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e=this.elements,t=e[0],i=e[1],r=e[2],s=e[3],o=e[4],a=e[5],l=e[6],c=e[7],h=e[8];return t*o*h-t*a*c-i*s*h+i*a*l+r*s*c-r*o*l}invert(){const e=this.elements,t=e[0],i=e[1],r=e[2],s=e[3],o=e[4],a=e[5],l=e[6],c=e[7],h=e[8],f=h*o-a*c,d=a*l-h*s,m=c*s-o*l,g=t*f+i*d+r*m;if(g===0)return this.set(0,0,0,0,0,0,0,0,0);const E=1/g;return e[0]=f*E,e[1]=(r*c-h*i)*E,e[2]=(a*i-r*o)*E,e[3]=d*E,e[4]=(h*t-r*l)*E,e[5]=(r*s-a*t)*E,e[6]=m*E,e[7]=(i*l-c*t)*E,e[8]=(o*t-i*s)*E,this}transpose(){let e;const t=this.elements;return e=t[1],t[1]=t[3],t[3]=e,e=t[2],t[2]=t[6],t[6]=e,e=t[5],t[5]=t[7],t[7]=e,this}getNormalMatrix(e){return this.setFromMatrix4(e).invert().transpose()}transposeIntoArray(e){const t=this.elements;return e[0]=t[0],e[1]=t[3],e[2]=t[6],e[3]=t[1],e[4]=t[4],e[5]=t[7],e[6]=t[2],e[7]=t[5],e[8]=t[8],this}setUvTransform(e,t,i,r,s,o,a){const l=Math.cos(s),c=Math.sin(s);return this.set(i*l,i*c,-i*(l*o+c*a)+o+e,-r*c,r*l,-r*(-c*o+l*a)+a+t,0,0,1),this}scale(e,t){return this.premultiply(f0.makeScale(e,t)),this}rotate(e){return this.premultiply(f0.makeRotation(-e)),this}translate(e,t){return this.premultiply(f0.makeTranslation(e,t)),this}makeTranslation(e,t){return e.isVector2?this.set(1,0,e.x,0,1,e.y,0,0,1):this.set(1,0,e,0,1,t,0,0,1),this}makeRotation(e){const t=Math.cos(e),i=Math.sin(e);return this.set(t,-i,0,i,t,0,0,0,1),this}makeScale(e,t){return this.set(e,0,0,0,t,0,0,0,1),this}equals(e){const t=this.elements,i=e.elements;for(let r=0;r<9;r++)if(t[r]!==i[r])return!1;return!0}fromArray(e,t=0){for(let i=0;i<9;i++)this.elements[i]=e[i+t];return this}toArray(e=[],t=0){const i=this.elements;return e[t]=i[0],e[t+1]=i[1],e[t+2]=i[2],e[t+3]=i[3],e[t+4]=i[4],e[t+5]=i[5],e[t+6]=i[6],e[t+7]=i[7],e[t+8]=i[8],e}clone(){return new this.constructor().fromArray(this.elements)}}const f0=new Ot;function rR(n){for(let e=n.length-1;e>=0;--e)if(n[e]>=65535)return!0;return!1}const x2={Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array};function yu(n,e){return new x2[n](e)}function df(n){return document.createElementNS("http://www.w3.org/1999/xhtml",n)}function sR(){const n=df("canvas");return n.style.display="block",n}const uT={};function Bp(n){n in uT||(uT[n]=!0)}const hT=new Ot().set(.8224621,.177538,0,.0331941,.9668058,0,.0170827,.0723974,.9105199),pT=new Ot().set(1.2249401,-.2249404,0,-.0420569,1.0420571,0,-.0196376,-.0786361,1.0982735),mm={[so]:{transfer:uf,primaries:hf,toReference:n=>n,fromReference:n=>n},[si]:{transfer:gn,primaries:hf,toReference:n=>n.convertSRGBToLinear(),fromReference:n=>n.convertLinearToSRGB()},[Of]:{transfer:uf,primaries:pf,toReference:n=>n.applyMatrix3(pT),fromReference:n=>n.applyMatrix3(hT)},[nA]:{transfer:gn,primaries:pf,toReference:n=>n.convertSRGBToLinear().applyMatrix3(pT),fromReference:n=>n.applyMatrix3(hT).convertLinearToSRGB()}},T2=new Set([so,Of]),an={enabled:!0,_workingColorSpace:so,get legacyMode(){return!this.enabled},set legacyMode(n){this.enabled=!n},get workingColorSpace(){return this._workingColorSpace},set workingColorSpace(n){if(!T2.has(n))throw new Error(`Unsupported working color space, "${n}".`);this._workingColorSpace=n},convert:function(n,e,t){if(this.enabled===!1||e===t||!e||!t)return n;const i=mm[e].toReference,r=mm[t].fromReference;return r(i(n))},fromWorkingColorSpace:function(n,e){return this.convert(n,this._workingColorSpace,e)},toWorkingColorSpace:function(n,e){return this.convert(n,e,this._workingColorSpace)},getPrimaries:function(n){return mm[n].primaries},getTransfer:function(n){return n===Tr?uf:mm[n].transfer}};function Ku(n){return n<.04045?n*.0773993808:Math.pow(n*.9478672986+.0521327014,2.4)}function d0(n){return n<.0031308?n*12.92:1.055*Math.pow(n,.41666)-.055}let Bc;class nw{static getDataURL(e){if(/^data:/i.test(e.src)||typeof HTMLCanvasElement>"u")return e.src;let t;if(e instanceof HTMLCanvasElement)t=e;else{Bc===void 0&&(Bc=df("canvas")),Bc.width=e.width,Bc.height=e.height;const i=Bc.getContext("2d");e instanceof ImageData?i.putImageData(e,0,0):i.drawImage(e,0,0,e.width,e.height),t=Bc}return t.width>2048||t.height>2048?t.toDataURL("image/jpeg",.6):t.toDataURL("image/png")}static sRGBToLinear(e){if(typeof HTMLImageElement<"u"&&e instanceof HTMLImageElement||typeof HTMLCanvasElement<"u"&&e instanceof HTMLCanvasElement||typeof ImageBitmap<"u"&&e instanceof ImageBitmap){const t=df("canvas");t.width=e.width,t.height=e.height;const i=t.getContext("2d");i.drawImage(e,0,0,e.width,e.height);const r=i.getImageData(0,0,e.width,e.height),s=r.data;for(let o=0;o<s.length;o++)s[o]=Ku(s[o]/255)*255;return i.putImageData(r,0,0),t}else if(e.data){const t=e.data.slice(0);for(let i=0;i<t.length;i++)t instanceof Uint8Array||t instanceof Uint8ClampedArray?t[i]=Math.floor(Ku(t[i]/255)*255):t[i]=Ku(t[i]);return{data:t,width:e.width,height:e.height}}else return e}}let J2=0;class Rl{constructor(e=null){this.isSource=!0,Object.defineProperty(this,"id",{value:J2++}),this.uuid=Br(),this.data=e,this.version=0}set needsUpdate(e){e===!0&&this.version++}toJSON(e){const t=e===void 0||typeof e=="string";if(!t&&e.images[this.uuid]!==void 0)return e.images[this.uuid];const i={uuid:this.uuid,url:""},r=this.data;if(r!==null){let s;if(Array.isArray(r)){s=[];for(let o=0,a=r.length;o<a;o++)r[o].isDataTexture?s.push(m0(r[o].image)):s.push(m0(r[o]))}else s=m0(r);i.url=s}return t||(e.images[this.uuid]=i),i}}function m0(n){return typeof HTMLImageElement<"u"&&n instanceof HTMLImageElement||typeof HTMLCanvasElement<"u"&&n instanceof HTMLCanvasElement||typeof ImageBitmap<"u"&&n instanceof ImageBitmap?nw.getDataURL(n):n.data?{data:Array.from(n.data),width:n.width,height:n.height,type:n.data.constructor.name}:{}}let I2=0;class fn extends co{constructor(e=fn.DEFAULT_IMAGE,t=fn.DEFAULT_MAPPING,i=oi,r=oi,s=pn,o=ro,a=bi,l=$s,c=fn.DEFAULT_ANISOTROPY,h=Tr){super(),this.isTexture=!0,Object.defineProperty(this,"id",{value:I2++}),this.uuid=Br(),this.name="",this.source=new Rl(e),this.mipmaps=[],this.mapping=t,this.channel=0,this.wrapS=i,this.wrapT=r,this.magFilter=s,this.minFilter=o,this.anisotropy=c,this.format=a,this.internalFormat=null,this.type=l,this.offset=new we(0,0),this.repeat=new we(1,1),this.center=new we(0,0),this.rotation=0,this.matrixAutoUpdate=!0,this.matrix=new Ot,this.generateMipmaps=!0,this.premultiplyAlpha=!1,this.flipY=!0,this.unpackAlignment=4,typeof h=="string"?this.colorSpace=h:(Bp("THREE.Texture: Property .encoding has been replaced by .colorSpace."),this.colorSpace=h===Da?si:Tr),this.userData={},this.version=0,this.onUpdate=null,this.isRenderTargetTexture=!1,this.needsPMREMUpdate=!1}get image(){return this.source.data}set image(e=null){this.source.data=e}updateMatrix(){this.matrix.setUvTransform(this.offset.x,this.offset.y,this.repeat.x,this.repeat.y,this.rotation,this.center.x,this.center.y)}clone(){return new this.constructor().copy(this)}copy(e){return this.name=e.name,this.source=e.source,this.mipmaps=e.mipmaps.slice(0),this.mapping=e.mapping,this.channel=e.channel,this.wrapS=e.wrapS,this.wrapT=e.wrapT,this.magFilter=e.magFilter,this.minFilter=e.minFilter,this.anisotropy=e.anisotropy,this.format=e.format,this.internalFormat=e.internalFormat,this.type=e.type,this.offset.copy(e.offset),this.repeat.copy(e.repeat),this.center.copy(e.center),this.rotation=e.rotation,this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrix.copy(e.matrix),this.generateMipmaps=e.generateMipmaps,this.premultiplyAlpha=e.premultiplyAlpha,this.flipY=e.flipY,this.unpackAlignment=e.unpackAlignment,this.colorSpace=e.colorSpace,this.userData=JSON.parse(JSON.stringify(e.userData)),this.needsUpdate=!0,this}toJSON(e){const t=e===void 0||typeof e=="string";if(!t&&e.textures[this.uuid]!==void 0)return e.textures[this.uuid];const i={metadata:{version:4.6,type:"Texture",generator:"Texture.toJSON"},uuid:this.uuid,name:this.name,image:this.source.toJSON(e).uuid,mapping:this.mapping,channel:this.channel,repeat:[this.repeat.x,this.repeat.y],offset:[this.offset.x,this.offset.y],center:[this.center.x,this.center.y],rotation:this.rotation,wrap:[this.wrapS,this.wrapT],format:this.format,internalFormat:this.internalFormat,type:this.type,colorSpace:this.colorSpace,minFilter:this.minFilter,magFilter:this.magFilter,anisotropy:this.anisotropy,flipY:this.flipY,generateMipmaps:this.generateMipmaps,premultiplyAlpha:this.premultiplyAlpha,unpackAlignment:this.unpackAlignment};return Object.keys(this.userData).length>0&&(i.userData=this.userData),t||(e.textures[this.uuid]=i),i}dispose(){this.dispatchEvent({type:"dispose"})}transformUv(e){if(this.mapping!==_g)return e;if(e.applyMatrix3(this.matrix),e.x<0||e.x>1)switch(this.wrapS){case io:e.x=e.x-Math.floor(e.x);break;case oi:e.x=e.x<0?0:1;break;case Gu:Math.abs(Math.floor(e.x)%2)===1?e.x=Math.ceil(e.x)-e.x:e.x=e.x-Math.floor(e.x);break}if(e.y<0||e.y>1)switch(this.wrapT){case io:e.y=e.y-Math.floor(e.y);break;case oi:e.y=e.y<0?0:1;break;case Gu:Math.abs(Math.floor(e.y)%2)===1?e.y=Math.ceil(e.y)-e.y:e.y=e.y-Math.floor(e.y);break}return this.flipY&&(e.y=1-e.y),e}set needsUpdate(e){e===!0&&(this.version++,this.source.needsUpdate=!0)}get encoding(){return Bp("THREE.Texture: Property .encoding has been replaced by .colorSpace."),this.colorSpace===si?Da:$U}set encoding(e){Bp("THREE.Texture: Property .encoding has been replaced by .colorSpace."),this.colorSpace=e===Da?si:Tr}}fn.DEFAULT_IMAGE=null;fn.DEFAULT_MAPPING=_g;fn.DEFAULT_ANISOTROPY=1;class $t{constructor(e=0,t=0,i=0,r=1){$t.prototype.isVector4=!0,this.x=e,this.y=t,this.z=i,this.w=r}get width(){return this.z}set width(e){this.z=e}get height(){return this.w}set height(e){this.w=e}set(e,t,i,r){return this.x=e,this.y=t,this.z=i,this.w=r,this}setScalar(e){return this.x=e,this.y=e,this.z=e,this.w=e,this}setX(e){return this.x=e,this}setY(e){return this.y=e,this}setZ(e){return this.z=e,this}setW(e){return this.w=e,this}setComponent(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;case 3:this.w=t;break;default:throw new Error("index is out of range: "+e)}return this}getComponent(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;case 3:return this.w;default:throw new Error("index is out of range: "+e)}}clone(){return new this.constructor(this.x,this.y,this.z,this.w)}copy(e){return this.x=e.x,this.y=e.y,this.z=e.z,this.w=e.w!==void 0?e.w:1,this}add(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this.w+=e.w,this}addScalar(e){return this.x+=e,this.y+=e,this.z+=e,this.w+=e,this}addVectors(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this.w=e.w+t.w,this}addScaledVector(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this.w+=e.w*t,this}sub(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this.w-=e.w,this}subScalar(e){return this.x-=e,this.y-=e,this.z-=e,this.w-=e,this}subVectors(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this.w=e.w-t.w,this}multiply(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this.w*=e.w,this}multiplyScalar(e){return this.x*=e,this.y*=e,this.z*=e,this.w*=e,this}applyMatrix4(e){const t=this.x,i=this.y,r=this.z,s=this.w,o=e.elements;return this.x=o[0]*t+o[4]*i+o[8]*r+o[12]*s,this.y=o[1]*t+o[5]*i+o[9]*r+o[13]*s,this.z=o[2]*t+o[6]*i+o[10]*r+o[14]*s,this.w=o[3]*t+o[7]*i+o[11]*r+o[15]*s,this}divideScalar(e){return this.multiplyScalar(1/e)}setAxisAngleFromQuaternion(e){this.w=2*Math.acos(e.w);const t=Math.sqrt(1-e.w*e.w);return t<1e-4?(this.x=1,this.y=0,this.z=0):(this.x=e.x/t,this.y=e.y/t,this.z=e.z/t),this}setAxisAngleFromRotationMatrix(e){let t,i,r,s;const l=e.elements,c=l[0],h=l[4],f=l[8],d=l[1],m=l[5],g=l[9],E=l[2],C=l[6],S=l[10];if(Math.abs(h-d)<.01&&Math.abs(f-E)<.01&&Math.abs(g-C)<.01){if(Math.abs(h+d)<.1&&Math.abs(f+E)<.1&&Math.abs(g+C)<.1&&Math.abs(c+m+S-3)<.1)return this.set(1,0,0,0),this;t=Math.PI;const y=(c+1)/2,w=(m+1)/2,x=(S+1)/2,k=(h+d)/4,I=(f+E)/4,R=(g+C)/4;return y>w&&y>x?y<.01?(i=0,r=.707106781,s=.707106781):(i=Math.sqrt(y),r=k/i,s=I/i):w>x?w<.01?(i=.707106781,r=0,s=.707106781):(r=Math.sqrt(w),i=k/r,s=R/r):x<.01?(i=.707106781,r=.707106781,s=0):(s=Math.sqrt(x),i=I/s,r=R/s),this.set(i,r,s,t),this}let v=Math.sqrt((C-g)*(C-g)+(f-E)*(f-E)+(d-h)*(d-h));return Math.abs(v)<.001&&(v=1),this.x=(C-g)/v,this.y=(f-E)/v,this.z=(d-h)/v,this.w=Math.acos((c+m+S-1)/2),this}min(e){return this.x=Math.min(this.x,e.x),this.y=Math.min(this.y,e.y),this.z=Math.min(this.z,e.z),this.w=Math.min(this.w,e.w),this}max(e){return this.x=Math.max(this.x,e.x),this.y=Math.max(this.y,e.y),this.z=Math.max(this.z,e.z),this.w=Math.max(this.w,e.w),this}clamp(e,t){return this.x=Math.max(e.x,Math.min(t.x,this.x)),this.y=Math.max(e.y,Math.min(t.y,this.y)),this.z=Math.max(e.z,Math.min(t.z,this.z)),this.w=Math.max(e.w,Math.min(t.w,this.w)),this}clampScalar(e,t){return this.x=Math.max(e,Math.min(t,this.x)),this.y=Math.max(e,Math.min(t,this.y)),this.z=Math.max(e,Math.min(t,this.z)),this.w=Math.max(e,Math.min(t,this.w)),this}clampLength(e,t){const i=this.length();return this.divideScalar(i||1).multiplyScalar(Math.max(e,Math.min(t,i)))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this.w=Math.floor(this.w),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this.w=Math.ceil(this.w),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this.w=Math.round(this.w),this}roundToZero(){return this.x=Math.trunc(this.x),this.y=Math.trunc(this.y),this.z=Math.trunc(this.z),this.w=Math.trunc(this.w),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this.w=-this.w,this}dot(e){return this.x*e.x+this.y*e.y+this.z*e.z+this.w*e.w}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z+this.w*this.w)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)+Math.abs(this.w)}normalize(){return this.divideScalar(this.length()||1)}setLength(e){return this.normalize().multiplyScalar(e)}lerp(e,t){return this.x+=(e.x-this.x)*t,this.y+=(e.y-this.y)*t,this.z+=(e.z-this.z)*t,this.w+=(e.w-this.w)*t,this}lerpVectors(e,t,i){return this.x=e.x+(t.x-e.x)*i,this.y=e.y+(t.y-e.y)*i,this.z=e.z+(t.z-e.z)*i,this.w=e.w+(t.w-e.w)*i,this}equals(e){return e.x===this.x&&e.y===this.y&&e.z===this.z&&e.w===this.w}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this.w=e[t+3],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e[t+3]=this.w,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this.w=e.getW(t),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this.w=Math.random(),this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z,yield this.w}}class oR extends co{constructor(e=1,t=1,i={}){super(),this.isRenderTarget=!0,this.width=e,this.height=t,this.depth=1,this.scissor=new $t(0,0,e,t),this.scissorTest=!1,this.viewport=new $t(0,0,e,t);const r={width:e,height:t,depth:1};i.encoding!==void 0&&(Bp("THREE.WebGLRenderTarget: option.encoding has been replaced by option.colorSpace."),i.colorSpace=i.encoding===Da?si:Tr),i=Object.assign({generateMipmaps:!1,internalFormat:null,minFilter:pn,depthBuffer:!0,stencilBuffer:!1,depthTexture:null,samples:0},i),this.texture=new fn(r,i.mapping,i.wrapS,i.wrapT,i.magFilter,i.minFilter,i.format,i.type,i.anisotropy,i.colorSpace),this.texture.isRenderTargetTexture=!0,this.texture.flipY=!1,this.texture.generateMipmaps=i.generateMipmaps,this.texture.internalFormat=i.internalFormat,this.depthBuffer=i.depthBuffer,this.stencilBuffer=i.stencilBuffer,this.depthTexture=i.depthTexture,this.samples=i.samples}setSize(e,t,i=1){(this.width!==e||this.height!==t||this.depth!==i)&&(this.width=e,this.height=t,this.depth=i,this.texture.image.width=e,this.texture.image.height=t,this.texture.image.depth=i,this.dispose()),this.viewport.set(0,0,e,t),this.scissor.set(0,0,e,t)}clone(){return new this.constructor().copy(this)}copy(e){this.width=e.width,this.height=e.height,this.depth=e.depth,this.scissor.copy(e.scissor),this.scissorTest=e.scissorTest,this.viewport.copy(e.viewport),this.texture=e.texture.clone(),this.texture.isRenderTargetTexture=!0;const t=Object.assign({},e.texture.image);return this.texture.source=new Rl(t),this.depthBuffer=e.depthBuffer,this.stencilBuffer=e.stencilBuffer,e.depthTexture!==null&&(this.depthTexture=e.depthTexture.clone()),this.samples=e.samples,this}dispose(){this.dispatchEvent({type:"dispose"})}}class Is extends oR{constructor(e=1,t=1,i={}){super(e,t,i),this.isWebGLRenderTarget=!0}}class iA extends fn{constructor(e=null,t=1,i=1,r=1){super(null),this.isDataArrayTexture=!0,this.image={data:e,width:t,height:i,depth:r},this.magFilter=Wn,this.minFilter=Wn,this.wrapR=oi,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}class L2 extends Is{constructor(e=1,t=1,i=1,r={}){super(e,t,r),this.isWebGLArrayRenderTarget=!0,this.depth=i,this.texture=new iA(null,e,t,i),this.texture.isRenderTargetTexture=!0}}class iw extends fn{constructor(e=null,t=1,i=1,r=1){super(null),this.isData3DTexture=!0,this.image={data:e,width:t,height:i,depth:r},this.magFilter=Wn,this.minFilter=Wn,this.wrapR=oi,this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}class B2 extends Is{constructor(e=1,t=1,i=1,r={}){super(e,t,r),this.isWebGL3DRenderTarget=!0,this.depth=i,this.texture=new iw(null,e,t,i),this.texture.isRenderTargetTexture=!0}}class K2 extends Is{constructor(e=1,t=1,i=1,r={}){super(e,t,r),this.isWebGLMultipleRenderTargets=!0;const s=this.texture;this.texture=[];for(let o=0;o<i;o++)this.texture[o]=s.clone(),this.texture[o].isRenderTargetTexture=!0}setSize(e,t,i=1){if(this.width!==e||this.height!==t||this.depth!==i){this.width=e,this.height=t,this.depth=i;for(let r=0,s=this.texture.length;r<s;r++)this.texture[r].image.width=e,this.texture[r].image.height=t,this.texture[r].image.depth=i;this.dispose()}this.viewport.set(0,0,e,t),this.scissor.set(0,0,e,t)}copy(e){this.dispose(),this.width=e.width,this.height=e.height,this.depth=e.depth,this.scissor.copy(e.scissor),this.scissorTest=e.scissorTest,this.viewport.copy(e.viewport),this.depthBuffer=e.depthBuffer,this.stencilBuffer=e.stencilBuffer,e.depthTexture!==null&&(this.depthTexture=e.depthTexture.clone()),this.texture.length=0;for(let t=0,i=e.texture.length;t<i;t++)this.texture[t]=e.texture[t].clone(),this.texture[t].isRenderTargetTexture=!0;return this}}class zn{constructor(e=0,t=0,i=0,r=1){this.isQuaternion=!0,this._x=e,this._y=t,this._z=i,this._w=r}static slerpFlat(e,t,i,r,s,o,a){let l=i[r+0],c=i[r+1],h=i[r+2],f=i[r+3];const d=s[o+0],m=s[o+1],g=s[o+2],E=s[o+3];if(a===0){e[t+0]=l,e[t+1]=c,e[t+2]=h,e[t+3]=f;return}if(a===1){e[t+0]=d,e[t+1]=m,e[t+2]=g,e[t+3]=E;return}if(f!