{"version":3,"file":"CrumpledPaperReveal.ZO2BESY9.mjs","names":["useState","useRef","useLayoutEffect","useEffect"],"sources":["https:/framerusercontent.com/modules/KGCdRVoz6YBrYGFTzraT/0VQbXvSZ3yFdg4ftHQFG/CrumpledPaperReveal.js"],"sourcesContent":["// CrumpledPaper Reveal – a letter, note or print that lies on the page as a crumpled paper ball and\n// unfolds into a sheet that keeps every crease (hover, click, scroll into view or scroll-scrubbed).\n// Own cloth simulation, procedural crease memory, raking light that follows the cursor.\n// One component = one sheet. Place as many as you like: all sheets share one WebGL renderer.\n// Static renderer (canvas, thumbnails, export) and Reduced Motion: useIsStaticRenderer() selects\n// StillSheet, a plain image with a baked crease overlay – no WebGL, no animation, no loops or listeners.\n// File order: component and controls first, then the WebGL engine, then the embedded data.\n// Built by Matthias Ölschlegel – https://framer.link/fsd2pgh\nfunction _define_property(obj,key,value){if(key in obj){Object.defineProperty(obj,key,{value:value,enumerable:true,configurable:true,writable:true});}else{obj[key]=value;}return obj;}import{jsx as _jsx,jsxs as _jsxs}from\"react/jsx-runtime\";import{useEffect,useLayoutEffect,useRef,useState}from\"react\";import{addPropertyControls,ControlType,useIsStaticRenderer}from\"framer\";import{animate}from\"framer-motion\";const DEFAULT_IMAGE={\"src\":\"https://framerusercontent.com/images/VjDQete0166VVFAnQHuXgEXcbBw.jpg\",\"alt\":\"Handwritten letter on ivory paper\"};const DEFAULT_TRANSITION={type:\"tween\",duration:1.2,ease:[.3,0,.2,1]};const GLOSS={matte:.06,satin:.35,gloss:.8};const FOLDS={none:0,half:1,thirds:2};const IDLE_RAKE_ANGLE=2.35;const RATIOS={\"4:5\":.8,\"3:4\":.75,\"2:3\":2/3,\"1:1\":1,\"4:3\":4/3,\"3:2\":1.5};const useIsoLayoutEffect=typeof window!==\"undefined\"?useLayoutEffect:useEffect;function boxSides(value){if(typeof value===\"number\")return[value,value,value,value];if(typeof value!==\"string\"||!value.trim())return[0,0,0,0];const parts=value.trim().split(/\\s+/).map(x=>parseFloat(x)||0);if(parts.length===1)return[parts[0],parts[0],parts[0],parts[0]];if(parts.length===2)return[parts[0],parts[1],parts[0],parts[1]];if(parts.length===3)return[parts[0],parts[1],parts[2],parts[1]];return[parts[0],parts[1],parts[2],parts[3]];}function percent(v,fallback){if(typeof v!==\"string\")return fallback;const n=parseFloat(v);return Number.isFinite(n)?Math.min(1,Math.max(0,n/100)):fallback;}function hash01(i,s){const x=Math.sin(i*127.1+s*311.7)*43758.5453;return x-Math.floor(x);}function texBucket(neededPx){return neededPx<=512?512:neededPx<=1024?1024:neededPx<=2048?2048:4096;}function scaled(url,neededPx){if(!/^https:\\/\\/framerusercontent\\.com\\/images\\/[^?]+$/.test(url))return url;const size=neededPx<=512?512:neededPx<=1024?1024:2048;return url+\"?scale-down-to=\"+size;}function resolveImage(image,altProp,neededPx){let src=scaled(DEFAULT_IMAGE.src,neededPx);let alt=altProp||\"\";let focus=[.5,.5];if(typeof image===\"string\"&&image){src=scaled(image,neededPx);}else if(image&&typeof image===\"object\"&&image.src){src=scaled(image.src,neededPx);if(image.srcSet){const cands=image.srcSet.split(\",\").map(s=>s.trim().split(/\\s+/)).map(([url,w])=>({url,w:parseInt(w,10)||0})).filter(c=>c.url&&c.w>0).sort((a,b)=>a.w-b.w);const hit=cands.find(c=>c.w>=neededPx);if(hit)src=hit.url;}focus=[percent(image.positionX,.5),percent(image.positionY,.5)];if(!alt&&image.alt)alt=image.alt;}else if(!alt){alt=DEFAULT_IMAGE.alt;}return{src,alt,focus};}// Still sheet look: a crease overlay baked once at build time (STATIC_CREASES, neutral grey = no change,\n// soft-light blend) is stretched over the print; its opacity follows Creases and the letter folds are\n// two CSS gradient lines. Nothing is computed at runtime.\nfunction staticFolds(fold){if(fold!==1&&fold!==2)return\"\";const dark=\"rgba(0, 0, 0, 0.2)\";const light=\"rgba(255, 255, 255, 0.16)\";const clear=\"rgba(0, 0, 0, 0)\";const line=\"rgba(0, 0, 0, 0.85)\";if(fold===1)return`linear-gradient(180deg, ${dark} 0%, ${dark} calc(50% - 1.5px), ${line} 50%, ${light} calc(50% + 1.5px), ${light} 100%)`;return`linear-gradient(180deg, ${dark} 0%, ${dark} calc(33.333% - 1.5px), ${line} 33.333%, ${clear} calc(33.333% + 1.5px), ${clear} calc(66.667% - 1.5px), ${line} 66.667%, ${light} calc(66.667% + 1.5px), ${light} 100%)`;}// off in the static renderer: no media query listener there\nfunction usePrefersReducedMotion(enabled){const[reduced,setReduced]=useState(false);useEffect(()=>{if(!enabled||typeof window===\"undefined\"||!window.matchMedia)return;const mq=window.matchMedia(\"(prefers-reduced-motion: reduce)\");const update=()=>setReduced(mq.matches);update();mq.addEventListener?.(\"change\",update);return()=>mq.removeEventListener?.(\"change\",update);},[enabled]);return enabled&&reduced;}const CSS=`.crumple-reveal-sheet{position:absolute;inset:0;display:block;outline:none;-webkit-tap-highlight-color:transparent;-webkit-user-select:none;user-select:none}.crumple-reveal-sheet:focus-visible{outline:2px solid var(--crumple-focus,#0A84FF);outline-offset:4px}`;// size of the component box (layout measurement only)\nfunction useSheetSize(rootRef){const[size,setSize]=useState({w:0,h:0});useIsoLayoutEffect(()=>{const el=rootRef.current;if(!el)return;const measure=()=>{const w=el.offsetWidth;const h=el.offsetHeight;setSize(s=>s.w===w&&s.h===h?s:{w,h});};measure();if(typeof ResizeObserver===\"undefined\")return;const ro=new ResizeObserver(measure);ro.observe(el);return()=>ro.disconnect();},[]);return size;}function sheetShadow(shadow,H){const c=parseColor(shadow,[.1,.08,.05,.4]);const rgb=`${Math.round(c[0]*255)}, ${Math.round(c[1]*255)}, ${Math.round(c[2]*255)}`;return`0 1px 2px rgba(${rgb}, ${(c[3]*.55).toFixed(3)}), 0 ${Math.round(H*.012)+2}px ${Math.round(H*.05)+6}px rgba(${rgb}, ${(c[3]*.45).toFixed(3)})`;}// the flat sheet as plain markup: paper, print, baked crease overlay and fold lines (no script, no animation)\nfunction PaperFace({paper,radiusCss,shadowCss,sides,seed,src,focus,creaseAmt,foldN}){const fx=hash01(seed,12)<.5?1:-1;const fy=hash01(seed,13)<.5?1:-1;const folds=staticFolds(foldN);return /*#__PURE__*/_jsxs(\"div\",{\"aria-hidden\":\"true\",style:{position:\"absolute\",inset:0,background:paper,borderRadius:radiusCss,boxShadow:shadowCss,paddingTop:sides[0],paddingRight:sides[1],paddingBottom:sides[2],paddingLeft:sides[3],boxSizing:\"border-box\",overflow:\"hidden\",transform:`rotate(${(hash01(seed,5)-.5)*.03*180/Math.PI}deg)`},children:[/*#__PURE__*/_jsx(\"img\",{src:src,alt:\"\",draggable:false,style:{display:\"block\",width:\"100%\",height:\"100%\",objectFit:\"cover\",objectPosition:`${focus[0]*100}% ${focus[1]*100}%`,pointerEvents:\"none\"}}),creaseAmt>0&&/*#__PURE__*/_jsx(\"div\",{style:{position:\"absolute\",inset:0,backgroundImage:folds?`${folds}, url(${STATIC_CREASES})`:`url(${STATIC_CREASES})`,backgroundSize:\"100% 100%\",mixBlendMode:\"soft-light\",opacity:creaseAmt,transform:foldN?`scaleX(${fx})`:`scale(${fx}, ${fy})`,pointerEvents:\"none\"}})]});}/**\n * @framerIntrinsicWidth 300\n * @framerIntrinsicHeight 375\n * @framerSupportedLayoutWidth any-prefer-fixed\n * @framerSupportedLayoutHeight any-prefer-fixed\n * @framerDisableUnlink\n */export default function CrumpledPaperReveal(props){// Static renderer (Framer canvas, thumbnails, export) and Reduced Motion: the still sheet only –\n// no WebGL, no animation, no frame loop, no timers or listeners. Everything that moves is in LiveSheet.\nconst isStaticRenderer=useIsStaticRenderer();const reducedMotion=usePrefersReducedMotion(!isStaticRenderer);if(isStaticRenderer||reducedMotion)return /*#__PURE__*/_jsx(StillSheet,{...props});return /*#__PURE__*/_jsx(LiveSheet,{...props});}// ---------- still sheet (static renderer, reduced motion) ----------\nfunction StillSheet(props){const{image,alt,fold=\"thirds\",link,newTab=false,shape=1,ratio=\"4:5\",paper=\"#F4F0E7\",border=\"0px\",radius=\"0px\",creases=60,shadow=\"rgba(28, 22, 14, 0.42)\",focusColor=\"#0A84FF\",style}=props;const rootRef=useRef(null);const size=useSheetSize(rootRef);const autoHeight=!style||style.height===undefined||style.height===\"auto\";const aspect=RATIOS[ratio]||.8;const W=Math.max(1,size.w||300);const H=Math.max(1,autoHeight?W/aspect:size.h||W/aspect);const dpr=typeof window!==\"undefined\"?Math.min(2,window.devicePixelRatio||1):1;const resolved=resolveImage(image,alt,Math.round(Math.max(W,H)*dpr));const radiusCss=boxSides(radius).map(r=>r+\"px\").join(\" \");const href=typeof link===\"string\"?link.trim():\"\";const face=/*#__PURE__*/_jsx(PaperFace,{paper:paper,radiusCss:radiusCss,shadowCss:sheetShadow(shadow,H),sides:boxSides(border),seed:Math.max(0,Math.round(shape)-1),src:resolved.src,focus:resolved.focus,creaseAmt:Math.max(0,Math.min(100,creases))/100,foldN:FOLDS[fold]||0});const sheetStyle={cursor:href?\"pointer\":\"default\",borderRadius:radiusCss};return /*#__PURE__*/_jsxs(\"div\",{ref:rootRef,style:{position:\"relative\",width:300,...style,height:autoHeight?H:style?.height,[\"--crumple-focus\"]:focusColor},children:[/*#__PURE__*/_jsx(\"style\",{children:CSS}),href?/*#__PURE__*/_jsx(\"a\",{className:\"crumple-reveal-sheet\",style:sheetStyle,href:href,target:newTab?\"_blank\":undefined,rel:newTab?