te=e.is_downed?2.6:1.5;this.downAmount=wb(this.downAmount,k,te,n);let A=Eb(0,1,this.downAmount);A>.72&&this.prevDown<=.72&&(this.landingVelocity=-.85),this.prevDown=A;let ne=-this.landingSpring*90-this.landingVelocity*12;this.landingVelocity+=ne*n,this.landingSpring=Xl.clamp(this.landingSpring+this.landingVelocity*n,-.09,.06),this.reactionT=Math.min(1,this.reactionT+n/.42);let re=Math.min(1,this.reactionPower/220),ie=(1-Eb(0,.8,this.reactionT))*re*(this.reactionTarget===`head`?1:.2),ae=Eb(0,.14,this.reactionT)*(1-Eb(.35,1,this.reactionT))*re,oe=Math.min(1,e.stunned_ticks/45),se=i?0:Math.sin(r*8.6)*.05*oe,ce=4.4-v*1.4,le=i||A>.5?0:-Math.abs(Math.sin(r*ce+this.walkPhase*.35))*(.017+v*.01),ue=i||A>.5?0:Math.sin(r*ce*.5)*.022,de=i?0:Math.sin(r*(2.2+v*2.6))*(.012+v*.03),j=-.035-y*.025,M=0,fe=.09+y*.06;e.defense===`weave`?(j=-.26,M=.34*c,fe=.3):e.defense===`slip_left`?(M=.2,fe=.12):e.defense===`slip_right`?(M=-.2,fe=.12):e.defense===`pull`&&(fe=-.26),e.is_foul_recovery_target&&(j=-.18,fe=.42),(e.clinch_ticks>0||e.clinch_startup_ticks>0)&&(fe=.4,j=-.08),j-=ae*(this.reactionTarget===`body`?.12:.05),fe-=ae*(this.reactionTarget===`body`?.18:.34),M+=ae*(this.reactionTarget===`body`?.16:.06)*(this.reactionDirection<0?-1:1),M+=se+this.inertiaRoll,fe+=this.inertiaPitch;let pe=0,me=0,he=0,ge=0,_e=0,ve=0,ye=0;if(this.punchT<1&&this.punchKind!==null){let{windup:e,extend:t}=Sb(this.punchKind,this.punchT,this.actionStartupFrac,this.actionActiveFrac),n=this.punchHand===`left`?-1:1,r=this.punchTargetKind===`body`?-.09*t:0;this.punchKind===`jab`?(pe=.14*t*n,me=.12*t,he=.06*t*n,_e=.3*t,ye=.15*t,fe+=.14*t):this.punchKind===`straight`?(pe=.38*t*n,he=.32*t*n,_e=.5*t,me=.12*t,ye=.1*t,fe+=.16*t):this.punchKind===`hook`?(pe=.34*t*n,he=.3*t*n,ve=.55*t,M+=.09*t*n,ye=.08*t):(pe=.26*t*n,he=.22*t*n,ge=-.18*e+.07*t,fe+=.14*e-.07*t,_e=.4*t),ge+=r}this.drop=wb(this.drop,j,12,n),this.hipsRoll=wb(this.hipsRoll,M,12,n),this.spinePitch=wb(this.spinePitch,fe,11,n),this.spineTwist=wb(this.spineTwist,pe,16,n),this.kinStep=wb(this.kinStep,me,14,n),this.kinHipYaw=wb(this.kinHipYaw,he,14,n),this.kinDrop=wb(this.kinDrop,ge,13,n),this.kinHeelR=wb(this.kinHeelR,_e,14,n),this.kinPivotL=wb(this.kinPivotL,ve,14,n),this.kinHeadTuck=wb(this.kinHeadTuck,ye,14,n);let be=.5*c,xe=this.yaw+be*(1-A);s.root.rotation.set(0,xe,0);let Se=Math.sin(xe)*this.kinStep*(1-A),N=Math.cos(xe)*this.kinStep*(1-A);s.root.position.set(this.rootX+Se,0,this.rootZ+N);let Ce=this.reactionDirection>=0?1:-1;s.hips.position.y=.955+le+(this.drop+this.kinDrop)*(1-A)-A*.8+this.landingSpring,s.hips.position.x=ue*(1-A),s.hips.rotation.set(-A*(Math.PI/2-.12)+this.spinePitch*.35*(1-A),this.kinHipYaw*(1-A)+A*.32*Ce,this.hipsRoll*.5*(1-A)+ue*.8*(1-A)+A*.15*Ce),s.spine.rotation.set(this.spinePitch*(1-A),(this.spineTwist+Math.sin(this.walkPhase)*.05*C)*(1-A),this.hipsRoll*.55*(1-A));let P=.1+this.kinHeadTuck-this.spinePitch*.7-ie*.55+A*.3,we=-this.hipsRoll*.8+ie*.3*(this.reactionDirection>=0?-1:1),F=i?0:Math.sin(r*.9)*.07+Math.sin(r*1.7)*.03;s.head.rotation.set(P,-this.spineTwist*.5+F*(1-A),we),s.chest.scale.set(1+de,1+de*.5,1+de),this.poseLegs(C,A,Ce,c,w,T),s.root.updateMatrixWorld(!0);let Te=e.defense===`guard_high`?mb:e.defense===`guard_low`?gb:vb,I=e.defense===`guard_high`?hb:e.defense===`guard_low`?_b:yb,Ee=Mb.copy(Te),L=Nb.copy(I);if(Ee.y-=y*.065,L.y-=y*.065,Ee.z-=y*.03,L.z-=y*.03,e.is_foul_recovery_target&&(Ee.set(.08,.32,.2),L.set(-.06,.3,.18)),(e.clinch_ticks>0||e.clinch_startup_ticks>0)&&(Ee.set(.16,-.05,.5),L.set(-.16,-.02,.48)),A>.03){let e=Math.sin(Eb(.06,.5,A)*Math.PI)*.42;Ee.lerp(Db.set(.56,.1,-.05),A),L.lerp(Db.set(-.54,.12,.02),A),Ee.y+=e,L.y+=e*.85,Ee.x+=e*.2*Ce,L.x+=e*.15*Ce}else oe>.15&&(Ee.lerp(Db.set(.3,-.25,.15),oe*.7),L.lerp(Db.set(-.3,-.22,.15),oe*.7));if(!i&&A<.1){let e=r*1.9+this.walkPhase*.2;Ee.x+=Math.sin(e)*.014,Ee.y+=Math.cos(e*1.3)*.012,L.x+=Math.cos(e*.8)*.012,L.y+=Math.sin(e*1.1)*.013;let t=(r*.27+(c>0?0:.5))%1,n=Eb(.86,.9,t)*(1-Eb(.9,.97,t));this.punchT>=1&&(c>0?Ee.z+=n*.12:L.z+=n*.12)}if(this.punchT<1&&this.punchKind!==null&&A<.85){let{windup:e,extend:r}=Sb(this.punchKind,this.punchT,this.actionStartupFrac,this.actionActiveFrac),i=r*(1-A),a=t.is_downed?-1.2:t.defense===`weave`?-.24:-.03;this.opponentDrop=wb(this.opponentDrop,a,4,n),Rb.set(this.mapping.x(t.x),(this.punchTargetKind===`body`?1.2:1.62)+this.opponentDrop,this.mapping.z(t.y));let o=s.chest.worldToLocal(Lb.copy(Rb)),c=Pb.copy(Cb(this.punchKind,this.punchTargetKind,this.punchPower));if(this.punchKind===`jab`||this.punchKind===`straight`)c.x=o.x*.92,c.y=o.y,c.z=Xl.clamp(o.z,.4,.8);else if(this.punchKind===`hook`){let e=Eb(this.actionStartupFrac*.85,this.actionStartupFrac+this.actionActiveFrac*.75,this.punchT),t=this.punchHand===`left`?1:-1;c.x=Xl.lerp(o.x+.3*t,o.x-.14*t,e),c.z=Math.min(.52,o.z*(.72+.28*Math.sin(e*Math.PI*.5))),c.y=o.y}else if(this.punchKind===`uppercut`){let e=Eb(this.actionStartupFrac*.7,this.actionStartupFrac+this.actionActiveFrac*.5,this.punchT);c.x=o.x*.9,c.y=Xl.lerp(-.26,o.y+.04,e),c.z=Xl.lerp(.24,o.z*.94,e)}let l=Ib.set(0,this.punchKind===`uppercut`?-.22:-.03,this.punchKind===`jab`?-.1:-.16).multiplyScalar(e),u=this.punchHand===`left`?Ee:L,d=this.punchHand===`left`?L:Ee,f=this.punchHand===`left`?-1:1;this.punchKind===`straight`&&d.set(.11*f,.34,.18),this.punchKind===`hook`&&d.set(.1*f,.36,.16),this.punchKind===`uppercut`&&(d.y-=.08);let p=Fb.copy(u).add(l).lerp(c,i);if(this.punchPower===`power`&&Math.abs(this.punchT-(this.actionStartupFrac+this.actionActiveFrac*.5))<.06){let e=(1-Math.abs(this.punchT-(this.actionStartupFrac+this.actionActiveFrac*.5))/.06)*.06;p.addScaledVector(c,e*i)}u.copy(p)}if(e.taunt_ticks>0&&A<.1){let t=(60-e.taunt_ticks)/60*4,n=Math.floor(t)%2==0?1:-1,r=Math.abs(Math.sin(t*Math.PI));Ee.set(Xl.lerp(.28,-.3,r*(n>0?1:.15)),.52+r*.18,.3),L.set(Xl.lerp(-.28,.3,r*(n<0?1:.15)),.46+r*.2,.3),s.hips.rotation.z+=n*r*.14,s.hips.position.y-=r*.035,s.spine.rotation.y+=n*r*.18,s.head.rotation.z+=n*r*.1}Ee.x*=c,L.x*=c;let De=A>.05?9:this.punchT<1?34:26;this.gloveLCurrent.x=wb(this.gloveLCurrent.x,Ee.x,De,n),this.gloveLCurrent.y=wb(this.gloveLCurrent.y,Ee.y,De,n),this.gloveLCurrent.z=wb(this.gloveLCurrent.z,Ee.z,De,n),this.gloveRCurrent.x=wb(this.gloveRCurrent.x,L.x,De,n),this.gloveRCurrent.y=wb(this.gloveRCurrent.y,L.y,De,n),this.gloveRCurrent.z=wb(this.gloveRCurrent.z,L.z,De,n),this.solveArmIK(s.shoulderL,s.elbowL,s.gloveL,this.gloveLCurrent,1,s),this.solveArmIK(s.shoulderR,s.elbowR,s.gloveR,this.gloveRCurrent,-1,s),this.applyTrauma(e,t,a)}poseLegs(e,t,n,r,i,a){let o=this.rig,s=.34*e*(1-t),c=.38*e*(1-t),l=Math.abs(i)>.05?Math.sign(i):0,u=a*e*(1-t),d=-(this.drop+this.kinDrop)*1.35*(1-t),f=this.walkPhase,p=this.walkPhase+Math.PI,m={hip:-.2-d*.5,knee:.34+d,ankle:-.1-d*.5},h={hip:.15-d*.5,knee:.38+d,ankle:-.12-d*.5},g=Math.sin(f)*s*l,_=Math.sin(p)*s*l,v=Math.max(0,Math.sin(f-Math.PI/2))*c,y=Math.max(0,Math.sin(p-Math.PI/2))*c,b=Eb(0,.3,t)*(1-Eb(.32,.62,t)),x=Math.sin(f)*.16*u;o.hipL.rotation.set(Xl.lerp(m.hip+g,-.18,t),.32*r*(1-t)+(this.punchHand===`left`?this.kinPivotL:0)*(1-t),Xl.lerp(.1*u+x,.5*n,t)),o.kneeL.rotation.x=Xl.lerp(m.knee+v+b*.85,.24,Math.max(t,b)),o.ankleL.rotation.x=Xl.lerp(m.ankle-g*.4-(r<0?this.kinHeelR:0)*(1-t),.42,t),o.ankleL.rotation.z=-.08*u-x*.45,o.hipR.rotation.set(Xl.lerp(h.hip+_,-.12,t),-.14*r*(1-t)+(this.punchHand===`right`?this.kinPivotL:0)*(1-t),Xl.lerp(.1*u-x,.35*n,t)),o.kneeR.rotation.x=Xl.lerp(h.knee+y+b*.8,.18,Math.max(t,b)),o.ankleR.rotation.x=Xl.lerp(h.ankle-_*.4-(r>0?this.kinHeelR:0)*(1-t),.42,t),o.ankleR.rotation.z=-.08*u+x*.45}solveArmIK(e,t,n,r,i,a){e.getWorldPosition(Ob),jb.copy(r),a.chest.localToWorld(jb),kb.set(.9*i,-1,-.25).applyQuaternion(a.chest.getWorldQuaternion(zb));let o=this.punchT<1&&(i===1&&this.punchHand===`left`||i===-1&&this.punchHand===`right`);sb(Ob,jb,kb,Ab,o&&this.punchKind===`hook`?.56:o&&this.punchKind===`uppercut`?.58:void 0),db(e,Ob,Ab.elbowWorld),e.updateMatrixWorld(!0),db(t,Ab.elbowWorld,Ab.targetWorld)}applyTrauma(e,t,n){let r=e.trauma,i=e=>Math.min(.85,e/170+r.swelling/420),a=Bb[n];this.rig.bruiseL.material.opacity=i(r.left_eye),this.rig.bruiseR.material.opacity=i(r.right_eye);let o=Math.min(1,r.left_cut/150+r.bleeding/450),s=Math.min(1,r.right_cut/150+r.bleeding/450);this.rig.cutL.material.opacity=o*a,this.rig.cutR.material.opacity=s*a;let c=n===`full`?1.8:1;this.rig.cutL.scale.set(1+o*.55*c,1+o*.7,1),this.rig.cutR.scale.set(1+s*.55*c,1+s*.7,1);let l=e=>Math.min(1.35,e/260+r.swelling/560),u=l(r.left_eye),d=l(r.right_eye);this.rig.swellL.scale.setScalar(.25+u*1.15),this.rig.swellR.scale.setScalar(.25+d*1.15),this.rig.swellL.material.opacity=Math.min(.92,u*1.1),this.rig.swellR.material.opacity=Math.min(.92,d*1.1);let f=Math.min(1,r.head/900+r.swelling/800);this.rig.cheekL.scale.setScalar(.2+f*1.05),this.rig.cheekR.scale.setScalar(.2+f*.95),this.rig.cheekL.material.opacity=f*.8,this.rig.cheekR.material.opacity=f*.75;let p=Math.min(1.9,(r.left_cut+r.bleeding)/220),m=Math.min(1.9,(r.right_cut+r.bleeding)/220);this.rig.streakL.scale.set(c,.15+p*c,1),this.rig.streakR.scale.set(c,.15+m*c,1),this.rig.streakL.material.opacity=Math.min(1,p)*a,this.rig.streakR.material.opacity=Math.min(1,m)*a;let h=Math.min(1.6,r.head/600+r.bleeding/340);this.rig.noseStreak.scale.set(c,.2+h*c,1),this.rig.noseStreak.material.opacity=Math.min(1,h)*a;let g=Math.min(1,r.head/650+r.bleeding/360);this.rig.mouthBlood.scale.set(1+g*c,1+g*.8,1),this.rig.mouthBlood.material.opacity=g*a;let _=Math.min(1,r.body/750);this.rig.ribL.scale.set(.5+_*.35,1.2+_*.5,.7+_*.2),this.rig.ribR.scale.set(.5+_*.3,1.2+_*.4,.7+_*.2),this.rig.ribL.material.opacity=_*.85,this.rig.ribR.material.opacity=_*.8;let v=Math.min(1,(t.trauma.bleeding+t.trauma.left_cut+t.trauma.right_cut)/620*(n===`off`?0:n===`reduced`?.3:1.5));this.rig.gloveLMaterial.color.copy(this.rig.gloveBaseColor).lerp(Vb,v);let y=Math.min(1.5,r.body/450+r.bleeding/340);this.rig.bodyStreak.scale.set(1+y*.55*c,.3+y*c,1),this.rig.bodyStreak.material.opacity=Math.min(1,y)*a,this.rig.bodyBruise.material.opacity=Math.min(.7,r.body/950);let b=1+Math.min(.12,r.swelling/2500);this.rig.headMesh.scale.set(.92*b,1.05*b,.95*b);let x=this.rig.skinMaterial;x.clearcoat=.25+Ub(e)*.4}};function Ub(e){return 1-e.stamina/Math.max(1,e.maximum_stamina)}var Wb=[2765120,3813162,2503738,4206894,3029548,3683390,4471856,5919048,3227722,4863298],Gb=[13081462,9067067,7225640,14726287,5517341,11105359],Kb=e=>()=>(e=Math.imul(e^e>>>15,1|e),e^=e+Math.imul(e^e>>>7,61|e),((e^e>>>14)>>>0)/4294967296);function qb(){let e=new Yu;e.name=`arena`;let t=[],n=[],r=[],i=new Em({color:`#05070c`,roughness:.95});n.push(i);let a=new Np(30,40);t.push(a);let o=new Q(a,i);o.rotation.x=-Math.PI/2,o.position.y=-1,o.receiveShadow=!0,e.add(o);let s=Kb(20260727),c=[{radius:8.2,y:-.55,count:120,scale:1},{radius:10.6,y:.35,count:150,scale:1.04},{radius:13.2,y:1.35,count:180,scale:1.08},{radius:16,y:2.45,count:210,scale:1.12}],l=c.reduce((e,t)=>e+t.count,0),u=new Mp(.19,.5,4,8),d=new mm(.115,8,7);t.push(u,d);let f=new Em({roughness:.9,metalness:0}),p=new Em({roughness:.75,metalness:0});n.push(f,p);let m=new Xf(u,f,l),h=new Xf(d,p,l);m.instanceMatrix.setUsage(ul),h.instanceMatrix.setUsage(ul);let g=new xu,_=new Z,v=new Float32Array(l),y=[],b=0;for(let e of c)for(let t=0;t{if(!n){let n=Math.floor(e*30%l);for(let t=0;t<90;t+=1){let r=(n+t)%l,i=y[r],a=Math.sin(e*1.6+v[r])*.05,o=Math.abs(Math.sin(e*2.3+v[r]*1.7))*.05;fe.setFromAxisAngle(me,i.yaw+a),j.compose(M.set(i.x,i.y+.45*i.scale+o,i.z+a*.4),fe,pe.set(i.scale,i.scale,i.scale)),m.setMatrixAt(r,j),fe.setFromAxisAngle(me,i.yaw+a*1.2),j.compose(M.set(i.x,i.y+.95*i.scale+o*1.2,i.z+a*.5),fe,pe),h.setMatrixAt(r,j)}m.instanceMatrix.needsUpdate=!0,h.instanceMatrix.needsUpdate=!0,ue-=t,ue<=0&&(de=.09+Math.random()*.08,ue=.25+Math.random()*1.6),de=Math.max(0,de-t),C.opacity=de>0?.85:0}},dispose:()=>{for(let e of t)e.dispose();for(let e of n)e.dispose();for(let e of r)e.dispose();m.dispose(),h.dispose()}}}var Jb=1.88,Yb=7.15,Xb=1.12,Zb=class{current=new X(0,Jb,Yb);look=new X(0,Xb,0);swayPhase=0;update(e,t,n,r,i,a,o,s){this.swayPhase+=e;let c=(n.x+r.x)/2,l=(n.z+r.z)/2,u=Xl.clamp(c,-1.4,1.4),d=Xl.clamp(l,-1.1,1.1),f=Xl.clamp(Yb+i*.42-(a?1.1:0),6.4,9.8),p=Jb+i*.1-(a?.35:0),m=s?0:Math.sin(this.swayPhase*.21)*.35,h=s?0:Math.sin(this.swayPhase*.13)*.3,g=u*.32+m,_=f+d*.2,v=p+h*.2;if(this.current.x+=(g-this.current.x)*(1-Math.exp(-2.6*e)),this.current.y+=(v-this.current.y)*(1-Math.exp(-2.6*e)),this.current.z+=(_-this.current.z)*(1-Math.exp(-2.6*e)),this.look.x+=(u-this.look.x)*(1-Math.exp(-3.2*e)),this.look.y+=((a?.75:Xb)-this.look.y)*(1-Math.exp(-3.2*e)),this.look.z+=(d*.6-this.look.z)*(1-Math.exp(-3.2*e)),!s&&o>5e-4){let e=t*61;this.current.x+=Math.sin(e*1.31)*o,this.current.y+=Math.cos(e*1.97)*o*.6,this.look.x+=Math.sin(e*1.53)*o*.5,this.look.y+=Math.cos(e*2.11)*o*.35}return{position:this.current,lookAt:this.look}}},Qb=3.05,$b=3.85,ex=4.05,tx=3.42,nx=[.5,.88,1.26];function rx(e){let t=Qb/Math.max(1,e.ring_half_width),n=Qb/Math.max(1,e.ring_half_height);return{x:e=>e*t,z:e=>-e*n}}var ix={blue:1920728,red:12131356,neutral:15067115},ax=[{skin:11563071,skinShadow:9065520,trunks:1327211,trunkTrim:14267484,glove:1920728,gloveTrim:15067115,hair:1643537,shoe:2240573},{skin:7225640,skinShadow:5582877,trunks:7017504,trunkTrim:15067115,glove:12131356,gloveTrim:14267484,hair:854794,shoe:2956316}],ox=900,sx=90,cx=48,lx=48,ux=2,dx=4,fx=24,px=16,mx=.12,hx=.085,gx=.05,_x=1/60,vx=e=>()=>(e=Math.imul(e^e>>>15,1|e),e^=e+Math.imul(e^e>>>7,61|e),((e^e>>>14)>>>0)/4294967296),yx=(e,t=0)=>Number.isFinite(e)?e:t,bx=e=>Number.isFinite(e)?Xl.clamp(e,0,gx):0,xx=new Set([`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`,`knockdown`,`bleed`]);function Sx(e){if(e.kind===`bleed`)return`ooze`;if(e.kind===`knockdown`)return`impact`;let t=e.detail.split(`:`);if(t.at(-1)===`body`)return`body_burst`;let n=t.find(e=>[`jab`,`straight`,`hook`,`uppercut`].includes(e));return n===`hook`?`fan`:n===`uppercut`?`plume`:`jet`}function Cx(e,t){e.set(yx(t.x),yx(t.y),yx(t.z),yx(t.w,1)),e.lengthSq()<1e-6?e.identity():e.normalize()}function wx(){let e=document.createElement(`canvas`);e.width=64,e.height=64;let t=e.getContext(`2d`);if(t!==null){let e=t.createRadialGradient(32,32,2,32,32,30);e.addColorStop(0,`rgba(120,10,16,0.72)`),e.addColorStop(.5,`rgba(90,8,14,0.36)`),e.addColorStop(1,`rgba(70,6,10,0)`),t.fillStyle=e,t.fillRect(0,0,64,64)}return new Dp(e)}var Tx=class{scene;points;droplets=[];dropletPositions;dropletColors;dropletGeometry;dropletMaterial;dropletIndex=0;mistPoints;mists=[];mistPositions;mistColors;mistGeometry;mistMaterial;mistMap;mistIndex=0;decals=[];decalGeometry;decalIndex=0;gibGeometry;gibMaterial;gibMesh;gibs=[];gibIndex=0;gibMatrix=new xu;gibPosition=new X;gibQuaternion=new Zl;gibEuler=new ju;gibScale=new X;headGeometry;headMaterials=[];heads=[];handGeometry;handMaterials=[];hands=[];stumpGeometry;wristStumpGeometry;stumpMaterial;stumps=[];handStumps=[];lastDecapitationEvent=[null,null];lastDismembermentEvent=Array(dx).fill(null);dripEmitters=[{position:new X,active:!1,rate:0,accumulator:0},{position:new X,active:!1,rate:0,accumulator:0}];simulationRemainder=0;ambientSeed=1597463007;shake=0;bloodLevel=`full`;constructor(e){this.scene=e,this.dropletPositions=new Float32Array(ox*3),this.dropletColors=new Float32Array(ox*3),this.dropletGeometry=new Qd,this.dropletGeometry.setAttribute(`position`,new Ld(this.dropletPositions,3)),this.dropletGeometry.setAttribute(`color`,new Ld(this.dropletColors,3)),this.dropletMaterial=new yp({size:.038,vertexColors:!0,transparent:!0,opacity:.96,depthWrite:!1,sizeAttenuation:!0}),this.points=new wp(this.dropletGeometry,this.dropletMaterial),this.points.frustumCulled=!1,e.add(this.points);for(let e=0;ee.alive).length}get liveBloodParticles(){return this.droplets.filter(e=>e.alive&&e.blood).length}get liveMist(){return this.mists.filter(e=>e.alive).length}get visibleDecals(){return this.decals.filter(e=>e.visible).length}get liveGibs(){return this.gibs.filter(e=>e.alive).length}get activeHeads(){return this.heads.filter(e=>e.active).length}get activeHands(){return this.hands.filter(e=>e.active).length}get activeStumps(){return[...this.stumps,...this.handStumps].filter(e=>e.active).length}spawnDroplet(e,t,n,r,i,a,o,s,c){let l=this.dropletIndex%ox;this.dropletIndex+=1;let u=this.droplets[l];u.alive=!0,u.blood=c,u.x=yx(e),u.y=yx(t,1),u.z=yx(n),u.vx=yx(r),u.vy=yx(i),u.vz=yx(a),u.maxLife=Math.max(.05,yx(s,.5)),u.life=u.maxLife,u.r=yx(o.r,.5),u.g=yx(o.g,.04),u.b=yx(o.b,.06),this.dropletPositions[l*3]=u.x,this.dropletPositions[l*3+1]=u.y,this.dropletPositions[l*3+2]=u.z,this.dropletColors[l*3]=u.r,this.dropletColors[l*3+1]=u.g,this.dropletColors[l*3+2]=u.b,this.dropletGeometry.attributes.position.needsUpdate=!0,this.dropletGeometry.attributes.color.needsUpdate=!0}spawnMist(e,t,n,r,i){let a=this.mistIndex%sx;this.mistIndex+=1;let o=this.mists[a];o.alive=!0,o.x=yx(e),o.y=yx(t,1),o.z=yx(n),o.maxLife=Math.max(.05,yx(i,.5)),o.life=o.maxLife,o.scale=Math.max(.1,yx(r,1)),this.mistPositions[a*3]=o.x,this.mistPositions[a*3+1]=o.y,this.mistPositions[a*3+2]=o.z,this.mistColors[a*3]=.6*o.scale,this.mistColors[a*3+1]=.07*o.scale,this.mistColors[a*3+2]=.08*o.scale,this.mistGeometry.attributes.position.needsUpdate=!0,this.mistGeometry.attributes.color.needsUpdate=!0}placeDecal(e,t,n,r,i,a,o){let s=this.decals[this.decalIndex%cx];this.decalIndex+=1,s.visible=!0,s.position.x=yx(e),s.position.z=yx(t),s.rotation.z=yx(i),s.scale.set(Math.max(.01,yx(n,.2)),Math.max(.01,yx(r,.15)),1);let c=s.material;c.opacity=Xl.clamp(yx(a,.4),0,1),c.color.setHex(o)}ambientRandom(){return this.ambientSeed=Math.imul(this.ambientSeed^this.ambientSeed>>>15,1|this.ambientSeed),this.ambientSeed^=this.ambientSeed+Math.imul(this.ambientSeed^this.ambientSeed>>>7,61|this.ambientSeed),((this.ambientSeed^this.ambientSeed>>>14)>>>0)/4294967296}splatter(e,t,n,r=()=>this.ambientRandom()){if(this.bloodLevel===`off`)return;let i=this.bloodLevel===`reduced`,a=i?3:12,o=i?.35:1;for(let s=0;sthis.ambientRandom()){if(this.bloodLevel===`off`)return;let i=this.bloodLevel===`reduced`,a=i?.35:1;if(this.placeDecal(e,t,2.8*n*a,2*n*a,r()*Math.PI,.56*a,4523529),!i)for(let n=0;n<3;n+=1){let n=r()*Math.PI*2,i=.18+r()*.32;this.placeDecal(e+Math.sin(n)*i,t+Math.cos(n)*i,.45+r()*.55,.22+r()*.38,r()*Math.PI,.38+r()*.18,6425104)}}addEvent(e,t,n){if(!xx.has(e.kind))return;let r=vx(e.event_id*7919+17),i=e.kind===`block`||e.kind===`perfect_block`,a=Sx(e),o=e.direction<0?-1:1,s={x:yx(t.x),y:e.detail.endsWith(`:body`)?1.05:1.58,z:yx(t.z)},c=n?0:Math.round((i?6:16)+Math.min(20,Math.max(0,e.amount)/20)),l=n||e.blood<=0||this.bloodLevel===`off`?0:this.bloodLevel===`reduced`?Math.min(24,Math.round(e.blood*.24)):Math.min(160,Math.round(e.blood*1.4));this.shake=Math.min(.09,this.shake+(i?.008:Math.max(.012,e.amount/2600))),e.kind===`knockdown`&&(this.shake=Math.min(.14,this.shake+.06));for(let t=0;t0&&this.bloodLevel!==`off`&&(e.amount>190||e.kind===`knockdown`||e.kind===`counter_hit`)){let t=this.bloodLevel===`reduced`?e.kind===`knockdown`?3:2:e.kind===`knockdown`?14:10,n=this.bloodLevel===`reduced`?.35:1;for(let e=0;e6&&this.bloodLevel!==`off`&&this.splatter(s.x+(r()-.5)*.6,s.z+(r()-.5)*.6,1+Math.min(2,e.blood/55),r),this.bloodLevel===`full`&&!n&&e.blood>=40&&[`hit`,`counter_hit`,`knockdown`].includes(e.kind)){let t=Math.min(12,Math.max(4,Math.round(e.blood/9)));for(let n=0;n=ux)return;let o=Math.trunc(e),s=Number.isSafeInteger(i)?i:0,c=this.heads[o];if(c.active||this.lastDecapitationEvent[o]===s)return;let l=vx(s*104729+o*8191+23),u=r<0?-1:1;this.lastDecapitationEvent[o]=s,c.active=!0,c.moving=!0,c.eventId=s,c.vx=u*(1.8+l()*1.1),c.vy=2.3+l()*1.1,c.vz=(l()-.5)*2.2,c.vrx=(l()-.5)*12,c.vry=(l()-.5)*12,c.vrz=(l()-.5)*12,c.bounces=0,c.stained=!1,c.mesh.position.set(yx(t.x),yx(t.y,1.55),yx(t.z)),Cx(c.mesh.quaternion,n),c.mesh.material.color.setHex(a),c.mesh.visible=!0;let d=this.stumps[o];d.active=!0,d.fountainLife=1.25,d.accumulator=0,d.seed=s|1,d.direction=u,d.mesh.position.copy(c.mesh.position),d.mesh.quaternion.copy(c.mesh.quaternion),d.mesh.visible=!0;for(let e=0;e=ux)return;let s=Math.trunc(e)*2+(t===`left`?0:1),c=Number.isSafeInteger(a)?a:0,l=this.hands[s];if(l.active||this.lastDismembermentEvent[s]===c)return;let u=vx(c*130363+s*12289+37),d=i<0?-1:1;this.lastDismembermentEvent[s]=c,l.active=!0,l.moving=!0,l.eventId=c,l.vx=d*(1.3+u()*1.1),l.vy=1.5+u()*1.2,l.vz=(u()-.5)*1.8,l.vrx=(u()-.5)*16,l.vry=(u()-.5)*16,l.vrz=(u()-.5)*16,l.bounces=0,l.stained=!1,l.mesh.position.set(yx(n.x),yx(n.y,1.25),yx(n.z)),Cx(l.mesh.quaternion,r),l.mesh.material.color.setHex(o),l.mesh.visible=!0;let f=this.handStumps[s];f.active=!0,f.fountainLife=.9,f.accumulator=0,f.seed=c|1,f.direction=d,f.mesh.position.copy(l.mesh.position),f.mesh.quaternion.copy(l.mesh.quaternion),f.mesh.visible=!0;for(let e=0;e=ux)return;let i=Math.trunc(e)*2+(t===`left`?0:1),a=this.handStumps[i];a.active&&(a.mesh.position.set(yx(n.x),yx(n.y,1.2),yx(n.z)),Cx(a.mesh.quaternion,r))}anchorStump(e,t,n){if(this.bloodLevel!==`full`||e<0||e>=ux)return;let r=this.stumps[Math.trunc(e)];r.active&&(r.mesh.position.set(yx(t.x),yx(t.y,1.5),yx(t.z)),Cx(r.mesh.quaternion,n))}restoreFighter(e){if(e<0||e>=ux)return;let t=Math.trunc(e),n=this.heads[t];n.active=!1,n.moving=!1,n.mesh.visible=!1,n.mesh.position.y=-50;let r=this.stumps[t];r.active=!1,r.fountainLife=0,r.accumulator=0,r.mesh.visible=!1,r.mesh.position.y=-50;for(let e of[t*2,t*2+1]){let t=this.hands[e];t.active=!1,t.moving=!1,t.mesh.visible=!1,t.mesh.position.y=-50;let n=this.handStumps[e];n.active=!1,n.fountainLife=0,n.accumulator=0,n.mesh.visible=!1,n.mesh.position.y=-50}}drip(e,t,n,r=0){let i=+(r===1);if(this.bloodLevel===`off`||n||t<=.05){this.stopDrip(i);return}let a=this.dripEmitters[i];a.position.set(yx(e.x),yx(e.y,1.5),yx(e.z)),a.rate=this.bloodLevel===`reduced`?Math.min(3,t*3):Math.min(18,t*14),a.active=!0}stopDrip(e){let t=this.dripEmitters[+(e===1)];t.active=!1,t.rate=0,t.accumulator=0}updateDripEmitters(e){for(let t of this.dripEmitters)if(t.active)for(t.accumulator+=e*t.rate;t.accumulator>=1;)--t.accumulator,this.spawnDroplet(t.position.x+(this.ambientRandom()-.5)*.14,t.position.y-.04,t.position.z+(this.ambientRandom()-.5)*.1,(this.ambientRandom()-.5)*.08,-.25-this.ambientRandom()*.4,(this.ambientRandom()-.5)*.08,{r:.5,g:.04,b:.06},1.1,!0)}spawnGib(e,t,n,r,i,a,o){let s=this.gibIndex%lx;this.gibIndex+=1;let c=this.gibs[s];c.alive=!0,c.x=yx(e),c.y=yx(t,1.5),c.z=yx(n),c.vx=yx(r),c.vy=yx(i),c.vz=yx(a),c.rx=o()*Math.PI*2,c.ry=o()*Math.PI*2,c.rz=o()*Math.PI*2,c.vrx=(o()-.5)*18,c.vry=(o()-.5)*18,c.vrz=(o()-.5)*18,c.life=1.8+o()*1.2,c.scale=.55+o()*1.2,c.bounces=0,c.stained=!1,this.writeGibMatrix(s,c),this.gibMesh.instanceMatrix.needsUpdate=!0}writeGibMatrix(e,t){t.alive?(this.gibPosition.set(t.x,t.y,t.z),this.gibEuler.set(t.rx,t.ry,t.rz),this.gibQuaternion.setFromEuler(this.gibEuler),this.gibScale.setScalar(t.scale)):(this.gibPosition.set(0,-50,0),this.gibQuaternion.identity(),this.gibScale.setScalar(0)),this.gibMatrix.compose(this.gibPosition,this.gibQuaternion,this.gibScale),this.gibMesh.setMatrixAt(e,this.gibMatrix)}updateGibs(e){let t=!1;for(let[n,r]of this.gibs.entries())if(r.alive){if(t=!0,r.life-=e,r.life<=0){r.alive=!1,this.writeGibMatrix(n,r);continue}r.vy-=6.4*e,r.x+=r.vx*e,r.y+=r.vy*e,r.z+=r.vz*e,r.rx+=r.vrx*e,r.ry+=r.vry*e,r.rz+=r.vrz*e,this.confineGib(r),r.y<=.015&&(r.y=.015,!r.stained&&this.bloodLevel===`full`&&(r.stained=!0,this.placeDecal(r.x,r.z,.24+r.scale*.16,.14+r.scale*.1,r.rz,.42,6425104)),r.bounces===0&&Math.abs(r.vy)>.35?(r.bounces=1,r.vy=Math.abs(r.vy)*.3,r.vx*=.68,r.vz*=.68,r.vrx*=.7,r.vry*=.7,r.vrz*=.7):r.alive=!1),this.writeGibMatrix(n,r)}t&&(this.gibMesh.instanceMatrix.needsUpdate=!0)}confineGib(e){Math.abs(e.x)>3.05&&(e.x=Math.sign(e.x)*Qb,e.vx*=-.45),Math.abs(e.z)>3.05&&(e.z=Math.sign(e.z)*Qb,e.vz*=-.45)}updateDetachedParts(e,t){for(let n of e)if(!(!n.active||!n.moving)){if(n.vy-=5.8*t,n.mesh.position.x+=n.vx*t,n.mesh.position.y+=n.vy*t,n.mesh.position.z+=n.vz*t,n.mesh.rotation.x+=n.vrx*t,n.mesh.rotation.y+=n.vry*t,n.mesh.rotation.z+=n.vrz*t,Math.abs(n.mesh.position.x)>3.05&&(n.mesh.position.x=Math.sign(n.mesh.position.x)*Qb,n.vx*=-.42),Math.abs(n.mesh.position.z)>3.05&&(n.mesh.position.z=Math.sign(n.mesh.position.z)*Qb,n.vz*=-.42),n.mesh.position.y<=0+n.radius){if(n.mesh.position.y=0+n.radius,!n.stained&&this.bloodLevel===`full`){n.stained=!0;let e=n.radius===mx?1:.55;this.placeDecal(n.mesh.position.x,n.mesh.position.z,1.3*e,.9*e,n.mesh.rotation.z,.58,4392199)}n.bounces<2&&Math.abs(n.vy)>.42?(n.bounces+=1,n.vy=Math.abs(n.vy)*.32,n.vx*=.62,n.vz*=.62,n.vrx*=.65,n.vry*=.65,n.vrz*=.65):(n.moving=!1,n.vx=0,n.vy=0,n.vz=0,n.vrx=0,n.vry=0,n.vrz=0)}(!Number.isFinite(n.mesh.position.x)||!Number.isFinite(n.mesh.position.y)||!Number.isFinite(n.mesh.position.z)||!Number.isFinite(n.mesh.quaternion.x)||!Number.isFinite(n.mesh.quaternion.y)||!Number.isFinite(n.mesh.quaternion.z)||!Number.isFinite(n.mesh.quaternion.w))&&(n.mesh.position.set(0,0+n.radius,0),n.mesh.quaternion.identity(),n.moving=!1,n.vx=0,n.vy=0,n.vz=0)}}stumpRandom(e){let t=e.seed|0;return t=Math.imul(t^t>>>15,1|t),t^=t+Math.imul(t^t>>>7,61|t),e.seed=t|0,((t^t>>>14)>>>0)/4294967296}updateStumpFountains(e){if(this.bloodLevel===`full`){for(let t of[...this.stumps,...this.handStumps])if(!(!t.active||t.fountainLife<=0))for(t.fountainLife=Math.max(0,t.fountainLife-e),t.accumulator+=e*36;t.accumulator>=1;){--t.accumulator;let e=this.stumpRandom(t),n=this.stumpRandom(t),r=this.stumpRandom(t);this.spawnDroplet(t.mesh.position.x+(e-.5)*.08,t.mesh.position.y+.015,t.mesh.position.z+(n-.5)*.08,t.direction*(.35+e*.55),1.3+n*1.45,(r-.5)*.85,{r:.58,g:.025,b:.045},.65+r*.5,!0)}}}update(e){for(this.simulationRemainder+=bx(e);this.simulationRemainder+1e-9>=_x;)this.simulationRemainder=Math.max(0,this.simulationRemainder-_x),this.simulate(_x)}simulate(e){this.shake*=.02**e,this.updateDripEmitters(e),this.updateStumpFountains(e),this.updateDetachedParts(this.heads,e),this.updateDetachedParts(this.hands,e),this.updateGibs(e);let t=!1;for(let[n,r]of this.droplets.entries()){if(!r.alive)continue;if(t=!0,r.life-=e,r.life<=0||r.y<0){if(r.y<0&&r.blood&&this.bloodLevel!==`off`&&this.ambientRandom()<(this.bloodLevel===`full`?.48:.18)){let e=this.bloodLevel===`full`?1:.35;this.placeDecal(r.x,r.z,(.22+this.ambientRandom()*.38)*e,(.14+this.ambientRandom()*.24)*e,this.ambientRandom()*Math.PI,.38*e,7212307)}r.alive=!1,this.dropletPositions[n*3+1]=-50;continue}r.vy-=4.6*e,r.x+=r.vx*e,r.y+=r.vy*e,r.z+=r.vz*e;let i=Math.min(1,r.life/(r.maxLife*.4));this.dropletPositions[n*3]=r.x,this.dropletPositions[n*3+1]=r.y,this.dropletPositions[n*3+2]=r.z,this.dropletColors[n*3]=r.r*i,this.dropletColors[n*3+1]=r.g*i,this.dropletColors[n*3+2]=r.b*i}t&&(this.dropletGeometry.attributes.position.needsUpdate=!0,this.dropletGeometry.attributes.color.needsUpdate=!0);let n=!1;for(let[t,r]of this.mists.entries()){if(!r.alive)continue;if(n=!0,r.life-=e,r.life<=0){r.alive=!1,this.mistPositions[t*3+1]=-50;continue}let i=1-r.life/r.maxLife,a=Math.max(0,1-i)*.7*r.scale;this.mistPositions[t*3]=r.x,this.mistPositions[t*3+1]=r.y+i*.14,this.mistPositions[t*3+2]=r.z,this.mistColors[t*3]=a,this.mistColors[t*3+1]=a*.1,this.mistColors[t*3+2]=a*.12}n&&(this.mistGeometry.attributes.position.needsUpdate=!0,this.mistGeometry.attributes.color.needsUpdate=!0)}clearDroplets(e){let t=!1;for(let[n,r]of this.droplets.entries())!r.alive||e&&!r.blood||(r.alive=!1,this.dropletPositions[n*3+1]=-50,t=!0);t&&(this.dropletGeometry.attributes.position.needsUpdate=!0,this.dropletGeometry.attributes.color.needsUpdate=!0)}clearMists(){let e=!1;for(let[t,n]of this.mists.entries())n.alive&&(n.alive=!1,this.mistPositions[t*3+1]=-50,e=!0);e&&(this.mistGeometry.attributes.position.needsUpdate=!0,this.mistGeometry.attributes.color.needsUpdate=!0)}clearGibs(){let e=!1;for(let[t,n]of 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Map,this.primitiveCache={},this.nodeCache={},this.meshCache={refs:{},uses:{}},this.cameraCache={refs:{},uses:{}},this.lightCache={refs:{},uses:{}},this.sourceCache={},this.textureCache={},this.nodeNamesUsed={};let n=!1,r=-1,i=!1,a=-1;if(typeof navigator<`u`&&navigator.userAgent!==void 0){let e=navigator.userAgent;n=/^((?!chrome|android).)*safari/i.test(e)===!0;let t=e.match(/Version\/(\d+)/);r=n&&t?parseInt(t[1],10):-1,i=e.indexOf(`Firefox`)>-1,a=i?e.match(/Firefox\/([0-9]+)\./)[1]:-1}typeof createImageBitmap>`u`||n&&r<17||i&&a<98?this.textureLoader=new ah(this.options.manager):this.textureLoader=new Ah(this.options.manager),this.textureLoader.setCrossOrigin(this.options.crossOrigin),this.textureLoader.setRequestHeader(this.options.requestHeader),this.fileLoader=new 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n=(i.samplers||{})[a.sampler]||{};return t.magFilter=lS[n.magFilter]||1006,t.minFilter=lS[n.minFilter]||1008,t.wrapS=uS[n.wrapS]||1e3,t.wrapT=uS[n.wrapT]||1e3,t.generateMipmaps=!t.isCompressedTexture&&t.minFilter!==1003&&t.minFilter!==1006,r.associations.set(t,{textures:e}),t}).catch(function(){return null});return this.textureCache[s]=c,c}loadImageSource(e,t){let n=this,r=this.json,i=this.options;if(this.sourceCache[e]!==void 0)return this.sourceCache[e].then(e=>e.clone());let a=r.images[e],o=self.URL||self.webkitURL,s=a.uri||``,c=!1;if(a.bufferView!==void 0)s=n.getDependency(`bufferView`,a.bufferView).then(function(e){c=!0;let t=new Blob([e],{type:a.mimeType});return s=o.createObjectURL(t),s});else if(a.uri===void 0)throw Error(`THREE.GLTFLoader: Image `+e+` is missing URI and bufferView`);let l=Promise.resolve(s).then(function(e){return new Promise(function(n,r){let a=n;t.isImageBitmapLoader===!0&&(a=function(e){let t=new 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n=0,o=e.length;n0&&bS(d,i),d.name=t.createUniqueName(i.name||`mesh_`+e),vS(d,i),u.extensions&&_S(r,d,u),t.assignFinalMaterial(d),c.push(d)}for(let n=0,r=c.length;n0){let e=t.userData.pivot,r=n[0];t.pivot=new X().fromArray(e),t.position.x-=e[0],t.position.y-=e[1],t.position.z-=e[2],r.position.set(0,0,0),delete t.userData.pivot}return t})}_loadNodeShallow(e){let t=this.json,n=this.extensions,r=this;if(this.nodeCache[e]!==void 0)return this.nodeCache[e];let i=t.nodes[e],a=i.name?r.createUniqueName(i.name):``,o=[],s=r._invokeOne(function(t){return t.createNodeMesh&&t.createNodeMesh(e)});return s&&o.push(s),i.camera!==void 0&&o.push(r.getDependency(`camera`,i.camera).then(function(e){return r._getNodeRef(r.cameraCache,i.camera,e)})),r._invokeAll(function(t){return t.createNodeAttachment&&t.createNodeAttachment(e)}).forEach(function(e){o.push(e)}),this.nodeCache[e]=Promise.all(o).then(function(t){let o;if(o=i.isBone===!0?new Lf:t.length>1?new Yu:t.length===1?t[0]:new Ju,o!==t[0])for(let e=0,n=t.length;e1){let e=r.associations.get(o);r.associations.set(o,{...e})}return r.associations.get(o).nodes=e,o}),this.nodeCache[e]}loadScene(e){let t=this.extensions,n=this.json.scenes[e],r=this,i=new Yu;n.name&&(i.name=r.createUniqueName(n.name)),vS(i,n),n.extensions&&_S(t,i,n);let a=n.nodes||[],o=[];for(let e=0,t=a.length;e{let t=new Map;for(let[e,n]of r.associations)(e instanceof rf||e instanceof hu)&&t.set(e,n);return e.traverse(e=>{let n=r.associations.get(e);n!=null&&t.set(e,n)}),t})(i),i})}_createAnimationTracks(e,t,n,r,i){let a=[],o=e.name?e.name:e.uuid,s=[];function c(e){e.morphTargetInfluences&&s.push(e.name?e.name:e.uuid)}pS[i.path]===pS.weights?(c(e),e.isGroup&&e.children.forEach(c)):s.push(o);let l;switch(pS[i.path]){case pS.weights:l=Hm;break;case pS.rotation:l=Wm;break;case pS.translation:case pS.scale:l=Km;break;default:switch(n.itemSize){case 1:l=Hm;break;default:l=Km;break}break}let u=r.interpolation===void 0?Yc:mS[r.interpolation],d=this._getArrayFromAccessor(n);for(let e=0,n=s.length;e(PS.set(e,LS(t)),t));return FS.set(e,r),r}function zS(){return Promise.all(Object.keys(jS).map(RS))}async function BS(){let e=Uint8Array.from(atob(kS),e=>e.charCodeAt(0)),t=new Response(e).body;if(t===null)throw Error(`fighter_glb_stream_unavailable`);return new Response(t.pipeThrough(new DecompressionStream(`gzip`))).arrayBuffer()}function VS(){if(IS===null){let e=BS().then(e=>new Promise((t,n)=>{new kx().parse(e,``,t,e=>n(e instanceof Error?e:Error(String(e))))}));IS=Promise.all([e,zS()]).then(([e])=>e)}return IS}function HS(e){let t=PS.get(e);if(t!==void 0)return t;let n=LS(new ah().load(jS[e]));return PS.set(e,n),n}function US(e,t){let n=[],r=[],i=new Map,a=null;if(e.traverse(e=>{if(!(e instanceof If)||Array.isArray(e.material))return;let o=e.material.name,s=NS[o];if(s===void 0)throw Error(`fighter GLB has unsupported material ${o}`);let c=i.get(o);if(c===void 0){let e=o===`MHeadMat0`||o===`MBodyMat0`,l=o===`GlovesMat0`||o===`PantsMat0`?t.gear:16777215;c=e?new Dm({map:HS(s),color:l,roughness:.58,metalness:.02,clearcoat:.25,clearcoatRoughness:.6}):new Em({map:HS(s),color:l,roughness:.4,metalness:.03}),c.name=o,i.set(o,c),r.push(c),c instanceof Dm&&n.push(c),o===`GlovesMat0`&&(a=c)}e.material=c,e.castShadow=!0,e.receiveShadow=!0,e.frustumCulled=!1}),n.length!==2||a===null||r.length!==5)throw Error(`fighter GLB material contract failed: ${n.length} skin, ${r.length} total`);return{skin:n,gloves:a,owned:r}}var WS=`idle.move_forward.move_backward.move_lateral_left.move_lateral_right.guard_high.guard_low.slip_left.slip_right.weave.pull.jab_left.jab_right.straight_left.straight_right.hook_left.hook_right.uppercut_left.uppercut_right.block_head_left.block_head_right.block_body_left.block_body_right.hit_head_left.hit_head_right.hit_body_left.hit_body_right.knockdown.getup.clinch.foul_recovery.stunned.exhausted.taunt`.split(`.`),GS=(e,t,n,r)=>e+(t-e)*(1-Math.exp(-n*r)),KS=(e,t,n,r)=>e+(((t-e+Math.PI)%(Math.PI*2)+Math.PI*2)%(Math.PI*2)-Math.PI)*(1-Math.exp(-n*r)),qS=class{root=new Yu;mixer;actions=new Map;bones=new Map;metrics;skinMaterials;ownedMaterials;gearMaterial;headMeshes=[];handMeshes={left:[],right:[]};decapitated=!1;dismemberedHands={left:!1,right:!1};gearBaseColor;skinBaseColor;overlays;constructor(e,t){let n=Dx(e.scene);n.scale.setScalar(MS),this.root.add(n);let r=US(n,t);this.skinMaterials=r.skin,this.ownedMaterials=r.owned,this.gearMaterial=r.gloves,this.gearBaseColor=new Z(t.gear),this.skinBaseColor=new Z(t.skin),n.traverse(e=>{e instanceof If&&e.name===`BoxerHead`&&this.headMeshes.push(e),e instanceof If&&e.name===`BoxerGloveLeft`&&this.handMeshes.left.push(e),e instanceof If&&e.name===`BoxerGloveRight`&&this.handMeshes.right.push(e),e instanceof Lf&&this.bones.set(e.name,e)});let i=Object.values(AS).filter(e=>!this.bones.has(e));if(i.length>0)throw Error(`fighter GLB missing required bones: ${i.join(`, `)}`);if(this.headMeshes.length!==1)throw Error(`fighter GLB requires one BoxerHead mesh, found ${this.headMeshes.length}`);for(let e of[`left`,`right`])if(this.handMeshes[e].length!==1)throw Error(`fighter GLB requires one ${e} glove mesh, found ${this.handMeshes[e].length}`);this.mixer=new Qh(n);for(let t of e.animations){let e=this.mixer.clipAction(t);this.actions.set(t.name,e),(/^(jab|straight|hook|uppercut|block_|hit_)/.test(t.name)||t.name===`knockdown`||t.name===`getup`||t.name===`taunt`)&&(e.setLoop(Gc,1),e.clampWhenFinished=!0)}let a=WS.filter(e=>!this.actions.has(e));if(a.length>0)throw Error(`fighter GLB missing clips: ${a.join(`, `)}`);n.updateMatrixWorld(!0);let o=(e,t)=>this.bone(e).getWorldPosition(new X).distanceTo(this.bone(t).getWorldPosition(new X));this.metrics={armUpper:o(`shoulderL`,`elbowL`),armFore:o(`elbowL`,`gloveL`),legThigh:o(`hipL`,`kneeL`),legShin:o(`kneeL`,`ankleL`),headRestY:this.bone(`head`).getWorldPosition(new X).y,chestRestY:this.bone(`chest`).getWorldPosition(new X).y,ankleRestY:this.bone(`ankleL`).getWorldPosition(new X).y},this.overlays=YS(this.bone(`head`),this.bone(`chest`),t.skin)}bone(e){return this.bones.get(AS[e]??e)??null}get trauma(){return this.overlays}get gloveGear(){return this.gearMaterial}get skin(){return this.skinMaterials[0]}get isDecapitated(){return this.decapitated}setDecapitated(e){this.decapitated=e;for(let t of this.headMeshes)t.visible=!e;this.bone(`head`).visible=!e}isHandDismembered(e){return this.dismemberedHands[e]}setHandDismembered(e,t){this.dismemberedHands[e]=t;for(let n of this.handMeshes[e])n.visible=!t}setSkinClearcoat(e){for(let t of this.skinMaterials)t.clearcoat=e}dispose(){this.mixer.stopAllAction();for(let e of this.ownedMaterials)e.dispose();this.overlays.dispose()}};function JS(e,t,n=0){let r=new Q(e,new Em({color:t,roughness:.7,transparent:!0,opacity:0,emissive:n}));return r.castShadow=!1,r}function YS(e,t,n){let r=[],i=(e,t,n,i=[1,1,1])=>{let a=t.getWorldScale(new X),o=1/Math.max(1e-4,a.x);return e.position.set(n[0]*1.3*o,n[1]*1.25*o,(n[2]*1.35+.045)*o),e.scale.set(i[0]*o,i[1]*o,i[2]*o),e.userData.baseScale=o,t.add(e),r.push(e),e},a=i(JS(new mm(.042,12,10),4856918),e,[.05,.15,.085],[1,.72,.5]),o=i(JS(new mm(.042,12,10),4856918),e,[-.05,.15,.085],[1,.72,.5]),s=i(JS(new mm(.035,12,10),7026034),e,[.052,.155,.088]),c=i(JS(new mm(.035,12,10),7026034),e,[-.052,.155,.088]),l=i(JS(new jp(.05,.008,.01),8326420,2753286),e,[.05,.178,.104]),u=i(JS(new jp(.05,.008,.01),8326420,2753286),e,[-.05,.178,.104]),d=i(JS(new jp(.014,.1,.006),9047830,3146762),e,[.052,.115,.106]),f=i(JS(new jp(.014,.1,.006),9047830,3146762),e,[-.052,.115,.106]),p=i(JS(new jp(.011,.07,.006),9047830,3146762),e,[.008,.075,.118]),m=i(JS(new jp(.03,.012,.006),9047830,3146762),e,[.02,.052,.104]),h=i(JS(new mm(.028,10,8),7026034),e,[.068,.095,.075]),g=i(JS(new mm(.028,10,8),7026034),e,[-.068,.095,.075]),_=i(JS(new mm(.09,12,10),6038608),t,[.16,.08,.02],[.5,1.2,.7]),v=i(JS(new mm(.09,12,10),6038608),t,[-.16,.08,.02],[.5,1.2,.7]),y=i(JS(new mm(.1,12,10),4856918),t,[.02,.05,.1],[1.05,1.35,.55]),b=i(JS(new jp(.05,.24,.008),9047830,3146762),t,[.03,.08,.155]);b.rotation.z=.12;let x=i(JS(new mm(.06,12,10),n),e,[0,-.005,.07],[1.3,.48,.82]);return x.userData.restPosition=x.position.clone(),{bruiseL:a,bruiseR:o,swellL:s,swellR:c,cutL:l,cutR:u,streakL:d,streakR:f,noseStreak:p,mouthBlood:m,cheekL:h,cheekR:g,ribL:_,ribR:v,bodyBruise:y,bodyStreak:b,jaw:x,dispose(){for(let e of r)e.geometry.dispose(),e.material.dispose(),e.removeFromParent()}}}function XS(e,t,n,r){let i=t.trauma,a=r===`off`?0:r===`reduced`?.35:1,o=r===`full`?1.8:1,s=e=>e.material,c=(e,t,n,r)=>{let i=typeof e.userData.baseScale==`number`?e.userData.baseScale:1;e.scale.set(t*i,n*i,r*i)},l=e=>Math.min(.85,e/170+i.swelling/420);s(e.bruiseL).opacity=l(i.left_eye),s(e.bruiseR).opacity=l(i.right_eye);let u=Math.min(1,i.left_cut/150+i.bleeding/450),d=Math.min(1,i.right_cut/150+i.bleeding/450);s(e.cutL).opacity=u*a,s(e.cutR).opacity=d*a,c(e.cutL,1+u*.55*o,1+u*.7,1),c(e.cutR,1+d*.55*o,1+d*.7,1);let f=Math.min(1.35,i.left_eye/260+i.swelling/560),p=Math.min(1.35,i.right_eye/260+i.swelling/560);c(e.swellL,.25+f*1.15,.25+f*1.15,.25+f*1.15),c(e.swellR,.25+p*1.15,.25+p*1.15,.25+p*1.15),s(e.swellL).opacity=Math.min(.92,f*1.1),s(e.swellR).opacity=Math.min(.92,p*1.1);let m=Math.min(1,i.head/900+i.swelling/800);c(e.cheekL,.2+m*1.05,.2+m*1.05,.2+m*1.05),c(e.cheekR,.2+m*.95,.2+m*.95,.2+m*.95),s(e.cheekL).opacity=m*.8,s(e.cheekR).opacity=m*.75;let h=Math.min(1.9,(i.left_cut+i.bleeding)/220),g=Math.min(1.9,(i.right_cut+i.bleeding)/220);c(e.streakL,o,.15+h*o,1),c(e.streakR,o,.15+g*o,1),s(e.streakL).opacity=Math.min(1,h)*a,s(e.streakR).opacity=Math.min(1,g)*a;let _=Math.min(1.6,i.head/600+i.bleeding/340);c(e.noseStreak,o,.2+_*o,1),s(e.noseStreak).opacity=Math.min(1,_)*a;let v=Math.min(1,i.head/650+i.bleeding/360);c(e.mouthBlood,1+v*o,1+v*.8,1),s(e.mouthBlood).opacity=v*a;let y=Math.min(1,i.body/750);c(e.ribL,.5+y*.35,1.2+y*.5,.7+y*.2),c(e.ribR,.5+y*.3,1.2+y*.4,.7+y*.2),s(e.ribL).opacity=y*.85,s(e.ribR).opacity=y*.8,s(e.bodyBruise).opacity=Math.min(.7,i.body/950);let b=Math.min(1.5,i.body/450+i.bleeding/340);c(e.bodyStreak,1+b*.55*o,.3+b*o,1),s(e.bodyStreak).opacity=Math.min(1,b)*a}var ZS=new Z(6031886),QS=[`idle`,`move_forward`,`move_backward`,`move_lateral_left`,`move_lateral_right`],$S=[`jab_left`,`jab_right`,`straight_left`,`straight_right`,`hook_left`,`hook_right`,`uppercut_left`,`uppercut_right`,`block_head_left`,`block_head_right`,`block_body_left`,`block_body_right`,`hit_head_left`,`hit_head_right`,`hit_body_left`,`hit_body_right`,`knockdown`,`getup`,`clinch`,`foul_recovery`,`stunned`,`exhausted`,`taunt`],eC=(e,t)=>`${e}_${t}`,tC=class{mapping;boxer;yaw=0;rootX=null;rootZ=0;activePunch=null;punchAgeTicks=0;punchTotalTicks=1;punchClass=`jab`;punchHand=`left`;punchTarget=`head`;punchPower=`normal`;punchTiming=Uy(`jab`,`head`,`normal`);actionId=null;completedActionId=null;predictedId=null;predictedAtSeconds=-1;predictionAgeTicks=0;predictedClip=`jab_left`;predictedTotalTicks=13;hitstop=0;reactionAction=null;stateAction=null;stateWeight=0;stateRequested=!1;downState=`up`;fallAge=0;riseAge=0;opponentDrop=0;liveOpponentHead=new X(0,.97,0);hasLiveHead=!1;defenseWeight=0;defenseClip=`guard_high`;hitstopScale=1;plantedL=null;plantedR=null;locomotionWeights={idle:1,move_forward:0,move_backward:0,move_lateral_left:0,move_lateral_right:0};scratchA=new X;scratchB=new X;scratchC=new X;scratchQ=new Zl;aimTarget=new X;aimShoulder=new X;aimTo=new X;aimPole=new X;aimBend=new X;aimElbow=new X;lockAnkle=new X;lockPinned=new X;lockHip=new X;lockTo=new X;lockPole=new X;lockBend=new X;lockKnee=new X;dislocation=null;constructor(e,t){this.mapping=t,this.boxer=e;for(let t of QS){let n=e.actions.get(t);n.setEffectiveWeight(+(t===`idle`)),n.play()}}get currentRoot(){return{x:this.rootX??0,z:this.rootZ}}predict(e,t,n){if(e.kind!==`punch`||e.id===void 0)return;this.predictedId=e.id,this.predictedAtSeconds=t,this.predictionAgeTicks=0,this.predictedClip=eC(e.class,e.hand);let r=Uy(e.class,e.target,e.power);this.punchClass=e.class,this.punchHand=e.hand,this.punchTarget=e.target,this.punchPower=e.power,this.punchTiming=r,this.predictedTotalTicks=Wy(r);let i=this.actionId!==null&&this.punchAgeTicks/this.punchTotalTicks>.55;(this.actionId===null||i)&&(this.actionId=null,this.beginPunch(this.boxer.actions.get(this.predictedClip),this.predictedTotalTicks),this.punchAgeTicks=0)}landedHit(e){this.hitstop=Math.max(this.hitstop,e?.045:.078)}setArcadeDislocation(e){this.dislocation=e;let t=this.boxer.trauma.jaw,n=t.userData.restPosition;t.position.copy(n),t.rotation.set(0,0,0),t.material.opacity=+(e===`jaw`)}react(e,t=`head`,n=1){let r=n<0?`left`:`right`,i=this.boxer.actions.get(`${e}_${t}_${r}`);i!==void 0&&(this.reactionAction!==null&&this.reactionAction!==i&&this.reactionAction.stop(),this.reactionAction=i,i.reset().setLoop(Gc,1),i.setEffectiveWeight(0).play())}setPunch(e,t){let n=e.getClip(),r=Uy(this.punchClass,`head`,`normal`),i=Math.max(1,n.duration*30-r.startup-r.active),a=this.punchTiming,o=Xl.clamp(t,0,Wy(a)),s;if(o<=a.startup)s=a.startup>0?o/a.startup*r.startup:r.startup;else if(o<=a.startup+a.active){let e=o-a.startup;s=r.startup+(a.active>0?e/a.active*r.active:r.active)}else{let e=o-a.startup-a.active;s=r.startup+r.active+(a.recovery>0?e/a.recovery*i:i)}e.time=Xl.clamp(s/30,0,Math.max(.001,n.duration-.001))}beginPunch(e,t){this.activePunch!==null&&this.activePunch!==e&&this.activePunch.stop(),this.activePunch=e,e.reset(),e.setLoop(Gc,1),e.setEffectiveWeight(0).play(),e.paused=!0,this.punchTotalTicks=Math.max(1,t)}update(e,t,n,r,i,a,o,s){let c=this.boxer,l=e.stance===`orthodox`?1:-1,u=this.mapping.x(e.x),d=this.mapping.z(e.y);this.rootX===null&&(this.rootX=u,this.rootZ=d);let f=.05;this.rootX+=Xl.clamp(u-this.rootX,-.05,f),this.rootZ+=Xl.clamp(d-this.rootZ,-.05,f);let p=Math.atan2(this.mapping.x(t.x)-u,(this.mapping.z(t.y)-d)*.45);this.yaw=KS(this.yaw,p,7,n),c.root.position.set(this.rootX,0,this.rootZ),c.root.rotation.set(0,this.yaw+.5*l,0);let m=.82+e.stamina/Math.max(1,e.maximum_stamina)*.18;if(this.hitstop=Math.max(0,this.hitstop-n),this.hitstopScale=this.hitstop>0?.12:1,e.action_id!==null&&e.action_id!==this.actionId&&e.action_id!==this.completedActionId){let t=e.action,n=e.action_hand??(e.stance===`orthodox`?`left`:`right`);if(t!==null){this.actionId=e.action_id,this.punchClass=t,this.punchHand=n,this.punchTarget=e.action_target??`head`,this.punchPower=e.action_power??`normal`,this.punchTiming={...Uy(this.punchClass,this.punchTarget,this.punchPower),startup:e.action_startup_ticks,active:e.action_active_ticks,recovery:e.action_recovery_ticks};let r=Math.max(1,e.action_startup_ticks+e.action_active_ticks+e.action_recovery_ticks);if(this.beginPunch(c.actions.get(eC(t,n)),r),this.punchAgeTicks=Math.max(0,o-e.action_start_tick),this.predictedId===e.action_id){let t=this.predictionAgeTicks,n=o-e.action_start_tick;Math.abs(t-n)>1&&(this.punchAgeTicks=n),this.predictedId=null}else this.punchAgeTicks=Math.max(0,o-e.action_start_tick)}}if(e.action_id===null&&(this.actionId=null,this.completedActionId=null),this.predictedId!==null&&(this.predictionAgeTicks+=n*30*this.hitstopScale,this.predictionAgeTicks>10&&(this.predictedId=null)),this.activePunch!==null){this.punchAgeTicks+=n*30*this.hitstopScale;let e=this.punchTotalTicks;this.setPunch(this.activePunch,this.punchAgeTicks),this.punchAgeTicks>=e&&(this.completedActionId=this.actionId,this.actionId=null,this.activePunch.stop(),this.activePunch=null)}this.reactionAction!==null&&!this.reactionAction.isRunning()&&(this.reactionAction.stop(),this.reactionAction=null);let h=this.mapping.x(e.velocity_x)*30,g=this.mapping.z(e.velocity_y)*30,_=Math.hypot(h,g),v=_>.05,y=Xl.clamp(_/1.1,0,1),b=h*e.facing,x=Math.sign(e.velocity_y)*Math.abs(g),S=Math.abs(b)+Math.abs(x),C={idle:1-y,move_forward:S>0?Math.max(0,b)/S*y:0,move_backward:S>0?Math.max(0,-b)/S*y:0,move_lateral_left:S>0?Math.max(0,-x)/S*y:0,move_lateral_right:S>0?Math.max(0,x)/S*y:0},w=m*Xl.clamp(.35+_/1.1*.65,.35,1.5);for(let e of QS){this.locomotionWeights[e]=GS(this.locomotionWeights[e]??0,C[e],10,n);let t=c.actions.get(e);t.setEffectiveWeight(this.locomotionWeights[e]);let r=e===`idle`?m:w;t.setEffectiveTimeScale(i?Math.min(.4,r):r)}let T=e.defense!==`none`;T&&(this.defenseClip=e.defense),this.defenseWeight=GS(this.defenseWeight,+!!T,12,n);let E=c.actions.get(this.defenseClip);this.defenseWeight>.001&&!E.isRunning()&&E.reset().play();let D=e.is_foul_recovery_target?`foul_recovery`:e.clinch_ticks>0||e.clinch_startup_ticks>0?`clinch`:e.stunned_ticks>0?`stunned`:e.taunt_ticks>0?`taunt`:e.stamina/Math.max(1,e.maximum_stamina)<.16&&!v&&!T?`exhausted`:null,O=D===null?null:c.actions.get(D);O!==null&&O!==this.stateAction&&(this.stateAction?.stop(),this.stateAction=O,this.stateWeight=0,this.stateAction.reset().play()),this.stateRequested=O!==null,this.stateWeight=GS(this.stateWeight,+!!this.stateRequested,14,n),!this.stateRequested&&this.stateWeight<.001&&(this.stateAction?.stop(),this.stateAction=null,this.stateWeight=0);let ee=t.is_downed?-(this.boxer.metrics.headRestY*.88):t.defense===`weave`?-.24:-.03;if(this.opponentDrop=GS(this.opponentDrop,ee,4,n),s!==void 0&&(this.liveOpponentHead.copy(s),this.hasLiveHead=!0),e.is_downed)if(this.activePunch!==null&&(this.activePunch.stop(),this.activePunch=null),this.actionId=null,this.predictedId=null,this.downState===`up`){this.downState=`falling`,this.fallAge=0;let 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Q(_,h);o.position.set(i,.78,a),o.castShadow=!0,r.add(o);let s=new Em({color:g[e],roughness:.55});t.push(s);for(let e of[.62,1.12]){let t=new Q(v,s);t.position.set(i*.985,e,a*.985),t.lookAt(0,e,0),t.castShadow=!0,r.add(t)}}let x=[12131356,15067115,1920728].map(e=>{let n=new Em({color:e,roughness:.42,metalness:.05});return t.push(n),n});for(let n=0;n<4;n+=1){let i=b[n],a=b[(n+1)%4];for(let[n,o]of nx.entries()){let s=i.clone().add(a).multiplyScalar(.5);s.y=o-.045;let c=new cm(new X(i.x,o,i.z),s,new X(a.x,o,a.z)),l=new hm(c,24,.028,8,!1);e.push(l);let u=new Q(l,x[n]);u.castShadow=!0,r.add(u);for(let n of[.33,.66]){let i=c.getPoint(n),a=new jp(.035,.82,.012);e.push(a);let s=new Em({color:14212840,roughness:.6});t.push(s);let l=new Q(a,s);l.position.set(i.x,o-.36,i.z),l.lookAt(0,o-.36,0),r.add(l)}}}return{group:r,materials:t,geometries:e,textures:n}}function SC(e){for(let t of e.geometries)t.dispose();for(let t of e.materials)t.dispose();for(let t of e.textures)t.dispose()}function CC(e,t=2){let n=e.getBoundingClientRect(),r=Math.max(1,Math.round(n.width)),i=Math.max(1,Math.round(n.height)),a=Math.min(t,Math.max(1,window.devicePixelRatio||1));(e.width!==Math.round(r*a)||e.height!==Math.round(i*a))&&(e.width=Math.round(r*a),e.height=Math.round(i*a));let o=e.getContext(`2d`);return o===null?null:(o.setTransform(a,0,0,a,0,0),{context:o,viewport:{width:r,height:i},dpr:a})}function wC(e,t,n){let r=e.detail.endsWith(`:head`)||e.detail.endsWith(`:body`);return t===void 0||![`hit`,`counter_hit`].includes(e.kind)||!r?!1:t.is_downed||n?.finish_method===`flash_ko`&&n.winner_id!==null&&n.winner_id===e.actor_id}function TC(e,t){let n=t.fighters.findIndex(t=>t.player_id===e.target_id),r=t.fighters.findIndex(t=>t.player_id===e.actor_id),i=e.kind===`block`||e.kind===`perfect_block`;return{recipientIndex:i?r:n,puncherIndex:i?n:r}}var EC=e=>e.kind===`hit`||e.kind===`counter_hit`,DC=e=>e.kind===`block`||e.kind===`perfect_block`;function OC(e,t){if(!(!EC(e)||e.action_id===null))return t.find(t=>DC(t)&&t.action_id===e.action_id&&t.actor_id===e.target_id&&t.target_id===e.actor_id)}function kC(e,t){if(!(!DC(e)||e.action_id===null))return t.find(t=>EC(t)&&t.action_id===e.action_id&&t.actor_id===e.target_id&&t.target_id===e.actor_id)}function AC(e,t){return e.map((n,r)=>{let{puncherIndex:i}=TC(n,t),a=t.fighters[i],o=a?.action_key?.split(`:`)??[],s=o.length>=3?`${o[0]}:${o[2]}`:n.detail,c=kC(n,e);if(DC(n))return{event:n,presentationEvent:{...n,detail:c?.detail||s,direction:c?.direction??a?.facing??n.direction,blood:c?.blood??n.blood},presentImpact:!0};if(OC(n,e)!==void 0)return{event:n,presentationEvent:n,presentImpact:!1};if(n.kind===`knockdown`){let t=e.slice(0,r).reverse().find(e=>EC(e)&&e.tick===n.tick&&e.actor_id===n.actor_id&&e.target_id===n.target_id);if(t!==void 0)return{event:n,presentationEvent:{...n,detail:t.detail,direction:t.direction,blood:t.blood,action_id:t.action_id},presentImpact:!0}}return{event:n,presentationEvent:n,presentImpact:!0}})}function jC(e){return e.result===null?e.tick-1:e.tick}function MC(e,t,n,r){if(!wC(e,t,n))return null;let i=Math.abs(e.event_id);if(e.detail.endsWith(`:head`))return i%2==0?`decapitation`:`jaw_dislocation`;let a=r?.action_key?.split(`:`)[1],o=a===`left`?`right`:a===`right`||Math.floor(i/2)%2==0?`left`:`right`;return i%2==0?`dismember_${o}`:`shoulder_${o}`}function NC(){let e=document.createElement(`canvas`);e.width=128,e.height=128;let t=e.getContext(`2d`);if(t!==null){let e=t.createRadialGradient(64,64,8,64,64,62);e.addColorStop(0,`rgba(0,0,0,0.68)`),e.addColorStop(.6,`rgba(0,0,0,0.34)`),e.addColorStop(1,`rgba(0,0,0,0)`),t.fillStyle=e,t.fillRect(0,0,128,128)}return new Dp(e)}var PC={tick_rate:30,ring_half_width:500,ring_half_height:330},FC=class{canvas;simulation;settings;renderer;scene=new id;camera;composer;ring;arena;boxers;referee;refereePosition=new X(.4,0,-2.1);animators;effects;director=new Zb;mapping;buffer=new ws;dedupe=new Ts;hudCanvas;cameraOverride=null;manualClock;blobShadows=[];blobTexture;lights=[];keyLight=null;followSpot=null;sizeCheck=new Y;refereeAway=new X;refereeYaw=0;raf=0;previous=performance.now();players={};viewerId=null;final=null;reconnectMs=0;destroyed=!1;graphs=null;glbLoading=!1;graphsReady=Promise.resolve();headCache=[new X,new X];headCacheValid=[!1,!1];arcadeInjuries=[null,null];observedInjuryDown=[!1,!1];downedPoolAccumulators=[0,0];downedPoolCounts=[0,0];bloodLevel=`full`;pendingContacts=[];onContact=null;onArcadeInjury=null;tmpA=new X;tmpB=new X;tmpHead=new X;tmpHeadQuaternion=new Zl;tmpStump=new X;tmpStumpOffset=new X;tmpStumpQuaternion=new Zl;tmpPart=new X;tmpPartQuaternion=new Zl;constructor(e,t=PC,n,r={}){this.canvas=e,this.simulation=t,this.settings=n,this.manualClock=r.manualClock===!0,this.mapping=rx(t),this.renderer=new Sy({canvas:e,antialias:!0,powerPreference:`high-performance`,preserveDrawingBuffer:r.manualClock===!0}),this.renderer.shadowMap.enabled=!0,this.renderer.shadowMap.type=1,this.renderer.toneMapping=4,this.renderer.toneMappingExposure=.92,this.renderer.setPixelRatio(Math.min(2,window.devicePixelRatio||1)),this.scene.background=new Z(`#04060b`),this.scene.fog=new rd(`#04060b`,.042),this.camera=new yh(38,1,.1,80),this.camera.position.set(0,2.05,7.6),this.camera.lookAt(0,1.1,0),this.setupLights(),this.ring=xC(),this.scene.add(this.ring.group),this.arena=qb(),this.scene.add(this.arena.group),this.effects=new Tx(this.scene),this.boxers=[Qy(ax[0]),Qy(ax[1])],this.animators=[new Hb(this.boxers[0],this.mapping),new Hb(this.boxers[1],this.mapping)],this.boxers[0].root.position.set(-.9,0,0),this.boxers[1].root.position.set(.9,0,0),this.boxers[0].root.rotation.y=Math.PI/2,this.boxers[1].root.rotation.y=-Math.PI/2,this.scene.add(this.boxers[0].root,this.boxers[1].root),this.referee=fb(),this.referee.root.position.copy(this.refereePosition),this.referee.shoulderL.rotation.x=-.42,this.referee.shoulderR.rotation.x=-.42,this.referee.elbowL.rotation.x=-.55,this.referee.elbowR.rotation.x=-.55,this.scene.add(this.referee.root),this.blobTexture=NC();let i=new fm(1,1);for(let e=0;e<3;e+=1){let t=new Q(i,new pf({map:this.blobTexture,transparent:!0,depthWrite:!1}));t.rotation.x=-Math.PI/2,t.position.y=.006+e*4e-4,t.renderOrder=1,this.blobShadows.push(t),this.scene.add(t)}this.composer=new jy(this.renderer),this.composer.addPass(new My(this.scene,this.camera));let a=new Py(new Y(1280,720),.32,.5,.85);this.composer.addPass(a),this.composer.addPass(new Iy),this.hudCanvas=document.createElement(`canvas`),this.hudCanvas.className=`fight-hud`,this.hudCanvas.style.cssText=`position:absolute;inset:0;width:100%;height:100%;pointer-events:none`,e.insertAdjacentElement(`afterend`,this.hudCanvas),this.bloodLevel=n().blood,this.effects.setBloodLevel(this.bloodLevel),this.ensureGraphs(),this.manualClock||(this.raf=requestAnimationFrame(e=>this.draw(e)))}ensureGraphs(){this.glbLoading||this.graphs!==null||new URLSearchParams(window.location.search).get(`procedural`)!==`1`&&(this.glbLoading=!0,this.graphsReady=VS().then(e=>{if(this.destroyed)return;let t=new qS(e,{skin:11563071,gear:1920728}),n=new qS(e,{skin:7225640,gear:12131356});this.graphs=[new tC(t,this.mapping),new tC(n,this.mapping)],this.syncInjuryPresentation(0),this.syncInjuryPresentation(1),this.scene.add(t.root,n.root);for(let e of this.boxers)this.scene.remove(e.root),pb(e)}).catch(e=>{this.glbLoading=!1,console.error(`boxer_glb_load_failed`,e)}))}get ready(){return this.graphsReady}get labRigs(){let e=this.graphs;return e===null?this.boxers.map(e=>e.root):[e[0].boxer.root,e[1].boxer.root]}get labScene(){return this.scene}get labEffects(){return this.effects}labSetCameraOverride(e,t){this.cameraOverride={position:new X(...e),lookAt:new X(...t)}}labFrame(e,t=!0){this.draw(e*1e3,!0,t)}setPlayers(e,t){this.players=e,this.viewerId=t}setFinal(e){this.final=e}setReconnect(e){this.reconnectMs=e}setBloodLevel(e){e!==`full`&&this.bloodLevel===`full`&&this.restoreAllInjuries(),this.bloodLevel=e,e===`off`&&this.downedPoolAccumulators.fill(0),this.effects.setBloodLevel(e)}setReducedMotion(e){e&&(this.restoreAllInjuries(),this.effects.clearDynamic())}syncInjuryPresentation(e){let t=this.arcadeInjuries[e],n=this.graphs;if(n!==null){let r=n[e];r.boxer.setDecapitated(t===`decapitation`),r.boxer.setHandDismembered(`left`,t===`dismember_left`),r.boxer.setHandDismembered(`right`,t===`dismember_right`);let i=t===`jaw_dislocation`?`jaw`:t===`shoulder_left`||t===`shoulder_right`?t:null;r.setArcadeDislocation(i);return}let r=this.boxers[e];r.head.visible=t!==`decapitation`,r.gloveLMesh.visible=t!==`dismember_left`,r.gloveRMesh.visible=t!==`dismember_right`}restoreInjury(e){this.arcadeInjuries[e]!==null&&(this.arcadeInjuries[e]=null,this.observedInjuryDown[e]=!1,this.syncInjuryPresentation(e),this.effects.restoreFighter(e))}restoreAllInjuries(){this.restoreInjury(0),this.restoreInjury(1),this.effects.clearArcadeGore()}headWorldPose(e){let t=this.graphs,n=t===null?this.boxers[e].head:t[e].boxer.bone(`head`);return n===null?null:(t===null?this.boxers[e].root.updateMatrixWorld(!0):t[e].boxer.root.updateMatrixWorld(!0),n.getWorldPosition(this.tmpHead),n.getWorldQuaternion(this.tmpHeadQuaternion),this.tmpStumpOffset.set(0,.12,.02).applyQuaternion(this.tmpHeadQuaternion),this.tmpHead.add(this.tmpStumpOffset),{position:this.tmpHead,quaternion:this.tmpHeadQuaternion})}handWorldPose(e,t){let n=this.graphs,r=n===null?t===`left`?this.boxers[e].gloveL:this.boxers[e].gloveR:n[e].boxer.bone(t===`left`?`gloveL`:`gloveR`);return r===null?null:(n===null?this.boxers[e].root.updateMatrixWorld(!0):n[e].boxer.root.updateMatrixWorld(!0),r.getWorldPosition(this.tmpPart),r.getWorldQuaternion(this.tmpPartQuaternion),{position:this.tmpPart,quaternion:this.tmpPartQuaternion})}gearColor(e){let t=this.graphs;return t===null?this.boxers[e].gloveBaseColor.getHex():t[e].boxer.gearBaseColor.getHex()}skinColor(e){let t=this.graphs;return t===null?this.boxers[e].skinMaterial.color.getHex():t[e].boxer.skinBaseColor.getHex()}stumpWorldPose(e){let t=this.graphs,n=t===null?this.boxers[e].head:t[e].boxer.bone(`Neck_012`);return n===null?null:(t===null?this.boxers[e].root.updateMatrixWorld(!0):t[e].boxer.root.updateMatrixWorld(!0),n.getWorldPosition(this.tmpStump),n.getWorldQuaternion(this.tmpStumpQuaternion),t===null&&(this.tmpStumpOffset.set(0,-.085,0).applyQuaternion(this.tmpStumpQuaternion),this.tmpStump.add(this.tmpStumpOffset)),{position:this.tmpStump,quaternion:this.tmpStumpQuaternion})}predictAction(e){let t=this.buffer.latest();if(t===null||this.viewerId===null)return;let n=t.fighters.findIndex(e=>e.player_id===this.viewerId);if(n<0)return;let r=this.graphs;r===null?this.animators[n].predict(e,performance.now()/1e3,this.simulation.tick_rate):r[n].predict(e,performance.now()/1e3,this.simulation.tick_rate)}push(e){if(!this.buffer.push(e))return;let t=this.dedupe.accept(e.events);for(let{event:n,presentationEvent:r,presentImpact:i}of AC(t,e)){let t=e.fighters.findIndex(e=>e.player_id===n.target_id),a=e.fighters.findIndex(e=>e.player_id===n.actor_id),{recipientIndex:o,puncherIndex:s}=TC(n,e),c=e.fighters[o]??e.fighters[t]??e.fighters[a]??e.fighters[0];if(this.tmpA.set(this.mapping.x(c.x),0,this.mapping.z(c.y)),[`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`,`knockdown`].includes(n.kind)){let t=s>=0?e.fighters[s]:null;this.pendingContacts.push({event:n,presentationEvent:r,presentImpact:i,contactTick:t?.action_contact_tick??n.tick,recipientIndex:o,puncherIndex:s,injury:MC(n,e.fighters[o],e.result,t??void 0)})}else n.kind===`bleed`&&this.effects.addEvent(n,this.tmpA,this.settings().reducedMotion)}}fireContacts(e){for(let t=0;te){t+=1;continue}this.pendingContacts.splice(t,1);let{event:r,presentationEvent:i,presentImpact:a,recipientIndex:o,puncherIndex:s,injury:c}=n,l=this.buffer.latest()?.fighters[o];a&&l!==void 0&&(this.tmpA.set(this.mapping.x(l.x),0,this.mapping.z(l.y)),this.effects.addEvent(i,this.tmpA,this.settings().reducedMotion));let u=this.settings();if(c!==null&&o>=0&&this.arcadeInjuries[o]===null&&u.blood===`full`&&!u.reducedMotion){let e=this.graphs!==null&&(c===`jaw_dislocation`||c===`shoulder_left`||c===`shoulder_right`);if(c===`decapitation`){let t=this.headWorldPose(o);if(t!==null){this.effects.decapitate(o,t.position,t.quaternion,r.direction,r.event_id,this.skinColor(o));let n=this.stumpWorldPose(o);n!==null&&this.effects.anchorStump(o,n.position,n.quaternion),e=!0}}else if(c===`dismember_left`||c===`dismember_right`){let t=c===`dismember_left`?`left`:`right`,n=this.handWorldPose(o,t);n!==null&&(this.effects.dismemberHand(o,t,n.position,n.quaternion,r.direction,r.event_id,this.gearColor(o)),this.effects.anchorHandStump(o,t,n.position,n.quaternion),e=!0)}e&&(this.arcadeInjuries[o]=c,this.observedInjuryDown[o]=!1,this.syncInjuryPresentation(o),this.onArcadeInjury?.(c,r))}let d=this.graphs;if(a&&o>=0&&[`hit`,`counter_hit`,`block`,`perfect_block`,`knockdown`].includes(r.kind)){let e=r.kind===`block`||r.kind===`perfect_block`,t=i.detail.endsWith(`:body`)?`body`:`head`;d===null?this.animators[o].impact({direction:i.direction,amount:e?r.amount*.35:r.amount,blocked:e,target:t}):d[o].react(e?`block`:`hit`,t,i.direction)}a&&s>=0&&[`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`].includes(r.kind)&&(d===null?this.animators[s].landedHit(r.kind===`block`||r.kind===`perfect_block`):d[s].landedHit(r.kind===`block`||r.kind===`perfect_block`)),this.onContact?.(r)}}setupLights(){let e=new sh(`#5a6a95`,`#0c0e16`,1.2);this.scene.add(e),this.lights.push(e);let t=new Dh(`#3a4468`,1.05);this.scene.add(t),this.lights.push(t);let n=new xh(`#fff4e0`,115,26,.68,.6,1.6);n.position.set(0,7.4,.9),n.target.position.set(0,0,0),n.castShadow=!0,n.shadow.mapSize.set(2048,2048),n.shadow.bias=-4e-4,n.shadow.camera.near=3,n.shadow.camera.far=14,this.keyLight=n,this.scene.add(n,n.target),this.lights.push(n);for(let[e,t,n,r]of[[`#b9cdff`,-6.5,4.4,-5.2],[`#ffd9b9`,6.2,4.1,-5.6],[`#9fb8ff`,-5.4,3.6,6],[`#c9d8ff`,5.8,3.9,5.7]]){let i=new xh(e,105,30,.7,.8,1.8);i.position.set(t,n,r),i.target.position.set(0,1,0),this.scene.add(i,i.target),this.lights.push(i)}let r=new Eh(`#dfe9ff`,.7);r.position.set(0,3.4,-6.5),this.scene.add(r),this.lights.push(r);let i=new xh(`#ffe8d0`,55,22,.34,.75,1.5);i.position.set(0,5.6,5.2),i.target.position.set(0,1,0),this.scene.add(i,i.target),this.lights.push(i),this.followSpot=i}draw(e,t=!1,n=!0){if(this.destroyed)return;let r=t?1/60:Math.min(.05,Math.max(.001,(e-this.previous)/1e3));this.previous=e;let i=this.canvas.clientWidth,a=this.canvas.clientHeight;i>0&&a>0&&(this.renderer.getSize(this.sizeCheck),(this.sizeCheck.x!==i||this.sizeCheck.y!==a)&&(this.renderer.setSize(i,a,!1),this.composer.setSize(i,a),this.camera.aspect=i/a,this.camera.updateProjectionMatrix()));let o=e/1e3,s=this.settings();this.setBloodLevel(s.blood);let c=this.buffer.latest(),l=c===null?0:jC(c),u=c===null?null:this.buffer.sample(l),d=1.8,f=!1;if(u!==null){let[e,t]=u.fighters;for(let[e,t]of u.fighters.entries())this.arcadeInjuries[e]!==null&&(t.is_downed?this.observedInjuryDown[e]=!0:this.observedInjuryDown[e]&&u.result===null&&this.restoreInjury(e));let n=this.graphs;if(n!==null){let i=this.headCacheValid[0]?this.headCache[0]:void 0,a=this.headCacheValid[1]?this.headCache[1]:void 0;n[0].update(e,t,r,o,s.reducedMotion,s.blood,l,a),n[1].update(t,e,r,o,s.reducedMotion,s.blood,l,i);for(let[e,t]of n.entries()){let n=t.boxer.bone(`head`);n!==null&&(t.boxer.root.updateMatrixWorld(!0),n.getWorldPosition(this.headCache[e]),this.headCacheValid[e]=!0)}}else this.animators[0].update(e,t,r,o,s.reducedMotion,s.blood,l),this.animators[1].update(t,e,r,o,s.reducedMotion,s.blood,l);for(let e=0;e.05&&!t.is_downed){this.downedPoolAccumulators[e]=0;let t=e===0?this.tmpA:this.tmpB;this.tmpHead.set(t.x,this.headHeightOf(e),t.z),this.effects.drip(this.tmpHead,n,s.reducedMotion,e)}else if(n>.3&&t.is_downed&&s.blood!==`off`)for(this.effects.stopDrip(e),this.downedPoolAccumulators[e]+=r*.8;this.downedPoolAccumulators[e]>=1;){--this.downedPoolAccumulators[e];let t=this.downedPoolCounts[e];this.downedPoolCounts[e]=t+1;let n=t*2.399963+e*Math.PI,r=.12+t*.618034%1*.24,i=e===0?this.tmpA:this.tmpB;this.effects.pool(i.x+Math.sin(n)*r,i.z+Math.cos(n)*r,.8)}else this.effects.stopDrip(e),this.downedPoolAccumulators[e]=0}}else this.tmpA.set(-.9,0,0),this.tmpB.set(.9,0,0);this.arena.update(o,r,s.reducedMotion),this.effects.update(r),this.updateReferee(r,o,s.reducedMotion),this.updateBlobShadows(),this.fireContacts(l),this.followSpot!==null&&this.followSpot.target.position.set((this.tmpA.x+this.tmpB.x)/2,1,(this.tmpA.z+this.tmpB.z)/2);let p=this.cameraOverride??this.director.update(r,o,{x:this.tmpA.x,z:this.tmpA.z},{x:this.tmpB.x,z:this.tmpB.z},d,f,this.effects.shakeAmount,s.reducedMotion);this.camera.position.copy(p.position),this.camera.lookAt(p.lookAt),n&&(this.composer.render(),this.drawHudOverlay(u)),!this.destroyed&&!this.manualClock&&(this.raf=requestAnimationFrame(e=>this.draw(e)))}headHeightOf(e){let t=this.graphs;return t===null?1.56:t[e].boxer.metrics.headRestY+.04}updateBlobShadows(){let e=[this.tmpA,this.tmpB,this.refereePosition];for(let[t,n]of this.blobShadows.entries()){let r=e[t];n.position.x=r.x,n.position.z=r.z;let i=t<2&&this.buffer.latest()?.fighters[t]?.is_downed===!0;n.scale.set(i?2.1:1.25,i?.9:.85,1)}}updateReferee(e,t,n){let r=(this.tmpA.x+this.tmpB.x)/2,i=(this.tmpA.z+this.tmpB.z)/2,a=this.refereeAway.set(this.refereePosition.x-r,0,this.refereePosition.z-i);a.lengthSq()<.01&&a.set(0,0,-1),a.normalize();let o=Xl.clamp(r+a.x*2.05,-2.4,2.4),s=Xl.clamp(i+a.z*2.05,-2.4,2.4),c=1-Math.exp(-1.6*e);this.refereePosition.x+=(o-this.refereePosition.x)*c,this.refereePosition.z+=(s-this.refereePosition.z)*c;for(let e of[this.tmpA,this.tmpB]){let t=this.refereePosition.x-e.x,n=this.refereePosition.z-e.z,r=Math.hypot(t,n);r<1.45&&r>.001&&(this.refereePosition.x=e.x+t/r*1.45,this.refereePosition.z=e.z+n/r*1.45)}this.referee.root.position.set(this.refereePosition.x,0,this.refereePosition.z);let l=((Math.atan2(r-this.refereePosition.x,i-this.refereePosition.z)-this.refereeYaw+Math.PI)%(Math.PI*2)+Math.PI*2)%(Math.PI*2)-Math.PI;this.refereeYaw+=l*(1-Math.exp(-3*e)),this.referee.root.rotation.y=this.refereeYaw,this.referee.hips.position.y=.98+(n?0:Math.sin(t*1.7)*.006)}drawHudOverlay(e){let t=CC(this.hudCanvas);if(t===null)return;let{context:n,viewport:r}=t;if(n.clearRect(0,0,r.width,r.height),e===null)return;let i=Math.max(...e.fighters.map(e=>e.trauma.head+e.trauma.body));if(i>350){let e=n.createRadialGradient(r.width/2,r.height/2,r.width*.2,r.width/2,r.height/2,r.width*.72);e.addColorStop(0,`rgba(90,0,8,0)`),e.addColorStop(1,`rgba(75,0,8,${Math.min(.3,i/4600)})`),n.fillStyle=e,n.fillRect(0,0,r.width,r.height)}_C(n,r.width,r.height,e,this.players,this.viewerId,this.final,this.reconnectMs,this.simulation.tick_rate)}destroy(){if(!this.destroyed){this.destroyed=!0,cancelAnimationFrame(this.raf),this.raf=0,this.buffer.clear(),this.dedupe.reset(),this.pendingContacts.length=0,this.effects.dispose(),this.arena.dispose(),SC(this.ring);for(let e of this.boxers)this.scene.remove(e.root),pb(e);if(this.graphs!==null){for(let e of this.graphs)this.scene.remove(e.boxer.root),e.dispose();this.graphs=null}this.scene.remove(this.referee.root),pb(this.referee);for(let e of this.lights)this.scene.remove(e);this.keyLight?.shadow.map?.dispose(),this.keyLight?.shadow.dispose(),this.renderer.renderLists.dispose(),this.composer.dispose(),this.renderer.dispose(),this.blobTexture.dispose();for(let e of this.blobShadows)this.scene.remove(e),e.geometry.dispose(),e.material.dispose();this.hudCanvas.remove()}}},IC=`hands.preferences.v1`,LC={length:0,clear:()=>void 0,getItem:()=>null,key:()=>null,removeItem:()=>void 0,setItem:()=>void 0},RC=()=>{try{return window.localStorage}catch{return LC}},zC=()=>({volume:.7,haptics:!0,reducedMotion:window.matchMedia?.(`(prefers-reduced-motion: reduce)`).matches??!1,blood:`full`});function BC(e=RC()){let t=zC();try{let n=JSON.parse(e.getItem(IC)??`null`);if(typeof n!=`object`||!n||Array.isArray(n))return t;let r=n;return{volume:typeof r.volume==`number`&&Number.isFinite(r.volume)?Math.max(0,Math.min(1,r.volume)):t.volume,haptics:typeof r.haptics==`boolean`?r.haptics:t.haptics,reducedMotion:typeof r.reducedMotion==`boolean`?r.reducedMotion:t.reducedMotion,blood:r.blood===`reduced`||r.blood===`off`||r.blood===`full`?r.blood:t.blood}}catch{return t}}function VC(e,t=RC()){try{t.setItem(IC,JSON.stringify({volume:Math.max(0,Math.min(1,e.volume)),haptics:e.haptics,reducedMotion:e.reducedMotion,blood:e.blood}))}catch{}}var HC=class{value;listeners=new Set;constructor(e=RC()){this.storage=e,this.value=BC(e)}storage;get current(){return this.value}update(e){this.value={...this.value,...e},VC(this.value,this.storage);for(let e of this.listeners)e(this.value)}subscribe(e){return this.listeners.add(e),()=>this.listeners.delete(e)}destroy(){this.listeners.clear()}},UC={stage:`bootstrapping`,player:null,playerId:null,role:null,players:{},simulation:null,snapshot:null,final:null,serverTick:0,nextSequence:0,reconnectMs:0,safeError:null},WC=e=>Object.fromEntries(e.map(e=>[e.id,e]));function GC(e,t){if(t.type===`bootstrap`)return{...e,stage:`authorizing`,simulation:t.simulation,safeError:null};if(t.type===`authorized`)return{...e,stage:`connecting`,player:t.player,safeError:null};if(t.type===`connecting`)return{...e,stage:`connecting`};if(t.type===`reconnect-tick`)return{...e,stage:`paused`,reconnectMs:Math.max(0,t.remainingMs)};if(t.type===`fatal`)return{...e,stage:`fatal`,safeError:t.code,reconnectMs:0};let n=t.message;switch(n.type){case`welcome`:return{...e,playerId:n.role===`fighter`?n.player_id:null,role:n.role,players:WC(n.players),serverTick:n.server_tick,nextSequence:n.role===`fighter`?n.next_sequence:0,safeError:null};case`ticket`:return e;case`waiting`:return{...e,stage:`waiting`};case`ready`:return{...e,stage:e.snapshot?.phase??`countdown`,players:WC(n.players)};case`paused`:return{...e,stage:`paused`,reconnectMs:n.grace_ms};case`resumed`:return{...e,stage:e.snapshot?.phase??`countdown`,reconnectMs:0};case`snapshot`:return{...e,stage:n.payload.phase,snapshot:n.payload,serverTick:Math.max(e.serverTick,n.payload.tick)};case`final`:return{...e,stage:`complete`,final:n,reconnectMs:0};case`error`:return{...e,stage:`fatal`,safeError:n.code,reconnectMs:0}}}var KC=new Set([`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`,`knockdown`]),qC=class{root;reloadPage;state=UC;settings=new HC;input=new xs;audio=new i(()=>this.settings.current);haptics=new as(()=>this.settings.current);feedbackEvents=new Ts;renderer=null;network=null;session=null;abort=new AbortController;destroyed=!1;generation=0;reloadOnRetry=!1;canvas;status;roleIndicator;controlsButton;controlsPanel;retry;fightSummary;liveFightStatus;finalSummary;constructor(e,t=()=>window.location.reload()){this.root=e,this.reloadPage=t,e.innerHTML=`
HANDSauthoritative two-player boxing

`,this.canvas=e.querySelector(`canvas`),this.status=e.querySelector(`[data-status]`),this.roleIndicator=e.querySelector(`[data-role]`),this.controlsButton=e.querySelector(`[data-controls]`),this.controlsPanel=e.querySelector(`[data-controls-panel]`),this.retry=e.querySelector(`[data-retry]`),this.fightSummary=e.querySelector(`[data-fight-summary]`),this.liveFightStatus=e.querySelector(`[data-fight-status]`),this.finalSummary=e.querySelector(`[data-final]`),this.retry.addEventListener(`click`,this.onRetry),this.bindPanels(),this.syncSettings()}start(){this.authorize()}resetForAuthorization(){this.reloadOnRetry=!1,this.network?.dispose(),this.network=null,this.session?.destroy(),this.session=null,this.renderer?.destroy(),this.renderer=null,this.abort.abort(),this.abort=new AbortController,this.state=UC,this.feedbackEvents.reset(),this.input.setActive(!1),this.input.reset(),this.finalSummary.textContent=``,this.fightSummary.textContent=``,this.liveFightStatus.textContent=``}async authorize(){let e=++this.generation;this.resetForAuthorization(),this.dispatch({type:`connecting`}),this.setText(this.status,`Securing Discord Activity session…`),this.retry.hidden=!0;try{let t=await rs(this.abort.signal);if(this.destroyed||e!==this.generation){t.destroy();return}this.session=t,this.dispatch({type:`bootstrap`,simulation:t.bootstrap.simulation}),this.dispatch({type:`authorized`,player:t.player}),this.renderer=new FC(this.canvas,t.bootstrap.simulation,()=>this.settings.current),this.renderer.onContact=e=>{this.audio.event(e),this.haptics.event(e)},this.renderer.onArcadeInjury=e=>this.audio.injury(e),this.input.onAction(e=>this.renderer?.predictAction?.(e));let n=t.takeTicket();if(n===null)throw Error(`ticket_unavailable`);let r=new ks(n,()=>this.input.frame(),{onMessage:e=>this.receive(e),onReconnect:e=>{this.dispatch({type:`reconnect-tick`,remainingMs:e}),this.renderer?.setReconnect(e),this.renderState()},onFatal:e=>this.fail(e),onFreshAuth:()=>{e===this.generation&&this.authorize()}});this.network=r,r.start(),this.setText(this.status,`Connecting to the ring…`)}catch(t){!this.abort.signal.aborted&&e===this.generation&&(this.reloadOnRetry=t instanceof M&&t.reloadRequired,this.fail(ge(t)))}}receive(e){if(e.type===`error`){this.fail(e.code);return}this.dispatch({type:`message`,message:e}),e.type===`snapshot`&&this.receiveSnapshot(e.payload),e.type===`final`&&(this.renderer?.setFinal(e),this.audio.result(e)),this.renderer?.setPlayers(this.state.players,this.state.playerId),this.renderer?.setReconnect(this.state.reconnectMs),this.renderState()}receiveSnapshot(e){this.renderer?.push(e);let t=e.fighters.find(e=>e.player_id===this.state.playerId);this.input.setKnockdown(t?.is_downed===!0),t!==void 0&&this.audio.snapshot(e.tick,t.stamina,t.maximum_stamina,t.trauma.head+t.trauma.body);for(let t of this.feedbackEvents.accept(e.events))KC.has(t.kind)||(this.audio.event(t),this.haptics.event(t))}dispatch(e){this.state=GC(this.state,e)}setText(e,t){e.textContent!==t&&(e.textContent=t)}renderState(){let e={bootstrapping:`Loading…`,authorizing:`Authorizing with Discord…`,connecting:`Connecting securely…`,waiting:`Waiting for one opponent to use Play now in this channel.`,countdown:`Bout countdown.`,fight:`Round ${this.state.snapshot?.round_number??1} in progress.`,knockdown:`Knockdown count ${this.state.snapshot?.fighters.find(e=>e.player_id===this.state.playerId)?.get_up_count??0}.`,foul_recovery:`Foul recovery in progress.`,rest:`Between-round rest.`,paused:`Connection paused. ${Math.ceil(this.state.reconnectMs/1e3)} seconds remain.`,complete:`Bout complete. Scorecards and rating changes are displayed.`,fatal:`Unable to continue (${this.state.safeError??`safe_error`}).`},t=this.state.role===`spectator`;this.setText(this.status,t?`Spectating — ${e[this.state.stage]}`:e[this.state.stage]),this.roleIndicator.hidden=!t,this.controlsButton.hidden=t,t&&(this.controlsPanel.hidden=!0,this.controlsButton.setAttribute(`aria-expanded`,`false`));let n=this.state.snapshot?.fighters.find(e=>e.player_id===this.state.playerId),r=t?`Spectating. ${e[this.state.stage]}`:this.state.stage===`knockdown`&&n?.is_downed===!0?`Knockdown. Count ${n.get_up_count}. ${n.get_up_prompt===null?`Wait for your private rhythm instruction.`:`Press ${n.get_up_prompt===`get_up_left`?`left`:`right`} now.`}`:this.state.stage===`paused`?`Connection paused.`:e[this.state.stage];this.setText(this.liveFightStatus,r),this.retry.hidden=this.state.stage!==`fatal`;let i=!t&&[`countdown`,`fight`,`knockdown`,`foul_recovery`].includes(this.state.stage);if(this.input.setActive(i),this.network?.setActive(i),this.renderFightSummary(),this.state.final!==null){let e=this.state.final;this.setText(this.finalSummary,`${e.method.replaceAll(`_`,` `)}. ${e.winner_id===null?`Draw`:`${this.state.players[e.winner_id]?.name??`Winner`} wins`}. Scorecards: ${e.scorecards.map(e=>`${e.judge}: ${e.player_one.reduce((e,t)=>e+t,0)} to ${e.player_two.reduce((e,t)=>e+t,0)}`).join(`; `)}. Ratings: ${Object.entries(e.ratings).map(([e,t])=>`${this.state.players[e]?.name??`fighter`} ${t.before} to ${t.after}`).join(`; `)}.`)}}renderFightSummary(){let e=this.state.snapshot;if(e===null)return;let t=this.state.simulation?.tick_rate??30,n=Math.floor(e.phase_ticks_remaining/t),r=`${Math.floor(n/60)}:${String(n%60).padStart(2,`0`)}`,i=e.fighters.map(e=>{let t=this.state.players[e.player_id];return`${t?.name??`Fighter`}, ELO ${t?.rating??`unknown`}, stamina ${Math.round(e.stamina)} of ${Math.round(e.maximum_stamina)}, guard ${Math.round(e.guard)}, poise ${Math.round(e.poise)}, conditioning ${Math.round(e.conditioning)}, ${e.warnings} warnings, ${e.knockdowns} knockdowns`}),a=e.fighters.find(e=>e.player_id===this.state.playerId),o=a?.is_downed===!0?a.get_up_prompt===null?`You are down. Count ${a.get_up_count}. Wait for your private rhythm instruction.`:`You are down. Count ${a.get_up_count}. Press ${a.get_up_prompt===`get_up_left`?`left`:`right`} now. Get-up progress ${a.get_up_meter} of ${a.get_up_required}.`:``;this.setText(this.fightSummary,`Round ${e.round_number}. ${e.phase.replace(`_`,` `)}. Clock ${r}. ${i.join(`. `)}. ${o}`.trim())}onRetry=()=>{if(this.reloadOnRetry){this.reloadPage();return}this.authorize()};bindPanels(){let e=(e,t)=>{let n=this.root.querySelector(e),r=this.root.querySelector(t);n.addEventListener(`click`,()=>{r.hidden=!r.hidden,n.setAttribute(`aria-expanded`,String(!r.hidden))})};e(`[data-controls]`,`[data-controls-panel]`),e(`[data-settings]`,`[data-settings-panel]`),this.root.querySelector(`[data-volume]`).addEventListener(`input`,e=>{this.settings.update({volume:Number(e.target.value)}),this.audio.setVolume()}),this.root.querySelector(`[data-haptics]`).addEventListener(`change`,e=>{this.settings.update({haptics:e.target.checked})}),this.root.querySelector(`[data-motion]`).addEventListener(`change`,e=>{let t=e.target.checked;this.settings.update({reducedMotion:t}),this.renderer?.setReducedMotion(t)}),this.root.querySelector(`[data-blood]`).addEventListener(`change`,e=>{let t=e.target.value;this.settings.update({blood:t}),this.renderer?.setBloodLevel(t)})}syncSettings(){let 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Cb=bb.hurtboxes,wb=bb.hitbox.glove_radius;bb.fatigue_scaling;var Tb=bb.rest.corner_offset,Eb=bb.ring.half_width,Db=bb.ring.half_height,Ob=bb.ring.fighter_radius,kb=bb.corners.reach,Ab=bb.combos.recovery_cancel_percent,jb=new Set(bb.combos.chains.map(([e,t])=>`${e}:${t}`));function Mb(e,t){return jb.has(`${e}:${t}`)}function Nb(e){return e.startup+e.active+Math.floor(e.recovery*Ab/100)}function Pb(e,t,n,r,i){return t&&!i&&Mb(e,n.class)&&r>=Lb(n.class,n.target,n.power)}function Fb(e){return xb[e].combo_window}function Ib(e,t,n){let r=xb[e],i=r.startup,a=r.active,o=r.recovery,s=r.reach,c=r.lateral_arc;if(t===`body`){let e=Sb.body;i+=e.startup_add??0,o+=e.recovery_add??0,s=Math.max(e.reach_min??0,s-(e.reach_sub??0)),c+=e.lateral_arc_add??0}if(n===`power`){let e=Sb.power;i+=e.startup_add??0,a+=e.active_add??0,o+=e.recovery_add??0,s+=e.reach_add??0}return{startup:i,active:a,recovery:o,reach:s,lateralArc:c}}function Lb(e,t,n){let r=xb[e].stamina_cost;return 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r=Math.max(2,Math.floor(zb*Ub(e.conditioning,e.trauma.body)/100));(t.defense===`guard_high`||t.defense===`guard_low`)&&(r=Math.max(2,Math.floor(r*Bb/100)));let i=Math.hypot(t.moveX,t.moveY),a=i>1e3?1e3/i:1;return n.x=t.moveX*a*r/1e3,n.y=t.moveY*a*r/1e3,n.speed=r,n}function Xb(e,t,n,r){if(n<=0||Jb(e))return{dx:0,dy:0};let i=r===void 0?e.action===null?0:1/0:qb(e,r);if(i>=n)return{dx:0,dy:0};let a=e.velocity_x,o=e.velocity_y,s=0,c=0,l=Math.floor(n),u=n-l;for(let e=0;e=i,r=t(e);a=(a+(n?r.x:0))/2,o=(o+(n?r.y:0))/2;let l=Math.hypot(a,o);l>r.speed&&(a=a/l*r.speed,o=o/l*r.speed),s+=a,c+=o}if(u>0){let e=l>=i,n=t(l);s+=(a+(e?n.x:0))/2*u,c+=(o+(e?n.y:0))/2*u}return{dx:s,dy:c}}var Zb=1e3,Qb=2.5,$b=class{history=[];offset={dx:0,dy:0};mean={x:0,y:0,speed:0};sample={x:0,y:0,speed:0};horizon=null;update(e,t,n,r,i,a,o,s){for(this.history.push({at:r,held:n?{...t,moveX:0,moveY:0}:t});this.history.length>2&&this.history[1].atthis.meanIntent(e,r-(n-1-i)*t,t),n,a)}let l=Qb*zb*s*o,u=c.dx-this.offset.dx,d=c.dy-this.offset.dy,f=Math.hypot(u,d),p=f>l?l/f:1;return this.offset.dx+=u*p,this.offset.dy+=d*p,{dx:this.offset.dx,dy:this.offset.dy}}meanIntent(e,t,n){let r=t-n/2,i=t+n/2,a=this.mean;a.x=0,a.y=0,a.speed=0;for(let t=0;tr?{x:i*(kb-r),y:a*r}:d>n?{x:i*n,y:a*(kb-n)}:{x:i*d,y:a*f}}function tx(e,t,n){let r=e.x+t.dx,i=e.y+t.dy;if(n!==null){let t=Math.min(Hb,Math.hypot(e.x-n.x,e.y-n.y)),a=r-n.x,o=i-n.y,s=Math.hypot(a,o);s1e-9?(r=n.x+a/s*t,i=n.y+o/s*t):(r=e.x,i=e.y))}let a=ex(r,i);return{dx:a.x-e.x,dy:a.y-e.y}}function nx(e){return e===`slip_left`||e===`slip_right`||e===`weave`||e===`pull`}function rx(e,t,n){return e.stunned_ticks>0||e.taunt_ticks>0||e.clinch_ticks>0?e.defense:n===null?nx(e.defense)?e.defense:t.defense:n}var ix=class{kind=null;id=``;pressedAt=0;until=0;sequence=null;started=!1;press(e,t,n,r,i){this.kind=e,this.id=t,this.pressedAt=n,this.until=n+(Math.max(0,r)+10)*1e3/i,this.sequence=null,this.started=!1}acknowledge(e,t,n){if(this.kind===null)return;this.sequence??=n?.(this.id)??null,e.defense===this.kind&&(this.started=!0);let r=!t||e.stunned_ticks>0||e.clinch_ticks>0,i=!this.started&&this.sequence!==null&&e.last_input_sequence>=this.sequence&&e.queued_actions===0;(r||i)&&(this.kind=null)}pose(e){return this.kind!==null&&e>=this.until&&(this.kind=null),this.kind}holdsFeet(e,t){return this.kind!==null&&e()=>(e=Math.imul(e^e>>>15,1|e),e^=e+Math.imul(e^e>>>7,61|e),((e^e>>>14)>>>0)/4294967296);function lx(){let e=new Nd;e.name=`arena`;let t=[],n=[],r=[],i=new sh({color:`#05070c`,roughness:.95});n.push(i);let a=new hm(30,40);t.push(a);let o=new up(a,i);o.rotation.x=-Math.PI/2,o.position.y=-1,o.receiveShadow=!0,e.add(o);let s=cx(20260727),c=[{radius:8.2,y:-.55,count:120,scale:1},{radius:10.6,y:.35,count:150,scale:1.04},{radius:13.2,y:1.35,count:180,scale:1.08},{radius:16,y:2.45,count:210,scale:1.12}],l=c.reduce((e,t)=>e+t.count,0),u=new mm(.19,.5,4,8),d=new Ym(.115,8,7);t.push(u,d);let f=new sh({roughness:.9,metalness:0,emissive:1317158,emissiveIntensity:.7}),p=new sh({roughness:.75,metalness:0,emissive:2759958,emissiveIntensity:.7});n.push(f,p);let m=new Ip(u,f,l),h=new Ip(d,p,l);m.instanceMatrix.setUsage(ql),h.instanceMatrix.setUsage(ql);let g=new ad,_=new Q,v=new Float32Array(l),y=[],b=0;for(let e of c)for(let t=0;t{if(L=Math.max(0,L-t*ax),!n){let n=.05+L*.06,r=.05+L*.2,i=2.3+L*3.2;for(let t=0;t0?.85:0}},excite:e=>{L=Math.min(1,L+Math.max(0,e))},excitement:()=>L,dispose:()=>{for(let e of t)e.dispose();for(let e of n)e.dispose();for(let e of r)e.dispose();m.dispose(),h.dispose()}}}var ux=2.05,dx=5.5,fx=1.05,px=2.5,mx=5.5;function hx(e,t,n){return e<2.5||t<2?null:(n+Math.floor((e-px)/mx))%2}function gx(e){return Math.max(0,e-px)%mx}var _x=.95,vx=2.6,yx=-25;function bx(e,t,n,r,i){let a=e===0?-1:1,o=r*Math.PI/180,s=-a*Math.SQRT1_2,c=a*Math.SQRT1_2,l=s*Math.cos(o)+c*Math.sin(o),u=-s*Math.sin(o)+c*Math.cos(o);return i.set(a*t+l*n,0,-a*t+u*n)}function xx(e,t,n,r,i){bx(e,t,vx,yx+Math.min(1,n/mx)*5,r).setY(1.45),bx(e,t,.62,27,i).setY(1.05)}var Sx=class{current=new Z(0,ux,dx);look=new Z(0,fx,0);swayPhase=0;update(e,t,n,r,i,a,o,s){this.swayPhase+=e;let c=(n.x+r.x)/2,l=(n.z+r.z)/2,u=Pu.clamp(c,-1.4,1.4),d=Pu.clamp(l,-1.1,1.1),f=Pu.clamp(dx+i*.6-(a?.9:0),4.6,8.4),p=ux+i*.08-(a?.45:0),m=s?0:Math.sin(this.swayPhase*.21)*.35,h=s?0:Math.sin(this.swayPhase*.13)*.3,g=u*.32+m,_=f+d*.2,v=p+h*.2;if(this.current.x+=(g-this.current.x)*(1-Math.exp(-2.6*e)),this.current.y+=(v-this.current.y)*(1-Math.exp(-2.6*e)),this.current.z+=(_-this.current.z)*(1-Math.exp(-2.6*e)),this.look.x+=(u-this.look.x)*(1-Math.exp(-3.2*e)),this.look.y+=((a?.7:fx)-this.look.y)*(1-Math.exp(-3.2*e)),this.look.z+=(d*.6-this.look.z)*(1-Math.exp(-3.2*e)),!s&&o>5e-4){let e=t*61;this.current.x+=Math.sin(e*1.31)*o,this.current.y+=Math.cos(e*1.97)*o*.6,this.look.x+=Math.sin(e*1.53)*o*.5,this.look.y+=Math.cos(e*2.11)*o*.35}return{position:this.current,lookAt:this.look}}},Cx=3.05,wx=3.85,Tx=4.05,Ex=3.42,Dx=[.5,.88,1.26];function Ox(e){let t=Cx/Math.max(1,e.ring_half_width),n=Cx/Math.max(1,e.ring_half_height);return{x:e=>e*t,z:e=>-e*n}}var kx={blue:1920728,red:12131356,neutral:15067115},Ax=900,jx=90,Mx=48,Nx=48,Px=2,Fx=4,Ix=24,Lx=16,Rx=.12,zx=.085,Bx=.05,Vx=1/60,Hx=e=>()=>(e=Math.imul(e^e>>>15,1|e),e^=e+Math.imul(e^e>>>7,61|e),((e^e>>>14)>>>0)/4294967296),Ux=(e,t=0)=>Number.isFinite(e)?e:t;function Wx(e){if(typeof e==`number`)return{x:e<0?-1:1,z:0};let t=Math.hypot(e.x,e.z);return Number.isFinite(t)&&t>1e-6?{x:e.x/t,z:e.z/t}:{x:1,z:0}}var Gx=new Z(0,1,0),Kx=e=>Number.isFinite(e)?Pu.clamp(e,0,Bx):0,qx=new Set([`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`,`knockdown`,`bleed`]);function Jx(e){if(e.kind===`bleed`)return`ooze`;if(e.kind===`knockdown`)return`impact`;let t=e.detail.split(`:`);if(t.at(-1)===`body`)return`body_burst`;let n=t.find(e=>[`jab`,`straight`,`hook`,`uppercut`].includes(e));return n===`hook`?`fan`:n===`uppercut`?`plume`:`jet`}function Yx(e,t){e.set(Ux(t.x),Ux(t.y),Ux(t.z),Ux(t.w,1)),e.lengthSq()<1e-6?e.identity():e.normalize()}function Xx(e){let t=document.createElement(`canvas`);t.width=128,t.height=128;let n=t.getContext(`2d`);if(n!==null){let t=Hx(e);n.clearRect(0,0,128,128),n.fillStyle=`rgba(255,255,255,1)`;let r=7+Math.floor(t()*6);for(let e=0;enew up(e.geometry,e.material))}setBloodLevel(e){if(e===this.bloodLevel)return;let t=this.bloodLevel;this.bloodLevel=e,(e===`off`||t===`full`&&e===`reduced`)&&this.clearArcadeGore()}get shakeAmount(){return this.shake}get liveParticles(){return this.droplets.filter(e=>e.alive).length}get liveBloodParticles(){return this.droplets.filter(e=>e.alive&&e.blood).length}get liveMist(){return this.mists.filter(e=>e.alive).length}get visibleDecals(){return this.decals.filter(e=>e.visible).length}get liveGibs(){return this.gibs.filter(e=>e.alive).length}get activeHeads(){return this.heads.filter(e=>e.active).length}severedHeadPosition(e,t){let n=this.heads[Math.trunc(e)];return n===void 0||!n.active?!1:(t.copy(n.mesh.position),!0)}get activeHands(){return this.hands.filter(e=>e.active).length}get activeStumps(){return[...this.stumps,...this.handStumps].filter(e=>e.active).length}spawnDroplet(e,t,n,r,i,a,o,s,c,l=c?.006+this.ambientRandom()*.009:.004+this.ambientRandom()*.004){let u=this.liveDroplets1e-4?(this.dropletVelocity.set(t.vx/n,t.vy/n,t.vz/n),this.dropletQuaternion.setFromUnitVectors(Gx,this.dropletVelocity)):this.dropletQuaternion.identity();let i=Math.min(1,t.life/(t.maxLife*.3));this.dropletScale.set(t.radius*i,t.radius*r*i,t.radius*i),this.dropletMatrix.compose(this.dropletVelocity.set(t.x,t.y,t.z),this.dropletQuaternion,this.dropletScale),this.dropletMesh.setMatrixAt(e,this.dropletMatrix)}spawnMist(e,t,n,r,i){let a=this.mistIndex%jx;this.mistIndex+=1;let o=this.mists[a];o.alive=!0,o.x=Ux(e),o.y=Ux(t,1),o.z=Ux(n),o.maxLife=Math.max(.05,Ux(i,.5)),o.life=o.maxLife,o.scale=Math.max(.1,Ux(r,1)),this.mistPositions[a*3]=o.x,this.mistPositions[a*3+1]=o.y,this.mistPositions[a*3+2]=o.z,this.mistColors[a*3]=.6*o.scale,this.mistColors[a*3+1]=.07*o.scale,this.mistColors[a*3+2]=.08*o.scale,this.mistGeometry.attributes.position.needsUpdate=!0,this.mistGeometry.attributes.color.needsUpdate=!0}placeDecal(e,t,n,r,i,a,o){let s=this.decals[this.decalIndex%Mx];this.decalIndex+=1,s.visible=!0,s.position.x=Ux(e),s.position.z=Ux(t),s.rotation.z=Ux(i),s.scale.set(Math.max(.01,Ux(n,.2))*1.4,Math.max(.01,Ux(r,.15))*1.4,1);let c=s.material;c.opacity=Pu.clamp(Ux(a,.4)*1.6,0,1),c.color.setHex(o)}ambientRandom(){return this.ambientSeed=Math.imul(this.ambientSeed^this.ambientSeed>>>15,1|this.ambientSeed),this.ambientSeed^=this.ambientSeed+Math.imul(this.ambientSeed^this.ambientSeed>>>7,61|this.ambientSeed),((this.ambientSeed^this.ambientSeed>>>14)>>>0)/4294967296}splatter(e,t,n,r=()=>this.ambientRandom()){if(this.bloodLevel===`off`)return;let i=this.bloodLevel===`reduced`,a=i?3:12,o=i?.35:1;for(let s=0;sthis.ambientRandom()){if(this.bloodLevel===`off`)return;let i=this.bloodLevel===`reduced`,a=i?.35:1;if(this.placeDecal(e,t,2.8*n*a,2*n*a,r()*Math.PI,.56*a,4523529),!i)for(let n=0;n<3;n+=1){let n=r()*Math.PI*2,i=.18+r()*.32;this.placeDecal(e+Math.sin(n)*i,t+Math.cos(n)*i,.45+r()*.55,.22+r()*.38,r()*Math.PI,.38+r()*.18,6425104)}}addEvent(e,t,n,r){if(!qx.has(e.kind))return;let i=Hx(e.event_id*7919+17),a=e.kind===`block`||e.kind===`perfect_block`,o=Jx(e),s=Wx(r??e.direction),c=r===void 0?Math.abs(Ux(e.direction)):1,l={x:Ux(t.x),y:e.detail.endsWith(`:body`)?1.05:1.58,z:Ux(t.z)},u=n?0:Math.round((a?6:16)+Math.min(20,Math.max(0,e.amount)/20)),d=n||e.blood<=0||this.bloodLevel===`off`?0:this.bloodLevel===`reduced`?Math.min(24,Math.round(e.blood*.24)):Math.min(120,Math.round(e.blood*1.1));this.shake=Math.min(.09,this.shake+(a?.008:Math.max(.012,e.amount/2600))),e.kind===`knockdown`&&(this.shake=Math.min(.14,this.shake+.06));for(let e=0;e0&&this.bloodLevel!==`off`&&(e.amount>190||e.kind===`knockdown`||e.kind===`counter_hit`)){let t=this.bloodLevel===`reduced`?e.kind===`knockdown`?3:2:e.kind===`knockdown`?14:10,n=this.bloodLevel===`reduced`?.35:1;for(let e=0;e6&&this.bloodLevel!==`off`&&this.splatter(l.x+(i()-.5)*.6,l.z+(i()-.5)*.6,1+Math.min(2,e.blood/55),i),this.bloodLevel===`full`&&!n&&e.blood>=40&&[`hit`,`counter_hit`,`knockdown`].includes(e.kind)){let t=Math.min(12,Math.max(4,Math.round(e.blood/9)));for(let e=0;e=Px)return;let s=Math.trunc(e),c=Number.isSafeInteger(i)?i:0,l=this.heads[s];if(l.active||this.lastDecapitationEvent[s]===c)return;this.applyBakedPart(l,o,a);let u=Hx(c*104729+s*8191+23),d=Wx(r);this.lastDecapitationEvent[s]=c,l.active=!0,l.moving=!0,l.eventId=c;let f=1.8+u()*1.1;l.vy=2.3+u()*1.1;let p=(u()-.5)*2.2;l.vx=f*d.x-p*d.z,l.vz=f*d.z+p*d.x,l.vrx=(u()-.5)*12,l.vry=(u()-.5)*12,l.vrz=(u()-.5)*12,l.bounces=0,l.stained=!1,l.mesh.position.set(Ux(t.x),Ux(t.y,1.55),Ux(t.z)),Yx(l.mesh.quaternion,n),l.mesh.visible=!0;let m=this.stumps[s];m.active=!0,m.fountainLife=1.25,m.accumulator=0,m.seed=c|1,m.direction=d,m.mesh.position.copy(l.mesh.position),m.mesh.quaternion.copy(l.mesh.quaternion),m.mesh.visible=!0;for(let e=0;e=Px)return;let c=Math.trunc(e)*2+(t===`left`?0:1),l=Number.isSafeInteger(a)?a:0,u=this.hands[c];if(u.active||this.lastDismembermentEvent[c]===l)return;this.applyBakedPart(u,s,o);let d=Hx(l*130363+c*12289+37),f=Wx(i);this.lastDismembermentEvent[c]=l,u.active=!0,u.moving=!0,u.eventId=l;let p=1.3+d()*1.1;u.vy=1.5+d()*1.2;let m=(d()-.5)*1.8;u.vx=p*f.x-m*f.z,u.vz=p*f.z+m*f.x,u.vrx=(d()-.5)*16,u.vry=(d()-.5)*16,u.vrz=(d()-.5)*16,u.bounces=0,u.stained=!1,u.mesh.position.set(Ux(n.x),Ux(n.y,1.25),Ux(n.z)),Yx(u.mesh.quaternion,r),u.mesh.visible=!0;let h=this.handStumps[c];h.active=!0,h.fountainLife=.9,h.accumulator=0,h.seed=l|1,h.direction=f,h.mesh.position.copy(u.mesh.position),h.mesh.quaternion.copy(u.mesh.quaternion),h.mesh.visible=!0;for(let e=0;e=Px)return;let i=Math.trunc(e)*2+(t===`left`?0:1),a=this.handStumps[i];a.active&&(a.mesh.position.set(Ux(n.x),Ux(n.y,1.2),Ux(n.z)),Yx(a.mesh.quaternion,r))}anchorStump(e,t,n){if(this.bloodLevel!==`full`||e<0||e>=Px)return;let r=this.stumps[Math.trunc(e)];r.active&&(r.mesh.position.set(Ux(t.x),Ux(t.y,1.5),Ux(t.z)),Yx(r.mesh.quaternion,n))}restoreFighter(e){if(e<0||e>=Px)return;let t=Math.trunc(e),n=this.heads[t];n.active=!1,n.moving=!1,n.mesh.visible=!1,n.mesh.position.y=-50,this.applyBakedPart(n,void 0,9063730);let r=this.stumps[t];r.active=!1,r.fountainLife=0,r.accumulator=0,r.mesh.visible=!1,r.mesh.position.y=-50;for(let e of[t*2,t*2+1]){let t=this.hands[e];t.active=!1,t.moving=!1,t.mesh.visible=!1,t.mesh.position.y=-50,this.applyBakedPart(t,void 0,1920728);let n=this.handStumps[e];n.active=!1,n.fountainLife=0,n.accumulator=0,n.mesh.visible=!1,n.mesh.position.y=-50}}drip(e,t,n,r=0){let i=+(r===1);if(this.bloodLevel===`off`||n||t<=.05){this.stopDrip(i);return}let a=this.dripEmitters[i];a.position.set(Ux(e.x),Ux(e.y,1.5),Ux(e.z)),a.rate=this.bloodLevel===`reduced`?Math.min(3,t*3):Math.min(18,t*14),a.active=!0}stopDrip(e){let t=this.dripEmitters[+(e===1)];t.active=!1,t.rate=0,t.accumulator=0}updateDripEmitters(e){for(let t of this.dripEmitters)if(t.active)for(t.accumulator+=e*t.rate;t.accumulator>=1;)--t.accumulator,this.spawnDroplet(t.position.x+(this.ambientRandom()-.5)*.14,t.position.y-.04,t.position.z+(this.ambientRandom()-.5)*.1,(this.ambientRandom()-.5)*.08,-.25-this.ambientRandom()*.4,(this.ambientRandom()-.5)*.08,{r:.5,g:.04,b:.06},1.1,!0)}spawnTeeth(e,t,n,r){if(this.bloodLevel===`off`)return;let i=Hx((Number.isSafeInteger(r)?r:0)*7331+91),a=Wx(t),o=Math.min(4,Math.max(1,Math.round(n*(this.bloodLevel===`reduced`?.5:1))));for(let t=0;t.35?(r.bounces+=1,r.vy=Math.abs(r.vy)*.3,r.vx*=.68,r.vz*=.68,r.vrx*=.7,r.vry*=.7,r.vrz*=.7):r.tooth?(r.vx=0,r.vy=0,r.vz=0,r.vrx=r.vry=r.vrz=0):r.alive=!1),this.writeGibMatrix(n,r)}t&&(this.gibMesh.instanceMatrix.needsUpdate=!0)}confineGib(e){Math.abs(e.x)>3.05&&(e.x=Math.sign(e.x)*Cx,e.vx*=-.45),Math.abs(e.z)>3.05&&(e.z=Math.sign(e.z)*Cx,e.vz*=-.45)}updateDetachedParts(e,t){for(let n of e)if(!(!n.active||!n.moving)){if(n.vy-=5.8*t,n.mesh.position.x+=n.vx*t,n.mesh.position.y+=n.vy*t,n.mesh.position.z+=n.vz*t,n.mesh.rotation.x+=n.vrx*t,n.mesh.rotation.y+=n.vry*t,n.mesh.rotation.z+=n.vrz*t,Math.abs(n.mesh.position.x)>3.05&&(n.mesh.position.x=Math.sign(n.mesh.position.x)*Cx,n.vx*=-.42),Math.abs(n.mesh.position.z)>3.05&&(n.mesh.position.z=Math.sign(n.mesh.position.z)*Cx,n.vz*=-.42),n.mesh.position.y<=0+n.radius){if(n.mesh.position.y=0+n.radius,!n.stained&&this.bloodLevel===`full`){n.stained=!0;let e=n.radius===Rx?1:.55;this.placeDecal(n.mesh.position.x,n.mesh.position.z,1.3*e,.9*e,n.mesh.rotation.z,.58,4392199)}n.bounces<2&&Math.abs(n.vy)>.42?(n.bounces+=1,n.vy=Math.abs(n.vy)*.32,n.vx*=.62,n.vz*=.62,n.vrx*=.65,n.vry*=.65,n.vrz*=.65):(n.moving=!1,n.vx=0,n.vy=0,n.vz=0,n.vrx=0,n.vry=0,n.vrz=0)}(!Number.isFinite(n.mesh.position.x)||!Number.isFinite(n.mesh.position.y)||!Number.isFinite(n.mesh.position.z)||!Number.isFinite(n.mesh.quaternion.x)||!Number.isFinite(n.mesh.quaternion.y)||!Number.isFinite(n.mesh.quaternion.z)||!Number.isFinite(n.mesh.quaternion.w))&&(n.mesh.position.set(0,0+n.radius,0),n.mesh.quaternion.identity(),n.moving=!1,n.vx=0,n.vy=0,n.vz=0)}}stumpRandom(e){let t=e.seed|0;return t=Math.imul(t^t>>>15,1|t),t^=t+Math.imul(t^t>>>7,61|t),e.seed=t|0,((t^t>>>14)>>>0)/4294967296}updateStumpFountains(e){if(this.bloodLevel===`full`){for(let t of[...this.stumps,...this.handStumps])if(!(!t.active||t.fountainLife<=0))for(t.fountainLife=Math.max(0,t.fountainLife-e),t.accumulator+=e*36;t.accumulator>=1;){--t.accumulator;let e=this.stumpRandom(t),n=this.stumpRandom(t),r=this.stumpRandom(t);this.sprayDroplet(t.direction,t.mesh.position.x+(e-.5)*.08,t.mesh.position.y+.015,t.mesh.position.z+(n-.5)*.08,.35+e*.55,1.3+n*1.45,(r-.5)*.85,{r:.58,g:.025,b:.045},.65+r*.5,!0)}}}update(e){for(this.simulationRemainder+=Kx(e);this.simulationRemainder+1e-9>=Vx;)this.simulationRemainder=Math.max(0,this.simulationRemainder-Vx),this.simulate(Vx)}simulate(e){this.shake*=.02**e,this.updateDripEmitters(e),this.updateStumpFountains(e),this.updateDetachedParts(this.heads,e),this.updateDetachedParts(this.hands,e),this.updateGibs(e);let t=this.liveDroplets,n=!1;for(let t=0;t0&&(this.dropletBuffers.position.needsUpdate=!0,this.dropletBuffers.color.needsUpdate=!0,this.uploadDroplets(0,this.liveDroplets,n));let r=!1;for(let[t,n]of 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aS={KHR_BINARY_GLTF:`KHR_binary_glTF`,KHR_DRACO_MESH_COMPRESSION:`KHR_draco_mesh_compression`,KHR_LIGHTS_PUNCTUAL:`KHR_lights_punctual`,KHR_MATERIALS_CLEARCOAT:`KHR_materials_clearcoat`,KHR_MATERIALS_DISPERSION:`KHR_materials_dispersion`,KHR_MATERIALS_IOR:`KHR_materials_ior`,KHR_MATERIALS_SHEEN:`KHR_materials_sheen`,KHR_MATERIALS_SPECULAR:`KHR_materials_specular`,KHR_MATERIALS_TRANSMISSION:`KHR_materials_transmission`,KHR_MATERIALS_IRIDESCENCE:`KHR_materials_iridescence`,KHR_MATERIALS_ANISOTROPY:`KHR_materials_anisotropy`,KHR_MATERIALS_UNLIT:`KHR_materials_unlit`,KHR_MATERIALS_VOLUME:`KHR_materials_volume`,KHR_TEXTURE_BASISU:`KHR_texture_basisu`,KHR_TEXTURE_TRANSFORM:`KHR_texture_transform`,KHR_MESH_QUANTIZATION:`KHR_mesh_quantization`,KHR_MATERIALS_EMISSIVE_STRENGTH:`KHR_materials_emissive_strength`,EXT_MATERIALS_BUMP:`EXT_materials_bump`,EXT_TEXTURE_WEBP:`EXT_texture_webp`,EXT_TEXTURE_AVIF:`EXT_texture_avif`,EXT_MESHOPT_COMPRESSION:`EXT_meshopt_compression`,KHR_MESHOPT_COMPRESSION:`KHR_meshopt_compression`,EXT_MESH_GPU_INSTANCING:`EXT_mesh_gpu_instancing`},oS=class{constructor(e){this.parser=e,this.name=aS.KHR_LIGHTS_PUNCTUAL,this.cache={refs:{},uses:{}}}_markDefs(){let 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X(1,1),i.normalTexture.scale!==void 0)){let e=i.normalTexture.scale;o.normalScale.set(e,e)}if(i.occlusionTexture!==void 0&&a!==Qf&&(c.push(t.assignTexture(o,`aoMap`,i.occlusionTexture)),i.occlusionTexture.strength!==void 0&&(o.aoMapIntensity=i.occlusionTexture.strength)),i.emissiveFactor!==void 0&&a!==Qf){let e=i.emissiveFactor;o.emissive=new Q().setRGB(e[0],e[1],e[2],Hl)}return i.emissiveTexture!==void 0&&a!==Qf&&c.push(t.assignTexture(o,`emissiveMap`,i.emissiveTexture,Vl)),Promise.all(c).then(function(){let n=new a(o);return i.name&&(n.name=i.name),GS(n,i),t.associations.set(n,{materials:e}),i.extensions&&WS(r,n,i),n})}createUniqueName(e){let t=Ng.sanitizeNodeName(e||``);return t in this.nodeNamesUsed?t+`_`+ ++this.nodeNamesUsed[t]:(this.nodeNamesUsed[t]=0,t)}loadGeometries(e){let t=this,n=this.extensions,r=this.primitiveCache;function i(e){return n[aS.KHR_DRACO_MESH_COMPRESSION].decodePrimitive(e,t).then(function(n){return tC(n,e,t)})}let a=[];for(let n=0,o=e.length;n$x(e,1)):o.mode===PS.TRIANGLE_FAN&&(e=e.then(e=>$x(e,2))),r[s]={primitive:o,promise:e},a.push(e)}}return Promise.all(a)}loadMesh(e){let t=this,n=this.json,r=this.extensions,i=n.meshes[e],a=i.primitives,o=[];for(let e=0,t=a.length;e0&&qS(d,i),d.name=t.createUniqueName(i.name||`mesh_`+e),GS(d,i),u.extensions&&WS(r,d,u),t.assignFinalMaterial(d),c.push(d)}for(let n=0,r=c.length;n0){let e=t.userData.pivot,r=n[0];t.pivot=new Z().fromArray(e),t.position.x-=e[0],t.position.y-=e[1],t.position.z-=e[2],r.position.set(0,0,0),delete t.userData.pivot}return t})}_loadNodeShallow(e){let t=this.json,n=this.extensions,r=this;if(this.nodeCache[e]!==void 0)return this.nodeCache[e];let i=t.nodes[e],a=i.name?r.createUniqueName(i.name):``,o=[],s=r._invokeOne(function(t){return t.createNodeMesh&&t.createNodeMesh(e)});return s&&o.push(s),i.camera!==void 0&&o.push(r.getDependency(`camera`,i.camera).then(function(e){return r._getNodeRef(r.cameraCache,i.camera,e)})),r._invokeAll(function(t){return t.createNodeAttachment&&t.createNodeAttachment(e)}).forEach(function(e){o.push(e)}),this.nodeCache[e]=Promise.all(o).then(function(t){let o;if(o=i.isBone===!0?new Cp:t.length>1?new Nd:t.length===1?t[0]:new Md,o!==t[0])for(let e=0,n=t.length;e1){let e=r.associations.get(o);r.associations.set(o,{...e})}return r.associations.get(o).nodes=e,o}),this.nodeCache[e]}loadScene(e){let t=this.extensions,n=this.json.scenes[e],r=this,i=new Nd;n.name&&(i.name=r.createUniqueName(n.name)),GS(i,n),n.extensions&&WS(t,i,n);let a=n.nodes||[],o=[];for(let e=0,t=a.length;e{let t=new Map;for(let[e,n]of r.associations)(e instanceof Kf||e instanceof $u)&&t.set(e,n);return e.traverse(e=>{let n=r.associations.get(e);n!=null&&t.set(e,n)}),t})(i),i})}_createAnimationTracks(e,t,n,r,i){let a=[],o=e.name?e.name:e.uuid,s=[];function c(e){e.morphTargetInfluences&&s.push(e.name?e.name:e.uuid)}BS[i.path]===BS.weights?(c(e),e.isGroup&&e.children.forEach(c)):s.push(o);let l;switch(BS[i.path]){case BS.weights:l=Oh;break;case BS.rotation:l=Ah;break;case BS.translation:case BS.scale:l=Mh;break;default:switch(n.itemSize){case 1:l=Oh;break;default:l=Mh;break}break}let u=r.interpolation===void 0?Nl:VS[r.interpolation],d=this._getArrayFromAccessor(n);for(let e=0,n=s.length;e 0.001) { + float mottle = 0.92 + 0.08 * sin(injuryPos.x * 3.1 + injuryPos.y * 2.3) * sin(injuryPos.z * 2.7 - injuryPos.y * 1.9); + float w = (1.0 - smoothstep(radius * 0.2, radius, d)) * mottle; + vec3 tone = mix(hematomaFresh, hematomaDeep, clamp(bruise * 1.2 - 0.2, 0.0, 1.0)); + vec3 stained = mix(diffuseColor.rgb * tone * 2.0, tone * 1.1, 0.35); + diffuseColor.rgb = mix(diffuseColor.rgb, stained, clamp(bruise, 0.0, 1.0) * w * 0.8); + } + float cut = uInjuryCut[i].y; + float halfLength = uInjuryCut[i].x; + if (cut > 0.001 && halfLength > 0.0) { + vec3 local = injuryPos - site; + float along = clamp(local.x, -halfLength, halfLength); + vec2 delta = vec2(local.x - along, local.y - 0.18 * sin(local.x * 3.0)); + float slit = length(delta) + abs(local.z) * 0.25; + float w = 1.0 - smoothstep(0.06 + cut * 0.06, 0.24 + cut * 0.12, slit); + float lip = (1.0 - smoothstep(0.24, 0.55, slit)) * 0.6; + diffuseColor.rgb = mix(diffuseColor.rgb, hematomaFresh * 0.8, cut * lip); + diffuseColor.rgb = mix(diffuseColor.rgb, cutColor, cut * w); + injuryWet = max(injuryWet, cut * w); + } + float blood = uInjuryBlood[i]; + if (blood > 0.001) { + vec3 origin = site + vec3(0.0, -radius * 0.35, 0.0); + float length = 3.5 + blood * 9.0; + float drop = origin.y - injuryPos.y; + if (drop > -0.4 && drop < length && injuryPos.z > origin.z - 3.2) { + float t = clamp(drop / length, 0.0, 1.0); + float wander = 0.4 * sin(injuryPos.y * 1.6 + float(i) * 1.7) + 0.25 * sin(injuryPos.y * 4.3 + float(i)); + float dx = abs(injuryPos.x - origin.x - wander * t); + float width = 0.28 + 0.28 * t + 0.25 * blood; + float edge = width + 0.18; + float stream = (1.0 - smoothstep(width * 0.6, edge, dx)) * (1.0 - t * t) * smoothstep(-0.4, 0.15, drop); + float head = (1.0 - smoothstep(0.0, radius * 0.9, distance(injuryPos, origin))) * 0.7; + float w = clamp(max(stream, head) * min(1.0, blood * 1.4), 0.0, 1.0); + diffuseColor.rgb = mix(diffuseColor.rgb, bloodColor, w * 0.96); + injuryWet = max(injuryWet, w); + } + } + } + injuryWet *= uInjuryWetness; +} +`,dC=` +roughnessFactor = mix(roughnessFactor, 0.18, injuryWet); +`,fC=class{material;sites;uniforms={uInjurySite:{value:[]},uInjuryCut:{value:[]},uInjurySwell:{value:new Float32Array(12)},uInjuryBruise:{value:new Float32Array(12)},uInjuryBlood:{value:new Float32Array(12)},uInjuryJaw:{value:0},uInjuryJawLevel:{value:114.5},uInjuryImpact:{value:new ed(0,-1e3,0,1)},uInjuryImpactPush:{value:new Z},uInjuryNose:{value:new ed(0,-1e3,0,0)},uInjuryWetness:{value:1}};index=new Map;constructor(e,t){if(this.material=e,this.sites=t,t.length!==12)throw Error(`injury shading requires 12 sites`);for(let[e,n]of t.entries())this.index.set(n.name,e),this.uniforms.uInjurySite.value.push(new ed(n.position[0],n.position[1],n.position[2],n.radius)),this.uniforms.uInjuryCut.value.push(new ed(n.cutHalfLength,0,0,0));if(e===null)return;let n=this.uniforms;e.onBeforeCompile=e=>{Object.assign(e.uniforms,n),e.vertexShader=e.vertexShader.replace(`#include `,`#include \n${sC}`).replace(`#include `,`#include \n${cC}`),e.fragmentShader=e.fragmentShader.replace(`#include `,`#include \n${lC}`).replace(`#include `,`#include \n${uC}`).replace(`#include `,`#include \n${dC}`)},e.customProgramCacheKey=()=>`hands-injury-12`,e.needsUpdate=!0}slot(e){let t=this.index.get(e);if(t===void 0)throw Error(`unknown injury site ${e}`);return t}set(e,t){let n=this.slot(e);t.bruise!==void 0&&(this.uniforms.uInjuryBruise.value[n]=Pu.clamp(t.bruise,0,1.2)),t.swell!==void 0&&(this.uniforms.uInjurySwell.value[n]=Pu.clamp(t.swell,0,2.2)),t.cut!==void 0&&(this.uniforms.uInjuryCut.value[n].y=Pu.clamp(t.cut,0,1)),t.blood!==void 0&&(this.uniforms.uInjuryBlood.value[n]=Pu.clamp(t.blood,0,1.4))}impact(e,t,n){let r=this.uniforms.uInjurySite.value[this.slot(e)];this.uniforms.uInjuryImpact.value.set(r.x,r.y,r.z,n),this.uniforms.uInjuryImpactPush.value.set(t[0],t[1],t[2])}setNoseShift(e){let t=this.index.get(`nose`);if(t===void 0)return;let n=this.uniforms.uInjurySite.value[t];this.uniforms.uInjuryNose.value.set(n.x,n.y,n.z,Pu.clamp(e,-1.4,1.4)||0)}update(e){let t=this.uniforms.uInjuryImpactPush.value;t.lengthSq()<1e-6||(t.multiplyScalar(Math.exp(-9*e)),t.lengthSq()<1e-4&&t.set(0,0,0))}get impactDepth(){return this.uniforms.uInjuryImpactPush.value.length()}setJaw(e){this.uniforms.uInjuryJaw.value=Pu.clamp(e,0,1)}clear(){this.uniforms.uInjuryBruise.value.fill(0),this.uniforms.uInjurySwell.value.fill(0),this.uniforms.uInjuryBlood.value.fill(0);for(let e of this.uniforms.uInjuryCut.value)e.y=0;this.uniforms.uInjuryJaw.value=0}level(e){let t=this.slot(e);return{bruise:this.uniforms.uInjuryBruise.value[t],swell:this.uniforms.uInjurySwell.value[t],cut:this.uniforms.uInjuryCut.value[t].y,blood:this.uniforms.uInjuryBlood.value[t]}}},pC=e=>e===`off`?0:e===`reduced`?.35:1;function mC(e,t,n){let r=pC(n),i=n===`full`?1:.6,a=e=>Math.min(1.2,e/380+t.swelling/900),o=e=>Math.min(2.2,(e/520+t.swelling/700)*1.6*i);e.set(`leftEye`,{bruise:a(t.left_eye),swell:o(t.left_eye)}),e.set(`rightEye`,{bruise:a(t.right_eye),swell:o(t.right_eye)});let s=e=>Math.min(1,e/220),c=e=>Math.min(1.4,(e/260+t.bleeding/520)*r);e.set(`leftBrow`,{bruise:Math.min(1,t.left_eye/700),swell:Math.min(1.2,t.left_eye/900)*i,cut:s(t.left_cut),blood:c(t.left_cut)}),e.set(`rightBrow`,{bruise:Math.min(1,t.right_eye/700),swell:Math.min(1.2,t.right_eye/900)*i,cut:s(t.right_cut),blood:c(t.right_cut)});let l=Math.min(1,t.head/950+t.swelling/1100);e.set(`leftCheek`,{bruise:l*.9,swell:Math.min(1.4,t.swelling/800)*i,cut:Math.min(1,Math.max(0,t.left_cut-350)/500),blood:Math.min(1,Math.max(0,t.left_cut-350)/400)*r}),e.set(`rightCheek`,{bruise:l*.85,swell:Math.min(1.4,t.swelling/800)*i,cut:Math.min(1,Math.max(0,t.right_cut-350)/500),blood:Math.min(1,Math.max(0,t.right_cut-350)/400)*r}),e.set(`nose`,{bruise:Math.min(1,t.head/800),swell:Math.min(.8,t.head/1400)*i,blood:Math.min(1.4,(Math.max(0,t.head-160)/520+t.bleeding/420)*r)}),e.set(`mouth`,{bruise:Math.min(.8,t.head/1100),cut:Math.min(1,Math.max(0,t.head-420)/700),blood:Math.min(1.2,(Math.max(0,t.head-280)/650+t.bleeding/500)*r)}),e.set(`chin`,{bruise:Math.min(.7,t.head/1300)});let u=t.left_eye>=t.right_eye?-1:1;e.setNoseShift(u*Math.min(1.1,Math.max(0,t.head-520)/450)*i),e.set(`leftJaw`,{bruise:Math.min(.9,t.left_eye/900+t.head/1600)}),e.set(`rightJaw`,{bruise:Math.min(.9,t.right_eye/900+t.head/1600)}),e.set(`forehead`,{bruise:Math.min(.6,t.swelling/1200),cut:Math.min(1,Math.max(0,t.swelling-520)/480),blood:Math.min(1.2,Math.max(0,t.swelling-520)/420)*r})}function hC(e,t,n){let r=pC(n),i=Math.min(1.1,t.body/620);e.set(`leftRibs`,{bruise:i,swell:Math.min(1,t.body/1300)}),e.set(`rightRibs`,{bruise:i*.9,swell:Math.min(1,t.body/1400)}),e.set(`solarPlexus`,{bruise:Math.min(1,t.body/800)}),e.set(`leftPec`,{bruise:Math.min(.8,t.body/1100)}),e.set(`rightPec`,{bruise:Math.min(.8,t.body/1150)});let a=Math.min(1.4,(t.bleeding/380+(t.left_cut+t.right_cut)/900)*r);e.set(`neckSmear`,{blood:a}),e.set(`leftShoulderSmear`,{blood:Math.min(1,t.left_cut/600)*r}),e.set(`rightShoulderSmear`,{blood:Math.min(1,t.right_cut/600)*r})}var gC={hips:rC.hips,spine:rC.spine,chest:`Spine1_024`,upperChest:rC.chest,neck:`Neck_012`,head:rC.head,clavicleL:`LeftShoulder_09`,shoulderL:rC.shoulderL,elbowL:rC.elbowL,gloveL:rC.gloveL,clavicleR:`RightShoulder_020`,shoulderR:rC.shoulderR,elbowR:rC.elbowR,gloveR:rC.gloveR,hipL:rC.hipL,kneeL:rC.kneeL,ankleL:rC.ankleL,toeL:`LeftToeBase_011`,hipR:rC.hipR,kneeR:rC.kneeR,ankleR:rC.ankleR,toeR:`RightToeBase_022`},_C=new Z,vC=new Z,yC=new Z,bC=new ad,xC=new Fu,SC=new Fu,CC=new Z,wC=new Z,TC=new Z,EC=new Z,DC=new Z,OC=new Z,kC=new Z,AC=new Z,jC=new Z,MC=new Z;function NC(e,t){return t.setFromMatrixPosition(e.matrixWorld)}function PC(e,t){return e.matrixWorld.decompose(CC,t,wC),t}function FC(e,t,n,r){return vC.copy(e).normalize(),n===`z`?(yC.copy(t).addScaledVector(vC,-t.dot(vC)),yC.lengthSq()<1e-8&&yC.set(0,0,1).addScaledVector(vC,-vC.z),yC.normalize(),_C.crossVectors(vC,yC).normalize()):(_C.copy(t).addScaledVector(vC,-t.dot(vC)),_C.lengthSq()<1e-8&&_C.set(1,0,0).addScaledVector(vC,-vC.x),_C.normalize(),yC.crossVectors(_C,vC).normalize()),bC.makeBasis(_C,vC,yC),r.setFromRotationMatrix(bC)}var IC=class{bones;metrics;restLocal=new Map;restLocalPosition=new Map;limb={reached:!1,joint:new Z};constructor(e){let t=new Map;e.traverse(e=>{e instanceof Cp&&t.set(e.name,e)});let n={};for(let[e,r]of Object.entries(gC)){let i=t.get(r);if(i===void 0)throw Error(`fighter rig missing bone ${r} (${e})`);n[e]=i}this.bones=n,e.updateMatrixWorld(!0);for(let e of t.values())this.restLocal.set(e,e.quaternion.clone()),this.restLocalPosition.set(e,e.position.clone());let r=(e,t)=>NC(n[e],TC).distanceTo(NC(n[t],EC)),i=NC(n.hips,TC).clone(),a=NC(n.hips.parent??e,EC).clone(),o=n.hips.position.length(),s=i.distanceTo(a);this.metrics={hipsHeight:i.y,headHeight:NC(n.head,TC).y,chestHeight:NC(n.upperChest,TC).y,ankleHeight:NC(n.ankleL,TC).y,armL:{upper:r(`shoulderL`,`elbowL`),lower:r(`elbowL`,`gloveL`)},armR:{upper:r(`shoulderR`,`elbowR`),lower:r(`elbowR`,`gloveR`)},legL:{upper:r(`hipL`,`kneeL`),lower:r(`kneeL`,`ankleL`)},legR:{upper:r(`hipR`,`kneeR`),lower:r(`kneeR`,`ankleR`)},footLength:r(`ankleL`,`toeL`),unitsPerMeter:s>1e-6?o/s:1}}resetToRest(){for(let[e,t]of this.restLocal){e.quaternion.copy(t);let n=this.restLocalPosition.get(e);n!==void 0&&e.position.copy(n)}}restLocalQuaternion(e){return this.restLocal.get(e)??e.quaternion}position(e,t){return NC(this.bones[e],t)}setWorldRotation(e,t){let n=e.parent;n===null?e.quaternion.copy(t):(PC(n,SC),e.quaternion.copy(SC.invert().multiply(t)).normalize()),e.updateWorldMatrix(!1,!1)}setWorldFrame(e,t,n,r){this.setWorldRotation(e,FC(t,n,r,xC))}setWorldPosition(e,t){let n=e.parent;n===null?e.position.copy(t):(e.position.copy(t),n.worldToLocal(e.position)),e.updateWorldMatrix(!1,!1)}aimAt(e,t,n){if(e.updateWorldMatrix(!1,!1),NC(e,TC),DC.subVectors(t,TC),DC.lengthSq()<1e-10)return;PC(e,xC);let r=n===`z`?MC.set(0,0,1):MC.set(1,0,0);this.setWorldFrame(e,DC,r.applyQuaternion(xC),n)}solveLimb(e,t,n,r,i,a,o,s=.01){e.updateWorldMatrix(!1,!1);let c=NC(e,TC);DC.subVectors(r,c);let l=n.upper+n.lower-s,u=Pu.clamp(DC.length(),Math.abs(n.upper-n.lower)+.005,l),d=DC.length()<=l;DC.lengthSq()<1e-10&&DC.set(0,-1,0),DC.normalize(),OC.copy(i).addScaledVector(DC,-i.dot(DC)),OC.lengthSq()<1e-8&&(OC.set(0,0,1).addScaledVector(DC,-DC.z),OC.lengthSq()<1e-8&&OC.set(1,0,0)),OC.normalize();let f=Pu.clamp((n.upper*n.upper+u*u-n.lower*n.lower)/(2*n.upper*u),-1,1),p=n.upper*f,m=n.upper*Math.sqrt(Math.max(0,1-f*f));kC.copy(c).addScaledVector(DC,p).addScaledVector(OC,m),AC.crossVectors(OC,DC).multiplyScalar(o).normalize(),jC.copy(kC).sub(c),this.setWorldFrame(e,jC,AC,a),t.updateWorldMatrix(!1,!1);let h=NC(t,EC);return jC.copy(c).addScaledVector(DC,u).sub(h),this.setWorldFrame(t,jC,AC,a),this.limb.reached=d,this.limb.joint.copy(h),this.limb}},LC=new Z(.2018,.081,-.027),RC=new Z(-.2018,.081,-.027),zC=(e,t,n)=>new Z(e,t,n),BC=(e,t,n)=>{let r=Pu.clamp((n-e)/Math.max(1e-6,t-e),0,1);return r*r*(3-2*r)},VC=(e,t=1.7)=>Pu.clamp(e,0,1)**+t,HC=(e,t=2)=>1-(1-Pu.clamp(e,0,1))**t,UC=new Fu,WC=new Z,GC=new Z,KC=new Z,qC=new Z,JC=new Z,YC=new Fu,XC=new Fu,ZC=new hd,QC=new Z(0,1,0),$C=[[`spine`,.25,.2],[`chest`,.55,.5],[`upperChest`,1,1]],ew=class{rig;chestLocal=new Z;constructor(e){this.rig=e}toWorld(e,t){return t.copy(e).applyQuaternion(UC).add(WC)}dirToWorld(e,t){return t.copy(e).applyQuaternion(UC)}setYawPitchRoll(e,t,n,r){ZC.set(n,t,r,`YXZ`),YC.setFromEuler(ZC),XC.copy(UC).multiply(YC),this.rig.setWorldRotation(e,XC)}apply(e,t){let n=this.rig,r=n.bones;n.resetToRest(),e.updateMatrixWorld(!0),PC(e,UC),NC(e,WC);let i=t.torso;this.toWorld(i.hips,GC),n.setWorldPosition(r.hips,GC),this.setYawPitchRoll(r.hips,i.hipsYaw,i.hipsPitch,i.hipsRoll);let a=i.shouldersYaw-i.hipsYaw;for(let e=0;e<$C.length;e+=1){let[t,n,o]=$C[e];this.setYawPitchRoll(r[t],i.hipsYaw+a*n,i.hipsPitch+i.spinePitch*o,i.hipsRoll+i.spineRoll*o)}let o=i.shouldersYaw+(i.headYaw-i.shouldersYaw)*.45,s=i.hipsPitch+i.spinePitch+(i.headPitch-i.spinePitch)*.5;this.setYawPitchRoll(r.neck,o,s,i.hipsRoll+i.spineRoll*.6+i.headRoll*.4),this.setYawPitchRoll(r.head,i.headYaw,i.headPitch,i.headRoll),i.headOffset.lengthSq()>0&&(NC(r.head,GC),this.dirToWorld(i.headOffset,KC),GC.add(KC),n.setWorldPosition(r.head,GC)),this.solveArm(`L`,t.handL,t.shrugL),this.solveArm(`R`,t.handR,t.shrugR),this.solveLeg(`L`,t.footL),this.solveLeg(`R`,t.footR)}solveArm(e,t,n){let r=this.rig,i=r.bones,a=e===`L`?i.clavicleL:i.clavicleR,o=e===`L`?i.shoulderL:i.shoulderR,s=e===`L`?i.elbowL:i.elbowR,c=e===`L`?i.gloveL:i.gloveR,l=e===`L`?r.metrics.armL:r.metrics.armR,u=e===`L`?LC:RC;this.chestLocal.copy(u),this.chestLocal.z+=n*.06,this.chestLocal.y+=n*.035,this.chestLocal.x*=1-n*.08,qC.copy(this.chestLocal).multiplyScalar(r.metrics.unitsPerMeter),i.upperChest.localToWorld(qC),r.aimAt(a,qC,`z`),o.updateWorldMatrix(!1,!1),this.toWorld(t.position,GC),this.dirToWorld(t.pole,KC),r.solveLimb(o,s,l,GC,KC,`z`,e===`L`?1:-1,.012),c.updateWorldMatrix(!1,!1),this.dirToWorld(t.knuckles,qC),this.dirToWorld(t.palm,JC),r.setWorldFrame(c,qC,JC,`z`)}solveLeg(e,t){let n=this.rig,r=n.bones,i=e===`L`?r.hipL:r.hipR,a=e===`L`?r.kneeL:r.kneeR,o=e===`L`?r.ankleL:r.ankleR,s=e===`L`?r.toeL:r.toeR,c=e===`L`?n.metrics.legL:n.metrics.legR;this.toWorld(t.position,GC),this.dirToWorld(t.toe,qC).normalize();let l=n.metrics.footLength;JC.copy(qC).multiplyScalar(l).addScaledVector(QC,-n.metrics.ankleHeight).normalize(),t.heel!==0&&(GC.addScaledVector(JC,l),YC.setFromAxisAngle(KC.crossVectors(qC,QC).normalize(),-t.heel),JC.applyQuaternion(YC),GC.addScaledVector(JC,-l)),this.dirToWorld(t.pole,KC),n.solveLimb(i,a,c,GC,KC,`x`,-1,.02),o.updateWorldMatrix(!1,!1),n.setWorldFrame(o,JC,QC,`z`),s.updateWorldMatrix(!1,!1),n.setWorldFrame(s,qC,QC,`z`)}},tw={bladeYaw:-1.05,hipsHeight:.8,leadFoot:zC(.12,0,.24),rearFoot:zC(-.1,0,-.34),leadToe:zC(-.34,0,.94),rearToe:zC(-.77,0,.64),relaxedLead:zC(.11,-.22,.36),relaxedRear:zC(-.11,-.16,.1),guardHighLead:zC(.14,-.02,.17),guardHighRear:zC(-.1,-.02,.11),guardLowLead:zC(.15,-.36,.22),guardLowRear:zC(-.13,-.34,.12),leadPole:zC(.45,-1,.2),rearPole:zC(-.5,-1,-.05),leadKnuckles:zC(.1,.55,.8),leadPalm:zC(-.9,.15,-.35),rearKnuckles:zC(-.05,.7,.7),rearPalm:zC(.95,.1,-.25)};function nw(e,t,n=new Z){return n.set(e.x*t,e.y,e.z)}var rw={MHeadMat0:`head`,GlovesMat0:`gloves`,MBodyMat0:`body`,ShoesMat0:`shoes`,PantsMat0:`pants`},iw=new Map,aw=new Map,ow=null,sw=null;function cw(e){return e.colorSpace=Vl,e.flipY=!1,e}function lw(e){let t=iw.get(e);if(t!==void 0)return Promise.resolve(t);let n=aw.get(e);if(n!==void 0)return n;let r=new Gh().loadAsync(iC[e]).then(t=>(iw.set(e,cw(t)),t));return aw.set(e,r),r}function uw(){return Promise.all(Object.keys(iC).map(lw))}async function dw(){let e=Uint8Array.from(atob(nC),e=>e.charCodeAt(0)),t=new Response(e).body;if(t===null)throw Error(`fighter_glb_stream_unavailable`);return new Response(t.pipeThrough(new DecompressionStream(`gzip`))).arrayBuffer()}function fw(){if(ow===null){let e=dw().then(e=>new Promise((t,n)=>{new nS().parse(e,``,t,e=>n(e instanceof Error?e:Error(String(e))))}));ow=Promise.all([e,uw()]).then(([e])=>(sw=e.scene,e))}return ow}function pw(){mw(sw,iw.values())}function mw(e,t){e?.traverse(e=>{e instanceof up&&e.geometry.dispose()});for(let e of t)e.dispose()}function hw(e){e.traverse(e=>{e instanceof Sp&&e.skeleton.dispose()})}function gw(e){let t=iw.get(e);if(t!==void 0)return t;let n=cw(new Gh().load(iC[e]));return iw.set(e,n),n}function _w(e,t){let n=t.bodyMap!==void 0,r=[],i=[],a=new Map,o=null,s=null,c=null;if(e.traverse(e=>{if(!(e instanceof Sp)||Array.isArray(e.material))return;let l=e.material.name,u=rw[l];if(u===void 0)throw Error(`fighter GLB has unsupported material ${l}`);let d=a.get(l);if(d===void 0){let e=l===`MHeadMat0`||l===`MBodyMat0`,f=l===`GlovesMat0`?t.gear:l===`PantsMat0`?t.pants??t.gear:16777215,p=l===`MBodyMat0`&&t.bodyMap!==void 0?t.bodyMap:gw(u);d=e&&!n?new ch({map:p,color:f,roughness:.58,metalness:.02,clearcoat:.25,clearcoatRoughness:.6}):new sh({map:p,color:f,roughness:e?l===`MBodyMat0`?.85:.58:.4,metalness:e?.02:.03}),d.name=l,a.set(l,d),i.push(d),e&&r.push(d),l===`GlovesMat0`&&(o=d),l===`MHeadMat0`&&(s=new fC(n?null:d,aC)),l===`MBodyMat0`&&(c=new fC(n?null:d,oC))}e.material=d,e.castShadow=!n,e.receiveShadow=!0,e.frustumCulled=!1}),r.length!==2||o===null||i.length!==5||s===null||c===null)throw Error(`fighter GLB material contract failed: ${r.length} skin, ${i.length} total`);return{skin:r,gloves:o,owned:i,headInjury:s,bodyInjury:c}}var vw=(e,t,n,r)=>e+(t-e)*(1-Math.exp(-n*r)),yw=(e,t,n,r)=>e+(((t-e+Math.PI)%(Math.PI*2)+Math.PI*2)%(Math.PI*2)-Math.PI)*(1-Math.exp(-n*r)),bw=Pu.clamp,xw=class{root=new Nd;bones=new Map;rig;metrics;skinMaterials;ownedMaterials;gearMaterial;headMeshes=[];handMeshes={left:[],right:[]};decapitated=!1;dismemberedHands={left:!1,right:!1};gearBaseColor;skinBaseColor;headInjury;bodyInjury;constructor(e,t){let n=eS(e.scene);n.scale.setScalar(1),this.root.add(n);let r=_w(n,t);this.skinMaterials=r.skin,this.ownedMaterials=r.owned,this.gearMaterial=r.gloves,this.headInjury=r.headInjury,this.bodyInjury=r.bodyInjury,this.gearBaseColor=new Q(t.gear),this.skinBaseColor=new Q(t.skin),n.traverse(e=>{e instanceof Sp&&e.name===`BoxerHead`&&this.headMeshes.push(e),e instanceof Sp&&e.name===`BoxerGloveLeft`&&this.handMeshes.left.push(e),e instanceof Sp&&e.name===`BoxerGloveRight`&&this.handMeshes.right.push(e),e instanceof Cp&&this.bones.set(e.name,e)});let i=Object.values(rC).filter(e=>!this.bones.has(e));if(i.length>0)throw Error(`fighter GLB missing required bones: ${i.join(`, `)}`);if(this.headMeshes.length!==1)throw Error(`fighter GLB requires one BoxerHead mesh, found ${this.headMeshes.length}`);for(let e of[`left`,`right`])if(this.handMeshes[e].length!==1)throw Error(`fighter GLB requires one ${e} glove mesh, found ${this.handMeshes[e].length}`);this.root.updateMatrixWorld(!0),this.rig=new IC(this.root);let a=this.rig.metrics;this.metrics={armUpper:a.armL.upper,armFore:a.armL.lower,legThigh:a.legL.upper,legShin:a.legL.lower,headRestY:a.headHeight,chestRestY:a.chestHeight,ankleRestY:a.ankleHeight}}bone(e){return this.bones.get(rC[e]??e)??null}get gloveGear(){return this.gearMaterial}get headMesh(){return this.headMeshes[0]}gloveMesh(e){return this.handMeshes[e][0]}get skin(){return this.skinMaterials[0]}get isDecapitated(){return this.decapitated}setDecapitated(e){this.decapitated=e;for(let t of this.headMeshes)t.visible=!e;this.bone(`head`).visible=!e}isHandDismembered(e){return this.dismemberedHands[e]}setHandDismembered(e,t){this.dismemberedHands[e]=t;for(let n of this.handMeshes[e])n.visible=!t}setSkinClearcoat(e){for(let t of this.skinMaterials)t instanceof ch&&(t.clearcoat=e)}dispose(){for(let e of this.ownedMaterials)e.dispose();hw(this.root)}},Sw=new Q(6031886),Cw=(e,t,n,r,i)=>{let a=e.value,o=e.velocity;o.addScaledVector(a,-n*t).multiplyScalar(Math.exp(-r*t)),a.addScaledVector(o,t),a.length()>i&&a.setLength(i)},ww=.06,Tw=150,Ew=.75,Dw=.38,Ow=.72,kw=.5,Aw=.2,jw=.55,Mw=.7,Nw=class{mapping;boxer;solver;yaw=0;yawInitialized=!1;rootX=null;rootZ=0;punchActive=!1;punchAgeTicks=0;punchTotalTicks=1;punchClass=`jab`;punchHand=`left`;punchTarget=`head`;punchPower=`normal`;punchTiming=Ib(`jab`,`head`,`normal`);actionId=null;completedActionId=null;ownActionId=null;ownLeadTicks=0;ownAuthoritativeAge=null;ownWaitedTicks=0;ownExpectedTicks=0;ownPulled=!1;ownSequence=null;ownStarted=!1;ownPressedAt=0;ownRefused=!1;ownQueued=null;contactId=null;contactParried=!1;shownFighter=null;shownOpponent=null;retiredOwnIds=[];hitstop=0;hitstopScale=1;downState=`up`;fallAge=0;riseProgress=0;riseFrom=0;fallSide=0;fallProne=!1;landProne=!1;landSide=0;landShift=new Z;landSettled=!1;liveOpponentHead=new Z;hasLiveHead=!1;guardOpponentHead=new Z;opponentHeadOffset=new Z;opponentSteadySeconds=0;followHead=0;aimActionId=null;headKick={value:new Z,velocity:new Z};torsoKick={value:new Z,velocity:new Z};rootKick={value:new Z,velocity:new Z};coverKick={value:new Z,velocity:new Z};foldDelay=0;pendingFold=0;guardKick=0;guardHigh=0;guardLow=0;slip=0;weave=0;weaveTime=0;pull=0;crouchExtra=0;bouncePhase=0;weightPhase=0;stunPhase=0;feintTimer=2;feint=0;stunAmount=0;tired=0;clinchWeight=0;foulWeight=0;tauntWeight=0;tauntEnd=null;lastSpeed=0;stool;stoolRoot=new Z;stoolYaw=0;enswell;treatTarget=new Z;treatScratch=new Z;treatFacing=new Z(0,0,-1);treatFacingLocal=new Z;treatSide=1;treating=!1;treatWeight=0;resting=!1;seated=0;stillTime=0;celebrateTime=0;celebration=0;waveTime=0;wave=0;breakTime=0;breakWeight=0;breakFighters=[new Z,new Z];breakAimed=!1;attending=!1;attendWeight=0;countdownTicks=null;countdownEnd=null;touchWeight=0;touchOffset=new Z;touchVelocity=new Z;debugHoldImpact=!1;feet=[{planted:new Z,from:new Z,to:new Z,progress:1,stepping:!1,duration:.2},{planted:new Z,from:new Z,to:new Z,progress:1,stepping:!1,duration:.2}];feetInitialized=!1;dislocation=null;scratch=new Z;scratchB=new Z;scratchC=new Z;scratchD=new Z;scratchE=new Z;clinchCentre=new Z;clinchForward=new Z;clinchTemp=new Z;scratchQ=new Fu;headWorld=new Z;hand={L:this.makeHand(),R:this.makeHand()};punchGuard=this.makeHand();punchDir=new Z;punchContact=new Z;punchStart=new Z;punchSweepFrom=new Z;punchSweepTo=new Z;punchMid=new Z;foot={L:this.makeFoot(),R:this.makeFoot()};torso={hips:new Z,hipsYaw:0,hipsPitch:0,hipsRoll:0,shouldersYaw:0,spinePitch:0,spineRoll:0,headYaw:0,headPitch:0,headRoll:0,headOffset:new Z};pose;downStanding=rT();downFrom=rT();downTo=rT();downResult=rT();downStand=1;fallStart=rT();fallStartStand=1;fallFromGetUp=!1;referee;refereeCount=0;refereeCounting=!1;countChangedTick=null;constructor(e,t,n={}){this.mapping=t,this.boxer=e,this.referee=n.referee===!0,this.solver=new ew(e.rig),this.pose={torso:this.torso,handL:this.hand.L,handR:this.hand.R,footL:this.foot.L,footR:this.foot.R,shrugL:0,shrugR:0},this.stool=TT(),this.stool.group.position.set(0,0,.02),e.root.add(this.stool.group),this.enswell=wT(),e.rig.bones.gloveL.add(this.enswell.group)}setResting(e){this.resting=e}get stoolVisible(){return this.stool.group.visible}celebrate(e=4.4){this.celebrateTime=e}resetTransient(e=!1){this.downState=e?`down`:`up`,this.landSettled=!1,this.fallAge=e?Ew:0,this.riseProgress=0,this.hitstop=0,this.hitstopScale=1;for(let e of[this.headKick,this.torsoKick,this.rootKick,this.coverKick])e.value.set(0,0,0),e.velocity.set(0,0,0);this.foldDelay=0,this.pendingFold=0,this.guardKick=0,this.stunAmount=0,this.celebrateTime=0,this.celebration=0,this.waveTime=0,this.wave=0,this.seated=0,this.stillTime=0,this.rootX=null,this.yawInitialized=!1,this.feetInitialized=!1,this.retirePunch(),this.ownQueued=null,this.completedActionId=null,this.retiredOwnIds.length=0}waveOff(e=2.6){this.waveTime=e}setCountdown(e){this.countdownTicks=e}attend(e){this.attending=e}treat(e,t,n=1){this.treating=e!==null,e!==null&&(this.treatTarget.copy(e),t!==void 0&&this.treatFacing.copy(t),this.treatSide=n)}breakClinch(e=1.3){this.breakTime=e}get breaking(){return this.breakTime>0}aimBreak(e,t){this.breakFighters[0].copy(e),this.breakFighters[1].copy(t),this.breakAimed=!0}makeHand(){return{position:new Z,knuckles:new Z(0,1,0),palm:new Z(0,0,1),pole:new Z(0,-1,0)}}makeFoot(){return{position:new Z,toe:new Z(0,0,1),heel:0,pole:new Z(0,0,1)}}get currentRoot(){return{x:this.rootX??0,z:this.rootZ}}get isDown(){return this.downState!==`up`}setRefereeCount(e,t){(e!==this.refereeCounting||t!==this.refereeCount)&&(this.countChangedTick=null),this.refereeCounting=e,this.refereeCount=t}predict(e,t,n,r=0,i){if(e.kind!==`punch`||e.id===void 0)return;let a={action:{...e,id:e.id},timing:i??Ib(e.class,e.target,e.power),leadTicks:r,pressedAt:t,sequence:null,started:!1,waited:0};if(this.punchActive&&this.ownActionId!==null&&this.ownAuthoritativeAge===null&&!this.ownPulled&&!this.ownStarted&&(t-this.ownPressedAt)*n0||e.clinch_ticks>0||e.clinch_startup_ticks>0,a=this.ownQueued;if(a!==null&&(a.sequence??=r?.(a.action.id)??null,e.action_id===a.action.id?a.started=!0:!a.started&&(i||a.sequence!==null&&e.last_input_sequence>=a.sequence&&e.queued_actions===0)&&(this.ownQueued=null)),!this.punchActive||this.ownActionId===null||this.ownPulled||this.ownRefused)return;this.ownStarted||(this.ownSequence??=r?.(this.ownActionId)??null);let o=e.action_id===this.ownActionId;o&&(this.ownStarted=!0);let s=this.ownQueued;if(s!==null&&s.sequence!==null&&r!==null&&!this.ownStarted&&this.ownSequence===null&&this.ownAuthoritativeAge===null){this.ownActionId=null,this.ownQueued=null,this.retirePunch(),this.startOwnPunch(s,Math.max(0,s.leadTicks-s.waited));return}(o?i&&e.action_contact_tick===null:!this.ownStarted&&this.ownAuthoritativeAge===null&&(i||this.ownSequence!==null&&e.last_input_sequence>=this.ownSequence&&e.queued_actions===0))&&(this.ownRefused=!0,this.punchAgeTicks0)?Nb(this.punchTiming):this.punchTotalTicks+1}releaseQueuedPress(e,t){let n=this.ownQueued;n!==null&&(n.waited+=e*30,!(this.punchActive&&!this.ownPulled&&this.punchAgeTicks6&&this.retiredOwnIds.shift()),this.actionId=null,this.punchActive=!1,this.ownActionId=null,this.ownLeadTicks=0,this.ownAuthoritativeAge=null,this.ownWaitedTicks=0,this.ownExpectedTicks=0,this.ownPulled=!1,this.ownSequence=null,this.ownStarted=!1,this.ownRefused=!1}landedHit(e){this.hitstop=Math.max(this.hitstop,e?.045:.078)}setArcadeDislocation(e){this.dislocation=e,this.boxer.headInjury.setJaw(+(e===`jaw`))}react(e,t=`head`,n=1,r=null,i=null,a=90){let o=bw(a/Tw,0,1),s=(.55+o*1.05)*(e===`block`?.35:1),c=i===`left`?1:i===`right`||n>=0?-1:1;if(t===`body`){switch(r){case`hook`:this.torsoKick.velocity.x+=3*s,this.torsoKick.velocity.z+=4.6*s*c,this.rootKick.velocity.x+=.5*s*c,this.coverKick.velocity.x+=2.2*s*c;break;case`uppercut`:this.rootKick.velocity.y+=.9*s,this.torsoKick.velocity.x-=1.6*s,this.foldDelay=.1,this.pendingFold=5.2*s;break;default:this.torsoKick.velocity.x+=4.6*s;break}this.rootKick.velocity.z-=.45*s,this.headKick.velocity.z-=.6*s,this.headKick.velocity.y-=.7*s,this.guardKick=Math.max(this.guardKick,.6*s)}else{switch(e===`hit`&&(this.guardKick=Math.max(this.guardKick,.4*s)),r){case`hook`:this.headKick.velocity.x+=2.6*s*c,this.headKick.velocity.z-=.7*s,this.torsoKick.velocity.z+=.9*s*c;break;case`uppercut`:this.headKick.velocity.y+=2.2*s,this.headKick.velocity.z-=1.2*s,this.torsoKick.velocity.x-=1.2*s;break;case`straight`:this.headKick.velocity.z-=2.4*s,this.torsoKick.velocity.x-=.6*s;break;default:this.headKick.velocity.z-=1.5*s,this.torsoKick.velocity.x-=.35*s;break}this.rootKick.velocity.z-=.45*s,e===`block`&&(this.guardKick=Math.max(this.guardKick,.9*s))}e===`hit`&&(this.dentSurface(t,c,r,o),this.fallSide=r===`hook`?c:c*.5,this.fallProne=r===`hook`||t===`body`)}dentSurface(e,t,n,r){let i=1.1+r*2.1;if(e===`body`){let e=n===`hook`?t>0?`rightRibs`:`leftRibs`:`solarPlexus`;this.boxer.bodyInjury.impact(e,[n===`hook`?t*i*.8:0,0,-i],9);return}n===`hook`?this.boxer.headInjury.impact(t>0?`rightCheek`:`leftCheek`,[t*i,0,-i*.35],5.5):n===`uppercut`?this.boxer.headInjury.impact(`chin`,[0,i*.7,-i*.6],5):this.boxer.headInjury.impact(n===`jab`?`nose`:`mouth`,[0,0,-i],4.5)}stepFeet(e,t,n,r,i,a){let o=this.scratch,s=this.scratchQ.setFromAxisAngle(ET,a);for(let a=0;a<2;a+=1){let c=this.feet[a],l=a===0==t>0?tw.leadFoot:tw.rearFoot;if(this.referee?o.set(a===0?.16:-.16,0,a===0?.02:-.02).applyQuaternion(s).add(i):o.set(l.x*t,0,l.z).applyQuaternion(s).add(i),o.y=0,!this.feetInitialized){c.planted.copy(o),c.progress=1,c.stepping=!1;continue}if(c.stepping){c.progress=Math.min(1,c.progress+e/c.duration),c.progress>=1&&(c.stepping=!1,c.planted.copy(c.to));continue}let u=this.feet[1-a];c.planted.distanceTo(o)>(n>.05?.09:.14)&&!u.stepping&&(c.stepping=!0,c.progress=0,c.duration=bw(.24-n*.07,.15,.24),c.from.copy(c.planted),c.to.copy(o).addScaledVector(r,c.duration*.6),c.to.y=0)}this.feetInitialized=!0}footWorld(e,t){let n=this.feet[e];if(!n.stepping)return t.copy(n.planted),0;let r=HC(n.progress,1.6);return t.copy(n.from).lerp(n.to,r),Math.sin(n.progress*Math.PI)*.055}update(e,t,n,r,i,a,o,s){let c=this.boxer,l=e.stance===`orthodox`?1:-1,u=i?.35:1,d=this.touchWalk(e,t,n,o),f=this.mapping.x(e.x)+d.x,p=this.mapping.z(e.y)+d.z;this.rootX===null&&(this.rootX=f,this.rootZ=p);let m=LT*Math.max(n,1/60);this.rootX+=bw(f-this.rootX,-m,m),this.rootZ+=bw(p-this.rootZ,-m,m);let h=Math.atan2(e.facing_x,-e.facing_y);this.yawInitialized||=(this.yaw=h,!0);let g=this.punchActive?3:this.downState===`up`?9:4;this.yaw=yw(this.yaw,h,g,n),c.root.position.set(this.rootX,0,this.rootZ),c.root.rotation.set(0,this.yaw,0),this.hitstop=Math.max(0,this.hitstop-n),this.hitstopScale=this.hitstop>0?.12:1;let _=n*this.hitstopScale;this.syncAction(e,t,o,_),this.debugHoldImpact||(this.boxer.headInjury.update(_),this.boxer.bodyInjury.update(_)),s!==void 0&&this.trackOpponentHead(t,s,n);let v=this.scratchB.set(this.mapping.x(e.velocity_x)*30,0,this.mapping.z(e.velocity_y)*30).add(this.touchVelocity),y=v.length();this.lastSpeed=y,this.stillTime=y<.03?this.stillTime+n:0;let b=this.resting&&this.stillTime>.2&&this.downState===`up`;this.seated=vw(this.seated,+!!b,b?2.2:4,n);let x=this.resting&&this.stillTime>.05&&this.downState===`up`;x&&(this.stoolRoot.set(this.rootX,0,this.rootZ),this.stoolYaw=this.yaw),this.stool.group.visible=x||this.seated>Fw&&this.downState===`up`,this.stool.group.position.set(this.stoolRoot.x-this.rootX,0,this.stoolRoot.z-this.rootZ).add(this.scratch.set(0,0,.02).applyAxisAngle(ET,this.stoolYaw)).applyAxisAngle(ET,-this.yaw),this.stool.group.rotation.y=this.stoolYaw-this.yaw,this.celebrateTime=Math.max(0,this.celebrateTime-n),this.celebration=vw(this.celebration,+(this.celebrateTime>0&&this.downState===`up`),3.5,n),this.waveTime=Math.max(0,this.waveTime-n),this.wave=vw(this.wave,+(this.waveTime>0&&this.downState===`up`),4,n),this.breakTime=Math.max(0,this.breakTime-n),this.breakWeight=vw(this.breakWeight,+(this.breakTime>0&&this.downState===`up`),6,n),this.attendWeight=vw(this.attendWeight,+!!this.attending,2.5,n),this.treatWeight=vw(this.treatWeight,+!!this.treating,3,n),this.enswell.group.visible=this.treatWeight>.4;let S=this.countdownTicks!==null&&this.countdownTicks<=Bw&&this.countdownTicks>=Vw;this.touchWeight=vw(this.touchWeight,+!!S,6,n);let C=e.stamina/Math.max(1,e.maximum_stamina);this.tired=vw(this.tired,bw((.55-C)/.5,0,1),2,n),this.stunAmount=vw(this.stunAmount,Math.min(1,e.stunned_ticks/24),8,n);let w=e.defense;this.guardHigh=vw(this.guardHigh,+(w===`guard_high`),14,n),this.guardLow=vw(this.guardLow,+(w===`guard_low`),14,n);let T=w===`slip_left`?1:w===`slip_right`?-1:0;this.slip=vw(this.slip,T,16,n);let E=w===`weave`;this.weaveTime=E?this.weaveTime+n:0,this.weave=vw(this.weave,+!!E,14,n),this.pull=vw(this.pull,+(w===`pull`),14,n),this.clinchWeight=vw(this.clinchWeight,+(e.clinch_ticks>0||e.clinch_startup_ticks>0),10,n),this.foulWeight=vw(this.foulWeight,+!!e.is_foul_recovery_target,8,n),this.tauntWeight=vw(this.tauntWeight,+(e.taunt_ticks>0),10,n),this.tauntEnd=ST(this.tauntEnd,o,e.taunt_ticks>0?e.taunt_ticks:null),Cw(this.headKick,n,190,7.5,.24),Cw(this.torsoKick,n,150,7,.7),Cw(this.rootKick,n,120,8,.12),Cw(this.coverKick,n,110,15,.3),this.foldDelay>0&&(this.foldDelay-=n,this.foldDelay<=0&&(this.torsoKick.velocity.x+=this.pendingFold,this.pendingFold=0)),this.guardKick=Math.max(0,this.guardKick-n*2.4),this.updateDownState(e,n,y);let D=(1.9-this.tired*.7)*(1-this.stunAmount*.6);this.bouncePhase+=n*D*Math.PI*2*u,this.weightPhase+=n*.55*Math.PI*2*u,this.stunPhase+=n*5.5,this.feintTimer-=n,this.feintTimer<=0&&!this.punchActive&&y<.05&&this.downState===`up`&&(this.feintTimer=2.5+this.bouncePhase%1.7,this.feint=1),this.feint=Math.max(0,this.feint-n*3.5);let O=this.scratchC.set(this.rootX,0,this.rootZ);(this.downState===`up`||this.downState===`rising`)&&this.stepFeet(n,l,y,v,O,this.yaw);let ee=this.scratchQ.setFromAxisAngle(ET,-this.yaw),k=l>0?this.foot.L:this.foot.R,A=l>0?this.foot.R:this.foot.L,te=l>0?0:1,j=+(l>0),M=this.footWorld(te,k.position),ne=this.footWorld(j,A.position);k.position.sub(O).applyQuaternion(ee),A.position.sub(O).applyQuaternion(ee);let N=this.boxer.rig.metrics.ankleHeight;k.position.y=N+M,A.position.y=N+ne,nw(tw.leadToe,l,k.toe),nw(tw.rearToe,l,A.toe),k.heel=0,A.heel=0,k.pole.copy(k.toe).setY(.35).normalize(),A.pole.copy(A.toe).setY(.35).normalize();let P=this.torso,F=tw.bladeYaw*l,re=Math.sin(this.bouncePhase)*.012*(1-this.stunAmount)*(y>.6?.6:1),ie=Math.sin(this.weightPhase)*.02,ae=.012+this.tired*.03+this.stunAmount*.05;P.hips.set(ie*l+Math.sin(this.stunPhase*.9)*.05*this.stunAmount,tw.hipsHeight-ae+re,0),P.hipsYaw=F,P.hipsPitch=.02+this.tired*.08,P.hipsRoll=Math.sin(this.stunPhase)*.09*this.stunAmount,P.shouldersYaw=F*.88,P.spinePitch=.16+this.tired*.16+Math.sin(r*(2.1+this.tired*1.8))*.012,P.spineRoll=Math.sin(this.stunPhase*1.3)*.06*this.stunAmount,P.headYaw=-.12*l+Math.sin(r*.9)*.05+Math.sin(this.stunPhase*.7)*.25*this.stunAmount,P.headPitch=.12+Math.sin(r*1.7)*.02+this.stunAmount*.18,P.headRoll=Math.sin(this.stunPhase*1.1)*.14*this.stunAmount,P.headOffset.set(0,0,0);let I=l>0?this.hand.L:this.hand.R,L=l>0?this.hand.R:this.hand.L,oe=this.headRestChar(l),se=bw(this.guardHigh+this.guardLow,0,1),ce=this.scratch.copy(tw.relaxedLead).lerp(tw.guardHighLead,this.guardHigh).lerp(tw.guardLowLead,this.guardLow),le=this.scratchB.copy(tw.relaxedRear).lerp(tw.guardHighRear,this.guardHigh).lerp(tw.guardLowRear,this.guardLow);ce.y-=this.tired*.12+this.stunAmount*.22,le.y-=this.tired*.1+this.stunAmount*.2,ce.z+=this.feint*.1+Math.sin(r*2.3)*.012*u,ce.x+=Math.sin(r*1.9)*.01*u,le.y+=Math.cos(r*2.7)*.01*u,ce.z-=this.guardKick*.07,le.z-=this.guardKick*.05,ce.y-=this.guardKick*.02,ce.add(oe),le.add(oe),I.position.set(ce.x*l,ce.y,ce.z),L.position.set(le.x*l,le.y,le.z),nw(tw.leadKnuckles,l,I.knuckles),nw(tw.leadPalm,l,I.palm),nw(tw.rearKnuckles,l,L.knuckles),nw(tw.rearPalm,l,L.palm),nw(tw.leadPole,l,I.pole),nw(tw.rearPole,l,L.pole);let ue=.15*se,de=.25*se;if(Math.abs(this.slip)>.001){let e=this.slip;P.headOffset.x+=e*.13,P.spineRoll+=-e*.28,P.hips.x+=e*.03,P.hips.y-=Math.abs(e)*.05,P.spinePitch+=Math.abs(e)*.12,P.headRoll+=-e*.2}if(this.weave>.001){let e=this.weave,t=bw(this.weaveTime/.42,0,1),n=Math.sin(t*Math.PI);P.hips.y-=e*.2,P.spinePitch+=e*.42,P.headOffset.x+=e*(1-2*t)*.16*l,P.headOffset.y-=e*n*.08,P.spineRoll+=e*(1-2*t)*.18*l,I.position.y-=e*.1,L.position.y-=e*.1}if(this.pull>.001){let e=this.pull;P.spinePitch-=e*.34,P.hips.z-=e*.11,P.hips.x-=e*.05*l,P.headOffset.z-=e*.06,P.headPitch-=e*.1}P.headOffset.add(this.headKick.value),P.headPitch+=-this.headKick.value.z*2.4+this.headKick.value.y*1.6,P.headYaw+=this.headKick.value.x*2.2,P.headRoll+=-this.headKick.value.x*.9,P.spinePitch+=this.torsoKick.value.x,P.spineRoll+=this.torsoKick.value.z*.5,P.hips.x+=this.rootKick.value.x,P.hips.z+=this.rootKick.value.z,P.hips.y-=Math.max(0,this.torsoKick.value.x)*.08,this.torsoKick.value.x>.05&&(I.position.y-=this.torsoKick.value.x*.25,L.position.y-=this.torsoKick.value.x*.2,I.position.z-=this.torsoKick.value.x*.1);let fe=Math.max(0,this.rootKick.value.y);P.hips.y+=fe,k.heel+=fe*6,A.heel+=fe*6;let pe=this.coverKick.value.x;if(Math.abs(pe)>.002){let e=pe>0?this.hand.R:this.hand.L;e.position.y-=Math.abs(pe)*.9,e.position.x+=pe*.2,e.position.z-=Math.abs(pe)*.25,e.pole.y-=Math.abs(pe)*3}if(this.punchActive){ue=0,de=0;let e=this.applyPunch(l,I,L,k,A,oe);this.punchHand===`left`==l>0?ue=e:de=e}if(this.referee&&this.applyRefereePose(l,I,L,k,A,oe,r,o),this.clinchWeight>.001&&this.applyClinchPose(this.clinchWeight,r,l,e,t,I,L,oe),this.foulWeight>.001){let e=this.foulWeight;P.hips.y-=e*.16,P.spinePitch+=e*.55,P.headPitch+=e*.2,I.position.lerp(this.scratch.set(.06*l,.72,.16),e),L.position.lerp(this.scratch.set(-.05*l,.7,.14),e),I.pole.set(.6*l,-.6,.5),L.pole.set(-.6*l,-.6,.5)}if(this.tauntWeight>.001){let e=this.tauntEnd===null?0:bw(this.tauntEnd-o,0,Jw);this.applyTauntPose(this.tauntWeight,(Jw-e)/Jw*Yw,l,I,L,oe)}if(this.dislocation===`shoulder_left`||this.dislocation===`shoulder_right`){let e=this.dislocation===`shoulder_left`?this.hand.L:this.hand.R,t=this.dislocation===`shoulder_left`?1:-1;e.position.set(.24*t,.55,.05),e.pole.set(.9*t,-.3,.2),e.knuckles.set(0,-1,.1),e.palm.set(-t,0,.2)}this.touchWeight>.001&&this.downState===`up`&&this.applyTouchGlovesPose(this.touchWeight,l,I,L),this.celebration>.001&&this.downState===`up`&&this.applyCelebratePose(this.celebration,r,l,I,L,k,A),this.wave>.001&&this.downState===`up`&&this.applyWaveOffPose(this.wave,r,l,I,L),this.breakWeight>.001&&this.downState===`up`&&this.applyBreakPose(this.breakWeight,l,I,L),this.attendWeight>.001&&this.downState===`up`&&this.applyAttendPose(this.attendWeight,r,l,I,L),this.treatWeight>.001&&this.downState===`up`&&this.applyTreatPose(this.treatWeight,r,l,I,L,k,A),this.seated>.001&&this.downState===`up`&&this.applySeatedPose(this.seated,r,l,I,L,k,A),this.downState!==`up`&&this.applyDownPose(l,I,L,k,A),ae=0;let me=this.pose;me.shrugL=l>0?ue:de,me.shrugR=l>0?de:ue,this.solver.apply(c.root,this.pose),this.applyDislocation();let he=Math.min(1,(t.trauma.bleeding+t.trauma.left_cut+t.trauma.right_cut)/620*(a===`off`?0:a===`reduced`?.3:1.5));c.gloveGear.color.copy(c.gearBaseColor).lerp(Sw,he),mC(c.headInjury,e.trauma,a),hC(c.bodyInjury,e.trauma,a),c.setSkinClearcoat(.25+(1-C)*.4)}applyTauntPose(e,t,n,r,i,a){let o=this.torso,s=.5-.5*Math.cos(t*Math.PI*2);i.position.lerp(this.scratch.set(-.3*n,a.y-.62,.02),e),i.pole.lerp(this.scratch.set(-.5*n,-.4,-.75),e).normalize(),i.knuckles.lerp(this.scratch.set(-.1*n,-.95,.3),e).normalize(),i.palm.lerp(this.scratch.set(0,.3,.95),e).normalize(),r.position.lerp(this.scratch.set(.26*n,a.y-.36+s*.1,.52-s*.24),e),r.pole.lerp(this.scratch.set(.7*n,-.7,.1),e).normalize(),r.knuckles.lerp(this.scratch.set(.1*n,.25+s*.6,.95-s*.7),e).normalize(),r.palm.lerp(this.scratch.set(-.2*n,.95,-.2-s*.5),e).normalize(),o.spinePitch-=e*.12,o.headPitch-=e*.22,o.headYaw+=Math.sin(t*Math.PI)*.15*e,o.shouldersYaw+=Math.sin(t*Math.PI*3)*.1*e,o.hips.x+=Math.sin(t*Math.PI)*.03*e*n,o.headOffset.z+=e*.03}applyClinchPose(e,t,n,r,i,a,o,s){let c=this.torso,l=r.player_idy&&(h.x*=y/v,h.z*=y/v),h.x+=o,h.z+=u,t.position.lerp(h,e),t.pole.lerp(this.clinchTemp.set(r*.85,l?.35:-.6,.25),e).normalize(),t.knuckles.lerp(this.clinchTemp.set(-p*r*.9+f.x*.3,l?-.25:.1,-m*r*.9+f.z*.3),e).normalize(),t.palm.lerp(this.clinchTemp.set(-f.x,l?.1:.35,-f.z),e).normalize()}}headRestChar(e){let t=this.boxer.rig.metrics;return this.headWorld.set(-.08,t.headHeight-t.hipsHeight+this.torso.hips.y,.02)}syncAction(e,t,n,r){this.shownFighter=e,this.shownOpponent=t;let i=this.ownQueued;if(i!==null&&e.action_id===i.action.id&&(this.ownQueued=null,this.retirePunch(),this.startOwnPunch(i,0)),e.action_id!==null&&e.action_id!==this.actionId&&e.action_id!==this.completedActionId&&!this.retiredOwnIds.includes(e.action_id)){let t=e.action;if(t!==null){let r=e.action_hand??(e.stance===`orthodox`?`left`:`right`),i=this.ownActionId===e.action_id&&this.punchActive,a=this.punchTiming;this.actionId=e.action_id,this.punchClass=t,this.punchHand=r,this.punchTarget=e.action_target??`head`,this.punchPower=e.action_power??`normal`,this.punchTiming={...Ib(this.punchClass,this.punchTarget,this.punchPower),startup:e.action_startup_ticks,active:e.action_active_ticks,recovery:e.action_recovery_ticks},this.punchTotalTicks=Math.max(1,e.action_startup_ticks+e.action_active_ticks+e.action_recovery_ticks);let o=Math.max(0,n-e.action_start_tick);i?(this.punchAgeTicks=IT(this.punchAgeTicks,a,this.punchTiming),this.ownAuthoritativeAge=o,this.ownRefused||(this.ownPulled=!1,o-this.punchAgeTicks>1&&(this.punchAgeTicks=o))):(this.punchAgeTicks=o,this.ownActionId=null,this.ownLeadTicks=0,this.ownAuthoritativeAge=null),this.ownWaitedTicks=0,this.punchActive=!0}}if(e.action_id===null)this.actionId=null,this.completedActionId=null;else if(e.action_id===this.actionId&&this.punchActive){let t=Math.max(0,n-e.action_start_tick);this.ownActionId===this.actionId?(this.ownAuthoritativeAge=t,!this.ownPulled&&t-this.punchAgeTicks>1.5&&(this.punchAgeTicks=t)):Math.abs(this.punchAgeTicks-t)>1.5&&(this.punchAgeTicks=t)}this.punchActive&&this.ownActionId!==null&&this.ownAuthoritativeAge===null&&!this.ownPulled&&(this.ownWaitedTicks+=r*30,this.ownWaitedTicks>this.ownExpectedTicks*1.5+OT&&this.punchAgeTicks=this.punchTotalTicks&&(this.retirePunch(),a=!0)),e.is_downed&&(this.punchActive&&this.retirePunch(),this.ownQueued=null),this.releaseQueuedPress(r,a);let o=this.actionId??this.ownActionId;o!==this.aimActionId&&(this.aimActionId=o,this.followHead=0),this.followHead=vw(this.followHead,+(o!==null&&o===this.contactId),PT,r)}trackOpponentHead(e,t,n){let r=this.guardOpponentHead.set(this.mapping.x(e.x),0,this.mapping.z(e.y));this.opponentSteadySeconds=MT.has(e.defense)?0:this.opponentSteadySeconds+n,(!this.hasLiveHead||this.opponentSteadySeconds>=NT)&&this.opponentHeadOffset.copy(t).sub(r),r.add(this.opponentHeadOffset),this.liveOpponentHead.copy(t),this.hasLiveHead=!0}ownPunchRate(){if(this.ownActionId===null)return 1;let e=this.punchTiming.startup,t=this.ownAuthoritativeAge;return t===null?this.punchAgeTicks0,p=f?t:n,m=f?n:t,h=f?1:-1,g=+(this.punchPower===`power`),_=+(this.punchTarget===`body`),v,y,b,x=1,S=1;if(c0){let t=this.scratchQ.setFromAxisAngle(ET,-N*e*C);r.toe.applyQuaternion(t),r.pole.applyQuaternion(t)}if(M>.3){let t=this.scratchQ.setFromAxisAngle(ET,.45*e*C);i.toe.applyQuaternion(t),i.pole.applyQuaternion(t)}let ue=this.scratchE;switch(this.punchClass){case`hook`:ue.set(.22*h*e,-.06,-.12);break;case`uppercut`:ue.set(.05*h*e,-.42,-.02);break;case`straight`:ue.set(.02*h*e,-.03,-.09-.05*g);break;default:ue.set(0,-.01,-.05-.04*g);break}let de=this.punchStart.copy(E).addScaledVector(ue,Math.max(y,this.punchClass===`hook`||this.punchClass===`uppercut`?(1-w)*.6*x:0));if(this.punchClass===`hook`){let t=Math.hypot(de.x-I.x,de.z-I.z),n=Math.hypot(le.x-I.x,le.z-I.z),r=this.punchSweepFrom.copy(de).sub(I).setY(0).normalize(),i=this.punchSweepTo.copy(le).sub(I).setY(0).normalize(),a=Math.acos(bw(r.dot(i),-1,1)),o=r.z*i.x-r.x*i.z>=0?1:-1,s=BC(0,1,w),c=r.applyAxisAngle(ET,a*s*o).normalize();p.position.copy(I).addScaledVector(c,Pu.lerp(t,n,s)),p.position.y=Pu.lerp(de.y,le.y,s),p.pole.set(.95*h*e,.08,.3).normalize(),p.knuckles.copy(c).applyAxisAngle(ET,o*Math.PI/2).setY(.05).normalize(),p.palm.set(0,-1,0)}else if(this.punchClass===`uppercut`){let t=BC(0,1,w),n=de,r=this.punchMid.copy(le).lerp(n,.5);r.y=Math.min(n.y,le.y)-.04,r.z+=.08,p.position.copy(n).lerp(r,t*2>1?1:t*2),t>.5&&p.position.copy(r).lerp(le,(t-.5)*2),p.pole.set(.3*h*e,-.2,1),p.knuckles.set(.05*h*e,.9,.35).normalize(),p.palm.set(-.2*h*e,.3,-.95).normalize()}else{p.position.copy(de).lerp(le,Math.min(1,w)),p.position.y+=Math.sin(bw(w,0,1)*Math.PI)*.025,p.pole.set(.55*h*e,-.9,.35);let t=BC(.55,1,w);p.knuckles.copy(L).lerp(this.scratchC.set(.1*h*e,.55,.8),1-t).normalize(),p.palm.set(-.9*h*e,.2,-.3).lerp(this.scratchC.set(0,-1,.1),t).normalize()}if(T>0&&(p.position.lerp(E,T),p.knuckles.lerp(D,T).normalize(),p.palm.lerp(O,T).normalize(),p.pole.lerp(ee,T).normalize()),S<1){let t=(1-p.pole.dot(ee)/Math.max(1e-6,p.pole.length()*ee.length()))/2;p.knuckles.lerp(D,1-S).normalize(),p.palm.lerp(O,1-S).normalize(),p.pole.lerp(ee,1-S).addScaledVector(this.scratchC.set(h*e,0,0),FT*t*Math.sin(Math.PI*S)).normalize()}let fe=this.scratchE.set(-.1*h*e,a.y-.04,.12+a.z);return m.position.lerp(fe,C*.7),C}applyRefereePose(e,t,n,r,i,a,o,s){let c=this.torso;c.hipsYaw=0,c.shouldersYaw=0,c.hipsPitch=0,c.spinePitch=.06,c.headYaw=Math.sin(o*.7)*.08,c.headPitch=.08,c.hips.y=tw.hipsHeight+.03,c.hips.x=0,c.hips.z=0,r.toe.set(.12*e,0,1).normalize(),i.toe.set(-.12*e,0,1).normalize(),r.pole.copy(r.toe).setY(.3).normalize(),i.pole.copy(i.toe).setY(.3).normalize();let l=Math.sin(o*1.3)*.01;if(t.position.set(.27*e,.86+l,.12),n.position.set(-.27*e,.86-l,.12),t.pole.set(.5*e,-.4,-.8).normalize(),n.pole.set(-.5*e,-.4,-.8).normalize(),t.knuckles.set(.15*e,-.9,.35).normalize(),n.knuckles.set(-.15*e,-.9,.35).normalize(),t.palm.set(-.9*e,.1,.35).normalize(),n.palm.set(.9*e,.1,.35).normalize(),this.refereeCounting){this.countChangedTick??=s;let r=bw((s-this.countChangedTick)/Iw,0,1),i=r=Ew&&(this.downState=`down`);else{let n=(e.get_up_required>0?bw(e.get_up_meter/e.get_up_required,0,1):0)*Ow;this.riseProgress+=bw(n-this.riseProgress,-.4*t,jw*t)}return}if((this.downState===`down`||this.downState===`falling`)&&(this.downState=`rising`,this.riseFrom=this.riseProgress,this.feetInitialized=!1),this.downState!==`rising`)return;let r=n>.3||this.punchActive,i=(1-this.riseFrom)/(r?Aw:kw);this.riseProgress=Math.min(1,this.riseProgress+(this.riseProgress=1&&(this.downState=`up`)}applyTouchGlovesPose(e,t,n,r){let i=this.torso,a=Pu.lerp;i.hips.z=a(i.hips.z,.06,e),i.hipsYaw=a(i.hipsYaw,i.hipsYaw*.4,e),i.shouldersYaw=a(i.shouldersYaw,0,e),i.spinePitch=a(i.spinePitch,.12,e),i.headPitch=a(i.headPitch,.1,e),n.position.lerp(Xw.set(.11*t,1.24,.5),e),r.position.lerp(Xw.set(-.11*t,1.22,.47),e),n.palm.lerp(Xw.set(-t,0,0),e).normalize(),r.palm.lerp(Xw.set(t,0,0),e).normalize(),n.knuckles.lerp(Xw.set(0,.15,1),e).normalize(),r.knuckles.lerp(Xw.set(0,.15,1),e).normalize(),n.pole.lerp(Xw.set(.7*t,-.7,0),e).normalize(),r.pole.lerp(Xw.set(-.7*t,-.7,0),e).normalize()}touchWalk(e,t,n,r){this.countdownEnd=ST(this.countdownEnd,r,this.countdownTicks);let i=this.countdownEnd===null?0:CT(this.countdownEnd-r),a=this.mapping.x(t.x)-this.mapping.x(e.x),o=this.mapping.z(t.y)-this.mapping.z(e.y),s=Math.hypot(a,o),c=s>Hw?(s-Hw)/2/s*i:0;return this.touchVelocity.set(a*c-this.touchOffset.x,0,o*c-this.touchOffset.z).divideScalar(Math.max(n,.001)).clampLength(0,qw),this.touchOffset.set(a*c,0,o*c)}applyCelebratePose(e,t,n,r,i,a,o){let s=this.torso,c=Pu.lerp,l=Math.sin(t*6)*.04;s.hips.y=c(s.hips.y,tw.hipsHeight+.035+l*.5,e),s.hipsYaw=c(s.hipsYaw,0,e),s.hipsPitch=c(s.hipsPitch,-.12,e),s.hipsRoll=c(s.hipsRoll,0,e),s.shouldersYaw=c(s.shouldersYaw,0,e),s.spinePitch=c(s.spinePitch,-.1,e),s.headPitch=c(s.headPitch,-.25,e),r.position.lerp(Xw.set(.3*n,1.86+l,.08),e),i.position.lerp(Xw.set(-.3*n,1.84+l,.06),e),r.palm.lerp(Xw.set(0,0,1),e).normalize(),i.palm.lerp(Xw.set(0,0,1),e).normalize(),r.knuckles.lerp(Xw.set(.15*n,1,0),e).normalize(),i.knuckles.lerp(Xw.set(-.15*n,1,0),e).normalize(),r.pole.lerp(Xw.set(n,.1,-.3),e).normalize(),i.pole.lerp(Xw.set(-n,.1,-.3),e).normalize(),a.heel=c(a.heel,.45,e),o.heel=c(o.heel,.45,e)}applyAttendPose(e,t,n,r,i){let a=this.torso,o=Pu.lerp,s=Math.sin(t*3.1)*.03;a.hips.z=o(a.hips.z,.12,e),a.hips.y=o(a.hips.y,tw.hipsHeight-.04,e),a.hipsPitch=o(a.hipsPitch,.3,e),a.spinePitch=o(a.spinePitch,.42,e),a.headPitch=o(a.headPitch,.4,e),r.position.lerp(Xw.set(.2*n,1.3+s,.62),e),i.position.lerp(Xw.set(-.18*n,1.24-s,.58),e),r.palm.lerp(Xw.set(0,-.6,.8),e).normalize(),i.palm.lerp(Xw.set(0,-.6,.8),e).normalize(),r.knuckles.lerp(Xw.set(.1*n,.5,1),e).normalize(),i.knuckles.lerp(Xw.set(-.1*n,.5,1),e).normalize(),r.pole.lerp(Xw.set(.8*n,-.5,-.1),e).normalize(),i.pole.lerp(Xw.set(-.8*n,-.5,-.1),e).normalize()}applyTreatPose(e,t,n,r,i,a,o){let s=this.torso,c=Pu.lerp,l=this.treatScratch.set(this.rootX??0,0,this.rootZ),u=this.scratchQ.setFromAxisAngle(ET,-this.yaw),d=Xw.copy(this.treatTarget).sub(l).applyQuaternion(u),f=this.treatFacingLocal.copy(this.treatFacing).applyQuaternion(u),p=f.z,m=-f.x,h=Math.sin(t*2.6)*.006;s.hips.lerp(this.treatScratch.set(0,.62,.04),e),s.hipsYaw=c(s.hipsYaw,0,e),s.hipsPitch=c(s.hipsPitch,.22,e),s.hipsRoll=c(s.hipsRoll,0,e),s.shouldersYaw=c(s.shouldersYaw,0,e),s.spinePitch=c(s.spinePitch,.3,e),s.headPitch=c(s.headPitch,.2,e),a.position.x=c(a.position.x,.24*n,e),a.position.z=c(a.position.z,.14,e),o.position.x=c(o.position.x,-.2*n,e),o.position.z=c(o.position.z,-.2,e),o.heel=c(o.heel,.55,e),a.toe.lerp(this.treatScratch.set(.2*n,0,1),e).normalize(),o.toe.lerp(this.treatScratch.set(-.1*n,0,1),e).normalize(),a.pole.lerp(this.treatScratch.set(.25*n,.4,1),e).normalize(),o.pole.lerp(this.treatScratch.set(-.2*n,.4,1),e).normalize();let g=.08-h;r.position.lerp(this.treatScratch.set(d.x+f.x*g,d.y-.07,d.z+f.z*g),e),r.knuckles.lerp(this.treatScratch.set(0,1,.05),e).normalize(),r.palm.lerp(this.treatScratch.set(-f.x,0,-f.z),e).normalize(),r.pole.lerp(this.treatScratch.set(.85*n,-.35,.1),e).normalize();let _=this.treatSide*.135;i.position.lerp(this.treatScratch.set(d.x-p*_+f.x*.05,d.y-.2,d.z-m*_+f.z*.05),e),i.knuckles.lerp(this.treatScratch.set(0,.9,.4),e).normalize(),i.palm.lerp(this.treatScratch.set(p*this.treatSide*.8-f.x*.6,.1,m*this.treatSide*.8-f.z*.6),e).normalize(),i.pole.lerp(this.treatScratch.set(-.85*n,-.4,.1),e).normalize()}applyBreakPose(e,t,n,r){let i=this.torso,a=Pu.lerp;i.hipsPitch=a(i.hipsPitch,.14,e),i.spinePitch=a(i.spinePitch,.08,e);let o=this.scratchC.set(.48*t,1.22,.52),s=this.scratchD.set(-.48*t,1.22,.52);if(this.breakAimed){let[e,n]=this.breakFighters,r=this.scratch.subVectors(n,e).setY(0).normalize(),i=this.scratchQ.setFromAxisAngle(ET,-this.yaw),a=this.scratchB.set(this.rootX??0,0,this.rootZ);o.copy(e).addScaledVector(r,Rw).sub(a).applyQuaternion(i),s.copy(n).addScaledVector(r,-Rw).sub(a).applyQuaternion(i),o.x*tEw*.15;let s=this.downResult;if(this.downState!==`falling`){let a=this.riseProgress,c=0;if(a=n||(n=u.length()+o,this.landProne=s,this.landSide=c,this.landShift.copy(u))}}ropeShift(e,t){let n=this.scratchQ.setFromAxisAngle(ET,this.yaw);$w.set(e.hipsPitch+e.spinePitch*.7,e.hipsYaw,e.hipsRoll,`YXZ`),hT[0].set(0,pT,0).applyEuler($w).add(e.hips),hT[1].set(.2,mT,0).applyEuler($w).add(e.hips),hT[2].set(-.2,mT,0).applyEuler($w).add(e.hips),hT[3].copy(e.leadHand),hT[4].copy(e.rearHand),hT[5].copy(e.leadFoot).z+=e.leadHeel>0?.25:.19,hT[6].copy(e.rearFoot).z+=e.rearHeel>0?.25:.19,hT[7].copy(e.hips);let r=1/0,i=-1/0,a=1/0,o=-1/0;for(let e=0;enew Z),gT=[.17,.22,.22,.13,.13,.12,.12,.2],_T=[[!1,1,0],[!1,0,.15],[!1,-1,.3],[!0,1,.4],[!0,0,.5],[!0,-1,.6]];function vT(e,t){return e<-fT&&t>fT?-(e+t)/2:e<-fT?-fT-e:t>fT?fT-t:0}function yT(e,t){return bT(e,t,t,0)}function bT(e,t,n,r){let i=Pu.lerp;return e.hips.copy(t.hips).lerp(n.hips,r),e.hipsYaw=i(t.hipsYaw,n.hipsYaw,r),e.hipsPitch=i(t.hipsPitch,n.hipsPitch,r),e.hipsRoll=i(t.hipsRoll,n.hipsRoll,r),e.shouldersYaw=i(t.shouldersYaw,n.shouldersYaw,r),e.spinePitch=i(t.spinePitch,n.spinePitch,r),e.headPitch=i(t.headPitch,n.headPitch,r),e.leadHand.copy(t.leadHand).lerp(n.leadHand,r),e.rearHand.copy(t.rearHand).lerp(n.rearHand,r),e.leadFoot.copy(t.leadFoot).lerp(n.leadFoot,r),e.rearFoot.copy(t.rearFoot).lerp(n.rearFoot,r),e.leadHeel=i(t.leadHeel,n.leadHeel,r),e.rearHeel=i(t.rearHeel,n.rearHeel,r),e.palmsDown=i(t.palmsDown,n.palmsDown,r),e}var xT=3;function ST(e,t,n){if(n===null)return null;let r=t+n;return e===null||Math.abs(r-e)>xT?r:e}function CT(e){return(1-BC(Ww,Uw,e))*BC(Kw,Gw,e)}function wT(){let e=new Nd;e.name=`enswell`,e.visible=!1;let t=new gm(.03,.03,.008,16),n=new gm(.008,.008,.06,8),r=new sh({color:13159634,roughness:.3,metalness:.9}),i=new up(t,r);i.rotation.x=Math.PI/2,i.position.set(0,.07,.075),e.add(i);let a=new up(n,r);return a.position.set(0,.035,.075),e.add(a),{group:e,dispose:()=>{t.dispose(),n.dispose(),r.dispose()}}}function TT(){let e=new Nd;e.name=`stool`,e.visible=!1;let t=new gm(.17,.17,.035,18),n=new gm(.012,.014,Pw-.02,8),r=new sh({color:13222581,roughness:.85}),i=new sh({color:2764083,roughness:.45,metalness:.6}),a=new up(t,r);a.position.y=Pw-.0175,a.castShadow=!0,e.add(a);for(let t=0;t<4;t+=1){let r=Math.PI/4+t*Math.PI/2,a=new up(n,i);a.position.set(Math.cos(r)*.13,(Pw-.02)/2,Math.sin(r)*.13),a.rotation.set(-Math.sin(r)*.12,0,Math.cos(r)*.12),a.castShadow=!0,e.add(a)}return{group:e,dispose:()=>{t.dispose(),n.dispose(),r.dispose(),i.dispose()}}}var ET=new Z(0,1,0),DT=6,OT=5,kT=1.5,AT=.5,jT=new Set([`hit`,`counter_hit`,`block`,`perfect_block`]),MT=new Set([`slip_left`,`slip_right`,`weave`,`pull`]),NT=.25,PT=30,FT=2;function IT(e,t,n){if(e0)||e>1e3||(this.elapsed+=e,this.frames+=1,this.elapsede.before*.9)return this.scale=e.previous,this.holdWindows=Math.min(VT,zT*2**this.fruitlessAttempts),this.fruitlessAttempts+=1,!0;this.fruitlessAttempts=0}if(this.raised!==null){let e=this.raised;if(t>this.options.slowMs)return this.raised=null,this.scale=e.previous,this.fastWindows=0,this.raiseHoldWindows=Math.min(VT,BT*2**this.failedRaises),this.failedRaises+=1,!0;e.windows+=1,e.windows>=UT&&(this.raised=null,this.failedRaises=0)}if(t>this.options.slowMs){if(this.fastWindows=0,this.holdWindows>0)return--this.holdWindows,!1;if(this.scale<=this.options.minimum)return!1;let e=this.scale;return this.scale=Math.max(this.options.minimum,this.scale-this.options.step),this.pending={before:t,previous:e},!0}return t0?(--this.raiseHoldWindows,!1):this.fastWindows>=HT&&this.scalee.tick>=i-1&&e.tick<=a+1),s=o[0],c=o.at(-1);if(s===void 0||c===void 0||o.length<8||s.tick>t.tick-12||c.tickZT?Math.min(1,(i-ZT)/4):0;this.strength+=(a-this.strength)*Math.min(1,t*18);let o=this.history.length>=YT?this.history.shift():new Z;if(o.copy(e),this.history.push(o),this.strength<.02||this.history.length<3){this.mesh.visible=!1;return}let s=this.history.length;for(let e=0;e abs(ropeWorld.z); +vec3 ropeOut = ropeSideX ? vec3(sign(ropeWorld.x), 0.0, 0.0) : vec3(0.0, 0.0, sign(ropeWorld.z)); +float ropeAlong = ropeSideX ? ropeWorld.z : ropeWorld.x; +float ropeFlex = 0.0; +for (int ropeIndex = 0; ropeIndex < 2; ropeIndex += 1) { + vec4 contact = ropeIndex == 0 ? uRopeContactA : uRopeContactB; + float along = ropeSideX ? contact.y : contact.x; + float press = ropeSideX ? contact.z : contact.w; + float sameSide = ropeSideX ? step(0.0, ropeOut.x * contact.x) : step(0.0, ropeOut.z * contact.y); + ropeFlex += press * sameSide * (1.0 - smoothstep(0.0, 0.8, abs(ropeAlong - along))); +} +float ropeAnchor = smoothstep(0.0, 0.7, ${Cx.toFixed(2)} - abs(ropeAlong)); +float ropeHeightWeight = 0.45 + 0.55 * smoothstep(0.4, 1.0, ropeWorld.y); +transformed += ropeOut * min(1.0, ropeFlex) * 0.22 * ropeHeightWeight * ropeAnchor; +`;function iE(e,t){let n=document.createElement(`canvas`);n.width=e,n.height=e;let r=n.getContext(`2d`);r!==null&&t(r,e);let i=new lm(n);return i.anisotropy=8,i.colorSpace=Vl,i}function aE(){return iE(1024,(e,t)=>{e.fillStyle=`#9d968a`,e.fillRect(0,0,t,t);let n=e.createLinearGradient(0,0,t,t);n.addColorStop(0,`rgba(255,255,255,0.08)`),n.addColorStop(.5,`rgba(60,50,40,0.06)`),n.addColorStop(1,`rgba(255,255,255,0.04)`),e.fillStyle=n,e.fillRect(0,0,t,t);for(let n=0;n<2600;n+=1){let r=Math.sin(n*12.9898)*43758.5453%1,i=Math.sin(n*78.233)*12543.1234%1;e.fillStyle=`rgba(${n%3==0?`255,255,255`:`70,55,45`},${.02+n%5*.006})`,e.fillRect(Math.abs(r)*t,Math.abs(i)*t,2+n%4,1+n%3)}for(let n=0;n<40;n+=1){let r=Math.abs(Math.sin(n*91.7)*7919.3%1)*t,i=Math.abs(Math.sin(n*47.1)*4271.9%1)*t;e.fillStyle=`rgba(80,60,50,${.05+n%4*.02})`,e.beginPath(),e.ellipse(r,i,18+n%7*6,6+n%5*3,n*.7%Math.PI,0,Math.PI*2),e.fill()}e.strokeStyle=`rgba(30,60,140,0.85)`,e.lineWidth=12,e.beginPath(),e.arc(t/2,t/2,t*.2,0,Math.PI*2),e.stroke(),e.fillStyle=`rgba(30,60,140,0.9)`,e.font=`800 ${Math.round(t*.062)}px Inter, system-ui, sans-serif`,e.textAlign=`center`,e.textBaseline=`middle`,e.fillText(`H A N D S`,t/2,t/2-t*.012),e.font=`600 ${Math.round(t*.024)}px Inter, system-ui, sans-serif`,e.fillText(`AUTHORITATIVE BOXING`,t/2,t/2+t*.052),e.strokeStyle=`rgba(30,60,140,0.6)`,e.lineWidth=6,e.strokeRect(t*.035,t*.035,t*.93,t*.93)})}function oE(){let e=[],t=[],n=[],r=new Nd;r.name=`ring`;let i=aE();n.push(i);let a=new sh({map:i,roughness:.88,metalness:0});t.push(a);let o=new qm(Cx*2,Cx*2);e.push(o);let s=new up(o,a);s.rotation.x=-Math.PI/2,s.position.y=.002,s.receiveShadow=!0,r.add(s);let c=new sh({color:`#1c2b52`,roughness:.85});t.push(c);let l=new Jm(Cx*.98,wx,4,1);e.push(l);let u=new up(l,c);u.rotation.x=-Math.PI/2,u.rotation.z=Math.PI/4,u.position.y=.001,u.receiveShadow=!0,r.add(u);let d=new sh({color:`#0c1424`,roughness:.9});t.push(d);let f=new pm(Tx*2,1,Tx*2);e.push(f);let p=new up(f,d);p.position.y=-.5,p.receiveShadow=!0,r.add(p);let m=new sh({color:`#101b33`,roughness:.95});t.push(m);for(let t=0;t<4;t+=1){let n=new qm(Tx*2,.95);e.push(n);let i=new up(n,m),a=t*Math.PI/2;i.position.set(Math.sin(a)*(Tx-.001),-.48,Math.cos(a)*(Tx-.001)),i.rotation.y=a,r.add(i)}let h=new sh({color:`#9aa7b5`,roughness:.35,metalness:.75});t.push(h);let g=[kx.blue,kx.neutral,kx.red,kx.neutral],_=new gm(.055,.055,1.55,12);e.push(_);let v=new pm(.34,.52,.13);e.push(v);let y=new pm(.16,.07,.1);e.push(y);let b=[];for(let e=0;e<4;e+=1){let n=Math.PI/4+e*Math.PI/2,i=Math.sin(n)*Ex*Math.SQRT2*.72,a=Math.cos(n)*Ex*Math.SQRT2*.72;b.push(new Z(i,0,a));let o=new up(_,h);o.position.set(i,.78,a),o.castShadow=!0,r.add(o);let s=new sh({color:g[e],roughness:.55});t.push(s);for(let e of[.62,1.12]){let t=new up(v,s);t.position.set(i*.985,e,a*.985),t.lookAt(0,e,0),t.castShadow=!0,r.add(t)}}let x=[new ed(0,0,0,0),new ed(0,0,0,0)],S={uRopeContactA:{value:x[0]},uRopeContactB:{value:x[1]}},C=[12131356,15067115,1920728].map(e=>{let n=new sh({color:e,roughness:.42,metalness:.05});return n.onBeforeCompile=e=>{e.uniforms.uRopeContactA=S.uRopeContactA,e.uniforms.uRopeContactB=S.uRopeContactB,e.vertexShader=e.vertexShader.replace(`#include `,`#include +uniform vec4 uRopeContactA; +uniform vec4 uRopeContactB;`).replace(`#include `,`#include ${rE}`)},t.push(n),n}),w=(e,t)=>{for(let[n,r]of[e,t].entries()){let e=x[n];if(r===null){e.set(0,0,0,0);continue}let t=nE(r.x,r.z);e.set(r.x,r.z,t.pressX,t.pressZ)}};for(let n=0;n<4;n+=1){let i=b[n],a=b[(n+1)%4];for(let[n,o]of Dx.entries()){let s=i.clone().add(a).multiplyScalar(.5);s.y=o-.045;let c=new Wm(new 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_E=e=>e.kind===`hit`||e.kind===`counter_hit`,vE=e=>e.kind===`block`||e.kind===`perfect_block`,yE=480,bE=.56,xE=1.8,SE=1.7,CE=.5,wE=3.42,TE=2.2,EE=2.95,DE=2.4,OE=1.6,kE={uniforms:{tDiffuse:{value:null},uTime:{value:0},uVignette:{value:.32},uGrain:{value:.035}},vertexShader:` +varying vec2 vUv; +void main() { + vUv = uv; + gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0); +}`,fragmentShader:` +uniform sampler2D tDiffuse; +uniform float uTime; +uniform float uVignette; +uniform float uGrain; +varying vec2 vUv; +float hash(vec2 p) { + return fract(sin(dot(p, vec2(127.1, 311.7)) + uTime * 43.7) * 43758.5453); +} +void main() { + vec4 color = texture2D(tDiffuse, vUv); + vec2 centered = vUv - 0.5; + float falloff = smoothstep(0.35, 0.95, dot(centered, centered) * 2.2); + color.rgb *= 1.0 - falloff * uVignette; + float grain = (hash(floor(vUv * vec2(960.0, 540.0))) - 0.5) * uGrain; + color.rgb += grain * (0.15 + color.rgb); + gl_FragColor = color; +}`},AE={hit:.18,counter_hit:.3,guard_break:.25,knockdown:1,block:.04,perfect_block:.1};function jE(e,t){if(!(!_E(e)||e.action_id===null))return t.find(t=>vE(t)&&t.action_id===e.action_id&&t.actor_id===e.target_id&&t.target_id===e.actor_id)}function ME(e,t){if(!(!vE(e)||e.action_id===null))return t.find(t=>_E(t)&&t.action_id===e.action_id&&t.actor_id===e.target_id&&t.target_id===e.actor_id)}function NE(e,t){return e.map((n,r)=>{let{puncherIndex:i}=hE(n,t),a=t.fighters[i],o=a?.action_key?.split(`:`)??[],s=o.length>=3?`${o[0]}:${o[2]}`:n.detail,c=ME(n,e);if(vE(n))return{event:n,presentationEvent:{...n,detail:c?.detail||s,direction:c?.direction??a?.facing??n.direction,blood:c?.blood??n.blood},presentImpact:!0,reactAmount:n.amount};if(jE(n,e)!==void 0)return{event:n,presentationEvent:n,presentImpact:!1,reactAmount:n.amount};if(n.kind===`knockdown`){let t=e.slice(0,r).reverse().find(e=>_E(e)&&e.tick===n.tick&&e.actor_id===n.actor_id&&e.target_id===n.target_id);if(t!==void 0)return{event:n,presentationEvent:{...n,detail:t.detail,direction:t.direction,blood:t.blood,action_id:t.action_id},presentImpact:!0,reactAmount:jE(t,e)===void 0?null:t.amount}}return{event:n,presentationEvent:n,presentImpact:!0,reactAmount:n.amount}})}function PE(e){return e.result===null?e.tick-1:e.tick}function FE(e,t,n,r){if(!lE(e,t,n))return null;let i=Math.abs(e.event_id);if(e.detail.endsWith(`:head`))return i%2==0?`decapitation`:`jaw_dislocation`;let a=r?.action_key?.split(`:`)[1],o=a===`left`?`right`:a===`right`||Math.floor(i/2)%2==0?`left`:`right`;return i%2==0?`dismember_${o}`:`shoulder_${o}`}function IE(){let e=document.createElement(`canvas`);e.width=128,e.height=128;let t=e.getContext(`2d`);if(t!==null){let e=t.createRadialGradient(64,64,8,64,64,62);e.addColorStop(0,`rgba(0,0,0,0.68)`),e.addColorStop(.6,`rgba(0,0,0,0.34)`),e.addColorStop(1,`rgba(0,0,0,0)`),t.fillStyle=e,t.fillRect(0,0,128,128)}return new lm(e)}var LE={tick_rate:30,ring_half_width:500,ring_half_height:500};function RE(e,t,n){let r=e.geometry,i=r.getAttribute(`position`),a=r.getIndex(),o=[],s=[];if(a===null)for(let e=0;e=i.start+o))return{action:i.punchClass,action_hand:i.hand,action_target:`head`,action_power:`normal`,action_id:`idle-${n}-${r}`,action_key:`${i.punchClass}:${i.hand}:head:normal`,action_start_tick:e-(t-i.start),action_startup_ticks:a.startup,action_active_ticks:a.active,action_recovery_ticks:a.recovery,action_contact_tick:e-(t-i.start)+a.startup}}return{}}var GE=1000003,KE=1.6;function qE(e,t,n,r,i,a){let o=r<0?-1:1,s=o=>Math.hypot(Pu.clamp(e+n*o*i,-a,a)-e,Pu.clamp(t+r*o*i,-a,a)-t);return s(o)>=i*.8||s(o)>=s(-o)?o:-o}function JE(e){return!e.is_downed&&e.stunned_ticks===0&&e.clinch_ticks===0&&e.clinch_startup_ticks===0&&e.taunt_ticks===0&&!e.is_foul_recovery_target}function YE(e){return e===`decapitation`||e===`dismember_left`||e===`dismember_right`}function XE(e,t,n=!1){return 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i=e.x/r.x(1),a=e.z/r.z(1),o={player_id:`referee`,x:i,y:a,facing:1,facing_x:Math.round(Math.sin(t)*1e3),facing_y:Math.round(-Math.cos(t)*1e3),velocity_x:n.x/r.x(1)/30,velocity_y:n.z/r.z(1)/30,stance:`orthodox`,defense:`none`,stamina:1e3,maximum_stamina:1e3,conditioning:1e3,guard:700,poise:600,trauma:{head:0,body:0,left_eye:0,right_eye:0,left_cut:0,right_cut:0,swelling:0,bleeding:0},knockdowns:0,warnings:0,deductions:0,stunned_ticks:0,is_downed:!1,action:null,action_hand:null,action_target:null,action_power:null,action_id:null,action_key:null,action_start_tick:0,action_startup_ticks:0,action_active_ticks:0,action_recovery_ticks:0,action_contact_tick:null,queued_actions:0,clinch_startup_ticks:0,clinch_ticks:0,is_foul_recovery_target:!1,taunt_ticks:0,get_up_prompt:null,get_up_meter:0,get_up_required:0,get_up_count:0,get_up_window_start_tick:0,get_up_window_end_tick:0,last_input_sequence:-1};return{self:o,focus:{...o,player_id:`focus`,x:i+Math.sin(t)*300,y:a-Math.cos(t)*300}}}var QE=class{canvas;simulation;settings;renderer;scene=new Hd;camera;composer;ring;arena;referee=null;cornermen=null;trails=[];trailGlove=new Z;cornerShirts=[];cornermanPosition=new Z;cornermanVelocity=new Z;cutmen=null;cutmanProgress=[0,0];cutmanFrom=new Z;cutmanTo=new Z;cutmanEye=new Z;cutmanFacing=new Z;cutmanLast=[new Z,new Z];refereePosition=new Z(.4,0,-2.1);refereeVelocity=new Z;effects;director=new Sx;mapping;buffer;localInput;inputSequenceOf;movement=new $b;evasion=new ix;lastManualTime=0;dedupe=new oc;hudCanvas;cameraOverride=null;manualClock;blobShadows=[];blobTexture;lights=[];keyLight=null;followSpot=null;sizeCheck=new X;refereeAway=new Z;refereeYaw=0;raf=0;previous=performance.now();scaler=new WT;pixelRatioCap=Es()?1.5:2;basePixelRatio=Math.min(this.pixelRatioCap,window.devicePixelRatio||1);players={};playerOrder=[];viewerId=null;final=null;reconnectMs=0;destroyed=!1;graphs=null;glbLoading=!1;refereeShirt=null;graphsReady=Promise.resolve();headCache=[new Z,new 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Fu;constructor(e,t=LE,n,r={}){this.canvas=e,this.simulation=t,this.settings=n,this.manualClock=r.manualClock===!0,this.localInput=r.localInput??null,this.inputSequenceOf=r.inputSequenceOf??null,this.buffer=new ac(8,t.tick_rate),this.mapping=Ox(t),this.renderer=new ab({canvas:e,antialias:!0,powerPreference:`high-performance`,preserveDrawingBuffer:r.manualClock===!0}),this.renderer.shadowMap.enabled=!0,this.renderer.shadowMap.type=1,this.renderer.toneMapping=4,this.renderer.toneMappingExposure=1,this.renderer.setPixelRatio(this.basePixelRatio),this.scene.background=new Q(`#04060b`),this.scene.fog=new Vd(`#04060b`,.042),this.camera=new ag(36,1,.1,80),this.camera.position.set(0,2.05,5.9),this.camera.lookAt(0,1.05,0),this.setupLights(),this.ring=oE(),this.scene.add(this.ring.group),this.arena=lx(),this.scene.add(this.arena.group),this.effects=new Qx(this.scene),this.blobTexture=IE();let i=new qm(1,1);for(let e=0;e<3;e+=1){let t=new up(i,new Qf({map:this.blobTexture,transparent:!0,depthWrite:!1}));t.rotation.x=-Math.PI/2,t.position.y=.006+e*4e-4,t.renderOrder=1,this.blobShadows.push(t),this.scene.add(t)}this.composer=new mb(this.renderer),this.composer.addPass(new hb(this.scene,this.camera));let a=new _b(new X(1280,720),.2,.45,1.08);this.bloomPass=a,this.composer.addPass(a),this.finishPass=new db(kE),this.composer.addPass(this.finishPass),this.composer.addPass(new yb),this.hudCanvas=document.createElement(`canvas`),this.hudCanvas.className=`fight-hud`,this.hudCanvas.style.cssText=`position:absolute;inset:0;width:100%;height:100%;pointer-events:none`,e.insertAdjacentElement(`afterend`,this.hudCanvas),this.bloodLevel=n().blood,this.effects.setBloodLevel(this.bloodLevel),this.ensureGraphs(),this.manualClock||(this.raf=requestAnimationFrame(e=>this.draw(e)))}ensureGraphs(){this.glbLoading||this.graphs!==null||(this.glbLoading=!0,this.graphsReady=fw().then(async e=>{if(this.destroyed)return;let t=new xw(e,{skin:11563071,gear:1920728}),n=new xw(e,{skin:7225640,gear:12131356});this.graphs=[new Nw(t,this.mapping),new Nw(n,this.mapping)],this.syncInjuryPresentation(0),this.syncInjuryPresentation(1),this.refereeShirt=BE();let r=new xw(e,{skin:13081462,gear:3889080,pants:1316380,bodyMap:this.refereeShirt});this.referee=new Nw(r,this.mapping,{referee:!0});let i=zE(`#2b4c9e`),a=zE(`#9e2b2b`);this.cornerShirts.push(i,a);let o=new xw(e,{skin:9067067,gear:1778224,pants:1316380,bodyMap:i}),s=new xw(e,{skin:14264188,gear:1778224,pants:1316380,bodyMap:a});this.cornermen=[new Nw(o,this.mapping,{referee:!0}),new Nw(s,this.mapping,{referee:!0})];let c=zE(`#e3e4e8`);this.cornerShirts.push(c);let l=new xw(e,{skin:12160102,gear:1778224,pants:1316380,bodyMap:c}),u=new xw(e,{skin:5913126,gear:1778224,pants:1316380,bodyMap:c});this.cutmen=[new Nw(l,this.mapping,{referee:!0}),new 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Z(...t)}}labFrame(e,t=!0){this.draw(e*1e3,!0,t)}setPlayers(e,t,n=Object.keys(e)){this.players=e,this.viewerId=t,this.playerOrder=n}updateIdleFighters(e,t,n){let r=this.graphs;if(r===null)return;let i=this.playerOrder.filter(e=>this.players[e]!==void 0).length<2;for(let[a,o]of r.entries()){let r=this.playerOrder[a]??`seat-${a}`,s=!i||r===this.viewerId||this.viewerId===null&&a===0;if(o.boxer.root.visible=s,!s)continue;let c=a===0?-1:1,l=Math.floor(t*this.simulation.tick_rate),u={...VE(r),x:i?0:c*180,y:i?-70:0,facing:i?1:-c,facing_x:i?0:-c*1e3,facing_y:i?-1e3:0,...i?WE(l):{}},d={...VE(this.playerOrder[1-a]??`opponent`),x:i?0:-c*180,y:i?-150:0};o.setResting(!1),o.update(u,d,e,t,this.settings().reducedMotion,this.bloodLevel,i?l:n)}}setFinal(e){if(this.final=e,this.finalRevealAt=this.frameSeconds+y(e),this.pendingFinish=null,e===null||!_.has(e.method))return;let t=this.lastKnockdown===null?null:qT(this.history,this.lastKnockdown.knockdown,this.simulation.tick_rate);if(t!==null&&this.graphs!==null&&!this.settings().reducedMotion){this.startReplay(t);return}let n=this.buffer.latest()?.result?.tick;n===void 0?this.presentFinish(e):this.pendingFinish={final:e,tick:n,latestAt:this.frameSeconds+CE}}presentFinishWhenShown(e){let t=this.pendingFinish;t===null||et.player_id!==e.winner_id&&t.player_id!==null)??-1;if(n>=0&&this.headCacheValid[n]&&!this.settings().reducedMotion&&(this.finishCloseUpIndex=n,this.finishCloseUpUntil=this.frameSeconds+SE),e.winner_id===null)return;let r=t?.findIndex(t=>t.player_id===e.winner_id)??-1;r>=0&&this.graphs?.[r]?.celebrate()}cornerShotFrame(e,t,n){if(t===null||t.phase!==`rest`||n||this.graphs===null)return null;let r=t.fighters.findIndex(e=>e.player_id===this.viewerId),i=e-this.restStartedAt,a=hx(i,t.phase_ticks_remaining/this.simulation.tick_rate,+(r===1));return a===null||!this.graphs[a].stoolVisible?null:(xx(a,this.mapping.x(Tb),gx(i),this.cornerPosition,this.cornerLookAt),{position:this.cornerPosition,lookAt:this.cornerLookAt})}closeUpFrame(e){if(e>=this.finishCloseUpUntil||this.finishCloseUpIndex<0||!this.headCacheValid[this.finishCloseUpIndex])return null;let t=this.arcadeInjuries[this.finishCloseUpIndex]===`decapitation`&&this.effects.severedHeadPosition(this.finishCloseUpIndex,this.closeUpTarget),n=t?this.closeUpTarget:this.headCache[this.finishCloseUpIndex],r=t?.8:1.05,i=(e-(this.finishCloseUpUntil-SE))*.25-.2,a=Math.atan2(-n.x,-n.z),o=(Math.hypot(n.x,n.z)>.4?a:.9)+i;return this.closeUpPosition.set(Pu.clamp(n.x+Math.sin(o)*r,-2.2,TE),n.y+(t?.42:.75),Pu.clamp(n.z+Math.cos(o)*r,-2.2,TE)),this.replayLookAt.copy(n),{position:this.closeUpPosition,lookAt:this.replayLookAt,tight:!0}}startReplay(e){let t=new ac(e.snapshots.length+2,this.simulation.tick_rate);for(let n of e.snapshots)t.push(n);this.replay={plan:e,buffer:t,startedAt:this.frameSeconds,impactFired:!1,side:null},this.replayFollow=0,this.replayFollowAt=0;for(let e of[0,1]){let t=this.arcadeInjuries[e],n=this.arcadeInjuryEvents[e];t!==null&&n!==null&&YE(t)&&(this.replayInjuries[e]={injury:t,event:n},this.restoreInjury(e))}for(let e of this.graphs??[])e.resetTransient(!1);this.finalRevealAt=this.frameSeconds+e.durationSeconds+y(this.final)}endReplay(){this.replay=null,this.reapplyReplayInjuries();let e=this.buffer.latest();for(let[t,n]of(this.graphs??[]).entries())n.resetTransient(e?.fighters[t]?.is_downed===!0);this.final!==null&&this.presentFinish(this.final)}fireReplayImpact(e){let t=this.lastKnockdown;if(t===null)return;let n=t.hit??{...t.knockdown,kind:`hit`,amount:420,blood:60},{recipientIndex:r,puncherIndex:i}=hE(n,e),a=e.fighters[r];if(a===void 0)return;this.tmpA.set(this.mapping.x(a.x),0,this.mapping.z(a.y));let o=gE(e.fighters[i],a,this.mapping);this.effects.addEvent(n,this.tmpA,this.settings().reducedMotion,o);let s=(i>=0?e.fighters[i]:void 0)?.action_key?.split(`:`)??[],c=s[0]??null,l=s[1]??null;this.graphs?.[r]?.react(`hit`,n.detail.endsWith(`:body`)?`body`:`head`,n.direction,c,l,n.amount),i>=0&&this.graphs?.[i]?.landedHit(!1),this.onContact?.(n),this.reapplyReplayInjuries(o)}replayFrame(e,t){let[n,r]=e.fighters,i=this.mapping.x(n.x),a=this.mapping.z(n.y),o=this.mapping.x(r.x),s=this.mapping.z(r.y),c=e.fighters.findIndex(e=>e.player_id===this.replay?.plan.impact.target_id),l=this.replay?.impactFired===!0&&c>=0&&this.headCacheValid[c]===!0,u=1-Math.exp(-3*Math.max(0,t-this.replayFollowAt));this.replayFollowAt=t,this.replayFollow+=(+!!l-this.replayFollow)*u;let d=c<0?0:Math.max(this.portraitPull>1.3?.7:0,this.replayFollow*.8),f=(i+o)/2+((c===1?o:i)-(i+o)/2)*d,p=(a+s)/2+((c===1?s:a)-(a+s)/2)*d,m=-(s-a),h=o-i,g=Math.hypot(m,h)||1;m/=g,h/=g;let _=2.5,v=this.replay;v!==null&&v.side===null&&(v.side=qE(f,p,m,h,_,TE));let y=v?.side??(h<0?-1:1);m*=y,h*=y;let b=.35*Math.sin(t*.7),x=m*Math.cos(b)-h*Math.sin(b),S=m*Math.sin(b)+h*Math.cos(b);this.replayCameraPosition.set(Pu.clamp(f+x*_,-2.2,TE),1.38-Math.min(.25,t*.05),Pu.clamp(p+S*_,-2.2,TE));let C=Math.hypot(this.replayCameraPosition.x-f,this.replayCameraPosition.z-p),w=Math.hypot(f,p);if(C.01){let e=KE-C;this.replayCameraPosition.x=Pu.clamp(this.replayCameraPosition.x-f/w*e,-2.2,TE),this.replayCameraPosition.z=Pu.clamp(this.replayCameraPosition.z-p/w*e,-2.2,TE)}let T=l?Pu.clamp(this.headCache[c].y,.45,1.28):1.28;return this.replayLookAt.set(f,1.28+(T-1.28)*this.replayFollow,p),{position:this.replayCameraPosition,lookAt:this.replayLookAt,tight:!0}}setInputLatency(e){this.inputLatencyMs=e}resyncClock(){this.buffer.resync()}setReconnect(e){this.reconnectMs=e}setBloodLevel(e){e!==`full`&&this.bloodLevel===`full`&&this.restoreAllInjuries(),this.bloodLevel=e,e===`off`&&this.downedPoolAccumulators.fill(0),this.effects.setBloodLevel(e)}setReducedMotion(e){e&&(this.restoreAllInjuries(),this.effects.clearDynamic())}syncInjuryPresentation(e){let t=this.arcadeInjuries[e],n=this.graphs;if(n!==null){let r=n[e];r.boxer.setDecapitated(t===`decapitation`),r.boxer.setHandDismembered(`left`,t===`dismember_left`),r.boxer.setHandDismembered(`right`,t===`dismember_right`);let i=t===`jaw_dislocation`?`jaw`:t===`shoulder_left`||t===`shoulder_right`?t:null;r.setArcadeDislocation(i)}}applyArcadeInjury(e,t,n,r){let i=this.graphs!==null&&(t===`jaw_dislocation`||t===`shoulder_left`||t===`shoulder_right`);if(t===`decapitation`){let t=this.headWorldPose(e);if(t!==null){let a=this.graphs?.[e],o=a===void 0?void 0:RE(a.boxer.headMesh,t.position,t.quaternion);this.effects.decapitate(e,t.position,t.quaternion,r??n.direction,n.event_id,this.skinColor(e),o);let s=this.stumpWorldPose(e);s!==null&&this.effects.anchorStump(e,s.position,s.quaternion),i=!0}}else if(t===`dismember_left`||t===`dismember_right`){let a=t===`dismember_left`?`left`:`right`,o=this.handWorldPose(e,a);if(o!==null){let t=this.graphs?.[e],s=t===void 0?void 0:RE(t.boxer.gloveMesh(a),o.position,o.quaternion);this.effects.dismemberHand(e,a,o.position,o.quaternion,r??n.direction,n.event_id,this.gearColor(e),s),this.effects.anchorHandStump(e,a,o.position,o.quaternion),i=!0}}return i?(this.arcadeInjuries[e]=t,this.arcadeInjuryEvents[e]=n,this.observedInjuryDown[e]=!1,this.syncInjuryPresentation(e),this.onArcadeInjury?.(t,n),!0):!1}reapplyReplayInjuries(e){for(let t of[0,1]){let n=this.replayInjuries[t];if(n===null)continue;this.replayInjuries[t]=null;let r=this.settings();r.blood!==`full`||r.reducedMotion||this.applyArcadeInjury(t,n.injury,{...n.event,event_id:n.event.event_id+GE},e)}}restoreInjury(e){this.arcadeInjuries[e]!==null&&(this.arcadeInjuries[e]=null,this.arcadeInjuryEvents[e]=null,this.observedInjuryDown[e]=!1,this.syncInjuryPresentation(e),this.effects.restoreFighter(e))}restoreAllInjuries(){this.restoreInjury(0),this.restoreInjury(1),this.effects.clearArcadeGore()}headWorldPose(e){let t=this.graphs,n=t===null?null:t[e].boxer.bone(`head`);return n===null||t===null?null:(t[e].boxer.root.updateMatrixWorld(!0),n.getWorldPosition(this.tmpHead),n.getWorldQuaternion(this.tmpHeadQuaternion),this.tmpStumpOffset.set(0,.12,.02).applyQuaternion(this.tmpHeadQuaternion),this.tmpHead.add(this.tmpStumpOffset),{position:this.tmpHead,quaternion:this.tmpHeadQuaternion})}handWorldPose(e,t){let n=this.graphs,r=n===null?null:n[e].boxer.bone(t===`left`?`gloveL`:`gloveR`);return r===null||n===null?null:(n[e].boxer.root.updateMatrixWorld(!0),r.getWorldPosition(this.tmpPart),r.getWorldQuaternion(this.tmpPartQuaternion),{position:this.tmpPart,quaternion:this.tmpPartQuaternion})}gearColor(e){return this.graphs?.[e]?.boxer.gearBaseColor.getHex()??1920728}skinColor(e){return this.graphs?.[e]?.boxer.skinBaseColor.getHex()??11563071}stumpWorldPose(e){let t=this.graphs,n=t===null?null:t[e].boxer.bone(`Neck_012`);return n===null||t===null?null:(t[e].boxer.root.updateMatrixWorld(!0),n.getWorldPosition(this.tmpStump),n.getWorldQuaternion(this.tmpStumpQuaternion),{position:this.tmpStump,quaternion:this.tmpStumpQuaternion})}predictAction(e){let t=this.buffer.latest();if(t===null||this.viewerId===null||this.replay!==null)return;let n=t.fighters.findIndex(e=>e.player_id===this.viewerId);if(n<0)return;let r=t.fighters[n];if(t.phase!==`fight`||!JE(r))return;let i=(this.inputLatencyMs??60)/1e3*this.simulation.tick_rate+this.buffer.interpolationDelayTicks;if(nx(e.kind)){!(this.graphs?.[n]?.ownPunchActive===!0||qb(r,t.tick)>0||r.queued_actions>0)&&e.id!==void 0&&r.stamina>=25&&this.evasion.press(e.kind,e.id,this.manualClock?this.lastManualTime:performance.now(),i,this.simulation.tick_rate);return}e.kind!==`punch`||!Kb(r,e)||this.graphs?.[n]?.predict(e,performance.now()/1e3,this.simulation.tick_rate,i,Gb(r,e,t.tick+1))}acknowledgeActions(e,t){for(let[n,r]of e.fighters.entries()){let i=r.player_id===this.viewerId;i&&this.evasion.acknowledge(r,e.phase===`fight`,this.inputSequenceOf);let a=t.filter(t=>hE(t,e).puncherIndex===n);this.graphs?.[n]?.acknowledge(r,e.phase===`fight`,a,i?this.inputSequenceOf:null)}}push(e){if(!this.buffer.push(e,this.manualClock?this.lastManualTime:performance.now()))return;let t=this.dedupe.accept(e.events);this.acknowledgeActions(e,t),this.history.push(e),this.history.length>yE&&this.history.shift();for(let e of t){if(this.roundStats.record(e),e.kind===`knockdown`){let n=t.find(t=>(t.kind===`hit`||t.kind===`counter_hit`)&&t.target_id===e.target_id)??null;this.lastKnockdown={knockdown:e,hit:n}}e.kind===`referee_break`&&this.referee?.breakClinch()}for(let{event:n,presentationEvent:r,presentImpact:i,reactAmount:a}of NE(t,e)){let t=e.fighters.findIndex(e=>e.player_id===n.target_id),o=e.fighters.findIndex(e=>e.player_id===n.actor_id),{recipientIndex:s,puncherIndex:c}=hE(n,e),l=e.fighters[s]??e.fighters[t]??e.fighters[o]??e.fighters[0];if(this.tmpA.set(this.mapping.x(l.x),0,this.mapping.z(l.y)),[`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`,`knockdown`].includes(n.kind)){let t=c>=0?e.fighters[c]:null;this.pendingContacts.push({event:n,presentationEvent:r,presentImpact:i,reactAmount:a,contactTick:t?.action_contact_tick??n.tick,recipientIndex:s,puncherIndex:c,injury:FE(n,e.fighters[s],e.result,t??void 0)})}else n.kind===`bleed`&&this.effects.addEvent(n,this.tmpA,this.settings().reducedMotion)}}fireContacts(e){for(let t=0;te){t+=1;continue}this.pendingContacts.splice(t,1);let{event:r,presentationEvent:i,presentImpact:a,reactAmount:o,recipientIndex:s,puncherIndex:c,injury:l}=n,u=this.buffer.latest()?.fighters[s],d=gE(this.buffer.latest()?.fighters[c],u,this.mapping);a&&u!==void 0&&(this.tmpA.set(this.mapping.x(u.x),0,this.mapping.z(u.y)),this.effects.addEvent(i,this.tmpA,this.settings().reducedMotion,d));let f=this.settings();a&&this.arena.excite(AE[r.kind]??0),a&&s>=0&&this.viewerId!==null&&this.buffer.latest()?.fighters[s]?.player_id===this.viewerId&&[`hit`,`counter_hit`,`knockdown`].includes(r.kind)&&(this.viewerHitFlash=Math.max(this.viewerHitFlash,Math.min(1,.35+r.amount/400))),l!==null&&s>=0&&this.arcadeInjuries[s]===null&&f.blood===`full`&&!f.reducedMotion&&this.applyArcadeInjury(s,l,r,d);let p=this.graphs;if(a&&s>=0&&[`hit`,`counter_hit`,`knockdown`].includes(r.kind)&&i.detail.endsWith(`:head`)&&r.amount>=260&&!f.reducedMotion&&f.blood!==`off`){let e=this.headWorldPose(s);e!==null&&(this.tmpB.set(0,-.07,.1).applyQuaternion(e.quaternion).add(e.position),this.effects.spawnTeeth(this.tmpB,d??i.direction,r.kind===`knockdown`?3:1+Math.floor((r.amount-260)/120),r.event_id))}if(a&&s>=0&&o!==null&&[`hit`,`counter_hit`,`block`,`perfect_block`,`knockdown`].includes(r.kind)){let e=r.kind===`block`||r.kind===`perfect_block`,t=i.detail.endsWith(`:body`)?`body`:`head`;if(p!==null){let n=(c>=0?this.buffer.latest()?.fighters[c]:void 0)?.action_key?.split(`:`)??[],r=n[0]??i.detail.split(`:`)[0]??null,a=n[1]??null;p[s].react(e?`block`:`hit`,t,i.direction,r,a,o)}}a&&c>=0&&[`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`].includes(r.kind)&&p?.[c]?.landedHit(r.kind===`block`||r.kind===`perfect_block`),this.onContact?.(r)}}get resultVisible(){return this.final!==null&&this.frameSeconds>=this.finalRevealAt}get resolutionScale(){return this.scaler.scale}get diagnostics(){let e=this.renderer.getContext(),t=e.getExtension(`WEBGL_debug_renderer_info`),n=t===null?e.getParameter(e.RENDERER):e.getParameter(t.UNMASKED_RENDERER_WEBGL);return{frameMs:this.frameMsAverage,resolutionScale:this.scaler.scale,gpu:this.memoryInfo,graphics:String(n)}}get memoryInfo(){return{geometries:this.renderer.info.memory.geometries,textures:this.renderer.info.memory.textures,programs:this.renderer.info.programs?.length??0}}applyResolutionScale(){let e=this.basePixelRatio*this.scaler.scale;this.renderer.setPixelRatio(e),this.composer.setPixelRatio(e);let t=this.scaler.scale<=bE;this.bloomPass.enabled=!t,this.keyLight!==null&&mE(this.keyLight.shadow,t,this.scaler.scale<.8?1024:2048)}setupLights(){let e=new qh(`#3c4a72`,`#07080c`,.55);this.scene.add(e),this.lights.push(e);let t=new sg(`#fff1dc`,150,24,.56,.55,1.7);t.position.set(.6,7.4,1.2),t.target.position.set(0,.6,0),t.castShadow=!0,t.shadow.mapSize.set(2048,2048),t.shadow.bias=fE,t.shadow.camera.near=3,t.shadow.camera.far=14,this.keyLight=t,this.scene.add(t,t.target),this.lights.push(t);let n=new sg(`#ffe6c8`,95,24,.6,.6,1.7);n.position.set(-2.6,7,-2.2),n.target.position.set(0,.8,0),this.scene.add(n,n.target),this.lights.push(n);for(let[e,t,n,r]of[[`#8fa8ff`,-5.5,3.8,-5.4],[`#7f95e8`,5.6,3.6,-5.6]]){let i=new sg(e,34,30,.72,.9,1.8);i.position.set(t,n,r),i.target.position.set(0,1.2,0),this.scene.add(i,i.target),this.lights.push(i)}let r=new sg(`#ffe8d0`,48,22,.32,.8,1.5);r.position.set(0,5.8,5.4),r.target.position.set(0,1,0),this.scene.add(r,r.target),this.lights.push(r),this.followSpot=r}draw(e,t=!1,n=!0){if(this.destroyed)return;let r=e-this.previous,i=t?1/60:Math.min(.05,Math.max(.001,r/1e3));this.previous=e,!t&&this.scaler.record(r)&&this.applyResolutionScale(),!t&&r>0&&r<1e3&&(this.frameMsAverage+=(r-this.frameMsAverage)*.05);let a=Math.min(this.pixelRatioCap,window.devicePixelRatio||1);a!==this.basePixelRatio&&(this.basePixelRatio=a,this.applyResolutionScale());let o=this.canvas.clientWidth,s=this.canvas.clientHeight;o>0&&s>0&&(this.renderer.getSize(this.sizeCheck),(this.sizeCheck.x!==o||this.sizeCheck.y!==s)&&(this.renderer.setSize(o,s,!1),this.composer.setSize(o,s),this.camera.aspect=o/s,this.portraitPull=Pu.clamp(1.2/this.camera.aspect,1,2.2),this.camera.fov=36*Math.min(1.3,Math.sqrt(this.portraitPull)),this.camera.updateProjectionMatrix()));let c=e/1e3;this.frameSeconds=c,this.finishPass.uniforms.uTime.value=c%1e3,t&&(this.lastManualTime=e);let l=this.settings();this.setBloodLevel(l.blood);let u=this.buffer.latest();if(u?.result!==null&&u?.result!==void 0&&_.has(u.result.finish_method)&&!this.finishSeen&&(this.finishSeen=!0,this.finishSlowMotion=2.2,this.arena.excite(1)),this.finishSlowMotion>0&&!l.reducedMotion){this.finishSlowMotion=Math.max(0,this.finishSlowMotion-i);let e=Math.min(1,this.finishSlowMotion/.5);i*=.3+.7*(1-e)}this.viewerHitFlash=Math.max(0,this.viewerHitFlash-i*3.2);let d=u===null?0:t?PE(u):this.buffer.renderTick(e),f=u===null?null:this.applyLocalPrediction(this.buffer.sample(d),i,e),p=this.replay;if(p!==null){let e=c-p.startedAt;e>=p.plan.durationSeconds?this.endReplay():(d=JT(p.plan,e,this.simulation.tick_rate),f=p.buffer.sample(d)??f,!p.impactFired&&d>=p.plan.impact.tick&&f!==null&&(p.impactFired=!0,this.fireReplayImpact(f)))}let m=this.replay===null?i:i*this.replay.plan.speed,h=1.8,g=!1;if(f!==null){let[e,t]=f.fighters;for(let[e,t]of f.fighters.entries())this.arcadeInjuries[e]===null||this.replay!==null||(t.is_downed?this.observedInjuryDown[e]=!0:this.observedInjuryDown[e]&&f.result===null&&this.restoreInjury(e));let n=this.graphs;if(n!==null){let r=this.headCacheValid[0]?this.headCache[0]:void 0,i=this.headCacheValid[1]?this.headCache[1]:void 0;n[0].boxer.root.visible=!0,n[1].boxer.root.visible=!0,n[0].setResting(f.phase===`rest`),n[1].setResting(f.phase===`rest`);let a=f.phase===`countdown`?f.phase_ticks_remaining:null;n[0].setCountdown(a),n[1].setCountdown(a),f.phase===`fight`&&this.lastPhase===`rest`&&this.replay===null&&(this.roundCalloutUntil=c+xE,this.roundCalloutRound=f.round_number),f.phase===`rest`&&this.lastPhase!==`rest`&&(this.restStartedAt=c),this.lastPhase=f.phase,n[0].update(e,t,m,c,l.reducedMotion,l.blood,d,i),n[1].update(t,e,m,c,l.reducedMotion,l.blood,d,r);for(let[e,t]of n.entries()){let n=t.boxer.bone(`head`);n!==null&&(t.boxer.root.updateMatrixWorld(!0),n.getWorldPosition(this.headCache[e]),this.headCacheValid[e]=!0)}}for(let e=0;e.05&&!t.is_downed){this.downedPoolAccumulators[e]=0;let t=e===0?this.tmpA:this.tmpB;this.tmpHead.set(t.x,this.headHeightOf(e),t.z),this.effects.drip(this.tmpHead,n,l.reducedMotion,e)}else if(n>.3&&t.is_downed&&l.blood!==`off`)for(this.effects.stopDrip(e),this.downedPoolAccumulators[e]+=i*.8;this.downedPoolAccumulators[e]>=1;){--this.downedPoolAccumulators[e];let t=this.downedPoolCounts[e];this.downedPoolCounts[e]=t+1;let n=t*2.399963+e*Math.PI,r=.12+t*.618034%1*.24,i=e===0?this.tmpA:this.tmpB;this.effects.pool(i.x+Math.sin(n)*r,i.z+Math.cos(n)*r,.8)}else this.effects.stopDrip(e),this.downedPoolAccumulators[e]=0}}else this.tmpA.set(-.9,0,0),this.tmpB.set(.9,0,0),this.updateIdleFighters(i,c,d);this.arena.update(c,i,l.reducedMotion),this.effects.update(m),this.updateTrails(m,l.reducedMotion),this.updateReferee(m,c,f,d),this.updateCornermen(m,c,f,d),this.updateCutmen(m,c,f,d),this.updateBlobShadows(),this.fireContacts(d),this.presentFinishWhenShown(d),this.followSpot!==null&&this.followSpot.target.position.set((this.tmpA.x+this.tmpB.x)/2,1,(this.tmpA.z+this.tmpB.z)/2);let v=this.director.update(i,c,{x:this.tmpA.x,z:this.tmpA.z},{x:this.tmpB.x,z:this.tmpB.z},h,g,this.effects.shakeAmount,l.reducedMotion),y=this.replay,b=this.cameraOverride??(y!==null&&f!==null?this.replayFrame(f,c-y.startedAt):this.closeUpFrame(c)??this.cornerShotFrame(c,f,l.reducedMotion)??v);if(this.cameraOverride===null&&this.portraitPull>1){let e=b.tight===!0,t=this.portraitPull/Math.min(1.3,Math.sqrt(this.portraitPull)),n=e?Math.min(t,1.25):t;this.tmpCamera.subVectors(b.position,b.lookAt).multiplyScalar(n),this.camera.position.copy(b.lookAt).add(this.tmpCamera),e&&(this.camera.position.x=Pu.clamp(this.camera.position.x,-2.2,TE),this.camera.position.z=Pu.clamp(this.camera.position.z,-2.2,TE)),this.camera.lookAt(b.lookAt.x,b.lookAt.y-(this.portraitPull-1)*(e?.08:.45),b.lookAt.z)}else this.camera.position.copy(b.position),this.camera.lookAt(b.lookAt);n&&(this.composer.render(),this.drawHudOverlay(f)),!this.destroyed&&!this.manualClock&&(this.raf=requestAnimationFrame(e=>this.draw(e)))}applyLocalPrediction(e,t,n){if(e===null||this.localInput===null||this.viewerId===null)return e;let r=e.fighters.findIndex(e=>e.player_id===this.viewerId),i=this.localInput()??{moveX:0,moveY:0,defense:`none`},a=(this.inputLatencyMs??60)/1e3*this.simulation.tick_rate+this.buffer.interpolationDelayTicks,o=r>=0&&e.phase===`fight`?e.fighters[r]:null,s=this.graphs?.[r]?.ownPunchActive===!0||this.evasion.holdsFeet(n,this.simulation.tick_rate),c=this.movement.update(o,i,s,n,a,e.tick,t,this.simulation.tick_rate),l=this.evasion.pose(n);if(r<0)return e;let u=e.fighters[r],d=o===null?u.defense:rx(o,i,l);if(Math.abs(c.dx)<.01&&Math.abs(c.dy)<.01&&d===u.defense)return e;let f=tx(u,c,e.fighters[+(r===0)]??null),p={...u,x:u.x+f.dx,y:u.y+f.dy,defense:d},m=r===0?[p,e.fighters[1]]:[e.fighters[0],p];return{...e,fighters:m}}headHeightOf(e){return(this.graphs?.[e]?.boxer.metrics.headRestY??1.52)+.04}updateBlobShadows(){let e=[this.tmpA,this.tmpB,this.refereePosition];for(let[t,n]of this.blobShadows.entries()){let r=t<2?this.graphs?.[t]:void 0,i=r?.boxer.root.visible===!0?r.currentRoot:e[t];n.position.x=i.x,n.position.z=i.z;let a=t<2&&this.buffer.latest()?.fighters[t]?.is_downed===!0;n.scale.set(a?2.1:1.25,a?.9:.85,1)}}updateReferee(e,t,n,r){let i=this.referee;if(i===null)return;let a=n?.fighters.find(e=>e.is_downed)??null,o=n?.fighters.some(e=>e.clinch_ticks>0||e.clinch_startup_ticks>0)??!1,s=a===null&&i.breaking,c=a===null?(this.tmpA.x+this.tmpB.x)/2:this.mapping.x(a.x),l=a===null?(this.tmpA.z+this.tmpB.z)/2:this.mapping.z(a.y),u=this.refereeAway.set(this.refereePosition.x-c,0,this.refereePosition.z-l);if(u.lengthSq()<.01&&u.set(0,0,-1),u.normalize(),s){let e=this.tmpB.z-this.tmpA.z,t=this.tmpA.x-this.tmpB.x,n=Math.hypot(e,t),r=e*u.x+t*u.z>=0?1:-1;n>.01&&u.set(e/n*r,0,t/n*r)}let{standoff:d,clearance:f}=XE(a!==null,o,s),p=Pu.clamp(c+u.x*d,-2.4,2.4),m=Pu.clamp(l+u.z*d,-2.4,2.4),h=this.refereePosition.x,g=this.refereePosition.z,_=1-Math.exp(-(s?8:1.6)*e),v=s?Math.min(1,DE*e/Math.max(1e-6,Math.hypot(p-this.refereePosition.x,m-this.refereePosition.z)*_)):1;this.refereePosition.x+=(p-this.refereePosition.x)*_*v,this.refereePosition.z+=(m-this.refereePosition.z)*_*v;for(let e of[this.tmpA,this.tmpB]){let t=this.refereePosition.x-e.x,n=this.refereePosition.z-e.z,r=Math.hypot(t,n);r.001&&(this.refereePosition.x=e.x+t/r*f,this.refereePosition.z=e.z+n/r*f)}e>0&&this.refereeVelocity.set((this.refereePosition.x-h)/e,0,(this.refereePosition.z-g)/e);let y=((Math.atan2(c-this.refereePosition.x,l-this.refereePosition.z)-this.refereeYaw+Math.PI)%(Math.PI*2)+Math.PI*2)%(Math.PI*2)-Math.PI;this.refereeYaw+=y*(1-Math.exp(-(s?8:3)*e));let b=ZE(this.refereePosition,this.refereeYaw,this.refereeVelocity,this.mapping);i.setRefereeCount(a!==null,a?.get_up_count??0),i.aimBreak(this.tmpA,this.tmpB),i.update(b.self,b.focus,e,t,!1,`off`,r)}updateTrails(e,t){let n=this.graphs;if(!(n===null||this.trails.length<4))for(let[r,i]of n.entries())for(let[n,a]of[`gloveL`,`gloveR`].entries()){let o=this.trails[r*2+n];if(!i.boxer.root.visible){o.reset();continue}i.boxer.rig.bones[a].getWorldPosition(this.trailGlove),o.update(this.trailGlove,e,this.camera.position,!t&&this.replay===null)}}updateCornermen(e,t,n,r){let i=this.cornermen;if(i===null)return;let a=n?.phase===`rest`;for(let[n,o]of i.entries()){let i=n===0?-1:1,s=a?EE:wE;this.cornermanPosition.set(i*s,0,-i*s);let c=n===0?3*Math.PI/4:-Math.PI/4;o.attend(a);let l=ZE(this.cornermanPosition,c,this.cornermanVelocity,this.mapping);o.update(l.self,l.focus,e,t,!1,`off`,r)}}updateCutmen(e,t,n,r){let i=this.cutmen,a=this.graphs;if(i===null||a===null)return;let o=n?.phase===`rest`,s=this.mapping.x(Tb);for(let[c,l]of i.entries()){let i=c===0?-1:1,u=o&&a[c].stoolVisible?1:0,d=this.cutmanProgress[c],f=d+Math.sign(u-d)*Math.min(Math.abs(u-d),e/OE);this.cutmanProgress[c]=f;let p=l.boxer.root.visible;if(l.boxer.root.visible=f>.005,!l.boxer.root.visible)continue;this.cutmanFrom.set(i*wE,0,-i*(wE-1)),bx(c===0?0:1,s,_x,32,this.cutmanTo);let m=f*f*(3-2*f);this.cornermanPosition.copy(this.cutmanFrom).lerp(this.cutmanTo,m);let h=this.cutmanLast[c];p||h.copy(this.cornermanPosition),this.cornermanVelocity.copy(this.cornermanPosition).sub(h).divideScalar(Math.max(e,.001)),h.copy(this.cornermanPosition);let g=f>.02&&f<.98,_=this.headCacheValid[c]?this.headCache[c]:null,v=g?Math.atan2(this.cutmanTo.x-this.cutmanFrom.x,this.cutmanTo.z-this.cutmanFrom.z)+(u===1?0:Math.PI):f>=.98?_===null?Math.atan2(i,-i):Math.atan2(_.x-this.cutmanTo.x,_.z-this.cutmanTo.z):Math.atan2(-this.cutmanFrom.x,-this.cutmanFrom.z),y=n?.fighters[c]?.trauma,b=y!==void 0&&y.right_eye+y.right_cut>y.left_eye+y.left_cut?-1:1;if(f>=.98&&_!==null){let e=a[c].boxer.root.rotation.y;this.cutmanFacing.set(Math.sin(e),0,Math.cos(e)),this.cutmanEye.copy(_).addScaledVector(this.cutmanFacing,.09),this.cutmanEye.x+=Math.cos(e)*b*.035,this.cutmanEye.z-=Math.sin(e)*b*.035,this.cutmanEye.y+=.08,l.treat(this.cutmanEye,this.cutmanFacing,b)}else l.treat(null);let x=ZE(this.cornermanPosition,v,this.cornermanVelocity,this.mapping);l.update(x.self,x.focus,e,t,!1,`off`,r)}}drawHudOverlay(e){let t=cE(this.hudCanvas);if(t===null)return;let{context:n,viewport:r}=t;if(n.clearRect(0,0,r.width,r.height),e===null)return;if(this.viewerHitFlash>.01&&!this.settings().reducedMotion){let e=n.createRadialGradient(r.width/2,r.height/2,r.width*.12,r.width/2,r.height/2,r.width*.7);e.addColorStop(0,`rgba(255,235,225,${(this.viewerHitFlash*.18).toFixed(3)})`),e.addColorStop(1,`rgba(140,0,10,${(this.viewerHitFlash*.55).toFixed(3)})`),n.fillStyle=e,n.fillRect(0,0,r.width,r.height)}let i=Math.max(...e.fighters.map(e=>e.trauma.head+e.trauma.body));if(i>350){let e=n.createRadialGradient(r.width/2,r.height/2,r.width*.2,r.width/2,r.height/2,r.width*.72);e.addColorStop(0,`rgba(90,0,8,0)`),e.addColorStop(1,`rgba(75,0,8,${Math.min(.3,i/4600)})`),n.fillStyle=e,n.fillRect(0,0,r.width,r.height)}b(n,r.width,r.height,e,this.players,this.viewerId,this.frameSeconds>=this.finalRevealAt?this.final:null,this.reconnectMs,this.simulation.tick_rate,this.roundStats,this.replay===null?null:`KNOCKOUT REPLAY`,this.inputLatencyMs,this.frameSecondsvoid 0,getItem:()=>null,key:()=>null,removeItem:()=>void 0,setItem:()=>void 0},tD=()=>{try{return window.localStorage}catch{return eD}},nD=()=>({volume:.7,haptics:!0,reducedMotion:window.matchMedia?.(`(prefers-reduced-motion: reduce)`).matches??!1,blood:`full`});function rD(e=tD()){let t=nD();try{let n=JSON.parse(e.getItem($E)??`null`);if(typeof n!=`object`||!n||Array.isArray(n))return t;let r=n;return{volume:typeof r.volume==`number`&&Number.isFinite(r.volume)?Math.max(0,Math.min(1,r.volume)):t.volume,haptics:typeof r.haptics==`boolean`?r.haptics:t.haptics,reducedMotion:typeof r.reducedMotion==`boolean`?r.reducedMotion:t.reducedMotion,blood:r.blood===`reduced`||r.blood===`off`||r.blood===`full`?r.blood:t.blood}}catch{return t}}function iD(e,t=tD()){try{t.setItem($E,JSON.stringify({volume:Math.max(0,Math.min(1,e.volume)),haptics:e.haptics,reducedMotion:e.reducedMotion,blood:e.blood}))}catch{}}var aD=class{value;listeners=new Set;constructor(e=tD()){this.storage=e,this.value=rD(e)}storage;get current(){return this.value}update(e){this.value={...this.value,...e},iD(this.value,this.storage);for(let e of this.listeners)e(this.value)}subscribe(e){return this.listeners.add(e),()=>this.listeners.delete(e)}destroy(){this.listeners.clear()}},oD={stage:`bootstrapping`,player:null,playerId:null,role:null,players:{},playerOrder:[],simulation:null,snapshot:null,final:null,serverTick:0,nextSequence:0,reconnectMs:0,safeError:null},sD=e=>Object.fromEntries(e.map(e=>[e.id,e]));function cD(e,t){if(t.type===`bootstrap`)return{...e,stage:`authorizing`,simulation:t.simulation,safeError:null};if(t.type===`authorized`)return{...e,stage:`connecting`,player:t.player,safeError:null};if(t.type===`connecting`)return{...e,stage:`connecting`};if(t.type===`reconnect-tick`)return{...e,stage:`paused`,reconnectMs:Math.max(0,t.remainingMs)};if(t.type===`fatal`)return{...e,stage:`fatal`,safeError:t.code,reconnectMs:0};let n=t.message;switch(n.type){case`welcome`:return{...e,playerId:n.role===`fighter`?n.player_id:null,role:n.role,players:sD(n.players),playerOrder:n.players.map(e=>e.id),serverTick:n.server_tick,nextSequence:n.role===`fighter`?n.next_sequence:0,safeError:null};case`ticket`:return e;case`waiting`:return{...e,stage:`waiting`};case`ready`:return{...e,stage:e.snapshot?.phase??`countdown`,players:sD(n.players),playerOrder:n.players.map(e=>e.id)};case`paused`:return{...e,stage:`paused`,reconnectMs:n.grace_ms};case`resumed`:return{...e,stage:e.snapshot?.phase??`countdown`,reconnectMs:0};case`snapshot`:return{...e,stage:n.payload.phase,snapshot:n.payload,serverTick:Math.max(e.serverTick,n.payload.tick)};case`final`:return{...e,stage:`complete`,final:n,reconnectMs:0};case`error`:return{...e,stage:`fatal`,safeError:n.code,reconnectMs:0}}}var lD=new Set([`hit`,`counter_hit`,`block`,`perfect_block`,`guard_break`,`knockdown`]),uD=`Move WASD · Jab F/J · Straight R/U · Hook G/H · Uppercut T/Y · Guard Q/E · Body Shift · Power Alt`,dD=`Left side: drag to move · Right pads: L/R punches · Hold BODY, POWER or GUARD · Tap SLIP, WEAVE, PULL or CLINCH`,fD=11e3,pD=4e3,mD=3e3,hD=6,gD=class{root;reloadPage;authorizer;state=oD;settings=new aD;input=new qs;audio=new E(()=>this.settings.current);haptics=new js(()=>this.settings.current);feedbackEvents=new oc;renderer=null;network=null;session=null;abort=new AbortController;destroyed=!1;generation=0;reloadOnRetry=!1;reloading=!1;canvas;status;overlay;roleIndicator;controlsButton;controlsPanel;retry;rematchButton;hint;diagnosticsTimer=null;finalReceivedAt=0;lastFinalMatchId=null;rematchAttempts=0;rematchTimer=null;rematchCountdownTimer=null;resultRevealTimer=null;resultWaitTimer=null;completeSince=null;summaryClock=new m;fightSummary;liveFightStatus;finalSummary;constructor(e,t=()=>window.location.reload(),n=new Cs){this.root=e,this.reloadPage=t,this.authorizer=n,e.innerHTML=`