==E||l!==d||c!==m||h!==g){let C=1-a;const S=l*d+c*m+h*g+f*E,v=S>=0?1:-1,y=1-S*S;if(y>Number.EPSILON){const x=Math.sqrt(y),k=Math.atan2(x,S*v);C=Math.sin(C*k)/x,a=Math.sin(a*k)/x}const w=a*v;if(l=l*C+d*w,c=c*C+m*w,h=h*C+g*w,f=f*C+E*w,C===1-a){const x=1/Math.sqrt(l*l+c*c+h*h+f*f);l*=x,c*=x,h*=x,f*=x}}e[t]=l,e[t+1]=c,e[t+2]=h,e[t+3]=f}static multiplyQuaternionsFlat(e,t,i,r,s,o){const a=i[r],l=i[r+1],c=i[r+2],h=i[r+3],f=s[o],d=s[o+1],m=s[o+2],g=s[o+3];return e[t]=a*g+h*f+l*m-c*d,e[t+1]=l*g+h*d+c*f-a*m,e[t+2]=c*g+h*m+a*d-l*f,e[t+3]=h*g-a*f-l*d-c*m,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,i,r){return this._x=e,this._y=t,this._z=i,this._w=r,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._w)}copy(e){return this._x=e.x,this._y=e.y,this._z=e.z,this._w=e.w,this._onChangeCallback(),this}setFromEuler(e,t){const i=e._x,r=e._y,s=e._z,o=e._order,a=Math.cos,l=Math.sin,c=a(i/2),h=a(r/2),f=a(s/2),d=l(i/2),m=l(r/2),g=l(s/2);switch(o){case"XYZ":this._x=d*h*f+c*m*g,this._y=c*m*f-d*h*g,this._z=c*h*g+d*m*f,this._w=c*h*f-d*m*g;break;case"YXZ":this._x=d*h*f+c*m*g,this._y=c*m*f-d*h*g,this._z=c*h*g-d*m*f,this._w=c*h*f+d*m*g;break;case"ZXY":this._x=d*h*f-c*m*g,this._y=c*m*f+d*h*g,this._z=c*h*g+d*m*f,this._w=c*h*f-d*m*g;break;case"ZYX":this._x=d*h*f-c*m*g,this._y=c*m*f+d*h*g,this._z=c*h*g-d*m*f,this._w=c*h*f+d*m*g;break;case"YZX":this._x=d*h*f+c*m*g,this._y=c*m*f+d*h*g,this._z=c*h*g-d*m*f,this._w=c*h*f-d*m*g;break;case"XZY":this._x=d*h*f-c*m*g,this._y=c*m*f-d*h*g,this._z=c*h*g+d*m*f,this._w=c*h*f+d*m*g;break;default:}return t!==!1&&this._onChangeCallback(),this}setFromAxisAngle(e,t){const i=t/2,r=Math.sin(i);return this._x=e.x*r,this._y=e.y*r,this._z=e.z*r,this._w=Math.cos(i),this._onChangeCallback(),this}setFromRotationMatrix(e){const t=e.elements,i=t[0],r=t[4],s=t[8],o=t[1],a=t[5],l=t[9],c=t[2],h=t[6],f=t[10],d=i+a+f;if(d>0){const m=.5/Math.sqrt(d+1);this._w=.25/m,this._x=(h-l)*m,this._y=(s-c)*m,this._z=(o-r)*m}else if(i>a&&i>f){const m=2*Math.sqrt(1+i-a-f);this._w=(h-l)/m,this._x=.25*m,this._y=(r+o)/m,this._z=(s+c)/m}else if(a>f){const m=2*Math.sqrt(1+a-i-f);this._w=(s-c)/m,this._x=(r+o)/m,this._y=.25*m,this._z=(l+h)/m}else{const m=2*Math.sqrt(1+f-i-a);this._w=(o-r)/m,this._x=(s+c)/m,this._y=(l+h)/m,this._z=.25*m}return this._onChangeCallback(),this}setFromUnitVectors(e,t){let i=e.dot(t)+1;return i<Number.EPSILON?(i=0,Math.abs(e.x)>Math.abs(e.z)?(this._x=-e.y,this._y=e.x,this._z=0,this._w=i):(this._x=0,this._y=-e.z,this._z=e.y,this._w=i)):(this._x=e.y*t.z-e.z*t.y,this._y=e.z*t.x-e.x*t.z,this._z=e.x*t.y-e.y*t.x,this._w=i),this.normalize()}angleTo(e){return 2*Math.acos(Math.abs(Hn(this.dot(e),-1,1)))}rotateTowards(e,t){const i=this.angleTo(e);if(i===0)return this;const r=Math.min(1,t/i);return this.slerp(e,r),this}identity(){return this.set(0,0,0,1)}invert(){return this.conjugate()}conjugate(){return this._x*=-1,this._y*=-1,this._z*=-1,this._onChangeCallback(),this}dot(e){return this._x*e._x+this._y*e._y+this._z*e._z+this._w*e._w}lengthSq(){return this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w}length(){return Math.sqrt(this._x*this._x+this._y*this._y+this._z*this._z+this._w*this._w)}normalize(){let e=this.length();return e===0?(this._x=0,this._y=0,this._z=0,this._w=1):(e=1/e,this._x=this._x*e,this._y=this._y*e,this._z=this._z*e,this._w=this._w*e),this._onChangeCallback(),this}multiply(e){return this.multiplyQuaternions(this,e)}premultiply(e){return this.multiplyQuaternions(e,this)}multiplyQuaternions(e,t){const i=e._x,r=e._y,s=e._z,o=e._w,a=t._x,l=t._y,c=t._z,h=t._w;return this._x=i*h+o*a+r*c-s*l,this._y=r*h+o*l+s*a-i*c,this._z=s*h+o*c+i*l-r*a,this._w=o*h-i*a-r*l-s*c,this._onChangeCallback(),this}slerp(e,t){if(t===0)return this;if(t===1)return this.copy(e);const i=this._x,r=this._y,s=this._z,o=this._w;let a=o*e._w+i*e._x+r*e._y+s*e._z;if(a<0?(this._w=-e._w,this._x=-e._x,this._y=-e._y,this._z=-e._z,a=-a):this.copy(e),a>=1)return this._w=o,this._x=i,this._y=r,this._z=s,this;const l=1-a*a;if(l<=Number.EPSILON){const m=1-t;return this._w=m*o+t*this._w,this._x=m*i+t*this._x,this._y=m*r+t*this._y,this._z=m*s+t*this._z,this.normalize(),this._onChangeCallback(),this}const c=Math.sqrt(l),h=Math.atan2(c,a),f=Math.sin((1-t)*h)/c,d=Math.sin(t*h)/c;return this._w=o*f+this._w*d,this._x=i*f+this._x*d,this._y=r*f+this._y*d,this._z=s*f+this._z*d,this._onChangeCallback(),this}slerpQuaternions(e,t,i){return this.copy(e).slerp(t,i)}random(){const e=Math.random(),t=Math.sqrt(1-e),i=Math.sqrt(e),r=2*Math.PI*Math.random(),s=2*Math.PI*Math.random();return this.set(t*Math.cos(r),i*Math.sin(s),i*Math.cos(s),t*Math.sin(r))}equals(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._w===this._w}fromArray(e,t=0){return this._x=e[t],this._y=e[t+1],this._z=e[t+2],this._w=e[t+3],this._onChangeCallback(),this}toArray(e=[],t=0){return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._w,e}fromBufferAttribute(e,t){return this._x=e.getX(t),this._y=e.getY(t),this._z=e.getZ(t),this._w=e.getW(t),this}toJSON(){return this.toArray()}_onChange(e){return this._onChangeCallback=e,this}_onChangeCallback(){}*[Symbol.iterator](){yield this._x,yield this._y,yield this._z,yield this._w}}class N{constructor(e=0,t=0,i=0){N.prototype.isVector3=!0,this.x=e,this.y=t,this.z=i}set(e,t,i){return i===void 0&&(i=this.z),this.x=e,this.y=t,this.z=i,this}setScalar(e){return this.x=e,this.y=e,this.z=e,this}setX(e){return this.x=e,this}setY(e){return this.y=e,this}setZ(e){return this.z=e,this}setComponent(e,t){switch(e){case 0:this.x=t;break;case 1:this.y=t;break;case 2:this.z=t;break;default:throw new Error("index is out of range: "+e)}return this}getComponent(e){switch(e){case 0:return this.x;case 1:return this.y;case 2:return this.z;default:throw new Error("index is out of range: "+e)}}clone(){return new this.constructor(this.x,this.y,this.z)}copy(e){return this.x=e.x,this.y=e.y,this.z=e.z,this}add(e){return this.x+=e.x,this.y+=e.y,this.z+=e.z,this}addScalar(e){return this.x+=e,this.y+=e,this.z+=e,this}addVectors(e,t){return this.x=e.x+t.x,this.y=e.y+t.y,this.z=e.z+t.z,this}addScaledVector(e,t){return this.x+=e.x*t,this.y+=e.y*t,this.z+=e.z*t,this}sub(e){return this.x-=e.x,this.y-=e.y,this.z-=e.z,this}subScalar(e){return this.x-=e,this.y-=e,this.z-=e,this}subVectors(e,t){return this.x=e.x-t.x,this.y=e.y-t.y,this.z=e.z-t.z,this}multiply(e){return this.x*=e.x,this.y*=e.y,this.z*=e.z,this}multiplyScalar(e){return this.x*=e,this.y*=e,this.z*=e,this}multiplyVectors(e,t){return this.x=e.x*t.x,this.y=e.y*t.y,this.z=e.z*t.z,this}applyEuler(e){return this.applyQuaternion(fT.setFromEuler(e))}applyAxisAngle(e,t){return this.applyQuaternion(fT.setFromAxisAngle(e,t))}applyMatrix3(e){const t=this.x,i=this.y,r=this.z,s=e.elements;return this.x=s[0]*t+s[3]*i+s[6]*r,this.y=s[1]*t+s[4]*i+s[7]*r,this.z=s[2]*t+s[5]*i+s[8]*r,this}applyNormalMatrix(e){return this.applyMatrix3(e).normalize()}applyMatrix4(e){const t=this.x,i=this.y,r=this.z,s=e.elements,o=1/(s[3]*t+s[7]*i+s[11]*r+s[15]);return this.x=(s[0]*t+s[4]*i+s[8]*r+s[12])*o,this.y=(s[1]*t+s[5]*i+s[9]*r+s[13])*o,this.z=(s[2]*t+s[6]*i+s[10]*r+s[14])*o,this}applyQuaternion(e){const t=this.x,i=this.y,r=this.z,s=e.x,o=e.y,a=e.z,l=e.w,c=2*(o*r-a*i),h=2*(a*t-s*r),f=2*(s*i-o*t);return this.x=t+l*c+o*f-a*h,this.y=i+l*h+a*c-s*f,this.z=r+l*f+s*h-o*c,this}project(e){return this.applyMatrix4(e.matrixWorldInverse).applyMatrix4(e.projectionMatrix)}unproject(e){return this.applyMatrix4(e.projectionMatrixInverse).applyMatrix4(e.matrixWorld)}transformDirection(e){const t=this.x,i=this.y,r=this.z,s=e.elements;return this.x=s[0]*t+s[4]*i+s[8]*r,this.y=s[1]*t+s[5]*i+s[9]*r,this.z=s[2]*t+s[6]*i+s[10]*r,this.normalize()}divide(e){return this.x/=e.x,this.y/=e.y,this.z/=e.z,this}divideScalar(e){return this.multiplyScalar(1/e)}min(e){return this.x=Math.min(this.x,e.x),this.y=Math.min(this.y,e.y),this.z=Math.min(this.z,e.z),this}max(e){return this.x=Math.max(this.x,e.x),this.y=Math.max(this.y,e.y),this.z=Math.max(this.z,e.z),this}clamp(e,t){return this.x=Math.max(e.x,Math.min(t.x,this.x)),this.y=Math.max(e.y,Math.min(t.y,this.y)),this.z=Math.max(e.z,Math.min(t.z,this.z)),this}clampScalar(e,t){return this.x=Math.max(e,Math.min(t,this.x)),this.y=Math.max(e,Math.min(t,this.y)),this.z=Math.max(e,Math.min(t,this.z)),this}clampLength(e,t){const i=this.length();return this.divideScalar(i||1).multiplyScalar(Math.max(e,Math.min(t,i)))}floor(){return this.x=Math.floor(this.x),this.y=Math.floor(this.y),this.z=Math.floor(this.z),this}ceil(){return this.x=Math.ceil(this.x),this.y=Math.ceil(this.y),this.z=Math.ceil(this.z),this}round(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this.z=Math.round(this.z),this}roundToZero(){return this.x=Math.trunc(this.x),this.y=Math.trunc(this.y),this.z=Math.trunc(this.z),this}negate(){return this.x=-this.x,this.y=-this.y,this.z=-this.z,this}dot(e){return this.x*e.x+this.y*e.y+this.z*e.z}lengthSq(){return this.x*this.x+this.y*this.y+this.z*this.z}length(){return Math.sqrt(this.x*this.x+this.y*this.y+this.z*this.z)}manhattanLength(){return Math.abs(this.x)+Math.abs(this.y)+Math.abs(this.z)}normalize(){return this.divideScalar(this.length()||1)}setLength(e){return this.normalize().multiplyScalar(e)}lerp(e,t){return this.x+=(e.x-this.x)*t,this.y+=(e.y-this.y)*t,this.z+=(e.z-this.z)*t,this}lerpVectors(e,t,i){return this.x=e.x+(t.x-e.x)*i,this.y=e.y+(t.y-e.y)*i,this.z=e.z+(t.z-e.z)*i,this}cross(e){return this.crossVectors(this,e)}crossVectors(e,t){const i=e.x,r=e.y,s=e.z,o=t.x,a=t.y,l=t.z;return this.x=r*l-s*a,this.y=s*o-i*l,this.z=i*a-r*o,this}projectOnVector(e){const t=e.lengthSq();if(t===0)return this.set(0,0,0);const i=e.dot(this)/t;return this.copy(e).multiplyScalar(i)}projectOnPlane(e){return S0.copy(this).projectOnVector(e),this.sub(S0)}reflect(e){return this.sub(S0.copy(e).multiplyScalar(2*this.dot(e)))}angleTo(e){const t=Math.sqrt(this.lengthSq()*e.lengthSq());if(t===0)return Math.PI/2;const i=this.dot(e)/t;return Math.acos(Hn(i,-1,1))}distanceTo(e){return Math.sqrt(this.distanceToSquared(e))}distanceToSquared(e){const t=this.x-e.x,i=this.y-e.y,r=this.z-e.z;return t*t+i*i+r*r}manhattanDistanceTo(e){return Math.abs(this.x-e.x)+Math.abs(this.y-e.y)+Math.abs(this.z-e.z)}setFromSpherical(e){return this.setFromSphericalCoords(e.radius,e.phi,e.theta)}setFromSphericalCoords(e,t,i){const r=Math.sin(t)*e;return this.x=r*Math.sin(i),this.y=Math.cos(t)*e,this.z=r*Math.cos(i),this}setFromCylindrical(e){return this.setFromCylindricalCoords(e.radius,e.theta,e.y)}setFromCylindricalCoords(e,t,i){return this.x=e*Math.sin(t),this.y=i,this.z=e*Math.cos(t),this}setFromMatrixPosition(e){const t=e.elements;return this.x=t[12],this.y=t[13],this.z=t[14],this}setFromMatrixScale(e){const t=this.setFromMatrixColumn(e,0).length(),i=this.setFromMatrixColumn(e,1).length(),r=this.setFromMatrixColumn(e,2).length();return this.x=t,this.y=i,this.z=r,this}setFromMatrixColumn(e,t){return this.fromArray(e.elements,t*4)}setFromMatrix3Column(e,t){return this.fromArray(e.elements,t*3)}setFromEuler(e){return this.x=e._x,this.y=e._y,this.z=e._z,this}setFromColor(e){return this.x=e.r,this.y=e.g,this.z=e.b,this}equals(e){return e.x===this.x&&e.y===this.y&&e.z===this.z}fromArray(e,t=0){return this.x=e[t],this.y=e[t+1],this.z=e[t+2],this}toArray(e=[],t=0){return e[t]=this.x,e[t+1]=this.y,e[t+2]=this.z,e}fromBufferAttribute(e,t){return this.x=e.getX(t),this.y=e.getY(t),this.z=e.getZ(t),this}random(){return this.x=Math.random(),this.y=Math.random(),this.z=Math.random(),this}randomDirection(){const e=(Math.random()-.5)*2,t=Math.random()*Math.PI*2,i=Math.sqrt(1-e**2);return this.x=i*Math.cos(t),this.y=i*Math.sin(t),this.z=e,this}*[Symbol.iterator](){yield this.x,yield this.y,yield this.z}}const S0=new N,fT=new zn;class Pi{constructor(e=new N(1/0,1/0,1/0),t=new N(-1/0,-1/0,-1/0)){this.isBox3=!0,this.min=e,this.max=t}set(e,t){return this.min.copy(e),this.max.copy(t),this}setFromArray(e){this.makeEmpty();for(let t=0,i=e.length;t<i;t+=3)this.expandByPoint(ds.fromArray(e,t));return this}setFromBufferAttribute(e){this.makeEmpty();for(let t=0,i=e.count;t<i;t++)this.expandByPoint(ds.fromBufferAttribute(e,t));return this}setFromPoints(e){this.makeEmpty();for(let t=0,i=e.length;t<i;t++)this.expandByPoint(e[t]);return this}setFromCenterAndSize(e,t){const i=ds.copy(t).multiplyScalar(.5);return this.min.copy(e).sub(i),this.max.copy(e).add(i),this}setFromObject(e,t=!1){return this.makeEmpty(),this.expandByObject(e,t)}clone(){return new this.constructor().copy(this)}copy(e){return this.min.copy(e.min),this.max.copy(e.max),this}makeEmpty(){return this.min.x=this.min.y=this.min.z=1/0,this.max.x=this.max.y=this.max.z=-1/0,this}isEmpty(){return this.max.x<this.min.x||this.max.y<this.min.y||this.max.z<this.min.z}getCenter(e){return this.isEmpty()?e.set(0,0,0):e.addVectors(this.min,this.max).multiplyScalar(.5)}getSize(e){return this.isEmpty()?e.set(0,0,0):e.subVectors(this.max,this.min)}expandByPoint(e){return this.min.min(e),this.max.max(e),this}expandByVector(e){return this.min.sub(e),this.max.add(e),this}expandByScalar(e){return this.min.addScalar(-e),this.max.addScalar(e),this}expandByObject(e,t=!1){e.updateWorldMatrix(!1,!1);const i=e.geometry;if(i!==void 0){const s=i.getAttribute("position");if(t===!0&&s!==void 0&&e.isInstancedMesh!==!0)for(let o=0,a=s.count;o<a;o++)e.isMesh===!0?e.getVertexPosition(o,ds):ds.fromBufferAttribute(s,o),ds.applyMatrix4(e.matrixWorld),this.expandByPoint(ds);else e.boundingBox!==void 0?(e.boundingBox===null&&e.computeBoundingBox(),Sm.copy(e.boundingBox)):(i.boundingBox===null&&i.computeBoundingBox(),Sm.copy(i.boundingBox)),Sm.applyMatrix4(e.matrixWorld),this.union(Sm)}const r=e.children;for(let s=0,o=r.length;s<o;s++)this.expandByObject(r[s],t);return this}containsPoint(e){return!(e.x<this.min.x||e.x>this.max.x||e.y<this.min.y||e.y>this.max.y||e.z<this.min.z||e.z>this.max.z)}containsBox(e){return this.min.x<=e.min.x&&e.max.x<=this.max.x&&this.min.y<=e.min.y&&e.max.y<=this.max.y&&this.min.z<=e.min.z&&e.max.z<=this.max.z}getParameter(e,t){return t.set((e.x-this.min.x)/(this.max.x-this.min.x),(e.y-this.min.y)/(this.max.y-this.min.y),(e.z-this.min.z)/(this.max.z-this.min.z))}intersectsBox(e){return!(e.max.x<this.min.x||e.min.x>this.max.x||e.max.y<this.min.y||e.min.y>this.max.y||e.max.z<this.min.z||e.min.z>this.max.z)}intersectsSphere(e){return this.clampPoint(e.center,ds),ds.distanceToSquared(e.center)<=e.radius*e.radius}intersectsPlane(e){let t,i;return e.normal.x>0?(t=e.normal.x*this.min.x,i=e.normal.x*this.max.x):(t=e.normal.x*this.max.x,i=e.normal.x*this.min.x),e.normal.y>0?(t+=e.normal.y*this.min.y,i+=e.normal.y*this.max.y):(t+=e.normal.y*this.max.y,i+=e.normal.y*this.min.y),e.normal.z>0?(t+=e.normal.z*this.min.z,i+=e.normal.z*this.max.z):(t+=e.normal.z*this.max.z,i+=e.normal.z*this.min.z),t<=-e.constant&&i>=-e.constant}intersectsTriangle(e){if(this.isEmpty())return!1;this.getCenter(Yh),gm.subVectors(this.max,Yh),Kc.subVectors(e.a,Yh),Rc.subVectors(e.b,Yh),Dc.subVectors(e.c,Yh),oa.subVectors(Rc,Kc),aa.subVectors(Dc,Rc),cl.subVectors(Kc,Dc);let t=[0,-oa.z,oa.y,0,-aa.z,aa.y,0,-cl.z,cl.y,oa.z,0,-oa.x,aa.z,0,-aa.x,cl.z,0,-cl.x,-oa.y,oa.x,0,-aa.y,aa.x,0,-cl.y,cl.x,0];return!g0(t,Kc,Rc,Dc,gm)||(t=[1,0,0,0,1,0,0,0,1],!g0(t,Kc,Rc,Dc,gm))?!1:(Am.crossVectors(oa,aa),t=[Am.x,Am.y,Am.z],g0(t,Kc,Rc,Dc,gm))}clampPoint(e,t){return t.copy(e).clamp(this.min,this.max)}distanceToPoint(e){return this.clampPoint(e,ds).distanceTo(e)}getBoundingSphere(e){return this.isEmpty()?e.makeEmpty():(this.getCenter(e.center),e.radius=this.getSize(ds).length()*.5),e}intersect(e){return this.min.max(e.min),this.max.min(e.max),this.isEmpty()&&this.makeEmpty(),this}union(e){return this.min.min(e.min),this.max.max(e.max),this}applyMatrix4(e){return this.isEmpty()?this:(yo[0].set(this.min.x,this.min.y,this.min.z).applyMatrix4(e),yo[1].set(this.min.x,this.min.y,this.max.z).applyMatrix4(e),yo[2].set(this.min.x,this.max.y,this.min.z).applyMatrix4(e),yo[3].set(this.min.x,this.max.y,this.max.z).applyMatrix4(e),yo[4].set(this.max.x,this.min.y,this.min.z).applyMatrix4(e),yo[5].set(this.max.x,this.min.y,this.max.z).applyMatrix4(e),yo[6].set(this.max.x,this.max.y,this.min.z).applyMatrix4(e),yo[7].set(this.max.x,this.max.y,this.max.z).applyMatrix4(e),this.setFromPoints(yo),this)}translate(e){return this.min.add(e),this.max.add(e),this}equals(e){return e.min.equals(this.min)&&e.max.equals(this.max)}}const yo=[new N,new N,new N,new N,new N,new N,new N,new N],ds=new N,Sm=new Pi,Kc=new N,Rc=new N,Dc=new N,oa=new N,aa=new N,cl=new N,Yh=new N,gm=new N,Am=new N,ul=new N;function g0(n,e,t,i,r){for(let s=0,o=n.length-3;s<=o;s+=3){ul.fromArray(n,s);const a=r.x*Math.abs(ul.x)+r.y*Math.abs(ul.y)+r.z*Math.abs(ul.z),l=e.dot(ul),c=t.dot(ul),h=i.dot(ul);if(Math.max(-Math.max(l,c,h),Math.min(l,c,h))>a)return!1}return!0}const R2=new Pi,Zh=new N,A0=new N;class vi{constructor(e=new N,t=-1){this.center=e,this.radius=t}set(e,t){return this.center.copy(e),this.radius=t,this}setFromPoints(e,t){const i=this.center;t!==void 0?i.copy(t):R2.setFromPoints(e).getCenter(i);let r=0;for(let s=0,o=e.length;s<o;s++)r=Math.max(r,i.distanceToSquared(e[s]));return this.radius=Math.sqrt(r),this}copy(e){return this.center.copy(e.center),this.radius=e.radius,this}isEmpty(){return this.radius<0}makeEmpty(){return this.center.set(0,0,0),this.radius=-1,this}containsPoint(e){return e.distanceToSquared(this.center)<=this.radius*this.radius}distanceToPoint(e){return e.distanceTo(this.center)-this.radius}intersectsSphere(e){const t=this.radius+e.radius;return e.center.distanceToSquared(this.center)<=t*t}intersectsBox(e){return e.intersectsSphere(this)}intersectsPlane(e){return Math.abs(e.distanceToPoint(this.center))<=this.radius}clampPoint(e,t){const i=this.center.distanceToSquared(e);return t.copy(e),i>this.radius*this.radius&&(t.sub(this.center).normalize(),t.multiplyScalar(this.radius).add(this.center)),t}getBoundingBox(e){return this.isEmpty()?