\"noopener noreferrer\":undefined,\"aria-label\":resolved.alt||undefined,children:face}):/*#__PURE__*/_jsx(\"div\",{className:\"crumple-reveal-sheet\",style:sheetStyle,role:\"img\",\"aria-label\":resolved.alt||undefined,children:face})]});}// ---------- live sheet (WebGL, only on the published site / preview) ----------\nfunction LiveSheet(props){const{image,alt:altProp,fold=\"thirds\",link,newTab=false,trigger=\"hover\",replay=true,startState=\"crumpled\",transition=DEFAULT_TRANSITION,shape=1,ratio=\"4:5\",paper=\"#F4F0E7\",border=\"0px\",radius=\"0px\",creases=60,finish=\"satin\",light=60,ballSize=140,shadow=\"rgba(28, 22, 14, 0.42)\",onUnfold,onCrumple,focusColor=\"#0A84FF\",style}=props;const autoHeight=!style||style.height===undefined||style.height===\"auto\";const rootRef=useRef(null);const size=useSheetSize(rootRef);const canvasRef=useRef(null);const rendererRef=useRef(null);const keyRef=useRef(\"\");const uploaded=useRef(\"\")// print (URL without size query) currently in this sheet's texture\n;if(!keyRef.current)keyRef.current=\"sheet\"+ ++sheetCounter;const[ready,setReady]=useState(false);const[failed,setFailed]=useState(false);const[isFlat,setIsFlat]=useState(()=>trigger===\"click\"&&startState===\"flat\");const[sceneTick,setSceneTick]=useState(0);const startP=trigger===\"click\"&&startState===\"flat\"?0:1;const anim=useRef({p:startP,target:startP,anim:null,rake:0,rakeAngle:IDLE_RAKE_ANGLE,lift:0});// visible: on screen (or about to be); nothing is rendered while false. waiting: print loaded, the first frame is\n// held back until the crease map for this size has been built step by step in the frame loop. revealed: first\n// frame drawn. dirty: something changed since the last frame. animating: the last frame moved something (the\n// next still frame draws the settled state once more).\nconst loop=useRef({raf:0,last:0,visible:typeof IntersectionObserver===\"undefined\",waiting:false,revealed:false,dirty:false,animating:false,px:0,py:0,near:false,hovered:false});const aspect=RATIOS[ratio]||.8;const W=Math.max(1,size.w||300);const H=Math.max(1,autoHeight?W/aspect:size.h||W/aspect);const margin=Math.round(Math.max(W,H)*.35);const dpr=typeof window!==\"undefined\"?Math.min(2,window.devicePixelRatio||1):1;const resolved=resolveImage(image,altProp,Math.round(Math.max(W,H)*dpr));const sides=boxSides(border);const radii=boxSides(radius);const lightAmt=Math.max(0,Math.min(100,light))/100;const creaseAmt=Math.max(0,Math.min(100,creases))/100;const foldN=FOLDS[fold]||0;const seed=Math.max(0,Math.round(shape)-1);const sceneOpts={width:W,height:H,margin,dpr,creases:creaseAmt,creaseAngle:48,lift:.004,ballSize:Math.max(60,Math.min(200,ballSize))/100,paper,gloss:GLOSS[finish]??.35,grain:1,rakeElev:.32,inset:sides,radii,shadow:shadow||\"rgba(0,0,0,0)\",shadowAmt:1.25,ao:1,show:.5,keyDir:[-.2635,.3387,.9033],fillDir:[.722,-.309,.619],seed:7};const latest=useRef({sceneOpts,resolved,lightAmt,trigger,foldN,seed,W,H});latest.current={sceneOpts,resolved,lightAmt,trigger,foldN,seed,W,H};const stateNow=()=>{const{resolved:res,foldN:fo,seed:sd,W:w,H:h}=latest.current;const a=anim.current;return{key:keyRef.current,x:0,y:0,w,h,progress:a.p,tiltAxis:hash01(sd,1)*Math.PI*2,tilt:(.3+.55*hash01(sd,2))*(hash01(sd,3)<.5?-1:1),spin:hash01(sd,4)*Math.PI*2,flatRot:(hash01(sd,5)-.5)*.03,offX:(hash01(sd,6)-.5)*.08,offY:(hash01(sd,7)-.5)*.06,curl:[hash01(sd,8),hash01(sd,9),hash01(sd,10),hash01(sd,11)].map(v=>v*v),rake:a.rake,rakeAngle:a.rakeAngle,focus:res.focus,flip:[hash01(sd,12)<.5?0:1,hash01(sd,13)<.5?0:1],hoverLift:a.lift,fold:fo,foldJitter:[hash01(sd,14)*2-1,hash01(sd,15)*2-1,hash01(sd,16)*2-1]};};const draw=()=>{const r=rendererRef.current;const c2=canvasRef.current;// offscreen sheets never render a WebGL frame; the visibility observer kicks the loop when they return\nif(!r||r.lost||!c2||!size.w||!loop.current.visible)return;try{const{pw,ph}=r.scene.render(latest.current.sceneOpts,[stateNow()]);if(c2.width!==pw||c2.height!==ph){c2.width=pw;c2.height=ph;}const ctx=c2.getContext(\"2d\");if(!ctx)return;ctx.clearRect(0,0,pw,ph);// the frame sits in the bottom-left corner of the shared canvas\nctx.drawImage(r.canvas,0,r.canvas.height-ph,pw,ph,0,0,pw,ph);}catch(e){setFailed(true);}};const drawRef=useRef(draw);drawRef.current=draw;const kick=()=>{const lp=loop.current;lp.dirty=true;if(lp.raf||typeof window===\"undefined\"||!lp.visible)return;lp.last=performance.now();const step=now=>{if(!lp.visible){lp.raf=0;return;}const dt=Math.min(.05,(now-lp.last)/1e3);lp.last=now;const{lightAmt:la,trigger:tr,W:w,H:h}=latest.current;const a=anim.current;const k=1-Math.exp(-dt*7);let busy=false;// the light follows the cursor while it is on or near the sheet\nlet targetAngle=IDLE_RAKE_ANGLE;let targetAmt=la*.45;if(lp.near){const dx=lp.px-w/2;const dy=lp.py-h/2;targetAngle=Math.atan2(-dy,dx);const dist=Math.hypot(dx,dy)/Math.hypot(w,h);targetAmt=la*(.45+.55*Math.max(0,1-dist));}let da=targetAngle-a.rakeAngle;da=Math.atan2(Math.sin(da),Math.cos(da));a.rakeAngle+=da*k;a.rake+=(targetAmt-a.rake)*k;if(Math.abs(da)>.002||Math.abs(targetAmt-a.rake)>.002)busy=true;// an interactive sheet lifts a little while the pointer rests on it\nconst liftTarget=lp.hovered&&(tr===\"hover\"||tr===\"click\")?1:0;a.lift+=(liftTarget-a.lift)*(1-Math.exp(-dt*6));if(Math.abs(liftTarget-a.lift)>.002)busy=true;else a.lift=liftTarget;if(a.anim)busy=true;if(tr===\"scroll\"){const d=a.target-a.p;a.p+=d*(1-Math.exp(-dt*9));if(Math.abs(d)>5e-4)busy=true;else a.p=a.target;}// crease map for this sheet size: built in slices (all sheets share ~8 ms of it per frame)\nconst sc=rendererRef.current?.scene;let mapPending=false;if(sc&&(lp.waiting||lp.revealed)){const o=latest.current.sceneOpts;if(!sc.creaseReady(w,h,o.dpr,o.seed)){sc.pumpCrease(8,now);if(sc.creaseReady(w,h,o.dpr,o.seed))lp.dirty=true;else mapPending=true;}}const fading=!!sc&&sc.fading(keyRef.current);if(lp.waiting){// first appearance once the map is complete: nothing is drawn before that\nif(firstDraws.frame!==now){firstDraws.frame=now;firstDraws.spent=0;}if(sc&&!mapPending&&firstDraws.spent<12){const t0=performance.now();lp.waiting=false;lp.revealed=true;drawRef.current();setReady(true);firstDraws.spent+=performance.now()-t0;}}else if(lp.revealed&&(busy||fading||lp.animating||lp.dirty)){drawRef.current();}lp.dirty=false;lp.animating=busy||fading;if((lp.animating||mapPending||lp.waiting&&!!sc)&&lp.visible)lp.raf=requestAnimationFrame(step);else lp.raf=0;};lp.raf=requestAnimationFrame(step);};const kickRef=useRef(kick);kickRef.current=kick;// ---------- renderer ----------\nuseEffect(()=>{let cancelled=false;let held=null;const onLost=()=>setFailed(true);acquireRenderer().then(r=>{if(cancelled){releaseRenderer(r);return;}held=r;rendererRef.current=r;r.listeners.add(onLost);anim.current.rake=latest.current.lightAmt*.45;setSceneTick(t=>t+1);}).catch(()=>!cancelled&&setFailed(true));return()=>{cancelled=true;const lp=loop.current;if(lp.raf)cancelAnimationFrame(lp.raf);lp.raf=0;anim.current.anim?.stop();if(held){held.listeners.delete(onLost);if(!held.lost)held.scene.removeItem(keyRef.current);releaseRenderer(held);}rendererRef.current=null;lp.waiting=false;lp.revealed=false;uploaded.current=\"\";setReady(false);};},[]);// ---------- image ----------\n// The print is uploaded at most at the size the sheet can show (512 / 1024 / 2048 / 4096 px, like the\n// scaled Framer image URLs): bigger files are scaled down first, so a huge photo neither blocks the\n// upload nor fills GPU memory, and nothing exceeds the device's texture limit.\nconst texCap=texBucket(Math.round(Math.max(W,H)*dpr));useEffect(()=>{if(failed||!sceneTick)return;if(!rendererRef.current)return;let cancelled=false;let shown=false;const src=resolved.src;const img=new Image;img.crossOrigin=\"anonymous\";img.decoding=\"async\";img.src=src;const show=()=>{if(cancelled||shown)return;shown=true;// first time: the frame loop builds the crease map in short slices and reveals the sheet once it is\n// complete; later (a new print, a resize) one more frame is enough\nif(!loop.current.revealed)loop.current.waiting=true;kickRef.current();};const upload=source=>{if(cancelled||!rendererRef.current)return;// same print at another resolution (resize): swap it without fading it in again\nconst same=uploaded.current===src.split(\"?\")[0];try{rendererRef.current.scene.setImage(keyRef.current,source,!same);uploaded.current=src.split(\"?\")[0];}catch(e){setFailed(true);}shown=false;show();};const apply=()=>{if(cancelled||!rendererRef.current)return;const iw=img.naturalWidth||1;const ih=img.naturalHeight||1;const limit=rendererRef.current.scene.maxTexture;const k=Math.min(texCap,limit)/Math.max(iw,ih);if(k>=.8&&Math.max(iw,ih)<=limit)return upload(img);const tw=Math.max(1,Math.round(iw*k));const th=Math.max(1,Math.round(ih*k));const viaCanvas=()=>{if(cancelled)return;const c=document.createElement(\"canvas\");c.width=tw;c.height=th;const x=c.getContext(\"2d\");if(!x)return upload(img);x.imageSmoothingQuality=\"high\";x.drawImage(img,0,0,tw,th);upload(c);};if(typeof createImageBitmap!==\"function\")return viaCanvas();const opts={resizeWidth:tw,resizeHeight:th,resizeQuality:\"high\",premultiplyAlpha:\"none\"};// browsers without the resize option return the full size: that one is scaled on a canvas\nconst fits=bmp=>{const ok=bmp.width<=tw+1;if(ok)upload(bmp);bmp.close();if(!ok)throw new Error(\"resize unsupported\");};// decode and scale the file off the main thread (Blob source); the decoded element is the fallback\nfetch(src).then(r=>r.ok?r.blob():Promise.reject(new Error(\"fetch\"))).then(b=>cancelled?undefined:createImageBitmap(b,opts).then(fits)).catch(()=>cancelled?undefined:createImageBitmap(img,opts).then(fits)).catch(viaCanvas);};if(img.decode)img.decode().then(apply,()=>cancelled?null:show());else img.onload=apply;const t=window.setTimeout(show,1200);return()=>{cancelled=true;window.clearTimeout(t);};},[resolved.src,texCap,failed,sceneTick]);// prop / size changes: one frame through the loop (skipped while offscreen)\nuseEffect(()=>{kickRef.current();});// ---------- progress ----------\nconst go=(target,delay=0)=>{const a=anim.current;if(a.target===target&&(a.anim||a.p===target))return;a.target=target;a.anim?.stop();a.anim=null;if(target===0)onUnfold?.