HANDSauthoritative two-player boxing

`,this.canvas=e.querySelector(`canvas`),this.status=e.querySelector(`[data-status]`),this.overlay=e.querySelector(`[data-overlay]`),this.roleIndicator=e.querySelector(`[data-role]`),this.controlsButton=e.querySelector(`[data-controls]`),this.controlsPanel=e.querySelector(`[data-controls-panel]`),this.retry=e.querySelector(`[data-retry]`),this.rematchButton=e.querySelector(`[data-rematch]`),this.hint=e.querySelector(`[data-hint]`),this.rematchButton.addEventListener(`click`,this.onRematch),this.fightSummary=e.querySelector(`[data-fight-summary]`),this.liveFightStatus=e.querySelector(`[data-fight-status]`),this.finalSummary=e.querySelector(`[data-final]`),this.retry.addEventListener(`click`,this.onRetry),this.bindPanels(),this.syncSettings(),this.input.attachTouch(e.querySelector(`.activity`))}start(){this.authorize()}resetForAuthorization(){this.reloadOnRetry=!1,this.network?.dispose(),this.network=null,this.session?.destroy(),this.session=null,this.renderer?.destroy(),this.renderer=null,this.abort.abort(),this.abort=new AbortController,this.state=oD,this.feedbackEvents.reset(),this.input.setActive(!1),this.input.reset(),this.finalSummary.textContent=``,this.fightSummary.textContent=``,this.liveFightStatus.textContent=``,this.clearRematchTimers(),this.rematchButton.hidden=!0}onRematch=()=>{this.rematchButton.disabled||this.state.stage!==`complete`||(this.rematchAttempts=1,this.authorize())};clearRematchTimers(){this.rematchTimer!==null&&window.clearTimeout(this.rematchTimer),this.rematchCountdownTimer!==null&&window.clearInterval(this.rematchCountdownTimer),this.rematchTimer=null,this.rematchCountdownTimer=null}awaitResultReveal(){this.resultRevealTimer!==null&&window.clearInterval(this.resultRevealTimer);let e=()=>{let e=this.renderer?.resultVisible??!0;this.overlay.hidden=this.state.stage===`complete`&&!e,(e||this.state.stage!==`complete`)&&this.resultRevealTimer!==null&&(window.clearInterval(this.resultRevealTimer),this.resultRevealTimer=null)};this.resultRevealTimer=window.setInterval(e,200),e()}startRematchCountdown(){if(this.clearRematchTimers(),this.state.role!==`fighter`)return;let e=()=>{let e=Math.ceil((this.finalReceivedAt+fD-Date.now())/1e3);this.rematchButton.hidden=this.state.stage!==`complete`,this.rematchButton.disabled=e>0,this.setText(this.rematchButton,e>0?`Rematch in ${e}s`:`Rematch`),e<=0&&this.rematchCountdownTimer!==null&&(window.clearInterval(this.rematchCountdownTimer),this.rematchCountdownTimer=null)};e(),this.rematchCountdownTimer=window.setInterval(e,1e3)}scheduleRematchRetry(){if(this.rematchTimer===null){if(this.rematchAttempts>=hD){this.fail(`rematch_unavailable`);return}this.rematchAttempts+=1,this.setText(this.status,`The ring is still being cleared… trying again.`),this.rematchTimer=window.setTimeout(()=>{this.rematchTimer=null,this.authorize()},mD)}}async authorize(){let e=++this.generation;this.resetForAuthorization(),this.dispatch({type:`connecting`}),this.setText(this.status,`Securing Discord Activity session…`),this.retry.hidden=!0;try{let t=await this.authorizer.authorize(this.abort.signal);if(this.destroyed||e!==this.generation){t.destroy();return}this.session=t,this.dispatch({type:`bootstrap`,simulation:t.bootstrap.simulation}),this.dispatch({type:`authorized`,player:t.player}),this.input.onAction(e=>{this.renderer?.predictAction?.(e),this.network?.notifyAction()});let n=t.takeTicket();if(n===null)throw Error(`ticket_unavailable`);let r=new gc(n,()=>this.input.frame(),{onMessage:e=>this.receive(e),onReconnect:e=>{this.dispatch({type:`reconnect-tick`,remainingMs:e}),this.renderer?.setReconnect(e),this.renderState()},onFatal:e=>this.fail(e),onFreshAuth:()=>{e===this.generation&&this.authorize()}});this.network=r,r.start(),this.setText(this.status,`Connecting to the ring…`)}catch(t){!this.abort.signal.aborted&&e===this.generation&&(this.reloadOnRetry=t instanceof Ee&&t.reloadRequired,this.fail(Me(t)))}}ensureRenderer(){if(this.renderer!==null||this.session===null||this.destroyed)return;let e=new QE(this.canvas,this.session.bootstrap.simulation,()=>this.settings.current,{localInput:()=>this.input.held(),inputSequenceOf:e=>this.network?.sequenceOf(e)??null});e.onContact=e=>{this.audio.event(e),this.haptics.event(e)},e.onArcadeInjury=e=>this.audio.injury(e),this.renderer=e}receive(e){if(e.type===`error`){this.fail(e.code);return}if(e.type===`welcome`&&this.ensureRenderer(),(e.type===`welcome`||e.type===`resumed`)&&this.renderer?.resyncClock(),(e.type===`waiting`||e.type===`ready`)&&(this.rematchAttempts=0),e.type===`final`&&this.rematchAttempts>0&&e.match_id===this.lastFinalMatchId){this.scheduleRematchRetry();return}this.dispatch({type:`message`,message:e}),e.type===`snapshot`&&this.receiveSnapshot(e.payload),e.type===`final`&&(this.rematchAttempts=0,this.lastFinalMatchId=e.match_id,this.finalReceivedAt=Date.now(),this.renderer?.setFinal(e),this.audio.result(e),this.startRematchCountdown(),this.awaitResultReveal()),this.renderer?.setPlayers(this.state.players,this.state.playerId,this.state.playerOrder),this.renderer?.setReconnect(this.state.reconnectMs),this.renderState()}get networkStats(){return{inputLatencyMs:this.network?.inputLatencyMs??null,resolutionScale:this.renderer?.resolutionScale??null,gpu:this.renderer?.memoryInfo??null}}receiveSnapshot(e){this.renderer?.setInputLatency(this.network?.inputLatencyMs??null),this.renderer?.push(e);let t=e.fighters.find(e=>e.player_id===this.state.playerId);this.input.setKnockdown(t?.is_downed===!0),t!==void 0&&this.audio.snapshot(e.tick,t.stamina,t.maximum_stamina,t.trauma.head+t.trauma.body),this.audio.roundClock(e.phase,e.round_number,e.phase_ticks_remaining,this.state.simulation?.tick_rate??30);for(let t of this.feedbackEvents.accept(e.events))lD.has(t.kind)||(this.audio.event(t),this.haptics.event(t))}dispatch(e){this.state=cD(this.state,e)}setText(e,t){e.textContent!==t&&(e.textContent=t)}renderState(){let e={bootstrapping:`Loading…`,authorizing:`Authorizing with Discord…`,connecting:`Connecting securely…`,waiting:`Waiting for one opponent to use Play now in this channel.`,countdown:`Bout countdown.`,fight:`Round ${this.state.snapshot?.round_number??1} in progress.`,knockdown:`Knockdown count ${this.state.snapshot?.fighters.find(e=>e.player_id===this.state.playerId)?.get_up_count??0}.`,foul_recovery:`Foul recovery in progress.`,rest:`Between-round rest.`,paused:`Connection paused. ${Math.ceil(this.state.reconnectMs/1e3)} seconds remain.`,complete:`Bout complete. Scorecards and rating changes are displayed.`,fatal:Ts(this.state.safeError??`safe_error`)},t=this.state.role===`spectator`;if(this.setText(this.status,t?`Spectating — ${e[this.state.stage]}`:e[this.state.stage]),this.status.hidden=[`countdown`,`fight`,`knockdown`,`foul_recovery`,`rest`].includes(this.state.stage),this.overlay.toggleAttribute(`data-raised`,this.state.snapshot!==null),this.state.stage!==`complete`)this.overlay.hidden=!1,this.completeSince=null;else if(this.state.final===null){this.completeSince??=Date.now();let e=Date.now()-this.completeSince;this.overlay.hidden=e{this.resultWaitTimer=null,this.renderState()},pD-e+50))}this.roleIndicator.hidden=!t,this.controlsButton.hidden=t,t&&(this.controlsPanel.hidden=!0,this.controlsButton.setAttribute(`aria-expanded`,`false`));let n=this.state.snapshot?.fighters.find(e=>e.player_id===this.state.playerId),r=t?`Spectating. ${e[this.state.stage]}`:this.state.stage===`knockdown`&&n?.is_downed===!0?`Knockdown. Count ${n.get_up_count}. ${n.get_up_prompt===null?`Wait for your private rhythm instruction.`:`Press ${n.get_up_prompt===`get_up_left`?`left`:`right`} now.`}`:this.state.stage===`paused`?`Connection paused.`:e[this.state.stage];this.setText(this.liveFightStatus,r),this.retry.hidden=this.state.stage!==`fatal`,this.setText(this.retry,this.reloadOnRetry?`Reload`:`Retry securely`),this.state.stage!==`complete`&&(this.rematchButton.hidden=!0);let i=!t&&(this.state.stage===`waiting`||this.state.stage===`countdown`);this.hint.hidden=!i,i&&this.setText(this.hint,Es()?dD:uD);let a=!t&&[`countdown`,`fight`,`knockdown`,`foul_recovery`].includes(this.state.stage),o=!t&&this.state.snapshot!==null&&(this.state.stage===`rest`||this.state.stage===`paused`);if(this.input.setActive(a,a||o),this.network?.setActive(a),this.renderFightSummary(),this.state.final!==null){let e=this.state.final;this.setText(this.finalSummary,`${e.method.replaceAll(`_`,` `)}. ${e.winner_id===null?`Draw`:`${this.state.players[e.winner_id]?.name??`Winner`} wins`}. Scorecards: ${e.scorecards.map(e=>`${e.judge}: ${e.player_one.reduce((e,t)=>e+t,0)} to ${e.player_two.reduce((e,t)=>e+t,0)}`).join(`; `)}. Ratings: ${Object.entries(e.ratings).map(([e,t])=>`${this.state.players[e]?.name??`fighter`} ${t.before} to ${t.after}`).join(`; `)}.`)}}renderFightSummary(){let e=this.state.snapshot;if(e===null)return;let t=this.state.simulation?.tick_rate??30,n=Math.floor(this.summaryClock.ticks(e)/t),r=`${Math.floor(n/60)}:${String(n%60).padStart(2,`0`)}`,i=e.fighters.map(e=>{let t=this.state.players[e.player_id];return`${t?.name??`Fighter`}, ELO ${t?.rating??`unknown`}, stamina ${Math.round(e.stamina)} of ${Math.round(e.maximum_stamina)}, guard ${Math.round(e.guard)}, poise ${Math.round(e.poise)}, conditioning ${Math.round(e.conditioning)}, ${e.warnings} warnings, ${e.knockdowns} knockdowns`}),a=e.fighters.find(e=>e.player_id===this.state.playerId),o=a?.is_downed===!0?a.get_up_prompt===null?`You are down. Count ${a.get_up_count}. Wait for your private rhythm instruction.`:`You are down. Count ${a.get_up_count}. Press ${a.get_up_prompt===`get_up_left`?`left`:`right`} now. Get-up progress ${a.get_up_meter} of ${a.get_up_required}.`:``;this.setText(this.fightSummary,`Round ${e.round_number}. ${e.phase.replace(`_`,` `)}. Clock ${r}. ${i.join(`. `)}. ${o}`.trim())}onRetry=()=>{if(this.reloadOnRetry){this.reloading=!0,this.reloadPage();return}this.authorize()};bindPanels(){let e=(e,t)=>{let n=this.root.querySelector(e),r=this.root.querySelector(t);n.addEventListener(`click`,()=>{r.hidden=!r.hidden,n.setAttribute(`aria-expanded`,String(!r.hidden))})};e(`[data-controls]`,`[data-controls-panel]`),e(`[data-settings]`,`[data-settings-panel]`);let t=this.root.querySelector(`[data-settings-panel]`);this.root.querySelector(`[data-settings]`).addEventListener(`click`,()=>{this.diagnosticsTimer!==null&&window.clearInterval(this.diagnosticsTimer),this.diagnosticsTimer=null,!t.hidden&&(this.refreshDiagnostics(),this.diagnosticsTimer=window.setInterval(()=>this.refreshDiagnostics(),1e3))});let n=this.root.querySelector(`[data-copy-diagnostics]`);n.addEventListener(`click`,()=>{let e=this.diagnosticsText(),t=()=>{this.setText(n,`Copied`),window.setTimeout(()=>this.setText(n,`Copy diagnostics`),1500)},r=()=>{let e=this.root.querySelector(`[data-diagnostics]`),t=window.getSelection();if(t===null)return;let r=document.createRange();r.selectNodeContents(e),t.removeAllRanges(),t.addRange(r),this.setText(n,`Selected. Copy manually`),window.setTimeout(()=>this.setText(n,`Copy diagnostics`),2500)},i=navigator.clipboard;if(i===void 0||typeof i.writeText!=`function`){r();return}i.writeText(e).then(t).catch(r)}),this.root.querySelector(`[data-volume]`).addEventListener(`input`,e=>{this.settings.update({volume:Number(e.target.value)}),this.audio.setVolume()}),this.root.querySelector(`[data-haptics]`).addEventListener(`change`,e=>{this.settings.update({haptics:e.target.checked})}),this.root.querySelector(`[data-motion]`).addEventListener(`change`,e=>{let t=e.target.checked;this.settings.update({reducedMotion:t}),this.renderer?.setReducedMotion(t)}),this.root.querySelector(`[data-blood]`).addEventListener(`change`,e=>{let t=e.target.value;this.settings.update({blood:t}),this.renderer?.setBloodLevel(t)})}diagnosticsText(){let e=this.networkStats,t=this.renderer?.diagnostics,n=t===void 0||t.frameMs<=0?`-`:(1e3/t.frameMs).toFixed(0);return[`stage: ${this.state.stage} · role: ${this.state.role??`-`}`,`input latency: ${e.inputLatencyMs===null?`-`:`${Math.round(e.inputLatencyMs)} ms`}`,`frame: ${t===void 0?`-`:`${t.frameMs.toFixed(1)} ms (${n} fps)`} · render scale: ${t?.resolutionScale??`-`}`,`gpu objects: ${t===void 0?`-`:`${t.gpu.geometries} geometries, ${t.gpu.textures} textures, ${t.gpu.programs} programs`}`,`graphics: ${t?.graphics??`-`}`,`browser: ${navigator.userAgent}`,`pointer: ${Es()?`coarse`:`fine`} · viewport: ${window.innerWidth}x${window.innerHeight} @${window.devicePixelRatio}`,`last error: ${this.state.safeError??`none`}`,`match: ${this.state.final?.match_id??`-`}`].join(` +`)}refreshDiagnostics(){this.setText(this.root.querySelector(`[data-diagnostics]`),this.diagnosticsText())}syncSettings(){let e=this.settings.current;this.root.querySelector(`[data-volume]`).value=String(e.volume),this.root.querySelector(`[data-haptics]`).checked=e.haptics,this.root.querySelector(`[data-motion]`).checked=e.reducedMotion,this.root.querySelector(`[data-blood]`).value=e.blood}fail(e){if(e===`room_closed`&&this.rematchAttempts>0){this.scheduleRematchRetry();return}e===`client_outdated`&&(this.reloadOnRetry=!0),this.dispatch({type:`fatal`,code:e}),this.network?.dispose(),this.network=null,this.session?.destroy(),this.session=null,this.renderer?.destroy(),this.renderer=null,this.input.setActive(!1),this.input.reset(),this.renderState()}destroy(){this.destroyed||(this.destroyed=!0,this.generation+=1,this.abort.abort(),this.network?.dispose(),this.session?.destroy(),this.reloading||this.authorizer.close(),this.renderer?.destroy(),this.input.destroy(),this.audio.destroy(),this.settings.destroy(),this.retry.removeEventListener(`click`,this.onRetry),this.rematchButton.removeEventListener(`click`,this.onRematch),this.clearRematchTimers(),this.diagnosticsTimer!==null&&window.clearInterval(this.diagnosticsTimer),this.resultRevealTimer!==null&&window.clearInterval(this.resultRevealTimer),this.resultWaitTimer!==null&&window.clearTimeout(this.resultWaitTimer),this.diagnosticsTimer=null,this.root.replaceChildren())}},_D={broadcast:{position:[0,1.88,7.15],lookAt:[0,1.12,0]},side:{position:[7.4,1.6,0],lookAt:[0,1.1,0]},top:{position:[.01,8.5,.01],lookAt:[0,0,0]},ringside:{position:[1.6,1.5,4.1],lookAt:[.2,1.25,0]}},vD=[[`hips`,`spine`],[`spine`,`head`],[`chest`,`shoulderL`],[`shoulderL`,`elbowL`],[`elbowL`,`gloveL`],[`chest`,`shoulderR`],[`shoulderR`,`elbowR`],[`elbowR`,`gloveR`],[`hips`,`hipL`],[`hipL`,`kneeL`],[`kneeL`,`ankleL`],[`hips`,`hipR`],[`hipR`,`kneeR`],[`kneeR`,`ankleR`]],yD=class{root;renderer=null;replay=null;raf=0;playing=!1;speed=1;virtualTick=0;carry=0;latencyMs=0;pendingQueue=[];destroyed=!1;overlays={skeleton:!1,hurtbox:!1,hitbox:!1};skeletonLines=[];hurtboxMeshes=[];hitboxMeshes=[];statusEl;metricsEl;canvas;constructor(e){this.root=e,e.innerHTML=`
HANDS LABloading replay…
@@ -4327,29 +4590,7 @@ void main() { -
`,this.canvas=e.querySelector(`canvas`),this.statusEl=e.querySelector(`[data-lab-status]`),this.metricsEl=e.querySelector(`[data-lab-metrics]`),this.bindControls()}async start(){let e=new URLSearchParams(window.location.search),t=e.get(`replay`)??`golden`,n=await fetch(`/replays/${t}.json`);if(n.ok||(n=await fetch(`/hands/replays/${t}.json`)),!n.ok)throw Error(`replay_load_failed:${n.status}`);this.replay=await n.json(),await VS(),this.renderer=new FC(this.canvas,{tick_rate:this.replay.tick_rate,ring_half_width:500,ring_half_height:330},()=>({volume:0,haptics:!1,reducedMotion:!1,blood:`full`}),{manualClock:!0});let r=Object.fromEntries(this.replay.ticks[0].snapshot.payload.fighters.map(e=>[e.player_id,{id:e.player_id,name:e.player_id===`one`?`Azure Vector`:`Crimson Geometry`,avatar:null,rating:1500,connected:!0}]));this.renderer.setPlayers(r,`one`),this.buildOverlays();let i=e.get(`tick`);if(e.get(`metrics`)===`1`){await this.renderer.ready,this.exportMetrics(),this.setStatus(`metrics done`);return}if(i!==null){let t=Number(i);await this.renderer.ready,this.seek(t);let n=YC[e.get(`camera`)??``]??YC.broadcast;this.renderer.labSetCameraOverride(n.position,n.lookAt),this.overlays.skeleton=e.get(`skeleton`)===`1`,this.overlays.hurtbox=e.get(`hurtbox`)===`1`,this.overlays.hitbox=e.get(`hitbox`)===`1`,this.syncOverlayVisibility(),this.renderCurrentTick(),window.__labDebug={roots:this.renderer.labRigs.map(e=>e.position.toArray().map(e=>Number(e.toFixed(3)))),heads:this.renderer.labRigs.map(e=>{let t=e.getObjectByName(AS.head??`head`);return t===void 0?null:t.getWorldPosition(new X).toArray().map(e=>Number(e.toFixed(3)))}),gloves:this.renderer.labRigs.map(e=>{let t=e.getObjectByName(AS.gloveL??`gloveL`);return t===void 0?null:t.getWorldPosition(new X).toArray().map(e=>Number(e.toFixed(3)))}),material:(()=>{let e=null;return this.renderer.labRigs[0]?.traverse(t=>{if(e===null&&t instanceof If){let n=t.material;e={colorHex:n.color.getHexString(),hasMap:n.map!==null,mapImage:n.map?.image?.width??`none`,mapVersion:n.map?.version,clearcoat:n.clearcoat,opacity:n.opacity}}}),e})()},this.setStatus(`filmstrip tick ${t}`);return}this.playing=!0;let a=()=>{this.destroyed||(this.advance(),this.raf=requestAnimationFrame(a))};this.raf=requestAnimationFrame(a)}bindControls(){this.root.querySelector(`[data-lab='play']`).addEventListener(`click`,e=>{this.playing=!this.playing,e.target.textContent=this.playing?`Pause`:`Play`}),this.root.querySelector(`[data-lab='step']`).addEventListener(`click`,()=>{this.playing=!1,this.root.querySelector(`[data-lab='play']`).textContent=`Play`,this.virtualTick=Math.min(this.virtualTick+1,(this.replay?.ticks.length??1)-1),this.pushUpTo(this.virtualTick),this.renderCurrentTick()}),this.root.querySelector(`[data-lab='speed']`).addEventListener(`change`,e=>{this.speed=Number(e.target.value)}),this.root.querySelector(`[data-lab='camera']`).addEventListener(`change`,e=>{let t=YC[e.target.value];this.renderer?.labSetCameraOverride(t.position,t.lookAt)});for(let e of[`skeleton`,`hurtbox`,`hitbox`])this.root.querySelector(`[data-lab='${e}']`).addEventListener(`change`,t=>{this.overlays[e]=t.target.checked,this.syncOverlayVisibility()});this.root.querySelector(`[data-lab='latency']`).addEventListener(`change`,e=>{this.latencyMs=Math.max(0,Math.min(500,Number(e.target.value)))}),this.root.querySelector(`[data-lab='metrics']`).addEventListener(`click`,()=>this.exportMetrics())}advance(){if(!this.playing||this.replay===null)return;let e=this.replay.ticks.length-1;if(!(this.virtualTick>=e)){for(this.carry+=this.speed;this.carry>=1&&this.virtualTick0?this.pendingQueue.push({at:performance.now()+this.latencyMs,tick:t}):this.renderer?.push(t.snapshot.payload))}drainLatencyQueue(){let e=performance.now();for(let t=this.pendingQueue.length-1;t>=0;--t){let n=this.pendingQueue[t];n.at<=e&&(this.renderer?.push(n.tick.snapshot.payload),this.pendingQueue.splice(t,1))}}seek(e,t=!0){if(this.replay===null||this.renderer===null)return;let n=Math.max(0,Math.min(e,this.replay.ticks.length-1));for(let e=0;e<=n;e+=1)this.renderer.push(this.replay.ticks[e].snapshot.payload),e>=n-15&&this.renderer.labEffects.update(1/30);this.virtualTick=n,this.renderOnSeek=t}renderOnSeek=!0;renderCurrentTick(e){if(this.replay===null||this.renderer===null)return;this.drainLatencyQueue(),this.renderer.labFrame(this.virtualTick/this.replay.tick_rate,e??this.renderOnSeek),this.renderer.labFrame((this.virtualTick+.5)/this.replay.tick_rate,e??this.renderOnSeek),this.updateOverlays(),this.updateTrajectory();let t=this.replay.ticks[this.virtualTick]?.snapshot.payload.phase??``;this.setStatus(`tick ${this.virtualTick}/${this.replay.ticks.length-1} · ${t} · ${this.speed}×`)}buildOverlays(){let e=this.renderer;if(e===null)return;let t=new ap({color:8257448,depthTest:!1,transparent:!0,opacity:.9});for(let n of e.labRigs){let r=new Qd;r.setAttribute(`position`,new Ld(new Float32Array(XC.length*6),3));let i=new _p(r,t);i.frustumCulled=!1,i.renderOrder=20,e.labScene.add(i),this.skeletonLines.push(i);let a=new Q(new Mp(.13,.16,4,8),new pf({color:16735581,wireframe:!0,transparent:!0,opacity:.85,depthTest:!1}));a.renderOrder=21,a.position.y=.12,(n.getObjectByName(AS.head??`head`)??n).add(a),this.hurtboxMeshes.push(a);let o=new Q(new Mp(.21,.34,4,8),new pf({color:16758877,wireframe:!0,transparent:!0,opacity:.7,depthTest:!1}));o.renderOrder=21,o.position.y=.16,(n.getObjectByName(AS.chest??`chest`)??n).add(o),this.hurtboxMeshes.push(o);for(let e of[`gloveL`,`gloveR`]){let t=new Q(new mm(.11,10,8),new pf({color:6141183,wireframe:!0,transparent:!0,opacity:.85,depthTest:!1}));t.renderOrder=22,(n.getObjectByName(AS[e]??e)??n).add(t),this.hitboxMeshes.push(t)}}this.syncOverlayVisibility()}syncOverlayVisibility(){for(let e of this.skeletonLines)e.visible=this.overlays.skeleton;for(let e of this.hurtboxMeshes)e.visible=this.overlays.hurtbox;for(let e of this.hitboxMeshes)e.visible=this.overlays.hitbox;this.updateTrajectory()}updateTrajectory(){if(this.trajectoryLine!==null&&(this.trajectoryLine.removeFromParent(),this.trajectoryLine.geometry.dispose(),this.trajectoryLine.material.dispose(),this.trajectoryLine=null),!this.overlays.hitbox||this.replay===null||this.renderer===null)return;let e=this.replay.ticks[this.virtualTick]?.snapshot.payload.fighters[0]?.action_key;if(e==null)return;let t=e.split(`:`),n=JC.trajectories[`${t[0]}:${t[1]}`];if(n===void 0)return;let r=this.renderer.labRigs[0],i=r.children[0]??r;i.updateMatrixWorld(!0);let a=(t[1]===`right`?n.right:n.left).map(e=>i.localToWorld(new X(e[0]??0,e[1]??0,e[2]??0)));if(a.length<2)return;let o=new Qd().setFromPoints(a);this.trajectoryLine=new pp(o,new ap({color:6141183,transparent:!0,opacity:.75,depthTest:!1})),this.trajectoryLine.renderOrder=23,this.trajectoryLine.frustumCulled=!1,this.renderer.labScene.add(this.trajectoryLine)}updateOverlays(){let e=this.renderer;if(e!==null)for(let[t,n]of e.labRigs.entries()){let e=this.skeletonLines[t];if(e===void 0||!e.visible)continue;let r=e.geometry.getAttribute(`position`),i=new X,a=new X;XC.forEach(([e,t],o)=>{let s=n.getObjectByName(e),c=n.getObjectByName(t);s===void 0||c===void 0||(s.getWorldPosition(i),c.getWorldPosition(a),r.setXYZ(o*2,i.x,i.y,i.z),r.setXYZ(o*2+1,a.x,a.y,a.z))}),r.needsUpdate=!0}}jointWorld(e,t){let n=(this.renderer?.labRigs[e])?.getObjectByName(AS[t]??t);return n==null?null:n.getWorldPosition(new X)}exportMetrics(){if(this.replay===null)return;let e={contactAlignment:[],maxRootStepMeters:0,footSlideMeters:0,phaseDriftTicks:0};for(let t of this.replay.ticks){let n=t.snapshot.payload.events.find(e=>[`hit`,`counter_hit`,`block`].includes(e.kind)),r=t.snapshot.payload.fighters[0].action_hand;if(n===void 0||r===null)continue;let i=Math.min(t.tick+1,this.replay.ticks.length-1);this.seek(i,!1),this.renderCurrentTick(!1);let a=this.jointWorld(0,r===`left`?`gloveL`:`gloveR`),o=this.jointWorld(1,`head`),s=this.jointWorld(1,`chest`);a!==null&&o!==null&&s!==null&&e.contactAlignment.push({tick:t.tick,kind:n.kind,gloveToHeadMeters:Number(Math.max(0,a.distanceTo(o)-Vy.head.radius).toFixed(4)),gloveToTorsoMeters:Number(Math.max(0,a.distanceTo(s)-Vy.torso.radius).toFixed(4))})}this.seek(0,!1);let t=null,n=null;for(let r of this.replay.ticks){this.seek(r.tick,!1),this.renderCurrentTick(!1);let i=this.renderer.labRigs[0].position.x;n!==null&&(e.maxRootStepMeters=Math.max(e.maxRootStepMeters,Math.abs(i-n))),n=i;let a=r.snapshot.payload.fighters[0],o=Math.hypot(a.velocity_x,a.velocity_y),s=this.replay.ticks.slice(Math.max(0,r.tick-30),r.tick+1).some(e=>e.snapshot.payload.fighters[0].is_downed);if(o===0&&!a.is_downed&&!s&&r.snapshot.payload.phase===`fight`){let n=[this.jointWorld(0,`ankleL`),this.jointWorld(0,`ankleR`)].filter(e=>e!==null);t!==null&&n.length===2&&(e.footSlideMeters=Math.max(e.footSlideMeters,Number(Math.max(n[0].distanceTo(t[0]),n[1].distanceTo(t[1])).toFixed(4)))),t=n}else t=null}this.metricsEl.textContent=` contacts: ${e.contactAlignment.map(e=>`${e.kind}@t${e.tick} glove-head ${e.gloveToHeadMeters}m`).join(` · `)} · max root step ${e.maxRootStepMeters.toFixed(3)}m · foot slide ${e.footSlideMeters}m`,window.__labDebug={roots:this.renderer.labRigs.map(e=>e.position.toArray().map(e=>Number(e.toFixed(3)))),graphsActive:this.renderer.graphs!==null,heads:this.renderer.labRigs.map(e=>{let t=e.getObjectByName(AS.head??`head`);return t===void 0?null:t.getWorldPosition(new X).toArray().map(e=>Number(e.toFixed(3)))})};let r=new Blob([JSON.stringify(e,null,1)],{type:`application/json`}),i=document.createElement(`a`);i.href=URL.createObjectURL(r),i.download=`hands-lab-metrics.json`,i.click(),URL.revokeObjectURL(i.href)}setStatus(e){this.statusEl.textContent!==e&&(this.statusEl.textContent=e)}destroy(){this.destroyed||(this.destroyed=!0,cancelAnimationFrame(this.raf),this.renderer?.destroy(),this.root.replaceChildren())}};function QC(e){let t=new ZC(e);return t.start().catch(t=>{e.querySelector(`[data-lab-status]`).textContent=`lab failed: ${String(t)}`}),()=>t.destroy()}var $C=class{root;renderer;scene=new id;camera;mixer=null;labMaterials=[];actions=new Map;current=null;skeletonHelper=null;model=null;raf=0;previous=performance.now();playing=!0;loop=!0;warnings=[];inventoryEl;clipsEl;warningsEl;timeSlider;constructor(e){this.root=e,e.innerHTML=`
+
`,this.canvas=e.querySelector(`canvas`),this.statusEl=e.querySelector(`[data-lab-status]`),this.metricsEl=e.querySelector(`[data-lab-metrics]`),this.bindControls()}async start(){let e=new URLSearchParams(window.location.search),t=e.get(`replay`)??`golden`,n=await fetch(`/replays/${t}.json`);if(n.ok||(n=await fetch(`/hands/replays/${t}.json`)),!n.ok)throw Error(`replay_load_failed:${n.status}`);this.replay=await n.json(),await fw(),this.renderer=new QE(this.canvas,{tick_rate:this.replay.tick_rate,ring_half_width:500,ring_half_height:500},()=>({volume:0,haptics:!1,reducedMotion:!1,blood:`full`}),{manualClock:!0});let r=Object.fromEntries(this.replay.ticks[0].snapshot.payload.fighters.map(e=>[e.player_id,{id:e.player_id,name:e.player_id===`one`?`Azure Vector`:`Crimson Geometry`,avatar:null,rating:1500,connected:!0}]));this.renderer.setPlayers(r,`one`),this.buildOverlays();let i=e.get(`tick`);if(e.get(`metrics`)===`1`){await this.renderer.ready,this.exportMetrics(),this.setStatus(`metrics done`);return}if(i!==null){let t=Number(i);await this.renderer.ready,this.seek(t);let n=_D[e.get(`camera`)??``]??_D.broadcast;this.renderer.labSetCameraOverride(n.position,n.lookAt),this.overlays.skeleton=e.get(`skeleton`)===`1`,this.overlays.hurtbox=e.get(`hurtbox`)===`1`,this.overlays.hitbox=e.get(`hitbox`)===`1`,this.syncOverlayVisibility(),this.renderCurrentTick(),window.__labDebug={roots:this.renderer.labRigs.map(e=>e.position.toArray().map(e=>Number(e.toFixed(3)))),heads:this.renderer.labRigs.map(e=>{let t=e.getObjectByName(rC.head??`head`);return t===void 0?null:t.getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3)))}),gloves:this.renderer.labRigs.map(e=>{let t=e.getObjectByName(rC.gloveL??`gloveL`);return t===void 0?null:t.getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3)))}),material:(()=>{let e=null;return this.renderer.labRigs[0]?.traverse(t=>{if(e===null&&t instanceof Sp){let n=t.material;e={colorHex:n.color.getHexString(),hasMap:n.map!==null,mapImage:n.map?.image?.width??`none`,mapVersion:n.map?.version,clearcoat:n.clearcoat,opacity:n.opacity}}}),e})()},this.setStatus(`filmstrip tick ${t}`);return}this.playing=!0;let a=()=>{this.destroyed||(this.advance(),this.raf=requestAnimationFrame(a))};this.raf=requestAnimationFrame(a)}bindControls(){this.root.querySelector(`[data-lab='play']`).addEventListener(`click`,e=>{this.playing=!this.playing,e.target.textContent=this.playing?`Pause`:`Play`}),this.root.querySelector(`[data-lab='step']`).addEventListener(`click`,()=>{this.playing=!1,this.root.querySelector(`[data-lab='play']`).textContent=`Play`,this.virtualTick=Math.min(this.virtualTick+1,(this.replay?.ticks.length??1)-1),this.pushUpTo(this.virtualTick),this.renderCurrentTick()}),this.root.querySelector(`[data-lab='speed']`).addEventListener(`change`,e=>{this.speed=Number(e.target.value)}),this.root.querySelector(`[data-lab='camera']`).addEventListener(`change`,e=>{let t=_D[e.target.value];this.renderer?.labSetCameraOverride(t.position,t.lookAt)});for(let e of[`skeleton`,`hurtbox`,`hitbox`])this.root.querySelector(`[data-lab='${e}']`).addEventListener(`change`,t=>{this.overlays[e]=t.target.checked,this.syncOverlayVisibility()});this.root.querySelector(`[data-lab='latency']`).addEventListener(`change`,e=>{this.latencyMs=Math.max(0,Math.min(500,Number(e.target.value)))}),this.root.querySelector(`[data-lab='metrics']`).addEventListener(`click`,()=>this.exportMetrics())}advance(){if(!this.playing||this.replay===null)return;let e=this.replay.ticks.length-1;if(!(this.virtualTick>=e)){for(this.carry+=this.speed;this.carry>=1&&this.virtualTick0?this.pendingQueue.push({at:performance.now()+this.latencyMs,tick:t}):this.renderer?.push(t.snapshot.payload))}drainLatencyQueue(){let e=performance.now();for(let t=this.pendingQueue.length-1;t>=0;--t){let n=this.pendingQueue[t];n.at<=e&&(this.renderer?.push(n.tick.snapshot.payload),this.pendingQueue.splice(t,1))}}seek(e,t=!0){if(this.replay===null||this.renderer===null)return;let n=Math.max(0,Math.min(e,this.replay.ticks.length-1));for(let e=0;e<=n;e+=1)this.renderer.push(this.replay.ticks[e].snapshot.payload),e>=n-15&&this.renderer.labEffects.update(1/30);this.virtualTick=n,this.renderOnSeek=t}renderOnSeek=!0;renderCurrentTick(e){if(this.replay===null||this.renderer===null)return;this.drainLatencyQueue(),this.renderer.labFrame(this.virtualTick/this.replay.tick_rate,e??this.renderOnSeek),this.renderer.labFrame((this.virtualTick+.5)/this.replay.tick_rate,e??this.renderOnSeek),this.updateOverlays();let t=this.replay.ticks[this.virtualTick]?.snapshot.payload.phase??``;this.setStatus(`tick ${this.virtualTick}/${this.replay.ticks.length-1} · ${t} · ${this.speed}×`)}buildOverlays(){let e=this.renderer;if(e===null)return;let t=new Vp({color:8257448,depthTest:!1,transparent:!0,opacity:.9});for(let n of e.labRigs){let r=new Lf;r.setAttribute(`position`,new Sf(new Float32Array(vD.length*6),3));let i=new $p(r,t);i.frustumCulled=!1,i.renderOrder=20,e.labScene.add(i),this.skeletonLines.push(i);let a=new up(new mm(.13,.16,4,8),new Qf({color:16735581,wireframe:!0,transparent:!0,opacity:.85,depthTest:!1}));a.renderOrder=21,a.position.y=.12,(n.getObjectByName(rC.head??`head`)??n).add(a),this.hurtboxMeshes.push(a);let o=new up(new mm(.21,.34,4,8),new Qf({color:16758877,wireframe:!0,transparent:!0,opacity:.7,depthTest:!1}));o.renderOrder=21,o.position.y=.16,(n.getObjectByName(rC.chest??`chest`)??n).add(o),this.hurtboxMeshes.push(o);for(let e of[`gloveL`,`gloveR`]){let t=new up(new Ym(.11,10,8),new Qf({color:6141183,wireframe:!0,transparent:!0,opacity:.85,depthTest:!1}));t.renderOrder=22,(n.getObjectByName(rC[e]??e)??n).add(t),this.hitboxMeshes.push(t)}}this.syncOverlayVisibility()}syncOverlayVisibility(){for(let e of this.skeletonLines)e.visible=this.overlays.skeleton;for(let e of this.hurtboxMeshes)e.visible=this.overlays.hurtbox;for(let e of this.hitboxMeshes)e.visible=this.overlays.hitbox}updateOverlays(){let e=this.renderer;if(e!==null)for(let[t,n]of e.labRigs.entries()){let e=this.skeletonLines[t];if(e===void 0||!e.visible)continue;let r=e.geometry.getAttribute(`position`),i=new Z,a=new Z;vD.forEach(([e,t],o)=>{let s=n.getObjectByName(e),c=n.getObjectByName(t);s===void 0||c===void 0||(s.getWorldPosition(i),c.getWorldPosition(a),r.setXYZ(o*2,i.x,i.y,i.z),r.setXYZ(o*2+1,a.x,a.y,a.z))}),r.needsUpdate=!0}}jointWorld(e,t){let n=(this.renderer?.labRigs[e])?.getObjectByName(rC[t]??t);return n==null?null:n.getWorldPosition(new Z)}exportMetrics(){if(this.replay===null)return;let e={contactAlignment:[],maxRootStepMeters:0,footSlideMeters:0,phaseDriftTicks:0};for(let t of this.replay.ticks){let n=t.snapshot.payload.events.find(e=>[`hit`,`counter_hit`,`block`].includes(e.kind)),r=t.snapshot.payload.fighters[0].action_hand;if(n===void 0||r===null)continue;let i=Math.min(t.tick+1,this.replay.ticks.length-1);this.seek(i,!1),this.renderCurrentTick(!1);let a=this.jointWorld(0,r===`left`?`gloveL`:`gloveR`),o=this.jointWorld(1,`head`),s=this.jointWorld(1,`chest`);a!==null&&o!==null&&s!==null&&e.contactAlignment.push({tick:t.tick,kind:n.kind,gloveToHeadMeters:Number(Math.max(0,a.distanceTo(o)-Cb.head.radius).toFixed(4)),gloveToTorsoMeters:Number(Math.max(0,a.distanceTo(s)-Cb.torso.radius).toFixed(4))})}this.seek(0,!1);let t=null,n=null;for(let r of this.replay.ticks){this.seek(r.tick,!1),this.renderCurrentTick(!1);let i=this.renderer.labRigs[0].position.x;n!==null&&(e.maxRootStepMeters=Math.max(e.maxRootStepMeters,Math.abs(i-n))),n=i;let a=r.snapshot.payload.fighters[0],o=Math.hypot(a.velocity_x,a.velocity_y),s=this.replay.ticks.slice(Math.max(0,r.tick-30),r.tick+1).some(e=>e.snapshot.payload.fighters[0].is_downed);if(o===0&&!a.is_downed&&!s&&r.snapshot.payload.phase===`fight`){let n=[this.jointWorld(0,`ankleL`),this.jointWorld(0,`ankleR`)].filter(e=>e!==null);t!==null&&n.length===2&&(e.footSlideMeters=Math.max(e.footSlideMeters,Number(Math.max(n[0].distanceTo(t[0]),n[1].distanceTo(t[1])).toFixed(4)))),t=n}else t=null}this.metricsEl.textContent=` contacts: ${e.contactAlignment.map(e=>`${e.kind}@t${e.tick} glove-head ${e.gloveToHeadMeters}m`).join(` · `)} · max root step ${e.maxRootStepMeters.toFixed(3)}m · foot slide ${e.footSlideMeters}m`,window.__labDebug={roots:this.renderer.labRigs.map(e=>e.position.toArray().map(e=>Number(e.toFixed(3)))),graphsActive:this.renderer.graphs!==null,heads:this.renderer.labRigs.map(e=>{let t=e.getObjectByName(rC.head??`head`);return t===void 0?null:t.getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3)))})};let r=new Blob([JSON.stringify(e,null,1)],{type:`application/json`}),i=document.createElement(`a`);i.href=URL.createObjectURL(r),i.download=`hands-lab-metrics.json`,i.click(),URL.revokeObjectURL(i.href)}setStatus(e){this.statusEl.textContent!==e&&(this.statusEl.textContent=e)}destroy(){this.destroyed||(this.destroyed=!0,cancelAnimationFrame(this.raf),this.renderer?.destroy(),this.root.replaceChildren())}};function bD(e){let t=new yD(e);return t.start().catch(t=>{e.querySelector(`[data-lab-status]`).textContent=`lab failed: ${String(t)}`}),()=>t.destroy()}var xD=()=>({player_id:`lab`,x:0,y:0,facing:1,facing_x:0,facing_y:-1e3,velocity_x:0,velocity_y:0,stance:`orthodox`,defense:`none`,stamina:1e3,maximum_stamina:1e3,conditioning:1e3,guard:700,poise:600,trauma:{head:0,body:0,left_eye:0,right_eye:0,left_cut:0,right_cut:0,swelling:0,bleeding:0},knockdowns:0,warnings:0,deductions:0,stunned_ticks:0,is_downed:!1,action:null,action_hand:null,action_target:null,action_power:null,action_id:null,action_key:null,action_start_tick:0,action_startup_ticks:0,action_active_ticks:0,action_recovery_ticks:0,action_contact_tick:null,queued_actions:0,clinch_startup_ticks:0,clinch_ticks:0,is_foul_recovery_target:!1,taunt_ticks:0,get_up_prompt:null,get_up_meter:0,get_up_required:0,get_up_count:0,get_up_window_start_tick:0,get_up_window_end_tick:0,last_input_sequence:-1}),SD={face:[.25,1.55,1],front:[0,1.35,3.4],side:[3.4,1.3,.2],"three-quarter":[2.4,1.5,2.6],top:[.01,4.5,.6],back:[.2,1.4,-3.4],low:[1.8,.5,2.6]},CD=class{root;renderer;scene=new Hd;camera;graph=null;boxer=null;trails=[];trailGlove=new Z;skeletonHelper=null;raf=0;previous=performance.now();elapsed=0;params=new URLSearchParams(window.location.search);reactionFired=!1;statusEl;constructor(e){this.root=e,e.innerHTML=`
-
HANDS MODEL LABloading…
- -
`,this.inventoryEl=e.querySelector(`[data-inventory]`),this.clipsEl=e.querySelector(`[data-clips]`),this.warningsEl=e.querySelector(`[data-warnings]`),this.timeSlider=e.querySelector(`[data-seek]`);let t=e.querySelector(`[data-canvas]`);this.renderer=new Sy({canvas:t,antialias:!0}),this.renderer.setPixelRatio(Math.min(2,window.devicePixelRatio||1)),this.renderer.shadowMap.enabled=!0,this.renderer.toneMapping=4,this.camera=new yh(38,1,.1,60),this.camera.position.set(.4,1.5,3.6),this.camera.lookAt(0,1,0),this.setupGameLighting(),this.bindControls()}setupGameLighting(){this.scene.background=new Z(`#04060b`),new URLSearchParams(window.location.search).get(`fog`)===`1`&&(this.scene.fog=new rd(`#04060b`,.042)),this.scene.add(new sh(`#5a6a95`,`#0c0e16`,1.2)),this.scene.add(new Dh(`#3a4468`,1.05));let e=new xh(`#fff4e0`,115,26,.68,.6,1.6);e.position.set(0,7.4,.9),e.castShadow=!0,e.target.position.set(0,0,0),this.scene.add(e,e.target);for(let[e,t,n,r]of[[`#b9cdff`,-6.5,4.4,-5.2],[`#ffd9b9`,6.2,4.1,-5.6],[`#9fb8ff`,-5.4,3.6,6],[`#c9d8ff`,5.8,3.9,5.7]]){let i=new xh(e,105,30,.7,.8,1.8);i.position.set(t,n,r),i.target.position.set(0,1,0),this.scene.add(i,i.target)}let t=new Eh(`#dfe9ff`,.7);t.position.set(0,3.4,-6.5),this.scene.add(t);let n=new Q(new Np(4,32),new Em({color:`#2c4386`,roughness:.9}));n.rotation.x=-Math.PI/2,n.receiveShadow=!0,this.scene.add(n)}async start(){let e=this.root.querySelector(`[data-status]`);try{let t=await VS();this.model=Dx(t.scene),this.model.scale.setScalar(MS),this.labMaterials=US(this.model,{skin:11105359,gear:1920728}).owned,this.scene.add(this.model),this.model.traverse(e=>{e instanceof If&&(e.castShadow=!0,e.frustumCulled=!1)}),this.mixer=new Qh(this.model);let n=[];for(let e of t.animations){let t=this.mixer.clipAction(e);this.actions.set(e.name,t),n.push({name:e.name,duration:e.duration.toFixed(3),tracks:e.tracks.length}),(e.name===``||e.name.startsWith(`unnamed`))&&this.warnings.push(`unnamed clip at index ${n.length-1}`)}this.buildClipList(n),this.buildInventory();let r=new URLSearchParams(window.location.search).get(`clip`);this.playClip(r!==null&&this.actions.has(r)?r:`idle`),this.skeletonHelper=new ng(this.model),this.skeletonHelper.visible=!1,this.scene.add(this.skeletonHelper),e.textContent=`ready`}catch(t){throw e.textContent=`load failed: ${String(t).slice(0,120)}`,this.warnings.push(String(t)),this.warningsEl.textContent=this.warnings.join(` -`),t}let t=e=>{let n=Math.min(.05,(e-this.previous)/1e3);this.previous=e,this.mixer!==null&&this.playing&&this.mixer.update(n),this.current!==null&&this.playing,this.syncSeek(),this.renderer.render(this.scene,this.camera),this.raf=requestAnimationFrame(t)};this.raf=requestAnimationFrame(t)}buildClipList(e){let t=document.createElement(`div`);t.className=`model-clip-list`;for(let n of e){let e=document.createElement(`button`);e.type=`button`,e.textContent=`${n.name} (${n.duration}s, ${n.tracks} tracks)`,e.dataset.clip=n.name,e.addEventListener(`click`,()=>this.playClip(n.name)),t.append(e)}this.clipsEl.replaceChildren(t)}buildInventory(){if(this.model===null)return;this.model.updateMatrixWorld(!0);let e=[],t=0,n=new Set,r=new Set;this.model.traverse(e=>{if(e instanceof If||e instanceof Q){let i=e.geometry,a=i.getIndex();t+=(a===null?i.getAttribute(`position`).count:a.count)/3;for(let t of Array.isArray(e.material)?e.material:[e.material]){n.add(t);let e=t;e.map!==null&&e.map!==void 0&&r.add(e.map)}}}),e.push(`triangles: ${Math.round(t)}`),e.push(`materials: ${n.size}`),e.push(`textures: ${r.size}`);for(let t of r){let n=t.image;e.push(`texture: ~${n?.width??`?`}×${n?.height??`?`}`)}e.push(``),e.push(`bone hierarchy:`);let i=[];this.model.traverse(e=>{e instanceof Lf&&i.push(e)});let a=i.filter(e=>!(e.parent instanceof Lf)),o=(t,n)=>{e.push(`${` `.repeat(n)}${t.name||`(unnamed)`}`),t.name===``&&this.warnings.push(`unnamed bone found`);for(let e of t.children)e instanceof Lf&&o(e,n+1)};for(let e of a)o(e,0);e.push(``),e.push(`adapter mapping:`);for(let[t,n]of Object.entries(AS))e.push(` ${t} → ${n}`);this.inventoryEl.textContent=e.join(` -`);let s=Object.values(AS).filter(e=>this.model.getObjectByName(e)===void 0);for(let e of s)this.warnings.push(`missing mapped bone: ${e}`);this.warnings.length>0&&(this.warningsEl.textContent=this.warnings.join(` -`))}playClip(e){let t=this.actions.get(e);if(t===void 0||this.mixer===null)return;let n=this.current;t.reset(),t.setLoop(this.loop?Kc:Gc,1/0),t.clampWhenFinished=!0,n!==null&&n!==t&&t.crossFadeFrom(n,.25,!0),t.play(),this.current=t;for(let t of this.clipsEl.querySelectorAll(`button`))t.classList.toggle(`active`,t.dataset.clip===e)}syncSeek(){if(this.current===null)return;let e=this.current.getClip().duration;this.playing?this.timeSlider.value=String(Math.round(this.current.time/e*1e3)):(this.current.time=Number(this.timeSlider.value)/1e3*e,this.mixer?.update(0))}bindControls(){this.root.querySelector(`[data-play]`).addEventListener(`click`,e=>{this.playing=!this.playing,e.target.textContent=this.playing?`Pause`:`Play`}),this.root.querySelector(`[data-loop]`).addEventListener(`change`,e=>{if(this.loop=e.target.checked,this.current!==null){let e=this.current.getClip().name;this.playClip(e)}}),this.root.querySelector(`[data-skeleton]`).addEventListener(`change`,e=>{this.skeletonHelper!==null&&(this.skeletonHelper.visible=e.target.checked)}),this.root.querySelector(`[data-scale]`).addEventListener(`input`,e=>{this.model?.scale.setScalar(Number(e.target.value)/100)}),this.root.querySelector(`[data-rotate]`).addEventListener(`input`,e=>{this.model!==null&&(this.model.rotation.y=Number(e.target.value)*Math.PI/180)}),this.root.querySelector(`[data-offx]`).addEventListener(`input`,e=>{this.model!==null&&(this.model.position.x=Number(e.target.value)/100)}),this.root.querySelector(`[data-offz]`).addEventListener(`input`,e=>{this.model!==null&&(this.model.position.z=Number(e.target.value)/100)})}destroy(){cancelAnimationFrame(this.raf);for(let e of this.labMaterials)e.dispose();this.renderer.dispose(),this.root.replaceChildren()}};function ew(e){let t=new $C(e);return t.start().catch(()=>void 0),()=>t.destroy()}var tw=document.querySelector(`#app`);if(tw===null)throw Error(`app_root_missing`);var nw,rw=new URLSearchParams(window.location.search),iw=window.location.pathname.endsWith(`/hands/lab`)||rw.get(`lab`)===`1`;if(window.location.pathname.endsWith(`/hands/model-lab`)||rw.get(`model-lab`)===`1`)nw=ew(tw);else if(iw)nw=QC(tw);else{let e=new qC(tw);e.start(),nw=()=>e.destroy()}window.addEventListener(`pagehide`,nw,{once:!0}); \ No newline at end of file +
HANDS POSE LABloading…
+`,this.statusEl=e.querySelector(`[data-status]`);let t=e.querySelector(`[data-canvas]`);this.renderer=new ab({canvas:t,antialias:!0,preserveDrawingBuffer:!0}),this.renderer.setPixelRatio(Math.min(2,window.devicePixelRatio||1)),this.renderer.shadowMap.enabled=!0,this.renderer.toneMapping=4,this.camera=new ag(38,1,.1,60);let n=SD[this.params.get(`cam`)??`three-quarter`]??SD[`three-quarter`];this.camera.position.set(...n),this.camera.lookAt(0,this.params.get(`cam`)===`face`?1.5:1,0),this.setupLighting()}setupLighting(){this.scene.background=new Q(`#101318`),this.scene.add(new qh(`#8fa0c8`,`#1a1c22`,1.4));let e=new fg(`#fff1dc`,2.6);e.position.set(2.5,5,3),e.castShadow=!0,e.shadow.mapSize.set(2048,2048),this.scene.add(e);let t=new fg(`#9fb8ff`,1.2);t.position.set(-3,3,-3),this.scene.add(t);let n=new up(new hm(4,48),new sh({color:`#3c4a7a`,roughness:.9}));n.rotation.x=-Math.PI/2,n.receiveShadow=!0,this.scene.add(n);let r=new zg(4,16,8952251,3358810);r.position.y=.002,this.scene.add(r)}synthesize(e){let t=this.params.get(`pose`)??`idle`,n=this.params.get(`stance`)===`southpaw`?`southpaw`:`orthodox`,r={...xD(),stance:n},i=this.params.get(`trauma`);i===`light`&&(r.trauma={head:220,body:260,left_eye:190,right_eye:60,left_cut:40,right_cut:0,swelling:120,bleeding:60}),i===`heavy`&&(r.trauma={head:900,body:700,left_eye:720,right_eye:380,left_cut:520,right_cut:190,swelling:620,bleeding:520}),i===`cut`&&(r.trauma={head:420,body:120,left_eye:380,right_eye:120,left_cut:300,right_cut:0,swelling:260,bleeding:380});let a={...xD(),player_id:`other`,x:0,y:-150,facing_x:0,facing_y:1e3},o=Math.floor(e*30),s=/^(jab|straight|hook|uppercut)_(left|right)(_body)?(_power)?$/.exec(t);if(s!==null){let e=s[1],t=s[2],n=s[3]===`_body`?`body`:`head`,i=s[4]===`_power`?`power`:`normal`,a={jab:[4,2,7],straight:[6,2,10],hook:[7,3,12],uppercut:[8,2,13]}[e],c=a[0]+a[1]+a[2],l=Math.floor(o/(c+12))*(c+12)+6;o>=l&&o{let i=Math.min(.05,(r-this.previous)/1e3);this.previous=r,t===null?(this.elapsed=e===null?this.elapsed+i:Number(e),this.step(e===null?i:1/60)):this.step(0),this.renderer.render(this.scene,this.camera),this.raf=requestAnimationFrame(n)};this.raf=requestAnimationFrame(n)}step(e){let t=this.graph;if(t===null)return;let n=this.renderer.domElement.clientWidth,r=this.renderer.domElement.clientHeight;n>0&&r>0&&(this.renderer.domElement.width!==n||this.renderer.domElement.height!==r)&&(this.renderer.setSize(n,r,!1),this.camera.aspect=n/r,this.camera.updateProjectionMatrix());let{fighter:i,opponent:a,sampledTick:o,head:s}=this.synthesize(this.elapsed),c=this.params.get(`pose`)??``;if(/^(hit|block)_/.test(c)){let n=this.elapsed%1.6;if(this.params.has(`freeze`)?!this.reactionFired&&this.elapsed>=.02:n0);window.__poseLab={head:this.boxer.bone(`head`).getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3))),gloveL:this.boxer.bone(`gloveL`).getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3))),gloveR:this.boxer.bone(`gloveR`).getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3))),ankleL:this.boxer.bone(`ankleL`).getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3))),ankleR:this.boxer.bone(`ankleR`).getWorldPosition(new Z).toArray().map(e=>Number(e.toFixed(3)))}}destroy(){cancelAnimationFrame(this.raf),this.graph?.dispose(),this.renderer.dispose(),this.root.replaceChildren()}};function wD(e){let t=new CD(e);return t.start().catch(()=>void 0),()=>t.destroy()}var TD=document.querySelector(`#app`);if(TD===null)throw Error(`app_root_missing`);var ED,DD=new URLSearchParams(window.location.search),OD=window.location.pathname.endsWith(`/hands/lab`)||DD.get(`lab`)===`1`;if(window.location.pathname.endsWith(`/hands/model-lab`)||DD.get(`model-lab`)===`1`)ED=wD(TD);else if(OD)ED=bD(TD);else{let e=new gD(TD);e.start(),ED=()=>e.destroy()}window.addEventListener(`pagehide`,ED,{once:!0}); \ No newline at end of file diff --git a/src/intelstream/hands/types.py b/src/intelstream/hands/types.py index f96ed2bf..0fbc8f26 100644 --- a/src/intelstream/hands/types.py +++ b/src/intelstream/hands/types.py @@ -138,6 +138,8 @@ class FighterSnapshot: x: int y: int facing: int + facing_x: int + facing_y: int velocity_x: int velocity_y: int stance: Stance @@ -175,6 +177,7 @@ class FighterSnapshot: get_up_count: int get_up_window_start_tick: int get_up_window_end_tick: int + last_input_sequence: int @dataclass(frozen=True, slots=True) diff --git a/tests/test_database.py b/tests/test_database.py index 03f5b5ac..9291e880 100644 --- a/tests/test_database.py +++ b/tests/test_database.py @@ -2222,13 +2222,14 @@ def result( guild_id: str = "guild-a", winner_id: str | None = "user-1", finish_method: FinishMethod = FinishMethod.KO, + player_two_id: str = "user-2", ) -> MatchResult: return MatchResult( match_id=match_id, activity_instance_id="instance-1", guild_id=guild_id, player_one_id="user-1", - player_two_id="user-2", + player_two_id=player_two_id, winner_id=winner_id, finish_method=finish_method, round_number=2, @@ -2321,6 +2322,48 @@ async def test_underdog_win_receives_larger_change(self, repository: Repository) match.player_two_rating_after - match.player_two_rating_before ) + async def test_repeat_pairings_within_a_day_exchange_less_and_less_rating( + self, repository: Repository + ) -> None: + gains = [] + for index in range(8): + match = await repository.record_hands_match(self.result(f"rematch-{index}")) + assert match.player_one_rating_after + match.player_two_rating_after == 2000 + gains.append(match.player_one_rating_after - match.player_one_rating_before) + one = await repository.get_hands_rating("guild-a", "user-1") + + assert gains == [16, 7, 3, 2, 1, 0, 0, 0] + assert one is not None + assert one.rating == 1000 + sum(gains) + assert (one.bouts, one.wins) == (8, 8) + + async def test_a_pairing_counts_in_full_again_once_the_window_has_passed( + self, repository: Repository + ) -> None: + await repository.record_hands_match(self.result("earlier")) + async with repository.session() as session: + earlier = await session.get(HandsMatch, "earlier") + assert earlier is not None + earlier.created_at = datetime.now(UTC) - timedelta(hours=25) + await session.commit() + + later = await repository.record_hands_match(self.result("later")) + + # 1016 against 984 at the full K of 32; a damped K of 16 would give 7. + assert later.player_one_rating_after - later.player_one_rating_before == 15 + + async def test_damping_applies_only_to_the_same_two_fighters( + self, repository: Repository + ) -> None: + await repository.record_hands_match(self.result("versus-two")) + + other = await repository.record_hands_match( + self.result("versus-three", player_two_id="user-3") + ) + + # 1016 against a new 1000 at the full K of 32; a damped K of 16 would give 8. + assert other.player_one_rating_after - other.player_one_rating_before == 15 + async def test_transaction_rolls_back_match_and_both_ratings_on_flush_failure( self, repository: Repository, monkeypatch: pytest.MonkeyPatch ) -> None: diff --git a/tests/test_hands/test_e2e_server.py b/tests/test_hands/test_e2e_server.py new file mode 100644 index 00000000..64a95238 --- /dev/null +++ b/tests/test_hands/test_e2e_server.py @@ -0,0 +1,50 @@ +from __future__ import annotations + +import asyncio + +import pytest +from scripts.hands_e2e_server import parse_args, run + +from intelstream.config import Settings +from intelstream.hands.server import HandsServer + + +def test_the_development_server_stays_off_the_production_port() -> None: + production = Settings.model_fields["hands_port"].default + assert parse_args([]).port != production + assert parse_args(["--port", "8195"]).port == 8195 + + +async def test_the_development_server_runs_and_closes_where_loops_have_no_signal_handlers( + monkeypatch: pytest.MonkeyPatch, +) -> None: + def unsupported(*_args: object) -> None: + raise NotImplementedError + + # Windows event loops raise this for every signal handler. + monkeypatch.setattr(asyncio.get_running_loop(), "add_signal_handler", unsupported) + started = asyncio.Event() + closed = asyncio.Event() + original_start = HandsServer.start + original_close = HandsServer.close + + async def start(server: HandsServer) -> None: + await original_start(server) + started.set() + + async def close(server: HandsServer) -> None: + await original_close(server) + closed.set() + + monkeypatch.setattr(HandsServer, "start", start) + monkeypatch.setattr(HandsServer, "close", close) + running = asyncio.create_task(run(parse_args(["--port", "0"]))) + async with asyncio.timeout(10): + await started.wait() + await asyncio.sleep(0) + assert not running.done() + + running.cancel() + with pytest.raises(asyncio.CancelledError): + await running + assert closed.is_set() diff --git a/tests/test_hands/test_engine.py b/tests/test_hands/test_engine.py index 390dca69..b1559bd8 100644 --- a/tests/test_hands/test_engine.py +++ b/tests/test_hands/test_engine.py @@ -1,9 +1,13 @@ from __future__ import annotations +import json +import math +import re from math import hypot import pytest +from intelstream.hands import rules from intelstream.hands.engine import ( ACTION_BUFFER_TICKS, MAX_PENDING_ACTIONS, @@ -12,8 +16,13 @@ ) from intelstream.hands.protocol import encode_snapshot from intelstream.hands.rules import ( + CLINCH_HOLD_DISTANCE, FIGHTER_RADIUS, + KNOCKDOWN_NEUTRAL_SEPARATION, + MINIMUM_SEPARATION, PUNCH_RULES, + REST_CORNER_OFFSET, + RING_CORNER_REACH, RING_HALF_HEIGHT, RING_HALF_WIDTH, ) @@ -348,6 +357,183 @@ def test_momentum_only_frames_regenerate_at_a_reduced_rate_until_stationary() -> assert fighter.stamina > before_recovery +def test_corner_posts_keep_fighters_out_of_the_corner_pad() -> None: + engine = make_engine(seed=95, round_ticks=2000) + fighter = engine.fighter("one") + limit = RING_HALF_WIDTH - FIGHTER_RADIUS + fighter.x = limit - 4 + fighter.y = limit - 4 + engine.fighter("two").x = -300 + + for sequence in range(1, 30): + engine.step({"one": command(sequence, move_x=1000, move_y=1000)}) + assert abs(fighter.x) + abs(fighter.y) <= RING_CORNER_REACH + + assert fighter.x > 0 and fighter.y > 0 + assert abs(fighter.x) + abs(fighter.y) >= RING_CORNER_REACH - 2 + assert abs(fighter.x - fighter.y) <= 2 + assert REST_CORNER_OFFSET * 2 <= RING_CORNER_REACH + + +@pytest.mark.parametrize( + ("name", "value", "key"), + [ + ("FACING_SCALE", 1024, "facing.scale"), + ("REST_CORNER_OFFSET", RING_CORNER_REACH // 2 + 1, "rest.corner_offset"), + ], +) +def test_manifest_check_refuses_values_the_engine_cannot_honour( + monkeypatch: pytest.MonkeyPatch, name: str, value: int, key: str +) -> None: + rules._manifest_check() + monkeypatch.setattr(rules, name, value) + with pytest.raises(RuntimeError, match=re.escape(key)): + rules._manifest_check() + + +def test_side_ropes_are_still_reachable_away_from_the_corners() -> None: + engine = make_engine(seed=96, round_ticks=2000) + fighter = engine.fighter("one") + fighter.x = RING_HALF_WIDTH - FIGHTER_RADIUS - 3 + fighter.y = 0 + engine.fighter("two").x = -300 + + for sequence in range(1, 6): + engine.step({"one": command(sequence, move_x=1000)}) + + assert fighter.x == RING_HALF_WIDTH - FIGHTER_RADIUS + + +def in_ring(fighter: object) -> bool: + x, y = fighter.x, fighter.y # type: ignore[attr-defined] + return ( + abs(x) <= RING_HALF_WIDTH - FIGHTER_RADIUS + and abs(y) <= RING_HALF_HEIGHT - FIGHTER_RADIUS + and abs(x) + abs(y) <= RING_CORNER_REACH + ) + + +@pytest.mark.parametrize( + ("start", "move_one", "move_two"), + [ + ((341, 215, 315, 334), (1000, 500), (1000, 200)), + ((286, -229, 413, -209), (1000, -500), (1000, -500)), + ((272, 304, 194, 326), (0, 1000), (707, 707)), + ((-351, -314, -206, -413), (-1000, 0), (-1000, 0)), + ], +) +def test_fighters_pressing_into_a_corner_come_to_rest( + start: tuple[int, int, int, int], move_one: tuple[int, int], move_two: tuple[int, int] +) -> None: + engine = make_engine(seed=97, round_ticks=5000) + one, two = engine.fighter("one"), engine.fighter("two") + one.x, one.y, two.x, two.y = start + + steps = [] + for sequence in range(1, 261): + before = (one.x, one.y, two.x, two.y) + engine.step( + { + "one": command(sequence, move_x=move_one[0], move_y=move_one[1]), + "two": command(sequence, move_x=move_two[0], move_y=move_two[1]), + } + ) + assert in_ring(one) and in_ring(two) + assert (one.x - two.x) ** 2 + (one.y - two.y) ** 2 >= MINIMUM_SEPARATION**2 + after = (one.x, one.y, two.x, two.y) + steps.append(max(abs(a - b) for a, b in zip(after, before, strict=True))) + + assert max(steps[-60:]) <= 3 + + +def test_fighters_meeting_at_an_angle_are_not_thrown_apart() -> None: + engine = make_engine(seed=98, round_ticks=5000) + one, two = engine.fighter("one"), engine.fighter("two") + one.x, one.y, two.x, two.y = -60, -50, 60, 50 + + largest = 0 + closest = hypot(two.x - one.x, two.y - one.y) + for sequence in range(1, 61): + before = (one.x, one.y, two.x, two.y) + engine.step( + { + "one": command(sequence, move_x=707, move_y=600), + "two": command(sequence, move_x=-707, move_y=-600), + } + ) + after = (one.x, one.y, two.x, two.y) + largest = max(largest, *(abs(a - b) for a, b in zip(after, before, strict=True))) + closest = min(closest, hypot(two.x - one.x, two.y - one.y)) + + assert MINIMUM_SEPARATION <= closest <= MINIMUM_SEPARATION + 2 + assert largest <= 8 + + +def test_sliding_along_a_corner_pad_keeps_its_speed_and_is_the_same_both_ways() -> None: + limit = RING_HALF_WIDTH - FIGHTER_RADIUS + low = RING_CORNER_REACH - limit + + def slide(start: tuple[int, int], move: tuple[int, int]) -> list[tuple[int, int, int, int]]: + engine = make_engine(seed=99, round_ticks=5000) + fighter = engine.fighter("one") + fighter.x, fighter.y = start + engine.fighter("two").x = -300 + trail = [] + for sequence in range(1, 21): + engine.step({"one": command(sequence, move_x=move[0], move_y=move[1])}) + trail.append((fighter.x, fighter.y, fighter.velocity_x, fighter.velocity_y)) + return trail + + up = slide((limit, low), (0, 1000)) + right = slide((low, limit), (1000, 0)) + assert [(y, x, vy, vx) for x, y, vx, vy in up] == right + assert all(x + y == RING_CORNER_REACH for x, y, _, _ in up) + assert up[-1][0] < up[0][0] and up[-1][1] > up[0][1] + assert up[-1][2] < 0 < up[-1][3] + + wedged = slide((low, limit), (259, 966)) + assert {(x, y) for x, y, _, _ in wedged} == {(low, limit)} + + +@pytest.mark.parametrize( + ("winner_at", "downed_at"), + [((367, 366), (300, 300)), ((333, 400), (265, 328)), ((-440, -293), (-370, -230))], +) +def test_cornered_winner_still_reaches_neutral_distance( + winner_at: tuple[int, int], downed_at: tuple[int, int] +) -> None: + engine = make_engine(seed=100, round_ticks=5000) + winner, downed = engine.fighter("one"), engine.fighter("two") + winner.x, winner.y = winner_at + downed.x, downed.y = downed_at + engine.step() + engine._knock_down(downed, winner) + assert engine.phase is MatchPhase.KNOCKDOWN + + for _ in range(150): + engine.step() + assert in_ring(winner) + assert hypot(winner.x - downed.x, winner.y - downed.y) >= MINIMUM_SEPARATION - 8 + if engine.phase is not MatchPhase.KNOCKDOWN: + break + + assert hypot(winner.x - downed.x, winner.y - downed.y) >= KNOCKDOWN_NEUTRAL_SEPARATION + assert (winner.velocity_x, winner.velocity_y) == (0, 0) + + +def test_clinch_holds_close_whatever_the_angle() -> None: + engine = make_engine(round_ticks=2000) + engine.fighter("one").x, engine.fighter("one").y = -30, -36 + engine.fighter("two").x, engine.fighter("two").y = 35, 30 + engine.step({"one": command(1, action=MovementAction(ActionKind.CLINCH))}) + assert advance_until(engine, {"clinch"}, limit=12) == "clinch" + + while engine.fighter("one").clinch_ticks > 1: + engine.step() + one, two = engine.fighter("one"), engine.fighter("two") + assert CLINCH_HOLD_DISTANCE <= hypot(two.x - one.x, two.y - one.y) <= CLINCH_HOLD_DISTANCE + 4 + + def test_ring_clamp_resets_fixed_point_momentum_and_position_remainder() -> None: engine = make_engine(seed=94, round_ticks=2000) fighter = engine.fighter("one") @@ -523,6 +709,56 @@ def test_clinch_has_range_cost_hold_and_referee_break() -> None: assert advance_until(engine, {"referee_break"}, limit=60) == "referee_break" +def test_clinch_draws_the_fighters_to_the_hold_distance_before_the_break() -> None: + engine = make_engine(round_ticks=2000) + engine.fighter("one").x = -50 + engine.fighter("two").x = 50 + engine.step({"one": command(1, action=MovementAction(ActionKind.CLINCH))}) + assert advance_until(engine, {"clinch"}, limit=12) == "clinch" + + distances = [] + while engine.fighter("one").clinch_ticks > 1: + engine.step() + one, two = engine.fighter("one"), engine.fighter("two") + distances.append(abs(two.x - one.x)) + assert distances[0] < 100 + assert min(distances) == CLINCH_HOLD_DISTANCE + assert distances[-1] == CLINCH_HOLD_DISTANCE + assert engine.fighter("one").x == -engine.fighter("two").x + + assert advance_until(engine, {"referee_break"}, limit=3) == "referee_break" + gap = abs(engine.fighter("two").x - engine.fighter("one").x) + assert gap >= MINIMUM_SEPARATION + + +def test_a_clinch_stops_both_fighters_for_the_whole_hold() -> None: + engine = make_engine(round_ticks=2000) + one = engine.fighter("one") + two = engine.fighter("two") + one.x, two.x = 0, 100 + # Two walks in at full speed and keeps holding forward through the tie-up. + engine.step( + { + "one": command(1, action=MovementAction(ActionKind.CLINCH)), + "two": command(1, move_x=-1000), + } + ) + assert advance_until(engine, {"clinch"}, limit=12) == "clinch" + for fighter in (one, two): + assert (fighter.velocity_x, fighter.velocity_y) == (0, 0) + assert (fighter.velocity_fixed_x, fighter.velocity_fixed_y) == (0, 0) + assert (fighter.position_remainder_x, fighter.position_remainder_y) == (0, 0) + + control = two.performance.control + while two.clinch_ticks: + snapshot = engine.step() + assert {(fighter.velocity_x, fighter.velocity_y) for fighter in snapshot.fighters} == { + (0, 0) + } + # Farther from the centre than the man he is tied to, so only pressure could score. + assert two.performance.control == control + + def test_out_of_range_clinch_is_denied_and_still_costs_stamina() -> None: engine = make_engine(round_ticks=2000) engine.fighter("one").x = -300 @@ -581,6 +817,42 @@ def test_exchange_stamina_recovers_but_long_term_fatigue_persists_after_rest() - assert one.stamina >= spent +def test_rest_walks_both_fighters_to_their_corners_and_seats_them_facing_the_ring() -> None: + engine = make_engine(round_ticks=30, rounds=2, rest_ticks=240) + one = engine.fighter("one") + two = engine.fighter("two") + for _ in range(28): + engine.step() + engine.step({"one": command(1, action=punch(PunchClass.UPPERCUT, power=Power.POWER))}) + assert engine.phase is MatchPhase.FIGHT + assert one.attack is not None or one.pending_actions + engine.step({"two": command(1, defense=DefensivePose.GUARD_HIGH)}) + assert engine.phase is MatchPhase.REST + assert one.attack is None and not one.pending_actions + assert two.defense is DefensivePose.NONE + + engine.step() + assert one.velocity_x < 0 and one.velocity_y < 0 + assert two.velocity_x > 0 and two.velocity_y > 0 + ticks = 0 + while (one.x, one.y) != (-REST_CORNER_OFFSET, -REST_CORNER_OFFSET): + engine.step({"one": command(2 + ticks, move_x=1000, move_y=1000)}) + ticks += 1 + assert ticks < 200 + assert (two.x, two.y) == (REST_CORNER_OFFSET, REST_CORNER_OFFSET) + assert (one.velocity_x, one.velocity_y) == (0, 0) + assert (two.velocity_x, two.velocity_y) == (0, 0) + for step in range(12): + engine.step({"one": command(300 + step, move_x=1000, move_y=1000)}) + assert (one.x, one.y) == (-REST_CORNER_OFFSET, -REST_CORNER_OFFSET) + assert one.facing_x > 0 and one.facing_y > 0 + assert two.facing_x < 0 and two.facing_y < 0 + while engine.phase is MatchPhase.REST: + engine.step() + assert engine.phase is MatchPhase.FIGHT + assert (one.x, one.y) == (-REST_CORNER_OFFSET, -REST_CORNER_OFFSET) + + def test_fatigue_reduces_hand_speed_foot_speed_guard_recovery_and_power() -> None: fresh = make_engine(round_ticks=2000) tired = make_engine(round_ticks=2000) @@ -830,6 +1102,7 @@ def test_collision_and_referee_separation_stay_inside_rope_center_bounds() -> No for fighter in (one, two): assert -maximum_x <= fighter.x <= maximum_x assert -maximum_y <= fighter.y <= maximum_y + assert abs(fighter.x) + abs(fighter.y) <= RING_CORNER_REACH assert (one.x - two.x) ** 2 + (one.y - two.y) ** 2 >= 76**2 one.x = maximum_x - 40 @@ -910,14 +1183,8 @@ def test_held_guard_heartbeat_preserves_a_new_guarded_follow_up() -> None: def test_action_buffer_expires_instead_of_forcing_old_directives() -> None: engine = make_engine(round_ticks=2000) - engine.step( - { - "one": command( - 1, - action=punch(PunchClass.UPPERCUT, power=Power.POWER), - ) - } - ) + engine.step({"one": command(1, action=MovementAction(ActionKind.TAUNT))}) + assert engine.fighter("one").taunt_ticks > 0 assert ( engine.submit_input( "one", @@ -931,7 +1198,126 @@ def test_action_buffer_expires_instead_of_forcing_old_directives() -> None: engine.step() assert engine.fighter("one").pending_actions == [] - assert [event.kind for event in engine.events].count("punch_start") == 1 + assert [event.kind for event in engine.events].count("punch_start") == 0 + + +def test_buffered_punch_survives_the_current_attack_and_dispatches_after_it() -> None: + engine = make_engine(round_ticks=2000) + engine.fighter("one").x = -300 + engine.fighter("two").x = 300 + engine.step({"one": command(1, action=punch(PunchClass.UPPERCUT, power=Power.POWER))}) + attack = engine.fighter("one").attack + assert attack is not None + total = attack.total_ticks + assert total > ACTION_BUFFER_TICKS + 1 + engine.step() + assert engine.submit_input("one", command(2, action=punch(PunchClass.JAB))) + + starts: list[int] = [] + for _ in range(total + 4): + snapshot = engine.step() + starts.extend(event.tick for event in snapshot.events if event.kind == "punch_start") + if not starts: + assert engine.fighter("one").pending_actions, "buffer dropped during the attack" + + assert len(starts) == 1 + assert starts[0] == 1 + total + 1 + assert engine.fighter("one").pending_actions == [] + + +def test_landed_punch_recovery_cancels_into_a_compatible_follow_up() -> None: + def follow_up_start( + first: PunchAction, second: PunchAction, *, in_range: bool, stunned: bool = False + ) -> tuple[int, int, int]: + engine = make_engine(round_ticks=2000) + if not in_range: + engine.fighter("one").x = -300 + engine.fighter("two").x = 300 + if stunned: + engine.fighter("two").stunned_ticks = 90 + engine.step({"one": command(1, action=first)}) + attack = engine.fighter("one").attack + assert attack is not None + cancel_age = attack.cancel_age + total = attack.total_ticks + assert 0 < cancel_age < total + engine.step({"one": command(2, action=second)}) + for _ in range(total + 4): + snapshot = engine.step() + for event in snapshot.events: + if event.kind == "punch_start" and event.detail.split(":")[1] == second.punch_class: + return event.tick - 1, cancel_age, total + raise AssertionError("follow-up never started") + + jab = punch(PunchClass.JAB, hand=Hand.LEFT) + straight = punch(PunchClass.STRAIGHT) + uppercut = punch(PunchClass.UPPERCUT) + + started, cancel_age, total = follow_up_start(jab, straight, in_range=True) + assert started == cancel_age < total + whiffed, _cancel_age, total = follow_up_start(jab, straight, in_range=False) + assert whiffed == total + 1 + incompatible, _cancel_age, total = follow_up_start(jab, uppercut, in_range=True) + assert incompatible == total + 1 + into_a_stun, _cancel_age, total = follow_up_start(jab, straight, in_range=True, stunned=True) + assert into_a_stun == total + 1 + + +def test_facing_vector_turns_toward_the_opponent_and_the_hit_test_follows() -> None: + engine = make_engine(round_ticks=2000) + one = engine.fighter("one") + two = engine.fighter("two") + one.x = one.y = 0 + two.x = 0 + two.y = 100 + assert (one.facing_x, one.facing_y) == (1000, 0) + for _ in range(12): + engine.step() + assert one.facing_y > 950 + assert abs(one.facing_x) < 200 + assert 990_000 <= one.facing_x**2 + one.facing_y**2 <= 1_010_000 + assert two.facing_y < -950 + + engine.step({"one": command(1, action=punch(PunchClass.STRAIGHT))}) + assert advance_until(engine, {"hit", "counter_hit"}) in {"hit", "counter_hit"} + + snapshot = engine.snapshot() + payload = json.loads(encode_snapshot(snapshot, viewer_id="one"))["payload"] + assert payload["fighters"][0]["facing_y"] == one.facing_y + assert payload["fighters"][0]["last_input_sequence"] == 1 + assert payload["fighters"][1]["last_input_sequence"] == -1 + + +def test_knockdown_walks_the_standing_fighter_to_neutral_distance_without_teleport() -> None: + engine = make_engine(round_ticks=2000) + defender = engine.fighter("two") + attacker = engine.fighter("one") + defender.poise = 1 + engine.step({"one": command(1, action=punch(PunchClass.UPPERCUT, power=Power.POWER))}) + advance_until(engine, {"knockdown"}) + downed_at = (defender.x, defender.y) + for _ in range(40): + engine.step() + assert (defender.x, defender.y) == downed_at + assert hypot(attacker.x - defender.x, attacker.y - defender.y) >= 230 + assert attacker.velocity_x == 0 and attacker.velocity_y == 0 + + sequence = 2 + used_window = -1 + while engine.phase is MatchPhase.KNOCKDOWN and engine.tick < 300: + fighter = next(item for item in engine.snapshot().fighters if item.player_id == "two") + if ( + fighter.get_up_prompt is not None + and engine.tick >= fighter.get_up_window_start_tick + and fighter.get_up_window_end_tick != used_window + ): + engine.step({"two": command(sequence, action=MovementAction(fighter.get_up_prompt))}) + used_window = fighter.get_up_window_end_tick + sequence += 1 + else: + engine.step() + assert engine.phase is MatchPhase.FIGHT + assert (defender.x, defender.y) == downed_at def test_short_buffered_combo_only_rewards_authored_compatible_chain() -> None: @@ -1163,30 +1549,30 @@ def test_counter_vulnerability_slip_sides_and_body_weave_are_skill_based() -> No ) assert advance_until(wrong, {"hit", "counter_hit"}) in {"hit", "counter_hit"} - body = make_engine(round_ticks=2000) - body.fighter("one").y = -20 - body.fighter("two").y = 20 - body.step( - { - "one": command(1, action=punch(PunchClass.HOOK, target=Target.BODY)), - "two": command(1, action=MovementAction(ActionKind.WEAVE)), - } - ) - assert advance_until(body, {"evade"}) == "evade" + def body_shot(punch_class: PunchClass, pose: ActionKind, *, steps_off_the_line: int) -> str: + engine = make_engine(round_ticks=2000) + one = engine.fighter("one") + two = engine.fighter("two") + one.x, one.y, two.x, two.y = -32, -24, 32, 24 + for _ in range(20): + engine.step() + # Settled: the attacker has turned square onto the defender, along (4, 3). + assert abs(math.degrees(math.atan2(one.facing_y, one.facing_x)) - 36.87) < 1 + shot = command(1, action=punch(punch_class, hand=Hand.RIGHT, target=Target.BODY)) + evasion = command(2, action=MovementAction(pose)) + # Square to the line, the defender steps off it once the punch has started. + step_aside = command(1, move_x=-600, move_y=800) + engine.step({"one": shot, "two": step_aside if steps_off_the_line else evasion}) + if steps_off_the_line: + for _ in range(steps_off_the_line - 1): + engine.step() + engine.step({"two": evasion}) + return advance_until(engine, {"hit", "counter_hit", "evade", "whiff"}) - body_uppercut = make_engine(round_ticks=2000) - body_uppercut.fighter("one").y = -10 - body_uppercut.fighter("two").y = 10 - body_uppercut.step( - { - "one": command( - 1, - action=punch(PunchClass.UPPERCUT, hand=Hand.RIGHT, target=Target.BODY), - ), - "two": command(1, action=MovementAction(ActionKind.SLIP_LEFT)), - } - ) - assert advance_until(body_uppercut, {"evade"}) == "evade" + assert body_shot(PunchClass.HOOK, ActionKind.WEAVE, steps_off_the_line=0) == "hit" + assert body_shot(PunchClass.HOOK, ActionKind.WEAVE, steps_off_the_line=3) == "evade" + assert body_shot(PunchClass.UPPERCUT, ActionKind.SLIP_LEFT, steps_off_the_line=0) == "hit" + assert body_shot(PunchClass.UPPERCUT, ActionKind.SLIP_LEFT, steps_off_the_line=3) == "evade" def test_forward_cone_rejects_beside_and_opponent_who_circles_behind() -> None: @@ -1608,3 +1994,159 @@ def test_identical_class_actions_get_distinct_fallback_ids() -> None: second = engine.snapshot().fighters[0].action_id assert first is not None and second is not None assert first != second + + +def test_recovery_is_only_cut_short_for_a_follow_up_the_fighter_can_afford() -> None: + engine = make_engine(round_ticks=2000) + one = engine.fighter("one") + jab = punch(PunchClass.JAB, hand=Hand.LEFT) + straight = punch(PunchClass.STRAIGHT) + straight_cost = PUNCH_RULES[(PunchClass.STRAIGHT, Target.HEAD, Power.NORMAL)].stamina_cost + jab_cost = PUNCH_RULES[(PunchClass.JAB, Target.HEAD, Power.NORMAL)].stamina_cost + one.stamina = jab_cost + straight_cost - 25 + engine.step({"one": command(1, action=jab)}) + attack = one.attack + assert attack is not None + engine.step({"one": command(2, action=straight)}) + kinds: set[str] = set() + while engine.tick <= attack.start_tick + attack.cancel_age: + kinds.update(event.kind for event in engine.step().events) + assert "hit" in kinds + assert one.stamina < straight_cost + assert one.attack is attack + + +def test_a_parried_punch_cannot_be_cut_short_into_a_combo_but_a_blocked_one_can() -> None: + def cut_short(*, parried: bool) -> tuple[bool, set[str]]: + engine = make_engine(round_ticks=2000) + one = engine.fighter("one") + jab = punch(PunchClass.JAB, hand=Hand.LEFT) + if not parried: + engine.step({"two": command(1, defense=DefensivePose.GUARD_HIGH)}) + for _ in range(10): + engine.step() + engine.step( + { + "one": command(1, action=jab), + "two": command(2, defense=DefensivePose.GUARD_HIGH), + } + ) + attack = one.attack + assert attack is not None + engine.step({"one": command(2, action=punch(PunchClass.STRAIGHT))}) + kinds: set[str] = set() + while engine.tick <= attack.start_tick + attack.cancel_age: + kinds.update(event.kind for event in engine.step().events) + return one.attack is not attack, kinds + + parried, parried_events = cut_short(parried=True) + assert "perfect_block" in parried_events + assert not parried + blocked, blocked_events = cut_short(parried=False) + assert "block" in blocked_events and "perfect_block" not in blocked_events + assert blocked + + +@pytest.mark.parametrize("mashes_weave", [False, True]) +def test_an_early_buffered_hook_uppercut_chain_cannot_hold_a_stunned_fighter( + mashes_weave: bool, +) -> None: + engine = make_engine(round_ticks=2000) + one = engine.fighter("one") + two = engine.fighter("two") + follow_ups = { + PunchClass.STRAIGHT: punch(PunchClass.HOOK, hand=Hand.LEFT), + PunchClass.HOOK: punch(PunchClass.UPPERCUT), + PunchClass.UPPERCUT: punch(PunchClass.HOOK, hand=Hand.LEFT), + } + engine.step({"one": command(1, action=punch(PunchClass.STRAIGHT))}) + pressed_during = None + sequence = 1 + stunned = False + free_ticks = 0 + while engine.phase is MatchPhase.FIGHT and engine.tick < 300: + inputs = {} + attack = one.attack + if attack is not None and attack is not pressed_during: + # One press early in every punch: the buffer keeps it until the punch gives way. + sequence += 1 + inputs["one"] = command(sequence, action=follow_ups[attack.action.punch_class]) + pressed_during = attack + if mashes_weave: + inputs["two"] = command(engine.tick, action=MovementAction(ActionKind.WEAVE)) + running_stun = two.stunned_ticks + before = one.attack + engine.step(inputs) + cut_short = before is not None and one.attack is not None and one.attack is not before + if running_stun > 1: + assert two.stunned_ticks < running_stun, "a punch started a running stun again" + assert not cut_short, "a punch was cut short into a stunned fighter" + stunned = stunned or two.stunned_ticks > 0 + if stunned and engine.phase is MatchPhase.FIGHT and two.stunned_ticks == 0: + free_ticks += 1 + + assert stunned + assert free_ticks > 0 + + +def test_fighters_walking_to_their_corners_go_round_each_other() -> None: + engine = make_engine(round_ticks=3, rounds=2, rest_ticks=300) + one = engine.fighter("one") + two = engine.fighter("two") + one.x, one.y = 60, 60 + two.x, two.y = -60, -60 + while engine.phase is not MatchPhase.REST: + engine.step() + closest = hypot(one.x - two.x, one.y - two.y) + while engine.phase is MatchPhase.REST: + engine.step() + closest = min(closest, hypot(one.x - two.x, one.y - two.y)) + assert closest >= MINIMUM_SEPARATION - 3 + assert (one.x, one.y) == (-REST_CORNER_OFFSET, -REST_CORNER_OFFSET) + assert (two.x, two.y) == (REST_CORNER_OFFSET, REST_CORNER_OFFSET) + + +@pytest.mark.parametrize("rest_ticks", [5, 0]) +def test_the_bell_clears_evasion_counter_and_combo_windows(rest_ticks: int) -> None: + engine = make_engine(round_ticks=20, rounds=2, rest_ticks=rest_ticks) + one = engine.fighter("one") + while engine.tick < 18: + engine.step() + engine.step({"one": command(1, action=MovementAction(ActionKind.SLIP_LEFT))}) + assert one.evasion_ticks > 0 + one.counter_ticks = 17 + one.combo_ticks = 12 + while engine.round_number == 1: + engine.step() + assert (one.evasion_ticks, one.counter_ticks, one.combo_ticks) == (0, 0, 0) + + +@pytest.mark.parametrize("rest_ticks", [150, 0]) +def test_a_walk_and_guard_held_at_the_bell_do_not_carry_into_the_next_round( + rest_ticks: int, +) -> None: + engine = make_engine(round_ticks=30, rounds=2, rest_ticks=rest_ticks) + one = engine.fighter("one") + engine.fighter("two").x = 300 + # Walking in behind a high guard at the bell, then no more frames: clients stop sending + # between rounds. + engine.step({"one": command(1, move_x=1000, defense=DefensivePose.GUARD_HIGH)}) + while engine.round_number == 1: + engine.step() + snapshots = [engine.step() for _ in range(7)] + + assert [snapshot.fighters[0].defense for snapshot in snapshots] == [DefensivePose.NONE] * 7 + assert (one.velocity_x, one.velocity_y) == (0, 0) + + +def test_the_facing_blends_toward_the_opponent_before_and_after_footwork_each_fight_tick() -> None: + engine = make_engine(round_ticks=2000) + one = engine.fighter("one") + two = engine.fighter("two") + one.x = one.y = 0 + two.x, two.y = 0, 300 + engine.step() + turned = math.degrees(math.atan2(one.facing_y, one.facing_x)) + single_blend = math.degrees(math.atan2(350, 650)) + assert turned > single_blend + 15 + assert 46 < turned < 52 diff --git a/tests/test_hands/test_integration.py b/tests/test_hands/test_integration.py index a0877eb9..724cb733 100644 --- a/tests/test_hands/test_integration.py +++ b/tests/test_hands/test_integration.py @@ -161,7 +161,7 @@ async def test_real_auth_spectator_reconnect_and_authoritative_elo(tmp_path) -> two = await client.ws_connect(f"{base}/api/hands/ws", headers=headers) await one.send_json( { - "version": 2, + "version": 3, "type": "authenticate", "ticket": credentials["one"]["ticket"], } @@ -169,7 +169,7 @@ async def test_real_auth_spectator_reconnect_and_authoritative_elo(tmp_path) -> welcome_one = await wait_for_type(one, "welcome") await two.send_json( { - "version": 2, + "version": 3, "type": "authenticate", "ticket": credentials["two"]["ticket"], } @@ -180,7 +180,7 @@ async def test_real_auth_spectator_reconnect_and_authoritative_elo(tmp_path) -> spectator = await client.ws_connect(f"{base}/api/hands/ws", headers=headers) await spectator.send_json( { - "version": 2, + "version": 3, "type": "authenticate", "ticket": credentials["three"]["ticket"], } @@ -198,7 +198,7 @@ async def test_real_auth_spectator_reconnect_and_authoritative_elo(tmp_path) -> replacement = await client.ws_connect(f"{base}/api/hands/ws", headers=headers) await replacement.send_json( { - "version": 2, + "version": 3, "type": "authenticate", "ticket": welcome_one["reconnect_ticket"], } diff --git a/tests/test_hands/test_protocol.py b/tests/test_hands/test_protocol.py index 4cc3154c..308b480b 100644 --- a/tests/test_hands/test_protocol.py +++ b/tests/test_hands/test_protocol.py @@ -6,6 +6,8 @@ from intelstream.hands.protocol import ( MAX_ACTIONS_PER_INPUT, MAX_FRAME_BYTES, + MAX_TICK_LAG, + MAX_TICK_LEAD, ProtocolError, encode_client_input, encode_snapshot, @@ -57,7 +59,7 @@ def test_round_trip_every_semantic_action() -> None: def valid_payload() -> dict[str, object]: return { - "version": 2, + "version": 3, "type": "input", "sequence": 2, "client_tick": 10, @@ -120,7 +122,7 @@ def test_rejects_unknown_nested_fields_and_malformed_actions() -> None: def test_rejects_duplicate_fields() -> None: frame = ( - '{"version":2,"type":"input","sequence":1,"sequence":2,' + '{"version":3,"type":"input","sequence":1,"sequence":2,' '"client_tick":1,"move":{"x":0,"y":0},"defense":"none","actions":[]}' ) @@ -140,19 +142,19 @@ def test_rejects_non_finite_and_non_integer_numbers() -> None: parse_client_input(json.dumps(payload), server_tick=10) -def test_rejects_stale_and_implausible_ticks() -> None: +def test_rejects_stale_sequences_but_clamps_implausible_ticks() -> None: frame = json.dumps(valid_payload()) with pytest.raises(ProtocolError, match="stale"): parse_client_input(frame, last_sequence=2, server_tick=10) payload = valid_payload() payload["client_tick"] = 500 - with pytest.raises(ProtocolError, match="far ahead"): - parse_client_input(json.dumps(payload), server_tick=10) + ahead = parse_client_input(json.dumps(payload), server_tick=10) + assert ahead.client_tick == 10 + MAX_TICK_LEAD payload["client_tick"] = 1 - with pytest.raises(ProtocolError, match="too old"): - parse_client_input(json.dumps(payload), server_tick=500) + stalled = parse_client_input(json.dumps(payload), server_tick=500) + assert stalled.client_tick == 500 - MAX_TICK_LAG def test_rejects_oversized_frames_and_action_arrays() -> None: @@ -172,13 +174,13 @@ def test_rejects_malformed_frames(frame: str | bytes) -> None: def test_ticket_ack_is_strict_and_distinct_from_semantic_input() -> None: - frame = '{"version":2,"type":"ticket_ack","refresh_id":"refresh-identifier"}' + frame = '{"version":3,"type":"ticket_ack","refresh_id":"refresh-identifier"}' assert parse_ticket_ack(frame) == "refresh-identifier" assert parse_ticket_ack(json.dumps(valid_payload())) is None for malformed in ( - '{"version":2,"type":"ticket_ack","refresh_id":"short"}', - '{"version":2,"type":"ticket_ack","refresh_id":"refresh-identifier","extra":1}', - '{"version":2,"type":"ticket_ack","refresh_id":"one","refresh_id":"two"}', + '{"version":3,"type":"ticket_ack","refresh_id":"short"}', + '{"version":3,"type":"ticket_ack","refresh_id":"refresh-identifier","extra":1}', + '{"version":3,"type":"ticket_ack","refresh_id":"one","refresh_id":"two"}', ): with pytest.raises(ProtocolError): parse_ticket_ack(malformed) diff --git a/tests/test_hands/test_rooms.py b/tests/test_hands/test_rooms.py index 3bab19e0..68b43f1b 100644 --- a/tests/test_hands/test_rooms.py +++ b/tests/test_hands/test_rooms.py @@ -2,17 +2,36 @@ import asyncio import json -from dataclasses import dataclass, field -from unittest.mock import AsyncMock +from dataclasses import dataclass, field, replace +from unittest.mock import AsyncMock, MagicMock import pytest from intelstream.database.repository import Repository +from intelstream.hands import rooms as rooms_module from intelstream.hands.auth import AuthenticatedPlayer from intelstream.hands.engine import EngineConfig from intelstream.hands.protocol import encode_client_input -from intelstream.hands.rooms import HandsRoomManager, RoomConfig, RoomError -from intelstream.hands.types import ActionKind, InputCommand, MovementAction +from intelstream.hands.rooms import ( + SNAPSHOT_BACKLOG_BYTES, + HandsRoom, + HandsRoomManager, + RoomConfig, + RoomError, + RoomMembership, +) +from intelstream.hands.types import ( + ActionKind, + CombatEvent, + DefensivePose, + EngineSnapshot, + Hand, + InputCommand, + MovementAction, + PunchAction, + PunchClass, + Target, +) @dataclass @@ -20,6 +39,9 @@ class FakeSocket: messages: list[str] = field(default_factory=list) closed: bool = False close_code: int | None = None + aborted: bool = False + uncompressed: list[str] = field(default_factory=list) + buffered: int = 0 block_send: asyncio.Event | None = None block_close: asyncio.Event | None = None close_entered: asyncio.Event | None = None @@ -34,6 +56,13 @@ async def send_str(self, data: str) -> None: if self.timeline is not None: self.timeline.append(f"send:{json.loads(data)['type']}") + async def send_uncompressed(self, data: str) -> None: + await self.send_str(data) + self.uncompressed.append(json.loads(data)["type"]) + + def write_buffer_size(self) -> int: + return self.buffered + async def close(self, *, code: int = 1000, message: bytes = b"") -> None: _ = message if self.close_entered is not None: @@ -45,6 +74,43 @@ async def close(self, *, code: int = 1000, message: bytes = b"") -> None: if self.timeline is not None: self.timeline.append("close") + def abort(self) -> None: + self.closed = True + self.aborted = True + + +@dataclass +class StalledSocket(FakeSocket): + """A socket whose peer stopped reading, modelled on aiohttp's flow control. + + Once the transport pauses, every write parks on one shared drain waiter, and close() drains + through the same waiter. Cancelling a writer parked there cancels the waiter itself. + """ + + paused: bool = True + drain_waiter: asyncio.Future[None] | None = None + + async def _drain(self) -> None: + if not self.paused: + return + if self.drain_waiter is None: + self.drain_waiter = asyncio.get_running_loop().create_future() + await self.drain_waiter + + async def send_str(self, data: str) -> None: + if self.closed: + raise ConnectionError + self.messages.append(data) + await self._drain() + + async def close(self, *, code: int = 1000, message: bytes = b"") -> None: + _ = message + if self.closed: + return + self.closed = True + self.close_code = code + await self._drain() + @pytest.fixture async def repository() -> Repository: @@ -66,6 +132,7 @@ def room_config( result_hold: float = 0.0, outbound_size: int = 16, final_delivery_timeout: float = 1.0, + close_timeout: float = 1.0, max_catch_up_ticks: int = 2, max_spectators: int = 20, ) -> RoomConfig: @@ -75,8 +142,10 @@ def room_config( reconnect_grace_seconds=reconnect_grace, result_hold_seconds=result_hold, final_delivery_timeout_seconds=final_delivery_timeout, + close_timeout_seconds=close_timeout, max_catch_up_ticks=max_catch_up_ticks, max_inputs_per_second=5, + max_input_frames_per_second=8, outbound_queue_size=outbound_size, max_spectators=max_spectators, engine_config=EngineConfig( @@ -292,9 +361,9 @@ async def controlled_sleep(_delay: float) -> None: replacement = await manager.join(player("three"), new_socket) await wait_until(lambda: "snapshot" in message_types(new_socket)) + await wait_until(lambda: old_socket.closed) assert old.role == replacement.role == "spectator" - assert old_socket.closed is True assert old_socket.close_code == 4001 assert replacement.room.player_ids == ("one", "two") assert replacement.room.spectator_ids == ("three",) @@ -371,6 +440,64 @@ async def test_post_start_disconnect_forfeits_and_pre_match_abandonment_does_not await waiting_manager.close() +async def test_burst_past_the_input_budget_keeps_the_newest_frame( + repository: Repository, +) -> None: + class MutableClock: + value = 0.0 + + def __call__(self) -> float: + return self.value + + clock = MutableClock() + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, reconnect_grace=30.0), + monotonic_clock=clock, + sleep=controlled_sleep, + match_id_factory=lambda: "match-burst", + ) + one = await manager.join(player("one"), FakeSocket()) + await manager.join(player("two"), FakeSocket()) + await sleep_entered.wait() + engine = one.room.engine + assert engine is not None + + for sequence in range(1, 6): + await one.room.submit_frame( + "one", + one.connection, + encode_client_input( + InputCommand(sequence=sequence, client_tick=engine.tick, move_x=1000) + ), + ) + for sequence in range(6, 9): + await one.room.submit_frame( + "one", + one.connection, + encode_client_input(InputCommand(sequence=sequence, client_tick=engine.tick)), + ) + assert engine.fighter("one").last_sequence == 5 + assert engine.fighter("one").held_input.move_x == 1000 + + clock.value += 0.25 + one.room._apply_deferred_inputs(clock()) + assert engine.fighter("one").last_sequence == 8 + assert engine.fighter("one").held_input.move_x == 0 + + one.room._apply_deferred_inputs(clock()) + assert engine.fighter("one").last_sequence == 8 + sleep_release.set() + await manager.close() + + async def test_input_protocol_rate_sequence_and_queue_bounds(repository: Repository) -> None: manager = HandsRoomManager( repository, @@ -396,12 +523,27 @@ async def test_input_protocol_rate_sequence_and_queue_bounds(repository: Reposit one.connection, encode_client_input(InputCommand(sequence=sequence, client_tick=tick)), ) + accepted = engine.fighter("one").last_sequence + await one.room.submit_frame( + "one", + one.connection, + encode_client_input(InputCommand(sequence=6, client_tick=engine.tick, move_x=1000)), + ) + assert engine.fighter("one").last_sequence == accepted + assert engine.fighter("one").held_input.move_x == 0 + await one.room.submit_frame( + "one", + one.connection, + encode_client_input(InputCommand(sequence=7, client_tick=engine.tick)), + ) + assert engine.fighter("one").last_sequence == accepted with pytest.raises(RoomError, match="rate_limited"): - await one.room.submit_frame( - "one", - one.connection, - encode_client_input(InputCommand(sequence=6, client_tick=engine.tick)), - ) + for sequence in range(8, 8 + 4 * 8): + await one.room.submit_frame( + "one", + one.connection, + encode_client_input(InputCommand(sequence=sequence, client_tick=engine.tick)), + ) await manager.close() @@ -450,7 +592,7 @@ async def controlled_sleep(_delay: float) -> None: assert not engine.fighter("one").pending_actions checksum = engine.snapshot().checksum - for sequence in range(5): + for sequence in range(8): await connected.room.submit_frame( "two", connected.connection, @@ -458,15 +600,24 @@ async def controlled_sleep(_delay: float) -> None: InputCommand(sequence=sequence, client_tick=engine.tick, move_x=1000) ), ) - with pytest.raises(RoomError, match="rate_limited"): - await connected.room.submit_frame( - "two", - connected.connection, - encode_client_input(InputCommand(sequence=5, client_tick=engine.tick, move_x=1000)), - ) + await connected.room.submit_frame( + "two", + connected.connection, + encode_client_input(InputCommand(sequence=8, client_tick=engine.tick, move_x=1000)), + ) assert engine.snapshot().checksum == checksum assert engine.fighter("two").last_sequence == -1 assert not engine.fighter("two").pending_actions + with pytest.raises(RoomError, match="rate_limited"): + for sequence in range(9, 9 + 4 * 8): + await connected.room.submit_frame( + "two", + connected.connection, + encode_client_input( + InputCommand(sequence=sequence, client_tick=engine.tick, move_x=1000) + ), + ) + assert engine.snapshot().checksum == checksum clock.value = 1.01 await manager.join(player("one"), FakeSocket()) @@ -507,6 +658,32 @@ async def test_bounded_periodic_snapshots_drop_slow_consumer( } +async def test_a_fighter_dropped_as_a_slow_consumer_still_pauses_and_forfeits( + repository: Repository, +) -> None: + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1_000_000, reconnect_grace=0.05), + match_id_factory=lambda: "match-stalled", + ) + stalled = StalledSocket() + opponent = FakeSocket() + stalled_membership = await manager.join(player("stalled"), stalled) + await manager.join(player("opponent"), opponent) + + await wait_until(lambda: "paused" in message_types(opponent), deadline_seconds=2.0) + slot = stalled_membership.room._slots["stalled"] + assert slot.connection is None + assert slot.reconnect_deadline is not None + await wait_until(lambda: stalled.aborted) + await wait_until(lambda: "final" in message_types(opponent)) + match = await repository.get_hands_match("match-stalled") + assert match is not None + assert match.finish_method == "forfeit" + assert match.winner_id == "opponent" + await manager.close() + + async def test_transient_queue_pressure_recovers_and_can_debounce_again( repository: Repository, ) -> None: @@ -541,6 +718,123 @@ async def test_transient_queue_pressure_recovers_and_can_debounce_again( await manager.close() +async def started_room_with_blocked_ticks( + repository: Repository, socket: FakeSocket, *, outbound_size: int = 16 +) -> tuple[HandsRoomManager, HandsRoom, asyncio.Event]: + """A started bout whose tick loop is parked, so the test broadcasts snapshots itself.""" + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, outbound_size=outbound_size), + sleep=controlled_sleep, + ) + membership = await manager.join(player("one"), socket) + await manager.join(player("two"), FakeSocket()) + await sleep_entered.wait() + return manager, membership.room, sleep_release + + +def snapshot_payloads(socket: FakeSocket) -> list[dict[str, object]]: + return [ + json.loads(message)["payload"] + for message in socket.messages + if json.loads(message)["type"] == "snapshot" + ] + + +async def test_a_backed_up_connection_gets_the_newest_snapshot_with_the_events_it_missed( + repository: Repository, +) -> None: + send_release = asyncio.Event() + socket = FakeSocket(block_send=send_release) + manager, room, sleep_release = await started_room_with_blocked_ticks(repository, socket) + engine = room.engine + assert engine is not None + base = engine.snapshot() + hit = CombatEvent(event_id=900, tick=base.tick + 1, kind="hit", actor_id="two", amount=12) + for offset in range(1, 6): + room._broadcast_snapshot( + replace(base, tick=base.tick + offset, events=(hit,) if offset == 1 else ()) + ) + + send_release.set() + await wait_until(lambda: bool(snapshot_payloads(socket))) + await asyncio.sleep(0.02) + snapshots = snapshot_payloads(socket) + assert [payload["tick"] for payload in snapshots] == [base.tick + 5] + events = snapshots[0]["events"] + assert isinstance(events, list) + assert 900 in {event["event_id"] for event in events} + sleep_release.set() + await manager.close() + + +async def test_snapshots_wait_while_the_transport_is_backed_up_and_then_send_the_newest( + repository: Repository, +) -> None: + socket = FakeSocket() + manager, room, sleep_release = await started_room_with_blocked_ticks(repository, socket) + engine = room.engine + assert engine is not None + await wait_until(lambda: bool(snapshot_payloads(socket))) + sent = len(snapshot_payloads(socket)) + base = engine.snapshot() + + socket.buffered = SNAPSHOT_BACKLOG_BYTES + 1 + room._broadcast_snapshot(replace(base, tick=base.tick + 1)) + await asyncio.sleep(0.05) + assert len(snapshot_payloads(socket)) == sent + room._broadcast_snapshot(replace(base, tick=base.tick + 2)) + socket.buffered = 0 + await wait_until(lambda: len(snapshot_payloads(socket)) == sent + 1) + assert snapshot_payloads(socket)[-1]["tick"] == base.tick + 2 + sleep_release.set() + await manager.close() + + +async def test_a_connection_whose_transport_never_drains_is_dropped( + repository: Repository, +) -> None: + socket = FakeSocket() + manager, room, sleep_release = await started_room_with_blocked_ticks( + repository, socket, outbound_size=3 + ) + engine = room.engine + assert engine is not None + await wait_until(lambda: bool(snapshot_payloads(socket))) + base = engine.snapshot() + + socket.buffered = SNAPSHOT_BACKLOG_BYTES + 1 + for offset in range(1, 6): + room._broadcast_snapshot(replace(base, tick=base.tick + offset)) + await wait_until(lambda: socket.closed) + assert room._slots["one"].connection is None + sleep_release.set() + await manager.close() + + +async def test_frames_that_carry_a_reconnect_ticket_are_never_compressed( + repository: Repository, +) -> None: + socket = FakeSocket() + manager = HandsRoomManager(repository, config=room_config(round_ticks=1000)) + membership = await manager.join(player("one"), socket, reconnect_ticket="first-rotation") + await manager.join(player("two"), FakeSocket()) + await membership.room.refresh_ticket( + "one", membership.connection, "next-rotation", "refresh-id-000001" + ) + await wait_until(lambda: {"ticket", "snapshot"} <= set(message_types(socket))) + + assert socket.uncompressed == ["welcome", "ticket"] + await manager.close() + + async def test_ticket_refresh_queue_coalesces_and_rejects_replaced_connection( repository: Repository, ) -> None: @@ -567,7 +861,7 @@ async def test_ticket_refresh_queue_coalesces_and_rejects_replaced_connection( "reconnect_ticket": "ticket-99", "refresh_id": "refresh-id-000099", "type": "ticket", - "version": 2, + "version": 3, } ] @@ -627,7 +921,9 @@ async def controlled_sleep(_delay: float) -> None: await wait_until(lambda: slow_socket.closed) maximum_queued = max(maximum_queued, slow.connection.outbox.qsize()) assert slow.connection.slow_drop_started - assert maximum_queued <= outbound_size + 3 + # The initial burst (waiting, ready), one snapshot slot and the stop sentinel, plus at most + # outbound_size control updates, however long the churn goes on. + assert maximum_queued <= outbound_size + 4 active_hands_tasks = { task.get_name() for task in asyncio.all_tasks() @@ -672,7 +968,7 @@ async def test_critical_initial_burst_is_ordered_despite_blocked_writer( @pytest.mark.parametrize("outbound_size", [1, 2]) -async def test_reconnect_waits_for_old_close_then_sends_welcome_snapshot_and_resumed( +async def test_reconnect_over_a_socket_still_closing_gets_welcome_snapshot_and_resumed( repository: Repository, outbound_size: int ) -> None: sleep_release = asyncio.Event() @@ -686,8 +982,9 @@ async def controlled_sleep(_delay: float) -> None: sleep=controlled_sleep, match_id_factory=lambda: "match-ordered-reconnect", ) + close_entered = asyncio.Event() close_release = asyncio.Event() - old_socket = FakeSocket(block_close=close_release) + old_socket = FakeSocket(block_close=close_release, close_entered=close_entered) old = await manager.join(player("one"), old_socket, reconnect_ticket="old-rotation") await manager.join(player("two"), FakeSocket()) engine = old.room.engine @@ -695,14 +992,16 @@ async def controlled_sleep(_delay: float) -> None: engine.fighter("two").get_up_meter = 77 replacement_socket = FakeSocket() - replacement_task = asyncio.create_task( - manager.join(player("one"), replacement_socket, reconnect_ticket="new-rotation") - ) - await asyncio.sleep(0) - assert replacement_socket.messages == [] - close_release.set() - replacement = await replacement_task + async with asyncio.timeout(1): + replacement = await manager.join( + player("one"), replacement_socket, reconnect_ticket="new-rotation" + ) await wait_until(lambda: len(replacement_socket.messages) >= 3) + await close_entered.wait() + assert not old_socket.closed + close_release.set() + await wait_until(lambda: old_socket.closed) + assert old_socket.close_code == 4001 messages = [json.loads(message) for message in replacement_socket.messages[:3]] assert [message["type"] for message in messages] == ["welcome", "snapshot", "resumed"] @@ -765,7 +1064,7 @@ async def controlled_sleep(_delay: float) -> None: "grace_ms": 22_750, "player_id": "two", "type": "paused", - "version": 2, + "version": 3, } two_socket = FakeSocket() @@ -775,7 +1074,7 @@ async def controlled_sleep(_delay: float) -> None: await manager.close() -async def test_reconnect_rechecks_final_state_after_waiting_for_old_socket_close( +async def test_a_replaced_socket_that_never_closes_is_aborted_without_holding_up_the_bout( repository: Repository, ) -> None: sleep_entered = asyncio.Event() @@ -787,13 +1086,12 @@ async def controlled_sleep(_delay: float) -> None: manager = HandsRoomManager( repository, - config=room_config(round_ticks=1000), + config=room_config(round_ticks=1000, close_timeout=0.05), sleep=controlled_sleep, match_id_factory=lambda: "match-final-during-reconnect", ) close_entered = asyncio.Event() - close_release = asyncio.Event() - old_socket = FakeSocket(block_close=close_release, close_entered=close_entered) + old_socket = FakeSocket(block_close=asyncio.Event(), close_entered=close_entered) membership = await manager.join(player("one"), old_socket) await manager.join(player("two"), FakeSocket()) await sleep_entered.wait() @@ -802,18 +1100,68 @@ async def controlled_sleep(_delay: float) -> None: engine.phase_ticks_remaining = 1 reconnect_socket = FakeSocket() - reconnect_task = asyncio.create_task( - manager.join(player("one"), reconnect_socket, reconnect_ticket="final-rotation") - ) + async with asyncio.timeout(1): + await manager.join(player("one"), reconnect_socket, reconnect_ticket="final-rotation") await close_entered.wait() sleep_release.set() - await wait_until(lambda: engine.result is not None) - close_release.set() - await reconnect_task + await wait_until(lambda: old_socket.aborted) await wait_until(lambda: "final" in message_types(reconnect_socket)) - assert message_types(reconnect_socket)[:3] == ["welcome", "snapshot", "final"] - assert "resumed" not in message_types(reconnect_socket) + assert message_types(reconnect_socket)[:3] == ["welcome", "snapshot", "resumed"] + assert old_socket.close_code is None + await manager.close() + + +async def test_reconnect_over_a_socket_parked_on_a_stalled_transport( + repository: Repository, +) -> None: + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, outbound_size=1000), + sleep=controlled_sleep, + match_id_factory=lambda: "match-parked-reconnect", + ) + stalled = StalledSocket() + await manager.join(player("one"), stalled) + await manager.join(player("two"), FakeSocket()) + await wait_until(lambda: stalled.drain_waiter is not None) + + replacement_socket = FakeSocket() + async with asyncio.timeout(1): + await manager.join(player("one"), replacement_socket) + await wait_until(lambda: len(replacement_socket.messages) >= 3) + assert message_types(replacement_socket)[:3] == ["welcome", "snapshot", "resumed"] + await wait_until(lambda: stalled.aborted) + await manager.close() + + +async def test_admission_into_one_room_does_not_hold_up_joins_elsewhere( + repository: Repository, monkeypatch: pytest.MonkeyPatch +) -> None: + manager = HandsRoomManager(repository, config=room_config(round_ticks=1000)) + entered = asyncio.Event() + release = asyncio.Event() + original_add = HandsRoom.add + + async def stuck_add(room: HandsRoom, identity: AuthenticatedPlayer, *args, **kwargs): + if identity.instance_id == "stuck-room": + entered.set() + await release.wait() + return await original_add(room, identity, *args, **kwargs) + + monkeypatch.setattr(HandsRoom, "add", stuck_add) + stuck = asyncio.create_task(manager.join(player("one", "stuck-room"), FakeSocket())) + await entered.wait() + async with asyncio.timeout(0.5): + elsewhere = await manager.join(player("two", "other-room"), FakeSocket()) + assert elsewhere.role == "fighter" + release.set() + assert (await stuck).role == "fighter" await manager.close() @@ -833,11 +1181,89 @@ async def test_persistence_failure_errors_closes_and_unregisters(repository: Rep assert one.closed and two.closed for socket in (one, two): errors = [json.loads(message) for message in socket.messages if '"type":"error"' in message] - assert errors == [{"code": "persistence_failed", "type": "error", "version": 2}] + assert errors == [{"code": "persistence_failed", "type": "error", "version": 3}] assert all("database detail" not in message for message in socket.messages) await manager.close() +async def test_an_engine_failure_voids_the_bout_and_frees_the_instance( + repository: Repository, monkeypatch: pytest.MonkeyPatch +) -> None: + safe_logger = MagicMock() + monkeypatch.setattr(rooms_module, "logger", safe_logger) + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000), + sleep=controlled_sleep, + match_id_factory=lambda: "match-engine-failure", + ) + sockets = (FakeSocket(), FakeSocket()) + one = await manager.join(player("one"), sockets[0]) + await manager.join(player("two"), sockets[1]) + await sleep_entered.wait() + engine = one.room.engine + assert engine is not None + + def broken_step(*_args: object) -> None: + raise RuntimeError("engine bug") + + monkeypatch.setattr(engine, "step", broken_step) + sleep_release.set() + await wait_until(lambda: manager.room_count == 0) + + for socket in sockets: + assert socket.closed + assert socket.close_code == 1011 + errors = [json.loads(message) for message in socket.messages if '"type":"error"' in message] + assert errors == [{"code": "internal_error", "type": "error", "version": 3}] + safe_logger.exception.assert_called_once() + assert await repository.get_hands_match("match-engine-failure") is None + for user_id in ("one", "two"): + rating = await repository.get_hands_rating("guild-1", user_id) + assert rating is not None + assert (rating.bouts, rating.rating) == (0, 1000) + again = await manager.join(player("one"), FakeSocket()) + assert again.room is not one.room + await manager.close() + + +async def test_a_result_the_engine_reached_is_recorded_even_if_broadcasting_it_fails( + repository: Repository, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setattr(rooms_module, "logger", MagicMock()) + original_broadcast = HandsRoom._broadcast_snapshot + + def broadcast_failing_on_the_result(room: HandsRoom, snapshot: EngineSnapshot) -> None: + if snapshot.result is not None: + raise RuntimeError("encoding bug") + original_broadcast(room, snapshot) + + monkeypatch.setattr(HandsRoom, "_broadcast_snapshot", broadcast_failing_on_the_result) + manager = HandsRoomManager( + repository, + config=room_config(), + match_id_factory=lambda: "match-broadcast-failure", + ) + sockets = (FakeSocket(), FakeSocket()) + await manager.join(player("one"), sockets[0]) + await manager.join(player("two"), sockets[1]) + await wait_until(lambda: manager.room_count == 0) + + match = await repository.get_hands_match("match-broadcast-failure") + assert match is not None + assert match.finish_method == "draw" + for socket in sockets: + assert "final" in message_types(socket) + await manager.close() + + async def test_shutdown_after_result_shields_persistence_from_cancelled_waiter( repository: Repository, ) -> None: @@ -1240,8 +1666,7 @@ async def delayed_record(result): recovered = await manager.join(player("one"), reconnect_socket) await wait_until(lambda: len(reconnect_socket.messages) >= 2) assert message_types(reconnect_socket)[:2] == ["welcome", "snapshot"] - with pytest.raises(RoomError, match="match_complete"): - await recovered.room.submit_frame("one", recovered.connection, "{}") + await recovered.room.submit_frame("one", recovered.connection, "{}") with pytest.raises(RoomError, match="room_closed"): await manager.join(player("three"), FakeSocket()) @@ -1298,8 +1723,7 @@ async def controlled_sleep(delay: float) -> None: "final", ] assert recovered_messages[2] == authoritative_final - with pytest.raises(RoomError, match="match_complete"): - await recovered.room.submit_frame("one", recovered.connection, "{}") + await recovered.room.submit_frame("one", recovered.connection, "{}") hold_release.set() await wait_until(lambda: reconnect_socket.closed) assert message_types(reconnect_socket).index("final") < len(reconnect_socket.messages) @@ -1335,3 +1759,359 @@ async def test_close_is_idempotent_and_leaves_no_hands_tasks(repository: Reposit if task is not asyncio.current_task() and not task.done() } assert not {name for name in active_names if name.startswith("hands-")} + + +async def test_a_rematch_reaches_a_new_room_while_the_old_one_is_still_closing( + repository: Repository, +) -> None: + hold = 0.2 + delivery = 0.3 + spectator_seated = asyncio.Event() + + async def sleep_once_the_spectator_is_seated(delay: float) -> None: + # The first tick only ends the countdown, so however coarse the platform's timer, the + # two-tick bout cannot finish before the spectator is in. + await spectator_seated.wait() + await asyncio.sleep(delay) + + manager = HandsRoomManager( + repository, + config=room_config(result_hold=hold, final_delivery_timeout=delivery), + sleep=sleep_once_the_spectator_is_seated, + ) + first, second = FakeSocket(), FakeSocket() + stalled = FakeSocket(block_send=asyncio.Event()) + one = await manager.join(player("one"), first) + two = await manager.join(player("two"), second) + await manager.join(player("spectator"), stalled) + spectator_seated.set() + await wait_until( + lambda: any(json.loads(message)["type"] == "final" for message in first.messages), + deadline_seconds=2.0, + ) + await manager.leave(one) + await manager.leave(two) + + outcomes: list[str] = [] + async with asyncio.timeout(hold + 2 * delivery + 1.0): + while not outcomes or outcomes[-1] != "new room": + try: + membership = await manager.join(player("one"), FakeSocket()) + outcome = "old room" if membership.room is one.room else "new room" + await manager.leave(membership) + except RoomError as exc: + outcome = f"refused: {exc.code}" + if not outcomes or outcomes[-1] != outcome: + outcomes.append(outcome) + await asyncio.sleep(0.01) + assert outcomes == ["old room", "new room"] + assert stalled.block_send is not None + stalled.block_send.set() + await manager.close() + + +class MutableClock: + value = 0.0 + + def __call__(self) -> float: + return self.value + + +async def burst_then_drop( + repository: Repository, label: str +) -> tuple[HandsRoomManager, RoomMembership, MutableClock, asyncio.Event]: + clock = MutableClock() + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, reconnect_grace=30.0), + monotonic_clock=clock, + sleep=controlled_sleep, + match_id_factory=lambda: f"match-{label}", + ) + one = await manager.join(player("one"), FakeSocket()) + await manager.join(player("two"), FakeSocket()) + await sleep_entered.wait() + engine = one.room.engine + assert engine is not None + for sequence in range(1, 8): + await one.room.submit_frame( + "one", + one.connection, + encode_client_input( + InputCommand(sequence=sequence, client_tick=engine.tick, move_x=1000) + ), + ) + assert engine.fighter("one").last_sequence == 5 + await manager.leave(one) + return manager, one, clock, sleep_release + + +async def test_a_fresh_client_is_not_broken_by_frames_held_back_from_its_dropped_connection( + repository: Repository, +) -> None: + manager, one, clock, sleep_release = await burst_then_drop(repository, "fresh") + room = one.room + engine = room.engine + assert engine is not None + socket = FakeSocket() + rejoined = await manager.join(player("one"), socket) + await wait_until(lambda: bool(socket.messages)) + welcome = json.loads(socket.messages[0]) + assert welcome["type"] == "welcome" + clock.value += 1.0 + room._apply_deferred_inputs(clock()) + assert engine.fighter("one").last_sequence == 5 + await room.submit_frame( + "one", + rejoined.connection, + encode_client_input( + InputCommand(sequence=welcome["next_sequence"], client_tick=engine.tick) + ), + ) + assert engine.fighter("one").last_sequence == welcome["next_sequence"] + sleep_release.set() + await manager.close() + + +async def test_a_new_connection_gets_its_own_frame_allowance(repository: Repository) -> None: + manager, one, clock, sleep_release = await burst_then_drop(repository, "allowance") + room = one.room + engine = room.engine + assert engine is not None + socket = FakeSocket() + rejoined = await manager.join(player("one"), socket) + await wait_until(lambda: bool(socket.messages)) + welcome = json.loads(socket.messages[0]) + clock.value += 0.4 + sequence = welcome["next_sequence"] + for offset in range(5): + await room.submit_frame( + "one", + rejoined.connection, + encode_client_input(InputCommand(sequence=sequence + offset, client_tick=engine.tick)), + ) + assert engine.fighter("one").last_sequence == sequence + 4 + sleep_release.set() + await manager.close() + + +@pytest.mark.parametrize("held_back", ["before the pause", "during the pause"]) +async def test_a_frame_held_back_by_the_input_budget_never_fires_after_a_pause( + repository: Repository, held_back: str +) -> None: + clock = MutableClock() + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, reconnect_grace=30.0), + monotonic_clock=clock, + sleep=controlled_sleep, + match_id_factory=lambda: "match-held-across-pause", + ) + one = await manager.join(player("one"), FakeSocket()) + two = await manager.join(player("two"), FakeSocket()) + await sleep_entered.wait() + room = one.room + engine = room.engine + assert engine is not None + for sequence in range(1, 6): + await room.submit_frame( + "one", + one.connection, + encode_client_input(InputCommand(sequence=sequence, client_tick=engine.tick)), + ) + jab = PunchAction(hand=Hand.LEFT, punch_class=PunchClass.JAB, target=Target.HEAD) + held = encode_client_input( + InputCommand(sequence=6, client_tick=engine.tick, move_x=1000, actions=(jab,)) + ) + if held_back == "before the pause": + await room.submit_frame("one", one.connection, held) + await manager.leave(two) + else: + await manager.leave(two) + await room.submit_frame("one", one.connection, held) + assert engine.fighter("one").last_sequence == 5 + + clock.value += 10.0 + await manager.join(player("two"), FakeSocket()) + room._apply_deferred_inputs(clock()) + fighter = engine.fighter("one") + assert fighter.last_sequence == 5 + assert not fighter.pending_actions + assert fighter.held_input.move_x == 0 + sleep_release.set() + await manager.close() + + +async def test_a_pause_returns_both_fighters_held_input_to_neutral( + repository: Repository, +) -> None: + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, reconnect_grace=30.0), + sleep=controlled_sleep, + match_id_factory=lambda: "match-held-input-pause", + ) + one = await manager.join(player("one"), FakeSocket()) + two = await manager.join(player("two"), FakeSocket()) + await sleep_entered.wait() + engine = one.room.engine + assert engine is not None + await one.room.submit_frame( + "one", + one.connection, + encode_client_input( + InputCommand( + sequence=1, + client_tick=engine.tick, + move_x=1000, + defense=DefensivePose.GUARD_HIGH, + ) + ), + ) + await two.room.submit_frame( + "two", + two.connection, + encode_client_input(InputCommand(sequence=1, client_tick=engine.tick, move_y=-1000)), + ) + assert engine.fighter("one").held_input.move_x == 1000 + + await manager.leave(two) + for player_id in ("one", "two"): + held = engine.fighter(player_id).held_input + assert (held.move_x, held.move_y, held.defense) == (0, 0, DefensivePose.NONE) + sleep_release.set() + await manager.close() + + +async def test_a_backlog_after_a_stall_is_dropped_but_a_lasting_flood_ends_the_bout( + repository: Repository, +) -> None: + class MutableClock: + value = 0.0 + + def __call__(self) -> float: + return self.value + + clock = MutableClock() + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, reconnect_grace=30.0), + monotonic_clock=clock, + sleep=controlled_sleep, + match_id_factory=lambda: "match-flood", + ) + one = await manager.join(player("one"), FakeSocket()) + await manager.join(player("two"), FakeSocket()) + await sleep_entered.wait() + room = one.room + engine = room.engine + assert engine is not None + sequence = 0 + + async def send(count: int, move_x: int = 0) -> None: + nonlocal sequence + for _ in range(count): + sequence += 1 + await room.submit_frame( + "one", + one.connection, + encode_client_input( + InputCommand(sequence=sequence, client_tick=engine.tick, move_x=move_x) + ), + ) + + await send(20, move_x=0) + await send(1, move_x=1000) + clock.value += 1.0 + room._apply_deferred_inputs(clock()) + assert engine.fighter("one").last_sequence == sequence + assert engine.fighter("one").held_input.move_x == 1000 + + with pytest.raises(RoomError, match="rate_limited"): + for _ in range(40): + clock.value += 0.1 + await send(1) + await send(1) + assert clock.value - 1.0 >= 3.0 + sleep_release.set() + await manager.close() + + +async def test_a_connection_that_replaces_a_live_one_starts_with_its_own_input_pacing( + repository: Repository, +) -> None: + clock = MutableClock() + sleep_entered = asyncio.Event() + sleep_release = asyncio.Event() + + async def controlled_sleep(_delay: float) -> None: + sleep_entered.set() + await sleep_release.wait() + + manager = HandsRoomManager( + repository, + config=room_config(round_ticks=1000, reconnect_grace=30.0), + monotonic_clock=clock, + sleep=controlled_sleep, + match_id_factory=lambda: "match-replace", + ) + one = await manager.join(player("one"), FakeSocket()) + await manager.join(player("two"), FakeSocket()) + await sleep_entered.wait() + room = one.room + engine = room.engine + assert engine is not None + for sequence in range(1, 10): + await room.submit_frame( + "one", + one.connection, + encode_client_input( + InputCommand(sequence=sequence, client_tick=engine.tick, move_x=1000) + ), + ) + socket = FakeSocket() + replacing = await manager.join(player("one"), socket) + await wait_until(lambda: bool(socket.messages)) + welcome = json.loads(socket.messages[0]) + clock.value += 0.4 + room._apply_deferred_inputs(clock()) + assert engine.fighter("one").last_sequence == 5 + for offset in range(5): + await room.submit_frame( + "one", + replacing.connection, + encode_client_input( + InputCommand(sequence=welcome["next_sequence"] + offset, client_tick=engine.tick) + ), + ) + assert engine.fighter("one").last_sequence == welcome["next_sequence"] + 4 + sleep_release.set() + await manager.close() diff --git a/tests/test_hands/test_server.py b/tests/test_hands/test_server.py index cb092cd1..db808b6e 100644 --- a/tests/test_hands/test_server.py +++ b/tests/test_hands/test_server.py @@ -1,8 +1,13 @@ from __future__ import annotations import asyncio +import base64 import json +import os +import socket +import struct import time +import zlib from types import SimpleNamespace from typing import TYPE_CHECKING from unittest.mock import AsyncMock, MagicMock @@ -16,7 +21,12 @@ from intelstream.hands import server as server_module from intelstream.hands.auth import AuthenticatedPlayer, AuthExchange, HandsAuth, HandsAuthError from intelstream.hands.engine import EngineConfig -from intelstream.hands.rooms import HandsRoomManager, RoomConfig, RoomError +from intelstream.hands.rooms import ( + SNAPSHOT_BACKLOG_BYTES, + HandsRoomManager, + RoomConfig, + RoomError, +) from intelstream.hands.server import AdmissionConfig, HandsServer if TYPE_CHECKING: @@ -142,6 +152,165 @@ async def start_server( return server, fake_auth, f"http://127.0.0.1:{server.bound_port}" +async def connect_reader_that_stalls( + port: int, ticket: str, *, read_frames: int = 0 +) -> tuple[socket.socket, list[dict[str, object]]]: + """Authenticates over a raw socket, reads `read_frames` server frames, then never reads again. + + The small receive buffer and the absent reads fill the server's transport within a fraction of + a second of per-tick snapshots, as a phone that switched networks or went to the background + would. + """ + loop = asyncio.get_running_loop() + raw = socket.socket(socket.AF_INET, socket.SOCK_STREAM) + raw.setsockopt(socket.SOL_SOCKET, socket.SO_RCVBUF, 4096) + raw.setblocking(False) + await loop.sock_connect(raw, ("127.0.0.1", port)) + key = base64.b64encode(os.urandom(16)).decode() + await loop.sock_sendall( + raw, + ( + "GET /api/hands/ws HTTP/1.1\r\n" + f"Host: 127.0.0.1:{port}\r\nUpgrade: websocket\r\nConnection: Upgrade\r\n" + f"Sec-WebSocket-Key: {key}\r\nSec-WebSocket-Version: 13\r\nOrigin: {ORIGIN}\r\n\r\n" + ).encode(), + ) + received = b"" + while b"\r\n\r\n" not in received: + received += await loop.sock_recv(raw, 1) + assert b" 101 " in received.split(b"\r\n", 1)[0] + payload = json.dumps({"version": 3, "type": "authenticate", "ticket": ticket}).encode() + assert len(payload) < 126 + mask = os.urandom(4) + masked = bytes(byte ^ mask[index % 4] for index, byte in enumerate(payload)) + await loop.sock_sendall(raw, bytes([0x81, 0x80 | len(payload)]) + mask + masked) + + async def read_exactly(count: int) -> bytes: + data = b"" + while len(data) < count: + chunk = await loop.sock_recv(raw, count - len(data)) + assert chunk, "server closed the socket" + data += chunk + return data + + frames: list[dict[str, object]] = [] + for _ in range(read_frames): + first, second = await read_exactly(2) + length = second & 0x7F + if length == 126: + (length,) = struct.unpack("!H", await read_exactly(2)) + elif length == 127: + (length,) = struct.unpack("!Q", await read_exactly(8)) + assert first & 0x40 == 0, "a raw reader does not negotiate compression" + frames.append(json.loads(await read_exactly(length))) + return raw, frames + + +async def connect_deflate_client( + port: int, ticket: str +) -> tuple[asyncio.StreamReader, asyncio.StreamWriter, str]: + """Authenticates over a raw socket that offers permessage-deflate, as browsers do.""" + reader, writer = await asyncio.open_connection("127.0.0.1", port) + key = base64.b64encode(os.urandom(16)).decode() + writer.write( + ( + "GET /api/hands/ws HTTP/1.1\r\n" + f"Host: 127.0.0.1:{port}\r\nUpgrade: websocket\r\nConnection: Upgrade\r\n" + f"Sec-WebSocket-Key: {key}\r\nSec-WebSocket-Version: 13\r\nOrigin: {ORIGIN}\r\n" + "Sec-WebSocket-Extensions: permessage-deflate; client_max_window_bits\r\n\r\n" + ).encode() + ) + head = (await reader.readuntil(b"\r\n\r\n")).decode() + assert " 101 " in head.split("\r\n", 1)[0] + extensions = next( + ( + line.split(":", 1)[1].strip() + for line in head.split("\r\n") + if line.lower().startswith("sec-websocket-extensions:") + ), + "", + ) + payload = json.dumps({"version": 3, "type": "authenticate", "ticket": ticket}).encode() + mask = os.urandom(4) + masked = bytes(byte ^ mask[index % 4] for index, byte in enumerate(payload)) + writer.write(bytes([0x81, 0x80 | len(payload)]) + mask + masked) + return reader, writer, extensions + + +async def read_server_frame(reader: asyncio.StreamReader) -> tuple[bool, int, bytes]: + first, second = await reader.readexactly(2) + length = second & 0x7F + if length == 126: + (length,) = struct.unpack("!H", await reader.readexactly(2)) + elif length == 127: + (length,) = struct.unpack("!Q", await reader.readexactly(8)) + return bool(first & 0x40), first & 0x0F, await reader.readexactly(length) + + +async def receive_until( + socket: aiohttp.ClientWebSocketResponse, kind: str, *, deadline_seconds: float = 10.0 +) -> dict[str, object]: + async with asyncio.timeout(deadline_seconds): + while True: + message = await socket.receive() + assert message.type == aiohttp.WSMsgType.TEXT, message + payload = json.loads(message.data) + if payload["type"] == kind: + return payload + + +def stalled_reader_rooms( + repository: Repository, match_id: str, *, outbound_queue_size: int = 16 +) -> HandsRoomManager: + return HandsRoomManager( + repository, + config=RoomConfig( + tick_interval_seconds=0.002, + reconnect_grace_seconds=0.5, + result_hold_seconds=0.0, + outbound_queue_size=outbound_queue_size, + engine_config=EngineConfig( + rounds=1, + round_ticks=1_000_000, + rest_ticks=0, + countdown_ticks=1, + flash_ko_enabled=False, + ), + ), + match_id_factory=lambda: match_id, + ) + + +async def start_capped_proxy(upstream_port: int, *, bytes_per_second: int) -> asyncio.Server: + """A TCP proxy whose server-to-client direction runs no faster than a weak mobile link.""" + + async def relay( + client_reader: asyncio.StreamReader, client_writer: asyncio.StreamWriter + ) -> None: + upstream_reader, upstream_writer = await asyncio.open_connection("127.0.0.1", upstream_port) + + async def up() -> None: + while data := await client_reader.read(65536): + upstream_writer.write(data) + await upstream_writer.drain() + + async def down() -> None: + loop = asyncio.get_running_loop() + started = loop.time() + relayed = 0 + while data := await upstream_reader.read(2048): + relayed += len(data) + client_writer.write(data) + await client_writer.drain() + await asyncio.sleep(max(0.0, relayed / bytes_per_second - (loop.time() - started))) + + await asyncio.gather(up(), down(), return_exceptions=True) + client_writer.close() + upstream_writer.close() + + return await asyncio.start_server(relay, "127.0.0.1", 0) + + async def post_bootstrap( client: aiohttp.ClientSession, base: str, @@ -222,12 +391,12 @@ async def test_bootstrap_token_origin_schema_media_and_no_store( bootstrap = await post_bootstrap(client, base, "instance", headers=headers) assert await bootstrap.json() == { "client_id": APP, - "protocol": 2, + "protocol": 3, "state": "oauth-state", "simulation": { "tick_rate": 30, "ring_half_width": 500, - "ring_half_height": 330, + "ring_half_height": 500, }, } assert bootstrap.headers["Cache-Control"] == "no-store" @@ -318,7 +487,7 @@ async def test_websocket_requires_ticket_first_without_query_and_times_out( await ws.close() malformed = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await malformed.send_json({"version": 2, "type": "authenticate", "ticket": "bad"}) + await malformed.send_json({"version": 3, "type": "authenticate", "ticket": "bad"}) message = await malformed.receive(timeout=1) assert json.loads(message.data)["code"] == "invalid_ticket" await malformed.close() @@ -326,6 +495,39 @@ async def test_websocket_requires_ticket_first_without_query_and_times_out( await server.close() +async def test_an_outdated_client_is_told_in_its_own_version_without_spending_its_ticket( + repository: Repository, +) -> None: + auth = FakeAuth() + auth.tickets["valid"] = AuthenticatedPlayer("one", GUILD, "room", "One", None) + server, _auth, base = await start_server(repository, auth=auth) + async with aiohttp.ClientSession() as client: + for frame in ( + {"version": 2, "type": "authenticate", "ticket": "valid"}, + {"version": 4, "type": "authenticate", "ticket": "valid", "build": "next"}, + ): + socket = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) + await socket.send_json(frame) + error = json.loads((await socket.receive(timeout=1)).data) + assert error == { + "code": "client_outdated", + "type": "error", + "version": frame["version"], + } + closing = await socket.receive(timeout=1) + assert closing.type == aiohttp.WSMsgType.CLOSE + assert closing.data == 4003 + await socket.close() + assert "valid" in auth.tickets + + socket = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) + await socket.send_json({"version": 3, "type": "resume", "ticket": "valid"}) + error = json.loads((await socket.receive(timeout=1)).data) + assert error == {"code": "invalid_ticket", "type": "error", "version": 3} + await socket.close() + await server.close() + + async def test_authenticated_room_admission_is_not_part_of_first_frame_timeout( repository: Repository, ) -> None: @@ -343,17 +545,21 @@ async def join(self, *_args, **_kwargs): auth = FakeAuth() auth.tickets["valid"] = AuthenticatedPlayer("one", GUILD, "room", "One", None) rooms = DelayedRejectionRooms() + # Well above Windows' 15.6 ms timer resolution, which let a 10 ms timeout expire before the + # authentication frame was read. + auth_timeout = 0.25 server, _auth, base = await start_server( repository, auth=auth, - auth_timeout=0.01, + auth_timeout=auth_timeout, rooms=rooms, ) async with aiohttp.ClientSession() as client: socket = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await socket.send_json({"version": 2, "type": "authenticate", "ticket": "valid"}) - await rooms.entered.wait() - await asyncio.sleep(0.03) + await socket.send_json({"version": 3, "type": "authenticate", "ticket": "valid"}) + async with asyncio.timeout(2): + await rooms.entered.wait() + await asyncio.sleep(2 * auth_timeout) rooms.release.set() error = json.loads((await socket.receive(timeout=1)).data) assert error["code"] == "room_full" @@ -390,7 +596,7 @@ def issue_ticket(self, player: AuthenticatedPlayer) -> str: server, _auth, base = await start_server(repository, auth=auth) async with aiohttp.ClientSession() as client: socket = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await socket.send_json({"version": 2, "type": "authenticate", "ticket": "valid"}) + await socket.send_json({"version": 3, "type": "authenticate", "ticket": "valid"}) await admission_entered.wait() assert auth.ticket_counter == 0 now = 2000.0 @@ -440,7 +646,7 @@ async def controlled_sleep(_delay: float) -> None: sockets = [] for ticket in ("one", "two"): ws = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await ws.send_json({"version": 2, "type": "authenticate", "ticket": ticket}) + await ws.send_json({"version": 3, "type": "authenticate", "ticket": ticket}) sockets.append(ws) async with asyncio.timeout(1): seen_ready = False @@ -449,7 +655,7 @@ async def controlled_sleep(_delay: float) -> None: if message.type == aiohttp.WSMsgType.TEXT: seen_ready = json.loads(message.data)["type"] == "ready" third = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await third.send_json({"version": 2, "type": "authenticate", "ticket": "three"}) + await third.send_json({"version": 3, "type": "authenticate", "ticket": "three"}) welcome = json.loads((await third.receive(timeout=1)).data) assert welcome["type"] == "welcome" assert welcome["role"] == "spectator" @@ -470,6 +676,227 @@ async def controlled_sleep(_delay: float) -> None: await server.close() +async def test_state_updates_are_deflated_but_frames_carrying_a_ticket_never_are( + repository: Repository, +) -> None: + refresh_now = asyncio.Event() + never = asyncio.Event() + refreshes = 0 + + async def ticket_sleep(_delay: float) -> None: + nonlocal refreshes + refreshes += 1 + await (refresh_now if refreshes == 1 else never).wait() + + auth = FakeAuth() + auth.tickets = { + "one": AuthenticatedPlayer("one", GUILD, "room", "One", None), + "two": AuthenticatedPlayer("two", GUILD, "room", "Two", None), + } + rooms = stalled_reader_rooms(repository, "deflated") + server, _auth, base = await start_server( + repository, auth=auth, rooms=rooms, ticket_refresh=1.0, ticket_sleep=ticket_sleep + ) + assert server.bound_port is not None + reader, writer, extensions = await connect_deflate_client(server.bound_port, "one") + assert extensions.startswith("permessage-deflate") + # One inflater for the whole stream: the server keeps its deflate context between messages. + inflater = zlib.decompressobj(-15) + received: list[tuple[dict[str, object], bool]] = [] + + async def read_until(kind: str, count: int = 1) -> None: + async with asyncio.timeout(10): + while sum(1 for message, _ in received if message["type"] == kind) < count: + compressed, opcode, payload = await read_server_frame(reader) + if opcode != 0x1: + continue + if compressed: + payload = inflater.decompress(payload + b"\x00\x00\xff\xff") + received.append((json.loads(payload), compressed)) + + async with aiohttp.ClientSession() as client: + two = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) + await two.send_json({"version": 3, "type": "authenticate", "ticket": "two"}) + await read_until("snapshot", 3) + refresh_now.set() + await read_until("ticket") + snapshots_before = sum(1 for message, _ in received if message["type"] == "snapshot") + await read_until("snapshot", snapshots_before + 3) + await two.close() + writer.close() + await server.close() + + welcome, welcome_compressed = received[0] + assert welcome["type"] == "welcome" + assert isinstance(welcome["reconnect_ticket"], str) + assert not welcome_compressed + ticket, ticket_compressed = next(item for item in received if item[0]["type"] == "ticket") + assert isinstance(ticket["reconnect_ticket"], str) + assert not ticket_compressed + assert all( + compressed + for message, compressed in received + if message["type"] not in {"welcome", "ticket"} + ) + + +async def test_a_spectator_on_a_slow_mobile_link_keeps_up_with_the_fight( + repository: Repository, +) -> None: + auth = FakeAuth() + for user in ("one", "two", "three"): + auth.tickets[user] = AuthenticatedPlayer(user, GUILD, "room", user.title(), None) + rooms = HandsRoomManager( + repository, + config=RoomConfig( + engine_config=EngineConfig( + rounds=1, round_ticks=1_000_000, countdown_ticks=1, flash_ko_enabled=False + ) + ), + match_id_factory=lambda: "slow-link", + ) + server, _auth, base = await start_server(repository, auth=auth, rooms=rooms) + assert server.bound_port is not None + proxy = await start_capped_proxy(server.bound_port, bytes_per_second=40_000) + proxy_port = proxy.sockets[0].getsockname()[1] + + async def fight(socket: aiohttp.ClientWebSocketResponse) -> None: + async for _message in socket: + pass + + async with aiohttp.ClientSession() as client: + fighters = [] + for ticket in ("one", "two"): + socket = await client.ws_connect( + f"{base}/api/hands/ws", headers={"Origin": ORIGIN}, compress=15 + ) + await socket.send_json({"version": 3, "type": "authenticate", "ticket": ticket}) + fighters.append(asyncio.create_task(fight(socket))) + spectator = await client.ws_connect( + f"http://127.0.0.1:{proxy_port}/api/hands/ws", headers={"Origin": ORIGIN}, compress=15 + ) + await spectator.send_json({"version": 3, "type": "authenticate", "ticket": "three"}) + loop = asyncio.get_running_loop() + started = loop.time() + lag_ticks: list[int] = [] + async with asyncio.timeout(10): + # Uncompressed per-tick snapshots need about 65 KB/s, so this link fell a third of a + # second further behind every second. + while loop.time() - started < 3.0: + payload = json.loads((await spectator.receive()).data) + if payload["type"] == "snapshot": + engine = rooms._rooms["room"].engine + assert engine is not None + lag_ticks.append(engine.tick - payload["payload"]["tick"]) + await spectator.close() + for task in fighters: + task.cancel() + await asyncio.gather(*fighters, return_exceptions=True) + proxy.close() + await server.close() + + assert max(lag_ticks[-30:]) <= 6 + assert len(lag_ticks) > 60 + + +async def test_a_fighter_whose_socket_stops_reading_is_paused_then_forfeits( + repository: Repository, +) -> None: + auth = FakeAuth() + auth.tickets = { + "one": AuthenticatedPlayer("one", GUILD, "room", "One", None), + "two": AuthenticatedPlayer("two", GUILD, "room", "Two", None), + } + rooms = stalled_reader_rooms(repository, "stalled-reader") + server, _auth, base = await start_server(repository, auth=auth, rooms=rooms) + assert server.bound_port is not None + async with aiohttp.ClientSession() as client: + one = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) + await one.send_json({"version": 3, "type": "authenticate", "ticket": "one"}) + await receive_until(one, "waiting") + stalled, _frames = await connect_reader_that_stalls(server.bound_port, "two") + try: + paused = await receive_until(one, "paused") + assert paused["player_id"] == "two" + final = await receive_until(one, "final") + finally: + stalled.close() + assert final["winner_id"] == "one" + assert final["method"] == "forfeit" + await one.close() + assert await repository.get_hands_match("stalled-reader") is not None + await server.close() + + +async def test_reconnecting_over_a_stalled_socket_does_not_hold_up_any_join( + repository: Repository, +) -> None: + auth = FakeAuth() + auth.tickets = { + "one": AuthenticatedPlayer("one", GUILD, "room", "One", None), + "two": AuthenticatedPlayer("two", GUILD, "room", "Two", None), + "elsewhere": AuthenticatedPlayer("three", GUILD, "other-room", "Three", None), + } + # A generous outbound bound keeps the stalled socket attached until the player reconnects. + rooms = stalled_reader_rooms(repository, "stalled-reconnect", outbound_queue_size=100_000) + server, _auth, base = await start_server(repository, auth=auth, rooms=rooms) + assert server.bound_port is not None + async with aiohttp.ClientSession() as client: + one = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) + await one.send_json({"version": 3, "type": "authenticate", "ticket": "one"}) + await receive_until(one, "waiting") + stalled, frames = await connect_reader_that_stalls(server.bound_port, "two", read_frames=1) + try: + assert frames[0]["type"] == "welcome" + room = rooms._rooms["room"] + old_connection = room._slots["two"].connection + assert old_connection is not None + old_socket = old_connection.socket + assert isinstance(old_socket, server_module._RoomSocket) + # The room holds snapshots back once a few kilobytes are buffered, short of the + # transport's own pause; a lower mark gets the paused transport a dead peer leaves. + # More than that backlog only builds once the peer's kernel buffers are full too, so + # the pause is lasting rather than one overlapped write still in flight. + transport = old_socket._request.transport + assert transport is not None + transport.set_write_buffer_limits(high=1024) + async with asyncio.timeout(10): + while not ( # noqa: ASYNC110 + old_socket._request.protocol.writing_paused + and transport.get_write_buffer_size() > SNAPSHOT_BACKLOG_BYTES + ): + await asyncio.sleep(0.01) + + replacement = await client.ws_connect( + f"{base}/api/hands/ws", headers={"Origin": ORIGIN} + ) + elsewhere = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) + await replacement.send_json( + {"version": 3, "type": "authenticate", "ticket": frames[0]["reconnect_ticket"]} + ) + await elsewhere.send_json({"version": 3, "type": "authenticate", "ticket": "elsewhere"}) + welcome = await receive_until(replacement, "welcome", deadline_seconds=2) + assert welcome["player_id"] == "two" + await receive_until(replacement, "resumed", deadline_seconds=2) + elsewhere_welcome = await receive_until(elsewhere, "welcome", deadline_seconds=2) + assert elsewhere_welcome["player_id"] == "three" + + # The stalled socket is aborted once its close times out. + loop = asyncio.get_running_loop() + async with asyncio.timeout(10): + while True: + try: + if not await loop.sock_recv(stalled, 65536): + break + except ConnectionError: + break + finally: + stalled.close() + for socket_ in (one, replacement, elsewhere): + await socket_.close() + await server.close() + + @pytest.mark.parametrize( "kwargs", [ @@ -734,11 +1161,11 @@ async def test_per_caller_websocket_auth_slots_release_and_isolate_callers( assert caught.value.status == 503 other = await client.ws_connect(f"{base}/api/hands/ws", headers=headers_two) - await other.send_json({"version": 2, "type": "authenticate", "ticket": "bad"}) + await other.send_json({"version": 3, "type": "authenticate", "ticket": "bad"}) assert json.loads((await other.receive(timeout=1)).data)["code"] == "invalid_ticket" await other.close() - await first.send_json({"version": 2, "type": "authenticate", "ticket": "bad"}) + await first.send_json({"version": 3, "type": "authenticate", "ticket": "bad"}) assert json.loads((await first.receive(timeout=1)).data)["code"] == "invalid_ticket" await first.close() replacement = await client.ws_connect(f"{base}/api/hands/ws", headers=headers_one) @@ -788,13 +1215,13 @@ async def begin(self, instance_id: object): with pytest.raises(aiohttp.WSServerHandshakeError) as caught: await client.ws_connect(f"{base}/api/hands/ws", headers=headers) assert caught.value.status == 503 - await first_ws.send_json({"version": 2, "type": "authenticate", "ticket": "bad"}) + await first_ws.send_json({"version": 3, "type": "authenticate", "ticket": "bad"}) await first_ws.receive(timeout=1) await first_ws.close() auth.tickets["valid"] = AuthenticatedPlayer("one", GUILD, "room", "One", None) available = await client.ws_connect(f"{base}/api/hands/ws", headers=headers) - await available.send_json({"version": 2, "type": "authenticate", "ticket": "valid"}) + await available.send_json({"version": 3, "type": "authenticate", "ticket": "valid"}) welcome = await available.receive(timeout=1) assert json.loads(welcome.data)["type"] == "welcome" await available.close() @@ -807,13 +1234,13 @@ async def test_ticket_replay_does_not_replace_live_socket(repository: Repository server, _auth, base = await start_server(repository, auth=auth) async with aiohttp.ClientSession() as client: live = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await live.send_json({"version": 2, "type": "authenticate", "ticket": "one-use"}) + await live.send_json({"version": 3, "type": "authenticate", "ticket": "one-use"}) welcome = json.loads((await live.receive(timeout=1)).data) assert welcome["type"] == "welcome" assert welcome["reconnect_ticket"].startswith("rotated-") replay = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await replay.send_json({"version": 2, "type": "authenticate", "ticket": "one-use"}) + await replay.send_json({"version": 3, "type": "authenticate", "ticket": "one-use"}) error = json.loads((await replay.receive(timeout=1)).data) assert error["code"] == "invalid_ticket" await replay.close() @@ -874,7 +1301,7 @@ def activate_ticket(self, ticket: object, player: AuthenticatedPlayer) -> None: base = f"http://127.0.0.1:{server.bound_port}" async with aiohttp.ClientSession() as client: live = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) - await live.send_json({"version": 2, "type": "authenticate", "ticket": initial_ticket}) + await live.send_json({"version": 3, "type": "authenticate", "ticket": initial_ticket}) welcome = json.loads((await live.receive(timeout=1)).data) original_rotation = welcome["reconnect_ticket"] @@ -888,7 +1315,7 @@ def activate_ticket(self, ticket: object, player: AuthenticatedPlayer) -> None: assert refreshed_ticket != original_rotation await live.send_json( { - "version": 2, + "version": 3, "type": "ticket_ack", "refresh_id": refreshed["refresh_id"], } @@ -902,7 +1329,7 @@ def activate_ticket(self, ticket: object, player: AuthenticatedPlayer) -> None: replacement = await client.ws_connect(f"{base}/api/hands/ws", headers={"Origin": ORIGIN}) await replacement.send_json( - {"version": 2, "type": "authenticate", "ticket": refreshed_ticket} + {"version": 3, "type": "authenticate", "ticket": refreshed_ticket} ) replacement_welcome = json.loads((await replacement.receive(timeout=1)).data) assert replacement_welcome["type"] == "welcome" @@ -927,9 +1354,9 @@ async def test_unexpected_post_upgrade_failure_closes_with_generic_error( 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"node_modules/undici": { - "version": "7.29.0", - "resolved": "https://registry.npmjs.org/undici/-/undici-7.29.0.tgz", - "integrity": "sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw==", + "version": "7.30.0", + "resolved": "https://registry.npmjs.org/undici/-/undici-7.30.0.tgz", + "integrity": "sha512-dkrQXeHSaoamnItlYbmzG0wFYrM0ZwDxCIg0A7aKjTyyhh9svRzCNFEzV+Vm05/yehjCzjDZ31KXfGEjYSztDQ==", "dev": true, "license": "MIT", "engines": { @@ -2677,19 +2696,19 @@ } }, "node_modules/vitest": { - "version": "4.1.10", - "resolved": "https://registry.npmjs.org/vitest/-/vitest-4.1.10.tgz", - "integrity": "sha512-R9jUTe5S4Qb0HCd4TNqpC7oGcrMssMRGXLW80ubjWsW9VH5GF8y1Y0SFLY9AbqSk6nt0PnOx4H4WNJYZ13GUPw==", + "version": "4.1.11", + "resolved": "https://registry.npmjs.org/vitest/-/vitest-4.1.11.tgz", + "integrity": "sha512-fhACrNXUidIbGSBr5FlbuBkO7VWC1ZyLl0DO4CU2DrQoAPxX84Ysxs+HeGQpii5lZWV1Q4gBZTTu49mF+A6Edw==", "dev": true, "license": "MIT", "dependencies": { - "@vitest/expect": "4.1.10", - "@vitest/mocker": "4.1.10", - "@vitest/pretty-format": "4.1.10", - "@vitest/runner": "4.1.10", - "@vitest/snapshot": "4.1.10", - "@vitest/spy": "4.1.10", - "@vitest/utils": "4.1.10", + "@vitest/expect": "4.1.11", + "@vitest/mocker": "4.1.11", + "@vitest/pretty-format": "4.1.11", + "@vitest/runner": "4.1.11", + "@vitest/snapshot": "4.1.11", + "@vitest/spy": "4.1.11", + "@vitest/utils": "4.1.11", "es-module-lexer": "^2.0.0", "expect-type": "^1.3.0", "magic-string": "^0.30.21", @@ -2717,12 +2736,12 @@ "@edge-runtime/vm": "*", "@opentelemetry/api": "^1.9.0", "@types/node": "^20.0.0 || ^22.0.0 || >=24.0.0", - "@vitest/browser-playwright": "4.1.10", - "@vitest/browser-preview": "4.1.10", - "@vitest/browser-webdriverio": "4.1.10", - "@vitest/coverage-istanbul": "4.1.10", - "@vitest/coverage-v8": "4.1.10", - "@vitest/ui": "4.1.10", + "@vitest/browser-playwright": "4.1.11", + "@vitest/browser-preview": "4.1.11", + "@vitest/browser-webdriverio": "4.1.11", + "@vitest/coverage-istanbul": "4.1.11", + "@vitest/coverage-v8": "4.1.11", + "@vitest/ui": "4.1.11", "happy-dom": "*", "jsdom": "*", "vite": "^6.0.0 || ^7.0.0 || ^8.0.0" diff --git a/web/hands/package.json b/web/hands/package.json index 82c8705c..50ea79db 100644 --- a/web/hands/package.json +++ b/web/hands/package.json @@ -10,20 +10,22 @@ "test:run": "vitest run", "build": "tsc --noEmit && vite build && npm run scan:build", "scan:build": "node scripts/scan-build.mjs", - "generate:fighter": "esbuild scripts/generate-fighter-glb.ts --bundle --platform=node --format=esm --outfile=node_modules/.cache/generate-fighter-glb.mjs && node node_modules/.cache/generate-fighter-glb.mjs", + "generate:fighter": "esbuild scripts/generate-fighter-glb.ts --bundle --packages=external --platform=node --format=esm --outfile=node_modules/.cache/generate-fighter-glb.mjs && node node_modules/.cache/generate-fighter-glb.mjs", "generate:audio": "uv run --project ../.. --with numpy==2.5.1 python scripts/generate-injury-sounds.py" }, "dependencies": { "@discord/embedded-app-sdk": "2.5.0", - "three": "0.185.1" + "three": "0.186.1" }, "devDependencies": { "@types/node": "26.1.1", - "@types/three": "0.185.1", + "@types/three": "0.186.0", "esbuild": "0.28.1", + "jpeg-js": "0.4.4", "jsdom": "29.1.1", + "pngjs": "7.0.0", "typescript": "7.0.2", "vite": "8.1.5", - "vitest": "4.1.10" + "vitest": "4.1.11" } } diff --git a/web/hands/replays/golden.json b/web/hands/replays/golden.json index 9f85187e..5ce0278f 100644 --- a/web/hands/replays/golden.json +++ b/web/hands/replays/golden.json @@ -29,7 +29,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "d21d442715479bbd46575cb3b4c9fdaf72dc89552460e6cc8a43c92434d642c7", + "checksum": "79766b22c72d9776f7e2722e7ff8c7e318509dcded3d36503b3aa70cb2c165d0", "events": [], "fighters": [ { @@ -50,6 +50,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -60,6 +62,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -102,6 +105,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -112,6 +117,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -144,7 +150,7 @@ "tick": 1 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 1 }, @@ -153,7 +159,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "902267c4132540716ea0895929298694b20b0bf9228ebfa8d4211511d7caf9e6", + "checksum": "de1a6e2c276b3a6021417d0c717893fd26625189512ed9b739cee3d3b6855c99", "events": [], "fighters": [ { @@ -174,6 +180,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -184,6 +192,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 1, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -226,6 +235,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -236,6 +247,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -268,7 +280,7 @@ "tick": 2 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 2 }, @@ -277,7 +289,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a10daf721d4ab838a8da2b2567f69f71cdcb56e0bf5f5083409c9705ab508d2c", + "checksum": "c03b865b0901eb4fcd4ebddccab47e7fe2707cc327346912fecff234207a8561", "events": [], "fighters": [ { @@ -298,6 +310,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -308,6 +322,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 2, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -350,6 +365,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -360,6 +377,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -392,7 +410,7 @@ "tick": 3 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 3 }, @@ -401,7 +419,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "f0e88a5b080fa1a1fad8f7613729ac5b275562d1771146da8f0ce1e312777acf", + "checksum": "33f624d69e5d7c950896629ff4e0398afbe78d5a6cb483f3bcd0d29f3ea3f2b1", "events": [], "fighters": [ { @@ -422,6 +440,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -432,6 +452,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 3, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -474,6 +495,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -484,6 +507,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -516,7 +540,7 @@ "tick": 4 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 4 }, @@ -525,7 +549,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "942994848b2817a17b99e9f54f34809ac61ae1a363ae2c99137cf4c31fb49822", + "checksum": "f826567353e5e4497f3b6c59e5d6290f743adbe2e5e5b71ccd3942282e4af137", "events": [], "fighters": [ { @@ -546,6 +570,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -556,6 +582,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 4, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -598,6 +625,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -608,6 +637,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -640,7 +670,7 @@ "tick": 5 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 5 }, @@ -649,7 +679,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "53d8d833e6dd1c08a7566be8f4da708178f09885b8908dac8da89d48e10d3245", + "checksum": "408e4343017ce544a0abdef19b185ef1eba98c3a434f407a53901519b32c4dcd", "events": [], "fighters": [ { @@ -670,6 +700,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -680,6 +712,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 5, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -722,6 +755,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -732,6 +767,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -764,7 +800,7 @@ "tick": 6 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 6 }, @@ -773,7 +809,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "cbda8267891b1c6c499373d644f7e17a4187dae9dcb24742113714a2d4edb5a7", + "checksum": "102381786e04e1a7ddc9b2fd69f03953a7c723e8d41bd254f9e8c30253ec51ee", "events": [], "fighters": [ { @@ -794,6 +830,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -804,6 +842,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 6, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -846,6 +885,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -856,6 +897,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -888,7 +930,7 @@ "tick": 7 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 7 }, @@ -897,7 +939,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a324afccd2189267fa7fc901d8b329440f625eafbac51b5b8387e1ce4da0fe83", + "checksum": "9405b93a294fadc4acf97ae76e91bcbdb67eb304b1f01cb4329463d4748ab548", "events": [], "fighters": [ { @@ -918,6 +960,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -928,6 +972,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 7, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -970,6 +1015,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -980,6 +1027,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1012,7 +1060,7 @@ "tick": 8 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 8 }, @@ -1021,7 +1069,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8211462ac823678d322c34e19a344cfd3494d051883d0793f3cd5d3e2e5fc55d", + "checksum": "1c589aae6813fc2a99c3942e4814f3219c7bca06db638dd8461bd5d58188b65d", "events": [], "fighters": [ { @@ -1042,6 +1090,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1052,6 +1102,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 8, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1094,6 +1145,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1104,6 +1157,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1136,7 +1190,7 @@ "tick": 9 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 9 }, @@ -1145,7 +1199,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "ad88349f0bdadf46035a21bf22c8cd873972f773fa3bbcd08b25805f11f14021", + "checksum": "16a339c5a15ea09a53e450bfd1436ea3d8920259da235ae13ff1706dbf9e3cb9", "events": [], "fighters": [ { @@ -1166,6 +1220,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1176,6 +1232,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 9, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1218,6 +1275,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1228,6 +1287,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1260,7 +1320,7 @@ "tick": 10 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 10 }, @@ -1269,7 +1329,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "861c0a242da4499c4af8ceb494da4897a4c736351493d57d56ee9967f5217c38", + "checksum": "954e0c472d5165c57f6c88810724749e85e5af2f26153901a4faa4107b3a3dcb", "events": [], "fighters": [ { @@ -1290,6 +1350,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1300,6 +1362,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 10, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1342,6 +1405,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1352,6 +1417,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1384,7 +1450,7 @@ "tick": 11 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 11 }, @@ -1393,7 +1459,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "e8ccb368429d8d71dd2b53ad46f0ab45e687cd864df3eae05815873fa74dedc0", + "checksum": "30a7e98a7148919981057de0372c7d10fe3b73f07434c8bb072ebb4cd72db05b", "events": [], "fighters": [ { @@ -1414,6 +1480,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1424,6 +1492,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 11, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1466,6 +1535,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1476,6 +1547,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1508,7 +1580,7 @@ "tick": 12 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 12 }, @@ -1517,7 +1589,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "fc324ade7e2c10167820e4e860015f949db82f3b70c8b0d5f26c4b65e29bf2ce", + "checksum": "f8b6686328491f8f2ee6499c131b6c7dedc418b9393552100500324be5cd0d39", "events": [], "fighters": [ { @@ -1538,6 +1610,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1548,6 +1622,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 12, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1590,6 +1665,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1600,6 +1677,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1632,7 +1710,7 @@ "tick": 13 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 13 }, @@ -1641,7 +1719,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "c15a51753112d37bf0c2a94e29acfd37db3ba84f0540e436d4ab15e578a743ed", + "checksum": "164f0b135e9e3041870194a459b8dd5d9e664d547c84bf6b877ee6984f05ecd7", "events": [], "fighters": [ { @@ -1662,6 +1740,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1672,6 +1752,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 13, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1714,6 +1795,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1724,6 +1807,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1756,7 +1840,7 @@ "tick": 14 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 14 }, @@ -1765,7 +1849,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "4e003b186d6141a9425ab392dd077bb99b7ba5b978e1332dfa8083e8e1c0df56", + "checksum": "8526e35d8af8036b64fab2a6c878ccb0412c146bd15d5db16812148d999fa401", "events": [], "fighters": [ { @@ -1786,6 +1870,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1796,6 +1882,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 14, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1838,6 +1925,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1848,6 +1937,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -1880,7 +1970,7 @@ "tick": 15 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 15 }, @@ -1889,7 +1979,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1d2f2a15b60cb45b874f1ffe8fcd39fc8ea785b773e68d39d3bf26a3d8d7210d", + "checksum": "5541ee70656c419eae45bddf454db3d83bccd45a13487aca2fad3193f44b5569", "events": [], "fighters": [ { @@ -1910,6 +2000,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1920,6 +2012,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 15, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -1962,6 +2055,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -1972,6 +2067,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2004,7 +2100,7 @@ "tick": 16 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 16 }, @@ -2013,7 +2109,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "84388bc89c8f9662f4da4ae27ecd5872838bc54ea9123d8fb10b45ed00637c39", + "checksum": "f804aa1e1062343517297df7fbedf374fb682fac8b11a393f4d38a71a51d1482", "events": [], "fighters": [ { @@ -2034,6 +2130,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2044,6 +2142,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 16, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2086,6 +2185,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2096,6 +2197,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2128,7 +2230,7 @@ "tick": 17 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 17 }, @@ -2137,7 +2239,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "13369a35ad1c4be145a962a2cf6dce7ef62bf2d46daeef6853c612f35370d6a9", + "checksum": "3ce17735cdf58c05ee1afabfd8daae827264a9450675d9a3197801eb5b7bed1c", "events": [], "fighters": [ { @@ -2158,6 +2260,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2168,6 +2272,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 17, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2210,6 +2315,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2220,6 +2327,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2252,7 +2360,7 @@ "tick": 18 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 18 }, @@ -2261,7 +2369,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "b6ee6fbc9fbb5fefc89a62250f40419c394ff0e29b03a3a6f8f7338fdfb7cd51", + "checksum": "baf088cff943a91d2d9aef390fdd09c77461c94a8620e7fcac631adc375a79d4", "events": [], "fighters": [ { @@ -2282,6 +2390,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2292,6 +2402,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 18, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2334,6 +2445,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2344,6 +2457,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2376,7 +2490,7 @@ "tick": 19 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 19 }, @@ -2385,7 +2499,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "6ee74fc3f20f25c6ccacfa8ac51beea08151464e62cb1d22bbf709c43f4763db", + "checksum": "2abab3e818918bdd6e6613050c3f4cdaaa6658800749a3e728042e6f5666585a", "events": [], "fighters": [ { @@ -2406,6 +2520,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2416,6 +2532,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 19, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2458,6 +2575,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2468,6 +2587,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2500,7 +2620,7 @@ "tick": 20 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 20 }, @@ -2509,7 +2629,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a08e3b2f8fc0d0457d8b2ecccabff74f22d0ab5ecf0c38961002b4ac56d3a25f", + "checksum": "61e4050b0df3fbd050ec384d0f9648bc9b52f0554a221ac8102d07e642141d04", "events": [], "fighters": [ { @@ -2530,6 +2650,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2540,6 +2662,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 20, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2582,6 +2705,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2592,6 +2717,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2624,7 +2750,7 @@ "tick": 21 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 21 }, @@ -2633,7 +2759,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "b6b5909057e89cc4ce7f2f2ba50f87a46ae8d04c6667f72f94fbc539acc9733f", + "checksum": "0b5768384f832314617b54a646753004c86ac5970206beaab0f140d40b433464", "events": [], "fighters": [ { @@ -2654,6 +2780,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2664,6 +2792,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 21, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2706,6 +2835,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2716,6 +2847,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2748,7 +2880,7 @@ "tick": 22 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 22 }, @@ -2757,7 +2889,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "0cc1594a7c6d9dafd198276f4fd0b3842a33be2c22e2199e81beca01acd7a87d", + "checksum": "1f54d3fdc91c9ac4c9d834806cece2dda9adc3b2e8ce49488129ad8ece1d0936", "events": [], "fighters": [ { @@ -2778,6 +2910,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2788,6 +2922,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 22, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2830,6 +2965,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2840,6 +2977,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2872,7 +3010,7 @@ "tick": 23 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 23 }, @@ -2881,7 +3019,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "cf43e7e0b122847a042e04e2caf89416f024c79c8c233ae8238502b728e95121", + "checksum": "6012f68de42ca0475f9507a8a2e292e9921d02ea98801f90ddc7fac9256fc75b", "events": [], "fighters": [ { @@ -2902,6 +3040,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2912,6 +3052,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 23, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -2954,6 +3095,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -2964,6 +3107,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -2996,7 +3140,7 @@ "tick": 24 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 24 }, @@ -3005,7 +3149,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a5c0febccc7813bacef9ec5dc9661cdbe44daffeeb3af6eea6cda48350b27c0c", + "checksum": "0ae8208503c82bc812fee8b8ecded926188c0acb3daf736ec5ba755c457fe40e", "events": [], "fighters": [ { @@ -3026,6 +3170,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3036,6 +3182,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 24, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3078,6 +3225,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3088,6 +3237,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3120,7 +3270,7 @@ "tick": 25 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 25 }, @@ -3129,7 +3279,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "d027826da6755a15e86d3fd6d546f0acfb5cfb906ee39846a523f0aa7b14841e", + "checksum": "ff32f2e05d0b020e07e85b21971aa98f3ee25cd8111a65832791f2de5f73d41e", "events": [], "fighters": [ { @@ -3150,6 +3300,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3160,6 +3312,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 25, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3202,6 +3355,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3212,6 +3367,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3244,7 +3400,7 @@ "tick": 26 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 26 }, @@ -3253,7 +3409,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "fcd4cd8eb6c5ad2992830b4164f6021bee1d301e0cf668baf6eaa7131d3b2755", + "checksum": "c78c09a8900b71dd264f06acade430fb75f2fd9862719f75337343e2859859ee", "events": [], "fighters": [ { @@ -3274,6 +3430,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3284,6 +3442,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 26, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3326,6 +3485,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3336,6 +3497,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3368,7 +3530,7 @@ "tick": 27 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 27 }, @@ -3377,7 +3539,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "ecdd7123988dc35108d6dad380a2f95895ab0f9439802b6b23e5feaa63a07883", + "checksum": "a888bff8cb907683f895b0c26a3992df56a5e5e515ad9024c99c3c32e9fb7789", "events": [], "fighters": [ { @@ -3398,6 +3560,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3408,6 +3572,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 27, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3450,6 +3615,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3460,6 +3627,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3492,7 +3660,7 @@ "tick": 28 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 28 }, @@ -3501,7 +3669,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "ed8c29094ba3d1bc0c2f28a1e4fcb07ad77f4913fb897505b011fe3a0c16a6f1", + "checksum": "2ec19283887ec620bc09c1dab49bcf6f270babe5e5790ef2bd4862985b33922a", "events": [], "fighters": [ { @@ -3522,6 +3690,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3532,6 +3702,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 28, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3574,6 +3745,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3584,6 +3757,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3616,7 +3790,7 @@ "tick": 29 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 29 }, @@ -3625,7 +3799,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "3b0287d5a521bbc41ccc8d2210924cbc11cd6634e520a70304688622bfc47147", + "checksum": "fd7596f2d3939c387f53a545e2146e8d5a70d56d47751e6d0d6acb493b9dbdc5", "events": [], "fighters": [ { @@ -3646,6 +3820,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3656,6 +3832,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 29, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3698,6 +3875,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3708,6 +3887,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3740,7 +3920,7 @@ "tick": 30 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 30 }, @@ -3749,7 +3929,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "31229cded21c6e09555a7cbbc220587a97030db0ad450273056702b5db0d09a7", + "checksum": "4bba12fb0c9d30e2324ab2d938bda1a4a25f29150565d2ecaab2c12a1c908458", "events": [], "fighters": [ { @@ -3770,6 +3950,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3780,6 +3962,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 30, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3822,6 +4005,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3832,6 +4017,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3864,7 +4050,7 @@ "tick": 31 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 31 }, @@ -3873,7 +4059,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8066fd2481cc01644539c2d0cca281e8df4ce9ef3fd8aa82fd4f2afbedc22bca", + "checksum": "a7e2604281f4dd6df5e3568921811585a12f292d96f1f0c764839ec3f7c00dbc", "events": [], "fighters": [ { @@ -3894,6 +4080,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3904,6 +4092,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 31, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -3946,6 +4135,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -3956,6 +4147,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -3988,7 +4180,7 @@ "tick": 32 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 32 }, @@ -3997,7 +4189,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "97fa9d3bb9970702e9d03a845ee08ba5f0aaba3dc502680278939c62c92732bf", + "checksum": "1d8624b77a995d03f314c0601397253fe89dd4fb585783cc2a46faedd51ed3f0", "events": [], "fighters": [ { @@ -4018,6 +4210,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4028,6 +4222,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 32, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4070,6 +4265,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4080,6 +4277,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4112,7 +4310,7 @@ "tick": 33 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 33 }, @@ -4121,7 +4319,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "b283f5d74e7ea2fa0ab5657575c23289917f8d66c5617c9b048f36d1c3bbc2d7", + "checksum": "6fcdc2dab202a4cf5aa9e455b73c41107b3bb684c646fa85ef999d7b882aa2e1", "events": [], "fighters": [ { @@ -4142,6 +4340,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4152,6 +4352,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 33, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4194,6 +4395,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4204,6 +4407,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4236,7 +4440,7 @@ "tick": 34 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 34 }, @@ -4245,7 +4449,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "48a792e3b88b88dff2106702d4fa19486073b75948496a8464c02926cd4cdec7", + "checksum": "38b77c909cac951109d7f02e7b8fb362f05b655cd66068424a0dba31c669f0a5", "events": [], "fighters": [ { @@ -4266,6 +4470,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4276,6 +4482,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 34, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4318,6 +4525,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4328,6 +4537,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4360,7 +4570,7 @@ "tick": 35 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 35 }, @@ -4369,7 +4579,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1b8e6b3634486e167f15c3cf3e8ae76c2eee122f4c6feab0273aaad0708b0055", + "checksum": "efa529d80553023827037261efa646f2f60513ddd3842deee1fb363cb3905a11", "events": [], "fighters": [ { @@ -4390,6 +4600,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4400,6 +4612,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 35, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4442,6 +4655,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4452,6 +4667,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4484,7 +4700,7 @@ "tick": 36 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 36 }, @@ -4493,7 +4709,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "048aee360ec609fc16a6da6493cb498d080f743dfd5f2b8b30e0d07606bc0719", + "checksum": "3ddcf973750658a70b49a9e7521c7a304e1b8fa1ab1e52ca168f526521ca366b", "events": [], "fighters": [ { @@ -4514,6 +4730,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4524,6 +4742,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 36, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4566,6 +4785,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4576,6 +4797,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4608,7 +4830,7 @@ "tick": 37 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 37 }, @@ -4617,7 +4839,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "0b0d11ec3a2f02efdd49de119f43350eb0e39ea7b953f4ea264cdb766709a5a5", + "checksum": "8fd5e97691d1f0fe8507d3a8b258b1af14281df0f56a63b698ee60e469999048", "events": [], "fighters": [ { @@ -4638,6 +4860,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4648,6 +4872,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 37, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4690,6 +4915,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4700,6 +4927,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4732,7 +4960,7 @@ "tick": 38 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 38 }, @@ -4741,7 +4969,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8367bf2a11cf987e55aa709957d6778c7d1ddd412ae7e66ebac8665386a2b0c8", + "checksum": "caf9ced612362ddef1f715372d3355bc806308d5906a28bb08e72ba99839ec86", "events": [], "fighters": [ { @@ -4762,6 +4990,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4772,6 +5002,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 38, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4814,6 +5045,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4824,6 +5057,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4856,7 +5090,7 @@ "tick": 39 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 39 }, @@ -4865,7 +5099,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1c495912a894f631ed1f1b8a4750d398a56ce4b88a8d503c5a04995369c84450", + "checksum": "0864173a68899a532b200a22b4d741484ec6fa581e0f451e88c4ca15f4d74c39", "events": [], "fighters": [ { @@ -4886,6 +5120,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4896,6 +5132,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 39, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -4938,6 +5175,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -4948,6 +5187,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -4980,7 +5220,7 @@ "tick": 40 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 40 }, @@ -4989,7 +5229,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "120c8f27eb065bd3ec3139ecca76c301a6806cdbf369b3d085e8ed56c201fbe1", + "checksum": "a15f075d9bdfd1a8fb624acd0aa770ce88f1ff74adaf2637c464fe6f2eafeff7", "events": [], "fighters": [ { @@ -5010,6 +5250,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5020,6 +5262,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 40, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5062,6 +5305,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5072,6 +5317,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5104,7 +5350,7 @@ "tick": 41 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 41 }, @@ -5113,7 +5359,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8dac9694b654d8a515c9ad7c2da3e449fb0d43583ec8daa956ba2ce9bd50ed31", + "checksum": "5a9f03e3d3a2936acfa90b5ff5fe2f0b0dcaddd7292d94df48958d4e57694055", "events": [], "fighters": [ { @@ -5134,6 +5380,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5144,6 +5392,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 41, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5186,6 +5435,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5196,6 +5447,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5228,7 +5480,7 @@ "tick": 42 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 42 }, @@ -5237,7 +5489,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "6e31d75565d7edaa57dc7677c3fbc39eb35331289db71ae25225b2635620296a", + "checksum": "c340198a48fe2b373550a6985081cf85d1d5fc441e3afc9d6284396e5b51de6c", "events": [], "fighters": [ { @@ -5258,6 +5510,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5268,6 +5522,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 42, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5310,6 +5565,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5320,6 +5577,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5352,7 +5610,7 @@ "tick": 43 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 43 }, @@ -5361,7 +5619,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "d3074d8f0b4b7dba00b04817d6c3255533eb972388b6ca8c2daa582d3d47e4bf", + "checksum": "b92be27b1d7cec9e021e20f7a45e052dadd6f4f8030969b85c8b7bce82633fde", "events": [], "fighters": [ { @@ -5382,6 +5640,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5392,6 +5652,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 43, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5434,6 +5695,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5444,6 +5707,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5476,7 +5740,7 @@ "tick": 44 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 44 }, @@ -5485,7 +5749,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "71dc6671112dafc43117ae4fdafa694001d0ab3e4ca52360fecec9d745878fa8", + "checksum": "bd9f88879f742cd99c042e2b53f3b24b7d01f44ef5aec6a164a19491987f3b5e", "events": [], "fighters": [ { @@ -5506,6 +5770,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5516,6 +5782,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 44, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5558,6 +5825,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5568,6 +5837,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5600,7 +5870,7 @@ "tick": 45 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 45 }, @@ -5609,7 +5879,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "4c68e89568eea8aa7327de8046f10c02b236881e180fbb8006eb2f457404d8ee", + "checksum": "a3abae2dde6746ade2489134c9cabe6d1168782a6c21ba1189d554af4749370a", "events": [], "fighters": [ { @@ -5630,6 +5900,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5640,6 +5912,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 45, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5682,6 +5955,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5692,6 +5967,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5724,7 +6000,7 @@ "tick": 46 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 46 }, @@ -5733,7 +6009,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "23791c8918df44f0ebb1f51826f57b2c8bb1e9382d0cf40864a020a64c355604", + "checksum": "46761be6c7643ea676cf83dc8ad70895b95ca50e0f4405dc46c91a43aed46a1a", "events": [], "fighters": [ { @@ -5754,6 +6030,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5764,6 +6042,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 46, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5806,6 +6085,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5816,6 +6097,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5848,7 +6130,7 @@ "tick": 47 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 47 }, @@ -5857,7 +6139,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "3d0a96a1fcc37b3c6be8cbe06665f7fdf9b9ab32fe30e5bfa30dc05fd5beb8ea", + "checksum": "9633402a915e804f043a259c4bb1a10a7b39346dc79f99966a7d50fa506116b5", "events": [], "fighters": [ { @@ -5878,6 +6160,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5888,6 +6172,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 47, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -5930,6 +6215,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -5940,6 +6227,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -5972,7 +6260,7 @@ "tick": 48 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 48 }, @@ -5981,7 +6269,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "811ae48d229b4b307bee21d4f3f5e8ea8990d114c8e1e68bfa2f180f204553d5", + "checksum": "1a5a884e6c95489dc95fa2e0952d713112ee058200116370dc40a39538d0e636", "events": [], "fighters": [ { @@ -6002,6 +6290,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6012,6 +6302,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 48, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6054,6 +6345,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6064,6 +6357,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6096,7 +6390,7 @@ "tick": 49 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 49 }, @@ -6105,7 +6399,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "7e3d2d4663d2e073fc602088cd1b0d07b335a33f402c039610df76a4169f959b", + "checksum": "cdbcdc9b4f3295823a21a2298d7ba574a528a1b3b4ae3943f6afe810d5fa390c", "events": [], "fighters": [ { @@ -6126,6 +6420,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6136,6 +6432,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 49, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6178,6 +6475,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6188,6 +6487,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6220,7 +6520,7 @@ "tick": 50 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 50 }, @@ -6229,7 +6529,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "7d10c716fef30b40a957b4ba9f0b8461794d3a6ea70aa0c18bcc128aacb6341b", + "checksum": "c94886af72d7de8969c652d02ce93048e85fc6672a44f5e0431ac4b6be358c62", "events": [], "fighters": [ { @@ -6250,6 +6550,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6260,6 +6562,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 50, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6302,6 +6605,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6312,6 +6617,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6344,7 +6650,7 @@ "tick": 51 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 51 }, @@ -6353,7 +6659,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "02715482231c7e21828d9659ace10dff3cab7d532ac8c855a863f7884f6071c4", + "checksum": "98dce9a9490e81924da180ebdf319fee3073a87fe3df26123882caf93c64a6b2", "events": [], "fighters": [ { @@ -6374,6 +6680,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6384,6 +6692,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 51, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6426,6 +6735,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6436,6 +6747,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6468,7 +6780,7 @@ "tick": 52 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 52 }, @@ -6477,7 +6789,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "632adb7c639540f4ce271a8d1e24b92020599a854e98eb6a4b0e477e36789d7d", + "checksum": "e1a53c87c6ce9046cb33b405e1d57d112f429061805c2cce049a92483e6537a5", "events": [], "fighters": [ { @@ -6498,6 +6810,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6508,6 +6822,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 52, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6550,6 +6865,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6560,6 +6877,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6592,7 +6910,7 @@ "tick": 53 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 53 }, @@ -6601,7 +6919,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "165323b2b504149adfd72435b00a8099ef59b01217fa7f93dda6591a094f2238", + "checksum": "472c8db0252fc995b15ef0cdf06fa226a99f5cf086458155fe41aae962557b46", "events": [], "fighters": [ { @@ -6622,6 +6940,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6632,6 +6952,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 53, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6674,6 +6995,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6684,6 +7007,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6716,7 +7040,7 @@ "tick": 54 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 54 }, @@ -6725,7 +7049,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a37fb675c36843d153c6a947aad98ef64e5bb77ab897aa0bf3a1f7c6f13fdb98", + "checksum": "674b0c2230f9be8ecc9c32c375497269b4d9218c86a8f14342473cfb57075b12", "events": [], "fighters": [ { @@ -6746,6 +7070,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6756,6 +7082,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 54, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6798,6 +7125,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6808,6 +7137,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6840,7 +7170,7 @@ "tick": 55 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 55 }, @@ -6849,7 +7179,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a2e14aa5b19f6351c330d1951dca992e142eeef107e50be3598aec0a405c32ec", + "checksum": "c41efd2170f700ee2d405117dfe744ddc7a9f74d0c1cbe76adabf50fae12d3e9", "events": [], "fighters": [ { @@ -6870,6 +7200,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6880,6 +7212,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 55, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -6922,6 +7255,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -6932,6 +7267,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -6964,7 +7300,7 @@ "tick": 56 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 56 }, @@ -6973,7 +7309,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "e179c2b22d7077ee7694bc502137e74d5f72ca289f4dfadfcedfd4fc3a535f0d", + "checksum": "b3335b27f1149c24141d1375e2fb7510cdeed7d3dcfe21c9575cefa2b116dbf2", "events": [], "fighters": [ { @@ -6994,6 +7330,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7004,6 +7342,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 56, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7046,6 +7385,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7056,6 +7397,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7088,7 +7430,7 @@ "tick": 57 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 57 }, @@ -7097,7 +7439,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "cb5ca80a94bb2b13b199d24c8eabe30dbfa0be95013fa53a4271d78e41014624", + "checksum": "6fc4316409f2b74c9675c86af4fb418fd9315bba6903d7d4b10093b6e292d127", "events": [], "fighters": [ { @@ -7118,6 +7460,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7128,6 +7472,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 57, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7170,6 +7515,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7180,6 +7527,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7212,7 +7560,7 @@ "tick": 58 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 58 }, @@ -7221,7 +7569,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "82237fe2c4fc82a6c8bab3973e6f0b055f561c694784cffb961f7172017f0221", + "checksum": "c4fc7264c0237db763d578ee1a10c2d556169244534aacd788dd2027a61e11d3", "events": [], "fighters": [ { @@ -7242,6 +7590,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7252,6 +7602,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 58, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7294,6 +7645,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7304,6 +7657,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7336,7 +7690,7 @@ "tick": 59 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 59 }, @@ -7345,7 +7699,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "c44e3a7c7ecc6eea1a9aafd18f0df25b9bdfe518a113217ac89d9b5bf868336d", + "checksum": "61fa36a9e7b235c8cceacd5b4adc50477f09e9baee31dc6ad5c8bcfdfa1a9cd7", "events": [], "fighters": [ { @@ -7366,6 +7720,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7376,6 +7732,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 59, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7418,6 +7775,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7428,6 +7787,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7460,7 +7820,7 @@ "tick": 60 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 60 }, @@ -7469,7 +7829,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "0ae7bbd97fc1d2bdc3c496575617bcb86def4cc4f77eef7ee404609c98cf1aaf", + "checksum": "c392aea37f6a317d4993bdb844e0f243d6d1c0c60612a163b4f543b7b35366c7", "events": [], "fighters": [ { @@ -7490,6 +7850,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7500,6 +7862,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 60, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7542,6 +7905,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7552,6 +7917,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7584,7 +7950,7 @@ "tick": 61 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 61 }, @@ -7593,7 +7959,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1a444fdc767b5c1eeaa6794f2977d68447261b5003d5c9991da7b6296a8f8183", + "checksum": "1f8e762d943170d38ffe9d72ff851f337ec1a88d270674bbdb56f3c139f98eba", "events": [], "fighters": [ { @@ -7614,6 +7980,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7624,6 +7992,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 61, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7666,6 +8035,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7676,6 +8047,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7708,7 +8080,7 @@ "tick": 62 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 62 }, @@ -7717,7 +8089,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "b49e811cecd5465f54e0cede88d6379bf02ef1dce147c3e795d20caff0ef9ecc", + "checksum": "affc5db381799946f1b243169e8388c80c4af8fcbe9b9a200f91dbfb3dbce111", "events": [], "fighters": [ { @@ -7738,6 +8110,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7748,6 +8122,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 62, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7790,6 +8165,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7800,6 +8177,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7832,7 +8210,7 @@ "tick": 63 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 63 }, @@ -7841,7 +8219,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "f98a4dd2f2a97b699628dd79bbceee85841d442ddfadfb8ccc491b1bd248401b", + "checksum": "c7dde928407a640e71bdbab86abae920869257ec647d54daf5fc72f187052bae", "events": [], "fighters": [ { @@ -7862,6 +8240,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7872,6 +8252,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 63, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -7914,6 +8295,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7924,6 +8307,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -7956,7 +8340,7 @@ "tick": 64 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 64 }, @@ -7965,7 +8349,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "f14df440eae734d60a704b4d4cf740aa22960b81af3b20c2af7daf67dc47cef7", + "checksum": "7848300e6aece7cca4370712246eb69f02c1e711f0b030f695adf14a5ed9882a", "events": [], "fighters": [ { @@ -7986,6 +8370,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -7996,6 +8382,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 64, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -8038,6 +8425,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8048,6 +8437,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8080,7 +8470,7 @@ "tick": 65 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 65 }, @@ -8089,7 +8479,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "b15aa8557bcf6da62d8a87b22f53949ae8d5e553ba4cc846cd6d05b2805de574", + "checksum": "918ce15996efbd24ad1baefb580f5ce468d6af77a3f934e9ae953677e5a42b2b", "events": [], "fighters": [ { @@ -8110,6 +8500,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8120,6 +8512,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 65, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -8162,6 +8555,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8172,6 +8567,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8204,7 +8600,7 @@ "tick": 66 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 66 }, @@ -8213,7 +8609,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "3015b59ae1e2a43c3730e2313d156bacd896fef4673de76e35ae1139593d23f1", + "checksum": "1cf08f75b388f033b1bf7c52402cdd99b178d0db63f579af575c71c68ec8e5b2", "events": [], "fighters": [ { @@ -8234,6 +8630,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8244,6 +8642,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 66, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -8286,6 +8685,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8296,6 +8697,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8328,7 +8730,7 @@ "tick": 67 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 67 }, @@ -8337,7 +8739,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "36cbc42cb3820c05c853fa0854e002e6d4cddc5cf7f005ddbdbefdb457e3cf48", + "checksum": "a875adde02d0fd76eaaae2acb0844839f9a66b83ab89cf454aa25b167cac2c8b", "events": [], "fighters": [ { @@ -8358,6 +8760,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8368,6 +8772,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 67, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -8410,6 +8815,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8420,6 +8827,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8452,7 +8860,7 @@ "tick": 68 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 68 }, @@ -8461,7 +8869,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "32027238370283b5a071ceaa727df20341812f93c8d14ea4df44834d0bfc8050", + "checksum": "f25ca7c75063ac897c69287530816a6ee43980e6bb65b52c1a92854aeb01d4d0", "events": [], "fighters": [ { @@ -8482,6 +8890,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8492,6 +8902,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 67, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -8534,6 +8945,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8544,6 +8957,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8576,7 +8990,7 @@ "tick": 69 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 69 }, @@ -8585,7 +8999,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "2cfa43be61fe9d7fd75f0004ea6b3cab1a9d422eec4810f41b0239d07e77a82c", + "checksum": "3b9382a37aef62ae45f68c463b27843c9b2d888f7d55b8bfc2bd590078906c10", "events": [], "fighters": [ { @@ -8606,6 +9020,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8616,6 +9032,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 67, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -8658,6 +9075,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8668,6 +9087,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8700,7 +9120,7 @@ "tick": 70 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 70 }, @@ -8709,7 +9129,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "797ce0a7d14124cdef0bba9746416270870c4e2d44d7dc262aa12a4b9c7eda22", + "checksum": "4c331e6738e4dc9ec865b74783f31d8fac227184292a00dc31face0fbc0190fe", "events": [], "fighters": [ { @@ -8730,6 +9150,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8740,6 +9162,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 67, "maximum_stamina": 1000, "player_id": "one", "poise": 600, @@ -8782,6 +9205,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8792,6 +9217,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8824,7 +9250,7 @@ "tick": 71 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 71 }, @@ -8844,7 +9270,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8caf706e92c426b9caa3c67afca1556e9573b2bfe5ee7e4dc51d4d0d9a0ed98f", + "checksum": "772bc6d7c01512d8307c457a76264c9c09f1c5b9d7f27c62a7622bc011dd2770", "events": [ { "action_id": "one@72", @@ -8878,6 +9304,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8888,6 +9316,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -8930,6 +9359,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -8940,6 +9371,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -8972,7 +9404,7 @@ "tick": 72 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 72 }, @@ -8992,7 +9424,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "016334516eff9c863dd4610a27354d019f06dd70276379307844bbb85f218819", + "checksum": "0707844ccbefb4db659a54da119f934f47ffcc22f588bce8ccda7345923d8bdb", "events": [], "fighters": [ { @@ -9013,6 +9445,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9023,6 +9457,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -9065,6 +9500,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9075,6 +9512,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -9107,7 +9545,7 @@ "tick": 73 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 73 }, @@ -9127,7 +9565,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "c6af354f2687e32877b1285bae2bca0bbc6d74f190317977434ce900a7b2b85d", + "checksum": "a95a6b944bdcf0ddd4db0ba32bbebfc8e4e2197669f22f6e4c69c028e5c04564", "events": [], "fighters": [ { @@ -9148,6 +9586,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9158,6 +9598,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -9200,6 +9641,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9210,6 +9653,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 600, @@ -9242,7 +9686,7 @@ "tick": 74 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 74 }, @@ -9262,7 +9706,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "325327d13fd5f68d06cb89e23438e06b292f27ecf0f2e2618c4c4e57c2bc66e1", + "checksum": "589b81316dc89f5ad6278d94644bff58a24154355728df0f3ed65e700650c313", "events": [ { "action_id": "one@72", @@ -9308,6 +9752,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9318,6 +9764,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -9360,6 +9807,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9370,6 +9819,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 566, @@ -9402,7 +9852,7 @@ "tick": 75 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 75 }, @@ -9422,7 +9872,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "602731918cd60fbd6beda8e0bcb69a86fabe6956338c0f0635e6b6ec9db7b99d", + "checksum": "096e48035830fef8d818f5af0ea55fa1311834317e82437e729248e135c1f355", "events": [], "fighters": [ { @@ -9443,6 +9893,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9453,6 +9905,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -9495,6 +9948,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9505,6 +9960,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 567, @@ -9537,7 +9993,7 @@ "tick": 76 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 76 }, @@ -9557,7 +10013,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "688173563547bcd78e7047b24d8ba4dc28c56c34843b4382c1c397f93b43db6e", + "checksum": "30f66859627a2ebdf7720c1308b851ba1c3962d9b3bcaea1af2ab89d09e9452b", "events": [], "fighters": [ { @@ -9578,6 +10034,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9588,6 +10046,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -9630,6 +10089,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9640,6 +10101,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 568, @@ -9672,7 +10134,7 @@ "tick": 77 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 77 }, @@ -9692,7 +10154,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "ef480a95a09c4cfc422b4472b706adc73c8fc7f3587de81ab5a360c9450e9ab1", + "checksum": "cc34e9e2446ae489ba3892ed242c2e2df750e16f44e14abd2a32460a09e3cbc5", "events": [], "fighters": [ { @@ -9713,6 +10175,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9723,6 +10187,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -9765,6 +10230,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9775,6 +10242,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 569, @@ -9807,7 +10275,7 @@ "tick": 78 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 78 }, @@ -9827,7 +10295,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1bbed9662798a5ce8ca6ac49ea68dea8097a3b94b0b4d4b20869ed0384be85dd", + "checksum": "f13ef5e652cedf0a845e327507b2cfe09f23e6006b8a1314a5a572287f4b66f2", "events": [], "fighters": [ { @@ -9848,6 +10316,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9858,6 +10328,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -9900,6 +10371,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9910,6 +10383,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 570, @@ -9942,7 +10416,7 @@ "tick": 79 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 79 }, @@ -9962,7 +10436,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "577ad0ce453c774325631bd10a315f74bd3b22b04c10b1c80f44977a8cb8f532", + "checksum": "e30e4fb8c2bc641a4e9353830830cd4a8e089ddfbe7abb16a58e299a88fd39f8", "events": [], "fighters": [ { @@ -9983,6 +10457,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -9993,6 +10469,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10035,6 +10512,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10045,6 +10524,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 571, @@ -10077,7 +10557,7 @@ "tick": 80 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 80 }, @@ -10097,7 +10577,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "754f595aa7441fa8fbc714f52c452c21dfc6d205fa9b0baa36fe4cbc2f50a830", + "checksum": "cb5f0be352c9c08c4d0eff8e43b0d6e9215a8e475b2cf88cbfa08d847d366165", "events": [], "fighters": [ { @@ -10118,6 +10598,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10128,6 +10610,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10170,6 +10653,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10180,6 +10665,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 572, @@ -10212,7 +10698,7 @@ "tick": 81 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 81 }, @@ -10232,7 +10718,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "4ffa172281582fc1db17822b09eb61100662b5d95c5076e69892076dc71bcc64", + "checksum": "06619441e1de9fd3256371a50dd918a7e7fd56f3eace853412470c96f9052efb", "events": [], "fighters": [ { @@ -10253,6 +10739,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10263,6 +10751,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10305,6 +10794,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10315,6 +10806,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 573, @@ -10347,7 +10839,7 @@ "tick": 82 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 82 }, @@ -10367,7 +10859,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "2f22d042c15ab6f34770bff0adb45e00e0ee9bfc59657794edc8821bb4f9e3cf", + "checksum": "bf10d3a9b570bca14f42f1f389b4c0b2b0726bcb3b04dcf5420108c15ba9e8c8", "events": [], "fighters": [ { @@ -10388,6 +10880,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10398,6 +10892,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10440,6 +10935,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10450,6 +10947,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 574, @@ -10482,7 +10980,7 @@ "tick": 83 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 83 }, @@ -10491,7 +10989,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "bfc1eb1df773f5489b741ec42ea3d315219cb67cac0397f8a62b736be5c947fc", + "checksum": "a2ab531be90b309e185017a3f431f8a07ada1b02a22f5c9bfa1fdee6f1cb67d8", "events": [], "fighters": [ { @@ -10512,6 +11010,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10522,6 +11022,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10564,6 +11065,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10574,6 +11077,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 575, @@ -10606,7 +11110,7 @@ "tick": 84 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 84 }, @@ -10615,7 +11119,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "59fd6f3052030561a76b5cce8cd923a6530933ab6896b65e4ecf7aff080f7545", + "checksum": "543f8dd95245a77f1195e965d225006868e9a5a24db6f8630fa3a7c28ce5518e", "events": [], "fighters": [ { @@ -10636,6 +11140,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10646,6 +11152,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 68, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10688,6 +11195,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10698,6 +11207,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 576, @@ -10730,7 +11240,7 @@ "tick": 85 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 85 }, @@ -10739,7 +11249,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "32e9a72ffe71ce5cba4afe5ae9a0ae27e5bbefd54d4b0f25758ba558de20b434", + "checksum": "761b9d5bbbea017a0a44e06de09779888e5907e16992c632ed5493d6aec5b70f", "events": [], "fighters": [ { @@ -10760,6 +11270,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10770,6 +11282,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 69, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10812,6 +11325,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10822,6 +11337,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 577, @@ -10854,7 +11370,7 @@ "tick": 86 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 86 }, @@ -10863,7 +11379,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "add9b66ea5b6e5fd4f0edc6f7c0990b8a43efa70be2fee0b051554714e4a8869", + "checksum": "fca60322f40deda09fbc0a19bc4a7cc1ddb19379c52d88713e769b5156baeb2e", "events": [], "fighters": [ { @@ -10884,6 +11400,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10894,6 +11412,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 70, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -10936,6 +11455,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -10946,6 +11467,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 578, @@ -10978,7 +11500,7 @@ "tick": 87 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 87 }, @@ -10987,7 +11509,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "fc2ecb41cfb92990403fa78eb1be6ac2c0710cded9108aae6f146fdf49e234a0", + "checksum": "a3bbdda8114bd6c112ba3f00619aa996fbcb358547cd4e96488d0301345e259a", "events": [], "fighters": [ { @@ -11008,6 +11530,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11018,6 +11542,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 71, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11060,6 +11585,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11070,6 +11597,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 579, @@ -11102,7 +11630,7 @@ "tick": 88 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 88 }, @@ -11111,7 +11639,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "4a03a406b62811c7f3adbbfbf0bf77fef7ebcd031caf6389e7e21faebe40c4e1", + "checksum": "84e1e2e05397e36ae94afa6a95c4e38bd5c7b7f85dc22e6b296930bc4cd2c9ec", "events": [], "fighters": [ { @@ -11132,6 +11660,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11142,6 +11672,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 72, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11184,6 +11715,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11194,6 +11727,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 580, @@ -11226,7 +11760,7 @@ "tick": 89 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 89 }, @@ -11235,7 +11769,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1e672400f23d7316b6fffb90fc98eaf6da2795591cb66c8bb12094a8b0c1c565", + "checksum": "5b4e29f1b30bec348194b79de695d08751cdfeff4bc41d047195a5249e6c3b88", "events": [], "fighters": [ { @@ -11256,6 +11790,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11266,6 +11802,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 73, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11308,6 +11845,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11318,6 +11857,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 581, @@ -11350,7 +11890,7 @@ "tick": 90 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 90 }, @@ -11359,7 +11899,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "30ae7be774917c5722dfe0a0f52c5c79c45f0d18290d6cb958f1ec84014c55cd", + "checksum": "167977262da1a8831ba53df08221dd455639eae7d2ea9f146df44207ecff003f", "events": [], "fighters": [ { @@ -11380,6 +11920,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11390,6 +11932,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 74, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11432,6 +11975,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11442,6 +11987,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 582, @@ -11474,7 +12020,7 @@ "tick": 91 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 91 }, @@ -11483,7 +12029,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "9ca0e661c4618f48925e745628ca1c0b4e97fa82df9df1aeecba23d84dac4dc0", + "checksum": "05238f5204e887a66e8ddddf23571163090e0faccd47dde5f3bae101788c5819", "events": [], "fighters": [ { @@ -11504,6 +12050,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11514,6 +12062,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 75, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11556,6 +12105,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11566,6 +12117,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 583, @@ -11598,7 +12150,7 @@ "tick": 92 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 92 }, @@ -11607,7 +12159,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "fdcfe8037013a736cb66afe7aa3840045caf872a61e7d2d22f382d4deec260d7", + "checksum": "be2c9f27c594727992142d6869dae1547a04a25f887b1c81bb5ce48c45670dea", "events": [], "fighters": [ { @@ -11628,6 +12180,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11638,6 +12192,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 76, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11680,6 +12235,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11690,6 +12247,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 584, @@ -11722,7 +12280,7 @@ "tick": 93 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 93 }, @@ -11731,7 +12289,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "5a1e833ed3b07955ab9083e3b6a06e302d043b4446933893e61d9ae70cb3b3f4", + "checksum": "fbf43e7cc6187f8b4cb182babc2513e06be557f8c3f985aaf4875799b42949dd", "events": [], "fighters": [ { @@ -11752,6 +12310,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11762,6 +12322,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 77, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11804,6 +12365,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11814,6 +12377,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 585, @@ -11846,7 +12410,7 @@ "tick": 94 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 94 }, @@ -11855,7 +12419,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "6605493ec173b976d5cb678596941e121ef70439ef8edb0ce94bb00f64bb5138", + "checksum": "dbaa395332b17cdb682fb326dfde52b46cf97337a73c40bd10ec983673387fbf", "events": [], "fighters": [ { @@ -11876,6 +12440,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11886,6 +12452,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 78, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -11928,6 +12495,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -11938,6 +12507,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 586, @@ -11970,7 +12540,7 @@ "tick": 95 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 95 }, @@ -11979,7 +12549,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "f1d7d4e0f6d65b8339b8415463b34bd850b03500e0e9bb07f364117b60329f1c", + "checksum": "e1b921fcca1cc26e93b508c49496f3675677574f829f1b18f4f14b0f39c7764f", "events": [], "fighters": [ { @@ -12000,6 +12570,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12010,6 +12582,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 79, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -12052,6 +12625,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12062,6 +12637,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 587, @@ -12094,7 +12670,7 @@ "tick": 96 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 96 }, @@ -12103,7 +12679,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "80fd84a73fa7ef4521a2b0c4e5003fd963ae1a31f0dbe94160ab0004d4d4ac20", + "checksum": "dbde59f45c0cee86a0c3a7283ad40a9e5a139f1373224ecd6ae69c0b48b3e0a2", "events": [], "fighters": [ { @@ -12124,6 +12700,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12134,6 +12712,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 80, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -12176,6 +12755,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12186,6 +12767,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 588, @@ -12218,7 +12800,7 @@ "tick": 97 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 97 }, @@ -12227,7 +12809,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "c1d36bc000e2a9e13f2f4187cf2e75f19d2e5fa7225cf3d922a91d47a7d385e7", + "checksum": "db8608d8a6b0e483e9b554dbb4aa0cfc2913155ce8503f95d730dac13ed03745", "events": [], "fighters": [ { @@ -12248,6 +12830,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12258,6 +12842,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 81, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -12300,6 +12885,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12310,6 +12897,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 589, @@ -12342,7 +12930,7 @@ "tick": 98 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 98 }, @@ -12351,7 +12939,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "0f711d891960744591d59499d8b6656e6ebc63c69211bc656eab0b1c78999f0a", + "checksum": "3119334d472fc7d7c1b858ceedf9beb317ebec69286453f018a3f337fa22c566", "events": [], "fighters": [ { @@ -12372,6 +12960,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12382,6 +12972,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 82, "maximum_stamina": 999, "player_id": "one", "poise": 600, @@ -12424,6 +13015,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12434,6 +13027,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 590, @@ -12466,7 +13060,7 @@ "tick": 99 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 99 }, @@ -12486,7 +13080,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "5f11d60e0da14e642a392950dfa7ff2c1fcfdddc0472fceb132ca63efbac8148", + "checksum": "362ca9db1d2c91ba7e48d6b4a9d7d37a2b42e6d94ca38deaa2cfe6da2ce84b9a", "events": [ { "action_id": "one@100", @@ -12520,6 +13114,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12530,6 +13126,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -12572,6 +13169,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12582,6 +13181,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 591, @@ -12614,7 +13214,7 @@ "tick": 100 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 100 }, @@ -12634,7 +13234,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "3afa151f98df682aeb9c3070b845a8c1100ab40148b519e84a89e44d0d20eec6", + "checksum": "368faecde2745982b39f149ac256719f49f409cec2c704a44d955c40529fef82", "events": [], "fighters": [ { @@ -12655,6 +13255,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12665,6 +13267,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -12707,6 +13310,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12717,6 +13322,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 592, @@ -12749,7 +13355,7 @@ "tick": 101 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 101 }, @@ -12769,7 +13375,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "0fb6b1ac7a345b9d4b564b3693904effaca9da3cf497704026f099e279f67f1b", + "checksum": "738cb1ee36416d28604bb88d0b66c216c41ef307ef23f33244b6271288f4b8c2", "events": [], "fighters": [ { @@ -12790,6 +13396,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12800,6 +13408,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -12842,6 +13451,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12852,6 +13463,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 593, @@ -12884,7 +13496,7 @@ "tick": 102 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 102 }, @@ -12904,7 +13516,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "04a4c6da67ebc470d248dc7b0f0aed251c9f444ce1294138d4df248dba965620", + "checksum": "9d2d83108224e52739c68ce29da0a21249acbf4e9f01b1324c659c19782b583b", "events": [ { "action_id": "one@100", @@ -12950,6 +13562,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -12960,6 +13574,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13002,6 +13617,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13012,6 +13629,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 559, @@ -13044,7 +13662,7 @@ "tick": 103 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 103 }, @@ -13064,7 +13682,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "e16884ab644761fe4f9529bae093f0ef9898d0edebcd8e849b5ed1ad8350b21f", + "checksum": "bfe18cf01ccc7408b63bb97f0bc4e075be8b83d6729143472ab4051c66b1f8f2", "events": [], "fighters": [ { @@ -13085,6 +13703,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13095,6 +13715,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13137,6 +13758,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13147,6 +13770,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 560, @@ -13179,7 +13803,7 @@ "tick": 104 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 104 }, @@ -13199,7 +13823,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "42c3fb3fb3ef7d5adbf58f07aa1eb00d5f77f77d1df103be8c2cfbfd9580c40c", + "checksum": "6a0be234b7a7c4330c2bd0c428310ee795a18f7b9769b6310432951f119c9fa5", "events": [], "fighters": [ { @@ -13220,6 +13844,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13230,6 +13856,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13272,6 +13899,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13282,6 +13911,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 561, @@ -13314,7 +13944,7 @@ "tick": 105 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 105 }, @@ -13334,7 +13964,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "5bd7570b2f74b91e2656e08dfc7ad8d89bb8d07f7b25c1971f0a14c94b2a8487", + "checksum": "4db80ad3694b7ed2d76e1ae3d41a3d6ab41b2469cd3f15117e1c36002fce53d0", "events": [], "fighters": [ { @@ -13355,6 +13985,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13365,6 +13997,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13407,6 +14040,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13417,6 +14052,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 562, @@ -13449,7 +14085,7 @@ "tick": 106 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 106 }, @@ -13469,7 +14105,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "89f610211e110c744d2a4be7c0530ddaeb0f330c63611027005f3a0cc05b9012", + "checksum": "217ebf75d8d34397e9dedb9166c393e78d268de62ba4595e9749b9c78cd78294", "events": [], "fighters": [ { @@ -13490,6 +14126,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13500,6 +14138,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13542,6 +14181,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13552,6 +14193,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 563, @@ -13584,7 +14226,7 @@ "tick": 107 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 107 }, @@ -13604,7 +14246,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "0d1118da7a339a83df12d1a879b85a32816d2c6ceeb46c06cac16217a294a5af", + "checksum": "c926639046b303712d7c4ec7d9f1067839b520fd4a59a067b41c4dce58489cda", "events": [], "fighters": [ { @@ -13625,6 +14267,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13635,6 +14279,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13677,6 +14322,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13687,6 +14334,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 564, @@ -13719,7 +14367,7 @@ "tick": 108 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 108 }, @@ -13739,7 +14387,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "3ebe69086af4fdfc78e0921f4f0cd2fb872fcbe0b988821973c525a3b8c13294", + "checksum": "a8d09740ab1ca6c7bab72d0a4edbcdb50b743c77f579ea3d6b1bfaeab9feb5ac", "events": [], "fighters": [ { @@ -13760,6 +14408,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13770,6 +14420,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13812,6 +14463,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13822,6 +14475,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 565, @@ -13854,7 +14508,7 @@ "tick": 109 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 109 }, @@ -13874,7 +14528,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "f75cd2cfce5e7434133a90e700ec86a5799af72c0a9823aa6b5d81ed293fd869", + "checksum": "e671932e1a140847e6c590ff1cfa227e75bbe07184a43ae453e7adbfa91cd21d", "events": [], "fighters": [ { @@ -13895,6 +14549,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13905,6 +14561,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -13947,6 +14604,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -13957,6 +14616,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 566, @@ -13989,7 +14649,7 @@ "tick": 110 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 110 }, @@ -14009,7 +14669,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "96b62fd63b8c59fcac62a0e19f567ec2855e89a5826a189a3192a4297a60c287", + "checksum": "a9e2bacdbc5afeb9b0fa559e50a121795dcc0dfd62821e945986e853b395dd62", "events": [], "fighters": [ { @@ -14030,6 +14690,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14040,6 +14702,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -14082,6 +14745,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14092,6 +14757,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 567, @@ -14124,7 +14790,7 @@ "tick": 111 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 111 }, @@ -14133,7 +14799,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8306df63adc353b7c75115257d2131445ec512f673908fc8578250a73f84b044", + "checksum": "0a0a113fba1e4d69dd08efc723ce43191839756fae21bb305353ceeb7e46bece", "events": [], "fighters": [ { @@ -14154,6 +14820,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14164,6 +14832,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -14206,6 +14875,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14216,6 +14887,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 568, @@ -14248,7 +14920,7 @@ "tick": 112 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 112 }, @@ -14257,7 +14929,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "9e9f007c54def9449fafc7f2facfd3d5f5a259171f091bc3f7131403acebf5ef", + "checksum": "5596592f5cf8d24d605e17e7ae143f983e135d31995b6e2e00d6fa456dea6023", "events": [], "fighters": [ { @@ -14278,6 +14950,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14288,6 +14962,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 83, "maximum_stamina": 998, "player_id": "one", "poise": 600, @@ -14330,6 +15005,8 @@ "deductions": 0, "defense": "guard_high", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14340,6 +15017,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 569, @@ -14372,7 +15050,7 @@ "tick": 113 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 113 }, @@ -14392,7 +15070,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "984c3ef767b48fc19d2f76b08c59710ad36ba16e9e50382f1eadbec5c22b46f3", + "checksum": "d6dab527b3da5aad0862f4bbf2dbb07c5d7fc4241353e6d96f25501f16ffd784", "events": [ { "action_id": "one@114", @@ -14426,6 +15104,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14436,6 +15116,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -14478,6 +15159,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14488,6 +15171,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 2, @@ -14520,7 +15204,7 @@ "tick": 114 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 114 }, @@ -14540,7 +15224,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "40cbd1f2b71327d27566db861d80f5e4c35328bd7a27864ac6b150f051482d55", + "checksum": "337cd3e7f71e70ddbe17541d75fd6e94e0a0e4c2c50999eb2b22a2e64d5dfcd6", "events": [], "fighters": [ { @@ -14561,6 +15245,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14571,6 +15257,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -14613,6 +15300,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14623,6 +15312,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 3, @@ -14655,7 +15345,7 @@ "tick": 115 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 115 }, @@ -14675,7 +15365,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "247c6cc14229a9b2eae7fbcb27ed2b06810ab260a53b92f6de6f71848b75d8f3", + "checksum": "e38e479eda4486659324dbe46cbac638963d39e288d0fdf4df637a762469a6fb", "events": [], "fighters": [ { @@ -14696,6 +15386,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14706,6 +15398,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -14748,6 +15441,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14758,6 +15453,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 4, @@ -14790,7 +15486,7 @@ "tick": 116 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 116 }, @@ -14810,7 +15506,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "fd62ddf63e7ac93c4272ed876d9aa150c66a64f3d4c6e3ba25a4362b9338fc8b", + "checksum": "dcee5558c6d1a827286a9582487bf410b7ca841a8a3f143a8dc2ba169b38704c", "events": [], "fighters": [ { @@ -14831,6 +15527,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14841,6 +15539,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -14883,6 +15582,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14893,6 +15594,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 5, @@ -14925,7 +15627,7 @@ "tick": 117 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 117 }, @@ -14945,7 +15647,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "465db4f76e345c0911dfee9e5b837ef217284fba7212f319dc2f5b2a0e1f5499", + "checksum": "f34a27f245c1b1b518af27f203fdd4ce53b836b892b8b76c855cedb7cd311505", "events": [], "fighters": [ { @@ -14966,6 +15668,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -14976,6 +15680,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15018,6 +15723,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15028,6 +15735,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 6, @@ -15060,7 +15768,7 @@ "tick": 118 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 118 }, @@ -15080,7 +15788,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "568d56b7d31247d0971fe922c678c59586c96673b9e150a0982f566850b31388", + "checksum": "16485b15ada4588ab428c58c79acee58a305447b24542d36996ea45d81571fb1", "events": [], "fighters": [ { @@ -15101,6 +15809,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15111,6 +15821,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15153,6 +15864,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15163,6 +15876,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 7, @@ -15195,7 +15909,7 @@ "tick": 119 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 119 }, @@ -15204,7 +15918,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8cdb61b7e4c1333477d8785ef99b8f8821da582a221c98c8644c406967bb3571", + "checksum": "ef3300eca87a0a4a0ae6d314e328d4314adeabc9bcb2aab21021ed5cf04c9c85", "events": [ { "action_id": "one@114", @@ -15250,6 +15964,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15260,6 +15976,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15302,6 +16019,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15312,6 +16031,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -15344,7 +16064,7 @@ "tick": 120 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 120 }, @@ -15353,7 +16073,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8a93a989cf50084df87d44370bcde683a546cf0df26ffdd9dd9c5ce4a091914b", + "checksum": "b2e3d9d1849e4abcca3a0b4e3efed8f598f5326dda2de89cb4e15f7843b63669", "events": [], "fighters": [ { @@ -15374,6 +16094,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15384,6 +16106,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15402,10 +16125,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 186, "y": 0 }, { @@ -15426,6 +16149,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15436,6 +16161,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -15468,7 +16194,7 @@ "tick": 121 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 121 }, @@ -15477,7 +16203,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "54bae7b7c24d907e050bb0929871f9adad636e9613855b578e8649b49301ee07", + "checksum": "1174eaa6f18a72f942c80626b36bdefc685b472365f8e33b247ecd93ae331ecb", "events": [], "fighters": [ { @@ -15498,6 +16224,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15508,6 +16236,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15526,10 +16255,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 182, "y": 0 }, { @@ -15550,6 +16279,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15560,6 +16291,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -15592,7 +16324,7 @@ "tick": 122 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 122 }, @@ -15601,7 +16333,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8ff82a8107c8be8f73fe611aec76cdda2ecc9469d30ae610708987aa1af47952", + "checksum": "d65b07f2473a8cd65fe2ce4c65b710f6f0e42195e1797b5c4d55480e4a7cbdaf", "events": [], "fighters": [ { @@ -15622,6 +16354,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15632,6 +16366,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15650,10 +16385,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 178, "y": 0 }, { @@ -15674,6 +16409,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15684,6 +16421,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -15716,7 +16454,7 @@ "tick": 123 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 123 }, @@ -15725,7 +16463,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "22d42df8b97119d4c50047f4cf9909ed5916e23f57f1317a325081416e2e2993", + "checksum": "2addde5d8de5fc0033c49826168b9773e3e47a061cbf78cd679554a89c660330", "events": [], "fighters": [ { @@ -15746,6 +16484,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15756,6 +16496,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15774,10 +16515,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 174, "y": 0 }, { @@ -15798,6 +16539,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15808,6 +16551,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -15840,7 +16584,7 @@ "tick": 124 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 124 }, @@ -15849,7 +16593,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "ab12b85ce39e980c8583efb0d94d84632c051a342957bafaaf3fe6815cee17cd", + "checksum": "74820874a91cfb77959465bf7eaf25f2d0c6edd2167eac2cbc42058e13d2d7f9", "events": [], "fighters": [ { @@ -15870,6 +16614,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15880,6 +16626,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -15898,10 +16645,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 170, "y": 0 }, { @@ -15922,6 +16669,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -15932,6 +16681,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -15964,7 +16714,7 @@ "tick": 125 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 125 }, @@ -15973,7 +16723,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "6c0a90dec8fcda0d2b390ad6ecc9cf5b1401c828501f8ca56e80b9676e90519e", + "checksum": "50d8cb6754a93f0c8e50e83b25f2a4845044469df6e5e2d4a98c6d74b3e6b39c", "events": [], "fighters": [ { @@ -15994,6 +16744,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16004,6 +16756,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16022,10 +16775,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 166, "y": 0 }, { @@ -16046,6 +16799,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16056,6 +16811,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16088,7 +16844,7 @@ "tick": 126 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 126 }, @@ -16097,7 +16853,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a84d55dbdd9b256a1d53e6beb132065aeeffca620216a8c63cefe69ad2cbefb9", + "checksum": "c7088f657933db140de36c742017e2fecb6366126b7031d02ee03e31a092ed6f", "events": [], "fighters": [ { @@ -16118,6 +16874,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16128,6 +16886,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16146,10 +16905,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 162, "y": 0 }, { @@ -16170,6 +16929,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16180,6 +16941,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16212,7 +16974,7 @@ "tick": 127 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 127 }, @@ -16221,7 +16983,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "f4f9a37f6a86f0dff1522fcf54c67739c2c75b9c58f0d1f2912bb6e2d7d7b07a", + "checksum": "597ba68542cebf6d3813906480b505d81f3cb14bcd3f074d417ebe7fdc002760", "events": [], "fighters": [ { @@ -16242,6 +17004,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16252,6 +17016,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16270,10 +17035,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 158, "y": 0 }, { @@ -16294,6 +17059,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16304,6 +17071,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16336,7 +17104,7 @@ "tick": 128 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 128 }, @@ -16345,7 +17113,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "9114dea9de19e2fbe3e9bb99a2e8bb71136803fc648b2e4f54970008ef212af6", + "checksum": "6945fe681a2293eabad2515b785f65514ca6a437202d21123ea2e4b92e26c6fa", "events": [], "fighters": [ { @@ -16366,6 +17134,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16376,6 +17146,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16394,10 +17165,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 154, "y": 0 }, { @@ -16418,6 +17189,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16428,6 +17201,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16460,7 +17234,7 @@ "tick": 129 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 129 }, @@ -16469,7 +17243,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "9d27cc9abcc782c87b04d45f3219fbe9951bdb4b034a503fbb98e14a4571c23c", + "checksum": "c537ff465d237d4de526ed55bc38ec5a53694bf1455df9433d8c2e2bb10cb3db", "events": [], "fighters": [ { @@ -16490,6 +17264,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16500,6 +17276,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16518,10 +17295,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 150, "y": 0 }, { @@ -16542,6 +17319,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16552,6 +17331,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16584,7 +17364,7 @@ "tick": 130 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 130 }, @@ -16593,7 +17373,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "fa084b74c32b884efbd1d6a2b7fd393936ff671551bc2d99d8711290a69bc904", + "checksum": "4e038ea8df16548909dda5dbcc393c241976797cce99f29f68b435e281ab5e5d", "events": [], "fighters": [ { @@ -16614,6 +17394,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16624,6 +17406,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16642,10 +17425,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 146, "y": 0 }, { @@ -16666,6 +17449,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16676,6 +17461,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16708,7 +17494,7 @@ "tick": 131 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 131 }, @@ -16717,7 +17503,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "adbbc069bb805583bd44a13a0a474725fb28ada39746b9c66525e0a0425703cd", + "checksum": "3e73d48af7e099a16ae4844b53ca04fb4b4ccfb1bc699fd88001e99bd3c1db73", "events": [], "fighters": [ { @@ -16738,6 +17524,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16748,6 +17536,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16766,10 +17555,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 142, "y": 0 }, { @@ -16790,6 +17579,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16800,6 +17591,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16832,7 +17624,7 @@ "tick": 132 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 132 }, @@ -16841,7 +17633,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "d056bf36d42e0b4124cc3695d75fe22cb79cb31090eae05451c4fa2eb65b7f73", + "checksum": "7c2cd5464b11dfac118eb92520143427be8310c65d4796585db4f19aed20b00e", "events": [], "fighters": [ { @@ -16862,6 +17654,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16872,6 +17666,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -16890,10 +17685,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 138, "y": 0 }, { @@ -16914,6 +17709,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16924,6 +17721,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -16956,7 +17754,7 @@ "tick": 133 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 133 }, @@ -16965,7 +17763,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "27f2a033a303edaf09ba2c4345be3f82eec473a423ae100e06d9eb2dfb4761d9", + "checksum": "cfa0f946444720c438845326e996f5e30b87b3b6a4a8e292850cc89fb89ec32b", "events": [], "fighters": [ { @@ -16986,6 +17784,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -16996,6 +17796,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17014,10 +17815,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 134, "y": 0 }, { @@ -17038,6 +17839,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17048,6 +17851,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17080,7 +17884,7 @@ "tick": 134 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 134 }, @@ -17089,7 +17893,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "5735cd2cc1659fadbcce873800c6901f962bda59afca7c411ef1e41222a92455", + "checksum": "477b30da03c6a7cdc98dd85adf5784fd6ade85e352c4112fde7d227f71d9db15", "events": [], "fighters": [ { @@ -17110,6 +17914,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17120,6 +17926,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17138,10 +17945,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 130, "y": 0 }, { @@ -17162,6 +17969,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17172,6 +17981,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17204,7 +18014,7 @@ "tick": 135 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 135 }, @@ -17213,7 +18023,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "8c96dea3ea33214aa2eb73104cfbef325408eb65b52709ac5ea0a2d028b66d7e", + "checksum": "8c09645e5734dbde61a3149e94dae7426798d675bfef5ea367bb3e071f3e29e2", "events": [], "fighters": [ { @@ -17234,6 +18044,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17244,6 +18056,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17262,10 +18075,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 126, "y": 0 }, { @@ -17286,6 +18099,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17296,6 +18111,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17328,7 +18144,7 @@ "tick": 136 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 136 }, @@ -17337,7 +18153,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "38d0e77f8dd5dade67eb6ce213fe80c716fb9d0f8da1267564cec1ab050486c3", + "checksum": "77f514433307710e56f00f7c894bec2a63a1f5a0ab4a15867a83934bd1a36008", "events": [], "fighters": [ { @@ -17358,6 +18174,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17368,6 +18186,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17386,10 +18205,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 122, "y": 0 }, { @@ -17410,6 +18229,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17420,6 +18241,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17452,7 +18274,7 @@ "tick": 137 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 137 }, @@ -17461,7 +18283,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1a1b42e9bffd319e78fab1d15e8dbc3e1aceb55c377e696fa37c1f6be1862453", + "checksum": "0e3737ddec344b104a48f557c44d0d361c892b02934245e66f310250988b9b50", "events": [], "fighters": [ { @@ -17482,6 +18304,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17492,6 +18316,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17510,10 +18335,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 118, "y": 0 }, { @@ -17534,6 +18359,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17544,6 +18371,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17576,7 +18404,7 @@ "tick": 138 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 138 }, @@ -17585,7 +18413,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "c08e67a5e79a7b424b73fd43df6491930c1f3faf41d99081a39679fc76a07865", + "checksum": "ebde7ecdbe4ddb900ff714cf9de9df0ddb3c6342e978d7f6085207c2bd31f521", "events": [], "fighters": [ { @@ -17606,6 +18434,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17616,6 +18446,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17634,10 +18465,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 114, "y": 0 }, { @@ -17658,6 +18489,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17668,6 +18501,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17700,7 +18534,7 @@ "tick": 139 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 139 }, @@ -17709,7 +18543,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "ee3076e61af9393aa517db814eec8cb1d596bc7cb4cce00920ac578bf4bd49d0", + "checksum": "76029bb5d2738ede74d36ea42daa05f9f0ac29690a8976226a2f8231eb5a5943", "events": [], "fighters": [ { @@ -17730,6 +18564,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17740,6 +18576,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17758,10 +18595,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 110, "y": 0 }, { @@ -17782,6 +18619,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17792,6 +18631,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17824,7 +18664,7 @@ "tick": 140 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 140 }, @@ -17833,7 +18673,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "2fa3396ff4349887236f51b3ae018ad6cd5d58583afb8c8d4cfe0a277b82743d", + "checksum": "fa877bdf0db2d76b2ef6087116d776cc5008df4375820bc6131a6134300bb194", "events": [], "fighters": [ { @@ -17854,6 +18694,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17864,6 +18706,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -17882,10 +18725,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 106, "y": 0 }, { @@ -17906,6 +18749,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17916,6 +18761,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -17948,7 +18794,7 @@ "tick": 141 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 141 }, @@ -17957,7 +18803,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "d9dc9cb1c62eaff3872609a0d008a4bb8e23cc1ee79dbedb25fb785d12524f5e", + "checksum": "25fc0a37cac2871da5379944218facc163d2ca47ccb1b59635f073c34298663a", "events": [], "fighters": [ { @@ -17978,6 +18824,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -17988,6 +18836,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18006,10 +18855,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 102, "y": 0 }, { @@ -18030,6 +18879,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18040,6 +18891,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18072,7 +18924,7 @@ "tick": 142 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 142 }, @@ -18081,7 +18933,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "84ca448c2a0664abe1b1acd3388548154c58e484a655119e1e0bd48e21375f0b", + "checksum": "1b6cebe67b1196786dca1506337e0061ca6a483cd2cc8448b2523c3f4eba114e", "events": [], "fighters": [ { @@ -18102,6 +18954,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18112,6 +18966,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18130,10 +18985,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 98, "y": 0 }, { @@ -18154,6 +19009,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18164,6 +19021,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18196,7 +19054,7 @@ "tick": 143 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 143 }, @@ -18205,7 +19063,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "96a979e92d64f6aec3b71c5a935c4e0e19a1481aba90f69306ad43c012f45061", + "checksum": "7101bed01789c9119012cc06bb94f3e83bada9e68495f9d52c4ac3e41c84a9bf", "events": [], "fighters": [ { @@ -18226,6 +19084,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18236,6 +19096,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18254,10 +19115,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 94, "y": 0 }, { @@ -18278,6 +19139,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18288,6 +19151,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18320,7 +19184,7 @@ "tick": 144 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 144 }, @@ -18329,7 +19193,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "d249e8266c083af885b5c13b1130c5e7e4e110bce1bb4c374f1a9a459b707019", + "checksum": "5631f87269d3e6bba9189a84e491c1096c36b6cab4f729a8c2f9581cf98cf2a9", "events": [], "fighters": [ { @@ -18350,6 +19214,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18360,6 +19226,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18378,10 +19245,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 90, "y": 0 }, { @@ -18402,6 +19269,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18412,6 +19281,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18444,7 +19314,7 @@ "tick": 145 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 145 }, @@ -18453,7 +19323,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "944c70e64adec6d932422beed636fb433de274de74a7ec1d41140997ff0b8173", + "checksum": "13a62360b3f9b9b70098ca4c185fa9e36880a90aef0c34df962b4f6e5bd60fe7", "events": [], "fighters": [ { @@ -18474,6 +19344,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18484,6 +19356,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18502,10 +19375,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 86, "y": 0 }, { @@ -18526,6 +19399,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18536,6 +19411,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18568,7 +19444,7 @@ "tick": 146 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 146 }, @@ -18577,7 +19453,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "c3bf545d6efec59d7c545adbb9242fd11a4d7347aacb3ad2e95189fb20aad548", + "checksum": "886fbd4216a22b966e729cffee9ef280eee917eeab785017a0d62963c285ef77", "events": [], "fighters": [ { @@ -18598,6 +19474,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18608,6 +19486,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18626,10 +19505,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 82, "y": 0 }, { @@ -18650,6 +19529,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18660,6 +19541,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18692,7 +19574,7 @@ "tick": 147 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 147 }, @@ -18701,7 +19583,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "4f344783a890dba31b0456eda6f1134a72762ac79d031804f772783aaa0e8ea1", + "checksum": "27c364905e99c293690c5696799a3369f37aca30a2c36448e8c056fa3bd2872a", "events": [], "fighters": [ { @@ -18722,6 +19604,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18732,6 +19616,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18750,10 +19635,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 78, "y": 0 }, { @@ -18774,6 +19659,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18784,6 +19671,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18816,7 +19704,7 @@ "tick": 148 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 148 }, @@ -18825,7 +19713,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "e98848e03e4417a3b1070899af7962c80da5bb7ed48e9c6775f1d220c60251fc", + "checksum": "730ee0710a7eb528a7630ca04dfc5de3560633a73498ebba7fbfa72e476a0158", "events": [], "fighters": [ { @@ -18846,6 +19734,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18856,6 +19746,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -18874,10 +19765,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 74, "y": 0 }, { @@ -18898,6 +19789,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 0, "get_up_meter": 0, "get_up_prompt": null, @@ -18908,6 +19801,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -18940,7 +19834,7 @@ "tick": 149 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 149 }, @@ -18949,7 +19843,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "67094a5a4a71833d6668e73aa76e258d120cd08c7041037990f38e65a59e18ad", + "checksum": "59b81f779e26816182cae754449cc4ed4d2b469131ad05dae7aed6c73b3b1b85", "events": [ { "action_id": null, @@ -18983,6 +19877,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -18993,6 +19889,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19011,10 +19908,10 @@ "right_eye": 0, "swelling": 0 }, - "velocity_x": 0, + "velocity_x": -4, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19035,6 +19932,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19045,6 +19944,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19077,7 +19977,7 @@ "tick": 150 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 150 }, @@ -19086,7 +19986,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "a87dcac9f540e64629573ed8de7d262fc118213e6d61ea27edb150f2783b444f", + "checksum": "a3f1c18fcc3213ceb1509035909e615e89745df7203891e3e39450db7bd52f81", "events": [], "fighters": [ { @@ -19107,6 +20007,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19117,6 +20019,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19138,7 +20041,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19159,6 +20062,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19169,6 +20074,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19201,7 +20107,7 @@ "tick": 151 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 151 }, @@ -19210,7 +20116,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "ce3ba94f6f8b6a02165507a2b4205a97df1ec6ff3ee7a303d2a306bd83c3d2c8", + "checksum": "8f6fee699ff7bcde333292125408c93e477777eb5d4be9e3450532e2ca0529a0", "events": [], "fighters": [ { @@ -19231,6 +20137,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19241,6 +20149,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19262,7 +20171,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19283,6 +20192,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19293,6 +20204,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19325,7 +20237,7 @@ "tick": 152 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 152 }, @@ -19334,7 +20246,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "247a17fd9126c6049a4c537d9500729286c8eb6bb4b179a58d3649109634e7ca", + "checksum": "36e0bc8c191c95adae86989087ae72ed78b2044e3d921d160a078e4d46dc6886", "events": [], "fighters": [ { @@ -19355,6 +20267,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19365,6 +20279,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19386,7 +20301,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19407,6 +20322,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19417,6 +20334,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19449,7 +20367,7 @@ "tick": 153 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 153 }, @@ -19458,7 +20376,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "5e9abbcc50b56f0220d6ab9f44e67bf709f0e0fca2cd8690471a29570c5dddd2", + "checksum": "31a8018b3a11cc2db8aaf6162afba5b282c68612543bfe2396b07d03b0499c2c", "events": [], "fighters": [ { @@ -19479,6 +20397,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19489,6 +20409,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19510,7 +20431,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19531,6 +20452,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19541,6 +20464,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19573,7 +20497,7 @@ "tick": 154 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 154 }, @@ -19582,7 +20506,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "bff87d20e9d408ced2cef6aba5f37536613a762fbcbd2697b63492dfafaf1274", + "checksum": "0528432162965c90a6446e8e12ea6a87c6234a3fb747d1cdf2c1d0a5b8103e01", "events": [], "fighters": [ { @@ -19603,6 +20527,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19613,6 +20539,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19634,7 +20561,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19655,6 +20582,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19665,6 +20594,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19697,7 +20627,7 @@ "tick": 155 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 155 }, @@ -19706,7 +20636,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "c5effb142db31370902186cdbfc3023c93a3d656c59f6f5e3cee3df3e4756bee", + "checksum": "c7dac0663e3a13f067e28e335b2962f2fc87c921d8350c9b0f12493de110c4fd", "events": [], "fighters": [ { @@ -19727,6 +20657,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19737,6 +20669,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19758,7 +20691,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19779,6 +20712,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19789,6 +20724,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19821,7 +20757,7 @@ "tick": 156 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 156 }, @@ -19830,7 +20766,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "00fc9e4c01fb62cac294a4f8ac18e3006cf1126f10b4da4f9cadee66c6ae26d9", + "checksum": "639bc6953b7dd799bf995b60af6d8c7d2a9e3948e1aa128e55c6ac09e44e8c59", "events": [], "fighters": [ { @@ -19851,6 +20787,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19861,6 +20799,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -19882,7 +20821,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -19903,6 +20842,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19913,6 +20854,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -19945,7 +20887,7 @@ "tick": 157 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 157 }, @@ -19954,7 +20896,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "79aea40685af8e3809c693ef6dbc5a225c4a253984eb4b2fccdc081e921c9a19", + "checksum": "4e31b967cc06ad097162bb6e48254df8340e74b85dbf2e74a6f70c01e71b2088", "events": [], "fighters": [ { @@ -19975,6 +20917,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -19985,6 +20929,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -20006,7 +20951,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -20027,6 +20972,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -20037,6 +20984,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -20069,7 +21017,7 @@ "tick": 158 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 158 }, @@ -20078,7 +21026,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "159ed1e52c7664a46ddac50b8a5b23858124a870b26069df165176f9288f6ba5", + "checksum": "fb1c58018ff89ef200def3885fe7af3c549690324bbea4847393f6e2adaeaf6c", "events": [], "fighters": [ { @@ -20099,6 +21047,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -20109,6 +21059,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -20130,7 +21081,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -20151,6 +21102,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -20161,6 +21114,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -20193,7 +21147,7 @@ "tick": 159 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 159 }, @@ -20202,7 +21156,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "732898861de011f25beb92dfd2b19a5def696b037f923d293dc40a1366ec4aa1", + "checksum": "0f4aa8b6a1528a7df67e84927dbcc77c4c852d616094bfe20777b72a811cbec9", "events": [], "fighters": [ { @@ -20223,6 +21177,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -20233,6 +21189,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -20254,7 +21211,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -20275,6 +21232,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -20285,6 +21244,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -20317,7 +21277,7 @@ "tick": 160 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 160 }, @@ -20326,7 +21286,7 @@ "attack_two": null, "snapshot": { "payload": { - "checksum": "1c0df01cb00d5bb96ee58fb7af1483824d5411dc1f58119304e04d4b74dc8bd0", + "checksum": "3509f66a4f71a6054d0ca754fb42dec21759bd34f0e53302287e75c243f0c8b7", "events": [], "fighters": [ { @@ -20347,6 +21307,8 @@ "deductions": 0, "defense": "none", "facing": 1, + "facing_x": 1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -20357,6 +21319,7 @@ "is_downed": false, "is_foul_recovery_target": false, "knockdowns": 0, + "last_input_sequence": 84, "maximum_stamina": 996, "player_id": "one", "poise": 600, @@ -20378,7 +21341,7 @@ "velocity_x": 0, "velocity_y": 0, "warnings": 0, - "x": 189, + "x": 70, "y": 0 }, { @@ -20399,6 +21362,8 @@ "deductions": 0, "defense": "none", "facing": -1, + "facing_x": -1000, + "facing_y": 0, "get_up_count": 1, "get_up_meter": 0, "get_up_prompt": null, @@ -20409,6 +21374,7 @@ "is_downed": true, "is_foul_recovery_target": false, "knockdowns": 1, + "last_input_sequence": -1, "maximum_stamina": 1000, "player_id": "two", "poise": 1, @@ -20441,7 +21407,7 @@ "tick": 161 }, "type": "snapshot", - "version": 2 + "version": 3 }, "tick": 161 } diff --git a/web/hands/scripts/generate-boxer-glb.ts b/web/hands/scripts/generate-boxer-glb.ts deleted file mode 100644 index a44ac3a7..00000000 --- a/web/hands/scripts/generate-boxer-glb.ts +++ /dev/null @@ -1,403 +0,0 @@ -/** - * Generates the skinned GLB humanoid for the Hands 3D presentation. - * - * The skeleton and bind pose mirror the procedural rig; clips are authored by - * driving the procedural animator through scripted states and baking per-bone - * keyframes at 30 Hz. Outputs: - * web/hands/src/assets/boxer-glb.ts (base64 GLB, embedded in the bundle) - * web/hands/src/assets/boxer-markers.json (glove trajectories per punch clip) - * - * Run: npm run generate:glb (from web/hands) - */ -import { createHash } from "node:crypto"; -import { mkdirSync, writeFileSync } from "node:fs"; -import { fileURLToPath } from "node:url"; -import * as THREE from "three"; -import { GLTFExporter } from "three/examples/jsm/exporters/GLTFExporter.js"; -import { BoxerAnimator } from "../src/render/animation"; -import { buildBoxer } from "../src/render/boxer"; -import { PALETTES, worldMapping } from "../src/render/world"; -import { punchTiming, totalTicks } from "../src/manifest"; -import type { FighterSnapshot } from "../src/types"; - -class FileReaderPolyfill { - result: unknown = null; - onloadend: (() => void) | null = null; - readAsArrayBuffer(blob: Blob): void { - void blob.arrayBuffer().then((buffer) => { - this.result = buffer; - this.onloadend?.(); - }); - } - readAsDataURL(blob: Blob): void { - void blob.arrayBuffer().then((buffer) => { - this.result = `data:application/octet-stream;base64,${Buffer.from(buffer).toString("base64")}`; - this.onloadend?.(); - }); - } -} -(globalThis as Record).FileReader = FileReaderPolyfill; -(globalThis as Record).document = { - createElement: (tag: string) => - tag === "canvas" ? { width: 0, height: 0, getContext: () => null } : {}, - createElementNS: () => ({}), -}; - -const OUT_DIR = fileURLToPath(new URL("./src/assets/", `file://${process.cwd()}/`)); -const MAPPING = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 330 }); - -interface BoneSpec { - readonly name: string; - readonly parent: string | null; - readonly position: readonly [number, number, number]; -} - -const BONES: readonly BoneSpec[] = [ - { name: "hips", parent: null, position: [0, 0.98, 0] }, - { name: "spine", parent: "hips", position: [0, 0.1, 0] }, - { name: "chest", parent: "spine", position: [0, 0, 0] }, - { name: "head", parent: "chest", position: [0, 0.44, 0] }, - { name: "shoulderL", parent: "chest", position: [0.215, 0.315, 0] }, - { name: "elbowL", parent: "shoulderL", position: [0, -0.3, 0] }, - { name: "gloveL", parent: "elbowL", position: [0, -0.3, 0] }, - { name: "shoulderR", parent: "chest", position: [-0.215, 0.315, 0] }, - { name: "elbowR", parent: "shoulderR", position: [0, -0.3, 0] }, - { name: "gloveR", parent: "elbowR", position: [0, -0.3, 0] }, - { name: "hipL", parent: "hips", position: [0.105, -0.02, 0] }, - { name: "kneeL", parent: "hipL", position: [0, -0.44, 0] }, - { name: "ankleL", parent: "kneeL", position: [0, -0.44, 0] }, - { name: "hipR", parent: "hips", position: [-0.105, -0.02, 0] }, - { name: "kneeR", parent: "hipR", position: [0, -0.44, 0] }, - { name: "ankleR", parent: "kneeR", position: [0, -0.44, 0] }, -]; - -const BONE_INDEX = new Map(BONES.map((bone, index) => [bone.name, index])); -const CHILD_BONE = new Map([ - ["chest", "head"], - ["spine", "chest"], - ["shoulderL", "elbowL"], - ["elbowL", "gloveL"], - ["shoulderR", "elbowR"], - ["elbowR", "gloveR"], - ["hipL", "kneeL"], - ["kneeL", "ankleL"], - ["hipR", "kneeR"], - ["kneeR", "ankleR"], -]); - -const baseFighter = (): FighterSnapshot => ({ - player_id: "one", x: 0, y: 0, facing: 1, velocity_x: 0, velocity_y: 0, - stance: "orthodox", defense: "none", stamina: 1000, maximum_stamina: 1000, - conditioning: 1000, guard: 700, poise: 600, - trauma: { head: 0, body: 0, left_eye: 0, right_eye: 0, left_cut: 0, right_cut: 0, swelling: 0, bleeding: 0 }, - knockdowns: 0, warnings: 0, deductions: 0, stunned_ticks: 0, is_downed: false, - action: null, action_hand: null, action_target: null, action_power: null, - action_id: null, action_key: null, action_start_tick: 0, - action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, - queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, - taunt_ticks: 0, get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, - get_up_window_start_tick: 0, get_up_window_end_tick: 0, -}); -const OPPONENT: FighterSnapshot = { ...baseFighter(), player_id: "two", x: 107, facing: -1 }; - -interface BakedClip { - readonly name: string; - readonly frames: number; - readonly tracks: Map; - readonly hipsPositions: number[][]; - readonly gloveMarkers: { left: number[][]; right: number[][] }; -} - -function bakeClip( - name: string, - frames: number, - drive: (fighter: FighterSnapshot, frame: number) => FighterSnapshot, - onFrame?: (animator: BoxerAnimator, frame: number) => void, -): BakedClip { - const rig = buildBoxer(PALETTES[0]); - const animator = new BoxerAnimator(rig, MAPPING); - const tracks = new Map(BONES.map((bone) => [bone.name, []])); - const hipsPositions: number[][] = []; - const gloveMarkers = { left: [] as number[][], right: [] as number[][] }; - for (let frame = -12; frame < frames; frame += 1) { - const active = Math.max(0, frame); - const fighter = drive(baseFighter(), active); - if (onFrame !== undefined && frame >= 0) onFrame(animator, frame); - animator.update(fighter, OPPONENT, 1 / 30, frame / 30, false, "full", active); - if (frame < 0) continue; - rig.root.updateMatrixWorld(true); - for (const bone of BONES) { - const joint = rig.root.getObjectByName(bone.name); - if (joint === undefined) throw new Error(`rig missing joint ${bone.name}`); - const q = joint.quaternion; - tracks.get(bone.name)!.push([q.x, q.y, q.z, q.w]); - } - hipsPositions.push([rig.hips.position.x, rig.hips.position.y, rig.hips.position.z]); - const left = rig.gloveL.getWorldPosition(new THREE.Vector3()); - const right = rig.gloveR.getWorldPosition(new THREE.Vector3()); - gloveMarkers.left.push([Number(left.x.toFixed(4)), Number(left.y.toFixed(4)), Number(left.z.toFixed(4))]); - gloveMarkers.right.push([Number(right.x.toFixed(4)), Number(right.y.toFixed(4)), Number(right.z.toFixed(4))]); - } - return { name, frames, tracks, hipsPositions, gloveMarkers }; -} - -function withPunch( - fighter: FighterSnapshot, - punchClass: "jab" | "straight" | "hook" | "uppercut", - hand: "left" | "right", -): FighterSnapshot { - const timing = punchTiming(punchClass, "head", "normal"); - return { - ...fighter, - action: punchClass, - action_hand: hand, - action_target: "head", - action_power: "normal", - action_id: `${punchClass}:${hand}`, - action_key: `${punchClass}:${hand}:head:normal`, - action_start_tick: 0, - action_startup_ticks: timing.startup, - action_active_ticks: timing.active, - action_recovery_ticks: timing.recovery, - }; -} - -function assignSkin( - geometry: THREE.BufferGeometry, - bone: string, - parentBone: string | null, - from: THREE.Vector3, - to: THREE.Vector3, -): void { - const position = geometry.getAttribute("position"); - const skinIndex = new Uint16Array(position.count * 4); - const skinWeight = new Float32Array(position.count * 4); - const direction = to.clone().sub(from); - const length = Math.max(0.001, direction.length()); - direction.normalize(); - const boneIndex = BONE_INDEX.get(bone)!; - const parentIndex = parentBone === null ? boneIndex : BONE_INDEX.get(parentBone)!; - const childName = CHILD_BONE.get(bone); - const childIndex = childName === undefined ? boneIndex : BONE_INDEX.get(childName)!; - const point = new THREE.Vector3(); - for (let i = 0; i < position.count; i += 1) { - point.set(position.getX(i), position.getY(i), position.getZ(i)); - const t = THREE.MathUtils.clamp(point.clone().sub(from).dot(direction) / length, 0, 1); - let primary = 1; - let secondary = 0; - let secondaryIndex = boneIndex; - if (t < 0.18 && parentBone !== null) { - secondary = 0.5 * (1 - t / 0.18); - secondaryIndex = parentIndex; - } else if (t > 0.82 && childName !== undefined) { - secondary = 0.5 * ((t - 0.82) / 0.18); - secondaryIndex = childIndex; - } - primary = 1 - secondary; - skinIndex[i * 4] = boneIndex; - skinIndex[i * 4 + 1] = secondaryIndex; - skinWeight[i * 4] = primary; - skinWeight[i * 4 + 1] = secondary; - } - geometry.setAttribute("skinIndex", new THREE.Uint16BufferAttribute(skinIndex, 4)); - geometry.setAttribute("skinWeight", new THREE.Float32BufferAttribute(skinWeight, 4)); -} - -function buildSkinnedGeometry(): { geometry: THREE.BufferGeometry; materialCount: number } { - const geometries: THREE.BufferGeometry[] = []; - const tags: number[] = []; - - const jointWorld = (name: string): THREE.Vector3 => { - const spec = BONES.find((bone) => bone.name === name)!; - const position = new THREE.Vector3(...spec.position); - let parent = spec.parent; - while (parent !== null) { - const parentSpec = BONES.find((bone) => bone.name === parent)!; - position.add(new THREE.Vector3(...parentSpec.position)); - parent = parentSpec.parent; - } - return position; - }; - - const addSegment = ( - from: THREE.Vector3, - to: THREE.Vector3, - radius: number, - bone: string, - parentBone: string | null, - tag: number, - flatten = 1, - ): void => { - const direction = to.clone().sub(from); - const length = direction.length(); - const unit = direction.clone().normalize(); - const fromExtended = from.clone().addScaledVector(unit, -length * 0.06); - const toExtended = to.clone().addScaledVector(unit, length * 0.06); - const extendedDirection = toExtended.clone().sub(fromExtended); - const extendedLength = extendedDirection.length(); - const geometry = new THREE.CapsuleGeometry(radius, extendedLength, 5, 12); - geometry.scale(1, 1, flatten); - const quaternion = new THREE.Quaternion().setFromUnitVectors(new THREE.Vector3(0, 1, 0), extendedDirection.clone().normalize()); - const midpoint = fromExtended.clone().add(toExtended).multiplyScalar(0.5); - geometry.applyMatrix4(new THREE.Matrix4().compose(midpoint, quaternion, new THREE.Vector3(1, 1, 1))); - assignSkin(geometry, bone, parentBone, fromExtended, toExtended); - tags.push(tag); - geometries.push(geometry); - }; - - const hips = jointWorld("hips"); - const chest = jointWorld("chest"); - const head = jointWorld("head"); - addSegment(hips.clone().add(new THREE.Vector3(0, -0.08, 0)), chest.clone().add(new THREE.Vector3(0, 0.16, 0)), 0.16, "chest", "spine", 0, 0.82); - addSegment(chest.clone().add(new THREE.Vector3(0, 0.12, 0)), chest.clone().add(new THREE.Vector3(0, 0.36, 0)), 0.175, "chest", "spine", 0, 0.85); - addSegment(head.clone().add(new THREE.Vector3(0, -0.02, 0)), head.clone().add(new THREE.Vector3(0, 0.14, 0)), 0.1, "head", "chest", 0, 0.95); - addSegment(head.clone().add(new THREE.Vector3(0, 0.1, 0)), head.clone().add(new THREE.Vector3(0, 0.26, 0)), 0.085, "head", "chest", 0, 0.98); - for (const side of ["L", "R"] as const) { - addSegment(jointWorld(`shoulder${side}`), jointWorld(`elbow${side}`), 0.06, `shoulder${side}`, "chest", 0); - addSegment(jointWorld(`elbow${side}`), jointWorld(`glove${side}`), 0.05, `elbow${side}`, `shoulder${side}`, 0); - addSegment(jointWorld(`glove${side}`), jointWorld(`glove${side}`).add(new THREE.Vector3(0, -0.12, 0.06)), 0.084, `glove${side}`, `elbow${side}`, 1); - addSegment(jointWorld(`hip${side}`), jointWorld(`knee${side}`), 0.08, `hip${side}`, "hips", 0); - addSegment(jointWorld(`knee${side}`), jointWorld(`ankle${side}`), 0.06, `knee${side}`, `hip${side}`, 0); - addSegment(jointWorld(`ankle${side}`), jointWorld(`ankle${side}`).add(new THREE.Vector3(0, -0.1, 0.08)), 0.05, `ankle${side}`, `knee${side}`, 1); - } - const trunks = new THREE.CylinderGeometry(0.185, 0.155, 0.42, 16); - trunks.translate(0, hips.y - 0.08, 0); - assignSkin(trunks, "hips", null, hips, hips.clone().add(new THREE.Vector3(0, 0.2, 0))); - tags.push(1); - geometries.push(trunks); - - let totalVertices = 0; - let totalIndices = 0; - const ordered = geometries.map((geometry, index) => ({ geometry, tag: tags[index]! })).sort((a, b) => a.tag - b.tag); - for (const { geometry } of ordered) { - totalVertices += geometry.getAttribute("position").count; - totalIndices += geometry.getIndex()!.count; - } - const positions = new Float32Array(totalVertices * 3); - const normals = new Float32Array(totalVertices * 3); - const skinIndex = new Uint16Array(totalVertices * 4); - const skinWeight = new Float32Array(totalVertices * 4); - const indices = new Uint32Array(totalIndices); - const merged = new THREE.BufferGeometry(); - let vertexOffset = 0; - let indexOffset = 0; - let groupStart = 0; - let groupLength = 0; - let currentTag = -1; - ordered.forEach(({ geometry, tag }) => { - if (tag !== currentTag) { - if (currentTag !== -1) merged.addGroup(groupStart, groupLength, currentTag); - currentTag = tag; - groupStart = indexOffset; - groupLength = 0; - } - const position = geometry.getAttribute("position"); - positions.set(position.array as Float32Array, vertexOffset * 3); - normals.set(geometry.getAttribute("normal").array as Float32Array, vertexOffset * 3); - skinIndex.set(geometry.getAttribute("skinIndex").array as Uint16Array, vertexOffset * 4); - skinWeight.set(geometry.getAttribute("skinWeight").array as Float32Array, vertexOffset * 4); - const index = geometry.getIndex()!; - for (let i = 0; i < index.count; i += 1) indices[indexOffset + i] = index.getX(i) + vertexOffset; - vertexOffset += position.count; - indexOffset += index.count; - groupLength += index.count; - }); - if (currentTag !== -1) merged.addGroup(groupStart, groupLength, currentTag); - merged.setAttribute("position", new THREE.BufferAttribute(positions, 3)); - merged.setAttribute("normal", new THREE.BufferAttribute(normals, 3)); - merged.setAttribute("skinIndex", new THREE.Uint16BufferAttribute(skinIndex, 4)); - merged.setAttribute("skinWeight", new THREE.Float32BufferAttribute(skinWeight, 4)); - merged.setIndex(new THREE.BufferAttribute(indices, 1)); - return { geometry: merged, materialCount: 2 }; -} - -async function main(): Promise { - const clips: BakedClip[] = []; - clips.push(bakeClip("idle", 60, (fighter) => fighter)); - clips.push(bakeClip("move_forward", 24, (fighter) => ({ ...fighter, velocity_x: 6 }))); - clips.push(bakeClip("move_backward", 24, (fighter) => ({ ...fighter, velocity_x: -6 }))); - clips.push(bakeClip("move_lateral", 24, (fighter) => ({ ...fighter, velocity_y: 6 }))); - clips.push(bakeClip("guard_high", 30, (fighter) => ({ ...fighter, defense: "guard_high" }))); - clips.push(bakeClip("guard_low", 30, (fighter) => ({ ...fighter, defense: "guard_low" }))); - - const markerTrajectories: Record = {}; - for (const punchClass of ["jab", "straight", "hook", "uppercut"] as const) { - for (const hand of ["left", "right"] as const) { - const total = totalTicks(punchTiming(punchClass, "head", "normal")); - const clip = bakeClip(`${punchClass}_${hand}`, total + 4, (fighter) => withPunch(fighter, punchClass, hand)); - clips.push(clip); - markerTrajectories[`${punchClass}:${hand}`] = { - frames: clip.frames, - left: clip.gloveMarkers.left, - right: clip.gloveMarkers.right, - }; - } - } - clips.push( - bakeClip("block_head", 14, (fighter) => fighter, (animator, frame) => { - if (frame === 0) animator.impact({ direction: 1, amount: 120, blocked: true }); - }), - ); - clips.push( - bakeClip("hit_head", 16, (fighter) => fighter, (animator, frame) => { - if (frame === 0) animator.impact({ direction: 1, amount: 320, blocked: false }); - }), - ); - clips.push(bakeClip("knockdown", 42, (fighter) => ({ ...fighter, is_downed: true }))); - clips.push(bakeClip("getup", 30, (fighter, frame) => ({ ...fighter, is_downed: frame < 10 }))); - - const { geometry } = buildSkinnedGeometry(); - const bones = BONES.map((spec) => { - const bone = new THREE.Bone(); - bone.name = spec.name; - bone.position.set(...spec.position); - return bone; - }); - BONES.forEach((spec, index) => { - if (spec.parent !== null) bones[BONE_INDEX.get(spec.parent)!]!.add(bones[index]!); - }); - const skinMaterial = new THREE.MeshStandardMaterial({ color: 0xa9744f, roughness: 0.6 }); - skinMaterial.name = "skin"; - const gearMaterial = new THREE.MeshStandardMaterial({ color: 0x14406b, roughness: 0.4 }); - gearMaterial.name = "gear"; - const mesh = new THREE.SkinnedMesh(geometry, [skinMaterial, gearMaterial]); - mesh.name = "boxer"; - mesh.add(bones[0]!); - bones[0]!.updateMatrixWorld(true); - mesh.updateMatrixWorld(true); - mesh.bind(new THREE.Skeleton(bones)); - - const animationClips = clips.map((clip) => { - const tracks: THREE.KeyframeTrack[] = []; - const times = Array.from({ length: clip.frames }, (_unused, index) => index / 30); - for (const bone of BONES) { - tracks.push(new THREE.QuaternionKeyframeTrack(`${bone.name}.quaternion`, times, clip.tracks.get(bone.name)!.flat())); - } - tracks.push(new THREE.VectorKeyframeTrack("hips.position", times, clip.hipsPositions.flat())); - return new THREE.AnimationClip(clip.name, clip.frames / 30, tracks); - }); - - const scene = new THREE.Scene(); - scene.add(mesh); - - const glb = await new Promise((resolve, reject) => { - new GLTFExporter().parse( - scene, - (result) => resolve(result as ArrayBuffer), - (error: unknown) => reject(error instanceof Error ? error : new Error(String(error))), - { binary: true, animations: animationClips }, - ); - }); - - mkdirSync(OUT_DIR, { recursive: true }); - const base64 = Buffer.from(glb).toString("base64"); - const sha = createHash("sha256").update(base64).digest("hex"); - writeFileSync( - `${OUT_DIR}/boxer-glb.ts`, - `// Generated by scripts/generate-boxer-glb.ts — do not edit by hand.\nexport const BOXER_GLB_BASE64 = "${base64}";\nexport const BOXER_GLB_SHA256 = "${sha}";\n`, - ); - writeFileSync(`${OUT_DIR}/boxer-markers.json`, JSON.stringify({ format: 1, trajectories: markerTrajectories }, null, 1) + "\n"); - console.log(`GLB: ${glb.byteLength} bytes, ${animationClips.length} clips, base64 ${base64.length} chars, sha256 ${sha}`); -} - -await main(); diff --git a/web/hands/scripts/generate-fighter-glb.ts b/web/hands/scripts/generate-fighter-glb.ts index 91bf09a0..f5a8399c 100644 --- a/web/hands/scripts/generate-fighter-glb.ts +++ b/web/hands/scripts/generate-fighter-glb.ts @@ -1,26 +1,25 @@ /** - * Generates the skinned HANDS fighter by retargeting the tuned procedural - * boxing motion onto the Texel Boxer armature (assets-src/Boxer.glb). + * Prepares the skinned HANDS fighter from the Texel Boxer source + * (assets-src/Boxer.glb): strips props and the source animation, splits the + * glove mesh into independently detachable left and right gloves, normalizes + * skin weights, and embeds the five base-color textures. All motion is + * generated at runtime by the pose solver, so the exported GLB carries no clips. * * Outputs: * web/hands/src/assets/fighter-glb.ts (base64 gzip-compressed GLB) * web/hands/src/assets/fighter-textures.ts (embedded source textures) - * web/hands/src/assets/fighter-markers.json (glove trajectories per punch) * * Run: npm run generate:fighter (from web/hands) */ import { createHash } from "node:crypto"; import { mkdirSync, readFileSync, writeFileSync } from "node:fs"; import { gzipSync } from "node:zlib"; +import { encode as encodeJpeg } from "jpeg-js"; +import { PNG } from "pngjs"; import * as THREE from "three"; import { GLTFExporter } from "three/examples/jsm/exporters/GLTFExporter.js"; import { GLTFLoader, type GLTF } from "three/examples/jsm/loaders/GLTFLoader.js"; -import { BoxerAnimator } from "../src/render/animation"; import { BONE_ADAPTER } from "../src/render/skeleton"; -import { buildBoxer } from "../src/render/boxer"; -import { PALETTES, worldMapping } from "../src/render/world"; -import { punchTiming, totalTicks } from "../src/manifest"; -import type { FighterSnapshot } from "../src/types"; class FileReaderPolyfill { result: unknown = null; @@ -49,43 +48,7 @@ globals.document = { }; const OUT_DIR = `${process.cwd()}/src/assets`; -const MAPPING = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 330 }); - - -const CANONICAL_ORDER = [ - "hips", "spine", "chest", "head", - "shoulderL", "elbowL", "gloveL", - "shoulderR", "elbowR", "gloveR", - "hipL", "kneeL", "ankleL", - "hipR", "kneeR", "ankleR", -] as const; - -/** Limb bones retarget by child-aim direction (convention-free). */ -const AIM_BONES: Record = { - shoulderL: "elbowL", - elbowL: "gloveL", - shoulderR: "elbowR", - elbowR: "gloveR", - hipL: "kneeL", - kneeL: "ankleL", - hipR: "kneeR", - kneeR: "ankleR", -}; - -const baseFighter = (): FighterSnapshot => ({ - player_id: "one", x: 0, y: 0, facing: 1, velocity_x: 0, velocity_y: 0, - stance: "orthodox", defense: "none", stamina: 1000, maximum_stamina: 1000, - conditioning: 1000, guard: 700, poise: 600, - trauma: { head: 0, body: 0, left_eye: 0, right_eye: 0, left_cut: 0, right_cut: 0, swelling: 0, bleeding: 0 }, - knockdowns: 0, warnings: 0, deductions: 0, stunned_ticks: 0, is_downed: false, - action: null, action_hand: null, action_target: null, action_power: null, - action_id: null, action_key: null, action_start_tick: 0, - action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, - queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, - taunt_ticks: 0, get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, - get_up_window_start_tick: 0, get_up_window_end_tick: 0, -}); -const OPPONENT: FighterSnapshot = { ...baseFighter(), player_id: "two", x: 0, y: -80, facing: -1 }; +const JPEG_QUALITY = 90; async function loadModel(path: string): Promise { const buffer = readFileSync(path); @@ -99,211 +62,6 @@ async function loadModel(path: string): Promise { }); } -interface RetargetContext { - readonly scene: THREE.Group; - readonly modelBones: Map; - readonly modelRestLocal: Map; - readonly modelRestWorld: Map; - readonly modelRestDirections: Map; - readonly oursRestWorld: Map; - readonly modelHipsRestLocal: THREE.Vector3; - readonly modelHipsRestWorld: THREE.Vector3; - readonly modelHipsParentInverse: THREE.Matrix4; - readonly hipsScale: number; -} - -function buildRetargetContext(model: GLTF): RetargetContext { - const scene = model.scene; - scene.updateMatrixWorld(true); - const modelBones = new Map(); - const modelRestLocal = new Map(); - scene.traverse((object) => { - modelRestLocal.set(object, object.quaternion.clone()); - if (object instanceof THREE.Bone) modelBones.set(object.name, object); - }); - const available = [...modelBones.keys()].sort(); - const missing = Object.entries(BONE_ADAPTER).filter(([, target]) => !modelBones.has(target)); - if (missing.length > 0) { - throw new Error( - `Boxer.glb is missing required bones: ${missing.map(([from, to]) => `${from}→${to}`).join(", ")} -available: ${available.join(", ")}`, - ); - } - const ours = buildBoxer(PALETTES[0]); - ours.root.updateMatrixWorld(true); - const oursRestWorld = new Map(); - for (const name of CANONICAL_ORDER) { - const joint = ours.root.getObjectByName(name); - if (joint === undefined) throw new Error(`procedural rig missing joint ${name}`); - oursRestWorld.set(name, joint.getWorldQuaternion(new THREE.Quaternion())); - } - const modelRestWorld = new Map(); - for (const [name, bone] of modelBones) { - modelRestWorld.set(name, bone.getWorldQuaternion(new THREE.Quaternion())); - } - const modelRestDirections = new Map(); - for (const [name, childName] of Object.entries(AIM_BONES)) { - const bonePosition = modelBones.get(BONE_ADAPTER[name]!)!.getWorldPosition(new THREE.Vector3()); - const childPosition = modelBones.get(BONE_ADAPTER[childName]!)!.getWorldPosition(new THREE.Vector3()); - modelRestDirections.set(BONE_ADAPTER[name]!, childPosition.sub(bonePosition).normalize()); - } - const modelHips = modelBones.get(BONE_ADAPTER.hips)!; - const modelHipsRestWorld = modelHips.getWorldPosition(new THREE.Vector3()); - const segmentLength = (root: THREE.Object3D, from: string, to: string): number => - root.getObjectByName(from)!.getWorldPosition(new THREE.Vector3()) - .distanceTo(root.getObjectByName(to)!.getWorldPosition(new THREE.Vector3())); - const modelLegLength = ( - segmentLength(scene, BONE_ADAPTER.hipL!, BONE_ADAPTER.kneeL!) - + segmentLength(scene, BONE_ADAPTER.kneeL!, BONE_ADAPTER.ankleL!) - + segmentLength(scene, BONE_ADAPTER.hipR!, BONE_ADAPTER.kneeR!) - + segmentLength(scene, BONE_ADAPTER.kneeR!, BONE_ADAPTER.ankleR!) - ) / 2; - const oursLegLength = ( - segmentLength(ours.root, "hipL", "kneeL") - + segmentLength(ours.root, "kneeL", "ankleL") - + segmentLength(ours.root, "hipR", "kneeR") - + segmentLength(ours.root, "kneeR", "ankleR") - ) / 2; - if (modelHips.parent === null) throw new Error("Boxer.glb hips bone has no parent"); - return { - scene, - modelBones, - modelRestLocal, - modelRestWorld, - modelRestDirections, - oursRestWorld, - modelHipsRestLocal: modelHips.position.clone(), - modelHipsRestWorld, - modelHipsParentInverse: modelHips.parent.matrixWorld.clone().invert(), - hipsScale: modelLegLength / oursLegLength, - }; -} - -interface BakedClip { - readonly name: string; - readonly frames: number; - readonly tracks: Map; - readonly hipsPositions: number[][]; - readonly gloveMarkers: { left: number[][]; right: number[][] }; -} - -function currentModelWorldQuaternion( - context: RetargetContext, - object: THREE.Object3D | null, - modelWorld: Map, -): THREE.Quaternion { - if (object === null) return new THREE.Quaternion(); - if (object instanceof THREE.Bone) { - const animated = modelWorld.get(object.name); - if (animated !== undefined) return animated.clone(); - } - return currentModelWorldQuaternion(context, object.parent, modelWorld).multiply( - context.modelRestLocal.get(object) ?? object.quaternion, - ); -} - -function restoreModelPose(context: RetargetContext): void { - for (const name of CANONICAL_ORDER) { - const bone = context.modelBones.get(BONE_ADAPTER[name]!)!; - bone.quaternion.copy(context.modelRestLocal.get(bone)!); - } - context.modelBones.get(BONE_ADAPTER.hips)!.position.copy(context.modelHipsRestLocal); - context.scene.updateMatrixWorld(true); -} - -function bakeRetargetedClip( - context: RetargetContext, - name: string, - frames: number, - drive: (fighter: FighterSnapshot, frame: number) => FighterSnapshot, - onFrame?: (animator: BoxerAnimator, frame: number) => void, - driveWarmup = true, - warmupFrames = 12, - dtScale = 1, -): BakedClip { - const rig = buildBoxer(PALETTES[0]); - const animator = new BoxerAnimator(rig, MAPPING); - const oursJoints = new Map(); - for (const jointName of CANONICAL_ORDER) { - oursJoints.set(jointName, rig.root.getObjectByName(jointName)!); - } - const tracks = new Map(CANONICAL_ORDER.map((jointName) => [jointName, []])); - const hipsPositions: number[][] = []; - const gloveMarkers = { left: [] as number[][], right: [] as number[][] }; - - const oursWorld = new THREE.Quaternion(); - const delta = new THREE.Quaternion(); - const deltaQ = new THREE.Quaternion(); - const targetWorld = new THREE.Quaternion(); - const modelWorld = new Map(); - const scratchBonePos = new THREE.Vector3(); - const scratchChildPos = new THREE.Vector3(); - const oursHipsRestLocal = new THREE.Vector3(0, 0.98, 0); - - for (let frame = -warmupFrames; frame < frames; frame += 1) { - const active = Math.max(0, frame); - const fighter = frame < 0 && !driveWarmup ? baseFighter() : drive(baseFighter(), active); - if (onFrame !== undefined && frame >= 0) onFrame(animator, frame); - animator.update(fighter, OPPONENT, dtScale / 30, (frame * dtScale) / 30, false, "full", active); - if (frame < 0) continue; - // Runtime owns facing and stance yaw; clips contain joint-local motion only. - const localRootMotion = rig.root.position.clone().applyQuaternion(rig.root.quaternion.clone().invert()); - rig.root.position.set(0, 0, 0); - rig.root.quaternion.identity(); - rig.root.updateMatrixWorld(true); - - modelWorld.clear(); - for (const jointName of CANONICAL_ORDER) { - const modelName = BONE_ADAPTER[jointName]!; - const modelBone = context.modelBones.get(modelName)!; - const parentWorld = currentModelWorldQuaternion(context, modelBone.parent, modelWorld); - const aimChild = AIM_BONES[jointName]; - if (jointName === "gloveL" || jointName === "gloveR") { - targetWorld.copy(parentWorld).multiply(context.modelRestLocal.get(modelBone)!); - } else if (aimChild !== undefined) { - const boneWorld = oursJoints.get(jointName)!.getWorldPosition(scratchBonePos); - const childWorld = oursJoints.get(aimChild)!.getWorldPosition(scratchChildPos); - const direction = childWorld.sub(boneWorld).normalize(); - const restDirection = context.modelRestDirections.get(modelName)!; - deltaQ.setFromUnitVectors(restDirection, direction); - targetWorld.copy(deltaQ).multiply(context.modelRestWorld.get(modelName)!); - } else { - oursJoints.get(jointName)!.getWorldQuaternion(oursWorld); - delta.copy(oursWorld).multiply(context.oursRestWorld.get(jointName)!.clone().invert()); - targetWorld.copy(delta).multiply(context.modelRestWorld.get(modelName)!); - } - modelWorld.set(modelName, targetWorld.clone()); - const local = parentWorld.invert().multiply(targetWorld).normalize(); - tracks.get(jointName)!.push([local.x, local.y, local.z, local.w]); - modelBone.quaternion.copy(local); - } - - const hipsDelta = rig.hips.position.clone().sub(oursHipsRestLocal).add(localRootMotion) - .multiplyScalar(context.hipsScale); - const modelHips = context.modelBones.get(BONE_ADAPTER.hips)!; - const modelHipsLocal = context.modelHipsRestWorld.clone().add(hipsDelta).applyMatrix4(context.modelHipsParentInverse); - modelHips.position.copy(modelHipsLocal); - context.scene.updateMatrixWorld(true); - for (let pass = 0; pass < 2; pass += 1) { - const floor = new THREE.Box3().setFromObject(context.scene, true).min.y; - if (!Number.isFinite(floor)) throw new Error(`${name} frame ${frame} has non-finite skinned bounds`); - if (Math.abs(floor) < 0.0001) break; - const hipsWorld = modelHips.getWorldPosition(new THREE.Vector3()).add(new THREE.Vector3(0, -floor, 0)); - modelHips.parent!.worldToLocal(hipsWorld); - modelHips.position.copy(hipsWorld); - context.scene.updateMatrixWorld(true); - } - hipsPositions.push([modelHips.position.x, modelHips.position.y, modelHips.position.z]); - - const wristL = context.modelBones.get(BONE_ADAPTER.gloveL)!.getWorldPosition(new THREE.Vector3()); - const wristR = context.modelBones.get(BONE_ADAPTER.gloveR)!.getWorldPosition(new THREE.Vector3()); - gloveMarkers.left.push([Number(wristL.x.toFixed(4)), Number(wristL.y.toFixed(4)), Number(wristL.z.toFixed(4))]); - gloveMarkers.right.push([Number(wristR.x.toFixed(4)), Number(wristR.y.toFixed(4)), Number(wristR.z.toFixed(4))]); - } - restoreModelPose(context); - return { name, frames, tracks, hipsPositions, gloveMarkers }; -} - interface SourceGltf { readonly bufferViews?: readonly { readonly buffer?: number; readonly byteOffset?: number; readonly byteLength: number }[]; readonly images?: readonly { readonly bufferView?: number; readonly mimeType?: string }[]; @@ -356,7 +114,11 @@ function embeddedTextureDataUrls(path: string): Record<(typeof TEXTURE_SPECS)[nu bufferView.byteOffset ?? 0, (bufferView.byteOffset ?? 0) + bufferView.byteLength, ); - result[spec.key] = `data:${image.mimeType};base64,${imageBytes.toString("base64")}`; + if (image.mimeType !== "image/png") throw new Error(`${spec.material} texture is ${image.mimeType}, expected image/png`); + const decoded = PNG.sync.read(Buffer.from(imageBytes)); + const jpeg = encodeJpeg({ data: decoded.data, width: decoded.width, height: decoded.height }, JPEG_QUALITY); + console.log(`texture ${spec.key}: ${decoded.width}x${decoded.height} png ${imageBytes.byteLength} bytes -> jpeg ${jpeg.data.byteLength} bytes`); + result[spec.key] = `data:image/jpeg;base64,${Buffer.from(jpeg.data).toString("base64")}`; } return result; } @@ -466,94 +228,23 @@ async function main(): Promise { } }); cleanSkinWeights(model.scene); + const bones = new Set(); + model.scene.traverse((object) => { + if (object instanceof THREE.Bone) bones.add(object.name); + }); + const missing = Object.entries(BONE_ADAPTER).filter(([, target]) => !bones.has(target)); + if (missing.length > 0) { + throw new Error(`Boxer.glb is missing required bones: ${missing.map(([from, to]) => `${from}→${to}`).join(", ")}`); + } model.scene.userData.attribution = '"Boxer" by Texel, Inc., CC BY 4.0'; model.scene.userData.source = "https://sketchfab.com/3d-models/boxer-84767168720948b38728ff78ee6f6090"; - const context = buildRetargetContext(model); - - const clips: BakedClip[] = []; - clips.push(bakeRetargetedClip(context, "idle", 60, (fighter) => fighter)); - clips.push(bakeRetargetedClip(context, "move_forward", 31, (fighter) => ({ ...fighter, velocity_x: 6 }))); - clips.push(bakeRetargetedClip(context, "move_backward", 31, (fighter) => ({ ...fighter, velocity_x: -6 }))); - clips.push(bakeRetargetedClip(context, "move_lateral_left", 31, (fighter) => ({ ...fighter, velocity_y: -4 }))); - clips.push(bakeRetargetedClip(context, "move_lateral_right", 31, (fighter) => ({ ...fighter, velocity_y: 4 }))); - clips.push(bakeRetargetedClip(context, "guard_high", 30, (fighter) => ({ ...fighter, defense: "guard_high" }))); - clips.push(bakeRetargetedClip(context, "guard_low", 30, (fighter) => ({ ...fighter, defense: "guard_low" }))); - clips.push(bakeRetargetedClip(context, "slip_left", 24, (fighter) => ({ ...fighter, defense: "slip_left" }))); - clips.push(bakeRetargetedClip(context, "slip_right", 24, (fighter) => ({ ...fighter, defense: "slip_right" }))); - clips.push(bakeRetargetedClip(context, "weave", 30, (fighter) => ({ ...fighter, defense: "weave" }))); - clips.push(bakeRetargetedClip(context, "pull", 24, (fighter) => ({ ...fighter, defense: "pull" }))); - - const markerTrajectories: Record = {}; - for (const punchClass of ["jab", "straight", "hook", "uppercut"] as const) { - for (const hand of ["left", "right"] as const) { - const timing = punchTiming(punchClass, "head", "normal"); - const total = totalTicks(timing); - const clip = bakeRetargetedClip(context, `${punchClass}_${hand}`, total + 4, (fighter) => ({ - ...fighter, - action: punchClass, - action_hand: hand, - action_target: "head", - action_power: "normal", - action_id: `${punchClass}:${hand}`, - action_key: `${punchClass}:${hand}:head:normal`, - action_start_tick: 0, - action_startup_ticks: timing.startup, - action_active_ticks: timing.active, - action_recovery_ticks: timing.recovery, - })); - clips.push(clip); - markerTrajectories[`${punchClass}:${hand}`] = { - frames: clip.frames, - left: clip.gloveMarkers.left, - right: clip.gloveMarkers.right, - }; - } - } - for (const reaction of ["block", "hit"] as const) { - for (const target of ["head", "body"] as const) { - for (const side of ["left", "right"] as const) { - clips.push(bakeRetargetedClip(context, `${reaction}_${target}_${side}`, reaction === "block" ? 14 : 16, (fighter) => fighter, (animator, frame) => { - if (frame === 0) { - animator.impact({ - direction: side === "left" ? -1 : 1, - amount: reaction === "block" ? 120 : 320, - blocked: reaction === "block", - target, - }); - } - })); - } - } - } - clips.push(bakeRetargetedClip(context, "knockdown", 42, (fighter) => ({ ...fighter, is_downed: true }), undefined, false)); - clips.push(bakeRetargetedClip(context, "getup", 30, (fighter, frame) => ({ ...fighter, is_downed: frame < 1 }), undefined, true, 21, 2)); - clips.push(bakeRetargetedClip(context, "clinch", 30, (fighter) => ({ ...fighter, clinch_ticks: 30 }))); - clips.push(bakeRetargetedClip(context, "foul_recovery", 30, (fighter) => ({ ...fighter, is_foul_recovery_target: true }))); - clips.push(bakeRetargetedClip(context, "stunned", 30, (fighter) => ({ ...fighter, stunned_ticks: 45 }))); - clips.push(bakeRetargetedClip(context, "exhausted", 45, (fighter) => ({ ...fighter, stamina: 60 }))); - clips.push(bakeRetargetedClip(context, "taunt", 60, (fighter, frame) => ({ - ...fighter, - taunt_ticks: frame >= 6 && frame < 48 - ? Math.max(1, 60 - Math.round((frame - 6) * 60 / 42)) - : 0, - }))); - - const animationClips = clips.map((clip) => { - const tracks: THREE.KeyframeTrack[] = []; - const times = Array.from({ length: clip.frames }, (_unused, index) => index / 30); - for (const name of CANONICAL_ORDER) { - tracks.push(new THREE.QuaternionKeyframeTrack(`${BONE_ADAPTER[name]}.quaternion`, times, clip.tracks.get(name)!.flat())); - } - tracks.push(new THREE.VectorKeyframeTrack(`${BONE_ADAPTER.hips}.position`, times, clip.hipsPositions.flat())); - return new THREE.AnimationClip(clip.name, clip.frames / 30, tracks); - }); const glb = await new Promise((resolve, reject) => { new GLTFExporter().parse( model.scene, (result) => resolve(result as ArrayBuffer), (error: unknown) => reject(error instanceof Error ? error : new Error(String(error))), - { binary: true, animations: animationClips }, + { binary: true, animations: [] }, ); }); @@ -569,8 +260,7 @@ async function main(): Promise { `${OUT_DIR}/fighter-textures.ts`, `// Generated from assets-src/Boxer.glb (Texel, Inc., CC BY 4.0).\nexport const FIGHTER_TEXTURE_DATA_URLS = ${JSON.stringify(textureDataUrls)} as const;\n`, ); - writeFileSync(`${OUT_DIR}/fighter-markers.json`, JSON.stringify({ format: 1, trajectories: markerTrajectories }, null, 1) + "\n"); - console.log(`fighter GLB: ${glb.byteLength} bytes, gzip ${compressed.byteLength} bytes, ${animationClips.length} clips, base64 ${base64.length} chars, sha256 ${sha}`); + console.log(`fighter GLB: ${glb.byteLength} bytes, gzip ${compressed.byteLength} bytes, base64 ${base64.length} chars, sha256 ${sha}`); } await main(); diff --git a/web/hands/src/api.test.ts b/web/hands/src/api.test.ts index 797c7413..2f9a3b34 100644 --- a/web/hands/src/api.test.ts +++ b/web/hands/src/api.test.ts @@ -8,7 +8,7 @@ const rawResponse = (body: string): Response => new Response(body, { describe("strict same-origin HTTP response parsing", () => { it("posts the launch instance so browsers send the same-origin Origin header", async () => { history.replaceState({}, "", "/"); - const fetchMock = vi.fn(async () => rawResponse('{"client_id":"123","state":"s","protocol":2,"simulation":{"tick_rate":30,"ring_half_width":500,"ring_half_height":330}}')); + const fetchMock = vi.fn(async () => rawResponse('{"client_id":"123","state":"s","protocol":3,"simulation":{"tick_rate":30,"ring_half_width":500,"ring_half_height":500}}')); vi.stubGlobal("fetch", fetchMock); await bootstrap("launch"); expect(fetchMock).toHaveBeenCalledWith( @@ -23,10 +23,18 @@ describe("strict same-origin HTTP response parsing", () => { it("rejects top-level duplicate bootstrap keys before schema decoding", async () => { history.replaceState({}, "", "/"); - vi.stubGlobal("fetch", vi.fn(async () => rawResponse('{"client_id":"123","client_id":"forged","state":"s","protocol":2,"simulation":{"tick_rate":30,"ring_half_width":500,"ring_half_height":330}}'))); + vi.stubGlobal("fetch", vi.fn(async () => rawResponse('{"client_id":"123","client_id":"forged","state":"s","protocol":3,"simulation":{"tick_rate":30,"ring_half_width":500,"ring_half_height":500}}'))); await expect(bootstrap("launch")).rejects.toEqual(new ClientError("bootstrap_failed")); }); + it("asks for a reload when the server speaks another protocol, and only then", async () => { + history.replaceState({}, "", "/"); + vi.stubGlobal("fetch", vi.fn(async () => rawResponse('{"client_id":"123","state":"s","protocol":4,"simulation":{"tick_rate":30,"ring_half_width":500,"ring_half_height":500},"build":"next"}'))); + await expect(bootstrap("launch")).rejects.toEqual(new ClientError("client_outdated", true)); + vi.stubGlobal("fetch", vi.fn(async () => rawResponse('{"client_id":"123","state":"s","protocol":3,"simulation":{"tick_rate":30,"ring_half_width":500,"ring_half_height":500},"extra":1}'))); + await expect(bootstrap("launch")).rejects.toEqual(new ClientError("invalid_bootstrap")); + }); + it("rejects nested duplicate token keys before schema decoding", async () => { vi.stubGlobal("fetch", vi.fn(async () => rawResponse('{"access_token":"a","ticket":"t","player":{"id":"one","name":"One","name":"Forged","avatar":null,"rating":1500}}'))); await expect(exchangeToken("code", "state")).rejects.toEqual(new ClientError("token_failed")); diff --git a/web/hands/src/api.ts b/web/hands/src/api.ts index 385f8991..0be43ab8 100644 --- a/web/hands/src/api.ts +++ b/web/hands/src/api.ts @@ -1,5 +1,5 @@ import { decodeBootstrap, decodeToken, parseStrictJson, ProtocolError } from "./protocol"; -import type { BootstrapResponse, TokenResponse } from "./types"; +import { PROTOCOL_VERSION, type BootstrapResponse, type TokenResponse } from "./types"; export class ClientError extends Error { override name = "ClientError"; @@ -16,9 +16,13 @@ export function launchInstance(search = window.location.search): string { if (values.length !== 1 || !/^[A-Za-z0-9_-]{1,255}$/u.test(values[0] ?? "")) throw new ClientError("invalid_launch"); return values[0]!; } +/** A server on another protocol cannot be played from this page; only a reload brings the matching client. */ +function requireCurrentProtocol(value: unknown): void { + if (typeof value === "object" && value !== null && "protocol" in value && value.protocol !== PROTOCOL_VERSION) throw new ClientError("client_outdated", true); +} export async function bootstrap(instanceId: string, signal?: AbortSignal): Promise { const url = new URL("/api/hands/bootstrap", window.location.origin); - try { return decodeBootstrap(await jsonResponse(await fetch(url, { method: "POST", credentials: "same-origin", cache: "no-store", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ instance_id: instanceId }), ...(signal === undefined ? {} : { signal }) }), "bootstrap_failed")); } + try { const value = await jsonResponse(await fetch(url, { method: "POST", credentials: "same-origin", cache: "no-store", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ instance_id: instanceId }), ...(signal === undefined ? {} : { signal }) }), "bootstrap_failed"); requireCurrentProtocol(value); return decodeBootstrap(value); } catch (error) { if (error instanceof ClientError) throw error; if (error instanceof ProtocolError) throw new ClientError("invalid_bootstrap"); throw new ClientError("bootstrap_failed"); } } export async function exchangeToken(code: string, state: string, signal?: AbortSignal): Promise { diff --git a/web/hands/src/app.test.ts b/web/hands/src/app.test.ts index c72bb482..16ed5848 100644 --- a/web/hands/src/app.test.ts +++ b/web/hands/src/app.test.ts @@ -2,29 +2,40 @@ import type { NetworkCallbacks } from "./network"; import type { EngineSnapshot, ServerMessage } from "./types"; import { fighter } from "./test/fixtures"; -const mocks = vi.hoisted(() => ({ - sessionDestroy: vi.fn(), - networkDispose: vi.fn(), - networkSetActive: vi.fn(), - inputDestroy: vi.fn(), - rendererDestroy: vi.fn(), - rendererPushes: [] as number[][], - callbacks: null as NetworkCallbacks | null, -})); +const mocks = vi.hoisted(() => { + const sessionDestroy = vi.fn(); + return { + sessionDestroy, + authorize: vi.fn(async () => ({ + sdk: {}, + bootstrap: { client_id: "123", state: "state", protocol: 3, simulation: { tick_rate: 20, ring_half_width: 500, ring_half_height: 500 } }, + player: { id: "one", name: "One", avatar: null, rating: 1500 }, + takeTicket: () => "ticket", + destroy: sessionDestroy, + })), + activityClose: vi.fn(), + networkDispose: vi.fn(), + networkSetActive: vi.fn(), + inputDestroy: vi.fn(), + rendererDestroy: vi.fn(), + rendererPushes: [] as number[][], + callbacks: null as NetworkCallbacks | null, + rendererResyncs: 0, + resultVisible: true, + }; +}); vi.mock("./discord", () => ({ - authorizeDiscord: vi.fn(async () => ({ - sdk: {}, - bootstrap: { client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 20, ring_half_width: 500, ring_half_height: 330 } }, - player: { id: "one", name: "One", avatar: null, rating: 1500 }, - takeTicket: () => "ticket", - destroy: mocks.sessionDestroy, - })), + DiscordActivity: class { + readonly authorize = mocks.authorize; + readonly close = mocks.activityClose; + }, })); vi.mock("./network", () => ({ NetworkController: class { constructor(_ticket: string, _input: unknown, callbacks: NetworkCallbacks) { mocks.callbacks = callbacks; } start(): void {} setActive(active: boolean): void { mocks.networkSetActive(active); } + notifyAction(): void {} dispose(): void { mocks.networkDispose(); } }, })); @@ -37,16 +48,30 @@ vi.mock("./render/renderer", () => ({ setReconnect(): void {} setBloodLevel(): void {} setReducedMotion(): void {} + resyncClock(): void { mocks.rendererResyncs += 1; } push(snapshot: EngineSnapshot): void { this.pushes.push(snapshot.tick); } destroy(): void { mocks.rendererDestroy(); } + setInputLatency(): void {} + get resultVisible(): boolean { return mocks.resultVisible; } }, })); +import type { IDiscordSDK } from "@discord/embedded-app-sdk"; import { ClientError } from "./api"; import { HandsApp } from "./app"; -import { authorizeDiscord } from "./discord"; const send = (message: ServerMessage): void => { mocks.callbacks?.onMessage(message); }; +/** A Discord client that answers every command; `close` is what would close the Activity. */ +const fakeDiscord = (instanceId: string) => ({ + instanceId, + ready: vi.fn(async () => undefined), + close: vi.fn(), + commands: { authorize: vi.fn(async () => ({ code: "oauth-code" })), authenticate: vi.fn(async () => ({})) }, +}); +const json = (value: unknown): Response => new Response(JSON.stringify(value), { status: 200, headers: { "Content-Type": "application/json" } }); +const handsBackend = () => vi.fn(async (input: URL | RequestInfo) => String(input).includes("bootstrap") + ? json({ client_id: "123", state: "state", protocol: 3, simulation: { tick_rate: 30, ring_half_width: 500, ring_half_height: 500 } }) + : json({ access_token: "access", ticket: "ticket", player: { id: "one", name: "One", avatar: null, rating: 1500 } })); const players = [ { id: "one", name: "One", avatar: null, rating: 1500, connected: true }, { id: "two", name: "Two", avatar: null, rating: 1500, connected: true }, @@ -66,6 +91,7 @@ describe("browser lifecycle and accessible overlays", () => { beforeEach(() => { mocks.callbacks = null; mocks.rendererPushes.length = 0; + mocks.resultVisible = true; vi.clearAllMocks(); }); @@ -86,18 +112,26 @@ describe("browser lifecycle and accessible overlays", () => { const app = new HandsApp(root); app.start(); await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); - send({ version: 2, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [players[0]], server_tick: 0, next_sequence: 0, reconnect_ticket: "rotated" }); - send({ version: 2, type: "waiting", open_seats: 1 }); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [players[0]], server_tick: 0, next_sequence: 0, reconnect_ticket: "rotated" }); + send({ version: 3, type: "waiting", open_seats: 1 }); expect(root.querySelector("[data-invite]")).toBeNull(); expect(root.querySelector("[data-status]")?.textContent).toContain("Play now"); - send({ version: 2, type: "ready", players: [...players] }); + expect(root.querySelector("[data-status]")?.hidden).toBe(false); + expect(root.querySelector("[data-overlay]")?.hasAttribute("data-raised")).toBe(false); + const hint = root.querySelector("[data-hint]")!; + expect(hint.hidden).toBe(false); + expect(hint.textContent).toContain("Jab"); + send({ version: 3, type: "ready", players: [...players] }); const cards = ["A", "B", "C"].map((judge) => ({ judge, player_one: [10], player_two: [9] })); - send({ version: 2, type: "final", match_id: "m", winner_id: "one", method: "decision", round: 1, scorecards: cards, ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }); + send({ version: 3, type: "final", match_id: "m", winner_id: "one", method: "decision", round: 1, scorecards: cards, ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }); expect(root.querySelector("[data-final]")?.textContent).toContain("A: 10 to 9"); + expect(root.querySelector("[data-hint]")!.hidden).toBe(true); + expect(mocks.activityClose).not.toHaveBeenCalled(); app.destroy(); expect(mocks.networkDispose).toHaveBeenCalled(); expect(mocks.rendererDestroy).toHaveBeenCalled(); expect(mocks.sessionDestroy).toHaveBeenCalled(); + expect(mocks.activityClose).toHaveBeenCalledOnce(); expect(root.children).toHaveLength(0); }); @@ -111,9 +145,9 @@ describe("browser lifecycle and accessible overlays", () => { controls.click(); expect(root.querySelector("[data-controls-panel]")!.hidden).toBe(false); - send({ version: 2, type: "welcome", role: "spectator", player_id: "viewer", players: [...players], server_tick: 30, reconnect_ticket: "spectator-ticket" }); + send({ version: 3, type: "welcome", role: "spectator", player_id: "viewer", players: [...players], server_tick: 30, reconnect_ticket: "spectator-ticket" }); const redacted = makeSnapshot(30, "knockdown"); - send({ version: 2, type: "snapshot", payload: redacted }); + send({ version: 3, type: "snapshot", payload: redacted }); expect(root.querySelector("[data-role]")!.hidden).toBe(false); expect(root.querySelector("[data-role]")?.textContent).toContain("SPECTATING"); @@ -127,18 +161,206 @@ describe("browser lifecycle and accessible overlays", () => { }); it("keeps authorization failures visible and reloads before retrying", async () => { - vi.mocked(authorizeDiscord).mockRejectedValueOnce(new ClientError("sdk_authenticate_failed", true)); + mocks.authorize.mockRejectedValueOnce(new ClientError("sdk_authenticate_failed", true)); history.replaceState({}, "", "/?instance_id=launch"); const root = document.createElement("div"); const reload = vi.fn(); const app = new HandsApp(root, reload); app.start(); - await vi.waitFor(() => expect(root.querySelector("[data-status]")?.textContent).toBe("Unable to continue (sdk_authenticate_failed).")); + await vi.waitFor(() => expect(root.querySelector("[data-status]")?.textContent).toBe("Unable to continue: Discord did not confirm your identity (sdk_authenticate_failed).")); const retry = root.querySelector("[data-retry]")!; expect(retry.hidden).toBe(false); retry.click(); expect(reload).toHaveBeenCalledOnce(); expect(mocks.sessionDestroy).not.toHaveBeenCalled(); + // The reload's pagehide tears the app down; closing the SDK then would close the Activity instead. + app.destroy(); + expect(mocks.activityClose).not.toHaveBeenCalled(); + }); + + it.each([ + ["the bootstrap", (): void => { mocks.authorize.mockRejectedValueOnce(new ClientError("client_outdated", true)); }], + ["the socket", (): void => undefined], + ])("asks for a reload, not another sign-in, when %s shows Hands was updated", async (source, arrange) => { + arrange(); + history.replaceState({}, "", "/?instance_id=launch"); + const root = document.createElement("div"); + const reload = vi.fn(); + const app = new HandsApp(root, reload); + app.start(); + if (source === "the socket") { + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + send({ version: 3, type: "error", code: "client_outdated" }); + mocks.callbacks?.onFatal("client_outdated"); + } + await vi.waitFor(() => expect(root.querySelector("[data-status]")?.textContent).toBe("Hands was updated. Reload to continue (client_outdated).")); + const retry = root.querySelector("[data-retry]")!; + expect(retry.hidden).toBe(false); + expect(retry.textContent).toBe("Reload"); + const authorizations = mocks.authorize.mock.calls.length; + retry.click(); + expect(reload).toHaveBeenCalledOnce(); + expect(mocks.authorize.mock.calls.length).toBe(authorizations); + app.destroy(); + }); + + it("plays the finish without the overlay while the result is still on its way, but not forever", async () => { + const root = document.createElement("main"); + const app = new HandsApp(root); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); + const overlay = root.querySelector("[data-overlay]")!; + expect(overlay.hidden).toBe(false); + vi.useFakeTimers(); + send({ version: 3, type: "snapshot", payload: makeSnapshot(101, "complete") }); + expect(overlay.hidden).toBe(true); + vi.advanceTimersByTime(4_200); + expect(overlay.hidden).toBe(false); + vi.useRealTimers(); + app.destroy(); + }); + + it("keeps the result overlay hidden until the knockout replay has revealed the result", async () => { + const root = document.createElement("main"); + const app = new HandsApp(root); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); + const overlay = root.querySelector("[data-overlay]")!; + expect(overlay.hidden).toBe(false); + mocks.resultVisible = false; + vi.useFakeTimers(); + send({ version: 3, type: "final", match_id: "m-replay", winner_id: "one", method: "ko", round: 1, scorecards: [], ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }); + expect(overlay.hidden).toBe(true); + vi.advanceTimersByTime(1_000); + expect(overlay.hidden).toBe(true); + mocks.resultVisible = true; + vi.advanceTimersByTime(250); + expect(overlay.hidden).toBe(false); + vi.useRealTimers(); + app.destroy(); + }); + + it("offers a rematch after the result hold and retries while the ring is still clearing", async () => { + history.replaceState({}, "", "/?instance_id=launch"); + const root = document.createElement("div"); + const app = new HandsApp(root); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); + const final = (matchId: string): ServerMessage => ({ version: 3, type: "final", match_id: matchId, winner_id: "one", method: "decision", round: 1, scorecards: [], ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }); + const button = root.querySelector("[data-rematch]")!; + expect(button.hidden).toBe(true); + vi.useFakeTimers(); + send(final("m1")); + expect(button.hidden).toBe(false); + expect(button.disabled).toBe(true); + expect(button.textContent).toContain("Rematch in"); + vi.advanceTimersByTime(11_500); + expect(button.disabled).toBe(false); + expect(button.textContent).toBe("Rematch"); + const first = mocks.callbacks; + button.click(); + vi.useRealTimers(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBe(first)); + expect(button.hidden).toBe(true); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1516, players: [...players], server_tick: 900, next_sequence: 0, reconnect_ticket: "again" }); + vi.useFakeTimers(); + const held = mocks.callbacks; + send(final("m1")); + expect(root.querySelector("[data-status]")?.textContent).toContain("still being cleared"); + expect(root.querySelector("[data-final]")?.textContent).toBe(""); + vi.advanceTimersByTime(3_100); + vi.useRealTimers(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBe(held)); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1516, players: [...players], server_tick: 1, next_sequence: 0, reconnect_ticket: "fresh" }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(1, "countdown") }); + expect(root.querySelector("[data-status]")?.textContent).toBe("Bout countdown."); + expect(root.querySelector("[data-status]")?.hidden).toBe(true); + expect(root.querySelector("[data-overlay]")?.hasAttribute("data-raised")).toBe(true); + send(final("m2")); + expect(root.querySelector("[data-status]")?.textContent).toBe("Bout complete. Scorecards and rating changes are displayed."); + expect(root.querySelector("[data-status]")?.hidden).toBe(false); + expect(button.hidden).toBe(false); + expect(button.disabled).toBe(true); + app.destroy(); + }); + + it("retries a rematch that reaches the old room while it is still closing, once per refusal", async () => { + history.replaceState({}, "", "/?instance_id=launch"); + const root = document.createElement("div"); + const app = new HandsApp(root); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); + vi.useFakeTimers(); + send({ version: 3, type: "final", match_id: "m1", winner_id: "one", method: "decision", round: 1, scorecards: [], ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }); + vi.advanceTimersByTime(11_500); + const first = mocks.callbacks; + root.querySelector("[data-rematch]")!.click(); + vi.useRealTimers(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBe(first)); + const closing = mocks.callbacks; + const authorizations = mocks.authorize.mock.calls.length; + vi.useFakeTimers(); + send({ version: 3, type: "error", code: "room_closed" }); + closing?.onFatal("room_closed"); + expect(root.querySelector("[data-status]")?.textContent).toContain("still being cleared"); + vi.advanceTimersByTime(3_100); + vi.useRealTimers(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBe(closing)); + expect(mocks.authorize.mock.calls.length).toBe(authorizations + 1); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1516, players: [players[0]], server_tick: 0, next_sequence: 0, reconnect_ticket: "fresh" }); + send({ version: 3, type: "waiting", open_seats: 1 }); + send({ version: 3, type: "error", code: "room_closed" }); + expect(root.querySelector("[data-status]")?.textContent).toContain("already ended"); + app.destroy(); + }); + + it("relearns the server clock on a new connection and when a paused bout resumes", async () => { + history.replaceState({}, "", "/?instance_id=launch"); + const root = document.createElement("div"); + const app = new HandsApp(root); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + mocks.rendererResyncs = 0; + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); + expect(mocks.rendererResyncs).toBe(1); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); + send({ version: 3, type: "paused", player_id: "two", grace_ms: 20_000 }); + expect(mocks.rendererResyncs).toBe(1); + send({ version: 3, type: "resumed", player_id: "two" }); + expect(mocks.rendererResyncs).toBe(2); + app.destroy(); + }); + + it("shows copyable diagnostics in the settings panel", async () => { + history.replaceState({}, "", "/?instance_id=launch"); + const root = document.createElement("div"); + const app = new HandsApp(root); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + const writeText = vi.fn((_text: string) => Promise.resolve()); + Object.defineProperty(navigator, "clipboard", { value: { writeText }, configurable: true }); + root.querySelector("[data-settings]")!.click(); + const text = root.querySelector("[data-diagnostics]")?.textContent ?? ""; + expect(text).toContain("frame:"); + expect(text).toContain("browser:"); + expect(text).toContain("last error: none"); + root.querySelector("[data-copy-diagnostics]")!.click(); + expect(writeText).toHaveBeenCalledOnce(); + expect(writeText).toHaveBeenCalledWith(expect.stringContaining("input latency:")); + Object.defineProperty(navigator, "clipboard", { value: undefined, configurable: true }); + document.body.append(root); + root.querySelector("[data-copy-diagnostics]")!.click(); + expect(root.querySelector("[data-copy-diagnostics]")?.textContent).toBe("Selected. Copy manually"); + expect(window.getSelection()?.toString()).toContain("frame:"); + root.remove(); app.destroy(); }); @@ -148,19 +370,21 @@ describe("browser lifecycle and accessible overlays", () => { const app = new HandsApp(root); app.start(); await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); - send({ version: 2, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); - send({ version: 2, type: "snapshot", payload: makeSnapshot(100) }); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); const firstCallbacks = mocks.callbacks!; firstCallbacks.onFatal("persistence_failed"); expect(mocks.rendererDestroy).toHaveBeenCalledOnce(); expect(root.querySelector("[data-retry]")!.hidden).toBe(false); expect(root.querySelector("canvas")).not.toBeNull(); root.querySelector("[data-retry]")!.click(); - await vi.waitFor(() => expect(mocks.rendererPushes).toHaveLength(2)); + await vi.waitFor(() => expect(mocks.callbacks).not.toBe(firstCallbacks)); expect(mocks.rendererDestroy).toHaveBeenCalledOnce(); expect(mocks.sessionDestroy).toHaveBeenCalledOnce(); - send({ version: 2, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 1, next_sequence: 0, reconnect_ticket: "new" }); - send({ version: 2, type: "snapshot", payload: makeSnapshot(1, "countdown") }); + expect(mocks.rendererPushes).toHaveLength(1); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 1, next_sequence: 0, reconnect_ticket: "new" }); + expect(mocks.rendererPushes).toHaveLength(2); + send({ version: 3, type: "snapshot", payload: makeSnapshot(1, "countdown") }); expect(mocks.rendererPushes).toEqual([[100], [1]]); expect(root.querySelector("[data-final]")?.textContent).toBe(""); expect(root.querySelector("[data-status]")?.textContent).toBe("Bout countdown."); @@ -174,10 +398,10 @@ describe("browser lifecycle and accessible overlays", () => { app.start(); await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); const longName = "A very long authoritative fighter name that canvas must truncate but semantics retain"; - send({ version: 2, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [{ ...players[0], name: longName }, players[1]], server_tick: 1, next_sequence: 0, reconnect_ticket: "new" }); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [{ ...players[0], name: longName }, players[1]], server_tick: 1, next_sequence: 0, reconnect_ticket: "new" }); const downed = { ...fighter("one", -100), is_downed: true, get_up_prompt: "get_up_left" as const, get_up_meter: 12, get_up_required: 50, get_up_count: 0 }; const snapshot = { ...makeSnapshot(2, "knockdown"), fighters: [downed, fighter("two", 100)] as const }; - send({ version: 2, type: "snapshot", payload: snapshot }); + send({ version: 3, type: "snapshot", payload: snapshot }); const summary = root.querySelector("[data-fight-summary]")!; const live = root.querySelector("[data-fight-status]")!; expect(summary.hasAttribute("aria-live")).toBe(false); @@ -187,13 +411,93 @@ describe("browser lifecycle and accessible overlays", () => { expect(live.textContent).toBe("Knockdown. Count 0. Press left now."); const firstLiveNode = live.firstChild; const staminaChanged = { ...snapshot, tick: 3, fighters: [{ ...downed, stamina: downed.stamina - 1 }, snapshot.fighters[1]] as const }; - send({ version: 2, type: "snapshot", payload: staminaChanged }); + send({ version: 3, type: "snapshot", payload: staminaChanged }); expect(summary.textContent).toContain(`stamina ${downed.stamina - 1}`); expect(live.firstChild).toBe(firstLiveNode); - send({ version: 2, type: "snapshot", payload: { ...staminaChanged, tick: 4, fighters: [{ ...staminaChanged.fighters[0], get_up_prompt: "get_up_right" }, staminaChanged.fighters[1]] } }); + send({ version: 3, type: "snapshot", payload: { ...staminaChanged, tick: 4, fighters: [{ ...staminaChanged.fighters[0], get_up_prompt: "get_up_right" }, staminaChanged.fighters[1]] } }); expect(live.textContent).toBe("Knockdown. Count 0. Press right now."); expect(live.firstChild).not.toBe(firstLiveNode); app.destroy(); }); + it("keeps the touch controls up but inert through the rest, and hides them outside the bout", async () => { + vi.mocked(window.matchMedia).mockImplementation((query: string) => ({ matches: query === "(pointer: coarse)", media: query, onchange: null, addListener: vi.fn(), removeListener: vi.fn(), addEventListener: vi.fn(), removeEventListener: vi.fn(), dispatchEvent: vi.fn() })); + history.replaceState({}, "", "/?instance_id=launch"); + const root = document.createElement("div"); + const app = new HandsApp(root); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + const controls = root.querySelector(".touch-controls")!; + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [players[0]], server_tick: 0, next_sequence: 0, reconnect_ticket: "rotated" }); + send({ version: 3, type: "waiting", open_seats: 1 }); + expect(controls.classList.contains("disabled")).toBe(true); + send({ version: 3, type: "ready", players: [...players] }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); + expect(controls.classList.contains("disabled")).toBe(false); + expect(controls.classList.contains("resting")).toBe(false); + send({ version: 3, type: "snapshot", payload: makeSnapshot(101, "rest") }); + expect(controls.classList.contains("disabled")).toBe(false); + expect(controls.classList.contains("resting")).toBe(true); + send({ version: 3, type: "snapshot", payload: makeSnapshot(102, "fight") }); + expect(controls.classList.contains("resting")).toBe(false); + send({ version: 3, type: "snapshot", payload: makeSnapshot(103, "complete") }); + expect(controls.classList.contains("disabled")).toBe(true); + app.destroy(); + }); + + it("keeps the page's one Discord SDK open through a rematch and a retried failure, and closes it at teardown", async () => { + const { DiscordActivity } = await vi.importActual("./discord"); + history.replaceState({}, "", "/?instance_id=launch&frame_id=frame&platform=mobile"); + vi.stubGlobal("fetch", handsBackend()); + const discord = fakeDiscord("launch"); + const makeSdk = vi.fn(() => discord as unknown as IDiscordSDK); + const root = document.createElement("div"); + const app = new HandsApp(root, vi.fn(), new DiscordActivity(makeSdk)); + app.start(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBeNull()); + send({ version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [...players], server_tick: 100, next_sequence: 8, reconnect_ticket: "rotated" }); + send({ version: 3, type: "snapshot", payload: makeSnapshot(100) }); + vi.useFakeTimers(); + send({ version: 3, type: "final", match_id: "m1", winner_id: "one", method: "decision", round: 1, scorecards: [], ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }); + vi.advanceTimersByTime(11_500); + const first = mocks.callbacks; + root.querySelector("[data-rematch]")!.click(); + vi.useRealTimers(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBe(first)); + expect(discord.commands.authorize).toHaveBeenCalledTimes(2); + expect(discord.close).not.toHaveBeenCalled(); + + const rematched = mocks.callbacks!; + rematched.onFatal("persistence_failed"); + expect(root.querySelector("[data-status]")?.textContent).toContain("could not be saved"); + expect(discord.close).not.toHaveBeenCalled(); + root.querySelector("[data-retry]")!.click(); + await vi.waitFor(() => expect(mocks.callbacks).not.toBe(rematched)); + expect(discord.commands.authorize).toHaveBeenCalledTimes(3); + expect(makeSdk).toHaveBeenCalledOnce(); + expect(discord.close).not.toHaveBeenCalled(); + + app.destroy(); + expect(discord.close).toHaveBeenCalledOnce(); + vi.unstubAllGlobals(); + }); + + it("reloads without closing the Activity when Discord authorization fails", async () => { + const { DiscordActivity } = await vi.importActual("./discord"); + history.replaceState({}, "", "/?instance_id=launch&frame_id=frame&platform=mobile"); + vi.stubGlobal("fetch", handsBackend()); + const discord = fakeDiscord("launch"); + discord.commands.authenticate.mockRejectedValue(new Error("host rejected")); + const reload = vi.fn(); + const root = document.createElement("div"); + const app = new HandsApp(root, reload, new DiscordActivity(() => discord as unknown as IDiscordSDK)); + app.start(); + await vi.waitFor(() => expect(root.querySelector("[data-status]")?.textContent).toContain("(sdk_authenticate_failed)")); + expect(discord.close).not.toHaveBeenCalled(); + root.querySelector("[data-retry]")!.click(); + expect(reload).toHaveBeenCalledOnce(); + app.destroy(); + expect(discord.close).not.toHaveBeenCalled(); + vi.unstubAllGlobals(); + }); }); diff --git a/web/hands/src/app.ts b/web/hands/src/app.ts index cdfd2a63..d609ecea 100644 --- a/web/hands/src/app.ts +++ b/web/hands/src/app.ts @@ -1,8 +1,11 @@ +import { RoundClock } from "./render/hud"; import { AudioFeedback } from "./audio"; import { ClientError, safeError } from "./api"; -import { authorizeDiscord, type DiscordSession } from "./discord"; +import { DiscordActivity, type ActivityAuthorizer, type DiscordSession } from "./discord"; +import { describeError } from "./errors"; import { HapticFeedback } from "./haptics"; import { CONTROL_HELP } from "./input/bindings"; +import { coarsePointer } from "./input/touch"; import { InputController } from "./input/input"; import { EventDeduplicator } from "./interpolation"; import { NetworkController } from "./network"; @@ -12,6 +15,15 @@ import { initialState, reduceState, type GameState } from "./state"; import type { EngineSnapshot, ServerMessage } from "./types"; const CONTACT_FEEDBACK_KINDS = new Set(["hit", "counter_hit", "block", "perfect_block", "guard_break", "knockdown"]); +// The room keeps the finished bout for its result hold (ten seconds by default); a rejoin inside +// that window only replays the old final, so the rematch waits it out and retries if it still hits it. +const CONTROL_HINT_KEYBOARD = "Move WASD · Jab F/J · Straight R/U · Hook G/H · Uppercut T/Y · Guard Q/E · Body Shift · Power Alt"; +const CONTROL_HINT_TOUCH = "Left side: drag to move · Right pads: L/R punches · Hold BODY, POWER or GUARD · Tap SLIP, WEAVE, PULL or CLINCH"; +const REMATCH_HOLD_MS = 11_000; +/** How long the finish plays without the overlay while the result is still on its way. */ +const RESULT_WAIT_MS = 4_000; +const REMATCH_RETRY_MS = 3_000; +const REMATCH_MAX_ATTEMPTS = 6; export class HandsApp { private state: GameState = initialState; @@ -27,13 +39,27 @@ export class HandsApp { private destroyed = false; private generation = 0; private reloadOnRetry = false; + private reloading = false; private readonly canvas: HTMLCanvasElement; private readonly status: HTMLElement; + private readonly overlay: HTMLElement; private readonly roleIndicator: HTMLElement; private readonly controlsButton: HTMLButtonElement; private readonly controlsPanel: HTMLElement; private readonly retry: HTMLButtonElement; + private readonly rematchButton: HTMLButtonElement; + private readonly hint: HTMLElement; + private diagnosticsTimer: number | null = null; + private finalReceivedAt = 0; + private lastFinalMatchId: string | null = null; + private rematchAttempts = 0; + private rematchTimer: number | null = null; + private rematchCountdownTimer: number | null = null; + private resultRevealTimer: number | null = null; + private resultWaitTimer: number | null = null; + private completeSince: number | null = null; + private readonly summaryClock = new RoundClock(); private readonly fightSummary: HTMLElement; private readonly liveFightStatus: HTMLElement; private readonly finalSummary: HTMLElement; @@ -41,20 +67,26 @@ export class HandsApp { constructor( private readonly root: HTMLElement, private readonly reloadPage: () => void = () => window.location.reload(), + private readonly authorizer: ActivityAuthorizer = new DiscordActivity(), ) { - root.innerHTML = `
HANDSauthoritative two-player boxing

`; + root.innerHTML = `
HANDSauthoritative two-player boxing