(e.makeEmpty(),e):(e.set(this.center,this.center),e.expandByScalar(this.radius),e)}applyMatrix4(e){return this.center.applyMatrix4(e),this.radius=this.radius*e.getMaxScaleOnAxis(),this}translate(e){return this.center.add(e),this}expandByPoint(e){if(this.isEmpty())return this.center.copy(e),this.radius=0,this;Zh.subVectors(e,this.center);const t=Zh.lengthSq();if(t>this.radius*this.radius){const i=Math.sqrt(t),r=(i-this.radius)*.5;this.center.addScaledVector(Zh,r/i),this.radius+=r}return this}union(e){return e.isEmpty()?this:this.isEmpty()?(this.copy(e),this):(this.center.equals(e.center)===!0?this.radius=Math.max(this.radius,e.radius):(A0.subVectors(e.center,this.center).setLength(e.radius),this.expandByPoint(Zh.copy(e.center).add(A0)),this.expandByPoint(Zh.copy(e.center).sub(A0))),this)}equals(e){return e.center.equals(this.center)&&e.radius===this.radius}clone(){return new this.constructor().copy(this)}}const Eo=new N,y0=new N,ym=new N,la=new N,E0=new N,Em=new N,C0=new N;class pc{constructor(e=new N,t=new N(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,Eo)),this}closestPointToPoint(e,t){t.subVectors(e,this.origin);const i=t.dot(this.direction);return i<0?t.copy(this.origin):t.copy(this.origin).addScaledVector(this.direction,i)}distanceToPoint(e){return Math.sqrt(this.distanceSqToPoint(e))}distanceSqToPoint(e){const t=Eo.subVectors(e,this.origin).dot(this.direction);return t<0?this.origin.distanceToSquared(e):(Eo.copy(this.origin).addScaledVector(this.direction,t),Eo.distanceToSquared(e))}distanceSqToSegment(e,t,i,r){y0.copy(e).add(t).multiplyScalar(.5),ym.copy(t).sub(e).normalize(),la.copy(this.origin).sub(y0);const s=e.distanceTo(t)*.5,o=-this.direction.dot(ym),a=la.dot(this.direction),l=-la.dot(ym),c=la.lengthSq(),h=Math.abs(1-o*o);let f,d,m,g;if(h>0)if(f=o*l-a,d=o*a-l,g=s*h,f>=0)if(d>=-g)if(d<=g){const E=1/h;f*=E,d*=E,m=f*(f+o*d+2*a)+d*(o*f+d+2*l)+c}else d=s,f=Math.max(0,-(o*d+a)),m=-f*f+d*(d+2*l)+c;else d=-s,f=Math.max(0,-(o*d+a)),m=-f*f+d*(d+2*l)+c;else d<=-g?(f=Math.max(0,-(-o*s+a)),d=f>0?-s:Math.min(Math.max(-s,-l),s),m=-f*f+d*(d+2*l)+c):d<=g?(f=0,d=Math.min(Math.max(-s,-l),s),m=d*(d+2*l)+c):(f=Math.max(0,-(o*s+a)),d=f>0?s:Math.min(Math.max(-s,-l),s),m=-f*f+d*(d+2*l)+c);else d=o>0?-s:s,f=Math.max(0,-(o*d+a)),m=-f*f+d*(d+2*l)+c;return i&&i.copy(this.origin).addScaledVector(this.direction,f),r&&r.copy(y0).addScaledVector(ym,d),m}intersectSphere(e,t){Eo.subVectors(e.center,this.origin);const i=Eo.dot(this.direction),r=Eo.dot(Eo)-i*i,s=e.radius*e.radius;if(r>s)return null;const o=Math.sqrt(s-r),a=i-o,l=i+o;return l<0?null:a<0?this.at(l,t):this.at(a,t)}intersectsSphere(e){return this.distanceSqToPoint(e.center)<=e.radius*e.radius}distanceToPlane(e){const t=e.normal.dot(this.direction);if(t===0)return e.distanceToPoint(this.origin)===0?0:null;const i=-(this.origin.dot(e.normal)+e.constant)/t;return i>=0?i:null}intersectPlane(e,t){const i=this.distanceToPlane(e);return i===null?null:this.at(i,t)}intersectsPlane(e){const t=e.distanceToPoint(this.origin);return t===0||e.normal.dot(this.direction)*t<0}intersectBox(e,t){let i,r,s,o,a,l;const c=1/this.direction.x,h=1/this.direction.y,f=1/this.direction.z,d=this.origin;return c>=0?(i=(e.min.x-d.x)*c,r=(e.max.x-d.x)*c):(i=(e.max.x-d.x)*c,r=(e.min.x-d.x)*c),h>=0?(s=(e.min.y-d.y)*h,o=(e.max.y-d.y)*h):(s=(e.max.y-d.y)*h,o=(e.min.y-d.y)*h),i>o||s>r||((s>i||isNaN(i))&&(i=s),(o<r||isNaN(r))&&(r=o),f>=0?(a=(e.min.z-d.z)*f,l=(e.max.z-d.z)*f):(a=(e.max.z-d.z)*f,l=(e.min.z-d.z)*f),i>l||a>r)||((a>i||i!==i)&&(i=a),(l<r||r!==r)&&(r=l),r<0)?null:this.at(i>=0?i:r,t)}intersectsBox(e){return this.intersectBox(e,Eo)!==null}intersectTriangle(e,t,i,r,s){E0.subVectors(t,e),Em.subVectors(i,e),C0.crossVectors(E0,Em);let o=this.direction.dot(C0),a;if(o>0){if(r)return null;a=1}else if(o<0)a=-1,o=-o;else return null;la.subVectors(this.origin,e);const l=a*this.direction.dot(Em.crossVectors(la,Em));if(l<0)return null;const c=a*this.direction.dot(E0.cross(la));if(c<0||l+c>o)return null;const h=-a*la.dot(C0);return h<0?null:this.at(h/o,s)}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)}}class tt{constructor(e,t,i,r,s,o,a,l,c,h,f,d,m,g,E,C){tt.prototype.isMatrix4=!0,this.elements=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],e!==void 0&&this.set(e,t,i,r,s,o,a,l,c,h,f,d,m,g,E,C)}set(e,t,i,r,s,o,a,l,c,h,f,d,m,g,E,C){const S=this.elements;return S[0]=e,S[4]=t,S[8]=i,S[12]=r,S[1]=s,S[5]=o,S[9]=a,S[13]=l,S[2]=c,S[6]=h,S[10]=f,S[14]=d,S[3]=m,S[7]=g,S[11]=E,S[15]=C,this}identity(){return this.set(1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1),this}clone(){return new tt().fromArray(this.elements)}copy(e){const t=this.elements,i=e.elements;return t[0]=i[0],t[1]=i[1],t[2]=i[2],t[3]=i[3],t[4]=i[4],t[5]=i[5],t[6]=i[6],t[7]=i[7],t[8]=i[8],t[9]=i[9],t[10]=i[10],t[11]=i[11],t[12]=i[12],t[13]=i[13],t[14]=i[14],t[15]=i[15],this}copyPosition(e){const t=this.elements,i=e.elements;return t[12]=i[12],t[13]=i[13],t[14]=i[14],this}setFromMatrix3(e){const t=e.elements;return this.set(t[0],t[3],t[6],0,t[1],t[4],t[7],0,t[2],t[5],t[8],0,0,0,0,1),this}extractBasis(e,t,i){return e.setFromMatrixColumn(this,0),t.setFromMatrixColumn(this,1),i.setFromMatrixColumn(this,2),this}makeBasis(e,t,i){return this.set(e.x,t.x,i.x,0,e.y,t.y,i.y,0,e.z,t.z,i.z,0,0,0,0,1),this}extractRotation(e){const t=this.elements,i=e.elements,r=1/bc.setFromMatrixColumn(e,0).length(),s=1/bc.setFromMatrixColumn(e,1).length(),o=1/bc.setFromMatrixColumn(e,2).length();return t[0]=i[0]*r,t[1]=i[1]*r,t[2]=i[2]*r,t[3]=0,t[4]=i[4]*s,t[5]=i[5]*s,t[6]=i[6]*s,t[7]=0,t[8]=i[8]*o,t[9]=i[9]*o,t[10]=i[10]*o,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}makeRotationFromEuler(e){const t=this.elements,i=e.x,r=e.y,s=e.z,o=Math.cos(i),a=Math.sin(i),l=Math.cos(r),c=Math.sin(r),h=Math.cos(s),f=Math.sin(s);if(e.order==="XYZ"){const d=o*h,m=o*f,g=a*h,E=a*f;t[0]=l*h,t[4]=-l*f,t[8]=c,t[1]=m+g*c,t[5]=d-E*c,t[9]=-a*l,t[2]=E-d*c,t[6]=g+m*c,t[10]=o*l}else if(e.order==="YXZ"){const d=l*h,m=l*f,g=c*h,E=c*f;t[0]=d+E*a,t[4]=g*a-m,t[8]=o*c,t[1]=o*f,t[5]=o*h,t[9]=-a,t[2]=m*a-g,t[6]=E+d*a,t[10]=o*l}else if(e.order==="ZXY"){const d=l*h,m=l*f,g=c*h,E=c*f;t[0]=d-E*a,t[4]=-o*f,t[8]=g+m*a,t[1]=m+g*a,t[5]=o*h,t[9]=E-d*a,t[2]=-o*c,t[6]=a,t[10]=o*l}else if(e.order==="ZYX"){const d=o*h,m=o*f,g=a*h,E=a*f;t[0]=l*h,t[4]=g*c-m,t[8]=d*c+E,t[1]=l*f,t[5]=E*c+d,t[9]=m*c-g,t[2]=-c,t[6]=a*l,t[10]=o*l}else if(e.order==="YZX"){const d=o*l,m=o*c,g=a*l,E=a*c;t[0]=l*h,t[4]=E-d*f,t[8]=g*f+m,t[1]=f,t[5]=o*h,t[9]=-a*h,t[2]=-c*h,t[6]=m*f+g,t[10]=d-E*f}else if(e.order==="XZY"){const d=o*l,m=o*c,g=a*l,E=a*c;t[0]=l*h,t[4]=-f,t[8]=c*h,t[1]=d*f+E,t[5]=o*h,t[9]=m*f-g,t[2]=g*f-m,t[6]=a*h,t[10]=E*f+d}return t[3]=0,t[7]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,this}makeRotationFromQuaternion(e){return this.compose(D2,e,b2)}lookAt(e,t,i){const r=this.elements;return wr.subVectors(e,t),wr.lengthSq()===0&&(wr.z=1),wr.normalize(),ca.crossVectors(i,wr),ca.lengthSq()===0&&(Math.abs(i.z)===1?wr.x+=1e-4:wr.z+=1e-4,wr.normalize(),ca.crossVectors(i,wr)),ca.normalize(),Cm.crossVectors(wr,ca),r[0]=ca.x,r[4]=Cm.x,r[8]=wr.x,r[1]=ca.y,r[5]=Cm.y,r[9]=wr.y,r[2]=ca.z,r[6]=Cm.z,r[10]=wr.z,this}multiply(e){return this.multiplyMatrices(this,e)}premultiply(e){return this.multiplyMatrices(e,this)}multiplyMatrices(e,t){const i=e.elements,r=t.elements,s=this.elements,o=i[0],a=i[4],l=i[8],c=i[12],h=i[1],f=i[5],d=i[9],m=i[13],g=i[2],E=i[6],C=i[10],S=i[14],v=i[3],y=i[7],w=i[11],x=i[15],k=r[0],I=r[4],R=r[8],T=r[12],L=r[1],O=r[5],V=r[9],ie=r[13],W=r[2],_=r[6],ne=r[10],oe=r[14],H=r[3],Z=r[7],te=r[11],ae=r[15];return s[0]=o*k+a*L+l*W+c*H,s[4]=o*I+a*O+l*_+c*Z,s[8]=o*R+a*V+l*ne+c*te,s[12]=o*T+a*ie+l*oe+c*ae,s[1]=h*k+f*L+d*W+m*H,s[5]=h*I+f*O+d*_+m*Z,s[9]=h*R+f*V+d*ne+m*te,s[13]=h*T+f*ie+d*oe+m*ae,s[2]=g*k+E*L+C*W+S*H,s[6]=g*I+E*O+C*_+S*Z,s[10]=g*R+E*V+C*ne+S*te,s[14]=g*T+E*ie+C*oe+S*ae,s[3]=v*k+y*L+w*W+x*H,s[7]=v*I+y*O+w*_+x*Z,s[11]=v*R+y*V+w*ne+x*te,s[15]=v*T+y*ie+w*oe+x*ae,this}multiplyScalar(e){const t=this.elements;return t[0]*=e,t[4]*=e,t[8]*=e,t[12]*=e,t[1]*=e,t[5]*=e,t[9]*=e,t[13]*=e,t[2]*=e,t[6]*=e,t[10]*=e,t[14]*=e,t[3]*=e,t[7]*=e,t[11]*=e,t[15]*=e,this}determinant(){const e=this.elements,t=e[0],i=e[4],r=e[8],s=e[12],o=e[1],a=e[5],l=e[9],c=e[13],h=e[2],f=e[6],d=e[10],m=e[14],g=e[3],E=e[7],C=e[11],S=e[15];return g*(+s*l*f-r*c*f-s*a*d+i*c*d+r*a*m-i*l*m)+E*(+t*l*m-t*c*d+s*o*d-r*o*m+r*c*h-s*l*h)+C*(+t*c*f-t*a*m-s*o*f+i*o*m+s*a*h-i*c*h)+S*(-r*a*h-t*l*f+t*a*d+r*o*f-i*o*d+i*l*h)}transpose(){const e=this.elements;let t;return t=e[1],e[1]=e[4],e[4]=t,t=e[2],e[2]=e[8],e[8]=t,t=e[6],e[6]=e[9],e[9]=t,t=e[3],e[3]=e[12],e[12]=t,t=e[7],e[7]=e[13],e[13]=t,t=e[11],e[11]=e[14],e[14]=t,this}setPosition(e,t,i){const r=this.elements;return e.isVector3?(r[12]=e.x,r[13]=e.y,r[14]=e.z):(r[12]=e,r[13]=t,r[14]=i),this}invert(){const e=this.elements,t=e[0],i=e[1],r=e[2],s=e[3],o=e[4],a=e[5],l=e[6],c=e[7],h=e[8],f=e[9],d=e[10],m=e[11],g=e[12],E=e[13],C=e[14],S=e[15],v=f*C*c-E*d*c+E*l*m-a*C*m-f*l*S+a*d*S,y=g*d*c-h*C*c-g*l*m+o*C*m+h*l*S-o*d*S,w=h*E*c-g*f*c+g*a*m-o*E*m-h*a*S+o*f*S,x=g*f*l-h*E*l-g*a*d+o*E*d+h*a*C-o*f*C,k=t*v+i*y+r*w+s*x;if(k===0)return this.set(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0);const I=1/k;return e[0]=v*I,e[1]=(E*d*s-f*C*s-E*r*m+i*C*m+f*r*S-i*d*S)*I,e[2]=(a*C*s-E*l*s+E*r*c-i*C*c-a*r*S+i*l*S)*I,e[3]=(f*l*s-a*d*s-f*r*c+i*d*c+a*r*m-i*l*m)*I,e[4]=y*I,e[5]=(h*C*s-g*d*s+g*r*m-t*C*m-h*r*S+t*d*S)*I,e[6]=(g*l*s-o*C*s-g*r*c+t*C*c+o*r*S-t*l*S)*I,e[7]=(o*d*s-h*l*s+h*r*c-t*d*c-o*r*m+t*l*m)*I,e[8]=w*I,e[9]=(g*f*s-h*E*s-g*i*m+t*E*m+h*i*S-t*f*S)*I,e[10]=(o*E*s-g*a*s+g*i*c-t*E*c-o*i*S+t*a*S)*I,e[11]=(h*a*s-o*f*s-h*i*c+t*f*c+o*i*m-t*a*m)*I,e[12]=x*I,e[13]=(h*E*r-g*f*r+g*i*d-t*E*d-h*i*C+t*f*C)*I,e[14]=(g*a*r-o*E*r-g*i*l+t*E*l+o*i*C-t*a*C)*I,e[15]=(o*f*r-h*a*r+h*i*l-t*f*l-o*i*d+t*a*d)*I,this}scale(e){const t=this.elements,i=e.x,r=e.y,s=e.z;return t[0]*=i,t[4]*=r,t[8]*=s,t[1]*=i,t[5]*=r,t[9]*=s,t[2]*=i,t[6]*=r,t[10]*=s,t[3]*=i,t[7]*=r,t[11]*=s,this}getMaxScaleOnAxis(){const e=this.elements,t=e[0]*e[0]+e[1]*e[1]+e[2]*e[2],i=e[4]*e[4]+e[5]*e[5]+e[6]*e[6],r=e[8]*e[8]+e[9]*e[9]+e[10]*e[10];return Math.sqrt(Math.max(t,i,r))}makeTranslation(e,t,i){return e.isVector3?this.set(1,0,0,e.x,0,1,0,e.y,0,0,1,e.z,0,0,0,1):this.set(1,0,0,e,0,1,0,t,0,0,1,i,0,0,0,1),this}makeRotationX(e){const t=Math.cos(e),i=Math.sin(e);return this.set(1,0,0,0,0,t,-i,0,0,i,t,0,0,0,0,1),this}makeRotationY(e){const t=Math.cos(e),i=Math.sin(e);return this.set(t,0,i,0,0,1,0,0,-i,0,t,0,0,0,0,1),this}makeRotationZ(e){const t=Math.cos(e),i=Math.sin(e);return this.set(t,-i,0,0,i,t,0,0,0,0,1,0,0,0,0,1),this}makeRotationAxis(e,t){const i=Math.cos(t),r=Math.sin(t),s=1-i,o=e.x,a=e.y,l=e.z,c=s*o,h=s*a;return this.set(c*o+i,c*a-r*l,c*l+r*a,0,c*a+r*l,h*a+i,h*l-r*o,0,c*l-r*a,h*l+r*o,s*l*l+i,0,0,0,0,1),this}makeScale(e,t,i){return this.set(e,0,0,0,0,t,0,0,0,0,i,0,0,0,0,1),this}makeShear(e,t,i,r,s,o){return this.set(1,i,s,0,e,1,o,0,t,r,1,0,0,0,0,1),this}compose(e,t,i){const r=this.elements,s=t._x,o=t._y,a=t._z,l=t._w,c=s+s,h=o+o,f=a+a,d=s*c,m=s*h,g=s*f,E=o*h,C=o*f,S=a*f,v=l*c,y=l*h,w=l*f,x=i.x,k=i.y,I=i.z;return r[0]=(1-(E+S))*x,r[1]=(m+w)*x,r[2]=(g-y)*x,r[3]=0,r[4]=(m-w)*k,r[5]=(1-(d+S))*k,r[6]=(C+v)*k,r[7]=0,r[8]=(g+y)*I,r[9]=(C-v)*I,r[10]=(1-(d+E))*I,r[11]=0,r[12]=e.x,r[13]=e.y,r[14]=e.z,r[15]=1,this}decompose(e,t,i){const r=this.elements;let s=bc.set(r[0],r[1],r[2]).length();const o=bc.set(r[4],r[5],r[6]).length(),a=bc.set(r[8],r[9],r[10]).length();this.determinant()<0&&(s=-s),e.x=r[12],e.y=r[13],e.z=r[14],ms.copy(this);const c=1/s,h=1/o,f=1/a;return ms.elements[0]*=c,ms.elements[1]*=c,ms.elements[2]*=c,ms.elements[4]*=h,ms.elements[5]*=h,ms.elements[6]*=h,ms.elements[8]*=f,ms.elements[9]*=f,ms.elements[10]*=f,t.setFromRotationMatrix(ms),i.x=s,i.y=o,i.z=a,this}makePerspective(e,t,i,r,s,o,a=Us){const l=this.elements,c=2*s/(t-e),h=2*s/(i-r),f=(t+e)/(t-e),d=(i+r)/(i-r);let m,g;if(a===Us)m=-(o+s)/(o-s),g=-2*o*s/(o-s);else if(a===qu)m=-o/(o-s),g=-o*s/(o-s);else throw new Error("THREE.Matrix4.makePerspective(): Invalid coordinate system: "+a);return l[0]=c,l[4]=0,l[8]=f,l[12]=0,l[1]=0,l[5]=h,l[9]=d,l[13]=0,l[2]=0,l[6]=0,l[10]=m,l[14]=g,l[3]=0,l[7]=0,l[11]=-1,l[15]=0,this}makeOrthographic(e,t,i,r,s,o,a=Us){const l=this.elements,c=1/(t-e),h=1/(i-r),f=1/(o-s),d=(t+e)*c,m=(i+r)*h;let g,E;if(a===Us)g=(o+s)*f,E=-2*f;else if(a===qu)g=s*f,E=-1*f;else throw new Error("THREE.Matrix4.makeOrthographic(): Invalid coordinate system: "+a);return l[0]=2*c,l[4]=0,l[8]=0,l[12]=-d,l[1]=0,l[5]=2*h,l[9]=0,l[13]=-m,l[2]=0,l[6]=0,l[10]=E,l[14]=-g,l[3]=0,l[7]=0,l[11]=0,l[15]=1,this}equals(e){const t=this.elements,i=e.elements;for(let r=0;r<16;r++)if(t[r]!==i[r])return!1;return!0}fromArray(e,t=0){for(let i=0;i<16;i++)this.elements[i]=e[i+t];return this}toArray(e=[],t=0){const i=this.elements;return e[t]=i[0],e[t+1]=i[1],e[t+2]=i[2],e[t+3]=i[3],e[t+4]=i[4],e[t+5]=i[5],e[t+6]=i[6],e[t+7]=i[7],e[t+8]=i[8],e[t+9]=i[9],e[t+10]=i[10],e[t+11]=i[11],e[t+12]=i[12],e[t+13]=i[13],e[t+14]=i[14],e[t+15]=i[15],e}}const bc=new N,ms=new tt,D2=new N(0,0,0),b2=new N(1,1,1),ca=new N,Cm=new N,wr=new N,dT=new tt,mT=new zn;class Zs{constructor(e=0,t=0,i=0,r=Zs.DEFAULT_ORDER){this.isEuler=!0,this._x=e,this._y=t,this._z=i,this._order=r}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 order(){return this._order}set order(e){this._order=e,this._onChangeCallback()}set(e,t,i,r=this._order){return this._x=e,this._y=t,this._z=i,this._order=r,this._onChangeCallback(),this}clone(){return new this.constructor(this._x,this._y,this._z,this._order)}copy(e){return this._x=e._x,this._y=e._y,this._z=e._z,this._order=e._order,this._onChangeCallback(),this}setFromRotationMatrix(e,t=this._order,i=!0){const r=e.elements,s=r[0],o=r[4],a=r[8],l=r[1],c=r[5],h=r[9],f=r[2],d=r[6],m=r[10];switch(t){case"XYZ":this._y=Math.asin(Hn(a,-1,1)),Math.abs(a)<.9999999?(this._x=Math.atan2(-h,m),this._z=Math.atan2(-o,s)):(this._x=Math.atan2(d,c),this._z=0);break;case"YXZ":this._x=Math.asin(-Hn(h,-1,1)),Math.abs(h)<.9999999?(this._y=Math.atan2(a,m),this._z=Math.atan2(l,c)):(this._y=Math.atan2(-f,s),this._z=0);break;case"ZXY":this._x=Math.asin(Hn(d,-1,1)),Math.abs(d)<.9999999?(this._y=Math.atan2(-f,m),this._z=Math.atan2(-o,c)):(this._y=0,this._z=Math.atan2(l,s));break;case"ZYX":this._y=Math.asin(-Hn(f,-1,1)),Math.abs(f)<.9999999?(this._x=Math.atan2(d,m),this._z=Math.atan2(l,s)):(this._x=0,this._z=Math.atan2(-o,c));break;case"YZX":this._z=Math.asin(Hn(l,-1,1)),Math.abs(l)<.9999999?(this._x=Math.atan2(-h,c),this._y=Math.atan2(-f,s)):(this._x=0,this._y=Math.atan2(a,m));break;case"XZY":this._z=Math.asin(-Hn(o,-1,1)),Math.abs(o)<.9999999?(this._x=Math.atan2(d,c),this._y=Math.atan2(a,s)):(this._x=Math.atan2(-h,m),this._y=0);break;default:}return this._order=t,i===!0&&this._onChangeCallback(),this}setFromQuaternion(e,t,i){return dT.makeRotationFromQuaternion(e),this.setFromRotationMatrix(dT,t,i)}setFromVector3(e,t=this._order){return this.set(e.x,e.y,e.z,t)}reorder(e){return mT.setFromEuler(this),this.setFromQuaternion(mT,e)}equals(e){return e._x===this._x&&e._y===this._y&&e._z===this._z&&e._order===this._order}fromArray(e){return this._x=e[0],this._y=e[1],this._z=e[2],e[3]!==void 0&&(this._order=e[3]),this._onChangeCallback(),this}toArray(e=[],t=0){return e[t]=this._x,e[t+1]=this._y,e[t+2]=this._z,e[t+3]=this._order,e}_onChange(e){return this._onChangeCallback=e,this}_onChangeCallback(){}*[Symbol.iterator](){yield this._x,yield this._y,yield this._z,yield this._order}}Zs.DEFAULT_ORDER="XYZ";class Hl{constructor(){this.mask=1}set(e){this.mask=(1<<e|0)>>>0}enable(e){this.mask|=1<<e|0}enableAll(){this.mask=-1}toggle(e){this.mask^=1<<e|0}disable(e){this.mask&=~(1<<e|0)}disableAll(){this.mask=0}test(e){return(this.mask&e.mask)!==0}isEnabled(e){return(this.mask&(1<<e|0))!==0}}let O2=0;const ST=new N,Oc=new zn,Co=new tt,vm=new N,jh=new N,F2=new N,P2=new zn,gT=new N(1,0,0),AT=new N(0,1,0),yT=new N(0,0,1),N2={type:"added"},Q2={type:"removed"};class Wt extends co{constructor(){super(),this.isObject3D=!0,Object.defineProperty(this,"id",{value:O2++}),this.uuid=Br(),this.name="",this.type="Object3D",this.parent=null,this.children=[],this.up=Wt.DEFAULT_UP.clone();const e=new N,t=new Zs,i=new zn,r=new N(1,1,1);function s(){i.setFromEuler(t,!1)}function o(){t.setFromQuaternion(i,void 0,!1)}t._onChange(s),i._onChange(o),Object.defineProperties(this,{position:{configurable:!0,enumerable:!0,value:e},rotation:{configurable:!0,enumerable:!0,value:t},quaternion:{configurable:!0,enumerable:!0,value:i},scale:{configurable:!0,enumerable:!0,value:r},modelViewMatrix:{value:new tt},normalMatrix:{value:new Ot}}),this.matrix=new tt,this.matrixWorld=new tt,this.matrixAutoUpdate=Wt.DEFAULT_MATRIX_AUTO_UPDATE,this.matrixWorldAutoUpdate=Wt.DEFAULT_MATRIX_WORLD_AUTO_UPDATE,this.matrixWorldNeedsUpdate=!1,this.layers=new Hl,this.visible=!0,this.castShadow=!1,this.receiveShadow=!1,this.frustumCulled=!0,this.renderOrder=0,this.animations=[],this.userData={}}onBeforeShadow(){}onAfterShadow(){}onBeforeRender(){}onAfterRender(){}applyMatrix4(e){this.matrixAutoUpdate&&this.updateMatrix(),this.matrix.premultiply(e),this.matrix.decompose(this.position,this.quaternion,this.scale)}applyQuaternion(e){return this.quaternion.premultiply(e),this}setRotationFromAxisAngle(e,t){this.quaternion.setFromAxisAngle(e,t)}setRotationFromEuler(e){this.quaternion.setFromEuler(e,!0)}setRotationFromMatrix(e){this.quaternion.setFromRotationMatrix(e)}setRotationFromQuaternion(e){this.quaternion.copy(e)}rotateOnAxis(e,t){return Oc.setFromAxisAngle(e,t),this.quaternion.multiply(Oc),this}rotateOnWorldAxis(e,t){return Oc.setFromAxisAngle(e,t),this.quaternion.premultiply(Oc),this}rotateX(e){return this.rotateOnAxis(gT,e)}rotateY(e){return this.rotateOnAxis(AT,e)}rotateZ(e){return this.rotateOnAxis(yT,e)}translateOnAxis(e,t){return ST.copy(e).applyQuaternion(this.quaternion),this.position.add(ST.multiplyScalar(t)),this}translateX(e){return this.translateOnAxis(gT,e)}translateY(e){return this.translateOnAxis(AT,e)}translateZ(e){return this.translateOnAxis(yT,e)}localToWorld(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(this.matrixWorld)}worldToLocal(e){return this.updateWorldMatrix(!0,!1),e.applyMatrix4(Co.copy(this.matrixWorld).invert())}lookAt(e,t,i){e.isVector3?vm.copy(e):vm.set(e,t,i);const r=this.parent;this.updateWorldMatrix(!0,!1),jh.setFromMatrixPosition(this.matrixWorld),this.isCamera||this.isLight?Co.lookAt(jh,vm,this.up):Co.lookAt(vm,jh,this.up),this.quaternion.setFromRotationMatrix(Co),r&&(Co.extractRotation(r.matrixWorld),Oc.setFromRotationMatrix(Co),this.quaternion.premultiply(Oc.invert()))}add(e){if(arguments.length>1){for(let t=0;t<arguments.length;t++)this.add(arguments[t]);return this}return e===this?this:(e&&e.isObject3D&&(e.parent!