();else onCrumple?.();setIsFlat(target===0);const tr=transition&&typeof transition===\"object\"?transition:DEFAULT_TRANSITION;a.anim=animate(a.p,target,{...tr,delay:(tr.delay||0)+delay,onUpdate:v=>{a.p=Math.min(1,Math.max(0,v));},onComplete:()=>{a.p=target;a.anim=null;kickRef.current();}});kickRef.current();};const snap=target=>{const a=anim.current;a.anim?.stop();a.anim=null;a.target=target;a.p=target;setIsFlat(target===0);};const goRef=useRef(go);const snapRef=useRef(snap);goRef.current=go;snapRef.current=snap;// trigger / start changes (also live in the editor preview)\nuseEffect(()=>{if(trigger===\"click\")snapRef.current(startState===\"flat\"?0:1);else if(trigger===\"hover\")snapRef.current(1);kickRef.current();},[trigger,startState]);// visibility: WebGL frames only while the sheet is on screen (200 px head start so it is ready when it arrives)\nconst scrollSync=useRef(null);useEffect(()=>{const el=rootRef.current;const lp=loop.current;if(!el||typeof IntersectionObserver===\"undefined\"){lp.visible=true;kickRef.current();return;}const io=new IntersectionObserver(entries=>{const e=entries[entries.length-1];const was=lp.visible;lp.visible=e.isIntersecting;if(lp.visible&&!was){scrollSync.current?.();kickRef.current();}else if(!lp.visible&&lp.raf){cancelAnimationFrame(lp.raf);lp.raf=0;}},{rootMargin:\"200px 0px 200px 0px\"});io.observe(el);return()=>{io.disconnect();lp.visible=false;};},[]);// in view trigger\nuseEffect(()=>{if(trigger!==\"inView\")return;const el=rootRef.current;if(!el||typeof IntersectionObserver===\"undefined\")return;let timer=0;const io=new IntersectionObserver(entries=>{for(const e of entries){const vh=window.innerHeight||1;const enough=e.intersectionRatio>=.35||e.intersectionRect.height>=vh*.45;if(enough){window.clearTimeout(timer);timer=window.setTimeout(()=>goRef.current(0),120);}else if(!e.isIntersecting&&replay){window.clearTimeout(timer);snapRef.current(1);}}},{threshold:[0,.2,.35,.6]});io.observe(el);return()=>{window.clearTimeout(timer);io.disconnect();};},[trigger,replay]);// scroll scrub: flat in the middle of the viewport, crumpled towards the edges\nuseEffect(()=>{if(trigger!==\"scroll\")return;const el=rootRef.current;if(!el)return;const measure=()=>{const r=el.getBoundingClientRect();const vh=window.innerHeight||1;const cy=(r.top+r.height/2)/vh;const d=Math.abs(cy-.5)*2;let t=(d-.2)/.7;t=t<0?0:t>1?1:t;anim.current.target=t*t*(3-2*t);};// offscreen: no layout read, no frame; on the way back in the sheet jumps to the state of its position\nconst update=()=>{if(!loop.current.visible)return;measure();kickRef.current();};scrollSync.current=()=>{measure();anim.current.p=anim.current.target;};measure();anim.current.p=anim.current.target;window.addEventListener(\"scroll\",update,{passive:true});window.addEventListener(\"resize\",update);return()=>{scrollSync.current=null;window.removeEventListener(\"scroll\",update);window.removeEventListener(\"resize\",update);};},[trigger]);// cursor light: follows a mouse pointer on or near the sheet (ignored while the sheet is offscreen)\nuseEffect(()=>{if(typeof window===\"undefined\")return;const onMove=e=>{if(e.pointerType===\"touch\")return;const lp=loop.current;if(!lp.visible){lp.near=false;return;}const el=rootRef.current;if(!el)return;const r=el.getBoundingClientRect();const px=e.clientX-r.left;const py=e.clientY-r.top;const reach=Math.max(r.width,r.height)*.6;const near=px>-reach&&py>-reach&&px<r.width+reach&&py<r.height+reach;if(!near&&!lp.near)return;lp.near=near;lp.px=px;lp.py=py;kickRef.current();};window.addEventListener(\"pointermove\",onMove,{passive:true});return()=>window.removeEventListener(\"pointermove\",onMove);},[]);// a sheet opened by a tap closes when another one opens\nconst selfClose=useRef(()=>{});useEffect(()=>{const close=()=>{if(anim.current.target===0)goRef.current(1);};selfClose.current=close;tapOpen.add(close);return()=>{tapOpen.delete(close);};},[]);// ---------- pointer ----------\nconst lastPointer=useRef(\"mouse\");const href=typeof link===\"string\"?link.trim():\"\";const hasLink=href.length>0;const handlers={onPointerDown:e=>{lastPointer.current=e.pointerType;},onPointerEnter:e=>{if(e.pointerType===\"touch\")return;loop.current.hovered=true;if(trigger===\"hover\")goRef.current(0);kickRef.current();},onPointerLeave:e=>{if(e.pointerType===\"touch\")return;loop.current.hovered=false;const focused=typeof document!==\"undefined\"&&document.activeElement===e.currentTarget&&e.currentTarget.matches(\":focus-visible\");if(trigger===\"hover\"&&!focused)goRef.current(1);kickRef.current();},onFocus:e=>{// keyboard focus only: a tap or click also focuses the sheet and is handled by onClick\nlet keyboard=true;try{keyboard=e.currentTarget.matches(\":focus-visible\");}catch(err){keyboard=lastPointer.current!==\"touch\";}if(trigger===\"hover\"&&keyboard)goRef.current(0);},onBlur:()=>{if(trigger===\"hover\"&&!loop.current.hovered)goRef.current(1);},onClick:e=>{const crumpled=anim.current.target===1;const touchHover=trigger===\"hover\"&&lastPointer.current===\"touch\";if(trigger===\"click\"||touchHover){if(hasLink&&!crumpled)return;// flat + link: follow the link\ne.preventDefault();if(touchHover&&crumpled)tapOpen.forEach(f=>f!==selfClose.current&&f());goRef.current(crumpled?0:1);}},onKeyDown:e=>{if(trigger!==\"click\"||hasLink)return;if(e.key===\"Enter\"||e.key===\" \"){e.preventDefault();goRef.current(anim.current.target===1?0:1);}}};// ---------- markup ----------\nconst radiusCss=radii.map(r=>r+\"px\").join(\" \");const isToggle=trigger===\"click\";// no WebGL (or the context was lost): the still sheet's look\nconst content=failed?/*#__PURE__*/_jsx(PaperFace,{paper:paper,radiusCss:radiusCss,shadowCss:sheetShadow(shadow,H),sides:sides,seed:seed,src:resolved.src,focus:resolved.focus,creaseAmt:creaseAmt,foldN:foldN}):null;const sheetProps={className:\"crumple-reveal-sheet\",style:{cursor:hasLink||isToggle?\"pointer\":\"default\",borderRadius:radiusCss},...handlers};return /*#__PURE__*/_jsxs(\"div\",{ref:rootRef,style:{position:\"relative\",width:300,...style,height:autoHeight?H:style?.height,[\"--crumple-focus\"]:focusColor},children:[/*#__PURE__*/_jsx(\"style\",{children:CSS}),/*#__PURE__*/_jsx(\"canvas\",{ref:canvasRef,\"aria-hidden\":\"true\",style:{position:\"absolute\",left:-margin,top:-margin,width:W+margin*2,height:H+margin*2,pointerEvents:\"none\",opacity:ready&&!failed?1:0,transition:\"opacity 0.35s ease\",display:failed?\"none\":\"block\"}}),hasLink?/*#__PURE__*/_jsx(\"a\",{...sheetProps,href:href,target:newTab?\"_blank\":undefined,rel:newTab?\"noopener noreferrer\":undefined,\"aria-label\":resolved.alt||undefined,children:content}):isToggle?/*#__PURE__*/_jsx(\"div\",{...sheetProps,role:\"button\",tabIndex:0,\"aria-label\":(isFlat?\"Crumple\":\"Unfold\")+(resolved.alt?\": \"+resolved.alt:\" image\"),children:content}):/*#__PURE__*/_jsx(\"div\",{...sheetProps,role:\"img\",\"aria-label\":resolved.alt||undefined,tabIndex:trigger===\"hover\"?0:undefined,children:content})]});}CrumpledPaperReveal.displayName=\"CrumpledPaper Reveal\";addPropertyControls(CrumpledPaperReveal,{image:{type:ControlType.ResponsiveImage,title:\"Image\"},alt:{type:ControlType.String,title:\"Alt Text\",defaultValue:\"\",placeholder:\"Describe the image\"},fold:{type:ControlType.Enum,title:\"Fold\",options:[\"none\",\"half\",\"thirds\"],optionTitles:[\"None\",\"Half\",\"Thirds\"],defaultValue:\"thirds\",displaySegmentedControl:true,description:\"Letter folds made before the crumple.\"},link:{type:ControlType.Link,title:\"Link\",defaultValue:\"\"},newTab:{type:ControlType.Boolean,title:\"New Tab\",defaultValue:false,hidden:p=>!p.link},trigger:{type:ControlType.Enum,title:\"Trigger\",options:[\"hover\",\"click\",\"inView\",\"scroll\"],optionTitles:[\"Hover\",\"Click\",\"In View\",\"Scroll\"],defaultValue:\"hover\",description:\"Hover unfolds the paper under the pointer (tap on touch). Scroll ties the fold to the scroll position.\"},replay:{type:ControlType.Boolean,title:\"Replay\",defaultValue:true,description:\"Crumples again when it leaves the viewport.\",hidden:p=>p.trigger!==\"inView\"},startState:{type:ControlType.Enum,title:\"Start\",options:[\"crumpled\",\"flat\"],optionTitles:[\"Crumpled\",\"Flat\"],defaultValue:\"crumpled\",displaySegmentedControl:true,hidden:p=>p.trigger!==\"click\"},transition:{type:ControlType.Transition,title:\"Transition\",defaultValue:DEFAULT_TRANSITION},shape:{type:ControlType.Number,title:\"Shape\",min:1,max:12,step:1,displayStepper:true,defaultValue:1,description:\"Each number crumples the ball differently – give neighbours different shapes.\"},ratio:{type:ControlType.Enum,title:\"Ratio\",options:[\"4:5\",\"3:4\",\"2:3\",\"1:1\",\"4:3\",\"3:2\"],defaultValue:\"4:5\",description:\"Used when the height is set to Fit.\"},paper:{type:ControlType.Color,title:\"Paper\",defaultValue:\"#F4F0E7\",description:\"Back of the sheet and the border.\"},border:{type:ControlType.Padding,title:\"Border\",defaultValue:\"0px\",description:\"Paper margin around the image.\"},radius:{type:ControlType.BorderRadius,title:\"Radius\",defaultValue:\"0px\"},creases:{type:ControlType.Number,title:\"Creases\",min:0,max:100,step:1,unit:\"%\",defaultValue:60,description:\"How much the unfolded paper remembers the crumple.