`; this.canvas = root.querySelector("canvas")!; this.status = root.querySelector("[data-status]")!; + this.overlay = root.querySelector("[data-overlay]")!; this.roleIndicator = root.querySelector("[data-role]")!; this.controlsButton = root.querySelector("[data-controls]")!; this.controlsPanel = root.querySelector("[data-controls-panel]")!; this.retry = root.querySelector("[data-retry]")!; + this.rematchButton = root.querySelector("[data-rematch]")!; + this.hint = root.querySelector("[data-hint]")!; + this.rematchButton.addEventListener("click", this.onRematch); this.fightSummary = root.querySelector("[data-fight-summary]")!; this.liveFightStatus = root.querySelector("[data-fight-status]")!; this.finalSummary = root.querySelector("[data-final]")!; this.retry.addEventListener("click", this.onRetry); this.bindPanels(); this.syncSettings(); + this.input.attachTouch(root.querySelector(".activity")!); } start(): void { @@ -78,6 +110,67 @@ export class HandsApp { this.finalSummary.textContent = ""; this.fightSummary.textContent = ""; this.liveFightStatus.textContent = ""; + this.clearRematchTimers(); + this.rematchButton.hidden = true; + } + + private readonly onRematch = (): void => { + if (this.rematchButton.disabled || this.state.stage !== "complete") return; + this.rematchAttempts = 1; + void this.authorize(); + }; + + private clearRematchTimers(): void { + if (this.rematchTimer !== null) window.clearTimeout(this.rematchTimer); + if (this.rematchCountdownTimer !== null) window.clearInterval(this.rematchCountdownTimer); + this.rematchTimer = null; + this.rematchCountdownTimer = null; + } + + /** Keeps the overlay out of the knockout replay's way until the result panel is on screen. */ + private awaitResultReveal(): void { + if (this.resultRevealTimer !== null) window.clearInterval(this.resultRevealTimer); + const check = (): void => { + const visible = this.renderer?.resultVisible ?? true; + this.overlay.hidden = this.state.stage === "complete" && !visible; + if ((visible || this.state.stage !== "complete") && this.resultRevealTimer !== null) { + window.clearInterval(this.resultRevealTimer); + this.resultRevealTimer = null; + } + }; + this.resultRevealTimer = window.setInterval(check, 200); + check(); + } + + private startRematchCountdown(): void { + this.clearRematchTimers(); + if (this.state.role !== "fighter") return; + const tick = (): void => { + const remaining = Math.ceil((this.finalReceivedAt + REMATCH_HOLD_MS - Date.now()) / 1000); + this.rematchButton.hidden = this.state.stage !== "complete"; + this.rematchButton.disabled = remaining > 0; + this.setText(this.rematchButton, remaining > 0 ? `Rematch in ${remaining}s` : "Rematch"); + if (remaining <= 0 && this.rematchCountdownTimer !== null) { + window.clearInterval(this.rematchCountdownTimer); + this.rematchCountdownTimer = null; + } + }; + tick(); + this.rematchCountdownTimer = window.setInterval(tick, 1000); + } + + private scheduleRematchRetry(): void { + if (this.rematchTimer !== null) return; + if (this.rematchAttempts >= REMATCH_MAX_ATTEMPTS) { + this.fail("rematch_unavailable"); + return; + } + this.rematchAttempts += 1; + this.setText(this.status, "The ring is still being cleared… trying again."); + this.rematchTimer = window.setTimeout(() => { + this.rematchTimer = null; + void this.authorize(); + }, REMATCH_RETRY_MS); } private async authorize(): Promise { @@ -87,7 +180,7 @@ export class HandsApp { this.setText(this.status, "Securing Discord Activity session…"); this.retry.hidden = true; try { - const session = await authorizeDiscord(this.abort.signal); + const session = await this.authorizer.authorize(this.abort.signal); if (this.destroyed || generation !== this.generation) { session.destroy(); return; @@ -95,13 +188,10 @@ export class HandsApp { this.session = session; this.dispatch({ type: "bootstrap", simulation: session.bootstrap.simulation }); this.dispatch({ type: "authorized", player: session.player }); - this.renderer = new FightRenderer(this.canvas, session.bootstrap.simulation, () => this.settings.current); - this.renderer.onContact = (event) => { - this.audio.event(event); - this.haptics.event(event); - }; - this.renderer.onArcadeInjury = (injury) => this.audio.injury(injury); - this.input.onAction((action) => this.renderer?.predictAction?.(action)); + this.input.onAction((action) => { + this.renderer?.predictAction?.(action); + this.network?.notifyAction(); + }); const ticket = session.takeTicket(); if (ticket === null) throw new Error("ticket_unavailable"); const network = new NetworkController(ticket, () => this.input.frame(), { @@ -127,29 +217,68 @@ export class HandsApp { } } + /** + * The renderer is built once the socket is authenticated. Building it + * earlier delayed the authenticate frame behind model parsing and shader + * compilation on slow machines, which tripped the server's handshake + * timeout. + */ + private ensureRenderer(): void { + if (this.renderer !== null || this.session === null || this.destroyed) return; + const renderer = new FightRenderer(this.canvas, this.session.bootstrap.simulation, () => this.settings.current, { + localInput: () => this.input.held(), + inputSequenceOf: (actionId) => this.network?.sequenceOf(actionId) ?? null, + }); + renderer.onContact = (event) => { + this.audio.event(event); + this.haptics.event(event); + }; + renderer.onArcadeInjury = (injury) => this.audio.injury(injury); + this.renderer = renderer; + } + private receive(message: ServerMessage): void { if (message.type === "error") { this.fail(message.code); return; } + if (message.type === "welcome") this.ensureRenderer(); + if (message.type === "welcome" || message.type === "resumed") this.renderer?.resyncClock(); + if (message.type === "waiting" || message.type === "ready") this.rematchAttempts = 0; + if (message.type === "final" && this.rematchAttempts > 0 && message.match_id === this.lastFinalMatchId) { + this.scheduleRematchRetry(); + return; + } this.dispatch({ type: "message", message }); if (message.type === "snapshot") this.receiveSnapshot(message.payload); if (message.type === "final") { + this.rematchAttempts = 0; + this.lastFinalMatchId = message.match_id; + this.finalReceivedAt = Date.now(); this.renderer?.setFinal(message); this.audio.result(message); + this.startRematchCountdown(); + this.awaitResultReveal(); } - this.renderer?.setPlayers(this.state.players, this.state.playerId); + this.renderer?.setPlayers(this.state.players, this.state.playerId, this.state.playerOrder); this.renderer?.setReconnect(this.state.reconnectMs); this.renderState(); } + /** Smoothed input acknowledgement latency of the local fighter and the render scale, for diagnostics. */ + get networkStats(): { inputLatencyMs: number | null; resolutionScale: number | null; gpu: { geometries: number; textures: number; programs: number } | null } { + return { inputLatencyMs: this.network?.inputLatencyMs ?? null, resolutionScale: this.renderer?.resolutionScale ?? null, gpu: this.renderer?.memoryInfo ?? null }; + } + private receiveSnapshot(snapshot: EngineSnapshot): void { + this.renderer?.setInputLatency(this.network?.inputLatencyMs ?? null); this.renderer?.push(snapshot); const viewer = snapshot.fighters.find((fighter) => fighter.player_id === this.state.playerId); this.input.setKnockdown(viewer?.is_downed === true); if (viewer !== undefined) { this.audio.snapshot(snapshot.tick, viewer.stamina, viewer.maximum_stamina, viewer.trauma.head + viewer.trauma.body); } + this.audio.roundClock(snapshot.phase, snapshot.round_number, snapshot.phase_ticks_remaining, this.state.simulation?.tick_rate ?? 30); for (const event of this.feedbackEvents.accept(snapshot.events)) { if (CONTACT_FEEDBACK_KINDS.has(event.kind)) continue; this.audio.event(event); @@ -178,10 +307,27 @@ export class HandsApp { rest: "Between-round rest.", paused: `Connection paused. ${Math.ceil(this.state.reconnectMs / 1000)} seconds remain.`, complete: "Bout complete. Scorecards and rating changes are displayed.", - fatal: `Unable to continue (${this.state.safeError ?? "safe_error"}).`, + fatal: describeError(this.state.safeError ?? "safe_error"), }; const spectating = this.state.role === "spectator"; this.setText(this.status, spectating ? `Spectating — ${labels[this.state.stage]}` : labels[this.state.stage]); + this.status.hidden = ["countdown", "fight", "knockdown", "foul_recovery", "rest"].includes(this.state.stage); + this.overlay.toggleAttribute("data-raised", this.state.snapshot !== null); + // The engine's last snapshot arrives before the result does; the finish plays without the overlay. + if (this.state.stage !== "complete") { + this.overlay.hidden = false; + this.completeSince = null; + } else if (this.state.final === null) { + this.completeSince ??= Date.now(); + const waited = Date.now() - this.completeSince; + this.overlay.hidden = waited < RESULT_WAIT_MS; + if (this.overlay.hidden && this.resultWaitTimer === null) { + this.resultWaitTimer = window.setTimeout(() => { + this.resultWaitTimer = null; + this.renderState(); + }, RESULT_WAIT_MS - waited + 50); + } + } this.roleIndicator.hidden = !spectating; this.controlsButton.hidden = spectating; if (spectating) { @@ -198,8 +344,15 @@ export class HandsApp { : labels[this.state.stage]; this.setText(this.liveFightStatus, liveStatus); this.retry.hidden = this.state.stage !== "fatal"; + this.setText(this.retry, this.reloadOnRetry ? "Reload" : "Retry securely"); + if (this.state.stage !== "complete") this.rematchButton.hidden = true; + const showHint = !spectating && (this.state.stage === "waiting" || this.state.stage === "countdown"); + this.hint.hidden = !showHint; + if (showHint) this.setText(this.hint, coarsePointer() ? CONTROL_HINT_TOUCH : CONTROL_HINT_KEYBOARD); const active = !spectating && ["countdown", "fight", "knockdown", "foul_recovery"].includes(this.state.stage); - this.input.setActive(active); + // Between rounds and through pauses the touch controls stay up, inert, so a thumb already in place counts at the bell. + const resting = !spectating && this.state.snapshot !== null && (this.state.stage === "rest" || this.state.stage === "paused"); + this.input.setActive(active, active || resting); this.network?.setActive(active); this.renderFightSummary(); if (this.state.final !== null) { @@ -212,7 +365,7 @@ export class HandsApp { const snapshot = this.state.snapshot; if (snapshot === null) return; const tickRate = this.state.simulation?.tick_rate ?? 30; - const seconds = Math.floor(snapshot.phase_ticks_remaining / tickRate); + const seconds = Math.floor(this.summaryClock.ticks(snapshot) / tickRate); const clock = `${Math.floor(seconds / 60)}:${String(seconds % 60).padStart(2, "0")}`; const fighters = snapshot.fighters.map((fighter) => { const player = this.state.players[fighter.player_id]; @@ -229,6 +382,8 @@ export class HandsApp { private readonly onRetry = (): void => { if (this.reloadOnRetry) { + // The reload brings up a new page and SDK; closing this SDK on the way out would close the Activity. + this.reloading = true; this.reloadPage(); return; } @@ -246,6 +401,39 @@ export class HandsApp { }; bind("[data-controls]", "[data-controls-panel]"); bind("[data-settings]", "[data-settings-panel]"); + const settingsPanel = this.root.querySelector("[data-settings-panel]")!; + this.root.querySelector("[data-settings]")!.addEventListener("click", () => { + if (this.diagnosticsTimer !== null) window.clearInterval(this.diagnosticsTimer); + this.diagnosticsTimer = null; + if (settingsPanel.hidden) return; + this.refreshDiagnostics(); + this.diagnosticsTimer = window.setInterval(() => this.refreshDiagnostics(), 1000); + }); + const copy = this.root.querySelector("[data-copy-diagnostics]")!; + copy.addEventListener("click", () => { + const text = this.diagnosticsText(); + const done = (): void => { + this.setText(copy, "Copied"); + window.setTimeout(() => this.setText(copy, "Copy diagnostics"), 1500); + }; + const selectFallback = (): void => { + const block = this.root.querySelector("[data-diagnostics]")!; + const selection = window.getSelection(); + if (selection === null) return; + const range = document.createRange(); + range.selectNodeContents(block); + selection.removeAllRanges(); + selection.addRange(range); + this.setText(copy, "Selected. Copy manually"); + window.setTimeout(() => this.setText(copy, "Copy diagnostics"), 2500); + }; + const clipboard = navigator.clipboard; + if (clipboard === undefined || typeof clipboard.writeText !== "function") { + selectFallback(); + return; + } + clipboard.writeText(text).then(done).catch(selectFallback); + }); this.root.querySelector("[data-volume]")!.addEventListener("input", (event) => { this.settings.update({ volume: Number((event.target as HTMLInputElement).value) }); this.audio.setVolume(); @@ -265,6 +453,28 @@ export class HandsApp { }); } + /** One block of text a player can paste into the server when reporting a problem. */ + private diagnosticsText(): string { + const stats = this.networkStats; + const diag = this.renderer?.diagnostics; + const fps = diag === undefined || diag.frameMs <= 0 ? "-" : (1000 / diag.frameMs).toFixed(0); + return [ + `stage: ${this.state.stage} · role: ${this.state.role ?? "-"}`, + `input latency: ${stats.inputLatencyMs === null ? "-" : `${Math.round(stats.inputLatencyMs)} ms`}`, + `frame: ${diag === undefined ? "-" : `${diag.frameMs.toFixed(1)} ms (${fps} fps)`} · render scale: ${diag?.resolutionScale ?? "-"}`, + `gpu objects: ${diag === undefined ? "-" : `${diag.gpu.geometries} geometries, ${diag.gpu.textures} textures, ${diag.gpu.programs} programs`}`, + `graphics: ${diag?.graphics ?? "-"}`, + `browser: ${navigator.userAgent}`, + `pointer: ${coarsePointer() ? "coarse" : "fine"} · viewport: ${window.innerWidth}x${window.innerHeight} @${window.devicePixelRatio}`, + `last error: ${this.state.safeError ?? "none"}`, + `match: ${this.state.final?.match_id ?? "-"}`, + ].join("\n"); + } + + private refreshDiagnostics(): void { + this.setText(this.root.querySelector("[data-diagnostics]")!, this.diagnosticsText()); + } + private syncSettings(): void { const settings = this.settings.current; this.root.querySelector("[data-volume]")!.value = String(settings.volume); @@ -274,6 +484,13 @@ export class HandsApp { } private fail(code: string): void { + // A rematch can reach the old room while it is still closing; a new one opens a moment later. + if (code === "room_closed" && this.rematchAttempts > 0) { + this.scheduleRematchRetry(); + return; + } + // A server on a newer protocol cannot be played from this page; Retry reloads it. + if (code === "client_outdated") this.reloadOnRetry = true; this.dispatch({ type: "fatal", code }); this.network?.dispose(); this.network = null; @@ -293,11 +510,18 @@ export class HandsApp { this.abort.abort(); this.network?.dispose(); this.session?.destroy(); + if (!this.reloading) this.authorizer.close(); this.renderer?.destroy(); this.input.destroy(); this.audio.destroy(); this.settings.destroy(); this.retry.removeEventListener("click", this.onRetry); + this.rematchButton.removeEventListener("click", this.onRematch); + this.clearRematchTimers(); + if (this.diagnosticsTimer !== null) window.clearInterval(this.diagnosticsTimer); + if (this.resultRevealTimer !== null) window.clearInterval(this.resultRevealTimer); + if (this.resultWaitTimer !== null) window.clearTimeout(this.resultWaitTimer); + this.diagnosticsTimer = null; this.root.replaceChildren(); } } diff --git a/web/hands/src/assets/fighter-glb.ts b/web/hands/src/assets/fighter-glb.ts index 9ad700cb..0ae3b1fa 100644 --- a/web/hands/src/assets/fighter-glb.ts +++ b/web/hands/src/assets/fighter-glb.ts @@ -1,3 +1,3 @@ // Generated from assets-src/Boxer.glb (Texel, Inc., CC BY 4.0). -export const FIGHTER_GLB_GZIP_BASE64 = "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"; -export const FIGHTER_GLB_SHA256 = "c24bd7bc5d387cbc03c16c40d716865d66e33591e6721d3c1b8f04ea779c1e33"; +export const FIGHTER_GLB_GZIP_BASE64 = "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1.5118, - 0.0281 - ], - [ - -0.1129, - 1.5117, - 0.0281 - ], - [ - -0.1137, - 1.5116, - 0.0281 - ] - ] - } - } -} diff --git a/web/hands/src/assets/fighter-textures.ts b/web/hands/src/assets/fighter-textures.ts index b894d918..876cae13 100644 --- a/web/hands/src/assets/fighter-textures.ts +++ b/web/hands/src/assets/fighter-textures.ts @@ -1,2 +1,2 @@ // Generated from assets-src/Boxer.glb (Texel, Inc., CC BY 4.0). -export const FIGHTER_TEXTURE_DATA_URLS = 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","gloves":"data:image/png;base64,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","body":"data:image/png;base64,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","shoes":"data:image/png;base64,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","pants":"data:image/png;base64,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"} as const; +export const FIGHTER_TEXTURE_DATA_URLS = 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","gloves":"data:image/jpeg;base64,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","body":"data:image/jpeg;base64,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","shoes":"data:image/jpeg;base64,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"} as const; diff --git a/web/hands/src/audio.ts b/web/hands/src/audio.ts index d860d1f7..d8922dca 100644 --- a/web/hands/src/audio.ts +++ b/web/hands/src/audio.ts @@ -21,6 +21,9 @@ interface ToneSpec { readonly delay?: number; } +/** Gestures that may unlock audio. A touch pointerdown is not a user activation; the pointerup, touchend and click after it are. */ +const UNLOCK_EVENTS = ["pointerdown", "pointerup", "touchend", "click", "keydown"] as const; + const WHOOSH: Record = { jab: { from: 520, to: 1500, duration: 0.09 }, straight: { from: 420, to: 1150, duration: 0.12 }, @@ -41,8 +44,13 @@ export class AudioFeedback { private readonly timers = new Set(); private lastBreathTick = -300; private lastHeartbeatTick = -300; + private clapperRound = 0; private readonly unlockListener = (): void => { + // Every gesture resumes the context itself until audio is unlocked: a resume() made during a + // touch press, which is not an activation, can stay pending, and the unlock waits on it. + const context = this.context; + if (context !== null && context.state !== "running") void context.resume().catch(() => undefined); void this.unlock().catch(() => undefined); }; @@ -54,8 +62,7 @@ export class AudioFeedback { }; constructor(private readonly settings: () => Settings) { - window.addEventListener("pointerdown", this.unlockListener); - window.addEventListener("keydown", this.unlockListener); + for (const type of UNLOCK_EVENTS) window.addEventListener(type, this.unlockListener); document.addEventListener("visibilitychange", this.visibility); } @@ -85,8 +92,7 @@ export class AudioFeedback { if (this.destroyed || this.context !== context) return; this.injuryBuffers = injuryBuffers; this.unlocked = true; - window.removeEventListener("pointerdown", this.unlockListener); - window.removeEventListener("keydown", this.unlockListener); + for (const type of UNLOCK_EVENTS) window.removeEventListener(type, this.unlockListener); if (!this.crowdStarted) { this.crowdStarted = true; this.crowdBed(); @@ -112,33 +118,35 @@ export class AudioFeedback { case "hit": case "counter_hit": { const body = event.detail.endsWith("body"); - const loud = Math.min(0.34, 0.16 + event.amount / 1400) * (event.kind === "counter_hit" ? 1.3 : 1); - this.tone({ from: body ? 120 : 150, to: 42, duration: 0.13, type: "sine", gain: loud }); - this.noise({ duration: 0.06, frequency: body ? 420 : 1650, gain: loud * 0.85, type: "bandpass", q: 0.9 }); - this.noise({ duration: 0.16, frequency: body ? 190 : 300, gain: loud * 0.6 }); - if (event.kind === "counter_hit") this.crowdSwell(0.5); + const weight = Math.min(1, event.amount / 260); + const loud = Math.min(0.36, 0.14 + weight * 0.2) * (event.kind === "counter_hit" ? 1.25 : 1); + this.impact(loud, body, weight); + if (event.kind === "counter_hit" || weight > 0.7) this.crowdSwell(0.35 + weight * 0.4); break; } case "block": - this.noise({ duration: 0.05, frequency: 900, gain: 0.15, type: "bandpass", q: 1.4 }); - this.tone({ from: 170, to: 120, duration: 0.05, type: "triangle", gain: 0.06 }); + this.noise({ duration: 0.045, frequency: 1200, sweepTo: 600, gain: 0.14, type: "bandpass", q: 1.1 }); + this.noise({ duration: 0.09, frequency: 260, gain: 0.08 }); + this.tone({ from: 160, to: 110, duration: 0.06, type: "triangle", gain: 0.05 }); break; case "perfect_block": - this.noise({ duration: 0.05, frequency: 1450, gain: 0.16, type: "bandpass", q: 1.6 }); - this.tone({ from: 260, to: 200, duration: 0.06, type: "triangle", gain: 0.07 }); + this.noise({ duration: 0.05, frequency: 1800, sweepTo: 900, gain: 0.16, type: "bandpass", q: 1.6 }); + this.tone({ from: 280, to: 210, duration: 0.06, type: "triangle", gain: 0.06 }); break; case "guard_break": - this.noise({ duration: 0.18, frequency: 520, gain: 0.24 }); - this.tone({ from: 230, to: 78, duration: 0.2, type: "sawtooth", gain: 0.1 }); - this.crowdSwell(0.4); + this.impact(0.3, false, 0.9); + this.tone({ from: 230, to: 78, duration: 0.2, type: "sawtooth", gain: 0.08 }); + this.crowdSwell(0.5); break; case "stun": this.tone({ from: 96, to: 74, duration: 0.22, type: "sine", gain: 0.1 }); + this.crowdSwell(0.3); break; case "knockdown": - this.tone({ from: 68, to: 32, duration: 0.34, type: "sine", gain: 0.3 }); - this.noise({ duration: 0.22, frequency: 260, gain: 0.26 }); - this.crowdSwell(1); + this.impact(0.34, false, 1); + this.tone({ from: 60, to: 28, duration: 0.42, type: "sine", gain: 0.3 }); + this.noise({ duration: 0.3, frequency: 140, gain: 0.24 }); + this.crowdRoar(1); break; case "bell": { const strikes = event.detail === "round_start" ? 3 : 1; @@ -159,19 +167,42 @@ export class AudioFeedback { case "clinch_start": this.noise({ duration: 0.12, frequency: 190, gain: 0.1 }); break; + case "taunt": + this.tone({ from: 520, to: 390, duration: 0.18, type: "triangle", gain: 0.05 }); + this.crowdSwell(0.45); + break; + case "clinch_denied": + case "clinch_interrupted": + this.noise({ duration: 0.1, frequency: 520, sweepTo: 240, gain: 0.05, type: "bandpass", q: 1 }); + break; case "bleed": break; case "exhausted": this.noise({ duration: 0.24, frequency: 360, gain: 0.05 }); break; case "result": - this.crowdSwell(0.8); + this.crowdRoar(0.8); break; default: break; } } + /** The ten-second clapper: two wood-block cracks once per round when ten seconds remain. */ + roundClock(phase: string, roundNumber: number, ticksRemaining: number, tickRate: number): void { + if (phase !== "fight" || ticksRemaining > 10 * tickRate || this.clapperRound === roundNumber) return; + this.clapperRound = roundNumber; + if (!this.unlocked) return; + this.noise({ duration: 0.05, frequency: 2600, gain: 0.42, type: "bandpass", q: 1.4 }); + this.noise({ duration: 0.09, frequency: 700, gain: 0.18, type: "bandpass", q: 0.8 }); + const timer = window.setTimeout(() => { + this.timers.delete(timer); + this.noise({ duration: 0.05, frequency: 2400, gain: 0.4, type: "bandpass", q: 1.4 }); + this.noise({ duration: 0.09, frequency: 660, gain: 0.16, type: "bandpass", q: 0.8 }); + }, 120); + this.timers.add(timer); + } + snapshot(tick: number, stamina: number, maximumStamina: number, trauma: number): void { if (!this.unlocked) return; const fatigue = 1 - stamina / Math.max(1, maximumStamina); @@ -229,6 +260,27 @@ export class AudioFeedback { return buffers; } + /** Layered punch impact: sub thump, glove thud, and a short leather snap scaled by weight. */ + private impact(loud: number, body: boolean, weight: number): void { + this.tone({ from: body ? 86 : 118, to: body ? 34 : 44, duration: 0.14 + weight * 0.06, type: "sine", gain: loud }); + this.noise({ duration: 0.05 + weight * 0.03, frequency: body ? 240 : 420, sweepTo: body ? 120 : 200, gain: loud * 0.8, type: "bandpass", q: 0.8 }); + this.noise({ duration: 0.028, frequency: body ? 1500 : 2600, sweepTo: body ? 700 : 1400, gain: loud * (body ? 0.35 : 0.6), type: "bandpass", q: 1.3 }); + this.noise({ duration: 0.18 + weight * 0.1, frequency: body ? 150 : 210, gain: loud * 0.45 }); + } + + /** Full crowd eruption with a slow decay, used for knockdowns and finishes. */ + private crowdRoar(intensity: number): void { + const context = this.context; + if (context === null) return; + this.noise({ duration: 0.5, frequency: 900, sweepTo: 520, gain: Math.min(0.3, 0.12 + intensity * 0.18), type: "bandpass", q: 0.5 }); + const crowd = this.crowdGain; + if (crowd !== null) { + const now = context.currentTime; + crowd.gain.setValueAtTime(Math.min(0.16, 0.06 + intensity * 0.1), now); + crowd.gain.exponentialRampToValueAtTime(0.022, now + 4.5); + } + } + private tone(spec: ToneSpec): void { const context = this.context; const master = this.master; @@ -349,8 +401,7 @@ export class AudioFeedback { destroy(): void { this.destroyed = true; - window.removeEventListener("pointerdown", this.unlockListener); - window.removeEventListener("keydown", this.unlockListener); + for (const type of UNLOCK_EVENTS) window.removeEventListener(type, this.unlockListener); document.removeEventListener("visibilitychange", this.visibility); for (const timer of this.timers) clearTimeout(timer); this.timers.clear(); diff --git a/web/hands/src/dev-e2e.ts b/web/hands/src/dev-e2e.ts new file mode 100644 index 00000000..c90e4320 --- /dev/null +++ b/web/hands/src/dev-e2e.ts @@ -0,0 +1,29 @@ +import type { IDiscordSDK } from "@discord/embedded-app-sdk"; +import { bootstrap, exchangeToken, launchInstance } from "./api"; +import type { DiscordSession } from "./discord"; + +/** + * Development-only authorizer for playing the real client against + * scripts/hands_e2e_server.py without Discord: the real bootstrap and token + * routes are used, with a local handshake code instead of an OAuth code. + */ +export async function devAuthorizer(signal: AbortSignal): Promise { + const name = new URLSearchParams(window.location.search).get("player") ?? "Player"; + const instance = launchInstance(); + const boot = await bootstrap(instance, signal); + const token = await exchangeToken(`dev:${name}`, boot.state, signal); + let ticket: string | null = token.ticket; + return { + sdk: null as unknown as IDiscordSDK, + bootstrap: boot, + player: token.player, + takeTicket: () => { + const current = ticket; + ticket = null; + return current; + }, + destroy: () => { + ticket = null; + }, + }; +} diff --git a/web/hands/src/dev-fixtures.ts b/web/hands/src/dev-fixtures.ts index 9d6a2bb1..995e160c 100644 --- a/web/hands/src/dev-fixtures.ts +++ b/web/hands/src/dev-fixtures.ts @@ -1,10 +1,14 @@ +import { REST_CORNER_OFFSET } from "./manifest"; +import * as THREE from "three"; +import { SharedActionIntent } from "./input/action-buffer"; +import { TouchInput, coarsePointer } from "./input/touch"; import { FightRenderer } from "./render/renderer"; import type { CombatEvent, EngineSnapshot, FighterSnapshot, PublicPlayer } from "./types"; type Draft = { -readonly [K in keyof FighterSnapshot]: FighterSnapshot[K] }; const base = (id: string): Draft => ({ - player_id: id, x: 0, y: 0, facing: id === "fixture-one" ? 1 : -1, velocity_x: 0, velocity_y: 0, + player_id: id, x: 0, y: 0, facing: id === "fixture-one" ? 1 : -1, facing_x: id === "fixture-one" ? 1000 : -1000, facing_y: 0, velocity_x: 0, velocity_y: 0, stance: id === "fixture-one" ? "orthodox" : "southpaw", defense: "guard_high", stamina: 760, maximum_stamina: 1000, conditioning: 820, guard: 670, poise: 520, trauma: id === "fixture-two" @@ -14,25 +18,31 @@ const base = (id: string): Draft => ({ action: null, action_hand: null, action_target: null, action_power: null, action_id: null, action_key: null, action_start_tick: 0, action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, taunt_ticks: 0, get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, get_up_window_start_tick: 0, get_up_window_end_tick: 0, + last_input_sequence: -1, }); const PUNCHES = ["jab", "straight", "hook", "uppercut"] as const; export function runDevelopmentFixture(root: HTMLElement): () => void { root.innerHTML = `
HANDS · DEV FIXTUREProduction never enters this harness
`; + const bloodParam = new URLSearchParams(window.location.search).get("blood"); + const blood = bloodParam === "reduced" || bloodParam === "off" ? bloodParam : "full"; const renderer = new FightRenderer( root.querySelector("canvas")!, - { tick_rate: 30, ring_half_width: 500, ring_half_height: 330 }, - () => ({ volume: 0, haptics: false, reducedMotion: false, blood: "full" }), + { tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }, + () => ({ volume: 0, haptics: false, reducedMotion: false, blood }), ); + renderer.setBloodLevel(blood); const players: Record = { "fixture-one": { id: "fixture-one", name: "Azure Vector", avatar: null, rating: 1512, connected: true }, "fixture-two": { id: "fixture-two", name: "Crimson Geometry", avatar: null, rating: 1494, connected: true }, }; renderer.setPlayers(players, "fixture-one"); + const touch = coarsePointer() ? new TouchInput(root.querySelector(".activity")!, new SharedActionIntent()) : null; let tick = 0; let eventId = 0; + let finalSent = false; const interval = window.setInterval(() => { tick += 3; const t = tick / 30; @@ -45,6 +55,11 @@ export function runDevelopmentFixture(root: HTMLElement): () => void { two.y = Math.cos(orbit + 0.35) * 150; one.facing = two.x >= one.x ? 1 : -1; two.facing = -one.facing; + const gap = Math.hypot(two.x - one.x, two.y - one.y) || 1; + one.facing_x = Math.round(((two.x - one.x) / gap) * 1000); + one.facing_y = Math.round(((two.y - one.y) / gap) * 1000); + two.facing_x = -one.facing_x; + two.facing_y = -one.facing_y; one.velocity_x = Math.cos(orbit) * 48; two.velocity_x = Math.cos(orbit + 0.25) * 48; const events: CombatEvent[] = []; @@ -56,7 +71,14 @@ export function runDevelopmentFixture(root: HTMLElement): () => void { one.taunt_ticks = Math.round((9.5 - tauntCycle) * 30); one.action = null; } - if (cycle < 0.55 && one.taunt_ticks === 0 && two.taunt_ticks === 0) { + const closing = tauntCycle > 1.6 && tauntCycle < 5.1; + if (closing) { + two.x = Math.round(one.x + one.facing_x * 0.06); + two.y = Math.round(one.y + one.facing_y * 0.06); + one.velocity_x = two.velocity_x = 0; + if (tauntCycle > 3.6) one.clinch_ticks = two.clinch_ticks = Math.round((5.1 - tauntCycle) * 30); + } + if (cycle < 0.55 && one.taunt_ticks === 0 && two.taunt_ticks === 0 && !closing) { const punch = PUNCHES[Math.floor(t / 3.2) % PUNCHES.length]!; attacker.action = punch; attacker.action_hand = Math.floor(t / 3.2) % 3 === 0 ? "right" : "left"; @@ -69,7 +91,11 @@ export function runDevelopmentFixture(root: HTMLElement): () => void { defender.stunned_ticks = 12; } } - const knockdownCycle = t % 14; + const search = new URLSearchParams(window.location.search); + const finisher = search.get("finisher"); + const forcedRest = search.get("phase") === "rest"; + const pinned = search.get("pin") === "1"; + const knockdownCycle = finisher === null ? t % 14 : (t < 2.5 ? 0 : 12); if (knockdownCycle > 11 && knockdownCycle < 13.4) { two.is_downed = true; two.action = null; @@ -77,22 +103,68 @@ export function runDevelopmentFixture(root: HTMLElement): () => void { two.y = 40; one.x = -60; one.y = -30; - if (knockdownCycle > 11 && knockdownCycle < 11.15) { + const trigger = finisher === null ? knockdownCycle > 11 && knockdownCycle < 11.15 : t >= 2.5 && t < 2.65; + if (trigger) { eventId += 1; - events.push({ event_id: eventId, tick, kind: "counter_hit", actor_id: one.player_id, target_id: two.player_id, amount: 500, detail: "right:uppercut:head", blood: 100, direction: 1, action_id: null }); + if (finisher !== null && eventId % 2 === 1) eventId += 1; + events.push({ event_id: eventId, tick, kind: "counter_hit", actor_id: one.player_id, target_id: two.player_id, amount: 500, detail: finisher === "hand" ? "left:hook:body" : "right:uppercut:head", blood: 100, direction: 1, action_id: null }); eventId += 1; events.push({ event_id: eventId, tick, kind: "knockdown", actor_id: one.player_id, target_id: two.player_id, amount: 420, detail: "knockdown", blood: 60, direction: 1, action_id: null }); } } + if (pinned) { + two.x = 460; + two.y = 40; + one.x = 330; + one.y = 20; + } + if (search.get("pin") === "corner") { + two.x = 366; + two.y = 366; + one.x = 292; + one.y = 284; + } + if (forcedRest) { + for (const [fighter, sign] of [[one, -1], [two, 1]] as const) { + fighter.x = sign * REST_CORNER_OFFSET; + fighter.y = sign * REST_CORNER_OFFSET; + fighter.velocity_x = fighter.velocity_y = 0; + fighter.facing_x = fighter.facing_y = -sign * 707; + fighter.facing = -sign; + fighter.action = null; + fighter.taunt_ticks = fighter.stunned_ticks = 0; + fighter.is_downed = false; + fighter.defense = "none"; + } + events.length = 0; + } const snapshot: EngineSnapshot = { - tick, phase: "fight", round_number: 3, phase_ticks_remaining: Math.max(0, 5400 - tick), + tick, phase: forcedRest ? "rest" : "fight", round_number: 3, phase_ticks_remaining: Math.max(0, 5400 - tick), fighters: [{ ...one }, { ...two }], events, result: null, checksum: "a".repeat(64), }; renderer.push(snapshot); + if (finisher !== null && t >= 3.4 && !finalSent) { + finalSent = true; + renderer.setFinal({ version: 3, type: "final", match_id: "fixture", winner_id: one.player_id, method: "ko", round: 3, scorecards: [], ratings: {} }); + } + (window as unknown as Record).__fixtureDebug = { + tick, + t: Number(t.toFixed(2)), + downed: two.is_downed, + severedHeads: renderer.labEffects.activeHeads, + severedHands: renderer.labEffects.activeHands, + rigs: renderer.labRigs.length, + resolutionScale: renderer.resolutionScale, + heads: renderer.labRigs.map((root) => { + const head = root.getObjectByName("Head_00"); + return head === undefined ? null : Number(head.getWorldPosition(new THREE.Vector3()).y.toFixed(3)); + }), + }; }, 100); return () => { window.clearInterval(interval); + touch?.destroy(); renderer.destroy(); root.replaceChildren(); }; diff --git a/web/hands/src/discord.test.ts b/web/hands/src/discord.test.ts index 32b969e8..8b6f4f31 100644 --- a/web/hands/src/discord.test.ts +++ b/web/hands/src/discord.test.ts @@ -1,72 +1,96 @@ import type { IDiscordSDK } from "@discord/embedded-app-sdk"; import { ClientError } from "./api"; -import { authorizeDiscord, OAUTH_SCOPES } from "./discord"; +import { DiscordActivity, OAUTH_SCOPES } from "./discord"; const response = (value: unknown): Response => new Response(JSON.stringify(value), { status: 200, headers: { "Content-Type": "application/json" } }); const launchUrl = "/?instance_id=launch-1&frame_id=frame-1&platform=desktop"; function sdk(instanceId: string, order: string[]): IDiscordSDK { return { instanceId, ready: vi.fn(async () => { order.push("ready"); }), close: vi.fn(() => { order.push("close"); }), commands: { authorize: vi.fn(async () => { order.push("authorize"); return { code: "oauth-code" }; }), authenticate: vi.fn(async () => { order.push("authenticate"); return {}; }) } } as unknown as IDiscordSDK; } +const backend = (order: string[] = []) => vi.fn(async (input: URL | RequestInfo) => { if (String(input).includes("bootstrap")) { order.push("bootstrap"); return response({ client_id: "123", state: "state", protocol: 3, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }); } order.push("token"); return response({ access_token: "access", ticket: "ticket", player: { id: "one", name: "One", avatar: null, rating: 1000 } }); }); describe("Discord SDK OAuth", () => { it("uses exact ready-authorize-token-authenticate order/scopes and memory-only ticket", async () => { history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); - vi.stubGlobal("fetch", vi.fn(async (input: URL | RequestInfo, init?: RequestInit) => { const url = String(input); if (url.includes("bootstrap")) { order.push("bootstrap"); expect(init?.body).toBe(JSON.stringify({ instance_id: "launch-1" })); return response({ client_id: "123", state: "oauth-state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }); } order.push("token"); expect(init?.body).toBe(JSON.stringify({ code: "oauth-code", state: "oauth-state" })); return response({ access_token: "access-secret", ticket: "ticket-secret", player: { id: "one", name: "One", avatar: null, rating: 1500 } }); })); - const session = await authorizeDiscord(undefined, () => mockSdk); expect(order).toEqual(["bootstrap", "ready", "authorize", "token", "authenticate"]); + vi.stubGlobal("fetch", vi.fn(async (input: URL | RequestInfo, init?: RequestInit) => { const url = String(input); if (url.includes("bootstrap")) { order.push("bootstrap"); expect(init?.body).toBe(JSON.stringify({ instance_id: "launch-1" })); return response({ client_id: "123", state: "oauth-state", protocol: 3, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }); } order.push("token"); expect(init?.body).toBe(JSON.stringify({ code: "oauth-code", state: "oauth-state" })); return response({ access_token: "access-secret", ticket: "ticket-secret", player: { id: "one", name: "One", avatar: null, rating: 1500 } }); })); + const activity = new DiscordActivity(() => mockSdk); const session = await activity.authorize(); expect(order).toEqual(["bootstrap", "ready", "authorize", "token", "authenticate"]); expect(OAUTH_SCOPES).toEqual(["identify", "guilds.members.read"]); expect(mockSdk.commands.authorize).toHaveBeenCalledWith({ client_id: "123", response_type: "code", state: "oauth-state", prompt: "none", scope: [...OAUTH_SCOPES] }); expect(mockSdk.commands.authenticate).toHaveBeenCalledWith({ access_token: "access-secret" }); - expect(session.takeTicket()).toBe("ticket-secret"); expect(session.takeTicket()).toBeNull(); expect(localStorage).toHaveLength(0); expect(location.href).not.toContain("secret"); session.destroy(); session.destroy(); expect(mockSdk.close).toHaveBeenCalledOnce(); expect(order.at(-1)).toBe("close"); + expect(session.takeTicket()).toBe("ticket-secret"); expect(session.takeTicket()).toBeNull(); expect(localStorage).toHaveLength(0); expect(location.href).not.toContain("secret"); + // Ending a session only drops its ticket: sdk.close posts the host CLOSE opcode, which closes the Activity. + session.destroy(); expect(mockSdk.close).not.toHaveBeenCalled(); + activity.close(); activity.close(); expect(mockSdk.close).toHaveBeenCalledOnce(); expect(order.at(-1)).toBe("close"); + }); + it("authorizes every later session (a rematch, a retry) on the same SDK without closing it", async () => { + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); const factory = vi.fn(() => mockSdk); vi.stubGlobal("fetch", backend(order)); + const activity = new DiscordActivity(factory); + const first = await activity.authorize(); expect(first.takeTicket()).toBe("ticket"); first.destroy(); + const second = await activity.authorize(); expect(second.takeTicket()).toBe("ticket"); second.destroy(); + expect(factory).toHaveBeenCalledOnce(); expect(mockSdk.commands.authorize).toHaveBeenCalledTimes(2); + // The SDK keeps its authentication; the second session needs only a fresh ticket from the token exchange. + expect(order).toEqual(["bootstrap", "ready", "authorize", "token", "authenticate", "bootstrap", "ready", "authorize", "token"]); expect(mockSdk.close).not.toHaveBeenCalled(); + activity.close(); expect(mockSdk.close).toHaveBeenCalledOnce(); }); it("rejects missing SDK launch parameters before construction", async () => { history.replaceState({}, "", "/?instance_id=launch-1"); const factory = vi.fn(() => sdk("launch-1", [])); const fetchMock = vi.fn(); vi.stubGlobal("fetch", fetchMock); - await expect(authorizeDiscord(undefined, factory)).rejects.toEqual(new ClientError("invalid_launch")); expect(factory).not.toHaveBeenCalled(); expect(fetchMock).not.toHaveBeenCalled(); + await expect(new DiscordActivity(factory).authorize()).rejects.toEqual(new ClientError("invalid_launch")); expect(factory).not.toHaveBeenCalled(); expect(fetchMock).not.toHaveBeenCalled(); }); it("requires a reload when SDK construction fails", async () => { - history.replaceState({}, "", launchUrl); vi.stubGlobal("fetch", vi.fn(async () => response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }))); - await expect(authorizeDiscord(undefined, () => { throw new Error("construction failed"); })).rejects.toEqual(new ClientError("sdk_initialization_failed", true)); + history.replaceState({}, "", launchUrl); vi.stubGlobal("fetch", backend()); + await expect(new DiscordActivity(() => { throw new Error("construction failed"); }).authorize()).rejects.toEqual(new ClientError("sdk_initialization_failed", true)); }); it("keeps the Activity open and identifies a known authorize RPC failure", async () => { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authorize as ReturnType).mockRejectedValue(Object.assign(new Error("host rejected"), { code: 4006 })); vi.stubGlobal("fetch", vi.fn(async () => response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }))); - await expect(authorizeDiscord(undefined, () => mockSdk)).rejects.toEqual(new ClientError("authorize_failed_4006", true)); expect(mockSdk.close).not.toHaveBeenCalled(); + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authorize as ReturnType).mockRejectedValue(Object.assign(new Error("host rejected"), { code: 4006 })); vi.stubGlobal("fetch", backend()); + await expect(new DiscordActivity(() => mockSdk).authorize()).rejects.toEqual(new ClientError("authorize_failed_4006", true)); expect(mockSdk.close).not.toHaveBeenCalled(); }); it("does not expose unknown host RPC error codes", async () => { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authorize as ReturnType).mockRejectedValue(Object.assign(new Error("host rejected"), { code: 9999 })); vi.stubGlobal("fetch", vi.fn(async () => response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }))); - await expect(authorizeDiscord(undefined, () => mockSdk)).rejects.toEqual(new ClientError("authorize_failed", true)); expect(mockSdk.close).not.toHaveBeenCalled(); + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authorize as ReturnType).mockRejectedValue(Object.assign(new Error("host rejected"), { code: 9999 })); vi.stubGlobal("fetch", backend()); + await expect(new DiscordActivity(() => mockSdk).authorize()).rejects.toEqual(new ClientError("authorize_failed", true)); expect(mockSdk.close).not.toHaveBeenCalled(); }); it("keeps the Activity open and preserves a safe token exchange failure", async () => { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); vi.stubGlobal("fetch", vi.fn(async (input: URL | RequestInfo) => String(input).includes("bootstrap") ? response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }) : new Response("{}", { status: 401, headers: { "Content-Type": "application/json" } }))); - await expect(authorizeDiscord(undefined, () => mockSdk)).rejects.toEqual(new ClientError("token_failed", true)); expect(mockSdk.close).not.toHaveBeenCalled(); + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); vi.stubGlobal("fetch", vi.fn(async (input: URL | RequestInfo) => String(input).includes("bootstrap") ? response({ client_id: "123", state: "state", protocol: 3, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }) : new Response("{}", { status: 401, headers: { "Content-Type": "application/json" } }))); + await expect(new DiscordActivity(() => mockSdk).authorize()).rejects.toEqual(new ClientError("token_failed", true)); expect(mockSdk.close).not.toHaveBeenCalled(); }); it("keeps the Activity open and identifies an authenticate RPC failure", async () => { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authenticate as ReturnType).mockRejectedValue(new Error("host rejected")); vi.stubGlobal("fetch", vi.fn(async (input: URL | RequestInfo) => String(input).includes("bootstrap") ? response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }) : response({ access_token: "access", ticket: "ticket", player: { id: "one", name: "One", avatar: null, rating: 1000 } }))); - await expect(authorizeDiscord(undefined, () => mockSdk)).rejects.toEqual(new ClientError("sdk_authenticate_failed", true)); expect(mockSdk.close).not.toHaveBeenCalled(); + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authenticate as ReturnType).mockRejectedValue(new Error("host rejected")); vi.stubGlobal("fetch", backend()); + await expect(new DiscordActivity(() => mockSdk).authorize()).rejects.toEqual(new ClientError("sdk_authenticate_failed", true)); expect(mockSdk.close).not.toHaveBeenCalled(); }); - it("closes the stalled realm when authenticate retains an access token", async () => { + it("keeps the Activity open and requires a reload when authenticate stalls", async () => { vi.useFakeTimers(); try { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authenticate as ReturnType).mockImplementation(() => new Promise(() => {})); vi.stubGlobal("fetch", vi.fn(async (input: URL | RequestInfo) => String(input).includes("bootstrap") ? response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }) : response({ access_token: "access", ticket: "ticket", player: { id: "one", name: "One", avatar: null, rating: 1000 } }))); - const attempt = expect(authorizeDiscord(undefined, () => mockSdk)).rejects.toEqual(new ClientError("sdk_authenticate_timeout")); + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.commands.authenticate as ReturnType).mockImplementation(() => new Promise(() => {})); vi.stubGlobal("fetch", backend()); + // The reload behind Retry discards the stalled SDK and the access token its command still holds. + const attempt = expect(new DiscordActivity(() => mockSdk).authorize()).rejects.toEqual(new ClientError("sdk_authenticate_timeout", true)); await vi.advanceTimersByTimeAsync(15_000); - await attempt; expect(mockSdk.close).toHaveBeenCalledOnce(); + await attempt; expect(mockSdk.close).not.toHaveBeenCalled(); } finally { vi.useRealTimers(); } }); - it("bounds a missing SDK ready response and closes the stalled realm", async () => { + it("bounds a missing SDK ready response and requires a reload without closing the Activity", async () => { vi.useFakeTimers(); try { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.ready as ReturnType).mockImplementation(() => new Promise(() => {})); vi.stubGlobal("fetch", vi.fn(async () => response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }))); - const attempt = expect(authorizeDiscord(undefined, () => mockSdk)).rejects.toEqual(new ClientError("sdk_ready_timeout")); + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); (mockSdk.ready as ReturnType).mockImplementation(() => new Promise(() => {})); vi.stubGlobal("fetch", backend()); + const attempt = expect(new DiscordActivity(() => mockSdk).authorize()).rejects.toEqual(new ClientError("sdk_ready_timeout", true)); await vi.advanceTimersByTimeAsync(15_000); - await attempt; expect(mockSdk.close).toHaveBeenCalledOnce(); + await attempt; expect(mockSdk.close).not.toHaveBeenCalled(); } finally { vi.useRealTimers(); } }); it("rejects SDK/launch instance disagreement before authorize", async () => { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("other", order); vi.stubGlobal("fetch", vi.fn(async () => response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }))); - await expect(authorizeDiscord(undefined, () => mockSdk)).rejects.toMatchObject({ code: "instance_mismatch" }); expect(mockSdk.commands.authorize).not.toHaveBeenCalled(); expect(mockSdk.close).toHaveBeenCalledOnce(); + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("other", order); vi.stubGlobal("fetch", backend()); + await expect(new DiscordActivity(() => mockSdk).authorize()).rejects.toMatchObject({ code: "instance_mismatch", reloadRequired: true }); expect(mockSdk.commands.authorize).not.toHaveBeenCalled(); expect(mockSdk.close).not.toHaveBeenCalled(); + }); + it("keeps the SDK for the next authorization when one is aborted after ready", async () => { + history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); const factory = vi.fn(() => mockSdk); const abort = new AbortController(); (mockSdk.ready as ReturnType).mockImplementationOnce(async () => { abort.abort(); }); vi.stubGlobal("fetch", backend()); + const activity = new DiscordActivity(factory); + await expect(activity.authorize(abort.signal)).rejects.toMatchObject({ code: "cancelled" }); expect(mockSdk.close).not.toHaveBeenCalled(); + const session = await activity.authorize(new AbortController().signal); expect(session.takeTicket()).toBe("ticket"); expect(factory).toHaveBeenCalledOnce(); + // The aborted attempt never authenticated, so this one does. + expect(mockSdk.commands.authenticate).toHaveBeenCalledOnce(); }); - it("closes a constructed SDK when authorization is aborted after ready", async () => { - history.replaceState({}, "", launchUrl); const order: string[] = []; const mockSdk = sdk("launch-1", order); const abort = new AbortController(); (mockSdk.ready as ReturnType).mockImplementation(async () => { abort.abort(); }); vi.stubGlobal("fetch", vi.fn(async () => response({ client_id: "123", state: "state", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 500, ring_half_height: 330 } }))); - await expect(authorizeDiscord(abort.signal, () => mockSdk)).rejects.toMatchObject({ code: "cancelled" }); expect(mockSdk.close).toHaveBeenCalledOnce(); + it("constructs no SDK after final teardown", async () => { + history.replaceState({}, "", launchUrl); const factory = vi.fn(() => sdk("launch-1", [])); vi.stubGlobal("fetch", backend()); + const activity = new DiscordActivity(factory); activity.close(); + await expect(activity.authorize()).rejects.toMatchObject({ code: "cancelled" }); expect(factory).not.toHaveBeenCalled(); }); }); diff --git a/web/hands/src/discord.ts b/web/hands/src/discord.ts index 3440075d..6bf08df8 100644 --- a/web/hands/src/discord.ts +++ b/web/hands/src/discord.ts @@ -9,8 +9,14 @@ export interface DiscordSession { readonly bootstrap: BootstrapResponse; readonly player: TokenPlayer; takeTicket(): string | null; + /** Drops the unused ticket; the SDK stays open for the next session. */ destroy(): void; } +/** Signs the page in for each bout. `close` ends the Activity, so it belongs to final teardown only. */ +export interface ActivityAuthorizer { + authorize(signal: AbortSignal): Promise; + close(): void; +} type SDKFactory = (clientId: string) => IDiscordSDK; function clientFailure(error: unknown, fallback: string): ClientError { @@ -81,97 +87,107 @@ async function sdkOperation( } } -function closeSdk(sdk: IDiscordSDK, message: string): void { - try { - sdk.close(RPCCloseCodes.CLOSE_NORMAL, message); - } catch { - // Construction succeeded, but an incomplete host bridge can still reject close. +/** + * The page's one Discord SDK. `sdk.close` posts the host CLOSE opcode, which closes the Activity, so + * a rematch, a retry or a failure authorizes again on the same SDK, and only `close`, at final + * teardown, ends it. + */ +export class DiscordActivity implements ActivityAuthorizer { + private sdk: IDiscordSDK | null = null; + private authenticated = false; + private closed = false; + + constructor(private readonly makeSDK: SDKFactory = (id) => new DiscordSDK(id)) {} + + async authorize(signal?: AbortSignal): Promise { + const instance = launchInstance(); + validateSdkLaunch(); + const boot = await bootstrap(instance, signal); + const sdk = this.open(boot.client_id); + const requireActive = (): void => { + if (signal?.aborted) throw new ClientError("cancelled"); + }; + try { + requireActive(); + await sdkOperation( + () => sdk.ready(), + signal, + "sdk_ready_failed", + "sdk_ready_timeout", + SDK_READY_TIMEOUT_MS, + ); + requireActive(); + if (sdk.instanceId !== instance) throw new ClientError("instance_mismatch"); + const authorization = await sdkOperation( + () => sdk.commands.authorize({ + client_id: boot.client_id, + response_type: "code", + state: boot.state, + prompt: "none", + scope: [...OAUTH_SCOPES], + }), + signal, + "authorize_failed", + "authorize_timeout", + SDK_AUTHORIZE_TIMEOUT_MS, + ); + requireActive(); + const token = await exchangeToken(authorization.code, boot.state, signal); + requireActive(); + // The SDK stays authenticated for the page; a later session only needs the server's fresh ticket. + if (!this.authenticated) { + const authentication = await sdkOperation( + () => sdk.commands.authenticate({ access_token: token.access_token }), + signal, + "sdk_authenticate_failed", + "sdk_authenticate_timeout", + SDK_AUTHENTICATE_TIMEOUT_MS, + ); + if (authentication == null) throw new ClientError("sdk_authenticate_failed"); + this.authenticated = true; + requireActive(); + } + let ticket: string | null = token.ticket; + return { + sdk, + bootstrap: boot, + player: token.player, + takeTicket: () => { + const current = ticket; + ticket = null; + return current; + }, + destroy: () => { + ticket = null; + }, + }; + } catch (error) { + if (signal?.aborted) throw new ClientError("cancelled"); + // The SDK stays open so the failure stays on screen; the reload behind Retry replaces it, + // together with any command it was left waiting on. + throw new ClientError(clientFailure(error, "authorization_failed").code, true); + } } -} -export async function authorizeDiscord( - signal?: AbortSignal, - makeSDK: SDKFactory = (id) => new DiscordSDK(id), -): Promise { - const instance = launchInstance(); - validateSdkLaunch(); - const boot = await bootstrap(instance, signal); - let sdk: IDiscordSDK; - try { - sdk = makeSDK(boot.client_id); - } catch (error) { - const failure = clientFailure(error, "sdk_initialization_failed"); - throw new ClientError(failure.code, true); + close(): void { + if (this.closed) return; + this.closed = true; + if (this.sdk === null) return; + try { + this.sdk.close(RPCCloseCodes.CLOSE_NORMAL, "Hands session closed"); + } catch { + // Construction succeeded, but an incomplete host bridge can still reject close. + } } - const requireActive = (): void => { - if (signal?.aborted) throw new ClientError("cancelled"); - }; - try { - requireActive(); - await sdkOperation( - () => sdk.ready(), - signal, - "sdk_ready_failed", - "sdk_ready_timeout", - SDK_READY_TIMEOUT_MS, - ); - requireActive(); - if (sdk.instanceId !== instance) throw new ClientError("instance_mismatch"); - const authorization = await sdkOperation( - () => sdk.commands.authorize({ - client_id: boot.client_id, - response_type: "code", - state: boot.state, - prompt: "none", - scope: [...OAUTH_SCOPES], - }), - signal, - "authorize_failed", - "authorize_timeout", - SDK_AUTHORIZE_TIMEOUT_MS, - ); - requireActive(); - const token = await exchangeToken(authorization.code, boot.state, signal); - requireActive(); - const authentication = await sdkOperation( - () => sdk.commands.authenticate({ access_token: token.access_token }), - signal, - "sdk_authenticate_failed", - "sdk_authenticate_timeout", - SDK_AUTHENTICATE_TIMEOUT_MS, - ); - if (authentication == null) throw new ClientError("sdk_authenticate_failed"); - requireActive(); - let ticket: string | null = token.ticket; - let destroyed = false; - return { - sdk, - bootstrap: boot, - player: token.player, - takeTicket: () => { - const current = ticket; - ticket = null; - return current; - }, - destroy: () => { - if (destroyed) return; - destroyed = true; - ticket = null; - closeSdk(sdk, "Hands session closed"); - }, - }; - } catch (error) { - const failure = signal?.aborted - ? new ClientError("cancelled") - : clientFailure(error, "authorization_failed"); - if ( - failure.code === "cancelled" - || failure.code === "instance_mismatch" - || failure.code.endsWith("_timeout") - ) { - closeSdk(sdk, "Hands authorization closed"); - throw failure; + + private open(clientId: string): IDiscordSDK { + if (this.closed) throw new ClientError("cancelled"); + if (this.sdk !== null) return this.sdk; + try { + this.sdk = this.makeSDK(clientId); + } catch (error) { + throw new ClientError(clientFailure(error, "sdk_initialization_failed").code, true); } - throw new ClientError(failure.code, true); + return this.sdk; } } diff --git a/web/hands/src/errors.test.ts b/web/hands/src/errors.test.ts new file mode 100644 index 00000000..ac9e4d78 --- /dev/null +++ b/web/hands/src/errors.test.ts @@ -0,0 +1,37 @@ +import { describe, expect, it } from "vitest"; +import { describeError } from "./errors"; + +describe("describeError", () => { + it("explains known codes in plain language and keeps the code", () => { + expect(describeError("room_closed")).toBe("Unable to continue: the bout has already ended; use Play now to start another (room_closed)."); + expect(describeError("authentication_timeout")).toContain("took too long to authenticate"); + expect(describeError("authentication_timeout")).toContain("(authentication_timeout)"); + }); + + it("falls back to the bare code for unknown failures", () => { + expect(describeError("mystery_failure")).toBe("Unable to continue (mystery_failure)."); + }); + + it("tells the player to reload when Hands was updated", () => { + expect(describeError("client_outdated")).toBe("Hands was updated. Reload to continue (client_outdated)."); + }); + + it("explains a Discord RPC failure by its stage and keeps the RPC number", () => { + expect(describeError("authorize_failed_4006")).toBe("Unable to continue: Discord did not authorize the session (authorize_failed_4006)."); + expect(describeError("sdk_ready_failed_4000")).toBe("Unable to continue: the Discord client did not respond (sdk_ready_failed_4000)."); + expect(describeError("sdk_authenticate_failed_4009")).toContain("Discord did not confirm your identity"); + expect(describeError("mystery_failure_4006")).toBe("Unable to continue (mystery_failure_4006)."); + }); + + it("explains every code the server and the client can end a session with", () => { + const server = [ + "already_in_room", "authentication_required", "authentication_timeout", "connection_replaced", "input_queue_full", + "internal_error", "invalid_activity", "invalid_guild", "invalid_input", "invalid_request", "invalid_state", + "invalid_ticket", "match_abandoned", "match_not_started", "not_in_activity", "persistence_failed", "rate_limited", + "room_closed", "room_full", "server_shutting_down", "service_busy", "service_unavailable", "spectator_read_only", + "upstream_unavailable", + ]; + const client = ["network_unavailable", "protocol_error", "unexpected_error", "rematch_unavailable", "bootstrap_failed", "token_failed"]; + for (const code of [...server, ...client]) expect(describeError(code), code).not.toBe(`Unable to continue (${code}).`); + }); +}); diff --git a/web/hands/src/errors.ts b/web/hands/src/errors.ts new file mode 100644 index 00000000..8c62cc0d --- /dev/null +++ b/web/hands/src/errors.ts @@ -0,0 +1,55 @@ +const REASONS: Readonly> = { + invalid_launch: "open Hands from a Discord voice channel with Play now", + cancelled: "the session was cancelled", + authorization_failed: "Discord did not authorize the session", + authorize_failed: "Discord did not authorize the session", + authorize_timeout: "Discord took too long to authorize the session", + sdk_ready_failed: "the Discord client did not respond", + sdk_ready_timeout: "the Discord client took too long to respond", + sdk_authenticate_failed: "Discord did not confirm your identity", + sdk_authenticate_timeout: "Discord took too long to confirm your identity", + sdk_initialization_failed: "the Discord client could not start the activity", + instance_mismatch: "this window belongs to a different activity instance", + bootstrap_failed: "the Hands server could not be reached", + token_failed: "the Hands server rejected the sign-in", + invalid_bootstrap: "the Hands server sent an unexpected reply", + invalid_token_response: "the Hands server sent an unexpected reply", + ticket_unavailable: "the session ticket was already used", + protocol_error: "the server and client disagree on the protocol", + unexpected_error: "something unexpected went wrong", + authentication_timeout: "the connection took too long to authenticate", + authentication_required: "the connection was not authenticated", + invalid_ticket: "the session ticket was rejected", + invalid_request: "the server rejected the request", + invalid_input: "the server rejected an input frame", + input_queue_full: "the server could not keep up with the inputs", + rate_limited: "too many requests were sent; wait a moment", + service_busy: "the server is busy right now", + service_unavailable: "the server is unavailable right now", + upstream_unavailable: "Discord is unavailable right now", + room_closed: "the bout has already ended; use Play now to start another", + room_full: "both seats in this bout are taken", + already_in_room: "you are already in a bout in another channel", + match_not_started: "the bout has not started yet", + connection_replaced: "this seat was taken over by a newer connection", + spectator_read_only: "spectators cannot send input", + server_shutting_down: "the server is restarting", + internal_error: "the server hit an internal error", + not_in_activity: "you are not a participant of this activity", + invalid_activity: "this activity instance is not valid", + invalid_state: "the sign-in state expired; retry", + invalid_guild: "this activity belongs to another server", + persistence_failed: "the result could not be saved", + rematch_unavailable: "the ring could not be cleared for a rematch; use Play now to start another bout", + network_unavailable: "the connection to the Hands server could not be opened", + match_abandoned: "both fighters lost their connection and the bout was called off", +}; + +/** Plain-language failure text; the full code stays in parentheses for diagnosis. */ +export function describeError(code: string): string { + // Nothing failed: the server was updated, and reloading the page brings the matching client. + if (code === "client_outdated") return "Hands was updated. Reload to continue (client_outdated)."; + // Discord SDK failures carry the RPC error number (authorize_failed_4006); the stage gives the reason. + const reason = REASONS[code] ?? REASONS[code.replace(/_\d+$/u, "")]; + return reason === undefined ? `Unable to continue (${code}).` : `Unable to continue: ${reason} (${code}).`; +} diff --git a/web/hands/src/feedback.test.ts b/web/hands/src/feedback.test.ts index 5ba9cb58..556f2585 100644 --- a/web/hands/src/feedback.test.ts +++ b/web/hands/src/feedback.test.ts @@ -15,6 +15,9 @@ class MockAudioContext { static operations: string[] = []; static last: MockAudioContext | null = null; static playedBuffers: Array = []; + /** The next resume() is outside a user activation: it stays pending until a later resume() starts the context. */ + static holdResume = false; + private readonly pendingResumes: (() => void)[] = []; state: AudioContextState = "suspended"; currentTime = 0; sampleRate = 8000; @@ -22,7 +25,13 @@ class MockAudioContext { resume = vi.fn(async () => { MockAudioContext.operations.push("resume"); if (MockAudioContext.failResume) { MockAudioContext.failResume = false; throw new Error("blocked"); } + if (MockAudioContext.holdResume) { + MockAudioContext.holdResume = false; + await new Promise((resolve) => { this.pendingResumes.push(resolve); }); + return; + } this.state = "running"; + for (const resolve of this.pendingResumes.splice(0)) resolve(); }); suspend = vi.fn(async () => { this.state = "suspended"; }); close = vi.fn(async () => {}); @@ -62,9 +71,36 @@ describe("authoritative audio and haptics", () => { MockAudioContext.operations = []; MockAudioContext.last = null; MockAudioContext.playedBuffers = []; + MockAudioContext.holdResume = false; vi.stubGlobal("AudioContext", MockAudioContext); }); + it.each(["pointerup", "touchend", "click"])("unlocks audio on the %s that ends a touch whose press could not start it", async (release) => { + MockAudioContext.holdResume = true; + const feedback = new AudioFeedback(() => settings); + try { + window.dispatchEvent(new Event("pointerdown")); + await Promise.resolve(); + expect(MockAudioContext.created).toBe(1); + expect(MockAudioContext.oscillatorStarts).toBe(0); + window.dispatchEvent(new Event(release)); + await vi.waitFor(() => expect(MockAudioContext.oscillatorStarts).toBe(1)); + expect(MockAudioContext.last!.state).toBe("running"); + } finally { + feedback.destroy(); + } + }); + + it.each(["touchend", "click"])("unlocks audio when %s is the first gesture", async (gesture) => { + const feedback = new AudioFeedback(() => settings); + try { + window.dispatchEvent(new Event(gesture)); + await vi.waitFor(() => expect(MockAudioContext.oscillatorStarts).toBe(1)); + } finally { + feedback.destroy(); + } + }); + it("creates WebAudio only after an explicit gesture and safely synthesizes events", async () => { const feedback = new AudioFeedback(() => settings); feedback.event({ event_id: 1, tick: 1, kind: "hit", actor_id: null, target_id: null, amount: 100, detail: "body", blood: 0, direction: 0, action_id: null }); @@ -75,6 +111,22 @@ describe("authoritative audio and haptics", () => { feedback.destroy(); }); + it("cracks the ten-second clapper once per round of the fight phase", async () => { + const feedback = new AudioFeedback(() => settings); + await feedback.unlock(); + const before = MockAudioContext.bufferStarts; + feedback.roundClock("fight", 1, 3500, 30); + feedback.roundClock("rest", 1, 200, 30); + expect(MockAudioContext.bufferStarts).toBe(before); + feedback.roundClock("fight", 1, 299, 30); + expect(MockAudioContext.bufferStarts).toBe(before + 2); + feedback.roundClock("fight", 1, 280, 30); + expect(MockAudioContext.bufferStarts).toBe(before + 2); + feedback.roundClock("fight", 2, 250, 30); + expect(MockAudioContext.bufferStarts).toBe(before + 4); + feedback.destroy(); + }); + it("shares one unlock promise, starts one crowd bed, and retries after resume rejection", async () => { const feedback = new AudioFeedback(() => settings); MockAudioContext.failResume = true; @@ -194,6 +246,31 @@ describe("authoritative audio and haptics", () => { expect(playEffect).toHaveBeenCalledOnce(); }); + it("vibrates a phone that has no pad to rumble, only with Haptics on and never on a desktop", () => { + const vibrate = vi.fn((_duration: number) => true); + Object.defineProperty(navigator, "vibrate", { configurable: true, value: vibrate }); + Object.defineProperty(navigator, "getGamepads", { configurable: true, value: () => [] }); + let coarse = true; + vi.mocked(window.matchMedia).mockImplementation((query: string) => ({ matches: coarse && query === "(pointer: coarse)", media: query, onchange: null, addListener: vi.fn(), removeListener: vi.fn(), addEventListener: vi.fn(), removeEventListener: vi.fn(), dispatchEvent: vi.fn() })); + try { + let haptics = true; + const feedback = new HapticFeedback(() => ({ ...settings, haptics })); + const hit = { event_id: 1, tick: 1, kind: "hit", actor_id: null, target_id: null, amount: 1, detail: "", blood: 0, direction: 0, action_id: null }; + feedback.event(hit); + feedback.event({ ...hit, event_id: 2, kind: "bell" }); + expect(vibrate).toHaveBeenCalledOnce(); + expect(vibrate).toHaveBeenCalledWith(85); + haptics = false; + feedback.event({ ...hit, event_id: 3 }); + haptics = true; + coarse = false; + feedback.event({ ...hit, event_id: 4 }); + expect(vibrate).toHaveBeenCalledOnce(); + } finally { + delete (navigator as { vibrate?: unknown }).vibrate; + } + }); + it("tolerates absent and throwing gamepad APIs", () => { const haptics = new HapticFeedback(() => settings); Object.defineProperty(navigator, "getGamepads", { configurable: true, value: undefined }); diff --git a/web/hands/src/haptics.ts b/web/hands/src/haptics.ts index 94317948..1b3bc2b2 100644 --- a/web/hands/src/haptics.ts +++ b/web/hands/src/haptics.ts @@ -1,3 +1,4 @@ +import { coarsePointer } from "./input/touch"; import type { Settings } from "./settings"; import type { CombatEvent } from "./types"; @@ -17,16 +18,12 @@ export class HapticFeedback { event(event: CombatEvent): void { if (!this.settings().haptics) return; const pattern = patterns[event.kind]; - if (pattern === undefined || typeof navigator.getGamepads !== "function") return; - let pads: (Gamepad | null)[]; - try { - pads = [...navigator.getGamepads.call(navigator)]; - } catch { + if (pattern === undefined) return; + const actuator = this.padActuator(); + if (actuator === null) { + this.vibrate(pattern[0]); return; } - const pad = pads.find((item): item is VibratingPad => item !== null && item.connected && "vibrationActuator" in item); - const actuator = pad?.vibrationActuator; - if (actuator == null || typeof actuator.playEffect !== "function") return; try { void Promise.resolve(actuator.playEffect("dual-rumble", { duration: Math.min(180, Math.max(0, pattern[0])), @@ -37,4 +34,27 @@ export class HapticFeedback { // Some gamepad implementations throw before returning their advertised promise. } } + + private padActuator(): NonNullable | null { + if (typeof navigator.getGamepads !== "function") return null; + let pads: (Gamepad | null)[]; + try { + pads = [...navigator.getGamepads.call(navigator)]; + } catch { + return null; + } + const pad = pads.find((item): item is VibratingPad => item !== null && item.connected && "vibrationActuator" in item); + const actuator = pad?.vibrationActuator; + return actuator == null || typeof actuator.playEffect !== "function" ? null : actuator; + } + + /** Phones have no pad to rumble; Android vibrates instead (iOS has no vibration API, so nothing happens). */ + private vibrate(duration: number): void { + if (!coarsePointer() || typeof navigator.vibrate !== "function") return; + try { + navigator.vibrate(Math.min(180, Math.max(0, duration))); + } catch { + // A host page can block vibration. + } + } } diff --git a/web/hands/src/input/action-buffer.ts b/web/hands/src/input/action-buffer.ts index 19aeea1c..79d0f28b 100644 --- a/web/hands/src/input/action-buffer.ts +++ b/web/hands/src/input/action-buffer.ts @@ -20,7 +20,7 @@ export function pushActionIntent( queue.push(action); } -export type ActionSource = "keyboard" | "gamepad"; +export type ActionSource = "keyboard" | "gamepad" | "touch"; export class SharedActionIntent { private readonly queue: Array<{ action: SemanticAction; source: ActionSource }> = []; diff --git a/web/hands/src/input/bindings.ts b/web/hands/src/input/bindings.ts index 838c16d2..0c9f4d84 100644 --- a/web/hands/src/input/bindings.ts +++ b/web/hands/src/input/bindings.ts @@ -24,4 +24,5 @@ export const CONTROL_HELP = [ "Controller actions: left stick press clinch · right stick press switch stance · hold right trigger + right stick press to taunt · D-pad up weave · D-pad down pull · tap and release D-pad left/right to slip; while down, D-pad left/right performs the private get-up rhythm immediately.", "Controller fouls: View/Back low blow · Menu/Start headbutt.", "Right-stick gesture: horizontal 0–22.5° hook · 22.5–45° jab · 45–70° straight · 70–90° uppercut; left/right direction selects hand.", + "Touch: drag the left side to move · tap a punch pad's left or right half for that hand · hold BODY, POWER, GUARD or LOW · tap ◀ SLIP, SLIP ▶, WEAVE, PULL or CLINCH.", ] as const; diff --git a/web/hands/src/input/input.test.ts b/web/hands/src/input/input.test.ts index 3cedebb0..02bbebbd 100644 --- a/web/hands/src/input/input.test.ts +++ b/web/hands/src/input/input.test.ts @@ -62,6 +62,22 @@ describe("combined input intent", () => { }); }); +describe("input across the bell", () => { + it("counts movement and guard keys pressed during the rest and held through the bell", () => { + Object.defineProperty(navigator, "getGamepads", { configurable: true, value: () => [] }); + const input = new InputController(); + input.setActive(false); + window.dispatchEvent(key("keydown", "KeyW")); + window.dispatchEvent(key("keydown", "KeyQ")); + expect(input.held()).toEqual({ moveX: 0, moveY: 0, defense: "none" }); + input.setActive(true); + expect(input.frame()).toEqual({ moveX: 0, moveY: 1000, defense: "guard_high", actions: [] }); + window.dispatchEvent(new Event("blur")); + expect(input.frame()).toEqual({ moveX: 0, moveY: 0, defense: "none", actions: [] }); + input.destroy(); + }); +}); + describe("action instance ids", () => { it("preserves the original id and notification when identical intent coalesces", () => { const buffer = new SharedActionIntent(1); diff --git a/web/hands/src/input/input.ts b/web/hands/src/input/input.ts index f65ce0d1..f17e3782 100644 --- a/web/hands/src/input/input.ts +++ b/web/hands/src/input/input.ts @@ -1,20 +1,30 @@ import { SharedActionIntent } from "./action-buffer"; import { GamepadInput } from "./gamepad"; import { KeyboardInput } from "./keyboard"; +import { TouchInput, coarsePointer } from "./touch"; +import type { HeldInput } from "../prediction"; import type { InputFrame, SemanticAction } from "../types"; export class InputController { private readonly actions = new SharedActionIntent(1); - readonly keyboard: KeyboardInput; readonly gamepad: GamepadInput; - readonly reset = (): void => { this.keyboard.reset(); this.gamepad.reset(); this.actions.clear(); this.gamepad.setKnockdown(false); }; + readonly keyboard: KeyboardInput; readonly gamepad: GamepadInput; touch: TouchInput | null = null; + readonly reset = (): void => { this.keyboard.reset(); this.gamepad.reset(); this.touch?.reset(); this.actions.clear(); this.gamepad.setKnockdown(false); }; constructor() { this.keyboard = new KeyboardInput(window, 1, this.actions); this.gamepad = new GamepadInput(1, this.actions); window.addEventListener("blur", this.reset); document.addEventListener("visibilitychange", this.visibility); } private readonly visibility = (): void => { if (document.hidden) this.reset(); }; - setActive(active: boolean): void { this.keyboard.setEnabled(active); this.gamepad.setEnabled(active); } - setKnockdown(value: boolean): void { this.gamepad.setKnockdown(value); } + attachTouch(container: HTMLElement, force = coarsePointer()): void { if (this.touch !== null || !force) return; this.touch = new TouchInput(container, this.actions); } + /** `touchShown` keeps the touch controls on screen, inert, while input is off (the rest, a pause). */ + setActive(active: boolean, touchShown = active): void { this.keyboard.setEnabled(active); this.gamepad.setEnabled(active); this.touch?.setEnabled(active, touchShown); } + setKnockdown(value: boolean): void { this.gamepad.setKnockdown(value); this.touch?.setKnockdown(value); } onAction(listener: ((action: SemanticAction) => void) | null): void { this.actions.setListener(listener); } + held(): HeldInput { + const keyboard = this.keyboard.frame(0); const gamepad = this.gamepad.frame(0); const touch = this.touch?.frame() ?? null; + const moveX = gamepad.moveX !== 0 ? gamepad.moveX : touch !== null && touch.moveX !== 0 ? touch.moveX : keyboard.moveX; + const moveY = gamepad.moveY !== 0 ? gamepad.moveY : touch !== null && touch.moveY !== 0 ? touch.moveY : keyboard.moveY; + const defense = gamepad.defense !== "none" ? gamepad.defense : touch !== null && touch.defense !== "none" ? touch.defense : keyboard.defense; + return { moveX, moveY, defense }; + } frame(): InputFrame { - const keyboard = this.keyboard.frame(0); const gamepad = this.gamepad.frame(0); - return { moveX: gamepad.moveX !== 0 ? gamepad.moveX : keyboard.moveX, moveY: gamepad.moveY !== 0 ? gamepad.moveY : keyboard.moveY, defense: gamepad.defense !== "none" ? gamepad.defense : keyboard.defense, actions: this.actions.drain(4) }; + return { ...this.held(), actions: this.actions.drain(4) }; } - destroy(): void { window.removeEventListener("blur", this.reset); document.removeEventListener("visibilitychange", this.visibility); this.keyboard.destroy(); this.gamepad.destroy(); } + destroy(): void { window.removeEventListener("blur", this.reset); document.removeEventListener("visibilitychange", this.visibility); this.keyboard.destroy(); this.gamepad.destroy(); this.touch?.destroy(); } } diff --git a/web/hands/src/input/keyboard.test.ts b/web/hands/src/input/keyboard.test.ts index ac52302f..1e3e0d55 100644 --- a/web/hands/src/input/keyboard.test.ts +++ b/web/hands/src/input/keyboard.test.ts @@ -6,5 +6,7 @@ describe("semantic keyboard parity", () => { it("maps W up and S down, normalizes diagonals and becomes neutral on blur", () => { const input = new KeyboardInput(); window.dispatchEvent(key("keydown", "KeyA")); window.dispatchEvent(key("keydown", "KeyW")); expect(input.frame()).toMatchObject({ moveX: -707, moveY: 707 }); window.dispatchEvent(key("keyup", "KeyW")); window.dispatchEvent(key("keydown", "KeyS")); expect(input.frame()).toMatchObject({ moveX: -707, moveY: -707 }); window.dispatchEvent(new Event("blur")); expect(input.frame()).toMatchObject({ moveX: 0, moveY: 0, defense: "none", actions: [] }); input.destroy(); }); it("coalesces rapid repeats of the same discrete key", () => { const input = new KeyboardInput(window, 3); for (let index = 0; index < 100; index += 1) { window.dispatchEvent(key("keydown", "KeyF")); window.dispatchEvent(key("keyup", "KeyF")); } const actions = input.frame(20).actions; expect(actions).toEqual([{ kind: "punch", hand: "left", class: "jab", target: "head", power: "normal" }]); input.destroy(); }); it("retains only the newest changed intent", () => { const input = new KeyboardInput(window, 1); for (const code of ["KeyF", "KeyJ", "KeyG"]) { window.dispatchEvent(key("keydown", code)); window.dispatchEvent(key("keyup", code)); } expect(input.frame(20).actions).toEqual([{ kind: "punch", hand: "left", class: "hook", target: "head", power: "normal" }]); input.destroy(); }); + it("keeps tracking keys while input is off, so keys held through the bell count from the first frame without a press", () => { const input = new KeyboardInput(); input.setEnabled(false); window.dispatchEvent(key("keydown", "KeyW")); window.dispatchEvent(key("keydown", "KeyQ")); window.dispatchEvent(key("keydown", "KeyF")); expect(input.frame()).toEqual({ moveX: 0, moveY: 0, defense: "none", actions: [] }); input.setEnabled(true); expect(input.frame()).toEqual({ moveX: 0, moveY: 1000, defense: "guard_high", actions: [] }); window.dispatchEvent(key("keydown", "KeyF", true)); expect(input.frame().actions).toEqual([]); window.dispatchEvent(key("keyup", "KeyQ")); expect(input.frame().defense).toBe("none"); input.destroy(); }); + it("takes the hold of a key pressed before the page had focus from its auto-repeat, never a press", () => { const input = new KeyboardInput(); window.dispatchEvent(key("keydown", "KeyD", true)); window.dispatchEvent(key("keydown", "KeyJ", true)); expect(input.frame()).toEqual({ moveX: 1000, moveY: 0, defense: "none", actions: [] }); input.destroy(); }); it("cancels stale intent when guard starts but allows a new punch from guard", () => { const input = new KeyboardInput(); window.dispatchEvent(key("keydown", "KeyF")); window.dispatchEvent(key("keyup", "KeyF")); window.dispatchEvent(key("keydown", "KeyQ")); expect(input.frame()).toEqual({ moveX: 0, moveY: 0, defense: "guard_high", actions: [] }); window.dispatchEvent(key("keydown", "KeyF")); expect(input.frame().actions).toEqual([{ kind: "punch", hand: "left", class: "jab", target: "head", power: "normal" }]); input.destroy(); }); }); diff --git a/web/hands/src/input/keyboard.ts b/web/hands/src/input/keyboard.ts index 9fa53731..845a03a2 100644 --- a/web/hands/src/input/keyboard.ts +++ b/web/hands/src/input/keyboard.ts @@ -6,8 +6,11 @@ export class KeyboardInput { private readonly held = new Set(); private readonly queue: SemanticAction[] = []; private enabled = true; private readonly keydown = (event: KeyboardEvent): void => { - if (!this.enabled || !ACTIVE_CODES.has(event.code)) return; - event.preventDefault(); if (event.repeat) return; this.held.add(event.code); + if (!ACTIVE_CODES.has(event.code)) return; + // Keys stay tracked while input is off (the rest, a pause), so one held through the bell counts from the first frame. + if (!this.enabled) { this.held.add(event.code); return; } + // A repeat takes the hold of a key pressed before the page had focus, never the press. + event.preventDefault(); if (event.repeat) { this.held.add(event.code); return; } this.held.add(event.code); if (event.code === "KeyQ" || event.code === "KeyE") this.clearActions(); const punch = PUNCH_KEYS[event.code]; if (punch !== undefined) this.push({ kind: "punch", hand: punch[0], class: punch[1], target: this.hasShift() ? "body" : "head", power: this.hasAlt() ? "power" : "normal" }); @@ -23,8 +26,10 @@ export class KeyboardInput { private hasAlt(): boolean { return this.held.has("AltLeft") || this.held.has("AltRight"); } private push(action: SemanticAction): void { if (this.sharedActions === undefined) pushActionIntent(this.queue, action, this.maximumQueue); else this.sharedActions.push("keyboard", action); } private clearActions(): void { this.queue.length = 0; this.sharedActions?.clear(); } - setEnabled(enabled: boolean): void { this.enabled = enabled; if (!enabled) this.reset(); } + /** Off drops queued presses but keeps the held keys; the frame stays neutral until input is on again. */ + setEnabled(enabled: boolean): void { this.enabled = enabled; if (!enabled) { this.queue.length = 0; this.sharedActions?.clearSource("keyboard"); } } frame(maxActions = 4): InputFrame { + if (!this.enabled) return { moveX: 0, moveY: 0, defense: "none", actions: [] }; let x = (this.held.has("KeyD") ? 1000 : 0) - (this.held.has("KeyA") ? 1000 : 0); let y = (this.held.has("KeyW") ? 1000 : 0) - (this.held.has("KeyS") ? 1000 : 0); if (x !== 0 && y !== 0) { x = Math.sign(x) * 707; y = Math.sign(y) * 707; } diff --git a/web/hands/src/input/touch.test.ts b/web/hands/src/input/touch.test.ts new file mode 100644 index 00000000..eb17e0a9 --- /dev/null +++ b/web/hands/src/input/touch.test.ts @@ -0,0 +1,154 @@ +import { SharedActionIntent } from "./action-buffer"; +import { ACTION_KEYS } from "./bindings"; +import { TouchInput } from "./touch"; + +const pointer = (type: string, target: Element, init: { pointerId?: number; clientX?: number; clientY?: number }): void => { + const event = new MouseEvent(type, { bubbles: true, cancelable: true, clientX: init.clientX ?? 0, clientY: init.clientY ?? 0 }) as MouseEvent & { pointerId: number }; + Object.defineProperty(event, "pointerId", { value: init.pointerId ?? 1 }); + target.dispatchEvent(event); +}; + +describe("touch controls", () => { + beforeEach(() => { + Element.prototype.setPointerCapture = () => undefined; + Element.prototype.releasePointerCapture = () => undefined; + }); + + it("splits punch pads by hand, applies hold modifiers, and drives the stick", () => { + const container = document.createElement("div"); + document.body.append(container); + const actions = new SharedActionIntent(4); + const touch = new TouchInput(container, actions); + const jab = container.querySelector("[data-punch='jab']")!; + jab.getBoundingClientRect = () => ({ left: 100, top: 0, width: 96, height: 64, right: 196, bottom: 64, x: 100, y: 0, toJSON: () => undefined }); + pointer("pointerdown", jab, { clientX: 110 }); + pointer("pointerdown", jab, { clientX: 190 }); + expect(actions.drain(4)).toEqual([ + { kind: "punch", hand: "left", class: "jab", target: "head", power: "normal", id: "c1" }, + { kind: "punch", hand: "right", class: "jab", target: "head", power: "normal", id: "c2" }, + ]); + + const body = container.querySelector("[data-mod='body']")!; + const power = container.querySelector("[data-mod='power']")!; + pointer("pointerdown", body, { pointerId: 7 }); + pointer("pointerdown", power, { pointerId: 8 }); + const hook = container.querySelector("[data-punch='hook']")!; + hook.getBoundingClientRect = jab.getBoundingClientRect; + pointer("pointerdown", hook, { clientX: 120 }); + expect(actions.drain(4)).toEqual([{ kind: "punch", hand: "left", class: "hook", target: "body", power: "power", id: "c3" }]); + pointer("pointerup", body, { pointerId: 7 }); + pointer("pointerup", power, { pointerId: 8 }); + + const guard = container.querySelector("[data-guard='guard_high']")!; + pointer("pointerdown", guard, { pointerId: 9 }); + expect(touch.frame().defense).toBe("guard_high"); + pointer("pointerup", guard, { pointerId: 9 }); + expect(touch.frame().defense).toBe("none"); + + const zone = container.querySelector("[data-stick]")!; + zone.getBoundingClientRect = () => ({ left: 0, top: 0, width: 400, height: 400, right: 400, bottom: 400, x: 0, y: 0, toJSON: () => undefined }); + pointer("pointerdown", zone, { pointerId: 3, clientX: 100, clientY: 200 }); + pointer("pointermove", zone, { pointerId: 3, clientX: 156, clientY: 200 }); + expect(touch.frame().moveX).toBe(1000); + expect(touch.frame().moveY).toBe(0); + pointer("pointermove", zone, { pointerId: 3, clientX: 100, clientY: 144 }); + expect(touch.frame().moveY).toBe(1000); + pointer("pointerup", zone, { pointerId: 3 }); + expect(touch.frame().moveX).toBe(0); + + touch.setKnockdown(true); + pointer("pointerdown", jab, { clientX: 190 }); + expect(actions.drain(4)).toEqual([{ kind: "get_up_right", id: "c4" }]); + touch.destroy(); + expect(container.querySelector(".touch-controls")).toBeNull(); + }); + + it("gives phone players the slips, weave, pull and clinch as the keyboard's actions, inert while down or off", () => { + const container = document.createElement("div"); + document.body.append(container); + const actions = new SharedActionIntent(4); + const touch = new TouchInput(container, actions); + const moves = [...container.querySelectorAll("[data-move]")]; + expect(moves.map((move) => move.getAttribute("aria-label"))).toEqual(["Slip left", "Weave", "Slip right", "Pull", "Clinch"]); + const press = (kind: string): void => pointer("pointerdown", container.querySelector(`[data-move='${kind}']`)!, {}); + for (const [code, kind] of [["KeyZ", "slip_left"], ["KeyX", "slip_right"], ["KeyC", "weave"], ["KeyV", "pull"], ["KeyB", "clinch"]] as const) { + press(kind); + const drained = actions.drain(4); + expect(drained).toHaveLength(1); + const { id, ...semantic } = drained[0]!; + expect(id).toMatch(/^c\d+$/u); + expect(semantic).toEqual(ACTION_KEYS[code]); + } + touch.setKnockdown(true); + press("slip_left"); + expect(actions.drain(4)).toEqual([]); + touch.setKnockdown(false); + touch.setEnabled(false, true); + press("clinch"); + expect(actions.drain(4)).toEqual([]); + touch.destroy(); + }); + + it("keeps the other guard, and body shots, while a second finger still holds them", () => { + const container = document.createElement("div"); + document.body.append(container); + const actions = new SharedActionIntent(4); + const touch = new TouchInput(container, actions); + const high = container.querySelector("[data-guard='guard_high']")!; + const low = container.querySelector("[data-guard='guard_low']")!; + pointer("pointerdown", high, { pointerId: 1 }); + pointer("pointerdown", low, { pointerId: 2 }); + expect(touch.frame().defense).toBe("guard_low"); + pointer("pointerup", low, { pointerId: 2 }); + expect(touch.frame().defense).toBe("guard_high"); + expect(high.classList.contains("pressed")).toBe(true); + expect(low.classList.contains("pressed")).toBe(false); + pointer("pointerdown", low, { pointerId: 3 }); + pointer("pointerup", high, { pointerId: 1 }); + expect(touch.frame().defense).toBe("guard_low"); + pointer("pointerup", low, { pointerId: 3 }); + expect(touch.frame().defense).toBe("none"); + + const body = container.querySelector("[data-mod='body']")!; + pointer("pointerdown", body, { pointerId: 4 }); + pointer("pointerdown", body, { pointerId: 5 }); + pointer("pointerup", body, { pointerId: 4 }); + const jab = container.querySelector("[data-punch='jab']")!; + jab.getBoundingClientRect = () => ({ left: 100, top: 0, width: 96, height: 64, right: 196, bottom: 64, x: 100, y: 0, toJSON: () => undefined }); + pointer("pointerdown", jab, { pointerId: 6, clientX: 110 }); + expect(actions.drain(4)).toMatchObject([{ kind: "punch", hand: "left", target: "body" }]); + expect(body.classList.contains("pressed")).toBe(true); + touch.destroy(); + }); + + it("stays up through the rest and holds a resting thumb from the first frame after the bell", () => { + const container = document.createElement("div"); + document.body.append(container); + const actions = new SharedActionIntent(4); + const touch = new TouchInput(container, actions); + const root = container.querySelector(".touch-controls")!; + touch.setEnabled(false, true); + expect(root.classList.contains("resting")).toBe(true); + expect(root.classList.contains("disabled")).toBe(false); + pointer("pointerdown", container.querySelector("[data-guard='guard_high']")!, { pointerId: 4 }); + const zone = container.querySelector("[data-stick]")!; + zone.getBoundingClientRect = () => ({ left: 0, top: 0, width: 400, height: 400, right: 400, bottom: 400, x: 0, y: 0, toJSON: () => undefined }); + pointer("pointerdown", zone, { pointerId: 5, clientX: 100, clientY: 200 }); + pointer("pointermove", zone, { pointerId: 5, clientX: 156, clientY: 200 }); + const jab = container.querySelector("[data-punch='jab']")!; + jab.getBoundingClientRect = () => ({ left: 100, top: 0, width: 96, height: 64, right: 196, bottom: 64, x: 100, y: 0, toJSON: () => undefined }); + pointer("pointerdown", jab, { pointerId: 6, clientX: 110 }); + expect(touch.frame()).toEqual({ moveX: 0, moveY: 0, defense: "none", actions: [] }); + expect(actions.drain(4)).toEqual([]); + + touch.setEnabled(true); + expect(root.classList.contains("resting")).toBe(false); + expect(touch.frame()).toMatchObject({ moveX: 1000, moveY: 0, defense: "guard_high" }); + + touch.setEnabled(false); + expect(root.classList.contains("disabled")).toBe(true); + touch.setEnabled(true); + expect(touch.frame()).toMatchObject({ moveX: 0, moveY: 0, defense: "none" }); + touch.destroy(); + }); +}); diff --git a/web/hands/src/input/touch.ts b/web/hands/src/input/touch.ts new file mode 100644 index 00000000..21430746 --- /dev/null +++ b/web/hands/src/input/touch.ts @@ -0,0 +1,227 @@ +import { SharedActionIntent } from "./action-buffer"; +import type { HeldDefense, InputFrame, MovementKind, PunchClass } from "../types"; + +/** + * On-screen controls for coarse-pointer clients (Discord mobile). The left + * half of the activity is a floating joystick for footwork; the right side + * carries four punch pads whose left or right half selects the hand, hold + * modifiers for body shots and power, hold guards, and a row of evasions and + * the clinch. During a knockdown the pads become the get-up rhythm buttons. + */ + +export function coarsePointer(): boolean { + try { + if (window.matchMedia?.("(pointer: coarse)").matches) return true; + } catch { + // matchMedia can be unavailable in embedded webviews. + } + return (navigator.maxTouchPoints ?? 0) > 0 && new URLSearchParams(window.location.search).get("platform") === "mobile"; +} + +const PUNCH_PADS: readonly { readonly label: string; readonly punchClass: PunchClass }[] = [ + { label: "JAB", punchClass: "jab" }, + { label: "STRAIGHT", punchClass: "straight" }, + { label: "HOOK", punchClass: "hook" }, + { label: "UPPER", punchClass: "uppercut" }, +]; + +/** The evasions and the clinch, the same actions as the keyboard's Z, C, X, V and B. */ +const MOVES: readonly { readonly label: string; readonly name: string; readonly kind: MovementKind }[] = [ + { label: "◀ SLIP", name: "Slip left", kind: "slip_left" }, + { label: "WEAVE", name: "Weave", kind: "weave" }, + { label: "SLIP ▶", name: "Slip right", kind: "slip_right" }, + { label: "PULL", name: "Pull", kind: "pull" }, + { label: "CLINCH", name: "Clinch", kind: "clinch" }, +]; + +export class TouchInput { + private readonly root: HTMLElement; + private readonly stickZone: HTMLElement; + private readonly stickBase: HTMLElement; + private readonly stickKnob: HTMLElement; + private readonly pads: HTMLButtonElement[] = []; + private readonly moves: HTMLButtonElement[] = []; + private stickPointer: number | null = null; + private stickOrigin = { x: 0, y: 0 }; + private moveX = 0; + private moveY = 0; + private body = false; + private power = false; + private guard: HeldDefense = "none"; + private knockdown = false; + private enabled = true; + private readonly heldPointers = new Map(); + + constructor(container: HTMLElement, private readonly sharedActions: SharedActionIntent) { + this.root = document.createElement("div"); + this.root.className = "touch-controls"; + this.root.setAttribute("aria-label", "Touch controls"); + this.root.innerHTML = `
+
+
${MOVES.map((move) => ``).join("")}
+
+ + + + +
+
${PUNCH_PADS.map((pad) => ``).join("")}
+
`; + container.append(this.root); + this.stickZone = this.root.querySelector("[data-stick]")!; + this.stickBase = this.root.querySelector("[data-stick-base]")!; + this.stickKnob = this.root.querySelector("[data-stick-knob]")!; + this.pads.push(...this.root.querySelectorAll("[data-punch]")); + this.moves.push(...this.root.querySelectorAll("[data-move]")); + this.bind(); + } + + private bind(): void { + const zone = this.stickZone; + // The stick and the hold buttons track fingers while input is off but shown (the rest, a pause); presses wait for input. + zone.addEventListener("pointerdown", (event) => { + if (this.stickPointer !== null) return; + event.preventDefault(); + this.stickPointer = event.pointerId; + this.stickOrigin = { x: event.clientX, y: event.clientY }; + zone.setPointerCapture(event.pointerId); + const rect = zone.getBoundingClientRect(); + this.stickBase.style.left = `${event.clientX - rect.left}px`; + this.stickBase.style.top = `${event.clientY - rect.top}px`; + this.stickBase.classList.add("active"); + this.updateStick(event.clientX, event.clientY); + }); + zone.addEventListener("pointermove", (event) => { + if (event.pointerId !== this.stickPointer) return; + event.preventDefault(); + this.updateStick(event.clientX, event.clientY); + }); + const release = (event: PointerEvent): void => { + if (event.pointerId !== this.stickPointer) return; + this.stickPointer = null; + this.moveX = 0; + this.moveY = 0; + this.stickKnob.style.transform = "translate(-50%, -50%)"; + this.stickBase.classList.remove("active"); + }; + zone.addEventListener("pointerup", release); + zone.addEventListener("pointercancel", release); + + for (const pad of this.pads) { + pad.addEventListener("pointerdown", (event) => { + if (!this.enabled) return; + event.preventDefault(); + const rect = pad.getBoundingClientRect(); + const hand = event.clientX - rect.left < rect.width / 2 ? "left" : "right"; + if (this.knockdown) { + this.sharedActions.push("touch", { kind: hand === "left" ? "get_up_left" : "get_up_right" }); + return; + } + const punchClass = pad.dataset.punch as PunchClass; + this.sharedActions.push("touch", { kind: "punch", hand, class: punchClass, target: this.body ? "body" : "head", power: this.power ? "power" : "normal" }); + pad.classList.add("pressed"); + window.setTimeout(() => pad.classList.remove("pressed"), 120); + }); + } + for (const move of this.moves) { + // A press must start on the button, like a punch pad; a thumb sliding over from the pads does nothing. + move.addEventListener("pointerdown", (event) => { + if (!this.enabled || this.knockdown) return; + event.preventDefault(); + this.sharedActions.push("touch", { kind: move.dataset.move as MovementKind }); + move.classList.add("pressed"); + window.setTimeout(() => move.classList.remove("pressed"), 120); + }); + } + for (const mod of this.root.querySelectorAll("[data-mod], [data-guard]")) { + const key = mod.dataset.mod ?? mod.dataset.guard ?? ""; + const press = (event: PointerEvent): void => { + event.preventDefault(); + mod.setPointerCapture(event.pointerId); + this.heldPointers.set(event.pointerId, key); + if (key === "guard_high" || key === "guard_low") this.sharedActions.clear(); + this.syncHeld(); + mod.classList.add("pressed"); + }; + const lift = (event: PointerEvent): void => { + if (!this.heldPointers.delete(event.pointerId)) return; + this.syncHeld(); + mod.classList.toggle("pressed", [...this.heldPointers.values()].includes(key)); + }; + mod.addEventListener("pointerdown", press); + mod.addEventListener("pointerup", lift); + mod.addEventListener("pointercancel", lift); + } + } + + /** Body, power and guard follow the fingers still down; with both guards held, the later one counts. */ + private syncHeld(): void { + const keys = [...this.heldPointers.values()]; + this.body = keys.includes("body"); + this.power = keys.includes("power"); + this.guard = keys.findLast((key): key is HeldDefense => key === "guard_high" || key === "guard_low") ?? "none"; + } + + private updateStick(clientX: number, clientY: number): void { + const radius = 56; + let dx = clientX - this.stickOrigin.x; + let dy = clientY - this.stickOrigin.y; + const length = Math.hypot(dx, dy); + if (length > radius) { + dx = (dx / length) * radius; + dy = (dy / length) * radius; + } + this.stickKnob.style.transform = `translate(calc(-50% + ${dx}px), calc(-50% + ${dy}px))`; + const magnitude = Math.min(1, length / radius); + const scaled = magnitude < 0.15 ? 0 : (magnitude - 0.15) / 0.85; + const unitX = length > 0 ? dx / Math.max(length, 1e-6) : 0; + const unitY = length > 0 ? dy / Math.max(length, 1e-6) : 0; + this.moveX = Math.round(unitX * scaled * 1000) || 0; + this.moveY = Math.round(-unitY * scaled * 1000) || 0; + } + + setKnockdown(value: boolean): void { + if (this.knockdown === value) return; + this.knockdown = value; + this.root.classList.toggle("knockdown", value); + for (const [index, pad] of this.pads.entries()) { + const label = pad.querySelector(".touch-pad-label"); + if (label !== null) label.textContent = value ? (index % 2 === 0 ? "GET UP" : "RHYTHM") : PUNCH_PADS[index]!.label; + } + } + + /** + * Off and hidden outside a bout. Through the rest and pauses the controls stay shown, dimmed: a + * thumb resting on the stick or a hold button counts from the first frame after the bell. + */ + setEnabled(enabled: boolean, shown = enabled): void { + this.enabled = enabled; + this.root.classList.toggle("disabled", !shown); + this.root.classList.toggle("resting", shown && !enabled); + if (!shown) this.reset(); + else if (!enabled) this.sharedActions.clearSource("touch"); + } + + frame(): InputFrame { + if (!this.enabled) return { moveX: 0, moveY: 0, defense: "none", actions: [] }; + return { moveX: this.moveX, moveY: this.moveY, defense: this.guard, actions: [] }; + } + + reset(): void { + this.stickPointer = null; + this.moveX = 0; + this.moveY = 0; + this.body = false; + this.power = false; + this.guard = "none"; + this.heldPointers.clear(); + this.stickBase.classList.remove("active"); + for (const pressed of this.root.querySelectorAll(".pressed")) pressed.classList.remove("pressed"); + this.sharedActions.clearSource("touch"); + } + + destroy(): void { + this.reset(); + this.root.remove(); + } +} diff --git a/web/hands/src/interpolation.test.ts b/web/hands/src/interpolation.test.ts index 3d625a49..47747e39 100644 --- a/web/hands/src/interpolation.test.ts +++ b/web/hands/src/interpolation.test.ts @@ -1,7 +1,118 @@ import { EventDeduplicator, SnapshotBuffer } from "./interpolation"; import { snapshot } from "./test/fixtures"; + +/** 30 Hz snapshots over an ordered (TCP) link with the given one-way latency, rendered at 60 Hz. */ +function simulateLink(endMs: number, latencyMs: (sentMs: number, tick: number) => number): { delayAt: (ms: number) => number; starvedAfter: (ms: number) => number } { + const buffer = new SnapshotBuffer(8, 30, 2); + const arrivals: { tick: number; at: number }[] = []; + let previous = -Infinity; + for (let tick = 1; tick * (1000 / 30) < endMs; tick += 1) { + const sent = tick * (1000 / 30); + previous = Math.max(sent + latencyMs(sent, tick), previous); + arrivals.push({ tick, at: previous }); + } + const delays: { at: number; delay: number }[] = []; + const starved: number[] = []; + let next = 0; + for (let now = 0; now < endMs; now += 1000 / 60) { + while (next < arrivals.length && arrivals[next]!.at <= now) { buffer.push(snapshot(arrivals[next]!.tick), arrivals[next]!.at); next += 1; } + const latest = buffer.latest(); + const rendered = buffer.renderTick(now); + if (latest !== null && now > 1000 && rendered >= latest.tick) starved.push(now); + delays.push({ at: now, delay: buffer.interpolationDelayTicks }); + } + return { + delayAt: (ms) => delays.findLast((sample) => sample.at <= ms)!.delay, + starvedAfter: (ms) => starved.filter((at) => at > ms).length, + }; +} + describe("authoritative interpolation", () => { - it("orders ticks, interpolates presentation geometry, and rejects stale state", () => { const buffer = new SnapshotBuffer(); const a = snapshot(10), b = { ...snapshot(12), fighters: [{ ...snapshot(12).fighters[0], x: 100 }, snapshot(12).fighters[1]] as const }; expect(buffer.push(a)).toBe(true); expect(buffer.push(a)).toBe(false); expect(buffer.push(b)).toBe(true); expect(buffer.sample(11)?.fighters[0].x).toBe(0); }); + it("orders ticks, interpolates presentation geometry, and rejects stale state", () => { const buffer = new SnapshotBuffer(); const a = snapshot(10), b = { ...snapshot(12), fighters: [{ ...snapshot(12).fighters[0], x: 100, facing_x: 0, facing_y: 1000 }, snapshot(12).fighters[1]] as const }; expect(buffer.push(a)).toBe(true); expect(buffer.push(a)).toBe(false); expect(buffer.push(b)).toBe(true); const mid = buffer.sample(11)!; expect(mid.fighters[0].x).toBe(0); expect(mid.fighters[0].facing_x).toBe(500); expect(mid.fighters[0].facing_y).toBe(500); expect(buffer.sample(11.5)!.fighters[0].x).toBe(50); }); it("snaps across phase and knockdown discontinuities", () => { const buffer = new SnapshotBuffer(); buffer.push(snapshot(10)); const b = { ...snapshot(12), phase: "knockdown" as const }; buffer.push(b); expect(buffer.sample(11)).toBe(b); }); + it("advances a continuous render clock behind the estimated server tick", () => { + const buffer = new SnapshotBuffer(8, 30, 2); + buffer.push(snapshot(10), 0); + buffer.push(snapshot(11), 1000 / 30); + buffer.push(snapshot(12), 2000 / 30); + expect(buffer.renderTick(2000 / 30)).toBeCloseTo(10, 5); + expect(buffer.renderTick(2500 / 30)).toBeCloseTo(10.5, 5); + expect(buffer.renderTick(2000)).toBe(12); + expect(buffer.renderTick(-5000)).toBe(10); + }); + it("widens the interpolation delay when the clock starves and relaxes it within seconds once snapshots arrive on time", () => { + const buffer = new SnapshotBuffer(8, 30, 2); + buffer.push(snapshot(10), 0); + buffer.push(snapshot(11), 1000 / 30); + expect(buffer.interpolationDelayTicks).toBe(2); + buffer.renderTick(400); + expect(buffer.interpolationDelayTicks).toBe(2.5); + buffer.renderTick(500); + expect(buffer.interpolationDelayTicks).toBe(2.5); + const delays = new Map(); + for (let tick = 12; tick < 12 + 30 * 9; tick += 1) { + const at = (tick - 10) * (1000 / 30); + buffer.push(snapshot(tick), at); + expect(buffer.renderTick(at)).toBeLessThanOrEqual(tick); + delays.set(at, buffer.interpolationDelayTicks); + } + // Held while the starved frame is in the lateness window, then back down to the floor. + expect(delays.get(75 * (1000 / 30))).toBe(2.5); + expect(delays.get(150 * (1000 / 30))).toBe(1.5); + expect(buffer.interpolationDelayTicks).toBe(1.5); + }); + it("recovers within seconds from a two-second latency spike", () => { + // 40 ms one way, then 150 ms more for the two seconds from 20 s. + const link = simulateLink(40_000, (sent) => 40 + (sent >= 20_000 && sent < 22_000 ? 150 : 0)); + expect(link.delayAt(19_000)).toBe(1.5); + expect(link.delayAt(22_000)).toBeGreaterThanOrEqual(4.5); + // Before, the delay was still 4.5 ticks at 39 s and took about two minutes to come back. + expect(link.delayAt(28_000)).toBe(1.5); + expect(link.starvedAfter(23_000)).toBe(0); + }); + it("settles above steady jitter instead of relaxing into it again and again", () => { + // Every eighth snapshot is 70 ms late, for good. + const link = simulateLink(30_000, (_sent, tick) => 40 + (tick % 8 === 0 ? 70 : 0)); + expect(link.starvedAfter(5_000)).toBe(0); + expect(link.delayAt(29_000)).toBeGreaterThanOrEqual(2.85); + }); + it("finds the server clock again by itself after the server stops for a disconnection", () => { + const buffer = new SnapshotBuffer(8, 30, 2); + const frame = 1000 / 60; + let now = 0; + let tick = 0; + const play = (seconds: number, onFrame?: (renderTick: number, latest: number) => void): void => { + const end = now + seconds * 1000; + let nextSnapshot = now; + for (; now < end; now += frame) { + while (nextSnapshot <= now) { + tick += 1; + buffer.push(snapshot(tick), nextSnapshot); + nextSnapshot += 1000 / 30; + } + onFrame?.(buffer.renderTick(now), tick); + } + }; + play(10); + const stalled = now + 10_000; + for (; now < stalled; now += frame) buffer.renderTick(now); + play(1); + let latestFrames = 0; + let frames = 0; + play(2, (renderTick, latest) => { frames += 1; if (renderTick >= latest) latestFrames += 1; }); + expect(latestFrames / frames).toBeLessThan(0.1); + expect(buffer.interpolationDelayTicks).toBeLessThanOrEqual(3); + }); + it("starts the clock over on resync, dropping a delay widened by the pause", () => { + const buffer = new SnapshotBuffer(8, 30, 2); + for (let tick = 1; tick <= 60; tick += 1) buffer.push(snapshot(tick), (tick * 1000) / 30); + for (let at = 2000; at < 12_000; at += 16) buffer.renderTick(at); + expect(buffer.interpolationDelayTicks).toBe(6); + buffer.resync(); + expect(buffer.interpolationDelayTicks).toBe(2); + buffer.push(snapshot(61), 12_000); + buffer.push(snapshot(62), 12_000 + 1000 / 30); + expect(buffer.renderTick(12_000 + 1000 / 30)).toBeCloseTo(60, 5); + }); it("deduplicates monotonic cosmetic events", () => { const events = [{ event_id: 2, tick: 1, kind: "hit", actor_id: null, target_id: null, amount: 1, detail: "", blood: 0, direction: 0, action_id: null }, { event_id: 1, tick: 1, kind: "block", actor_id: null, target_id: null, amount: 0, detail: "", blood: 0, direction: 0, action_id: null }, { event_id: 2, tick: 1, kind: "hit", actor_id: null, target_id: null, amount: 1, detail: "", blood: 0, direction: 0, action_id: null }]; const dedupe = new EventDeduplicator(); expect(dedupe.accept(events).map((e) => e.event_id)).toEqual([1, 2]); expect(dedupe.accept(events)).toEqual([]); }); }); diff --git a/web/hands/src/interpolation.ts b/web/hands/src/interpolation.ts index b8ad681e..6872d2d1 100644 --- a/web/hands/src/interpolation.ts +++ b/web/hands/src/interpolation.ts @@ -4,18 +4,112 @@ const mix = (a: number, b: number, t: number): number => a + (b - a) * t; const presentationFighter = (a: FighterSnapshot, b: FighterSnapshot, t: number): FighterSnapshot => ({ ...b, x: mix(a.x, b.x, t), y: mix(a.y, b.y, t), facing: mix(a.facing, b.facing, t), + facing_x: mix(a.facing_x, b.facing_x, t), facing_y: mix(a.facing_y, b.facing_y, t), velocity_x: mix(a.velocity_x, b.velocity_x, t), velocity_y: mix(a.velocity_y, b.velocity_y, t), stamina: mix(a.stamina, b.stamina, t), maximum_stamina: mix(a.maximum_stamina, b.maximum_stamina, t), conditioning: mix(a.conditioning, b.conditioning, t), guard: mix(a.guard, b.guard, t), poise: mix(a.poise, b.poise, t), }); + +const MIN_DELAY_TICKS = 1.5; +const MAX_DELAY_TICKS = 6; +const STARVATION_STEP_TICKS = 0.5; +/** How long a late snapshot or a starved frame keeps the delay up: long enough to span a burst of jitter. */ +const LATENESS_WINDOW_MS = 2500; +/** On top of a snapshot's lateness, one more interval keeps the next snapshot in hand. */ +const LATENESS_MARGIN_TICKS = 1; +/** While the delay comes down the presentation runs this much faster than real time, too little to see. */ +const RELAX_RATE = 0.04; +/** Longest frame gap the relaxation counts, so a page coming back from the background eases in instead of jumping. */ +const RELAX_FRAME_CAP_MS = 100; +const OFFSET_DRIFT_PER_PUSH = 0.01; +/** Consecutive snapshots this far behind the clock mean the server stopped (a paused bout), not jitter. */ +const RESEED_AFTER_PUSHES = 4; + +/** + * Holds recent authoritative snapshots and provides a continuously advancing + * render clock: the client estimates the server tick from snapshot arrival + * times and presents the state a small, adaptive delay behind it so that + * every rendered frame interpolates between two real snapshots instead of + * holding the latest pose until the next packet arrives. + * + * A starved frame widens the delay at once. It comes back down, at a pace + * too slow to see, to what the last few seconds of arrivals needed: the + * worst lateness behind the clock plus one snapshot interval. + */ export class SnapshotBuffer { private readonly snapshots: EngineSnapshot[] = []; - constructor(private readonly maximum = 6) {} - push(snapshot: EngineSnapshot): boolean { + private offsetTicks: number | null = null; + private delayTicks: number; + private lastStarvationMs = -Infinity; + private lastFrameMs: number | null = null; + private behindPushes = 0; + /** Delays recent moments needed, newest last and decreasing, so the first is the largest in the window. */ + private readonly needs: { readonly atMs: number; readonly ticks: number }[] = []; + constructor(private readonly maximum = 8, private readonly tickRate = 30, private readonly initialDelayTicks = 2) { + this.delayTicks = initialDelayTicks; + } + get interpolationDelayTicks(): number { return this.delayTicks; } + push(snapshot: EngineSnapshot, nowMs?: number): boolean { const latest = this.snapshots.at(-1); if (latest !== undefined && snapshot.tick <= latest.tick) return false; - this.snapshots.push(snapshot); if (this.snapshots.length > this.maximum) this.snapshots.shift(); return true; + this.snapshots.push(snapshot); if (this.snapshots.length > this.maximum) this.snapshots.shift(); + if (nowMs !== undefined && Number.isFinite(nowMs)) { + const sample = snapshot.tick - (nowMs * this.tickRate) / 1000; + if (this.offsetTicks !== null && sample < this.offsetTicks - MAX_DELAY_TICKS) this.behindPushes += 1; + else this.behindPushes = 0; + if (this.behindPushes >= RESEED_AFTER_PUSHES) this.restartClock(); + if (this.offsetTicks === null) { + this.offsetTicks = sample; + // A new clock keeps its starting delay until a full window of arrivals shows what the link needs. + this.need(nowMs, this.initialDelayTicks); + } else { + this.offsetTicks = Math.max(sample, this.offsetTicks - OFFSET_DRIFT_PER_PUSH); + } + this.need(nowMs, this.offsetTicks - sample + LATENESS_MARGIN_TICKS); + } + return true; + } + /** Forgets the server clock and the delay it taught, for a new connection or a bout resuming after a pause. */ + resync(): void { + this.restartClock(); + } + private restartClock(): void { + this.offsetTicks = null; + this.delayTicks = this.initialDelayTicks; + this.lastStarvationMs = -Infinity; + this.behindPushes = 0; + this.needs.length = 0; + } + private need(atMs: number, ticks: number): void { + while (this.needs.length > 0 && this.needs.at(-1)!.ticks <= ticks) this.needs.pop(); + this.needs.push({ atMs, ticks }); + } + private recentNeed(nowMs: number): number { + while (this.needs.length > 0 && this.needs[0]!.atMs <= nowMs - LATENESS_WINDOW_MS) this.needs.shift(); + return this.needs[0]?.ticks ?? 0; } latest(): EngineSnapshot | null { return this.snapshots.at(-1) ?? null; } + /** Fractional tick to present at `nowMs`, clamped to the buffered range. */ + renderTick(nowMs: number): number { + const latest = this.latest(); + if (latest === null) return 0; + const oldest = this.snapshots[0]!.tick; + if (this.offsetTicks === null) return Math.max(oldest, latest.tick - 1); + const frameMs = this.lastFrameMs === null ? 0 : Math.min(RELAX_FRAME_CAP_MS, Math.max(0, nowMs - this.lastFrameMs)); + this.lastFrameMs = nowMs; + const estimate = (nowMs * this.tickRate) / 1000 + this.offsetTicks - this.delayTicks; + if (estimate > latest.tick + 0.25) { + if (nowMs - this.lastStarvationMs > 250) { + this.lastStarvationMs = nowMs; + this.delayTicks = Math.min(MAX_DELAY_TICKS, this.delayTicks + STARVATION_STEP_TICKS); + // The snapshots that will show how late the link runs have not arrived yet; hold the new delay meanwhile. + this.need(nowMs, this.delayTicks); + } + } else { + const target = Math.max(MIN_DELAY_TICKS, this.recentNeed(nowMs)); + if (this.delayTicks > target) this.delayTicks = Math.max(target, this.delayTicks - (RELAX_RATE * frameMs * this.tickRate) / 1000); + } + return Math.min(latest.tick, Math.max(oldest, estimate)); + } sample(tick: number): EngineSnapshot | null { const nextIndex = this.snapshots.findIndex((item) => item.tick >= tick); if (nextIndex <= 0) return this.snapshots[Math.max(0, nextIndex)] ?? this.latest(); @@ -24,7 +118,7 @@ export class SnapshotBuffer { const t = Math.max(0, Math.min(1, (tick - a.tick) / Math.max(1, b.tick - a.tick))); return { ...b, fighters: [presentationFighter(a.fighters[0], b.fighters[0], t), presentationFighter(a.fighters[1], b.fighters[1], t)] }; } - clear(): void { this.snapshots.length = 0; } + clear(): void { this.snapshots.length = 0; this.offsetTicks = null; } } export class EventDeduplicator { private highest = -1; diff --git a/web/hands/src/lab/lab.ts b/web/hands/src/lab/lab.ts index e92959d1..6cf18915 100644 --- a/web/hands/src/lab/lab.ts +++ b/web/hands/src/lab/lab.ts @@ -2,7 +2,6 @@ import * as THREE from "three"; import { HURTBOXES } from "../manifest"; import { BONE_ADAPTER, loadBoxerGlb } from "../render/graph"; import { FightRenderer } from "../render/renderer"; -import markerData from "../assets/fighter-markers.json"; import type { BloodLevel } from "../settings"; import type { EngineSnapshot } from "../types"; @@ -66,7 +65,6 @@ export class LabApp { private readonly pendingQueue: Array<{ at: number; tick: ReplayTick }> = []; private destroyed = false; private overlays = { skeleton: false, hurtbox: false, hitbox: false }; - private trajectoryLine: THREE.Line | null = null; private readonly skeletonLines: THREE.LineSegments[] = []; private readonly hurtboxMeshes: THREE.Mesh[] = []; private readonly hitboxMeshes: THREE.Mesh[] = []; @@ -106,7 +104,7 @@ export class LabApp { await loadBoxerGlb(); this.renderer = new FightRenderer( this.canvas, - { tick_rate: this.replay.tick_rate, ring_half_width: 500, ring_half_height: 330 }, + { tick_rate: this.replay.tick_rate, ring_half_width: 500, ring_half_height: 500 }, () => ({ volume: 0, haptics: false, reducedMotion: false, blood: "full" as BloodLevel }), { manualClock: true }, ); @@ -254,7 +252,6 @@ export class LabApp { this.renderer.labFrame(this.virtualTick / this.replay.tick_rate, render ?? this.renderOnSeek); this.renderer.labFrame((this.virtualTick + 0.5) / this.replay.tick_rate, render ?? this.renderOnSeek); this.updateOverlays(); - this.updateTrajectory(); const tick = this.replay.ticks[this.virtualTick]; const phase = tick?.snapshot.payload.phase ?? ""; this.setStatus(`tick ${this.virtualTick}/${this.replay.ticks.length - 1} · ${phase} · ${this.speed}×`); @@ -307,39 +304,6 @@ export class LabApp { for (const lines of this.skeletonLines) lines.visible = this.overlays.skeleton; for (const mesh of this.hurtboxMeshes) mesh.visible = this.overlays.hurtbox; for (const mesh of this.hitboxMeshes) mesh.visible = this.overlays.hitbox; - this.updateTrajectory(); - } - - private updateTrajectory(): void { - if (this.trajectoryLine !== null) { - this.trajectoryLine.removeFromParent(); - this.trajectoryLine.geometry.dispose(); - (this.trajectoryLine.material as THREE.Material).dispose(); - this.trajectoryLine = null; - } - if (!this.overlays.hitbox || this.replay === null || this.renderer === null) return; - const entry = this.replay.ticks[this.virtualTick]; - const fighter = entry?.snapshot.payload.fighters[0]; - const key = fighter?.action_key; - if (key === undefined || key === null) return; - const parts = key.split(":"); - const trajectory = (markerData.trajectories as Record)[`${parts[0]}:${parts[1]}`]; - if (trajectory === undefined) return; - const fighterRoot = this.renderer.labRigs[0]!; - const fighterModel = fighterRoot.children[0] ?? fighterRoot; - fighterModel.updateMatrixWorld(true); - const points = (parts[1] === "right" ? trajectory.right : trajectory.left).map( - (point) => fighterModel.localToWorld(new THREE.Vector3(point[0] ?? 0, point[1] ?? 0, point[2] ?? 0)), - ); - if (points.length < 2) return; - const geometry = new THREE.BufferGeometry().setFromPoints(points); - this.trajectoryLine = new THREE.Line( - geometry, - new THREE.LineBasicMaterial({ color: 0x5db4ff, transparent: true, opacity: 0.75, depthTest: false }), - ); - this.trajectoryLine.renderOrder = 23; - this.trajectoryLine.frustumCulled = false; - this.renderer.labScene.add(this.trajectoryLine); } private updateOverlays(): void { diff --git a/web/hands/src/lab/model-lab.ts b/web/hands/src/lab/model-lab.ts index c1b41dc2..678a7b2a 100644 --- a/web/hands/src/lab/model-lab.ts +++ b/web/hands/src/lab/model-lab.ts @@ -1,276 +1,249 @@ import * as THREE from "three"; -import { clone as cloneSkeleton } from "three/examples/jsm/utils/SkeletonUtils.js"; -import { BONE_ADAPTER, FIGHTER_MODEL_SCALE, applyFighterSkin, loadBoxerGlb } from "../render/graph"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb } from "../render/graph"; +import { GloveTrail } from "../render/trails"; +import { worldMapping } from "../render/world"; +import type { FighterSnapshot, Hand, PunchClass, Target } from "../types"; -interface ClipRow { - readonly name: string; - readonly duration: string; - readonly tracks: number; -} +/** + * Pose lab: drives the runtime animation graph with synthetic fighter state so + * every authored pose can be inspected from any angle without a match. + * Query parameters: pose (idle, guard_high, guard_low, slip_left, slip_right, + * weave, pull, jab_left, straight_right, hook_left, uppercut_right, ..., + * hit_head, hit_body, block, knockdown, getup, stunned, taunt, clinch, seated, celebrate, wave_off, break, touch_gloves, walk), + * t (seconds into the pose), stance (orthodox|southpaw), cam (front|side| + * three-quarter|top|back), skeleton (1). + */ + +type Draft = { -readonly [K in keyof FighterSnapshot]: FighterSnapshot[K] }; + +const base = (): Draft => ({ + player_id: "lab", x: 0, y: 0, facing: 1, facing_x: 0, facing_y: -1000, velocity_x: 0, velocity_y: 0, + stance: "orthodox", defense: "none", stamina: 1000, maximum_stamina: 1000, conditioning: 1000, guard: 700, poise: 600, + trauma: { head: 0, body: 0, left_eye: 0, right_eye: 0, left_cut: 0, right_cut: 0, swelling: 0, bleeding: 0 }, + knockdowns: 0, warnings: 0, deductions: 0, stunned_ticks: 0, is_downed: false, + action: null, action_hand: null, action_target: null, action_power: null, action_id: null, action_key: null, + action_start_tick: 0, action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, + queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, taunt_ticks: 0, + get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, get_up_window_start_tick: 0, get_up_window_end_tick: 0, + last_input_sequence: -1, +}); + +const CAMERAS: Record = { + face: [0.25, 1.55, 1.0], + front: [0, 1.35, 3.4], + side: [3.4, 1.3, 0.2], + "three-quarter": [2.4, 1.5, 2.6], + top: [0.01, 4.5, 0.6], + back: [0.2, 1.4, -3.4], + low: [1.8, 0.5, 2.6], +}; export class ModelLab { private readonly renderer: THREE.WebGLRenderer; private readonly scene = new THREE.Scene(); private readonly camera: THREE.PerspectiveCamera; - private mixer: THREE.AnimationMixer | null = null; - private labMaterials: readonly THREE.Material[] = []; - private actions = new Map(); - private current: THREE.AnimationAction | null = null; + private graph: BoxingGraph | null = null; + private boxer: SkinnedBoxer | null = null; + private trails: GloveTrail[] = []; + private readonly trailGlove = new THREE.Vector3(); private skeletonHelper: THREE.SkeletonHelper | null = null; - private model: THREE.Object3D | null = null; private raf = 0; private previous = performance.now(); - private playing = true; - private loop = true; - private readonly warnings: string[] = []; - private readonly inventoryEl: HTMLElement; - private readonly clipsEl: HTMLElement; - private readonly warningsEl: HTMLElement; - private readonly timeSlider: HTMLInputElement; + private elapsed = 0; + private readonly params = new URLSearchParams(window.location.search); + private reactionFired = false; + private readonly statusEl: HTMLElement; constructor(private readonly root: HTMLElement) { root.innerHTML = `
-
HANDS MODEL LABloading…
- +
HANDS POSE LABloading…
`; - this.inventoryEl = root.querySelector("[data-inventory]")!; - this.clipsEl = root.querySelector("[data-clips]")!; - this.warningsEl = root.querySelector("[data-warnings]")!; - this.timeSlider = root.querySelector("[data-seek]")!; + this.statusEl = root.querySelector("[data-status]")!; const canvas = root.querySelector("[data-canvas]")!; - this.renderer = new THREE.WebGLRenderer({ canvas, antialias: true }); + this.renderer = new THREE.WebGLRenderer({ canvas, antialias: true, preserveDrawingBuffer: true }); this.renderer.setPixelRatio(Math.min(2, window.devicePixelRatio || 1)); this.renderer.shadowMap.enabled = true; this.renderer.toneMapping = THREE.ACESFilmicToneMapping; this.camera = new THREE.PerspectiveCamera(38, 1, 0.1, 60); - this.camera.position.set(0.4, 1.5, 3.6); - this.camera.lookAt(0, 1.0, 0); - this.setupGameLighting(); - this.bindControls(); + const cam = CAMERAS[this.params.get("cam") ?? "three-quarter"] ?? CAMERAS["three-quarter"]!; + this.camera.position.set(...cam); + this.camera.lookAt(0, this.params.get("cam") === "face" ? 1.5 : 1.0, 0); + this.setupLighting(); } - private setupGameLighting(): void { - this.scene.background = new THREE.Color("#04060b"); - if (new URLSearchParams(window.location.search).get("fog") === "1") this.scene.fog = new THREE.FogExp2("#04060b", 0.042); - this.scene.add(new THREE.HemisphereLight("#5a6a95", "#0c0e16", 1.2)); - this.scene.add(new THREE.AmbientLight("#3a4468", 1.05)); - const key = new THREE.SpotLight("#fff4e0", 115, 26, 0.68, 0.6, 1.6); - key.position.set(0, 7.4, 0.9); + private setupLighting(): void { + this.scene.background = new THREE.Color("#101318"); + this.scene.add(new THREE.HemisphereLight("#8fa0c8", "#1a1c22", 1.4)); + const key = new THREE.DirectionalLight("#fff1dc", 2.6); + key.position.set(2.5, 5, 3); key.castShadow = true; - key.target.position.set(0, 0, 0); - this.scene.add(key, key.target); - const fills: Array<[string, number, number, number]> = [ - ["#b9cdff", -6.5, 4.4, -5.2], - ["#ffd9b9", 6.2, 4.1, -5.6], - ["#9fb8ff", -5.4, 3.6, 6.0], - ["#c9d8ff", 5.8, 3.9, 5.7], - ]; - for (const [color, x, y, z] of fills) { - const fill = new THREE.SpotLight(color, 105, 30, 0.7, 0.8, 1.8); - fill.position.set(x, y, z); - fill.target.position.set(0, 1, 0); - this.scene.add(fill, fill.target); - } - const rim = new THREE.DirectionalLight("#dfe9ff", 0.7); - rim.position.set(0, 3.4, -6.5); + key.shadow.mapSize.set(2048, 2048); + this.scene.add(key); + const rim = new THREE.DirectionalLight("#9fb8ff", 1.2); + rim.position.set(-3, 3, -3); this.scene.add(rim); - const floor = new THREE.Mesh(new THREE.CircleGeometry(4, 32), new THREE.MeshStandardMaterial({ color: "#2c4386", roughness: 0.9 })); + const floor = new THREE.Mesh(new THREE.CircleGeometry(4, 48), new THREE.MeshStandardMaterial({ color: "#3c4a7a", roughness: 0.9 })); floor.rotation.x = -Math.PI / 2; floor.receiveShadow = true; this.scene.add(floor); + const grid = new THREE.GridHelper(4, 16, 0x8899bb, 0x33405a); + grid.position.y = 0.002; + this.scene.add(grid); + } + + private synthesize(seconds: number): { fighter: FighterSnapshot; opponent: FighterSnapshot; sampledTick: number; head: THREE.Vector3 } { + const pose = this.params.get("pose") ?? "idle"; + const stance = this.params.get("stance") === "southpaw" ? "southpaw" : "orthodox"; + const fighter: Draft = { ...base(), stance }; + const trauma = this.params.get("trauma"); + if (trauma === "light") fighter.trauma = { head: 220, body: 260, left_eye: 190, right_eye: 60, left_cut: 40, right_cut: 0, swelling: 120, bleeding: 60 }; + if (trauma === "heavy") fighter.trauma = { head: 900, body: 700, left_eye: 720, right_eye: 380, left_cut: 520, right_cut: 190, swelling: 620, bleeding: 520 }; + if (trauma === "cut") fighter.trauma = { head: 420, body: 120, left_eye: 380, right_eye: 120, left_cut: 300, right_cut: 0, swelling: 260, bleeding: 380 }; + const opponent = { ...base(), player_id: "other", x: 0, y: -150, facing_x: 0, facing_y: 1000 } as FighterSnapshot; + const tick = Math.floor(seconds * 30); + const punch = /^(jab|straight|hook|uppercut)_(left|right)(_body)?(_power)?$/.exec(pose); + if (punch !== null) { + const punchClass = punch[1] as PunchClass; + const hand = punch[2] as Hand; + const target: Target = punch[3] === "_body" ? "body" : "head"; + const power = punch[4] === "_power" ? "power" : "normal"; + const timing = { jab: [4, 2, 7], straight: [6, 2, 10], hook: [7, 3, 12], uppercut: [8, 2, 13] }[punchClass]!; + const total = timing[0]! + timing[1]! + timing[2]!; + const startTick = Math.floor(tick / (total + 12)) * (total + 12) + 6; + if (tick >= startTick && tick < startTick + total) { + fighter.action = punchClass; + fighter.action_hand = hand; + fighter.action_target = target; + fighter.action_power = power; + fighter.action_id = `lab-${startTick}`; + fighter.action_key = `${punchClass}:${hand}:${target}:${power}`; + fighter.action_start_tick = startTick; + fighter.action_startup_ticks = timing[0]!; + fighter.action_active_ticks = timing[1]!; + fighter.action_recovery_ticks = timing[2]!; + } + } else if (["guard_high", "guard_low", "slip_left", "slip_right", "weave", "pull"].includes(pose)) { + fighter.defense = pose as FighterSnapshot["defense"]; + } else if (pose === "knockdown") { + fighter.is_downed = seconds % 6 < 3.2; + } else if (pose === "stunned") { + fighter.stunned_ticks = 40; + } else if (pose === "taunt") { + fighter.taunt_ticks = Math.max(1, 60 - (tick % 60)); + } else if (pose === "clinch") { + fighter.clinch_ticks = 30; + } else if (pose === "foul") { + fighter.is_foul_recovery_target = true; + } else if (pose === "exhausted") { + fighter.stamina = 80; + } else if (pose.startsWith("walk")) { + const direction = pose.split("_")[1] ?? "forward"; + const speed = 6; + fighter.velocity_x = direction === "left" ? -speed : direction === "right" ? speed : 0; + fighter.velocity_y = direction === "forward" ? speed : direction === "back" ? -speed : 0; + const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); + const travel = seconds * speed * 30; + fighter.x = Math.round(Math.sin(seconds * 0.9) * 0); + fighter.y = Math.round(((travel % 400) - 200) * (direction === "forward" ? 1 : direction === "back" ? -1 : 0)); + fighter.x = Math.round(((travel % 400) - 200) * (direction === "right" ? 1 : direction === "left" ? -1 : 0)); + void mapping; + } + const head = new THREE.Vector3(0, 1.5, 150 * (3.05 / 500)); + return { fighter, opponent, sampledTick: tick, head }; } async start(): Promise { - const status = this.root.querySelector("[data-status]")!; try { const gltf = await loadBoxerGlb(); - this.model = cloneSkeleton(gltf.scene); - this.model.scale.setScalar(FIGHTER_MODEL_SCALE); - this.labMaterials = applyFighterSkin(this.model, { skin: 0xa9744f, gear: 0x1d4ed8 }).owned; - this.scene.add(this.model); - this.model.traverse((object) => { - if (object instanceof THREE.SkinnedMesh) { - object.castShadow = true; - object.frustumCulled = false; - } - }); - this.mixer = new THREE.AnimationMixer(this.model); - const clipRows: ClipRow[] = []; - for (const clip of gltf.animations) { - const action = this.mixer.clipAction(clip); - this.actions.set(clip.name, action); - clipRows.push({ name: clip.name, duration: clip.duration.toFixed(3), tracks: clip.tracks.length }); - if (clip.name === "" || clip.name.startsWith("unnamed")) this.warnings.push(`unnamed clip at index ${clipRows.length - 1}`); + this.boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); + this.graph = new BoxingGraph(this.boxer, worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 })); + this.scene.add(this.boxer.root); + this.trails = [new GloveTrail(new THREE.Color(0xdbe4ff)), new GloveTrail(new THREE.Color(0xdbe4ff))]; + for (const trail of this.trails) this.scene.add(trail.mesh); + if (this.params.get("skeleton") === "1") { + this.skeletonHelper = new THREE.SkeletonHelper(this.boxer.root); + this.scene.add(this.skeletonHelper); } - this.buildClipList(clipRows); - this.buildInventory(); - const requested = new URLSearchParams(window.location.search).get("clip"); - this.playClip(requested !== null && this.actions.has(requested) ? requested : "idle"); - this.skeletonHelper = new THREE.SkeletonHelper(this.model); - this.skeletonHelper.visible = false; - this.scene.add(this.skeletonHelper); - status.textContent = "ready"; + const dislocation = this.params.get("dislocation"); + if (dislocation === "jaw" || dislocation === "shoulder_left" || dislocation === "shoulder_right") this.graph.setArcadeDislocation(dislocation); + this.statusEl.textContent = `pose ${this.params.get("pose") ?? "idle"}`; } catch (error) { - status.textContent = `load failed: ${String(error).slice(0, 120)}`; - this.warnings.push(String(error)); - this.warningsEl.textContent = this.warnings.join("\n"); + this.statusEl.textContent = `load failed: ${String(error).slice(0, 120)}`; throw error; } + const fixed = this.params.get("t"); + const freeze = this.params.get("freeze"); + if (freeze !== null) { + const until = Number(freeze); + while (this.elapsed < until) { + this.elapsed += 1 / 60; + this.step(1 / 60); + } + } const loop = (time: number): void => { const dt = Math.min(0.05, (time - this.previous) / 1000); this.previous = time; - if (this.mixer !== null && this.playing) this.mixer.update(dt); - if (this.current !== null && !this.playing) { - // seek mode: hold the slider time + if (freeze !== null) { + this.step(0); + } else { + this.elapsed = fixed !== null ? Number(fixed) : this.elapsed + dt; + this.step(fixed !== null ? 1 / 60 : dt); } - this.syncSeek(); this.renderer.render(this.scene, this.camera); this.raf = requestAnimationFrame(loop); }; this.raf = requestAnimationFrame(loop); } - private buildClipList(rows: readonly ClipRow[]): void { - const list = document.createElement("div"); - list.className = "model-clip-list"; - for (const row of rows) { - const button = document.createElement("button"); - button.type = "button"; - button.textContent = `${row.name} (${row.duration}s, ${row.tracks} tracks)`; - button.dataset.clip = row.name; - button.addEventListener("click", () => this.playClip(row.name)); - list.append(button); + private step(dt: number): void { + const graph = this.graph; + if (graph === null) return; + const width = this.renderer.domElement.clientWidth; + const height = this.renderer.domElement.clientHeight; + if (width > 0 && height > 0 && (this.renderer.domElement.width !== width || this.renderer.domElement.height !== height)) { + this.renderer.setSize(width, height, false); + this.camera.aspect = width / height; + this.camera.updateProjectionMatrix(); } - this.clipsEl.replaceChildren(list); - } - - private buildInventory(): void { - if (this.model === null) return; - this.model.updateMatrixWorld(true); - const lines: string[] = []; - let triangles = 0; - const materials = new Set(); - const textures = new Set(); - this.model.traverse((object) => { - if (object instanceof THREE.SkinnedMesh || object instanceof THREE.Mesh) { - const geometry = object.geometry; - const index = geometry.getIndex(); - triangles += (index !== null ? index.count : geometry.getAttribute("position").count) / 3; - for (const material of Array.isArray(object.material) ? object.material : [object.material]) { - materials.add(material); - const standard = material as THREE.MeshStandardMaterial; - if (standard.map !== null && standard.map !== undefined) textures.add(standard.map); - } + const { fighter, opponent, sampledTick, head } = this.synthesize(this.elapsed); + const reaction = this.params.get("pose") ?? ""; + if (/^(hit|block)_/.test(reaction)) { + const period = 1.6; + const phase = this.elapsed % period; + const fire = this.params.has("freeze") ? !this.reactionFired && this.elapsed >= 0.02 : phase < dt * 1.5; + if (fire) { + this.reactionFired = true; + const [kind, target, punchClass, hand] = reaction.split("_"); + graph.react(kind === "block" ? "block" : "hit", (target as Target) ?? "head", 1, (punchClass as PunchClass) ?? "straight", (hand as Hand) ?? "right", 320); } - }); - lines.push(`triangles: ${Math.round(triangles)}`); - lines.push(`materials: ${materials.size}`); - lines.push(`textures: ${textures.size}`); - for (const texture of textures) { - const image = texture.image as { width?: number; height?: number } | undefined; - lines.push(`texture: ~${image?.width ?? "?"}×${image?.height ?? "?"}`); } - lines.push(""); - lines.push("bone hierarchy:"); - const bones: THREE.Bone[] = []; - this.model.traverse((object) => { - if (object instanceof THREE.Bone) bones.push(object); - }); - const roots = bones.filter((bone) => !(bone.parent instanceof THREE.Bone)); - const walk = (bone: THREE.Bone, depth: number): void => { - lines.push(`${" ".repeat(depth)}${bone.name || "(unnamed)"}`); - if (bone.name === "") this.warnings.push("unnamed bone found"); - for (const child of bone.children) if (child instanceof THREE.Bone) walk(child, depth + 1); - }; - for (const rootBone of roots) walk(rootBone, 0); - lines.push(""); - lines.push("adapter mapping:"); - for (const [canonical, model] of Object.entries(BONE_ADAPTER)) lines.push(` ${canonical} → ${model}`); - this.inventoryEl.textContent = lines.join("\n"); - const missing = Object.values(BONE_ADAPTER).filter((name) => this.model!.getObjectByName(name) === undefined); - for (const name of missing) this.warnings.push(`missing mapped bone: ${name}`); - if (this.warnings.length > 0) this.warningsEl.textContent = this.warnings.join("\n"); - } - - private playClip(name: string): void { - const next = this.actions.get(name); - if (next === undefined || this.mixer === null) return; - const previous = this.current; - next.reset(); - next.setLoop(this.loop ? THREE.LoopRepeat : THREE.LoopOnce, Infinity); - next.clampWhenFinished = true; - if (previous !== null && previous !== next) { - next.crossFadeFrom(previous, 0.25, true); + if (this.params.get("pose") === "knockdown" && this.params.get("fall") === "prone" && this.elapsed % 6 < dt * 1.5) { + graph.react("hit", "head", 1, "hook", "left", 420); } - next.play(); - this.current = next; - for (const button of this.clipsEl.querySelectorAll("button")) { - button.classList.toggle("active", button.dataset.clip === name); + graph.debugHoldImpact = this.params.get("dent") === "hold"; + graph.setResting(this.params.get("pose") === "seated"); + if (this.params.get("pose") === "celebrate") graph.celebrate(60); + if (this.params.get("pose") === "wave_off") graph.waveOff(60); + if (this.params.get("pose") === "break") graph.breakClinch(60); + graph.setCountdown(this.params.get("pose") === "touch_gloves" ? 30 : null); + graph.update(fighter, opponent, dt, this.elapsed, false, "full", sampledTick, head); + for (const [index, bone] of (["gloveL", "gloveR"] as const).entries()) { + this.boxer!.rig.bones[bone].getWorldPosition(this.trailGlove); + this.trails[index]?.update(this.trailGlove, dt, this.camera.position, dt > 0); } - } - - private syncSeek(): void { - if (this.current === null) return; - const duration = this.current.getClip().duration; - if (this.playing) { - this.timeSlider.value = String(Math.round((this.current.time / duration) * 1000)); - } else { - this.current.time = (Number(this.timeSlider.value) / 1000) * duration; - this.mixer?.update(0); - } - } - - private bindControls(): void { - this.root.querySelector("[data-play]")!.addEventListener("click", (event) => { - this.playing = !this.playing; - (event.target as HTMLButtonElement).textContent = this.playing ? "Pause" : "Play"; - }); - this.root.querySelector("[data-loop]")!.addEventListener("change", (event) => { - this.loop = (event.target as HTMLInputElement).checked; - if (this.current !== null) { - const name = this.current.getClip().name; - this.playClip(name); - } - }); - this.root.querySelector("[data-skeleton]")!.addEventListener("change", (event) => { - if (this.skeletonHelper !== null) this.skeletonHelper.visible = (event.target as HTMLInputElement).checked; - }); - this.root.querySelector("[data-scale]")!.addEventListener("input", (event) => { - this.model?.scale.setScalar(Number((event.target as HTMLInputElement).value) / 100); - }); - this.root.querySelector("[data-rotate]")!.addEventListener("input", (event) => { - if (this.model !== null) this.model.rotation.y = (Number((event.target as HTMLInputElement).value) * Math.PI) / 180; - }); - this.root.querySelector("[data-offx]")!.addEventListener("input", (event) => { - if (this.model !== null) this.model.position.x = Number((event.target as HTMLInputElement).value) / 100; - }); - this.root.querySelector("[data-offz]")!.addEventListener("input", (event) => { - if (this.model !== null) this.model.position.z = Number((event.target as HTMLInputElement).value) / 100; - }); + (window as unknown as Record).__poseLab = { + head: this.boxer!.bone("head")!.getWorldPosition(new THREE.Vector3()).toArray().map((v) => Number(v.toFixed(3))), + gloveL: this.boxer!.bone("gloveL")!.getWorldPosition(new THREE.Vector3()).toArray().map((v) => Number(v.toFixed(3))), + gloveR: this.boxer!.bone("gloveR")!.getWorldPosition(new THREE.Vector3()).toArray().map((v) => Number(v.toFixed(3))), + ankleL: this.boxer!.bone("ankleL")!.getWorldPosition(new THREE.Vector3()).toArray().map((v) => Number(v.toFixed(3))), + ankleR: this.boxer!.bone("ankleR")!.getWorldPosition(new THREE.Vector3()).toArray().map((v) => Number(v.toFixed(3))), + }; } destroy(): void { cancelAnimationFrame(this.raf); - for (const material of this.labMaterials) material.dispose(); + this.graph?.dispose(); this.renderer.dispose(); this.root.replaceChildren(); } diff --git a/web/hands/src/main.ts b/web/hands/src/main.ts index 254754e8..8f98e259 100644 --- a/web/hands/src/main.ts +++ b/web/hands/src/main.ts @@ -1,5 +1,6 @@ import "./style.css"; import { HandsApp } from "./app"; +import { devAuthorizer } from "./dev-e2e"; import { runDevelopmentFixture } from "./dev-fixtures"; import { runLab } from "./lab/lab"; import { runModelLab } from "./lab/model-lab"; @@ -13,7 +14,13 @@ const modelLabMode = window.location.pathname.endsWith("/hands/model-lab") || pa if (modelLabMode) teardown = runModelLab(root); else if (labMode) teardown = runLab(root); else if (import.meta.env.DEV && params.get("fixture") === "1") teardown = runDevelopmentFixture(root); -else { +else if (import.meta.env.DEV && params.get("e2e") === "1") { + // The development authorizer runs without Discord, so there is no SDK to close. + const app = new HandsApp(root, undefined, { authorize: devAuthorizer, close: () => undefined }); + (window as unknown as Record).__handsApp = app; + app.start(); + teardown = () => app.destroy(); +} else { const app = new HandsApp(root); app.start(); teardown = () => app.destroy(); diff --git a/web/hands/src/manifest.ts b/web/hands/src/manifest.ts index 89bb157d..84387146 100644 --- a/web/hands/src/manifest.ts +++ b/web/hands/src/manifest.ts @@ -17,6 +17,9 @@ interface ManifestVariant { readonly reach_min?: number; readonly reach_sub?: number; readonly lateral_arc_add?: number; + readonly stamina_cost_add?: number; + readonly stamina_cost_mul_num?: number; + readonly stamina_cost_mul_den?: number; } interface ManifestPunch { @@ -25,6 +28,8 @@ interface ManifestPunch { readonly recovery: number; readonly reach: number; readonly lateral_arc: number; + readonly stamina_cost: number; + readonly combo_window: number; } const punches = manifestJson.punches as unknown as Record; @@ -36,6 +41,48 @@ export const HITSTOP_MS = manifestJson.hitstop_ms; export const HURTBOXES = manifestJson.hurtboxes; export const GLOVE_HITBOX_RADIUS = manifestJson.hitbox.glove_radius; export const FATIGUE_SCALING = manifestJson.fatigue_scaling; +export const REST_CORNER_OFFSET = manifestJson.rest.corner_offset; +export const RING_HALF_WIDTH = manifestJson.ring.half_width; +export const RING_HALF_HEIGHT = manifestJson.ring.half_height; +export const FIGHTER_RADIUS = manifestJson.ring.fighter_radius; +export const RING_CORNER_REACH = manifestJson.corners.reach; +/** Percent of a punch's recovery that must pass before a chained follow-up may cut the rest of it short. */ +export const RECOVERY_CANCEL_PERCENT = manifestJson.combos.recovery_cancel_percent; +const comboChains = new Set(manifestJson.combos.chains.map(([first, second]) => `${first}:${second}`)); + +/** Whether the engine counts `second` straight after `first` as a combination. */ +export function comboChain(first: PunchClass, second: PunchClass): boolean { + return comboChains.has(`${first}:${second}`); +} + +/** Age from which a punch's recovery may give way to a follow-up: the engine's `cancel_age`. */ +export function recoveryCancelAge(timing: Pick): number { + return timing.startup + timing.active + Math.floor((timing.recovery * RECOVERY_CANCEL_PERCENT) / 100); +} + +/** + * The engine's `_can_cancel_recovery` for a punch past its `recoveryCancelAge`: the follow-up waiting + * on it starts at once only if the punch landed (a hit or an ordinary block, not a whiff, an evade or a + * parry), the two form a combination, the fighter can pay the follow-up's full cost and the defender is + * not stunned. Otherwise the follow-up starts the tick after the punch ends. + */ +export function cancelsRecovery( + punch: PunchClass, + landed: boolean, + followUp: { readonly class: PunchClass; readonly target: Target; readonly power: Power }, + stamina: number, + defenderStunned: boolean, +): boolean { + return landed + && !defenderStunned + && comboChain(punch, followUp.class) + && stamina >= punchStaminaCost(followUp.class, followUp.target, followUp.power); +} + +/** Ticks after a punch ends during which a compatible follow-up still counts as a combination. */ +export function comboWindow(punchClass: PunchClass): number { + return punches[punchClass].combo_window; +} export function punchTiming(punchClass: PunchClass, target: Target, power: Power): PunchTiming { const base = punches[punchClass]; @@ -61,6 +108,14 @@ export function punchTiming(punchClass: PunchClass, target: Target, power: Power return { startup, active, recovery, reach, lateralArc }; } +/** Stamina the engine charges to start this punch, before any combo discount. */ +export function punchStaminaCost(punchClass: PunchClass, target: Target, power: Power): number { + let cost = punches[punchClass].stamina_cost; + if (target === "body") cost += variants.body.stamina_cost_add ?? 0; + if (power === "power") cost = Math.floor((cost * (variants.power.stamina_cost_mul_num ?? 1)) / (variants.power.stamina_cost_mul_den ?? 1)); + return cost; +} + export function actionKey(punchClass: PunchClass, hand: Hand, target: Target, power: Power): string { return `${punchClass}:${hand}:${target}:${power}`; } diff --git a/web/hands/src/network.test.ts b/web/hands/src/network.test.ts index f6185cb0..a1a4c9af 100644 --- a/web/hands/src/network.test.ts +++ b/web/hands/src/network.test.ts @@ -1,3 +1,4 @@ +import { snapshot } from "./test/fixtures"; import { NetworkController, websocketUrl } from "./network"; import type { ServerMessage } from "./types"; @@ -10,6 +11,7 @@ class FakeSocket { onerror: ((event: Event) => void) | null = null; sent: string[] = []; closed = false; + bufferedAmount = 0; send(data: string): void { this.sent.push(data); } close(): void { this.closed = true; } open(): void { this.onopen?.(new Event("open")); } @@ -30,18 +32,18 @@ const callbacks = (overrides: Partial<{ }); const welcome = (ticket = "ticket-b") => ({ - version: 2, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, + version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [{ id: "one", name: "One", avatar: null, rating: 1500, connected: true }], server_tick: 40, next_sequence: 5, reconnect_ticket: ticket, }); const ready = { - version: 2, type: "ready", players: [ + version: 3, type: "ready", players: [ { id: "one", name: "One", avatar: null, rating: 1500, connected: true }, { id: "two", name: "Two", avatar: null, rating: 1500, connected: true }, ], }; const final = { - version: 2, type: "final", match_id: "match", winner_id: "one", method: "decision", round: 1, + version: 3, type: "final", match_id: "match", winner_id: "one", method: "decision", round: 1, scorecards: ["A", "B", "C"].map((judge) => ({ judge, player_one: [10], player_two: [9] })), ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } }, }; @@ -85,6 +87,32 @@ describe("same-origin WebSocket controller", () => { controller.dispose(); }); + it("measures input acknowledgement latency from the local fighter's acknowledged sequence", () => { + vi.useFakeTimers(); + history.replaceState({}, "", "/"); + const socket = new FakeSocket(); + const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks(), () => socket, () => Date.now()); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + expect(controller.inputLatencyMs).toBeNull(); + vi.advanceTimersByTime(40); + const sent = JSON.parse(socket.sent.at(-1)!) as { sequence: number }; + vi.advanceTimersByTime(70); + const base = snapshot(); + const acknowledged = { ...base, tick: 44, fighters: [{ ...base.fighters[0], player_id: welcome().player_id, last_input_sequence: sent.sequence }, base.fighters[1]] as const }; + socket.message({ version: 3, type: "snapshot", payload: acknowledged }); + const measured = controller.inputLatencyMs; + expect(measured).not.toBeNull(); + expect(measured!).toBeGreaterThanOrEqual(70); + expect(measured!).toBeLessThan(120); + vi.advanceTimersByTime(40); + socket.message({ version: 3, type: "snapshot", payload: { ...acknowledged, tick: 45 } }); + expect(controller.inputLatencyMs).toBe(measured); + controller.dispose(); + }); + it("never sends gameplay input for a server-declared spectator", () => { vi.useFakeTimers(); const socket = new FakeSocket(); @@ -93,7 +121,7 @@ describe("same-origin WebSocket controller", () => { controller.start(); socket.open(); socket.message({ - version: 2, + version: 3, type: "welcome", role: "spectator", player_id: "viewer", @@ -125,9 +153,9 @@ describe("same-origin WebSocket controller", () => { controller.start(); sockets[0]!.open(); sockets[0]!.message(welcome("ticket-b")); - sockets[0]!.message({ version: 2, type: "ticket", reconnect_ticket: "ticket-c", refresh_id: "refresh-identifier" }); + sockets[0]!.message({ version: 3, type: "ticket", reconnect_ticket: "ticket-c", refresh_id: "refresh-identifier" }); expect(messages.map((message) => message.type)).toEqual(["welcome"]); - expect(JSON.parse(sockets[0]!.sent[1]!)).toEqual({ version: 2, type: "ticket_ack", refresh_id: "refresh-identifier" }); + expect(JSON.parse(sockets[0]!.sent[1]!)).toEqual({ version: 3, type: "ticket_ack", refresh_id: "refresh-identifier" }); sockets[0]!.disconnect(); vi.advanceTimersByTime(250); sockets[1]!.open(); @@ -158,6 +186,87 @@ describe("same-origin WebSocket controller", () => { expect(socket.sent.slice(1)).toHaveLength(1); }); + it("sends one neutral frame as input goes off at the bell, and one on a later focus loss, so held input stops driving the fighter", () => { + vi.useFakeTimers(); + const socket = new FakeSocket(); + const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 1000, defense: "guard_high", actions: [] }), callbacks(), () => socket); + const inputs = (): Record[] => socket.sent.map((frame) => JSON.parse(frame) as Record).filter((frame) => frame.type === "input"); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + socket.message({ version: 3, type: "snapshot", payload: { ...snapshot(41), phase: "fight" } }); + vi.advanceTimersByTime(40); + expect(inputs().at(-1)).toMatchObject({ move: { x: 0, y: 1000 }, defense: "guard_high" }); + const held = inputs().length; + socket.message({ version: 3, type: "snapshot", payload: { ...snapshot(42), phase: "rest" } }); + expect(inputs()).toHaveLength(held + 1); + expect(inputs().at(-1)).toMatchObject({ move: { x: 0, y: 0 }, defense: "none", actions: [] }); + controller.setActive(false); + vi.advanceTimersByTime(500); + expect(inputs()).toHaveLength(held + 1); + window.dispatchEvent(new Event("blur")); + expect(inputs()).toHaveLength(held + 2); + expect(inputs().at(-1)).toMatchObject({ move: { x: 0, y: 0 }, defense: "none" }); + controller.dispose(); + }); + + it("sends touch input from a frame that never gets document focus, and still stops for a hidden page", () => { + vi.useFakeTimers(); + vi.spyOn(document, "hasFocus").mockReturnValue(false); + const focus = vi.spyOn(window, "focus").mockImplementation(() => undefined); + let hidden = false; + Object.defineProperty(document, "hidden", { configurable: true, get: () => hidden }); + try { + const socket = new FakeSocket(); + const controller = new NetworkController("ticket", () => ({ moveX: 1000, moveY: 0, defense: "none", actions: [] }), callbacks(), () => socket); + const inputs = (): Record[] => socket.sent.map((frame) => JSON.parse(frame) as Record).filter((frame) => frame.type === "input"); + const touch = (): void => { document.body.dispatchEvent(new MouseEvent("pointerdown", { bubbles: true, cancelable: true })); }; + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + vi.advanceTimersByTime(100); + expect(inputs()).toHaveLength(0); + touch(); + expect(focus).toHaveBeenCalledOnce(); + vi.advanceTimersByTime(100); + expect(inputs().length).toBeGreaterThanOrEqual(2); + expect(inputs().at(-1)).toMatchObject({ move: { x: 1000, y: 0 } }); + + hidden = true; + document.dispatchEvent(new Event("visibilitychange")); + expect(inputs().at(-1)).toMatchObject({ move: { x: 0, y: 0 }, defense: "none" }); + const stopped = inputs().length; + vi.advanceTimersByTime(200); + hidden = false; + document.dispatchEvent(new Event("visibilitychange")); + vi.advanceTimersByTime(200); + expect(inputs()).toHaveLength(stopped); + touch(); + vi.advanceTimersByTime(100); + expect(inputs().length).toBeGreaterThan(stopped); + controller.dispose(); + } finally { + delete (document as { hidden?: boolean }).hidden; + } + }); + + it("sends nothing before the bout starts, even on a focus loss, since the server ends the connection for it", () => { + vi.useFakeTimers(); + const socket = new FakeSocket(); + const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 1000, defense: "guard_high", actions: [] }), callbacks(), () => socket); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message({ version: 3, type: "waiting", open_seats: 1 }); + controller.setActive(false); + window.dispatchEvent(new Event("blur")); + vi.advanceTimersByTime(200); + expect(socket.sent.map((frame) => JSON.parse(frame).type)).toEqual(["authenticate"]); + controller.dispose(); + }); + it.each(["room_full", "persistence_failed", "abandoned"])("treats server error %s as terminal", (code) => { vi.useFakeTimers(); const socket = new FakeSocket(); @@ -168,7 +277,7 @@ describe("same-origin WebSocket controller", () => { controller.start(); socket.open(); socket.message(welcome()); - socket.message({ version: 2, type: "error", code }); + socket.message({ version: 3, type: "error", code }); expect(fatal).toHaveBeenCalledOnce(); expect(fatal).toHaveBeenCalledWith(code); expect(socket.closed).toBe(true); @@ -179,13 +288,34 @@ describe("same-origin WebSocket controller", () => { controller.dispose(); }); + it("reports a frame from another protocol version as an outdated client, and a malformed one as a protocol error", () => { + const outdated = new FakeSocket(); + const fatal = vi.fn(); + const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks({ onFatal: fatal }), () => outdated); + controller.start(); + outdated.open(); + // A server that moved on answers authenticate with its own version, so the frame itself does not decode. + outdated.message({ version: 4, type: "error", code: "client_outdated" }); + expect(fatal).toHaveBeenCalledWith("client_outdated"); + controller.dispose(); + + const malformed = new FakeSocket(); + const protocolFatal = vi.fn(); + const other = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks({ onFatal: protocolFatal }), () => malformed); + other.start(); + malformed.open(); + malformed.message({ version: 3, type: "waiting", open_seats: 2 }); + expect(protocolFatal).toHaveBeenCalledWith("protocol_error"); + other.dispose(); + }); + it("ticks an open-socket opponent pause from its current grace to zero", () => { vi.useFakeTimers(); const reconnect = vi.fn(); const socket = new FakeSocket(); const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks({ onReconnect: reconnect }), () => socket, () => Date.now()); controller.start(); socket.open(); socket.message(welcome()); - socket.message({ version: 2, type: "paused", player_id: "two", grace_ms: 1_000 }); + socket.message({ version: 3, type: "paused", player_id: "two", grace_ms: 1_000 }); expect(reconnect).toHaveBeenLastCalledWith(1_000); vi.advanceTimersByTime(250); expect(reconnect).toHaveBeenLastCalledWith(750); vi.advanceTimersByTime(750); expect(reconnect).toHaveBeenLastCalledWith(0); @@ -199,9 +329,9 @@ describe("same-origin WebSocket controller", () => { const socket = new FakeSocket(); const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks({ onReconnect: reconnect }), () => socket, () => Date.now()); controller.start(); socket.open(); socket.message(welcome()); - socket.message({ version: 2, type: "paused", player_id: "two", grace_ms: 2_000 }); + socket.message({ version: 3, type: "paused", player_id: "two", grace_ms: 2_000 }); vi.advanceTimersByTime(250); - socket.message({ version: 2, type: "resumed", player_id: "two" }); + socket.message({ version: 3, type: "resumed", player_id: "two" }); expect(reconnect).toHaveBeenLastCalledWith(0); const calls = reconnect.mock.calls.length; vi.advanceTimersByTime(3_000); @@ -215,7 +345,7 @@ describe("same-origin WebSocket controller", () => { const socket = new FakeSocket(); const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks({ onReconnect: reconnect }), () => socket, () => Date.now()); controller.start(); socket.open(); socket.message(welcome()); - socket.message({ version: 2, type: "paused", player_id: "two", grace_ms: 5_000 }); + socket.message({ version: 3, type: "paused", player_id: "two", grace_ms: 5_000 }); vi.advanceTimersByTime(4_000); socket.disconnect(); expect(reconnect).toHaveBeenLastCalledWith(20_000); @@ -229,7 +359,7 @@ describe("same-origin WebSocket controller", () => { const finalSocket = new FakeSocket(); const finalController = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks({ onReconnect: finalReconnect }), () => finalSocket, () => Date.now()); finalController.start(); finalSocket.open(); finalSocket.message(welcome()); - finalSocket.message({ version: 2, type: "paused", player_id: "two", grace_ms: 2_000 }); + finalSocket.message({ version: 3, type: "paused", player_id: "two", grace_ms: 2_000 }); finalSocket.message(final); expect(finalReconnect).toHaveBeenLastCalledWith(0); expect(vi.getTimerCount()).toBe(0); @@ -238,7 +368,7 @@ describe("same-origin WebSocket controller", () => { const disposeSocket = new FakeSocket(); const disposeController = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none", actions: [] }), callbacks({ onReconnect: disposeReconnect }), () => disposeSocket, () => Date.now()); disposeController.start(); disposeSocket.open(); disposeSocket.message(welcome()); - disposeSocket.message({ version: 2, type: "paused", player_id: "two", grace_ms: 2_000 }); + disposeSocket.message({ version: 3, type: "paused", player_id: "two", grace_ms: 2_000 }); disposeController.dispose(); expect(disposeReconnect).toHaveBeenLastCalledWith(0); expect(vi.getTimerCount()).toBe(0); @@ -258,9 +388,9 @@ describe("same-origin WebSocket controller", () => { controller.start(); sockets[0]!.open(); sockets[0]!.message(welcome()); - sockets[0]!.message({ version: 2, type: "paused", player_id: "two", grace_ms: 5_000 }); + sockets[0]!.message({ version: 3, type: "paused", player_id: "two", grace_ms: 5_000 }); now = 5_500; - sockets[0]!.message({ version: 2, type: "resumed", player_id: "two" }); + sockets[0]!.message({ version: 3, type: "resumed", player_id: "two" }); now = 8_000; sockets[0]!.disconnect(); expect(reconnect).toHaveBeenLastCalledWith(20_000); @@ -278,3 +408,234 @@ describe("same-origin WebSocket controller", () => { controller.dispose(); }); }); + +describe("edge-triggered action sends", () => { + it("flushes immediately on notifyAction and coalesces bursts", () => { + vi.useFakeTimers(); + let now = 1000; + const socket = new FakeSocket(); + const frames = [ + { moveX: 0, moveY: 0, defense: "none" as const, actions: [{ kind: "punch" as const, hand: "left" as const, class: "jab" as const, target: "head" as const, power: "normal" as const, id: "c1" }] }, + { moveX: 0, moveY: 0, defense: "none" as const, actions: [] }, + ]; + let frameIndex = 0; + const controller = new NetworkController( + "ticket", + () => frames[Math.min(frameIndex++, frames.length - 1)]!, + callbacks(), + () => socket, + () => now, + ); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + controller.setActive(true); + controller.notifyAction(); + expect(socket.sent).toHaveLength(2); + expect(JSON.parse(socket.sent[1]!).actions).toEqual([{ kind: "punch", hand: "left", class: "jab", target: "head", power: "normal", id: "c1" }]); + controller.notifyAction(); + expect(socket.sent).toHaveLength(2); + now += 20; + controller.notifyAction(); + expect(socket.sent).toHaveLength(3); + controller.dispose(); + vi.useRealTimers(); + }); + + it("sends a press at once in the middle of a bout, when the periodic flush has filled the last second", () => { + vi.useFakeTimers(); + let now = 1000; + const socket = new FakeSocket(); + const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none" as const, actions: [] }), callbacks(), () => socket, () => now); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + controller.setActive(true); + for (let millisecond = 0; millisecond < 1500; millisecond += 1) { + now += 1; + vi.advanceTimersByTime(1); + } + now += 10; + const before = socket.sent.length; + controller.notifyAction(); + expect(socket.sent.length).toBe(before + 1); + let edges = 0; + for (let millisecond = 0; millisecond < 1000; millisecond += 10) { + now += 10; + vi.advanceTimersByTime(10); + const sent = socket.sent.length; + controller.notifyAction(); + edges += socket.sent.length - sent; + } + expect(edges).toBeLessThanOrEqual(20); + expect(edges).toBeGreaterThanOrEqual(15); + controller.dispose(); + vi.useRealTimers(); + }); + + it("sends a press at once however soon after a periodic flush it comes", () => { + vi.useFakeTimers(); + let now = 1000; + const socket = new FakeSocket(); + const queued: string[] = []; + const controller = new NetworkController( + "ticket", + () => ({ moveX: 0, moveY: 0, defense: "none" as const, actions: queued.splice(0, 4).map((id) => ({ kind: "punch" as const, hand: "left" as const, class: "jab" as const, target: "head" as const, power: "normal" as const, id })) }), + callbacks(), + () => socket, + () => now, + ); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + controller.setActive(true); + const step = (): void => { now += 1; vi.advanceTimersByTime(1); }; + const carried = (id: string): boolean => socket.sent.some((frame) => (JSON.parse(frame).actions ?? []).some((action: { id?: string }) => action.id === id)); + const waits: number[] = []; + for (let offset = 0; offset < 33; offset += 1) { + for (let rest = 0; rest < 100; rest += 1) step(); + const sent = socket.sent.length; + while (socket.sent.length === sent) step(); + for (let elapsed = 0; elapsed < offset; elapsed += 1) step(); + const id = `p${offset}`; + queued.push(id); + controller.notifyAction(); + let waited = 0; + while (!carried(id)) { step(); waited += 1; } + waits.push(waited); + } + expect(waits).toEqual(Array.from({ length: 33 }, () => 0)); + controller.dispose(); + vi.useRealTimers(); + }); + + it("keeps room for the periodic flush when presses come in a burst", () => { + vi.useFakeTimers(); + let now = 1000; + const socket = new FakeSocket(); + const controller = new NetworkController("ticket", () => ({ moveX: 0, moveY: 0, defense: "none" as const, actions: [] }), callbacks(), () => socket, () => now); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + controller.setActive(true); + let edges = 0; + for (let millisecond = 0; millisecond < 400; millisecond += 9) { + now += 9; + vi.advanceTimersByTime(9); + const sent = socket.sent.length; + controller.notifyAction(); + edges += socket.sent.length - sent; + } + expect(edges).toBe(20); + controller.dispose(); + vi.useRealTimers(); + }); + + it("remembers which input sequence carried each press, for telling a refused press from a late one", () => { + vi.useFakeTimers(); + let now = 1000; + const socket = new FakeSocket(); + const queued: string[] = []; + const controller = new NetworkController( + "ticket", + () => ({ moveX: 0, moveY: 0, defense: "none" as const, actions: queued.splice(0, 4).map((id) => ({ kind: "punch" as const, hand: "left" as const, class: "jab" as const, target: "head" as const, power: "normal" as const, id })) }), + callbacks(), + () => socket, + () => now, + ); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + controller.setActive(true); + queued.push("c1"); + expect(controller.sequenceOf("c1")).toBeNull(); + controller.notifyAction(); + expect(controller.sequenceOf("c1")).toBe(5); + now += 20; + queued.push("c2", "c3"); + controller.notifyAction(); + expect([controller.sequenceOf("c2"), controller.sequenceOf("c3")]).toEqual([6, 6]); + expect(controller.sequenceOf("c9")).toBeNull(); + controller.dispose(); + vi.useRealTimers(); + }); + + it("holds its input while the connection is stalled and sends the current state when it clears", () => { + vi.useFakeTimers(); + let now = 1000; + const socket = new FakeSocket(); + let held = 1000; + const queued: string[] = ["p1"]; + const controller = new NetworkController( + "ticket", + () => ({ moveX: held, moveY: 0, defense: "none" as const, actions: queued.splice(0, 4).map((id) => ({ kind: "punch" as const, hand: "left" as const, class: "jab" as const, target: "head" as const, power: "normal" as const, id })) }), + callbacks(), + () => socket, + () => now, + ); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + controller.setActive(true); + const authenticated = socket.sent.length; + socket.bufferedAmount = 5000; + for (let millisecond = 0; millisecond < 2000; millisecond += 1) { now += 1; vi.advanceTimersByTime(1); } + controller.notifyAction(); + expect(socket.sent.length).toBe(authenticated); + held = 0; + socket.bufferedAmount = 0; + for (let millisecond = 0; millisecond < 40; millisecond += 1) { now += 1; vi.advanceTimersByTime(1); } + const frames = socket.sent.slice(authenticated).map((frame) => JSON.parse(frame) as { move: { x: number }; actions: { id: string }[] }); + expect(frames.length).toBeGreaterThanOrEqual(1); + expect(frames.length).toBeLessThanOrEqual(2); + expect(frames[0]!.move.x).toBe(0); + expect(frames[0]!.actions.map((action) => action.id)).toEqual(["p1"]); + controller.dispose(); + vi.useRealTimers(); + }); + + it("stays under the server's input limit however fast the player mashes, without losing a press", () => { + vi.useFakeTimers(); + let now = 1000; + const socket = new FakeSocket(); + const queued: string[] = []; + let pressed = 0; + const controller = new NetworkController( + "ticket", + () => ({ moveX: 0, moveY: 0, defense: "none" as const, actions: queued.splice(0, 4).map((id) => ({ kind: "punch" as const, hand: "left" as const, class: "jab" as const, target: "head" as const, power: "normal" as const, id })) }), + callbacks(), + () => socket, + () => now, + ); + controller.start(); + socket.open(); + socket.message(welcome()); + socket.message(ready); + controller.setActive(true); + const authenticated = socket.sent.length; + const times: number[] = []; + const record = (): void => { while (times.length < socket.sent.length - authenticated) times.push(now); }; + for (let millisecond = 0; millisecond < 3000; millisecond += 1) { + now += 1; + vi.advanceTimersByTime(1); + record(); + if (millisecond < 2000 && millisecond % 2 === 0) { + if (queued.length < 4) { pressed += 1; queued.push(`p${pressed}`); } + controller.notifyAction(); + record(); + } + } + for (const start of times) expect(times.filter((at) => at >= start && at < start + 1000).length).toBeLessThanOrEqual(50); + expect(times.length).toBeGreaterThan(90); + const delivered = socket.sent.slice(authenticated).flatMap((frame) => (JSON.parse(frame).actions as { id: string }[]).map((action) => action.id)); + expect(delivered).toEqual(Array.from({ length: pressed }, (_unused, index) => `p${index + 1}`)); + controller.dispose(); + vi.useRealTimers(); + }); +}); diff --git a/web/hands/src/network.ts b/web/hands/src/network.ts index f04d7d1b..5d197d20 100644 --- a/web/hands/src/network.ts +++ b/web/hands/src/network.ts @@ -1,6 +1,6 @@ -import { safeError } from "./api"; -import { decodeServerFrame, encodeInput } from "./protocol"; -import { PROTOCOL_VERSION, type ConnectionRole, type InputFrame, type ServerMessage } from "./types"; +import { ClientError, safeError } from "./api"; +import { decodeServerFrame, encodeInput, parseStrictJson } from "./protocol"; +import { PROTOCOL_VERSION, type ConnectionRole, type EngineSnapshot, type InputFrame, type ServerMessage } from "./types"; export function websocketUrl(location: Location = window.location): string { const url = new URL("/api/hands/ws", location.origin); @@ -21,6 +21,7 @@ export interface NetworkCallbacks { interface SocketLike { readonly readyState: number; + readonly bufferedAmount?: number; binaryType: BinaryType; onopen: ((event: Event) => void) | null; onmessage: ((event: MessageEvent) => void) | null; @@ -33,6 +34,31 @@ interface SocketLike { type SocketFactory = (url: string) => SocketLike; const OPEN = 1; const NEUTRAL_INPUT: InputFrame = { moveX: 0, moveY: 0, defense: "none", actions: [] }; +const INPUT_FLUSH_MS = 33; +const MIN_EDGE_SEND_GAP_MS = 8; +/** The server accepts 60 inputs a second; staying under it leaves room for frames the network bunches together. */ +const MAX_SENDS_PER_SECOND = 50; +/** Edge sends have a budget of their own on top of the 30 a second flush, together under MAX_SENDS_PER_SECOND. */ +const MAX_EDGE_SENDS_PER_SECOND = 20; +/** Bytes still waiting in the socket above which the connection is stalled; frames queued behind it would all land at once. */ +const BACKLOG_BYTES = 2048; + +/** Decodes a server frame. One that declares another protocol version means this page is out of date, not that the server misbehaved. */ +function decodeFrame(data: string | ArrayBuffer): ServerMessage { + try { + return decodeServerFrame(data); + } catch (error) { + let version: unknown; + try { + const value = parseStrictJson(data); + version = typeof value === "object" && value !== null && "version" in value ? value.version : undefined; + } catch { + // Not even JSON: the original error stands. + } + if (typeof version === "number" && version !== PROTOCOL_VERSION) throw new ClientError("client_outdated", true); + throw error; + } +} export class NetworkController { private socket: SocketLike | null = null; @@ -45,13 +71,24 @@ export class NetworkController { private opponentPaused = false; private attempts = 0; private nextSequence = 0; + private playerId: string | null = null; + private readonly sentAt = new Map(); + private readonly actionSequences = new Map(); + private latencyMs: number | null = null; private serverTick = 0; private role: ConnectionRole | null = null; private active = false; + /** Input has been on, so the server's engine exists and accepts a frame in any phase. */ + private boutStarted = false; private disposed = false; private terminal = false; private inputSuppressed = false; + /** A pointer pressed in the page since the last blur or hidden page; it stands in for document focus. */ + private pointerFocus = false; private listenersBound = false; + private lastInputSentAt = -Infinity; + private readonly sendTimes: number[] = []; + private readonly edgeSendTimes: number[] = []; constructor( ticket: string, @@ -68,25 +105,77 @@ export class NetworkController { this.listenersBound = true; window.addEventListener("blur", this.onInputLoss); window.addEventListener("focus", this.onInputRegain); + window.addEventListener("pointerdown", this.onPagePointer, true); document.addEventListener("visibilitychange", this.onVisibilityChange); this.connect(); - if (!this.disposed && !this.terminal) this.inputTimer = window.setInterval(() => this.flushInput(), 40); + if (!this.disposed && !this.terminal) this.inputTimer = window.setInterval(() => this.flushInput(), INPUT_FLUSH_MS); } setActive(active: boolean): void { + this.setInputActive(active); + } + + /** + * The server keeps applying the last frame's movement and guard until the next frame arrives, and + * none comes while input is off: one neutral frame as it goes off (the bell, a pause) stops a key + * held at the bell from walking the fighter out at the start of the next round. + */ + private setInputActive(active: boolean): void { + const wasActive = this.active; this.active = active; + if (active) this.boutStarted = true; + else if (wasActive) this.sendInput(NEUTRAL_INPUT, true); + } + + /** Sends the pending input frame on the action edge instead of waiting for the periodic flush. */ + notifyAction(): void { + // The gap merges presses that land together. It counts edge sends only: measured from the + // periodic flush too, a press in the 8 ms after each flush waited a whole flush period. + if (this.now() - (this.edgeSendTimes.at(-1) ?? -Infinity) < MIN_EDGE_SEND_GAP_MS) return; + // Past the budget the press stays queued and leaves with the next periodic flush. + if (this.withinLastSecond(this.edgeSendTimes) >= MAX_EDGE_SENDS_PER_SECOND) return; + if (this.flushInput()) this.edgeSendTimes.push(this.lastInputSentAt); + } + + private sendsInLastSecond(): number { + return this.withinLastSecond(this.sendTimes); + } + + private withinLastSecond(times: number[]): number { + const cutoff = this.now() - 1000; + while (times.length > 0 && times[0]! <= cutoff) times.shift(); + return times.length; } private readonly onInputLoss = (): void => { if (this.inputSuppressed) return; - this.sendInput(NEUTRAL_INPUT); + // Sent while input is off too (the rest, a pause); before the bout starts the server refuses input. + this.sendInput(NEUTRAL_INPUT, this.boutStarted); this.inputSuppressed = true; + this.pointerFocus = false; }; private readonly onInputRegain = (): void => { if (!document.hidden && document.hasFocus()) this.inputSuppressed = false; }; + /** + * Inside Discord the page is a frame, and a touch may never focus it: the touch controls cancel + * pointerdown, and the focus change with it. A pointer pressed in the page counts as focus until + * a blur or a hidden page. + */ + private readonly onPagePointer = (): void => { + if (document.hidden) return; + this.pointerFocus = true; + this.inputSuppressed = false; + if (document.hasFocus()) return; + try { + window.focus(); + } catch { + // The host can refuse focus; the press still counts. + } + }; + private readonly onVisibilityChange = (): void => { if (document.hidden) this.onInputLoss(); else this.onInputRegain(); @@ -130,7 +219,7 @@ export class NetworkController { if (this.socket !== socket || this.disposed || this.terminal) return; try { if (typeof event.data !== "string" && !(event.data instanceof ArrayBuffer)) throw new Error("unsupported_frame"); - const message = decodeServerFrame(event.data); + const message = decodeFrame(event.data); this.applyMessage(message); if (message.type === "ticket") { try { @@ -164,6 +253,8 @@ export class NetworkController { this.reconnectTicket = message.reconnect_ticket; this.serverTick = message.server_tick; this.role = message.role; + this.playerId = message.role === "fighter" ? message.player_id : null; + this.sentAt.clear(); if (message.role === "fighter") this.nextSequence = Math.max(this.nextSequence, message.next_sequence); else this.stopInputLifecycle(); this.attempts = 0; @@ -172,18 +263,19 @@ export class NetworkController { this.reconnectTicket = message.reconnect_ticket; } else if (message.type === "snapshot") { this.serverTick = Math.max(this.serverTick, message.payload.tick); - this.active = ["countdown", "fight", "knockdown", "foul_recovery"].includes(message.payload.phase); + this.setInputActive(["countdown", "fight", "knockdown", "foul_recovery"].includes(message.payload.phase)); + this.observeAcknowledgement(message.payload); } else if (message.type === "paused") { - this.active = false; + this.setInputActive(false); this.startOpponentPause(message.grace_ms); } else if (message.type === "resumed") { - this.active = true; + this.setInputActive(true); this.attempts = 0; this.clearOpponentPause(true); } else if (message.type === "ready") { - this.active = true; + this.setInputActive(true); } else if (message.type === "waiting") { - this.active = false; + this.setInputActive(false); } else if (message.type === "final" || message.type === "error") { this.active = false; this.clearOpponentPause(true); @@ -234,20 +326,58 @@ export class NetworkController { }, delay); } - private sendInput(frame: InputFrame): void { + /** Smoothed round trip from an input send to the first snapshot acknowledging it, in milliseconds. */ + get inputLatencyMs(): number | null { + return this.latencyMs; + } + + /** + * The input sequence that carried the press with this instance id, or null before it is sent. Once + * the fighter's last_input_sequence reaches it, the server has seen the press. + */ + sequenceOf(actionId: string): number | null { + return this.actionSequences.get(actionId) ?? null; + } + + private observeAcknowledgement(snapshot: EngineSnapshot): void { + if (this.playerId === null) return; + const self = snapshot.fighters.find((fighter) => fighter.player_id === this.playerId); + if (self === undefined || self.last_input_sequence < 0) return; + const sent = this.sentAt.get(self.last_input_sequence); + if (sent !== undefined) { + const sample = Math.max(0, this.now() - sent); + this.latencyMs = this.latencyMs === null ? sample : this.latencyMs * 0.8 + sample * 0.2; + } + for (const sequence of this.sentAt.keys()) if (sequence <= self.last_input_sequence) this.sentAt.delete(sequence); + } + + private sendInput(frame: InputFrame, whileInactive = false): boolean { const socket = this.socket; - if (this.role !== "fighter" || !this.active || this.disposed || this.terminal || socket?.readyState !== OPEN) return; + if (this.role !== "fighter" || (!this.active && !whileInactive) || this.disposed || this.terminal || socket?.readyState !== OPEN) return false; try { - socket.send(encodeInput(this.nextSequence, this.serverTick, { ...frame, actions: frame.actions.slice(0, 4) })); + const actions = frame.actions.slice(0, 4); + socket.send(encodeInput(this.nextSequence, this.serverTick, { ...frame, actions })); + this.sentAt.set(this.nextSequence, this.now()); + if (this.sentAt.size > 128) this.sentAt.delete(this.sentAt.keys().next().value!); + for (const action of actions) if (action.id !== undefined) this.actionSequences.set(action.id, this.nextSequence); + while (this.actionSequences.size > 64) this.actionSequences.delete(this.actionSequences.keys().next().value!); this.nextSequence += 1; + this.lastInputSentAt = this.now(); + this.sendTimes.push(this.lastInputSentAt); + return true; } catch { this.handleClose(socket); + return false; } } - private flushInput(): void { - if (this.inputSuppressed || document.hidden || !document.hasFocus()) return; - this.sendInput(this.getInput()); + private flushInput(): boolean { + if (this.inputSuppressed || document.hidden || !(this.pointerFocus || document.hasFocus())) return false; + if (this.sendsInLastSecond() >= MAX_SENDS_PER_SECOND) return false; + // While the connection is stalled the input stays here, current, instead of joining a queue + // of stale frames; presses wait in the input buffer and leave with the next frame that goes. + if ((this.socket?.bufferedAmount ?? 0) > BACKLOG_BYTES) return false; + return this.sendInput(this.getInput()); } private startOpponentPause(graceMs: number): void { @@ -307,6 +437,7 @@ export class NetworkController { if (this.listenersBound) { window.removeEventListener("blur", this.onInputLoss); window.removeEventListener("focus", this.onInputRegain); + window.removeEventListener("pointerdown", this.onPagePointer, true); document.removeEventListener("visibilitychange", this.onVisibilityChange); this.listenersBound = false; } diff --git a/web/hands/src/prediction.test.ts b/web/hands/src/prediction.test.ts new file mode 100644 index 00000000..f5f8aac1 --- /dev/null +++ b/web/hands/src/prediction.test.ts @@ -0,0 +1,290 @@ +import { cancelsRecovery, punchStaminaCost, punchTiming, recoveryCancelAge } from "./manifest"; +import { readFileSync } from "node:fs"; +import { resolve } from "node:path"; +import { SnapshotBuffer } from "./interpolation"; +import { attackTicksRemaining, canAffordPunch, constrainPrediction, EVASION_STAMINA, EVASION_TICKS, EvasionPrediction, fatigueFactor, MINIMUM_SEPARATION, MovementPrediction, movementLocked, predictedDefense, predictMovement, predictedPunchTiming, type HeldInput } from "./prediction"; +import { fighter, snapshot } from "./test/fixtures"; +import timingTable from "./test/punch-timing-table.json"; +import type { EngineSnapshot, FighterSnapshot, PunchClass } from "./types"; + +describe("local movement prediction", () => { + it("mirrors the authoritative fatigue factor", () => { + expect(fatigueFactor(1000, 0)).toBe(100); + expect(fatigueFactor(0, 0)).toBe(48); + expect(fatigueFactor(820, 350)).toBe(100 - 10 - 10); + }); + it("accelerates toward the held direction and never exceeds the speed cap", () => { + const still = { ...fighter("one"), conditioning: 1000 }; + const one = predictMovement(still, { moveX: 1000, moveY: 0, defense: "none" }, 1); + const four = predictMovement(still, { moveX: 1000, moveY: 0, defense: "none" }, 4); + expect(one.dx).toBeCloseTo(3.5, 5); + expect(one.dy).toBe(0); + expect(four.dx).toBeGreaterThan(one.dx); + expect(four.dx).toBeLessThanOrEqual(7 * 4); + const diagonal = predictMovement(still, { moveX: 1000, moveY: 1000, defense: "none" }, 4); + expect(Math.hypot(diagonal.dx, diagonal.dy)).toBeLessThanOrEqual(7 * 4 + 1e-9); + expect(diagonal.dx).toBeCloseTo(diagonal.dy, 9); + }); + it("slows while guarding and stops entirely while punching, stunned, or down", () => { + const still = { ...fighter("one"), conditioning: 1000 }; + const guarded = predictMovement(still, { moveX: 1000, moveY: 0, defense: "guard_high" }, 4); + const open = predictMovement(still, { moveX: 1000, moveY: 0, defense: "none" }, 4); + expect(guarded.dx).toBeLessThan(open.dx); + expect(guarded.dx).toBeGreaterThan(0); + for (const locked of [ + { ...still, action: "jab" as const }, + { ...still, stunned_ticks: 5 }, + { ...still, is_downed: true }, + { ...still, defense: "weave" as const }, + ]) { + expect(movementLocked(locked)).toBe(true); + expect(predictMovement(locked, { moveX: 1000, moveY: 0, defense: "none" }, 4)).toEqual({ dx: 0, dy: 0 }); + } + expect(movementLocked(still)).toBe(false); + }); + it("frees the fighter when the punch ends even though the snapshot still presents it", () => { + const still = { ...fighter("one"), conditioning: 1000 }; + const hook = { ...still, action: "hook" as const, action_start_tick: 100, action_startup_ticks: 7, action_active_ticks: 3, action_recovery_ticks: 12 }; + const held = { moveX: 1000, moveY: 0, defense: "none" as const }; + expect(attackTicksRemaining(hook, 110)).toBe(12); + expect(attackTicksRemaining(hook, 122)).toBe(0); + expect(attackTicksRemaining(hook, 130)).toBe(0); + expect(movementLocked(hook, 110)).toBe(true); + expect(movementLocked(hook, 122)).toBe(false); + expect(predictMovement(hook, held, 4, 110)).toEqual({ dx: 0, dy: 0 }); + expect(predictMovement(hook, held, 4, 130)).toEqual(predictMovement(still, held, 4)); + const leaving = predictMovement(hook, held, 4, 120); + expect(leaving.dx).toBeGreaterThan(0); + expect(leaving.dx).toBeCloseTo(predictMovement(still, held, 2).dx); + expect(predictMovement({ ...hook, stunned_ticks: 5 }, held, 4, 130)).toEqual({ dx: 0, dy: 0 }); + expect(predictMovement({ ...hook, queued_actions: 1 }, held, 4, 130)).toEqual({ dx: 0, dy: 0 }); + expect(movementLocked({ ...still, queued_actions: 1 }, 130)).toBe(true); + }); + + it("predicts the timing and cost the engine will use", () => { + const fresh = { ...fighter("one"), conditioning: 1000, stance: "orthodox" as const }; + const jab = { class: "jab" as const, hand: "left" as const, target: "head" as const, power: "normal" as const }; + expect(predictedPunchTiming(fresh, jab)).toMatchObject({ startup: 3, active: 2, recovery: 7 }); + expect(predictedPunchTiming(fresh, { ...jab, hand: "right" })).toMatchObject({ startup: 4, recovery: 7 }); + expect(predictedPunchTiming({ ...fresh, stance: "southpaw" }, { ...jab, hand: "right" })).toMatchObject({ startup: 3 }); + const tired = { ...fresh, conditioning: 640 }; + expect(fatigueFactor(tired.conditioning, 0)).toBe(80); + expect(predictedPunchTiming(tired, jab)).toMatchObject({ startup: 4, recovery: 8 }); + expect(predictedPunchTiming(tired, { ...jab, class: "hook", power: "power" })).toMatchObject({ startup: 11, active: 4, recovery: 18 }); + expect(punchStaminaCost("jab", "head", "normal")).toBe(42); + expect(punchStaminaCost("jab", "body", "normal")).toBe(46); + expect(punchStaminaCost("jab", "head", "power")).toBe(65); + expect(punchStaminaCost("jab", "body", "power")).toBe(71); + expect(canAffordPunch({ ...fresh, stamina: 42 }, jab)).toBe(true); + expect(canAffordPunch({ ...fresh, stamina: 41 }, jab)).toBe(false); + }); + + it("predicts the startup and recovery the engine gives every punch, its own cost taken off the conditioning first", () => { + const classes: Record = { j: "jab", s: "straight", h: "hook", u: "uppercut" }; + const mismatches: string[] = []; + for (const row of timingTable as string[]) { + const [key, conditioning, body, startup, recovery] = row.split(",") as [string, string, string, string, string]; + const base = fighter("one"); + const state: FighterSnapshot = { ...base, stance: "orthodox", conditioning: Number(conditioning), trauma: { ...base.trauma, body: Number(body) } }; + const timing = predictedPunchTiming(state, { class: classes[key[0]!]!, target: key[1] === "h" ? "head" : "body", power: key[2] === "p" ? "power" : "normal", hand: key[3] === "l" ? "left" : "right" }); + if (timing.startup !== Number(startup) || timing.recovery !== Number(recovery)) mismatches.push(`${row} -> ${timing.startup},${timing.recovery}`); + } + expect(timingTable.length).toBeGreaterThan(1000); + expect(mismatches).toEqual([]); + }); + + it("charges a punch thrown inside the combination window at the engine's discount", () => { + const afterJab = { ...fighter("one"), stance: "orthodox" as const, conditioning: 108, action: "jab" as const, action_start_tick: 100, action_startup_ticks: 3, action_active_ticks: 2, action_recovery_ticks: 7 }; + const straight = { class: "straight" as const, hand: "right" as const, target: "head" as const, power: "power" as const }; + expect(predictedPunchTiming(afterJab, straight, 110)).toMatchObject({ startup: 15, recovery: 25 }); + expect(predictedPunchTiming(afterJab, straight, 125)).toMatchObject({ startup: 16, recovery: 26 }); + expect(predictedPunchTiming(afterJab, { ...straight, class: "uppercut" }, 110)).toEqual(predictedPunchTiming(afterJab, { ...straight, class: "uppercut" }, 125)); + }); + + it("keeps the predicted fighter inside the ropes and corner pads and clear of the opponent", () => { + const held = { moveX: 1000, moveY: 0, defense: "none" as const }; + const onRope = { ...fighter("one", 462), conditioning: 1000 }; + const pressing = predictMovement(onRope, held, 4); + expect(pressing.dx).toBeGreaterThan(10); + expect(constrainPrediction(onRope, pressing, null).dx).toBeCloseTo(0, 9); + const corner = { ...fighter("one", 400), y: 330 }; + const intoCorner = constrainPrediction(corner, { dx: 30, dy: 30 }, null); + expect(Math.abs(corner.x + intoCorner.dx) + Math.abs(corner.y + intoCorner.dy)).toBeLessThanOrEqual(733 + 1e-9); + const facing = { ...fighter("one", 0), conditioning: 1000 }; + const opponent = fighter("two", MINIMUM_SEPARATION); + const closer = constrainPrediction(facing, predictMovement(facing, held, 4), opponent); + expect(Math.hypot(facing.x + closer.dx - opponent.x, facing.y + closer.dy - opponent.y)).toBeGreaterThanOrEqual(MINIMUM_SEPARATION - 1e-9); + const clinched = fighter("two", 60); + expect(constrainPrediction(facing, { dx: 0, dy: 0 }, clinched)).toEqual({ dx: 0, dy: 0 }); + const away = constrainPrediction(facing, { dx: -12, dy: 0 }, opponent); + expect(away.dx).toBeCloseTo(-12, 9); + }); + + it("carries existing velocity forward when the stick is released", () => { + const moving = { ...fighter("one"), conditioning: 1000, velocity_x: 6 }; + const coast = predictMovement(moving, { moveX: 0, moveY: 0, defense: "none" }, 3); + expect(coast.dx).toBeCloseTo(3 + 1.5 + 0.75, 5); + }); + + it("mirrors the engine's recovery cancel: a landed, chained, affordable follow-up on a defender who is not stunned", () => { + expect(recoveryCancelAge(punchTiming("straight", "head", "normal"))).toBe(6 + 2 + 5); + expect(recoveryCancelAge(punchTiming("hook", "head", "normal"))).toBe(7 + 3 + 6); + expect(recoveryCancelAge({ startup: 4, active: 2, recovery: 9 })).toBe(4 + 2 + 4); + const hook = { class: "hook" as const, target: "head" as const, power: "normal" as const }; + expect(cancelsRecovery("straight", true, hook, 900, false)).toBe(true); + expect(cancelsRecovery("straight", false, hook, 900, false)).toBe(false); + expect(cancelsRecovery("straight", true, hook, 900, true)).toBe(false); + expect(cancelsRecovery("straight", true, hook, punchStaminaCost("hook", "head", "normal") - 1, false)).toBe(false); + expect(cancelsRecovery("straight", true, { ...hook, class: "jab" }, 900, false)).toBe(false); + expect(cancelsRecovery("hook", true, { ...hook, class: "uppercut" }, 900, false)).toBe(true); + }); +}); + +describe("walking behind a round trip", () => { + const PRESS_MS = 500; + const RELEASE_MS = 1500; + const TICK_MS = 1000 / 30; + + /** + * Walks right from PRESS_MS to RELEASE_MS behind a round trip of `rtt` ms. The engine's integrator + * steps at 30 Hz on inputs flushed at 30 Hz, `phase` ms out of step with its ticks; its snapshots go + * into the client's real buffer, the client measures the input latency as the network does, and + * 60 fps frames draw the fighter where the prediction puts him. + */ + function walk(rtt: number, phase: number): { t: number; drawn: number; server: number }[] { + const buffer = new SnapshotBuffer(8, 30); + const prediction = new MovementPrediction(); + const heldAt = (t: number): HeldInput => ({ moveX: t >= PRESS_MS && t < RELEASE_MS ? 