==null&&e.parent.remove(e),e.parent=this,this.children.push(e),e.dispatchEvent(N2)),this)}remove(e){if(arguments.length>1){for(let i=0;i<arguments.length;i++)this.remove(arguments[i]);return this}const t=this.children.indexOf(e);return t!==-1&&(e.parent=null,this.children.splice(t,1),e.dispatchEvent(Q2)),this}removeFromParent(){const e=this.parent;return e!==null&&e.remove(this),this}clear(){return this.remove(...this.children)}attach(e){return this.updateWorldMatrix(!0,!1),Co.copy(this.matrixWorld).invert(),e.parent!==null&&(e.parent.updateWorldMatrix(!0,!1),Co.multiply(e.parent.matrixWorld)),e.applyMatrix4(Co),this.add(e),e.updateWorldMatrix(!1,!0),this}getObjectById(e){return this.getObjectByProperty("id",e)}getObjectByName(e){return this.getObjectByProperty("name",e)}getObjectByProperty(e,t){if(this[e]===t)return this;for(let i=0,r=this.children.length;i<r;i++){const o=this.children[i].getObjectByProperty(e,t);if(o!==void 0)return o}}getObjectsByProperty(e,t,i=[]){this[e]===t&&i.push(this);const r=this.children;for(let s=0,o=r.length;s<o;s++)r[s].getObjectsByProperty(e,t,i);return i}getWorldPosition(e){return this.updateWorldMatrix(!0,!1),e.setFromMatrixPosition(this.matrixWorld)}getWorldQuaternion(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(jh,e,F2),e}getWorldScale(e){return this.updateWorldMatrix(!0,!1),this.matrixWorld.decompose(jh,P2,e),e}getWorldDirection(e){this.updateWorldMatrix(!0,!1);const t=this.matrixWorld.elements;return e.set(t[8],t[9],t[10]).normalize()}raycast(){}traverse(e){e(this);const t=this.children;for(let i=0,r=t.length;i<r;i++)t[i].traverse(e)}traverseVisible(e){if(this.visible===!1)return;e(this);const t=this.children;for(let i=0,r=t.length;i<r;i++)t[i].traverseVisible(e)}traverseAncestors(e){const t=this.parent;t!==null&&(e(t),t.traverseAncestors(e))}updateMatrix(){this.matrix.compose(this.position,this.quaternion,this.scale),this.matrixWorldNeedsUpdate=!0}updateMatrixWorld(e){this.matrixAutoUpdate&&this.updateMatrix(),(this.matrixWorldNeedsUpdate||e)&&(this.parent===null?this.matrixWorld.copy(this.matrix):this.matrixWorld.multiplyMatrices(this.parent.matrixWorld,this.matrix),this.matrixWorldNeedsUpdate=!1,e=!0);const t=this.children;for(let i=0,r=t.length;i<r;i++){const s=t[i];(s.matrixWorldAutoUpdate===!0||e===!0)&&s.updateMatrixWorld(e)}}updateWorldMatrix(e,t){const i=this.parent;if(e===!0&&i!==null&&i.matrixWorldAutoUpdate===!0&&i.updateWorldMatrix(!0,!1),this.matrixAutoUpdate&&this.updateMatrix(),this.parent===null?this.matrixWorld.copy(this.matrix):this.matrixWorld.multiplyMatrices(this.parent.matrixWorld,this.matrix),t===!0){const r=this.children;for(let s=0,o=r.length;s<o;s++){const a=r[s];a.matrixWorldAutoUpdate===!0&&a.updateWorldMatrix(!1,!0)}}}toJSON(e){const t=e===void 0||typeof e=="string",i={};t&&(e={geometries:{},materials:{},textures:{},images:{},shapes:{},skeletons:{},animations:{},nodes:{}},i.metadata={version:4.6,type:"Object",generator:"Object3D.toJSON"});const r={};r.uuid=this.uuid,r.type=this.type,this.name!==""&&(r.name=this.name),this.castShadow===!0&&(r.castShadow=!0),this.receiveShadow===!0&&(r.receiveShadow=!0),this.visible===!1&&(r.visible=!1),this.frustumCulled===!1&&(r.frustumCulled=!1),this.renderOrder!==0&&(r.renderOrder=this.renderOrder),Object.keys(this.userData).length>0&&(r.userData=this.userData),r.layers=this.layers.mask,r.matrix=this.matrix.toArray(),r.up=this.up.toArray(),this.matrixAutoUpdate===!1&&(r.matrixAutoUpdate=!1),this.isInstancedMesh&&(r.type="InstancedMesh",r.count=this.count,r.instanceMatrix=this.instanceMatrix.toJSON(),this.instanceColor!==null&&(r.instanceColor=this.instanceColor.toJSON())),this.isBatchedMesh&&(r.type="BatchedMesh",r.perObjectFrustumCulled=this.perObjectFrustumCulled,r.sortObjects=this.sortObjects,r.drawRanges=this._drawRanges,r.reservedRanges=this._reservedRanges,r.visibility=this._visibility,r.active=this._active,r.bounds=this._bounds.map(a=>({boxInitialized:a.boxInitialized,boxMin:a.box.min.toArray(),boxMax:a.box.max.toArray(),sphereInitialized:a.sphereInitialized,sphereRadius:a.sphere.radius,sphereCenter:a.sphere.center.toArray()})),r.maxGeometryCount=this._maxGeometryCount,r.maxVertexCount=this._maxVertexCount,r.maxIndexCount=this._maxIndexCount,r.geometryInitialized=this._geometryInitialized,r.geometryCount=this._geometryCount,r.matricesTexture=this._matricesTexture.toJSON(e),this.boundingSphere!==null&&(r.boundingSphere={center:r.boundingSphere.center.toArray(),radius:r.boundingSphere.radius}),this.boundingBox!==null&&(r.boundingBox={min:r.boundingBox.min.toArray(),max:r.boundingBox.max.toArray()}));function s(a,l){return a[l.uuid]===void 0&&(a[l.uuid]=l.toJSON(e)),l.uuid}if(this.isScene)this.background&&(this.background.isColor?r.background=this.background.toJSON():this.background.isTexture&&(r.background=this.background.toJSON(e).uuid)),this.environment&&this.environment.isTexture&&this.environment.isRenderTargetTexture!==!0&&(r.environment=this.environment.toJSON(e).uuid);else if(this.isMesh||this.isLine||this.isPoints){r.geometry=s(e.geometries,this.geometry);const a=this.geometry.parameters;if(a!==void 0&&a.shapes!==void 0){const l=a.shapes;if(Array.isArray(l))for(let c=0,h=l.length;c<h;c++){const f=l[c];s(e.shapes,f)}else s(e.shapes,l)}}if(this.isSkinnedMesh&&(r.bindMode=this.bindMode,r.bindMatrix=this.bindMatrix.toArray(),this.skeleton!==void 0&&(s(e.skeletons,this.skeleton),r.skeleton=this.skeleton.uuid)),this.material!==void 0)if(Array.isArray(this.material)){const a=[];for(let l=0,c=this.material.length;l<c;l++)a.push(s(e.materials,this.material[l]));r.material=a}else r.material=s(e.materials,this.material);if(this.children.length>0){r.children=[];for(let a=0;a<this.children.length;a++)r.children.push(this.children[a].toJSON(e).object)}if(this.animations.length>0){r.animations=[];for(let a=0;a<this.animations.length;a++){const l=this.animations[a];r.animations.push(s(e.animations,l))}}if(t){const a=o(e.geometries),l=o(e.materials),c=o(e.textures),h=o(e.images),f=o(e.shapes),d=o(e.skeletons),m=o(e.animations),g=o(e.nodes);a.length>0&&(i.geometries=a),l.length>0&&(i.materials=l),c.length>0&&(i.textures=c),h.length>0&&(i.images=h),f.length>0&&(i.shapes=f),d.length>0&&(i.skeletons=d),m.length>0&&(i.animations=m),g.length>0&&(i.nodes=g)}return i.object=r,i;function o(a){const l=[];for(const c in a){const h=a[c];delete h.metadata,l.push(h)}return l}}clone(e){return new this.constructor().copy(this,e)}copy(e,t=!0){if(this.name=e.name,this.up.copy(e.up),this.position.copy(e.position),this.rotation.order=e.rotation.order,this.quaternion.copy(e.quaternion),this.scale.copy(e.scale),this.matrix.copy(e.matrix),this.matrixWorld.copy(e.matrixWorld),this.matrixAutoUpdate=e.matrixAutoUpdate,this.matrixWorldAutoUpdate=e.matrixWorldAutoUpdate,this.matrixWorldNeedsUpdate=e.matrixWorldNeedsUpdate,this.layers.mask=e.layers.mask,this.visible=e.visible,this.castShadow=e.castShadow,this.receiveShadow=e.receiveShadow,this.frustumCulled=e.frustumCulled,this.renderOrder=e.renderOrder,this.animations=e.animations.slice(),this.userData=JSON.parse(JSON.stringify(e.userData)),t===!0)for(let i=0;i<e.children.length;i++){const r=e.children[i];this.add(r.clone())}return this}}Wt.DEFAULT_UP=new N(0,1,0);Wt.DEFAULT_MATRIX_AUTO_UPDATE=!0;Wt.DEFAULT_MATRIX_WORLD_AUTO_UPDATE=!0;const Ss=new N,vo=new N,v0=new N,Uo=new N,Fc=new N,Pc=new N,ET=new N,U0=new N,w0=new N,M0=new N;let Um=!1;class pr{constructor(e=new N,t=new N,i=new N){this.a=e,this.b=t,this.c=i}static getNormal(e,t,i,r){r.subVectors(i,t),Ss.subVectors(e,t),r.cross(Ss);const s=r.lengthSq();return s>0?r.multiplyScalar(1/Math.sqrt(s)):r.set(0,0,0)}static getBarycoord(e,t,i,r,s){Ss.subVectors(r,t),vo.subVectors(i,t),v0.subVectors(e,t);const o=Ss.dot(Ss),a=Ss.dot(vo),l=Ss.dot(v0),c=vo.dot(vo),h=vo.dot(v0),f=o*c-a*a;if(f===0)return s.set(-2,-1,-1);const d=1/f,m=(c*l-a*h)*d,g=(o*h-a*l)*d;return s.set(1-m-g,g,m)}static containsPoint(e,t,i,r){return this.getBarycoord(e,t,i,r,Uo),Uo.x>=0&&Uo.y>=0&&Uo.x+Uo.y<=1}static getUV(e,t,i,r,s,o,a,l){return Um===!1&&(Um=!0),this.getInterpolation(e,t,i,r,s,o,a,l)}static getInterpolation(e,t,i,r,s,o,a,l){return this.getBarycoord(e,t,i,r,Uo),l.setScalar(0),l.addScaledVector(s,Uo.x),l.addScaledVector(o,Uo.y),l.addScaledVector(a,Uo.z),l}static isFrontFacing(e,t,i,r){return Ss.subVectors(i,t),vo.subVectors(e,t),Ss.cross(vo).dot(r)<0}set(e,t,i){return this.a.copy(e),this.b.copy(t),this.c.copy(i),this}setFromPointsAndIndices(e,t,i,r){return this.a.copy(e[t]),this.b.copy(e[i]),this.c.copy(e[r]),this}setFromAttributeAndIndices(e,t,i,r){return this.a.fromBufferAttribute(e,t),this.b.fromBufferAttribute(e,i),this.c.fromBufferAttribute(e,r),this}clone(){return new this.constructor().copy(this)}copy(e){return this.a.copy(e.a),this.b.copy(e.b),this.c.copy(e.c),this}getArea(){return Ss.subVectors(this.c,this.b),vo.subVectors(this.a,this.b),Ss.cross(vo).length()*.5}getMidpoint(e){return e.addVectors(this.a,this.b).add(this.c).multiplyScalar(1/3)}getNormal(e){return pr.getNormal(this.a,this.b,this.c,e)}getPlane(e){return e.setFromCoplanarPoints(this.a,this.b,this.c)}getBarycoord(e,t){return pr.getBarycoord(e,this.a,this.b,this.c,t)}getUV(e,t,i,r,s){return Um===!1&&(Um=!0),pr.getInterpolation(e,this.a,this.b,this.c,t,i,r,s)}getInterpolation(e,t,i,r,s){return pr.getInterpolation(e,this.a,this.b,this.c,t,i,r,s)}containsPoint(e){return pr.containsPoint(e,this.a,this.b,this.c)}isFrontFacing(e){return pr.isFrontFacing(this.a,this.b,this.c,e)}intersectsBox(e){return e.intersectsTriangle(this)}closestPointToPoint(e,t){const i=this.a,r=this.b,s=this.c;let o,a;Fc.subVectors(r,i),Pc.subVectors(s,i),U0.subVectors(e,i);const l=Fc.dot(U0),c=Pc.dot(U0);if(l<=0&&c<=0)return t.copy(i);w0.subVectors(e,r);const h=Fc.dot(w0),f=Pc.dot(w0);if(h>=0&&f<=h)return t.copy(r);const d=l*f-h*c;if(d<=0&&l>=0&&h<=0)return o=l/(l-h),t.copy(i).addScaledVector(Fc,o);M0.subVectors(e,s);const m=Fc.dot(M0),g=Pc.dot(M0);if(g>=0&&m<=g)return t.copy(s);const E=m*c-l*g;if(E<=0&&c>=0&&g<=0)return a=c/(c-g),t.copy(i).addScaledVector(Pc,a);const C=h*g-m*f;if(C<=0&&f-h>=0&&m-g>=0)return ET.subVectors(s,r),a=(f-h)/(f-h+(m-g)),t.copy(r).addScaledVector(ET,a);const S=1/(C+E+d);return o=E*S,a=d*S,t.copy(i).addScaledVector(Fc,o).addScaledVector(Pc,a)}equals(e){return e.a.equals(this.a)&&e.b.equals(this.b)&&e.c.equals(this.c)}}const aR={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},ua={h:0,s:0,l:0},wm={h:0,s:0,l:0};function k0(n,e,t){return t<0&&(t+=1),t>1&&(t-=1),t<1/6?n+(e-n)*6*t:t<1/2?e:t<2/3?n+(e-n)*6*(2/3-t):n}let ze=class{constructor(e,t,i){return this.isColor=!0,this.r=1,this.g=1,this.b=1,this.set(e,t,i)}set(e,t,i){if(t===void 0&&i===void 0){const r=e;r&&r.isColor?this.copy(r):typeof r=="number"?this.setHex(r):typeof r=="string"&&this.setStyle(r)}else this.setRGB(e,t,i);return this}setScalar(e){return this.r=e,this.g=e,this.b=e,this}setHex(e,t=si){return e=Math.floor(e),this.r=(e>>16&255)/255,this.g=(e>>8&255)/255,this.b=(e&255)/255,an.toWorkingColorSpace(this,t),this}setRGB(e,t,i,r=an.workingColorSpace){return this.r=e,this.g=t,this.b=i,an.toWorkingColorSpace(this,r),this}setHSL(e,t,i,r=an.workingColorSpace){if(e=tw(e,1),t=Hn(t,0,1),i=Hn(i,0,1),t===0)this.r=this.g=this.b=i;else{const s=i<=.5?i*(1+t):i+t-i*t,o=2*i-s;this.r=k0(o,s,e+1/3),this.g=k0(o,s,e),this.b=k0(o,s,e-1/3)}return an.toWorkingColorSpace(this,r),this}setStyle(e,t=si){function i(s){s!==void 0&&parseFloat(s)<1}let r;if(r=/^(\w+)\(([^\)]*)\)/.exec(e)){let s;const o=r[1],a=r[2];switch(o){case"rgb":case"rgba":if(s=/^\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(a))return i(s[4]),this.setRGB(Math.min(255,parseInt(s[1],10))/255,Math.min(255,parseInt(s[2],10))/255,Math.min(255,parseInt(s[3],10))/255,t);if(s=/^\s*(\d+)\%\s*,\s*(\d+)\%\s*,\s*(\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(a))return i(s[4]),this.setRGB(Math.min(100,parseInt(s[1],10))/100,Math.min(100,parseInt(s[2],10))/100,Math.min(100,parseInt(s[3],10))/100,t);break;case"hsl":case"hsla":if(s=/^\s*(\d*\.?\d+)\s*,\s*(\d*\.?\d+)\%\s*,\s*(\d*\.?\d+)\%\s*(?:,\s*(\d*\.?\d+)\s*)?$/.exec(a))return i(s[4]),this.setHSL(parseFloat(s[1])/360,parseFloat(s[2])/100,parseFloat(s[3])/100,t);break;default:}}else if(r=/^\#([A-Fa-f\d]+)$/.exec(e)){const s=r[1],o=s.length;if(o===3)return this.setRGB(parseInt(s.charAt(0),16)/15,parseInt(s.charAt(1),16)/15,parseInt(s.charAt(2),16)/15,t);if(o===6)return this.setHex(parseInt(s,16),t)}else if(e&&e.length>0)return this.setColorName(e,t);return this}setColorName(e,t=si){const i=aR[e.toLowerCase()];return i!==void 0&&this.setHex(i,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=Ku(e.r),this.g=Ku(e.g),this.b=Ku(e.b),this}copyLinearToSRGB(e){return this.r=d0(e.r),this.g=d0(e.g),this.b=d0(e.b),this}convertSRGBToLinear(){return this.copySRGBToLinear(this),this}convertLinearToSRGB(){return this.copyLinearToSRGB(this),this}getHex(e=si){return an.fromWorkingColorSpace(Ki.copy(this),e),Math.round(Hn(Ki.r*255,0,255))*65536+Math.round(Hn(Ki.g*255,0,255))*256+Math.round(Hn(Ki.b*255,0,255))}getHexString(e=si){return("000000"+this.getHex(e).toString(16)).slice(-6)}getHSL(e,t=an.workingColorSpace){an.fromWorkingColorSpace(Ki.copy(this),t);const i=Ki.r,r=Ki.g,s=Ki.b,o=Math.max(i,r,s),a=Math.min(i,r,s);let l,c;const h=(a+o)/2;if(a===o)l=0,c=0;else{const f=o-a;switch(c=h<=.5?f/(o+a):f/(2-o-a),o){case i:l=(r-s)/f+(r<s?6:0);break;case r:l=(s-i)/f+2;break;case s:l=(i-r)/f+4;break}l/=6}return e.h=l,e.s=c,e.l=h,e}getRGB(e,t=an.workingColorSpace){return an.fromWorkingColorSpace(Ki.copy(this),t),e.r=Ki.r,e.g=Ki.g,e.b=Ki.b,e}getStyle(e=si){an.fromWorkingColorSpace(Ki.copy(this),e);const t=Ki.r,i=Ki.g,r=Ki.b;return e!==si?`color(${e} ${t.toFixed(3)} ${i.toFixed(3)} ${r.toFixed(3)})`:`rgb(${Math.round(t*255)},${Math.round(i*255)},${Math.round(r*255)})`}offsetHSL(e,t,i){return this.getHSL(ua),this.setHSL(ua.h+e,ua.s+t,ua.l+i)}add(e){return this.r+=e.r,this.g+=e.g,this.b+=e.b,this}addColors(e,t){return this.r=e.r+t.r,this.g=e.g+t.g,this.b=e.b+t.b,this}addScalar(e){return this.r+=e,this.g+=e,this.b+=e,this}sub(e){return this.r=Math.max(0,this.r-e.r),this.g=Math.max(0,this.g-e.g),this.b=Math.max(0,this.b-e.b),this}multiply(e){return this.r*=e.r,this.g*=e.g,this.b*=e.b,this}multiplyScalar(e){return this.r*=e,this.g*=e,this.b*=e,this}lerp(e,t){return this.r+=(e.r-this.r)*t,this.g+=(e.g-this.g)*t,this.b+=(e.b-this.b)*t,this}lerpColors(e,t,i){return this.r=e.r+(t.r-e.r)*i,this.g=e.g+(t.g-e.g)*i,this.b=e.b+(t.b-e.b)*i,this}lerpHSL(e,t){this.getHSL(ua),e.getHSL(wm);const i=Lp(ua.h,wm.h,t),r=Lp(ua.s,wm.s,t),s=Lp(ua.l,wm.l,t);return this.setHSL(i,r,s),this}setFromVector3(e){return this.r=e.x,this.g=e.y,this.b=e.z,this}applyMatrix3(e){const t=this.r,i=this.g,r=this.b,s=e.elements;return this.r=s[0]*t+s[3]*i+s[6]*r,this.g=s[1]*t+s[4]*i+s[7]*r,this.b=s[2]*t+s[5]*i+s[8]*r,this}equals(e){return e.r===this.r&&e.g===this.g&&e.b===this.b}fromArray(e,t=0){return this.r=e[t],this.g=e[t+1],this.b=e[t+2],this}toArray(e=[],t=0){return e[t]=this.r,e[t+1]=this.g,e[t+2]=this.b,e}fromBufferAttribute(e,t){return this.r=e.getX(t),this.g=e.getY(t),this.b=e.getZ(t),this}toJSON(){return this.getHex()}*[Symbol.iterator](){yield this.r,yield this.g,yield this.b}};const Ki=new ze;ze.NAMES=aR;let W2=0;class ti extends co{constructor(){super(),this.isMaterial=!0,Object.defineProperty(this,"id",{value:W2++}),this.uuid=Br(),this.name="",this.type="Material",this.blending=Ql,this.side=to,this.vertexColors=!1,this.opacity=1,this.transparent=!1,this.alphaHash=!1,this.blendSrc=dg,this.blendDst=mg,this.blendEquation=Ca,this.blendSrcAlpha=null,this.blendDstAlpha=null,this.blendEquationAlpha=null,this.blendColor=new ze(0,0,0),this.blendAlpha=0,this.depthFunc=of,this.depthTest=!0,this.depthWrite=!0,this.stencilWriteMask=255,this.stencilFunc=tv,this.stencilRef=0,this.stencilFuncMask=255,this.stencilFail=xl,this.stencilZFail=xl,this.stencilZPass=xl,this.stencilWrite=!1,this.clippingPlanes=null,this.clipIntersection=!1,this.clipShadows=!1,this.shadowSide=null,this.colorWrite=!0,this.precision=null,this.polygonOffset=!1,this.polygonOffsetFactor=0,this.polygonOffsetUnits=0,this.dithering=!1,this.alphaToCoverage=!1,this.premultipliedAlpha=!1,this.forceSinglePass=!1,this.visible=!0,this.toneMapped=!0,this.userData={},this.version=0,this._alphaTest=0}get alphaTest(){return this._alphaTest}set alphaTest(e){this._alphaTest>0!=e>0&&this.version++,this._alphaTest=e}onBuild(){}onBeforeRender(){}onBeforeCompile(){}customProgramCacheKey(){return this.onBeforeCompile.toString()}setValues(e){if(e!==void 0)for(const t in e){const i=e[t];if(i===void 0)continue;const r=this[t];r!==void 0&&(r&&r.isColor?r.set(i):r&&r.isVector3&&i&&i.isVector3?r.copy(i):this[t]=i)}}toJSON(e){const t=e===void 0||typeof e=="string";t&&(e={textures:{},images:{}});const i={metadata:{version:4.6,type:"Material",generator:"Material.toJSON"}};i.uuid=this.uuid,i.type=this.type,this.name!==""&&(i.name=this.name),this.color&&this.color.isColor&&(i.color=this.color.getHex()),this.roughness!==void 0&&(i.roughness=this.roughness),this.metalness!==void 0&&(i.metalness=this.metalness),this.sheen!==void 0&&(i.sheen=this.sheen),this.sheenColor&&this.sheenColor.isColor&&(i.sheenColor=this.sheenColor.getHex()),this.sheenRoughness!==void 0&&(i.sheenRoughness=this.sheenRoughness),this.emissive&&this.emissive.isColor&&(i.emissive=this.emissive.getHex()),this.emissiveIntensity&&this.emissiveIntensity!==1&&(i.emissiveIntensity=this.emissiveIntensity),this.specular&&this.specular.isColor&&(i.specular=this.specular.getHex()),this.specularIntensity!==void 0&&(i.specularIntensity=this.specularIntensity),this.specularColor&&this.specularColor.isColor&&(i.specularColor=this.specularColor.getHex()),this.shininess!==void 0&&(i.shininess=this.shininess),this.clearcoat!==void 0&&(i.clearcoat=this.clearcoat),this.clearcoatRoughness!