\"},finish:{type:ControlType.Enum,title:\"Finish\",options:[\"matte\",\"satin\",\"gloss\"],optionTitles:[\"Matte\",\"Satin\",\"Gloss\"],defaultValue:\"satin\",displaySegmentedControl:true},light:{type:ControlType.Number,title:\"Cursor Light\",min:0,max:100,step:1,unit:\"%\",defaultValue:60},ballSize:{type:ControlType.Number,title:\"Ball Size\",min:60,max:200,step:1,unit:\"%\",defaultValue:140},shadow:{type:ControlType.Color,title:\"Shadow\",defaultValue:\"rgba(28, 22, 14, 0.42)\"},onUnfold:{type:ControlType.EventHandler,title:\"On Unfold\"},onCrumple:{type:ControlType.EventHandler,title:\"On Crumple\"},focusColor:{type:ControlType.Color,title:\"Focus Ring\",defaultValue:\"#0A84FF\",description:\"Built by Matthias \\xd6lschlegel 💪  \\n[Explore more components](https://framer.link/fsd2pgh)\"}});// ---------- WebGL engine: only LiveSheet uses anything below ----------\nlet dataPromise=null;function loadCrumpleData(){if(!dataPromise){dataPromise=decodeCrumple(CRUMPLE_DATA);dataPromise.catch(()=>{dataPromise=null;});}return dataPromise;}let shared=null;let creating=null;// start-up in separate short tasks: decode the fold data, then compile the shaders (in the background\n// where the browser supports it), then build the buffers\nconst nextTask=()=>new Promise(r=>setTimeout(r,0));function createRenderer(){if(!creating){creating=(async()=>{const data=await loadCrumpleData();await nextTask();const canvas=document.createElement(\"canvas\");const scene=await prepareScene(canvas,data);const r={scene,canvas,users:0,lost:false,listeners:new Set};canvas.addEventListener(\"webglcontextlost\",e=>{e.preventDefault();r.lost=true;r.listeners.forEach(f=>f());});shared=r;return r;})();const clear=()=>{creating=null;};creating.then(clear,clear);}return creating;}async function acquireRenderer(){const r=shared&&!shared.lost?shared:await createRenderer();r.users++;return r;}function releaseRenderer(r){r.users--;if(r.users>0)return;// Framer remounts components often (breakpoints, preview): keep the context a moment\nwindow.setTimeout(()=>{if(r.users<=0&&shared===r){r.scene.dispose();shared=null;}},4e3);}let sheetCounter=0;// first frames of many sheets that become ready together are spread over a few frames (~12 ms each)\nconst firstDraws={frame:-1,spent:0};// sheets opened by a tap (hover trigger on touch screens) close again when another one opens\nconst tapOpen=new Set;async function inflateRaw(bytes){const DS=globalThis.DecompressionStream;if(!DS)throw new Error(\"DecompressionStream unavailable\");const stream=new Blob([bytes]).stream().pipeThrough(new DS(\"deflate-raw\"));return new Uint8Array(await new Response(stream).arrayBuffer());}function b64ToBytes(b64){const bin=atob(b64);const out=new Uint8Array(bin.length);for(let i=0;i<bin.length;i++)out[i]=bin.charCodeAt(i);return out;}async function decodeCrumple(b64){const buf=await inflateRaw(b64ToBytes(b64));const dv=new DataView(buf.buffer,buf.byteOffset,buf.byteLength);const magic=String.fromCharCode(buf[0],buf[1],buf[2],buf[3]);if(magic!==\"CRP1\")throw new Error(\"Unknown crumple data\");let o=4;const N=dv.getUint16(o,true);const F=dv.getUint16(o+2,true);const K=dv.getUint16(o+4,true);const qbits=dv.getUint16(o+6,true);const midStep=dv.getUint16(o+8,true);o+=16// counts (10) + relief scale (4) + flags (2)\n;const restQ=new Uint16Array(N*2);for(let i=0;i<N*2;i++,o+=2)restQ[i]=dv.getUint16(o,true);const faceLen=dv.getUint32(o,true);o+=4;let p=o;const readVar=()=>{let v=0;let s=1;let b=0;do{b=buf[p++];v+=(b&127)*s;s*=128;}while(b&128)return v;};const faces=new Uint16Array(F*3);let a=0;for(let f=0;f<F;f++){a+=readVar();faces[f*3]=a;faces[f*3+1]=a+readVar();faces[f*3+2]=a+readVar();}o+=faceLen;const relief=new Float32Array(N);for(let i=0;i<N;i++,o+=2)relief[i]=dv.getInt16(o,true)/32767;// unique edges (sorted) -> sharp bitmask length and \"previous neighbour\" lists\nconst keysE=[];for(let f=0;f<F;f++){for(let c=0;c<3;c++){const u=faces[f*3+c];const v=faces[f*3+(c+1)%3];keysE.push(u<v?u*65536+v:v*65536+u);}}keysE.sort((x,y)=>x-y);const edges=[];for(let i=0;i<keysE.length;i++)if(i===0||keysE[i]!==keysE[i-1])edges.push(keysE[i]);o+=Math.ceil(edges.length/8);const prevStart=new Int32Array(N+1);for(const e of edges)prevStart[e%65536+1]++;for(let i=0;i<N;i++)prevStart[i+1]+=prevStart[i];const prevList=new Int32Array(prevStart[N]);const fillP=prevStart.slice(0,N);for(const e of edges)prevList[fillP[e%65536]++]=Math.floor(e/65536);// keyframes: closed-loop DPCM with neighbour prediction\np=o;const zig=()=>{const v=readVar();return v%2===0?v/2:-(v+1)/2;};const Q=Math.pow(2,qbits);const dec=new Int32Array(K*N*3);for(let v=0;v<N;v++){dec[v*3]=Math.floor((restQ[v*2]*Q+32767)/65535)-Q/2;dec[v*3+1]=Math.floor((restQ[v*2+1]*Q+32767)/65535)-Q/2;}const rq=new Int32Array(N*3);const rdec=new Int32Array(N*3);for(let k=1;k<K;k++){const step=k<=2||k>=K-3?1:midStep;for(let c=0;c<3;c++)for(let v=0;v<N;v++)rq[v*3+c]=zig();for(let v=0;v<N;v++){const s0=prevStart[v];const s1=prevStart[v+1];const n=s1-s0;for(let c=0;c<3;c++){let pred=0;if(n>0){let s=0;for(let j=s0;j<s1;j++)s+=rdec[prevList[j]*3+c];pred=Math.floor((2*s+n)/(2*n));}rdec[v*3+c]=pred+rq[v*3+c]*step;}}const cur=k*N*3;const prev=(k-1)*N*3;const prev2=(k-2)*N*3;for(let i=0;i<N*3;i++){const base=k<2?dec[prev+i]:2*dec[prev+i]-dec[prev2+i];dec[cur+i]=base+rdec[i];}}const keys=new Float32Array(K*N*3);for(let i=0;i<keys.length;i++)keys[i]=dec[i]/Q;const rest=new Float32Array(N*2);for(let i=0;i<N*2;i++)rest[i]=restQ[i]/65535;// per keyframe: compactness (0 flat .. 1 ball) and bounding box centre\nconst ext=new Float32Array(K);const center=new Float32Array(K*2);for(let k=0;k<K;k++){let x0=1e9;let x1=-1e9;let y0=1e9;let y1=-1e9;for(let v=0;v<N;v++){const x=keys[(k*N+v)*3];const y=keys[(k*N+v)*3+1];if(x<x0)x0=x;if(x>x1)x1=x;if(y<y0)y0=y;if(y>y1)y1=y;}ext[k]=Math.max(x1-x0,y1-y0);center[k*2]=(x0+x1)/2;center[k*2+1]=(y0+y1)/2;}let eMin=ext[0];for(let k=0;k<K;k++)eMin=Math.min(eMin,ext[k]);const crumple=new Float32Array(K);for(let k=0;k<K;k++)crumple[k]=Math.min(1,Math.max(0,(ext[0]-ext[k])/(ext[0]-eMin)));return{N,F,K,rest,faces,relief,keys,crumple,center};}// ---------------------------------------------------------------------------------------------\n// Procedural crease map: slope field of a sheet that was crumpled and smoothed out again.\n// Every crease is a straight fold; the paper keeps a small tilt on both sides (facets).\n// RGBA8: r,g = slope x/y (0.5 = flat), a = fine ink crack along sharp folds.\nfunction mulberry32(seed){let a=seed|0;return()=>{a=a+1831565813|0;let t=Math.imul(a^a>>>15,1|a);t=t+Math.imul(t^t>>>7,61|t)^t;return((t^t>>>14)>>>0)/4294967296;};}// Bowyer-Watson Delaunay triangulation. Triangles are bucketed on a grid by their circumcircle,\n// so each insertion only tests the triangles whose circle can contain the new point.\n// A generator: it pauses every 64 insertions so the caller can spread it over frames.\nfunction*delaunay(xs,ys){const n=xs.length;let minX=Infinity,minY=Infinity,maxX=-Infinity,maxY=-Infinity;for(let i=0;i<n;i++){if(xs[i]<minX)minX=xs[i];if(ys[i]<minY)minY=ys[i];if(xs[i]>maxX)maxX=xs[i];if(ys[i]>maxY)maxY=ys[i];}const span=Math.max(maxX-minX,maxY-minY,1e-6);const d=span*20;const X=xs.concat([minX-d,minX+d*2,minX-d]);const Y=ys.concat([minY-d,minY-d,minY+d*2]);const TA=[],TB=[],TC=[];const TX=[],TY=[],TR=[];const alive=[];const G=Math.max(1,Math.round(Math.sqrt(n)/1.6));const cw=(maxX-minX)/G||1;const ch=(maxY-minY)/G||1;const cells=[];for(let i=0;i<G*G;i++)cells.push([]);const addTri=(a,b,c)=>{const ax=X[a],ay=Y[a],bx=X[b],by=Y[b],cx=X[c],cy=Y[c];const dd=2*(ax*(by-cy)+bx*(cy-ay)+cx*(ay-by))||1e-12;const ux=((ax*ax+ay*ay)*(by-cy)+(bx*bx+by*by)*(cy-ay)+(cx*cx+cy*cy)*(ay-by))/dd;const uy=((ax*ax+ay*ay)*(cx-bx)+(bx*bx+by*by)*(ax-cx)+(cx*cx+cy*cy)*(bx-ax))/dd;const r2=(ax-ux)*(ax-ux)+(ay-uy)*(ay-uy);const id=TA.length;TA.push(a);TB.push(b);TC.push(c);TX.push(ux);TY.push(uy);TR.push(r2);alive.push(1);const r=Math.sqrt(r2);const gx0=Math.max(0,Math.floor((ux-r-minX)/cw));const gx1=Math.min(G-1,Math.floor((ux+r-minX)/cw));const gy0=Math.max(0,Math.floor((uy-r-minY)/ch));const gy1=Math.min(G-1,Math.floor((uy+r-minY)/ch));for(let gy=gy0;gy<=gy1;gy++)for(let gx=gx0;gx<=gx1;gx++)cells[gy*G+gx].push(id);};addTri(n,n+1,n+2);const bad=[];const eu=[],ev=[];for(let i=0;i<n;i++){if(i%64===63)yield;const px=X[i],py=Y[i];const gx=Math.min(G-1,Math.max(0,Math.floor((px-minX)/cw)));const gy=Math.min(G-1,Math.max(0,Math.floor((py-minY)/ch)));const cell=cells[gy*G+gx];bad.length=0;let k=0;for(let j=0;j<cell.length;j++){const id=cell[j];if(!alive[id])continue;cell[k++]=id;const dx=px-TX[id],dy=py-TY[id];if(dx*dx+dy*dy<=TR[id])bad.push(id);}cell.length=k;eu.length=0;ev.length=0;for(const id of bad){alive[id]=0;const a=TA[id],b=TB[id],c=TC[id];eu.push(a,b,c);ev.push(b,c,a);}// boundary of the cavity: edges that are not shared by two bad triangles\nconst m=eu.length;for(let e=0;e<m;e++){const u=eu[e],v=ev[e];let shared=false;for(let f=0;f<m;f++){if(f!==e&&eu[f]===v&&ev[f]===u){shared=true;break;}}if(!shared)addTri(u,v,i);}}const out=[];for(let id=0;id<TA.length;id++){if(!alive[id])continue;const a=TA[id],b=TB[id],c=TC[id];if(a<n&&b<n&&c<n)out.push(a,b,c);}return out;}// Crease map: the slope field of a sheet that was crumpled and smoothed out again.\n// Four layers of random triangular facets (long folds .. fine crinkle). Every shared facet edge\n// is a straight fold; fine crinkle gathers in a few areas like in real paper.\n// RGBA8: r,g = slope x/y (0.5 = level, 0/1 = -0.5/+0.5), b = fold line (0.5 = none, above =\n// ridge, below = valley), a = ink crack along the sharpest ridges.\n// The map is built in small steps (a generator): every loop pauses after about STEP pixels of work,\n// so a caller with a time budget per frame never blocks the main thread for long.