1000 : 0, moveY: 0, defense: "none" }); + const inputs: { arrives: number; held: HeldInput; sequence: number }[] = []; + const snapshots: { arrives: number; snapshot: EngineSnapshot; acknowledged: number }[] = []; + const sentAt = new Map(); + let x = -200; + let velocity = 0; + let tick = 0; + let applied = heldAt(0); + let acknowledged = -1; + let sequence = 0; + let latency: number | null = null; + let nextFlush = phase; + let nextTick = 0; + let lastFrame = -1; + const drawn: { t: number; drawn: number; server: number }[] = []; + for (let t = 0; t < 2600; t += 1) { + if (t >= nextFlush) { + sentAt.set(sequence, t); + inputs.push({ arrives: t + rtt / 2, held: heldAt(t), sequence }); + sequence += 1; + nextFlush += TICK_MS; + } + while (inputs.length > 0 && inputs[0]!.arrives <= t) { + const frame = inputs.shift()!; + applied = frame.held; + acknowledged = frame.sequence; + } + if (t >= nextTick) { + tick += 1; + velocity = Math.max(-7, Math.min(7, (velocity + (applied.moveX * 7) / 1000) / 2)); + x += velocity; + const base = snapshot(tick); + const self = { ...fighter("one", x), conditioning: 1000, velocity_x: velocity }; + snapshots.push({ arrives: t + rtt / 2, snapshot: { ...base, fighters: [self, { ...base.fighters[1], x: 400 }] }, acknowledged }); + nextTick += TICK_MS; + } + while (snapshots.length > 0 && snapshots[0]!.arrives <= t) { + const arrived = snapshots.shift()!; + buffer.push(arrived.snapshot, t); + const sent = sentAt.get(arrived.acknowledged); + if (sent !== undefined) latency = latency === null ? t - sent : latency * 0.8 + (t - sent) * 0.2; + } + const frame = Math.floor((t * 60) / 1000); + if (frame === lastFrame || buffer.latest() === null) continue; + lastFrame = frame; + const shown = buffer.sample(buffer.renderTick(t))!; + const self = shown.fighters[0]; + const lead = ((latency ?? rtt) / 1000) * 30 + buffer.interpolationDelayTicks; + const offset = constrainPrediction(self, prediction.update(self, heldAt(t), false, t, lead, shown.tick, 1 / 60, 30), shown.fighters[1]); + drawn.push({ t, drawn: self.x + offset.dx, server: x }); + } + return drawn; + } + + for (const rtt of [120, 220]) { + for (const phase of [0, 17]) { + it(`sets off on the press and stops on the release at ${rtt} ms round trip (flush ${phase} ms off the tick)`, () => { + const frames = walk(rtt, phase); + const at = (ms: number): number => frames.find((frame) => frame.t >= ms)!.drawn; + // Walking speed is 7 units a tick, 210 a second. + expect(at(PRESS_MS + 150) - at(PRESS_MS)).toBeGreaterThan(20); + const stallEnd = PRESS_MS + rtt + 100; + expect(((at(stallEnd) - at(PRESS_MS + 150)) / (stallEnd - PRESS_MS - 150)) * 1000).toBeGreaterThan(0.75 * 210); + const afterRelease = frames.filter((frame) => frame.t >= RELEASE_MS).map((frame) => frame.drawn); + expect(Math.max(...afterRelease) - at(RELEASE_MS)).toBeLessThan(8); + for (let index = 1; index < frames.length; index += 1) expect(frames[index - 1]!.drawn - frames[index]!.drawn).toBeLessThan(2.5); + expect(Math.abs(frames.at(-1)!.drawn - frames.at(-1)!.server)).toBeLessThan(0.5); + }); + } + } +}); + +describe("the player's own defence", () => { + const guarding: HeldInput = { moveX: 0, moveY: 0, defense: "guard_high" }; + const open = fighter("one"); + + it("shows the guard held now instead of the one in the delayed snapshot, unless the server overrides it", () => { + expect(predictedDefense(open, guarding, null)).toBe("guard_high"); + expect(predictedDefense({ ...open, defense: "guard_low" }, { ...guarding, defense: "none" }, null)).toBe("none"); + // A stun drops the guard, a taunt has none and a clinch keeps what it had. + expect(predictedDefense({ ...open, stunned_ticks: 12 }, guarding, "weave")).toBe("none"); + expect(predictedDefense({ ...open, taunt_ticks: 30 }, guarding, null)).toBe("none"); + expect(predictedDefense({ ...open, clinch_ticks: 30, defense: "guard_low" }, guarding, null)).toBe("guard_low"); + // An evasion the server is playing stands; one just pressed shows at once. + expect(predictedDefense({ ...open, defense: "slip_left" }, guarding, null)).toBe("slip_left"); + expect(predictedDefense(open, guarding, "weave")).toBe("weave"); + }); + + it("plays a slip from the press until the server's copy has played on screen, and keeps the feet still while the server does", () => { + const evasion = new EvasionPrediction(); + const tick = 1000 / 30; + evasion.press("slip_left", "c7", 1000, 6, 30); + expect(evasion.pose(1000)).toBe("slip_left"); + expect(evasion.holdsFeet(1000 + (EVASION_TICKS - 1) * tick, 30)).toBe(true); + expect(evasion.holdsFeet(1000 + EVASION_TICKS * tick, 30)).toBe(false); + // The server starts it and plays it out; the frame that carried it is long acknowledged by then. + evasion.acknowledge({ ...open, defense: "slip_left", last_input_sequence: 30 }, true, (id) => (id === "c7" ? 30 : null)); + evasion.acknowledge({ ...open, last_input_sequence: 34 }, true, (id) => (id === "c7" ? 30 : null)); + expect(evasion.pose(1000 + (6 + EVASION_TICKS - 1) * tick)).toBe("slip_left"); + expect(evasion.pose(1000 + (6 + EVASION_TICKS) * tick)).toBeNull(); + }); + + it("drops a slip the server turned down or a stun cut short", () => { + const sequenceOf = (id: string): number | null => (id === "c8" ? 41 : null); + const refused = new EvasionPrediction(); + refused.press("pull", "c8", 0, 4, 30); + // Snapshots before the frame went out say nothing about it. + refused.acknowledge({ ...open, last_input_sequence: 40 }, true, sequenceOf); + expect(refused.pose(10)).toBe("pull"); + // Not enough stamina there, or a punch pressed in the same tick took its place. + refused.acknowledge({ ...open, last_input_sequence: 41 }, true, sequenceOf); + expect(refused.pose(20)).toBeNull(); + const waiting = new EvasionPrediction(); + waiting.press("pull", "c8", 0, 4, 30); + waiting.acknowledge({ ...open, last_input_sequence: 41, queued_actions: 1 }, true, sequenceOf); + expect(waiting.pose(20)).toBe("pull"); + const stunned = new EvasionPrediction(); + stunned.press("weave", "c9", 0, 4, 30); + stunned.acknowledge({ ...open, defense: "weave" }, true, null); + stunned.acknowledge({ ...open, stunned_ticks: 20 }, true, null); + expect(stunned.pose(20)).toBeNull(); + const bell = new EvasionPrediction(); + bell.press("weave", "c9", 0, 4, 30); + bell.acknowledge(open, false, null); + expect(bell.pose(20)).toBeNull(); + }); + + it("matches the engine's evasion length and stamina gate", () => { + // Tests run from the client's package root, two levels below the repository's. + const engine = readFileSync(resolve(process.cwd(), "../../src/intelstream/hands/engine.py"), "utf8"); + expect(engine).toContain(`EVASION_TICKS: Final = ${EVASION_TICKS}`); + expect(engine).toContain(`if fighter.stamina < ${EVASION_STAMINA}:`); + }); +}); diff --git a/web/hands/src/prediction.ts b/web/hands/src/prediction.ts new file mode 100644 index 00000000..77b5c68c --- /dev/null +++ b/web/hands/src/prediction.ts @@ -0,0 +1,337 @@ +import { comboChain, comboWindow, FIGHTER_RADIUS, punchStaminaCost, punchTiming, RING_CORNER_REACH, RING_HALF_HEIGHT, RING_HALF_WIDTH, type PunchTiming } from "./manifest"; +import type { DefensivePose, FighterSnapshot, Hand, HeldDefense, MovementKind, Power, PunchClass, Target } from "./types"; + +export interface HeldInput { + readonly moveX: number; + readonly moveY: number; + readonly defense: HeldDefense; +} + +export interface PredictedOffset { + readonly dx: number; + readonly dy: number; +} + +const MAX_SPEED = 7; +const GUARD_SPEED_PERCENT = 70; +const MAX_CONDITIONING = 1000; +export const MINIMUM_SEPARATION = FIGHTER_RADIUS * 2; + +export function fatigueFactor(conditioning: number, bodyTrauma: number): number { + return Math.max(48, 100 - Math.floor((MAX_CONDITIONING - conditioning) / 18) - Math.floor(bodyTrauma / 35)); +} + +export interface PunchIntent { + readonly class: PunchClass; + readonly hand: Hand; + readonly target: Target; + readonly power: Power; +} + +/** Whether a punch started at `tick` follows the fighter's last one inside its combination window. */ +export function inComboWindow(fighter: FighterSnapshot, punch: PunchIntent, tick: number): boolean { + if (fighter.action === null || !comboChain(fighter.action, punch.class)) return false; + const total = fighter.action_startup_ticks + fighter.action_active_ticks + fighter.action_recovery_ticks; + return tick - fighter.action_start_tick < total + comboWindow(fighter.action); +} + +/** + * The timing the engine will give this punch if it starts at `tick`: slower for a tired fighter, a + * tick quicker for the lead-hand jab. The engine takes the punch's own cost off the conditioning + * before it measures fatigue, at the combination discount inside the window. + */ +export function predictedPunchTiming(fighter: FighterSnapshot, punch: PunchIntent, tick?: number): PunchTiming { + const base = punchTiming(punch.class, punch.target, punch.power); + const fullCost = punchStaminaCost(punch.class, punch.target, punch.power); + const cost = tick !== undefined && inComboWindow(fighter, punch, tick) ? Math.max(1, Math.floor((fullCost * 90) / 100)) : fullCost; + const conditioning = Math.max(0, fighter.conditioning - Math.max(1, Math.floor(cost / 12))); + const speed = fatigueFactor(conditioning, fighter.trauma.body); + const lead = fighter.stance === "orthodox" ? "left" : "right"; + const quick = punch.class === "jab" && punch.hand === lead ? 1 : 0; + return { + ...base, + startup: Math.max(2, Math.floor((base.startup * 100) / speed) - quick), + recovery: Math.max(4, Math.floor((base.recovery * 100) / speed)), + }; +} + +/** False when the fighter cannot pay the punch's full cost: the engine checks it before any combo discount. */ +export function canAffordPunch(fighter: FighterSnapshot, punch: PunchIntent): boolean { + return fighter.stamina >= punchStaminaCost(punch.class, punch.target, punch.power); +} + +/** + * Ticks until the fighter's punch ends, as of snapshot `tick`. The engine keeps a finished punch in + * snapshots for a while so clients can present it, so `action` alone does not mean the fighter is + * still committed to it. + */ +export function attackTicksRemaining(fighter: FighterSnapshot, tick: number): number { + if (fighter.action === null) return 0; + const end = fighter.action_start_tick + fighter.action_startup_ticks + fighter.action_active_ticks + fighter.action_recovery_ticks; + return Math.max(0, end - tick); +} + +export function movementLocked(fighter: FighterSnapshot, tick?: number): boolean { + return (tick === undefined ? fighter.action !== null : attackTicksRemaining(fighter, tick) > 0) + || stateLocked(fighter); +} + +function stateLocked(fighter: FighterSnapshot): boolean { + // A queued punch starts the tick the current one ends, so the fighter is never free in between. + return fighter.queued_actions > 0 + || fighter.is_downed + || fighter.stunned_ticks > 0 + || fighter.clinch_ticks > 0 + || fighter.clinch_startup_ticks > 0 + || fighter.taunt_ticks > 0 + || fighter.is_foul_recovery_target + || ["slip_left", "slip_right", "weave", "pull"].includes(fighter.defense); +} + +/** What the engine walks toward for a held input: the velocity it blends halfway to each tick, and its speed cap. */ +export interface MovementIntent { + readonly x: number; + readonly y: number; + readonly speed: number; +} + +/** The fatigue- and guard-scaled walking intent of `held`, as the engine's `_move_fighter` works it out, written to `out`. */ +export function movementIntent(fighter: FighterSnapshot, held: HeldInput, out: { x: number; y: number; speed: number } = { x: 0, y: 0, speed: 0 }): MovementIntent { + let speed = Math.max(2, Math.floor((MAX_SPEED * fatigueFactor(fighter.conditioning, fighter.trauma.body)) / 100)); + if (held.defense === "guard_high" || held.defense === "guard_low") speed = Math.max(2, Math.floor((speed * GUARD_SPEED_PERCENT) / 100)); + const magnitude = Math.hypot(held.moveX, held.moveY); + const scale = magnitude > 1000 ? 1000 / magnitude : 1; + out.x = (held.moveX * scale * speed) / 1000; + out.y = (held.moveY * scale * speed) / 1000; + out.speed = speed; + return out; +} + +/** + * Mirrors the authoritative movement integrator (velocity blends halfway to + * the held direction each tick, capped at the fatigue-scaled speed) so the + * viewer's own fighter can be shown `ticks` ahead of the delayed snapshot, + * walking toward `intent(step)` on each tick. With the snapshot `tick`, a + * punch only holds the fighter for the ticks it has left, so stepping out of + * a punch is predicted as soon as it ends. + */ +export function replayMovement(fighter: FighterSnapshot, intent: (step: number) => MovementIntent, ticks: number, tick?: number): PredictedOffset { + if (ticks <= 0 || stateLocked(fighter)) return { dx: 0, dy: 0 }; + const committed = tick === undefined ? (fighter.action !== null ? Infinity : 0) : attackTicksRemaining(fighter, tick); + if (committed >= ticks) return { dx: 0, dy: 0 }; + let vx = fighter.velocity_x; + let vy = fighter.velocity_y; + let dx = 0; + let dy = 0; + const whole = Math.floor(ticks); + const fraction = ticks - whole; + for (let step = 0; step < whole; step += 1) { + const free = step >= committed; + const want = intent(step); + vx = (vx + (free ? want.x : 0)) / 2; + vy = (vy + (free ? want.y : 0)) / 2; + const length = Math.hypot(vx, vy); + if (length > want.speed) { + vx = (vx / length) * want.speed; + vy = (vy / length) * want.speed; + } + dx += vx; + dy += vy; + } + if (fraction > 0) { + const free = whole >= committed; + const want = intent(whole); + dx += ((vx + (free ? want.x : 0)) / 2) * fraction; + dy += ((vy + (free ? want.y : 0)) / 2) * fraction; + } + return { dx, dy }; +} + +/** `replayMovement` with the same input held on every tick. */ +export function predictMovement(fighter: FighterSnapshot, held: HeldInput, ticks: number, tick?: number): PredictedOffset { + const intent = movementIntent(fighter, held); + return replayMovement(fighter, () => intent, ticks, tick); +} + +/** Held input kept for replay, longer than any lead the renderer works with. */ +const HELD_HISTORY_MS = 1000; +/** The prediction offset may move at most this many times the top walking speed: real motion is never slowed, a correction slides. */ +const OFFSET_SPEED_LIMIT = 2.5; +/** Rate at which the lead eases to a new estimate of the latency or the interpolation delay. */ +const HORIZON_EASE_RATE = 4; + +/** + * Keeps the viewer's own fighter ahead of the delayed snapshot on screen by the input latency plus + * the interpolation delay. That far ahead the server is still applying inputs held in the past, so + * rather than assume the current one was held all along, each tick ahead replays the input the + * server applies at that tick: the one a flush sent a lead earlier. The fighter then sets off on the + * press and stops on the release instead of stepping, stalling and overshooting. + */ +export class MovementPrediction { + private readonly history: { readonly at: number; readonly held: HeldInput }[] = []; + private readonly offset = { dx: 0, dy: 0 }; + private readonly mean = { x: 0, y: 0, speed: 0 }; + private readonly sample = { x: 0, y: 0, speed: 0 }; + private horizon: number | null = null; + + /** + * The offset to draw `fighter`, as shown, by this frame. `held` is the input held now; with + * `holdFeet` (the viewer's own punch playing) the server will not walk him for it. `fighter` is + * null outside the fight, where the offset eases away. + */ + update(fighter: FighterSnapshot | null, held: HeldInput, holdFeet: boolean, nowMs: number, horizonTicks: number, tick: number, dt: number, tickRate: number): PredictedOffset { + this.history.push({ at: nowMs, held: holdFeet ? { ...held, moveX: 0, moveY: 0 } : held }); + while (this.history.length > 2 && this.history[1]!.at < nowMs - HELD_HISTORY_MS) this.history.shift(); + this.horizon = this.horizon === null ? horizonTicks : this.horizon + (horizonTicks - this.horizon) * (1 - Math.exp(-HORIZON_EASE_RATE * dt)); + let target: PredictedOffset = { dx: 0, dy: 0 }; + if (fighter !== null) { + const tickMs = 1000 / tickRate; + const lead = this.horizon; + // The input applied `step` ticks ahead left with a flush around `lead - 1 - step` ticks ago. + target = replayMovement(fighter, (step) => this.meanIntent(fighter, nowMs - (lead - 1 - step) * tickMs, tickMs), lead, tick); + } + const limit = OFFSET_SPEED_LIMIT * MAX_SPEED * tickRate * dt; + const changeX = target.dx - this.offset.dx; + const changeY = target.dy - this.offset.dy; + const change = Math.hypot(changeX, changeY); + const scale = change > limit ? limit / change : 1; + this.offset.dx += changeX * scale; + this.offset.dy += changeY * scale; + return { dx: this.offset.dx, dy: this.offset.dy }; + } + + /** The walking intent averaged over the `width` ms around `centre`, the input held after now being the current one. */ + private meanIntent(fighter: FighterSnapshot, centre: number, width: number): MovementIntent { + const from = centre - width / 2; + const to = centre + width / 2; + const mean = this.mean; + mean.x = 0; + mean.y = 0; + mean.speed = 0; + for (let index = 0; index < this.history.length; index += 1) { + const start = index === 0 ? from : Math.max(from, this.history[index]!.at); + const end = Math.min(to, this.history[index + 1]?.at ?? Infinity); + if (end <= start) continue; + const intent = movementIntent(fighter, this.history[index]!.held, this.sample); + const weight = (end - start) / width; + mean.x += intent.x * weight; + mean.y += intent.y * weight; + mean.speed += intent.speed * weight; + } + return mean; + } +} + +/** The nearest point inside the ropes and corner pads, the engine's ring projection without its integer rounding. */ +export function ringPoint(x: number, y: number): { x: number; y: number } { + const limitX = RING_HALF_WIDTH - FIGHTER_RADIUS; + const limitY = RING_HALF_HEIGHT - FIGHTER_RADIUS; + const signX = x < 0 ? -1 : 1; + const signY = y < 0 ? -1 : 1; + const reachX = Math.abs(x); + const reachY = Math.abs(y); + const insideX = Math.min(reachX, limitX); + const insideY = Math.min(reachY, limitY); + if (insideX + insideY <= RING_CORNER_REACH) return { x: signX * insideX, y: signY * insideY }; + const excess = reachX + reachY - RING_CORNER_REACH; + const cutX = reachX - excess / 2; + const cutY = reachY - excess / 2; + if (cutY > limitY) return { x: signX * (RING_CORNER_REACH - limitY), y: signY * limitY }; + if (cutX > limitX) return { x: signX * limitX, y: signY * (RING_CORNER_REACH - limitX) }; + return { x: signX * cutX, y: signY * cutY }; +} + +/** + * Keeps a predicted step where the engine can put the fighter: inside the ropes and corner pads, and + * no nearer the opponent than the engine's minimum separation (or than they already stand, in a clinch). + */ +export function constrainPrediction(fighter: { readonly x: number; readonly y: number }, offset: PredictedOffset, opponent: { readonly x: number; readonly y: number } | null): PredictedOffset { + let x = fighter.x + offset.dx; + let y = fighter.y + offset.dy; + if (opponent !== null) { + const limit = Math.min(MINIMUM_SEPARATION, Math.hypot(fighter.x - opponent.x, fighter.y - opponent.y)); + const awayX = x - opponent.x; + const awayY = y - opponent.y; + const apart = Math.hypot(awayX, awayY); + if (apart < limit) { + if (apart > 1e-9) { + x = opponent.x + (awayX / apart) * limit; + y = opponent.y + (awayY / apart) * limit; + } else { + x = fighter.x; + y = fighter.y; + } + } + } + const inside = ringPoint(x, y); + return { dx: inside.x - fighter.x, dy: inside.y - fighter.y }; +} + +/** Ticks a slip, weave or pull lasts on the server (the engine's EVASION_TICKS). */ +export const EVASION_TICKS = 10; +/** Stamina the server asks of a slip, weave or pull before it starts one. */ +export const EVASION_STAMINA = 25; + +export type EvasionKind = "slip_left" | "slip_right" | "weave" | "pull"; + +export function isEvasion(kind: MovementKind | "punch" | "foul" | DefensivePose): kind is EvasionKind { + return kind === "slip_left" || kind === "slip_right" || kind === "weave" || kind === "pull"; +} + +/** + * The defence the viewer's own fighter is shown in during the fight: the guard held now, ahead of the + * snapshot like his feet, or the slip, weave or pull just pressed. The server's own defence stands + * while it overrides the held guard: none while stunned or taunting, unchanged in a clinch, and an + * evasion it is playing. + */ +export function predictedDefense(server: FighterSnapshot, held: HeldInput, evasion: EvasionKind | null): DefensivePose { + if (server.stunned_ticks > 0 || server.taunt_ticks > 0 || server.clinch_ticks > 0) return server.defense; + if (evasion !== null) return evasion; + if (isEvasion(server.defense)) return server.defense; + return held.defense; +} + +/** + * A slip, weave or pull the viewer pressed, shown on the press the way his punches are. It lasts the + * lead plus its own ticks, so it ends as the server's copy does on screen, unless the server turns it + * down: once a snapshot has the frame that carried it, the fighter is evading or never will for it, and + * a stun, a clinch or the end of the fight phase clears it. + */ +export class EvasionPrediction { + private kind: EvasionKind | null = null; + private id = ""; + private pressedAt = 0; + private until = 0; + private sequence: number | null = null; + private started = false; + + press(kind: EvasionKind, id: string, nowMs: number, leadTicks: number, tickRate: number): void { + this.kind = kind; + this.id = id; + this.pressedAt = nowMs; + this.until = nowMs + ((Math.max(0, leadTicks) + EVASION_TICKS) * 1000) / tickRate; + this.sequence = null; + this.started = false; + } + + /** Squares the pressed evasion with the newest snapshot; `sequenceOf` gives the frame that carried a press once it has gone out. */ + acknowledge(server: FighterSnapshot, fighting: boolean, sequenceOf: ((actionId: string) => number | null) | null): void { + if (this.kind === null) return; + this.sequence ??= sequenceOf?.(this.id) ?? null; + if (server.defense === this.kind) this.started = true; + const cutOff = !fighting || server.stunned_ticks > 0 || server.clinch_ticks > 0; + const refused = !this.started && this.sequence !== null && server.last_input_sequence >= this.sequence && server.queued_actions === 0; + if (cutOff || refused) this.kind = null; + } + + /** The evasion to show at `nowMs`, or null. */ + pose(nowMs: number): EvasionKind | null { + if (this.kind !== null && nowMs >= this.until) this.kind = null; + return this.kind; + } + + /** True while the server, evading, keeps the fighter's feet still for inputs sent now. */ + holdsFeet(nowMs: number, tickRate: number): boolean { + return this.kind !== null && nowMs < this.pressedAt + (EVASION_TICKS * 1000) / tickRate; + } +} diff --git a/web/hands/src/protocol.test.ts b/web/hands/src/protocol.test.ts index e6b6a172..5a8816fe 100644 --- a/web/hands/src/protocol.test.ts +++ b/web/hands/src/protocol.test.ts @@ -1,37 +1,37 @@ import { decodeBootstrap, decodeServerFrame, decodeToken, encodeInput, ProtocolError } from "./protocol"; import { envelope, publicPlayers, snapshot } from "./test/fixtures"; -describe("strict protocol v2", () => { +describe("strict protocol v3", () => { it("decodes every control envelope and a populated final", () => { const messages = [ - { version: 2, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [publicPlayers[0]], server_tick: 0, next_sequence: 0, reconnect_ticket: "secret-ticket" }, - { version: 2, type: "ticket", reconnect_ticket: "refreshed-ticket", refresh_id: "refresh-identifier" }, - { version: 2, type: "waiting", open_seats: 1 }, { version: 2, type: "ready", players: publicPlayers }, - { version: 2, type: "paused", player_id: "two", grace_ms: 20000 }, { version: 2, type: "resumed", player_id: "two" }, - { version: 2, type: "error", code: "room_full" }, envelope(), - { version: 2, type: "final", match_id: "m", winner_id: "one", method: "decision", round: 12, scorecards: [{ judge: "A", player_one: [10], player_two: [9] }, { judge: "B", player_one: [9], player_two: [10] }, { judge: "C", player_one: [10], player_two: [9] }], ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }, + { version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [publicPlayers[0]], server_tick: 0, next_sequence: 0, reconnect_ticket: "secret-ticket" }, + { version: 3, type: "ticket", reconnect_ticket: "refreshed-ticket", refresh_id: "refresh-identifier" }, + { version: 3, type: "waiting", open_seats: 1 }, { version: 3, type: "ready", players: publicPlayers }, + { version: 3, type: "paused", player_id: "two", grace_ms: 20000 }, { version: 3, type: "resumed", player_id: "two" }, + { version: 3, type: "error", code: "room_full" }, envelope(), + { version: 3, type: "final", match_id: "m", winner_id: "one", method: "decision", round: 12, scorecards: [{ judge: "A", player_one: [10], player_two: [9] }, { judge: "B", player_one: [9], player_two: [10] }, { judge: "C", player_one: [10], player_two: [9] }], ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }, ]; expect(messages.map((message) => decodeServerFrame(JSON.stringify(message)).type)).toEqual(["welcome", "ticket", "waiting", "ready", "paused", "resumed", "error", "snapshot", "final"]); }); it("decodes spectators without granting fighter fields", () => { - const spectator = { version: 2, type: "welcome", role: "spectator", player_id: "viewer", players: publicPlayers, server_tick: 40, reconnect_ticket: "spectator-ticket" }; + const spectator = { version: 3, type: "welcome", role: "spectator", player_id: "viewer", players: publicPlayers, server_tick: 40, reconnect_ticket: "spectator-ticket" }; expect(decodeServerFrame(JSON.stringify(spectator))).toEqual(spectator); expect(() => decodeServerFrame(JSON.stringify({ ...spectator, seat: 1 }))).toThrow(ProtocolError); expect(() => decodeServerFrame(JSON.stringify({ ...spectator, player_id: "one" }))).toThrow(/spectator/u); - const fighterWithoutRole = { version: 2, type: "welcome", player_id: "one", seat: 1, rating: 1500, players: [publicPlayers[0]], server_tick: 0, next_sequence: 0 }; + const fighterWithoutRole = { version: 3, type: "welcome", player_id: "one", seat: 1, rating: 1500, players: [publicPlayers[0]], server_tick: 0, next_sequence: 0 }; expect(() => decodeServerFrame(JSON.stringify(fighterWithoutRole))).toThrow(ProtocolError); }); it("decodes a fully populated embedded result", () => { const value = snapshot(); value.events as unknown as unknown[]; const populated = { ...value, result: { match_id: "m", activity_instance_id: "i", guild_id: "g", player_one_id: "one", player_two_id: "two", winner_id: null, finish_method: "draw", round_number: 15, tick: 10, scorecards: [{ judge: "A", player_one: [], player_two: [] }, { judge: "B", player_one: [], player_two: [] }, { judge: "C", player_one: [], player_two: [] }], player_one_knockdowns: 1, player_two_knockdowns: 1, player_one_damage: 200, player_two_damage: 210 } }; - expect(decodeServerFrame(JSON.stringify({ version: 2, type: "snapshot", payload: populated })).type).toBe("snapshot"); + expect(decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: populated })).type).toBe("snapshot"); }); it.each([ - ["missing", { version: 2, type: "waiting" }], ["extra", { version: 2, type: "waiting", open_seats: 1, winner_id: "forged" }], - ["version", { version: 3, type: "waiting", open_seats: 1 }], ["nonfinite", "{\"version\":1,\"type\":\"paused\",\"player_id\":\"one\",\"grace_ms\":NaN}"], + ["missing", { version: 3, type: "waiting" }], ["extra", { version: 3, type: "waiting", open_seats: 1, winner_id: "forged" }], + ["version", { version: 4, type: "waiting", open_seats: 1 }], ["nonfinite", "{\"version\":1,\"type\":\"paused\",\"player_id\":\"one\",\"grace_ms\":NaN}"], ])("rejects %s fields", (_name, value) => expect(() => decodeServerFrame(typeof value === "string" ? value : JSON.stringify(value))).toThrow(ProtocolError)); it("rejects duplicate, oversized, and same-player snapshots", () => { - expect(() => decodeServerFrame('{"version":2,"type":"waiting","type":"ready","open_seats":1}')).toThrow(/duplicate/u); + expect(() => decodeServerFrame('{"version":3,"type":"waiting","type":"ready","open_seats":1}')).toThrow(/duplicate/u); expect(() => decodeServerFrame(" ".repeat(65_537))).toThrow(/large/u); const bad = structuredClone(envelope()) as { payload: { fighters: { player_id: string }[] } }; bad.payload.fighters[1]!.player_id = "one"; expect(() => decodeServerFrame(JSON.stringify(bad))).toThrow(/distinct/u); @@ -39,33 +39,33 @@ describe("strict protocol v2", () => { it("encodes only authorized fields, clamps movement, and caps actions", () => { const forged = { kind: "punch", hand: "left", class: "jab", target: "head", power: "normal", winner_id: "one" } as const; const encoded = JSON.parse(encodeInput(3, 9, { moveX: Infinity, moveY: -9000, defense: "guard_high", actions: [forged, forged, forged, forged, forged] })) as Record; - expect(encoded).toMatchObject({ version: 2, type: "input", sequence: 3, client_tick: 9, move: { x: 0, y: -1000 } }); expect(encoded).not.toHaveProperty("winner_id"); expect((encoded.actions as unknown[])).toHaveLength(4); expect((encoded.actions as Record[])[0]).not.toHaveProperty("winner_id"); + expect(encoded).toMatchObject({ version: 3, type: "input", sequence: 3, client_tick: 9, move: { x: 0, y: -1000 } }); expect(encoded).not.toHaveProperty("winner_id"); expect((encoded.actions as unknown[])).toHaveLength(4); expect((encoded.actions as Record[])[0]).not.toHaveProperty("winner_id"); }); it("accepts authoritative rounds 13–15 with exactly three complete judge cards", () => { const rounds = Array.from({ length: 15 }, () => 10); const cards = ["A", "B", "C"].map((judge) => ({ judge, player_one: rounds, player_two: rounds.map(() => 9) })); - const final = { version: 2, type: "final", match_id: "m", winner_id: "one", method: "decision", round: 15, scorecards: cards, ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }; + const final = { version: 3, type: "final", match_id: "m", winner_id: "one", method: "decision", round: 15, scorecards: cards, ratings: { one: { before: 1500, after: 1516 }, two: { before: 1500, after: 1484 } } }; expect(decodeServerFrame(JSON.stringify(final))).toMatchObject({ type: "final", round: 15 }); const atThirteen = { ...snapshot(), round_number: 13 }; - expect(decodeServerFrame(JSON.stringify({ version: 2, type: "snapshot", payload: atThirteen }))).toMatchObject({ type: "snapshot", payload: { round_number: 13 } }); + expect(decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: atThirteen }))).toMatchObject({ type: "snapshot", payload: { round_number: 13 } }); }); it.each([ { winner_id: null, method: "decision" }, { winner_id: "one", method: "draw" }, ])("rejects incoherent final winner/method combinations", ({ winner_id, method }) => { const cards = ["A", "B", "C"].map((judge) => ({ judge, player_one: [], player_two: [] })); - expect(() => decodeServerFrame(JSON.stringify({ version: 2, type: "final", match_id: "m", winner_id, method, round: 1, scorecards: cards, ratings: { one: { before: 1, after: 1 }, two: { before: 1, after: 1 } } }))).toThrow(/coherent/u); + expect(() => decodeServerFrame(JSON.stringify({ version: 3, type: "final", match_id: "m", winner_id, method, round: 1, scorecards: cards, ratings: { one: { before: 1, after: 1 }, two: { before: 1, after: 1 } } }))).toThrow(/coherent/u); }); it("accepts exact fighter-domain boundaries and the private get-up sentinel", () => { const base = snapshot(); - const lower = { ...base.fighters[0], x: -462, y: -292, facing: -1, velocity_x: -7, velocity_y: -7, maximum_stamina: 330, stamina: 0, poise: 0, get_up_required: 45 }; - const upper = { ...base.fighters[1], x: 462, y: 292, facing: 1, velocity_x: 7, velocity_y: 7, maximum_stamina: 1000, stamina: 1000, poise: 600, get_up_required: 169 }; - expect(decodeServerFrame(JSON.stringify({ version: 2, type: "snapshot", payload: { ...base, fighters: [lower, upper] } }))).toMatchObject({ type: "snapshot", payload: { fighters: [{ get_up_required: 45 }, { get_up_required: 169 }] } }); + const lower = { ...base.fighters[0], x: -462, y: -462, facing: -1, velocity_x: -7, velocity_y: -7, maximum_stamina: 330, stamina: 0, poise: 0, get_up_required: 45 }; + const upper = { ...base.fighters[1], x: 462, y: 462, facing: 1, velocity_x: 7, velocity_y: 7, maximum_stamina: 1000, stamina: 1000, poise: 600, get_up_required: 169 }; + expect(decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [lower, upper] } }))).toMatchObject({ type: "snapshot", payload: { fighters: [{ get_up_required: 45 }, { get_up_required: 169 }] } }); const redactedOpponent = { ...upper, get_up_required: 0 }; - expect(decodeServerFrame(JSON.stringify({ version: 2, type: "snapshot", payload: { ...base, fighters: [lower, redactedOpponent] } }))).toMatchObject({ payload: { fighters: [{ get_up_required: 45 }, { get_up_required: 0 }] } }); + expect(decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [lower, redactedOpponent] } }))).toMatchObject({ payload: { fighters: [{ get_up_required: 45 }, { get_up_required: 0 }] } }); }); it.each([ - ["x below", "x", -463], ["x above", "x", 463], ["y below", "y", -293], ["y above", "y", 293], + ["x below", "x", -463], ["x above", "x", 463], ["y below", "y", -463], ["y above", "y", 463], ["zero facing", "facing", 0], ["velocity x below", "velocity_x", -8], ["velocity x above", "velocity_x", 8], ["velocity y below", "velocity_y", -8], ["velocity y above", "velocity_y", 8], ["maximum stamina below", "maximum_stamina", 329], ["maximum stamina above", "maximum_stamina", 1001], ["poise below", "poise", -1], ["poise above", "poise", 601], @@ -73,23 +73,37 @@ describe("strict protocol v2", () => { ])("rejects %s fighter output", (_name, field, value) => { const base = snapshot(); const changed = { ...base.fighters[0], [field]: value }; - expect(() => decodeServerFrame(JSON.stringify({ version: 2, type: "snapshot", payload: { ...base, fighters: [changed, base.fighters[1]] } }))).toThrow(ProtocolError); + expect(() => decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [changed, base.fighters[1]] } }))).toThrow(ProtocolError); }); it("rejects stamina above the decoded maximum", () => { const base = snapshot(); const exhausted = { ...base.fighters[0], maximum_stamina: 330, stamina: 331 }; - expect(() => decodeServerFrame(JSON.stringify({ version: 2, type: "snapshot", payload: { ...base, fighters: [exhausted, base.fighters[1]] } }))).toThrow(ProtocolError); + expect(() => decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [exhausted, base.fighters[1]] } }))).toThrow(ProtocolError); }); it("rejects out-of-authority event and fighter bounds", () => { const base = snapshot(); - const badEvent = { version: 2, type: "snapshot", payload: { ...base, events: [{ event_id: 1, tick: 1, kind: "x".repeat(33), actor_id: null, target_id: null, amount: 10_001, detail: "", blood: 101, direction: 2 }] } }; + const badEvent = { version: 3, type: "snapshot", payload: { ...base, events: [{ event_id: 1, tick: 1, kind: "x".repeat(33), actor_id: null, target_id: null, amount: 10_001, detail: "", blood: 101, direction: 2 }] } }; expect(() => decodeServerFrame(JSON.stringify(badEvent))).toThrow(); - const badQueue = { version: 2, type: "snapshot", payload: { ...base, fighters: [{ ...base.fighters[0], queued_actions: 2 }, base.fighters[1]] } }; + const badQueue = { version: 3, type: "snapshot", payload: { ...base, fighters: [{ ...base.fighters[0], queued_actions: 2 }, base.fighters[1]] } }; expect(() => decodeServerFrame(JSON.stringify(badQueue))).toThrow(); }); it("strictly decodes same-origin API payload schemas", () => { - expect(decodeBootstrap({ client_id: "123", state: "s", protocol: 2, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }).simulation.tick_rate).toBe(30); + expect(decodeBootstrap({ client_id: "123", state: "s", protocol: 3, simulation: { tick_rate: 30, ring_half_width: 6000, ring_half_height: 4000 } }).simulation.tick_rate).toBe(30); expect(decodeToken({ access_token: "a", ticket: "t", player: { id: "one", name: "One", avatar: null, rating: 1500 } }).player.id).toBe("one"); expect(() => decodeToken({ access_token: "a", ticket: "t", outcome: "forged", player: { id: "one", name: "One", avatar: null, rating: 1500 } })).toThrow(); }); }); + +describe("facing vector and input acknowledgement", () => { + it("rejects a zero facing vector and negative acknowledgements below the sentinel", () => { + const base = snapshot(); + const zero = { ...base.fighters[0], facing_x: 0, facing_y: 0 }; + expect(() => decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [zero, base.fighters[1]] } }))).toThrow(/facing vector/u); + const oversized = { ...base.fighters[0], facing_x: 1001 }; + expect(() => decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [oversized, base.fighters[1]] } }))).toThrow(ProtocolError); + const unacknowledged = { ...base.fighters[0], last_input_sequence: -2 }; + expect(() => decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [unacknowledged, base.fighters[1]] } }))).toThrow(ProtocolError); + const turned = { ...base.fighters[0], facing_x: 0, facing_y: -1000, last_input_sequence: 41 }; + expect(decodeServerFrame(JSON.stringify({ version: 3, type: "snapshot", payload: { ...base, fighters: [turned, base.fighters[1]] } }))).toMatchObject({ payload: { fighters: [{ facing_y: -1000, last_input_sequence: 41 }, { facing_x: -1000 }] } }); + }); +}); diff --git a/web/hands/src/protocol.ts b/web/hands/src/protocol.ts index b9234ece..a1f73c09 100644 --- a/web/hands/src/protocol.ts +++ b/web/hands/src/protocol.ts @@ -114,14 +114,14 @@ function trauma(value: unknown): TraumaSnapshot { function fighter(value: unknown): FighterSnapshot { const o = object(value, "fighter"); exact(o, [ - "player_id", "x", "y", "facing", "velocity_x", "velocity_y", "stance", "defense", + "player_id", "x", "y", "facing", "facing_x", "facing_y", "velocity_x", "velocity_y", "stance", "defense", "stamina", "maximum_stamina", "conditioning", "guard", "poise", "trauma", "knockdowns", "warnings", "deductions", "stunned_ticks", "is_downed", "action", "action_hand", "action_target", "action_power", "action_id", "action_key", "action_start_tick", "action_startup_ticks", "action_active_ticks", "action_recovery_ticks", "action_contact_tick", "queued_actions", "clinch_startup_ticks", "clinch_ticks", "is_foul_recovery_target", "taunt_ticks", "get_up_prompt", "get_up_meter", "get_up_required", "get_up_count", - "get_up_window_start_tick", "get_up_window_end_tick", + "get_up_window_start_tick", "get_up_window_end_tick", "last_input_sequence", ]); const action = o.action === null ? null : oneOf(o.action, classes, "action"); const actionHand = o.action_hand === null ? null : oneOf(o.action_hand, hands, "action hand"); @@ -138,10 +138,13 @@ function fighter(value: unknown): FighterSnapshot { const getUpRequired = integer(o.get_up_required, "get_up_required", 0, 169); const facing = integer(o.facing, "facing", -1, 1); if (facing === 0) throw new ProtocolError("invalid facing"); + const facingX = integer(o.facing_x, "facing_x", -1000, 1000); + const facingY = integer(o.facing_y, "facing_y", -1000, 1000); + if (facingX === 0 && facingY === 0) throw new ProtocolError("invalid facing vector"); if (getUpRequired !== 0 && getUpRequired < 34) throw new ProtocolError("invalid get-up requirement"); return { - player_id: string(o.player_id, "player_id"), x: integer(o.x, "x", -462, 462), y: integer(o.y, "y", -292, 292), - facing, velocity_x: integer(o.velocity_x, "velocity_x", -7, 7), velocity_y: integer(o.velocity_y, "velocity_y", -7, 7), + player_id: string(o.player_id, "player_id"), x: integer(o.x, "x", -462, 462), y: integer(o.y, "y", -462, 462), + facing, facing_x: facingX, facing_y: facingY, velocity_x: integer(o.velocity_x, "velocity_x", -7, 7), velocity_y: integer(o.velocity_y, "velocity_y", -7, 7), stance: oneOf(o.stance, stances, "stance"), defense: oneOf(o.defense, defenses, "defense"), stamina, maximum_stamina: maximumStamina, conditioning: integer(o.conditioning, "conditioning", 0, 1000), guard: integer(o.guard, "guard", 0, 700), poise: integer(o.poise, "poise", 0, 600), @@ -159,6 +162,7 @@ function fighter(value: unknown): FighterSnapshot { is_foul_recovery_target: bool(o.is_foul_recovery_target, "is_foul_recovery_target"), taunt_ticks: integer(o.taunt_ticks, "taunt_ticks", 0, 60), get_up_prompt: prompt, get_up_meter: integer(o.get_up_meter, "get_up_meter", 0, 256), get_up_required: getUpRequired, get_up_count: integer(o.get_up_count, "get_up_count", 0, 10), get_up_window_start_tick: integer(o.get_up_window_start_tick, "get_up_window_start_tick"), get_up_window_end_tick: integer(o.get_up_window_end_tick, "get_up_window_end_tick"), + last_input_sequence: integer(o.last_input_sequence, "last_input_sequence", -1), }; } function event(value: unknown): CombatEvent { @@ -205,20 +209,20 @@ export function decodeServerFrame(frame: string | ArrayBuffer | Uint8Array): Ser exact(o, ["version", "type", "role", "player_id", "seat", "rating", "players", "server_tick", "next_sequence"], ["reconnect_ticket"]); const decodedPlayers = players(o.players); if (!decodedPlayers.some((player) => player.id === playerId)) throw new ProtocolError("welcome fighter is absent"); - return { version: 2, type, role, player_id: playerId, seat: integer(o.seat, "seat", 1, 2) as 1 | 2, rating: integer(o.rating, "rating"), players: decodedPlayers, server_tick: integer(o.server_tick, "server_tick"), next_sequence: integer(o.next_sequence, "next_sequence"), ...reconnect }; + return { version: 3, type, role, player_id: playerId, seat: integer(o.seat, "seat", 1, 2) as 1 | 2, rating: integer(o.rating, "rating"), players: decodedPlayers, server_tick: integer(o.server_tick, "server_tick"), next_sequence: integer(o.next_sequence, "next_sequence"), ...reconnect }; } exact(o, ["version", "type", "role", "player_id", "players", "server_tick"], ["reconnect_ticket"]); const decodedPlayers = players(o.players, 2); if (decodedPlayers.some((player) => player.id === playerId)) throw new ProtocolError("spectator cannot be a fighter"); - return { version: 2, type, role, player_id: playerId, players: [decodedPlayers[0]!, decodedPlayers[1]!], server_tick: integer(o.server_tick, "server_tick"), ...reconnect }; + return { version: 3, type, role, player_id: playerId, players: [decodedPlayers[0]!, decodedPlayers[1]!], server_tick: integer(o.server_tick, "server_tick"), ...reconnect }; } - if (type === "ticket") { exact(o, ["version", "type", "reconnect_ticket", "refresh_id"]); return { version: 2, type, reconnect_ticket: string(o.reconnect_ticket, "reconnect_ticket", 4096), refresh_id: string(o.refresh_id, "refresh_id", 128, 16) }; } - if (type === "waiting") { exact(o, ["version", "type", "open_seats"]); if (o.open_seats !== 1) throw new ProtocolError("invalid open seats"); return { version: 2, type, open_seats: 1 }; } - if (type === "ready") { exact(o, ["version", "type", "players"]); const ps = players(o.players, 2); return { version: 2, type, players: [ps[0]!, ps[1]!] }; } - if (type === "paused") { exact(o, ["version", "type", "player_id", "grace_ms"]); return { version: 2, type, player_id: string(o.player_id, "player_id"), grace_ms: integer(o.grace_ms, "grace_ms", 0, 60_000) }; } - if (type === "resumed") { exact(o, ["version", "type", "player_id"]); return { version: 2, type, player_id: string(o.player_id, "player_id") }; } - if (type === "snapshot") { exact(o, ["version", "type", "payload"]); return { version: 2, type, payload: snapshot(o.payload) }; } - if (type === "error") { exact(o, ["version", "type", "code"]); return { version: 2, type, code: string(o.code, "error code", 80) }; } + if (type === "ticket") { exact(o, ["version", "type", "reconnect_ticket", "refresh_id"]); return { version: 3, type, reconnect_ticket: string(o.reconnect_ticket, "reconnect_ticket", 4096), refresh_id: string(o.refresh_id, "refresh_id", 128, 16) }; } + if (type === "waiting") { exact(o, ["version", "type", "open_seats"]); if (o.open_seats !== 1) throw new ProtocolError("invalid open seats"); return { version: 3, type, open_seats: 1 }; } + if (type === "ready") { exact(o, ["version", "type", "players"]); const ps = players(o.players, 2); return { version: 3, type, players: [ps[0]!, ps[1]!] }; } + if (type === "paused") { exact(o, ["version", "type", "player_id", "grace_ms"]); return { version: 3, type, player_id: string(o.player_id, "player_id"), grace_ms: integer(o.grace_ms, "grace_ms", 0, 60_000) }; } + if (type === "resumed") { exact(o, ["version", "type", "player_id"]); return { version: 3, type, player_id: string(o.player_id, "player_id") }; } + if (type === "snapshot") { exact(o, ["version", "type", "payload"]); return { version: 3, type, payload: snapshot(o.payload) }; } + if (type === "error") { exact(o, ["version", "type", "code"]); return { version: 3, type, code: string(o.code, "error code", 80) }; } if (type === "final") return decodeFinal(o, type); throw new ProtocolError("unsupported server message type"); } @@ -229,7 +233,7 @@ function decodeFinal(o: Obj, type: "final"): FinalMessage { for (const [id, raw] of entries) { string(id, "rating player id"); const r = object(raw, "rating"); exact(r, ["before", "after"]); ratings[id] = { before: integer(r.before, "before"), after: integer(r.after, "after") }; } const winner = nullableString(o.winner_id, "winner_id"); if (winner !== null && !Object.hasOwn(ratings, winner)) throw new ProtocolError("winner absent from ratings"); const method = oneOf(o.method, methods, "finish method"); coherentFinish(winner, method); - return { version: 2, type, match_id: string(o.match_id, "match_id"), winner_id: winner, method, round: integer(o.round, "round", 1, 15), scorecards: scorecards(o.scorecards), ratings }; + return { version: 3, type, match_id: string(o.match_id, "match_id"), winner_id: winner, method, round: integer(o.round, "round", 1, 15), scorecards: scorecards(o.scorecards), ratings }; } export function encodeInput(sequence: number, clientTick: number, frame: { moveX: number; moveY: number; defense: HeldDefense; actions: readonly SemanticAction[] }): string { @@ -239,12 +243,12 @@ export function encodeInput(sequence: number, clientTick: number, frame: { moveX if (raw.kind === "foul") return { kind: "foul", foul: oneOf(raw.foul, fouls, "foul"), ...id }; return { kind: oneOf(raw.kind, movementKinds, "action"), ...id }; }; - return JSON.stringify({ version: 2, type: "input", sequence: integer(sequence, "sequence"), client_tick: integer(clientTick, "client tick"), move: { x: Math.max(-1000, Math.min(1000, Math.round(Number.isFinite(frame.moveX) ? frame.moveX : 0))), y: Math.max(-1000, Math.min(1000, Math.round(Number.isFinite(frame.moveY) ? frame.moveY : 0))) }, defense: oneOf(frame.defense, heldDefenses, "held defense"), actions: frame.actions.slice(0, 4).map(action) }); + return JSON.stringify({ version: 3, type: "input", sequence: integer(sequence, "sequence"), client_tick: integer(clientTick, "client tick"), move: { x: Math.max(-1000, Math.min(1000, Math.round(Number.isFinite(frame.moveX) ? frame.moveX : 0))), y: Math.max(-1000, Math.min(1000, Math.round(Number.isFinite(frame.moveY) ? frame.moveY : 0))) }, defense: oneOf(frame.defense, heldDefenses, "held defense"), actions: frame.actions.slice(0, 4).map(action) }); } export function decodeBootstrap(value: unknown): BootstrapResponse { - const o = object(value, "bootstrap"); exact(o, ["client_id", "state", "protocol", "simulation"]); if (o.protocol !== 2) throw new ProtocolError("unsupported protocol version"); const s = object(o.simulation, "simulation"); exact(s, ["tick_rate", "ring_half_width", "ring_half_height"]); - return { client_id: string(o.client_id, "client_id", 36), state: string(o.state, "state", 128), protocol: 2, simulation: { tick_rate: integer(s.tick_rate, "tick rate", 1, 120), ring_half_width: integer(s.ring_half_width, "ring width", 1), ring_half_height: integer(s.ring_half_height, "ring height", 1) } }; + const o = object(value, "bootstrap"); exact(o, ["client_id", "state", "protocol", "simulation"]); if (o.protocol !== 3) throw new ProtocolError("unsupported protocol version"); const s = object(o.simulation, "simulation"); exact(s, ["tick_rate", "ring_half_width", "ring_half_height"]); + return { client_id: string(o.client_id, "client_id", 36), state: string(o.state, "state", 128), protocol: 3, simulation: { tick_rate: integer(s.tick_rate, "tick rate", 1, 120), ring_half_width: integer(s.ring_half_width, "ring width", 1), ring_half_height: integer(s.ring_half_height, "ring height", 1) } }; } export function decodeToken(value: unknown): TokenResponse { const o = object(value, "token response"); exact(o, ["access_token", "ticket", "player"]); const p = object(o.player, "player"); exact(p, ["id", "name", "avatar", "rating"]); diff --git a/web/hands/src/render/animation.ts b/web/hands/src/render/animation.ts deleted file mode 100644 index f705a2bd..00000000 --- a/web/hands/src/render/animation.ts +++ /dev/null @@ -1,644 +0,0 @@ -import * as THREE from "three"; -import { punchTiming, TICK_RATE, totalTicks } from "../manifest"; -import type { BloodLevel } from "../settings"; -import type { FighterSnapshot, Hand, Power, PunchClass, SemanticAction, Target } from "../types"; -import { aimBone, solveArm, type BoxerRig } from "./boxer"; -import type { WorldMapping } from "./world"; - -const GUARD_HIGH_L = new THREE.Vector3(0.13, 0.38, 0.23); -const GUARD_HIGH_R = new THREE.Vector3(-0.12, 0.4, 0.2); -const GUARD_LOW_L = new THREE.Vector3(0.18, 0.12, 0.3); -const GUARD_LOW_R = new THREE.Vector3(-0.17, 0.14, 0.28); -const RELAXED_L = new THREE.Vector3(0.16, 0.27, 0.3); -const RELAXED_R = new THREE.Vector3(-0.15, 0.29, 0.26); - -const HEAD_Y = 0.33; -const BODY_Y = -0.02; - -interface PhaseEnvelope { - readonly windup: number; - readonly extend: number; -} - -function punchEnvelope(kind: PunchClass, t: number, startupFrac: number, activeFrac: number): PhaseEnvelope { - const contact = startupFrac; - const recoverStart = Math.min(0.99, startupFrac + activeFrac); - switch (kind) { - case "jab": - return { - windup: smoothstep(0, contact * 0.5, t) * (1 - smoothstep(contact * 0.5, contact, t)), - extend: smoothstep(contact * 0.3, contact, t) * (1 - smoothstep(recoverStart, recoverStart + (1 - recoverStart) * 0.55, t)), - }; - case "straight": - return { - windup: smoothstep(0, contact * 0.6, t) * (1 - smoothstep(contact * 0.6, contact, t)), - extend: smoothstep(contact * 0.45, contact, t) * (1 - smoothstep(recoverStart, recoverStart + (1 - recoverStart) * 0.7, t)), - }; - case "hook": - return { - windup: smoothstep(0, contact * 0.7, t) * (1 - smoothstep(contact * 0.7, contact, t)), - extend: smoothstep(contact * 0.35, contact * 0.85, t) * (1 - smoothstep(recoverStart, recoverStart + (1 - recoverStart) * 0.75, t)), - }; - case "uppercut": - return { - windup: smoothstep(0, contact * 0.75, t) * (1 - smoothstep(contact * 0.7, contact, t)), - extend: smoothstep(contact * 0.5, contact, t) * (1 - smoothstep(recoverStart, recoverStart + (1 - recoverStart) * 0.75, t)), - }; - } -} - -function punchTarget(kind: PunchClass, target: Target, power: Power): THREE.Vector3 { - const boost = power === "power" ? 0.12 : 0; - const y = target === "head" ? HEAD_Y : BODY_Y; - switch (kind) { - case "jab": return new THREE.Vector3(0.06, y, 0.56 + boost * 0.5); - case "straight": return new THREE.Vector3(-0.04, y, 0.62 + boost * 0.5); - case "hook": return new THREE.Vector3(-0.3, y + 0.02, 0.48 + boost * 0.4); - case "uppercut": return new THREE.Vector3(0.0, y + 0.1, 0.46 + boost * 0.4); - } -} - -export interface Impact { - direction: number; - amount: number; - blocked: boolean; - target?: Target; -} - -const smooth = (current: number, target: number, rate: number, dt: number): number => current + (target - current) * (1 - Math.exp(-rate * dt)); -const smoothAngle = (current: number, target: number, rate: number, dt: number): number => { - const delta = ((target - current + Math.PI) % (Math.PI * 2) + Math.PI * 2) % (Math.PI * 2) - Math.PI; - return current + delta * (1 - Math.exp(-rate * dt)); -}; -const smoothstep = (edge0: number, edge1: number, value: number): number => { - const t = Math.max(0, Math.min(1, (value - edge0) / (edge1 - edge0))); - return t * t * (3 - 2 * t); -}; - -const scratchTarget = new THREE.Vector3(); -const scratchShoulder = new THREE.Vector3(); -const scratchPole = new THREE.Vector3(); -const scratchElbowOut = { elbowWorld: new THREE.Vector3(), targetWorld: new THREE.Vector3() }; -const scratchGlove = new THREE.Vector3(); -const scratchFinalL = new THREE.Vector3(); -const scratchFinalR = new THREE.Vector3(); -const scratchPunch = new THREE.Vector3(); -const scratchMixed = new THREE.Vector3(); -const scratchWindup = new THREE.Vector3(); -const scratchAim = new THREE.Vector3(); -const scratchAimWorld = new THREE.Vector3(); -const scratchQuat = new THREE.Quaternion(); - -const BLOOD_CUT_SCALE: Record = { full: 1, reduced: 0.35, off: 0 }; -const BLOODED_GLOVE = new THREE.Color(0x5c0a0e); - -export class BoxerAnimator { - private yaw = 0; - private punchT = 1; - private punchKind: PunchClass | null = null; - private punchHand: Hand = "left"; - private punchTargetKind: Target = "head"; - private punchPower: Power = "normal"; - private actionId: string | null = null; - private actionStartTick = 0; - private actionTotalTicks = 1; - private actionStartupFrac = 0.33; - private actionActiveFrac = 0.1; - private completedActionId: string | null = null; - private opponentDrop = 0; - private frozenTicks = 0; - private lastAgeTicks = 0; - private predictedId: string | null = null; - private predictedAtSeconds = -1; - private predictedTotalTicks = 1; - private predictionExpiredTicks = 0; - private downAmount = 0; - private rootX: number | null = null; - private rootZ = 0; - private reactionT = 1; - private reactionDirection = 1; - private reactionPower = 0; - private reactionTarget: Target = "head"; - private walkPhase = 0; - private readonly gloveLCurrent = new THREE.Vector3().copy(RELAXED_L); - private readonly gloveRCurrent = new THREE.Vector3().copy(RELAXED_R); - private hipsRoll = 0; - private spinePitch = 0; - private spineTwist = 0; - private drop = 0; - private kinStep = 0; - private kinHipYaw = 0; - private kinDrop = 0; - private kinHeelR = 0; - private kinPivotL = 0; - private kinHeadTuck = 0; - private hitstop = 0; - private prevVelocityX = 0; - private prevVelocityY = 0; - private inertiaPitch = 0; - private inertiaRoll = 0; - private prevDown = 0; - private landingSpring = 0; - private landingVelocity = 0; - - constructor(private readonly rig: BoxerRig, private readonly mapping: WorldMapping) {} - - get landingOffset(): number { - return this.landingSpring; - } - - impact(impact: Impact): void { - if (impact.amount > this.reactionPower || this.reactionT > 0.4) { - this.reactionT = 0; - this.reactionDirection = impact.direction; - this.reactionPower = Math.max(this.reactionPower * 0.4, impact.amount); - this.reactionTarget = impact.target ?? "head"; - } - } - - landedHit(blocked: boolean): void { - this.hitstop = Math.max(this.hitstop, blocked ? 0.045 : 0.078); - } - - predict(action: SemanticAction, timeSeconds: number, tickRate: number): void { - if (action.kind !== "punch") return; - if (action.id === undefined) return; - this.predictedId = action.id; - this.predictedAtSeconds = timeSeconds; - this.predictionExpiredTicks = 0; - this.punchKind = action.class; - this.punchHand = action.hand; - this.punchTargetKind = action.target; - this.punchPower = action.power; - const timing = punchTiming(action.class, action.target, action.power); - this.predictedTotalTicks = totalTicks(timing); - this.actionStartupFrac = timing.startup / this.predictedTotalTicks; - this.actionActiveFrac = timing.active / this.predictedTotalTicks; - if (this.actionId === null || this.punchT > 0.45) { - this.punchT = 0; - this.frozenTicks = 0; - this.lastAgeTicks = 0; - } - } - - private beginAuthoritative(fighter: FighterSnapshot, sampledTick: number, timeSeconds: number): void { - const matchedPrediction = this.predictedId !== null && fighter.action_id === this.predictedId; - this.actionId = fighter.action_id; - this.actionStartTick = fighter.action_start_tick; - this.actionTotalTicks = Math.max( - 1, - fighter.action_startup_ticks + fighter.action_active_ticks + fighter.action_recovery_ticks, - ); - this.actionStartupFrac = fighter.action_startup_ticks / this.actionTotalTicks; - this.actionActiveFrac = fighter.action_active_ticks / this.actionTotalTicks; - this.punchKind = fighter.action; - this.punchHand = fighter.action_hand ?? (fighter.stance === "orthodox" ? "left" : "right"); - this.punchTargetKind = fighter.action_target ?? "head"; - this.punchPower = fighter.action_power ?? "normal"; - if (matchedPrediction) { - const predictedAgeTicks = (timeSeconds - this.predictedAtSeconds) * 30; - const authoritativeAgeTicks = sampledTick - fighter.action_start_tick; - const drift = predictedAgeTicks - authoritativeAgeTicks; - if (Math.abs(drift) > 1) { - this.punchT = Math.max(0, Math.min(1, authoritativeAgeTicks / this.actionTotalTicks)); - this.frozenTicks = 0; - } - this.predictedId = null; - } else { - this.punchT = Math.max(0, Math.min(1, (sampledTick - fighter.action_start_tick) / this.actionTotalTicks)); - this.frozenTicks = 0; - this.lastAgeTicks = this.punchT * this.actionTotalTicks; - } - } - - update(fighter: FighterSnapshot, opponent: FighterSnapshot, dt: number, time: number, reducedMotion: boolean, blood: BloodLevel = "full", sampledTick = 0): void { - const rig = this.rig; - const mirror = fighter.stance === "orthodox" ? 1 : -1; - - const worldX = this.mapping.x(fighter.x); - const worldZ = this.mapping.z(fighter.y); - if (this.rootX === null) { - this.rootX = worldX; - this.rootZ = worldZ; - } - const maxStep = 0.05; - const rootDx = THREE.MathUtils.clamp(worldX - this.rootX, -maxStep, maxStep); - const rootDz = THREE.MathUtils.clamp(worldZ - this.rootZ, -maxStep, maxStep); - this.rootX += rootDx; - this.rootZ += rootDz; - const targetYaw = Math.atan2(this.mapping.x(opponent.x) - worldX, (this.mapping.z(opponent.y) - worldZ) * 0.45); - this.yaw = smoothAngle(this.yaw, targetYaw, 7, dt); - - if (fighter.action_id !== null && fighter.action_id !== this.actionId && fighter.action_id !== this.completedActionId) { - this.beginAuthoritative(fighter, sampledTick, time); - } - if (fighter.action_id === null) { - this.actionId = null; - this.completedActionId = null; - } - if (this.predictedId !== null) { - this.predictionExpiredTicks += dt * 30; - if (this.predictionExpiredTicks > 10) { - this.predictedId = null; - this.punchT = 1; - } - } - const playingPrediction = this.predictedId !== null && this.actionId === null; - let ageTicks = 0; - let totalDuration = 1; - if (playingPrediction) { - ageTicks = (time - this.predictedAtSeconds) * 30 - this.frozenTicks; - totalDuration = this.predictedTotalTicks; - } else if (this.actionId !== null) { - ageTicks = sampledTick - this.actionStartTick - this.frozenTicks; - totalDuration = this.actionTotalTicks; - } - if (this.hitstop > 0) { - this.hitstop = Math.max(0, this.hitstop - dt); - this.frozenTicks += dt * 30; - } - if (playingPrediction || this.actionId !== null) { - this.punchT = Math.max(0, Math.min(1, ageTicks / totalDuration)); - if (this.punchT >= 1 && this.actionId !== null) { - this.completedActionId = this.actionId; - this.actionId = null; - } - } else { - this.punchT = 1; - } - - const tired = 1 - fighter.stamina / Math.max(1, fighter.maximum_stamina); - const fatiguePose = THREE.MathUtils.clamp((tired - 0.1) / 0.9, 0, 1); - const velocityWorldX = this.mapping.x(fighter.velocity_x) * TICK_RATE; - const velocityWorldZ = this.mapping.z(fighter.velocity_y) * TICK_RATE; - const speed = Math.hypot(velocityWorldX, velocityWorldZ); - const speedFactor = Math.min(1, speed / 1.1); - const forwardMotion = THREE.MathUtils.clamp((fighter.velocity_x * fighter.facing) / 7, -1, 1); - const lateralMotion = THREE.MathUtils.clamp(fighter.velocity_y / 7, -1, 1); - this.walkPhase += speed * dt * 5.72; - - const accelX = (fighter.velocity_x - this.prevVelocityX) / Math.max(0.001, dt); - const accelY = (fighter.velocity_y - this.prevVelocityY) / Math.max(0.001, dt); - this.prevVelocityX = fighter.velocity_x; - this.prevVelocityY = fighter.velocity_y; - const accelForward = (Math.sin(this.yaw) * this.mapping.x(accelX) + Math.cos(this.yaw) * this.mapping.z(accelY)) * 0.12; - const accelLateral = (Math.cos(this.yaw) * this.mapping.x(accelX) - Math.sin(this.yaw) * this.mapping.z(accelY)) * 0.12; - this.inertiaPitch = smooth(this.inertiaPitch, THREE.MathUtils.clamp(-accelForward, -0.16, 0.16), 6, dt); - this.inertiaRoll = smooth(this.inertiaRoll, THREE.MathUtils.clamp(accelLateral, -0.12, 0.12), 6, dt); - - const downTarget = fighter.is_downed ? 1 : 0; - const downRate = fighter.is_downed ? 2.6 : 1.5; - this.downAmount = smooth(this.downAmount, downTarget, downRate, dt); - const down = smoothstep(0, 1, this.downAmount); - if (down > 0.72 && this.prevDown <= 0.72) this.landingVelocity = -0.85; - this.prevDown = down; - const springAccel = -this.landingSpring * 90 - this.landingVelocity * 12; - this.landingVelocity += springAccel * dt; - this.landingSpring = THREE.MathUtils.clamp(this.landingSpring + this.landingVelocity * dt, -0.09, 0.06); - - this.reactionT = Math.min(1, this.reactionT + dt / 0.42); - const reactionPower = Math.min(1, this.reactionPower / 220); - const reactionHead = (1 - smoothstep(0, 0.8, this.reactionT)) * reactionPower - * (this.reactionTarget === "head" ? 1 : 0.2); - const reaction = smoothstep(0, 0.14, this.reactionT) * (1 - smoothstep(0.35, 1, this.reactionT)) * reactionPower; - - const stunned = Math.min(1, fighter.stunned_ticks / 45); - const wobble = reducedMotion ? 0 : Math.sin(time * 8.6) * 0.05 * stunned; - - const idleTempo = 4.4 - tired * 1.4; - const stepBounce = reducedMotion || down > 0.5 ? 0 : -Math.abs(Math.sin(time * idleTempo + this.walkPhase * 0.35)) * (0.017 + tired * 0.01); - const weightSway = reducedMotion || down > 0.5 ? 0 : Math.sin(time * idleTempo * 0.5) * 0.022; - const breath = reducedMotion ? 0 : Math.sin(time * (2.2 + tired * 2.6)) * (0.012 + tired * 0.03); - - let dropTarget = -0.035 - fatiguePose * 0.025; - let rollTarget = 0; - let pitchTarget = 0.09 + fatiguePose * 0.06; - if (fighter.defense === "weave") { dropTarget = -0.26; rollTarget = 0.34 * mirror; pitchTarget = 0.3; } - else if (fighter.defense === "slip_left") { rollTarget = 0.2; pitchTarget = 0.12; } - else if (fighter.defense === "slip_right") { rollTarget = -0.2; pitchTarget = 0.12; } - else if (fighter.defense === "pull") { pitchTarget = -0.26; } - if (fighter.is_foul_recovery_target) { dropTarget = -0.18; pitchTarget = 0.42; } - if (fighter.clinch_ticks > 0 || fighter.clinch_startup_ticks > 0) { pitchTarget = 0.4; dropTarget = -0.08; } - dropTarget -= reaction * (this.reactionTarget === "body" ? 0.12 : 0.05); - pitchTarget -= reaction * (this.reactionTarget === "body" ? 0.18 : 0.34); - rollTarget += reaction * (this.reactionTarget === "body" ? 0.16 : 0.06) - * (this.reactionDirection < 0 ? -1 : 1); - rollTarget += wobble + this.inertiaRoll; - pitchTarget += this.inertiaPitch; - - let twistTarget = 0; - let stepTarget = 0; - let hipYawTarget = 0; - let kinDropTarget = 0; - let heelRearTarget = 0; - let pivotPunchTarget = 0; - let tuckTarget = 0; - if (this.punchT < 1 && this.punchKind !== null) { - const { windup, extend } = punchEnvelope(this.punchKind, this.punchT, this.actionStartupFrac, this.actionActiveFrac); - // three.js: rotation.y > 0 brings the anatomical RIGHT shoulder forward. - // The punching shoulder must rotate through the target line regardless of stance. - const handTwist = this.punchHand === "left" ? -1 : 1; - const bodyDip = this.punchTargetKind === "body" ? -0.09 * extend : 0; - if (this.punchKind === "jab") { - twistTarget = 0.14 * extend * handTwist; - stepTarget = 0.12 * extend; - hipYawTarget = 0.06 * extend * handTwist; - heelRearTarget = 0.3 * extend; - tuckTarget = 0.15 * extend; - pitchTarget += 0.14 * extend; - } else if (this.punchKind === "straight") { - twistTarget = 0.38 * extend * handTwist; - hipYawTarget = 0.32 * extend * handTwist; - heelRearTarget = 0.5 * extend; - stepTarget = 0.12 * extend; - tuckTarget = 0.1 * extend; - pitchTarget += 0.16 * extend; - } else if (this.punchKind === "hook") { - twistTarget = 0.34 * extend * handTwist; - hipYawTarget = 0.3 * extend * handTwist; - pivotPunchTarget = 0.55 * extend; - rollTarget += 0.09 * extend * handTwist; - tuckTarget = 0.08 * extend; - } else { - twistTarget = 0.26 * extend * handTwist; - hipYawTarget = 0.22 * extend * handTwist; - kinDropTarget = -0.18 * windup + 0.07 * extend; - pitchTarget += 0.14 * windup - 0.07 * extend; - heelRearTarget = 0.4 * extend; - } - kinDropTarget += bodyDip; - } - this.drop = smooth(this.drop, dropTarget, 12, dt); - this.hipsRoll = smooth(this.hipsRoll, rollTarget, 12, dt); - this.spinePitch = smooth(this.spinePitch, pitchTarget, 11, dt); - this.spineTwist = smooth(this.spineTwist, twistTarget, 16, dt); - this.kinStep = smooth(this.kinStep, stepTarget, 14, dt); - this.kinHipYaw = smooth(this.kinHipYaw, hipYawTarget, 14, dt); - this.kinDrop = smooth(this.kinDrop, kinDropTarget, 13, dt); - this.kinHeelR = smooth(this.kinHeelR, heelRearTarget, 14, dt); - this.kinPivotL = smooth(this.kinPivotL, pivotPunchTarget, 14, dt); - this.kinHeadTuck = smooth(this.kinHeadTuck, tuckTarget, 14, dt); - - const blade = 0.5 * mirror; - const rootYaw = this.yaw + blade * (1 - down); - rig.root.rotation.set(0, rootYaw, 0); - const stepForwardX = Math.sin(rootYaw) * this.kinStep * (1 - down); - const stepForwardZ = Math.cos(rootYaw) * this.kinStep * (1 - down); - rig.root.position.set(this.rootX + stepForwardX, 0, this.rootZ + stepForwardZ); - - const fallSide = this.reactionDirection >= 0 ? 1 : -1; - rig.hips.position.y = 0.955 + stepBounce + (this.drop + this.kinDrop) * (1 - down) - down * 0.8 + this.landingSpring; - rig.hips.position.x = weightSway * (1 - down); - rig.hips.rotation.set( - -down * (Math.PI / 2 - 0.12) + this.spinePitch * 0.35 * (1 - down), - this.kinHipYaw * (1 - down) + down * 0.32 * fallSide, - this.hipsRoll * 0.5 * (1 - down) + weightSway * 0.8 * (1 - down) + down * 0.15 * fallSide, - ); - rig.spine.rotation.set(this.spinePitch * (1 - down), (this.spineTwist + Math.sin(this.walkPhase) * 0.05 * speedFactor) * (1 - down), this.hipsRoll * 0.55 * (1 - down)); - - const headPitch = 0.1 + this.kinHeadTuck - this.spinePitch * 0.7 - reactionHead * 0.55 + down * 0.3; - const headRoll = -this.hipsRoll * 0.8 + reactionHead * 0.3 * (this.reactionDirection >= 0 ? -1 : 1); - const headWeave = reducedMotion ? 0 : Math.sin(time * 0.9) * 0.07 + Math.sin(time * 1.7) * 0.03; - rig.head.rotation.set(headPitch, -this.spineTwist * 0.5 + headWeave * (1 - down), headRoll); - rig.chest.scale.set(1 + breath, 1 + breath * 0.5, 1 + breath); - - this.poseLegs(speedFactor, down, fallSide, mirror, forwardMotion, lateralMotion); - - rig.root.updateMatrixWorld(true); - - const guardL = fighter.defense === "guard_high" ? GUARD_HIGH_L : fighter.defense === "guard_low" ? GUARD_LOW_L : RELAXED_L; - const guardR = fighter.defense === "guard_high" ? GUARD_HIGH_R : fighter.defense === "guard_low" ? GUARD_LOW_R : RELAXED_R; - const finalL = scratchFinalL.copy(guardL); - const finalR = scratchFinalR.copy(guardR); - finalL.y -= fatiguePose * 0.065; - finalR.y -= fatiguePose * 0.065; - finalL.z -= fatiguePose * 0.03; - finalR.z -= fatiguePose * 0.03; - if (fighter.is_foul_recovery_target) { finalL.set(0.08, 0.32, 0.2); finalR.set(-0.06, 0.3, 0.18); } - if (fighter.clinch_ticks > 0 || fighter.clinch_startup_ticks > 0) { finalL.set(0.16, -0.05, 0.5); finalR.set(-0.16, -0.02, 0.48); } - if (down > 0.03) { - const flail = Math.sin(smoothstep(0.06, 0.5, down) * Math.PI) * 0.42; - finalL.lerp(scratchTarget.set(0.56, 0.1, -0.05), down); - finalR.lerp(scratchTarget.set(-0.54, 0.12, 0.02), down); - finalL.y += flail; - finalR.y += flail * 0.85; - finalL.x += flail * 0.2 * fallSide; - finalR.x += flail * 0.15 * fallSide; - } else if (stunned > 0.15) { - finalL.lerp(scratchTarget.set(0.3, -0.25, 0.15), stunned * 0.7); - finalR.lerp(scratchTarget.set(-0.3, -0.22, 0.15), stunned * 0.7); - } - - if (!reducedMotion && down < 0.1) { - const driftPhase = time * 1.9 + this.walkPhase * 0.2; - finalL.x += Math.sin(driftPhase) * 0.014; - finalL.y += Math.cos(driftPhase * 1.3) * 0.012; - finalR.x += Math.cos(driftPhase * 0.8) * 0.012; - finalR.y += Math.sin(driftPhase * 1.1) * 0.013; - const feintCycle = (time * 0.27 + (mirror > 0 ? 0 : 0.5)) % 1; - const feint = smoothstep(0.86, 0.9, feintCycle) * (1 - smoothstep(0.9, 0.97, feintCycle)); - if (this.punchT >= 1) { - if (mirror > 0) finalL.z += feint * 0.12; - else finalR.z += feint * 0.12; - } - } - - if (this.punchT < 1 && this.punchKind !== null && down < 0.85) { - const { windup, extend } = punchEnvelope(this.punchKind, this.punchT, this.actionStartupFrac, this.actionActiveFrac); - const scaledExtend = extend * (1 - down); - const dropTarget = opponent.is_downed ? -1.2 : opponent.defense === "weave" ? -0.24 : -0.03; - this.opponentDrop = smooth(this.opponentDrop, dropTarget, 4, dt); - scratchAimWorld.set( - this.mapping.x(opponent.x), - (this.punchTargetKind === "body" ? 1.2 : 1.62) + this.opponentDrop, - this.mapping.z(opponent.y), - ); - const aim = rig.chest.worldToLocal(scratchAim.copy(scratchAimWorld)); - const punch = scratchPunch.copy(punchTarget(this.punchKind, this.punchTargetKind, this.punchPower)); - if (this.punchKind === "jab" || this.punchKind === "straight") { - punch.x = aim.x * 0.92; - punch.y = aim.y; - punch.z = THREE.MathUtils.clamp(aim.z, 0.4, 0.8); - } else if (this.punchKind === "hook") { - const sweep = smoothstep(this.actionStartupFrac * 0.85, this.actionStartupFrac + this.actionActiveFrac * 0.75, this.punchT); - const sideSign = this.punchHand === "left" ? 1 : -1; - punch.x = THREE.MathUtils.lerp(aim.x + 0.3 * sideSign, aim.x - 0.14 * sideSign, sweep); - punch.z = Math.min(0.52, aim.z * (0.72 + 0.28 * Math.sin(sweep * Math.PI * 0.5))); - punch.y = aim.y; - } else if (this.punchKind === "uppercut") { - const rise = smoothstep(this.actionStartupFrac * 0.7, this.actionStartupFrac + this.actionActiveFrac * 0.5, this.punchT); - punch.x = aim.x * 0.9; - punch.y = THREE.MathUtils.lerp(-0.26, aim.y + 0.04, rise); - punch.z = THREE.MathUtils.lerp(0.24, aim.z * 0.94, rise); - } - const windupOffset = scratchWindup.set(0, this.punchKind === "uppercut" ? -0.22 : -0.03, this.punchKind === "jab" ? -0.1 : -0.16).multiplyScalar(windup); - const base = this.punchHand === "left" ? finalL : finalR; - const other = this.punchHand === "left" ? finalR : finalL; - const otherSide = this.punchHand === "left" ? -1 : 1; - if (this.punchKind === "straight") other.set(0.11 * otherSide, 0.34, 0.18); - if (this.punchKind === "hook") other.set(0.1 * otherSide, 0.36, 0.16); - if (this.punchKind === "uppercut") other.y -= 0.08; - const mixed = scratchMixed.copy(base).add(windupOffset).lerp(punch, scaledExtend); - if (this.punchPower === "power" && Math.abs(this.punchT - (this.actionStartupFrac + this.actionActiveFrac * 0.5)) < 0.06) { - const overshoot = (1 - Math.abs(this.punchT - (this.actionStartupFrac + this.actionActiveFrac * 0.5)) / 0.06) * 0.06; - mixed.addScaledVector(punch, overshoot * scaledExtend); - } - base.copy(mixed); - } - - if (fighter.taunt_ticks > 0 && down < 0.1) { - const beat = ((60 - fighter.taunt_ticks) / 60) * 4; - const direction = Math.floor(beat) % 2 === 0 ? 1 : -1; - const swing = Math.abs(Math.sin(beat * Math.PI)); - finalL.set(THREE.MathUtils.lerp(0.28, -0.3, swing * (direction > 0 ? 1 : 0.15)), 0.52 + swing * 0.18, 0.3); - finalR.set(THREE.MathUtils.lerp(-0.28, 0.3, swing * (direction < 0 ? 1 : 0.15)), 0.46 + swing * 0.2, 0.3); - rig.hips.rotation.z += direction * swing * 0.14; - rig.hips.position.y -= swing * 0.035; - rig.spine.rotation.y += direction * swing * 0.18; - rig.head.rotation.z += direction * swing * 0.1; - } - - finalL.x *= mirror; - finalR.x *= mirror; - const gloveRate = down > 0.05 ? 9 : this.punchT < 1 ? 34 : 26; - this.gloveLCurrent.x = smooth(this.gloveLCurrent.x, finalL.x, gloveRate, dt); - this.gloveLCurrent.y = smooth(this.gloveLCurrent.y, finalL.y, gloveRate, dt); - this.gloveLCurrent.z = smooth(this.gloveLCurrent.z, finalL.z, gloveRate, dt); - this.gloveRCurrent.x = smooth(this.gloveRCurrent.x, finalR.x, gloveRate, dt); - this.gloveRCurrent.y = smooth(this.gloveRCurrent.y, finalR.y, gloveRate, dt); - this.gloveRCurrent.z = smooth(this.gloveRCurrent.z, finalR.z, gloveRate, dt); - - this.solveArmIK(rig.shoulderL, rig.elbowL, rig.gloveL, this.gloveLCurrent, 1, rig); - this.solveArmIK(rig.shoulderR, rig.elbowR, rig.gloveR, this.gloveRCurrent, -1, rig); - - this.applyTrauma(fighter, opponent, blood); - } - - private poseLegs( - speedFactor: number, - down: number, - fallSide: number, - mirror: number, - forwardMotion: number, - lateralMotion: number, - ): void { - const rig = this.rig; - const strideAmp = 0.34 * speedFactor * (1 - down); - const liftAmp = 0.38 * speedFactor * (1 - down); - const forwardDirection = Math.abs(forwardMotion) > 0.05 ? Math.sign(forwardMotion) : 0; - const lateralStride = lateralMotion * speedFactor * (1 - down); - const crouch = -(this.drop + this.kinDrop) * 1.35 * (1 - down); - const phaseL = this.walkPhase; - const phaseR = this.walkPhase + Math.PI; - const baseL = { hip: -0.2 - crouch * 0.5, knee: 0.34 + crouch, ankle: -0.1 - crouch * 0.5 }; - const baseR = { hip: 0.15 - crouch * 0.5, knee: 0.38 + crouch, ankle: -0.12 - crouch * 0.5 }; - const swingL = Math.sin(phaseL) * strideAmp * forwardDirection; - const swingR = Math.sin(phaseR) * strideAmp * forwardDirection; - const liftL = Math.max(0, Math.sin(phaseL - Math.PI / 2)) * liftAmp; - const liftR = Math.max(0, Math.sin(phaseR - Math.PI / 2)) * liftAmp; - const buckle = smoothstep(0, 0.3, down) * (1 - smoothstep(0.32, 0.62, down)); - const lateralPhase = Math.sin(phaseL) * 0.16 * lateralStride; - rig.hipL.rotation.set( - THREE.MathUtils.lerp(baseL.hip + swingL, -0.18, down), - 0.32 * mirror * (1 - down) + (this.punchHand === "left" ? this.kinPivotL : 0) * (1 - down), - THREE.MathUtils.lerp(0.1 * lateralStride + lateralPhase, 0.5 * fallSide, down), - ); - rig.kneeL.rotation.x = THREE.MathUtils.lerp(baseL.knee + liftL + buckle * 0.85, 0.24, Math.max(down, buckle)); - rig.ankleL.rotation.x = THREE.MathUtils.lerp(baseL.ankle - swingL * 0.4 - (mirror < 0 ? this.kinHeelR : 0) * (1 - down), 0.42, down); - rig.ankleL.rotation.z = -0.08 * lateralStride - lateralPhase * 0.45; - rig.hipR.rotation.set( - THREE.MathUtils.lerp(baseR.hip + swingR, -0.12, down), - -0.14 * mirror * (1 - down) + (this.punchHand === "right" ? this.kinPivotL : 0) * (1 - down), - THREE.MathUtils.lerp(0.1 * lateralStride - lateralPhase, 0.35 * fallSide, down), - ); - rig.kneeR.rotation.x = THREE.MathUtils.lerp(baseR.knee + liftR + buckle * 0.8, 0.18, Math.max(down, buckle)); - rig.ankleR.rotation.x = THREE.MathUtils.lerp(baseR.ankle - swingR * 0.4 - (mirror > 0 ? this.kinHeelR : 0) * (1 - down), 0.42, down); - rig.ankleR.rotation.z = -0.08 * lateralStride + lateralPhase * 0.45; - } - - private solveArmIK(shoulder: THREE.Group, elbow: THREE.Group, glove: THREE.Group, localTarget: THREE.Vector3, side: 1 | -1, rig: BoxerRig): void { - shoulder.getWorldPosition(scratchShoulder); - scratchGlove.copy(localTarget); - rig.chest.localToWorld(scratchGlove); - scratchPole.set(0.9 * side, -1, -0.25).applyQuaternion(rig.chest.getWorldQuaternion(scratchQuat)); - const isPunchingArm = this.punchT < 1 - && ((side === 1 && this.punchHand === "left") || (side === -1 && this.punchHand === "right")); - const maximumReach = isPunchingArm && this.punchKind === "hook" - ? 0.56 - : isPunchingArm && this.punchKind === "uppercut" - ? 0.58 - : undefined; - solveArm(scratchShoulder, scratchGlove, scratchPole, scratchElbowOut, maximumReach); - aimBone(shoulder, scratchShoulder, scratchElbowOut.elbowWorld); - shoulder.updateMatrixWorld(true); - aimBone(elbow, scratchElbowOut.elbowWorld, scratchElbowOut.targetWorld); - } - - private applyTrauma(fighter: FighterSnapshot, opponent: FighterSnapshot, blood: BloodLevel): void { - const trauma = fighter.trauma; - const bruise = (value: number): number => Math.min(0.85, value / 170 + trauma.swelling / 420); - const cutScale = BLOOD_CUT_SCALE[blood]; - (this.rig.bruiseL.material as THREE.MeshStandardMaterial).opacity = bruise(trauma.left_eye); - (this.rig.bruiseR.material as THREE.MeshStandardMaterial).opacity = bruise(trauma.right_eye); - const cutL = Math.min(1, trauma.left_cut / 150 + trauma.bleeding / 450); - const cutR = Math.min(1, trauma.right_cut / 150 + trauma.bleeding / 450); - (this.rig.cutL.material as THREE.MeshStandardMaterial).opacity = cutL * cutScale; - (this.rig.cutR.material as THREE.MeshStandardMaterial).opacity = cutR * cutScale; - const graphicScale = blood === "full" ? 1.8 : 1; - this.rig.cutL.scale.set(1 + cutL * 0.55 * graphicScale, 1 + cutL * 0.7, 1); - this.rig.cutR.scale.set(1 + cutR * 0.55 * graphicScale, 1 + cutR * 0.7, 1); - - const swellAmount = (value: number): number => Math.min(1.35, value / 260 + trauma.swelling / 560); - const swellL = swellAmount(trauma.left_eye); - const swellR = swellAmount(trauma.right_eye); - this.rig.swellL.scale.setScalar(0.25 + swellL * 1.15); - this.rig.swellR.scale.setScalar(0.25 + swellR * 1.15); - (this.rig.swellL.material as THREE.MeshStandardMaterial).opacity = Math.min(0.92, swellL * 1.1); - (this.rig.swellR.material as THREE.MeshStandardMaterial).opacity = Math.min(0.92, swellR * 1.1); - const cheekAmount = Math.min(1, trauma.head / 900 + trauma.swelling / 800); - this.rig.cheekL.scale.setScalar(0.2 + cheekAmount * 1.05); - this.rig.cheekR.scale.setScalar(0.2 + cheekAmount * 0.95); - (this.rig.cheekL.material as THREE.MeshStandardMaterial).opacity = cheekAmount * 0.8; - (this.rig.cheekR.material as THREE.MeshStandardMaterial).opacity = cheekAmount * 0.75; - - const dripL = Math.min(1.9, (trauma.left_cut + trauma.bleeding) / 220); - const dripR = Math.min(1.9, (trauma.right_cut + trauma.bleeding) / 220); - this.rig.streakL.scale.set(graphicScale, 0.15 + dripL * graphicScale, 1); - this.rig.streakR.scale.set(graphicScale, 0.15 + dripR * graphicScale, 1); - (this.rig.streakL.material as THREE.MeshStandardMaterial).opacity = Math.min(1, dripL) * cutScale; - (this.rig.streakR.material as THREE.MeshStandardMaterial).opacity = Math.min(1, dripR) * cutScale; - const noseAmount = Math.min(1.6, trauma.head / 600 + trauma.bleeding / 340); - this.rig.noseStreak.scale.set(graphicScale, 0.2 + noseAmount * graphicScale, 1); - (this.rig.noseStreak.material as THREE.MeshStandardMaterial).opacity = Math.min(1, noseAmount) * cutScale; - const mouth = Math.min(1, trauma.head / 650 + trauma.bleeding / 360); - this.rig.mouthBlood.scale.set(1 + mouth * graphicScale, 1 + mouth * 0.8, 1); - (this.rig.mouthBlood.material as THREE.MeshStandardMaterial).opacity = mouth * cutScale; - - const ribAmount = Math.min(1, trauma.body / 750); - this.rig.ribL.scale.set(0.5 + ribAmount * 0.35, 1.2 + ribAmount * 0.5, 0.7 + ribAmount * 0.2); - this.rig.ribR.scale.set(0.5 + ribAmount * 0.3, 1.2 + ribAmount * 0.4, 0.7 + ribAmount * 0.2); - (this.rig.ribL.material as THREE.MeshStandardMaterial).opacity = ribAmount * 0.85; - (this.rig.ribR.material as THREE.MeshStandardMaterial).opacity = ribAmount * 0.8; - - const opponentBlood = Math.min( - 1, - (opponent.trauma.bleeding + opponent.trauma.left_cut + opponent.trauma.right_cut) / 620 - * (blood === "off" ? 0 : blood === "reduced" ? 0.3 : 1.5), - ); - this.rig.gloveLMaterial.color.copy(this.rig.gloveBaseColor).lerp(BLOODED_GLOVE, opponentBlood); - - const smear = Math.min(1.5, trauma.body / 450 + trauma.bleeding / 340); - this.rig.bodyStreak.scale.set(1 + smear * 0.55 * graphicScale, 0.3 + smear * graphicScale, 1); - (this.rig.bodyStreak.material as THREE.MeshStandardMaterial).opacity = Math.min(1, smear) * cutScale; - - (this.rig.bodyBruise.material as THREE.MeshStandardMaterial).opacity = Math.min(0.7, trauma.body / 950); - const swell = 1 + Math.min(0.12, trauma.swelling / 2500); - this.rig.headMesh.scale.set(0.92 * swell, 1.05 * swell, 0.95 * swell); - const skin = this.rig.skinMaterial; - skin.clearcoat = 0.25 + tiredSheen(fighter) * 0.4; - } -} - -function tiredSheen(fighter: FighterSnapshot): number { - return 1 - fighter.stamina / Math.max(1, fighter.maximum_stamina); -} diff --git a/web/hands/src/render/arena.ts b/web/hands/src/render/arena.ts index 74c55d87..bfc0d059 100644 --- a/web/hands/src/render/arena.ts +++ b/web/hands/src/render/arena.ts @@ -3,9 +3,14 @@ import * as THREE from "three"; export interface BuiltArena { readonly group: THREE.Group; readonly update: (time: number, dt: number, reducedMotion: boolean) => void; + /** Raises crowd excitement (0..1); it decays over a few seconds. */ + readonly excite: (amount: number) => void; + readonly excitement: () => number; readonly dispose: () => void; } +const EXCITEMENT_DECAY_PER_SECOND = 0.3; + const CROWD_BODY_COLORS = [0x2a3140, 0x3a2f2a, 0x26343a, 0x40312e, 0x2e3a2c, 0x38343e, 0x443c30, 0x5a5148, 0x31404a, 0x4a3542]; const CROWD_SKIN_COLORS = [0xc79b76, 0x8a5a3b, 0x6e4128, 0xe0b48f, 0x54301d, 0xa9744f]; @@ -44,8 +49,8 @@ export function buildArena(): BuiltArena { const bodyGeo = new THREE.CapsuleGeometry(0.19, 0.5, 4, 8); const headGeo = new THREE.SphereGeometry(0.115, 8, 7); geometries.push(bodyGeo, headGeo); - const bodyMat = new THREE.MeshStandardMaterial({ roughness: 0.9, metalness: 0 }); - const headMat = new THREE.MeshStandardMaterial({ roughness: 0.75, metalness: 0 }); + const bodyMat = new THREE.MeshStandardMaterial({ roughness: 0.9, metalness: 0, emissive: 0x141926, emissiveIntensity: 0.7 }); + const headMat = new THREE.MeshStandardMaterial({ roughness: 0.75, metalness: 0, emissive: 0x2a1d16, emissiveIntensity: 0.7 }); materials.push(bodyMat, headMat); const bodies = new THREE.InstancedMesh(bodyGeo, bodyMat, total); const heads = new THREE.InstancedMesh(headGeo, headMat, total); @@ -171,20 +176,22 @@ export function buildArena(): BuiltArena { let flashTimer = 0; let flashOn = 0; + let excitement = 0; const crowdMatrix = new THREE.Matrix4(); const crowdPosition = new THREE.Vector3(); const crowdQuaternion = new THREE.Quaternion(); const crowdScale = new THREE.Vector3(); const yAxis = new THREE.Vector3(0, 1, 0); const update = (time: number, dt: number, reducedMotion: boolean): void => { + excitement = Math.max(0, excitement - dt * EXCITEMENT_DECAY_PER_SECOND); if (!reducedMotion) { - const subset = 90; - const start = Math.floor((time * 30) % total); - for (let n = 0; n < subset; n += 1) { - const i = (start + n) % total; + const swayAmplitude = 0.05 + excitement * 0.06; + const bounceAmplitude = 0.05 + excitement * 0.2; + const bounceRate = 2.3 + excitement * 3.2; + for (let i = 0; i < total; i += 1) { const base = bases[i]!; - const sway = Math.sin(time * 1.6 + phases[i]!) * 0.05; - const bounce = Math.abs(Math.sin(time * 2.3 + phases[i]! * 1.7)) * 0.05; + const sway = Math.sin(time * 1.6 + phases[i]!) * swayAmplitude; + const bounce = Math.abs(Math.sin(time * bounceRate + phases[i]! * 1.7)) * bounceAmplitude; crowdQuaternion.setFromAxisAngle(yAxis, base.yaw + sway); crowdMatrix.compose( crowdPosition.set(base.x, base.y + 0.45 * base.scale + bounce, base.z + sway * 0.4), @@ -205,7 +212,7 @@ export function buildArena(): BuiltArena { flashTimer -= dt; if (flashTimer <= 0) { flashOn = 0.09 + Math.random() * 0.08; - flashTimer = 0.25 + Math.random() * 1.6; + flashTimer = (0.25 + Math.random() * 1.6) / (1 + excitement * 4); } flashOn = Math.max(0, flashOn - dt); flashMat.opacity = flashOn > 0 ? 0.85 : 0; @@ -220,5 +227,9 @@ export function buildArena(): BuiltArena { heads.dispose(); }; - return { group, update, dispose }; + const excite = (amount: number): void => { + excitement = Math.min(1, excitement + Math.max(0, amount)); + }; + + return { group, update, excite, excitement: () => excitement, dispose }; } diff --git a/web/hands/src/render/boxer.ts b/web/hands/src/render/boxer.ts deleted file mode 100644 index 36727f34..00000000 --- a/web/hands/src/render/boxer.ts +++ /dev/null @@ -1,608 +0,0 @@ -import * as THREE from "three"; -import type { FighterPalette } from "./world"; - -export interface BoxerRig { - readonly root: THREE.Group; - readonly hips: THREE.Group; - readonly spine: THREE.Group; - readonly chest: THREE.Group; - readonly head: THREE.Group; - readonly shoulderL: THREE.Group; - readonly elbowL: THREE.Group; - readonly gloveL: THREE.Group; - readonly shoulderR: THREE.Group; - readonly elbowR: THREE.Group; - readonly gloveR: THREE.Group; - readonly hipL: THREE.Group; - readonly kneeL: THREE.Group; - readonly ankleL: THREE.Group; - readonly hipR: THREE.Group; - readonly kneeR: THREE.Group; - readonly ankleR: THREE.Group; - readonly chestMesh: THREE.Mesh; - readonly headMesh: THREE.Mesh; - readonly browL: THREE.Mesh; - readonly browR: THREE.Mesh; - readonly bruiseL: THREE.Mesh; - readonly bruiseR: THREE.Mesh; - readonly bodyBruise: THREE.Mesh; - readonly cutL: THREE.Mesh; - readonly cutR: THREE.Mesh; - readonly swellL: THREE.Mesh; - readonly swellR: THREE.Mesh; - readonly cheekL: THREE.Mesh; - readonly cheekR: THREE.Mesh; - readonly streakL: THREE.Mesh; - readonly streakR: THREE.Mesh; - readonly noseStreak: THREE.Mesh; - readonly mouthBlood: THREE.Mesh; - readonly ribL: THREE.Mesh; - readonly ribR: THREE.Mesh; - readonly bodyStreak: THREE.Mesh; - readonly gloveLMesh: THREE.Mesh; - readonly gloveRMesh: THREE.Mesh; - readonly gloveLMaterial: THREE.MeshStandardMaterial; - readonly gloveRMaterial: THREE.MeshStandardMaterial; - readonly gloveBaseColor: THREE.Color; - readonly skinMaterial: THREE.MeshPhysicalMaterial; - readonly chestDetails: THREE.Object3D[]; - readonly materials: readonly THREE.Material[]; - readonly geometries: readonly THREE.BufferGeometry[]; -} - -const UPPER_ARM = 0.3; -const FOREARM = 0.3; -export const ARM_LENGTHS = { upper: UPPER_ARM, fore: FOREARM } as const; - -function capsule(radius: number, length: number, material: THREE.Material, geometries: THREE.BufferGeometry[]): THREE.Mesh { - const geometry = new THREE.CapsuleGeometry(radius, length, 6, 14); - geometries.push(geometry); - const mesh = new THREE.Mesh(geometry, material); - mesh.castShadow = true; - return mesh; -} - -function sphere(radius: number, material: THREE.Material, geometries: THREE.BufferGeometry[], width = 18, height = 14): THREE.Mesh { - const geometry = new THREE.SphereGeometry(radius, width, height); - geometries.push(geometry); - const mesh = new THREE.Mesh(geometry, material); - mesh.castShadow = true; - return mesh; -} - -function box(width: number, height: number, depth: number, material: THREE.Material, geometries: THREE.BufferGeometry[]): THREE.Mesh { - const geometry = new THREE.BoxGeometry(width, height, depth); - geometries.push(geometry); - const mesh = new THREE.Mesh(geometry, material); - mesh.castShadow = true; - return mesh; -} - -let sharedSkinBump: THREE.CanvasTexture | null = null; - -function skinBumpTexture(): THREE.CanvasTexture { - if (sharedSkinBump !== null) return sharedSkinBump; - const canvas = document.createElement("canvas"); - canvas.width = 128; - canvas.height = 128; - const ctx = canvas.getContext("2d"); - if (ctx !== null) { - ctx.fillStyle = "#808080"; - ctx.fillRect(0, 0, 128, 128); - let seed = 55_444_333; - for (let i = 0; i < 2600; i += 1) { - seed = (seed * 16_807) % 2_147_483_647; - const x = seed % 128; - seed = (seed * 16_807) % 2_147_483_647; - const y = seed % 128; - const shade = 108 + (seed % 40); - ctx.fillStyle = `rgb(${shade},${shade},${shade})`; - ctx.fillRect(x, y, 1 + (seed % 2), 1); - } - } - sharedSkinBump = new THREE.CanvasTexture(canvas); - sharedSkinBump.wrapS = THREE.RepeatWrapping; - sharedSkinBump.wrapT = THREE.RepeatWrapping; - sharedSkinBump.repeat.set(3, 3); - return sharedSkinBump; -} - -export function buildBoxer(palette: FighterPalette): BoxerRig { - const geometries: THREE.BufferGeometry[] = []; - const skin = new THREE.MeshPhysicalMaterial({ color: palette.skin, roughness: 0.58, metalness: 0.02, clearcoat: 0.25, clearcoatRoughness: 0.6, sheen: 0.3, sheenColor: new THREE.Color(0xd9a98c), sheenRoughness: 0.55, bumpMap: skinBumpTexture(), bumpScale: 0.0015 }); - const skinDark = new THREE.MeshStandardMaterial({ color: palette.skinShadow, roughness: 0.58, metalness: 0.02 }); - const trunks = new THREE.MeshStandardMaterial({ color: palette.trunks, roughness: 0.34, metalness: 0.05 }); - const trim = new THREE.MeshStandardMaterial({ color: palette.trunkTrim, roughness: 0.4, metalness: 0.1 }); - const gloveMat = new THREE.MeshStandardMaterial({ color: palette.glove, roughness: 0.28, metalness: 0.04 }); - const gloveTrimMat = new THREE.MeshStandardMaterial({ color: palette.gloveTrim, roughness: 0.45 }); - const hairMat = new THREE.MeshStandardMaterial({ color: palette.hair, roughness: 0.72 }); - const shoeMat = new THREE.MeshStandardMaterial({ color: palette.shoe, roughness: 0.5 }); - const bruiseMat = new THREE.MeshStandardMaterial({ color: 0x4a1c56, roughness: 0.9, transparent: true, opacity: 0 }); - const bruiseMatR = bruiseMat.clone(); - const bodyBruiseMat = bruiseMat.clone(); - const cutMat = new THREE.MeshStandardMaterial({ color: 0x7f0d14, roughness: 0.6, transparent: true, opacity: 0, emissive: 0x2a0306 }); - const cutMatR = cutMat.clone(); - const swellMat = new THREE.MeshStandardMaterial({ color: 0x6b3572, roughness: 0.75, transparent: true, opacity: 0 }); - const swellMatR = swellMat.clone(); - const cheekMat = swellMat.clone(); - const cheekMatR = swellMat.clone(); - const streakMat = new THREE.MeshStandardMaterial({ color: 0x8a0f16, roughness: 0.35, transparent: true, opacity: 0, emissive: 0x30040a }); - const streakMatR = streakMat.clone(); - const noseStreakMat = streakMat.clone(); - const mouthMat = streakMat.clone(); - const ribMat = new THREE.MeshStandardMaterial({ color: 0x5c2450, roughness: 0.85, transparent: true, opacity: 0 }); - const ribMatR = ribMat.clone(); - const bodyStreakMat = streakMat.clone(); - const materials = [skin, skinDark, trunks, trim, gloveMat, gloveTrimMat, hairMat, shoeMat, bruiseMat, bruiseMatR, bodyBruiseMat, cutMat, cutMatR, swellMat, swellMatR, cheekMat, cheekMatR, streakMat, streakMatR, noseStreakMat, mouthMat, ribMat, ribMatR, bodyStreakMat]; - - const root = new THREE.Group(); - root.name = "boxer"; - - const hips = new THREE.Group(); - hips.name = "hips"; - hips.position.y = 0.98; - root.add(hips); - - const pelvis = capsule(0.145, 0.1, trunks, geometries); - pelvis.scale.set(1.18, 1, 0.88); - pelvis.position.y = 0.02; - hips.add(pelvis); - const waistband = new THREE.Mesh(new THREE.CylinderGeometry(0.168, 0.172, 0.035, 18), trim); - geometries.push(waistband.geometry); - waistband.scale.set(1.05, 1, 0.82); - waistband.position.y = 0.1; - waistband.castShadow = true; - hips.add(waistband); - - const spine = new THREE.Group(); - spine.name = "spine"; - spine.position.y = 0.1; - hips.add(spine); - - const chest = new THREE.Group(); - chest.name = "chest"; - spine.add(chest); - - const torsoProfile: Array<[number, number]> = [ - [0.138, -0.13], [0.146, -0.07], [0.128, 0.0], [0.148, 0.06], [0.172, 0.14], - [0.19, 0.22], [0.186, 0.3], [0.152, 0.36], [0.102, 0.42], [0.062, 0.46], - ]; - const torsoGeo = new THREE.LatheGeometry(torsoProfile.map(([r, y]) => new THREE.Vector2(r, y)), 24); - geometries.push(torsoGeo); - const chestMesh = new THREE.Mesh(torsoGeo, skin); - chestMesh.scale.set(1.28, 1, 0.8); - chestMesh.castShadow = true; - chest.add(chestMesh); - const pecL = sphere(0.062, skin, geometries); - pecL.scale.set(1.05, 0.62, 0.42); - pecL.position.set(0.085, 0.26, 0.125); - chest.add(pecL); - const pecR = pecL.clone(); - pecR.position.x = -0.085; - chest.add(pecR); - const deltL = sphere(0.075, skin, geometries); - deltL.scale.set(1.05, 1.1, 0.95); - deltL.position.set(0.215, 0.315, 0); - chest.add(deltL); - const deltR = deltL.clone(); - deltR.position.x = -0.215; - chest.add(deltR); - const chestDetails: THREE.Object3D[] = [pecL, pecR, deltL, deltR]; - - const bodyBruise = sphere(0.1, bodyBruiseMat, geometries); - bodyBruise.scale.set(1.05, 1.35, 0.55); - bodyBruise.position.set(0.02, 0.05, 0.1); - bodyBruise.castShadow = false; - chest.add(bodyBruise); - - const trapL = box(0.13, 0.06, 0.1, skin, geometries); - trapL.position.set(0.115, 0.4, -0.02); - trapL.rotation.z = -0.5; - chest.add(trapL); - const trapR = box(0.13, 0.06, 0.1, skin, geometries); - trapR.position.set(-0.115, 0.4, -0.02); - trapR.rotation.z = 0.5; - chest.add(trapR); - chestDetails.push(trapL, trapR); - - const head = new THREE.Group(); - head.name = "head"; - head.position.y = 0.44; - chest.add(head); - const neck = new THREE.Mesh(new THREE.CylinderGeometry(0.052, 0.062, 0.11, 12), skinDark); - geometries.push(neck.geometry); - neck.position.y = 0.02; - neck.castShadow = true; - head.add(neck); - const skullProfile: Array<[number, number]> = [ - [0.05, 0.02], [0.076, 0.05], [0.096, 0.08], [0.106, 0.13], [0.102, 0.18], [0.072, 0.23], [0.02, 0.26], - ]; - const skullGeo = new THREE.LatheGeometry(skullProfile.map(([r, y]) => new THREE.Vector2(r, y)), 22); - geometries.push(skullGeo); - const headMesh = new THREE.Mesh(skullGeo, skin); - headMesh.scale.set(0.92, 1.05, 0.95); - headMesh.castShadow = true; - head.add(headMesh); - const jaw = sphere(0.085, skin, geometries, 16, 12); - jaw.scale.set(0.85, 0.72, 0.9); - jaw.position.set(0, 0.075, 0.028); - head.add(jaw); - const nose = box(0.032, 0.045, 0.035, skinDark, geometries); - nose.position.set(0, 0.12, 0.112); - head.add(nose); - const noseBridge = box(0.022, 0.05, 0.02, skin, geometries); - noseBridge.position.set(0, 0.16, 0.104); - head.add(noseBridge); - const lips = box(0.045, 0.012, 0.012, skinDark, geometries); - lips.position.set(0, 0.062, 0.104); - head.add(lips); - const chin = sphere(0.04, skin, geometries, 12, 10); - chin.scale.set(0.9, 0.75, 0.8); - chin.position.set(0, 0.035, 0.07); - head.add(chin); - const cheekboneL = sphere(0.028, skin, geometries, 10, 8); - cheekboneL.scale.set(1.1, 0.7, 0.8); - cheekboneL.position.set(0.07, 0.11, 0.075); - head.add(cheekboneL); - const cheekboneR = cheekboneL.clone(); - cheekboneR.position.x = -0.07; - head.add(cheekboneR); - const browL = box(0.052, 0.016, 0.02, skinDark, geometries); - browL.position.set(0.048, 0.165, 0.1); - head.add(browL); - const browR = browL.clone(); - browR.position.x = -0.048; - head.add(browR); - const earL = sphere(0.026, skinDark, geometries, 10, 8); - earL.scale.set(0.5, 1, 0.75); - earL.position.set(0.104, 0.125, 0.01); - head.add(earL); - const earR = earL.clone(); - earR.position.x = -0.104; - head.add(earR); - const eyeMat = new THREE.MeshStandardMaterial({ color: 0x141210, roughness: 0.35 }); - materials.push(eyeMat); - const eyeL = sphere(0.016, eyeMat, geometries, 8, 8); - eyeL.position.set(0.045, 0.145, 0.102); - head.add(eyeL); - const eyeR = eyeL.clone(); - eyeR.position.x = -0.045; - head.add(eyeR); - const hair = sphere(0.118, hairMat, geometries, 20, 14); - hair.scale.set(0.94, 0.98, 1); - hair.position.set(0, 0.165, -0.018); - head.add(hair); - const hairline = sphere(0.112, hairMat, geometries, 18, 12); - hairline.scale.set(0.9, 0.58, 0.92); - hairline.position.set(0, 0.2, 0.005); - head.add(hairline); - - const bruiseL = sphere(0.042, bruiseMat, geometries, 12, 10); - bruiseL.scale.set(1, 0.72, 0.5); - bruiseL.position.set(0.05, 0.15, 0.085); - bruiseL.castShadow = false; - head.add(bruiseL); - const bruiseR = sphere(0.042, bruiseMatR, geometries, 12, 10); - bruiseR.scale.set(1, 0.72, 0.5); - bruiseR.position.set(-0.05, 0.15, 0.085); - bruiseR.castShadow = false; - head.add(bruiseR); - const cutL = box(0.05, 0.008, 0.01, cutMat, geometries); - cutL.position.set(0.05, 0.178, 0.104); - cutL.castShadow = false; - head.add(cutL); - const cutR = box(0.05, 0.008, 0.01, cutMatR, geometries); - cutR.position.set(-0.05, 0.178, 0.104); - cutR.castShadow = false; - head.add(cutR); - - const swellL = sphere(0.035, swellMat, geometries, 12, 10); - swellL.position.set(0.052, 0.155, 0.088); - swellL.castShadow = false; - head.add(swellL); - const swellR = sphere(0.035, swellMatR, geometries, 12, 10); - swellR.position.set(-0.052, 0.155, 0.088); - swellR.castShadow = false; - head.add(swellR); - const cheekL = sphere(0.028, cheekMat, geometries, 10, 8); - cheekL.position.set(0.068, 0.095, 0.075); - cheekL.castShadow = false; - head.add(cheekL); - const cheekR = sphere(0.028, cheekMatR, geometries, 10, 8); - cheekR.position.set(-0.068, 0.095, 0.075); - cheekR.castShadow = false; - head.add(cheekR); - const streakL = box(0.014, 0.1, 0.006, streakMat, geometries); - streakL.position.set(0.052, 0.115, 0.106); - streakL.castShadow = false; - head.add(streakL); - const streakR = box(0.014, 0.1, 0.006, streakMatR, geometries); - streakR.position.set(-0.052, 0.115, 0.106); - streakR.castShadow = false; - head.add(streakR); - const noseStreak = box(0.011, 0.07, 0.006, noseStreakMat, geometries); - noseStreak.position.set(0.008, 0.075, 0.118); - noseStreak.castShadow = false; - head.add(noseStreak); - const mouthBlood = box(0.03, 0.012, 0.006, mouthMat, geometries); - mouthBlood.position.set(0.02, 0.052, 0.104); - mouthBlood.castShadow = false; - head.add(mouthBlood); - - const ribL = sphere(0.09, ribMat, geometries, 12, 10); - ribL.scale.set(0.5, 1.2, 0.7); - ribL.position.set(0.16, 0.08, 0.02); - ribL.castShadow = false; - chest.add(ribL); - const ribR = sphere(0.09, ribMatR, geometries, 12, 10); - ribR.scale.set(0.5, 1.2, 0.7); - ribR.position.set(-0.16, 0.08, 0.02); - ribR.castShadow = false; - chest.add(ribR); - const bodyStreak = box(0.05, 0.24, 0.008, bodyStreakMat, geometries); - bodyStreak.position.set(0.03, 0.08, 0.155); - bodyStreak.rotation.z = 0.12; - bodyStreak.castShadow = false; - chest.add(bodyStreak); - - const buildArm = (side: 1 | -1): { shoulder: THREE.Group; elbow: THREE.Group; glove: THREE.Group; gloveMesh: THREE.Mesh } => { - const shoulder = new THREE.Group(); - shoulder.name = side === 1 ? "shoulderL" : "shoulderR"; - shoulder.position.set(0.215 * side, 0.315, 0); - chest.add(shoulder); - const upper = capsule(0.056, UPPER_ARM - 0.12, skin, geometries); - upper.scale.set(1.16, 1, 1.16); - upper.position.y = -UPPER_ARM / 2; - shoulder.add(upper); - const elbow = new THREE.Group(); - elbow.name = side === 1 ? "elbowL" : "elbowR"; - elbow.position.y = -UPPER_ARM; - shoulder.add(elbow); - const elbowJoint = sphere(0.048, skin, geometries, 12, 10); - elbow.add(elbowJoint); - const fore = capsule(0.048, FOREARM - 0.13, skin, geometries); - fore.scale.set(1.1, 1, 0.92); - fore.position.y = -FOREARM / 2 + 0.01; - elbow.add(fore); - const glove = new THREE.Group(); - glove.name = side === 1 ? "gloveL" : "gloveR"; - glove.position.y = -FOREARM; - elbow.add(glove); - const cuff = new THREE.Mesh(new THREE.CylinderGeometry(0.055, 0.062, 0.07, 12), gloveTrimMat); - geometries.push(cuff.geometry); - cuff.position.y = 0.01; - cuff.castShadow = true; - glove.add(cuff); - const gloveMesh = sphere(0.088, gloveMat, geometries, 18, 14); - gloveMesh.scale.set(1, 1.12, 1.38); - gloveMesh.position.set(0, -0.05, 0.02); - glove.add(gloveMesh); - const thumb = sphere(0.032, gloveMat, geometries, 10, 8); - thumb.position.set(-0.05 * side, -0.045, 0.075); - glove.add(thumb); - const lace = box(0.05, 0.008, 0.012, gloveTrimMat, geometries); - lace.position.set(0, -0.028, 0.1); - glove.add(lace); - return { shoulder, elbow, glove, gloveMesh }; - }; - const armL = buildArm(1); - const armR = buildArm(-1); - - const buildLeg = (side: 1 | -1): { hip: THREE.Group; knee: THREE.Group; ankle: THREE.Group } => { - const hip = new THREE.Group(); - hip.name = side === 1 ? "hipL" : "hipR"; - hip.position.set(0.105 * side, -0.02, 0); - hips.add(hip); - const thigh = capsule(0.078, 0.24, skin, geometries); - thigh.scale.set(1.14, 1, 1.08); - thigh.position.y = -0.21; - hip.add(thigh); - const trunkLeg = capsule(0.092, 0.16, trunks, geometries); - trunkLeg.position.y = -0.14; - hip.add(trunkLeg); - const hem = new THREE.Mesh(new THREE.CylinderGeometry(0.096, 0.1, 0.03, 14), trim); - geometries.push(hem.geometry); - hem.position.y = -0.24; - hem.castShadow = true; - hip.add(hem); - const knee = new THREE.Group(); - knee.name = side === 1 ? "kneeL" : "kneeR"; - knee.position.y = -0.44; - hip.add(knee); - const kneeJoint = sphere(0.06, skin, geometries, 12, 10); - kneeJoint.scale.set(0.95, 1.05, 1); - knee.add(kneeJoint); - const shin = capsule(0.058, 0.24, skin, geometries); - shin.scale.set(1.05, 1, 1.12); - shin.position.y = -0.21; - knee.add(shin); - const ankle = new THREE.Group(); - ankle.name = side === 1 ? "ankleL" : "ankleR"; - ankle.position.y = -0.44; - knee.add(ankle); - const shoe = box(0.1, 0.075, 0.3, shoeMat, geometries); - shoe.position.set(0, -0.035, 0.06); - ankle.add(shoe); - const toe = sphere(0.05, shoeMat, geometries, 10, 8); - toe.scale.set(0.95, 0.62, 1); - toe.position.set(0, -0.055, 0.2); - ankle.add(toe); - const sock = new THREE.Mesh(new THREE.CylinderGeometry(0.052, 0.058, 0.08, 10), shoeMat); - geometries.push(sock.geometry); - sock.position.y = 0.01; - sock.castShadow = true; - ankle.add(sock); - return { hip, knee, ankle }; - }; - const legL = buildLeg(1); - const legR = buildLeg(-1); - - return { - root, - hips, - spine, - chest, - head, - shoulderL: armL.shoulder, - elbowL: armL.elbow, - gloveL: armL.glove, - shoulderR: armR.shoulder, - elbowR: armR.elbow, - gloveR: armR.glove, - hipL: legL.hip, - kneeL: legL.knee, - ankleL: legL.ankle, - hipR: legR.hip, - kneeR: legR.knee, - ankleR: legR.ankle, - chestMesh, - headMesh, - browL, - browR, - bruiseL, - bruiseR, - bodyBruise, - cutL, - cutR, - swellL, - swellR, - cheekL, - cheekR, - streakL, - streakR, - noseStreak, - mouthBlood, - ribL, - ribR, - bodyStreak, - gloveLMesh: armL.gloveMesh, - gloveRMesh: armR.gloveMesh, - gloveLMaterial: gloveMat, - gloveRMaterial: gloveMat, - gloveBaseColor: new THREE.Color(palette.glove), - skinMaterial: skin, - chestDetails, - materials, - geometries, - }; -} - -const scratchS = new THREE.Vector3(); -const scratchT = new THREE.Vector3(); -const scratchDir = new THREE.Vector3(); -const scratchBend = new THREE.Vector3(); -const scratchElbow = new THREE.Vector3(); -const scratchPole = new THREE.Vector3(); -const downAxis = new THREE.Vector3(0, -1, 0); -const scratchClamped = new THREE.Vector3(); - -export function solveArm( - shoulderWorld: THREE.Vector3, - targetWorld: THREE.Vector3, - pole: THREE.Vector3, - out: { elbowWorld: THREE.Vector3; targetWorld: THREE.Vector3 }, - maximumReach = UPPER_ARM + FOREARM + 0.06 - 0.015, -): void { - const l1 = UPPER_ARM; - const l2 = FOREARM + 0.06; - scratchS.copy(shoulderWorld); - scratchT.copy(targetWorld); - scratchDir.subVectors(scratchT, scratchS); - const distance = THREE.MathUtils.clamp(scratchDir.length(), 0.12, maximumReach); - scratchDir.normalize(); - const a = (l1 * l1 - l2 * l2 + distance * distance) / (2 * distance); - const h = Math.sqrt(Math.max(0.0001, l1 * l1 - a * a)); - scratchPole.copy(pole).normalize(); - scratchBend.copy(scratchPole).addScaledVector(scratchDir, -scratchPole.dot(scratchDir)); - if (scratchBend.lengthSq() < 0.0001) scratchBend.set(0, -1, 0).addScaledVector(scratchDir, scratchDir.y); - scratchBend.normalize(); - scratchElbow.copy(scratchS).addScaledVector(scratchDir, a).addScaledVector(scratchBend, h); - out.elbowWorld.copy(scratchElbow); - scratchClamped.copy(scratchS).addScaledVector(scratchDir, distance); - out.targetWorld.copy(scratchClamped); -} - -const boneDir = new THREE.Vector3(); -const parentWorldQuat = new THREE.Quaternion(); -const worldQuat = new THREE.Quaternion(); - -export function aimBone(joint: THREE.Object3D, fromWorld: THREE.Vector3, toWorld: THREE.Vector3, twist = 0): void { - boneDir.subVectors(toWorld, fromWorld); - if (boneDir.lengthSq() < 0.000001) return; - boneDir.normalize(); - worldQuat.setFromUnitVectors(downAxis, boneDir); - if (twist !== 0) { - const twistQuat = new THREE.Quaternion().setFromAxisAngle(boneDir, twist); - worldQuat.premultiply(twistQuat); - } - const parent = joint.parent; - if (parent === null) { - joint.quaternion.copy(worldQuat); - return; - } - parent.getWorldQuaternion(parentWorldQuat); - joint.quaternion.copy(parentWorldQuat.invert().multiply(worldQuat)); -} - -export function buildReferee(): BoxerRig { - const palette = { - skin: 0xc79b76, - skinShadow: 0xa87c5c, - trunks: 0x14161c, - trunkTrim: 0x14161c, - glove: 0xc79b76, - gloveTrim: 0xe8e9ec, - hair: 0x2b2320, - shoe: 0x101114, - } satisfies FighterPalette; - const rig = buildBoxer(palette); - for (const detail of rig.chestDetails) detail.visible = false; - const shirt = new THREE.MeshStandardMaterial({ color: 0xbfc5cf, roughness: 0.72 }); - const pants = new THREE.MeshStandardMaterial({ color: 0x14161c, roughness: 0.7 }); - const shirtProfile: Array<[number, number]> = [ - [0.155, -0.2], [0.16, -0.13], [0.158, -0.07], [0.148, 0.0], [0.162, 0.06], [0.186, 0.14], - [0.204, 0.22], [0.2, 0.3], [0.164, 0.36], [0.11, 0.42], [0.066, 0.46], - ]; - const shirtGeo = new THREE.LatheGeometry(shirtProfile.map(([r, y]) => new THREE.Vector2(r, y)), 24); - const shirtTorso = new THREE.Mesh(shirtGeo, shirt); - shirtTorso.scale.set(1.28, 1, 0.84); - shirtTorso.castShadow = true; - rig.chest.add(shirtTorso); - const collar = new THREE.Mesh(new THREE.CylinderGeometry(0.07, 0.09, 0.05, 12), shirt); - collar.position.y = 0.44; - rig.chest.add(collar); - const bowtie = new THREE.Mesh(new THREE.BoxGeometry(0.07, 0.025, 0.02), pants); - bowtie.position.set(0, 0.42, 0.1); - rig.chest.add(bowtie); - const addedGeometries: THREE.BufferGeometry[] = [shirtTorso.geometry, collar.geometry, bowtie.geometry]; - for (const shoulder of [rig.shoulderL, rig.shoulderR]) { - const sleeve = new THREE.Mesh(new THREE.CapsuleGeometry(0.066, 0.24, 4, 10), shirt); - sleeve.position.y = -0.17; - sleeve.castShadow = true; - shoulder.add(sleeve); - addedGeometries.push(sleeve.geometry); - } - for (const hip of [rig.hipL, rig.hipR]) { - const pantLeg = new THREE.Mesh(new THREE.CapsuleGeometry(0.088, 0.26, 4, 10), pants); - pantLeg.position.y = -0.21; - pantLeg.castShadow = true; - hip.add(pantLeg); - addedGeometries.push(pantLeg.geometry); - } - for (const knee of [rig.kneeL, rig.kneeR]) { - const pantShin = new THREE.Mesh(new THREE.CapsuleGeometry(0.066, 0.26, 4, 10), pants); - pantShin.position.y = -0.21; - pantShin.castShadow = true; - knee.add(pantShin); - addedGeometries.push(pantShin.geometry); - } - (rig.geometries as THREE.BufferGeometry[]).push(...addedGeometries); - (rig.materials as THREE.Material[]).push(shirt, pants); - return rig; -} - -export function disposeBoxer(rig: BoxerRig): void { - for (const geometry of rig.geometries) geometry.dispose(); - for (const material of rig.materials) material.dispose(); -} - diff --git a/web/hands/src/render/camera.ts b/web/hands/src/render/camera.ts index 0d923c06..782c7e3c 100644 --- a/web/hands/src/render/camera.ts +++ b/web/hands/src/render/camera.ts @@ -1,14 +1,56 @@ import * as THREE from "three"; -const BASE_HEIGHT = 1.88; -const BASE_DISTANCE = 7.15; -const LOOK_HEIGHT = 1.12; +const BASE_HEIGHT = 2.05; +const BASE_DISTANCE = 5.5; +const LOOK_HEIGHT = 1.05; export interface CameraFrame { readonly position: THREE.Vector3; readonly lookAt: THREE.Vector3; } +export const CORNER_SHOT_LEAD_SECONDS = 2.5; +export const CORNER_SHOT_TAIL_SECONDS = 2; +export const CORNER_SHOT_SECONDS = 5.5; + +/** Which corner the broadcast cuts to during the rest, or null for the wide shot while the fighters walk over and before the bell. */ +export function cornerShot(elapsedSeconds: number, remainingSeconds: number, firstCorner: 0 | 1): 0 | 1 | null { + if (elapsedSeconds < CORNER_SHOT_LEAD_SECONDS || remainingSeconds < CORNER_SHOT_TAIL_SECONDS) return null; + const segment = Math.floor((elapsedSeconds - CORNER_SHOT_LEAD_SECONDS) / CORNER_SHOT_SECONDS); + return ((firstCorner + segment) % 2) as 0 | 1; +} + +/** Seconds into the current corner shot, for its slow drift. */ +export function cornerShotProgress(elapsedSeconds: number): number { + return Math.max(0, elapsedSeconds - CORNER_SHOT_LEAD_SECONDS) % CORNER_SHOT_SECONDS; +} + +export const CUTMAN_WORK_DISTANCE = 0.95; +export const CUTMAN_WORK_DEGREES = 32; +const CORNER_CAMERA_DISTANCE = 2.6; +const CORNER_CAMERA_DEGREES = -25; + +/** + * Point `distance` metres from a corner stool, swung `degrees` off the diagonal the seated fighter + * faces (positive toward the fighter's left). `corner` is the stool's distance from centre along each axis. + */ +export function cornerPoint(index: 0 | 1, corner: number, distance: number, degrees: number, out: THREE.Vector3): THREE.Vector3 { + const sign = index === 0 ? -1 : 1; + const angle = (degrees * Math.PI) / 180; + const forwardX = -sign * Math.SQRT1_2; + const forwardZ = sign * Math.SQRT1_2; + const x = forwardX * Math.cos(angle) + forwardZ * Math.sin(angle); + const z = -forwardX * Math.sin(angle) + forwardZ * Math.cos(angle); + return out.set(sign * corner + x * distance, 0, -sign * corner + z * distance); +} + +/** Three-quarter shot from inside the ropes: the cutman works from the fighter's left, the camera shoots from the right. */ +export function cornerFrame(index: 0 | 1, corner: number, shotSeconds: number, position: THREE.Vector3, lookAt: THREE.Vector3): void { + const drift = Math.min(1, shotSeconds / CORNER_SHOT_SECONDS) * 5; + cornerPoint(index, corner, CORNER_CAMERA_DISTANCE, CORNER_CAMERA_DEGREES + drift, position).setY(1.45); + cornerPoint(index, corner, 0.62, 27, lookAt).setY(1.05); +} + export class CameraDirector { private readonly current = new THREE.Vector3(0, BASE_HEIGHT, BASE_DISTANCE); private readonly look = new THREE.Vector3(0, LOOK_HEIGHT, 0); @@ -30,8 +72,8 @@ export class CameraDirector { const clampedX = THREE.MathUtils.clamp(midX, -1.4, 1.4); const clampedZ = THREE.MathUtils.clamp(midZ, -1.1, 1.1); - const distance = THREE.MathUtils.clamp(BASE_DISTANCE + separation * 0.42 - (knockdown ? 1.1 : 0), 6.4, 9.8); - const height = BASE_HEIGHT + separation * 0.1 - (knockdown ? 0.35 : 0); + const distance = THREE.MathUtils.clamp(BASE_DISTANCE + separation * 0.6 - (knockdown ? 0.9 : 0), 4.6, 8.4); + const height = BASE_HEIGHT + separation * 0.08 - (knockdown ? 0.45 : 0); const sway = reducedMotion ? 0 : Math.sin(this.swayPhase * 0.21) * 0.35; const drift = reducedMotion ? 0 : Math.sin(this.swayPhase * 0.13) * 0.3; @@ -45,7 +87,7 @@ export class CameraDirector { this.current.z += (targetZ - this.current.z) * (1 - Math.exp(-followRate * dt)); this.look.x += (clampedX - this.look.x) * (1 - Math.exp(-3.2 * dt)); - this.look.y += ((knockdown ? 0.75 : LOOK_HEIGHT) - this.look.y) * (1 - Math.exp(-3.2 * dt)); + this.look.y += ((knockdown ? 0.7 : LOOK_HEIGHT) - this.look.y) * (1 - Math.exp(-3.2 * dt)); this.look.z += (clampedZ * 0.6 - this.look.z) * (1 - Math.exp(-3.2 * dt)); if (!reducedMotion && shake > 0.0005) { diff --git a/web/hands/src/render/effects.ts b/web/hands/src/render/effects.ts index 37d9ecc3..41991e20 100644 --- a/web/hands/src/render/effects.ts +++ b/web/hands/src/render/effects.ts @@ -24,6 +24,13 @@ interface Droplet { life: number; maxLife: number; r: number; g: number; b: number; + radius: number; +} + +export interface BakedPart { + readonly geometry: THREE.BufferGeometry; + readonly map: THREE.Texture | null; + readonly color: number; } interface Mist { @@ -44,10 +51,15 @@ interface Gib { scale: number; bounces: number; stained: boolean; + tooth: boolean; } interface SeveredHead { readonly mesh: THREE.Mesh; + readonly defaultGeometry: THREE.BufferGeometry; + readonly defaultScale: THREE.Vector3; + readonly cap: THREE.Mesh; + baked: THREE.BufferGeometry | null; readonly radius: number; active: boolean; moving: boolean; @@ -64,7 +76,7 @@ interface Stump { fountainLife: number; accumulator: number; seed: number; - direction: number; + direction: SprayDirection; } interface DripEmitter { @@ -81,6 +93,21 @@ const seeded = (seed: number): (() => number) => () => { }; const finite = (value: number, fallback = 0): number => Number.isFinite(value) ? value : fallback; + +/** Horizontal world direction (x and z) a spray flies in. */ +export interface SprayDirection { + readonly x: number; + readonly z: number; +} + +/** A spray direction as a unit vector; a bare number is the world-x sign that hit events carry. */ +function unitSpray(direction: number | SprayDirection): SprayDirection { + if (typeof direction === "number") return { x: direction < 0 ? -1 : 1, z: 0 }; + const length = Math.hypot(direction.x, direction.z); + return Number.isFinite(length) && length > 1e-6 ? { x: direction.x / length, z: direction.z / length } : { x: 1, z: 0 }; +} + +const unitY = new THREE.Vector3(0, 1, 0); const safeStep = (dt: number): number => Number.isFinite(dt) ? THREE.MathUtils.clamp(dt, 0, MAX_STEP) : 0; const IMPACT_KINDS = new Set(["hit", "counter_hit", "block", "perfect_block", "guard_break", "knockdown", "bleed"]); @@ -103,6 +130,39 @@ function copyFiniteQuaternion(target: THREE.Quaternion, source: THREE.Quaternion else target.normalize(); } +function splatTexture(seed: number): THREE.CanvasTexture { + const canvas = document.createElement("canvas"); + canvas.width = 128; + canvas.height = 128; + const ctx = canvas.getContext("2d"); + if (ctx !== null) { + const rand = seeded(seed); + ctx.clearRect(0, 0, 128, 128); + ctx.fillStyle = "rgba(255,255,255,1)"; + const blobs = 7 + Math.floor(rand() * 6); + for (let i = 0; i < blobs; i += 1) { + const angle = rand() * Math.PI * 2; + const distance = i === 0 ? 0 : 8 + rand() * 40; + const radius = i === 0 ? 24 + rand() * 12 : 3 + rand() * 12; + ctx.globalAlpha = i === 0 ? 1 : 0.7 + rand() * 0.3; + ctx.beginPath(); + ctx.ellipse(64 + Math.cos(angle) * distance, 64 + Math.sin(angle) * distance, radius, radius * (0.55 + rand() * 0.5), rand() * Math.PI, 0, Math.PI * 2); + ctx.fill(); + } + ctx.globalAlpha = 1; + for (let i = 0; i < 12; i += 1) { + const angle = rand() * Math.PI * 2; + const distance = 30 + rand() * 30; + ctx.beginPath(); + ctx.arc(64 + Math.cos(angle) * distance, 64 + Math.sin(angle) * distance, 1 + rand() * 3, 0, Math.PI * 2); + ctx.fill(); + } + } + const texture = new THREE.CanvasTexture(canvas); + texture.colorSpace = THREE.NoColorSpace; + return texture; +} + function mistTexture(): THREE.CanvasTexture { const canvas = document.createElement("canvas"); canvas.width = 64; @@ -120,13 +180,22 @@ function mistTexture(): THREE.CanvasTexture { } export class Effects3D { - readonly points: THREE.Points; + readonly dropletMesh: THREE.InstancedMesh; private readonly droplets: Droplet[] = []; private readonly dropletPositions: Float32Array; private readonly dropletColors: Float32Array; - private readonly dropletGeometry: THREE.BufferGeometry; - private readonly dropletMaterial: THREE.PointsMaterial; + readonly dropletBuffers: { readonly position: THREE.BufferAttribute; readonly color: THREE.BufferAttribute }; + private readonly dropletGeometry: THREE.SphereGeometry; + private readonly dropletMaterial: THREE.MeshStandardMaterial; + private readonly dropletMatrix = new THREE.Matrix4(); + private readonly dropletQuaternion = new THREE.Quaternion(); + private readonly dropletScale = new THREE.Vector3(); + private readonly dropletVelocity = new THREE.Vector3(); + private readonly dropletColor = new THREE.Color(); + private readonly splatMaps: THREE.CanvasTexture[] = []; private dropletIndex = 0; + /** Live droplets fill the front of the pool, and only they are drawn and uploaded. */ + private liveDroplets = 0; readonly mistPoints: THREE.Points; private readonly mists: Mist[] = []; @@ -138,12 +207,13 @@ export class Effects3D { private mistIndex = 0; private readonly decals: THREE.Mesh[] = []; - private readonly decalGeometry: THREE.CircleGeometry; + private readonly decalGeometry: THREE.PlaneGeometry; private decalIndex = 0; private readonly gibGeometry: THREE.IcosahedronGeometry; private readonly gibMaterial: THREE.MeshStandardMaterial; private readonly gibMesh: THREE.InstancedMesh; + private readonly gibColor = new THREE.Color(); private readonly gibs: Gib[] = []; private gibIndex = 0; private readonly gibMatrix = new THREE.Matrix4(); @@ -178,17 +248,27 @@ export class Effects3D { constructor(private readonly scene: THREE.Scene) { this.dropletPositions = new Float32Array(MAX_DROPLETS * 3); this.dropletColors = new Float32Array(MAX_DROPLETS * 3); - this.dropletGeometry = new THREE.BufferGeometry(); - this.dropletGeometry.setAttribute("position", new THREE.BufferAttribute(this.dropletPositions, 3)); - this.dropletGeometry.setAttribute("color", new THREE.BufferAttribute(this.dropletColors, 3)); - this.dropletMaterial = new THREE.PointsMaterial({ size: 0.038, vertexColors: true, transparent: true, opacity: 0.96, depthWrite: false, sizeAttenuation: true }); - this.points = new THREE.Points(this.dropletGeometry, this.dropletMaterial); - this.points.frustumCulled = false; - scene.add(this.points); + this.dropletBuffers = { + position: new THREE.BufferAttribute(this.dropletPositions, 3), + color: new THREE.BufferAttribute(this.dropletColors, 3), + }; + this.dropletGeometry = new THREE.SphereGeometry(1, 7, 5); + this.dropletMaterial = new THREE.MeshStandardMaterial({ color: 0xffffff, roughness: 0.22, metalness: 0.02 }); + this.dropletMesh = new THREE.InstancedMesh(this.dropletGeometry, this.dropletMaterial, MAX_DROPLETS); + this.dropletMesh.instanceMatrix.setUsage(THREE.DynamicDrawUsage); + this.dropletMesh.frustumCulled = false; + this.dropletMesh.castShadow = false; + scene.add(this.dropletMesh); for (let i = 0; i < MAX_DROPLETS; i += 1) { - this.droplets.push({ alive: false, blood: false, x: 0, y: -50, z: 0, vx: 0, vy: 0, vz: 0, life: 0, maxLife: 1, r: 1, g: 1, b: 1 }); + this.droplets.push({ alive: false, blood: false, x: 0, y: -50, z: 0, vx: 0, vy: 0, vz: 0, life: 0, maxLife: 1, r: 1, g: 1, b: 1, radius: 0.012 }); this.dropletPositions[i * 3 + 1] = -50; + this.dropletMesh.setColorAt(i, this.dropletColor.setRGB(0.5, 0.02, 0.04)); + this.writeDropletMatrix(i, this.droplets[i]!); } + this.dropletMesh.instanceColor?.setUsage(THREE.DynamicDrawUsage); + this.dropletMesh.instanceMatrix.needsUpdate = true; + this.dropletMesh.count = 0; + for (let i = 0; i < 4; i += 1) this.splatMaps.push(splatTexture(0x3a1f_00d1 + i * 977)); this.mistPositions = new Float32Array(MAX_MIST * 3); this.mistColors = new Float32Array(MAX_MIST * 3); @@ -205,9 +285,9 @@ export class Effects3D { this.mistPositions[i * 3 + 1] = -50; } - this.decalGeometry = new THREE.CircleGeometry(0.09, 12); + this.decalGeometry = new THREE.PlaneGeometry(0.2, 0.2); for (let i = 0; i < MAX_DECALS; i += 1) { - const decal = new THREE.Mesh(this.decalGeometry, new THREE.MeshBasicMaterial({ color: 0x6e0d13, transparent: true, opacity: 0.42, depthWrite: false })); + const decal = new THREE.Mesh(this.decalGeometry, new THREE.MeshStandardMaterial({ color: 0x6e0d13, map: this.splatMaps[i % this.splatMaps.length]!, alphaMap: this.splatMaps[i % this.splatMaps.length]!, transparent: true, opacity: 0.42, depthWrite: false, roughness: 0.25, metalness: 0 })); decal.rotation.x = -Math.PI / 2; decal.position.y = CANVAS_TOP + 0.004 + i * 0.00015; decal.visible = false; @@ -222,8 +302,9 @@ export class Effects3D { this.gibMesh.frustumCulled = false; scene.add(this.gibMesh); for (let i = 0; i < MAX_GIBS; i += 1) { - const gib: Gib = { alive: false, x: 0, y: -50, z: 0, vx: 0, vy: 0, vz: 0, rx: 0, ry: 0, rz: 0, vrx: 0, vry: 0, vrz: 0, life: 0, scale: 0, bounces: 0, stained: false }; + const gib: Gib = { alive: false, x: 0, y: -50, z: 0, vx: 0, vy: 0, vz: 0, rx: 0, ry: 0, rz: 0, vrx: 0, vry: 0, vrz: 0, life: 0, scale: 0, bounces: 0, stained: false, tooth: false }; this.gibs.push(gib); + this.gibMesh.setColorAt(i, this.gibColor.setHex(0xffffff)); this.writeGibMatrix(i, gib); } this.gibMesh.instanceMatrix.needsUpdate = true; @@ -241,12 +322,17 @@ export class Effects3D { headMesh.castShadow = true; headMesh.visible = false; scene.add(headMesh); - this.heads.push({ mesh: headMesh, radius: HEAD_RADIUS, active: false, moving: false, eventId: null, vx: 0, vy: 0, vz: 0, vrx: 0, vry: 0, vrz: 0, bounces: 0, stained: false }); + const cap = new THREE.Mesh(new THREE.CircleGeometry(0.058, 14), this.stumpMaterial); + cap.rotation.x = Math.PI / 2; + cap.position.y = -0.1; + cap.visible = false; + headMesh.add(cap); + this.heads.push({ mesh: headMesh, defaultGeometry: this.headGeometry, defaultScale: headMesh.scale.clone(), cap, baked: null, radius: HEAD_RADIUS, active: false, moving: false, eventId: null, vx: 0, vy: 0, vz: 0, vrx: 0, vry: 0, vrz: 0, bounces: 0, stained: false }); const stumpMesh = new THREE.Mesh(this.stumpGeometry, this.stumpMaterial); stumpMesh.visible = false; scene.add(stumpMesh); - this.stumps.push({ mesh: stumpMesh, active: false, fountainLife: 0, accumulator: 0, seed: 1, direction: 1 }); + this.stumps.push({ mesh: stumpMesh, active: false, fountainLife: 0, accumulator: 0, seed: 1, direction: { x: 1, z: 0 } }); } for (let index = 0; index < MAX_HANDS; index += 1) { const material = new THREE.MeshStandardMaterial({ color: 0x1d4ed8, roughness: 0.38, metalness: 0.03 }); @@ -256,15 +342,29 @@ export class Effects3D { handMesh.castShadow = true; handMesh.visible = false; scene.add(handMesh); - this.hands.push({ mesh: handMesh, radius: HAND_RADIUS, active: false, moving: false, eventId: null, vx: 0, vy: 0, vz: 0, vrx: 0, vry: 0, vrz: 0, bounces: 0, stained: false }); + const cap = new THREE.Mesh(new THREE.CircleGeometry(0.04, 12), this.stumpMaterial); + cap.rotation.x = Math.PI / 2; + cap.position.y = 0.02; + cap.visible = false; + handMesh.add(cap); + this.hands.push({ mesh: handMesh, defaultGeometry: this.handGeometry, defaultScale: handMesh.scale.clone(), cap, baked: null, radius: HAND_RADIUS, active: false, moving: false, eventId: null, vx: 0, vy: 0, vz: 0, vrx: 0, vry: 0, vrz: 0, bounces: 0, stained: false }); const stumpMesh = new THREE.Mesh(this.wristStumpGeometry, this.stumpMaterial); stumpMesh.visible = false; scene.add(stumpMesh); - this.handStumps.push({ mesh: stumpMesh, active: false, fountainLife: 0, accumulator: 0, seed: 1, direction: 1 }); + this.handStumps.push({ mesh: stumpMesh, active: false, fountainLife: 0, accumulator: 0, seed: 1, direction: { x: 1, z: 0 } }); } } + /** + * Stand-ins sharing the hidden pools' geometry and materials (blood on the canvas, severed parts and + * their stumps), so their shaders can be compiled ahead of the first bloody hit instead of inside it. + */ + compileStandIns(): THREE.Mesh[] { + const hidden = [this.decals[0]!, this.heads[0]!.mesh, this.hands[0]!.mesh, this.stumps[0]!.mesh, this.handStumps[0]!.mesh]; + return hidden.map((mesh) => new THREE.Mesh(mesh.geometry, mesh.material)); + } + setBloodLevel(level: BloodLevel): void { if (level === this.bloodLevel) return; const previous = this.bloodLevel; @@ -300,6 +400,14 @@ export class Effects3D { return this.heads.filter((head) => head.active).length; } + /** Copies the world position of a fighter's severed head into `out`; false when the head is still on. */ + severedHeadPosition(fighterIndex: number, out: THREE.Vector3): boolean { + const head = this.heads[Math.trunc(fighterIndex)]; + if (head === undefined || !head.active) return false; + out.copy(head.mesh.position); + return true; + } + get activeHands(): number { return this.hands.filter((hand) => hand.active).length; } @@ -308,12 +416,13 @@ export class Effects3D { return [...this.stumps, ...this.handStumps].filter((stump) => stump.active).length; } - private spawnDroplet(x: number, y: number, z: number, vx: number, vy: number, vz: number, color: { r: number; g: number; b: number }, life: number, blood: boolean): void { - const index = this.dropletIndex % MAX_DROPLETS; - this.dropletIndex += 1; + private spawnDroplet(x: number, y: number, z: number, vx: number, vy: number, vz: number, color: { r: number; g: number; b: number }, life: number, blood: boolean, radius = blood ? 0.006 + this.ambientRandom() * 0.009 : 0.004 + this.ambientRandom() * 0.004): void { + // A new droplet joins the live ones at the front; a full pool reuses its slots in turn. + const index = this.liveDroplets < MAX_DROPLETS ? this.liveDroplets++ : this.dropletIndex++ % MAX_DROPLETS; const droplet = this.droplets[index]!; droplet.alive = true; droplet.blood = blood; + droplet.radius = radius; droplet.x = finite(x); droplet.y = finite(y, 1); droplet.z = finite(z); @@ -331,8 +440,67 @@ export class Effects3D { this.dropletColors[index * 3] = droplet.r; this.dropletColors[index * 3 + 1] = droplet.g; this.dropletColors[index * 3 + 2] = droplet.b; - this.dropletGeometry.attributes.position!.needsUpdate = true; - this.dropletGeometry.attributes.color!.needsUpdate = true; + this.dropletMesh.setColorAt(index, this.dropletColor.setRGB(droplet.r, droplet.g, droplet.b)); + this.writeDropletMatrix(index, droplet); + this.uploadDroplets(index, index + 1, true); + } + + /** Draws only the live droplets and uploads the instances from `from` up to `to`. */ + private uploadDroplets(from: number, to: number, colors: boolean): void { + this.dropletMesh.count = this.liveDroplets; + if (to <= from) return; + this.dropletMesh.instanceMatrix.addUpdateRange(from * 16, (to - from) * 16); + this.dropletMesh.instanceMatrix.needsUpdate = true; + const instanceColor = this.dropletMesh.instanceColor; + if (!colors || instanceColor === null) return; + instanceColor.addUpdateRange(from * 3, (to - from) * 3); + instanceColor.needsUpdate = true; + } + + /** Retires the droplet in slot `index` and moves the last live droplet into its place. */ + private retireDroplet(index: number): void { + const last = this.liveDroplets - 1; + const retired = this.droplets[index]!; + retired.alive = false; + this.liveDroplets = last; + if (index !== last) { + const moved = this.droplets[last]!; + this.droplets[index] = moved; + this.droplets[last] = retired; + this.dropletPositions.copyWithin(index * 3, last * 3, last * 3 + 3); + this.dropletColors.copyWithin(index * 3, last * 3, last * 3 + 3); + this.dropletMesh.setColorAt(index, this.dropletColor.setRGB(moved.r, moved.g, moved.b)); + this.writeDropletMatrix(index, moved); + } + this.dropletPositions[last * 3 + 1] = -50; + this.writeDropletMatrix(last, retired); + } + + /** Spawns a droplet whose horizontal velocity is given along the spray and across it. */ + private sprayDroplet(spray: SprayDirection, x: number, y: number, z: number, along: number, vy: number, across: number, color: { r: number; g: number; b: number }, life: number, blood: boolean): void { + this.spawnDroplet(x, y, z, along * spray.x - across * spray.z, vy, along * spray.z + across * spray.x, color, life, blood); + } + + private writeDropletMatrix(index: number, droplet: Droplet): void { + if (!droplet.alive) { + this.dropletScale.setScalar(0); + this.dropletQuaternion.identity(); + this.dropletMatrix.compose(this.dropletVelocity.set(0, -50, 0), this.dropletQuaternion, this.dropletScale); + this.dropletMesh.setMatrixAt(index, this.dropletMatrix); + return; + } + const speed = Math.hypot(droplet.vx, droplet.vy, droplet.vz); + const stretch = 1 + Math.min(3.2, speed * 0.55); + if (speed > 1e-4) { + this.dropletVelocity.set(droplet.vx / speed, droplet.vy / speed, droplet.vz / speed); + this.dropletQuaternion.setFromUnitVectors(unitY, this.dropletVelocity); + } else { + this.dropletQuaternion.identity(); + } + const fade = Math.min(1, droplet.life / (droplet.maxLife * 0.3)); + this.dropletScale.set(droplet.radius * fade, droplet.radius * stretch * fade, droplet.radius * fade); + this.dropletMatrix.compose(this.dropletVelocity.set(droplet.x, droplet.y, droplet.z), this.dropletQuaternion, this.dropletScale); + this.dropletMesh.setMatrixAt(index, this.dropletMatrix); } private spawnMist(x: number, y: number, z: number, scale: number, life: number): void { @@ -363,9 +531,9 @@ export class Effects3D { decal.position.x = finite(x); decal.position.z = finite(z); decal.rotation.z = finite(rotation); - decal.scale.set(Math.max(0.01, finite(scaleX, 0.2)), Math.max(0.01, finite(scaleZ, 0.15)), 1); - const material = decal.material as THREE.MeshBasicMaterial; - material.opacity = THREE.MathUtils.clamp(finite(opacity, 0.4), 0, 1); + decal.scale.set(Math.max(0.01, finite(scaleX, 0.2)) * 1.4, Math.max(0.01, finite(scaleZ, 0.15)) * 1.4, 1); + const material = decal.material as THREE.MeshStandardMaterial; + material.opacity = THREE.MathUtils.clamp(finite(opacity, 0.4) * 1.6, 0, 1); material.color.setHex(color); } @@ -408,30 +576,37 @@ export class Effects3D { } } - addEvent(event: CombatEvent, targetWorld: THREE.Vector3, reducedMotion: boolean): void { + /** + * Blood, sweat and chunks for a contact. `spray` is the way the punch travelled (from puncher to + * recipient); without it the event's world-x sign stands in. + */ + addEvent(event: CombatEvent, targetWorld: THREE.Vector3, reducedMotion: boolean, spray?: SprayDirection): void { if (!IMPACT_KINDS.has(event.kind)) return; const rand = seeded(event.event_id * 7919 + 17); const blocked = event.kind === "block" || event.kind === "perfect_block"; const pattern = bloodPatternFor(event); - const launchDirection = event.direction < 0 ? -1 : 1; + const launch = unitSpray(spray ?? event.direction); + // Sweat and chunks are pushed along the punch as hard as the event's sign says (a block may carry none). + const push = spray === undefined ? Math.abs(finite(event.direction)) : 1; const origin = { x: finite(targetWorld.x), y: event.detail.endsWith(":body") ? 1.05 : 1.58, z: finite(targetWorld.z) }; const sweatCount = reducedMotion ? 0 : Math.round((blocked ? 6 : 16) + Math.min(20, Math.max(0, event.amount) / 20)); const bloodCount = reducedMotion || event.blood <= 0 || this.bloodLevel === "off" ? 0 : this.bloodLevel === "reduced" ? Math.min(24, Math.round(event.blood * 0.24)) - : Math.min(160, Math.round(event.blood * 1.4)); + : Math.min(120, Math.round(event.blood * 1.1)); this.shake = Math.min(0.09, this.shake + (blocked ? 0.008 : Math.max(0.012, event.amount / 2600))); if (event.kind === "knockdown") this.shake = Math.min(0.14, this.shake + 0.06); for (let i = 0; i < sweatCount; i += 1) { const angle = rand() * Math.PI * 2; const outward = 0.4 + rand() * 0.9; - this.spawnDroplet( + this.sprayDroplet( + launch, origin.x + (rand() - 0.5) * 0.12, origin.y + (rand() - 0.5) * 0.14, origin.z + (rand() - 0.5) * 0.12, - Math.sin(angle) * outward + event.direction * (0.5 + rand() * 0.9), + Math.sin(angle) * outward + push * (0.5 + rand() * 0.9), 0.6 + rand() * 1.5, Math.cos(angle) * outward, { r: 0.82, g: 0.9, b: 1.0 }, @@ -443,43 +618,44 @@ export class Effects3D { const arterial = i % 4 === 0; const angle = (rand() - 0.5) * Math.PI; const speed = arterial ? 2.2 + rand() * 1.8 : 0.9 + rand() * 1.5; - let vx = launchDirection * speed; + let along = speed; let vy = 0.5 + rand() * 1.25; - let vz = (rand() - 0.5) * 0.5; + let across = (rand() - 0.5) * 0.5; if (pattern === "fan") { - vx = launchDirection * speed * (0.45 + Math.cos(angle) * 0.35); + along = speed * (0.45 + Math.cos(angle) * 0.35); vy = 0.55 + rand() * 1.15; - vz = Math.sin(angle) * speed * 0.9; + across = Math.sin(angle) * speed * 0.9; } else if (pattern === "plume") { - vx = launchDirection * speed * (0.25 + rand() * 0.25); + along = speed * (0.25 + rand() * 0.25); vy = 1.8 + rand() * 2.2; - vz = (rand() - 0.5) * speed * 0.65; + across = (rand() - 0.5) * speed * 0.65; } else if (pattern === "body_burst") { - vx = launchDirection * speed * (0.55 + rand() * 0.45); + along = speed * (0.55 + rand() * 0.45); vy = -0.15 + rand() * 1.05; - vz = Math.sin(angle) * speed * 0.75; + across = Math.sin(angle) * speed * 0.75; } else if (pattern === "ooze") { - vx = launchDirection * (0.08 + rand() * 0.22); + along = 0.08 + rand() * 0.22; vy = -0.3 - rand() * 0.55; - vz = (rand() - 0.5) * 0.22; + across = (rand() - 0.5) * 0.22; } else if (pattern === "impact") { - vx = launchDirection * speed * (0.45 + rand() * 0.65); + along = speed * (0.45 + rand() * 0.65); vy = 0.9 + rand() * 2.1; - vz = Math.sin(angle) * speed; + across = Math.sin(angle) * speed; } else { const spread = arterial ? 0.12 : 0.34; - vx = launchDirection * speed * (0.8 + rand() * 0.35); + along = speed * (0.8 + rand() * 0.35); vy = arterial ? 1.3 + rand() * 1.6 : 0.5 + rand() * 1.25; - vz = (rand() - 0.5) * speed * spread; + across = (rand() - 0.5) * speed * spread; } const shade = rand(); - this.spawnDroplet( + this.sprayDroplet( + launch, origin.x + (rand() - 0.5) * 0.12, origin.y + (rand() - 0.5) * 0.14, origin.z + (rand() - 0.5) * 0.12, - vx, + along, vy, - vz, + across, shade < 0.3 ? { r: 0.72, g: 0.055, b: 0.08 } : shade < 0.7 ? { r: 0.5, g: 0.025, b: 0.045 } : { r: 0.3, g: 0.012, b: 0.025 }, 0.65 + rand() * 0.85, true, @@ -505,11 +681,12 @@ export class Effects3D { for (let index = 0; index < chunks; index += 1) { const angle = rand() * Math.PI * 2; const speed = 0.5 + rand() * 1.8; - this.spawnGib( + this.sprayGib( + launch, origin.x + (rand() - 0.5) * 0.12, origin.y + (rand() - 0.5) * 0.14, origin.z + (rand() - 0.5) * 0.12, - event.direction * (0.5 + rand() * 1.4) + Math.sin(angle) * speed * 0.5, + push * (0.5 + rand() * 1.4) + Math.sin(angle) * speed * 0.5, 0.5 + rand() * 1.7, Math.cos(angle) * speed, rand, @@ -518,29 +695,59 @@ export class Effects3D { } } + private applyBakedPart(part: SeveredHead, baked: BakedPart | undefined, fallbackColor: number): void { + if (part.baked !== null) { + part.baked.dispose(); + part.baked = null; + } + const material = part.mesh.material as THREE.MeshStandardMaterial; + if (baked !== undefined) { + part.mesh.geometry = baked.geometry; + part.baked = baked.geometry; + part.mesh.scale.setScalar(1); + material.map = baked.map; + material.color.setHex(baked.color); + baked.geometry.computeBoundingBox(); + const box = baked.geometry.boundingBox; + if (box !== null) part.cap.position.y = box.min.y + 0.004; + part.cap.visible = true; + } else { + part.mesh.geometry = part.defaultGeometry; + part.mesh.scale.copy(part.defaultScale); + material.map = null; + material.color.setHex(fallbackColor); + part.cap.visible = false; + } + material.needsUpdate = true; + } + decapitate( fighterIndex: number, position: THREE.Vector3, quaternion: THREE.Quaternion, - direction: number, + direction: number | SprayDirection, eventId: number, skinColor = 0x8a4d32, + baked?: BakedPart, ): void { if (this.bloodLevel !== "full" || fighterIndex < 0 || fighterIndex >= MAX_HEADS) return; const index = Math.trunc(fighterIndex); const safeEventId = Number.isSafeInteger(eventId) ? eventId : 0; const head = this.heads[index]!; if (head.active || this.lastDecapitationEvent[index] === safeEventId) return; + this.applyBakedPart(head, baked, skinColor); const rand = seeded(safeEventId * 104729 + index * 8191 + 23); - const launchDirection = direction < 0 ? -1 : 1; + const launch = unitSpray(direction); this.lastDecapitationEvent[index] = safeEventId; head.active = true; head.moving = true; head.eventId = safeEventId; - head.vx = launchDirection * (1.8 + rand() * 1.1); + const along = 1.8 + rand() * 1.1; head.vy = 2.3 + rand() * 1.1; - head.vz = (rand() - 0.5) * 2.2; + const across = (rand() - 0.5) * 2.2; + head.vx = along * launch.x - across * launch.z; + head.vz = along * launch.z + across * launch.x; head.vrx = (rand() - 0.5) * 12; head.vry = (rand() - 0.5) * 12; head.vrz = (rand() - 0.5) * 12; @@ -548,7 +755,6 @@ export class Effects3D { head.stained = false; head.mesh.position.set(finite(position.x), finite(position.y, 1.55), finite(position.z)); copyFiniteQuaternion(head.mesh.quaternion, quaternion); - (head.mesh.material as THREE.MeshStandardMaterial).color.setHex(skinColor); head.mesh.visible = true; const stump = this.stumps[index]!; @@ -556,7 +762,7 @@ export class Effects3D { stump.fountainLife = 1.25; stump.accumulator = 0; stump.seed = safeEventId | 1; - stump.direction = launchDirection; + stump.direction = launch; stump.mesh.position.copy(head.mesh.position); stump.mesh.quaternion.copy(head.mesh.quaternion); stump.mesh.visible = true; @@ -564,11 +770,12 @@ export class Effects3D { for (let i = 0; i < GIBS_PER_DECAPITATION; i += 1) { const angle = rand() * Math.PI * 2; const speed = 0.8 + rand() * 2.4; - this.spawnGib( + this.sprayGib( + launch, head.mesh.position.x + (rand() - 0.5) * 0.12, head.mesh.position.y + (rand() - 0.5) * 0.12, head.mesh.position.z + (rand() - 0.5) * 0.12, - launchDirection * (0.7 + rand() * 1.8) + Math.sin(angle) * speed * 0.55, + 0.7 + rand() * 1.8 + Math.sin(angle) * speed * 0.55, 0.8 + rand() * 2.4, Math.cos(angle) * speed, rand, @@ -578,11 +785,12 @@ export class Effects3D { const angle = rand() * Math.PI * 2; const speed = 1 + rand() * 2.6; const shade = rand(); - this.spawnDroplet( + this.sprayDroplet( + launch, head.mesh.position.x + (rand() - 0.5) * 0.12, head.mesh.position.y + (rand() - 0.5) * 0.1, head.mesh.position.z + (rand() - 0.5) * 0.12, - launchDirection * (1.2 + rand() * 2.2) + Math.sin(angle) * speed * 0.35, + 1.2 + rand() * 2.2 + Math.sin(angle) * speed * 0.35, 0.7 + rand() * 2.7, Math.cos(angle) * speed, shade < 0.5 ? { r: 0.64, g: 0.035, b: 0.055 } : { r: 0.36, g: 0.015, b: 0.03 }, @@ -601,24 +809,28 @@ export class Effects3D { side: Hand, position: THREE.Vector3, quaternion: THREE.Quaternion, - direction: number, + direction: number | SprayDirection, eventId: number, color: number, + baked?: BakedPart, ): void { if (this.bloodLevel !== "full" || fighterIndex < 0 || fighterIndex >= MAX_HEADS) return; const index = Math.trunc(fighterIndex) * 2 + (side === "left" ? 0 : 1); const safeEventId = Number.isSafeInteger(eventId) ? eventId : 0; const hand = this.hands[index]!; if (hand.active || this.lastDismembermentEvent[index] === safeEventId) return; + this.applyBakedPart(hand, baked, color); const rand = seeded(safeEventId * 130363 + index * 12289 + 37); - const launchDirection = direction < 0 ? -1 : 1; + const launch = unitSpray(direction); this.lastDismembermentEvent[index] = safeEventId; hand.active = true; hand.moving = true; hand.eventId = safeEventId; - hand.vx = launchDirection * (1.3 + rand() * 1.1); + const along = 1.3 + rand() * 1.1; hand.vy = 1.5 + rand() * 1.2; - hand.vz = (rand() - 0.5) * 1.8; + const across = (rand() - 0.5) * 1.8; + hand.vx = along * launch.x - across * launch.z; + hand.vz = along * launch.z + across * launch.x; hand.vrx = (rand() - 0.5) * 16; hand.vry = (rand() - 0.5) * 16; hand.vrz = (rand() - 0.5) * 16; @@ -626,7 +838,6 @@ export class Effects3D { hand.stained = false; hand.mesh.position.set(finite(position.x), finite(position.y, 1.25), finite(position.z)); copyFiniteQuaternion(hand.mesh.quaternion, quaternion); - (hand.mesh.material as THREE.MeshStandardMaterial).color.setHex(color); hand.mesh.visible = true; const stump = this.handStumps[index]!; @@ -634,7 +845,7 @@ export class Effects3D { stump.fountainLife = 0.9; stump.accumulator = 0; stump.seed = safeEventId | 1; - stump.direction = launchDirection; + stump.direction = launch; stump.mesh.position.copy(hand.mesh.position); stump.mesh.quaternion.copy(hand.mesh.quaternion); stump.mesh.visible = true; @@ -642,11 +853,12 @@ export class Effects3D { for (let gib = 0; gib < GIBS_PER_HAND; gib += 1) { const angle = rand() * Math.PI * 2; const speed = 0.55 + rand() * 1.8; - this.spawnGib( + this.sprayGib( + launch, hand.mesh.position.x + (rand() - 0.5) * 0.08, hand.mesh.position.y + (rand() - 0.5) * 0.08, hand.mesh.position.z + (rand() - 0.5) * 0.08, - launchDirection * (0.5 + rand() * 1.4) + Math.sin(angle) * speed * 0.45, + 0.5 + rand() * 1.4 + Math.sin(angle) * speed * 0.45, 0.5 + rand() * 1.9, Math.cos(angle) * speed, rand, @@ -655,11 +867,12 @@ export class Effects3D { for (let drop = 0; drop < 80; drop += 1) { const angle = rand() * Math.PI * 2; const speed = 0.8 + rand() * 2.1; - this.spawnDroplet( + this.sprayDroplet( + launch, hand.mesh.position.x + (rand() - 0.5) * 0.08, hand.mesh.position.y + (rand() - 0.5) * 0.08, hand.mesh.position.z + (rand() - 0.5) * 0.08, - launchDirection * (0.8 + rand() * 1.7) + Math.sin(angle) * speed * 0.35, + 0.8 + rand() * 1.7 + Math.sin(angle) * speed * 0.35, 0.5 + rand() * 2.1, Math.cos(angle) * speed, { r: 0.56, g: 0.025, b: 0.045 }, @@ -709,6 +922,7 @@ export class Effects3D { head.moving = false; head.mesh.visible = false; head.mesh.position.y = -50; + this.applyBakedPart(head, undefined, 0x8a4d32); const stump = this.stumps[index]!; stump.active = false; stump.fountainLife = 0; @@ -721,6 +935,7 @@ export class Effects3D { hand.moving = false; hand.mesh.visible = false; hand.mesh.position.y = -50; + this.applyBakedPart(hand, undefined, 0x1d4ed8); const handStump = this.handStumps[handIndex]!; handStump.active = false; handStump.fountainLife = 0; @@ -770,11 +985,40 @@ export class Effects3D { } } - private spawnGib(x: number, y: number, z: number, vx: number, vy: number, vz: number, rand: () => number): void { + /** Ejects teeth from the mouth on heavy head contact. */ + spawnTeeth(mouthWorld: THREE.Vector3, direction: number | SprayDirection, count: number, eventId: number): void { + if (this.bloodLevel === "off") return; + const rand = seeded((Number.isSafeInteger(eventId) ? eventId : 0) * 7331 + 91); + const launch = unitSpray(direction); + const teeth = Math.min(4, Math.max(1, Math.round(count * (this.bloodLevel === "reduced" ? 0.5 : 1)))); + for (let i = 0; i < teeth; i += 1) { + const angle = rand() * Math.PI * 2; + this.sprayGib( + launch, + finite(mouthWorld.x) + (rand() - 0.5) * 0.04, + finite(mouthWorld.y, 1.4) + (rand() - 0.5) * 0.02, + finite(mouthWorld.z) + (rand() - 0.5) * 0.04, + 0.9 + rand() * 1.6 + Math.sin(angle) * 0.6, + 1.1 + rand() * 1.4, + Math.cos(angle) * 0.7, + rand, + true, + ); + } + for (let i = 0; i < 18; i += 1) { + const angle = rand() * Math.PI * 2; + this.sprayDroplet(launch, finite(mouthWorld.x), finite(mouthWorld.y, 1.4), finite(mouthWorld.z), 0.8 + rand() * 1.4 + Math.sin(angle) * 0.5, 0.6 + rand() * 1.3, Math.cos(angle) * 0.5, { r: 0.55, g: 0.02, b: 0.04 }, 0.6 + rand() * 0.6, true); + } + } + + private spawnGib(x: number, y: number, z: number, vx: number, vy: number, vz: number, rand: () => number, tooth = false): void { const index = this.gibIndex % MAX_GIBS; this.gibIndex += 1; const gib = this.gibs[index]!; gib.alive = true; + gib.tooth = tooth; + this.gibMesh.setColorAt(index, this.gibColor.setHex(tooth ? 0xf3ead6 : 0xffffff)); + if (this.gibMesh.instanceColor !== null) this.gibMesh.instanceColor.needsUpdate = true; gib.x = finite(x); gib.y = finite(y, 1.5); gib.z = finite(z); @@ -787,14 +1031,19 @@ export class Effects3D { gib.vrx = (rand() - 0.5) * 18; gib.vry = (rand() - 0.5) * 18; gib.vrz = (rand() - 0.5) * 18; - gib.life = 1.8 + rand() * 1.2; - gib.scale = 0.55 + rand() * 1.2; + gib.life = tooth ? 6 : 1.8 + rand() * 1.2; + gib.scale = tooth ? 0.22 + rand() * 0.12 : 0.32 + rand() * 0.7; gib.bounces = 0; gib.stained = false; this.writeGibMatrix(index, gib); this.gibMesh.instanceMatrix.needsUpdate = true; } + /** Spawns a gib whose horizontal velocity is given along the spray and across it. */ + private sprayGib(spray: SprayDirection, x: number, y: number, z: number, along: number, vy: number, across: number, rand: () => number, tooth = false): void { + this.spawnGib(x, y, z, along * spray.x - across * spray.z, vy, along * spray.z + across * spray.x, rand, tooth); + } + private writeGibMatrix(index: number, gib: Gib): void { if (!gib.alive) { this.gibPosition.set(0, -50, 0); @@ -831,18 +1080,23 @@ export class Effects3D { this.confineGib(gib); if (gib.y <= CANVAS_TOP + 0.015) { gib.y = CANVAS_TOP + 0.015; - if (!gib.stained && this.bloodLevel === "full") { + if (!gib.stained && this.bloodLevel === "full" && !gib.tooth) { gib.stained = true; this.placeDecal(gib.x, gib.z, 0.24 + gib.scale * 0.16, 0.14 + gib.scale * 0.1, gib.rz, 0.42, 0x620a10); } - if (gib.bounces === 0 && Math.abs(gib.vy) > 0.35) { - gib.bounces = 1; + if (gib.bounces < (gib.tooth ? 3 : 1) && Math.abs(gib.vy) > 0.35) { + gib.bounces += 1; gib.vy = Math.abs(gib.vy) * 0.3; gib.vx *= 0.68; gib.vz *= 0.68; gib.vrx *= 0.7; gib.vry *= 0.7; gib.vrz *= 0.7; + } else if (gib.tooth) { + gib.vx = 0; + gib.vy = 0; + gib.vz = 0; + gib.vrx = gib.vry = gib.vrz = 0; } else { gib.alive = false; } @@ -936,11 +1190,12 @@ export class Effects3D { const first = this.stumpRandom(stump); const second = this.stumpRandom(stump); const third = this.stumpRandom(stump); - this.spawnDroplet( + this.sprayDroplet( + stump.direction, stump.mesh.position.x + (first - 0.5) * 0.08, stump.mesh.position.y + 0.015, stump.mesh.position.z + (second - 0.5) * 0.08, - stump.direction * (0.35 + first * 0.55), + 0.35 + first * 0.55, 1.3 + second * 1.45, (third - 0.5) * 0.85, { r: 0.58, g: 0.025, b: 0.045 }, @@ -967,18 +1222,19 @@ export class Effects3D { this.updateDetachedParts(this.hands, step); this.updateGibs(step); - let dropletsChanged = false; - for (const [i, droplet] of this.droplets.entries()) { - if (!droplet.alive) continue; - dropletsChanged = true; + const live = this.liveDroplets; + let retired = false; + for (let i = 0; i < this.liveDroplets;) { + const droplet = this.droplets[i]!; droplet.life -= step; if (droplet.life <= 0 || droplet.y < CANVAS_TOP) { if (droplet.y < CANVAS_TOP && droplet.blood && this.bloodLevel !== "off" && this.ambientRandom() < (this.bloodLevel === "full" ? 0.48 : 0.18)) { const scale = this.bloodLevel === "full" ? 1 : 0.35; this.placeDecal(droplet.x, droplet.z, (0.22 + this.ambientRandom() * 0.38) * scale, (0.14 + this.ambientRandom() * 0.24) * scale, this.ambientRandom() * Math.PI, 0.38 * scale, 0x6e0d13); } - droplet.alive = false; - this.dropletPositions[i * 3 + 1] = -50; + // The last live droplet takes this slot and is stepped next. + this.retireDroplet(i); + retired = true; continue; } droplet.vy -= 4.6 * step; @@ -992,10 +1248,13 @@ export class Effects3D { this.dropletColors[i * 3] = droplet.r * fade; this.dropletColors[i * 3 + 1] = droplet.g * fade; this.dropletColors[i * 3 + 2] = droplet.b * fade; + this.writeDropletMatrix(i, droplet); + i += 1; } - if (dropletsChanged) { - this.dropletGeometry.attributes.position!.needsUpdate = true; - this.dropletGeometry.attributes.color!.needsUpdate = true; + if (live > 0) { + this.dropletBuffers.position.needsUpdate = true; + this.dropletBuffers.color.needsUpdate = true; + this.uploadDroplets(0, this.liveDroplets, retired); } let mistChanged = false; @@ -1024,16 +1283,14 @@ export class Effects3D { } private clearDroplets(bloodOnly: boolean): void { - let changed = false; - for (const [index, droplet] of this.droplets.entries()) { - if (!droplet.alive || (bloodOnly && !droplet.blood)) continue; - droplet.alive = false; - this.dropletPositions[index * 3 + 1] = -50; - changed = true; + const live = this.liveDroplets; + for (let index = 0; index < this.liveDroplets;) { + if (bloodOnly && !this.droplets[index]!.blood) index += 1; + else this.retireDroplet(index); } - if (changed) { - this.dropletGeometry.attributes.position!.needsUpdate = true; - this.dropletGeometry.attributes.color!.needsUpdate = true; + if (this.liveDroplets !== live) { + this.dropletBuffers.position.needsUpdate = true; + this.uploadDroplets(0, this.liveDroplets, true); } } @@ -1091,14 +1348,21 @@ export class Effects3D { } dispose(): void { - this.scene.remove(this.points); + this.scene.remove(this.dropletMesh); this.scene.remove(this.mistPoints); this.scene.remove(this.gibMesh); + this.dropletMesh.dispose(); this.dropletGeometry.dispose(); this.dropletMaterial.dispose(); + for (const map of this.splatMaps) map.dispose(); + for (const part of [...this.heads, ...this.hands]) { + part.baked?.dispose(); + part.cap.geometry.dispose(); + } this.mistGeometry.dispose(); this.mistMaterial.dispose(); this.mistMap.dispose(); + this.gibMesh.dispose(); this.gibGeometry.dispose(); this.gibMaterial.dispose(); this.headGeometry.dispose(); diff --git a/web/hands/src/render/fighter-asset.test.ts b/web/hands/src/render/fighter-asset.test.ts deleted file mode 100644 index 2cf8b5c6..00000000 --- a/web/hands/src/render/fighter-asset.test.ts +++ /dev/null @@ -1,421 +0,0 @@ -import { createHash } from "node:crypto"; -import { readFileSync } from "node:fs"; -import { resolve } from "node:path"; -import * as THREE from "three"; -import { clone as cloneSkeleton } from "three/examples/jsm/utils/SkeletonUtils.js"; -import markerData from "../assets/fighter-markers.json"; -import { FIGHTER_TEXTURE_DATA_URLS } from "../assets/fighter-textures"; -import { BONE_ADAPTER, CLIP_NAMES, FIGHTER_MODEL_SCALE, type ClipName, loadBoxerGlb } from "./graph"; - -const EXPECTED_FRAMES: Readonly> = { - idle: 60, - move_forward: 31, - move_backward: 31, - move_lateral_left: 31, - move_lateral_right: 31, - guard_high: 30, - guard_low: 30, - slip_left: 24, - slip_right: 24, - weave: 30, - pull: 24, - jab_left: 17, - jab_right: 17, - straight_left: 22, - straight_right: 22, - hook_left: 26, - hook_right: 26, - uppercut_left: 27, - uppercut_right: 27, - block_head_left: 14, - block_head_right: 14, - block_body_left: 14, - block_body_right: 14, - hit_head_left: 16, - hit_head_right: 16, - hit_body_left: 16, - hit_body_right: 16, - knockdown: 42, - getup: 30, - clinch: 30, - foul_recovery: 30, - stunned: 30, - exhausted: 45, - taunt: 60, -}; - -function sourceJson(bytes: Buffer): Record { - const view = new DataView(bytes.buffer, bytes.byteOffset, bytes.byteLength); - expect(view.getUint32(0, true)).toBe(0x46546c67); - expect(view.getUint32(4, true)).toBe(2); - expect(view.getUint32(16, true)).toBe(0x4e4f534a); - return JSON.parse(bytes.subarray(20, 20 + view.getUint32(12, true)).toString("utf8")) as Record; -} - -function skinnedMeshes(root: THREE.Object3D): THREE.SkinnedMesh[] { - const meshes: THREE.SkinnedMesh[] = []; - root.traverse((object) => { - if (object instanceof THREE.SkinnedMesh) meshes.push(object); - }); - return meshes; -} - -function updateSkin(root: THREE.Object3D): void { - root.updateMatrixWorld(true); - for (const mesh of skinnedMeshes(root)) mesh.skeleton.update(); -} - -function sampledVertices(root: THREE.Object3D): THREE.Vector3[] { - updateSkin(root); - const result: THREE.Vector3[] = []; - for (const mesh of skinnedMeshes(root)) { - const count = mesh.geometry.getAttribute("position").count; - const step = Math.max(1, Math.floor(count / 32)); - for (let index = 0; index < count; index += step) { - const point = mesh.getVertexPosition(index, new THREE.Vector3()); - result.push(mesh.localToWorld(point)); - } - } - return result; -} - -function maximumDisplacement(left: readonly THREE.Vector3[], right: readonly THREE.Vector3[]): number { - return Math.max(...left.map((point, index) => point.distanceTo(right[index]!))); -} - -function poseAt(gltf: Awaited>, clipName: ClipName, time: number): THREE.Object3D { - const root = cloneSkeleton(gltf.scene); - const mixer = new THREE.AnimationMixer(root); - const clip = THREE.AnimationClip.findByName(gltf.animations, clipName)!; - mixer.clipAction(clip).setLoop(THREE.LoopOnce, 1).play().clampWhenFinished = true; - mixer.setTime(Math.min(time, clip.duration)); - updateSkin(root); - return root; -} - -describe("Texel Boxer source asset", () => { - it("pins official provenance, license, and structural inventory", () => { - const bytes = readFileSync(resolve(process.cwd(), "assets-src/Boxer.glb")); - expect(bytes.byteLength).toBe(3_216_472); - expect(createHash("sha256").update(bytes).digest("hex")).toBe("545be2380b259698ca3ae864bba2b00a54aaaf987fd0837b8dde65cc18da3961"); - const gltf = sourceJson(bytes) as { - asset: { version: string; extras: Record }; - nodes: unknown[]; - meshes: unknown[]; - skins: { joints: number[] }[]; - materials: { name: string }[]; - images: unknown[]; - animations: { name: string }[]; - extensionsRequired?: string[]; - }; - expect(gltf.asset.version).toBe("2.0"); - expect(gltf.asset.extras).toMatchObject({ - author: "Texel, Inc. (https://sketchfab.com/texel)", - license: "CC-BY-4.0 (http://creativecommons.org/licenses/by/4.0/)", - source: "https://sketchfab.com/3d-models/boxer-84767168720948b38728ff78ee6f6090", - title: "Boxer", - }); - expect(gltf.extensionsRequired ?? []).toEqual([]); - expect(gltf.nodes).toHaveLength(48); - expect(gltf.meshes).toHaveLength(5); - expect(gltf.skins).toHaveLength(1); - expect(gltf.skins[0]!.joints).toHaveLength(27); - expect(gltf.materials.map((material) => material.name)).toEqual([ - "MHeadMat0", "GlovesMat0", "MBodyMat0", "ShoesMat0", "PantsMat0", - ]); - expect(gltf.images).toHaveLength(5); - expect(gltf.animations.map((animation) => animation.name)).toEqual(["Animation"]); - }); - - it("pins extracted PNG dimensions, bytes, hashes, and runtime scale", () => { - const expected = { - head: [1024, 1024, 1_118_400, "e2f99ac2fc9332f250180492ad3dd1d70bef2872fd7da3587fc3e94d7850dbd0"], - gloves: [256, 256, 57_215, "3e9b08a173fa288ddfd61b1d5662eb5c4fcdbe0174d72494fa1ed789b3b3c9e4"], - body: [1024, 1024, 610_245, "cbfd4d637b6b8e8ee12b5dabb6e17eb087a7ca9352c982cf7176bfc673234416"], - shoes: [256, 256, 78_886, "f1d0449390f23cd815d7009b64a0b8c3f9f4c5e1498ab5c624c90def72d0e012"], - pants: [512, 512, 93_952, "7da721303a0c25d6192338298d7efcc43193a73d7e61494c2c45036f2a885a90"], - } as const; - expect(Object.keys(FIGHTER_TEXTURE_DATA_URLS)).toEqual(Object.keys(expected)); - for (const [name, [width, height, byteLength, sha256]] of Object.entries(expected)) { - const dataUrl = FIGHTER_TEXTURE_DATA_URLS[name as keyof typeof FIGHTER_TEXTURE_DATA_URLS]; - expect(dataUrl.startsWith("data:image/png;base64,")).toBe(true); - const bytes = Buffer.from(dataUrl.slice(dataUrl.indexOf(",") + 1), "base64"); - expect(bytes.subarray(0, 8).toString("hex")).toBe("89504e470d0a1a0a"); - expect(bytes.readUInt32BE(16)).toBe(width); - expect(bytes.readUInt32BE(20)).toBe(height); - expect(bytes.byteLength).toBe(byteLength); - expect(createHash("sha256").update(bytes).digest("hex")).toBe(sha256); - } - expect(FIGHTER_MODEL_SCALE).toBe(0.96); - }); -}); - -describe("generated fighter animation asset", () => { - it("leaves facing and stance yaw to the runtime root", async () => { - const gltf = await loadBoxerGlb(); - const hipsName = BONE_ADAPTER.hips!; - const hips = gltf.scene.getObjectByName(hipsName)!; - const idle = gltf.animations.find((clip) => clip.name === "idle")!; - const track = idle.tracks.find((candidate) => candidate.name === `${hipsName}.quaternion`)!; - const firstPose = new THREE.Quaternion().fromArray(track.values, 0); - expect(hips.quaternion.angleTo(firstPose)).toBeLessThan(0.08); - }); - - it("has six smoothly skinned semantic parts with independently detachable gloves", async () => { - const gltf = await loadBoxerGlb(); - const meshes = skinnedMeshes(gltf.scene); - expect(meshes.map((mesh) => mesh.name)).toEqual([ - "BoxerHead", "BoxerBody", "BoxerShoes", "BoxerPants", "BoxerGloveLeft", "BoxerGloveRight", - ]); - expect(meshes.map((mesh) => (mesh.material as THREE.Material).name)).toEqual([ - "MHeadMat0", "MBodyMat0", "ShoesMat0", "PantsMat0", "GlovesMat0", "GlovesMat0", - ]); - let blendedVertices = 0; - for (const mesh of meshes) { - const joints = mesh.geometry.getAttribute("skinIndex"); - const weights = mesh.geometry.getAttribute("skinWeight"); - expect(joints.count).toBe(weights.count); - expect(mesh.skeleton.bones).toHaveLength(27); - for (let index = 0; index < weights.count; index += 1) { - const values = [weights.getX(index), weights.getY(index), weights.getZ(index), weights.getW(index)]; - expect(values.every(Number.isFinite)).toBe(true); - expect(values.reduce((sum, value) => sum + value, 0)).toBeCloseTo(1, 5); - if (values.filter((value) => value > 0.0001).length > 1) blendedVertices += 1; - } - } - expect(blendedVertices).toBeGreaterThan(8_000); - }); - - it.each(CLIP_NAMES)("validates every keyframe and real skin deformation in %s", async (clipName) => { - const gltf = await loadBoxerGlb(); - const clip = THREE.AnimationClip.findByName(gltf.animations, clipName)!; - const frames = EXPECTED_FRAMES[clipName]; - expect(clip.tracks).toHaveLength(17); - expect(clip.duration).toBeCloseTo((frames - 1) / 30, 5); - const expectedTargets = new Set([ - ...Object.values(BONE_ADAPTER).map((bone) => `${bone}.quaternion`), - `${BONE_ADAPTER.hips}.position`, - ]); - expect(new Set(clip.tracks.map((track) => track.name))).toEqual(expectedTargets); - for (const track of clip.tracks) { - expect(track.times).toHaveLength(frames); - expect(track.times[0]).toBeCloseTo(0, 7); - expect(track.times[frames - 1]).toBeCloseTo((frames - 1) / 30, 5); - expect([...track.values].every(Number.isFinite)).toBe(true); - if (track.ValueTypeName === "quaternion") { - for (let index = 0; index < track.values.length; index += 4) { - expect(Math.hypot(...track.values.slice(index, index + 4))).toBeCloseTo(1, 5); - } - } - } - - const root = cloneSkeleton(gltf.scene); - const mixer = new THREE.AnimationMixer(root); - const action = mixer.clipAction(clip); - action.setLoop(THREE.LoopOnce, 1); - action.clampWhenFinished = true; - action.play(); - let baseline: THREE.Vector3[] | null = null; - let maximum = 0; - for (let frame = 0; frame < frames; frame += 1) { - mixer.setTime(frame / 30); - const vertices = sampledVertices(root); - baseline ??= vertices.map((point) => point.clone()); - maximum = Math.max(maximum, maximumDisplacement(baseline, vertices)); - const bounds = new THREE.Box3().setFromObject(root, true); - expect([...bounds.min.toArray(), ...bounds.max.toArray()].every(Number.isFinite)).toBe(true); - expect(bounds.min.y).toBeGreaterThanOrEqual(-0.01); - expect(bounds.max.y).toBeLessThan(2.1); - const size = bounds.getSize(new THREE.Vector3()); - expect(Math.max(size.x, size.y, size.z)).toBeLessThan(3); - } - expect(maximum).toBeGreaterThan(0.002); - }); - - it("keeps guards, punches, knockdown, and get-up semantically distinct and continuous", async () => { - const gltf = await loadBoxerGlb(); - const handPosition = (root: THREE.Object3D, side: "left" | "right"): THREE.Vector3 => - root.getObjectByName(side === "left" ? BONE_ADAPTER.gloveL! : BONE_ADAPTER.gloveR!)!.getWorldPosition(new THREE.Vector3()); - const high = poseAt(gltf, "guard_high", 0); - const low = poseAt(gltf, "guard_low", 0); - expect(handPosition(high, "left").y - handPosition(low, "left").y).toBeGreaterThan(0.12); - expect(handPosition(high, "right").y - handPosition(low, "right").y).toBeGreaterThan(0.12); - - for (const clipName of CLIP_NAMES.filter((name) => /^(jab|straight|hook|uppercut)_/.test(name))) { - const side = clipName.endsWith("_left") ? "left" : "right"; - const start = poseAt(gltf, clipName, 0); - const contact = poseAt(gltf, clipName, THREE.AnimationClip.findByName(gltf.animations, clipName)!.duration * 0.5); - expect(handPosition(start, side).distanceTo(handPosition(contact, side)), clipName).toBeGreaterThan(0.25); - } - - const idleStart = poseAt(gltf, "idle", 0); - const knockdownStart = poseAt(gltf, "knockdown", 0); - const knockdownEnd = poseAt(gltf, "knockdown", 10); - const getupStart = poseAt(gltf, "getup", 0); - const getupEnd = poseAt(gltf, "getup", 10); - const head = (root: THREE.Object3D): THREE.Vector3 => root.getObjectByName(BONE_ADAPTER.head!)!.getWorldPosition(new THREE.Vector3()); - expect(head(idleStart).distanceTo(head(knockdownStart))).toBeLessThan(0.04); - expect(head(knockdownEnd).distanceTo(head(getupStart))).toBeLessThan(0.04); - expect(head(getupEnd).distanceTo(head(idleStart))).toBeLessThan(0.04); - expect(head(knockdownEnd).y).toBeLessThan(head(idleStart).y - 0.8); - }); - - it("keeps every authored joint transition below a realistic angular speed", async () => { - const gltf = await loadBoxerGlb(); - const maximumStep = THREE.MathUtils.degToRad(56); - for (const clip of gltf.animations) { - for (const track of clip.tracks.filter((candidate) => candidate.ValueTypeName === "quaternion")) { - let previous = new THREE.Quaternion().fromArray(track.values, 0); - for (let index = 4; index < track.values.length; index += 4) { - const current = new THREE.Quaternion().fromArray(track.values, index); - expect(previous.angleTo(current), `${clip.name} ${track.name} frame ${index / 4}`).toBeLessThanOrEqual(maximumStep); - previous = current; - } - } - } - }); - - it("keeps hook and uppercut elbows bent while allowing linear punches to extend", async () => { - const gltf = await loadBoxerGlb(); - const elbowAngle = (root: THREE.Object3D, side: "left" | "right"): number => { - const shoulder = root.getObjectByName(side === "left" ? BONE_ADAPTER.shoulderL! : BONE_ADAPTER.shoulderR!)! - .getWorldPosition(new THREE.Vector3()); - const elbow = root.getObjectByName(side === "left" ? BONE_ADAPTER.elbowL! : BONE_ADAPTER.elbowR!)! - .getWorldPosition(new THREE.Vector3()); - const glove = root.getObjectByName(side === "left" ? BONE_ADAPTER.gloveL! : BONE_ADAPTER.gloveR!)! - .getWorldPosition(new THREE.Vector3()); - return new THREE.Vector3().subVectors(shoulder, elbow) - .angleTo(new THREE.Vector3().subVectors(glove, elbow)); - }; - for (const side of ["left", "right"] as const) { - for (const [punchClass, startup, active, minimum, maximum] of [ - ["hook", 7, 3, 85, 130], - ["uppercut", 8, 2, 65, 135], - ] as const) { - for (let frame = startup; frame <= startup + active; frame += 1) { - const angle = THREE.MathUtils.radToDeg(elbowAngle(poseAt(gltf, `${punchClass}_${side}`, frame / 30), side)); - expect(angle, `${punchClass}_${side} frame ${frame}`).toBeGreaterThanOrEqual(minimum); - expect(angle, `${punchClass}_${side} frame ${frame}`).toBeLessThanOrEqual(maximum); - } - } - for (const punchClass of ["jab", "straight"] as const) { - const startup = punchClass === "jab" ? 4 : 6; - const angles = Array.from({ length: 3 }, (_unused, offset) => - THREE.MathUtils.radToDeg(elbowAngle(poseAt(gltf, `${punchClass}_${side}`, (startup + offset) / 30), side)), - ); - expect(Math.max(...angles), `${punchClass}_${side}`).toBeGreaterThan(95); - expect(Math.max(...angles), `${punchClass}_${side}`).toBeLessThan(160); - } - } - }); - - it("authors evasions, special states, and articulated locomotion instead of idle aliases", async () => { - const gltf = await loadBoxerGlb(); - const world = (root: THREE.Object3D, bone: string): THREE.Vector3 => - root.getObjectByName(bone)!.getWorldPosition(new THREE.Vector3()); - const idle = poseAt(gltf, "idle", 0); - const idleHead = world(idle, BONE_ADAPTER.head!); - const slipLeft = world(poseAt(gltf, "slip_left", 0), BONE_ADAPTER.head!).sub(idleHead); - const slipRight = world(poseAt(gltf, "slip_right", 0), BONE_ADAPTER.head!).sub(idleHead); - expect(slipLeft.x).toBeLessThan(-0.12); - expect(slipRight.x).toBeGreaterThan(0.12); - expect(world(poseAt(gltf, "weave", 0), BONE_ADAPTER.head!).distanceTo(idleHead)).toBeGreaterThan(0.25); - expect(world(poseAt(gltf, "pull", 0), BONE_ADAPTER.head!).distanceTo(idleHead)).toBeGreaterThan(0.25); - - for (const clipName of ["clinch", "foul_recovery", "stunned"] as const) { - const state = poseAt(gltf, clipName, 0); - const left = world(state, BONE_ADAPTER.gloveL!).distanceTo(world(idle, BONE_ADAPTER.gloveL!)); - const right = world(state, BONE_ADAPTER.gloveR!).distanceTo(world(idle, BONE_ADAPTER.gloveR!)); - expect(Math.max(left, right), clipName).toBeGreaterThan(0.16); - } - - const exhausted = poseAt(gltf, "exhausted", 0); - expect(world(exhausted, BONE_ADAPTER.gloveL!).distanceTo(world(idle, BONE_ADAPTER.gloveL!))).toBeGreaterThan(0.05); - - const taunt = THREE.AnimationClip.findByName(gltf.animations, "taunt")!; - const excursion = (bone: string): number => { - const track = taunt.tracks.find((candidate) => candidate.name === `${bone}.quaternion`)!; - const start = new THREE.Quaternion().fromArray(track.values, 0); - let maximum = 0; - for (let index = 4; index < track.values.length; index += 4) { - maximum = Math.max(maximum, start.angleTo(new THREE.Quaternion().fromArray(track.values, index))); - } - return THREE.MathUtils.radToDeg(maximum); - }; - expect(excursion(BONE_ADAPTER.shoulderL!)).toBeGreaterThan(12); - expect(excursion(BONE_ADAPTER.hips!)).toBeGreaterThan(3); - const idleClip = THREE.AnimationClip.findByName(gltf.animations, "idle")!; - for (const bone of [BONE_ADAPTER.shoulderL!, BONE_ADAPTER.shoulderR!, BONE_ADAPTER.hips!]) { - const tauntTrack = taunt.tracks.find((candidate) => candidate.name === `${bone}.quaternion`)!; - const idleTrack = idleClip.tracks.find((candidate) => candidate.name === `${bone}.quaternion`)!; - const first = new THREE.Quaternion().fromArray(tauntTrack.values, 0); - const last = new THREE.Quaternion().fromArray(tauntTrack.values, tauntTrack.values.length - 4); - const idleStart = new THREE.Quaternion().fromArray(idleTrack.values, 0); - const idleLast = new THREE.Quaternion().fromArray(idleTrack.values, idleTrack.values.length - 4); - expect(THREE.MathUtils.radToDeg(idleStart.angleTo(first)), `${bone} entry`).toBeLessThan(2); - expect(THREE.MathUtils.radToDeg(idleLast.angleTo(last)), `${bone} recovery`).toBeLessThan(2); - } - - for (const clipName of ["move_forward", "move_backward", "move_lateral_left", "move_lateral_right"] as const) { - const clip = THREE.AnimationClip.findByName(gltf.animations, clipName)!; - for (const knee of [BONE_ADAPTER.kneeL!, BONE_ADAPTER.kneeR!]) { - const track = clip.tracks.find((candidate) => candidate.name === `${knee}.quaternion`)!; - const start = new THREE.Quaternion().fromArray(track.values, 0); - let excursion = 0; - for (let index = 4; index < track.values.length; index += 4) { - excursion = Math.max(excursion, start.angleTo(new THREE.Quaternion().fromArray(track.values, index))); - } - expect(THREE.MathUtils.radToDeg(excursion), `${clipName} ${knee}`).toBeGreaterThan(18); - } - } - const forward = poseAt(gltf, "move_forward", 0.75); - const backward = poseAt(gltf, "move_backward", 0.75); - expect(world(forward, BONE_ADAPTER.chest!).distanceTo(world(backward, BONE_ADAPTER.chest!))).toBeGreaterThan(0.05); - }); - - it("distinguishes head recoil from body-hit compression", async () => { - const gltf = await loadBoxerGlb(); - const displacement = (clipName: ClipName, bone: string): number => { - const start = poseAt(gltf, clipName, 0).getObjectByName(bone)!.getWorldPosition(new THREE.Vector3()); - let maximum = 0; - for (let frame = 1; frame < EXPECTED_FRAMES[clipName]; frame += 1) { - const current = poseAt(gltf, clipName, frame / 30).getObjectByName(bone)!.getWorldPosition(new THREE.Vector3()); - maximum = Math.max(maximum, start.distanceTo(current)); - } - return maximum; - }; - for (const side of ["left", "right"] as const) { - const headHit = displacement(`hit_head_${side}`, BONE_ADAPTER.head!); - const bodyHit = displacement(`hit_body_${side}`, BONE_ADAPTER.head!); - expect(headHit).toBeGreaterThan(bodyHit + 0.06); - expect(displacement(`hit_body_${side}`, BONE_ADAPTER.hips!)).toBeGreaterThan(0.02); - } - }); - - it("matches every generated punch marker to its live glove bone", async () => { - const gltf = await loadBoxerGlb(); - const trajectories = markerData.trajectories as Record; - for (const clipName of CLIP_NAMES.filter((name) => /^(jab|straight|hook|uppercut)_/.test(name))) { - const [punchClass, side] = clipName.split("_") as [string, "left" | "right"]; - const trajectory = trajectories[`${punchClass}:${side}`]!; - const root = cloneSkeleton(gltf.scene); - const mixer = new THREE.AnimationMixer(root); - const clip = THREE.AnimationClip.findByName(gltf.animations, clipName)!; - const action = mixer.clipAction(clip); - action.setLoop(THREE.LoopOnce, 1); - action.clampWhenFinished = true; - action.play(); - expect(trajectory.frames).toBe(EXPECTED_FRAMES[clipName]); - const markers = side === "left" ? trajectory.left : trajectory.right; - expect(markers).toHaveLength(trajectory.frames); - for (let frame = 0; frame < trajectory.frames; frame += 1) { - mixer.setTime(frame / 30); - root.updateMatrixWorld(true); - const glove = root.getObjectByName(side === "left" ? BONE_ADAPTER.gloveL! : BONE_ADAPTER.gloveR!)