==void 0&&(i.clearcoatRoughness=this.clearcoatRoughness),this.clearcoatMap&&this.clearcoatMap.isTexture&&(i.clearcoatMap=this.clearcoatMap.toJSON(e).uuid),this.clearcoatRoughnessMap&&this.clearcoatRoughnessMap.isTexture&&(i.clearcoatRoughnessMap=this.clearcoatRoughnessMap.toJSON(e).uuid),this.clearcoatNormalMap&&this.clearcoatNormalMap.isTexture&&(i.clearcoatNormalMap=this.clearcoatNormalMap.toJSON(e).uuid,i.clearcoatNormalScale=this.clearcoatNormalScale.toArray()),this.iridescence!==void 0&&(i.iridescence=this.iridescence),this.iridescenceIOR!==void 0&&(i.iridescenceIOR=this.iridescenceIOR),this.iridescenceThicknessRange!==void 0&&(i.iridescenceThicknessRange=this.iridescenceThicknessRange),this.iridescenceMap&&this.iridescenceMap.isTexture&&(i.iridescenceMap=this.iridescenceMap.toJSON(e).uuid),this.iridescenceThicknessMap&&this.iridescenceThicknessMap.isTexture&&(i.iridescenceThicknessMap=this.iridescenceThicknessMap.toJSON(e).uuid),this.anisotropy!==void 0&&(i.anisotropy=this.anisotropy),this.anisotropyRotation!==void 0&&(i.anisotropyRotation=this.anisotropyRotation),this.anisotropyMap&&this.anisotropyMap.isTexture&&(i.anisotropyMap=this.anisotropyMap.toJSON(e).uuid),this.map&&this.map.isTexture&&(i.map=this.map.toJSON(e).uuid),this.matcap&&this.matcap.isTexture&&(i.matcap=this.matcap.toJSON(e).uuid),this.alphaMap&&this.alphaMap.isTexture&&(i.alphaMap=this.alphaMap.toJSON(e).uuid),this.lightMap&&this.lightMap.isTexture&&(i.lightMap=this.lightMap.toJSON(e).uuid,i.lightMapIntensity=this.lightMapIntensity),this.aoMap&&this.aoMap.isTexture&&(i.aoMap=this.aoMap.toJSON(e).uuid,i.aoMapIntensity=this.aoMapIntensity),this.bumpMap&&this.bumpMap.isTexture&&(i.bumpMap=this.bumpMap.toJSON(e).uuid,i.bumpScale=this.bumpScale),this.normalMap&&this.normalMap.isTexture&&(i.normalMap=this.normalMap.toJSON(e).uuid,i.normalMapType=this.normalMapType,i.normalScale=this.normalScale.toArray()),this.displacementMap&&this.displacementMap.isTexture&&(i.displacementMap=this.displacementMap.toJSON(e).uuid,i.displacementScale=this.displacementScale,i.displacementBias=this.displacementBias),this.roughnessMap&&this.roughnessMap.isTexture&&(i.roughnessMap=this.roughnessMap.toJSON(e).uuid),this.metalnessMap&&this.metalnessMap.isTexture&&(i.metalnessMap=this.metalnessMap.toJSON(e).uuid),this.emissiveMap&&this.emissiveMap.isTexture&&(i.emissiveMap=this.emissiveMap.toJSON(e).uuid),this.specularMap&&this.specularMap.isTexture&&(i.specularMap=this.specularMap.toJSON(e).uuid),this.specularIntensityMap&&this.specularIntensityMap.isTexture&&(i.specularIntensityMap=this.specularIntensityMap.toJSON(e).uuid),this.specularColorMap&&this.specularColorMap.isTexture&&(i.specularColorMap=this.specularColorMap.toJSON(e).uuid),this.envMap&&this.envMap.isTexture&&(i.envMap=this.envMap.toJSON(e).uuid,this.combine!==void 0&&(i.combine=this.combine)),this.envMapIntensity!==void 0&&(i.envMapIntensity=this.envMapIntensity),this.reflectivity!==void 0&&(i.reflectivity=this.reflectivity),this.refractionRatio!==void 0&&(i.refractionRatio=this.refractionRatio),this.gradientMap&&this.gradientMap.isTexture&&(i.gradientMap=this.gradientMap.toJSON(e).uuid),this.transmission!==void 0&&(i.transmission=this.transmission),this.transmissionMap&&this.transmissionMap.isTexture&&(i.transmissionMap=this.transmissionMap.toJSON(e).uuid),this.thickness!==void 0&&(i.thickness=this.thickness),this.thicknessMap&&this.thicknessMap.isTexture&&(i.thicknessMap=this.thicknessMap.toJSON(e).uuid),this.attenuationDistance!==void 0&&this.attenuationDistance!==1/0&&(i.attenuationDistance=this.attenuationDistance),this.attenuationColor!==void 0&&(i.attenuationColor=this.attenuationColor.getHex()),this.size!==void 0&&(i.size=this.size),this.shadowSide!==null&&(i.shadowSide=this.shadowSide),this.sizeAttenuation!==void 0&&(i.sizeAttenuation=this.sizeAttenuation),this.blending!==Ql&&(i.blending=this.blending),this.side!==to&&(i.side=this.side),this.vertexColors===!0&&(i.vertexColors=!0),this.opacity<1&&(i.opacity=this.opacity),this.transparent===!0&&(i.transparent=!0),this.blendSrc!==dg&&(i.blendSrc=this.blendSrc),this.blendDst!==mg&&(i.blendDst=this.blendDst),this.blendEquation!==Ca&&(i.blendEquation=this.blendEquation),this.blendSrcAlpha!==null&&(i.blendSrcAlpha=this.blendSrcAlpha),this.blendDstAlpha!==null&&(i.blendDstAlpha=this.blendDstAlpha),this.blendEquationAlpha!==null&&(i.blendEquationAlpha=this.blendEquationAlpha),this.blendColor&&this.blendColor.isColor&&(i.blendColor=this.blendColor.getHex()),this.blendAlpha!==0&&(i.blendAlpha=this.blendAlpha),this.depthFunc!==of&&(i.depthFunc=this.depthFunc),this.depthTest===!1&&(i.depthTest=this.depthTest),this.depthWrite===!1&&(i.depthWrite=this.depthWrite),this.colorWrite===!1&&(i.colorWrite=this.colorWrite),this.stencilWriteMask!==255&&(i.stencilWriteMask=this.stencilWriteMask),this.stencilFunc!==tv&&(i.stencilFunc=this.stencilFunc),this.stencilRef!==0&&(i.stencilRef=this.stencilRef),this.stencilFuncMask!==255&&(i.stencilFuncMask=this.stencilFuncMask),this.stencilFail!==xl&&(i.stencilFail=this.stencilFail),this.stencilZFail!==xl&&(i.stencilZFail=this.stencilZFail),this.stencilZPass!==xl&&(i.stencilZPass=this.stencilZPass),this.stencilWrite===!0&&(i.stencilWrite=this.stencilWrite),this.rotation!==void 0&&this.rotation!==0&&(i.rotation=this.rotation),this.polygonOffset===!0&&(i.polygonOffset=!0),this.polygonOffsetFactor!==0&&(i.polygonOffsetFactor=this.polygonOffsetFactor),this.polygonOffsetUnits!==0&&(i.polygonOffsetUnits=this.polygonOffsetUnits),this.linewidth!==void 0&&this.linewidth!==1&&(i.linewidth=this.linewidth),this.dashSize!==void 0&&(i.dashSize=this.dashSize),this.gapSize!==void 0&&(i.gapSize=this.gapSize),this.scale!==void 0&&(i.scale=this.scale),this.dithering===!0&&(i.dithering=!0),this.alphaTest>0&&(i.alphaTest=this.alphaTest),this.alphaHash===!0&&(i.alphaHash=!0),this.alphaToCoverage===!0&&(i.alphaToCoverage=!0),this.premultipliedAlpha===!0&&(i.premultipliedAlpha=!0),this.forceSinglePass===!0&&(i.forceSinglePass=!0),this.wireframe===!0&&(i.wireframe=!0),this.wireframeLinewidth>1&&(i.wireframeLinewidth=this.wireframeLinewidth),this.wireframeLinecap!=="round"&&(i.wireframeLinecap=this.wireframeLinecap),this.wireframeLinejoin!=="round"&&(i.wireframeLinejoin=this.wireframeLinejoin),this.flatShading===!0&&(i.flatShading=!0),this.visible===!1&&(i.visible=!1),this.toneMapped===!1&&(i.toneMapped=!1),this.fog===!1&&(i.fog=!1),Object.keys(this.userData).length>0&&(i.userData=this.userData);function r(s){const o=[];for(const a in s){const l=s[a];delete l.metadata,o.push(l)}return o}if(t){const s=r(e.textures),o=r(e.images);s.length>0&&(i.textures=s),o.length>0&&(i.images=o)}return i}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;const t=e.clippingPlanes;let i=null;if(t!==null){const r=t.length;i=new Array(r);for(let s=0;s!==r;++s)i[s]=t[s].clone()}return this.clippingPlanes=i,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.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++}}class Ir extends ti{constructor(e){super(),this.isMeshBasicMaterial=!0,this.type="MeshBasicMaterial",this.color=new ze(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.combine=bf,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.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}}const Lo=H2();function H2(){const n=new ArrayBuffer(4),e=new Float32Array(n),t=new Uint32Array(n),i=new Uint32Array(512),r=new Uint32Array(512);for(let l=0;l<256;++l){const c=l-127;c<-27?(i[l]=0,i[l|256]=32768,r[l]=24,r[l|256]=24):c<-14?(i[l]=1024>>-c-14,i[l|256]=1024>>-c-14|32768,r[l]=-c-1,r[l|256]=-c-1):c<=15?(i[l]=c+15<<10,i[l|256]=c+15<<10|32768,r[l]=13,r[l|256]=13):c<128?(i[l]=31744,i[l|256]=64512,r[l]=24,r[l|256]=24):(i[l]=31744,i[l|256]=64512,r[l]=13,r[l|256]=13)}const s=new Uint32Array(2048),o=new Uint32Array(64),a=new Uint32Array(64);for(let l=1;l<1024;++l){let c=l<<13,h=0;for(;!(c&8388608);)c<<=1,h-=8388608;c&=-8388609,h+=947912704,s[l]=c|h}for(let l=1024;l<2048;++l)s[l]=939524096+(l-1024<<13);for(let l=1;l<31;++l)o[l]=l<<23;o[31]=1199570944,o[32]=2147483648;for(let l=33;l<63;++l)o[l]=2147483648+(l-32<<23);o[63]=3347054592;for(let l=1;l<64;++l)l!==32&&(a[l]=1024);return{floatView:e,uint32View:t,baseTable:i,shiftTable:r,mantissaTable:s,exponentTable:o,offsetTable:a}}function ar(n){Math.abs(n)>65504,n=Hn(n,-65504,65504),Lo.floatView[0]=n;const e=Lo.uint32View[0],t=e>>23&511;return Lo.baseTable[t]+((e&8388607)>>Lo.shiftTable[t])}function Sp(n){const e=n>>10;return Lo.uint32View[0]=Lo.mantissaTable[Lo.offsetTable[e]+(n&1023)]+Lo.exponentTable[e],Lo.floatView[0]}const Dl={toHalfFloat:ar,fromHalfFloat:Sp},$n=new N,Mm=new we;class Xt{constructor(e,t,i=!1){if(Array.isArray(e))throw new TypeError("THREE.BufferAttribute: array should be a Typed Array.");this.isBufferAttribute=!0,this.name="",this.array=e,this.itemSize=t,this.count=e!==void 0?e.length/t:0,this.normalized=i,this.usage=ff,this._updateRange={offset:0,count:-1},this.updateRanges=[],this.gpuType=Ei,this.version=0}onUploadCallback(){}set needsUpdate(e){e===!0&&this.version++}get updateRange(){return this._updateRange}setUsage(e){return this.usage=e,this}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}copy(e){return this.name=e.name,this.array=new e.array.constructor(e.array),this.itemSize=e.itemSize,this.count=e.count,this.normalized=e.normalized,this.usage=e.usage,this.gpuType=e.gpuType,this}copyAt(e,t,i){e*=this.itemSize,i*=t.itemSize;for(let r=0,s=this.itemSize;r<s;r++)this.array[e+r]=t.array[i+r];return this}copyArray(e){return this.array.set(e),this}applyMatrix3(e){if(this.itemSize===2)for(let t=0,i=this.count;t<i;t++)Mm.fromBufferAttribute(this,t),Mm.applyMatrix3(e),this.setXY(t,Mm.x,Mm.y);else if(this.itemSize===3)for(let t=0,i=this.count;t<i;t++)$n.fromBufferAttribute(this,t),$n.applyMatrix3(e),this.setXYZ(t,$n.x,$n.y,$n.z);return this}applyMatrix4(e){for(let t=0,i=this.count;t<i;t++)$n.fromBufferAttribute(this,t),$n.applyMatrix4(e),this.setXYZ(t,$n.x,$n.y,$n.z);return this}applyNormalMatrix(e){for(let t=0,i=this.count;t<i;t++)$n.fromBufferAttribute(this,t),$n.applyNormalMatrix(e),this.setXYZ(t,$n.x,$n.y,$n.z);return this}transformDirection(e){for(let t=0,i=this.count;t<i;t++)$n.fromBufferAttribute(this,t),$n.transformDirection(e),this.setXYZ(t,$n.x,$n.y,$n.z);return this}set(e,t=0){return this.array.set(e,t),this}getComponent(e,t){let i=this.array[e*this.itemSize+t];return this.normalized&&(i=fr(i,this.array)),i}setComponent(e,t,i){return this.normalized&&(i=Ft(i,this.array)),this.array[e*this.itemSize+t]=i,this}getX(e){let t=this.array[e*this.itemSize];return this.normalized&&(t=fr(t,this.array)),t}setX(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize]=t,this}getY(e){let t=this.array[e*this.itemSize+1];return this.normalized&&(t=fr(t,this.array)),t}setY(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize+1]=t,this}getZ(e){let t=this.array[e*this.itemSize+2];return this.normalized&&(t=fr(t,this.array)),t}setZ(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize+2]=t,this}getW(e){let t=this.array[e*this.itemSize+3];return this.normalized&&(t=fr(t,this.array)),t}setW(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize+3]=t,this}setXY(e,t,i){return e*=this.itemSize,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array)),this.array[e+0]=t,this.array[e+1]=i,this}setXYZ(e,t,i,r){return e*=this.itemSize,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array),r=Ft(r,this.array)),this.array[e+0]=t,this.array[e+1]=i,this.array[e+2]=r,this}setXYZW(e,t,i,r,s){return e*=this.itemSize,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array),r=Ft(r,this.array),s=Ft(s,this.array)),this.array[e+0]=t,this.array[e+1]=i,this.array[e+2]=r,this.array[e+3]=s,this}onUpload(e){return this.onUploadCallback=e,this}clone(){return new this.constructor(this.array,this.itemSize).copy(this)}toJSON(){const e={itemSize:this.itemSize,type:this.array.constructor.name,array:Array.from(this.array),normalized:this.normalized};return this.name!==""&&(e.name=this.name),this.usage!==ff&&(e.usage=this.usage),e}}class z2 extends Xt{constructor(e,t,i){super(new Int8Array(e),t,i)}}class G2 extends Xt{constructor(e,t,i){super(new Uint8Array(e),t,i)}}class V2 extends Xt{constructor(e,t,i){super(new Uint8ClampedArray(e),t,i)}}class q2 extends Xt{constructor(e,t,i){super(new Int16Array(e),t,i)}}class rA extends Xt{constructor(e,t,i){super(new Uint16Array(e),t,i)}}class Y2 extends Xt{constructor(e,t,i){super(new Int32Array(e),t,i)}}class rw extends Xt{constructor(e,t,i){super(new Uint32Array(e),t,i)}}class Z2 extends Xt{constructor(e,t,i){super(new Uint16Array(e),t,i),this.isFloat16BufferAttribute=!0}getX(e){let t=Sp(this.array[e*this.itemSize]);return this.normalized&&(t=fr(t,this.array)),t}setX(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize]=ar(t),this}getY(e){let t=Sp(this.array[e*this.itemSize+1]);return this.normalized&&(t=fr(t,this.array)),t}setY(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize+1]=ar(t),this}getZ(e){let t=Sp(this.array[e*this.itemSize+2]);return this.normalized&&(t=fr(t,this.array)),t}setZ(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize+2]=ar(t),this}getW(e){let t=Sp(this.array[e*this.itemSize+3]);return this.normalized&&(t=fr(t,this.array)),t}setW(e,t){return this.normalized&&(t=Ft(t,this.array)),this.array[e*this.itemSize+3]=ar(t),this}setXY(e,t,i){return e*=this.itemSize,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array)),this.array[e+0]=ar(t),this.array[e+1]=ar(i),this}setXYZ(e,t,i,r){return e*=this.itemSize,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array),r=Ft(r,this.array)),this.array[e+0]=ar(t),this.array[e+1]=ar(i),this.array[e+2]=ar(r),this}setXYZW(e,t,i,r,s){return e*=this.itemSize,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array),r=Ft(r,this.array),s=Ft(s,this.array)),this.array[e+0]=ar(t),this.array[e+1]=ar(i),this.array[e+2]=ar(r),this.array[e+3]=ar(s),this}}class ot extends Xt{constructor(e,t,i){super(new Float32Array(e),t,i)}}class j2 extends Xt{constructor(e,t,i){super(new Float64Array(e),t,i)}}let X2=0;const Yr=new tt,x0=new Wt,Nc=new N,Mr=new Pi,Xh=new Pi,fi=new N;class Tt extends co{constructor(){super(),this.isBufferGeometry=!0,Object.defineProperty(this,"id",{value:X2++}),this.uuid=Br(),this.name="",this.type="BufferGeometry",this.index=null,this.attributes={},this.morphAttributes={},this.morphTargetsRelative=!1,this.groups=[],this.boundingBox=null,this.boundingSphere=null,this.drawRange={start:0,count:1/0},this.userData={}}getIndex(){return this.index}setIndex(e){return Array.isArray(e)?this.index=new(rR(e)?rw:rA)(e,1):this.index=e,this}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 0}addGroup(e,t,i=0){this.groups.push({start:e,count:t,materialIndex:i})}clearGroups(){this.groups=[]}setDrawRange(e,t){this.drawRange.start=e,this.drawRange.count=t}applyMatrix4(e){const t=this.attributes.position;t!==void 0&&(t.applyMatrix4(e),t.needsUpdate=!0);const i=this.attributes.normal;if(i!==void 0){const s=new Ot().getNormalMatrix(e);i.applyNormalMatrix(s),i.needsUpdate=!0}const r=this.attributes.tangent;return r!==void 0&&(r.transformDirection(e),r.needsUpdate=!0),this.boundingBox!==null&&this.computeBoundingBox(),this.boundingSphere!==null&&this.computeBoundingSphere(),this}applyQuaternion(e){return Yr.makeRotationFromQuaternion(e),this.applyMatrix4(Yr),this}rotateX(e){return Yr.makeRotationX(e),this.applyMatrix4(Yr),this}rotateY(e){return Yr.makeRotationY(e),this.applyMatrix4(Yr),this}rotateZ(e){return Yr.makeRotationZ(e),this.applyMatrix4(Yr),this}translate(e,t,i){return Yr.makeTranslation(e,t,i),this.applyMatrix4(Yr),this}scale(e,t,i){return Yr.makeScale(e,t,i),this.applyMatrix4(Yr),this}lookAt(e){return x0.lookAt(e),x0.updateMatrix(),this.applyMatrix4(x0.matrix),this}center(){return this.computeBoundingBox(),this.boundingBox.getCenter(Nc).negate(),this.translate(Nc.x,Nc.y,Nc.z),this}setFromPoints(e){const t=[];for(let i=0,r=e.length;i<r;i++){const s=e[i];t.push(s.x,s.y,s.z||0)}return this.setAttribute("position",new ot(t,3)),this}computeBoundingBox(){this.boundingBox===null&&(this.boundingBox=new Pi);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute){this.boundingBox.set(new N(-1/0,-1/0,-1/0),new N(1/0,1/0,1/0));return}if(e!==void 0){if(this.boundingBox.setFromBufferAttribute(e),t)for(let i=0,r=t.length;i<r;i++){const s=t[i];Mr.setFromBufferAttribute(s),this.morphTargetsRelative?(fi.addVectors(this.boundingBox.min,Mr.min),this.boundingBox.expandByPoint(fi),fi.addVectors(this.boundingBox.max,Mr.max),this.boundingBox.expandByPoint(fi)):(this.boundingBox.expandByPoint(Mr.min),this.boundingBox.expandByPoint(Mr.max))}}else this.boundingBox.makeEmpty();isNaN(this.boundingBox.min.x)||isNaN(this.boundingBox.min.y)||isNaN(this.boundingBox.min.z)}computeBoundingSphere(){this.boundingSphere===null&&(this.boundingSphere=new vi);const e=this.attributes.position,t=this.morphAttributes.position;if(e&&e.isGLBufferAttribute){this.boundingSphere.set(new N,1/0);return}if(e){const i=this.boundingSphere.center;if(Mr.setFromBufferAttribute(e),t)for(let s=0,o=t.length;s<o;s++){const a=t[s];Xh.setFromBufferAttribute(a),this.morphTargetsRelative?(fi.addVectors(Mr.min,Xh.min),Mr.expandByPoint(fi),fi.addVectors(Mr.max,Xh.max),Mr.expandByPoint(fi)):(Mr.expandByPoint(Xh.min),Mr.expandByPoint(Xh.max))}Mr.getCenter(i);let r=0;for(let s=0,o=e.count;s<o;s++)fi.fromBufferAttribute(e,s),r=Math.max(r,i.distanceToSquared(fi));if(t)for(let s=0,o=t.length;s<o;s++){const a=t[s],l=this.morphTargetsRelative;for(let c=0,h=a.count;c<h;c++)fi.fromBufferAttribute(a,c),l&&(Nc.fromBufferAttribute(e,c),fi.add(Nc)),r=Math.max(r,i.distanceToSquared(fi))}this.boundingSphere.radius=Math.sqrt(r),isNaN(this.boundingSphere.radius)}}computeTangents(){const e=this.index,t=this.attributes;if(e===null||t.position===void 0||t.normal===void 0||t.uv===void 0)return;const i=e.array,r=t.position.array,s=t.normal.array,o=t.uv.array,a=r.length/3;this.hasAttribute("tangent")===!1&&this.setAttribute("tangent",new Xt(new Float32Array(4*a),4));const l=this.getAttribute("tangent").array,c=[],h=[];for(let L=0;L<a;L++)c[L]=new N,h[L]=new N;const f=new N,d=new N,m=new N,g=new we,E=new we,C=new we,S=new N,v=new N;function y(L,O,V){f.fromArray(r,L*3),d.fromArray(r,O*3),m.fromArray(r,V*3),g.fromArray(o,L*2),E.fromArray(o,O*2),C.fromArray(o,V*2),d.sub(f),m.sub(f),E.sub(g),C.sub(g);const ie=1/(E.x*C.y-C.x*E.y);isFinite(ie)&&(S.copy(d).multiplyScalar(C.y).addScaledVector(m,-E.y).multiplyScalar(ie),v.copy(m).multiplyScalar(E.x).addScaledVector(d,-C.x).multiplyScalar(ie),c[L].add(S),c[O].add(S),c[V].add(S),h[L].add(v),h[O].add(v),h[V].add(v))}let w=this.groups;w.length===0&&(w=[{start:0,count:i.length}]);for(let L=0,O=w.length;L<O;++L){const V=w[L],ie=V.start,W=V.count;for(let _=ie,ne=ie+W;_<ne;_+=3)y(i[_+0],i[_+1],i[_+2])}const x=new N,k=new N,I=new N,R=new N;function T(L){I.fromArray(s,L*3),R.copy(I);const O=c[L];x.copy(O),x.sub(I.multiplyScalar(I.dot(O))).normalize(),k.crossVectors(R,O);const ie=k.dot(h[L])<0?