\nconst STEP=6e3;function*creaseMapJob(w,h,seed){const n=w*h;let work=0;const GX=new Float32Array(n);const GY=new Float32Array(n);const FL=new Float32Array(n);const CR=new Float32Array(n);const rnd=mulberry32(seed);const S=Math.max(w,h);const px=S/640// line widths are tuned for a ~640px map\n;// crinkle density: a few soft blobs over a calm base, normalised to a mean of 1\nconst blobs=[];for(let i=0;i<6;i++)blobs.push([rnd()*w,rnd()*h,(.12+.2*rnd())*S,.7+1.5*rnd()]);const densRaw=(x,y)=>{let d=.4;for(const b of blobs){const dx=x-b[0];const dy=y-b[1];d+=b[3]*Math.exp(-(dx*dx+dy*dy)/(b[2]*b[2]));}return d;};let mean=0;for(let i=0;i<400;i++)mean+=densRaw(rnd()*w,rnd()*h);mean/=400;const dens=(x,y)=>densRaw(Math.min(w,Math.max(0,x)),Math.min(h,Math.max(0,y)))/mean;let dMax=1;for(let i=0;i<400;i++)dMax=Math.max(dMax,dens(rnd()*w,rnd()*h));dMax*=1.25;const layer=function*(count,amp,clustered,lineW,lineAmt,crackAmt){const pad=S*.12;const X0=-pad;const Y0=-pad;const W2=w+2*pad;const H2=h+2*pad;const spacing=Math.sqrt(W2*H2/count);const dAt=(x,y)=>clustered?dens(x,y):1;// blue-noise points (dart throwing), denser where the paper crinkled more\nconst rf=.6*spacing;const cell=rf/Math.sqrt(clustered?dMax:1);const gw=Math.ceil(W2/cell)+1;const gh=Math.ceil(H2/cell)+1;const grid=new Array(gw*gh);const xs=[];const ys=[];let tries=0;while(xs.length<count&&tries<count*40){tries++;if(tries%512===0)yield;const x=X0+rnd()*W2;const y=Y0+rnd()*H2;const d=dAt(x,y);if(clustered&&rnd()*dMax>d)continue;const r=rf/Math.sqrt(d);const gx=Math.floor((x-X0)/cell);const gy=Math.floor((y-Y0)/cell);const R=Math.ceil(r/cell);let ok=true;for(let yy=Math.max(0,gy-R);ok&&yy<=Math.min(gh-1,gy+R);yy++){for(let xx=Math.max(0,gx-R);xx<=Math.min(gw-1,gx+R);xx++){const c=grid[yy*gw+xx];if(!c)continue;for(const j of c){const dx=xs[j]-x;const dy=ys[j]-y;if(dx*dx+dy*dy<r*r){ok=false;break;}}if(!ok)break;}}if(!ok)continue;const gi=gy*gw+gx;(grid[gi]||(grid[gi]=[])).push(xs.length);xs.push(x);ys.push(y);}yield;const P=xs.length;const zs=new Float32Array(P);for(let i=0;i<P;i++)zs[i]=(rnd()*2-1)*amp*(spacing/Math.sqrt(dAt(xs[i],ys[i])));const tri=yield*delaunay(xs,ys);yield;const T=tri.length/3;const tgx=new Float32Array(T);const tgy=new Float32Array(T);for(let t=0;t<T;t++){const a=tri[t*3],b=tri[t*3+1],c=tri[t*3+2];const x0=xs[a],y0=ys[a],x1=xs[b],y1=ys[b],x2=xs[c],y2=ys[c];const det=(x1-x0)*(y2-y0)-(x2-x0)*(y1-y0);if(Math.abs(det)<1e-9)continue;// plane slope through the three corner heights\nconst dz1=zs[b]-zs[a],dz2=zs[c]-zs[a];const gx=(dz1*(y2-y0)-dz2*(y1-y0))/det;const gy=(dz2*(x1-x0)-dz1*(x2-x0))/det;tgx[t]=gx;tgy[t]=gy;// scanline fill: pixel centres in [ymin, ymax) x [xl, xr); shared edges are evaluated\n// from the same endpoints in both triangles, so neighbours tile without gaps\nlet ya=Math.min(y0,y1,y2);let yb=Math.max(y0,y1,y2);const ry0=Math.max(0,Math.ceil(ya-.5));const ry1=Math.min(h-1,Math.ceil(yb-.5)-1);for(let y=ry0;y<=ry1;y++){const py=y+.5;let xl=Infinity;let xr=-Infinity;for(let e=0;e<3;e++){let pxa=e===0?x0:e===1?x1:x2;let pya=e===0?y0:e===1?y1:y2;let pxb=e===0?x1:e===1?x2:x0;let pyb=e===0?y1:e===1?y2:y0;if(pya>pyb||pya===pyb&&pxa>pxb){const tx=pxa,ty=pya;pxa=pxb;pya=pyb;pxb=tx;pyb=ty;}if(py<pya||py>=pyb)continue;const xe=pxa+(py-pya)*(pxb-pxa)/(pyb-pya);if(xe<xl)xl=xe;if(xe>xr)xr=xe;}if(!(xr>xl))continue;const rx0=Math.max(0,Math.ceil(xl-.5));const rx1=Math.min(w-1,Math.ceil(xr-.5)-1);work+=rx1-rx0+8;let i=y*w+rx0;for(let x=rx0;x<=rx1;x++,i++){GX[i]+=gx;GY[i]+=gy;}// pause between rows (big facets span many)\nif(work>STEP){work=0;yield;}}}if(lineAmt<=0)return;yield;// fold lines along the shared edges: ridges catch light, valleys hold a little shadow\nconst edges=new Map;const lw=lineW*px;const cw=Math.max(.55,lineW*.42*px);const kRef=1.5*amp;for(let t=0;t<T;t++){for(let k=0;k<3;k++){const a=tri[t*3+k];const b=tri[t*3+(k+1)%3];const key=a<b?a*P+b:b*P+a;const other=edges.get(key);if(other===undefined){edges.set(key,t*3+k);continue;}edges.delete(key);const t1=Math.floor(other/3);const k1=other%3;const c1=tri[t1*3+(k1+2)%3];const ax=xs[a],ay=ys[a],bx=xs[b],by=ys[b];if(Math.max(ax,bx)<-lw||Math.min(ax,bx)>w+lw||Math.max(ay,by)<-lw||Math.min(ay,by)>h+lw)continue;const ex=bx-ax;const ey=by-ay;const el=Math.hypot(ex,ey);if(el<1e-6)continue;let mx=-ey/el;let my=ex/el;if((xs[c1]-ax)*mx+(ys[c1]-ay)*my>0){mx=-mx;my=-my;}const kap=(tgx[t]-tgx[t1])*mx+(tgy[t]-tgy[t1])*my;const s=Math.min(1.5,Math.abs(kap)/kRef);if(s<.04)continue;const sign=kap<0?1:-1// + ridge, - valley\n;const amt=sign*s*lineAmt;// ink cracks: only the sharpest ridges, broken up along their length\nconst crack=sign>0&&crackAmt>0&&rnd()<.45?crackAmt*Math.min(1,Math.max(0,(s-.5)*2)):0;// intensity varies along the fold and fades out where the fold ends\nconst knots=Math.ceil(el/(22*px))+2;const kv=[];for(let i=0;i<knots;i++)kv.push(rnd());const il2=1/(el*el);// walk the major axis and only visit the band around the line\nconst xMajor=Math.abs(ex)>=Math.abs(ey);const reach=lw+1.5;const half=reach/(xMajor?Math.abs(ex)/el:Math.abs(ey)/el);const m0=Math.max(0,Math.floor((xMajor?Math.min(ax,bx):Math.min(ay,by))-reach));const m1=Math.min((xMajor?w:h)-1,Math.ceil((xMajor?Math.max(ax,bx):Math.max(ay,by))+reach));for(let mj=m0;mj<=m1;mj++){const pm=mj+.5;let tt=xMajor?(pm-ax)/ex:(pm-ay)/ey;tt=tt<0?0:tt>1?1:tt;const mc=xMajor?ay+ey*tt:ax+ex*tt;const n0=Math.max(0,Math.floor(mc-half));const n1=Math.min((xMajor?h:w)-1,Math.ceil(mc+half));work+=n1-n0+4;if(work>STEP){work=0;yield;}for(let mn=n0;mn<=n1;mn++){const x=xMajor?mj:mn;const y=xMajor?mn:mj;const pxx=x+.5;const py=y+.5;let u=((pxx-ax)*ex+(py-ay)*ey)*il2;u=u<0?0:u>1?1:u;const dx=pxx-(ax+ex*u);const dy=py-(ay+ey*u);const d=Math.sqrt(dx*dx+dy*dy);if(d>=lw+.5)continue;let p=1-d/(lw+.5);p*=p;const i=y*w+x;const f=u*(knots-1);const f0=Math.min(knots-2,Math.floor(f));let ft=f-f0;ft=ft*ft*(3-2*ft);const v=kv[f0]*(1-ft)+kv[f0+1]*ft;const ends=Math.min(1,Math.min(u,1-u)*el/(7*px));FL[i]+=amt*p*(.4+.6*v)*(.35+.65*ends);if(crack>0&&d<cw+1.5){const m=Math.min(1,Math.max(0,(v-.3)/.45));// the crack wanders a little around the fold line\nconst side=(dx*ey-dy*ex)/el;const wob=(kv[(f0+1)%knots]-.5)*1.2*px*Math.sin(ft*3.1416);const dc=Math.abs(side-wob);if(dc>=cw+.5)continue;const c=crack*m*m*(3-2*m)*ends*(1-dc/(cw+.5));if(c>CR[i])CR[i]=c;}}}}}};// big facets can only tilt a little (the sheet lies flat), small crinkle tilts more\nyield;yield*layer(16,.05,false,1.7,.85,.8);yield*layer(80,.075,false,1.4,.7,.5);yield*layer(380,.09,true,1.1,.32,.15);yield*layer(1400,.075,true,.9,.14,0);yield;const out=new Uint8Array(n*4);for(let i=0;i<n;i++){if(i%8192===8191)yield;const gx=Math.max(-1,Math.min(1,GX[i]*2));const gy=Math.max(-1,Math.min(1,-GY[i]*2))// texture rows run down, world y runs up\n;const fl=Math.max(-1,Math.min(1,FL[i]));out[i*4]=Math.round((gx*.5+.5)*255);out[i*4+1]=Math.round((gy*.5+.5)*255);out[i*4+2]=Math.round((fl*.5+.5)*255);out[i*4+3]=Math.round(Math.min(1,CR[i])*255);}return out;}const VS_PAPER=`#version 300 es\nin vec3 aPos; in vec3 aNormal; in vec2 aRest; in float aAO;\nuniform vec2 uHalf; uniform vec2 uCenter; uniform float uD;\nout vec3 vPos; out vec3 vNormal; out vec2 vRest; out float vAO;\nvoid main(){\n  vPos=aPos; vNormal=aNormal; vRest=aRest; vAO=aAO;\n  // straight-down camera above each sheet: z = 0 maps exactly onto the css layout\n  float k = uD/(uD - aPos.z);\n  vec2 s = uCenter + (aPos.xy - uCenter)*k;\n  gl_Position = vec4(s/uHalf, -aPos.z/uD, 1.0);\n}`;const FS_PAPER=`#version 300 es\nprecision highp float;\nin vec3 vPos; in vec3 vNormal; in vec2 vRest; in float vAO;\nuniform sampler2D uImage; uniform sampler2D uCrease;\nuniform vec4 uCover; uniform vec4 uInset; uniform float uHasImage; uniform vec3 uPaper;\nuniform vec3 uKey; uniform vec3 uFill; uniform vec3 uRake;\nuniform float uRakeAmt; uniform float uGloss; uniform float uGrain; uniform float uCrumple;\nuniform vec3 uEye; uniform vec2 uSheetPx; uniform vec4 uRadii; uniform float uShow;\nuniform float uCreaseAmt; uniform float uCrack; uniform vec2 uFlip; uniform float uImgFade;\nuniform vec3 uKeyD; uniform float uFoldAmt; uniform vec4 uLetter; uniform float uLetterTilt;\nout vec4 outColor;\n\nfloat hash(vec2 p){ p=fract(p*vec2(123.34,456.21)); p+=dot(p,p+45.32); return fract(p.x*p.y); }\nfloat vnoise(vec2 p){ vec2 i=floor(p), f=fract(p); f=f*f*(3.0-2.0*f);\n  return mix(mix(hash(i),hash(i+vec2(1,0)),f.x), mix(hash(i+vec2(0,1)),hash(i+vec2(1,1)),f.x), f.y); }\nvec3 toLinear(vec3 c){ return pow(max(c,0.0), vec3(2.2)); }\nvec3 toSRGB(vec3 c){ return pow(max(c,0.0), vec3(1.0/2.2)); }\nfloat lightAt(vec3 n){\n  return max(dot(n,uKey),0.0)*0.78 + max(dot(n,uFill),0.0)*0.14 + 0.16 + 0.2*(n.z*0.5+0.5);\n}\n\nvoid main(){\n  // rounded corners (per corner radius, sheet pixels)\n  vec2 sp = (vRest-0.5)*uSheetPx;\n  float r = sp.x < 0.0 ? (sp.y > 0.0 ? uRadii.x : uRadii.w) : (sp.y > 0.0 ? uRadii.y : uRadii.z);\n  vec2 q = abs(sp) - (0.5*uSheetPx - vec2(r));\n  float sd = length(max(q,0.0)) + min(max(q.x,q.y),0.0) - r;\n  float aa = clamp(0.5 - sd, 0.0, 1.0);\n  if (aa <= 0.0) discard;\n\n  vec3 n = normalize(vNormal);\n  bool front = gl_FrontFacing;\n  if (!front) n = -n;\n  vec3 nG = n;\n\n  // crease map through a cotangent frame (works flat and crumpled)\n  vec2 cuv = vec2(vRest.x, 1.0 - vRest.y);\n  cuv = mix(cuv, 1.0 - cuv, uFlip);\n  vec4 cm = texture(uCrease, cuv);\n  vec2 slope = (cm.rg * 2.0 - 1.0) * 0.5 * mix(vec2(1.0), vec2(-1.0), uFlip) * uCreaseAmt;\n  float fold = (cm.b * 2.0 - 1.0) * uFoldAmt * (front ? 