! - .getWorldPosition(new THREE.Vector3()); - expect(glove.distanceTo(new THREE.Vector3().fromArray(markers[frame]!)), `${clipName} frame ${frame}`).toBeLessThan(0.001); - } - } - }); - -}); diff --git a/web/hands/src/render/fighter-presentation.test.ts b/web/hands/src/render/fighter-presentation.test.ts new file mode 100644 index 00000000..d6bb093e --- /dev/null +++ b/web/hands/src/render/fighter-presentation.test.ts @@ -0,0 +1,180 @@ +import * as THREE from "three"; +import { fighter as baseFighter } from "../test/fixtures"; +import type { FighterSnapshot } from "../types"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb } from "./graph"; +import { FightRenderer } from "./renderer"; +import { worldPosition, type CanonicalBone } from "./rig"; +import { worldMapping } from "./world"; + +const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); +const gltf = await loadBoxerGlb(); + +const bone = (boxer: SkinnedBoxer, name: CanonicalBone, out = new THREE.Vector3()): THREE.Vector3 => { + boxer.root.updateMatrixWorld(true); + return worldPosition(boxer.rig.bones[name], out); +}; + +/** World x of the front of a fighter's gloves: the skinned glove surface furthest along `toward` (+1 or -1). */ +function gloveFront(boxer: SkinnedBoxer, toward: number): number { + boxer.root.updateMatrixWorld(true); + let front = -Infinity; + const vertex = new THREE.Vector3(); + for (const side of ["left", "right"] as const) { + const mesh = boxer.gloveMesh(side); + const count = mesh.geometry.getAttribute("position").count; + for (let index = 0; index < count; index += 3) { + mesh.getVertexPosition(index, vertex).applyMatrix4(mesh.matrixWorld); + front = Math.max(front, vertex.x * toward); + } + } + return front * toward; +} + +function makeGraph(palette = { skin: 0xb0703f, gear: 0x1d4ed8 }): { boxer: SkinnedBoxer; graph: BoxingGraph } { + const boxer = new SkinnedBoxer(gltf, palette); + return { boxer, graph: new BoxingGraph(boxer, mapping) }; +} + +describe("corner stool", () => { + it("stays where it stood until the fighter has risen off it, even if he walks out at the bell", () => { + const { boxer, graph } = makeGraph(); + const stool = boxer.root.getObjectByName("stool")!; + const corner: FighterSnapshot = { ...baseFighter("one"), x: -365, y: -365, facing_x: 707, facing_y: 707 }; + const opponent: FighterSnapshot = { ...baseFighter("two"), x: 365, y: 365 }; + graph.setResting(true); + let tick = 0; + for (let frame = 0; frame < 180; frame += 1) { + tick += 0.5; + graph.update(corner, opponent, 1 / 60, frame / 60, false, "full", tick); + } + expect(graph.stoolVisible).toBe(true); + expect(bone(boxer, "hips").y).toBeLessThan(0.56); + const seat = stool.getWorldPosition(new THREE.Vector3()); + + // The bell: the round starts and the fighter walks straight out of the corner at full speed. + graph.setResting(false); + let visibleFrames = 0; + for (let frame = 0; frame < 60; frame += 1) { + tick += 0.5; + const walking = { ...corner, x: corner.x + frame * 2.5, y: corner.y + frame * 2.5, velocity_x: 5, velocity_y: 5 }; + graph.update(walking, opponent, 1 / 60, 3 + frame / 60, false, "full", tick); + const hips = bone(boxer, "hips").y; + if (graph.stoolVisible) { + visibleFrames += 1; + expect(stool.getWorldPosition(new THREE.Vector3()).distanceTo(seat)).toBeLessThan(1e-6); + } else { + expect(hips).toBeGreaterThan(0.7); + } + } + expect(visibleFrames).toBeGreaterThan(6); + expect(graph.stoolVisible).toBe(false); + }); +}); + +describe("taunt", () => { + it("beckons four times and moves the glove on every frame, not on the server's ticks", () => { + const { boxer, graph } = makeGraph(); + const idle: FighterSnapshot = { ...baseFighter("one"), x: 0, y: 0, facing_x: 0, facing_y: -1000 }; + const opponent: FighterSnapshot = { ...baseFighter("two"), x: 0, y: -150, facing_x: 0, facing_y: 1000 }; + let renderTick = 100; + for (let frame = 0; frame < 30; frame += 1) { + renderTick += 0.5; + graph.update(idle, opponent, 1 / 60, renderTick / 30, false, "full", renderTick); + } + // At 60 frames a second each snapshot, with its whole-tick taunt count, is presented for two frames. + const start = Math.ceil(renderTick); + const reach: number[] = []; + for (let frame = 0; frame < 140; frame += 1) { + renderTick += 0.5; + const tauntTicks = Math.max(0, 60 - (Math.ceil(renderTick) - start)); + graph.update({ ...idle, taunt_ticks: tauntTicks }, opponent, 1 / 60, renderTick / 30, false, "full", renderTick); + reach.push(bone(boxer, "gloveL").z); + } + const steps = reach.slice(1).map((z, index) => z - reach[index]!); + let held = 0; + for (let index = 1; index < steps.length - 1; index += 1) { + const around = (Math.abs(steps[index - 1]!) + Math.abs(steps[index + 1]!)) / 2; + if (around > 0.004 && Math.abs(steps[index]!) < around * 0.25) held += 1; + } + expect(held).toBeLessThan(5); + const outstretched = Math.max(...reach); + let beckons = 0; + let curled = false; + for (const z of reach) { + if (!curled && z < outstretched - 0.15) { + curled = true; + beckons += 1; + } else if (curled && z > outstretched - 0.05) { + curled = false; + } + } + expect(beckons).toBe(4); + }); +}); + +describe("glove touch", () => { + it("walks both fighters in from their marks until the gloves meet, and back onto them before the bell", () => { + const blue = makeGraph(); + const red = makeGraph({ skin: 0x6e4128, gear: 0xb91c1c }); + // Through the three-second countdown the engine holds both fighters on their marks, 2.2 m apart. + const left: FighterSnapshot = { ...baseFighter("one"), x: -180, y: 0, facing_x: 1000, facing_y: 0 }; + const right: FighterSnapshot = { ...baseFighter("two"), x: 180, y: 0, facing_x: -1000, facing_y: 0 }; + const marks = [mapping.x(-180), mapping.x(180)]; + const blobs = [0, 1, 2].map(() => new THREE.Mesh()); + const renderer = { + blobShadows: blobs, tmpA: new THREE.Vector3(marks[0], 0, 0), tmpB: new THREE.Vector3(marks[1], 0, 0), refereePosition: new THREE.Vector3(0, 0, -2), + graphs: [blue.graph, red.graph], buffer: { latest: () => null }, + }; + const updateBlobShadows = (FightRenderer.prototype as unknown as { updateBlobShadows: () => void }).updateBlobShadows; + let renderTick = 0; + let closest = Infinity; + let fastest = 0; + let atBell: number[] | null = null; + for (let frame = 0; frame < 240; frame += 1) { + renderTick += 0.5; + const ticksLeft = 90 - Math.ceil(renderTick); + const countdown = ticksLeft > 0 ? ticksLeft : null; + const before = [blue.boxer.root.position.x, red.boxer.root.position.x]; + blue.graph.setCountdown(countdown); + red.graph.setCountdown(countdown); + blue.graph.update(left, right, 1 / 60, renderTick / 30, false, "full", renderTick); + red.graph.update(right, left, 1 / 60, renderTick / 30, false, "full", renderTick); + if (frame > 0) fastest = Math.max(fastest, Math.abs(blue.boxer.root.position.x - before[0]!), Math.abs(red.boxer.root.position.x - before[1]!)); + if (ticksLeft <= 40 && ticksLeft >= 24) closest = Math.min(closest, gloveFront(red.boxer, -1) - gloveFront(blue.boxer, 1)); + if (ticksLeft === 30) { + updateBlobShadows.call(renderer); + expect(blobs[0]!.position.x).toBeCloseTo(blue.boxer.root.position.x, 6); + expect(blobs[1]!.position.x).toBeCloseTo(red.boxer.root.position.x, 6); + expect(blobs[0]!.position.x - marks[0]!).toBeGreaterThan(0.3); + } + if (countdown === null && atBell === null) atBell = [blue.boxer.root.position.x, red.boxer.root.position.x]; + } + expect(closest).toBeLessThan(0.02); + expect(closest).toBeGreaterThan(-0.03); + expect(fastest).toBeLessThan(0.025); + expect(Math.abs(atBell![0]! - marks[0]!)).toBeLessThan(1e-3); + expect(Math.abs(atBell![1]! - marks[1]!)).toBeLessThan(1e-3); + expect(Math.abs(blue.boxer.root.position.x - marks[0]!)).toBeLessThan(1e-3); + }); + + it("does not stride across the ring when the countdown is first seen halfway through the walk", () => { + const { boxer, graph } = makeGraph(); + const left: FighterSnapshot = { ...baseFighter("one"), x: -180, y: 0, facing_x: 1000, facing_y: 0 }; + const right: FighterSnapshot = { ...baseFighter("two"), x: 180, y: 0, facing_x: -1000, facing_y: 0 }; + // Waiting on his mark until the first snapshot arrives, already well into the countdown. + let renderTick = 0; + for (let frame = 0; frame < 30; frame += 1) { + renderTick += 0.5; + graph.update(left, right, 1 / 60, renderTick / 30, false, "full", renderTick); + } + let furthest = 0; + for (let frame = 0; frame < 60; frame += 1) { + renderTick += 0.5; + graph.setCountdown(60 - Math.floor(frame / 2)); + graph.update(left, right, 1 / 60, renderTick / 30, false, "full", renderTick); + for (const ankle of ["ankleL", "ankleR"] as const) furthest = Math.max(furthest, bone(boxer, ankle).x - boxer.root.position.x); + } + // The lead foot's place in the stance is 0.24 m ahead of the fighter. + expect(furthest).toBeLessThan(0.3); + }); +}); diff --git a/web/hands/src/render/gore-geometry.test.ts b/web/hands/src/render/gore-geometry.test.ts new file mode 100644 index 00000000..8cf2ae5c --- /dev/null +++ b/web/hands/src/render/gore-geometry.test.ts @@ -0,0 +1,101 @@ +import * as THREE from "three"; +import { fighter } from "../test/fixtures"; +import { Effects3D } from "./effects"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb } from "./graph"; +import { HEAD_SITES, InjuryShading } from "./injury"; +import { bakeSkinnedPart } from "./renderer"; +import { worldMapping } from "./world"; + +const gltf = await loadBoxerGlb(); +const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); + +/** A fighter of the real model standing in guard, facing his opponent. */ +function inGuard(): SkinnedBoxer { + const boxer = new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }); + const graph = new BoxingGraph(boxer, mapping); + const self = { ...fighter("one"), x: 0, y: 0, facing_x: 0, facing_y: -1000 }; + const opponent = { ...fighter("two"), x: 0, y: -150, facing_x: 0, facing_y: 1000 }; + for (let frame = 0; frame < 60; frame += 1) graph.update(self, opponent, 1 / 60, frame / 60, false, "full", frame / 2); + boxer.root.updateMatrixWorld(true); + return boxer; +} + +/** + * The jaw dislocation mask exactly as the head's vertex shader computes it: the expression is taken from + * the shader source and evaluated for a bind-space point (centimetres). + */ +function shaderJawMask(): (y: number, z: number) => number { + const material = new THREE.MeshStandardMaterial(); + const shading = new InjuryShading(material, HEAD_SITES); + const shader = { uniforms: {}, vertexShader: "#include \n#include ", fragmentShader: "#include \n#include \n#include " }; + material.onBeforeCompile(shader as unknown as THREE.WebGLProgramParametersWithUniforms, {} as THREE.WebGLRenderer); + const expression = /float jawMask = ([^;]+);/.exec(shader.vertexShader)![1]!; + const smoothstep = (edge0: number, edge1: number, x: number): number => { + const t = THREE.MathUtils.clamp((x - edge0) / (edge1 - edge0), 0, 1); + return t * t * (3 - 2 * t); + }; + const mask = new Function("smoothstep", "transformed", "uInjuryJawLevel", `return ${expression};`) as (step: typeof smoothstep, transformed: { y: number; z: number }, level: number) => number; + material.dispose(); + return (y, z) => mask(smoothstep, { y, z }, shading.uniforms.uInjuryJawLevel.value); +} + +describe("dislocated jaw", () => { + it("moves the mandible but not the throat where the head meets the body", () => { + const boxer = new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }); + const meshes: THREE.SkinnedMesh[] = []; + boxer.root.traverse((object) => { + if (object instanceof THREE.SkinnedMesh) meshes.push(object); + }); + const key = (positions: THREE.BufferAttribute | THREE.InterleavedBufferAttribute, vertex: number): string => + [positions.getX(vertex), positions.getY(vertex), positions.getZ(vertex)].map((value) => Math.round(value * 1000)).join(","); + // Head vertices that coincide with body vertices are the seam between the two meshes. + const body = meshes.find((mesh) => mesh.name === "BoxerBody")!.geometry.getAttribute("position"); + const onBody = new Set(Array.from({ length: body.count }, (_unused, vertex) => key(body, vertex))); + const head = boxer.headMesh.geometry.getAttribute("position"); + const mask = shaderJawMask(); + const seam: number[] = []; + const chin: number[] = []; + const chinSite = new THREE.Vector3(...HEAD_SITES.find((site) => site.name === "chin")!.position); + const point = new THREE.Vector3(); + for (let vertex = 0; vertex < head.count; vertex += 1) { + point.fromBufferAttribute(head, vertex); + if (onBody.has(key(head, vertex))) seam.push(mask(point.y, point.z)); + else if (point.distanceTo(chinSite) < 2.2) chin.push(mask(point.y, point.z)); + } + expect(seam.length).toBeGreaterThan(20); + expect(chin.length).toBeGreaterThan(20); + // At full dislocation the jaw shifts 1.96 cm; the seam may move a twentieth of that at most. + expect(Math.max(...seam)).toBeLessThan(0.05); + expect(Math.min(...chin)).toBeGreaterThan(0.85); + }); +}); + +describe("severed glove", () => { + it("keeps only the glove's own vertices and caps the wrist on the glove", () => { + const boxer = inGuard(); + const glove = boxer.gloveMesh("left"); + const sourceIndex = glove.geometry.getIndex()!; + const own = new Set(Array.from({ length: sourceIndex.count }, (_unused, corner) => sourceIndex.getX(corner))); + expect(own.size).toBeLessThan(glove.geometry.getAttribute("position").count); + const bone = boxer.bone("gloveL")!; + const pivot = bone.getWorldPosition(new THREE.Vector3()); + const turn = bone.getWorldQuaternion(new THREE.Quaternion()); + const baked = bakeSkinnedPart(glove, pivot, turn); + const positions = baked.geometry.getAttribute("position"); + expect(positions.count).toBe(own.size); + const index = baked.geometry.getIndex()!; + expect(index.count).toBe(sourceIndex.count); + let lowest = Infinity; + for (let corner = 0; corner < index.count; corner += 1) lowest = Math.min(lowest, positions.getY(index.getX(corner))); + + const scene = new THREE.Scene(); + const effects = new Effects3D(scene); + effects.dismemberHand(0, "left", pivot, turn, 1, 7, 0x1d4ed8, baked); + const hand = scene.children.find((child) => child instanceof THREE.Mesh && child.geometry === baked.geometry)!; + const cap = hand.children[0]!; + expect(cap.visible).toBe(true); + // The wrist cap sits on the glove's own surface, not out where the other glove's vertices were. + expect(Math.abs(cap.position.y - lowest)).toBeLessThan(0.01); + effects.dispose(); + }); +}); diff --git a/web/hands/src/render/graph.test.ts b/web/hands/src/render/graph.test.ts deleted file mode 100644 index c840cd0e..00000000 --- a/web/hands/src/render/graph.test.ts +++ /dev/null @@ -1,451 +0,0 @@ -import * as THREE from "three"; -import { FIGHTER_TEXTURE_DATA_URLS } from "../assets/fighter-textures"; -import { BONE_ADAPTER, BoxingGraph, CLIP_NAMES, FIGHTER_MODEL_SCALE, SkinnedBoxer, aimBoneLocal, loadBoxerGlb } from "./graph"; -import { worldMapping } from "./world"; -import { fighter } from "../test/fixtures"; -import type { FighterSnapshot } from "../types"; - -const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 330 }); - -const withAction = ( - base: FighterSnapshot, - action: "jab" | "straight", - id: string, - startTick: number, - startup = 3, - active = 2, - recovery = 8, -): FighterSnapshot => ({ - ...base, - action, - action_hand: "left", - action_target: "head", - action_power: "normal", - action_id: id, - action_key: `${action}:left:head:normal`, - action_start_tick: startTick, - action_startup_ticks: startup, - action_active_ticks: active, - action_recovery_ticks: recovery, - action_contact_tick: null, -}); - -describe("skinned GLB humanoid and animation graph", () => { - it("loads the embedded GLB with the full clip set and skeleton", async () => { - const gltf = await loadBoxerGlb(); - expect(gltf.animations.map((clip) => clip.name).sort()).toEqual([...CLIP_NAMES].sort()); - let skinned = 0; - const boneNames = new Set(); - gltf.scene.traverse((object) => { - if (object instanceof THREE.SkinnedMesh) skinned += 1; - if (object instanceof THREE.Bone) boneNames.add(object.name); - }); - expect(skinned).toBe(6); - for (const name of Object.values(BONE_ADAPTER)) { - expect(boneNames.has(name), name).toBe(true); - } - expect(boneNames.has("Neck_012"), "decapitation stump anchor").toBe(true); - }); - - it("drives locomotion blending and committed punch playback with phase locking", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const two = fighter("two"); - for (let i = 0; i < 20; i += 1) graph.update(fighter("one"), two, 1 / 60, i / 60, false, "full", i / 2); - const idleAction = boxer.actions.get("idle")!; - expect(idleAction.getEffectiveWeight()).toBeGreaterThan(0.8); - - const moving = { ...fighter("one"), velocity_x: 6 }; - for (let i = 0; i < 40; i += 1) graph.update(moving, two, 1 / 60, 1 + i / 60, false, "full", 10 + i / 2); - expect(boxer.actions.get("move_forward")!.getEffectiveWeight()).toBeGreaterThan(0.6); - - const movingLeft = { ...fighter("one"), velocity_y: -4 }; - for (let i = 0; i < 40; i += 1) graph.update(movingLeft, two, 1 / 60, 2 + i / 60, false, "full", 30 + i / 2); - expect(boxer.actions.get("move_lateral_left")!.getEffectiveWeight()).toBeGreaterThan(0.6); - expect(boxer.actions.get("move_lateral_right")!.getEffectiveWeight()).toBeLessThan(0.01); - const movingRight = { ...fighter("one"), velocity_y: 4 }; - for (let i = 0; i < 40; i += 1) graph.update(movingRight, two, 1 / 60, 3 + i / 60, false, "full", 50 + i / 2); - expect(boxer.actions.get("move_lateral_right")!.getEffectiveWeight()).toBeGreaterThan(0.6); - expect(boxer.actions.get("move_lateral_left")!.getEffectiveWeight()).toBeLessThan(0.01); - - const punching = withAction(fighter("one"), "jab", "a1", 30, 3, 2, 8); - for (let i = 0; i < 12; i += 1) graph.update(punching, two, 1 / 60, 2 + i / 60, false, "full", 30 + Math.floor(i / 2)); - const jab = boxer.actions.get("jab_left")!; - expect(jab.getEffectiveWeight()).toBeCloseTo(1, 5); - expect(jab.time).toBeGreaterThan(0.12); - expect(jab.time).toBeLessThan(0.3); - boxer.dispose(); - }); - - it("scales gait blend and cadence through maximum legal X and Y velocities", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const opponent = fighter("two"); - const forwardSamples: Array<{ weight: number; rate: number }> = []; - for (const [sample, velocity] of [1, 2, 6, 7].entries()) { - const moving = { ...fighter("one"), velocity_x: velocity }; - for (let frame = 0; frame < 50; frame += 1) { - graph.update(moving, opponent, 1 / 60, sample + frame / 60, false, "full", sample * 50 + frame / 2); - } - const action = boxer.actions.get("move_forward")!; - forwardSamples.push({ weight: action.getEffectiveWeight(), rate: action.getEffectiveTimeScale() }); - } - expect(forwardSamples[0]!.weight).toBeGreaterThan(0.1); - expect(forwardSamples[0]!.weight).toBeLessThan(forwardSamples[1]!.weight); - expect(forwardSamples[1]!.weight).toBeLessThan(forwardSamples[2]!.weight); - expect(forwardSamples[0]!.rate).toBeLessThan(forwardSamples[1]!.rate); - expect(forwardSamples[1]!.rate).toBeLessThan(forwardSamples[2]!.rate); - expect(forwardSamples[2]!.rate).toBeLessThan(forwardSamples[3]!.rate); - expect(forwardSamples[2]!.weight).toBeGreaterThan(0.95); - expect(forwardSamples[3]!.weight).toBeGreaterThan(0.95); - - const lateralRates: number[] = []; - for (const [sample, velocity] of [4, 7].entries()) { - const moving = { ...fighter("one"), velocity_y: velocity }; - for (let frame = 0; frame < 50; frame += 1) { - graph.update(moving, opponent, 1 / 60, 5 + sample + frame / 60, false, "full", 220 + sample * 50 + frame / 2); - } - const action = boxer.actions.get("move_lateral_right")!; - expect(action.getEffectiveWeight()).toBeGreaterThan(0.95); - lateralRates.push(action.getEffectiveTimeScale()); - } - expect(lateralRates[0]!).toBeLessThan(lateralRates[1]!); - expect(lateralRates[1]!).toBeLessThanOrEqual(1.5); - boxer.dispose(); - }); - - it("keeps low-stamina locomotion and authoritative guards visible", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const opponent = fighter("two"); - const exhausted = { ...fighter("one"), stamina: 60 }; - for (let frame = 0; frame < 30; frame += 1) { - graph.update(exhausted, opponent, 1 / 60, frame / 60, false, "full", frame / 2); - } - expect(boxer.actions.get("exhausted")!.getEffectiveWeight()).toBeGreaterThan(0.95); - - const moving = { ...exhausted, velocity_x: 6 }; - for (let frame = 0; frame < 40; frame += 1) { - graph.update(moving, opponent, 1 / 60, 1 + frame / 60, false, "full", 30 + frame / 2); - } - expect(boxer.actions.get("exhausted")!.getEffectiveWeight()).toBe(0); - expect(boxer.actions.get("move_forward")!.getEffectiveWeight()).toBeGreaterThan(0.9); - - const guarding = { ...exhausted, defense: "guard_high" as const }; - for (let frame = 0; frame < 40; frame += 1) { - graph.update(guarding, opponent, 1 / 60, 2 + frame / 60, false, "full", 50 + frame / 2); - } - expect(boxer.actions.get("exhausted")!.getEffectiveWeight()).toBe(0); - expect(boxer.actions.get("guard_high")!.getEffectiveWeight()).toBeGreaterThan(0.95); - boxer.dispose(); - }); - - it("keeps full-body layers normalized and reaches the authored knockdown pose", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const two = fighter("two"); - const totalWeight = (): number => [...boxer.actions.values()] - .reduce((total, action) => total + action.getEffectiveWeight(), 0); - - graph.update(fighter("one"), two, 1 / 60, 0, false, "full", 0); - expect(totalWeight()).toBeCloseTo(1, 5); - const punching = withAction(fighter("one"), "jab", "normalized", 0, 3, 2, 8); - graph.update(punching, two, 1 / 60, 1 / 60, false, "full", 0); - expect(totalWeight()).toBeCloseTo(1, 5); - - const downed = { ...fighter("one"), is_downed: true }; - for (let frame = 0; frame < 100; frame += 1) { - graph.update(downed, two, 1 / 60, frame / 60, false, "full", frame / 2); - } - expect(totalWeight()).toBeCloseTo(1, 5); - expect(boxer.actions.get("knockdown")!.getEffectiveWeight()).toBeCloseTo(1, 5); - - const reference = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const knockdown = reference.actions.get("knockdown")!; - knockdown.setEffectiveWeight(1).play(); - reference.mixer.setTime(knockdown.getClip().duration); - reference.root.updateMatrixWorld(true); - boxer.root.updateMatrixWorld(true); - const expectedHeadY = reference.bone("head")!.getWorldPosition(new THREE.Vector3()).y; - const actualHeadY = boxer.bone("head")!.getWorldPosition(new THREE.Vector3()).y; - expect(actualHeadY).toBeCloseTo(expectedHeadY, 2); - reference.dispose(); - boxer.dispose(); - }); - - it.each([ - ["slip_left", { defense: "slip_left" }], - ["slip_right", { defense: "slip_right" }], - ["weave", { defense: "weave" }], - ["pull", { defense: "pull" }], - ["clinch", { clinch_ticks: 20 }], - ["foul_recovery", { is_foul_recovery_target: true }], - ["stunned", { stunned_ticks: 20 }], - ["exhausted", { stamina: 60 }], - ["taunt", { taunt_ticks: 40 }], - ] as const)("presents the %s snapshot state instead of idling", async (clipName, state) => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const one = { ...fighter("one"), ...state } as FighterSnapshot; - for (let frame = 0; frame < 30; frame += 1) { - graph.update(one, fighter("two"), 1 / 60, frame / 60, false, "full", frame / 2); - } - expect(boxer.actions.get(clipName)!.getEffectiveWeight()).toBeGreaterThan(0.95); - boxer.dispose(); - }); - - it("crossfades taunt entry and recovery without dropping total pose weight", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const opponent = fighter("two"); - const totalWeight = (): number => [...boxer.actions.values()] - .reduce((total, action) => total + action.getEffectiveWeight(), 0); - for (let frame = 0; frame < 20; frame += 1) { - graph.update(fighter("one"), opponent, 1 / 60, frame / 60, false, "full", frame / 2); - } - - const taunting = { ...fighter("one"), taunt_ticks: 60 }; - expect(boxer.actions.get("taunt")!.loop).toBe(THREE.LoopOnce); - expect(boxer.actions.get("taunt")!.clampWhenFinished).toBe(true); - graph.update(taunting, opponent, 1 / 60, 1, false, "full", 20); - expect(boxer.actions.get("taunt")!.getEffectiveWeight()).toBeGreaterThan(0); - expect(boxer.actions.get("taunt")!.getEffectiveWeight()).toBeLessThan(0.5); - expect(boxer.actions.get("idle")!.getEffectiveWeight()).toBeGreaterThan(0.5); - expect(totalWeight()).toBeCloseTo(1, 5); - for (let frame = 0; frame < 30; frame += 1) { - graph.update(taunting, opponent, 1 / 60, 1 + frame / 60, false, "full", 21 + frame / 2); - } - expect(boxer.actions.get("taunt")!.getEffectiveWeight()).toBeGreaterThan(0.95); - - graph.update(fighter("one"), opponent, 1 / 60, 2, false, "full", 50); - expect(boxer.actions.get("taunt")!.getEffectiveWeight()).toBeGreaterThan(0.5); - expect(boxer.actions.get("idle")!.getEffectiveWeight()).toBeGreaterThan(0); - expect(totalWeight()).toBeCloseTo(1, 5); - for (let frame = 0; frame < 45; frame += 1) { - graph.update(fighter("one"), opponent, 1 / 60, 2 + frame / 60, false, "full", 51 + frame / 2); - } - expect(boxer.actions.get("taunt")!.getEffectiveWeight()).toBe(0); - expect(boxer.actions.get("idle")!.getEffectiveWeight()).toBeGreaterThan(0.99); - boxer.dispose(); - }); - - it("restarts identical actions on new instance ids and locks phase to start ticks", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const two = fighter("two"); - const first = withAction(fighter("one"), "jab", "a1", 0, 3, 2, 8); - for (let i = 0; i < 10; i += 1) graph.update(first, two, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - const jab = boxer.actions.get("jab_left")!; - const timeBefore = jab.time; - expect(timeBefore).toBeGreaterThan(0.05); - const second = withAction(fighter("one"), "jab", "a2", 6, 3, 2, 8); - graph.update(second, two, 1 / 60, 12 / 60, false, "full", 6); - expect(jab.time).toBeLessThan(timeBefore); - boxer.dispose(); - }); - - it("plays knockdown and getup states and reaction clips on contact", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const two = fighter("two"); - const downed = { ...fighter("one"), is_downed: true }; - for (let i = 0; i < 30; i += 1) graph.update(downed, two, 1 / 60, i / 60, false, "full", i / 2); - expect(boxer.actions.get("knockdown")!.isRunning()).toBe(true); - graph.react("hit"); - expect(boxer.actions.get("hit_head_right")!.isRunning()).toBe(true); - for (let i = 0; i < 90; i += 1) graph.update(fighter("one"), two, 1 / 60, 1 + i / 60, false, "full", 20 + i / 2); - expect(boxer.actions.get("knockdown")!.isRunning()).toBe(false); - boxer.dispose(); - }); -}); - -it("keeps fighters independent: one animating does not move or restyle the other", async () => { - const gltf = await loadBoxerGlb(); - const boxerA = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const boxerB = new SkinnedBoxer(gltf, { skin: 0x6e4128, gear: 0xb91c1c }); - const graphA = new BoxingGraph(boxerA, mapping); - const graphB = new BoxingGraph(boxerB, mapping); - const two = fighter("two"); - const punching = withAction(fighter("one"), "jab", "shared-1", 0, 3, 2, 8); - for (let i = 0; i < 10; i += 1) { - graphA.update(punching, two, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - graphB.update(fighter("two"), fighter("one"), 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - } - expect(boxerA.actions.get("jab_left")!.getEffectiveWeight()).toBeCloseTo(1, 5); - expect(boxerB.actions.get("jab_left")!.getEffectiveWeight()).toBe(0); - const headA = boxerA.bone("head")!.getWorldPosition(new THREE.Vector3()); - const headB = boxerB.bone("head")!.getWorldPosition(new THREE.Vector3()); - expect(headB.distanceTo(headA)).toBeGreaterThan(0); - boxerA.gloveGear.color.setHex(0x101010); - expect(boxerB.gloveGear.color.getHex()).toBe(new THREE.Color(0xb91c1c).getHex()); - boxerA.dispose(); - boxerB.dispose(); -}); - -it("preloads the five mapped textures and keeps every fighter material independent", async () => { - const gltf = await loadBoxerGlb(); - const boxerA = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const boxerB = new SkinnedBoxer(gltf, { skin: 0x6e4128, gear: 0xb91c1c }); - const materials = (boxer: SkinnedBoxer): Map => { - const found = new Map(); - boxer.root.traverse((object) => { - if (object instanceof THREE.SkinnedMesh && !Array.isArray(object.material)) { - found.set(object.name, object.material as THREE.MeshStandardMaterial); - } - }); - return found; - }; - const first = materials(boxerA); - const second = materials(boxerB); - const expected = { - BoxerHead: "head", - BoxerGloveLeft: "gloves", - BoxerGloveRight: "gloves", - BoxerBody: "body", - BoxerShoes: "shoes", - BoxerPants: "pants", - } as const; - expect(boxerA.root.children[0]!.scale.x).toBe(FIGHTER_MODEL_SCALE); - for (const [meshName, textureName] of Object.entries(expected)) { - const materialA = first.get(meshName)!; - const materialB = second.get(meshName)!; - expect(materialA).not.toBe(materialB); - expect(materialA.map).toBe(materialB.map); - expect(materialA.map?.colorSpace).toBe(THREE.SRGBColorSpace); - expect(materialA.map?.flipY).toBe(false); - expect((materialA.map?.image as HTMLImageElement).src).toBe(FIGHTER_TEXTURE_DATA_URLS[textureName]); - } - expect(new Set([...first.values()].map((material) => material.uuid)).size).toBe(5); - expect(new Set([...first.values()].map((material) => material.map?.uuid)).size).toBe(5); - boxerA.dispose(); - boxerB.dispose(); -}); - -it("embedded GLB bytes match their recorded sha256", async () => { - const { createHash } = await import("node:crypto"); - const { gunzipSync } = await import("node:zlib"); - const { FIGHTER_GLB_GZIP_BASE64, FIGHTER_GLB_SHA256 } = await import("../assets/fighter-glb"); - const bytes = gunzipSync(Buffer.from(FIGHTER_GLB_GZIP_BASE64, "base64")); - expect(createHash("sha256").update(bytes).digest("hex")).toBe(FIGHTER_GLB_SHA256); -}); - -it("preserves imported bone roll when the aim target is unchanged", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - new BoxingGraph(boxer, mapping); - boxer.root.updateMatrixWorld(true); - for (const [jointName, childName] of [ - ["shoulderL", "elbowL"], ["elbowL", "gloveL"], - ["shoulderR", "elbowR"], ["elbowR", "gloveR"], - ["hipL", "kneeL"], ["kneeL", "ankleL"], - ["hipR", "kneeR"], ["kneeR", "ankleR"], - ] as const) { - const joint = boxer.bone(jointName)!; - const child = boxer.bone(childName)!; - const localBefore = joint.quaternion.clone().normalize(); - const childBefore = child.getWorldPosition(new THREE.Vector3()); - aimBoneLocal(joint, child, childBefore.clone()); - boxer.root.updateMatrixWorld(true); - expect(joint.quaternion.clone().normalize().angleTo(localBefore), jointName).toBeLessThan(0.000001); - expect(child.getWorldPosition(new THREE.Vector3()).distanceTo(childBefore), childName).toBeLessThan(0.000001); - } - boxer.dispose(); -}); - - -it("makes imported-fighter wounds graphic in full mode while off preserves non-bloody trauma", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const wounded = { - ...fighter("one"), - trauma: { head: 850, body: 700, left_eye: 280, right_eye: 240, left_cut: 260, right_cut: 220, swelling: 300, bleeding: 300 }, - }; - const bloodiedOpponent = { - ...fighter("two"), - trauma: { ...fighter("two").trauma, left_cut: 260, right_cut: 220, bleeding: 300 }, - }; - const material = (mesh: THREE.Mesh): THREE.MeshStandardMaterial => mesh.material as THREE.MeshStandardMaterial; - - graph.update(wounded, bloodiedOpponent, 1 / 60, 0, false, "full", 0); - const fullCut = material(boxer.trauma.cutL).opacity; - const fullStreakWidth = boxer.trauma.streakL.scale.x; - const fullGlove = boxer.gloveGear.color.clone(); - graph.update(wounded, bloodiedOpponent, 1 / 60, 0.1, false, "reduced", 1); - const reducedCut = material(boxer.trauma.cutL).opacity; - const reducedStreakWidth = boxer.trauma.streakL.scale.x; - expect(fullCut).toBeGreaterThan(reducedCut); - expect(reducedCut).toBeGreaterThan(0); - expect(fullStreakWidth).toBeGreaterThan(reducedStreakWidth); - const colorDistance = (left: THREE.Color, right: THREE.Color): number => Math.abs(left.r - right.r) + Math.abs(left.g - right.g) + Math.abs(left.b - right.b); - expect(colorDistance(fullGlove, boxer.gearBaseColor)).toBeGreaterThan(colorDistance(boxer.gloveGear.color, boxer.gearBaseColor)); - - graph.update(wounded, bloodiedOpponent, 1 / 60, 0.2, false, "off", 2); - for (const overlay of [boxer.trauma.cutL, boxer.trauma.cutR, boxer.trauma.streakL, boxer.trauma.streakR, boxer.trauma.noseStreak, boxer.trauma.mouthBlood, boxer.trauma.bodyStreak]) { - expect(material(overlay).opacity).toBe(0); - } - expect(material(boxer.trauma.bruiseL).opacity).toBeGreaterThan(0); - expect(material(boxer.trauma.ribL).opacity).toBeGreaterThan(0); - expect(boxer.gloveGear.color.getHex()).toBe(boxer.gearBaseColor.getHex()); - boxer.dispose(); -}); - -it("presents and restores visible jaw and shoulder dislocations", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const graph = new BoxingGraph(boxer, mapping); - const jawMaterial = boxer.trauma.jaw.material as THREE.MeshStandardMaterial; - const jawRest = boxer.trauma.jaw.position.clone(); - graph.setArcadeDislocation("jaw"); - graph.update(fighter("one"), fighter("two"), 1 / 60, 0, false, "full", 0); - expect(jawMaterial.opacity).toBe(1); - expect(boxer.trauma.jaw.position.distanceTo(jawRest)).toBeGreaterThan(0.05); - expect(jawMaterial.color.getHex()).toBe(0xa9744f); - graph.setArcadeDislocation(null); - expect(jawMaterial.opacity).toBe(0); - expect(boxer.trauma.jaw.position.distanceTo(jawRest)).toBeLessThan(0.000001); - - graph.setArcadeDislocation("shoulder_left"); - graph.update(fighter("one"), fighter("two"), 1 / 60, 0.1, false, "full", 1); - boxer.root.updateMatrixWorld(true); - const shoulder = boxer.bone("shoulderL")!.getWorldPosition(new THREE.Vector3()); - const elbow = boxer.bone("elbowL")!.getWorldPosition(new THREE.Vector3()); - expect(elbow.sub(shoulder).normalize().y).toBeLessThan(-0.75); - boxer.dispose(); -}); - -it("hides and restores only the separable head for arcade decapitation", async () => { - const gltf = await loadBoxerGlb(); - const boxer = new SkinnedBoxer(gltf, { skin: 0xa9744f, gear: 0x1d4ed8 }); - const meshes = new Map(); - boxer.root.traverse((object) => { - if (object instanceof THREE.SkinnedMesh) meshes.set(object.name, object); - }); - boxer.setDecapitated(true); - expect(boxer.isDecapitated).toBe(true); - expect(meshes.get("BoxerHead")!.visible).toBe(false); - expect(boxer.bone("head")!.visible).toBe(false); - for (const name of ["BoxerBody", "BoxerGloveLeft", "BoxerGloveRight", "BoxerShoes", "BoxerPants"]) { - expect(meshes.get(name)!.visible).toBe(true); - } - boxer.mixer.clipAction(THREE.AnimationClip.findByName(gltf.animations, "knockdown")!).play(); - boxer.mixer.update(0.25); - boxer.setDecapitated(false); - expect(meshes.get("BoxerHead")!.visible).toBe(true); - expect(boxer.bone("head")!.visible).toBe(true); - boxer.setHandDismembered("left", true); - expect(boxer.isHandDismembered("left")).toBe(true); - expect(meshes.get("BoxerGloveLeft")!.visible).toBe(false); - expect(meshes.get("BoxerGloveRight")!.visible).toBe(true); - boxer.setHandDismembered("left", false); - expect(meshes.get("BoxerGloveLeft")!.visible).toBe(true); - boxer.dispose(); -}); diff --git a/web/hands/src/render/graph.ts b/web/hands/src/render/graph.ts index c00183de..59df7563 100644 --- a/web/hands/src/render/graph.ts +++ b/web/hands/src/render/graph.ts @@ -1,16 +1,19 @@ import * as THREE from "three"; import { GLTFLoader, type GLTF } from "three/examples/jsm/loaders/GLTFLoader.js"; import { clone as cloneSkeleton } from "three/examples/jsm/utils/SkeletonUtils.js"; -import { GLOVE_HITBOX_RADIUS, HURTBOXES, punchTiming, totalTicks, type PunchTiming } from "../manifest"; +import { GLOVE_HITBOX_RADIUS, HURTBOXES, cancelsRecovery, punchTiming, recoveryCancelAge, totalTicks, type PunchTiming } from "../manifest"; import type { BloodLevel } from "../settings"; -import type { FighterSnapshot, Hand, Power, PunchClass, SemanticAction, Target } from "../types"; +import type { CombatEvent, FighterSnapshot, Hand, Power, PunchAction, PunchClass, SemanticAction, Target } from "../types"; import { FIGHTER_GLB_GZIP_BASE64 } from "../assets/fighter-glb"; import { BONE_ADAPTER } from "./skeleton"; export { BONE_ADAPTER }; import { FIGHTER_TEXTURE_DATA_URLS } from "../assets/fighter-textures"; -import type { WorldMapping } from "./world"; +import { BODY_SITES, HEAD_SITES, InjuryShading, applyBodyTrauma, applyHeadTrauma } from "./injury"; +import { PoseSolver, STANCE, easeIn, easeOut, mirrorX, smoothstep, vec, type FootTarget, type HandTarget, type PoseDescription } from "./poser"; +import { SolvedRig } from "./rig"; +import { POST_RADIUS, type WorldMapping } from "./world"; -export const FIGHTER_MODEL_SCALE = 0.96; +export const FIGHTER_MODEL_SCALE = 1; type FighterTexture = keyof typeof FIGHTER_TEXTURE_DATA_URLS; @@ -24,6 +27,7 @@ const MATERIAL_TEXTURE: Readonly> = { const cachedTextures = new Map(); const cachedTextureLoads = new Map>(); let cachedGltf: Promise | null = null; +let loadedScene: THREE.Object3D | null = null; function configureFighterTexture(texture: THREE.Texture): THREE.Texture { texture.colorSpace = THREE.SRGBColorSpace; @@ -60,11 +64,36 @@ export function loadBoxerGlb(): Promise { const gltf = decompressFighterGlb().then((bytes) => new Promise((resolve, reject) => { new GLTFLoader().parse(bytes, "", resolve, (error: unknown) => reject(error instanceof Error ? error : new Error(String(error)))); })); - cachedGltf = Promise.all([gltf, preloadFighterTextures()]).then(([loaded]) => loaded); + cachedGltf = Promise.all([gltf, preloadFighterTextures()]).then(([loaded]) => { + loadedScene = loaded.scene; + return loaded; + }); } return cachedGltf; } +/** + * Every fighter shares the model's geometry and textures, and a rematch builds a new renderer on the + * same graphics context: the last renderer frees their graphics copies, and the next uploads them again. + */ +export function releaseFighterGpu(): void { + releaseSharedGpu(loadedScene, cachedTextures.values()); +} + +export function releaseSharedGpu(scene: THREE.Object3D | null, textures: Iterable): void { + scene?.traverse((object) => { + if (object instanceof THREE.Mesh) object.geometry.dispose(); + }); + for (const texture of textures) texture.dispose(); +} + +/** Each skinned mesh's skeleton holds its bones in a texture on the graphics card. */ +export function disposeSkeletons(root: THREE.Object3D): void { + root.traverse((object) => { + if (object instanceof THREE.SkinnedMesh) object.skeleton.dispose(); + }); +} + function fighterTexture(name: FighterTexture): THREE.Texture { const existing = cachedTextures.get(name); if (existing !== undefined) return existing; @@ -74,16 +103,22 @@ function fighterTexture(name: FighterTexture): THREE.Texture { } interface AppliedFighterMaterials { - readonly skin: readonly THREE.MeshPhysicalMaterial[]; + readonly skin: readonly THREE.MeshStandardMaterial[]; readonly gloves: THREE.MeshStandardMaterial; readonly owned: readonly THREE.Material[]; + readonly headInjury: InjuryShading; + readonly bodyInjury: InjuryShading; } export function applyFighterSkin(target: THREE.Object3D, palette: BoxerPaletteColors): AppliedFighterMaterials { - const skin: THREE.MeshPhysicalMaterial[] = []; + // An official never takes damage or sweats: plain materials, injury state that shades nothing, and no shadow. + const official = palette.bodyMap !== undefined; + const skin: THREE.MeshStandardMaterial[] = []; const owned: THREE.Material[] = []; const bySource = new Map(); let gloves: THREE.MeshStandardMaterial | null = null; + let headInjury: InjuryShading | null = null; + let bodyInjury: InjuryShading | null = null; target.traverse((object) => { if (!(object instanceof THREE.SkinnedMesh) || Array.isArray(object.material)) return; const sourceName = object.material.name; @@ -92,42 +127,36 @@ export function applyFighterSkin(target: THREE.Object3D, palette: BoxerPaletteCo let material = bySource.get(sourceName); if (material === undefined) { const isSkin = sourceName === "MHeadMat0" || sourceName === "MBodyMat0"; - const color = sourceName === "GlovesMat0" || sourceName === "PantsMat0" ? palette.gear : 0xffffff; - material = isSkin - ? new THREE.MeshPhysicalMaterial({ map: fighterTexture(textureName), color, roughness: 0.58, metalness: 0.02, clearcoat: 0.25, clearcoatRoughness: 0.6 }) - : new THREE.MeshStandardMaterial({ map: fighterTexture(textureName), color, roughness: 0.4, metalness: 0.03 }); + const color = sourceName === "GlovesMat0" ? palette.gear : sourceName === "PantsMat0" ? (palette.pants ?? palette.gear) : 0xffffff; + const map = sourceName === "MBodyMat0" && palette.bodyMap !== undefined ? palette.bodyMap : fighterTexture(textureName); + material = isSkin && !official + ? new THREE.MeshPhysicalMaterial({ map, color, roughness: 0.58, metalness: 0.02, clearcoat: 0.25, clearcoatRoughness: 0.6 }) + : new THREE.MeshStandardMaterial({ map, color, roughness: isSkin ? (sourceName === "MBodyMat0" ? 0.85 : 0.58) : 0.4, metalness: isSkin ? 0.02 : 0.03 }); material.name = sourceName; bySource.set(sourceName, material); owned.push(material); - if (material instanceof THREE.MeshPhysicalMaterial) skin.push(material); + if (isSkin) skin.push(material); if (sourceName === "GlovesMat0") gloves = material; + if (sourceName === "MHeadMat0") headInjury = new InjuryShading(official ? null : material, HEAD_SITES); + if (sourceName === "MBodyMat0") bodyInjury = new InjuryShading(official ? null : material, BODY_SITES); } object.material = material; - object.castShadow = true; + object.castShadow = !official; object.receiveShadow = true; object.frustumCulled = false; }); - if (skin.length !== 2 || gloves === null || owned.length !== 5) { + if (skin.length !== 2 || gloves === null || owned.length !== 5 || headInjury === null || bodyInjury === null) { throw new Error(`fighter GLB material contract failed: ${skin.length} skin, ${owned.length} total`); } - return { skin, gloves, owned }; + return { skin, gloves, owned, headInjury, bodyInjury }; } -export const CLIP_NAMES = [ - "idle", "move_forward", "move_backward", "move_lateral_left", "move_lateral_right", - "guard_high", "guard_low", "slip_left", "slip_right", "weave", "pull", - "jab_left", "jab_right", "straight_left", "straight_right", "hook_left", "hook_right", - "uppercut_left", "uppercut_right", - "block_head_left", "block_head_right", "block_body_left", "block_body_right", - "hit_head_left", "hit_head_right", "hit_body_left", "hit_body_right", - "knockdown", "getup", "clinch", "foul_recovery", "stunned", "exhausted", "taunt", -] as const; - -export type ClipName = (typeof CLIP_NAMES)[number]; - export interface BoxerPaletteColors { readonly skin: number; readonly gear: number; + readonly pants?: number; + /** An official's shirt. Officials get plain materials: no injury shading, no sweat and no shadow (see applyFighterSkin). */ + readonly bodyMap?: THREE.Texture; } export type ArcadeDislocation = "jaw" | "shoulder_left" | "shoulder_right"; @@ -137,16 +166,15 @@ const smoothAngle = (current: number, target: number, rate: number, dt: number): const delta = ((target - current + Math.PI) % (Math.PI * 2) + Math.PI * 2) % (Math.PI * 2) - Math.PI; return current + delta * (1 - Math.exp(-rate * dt)); }; -const clamp01 = (value: number): number => Math.max(0, Math.min(1, value)); +const clamp = THREE.MathUtils.clamp; export class SkinnedBoxer { readonly root = new THREE.Group(); - readonly mixer: THREE.AnimationMixer; - readonly actions = new Map(); readonly bones = new Map(); + readonly rig: SolvedRig; /** Bone-derived measurements in world units (after MODEL_SCALE). */ readonly metrics: { armUpper: number; armFore: number; legThigh: number; legShin: number; headRestY: number; chestRestY: number; ankleRestY: number }; - private readonly skinMaterials: readonly THREE.MeshPhysicalMaterial[]; + private readonly skinMaterials: readonly THREE.MeshStandardMaterial[]; private readonly ownedMaterials: readonly THREE.Material[]; private readonly gearMaterial: THREE.MeshStandardMaterial; private readonly headMeshes: THREE.SkinnedMesh[] = []; @@ -155,7 +183,8 @@ export class SkinnedBoxer { private readonly dismemberedHands: Record = { left: false, right: false }; readonly gearBaseColor: THREE.Color; readonly skinBaseColor: THREE.Color; - private readonly overlays: TraumaOverlays; + readonly headInjury: InjuryShading; + readonly bodyInjury: InjuryShading; constructor(gltf: GLTF, palette: BoxerPaletteColors) { const instance = cloneSkeleton(gltf.scene); @@ -165,6 +194,8 @@ export class SkinnedBoxer { this.skinMaterials = materials.skin; this.ownedMaterials = materials.owned; this.gearMaterial = materials.gloves; + this.headInjury = materials.headInjury; + this.bodyInjury = materials.bodyInjury; this.gearBaseColor = new THREE.Color(palette.gear); this.skinBaseColor = new THREE.Color(palette.skin); instance.traverse((object) => { @@ -181,50 +212,37 @@ export class SkinnedBoxer { throw new Error(`fighter GLB requires one ${side} glove mesh, found ${this.handMeshes[side].length}`); } } - this.mixer = new THREE.AnimationMixer(instance); - for (const clip of gltf.animations) { - const action = this.mixer.clipAction(clip); - this.actions.set(clip.name as ClipName, action); - if ( - /^(jab|straight|hook|uppercut|block_|hit_)/.test(clip.name) - || clip.name === "knockdown" - || clip.name === "getup" - || clip.name === "taunt" - ) { - action.setLoop(THREE.LoopOnce, 1); - action.clampWhenFinished = true; - } - } - const missingClips = CLIP_NAMES.filter((name) => !this.actions.has(name)); - if (missingClips.length > 0) throw new Error(`fighter GLB missing clips: ${missingClips.join(", ")}`); - instance.updateMatrixWorld(true); - const jointDistance = (from: string, to: string): number => - this.bone(from)!.getWorldPosition(new THREE.Vector3()).distanceTo(this.bone(to)!.getWorldPosition(new THREE.Vector3())); + this.root.updateMatrixWorld(true); + this.rig = new SolvedRig(this.root); + const rigMetrics = this.rig.metrics; this.metrics = { - armUpper: jointDistance("shoulderL", "elbowL"), - armFore: jointDistance("elbowL", "gloveL"), - legThigh: jointDistance("hipL", "kneeL"), - legShin: jointDistance("kneeL", "ankleL"), - headRestY: this.bone("head")!.getWorldPosition(new THREE.Vector3()).y, - chestRestY: this.bone("chest")!.getWorldPosition(new THREE.Vector3()).y, - ankleRestY: this.bone("ankleL")!.getWorldPosition(new THREE.Vector3()).y, + armUpper: rigMetrics.armL.upper, + armFore: rigMetrics.armL.lower, + legThigh: rigMetrics.legL.upper, + legShin: rigMetrics.legL.lower, + headRestY: rigMetrics.headHeight, + chestRestY: rigMetrics.chestHeight, + ankleRestY: rigMetrics.ankleHeight, }; - this.overlays = buildTraumaOverlays(this.bone("head")!, this.bone("chest")!, palette.skin); } bone(name: string): THREE.Bone | null { return this.bones.get(BONE_ADAPTER[name] ?? name) ?? null; } - get trauma(): TraumaOverlays { - return this.overlays; - } - get gloveGear(): THREE.MeshStandardMaterial { return this.gearMaterial; } - get skin(): THREE.MeshPhysicalMaterial { + get headMesh(): THREE.SkinnedMesh { + return this.headMeshes[0]!; + } + + gloveMesh(side: Hand): THREE.SkinnedMesh { + return this.handMeshes[side][0]!; + } + + get skin(): THREE.MeshStandardMaterial { return this.skinMaterials[0]!; } @@ -247,167 +265,86 @@ export class SkinnedBoxer { for (const mesh of this.handMeshes[side]) mesh.visible = !value; } + /** Sweat sheen; only a fighter's skin is clearcoated, an official's stays matte. */ setSkinClearcoat(value: number): void { - for (const material of this.skinMaterials) material.clearcoat = value; + for (const material of this.skinMaterials) if (material instanceof THREE.MeshPhysicalMaterial) material.clearcoat = value; } dispose(): void { - this.mixer.stopAllAction(); for (const material of this.ownedMaterials) material.dispose(); - this.overlays.dispose(); + disposeSkeletons(this.root); } } -export interface TraumaOverlays { - readonly bruiseL: THREE.Mesh; - readonly bruiseR: THREE.Mesh; - readonly swellL: THREE.Mesh; - readonly swellR: THREE.Mesh; - readonly cutL: THREE.Mesh; - readonly cutR: THREE.Mesh; - readonly streakL: THREE.Mesh; - readonly streakR: THREE.Mesh; - readonly noseStreak: THREE.Mesh; - readonly mouthBlood: THREE.Mesh; - readonly cheekL: THREE.Mesh; - readonly cheekR: THREE.Mesh; - readonly ribL: THREE.Mesh; - readonly ribR: THREE.Mesh; - readonly bodyBruise: THREE.Mesh; - readonly bodyStreak: THREE.Mesh; - readonly jaw: THREE.Mesh; - dispose(): void; -} +const BLOODED_GLOVE_COLOR = new THREE.Color(0x5c0a0e); + +export type ReactionKind = "block" | "hit"; -function overlayMesh(geometry: THREE.BufferGeometry, color: number, emissive = 0x000000): THREE.Mesh { - const mesh = new THREE.Mesh( - geometry, - new THREE.MeshStandardMaterial({ color, roughness: 0.7, transparent: true, opacity: 0, emissive }), - ); - mesh.castShadow = false; - return mesh; +interface FootState { + readonly planted: THREE.Vector3; + readonly from: THREE.Vector3; + readonly to: THREE.Vector3; + progress: number; + stepping: boolean; + duration: number; } -function buildTraumaOverlays(head: THREE.Bone, chest: THREE.Bone, skinColor: number): TraumaOverlays { - const overlays: THREE.Mesh[] = []; - const add = (mesh: THREE.Mesh, parent: THREE.Bone, position: [number, number, number], scale: [number, number, number] = [1, 1, 1]): THREE.Mesh => { - const parentScale = parent.getWorldScale(new THREE.Vector3()); - const compensation = 1 / Math.max(0.0001, parentScale.x); - mesh.position.set( - position[0] * 1.3 * compensation, - position[1] * 1.25 * compensation, - (position[2] * 1.35 + 0.045) * compensation, - ); - mesh.scale.set(scale[0] * compensation, scale[1] * compensation, scale[2] * compensation); - mesh.userData.baseScale = compensation; - parent.add(mesh); - overlays.push(mesh); - return mesh; - }; - const bruiseL = add(overlayMesh(new THREE.SphereGeometry(0.042, 12, 10), 0x4a1c56), head, [0.05, 0.15, 0.085], [1, 0.72, 0.5]); - const bruiseR = add(overlayMesh(new THREE.SphereGeometry(0.042, 12, 10), 0x4a1c56), head, [-0.05, 0.15, 0.085], [1, 0.72, 0.5]); - const swellL = add(overlayMesh(new THREE.SphereGeometry(0.035, 12, 10), 0x6b3572), head, [0.052, 0.155, 0.088]); - const swellR = add(overlayMesh(new THREE.SphereGeometry(0.035, 12, 10), 0x6b3572), head, [-0.052, 0.155, 0.088]); - const cutL = add(overlayMesh(new THREE.BoxGeometry(0.05, 0.008, 0.01), 0x7f0d14, 0x2a0306), head, [0.05, 0.178, 0.104]); - const cutR = add(overlayMesh(new THREE.BoxGeometry(0.05, 0.008, 0.01), 0x7f0d14, 0x2a0306), head, [-0.05, 0.178, 0.104]); - const streakL = add(overlayMesh(new THREE.BoxGeometry(0.014, 0.1, 0.006), 0x8a0f16, 0x30040a), head, [0.052, 0.115, 0.106]); - const streakR = add(overlayMesh(new THREE.BoxGeometry(0.014, 0.1, 0.006), 0x8a0f16, 0x30040a), head, [-0.052, 0.115, 0.106]); - const noseStreak = add(overlayMesh(new THREE.BoxGeometry(0.011, 0.07, 0.006), 0x8a0f16, 0x30040a), head, [0.008, 0.075, 0.118]); - const mouthBlood = add(overlayMesh(new THREE.BoxGeometry(0.03, 0.012, 0.006), 0x8a0f16, 0x30040a), head, [0.02, 0.052, 0.104]); - const cheekL = add(overlayMesh(new THREE.SphereGeometry(0.028, 10, 8), 0x6b3572), head, [0.068, 0.095, 0.075]); - const cheekR = add(overlayMesh(new THREE.SphereGeometry(0.028, 10, 8), 0x6b3572), head, [-0.068, 0.095, 0.075]); - const ribL = add(overlayMesh(new THREE.SphereGeometry(0.09, 12, 10), 0x5c2450), chest, [0.16, 0.08, 0.02], [0.5, 1.2, 0.7]); - const ribR = add(overlayMesh(new THREE.SphereGeometry(0.09, 12, 10), 0x5c2450), chest, [-0.16, 0.08, 0.02], [0.5, 1.2, 0.7]); - const bodyBruise = add(overlayMesh(new THREE.SphereGeometry(0.1, 12, 10), 0x4a1c56), chest, [0.02, 0.05, 0.1], [1.05, 1.35, 0.55]); - const bodyStreak = add(overlayMesh(new THREE.BoxGeometry(0.05, 0.24, 0.008), 0x8a0f16, 0x30040a), chest, [0.03, 0.08, 0.155]); - bodyStreak.rotation.z = 0.12; - const jaw = add(overlayMesh(new THREE.SphereGeometry(0.06, 12, 10), skinColor), head, [0, -0.005, 0.07], [1.3, 0.48, 0.82]); - jaw.userData.restPosition = jaw.position.clone(); - return { - bruiseL, bruiseR, swellL, swellR, cutL, cutR, streakL, streakR, noseStreak, mouthBlood, - cheekL, cheekR, ribL, ribR, bodyBruise, bodyStreak, jaw, - dispose() { - for (const mesh of overlays) { - mesh.geometry.dispose(); - (mesh.material as THREE.Material).dispose(); - mesh.removeFromParent(); - } - }, - }; +interface Spring3 { + readonly value: THREE.Vector3; + readonly velocity: THREE.Vector3; } -export function applyTraumaToOverlays(overlays: TraumaOverlays, fighter: FighterSnapshot, opponentBlood: number, blood: BloodLevel): void { - const trauma = fighter.trauma; - const cutScale = blood === "off" ? 0 : blood === "reduced" ? 0.35 : 1; - const graphicScale = blood === "full" ? 1.8 : 1; - const mat = (mesh: THREE.Mesh): THREE.MeshStandardMaterial => mesh.material as THREE.MeshStandardMaterial; - const scale = (mesh: THREE.Mesh, x: number, y: number, z: number): void => { - const base = typeof mesh.userData.baseScale === "number" ? mesh.userData.baseScale : 1; - mesh.scale.set(x * base, y * base, z * base); - }; - const bruise = (value: number): number => Math.min(0.85, value / 170 + trauma.swelling / 420); - mat(overlays.bruiseL).opacity = bruise(trauma.left_eye); - mat(overlays.bruiseR).opacity = bruise(trauma.right_eye); - const cutL = Math.min(1, trauma.left_cut / 150 + trauma.bleeding / 450); - const cutR = Math.min(1, trauma.right_cut / 150 + trauma.bleeding / 450); - mat(overlays.cutL).opacity = cutL * cutScale; - mat(overlays.cutR).opacity = cutR * cutScale; - scale(overlays.cutL, 1 + cutL * 0.55 * graphicScale, 1 + cutL * 0.7, 1); - scale(overlays.cutR, 1 + cutR * 0.55 * graphicScale, 1 + cutR * 0.7, 1); - const swellL = Math.min(1.35, trauma.left_eye / 260 + trauma.swelling / 560); - const swellR = Math.min(1.35, trauma.right_eye / 260 + trauma.swelling / 560); - scale(overlays.swellL, 0.25 + swellL * 1.15, 0.25 + swellL * 1.15, 0.25 + swellL * 1.15); - scale(overlays.swellR, 0.25 + swellR * 1.15, 0.25 + swellR * 1.15, 0.25 + swellR * 1.15); - mat(overlays.swellL).opacity = Math.min(0.92, swellL * 1.1); - mat(overlays.swellR).opacity = Math.min(0.92, swellR * 1.1); - const cheek = Math.min(1, trauma.head / 900 + trauma.swelling / 800); - scale(overlays.cheekL, 0.2 + cheek * 1.05, 0.2 + cheek * 1.05, 0.2 + cheek * 1.05); - scale(overlays.cheekR, 0.2 + cheek * 0.95, 0.2 + cheek * 0.95, 0.2 + cheek * 0.95); - mat(overlays.cheekL).opacity = cheek * 0.8; - mat(overlays.cheekR).opacity = cheek * 0.75; - const dripL = Math.min(1.9, (trauma.left_cut + trauma.bleeding) / 220); - const dripR = Math.min(1.9, (trauma.right_cut + trauma.bleeding) / 220); - scale(overlays.streakL, graphicScale, 0.15 + dripL * graphicScale, 1); - scale(overlays.streakR, graphicScale, 0.15 + dripR * graphicScale, 1); - mat(overlays.streakL).opacity = Math.min(1, dripL) * cutScale; - mat(overlays.streakR).opacity = Math.min(1, dripR) * cutScale; - const nose = Math.min(1.6, trauma.head / 600 + trauma.bleeding / 340); - scale(overlays.noseStreak, graphicScale, 0.2 + nose * graphicScale, 1); - mat(overlays.noseStreak).opacity = Math.min(1, nose) * cutScale; - const mouth = Math.min(1, trauma.head / 650 + trauma.bleeding / 360); - scale(overlays.mouthBlood, 1 + mouth * graphicScale, 1 + mouth * 0.8, 1); - mat(overlays.mouthBlood).opacity = mouth * cutScale; - const rib = Math.min(1, trauma.body / 750); - scale(overlays.ribL, 0.5 + rib * 0.35, 1.2 + rib * 0.5, 0.7 + rib * 0.2); - scale(overlays.ribR, 0.5 + rib * 0.3, 1.2 + rib * 0.4, 0.7 + rib * 0.2); - mat(overlays.ribL).opacity = rib * 0.85; - mat(overlays.ribR).opacity = rib * 0.8; - mat(overlays.bodyBruise).opacity = Math.min(0.7, trauma.body / 950); - const smear = Math.min(1.5, trauma.body / 450 + trauma.bleeding / 340); - scale(overlays.bodyStreak, 1 + smear * 0.55 * graphicScale, 0.3 + smear * graphicScale, 1); - mat(overlays.bodyStreak).opacity = Math.min(1, smear) * cutScale; - void opponentBlood; +/** A press of the viewer's own punch, kept until it plays. */ +interface OwnPress { + readonly action: PunchAction & { readonly id: string }; + readonly timing: PunchTiming; + readonly leadTicks: number; + readonly pressedAt: number; + /** The input frame that carried it, once known. */ + sequence: number | null; + /** The server has started it, so it is no longer the server's to refuse. */ + started: boolean; + /** Real ticks since the key was pressed. */ + waited: number; } -const BLOODED_GLOVE_COLOR = new THREE.Color(0x5c0a0e); -const LOCOMOTION = [ - "idle", "move_forward", "move_backward", "move_lateral_left", "move_lateral_right", -] as const satisfies readonly ClipName[]; -const ONE_SHOTS: readonly ClipName[] = [ - "jab_left", "jab_right", "straight_left", "straight_right", "hook_left", "hook_right", - "uppercut_left", "uppercut_right", - "block_head_left", "block_head_right", "block_body_left", "block_body_right", - "hit_head_left", "hit_head_right", "hit_body_left", "hit_body_right", - "knockdown", "getup", "clinch", "foul_recovery", "stunned", "exhausted", "taunt", -]; -const PUNCH_CLIP = (punchClass: PunchClass, hand: Hand): ClipName => `${punchClass}_${hand}` as ClipName; +const springStep = (spring: Spring3, dt: number, stiffness: number, damping: number, limit: number): void => { + const value = spring.value; + const velocity = spring.velocity; + velocity.addScaledVector(value, -stiffness * dt).multiplyScalar(Math.exp(-damping * dt)); + value.addScaledVector(velocity, dt); + if (value.length() > limit) value.setLength(limit); +}; + +const PUNCH_CONTACT_OFFSET = 0.06; +/** Damage of the hardest hit the engine deals (a countered power uppercut in a combination, about 153). */ +const HARDEST_HIT = 150; +const KNOCKDOWN_FALL_SECONDS = 0.75; +/** + * The get-up runs lying -> all fours (RISE_FOURS) -> one knee (RISE_KNEE) -> standing (1). While he is down it + * follows the get-up meter, as far as one knee; once the server lets him up he can walk at once and act after + * a 20-tick stun, so the rest takes at most GETUP_SECONDS, or GETUP_HURRIED_SECONDS once he moves or punches. + */ +const RISE_FOURS = 0.38; +const RISE_KNEE = 0.72; +const GETUP_SECONDS = 0.5; +const GETUP_HURRIED_SECONDS = 0.2; +/** How fast the get-up follows the meter while he is down, pushing up and sinking back. */ +const RISE_PUSH_RATE = 0.55; +const RISE_SINK_RATE = 0.4; +/** Rolling off the back onto all fours is a big movement, never hurried past this. */ +const RISE_ROLL_RATE = 0.7; + +const SIDE_FROM_HAND = (hand: Hand): "L" | "R" => (hand === "left" ? "L" : "R"); export class BoxingGraph { readonly boxer: SkinnedBoxer; + private readonly solver: PoseSolver; private yaw = 0; + private yawInitialized = false; private rootX: number | null = null; private rootZ = 0; - private activePunch: THREE.AnimationAction | null = null; + private punchActive = false; private punchAgeTicks = 0; private punchTotalTicks = 1; private punchClass: PunchClass = "jab"; @@ -417,86 +354,469 @@ export class BoxingGraph { private punchTiming: PunchTiming = punchTiming("jab", "head", "normal"); private actionId: string | null = null; private completedActionId: string | null = null; - private predictedId: string | null = null; - private predictedAtSeconds = -1; - private predictionAgeTicks = 0; - private predictedClip: ClipName = "jab_left"; - private predictedTotalTicks = 13; + /** Id of the viewer's own punch while its animation is the one started on the key press. */ + private ownActionId: string | null = null; + /** Ticks the key press led the server's presentation, absorbed by stretching the punch's startup. */ + private ownLeadTicks = 0; + private ownAuthoritativeAge: number | null = null; + /** Real ticks the own punch has waited for the server, and how long that is expected to take. */ + private ownWaitedTicks = 0; + private ownExpectedTicks = 0; + /** The server turned the punch down before it landed, so the glove is coming back the way it went. */ + private ownPulled = false; + /** Input frame that carried the press, once known: once a snapshot has it, the punch has started there or never will. */ + private ownSequence: number | null = null; + /** A snapshot has shown the server playing the punch. */ + private ownStarted = false; + /** When the key was pressed, in seconds. */ + private ownPressedAt = 0; + /** The server refused the punch or cut it off before contact, so the pull-back is final. */ + private ownRefused = false; + /** A press made during a punch: the server holds it until that punch lets it go, and so does the graph. */ + private ownQueued: OwnPress | null = null; + /** This fighter's newest punch the server reported meeting the opponent, and whether it was parried. */ + private contactId: string | null = null; + private contactParried = false; + /** The fighters as last shown, for the recovery cancel's stamina and stun checks. */ + private shownFighter: FighterSnapshot | null = null; + private shownOpponent: FighterSnapshot | null = null; + /** Own punches already played or cut short here; the server's copy of them is not played again. */ + private readonly retiredOwnIds: string[] = []; private hitstop = 0; - private reactionAction: THREE.AnimationAction | null = null; - private stateAction: THREE.AnimationAction | null = null; - private stateWeight = 0; - private stateRequested = false; + private hitstopScale = 1; private downState: "up" | "falling" | "down" | "rising" = "up"; private fallAge = 0; - private riseAge = 0; - private opponentDrop = 0; - private readonly liveOpponentHead = new THREE.Vector3(0, 0.97, 0); + /** How far along the get-up he is (see RISE_KNEE), and where it stood when the server let him up. */ + private riseProgress = 0; + private riseFrom = 0; + private fallSide = 0; + private fallProne = false; + /** The fall played: the punch's own, or the nearest variant that keeps the body inside the ropes, moved in as far as it must. */ + private landProne = false; + private landSide = 0; + private readonly landShift = new THREE.Vector3(); + private landSettled = false; + private readonly liveOpponentHead = new THREE.Vector3(); private hasLiveHead = false; - private defenseWeight = 0; - private defenseClip: "guard_high" | "guard_low" | "slip_left" | "slip_right" | "weave" | "pull" = "guard_high"; - private hitstopScale = 1; - private plantedL: THREE.Vector3 | null = null; - private plantedR: THREE.Vector3 | null = null; - private readonly locomotionWeights: Record = { - idle: 1, - move_forward: 0, - move_backward: 0, - move_lateral_left: 0, - move_lateral_right: 0, - }; - private readonly scratchA = new THREE.Vector3(); + /** + * Where the opponent's head would be without a slip, weave or pull: its offset from his root, learnt + * while he stands his ground, is held from the moment he evades until his head is back. + */ + private readonly guardOpponentHead = new THREE.Vector3(); + private readonly opponentHeadOffset = new THREE.Vector3(); + private opponentSteadySeconds = 0; + /** How far the punch's aim has moved from that head onto the live one: only once the punch is known to have met him. */ + private followHead = 0; + private aimActionId: string | null = null; + private readonly headKick: Spring3 = { value: new THREE.Vector3(), velocity: new THREE.Vector3() }; + private readonly torsoKick: Spring3 = { value: new THREE.Vector3(), velocity: new THREE.Vector3() }; + private readonly rootKick: Spring3 = { value: new THREE.Vector3(), velocity: new THREE.Vector3() }; + /** x: how far the elbow on the side a body hook struck drops to cover the ribs (+ right, - left). */ + private readonly coverKick: Spring3 = { value: new THREE.Vector3(), velocity: new THREE.Vector3() }; + /** A body uppercut folds the fighter over it once the lift has peaked. */ + private foldDelay = 0; + private pendingFold = 0; + private guardKick = 0; + private guardHigh = 0; + private guardLow = 0; + private slip = 0; + private weave = 0; + private weaveTime = 0; + private pull = 0; + private crouchExtra = 0; + private bouncePhase = 0; + private weightPhase = 0; + private stunPhase = 0; + private feintTimer = 2; + private feint = 0; + private stunAmount = 0; + private tired = 0; + private clinchWeight = 0; + private foulWeight = 0; + private tauntWeight = 0; + /** Render tick the taunt ends on (see latchEndTick). */ + private tauntEnd: number | null = null; + private lastSpeed = 0; + private readonly stool: { group: THREE.Group; dispose: () => void }; + /** Root position and yaw the stool was set down at, where it stays while the fighter rises off it. */ + private readonly stoolRoot = new THREE.Vector3(); + private stoolYaw = 0; + private readonly enswell: { group: THREE.Group; dispose: () => void }; + private readonly treatTarget = new THREE.Vector3(); + private readonly treatScratch = new THREE.Vector3(); + private readonly treatFacing = new THREE.Vector3(0, 0, -1); + private readonly treatFacingLocal = new THREE.Vector3(); + private treatSide = 1; + private treating = false; + private treatWeight = 0; + private resting = false; + private seated = 0; + private stillTime = 0; + private celebrateTime = 0; + private celebration = 0; + private waveTime = 0; + private wave = 0; + private breakTime = 0; + private breakWeight = 0; + private readonly breakFighters: [THREE.Vector3, THREE.Vector3] = [new THREE.Vector3(), new THREE.Vector3()]; + private breakAimed = false; + private attending = false; + private attendWeight = 0; + private countdownTicks: number | null = null; + /** Render tick the opening countdown ends on (see latchEndTick). */ + private countdownEnd: number | null = null; + private touchWeight = 0; + /** The walk in to the glove touch: offset from the engine position, and its velocity for the footwork. */ + private readonly touchOffset = new THREE.Vector3(); + private readonly touchVelocity = new THREE.Vector3(); + /** Pose lab: keep the impact dent at full depth for review. */ + debugHoldImpact = false; + private readonly feet: [FootState, FootState] = [ + { planted: new THREE.Vector3(), from: new THREE.Vector3(), to: new THREE.Vector3(), progress: 1, stepping: false, duration: 0.2 }, + { planted: new THREE.Vector3(), from: new THREE.Vector3(), to: new THREE.Vector3(), progress: 1, stepping: false, duration: 0.2 }, + ]; + private feetInitialized = false; + private dislocation: ArcadeDislocation | null = null; + private readonly scratch = new THREE.Vector3(); private readonly scratchB = new THREE.Vector3(); private readonly scratchC = new THREE.Vector3(); + private readonly scratchD = new THREE.Vector3(); + private readonly scratchE = new THREE.Vector3(); + private readonly clinchCentre = new THREE.Vector3(); + private readonly clinchForward = new THREE.Vector3(); + private readonly clinchTemp = new THREE.Vector3(); private readonly scratchQ = new THREE.Quaternion(); - private readonly aimTarget = new THREE.Vector3(); - private readonly aimShoulder = new THREE.Vector3(); - private readonly aimTo = new THREE.Vector3(); - private readonly aimPole = new THREE.Vector3(); - private readonly aimBend = new THREE.Vector3(); - private readonly aimElbow = new THREE.Vector3(); - private readonly lockAnkle = new THREE.Vector3(); - private readonly lockPinned = new THREE.Vector3(); - private readonly lockHip = new THREE.Vector3(); - private readonly lockTo = new THREE.Vector3(); - private readonly lockPole = new THREE.Vector3(); - private readonly lockBend = new THREE.Vector3(); - private readonly lockKnee = new THREE.Vector3(); - private dislocation: ArcadeDislocation | null = null; + private readonly headWorld = new THREE.Vector3(); + private readonly hand = { L: this.makeHand(), R: this.makeHand() }; + /** Scratch for the punch path, so a punch allocates nothing per frame. */ + private readonly punchGuard = this.makeHand(); + private readonly punchDir = new THREE.Vector3(); + private readonly punchContact = new THREE.Vector3(); + private readonly punchStart = new THREE.Vector3(); + private readonly punchSweepFrom = new THREE.Vector3(); + private readonly punchSweepTo = new THREE.Vector3(); + private readonly punchMid = new THREE.Vector3(); + private readonly foot = { L: this.makeFoot(), R: this.makeFoot() }; + private readonly torso = { + hips: new THREE.Vector3(), + hipsYaw: 0, + hipsPitch: 0, + hipsRoll: 0, + shouldersYaw: 0, + spinePitch: 0, + spineRoll: 0, + headYaw: 0, + headPitch: 0, + headRoll: 0, + headOffset: new THREE.Vector3(), + }; + private readonly pose: PoseDescription; + /** Scratch poses for the fall and the get-up: the live pose, the two being blended and the result. */ + private readonly downStanding = downPose(); + private readonly downFrom = downPose(); + private readonly downTo = downPose(); + private readonly downResult = downPose(); + /** The last pose written by `writeDown` and its share of the standing pose, where a fall that cuts into a get-up starts. */ + private downStand = 1; + private readonly fallStart = downPose(); + private fallStartStand = 1; + private fallFromGetUp = false; - constructor(boxer: SkinnedBoxer, private readonly mapping: WorldMapping) { + private readonly referee: boolean; + private refereeCount = 0; + private refereeCounting = false; + /** Render tick the referee's count last changed on; the counting arm is timed from it. */ + private countChangedTick: number | null = null; + + constructor(boxer: SkinnedBoxer, private readonly mapping: WorldMapping, options: { referee?: boolean } = {}) { this.boxer = boxer; - for (const name of LOCOMOTION) { - const action = boxer.actions.get(name)!; - action.setEffectiveWeight(name === "idle" ? 1 : 0); - action.play(); + this.referee = options.referee === true; + this.solver = new PoseSolver(boxer.rig); + this.pose = { torso: this.torso, handL: this.hand.L, handR: this.hand.R, footL: this.foot.L, footR: this.foot.R, shrugL: 0, shrugR: 0 }; + this.stool = buildStool(); + this.stool.group.position.set(0, 0, 0.02); + boxer.root.add(this.stool.group); + this.enswell = buildEnswell(); + boxer.rig.bones.gloveL.add(this.enswell.group); + } + + /** Between rounds the fighter walks to the corner, and once still, sits on the stool. */ + setResting(resting: boolean): void { + this.resting = resting; + } + + get stoolVisible(): boolean { + return this.stool.group.visible; + } + + /** Raises both gloves overhead for a stoppage win, then settles back to the guard. */ + celebrate(seconds = 4.4): void { + this.celebrateTime = seconds; + } + + /** + * Drops every transient animation state (falls, reactions, celebrations, + * smoothing) so the next update snaps to its snapshot; used around the + * knockout replay. `downed` seeds the lying pose instead of standing. + */ + resetTransient(downed = false): void { + this.downState = downed ? "down" : "up"; + this.landSettled = false; + this.fallAge = downed ? KNOCKDOWN_FALL_SECONDS : 0; + this.riseProgress = 0; + this.hitstop = 0; + this.hitstopScale = 1; + for (const spring of [this.headKick, this.torsoKick, this.rootKick, this.coverKick]) { + spring.value.set(0, 0, 0); + spring.velocity.set(0, 0, 0); } + this.foldDelay = 0; + this.pendingFold = 0; + this.guardKick = 0; + this.stunAmount = 0; + this.celebrateTime = 0; + this.celebration = 0; + this.waveTime = 0; + this.wave = 0; + this.seated = 0; + this.stillTime = 0; + this.rootX = null; + this.yawInitialized = false; + this.feetInitialized = false; + this.retirePunch(); + this.ownQueued = null; + this.completedActionId = null; + this.retiredOwnIds.length = 0; + } + + /** Referee wave-off: both arms sweep crossing overhead to call the fight. */ + waveOff(seconds = 2.6): void { + this.waveTime = seconds; + } + + /** Ticks left in the opening countdown, or null outside it; drives the glove touch before the bell. */ + setCountdown(ticksRemaining: number | null): void { + this.countdownTicks = ticksRemaining; + } + + /** Cornerman: lean in over the top rope and work on the seated fighter while attending. */ + attend(active: boolean): void { + this.attending = active; + } + + /** + * Cutman: crouch by a seated fighter and press the enswell on the eye at `eye` (world). `facing` is + * the direction the fighter's face points and `side` is 1 when the eye is the fighter's left. + */ + treat(eye: THREE.Vector3 | null, facing?: THREE.Vector3, side = 1): void { + this.treating = eye !== null; + if (eye === null) return; + this.treatTarget.copy(eye); + if (facing !== undefined) this.treatFacing.copy(facing); + this.treatSide = side; + } + + /** Referee break: both arms push out and apart at chest height to separate a clinch. */ + breakClinch(seconds = 1.3): void { + this.breakTime = seconds; + } + + /** Whether the referee is separating a clinch. */ + get breaking(): boolean { + return this.breakTime > 0; + } + + /** Where the two fighters stand (world, on the canvas): the break puts a palm on each one's chest. */ + aimBreak(first: THREE.Vector3, second: THREE.Vector3): void { + this.breakFighters[0].copy(first); + this.breakFighters[1].copy(second); + this.breakAimed = true; + } + + private makeHand(): { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 } { + return { position: new THREE.Vector3(), knuckles: new THREE.Vector3(0, 1, 0), palm: new THREE.Vector3(0, 0, 1), pole: new THREE.Vector3(0, -1, 0) }; + } + + private makeFoot(): { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 } { + return { position: new THREE.Vector3(), toe: new THREE.Vector3(0, 0, 1), heel: 0, pole: new THREE.Vector3(0, 0, 1) }; } get currentRoot(): { x: number; z: number } { return { x: this.rootX ?? 0, z: this.rootZ }; } - predict(action: SemanticAction, timeSeconds: number, tickRate: number): void { + get isDown(): boolean { + return this.downState !== "up"; + } + + setRefereeCount(counting: boolean, count: number): void { + if (counting !== this.refereeCounting || count !== this.refereeCount) this.countChangedTick = null; + this.refereeCounting = counting; + this.refereeCount = count; + } + + /** + * Starts the viewer's own punch on the key press. `leadTicks` estimates how far ahead of the + * server's presentation that is (input latency plus the interpolation delay); the startup is + * stretched by it so the glove arrives when the hit is shown. A press made during a punch waits, as + * it does on the server, until that punch lets it go. + */ + predict(action: SemanticAction, timeSeconds: number, tickRate: number, leadTicks = 0, expected?: PunchTiming): void { if (action.kind !== "punch" || action.id === undefined) return; - this.predictedId = action.id; - this.predictedAtSeconds = timeSeconds; - this.predictionAgeTicks = 0; - this.predictedClip = PUNCH_CLIP(action.class, action.hand); - const timing = punchTiming(action.class, action.target, action.power); + const press: OwnPress = { + action: { ...action, id: action.id }, + timing: expected ?? punchTiming(action.class, action.target, action.power), + leadTicks, + pressedAt: timeSeconds, + sequence: null, + started: false, + waited: 0, + }; + // The server keeps one press waiting and a newer one takes its place. Two presses less than half a + // tick apart usually reach it before the same step, so only the second starts there: it replaces + // the first here too, unless the server has already started it. (Two presses sent in one input + // frame are only ever the newer one; `acknowledge` catches that once the newer one has gone out.) + const unstarted = this.punchActive && this.ownActionId !== null && this.ownAuthoritativeAge === null && !this.ownPulled && !this.ownStarted; + if (unstarted && (timeSeconds - this.ownPressedAt) * tickRate < SAME_STEP_TICKS) { + // Not retired: if the first did start after all, it plays on the server's timeline. + this.ownActionId = null; + } else if (this.punchActive && !this.ownPulled) { + // Behind a punch the server holds the press until a combination cuts the recovery short or the + // punch ends. A press it already holds is replaced only if it is still held when this one + // arrives; otherwise it has started by then, and this one waits behind it and plays when shown. + if (this.ownQueued !== null && this.followUpStartAge(this.ownQueued) - this.punchAgeTicks <= leadTicks) return; + if (this.punchAgeTicks < this.followUpStartAge(press)) { + this.ownQueued = press; + return; + } + } + this.ownQueued = null; + this.retirePunch(); + this.startOwnPunch(press, leadTicks); + } + + /** True while the viewer's own punch, started on the key press, is playing. */ + get ownPunchActive(): boolean { + return this.punchActive && this.ownActionId !== null; + } + + /** + * Squares the viewer's own punches with the newest snapshot, which is ahead of the one on screen by + * the interpolation delay. `sequenceOf` gives the input frame that carried a press once it has gone + * out. Once the snapshot has that frame, the punch has started on the server or never will: a guard + * raised in the same tick, a newer press or a stun clears it there. A stun, a clinch or the end of + * the fight phase also clears a press still waiting and cuts off a punch the server did start, unless + * it had already landed. Either way the glove comes straight back. `contacts` are the snapshot's + * contact events for this fighter's punches. + */ + acknowledge(server: FighterSnapshot, fighting: boolean, contacts: readonly CombatEvent[] = [], sequenceOf: ((actionId: string) => number | null) | null = null): void { + for (const event of contacts) { + if (event.action_id === null || !CONNECTING_CONTACTS.has(event.kind)) continue; + if (event.action_id !== this.contactId) { + this.contactId = event.action_id; + this.contactParried = false; + } + if (event.kind === "perfect_block") this.contactParried = true; + } + const cutOff = !fighting || server.stunned_ticks > 0 || server.clinch_ticks > 0 || server.clinch_startup_ticks > 0; + const queued = this.ownQueued; + if (queued !== null) { + queued.sequence ??= sequenceOf?.(queued.action.id) ?? null; + if (server.action_id === queued.action.id) queued.started = true; + else if (!queued.started && (cutOff || (queued.sequence !== null && server.last_input_sequence >= queued.sequence && server.queued_actions === 0))) this.ownQueued = null; + } + if (!this.punchActive || this.ownActionId === null || this.ownPulled || this.ownRefused) return; + if (!this.ownStarted) this.ownSequence ??= sequenceOf?.(this.ownActionId) ?? null; + const started = server.action_id === this.ownActionId; + if (started) this.ownStarted = true; + const held = this.ownQueued; + if (held !== null && held.sequence !== null && sequenceOf !== null && !this.ownStarted && this.ownSequence === null && this.ownAuthoritativeAge === null) { + // A later press went out and this one never did: the input queue kept only the newer press, so + // the server never sees this one and starts that one as soon as it gets it. + this.ownActionId = null; + this.ownQueued = null; + this.retirePunch(); + this.startOwnPunch(held, Math.max(0, held.leadTicks - held.waited)); + return; + } + const refused = started + ? cutOff && server.action_contact_tick === null + : !this.ownStarted && this.ownAuthoritativeAge === null + && (cutOff || (this.ownSequence !== null && server.last_input_sequence >= this.ownSequence && server.queued_actions === 0)); + if (!refused) return; + this.ownRefused = true; + // Before contact the glove comes back the way it went; after it the punch simply finishes. + if (this.punchAgeTicks < this.punchTiming.startup) this.ownPulled = true; + } + + /** Plays the viewer's own press from its first frame, its startup stretched by `leadTicks`. */ + private startOwnPunch(press: OwnPress, leadTicks: number): void { + const { action, timing } = press; this.punchClass = action.class; this.punchHand = action.hand; this.punchTarget = action.target; this.punchPower = action.power; this.punchTiming = timing; - this.predictedTotalTicks = totalTicks(timing); - const inRecovery = this.actionId !== null && this.punchAgeTicks / this.punchTotalTicks > 0.55; - if (this.actionId === null || inRecovery) { - this.actionId = null; - this.beginPunch(this.boxer.actions.get(this.predictedClip)!, this.predictedTotalTicks); - this.punchAgeTicks = 0; + this.punchTotalTicks = Math.max(1, totalTicks(timing)); + this.punchAgeTicks = 0; + this.punchActive = true; + this.ownActionId = action.id; + this.ownLeadTicks = clamp(leadTicks, 0, MAX_OWN_LEAD_TICKS); + this.ownExpectedTicks = Math.max(0, leadTicks); + this.ownSequence = press.sequence; + this.ownStarted = press.started; + this.ownPressedAt = press.pressedAt; + } + + /** + * Age of the punch being played at which the server starts `press`, held behind it: the cancel age + * when a combination may cut the recovery short (the engine's rule, with the fighters as shown), + * otherwise the tick after the punch ends. + */ + private followUpStartAge(press: OwnPress): number { + const fighter = this.shownFighter; + const opponent = this.shownOpponent; + const id = this.actionId ?? this.ownActionId; + const landed = id !== null && id === this.contactId && !this.contactParried; + if (fighter !== null && opponent !== null && cancelsRecovery(this.punchClass, landed, press.action, fighter.stamina, opponent.stunned_ticks > 0)) { + return recoveryCancelAge(this.punchTiming); + } + return this.punchTotalTicks + 1; + } + + /** + * Starts the held press when the server would: at the cancel age when a combination cuts the + * recovery short, the tick after the punch ends otherwise, and at once if the punch in front of it + * was refused. Its startup is stretched by whatever lead the wait has not used up. + */ + private releaseQueuedPress(simDt: number, ended: boolean): void { + const press = this.ownQueued; + if (press === null) return; + press.waited += simDt * 30; + if (this.punchActive && !this.ownPulled && this.punchAgeTicks < this.followUpStartAge(press)) return; + this.ownQueued = null; + this.retirePunch(); + this.startOwnPunch(press, Math.max(ended ? 1 : 0, press.leadTicks - press.waited)); + } + + /** Marks the punch being played as done so neither copy of it is started again. */ + private retirePunch(): void { + if (this.actionId !== null) this.completedActionId = this.actionId; + if (this.ownActionId !== null) { + this.retiredOwnIds.push(this.ownActionId); + if (this.retiredOwnIds.length > 6) this.retiredOwnIds.shift(); } - void tickRate; + this.actionId = null; + this.punchActive = false; + this.ownActionId = null; + this.ownLeadTicks = 0; + this.ownAuthoritativeAge = null; + this.ownWaitedTicks = 0; + this.ownExpectedTicks = 0; + this.ownPulled = false; + this.ownSequence = null; + this.ownStarted = false; + this.ownRefused = false; } landedHit(blocked: boolean): void { @@ -505,51 +825,141 @@ export class BoxingGraph { setArcadeDislocation(dislocation: ArcadeDislocation | null): void { this.dislocation = dislocation; - const jaw = this.boxer.trauma.jaw; - const rest = jaw.userData.restPosition as THREE.Vector3; - jaw.position.copy(rest); - jaw.rotation.set(0, 0, 0); - (jaw.material as THREE.MeshStandardMaterial).opacity = dislocation === "jaw" ? 1 : 0; - } - - react(kind: "block" | "hit", target: Target = "head", direction = 1): void { - const side = direction < 0 ? "left" : "right"; - const clip = this.boxer.actions.get(`${kind}_${target}_${side}` as ClipName); - if (clip === undefined) return; - if (this.reactionAction !== null && this.reactionAction !== clip) this.reactionAction.stop(); - this.reactionAction = clip; - clip.reset().setLoop(THREE.LoopOnce, 1); - clip.setEffectiveWeight(0).play(); - } - - private setPunch(action: THREE.AnimationAction, ageTicks: number): void { - const clip = action.getClip(); - const source = punchTiming(this.punchClass, "head", "normal"); - const sourceRecovery = Math.max(1, clip.duration * 30 - source.startup - source.active); - const target = this.punchTiming; - const age = THREE.MathUtils.clamp(ageTicks, 0, totalTicks(target)); - let clipTicks: number; - if (age <= target.startup) { - clipTicks = target.startup > 0 ? (age / target.startup) * source.startup : source.startup; - } else if (age <= target.startup + target.active) { - const activeAge = age - target.startup; - clipTicks = source.startup + (target.active > 0 ? (activeAge / target.active) * source.active : source.active); + this.boxer.headInjury.setJaw(dislocation === "jaw" ? 1 : 0); + } + + /** + * Contact-synchronised reaction. `punchClass`/`hand` describe the incoming + * punch so the head snaps along the real impact line; `direction` is the + * legacy world-x sign used when the class is unknown. `amount` is the hit's + * damage, which tops out at `HARDEST_HIT`. + */ + react(kind: ReactionKind, target: Target = "head", direction = 1, punchClass: PunchClass | null = null, hand: Hand | null = null, amount = 90): void { + const force = clamp(amount / HARDEST_HIT, 0, 1); + const scale = (0.55 + force * 1.05) * (kind === "block" ? 0.35 : 1); + const lateral = hand === "left" ? 1 : hand === "right" ? -1 : direction >= 0 ? -1 : 1; + if (target === "body") { + switch (punchClass) { + case "hook": + // Into the ribs from the side: the trunk bends around the fist, the hips give way from it and + // the elbow on that side drops to cover. + this.torsoKick.velocity.x += 3 * scale; + this.torsoKick.velocity.z += 4.6 * scale * lateral; + this.rootKick.velocity.x += 0.5 * scale * lateral; + this.coverKick.velocity.x += 2.2 * scale * lateral; + break; + case "uppercut": + // Up under the ribs: the blow lifts him onto his toes and straightens him, then he folds over it. + this.rootKick.velocity.y += 0.9 * scale; + this.torsoKick.velocity.x -= 1.6 * scale; + this.foldDelay = 0.1; + this.pendingFold = 5.2 * scale; + break; + default: + this.torsoKick.velocity.x += 4.6 * scale; + break; + } + this.rootKick.velocity.z -= 0.45 * scale; + this.headKick.velocity.z -= 0.6 * scale; + this.headKick.velocity.y -= 0.7 * scale; + this.guardKick = Math.max(this.guardKick, 0.6 * scale); } else { - const recoveryAge = age - target.startup - target.active; - clipTicks = source.startup + source.active - + (target.recovery > 0 ? (recoveryAge / target.recovery) * sourceRecovery : sourceRecovery); + if (kind === "hit") this.guardKick = Math.max(this.guardKick, 0.4 * scale); + switch (punchClass) { + case "hook": + this.headKick.velocity.x += 2.6 * scale * lateral; + this.headKick.velocity.z -= 0.7 * scale; + this.torsoKick.velocity.z += 0.9 * scale * lateral; + break; + case "uppercut": + this.headKick.velocity.y += 2.2 * scale; + this.headKick.velocity.z -= 1.2 * scale; + this.torsoKick.velocity.x -= 1.2 * scale; + break; + case "straight": + this.headKick.velocity.z -= 2.4 * scale; + this.torsoKick.velocity.x -= 0.6 * scale; + break; + default: + this.headKick.velocity.z -= 1.5 * scale; + this.torsoKick.velocity.x -= 0.35 * scale; + break; + } + this.rootKick.velocity.z -= 0.45 * scale; + if (kind === "block") this.guardKick = Math.max(this.guardKick, 0.9 * scale); + } + if (kind === "hit") { + this.dentSurface(target, lateral, punchClass, force); + // A knockdown only gives the count, so every clean hit sets how the fighter would go down: a + // hook or a body shot pitches him forward onto his face, anything else onto his back, and + // either way he falls away from the side the punch came from, a hook twisting him furthest. + this.fallSide = punchClass === "hook" ? lateral : lateral * 0.5; + this.fallProne = punchClass === "hook" || target === "body"; } - action.time = THREE.MathUtils.clamp(clipTicks / 30, 0, Math.max(0.001, clip.duration - 0.001)); } - private beginPunch(action: THREE.AnimationAction, totalTicksValue: number): void { - if (this.activePunch !== null && this.activePunch !== action) this.activePunch.stop(); - this.activePunch = action; - action.reset(); - action.setLoop(THREE.LoopOnce, 1); - action.setEffectiveWeight(0).play(); - action.paused = true; - this.punchTotalTicks = Math.max(1, totalTicksValue); + /** Transient compression of the struck surface at contact; the injury shading releases it. */ + private dentSurface(target: Target, lateral: number, punchClass: PunchClass | null, force: number): void { + const depth = 1.1 + force * 2.1; + if (target === "body") { + const site = punchClass === "hook" ? (lateral > 0 ? "rightRibs" : "leftRibs") : "solarPlexus"; + this.boxer.bodyInjury.impact(site, [punchClass === "hook" ? lateral * depth * 0.8 : 0, 0, -depth], 9); + return; + } + if (punchClass === "hook") this.boxer.headInjury.impact(lateral > 0 ? "rightCheek" : "leftCheek", [lateral * depth, 0, -depth * 0.35], 5.5); + else if (punchClass === "uppercut") this.boxer.headInjury.impact("chin", [0, depth * 0.7, -depth * 0.6], 5); + else this.boxer.headInjury.impact(punchClass === "jab" ? "nose" : "mouth", [0, 0, -depth], 4.5); + } + + private stepFeet(dt: number, mirror: number, speed: number, velocityWorld: THREE.Vector3, rootPosition: THREE.Vector3, yaw: number): void { + const desired = this.scratch; + const rotate = this.scratchQ.setFromAxisAngle(worldUpVector, yaw); + for (let index = 0; index < 2; index += 1) { + const foot = this.feet[index]!; + const isLead = (index === 0) === (mirror > 0); + const offset = isLead ? STANCE.leadFoot : STANCE.rearFoot; + if (this.referee) desired.set((index === 0 ? 0.16 : -0.16), 0, index === 0 ? 0.02 : -0.02).applyQuaternion(rotate).add(rootPosition); + else desired.set(offset.x * mirror, 0, offset.z).applyQuaternion(rotate).add(rootPosition); + desired.y = 0; + if (!this.feetInitialized) { + foot.planted.copy(desired); + foot.progress = 1; + foot.stepping = false; + continue; + } + if (foot.stepping) { + foot.progress = Math.min(1, foot.progress + dt / foot.duration); + if (foot.progress >= 1) { + foot.stepping = false; + foot.planted.copy(foot.to); + } + continue; + } + const other = this.feet[1 - index]!; + const drift = foot.planted.distanceTo(desired); + const threshold = speed > 0.05 ? 0.09 : 0.14; + if (drift > threshold && !other.stepping) { + foot.stepping = true; + foot.progress = 0; + foot.duration = clamp(0.24 - speed * 0.07, 0.15, 0.24); + foot.from.copy(foot.planted); + foot.to.copy(desired).addScaledVector(velocityWorld, foot.duration * 0.6); + foot.to.y = 0; + } + } + this.feetInitialized = true; + } + + /** Writes the foot's world position into `out` and returns how high it is lifted mid-step. */ + private footWorld(index: 0 | 1, out: THREE.Vector3): number { + const foot = this.feet[index]; + if (!foot.stepping) { + out.copy(foot.planted); + return 0; + } + const t = easeOut(foot.progress, 1.6); + out.copy(foot.from).lerp(foot.to, t); + return Math.sin(foot.progress * Math.PI) * 0.055; } update( @@ -564,29 +974,413 @@ export class BoxingGraph { ): void { const boxer = this.boxer; const mirror = fighter.stance === "orthodox" ? 1 : -1; + const motionScale = reducedMotion ? 0.35 : 1; - const worldX = this.mapping.x(fighter.x); - const worldZ = this.mapping.z(fighter.y); + const touch = this.touchWalk(fighter, opponent, dt, sampledTick); + const worldX = this.mapping.x(fighter.x) + touch.x; + const worldZ = this.mapping.z(fighter.y) + touch.z; if (this.rootX === null) { this.rootX = worldX; this.rootZ = worldZ; } - const maxStep = 0.05; - this.rootX += THREE.MathUtils.clamp(worldX - this.rootX, -maxStep, maxStep); - this.rootZ += THREE.MathUtils.clamp(worldZ - this.rootZ, -maxStep, maxStep); - const targetYaw = Math.atan2(this.mapping.x(opponent.x) - worldX, (this.mapping.z(opponent.y) - worldZ) * 0.45); - this.yaw = smoothAngle(this.yaw, targetYaw, 7, dt); + const maxStep = ROOT_FOLLOW_SPEED * Math.max(dt, 1 / 60); + this.rootX += clamp(worldX - this.rootX, -maxStep, maxStep); + this.rootZ += clamp(worldZ - this.rootZ, -maxStep, maxStep); + const targetYaw = Math.atan2(fighter.facing_x, -fighter.facing_y); + if (!this.yawInitialized) { + this.yaw = targetYaw; + this.yawInitialized = true; + } + // On the canvas and getting up he turns with his whole body on the ground, so more slowly. + const turnRate = this.punchActive ? 3 : this.downState === "up" ? 9 : 4; + this.yaw = smoothAngle(this.yaw, targetYaw, turnRate, dt); boxer.root.position.set(this.rootX, 0, this.rootZ); - boxer.root.rotation.set(0, this.yaw + 0.5 * mirror, 0); + boxer.root.rotation.set(0, this.yaw, 0); - const fatigueScale = 0.82 + (fighter.stamina / Math.max(1, fighter.maximum_stamina)) * 0.18; this.hitstop = Math.max(0, this.hitstop - dt); this.hitstopScale = this.hitstop > 0 ? 0.12 : 1; + const simDt = dt * this.hitstopScale; + + this.syncAction(fighter, opponent, sampledTick, simDt); + if (!this.debugHoldImpact) { + this.boxer.headInjury.update(simDt); + this.boxer.bodyInjury.update(simDt); + } + + if (opponentHeadWorld !== undefined) this.trackOpponentHead(opponent, opponentHeadWorld, dt); + + const velocityWorld = this.scratchB.set(this.mapping.x(fighter.velocity_x) * 30, 0, this.mapping.z(fighter.velocity_y) * 30).add(this.touchVelocity); + const speed = velocityWorld.length(); + this.lastSpeed = speed; + this.stillTime = speed < 0.03 ? this.stillTime + dt : 0; + const wantSeated = this.resting && this.stillTime > 0.2 && this.downState === "up"; + this.seated = smooth(this.seated, wantSeated ? 1 : 0, wantSeated ? 2.2 : 4, dt); + const onStool = this.resting && this.stillTime > 0.05 && this.downState === "up"; + if (onStool) { + this.stoolRoot.set(this.rootX, 0, this.rootZ); + this.stoolYaw = this.yaw; + } + // The round can start with the fighter still seated: the stool stays where it stood until his hips are clear of it. + this.stool.group.visible = onStool || (this.seated > STOOL_CLEAR_SEATED && this.downState === "up"); + this.stool.group.position.set(this.stoolRoot.x - this.rootX, 0, this.stoolRoot.z - this.rootZ) + .add(this.scratch.set(0, 0, 0.02).applyAxisAngle(worldUpVector, this.stoolYaw)) + .applyAxisAngle(worldUpVector, -this.yaw); + this.stool.group.rotation.y = this.stoolYaw - this.yaw; + this.celebrateTime = Math.max(0, this.celebrateTime - dt); + this.celebration = smooth(this.celebration, this.celebrateTime > 0 && this.downState === "up" ? 1 : 0, 3.5, dt); + this.waveTime = Math.max(0, this.waveTime - dt); + this.wave = smooth(this.wave, this.waveTime > 0 && this.downState === "up" ? 1 : 0, 4, dt); + this.breakTime = Math.max(0, this.breakTime - dt); + this.breakWeight = smooth(this.breakWeight, this.breakTime > 0 && this.downState === "up" ? 1 : 0, 6, dt); + this.attendWeight = smooth(this.attendWeight, this.attending ? 1 : 0, 2.5, dt); + this.treatWeight = smooth(this.treatWeight, this.treating ? 1 : 0, 3, dt); + this.enswell.group.visible = this.treatWeight > 0.4; + const touching = this.countdownTicks !== null && this.countdownTicks <= TOUCH_GLOVES_START_TICKS && this.countdownTicks >= TOUCH_GLOVES_END_TICKS; + this.touchWeight = smooth(this.touchWeight, touching ? 1 : 0, 6, dt); + const stamina = fighter.stamina / Math.max(1, fighter.maximum_stamina); + this.tired = smooth(this.tired, clamp((0.55 - stamina) / 0.5, 0, 1), 2, dt); + this.stunAmount = smooth(this.stunAmount, Math.min(1, fighter.stunned_ticks / 24), 8, dt); + const defending = fighter.defense; + this.guardHigh = smooth(this.guardHigh, defending === "guard_high" ? 1 : 0, 14, dt); + this.guardLow = smooth(this.guardLow, defending === "guard_low" ? 1 : 0, 14, dt); + const slipTarget = defending === "slip_left" ? 1 : defending === "slip_right" ? -1 : 0; + this.slip = smooth(this.slip, slipTarget, 16, dt); + const weaving = defending === "weave"; + this.weaveTime = weaving ? this.weaveTime + dt : 0; + this.weave = smooth(this.weave, weaving ? 1 : 0, 14, dt); + this.pull = smooth(this.pull, defending === "pull" ? 1 : 0, 14, dt); + this.clinchWeight = smooth(this.clinchWeight, fighter.clinch_ticks > 0 || fighter.clinch_startup_ticks > 0 ? 1 : 0, 10, dt); + this.foulWeight = smooth(this.foulWeight, fighter.is_foul_recovery_target ? 1 : 0, 8, dt); + this.tauntWeight = smooth(this.tauntWeight, fighter.taunt_ticks > 0 ? 1 : 0, 10, dt); + this.tauntEnd = latchEndTick(this.tauntEnd, sampledTick, fighter.taunt_ticks > 0 ? fighter.taunt_ticks : null); - if (fighter.action_id !== null && fighter.action_id !== this.actionId && fighter.action_id !== this.completedActionId) { + springStep(this.headKick, dt, 190, 7.5, 0.24); + springStep(this.torsoKick, dt, 150, 7, 0.7); + springStep(this.rootKick, dt, 120, 8, 0.12); + springStep(this.coverKick, dt, 110, 15, 0.3); + if (this.foldDelay > 0) { + this.foldDelay -= dt; + if (this.foldDelay <= 0) { + this.torsoKick.velocity.x += this.pendingFold; + this.pendingFold = 0; + } + } + this.guardKick = Math.max(0, this.guardKick - dt * 2.4); + + this.updateDownState(fighter, dt, speed); + + const bounceTempo = (1.9 - this.tired * 0.7) * (1 - this.stunAmount * 0.6); + this.bouncePhase += dt * bounceTempo * Math.PI * 2 * motionScale; + this.weightPhase += dt * 0.55 * Math.PI * 2 * motionScale; + this.stunPhase += dt * 5.5; + this.feintTimer -= dt; + if (this.feintTimer <= 0 && !this.punchActive && speed < 0.05 && this.downState === "up") { + this.feintTimer = 2.5 + (this.bouncePhase % 1.7); + this.feint = 1; + } + this.feint = Math.max(0, this.feint - dt * 3.5); + + // Feet. + const rootPosition = this.scratchC.set(this.rootX, 0, this.rootZ); + // Getting up, the feet are planted again under him and step as he turns or walks, ready for the standing pose. + if (this.downState === "up" || this.downState === "rising") this.stepFeet(dt, mirror, speed, velocityWorld, rootPosition, this.yaw); + const rootQuatInverse = this.scratchQ.setFromAxisAngle(worldUpVector, -this.yaw); + const lead = mirror > 0 ? this.foot.L : this.foot.R; + const rear = mirror > 0 ? this.foot.R : this.foot.L; + const leadIndex: 0 | 1 = mirror > 0 ? 0 : 1; + const rearIndex: 0 | 1 = mirror > 0 ? 1 : 0; + const leadLift = this.footWorld(leadIndex, lead.position); + const rearLift = this.footWorld(rearIndex, rear.position); + lead.position.sub(rootPosition).applyQuaternion(rootQuatInverse); + rear.position.sub(rootPosition).applyQuaternion(rootQuatInverse); + const ankleRest = this.boxer.rig.metrics.ankleHeight; + lead.position.y = ankleRest + leadLift; + rear.position.y = ankleRest + rearLift; + mirrorX(STANCE.leadToe, mirror, lead.toe); + mirrorX(STANCE.rearToe, mirror, rear.toe); + lead.heel = 0; + rear.heel = 0; + lead.pole.copy(lead.toe).setY(0.35).normalize(); + rear.pole.copy(rear.toe).setY(0.35).normalize(); + + // Torso baseline. + const torso = this.torso; + const blade = STANCE.bladeYaw * mirror; + const bounce = Math.sin(this.bouncePhase) * 0.012 * (1 - this.stunAmount) * (speed > 0.6 ? 0.6 : 1); + const sway = Math.sin(this.weightPhase) * 0.02; + let crouch = 0.012 + this.tired * 0.03 + this.stunAmount * 0.05; + torso.hips.set(sway * mirror + Math.sin(this.stunPhase * 0.9) * 0.05 * this.stunAmount, STANCE.hipsHeight - crouch + bounce, 0.0); + torso.hipsYaw = blade; + torso.hipsPitch = 0.02 + this.tired * 0.08; + torso.hipsRoll = Math.sin(this.stunPhase) * 0.09 * this.stunAmount; + torso.shouldersYaw = blade * 0.88; + torso.spinePitch = 0.16 + this.tired * 0.16 + Math.sin(time * (2.1 + this.tired * 1.8)) * 0.012; + torso.spineRoll = Math.sin(this.stunPhase * 1.3) * 0.06 * this.stunAmount; + torso.headYaw = -0.12 * mirror + Math.sin(time * 0.9) * 0.05 + Math.sin(this.stunPhase * 0.7) * 0.25 * this.stunAmount; + torso.headPitch = 0.12 + Math.sin(time * 1.7) * 0.02 + this.stunAmount * 0.18; + torso.headRoll = Math.sin(this.stunPhase * 1.1) * 0.14 * this.stunAmount; + torso.headOffset.set(0, 0, 0); + + // Hands: guard baseline with feints, fatigue, stun. + const leadHand = mirror > 0 ? this.hand.L : this.hand.R; + const rearHand = mirror > 0 ? this.hand.R : this.hand.L; + const headRest = this.headRestChar(mirror); + const guardBlend = clamp(this.guardHigh + this.guardLow, 0, 1); + const leadTarget = this.scratch.copy(STANCE.relaxedLead).lerp(STANCE.guardHighLead, this.guardHigh).lerp(STANCE.guardLowLead, this.guardLow); + const rearTarget = this.scratchB.copy(STANCE.relaxedRear).lerp(STANCE.guardHighRear, this.guardHigh).lerp(STANCE.guardLowRear, this.guardLow); + leadTarget.y -= this.tired * 0.12 + this.stunAmount * 0.22; + rearTarget.y -= this.tired * 0.1 + this.stunAmount * 0.2; + leadTarget.z += this.feint * 0.1 + Math.sin(time * 2.3) * 0.012 * motionScale; + leadTarget.x += Math.sin(time * 1.9) * 0.01 * motionScale; + rearTarget.y += Math.cos(time * 2.7) * 0.01 * motionScale; + leadTarget.z -= this.guardKick * 0.07; + rearTarget.z -= this.guardKick * 0.05; + leadTarget.y -= this.guardKick * 0.02; + leadTarget.add(headRest); + rearTarget.add(headRest); + leadHand.position.set(leadTarget.x * mirror, leadTarget.y, leadTarget.z); + rearHand.position.set(rearTarget.x * mirror, rearTarget.y, rearTarget.z); + mirrorX(STANCE.leadKnuckles, mirror, leadHand.knuckles); + mirrorX(STANCE.leadPalm, mirror, leadHand.palm); + mirrorX(STANCE.rearKnuckles, mirror, rearHand.knuckles); + mirrorX(STANCE.rearPalm, mirror, rearHand.palm); + mirrorX(STANCE.leadPole, mirror, leadHand.pole); + mirrorX(STANCE.rearPole, mirror, rearHand.pole); + let shrugLead = 0.15 * guardBlend; + let shrugRear = 0.25 * guardBlend; + + // Defensive body movement. + if (Math.abs(this.slip) > 0.001) { + const s = this.slip; + torso.headOffset.x += s * 0.13; + torso.spineRoll += -s * 0.28; + torso.hips.x += s * 0.03; + torso.hips.y -= Math.abs(s) * 0.05; + torso.spinePitch += Math.abs(s) * 0.12; + torso.headRoll += -s * 0.2; + } + if (this.weave > 0.001) { + const w = this.weave; + const phase = clamp(this.weaveTime / 0.42, 0, 1); + const arc = Math.sin(phase * Math.PI); + torso.hips.y -= w * 0.2; + torso.spinePitch += w * 0.42; + torso.headOffset.x += w * (1 - 2 * phase) * 0.16 * mirror; + torso.headOffset.y -= w * arc * 0.08; + torso.spineRoll += w * (1 - 2 * phase) * 0.18 * mirror; + leadHand.position.y -= w * 0.1; + rearHand.position.y -= w * 0.1; + } + if (this.pull > 0.001) { + const p = this.pull; + torso.spinePitch -= p * 0.34; + torso.hips.z -= p * 0.11; + torso.hips.x -= p * 0.05 * mirror; + torso.headOffset.z -= p * 0.06; + torso.headPitch -= p * 0.1; + } + + // Reactions. + torso.headOffset.add(this.headKick.value); + torso.headPitch += -this.headKick.value.z * 2.4 + this.headKick.value.y * 1.6; + torso.headYaw += this.headKick.value.x * 2.2; + torso.headRoll += -this.headKick.value.x * 0.9; + torso.spinePitch += this.torsoKick.value.x; + torso.spineRoll += this.torsoKick.value.z * 0.5; + torso.hips.x += this.rootKick.value.x; + torso.hips.z += this.rootKick.value.z; + torso.hips.y -= Math.max(0, this.torsoKick.value.x) * 0.08; + if (this.torsoKick.value.x > 0.05) { + leadHand.position.y -= this.torsoKick.value.x * 0.25; + rearHand.position.y -= this.torsoKick.value.x * 0.2; + leadHand.position.z -= this.torsoKick.value.x * 0.1; + } + // A body uppercut lifts the fighter onto his toes. + const lift = Math.max(0, this.rootKick.value.y); + torso.hips.y += lift; + lead.heel += lift * 6; + rear.heel += lift * 6; + const cover = this.coverKick.value.x; + if (Math.abs(cover) > 0.002) { + const near = cover > 0 ? this.hand.R : this.hand.L; + near.position.y -= Math.abs(cover) * 0.9; + near.position.x += cover * 0.2; + near.position.z -= Math.abs(cover) * 0.25; + near.pole.y -= Math.abs(cover) * 3; + } + + // Punch. + if (this.punchActive) { + shrugLead = 0; + shrugRear = 0; + const shrug = this.applyPunch(mirror, leadHand, rearHand, lead, rear, headRest); + if ((this.punchHand === "left") === (mirror > 0)) shrugLead = shrug; + else shrugRear = shrug; + } + + if (this.referee) this.applyRefereePose(mirror, leadHand, rearHand, lead, rear, headRest, time, sampledTick); + + // Special states. + if (this.clinchWeight > 0.001) this.applyClinchPose(this.clinchWeight, time, mirror, fighter, opponent, leadHand, rearHand, headRest); + if (this.foulWeight > 0.001) { + const f = this.foulWeight; + torso.hips.y -= f * 0.16; + torso.spinePitch += f * 0.55; + torso.headPitch += f * 0.2; + leadHand.position.lerp(this.scratch.set(0.06 * mirror, 0.72, 0.16), f); + rearHand.position.lerp(this.scratch.set(-0.05 * mirror, 0.7, 0.14), f); + leadHand.pole.set(0.6 * mirror, -0.6, 0.5); + rearHand.pole.set(-0.6 * mirror, -0.6, 0.5); + } + if (this.tauntWeight > 0.001) { + const tauntLeft = this.tauntEnd === null ? 0 : clamp(this.tauntEnd - sampledTick, 0, TAUNT_TICKS); + this.applyTauntPose(this.tauntWeight, ((TAUNT_TICKS - tauntLeft) / TAUNT_TICKS) * TAUNT_BECKONS, mirror, leadHand, rearHand, headRest); + } + + // Exhaustion and stun on guard. + if (this.dislocation === "shoulder_left" || this.dislocation === "shoulder_right") { + const hand = this.dislocation === "shoulder_left" ? this.hand.L : this.hand.R; + const side = this.dislocation === "shoulder_left" ? 1 : -1; + hand.position.set(0.24 * side, 0.55, 0.05); + hand.pole.set(0.9 * side, -0.3, 0.2); + hand.knuckles.set(0, -1, 0.1); + hand.palm.set(-side, 0, 0.2); + } + + // Knockdown overrides everything above. + if (this.touchWeight > 0.001 && this.downState === "up") this.applyTouchGlovesPose(this.touchWeight, mirror, leadHand, rearHand); + if (this.celebration > 0.001 && this.downState === "up") this.applyCelebratePose(this.celebration, time, mirror, leadHand, rearHand, lead, rear); + if (this.wave > 0.001 && this.downState === "up") this.applyWaveOffPose(this.wave, time, mirror, leadHand, rearHand); + if (this.breakWeight > 0.001 && this.downState === "up") this.applyBreakPose(this.breakWeight, mirror, leadHand, rearHand); + if (this.attendWeight > 0.001 && this.downState === "up") this.applyAttendPose(this.attendWeight, time, mirror, leadHand, rearHand); + if (this.treatWeight > 0.001 && this.downState === "up") this.applyTreatPose(this.treatWeight, time, mirror, leadHand, rearHand, lead, rear); + if (this.seated > 0.001 && this.downState === "up") this.applySeatedPose(this.seated, time, mirror, leadHand, rearHand, lead, rear); + if (this.downState !== "up") this.applyDownPose(mirror, leadHand, rearHand, lead, rear); + + crouch = 0; + void crouch; + const pose = this.pose as { shrugL: number; shrugR: number }; + pose.shrugL = mirror > 0 ? shrugLead : shrugRear; + pose.shrugR = mirror > 0 ? shrugRear : shrugLead; + this.solver.apply(boxer.root, this.pose); + this.applyDislocation(); + + const opponentBlood = Math.min( + 1, + (opponent.trauma.bleeding + opponent.trauma.left_cut + opponent.trauma.right_cut) / 620 + * (blood === "off" ? 0 : blood === "reduced" ? 0.3 : 1.5), + ); + boxer.gloveGear.color.copy(boxer.gearBaseColor).lerp(BLOODED_GLOVE_COLOR, opponentBlood); + applyHeadTrauma(boxer.headInjury, fighter.trauma, blood); + applyBodyTrauma(boxer.bodyInjury, fighter.trauma, blood); + boxer.setSkinClearcoat(0.25 + (1 - stamina) * 0.4); + } + + /** + * Showboat: the rear glove drops to the hip with the chest out and chin up + * while the lead glove beckons the opponent in, palm up, four times per taunt. + */ + private applyTauntPose(t: number, beat: number, mirror: number, leadHand: HandTarget, rearHand: HandTarget, headRest: THREE.Vector3): void { + const torso = this.torso; + const curl = 0.5 - 0.5 * Math.cos(beat * Math.PI * 2); + rearHand.position.lerp(this.scratch.set(-0.3 * mirror, headRest.y - 0.62, 0.02), t); + rearHand.pole.lerp(this.scratch.set(-0.5 * mirror, -0.4, -0.75), t).normalize(); + rearHand.knuckles.lerp(this.scratch.set(-0.1 * mirror, -0.95, 0.3), t).normalize(); + rearHand.palm.lerp(this.scratch.set(0, 0.3, 0.95), t).normalize(); + leadHand.position.lerp(this.scratch.set(0.26 * mirror, headRest.y - 0.36 + curl * 0.1, 0.52 - curl * 0.24), t); + leadHand.pole.lerp(this.scratch.set(0.7 * mirror, -0.7, 0.1), t).normalize(); + leadHand.knuckles.lerp(this.scratch.set(0.1 * mirror, 0.25 + curl * 0.6, 0.95 - curl * 0.7), t).normalize(); + leadHand.palm.lerp(this.scratch.set(-0.2 * mirror, 0.95, -0.2 - curl * 0.5), t).normalize(); + torso.spinePitch -= t * 0.12; + torso.headPitch -= t * 0.22; + torso.headYaw += Math.sin(beat * Math.PI) * 0.15 * t; + torso.shouldersYaw += Math.sin(beat * Math.PI * 3) * 0.1 * t; + torso.hips.x += Math.sin(beat * Math.PI) * 0.03 * t * mirror; + torso.headOffset.z += t * 0.03; + } + + /** + * Tie-up: the fighter whose id sorts first hooks over the opponent's arms, + * the other digs under them around the ribs. Both lean in over the bladed + * chest line and rest the head to their own right, so the skulls pass on + * opposite shoulders, and both keep working for position while they hold. + */ + private applyClinchPose(c: number, time: number, mirror: number, fighter: FighterSnapshot, opponent: FighterSnapshot, leadHand: HandTarget, rearHand: HandTarget, headRest: THREE.Vector3): void { + const torso = this.torso; + const over = fighter.player_id < opponent.player_id; + const struggle = Math.sin(time * 7.3) * 0.5 + Math.sin(time * 4.1 + 1.2) * 0.5; + const centre = this.clinchCentre + .set(this.mapping.x(opponent.x) - (this.rootX ?? 0), 0, this.mapping.z(opponent.y) - this.rootZ) + .applyQuaternion(this.scratchQ.setFromAxisAngle(worldUpVector, -this.yaw)); + if (centre.lengthSq() < 0.04) centre.set(0, 0, 0.5); + const forward = this.clinchForward.copy(centre).normalize(); + const acrossX = forward.z; + const acrossZ = -forward.x; + torso.spinePitch += c * (over ? 0.28 : 0.42) + struggle * 0.025 * c; + torso.hips.z += c * (over ? 0.04 : 0.06); + torso.hips.x += struggle * 0.02 * c; + torso.hips.y -= c * (over ? 0 : 0.03) + Math.abs(struggle) * 0.012 * c; + torso.hipsYaw += struggle * 0.06 * c; + torso.headPitch += c * (over ? 0.15 : 0.3); + torso.headYaw -= c * 0.3; + torso.headOffset.x -= c * 0.05; + torso.headOffset.y -= c * (over ? 0.02 : 0.06); + const metrics = this.boxer.rig.metrics; + const reach = Math.min(metrics.armL.upper + metrics.armL.lower, metrics.armR.upper + metrics.armR.lower) * 0.92; + for (const [hand, side] of [[leadHand, mirror], [rearHand, -mirror]] as const) { + const wrap = over ? 0.2 : 0.17; + const depth = over ? 0.05 : 0.1; + const shoulderX = 0.19 * side; + const shoulderZ = torso.hips.z + 0.04 + torso.spinePitch * 0.25; + const target = this.clinchTemp.set( + centre.x + acrossX * wrap * side + forward.x * depth - shoulderX, + headRest.y - (over ? 0.24 : 0.5) - (side === mirror ? 0 : 0.05), + centre.z + acrossZ * wrap * side + forward.z * depth - shoulderZ, + ); + const rise = target.y - (headRest.y - 0.22); + const horizontal = Math.hypot(target.x, target.z); + const limit = Math.sqrt(Math.max(0.01, reach * reach - rise * rise)); + if (horizontal > limit) { + target.x *= limit / horizontal; + target.z *= limit / horizontal; + } + target.x += shoulderX; + target.z += shoulderZ; + hand.position.lerp(target, c); + hand.pole.lerp(this.clinchTemp.set(side * 0.85, over ? 0.35 : -0.6, 0.25), c).normalize(); + hand.knuckles.lerp(this.clinchTemp.set(-acrossX * side * 0.9 + forward.x * 0.3, over ? -0.25 : 0.1, -acrossZ * side * 0.9 + forward.z * 0.3), c).normalize(); + hand.palm.lerp(this.clinchTemp.set(-forward.x, over ? 0.1 : 0.35, -forward.z), c).normalize(); + } + } + + /** Character-space head rest position for hand offsets (before torso deltas). */ + private headRestChar(mirror: number): THREE.Vector3 { + const metrics = this.boxer.rig.metrics; + void mirror; + return this.headWorld.set(-0.08, metrics.headHeight - metrics.hipsHeight + this.torso.hips.y, 0.02); + } + + private syncAction(fighter: FighterSnapshot, opponent: FighterSnapshot, sampledTick: number, simDt: number): void { + this.shownFighter = fighter; + this.shownOpponent = opponent; + const queued = this.ownQueued; + if (queued !== null && fighter.action_id === queued.action.id) { + // The server let the held press go sooner than expected: it plays on the server's timeline. + this.ownQueued = null; + this.retirePunch(); + this.startOwnPunch(queued, 0); + } + if ( + fighter.action_id !== null + && fighter.action_id !== this.actionId + && fighter.action_id !== this.completedActionId + && !this.retiredOwnIds.includes(fighter.action_id) + ) { const punchClass = fighter.action; - const hand = fighter.action_hand ?? (fighter.stance === "orthodox" ? "left" : "right"); if (punchClass !== null) { + const hand = fighter.action_hand ?? (fighter.stance === "orthodox" ? "left" : "right"); + const own = this.ownActionId === fighter.action_id && this.punchActive; + const predictedTiming = this.punchTiming; this.actionId = fighter.action_id; this.punchClass = punchClass; this.punchHand = hand; @@ -598,320 +1392,1158 @@ export class BoxingGraph { active: fighter.action_active_ticks, recovery: fighter.action_recovery_ticks, }; - const total = Math.max(1, fighter.action_startup_ticks + fighter.action_active_ticks + fighter.action_recovery_ticks); - this.beginPunch(boxer.actions.get(PUNCH_CLIP(punchClass, hand))!, total); - this.punchAgeTicks = Math.max(0, sampledTick - fighter.action_start_tick); - if (this.predictedId === fighter.action_id) { - const predictedAge = this.predictionAgeTicks; - const authoritativeAge = sampledTick - fighter.action_start_tick; - if (Math.abs(predictedAge - authoritativeAge) > 1) this.punchAgeTicks = authoritativeAge; - this.predictedId = null; + this.punchTotalTicks = Math.max(1, fighter.action_startup_ticks + fighter.action_active_ticks + fighter.action_recovery_ticks); + const authoritativeAge = Math.max(0, sampledTick - fighter.action_start_tick); + if (own) { + // The server's timing can differ from the predicted one (fatigue); keep the glove where it is. + this.punchAgeTicks = remapPunchAge(this.punchAgeTicks, predictedTiming, this.punchTiming); + this.ownAuthoritativeAge = authoritativeAge; + // A punch the server cut off keeps coming back; one that was only late resumes. + if (!this.ownRefused) { + this.ownPulled = false; + if (authoritativeAge - this.punchAgeTicks > 1) this.punchAgeTicks = authoritativeAge; + } } else { - this.punchAgeTicks = Math.max(0, sampledTick - fighter.action_start_tick); + this.punchAgeTicks = authoritativeAge; + this.ownActionId = null; + this.ownLeadTicks = 0; + this.ownAuthoritativeAge = null; } + this.ownWaitedTicks = 0; + this.punchActive = true; } } if (fighter.action_id === null) { this.actionId = null; this.completedActionId = null; + } else if (fighter.action_id === this.actionId && this.punchActive) { + // Same instance: re-lock the phase if the render clock drifted more than a tick. The viewer's + // own punch started ahead of the server, so it only ever catches up, never goes back. + const authoritativeAge = Math.max(0, sampledTick - fighter.action_start_tick); + if (this.ownActionId === this.actionId) { + this.ownAuthoritativeAge = authoritativeAge; + if (!this.ownPulled && authoritativeAge - this.punchAgeTicks > 1.5) this.punchAgeTicks = authoritativeAge; + } else if (Math.abs(this.punchAgeTicks - authoritativeAge) > 1.5) { + this.punchAgeTicks = authoritativeAge; + } } - - if (this.predictedId !== null) { - this.predictionAgeTicks += dt * 30 * this.hitstopScale; - if (this.predictionAgeTicks > 10) { - this.predictedId = null; + if (this.punchActive && this.ownActionId !== null && this.ownAuthoritativeAge === null && !this.ownPulled) { + // No word from the server well past when it was due: it turned the punch down. Before + // contact the glove comes back; after it the punch simply finishes. + this.ownWaitedTicks += simDt * 30; + if (this.ownWaitedTicks > this.ownExpectedTicks * 1.5 + OWN_PUNCH_GRACE_TICKS && this.punchAgeTicks < this.punchTiming.startup) this.ownPulled = true; + } + let ended = false; + if (this.punchActive && this.ownPulled) { + this.punchAgeTicks -= simDt * 30 * OWN_PUNCH_PULL_RATE; + if (this.punchAgeTicks <= 0) { + // Only a punch the server refused is retired. One that was merely late is not: if the server + // does start it after all, it plays on the server's timeline. + if (!this.ownRefused) this.ownActionId = null; + this.retirePunch(); } + } else if (this.punchActive) { + this.punchAgeTicks += simDt * 30 * this.ownPunchRate(); + if (this.punchAgeTicks >= this.punchTotalTicks) { + this.retirePunch(); + ended = true; + } + } + if (fighter.is_downed) { + if (this.punchActive) this.retirePunch(); + this.ownQueued = null; + } + this.releaseQueuedPress(simDt, ended); + // A punch the server says met the opponent, hit or block, follows his head wherever it went. + const aimed = this.actionId ?? this.ownActionId; + if (aimed !== this.aimActionId) { + this.aimActionId = aimed; + this.followHead = 0; } + this.followHead = smooth(this.followHead, aimed !== null && aimed === this.contactId ? 1 : 0, FOLLOW_HEAD_RATE, simDt); + } - if (this.activePunch !== null) { - this.punchAgeTicks += dt * 30 * this.hitstopScale; - const total = this.punchTotalTicks; - this.setPunch(this.activePunch, this.punchAgeTicks); - if (this.punchAgeTicks >= total) { - this.completedActionId = this.actionId; - this.actionId = null; - this.activePunch.stop(); - this.activePunch = null; - } + /** Takes the opponent's head as drawn and keeps where it would be without his slip, weave or pull. */ + private trackOpponentHead(opponent: FighterSnapshot, head: THREE.Vector3, dt: number): void { + const root = this.guardOpponentHead.set(this.mapping.x(opponent.x), 0, this.mapping.z(opponent.y)); + this.opponentSteadySeconds = EVASION_POSES.has(opponent.defense) ? 0 : this.opponentSteadySeconds + dt; + if (!this.hasLiveHead || this.opponentSteadySeconds >= HEAD_SETTLE_SECONDS) this.opponentHeadOffset.copy(head).sub(root); + root.add(this.opponentHeadOffset); + this.liveOpponentHead.copy(head); + this.hasLiveHead = true; + } + + /** + * Playback rate of the viewer's own punch. Until the server's version is on screen the startup is + * stretched by the estimated lead; once it is, the rate aims the glove at the server's contact + * tick, and any lead left after contact is worked off in a slower recovery. + */ + private ownPunchRate(): number { + if (this.ownActionId === null) return 1; + const startup = this.punchTiming.startup; + const authoritative = this.ownAuthoritativeAge; + if (authoritative === null) return this.punchAgeTicks < startup ? startup / (startup + this.ownLeadTicks) : 1; + if (this.punchAgeTicks - authoritative <= 0.25) return 1; + if (this.punchAgeTicks < startup && authoritative < startup) return clamp((startup - this.punchAgeTicks) / (startup - authoritative), 0.25, 1); + return 0.5; + } + + /** Punch mechanics. Returns the punching shoulder's shrug. */ + private applyPunch( + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + lead: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + rear: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + headRest: THREE.Vector3, + ): number { + const torso = this.torso; + const timing = this.punchTiming; + const age = this.punchAgeTicks; + const startup = Math.max(1, timing.startup); + const active = Math.max(0.5, timing.active); + const recovery = Math.max(1, timing.recovery); + const isLead = (this.punchHand === "left") === (mirror > 0); + const hand = isLead ? leadHand : rearHand; + const other = isLead ? rearHand : leadHand; + const side = isLead ? 1 : -1; + const power = this.punchPower === "power" ? 1 : 0; + const body = this.punchTarget === "body" ? 1 : 0; + + let extend: number; + let windup: number; + let phase: "startup" | "active" | "recovery"; + // Every punch leaves the guard and eases into its windup instead of jumping on its first frame: + // the hand over the windup, its turn and the elbow over twice that. + let windupIn = 1; + let onset = 1; + if (age < startup) { + phase = "startup"; + const u = age / startup; + const windupEnd = this.punchClass === "hook" ? 0.3 : this.punchClass === "uppercut" ? 0.45 : 0.18; + windup = smoothstep(0, windupEnd, u) * (1 - smoothstep(windupEnd, Math.min(1, windupEnd + 0.4), u)); + extend = u <= windupEnd ? 0 : easeIn((u - windupEnd) / (1 - windupEnd), 1.65); + windupIn = smoothstep(0, windupEnd, u); + onset = smoothstep(0, Math.min(1, windupEnd * 2), u); + } else if (age < startup + active) { + phase = "active"; + windup = 0; + extend = 1 + 0.06 * Math.sin(((age - startup) / active) * Math.PI); + } else { + phase = "recovery"; + windup = 0; + extend = 1 - easeOut((age - startup - active) / recovery, 1.9); } - if (this.reactionAction !== null && !this.reactionAction.isRunning()) { - this.reactionAction.stop(); - this.reactionAction = null; - } - - const worldVelocityX = this.mapping.x(fighter.velocity_x) * 30; - const worldVelocityZ = this.mapping.z(fighter.velocity_y) * 30; - const worldSpeed = Math.hypot(worldVelocityX, worldVelocityZ); - const moving = worldSpeed > 0.05; - const moveWeight = THREE.MathUtils.clamp(worldSpeed / 1.1, 0, 1); - const forward = worldVelocityX * fighter.facing; - const lateral = Math.sign(fighter.velocity_y) * Math.abs(worldVelocityZ); - const directionTotal = Math.abs(forward) + Math.abs(lateral); - const targets = { - idle: 1 - moveWeight, - move_forward: directionTotal > 0 ? Math.max(0, forward) / directionTotal * moveWeight : 0, - move_backward: directionTotal > 0 ? Math.max(0, -forward) / directionTotal * moveWeight : 0, - move_lateral_left: directionTotal > 0 ? Math.max(0, -lateral) / directionTotal * moveWeight : 0, - move_lateral_right: directionTotal > 0 ? Math.max(0, lateral) / directionTotal * moveWeight : 0, - }; - const gaitCadence = THREE.MathUtils.clamp(0.35 + worldSpeed / 1.1 * 0.65, 0.35, 1.5); - const gaitTimeScale = fatigueScale * gaitCadence; - for (const name of LOCOMOTION) { - this.locomotionWeights[name] = smooth(this.locomotionWeights[name] ?? 0, targets[name], 10, dt); - const action = boxer.actions.get(name)!; - action.setEffectiveWeight(this.locomotionWeights[name]!); - const playbackRate = name === "idle" ? fatigueScale : gaitTimeScale; - action.setEffectiveTimeScale(reducedMotion ? Math.min(0.4, playbackRate) : playbackRate); - } - - const defending = fighter.defense !== "none"; - if (defending) this.defenseClip = fighter.defense; - this.defenseWeight = smooth(this.defenseWeight, defending ? 1 : 0, 12, dt); - const defenseAction = boxer.actions.get(this.defenseClip)!; - if (this.defenseWeight > 0.001 && !defenseAction.isRunning()) defenseAction.reset().play(); - - const stateClip: ClipName | null = fighter.is_foul_recovery_target - ? "foul_recovery" - : fighter.clinch_ticks > 0 || fighter.clinch_startup_ticks > 0 - ? "clinch" - : fighter.stunned_ticks > 0 - ? "stunned" - : fighter.taunt_ticks > 0 - ? "taunt" - : fighter.stamina / Math.max(1, fighter.maximum_stamina) < 0.16 && !moving && !defending - ? "exhausted" - : null; - const nextStateAction = stateClip === null ? null : boxer.actions.get(stateClip)!; - if (nextStateAction !== null && nextStateAction !== this.stateAction) { - this.stateAction?.stop(); - this.stateAction = nextStateAction; - this.stateWeight = 0; - this.stateAction.reset().play(); - } - this.stateRequested = nextStateAction !== null; - this.stateWeight = smooth(this.stateWeight, this.stateRequested ? 1 : 0, 14, dt); - if (!this.stateRequested && this.stateWeight < 0.001) { - this.stateAction?.stop(); - this.stateAction = null; - this.stateWeight = 0; - } - - const dropTarget = opponent.is_downed ? -(this.boxer.metrics.headRestY * 0.88) : opponent.defense === "weave" ? -0.24 : -0.03; - this.opponentDrop = smooth(this.opponentDrop, dropTarget, 4, dt); - if (opponentHeadWorld !== undefined) { - this.liveOpponentHead.copy(opponentHeadWorld); - this.hasLiveHead = true; + const e = clamp(extend, 0, 1.1); + // The swing follows its arc out to contact; on the way back the glove retracts straight to the + // guard instead of retracing the arc (a hook must not swing back out wide). + const travel = phase === "recovery" ? 1 : e; + const retract = phase === "recovery" ? 1 - e : 0; + + const guard = this.punchGuard.position.copy(hand.position); + const guardKnuckles = this.punchGuard.knuckles.copy(hand.knuckles); + const guardPalm = this.punchGuard.palm.copy(hand.palm); + const guardPole = this.punchGuard.pole.copy(hand.pole); + + // Torso rotation: lead punches blade further, rear punches square up. + const blade = STANCE.bladeYaw * mirror; + let yawTravel: number; + let hipsTravel: number; + let hipsForward = 0; + let heelRear = 0; + let heelLead = 0; + let leadPivot = 0; + let dip = 0; + switch (this.punchClass) { + case "jab": + yawTravel = -0.2 * side; + hipsTravel = -0.06 * side; + hipsForward = 0.03; + heelRear = 0.18; + break; + case "straight": + yawTravel = isLead ? -0.3 : 1.15 + 0.15 * power; + hipsTravel = isLead ? -0.1 : 1.05 + 0.1 * power; + hipsForward = 0.08; + heelRear = isLead ? 0.2 : 0.62; + break; + case "hook": + yawTravel = isLead ? -0.95 - 0.2 * power : 1.35 + 0.2 * power; + hipsTravel = isLead ? -0.8 : 1.15; + heelRear = isLead ? 0.1 : 0.55; + heelLead = isLead ? 0.45 : 0; + leadPivot = isLead ? 0.5 : 0; + hipsForward = 0.02; + break; + default: + yawTravel = isLead ? -0.55 : 0.95; + hipsTravel = isLead ? -0.45 : 0.85; + heelRear = isLead ? 0.15 : 0.5; + dip = 0.12 + 0.05 * power; + break; + } + const rotation = this.punchClass === "hook" ? smoothstep(0.15, 1, e) : e; + torso.shouldersYaw = blade * 0.88 + yawTravel * mirror * rotation; + torso.hipsYaw = blade + hipsTravel * mirror * rotation; + torso.hips.z += hipsForward * e; + torso.hips.x += (isLead ? 0.02 : 0.05) * mirror * e; + torso.hips.y -= body * 0.1 * e + dip * windup + dip * 0.3 * e; + torso.spinePitch += 0.06 * e + body * 0.25 * e + dip * 1.4 * windup; + torso.headPitch += 0.05 * e + body * 0.12 * e; + torso.headOffset.z += 0.02 * e; + torso.headYaw += -yawTravel * mirror * rotation * 0.35; + + // Target in character space, measured from the rotated shoulder. + const target = this.scratch; + const rootPosition = this.scratchB.set(this.rootX ?? 0, 0, this.rootZ); + if (this.hasLiveHead) { + // An evading head is aimed at where it was, so a slip or weave that worked shows the glove go by. + target.copy(this.guardOpponentHead).lerp(this.liveOpponentHead, this.followHead).sub(rootPosition).applyQuaternion(this.scratchQ.setFromAxisAngle(worldUpVector, -this.yaw)); + if (body === 1) target.y -= 0.42; + else target.y -= 0.04; + } else { + target.set(0, body === 1 ? 1.15 : 1.5, 0.9); + } + const shoulderSpan = 0.19 * side * mirror; + const shoulderChar = this.scratchD.set( + torso.hips.x + shoulderSpan * Math.cos(torso.shouldersYaw), + headRest.y - 0.22, + torso.hips.z + 0.04 + torso.spinePitch * 0.25 - shoulderSpan * Math.sin(torso.shouldersYaw), + ); + const dir = this.punchDir.copy(target).sub(shoulderChar); + const distance = dir.length(); + dir.normalize(); + const reach = 0.5 + 0.04 * power + (this.punchClass === "straight" ? 0.06 : 0) + (this.punchClass === "jab" ? 0.03 : 0) + - (this.punchClass === "hook" ? 0.08 : 0) - (this.punchClass === "uppercut" ? 0.08 : 0); + const contactDistance = Math.min(distance - HURTBOXES.head.radius - GLOVE_HITBOX_RADIUS + PUNCH_CONTACT_OFFSET, reach); + // Pressed together there is little room: the punch shortens and the elbow stays bent rather than + // the glove going past the contact point into the face. + const contact = this.punchContact.copy(shoulderChar).addScaledVector(dir, Math.max(0, contactDistance)); + rear.heel = heelRear * e; + lead.heel = heelLead * e; + if (leadPivot > 0) { + const pivot = this.scratchQ.setFromAxisAngle(worldUpVector, -leadPivot * mirror * e); + lead.toe.applyQuaternion(pivot); + lead.pole.applyQuaternion(pivot); + } + if (heelRear > 0.3) { + const pivot = this.scratchQ.setFromAxisAngle(worldUpVector, 0.45 * mirror * e); + rear.toe.applyQuaternion(pivot); + rear.pole.applyQuaternion(pivot); + } + + // Hand path. + const windupOffset = this.scratchE; + switch (this.punchClass) { + case "hook": + windupOffset.set(0.22 * side * mirror, -0.06, -0.12); + break; + case "uppercut": + windupOffset.set(0.05 * side * mirror, -0.42, -0.02); + break; + case "straight": + windupOffset.set(0.02 * side * mirror, -0.03, -0.09 - 0.05 * power); + break; + default: + windupOffset.set(0, -0.01, -0.05 - 0.04 * power); + break; + } + // A hook or uppercut keeps part of its windup until it travels, once the windup has eased in. + const start = this.punchStart.copy(guard).addScaledVector(windupOffset, Math.max(windup, this.punchClass === "hook" || this.punchClass === "uppercut" ? (1 - travel) * 0.6 * windupIn : 0)); + if (this.punchClass === "hook") { + // Horizontal sweep around the shoulder from the wide windup into the target. The radius runs + // from the windup's to the contact's, measured flat, so the sweep ends on the contact point. + const startRadius = Math.hypot(start.x - shoulderChar.x, start.z - shoulderChar.z); + const contactRadius = Math.hypot(contact.x - shoulderChar.x, contact.z - shoulderChar.z); + const startDir = this.punchSweepFrom.copy(start).sub(shoulderChar).setY(0).normalize(); + const endDir = this.punchSweepTo.copy(contact).sub(shoulderChar).setY(0).normalize(); + const angle = Math.acos(clamp(startDir.dot(endDir), -1, 1)); + // The sign of the cross product's vertical component: which way round the shoulder the sweep turns. + const turn = startDir.z * endDir.x - startDir.x * endDir.z >= 0 ? 1 : -1; + const sweep = smoothstep(0, 1, travel); + // The start direction is not needed again, so it turns in place. + const rotated = startDir.applyAxisAngle(worldUpVector, angle * sweep * turn).normalize(); + hand.position.copy(shoulderChar).addScaledVector(rotated, THREE.MathUtils.lerp(startRadius, contactRadius, sweep)); + hand.position.y = THREE.MathUtils.lerp(start.y, contact.y, sweep); + hand.pole.set(0.95 * side * mirror, 0.08, 0.3).normalize(); + hand.knuckles.copy(rotated).applyAxisAngle(worldUpVector, turn * Math.PI / 2).setY(0.05).normalize(); + hand.palm.set(0, -1, 0); + } else if (this.punchClass === "uppercut") { + const rise = smoothstep(0, 1, travel); + const low = start; + const mid = this.punchMid.copy(contact).lerp(low, 0.5); + mid.y = Math.min(low.y, contact.y) - 0.04; + mid.z += 0.08; + hand.position.copy(low).lerp(mid, rise * 2 > 1 ? 1 : rise * 2); + if (rise > 0.5) hand.position.copy(mid).lerp(contact, (rise - 0.5) * 2); + hand.pole.set(0.3 * side * mirror, -0.2, 1); + hand.knuckles.set(0.05 * side * mirror, 0.9, 0.35).normalize(); + hand.palm.set(-0.2 * side * mirror, 0.3, -0.95).normalize(); + } else { + hand.position.copy(start).lerp(contact, Math.min(1, travel)); + hand.position.y += Math.sin(clamp(travel, 0, 1) * Math.PI) * 0.025; + hand.pole.set(0.55 * side * mirror, -0.9, 0.35); + const pronate = smoothstep(0.55, 1, travel); + hand.knuckles.copy(dir).lerp(this.scratchC.set(0.1 * side * mirror, 0.55, 0.8), 1 - pronate).normalize(); + hand.palm.set(-0.9 * side * mirror, 0.2, -0.3).lerp(this.scratchC.set(0, -1, 0.1), pronate).normalize(); + } + + if (retract > 0) { + hand.position.lerp(guard, retract); + hand.knuckles.lerp(guardKnuckles, retract).normalize(); + hand.palm.lerp(guardPalm, retract).normalize(); + hand.pole.lerp(guardPole, retract).normalize(); + } + if (onset < 1) { + // The hand turns and the elbow lifts out of the guard over the windup too. The further the elbow + // has to turn, the more it swings out on the way, so its pull never lines up with the arm, which + // would flip it in a frame. + const turn = (1 - hand.pole.dot(guardPole) / Math.max(1e-6, hand.pole.length() * guardPole.length())) / 2; + hand.knuckles.lerp(guardKnuckles, 1 - onset).normalize(); + hand.palm.lerp(guardPalm, 1 - onset).normalize(); + hand.pole.lerp(guardPole, 1 - onset).addScaledVector(this.scratchC.set(side * mirror, 0, 0), ONSET_ELBOW_FLARE * turn * Math.sin(Math.PI * onset)).normalize(); + } + + // Non-punching hand protects the chin. + const chin = this.scratchE.set(-0.1 * side * mirror, headRest.y - 0.04, 0.12 + headRest.z); + other.position.lerp(chin, e * 0.7); + return e; + } + + /** Square, hands-low official's posture with a raised counting arm during knockdowns. */ + private applyRefereePose( + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + lead: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + rear: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + headRest: THREE.Vector3, + time: number, + sampledTick: number, + ): void { + const torso = this.torso; + torso.hipsYaw = 0; + torso.shouldersYaw = 0; + torso.hipsPitch = 0; + torso.spinePitch = 0.06; + torso.headYaw = Math.sin(time * 0.7) * 0.08; + torso.headPitch = 0.08; + torso.hips.y = STANCE.hipsHeight + 0.03; + torso.hips.x = 0; + torso.hips.z = 0; + lead.toe.set(0.12 * mirror, 0, 1).normalize(); + rear.toe.set(-0.12 * mirror, 0, 1).normalize(); + lead.pole.copy(lead.toe).setY(0.3).normalize(); + rear.pole.copy(rear.toe).setY(0.3).normalize(); + const sway = Math.sin(time * 1.3) * 0.01; + leadHand.position.set(0.27 * mirror, 0.86 + sway, 0.12); + rearHand.position.set(-0.27 * mirror, 0.86 - sway, 0.12); + leadHand.pole.set(0.5 * mirror, -0.4, -0.8).normalize(); + rearHand.pole.set(-0.5 * mirror, -0.4, -0.8).normalize(); + leadHand.knuckles.set(0.15 * mirror, -0.9, 0.35).normalize(); + rearHand.knuckles.set(-0.15 * mirror, -0.9, 0.35).normalize(); + leadHand.palm.set(-0.9 * mirror, 0.1, 0.35).normalize(); + rearHand.palm.set(0.9 * mirror, 0.1, 0.35).normalize(); + if (this.refereeCounting) { + // The arm comes up through each second of the count and chops down onto the next number. + this.countChangedTick ??= sampledTick; + const beat = clamp((sampledTick - this.countChangedTick) / COUNT_TICKS, 0, 1); + const pump = beat < COUNT_DROP_START ? easeOut(beat / COUNT_DROP_START) : 1 - easeIn((beat - COUNT_DROP_START) / (1 - COUNT_DROP_START), 2); + rearHand.position.set(-0.22 * mirror, headRest.y - 0.05 + pump * 0.12, 0.34 + pump * 0.08); + rearHand.pole.set(-0.9 * mirror, -0.3, 0.2).normalize(); + rearHand.knuckles.set(0, 0.7, 0.7).normalize(); + rearHand.palm.set(0, 0.3, -0.95).normalize(); + torso.spinePitch += 0.12; + torso.headPitch += 0.18; + leadHand.position.set(0.24 * mirror, 0.95, 0.08); } + } + private updateDownState(fighter: FighterSnapshot, dt: number, speed: number): void { if (fighter.is_downed) { - if (this.activePunch !== null) { - this.activePunch.stop(); - this.activePunch = null; - } - this.actionId = null; - this.predictedId = null; - if (this.downState === "up") { + if (this.downState === "up" || this.downState === "rising") { + // Knocked down again while getting up, he falls from where the get-up had him, not from standing. + this.fallFromGetUp = this.downState === "rising"; + if (this.fallFromGetUp) { + copyDownPose(this.fallStart, this.downResult); + this.fallStartStand = this.downStand; + } this.downState = "falling"; this.fallAge = 0; - const knockdown = boxer.actions.get("knockdown")!; - knockdown.reset().setLoop(THREE.LoopOnce, 1); - knockdown.setEffectiveWeight(0).play(); + this.riseProgress = 0; + this.landSettled = false; } else if (this.downState === "falling") { this.fallAge += dt; - } - } else if (this.downState !== "up") { - if (this.downState === "down" || this.downState === "falling") { - this.downState = "rising"; - this.riseAge = 0; - const getup = boxer.actions.get("getup")!; - getup.reset().setLoop(THREE.LoopOnce, 1); - getup.setEffectiveWeight(0).play(); + if (this.fallAge >= KNOCKDOWN_FALL_SECONDS) this.downState = "down"; } else { - this.riseAge += dt; - if (this.riseAge > this.boxer.actions.get("getup")!.getClip().duration) { - this.downState = "up"; - this.boxer.actions.get("knockdown")!.stop(); - this.boxer.actions.get("getup")!.stop(); - } + // Each good press of the get-up prompt pushes him further up; a bad one lets him sink back. + const meter = fighter.get_up_required > 0 ? clamp(fighter.get_up_meter / fighter.get_up_required, 0, 1) : 0; + const target = meter * RISE_KNEE; + this.riseProgress += clamp(target - this.riseProgress, -RISE_SINK_RATE * dt, RISE_PUSH_RATE * dt); } + return; + } + if (this.downState === "down" || this.downState === "falling") { + this.downState = "rising"; + this.riseFrom = this.riseProgress; + this.feetInitialized = false; } - if (this.downState === "falling" && this.fallAge > 1.3) this.downState = "down"; + if (this.downState !== "rising") return; + // The server already has him fighting: finish inside the stun, sooner if he walks or throws. + const hurried = speed > 0.3 || this.punchActive; + const rate = (1 - this.riseFrom) / (hurried ? GETUP_HURRIED_SECONDS : GETUP_SECONDS); + this.riseProgress = Math.min(1, this.riseProgress + (this.riseProgress < RISE_FOURS ? Math.min(rate, RISE_ROLL_RATE) : rate) * dt); + if (this.riseProgress >= 1) this.downState = "up"; + } - this.applyActionWeights(); - boxer.mixer.update(dt * this.hitstopScale); + private applyTouchGlovesPose( + blend: number, + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const lerp = THREE.MathUtils.lerp; + torso.hips.z = lerp(torso.hips.z, 0.06, blend); + torso.hipsYaw = lerp(torso.hipsYaw, torso.hipsYaw * 0.4, blend); + torso.shouldersYaw = lerp(torso.shouldersYaw, 0, blend); + torso.spinePitch = lerp(torso.spinePitch, 0.12, blend); + torso.headPitch = lerp(torso.headPitch, 0.1, blend); + leadHand.position.lerp(seatedScratch.set(0.11 * mirror, 1.24, 0.5), blend); + rearHand.position.lerp(seatedScratch.set(-0.11 * mirror, 1.22, 0.47), blend); + leadHand.palm.lerp(seatedScratch.set(-mirror, 0, 0), blend).normalize(); + rearHand.palm.lerp(seatedScratch.set(mirror, 0, 0), blend).normalize(); + leadHand.knuckles.lerp(seatedScratch.set(0, 0.15, 1), blend).normalize(); + rearHand.knuckles.lerp(seatedScratch.set(0, 0.15, 1), blend).normalize(); + leadHand.pole.lerp(seatedScratch.set(0.7 * mirror, -0.7, 0), blend).normalize(); + rearHand.pole.lerp(seatedScratch.set(-0.7 * mirror, -0.7, 0), blend).normalize(); + } - this.applyAimCorrection(fighter, opponent); - this.lockFeet(fighter, moving); - this.applyDislocation(); + /** + * Through the opening countdown the engine holds both fighters 2.2 m apart, so for the glove touch + * the rendered fighter walks in until the gloves meet and is back on his mark before the bell. + * Returns the offset from the engine position, and keeps the walk's velocity for the footwork. + */ + private touchWalk(fighter: FighterSnapshot, opponent: FighterSnapshot, dt: number, sampledTick: number): THREE.Vector3 { + this.countdownEnd = latchEndTick(this.countdownEnd, sampledTick, this.countdownTicks); + const walk = this.countdownEnd === null ? 0 : touchWalkProgress(this.countdownEnd - sampledTick); + const towardX = this.mapping.x(opponent.x) - this.mapping.x(fighter.x); + const towardZ = this.mapping.z(opponent.y) - this.mapping.z(fighter.y); + const gap = Math.hypot(towardX, towardZ); + const share = gap > TOUCH_GLOVES_GAP ? ((gap - TOUCH_GLOVES_GAP) / 2 / gap) * walk : 0; + // Capped at a walk, so a jump (a client that joins mid-countdown) is not taken as one huge stride. + this.touchVelocity.set(towardX * share - this.touchOffset.x, 0, towardZ * share - this.touchOffset.z).divideScalar(Math.max(dt, 1e-3)).clampLength(0, TOUCH_WALK_TOP_SPEED); + return this.touchOffset.set(towardX * share, 0, towardZ * share); + } - const opponentBlood = Math.min( - 1, - (opponent.trauma.bleeding + opponent.trauma.left_cut + opponent.trauma.right_cut) / 620 - * (blood === "off" ? 0 : blood === "reduced" ? 0.3 : 1.5), - ); - boxer.gloveGear.color.copy(boxer.gearBaseColor).lerp(BLOODED_GLOVE_COLOR, opponentBlood); - applyTraumaToOverlays(boxer.trauma, fighter, opponentBlood, blood); - boxer.setSkinClearcoat(0.25 + (1 - fighter.stamina / Math.max(1, fighter.maximum_stamina)) * 0.4); - void time; - } - - private applyActionWeights(): void { - const downAction = this.downState === "falling" || this.downState === "down" - ? this.boxer.actions.get("knockdown")! - : this.downState === "rising" - ? this.boxer.actions.get("getup")! - : null; - const hardOverride = downAction ?? this.reactionAction ?? this.activePunch; - const stateWeight = hardOverride === null && this.stateAction !== null ? this.stateWeight : 0; - const baseWeight = hardOverride === null ? 1 - stateWeight : 0; - const defenseWeight = this.defenseWeight * baseWeight; - const locomotionWeight = (1 - this.defenseWeight) * baseWeight; - const locomotionTotal = LOCOMOTION.reduce( - (total, name) => total + Math.max(0, this.locomotionWeights[name] ?? 0), - 0, - ); - for (const name of LOCOMOTION) { - const normalized = locomotionTotal > 0 - ? Math.max(0, this.locomotionWeights[name] ?? 0) / locomotionTotal - : name === "idle" ? 1 : 0; - this.boxer.actions.get(name)!.setEffectiveWeight(normalized * locomotionWeight); - } - for (const name of ["guard_high", "guard_low", "slip_left", "slip_right", "weave", "pull"] as const) { - this.boxer.actions.get(name)!.setEffectiveWeight(name === this.defenseClip ? defenseWeight : 0); - } - for (const name of ONE_SHOTS) { - const action = this.boxer.actions.get(name)!; - const weight = action === hardOverride - ? 1 - : hardOverride === null && action === this.stateAction - ? stateWeight - : 0; - action.setEffectiveWeight(weight); - } - } - - private applyAimCorrection(fighter: FighterSnapshot, opponent: FighterSnapshot): void { - if (this.activePunch === null || fighter.is_downed) return; - const startupFrac = this.punchTiming.startup / Math.max(1, totalTicks(this.punchTiming)); - const punchT = this.punchAgeTicks / this.punchTotalTicks; - if (punchT < startupFrac * 0.45 || punchT > startupFrac + 0.2) return; - const metrics = this.boxer.metrics; - const hurtbox = this.punchTarget === "body" ? HURTBOXES.torso : HURTBOXES.head; - const opponentTarget = this.scratchA.set( - this.mapping.x(opponent.x), - (this.punchTarget === "body" ? metrics.chestRestY : metrics.headRestY) + hurtbox.offset_y + this.opponentDrop, - this.mapping.z(opponent.y), - ); - if (this.punchTarget === "head" && this.hasLiveHead) { - opponentTarget.copy(this.liveOpponentHead).addScaledVector(this.boxer.root.up, hurtbox.offset_y); - } - const gloveName = this.punchHand === "left" ? "gloveL" : "gloveR"; - const gloveBone = this.boxer.bone(gloveName); - const elbowBone = this.boxer.bone(gloveName === "gloveL" ? "elbowL" : "elbowR"); - const shoulderBone = this.boxer.bone(gloveName === "gloveL" ? "shoulderL" : "shoulderR"); - if (gloveBone === null || elbowBone === null || shoulderBone === null) return; - this.boxer.root.updateMatrixWorld(true); - const gloveWorld = gloveBone.getWorldPosition(this.scratchB); - const correction = this.scratchC.subVectors(opponentTarget, gloveWorld); - const contactDistance = hurtbox.radius + GLOVE_HITBOX_RADIUS; - const overshoot = correction.length() - contactDistance; - if (overshoot <= 0.01) return; - correction.setLength(Math.min(0.42, overshoot)); - const targetWorld = this.aimTarget.copy(gloveWorld).add(correction); - const shoulderWorld = shoulderBone.getWorldPosition(this.aimShoulder); - const upper = this.boxer.metrics.armUpper; - const fore = this.boxer.metrics.armFore; - const to = this.aimTo.copy(targetWorld).sub(shoulderWorld); - const reachReserve = this.punchClass === "hook" ? 0.11 : this.punchClass === "uppercut" ? 0.07 : 0.015; - const distance = THREE.MathUtils.clamp(to.length(), 0.12, upper + fore - reachReserve); - to.normalize(); - const a = (upper * upper - fore * fore + distance * distance) / (2 * distance); - const h = Math.sqrt(Math.max(0.0001, upper * upper - a * a)); - const pole = this.aimPole.set(0.9 * (gloveName === "gloveL" ? 1 : -1), -1, -0.25).applyQuaternion(this.boxer.root.quaternion); - const bend = this.aimBend.copy(pole).addScaledVector(to, -pole.dot(to)).normalize(); - const elbowWorld = this.aimElbow.copy(shoulderWorld).addScaledVector(to, a).addScaledVector(bend, h); - aimBoneLocal(shoulderBone, elbowBone, elbowWorld); - shoulderBone.updateMatrixWorld(true); - aimBoneLocal(elbowBone, gloveBone, targetWorld); + private applyCelebratePose( + blend: number, + time: number, + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + lead: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + rear: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const lerp = THREE.MathUtils.lerp; + const pump = Math.sin(time * 6) * 0.04; + torso.hips.y = lerp(torso.hips.y, STANCE.hipsHeight + 0.035 + pump * 0.5, blend); + torso.hipsYaw = lerp(torso.hipsYaw, 0, blend); + torso.hipsPitch = lerp(torso.hipsPitch, -0.12, blend); + torso.hipsRoll = lerp(torso.hipsRoll, 0, blend); + torso.shouldersYaw = lerp(torso.shouldersYaw, 0, blend); + torso.spinePitch = lerp(torso.spinePitch, -0.1, blend); + torso.headPitch = lerp(torso.headPitch, -0.25, blend); + leadHand.position.lerp(seatedScratch.set(0.3 * mirror, 1.86 + pump, 0.08), blend); + rearHand.position.lerp(seatedScratch.set(-0.3 * mirror, 1.84 + pump, 0.06), blend); + leadHand.palm.lerp(seatedScratch.set(0, 0, 1), blend).normalize(); + rearHand.palm.lerp(seatedScratch.set(0, 0, 1), blend).normalize(); + leadHand.knuckles.lerp(seatedScratch.set(0.15 * mirror, 1, 0), blend).normalize(); + rearHand.knuckles.lerp(seatedScratch.set(-0.15 * mirror, 1, 0), blend).normalize(); + leadHand.pole.lerp(seatedScratch.set(mirror, 0.1, -0.3), blend).normalize(); + rearHand.pole.lerp(seatedScratch.set(-mirror, 0.1, -0.3), blend).normalize(); + lead.heel = lerp(lead.heel, 0.45, blend); + rear.heel = lerp(rear.heel, 0.45, blend); } - private applyDislocation(): void { - if (this.dislocation === null) return; - if (this.dislocation === "jaw") { - const head = this.boxer.bone("head"); - if (head !== null) { - head.quaternion.multiply( - this.scratchQ.setFromEuler(new THREE.Euler(0.08, 0.2, -0.22)), - ); + private applyAttendPose( + blend: number, + time: number, + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const lerp = THREE.MathUtils.lerp; + const work = Math.sin(time * 3.1) * 0.03; + torso.hips.z = lerp(torso.hips.z, 0.12, blend); + torso.hips.y = lerp(torso.hips.y, STANCE.hipsHeight - 0.04, blend); + torso.hipsPitch = lerp(torso.hipsPitch, 0.3, blend); + torso.spinePitch = lerp(torso.spinePitch, 0.42, blend); + torso.headPitch = lerp(torso.headPitch, 0.4, blend); + leadHand.position.lerp(seatedScratch.set(0.2 * mirror, 1.3 + work, 0.62), blend); + rearHand.position.lerp(seatedScratch.set(-0.18 * mirror, 1.24 - work, 0.58), blend); + leadHand.palm.lerp(seatedScratch.set(0, -0.6, 0.8), blend).normalize(); + rearHand.palm.lerp(seatedScratch.set(0, -0.6, 0.8), blend).normalize(); + leadHand.knuckles.lerp(seatedScratch.set(0.1 * mirror, 0.5, 1), blend).normalize(); + rearHand.knuckles.lerp(seatedScratch.set(-0.1 * mirror, 0.5, 1), blend).normalize(); + leadHand.pole.lerp(seatedScratch.set(0.8 * mirror, -0.5, -0.1), blend).normalize(); + rearHand.pole.lerp(seatedScratch.set(-0.8 * mirror, -0.5, -0.1), blend).normalize(); + } + + /** Cutman work: a deep crouch before the seated fighter, the lead glove pressing the enswell on the eye, the rear hand steadying the jaw. */ + private applyTreatPose( + blend: number, + time: number, + mirror: number, + leadHand: HandTarget, + rearHand: HandTarget, + lead: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + rear: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const lerp = THREE.MathUtils.lerp; + const rootPosition = this.treatScratch.set(this.rootX ?? 0, 0, this.rootZ); + const inverse = this.scratchQ.setFromAxisAngle(worldUpVector, -this.yaw); + const eye = seatedScratch.copy(this.treatTarget).sub(rootPosition).applyQuaternion(inverse); + const facing = this.treatFacingLocal.copy(this.treatFacing).applyQuaternion(inverse); + const leftX = facing.z; + const leftZ = -facing.x; + const press = Math.sin(time * 2.6) * 0.006; + torso.hips.lerp(this.treatScratch.set(0, 0.62, 0.04), blend); + torso.hipsYaw = lerp(torso.hipsYaw, 0, blend); + torso.hipsPitch = lerp(torso.hipsPitch, 0.22, blend); + torso.hipsRoll = lerp(torso.hipsRoll, 0, blend); + torso.shouldersYaw = lerp(torso.shouldersYaw, 0, blend); + torso.spinePitch = lerp(torso.spinePitch, 0.3, blend); + torso.headPitch = lerp(torso.headPitch, 0.2, blend); + lead.position.x = lerp(lead.position.x, 0.24 * mirror, blend); + lead.position.z = lerp(lead.position.z, 0.14, blend); + rear.position.x = lerp(rear.position.x, -0.2 * mirror, blend); + rear.position.z = lerp(rear.position.z, -0.2, blend); + rear.heel = lerp(rear.heel, 0.55, blend); + lead.toe.lerp(this.treatScratch.set(0.2 * mirror, 0, 1), blend).normalize(); + rear.toe.lerp(this.treatScratch.set(-0.1 * mirror, 0, 1), blend).normalize(); + lead.pole.lerp(this.treatScratch.set(0.25 * mirror, 0.4, 1), blend).normalize(); + rear.pole.lerp(this.treatScratch.set(-0.2 * mirror, 0.4, 1), blend).normalize(); + const reach = 0.08 - press; + leadHand.position.lerp(this.treatScratch.set(eye.x + facing.x * reach, eye.y - 0.07, eye.z + facing.z * reach), blend); + leadHand.knuckles.lerp(this.treatScratch.set(0, 1, 0.05), blend).normalize(); + leadHand.palm.lerp(this.treatScratch.set(-facing.x, 0, -facing.z), blend).normalize(); + leadHand.pole.lerp(this.treatScratch.set(0.85 * mirror, -0.35, 0.1), blend).normalize(); + const jaw = this.treatSide * 0.135; + rearHand.position.lerp(this.treatScratch.set(eye.x - leftX * jaw + facing.x * 0.05, eye.y - 0.2, eye.z - leftZ * jaw + facing.z * 0.05), blend); + rearHand.knuckles.lerp(this.treatScratch.set(0, 0.9, 0.4), blend).normalize(); + rearHand.palm.lerp(this.treatScratch.set(leftX * this.treatSide * 0.8 - facing.x * 0.6, 0.1, leftZ * this.treatSide * 0.8 - facing.z * 0.6), blend).normalize(); + rearHand.pole.lerp(this.treatScratch.set(-0.85 * mirror, -0.4, 0.1), blend).normalize(); + } + + private applyBreakPose( + blend: number, + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const lerp = THREE.MathUtils.lerp; + torso.hipsPitch = lerp(torso.hipsPitch, 0.14, blend); + torso.spinePitch = lerp(torso.spinePitch, 0.08, blend); + const leadTarget = this.scratchC.set(0.48 * mirror, 1.22, 0.52); + const rearTarget = this.scratchD.set(-0.48 * mirror, 1.22, 0.52); + if (this.breakAimed) { + // A palm on the front of each fighter's chest, the side facing the other fighter. + const [first, second] = this.breakFighters; + const toward = this.scratch.subVectors(second, first).setY(0).normalize(); + const inverse = this.scratchQ.setFromAxisAngle(worldUpVector, -this.yaw); + const root = this.scratchB.set(this.rootX ?? 0, 0, this.rootZ); + leadTarget.copy(first).addScaledVector(toward, BREAK_CHEST_DEPTH).sub(root).applyQuaternion(inverse); + rearTarget.copy(second).addScaledVector(toward, -BREAK_CHEST_DEPTH).sub(root).applyQuaternion(inverse); + if (leadTarget.x * mirror < rearTarget.x * mirror) { + root.copy(leadTarget); + leadTarget.copy(rearTarget); + rearTarget.copy(root); } - const jaw = this.boxer.trauma.jaw; - const rest = jaw.userData.restPosition as THREE.Vector3; - jaw.position.copy(rest).add(this.scratchA.set(0.04, -0.04, 0.018)); - jaw.rotation.set(0.16, 0.08, -0.18); - return; + leadTarget.y = BREAK_CHEST_HEIGHT; + rearTarget.y = BREAK_CHEST_HEIGHT; } - const side = this.dislocation === "shoulder_left" ? "L" : "R"; - const shoulder = this.boxer.bone(`shoulder${side}`); - const elbow = this.boxer.bone(`elbow${side}`); - if (shoulder === null || elbow === null) return; - this.boxer.root.updateMatrixWorld(true); - const shoulderWorld = shoulder.getWorldPosition(this.scratchA); - const hangingOffset = this.scratchB - .set(side === "L" ? 0.2 : -0.2, -0.38, 0.04) - .applyQuaternion(this.boxer.root.quaternion); - aimBoneLocal(shoulder, elbow, hangingOffset.add(shoulderWorld)); - } - - private lockFeet(fighter: FighterSnapshot, moving: boolean): void { - for (const side of ["L", "R"] as const) { - const ankle = this.boxer.bone(`ankle${side}`); - const knee = this.boxer.bone(`knee${side}`); - const hip = this.boxer.bone(`hip${side}`); - if (ankle === null || knee === null || hip === null) continue; - this.boxer.root.updateMatrixWorld(true); - const world = ankle.getWorldPosition(this.lockAnkle); - const key = side === "L" ? "plantedL" : "plantedR"; - let planted = this[key]; - if (moving || fighter.is_downed || world.y > this.boxer.metrics.ankleRestY * 1.35) { - this[key] = null; - continue; - } - if (planted === null) { - this[key] = world.clone(); - continue; - } - const flatDrift = Math.hypot(world.x - planted.x, world.z - planted.z); - if (flatDrift > 0.11) { - this[key] = world.clone(); - planted = this[key]; - continue; + leadHand.position.lerp(leadTarget, blend); + rearHand.position.lerp(rearTarget, blend); + leadHand.palm.lerp(seatedScratch.set(mirror, 0, 0.2), blend).normalize(); + rearHand.palm.lerp(seatedScratch.set(-mirror, 0, 0.2), blend).normalize(); + leadHand.knuckles.lerp(seatedScratch.set(0, 0.3, 1), blend).normalize(); + rearHand.knuckles.lerp(seatedScratch.set(0, 0.3, 1), blend).normalize(); + leadHand.pole.lerp(seatedScratch.set(0.2 * mirror, -1, 0.1), blend).normalize(); + rearHand.pole.lerp(seatedScratch.set(-0.2 * mirror, -1, 0.1), blend).normalize(); + } + + private applyWaveOffPose( + blend: number, + time: number, + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const lerp = THREE.MathUtils.lerp; + const sweep = Math.cos(time * 7.5); + torso.hipsPitch = lerp(torso.hipsPitch, 0.08, blend); + torso.spinePitch = lerp(torso.spinePitch, 0.05, blend); + torso.headPitch = lerp(torso.headPitch, -0.1, blend); + leadHand.position.lerp(seatedScratch.set(0.42 * sweep * mirror, 1.66 + Math.abs(sweep) * 0.08, 0.34), blend); + rearHand.position.lerp(seatedScratch.set(-0.42 * sweep * mirror, 1.62 + Math.abs(sweep) * 0.08, 0.24), blend); + leadHand.palm.lerp(seatedScratch.set(0, 0, 1), blend).normalize(); + rearHand.palm.lerp(seatedScratch.set(0, 0, 1), blend).normalize(); + leadHand.knuckles.lerp(seatedScratch.set(0, 1, 0), blend).normalize(); + rearHand.knuckles.lerp(seatedScratch.set(0, 1, 0), blend).normalize(); + leadHand.pole.lerp(seatedScratch.set(mirror, -0.2, -0.3), blend).normalize(); + rearHand.pole.lerp(seatedScratch.set(-mirror, -0.2, -0.3), blend).normalize(); + } + + private applySeatedPose( + blend: number, + time: number, + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + lead: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + rear: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const lerp = THREE.MathUtils.lerp; + const breath = 0.5 + 0.5 * Math.sin(time * 1.9); + torso.hips.lerp(seatedScratch.set(0.02 * mirror, STOOL_SEAT_HEIGHT + 0.07 + breath * 0.004, -0.06), blend); + torso.hipsYaw = lerp(torso.hipsYaw, 0, blend); + torso.hipsPitch = lerp(torso.hipsPitch, 0.32 + breath * 0.03, blend); + torso.hipsRoll = lerp(torso.hipsRoll, 0, blend); + torso.shouldersYaw = lerp(torso.shouldersYaw, 0, blend); + torso.spinePitch = lerp(torso.spinePitch, 0.1 - breath * 0.05, blend); + torso.headPitch = lerp(torso.headPitch, 0.28 - breath * 0.08, blend); + leadHand.position.lerp(seatedScratch.set(0.21 * mirror, STOOL_SEAT_HEIGHT + 0.17, 0.36), blend); + rearHand.position.lerp(seatedScratch.set(-0.21 * mirror, STOOL_SEAT_HEIGHT + 0.17, 0.36), blend); + leadHand.palm.lerp(seatedScratch.set(0, -1, 0), blend).normalize(); + rearHand.palm.lerp(seatedScratch.set(0, -1, 0), blend).normalize(); + leadHand.knuckles.lerp(seatedScratch.set(0.2 * mirror, 0, 1), blend).normalize(); + rearHand.knuckles.lerp(seatedScratch.set(-0.2 * mirror, 0, 1), blend).normalize(); + leadHand.pole.lerp(seatedScratch.set(0.9 * mirror, -0.3, -0.2), blend).normalize(); + rearHand.pole.lerp(seatedScratch.set(-0.9 * mirror, -0.3, -0.2), blend).normalize(); + // Foot targets are ankle joints: the soles rest on the canvas. + const ankle = this.boxer.rig.metrics.ankleHeight; + lead.position.lerp(seatedScratch.set(0.18 * mirror, ankle, 0.4), blend); + rear.position.lerp(seatedScratch.set(-0.18 * mirror, ankle, 0.38), blend); + lead.heel = lerp(lead.heel, 0, blend); + rear.heel = lerp(rear.heel, 0, blend); + lead.toe.lerp(seatedScratch.set(0.15 * mirror, 0, 1), blend).normalize(); + rear.toe.lerp(seatedScratch.set(-0.15 * mirror, 0, 1), blend).normalize(); + lead.pole.lerp(seatedScratch.set(0.1 * mirror, 0.5, 1), blend).normalize(); + rear.pole.lerp(seatedScratch.set(-0.1 * mirror, 0.5, 1), blend).normalize(); + } + + private applyDownPose( + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + lead: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + rear: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + ): void { + const torso = this.torso; + const standing = this.downStanding; + standing.hips.copy(torso.hips); + standing.hipsYaw = torso.hipsYaw; + standing.hipsPitch = torso.hipsPitch; + standing.hipsRoll = torso.hipsRoll; + standing.shouldersYaw = torso.shouldersYaw; + standing.spinePitch = torso.spinePitch; + standing.headPitch = torso.headPitch; + standing.leadHand.copy(leadHand.position); + standing.rearHand.copy(rearHand.position); + standing.leadFoot.copy(lead.position); + standing.rearFoot.copy(rear.position); + standing.leadHeel = lead.heel; + standing.rearHeel = rear.heel; + // Where he lands is chosen while the fall is still barely visible (the hit that decides it can arrive a + // frame after the knockdown), then kept. + if (!this.landSettled) this.chooseLanding(mirror); + this.landSettled = this.downState !== "falling" || this.fallAge > KNOCKDOWN_FALL_SECONDS * 0.15; + const pose = this.downResult; + if (this.downState !== "falling") { + // Down and getting up: lying -> all fours -> one knee -> stand, as far as the get-up has come. + const u = this.riseProgress; + let stand = 0; + if (u < RISE_FOURS) { + const s = smoothstep(0, RISE_FOURS, u); + const lying = this.placeLying(mirror); + const fours = this.placeDown(this.downTo, ALL_FOURS, mirror); + lerpDownPose(pose, lying, fours, s); + // Face down, he pushes up on his gloves before the knees come under him: the hips rise first. + if (this.landProne) pose.hips.y = THREE.MathUtils.lerp(lying.hips.y, fours.hips.y, easeOut(s, 3)); + } else if (u < RISE_KNEE) { + lerpDownPose(pose, this.placeDown(this.downFrom, ALL_FOURS, mirror), this.placeDown(this.downTo, ONE_KNEE, mirror), smoothstep(RISE_FOURS, RISE_KNEE, u)); + } else { + stand = smoothstep(RISE_KNEE, 1, u); + lerpDownPose(pose, this.placeDown(this.downFrom, ONE_KNEE, mirror), standing, stand); } - if (flatDrift < 0.008) continue; - const pinned = this.lockPinned.set(planted.x, world.y, planted.z); - const hipWorld = hip.getWorldPosition(this.lockHip); - const thigh = this.boxer.metrics.legThigh; - const shin = this.boxer.metrics.legShin; - const to = this.lockTo.copy(pinned).sub(hipWorld); - const distance = THREE.MathUtils.clamp(to.length(), 0.15, thigh + shin - 0.02); - to.normalize(); - const a = (thigh * thigh - shin * shin + distance * distance) / (2 * distance); - const h = Math.sqrt(Math.max(0.0001, thigh * thigh - a * a)); - const pole = this.lockPole.set(0, 0.2, 1).applyQuaternion(this.boxer.root.quaternion); - const bend = this.lockBend.copy(pole).addScaledVector(to, -pole.dot(to)); - if (bend.lengthSq() < 0.0001) bend.set(0, 0, 1); - bend.normalize(); - const kneeWorld = this.lockKnee.copy(hipWorld).addScaledVector(to, a).addScaledVector(bend, h); - aimBoneLocal(hip, knee, kneeWorld); - hip.updateMatrixWorld(true); - aimBoneLocal(knee, ankle, pinned); + this.writeDown(pose, mirror, leadHand, rearHand, lead, rear, 0, stand); + return; + } + const lying = this.placeLying(mirror); + const u = clamp(this.fallAge / KNOCKDOWN_FALL_SECONDS, 0, 1); + const t = easeIn(u, 2.1); + const start = this.fallFromGetUp ? this.fallStart : standing; + if (!this.fallFromGetUp) standing.hips.y -= smoothstep(0, 0.35, u) * (1 - smoothstep(0.35, 0.8, u)) * 0.12; + lerpDownPose(pose, start, lying, t); + // The feet slide out from under him while he is still high, so his knees never fold through the canvas; + // knocked down from his knees, the folded legs go with him from the start. + const feet = this.fallFromGetUp ? smoothstep(0, 0.6, u) : smoothstep(0.3, 0.9, u); + pose.leadFoot.lerpVectors(start.leadFoot, lying.leadFoot, feet); + pose.rearFoot.lerpVectors(start.rearFoot, lying.rearFoot, feet); + pose.leadHeel = THREE.MathUtils.lerp(start.leadHeel, lying.leadHeel, feet); + pose.rearHeel = THREE.MathUtils.lerp(start.rearHeel, lying.rearHeel, feet); + if (this.landProne) { + // Pitching forward, the gloves reach out ahead of him to break the fall. + const reach = easeOut(u, 2.5); + pose.leadHand.lerpVectors(start.leadHand, lying.leadHand, reach); + pose.rearHand.lerpVectors(start.rearHand, lying.rearHand, reach); + } else { + const flail = Math.sin(u * Math.PI) * 0.35; + pose.leadHand.y += flail; + pose.rearHand.y += flail * 0.8; + } + const stand = (this.fallFromGetUp ? this.fallStartStand : 1) * (1 - t); + this.writeDown(pose, mirror, leadHand, rearHand, lead, rear, Math.sin(u * Math.PI) * 0.12, stand); + } + + /** The pose the fighter ends up in on the canvas: face down or on his back, twisted by the fall side. */ + private placeLying(mirror: number): DownPose { + const ankle = this.boxer.rig.metrics.ankleHeight; + const pose = this.landProne + ? placeDownPose(this.downFrom, PRONE, PRONE_TWIST, mirror, this.landSide, ankle) + : placeDownPose(this.downFrom, LYING, LYING_TWIST, mirror, this.landSide, ankle); + return moveDownPose(pose, this.landShift); + } + + /** A get-up stage, over the root: a body that landed moved in from the ropes comes back as he gets onto all fours. */ + private placeDown(out: DownPose, base: DownPose, mirror: number): DownPose { + return placeDownPose(out, base, null, mirror, 0, this.boxer.rig.metrics.ankleHeight); + } + + /** + * Picks the fall that keeps the body inside the ropes: the punch's own when it fits, otherwise the variant + * (untwisted, twisted the other way, or falling the other way round) that needs the least moving in from + * the ropes, counting each change from the punch's fall as some distance moved. + */ + private chooseLanding(mirror: number): void { + const ankle = this.boxer.rig.metrics.ankleHeight; + let best = Infinity; + for (let index = 0; index < LANDINGS.length; index += 1) { + const [otherWay, twist, cost] = LANDINGS[index]!; + const prone = this.fallProne !== otherWay; + const side = this.fallSide * twist; + const pose = placeDownPose(this.downTo, prone ? PRONE : LYING, prone ? PRONE_TWIST : LYING_TWIST, mirror, side, ankle); + const shift = this.ropeShift(pose, this.scratchE); + if (shift.length() + cost >= best) continue; + best = shift.length() + cost; + this.landProne = prone; + this.landSide = side; + this.landShift.copy(shift); + } + } + + /** How far, in character space, a body lying in `pose` must move to stay inside the ropes. */ + private ropeShift(pose: DownPose, out: THREE.Vector3): THREE.Vector3 { + const turn = this.scratchQ.setFromAxisAngle(worldUpVector, this.yaw); + // The head and shoulders sit along the spine from the hips (the elbows bend out past the shoulders); the + // feet reach past the ankles to the toes, or to the heels when they are up on their toes. + downEuler.set(pose.hipsPitch + pose.spinePitch * 0.7, pose.hipsYaw, pose.hipsRoll, "YXZ"); + REACH_POINTS[0]!.set(0, HIPS_TO_HEAD, 0).applyEuler(downEuler).add(pose.hips); + REACH_POINTS[1]!.set(0.2, HIPS_TO_SHOULDERS, 0).applyEuler(downEuler).add(pose.hips); + REACH_POINTS[2]!.set(-0.2, HIPS_TO_SHOULDERS, 0).applyEuler(downEuler).add(pose.hips); + REACH_POINTS[3]!.copy(pose.leadHand); + REACH_POINTS[4]!.copy(pose.rearHand); + REACH_POINTS[5]!.copy(pose.leadFoot).z += pose.leadHeel > 0 ? 0.25 : 0.19; + REACH_POINTS[6]!.copy(pose.rearFoot).z += pose.rearHeel > 0 ? 0.25 : 0.19; + REACH_POINTS[7]!.copy(pose.hips); + let minX = Infinity; + let maxX = -Infinity; + let minZ = Infinity; + let maxZ = -Infinity; + for (let index = 0; index < REACH_POINTS.length; index += 1) { + const point = REACH_POINTS[index]!.applyQuaternion(turn); + const radius = REACH_RADII[index]!; + minX = Math.min(minX, (this.rootX ?? 0) + point.x - radius); + maxX = Math.max(maxX, (this.rootX ?? 0) + point.x + radius); + minZ = Math.min(minZ, this.rootZ + point.z - radius); + maxZ = Math.max(maxZ, this.rootZ + point.z + radius); + } + return out.set(fitInsideRopes(minX, maxX), 0, fitInsideRopes(minZ, maxZ)).applyQuaternion(turn.invert()); + } + + /** + * Writes a down or rising pose over the targets. `stand` is the share of the live standing pose in + * it: what the standing layers set (the guard's arm and knee directions, reactions) fades out on the + * way down and back in on the way up. + */ + private writeDown( + state: DownPose, + mirror: number, + leadHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + rearHand: { position: THREE.Vector3; knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, + lead: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + rear: { position: THREE.Vector3; toe: THREE.Vector3; heel: number; pole: THREE.Vector3 }, + headLag: number, + stand: number, + ): void { + const torso = this.torso; + const down = 1 - stand; + this.downStand = stand; + torso.hips.copy(state.hips); + torso.hipsYaw = state.hipsYaw; + torso.hipsPitch = state.hipsPitch; + torso.hipsRoll = state.hipsRoll; + torso.shouldersYaw = state.shouldersYaw; + torso.spinePitch = state.spinePitch; + torso.spineRoll *= stand; + torso.headPitch = state.headPitch; + torso.headYaw *= stand; + torso.headRoll *= stand; + torso.headOffset.multiplyScalar(stand); + torso.headOffset.z -= headLag; + leadHand.position.copy(state.leadHand); + rearHand.position.copy(state.rearHand); + turnDownArm(leadHand, mirror, state.palmsDown, down); + turnDownArm(rearHand, -mirror, state.palmsDown, down); + lead.position.copy(state.leadFoot); + rear.position.copy(state.rearFoot); + lead.toe.lerp(downScratch.set(0.2 * mirror, 0, 1).normalize(), down).normalize(); + rear.toe.lerp(downScratch.set(-0.2 * mirror, 0, 1).normalize(), down).normalize(); + lead.heel = state.leadHeel; + rear.heel = state.rearHeel; + // Knees bend the way the pelvis faces, whether that is the sky, the canvas or the opponent. + const forward = downScratch.set(0, 0, 1).applyEuler(downEuler.set(state.hipsPitch, state.hipsYaw, state.hipsRoll, "YXZ")); + lead.pole.lerp(forward, down); + rear.pole.lerp(forward, down); + } + + private applyDislocation(): void { + if (this.dislocation !== "jaw") return; + const head = this.boxer.bone("head"); + if (head !== null) { + head.quaternion.multiply(JAW_DISLOCATION); + head.updateWorldMatrix(false, true); } } dispose(): void { + this.stool.dispose(); + this.enswell.dispose(); this.boxer.dispose(); } } +const STOOL_SEAT_HEIGHT = 0.44; +/** Seated weight below which a rising fighter's hips are about 0.2 m clear of the seat. */ +const STOOL_CLEAR_SEATED = 0.2; +/** The engine counts a knockdown one number a second; the counting arm starts down this far into each second. */ +const COUNT_TICKS = 30; +const COUNT_DROP_START = 0.75; +/** Where the referee's palms press to break a clinch: on each fighter's chest, this far toward the other from his centre, at sternum height. */ +const BREAK_CHEST_DEPTH = 0.26; +const BREAK_CHEST_HEIGHT = 1.2; +const TOUCH_GLOVES_START_TICKS = 48; +const TOUCH_GLOVES_END_TICKS = 14; +/** Root-to-root distance at which the touch pose's gloves meet: each glove's front reaches 0.68 m ahead. */ +const TOUCH_GLOVES_GAP = 1.34; +/** Countdown ticks left over which the fighters walk in to the touch, and back onto their marks for the bell. */ +const TOUCH_WALK_IN_START_TICKS = 80; +const TOUCH_WALK_IN_END_TICKS = 56; +const TOUCH_WALK_BACK_START_TICKS = 24; +const TOUCH_WALK_BACK_END_TICKS = 4; +/** Metres per second; the walk itself peaks at about 1. */ +const TOUCH_WALK_TOP_SPEED = 1.5; +/** The engine's taunt length in ticks, over which the lead glove beckons TAUNT_BECKONS times. */ +const TAUNT_TICKS = 60; +const TAUNT_BECKONS = 4; +const seatedScratch = new THREE.Vector3(); +const JAW_DISLOCATION = new THREE.Quaternion().setFromEuler(new THREE.Euler(0.08, 0.2, -0.22)); + +/** A whole-body pose on the way down and back up, in character space. */ +interface DownPose { + readonly hips: THREE.Vector3; + hipsYaw: number; + hipsPitch: number; + hipsRoll: number; + shouldersYaw: number; + spinePitch: number; + headPitch: number; + readonly leadHand: THREE.Vector3; + readonly rearHand: THREE.Vector3; + /** Ankle positions; the tables give the sole's height above the canvas instead. */ + readonly leadFoot: THREE.Vector3; + readonly rearFoot: THREE.Vector3; + /** Heel lift: a foot pitched onto its toes, as on the canvas behind a kneeling or prone fighter. */ + leadHeel: number; + rearHeel: number; + /** 0 with the arms thrown out palm-up, 1 with the gloves pressed palm-down on the canvas. */ + palmsDown: number; +} + +const downScratch = new THREE.Vector3(); +const downEuler = new THREE.Euler(); +/** Arm directions on the canvas for an orthodox fighter's lead arm, thrown out palm-up or pressing palm-down. */ +const PALM_UP = { pole: vec(0.4, 0.9, 0.2), knuckles: vec(0.6, 0.2, -0.75).normalize(), palm: vec(0, 1, 0.2).normalize() }; +const PALM_DOWN = { pole: vec(0.6, 0.2, -0.7), knuckles: vec(0.25, -0.1, 1).normalize(), palm: vec(0, -1, 0.1).normalize() }; + +/** Turns an arm from its standing directions toward the down ones; `sideX` mirrors x for the stance and the arm. */ +function turnDownArm(hand: { knuckles: THREE.Vector3; palm: THREE.Vector3; pole: THREE.Vector3 }, sideX: number, palmsDown: number, down: number): void { + downScratch.lerpVectors(PALM_UP.pole, PALM_DOWN.pole, palmsDown); + downScratch.x *= sideX; + hand.pole.lerp(downScratch, down); + downScratch.lerpVectors(PALM_UP.knuckles, PALM_DOWN.knuckles, palmsDown); + downScratch.x *= sideX; + hand.knuckles.lerp(downScratch.normalize(), down).normalize(); + downScratch.lerpVectors(PALM_UP.palm, PALM_DOWN.palm, palmsDown); + downScratch.x *= sideX; + hand.palm.lerp(downScratch.normalize(), down).normalize(); +} + +function downPose(pose: Partial = {}): DownPose { + return { + hips: new THREE.Vector3(), + hipsYaw: 0, + hipsPitch: 0, + hipsRoll: 0, + shouldersYaw: 0, + spinePitch: 0, + headPitch: 0, + leadHand: new THREE.Vector3(), + rearHand: new THREE.Vector3(), + leadFoot: new THREE.Vector3(), + rearFoot: new THREE.Vector3(), + leadHeel: 0, + rearHeel: 0, + palmsDown: 0, + ...pose, + }; +} + +// The authored poses are for an orthodox fighter; a twist table is added per unit of fall side. +/** Lying on the back with the knees up; turning the hips swings the head the opposite way. */ +const LYING = downPose({ + hips: vec(0, 0.14, -0.4), hipsPitch: -1.42, spinePitch: 0.1, headPitch: -0.5, + leadHand: vec(0.52, 0.1, -0.62), rearHand: vec(-0.5, 0.1, -0.7), leadFoot: vec(0.17, 0, 0.16), rearFoot: vec(-0.16, 0, -0.02), +}); +const LYING_TWIST = downPose({ hips: vec(0.22, 0, 0), hipsYaw: -0.35, hipsRoll: -0.25, shouldersYaw: -0.2, leadFoot: vec(0.05, 0, 0), rearFoot: vec(0.05, 0, 0) }); +/** Face down after a hook or a body shot, on the toes: the fighter pitches forward over the front foot. */ +const PRONE = downPose({ + hips: vec(0, 0.25, 0.32), hipsPitch: 1.5, spinePitch: 0.05, headPitch: 0.2, palmsDown: 1, + leadHand: vec(0.34, 0.12, 0.78), rearHand: vec(-0.3, 0.12, 0.62), leadFoot: vec(0.16, 0, -0.82), rearFoot: vec(-0.15, 0, -0.86), leadHeel: 1.3, rearHeel: 1.3, +}); +const PRONE_TWIST = downPose({ hips: vec(0.12, 0, 0), hipsYaw: 0.3, hipsRoll: 0.15, shouldersYaw: 0.15, leadFoot: vec(0.04, 0, 0), rearFoot: vec(0.04, 0, 0) }); +/** The get-up's first stage, on the gloves and knees with the toes tucked under. */ +const ALL_FOURS = downPose({ + hips: vec(0.05, 0.52, -0.2), hipsYaw: STANCE.bladeYaw * 0.15, hipsPitch: 1.38, shouldersYaw: STANCE.bladeYaw * 0.15, spinePitch: 0.35, headPitch: 1.0, palmsDown: 1, + leadHand: vec(0.2, 0.115, 0.36), rearHand: vec(-0.2, 0.115, 0.32), leadFoot: vec(0.15, 0, -0.74), rearFoot: vec(-0.14, 0, -0.78), leadHeel: 1.25, rearHeel: 1.25, +}); +/** The get-up's second stage, on the rear knee with the lead foot planted and a glove on the knee. */ +const ONE_KNEE = downPose({ + hips: vec(0, 0.47, -0.05), hipsYaw: STANCE.bladeYaw * 0.12, hipsPitch: 0.2, shouldersYaw: STANCE.bladeYaw * 0.4, spinePitch: 0.3, headPitch: 0.2, palmsDown: 1, + leadHand: vec(0.15, 0.68, 0.32), rearHand: vec(-0.26, 0.42, 0.02), leadFoot: vec(0.15, 0, 0.36), rearFoot: vec(-0.13, 0, -0.7), rearHeel: 1.2, +}); + +/** Writes `base` mirrored for the stance, plus `twist` per unit of `side`, into `out`, with the feet raised by `ankle`. */ +function placeDownPose(out: DownPose, base: DownPose, twist: DownPose | null, mirror: number, side: number, ankle: number): DownPose { + out.hips.set(base.hips.x * mirror, base.hips.y, base.hips.z); + out.hipsYaw = base.hipsYaw * mirror; + out.hipsPitch = base.hipsPitch; + out.hipsRoll = base.hipsRoll * mirror; + out.shouldersYaw = base.shouldersYaw * mirror; + out.spinePitch = base.spinePitch; + out.headPitch = base.headPitch; + mirrorX(base.leadHand, mirror, out.leadHand); + mirrorX(base.rearHand, mirror, out.rearHand); + mirrorX(base.leadFoot, mirror, out.leadFoot).y += ankle; + mirrorX(base.rearFoot, mirror, out.rearFoot).y += ankle; + out.leadHeel = base.leadHeel; + out.rearHeel = base.rearHeel; + out.palmsDown = base.palmsDown; + if (twist === null || side === 0) return out; + out.hips.addScaledVector(twist.hips, side); + out.hipsYaw += twist.hipsYaw * side; + out.hipsPitch += twist.hipsPitch * side; + out.hipsRoll += twist.hipsRoll * side; + out.shouldersYaw += twist.shouldersYaw * side; + out.spinePitch += twist.spinePitch * side; + out.headPitch += twist.headPitch * side; + out.leadHand.addScaledVector(twist.leadHand, side); + out.rearHand.addScaledVector(twist.rearHand, side); + out.leadFoot.addScaledVector(twist.leadFoot, side); + out.rearFoot.addScaledVector(twist.rearFoot, side); + return out; +} + +/** Moves a whole pose by `shift` (character space). */ +function moveDownPose(pose: DownPose, shift: THREE.Vector3): DownPose { + pose.hips.add(shift); + pose.leadHand.add(shift); + pose.rearHand.add(shift); + pose.leadFoot.add(shift); + pose.rearFoot.add(shift); + return pose; +} + +/** The rope line between the corner posts (as built in ring.ts), less a margin for the rough reach of a lying body. */ +const ROPE_LINE = POST_RADIUS * 0.72 - 0.05; +/** Hips to the head bone, and to the shoulder line, along the spine of a body lying on the canvas. */ +const HIPS_TO_HEAD = 0.78; +const HIPS_TO_SHOULDERS = 0.5; +/** Head, shoulders, gloves, feet and hips of a lying body, and how far the mesh reaches around each. */ +const REACH_POINTS = Array.from({ length: 8 }, () => new THREE.Vector3()); +const REACH_RADII = [0.17, 0.22, 0.22, 0.13, 0.13, 0.12, 0.12, 0.2] as const; +/** Falls tried near the ropes: [the other way round, the punch's twist scaled by, cost of the change in metres]. */ +const LANDINGS: readonly (readonly [boolean, number, number])[] = [ + [false, 1, 0], + [false, 0, 0.15], + [false, -1, 0.3], + [true, 1, 0.4], + [true, 0, 0.5], + [true, -1, 0.6], +]; + +/** The move along one axis that brings the span [low, high] inside the rope line (centred if it cannot fit). */ +function fitInsideRopes(low: number, high: number): number { + if (low < -ROPE_LINE && high > ROPE_LINE) return -(low + high) / 2; + if (low < -ROPE_LINE) return -ROPE_LINE - low; + if (high > ROPE_LINE) return ROPE_LINE - high; + return 0; +} + +function copyDownPose(out: DownPose, from: DownPose): DownPose { + return lerpDownPose(out, from, from, 0); +} + +/** Writes the blend from `a` to `b` into `out`, which may be `a` but not `b`. */ +function lerpDownPose(out: DownPose, a: DownPose, b: DownPose, t: number): DownPose { + const lerp = THREE.MathUtils.lerp; + out.hips.copy(a.hips).lerp(b.hips, t); + out.hipsYaw = lerp(a.hipsYaw, b.hipsYaw, t); + out.hipsPitch = lerp(a.hipsPitch, b.hipsPitch, t); + out.hipsRoll = lerp(a.hipsRoll, b.hipsRoll, t); + out.shouldersYaw = lerp(a.shouldersYaw, b.shouldersYaw, t); + out.spinePitch = lerp(a.spinePitch, b.spinePitch, t); + out.headPitch = lerp(a.headPitch, b.headPitch, t); + out.leadHand.copy(a.leadHand).lerp(b.leadHand, t); + out.rearHand.copy(a.rearHand).lerp(b.rearHand, t); + out.leadFoot.copy(a.leadFoot).lerp(b.leadFoot, t); + out.rearFoot.copy(a.rearFoot).lerp(b.rearFoot, t); + out.leadHeel = lerp(a.leadHeel, b.leadHeel, t); + out.rearHeel = lerp(a.rearHeel, b.rearHeel, t); + out.palmsDown = lerp(a.palmsDown, b.palmsDown, t); + return out; +} + +/** How far a count's end may stray from the one held before it is taken again: a few snapshots. */ +const LATCH_SLACK_TICKS = 3; + +/** + * Render tick at which a count carried in the snapshots runs out. The snapshots step such counts once + * per tick while the render tick moves every frame, so a pose timed straight from the count moves in + * 30 Hz steps. The end is held instead, and taken again only when the count disagrees with it by more + * than a few snapshots (a new count, or a jump in the clock). Null while there is no count. + */ +function latchEndTick(held: number | null, sampledTick: number, remaining: number | null): number | null { + if (remaining === null) return null; + const end = sampledTick + remaining; + return held === null || Math.abs(end - held) > LATCH_SLACK_TICKS ? end : held; +} + +/** How far through the walk in to the glove touch a fighter is, by countdown ticks left: 0 on his mark, 1 at the touch. */ +function touchWalkProgress(ticksLeft: number): number { + return (1 - smoothstep(TOUCH_WALK_IN_END_TICKS, TOUCH_WALK_IN_START_TICKS, ticksLeft)) * smoothstep(TOUCH_WALK_BACK_END_TICKS, TOUCH_WALK_BACK_START_TICKS, ticksLeft); +} + +function buildEnswell(): { group: THREE.Group; dispose: () => void } { + const group = new THREE.Group(); + group.name = "enswell"; + group.visible = false; + const plateGeometry = new THREE.CylinderGeometry(0.03, 0.03, 0.008, 16); + const handleGeometry = new THREE.CylinderGeometry(0.008, 0.008, 0.06, 8); + const metal = new THREE.MeshStandardMaterial({ color: 0xc8ccd2, roughness: 0.3, metalness: 0.9 }); + const plate = new THREE.Mesh(plateGeometry, metal); + plate.rotation.x = Math.PI / 2; + plate.position.set(0, 0.07, 0.075); + group.add(plate); + const handle = new THREE.Mesh(handleGeometry, metal); + handle.position.set(0, 0.035, 0.075); + group.add(handle); + return { + group, + dispose: () => { + plateGeometry.dispose(); + handleGeometry.dispose(); + metal.dispose(); + }, + }; +} + +function buildStool(): { group: THREE.Group; dispose: () => void } { + const group = new THREE.Group(); + group.name = "stool"; + group.visible = false; + const seatGeometry = new THREE.CylinderGeometry(0.17, 0.17, 0.035, 18); + const legGeometry = new THREE.CylinderGeometry(0.012, 0.014, STOOL_SEAT_HEIGHT - 0.02, 8); + const seatMaterial = new THREE.MeshStandardMaterial({ color: 0xc9c2b5, roughness: 0.85 }); + const legMaterial = new THREE.MeshStandardMaterial({ color: 0x2a2d33, roughness: 0.45, metalness: 0.6 }); + const seat = new THREE.Mesh(seatGeometry, seatMaterial); + seat.position.y = STOOL_SEAT_HEIGHT - 0.0175; + seat.castShadow = true; + group.add(seat); + for (let index = 0; index < 4; index += 1) { + const angle = Math.PI / 4 + (index * Math.PI) / 2; + const leg = new THREE.Mesh(legGeometry, legMaterial); + leg.position.set(Math.cos(angle) * 0.13, (STOOL_SEAT_HEIGHT - 0.02) / 2, Math.sin(angle) * 0.13); + leg.rotation.set(-Math.sin(angle) * 0.12, 0, Math.cos(angle) * 0.12); + leg.castShadow = true; + group.add(leg); + } + return { + group, + dispose: () => { + seatGeometry.dispose(); + legGeometry.dispose(); + seatMaterial.dispose(); + legMaterial.dispose(); + }, + }; +} + +const worldUpVector = new THREE.Vector3(0, 1, 0); +/** Most ticks of latency a predicted punch absorbs by stretching its startup; beyond this the hit is shown late instead. */ +const MAX_OWN_LEAD_TICKS = 6; +const OWN_PUNCH_GRACE_TICKS = 5; +const OWN_PUNCH_PULL_RATE = 1.5; +/** Presses closer together than this usually reach the server before the same step, where the newer one replaces the older. */ +const SAME_STEP_TICKS = 0.5; +/** Contact events in which a punch met the opponent: a hit or a block, a parry included. */ +const CONNECTING_CONTACTS: ReadonlySet = new Set(["hit", "counter_hit", "block", "perfect_block"]); +const EVASION_POSES: ReadonlySet = new Set(["slip_left", "slip_right", "weave", "pull"]); +/** Seconds after an evasion ends for the head to settle back (the slip, weave and pull ease at 14-16 a second). */ +const HEAD_SETTLE_SECONDS = 0.25; +/** Rate at which a punch known to connect turns its aim onto the head where it actually is. */ +const FOLLOW_HEAD_RATE = 30; +/** How far the elbow's pull swings out while it turns from the guard's to the punch's. */ +const ONSET_ELBOW_FLARE = 2; + +/** Age in `to`'s timing at the same progress through the same phase as `age` in `from`'s. */ +export function remapPunchAge(age: number, from: PunchTiming, to: PunchTiming): number { + if (age < from.startup) return (age / Math.max(1, from.startup)) * to.startup; + const active = age - from.startup; + if (active < from.active) return to.startup + (active / Math.max(1, from.active)) * to.active; + const recovery = Math.min(1, (active - from.active) / Math.max(1, from.recovery)); + return to.startup + to.active + recovery * to.recovery; +} +/** Metres per second the rendered root may move toward the authoritative position; above any walking speed so slow frames never fall behind. */ +const ROOT_FOLLOW_SPEED = 6; + const aimJointWorld = new THREE.Vector3(); const aimChildWorld = new THREE.Vector3(); const aimCurrentDirection = new THREE.Vector3(); diff --git a/web/hands/src/render/hud.ts b/web/hands/src/render/hud.ts index f17e8f4b..6323d616 100644 --- a/web/hands/src/render/hud.ts +++ b/web/hands/src/render/hud.ts @@ -1,4 +1,4 @@ -import type { EngineSnapshot, FinalMessage, PublicPlayer } from "../types"; +import type { CombatEvent, EngineSnapshot, FinalMessage, PublicPlayer } from "../types"; export const HUD_MAX_GUARD = 700; export const HUD_MAX_POISE = 600; @@ -12,6 +12,12 @@ const fit = (ctx: CanvasRenderingContext2D, text: string, width: number): string return `${value}…`; }; +/** Largest font size from `maximum` down to `minimum` (whole pixels) at which `measure` fits `width`, else `minimum`. */ +export const fitFontSize = (measure: (size: number) => number, width: number, maximum: number, minimum: number): number => { + for (let size = maximum; size > minimum; size -= 1) if (measure(size) <= width) return size; + return minimum; +}; + interface BarSpec { readonly label: string; readonly value: number; @@ -83,8 +89,13 @@ function fighterPlate( const textX = mirror ? x + width - 20 : x + 20; ctx.textAlign = mirror ? "right" : "left"; ctx.fillStyle = "#f5f8ff"; - ctx.font = "800 16px Inter, system-ui, sans-serif"; - ctx.fillText(fit(ctx, name.toUpperCase(), width - 44), textX, y + 21); + const label = name.toUpperCase(); + const nameSize = fitFontSize((size) => { + ctx.font = `800 ${size}px Inter, system-ui, sans-serif`; + return ctx.measureText(label).width; + }, width - 44, 16, 11); + ctx.font = `800 ${nameSize}px Inter, system-ui, sans-serif`; + ctx.fillText(fit(ctx, label, width - 44), textX, y + 21); ctx.fillStyle = "#93a3bd"; ctx.font = "600 10px Inter, system-ui, sans-serif"; ctx.fillText(detail, textX, y + 35); @@ -134,9 +145,18 @@ function roundCard(ctx: CanvasRenderingContext2D, centerX: number, y: number, cl ctx.restore(); } +const PANEL_HEIGHT = 78; +const SHORT_PANEL_HEIGHT = 50; +const panelHeightFor = (height: number): number => (height < 480 ? SHORT_PANEL_HEIGHT : PANEL_HEIGHT); + +/** Offset that parks a centre panel under the top bar, or under the round card on narrow screens, clear of the fighters. */ +export const topPanelOffset = (width: number, height: number): number => + Math.max(width < 640 ? 