-1:1;l[L*4]=x.x,l[L*4+1]=x.y,l[L*4+2]=x.z,l[L*4+3]=ie}for(let L=0,O=w.length;L<O;++L){const V=w[L],ie=V.start,W=V.count;for(let _=ie,ne=ie+W;_<ne;_+=3)T(i[_+0]),T(i[_+1]),T(i[_+2])}}computeVertexNormals(){const e=this.index,t=this.getAttribute("position");if(t!==void 0){let i=this.getAttribute("normal");if(i===void 0)i=new Xt(new Float32Array(t.count*3),3),this.setAttribute("normal",i);else for(let d=0,m=i.count;d<m;d++)i.setXYZ(d,0,0,0);const r=new N,s=new N,o=new N,a=new N,l=new N,c=new N,h=new N,f=new N;if(e)for(let d=0,m=e.count;d<m;d+=3){const g=e.getX(d+0),E=e.getX(d+1),C=e.getX(d+2);r.fromBufferAttribute(t,g),s.fromBufferAttribute(t,E),o.fromBufferAttribute(t,C),h.subVectors(o,s),f.subVectors(r,s),h.cross(f),a.fromBufferAttribute(i,g),l.fromBufferAttribute(i,E),c.fromBufferAttribute(i,C),a.add(h),l.add(h),c.add(h),i.setXYZ(g,a.x,a.y,a.z),i.setXYZ(E,l.x,l.y,l.z),i.setXYZ(C,c.x,c.y,c.z)}else for(let d=0,m=t.count;d<m;d+=3)r.fromBufferAttribute(t,d+0),s.fromBufferAttribute(t,d+1),o.fromBufferAttribute(t,d+2),h.subVectors(o,s),f.subVectors(r,s),h.cross(f),i.setXYZ(d+0,h.x,h.y,h.z),i.setXYZ(d+1,h.x,h.y,h.z),i.setXYZ(d+2,h.x,h.y,h.z);this.normalizeNormals(),i.needsUpdate=!0}}normalizeNormals(){const e=this.attributes.normal;for(let t=0,i=e.count;t<i;t++)fi.fromBufferAttribute(e,t),fi.normalize(),e.setXYZ(t,fi.x,fi.y,fi.z)}toNonIndexed(){function e(a,l){const c=a.array,h=a.itemSize,f=a.normalized,d=new c.constructor(l.length*h);let m=0,g=0;for(let E=0,C=l.length;E<C;E++){a.isInterleavedBufferAttribute?m=l[E]*a.data.stride+a.offset:m=l[E]*h;for(let S=0;S<h;S++)d[g++]=c[m++]}return new Xt(d,h,f)}if(this.index===null)return this;const t=new Tt,i=this.index.array,r=this.attributes;for(const a in r){const l=r[a],c=e(l,i);t.setAttribute(a,c)}const s=this.morphAttributes;for(const a in s){const l=[],c=s[a];for(let h=0,f=c.length;h<f;h++){const d=c[h],m=e(d,i);l.push(m)}t.morphAttributes[a]=l}t.morphTargetsRelative=this.morphTargetsRelative;const o=this.groups;for(let a=0,l=o.length;a<l;a++){const c=o[a];t.addGroup(c.start,c.count,c.materialIndex)}return t}toJSON(){const e={metadata:{version:4.6,type:"BufferGeometry",generator:"BufferGeometry.toJSON"}};if(e.uuid=this.uuid,e.type=this.type,this.name!==""&&(e.name=this.name),Object.keys(this.userData).length>0&&(e.userData=this.userData),this.parameters!==void 0){const l=this.parameters;for(const c in l)l[c]!==void 0&&(e[c]=l[c]);return e}e.data={attributes:{}};const t=this.index;t!==null&&(e.data.index={type:t.array.constructor.name,array:Array.prototype.slice.call(t.array)});const i=this.attributes;for(const l in i){const c=i[l];e.data.attributes[l]=c.toJSON(e.data)}const r={};let s=!1;for(const l in this.morphAttributes){const c=this.morphAttributes[l],h=[];for(let f=0,d=c.length;f<d;f++){const m=c[f];h.push(m.toJSON(e.data))}h.length>0&&(r[l]=h,s=!0)}s&&(e.data.morphAttributes=r,e.data.morphTargetsRelative=this.morphTargetsRelative);const o=this.groups;o.length>0&&(e.data.groups=JSON.parse(JSON.stringify(o)));const a=this.boundingSphere;return a!==null&&(e.data.boundingSphere={center:a.center.toArray(),radius:a.radius}),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;const t={};this.name=e.name;const i=e.index;i!==null&&this.setIndex(i.clone(t));const r=e.attributes;for(const c in r){const h=r[c];this.setAttribute(c,h.clone(t))}const s=e.morphAttributes;for(const c in s){const h=[],f=s[c];for(let d=0,m=f.length;d<m;d++)h.push(f[d].clone(t));this.morphAttributes[c]=h}this.morphTargetsRelative=e.morphTargetsRelative;const o=e.groups;for(let c=0,h=o.length;c<h;c++){const f=o[c];this.addGroup(f.start,f.count,f.materialIndex)}const a=e.boundingBox;a!==null&&(this.boundingBox=a.clone());const l=e.boundingSphere;return l!==null&&(this.boundingSphere=l.clone()),this.drawRange.start=e.drawRange.start,this.drawRange.count=e.drawRange.count,this.userData=e.userData,this}dispose(){this.dispatchEvent({type:"dispose"})}}const CT=new tt,hl=new pc,km=new vi,vT=new N,Qc=new N,Wc=new N,Hc=new N,T0=new N,xm=new N,Tm=new we,Jm=new we,Im=new we,UT=new N,wT=new N,MT=new N,Lm=new N,Bm=new N;class Gn extends Wt{constructor(e=new Tt,t=new Ir){super(),this.isMesh=!0,this.type="Mesh",this.geometry=e,this.material=t,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(){const t=this.geometry.morphAttributes,i=Object.keys(t);if(i.length>0){const r=t[i[0]];if(r!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let s=0,o=r.length;s<o;s++){const a=r[s].name||String(s);this.morphTargetInfluences.push(0),this.morphTargetDictionary[a]=s}}}}getVertexPosition(e,t){const i=this.geometry,r=i.attributes.position,s=i.morphAttributes.position,o=i.morphTargetsRelative;t.fromBufferAttribute(r,e);const a=this.morphTargetInfluences;if(s&&a){xm.set(0,0,0);for(let l=0,c=s.length;l<c;l++){const h=a[l],f=s[l];h!==0&&(T0.fromBufferAttribute(f,e),o?xm.addScaledVector(T0,h):xm.addScaledVector(T0.sub(t),h))}t.add(xm)}return t}raycast(e,t){const i=this.geometry,r=this.material,s=this.matrixWorld;r!==void 0&&(i.boundingSphere===null&&i.computeBoundingSphere(),km.copy(i.boundingSphere),km.applyMatrix4(s),hl.copy(e.ray).recast(e.near),!(km.containsPoint(hl.origin)===!1&&(hl.intersectSphere(km,vT)===null||hl.origin.distanceToSquared(vT)>(e.far-e.near)**2))&&(CT.copy(s).invert(),hl.copy(e.ray).applyMatrix4(CT),!(i.boundingBox!==null&&hl.intersectsBox(i.boundingBox)===!1)&&this._computeIntersections(e,t,hl)))}_computeIntersections(e,t,i){let r;const s=this.geometry,o=this.material,a=s.index,l=s.attributes.position,c=s.attributes.uv,h=s.attributes.uv1,f=s.attributes.normal,d=s.groups,m=s.drawRange;if(a!==null)if(Array.isArray(o))for(let g=0,E=d.length;g<E;g++){const C=d[g],S=o[C.materialIndex],v=Math.max(C.start,m.start),y=Math.min(a.count,Math.min(C.start+C.count,m.start+m.count));for(let w=v,x=y;w<x;w+=3){const k=a.getX(w),I=a.getX(w+1),R=a.getX(w+2);r=Km(this,S,e,i,c,h,f,k,I,R),r&&(r.faceIndex=Math.floor(w/3),r.face.materialIndex=C.materialIndex,t.push(r))}}else{const g=Math.max(0,m.start),E=Math.min(a.count,m.start+m.count);for(let C=g,S=E;C<S;C+=3){const v=a.getX(C),y=a.getX(C+1),w=a.getX(C+2);r=Km(this,o,e,i,c,h,f,v,y,w),r&&(r.faceIndex=Math.floor(C/3),t.push(r))}}else if(l!==void 0)if(Array.isArray(o))for(let g=0,E=d.length;g<E;g++){const C=d[g],S=o[C.materialIndex],v=Math.max(C.start,m.start),y=Math.min(l.count,Math.min(C.start+C.count,m.start+m.count));for(let w=v,x=y;w<x;w+=3){const k=w,I=w+1,R=w+2;r=Km(this,S,e,i,c,h,f,k,I,R),r&&(r.faceIndex=Math.floor(w/3),r.face.materialIndex=C.materialIndex,t.push(r))}}else{const g=Math.max(0,m.start),E=Math.min(l.count,m.start+m.count);for(let C=g,S=E;C<S;C+=3){const v=C,y=C+1,w=C+2;r=Km(this,o,e,i,c,h,f,v,y,w),r&&(r.faceIndex=Math.floor(C/3),t.push(r))}}}}function _2(n,e,t,i,r,s,o,a){let l;if(e.side===$i?l=i.intersectTriangle(o,s,r,!0,a):l=i.intersectTriangle(r,s,o,e.side===to,a),l===null)return null;Bm.copy(a),Bm.applyMatrix4(n.matrixWorld);const c=t.ray.origin.distanceTo(Bm);return c<t.near||c>t.far?null:{distance:c,point:Bm.clone(),object:n}}function Km(n,e,t,i,r,s,o,a,l,c){n.getVertexPosition(a,Qc),n.getVertexPosition(l,Wc),n.getVertexPosition(c,Hc);const h=_2(n,e,t,i,Qc,Wc,Hc,Lm);if(h){r&&(Tm.fromBufferAttribute(r,a),Jm.fromBufferAttribute(r,l),Im.fromBufferAttribute(r,c),h.uv=pr.getInterpolation(Lm,Qc,Wc,Hc,Tm,Jm,Im,new we)),s&&(Tm.fromBufferAttribute(s,a),Jm.fromBufferAttribute(s,l),Im.fromBufferAttribute(s,c),h.uv1=pr.getInterpolation(Lm,Qc,Wc,Hc,Tm,Jm,Im,new we),h.uv2=h.uv1),o&&(UT.fromBufferAttribute(o,a),wT.fromBufferAttribute(o,l),MT.fromBufferAttribute(o,c),h.normal=pr.getInterpolation(Lm,Qc,Wc,Hc,UT,wT,MT,new N),h.normal.dot(i.direction)>0&&h.normal.multiplyScalar(-1));const f={a,b:l,c,normal:new N,materialIndex:0};pr.getNormal(Qc,Wc,Hc,f.normal),h.face=f}return h}class fc extends Tt{constructor(e=1,t=1,i=1,r=1,s=1,o=1){super(),this.type="BoxGeometry",this.parameters={width:e,height:t,depth:i,widthSegments:r,heightSegments:s,depthSegments:o};const a=this;r=Math.floor(r),s=Math.floor(s),o=Math.floor(o);const l=[],c=[],h=[],f=[];let d=0,m=0;g("z","y","x",-1,-1,i,t,e,o,s,0),g("z","y","x",1,-1,i,t,-e,o,s,1),g("x","z","y",1,1,e,i,t,r,o,2),g("x","z","y",1,-1,e,i,-t,r,o,3),g("x","y","z",1,-1,e,t,i,r,s,4),g("x","y","z",-1,-1,e,t,-i,r,s,5),this.setIndex(l),this.setAttribute("position",new ot(c,3)),this.setAttribute("normal",new ot(h,3)),this.setAttribute("uv",new ot(f,2));function g(E,C,S,v,y,w,x,k,I,R,T){const L=w/I,O=x/R,V=w/2,ie=x/2,W=k/2,_=I+1,ne=R+1;let oe=0,H=0;const Z=new N;for(let te=0;te<ne;te++){const ae=te*O-ie;for(let fe=0;fe<_;fe++){const ce=fe*L-V;Z[E]=ce*v,Z[C]=ae*y,Z[S]=W,c.push(Z.x,Z.y,Z.z),Z[E]=0,Z[C]=0,Z[S]=k>0?1:-1,h.push(Z.x,Z.y,Z.z),f.push(fe/I),f.push(1-te/R),oe+=1}}for(let te=0;te<R;te++)for(let ae=0;ae<I;ae++){const fe=d+ae+_*te,ce=d+ae+_*(te+1),me=d+(ae+1)+_*(te+1),Te=d+(ae+1)+_*te;l.push(fe,ce,Te),l.push(ce,me,Te),H+=6}a.addGroup(m,H,T),m+=H,d+=oe}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new fc(e.width,e.height,e.depth,e.widthSegments,e.heightSegments,e.depthSegments)}}function Zu(n){const e={};for(const t in n){e[t]={};for(const i in n[t]){const r=n[t][i];r&&(r.isColor||r.isMatrix3||r.isMatrix4||r.isVector2||r.isVector3||r.isVector4||r.isTexture||r.isQuaternion)?r.isRenderTargetTexture?e[t][i]=null:e[t][i]=r.clone():Array.isArray(r)?e[t][i]=r.slice():e[t][i]=r}}return e}function qi(n){const e={};for(let t=0;t<n.length;t++){const i=Zu(n[t]);for(const r in i)e[r]=i[r]}return e}function $2(n){const e=[];for(let t=0;t<n.length;t++)e.push(n[t].clone());return e}function lR(n){return n.getRenderTarget()===null?n.outputColorSpace:an.workingColorSpace}const cR={clone:Zu,merge:qi};var eW=`void main() {
	gl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );
}`,tW=`void main() {
	gl_FragColor = vec4( 1.0, 0.0, 0.0, 1.0 );
}`;class Ls extends ti{constructor(e){super(),this.isShaderMaterial=!0,this.type="ShaderMaterial",this.defines={},this.uniforms={},this.uniformsGroups=[],this.vertexShader=eW,this.fragmentShader=tW,this.linewidth=1,this.wireframe=!1,this.wireframeLinewidth=1,this.fog=!1,this.lights=!1,this.clipping=!1,this.forceSinglePass=!0,this.extensions={derivatives:!1,fragDepth:!1,drawBuffers:!1,shaderTextureLOD:!1},this.defaultAttributeValues={color:[1,1,1],uv:[0,0],uv1:[0,0]},this.index0AttributeName=void 0,this.uniformsNeedUpdate=!1,this.glslVersion=null,e!==void 0&&this.setValues(e)}copy(e){return super.copy(e),this.fragmentShader=e.fragmentShader,this.vertexShader=e.vertexShader,this.uniforms=Zu(e.uniforms),this.uniformsGroups=$2(e.uniformsGroups),this.defines=Object.assign({},e.defines),this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.fog=e.fog,this.lights=e.lights,this.clipping=e.clipping,this.extensions=Object.assign({},e.extensions),this.glslVersion=e.glslVersion,this}toJSON(e){const t=super.toJSON(e);t.glslVersion=this.glslVersion,t.uniforms={};for(const r in this.uniforms){const o=this.uniforms[r].value;o&&o.isTexture?t.uniforms[r]={type:"t",value:o.toJSON(e).uuid}:o&&o.isColor?t.uniforms[r]={type:"c",value:o.getHex()}:o&&o.isVector2?t.uniforms[r]={type:"v2",value:o.toArray()}:o&&o.isVector3?t.uniforms[r]={type:"v3",value:o.toArray()}:o&&o.isVector4?t.uniforms[r]={type:"v4",value:o.toArray()}:o&&o.isMatrix3?t.uniforms[r]={type:"m3",value:o.toArray()}:o&&o.isMatrix4?t.uniforms[r]={type:"m4",value:o.toArray()}:t.uniforms[r]={value:o}}Object.keys(this.defines).length>0&&(t.defines=this.defines),t.vertexShader=this.vertexShader,t.fragmentShader=this.fragmentShader,t.lights=this.lights,t.clipping=this.clipping;const i={};for(const r in this.extensions)this.extensions[r]===!0&&(i[r]=!0);return Object.keys(i).length>0&&(t.extensions=i),t}}class Ff extends Wt{constructor(){super(),this.isCamera=!0,this.type="Camera",this.matrixWorldInverse=new tt,this.projectionMatrix=new tt,this.projectionMatrixInverse=new tt,this.coordinateSystem=Us}copy(e,t){return super.copy(e,t),this.matrixWorldInverse.copy(e.matrixWorldInverse),this.projectionMatrix.copy(e.projectionMatrix),this.projectionMatrixInverse.copy(e.projectionMatrixInverse),this.coordinateSystem=e.coordinateSystem,this}getWorldDirection(e){return super.getWorldDirection(e).negate()}updateMatrixWorld(e){super.updateMatrixWorld(e),this.matrixWorldInverse.copy(this.matrixWorld).invert()}updateWorldMatrix(e,t){super.updateWorldMatrix(e,t),this.matrixWorldInverse.copy(this.matrixWorld).invert()}clone(){return new this.constructor().copy(this)}}class xn extends Ff{constructor(e=50,t=1,i=.1,r=2e3){super(),this.isPerspectiveCamera=!0,this.type="PerspectiveCamera",this.fov=e,this.zoom=1,this.near=i,this.far=r,this.focus=10,this.aspect=t,this.view=null,this.filmGauge=35,this.filmOffset=0,this.updateProjectionMatrix()}copy(e,t){return super.copy(e,t),this.fov=e.fov,this.zoom=e.zoom,this.near=e.near,this.far=e.far,this.focus=e.focus,this.aspect=e.aspect,this.view=e.view===null?null:Object.assign({},e.view),this.filmGauge=e.filmGauge,this.filmOffset=e.filmOffset,this}setFocalLength(e){const t=.5*this.getFilmHeight()/e;this.fov=Yu*2*Math.atan(t),this.updateProjectionMatrix()}getFocalLength(){const e=Math.tan(Wl*.5*this.fov);return .5*this.getFilmHeight()/e}getEffectiveFOV(){return Yu*2*Math.atan(Math.tan(Wl*.5*this.fov)/this.zoom)}getFilmWidth(){return this.filmGauge*Math.min(this.aspect,1)}getFilmHeight(){return this.filmGauge/Math.max(this.aspect,1)}setViewOffset(e,t,i,r,s,o){this.aspect=e/t,this.view===null&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=e,this.view.fullHeight=t,this.view.offsetX=i,this.view.offsetY=r,this.view.width=s,this.view.height=o,this.updateProjectionMatrix()}clearViewOffset(){this.view!==null&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const e=this.near;let t=e*Math.tan(Wl*.5*this.fov)/this.zoom,i=2*t,r=this.aspect*i,s=-.5*r;const o=this.view;if(this.view!==null&&this.view.enabled){const l=o.fullWidth,c=o.fullHeight;s+=o.offsetX*r/l,t-=o.offsetY*i/c,r*=o.width/l,i*=o.height/c}const a=this.filmOffset;a!==0&&(s+=e*a/this.getFilmWidth()),this.projectionMatrix.makePerspective(s,s+r,t,t-i,e,this.far,this.coordinateSystem),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(e){const t=super.toJSON(e);return t.object.fov=this.fov,t.object.zoom=this.zoom,t.object.near=this.near,t.object.far=this.far,t.object.focus=this.focus,t.object.aspect=this.aspect,this.view!==null&&(t.object.view=Object.assign({},this.view)),t.object.filmGauge=this.filmGauge,t.object.filmOffset=this.filmOffset,t}}const zc=-90,Gc=1;class uR extends Wt{constructor(e,t,i){super(),this.type="CubeCamera",this.renderTarget=i,this.coordinateSystem=null,this.activeMipmapLevel=0;const r=new xn(zc,Gc,e,t);r.layers=this.layers,this.add(r);const s=new xn(zc,Gc,e,t);s.layers=this.layers,this.add(s);const o=new xn(zc,Gc,e,t);o.layers=this.layers,this.add(o);const a=new xn(zc,Gc,e,t);a.layers=this.layers,this.add(a);const l=new xn(zc,Gc,e,t);l.layers=this.layers,this.add(l);const c=new xn(zc,Gc,e,t);c.layers=this.layers,this.add(c)}updateCoordinateSystem(){const e=this.coordinateSystem,t=this.children.concat(),[i,r,s,o,a,l]=t;for(const c of t)this.remove(c);if(e===Us)i.up.set(0,1,0),i.lookAt(1,0,0),r.up.set(0,1,0),r.lookAt(-1,0,0),s.up.set(0,0,-1),s.lookAt(0,1,0),o.up.set(0,0,1),o.lookAt(0,-1,0),a.up.set(0,1,0),a.lookAt(0,0,1),l.up.set(0,1,0),l.lookAt(0,0,-1);else if(e===qu)i.up.set(0,-1,0),i.lookAt(-1,0,0),r.up.set(0,-1,0),r.lookAt(1,0,0),s.up.set(0,0,1),s.lookAt(0,1,0),o.up.set(0,0,-1),o.lookAt(0,-1,0),a.up.set(0,-1,0),a.lookAt(0,0,1),l.up.set(0,-1,0),l.lookAt(0,0,-1);else throw new Error("THREE.CubeCamera.updateCoordinateSystem(): Invalid coordinate system: "+e);for(const c of t)this.add(c),c.updateMatrixWorld()}update(e,t){this.parent===null&&this.updateMatrixWorld();const{renderTarget:i,activeMipmapLevel:r}=this;this.coordinateSystem!==e.coordinateSystem&&(this.coordinateSystem=e.coordinateSystem,this.updateCoordinateSystem());const[s,o,a,l,c,h]=this.children,f=e.getRenderTarget(),d=e.getActiveCubeFace(),m=e.getActiveMipmapLevel(),g=e.xr.enabled;e.xr.enabled=!1;const E=i.texture.generateMipmaps;i.texture.generateMipmaps=!1,e.setRenderTarget(i,0,r),e.render(t,s),e.setRenderTarget(i,1,r),e.render(t,o),e.setRenderTarget(i,2,r),e.render(t,a),e.setRenderTarget(i,3,r),e.render(t,l),e.setRenderTarget(i,4,r),e.render(t,c),i.texture.generateMipmaps=E,e.setRenderTarget(i,5,r),e.render(t,h),e.setRenderTarget(f,d,m),e.xr.enabled=g,i.texture.needsPMREMUpdate=!0}}class Pf extends fn{constructor(e,t,i,r,s,o,a,l,c,h){e=e!==void 0?e:[],t=t!==void 0?t:no,super(e,t,i,r,s,o,a,l,c,h),this.isCubeTexture=!0,this.flipY=!1}get images(){return this.image}set images(e){this.image=e}}class sw extends Is{constructor(e=1,t={}){super(e,e,t),this.isWebGLCubeRenderTarget=!0;const i={width:e,height:e,depth:1},r=[i,i,i,i,i,i];t.encoding!==void 0&&(Bp("THREE.WebGLCubeRenderTarget: option.encoding has been replaced by option.colorSpace."),t.colorSpace=t.encoding===Da?si:Tr),this.texture=new Pf(r,t.mapping,t.wrapS,t.wrapT,t.magFilter,t.minFilter,t.format,t.type,t.anisotropy,t.colorSpace),this.texture.isRenderTargetTexture=!0,this.texture.generateMipmaps=t.generateMipmaps!==void 0?t.generateMipmaps:!1,this.texture.minFilter=t.minFilter!==void 0?t.minFilter:pn}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;const i={uniforms:{tEquirect:{value:null}},vertexShader:`