1.0 : -1.0);\n  float crack = cm.a * uCrack;\n\n  // letter folds (made before the crumple): valley folds with a rounded bend, the outer panels\n  // rise a little; a thin groove holds shadow and the lip above it catches the light\n  float lf = 0.0;\n  float lip = 0.0;\n  if (uLetter.x > 0.5) {\n    float yy = vRest.y * uSheetPx.y;\n    float xx = (vRest.x - 0.5) * uSheetPx.x;\n    float tw = max(fwidth(yy), 0.35);\n    float s1 = yy - (uLetter.y * uSheetPx.y + xx * uLetterTilt);\n    float s2 = yy - (uLetter.z * uSheetPx.y - xx * uLetterTilt * 0.7);\n    float wob = vnoise(vec2(xx * 0.05, 3.7)) * 0.6 + 0.4;\n    float l1 = 1.0 - smoothstep(0.15 * tw, 0.9 * tw + 0.35, abs(s1));\n    float b1 = smoothstep(-2.5, 2.5, s1) * 2.0 - 1.0;\n    lip = (1.0 - smoothstep(0.0, 1.6 * tw + 0.8, abs(s1 - 1.4 * tw - 0.6)));\n    if (uLetter.x < 1.5) {\n      slope.y += b1 * uLetter.w;\n      lf = l1 * wob;\n    } else {\n      float l2 = 1.0 - smoothstep(0.15 * tw, 0.9 * tw + 0.35, abs(s2));\n      float b2 = smoothstep(-2.5, 2.5, s2);\n      slope.y += (b1 * 0.5 - 0.5) * uLetter.w + b2 * uLetter.w;\n      lf = max(l1, l2) * wob;\n      lip = max(lip, 1.0 - smoothstep(0.0, 1.6 * tw + 0.8, abs(s2 - 1.4 * tw - 0.6)));\n    }\n  }\n  vec2 pert = -slope;\n  vec3 dp1 = dFdx(vPos), dp2 = dFdy(vPos);\n  vec2 du1 = dFdx(vRest), du2 = dFdy(vRest);\n  vec3 dp2perp = cross(dp2, n), dp1perp = cross(n, dp1);\n  vec3 T = dp2perp * du1.x + dp1perp * du2.x;\n  vec3 B = dp2perp * du1.y + dp1perp * du2.y;\n  float invmax = inversesqrt(max(max(dot(T,T), dot(B,B)), 1e-20));\n  n = normalize(n + (T * pert.x + B * pert.y) * invmax * (front ? 1.0 : -1.0));\n\n  // paper fibre grain\n  vec2 gp = vRest*uSheetPx*0.9;\n  float grain = (vnoise(gp*0.55)*0.6 + vnoise(gp*1.7+17.0)*0.4) - 0.5;\n\n  // albedo: printed image on the front, paper (with a faint show-through) on the back\n  vec2 img = vec2((vRest.x-uInset.x)/(uInset.z-uInset.x), ((1.0-vRest.y)-uInset.y)/(uInset.w-uInset.y));\n  // anti-aliased edge of the printed area (sheet pixel space)\n  vec2 pp = vec2(vRest.x, 1.0-vRest.y) * uSheetPx;\n  vec2 r0 = uInset.xy * uSheetPx, r1 = uInset.zw * uSheetPx;\n  vec2 dd = max(r0 - pp, pp - r1);\n  float dimg = max(dd.x, dd.y);\n  float inImg = clamp(0.5 - dimg / max(fwidth(dimg), 1e-4), 0.0, 1.0) * uHasImage * uImgFade;\n  vec3 paper = toLinear(uPaper);\n  vec3 albedo = paper;\n  if (front) {\n    vec3 ic = toLinear(texture(uImage, uCover.xy + clamp(img,0.0,1.0)*uCover.zw).rgb);\n    albedo = mix(paper, ic, inImg);\n    // ink cracks and worn fibres along the folds show the paper through the print\n    float wht = crack + max(fold, 0.0) * 0.015 + lf * 0.16 * uFoldAmt;\n    albedo = mix(albedo, paper * 1.02, clamp(wht, 0.0, 0.6) * inImg);\n  } else {\n    vec2 mimg = vec2(1.0-img.x, img.y);\n    vec3 ic = toLinear(texture(uImage, uCover.xy + clamp(mimg,0.0,1.0)*uCover.zw).rgb);\n    float lum = dot(ic, vec3(0.3,0.59,0.11));\n    albedo = paper * mix(1.0, 0.82 + 0.18*lum/max(dot(paper,vec3(0.3,0.59,0.11)),0.01), uShow*inImg);\n  }\n  albedo *= 1.0 + grain*uGrain*mix(0.06, 0.09, 1.0-inImg);\n\n  // lighting, normalised so a flat, level sheet shows the image 1:1\n  vec3 nFlat = vec3(0.0,0.0,1.0);\n  float L = lightAt(n)/lightAt(nFlat);\n  // the creases read like under a desk lamp: a lower light brings out the facets\n  L += (max(dot(n,uKeyD),0.0) - max(dot(nG,uKeyD),0.0)) * 0.6;\n  // fold lines: valleys hold a little shadow, ridges catch the light\n  L *= 1.0 - max(-fold, 0.0) * 0.22 - lf * 0.3 * min(uFoldAmt * 2.0, 1.0);\n  L += max(fold, 0.0) * 0.07 + lip * 0.05 * min(uFoldAmt * 2.0, 1.0);\n  float rake = (max(dot(n,uRake),0.0) - max(dot(nFlat,uRake),0.0)*(1.0-uCrumple)) * uRakeAmt * 1.6;\n  vec3 V = normalize(uEye - vPos);\n  vec3 H = normalize(uKey + V);\n  float shin = mix(18.0, 110.0, uGloss);\n  float ks = mix(0.012, 0.16, uGloss);\n  float spec = pow(max(dot(n,H),0.0), shin) * ks;\n  float specR = pow(max(dot(n,normalize(uRake + V)),0.0), shin*0.7) * mix(0.01, 0.14, uGloss) * uRakeAmt;\n  // keep a little of the broad sheen on the smoothed print: it reads as real photo paper\n  float flatSpec = pow(max(dot(nFlat,H),0.0), shin) * ks * (1.0-uCrumple);\n  float lum = dot(albedo, vec3(0.3,0.59,0.11));\n  float sheen = mix(0.22, 1.0, clamp(lum*2.2, 0.0, 1.0));\n  vec3 col = albedo * (L*vAO + rake) + vec3((spec + specR - flatSpec*0.7) * sheen);\n  outColor = vec4(toSRGB(col)*aa, aa);\n}`;const VS_MASK=`#version 300 es\nin vec3 aPos;\nuniform vec3 uDir; uniform vec2 uHalf;\nvoid main(){ vec2 p = aPos.xy - uDir.xy/uDir.z*aPos.z; gl_Position = vec4(p/uHalf, 0.0, 1.0); }`;const FS_MASK=`#version 300 es\nprecision mediump float;\nuniform vec4 uCol; out vec4 o; void main(){ o = uCol; }`;const VS_QUAD=`#version 300 es\nin vec2 aQ; out vec2 vUV;\nvoid main(){ vUV = aQ*0.5+0.5; gl_Position = vec4(aQ,0.0,1.0); }`;const FS_BLUR=`#version 300 es\nprecision highp float;\nin vec2 vUV; uniform sampler2D uTex; uniform vec2 uStepA; uniform vec2 uStepB; out vec4 o;\nvoid main(){\n  vec2 acc = vec2(0.0); float wsum = 0.0;\n  for (int i=-12;i<=12;i++){ float x=float(i); float w=exp(-x*x/72.0);\n    acc.x += texture(uTex, vUV+uStepA*x).r*w; acc.y += texture(uTex, vUV+uStepB*x).g*w; wsum += w; }\n  o = vec4(acc/wsum, 0.0, 1.0);\n}`;const FS_SHADOW=`#version 300 es\nprecision highp float;\nin vec2 vUV; uniform sampler2D uTex; uniform vec3 uShadow; uniform vec2 uAmt; out vec4 o;\nvoid main(){ vec2 m = texture(uTex, vUV).rg; float a = clamp(m.r*uAmt.x + m.g*uAmt.y, 0.0, 1.0);\n  o = vec4(uShadow*a, a); }`;const GL_ATTRS={antialias:true,premultipliedAlpha:true,alpha:true};// Shaders are compiled and linked without asking for their status in between, so the driver can work\n// on all programs at once (and in the background with KHR_parallel_shader_compile, see prepareScene).\nfunction linkStart(gl,vs,fs){const p=gl.createProgram();for(const[type,src]of[[gl.VERTEX_SHADER,vs],[gl.FRAGMENT_SHADER,fs]]){const s=gl.createShader(type);gl.shaderSource(s,src);gl.compileShader(s);gl.attachShader(p,s);}gl.linkProgram(p);return p;}function linkFinish(gl,p){if(!gl.getProgramParameter(p,gl.LINK_STATUS)){const logs=(gl.getAttachedShaders(p)||[]).map(s=>gl.getShaderInfoLog(s)||\"\").join(\"\\n\");throw new Error((gl.getProgramInfoLog(p)||\"link\")+\"\\n\"+logs);}const u={};const n=gl.getProgramParameter(p,gl.ACTIVE_UNIFORMS);for(let i=0;i<n;i++){const info=gl.getActiveUniform(p,i);if(info)u[info.name]=gl.getUniformLocation(p,info.name);}return{p,u};}function startPrograms(gl){return[linkStart(gl,VS_PAPER,FS_PAPER),linkStart(gl,VS_MASK,FS_MASK),linkStart(gl,VS_QUAD,FS_BLUR),linkStart(gl,VS_QUAD,FS_SHADOW)];}// Creates the scene without blocking the main thread on shader compilation: where the browser\n// compiles in the background (KHR_parallel_shader_compile) this waits in short timer steps until\n// all programs are linked; otherwise the status query in the constructor waits as before.\nasync function prepareScene(canvas,data){const gl=canvas.getContext(\"webgl2\",GL_ATTRS);if(!gl)throw new Error(\"WebGL2 unavailable\");const programs=startPrograms(gl);const ext=gl.getExtension(\"KHR_parallel_shader_compile\");if(ext){const t0=Date.now();const done=()=>programs.every(p=>gl.getProgramParameter(p,ext.COMPLETION_STATUS_KHR)!==false);while(!done()&&Date.now()-t0<4e3)await new Promise(r=>setTimeout(r,8));}return new CrumpleScene(canvas,data,{gl,programs});}function parseColor(c,fallback){if(!c||typeof c!==\"string\")return fallback;const s=c.trim();if(s[0]===\"#\"){let h=s.slice(1);if(h.length===3||h.length===4)h=h.split(\"\").map(x=>x+x).join(\"\");const r=parseInt(h.slice(0,2),16)/255;const g=parseInt(h.slice(2,4),16)/255;const b=parseInt(h.slice(4,6),16)/255;const a=h.length>=8?parseInt(h.slice(6,8),16)/255:1;return[r,g,b,a].some(x=>Number.isNaN(x))?fallback:[r,g,b,a];}const m=s.match(/rgba?\\(([^)]+)\\)/i);if(m){const v=m[1].split(/[\\s,/]+/).filter(Boolean).map(x=>parseFloat(x));if(v.length>=3)return[v[0]/255,v[1]/255,v[2]/255,v.length>3?v[3]:1];}return fallback;}class CrumpleScene{// true while a crease map is still being built (callers keep their render loop running)\ncreasePending(){return this.creaseQueue.length>0;}// Advances the crease map jobs for about budgetMs. With a frame id (the rAF timestamp) the budget is\n// shared by every sheet that pumps in that frame, so many sheets never add up to a long task.\n// A finished map is uploaded in a slice of its own.\npumpCrease(budgetMs,frame){const now=()=>typeof performance!==\"undefined\"?performance.now():Date.now();const t0=now();if(frame!==undefined){if(frame!==this.pumpFrame){this.pumpFrame=frame;this.pumpSpent=0;}budgetMs-=this.pumpSpent;if(budgetMs<=0)return;}const gl=this.gl;try{while(this.creaseQueue.length){const q=this.creaseQueue[0];const m=this.creaseMaps.get(q.key);// nobody asked for this size for a second (resized away, or its sheet left the screen): drop it\nif(!m||t0-m.used>1e3){this.creaseQueue.shift();if(m){gl.deleteTexture(m.tex);this.creaseMaps.delete(q.key);}continue;}if(!q.data){let r=q.job.next();while(!r.done&&now()-t0<budgetMs)r=q.job.next();if(!r.done)return;q.data=r.value;if(now()-t0>=budgetMs*.5)return;}this.creaseQueue.shift();gl.bindTexture(gl.TEXTURE_2D,m.tex);gl.pixelStorei(gl.UNPACK_ALIGNMENT,1);gl.pixelStorei(gl.UNPACK_FLIP_Y_WEBGL,false);gl.texImage2D(gl.TEXTURE_2D,0,gl.RGBA,q.w,q.h,0,gl.RGBA,gl.UNSIGNED_BYTE,q.data);gl.generateMipmap(gl.TEXTURE_2D);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MIN_FILTER,gl.LINEAR_MIPMAP_LINEAR);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MAG_FILTER,gl.LINEAR);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_S,gl.CLAMP_TO_EDGE);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_T,gl.CLAMP_TO_EDGE);m.ready=true;q.data=null;if(now()-t0>=budgetMs)return;}}finally{if(frame!==undefined)this.pumpSpent+=now()-t0;}}creaseKey(W,H,dpr,seed){const s=Math.min(1,1024/Math.max(W*dpr,H*dpr,1));const w=Math.max(64,Math.round(W*dpr*s/32)*32);const h=Math.max(64,Math.round(H*dpr*s/32)*32);return{w,h,key:w+\"x\"+h+\":\"+seed};}// true once the crease map for this sheet size is built and uploaded (registers its job if needed)\ncreaseReady(W,H,dpr,seed){this.creaseFor(W,H,dpr,seed);const m=this.creaseMaps.get(this.creaseKey(W,H,dpr,seed).key);return!!m&&m.ready;}// Crease texture for a sheet size. Until its map is built, the most recently used finished map of the\n// same seed stands in (same pattern at another resolution for the same aspect), else level paper.