112 : 56, height * 0.1) + panelHeightFor(height) / 2 - height / 2; + function centerPanel(ctx: CanvasRenderingContext2D, width: number, height: number, title: string, subtitle: string, yOffset = 0): void { - const panelWidth = 320; - const panelHeight = 78; + const panelWidth = Math.min(320, width - 24); + const panelHeight = panelHeightFor(height); + const short = panelHeight === SHORT_PANEL_HEIGHT; const x = width / 2 - panelWidth / 2; const y = height / 2 - panelHeight / 2 + yOffset; ctx.fillStyle = "rgba(3,6,12,0.88)"; @@ -146,11 +166,102 @@ function centerPanel(ctx: CanvasRenderingContext2D, width: number, height: numbe ctx.strokeRect(x + 2, y + 2, panelWidth - 4, panelHeight - 4); ctx.textAlign = "center"; ctx.fillStyle = "#ffd77a"; - ctx.font = "800 22px Inter, system-ui, sans-serif"; - ctx.fillText(title, width / 2, y + 34); + ctx.font = `800 ${short ? 17 : 22}px Inter, system-ui, sans-serif`; + ctx.fillText(title, width / 2, y + (short ? 22 : 34)); ctx.fillStyle = "#c8d3e6"; - ctx.font = "600 12px Inter, system-ui, sans-serif"; - ctx.fillText(subtitle, width / 2, y + 58); + ctx.font = `600 ${short ? 11 : 12}px Inter, system-ui, sans-serif`; + ctx.fillText(fit(ctx, subtitle, panelWidth - 24), width / 2, y + (short ? 39 : 58)); +} + +/** Holds the round clock while a knockdown count or a foul timeout runs its own timer. */ +export class RoundClock { + private fightTicks: number | null = null; + private round = 0; + + ticks(snapshot: EngineSnapshot): number { + if (snapshot.round_number !== this.round) { + this.round = snapshot.round_number; + this.fightTicks = null; + } + if (snapshot.phase === "fight") this.fightTicks = snapshot.phase_ticks_remaining; + const held = snapshot.phase === "knockdown" || snapshot.phase === "foul_recovery"; + return held && this.fightTicks !== null ? this.fightTicks : snapshot.phase_ticks_remaining; + } +} + +export interface RoundPunchStats { + thrown: number; + landed: number; +} + +/** Punches thrown and landed per fighter in the current round, reset on the round-start bell. */ +export class RoundStatsTracker { + private readonly stats = new Map(); + private readonly totals = new Map(); + + record(event: CombatEvent): void { + if (event.kind === "bell") { + if (event.detail === "round_start") this.stats.clear(); + return; + } + if (event.actor_id === null) return; + if (event.kind === "punch_start") { + this.entry(this.stats, event.actor_id).thrown += 1; + this.entry(this.totals, event.actor_id).thrown += 1; + } else if (event.kind === "hit" || event.kind === "counter_hit") { + this.entry(this.stats, event.actor_id).landed += 1; + this.entry(this.totals, event.actor_id).landed += 1; + } + } + + get(playerId: string): RoundPunchStats { + return this.stats.get(playerId) ?? { thrown: 0, landed: 0 }; + } + + /** Punches over the whole bout, for the result panel. */ + total(playerId: string): RoundPunchStats { + return this.totals.get(playerId) ?? { thrown: 0, landed: 0 }; + } + + private entry(map: Map, playerId: string): RoundPunchStats { + let entry = map.get(playerId); + if (entry === undefined) { + entry = { thrown: 0, landed: 0 }; + map.set(playerId, entry); + } + return entry; + } +} + +/** Headline for the result panel: decisions and draws say whether the judges were unanimous, split or majority. */ +export function decisionLabel(final: FinalMessage): string { + const base = final.method.replaceAll("_", " ").toUpperCase(); + if (final.method !== "decision" && final.method !== "draw") return base; + let one = 0; + let two = 0; + let even = 0; + for (const card of final.scorecards) { + const a = scoreTotal(card.player_one); + const b = scoreTotal(card.player_two); + if (a > b) one += 1; + else if (b > a) two += 1; + else even += 1; + } + const cards = final.scorecards.length; + if (cards === 0) return base; + if (final.method === "draw") return even === cards ? "UNANIMOUS DRAW" : one === two ? "SPLIT DRAW" : "MAJORITY DRAW"; + const winnerCards = Math.max(one, two); + if (winnerCards === cards) return "UNANIMOUS DECISION"; + if (even > 0) return "MAJORITY DECISION"; + return "SPLIT DECISION"; +} + +export const STOPPAGE_METHODS: ReadonlySet = new Set(["ko", "flash_ko", "tko"]); +export const FINAL_REVEAL_DELAY_SECONDS = 3.6; + +/** Seconds to hold the result panel back so a stoppage's slow-motion fall stays visible. */ +export function finalRevealDelay(final: FinalMessage | null): number { + return final !== null && STOPPAGE_METHODS.has(final.method) ? FINAL_REVEAL_DELAY_SECONDS : 0; } export function drawHud( @@ -163,10 +274,17 @@ export function drawHud( final: FinalMessage | null, reconnectMs: number, tickRate = 30, + roundStats: RoundStatsTracker | null = null, + replayLabel: string | null = null, + inputLatencyMs: number | null = null, + roundCallout: string | null = null, + clockTicks: number | null = null, ): void { ctx.save(); ctx.textBaseline = "alphabetic"; - const plateWidth = Math.min(300, width * 0.38); + // Below 640 px the two plates share the bottom edge and the round card moves under the top bar. + const compact = width < 640; + const plateWidth = compact ? (width - 56) / 2 : Math.min(300, width * 0.38); const plateY = height - 84; snapshot.fighters.forEach((fighter, index) => { @@ -175,110 +293,198 @@ export function drawHud( const player = players[fighter.player_id]; const detail = `ELO ${player?.rating ?? "—"} · KD ${fighter.knockdowns} · W ${fighter.warnings} · −${fighter.deductions}`; const bars: BarSpec[] = [ - { label: `STAMINA ${Math.round(fighter.stamina)}`, value: fighter.stamina, maximum: fighter.maximum_stamina, from: "#ffe08a", to: "#d9a53a" }, - { label: `HEALTH ${Math.round(fighter.conditioning)}`, value: fighter.conditioning, maximum: HUD_MAX_CONDITIONING, from: "#ff8a7a", to: "#b02a20" }, + { label: `${compact ? "STA" : "STAMINA"} ${Math.round(fighter.stamina)}`, value: fighter.stamina, maximum: fighter.maximum_stamina, from: "#ffe08a", to: "#d9a53a" }, + { label: `${compact ? "HP" : "HEALTH"} ${Math.round(fighter.conditioning)}`, value: fighter.conditioning, maximum: HUD_MAX_CONDITIONING, from: "#ff8a7a", to: "#b02a20" }, { label: "GUARD", value: fighter.guard, maximum: HUD_MAX_GUARD, from: "#9ec7ff", to: "#3d6fb8" }, { label: `POISE ${Math.round(fighter.poise)}`, value: fighter.poise, maximum: HUD_MAX_POISE, from: "#e8c890", to: "#8a6a34" }, ]; fighterPlate(ctx, x, plateY, plateWidth, player?.name ?? "Fighter", detail, bars.slice(0, 2), mirror, index === 0 ? "#3d6fb8" : "#b02a20"); const miniY = plateY - 12; - broadcastBar(ctx, mirror ? x + plateWidth - 148 : x + 20, miniY, 64, bars[2]!, mirror); - broadcastBar(ctx, mirror ? x + plateWidth - 72 : x + 96, miniY, 64, bars[3]!, mirror); + // Guard and poise ride above the plate, as wide as the plate's own bars once the plate is narrow. + const miniWidth = Math.min(64, (plateWidth - 52) / 2); + broadcastBar(ctx, mirror ? x + plateWidth - 20 - 2 * miniWidth : x + 20, miniY, miniWidth, bars[2]!, mirror); + broadcastBar(ctx, mirror ? x + plateWidth - 8 - miniWidth : x + 32 + miniWidth, miniY, miniWidth, bars[3]!, mirror); }); - const seconds = Math.floor(snapshot.phase_ticks_remaining / tickRate); + const seconds = Math.floor((clockTicks ?? snapshot.phase_ticks_remaining) / tickRate); const clock = `${Math.floor(seconds / 60)}:${String(seconds % 60).padStart(2, "0")}`; - roundCard(ctx, width / 2, height - 84, clock, `ROUND ${snapshot.round_number}`, snapshot.phase.replace("_", " ").toUpperCase()); + roundCard(ctx, width / 2, compact ? 54 : height - 84, clock, `ROUND ${snapshot.round_number}`, snapshot.phase.replace("_", " ").toUpperCase()); + if (inputLatencyMs !== null && final === null && snapshot.fighters.some((fighter) => fighter.player_id === viewerId)) { + const rounded = Math.round(inputLatencyMs); + ctx.save(); + ctx.textAlign = "right"; + ctx.font = "700 11px ui-monospace, monospace"; + ctx.fillStyle = rounded < 90 ? "rgba(170,200,180,0.75)" : rounded < 160 ? "rgba(240,200,110,0.9)" : "rgba(255,110,100,0.95)"; + ctx.fillText(`INPUT ${rounded} ms`, width - 24, compact ? 128 : 36); + ctx.restore(); + } + if (replayLabel !== null) { + const tagY = compact ? 120 : 64; + ctx.save(); + ctx.fillStyle = "rgba(3,6,12,0.82)"; + ctx.fillRect(24, tagY, 196, 34); + ctx.fillStyle = "#ff3b3b"; + ctx.beginPath(); + ctx.arc(42, tagY + 17, 6, 0, Math.PI * 2); + ctx.fill(); + ctx.fillStyle = "#f6f7fb"; + ctx.font = "800 14px Inter, system-ui, sans-serif"; + ctx.textAlign = "left"; + ctx.fillText(replayLabel, 56, tagY + 22); + ctx.restore(); + } + if (roundCallout !== null && snapshot.phase === "fight") { + ctx.save(); + ctx.textAlign = "center"; + ctx.font = "900 46px Inter, system-ui, sans-serif"; + ctx.lineWidth = 6; + ctx.strokeStyle = "rgba(0,0,0,0.75)"; + ctx.strokeText(roundCallout, width / 2, height * 0.22); + ctx.fillStyle = "#f6d57a"; + ctx.fillText(roundCallout, width / 2, height * 0.22); + ctx.restore(); + } + if (snapshot.phase === "countdown") { + centerPanel(ctx, width, height, `ROUND ${snapshot.round_number}`, "Touch gloves. Protect yourself at all times.", topPanelOffset(width, height)); + } if (snapshot.phase === "knockdown") { const viewer = snapshot.fighters.find((fighter) => fighter.player_id === viewerId); const downed = snapshot.fighters.find((fighter) => fighter.is_downed) ?? viewer; const count = Math.max(...snapshot.fighters.map((fighter) => fighter.get_up_count)); - const panelWidth = 380; - const panelHeight = 150; - const x = width / 2 - panelWidth / 2; - const y = height * 0.24; - ctx.fillStyle = "rgba(3,6,12,0.88)"; - ctx.fillRect(x, y, panelWidth, panelHeight); - ctx.strokeStyle = "rgba(246,213,122,0.5)"; - ctx.lineWidth = 2; - ctx.strokeRect(x + 2, y + 2, panelWidth - 4, panelHeight - 4); + const downedName = players[downed?.player_id ?? ""]?.name ?? "Fighter"; + ctx.save(); ctx.textAlign = "center"; - ctx.fillStyle = "#ffd77a"; - ctx.font = "800 30px Inter, system-ui, sans-serif"; - ctx.fillText(`COUNT ${count}`, width / 2, y + 40); - const prompt = viewer?.is_downed === true ? viewer.get_up_prompt : null; - if (prompt !== null && prompt !== undefined && viewer !== undefined) { - const inWindow = snapshot.tick >= viewer.get_up_window_start_tick && snapshot.tick <= viewer.get_up_window_end_tick; - const arrow = prompt === "get_up_left" ? "←" : "→"; - if (inWindow) { - ctx.fillStyle = "#ffe9a8"; - ctx.font = "900 64px Inter, system-ui, sans-serif"; - ctx.fillText(arrow, width / 2 - 90, y + 106); - ctx.fillStyle = "#7dffa8"; - ctx.font = "900 34px Inter, system-ui, sans-serif"; - ctx.fillText("NOW!", width / 2 + 62, y + 100); + ctx.font = "900 44px Inter, system-ui, sans-serif"; + ctx.lineWidth = 6; + ctx.strokeStyle = "rgba(0,0,0,0.75)"; + ctx.strokeText("KNOCKDOWN", width / 2, height * 0.16); + ctx.fillStyle = "#ff4d4d"; + ctx.fillText("KNOCKDOWN", width / 2, height * 0.16); + ctx.font = "700 15px Inter, system-ui, sans-serif"; + ctx.fillStyle = "#e6ecf7"; + ctx.fillText(`${fit(ctx, downedName.toUpperCase(), width * 0.5)} IS DOWN`, width / 2, height * 0.16 + 24); + ctx.restore(); + } + if (snapshot.phase === "knockdown" && replayLabel === null) { + const viewer = snapshot.fighters.find((fighter) => fighter.player_id === viewerId); + const count = Math.max(...snapshot.fighters.map((fighter) => fighter.get_up_count)); + if (viewer?.is_downed !== true) { + ctx.save(); + ctx.textAlign = "center"; + ctx.font = "900 36px Inter, system-ui, sans-serif"; + ctx.lineWidth = 5; + ctx.strokeStyle = "rgba(0,0,0,0.75)"; + ctx.strokeText(`COUNT ${count}`, width / 2, height * 0.16 + 64); + ctx.fillStyle = "#ffd77a"; + ctx.fillText(`COUNT ${count}`, width / 2, height * 0.16 + 64); + ctx.restore(); + } else { + const panelWidth = Math.min(380, width - 24); + const panelHeight = 150; + const x = width / 2 - panelWidth / 2; + const y = height * 0.24; + ctx.fillStyle = "rgba(3,6,12,0.88)"; + ctx.fillRect(x, y, panelWidth, panelHeight); + ctx.strokeStyle = "rgba(246,213,122,0.5)"; + ctx.lineWidth = 2; + ctx.strokeRect(x + 2, y + 2, panelWidth - 4, panelHeight - 4); + ctx.textAlign = "center"; + ctx.fillStyle = "#ffd77a"; + ctx.font = "800 30px Inter, system-ui, sans-serif"; + ctx.fillText(`COUNT ${count}`, width / 2, y + 40); + const prompt = viewer?.is_downed === true ? viewer.get_up_prompt : null; + if (prompt !== null && prompt !== undefined && viewer !== undefined) { + const inWindow = snapshot.tick >= viewer.get_up_window_start_tick && snapshot.tick <= viewer.get_up_window_end_tick; + const arrow = prompt === "get_up_left" ? "←" : "→"; + if (inWindow) { + ctx.fillStyle = "#ffe9a8"; + ctx.font = "900 64px Inter, system-ui, sans-serif"; + ctx.fillText(arrow, width / 2 - 90, y + 106); + ctx.fillStyle = "#7dffa8"; + ctx.font = "900 34px Inter, system-ui, sans-serif"; + ctx.fillText("NOW!", width / 2 + 62, y + 100); + } else { + ctx.fillStyle = "#8fa3c8"; + ctx.font = "800 30px Inter, system-ui, sans-serif"; + ctx.fillText(`GET READY ${arrow}`, width / 2, y + 98); + } + const meterWidth = panelWidth - 60; + const ratio = Math.max(0, Math.min(1, viewer.get_up_meter / Math.max(1, viewer.get_up_required))); + ctx.fillStyle = "rgba(2,4,9,0.9)"; + ctx.fillRect(x + 30, y + 120, meterWidth, 16); + const meterFill = ctx.createLinearGradient(x + 30, 0, x + 30 + meterWidth, 0); + meterFill.addColorStop(0, "#7dffa8"); + meterFill.addColorStop(1, "#2ea860"); + ctx.fillStyle = meterFill; + ctx.fillRect(x + 30, y + 120, meterWidth * ratio, 16); + ctx.strokeStyle = "rgba(210,220,235,0.5)"; + ctx.lineWidth = 1; + ctx.strokeRect(x + 29.5, y + 119.5, meterWidth + 1, 17); } else { - ctx.fillStyle = "#8fa3c8"; - ctx.font = "800 30px Inter, system-ui, sans-serif"; - ctx.fillText(`GET READY ${arrow}`, width / 2, y + 98); + ctx.fillStyle = "#c8d3e6"; + ctx.font = "600 14px Inter, system-ui, sans-serif"; + ctx.fillText("Waiting for your rhythm instruction…", width / 2, y + 100); } - const meterWidth = panelWidth - 60; - const ratio = Math.max(0, Math.min(1, viewer.get_up_meter / Math.max(1, viewer.get_up_required))); - ctx.fillStyle = "rgba(2,4,9,0.9)"; - ctx.fillRect(x + 30, y + 120, meterWidth, 16); - const meterFill = ctx.createLinearGradient(x + 30, 0, x + 30 + meterWidth, 0); - meterFill.addColorStop(0, "#7dffa8"); - meterFill.addColorStop(1, "#2ea860"); - ctx.fillStyle = meterFill; - ctx.fillRect(x + 30, y + 120, meterWidth * ratio, 16); - ctx.strokeStyle = "rgba(210,220,235,0.5)"; - ctx.lineWidth = 1; - ctx.strokeRect(x + 29.5, y + 119.5, meterWidth + 1, 17); - } else { - ctx.fillStyle = "#c8d3e6"; - ctx.font = "600 14px Inter, system-ui, sans-serif"; - ctx.fillText(downed !== undefined && downed.player_id === viewerId ? "Waiting for your rhythm instruction…" : "Waiting for the count", width / 2, y + 100); } } if (snapshot.phase === "foul_recovery") { const victim = snapshot.fighters.find((fighter) => fighter.is_foul_recovery_target); - centerPanel(ctx, width, height, "FOUL RECOVERY", `${players[victim?.player_id ?? ""]?.name ?? "Fighter"} is recovering`); + centerPanel(ctx, width, height, "FOUL RECOVERY", `${players[victim?.player_id ?? ""]?.name ?? "Fighter"} is recovering`, topPanelOffset(width, height)); } if (snapshot.phase === "rest") { - centerPanel(ctx, width, height, "CORNERS · RECOVER", "Conditioning governs recovery"); + const statsLine = snapshot.fighters + .map((fighter) => ({ name: players[fighter.player_id]?.name ?? "Fighter", stats: roundStats?.get(fighter.player_id) ?? { thrown: 0, landed: 0 } })) + .filter(({ stats }) => stats.thrown > 0 || stats.landed > 0) + .map(({ name, stats }) => `${fit(ctx, name, width * 0.22)} ${stats.landed}/${stats.thrown}`) + .join(" · "); + centerPanel(ctx, width, height, "CORNERS · RECOVER", statsLine.length > 0 ? `Landed this round: ${statsLine}` : "Conditioning governs recovery", topPanelOffset(width, height)); } if (reconnectMs > 0) { centerPanel(ctx, width, height, `OPPONENT RECONNECTING · ${Math.ceil(reconnectMs / 1000)}s`, "The bout is paused"); } - if (final !== null) drawFinal(ctx, width, height, final, players); + if (final !== null) drawFinal(ctx, width, height, final, players, snapshot.fighters.map((fighter) => ({ name: players[fighter.player_id]?.name ?? "Fighter", stats: roundStats?.total(fighter.player_id) ?? { thrown: 0, landed: 0 } }))); ctx.restore(); } -function drawFinal(ctx: CanvasRenderingContext2D, width: number, height: number, final: FinalMessage, players: Readonly>): void { +function fitted(ctx: CanvasRenderingContext2D, text: string, x: number, y: number, maxWidth: number, weight: number, maximum: number, minimum: number, family = "Inter, system-ui, sans-serif"): void { + const size = fitFontSize((candidate) => { + ctx.font = `${weight} ${candidate}px ${family}`; + return ctx.measureText(text).width; + }, maxWidth, maximum, minimum); + ctx.font = `${weight} ${size}px ${family}`; + ctx.fillText(fit(ctx, text, maxWidth), x, y); +} + +function drawFinal(ctx: CanvasRenderingContext2D, width: number, height: number, final: FinalMessage, players: Readonly>, punches: readonly { name: string; stats: RoundPunchStats }[] = []): void { ctx.fillStyle = "rgba(2,4,9,0.94)"; ctx.fillRect(width * 0.14, height * 0.13, width * 0.72, height * 0.74); ctx.strokeStyle = "rgba(246,213,122,0.5)"; ctx.lineWidth = 2; ctx.strokeRect(width * 0.14 + 4, height * 0.13 + 4, width * 0.72 - 8, height * 0.74 - 8); + const inner = width * 0.72 - 32; ctx.textAlign = "center"; ctx.fillStyle = "#f6d57a"; - ctx.font = "800 26px Inter, system-ui, sans-serif"; - ctx.fillText(final.method.replaceAll("_", " ").toUpperCase(), width / 2, height * 0.21); + fitted(ctx, decisionLabel(final), width / 2, height * 0.21, inner, 800, 26, 14); const winner = final.winner_id === null ? "DRAW" : `${players[final.winner_id]?.name ?? "Winner"} WINS`; ctx.fillStyle = "white"; - ctx.font = "700 18px Inter, system-ui, sans-serif"; - ctx.fillText(fit(ctx, winner, width * 0.6), width / 2, height * 0.27); - ctx.font = "12px ui-monospace, monospace"; + fitted(ctx, winner, width / 2, height * 0.27, inner, 700, 18, 11); + const thrown = punches.filter(({ stats }) => stats.thrown > 0); + if (thrown.length > 0) { + ctx.fillStyle = "#c8d3e6"; + ctx.font = "600 13px Inter, system-ui, sans-serif"; + const line = thrown.map(({ name, stats }) => `${fit(ctx, name, inner / thrown.length - 70)} ${stats.landed}/${stats.thrown} landed`).join(" · "); + fitted(ctx, line, width / 2, height * 0.32, inner, 600, 13, 9); + } final.scorecards.forEach((card, index) => { const y = height * 0.37 + index * 36; ctx.fillStyle = "#aebbd0"; - ctx.fillText(`${fit(ctx, card.judge, 100)} ${scoreTotal(card.player_one)} — ${scoreTotal(card.player_two)} [${card.player_one.join("·")}] [${card.player_two.join("·")}]`, width / 2, y); + fitted(ctx, `${card.judge} ${scoreTotal(card.player_one)} — ${scoreTotal(card.player_two)} [${card.player_one.join("·")}] [${card.player_two.join("·")}]`, width / 2, y, inner, 400, 12, 8, "ui-monospace, monospace"); }); const ratings = Object.entries(final.ratings); - ctx.font = "600 13px Inter, system-ui, sans-serif"; ratings.forEach(([id, rating], index) => { ctx.fillStyle = rating.after >= rating.before ? "#55df9b" : "#ff7b74"; - ctx.fillText(`${fit(ctx, players[id]?.name ?? "Fighter", 100)} ${rating.before} → ${rating.after} (${rating.after - rating.before >= 0 ? "+" : ""}${rating.after - rating.before})`, width / 2, height * 0.61 + index * 27); + const change = `${rating.before} → ${rating.after} (${rating.after - rating.before >= 0 ? "+" : ""}${rating.after - rating.before})`; + fitted(ctx, `${players[id]?.name ?? "Fighter"} ${change}`, width / 2, height * 0.61 + index * 27, inner, 600, 13, 9); }); } diff --git a/web/hands/src/render/injury.ts b/web/hands/src/render/injury.ts new file mode 100644 index 00000000..d8782bf5 --- /dev/null +++ b/web/hands/src/render/injury.ts @@ -0,0 +1,321 @@ +import * as THREE from "three"; +import type { BloodLevel } from "../settings"; +import type { TraumaSnapshot } from "../types"; + +/** + * Object-space injury shading for the Texel Boxer skin materials. + * + * The source textures are a fragmented photogrammetry atlas, so damage is not + * painted in UV space. Instead each material gets a fixed set of anatomical + * sites in the mesh's bind space (centimetres). The vertex shader swells + * tissue around bruised sites and can shear the jaw; the fragment shader + * blends hematoma discolouration, cuts, and gravity-fed blood streaks into the + * albedo and wets the surface where blood sits. + */ + +export const INJURY_SITE_COUNT = 12; + +export interface InjurySite { + readonly name: string; + readonly position: readonly [number, number, number]; + readonly radius: number; + /** Cut segment half-length along local x; zero means the site never cuts. */ + readonly cutHalfLength: number; + /** Whether blood can stream downward from this site. */ + readonly bleeds: boolean; +} + +export const HEAD_SITES: readonly InjurySite[] = [ + { name: "leftEye", position: [2.4, 120.0, 3.4], radius: 3.4, cutHalfLength: 0, bleeds: false }, + { name: "rightEye", position: [-2.8, 120.1, 3.2], radius: 3.4, cutHalfLength: 0, bleeds: false }, + { name: "leftBrow", position: [2.9, 123.4, 3.0], radius: 2.2, cutHalfLength: 1.1, bleeds: true }, + { name: "rightBrow", position: [-2.7, 123.0, 3.3], radius: 2.2, cutHalfLength: 1.1, bleeds: true }, + { name: "nose", position: [0, 117.0, 5.3], radius: 1.6, cutHalfLength: 0, bleeds: true }, + { name: "mouth", position: [0, 114.3, 4.6], radius: 1.8, cutHalfLength: 0.9, bleeds: true }, + { name: "leftCheek", position: [3.4, 117.8, 3.4], radius: 3.0, cutHalfLength: 0.8, bleeds: true }, + { name: "rightCheek", position: [-3.4, 117.9, 3.3], radius: 3.0, cutHalfLength: 0.8, bleeds: true }, + { name: "chin", position: [0, 110.8, 4.2], radius: 2.2, cutHalfLength: 0, bleeds: false }, + { name: "leftJaw", position: [4.6, 113.0, 1.4], radius: 2.6, cutHalfLength: 0, bleeds: false }, + { name: "rightJaw", position: [-4.6, 113.0, 1.4], radius: 2.6, cutHalfLength: 0, bleeds: false }, + { name: "forehead", position: [0, 125.5, 3.5], radius: 3.2, cutHalfLength: 1.3, bleeds: true }, +]; + +export const BODY_SITES: readonly InjurySite[] = [ + { name: "leftRibs", position: [13.5, 98.0, 1.0], radius: 7.5, cutHalfLength: 0, bleeds: false }, + { name: "rightRibs", position: [-13.5, 98.0, 1.0], radius: 7.5, cutHalfLength: 0, bleeds: false }, + { name: "solarPlexus", position: [0.5, 96.5, 5.5], radius: 6.0, cutHalfLength: 0, bleeds: false }, + { name: "leftPec", position: [9.0, 96.2, 4.4], radius: 6.0, cutHalfLength: 0, bleeds: false }, + { name: "rightPec", position: [-8.8, 96.2, 4.4], radius: 6.0, cutHalfLength: 0, bleeds: false }, + { name: "neckSmear", position: [0.4, 105.5, 5.8], radius: 4.0, cutHalfLength: 0, bleeds: true }, + { name: "leftShoulderSmear", position: [10.5, 104.0, 4.5], radius: 3.0, cutHalfLength: 0, bleeds: true }, + { name: "rightShoulderSmear", position: [-10.5, 104.0, 4.5], radius: 3.0, cutHalfLength: 0, bleeds: true }, + { name: "unused0", position: [0, -100, 0], radius: 0, cutHalfLength: 0, bleeds: false }, + { name: "unused1", position: [0, -100, 0], radius: 0, cutHalfLength: 0, bleeds: false }, + { name: "unused2", position: [0, -100, 0], radius: 0, cutHalfLength: 0, bleeds: false }, + { name: "unused3", position: [0, -100, 0], radius: 0, cutHalfLength: 0, bleeds: false }, +]; + +export interface InjuryLevels { + readonly bruise: Float32Array; + readonly swell: Float32Array; + readonly cut: Float32Array; + readonly blood: Float32Array; +} + +const VERTEX_DECLARATIONS = /* glsl */ ` +uniform vec4 uInjurySite[${INJURY_SITE_COUNT}]; +uniform float uInjurySwell[${INJURY_SITE_COUNT}]; +uniform float uInjuryJaw; +uniform float uInjuryJawLevel; +uniform vec4 uInjuryImpact; +uniform vec3 uInjuryImpactPush; +uniform vec4 uInjuryNose; +varying vec3 vInjuryPos; +`; + +const VERTEX_BODY = /* glsl */ ` +vInjuryPos = transformed; +{ + float injurySwell = 0.0; + for (int i = 0; i < ${INJURY_SITE_COUNT}; i++) { + float radius = uInjurySite[i].w; + if (radius <= 0.0) continue; + float d = distance(transformed, uInjurySite[i].xyz); + float w = 1.0 - smoothstep(0.0, radius * 1.15, d); + injurySwell += uInjurySwell[i] * w * w; + } + transformed += objectNormal * injurySwell; + float noseWeight = 1.0 - smoothstep(0.0, 2.6, distance(transformed, uInjuryNose.xyz)); + transformed.x += uInjuryNose.w * 1.1 * noseWeight * noseWeight; + transformed.z -= abs(uInjuryNose.w) * 0.5 * noseWeight * noseWeight; + float impactDistance = distance(transformed, uInjuryImpact.xyz); + float impactWeight = 1.0 - smoothstep(0.0, max(uInjuryImpact.w, 0.001), impactDistance); + transformed += uInjuryImpactPush * (impactWeight * impactWeight); + // Only the mandible: the mask fades out again under the chin, above the throat and the seam with the body. + float jawMask = (1.0 - smoothstep(uInjuryJawLevel - 2.5, uInjuryJawLevel + 1.5, transformed.y)) + * smoothstep(uInjuryJawLevel - 6.0, uInjuryJawLevel - 4.0, transformed.y) + * smoothstep(-6.0, 0.0, transformed.z); + transformed.x += uInjuryJaw * 1.7 * jawMask; + transformed.y -= uInjuryJaw * 0.9 * jawMask; + transformed.z -= uInjuryJaw * 0.4 * jawMask; +} +`; + +const FRAGMENT_DECLARATIONS = /* glsl */ ` +uniform vec4 uInjurySite[${INJURY_SITE_COUNT}]; +uniform vec4 uInjuryCut[${INJURY_SITE_COUNT}]; +uniform float uInjuryBruise[${INJURY_SITE_COUNT}]; +uniform float uInjuryBlood[${INJURY_SITE_COUNT}]; +uniform float uInjuryWetness; +varying vec3 vInjuryPos; +float injuryWet = 0.0; + +float injuryHash(float n) { return fract(sin(n) * 43758.5453123); } +`; + +const FRAGMENT_BODY = /* glsl */ ` +{ + vec3 injuryPos = vInjuryPos; + vec3 hematomaFresh = vec3(0.31, 0.05, 0.08); + vec3 hematomaDeep = vec3(0.12, 0.035, 0.13); + vec3 bloodColor = vec3(0.30, 0.008, 0.012); + vec3 cutColor = vec3(0.13, 0.004, 0.005); + for (int i = 0; i < ${INJURY_SITE_COUNT}; i++) { + float radius = uInjurySite[i].w; + if (radius <= 0.0) continue; + vec3 site = uInjurySite[i].xyz; + float d = distance(injuryPos, site); + float bruise = uInjuryBruise[i]; + if (bruise > 0.001) { + float mottle = 0.92 + 0.08 * sin(injuryPos.x * 3.1 + injuryPos.y * 2.3) * sin(injuryPos.z * 2.7 - injuryPos.y * 1.9); + float w = (1.0 - smoothstep(radius * 0.2, radius, d)) * mottle; + vec3 tone = mix(hematomaFresh, hematomaDeep, clamp(bruise * 1.2 - 0.2, 0.0, 1.0)); + vec3 stained = mix(diffuseColor.rgb * tone * 2.0, tone * 1.1, 0.35); + diffuseColor.rgb = mix(diffuseColor.rgb, stained, clamp(bruise, 0.0, 1.0) * w * 0.8); + } + float cut = uInjuryCut[i].y; + float halfLength = uInjuryCut[i].x; + if (cut > 0.001 && halfLength > 0.0) { + vec3 local = injuryPos - site; + float along = clamp(local.x, -halfLength, halfLength); + vec2 delta = vec2(local.x - along, local.y - 0.18 * sin(local.x * 3.0)); + float slit = length(delta) + abs(local.z) * 0.25; + float w = 1.0 - smoothstep(0.06 + cut * 0.06, 0.24 + cut * 0.12, slit); + float lip = (1.0 - smoothstep(0.24, 0.55, slit)) * 0.6; + diffuseColor.rgb = mix(diffuseColor.rgb, hematomaFresh * 0.8, cut * lip); + diffuseColor.rgb = mix(diffuseColor.rgb, cutColor, cut * w); + injuryWet = max(injuryWet, cut * w); + } + float blood = uInjuryBlood[i]; + if (blood > 0.001) { + vec3 origin = site + vec3(0.0, -radius * 0.35, 0.0); + float length = 3.5 + blood * 9.0; + float drop = origin.y - injuryPos.y; + if (drop > -0.4 && drop < length && injuryPos.z > origin.z - 3.2) { + float t = clamp(drop / length, 0.0, 1.0); + float wander = 0.4 * sin(injuryPos.y * 1.6 + float(i) * 1.7) + 0.25 * sin(injuryPos.y * 4.3 + float(i)); + float dx = abs(injuryPos.x - origin.x - wander * t); + float width = 0.28 + 0.28 * t + 0.25 * blood; + float edge = width + 0.18; + float stream = (1.0 - smoothstep(width * 0.6, edge, dx)) * (1.0 - t * t) * smoothstep(-0.4, 0.15, drop); + float head = (1.0 - smoothstep(0.0, radius * 0.9, distance(injuryPos, origin))) * 0.7; + float w = clamp(max(stream, head) * min(1.0, blood * 1.4), 0.0, 1.0); + diffuseColor.rgb = mix(diffuseColor.rgb, bloodColor, w * 0.96); + injuryWet = max(injuryWet, w); + } + } + } + injuryWet *= uInjuryWetness; +} +`; + +const ROUGHNESS_BODY = /* glsl */ ` +roughnessFactor = mix(roughnessFactor, 0.18, injuryWet); +`; + +const IMPACT_RELEASE_RATE = 9; + +export class InjuryShading { + readonly uniforms = { + uInjurySite: { value: [] as THREE.Vector4[] }, + uInjuryCut: { value: [] as THREE.Vector4[] }, + uInjurySwell: { value: new Float32Array(INJURY_SITE_COUNT) }, + uInjuryBruise: { value: new Float32Array(INJURY_SITE_COUNT) }, + uInjuryBlood: { value: new Float32Array(INJURY_SITE_COUNT) }, + uInjuryJaw: { value: 0 }, + uInjuryJawLevel: { value: 114.5 }, + uInjuryImpact: { value: new THREE.Vector4(0, -1000, 0, 1) }, + uInjuryImpactPush: { value: new THREE.Vector3() }, + uInjuryNose: { value: new THREE.Vector4(0, -1000, 0, 0) }, + uInjuryWetness: { value: 1 }, + }; + private readonly index = new Map(); + + /** With no material the state is kept but shades nothing: an official, who never takes damage. */ + constructor(readonly material: THREE.MeshStandardMaterial | null, readonly sites: readonly InjurySite[]) { + if (sites.length !== INJURY_SITE_COUNT) throw new Error(`injury shading requires ${INJURY_SITE_COUNT} sites`); + for (const [index, site] of sites.entries()) { + this.index.set(site.name, index); + this.uniforms.uInjurySite.value.push(new THREE.Vector4(site.position[0], site.position[1], site.position[2], site.radius)); + this.uniforms.uInjuryCut.value.push(new THREE.Vector4(site.cutHalfLength, 0, 0, 0)); + } + if (material === null) return; + const uniforms = this.uniforms; + material.onBeforeCompile = (shader) => { + Object.assign(shader.uniforms, uniforms); + shader.vertexShader = shader.vertexShader + .replace("#include ", `#include \n${VERTEX_DECLARATIONS}`) + .replace("#include ", `#include \n${VERTEX_BODY}`); + shader.fragmentShader = shader.fragmentShader + .replace("#include ", `#include \n${FRAGMENT_DECLARATIONS}`) + .replace("#include ", `#include \n${FRAGMENT_BODY}`) + .replace("#include ", `#include \n${ROUGHNESS_BODY}`); + }; + material.customProgramCacheKey = () => `hands-injury-${INJURY_SITE_COUNT}`; + material.needsUpdate = true; + } + + private slot(name: string): number { + const index = this.index.get(name); + if (index === undefined) throw new Error(`unknown injury site ${name}`); + return index; + } + + set(name: string, levels: { bruise?: number; swell?: number; cut?: number; blood?: number }): void { + const index = this.slot(name); + if (levels.bruise !== undefined) this.uniforms.uInjuryBruise.value[index] = THREE.MathUtils.clamp(levels.bruise, 0, 1.2); + if (levels.swell !== undefined) this.uniforms.uInjurySwell.value[index] = THREE.MathUtils.clamp(levels.swell, 0, 2.2); + if (levels.cut !== undefined) this.uniforms.uInjuryCut.value[index]!.y = THREE.MathUtils.clamp(levels.cut, 0, 1); + if (levels.blood !== undefined) this.uniforms.uInjuryBlood.value[index] = THREE.MathUtils.clamp(levels.blood, 0, 1.4); + } + + /** Dents the surface around a site along `push` (object-space centimetres); released by update(). */ + impact(name: string, push: readonly [number, number, number], radius: number): void { + const site = this.uniforms.uInjurySite.value[this.slot(name)]!; + this.uniforms.uInjuryImpact.value.set(site.x, site.y, site.z, radius); + this.uniforms.uInjuryImpactPush.value.set(push[0], push[1], push[2]); + } + + /** Persistent sideways shift of the nose (object-space centimetres) once the bridge has gone. */ + setNoseShift(shift: number): void { + const index = this.index.get("nose"); + if (index === undefined) return; + const site = this.uniforms.uInjurySite.value[index]!; + this.uniforms.uInjuryNose.value.set(site.x, site.y, site.z, THREE.MathUtils.clamp(shift, -1.4, 1.4) || 0); + } + + update(dt: number): void { + const push = this.uniforms.uInjuryImpactPush.value; + if (push.lengthSq() < 1e-6) return; + push.multiplyScalar(Math.exp(-IMPACT_RELEASE_RATE * dt)); + if (push.lengthSq() < 1e-4) push.set(0, 0, 0); + } + + get impactDepth(): number { + return this.uniforms.uInjuryImpactPush.value.length(); + } + + setJaw(amount: number): void { + this.uniforms.uInjuryJaw.value = THREE.MathUtils.clamp(amount, 0, 1); + } + + clear(): void { + this.uniforms.uInjuryBruise.value.fill(0); + this.uniforms.uInjurySwell.value.fill(0); + this.uniforms.uInjuryBlood.value.fill(0); + for (const cut of this.uniforms.uInjuryCut.value) cut.y = 0; + this.uniforms.uInjuryJaw.value = 0; + } + + level(name: string): { bruise: number; swell: number; cut: number; blood: number } { + const index = this.slot(name); + return { + bruise: this.uniforms.uInjuryBruise.value[index]!, + swell: this.uniforms.uInjurySwell.value[index]!, + cut: this.uniforms.uInjuryCut.value[index]!.y, + blood: this.uniforms.uInjuryBlood.value[index]!, + }; + } +} + +const bloodScale = (blood: BloodLevel): number => (blood === "off" ? 0 : blood === "reduced" ? 0.35 : 1); + +/** Maps authoritative trauma onto head injury sites. */ +export function applyHeadTrauma(shading: InjuryShading, trauma: TraumaSnapshot, blood: BloodLevel): void { + const bleed = bloodScale(blood); + const graphic = blood === "full" ? 1 : 0.6; + const eye = (value: number): number => Math.min(1.2, value / 380 + trauma.swelling / 900); + const swell = (value: number): number => Math.min(2.2, (value / 520 + trauma.swelling / 700) * 1.6 * graphic); + shading.set("leftEye", { bruise: eye(trauma.left_eye), swell: swell(trauma.left_eye) }); + shading.set("rightEye", { bruise: eye(trauma.right_eye), swell: swell(trauma.right_eye) }); + const browCut = (cut: number): number => Math.min(1, cut / 220); + const browBlood = (cut: number): number => Math.min(1.4, (cut / 260 + trauma.bleeding / 520) * bleed); + shading.set("leftBrow", { bruise: Math.min(1, trauma.left_eye / 700), swell: Math.min(1.2, trauma.left_eye / 900) * graphic, cut: browCut(trauma.left_cut), blood: browBlood(trauma.left_cut) }); + shading.set("rightBrow", { bruise: Math.min(1, trauma.right_eye / 700), swell: Math.min(1.2, trauma.right_eye / 900) * graphic, cut: browCut(trauma.right_cut), blood: browBlood(trauma.right_cut) }); + const cheek = Math.min(1, trauma.head / 950 + trauma.swelling / 1100); + shading.set("leftCheek", { bruise: cheek * 0.9, swell: Math.min(1.4, trauma.swelling / 800) * graphic, cut: Math.min(1, Math.max(0, trauma.left_cut - 350) / 500), blood: Math.min(1, Math.max(0, trauma.left_cut - 350) / 400) * bleed }); + shading.set("rightCheek", { bruise: cheek * 0.85, swell: Math.min(1.4, trauma.swelling / 800) * graphic, cut: Math.min(1, Math.max(0, trauma.right_cut - 350) / 500), blood: Math.min(1, Math.max(0, trauma.right_cut - 350) / 400) * bleed }); + shading.set("nose", { bruise: Math.min(1, trauma.head / 800), swell: Math.min(0.8, trauma.head / 1400) * graphic, blood: Math.min(1.4, (Math.max(0, trauma.head - 160) / 520 + trauma.bleeding / 420) * bleed) }); + shading.set("mouth", { bruise: Math.min(0.8, trauma.head / 1100), cut: Math.min(1, Math.max(0, trauma.head - 420) / 700), blood: Math.min(1.2, (Math.max(0, trauma.head - 280) / 650 + trauma.bleeding / 500) * bleed) }); + shading.set("chin", { bruise: Math.min(0.7, trauma.head / 1300) }); + const noseSide = trauma.left_eye >= trauma.right_eye ? -1 : 1; + shading.setNoseShift(noseSide * Math.min(1.1, Math.max(0, trauma.head - 520) / 450) * graphic); + shading.set("leftJaw", { bruise: Math.min(0.9, trauma.left_eye / 900 + trauma.head / 1600) }); + shading.set("rightJaw", { bruise: Math.min(0.9, trauma.right_eye / 900 + trauma.head / 1600) }); + shading.set("forehead", { bruise: Math.min(0.6, trauma.swelling / 1200), cut: Math.min(1, Math.max(0, trauma.swelling - 520) / 480), blood: Math.min(1.2, Math.max(0, trauma.swelling - 520) / 420) * bleed }); +} + +/** Maps authoritative trauma onto torso injury sites. Head bleeding smears down the neck and chest. */ +export function applyBodyTrauma(shading: InjuryShading, trauma: TraumaSnapshot, blood: BloodLevel): void { + const bleed = bloodScale(blood); + const ribs = Math.min(1.1, trauma.body / 620); + shading.set("leftRibs", { bruise: ribs, swell: Math.min(1, trauma.body / 1300) }); + shading.set("rightRibs", { bruise: ribs * 0.9, swell: Math.min(1, trauma.body / 1400) }); + shading.set("solarPlexus", { bruise: Math.min(1, trauma.body / 800) }); + shading.set("leftPec", { bruise: Math.min(0.8, trauma.body / 1100) }); + shading.set("rightPec", { bruise: Math.min(0.8, trauma.body / 1150) }); + const smear = Math.min(1.4, (trauma.bleeding / 380 + (trauma.left_cut + trauma.right_cut) / 900) * bleed); + shading.set("neckSmear", { blood: smear }); + shading.set("leftShoulderSmear", { blood: Math.min(1, trauma.left_cut / 600) * bleed }); + shading.set("rightShoulderSmear", { blood: Math.min(1, trauma.right_cut / 600) * bleed }); +} diff --git a/web/hands/src/render/officials.test.ts b/web/hands/src/render/officials.test.ts new file mode 100644 index 00000000..1a436b54 --- /dev/null +++ b/web/hands/src/render/officials.test.ts @@ -0,0 +1,175 @@ +import * as THREE from "three"; +import { fighter as baseFighter, snapshot as baseSnapshot } from "../test/fixtures"; +import type { EngineSnapshot, FighterSnapshot } from "../types"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb } from "./graph"; +import { FightRenderer, refereeSpacing } from "./renderer"; +import { applyHeadTrauma } from "./injury"; +import { worldPosition } from "./rig"; +import { worldMapping } from "./world"; + +const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); +const gltf = await loadBoxerGlb(); + +const official = (): SkinnedBoxer => new SkinnedBoxer(gltf, { skin: 0xc79b76, gear: 0x3b57b8, pants: 0x14161c, bodyMap: new THREE.Texture() }); + +/** Skinned world positions of a boxer's mesh vertices, optionally only those bound mostly to bones matching `bones`. */ +function surface(boxer: SkinnedBoxer, meshes: RegExp, bones?: RegExp): THREE.Vector3[] { + boxer.root.updateMatrixWorld(true); + const out: THREE.Vector3[] = []; + boxer.root.traverse((object) => { + if (!(object instanceof THREE.SkinnedMesh) || !meshes.test(object.name)) return; + const skinIndex = object.geometry.getAttribute("skinIndex"); + const skinWeight = object.geometry.getAttribute("skinWeight"); + for (let index = 0; index < object.geometry.getAttribute("position").count; index += 1) { + if (bones !== undefined) { + let strongest = 0; + for (let slot = 1; slot < 4; slot += 1) if (skinWeight.getComponent(index, slot) > skinWeight.getComponent(index, strongest)) strongest = slot; + if (!bones.test(object.skeleton.bones[skinIndex.getComponent(index, strongest)]!.name)) continue; + } + out.push(object.getVertexPosition(index, new THREE.Vector3()).applyMatrix4(object.matrixWorld)); + } + }); + return out; +} + +const closest = (from: readonly THREE.Vector3[], to: readonly THREE.Vector3[]): number => { + let best = Infinity; + for (const a of from) for (const b of to) best = Math.min(best, a.distanceToSquared(b)); + return Math.sqrt(best); +}; + +describe("referee clinch break", () => { + const updateReferee = (FightRenderer.prototype as unknown as { updateReferee: (dt: number, time: number, snapshot: EngineSnapshot | null, sampledTick: number) => void }).updateReferee; + + it.each([["behind the fighters", -Math.PI / 2], ["almost in line with them", -0.3], ["in front of them", 0.9]])("steps in from %s and puts a palm on each fighter's chest", (_from, angle) => { + const referee = official(); + const graph = new BoxingGraph(referee, mapping, { referee: true }); + const blue = new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }); + const red = new SkinnedBoxer(gltf, { skin: 0x6e4128, gear: 0xb91c1c }); + const blueGraph = new BoxingGraph(blue, mapping); + const redGraph = new BoxingGraph(red, mapping); + // The renderer's referee state, driven through its own placement code. + const renderer = { + referee: graph, mapping, tmpA: new THREE.Vector3(), tmpB: new THREE.Vector3(), + refereePosition: new THREE.Vector3(Math.cos(angle) * 2, 0, Math.sin(angle) * 2), refereeAway: new THREE.Vector3(), refereeVelocity: new THREE.Vector3(), refereeYaw: 0, + }; + let tick = 0; + const step = (one: FighterSnapshot, two: FighterSnapshot): void => { + tick += 0.5; + renderer.tmpA.set(mapping.x(one.x), 0, mapping.z(one.y)); + renderer.tmpB.set(mapping.x(two.x), 0, mapping.z(two.y)); + blueGraph.update(one, two, 1 / 60, tick / 30, false, "full", tick); + redGraph.update(two, one, 1 / 60, tick / 30, false, "full", tick); + updateReferee.call(renderer, 1 / 60, tick / 30, { ...baseSnapshot(Math.ceil(tick)), fighters: [one, two] }, tick); + }; + // Tied up at the hold distance, then the engine's break pushes them apart and the referee_break event arrives. + const heldBlue: FighterSnapshot = { ...baseFighter("one"), x: -30, y: 0, facing_x: 1000, facing_y: 0, clinch_ticks: 30 }; + const heldRed: FighterSnapshot = { ...baseFighter("two"), x: 30, y: 0, facing_x: -1000, facing_y: 0, clinch_ticks: 30 }; + for (let frame = 0; frame < 120; frame += 1) step(heldBlue, heldRed); + graph.breakClinch(); + for (let frame = 0; frame < 4; frame += 1) step(heldBlue, heldRed); + for (let frame = 0; frame < 50; frame += 1) step({ ...heldBlue, x: -75, clinch_ticks: 0 }, { ...heldRed, x: 75, clinch_ticks: 0 }); + + expect(Math.hypot(renderer.refereePosition.x, renderer.refereePosition.z)).toBeLessThan(0.55); + const gloves = { left: surface(referee, /^BoxerGloveLeft$/), right: surface(referee, /^BoxerGloveRight$/) }; + const reaches: Record<"left" | "right", number>[] = []; + for (const fighter of [blue, red]) { + const chest = surface(fighter, /^BoxerBody$/, /^(Spine|Hips|Neck)/); + reaches.push({ left: closest(gloves.left, chest), right: closest(gloves.right, chest) }); + // On the chest, not buried in it. + const centre = worldPosition(fighter.rig.bones.upperChest, new THREE.Vector3()).setY(0); + for (const side of ["gloveL", "gloveR"] as const) expect(worldPosition(referee.rig.bones[side], new THREE.Vector3()).setY(0).distanceTo(centre)).toBeGreaterThan(0.22); + } + // One palm on each fighter. + const [first, second] = reaches as [Record<"left" | "right", number>, Record<"left" | "right", number>]; + expect(Math.min(Math.max(first.left, second.right), Math.max(first.right, second.left))).toBeLessThan(0.03); + }); + + it("only comes in that close to break a clinch, and a count still comes first", () => { + expect(refereeSpacing(false, true, true).standoff).toBeLessThan(0.5); + expect(refereeSpacing(false, true, true).standoff).toBeLessThan(refereeSpacing(false, true).standoff); + expect(refereeSpacing(true, false, true)).toEqual(refereeSpacing(true, false)); + }); +}); + +describe("referee count", () => { + it("chops the counting arm down onto each number as it changes", () => { + const referee = official(); + const graph = new BoxingGraph(referee, mapping, { referee: true }); + const self: FighterSnapshot = { ...baseFighter("referee"), x: 0, y: 160, facing_x: 0, facing_y: -1000 }; + const focus: FighterSnapshot = { ...baseFighter("focus"), x: 0, y: -140 }; + // Knocked down on tick 308: the engine counts a number every 30 ticks after that, and the numbers + // change a quarter of a second past each whole second of the clock (where a free-running beat sits high). + const knockdownTick = 308; + const heights: number[] = []; + const changes: number[] = []; + let renderTick = 280; + let shown = -1; + for (let frame = 0; frame < 330; frame += 1) { + renderTick += 0.5; + const presentedTick = Math.ceil(renderTick); + const counting = presentedTick >= knockdownTick; + const count = counting ? Math.floor((presentedTick - knockdownTick) / 30) : 0; + if (counting && count !== shown) { + if (shown >= 0) changes.push(frame); + shown = count; + } + graph.setRefereeCount(counting, count); + graph.update(self, focus, 1 / 60, renderTick / 30, false, "off", renderTick); + referee.root.updateMatrixWorld(true); + heights.push(worldPosition(referee.rig.bones.gloveR, new THREE.Vector3()).y); + } + expect(changes.length).toBeGreaterThanOrEqual(4); + for (const change of changes) { + const around = heights.slice(change - 20, change + 21); + // At its lowest as the number changes, having come down hard into it. + expect(heights[change]!).toBeLessThan(Math.min(...around) + 0.005); + expect(heights[change - 6]! - heights[change]!).toBeGreaterThan(0.05); + } + }); +}); + +describe("officials' materials", () => { + const meshes = (boxer: SkinnedBoxer): THREE.SkinnedMesh[] => { + const out: THREE.SkinnedMesh[] = []; + boxer.root.traverse((object) => { + if (object instanceof THREE.SkinnedMesh) out.push(object); + }); + return out; + }; + const materialOf = (mesh: THREE.SkinnedMesh): THREE.MeshStandardMaterial => mesh.material as THREE.MeshStandardMaterial; + + it("dresses officials in plain materials that skip the injury shader, the sweat sheen and the shadow pass", () => { + const fighter = new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }); + const referee = official(); + // Fighters keep the clearcoated, injury-shaded skin and cast shadows. + expect(fighter.headMesh.material).toBeInstanceOf(THREE.MeshPhysicalMaterial); + expect(materialOf(fighter.headMesh).customProgramCacheKey()).toContain("hands-injury"); + for (const mesh of meshes(fighter)) expect(mesh.castShadow).toBe(true); + for (const mesh of meshes(referee)) { + expect(mesh.material).toBeInstanceOf(THREE.MeshStandardMaterial); + expect(mesh.material).not.toBeInstanceOf(THREE.MeshPhysicalMaterial); + expect(materialOf(mesh).customProgramCacheKey()).not.toContain("hands-injury"); + expect(mesh.castShadow).toBe(false); + } + // An official never takes damage, but the graph can still hand him trauma. + expect(() => applyHeadTrauma(referee.headInjury, { ...baseFighter("one").trauma, head: 900, left_cut: 600 }, "full")).not.toThrow(); + + // A tired fighter's skin takes on a sweaty sheen; the officials' skin and shirts stay matte. + const tired: FighterSnapshot = { ...baseFighter("one"), stamina: 100 }; + new BoxingGraph(fighter, mapping).update(tired, baseFighter("two"), 1 / 60, 0, false, "full", 1); + new BoxingGraph(referee, mapping, { referee: true }).update(tired, baseFighter("two"), 1 / 60, 0, false, "off", 1); + expect((fighter.headMesh.material as THREE.MeshPhysicalMaterial).clearcoat).toBeGreaterThan(0.5); + for (const mesh of meshes(referee)) expect("clearcoat" in mesh.material ? mesh.material.clearcoat : 0).toBe(0); + }); + + it("still frees every material an official owns", () => { + const referee = official(); + const materials = new Set(meshes(referee).map(materialOf)); + const freed = new Set(); + for (const material of materials) material.addEventListener("dispose", () => freed.add(material)); + referee.dispose(); + expect(materials.size).toBe(5); + expect(freed).toEqual(materials); + }); +}); diff --git a/web/hands/src/render/poser.test.ts b/web/hands/src/render/poser.test.ts new file mode 100644 index 00000000..2ea5e085 --- /dev/null +++ b/web/hands/src/render/poser.test.ts @@ -0,0 +1,1126 @@ +import * as THREE from "three"; +import { punchTiming } from "../manifest"; +import { fighter as baseFighter } from "../test/fixtures"; +import type { FighterSnapshot } from "../types"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb, remapPunchAge } from "./graph"; +import { applyHeadTrauma } from "./injury"; +import { STANCE } from "./poser"; +import { worldPosition, worldQuaternion, type CanonicalBone } from "./rig"; +import { worldMapping } from "./world"; + +const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); +const gltf = await loadBoxerGlb(); + +const facingOpponent = (fighter: FighterSnapshot): FighterSnapshot => ({ ...fighter, facing_x: 0, facing_y: -1000, x: 0, y: 0 }); +const opponentFor = (id: string): FighterSnapshot => ({ ...baseFighter(id), x: 0, y: -150, facing_x: 0, facing_y: 1000 }); +const bone = (boxer: SkinnedBoxer, name: CanonicalBone | string, out = new THREE.Vector3()): THREE.Vector3 => { + const found = boxer.rig.bones[name as CanonicalBone] ?? boxer.bone(name); + if (found === null || found === undefined) throw new Error(`missing bone ${name}`); + boxer.root.updateMatrixWorld(true); + return worldPosition(found, out); +}; + +const skinnedVertex = new THREE.Vector3(); +/** Height of the lowest skinned vertex, of every mesh or only those with the given material. */ +function lowestVertex(boxer: SkinnedBoxer, material?: string): number { + boxer.root.updateMatrixWorld(true); + let lowest = Infinity; + boxer.root.traverse((object) => { + if (!(object instanceof THREE.SkinnedMesh) || (material !== undefined && (object.material as THREE.Material).name !== material)) return; + const count = object.geometry.getAttribute("position").count; + for (let index = 0; index < count; index += 1) { + lowest = Math.min(lowest, object.getVertexPosition(index, skinnedVertex).applyMatrix4(object.matrixWorld).y); + } + }); + return lowest; +} + +function makeGraph(palette = { skin: 0xb0703f, gear: 0x1d4ed8 }): { boxer: SkinnedBoxer; graph: BoxingGraph } { + const boxer = new SkinnedBoxer(gltf, palette); + return { boxer, graph: new BoxingGraph(boxer, mapping) }; +} + +function run(graph: BoxingGraph, fighter: FighterSnapshot, opponent: FighterSnapshot, frames: number, head: THREE.Vector3 | undefined, startTick = 0, startTime = 0): number { + let tick = startTick; + for (let frame = 0; frame < frames; frame += 1) { + tick += 0.5; + graph.update(fighter, opponent, 1 / 60, startTime + frame / 60, false, "full", tick, head); + } + return tick; +} + +describe("rest corner", () => { + it("sits on the stool once still during rest and stands back up when the round starts", () => { + const { boxer, graph } = makeGraph(); + const fighter = { ...facingOpponent(baseFighter("one")), x: -420, y: -420 }; + const opponent = opponentFor("two"); + graph.setResting(true); + run(graph, fighter, opponent, 150, undefined); + expect(graph.stoolVisible).toBe(true); + expect(bone(boxer, "hips").y).toBeLessThan(0.62); + expect(bone(boxer, "ankleL").y).toBeLessThan(0.2); + expect(bone(boxer, "ankleR").y).toBeLessThan(0.2); + graph.setResting(false); + run(graph, fighter, opponent, 120, undefined, 75, 2.5); + expect(graph.stoolVisible).toBe(false); + expect(bone(boxer, "hips").y).toBeGreaterThan(0.72); + }); + + it("rests the seated fighter's feet on the canvas and keeps them there as he stands up", () => { + const { boxer, graph } = makeGraph(); + const fighter = { ...facingOpponent(baseFighter("one")), x: -420, y: -420 }; + const opponent = opponentFor("two"); + graph.setResting(true); + run(graph, fighter, opponent, 150, undefined); + const seated = lowestVertex(boxer, "ShoesMat0"); + expect(seated).toBeGreaterThan(-0.02); + expect(seated).toBeLessThan(0.02); + graph.setResting(false); + let lowest = Infinity; + for (let frame = 0; frame < 60; frame += 2) { + run(graph, fighter, opponent, 2, undefined, 75 + frame / 2, 2.5 + frame / 60); + lowest = Math.min(lowest, lowestVertex(boxer, "ShoesMat0")); + } + expect(lowest).toBeGreaterThan(-0.02); + }); +}); + +describe("celebration", () => { + it("raises both gloves overhead for a stoppage win and settles back afterwards", () => { + const { boxer, graph } = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + graph.celebrate(1.5); + run(graph, fighter, opponent, 60, undefined); + expect(bone(boxer, "gloveL").y).toBeGreaterThan(1.7); + expect(bone(boxer, "gloveR").y).toBeGreaterThan(1.7); + run(graph, fighter, opponent, 180, undefined, 30, 1); + expect(bone(boxer, "gloveL").y).toBeLessThan(1.55); + expect(bone(boxer, "gloveR").y).toBeLessThan(1.55); + }); +}); + +describe("fall direction", () => { + // The engine's hardest hit does about 153 damage, and the knockdown event that follows the hit carries + // the knockdown count (1-3) as its amount, so the fall must not depend on the amount at all. + const fall = (punchClass: "hook" | "uppercut" | "straight", target: "head" | "body", hand: "left" | "right", damage: number): { head: THREE.Vector3; hips: THREE.Vector3 } => { + const { boxer, graph } = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + run(graph, fighter, opponent, 10, undefined); + graph.react("hit", target, 1, punchClass, hand, damage); + graph.react("hit", target, 1, punchClass, hand, 1); + run(graph, { ...fighter, is_downed: true }, opponent, 70, undefined, 5, 10 / 60); + return { head: bone(boxer, "head"), hips: bone(boxer, "hips") }; + }; + + it("drops face down after a hook or a body shot and onto the back after an uppercut, whatever the damage", () => { + for (const [punchClass, target, faceDown] of [["hook", "head", true], ["uppercut", "head", false], ["straight", "body", true]] as const) { + for (const damage of [40, 153]) { + const { head, hips } = fall(punchClass, target, "left", damage); + expect(head.y).toBeLessThan(0.45); + expect(head.z > hips.z).toBe(faceDown); + } + } + }); + + it("falls away from the side the punch came from", () => { + expect(fall("hook", "head", "left", 90).head.x).toBeGreaterThan(fall("hook", "head", "right", 90).head.x + 0.2); + expect(fall("uppercut", "head", "left", 90).head.x).toBeGreaterThan(fall("uppercut", "head", "right", 90).head.x + 0.2); + }); +}); + +describe("broken nose", () => { + it("shifts the nose sideways only under heavy head trauma, toward the less damaged side", () => { + const { boxer } = makeGraph(); + const base = baseFighter("one").trauma; + applyHeadTrauma(boxer.headInjury, { ...base, head: 300, left_eye: 200, right_eye: 50 }, "full"); + expect(boxer.headInjury.uniforms.uInjuryNose.value.w).toBe(0); + applyHeadTrauma(boxer.headInjury, { ...base, head: 900, left_eye: 600, right_eye: 100 }, "full"); + expect(boxer.headInjury.uniforms.uInjuryNose.value.w).toBeLessThan(-0.7); + expect(boxer.headInjury.uniforms.uInjuryNose.value.y).toBeCloseTo(117, 0); + applyHeadTrauma(boxer.headInjury, { ...base, head: 900, left_eye: 100, right_eye: 600 }, "full"); + expect(boxer.headInjury.uniforms.uInjuryNose.value.w).toBeGreaterThan(0.7); + }); +}); + +describe("impact dent", () => { + it("dents the struck cheek on a hook and releases within a second", () => { + const { boxer, graph } = makeGraph(); + graph.react("hit", "head", 1, "hook", "left", 300); + expect(boxer.headInjury.uniforms.uInjuryImpact.value.x).toBeLessThan(0); + expect(boxer.headInjury.uniforms.uInjuryImpactPush.value.x).toBeGreaterThan(1); + expect(boxer.headInjury.impactDepth).toBeGreaterThan(1); + run(graph, facingOpponent(baseFighter("one")), opponentFor("two"), 60, undefined); + expect(boxer.headInjury.impactDepth).toBeLessThan(0.2); + graph.react("hit", "body", 1, "straight", "right", 260); + expect(boxer.bodyInjury.uniforms.uInjuryImpact.value.y).toBeCloseTo(96.5, 1); + expect(boxer.bodyInjury.uniforms.uInjuryImpactPush.value.z).toBeLessThan(-1); + }); + + it("presses its deepest for the hardest hit the engine deals", () => { + const { boxer, graph } = makeGraph(); + graph.react("hit", "head", 1, "straight", "right", 153); + expect(boxer.headInjury.impactDepth).toBeCloseTo(3.2, 1); + graph.react("hit", "head", 1, "straight", "right", 34); + expect(boxer.headInjury.impactDepth).toBeLessThan(1.8); + }); +}); + +/** How far a knee bends along the pelvis' forward axis (1: straight ahead of it), or null when the leg is nearly straight. */ +function kneeBend(boxer: SkinnedBoxer, side: "L" | "R"): number | null { + const hip = bone(boxer, side === "L" ? "hipL" : "hipR"); + const ankle = bone(boxer, side === "L" ? "ankleL" : "ankleR"); + const bend = bone(boxer, side === "L" ? "kneeL" : "kneeR").sub(hip); + const along = ankle.sub(hip).normalize(); + bend.addScaledVector(along, -bend.dot(along)); + if (bend.length() < 0.02) return null; + return bend.normalize().dot(new THREE.Vector3(0, 0, 1).applyQuaternion(worldQuaternion(boxer.rig.bones.hips, new THREE.Quaternion()))); +} + +describe("down and get-up poses", () => { + /** + * Knocks a fighter down with `punchClass`, fills his get-up meter in two good presses while he is down, + * then lets him up, sampling every frame. + */ + const knockdown = (punchClass: "hook" | "uppercut", stance: "orthodox" | "southpaw", sample: (boxer: SkinnedBoxer, frame: number) => void): void => { + const { boxer, graph } = makeGraph(); + const fighter = facingOpponent({ ...baseFighter("one"), stance, get_up_required: 60 }); + const opponent = opponentFor("two"); + run(graph, fighter, opponent, 20, undefined); + graph.react("hit", "head", 1, punchClass, "left", 120); + let tick = 10; + for (let frame = 0; frame < 240; frame += 1) { + tick += 0.5; + const meter = frame < 60 ? 0 : frame < 100 ? 30 : 60; + graph.update(frame < 140 ? { ...fighter, is_downed: true, get_up_meter: meter } : { ...fighter, get_up_meter: 60, stunned_ticks: 20 }, opponent, 1 / 60, 1 + frame / 60, false, "full", tick); + sample(boxer, frame); + } + }; + + it("bends the knees the way the pelvis faces, on the back, face down, on all fours and on one knee", () => { + for (const punchClass of ["hook", "uppercut"] as const) { + for (const stance of ["orthodox", "southpaw"] as const) { + let worst = Infinity; + knockdown(punchClass, stance, (boxer) => { + for (const side of ["L", "R"] as const) worst = Math.min(worst, kneeBend(boxer, side) ?? Infinity); + }); + expect(worst).toBeGreaterThan(0.3); + } + } + }); + + it("keeps the shoes out of the canvas and puts the gloves and knees on it to get up", () => { + for (const punchClass of ["hook", "uppercut"] as const) { + let lowest = Infinity; + let gloves = Infinity; + let knees = Infinity; + knockdown(punchClass, "orthodox", (boxer, frame) => { + if (frame % 3 !== 0) return; + lowest = Math.min(lowest, lowestVertex(boxer)); + if (frame < 60) return; + // Up off the canvas (the hips are high) the gloves and then the trunks' knees must still reach it. + if (bone(boxer, "hips").y > 0.42) gloves = Math.min(gloves, lowestVertex(boxer, "GlovesMat0")); + if (bone(boxer, "head").y > 0.9) knees = Math.min(knees, lowestVertex(boxer, "PantsMat0")); + }); + expect(lowest).toBeGreaterThan(-0.02); + expect(gloves).toBeLessThan(0.03); + expect(knees).toBeLessThan(0.03); + } + }); +}); + +describe("get-up", () => { + // The engine puts a fighter straight back in the fight when he beats the count: he can walk at once and + // act once a 20-tick (0.67 s) stun runs out. + const knockedDown = (): { boxer: SkinnedBoxer; step: (fighter: FighterSnapshot, frames: number) => number; standing: FighterSnapshot; downed: FighterSnapshot; guardZ: number } => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const head = new THREE.Vector3(0, 1.5, mapping.z(-150)); + const standing = facingOpponent({ ...baseFighter("one"), get_up_required: 66 }); + let tick = 0; + const step = (fighter: FighterSnapshot, frames: number): number => { + for (let frame = 0; frame < frames; frame += 1) { + tick += 0.5; + graph.update(fighter, opponent, 1 / 60, tick / 30, false, "full", tick, head); + } + return tick; + }; + step(standing, 20); + const guardZ = bone(boxer, "gloveL").z; + graph.react("hit", "head", 1, "uppercut", "right", 120); + const downed = { ...standing, is_downed: true }; + step(downed, 60); + return { boxer, step, standing, downed, guardZ }; + }; + + it("rises with the get-up meter while down, then stands inside the stun and throws at full reach", () => { + const { boxer, step, standing, downed, guardZ } = knockedDown(); + const lying = bone(boxer, "head").y; + step({ ...downed, get_up_meter: 22 }, 30); + step({ ...downed, get_up_meter: 44 }, 30); + expect(bone(boxer, "head").y).toBeGreaterThan(lying + 0.3); + const released = { ...standing, get_up_meter: 66, stunned_ticks: 20 }; + step(released, 33); + expect(bone(boxer, "head").y).toBeGreaterThan(1.4); + const startTick = step(released, 9); + const timing = punchTiming("jab", "head", "normal"); + const jab = { + ...standing, + action: "jab" as const, action_hand: "left" as const, action_target: "head" as const, action_power: "normal" as const, action_id: "after-get-up", action_key: "jab:left:head:normal", + action_start_tick: startTick, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + let reach = -Infinity; + for (let frame = 0; frame < (timing.startup + timing.active) * 2; frame += 1) { + step(jab, 1); + reach = Math.max(reach, bone(boxer, "gloveL").z); + } + expect(reach).toBeGreaterThan(guardZ + 0.25); + }); + + it("falls again from where the get-up had him when he is knocked down mid-rise", () => { + const { boxer, step, standing, downed } = knockedDown(); + step({ ...downed, get_up_meter: 22 }, 30); + step({ ...downed, get_up_meter: 44 }, 30); + step({ ...standing, get_up_meter: 66, stunned_ticks: 20 }, 8); + const names = Object.keys(boxer.rig.bones) as CanonicalBone[]; + let previous = names.map((name) => bone(boxer, name)); + expect(previous[names.indexOf("head")]!.y).toBeLessThan(1.3); + let jump = 0; + for (let frame = 0; frame < 60; frame += 1) { + step(downed, 1); + const now = names.map((name) => bone(boxer, name)); + for (const [index, position] of now.entries()) jump = Math.max(jump, position.distanceTo(previous[index]!)); + previous = now; + } + expect(jump).toBeLessThan(0.12); + expect(bone(boxer, "head").y).toBeLessThan(0.5); + }); + + it("plants the feet under him as he gets up, so they do not jump when the get-up ends", () => { + const { boxer, step, standing, downed } = knockedDown(); + step({ ...downed, get_up_meter: 22 }, 30); + step({ ...downed, get_up_meter: 44 }, 30); + // The engine turns him to face the opponent, who walked away during the count. + const turned = { ...standing, facing_x: 1000, facing_y: 0, get_up_meter: 66, stunned_ticks: 20 }; + let previous = [bone(boxer, "ankleL"), bone(boxer, "ankleR")]; + let jump = 0; + for (let frame = 0; frame < 60; frame += 1) { + step(turned, 1); + const now = [bone(boxer, "ankleL"), bone(boxer, "ankleR")]; + for (const [index, ankle] of now.entries()) jump = Math.max(jump, ankle.distanceTo(previous[index]!)); + previous = now; + } + expect(jump).toBeLessThan(0.12); + }); + + it("finishes the get-up at once when he walks off", () => { + const { boxer, step, standing, downed } = knockedDown(); + step({ ...downed, get_up_meter: 22 }, 30); + step({ ...downed, get_up_meter: 44 }, 30); + let walking = { ...standing, get_up_meter: 66, stunned_ticks: 20, velocity_y: 6 }; + for (let frame = 0; frame < 15; frame += 1) { + walking = { ...walking, y: walking.y + 3 }; + step(walking, 1); + } + expect(bone(boxer, "head").y).toBeGreaterThan(1.4); + }); +}); + +describe("falls near the ropes", () => { + // The rope line runs between the corner posts at 2.46 m from the centre; the engine lets a fighter's + // centre reach 2.82 m (pressing the ropes out). + const ropeLine = 2.46; + const skinned = new THREE.Vector3(); + const furthest = (boxer: SkinnedBoxer): number => { + boxer.root.updateMatrixWorld(true); + let reach = 0; + boxer.root.traverse((object) => { + if (!(object instanceof THREE.SkinnedMesh)) return; + const count = object.geometry.getAttribute("position").count; + for (let index = 0; index < count; index += 2) { + object.getVertexPosition(index, skinned).applyMatrix4(object.matrixWorld); + reach = Math.max(reach, Math.abs(skinned.x), Math.abs(skinned.z)); + } + }); + return reach; + }; + /** Knocks the fighter down; `reach` is where he lands, `overshoot` how far past the ropes (or his start, if out there) the fall went. */ + const fall = (fighter: FighterSnapshot, punchClass: "hook" | "uppercut"): { boxer: SkinnedBoxer; reach: number; overshoot: number } => { + const { boxer, graph } = makeGraph(); + const opponent = { ...baseFighter("two"), x: 0, y: 0 }; + run(graph, fighter, opponent, 20, undefined); + const start = furthest(boxer); + graph.react("hit", "head", 1, punchClass, "left", 120); + let widest = 0; + for (let frame = 0; frame < 70; frame += 5) { + run(graph, { ...fighter, is_downed: true }, opponent, 5, undefined, 10 + frame / 2, 1 + frame / 60); + widest = Math.max(widest, furthest(boxer)); + } + return { boxer, reach: furthest(boxer), overshoot: widest - Math.max(start, ropeLine) }; + }; + + it("keeps a fighter knocked down against the ropes inside them", () => { + // Back to the ropes and facing the centre, an uppercut would lay him under the ropes or off the apron. + for (const x of [300, 400, 462]) { + const pinned = { ...baseFighter("one"), x, y: 0, facing_x: -1000, facing_y: 0 }; + const { boxer, reach, overshoot } = fall(pinned, "uppercut"); + expect(reach).toBeLessThan(ropeLine); + expect(overshoot).toBeLessThan(0.01); + expect(bone(boxer, "head").x).toBeLessThan(bone(boxer, "hips").x); + } + // Facing the ropes, a hook would put his head through them. + expect(fall({ ...baseFighter("one"), x: 400, y: 0, facing_x: 1000, facing_y: 0 }, "hook").reach).toBeLessThan(ropeLine); + // Wedged in a corner, neither fall fits as it is. + expect(fall({ ...baseFighter("one"), x: 380, y: 380, facing_x: 1000, facing_y: -1000 }, "uppercut").reach).toBeLessThan(ropeLine); + }); +}); + +describe("body shots", () => { + // Two fighters in lockstep, one hit and one not (or hit differently), so the idle sway cancels out. + const pair = (react: (graph: BoxingGraph) => void, other: (graph: BoxingGraph) => void, sample: (boxer: SkinnedBoxer) => number[]): number[][] => { + const hit = makeGraph(); + const reference = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + run(hit.graph, fighter, opponent, 30, undefined); + run(reference.graph, fighter, opponent, 30, undefined); + react(hit.graph); + other(reference.graph); + const frames: number[][] = []; + for (let frame = 0; frame < 30; frame += 1) { + for (const { graph } of [hit, reference]) graph.update(fighter, opponent, 1 / 60, 0.5 + frame / 60, false, "full", 15 + frame / 2); + const a = sample(hit.boxer); + const b = sample(reference.boxer); + frames.push(a.map((value, index) => value - b[index]!)); + } + return frames; + }; + const hipsAxis = (boxer: SkinnedBoxer, x: number, z: number): THREE.Vector3 => + new THREE.Vector3(x, 0, z).applyQuaternion(worldQuaternion(boxer.rig.bones.hips, new THREE.Quaternion())); + const fromHips = (boxer: SkinnedBoxer, name: CanonicalBone): THREE.Vector3 => bone(boxer, name).sub(bone(boxer, "hips")); + + it("bend the fighter toward the ribs a hook lands on and drop the elbow on that side", () => { + // A left hook lands on the right ribs, the fighter's -x side; a straight to the solar plexus does not lean him. + const frames = pair( + (graph) => graph.react("hit", "body", 1, "hook", "left", 120), + (graph) => graph.react("hit", "body", 1, "straight", "left", 120), + (boxer) => [fromHips(boxer, "neck").dot(hipsAxis(boxer, 1, 0)), bone(boxer, "elbowR").y, bone(boxer, "elbowL").y, bone(boxer, "hips").x], + ); + expect(Math.min(...frames.map(([lean]) => lean!))).toBeLessThan(-0.03); + expect(Math.min(...frames.map(([, right]) => right!))).toBeLessThan(-0.04); + expect(Math.min(...frames.map(([, , left]) => left!))).toBeGreaterThan(-0.02); + expect(Math.max(...frames.map(([, , , hips]) => hips!))).toBeGreaterThan(0.02); + }); + + it("lift the fighter onto his toes on an uppercut before he folds over it", () => { + const frames = pair( + (graph) => graph.react("hit", "body", 1, "uppercut", "right", 120), + () => undefined, + (boxer) => [bone(boxer, "hips").y, fromHips(boxer, "head").dot(hipsAxis(boxer, 0, 1))], + ); + const lifts = frames.map(([lift]) => lift!); + const folds = frames.map(([, fold]) => fold!); + expect(Math.max(...lifts)).toBeGreaterThan(0.04); + expect(Math.min(...folds.slice(0, 6))).toBeLessThan(-0.02); + expect(Math.max(...folds)).toBeGreaterThan(0.06); + expect(folds.indexOf(Math.max(...folds))).toBeGreaterThan(lifts.indexOf(Math.max(...lifts))); + }); +}); + +describe("transient reset", () => { + it("snaps back to standing after a fall and can seed the lying pose directly", () => { + const { boxer, graph } = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + run(graph, fighter, opponent, 10, undefined); + graph.react("hit", "head", 1, "uppercut", "right", 420); + run(graph, { ...fighter, is_downed: true }, opponent, 70, undefined, 5, 10 / 60); + expect(bone(boxer, "head").y).toBeLessThan(0.45); + graph.resetTransient(false); + run(graph, fighter, opponent, 3, undefined, 40, 80 / 60); + expect(bone(boxer, "hips").y).toBeGreaterThan(0.72); + graph.resetTransient(true); + run(graph, { ...fighter, is_downed: true }, opponent, 3, undefined, 42, 83 / 60); + expect(bone(boxer, "head").y).toBeLessThan(0.45); + }); +}); + +describe("glove touch", () => { + it("extends both gloves toward the opponent late in the countdown and returns to guard", () => { + const { boxer, graph } = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + run(graph, fighter, opponent, 30, undefined); + const guardLeadZ = bone(boxer, "gloveL").z; + const guardRearZ = bone(boxer, "gloveR").z; + graph.setCountdown(30); + run(graph, fighter, opponent, 60, undefined, 15, 0.5); + expect(bone(boxer, "gloveL").z).toBeGreaterThan(guardLeadZ + 0.08); + expect(bone(boxer, "gloveR").z).toBeGreaterThan(guardRearZ + 0.28); + expect(Math.abs(bone(boxer, "gloveL").x - bone(boxer, "gloveR").x)).toBeLessThan(0.3); + graph.setCountdown(5); + run(graph, fighter, opponent, 60, undefined, 45, 1.5); + expect(bone(boxer, "gloveR").z).toBeLessThan(guardRearZ + 0.1); + }); +}); + +describe("cornerman", () => { + it("leans in over the rope with both hands forward while attending", () => { + const boxer = new SkinnedBoxer(gltf, { skin: 0xc79b76, gear: 0x2b4c9e }); + const graph = new BoxingGraph(boxer, mapping, { referee: true }); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + run(graph, fighter, opponent, 30, undefined); + const idleHead = bone(boxer, "head").clone(); + graph.attend(true); + run(graph, fighter, opponent, 120, undefined, 15, 0.5); + const head = bone(boxer, "head"); + const left = bone(boxer, "gloveL"); + expect(head.z).toBeGreaterThan(idleHead.z + 0.12); + expect(head.y).toBeLessThan(idleHead.y - 0.08); + expect(left.z).toBeGreaterThan(0.45); + expect(left.y).toBeGreaterThan(1.1); + }); +}); + +describe("clinch break", () => { + it("pushes both gloves out and apart at chest height", () => { + const { boxer, graph } = makeGraph(); + graph.breakClinch(2); + run(graph, facingOpponent(baseFighter("one")), opponentFor("two"), 45, undefined); + const left = bone(boxer, "gloveL"); + const right = bone(boxer, "gloveR"); + expect(Math.abs(left.x - right.x)).toBeGreaterThan(0.7); + expect(left.y).toBeGreaterThan(1.05); + expect(left.y).toBeLessThan(1.45); + expect(left.z).toBeGreaterThan(0.3); + }); +}); + +describe("root follow", () => { + it("catches a teleport at the same speed whatever the frame rate", () => { + const fast = makeGraph(); + const slow = makeGraph(); + const start = facingOpponent(baseFighter("one")); + run(fast.graph, start, opponentFor("two"), 5, undefined); + run(slow.graph, start, opponentFor("two"), 5, undefined); + const moved = { ...start, x: 300 }; + for (let frame = 0; frame < 30; frame += 1) fast.graph.update(moved, opponentFor("two"), 1 / 60, frame / 60, false, "full", frame, undefined); + for (let frame = 0; frame < 3; frame += 1) slow.graph.update(moved, opponentFor("two"), 1 / 6, frame / 6, false, "full", frame * 5, undefined); + const target = mapping.x(300); + expect(Math.abs(fast.boxer.root.position.x - target)).toBeLessThan(0.01); + expect(Math.abs(slow.boxer.root.position.x - target)).toBeLessThan(0.01); + }); +}); + +describe("taunt", () => { + it("drops the rear glove to the hip and beckons with the lead glove out front", () => { + const { boxer, graph } = makeGraph(); + const taunting = { ...facingOpponent(baseFighter("one")), taunt_ticks: 45 }; + run(graph, taunting, opponentFor("two"), 45, undefined); + const left = bone(boxer, "gloveL"); + const right = bone(boxer, "gloveR"); + expect(right.y).toBeLessThan(1.05); + expect(right.z).toBeLessThan(0.2); + expect(left.y).toBeGreaterThan(right.y + 0.15); + expect(left.z).toBeGreaterThan(0.3); + }); +}); + +describe("cutman", () => { + it("crouches before the seated fighter, presses the enswell on the eye, and stands back up when done", () => { + const { boxer, graph } = makeGraph(); + const eye = new THREE.Vector3(0.03, 1.18, 0.5); + graph.treat(eye, new THREE.Vector3(0, 0, -1), 1); + run(graph, facingOpponent(baseFighter("one")), opponentFor("two"), 90, undefined); + const glove = bone(boxer, "gloveL"); + expect(glove.distanceTo(new THREE.Vector3(eye.x, eye.y - 0.07, eye.z - 0.08))).toBeLessThan(0.1); + expect(bone(boxer, "hips").y).toBeLessThan(0.7); + expect(boxer.rig.bones.gloveL.getObjectByName("enswell")?.visible).toBe(true); + graph.treat(null); + run(graph, facingOpponent(baseFighter("one")), opponentFor("two"), 90, undefined, 45, 1.5); + expect(bone(boxer, "hips").y).toBeGreaterThan(0.75); + expect(boxer.rig.bones.gloveL.getObjectByName("enswell")?.visible).toBe(false); + }); +}); + +describe("own punch prediction", () => { + const jab = { kind: "punch" as const, id: "own-1", class: "jab" as const, hand: "left" as const, target: "head" as const, power: "normal" as const }; + const age = (graph: BoxingGraph): number => (graph as unknown as { punchAgeTicks: number }).punchAgeTicks; + const active = (graph: BoxingGraph): boolean => (graph as unknown as { punchActive: boolean }).punchActive; + + it("starts on the key press, never jumps back when the server confirms late, and lands on the server's contact tick", () => { + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + const timing = punchTiming("jab", "head", "normal"); + run(graph, idle, opponentFor("two"), 10, undefined); + graph.predict(jab, 0, 30, 6); + expect(active(graph)).toBe(true); + const ages: number[] = []; + let tick = 100; + const step = (fighter: FighterSnapshot): void => { + tick += 0.5; + graph.update(fighter, opponentFor("two"), 1 / 60, tick / 30, false, "full", tick, undefined); + if (active(graph)) ages.push(age(graph)); + }; + for (let frame = 0; frame < 12; frame += 1) step(idle); + expect(age(graph)).toBeGreaterThan(1.5); + expect(age(graph)).toBeLessThan(timing.startup); + const startTick = tick; + const confirmed = { ...idle, action: "jab" as const, action_hand: "left" as const, action_target: "head" as const, action_power: "normal" as const, action_id: "own-1", action_key: "jab:left:head:normal", action_start_tick: startTick, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery }; + let contactAt: number | null = null; + for (let frame = 0; frame < 40 && active(graph); frame += 1) { + step(confirmed); + if (contactAt === null && age(graph) >= timing.startup) contactAt = tick; + } + for (let index = 1; index < ages.length; index += 1) expect(ages[index]!).toBeGreaterThanOrEqual(ages[index - 1]!); + expect(contactAt).not.toBeNull(); + expect(Math.abs(contactAt! - (startTick + timing.startup))).toBeLessThanOrEqual(1); + }); + + const state = (graph: BoxingGraph): { punchClass: string; ownActionId: string | null; actionId: string | null } => + graph as unknown as { punchClass: string; ownActionId: string | null; actionId: string | null }; + const serverPunch = (base: FighterSnapshot, id: string, punchClass: "jab" | "straight" | "hook" | "uppercut", startTick: number, scale = 1): FighterSnapshot => { + const timing = punchTiming(punchClass, "head", "normal"); + return { ...base, action: punchClass, action_hand: "left", action_target: "head", action_power: "normal", action_id: id, action_key: `${punchClass}:left:head:normal`, action_start_tick: startTick, action_startup_ticks: Math.round(timing.startup * scale), action_active_ticks: timing.active, action_recovery_ticks: Math.round(timing.recovery * scale) }; + }; + + it("keeps the punch in flight when a second punch is pressed before the server confirms the first", () => { + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + run(graph, idle, opponentFor("two"), 10, undefined); + graph.predict(jab, 0, 30, 4); + let tick = 100; + const step = (fighter: FighterSnapshot): void => { tick += 0.5; graph.update(fighter, opponentFor("two"), 1 / 60, tick / 30, false, "full", tick, undefined); }; + for (let frame = 0; frame < 3; frame += 1) step(idle); + const before = age(graph); + graph.predict({ ...jab, id: "own-2", class: "straight" }, 3 / 60, 30, 4); + expect(state(graph).punchClass).toBe("jab"); + expect(state(graph).ownActionId).toBe("own-1"); + expect(age(graph)).toBe(before); + const ages: number[] = []; + for (let frame = 0; frame < 6; frame += 1) { step(serverPunch(idle, "own-1", "jab", tick)); ages.push(age(graph)); } + for (let index = 1; index < ages.length; index += 1) expect(ages[index]!).toBeGreaterThanOrEqual(ages[index - 1]!); + expect(state(graph).punchClass).toBe("jab"); + }); + + it("cuts a follow-up in at the cancel age of a landed combination without the first punch coming back", () => { + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + run(graph, idle, opponentFor("two"), 10, undefined); + let tick = 300; + const hook = serverPunch(idle, "theirs-hook", "hook", tick); + const step = (fighter: FighterSnapshot): void => { tick += 0.5; graph.update(fighter, opponentFor("two"), 1 / 60, tick / 30, false, "full", tick, undefined); }; + graph.acknowledge(hook, true, [{ event_id: 1, tick: 307, kind: "hit", actor_id: "one", target_id: "two", amount: 30, detail: "hook:head", blood: 0, direction: 1, action_id: "theirs-hook" }]); + // The engine lets a chained follow-up cut a landed hook's recovery short from 7 + 3 + 12 / 2 ticks. + while (age(graph) < 16) step(hook); + expect(state(graph).punchClass).toBe("hook"); + graph.predict({ ...jab, id: "own-3", class: "uppercut" }, 0, 30, 3); + expect(state(graph).punchClass).toBe("uppercut"); + for (let frame = 0; frame < 6; frame += 1) { + step(hook); + expect(state(graph).punchClass).toBe("uppercut"); + expect(state(graph).ownActionId).toBe("own-3"); + } + }); + + it("does not replay a punch the server confirms after it has finished here", () => { + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + run(graph, idle, opponentFor("two"), 10, undefined); + graph.predict(jab, 0, 30, 2); + let tick = 500; + const step = (fighter: FighterSnapshot): void => { tick += 0.5; graph.update(fighter, opponentFor("two"), 1 / 60, tick / 30, false, "full", tick, undefined); }; + let frames = 0; + while (active(graph) && frames < 200) { step(idle); frames += 1; } + expect(active(graph)).toBe(false); + step(serverPunch(idle, "own-1", "jab", tick - 3)); + expect(active(graph)).toBe(false); + }); + + it("brings the glove back the way it went when the server never starts the punch", () => { + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + const timing = punchTiming("hook", "head", "normal"); + run(graph, idle, opponentFor("two"), 10, undefined); + graph.predict({ ...jab, id: "own-hook", class: "hook" }, 0, 30, 2); + let tick = 600; + const step = (fighter: FighterSnapshot): void => { tick += 0.5; graph.update(fighter, opponentFor("two"), 1 / 60, tick / 30, false, "full", tick, undefined); }; + const ages: number[] = []; + let frames = 0; + while (active(graph) && frames < 200) { step(idle); frames += 1; if (active(graph)) ages.push(age(graph)); } + expect(active(graph)).toBe(false); + expect(frames / 2).toBeLessThan(timing.startup + timing.active + timing.recovery - 4); + const peak = ages.indexOf(Math.max(...ages)); + expect(Math.max(...ages)).toBeLessThan(timing.startup); + for (let index = peak + 1; index < ages.length; index += 1) expect(ages[index]!).toBeLessThan(ages[index - 1]!); + step(serverPunch(idle, "own-hook", "hook", tick)); + expect(active(graph)).toBe(true); + }); + + it("keeps the glove where it is when the server's timing is slower than predicted", () => { + const from = punchTiming("jab", "head", "normal"); + const to = { ...from, startup: from.startup + 2, recovery: from.recovery + 3 }; + expect(remapPunchAge(from.startup / 2, from, to)).toBeCloseTo(to.startup / 2); + expect(remapPunchAge(from.startup + from.active / 2, from, to)).toBeCloseTo(to.startup + to.active / 2); + expect(remapPunchAge(from.startup + from.active + from.recovery, from, to)).toBeCloseTo(to.startup + to.active + to.recovery); + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + run(graph, idle, opponentFor("two"), 10, undefined); + graph.predict(jab, 0, 30, 4); + let tick = 700; + const step = (fighter: FighterSnapshot): void => { tick += 0.5; graph.update(fighter, opponentFor("two"), 1 / 60, tick / 30, false, "full", tick, undefined); }; + for (let frame = 0; frame < 6; frame += 1) step(idle); + const progress = age(graph) / from.startup; + step(serverPunch(idle, "own-1", "jab", tick, 1.5)); + const slower = Math.round(from.startup * 1.5); + expect(age(graph) / slower).toBeGreaterThanOrEqual(progress - 0.01); + }); + + it("forgets the punch when the fighter is reset for the replay", () => { + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + run(graph, idle, opponentFor("two"), 10, undefined); + graph.predict(jab, 0, 30, 4); + expect(graph.ownPunchActive).toBe(true); + graph.resetTransient(false); + expect(active(graph)).toBe(false); + expect(graph.ownPunchActive).toBe(false); + graph.update(serverPunch(idle, "own-1", "jab", 900), opponentFor("two"), 1 / 60, 30, false, "full", 902, undefined); + expect(active(graph)).toBe(true); + }); + + it("plays an opponent's punch on the server's timeline", () => { + const { graph } = makeGraph(); + const idle = facingOpponent(baseFighter("one")); + const timing = punchTiming("jab", "head", "normal"); + run(graph, idle, opponentFor("two"), 10, undefined); + const thrown = { ...idle, action: "jab" as const, action_hand: "left" as const, action_target: "head" as const, action_power: "normal" as const, action_id: "theirs-1", action_key: "jab:left:head:normal", action_start_tick: 200, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery }; + graph.update(thrown, opponentFor("two"), 1 / 60, 0, false, "full", 203, undefined); + expect(age(graph)).toBeCloseTo(3 + 0.5, 1); + }); +}); + +describe("clinch hold", () => { + it("ties up over the arms for the first-sorted fighter and under them for the other, heads to the right", () => { + const clinched = (id: string): FighterSnapshot => ({ ...facingOpponent(baseFighter(id)), clinch_ticks: 30 }); + const held = (id: string): FighterSnapshot => ({ ...opponentFor(id), y: -100, clinch_ticks: 30 }); + const idle = makeGraph(); + run(idle.graph, facingOpponent(baseFighter("one")), held("two"), 60, undefined); + const over = makeGraph(); + run(over.graph, clinched("one"), held("two"), 60, undefined); + const under = makeGraph(); + run(under.graph, clinched("two"), held("one"), 60, undefined); + for (const { boxer } of [over, under]) { + const left = bone(boxer, "gloveL"); + const right = bone(boxer, "gloveR"); + expect(left.z).toBeGreaterThan(0.35); + expect(right.z).toBeGreaterThan(0.35); + expect(left.x - right.x).toBeGreaterThan(0.25); + expect(bone(idle.boxer, "head").x - bone(boxer, "head").x).toBeGreaterThan(0.08); + } + expect(bone(over.boxer, "gloveL").y).toBeGreaterThan(1.2); + expect(bone(over.boxer, "gloveR").y).toBeGreaterThan(1.15); + expect(bone(under.boxer, "gloveL").y).toBeLessThan(1.1); + expect(bone(under.boxer, "gloveR").y).toBeLessThan(1.1); + expect(bone(over.boxer, "head").y).toBeGreaterThan(bone(under.boxer, "head").y); + const sway: number[] = []; + for (let frame = 0; frame < 40; frame += 1) { + over.graph.update(clinched("one"), held("two"), 1 / 60, 1 + frame / 60, false, "full", 60 + frame, undefined); + sway.push(bone(over.boxer, "hips").x); + } + expect(Math.max(...sway) - Math.min(...sway)).toBeGreaterThan(0.008); + }); +}); + +describe("wave-off", () => { + it("sweeps both gloves across overhead while waving the fight off", () => { + const { boxer, graph } = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + graph.waveOff(4); + run(graph, fighter, opponent, 60, undefined); + const first = bone(boxer, "gloveL").clone(); + expect(first.y).toBeGreaterThan(1.45); + run(graph, fighter, opponent, 12, undefined, 30, 1); + const later = bone(boxer, "gloveL"); + expect(later.y).toBeGreaterThan(1.45); + expect(Math.abs(later.x - first.x)).toBeGreaterThan(0.15); + }); +}); + +describe("skinned rig solver", () => { + it("reproduces the rest limb frames when solving onto rest targets", () => { + const { boxer } = makeGraph(); + const rig = boxer.rig; + boxer.root.updateMatrixWorld(true); + const limbs = [ + { upper: "shoulderL", lower: "elbowL", end: "gloveL", lengths: rig.metrics.armL, axis: "z" as const, sign: 1 as const }, + { upper: "shoulderR", lower: "elbowR", end: "gloveR", lengths: rig.metrics.armR, axis: "z" as const, sign: -1 as const }, + { upper: "hipL", lower: "kneeL", end: "ankleL", lengths: rig.metrics.legL, axis: "x" as const, sign: -1 as const }, + { upper: "hipR", lower: "kneeR", end: "ankleR", lengths: rig.metrics.legR, axis: "x" as const, sign: -1 as const }, + ] as const; + for (const limb of limbs) { + rig.resetToRest(); + boxer.root.updateMatrixWorld(true); + const root = rig.position(limb.upper, new THREE.Vector3()); + const joint = rig.position(limb.lower, new THREE.Vector3()); + const end = rig.position(limb.end, new THREE.Vector3()); + const restUpper = worldQuaternion(rig.bones[limb.upper], new THREE.Quaternion()); + const restLower = worldQuaternion(rig.bones[limb.lower], new THREE.Quaternion()); + const direction = end.clone().sub(root).normalize(); + const pole = joint.clone().sub(root); + pole.addScaledVector(direction, -pole.dot(direction)).normalize(); + const result = rig.solveLimb(rig.bones[limb.upper], rig.bones[limb.lower], limb.lengths, end, pole, limb.axis, limb.sign); + rig.bones[limb.end].updateWorldMatrix(false, false); + expect(result.reached).toBe(true); + expect(rig.position(limb.end, new THREE.Vector3()).distanceTo(end)).toBeLessThan(0.002); + expect(result.joint.distanceTo(joint)).toBeLessThan(0.002); + expect(Math.abs(worldQuaternion(rig.bones[limb.upper], new THREE.Quaternion()).dot(restUpper))).toBeGreaterThan(0.99); + expect(Math.abs(worldQuaternion(rig.bones[limb.lower], new THREE.Quaternion()).dot(restLower))).toBeGreaterThan(0.99); + } + }); +}); + +describe("runtime boxing graph", () => { + it("plants both feet on the authored stance and never slides them while idle", () => { + const { boxer, graph } = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + run(graph, fighter, opponent, 30, undefined); + const left = bone(boxer, "ankleL").clone(); + const right = bone(boxer, "ankleR").clone(); + expect(left.x).toBeCloseTo(STANCE.leadFoot.x, 2); + expect(left.z).toBeCloseTo(STANCE.leadFoot.z, 2); + expect(right.x).toBeCloseTo(STANCE.rearFoot.x, 2); + expect(right.z).toBeCloseTo(STANCE.rearFoot.z, 2); + expect(left.y).toBeCloseTo(boxer.rig.metrics.ankleHeight, 2); + run(graph, fighter, opponent, 120, undefined, 15, 0.5); + expect(bone(boxer, "ankleL").distanceTo(left)).toBeLessThan(1e-4); + expect(bone(boxer, "ankleR").distanceTo(right)).toBeLessThan(1e-4); + expect(bone(boxer, "head").y).toBeGreaterThan(1.45); + }); + + it("steps instead of sliding when the authoritative root moves", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + let fighter = facingOpponent({ ...baseFighter("one"), velocity_y: -6 }); + graph.update(fighter, opponent, 1 / 60, 0, false, "full", 0); + const stationary = bone(boxer, "ankleL").clone(); + let lifted = false; + let moved = 0; + for (let frame = 1; frame <= 90; frame += 1) { + fighter = { ...fighter, y: -Math.round(frame * 3) }; + graph.update(fighter, opponent, 1 / 60, frame / 60, false, "full", frame / 2); + const ankle = bone(boxer, "ankleL"); + if (ankle.y > boxer.rig.metrics.ankleHeight + 0.02) lifted = true; + moved = Math.max(moved, ankle.distanceTo(stationary)); + } + expect(lifted).toBe(true); + expect(moved).toBeGreaterThan(0.3); + }); + + it("lands the punching glove on the opponent's head hurtbox at the contact tick", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const head = new THREE.Vector3(0, 1.5, mapping.z(-150)); + const timing = punchTiming("jab", "head", "normal"); + let fighter = facingOpponent(baseFighter("one")); + run(graph, fighter, opponent, 20, head); + fighter = { + ...fighter, + action: "jab", action_hand: "left", action_target: "head", action_power: "normal", action_id: "c1", action_key: "jab:left:head:normal", + action_start_tick: 10, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + let contactDistance = Infinity; + let tick = 10; + for (let frame = 0; frame < 40; frame += 1) { + tick += 0.5; + graph.update(fighter, opponent, 1 / 60, 1 + frame / 60, false, "full", tick, head); + if (Math.abs(tick - (10 + timing.startup)) < 0.26) contactDistance = Math.min(contactDistance, bone(boxer, "gloveL").distanceTo(head)); + } + expect(contactDistance).toBeLessThan(0.13 + 0.11 + 0.02); + expect(contactDistance).toBeGreaterThan(0.08); + }); + + it("keeps the toes flat on the canvas when the heel lifts", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const head = new THREE.Vector3(0, 1.5, mapping.z(-150)); + const timing = punchTiming("straight", "head", "power"); + const idle = facingOpponent(baseFighter("one")); + run(graph, idle, opponent, 20, head); + expect(lowestVertex(boxer, "ShoesMat0")).toBeGreaterThan(-0.02); + const straight = { + ...idle, + action: "straight" as const, action_hand: "right" as const, action_target: "head" as const, action_power: "power" as const, action_id: "p1", action_key: "straight:right:head:power", + action_start_tick: 10, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + let lowest = Infinity; + let tick = 10; + for (let frame = 0; frame < (timing.startup + timing.active) * 2; frame += 1) { + tick += 0.5; + graph.update(straight, opponent, 1 / 60, 1 + frame / 60, false, "full", tick, head); + if (tick >= 10 + timing.startup) lowest = Math.min(lowest, lowestVertex(boxer, "ShoesMat0")); + } + expect(lowest).toBeGreaterThan(-0.02); + graph.celebrate(2); + run(graph, idle, opponent, 60, undefined, 40, 2); + expect(lowestVertex(boxer, "ShoesMat0")).toBeGreaterThan(-0.02); + }); + + it("retracts a hook straight back to the guard instead of swinging back out wide", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const head = new THREE.Vector3(0, 1.5, mapping.z(-150)); + const timing = punchTiming("hook", "head", "normal"); + const idle = facingOpponent(baseFighter("one")); + run(graph, idle, opponent, 30, head); + const guard = bone(boxer, "gloveL").clone(); + const fighter = { + ...idle, + action: "hook" as const, action_hand: "left" as const, action_target: "head" as const, action_power: "normal" as const, action_id: "h1", action_key: "hook:left:head:normal", + action_start_tick: 15, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + let contact = new THREE.Vector3(); + let midRecovery = new THREE.Vector3(); + let widest = 0; + let tick = 15; + const contactTick = 15 + timing.startup + timing.active / 2; + const midTick = 15 + timing.startup + timing.active + timing.recovery / 2; + for (let frame = 0; frame < 60; frame += 1) { + tick += 0.5; + graph.update(fighter, opponent, 1 / 60, 2 + frame / 60, false, "full", tick, head); + const glove = bone(boxer, "gloveL"); + if (Math.abs(tick - contactTick) < 0.26) contact = glove.clone(); + if (Math.abs(tick - midTick) < 0.26) midRecovery = glove.clone(); + if (tick > 15 + timing.startup + timing.active) widest = Math.max(widest, glove.x); + } + expect(contact.z).toBeGreaterThan(guard.z + 0.2); + expect(midRecovery.distanceTo(guard)).toBeLessThan(midRecovery.distanceTo(contact)); + expect(widest).toBeLessThan(guard.x + 0.12); + }); + + it("mirrors the southpaw stance across the character's centre line", () => { + const orthodox = makeGraph(); + const southpaw = makeGraph(); + const opponent = opponentFor("two"); + run(orthodox.graph, facingOpponent(baseFighter("one")), opponent, 40, undefined); + run(southpaw.graph, facingOpponent({ ...baseFighter("one"), stance: "southpaw" }), opponent, 40, undefined); + const pairs: [CanonicalBone, CanonicalBone][] = [["ankleL", "ankleR"], ["gloveL", "gloveR"], ["elbowL", "elbowR"]]; + for (const [left, right] of pairs) { + const a = bone(orthodox.boxer, left); + const b = bone(southpaw.boxer, right); + expect(Math.abs(a.x + b.x)).toBeLessThan(0.02); + expect(Math.abs(a.y - b.y)).toBeLessThan(0.02); + expect(Math.abs(a.z - b.z)).toBeLessThan(0.02); + } + }); + + it("falls to the canvas when downed and stands back up on recovery", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const standing = facingOpponent(baseFighter("one")); + run(graph, standing, opponent, 30, undefined); + run(graph, { ...standing, is_downed: true }, opponent, 90, undefined, 15, 0.5); + expect(bone(boxer, "head").y).toBeLessThan(0.55); + expect(bone(boxer, "hips").y).toBeLessThan(0.3); + expect(graph.isDown).toBe(true); + run(graph, standing, opponent, 150, undefined, 60, 2); + expect(graph.isDown).toBe(false); + expect(bone(boxer, "head").y).toBeGreaterThan(1.45); + }); + + it("snaps the head along the impact line on a hit reaction and settles afterwards", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const fighter = facingOpponent(baseFighter("one")); + run(graph, fighter, opponent, 30, undefined); + const rest = bone(boxer, "head").clone(); + graph.react("hit", "head", 1, "hook", "left", 320); + let peak = 0; + for (let frame = 0; frame < 12; frame += 1) { + graph.update(fighter, opponent, 1 / 60, 0.5 + frame / 60, false, "full", 15 + frame / 2); + peak = Math.max(peak, bone(boxer, "head").x - rest.x); + } + expect(peak).toBeGreaterThan(0.05); + run(graph, fighter, opponent, 120, undefined, 21, 0.7); + expect(Math.abs(bone(boxer, "head").x - rest.x)).toBeLessThan(0.02); + }); + + it("restarts identical actions on new instance ids and follows the authoritative start tick", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const head = new THREE.Vector3(0, 1.5, mapping.z(-150)); + const timing = punchTiming("jab", "head", "normal"); + const base = facingOpponent(baseFighter("one")); + const punch = (id: string, start: number): FighterSnapshot => ({ + ...base, + action: "jab", action_hand: "left", action_target: "head", action_power: "normal", action_id: id, action_key: "jab:left:head:normal", + action_start_tick: start, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }); + run(graph, base, opponent, 10, head); + const guard = bone(boxer, "gloveL").z; + let tick = 5; + let firstContact = -Infinity; + const total = timing.startup + timing.active + timing.recovery; + for (let frame = 0; frame < total * 2; frame += 1) { + tick += 0.5; + graph.update(punch("c1", 5), opponent, 1 / 60, 0.2 + frame / 60, false, "full", tick, head); + if (Math.abs(tick - (5 + timing.startup)) < 0.26) firstContact = bone(boxer, "gloveL").z; + } + const retracted = bone(boxer, "gloveL").z; + expect(firstContact).toBeGreaterThan(guard + 0.25); + expect(retracted).toBeLessThan(guard + 0.08); + graph.update(punch("c2", 30), opponent, 1 / 60, 1, false, "full", 30, head); + expect(bone(boxer, "gloveL").z).toBeLessThan(guard + 0.1); + graph.update(punch("c2", 30), opponent, 1 / 60, 1.5, false, "full", 30 + timing.startup, head); + expect(bone(boxer, "gloveL").z).toBeGreaterThan(guard + 0.25); + }); + + it("produces identical poses for identical input sequences", () => { + const a = makeGraph(); + const b = makeGraph(); + const opponent = opponentFor("two"); + const fighter = facingOpponent({ ...baseFighter("one"), defense: "guard_high", velocity_x: 3 }); + for (let frame = 0; frame < 60; frame += 1) { + const moving = { ...fighter, x: frame * 2 }; + a.graph.update(moving, opponent, 1 / 60, frame / 60, false, "full", frame / 2); + b.graph.update(moving, opponent, 1 / 60, frame / 60, false, "full", frame / 2); + } + for (const name of ["head", "gloveL", "gloveR", "ankleL", "ankleR", "kneeL"] as const) { + expect(bone(a.boxer, name).distanceTo(bone(b.boxer, name))).toBeLessThan(1e-9); + } + }); +}); + +describe("per-frame allocations", () => { + /** Counts the vectors, quaternions and Euler angles built (clones included) while `body` runs. */ + const constructions = (body: () => void): number => { + let count = 0; + const counted = [[THREE.Vector3.prototype, "x"], [THREE.Quaternion.prototype, "_x"], [THREE.Euler.prototype, "_x"]] as const; + for (const [prototype, key] of counted) { + // Each constructor assigns this field first: count it, then make it the instance's own plain field. + Object.defineProperty(prototype, key, { + configurable: true, + set(this: object, value: number) { + count += 1; + Object.defineProperty(this, key, { value, writable: true, enumerable: true, configurable: true }); + }, + }); + } + try { + body(); + } finally { + for (const [prototype, key] of counted) Reflect.deleteProperty(prototype, key); + } + return count; + }; + + it("builds no vectors while idle, falling, down or getting up, or with a dislocated jaw", () => { + const { graph } = makeGraph(); + const fighter = facingOpponent(baseFighter("one")); + const opponent = opponentFor("two"); + const downed = { ...fighter, is_downed: true }; + run(graph, fighter, opponent, 30, undefined); + expect(constructions(() => run(graph, fighter, opponent, 10, undefined, 15, 0.5))).toBe(0); + graph.react("hit", "head", 1, "uppercut", "left", 120); + expect(constructions(() => run(graph, downed, opponent, 20, undefined, 20, 0.7))).toBe(0); + run(graph, downed, opponent, 60, undefined, 30, 1); + expect(constructions(() => run(graph, downed, opponent, 10, undefined, 60, 2))).toBe(0); + expect(constructions(() => run(graph, fighter, opponent, 60, undefined, 65, 2.2))).toBe(0); + graph.setArcadeDislocation("jaw"); + expect(constructions(() => run(graph, fighter, opponent, 10, undefined, 100, 3.5))).toBe(0); + }); +}); + +describe("transition sweep", () => { + const PUNCHES = ["jab", "straight", "hook", "uppercut"] as const; + // 9 m/s: a straight's glove peaks near 7 m/s, while the snaps this guards against moved bones 0.5 m in a frame. + const MAX_STEP = 0.15; + + it("moves every bone smoothly, keeps the skin above the canvas and bends the knees forward from idle through punches, falls, get-ups, the corner stool and a taunt", () => { + const { boxer, graph } = makeGraph(); + const opponent = opponentFor("two"); + const head = new THREE.Vector3(0, 1.5, mapping.z(-150)); + const idle = facingOpponent({ ...baseFighter("one"), get_up_required: 66 }); + const downed = { ...idle, is_downed: true }; + const released = { ...idle, get_up_meter: 66, stunned_ticks: 20 }; + const bones = Object.entries(boxer.rig.bones); + const previous = bones.map(() => new THREE.Vector3()); + const position = new THREE.Vector3(); + const vertex = new THREE.Vector3(); + const meshes: THREE.SkinnedMesh[] = []; + boxer.root.traverse((object) => { + if (object instanceof THREE.SkinnedMesh) meshes.push(object); + }); + let tick = 0; + let frames = 0; + let jump = { distance: 0, at: "" }; + let lowest = { height: Infinity, at: "" }; + let knee = { along: Infinity, at: "" }; + const step = (label: string, fighter: FighterSnapshot | ((frame: number) => FighterSnapshot), count: number): void => { + for (let frame = 0; frame < count; frame += 1) { + tick += 0.5; + graph.update(typeof fighter === "function" ? fighter(frame) : fighter, opponent, 1 / 60, tick / 30, false, "full", tick, head); + boxer.root.updateMatrixWorld(true); + for (const [index, [name, joint]] of bones.entries()) { + const distance = frames === 0 ? 0 : worldPosition(joint, position).distanceTo(previous[index]!); + if (distance > jump.distance) jump = { distance, at: `${label} frame ${frame} ${name}` }; + worldPosition(joint, previous[index]!); + } + if (frames % 3 === 0) { + for (const mesh of meshes) { + const count = mesh.geometry.getAttribute("position").count; + for (let index = 0; index < count; index += 2) { + const height = mesh.getVertexPosition(index, vertex).applyMatrix4(mesh.matrixWorld).y; + if (height < lowest.height) lowest = { height, at: `${label} frame ${frame} ${mesh.name}` }; + } + } + } + for (const side of ["L", "R"] as const) { + const along = kneeBend(boxer, side); + if (along !== null && along < knee.along) knee = { along, at: `${label} frame ${frame} knee${side}` }; + } + frames += 1; + } + }; + const punch = (punchClass: (typeof PUNCHES)[number], hand: "left" | "right"): FighterSnapshot => { + const timing = punchTiming(punchClass, "head", "normal"); + return { + ...idle, + action: punchClass, action_hand: hand, action_target: "head", action_power: "normal", action_id: `${punchClass}-${tick}`, action_key: `${punchClass}:${hand}:head:normal`, + action_start_tick: tick + 0.5, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + }; + const getUp = (label: string): void => { + step(`${label} get-up meter`, (frame) => ({ ...downed, get_up_meter: frame < 30 ? 22 : 44 }), 60); + step(`${label} get-up`, released, 45); + }; + + step("idle", idle, 30); + for (const punchClass of PUNCHES) step(punchClass, punch(punchClass, punchClass === "jab" || punchClass === "hook" ? "left" : "right"), 40); + graph.react("hit", "head", 1, "hook", "left", 140); + step("fall face down", downed, 70); + getUp("first"); + step("stand", idle, 30); + graph.react("hit", "head", 1, "uppercut", "right", 120); + step("fall on the back", downed, 70); + step("get-up meter", (frame) => ({ ...downed, get_up_meter: frame < 30 ? 22 : 44 }), 60); + step("get-up", released, 8); + step("knocked down rising", downed, 70); + getUp("second"); + step("fight on", idle, 30); + graph.setResting(true); + step("rest", idle, 150); + graph.setResting(false); + step("round starts", idle, 90); + // The count steps once per engine tick, every second frame. + step("taunt", (frame) => ({ ...idle, taunt_ticks: Math.max(0, 60 - Math.floor(frame / 2)) }), 140); + + expect(jump.distance, jump.at).toBeLessThan(MAX_STEP); + expect(lowest.height, lowest.at).toBeGreaterThan(-0.02); + expect(knee.along, knee.at).toBeGreaterThan(0.25); + }); +}); diff --git a/web/hands/src/render/poser.ts b/web/hands/src/render/poser.ts new file mode 100644 index 00000000..acf669dc --- /dev/null +++ b/web/hands/src/render/poser.ts @@ -0,0 +1,243 @@ +import * as THREE from "three"; +import { SolvedRig, worldPosition, worldQuaternion, type CanonicalBone } from "./rig"; + +/** + * Character-space boxing pose description and the solver that applies it to + * the skinned rig. Character space is metres relative to the fighter's root: + * +Z toward the opponent, +X the fighter's left, +Y up. Orthodox poses are + * authored for a left lead; southpaw mirrors x and swaps limb roles. + */ + +export interface HandTarget { + /** Character-space wrist position. */ + readonly position: THREE.Vector3; + /** Character-space knuckle direction (bone +Y). */ + readonly knuckles: THREE.Vector3; + /** Character-space palm normal (bone +Z). */ + readonly palm: THREE.Vector3; + /** Character-space direction the elbow bends toward. */ + readonly pole: THREE.Vector3; +} + +export interface FootTarget { + /** Character-space ankle position. */ + readonly position: THREE.Vector3; + /** Character-space horizontal toe direction. */ + readonly toe: THREE.Vector3; + /** Heel lift in radians (foot pitched onto the ball). */ + readonly heel: number; + /** Character-space direction the knee bends toward. */ + readonly pole: THREE.Vector3; +} + +export interface TorsoPose { + /** Hips centre in character space. */ + readonly hips: THREE.Vector3; + readonly hipsYaw: number; + readonly hipsPitch: number; + readonly hipsRoll: number; + /** Shoulder-line yaw relative to the root, distributed over the spine. */ + readonly shouldersYaw: number; + readonly spinePitch: number; + readonly spineRoll: number; + readonly headYaw: number; + readonly headPitch: number; + readonly headRoll: number; + /** Extra head translation (whiplash) in character space. */ + readonly headOffset: THREE.Vector3; +} + +export interface PoseDescription { + readonly torso: TorsoPose; + readonly handL: HandTarget; + readonly handR: HandTarget; + readonly footL: FootTarget; + readonly footR: FootTarget; + /** Clavicle protraction per side (0..1 pushes the shoulder forward and up). */ + readonly shrugL: number; + readonly shrugR: number; +} + +export const HIPS_TO_THIGH = { x: 0.1059, y: 0.0253, z: -0.0026 } as const; +const HIPS_TO_SPINE = 0.0815; +const SPINE_TO_CHEST = 0.2606; +const CHEST_TO_UPPER = 0.1337; +const UPPER_TO_NECK = 0.1923; +const NECK_TO_HEAD = { y: 0.1025, z: 0.0313 } as const; +const CLAVICLE_ROOT = { x: 0.0109, y: 0.1200, z: -0.0006 } as const; +const CLAVICLE_LENGTH = 0.2; +/** Rest arm-root positions in upper-chest space: the left hangs lower and forward. */ +const ARM_ROOT_L = new THREE.Vector3(0.2018, 0.081, -0.027); +const ARM_ROOT_R = new THREE.Vector3(-0.2018, 0.081, -0.027); + +export const vec = (x: number, y: number, z: number): THREE.Vector3 => new THREE.Vector3(x, y, z); +export const lerpVec = (out: THREE.Vector3, a: THREE.Vector3, b: THREE.Vector3, t: number): THREE.Vector3 => out.copy(a).lerp(b, t); +export const smoothstep = (edge0: number, edge1: number, value: number): number => { + const t = THREE.MathUtils.clamp((value - edge0) / Math.max(1e-6, edge1 - edge0), 0, 1); + return t * t * (3 - 2 * t); +}; +export const easeIn = (t: number, power = 1.7): number => Math.pow(THREE.MathUtils.clamp(t, 0, 1), power); +export const easeOut = (t: number, power = 2): number => 1 - Math.pow(1 - THREE.MathUtils.clamp(t, 0, 1), power); + +const rootQuat = new THREE.Quaternion(); +const rootPos = new THREE.Vector3(); +const scratch = new THREE.Vector3(); +const scratchB = new THREE.Vector3(); +const scratchC = new THREE.Vector3(); +const scratchD = new THREE.Vector3(); +const scratchQ = new THREE.Quaternion(); +const scratchQ2 = new THREE.Quaternion(); +const scratchEuler = new THREE.Euler(); +const worldUp = new THREE.Vector3(0, 1, 0); +/** Each spine bone's share of the shoulder twist and of the spine's pitch and roll. */ +const SPINE_SEGMENTS: readonly (readonly [CanonicalBone, number, number])[] = [ + ["spine", 0.25, 0.2], + ["chest", 0.55, 0.5], + ["upperChest", 1.0, 1.0], +]; + +/** Applies a character-space pose to the rig in world space. */ +export class PoseSolver { + private readonly chestLocal = new THREE.Vector3(); + constructor(private readonly rig: SolvedRig) {} + + private toWorld(local: THREE.Vector3, out: THREE.Vector3): THREE.Vector3 { + return out.copy(local).applyQuaternion(rootQuat).add(rootPos); + } + + private dirToWorld(local: THREE.Vector3, out: THREE.Vector3): THREE.Vector3 { + return out.copy(local).applyQuaternion(rootQuat); + } + + private setYawPitchRoll(bone: THREE.Bone, yaw: number, pitch: number, roll: number): void { + scratchEuler.set(pitch, yaw, roll, "YXZ"); + scratchQ.setFromEuler(scratchEuler); + scratchQ2.copy(rootQuat).multiply(scratchQ); + this.rig.setWorldRotation(bone, scratchQ2); + } + + apply(root: THREE.Object3D, pose: PoseDescription): void { + const rig = this.rig; + const bones = rig.bones; + rig.resetToRest(); + root.updateMatrixWorld(true); + worldQuaternion(root, rootQuat); + worldPosition(root, rootPos); + + const torso = pose.torso; + this.toWorld(torso.hips, scratch); + rig.setWorldPosition(bones.hips, scratch); + this.setYawPitchRoll(bones.hips, torso.hipsYaw, torso.hipsPitch, torso.hipsRoll); + const twist = torso.shouldersYaw - torso.hipsYaw; + for (let index = 0; index < SPINE_SEGMENTS.length; index += 1) { + const [name, twistShare, pitchShare] = SPINE_SEGMENTS[index]!; + this.setYawPitchRoll( + bones[name], + torso.hipsYaw + twist * twistShare, + torso.hipsPitch + torso.spinePitch * pitchShare, + torso.hipsRoll + torso.spineRoll * pitchShare, + ); + } + const neckYaw = torso.shouldersYaw + (torso.headYaw - torso.shouldersYaw) * 0.45; + const neckPitch = torso.hipsPitch + torso.spinePitch + (torso.headPitch - torso.spinePitch) * 0.5; + this.setYawPitchRoll(bones.neck, neckYaw, neckPitch, torso.hipsRoll + torso.spineRoll * 0.6 + torso.headRoll * 0.4); + this.setYawPitchRoll(bones.head, torso.headYaw, torso.headPitch, torso.headRoll); + if (torso.headOffset.lengthSq() > 0) { + worldPosition(bones.head, scratch); + this.dirToWorld(torso.headOffset, scratchB); + scratch.add(scratchB); + rig.setWorldPosition(bones.head, scratch); + } + + this.solveArm("L", pose.handL, pose.shrugL); + this.solveArm("R", pose.handR, pose.shrugR); + this.solveLeg("L", pose.footL); + this.solveLeg("R", pose.footR); + } + + private solveArm(side: "L" | "R", hand: HandTarget, shrug: number): void { + const rig = this.rig; + const bones = rig.bones; + const clavicle = side === "L" ? bones.clavicleL : bones.clavicleR; + const shoulder = side === "L" ? bones.shoulderL : bones.shoulderR; + const elbow = side === "L" ? bones.elbowL : bones.elbowR; + const glove = side === "L" ? bones.gloveL : bones.gloveR; + const lengths = side === "L" ? rig.metrics.armL : rig.metrics.armR; + const restRoot = side === "L" ? ARM_ROOT_L : ARM_ROOT_R; + // Clavicle: aim at the rest arm root (upper-chest space) pushed forward and up by the shrug. + this.chestLocal.copy(restRoot); + this.chestLocal.z += shrug * 0.06; + this.chestLocal.y += shrug * 0.035; + this.chestLocal.x *= 1 - shrug * 0.08; + scratchC.copy(this.chestLocal).multiplyScalar(rig.metrics.unitsPerMeter); + bones.upperChest.localToWorld(scratchC); + rig.aimAt(clavicle, scratchC, "z"); + shoulder.updateWorldMatrix(false, false); + this.toWorld(hand.position, scratch); + this.dirToWorld(hand.pole, scratchB); + rig.solveLimb(shoulder, elbow, lengths, scratch, scratchB, "z", side === "L" ? 1 : -1, 0.012); + glove.updateWorldMatrix(false, false); + this.dirToWorld(hand.knuckles, scratchC); + this.dirToWorld(hand.palm, scratchD); + rig.setWorldFrame(glove, scratchC, scratchD, "z"); + void CLAVICLE_ROOT; + void CLAVICLE_LENGTH; + } + + private solveLeg(side: "L" | "R", foot: FootTarget): void { + const rig = this.rig; + const bones = rig.bones; + const hip = side === "L" ? bones.hipL : bones.hipR; + const knee = side === "L" ? bones.kneeL : bones.kneeR; + const ankle = side === "L" ? bones.ankleL : bones.ankleR; + const toe = side === "L" ? bones.toeL : bones.toeR; + const lengths = side === "L" ? rig.metrics.legL : rig.metrics.legR; + this.toWorld(foot.position, scratch); + this.dirToWorld(foot.toe, scratchC).normalize(); + // Foot: +Y runs from the ankle down to the toe base, pitched by the heel lift. + const footLength = rig.metrics.footLength; + scratchD.copy(scratchC).multiplyScalar(footLength).addScaledVector(worldUp, -rig.metrics.ankleHeight).normalize(); + if (foot.heel !== 0) { + // Pivot on the ball of the foot: the toe base stays where the flat foot puts it while the ankle rises + // and drifts forward around it. + scratch.addScaledVector(scratchD, footLength); + scratchQ.setFromAxisAngle(scratchB.crossVectors(scratchC, worldUp).normalize(), -foot.heel); + scratchD.applyQuaternion(scratchQ); + scratch.addScaledVector(scratchD, -footLength); + } + this.dirToWorld(foot.pole, scratchB); + rig.solveLimb(hip, knee, lengths, scratch, scratchB, "x", -1, 0.02); + ankle.updateWorldMatrix(false, false); + rig.setWorldFrame(ankle, scratchD, worldUp, "z"); + toe.updateWorldMatrix(false, false); + // The toes bend at the ball, so they stay flat on the canvas however far the heel is raised. + rig.setWorldFrame(toe, scratchC, worldUp, "z"); + } +} + +/** Constants describing the authored orthodox stance in character space. */ +export const STANCE = { + bladeYaw: -1.05, + hipsHeight: 0.8, + leadFoot: vec(0.12, 0, 0.24), + rearFoot: vec(-0.1, 0, -0.34), + leadToe: vec(-0.34, 0, 0.94), + rearToe: vec(-0.77, 0, 0.64), + /** Hand offsets relative to the head bone. */ + relaxedLead: vec(0.11, -0.22, 0.36), + relaxedRear: vec(-0.11, -0.16, 0.1), + guardHighLead: vec(0.14, -0.02, 0.17), + guardHighRear: vec(-0.1, -0.02, 0.11), + guardLowLead: vec(0.15, -0.36, 0.22), + guardLowRear: vec(-0.13, -0.34, 0.12), + leadPole: vec(0.45, -1, 0.2), + rearPole: vec(-0.5, -1, -0.05), + leadKnuckles: vec(0.1, 0.55, 0.8), + leadPalm: vec(-0.9, 0.15, -0.35), + rearKnuckles: vec(-0.05, 0.7, 0.7), + rearPalm: vec(0.95, 0.1, -0.25), +} as const; + +export function mirrorX(v: THREE.Vector3, mirror: number, out = new THREE.Vector3()): THREE.Vector3 { + return out.set(v.x * mirror, v.y, v.z); +} diff --git a/web/hands/src/render/punch-aim.test.ts b/web/hands/src/render/punch-aim.test.ts new file mode 100644 index 00000000..cd56601a --- /dev/null +++ b/web/hands/src/render/punch-aim.test.ts @@ -0,0 +1,189 @@ +import * as THREE from "three"; +import { GLOVE_HITBOX_RADIUS, HURTBOXES, punchTiming } from "../manifest"; +import { fighter as baseFighter } from "../test/fixtures"; +import type { DefensivePose, FighterSnapshot, Hand, PunchClass, Target } from "../types"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb } from "./graph"; +import { worldPosition } from "./rig"; +import { worldMapping } from "./world"; + +const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); +const gltf = await loadBoxerGlb(); + +/** Where the glove's centre stops short of the aimed point: the head and glove hurtboxes, overlapped for visible contact. */ +const STAND_OFF = HURTBOXES.head.radius + GLOVE_HITBOX_RADIUS - 0.06; + +const facingOpponent = (fighter: FighterSnapshot): FighterSnapshot => ({ ...fighter, facing_x: 0, facing_y: -1000, x: 0, y: 0 }); +const opponentAt = (units: number): FighterSnapshot => ({ ...baseFighter("two"), x: 0, y: -units, facing_x: 0, facing_y: 1000 }); +/** The fighter stands at the origin facing world +z, so character space and world space coincide. */ +const handTarget = (graph: BoxingGraph, hand: Hand): THREE.Vector3 => + (graph as unknown as { hand: Record<"L" | "R", { position: THREE.Vector3 }> }).hand[hand === "left" ? "L" : "R"].position; + +/** + * Plays a server punch of `punchClass` at an opponent `units` away and returns the punching hand's IK + * target at every frame through the startup, ending on the contact age, and through the active phase + * after it, with the point it aims at. + */ +function throwPunch(punchClass: PunchClass, hand: Hand, target: Target, units: number): { path: THREE.Vector3[]; active: THREE.Vector3[]; aim: THREE.Vector3 } { + const graph = new BoxingGraph(new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }), mapping); + const opponent = opponentAt(units); + const head = new THREE.Vector3(0, 1.5, mapping.z(-units)); + const idle = facingOpponent(baseFighter("one")); + for (let frame = 0; frame < 20; frame += 1) graph.update(idle, opponent, 1 / 60, frame / 60, false, "full", frame / 2, head); + const timing = punchTiming(punchClass, target, "normal"); + const punch: FighterSnapshot = { + ...idle, action: punchClass, action_hand: hand, action_target: target, action_power: "normal", action_id: "p1", action_key: `${punchClass}:${hand}:${target}:normal`, + action_start_tick: 100, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + const path: THREE.Vector3[] = []; + const active: THREE.Vector3[] = []; + // Each frame advances the punch half a tick from the authoritative age, so frame 2 * startup - 1 sits on the contact age. + for (let frame = 0; frame < (timing.startup + timing.active) * 2; frame += 1) { + graph.update(punch, opponent, 1 / 60, 1 + frame / 60, false, "full", 100 + (frame - 1) / 2, head); + (frame < timing.startup * 2 ? path : active).push(handTarget(graph, hand).clone()); + } + return { path, active, aim: head.clone().setY(head.y - (target === "body" ? 0.42 : 0.04)) }; +} + +describe("hook sweep", () => { + it("ends the sweep on its own contact point instead of a fixed wider radius", () => { + for (const [hand, target, units] of [["left", "head", 124], ["left", "body", 110], ["right", "head", 124]] as const) { + const { path, aim } = throwPunch("hook", hand, target, units); + expect(path.at(-1)!.distanceTo(aim), `${hand} hook to the ${target} at ${units}`).toBeCloseTo(STAND_OFF, 2); + } + }); +}); + +describe("close range punches", () => { + it("shorten instead of driving the glove past the contact point into the face", () => { + for (const [punchClass, hand, units] of [["jab", "left", 76], ["jab", "left", 100], ["straight", "right", 76], ["straight", "right", 100]] as const) { + const { path, active, aim } = throwPunch(punchClass, hand, "head", units); + const label = `${punchClass} at ${units}`; + expect(path.at(-1)!.distanceTo(aim), label).toBeCloseTo(STAND_OFF, 2); + for (const glove of active) expect(glove.distanceTo(aim), label).toBeGreaterThan(STAND_OFF - 0.005); + } + }); +}); + +describe("punch pose allocations", () => { + it("clones no vectors per frame for any punch beyond what an idle frame does", () => { + const graph = new BoxingGraph(new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }), mapping); + const opponent = opponentAt(120); + const head = new THREE.Vector3(0, 1.5, mapping.z(-120)); + const idle = facingOpponent(baseFighter("one")); + let tick = 0; + const frames = (fighter: FighterSnapshot, count: number): number => { + const clones = vi.spyOn(THREE.Vector3.prototype, "clone"); + for (let frame = 0; frame < count; frame += 1) { + tick += 0.5; + graph.update(fighter, opponent, 1 / 60, tick / 30, false, "full", tick, head); + } + const calls = clones.mock.calls.length; + clones.mockRestore(); + return calls; + }; + frames(idle, 20); + const perIdleFrame = frames(idle, 30) / 30; + for (const punchClass of ["jab", "straight", "hook", "uppercut"] as const) { + const timing = punchTiming(punchClass, "head", "normal"); + const punch: FighterSnapshot = { + ...idle, action: punchClass, action_hand: "left", action_target: "head", action_power: "normal", action_id: `a-${punchClass}`, action_key: `${punchClass}:left:head:normal`, + action_start_tick: tick, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + const count = (timing.startup + timing.active + timing.recovery) * 2 - 2; + expect(frames(punch, count) / count, punchClass).toBe(perIdleFrame); + } + }); +}); + +describe("punches at an evading head", () => { + /** + * Throws a left `punchClass` at a defender `units` away who goes into `defense` the tick after it + * starts, with two graphs handing each other their heads a frame late as the renderer does. Returns + * the glove and the defender's head at the contact tick. `connects` reports a hit for the punch, as + * the server does when the evasion was the wrong one. + */ + function throwAt(punchClass: PunchClass, defense: DefensivePose, units: number, connects: boolean): { glove: THREE.Vector3; head: THREE.Vector3 } { + const attacker = new BoxingGraph(new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }), mapping); + const defender = new BoxingGraph(new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0xb91c1c }), mapping); + const attackerIdle = facingOpponent(baseFighter("one")); + const defenderIdle = opponentAt(units); + const timing = punchTiming(punchClass, "head", "normal"); + const start = 100; + const punch: FighterSnapshot = { + ...attackerIdle, action: punchClass, action_hand: "left", action_target: "head", action_power: "normal", action_id: "p1", action_key: `${punchClass}:left:head:normal`, + action_start_tick: start, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + const hit = { event_id: 3, tick: start + timing.startup, kind: "hit", actor_id: "one", target_id: "two", amount: 30, detail: `${punchClass}:head`, blood: 0, direction: 1, action_id: "p1" }; + const attackerHead = new THREE.Vector3(); + const defenderHead = new THREE.Vector3(); + const glove = new THREE.Vector3(); + for (let tick = start - 10; tick <= start + timing.startup; tick += 0.5) { + const shownAttacker = tick >= start ? punch : attackerIdle; + const shownDefender = tick >= start + 1 && tick < start + 11 ? { ...defenderIdle, defense } : defenderIdle; + // The newest snapshot reaches the client a couple of ticks before the contact is shown. + if (connects && tick === start + timing.startup - 2) attacker.acknowledge(punch, true, [hit]); + attacker.update(shownAttacker, shownDefender, 1 / 60, tick / 30, false, "full", tick, tick > start - 10 ? defenderHead : undefined); + defender.update(shownDefender, shownAttacker, 1 / 60, tick / 30, false, "full", tick, tick > start - 10 ? attackerHead : undefined); + attacker.boxer.root.updateMatrixWorld(true); + defender.boxer.root.updateMatrixWorld(true); + worldPosition(attacker.boxer.rig.bones.head, attackerHead); + worldPosition(defender.boxer.rig.bones.head, defenderHead); + worldPosition(attacker.boxer.rig.bones.gloveL, glove); + } + return { glove, head: defenderHead }; + } + + it("sends the glove where the head was when a slip or weave worked, and after the head when the punch still connected", () => { + const cleanJab = throwAt("jab", "none", 150, true); + const cleanReach = cleanJab.glove.distanceTo(cleanJab.head); + // A left jab is slipped to the defender's right: the glove goes where it would have met him and misses. + const slipped = throwAt("jab", "slip_right", 150, false); + expect(slipped.glove.distanceTo(cleanJab.glove)).toBeLessThan(0.02); + expect(slipped.glove.distanceTo(slipped.head)).toBeGreaterThan(cleanReach + 0.08); + // Slipping left does not get away from it: the server reports the hit and the glove follows the head. + const caught = throwAt("jab", "slip_left", 150, true); + expect(Math.abs(caught.glove.distanceTo(caught.head) - cleanReach)).toBeLessThan(0.05); + // A weave ducks a hook: the glove ends where it would on a defender standing still, never deeper. + const cleanHook = throwAt("hook", "none", 110, true); + const weaved = throwAt("hook", "weave", 110, false); + expect(weaved.glove.distanceTo(cleanHook.glove)).toBeLessThan(0.02); + expect(weaved.glove.distanceTo(weaved.head)).toBeGreaterThan(cleanHook.glove.distanceTo(cleanHook.head)); + }); +}); + +describe("punch onset", () => { + it("starts every punch from the guard and eases into the windup instead of jumping on its first frame", () => { + for (const punchClass of ["jab", "straight", "hook", "uppercut"] as const) { + for (const hand of ["left", "right"] as const) { + const graph = new BoxingGraph(new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }), mapping); + const opponent = opponentAt(120); + const head = new THREE.Vector3(0, 1.5, mapping.z(-120)); + const idle = facingOpponent(baseFighter("one")); + const timing = punchTiming(punchClass, "head", "normal"); + const punch: FighterSnapshot = { + ...idle, action: punchClass, action_hand: hand, action_target: "head", action_power: "normal", action_id: "p1", action_key: `${punchClass}:${hand}:head:normal`, + action_start_tick: 100, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + const bones = hand === "left" ? (["gloveL", "elbowL"] as const) : (["gloveR", "elbowR"] as const); + const last = bones.map(() => new THREE.Vector3()); + const now = new THREE.Vector3(); + // Glove and elbow travel on each of the punch's first four frames, out of the guard into the windup. + const moves: number[] = []; + for (let tick = 90; tick < 102; tick += 0.5) { + graph.update(tick < 100 ? idle : punch, opponent, 1 / 60, tick / 30, false, "full", tick - 0.5, head); + graph.boxer.root.updateMatrixWorld(true); + const step = Math.max(...bones.map((name, index) => { + const travel = worldPosition(graph.boxer.rig.bones[name], now).distanceTo(last[index]!); + last[index]!.copy(now); + return travel; + })); + if (tick >= 100) moves.push(step); + } + expect(moves[0], `${hand} ${punchClass} first frame`).toBeLessThan(0.05); + // No faster than the punches themselves move near contact, and building up rather than starting there. + expect(Math.max(...moves), `${hand} ${punchClass} windup`).toBeLessThan(0.15); + expect(moves[0]!, `${hand} ${punchClass} eases in`).toBeLessThan(Math.max(...moves)); + } + } + }); +}); diff --git a/web/hands/src/render/punch-prediction.test.ts b/web/hands/src/render/punch-prediction.test.ts new file mode 100644 index 00000000..b2238b7a --- /dev/null +++ b/web/hands/src/render/punch-prediction.test.ts @@ -0,0 +1,337 @@ +import * as THREE from "three"; +import { predictedPunchTiming } from "../prediction"; +import { fighter as baseFighter } from "../test/fixtures"; +import type { FighterSnapshot, PunchAction, PunchClass } from "../types"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb } from "./graph"; +import { worldMapping } from "./world"; + +const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); +const gltf = await loadBoxerGlb(); + +const idle: FighterSnapshot = { ...baseFighter("one"), facing_x: 0, facing_y: -1000, x: 0, y: 0, stance: "orthodox", last_input_sequence: 40 }; +const opponent: FighterSnapshot = { ...baseFighter("two"), x: 0, y: -150, facing_x: 0, facing_y: 1000 }; +const head = new THREE.Vector3(0, 1.5, mapping.z(-150)); +/** The render clock trails the newest snapshot by this much, the rest of the lead being the input round trip. */ +const INTERPOLATION_TICKS = 2; + +interface PunchState { punchActive: boolean; punchAgeTicks: number; ownActionId: string | null; punchClass: PunchClass } +const state = (graph: BoxingGraph): PunchState => graph as unknown as PunchState; + +function makeGraph(): BoxingGraph { + const graph = new BoxingGraph(new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }), mapping); + for (let frame = 0; frame < 10; frame += 1) graph.update(idle, opponent, 1 / 60, frame / 60, false, "full", frame / 2, head); + return graph; +} + +const press = (id: string, punchClass: PunchClass, hand: "left" | "right"): PunchAction => ({ kind: "punch", id, class: punchClass, hand, target: "head", power: "normal" }); + +/** The input frames presses went out in, looked up by press id as the network does once a frame is sent. */ +function frames(): { sent: Map; sequenceOf: (actionId: string) => number | null } { + const sent = new Map(); + return { sent, sequenceOf: (actionId) => sent.get(actionId) ?? null }; +} + +/** Steps the graph one 60 fps frame on the delayed snapshot `shown`, starting from tick `from`. */ +function stepper(graph: BoxingGraph, from: number): (shown: FighterSnapshot) => number { + let tick = from; + return (shown) => { + tick += 0.5; + graph.update(shown, opponent, 1 / 60, tick / 30, false, "full", tick, head); + return tick; + }; +} + +describe("own punch the server refuses", () => { + for (const [punchClass, hand] of [["jab", "left"], ["straight", "right"]] as const) { + for (const lead of [2.6, 3.8, 8.6]) { + it(`pulls a ${punchClass} back before contact once the frame that carried it is acknowledged, at a lead of ${lead} ticks`, () => { + const graph = makeGraph(); + const { sent, sequenceOf } = frames(); + const action = press("own-1", punchClass, hand); + const timing = predictedPunchTiming(idle, action); + graph.predict(action, 0, 30, lead, timing); + sent.set("own-1", 41); + const step = stepper(graph, 100); + const ackFrame = Math.round((lead - INTERPOLATION_TICKS) * 2); + const ages: number[] = []; + for (let frame = 0; state(graph).punchActive && frame < 120; frame += 1) { + // The server took the frame but never started the punch: no action, nothing queued. + graph.acknowledge({ ...idle, last_input_sequence: frame >= ackFrame ? 41 : 40 }, true, [], sequenceOf); + step(idle); + if (state(graph).punchActive) ages.push(state(graph).punchAgeTicks); + } + expect(state(graph).punchActive).toBe(false); + expect(Math.max(...ages)).toBeLessThan(timing.startup); + const peak = ages.indexOf(Math.max(...ages)); + expect(peak).toBeLessThanOrEqual(ackFrame + 1); + for (let index = peak + 1; index < ages.length; index += 1) expect(ages[index]!).toBeLessThan(ages[index - 1]!); + }); + } + } + + it("keeps a punch the server has queued behind another, then lets it play once started", () => { + const graph = makeGraph(); + const { sent, sequenceOf } = frames(); + const action = press("own-1", "jab", "left"); + graph.predict(action, 0, 30, 4, predictedPunchTiming(idle, action)); + sent.set("own-1", 41); + const step = stepper(graph, 100); + for (let frame = 0; frame < 4; frame += 1) { + graph.acknowledge({ ...idle, last_input_sequence: 41, queued_actions: 1 }, true, [], sequenceOf); + step(idle); + } + graph.acknowledge({ ...idle, last_input_sequence: 41, action: "jab", action_id: "own-1" }, true, [], sequenceOf); + // The press started and finished there; later snapshots no longer show it. + graph.acknowledge({ ...idle, last_input_sequence: 43 }, true, [], sequenceOf); + for (let frame = 0; frame < 4; frame += 1) step(idle); + expect(state(graph).punchActive).toBe(true); + expect(state(graph).ownActionId).toBe("own-1"); + expect((graph as unknown as { ownPulled: boolean }).ownPulled).toBe(false); + }); + + it("does not judge a press before the frame carrying it has gone out", () => { + const graph = makeGraph(); + const { sent, sequenceOf } = frames(); + const action = press("own-1", "jab", "left"); + graph.predict(action, 0, 30, 4, predictedPunchTiming(idle, action)); + const step = stepper(graph, 100); + // Snapshots acknowledging earlier frames say nothing about this press. + graph.acknowledge({ ...idle, last_input_sequence: 99 }, true, [], sequenceOf); + step(idle); + expect((graph as unknown as { ownPulled: boolean }).ownPulled).toBe(false); + sent.set("own-1", 100); + graph.acknowledge({ ...idle, last_input_sequence: 100 }, true, [], sequenceOf); + expect((graph as unknown as { ownPulled: boolean }).ownPulled).toBe(true); + }); + + it("pulls the glove back at once when the server shows the fighter stunned", () => { + const graph = makeGraph(); + const action = press("own-1", "jab", "left"); + const timing = predictedPunchTiming(idle, action); + graph.predict(action, 0, 30, 6, timing); + const step = stepper(graph, 100); + step(idle); + step(idle); + const before = state(graph).punchAgeTicks; + graph.acknowledge({ ...idle, last_input_sequence: 40, stunned_ticks: 12 }, true); + step(idle); + expect(state(graph).punchAgeTicks).toBeLessThan(before); + let frames = 0; + while (state(graph).punchActive && frames < 60) { step(idle); frames += 1; } + expect(state(graph).punchActive).toBe(false); + }); + + it("pulls back a started punch a stun cuts off before contact, and the late confirmation does not throw it again", () => { + const graph = makeGraph(); + const action = press("own-1", "jab", "left"); + const timing = predictedPunchTiming(idle, action); + graph.predict(action, 0, 30, 6, timing); + const step = stepper(graph, 100); + for (let frame = 0; frame < 3; frame += 1) step(idle); + const thrown: FighterSnapshot = { + ...idle, last_input_sequence: 41, action: "jab", action_hand: "left", action_target: "head", action_power: "normal", action_id: "own-1", action_key: "jab:left:head:normal", + action_start_tick: 101, action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; + graph.acknowledge(thrown, true); + graph.acknowledge({ ...thrown, stunned_ticks: 40 }, true); + const ages: number[] = [state(graph).punchAgeTicks]; + // The delayed snapshot on screen now shows the punch starting, before the stun reaches it. + while (state(graph).punchActive && ages.length < 60) { + step(thrown); + if (state(graph).punchActive) ages.push(state(graph).punchAgeTicks); + } + expect(state(graph).punchActive).toBe(false); + expect(Math.max(...ages)).toBeLessThan(timing.startup); + for (let index = 1; index < ages.length; index += 1) expect(ages[index]!).toBeLessThanOrEqual(ages[index - 1]!); + step(thrown); + expect(state(graph).punchActive).toBe(false); + }); + + it("lets a started punch that already landed finish when a stun or the bell follows", () => { + const graph = makeGraph(); + const action = press("own-1", "jab", "left"); + const timing = predictedPunchTiming(idle, action); + graph.predict(action, 0, 30, 2, timing); + const step = stepper(graph, 100); + for (let frame = 0; frame < 4; frame += 1) step(idle); + graph.acknowledge({ ...idle, last_input_sequence: 41, action: "jab", action_id: "own-1", action_contact_tick: 104, stunned_ticks: 30 }, false); + expect((graph as unknown as { ownPulled: boolean }).ownPulled).toBe(false); + }); +}); + +const serverPunch = (base: FighterSnapshot, id: string, action: PunchAction, startTick: number): FighterSnapshot => { + const timing = predictedPunchTiming(base, action); + return { + ...base, action: action.class, action_hand: action.hand, action_target: action.target, action_power: action.power, action_id: id, + action_key: `${action.class}:${action.hand}:${action.target}:${action.power}`, action_start_tick: startTick, + action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + }; +}; + +describe("two presses inside one server tick", () => { + const jab = press("own-1", "jab", "left"); + const straight = press("own-2", "straight", "right"); + + it("switches to the newer press once it goes out in the frame the first never made, as the server only ever sees that one", () => { + const graph = makeGraph(); + const { sent, sequenceOf } = frames(); + graph.predict(jab, 10, 30, 4, predictedPunchTiming(idle, jab)); + // Too long after the jab to replace it outright; both wait for the same flush, which sends only the straight. + graph.predict(straight, 10 + 0.6 / 30, 30, 4, predictedPunchTiming(idle, straight)); + expect(state(graph).ownActionId).toBe("own-1"); + sent.set("own-2", 41); + graph.acknowledge({ ...idle, last_input_sequence: 40 }, true, [], sequenceOf); + expect(state(graph).punchClass).toBe("straight"); + expect(state(graph).ownActionId).toBe("own-2"); + }); + + it("predicts the newer press when it comes less than half a tick after the first, in the next frame", () => { + const graph = makeGraph(); + graph.predict(jab, 10, 30, 4, predictedPunchTiming(idle, jab)); + graph.predict(straight, 10 + 0.4 / 30, 30, 4, predictedPunchTiming(idle, straight)); + expect(state(graph).punchClass).toBe("straight"); + expect(state(graph).ownActionId).toBe("own-2"); + }); + + it("keeps the first press once a tick has gone by, or once the server shows it started", () => { + const later = makeGraph(); + later.predict(jab, 10, 30, 4, predictedPunchTiming(idle, jab)); + const step = stepper(later, 100); + step(idle); + step(idle); + later.predict(straight, 10 + 1 / 30, 30, 4, predictedPunchTiming(idle, straight)); + expect(state(later).punchClass).toBe("jab"); + expect(state(later).ownActionId).toBe("own-1"); + const started = makeGraph(); + started.predict(jab, 10, 30, 4, predictedPunchTiming(idle, jab)); + started.acknowledge(serverPunch({ ...idle, last_input_sequence: 41 }, "own-1", jab, 100), true); + started.predict(straight, 10 + 0.4 / 30, 30, 4, predictedPunchTiming(idle, straight)); + expect(state(started).ownActionId).toBe("own-1"); + }); + + it("never snaps the glove back when the server confirms the newer press, and plays the first if the server threw it after all", () => { + const graph = makeGraph(); + graph.predict(jab, 10, 30, 4, predictedPunchTiming(idle, jab)); + graph.predict(straight, 10.005, 30, 4, predictedPunchTiming(idle, straight)); + const step = stepper(graph, 100); + const ages: number[] = []; + for (let frame = 0; frame < 4; frame += 1) { step(idle); ages.push(state(graph).punchAgeTicks); } + const confirmed = serverPunch(idle, "own-2", straight, 101); + for (let frame = 0; frame < 10; frame += 1) { + step(confirmed); + expect(state(graph).ownActionId).toBe("own-2"); + expect((graph as unknown as { punchHand: string }).punchHand).toBe("right"); + ages.push(state(graph).punchAgeTicks); + } + for (let index = 1; index < ages.length; index += 1) expect(ages[index]!).toBeGreaterThanOrEqual(ages[index - 1]!); + const other = makeGraph(); + other.predict(jab, 10, 30, 4, predictedPunchTiming(idle, jab)); + other.predict(straight, 10.005, 30, 4, predictedPunchTiming(idle, straight)); + stepper(other, 200)(serverPunch(idle, "own-1", jab, 199)); + expect(state(other).punchClass).toBe("jab"); + expect(state(other).punchActive).toBe(true); + }); +}); + +describe("follow-up pressed during a punch", () => { + const straight = press("s1", "straight", "right"); + const hook = press("own-hook", "hook", "left"); + const straightTiming = predictedPunchTiming(idle, straight); + const hookTiming = predictedPunchTiming(idle, hook); + const T0 = 300; + const thrown = serverPunch(idle, "s1", straight, T0); + const contact = (kind: string, actionId = "s1") => ({ event_id: 7, tick: T0 + 6, kind, actor_id: kind.includes("block") ? "two" : "one", target_id: kind.includes("block") ? "one" : "two", amount: 30, detail: "straight:head", blood: 0, direction: 1, action_id: actionId }); + + /** + * Plays a straight from T0 and presses a hook at `pressAge` with a lead of 4 ticks; the snapshots + * on screen show the server's hook from `serverStart`. Returns the tick at which the graph first + * plays the hook and the tick at which it reaches contact. + */ + function followUp(serverStart: number, options: { contacts?: ReturnType[]; stunnedUntil?: number; pressAge?: number } = {}): { start: number; contact: number } { + const graph = makeGraph(); + const pressAge = options.pressAge ?? 10; + const served = serverPunch(idle, "own-hook", hook, serverStart); + let tick = T0 - 0.5; + let start = NaN; + let reached = NaN; + graph.acknowledge(thrown, true, options.contacts ?? []); + for (let frame = 0; frame < 120 && Number.isNaN(reached); frame += 1) { + tick += 0.5; + const opposite = { ...opponent, stunned_ticks: tick < (options.stunnedUntil ?? -Infinity) ? 20 : 0 }; + graph.update(tick < serverStart ? thrown : served, opposite, 1 / 60, tick / 30, false, "full", tick, head); + if (tick === T0 + pressAge) graph.predict(hook, tick / 30, 30, 4, hookTiming); + if (state(graph).ownActionId !== "own-hook") continue; + if (Number.isNaN(start)) start = tick; + if (state(graph).punchAgeTicks >= hookTiming.startup) reached = tick; + } + return { start, contact: reached }; + } + const near = (actual: number, expected: number): void => expect(Math.abs(actual - expected)).toBeLessThanOrEqual(1); + + it("waits for a whiffed straight to end and starts the hook the tick after, as the engine does", () => { + expect(straightTiming).toMatchObject({ startup: 6, active: 2, recovery: 10 }); + // Pressed at 56% of the straight, the engine starts the hook at T0 + 19 and lands it 7 ticks later. + const { start, contact: reached } = followUp(T0 + 19); + expect(start).toBeGreaterThanOrEqual(T0 + 17.5); + near(reached, T0 + 19 + hookTiming.startup); + }); + + it("cuts a landed straight's recovery short at its cancel age, or when the press arrives after it", () => { + // Cancel age 6 + 2 + 5: pressed at age 8 the hook reaches the server before it and starts there. + near(followUp(T0 + 13, { contacts: [contact("hit")], pressAge: 8 }).contact, T0 + 13 + hookTiming.startup); + // Pressed at age 10 with a lead of 4 it reaches the server at T0 + 14 and starts at once. + near(followUp(T0 + 14, { contacts: [contact("hit")], pressAge: 10 }).contact, T0 + 14 + hookTiming.startup); + // An ordinary block lets the combination through too. + near(followUp(T0 + 13, { contacts: [contact("block"), contact("hit")], pressAge: 8 }).contact, T0 + 13 + hookTiming.startup); + }); + + it("does not cut the recovery short for a parried straight or a contact that belongs to another punch", () => { + for (const contacts of [[contact("perfect_block"), contact("hit")], [contact("hit", "s0")]]) { + const { start, contact: reached } = followUp(T0 + 19, { contacts, pressAge: 8 }); + expect(start).toBeGreaterThanOrEqual(T0 + 17.5); + near(reached, T0 + 19 + hookTiming.startup); + } + }); + + it("holds the follow-up while the defender is stunned and cuts in once he is not", () => { + const { start, contact: reached } = followUp(T0 + 15, { contacts: [contact("hit")], pressAge: 8, stunnedUntil: T0 + 15 }); + expect(start).toBeGreaterThanOrEqual(T0 + 15); + near(reached, T0 + 15 + hookTiming.startup); + const held = followUp(T0 + 19, { contacts: [contact("hit")], pressAge: 8, stunnedUntil: T0 + 40 }); + expect(held.start).toBeGreaterThanOrEqual(T0 + 17.5); + near(held.contact, T0 + 19 + hookTiming.startup); + }); + + it("plays the held press from the server's timeline when the server starts it sooner than expected", () => { + // No contact reached the client, so the graph expects the hook after the straight; the server cut in at T0 + 14. + const { start, contact: reached } = followUp(T0 + 14, { pressAge: 10 }); + expect(start).toBe(T0 + 14); + near(reached, T0 + 14 + hookTiming.startup); + }); + + it("keeps only the newest held press while the punch in front still holds it, and forgets one the server drops", () => { + const graph = makeGraph(); + const step = stepper(graph, T0 - 0.5); + let tick = T0; + while (tick < T0 + 8) tick = step(thrown); + graph.predict(hook, tick / 30, 30, 4, hookTiming); + const uppercut = press("own-upper", "uppercut", "right"); + graph.predict(uppercut, tick / 30 + 0.1, 30, 4, predictedPunchTiming(idle, uppercut)); + while (tick < T0 + 16) tick = step(thrown); + // Three ticks from the end, a press arrives after the held one has started: it is not predicted. + graph.predict(press("own-late", "jab", "left"), tick / 30, 30, 4, predictedPunchTiming(idle, press("own-late", "jab", "left"))); + while (tick < T0 + 19.5) tick = step(thrown); + expect(state(graph).ownActionId).toBe("own-upper"); + expect(state(graph).punchClass).toBe("uppercut"); + const dropped = makeGraph(); + const next = stepper(dropped, T0 - 0.5); + tick = T0; + while (tick < T0 + 8) tick = next(thrown); + dropped.predict(hook, tick / 30, 30, 4, hookTiming); + // The server got the frame and holds nothing: a guard raised in the same tick cleared it. + dropped.acknowledge({ ...thrown, last_input_sequence: 51, queued_actions: 0 }, true, [], (actionId) => (actionId === "own-hook" ? 51 : null)); + while (tick < T0 + 24) tick = next(thrown); + expect(state(dropped).ownActionId).toBeNull(); + expect(state(dropped).punchClass).toBe("straight"); + }); +}); diff --git a/web/hands/src/render/quality.test.ts b/web/hands/src/render/quality.test.ts new file mode 100644 index 00000000..847041cf --- /dev/null +++ b/web/hands/src/render/quality.test.ts @@ -0,0 +1,107 @@ +import { describe, expect, it } from "vitest"; +import { ResolutionScaler } from "./quality"; + +function feed(scaler: ResolutionScaler, frameMs: number, count: number): number { + let changes = 0; + for (let index = 0; index < count; index += 1) if (scaler.record(frameMs)) changes += 1; + return changes; +} + +describe("ResolutionScaler", () => { + it("starts at full scale and ignores frames while a window is still filling", () => { + const scaler = new ResolutionScaler(); + expect(scaler.scale).toBe(1); + expect(feed(scaler, 33, 20)).toBe(0); + expect(scaler.scale).toBe(1); + }); + + it("steps down after a slow window and keeps the step when frames get faster", () => { + const scaler = new ResolutionScaler(); + expect(feed(scaler, 40, 25)).toBe(1); + expect(scaler.scale).toBeCloseTo(0.85); + expect(feed(scaler, 30, 34)).toBe(1); + expect(scaler.scale).toBeCloseTo(0.7); + }); + + it("reverts a downscale that did not speed the next window up and holds off with backoff", () => { + const scaler = new ResolutionScaler(); + feed(scaler, 40, 25); + expect(scaler.scale).toBeCloseTo(0.85); + expect(feed(scaler, 40, 25)).toBe(1); + expect(scaler.scale).toBe(1); + expect(feed(scaler, 40, 25 * 10)).toBe(0); + expect(feed(scaler, 40, 25)).toBe(1); + expect(scaler.scale).toBeCloseTo(0.85); + expect(feed(scaler, 40, 25)).toBe(1); + expect(scaler.scale).toBe(1); + expect(feed(scaler, 40, 25 * 20)).toBe(0); + expect(feed(scaler, 40, 25)).toBe(1); + expect(scaler.scale).toBeCloseTo(0.85); + }); + + it("never drops below the minimum or rises above the maximum", () => { + const scaler = new ResolutionScaler({ maximum: 1, minimum: 0.55, slowMs: 24, fastMs: 17.5, windowMs: 1000, step: 0.15 }); + const slow = [60, 50, 40, 32, 26]; + for (const frameMs of slow) feed(scaler, frameMs, Math.ceil(1000 / frameMs) + 1); + expect(scaler.scale).toBeCloseTo(0.55); + feed(scaler, 25, 41); + expect(scaler.scale).toBeCloseTo(0.55); + feed(scaler, 16, 63 * 12); + expect(scaler.scale).toBe(1); + }); + + it("needs three consecutive fast windows before raising the scale", () => { + const scaler = new ResolutionScaler(); + feed(scaler, 40, 25); + feed(scaler, 30, 34); + expect(scaler.scale).toBeCloseTo(0.7); + expect(feed(scaler, 16, 63 * 2)).toBe(0); + feed(scaler, 20, 51); + expect(feed(scaler, 16, 63 * 2)).toBe(0); + expect(feed(scaler, 16, 63)).toBe(1); + expect(scaler.scale).toBeCloseTo(0.85); + }); + + it("settles one step down on a client that needs exactly one step instead of pumping between two scales", () => { + // 26 ms a frame at full resolution and a steady 60 fps one step down, for two minutes. + const scaler = new ResolutionScaler(); + let changes = 0; + let slowMs = 0; + for (let elapsed = 0; elapsed < 120_000;) { + const frameMs = scaler.scale > 0.9 ? 26 : 16.7; + if (scaler.record(frameMs)) changes += 1; + if (frameMs > 24) slowMs += frameMs; + elapsed += frameMs; + } + expect(changes).toBeLessThanOrEqual(10); + expect(slowMs).toBeLessThan(6_000); + expect(scaler.scale).toBeCloseTo(0.85); + }); + + it("keeps a raise that holds up and tries a failed one again only after a doubling hold", () => { + const scaler = new ResolutionScaler(); + feed(scaler, 40, 25); + expect(scaler.scale).toBeCloseTo(0.85); + expect(feed(scaler, 16, 63 * 3)).toBe(1); + expect(scaler.scale).toBe(1); + expect(feed(scaler, 40, 25)).toBe(1); + expect(scaler.scale).toBeCloseTo(0.85); + expect(feed(scaler, 16, 63 * 10)).toBe(0); + expect(feed(scaler, 16, 63)).toBe(1); + expect(scaler.scale).toBe(1); + expect(feed(scaler, 16, 63 * 3)).toBe(0); + expect(feed(scaler, 40, 25)).toBe(1); + expect(scaler.scale).toBeCloseTo(0.85); + expect(feed(scaler, 16, 63 * 3)).toBe(1); + expect(scaler.scale).toBe(1); + }); + + it("ignores hidden-tab gaps and non-positive intervals", () => { + const scaler = new ResolutionScaler(); + expect(scaler.record(0)).toBe(false); + expect(scaler.record(Number.NaN)).toBe(false); + expect(scaler.record(5000)).toBe(false); + expect(feed(scaler, 16, 63 * 3)).toBe(0); + expect(scaler.scale).toBe(1); + }); +}); diff --git a/web/hands/src/render/quality.ts b/web/hands/src/render/quality.ts new file mode 100644 index 00000000..27f276fa --- /dev/null +++ b/web/hands/src/render/quality.ts @@ -0,0 +1,117 @@ +export interface ResolutionScalerOptions { + readonly maximum: number; + readonly minimum: number; + readonly slowMs: number; + readonly fastMs: number; + readonly windowMs: number; + readonly step: number; +} + +export const DEFAULT_SCALER_OPTIONS: ResolutionScalerOptions = { + maximum: 1, + minimum: 0.55, + slowMs: 24, + fastMs: 17.5, + windowMs: 1000, + step: 0.15, +}; + +const HOLD_WINDOWS_AFTER_NO_GAIN = 10; +const HOLD_WINDOWS_AFTER_FAILED_RAISE = 10; +const MAXIMUM_HOLD_WINDOWS = 160; +const FAST_WINDOWS_BEFORE_RAISE = 3; +const RAISE_TRIAL_WINDOWS = 3; + +/** + * Dynamic render-resolution controller. Frame times are averaged over a + * window; a slow window lowers the scale one step, and three fast windows in a + * row raise it again. A downscale that does not make the next window at least + * ten percent faster is reverted and further downscales are held off, with + * the hold doubling on every fruitless attempt, so a client whose frame time + * is capped by its display or by the CPU keeps its full resolution. A raise + * that brings a slow window back within three windows is undone at once and + * further raises are held off the same way, so a client that needs exactly one + * step down settles there instead of pumping between two scales. + */ +export class ResolutionScaler { + scale: number; + private elapsed = 0; + private frames = 0; + private fastWindows = 0; + private holdWindows = 0; + private fruitlessAttempts = 0; + private pending: { readonly before: number; readonly previous: number } | null = null; + private raised: { readonly previous: number; windows: number } | null = null; + private raiseHoldWindows = 0; + private failedRaises = 0; + + constructor(private readonly options: ResolutionScalerOptions = DEFAULT_SCALER_OPTIONS) { + this.scale = options.maximum; + } + + /** Records one frame interval in milliseconds; returns true when the scale changed. */ + record(frameMs: number): boolean { + if (!(frameMs > 0) || frameMs > 1000) return false; + this.elapsed += frameMs; + this.frames += 1; + if (this.elapsed < this.options.windowMs) return false; + const average = this.elapsed / this.frames; + this.elapsed = 0; + this.frames = 0; + if (this.pending !== null) { + const pending = this.pending; + this.pending = null; + if (average > pending.before * 0.9) { + this.scale = pending.previous; + this.holdWindows = Math.min(MAXIMUM_HOLD_WINDOWS, HOLD_WINDOWS_AFTER_NO_GAIN * 2 ** this.fruitlessAttempts); + this.fruitlessAttempts += 1; + return true; + } + this.fruitlessAttempts = 0; + } + if (this.raised !== null) { + const raised = this.raised; + if (average > this.options.slowMs) { + this.raised = null; + this.scale = raised.previous; + this.fastWindows = 0; + this.raiseHoldWindows = Math.min(MAXIMUM_HOLD_WINDOWS, HOLD_WINDOWS_AFTER_FAILED_RAISE * 2 ** this.failedRaises); + this.failedRaises += 1; + return true; + } + raised.windows += 1; + if (raised.windows >= RAISE_TRIAL_WINDOWS) { + this.raised = null; + this.failedRaises = 0; + } + } + if (average > this.options.slowMs) { + this.fastWindows = 0; + if (this.holdWindows > 0) { + this.holdWindows -= 1; + return false; + } + if (this.scale <= this.options.minimum) return false; + const previous = this.scale; + this.scale = Math.max(this.options.minimum, this.scale - this.options.step); + this.pending = { before: average, previous }; + return true; + } + if (average < this.options.fastMs) { + this.fastWindows += 1; + if (this.raiseHoldWindows > 0) { + this.raiseHoldWindows -= 1; + return false; + } + if (this.fastWindows >= FAST_WINDOWS_BEFORE_RAISE && this.scale < this.options.maximum) { + this.fastWindows = 0; + this.raised = { previous: this.scale, windows: 0 }; + this.scale = Math.min(this.options.maximum, this.scale + this.options.step); + return true; + } + return false; + } + this.fastWindows = 0; + return false; + } +} diff --git a/web/hands/src/render/render.test.ts b/web/hands/src/render/render.test.ts index e0293130..c19f3062 100644 --- a/web/hands/src/render/render.test.ts +++ b/web/hands/src/render/render.test.ts @@ -1,17 +1,15 @@ import * as THREE from "three"; import { punchTiming, totalTicks } from "../manifest"; import { buildArena } from "./arena"; -import { BoxerAnimator } from "./animation"; -import { buildBoxer, buildReferee } from "./boxer"; -import { CameraDirector } from "./camera"; +import { CameraDirector, cornerFrame, cornerPoint, cornerShot, cornerShotProgress, CUTMAN_WORK_DEGREES, CUTMAN_WORK_DISTANCE } from "./camera"; import { bloodPatternFor, Effects3D } from "./effects"; -import { drawHud, HUD_MAX_GUARD, HUD_MAX_POISE, scoreTotal } from "./hud"; -import { buildRing } from "./ring"; +import { decisionLabel, drawHud, FINAL_REVEAL_DELAY_SECONDS, finalRevealDelay, fitFontSize, HUD_MAX_GUARD, HUD_MAX_POISE, RoundClock, RoundStatsTracker, scoreTotal, topPanelOffset } from "./hud"; +import { buildRing, ropePress } from "./ring"; import { resizeHighDpi } from "./viewport"; import { PALETTES, worldMapping } from "./world"; import { fighter, publicPlayers, snapshot } from "../test/fixtures"; -const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 330 }); +const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); const withAction = ( base: ReturnType, @@ -39,12 +37,12 @@ const withAction = ( describe("world mapping", () => { it("maps sim up (W/stick-up) away from the broadcast camera and sim right to screen right", () => { - const map = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 330 }); - expect(map.z(330)).toBeLessThan(0); - expect(map.z(-330)).toBeGreaterThan(0); + const map = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); + expect(map.z(500)).toBeLessThan(0); + expect(map.z(-500)).toBeGreaterThan(0); expect(map.x(500)).toBeGreaterThan(0); expect(map.x(-500)).toBeLessThan(0); - expect(Math.abs(map.x(500))).toBeCloseTo(Math.abs(map.z(330)), 5); + expect(Math.abs(map.x(500))).toBeCloseTo(Math.abs(map.z(500)), 5); }); }); @@ -58,25 +56,6 @@ describe("scene construction", () => { expect(ring.geometries.some((geometry) => geometry.type === "PlaneGeometry")).toBe(true); }); - it("builds anatomically complete boxers with distinct corner palettes", () => { - const blue = buildBoxer(PALETTES[0]); - const red = buildBoxer(PALETTES[1]); - for (const joint of ["hips", "spine", "chest", "head", "shoulderL", "elbowL", "gloveL", "shoulderR", "elbowR", "gloveR", "hipL", "kneeL", "hipR", "kneeR"]) { - expect(blue.root.getObjectByName(joint), joint).toBeTruthy(); - } - expect(blue.gloveLMesh).toBeTruthy(); - expect(blue.gloveRMesh).toBeTruthy(); - expect((blue.gloveLMesh.material as THREE.MeshStandardMaterial).color.getHex()).not.toBe((red.gloveLMesh.material as THREE.MeshStandardMaterial).color.getHex()); - expect(blue.geometries.length).toBeGreaterThan(20); - }); - - it("builds a clothed referee sharing the boxer rig", () => { - const referee = buildReferee(); - expect(referee.root.getObjectByName("hips")).toBeTruthy(); - expect(referee.root.getObjectByName("head")).toBeTruthy(); - expect(referee.materials.length).toBeGreaterThan(8); - }); - it("builds and animates the arena crowd deterministically", () => { const arena = buildArena(); arena.update(1.5, 1 / 60, false); @@ -86,271 +65,6 @@ describe("scene construction", () => { }); }); -describe("boxer animation", () => { - const make = () => { - const rig = buildBoxer(PALETTES[0]); - return { rig, animator: new BoxerAnimator(rig, mapping) }; - }; - - it("moves the rig to authoritative world positions and faces the opponent", () => { - const { rig, animator } = make(); - const one = { ...fighter("one"), x: -200, y: 100 }; - const two = { ...fighter("two"), x: 200, y: -50 }; - for (let i = 0; i < 60; i += 1) animator.update(one, two, 1 / 60, i / 60, false); - expect(rig.root.position.x).toBeCloseTo(mapping.x(-200), 5); - expect(rig.root.position.z).toBeCloseTo(mapping.z(100), 5); - const expectedYaw = Math.atan2(mapping.x(200) - mapping.x(-200), (mapping.z(-50) - mapping.z(100)) * 0.45); - expect(Math.abs(rig.root.rotation.y - expectedYaw)).toBeLessThan(0.6); - }); - - it("drives punch timelines from action instances and returns to guard", () => { - const { rig, animator } = make(); - const one = fighter("one"); - const two = fighter("two"); - for (let i = 0; i < 30; i += 1) animator.update(one, two, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - const guardZ = rig.gloveL.getWorldPosition(new THREE.Vector3()).z; - const punching = withAction({ ...one, x: 0 }, "straight", "right"); - const farOpponent = { ...two, x: 195 }; - let maxExtension = 0; - for (let i = 0; i < 40; i += 1) { - const snapshotTick = 15 + Math.floor(i / 2); - const frame = i < 34 ? { ...punching, action_start_tick: 15 } : { ...one, action_start_tick: 15 }; - animator.update(frame, farOpponent, 1 / 60, 0.5 + i / 60, false, "full", snapshotTick); - const shoulder = rig.shoulderR.getWorldPosition(new THREE.Vector3()); - const glove = rig.gloveR.getWorldPosition(new THREE.Vector3()); - maxExtension = Math.max(maxExtension, shoulder.distanceTo(glove)); - } - expect(maxExtension).toBeGreaterThan(0.55); - expect(maxExtension).toBeLessThanOrEqual(0.67); - for (let i = 0; i < 90; i += 1) animator.update(one, two, 1 / 60, 1.5 + i / 60, false, "full", 40 + Math.floor(i / 2)); - const recovered = rig.gloveL.getWorldPosition(new THREE.Vector3()).z; - expect(Math.abs(recovered - guardZ)).toBeLessThan(0.25); - }); - - it("drops the hips to the canvas when downed and rises on recovery", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const downed = { ...fighter("one"), is_downed: true }; - for (let i = 0; i < 120; i += 1) animator.update(downed, two, 1 / 60, i / 60, false); - expect(rig.hips.position.y).toBeLessThan(0.35); - const standing = fighter("one"); - for (let i = 0; i < 240; i += 1) animator.update(standing, two, 1 / 60, 2 + i / 60, false); - expect(rig.hips.position.y).toBeGreaterThan(0.9); - }); - - it("shows trauma overlays scaled by authoritative trauma", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const hurt = { ...fighter("one"), trauma: { head: 500, body: 900, left_eye: 300, right_eye: 40, left_cut: 260, right_cut: 0, swelling: 0, bleeding: 300 } }; - animator.update(hurt, two, 1 / 60, 0, false); - expect((rig.bruiseL.material as THREE.MeshStandardMaterial).opacity).toBeGreaterThan(0.5); - expect((rig.bruiseR.material as THREE.MeshStandardMaterial).opacity).toBeLessThan(0.5); - expect((rig.cutL.material as THREE.MeshStandardMaterial).opacity).toBeGreaterThan(0.5); - expect((rig.bodyBruise.material as THREE.MeshStandardMaterial).opacity).toBeGreaterThan(0.4); - }); - - it("reacts to impacts without mutating the snapshot", () => { - const { animator } = make(); - const one = fighter("one"); - const two = fighter("two"); - const serialized = JSON.stringify(one); - animator.impact({ direction: 1, amount: 300, blocked: false }); - animator.update(one, two, 1 / 60, 0, false); - expect(JSON.stringify(one)).toBe(serialized); - }); - - it("grows swelling, streaks and rib bruising with trauma and gates blood by setting", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const hurt = { ...fighter("one"), trauma: { head: 800, body: 700, left_eye: 400, right_eye: 100, left_cut: 300, right_cut: 50, swelling: 300, bleeding: 350 } }; - animator.update(hurt, two, 1 / 60, 0, false, "full"); - expect(rig.swellL.scale.x).toBeGreaterThan(1); - expect(rig.swellR.scale.x).toBeLessThan(rig.swellL.scale.x); - expect((rig.streakL.material as THREE.MeshStandardMaterial).opacity).toBeGreaterThan(0.8); - expect((rig.ribL.material as THREE.MeshStandardMaterial).opacity).toBeGreaterThan(0.5); - expect((rig.noseStreak.material as THREE.MeshStandardMaterial).opacity).toBeGreaterThan(0.5); - animator.update(hurt, two, 1 / 60, 0.1, false, "off"); - expect((rig.streakL.material as THREE.MeshStandardMaterial).opacity).toBe(0); - expect((rig.cutL.material as THREE.MeshStandardMaterial).opacity).toBe(0); - expect((rig.mouthBlood.material as THREE.MeshStandardMaterial).opacity).toBe(0); - expect((rig.swellL.material as THREE.MeshStandardMaterial).opacity).toBeGreaterThan(0); - }); - - it("bloodies the attacker's gloves with the opponent's bleeding", () => { - const { rig, animator } = make(); - const one = fighter("one"); - const bloodied = { ...fighter("two"), trauma: { head: 500, body: 0, left_eye: 0, right_eye: 0, left_cut: 300, right_cut: 200, swelling: 0, bleeding: 500 } }; - animator.update(one, bloodied, 1 / 60, 0, false, "full"); - const tinted = rig.gloveLMaterial.color.getHex(); - animator.update(one, fighter("two"), 1 / 60, 0.1, false, "full"); - expect(rig.gloveLMaterial.color.getHex()).not.toBe(tinted); - expect(tinted).not.toBe(rig.gloveBaseColor.getHex()); - animator.update(one, bloodied, 1 / 60, 0.2, false, "off"); - expect(rig.gloveLMaterial.color.getHex()).toBe(rig.gloveBaseColor.getHex()); - }); - - it("retracts a punch when the fighter goes down mid-animation", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const punching = { ...fighter("one"), action: "straight" as const, action_hand: "right" as const, action_target: "head" as const, action_power: "power" as const }; - for (let i = 0; i < 8; i += 1) animator.update(punching, two, 1 / 60, i / 60, false); - const extendedZ = rig.gloveR.getWorldPosition(new THREE.Vector3()).z - rig.root.position.z; - const downed = { ...punching, is_downed: true, action: null }; - for (let i = 0; i < 120; i += 1) animator.update(downed, two, 1 / 60, 1 + i / 60, false); - const downZ = rig.gloveR.getWorldPosition(new THREE.Vector3()).z - rig.root.position.z; - expect(downZ).toBeLessThan(extendedZ); - }); - - it("freezes the punch during hitstop and rotates the punching shoulder into a cross", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const punching = withAction(fighter("one"), "straight", "right"); - for (let i = 0; i < 5; i += 1) animator.update(punching, two, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - const gloveBefore = rig.gloveR.getWorldPosition(new THREE.Vector3()).z; - animator.landedHit(false); - for (let i = 0; i < 3; i += 1) animator.update(punching, two, 1 / 60, 0.1 + i / 60, false, "full", 2); - const gloveDuringStop = rig.gloveR.getWorldPosition(new THREE.Vector3()).z; - expect(Math.abs(gloveDuringStop - gloveBefore)).toBeLessThan(0.06); - for (let i = 0; i < 20; i += 1) animator.update(punching, two, 1 / 60, 0.3 + i / 60, false, "full", 2 + Math.floor(i / 2)); - expect(rig.hips.rotation.y).toBeGreaterThan(0.1); - expect(rig.spine.rotation.y).toBeGreaterThan(0.1); - const southpawRig = buildBoxer(PALETTES[1]); - const southpawAnimator = new BoxerAnimator(southpawRig, mapping); - const southpawPunch = withAction({ ...fighter("two"), stance: "southpaw" as const }, "straight", "right"); - for (let i = 0; i < 20; i += 1) southpawAnimator.update(southpawPunch, fighter("one"), 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - expect(southpawRig.spine.rotation.y).toBeGreaterThan(0.1); - }); - - it("drops level for body punches and springs the canvas landing on knockdown", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const bodyPunch = withAction(fighter("one"), "straight", "left", "body"); - for (let i = 0; i < 14; i += 1) animator.update(bodyPunch, two, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - const bodyHeight = rig.hips.position.y; - const headPunch = withAction(fighter("one"), "straight", "left", "head"); - const second = make(); - for (let i = 0; i < 14; i += 1) second.animator.update(headPunch, two, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - expect(bodyHeight).toBeLessThan(second.rig.hips.position.y - 0.03); - const downed = { ...fighter("one"), is_downed: true }; - const third = make(); - let maxSpring = 0; - for (let i = 0; i < 150; i += 1) { - third.animator.update(downed, two, 1 / 60, i / 60, false); - maxSpring = Math.max(maxSpring, Math.abs(third.animator.landingOffset)); - } - expect(maxSpring).toBeGreaterThan(0.025); - expect(third.rig.hips.position.y).toBeLessThan(0.35); - }); - - it("dances the taunt with overhead swings and hip wiggle", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const taunting = { ...fighter("one"), taunt_ticks: 45 }; - let maxGloveY = -Infinity; - let maxRoll = 0; - for (let i = 0; i < 40; i += 1) { - animator.update({ ...taunting, taunt_ticks: 45 - i }, two, 1 / 60, i / 60, false); - maxGloveY = Math.max(maxGloveY, rig.gloveL.getWorldPosition(new THREE.Vector3()).y); - maxRoll = Math.max(maxRoll, Math.abs(rig.hips.rotation.z)); - } - expect(maxGloveY).toBeGreaterThan(1.55); - expect(maxRoll).toBeGreaterThan(0.05); - }); - - it("differentiates punch silhouettes: hook sweeps wide, jab recovers fastest", () => { - const two = fighter("two"); - const trace = (action: "jab" | "hook"): { maxLateral: number; recoverFrames: number } => { - const { rig, animator } = make(); - const punching = withAction(fighter("one"), action, "left"); - const farOpponent = { ...two, x: 195 }; - animator.update(fighter("one"), farOpponent, 1 / 60, 0, false, "full", 0); - const guardZ = rig.chest.worldToLocal(rig.gloveL.getWorldPosition(new THREE.Vector3())).z; - let maxLateral = 0; - let peakZ = -Infinity; - let peakTick = 0; - let extended = false; - let recoverTick = Infinity; - for (let i = 0; i < 90; i += 1) { - const frame = i < 40 ? punching : fighter("one"); - animator.update(frame, farOpponent, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - const local = rig.chest.worldToLocal(rig.gloveL.getWorldPosition(new THREE.Vector3())); - maxLateral = Math.max(maxLateral, Math.abs(local.x)); - if (local.z > guardZ + 0.15) extended = true; - if (local.z > peakZ) { - peakZ = local.z; - peakTick = i; - } else if (extended && recoverTick === Infinity && i > peakTick && local.z < guardZ + 0.04) { - recoverTick = i; - } - } - return { maxLateral, recoverFrames: recoverTick - peakTick }; - }; - const jab = trace("jab"); - const hook = trace("hook"); - expect(hook.maxLateral).toBeGreaterThan(jab.maxLateral + 0.1); - expect(totalTicks(punchTiming("jab", "head", "normal"))).toBeLessThan(totalTicks(punchTiming("hook", "head", "normal"))); - expect(totalTicks(punchTiming("straight", "head", "normal"))).toBeLessThan(totalTicks(punchTiming("uppercut", "head", "normal"))); - }); - - it("buckles the knees early in a knockdown before settling flat", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const downed = { ...fighter("one"), is_downed: true }; - let earlyKnee = 0; - for (let i = 0; i < 18; i += 1) { - animator.update(downed, two, 1 / 60, i / 60, false); - earlyKnee = Math.max(earlyKnee, rig.kneeL.rotation.x); - } - expect(earlyKnee).toBeGreaterThan(0.5); - for (let i = 0; i < 150; i += 1) animator.update(downed, two, 1 / 60, 1 + i / 60, false); - expect(rig.kneeL.rotation.x).toBeLessThan(0.4); - }); - - it("restarts identical punches on new action instances", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const jabOne = withAction(fighter("one"), "jab", "left"); - for (let i = 0; i < 16; i += 1) animator.update(jabOne, two, 1 / 60, i / 60, false, "full", Math.floor(i / 2)); - const midZ = rig.chest.worldToLocal(rig.gloveL.getWorldPosition(new THREE.Vector3())).z; - expect(midZ).toBeGreaterThan(0.33); - const jabTwo = { ...withAction(fighter("one"), "jab", "left"), action_id: "jab-left-head-normal-2" }; - animator.update(jabTwo, two, 1 / 60, 1, false, "full", 8); - const restartZ = rig.chest.worldToLocal(rig.gloveL.getWorldPosition(new THREE.Vector3())).z; - expect(restartZ).toBeLessThan(midZ); - }); - - it("begins predicted punches locally and reconciles within one tick", () => { - const { rig, animator } = make(); - const two = fighter("two"); - const baseline = rig.chest.worldToLocal(rig.gloveL.getWorldPosition(new THREE.Vector3())).z; - animator.predict({ kind: "punch", hand: "left", class: "jab", target: "head", power: "normal", id: "c7" }, 0, 30); - animator.update(fighter("one"), two, 1 / 60, 1 / 60, false, "full", 0); - const predictedZ = rig.chest.worldToLocal(rig.gloveL.getWorldPosition(new THREE.Vector3())).z; - expect(predictedZ).toBeGreaterThan(baseline + 0.005); - const authoritative = { - ...withAction(fighter("one"), "jab", "left"), - action_id: "c7", - action_start_tick: 2, - }; - animator.update(authoritative, two, 1 / 60, 2 / 60, false, "full", 2); - const reconciledZ = rig.chest.worldToLocal(rig.gloveL.getWorldPosition(new THREE.Vector3())).z; - expect(Math.abs(reconciledZ - predictedZ)).toBeLessThan(0.3); - }); - - it("mirrors southpaw glove placement", () => { - const { rig, animator } = make(); - const one = { ...fighter("one"), stance: "southpaw" as const }; - const two = fighter("two"); - for (let i = 0; i < 30; i += 1) animator.update(one, two, 1 / 60, i / 60, false); - const leftX = rig.gloveL.getWorldPosition(new THREE.Vector3()).x - rig.root.position.x; - const orthodox = buildBoxer(PALETTES[0]); - const orthodoxAnimator = new BoxerAnimator(orthodox, mapping); - for (let i = 0; i < 30; i += 1) orthodoxAnimator.update(fighter("one"), two, 1 / 60, i / 60, false); - const orthodoxLeftX = orthodox.gloveL.getWorldPosition(new THREE.Vector3()).x - orthodox.root.position.x; - expect(Math.sign(leftX)).not.toBe(Math.sign(orthodoxLeftX)); - }); -}); - describe("camera direction", () => { it("follows the fighters midpoint and pushes in on knockdowns", () => { const director = new CameraDirector(); @@ -397,8 +111,8 @@ describe("effects", () => { const effects = new Effects3D(new THREE.Scene()); effects.addEvent({ ...severeHit(20), detail }, new THREE.Vector3(), false); effects.update(0.1); - const positions = effects.points.geometry.getAttribute("position") as THREE.BufferAttribute; - const colors = effects.points.geometry.getAttribute("color") as THREE.BufferAttribute; + const positions = effects.dropletBuffers.position; + const colors = effects.dropletBuffers.color; const heights: number[] = []; for (let index = 0; index < positions.count; index += 1) { if (colors.getY(index) < 0.2 && positions.getY(index) > -10) heights.push(positions.getY(index)); @@ -414,7 +128,7 @@ describe("effects", () => { const full = new Effects3D(new THREE.Scene()); full.addEvent(severeHit(1), origin, false); - expect(full.liveBloodParticles).toBe(140); + expect(full.liveBloodParticles).toBe(110); expect(full.liveMist).toBe(10); expect(full.liveGibs).toBe(11); expect(full.visibleDecals).toBe(12); @@ -454,7 +168,7 @@ describe("effects", () => { effects.update(1 / 60); } expect(effects.liveBloodParticles).toBe(2); - const positions = effects.points.geometry.getAttribute("position") as THREE.BufferAttribute; + const positions = effects.dropletBuffers.position; const liveX = Array.from({ length: positions.count }, (_unused, index) => positions.getX(index)) .filter((_x, index) => positions.getY(index) > -10); expect(liveX.some((x) => x < 0)).toBe(true); @@ -462,6 +176,27 @@ describe("effects", () => { effects.dispose(); }); + it("reports where a severed head is, follows it as it falls, and can sever again after a restore", () => { + const scene = new THREE.Scene(); + const effects = new Effects3D(scene); + const where = new THREE.Vector3(); + expect(effects.severedHeadPosition(0, where)).toBe(false); + effects.decapitate(0, new THREE.Vector3(0.2, 1.5, -0.1), new THREE.Quaternion(), 1, 77); + expect(effects.severedHeadPosition(0, where)).toBe(true); + expect(where.y).toBeCloseTo(1.5, 1); + for (let frame = 0; frame < 240; frame += 1) effects.update(1 / 60); + expect(effects.severedHeadPosition(0, where)).toBe(true); + expect(where.y).toBeLessThan(0.6); + expect(effects.severedHeadPosition(1, where)).toBe(false); + effects.restoreFighter(0); + expect(effects.severedHeadPosition(0, where)).toBe(false); + effects.decapitate(0, new THREE.Vector3(0, 1.5, 0), new THREE.Quaternion(), 1, 77); + expect(effects.activeHeads).toBe(0); + effects.decapitate(0, new THREE.Vector3(0, 1.5, 0), new THREE.Quaternion(), 1, 77 + 1_000_003); + expect(effects.activeHeads).toBe(1); + effects.dispose(); + }); + it("immediately clears every red effect when blood is turned off while retaining sweat", () => { const scene = new THREE.Scene(); const effects = new Effects3D(scene); @@ -501,7 +236,7 @@ describe("effects", () => { effects.decapitate(0, position, quaternion, 1, 42, 0xb0703f); expect(effects.activeHeads).toBe(1); const visibleHead = scene.children.find((child) => - child instanceof THREE.Mesh && child.visible && child.geometry instanceof THREE.SphereGeometry, + child instanceof THREE.Mesh && !(child instanceof THREE.InstancedMesh) && child.visible && child.geometry instanceof THREE.SphereGeometry, ) as THREE.Mesh; expect(visibleHead.material.color.getHex()).toBe(0xb0703f); expect(effects.activeStumps).toBe(1); @@ -518,7 +253,7 @@ describe("effects", () => { effects.decapitate(1, position, quaternion, -1, 43, 0x6e4128); expect(effects.activeHeads).toBe(2); const visibleHeadColors = scene.children - .filter((child) => child instanceof THREE.Mesh && child.visible && child.geometry instanceof THREE.SphereGeometry) + .filter((child) => child instanceof THREE.Mesh && !(child instanceof THREE.InstancedMesh) && child.visible && child.geometry instanceof THREE.SphereGeometry) .map((child) => ((child as THREE.Mesh).material as THREE.MeshStandardMaterial).color.getHex()); expect(visibleHeadColors).toEqual([0xb0703f, 0x6e4128]); expect(effects.activeStumps).toBe(2); @@ -635,7 +370,7 @@ describe("effects", () => { effects.update(dt); } const head = scene.children.find((child) => - child instanceof THREE.Mesh && child.visible && child.geometry instanceof THREE.SphereGeometry, + child instanceof THREE.Mesh && !