				varying vec3 vWorldDirection;

				vec3 transformDirection( in vec3 dir, in mat4 matrix ) {

					return normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );

				}

				void main() {

					vWorldDirection = transformDirection( position, modelMatrix );

					#include <begin_vertex>
					#include <project_vertex>

				}
			`,fragmentShader:`

				uniform sampler2D tEquirect;

				varying vec3 vWorldDirection;

				#include <common>

				void main() {

					vec3 direction = normalize( vWorldDirection );

					vec2 sampleUV = equirectUv( direction );

					gl_FragColor = texture2D( tEquirect, sampleUV );

				}
			`},r=new fc(5,5,5),s=new Ls({name:"CubemapFromEquirect",uniforms:Zu(i.uniforms),vertexShader:i.vertexShader,fragmentShader:i.fragmentShader,side:$i,blending:Oo});s.uniforms.tEquirect.value=t;const o=new Gn(r,s),a=t.minFilter;return t.minFilter===ro&&(t.minFilter=pn),new uR(1,10,this).update(e,o),t.minFilter=a,o.geometry.dispose(),o.material.dispose(),this}clear(e,t,i,r){const s=e.getRenderTarget();for(let o=0;o<6;o++)e.setRenderTarget(this,o),e.clear(t,i,r);e.setRenderTarget(s)}}const J0=new N,nW=new N,iW=new Ot;class Jo{constructor(e=new N(1,0,0),t=0){this.isPlane=!0,this.normal=e,this.constant=t}set(e,t){return this.normal.copy(e),this.constant=t,this}setComponents(e,t,i,r){return this.normal.set(e,t,i),this.constant=r,this}setFromNormalAndCoplanarPoint(e,t){return this.normal.copy(e),this.constant=-t.dot(this.normal),this}setFromCoplanarPoints(e,t,i){const r=J0.subVectors(i,t).cross(nW.subVectors(e,t)).normalize();return this.setFromNormalAndCoplanarPoint(r,e),this}copy(e){return this.normal.copy(e.normal),this.constant=e.constant,this}normalize(){const e=1/this.normal.length();return this.normal.multiplyScalar(e),this.constant*=e,this}negate(){return this.constant*=-1,this.normal.negate(),this}distanceToPoint(e){return this.normal.dot(e)+this.constant}distanceToSphere(e){return this.distanceToPoint(e.center)-e.radius}projectPoint(e,t){return t.copy(e).addScaledVector(this.normal,-this.distanceToPoint(e))}intersectLine(e,t){const i=e.delta(J0),r=this.normal.dot(i);if(r===0)return this.distanceToPoint(e.start)===0?t.copy(e.start):null;const s=-(e.start.dot(this.normal)+this.constant)/r;return s<0||s>1?null:t.copy(e.start).addScaledVector(i,s)}intersectsLine(e){const t=this.distanceToPoint(e.start),i=this.distanceToPoint(e.end);return t<0&&i>0||i<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){const i=t||iW.getNormalMatrix(e),r=this.coplanarPoint(J0).applyMatrix4(e),s=this.normal.applyMatrix3(i).normalize();return this.constant=-r.dot(s),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)}}const pl=new vi,Rm=new N;class Nf{constructor(e=new Jo,t=new Jo,i=new Jo,r=new Jo,s=new Jo,o=new Jo){this.planes=[e,t,i,r,s,o]}set(e,t,i,r,s,o){const a=this.planes;return a[0].copy(e),a[1].copy(t),a[2].copy(i),a[3].copy(r),a[4].copy(s),a[5].copy(o),this}copy(e){const t=this.planes;for(let i=0;i<6;i++)t[i].copy(e.planes[i]);return this}setFromProjectionMatrix(e,t=Us){const i=this.planes,r=e.elements,s=r[0],o=r[1],a=r[2],l=r[3],c=r[4],h=r[5],f=r[6],d=r[7],m=r[8],g=r[9],E=r[10],C=r[11],S=r[12],v=r[13],y=r[14],w=r[15];if(i[0].setComponents(l-s,d-c,C-m,w-S).normalize(),i[1].setComponents(l+s,d+c,C+m,w+S).normalize(),i[2].setComponents(l+o,d+h,C+g,w+v).normalize(),i[3].setComponents(l-o,d-h,C-g,w-v).normalize(),i[4].setComponents(l-a,d-f,C-E,w-y).normalize(),t===Us)i[5].setComponents(l+a,d+f,C+E,w+y).normalize();else if(t===qu)i[5].setComponents(a,f,E,y).normalize();else throw new Error("THREE.Frustum.setFromProjectionMatrix(): Invalid coordinate system: "+t);return this}intersectsObject(e){if(e.boundingSphere!==void 0)e.boundingSphere===null&&e.computeBoundingSphere(),pl.copy(e.boundingSphere).applyMatrix4(e.matrixWorld);else{const t=e.geometry;t.boundingSphere===null&&t.computeBoundingSphere(),pl.copy(t.boundingSphere).applyMatrix4(e.matrixWorld)}return this.intersectsSphere(pl)}intersectsSprite(e){return pl.center.set(0,0,0),pl.radius=.7071067811865476,pl.applyMatrix4(e.matrixWorld),this.intersectsSphere(pl)}intersectsSphere(e){const t=this.planes,i=e.center,r=-e.radius;for(let s=0;s<6;s++)if(t[s].distanceToPoint(i)<r)return!1;return!0}intersectsBox(e){const t=this.planes;for(let i=0;i<6;i++){const r=t[i];if(Rm.x=r.normal.x>0?e.max.x:e.min.x,Rm.y=r.normal.y>0?e.max.y:e.min.y,Rm.z=r.normal.z>0?e.max.z:e.min.z,r.distanceToPoint(Rm)<0)return!1}return!0}containsPoint(e){const t=this.planes;for(let i=0;i<6;i++)if(t[i].distanceToPoint(e)<0)return!1;return!0}clone(){return new this.constructor().copy(this)}}function hR(){let n=null,e=!1,t=null,i=null;function r(s,o){t(s,o),i=n.requestAnimationFrame(r)}return{start:function(){e!==!0&&t!==null&&(i=n.requestAnimationFrame(r),e=!0)},stop:function(){n.cancelAnimationFrame(i),e=!1},setAnimationLoop:function(s){t=s},setContext:function(s){n=s}}}function rW(n,e){const t=e.isWebGL2,i=new WeakMap;function r(c,h){const f=c.array,d=c.usage,m=f.byteLength,g=n.createBuffer();n.bindBuffer(h,g),n.bufferData(h,f,d),c.onUploadCallback();let E;if(f instanceof Float32Array)E=n.FLOAT;else if(f instanceof Uint16Array)if(c.isFloat16BufferAttribute)if(t)E=n.HALF_FLOAT;else throw new Error("THREE.WebGLAttributes: Usage of Float16BufferAttribute requires WebGL2.");else E=n.UNSIGNED_SHORT;else if(f instanceof Int16Array)E=n.SHORT;else if(f instanceof Uint32Array)E=n.UNSIGNED_INT;else if(f instanceof Int32Array)E=n.INT;else if(f instanceof Int8Array)E=n.BYTE;else if(f instanceof Uint8Array)E=n.UNSIGNED_BYTE;else if(f instanceof Uint8ClampedArray)E=n.UNSIGNED_BYTE;else throw new Error("THREE.WebGLAttributes: Unsupported buffer data format: "+f);return{buffer:g,type:E,bytesPerElement:f.BYTES_PER_ELEMENT,version:c.version,size:m}}function s(c,h,f){const d=h.array,m=h._updateRange,g=h.updateRanges;if(n.bindBuffer(f,c),m.count===-1&&g.length===0&&n.bufferSubData(f,0,d),g.length!==0){for(let E=0,C=g.length;E<C;E++){const S=g[E];t?n.bufferSubData(f,S.start*d.BYTES_PER_ELEMENT,d,S.start,S.count):n.bufferSubData(f,S.start*d.BYTES_PER_ELEMENT,d.subarray(S.start,S.start+S.count))}h.clearUpdateRanges()}m.count!==-1&&(t?n.bufferSubData(f,m.offset*d.BYTES_PER_ELEMENT,d,m.offset,m.count):n.bufferSubData(f,m.offset*d.BYTES_PER_ELEMENT,d.subarray(m.offset,m.offset+m.count)),m.count=-1),h.onUploadCallback()}function o(c){return c.isInterleavedBufferAttribute&&(c=c.data),i.get(c)}function a(c){c.isInterleavedBufferAttribute&&(c=c.data);const h=i.get(c);h&&(n.deleteBuffer(h.buffer),i.delete(c))}function l(c,h){if(c.isGLBufferAttribute){const d=i.get(c);(!d||d.version<c.version)&&i.set(c,{buffer:c.buffer,type:c.type,bytesPerElement:c.elementSize,version:c.version});return}c.isInterleavedBufferAttribute&&(c=c.data);const f=i.get(c);if(f===void 0)i.set(c,r(c,h));else if(f.version<c.version){if(f.size!==c.array.byteLength)throw new Error("THREE.WebGLAttributes: The size of the buffer attribute's array buffer does not match the original size. Resizing buffer attributes is not supported.");s(f.buffer,c,h),f.version=c.version}}return{get:o,remove:a,update:l}}class Qf extends Tt{constructor(e=1,t=1,i=1,r=1){super(),this.type="PlaneGeometry",this.parameters={width:e,height:t,widthSegments:i,heightSegments:r};const s=e/2,o=t/2,a=Math.floor(i),l=Math.floor(r),c=a+1,h=l+1,f=e/a,d=t/l,m=[],g=[],E=[],C=[];for(let S=0;S<h;S++){const v=S*d-o;for(let y=0;y<c;y++){const w=y*f-s;g.push(w,-v,0),E.push(0,0,1),C.push(y/a),C.push(1-S/l)}}for(let S=0;S<l;S++)for(let v=0;v<a;v++){const y=v+c*S,w=v+c*(S+1),x=v+1+c*(S+1),k=v+1+c*S;m.push(y,w,k),m.push(w,x,k)}this.setIndex(m),this.setAttribute("position",new ot(g,3)),this.setAttribute("normal",new ot(E,3)),this.setAttribute("uv",new ot(C,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Qf(e.width,e.height,e.widthSegments,e.heightSegments)}}var sW=`#ifdef USE_ALPHAHASH
	if ( diffuseColor.a < getAlphaHashThreshold( vPosition ) ) discard;
#endif`,oW=`#ifdef USE_ALPHAHASH
	const float ALPHA_HASH_SCALE = 0.05;
	float hash2D( vec2 value ) {
		return fract( 1.0e4 * sin( 17.0 * value.x + 0.1 * value.y ) * ( 0.1 + abs( sin( 13.0 * value.y + value.x ) ) ) );
	}
	float hash3D( vec3 value ) {
		return hash2D( vec2( hash2D( value.xy ), value.z ) );
	}
	float getAlphaHashThreshold( vec3 position ) {
		float maxDeriv = max(
			length( dFdx( position.xyz ) ),
			length( dFdy( position.xyz ) )
		);
		float pixScale = 1.0 / ( ALPHA_HASH_SCALE * maxDeriv );
		vec2 pixScales = vec2(
			exp2( floor( log2( pixScale ) ) ),
			exp2( ceil( log2( pixScale ) ) )
		);
		vec2 alpha = vec2(
			hash3D( floor( pixScales.x * position.xyz ) ),
			hash3D( floor( pixScales.y * position.xyz ) )
		);
		float lerpFactor = fract( log2( pixScale ) );
		float x = ( 1.0 - lerpFactor ) * alpha.x + lerpFactor * alpha.y;
		float a = min( lerpFactor, 1.0 - lerpFactor );
		vec3 cases = vec3(
			x * x / ( 2.0 * a * ( 1.0 - a ) ),
			( x - 0.5 * a ) / ( 1.0 - a ),
			1.0 - ( ( 1.0 - x ) * ( 1.0 - x ) / ( 2.0 * a * ( 1.0 - a ) ) )
		);
		float threshold = ( x < ( 1.0 - a ) )
			? ( ( x < a ) ? cases.x : cases.y )
			: cases.z;
		return clamp( threshold , 1.0e-6, 1.0 );
	}
#endif`,aW=`#ifdef USE_ALPHAMAP
	diffuseColor.a *= texture2D( alphaMap, vAlphaMapUv ).g;
#endif`,lW=`#ifdef USE_ALPHAMAP
	uniform sampler2D alphaMap;
#endif`,cW=`#ifdef USE_ALPHATEST
	if ( diffuseColor.a < alphaTest ) discard;
#endif`,uW=`#ifdef USE_ALPHATEST
	uniform float alphaTest;
#endif`,hW=`#ifdef USE_AOMAP
	float ambientOcclusion = ( texture2D( aoMap, vAoMapUv ).r - 1.0 ) * aoMapIntensity + 1.0;
	reflectedLight.indirectDiffuse *= ambientOcclusion;
	#if defined( USE_CLEARCOAT ) 
		clearcoatSpecularIndirect *= ambientOcclusion;
	#endif
	#if defined( USE_SHEEN ) 
		sheenSpecularIndirect *= ambientOcclusion;
	#endif
	#if defined( USE_ENVMAP ) && defined( STANDARD )
		float dotNV = saturate( dot( geometryNormal, geometryViewDir ) );
		reflectedLight.indirectSpecular *= computeSpecularOcclusion( dotNV, ambientOcclusion, material.roughness );
	#endif
#endif`,pW=`#ifdef USE_AOMAP
	uniform sampler2D aoMap;
	uniform float aoMapIntensity;
#endif`,fW=`#ifdef USE_BATCHING
	attribute float batchId;
	uniform highp sampler2D batchingTexture;
	mat4 getBatchingMatrix( const in float i ) {
		int size = textureSize( batchingTexture, 0 ).x;
		int j = int( i ) * 4;
		int x = j % size;
		int y = j / size;
		vec4 v1 = texelFetch( batchingTexture, ivec2( x, y ), 0 );
		vec4 v2 = texelFetch( batchingTexture, ivec2( x + 1, y ), 0 );
		vec4 v3 = texelFetch( batchingTexture, ivec2( x + 2, y ), 0 );
		vec4 v4 = texelFetch( batchingTexture, ivec2( x + 3, y ), 0 );
		return mat4( v1, v2, v3, v4 );
	}
#endif`,dW=`#ifdef USE_BATCHING
	mat4 batchingMatrix = getBatchingMatrix( batchId );
#endif`,mW=`vec3 transformed = vec3( position );
#ifdef USE_ALPHAHASH
	vPosition = vec3( position );
#endif`,SW=`vec3 objectNormal = vec3( normal );
#ifdef USE_TANGENT
	vec3 objectTangent = vec3( tangent.xyz );
#endif`,gW=`float G_BlinnPhong_Implicit( ) {
	return 0.25;
}
float D_BlinnPhong( const in float shininess, const in float dotNH ) {
	return RECIPROCAL_PI * ( shininess * 0.5 + 1.0 ) * pow( dotNH, shininess );
}
vec3 BRDF_BlinnPhong( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in vec3 specularColor, const in float shininess ) {
	vec3 halfDir = normalize( lightDir + viewDir );
	float dotNH = saturate( dot( normal, halfDir ) );
	float dotVH = saturate( dot( viewDir, halfDir ) );
	vec3 F = F_Schlick( specularColor, 1.0, dotVH );
	float G = G_BlinnPhong_Implicit( );
	float D = D_BlinnPhong( shininess, dotNH );
	return F * ( G * D );
} // validated`,AW=`#ifdef USE_IRIDESCENCE
	const mat3 XYZ_TO_REC709 = mat3(
		 3.2404542, -0.9692660,  0.0556434,
		-1.5371385,  1.8760108, -0.2040259,
		-0.4985314,  0.0415560,  1.0572252
	);
	vec3 Fresnel0ToIor( vec3 fresnel0 ) {
		vec3 sqrtF0 = sqrt( fresnel0 );
		return ( vec3( 1.0 ) + sqrtF0 ) / ( vec3( 1.0 ) - sqrtF0 );
	}
	vec3 IorToFresnel0( vec3 transmittedIor, float incidentIor ) {
		return pow2( ( transmittedIor - vec3( incidentIor ) ) / ( transmittedIor + vec3( incidentIor ) ) );
	}
	float IorToFresnel0( float transmittedIor, float incidentIor ) {
		return pow2( ( transmittedIor - incidentIor ) / ( transmittedIor + incidentIor ));
	}
	vec3 evalSensitivity( float OPD, vec3 shift ) {
		float phase = 2.0 * PI * OPD * 1.0e-9;
		vec3 val = vec3( 5.4856e-13, 4.4201e-13, 5.2481e-13 );
		vec3 pos = vec3( 1.6810e+06, 1.7953e+06, 2.2084e+06 );
		vec3 var = vec3( 4.3278e+09, 9.3046e+09, 6.6121e+09 );
		vec3 xyz = val * sqrt( 2.0 * PI * var ) * cos( pos * phase + shift ) * exp( - pow2( phase ) * var );
		xyz.x += 9.7470e-14 * sqrt( 2.0 * PI * 4.5282e+09 ) * cos( 2.2399e+06 * phase + shift[ 0 ] ) * exp( - 4.5282e+09 * pow2( phase ) );
		xyz /= 1.0685e-7;
		vec3 rgb = XYZ_TO_REC709 * xyz;
		return rgb;
	}
	vec3 evalIridescence( float outsideIOR, float eta2, float cosTheta1, float thinFilmThickness, vec3 baseF0 ) {
		vec3 I;
		float iridescenceIOR = mix( outsideIOR, eta2, smoothstep( 0.0, 0.03, thinFilmThickness ) );
		float sinTheta2Sq = pow2( outsideIOR / iridescenceIOR ) * ( 1.0 - pow2( cosTheta1 ) );
		float cosTheta2Sq = 1.0 - sinTheta2Sq;
		if ( cosTheta2Sq < 0.0 ) {
			return vec3( 1.0 );
		}
		float cosTheta2 = sqrt( cosTheta2Sq );
		float R0 = IorToFresnel0( iridescenceIOR, outsideIOR );
		float R12 = F_Schlick( R0, 1.0, cosTheta1 );
		float T121 = 1.0 - R12;
		float phi12 = 0.0;
		if ( iridescenceIOR < outsideIOR ) phi12 = PI;
		float phi21 = PI - phi12;
		vec3 baseIOR = Fresnel0ToIor( clamp( baseF0, 0.0, 0.9999 ) );		vec3 R1 = IorToFresnel0( baseIOR, iridescenceIOR );
		vec3 R23 = F_Schlick( R1, 1.0, cosTheta2 );
		vec3 phi23 = vec3( 0.0 );
		if ( baseIOR[ 0 ] < iridescenceIOR ) phi23[ 0 ] = PI;
		if ( baseIOR[ 1 ] < iridescenceIOR ) phi23[ 1 ] = PI;
		if ( baseIOR[ 2 ] < iridescenceIOR ) phi23[ 2 ] = PI;
		float OPD = 2.0 * iridescenceIOR * thinFilmThickness * cosTheta2;
		vec3 phi = vec3( phi21 ) + phi23;
		vec3 R123 = clamp( R12 * R23, 1e-5, 0.9999 );
		vec3 r123 = sqrt( R123 );
		vec3 Rs = pow2( T121 ) * R23 / ( vec3( 1.0 ) - R123 );
		vec3 C0 = R12 + Rs;
		I = C0;
		vec3 Cm = Rs - T121;
		for ( int m = 1; m <= 2; ++ m ) {
			Cm *= r123;
			vec3 Sm = 2.0 * evalSensitivity( float( m ) * OPD, float( m ) * phi );
			I += Cm * Sm;
		}
		return max( I, vec3( 0.0 ) );
	}
#endif`,yW=`#ifdef USE_BUMPMAP
	uniform sampler2D bumpMap;
	uniform float bumpScale;
	vec2 dHdxy_fwd() {
		vec2 dSTdx = dFdx( vBumpMapUv );
		vec2 dSTdy = dFdy( vBumpMapUv );
		float Hll = bumpScale * texture2D( bumpMap, vBumpMapUv ).x;
		float dBx = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdx ).x - Hll;
		float dBy = bumpScale * texture2D( bumpMap, vBumpMapUv + dSTdy ).x - Hll;
		return vec2( dBx, dBy );
	}
	vec3 perturbNormalArb( vec3 surf_pos, vec3 surf_norm, vec2 dHdxy, float faceDirection ) {
		vec3 vSigmaX = normalize( dFdx( surf_pos.xyz ) );
		vec3 vSigmaY = normalize( dFdy( surf_pos.xyz ) );
		vec3 vN = surf_norm;
		vec3 R1 = cross( vSigmaY, vN );
		vec3 R2 = cross( vN, vSigmaX );
		float fDet = dot( vSigmaX, R1 ) * faceDirection;
		vec3 vGrad = sign( fDet ) * ( dHdxy.x * R1 + dHdxy.y * R2 );
		return normalize( abs( fDet ) * surf_norm - vGrad );
	}
#endif`,EW=`#if NUM_CLIPPING_PLANES > 0
	vec4 plane;
	#pragma unroll_loop_start
	for ( int i = 0; i < UNION_CLIPPING_PLANES; i ++ ) {
		plane = clippingPlanes[ i ];
		if ( dot( vClipPosition, plane.xyz ) > plane.w ) discard;
	}
	#pragma unroll_loop_end
	#if UNION_CLIPPING_PLANES < NUM_CLIPPING_PLANES
		bool clipped = true;
		#pragma unroll_loop_start
		for ( int i = UNION_CLIPPING_PLANES; i < NUM_CLIPPING_PLANES; i ++ ) {
			plane = clippingPlanes[ i ];
			clipped = ( dot( vClipPosition, plane.xyz ) > plane.w ) && clipped;
		}
		#pragma unroll_loop_end
		if ( clipped ) discard;
	#endif
#endif`,CW=`#if NUM_CLIPPING_PLANES > 0
	varying vec3 vClipPosition;
	uniform vec4 clippingPlanes[ NUM_CLIPPING_PLANES ];
#endif`,vW=`#if NUM_CLIPPING_PLANES > 0
	varying vec3 vClipPosition;
#endif`,UW=`#if NUM_CLIPPING_PLANES > 0
	vClipPosition = - mvPosition.xyz;
#endif`,wW=`#if defined( USE_COLOR_ALPHA )
	diffuseColor *= vColor;
#elif defined( USE_COLOR )
	diffuseColor.rgb *= vColor;
#endif`,MW=`#if defined( USE_COLOR_ALPHA )
	varying vec4 vColor;
#elif defined( USE_COLOR )
	varying vec3 vColor;
#endif`,kW=`#if defined( USE_COLOR_ALPHA )
	varying vec4 vColor;
#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )
	varying vec3 vColor;
#endif`,xW=`#if defined( USE_COLOR_ALPHA )
	vColor = vec4( 1.0 );
#elif defined( USE_COLOR ) || defined( USE_INSTANCING_COLOR )
	vColor = vec3( 1.0 );
#endif
#ifdef USE_COLOR
	vColor *= color;
#endif
#ifdef USE_INSTANCING_COLOR
	vColor.xyz *= instanceColor.xyz;
#endif`,TW=`#define PI 3.141592653589793
#define PI2 6.283185307179586
#define PI_HALF 1.5707963267948966
#define RECIPROCAL_PI 0.3183098861837907
#define RECIPROCAL_PI2 0.15915494309189535
#define EPSILON 1e-6
#ifndef saturate
#define saturate( a ) clamp( a, 0.0, 1.0 )
#endif
#define whiteComplement( a ) ( 1.0 - saturate( a ) )
float pow2( const in float x ) { return x*x; }
vec3 pow2( const in vec3 x ) { return x*x; }
float pow3( const in float x ) { return x*x*x; }
float pow4( const in float x ) { float x2 = x*x; return x2*x2; }
float max3( const in vec3 v ) { return max( max( v.x, v.y ), v.z ); }
float average( const in vec3 v ) { return dot( v, vec3( 0.3333333 ) ); }
highp float rand( const in vec2 uv ) {
	const highp float a = 12.9898, b = 78.233, c = 43758.5453;
	highp float dt = dot( uv.xy, vec2( a,b ) ), sn = mod( dt, PI );
	return fract( sin( sn ) * c );
}
#ifdef HIGH_PRECISION
	float precisionSafeLength( vec3 v ) { return length( v ); }
#else
	float precisionSafeLength( vec3 v ) {
		float maxComponent = max3( abs( v ) );
		return length( v / maxComponent ) * maxComponent;
	}
#endif
struct IncidentLight {
	vec3 color;
	vec3 direction;
	bool visible;
};
struct ReflectedLight {
	vec3 directDiffuse;
	vec3 directSpecular;
	vec3 indirectDiffuse;
	vec3 indirectSpecular;
};
#ifdef USE_ALPHAHASH
	varying vec3 vPosition;
#endif
vec3 transformDirection( in vec3 dir, in mat4 matrix ) {
	return normalize( ( matrix * vec4( dir, 0.0 ) ).xyz );
}
vec3 inverseTransformDirection( in vec3 dir, in mat4 matrix ) {
	return normalize( ( vec4( dir, 0.0 ) * matrix ).xyz );
}
mat3 transposeMat3( const in mat3 m ) {
	mat3 tmp;
	tmp[ 0 ] = vec3( m[ 0 ].x, m[ 1 ].x, m[ 2 ].x );
	tmp[ 1 ] = vec3( m[ 0 ].y, m[ 1 ].y, m[ 2 ].y );
	tmp[ 2 ] = vec3( m[ 0 ].z, m[ 1 ].z, m[ 2 ].z );
	return tmp;
}
float luminance( const in vec3 rgb ) {
	const vec3 weights = vec3( 0.2126729, 0.7151522, 0.0721750 );
	return dot( weights, rgb );
}
bool isPerspectiveMatrix( mat4 m ) {
	return m[ 2 ][ 3 ] == - 1.0;
}
vec2 equirectUv( in vec3 dir ) {
	float u = atan( dir.z, dir.x ) * RECIPROCAL_PI2 + 0.5;
	float v = asin( clamp( dir.y, - 1.0, 1.0 ) ) * RECIPROCAL_PI + 0.5;
	return vec2( u, v );
}
vec3 BRDF_Lambert( const in vec3 diffuseColor ) {
	return RECIPROCAL_PI * diffuseColor;
}
vec3 F_Schlick( const in vec3 f0, const in float f90, const in float dotVH ) {
	float fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );
	return f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );
}
float F_Schlick( const in float f0, const in float f90, const in float dotVH ) {
	float fresnel = exp2( ( - 5.55473 * dotVH - 6.98316 ) * dotVH );
	return f0 * ( 1.0 - fresnel ) + ( f90 * fresnel );
} // validated`,JW=`#ifdef ENVMAP_TYPE_CUBE_UV
	#define cubeUV_minMipLevel 4.0
	#define cubeUV_minTileSize 16.0
	float getFace( vec3 direction ) {
		vec3 absDirection = abs( direction );
		float face = - 1.0;
		if ( absDirection.x > absDirection.z ) {
			if ( absDirection.x > absDirection.y )
				face = direction.x > 0.0 ? 0.0 : 3.0;
			else
				face = direction.y > 0.0 ? 1.0 : 4.0;
		} else {
			if ( absDirection.z > absDirection.y )
				face = direction.z > 0.0 ? 2.0 : 5.0;
			else
				face = direction.y > 0.0 ? 1.0 : 4.0;
		}
		return face;
	}
	vec2 getUV( vec3 direction, float face ) {
		vec2 uv;
		if ( face == 0.0 ) {
			uv = vec2( direction.z, direction.y ) / abs( direction.x );
		} else if ( face == 1.0 ) {
			uv = vec2( - direction.x, - direction.z ) / abs( direction.y );
		} else if ( face == 2.0 ) {
			uv = vec2( - direction.x, direction.y ) / abs( direction.z );
		} else if ( face == 3.0 ) {
			uv = vec2( - direction.z, direction.y ) / abs( direction.x );
		} else if ( face == 4.0 ) {
			uv = vec2( - direction.x, direction.z ) / abs( direction.y );
		} else {
			uv = vec2( direction.x, direction.y ) / abs( direction.z );
		}
		return 0.5 * ( uv + 1.0 );
	}
	vec3 bilinearCubeUV( sampler2D envMap, vec3 direction, float mipInt ) {
		float face = getFace( direction );
		float filterInt = max( cubeUV_minMipLevel - mipInt, 0.0 );
		mipInt = max( mipInt, cubeUV_minMipLevel );
		float faceSize = exp2( mipInt );
		highp vec2 uv = getUV( direction, face ) * ( faceSize - 2.0 ) + 1.0;
		if ( face > 2.0 ) {
			uv.y += faceSize;
			face -= 3.0;
		}
		uv.x += face * faceSize;
		uv.x += filterInt * 3.0 * cubeUV_minTileSize;
		uv.y += 4.0 * ( exp2( CUBEUV_MAX_MIP ) - faceSize );
		uv.x *= CUBEUV_TEXEL_WIDTH;
		uv.y *= CUBEUV_TEXEL_HEIGHT;
		#ifdef texture2DGradEXT
			return texture2DGradEXT( envMap, uv, vec2( 0.0 ), vec2( 0.0 ) ).rgb;
		#else
			return texture2D( envMap, uv ).rgb;
		#endif
	}
	#define cubeUV_r0 1.0
	#define cubeUV_v0 0.339
	#define cubeUV_m0 - 2.0
	#define cubeUV_r1 0.8
	#define cubeUV_v1 0.276
	#define cubeUV_m1 - 1.0
	#define cubeUV_r4 0.4
	#define cubeUV_v4 0.046
	#define cubeUV_m4 2.0
	#define cubeUV_r5 0.305
	#define cubeUV_v5 0.016
	#define cubeUV_m5 3.0
	#define cubeUV_r6 0.21
	#define cubeUV_v6 0.0038
	#define cubeUV_m6 4.0
	float roughnessToMip( float roughness ) {
		float mip = 0.0;
		if ( roughness >= cubeUV_r1 ) {
			mip = ( cubeUV_r0 - roughness ) * ( cubeUV_m1 - cubeUV_m0 ) / ( cubeUV_r0 - cubeUV_r1 ) + cubeUV_m0;
		} else if ( roughness >= cubeUV_r4 ) {
			mip = ( cubeUV_r1 - roughness ) * ( cubeUV_m4 - cubeUV_m1 ) / ( cubeUV_r1 - cubeUV_r4 ) + cubeUV_m1;
		} else if ( roughness >= cubeUV_r5 ) {
			mip = ( cubeUV_r4 - roughness ) * ( cubeUV_m5 - cubeUV_m4 ) / ( cubeUV_r4 - cubeUV_r5 ) + cubeUV_m4;
		} else if ( roughness >= cubeUV_r6 ) {
			mip = ( cubeUV_r5 - roughness ) * ( cubeUV_m6 - cubeUV_m5 ) / ( cubeUV_r5 - cubeUV_r6 ) + cubeUV_m5;
		} else {
			mip = - 2.0 * log2( 1.16 * roughness );		}
		return mip;
	}
	vec4 textureCubeUV( sampler2D envMap, vec3 sampleDir, float roughness ) {
		float mip = clamp( roughnessToMip( roughness ), cubeUV_m0, CUBEUV_MAX_MIP );
		float mipF = fract( mip );
		float mipInt = floor( mip );
		vec3 color0 = bilinearCubeUV( envMap, sampleDir, mipInt );
		if ( mipF == 0.0 ) {
			return vec4( color0, 1.0 );
		} else {
			vec3 color1 = bilinearCubeUV( envMap, sampleDir, mipInt + 1.0 );
			return vec4( mix( color0, color1, mipF ), 1.0 );
		}
	}
#endif`,IW=`vec3 transformedNormal = objectNormal;
#ifdef USE_TANGENT
	vec3 transformedTangent = objectTangent;
#endif
#ifdef USE_BATCHING
	mat3 bm = mat3( batchingMatrix );
	transformedNormal /= vec3( dot( bm[ 0 ], bm[ 0 ] ), dot( bm[ 1 ], bm[ 1 ] ), dot( bm[ 2 ], bm[ 2 ] ) );
	transformedNormal = bm * transformedNormal;
	#ifdef USE_TANGENT
		transformedTangent = bm * transformedTangent;
	#endif
#endif
#ifdef USE_INSTANCING
	mat3 im = mat3( instanceMatrix );
	transformedNormal /= vec3( dot( im[ 0 ], im[ 0 ] ), dot( im[ 1 ], im[ 1 ] ), dot( im[ 2 ], im[ 2 ] ) );
	transformedNormal = im * transformedNormal;
	#ifdef USE_TANGENT
		transformedTangent = im * transformedTangent;
	#endif
#endif
transformedNormal = normalMatrix * transformedNormal;
#ifdef FLIP_SIDED
	transformedNormal = - transformedNormal;
#endif
#ifdef USE_TANGENT
	transformedTangent = ( modelViewMatrix * vec4( transformedTangent, 0.0 ) ).xyz;
	#ifdef FLIP_SIDED
		transformedTangent = - transformedTangent;
	#endif
#endif`,LW=`#ifdef USE_DISPLACEMENTMAP
	uniform sampler2D displacementMap;
	uniform float displacementScale;
	uniform float displacementBias;
#endif`,BW=`#ifdef USE_DISPLACEMENTMAP
	transformed += normalize( objectNormal ) * ( texture2D( displacementMap, vDisplacementMapUv ).x * displacementScale + displacementBias );
#endif`,KW=`#ifdef USE_EMISSIVEMAP
	vec4 emissiveColor = texture2D( emissiveMap, vEmissiveMapUv );
	totalEmissiveRadiance *= emissiveColor.rgb;
#endif`,RW=`#ifdef USE_EMISSIVEMAP
	uniform sampler2D emissiveMap;
#endif`,DW="gl_FragColor = linearToOutputTexel( gl_FragColor );",bW=`
const mat3 LINEAR_SRGB_TO_LINEAR_DISPLAY_P3 = mat3(
	vec3( 0.8224621, 0.177538, 0.0 ),
	vec3( 0.0331941, 0.9668058, 0.0 ),
	vec3( 0.0170827, 0.0723974, 0.9105199 )
);
const mat3 LINEAR_DISPLAY_P3_TO_LINEAR_SRGB = mat3(
	vec3( 1.2249401, - 0.2249404, 0.0 ),
	vec3( - 0.0420569, 1.0420571, 0.0 ),
	vec3( - 0.0196376, - 0.0786361, 1.0982735 )
);
vec4 LinearSRGBToLinearDisplayP3( in vec4 value ) {
	return vec4( value.rgb * LINEAR_SRGB_TO_LINEAR_DISPLAY_P3, value.a );
}
vec4 LinearDisplayP3ToLinearSRGB( in vec4 value ) {
	return vec4( value.rgb * LINEAR_DISPLAY_P3_TO_LINEAR_SRGB, value.a );
}
vec4 LinearTransferOETF( in vec4 value ) {
	return value;
}
vec4 sRGBTransferOETF( in vec4 value ) {
	return vec4( mix( pow( value.rgb, vec3( 0.41666 ) ) * 1.055 - vec3( 0.055 ), value.rgb * 12.92, vec3( lessThanEqual( value.rgb, vec3( 0.0031308 ) ) ) ), value.a );
}
vec4 LinearToLinear( in vec4 value ) {
	return value;
}
vec4 LinearTosRGB( in vec4 value ) {
	return sRGBTransferOETF( value );
}`,OW=`#ifdef USE_ENVMAP
	#ifdef ENV_WORLDPOS
		vec3 cameraToFrag;
		if ( isOrthographic ) {
			cameraToFrag = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );
		} else {
			cameraToFrag = normalize( vWorldPosition - cameraPosition );
		}
		vec3 worldNormal = inverseTransformDirection( normal, viewMatrix );
		#ifdef ENVMAP_MODE_REFLECTION
			vec3 reflectVec = reflect( cameraToFrag, worldNormal );
		#else
			vec3 reflectVec = refract( cameraToFrag, worldNormal, refractionRatio );
		#endif
	#else
		vec3 reflectVec = vReflect;
	#endif
	#ifdef ENVMAP_TYPE_CUBE
		vec4 envColor = textureCube( envMap, vec3( flipEnvMap * reflectVec.x, reflectVec.yz ) );
	#else
		vec4 envColor = vec4( 0.0 );
	#endif
	#ifdef ENVMAP_BLENDING_MULTIPLY
		outgoingLight = mix( outgoingLight, outgoingLight * envColor.xyz, specularStrength * reflectivity );
	#elif defined( ENVMAP_BLENDING_MIX )
		outgoingLight = mix( outgoingLight, envColor.xyz, specularStrength * reflectivity );
	#elif defined( ENVMAP_BLENDING_ADD )
		outgoingLight += envColor.xyz * specularStrength * reflectivity;
	#endif
#endif`,FW=`#ifdef USE_ENVMAP
	uniform float envMapIntensity;
	uniform float flipEnvMap;
	#ifdef ENVMAP_TYPE_CUBE
		uniform samplerCube envMap;
	#else
		uniform sampler2D envMap;
	#endif
	