\ncreaseFor(W,H,dpr,seed){const{w,h,key}=this.creaseKey(W,H,dpr,seed);const t=typeof performance!==\"undefined\"?performance.now():Date.now();let m=this.creaseMaps.get(key);if(!m){if(this.creaseMaps.size>=4){let oldest=\"\";let ot=Infinity;for(const[k,v]of this.creaseMaps)if(v.ready&&v.used<ot)ot=v.used,oldest=k;const old=oldest?this.creaseMaps.get(oldest):undefined;if(old){this.gl.deleteTexture(old.tex);this.creaseMaps.delete(oldest);}}m={tex:this.gl.createTexture(),ready:false,used:t,seed};this.creaseMaps.set(key,m);this.creaseQueue.push({key,w,h,job:creaseMapJob(w,h,seed),data:null});}m.used=t;if(m.ready)return m.tex;let best=null;for(const v of this.creaseMaps.values())if(v.ready&&v.seed===seed&&(!best||v.used>best.used))best=v;return best?best.tex:this.neutralTex;}item(key){let it=this.items.get(key);if(it)return it;const gl=this.gl;const F=this.d.F;const soupPos=new Float32Array(F*9);const soupNrm=new Float32Array(F*9);const soupAO=new Float32Array(F*3);const P=this.paperProg.p;const vao=gl.createVertexArray();gl.bindVertexArray(vao);const mk=(arr,name,size)=>{const b=gl.createBuffer();const loc=gl.getAttribLocation(P,name);gl.bindBuffer(gl.ARRAY_BUFFER,b);gl.bufferData(gl.ARRAY_BUFFER,arr,gl.DYNAMIC_DRAW);if(loc>=0){gl.enableVertexAttribArray(loc);gl.vertexAttribPointer(loc,size,gl.FLOAT,false,0,0);}return b;};const bPos=mk(soupPos,\"aPos\",3);const bNrm=mk(soupNrm,\"aNormal\",3);const bAO=mk(soupAO,\"aAO\",1);const lr=gl.getAttribLocation(P,\"aRest\");gl.bindBuffer(gl.ARRAY_BUFFER,this.bRest);if(lr>=0){gl.enableVertexAttribArray(lr);gl.vertexAttribPointer(lr,2,gl.FLOAT,false,0,0);}const maskVao=gl.createVertexArray();gl.bindVertexArray(maskVao);gl.bindBuffer(gl.ARRAY_BUFFER,bPos);const lm=gl.getAttribLocation(this.maskProg.p,\"aPos\");gl.enableVertexAttribArray(lm);gl.vertexAttribPointer(lm,3,gl.FLOAT,false,0,0);gl.bindVertexArray(null);const tex=gl.createTexture();gl.bindTexture(gl.TEXTURE_2D,tex);gl.texImage2D(gl.TEXTURE_2D,0,gl.RGBA,1,1,0,gl.RGBA,gl.UNSIGNED_BYTE,new Uint8Array([240,238,232,255]));it={vao,maskVao,bPos,bNrm,bAO,tex,imgW:1,imgH:1,hasImage:0,img:null,fadeStart:0,soupPos,soupNrm,soupAO,built:\"\",c:0};this.items.set(key,it);return it;}removeItem(key){const it=this.items.get(key);if(!it)return;const gl=this.gl;gl.deleteVertexArray(it.vao);gl.deleteVertexArray(it.maskVao);gl.deleteBuffer(it.bPos);gl.deleteBuffer(it.bNrm);gl.deleteBuffer(it.bAO);gl.deleteTexture(it.tex);this.items.delete(key);}removeItemsExcept(keys){const gl=this.gl;for(const[k,it]of this.items){if(keys.includes(k))continue;gl.deleteVertexArray(it.vao);gl.deleteVertexArray(it.maskVao);gl.deleteBuffer(it.bPos);gl.deleteBuffer(it.bNrm);gl.deleteBuffer(it.bAO);gl.deleteTexture(it.tex);this.items.delete(k);}}// img: a decoded image, or an ImageBitmap / canvas already scaled to the size the sheet needs\n// (callers keep it within maxTexture). fade: false swaps the print without fading it in again.\nsetImage(key,img,fade=true){const gl=this.gl;const it=this.item(key);if(it.img===img)return;it.img=img;gl.bindTexture(gl.TEXTURE_2D,it.tex);if(!img){gl.texImage2D(gl.TEXTURE_2D,0,gl.RGBA,1,1,0,gl.RGBA,gl.UNSIGNED_BYTE,new Uint8Array([240,238,232,255]));it.hasImage=0;return;}gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL,false);gl.pixelStorei(gl.UNPACK_FLIP_Y_WEBGL,false);gl.texImage2D(gl.TEXTURE_2D,0,gl.RGBA,gl.RGBA,gl.UNSIGNED_BYTE,img);gl.generateMipmap(gl.TEXTURE_2D);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MIN_FILTER,gl.LINEAR_MIPMAP_LINEAR);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MAG_FILTER,gl.LINEAR);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_S,gl.CLAMP_TO_EDGE);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_T,gl.CLAMP_TO_EDGE);const an=gl.getExtension(\"EXT_texture_filter_anisotropic\");if(an)gl.texParameterf(gl.TEXTURE_2D,an.TEXTURE_MAX_ANISOTROPY_EXT,8);it.imgW=img.naturalWidth||img.width||1;it.imgH=img.naturalHeight||img.height||1;const had=it.hasImage;it.hasImage=1;if(fade||!had)it.fadeStart=typeof performance!==\"undefined\"?performance.now():0;}// true while a print (this sheet's, or any without a key) is still fading in (the caller keeps its loop running)\nfading(key){const now=typeof performance!==\"undefined\"?performance.now():0;if(key!==undefined){const it=this.items.get(key);return!!it&&!!it.hasImage&&now-it.fadeStart<450;}for(const it of this.items.values())if(it.hasImage&&now-it.fadeStart<450)return true;return false;}ensureShadowRT(w,h){const gl=this.gl;const key=w+\"x\"+h;const t=typeof performance!==\"undefined\"?performance.now():Date.now();const hit=this.shadowRTs.get(key);if(hit){hit.used=t;return hit;}if(this.shadowRTs.size>=4){let oldest=\"\";let ot=Infinity;for(const[k,v]of this.shadowRTs)if(v.used<ot)ot=v.used,oldest=k;const old=this.shadowRTs.get(oldest);if(old){for(const x of[old.a,old.b]){gl.deleteTexture(x.t);gl.deleteFramebuffer(x.fb);}this.shadowRTs.delete(oldest);}}const mk=()=>{const t=gl.createTexture();gl.bindTexture(gl.TEXTURE_2D,t);gl.texImage2D(gl.TEXTURE_2D,0,gl.RGBA8,w,h,0,gl.RGBA,gl.UNSIGNED_BYTE,null);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MIN_FILTER,gl.LINEAR);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_MAG_FILTER,gl.LINEAR);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_S,gl.CLAMP_TO_EDGE);gl.texParameteri(gl.TEXTURE_2D,gl.TEXTURE_WRAP_T,gl.CLAMP_TO_EDGE);const fb=gl.createFramebuffer();gl.bindFramebuffer(gl.FRAMEBUFFER,fb);gl.framebufferTexture2D(gl.FRAMEBUFFER,gl.COLOR_ATTACHMENT0,gl.TEXTURE_2D,t,0);return{t,fb};};const rt={w,h,used:t,a:mk(),b:mk()};this.shadowRTs.set(key,rt);gl.bindFramebuffer(gl.FRAMEBUFFER,null);return rt;}// world space: css px, origin at the component centre, y up\nbuild(it,st,o){const{N,F,K,keys,faces,relief,crumple,center,rest}=this.d;const p=Math.min(1,Math.max(0,st.progress));const u=p*(K-1);const k1=Math.min(K-2,Math.floor(u));const t=u-k1;const k0=Math.max(0,k1-1);const k2=k1+1;const k3=Math.min(K-1,k1+2);const t2=t*t;const t3=t2*t;const w0=-.5*t3+t2-.5*t;const w1=1.5*t3-2.5*t2+1;const w2=-1.5*t3+2*t2+.5*t;const w3=.5*t3-.5*t2;const c=crumple[k1]*(1-t)+crumple[k2]*t;it.c=c;const W=st.w;const H=st.h;const S=Math.sqrt(W*H);const bs=1+(o.ballSize-1)*c;const sx=(W+(S-W)*c)*bs;const sy=(H+(S-H)*c)*bs;const ccx=(center[k1*2]*(1-t)+center[k2*2]*t)*c;const ccy=(center[k1*2+1]*(1-t)+center[k2*2+1]*t)*c;const pos=this.pos;const b0=k0*N*3;const b1=k1*N*3;const b2=k2*N*3;const b3=k3*N*3;// rotations: tilt (shows another side of the ball) grows with the crumple, spin blends to the print angle\nconst tl=st.tilt*c*c;const ax=Math.cos(st.tiltAxis);const ay=Math.sin(st.tiltAxis);const ct=Math.cos(tl);const stn=Math.sin(tl);const rot=st.flatRot+(st.spin-st.flatRot)*c;const cr=Math.cos(rot);const sr=Math.sin(rot);let zc=0;for(let v=0;v<N;v++)zc+=keys[b1+v*3+2]*(1-t)+keys[b2+v*3+2]*t;zc=zc/N*S*bs;let minZ=1e9;for(let v=0;v<N;v++){const i=v*3;const x=(w0*keys[b0+i]+w1*keys[b1+i]+w2*keys[b2+i]+w3*keys[b3+i]-ccx)*sx;const y=(w0*keys[b0+i+1]+w1*keys[b1+i+1]+w2*keys[b2+i+1]+w3*keys[b3+i+1]-ccy)*sy;const z=Math.max(0,w0*keys[b0+i+2]+w1*keys[b1+i+2]+w2*keys[b2+i+2]+w3*keys[b3+i+2])*S*bs-zc;// Rodrigues rotation around the horizontal axis (ax, ay, 0)\nconst d=ax*x+ay*y;const rx=x*ct+ay*z*stn+ax*d*(1-ct);const ry=y*ct-ax*z*stn+ay*d*(1-ct);const rz=z*ct+(ax*y-ay*x)*stn;pos[i]=rx*cr-ry*sr;pos[i+1]=rx*sr+ry*cr;pos[i+2]=rz;if(rz<minZ)minZ=rz;}// the smoothed print keeps a memory of its creases and lifts slightly at the corners\nconst flat=Math.pow(1-c,3);const reliefAmp=o.creases*.02*S*flat;const curlAmp=o.creases*.03*S*flat;const lift=o.lift*S+st.hoverLift*S*.035*flat;const cxw=st.x+W/2-o.width/2+st.offX*st.w*c;const cyw=-(st.y+H/2-o.height/2)-st.offY*st.h*c;const cu=st.curl;for(let v=0;v<N;v++){const i=v*3;const ru=rest[v*2];const rv=rest[v*2+1];// corner lift: 0 tl, 1 tr, 2 br, 3 bl (rest y points up)\nconst d0=Math.max(0,1-Math.hypot(ru,1-rv)/.42);const d1=Math.max(0,1-Math.hypot(1-ru,1-rv)/.42);const d2=Math.max(0,1-Math.hypot(1-ru,rv)/.42);const d3=Math.max(0,1-Math.hypot(ru,rv)/.42);const curl=Math.max(0,cu[0])*d0*d0*d0+Math.max(0,cu[1])*d1*d1*d1+Math.max(0,cu[2])*d2*d2*d2+Math.max(0,cu[3])*d3*d3*d3;pos[i]+=cxw;pos[i+1]+=cyw;pos[i+2]+=-minZ+(relief[v]+.4)*reliefAmp+curl*curlAmp+lift;}const fn=this.fn;const fu=this.fu;for(let f=0;f<F;f++){const a=faces[f*3]*3;const b=faces[f*3+1]*3;const cc=faces[f*3+2]*3;const e1x=pos[b]-pos[a];const e1y=pos[b+1]-pos[a+1];const e1z=pos[b+2]-pos[a+2];const e2x=pos[cc]-pos[a];const e2y=pos[cc+1]-pos[a+1];const e2z=pos[cc+2]-pos[a+2];const nx=e1y*e2z-e1z*e2y;const ny=e1z*e2x-e1x*e2z;const nz=e1x*e2y-e1y*e2x;fn[f*3]=nx;fn[f*3+1]=ny;fn[f*3+2]=nz;const l=Math.hypot(nx,ny,nz)||1;fu[f*3]=nx/l;fu[f*3+1]=ny/l;fu[f*3+2]=nz/l;}// ambient occlusion: deep inside the ball gets darker\nlet mx=0;let my=0;let mz=0;for(let v=0;v<N;v++){mx+=pos[v*3];my+=pos[v*3+1];mz+=pos[v*3+2];}mx/=N;my/=N;mz/=N;const ao=this.ao;let rmax=1e-6;for(let v=0;v<N;v++){const r=Math.hypot(pos[v*3]-mx,pos[v*3+1]-my,pos[v*3+2]-mz);ao[v]=r;if(r>rmax)rmax=r;}const aoAmt=o.ao*c*c;for(let v=0;v<N;v++){let tt=(ao[v]/rmax-.45)/.5;tt=tt<0?0:tt>1?1:tt;tt=tt*tt*(3-2*tt);ao[v]=1-aoAmt*(1-tt)*.75;}const cosT=Math.cos(o.creaseAngle*Math.PI/180);const fanStart=this.fanStart;const fan=this.fan;const sp=it.soupPos;const sn=it.soupNrm;const sa=it.soupAO;for(let f=0;f<F;f++){const ux=fu[f*3];const uy=fu[f*3+1];const uz=fu[f*3+2];for(let k=0;k<3;k++){const v=faces[f*3+k];let nx=0;let ny=0;let nz=0;for(let j=fanStart[v];j<fanStart[v+1];j++){const g=fan[j];if(fu[g*3]*ux+fu[g*3+1]*uy+fu[g*3+2]*uz>=cosT){nx+=fn[g*3];ny+=fn[g*3+1];nz+=fn[g*3+2];}}const l=Math.hypot(nx,ny,nz)||1;const s=(f*3+k)*3;sn[s]=nx/l;sn[s+1]=ny/l;sn[s+2]=nz/l;sp[s]=pos[v*3];sp[s+1]=pos[v*3+1];sp[s+2]=pos[v*3+2];sa[f*3+k]=ao[v];}}const gl=this.gl;gl.bindBuffer(gl.ARRAY_BUFFER,it.bPos);gl.bufferSubData(gl.ARRAY_BUFFER,0,sp);gl.bindBuffer(gl.ARRAY_BUFFER,it.bNrm);gl.bufferSubData(gl.ARRAY_BUFFER,0,sn);gl.bindBuffer(gl.ARRAY_BUFFER,it.bAO);gl.bufferSubData(gl.ARRAY_BUFFER,0,sa);}// Renders into the bottom-left pw x ph pixels of the canvas (the canvas only grows, so sheets of\n// different sizes can share it). Returns the drawn size for copying the result elsewhere.