(child instanceof THREE.InstancedMesh) && child.visible && child.geometry instanceof THREE.SphereGeometry, )!; const gibMesh = scene.children.find((child) => child instanceof THREE.InstancedMesh) as THREE.InstancedMesh; const matrix = new THREE.Matrix4(); @@ -644,7 +379,7 @@ describe("effects", () => { const result = { head: head.position.toArray(), gib: gibPosition.toArray(), - particles: Array.from(effects.points.geometry.getAttribute("position").array), + particles: Array.from(effects.dropletBuffers.position.array), decals: effects.visibleDecals, }; effects.dispose(); @@ -653,6 +388,105 @@ describe("effects", () => { expect(simulate(1 / 30)).toEqual(simulate(1 / 60)); }); + it("draws and uploads only the droplets in flight", () => { + const effects = new Effects3D(new THREE.Scene()); + const mesh = effects.dropletMesh; + const matrices = mesh.instanceMatrix; + expect(mesh.count).toBe(0); + effects.addEvent(severeHit(40), new THREE.Vector3(), false); + expect(mesh.count).toBe(effects.liveParticles); + // A step moves every live droplet and uploads just their matrices, packed at the front of the pool. + matrices.clearUpdateRanges(); + effects.update(1 / 60); + const live = mesh.count; + expect(live).toBe(effects.liveParticles); + expect(matrices.updateRanges).toEqual([{ start: 0, count: live * 16 }]); + const positions = effects.dropletBuffers.position; + for (let index = 0; index < 900; index += 1) expect(positions.getY(index) > -10).toBe(index < live); + // Once the blood has landed nothing is drawn or uploaded. + for (let frame = 0; frame < 180; frame += 1) effects.update(1 / 60); + expect(effects.liveParticles).toBe(0); + expect(mesh.count).toBe(0); + matrices.clearUpdateRanges(); + const version = matrices.version; + effects.update(1 / 60); + expect(matrices.version).toBe(version); + // A full pool keeps reusing its slots. + for (let eventId = 0; eventId < 12; eventId += 1) effects.addEvent(severeHit(100 + eventId), new THREE.Vector3(), false); + expect(mesh.count).toBe(900); + expect(effects.liveParticles).toBe(900); + effects.dispose(); + }); + + it("sprays blood, teeth and severed parts along the line the punch travelled", () => { + const towardsAway = { x: 0, z: -1 }; + /** Mean horizontal position of the airborne blood droplets, or of the airborne gibs. */ + const bloodCentre = (effects: Effects3D): THREE.Vector2 => { + const positions = effects.dropletBuffers.position; + const colors = effects.dropletBuffers.color; + const centre = new THREE.Vector2(); + let count = 0; + for (let index = 0; index < positions.count; index += 1) { + if (positions.getY(index) < -10 || colors.getY(index) >= 0.2) continue; + centre.x += positions.getX(index); + centre.y += positions.getZ(index); + count += 1; + } + return centre.divideScalar(Math.max(1, count)); + }; + const gibCentre = (scene: THREE.Scene): THREE.Vector2 => { + const gibs = scene.children.find((child) => child instanceof THREE.InstancedMesh && child.geometry instanceof THREE.IcosahedronGeometry) as THREE.InstancedMesh; + const matrix = new THREE.Matrix4(); + const position = new THREE.Vector3(); + const centre = new THREE.Vector2(); + let count = 0; + for (let index = 0; index < gibs.count; index += 1) { + gibs.getMatrixAt(index, matrix); + position.setFromMatrixPosition(matrix); + if (position.y < -10) continue; + centre.x += position.x; + centre.y += position.z; + count += 1; + } + return centre.divideScalar(Math.max(1, count)); + }; + const run = (effects: Effects3D, seconds: number): void => { + for (let elapsed = 0; elapsed < seconds; elapsed += 1 / 60) effects.update(1 / 60); + }; + const along = (centre: { x: number; y: number }): void => { + expect(centre.y).toBeLessThan(-0.15); + expect(Math.abs(centre.x)).toBeLessThan(Math.abs(centre.y)); + }; + + const scene = new THREE.Scene(); + const effects = new Effects3D(scene); + effects.addEvent({ ...severeHit(30), detail: "straight:head" }, new THREE.Vector3(), false, towardsAway); + run(effects, 0.25); + along(bloodCentre(effects)); + along(gibCentre(scene)); + effects.clearDynamic(); + effects.spawnTeeth(new THREE.Vector3(0, 1.5, 0), towardsAway, 4, 31); + run(effects, 0.25); + along(gibCentre(scene)); + const head = new THREE.Vector3(); + effects.decapitate(0, new THREE.Vector3(0, 1.55, 0), new THREE.Quaternion(), towardsAway, 32); + run(effects, 0.3); + effects.severedHeadPosition(0, head); + along({ x: head.x, y: head.z }); + effects.dismemberHand(1, "left", new THREE.Vector3(0, 1.3, 0), new THREE.Quaternion(), towardsAway, 33, 0x1d4ed8); + run(effects, 0.3); + const hand = scene.children.find((child) => child instanceof THREE.Mesh && child.visible && child.geometry instanceof THREE.CapsuleGeometry)!; + along({ x: hand.position.x, y: hand.position.z }); + effects.dispose(); + + // Without the fighters' positions the event's world-x sign still decides. + const fallback = new Effects3D(new THREE.Scene()); + fallback.addEvent({ ...severeHit(34), detail: "straight:head", direction: -1 }, new THREE.Vector3(), false); + run(fallback, 0.25); + expect(bloodCentre(fallback).x).toBeLessThan(-0.15); + fallback.dispose(); + }); + it("never exceeds any fixed pool under repeated production-valid events", () => { const scene = new THREE.Scene(); const effects = new Effects3D(scene); @@ -705,6 +539,8 @@ describe("viewport and broadcast HUD", () => { drawHud(ctx, 800, 600, opponentPrompt, players, "one", null, 0); expect(texts.join(" ")).not.toContain("NOW!"); expect(texts.join(" ")).not.toContain("GET READY"); + expect(texts).toContain("COUNT 4"); + expect(texts.join(" ")).not.toContain("Waiting for"); texts.length = 0; const ownPrompt = { ...opponentPrompt, fighters: [{ ...base.fighters[0], is_downed: true, get_up_prompt: "get_up_right" as const, get_up_meter: 2, get_up_required: 4 }, opponentPrompt.fighters[1]] as const }; drawHud(ctx, 800, 600, ownPrompt, players, "one", null, 0); @@ -739,6 +575,126 @@ describe("viewport and broadcast HUD", () => { }); }); +describe("rope flex", () => { + it("presses into the nearest ropes only when a fighter is within reach of them", () => { + expect(ropePress(0, 0)).toEqual({ pressX: 0, pressZ: 0 }); + expect(ropePress(2.82, 0).pressX).toBeGreaterThan(0.95); + expect(ropePress(2.82, 0).pressZ).toBe(0); + expect(ropePress(0, -2.82).pressZ).toBeGreaterThan(0.95); + expect(ropePress(2.6, 0).pressX).toBeGreaterThan(0.1); + expect(ropePress(2.6, 0).pressX).toBeLessThan(0.6); + }); + + it("writes fighter contacts into the rope shader uniforms and clears them", () => { + const ring = buildRing(); + ring.setRopeContacts({ x: 2.82, z: 0.4 }, null); + expect(ring.ropeContacts[0].x).toBeCloseTo(2.82); + expect(ring.ropeContacts[0].y).toBeCloseTo(0.4); + expect(ring.ropeContacts[0].z).toBeGreaterThan(0.95); + expect(ring.ropeContacts[1].toArray()).toEqual([0, 0, 0, 0]); + ring.setRopeContacts(null, null); + expect(ring.ropeContacts[0].toArray()).toEqual([0, 0, 0, 0]); + }); +}); + +describe("round stats", () => { + const event = (kind: string, actor: string, detail = ""): Parameters[0] => + ({ event_id: 1, tick: 1, kind, actor_id: actor, target_id: null, amount: 0, detail, blood: 0, direction: 1, action_id: null }); + + it("counts punches thrown and landed per fighter and resets on the round-start bell", () => { + const tracker = new RoundStatsTracker(); + tracker.record(event("punch_start", "one")); + tracker.record(event("punch_start", "one")); + tracker.record(event("hit", "one")); + tracker.record(event("punch_start", "two")); + tracker.record(event("counter_hit", "two")); + tracker.record(event("block", "two")); + expect(tracker.get("one")).toEqual({ thrown: 2, landed: 1 }); + expect(tracker.get("two")).toEqual({ thrown: 1, landed: 1 }); + tracker.record(event("bell", "", "round_end")); + expect(tracker.get("one")).toEqual({ thrown: 2, landed: 1 }); + tracker.record(event("bell", "", "round_start")); + expect(tracker.get("one")).toEqual({ thrown: 0, landed: 0 }); + }); + + it("keeps bout totals across rounds and prints them on the result panel", () => { + const tracker = new RoundStatsTracker(); + tracker.record(event("punch_start", "one")); + tracker.record(event("hit", "one")); + tracker.record(event("bell", "", "round_start")); + tracker.record(event("punch_start", "one")); + tracker.record(event("punch_start", "two")); + expect(tracker.get("one")).toEqual({ thrown: 1, landed: 0 }); + expect(tracker.total("one")).toEqual({ thrown: 2, landed: 1 }); + const texts: string[] = []; + const ctx = mockHudContext(texts); + const players = Object.fromEntries(publicPlayers.map((player) => [player.id, player])); + const final = { version: 3 as const, type: "final" as const, match_id: "m", winner_id: "one", method: "decision" as const, round: 3, scorecards: [], ratings: {} }; + drawHud(ctx, 1280, 720, { ...snapshot(), phase: "complete" }, players, "one", final, 0, 30, tracker); + expect(texts.some((text) => text.includes("One 1/2 landed") && text.includes("Two 0/1 landed"))).toBe(true); + }); + + it("draws the round callout only while the renderer asks for it", () => { + const texts: string[] = []; + const ctx = mockHudContext(texts); + const players = Object.fromEntries(publicPlayers.map((player) => [player.id, player])); + drawHud(ctx, 1280, 720, { ...snapshot(), phase: "fight", round_number: 2 }, players, "one", null, 0, 30, null, null, null, "ROUND 2"); + expect(texts.filter((text) => text === "ROUND 2").length).toBeGreaterThanOrEqual(2); + texts.length = 0; + drawHud(ctx, 1280, 720, { ...snapshot(), phase: "fight", round_number: 2 }, players, "one", null, 0, 30, null, null, null, null); + expect(texts.filter((text) => text === "ROUND 2").length).toBe(1); + }); + + it("shows the local fighter's input latency readout", () => { + const texts: string[] = []; + const ctx = mockHudContext(texts); + const players = Object.fromEntries(publicPlayers.map((player) => [player.id, player])); + drawHud(ctx, 1280, 720, snapshot(), players, "one", null, 0, 30, null, null, 48.4); + expect(texts).toContain("INPUT 48 ms"); + texts.length = 0; + drawHud(ctx, 1280, 720, snapshot(), players, null, null, 0, 30, null, null, 48.4); + expect(texts.some((text) => text.startsWith("INPUT"))).toBe(false); + }); + + it("shows the landed counts on the rest panel", () => { + const texts: string[] = []; + const ctx = mockHudContext(texts); + const tracker = new RoundStatsTracker(); + tracker.record(event("punch_start", "one")); + tracker.record(event("hit", "one")); + drawHud(ctx, 1280, 720, { ...snapshot(), phase: "rest" }, Object.fromEntries(publicPlayers.map((player) => [player.id, player])), "one", null, 0, 30, tracker); + expect(texts.some((text) => text.includes("One 1/1"))).toBe(true); + }); +}); + +describe("decision label", () => { + const card = (one: number[], two: number[], judge = "J") => ({ judge, player_one: one, player_two: two }); + const final = (method: "decision" | "draw" | "ko" | "tko", scorecards: ReturnType[]) => + ({ version: 3 as const, type: "final" as const, match_id: "m", winner_id: method === "draw" ? null : "one", method, round: 3, scorecards, ratings: {} }); + + it("names unanimous, split and majority decisions and draws from the scorecards", () => { + expect(decisionLabel(final("decision", [card([10, 10, 10], [9, 9, 9]), card([10, 10, 9], [9, 9, 10]), card([10, 10, 10], [9, 9, 9])]))).toBe("UNANIMOUS DECISION"); + expect(decisionLabel(final("decision", [card([10, 10, 10], [9, 9, 9]), card([9, 9, 10], [10, 10, 9]), card([10, 10, 10], [9, 9, 9])]))).toBe("SPLIT DECISION"); + expect(decisionLabel(final("decision", [card([10, 10, 10], [9, 9, 9]), card([10, 9], [9, 10]), card([10, 10, 10], [9, 9, 9])]))).toBe("MAJORITY DECISION"); + expect(decisionLabel(final("draw", [card([10], [10]), card([10], [10]), card([10], [10])]))).toBe("UNANIMOUS DRAW"); + expect(decisionLabel(final("draw", [card([10], [9]), card([9], [10]), card([10], [10])]))).toBe("SPLIT DRAW"); + expect(decisionLabel(final("draw", [card([10], [9]), card([10], [10]), card([10], [10])]))).toBe("MAJORITY DRAW"); + expect(decisionLabel(final("tko", []))).toBe("TKO"); + expect(decisionLabel(final("decision", []))).toBe("DECISION"); + }); +}); + +describe("final reveal", () => { + const final = { version: 3 as const, type: "final" as const, match_id: "m", winner_id: "one", method: "ko" as const, round: 1, scorecards: [], ratings: {} }; + it("holds stoppage results back for the slow-motion fall and shows decisions at once", () => { + expect(finalRevealDelay(final)).toBe(FINAL_REVEAL_DELAY_SECONDS); + expect(finalRevealDelay({ ...final, method: "tko" })).toBe(FINAL_REVEAL_DELAY_SECONDS); + expect(finalRevealDelay({ ...final, method: "flash_ko" })).toBe(FINAL_REVEAL_DELAY_SECONDS); + expect(finalRevealDelay({ ...final, method: "decision" })).toBe(0); + expect(finalRevealDelay(null)).toBe(0); + }); +}); + function mockHudContext(texts: string[]): CanvasRenderingContext2D { const gradient = { addColorStop: () => {} }; return { @@ -754,6 +710,7 @@ function mockHudContext(texts: string[]): CanvasRenderingContext2D { strokeRect: () => {}, clearRect: () => {}, fillText: (text: string) => texts.push(text), + strokeText: () => undefined, measureText: (text: string) => ({ width: text.length * 7 }), createLinearGradient: () => gradient, createRadialGradient: () => gradient, @@ -765,3 +722,159 @@ function mockHudContext(texts: string[]): CanvasRenderingContext2D { set textBaseline(_value: CanvasTextBaseline) {}, } as unknown as CanvasRenderingContext2D; } + +describe("fitFontSize", () => { + it("returns the largest size that fits and the minimum when nothing does", () => { + const measure = (size: number) => size * 10; + expect(fitFontSize(measure, 160, 16, 11)).toBe(16); + expect(fitFontSize(measure, 135, 16, 11)).toBe(13); + expect(fitFontSize(measure, 50, 16, 11)).toBe(11); + }); +}); + +describe("topPanelOffset", () => { + it("parks the panel under the top bar and lower on narrow screens", () => { + const top = (width: number, height: number): number => height / 2 + topPanelOffset(width, height) - (height < 480 ? 25 : 39); + expect(top(1280, 720)).toBeCloseTo(72); + expect(top(844, 390)).toBeCloseTo(56); + expect(top(390, 844)).toBeCloseTo(112); + }); +}); + +describe("corner shots", () => { + it("stays wide while the fighters walk over and before the bell, then alternates corners starting with the viewer's", () => { + expect(cornerShot(1, 14, 0)).toBeNull(); + expect(cornerShot(3, 12, 0)).toBe(0); + expect(cornerShot(3, 12, 1)).toBe(1); + expect(cornerShot(8.5, 6.5, 0)).toBe(1); + expect(cornerShot(13.6, 1.4, 0)).toBeNull(); + expect(cornerShotProgress(3)).toBeCloseTo(0.5); + expect(cornerShotProgress(8.5)).toBeCloseTo(0.5); + }); + + it("shoots each corner from inside the ropes, mirrored, looking at the stool", () => { + const position = new THREE.Vector3(); + const lookAt = new THREE.Vector3(); + cornerFrame(1, 2.56, 0, position, lookAt); + expect(Math.abs(position.x)).toBeLessThan(3.05); + expect(Math.abs(position.z)).toBeLessThan(3.05); + expect(position.distanceTo(new THREE.Vector3(2.56, 1, -2.56))).toBeGreaterThan(2); + expect(position.distanceTo(new THREE.Vector3(2.56, 1, -2.56))).toBeLessThan(2.9); + expect(lookAt.distanceTo(new THREE.Vector3(2.56, 1, -2.56))).toBeLessThan(0.8); + const mirrored = new THREE.Vector3(); + cornerFrame(0, 2.56, 0, mirrored, lookAt); + expect(mirrored.x).toBeCloseTo(-position.x); + expect(mirrored.z).toBeCloseTo(-position.z); + }); +}); + +describe("corner staging", () => { + it("puts the cutman on the fighter's left and the camera on the right, both inside the ropes", () => { + const cutman = cornerPoint(1, 2.56, CUTMAN_WORK_DISTANCE, CUTMAN_WORK_DEGREES, new THREE.Vector3()); + const camera = new THREE.Vector3(); + const lookAt = new THREE.Vector3(); + cornerFrame(1, 2.56, 0, camera, lookAt); + for (const point of [cutman, camera]) { + expect(Math.abs(point.x)).toBeLessThan(2.6); + expect(Math.abs(point.z)).toBeLessThan(2.6); + } + const stool = new THREE.Vector3(2.56, 0, -2.56); + const forward = new THREE.Vector3(-1, 0, 1).normalize(); + const left = new THREE.Vector3(forward.z, 0, -forward.x); + expect(cutman.clone().sub(stool).dot(left)).toBeGreaterThan(0.2); + expect(camera.clone().setY(0).sub(stool).dot(left)).toBeLessThan(-0.8); + expect(cutman.distanceTo(stool)).toBeCloseTo(CUTMAN_WORK_DISTANCE); + }); +}); + +describe("round clock", () => { + it("holds the round time through a knockdown count and a foul timeout, and resets for a new round", () => { + const clock = new RoundClock(); + const base = snapshot(); + expect(clock.ticks({ ...base, phase: "fight", round_number: 1, phase_ticks_remaining: 2400 })).toBe(2400); + expect(clock.ticks({ ...base, phase: "knockdown", round_number: 1, phase_ticks_remaining: 270 })).toBe(2400); + expect(clock.ticks({ ...base, phase: "fight", round_number: 1, phase_ticks_remaining: 2390 })).toBe(2390); + expect(clock.ticks({ ...base, phase: "foul_recovery", round_number: 1, phase_ticks_remaining: 60 })).toBe(2390); + expect(clock.ticks({ ...base, phase: "rest", round_number: 1, phase_ticks_remaining: 450 })).toBe(450); + expect(clock.ticks({ ...base, phase: "knockdown", round_number: 2, phase_ticks_remaining: 250 })).toBe(250); + }); +}); + +describe("compact scoreboard labels", () => { + it("abbreviates the bar labels on narrow screens so four-digit values do not collide", () => { + const texts: string[] = []; + const ctx = mockHudContext(texts); + const players = Object.fromEntries(publicPlayers.map((p) => [p.id, p])); + drawHud(ctx, 390, 844, snapshot(), players, "one", null, 0, 30); + expect(texts.some((text) => text.startsWith("STA "))).toBe(true); + expect(texts.some((text) => text.startsWith("HP "))).toBe(true); + expect(texts.some((text) => text.startsWith("STAMINA"))).toBe(false); + }); +}); + +describe("compact scoreboard mini bars", () => { + /** Records filled rectangles and where each text lands, measuring text at 0.6 em per character. */ + function layoutContext(): { ctx: CanvasRenderingContext2D; rects: { x: number; y: number; w: number; h: number }[]; texts: { text: string; left: number; right: number; y: number }[] } { + const rects: { x: number; y: number; w: number; h: number }[] = []; + const texts: { text: string; left: number; right: number; y: number }[] = []; + let size = 10; + let align: CanvasTextAlign = "left"; + const width = (text: string): number => text.length * size * 0.6; + const ctx = Object.assign(mockHudContext([]), { + fillRect: (x: number, y: number, w: number, h: number) => rects.push({ x, y, w, h }), + fillText: (text: string, x: number, y: number) => { + const left = align === "right" ? x - width(text) : align === "center" ? x - width(text) / 2 : x; + texts.push({ text, left, right: left + width(text), y }); + }, + measureText: (text: string) => ({ width: width(text) }), + }); + Object.defineProperty(ctx, "font", { set: (font: string) => { size = Number(/(\d+)px/.exec(font)?.[1] ?? 10); } }); + Object.defineProperty(ctx, "textAlign", { set: (value: CanvasTextAlign) => { align = value; } }); + return { ctx, rects, texts }; + } + + it("fit side by side inside their plates on a 320 px phone", () => { + const { ctx, rects, texts } = layoutContext(); + const width = 320; + const height = 640; + drawHud(ctx, width, height, snapshot(), Object.fromEntries(publicPlayers.map((p) => [p.id, p])), "one", null, 0, 30); + const miniY = height - 84 - 12; + // Each bar first fills its frame, a pixel larger than the bar all round. + const bars = rects.filter((rect) => rect.y === miniY - 1 && rect.h === 11).sort((a, b) => a.x - b.x); + const labels = texts.filter((text) => text.y === miniY - 4).sort((a, b) => a.left - b.left); + expect(bars).toHaveLength(4); + expect(labels.map((label) => label.text.split(" ")[0])).toEqual(["GUARD", "POISE", "GUARD", "POISE"]); + const plateWidth = (width - 56) / 2; + const plates = [[24, 24 + plateWidth], [width - 24 - plateWidth, width - 24]] as const; + for (const [index, bar] of bars.entries()) { + const [left, right] = plates[index < 2 ? 0 : 1]; + expect(bar.x + 1).toBeGreaterThanOrEqual(left); + expect(bar.x + bar.w - 1).toBeLessThanOrEqual(right); + } + for (let index = 1; index < 4; index += 1) { + expect(bars[index]!.x).toBeGreaterThanOrEqual(bars[index - 1]!.x + bars[index - 1]!.w); + expect(labels[index]!.left).toBeGreaterThanOrEqual(labels[index - 1]!.right); + } + }); + + it("keep their broadcast size and place on a desktop", () => { + const { ctx, rects } = layoutContext(); + drawHud(ctx, 1280, 720, snapshot(), Object.fromEntries(publicPlayers.map((p) => [p.id, p])), "one", null, 0, 30); + const bars = rects.filter((rect) => rect.y === 720 - 84 - 12 - 1 && rect.h === 11).sort((a, b) => a.x - b.x); + expect(bars.map((bar) => [bar.x + 1, bar.w - 2])).toEqual([[44, 64], [120, 64], [1280 - 24 - 148, 64], [1280 - 24 - 72, 64]]); + }); +}); + +describe("result panel text", () => { + it("keeps a long winner name whole on a narrow screen instead of cutting the verdict", () => { + const texts: string[] = []; + const ctx = mockHudContext(texts); + const longName = "Anastasia-the-Great5"; + const players = { one: { id: "one", name: longName, avatar: null, rating: 1500, connected: true }, two: { id: "two", name: "Bo", avatar: null, rating: 1500, connected: true } }; + const final = { version: 3 as const, type: "final" as const, match_id: "m", winner_id: "one", method: "decision" as const, round: 2, scorecards: [{ judge: "Impact", player_one: [10, 10], player_two: [9, 10] }], ratings: { one: { before: 1000, after: 1016 }, two: { before: 1000, after: 984 } } }; + drawHud(ctx, 390, 844, { ...snapshot(), phase: "complete" }, players, "one", final, 0, 30); + expect(texts).toContain(`${longName} WINS`); + expect(texts.some((text) => text.startsWith(`${longName} 1000`))).toBe(true); + expect(texts.some((text) => text.startsWith("INPUT"))).toBe(false); + }); +}); diff --git a/web/hands/src/render/renderer-gpu.test.ts b/web/hands/src/render/renderer-gpu.test.ts new file mode 100644 index 00000000..e78c3736 --- /dev/null +++ b/web/hands/src/render/renderer-gpu.test.ts @@ -0,0 +1,248 @@ +import * as THREE from "three"; +import type { Settings } from "../settings"; +import { fighter, snapshot } from "../test/fixtures"; +import type { CombatEvent, FighterSnapshot, FinalMessage, MatchResult } from "../types"; +import { attachFakeWebGl, type FakeWebGl } from "../test/webgl"; +import type { Effects3D } from "./effects"; +import type { BoxingGraph } from "./graph"; +import { FightRenderer } from "./renderer"; + +/** The renderer's private parts a test drives or inspects. */ +interface Internals { + readonly renderer: THREE.WebGLRenderer; + readonly scene: THREE.Scene; + readonly scaler: { scale: number }; + applyResolutionScale(): void; + readonly keyLight: THREE.SpotLight; + readonly effects: Effects3D; + readonly graphs: readonly [BoxingGraph, BoxingGraph]; + restoreAllInjuries(): void; +} + +const punch = (eventId: number, tick: number, detail = "straight:head"): CombatEvent => ({ + event_id: eventId, tick, kind: "hit", actor_id: "one", target_id: "two", amount: 420, detail, blood: 100, direction: 1, action_id: `punch-${eventId}`, +}); + +/** Fighter one landing a straight on fighter two at `tick`. */ +const exchange = (tick: number, target: "head" | "body", downed = false): readonly [FighterSnapshot, FighterSnapshot] => [ + { ...fighter("one", -60), action_key: `straight:right:${target}:normal`, action_contact_tick: tick }, + { ...fighter("two", 60), is_downed: downed }, +]; + +/** Pushes the snapshot carrying `events` and the next one, so the manual clock presents the contact. */ +function land(fight: FightRenderer, tick: number, events: readonly CombatEvent[], fighters: readonly [FighterSnapshot, FighterSnapshot]): void { + fight.push({ ...snapshot(tick), fighters, events }); + fight.push({ ...snapshot(tick + 1), fighters }); +} + +/** The graphics-card handle three made for a texture. */ +const glTexture = (renderer: THREE.WebGLRenderer, texture: THREE.Texture | null | undefined): unknown => + texture === null || texture === undefined ? undefined : (renderer.properties.get(texture) as { __webglTexture?: unknown }).__webglTexture; + +const mounted: FightRenderer[] = []; + +/** Draws a few frames so everything the idle scene shows has been drawn once. */ +function settle(fight: FightRenderer, from = 0): number { + for (let frame = 1; frame <= 6; frame += 1) fight.labFrame(from + frame / 10); + return from + 0.6; +} + +async function mount(settings: Partial = {}, manualClock = true): Promise<{ gl: FakeWebGl; fight: FightRenderer; internals: Internals }> { + const canvas = document.createElement("canvas"); + document.body.append(canvas); + const gl = attachFakeWebGl(canvas); + const current: Settings = { volume: 0, haptics: false, reducedMotion: false, blood: "full", ...settings }; + const fight = new FightRenderer(canvas, undefined, () => current, { manualClock }); + mounted.push(fight); + await fight.ready; + return { gl, fight, internals: fight as unknown as Internals }; +} + +afterEach(() => { + for (const fight of mounted.splice(0)) fight.destroy(); + document.body.replaceChildren(); +}); + +describe("quality tiers on the graphics card", () => { + it("drops the key shadow at the low tier and brings it back without compiling a shader", async () => { + const { gl, fight, internals } = await mount(); + const setScale = (scale: number): void => { + internals.scaler.scale = scale; + internals.applyResolutionScale(); + }; + const time = settle(fight); + const programs = gl.created.programs; + const key = internals.keyLight; + const depth = glTexture(internals.renderer, key.shadow.map?.depthTexture); + expect(gl.alive(depth)).toBe(true); + setScale(0.55); + fight.labFrame(time + 0.1); + expect(gl.created.programs).toBe(programs); + expect(key.castShadow).toBe(true); + expect(key.shadow.intensity).toBe(0); + // The shadow map is no longer drawn, and its depth target is freed. + expect(key.shadow.map).toBeNull(); + expect(gl.alive(depth)).toBe(false); + setScale(0.7); + fight.labFrame(time + 0.2); + expect(gl.created.programs).toBe(programs); + expect(key.shadow.intensity).toBe(1); + expect(key.shadow.map).not.toBeNull(); + expect(key.shadow.map?.width).toBe(1024); + }); +}); + +describe("spray direction", () => { + it("throws the blood and the severed head along the punch when the fighters face each other along y", async () => { + const { fight, internals } = await mount(); + let time = settle(fight); + // One at (0, -60) punches two at (0, 60), towards world -z; the event still carries the engine's + // world-x sign, +1. + const fighters = [ + { ...fighter("one"), x: 0, y: -60, facing_x: 0, facing_y: 1000, action_key: "straight:right:head:normal", action_contact_tick: 20 }, + { ...fighter("two"), x: 0, y: 60, facing_x: 0, facing_y: -1000, is_downed: true }, + ] as const; + land(fight, 20, [punch(40, 20)], fighters); + for (let frame = 0; frame < 18; frame += 1) fight.labFrame((time += 1 / 60)); + expect(internals.effects.activeHeads).toBe(1); + const target = { x: 0, z: -60 * (3.05 / 500) }; + const positions = internals.effects.dropletBuffers.position; + const colors = internals.effects.dropletBuffers.color; + let x = 0; + let z = 0; + let count = 0; + for (let index = 0; index < positions.count; index += 1) { + if (positions.getY(index) < -10 || colors.getY(index) >= 0.2) continue; + x += positions.getX(index) - target.x; + z += positions.getZ(index) - target.z; + count += 1; + } + expect(count).toBeGreaterThan(50); + expect(z / count).toBeLessThan(-0.15); + expect(Math.abs(x / count)).toBeLessThan(Math.abs(z / count) / 2); + const head = new THREE.Vector3(); + internals.effects.severedHeadPosition(1, head); + expect(head.z - target.z).toBeLessThan(-0.2); + expect(Math.abs(head.x - target.x)).toBeLessThan(Math.abs(head.z - target.z)); + }); +}); + +describe("knockdown punch", () => { + it("leaves the punch's own dent in the face, not the knockdown's minimum one", async () => { + const { fight, internals } = await mount({ blood: "reduced" }); + const time = settle(fight); + const hit = { ...punch(51, 20), amount: 90 }; + const knockdown: CombatEvent = { ...hit, event_id: 52, kind: "knockdown", amount: 1, detail: "", blood: 0, direction: 0, action_id: null }; + land(fight, 20, [hit, knockdown], exchange(20, "head", true)); + fight.labFrame(time + 0.1); + // A straight to the head dents the mouth 1.1 cm, plus up to 2.1 cm more as the damage nears the engine's hardest hit (150). + expect(internals.graphs[1].boxer.headInjury.impactDepth).toBeCloseTo(1.1 + (2.1 * hit.amount) / 150, 2); + }); +}); + +describe("stoppage without a replay", () => { + it("cuts to the finish only once the punch that ended the bout is on screen", async () => { + const now = vi.spyOn(performance, "now").mockReturnValue(0); + const { fight } = await mount({}, false); + const draw = (time: number): void => (fight as unknown as { draw(time: number): void }).draw(time); + const presentFinish = vi.spyOn(fight as unknown as { presentFinish(final: FinalMessage): void }, "presentFinish"); + const shown: number[] = []; + fight.onContact = (event) => shown.push(event.event_id); + // Thirty ticks a second; the third knockdown ends the bout on tick 30, and the server stops there. + const finisher = { ...punch(300, 30, "hook:head"), amount: 520 }; + const knockdown: CombatEvent = { ...finisher, event_id: 301, kind: "knockdown", amount: 3, detail: "", blood: 0, direction: 0, action_id: null }; + const result: MatchResult = { + match_id: "m", activity_instance_id: "a", guild_id: "g", player_one_id: "one", player_two_id: "two", winner_id: "one", finish_method: "tko", + round_number: 1, tick: 30, scorecards: [], player_one_knockdowns: 0, player_two_knockdowns: 3, player_one_damage: 0, player_two_damage: 900, + }; + for (let tick = 1; tick <= 30; tick += 1) { + now.mockReturnValue((tick * 1000) / 30); + if (tick < 30) fight.push(snapshot(tick)); + else fight.push({ ...snapshot(30), phase: "complete", fighters: [{ ...exchange(30, "head")[0], action_key: "hook:left:head:power" }, { ...fighter("two", 60), is_downed: true, knockdowns: 3 }], events: [finisher, knockdown], result }); + draw((tick * 1000) / 30); + } + // The final message lands a moment after the result, while the screen is still two ticks behind it. + fight.setFinal({ version: 3, type: "final", match_id: "m", winner_id: "one", method: "tko", round: 1, scorecards: [], ratings: {} }); + expect(presentFinish).not.toHaveBeenCalled(); + for (let time = 1000; time < 1500 && presentFinish.mock.calls.length === 0; time += 1000 / 60) { + now.mockReturnValue(time); + draw(time); + } + expect(presentFinish).toHaveBeenCalledOnce(); + expect(shown).toContain(finisher.event_id); + }); +}); + +describe("device pixel ratio", () => { + const setDevicePixelRatio = (ratio: number): void => { + Object.defineProperty(window, "devicePixelRatio", { configurable: true, value: ratio }); + }; + afterEach(() => setDevicePixelRatio(2)); + + it("follows a zoom or a move to another monitor, capped and scaled by the quality tier", async () => { + const { fight, internals } = await mount(); + fight.labFrame(0.1); + expect(internals.renderer.getPixelRatio()).toBe(2); + setDevicePixelRatio(1.25); + fight.labFrame(0.2); + expect(internals.renderer.getPixelRatio()).toBe(1.25); + setDevicePixelRatio(3); + fight.labFrame(0.3); + expect(internals.renderer.getPixelRatio()).toBe(2); + internals.scaler.scale = 0.7; + internals.applyResolutionScale(); + setDevicePixelRatio(1); + fight.labFrame(0.4); + expect(internals.renderer.getPixelRatio()).toBeCloseTo(0.7); + }); +}); + +describe("graphics memory across rematches on a shared context", () => { + it("leaves nothing on the context but what three itself keeps per renderer", async () => { + // A bare renderer's own leftovers: its state's placeholder textures and its copy framebuffers. + const bareCanvas = document.createElement("canvas"); + const bare = attachFakeWebGl(bareCanvas); + new THREE.WebGLRenderer({ canvas: bareCanvas }).dispose(); + const { gl, fight, internals } = await mount(); + const time = settle(fight); + land(fight, 20, [punch(41, 20)], exchange(20, "head")); + fight.labFrame(time + 0.1); + expect(internals.effects.liveGibs).toBeGreaterThan(0); + // Upload every canvas-drawn texture the scene uses, as drawing it on a real card does. + internals.scene.traverse((object) => { + for (const material of [(object as THREE.Mesh).material ?? []].flat()) { + for (const value of Object.values(material)) if (value instanceof THREE.CanvasTexture) internals.renderer.initTexture(value); + } + }); + // The shadow map's depth material belongs to three and is never disposed. + const threeOwned = internals.renderer.info.programs!.filter((program) => program.cacheKey.startsWith("depth,")).map((program) => (program as unknown as { program: unknown }).program); + fight.destroy(); + const live = gl.live(); + expect(live.buffers).toBe(0); + expect(live.vertexArrays).toBe(0); + expect(live.renderbuffers).toBe(0); + expect(live.textures).toBe(bare.live().textures); + expect(live.framebuffers).toBe(bare.live().framebuffers); + expect(live.programs).toBe(threeOwned.filter((program) => gl.alive(program)).length); + }); +}); + +describe("shaders for effects that start hidden", () => { + it("are compiled before the first bloody hit, decapitation and severed hand", async () => { + const { gl, fight, internals } = await mount(); + let time = settle(fight); + const programs = gl.created.programs; + land(fight, 20, [punch(41, 20)], exchange(20, "head")); + fight.labFrame((time += 0.1)); + expect(internals.effects.visibleDecals).toBeGreaterThan(0); + land(fight, 22, [punch(42, 22)], exchange(22, "head", true)); + fight.labFrame((time += 0.1)); + expect(internals.effects.activeHeads).toBe(1); + internals.restoreAllInjuries(); + land(fight, 24, [punch(44, 24, "straight:body")], exchange(24, "body", true)); + fight.labFrame((time += 0.1)); + expect(internals.effects.activeHands).toBe(1); + fight.labFrame((time += 0.1)); + expect(gl.created.programs).toBe(programs); + }); +}); diff --git a/web/hands/src/render/renderer.test.ts b/web/hands/src/render/renderer.test.ts index 960af0ba..aa8ca9ed 100644 --- a/web/hands/src/render/renderer.test.ts +++ b/web/hands/src/render/renderer.test.ts @@ -1,12 +1,9 @@ import { fighter, snapshot } from "../test/fixtures"; import type { CombatEvent, MatchResult } from "../types"; -import { - arcadeInjuryFor, - contactParticipants, - contactPresentationPlan, - isArcadeInjuryCandidate, - presentationTickFor, -} from "./renderer"; +import * as THREE from "three"; +import { releaseSharedGpu, disposeSkeletons } from "./graph"; +import { arcadeInjuryFor, canStartPunch, compileForComposer, contactParticipants, contactPresentationPlan, disposeComposer, FightRenderer, isArcadeInjuryCandidate, presentationTickFor, refereeSpacing, replayCameraSide, replayReattaches, sprayDirection } from "./renderer"; +import { worldMapping } from "./world"; const event = (kind: string, detail: string): CombatEvent => ({ event_id: 1, @@ -75,6 +72,34 @@ describe("contact presentation tick", () => { expect(plan[0]!.presentationEvent).toMatchObject({ kind: "block", detail: "straight:body", direction: -1, blood: 12 }); expect(plan[2]!.presentationEvent).toMatchObject({ kind: "knockdown", detail: "straight:body", direction: -1, blood: 12 }); }); + + it("reacts once to the punch that knocks a fighter down, at the punch's own strength", () => { + const frame = snapshot(10); + const hit = event("hit", "straight:head"); + const knockdown = { ...event("knockdown", ""), event_id: 2, amount: 1, blood: 0, direction: 0, action_id: null }; + expect(contactPresentationPlan([hit, knockdown], frame).map((entry) => entry.reactAmount)).toEqual([500, null]); + // Through a block, the block's entry presents the punch, so the knockdown reacts for the hit that leaked. + const block = { ...event("block", ""), actor_id: "two", target_id: "one", amount: 30, blood: 0, direction: 0 }; + expect(contactPresentationPlan([block, { ...hit, amount: 18 }, knockdown], frame).map((entry) => entry.reactAmount)).toEqual([30, 18, 18]); + }); +}); + +describe("spray direction", () => { + const mapping = worldMapping({ tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }); + + it("runs from the puncher to the recipient in the world, whichever way they face", () => { + const towards = (from: [number, number], to: [number, number]) => sprayDirection({ ...fighter("one"), x: from[0], y: from[1] }, { ...fighter("two"), x: to[0], y: to[1] }, mapping); + expect(towards([0, -60], [0, 60])).toEqual({ x: 0, z: -1 }); + expect(towards([60, 0], [-60, 0])).toEqual({ x: -1, z: 0 }); + const diagonal = towards([0, 0], [100, 100])!; + expect(diagonal.x).toBeCloseTo(Math.SQRT1_2); + expect(diagonal.z).toBeCloseTo(-Math.SQRT1_2); + }); + + it("leaves effects to the event's sign when a fighter is missing or both stand on one spot", () => { + expect(sprayDirection(undefined, fighter("two"), mapping)).toBeUndefined(); + expect(sprayDirection(fighter("one", 40), fighter("two", 40), mapping)).toBeUndefined(); + }); }); describe("arcade injury candidate routing", () => { @@ -106,3 +131,114 @@ describe("arcade injury candidate routing", () => { expect(isArcadeInjuryCandidate(combatEvent, target, result)).toBe(false); }); }); + +describe("referee spacing", () => { + it("stands off during the action, steps in for a clinch and tightest over a count", () => { + expect(refereeSpacing(false, false).standoff).toBeGreaterThan(refereeSpacing(false, true).standoff); + expect(refereeSpacing(false, true).standoff).toBeGreaterThan(refereeSpacing(true, true).standoff - 0.2); + expect(refereeSpacing(true, false).clearance).toBeLessThan(refereeSpacing(false, false).clearance); + expect(refereeSpacing(false, true).clearance).toBeLessThan(refereeSpacing(false, false).clearance); + }); +}); + +describe("knockout replay injuries", () => { + it("reattaches severed parts for the replay but leaves dislocations in place", () => { + expect(replayReattaches("decapitation")).toBe(true); + expect(replayReattaches("dismember_left")).toBe(true); + expect(replayReattaches("dismember_right")).toBe(true); + expect(replayReattaches("jaw_dislocation")).toBe(false); + expect(replayReattaches("shoulder_left")).toBe(false); + }); +}); + +describe("replay camera side", () => { + it("shoots from the broadcast side with room to spare and switches when the ropes would crowd it", () => { + expect(replayCameraSide(0, 0, 0, 1, 2.5, 2.2)).toBe(1); + expect(replayCameraSide(0, 0, 0, -1, 2.5, 2.2)).toBe(-1); + expect(replayCameraSide(0, 1.2, 0, 1, 2.5, 2.2)).toBe(-1); + expect(replayCameraSide(0, 2.4, 0, 1, 2.5, 2.2)).toBe(-1); + expect(replayCameraSide(0, -1.5, 0, 1, 2.5, 2.2)).toBe(1); + }); +}); + +describe("punch prediction gate", () => { + it("only predicts a punch the server would start", () => { + const ready = fighter("one"); + expect(canStartPunch(ready)).toBe(true); + expect(canStartPunch({ ...ready, is_downed: true })).toBe(false); + expect(canStartPunch({ ...ready, stunned_ticks: 3 })).toBe(false); + expect(canStartPunch({ ...ready, clinch_ticks: 10 })).toBe(false); + expect(canStartPunch({ ...ready, taunt_ticks: 10 })).toBe(false); + expect(canStartPunch({ ...ready, is_foul_recovery_target: true })).toBe(false); + }); +}); + +describe("replay injuries", () => { + it("does not sever again when reduced motion or a lower blood level was chosen during the replay", () => { + const event = { event_id: 5, tick: 10, kind: "knockdown", actor_id: "one", target_id: "two", amount: 400, detail: "", blood: 60, direction: 1, action_id: null }; + const apply = (settings: { blood: string; reducedMotion: boolean }): number => { + const applied: unknown[] = []; + const stub = { replayInjuries: [{ injury: "decapitation", event }, null], settings: () => settings, applyArcadeInjury: (...args: unknown[]) => { applied.push(args); return true; } }; + (FightRenderer.prototype as unknown as { reapplyReplayInjuries: () => void }).reapplyReplayInjuries.call(stub); + expect(stub.replayInjuries[0]).toBeNull(); + return applied.length; + }; + expect(apply({ blood: "full", reducedMotion: false })).toBe(1); + expect(apply({ blood: "full", reducedMotion: true })).toBe(0); + expect(apply({ blood: "reduced", reducedMotion: false })).toBe(0); + }); +}); + +describe("graphics memory across rematches", () => { + it("frees every composer pass before the composer itself", () => { + const order: string[] = []; + const composer = { + passes: [{ dispose: () => order.push("render") }, {}, { dispose: () => order.push("bloom") }, { dispose: () => order.push("output") }], + dispose: () => order.push("composer"), + }; + disposeComposer(composer); + expect(order).toEqual(["render", "bloom", "output", "composer"]); + }); + + it("frees each fighter's bone texture with the fighter", () => { + const bones = [new THREE.Bone(), new THREE.Bone()]; + bones[0]!.add(bones[1]!); + const meshes = [0, 1].map(() => { + const mesh = new THREE.SkinnedMesh(new THREE.BufferGeometry(), new THREE.MeshBasicMaterial()); + mesh.bind(new THREE.Skeleton(bones)); + return mesh; + }); + const root = new THREE.Group(); + root.add(bones[0]!, ...meshes); + const disposed = meshes.map((mesh) => vi.spyOn(mesh.skeleton, "dispose")); + disposeSkeletons(root); + for (const spy of disposed) expect(spy).toHaveBeenCalledOnce(); + }); + + it("frees the graphics copies of the shared model and textures but keeps their data for the next renderer", () => { + const geometry = new THREE.BoxGeometry(); + const scene = new THREE.Group(); + scene.add(new THREE.Mesh(geometry), new THREE.Group().add(new THREE.SkinnedMesh(geometry, new THREE.MeshBasicMaterial()))); + const texture = new THREE.Texture(); + const geometryDisposed = vi.fn(); + const textureDisposed = vi.fn(); + geometry.addEventListener("dispose", geometryDisposed); + texture.addEventListener("dispose", textureDisposed); + releaseSharedGpu(scene, [texture]); + expect(geometryDisposed).toHaveBeenCalled(); + expect(textureDisposed).toHaveBeenCalledOnce(); + expect(geometry.getAttribute("position").count).toBeGreaterThan(0); + releaseSharedGpu(null, []); + }); + + it("compiles the fighters' shaders for the composer's own target, then lets go of it", async () => { + const calls: string[] = []; + const readBuffer = { name: "composer target" }; + const renderer = { + setRenderTarget: (target: unknown) => calls.push(target === readBuffer ? "bind composer target" : target === null ? "unbind" : "bind other"), + compileAsync: () => { calls.push("compile"); return Promise.resolve(); }, + }; + await compileForComposer(renderer as unknown as Parameters[0], { readBuffer } as unknown as Parameters[1], new THREE.Group(), new THREE.PerspectiveCamera(), new THREE.Scene()); + expect(calls).toEqual(["bind composer target", "compile", "unbind"]); + }); +}); diff --git a/web/hands/src/render/renderer.ts b/web/hands/src/render/renderer.ts index 52e5fc5e..79a6e038 100644 --- a/web/hands/src/render/renderer.ts +++ b/web/hands/src/render/renderer.ts @@ -3,16 +3,21 @@ import { EffectComposer } from "three/examples/jsm/postprocessing/EffectComposer import { RenderPass } from "three/examples/jsm/postprocessing/RenderPass.js"; import { UnrealBloomPass } from "three/examples/jsm/postprocessing/UnrealBloomPass.js"; import { OutputPass } from "three/examples/jsm/postprocessing/OutputPass.js"; +import { ShaderPass } from "three/examples/jsm/postprocessing/ShaderPass.js"; import { EventDeduplicator, SnapshotBuffer } from "../interpolation"; +import { coarsePointer } from "../input/touch"; +import { REST_CORNER_OFFSET, punchTiming } from "../manifest"; +import { EVASION_STAMINA, EvasionPrediction, MovementPrediction, attackTicksRemaining, canAffordPunch, constrainPrediction, isEvasion, predictedDefense, predictedPunchTiming, type HeldInput } from "../prediction"; import type { BloodLevel, Settings } from "../settings"; -import type { CombatEvent, EngineSnapshot, FighterSnapshot, FinalMessage, MatchResult, PublicPlayer, SemanticAction, SimulationInfo } from "../types"; -import { BoxerAnimator } from "./animation"; +import type { CombatEvent, EngineSnapshot, FighterSnapshot, FinalMessage, Hand, MatchResult, PublicPlayer, PunchClass, SemanticAction, SimulationInfo } from "../types"; import { buildArena, type BuiltArena } from "./arena"; -import { buildBoxer, buildReferee, disposeBoxer, type BoxerRig } from "./boxer"; -import { CameraDirector } from "./camera"; -import { Effects3D } from "./effects"; -import { BoxingGraph, SkinnedBoxer, loadBoxerGlb, type ArcadeDislocation } from "./graph"; -import { drawHud } from "./hud"; +import { CameraDirector, CUTMAN_WORK_DEGREES, CUTMAN_WORK_DISTANCE, cornerFrame, cornerPoint, cornerShot, cornerShotProgress } from "./camera"; +import { Effects3D, type BakedPart, type SprayDirection } from "./effects"; +import { BoxingGraph, SkinnedBoxer, loadBoxerGlb, releaseFighterGpu, type ArcadeDislocation } from "./graph"; +import { drawHud, finalRevealDelay, RoundStatsTracker, STOPPAGE_METHODS, RoundClock } from "./hud"; +import { ResolutionScaler } from "./quality"; +import { planKnockoutReplay, replayTick, type ReplayPlan } from "./replay"; +import { GloveTrail } from "./trails"; export type ArcadeInjury = | "decapitation" @@ -36,6 +41,50 @@ export function isArcadeInjuryCandidate( ); } +/** EffectComposer.dispose frees only its own targets; each pass (bloom keeps a chain of them) is freed too. */ +export function disposeComposer(composer: { readonly passes: readonly { dispose?: () => void }[]; dispose(): void }): void { + for (const pass of composer.passes) pass.dispose?.(); + composer.dispose(); +} + +/** + * Compiles a scene's shaders for the composer's own target (linear, without tone mapping), which is + * what the scene is drawn into; compiled for the screen they would be variants the frame never uses. + */ +export function compileForComposer( + renderer: Pick, + composer: { readonly readBuffer: THREE.WebGLRenderTarget }, + staging: THREE.Object3D, + camera: THREE.Camera, + scene: THREE.Scene, +): Promise { + renderer.setRenderTarget(composer.readBuffer); + // compileAsync builds the programs before it returns, so the target can be let go at once. + const compiled = renderer.compileAsync(staging, camera, scene); + renderer.setRenderTarget(null); + return compiled; +} + +const KEY_SHADOW_BIAS = -0.0004; +/** Past the shadow camera's far plane, so every lit pixel skips the shadow lookups. */ +const SKIPPED_SHADOW_BIAS = 10; + +/** + * Sets the key light's shadow for a quality tier without touching castShadow, which is part of every + * material's program key: flipping it would recompile every shader in one frame on the slowest + * devices. Turned off, the shadow stops being drawn, its depth target is freed, and it is hidden. + */ +export function setKeyShadowTier(shadow: THREE.LightShadow, off: boolean, size: number): void { + shadow.autoUpdate = !off; + shadow.intensity = off ? 0 : 1; + shadow.bias = off ? SKIPPED_SHADOW_BIAS : KEY_SHADOW_BIAS; + if ((off && shadow.map !== null) || shadow.mapSize.x !== size) { + shadow.mapSize.set(size, size); + shadow.map?.dispose(); + shadow.map = null; + } +} + export function contactParticipants(event: CombatEvent, snapshot: EngineSnapshot): { recipientIndex: number; puncherIndex: number; @@ -49,14 +98,72 @@ export function contactParticipants(event: CombatEvent, snapshot: EngineSnapshot }; } +/** + * The way a punch travelled in the world, from the puncher to the recipient, for its blood, teeth and + * severed parts. Hit events only carry the sign of the puncher's world-x facing, which is wrong + * whenever the fighters exchange along any other line of the square ring; undefined leaves effects + * to that sign, when a fighter is missing or the two stand on the same spot. + */ +export function sprayDirection(puncher: FighterSnapshot | undefined, recipient: FighterSnapshot | undefined, mapping: WorldMapping): SprayDirection | undefined { + if (puncher === undefined || recipient === undefined) return undefined; + const x = mapping.x(recipient.x) - mapping.x(puncher.x); + const z = mapping.z(recipient.y) - mapping.z(puncher.y); + const length = Math.hypot(x, z); + return Number.isFinite(length) && length > 1e-3 ? { x: x / length, z: z / length } : undefined; +} + export interface ContactPresentation { readonly event: CombatEvent; readonly presentationEvent: CombatEvent; readonly presentImpact: boolean; + /** How hard the recipient reacts, or null when the punch's own entry already reacts to it. */ + readonly reactAmount: number | null; } const isHit = (event: CombatEvent): boolean => event.kind === "hit" || event.kind === "counter_hit"; const isBlock = (event: CombatEvent): boolean => event.kind === "block" || event.kind === "perfect_block"; +const HISTORY_LIMIT = 480; +const LOW_TIER_SCALE = 0.56; +const ROUND_CALLOUT_SECONDS = 1.8; +const FINISH_CLOSE_UP_SECONDS = 1.7; +/** Longest a finish waits for its punch to be shown (the render clock runs at most 6 ticks behind). */ +const FINISH_WAIT_LIMIT_SECONDS = 0.5; +const CORNERMAN_APRON_DISTANCE = 3.42; +/** Close cameras stay inside the rope line (posts stand at 2.46 m) so a rope never fills the lens. */ +const TIGHT_SHOT_LIMIT = 2.2; +const CORNERMAN_WORK_DISTANCE = 2.95; +/** Metres per second the referee steps in at to break a clinch. */ +const REFEREE_BREAK_SPEED = 2.4; +const CUTMAN_WALK_SECONDS = 1.6; +// Broadcast finish: a soft vignette and a whisper of grain, applied before tone mapping. +const BROADCAST_FINISH_SHADER = { + uniforms: { tDiffuse: { value: null }, uTime: { value: 0 }, uVignette: { value: 0.32 }, uGrain: { value: 0.035 } }, + vertexShader: ` +varying vec2 vUv; +void main() { + vUv = uv; + gl_Position = projectionMatrix * modelViewMatrix * vec4(position, 1.0); +}`, + fragmentShader: ` +uniform sampler2D tDiffuse; +uniform float uTime; +uniform float uVignette; +uniform float uGrain; +varying vec2 vUv; +float hash(vec2 p) { + return fract(sin(dot(p, vec2(127.1, 311.7)) + uTime * 43.7) * 43758.5453); +} +void main() { + vec4 color = texture2D(tDiffuse, vUv); + vec2 centered = vUv - 0.5; + float falloff = smoothstep(0.35, 0.95, dot(centered, centered) * 2.2); + color.rgb *= 1.0 - falloff * uVignette; + float grain = (hash(floor(vUv * vec2(960.0, 540.0))) - 0.5) * uGrain; + color.rgb += grain * (0.15 + color.rgb); + gl_FragColor = color; +}`, +}; +const CROWD_EXCITEMENT: Readonly> = { hit: 0.18, counter_hit: 0.3, guard_break: 0.25, knockdown: 1, block: 0.04, perfect_block: 0.1 }; function pairedBlock(event: CombatEvent, events: readonly CombatEvent[]): CombatEvent | undefined { if (!isHit(event) || event.action_id === null) return undefined; @@ -94,10 +201,11 @@ export function contactPresentationPlan( blood: hit?.blood ?? event.blood, }, presentImpact: true, + reactAmount: event.amount, }; } if (pairedBlock(event, events) !== undefined) { - return { event, presentationEvent: event, presentImpact: false }; + return { event, presentationEvent: event, presentImpact: false, reactAmount: event.amount }; } if (event.kind === "knockdown") { const hitEvent = events.slice(0, eventIndex).reverse().find((candidate) => isHit(candidate) @@ -115,10 +223,12 @@ export function contactPresentationPlan( action_id: hitEvent.action_id, }, presentImpact: true, + // A knockdown's amount is its count. The punch reacts in its own entry, unless a block took its place. + reactAmount: pairedBlock(hitEvent, events) === undefined ? null : hitEvent.amount, }; } } - return { event, presentationEvent: event, presentImpact: true }; + return { event, presentationEvent: event, presentImpact: true, reactAmount: event.amount }; }); } @@ -141,7 +251,7 @@ export function arcadeInjuryFor( } import { buildRing, disposeRing, type BuiltRing } from "./ring"; import { resizeHighDpi } from "./viewport"; -import { PALETTES, worldMapping, type WorldMapping } from "./world"; +import { worldMapping, type WorldMapping } from "./world"; function blobShadowTexture(): THREE.CanvasTexture { const canvas = document.createElement("canvas"); @@ -159,7 +269,197 @@ function blobShadowTexture(): THREE.CanvasTexture { return new THREE.CanvasTexture(canvas); } -const DEFAULT_SIM: SimulationInfo = { tick_rate: 30, ring_half_width: 500, ring_half_height: 330 }; +const DEFAULT_SIM: SimulationInfo = { tick_rate: 30, ring_half_width: 500, ring_half_height: 500 }; + +/** + * Freezes a skinned mesh's current deformed surface into a static geometry + * expressed relative to `pivot` so it can fly as a rigid severed part. Only the + * vertices its triangles use are kept: each glove of the model indexes its own + * half of a vertex buffer the two gloves share. + */ +export function bakeSkinnedPart(mesh: THREE.SkinnedMesh, pivotPosition: THREE.Vector3, pivotQuaternion: THREE.Quaternion): BakedPart { + const source = mesh.geometry; + const positions = source.getAttribute("position"); + const index = source.getIndex(); + // The source vertex behind each kept vertex, and the triangles renumbered to the kept vertices. + const kept: number[] = []; + const triangles: number[] = []; + if (index === null) { + for (let vertex = 0; vertex < positions.count; vertex += 1) kept.push(vertex); + } else { + const renumbered = new Int32Array(positions.count).fill(-1); + for (let corner = 0; corner < index.count; corner += 1) { + const vertex = index.getX(corner); + if (renumbered[vertex]! < 0) renumbered[vertex] = kept.push(vertex) - 1; + triangles.push(renumbered[vertex]!); + } + } + const baked = new Float32Array(kept.length * 3); + const vertex = new THREE.Vector3(); + const inverse = pivotQuaternion.clone().invert(); + mesh.updateMatrixWorld(true); + for (const [target, from] of kept.entries()) { + vertex.fromBufferAttribute(positions, from); + mesh.applyBoneTransform(from, vertex); + vertex.applyMatrix4(mesh.matrixWorld).sub(pivotPosition).applyQuaternion(inverse); + baked[target * 3] = vertex.x; + baked[target * 3 + 1] = vertex.y; + baked[target * 3 + 2] = vertex.z; + } + const geometry = new THREE.BufferGeometry(); + geometry.setAttribute("position", new THREE.BufferAttribute(baked, 3)); + const uv = source.getAttribute("uv"); + if (uv !== undefined) { + const uvs = new Float32Array(kept.length * 2); + for (const [target, from] of kept.entries()) { + uvs[target * 2] = uv.getX(from); + uvs[target * 2 + 1] = uv.getY(from); + } + geometry.setAttribute("uv", new THREE.BufferAttribute(uvs, 2)); + } + if (index !== null) geometry.setIndex(triangles); + geometry.computeVertexNormals(); + const material = Array.isArray(mesh.material) ? mesh.material[0] : mesh.material; + const map = material instanceof THREE.MeshStandardMaterial ? material.map : null; + const color = material instanceof THREE.MeshStandardMaterial ? material.color.getHex() : 0xffffff; + return { geometry, map, color }; +} + +function cornerShirtTexture(color: string): THREE.CanvasTexture { + const canvas = document.createElement("canvas"); + canvas.width = 256; + canvas.height = 256; + const ctx = canvas.getContext("2d"); + if (ctx !== null) { + ctx.fillStyle = color; + ctx.fillRect(0, 0, 256, 256); + ctx.fillStyle = "rgba(0,0,0,0.35)"; + ctx.fillRect(0, 0, 256, 16); + ctx.fillStyle = "rgba(255,255,255,0.12)"; + ctx.fillRect(96, 60, 64, 22); + } + const texture = new THREE.CanvasTexture(canvas); + texture.colorSpace = THREE.SRGBColorSpace; + texture.flipY = false; + return texture; +} + +function refereeShirtTexture(): THREE.CanvasTexture { + const canvas = document.createElement("canvas"); + canvas.width = 256; + canvas.height = 256; + const ctx = canvas.getContext("2d"); + if (ctx !== null) { + ctx.fillStyle = "#9fb4d8"; + ctx.fillRect(0, 0, 256, 256); + ctx.fillStyle = "rgba(255,255,255,0.08)"; + for (let x = 0; x < 256; x += 8) ctx.fillRect(x, 0, 2, 256); + ctx.fillStyle = "#1b2230"; + ctx.fillRect(0, 0, 256, 18); + } + const texture = new THREE.CanvasTexture(canvas); + texture.colorSpace = THREE.SRGBColorSpace; + texture.flipY = false; + return texture; +} + +function blankFighter(playerId: string): FighterSnapshot { + return { + player_id: playerId, x: 0, y: 0, facing: 1, facing_x: 1000, facing_y: 0, velocity_x: 0, velocity_y: 0, + stance: "orthodox", defense: "guard_high", stamina: 1000, maximum_stamina: 1000, conditioning: 1000, guard: 700, poise: 600, + trauma: { head: 0, body: 0, left_eye: 0, right_eye: 0, left_cut: 0, right_cut: 0, swelling: 0, bleeding: 0 }, + knockdowns: 0, warnings: 0, deductions: 0, stunned_ticks: 0, is_downed: false, + action: null, action_hand: null, action_target: null, action_power: null, action_id: null, action_key: null, + action_start_tick: 0, action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, + queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, taunt_ticks: 0, + get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, get_up_window_start_tick: 0, get_up_window_end_tick: 0, + last_input_sequence: -1, + }; +} + +const SHADOW_BOXING_CYCLE_TICKS = 126; +const SHADOW_BOXING: readonly { readonly start: number; readonly punchClass: PunchClass; readonly hand: Hand }[] = [ + { start: 0, punchClass: "jab", hand: "left" }, + { start: 16, punchClass: "jab", hand: "left" }, + { start: 33, punchClass: "straight", hand: "right" }, + { start: 78, punchClass: "hook", hand: "left" }, +]; + +/** A lone fighter shadow boxes while waiting: a jab-jab-straight then a hook every few seconds. */ +function shadowBoxing(idleTick: number): Partial { + const cycleTick = idleTick % SHADOW_BOXING_CYCLE_TICKS; + const cycle = Math.floor(idleTick / SHADOW_BOXING_CYCLE_TICKS); + for (const [index, punch] of SHADOW_BOXING.entries()) { + const timing = punchTiming(punch.punchClass, "head", "normal"); + const total = timing.startup + timing.active + timing.recovery; + if (cycleTick < punch.start || cycleTick >= punch.start + total) continue; + return { + action: punch.punchClass, action_hand: punch.hand, action_target: "head", action_power: "normal", + action_id: `idle-${cycle}-${index}`, action_key: `${punch.punchClass}:${punch.hand}:head:normal`, + action_start_tick: idleTick - (cycleTick - punch.start), action_startup_ticks: timing.startup, action_active_ticks: timing.active, action_recovery_ticks: timing.recovery, + action_contact_tick: idleTick - (cycleTick - punch.start) + timing.startup, + }; + } + return {}; +} + +const REPLAY_EVENT_ID_OFFSET = 1_000_003; +const REPLAY_MINIMUM_DISTANCE = 1.6; + +/** + * Which side of the fighters' line the replay camera shoots from: the broadcast side, unless the + * ropes would crowd it there and the other side has more room. + */ +export function replayCameraSide(midX: number, midZ: number, nx: number, nz: number, distance: number, limit: number): 1 | -1 { + const preferred = nz < 0 ? -1 : 1; + const room = (side: number): number => Math.hypot( + THREE.MathUtils.clamp(midX + nx * side * distance, -limit, limit) - midX, + THREE.MathUtils.clamp(midZ + nz * side * distance, -limit, limit) - midZ, + ); + return room(preferred) >= distance * 0.8 || room(preferred) >= room(-preferred) ? preferred : (-preferred as 1 | -1); +} + +/** Whether the server would start a punch for this fighter now. */ +export function canStartPunch(fighter: FighterSnapshot): boolean { + return !fighter.is_downed + && fighter.stunned_ticks === 0 + && fighter.clinch_ticks === 0 + && fighter.clinch_startup_ticks === 0 + && fighter.taunt_ticks === 0 + && !fighter.is_foul_recovery_target; +} + +/** Whether the knockout replay puts this injury back so it can happen again on screen. */ +export function replayReattaches(injury: ArcadeInjury): boolean { + return injury === "decapitation" || injury === "dismember_left" || injury === "dismember_right"; +} + +/** How far the referee stands from the action and how close he may get to a fighter: tight over a count, in close for a clinch, between the two to break it, otherwise out of the way. */ +export function refereeSpacing(downed: boolean, clinched: boolean, breaking = false): { standoff: number; clearance: number } { + if (downed) return { standoff: 1.25, clearance: 1.0 }; + if (breaking) return { standoff: 0.45, clearance: 0.5 }; + if (clinched) return { standoff: 1.15, clearance: 0.9 }; + return { standoff: 2.05, clearance: 1.45 }; +} + +function refereeSnapshot(position: THREE.Vector3, yaw: number, velocity: THREE.Vector3, mapping: WorldMapping): { self: FighterSnapshot; focus: FighterSnapshot } { + const simX = position.x / mapping.x(1); + const simY = position.z / mapping.z(1); + const base: FighterSnapshot = { + player_id: "referee", x: simX, y: simY, facing: 1, facing_x: Math.round(Math.sin(yaw) * 1000), facing_y: Math.round(-Math.cos(yaw) * 1000), + velocity_x: velocity.x / mapping.x(1) / 30, velocity_y: velocity.z / mapping.z(1) / 30, + stance: "orthodox", defense: "none", stamina: 1000, maximum_stamina: 1000, conditioning: 1000, guard: 700, poise: 600, + trauma: { head: 0, body: 0, left_eye: 0, right_eye: 0, left_cut: 0, right_cut: 0, swelling: 0, bleeding: 0 }, + knockdowns: 0, warnings: 0, deductions: 0, stunned_ticks: 0, is_downed: false, + action: null, action_hand: null, action_target: null, action_power: null, action_id: null, action_key: null, + action_start_tick: 0, action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, + queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, taunt_ticks: 0, + get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, get_up_window_start_tick: 0, get_up_window_end_tick: 0, + last_input_sequence: -1, + }; + const focus: FighterSnapshot = { ...base, player_id: "focus", x: simX + Math.sin(yaw) * 300, y: simY - Math.cos(yaw) * 300 }; + return { self: base, focus }; +} export class FightRenderer { private readonly renderer: THREE.WebGLRenderer; @@ -168,14 +468,32 @@ export class FightRenderer { private readonly composer: EffectComposer; private readonly ring: BuiltRing; private readonly arena: BuiltArena; - private readonly boxers: [BoxerRig, BoxerRig]; - private readonly referee: BoxerRig; + private referee: BoxingGraph | null = null; + private cornermen: [BoxingGraph, BoxingGraph] | null = null; + private trails: GloveTrail[] = []; + private readonly trailGlove = new THREE.Vector3(); + private readonly cornerShirts: THREE.CanvasTexture[] = []; + private readonly cornermanPosition = new THREE.Vector3(); + private readonly cornermanVelocity = new THREE.Vector3(); + private cutmen: [BoxingGraph, BoxingGraph] | null = null; + private readonly cutmanProgress = [0, 0]; + private readonly cutmanFrom = new THREE.Vector3(); + private readonly cutmanTo = new THREE.Vector3(); + private readonly cutmanEye = new THREE.Vector3(); + private readonly cutmanFacing = new THREE.Vector3(); + private readonly cutmanLast = [new THREE.Vector3(), new THREE.Vector3()]; private readonly refereePosition = new THREE.Vector3(0.4, 0, -2.1); - private readonly animators: [BoxerAnimator, BoxerAnimator]; + private readonly refereeVelocity = new THREE.Vector3(); private readonly effects: Effects3D; private readonly director = new CameraDirector(); private readonly mapping: WorldMapping; - private readonly buffer = new SnapshotBuffer(); + private readonly buffer: SnapshotBuffer; + private readonly localInput: (() => HeldInput | null) | null; + /** Sequence of the input frame that carried a press, once it has gone out; null before then. */ + private readonly inputSequenceOf: ((actionId: string) => number | null) | null; + private readonly movement = new MovementPrediction(); + private readonly evasion = new EvasionPrediction(); + private lastManualTime = 0; private readonly dedupe = new EventDeduplicator(); private readonly hudCanvas: HTMLCanvasElement; private cameraOverride: { position: THREE.Vector3; lookAt: THREE.Vector3 } | null = null; @@ -190,25 +508,64 @@ export class FightRenderer { private refereeYaw = 0; private raf = 0; private previous = performance.now(); + private readonly scaler = new ResolutionScaler(); + private readonly pixelRatioCap = coarsePointer() ? 1.5 : 2; + private basePixelRatio = Math.min(this.pixelRatioCap, window.devicePixelRatio || 1); private players: Readonly> = {}; + private playerOrder: readonly string[] = []; private viewerId: string | null = null; private final: FinalMessage | null = null; private reconnectMs = 0; private destroyed = false; private graphs: [BoxingGraph, BoxingGraph] | null = null; private glbLoading = false; + private refereeShirt: THREE.CanvasTexture | null = null; private graphsReady: Promise = Promise.resolve(); private readonly headCache = [new THREE.Vector3(), new THREE.Vector3()]; private readonly headCacheValid = [false, false]; private readonly arcadeInjuries: [ArcadeInjury | null, ArcadeInjury | null] = [null, null]; private readonly observedInjuryDown: [boolean, boolean] = [false, false]; + private readonly arcadeInjuryEvents: [CombatEvent | null, CombatEvent | null] = [null, null]; + private readonly replayInjuries: [{ injury: ArcadeInjury; event: CombatEvent } | null, { injury: ArcadeInjury; event: CombatEvent } | null] = [null, null]; + private readonly closeUpTarget = new THREE.Vector3(); private readonly downedPoolAccumulators: [number, number] = [0, 0]; private readonly downedPoolCounts: [number, number] = [0, 0]; private bloodLevel: BloodLevel = "full"; + private viewerHitFlash = 0; + private finishSlowMotion = 0; + private finishSeen = false; + private finalRevealAt = 0; + private pendingFinish: { readonly final: FinalMessage; readonly tick: number; readonly latestAt: number } | null = null; + private portraitPull = 1; + private lastPhase: string | null = null; + private restStartedAt = 0; + private readonly roundClock = new RoundClock(); + private replayFollow = 0; + private replayFollowAt = 0; + private readonly cornerPosition = new THREE.Vector3(); + private readonly cornerLookAt = new THREE.Vector3(); + private finishCloseUpUntil = 0; + private finishCloseUpIndex = -1; + private readonly closeUpPosition = new THREE.Vector3(); + private roundCalloutUntil = 0; + private roundCalloutRound = 0; + private readonly tmpCamera = new THREE.Vector3(); + private readonly roundStats = new RoundStatsTracker(); + private readonly history: EngineSnapshot[] = []; + private lastKnockdown: { readonly knockdown: CombatEvent; readonly hit: CombatEvent | null } | null = null; + private replay: { readonly plan: ReplayPlan; readonly buffer: SnapshotBuffer; readonly startedAt: number; impactFired: boolean; side: 1 | -1 | null } | null = null; + private readonly finishPass: ShaderPass; + private readonly bloomPass: UnrealBloomPass; + private inputLatencyMs: number | null = null; + private frameMsAverage = 16.7; + private readonly replayCameraPosition = new THREE.Vector3(); + private readonly replayLookAt = new THREE.Vector3(); + private frameSeconds = 0; private readonly pendingContacts: Array<{ event: CombatEvent; presentationEvent: CombatEvent; presentImpact: boolean; + reactAmount: number | null; contactTick: number; recipientIndex: number; puncherIndex: number; @@ -230,22 +587,25 @@ export class FightRenderer { private readonly canvas: HTMLCanvasElement, private readonly simulation: SimulationInfo = DEFAULT_SIM, private readonly settings: () => Settings, - options: { manualClock?: boolean } = {}, + options: { manualClock?: boolean; localInput?: () => HeldInput | null; inputSequenceOf?: (actionId: string) => number | null } = {}, ) { this.manualClock = options.manualClock === true; + this.localInput = options.localInput ?? null; + this.inputSequenceOf = options.inputSequenceOf ?? null; + this.buffer = new SnapshotBuffer(8, simulation.tick_rate); this.mapping = worldMapping(simulation); this.renderer = new THREE.WebGLRenderer({ canvas, antialias: true, powerPreference: "high-performance", preserveDrawingBuffer: options.manualClock === true }); this.renderer.shadowMap.enabled = true; this.renderer.shadowMap.type = THREE.PCFShadowMap; this.renderer.toneMapping = THREE.ACESFilmicToneMapping; - this.renderer.toneMappingExposure = 0.92; - this.renderer.setPixelRatio(Math.min(2, window.devicePixelRatio || 1)); + this.renderer.toneMappingExposure = 1.0; + this.renderer.setPixelRatio(this.basePixelRatio); this.scene.background = new THREE.Color("#04060b"); this.scene.fog = new THREE.FogExp2("#04060b", 0.042); - this.camera = new THREE.PerspectiveCamera(38, 1, 0.1, 80); - this.camera.position.set(0, 2.05, 7.6); - this.camera.lookAt(0, 1.1, 0); + this.camera = new THREE.PerspectiveCamera(36, 1, 0.1, 80); + this.camera.position.set(0, 2.05, 5.9); + this.camera.lookAt(0, 1.05, 0); this.setupLights(); this.ring = buildRing(); @@ -254,22 +614,6 @@ export class FightRenderer { this.scene.add(this.arena.group); this.effects = new Effects3D(this.scene); - this.boxers = [buildBoxer(PALETTES[0]), buildBoxer(PALETTES[1])]; - this.animators = [new BoxerAnimator(this.boxers[0], this.mapping), new BoxerAnimator(this.boxers[1], this.mapping)]; - this.boxers[0].root.position.set(-0.9, 0, 0); - this.boxers[1].root.position.set(0.9, 0, 0); - this.boxers[0].root.rotation.y = Math.PI / 2; - this.boxers[1].root.rotation.y = -Math.PI / 2; - this.scene.add(this.boxers[0].root, this.boxers[1].root); - - this.referee = buildReferee(); - this.referee.root.position.copy(this.refereePosition); - this.referee.shoulderL.rotation.x = -0.42; - this.referee.shoulderR.rotation.x = -0.42; - this.referee.elbowL.rotation.x = -0.55; - this.referee.elbowR.rotation.x = -0.55; - this.scene.add(this.referee.root); - this.blobTexture = blobShadowTexture(); const blobGeometry = new THREE.PlaneGeometry(1, 1); for (let i = 0; i < 3; i += 1) { @@ -283,8 +627,11 @@ export class FightRenderer { this.composer = new EffectComposer(this.renderer); this.composer.addPass(new RenderPass(this.scene, this.camera)); - const bloom = new UnrealBloomPass(new THREE.Vector2(1280, 720), 0.32, 0.5, 0.85); + const bloom = new UnrealBloomPass(new THREE.Vector2(1280, 720), 0.2, 0.45, 1.08); + this.bloomPass = bloom; this.composer.addPass(bloom); + this.finishPass = new ShaderPass(BROADCAST_FINISH_SHADER); + this.composer.addPass(this.finishPass); this.composer.addPass(new OutputPass()); this.hudCanvas = document.createElement("canvas"); @@ -300,21 +647,45 @@ export class FightRenderer { private ensureGraphs(): void { if (this.glbLoading || this.graphs !== null) return; - if (new URLSearchParams(window.location.search).get("procedural") === "1") return; this.glbLoading = true; this.graphsReady = loadBoxerGlb() - .then((gltf) => { + .then(async (gltf) => { if (this.destroyed) return; const first = new SkinnedBoxer(gltf, { skin: 0xb0703f, gear: 0x1d4ed8 }); const second = new SkinnedBoxer(gltf, { skin: 0x6e4128, gear: 0xb91c1c }); this.graphs = [new BoxingGraph(first, this.mapping), new BoxingGraph(second, this.mapping)]; this.syncInjuryPresentation(0); this.syncInjuryPresentation(1); - this.scene.add(first.root, second.root); - for (const boxer of this.boxers) { - this.scene.remove(boxer.root); - disposeBoxer(boxer); + this.refereeShirt = refereeShirtTexture(); + const official = new SkinnedBoxer(gltf, { skin: 0xc79b76, gear: 0x3b57b8, pants: 0x14161c, bodyMap: this.refereeShirt }); + this.referee = new BoxingGraph(official, this.mapping, { referee: true }); + const blueShirt = cornerShirtTexture("#2b4c9e"); + const redShirt = cornerShirtTexture("#9e2b2b"); + this.cornerShirts.push(blueShirt, redShirt); + const blueCorner = new SkinnedBoxer(gltf, { skin: 0x8a5a3b, gear: 0x1b2230, pants: 0x14161c, bodyMap: blueShirt }); + const redCorner = new SkinnedBoxer(gltf, { skin: 0xd9a77c, gear: 0x1b2230, pants: 0x14161c, bodyMap: redShirt }); + this.cornermen = [new BoxingGraph(blueCorner, this.mapping, { referee: true }), new BoxingGraph(redCorner, this.mapping, { referee: true })]; + const whiteShirt = cornerShirtTexture("#e3e4e8"); + this.cornerShirts.push(whiteShirt); + const blueCutman = new SkinnedBoxer(gltf, { skin: 0xb98c66, gear: 0x1b2230, pants: 0x14161c, bodyMap: whiteShirt }); + const redCutman = new SkinnedBoxer(gltf, { skin: 0x5a3a26, gear: 0x1b2230, pants: 0x14161c, bodyMap: whiteShirt }); + this.cutmen = [new BoxingGraph(blueCutman, this.mapping, { referee: true }), new BoxingGraph(redCutman, this.mapping, { referee: true })]; + blueCutman.root.visible = false; + redCutman.root.visible = false; + this.trails = [0x1d4ed8, 0xb91c1c].flatMap((gear) => [0, 1].map(() => new GloveTrail(new THREE.Color(gear).lerp(new THREE.Color(0xffffff), 0.55)))); + // Compile the skinned materials, and the effects that start hidden (glove trails, blood on the + // canvas, severed parts), off the critical path (parallel shader compile where available) so + // neither the first frame with fighters nor the first bloody hit stalls the page. + const staging = new THREE.Group(); + staging.add(first.root, second.root, official.root, blueCorner.root, redCorner.root, blueCutman.root, redCutman.root, ...this.trails.map((trail) => trail.mesh), ...this.effects.compileStandIns()); + try { + await compileForComposer(this.renderer, this.composer, staging, this.camera, this.scene); + } catch { + // Fall back to compiling on the first draw. } + if (this.destroyed) return; + this.scene.add(first.root, second.root, official.root, blueCorner.root, redCorner.root, blueCutman.root, redCutman.root); + for (const trail of this.trails) this.scene.add(trail.mesh); }) .catch((error: unknown) => { this.glbLoading = false; @@ -329,7 +700,7 @@ export class FightRenderer { get labRigs(): THREE.Object3D[] { const graphs = this.graphs; if (graphs !== null) return [graphs[0].boxer.root, graphs[1].boxer.root]; - return this.boxers.map((boxer) => boxer.root); + return []; } get labScene(): THREE.Scene { @@ -348,13 +719,204 @@ export class FightRenderer { this.draw(virtualSeconds * 1000, true, render); } - setPlayers(players: Readonly>, viewerId: string | null): void { + setPlayers(players: Readonly>, viewerId: string | null, order: readonly string[] = Object.keys(players)): void { this.players = players; this.viewerId = viewerId; + this.playerOrder = order; + } + + /** Before the first snapshot the known fighters wait in guard instead of overlapping at the origin. */ + private updateIdleFighters(dt: number, time: number, sampledTick: number): void { + const graphs = this.graphs; + if (graphs === null) return; + const known = this.playerOrder.filter((id) => this.players[id] !== undefined); + const alone = known.length < 2; + for (const [index, graph] of graphs.entries()) { + const id = this.playerOrder[index] ?? `seat-${index}`; + const present = alone ? id === this.viewerId || (this.viewerId === null && index === 0) : true; + graph.boxer.root.visible = present; + if (!present) continue; + const sign = index === 0 ? -1 : 1; + const idleTick = Math.floor(time * this.simulation.tick_rate); + const self = { ...blankFighter(id), x: alone ? 0 : sign * 180, y: alone ? -70 : 0, facing: alone ? 1 : -sign, facing_x: alone ? 0 : -sign * 1000, facing_y: alone ? -1000 : 0, ...(alone ? shadowBoxing(idleTick) : {}) }; + const other = { ...blankFighter(this.playerOrder[1 - index] ?? "opponent"), x: alone ? 0 : -sign * 180, y: alone ? -150 : 0 }; + graph.setResting(false); + graph.update(self, other, dt, time, this.settings().reducedMotion, this.bloodLevel, alone ? idleTick : sampledTick); + } } + /** A stoppage's result panel waits for the slow-motion fall; decisions show at once. */ setFinal(final: FinalMessage | null): void { this.final = final; + this.finalRevealAt = this.frameSeconds + finalRevealDelay(final); + this.pendingFinish = null; + if (final === null || !STOPPAGE_METHODS.has(final.method)) return; + const plan = this.lastKnockdown === null ? null : planKnockoutReplay(this.history, this.lastKnockdown.knockdown, this.simulation.tick_rate); + if (plan !== null && this.graphs !== null && !this.settings().reducedMotion) { + this.startReplay(plan); + return; + } + // The result arrives while the screen is still a few ticks behind it, so the finish waits for the + // punch that ended the bout to be shown. + const resultTick = this.buffer.latest()?.result?.tick; + if (resultTick === undefined) this.presentFinish(final); + else this.pendingFinish = { final, tick: resultTick, latestAt: this.frameSeconds + FINISH_WAIT_LIMIT_SECONDS }; + } + + /** Presents a finish waiting for its punch once the presented tick reaches the result (or the wait runs out). */ + private presentFinishWhenShown(sampledTick: number): void { + const pending = this.pendingFinish; + if (pending === null || (sampledTick < pending.tick && this.frameSeconds < pending.latestAt)) return; + this.pendingFinish = null; + this.presentFinish(pending.final); + } + + private presentFinish(final: FinalMessage): void { + this.referee?.waveOff(); + const fighters = this.buffer.latest()?.fighters; + const loserIndex = fighters?.findIndex((fighter) => fighter.player_id !== final.winner_id && fighter.player_id !== null) ?? -1; + if (loserIndex >= 0 && this.headCacheValid[loserIndex] && !this.settings().reducedMotion) { + this.finishCloseUpIndex = loserIndex; + this.finishCloseUpUntil = this.frameSeconds + FINISH_CLOSE_UP_SECONDS; + } + if (final.winner_id === null) return; + const index = fighters?.findIndex((fighter) => fighter.player_id === final.winner_id) ?? -1; + if (index >= 0) this.graphs?.[index]?.celebrate(); + } + + /** Between rounds the broadcast cuts to each corner in turn, the viewer's own first, once its fighter is seated. */ + private cornerShotFrame(seconds: number, snapshot: EngineSnapshot | null, reducedMotion: boolean): { position: THREE.Vector3; lookAt: THREE.Vector3 } | null { + if (snapshot === null || snapshot.phase !== "rest" || reducedMotion || this.graphs === null) return null; + const viewer = snapshot.fighters.findIndex((fighter) => fighter.player_id === this.viewerId); + const elapsed = seconds - this.restStartedAt; + const index = cornerShot(elapsed, snapshot.phase_ticks_remaining / this.simulation.tick_rate, viewer === 1 ? 1 : 0); + if (index === null || !this.graphs[index].stoolVisible) return null; + cornerFrame(index, this.mapping.x(REST_CORNER_OFFSET), cornerShotProgress(elapsed), this.cornerPosition, this.cornerLookAt); + return { position: this.cornerPosition, lookAt: this.cornerLookAt }; + } + + /** A short high three-quarter close-up on the beaten fighter's face, or on the head where it came to rest, before the result panel. */ + private closeUpFrame(seconds: number): { position: THREE.Vector3; lookAt: THREE.Vector3; tight: boolean } | null { + if (seconds >= this.finishCloseUpUntil || this.finishCloseUpIndex < 0 || !this.headCacheValid[this.finishCloseUpIndex]) return null; + const severed = this.arcadeInjuries[this.finishCloseUpIndex] === "decapitation" && this.effects.severedHeadPosition(this.finishCloseUpIndex, this.closeUpTarget); + const head = severed ? this.closeUpTarget : this.headCache[this.finishCloseUpIndex]!; + const reach = severed ? 0.8 : 1.05; + const drift = (seconds - (this.finishCloseUpUntil - FINISH_CLOSE_UP_SECONDS)) * 0.25 - 0.2; + // Shoot from the ring-centre side of the fighter so the ropes stay behind the face. + const toCentre = Math.atan2(-head.x, -head.z); + const angle = (Math.hypot(head.x, head.z) > 0.4 ? toCentre : 0.9) + drift; + this.closeUpPosition.set( + THREE.MathUtils.clamp(head.x + Math.sin(angle) * reach, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT), + head.y + (severed ? 0.42 : 0.75), + THREE.MathUtils.clamp(head.z + Math.cos(angle) * reach, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT), + ); + this.replayLookAt.copy(head); + return { position: this.closeUpPosition, lookAt: this.replayLookAt, tight: true }; + } + + /** Replays the recorded snapshots around the knockdown from a close camera before the result panel. */ + private startReplay(plan: ReplayPlan): void { + const buffer = new SnapshotBuffer(plan.snapshots.length + 2, this.simulation.tick_rate); + for (const snapshot of plan.snapshots) buffer.push(snapshot); + this.replay = { plan, buffer, startedAt: this.frameSeconds, impactFired: false, side: null }; + this.replayFollow = 0; + this.replayFollowAt = 0; + for (const index of [0, 1] as const) { + const injury = this.arcadeInjuries[index]; + const event = this.arcadeInjuryEvents[index]; + if (injury !== null && event !== null && replayReattaches(injury)) { + this.replayInjuries[index] = { injury, event }; + this.restoreInjury(index); + } + } + for (const graph of this.graphs ?? []) graph.resetTransient(false); + this.finalRevealAt = this.frameSeconds + plan.durationSeconds + finalRevealDelay(this.final); + } + + private endReplay(): void { + this.replay = null; + this.reapplyReplayInjuries(); + const live = this.buffer.latest(); + for (const [index, graph] of (this.graphs ?? []).entries()) graph.resetTransient(live?.fighters[index]?.is_downed === true); + if (this.final !== null) this.presentFinish(this.final); + } + + private fireReplayImpact(snapshot: EngineSnapshot): void { + const record = this.lastKnockdown; + if (record === null) return; + const event = record.hit ?? { ...record.knockdown, kind: "hit", amount: 420, blood: 60 }; + const { recipientIndex, puncherIndex } = contactParticipants(event, snapshot); + const recipient = snapshot.fighters[recipientIndex]; + if (recipient === undefined) return; + this.tmpA.set(this.mapping.x(recipient.x), 0, this.mapping.z(recipient.y)); + const spray = sprayDirection(snapshot.fighters[puncherIndex], recipient, this.mapping); + this.effects.addEvent(event, this.tmpA, this.settings().reducedMotion, spray); + const puncher = puncherIndex >= 0 ? snapshot.fighters[puncherIndex] : undefined; + const keyParts = puncher?.action_key?.split(":") ?? []; + const punchClass = (keyParts[0] ?? null) as PunchClass | null; + const hand = (keyParts[1] ?? null) as Hand | null; + this.graphs?.[recipientIndex]?.react("hit", event.detail.endsWith(":body") ? "body" : "head", event.direction, punchClass, hand, event.amount); + if (puncherIndex >= 0) this.graphs?.[puncherIndex]?.landedHit(false); + this.onContact?.(event); + this.reapplyReplayInjuries(spray); + } + + private replayFrame(snapshot: EngineSnapshot, elapsed: number): { position: THREE.Vector3; lookAt: THREE.Vector3; tight: boolean } { + const [a, b] = snapshot.fighters; + const ax = this.mapping.x(a.x); + const az = this.mapping.z(a.y); + const bx = this.mapping.x(b.x); + const bz = this.mapping.z(b.y); + // A portrait screen is too narrow for both fighters up close, so it favours the one being hit; + // after the impact every screen follows that fighter down to the canvas. + const victim = snapshot.fighters.findIndex((fighter) => fighter.player_id === this.replay?.plan.impact.target_id); + const falling = this.replay?.impactFired === true && victim >= 0 && this.headCacheValid[victim] === true; + const follow = 1 - Math.exp(-3 * Math.max(0, elapsed - this.replayFollowAt)); + this.replayFollowAt = elapsed; + this.replayFollow += ((falling ? 1 : 0) - this.replayFollow) * follow; + const favour = victim < 0 ? 0 : Math.max(this.portraitPull > 1.3 ? 0.7 : 0, this.replayFollow * 0.8); + const midX = (ax + bx) / 2 + ((victim === 1 ? bx : ax) - (ax + bx) / 2) * favour; + const midZ = (az + bz) / 2 + ((victim === 1 ? bz : az) - (az + bz) / 2) * favour; + let nx = -(bz - az); + let nz = bx - ax; + const length = Math.hypot(nx, nz) || 1; + nx /= length; + nz /= length; + const distance = 2.5; + const replay = this.replay; + // The side is chosen once so the shot never cuts across the fighters mid-replay. + if (replay !== null && replay.side === null) replay.side = replayCameraSide(midX, midZ, nx, nz, distance, TIGHT_SHOT_LIMIT); + const side = replay?.side ?? (nz < 0 ? -1 : 1); + nx *= side; + nz *= side; + const orbit = 0.35 * Math.sin(elapsed * 0.7); + const dx = nx * Math.cos(orbit) - nz * Math.sin(orbit); + const dz = nx * Math.sin(orbit) + nz * Math.cos(orbit); + this.replayCameraPosition.set( + THREE.MathUtils.clamp(midX + dx * distance, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT), + 1.38 - Math.min(0.25, elapsed * 0.05), + THREE.MathUtils.clamp(midZ + dz * distance, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT), + ); + // In a corner both sides are short of room; back off toward the ring centre instead of crowding the fighters. + const room = Math.hypot(this.replayCameraPosition.x - midX, this.replayCameraPosition.z - midZ); + const centre = Math.hypot(midX, midZ); + if (room < REPLAY_MINIMUM_DISTANCE && centre > 0.01) { + const push = REPLAY_MINIMUM_DISTANCE - room; + this.replayCameraPosition.x = THREE.MathUtils.clamp(this.replayCameraPosition.x - (midX / centre) * push, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT); + this.replayCameraPosition.z = THREE.MathUtils.clamp(this.replayCameraPosition.z - (midZ / centre) * push, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT); + } + const headHeight = falling ? THREE.MathUtils.clamp(this.headCache[victim]!.y, 0.45, 1.28) : 1.28; + this.replayLookAt.set(midX, 1.28 + (headHeight - 1.28) * this.replayFollow, midZ); + return { position: this.replayCameraPosition, lookAt: this.replayLookAt, tight: true }; + } + + setInputLatency(milliseconds: number | null): void { + this.inputLatencyMs = milliseconds; + } + + /** The server clock starts over after a new connection or a paused bout, so the render clock relearns it. */ + resyncClock(): void { + this.buffer.resync(); } setReconnect(milliseconds: number): void { @@ -389,17 +951,79 @@ export class FightRenderer { ? injury : null; graph.setArcadeDislocation(dislocation); - return; } - const boxer = this.boxers[index]!; - boxer.head.visible = injury !== "decapitation"; - boxer.gloveLMesh.visible = injury !== "dismember_left"; - boxer.gloveRMesh.visible = injury !== "dismember_right"; + } + + /** + * Severs the head or a hand from the fighter's current pose, flying the way the punch travelled, or + * sets a dislocation, and records it. + */ + private applyArcadeInjury(index: number, injury: ArcadeInjury, event: CombatEvent, spray?: SprayDirection): boolean { + let applied = this.graphs !== null + && (injury === "jaw_dislocation" || injury === "shoulder_left" || injury === "shoulder_right"); + if (injury === "decapitation") { + const pose = this.headWorldPose(index); + if (pose !== null) { + const graph = this.graphs?.[index]; + const baked = graph === undefined ? undefined : bakeSkinnedPart(graph.boxer.headMesh, pose.position, pose.quaternion); + this.effects.decapitate( + index, + pose.position, + pose.quaternion, + spray ?? event.direction, + event.event_id, + this.skinColor(index), + baked, + ); + const stumpPose = this.stumpWorldPose(index); + if (stumpPose !== null) this.effects.anchorStump(index, stumpPose.position, stumpPose.quaternion); + applied = true; + } + } else if (injury === "dismember_left" || injury === "dismember_right") { + const side = injury === "dismember_left" ? "left" : "right"; + const pose = this.handWorldPose(index, side); + if (pose !== null) { + const graph = this.graphs?.[index]; + const baked = graph === undefined ? undefined : bakeSkinnedPart(graph.boxer.gloveMesh(side), pose.position, pose.quaternion); + this.effects.dismemberHand( + index, + side, + pose.position, + pose.quaternion, + spray ?? event.direction, + event.event_id, + this.gearColor(index), + baked, + ); + this.effects.anchorHandStump(index, side, pose.position, pose.quaternion); + applied = true; + } + } + if (!applied) return false; + this.arcadeInjuries[index] = injury; + this.arcadeInjuryEvents[index] = event; + this.observedInjuryDown[index] = false; + this.syncInjuryPresentation(index); + this.onArcadeInjury?.(injury, event); + return true; + } + + /** Severed parts go back on for the replay and come off again, from the replayed pose, at its impact. */ + private reapplyReplayInjuries(spray?: SprayDirection): void { + for (const index of [0, 1] as const) { + const stash = this.replayInjuries[index]; + if (stash === null) continue; + this.replayInjuries[index] = null; + const settings = this.settings(); + if (settings.blood !== "full" || settings.reducedMotion) continue; + this.applyArcadeInjury(index, stash.injury, { ...stash.event, event_id: stash.event.event_id + REPLAY_EVENT_ID_OFFSET }, spray); + } } private restoreInjury(index: number): void { if (this.arcadeInjuries[index] === null) return; this.arcadeInjuries[index] = null; + this.arcadeInjuryEvents[index] = null; this.observedInjuryDown[index] = false; this.syncInjuryPresentation(index); this.effects.restoreFighter(index); @@ -413,10 +1037,9 @@ export class FightRenderer { private headWorldPose(index: number): { position: THREE.Vector3; quaternion: THREE.Quaternion } | null { const graphs = this.graphs; - const head = graphs !== null ? graphs[index]!.boxer.bone("head") : this.boxers[index]!.head; - if (head === null) return null; - if (graphs !== null) graphs[index]!.boxer.root.updateMatrixWorld(true); - else this.boxers[index]!.root.updateMatrixWorld(true); + const head = graphs !== null ? graphs[index]!.boxer.bone("head") : null; + if (head === null || graphs === null) return null; + graphs[index]!.boxer.root.updateMatrixWorld(true); head.getWorldPosition(this.tmpHead); head.getWorldQuaternion(this.tmpHeadQuaternion); this.tmpStumpOffset.set(0, 0.12, 0.02).applyQuaternion(this.tmpHeadQuaternion); @@ -429,60 +1052,81 @@ export class FightRenderer { side: "left" | "right", ): { position: THREE.Vector3; quaternion: THREE.Quaternion } | null { const graphs = this.graphs; - const hand = graphs !== null - ? graphs[index]!.boxer.bone(side === "left" ? "gloveL" : "gloveR") - : side === "left" ? this.boxers[index]!.gloveL : this.boxers[index]!.gloveR; - if (hand === null) return null; - if (graphs !== null) graphs[index]!.boxer.root.updateMatrixWorld(true); - else this.boxers[index]!.root.updateMatrixWorld(true); + const hand = graphs !== null ? graphs[index]!.boxer.bone(side === "left" ? "gloveL" : "gloveR") : null; + if (hand === null || graphs === null) return null; + graphs[index]!.boxer.root.updateMatrixWorld(true); hand.getWorldPosition(this.tmpPart); hand.getWorldQuaternion(this.tmpPartQuaternion); return { position: this.tmpPart, quaternion: this.tmpPartQuaternion }; } private gearColor(index: number): number { - const graphs = this.graphs; - return graphs !== null - ? graphs[index]!.boxer.gearBaseColor.getHex() - : this.boxers[index]!.gloveBaseColor.getHex(); + return this.graphs?.[index]?.boxer.gearBaseColor.getHex() ?? 0x1d4ed8; } private skinColor(index: number): number { - const graphs = this.graphs; - return graphs !== null - ? graphs[index]!.boxer.skinBaseColor.getHex() - : this.boxers[index]!.skinMaterial.color.getHex(); + return this.graphs?.[index]?.boxer.skinBaseColor.getHex() ?? 0xb0703f; } private stumpWorldPose(index: number): { position: THREE.Vector3; quaternion: THREE.Quaternion } | null { const graphs = this.graphs; - const anchor = graphs !== null ? graphs[index]!.boxer.bone("Neck_012") : this.boxers[index]!.head; - if (anchor === null) return null; - if (graphs !== null) graphs[index]!.boxer.root.updateMatrixWorld(true); - else this.boxers[index]!.root.updateMatrixWorld(true); + const anchor = graphs !== null ? graphs[index]!.boxer.bone("Neck_012") : null; + if (anchor === null || graphs === null) return null; + graphs[index]!.boxer.root.updateMatrixWorld(true); anchor.getWorldPosition(this.tmpStump); anchor.getWorldQuaternion(this.tmpStumpQuaternion); - if (graphs === null) { - this.tmpStumpOffset.set(0, -0.085, 0).applyQuaternion(this.tmpStumpQuaternion); - this.tmpStump.add(this.tmpStumpOffset); - } return { position: this.tmpStump, quaternion: this.tmpStumpQuaternion }; } predictAction(action: SemanticAction): void { const latest = this.buffer.latest(); - if (latest === null || this.viewerId === null) return; + if (latest === null || this.viewerId === null || this.replay !== null) return; const index = latest.fighters.findIndex((fighter) => fighter.player_id === this.viewerId); if (index < 0) return; - const graphs = this.graphs; - if (graphs !== null) graphs[index]!.predict(action, performance.now() / 1000, this.simulation.tick_rate); - else this.animators[index]!.predict(action, performance.now() / 1000, this.simulation.tick_rate); + // The server turns a punch or an evasion down outside the fight phase and while the fighter cannot act or pay for it. + const fighter = latest.fighters[index]!; + if (latest.phase !== "fight" || !canStartPunch(fighter)) return; + const leadTicks = ((this.inputLatencyMs ?? 60) / 1000) * this.simulation.tick_rate + this.buffer.interpolationDelayTicks; + if (isEvasion(action.kind)) { + // Behind a punch the server holds it, so it is shown at once only when the fighter is free. + const busy = this.graphs?.[index]?.ownPunchActive === true || attackTicksRemaining(fighter, latest.tick) > 0 || fighter.queued_actions > 0; + if (!busy && action.id !== undefined && fighter.stamina >= EVASION_STAMINA) { + this.evasion.press(action.kind, action.id, this.manualClock ? this.lastManualTime : performance.now(), leadTicks, this.simulation.tick_rate); + } + return; + } + if (action.kind !== "punch" || !canAffordPunch(fighter, action)) return; + this.graphs?.[index]?.predict(action, performance.now() / 1000, this.simulation.tick_rate, leadTicks, predictedPunchTiming(fighter, action, latest.tick + 1)); + } + + /** + * Every snapshot, as it arrives, tells the viewer's own punches whether the server took them (matching + * each press to the input frame that carried it), and both fighters' punches how they met the opponent. + */ + private acknowledgeActions(snapshot: EngineSnapshot, events: readonly CombatEvent[]): void { + for (const [index, fighter] of snapshot.fighters.entries()) { + const viewer = fighter.player_id === this.viewerId; + if (viewer) this.evasion.acknowledge(fighter, snapshot.phase === "fight", this.inputSequenceOf); + const contacts = events.filter((event) => contactParticipants(event, snapshot).puncherIndex === index); + this.graphs?.[index]?.acknowledge(fighter, snapshot.phase === "fight", contacts, viewer ? this.inputSequenceOf : null); + } } push(snapshot: EngineSnapshot): void { - if (!this.buffer.push(snapshot)) return; + if (!this.buffer.push(snapshot, this.manualClock ? this.lastManualTime : performance.now())) return; const accepted = this.dedupe.accept(snapshot.events); - for (const { event, presentationEvent, presentImpact } of contactPresentationPlan(accepted, snapshot)) { + this.acknowledgeActions(snapshot, accepted); + this.history.push(snapshot); + if (this.history.length > HISTORY_LIMIT) this.history.shift(); + for (const event of accepted) { + this.roundStats.record(event); + if (event.kind === "knockdown") { + const hit = accepted.find((candidate) => (candidate.kind === "hit" || candidate.kind === "counter_hit") && candidate.target_id === event.target_id) ?? null; + this.lastKnockdown = { knockdown: event, hit }; + } + if (event.kind === "referee_break") this.referee?.breakClinch(); + } + for (const { event, presentationEvent, presentImpact, reactAmount } of contactPresentationPlan(accepted, snapshot)) { const targetIndex = snapshot.fighters.findIndex((fighter) => fighter.player_id === event.target_id); const actorIndex = snapshot.fighters.findIndex((fighter) => fighter.player_id === event.actor_id); const { recipientIndex, puncherIndex } = contactParticipants(event, snapshot); @@ -497,6 +1141,7 @@ export class FightRenderer { event, presentationEvent, presentImpact, + reactAmount, contactTick: puncher?.action_contact_tick ?? event.tick, recipientIndex, puncherIndex, @@ -516,13 +1161,24 @@ export class FightRenderer { continue; } this.pendingContacts.splice(index, 1); - const { event, presentationEvent, presentImpact, recipientIndex, puncherIndex, injury } = pending; + const { event, presentationEvent, presentImpact, reactAmount, recipientIndex, puncherIndex, injury } = pending; const target = this.buffer.latest()?.fighters[recipientIndex]; + const spray = sprayDirection(this.buffer.latest()?.fighters[puncherIndex], target, this.mapping); if (presentImpact && target !== undefined) { this.tmpA.set(this.mapping.x(target.x), 0, this.mapping.z(target.y)); - this.effects.addEvent(presentationEvent, this.tmpA, this.settings().reducedMotion); + this.effects.addEvent(presentationEvent, this.tmpA, this.settings().reducedMotion, spray); } const currentSettings = this.settings(); + if (presentImpact) this.arena.excite(CROWD_EXCITEMENT[event.kind] ?? 0); + if ( + presentImpact + && recipientIndex >= 0 + && this.viewerId !== null + && this.buffer.latest()?.fighters[recipientIndex]?.player_id === this.viewerId + && ["hit", "counter_hit", "knockdown"].includes(event.kind) + ) { + this.viewerHitFlash = Math.max(this.viewerHitFlash, Math.min(1, 0.35 + event.amount / 400)); + } if ( injury !== null && recipientIndex >= 0 @@ -530,64 +1186,38 @@ export class FightRenderer { && currentSettings.blood === "full" && !currentSettings.reducedMotion ) { - let applied = this.graphs !== null - && (injury === "jaw_dislocation" || injury === "shoulder_left" || injury === "shoulder_right"); - if (injury === "decapitation") { - const pose = this.headWorldPose(recipientIndex); - if (pose !== null) { - this.effects.decapitate( - recipientIndex, - pose.position, - pose.quaternion, - event.direction, - event.event_id, - this.skinColor(recipientIndex), - ); - const stumpPose = this.stumpWorldPose(recipientIndex); - if (stumpPose !== null) this.effects.anchorStump(recipientIndex, stumpPose.position, stumpPose.quaternion); - applied = true; - } - } else if (injury === "dismember_left" || injury === "dismember_right") { - const side = injury === "dismember_left" ? "left" : "right"; - const pose = this.handWorldPose(recipientIndex, side); - if (pose !== null) { - this.effects.dismemberHand( - recipientIndex, - side, - pose.position, - pose.quaternion, - event.direction, - event.event_id, - this.gearColor(recipientIndex), - ); - this.effects.anchorHandStump(recipientIndex, side, pose.position, pose.quaternion); - applied = true; - } - } - if (applied) { - this.arcadeInjuries[recipientIndex] = injury; - this.observedInjuryDown[recipientIndex] = false; - this.syncInjuryPresentation(recipientIndex); - this.onArcadeInjury?.(injury, event); - } + this.applyArcadeInjury(recipientIndex, injury, event, spray); } const graphs = this.graphs; if ( presentImpact && recipientIndex >= 0 + && ["hit", "counter_hit", "knockdown"].includes(event.kind) + && presentationEvent.detail.endsWith(":head") + && event.amount >= 260 + && !currentSettings.reducedMotion + && currentSettings.blood !== "off" + ) { + const pose = this.headWorldPose(recipientIndex); + if (pose !== null) { + this.tmpB.set(0, -0.07, 0.1).applyQuaternion(pose.quaternion).add(pose.position); + this.effects.spawnTeeth(this.tmpB, spray ?? presentationEvent.direction, event.kind === "knockdown" ? 3 : 1 + Math.floor((event.amount - 260) / 120), event.event_id); + } + } + if ( + presentImpact + && recipientIndex >= 0 + && reactAmount !== null && ["hit", "counter_hit", "block", "perfect_block", "knockdown"].includes(event.kind) ) { const blocked = event.kind === "block" || event.kind === "perfect_block"; const targetKind = presentationEvent.detail.endsWith(":body") ? "body" : "head"; if (graphs !== null) { - graphs[recipientIndex]!.react(blocked ? "block" : "hit", targetKind, presentationEvent.direction); - } else { - this.animators[recipientIndex]!.impact({ - direction: presentationEvent.direction, - amount: blocked ? event.amount * 0.35 : event.amount, - blocked, - target: targetKind, - }); + const puncher = puncherIndex >= 0 ? this.buffer.latest()?.fighters[puncherIndex] : undefined; + const keyParts = puncher?.action_key?.split(":") ?? []; + const punchClass = (keyParts[0] ?? presentationEvent.detail.split(":")[0] ?? null) as PunchClass | null; + const punchHand = (keyParts[1] ?? null) as Hand | null; + graphs[recipientIndex]!.react(blocked ? "block" : "hit", targetKind, presentationEvent.direction, punchClass, punchHand, reactAmount); } } if ( @@ -595,55 +1225,81 @@ export class FightRenderer { && puncherIndex >= 0 && ["hit", "counter_hit", "block", "perfect_block", "guard_break"].includes(event.kind) ) { - if (graphs !== null) graphs[puncherIndex]!.landedHit(event.kind === "block" || event.kind === "perfect_block"); - else this.animators[puncherIndex]!.landedHit(event.kind === "block" || event.kind === "perfect_block"); + graphs?.[puncherIndex]?.landedHit(event.kind === "block" || event.kind === "perfect_block"); } this.onContact?.(event); } } + /** True once the result panel is on screen, after any knockout replay and close-up. */ + get resultVisible(): boolean { + return this.final !== null && this.frameSeconds >= this.finalRevealAt; + } + + get resolutionScale(): number { + return this.scaler.scale; + } + + /** Snapshot for the diagnostics panel: smoothed frame time, render scale, GPU objects and the graphics adapter. */ + get diagnostics(): { frameMs: number; resolutionScale: number; gpu: { geometries: number; textures: number; programs: number }; graphics: string } { + const gl = this.renderer.getContext(); + const info = gl.getExtension("WEBGL_debug_renderer_info"); + const graphics = info === null ? gl.getParameter(gl.RENDERER) : gl.getParameter(info.UNMASKED_RENDERER_WEBGL); + return { frameMs: this.frameMsAverage, resolutionScale: this.scaler.scale, gpu: this.memoryInfo, graphics: String(graphics) }; + } + + /** Live GPU object counts from three, for leak checks across rematches. */ + get memoryInfo(): { geometries: number; textures: number; programs: number } { + return { geometries: this.renderer.info.memory.geometries, textures: this.renderer.info.memory.textures, programs: this.renderer.info.programs?.length ?? 0 }; + } + + private applyResolutionScale(): void { + const ratio = this.basePixelRatio * this.scaler.scale; + this.renderer.setPixelRatio(ratio); + this.composer.setPixelRatio(ratio); + // At the bottom of the scale the client is struggling: drop bloom and the key shadow entirely. + const low = this.scaler.scale <= LOW_TIER_SCALE; + this.bloomPass.enabled = !low; + if (this.keyLight !== null) setKeyShadowTier(this.keyLight.shadow, low, this.scaler.scale < 0.8 ? 1024 : 2048); + } + private setupLights(): void { - const hemisphere = new THREE.HemisphereLight("#5a6a95", "#0c0e16", 1.2); + const hemisphere = new THREE.HemisphereLight("#3c4a72", "#07080c", 0.55); this.scene.add(hemisphere); this.lights.push(hemisphere); - const ambient = new THREE.AmbientLight("#3a4468", 1.05); - this.scene.add(ambient); - this.lights.push(ambient); - - const key = new THREE.SpotLight("#fff4e0", 115, 26, 0.68, 0.6, 1.6); - key.position.set(0, 7.4, 0.9); - key.target.position.set(0, 0, 0); + const key = new THREE.SpotLight("#fff1dc", 150, 24, 0.56, 0.55, 1.7); + key.position.set(0.6, 7.4, 1.2); + key.target.position.set(0, 0.6, 0); key.castShadow = true; key.shadow.mapSize.set(2048, 2048); - key.shadow.bias = -0.0004; + key.shadow.bias = KEY_SHADOW_BIAS; key.shadow.camera.near = 3; key.shadow.camera.far = 14; this.keyLight = key; this.scene.add(key, key.target); this.lights.push(key); - const fills: Array<[string, number, number, number]> = [ - ["#b9cdff", -6.5, 4.4, -5.2], - ["#ffd9b9", 6.2, 4.1, -5.6], - ["#9fb8ff", -5.4, 3.6, 6.0], - ["#c9d8ff", 5.8, 3.9, 5.7], + const secondary = new THREE.SpotLight("#ffe6c8", 95, 24, 0.6, 0.6, 1.7); + secondary.position.set(-2.6, 7.0, -2.2); + secondary.target.position.set(0, 0.8, 0); + this.scene.add(secondary, secondary.target); + this.lights.push(secondary); + + const rims: Array<[string, number, number, number]> = [ + ["#8fa8ff", -5.5, 3.8, -5.4], + ["#7f95e8", 5.6, 3.6, -5.6], ]; - for (const [color, x, y, z] of fills) { - const fill = new THREE.SpotLight(color, 105, 30, 0.7, 0.8, 1.8); - fill.position.set(x, y, z); - fill.target.position.set(0, 1, 0); - this.scene.add(fill, fill.target); - this.lights.push(fill); + for (const [color, x, y, z] of rims) { + const rim = new THREE.SpotLight(color, 34, 30, 0.72, 0.9, 1.8); + rim.position.set(x, y, z); + rim.target.position.set(0, 1.2, 0); + this.scene.add(rim, rim.target); + this.lights.push(rim); } - const rim = new THREE.DirectionalLight("#dfe9ff", 0.7); - rim.position.set(0, 3.4, -6.5); - this.scene.add(rim); - this.lights.push(rim); - - const follow = new THREE.SpotLight("#ffe8d0", 55, 22, 0.34, 0.75, 1.5); - follow.position.set(0, 5.6, 5.2); + const follow = new THREE.SpotLight("#ffe8d0", 48, 22, 0.32, 0.8, 1.5); + follow.position.set(0, 5.8, 5.4); follow.target.position.set(0, 1, 0); this.scene.add(follow, follow.target); this.lights.push(follow); @@ -652,8 +1308,17 @@ export class FightRenderer { private draw(time: number, manual = false, render = true): void { if (this.destroyed) return; - const dt = manual ? 1 / 60 : Math.min(0.05, Math.max(0.001, (time - this.previous) / 1000)); + const frameMs = time - this.previous; + let dt = manual ? 1 / 60 : Math.min(0.05, Math.max(0.001, frameMs / 1000)); this.previous = time; + if (!manual && this.scaler.record(frameMs)) this.applyResolutionScale(); + if (!manual && frameMs > 0 && frameMs < 1000) this.frameMsAverage += (frameMs - this.frameMsAverage) * 0.05; + // Zooming or moving the window to another monitor changes the pixel ratio, often without a resize. + const pixelRatio = Math.min(this.pixelRatioCap, window.devicePixelRatio || 1); + if (pixelRatio !== this.basePixelRatio) { + this.basePixelRatio = pixelRatio; + this.applyResolutionScale(); + } const width = this.canvas.clientWidth; const height = this.canvas.clientHeight; @@ -663,23 +1328,58 @@ export class FightRenderer { this.renderer.setSize(width, height, false); this.composer.setSize(width, height); this.camera.aspect = width / height; + // Narrow viewports widen the lens a little and pull the camera back (see the frame step below). + this.portraitPull = THREE.MathUtils.clamp(1.2 / this.camera.aspect, 1, 2.2); + this.camera.fov = 36 * Math.min(1.3, Math.sqrt(this.portraitPull)); this.camera.updateProjectionMatrix(); } } const seconds = time / 1000; + this.frameSeconds = seconds; + this.finishPass.uniforms.uTime!.value = seconds % 1000; + if (manual) this.lastManualTime = time; const current = this.settings(); this.setBloodLevel(current.blood); const latest = this.buffer.latest(); - const sampledTick = latest === null ? 0 : presentationTickFor(latest); - const snapshot = latest === null ? null : this.buffer.sample(sampledTick); + const finishing = latest?.result !== null && latest?.result !== undefined + && STOPPAGE_METHODS.has(latest.result.finish_method); + if (finishing && !this.finishSeen) { + this.finishSeen = true; + this.finishSlowMotion = 2.2; + this.arena.excite(1); + } + if (this.finishSlowMotion > 0 && !current.reducedMotion) { + this.finishSlowMotion = Math.max(0, this.finishSlowMotion - dt); + const eased = Math.min(1, this.finishSlowMotion / 0.5); + dt *= 0.3 + 0.7 * (1 - eased); + } + this.viewerHitFlash = Math.max(0, this.viewerHitFlash - dt * 3.2); + let sampledTick = latest === null ? 0 : manual ? presentationTickFor(latest) : this.buffer.renderTick(time); + let snapshot = latest === null ? null : this.applyLocalPrediction(this.buffer.sample(sampledTick), dt, time); + const replay = this.replay; + if (replay !== null) { + const elapsed = seconds - replay.startedAt; + if (elapsed >= replay.plan.durationSeconds) { + this.endReplay(); + } else { + sampledTick = replayTick(replay.plan, elapsed, this.simulation.tick_rate); + snapshot = replay.buffer.sample(sampledTick) ?? snapshot; + if (!replay.impactFired && sampledTick >= replay.plan.impact.tick && snapshot !== null) { + replay.impactFired = true; + this.fireReplayImpact(snapshot); + } + } + } + // Everyone in the ring moves in slow motion with the replayed snapshots. + const actorDt = this.replay !== null ? dt * this.replay.plan.speed : dt; let separation = 1.8; let knockdown = false; if (snapshot !== null) { const [a, b] = snapshot.fighters; for (const [index, fighter] of snapshot.fighters.entries()) { - if (this.arcadeInjuries[index] === null) continue; + if (this.arcadeInjuries[index] === null || this.replay !== null) continue; if (fighter.is_downed) this.observedInjuryDown[index] = true; else if (this.observedInjuryDown[index] && snapshot.result === null) this.restoreInjury(index); } @@ -687,8 +1387,21 @@ export class FightRenderer { if (graphs !== null) { const headA = this.headCacheValid[0] ? this.headCache[0] : undefined; const headB = this.headCacheValid[1] ? this.headCache[1] : undefined; - graphs[0].update(a, b, dt, seconds, current.reducedMotion, current.blood, sampledTick, headB); - graphs[1].update(b, a, dt, seconds, current.reducedMotion, current.blood, sampledTick, headA); + graphs[0].boxer.root.visible = true; + graphs[1].boxer.root.visible = true; + graphs[0].setResting(snapshot.phase === "rest"); + graphs[1].setResting(snapshot.phase === "rest"); + const countdown = snapshot.phase === "countdown" ? snapshot.phase_ticks_remaining : null; + graphs[0].setCountdown(countdown); + graphs[1].setCountdown(countdown); + if (snapshot.phase === "fight" && this.lastPhase === "rest" && this.replay === null) { + this.roundCalloutUntil = seconds + ROUND_CALLOUT_SECONDS; + this.roundCalloutRound = snapshot.round_number; + } + if (snapshot.phase === "rest" && this.lastPhase !== "rest") this.restStartedAt = seconds; + this.lastPhase = snapshot.phase; + graphs[0].update(a, b, actorDt, seconds, current.reducedMotion, current.blood, sampledTick, headB); + graphs[1].update(b, a, actorDt, seconds, current.reducedMotion, current.blood, sampledTick, headA); for (const [index, graph] of graphs.entries()) { const headBone = graph.boxer.bone("head"); if (headBone !== null) { @@ -697,9 +1410,6 @@ export class FightRenderer { this.headCacheValid[index] = true; } } - } else { - this.animators[0].update(a, b, dt, seconds, current.reducedMotion, current.blood, sampledTick); - this.animators[1].update(b, a, dt, seconds, current.reducedMotion, current.blood, sampledTick); } for (let index = 0; index < this.arcadeInjuries.length; index += 1) { const injury = this.arcadeInjuries[index]; @@ -718,6 +1428,7 @@ export class FightRenderer { const bz = this.mapping.z(b.y); separation = Math.hypot(ax - bx, az - bz); knockdown = a.is_downed || b.is_downed; + this.ring.setRopeContacts({ x: ax, z: az }, { x: bx, z: bz }); this.tmpA.set(ax, 0, az); this.tmpB.set(bx, 0, bz); for (const [index, fighter] of snapshot.fighters.entries()) { @@ -747,17 +1458,22 @@ export class FightRenderer { } else { this.tmpA.set(-0.9, 0, 0); this.tmpB.set(0.9, 0, 0); + this.updateIdleFighters(dt, seconds, sampledTick); } this.arena.update(seconds, dt, current.reducedMotion); - this.effects.update(dt); - this.updateReferee(dt, seconds, current.reducedMotion); + this.effects.update(actorDt); + this.updateTrails(actorDt, current.reducedMotion); + this.updateReferee(actorDt, seconds, snapshot, sampledTick); + this.updateCornermen(actorDt, seconds, snapshot, sampledTick); + this.updateCutmen(actorDt, seconds, snapshot, sampledTick); this.updateBlobShadows(); this.fireContacts(sampledTick); + this.presentFinishWhenShown(sampledTick); if (this.followSpot !== null) { this.followSpot.target.position.set((this.tmpA.x + this.tmpB.x) / 2, 1.0, (this.tmpA.z + this.tmpB.z) / 2); } - const frame = this.cameraOverride ?? this.director.update( + const directed = this.director.update( dt, seconds, { x: this.tmpA.x, z: this.tmpA.z }, @@ -767,8 +1483,23 @@ export class FightRenderer { this.effects.shakeAmount, current.reducedMotion, ); - this.camera.position.copy(frame.position); - this.camera.lookAt(frame.lookAt); + const replaying = this.replay; + const frame: { position: THREE.Vector3; lookAt: THREE.Vector3; tight?: boolean } = this.cameraOverride ?? (replaying !== null && snapshot !== null ? this.replayFrame(snapshot, seconds - replaying.startedAt) : (this.closeUpFrame(seconds) ?? this.cornerShotFrame(seconds, snapshot, current.reducedMotion) ?? directed)); + if (this.cameraOverride === null && this.portraitPull > 1) { + const tight = frame.tight === true; + const pull = this.portraitPull / Math.min(1.3, Math.sqrt(this.portraitPull)); + const distanceScale = tight ? Math.min(pull, 1.25) : pull; + this.tmpCamera.subVectors(frame.position, frame.lookAt).multiplyScalar(distanceScale); + this.camera.position.copy(frame.lookAt).add(this.tmpCamera); + if (tight) { + this.camera.position.x = THREE.MathUtils.clamp(this.camera.position.x, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT); + this.camera.position.z = THREE.MathUtils.clamp(this.camera.position.z, -TIGHT_SHOT_LIMIT, TIGHT_SHOT_LIMIT); + } + this.camera.lookAt(frame.lookAt.x, frame.lookAt.y - (this.portraitPull - 1) * (tight ? 0.08 : 0.45), frame.lookAt.z); + } else { + this.camera.position.copy(frame.position); + this.camera.lookAt(frame.lookAt); + } if (render) { this.composer.render(); @@ -778,16 +1509,40 @@ export class FightRenderer { if (!this.destroyed && !this.manualClock) this.raf = requestAnimationFrame((next) => this.draw(next)); } + private applyLocalPrediction(snapshot: EngineSnapshot | null, dt: number, timeMs: number): EngineSnapshot | null { + if (snapshot === null || this.localInput === null || this.viewerId === null) return snapshot; + const index = snapshot.fighters.findIndex((fighter) => fighter.player_id === this.viewerId); + const held = this.localInput() ?? { moveX: 0, moveY: 0, defense: "none" }; + // Shown as far ahead of the snapshot on screen as an input pressed now takes to show up in it: the + // round trip plus the interpolation delay. The player's own punch starts here before the server + // has it, and holds the feet from then on. + const leadTicks = ((this.inputLatencyMs ?? 60) / 1000) * this.simulation.tick_rate + this.buffer.interpolationDelayTicks; + const fighting = index >= 0 && snapshot.phase === "fight" ? snapshot.fighters[index]! : null; + const holdFeet = this.graphs?.[index]?.ownPunchActive === true || this.evasion.holdsFeet(timeMs, this.simulation.tick_rate); + const local = this.movement.update(fighting, held, holdFeet, timeMs, leadTicks, snapshot.tick, dt, this.simulation.tick_rate); + // The guard is the most latency-sensitive thing the player controls: it is shown as held, and a + // slip, weave or pull on the press, wherever the server is not overriding it. + const evading = this.evasion.pose(timeMs); + if (index < 0) return snapshot; + const viewer = snapshot.fighters[index]!; + const defense = fighting !== null ? predictedDefense(fighting, held, evading) : viewer.defense; + if (Math.abs(local.dx) < 0.01 && Math.abs(local.dy) < 0.01 && defense === viewer.defense) return snapshot; + const offset = constrainPrediction(viewer, local, snapshot.fighters[index === 0 ? 1 : 0] ?? null); + const predicted = { ...viewer, x: viewer.x + offset.dx, y: viewer.y + offset.dy, defense }; + const fighters: [FighterSnapshot, FighterSnapshot] = index === 0 ? [predicted, snapshot.fighters[1]] : [snapshot.fighters[0], predicted]; + return { ...snapshot, fighters }; + } + private headHeightOf(index: number): number { - const graphs = this.graphs; - if (graphs !== null) return graphs[index]!.boxer.metrics.headRestY + 0.04; - return 1.56; + return (this.graphs?.[index]?.boxer.metrics.headRestY ?? 1.52) + 0.04; } private updateBlobShadows(): void { const anchors = [this.tmpA, this.tmpB, this.refereePosition]; for (const [index, blob] of this.blobShadows.entries()) { - const anchor = anchors[index]!; + // A fighter's blob sits under the rendered fighter, who walks in from his mark for the glove touch. + const graph = index < 2 ? this.graphs?.[index] : undefined; + const anchor = graph?.boxer.root.visible === true ? graph.currentRoot : anchors[index]!; blob.position.x = anchor.x; blob.position.z = anchor.z; const downed = index < 2 && this.buffer.latest()?.fighters[index]?.is_downed === true; @@ -795,32 +1550,135 @@ export class FightRenderer { } } - private updateReferee(dt: number, time: number, reducedMotion: boolean): void { - const midX = (this.tmpA.x + this.tmpB.x) / 2; - const midZ = (this.tmpA.z + this.tmpB.z) / 2; - const away = this.refereeAway.set(this.refereePosition.x - midX, 0, this.refereePosition.z - midZ); + private updateReferee(dt: number, time: number, snapshot: EngineSnapshot | null, sampledTick: number): void { + const referee = this.referee; + if (referee === null) return; + const downed = snapshot?.fighters.find((fighter) => fighter.is_downed) ?? null; + const clinched = snapshot?.fighters.some((fighter) => fighter.clinch_ticks > 0 || fighter.clinch_startup_ticks > 0) ?? false; + const breaking = downed === null && referee.breaking; + const focusX = downed !== null ? this.mapping.x(downed.x) : (this.tmpA.x + this.tmpB.x) / 2; + const focusZ = downed !== null ? this.mapping.z(downed.y) : (this.tmpA.z + this.tmpB.z) / 2; + const away = this.refereeAway.set(this.refereePosition.x - focusX, 0, this.refereePosition.z - focusZ); if (away.lengthSq() < 0.01) away.set(0, 0, -1); away.normalize(); - const targetX = THREE.MathUtils.clamp(midX + away.x * 2.05, -2.4, 2.4); - const targetZ = THREE.MathUtils.clamp(midZ + away.z * 2.05, -2.4, 2.4); - const rate = 1 - Math.exp(-1.6 * dt); - this.refereePosition.x += (targetX - this.refereePosition.x) * rate; - this.refereePosition.z += (targetZ - this.refereePosition.z) * rate; + if (breaking) { + // He steps in square to the line between the two, on his side of it, so a hand reaches each chest. + const acrossX = this.tmpB.z - this.tmpA.z; + const acrossZ = this.tmpA.x - this.tmpB.x; + const across = Math.hypot(acrossX, acrossZ); + const side = acrossX * away.x + acrossZ * away.z >= 0 ? 1 : -1; + if (across > 0.01) away.set((acrossX / across) * side, 0, (acrossZ / across) * side); + } + const { standoff, clearance } = refereeSpacing(downed !== null, clinched, breaking); + const targetX = THREE.MathUtils.clamp(focusX + away.x * standoff, -2.4, 2.4); + const targetZ = THREE.MathUtils.clamp(focusZ + away.z * standoff, -2.4, 2.4); + const previousX = this.refereePosition.x; + const previousZ = this.refereePosition.z; + // A break is a brisk step in, never faster than REFEREE_BREAK_SPEED; otherwise he drifts into place. + const rate = 1 - Math.exp(-(breaking ? 8 : 1.6) * dt); + const pace = breaking ? Math.min(1, (REFEREE_BREAK_SPEED * dt) / Math.max(1e-6, Math.hypot(targetX - this.refereePosition.x, targetZ - this.refereePosition.z) * rate)) : 1; + this.refereePosition.x += (targetX - this.refereePosition.x) * rate * pace; + this.refereePosition.z += (targetZ - this.refereePosition.z) * rate * pace; for (const fighter of [this.tmpA, this.tmpB]) { const dx = this.refereePosition.x - fighter.x; const dz = this.refereePosition.z - fighter.z; const distance = Math.hypot(dx, dz); - if (distance < 1.45 && distance > 0.001) { - this.refereePosition.x = fighter.x + (dx / distance) * 1.45; - this.refereePosition.z = fighter.z + (dz / distance) * 1.45; + if (distance < clearance && distance > 0.001) { + this.refereePosition.x = fighter.x + (dx / distance) * clearance; + this.refereePosition.z = fighter.z + (dz / distance) * clearance; + } + } + if (dt > 0) { + this.refereeVelocity.set((this.refereePosition.x - previousX) / dt, 0, (this.refereePosition.z - previousZ) / dt); + } + const yaw = Math.atan2(focusX - this.refereePosition.x, focusZ - this.refereePosition.z); + const yawDelta = ((yaw - this.refereeYaw + Math.PI) % (Math.PI * 2) + Math.PI * 2) % (Math.PI * 2) - Math.PI; + this.refereeYaw += yawDelta * (1 - Math.exp(-(breaking ? 8 : 3) * dt)); + const state = refereeSnapshot(this.refereePosition, this.refereeYaw, this.refereeVelocity, this.mapping); + referee.setRefereeCount(downed !== null, downed?.get_up_count ?? 0); + referee.aimBreak(this.tmpA, this.tmpB); + referee.update(state.self, state.focus, dt, time, false, "off", sampledTick); + } + + private updateTrails(dt: number, reducedMotion: boolean): void { + const graphs = this.graphs; + if (graphs === null || this.trails.length < 4) return; + for (const [index, graph] of graphs.entries()) { + for (const [gloveIndex, bone] of (["gloveL", "gloveR"] as const).entries()) { + const trail = this.trails[index * 2 + gloveIndex]!; + if (!graph.boxer.root.visible) { + trail.reset(); + continue; + } + graph.boxer.rig.bones[bone].getWorldPosition(this.trailGlove); + trail.update(this.trailGlove, dt, this.camera.position, !reducedMotion && this.replay === null); } } - this.referee.root.position.set(this.refereePosition.x, 0, this.refereePosition.z); - const yaw = Math.atan2(midX - this.refereePosition.x, midZ - this.refereePosition.z); - let yawDelta = ((yaw - this.refereeYaw + Math.PI) % (Math.PI * 2) + Math.PI * 2) % (Math.PI * 2) - Math.PI; - this.refereeYaw += yawDelta * (1 - Math.exp(-3 * dt)); - this.referee.root.rotation.y = this.refereeYaw; - this.referee.hips.position.y = 0.98 + (reducedMotion ? 0 : Math.sin(time * 1.7) * 0.006); + } + + /** Cornermen stand on the apron outside their fighter's corner and lean in during the rest. */ + private updateCornermen(dt: number, time: number, snapshot: EngineSnapshot | null, sampledTick: number): void { + const cornermen = this.cornermen; + if (cornermen === null) return; + const resting = snapshot?.phase === "rest"; + for (const [index, graph] of cornermen.entries()) { + const sign = index === 0 ? -1 : 1; + const reach = resting ? CORNERMAN_WORK_DISTANCE : CORNERMAN_APRON_DISTANCE; + this.cornermanPosition.set(sign * reach, 0, -sign * reach); + const yaw = index === 0 ? (3 * Math.PI) / 4 : -Math.PI / 4; + graph.attend(resting); + const state = refereeSnapshot(this.cornermanPosition, yaw, this.cornermanVelocity, this.mapping); + graph.update(state.self, state.focus, dt, time, false, "off", sampledTick); + } + } + + /** Between rounds each cutman climbs in from the apron, crouches before the seated fighter and works the worse eye, then climbs back out for the bell. */ + private updateCutmen(dt: number, time: number, snapshot: EngineSnapshot | null, sampledTick: number): void { + const cutmen = this.cutmen; + const graphs = this.graphs; + if (cutmen === null || graphs === null) return; + const resting = snapshot?.phase === "rest"; + const corner = this.mapping.x(REST_CORNER_OFFSET); + for (const [index, graph] of cutmen.entries()) { + const sign = index === 0 ? -1 : 1; + const wanted = resting && graphs[index]!.stoolVisible ? 1 : 0; + const progress = this.cutmanProgress[index]!; + const next = progress + Math.sign(wanted - progress) * Math.min(Math.abs(wanted - progress), dt / CUTMAN_WALK_SECONDS); + this.cutmanProgress[index] = next; + const wasVisible = graph.boxer.root.visible; + graph.boxer.root.visible = next > 0.005; + if (!graph.boxer.root.visible) continue; + this.cutmanFrom.set(sign * CORNERMAN_APRON_DISTANCE, 0, -sign * (CORNERMAN_APRON_DISTANCE - 1)); + cornerPoint(index === 0 ? 0 : 1, corner, CUTMAN_WORK_DISTANCE, CUTMAN_WORK_DEGREES, this.cutmanTo); + const eased = next * next * (3 - 2 * next); + this.cornermanPosition.copy(this.cutmanFrom).lerp(this.cutmanTo, eased); + const last = this.cutmanLast[index]!; + if (!wasVisible) last.copy(this.cornermanPosition); + this.cornermanVelocity.copy(this.cornermanPosition).sub(last).divideScalar(Math.max(dt, 1e-3)); + last.copy(this.cornermanPosition); + const travelling = next > 0.02 && next < 0.98; + const head = this.headCacheValid[index] ? this.headCache[index]! : null; + const yaw = travelling + ? Math.atan2(this.cutmanTo.x - this.cutmanFrom.x, this.cutmanTo.z - this.cutmanFrom.z) + (wanted === 1 ? 0 : Math.PI) + : next >= 0.98 + ? (head !== null ? Math.atan2(head.x - this.cutmanTo.x, head.z - this.cutmanTo.z) : Math.atan2(sign, -sign)) + : Math.atan2(-this.cutmanFrom.x, -this.cutmanFrom.z); + const trauma = snapshot?.fighters[index]?.trauma; + const side = trauma !== undefined && trauma.right_eye + trauma.right_cut > trauma.left_eye + trauma.left_cut ? -1 : 1; + if (next >= 0.98 && head !== null) { + const fighterYaw = graphs[index]!.boxer.root.rotation.y; + this.cutmanFacing.set(Math.sin(fighterYaw), 0, Math.cos(fighterYaw)); + this.cutmanEye.copy(head).addScaledVector(this.cutmanFacing, 0.09); + this.cutmanEye.x += Math.cos(fighterYaw) * side * 0.035; + this.cutmanEye.z -= Math.sin(fighterYaw) * side * 0.035; + this.cutmanEye.y += 0.08; + graph.treat(this.cutmanEye, this.cutmanFacing, side); + } else { + graph.treat(null); + } + const state = refereeSnapshot(this.cornermanPosition, yaw, this.cornermanVelocity, this.mapping); + graph.update(state.self, state.focus, dt, time, false, "off", sampledTick); + } } private drawHudOverlay(snapshot: EngineSnapshot | null): void { @@ -829,6 +1687,13 @@ export class FightRenderer { const { context: ctx, viewport } = resized; ctx.clearRect(0, 0, viewport.width, viewport.height); if (snapshot === null) return; + if (this.viewerHitFlash > 0.01 && !this.settings().reducedMotion) { + const flash = ctx.createRadialGradient(viewport.width / 2, viewport.height / 2, viewport.width * 0.12, viewport.width / 2, viewport.height / 2, viewport.width * 0.7); + flash.addColorStop(0, `rgba(255,235,225,${(this.viewerHitFlash * 0.18).toFixed(3)})`); + flash.addColorStop(1, `rgba(140,0,10,${(this.viewerHitFlash * 0.55).toFixed(3)})`); + ctx.fillStyle = flash; + ctx.fillRect(0, 0, viewport.width, viewport.height); + } const hurt = Math.max(...snapshot.fighters.map((fighter) => fighter.trauma.head + fighter.trauma.body)); if (hurt > 350) { const vignette = ctx.createRadialGradient(viewport.width / 2, viewport.height / 2, viewport.width * 0.2, viewport.width / 2, viewport.height / 2, viewport.width * 0.72); @@ -837,7 +1702,7 @@ export class FightRenderer { ctx.fillStyle = vignette; ctx.fillRect(0, 0, viewport.width, viewport.height); } - drawHud(ctx, viewport.width, viewport.height, snapshot, this.players, this.viewerId, this.final, this.reconnectMs, this.simulation.tick_rate); + drawHud(ctx, viewport.width, viewport.height, snapshot, this.players, this.viewerId, this.frameSeconds >= this.finalRevealAt ? this.final : null, this.reconnectMs, this.simulation.tick_rate, this.roundStats, this.replay !== null ? "KNOCKOUT REPLAY" : null, this.inputLatencyMs, this.frameSeconds < this.roundCalloutUntil ? `ROUND ${this.roundCalloutRound}` : null, this.roundClock.ticks(snapshot)); } destroy(): void { @@ -851,10 +1716,6 @@ export class FightRenderer { this.effects.dispose(); this.arena.dispose(); disposeRing(this.ring); - for (const boxer of this.boxers) { - this.scene.remove(boxer.root); - disposeBoxer(boxer); - } if (this.graphs !== null) { for (const graph of this.graphs) { this.scene.remove(graph.boxer.root); @@ -862,20 +1723,49 @@ export class FightRenderer { } this.graphs = null; } - this.scene.remove(this.referee.root); - disposeBoxer(this.referee); + if (this.referee !== null) { + this.scene.remove(this.referee.boxer.root); + this.referee.dispose(); + this.referee = null; + } + for (const trail of this.trails) { + this.scene.remove(trail.mesh); + trail.dispose(); + } + this.trails = []; + if (this.cornermen !== null) { + for (const graph of this.cornermen) { + this.scene.remove(graph.boxer.root); + graph.dispose(); + } + this.cornermen = null; + } + if (this.cutmen !== null) { + for (const graph of this.cutmen) { + this.scene.remove(graph.boxer.root); + graph.dispose(); + } + this.cutmen = null; + } + for (const shirt of this.cornerShirts) shirt.dispose(); + this.cornerShirts.length = 0; + this.refereeShirt?.dispose(); for (const light of this.lights) this.scene.remove(light); this.keyLight?.shadow.map?.dispose(); this.keyLight?.shadow.dispose(); - this.renderer.renderLists.dispose(); - this.composer.dispose(); - this.renderer.dispose(); this.blobTexture.dispose(); for (const blob of this.blobShadows) { this.scene.remove(blob); blob.geometry.dispose(); (blob.material as THREE.Material).dispose(); } + this.renderer.renderLists.dispose(); + disposeComposer(this.composer); + // three's UnrealBloomPass.dispose leaves its bright-pass filter out. + this.bloomPass.materialHighPassFilter.dispose(); + releaseFighterGpu(); + // Last: a disposed renderer forgets what it allocated, so anything freed after it stays on the card. + this.renderer.dispose(); this.hudCanvas.remove(); } } diff --git a/web/hands/src/render/replay.test.ts b/web/hands/src/render/replay.test.ts new file mode 100644 index 00000000..60eaea94 --- /dev/null +++ b/web/hands/src/render/replay.test.ts @@ -0,0 +1,41 @@ +import { describe, expect, it } from "vitest"; +import { snapshot } from "../test/fixtures"; +import type { CombatEvent, EngineSnapshot } from "../types"; +import { planKnockoutReplay, REPLAY_AFTER_TICKS, REPLAY_BEFORE_TICKS, REPLAY_SPEED, REPLAY_TAIL_SECONDS, replayTick } from "./replay"; + +const history = (from: number, to: number): EngineSnapshot[] => { + const base = snapshot(); + const result: EngineSnapshot[] = []; + for (let tick = from; tick <= to; tick += 1) result.push({ ...base, tick }); + return result; +}; +const knockdown = (tick: number): CombatEvent => ({ event_id: 9, tick, kind: "knockdown", actor_id: "one", target_id: "two", amount: 1, detail: "", blood: 0, direction: 1, action_id: null }); + +describe("knockout replay plan", () => { + it("covers the ticks before and after the knockdown at replay speed", () => { + const plan = planKnockoutReplay(history(0, 200), knockdown(100)); + expect(plan).not.toBeNull(); + expect(plan!.fromTick).toBe(100 - REPLAY_BEFORE_TICKS); + expect(plan!.toTick).toBe(100 + REPLAY_AFTER_TICKS); + expect(plan!.snapshots[0]!.tick).toBeLessThanOrEqual(plan!.fromTick); + expect(plan!.snapshots.at(-1)!.tick).toBeGreaterThanOrEqual(plan!.toTick); + expect(plan!.durationSeconds).toBeCloseTo((REPLAY_BEFORE_TICKS + REPLAY_AFTER_TICKS) / 30 / REPLAY_SPEED + REPLAY_TAIL_SECONDS); + expect(replayTick(plan!, 0)).toBe(plan!.fromTick); + expect(replayTick(plan!, 1)).toBeCloseTo(plan!.fromTick + 30 * REPLAY_SPEED); + expect(replayTick(plan!, 100)).toBe(plan!.toTick); + }); + + it("trims to the recording when it starts or ends inside the window", () => { + const plan = planKnockoutReplay(history(80, 120), knockdown(100)); + expect(plan).not.toBeNull(); + expect(plan!.fromTick).toBe(80); + expect(plan!.toTick).toBe(120); + }); + + it("declines when the recording does not reach the knockdown", () => { + expect(planKnockoutReplay(history(0, 200), knockdown(5))).toBeNull(); + expect(planKnockoutReplay(history(0, 200), knockdown(195))).toBeNull(); + expect(planKnockoutReplay([], knockdown(100))).toBeNull(); + expect(planKnockoutReplay(history(0, 200).filter((item) => item.tick % 40 === 0), knockdown(100))).toBeNull(); + }); +}); diff --git a/web/hands/src/render/replay.ts b/web/hands/src/render/replay.ts new file mode 100644 index 00000000..ada5b2af --- /dev/null +++ b/web/hands/src/render/replay.ts @@ -0,0 +1,42 @@ +import type { CombatEvent, EngineSnapshot } from "../types"; + +export const REPLAY_BEFORE_TICKS = 42; +export const REPLAY_AFTER_TICKS = 33; +export const REPLAY_SPEED = 0.4; +export const REPLAY_TAIL_SECONDS = 0.5; + +export interface ReplayPlan { + readonly snapshots: readonly EngineSnapshot[]; + readonly fromTick: number; + readonly toTick: number; + readonly impact: CombatEvent; + readonly speed: number; + readonly durationSeconds: number; +} + +/** + * Selects the recorded snapshots around the knockdown that ended the bout for + * a slow-motion replay, or null when the recording does not cover it. + */ +export function planKnockoutReplay( + history: readonly EngineSnapshot[], + impact: CombatEvent, + tickRate = 30, + speed = REPLAY_SPEED, +): ReplayPlan | null { + const wantedFrom = impact.tick - REPLAY_BEFORE_TICKS; + const wantedTo = impact.tick + REPLAY_AFTER_TICKS; + const snapshots = history.filter((snapshot) => snapshot.tick >= wantedFrom - 1 && snapshot.tick <= wantedTo + 1); + const first = snapshots[0]; + const last = snapshots.at(-1); + if (first === undefined || last === undefined || snapshots.length < 8) return null; + if (first.tick > impact.tick - 12 || last.tick < impact.tick + 12) return null; + const fromTick = Math.max(wantedFrom, first.tick); + const toTick = Math.min(wantedTo, last.tick); + return { snapshots, fromTick, toTick, impact, speed, durationSeconds: (toTick - fromTick) / tickRate / speed + REPLAY_TAIL_SECONDS }; +} + +/** Fractional simulation tick to present `elapsedSeconds` into the replay. */ +export function replayTick(plan: ReplayPlan, elapsedSeconds: number, tickRate = 30): number { + return Math.min(plan.toTick, plan.fromTick + Math.max(0, elapsedSeconds) * tickRate * plan.speed); +} diff --git a/web/hands/src/render/rig.ts b/web/hands/src/render/rig.ts new file mode 100644 index 00000000..9f5460ee --- /dev/null +++ b/web/hands/src/render/rig.ts @@ -0,0 +1,256 @@ +import * as THREE from "three"; +import { BONE_ADAPTER } from "./skeleton"; + +/** + * Direct world-space skeleton control for the Texel Boxer rig. + * + * Every bone points down its local +Y axis. Elbows hinge about the arm bones' + * local Z (mirrored sign per side), knees hinge about the leg bones' local X, + * hands use local +Y for the knuckles and local +Z for the palm normal, and the + * torso chain uses +Y up with +Z as anatomical forward. The rig solves bones top + * down, refreshing each bone's world matrix immediately so children can be + * solved against the parent's new frame. + */ + +export type CanonicalBone = + | "hips" | "spine" | "chest" | "upperChest" | "neck" | "head" + | "clavicleL" | "shoulderL" | "elbowL" | "gloveL" | "clavicleR" | "shoulderR" | "elbowR" | "gloveR" + | "hipL" | "kneeL" | "ankleL" | "toeL" | "hipR" | "kneeR" | "ankleR" | "toeR"; + +export const RIG_BONES: Readonly> = { + hips: BONE_ADAPTER.hips!, + spine: BONE_ADAPTER.spine!, + chest: "Spine1_024", + upperChest: BONE_ADAPTER.chest!, + neck: "Neck_012", + head: BONE_ADAPTER.head!, + clavicleL: "LeftShoulder_09", + shoulderL: BONE_ADAPTER.shoulderL!, + elbowL: BONE_ADAPTER.elbowL!, + gloveL: BONE_ADAPTER.gloveL!, + clavicleR: "RightShoulder_020", + shoulderR: BONE_ADAPTER.shoulderR!, + elbowR: BONE_ADAPTER.elbowR!, + gloveR: BONE_ADAPTER.gloveR!, + hipL: BONE_ADAPTER.hipL!, + kneeL: BONE_ADAPTER.kneeL!, + ankleL: BONE_ADAPTER.ankleL!, + toeL: "LeftToeBase_011", + hipR: BONE_ADAPTER.hipR!, + kneeR: BONE_ADAPTER.kneeR!, + ankleR: BONE_ADAPTER.ankleR!, + toeR: "RightToeBase_022", +}; + +export interface LimbLengths { + readonly upper: number; + readonly lower: number; +} + +export interface RigMetrics { + readonly hipsHeight: number; + readonly headHeight: number; + readonly chestHeight: number; + readonly ankleHeight: number; + readonly armL: LimbLengths; + readonly armR: LimbLengths; + readonly legL: LimbLengths; + readonly legR: LimbLengths; + readonly footLength: number; + readonly unitsPerMeter: number; +} + +const scratchX = new THREE.Vector3(); +const scratchY = new THREE.Vector3(); +const scratchZ = new THREE.Vector3(); +const scratchMatrix = new THREE.Matrix4(); +const scratchWorld = new THREE.Quaternion(); +const scratchParent = new THREE.Quaternion(); +const scratchPosition = new THREE.Vector3(); +const scratchScale = new THREE.Vector3(); +const scratchA = new THREE.Vector3(); +const scratchB = new THREE.Vector3(); +const scratchDir = new THREE.Vector3(); +const scratchBend = new THREE.Vector3(); +const scratchMid = new THREE.Vector3(); +const scratchNormal = new THREE.Vector3(); +const scratchLower = new THREE.Vector3(); +const scratchHint = new THREE.Vector3(); + +export function worldPosition(object: THREE.Object3D, target: THREE.Vector3): THREE.Vector3 { + return target.setFromMatrixPosition(object.matrixWorld); +} + +export function worldQuaternion(object: THREE.Object3D, target: THREE.Quaternion): THREE.Quaternion { + object.matrixWorld.decompose(scratchPosition, target, scratchScale); + return target; +} + +/** Builds a right-handed world rotation whose +Y is `yDir` and whose `axis` (X or Z) is as close as possible to `hint`. */ +export function frameFromAxes(yDir: THREE.Vector3, hint: THREE.Vector3, axis: "x" | "z", target: THREE.Quaternion): THREE.Quaternion { + scratchY.copy(yDir).normalize(); + if (axis === "z") { + scratchZ.copy(hint).addScaledVector(scratchY, -hint.dot(scratchY)); + if (scratchZ.lengthSq() < 1e-8) scratchZ.set(0, 0, 1).addScaledVector(scratchY, -scratchY.z); + scratchZ.normalize(); + scratchX.crossVectors(scratchY, scratchZ).normalize(); + } else { + scratchX.copy(hint).addScaledVector(scratchY, -hint.dot(scratchY)); + if (scratchX.lengthSq() < 1e-8) scratchX.set(1, 0, 0).addScaledVector(scratchY, -scratchY.x); + scratchX.normalize(); + scratchZ.crossVectors(scratchX, scratchY).normalize(); + } + scratchMatrix.makeBasis(scratchX, scratchY, scratchZ); + return target.setFromRotationMatrix(scratchMatrix); +} + +export class SolvedRig { + readonly bones: Readonly>; + readonly metrics: RigMetrics; + private readonly restLocal = new Map(); + private readonly restLocalPosition = new Map(); + private readonly limb = { reached: false, joint: new THREE.Vector3() }; + + constructor(root: THREE.Object3D) { + const found = new Map(); + root.traverse((object) => { + if (object instanceof THREE.Bone) found.set(object.name, object); + }); + const bones = {} as Record; + for (const [canonical, name] of Object.entries(RIG_BONES) as [CanonicalBone, string][]) { + const bone = found.get(name); + if (bone === undefined) throw new Error(`fighter rig missing bone ${name} (${canonical})`); + bones[canonical] = bone; + } + this.bones = bones; + root.updateMatrixWorld(true); + for (const bone of found.values()) { + this.restLocal.set(bone, bone.quaternion.clone()); + this.restLocalPosition.set(bone, bone.position.clone()); + } + const distance = (from: CanonicalBone, to: CanonicalBone): number => + worldPosition(bones[from], scratchA).distanceTo(worldPosition(bones[to], scratchB)); + const hipsWorld = worldPosition(bones.hips, scratchA).clone(); + const hipsParent = bones.hips.parent ?? root; + const parentWorld = worldPosition(hipsParent, scratchB).clone(); + const localLength = bones.hips.position.length(); + const worldLength = hipsWorld.distanceTo(parentWorld); + this.metrics = { + hipsHeight: hipsWorld.y, + headHeight: worldPosition(bones.head, scratchA).y, + chestHeight: worldPosition(bones.upperChest, scratchA).y, + ankleHeight: worldPosition(bones.ankleL, scratchA).y, + armL: { upper: distance("shoulderL", "elbowL"), lower: distance("elbowL", "gloveL") }, + armR: { upper: distance("shoulderR", "elbowR"), lower: distance("elbowR", "gloveR") }, + legL: { upper: distance("hipL", "kneeL"), lower: distance("kneeL", "ankleL") }, + legR: { upper: distance("hipR", "kneeR"), lower: distance("kneeR", "ankleR") }, + footLength: distance("ankleL", "toeL"), + unitsPerMeter: worldLength > 1e-6 ? localLength / worldLength : 1, + }; + } + + resetToRest(): void { + for (const [bone, quaternion] of this.restLocal) { + bone.quaternion.copy(quaternion); + const position = this.restLocalPosition.get(bone); + if (position !== undefined) bone.position.copy(position); + } + } + + restLocalQuaternion(bone: THREE.Bone): THREE.Quaternion { + return this.restLocal.get(bone) ?? bone.quaternion; + } + + position(bone: CanonicalBone, target: THREE.Vector3): THREE.Vector3 { + return worldPosition(this.bones[bone], target); + } + + /** Sets a bone's world rotation, keeping its rest position, and refreshes its world matrix. */ + setWorldRotation(bone: THREE.Bone, world: THREE.Quaternion): void { + const parent = bone.parent; + if (parent === null) { + bone.quaternion.copy(world); + } else { + worldQuaternion(parent, scratchParent); + bone.quaternion.copy(scratchParent.invert().multiply(world)).normalize(); + } + bone.updateWorldMatrix(false, false); + } + + setWorldFrame(bone: THREE.Bone, yDir: THREE.Vector3, hint: THREE.Vector3, axis: "x" | "z"): void { + this.setWorldRotation(bone, frameFromAxes(yDir, hint, axis, scratchWorld)); + } + + /** Moves a bone to a world position (its parent's frame is converted), keeping rotation. */ + setWorldPosition(bone: THREE.Bone, world: THREE.Vector3): void { + const parent = bone.parent; + if (parent === null) { + bone.position.copy(world); + } else { + bone.position.copy(world); + parent.worldToLocal(bone.position); + } + bone.updateWorldMatrix(false, false); + } + + /** Rotates a bone so its +Y points at `target` while keeping its rest roll as closely as possible. */ + aimAt(bone: THREE.Bone, target: THREE.Vector3, axis: "x" | "z"): void { + bone.updateWorldMatrix(false, false); + worldPosition(bone, scratchA); + scratchDir.subVectors(target, scratchA); + if (scratchDir.lengthSq() < 1e-10) return; + worldQuaternion(bone, scratchWorld); + const hint = axis === "z" ? scratchHint.set(0, 0, 1) : scratchHint.set(1, 0, 0); + this.setWorldFrame(bone, scratchDir, hint.applyQuaternion(scratchWorld), axis); + } + + /** + * Two-bone IK. `pole` is a world direction the joint bends toward. `hingeAxis` + * selects which local axis of the two bones is the hinge and `hingeSign` + * orients it (+1: hinge = pole x limb direction, -1: the opposite). The + * returned result is reused by the next solve. + */ + solveLimb( + upper: THREE.Bone, + lower: THREE.Bone, + lengths: LimbLengths, + target: THREE.Vector3, + pole: THREE.Vector3, + hingeAxis: "x" | "z", + hingeSign: 1 | -1, + minimumBend = 0.01, + ): { readonly reached: boolean; readonly joint: THREE.Vector3 } { + upper.updateWorldMatrix(false, false); + const root = worldPosition(upper, scratchA); + scratchDir.subVectors(target, root); + const maximum = lengths.upper + lengths.lower - minimumBend; + const distance = THREE.MathUtils.clamp(scratchDir.length(), Math.abs(lengths.upper - lengths.lower) + 0.005, maximum); + const reached = scratchDir.length() <= maximum; + if (scratchDir.lengthSq() < 1e-10) scratchDir.set(0, -1, 0); + scratchDir.normalize(); + scratchBend.copy(pole).addScaledVector(scratchDir, -pole.dot(scratchDir)); + if (scratchBend.lengthSq() < 1e-8) { + scratchBend.set(0, 0, 1).addScaledVector(scratchDir, -scratchDir.z); + if (scratchBend.lengthSq() < 1e-8) scratchBend.set(1, 0, 0); + } + scratchBend.normalize(); + const cosUpper = THREE.MathUtils.clamp( + (lengths.upper * lengths.upper + distance * distance - lengths.lower * lengths.lower) / (2 * lengths.upper * distance), + -1, + 1, + ); + const along = lengths.upper * cosUpper; + const out = lengths.upper * Math.sqrt(Math.max(0, 1 - cosUpper * cosUpper)); + scratchMid.copy(root).addScaledVector(scratchDir, along).addScaledVector(scratchBend, out); + scratchNormal.crossVectors(scratchBend, scratchDir).multiplyScalar(hingeSign).normalize(); + scratchLower.copy(scratchMid).sub(root); + this.setWorldFrame(upper, scratchLower, scratchNormal, hingeAxis); + lower.updateWorldMatrix(false, false); + const jointWorld = worldPosition(lower, scratchB); + scratchLower.copy(root).addScaledVector(scratchDir, distance).sub(jointWorld); + this.setWorldFrame(lower, scratchLower, scratchNormal, hingeAxis); + this.limb.reached = reached; + this.limb.joint.copy(jointWorld); + return this.limb; + } +} diff --git a/web/hands/src/render/ring.ts b/web/hands/src/render/ring.ts index b001f34f..9fb709d2 100644 --- a/web/hands/src/render/ring.ts +++ b/web/hands/src/render/ring.ts @@ -6,8 +6,50 @@ export interface BuiltRing { readonly materials: readonly THREE.Material[]; readonly geometries: readonly THREE.BufferGeometry[]; readonly textures: readonly THREE.Texture[]; + /** Feeds the two fighters' world positions to the rope flex shader. */ + readonly setRopeContacts: (a: { x: number; z: number } | null, b: { x: number; z: number } | null) => void; + readonly ropeContacts: readonly [THREE.Vector4, THREE.Vector4]; } +export interface RopePress { + readonly pressX: number; + readonly pressZ: number; +} + +const ROPE_PRESS_START = 0.6; +const ROPE_PRESS_FULL = 0.22; + +function smoothstep(edge0: number, edge1: number, value: number): number { + const t = Math.min(1, Math.max(0, (value - edge0) / (edge1 - edge0))); + return t * t * (3 - 2 * t); +} + +/** How hard a fighter at (x, z) leans into the x-facing and z-facing ropes (0..1 each). */ +export function ropePress(x: number, z: number): RopePress { + return { + pressX: smoothstep(ROPE_PRESS_START, ROPE_PRESS_FULL, RING_FIGHT_HALF - Math.abs(x)), + pressZ: smoothstep(ROPE_PRESS_START, ROPE_PRESS_FULL, RING_FIGHT_HALF - Math.abs(z)), + }; +} + +const ROPE_FLEX_GLSL = ` +vec3 ropeWorld = (modelMatrix * vec4(transformed, 1.0)).xyz; +bool ropeSideX = abs(ropeWorld.x) > abs(ropeWorld.z); +vec3 ropeOut = ropeSideX ? vec3(sign(ropeWorld.x), 0.0, 0.0) : vec3(0.0, 0.0, sign(ropeWorld.z)); +float ropeAlong = ropeSideX ? ropeWorld.z : ropeWorld.x; +float ropeFlex = 0.0; +for (int ropeIndex = 0; ropeIndex < 2; ropeIndex += 1) { + vec4 contact = ropeIndex == 0 ? uRopeContactA : uRopeContactB; + float along = ropeSideX ? contact.y : contact.x; + float press = ropeSideX ? contact.z : contact.w; + float sameSide = ropeSideX ? step(0.0, ropeOut.x * contact.x) : step(0.0, ropeOut.z * contact.y); + ropeFlex += press * sameSide * (1.0 - smoothstep(0.0, 0.8, abs(ropeAlong - along))); +} +float ropeAnchor = smoothstep(0.0, 0.7, ${RING_FIGHT_HALF.toFixed(2)} - abs(ropeAlong)); +float ropeHeightWeight = 0.45 + 0.55 * smoothstep(0.4, 1.0, ropeWorld.y); +transformed += ropeOut * min(1.0, ropeFlex) * 0.22 * ropeHeightWeight * ropeAnchor; +`; + function canvasTexture(size: number, draw: (ctx: CanvasRenderingContext2D, size: number) => void): THREE.CanvasTexture { const canvas = document.createElement("canvas"); canvas.width = size; @@ -22,34 +64,42 @@ function canvasTexture(size: number, draw: (ctx: CanvasRenderingContext2D, size: function ringCanvasTexture(): THREE.CanvasTexture { return canvasTexture(1024, (ctx, size) => { - ctx.fillStyle = "#2c4386"; + ctx.fillStyle = "#9d968a"; ctx.fillRect(0, 0, size, size); const noise = ctx.createLinearGradient(0, 0, size, size); - noise.addColorStop(0, "rgba(255,255,255,0.05)"); - noise.addColorStop(0.5, "rgba(0,0,0,0.04)"); - noise.addColorStop(1, "rgba(255,255,255,0.03)"); + noise.addColorStop(0, "rgba(255,255,255,0.08)"); + noise.addColorStop(0.5, "rgba(60,50,40,0.06)"); + noise.addColorStop(1, "rgba(255,255,255,0.04)"); ctx.fillStyle = noise; ctx.fillRect(0, 0, size, size); - for (let i = 0; i < 900; i += 1) { + for (let i = 0; i < 2600; i += 1) { const x = (Math.sin(i * 12.9898) * 43758.5453) % 1; const y = (Math.sin(i * 78.233) * 12543.1234) % 1; - ctx.fillStyle = `rgba(${i % 2 === 0 ? "255,255,255" : "10,20,50"},${0.015 + (i % 5) * 0.004})`; - ctx.fillRect(Math.abs(x) * size, Math.abs(y) * size, 2 + (i % 3), 1 + (i % 2)); + ctx.fillStyle = `rgba(${i % 3 === 0 ? "255,255,255" : "70,55,45"},${0.02 + (i % 5) * 0.006})`; + ctx.fillRect(Math.abs(x) * size, Math.abs(y) * size, 2 + (i % 4), 1 + (i % 3)); } - ctx.strokeStyle = "rgba(235,240,255,0.9)"; - ctx.lineWidth = 10; + for (let i = 0; i < 40; i += 1) { + const x = Math.abs((Math.sin(i * 91.7) * 7919.3) % 1) * size; + const y = Math.abs((Math.sin(i * 47.1) * 4271.9) % 1) * size; + ctx.fillStyle = `rgba(80,60,50,${0.05 + (i % 4) * 0.02})`; + ctx.beginPath(); + ctx.ellipse(x, y, 18 + (i % 7) * 6, 6 + (i % 5) * 3, (i * 0.7) % Math.PI, 0, Math.PI * 2); + ctx.fill(); + } + ctx.strokeStyle = "rgba(30,60,140,0.85)"; + ctx.lineWidth = 12; ctx.beginPath(); ctx.arc(size / 2, size / 2, size * 0.2, 0, Math.PI * 2); ctx.stroke(); - ctx.fillStyle = "rgba(235,240,255,0.92)"; + ctx.fillStyle = "rgba(30,60,140,0.9)"; ctx.font = `800 ${Math.round(size * 0.062)}px Inter, system-ui, sans-serif`; ctx.textAlign = "center"; ctx.textBaseline = "middle"; ctx.fillText("H A N D S", size / 2, size / 2 - size * 0.012); ctx.font = `600 ${Math.round(size * 0.024)}px Inter, system-ui, sans-serif`; ctx.fillText("AUTHORITATIVE BOXING", size / 2, size / 2 + size * 0.052); - ctx.strokeStyle = "rgba(235,240,255,0.55)"; - ctx.lineWidth = 5; + ctx.strokeStyle = "rgba(30,60,140,0.6)"; + ctx.lineWidth = 6; ctx.strokeRect(size * 0.035, size * 0.035, size * 0.93, size * 0.93); }); } @@ -63,7 +113,7 @@ export function buildRing(): BuiltRing { const canvasMap = ringCanvasTexture(); textures.push(canvasMap); - const canvasMat = new THREE.MeshStandardMaterial({ map: canvasMap, roughness: 0.92, metalness: 0 }); + const canvasMat = new THREE.MeshStandardMaterial({ map: canvasMap, roughness: 0.88, metalness: 0 }); materials.push(canvasMat); const canvasGeo = new THREE.PlaneGeometry(RING_FIGHT_HALF * 2, RING_FIGHT_HALF * 2); geometries.push(canvasGeo); @@ -73,7 +123,7 @@ export function buildRing(): BuiltRing { canvasMesh.receiveShadow = true; group.add(canvasMesh); - const apronMat = new THREE.MeshStandardMaterial({ color: "#16233f", roughness: 0.85 }); + const apronMat = new THREE.MeshStandardMaterial({ color: "#1c2b52", roughness: 0.85 }); materials.push(apronMat); const apronGeo = new THREE.RingGeometry(RING_FIGHT_HALF * 0.98, RING_APRON_HALF, 4, 1); geometries.push(apronGeo); @@ -135,12 +185,32 @@ export function buildRing(): BuiltRing { } } + const ropeContacts: [THREE.Vector4, THREE.Vector4] = [new THREE.Vector4(0, 0, 0, 0), new THREE.Vector4(0, 0, 0, 0)]; + const ropeUniforms = { uRopeContactA: { value: ropeContacts[0] }, uRopeContactB: { value: ropeContacts[1] } }; const ropeColors = [0xb91c1c, 0xe5e7eb, 0x1d4ed8]; const ropeMats = ropeColors.map((color) => { const material = new THREE.MeshStandardMaterial({ color, roughness: 0.42, metalness: 0.05 }); + material.onBeforeCompile = (shader) => { + shader.uniforms.uRopeContactA = ropeUniforms.uRopeContactA; + shader.uniforms.uRopeContactB = ropeUniforms.uRopeContactB; + shader.vertexShader = shader.vertexShader + .replace("#include ", "#include \nuniform vec4 uRopeContactA;\nuniform vec4 uRopeContactB;") + .replace("#include ", `#include ${ROPE_FLEX_GLSL}`); + }; materials.push(material); return material; }); + const setRopeContacts = (a: { x: number; z: number } | null, b: { x: number; z: number } | null): void => { + for (const [index, contact] of [a, b].entries()) { + const target = ropeContacts[index]!; + if (contact === null) { + target.set(0, 0, 0, 0); + continue; + } + const press = ropePress(contact.x, contact.z); + target.set(contact.x, contact.z, press.pressX, press.pressZ); + } + }; for (let side = 0; side < 4; side += 1) { const from = corners[side]!; const to = corners[(side + 1) % 4]!; @@ -171,7 +241,7 @@ export function buildRing(): BuiltRing { } } - return { group, materials, geometries, textures }; + return { group, materials, geometries, textures, setRopeContacts, ropeContacts }; } export function disposeRing(ring: BuiltRing): void { diff --git a/web/hands/src/render/trails.test.ts b/web/hands/src/render/trails.test.ts new file mode 100644 index 00000000..65a4861b --- /dev/null +++ b/web/hands/src/render/trails.test.ts @@ -0,0 +1,50 @@ +import * as THREE from "three"; +import { describe, expect, it } from "vitest"; +import { GloveTrail } from "./trails"; + +describe("glove trail", () => { + it("appears only while the glove moves at punch speed and fades out afterwards", () => { + const trail = new GloveTrail(new THREE.Color(0xffffff)); + const camera = new THREE.Vector3(0, 2, 5); + const glove = new THREE.Vector3(0, 1.3, 0); + for (let frame = 0; frame < 12; frame += 1) { + glove.z += 0.01; + trail.update(glove, 1 / 60, camera, true); + } + expect(trail.active).toBe(false); + for (let frame = 0; frame < 12; frame += 1) { + glove.z += 0.1; + trail.update(glove, 1 / 60, camera, true); + } + expect(trail.active).toBe(true); + const alphas = trail.mesh.geometry.getAttribute("color") as THREE.BufferAttribute; + expect(alphas.getW(alphas.count - 1)).toBeGreaterThan(alphas.getW(0)); + for (let frame = 0; frame < 30; frame += 1) trail.update(glove, 1 / 60, camera, true); + expect(trail.active).toBe(false); + for (let frame = 0; frame < 12; frame += 1) { + glove.z += 0.1; + trail.update(glove, 1 / 60, camera, false); + } + expect(trail.active).toBe(false); + trail.dispose(); + }); + + it("reuses its sample vectors instead of allocating one every frame", () => { + const trail = new GloveTrail(new THREE.Color(0xffffff)); + const camera = new THREE.Vector3(0, 2, 5); + const glove = new THREE.Vector3(0, 1.3, 0); + const history = (trail as unknown as { history: THREE.Vector3[] }).history; + for (let frame = 0; frame < 40; frame += 1) { + glove.z += 0.05; + trail.update(glove, 1 / 60, camera, true); + } + const pool = new Set(history); + for (let frame = 0; frame < 200; frame += 1) { + glove.z += 0.05; + trail.update(glove, 1 / 60, camera, true); + for (const sample of history) expect(pool.has(sample)).toBe(true); + } + expect(history.at(-1)!.z).toBeCloseTo(glove.z); + trail.dispose(); + }); +}); diff --git a/web/hands/src/render/trails.ts b/web/hands/src/render/trails.ts new file mode 100644 index 00000000..fa32fbcb --- /dev/null +++ b/web/hands/src/render/trails.ts @@ -0,0 +1,104 @@ +import * as THREE from "three"; + +const SAMPLES = 10; +const WIDTH = 0.055; +const MIN_SPEED = 3.2; + +/** + * Additive ribbon behind a fast-moving glove. Positions are sampled every + * frame; the ribbon only shows while the glove moves faster than a punch + * threshold and fades toward its tail. + */ +export class GloveTrail { + readonly mesh: THREE.Mesh; + private readonly geometry: THREE.BufferGeometry; + private readonly positions = new Float32Array(SAMPLES * 2 * 3); + private readonly colors = new Float32Array(SAMPLES * 2 * 4); + private readonly history: THREE.Vector3[] = []; + private readonly last = new THREE.Vector3(); + private hasLast = false; + private readonly tangent = new THREE.Vector3(); + private readonly side = new THREE.Vector3(); + private readonly toCamera = new THREE.Vector3(); + private strength = 0; + + constructor(private readonly color: THREE.Color) { + this.geometry = new THREE.BufferGeometry(); + this.geometry.setAttribute("position", new THREE.BufferAttribute(this.positions, 3).setUsage(THREE.DynamicDrawUsage)); + this.geometry.setAttribute("color", new THREE.BufferAttribute(this.colors, 4).setUsage(THREE.DynamicDrawUsage)); + const index: number[] = []; + for (let i = 0; i < SAMPLES - 1; i += 1) { + const a = i * 2; + index.push(a, a + 1, a + 2, a + 1, a + 3, a + 2); + } + this.geometry.setIndex(index); + const material = new THREE.MeshBasicMaterial({ vertexColors: true, transparent: true, blending: THREE.AdditiveBlending, depthWrite: false, side: THREE.DoubleSide }); + this.mesh = new THREE.Mesh(this.geometry, material); + this.mesh.frustumCulled = false; + this.mesh.visible = false; + this.mesh.renderOrder = 4; + } + + /** Feeds the glove's world position for this frame. */ + update(glove: THREE.Vector3, dt: number, cameraPosition: THREE.Vector3, enabled: boolean): void { + if (dt <= 0) return; + const speed = this.hasLast ? glove.distanceTo(this.last) / dt : 0; + this.last.copy(glove); + this.hasLast = true; + const target = enabled && speed > MIN_SPEED ? Math.min(1, (speed - MIN_SPEED) / 4) : 0; + this.strength += (target - this.strength) * Math.min(1, dt * 18); + const sample = this.history.length >= SAMPLES ? this.history.shift()! : new THREE.Vector3(); + sample.copy(glove); + this.history.push(sample); + if (this.strength < 0.02 || this.history.length < 3) { + this.mesh.visible = false; + return; + } + const count = this.history.length; + for (let i = 0; i < SAMPLES; i += 1) { + const point = this.history[Math.max(0, count - SAMPLES + i)]!; + const next = this.history[Math.min(count - 1, Math.max(1, count - SAMPLES + i + 1))]!; + const previous = this.history[Math.max(0, count - SAMPLES + i - 1)]!; + this.tangent.subVectors(next, previous); + if (this.tangent.lengthSq() < 1e-8) this.tangent.set(0, 1, 0); + this.toCamera.subVectors(cameraPosition, point); + this.side.crossVectors(this.tangent, this.toCamera).normalize(); + const age = i / (SAMPLES - 1); + const width = WIDTH * (0.35 + 0.65 * age); + const alpha = this.strength * age * age; + const offset = i * 6; + this.positions[offset] = point.x - this.side.x * width; + this.positions[offset + 1] = point.y - this.side.y * width; + this.positions[offset + 2] = point.z - this.side.z * width; + this.positions[offset + 3] = point.x + this.side.x * width; + this.positions[offset + 4] = point.y + this.side.y * width; + this.positions[offset + 5] = point.z + this.side.z * width; + for (let corner = 0; corner < 2; corner += 1) { + const c = (i * 2 + corner) * 4; + this.colors[c] = this.color.r; + this.colors[c + 1] = this.color.g; + this.colors[c + 2] = this.color.b; + this.colors[c + 3] = alpha; + } + } + (this.geometry.getAttribute("position") as THREE.BufferAttribute).needsUpdate = true; + (this.geometry.getAttribute("color") as THREE.BufferAttribute).needsUpdate = true; + this.mesh.visible = true; + } + + get active(): boolean { + return this.mesh.visible; + } + + reset(): void { + this.history.length = 0; + this.hasLast = false; + this.strength = 0; + this.mesh.visible = false; + } + + dispose(): void { + this.geometry.dispose(); + (this.mesh.material as THREE.Material).dispose(); + } +} diff --git a/web/hands/src/state.test.ts b/web/hands/src/state.test.ts index 2c12d9ba..8aa410ef 100644 --- a/web/hands/src/state.test.ts +++ b/web/hands/src/state.test.ts @@ -2,20 +2,20 @@ import { initialState, reduceState } from "./state"; import { publicPlayers, snapshot } from "./test/fixtures"; describe("authoritative state reducer", () => { it("moves through wait, ready, combat, pause, resume and final without client outcomes", () => { - let state = reduceState(initialState, { type: "message", message: { version: 2, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [publicPlayers[0]], server_tick: 0, next_sequence: 7 } }); + let state = reduceState(initialState, { type: "message", message: { version: 3, type: "welcome", role: "fighter", player_id: "one", seat: 1, rating: 1500, players: [publicPlayers[0]], server_tick: 0, next_sequence: 7 } }); expect(state).toMatchObject({ role: "fighter", playerId: "one", nextSequence: 7 }); - state = reduceState(state, { type: "message", message: { version: 2, type: "waiting", open_seats: 1 } }); expect(state.stage).toBe("waiting"); - state = reduceState(state, { type: "message", message: { version: 2, type: "ready", players: [...publicPlayers] } }); expect(Object.keys(state.players)).toHaveLength(2); - state = reduceState(state, { type: "message", message: { version: 2, type: "snapshot", payload: snapshot(20) } }); expect(state.stage).toBe("fight"); - state = reduceState(state, { type: "message", message: { version: 2, type: "paused", player_id: "two", grace_ms: 20000 } }); expect(state.stage).toBe("paused"); - state = reduceState(state, { type: "message", message: { version: 2, type: "resumed", player_id: "two" } }); expect(state.stage).toBe("fight"); - state = reduceState(state, { type: "message", message: { version: 2, type: "final", match_id: "m", winner_id: null, method: "draw", round: 12, scorecards: [], ratings: { one: { before: 1500, after: 1500 }, two: { before: 1500, after: 1500 } } } }); expect(state.stage).toBe("complete"); + state = reduceState(state, { type: "message", message: { version: 3, type: "waiting", open_seats: 1 } }); expect(state.stage).toBe("waiting"); + state = reduceState(state, { type: "message", message: { version: 3, type: "ready", players: [...publicPlayers] } }); expect(Object.keys(state.players)).toHaveLength(2); + state = reduceState(state, { type: "message", message: { version: 3, type: "snapshot", payload: snapshot(20) } }); expect(state.stage).toBe("fight"); + state = reduceState(state, { type: "message", message: { version: 3, type: "paused", player_id: "two", grace_ms: 20000 } }); expect(state.stage).toBe("paused"); + state = reduceState(state, { type: "message", message: { version: 3, type: "resumed", player_id: "two" } }); expect(state.stage).toBe("fight"); + state = reduceState(state, { type: "message", message: { version: 3, type: "final", match_id: "m", winner_id: null, method: "draw", round: 12, scorecards: [], ratings: { one: { before: 1500, after: 1500 }, two: { before: 1500, after: 1500 } } } }); expect(state.stage).toBe("complete"); }); it("stores spectator role without granting fighter identity or sequence authority", () => { - const state = reduceState(initialState, { type: "message", message: { version: 2, type: "welcome", role: "spectator", player_id: "viewer", players: [...publicPlayers], server_tick: 30 } }); + const state = reduceState(initialState, { type: "message", message: { version: 3, type: "welcome", role: "spectator", player_id: "viewer", players: [...publicPlayers], server_tick: 30 } }); expect(state).toMatchObject({ role: "spectator", playerId: null, nextSequence: 0, serverTick: 30 }); expect(Object.keys(state.players)).toEqual(["one", "two"]); }); - it("keeps refreshed credentials out of application state", () => expect(reduceState(initialState, { type: "message", message: { version: 2, type: "ticket", reconnect_ticket: "memory-only", refresh_id: "refresh-identifier" } })).toBe(initialState)); - it("fails closed on safe server errors", () => expect(reduceState(initialState, { type: "message", message: { version: 2, type: "error", code: "invalid_input" } }).safeError).toBe("invalid_input")); + it("keeps refreshed credentials out of application state", () => expect(reduceState(initialState, { type: "message", message: { version: 3, type: "ticket", reconnect_ticket: "memory-only", refresh_id: "refresh-identifier" } })).toBe(initialState)); + it("fails closed on safe server errors", () => expect(reduceState(initialState, { type: "message", message: { version: 3, type: "error", code: "invalid_input" } }).safeError).toBe("invalid_input")); }); diff --git a/web/hands/src/state.ts b/web/hands/src/state.ts index 6d2aae1f..750f4dcd 100644 --- a/web/hands/src/state.ts +++ b/web/hands/src/state.ts @@ -7,6 +7,7 @@ export interface GameState { readonly playerId: string | null; readonly role: ConnectionRole | null; readonly players: Readonly>; + readonly playerOrder: readonly string[]; readonly simulation: SimulationInfo | null; readonly snapshot: EngineSnapshot | null; readonly final: FinalMessage | null; @@ -15,7 +16,7 @@ export interface GameState { readonly reconnectMs: number; readonly safeError: string | null; } -export const initialState: GameState = { stage: "bootstrapping", player: null, playerId: null, role: null, players: {}, simulation: null, snapshot: null, final: null, serverTick: 0, nextSequence: 0, reconnectMs: 0, safeError: null }; +export const initialState: GameState = { stage: "bootstrapping", player: null, playerId: null, role: null, players: {}, playerOrder: [], simulation: null, snapshot: null, final: null, serverTick: 0, nextSequence: 0, reconnectMs: 0, safeError: null }; export type StateAction = { type: "bootstrap"; simulation: SimulationInfo } | { type: "authorized"; player: TokenPlayer } | { type: "connecting" } | { type: "message"; message: ServerMessage } | { type: "reconnect-tick"; remainingMs: number } | { type: "fatal"; code: string }; const mapPlayers = (players: readonly PublicPlayer[]): Readonly> => Object.fromEntries(players.map((player) => [player.id, player])); @@ -27,10 +28,10 @@ export function reduceState(state: GameState, action: StateAction): GameState { if (action.type === "fatal") return { ...state, stage: "fatal", safeError: action.code, reconnectMs: 0 }; const message = action.message; switch (message.type) { - case "welcome": return { ...state, playerId: message.role === "fighter" ? message.player_id : null, role: message.role, players: mapPlayers(message.players), serverTick: message.server_tick, nextSequence: message.role === "fighter" ? message.next_sequence : 0, safeError: null }; + case "welcome": return { ...state, playerId: message.role === "fighter" ? message.player_id : null, role: message.role, players: mapPlayers(message.players), playerOrder: message.players.map((player) => player.id), serverTick: message.server_tick, nextSequence: message.role === "fighter" ? message.next_sequence : 0, safeError: null }; case "ticket": return state; case "waiting": return { ...state, stage: "waiting" }; - case "ready": return { ...state, stage: state.snapshot?.phase ?? "countdown", players: mapPlayers(message.players) }; + case "ready": return { ...state, stage: state.snapshot?.phase ?? "countdown", players: mapPlayers(message.players), playerOrder: message.players.map((player) => player.id) }; case "paused": return { ...state, stage: "paused", reconnectMs: message.grace_ms }; case "resumed": return { ...state, stage: state.snapshot?.phase ?? "countdown", reconnectMs: 0 }; case "snapshot": return { ...state, stage: message.payload.phase, snapshot: message.payload, serverTick: Math.max(state.serverTick, message.payload.tick) }; diff --git a/web/hands/src/style.css b/web/hands/src/style.css index 237654eb..832d62f1 100644 --- a/web/hands/src/style.css +++ b/web/hands/src/style.css @@ -1,4 +1,6 @@ -:root{font-family:Inter,ui-sans-serif,system-ui,-apple-system,BlinkMacSystemFont,"Segoe UI",sans-serif;color:#f2f6ff;background:#07090e;font-synthesis:none}*{box-sizing:border-box}html,body,#app{width:100%;height:100%;margin:0;overflow:hidden}.activity{position:relative;width:100%;height:100%;min-height:320px;background:#080b12}.fight{display:block;width:100%;height:100%;touch-action:none}.topbar{position:absolute;top:max(8px,env(safe-area-inset-top));left:50%;transform:translateX(-50%);display:flex;align-items:center;gap:12px;padding:7px 10px;border:1px solid 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+++ b/web/hands/src/test/fixtures.ts @@ -1,5 +1,5 @@ import type { EngineSnapshot, FighterSnapshot } from "../types"; -export const fighter = (id: string, x = 0): FighterSnapshot => ({ player_id: id, x, y: 0, facing: id === "one" ? 1 : -1, velocity_x: 0, velocity_y: 0, stance: "orthodox", defense: "none", stamina: 900, maximum_stamina: 1000, conditioning: 850, guard: 650, poise: 550, trauma: { head: 0, body: 0, left_eye: 0, right_eye: 0, left_cut: 0, right_cut: 0, swelling: 0, bleeding: 0 }, knockdowns: 0, warnings: 0, deductions: 0, stunned_ticks: 0, is_downed: false, action: null, action_hand: null, action_target: null, action_power: null, action_id: null, action_key: null, action_start_tick: 0, action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, taunt_ticks: 0, get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, get_up_window_start_tick: 0, get_up_window_end_tick: 0 }); +export const fighter = (id: string, x = 0): FighterSnapshot => ({ player_id: id, x, y: 0, facing: id === "one" ? 1 : -1, facing_x: id === "one" ? 1000 : -1000, facing_y: 0, velocity_x: 0, velocity_y: 0, stance: "orthodox", defense: "none", stamina: 900, maximum_stamina: 1000, conditioning: 850, guard: 650, poise: 550, trauma: { head: 0, body: 0, left_eye: 0, right_eye: 0, left_cut: 0, right_cut: 0, swelling: 0, bleeding: 0 }, knockdowns: 0, warnings: 0, deductions: 0, stunned_ticks: 0, is_downed: false, action: null, action_hand: null, action_target: null, action_power: null, action_id: null, action_key: null, action_start_tick: 0, action_startup_ticks: 0, action_active_ticks: 0, action_recovery_ticks: 0, action_contact_tick: null, queued_actions: 0, clinch_startup_ticks: 0, clinch_ticks: 0, is_foul_recovery_target: false, taunt_ticks: 0, get_up_prompt: null, get_up_meter: 0, get_up_required: 0, get_up_count: 0, get_up_window_start_tick: 0, get_up_window_end_tick: 0, last_input_sequence: -1 }); export const snapshot = (tick = 10): EngineSnapshot => ({ tick, phase: "fight", round_number: 1, phase_ticks_remaining: 5000, fighters: [fighter("one", -100), fighter("two", 100)], events: [], result: null, checksum: "a".repeat(64) }); -export const envelope = (tick = 10): Record => ({ version: 2, type: "snapshot", payload: snapshot(tick) }); +export const envelope = (tick = 10): Record => ({ version: 3, type: "snapshot", payload: snapshot(tick) }); export const publicPlayers = [{ id: "one", name: "One", avatar: null, rating: 1500, connected: true }, { id: "two", name: "Two", avatar: null, rating: 1500, connected: true }] as const; diff --git a/web/hands/src/test/punch-timing-table.json b/web/hands/src/test/punch-timing-table.json new file mode 100644 index 00000000..a408b033 --- /dev/null +++ b/web/hands/src/test/punch-timing-table.json @@ -0,0 +1 @@ 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diff --git a/web/hands/src/test/webgl.ts b/web/hands/src/test/webgl.ts new file mode 100644 index 00000000..60bb9187 --- /dev/null +++ b/web/hands/src/test/webgl.ts @@ -0,0 +1,127 @@ +/** + * A WebGL 2 stand-in for jsdom: enough for three.js to build its programs, buffers, textures and render + * targets and to draw (as no-ops), so a real FightRenderer can run in a test. It counts the graphics + * objects alive on the context, as the rematch scenario does in a real browser, because three's own + * counters start again at zero with every renderer on a shared context. + */ +export type GlObjectKind = "buffers" | "textures" | "programs" | "shaders" | "framebuffers" | "renderbuffers" | "vertexArrays"; + +export interface FakeWebGl { + readonly context: WebGL2RenderingContext; + /** Objects created and not deleted yet, per kind. */ + live(): Record; + /** Objects created since the context was made, per kind. */ + readonly created: Record; + /** Whether a handle the context gave out is still alive. */ + alive(handle: unknown): boolean; +} + +const KINDS: readonly GlObjectKind[] = ["buffers", "textures", "programs", "shaders", "framebuffers", "renderbuffers", "vertexArrays"]; +const CREATE: Readonly> = { + createBuffer: "buffers", createTexture: "textures", createProgram: "programs", createShader: "shaders", + createFramebuffer: "framebuffers", createRenderbuffer: "renderbuffers", createVertexArray: "vertexArrays", +}; +const DELETE: Readonly> = { + deleteBuffer: "buffers", deleteTexture: "textures", deleteProgram: "programs", deleteShader: "shaders", + deleteFramebuffer: "framebuffers", deleteRenderbuffer: "renderbuffers", deleteVertexArray: "vertexArrays", +}; +const PARAMETERS: Readonly> = { + VERSION: "WebGL 2.0 (test)", SHADING_LANGUAGE_VERSION: "WebGL GLSL ES 3.00 (test)", VENDOR: "test", RENDERER: "test", + MAX_TEXTURE_IMAGE_UNITS: 16, MAX_VERTEX_TEXTURE_IMAGE_UNITS: 16, MAX_COMBINED_TEXTURE_IMAGE_UNITS: 32, + MAX_TEXTURE_SIZE: 4096, MAX_CUBE_MAP_TEXTURE_SIZE: 4096, MAX_RENDERBUFFER_SIZE: 4096, MAX_3D_TEXTURE_SIZE: 2048, + MAX_ARRAY_TEXTURE_LAYERS: 256, MAX_VERTEX_ATTRIBS: 16, MAX_VERTEX_UNIFORM_VECTORS: 1024, MAX_VARYING_VECTORS: 30, + MAX_FRAGMENT_UNIFORM_VECTORS: 1024, MAX_SAMPLES: 4, SAMPLES: 4, MAX_UNIFORM_BUFFER_BINDINGS: 24, MAX_DRAW_BUFFERS: 8, +}; + +export function fakeWebGl(canvas: HTMLCanvasElement): FakeWebGl { + const handles = new Map(); + const created = Object.fromEntries(KINDS.map((kind) => [kind, 0])) as Record; + // Enum values only need to be distinct and stable; parameters are looked up by name. + const enums = new Map(); + const names = new Map(); + const constant = (name: string): number => { + let value = enums.get(name); + if (value === undefined) { + value = 0x10000 + enums.size; + enums.set(name, value); + names.set(value, name); + } + return value; + }; + const methods: Record unknown> = { + getParameter: (pname) => { + const name = names.get(pname as number) ?? ""; + if (name === "SCISSOR_BOX" || name === "VIEWPORT") return new Int32Array([0, 0, canvas.width, canvas.height]); + return PARAMETERS[name] ?? 0; + }, + getContextAttributes: () => ({ alpha: true, antialias: true, depth: true, stencil: false, premultipliedAlpha: true, preserveDrawingBuffer: false, powerPreference: "default", failIfMajorPerformanceCaveat: false }), + getExtension: () => null, + getSupportedExtensions: () => [], + getShaderPrecisionFormat: () => ({ precision: 23, rangeMin: 127, rangeMax: 127 }), + getShaderParameter: () => true, + // No active uniforms or attributes: three uploads geometry and render targets regardless, and + // textures a test asks for with renderer.initTexture. + getProgramParameter: (_program, pname) => { + const name = names.get(pname as number); + return name === "ACTIVE_UNIFORMS" || name === "ACTIVE_ATTRIBUTES" ? 0 : true; + }, + getShaderInfoLog: () => "", + getProgramInfoLog: () => "", + getShaderSource: () => "", + checkFramebufferStatus: () => constant("FRAMEBUFFER_COMPLETE"), + isContextLost: () => false, + getError: () => 0, + getUniformLocation: () => null, + getAttribLocation: () => -1, + }; + for (const [method, kind] of Object.entries(CREATE)) { + methods[method] = () => { + const handle = { kind }; + handles.set(handle, kind); + created[kind] += 1; + return handle; + }; + } + for (const method of Object.keys(DELETE)) { + methods[method] = (handle) => { + if (typeof handle === "object" && handle !== null) handles.delete(handle); + }; + } + const noop = (): void => undefined; + const context = new Proxy({} as WebGL2RenderingContext, { + get(_target, property) { + if (typeof property !== "string") return undefined; + if (property === "canvas") return canvas; + if (property === "drawingBufferWidth") return canvas.width; + if (property === "drawingBufferHeight") return canvas.height; + const method = methods[property]; + if (method !== undefined) return method; + if (/^[A-Z][A-Z0-9_]*$/.test(property)) return constant(property); + return noop; + }, + set() { + return true; + }, + }); + return { + context, + created, + live: () => { + const counts = Object.fromEntries(KINDS.map((kind) => [kind, 0])) as Record; + for (const kind of handles.values()) counts[kind] += 1; + return counts; + }, + alive: (handle) => typeof handle === "object" && handle !== null && handles.has(handle), + }; +} + +/** Makes `canvas` hand out the fake context for WebGL 2, and the shared 2D test context otherwise. */ +export function attachFakeWebGl(canvas: HTMLCanvasElement): FakeWebGl { + const gl = fakeWebGl(canvas); + const other = HTMLCanvasElement.prototype.getContext; + Object.defineProperty(canvas, "getContext", { + configurable: true, + value: (type: string, ...rest: unknown[]) => (type === "webgl2" ? gl.context : Reflect.apply(other, canvas, [type, ...rest])), + }); + return gl; +} diff --git a/web/hands/src/types.ts b/web/hands/src/types.ts index 024ab76e..d08d4b1c 100644 --- a/web/hands/src/types.ts +++ b/web/hands/src/types.ts @@ -1,4 +1,4 @@ -export const PROTOCOL_VERSION = 2 as const; +export const PROTOCOL_VERSION = 3 as const; export const MAX_SERVER_FRAME_BYTES = 65_536; export type Hand = "left" | "right"; @@ -25,6 +25,7 @@ export interface PublicPlayer { readonly id: string; readonly name: string; read export interface TraumaSnapshot { readonly head: number; readonly body: number; readonly left_eye: number; readonly right_eye: number; readonly left_cut: number; readonly right_cut: number; readonly swelling: number; readonly bleeding: number } export interface FighterSnapshot { readonly player_id: string; readonly x: number; readonly y: number; readonly facing: number; + readonly facing_x: number; readonly facing_y: number; readonly velocity_x: number; readonly velocity_y: number; readonly stance: Stance; readonly defense: DefensivePose; readonly stamina: number; readonly maximum_stamina: number; readonly conditioning: number; readonly guard: number; readonly poise: number; readonly trauma: TraumaSnapshot; readonly knockdowns: number; readonly warnings: number; @@ -44,6 +45,7 @@ export interface FighterSnapshot { readonly get_up_prompt: "get_up_left" | "get_up_right" | null; readonly get_up_meter: number; readonly get_up_required: number; readonly get_up_count: number; readonly get_up_window_start_tick: number; readonly get_up_window_end_tick: number; + readonly last_input_sequence: number; } export interface CombatEvent { readonly event_id: number; readonly tick: number; readonly kind: string; readonly actor_id: string | null; readonly target_id: string | null; readonly amount: number; readonly detail: string; readonly blood: number; readonly direction: number; readonly action_id: string | null } export interface JudgeCard { readonly judge: string; readonly player_one: readonly number[]; readonly player_two: readonly number[] } @@ -56,22 +58,22 @@ export interface MatchResult { } export interface EngineSnapshot { readonly tick: number; readonly phase: MatchPhase; readonly round_number: number; readonly phase_ticks_remaining: number; readonly fighters: readonly [FighterSnapshot, FighterSnapshot]; readonly events: readonly CombatEvent[]; readonly result: MatchResult | null; readonly checksum: string } -interface WelcomeBase { readonly version: 2; readonly type: "welcome"; readonly player_id: string; readonly players: readonly PublicPlayer[]; readonly server_tick: number; readonly reconnect_ticket?: string } +interface WelcomeBase { readonly version: 3; readonly type: "welcome"; readonly player_id: string; readonly players: readonly PublicPlayer[]; readonly server_tick: number; readonly reconnect_ticket?: string } export interface FighterWelcomeMessage extends WelcomeBase { readonly role: "fighter"; readonly seat: 1 | 2; readonly rating: number; readonly next_sequence: number } export interface SpectatorWelcomeMessage extends WelcomeBase { readonly role: "spectator"; readonly players: readonly [PublicPlayer, PublicPlayer] } export type WelcomeMessage = FighterWelcomeMessage | SpectatorWelcomeMessage; -export interface TicketMessage { readonly version: 2; readonly type: "ticket"; readonly reconnect_ticket: string; readonly refresh_id: string } -export interface WaitingMessage { readonly version: 2; readonly type: "waiting"; readonly open_seats: 1 } -export interface ReadyMessage { readonly version: 2; readonly type: "ready"; readonly players: readonly [PublicPlayer, PublicPlayer] } -export interface PausedMessage { readonly version: 2; readonly type: "paused"; readonly player_id: string; readonly grace_ms: number } -export interface ResumedMessage { readonly version: 2; readonly type: "resumed"; readonly player_id: string } -export interface SnapshotMessage { readonly version: 2; readonly type: "snapshot"; readonly payload: EngineSnapshot } +export interface TicketMessage { readonly version: 3; readonly type: "ticket"; readonly reconnect_ticket: string; readonly refresh_id: string } +export interface WaitingMessage { readonly version: 3; readonly type: "waiting"; readonly open_seats: 1 } +export interface ReadyMessage { readonly version: 3; readonly type: "ready"; readonly players: readonly [PublicPlayer, PublicPlayer] } +export interface PausedMessage { readonly version: 3; readonly type: "paused"; readonly player_id: string; readonly grace_ms: number } +export interface ResumedMessage { readonly version: 3; readonly type: "resumed"; readonly player_id: string } +export interface SnapshotMessage { readonly version: 3; readonly type: "snapshot"; readonly payload: EngineSnapshot } export interface RatingDelta { readonly before: number; readonly after: number } -export interface FinalMessage { readonly version: 2; readonly type: "final"; readonly match_id: string; readonly winner_id: string | null; readonly method: FinishMethod; readonly round: number; readonly scorecards: readonly JudgeCard[]; readonly ratings: Readonly> } -export interface ErrorMessage { readonly version: 2; readonly type: "error"; readonly code: string } +export interface FinalMessage { readonly version: 3; readonly type: "final"; readonly match_id: string; readonly winner_id: string | null; readonly method: FinishMethod; readonly round: number; readonly scorecards: readonly JudgeCard[]; readonly ratings: Readonly> } +export interface ErrorMessage { readonly version: 3; readonly type: "error"; readonly code: string } export type ServerMessage = WelcomeMessage | TicketMessage | WaitingMessage | ReadyMessage | PausedMessage | ResumedMessage | SnapshotMessage | FinalMessage | ErrorMessage; export interface SimulationInfo { readonly tick_rate: number; readonly ring_half_width: number; readonly ring_half_height: number } -export interface BootstrapResponse { readonly client_id: string; readonly state: string; readonly protocol: 2; readonly simulation: SimulationInfo } +export interface BootstrapResponse { readonly client_id: string; readonly state: string; readonly protocol: 3; readonly simulation: SimulationInfo } export interface TokenPlayer { readonly id: string; readonly name: string; readonly avatar: string | null; readonly rating: number } export interface TokenResponse { readonly access_token: string; readonly ticket: string; readonly player: TokenPlayer }