\nrender(o,states){const gl=this.gl;const M=o.margin;const cw=o.width+2*M;const ch=o.height+2*M;const pw=Math.max(1,Math.round(cw*o.dpr));const ph=Math.max(1,Math.round(ch*o.dpr));if(this.canvas.width<pw||this.canvas.height<ph){this.canvas.width=Math.max(this.canvas.width,pw);this.canvas.height=Math.max(this.canvas.height,ph);}const halfW=cw/2;const halfH=ch/2;if(!states.length){gl.bindFramebuffer(gl.FRAMEBUFFER,null);gl.viewport(0,0,pw,ph);gl.clearColor(0,0,0,0);gl.clear(gl.COLOR_BUFFER_BIT);return{pw,ph};}const cellW=states[0].w;const cellH=states[0].h;// the crease map is built by pumpCrease() from the caller's frame loop, never here\nconst creaseTex=this.creaseFor(cellW,cellH,o.dpr,o.seed);const geoKey=[o.width,o.height,o.creases,o.creaseAngle,o.lift,o.ballSize,o.ao].join(\"|\");for(const st of states){const it=this.item(st.key);const key=geoKey+\"|\"+[st.x,st.y,st.w,st.h,st.progress.toFixed(5),st.tilt,st.tiltAxis,st.spin,st.flatRot,st.offX,st.offY,st.curl.join(\",\"),st.hoverLift.toFixed(4)].join(\"|\");if(it.built!==key){this.build(it,st,o);it.built=key;}}const S=Math.sqrt(cellW*cellH);const D=Math.max(cellW,cellH)*2.6;// ---- shadow mask: ambient (straight down) in R, key light in G ----\nconst sw=Math.max(64,Math.round(cw/3));const sh=Math.max(64,Math.round(ch/3));const rt=this.ensureShadowRT(sw,sh);gl.bindFramebuffer(gl.FRAMEBUFFER,rt.a.fb);gl.viewport(0,0,sw,sh);gl.clearColor(0,0,0,0);gl.clear(gl.COLOR_BUFFER_BIT);gl.disable(gl.DEPTH_TEST);gl.enable(gl.BLEND);gl.blendFunc(gl.ONE,gl.ONE);gl.blendEquation(gl.MAX);gl.useProgram(this.maskProg.p);gl.uniform2f(this.maskProg.u.uHalf,halfW,halfH);const kd=o.keyDir;for(const st of states){const it=this.item(st.key);gl.bindVertexArray(it.maskVao);gl.colorMask(true,false,false,false);gl.uniform3f(this.maskProg.u.uDir,0,0,1);gl.uniform4f(this.maskProg.u.uCol,1,0,0,0);gl.drawArrays(gl.TRIANGLES,0,this.d.F*3);gl.colorMask(false,true,false,false);gl.uniform3f(this.maskProg.u.uDir,kd[0],kd[1],kd[2]);gl.uniform4f(this.maskProg.u.uCol,0,1,0,0);gl.drawArrays(gl.TRIANGLES,0,this.d.F*3);}gl.colorMask(true,true,true,true);gl.blendEquation(gl.FUNC_ADD);gl.disable(gl.BLEND);gl.useProgram(this.blurProg.p);gl.bindVertexArray(this.quadVao);const ra=S*.026/3/6;const rk=S*.012/3/6;gl.activeTexture(gl.TEXTURE0);gl.bindFramebuffer(gl.FRAMEBUFFER,rt.b.fb);gl.bindTexture(gl.TEXTURE_2D,rt.a.t);gl.uniform1i(this.blurProg.u.uTex,0);gl.uniform2f(this.blurProg.u.uStepA,ra/sw,0);gl.uniform2f(this.blurProg.u.uStepB,rk/sw,0);gl.drawArrays(gl.TRIANGLE_STRIP,0,4);gl.bindFramebuffer(gl.FRAMEBUFFER,rt.a.fb);gl.bindTexture(gl.TEXTURE_2D,rt.b.t);gl.uniform2f(this.blurProg.u.uStepA,0,ra/sh);gl.uniform2f(this.blurProg.u.uStepB,0,rk/sh);gl.drawArrays(gl.TRIANGLE_STRIP,0,4);// ---- main pass ----\ngl.bindFramebuffer(gl.FRAMEBUFFER,null);gl.viewport(0,0,pw,ph);gl.clearColor(0,0,0,0);gl.clearDepth(1);gl.clear(gl.COLOR_BUFFER_BIT|gl.DEPTH_BUFFER_BIT);gl.enable(gl.BLEND);gl.blendFunc(gl.ONE,gl.ONE_MINUS_SRC_ALPHA);gl.useProgram(this.shadowProg.p);gl.bindTexture(gl.TEXTURE_2D,rt.a.t);gl.uniform1i(this.shadowProg.u.uTex,0);const sc=parseColor(o.shadow,[.1,.08,.05,.4]);gl.uniform3f(this.shadowProg.u.uShadow,sc[0],sc[1],sc[2]);const sA=sc[3]*o.shadowAmt;gl.uniform2f(this.shadowProg.u.uAmt,sA*.55,sA*.5);gl.drawArrays(gl.TRIANGLE_STRIP,0,4);gl.enable(gl.DEPTH_TEST);gl.depthFunc(gl.LEQUAL);gl.disable(gl.CULL_FACE);gl.useProgram(this.paperProg.p);const U=this.paperProg.u;gl.uniform2f(U.uHalf,halfW,halfH);gl.uniform1f(U.uD,D);gl.activeTexture(gl.TEXTURE1);gl.bindTexture(gl.TEXTURE_2D,creaseTex);gl.uniform1i(U.uCrease,1);gl.activeTexture(gl.TEXTURE0);gl.uniform1i(U.uImage,0);const pc=parseColor(o.paper,[.96,.95,.92,1]);gl.uniform3f(U.uPaper,pc[0],pc[1],pc[2]);gl.uniform3f(U.uKey,kd[0],kd[1],kd[2]);const kaz=Math.atan2(kd[1],kd[0]);const kel=38*Math.PI/180;gl.uniform3f(U.uKeyD,Math.cos(kaz)*Math.cos(kel),Math.sin(kaz)*Math.cos(kel),Math.sin(kel));gl.uniform3f(U.uFill,o.fillDir[0],o.fillDir[1],o.fillDir[2]);gl.uniform1f(U.uGloss,o.gloss);gl.uniform1f(U.uGrain,o.grain);gl.uniform1f(U.uShow,o.show);for(const st of states){const it=this.item(st.key);const W=st.w;const H=st.h;const cx=st.x+W/2-o.width/2;const cy=-(st.y+H/2-o.height/2);gl.uniform2f(U.uCenter,cx,cy);gl.uniform3f(U.uEye,cx,cy,D);gl.bindTexture(gl.TEXTURE_2D,it.tex);const ins=o.inset;const ix0=Math.min(.45,ins[3]/W);const iy0=Math.min(.45,ins[0]/H);const ix1=Math.max(ix0+.05,1-ins[1]/W);const iy1=Math.max(iy0+.05,1-ins[2]/H);gl.uniform4f(U.uInset,ix0,iy0,ix1,iy1);const rAsp=(ix1-ix0)*W/((iy1-iy0)*H);const iAsp=it.imgW/it.imgH;let cu=1;let cv=1;if(iAsp>rAsp)cu=rAsp/iAsp;else cv=iAsp/rAsp;gl.uniform4f(U.uCover,(1-cu)*st.focus[0],(1-cv)*st.focus[1],cu,cv);gl.uniform1f(U.uHasImage,it.hasImage);const re=o.rakeElev;gl.uniform3f(U.uRake,Math.cos(st.rakeAngle)*Math.cos(re),Math.sin(st.rakeAngle)*Math.cos(re),Math.sin(re));gl.uniform1f(U.uRakeAmt,st.rake);gl.uniform1f(U.uCrumple,it.c);gl.uniform2f(U.uSheetPx,W,H);const maxR=Math.min(W,H)/2;gl.uniform4f(U.uRadii,Math.min(o.radii[0],maxR),Math.min(o.radii[1],maxR),Math.min(o.radii[2],maxR),Math.min(o.radii[3],maxR));const fl1=1-it.c;gl.uniform1f(U.uCreaseAmt,o.creases*1.05*(.35+.65*fl1));gl.uniform1f(U.uFoldAmt,Math.min(1,o.creases*1.4)*(.4+.6*fl1));gl.uniform1f(U.uCrack,Math.min(1,o.creases*1.2)*.32*fl1);const fj=st.foldJitter||[0,0,0];const tent=.11*Math.pow(fl1,3);if(st.fold===1)gl.uniform4f(U.uLetter,1,.5+fj[0]*.015,0,tent);else if(st.fold===2)gl.uniform4f(U.uLetter,2,1/3+fj[0]*.015,2/3+fj[1]*.015,tent);else gl.uniform4f(U.uLetter,0,0,0,0);gl.uniform1f(U.uLetterTilt,fj[2]*.012);gl.uniform2f(U.uFlip,st.flip[0],st.flip[1]);const now=typeof performance!==\"undefined\"?performance.now():0;const fz=it.hasImage?Math.min(1,(now-it.fadeStart)/450):0;gl.uniform1f(U.uImgFade,fz*fz*(3-2*fz));gl.bindVertexArray(it.vao);gl.drawArrays(gl.TRIANGLES,0,this.d.F*3);}gl.bindVertexArray(null);return{pw,ph};}dispose(){const ext=this.gl.getExtension(\"WEBGL_lose_context\");if(ext)ext.loseContext();}// pre: context + linked programs from prepareScene() (compiled without blocking); without it the\n// constructor compiles synchronously\nconstructor(canvas,data,pre){_define_property(this,\"canvas\",void 0);_define_property(this,\"gl\",void 0);_define_property(this,\"d\",void 0);_define_property(this,\"paperProg\",void 0);_define_property(this,\"maskProg\",void 0);_define_property(this,\"blurProg\",void 0);_define_property(this,\"shadowProg\",void 0);_define_property(this,\"fanStart\",void 0);_define_property(this,\"fan\",void 0);_define_property(this,\"pos\",void 0);_define_property(this,\"fn\",void 0);_define_property(this,\"fu\",void 0);_define_property(this,\"ao\",void 0);_define_property(this,\"bRest\",void 0);_define_property(this,\"quadVao\",void 0);_define_property(this,\"neutralTex\",void 0);// crease maps and shadow targets are cached per sheet size: many sheets can share one renderer\n_define_property(this,\"creaseMaps\",new Map);_define_property(this,\"creaseQueue\",[]);_define_property(this,\"pumpFrame\",-1);_define_property(this,\"pumpSpent\",0);_define_property(this,\"maxTexture\",4096);_define_property(this,\"items\",new Map);_define_property(this,\"shadowRTs\",new Map);this.canvas=canvas;this.d=data;const gl=pre?pre.gl:canvas.getContext(\"webgl2\",GL_ATTRS);if(!gl)throw new Error(\"WebGL2 unavailable\");this.gl=gl;const progs=pre?pre.programs:startPrograms(gl);this.paperProg=linkFinish(gl,progs[0]);this.maskProg=linkFinish(gl,progs[1]);this.blurProg=linkFinish(gl,progs[2]);this.shadowProg=linkFinish(gl,progs[3]);this.maxTexture=gl.getParameter(gl.MAX_TEXTURE_SIZE)||4096;const{N,F,faces,rest}=data;const fanStart=new Int32Array(N+1);for(let i=0;i<F*3;i++)fanStart[faces[i]+1]++;for(let i=0;i<N;i++)fanStart[i+1]+=fanStart[i];const fan=new Int32Array(F*3);const fill=fanStart.slice(0,N);for(let f=0;f<F;f++)for(let c=0;c<3;c++)fan[fill[faces[f*3+c]]++]=f;this.fanStart=fanStart;this.fan=fan;this.pos=new Float32Array(N*3);this.fn=new Float32Array(F*3);this.fu=new Float32Array(F*3);this.ao=new Float32Array(N);const soupRest=new Float32Array(F*6);for(let i=0;i<F*3;i++){soupRest[i*2]=rest[faces[i]*2];soupRest[i*2+1]=rest[faces[i]*2+1];}this.bRest=gl.createBuffer();gl.bindBuffer(gl.ARRAY_BUFFER,this.bRest);gl.bufferData(gl.ARRAY_BUFFER,soupRest,gl.STATIC_DRAW);this.quadVao=gl.createVertexArray();gl.bindVertexArray(this.quadVao);const qb=gl.createBuffer();gl.bindBuffer(gl.ARRAY_BUFFER,qb);gl.bufferData(gl.ARRAY_BUFFER,new Float32Array([-1,-1,1,-1,-1,1,1,1]),gl.STATIC_DRAW);for(const pr of[this.blurProg,this.shadowProg]){const l=gl.getAttribLocation(pr.p,\"aQ\");if(l>=0){gl.enableVertexAttribArray(l);gl.vertexAttribPointer(l,2,gl.FLOAT,false,0,0);}}gl.bindVertexArray(null);// neutral crease map until the procedural one is ready: level, no folds, no cracks\nthis.neutralTex=gl.createTexture();gl.bindTexture(gl.TEXTURE_2D,this.neutralTex);gl.texImage2D(gl.TEXTURE_2D,0,gl.RGBA,1,1,0,gl.RGBA,gl.UNSIGNED_BYTE,new Uint8Array([128,128,128,0]));}}// ---------- embedded data ----------\n// fold simulation (deflate + base64) and the baked crease overlay of the still sheet (JPEG)\nconst CRUMPLE_DATA=\"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\";const 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