#endif`,PW=`#ifdef USE_ENVMAP
	uniform float reflectivity;
	#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )
		#define ENV_WORLDPOS
	#endif
	#ifdef ENV_WORLDPOS
		varying vec3 vWorldPosition;
		uniform float refractionRatio;
	#else
		varying vec3 vReflect;
	#endif
#endif`,NW=`#ifdef USE_ENVMAP
	#if defined( USE_BUMPMAP ) || defined( USE_NORMALMAP ) || defined( PHONG ) || defined( LAMBERT )
		#define ENV_WORLDPOS
	#endif
	#ifdef ENV_WORLDPOS
		
		varying vec3 vWorldPosition;
	#else
		varying vec3 vReflect;
		uniform float refractionRatio;
	#endif
#endif`,QW=`#ifdef USE_ENVMAP
	#ifdef ENV_WORLDPOS
		vWorldPosition = worldPosition.xyz;
	#else
		vec3 cameraToVertex;
		if ( isOrthographic ) {
			cameraToVertex = normalize( vec3( - viewMatrix[ 0 ][ 2 ], - viewMatrix[ 1 ][ 2 ], - viewMatrix[ 2 ][ 2 ] ) );
		} else {
			cameraToVertex = normalize( worldPosition.xyz - cameraPosition );
		}
		vec3 worldNormal = inverseTransformDirection( transformedNormal, viewMatrix );
		#ifdef ENVMAP_MODE_REFLECTION
			vReflect = reflect( cameraToVertex, worldNormal );
		#else
			vReflect = refract( cameraToVertex, worldNormal, refractionRatio );
		#endif
	#endif
#endif`,WW=`#ifdef USE_FOG
	vFogDepth = - mvPosition.z;
#endif`,HW=`#ifdef USE_FOG
	varying float vFogDepth;
#endif`,zW=`#ifdef USE_FOG
	#ifdef FOG_EXP2
		float fogFactor = 1.0 - exp( - fogDensity * fogDensity * vFogDepth * vFogDepth );
	#else
		float fogFactor = smoothstep( fogNear, fogFar, vFogDepth );
	#endif
	gl_FragColor.rgb = mix( gl_FragColor.rgb, fogColor, fogFactor );
#endif`,GW=`#ifdef USE_FOG
	uniform vec3 fogColor;
	varying float vFogDepth;
	#ifdef FOG_EXP2
		uniform float fogDensity;
	#else
		uniform float fogNear;
		uniform float fogFar;
	#endif
#endif`,VW=`#ifdef USE_GRADIENTMAP
	uniform sampler2D gradientMap;
#endif
vec3 getGradientIrradiance( vec3 normal, vec3 lightDirection ) {
	float dotNL = dot( normal, lightDirection );
	vec2 coord = vec2( dotNL * 0.5 + 0.5, 0.0 );
	#ifdef USE_GRADIENTMAP
		return vec3( texture2D( gradientMap, coord ).r );
	#else
		vec2 fw = fwidth( coord ) * 0.5;
		return mix( vec3( 0.7 ), vec3( 1.0 ), smoothstep( 0.7 - fw.x, 0.7 + fw.x, coord.x ) );
	#endif
}`,qW=`#ifdef USE_LIGHTMAP
	vec4 lightMapTexel = texture2D( lightMap, vLightMapUv );
	vec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;
	reflectedLight.indirectDiffuse += lightMapIrradiance;
#endif`,YW=`#ifdef USE_LIGHTMAP
	uniform sampler2D lightMap;
	uniform float lightMapIntensity;
#endif`,ZW=`LambertMaterial material;
material.diffuseColor = diffuseColor.rgb;
material.specularStrength = specularStrength;`,jW=`varying vec3 vViewPosition;
struct LambertMaterial {
	vec3 diffuseColor;
	float specularStrength;
};
void RE_Direct_Lambert( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {
	float dotNL = saturate( dot( geometryNormal, directLight.direction ) );
	vec3 irradiance = dotNL * directLight.color;
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
void RE_IndirectDiffuse_Lambert( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in LambertMaterial material, inout ReflectedLight reflectedLight ) {
	reflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
#define RE_Direct				RE_Direct_Lambert
#define RE_IndirectDiffuse		RE_IndirectDiffuse_Lambert`,XW=`uniform bool receiveShadow;
uniform vec3 ambientLightColor;
#if defined( USE_LIGHT_PROBES )
	uniform vec3 lightProbe[ 9 ];
#endif
vec3 shGetIrradianceAt( in vec3 normal, in vec3 shCoefficients[ 9 ] ) {
	float x = normal.x, y = normal.y, z = normal.z;
	vec3 result = shCoefficients[ 0 ] * 0.886227;
	result += shCoefficients[ 1 ] * 2.0 * 0.511664 * y;
	result += shCoefficients[ 2 ] * 2.0 * 0.511664 * z;
	result += shCoefficients[ 3 ] * 2.0 * 0.511664 * x;
	result += shCoefficients[ 4 ] * 2.0 * 0.429043 * x * y;
	result += shCoefficients[ 5 ] * 2.0 * 0.429043 * y * z;
	result += shCoefficients[ 6 ] * ( 0.743125 * z * z - 0.247708 );
	result += shCoefficients[ 7 ] * 2.0 * 0.429043 * x * z;
	result += shCoefficients[ 8 ] * 0.429043 * ( x * x - y * y );
	return result;
}
vec3 getLightProbeIrradiance( const in vec3 lightProbe[ 9 ], const in vec3 normal ) {
	vec3 worldNormal = inverseTransformDirection( normal, viewMatrix );
	vec3 irradiance = shGetIrradianceAt( worldNormal, lightProbe );
	return irradiance;
}
vec3 getAmbientLightIrradiance( const in vec3 ambientLightColor ) {
	vec3 irradiance = ambientLightColor;
	return irradiance;
}
float getDistanceAttenuation( const in float lightDistance, const in float cutoffDistance, const in float decayExponent ) {
	#if defined ( LEGACY_LIGHTS )
		if ( cutoffDistance > 0.0 && decayExponent > 0.0 ) {
			return pow( saturate( - lightDistance / cutoffDistance + 1.0 ), decayExponent );
		}
		return 1.0;
	#else
		float distanceFalloff = 1.0 / max( pow( lightDistance, decayExponent ), 0.01 );
		if ( cutoffDistance > 0.0 ) {
			distanceFalloff *= pow2( saturate( 1.0 - pow4( lightDistance / cutoffDistance ) ) );
		}
		return distanceFalloff;
	#endif
}
float getSpotAttenuation( const in float coneCosine, const in float penumbraCosine, const in float angleCosine ) {
	return smoothstep( coneCosine, penumbraCosine, angleCosine );
}
#if NUM_DIR_LIGHTS > 0
	struct DirectionalLight {
		vec3 direction;
		vec3 color;
	};
	uniform DirectionalLight directionalLights[ NUM_DIR_LIGHTS ];
	void getDirectionalLightInfo( const in DirectionalLight directionalLight, out IncidentLight light ) {
		light.color = directionalLight.color;
		light.direction = directionalLight.direction;
		light.visible = true;
	}
#endif
#if NUM_POINT_LIGHTS > 0
	struct PointLight {
		vec3 position;
		vec3 color;
		float distance;
		float decay;
	};
	uniform PointLight pointLights[ NUM_POINT_LIGHTS ];
	void getPointLightInfo( const in PointLight pointLight, const in vec3 geometryPosition, out IncidentLight light ) {
		vec3 lVector = pointLight.position - geometryPosition;
		light.direction = normalize( lVector );
		float lightDistance = length( lVector );
		light.color = pointLight.color;
		light.color *= getDistanceAttenuation( lightDistance, pointLight.distance, pointLight.decay );
		light.visible = ( light.color != vec3( 0.0 ) );
	}
#endif
#if NUM_SPOT_LIGHTS > 0
	struct SpotLight {
		vec3 position;
		vec3 direction;
		vec3 color;
		float distance;
		float decay;
		float coneCos;
		float penumbraCos;
	};
	uniform SpotLight spotLights[ NUM_SPOT_LIGHTS ];
	void getSpotLightInfo( const in SpotLight spotLight, const in vec3 geometryPosition, out IncidentLight light ) {
		vec3 lVector = spotLight.position - geometryPosition;
		light.direction = normalize( lVector );
		float angleCos = dot( light.direction, spotLight.direction );
		float spotAttenuation = getSpotAttenuation( spotLight.coneCos, spotLight.penumbraCos, angleCos );
		if ( spotAttenuation > 0.0 ) {
			float lightDistance = length( lVector );
			light.color = spotLight.color * spotAttenuation;
			light.color *= getDistanceAttenuation( lightDistance, spotLight.distance, spotLight.decay );
			light.visible = ( light.color != vec3( 0.0 ) );
		} else {
			light.color = vec3( 0.0 );
			light.visible = false;
		}
	}
#endif
#if NUM_RECT_AREA_LIGHTS > 0
	struct RectAreaLight {
		vec3 color;
		vec3 position;
		vec3 halfWidth;
		vec3 halfHeight;
	};
	uniform sampler2D ltc_1;	uniform sampler2D ltc_2;
	uniform RectAreaLight rectAreaLights[ NUM_RECT_AREA_LIGHTS ];
#endif
#if NUM_HEMI_LIGHTS > 0
	struct HemisphereLight {
		vec3 direction;
		vec3 skyColor;
		vec3 groundColor;
	};
	uniform HemisphereLight hemisphereLights[ NUM_HEMI_LIGHTS ];
	vec3 getHemisphereLightIrradiance( const in HemisphereLight hemiLight, const in vec3 normal ) {
		float dotNL = dot( normal, hemiLight.direction );
		float hemiDiffuseWeight = 0.5 * dotNL + 0.5;
		vec3 irradiance = mix( hemiLight.groundColor, hemiLight.skyColor, hemiDiffuseWeight );
		return irradiance;
	}
#endif`,_W=`#ifdef USE_ENVMAP
	vec3 getIBLIrradiance( const in vec3 normal ) {
		#ifdef ENVMAP_TYPE_CUBE_UV
			vec3 worldNormal = inverseTransformDirection( normal, viewMatrix );
			vec4 envMapColor = textureCubeUV( envMap, worldNormal, 1.0 );
			return PI * envMapColor.rgb * envMapIntensity;
		#else
			return vec3( 0.0 );
		#endif
	}
	vec3 getIBLRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness ) {
		#ifdef ENVMAP_TYPE_CUBE_UV
			vec3 reflectVec = reflect( - viewDir, normal );
			reflectVec = normalize( mix( reflectVec, normal, roughness * roughness) );
			reflectVec = inverseTransformDirection( reflectVec, viewMatrix );
			vec4 envMapColor = textureCubeUV( envMap, reflectVec, roughness );
			return envMapColor.rgb * envMapIntensity;
		#else
			return vec3( 0.0 );
		#endif
	}
	#ifdef USE_ANISOTROPY
		vec3 getIBLAnisotropyRadiance( const in vec3 viewDir, const in vec3 normal, const in float roughness, const in vec3 bitangent, const in float anisotropy ) {
			#ifdef ENVMAP_TYPE_CUBE_UV
				vec3 bentNormal = cross( bitangent, viewDir );
				bentNormal = normalize( cross( bentNormal, bitangent ) );
				bentNormal = normalize( mix( bentNormal, normal, pow2( pow2( 1.0 - anisotropy * ( 1.0 - roughness ) ) ) ) );
				return getIBLRadiance( viewDir, bentNormal, roughness );
			#else
				return vec3( 0.0 );
			#endif
		}
	#endif
#endif`,$W=`ToonMaterial material;
material.diffuseColor = diffuseColor.rgb;`,eH=`varying vec3 vViewPosition;
struct ToonMaterial {
	vec3 diffuseColor;
};
void RE_Direct_Toon( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {
	vec3 irradiance = getGradientIrradiance( geometryNormal, directLight.direction ) * directLight.color;
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
void RE_IndirectDiffuse_Toon( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in ToonMaterial material, inout ReflectedLight reflectedLight ) {
	reflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
#define RE_Direct				RE_Direct_Toon
#define RE_IndirectDiffuse		RE_IndirectDiffuse_Toon`,tH=`BlinnPhongMaterial material;
material.diffuseColor = diffuseColor.rgb;
material.specularColor = specular;
material.specularShininess = shininess;
material.specularStrength = specularStrength;`,nH=`varying vec3 vViewPosition;
struct BlinnPhongMaterial {
	vec3 diffuseColor;
	vec3 specularColor;
	float specularShininess;
	float specularStrength;
};
void RE_Direct_BlinnPhong( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {
	float dotNL = saturate( dot( geometryNormal, directLight.direction ) );
	vec3 irradiance = dotNL * directLight.color;
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
	reflectedLight.directSpecular += irradiance * BRDF_BlinnPhong( directLight.direction, geometryViewDir, geometryNormal, material.specularColor, material.specularShininess ) * material.specularStrength;
}
void RE_IndirectDiffuse_BlinnPhong( const in vec3 irradiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in BlinnPhongMaterial material, inout ReflectedLight reflectedLight ) {
	reflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
#define RE_Direct				RE_Direct_BlinnPhong
#define RE_IndirectDiffuse		RE_IndirectDiffuse_BlinnPhong`,iH=`PhysicalMaterial material;
material.diffuseColor = diffuseColor.rgb * ( 1.0 - metalnessFactor );
vec3 dxy = max( abs( dFdx( nonPerturbedNormal ) ), abs( dFdy( nonPerturbedNormal ) ) );
float geometryRoughness = max( max( dxy.x, dxy.y ), dxy.z );
material.roughness = max( roughnessFactor, 0.0525 );material.roughness += geometryRoughness;
material.roughness = min( material.roughness, 1.0 );
#ifdef IOR
	material.ior = ior;
	#ifdef USE_SPECULAR
		float specularIntensityFactor = specularIntensity;
		vec3 specularColorFactor = specularColor;
		#ifdef USE_SPECULAR_COLORMAP
			specularColorFactor *= texture2D( specularColorMap, vSpecularColorMapUv ).rgb;
		#endif
		#ifdef USE_SPECULAR_INTENSITYMAP
			specularIntensityFactor *= texture2D( specularIntensityMap, vSpecularIntensityMapUv ).a;
		#endif
		material.specularF90 = mix( specularIntensityFactor, 1.0, metalnessFactor );
	#else
		float specularIntensityFactor = 1.0;
		vec3 specularColorFactor = vec3( 1.0 );
		material.specularF90 = 1.0;
	#endif
	material.specularColor = mix( min( pow2( ( material.ior - 1.0 ) / ( material.ior + 1.0 ) ) * specularColorFactor, vec3( 1.0 ) ) * specularIntensityFactor, diffuseColor.rgb, metalnessFactor );
#else
	material.specularColor = mix( vec3( 0.04 ), diffuseColor.rgb, metalnessFactor );
	material.specularF90 = 1.0;
#endif
#ifdef USE_CLEARCOAT
	material.clearcoat = clearcoat;
	material.clearcoatRoughness = clearcoatRoughness;
	material.clearcoatF0 = vec3( 0.04 );
	material.clearcoatF90 = 1.0;
	#ifdef USE_CLEARCOATMAP
		material.clearcoat *= texture2D( clearcoatMap, vClearcoatMapUv ).x;
	#endif
	#ifdef USE_CLEARCOAT_ROUGHNESSMAP
		material.clearcoatRoughness *= texture2D( clearcoatRoughnessMap, vClearcoatRoughnessMapUv ).y;
	#endif
	material.clearcoat = saturate( material.clearcoat );	material.clearcoatRoughness = max( material.clearcoatRoughness, 0.0525 );
	material.clearcoatRoughness += geometryRoughness;
	material.clearcoatRoughness = min( material.clearcoatRoughness, 1.0 );
#endif
#ifdef USE_IRIDESCENCE
	material.iridescence = iridescence;
	material.iridescenceIOR = iridescenceIOR;
	#ifdef USE_IRIDESCENCEMAP
		material.iridescence *= texture2D( iridescenceMap, vIridescenceMapUv ).r;
	#endif
	#ifdef USE_IRIDESCENCE_THICKNESSMAP
		material.iridescenceThickness = (iridescenceThicknessMaximum - iridescenceThicknessMinimum) * texture2D( iridescenceThicknessMap, vIridescenceThicknessMapUv ).g + iridescenceThicknessMinimum;
	#else
		material.iridescenceThickness = iridescenceThicknessMaximum;
	#endif
#endif
#ifdef USE_SHEEN
	material.sheenColor = sheenColor;
	#ifdef USE_SHEEN_COLORMAP
		material.sheenColor *= texture2D( sheenColorMap, vSheenColorMapUv ).rgb;
	#endif
	material.sheenRoughness = clamp( sheenRoughness, 0.07, 1.0 );
	#ifdef USE_SHEEN_ROUGHNESSMAP
		material.sheenRoughness *= texture2D( sheenRoughnessMap, vSheenRoughnessMapUv ).a;
	#endif
#endif
#ifdef USE_ANISOTROPY
	#ifdef USE_ANISOTROPYMAP
		mat2 anisotropyMat = mat2( anisotropyVector.x, anisotropyVector.y, - anisotropyVector.y, anisotropyVector.x );
		vec3 anisotropyPolar = texture2D( anisotropyMap, vAnisotropyMapUv ).rgb;
		vec2 anisotropyV = anisotropyMat * normalize( 2.0 * anisotropyPolar.rg - vec2( 1.0 ) ) * anisotropyPolar.b;
	#else
		vec2 anisotropyV = anisotropyVector;
	#endif
	material.anisotropy = length( anisotropyV );
	if( material.anisotropy == 0.0 ) {
		anisotropyV = vec2( 1.0, 0.0 );
	} else {
		anisotropyV /= material.anisotropy;
		material.anisotropy = saturate( material.anisotropy );
	}
	material.alphaT = mix( pow2( material.roughness ), 1.0, pow2( material.anisotropy ) );
	material.anisotropyT = tbn[ 0 ] * anisotropyV.x + tbn[ 1 ] * anisotropyV.y;
	material.anisotropyB = tbn[ 1 ] * anisotropyV.x - tbn[ 0 ] * anisotropyV.y;
#endif`,rH=`struct PhysicalMaterial {
	vec3 diffuseColor;
	float roughness;
	vec3 specularColor;
	float specularF90;
	#ifdef USE_CLEARCOAT
		float clearcoat;
		float clearcoatRoughness;
		vec3 clearcoatF0;
		float clearcoatF90;
	#endif
	#ifdef USE_IRIDESCENCE
		float iridescence;
		float iridescenceIOR;
		float iridescenceThickness;
		vec3 iridescenceFresnel;
		vec3 iridescenceF0;
	#endif
	#ifdef USE_SHEEN
		vec3 sheenColor;
		float sheenRoughness;
	#endif
	#ifdef IOR
		float ior;
	#endif
	#ifdef USE_TRANSMISSION
		float transmission;
		float transmissionAlpha;
		float thickness;
		float attenuationDistance;
		vec3 attenuationColor;
	#endif
	#ifdef USE_ANISOTROPY
		float anisotropy;
		float alphaT;
		vec3 anisotropyT;
		vec3 anisotropyB;
	#endif
};
vec3 clearcoatSpecularDirect = vec3( 0.0 );
vec3 clearcoatSpecularIndirect = vec3( 0.0 );
vec3 sheenSpecularDirect = vec3( 0.0 );
vec3 sheenSpecularIndirect = vec3(0.0 );
vec3 Schlick_to_F0( const in vec3 f, const in float f90, const in float dotVH ) {
    float x = clamp( 1.0 - dotVH, 0.0, 1.0 );
    float x2 = x * x;
    float x5 = clamp( x * x2 * x2, 0.0, 0.9999 );
    return ( f - vec3( f90 ) * x5 ) / ( 1.0 - x5 );
}
float V_GGX_SmithCorrelated( const in float alpha, const in float dotNL, const in float dotNV ) {
	float a2 = pow2( alpha );
	float gv = dotNL * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNV ) );
	float gl = dotNV * sqrt( a2 + ( 1.0 - a2 ) * pow2( dotNL ) );
	return 0.5 / max( gv + gl, EPSILON );
}
float D_GGX( const in float alpha, const in float dotNH ) {
	float a2 = pow2( alpha );
	float denom = pow2( dotNH ) * ( a2 - 1.0 ) + 1.0;
	return RECIPROCAL_PI * a2 / pow2( denom );
}
#ifdef USE_ANISOTROPY
	float V_GGX_SmithCorrelated_Anisotropic( const in float alphaT, const in float alphaB, const in float dotTV, const in float dotBV, const in float dotTL, const in float dotBL, const in float dotNV, const in float dotNL ) {
		float gv = dotNL * length( vec3( alphaT * dotTV, alphaB * dotBV, dotNV ) );
		float gl = dotNV * length( vec3( alphaT * dotTL, alphaB * dotBL, dotNL ) );
		float v = 0.5 / ( gv + gl );
		return saturate(v);
	}
	float D_GGX_Anisotropic( const in float alphaT, const in float alphaB, const in float dotNH, const in float dotTH, const in float dotBH ) {
		float a2 = alphaT * alphaB;
		highp vec3 v = vec3( alphaB * dotTH, alphaT * dotBH, a2 * dotNH );
		highp float v2 = dot( v, v );
		float w2 = a2 / v2;
		return RECIPROCAL_PI * a2 * pow2 ( w2 );
	}
#endif
#ifdef USE_CLEARCOAT
	vec3 BRDF_GGX_Clearcoat( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material) {
		vec3 f0 = material.clearcoatF0;
		float f90 = material.clearcoatF90;
		float roughness = material.clearcoatRoughness;
		float alpha = pow2( roughness );
		vec3 halfDir = normalize( lightDir + viewDir );
		float dotNL = saturate( dot( normal, lightDir ) );
		float dotNV = saturate( dot( normal, viewDir ) );
		float dotNH = saturate( dot( normal, halfDir ) );
		float dotVH = saturate( dot( viewDir, halfDir ) );
		vec3 F = F_Schlick( f0, f90, dotVH );
		float V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );
		float D = D_GGX( alpha, dotNH );
		return F * ( V * D );
	}
#endif
vec3 BRDF_GGX( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, const in PhysicalMaterial material ) {
	vec3 f0 = material.specularColor;
	float f90 = material.specularF90;
	float roughness = material.roughness;
	float alpha = pow2( roughness );
	vec3 halfDir = normalize( lightDir + viewDir );
	float dotNL = saturate( dot( normal, lightDir ) );
	float dotNV = saturate( dot( normal, viewDir ) );
	float dotNH = saturate( dot( normal, halfDir ) );
	float dotVH = saturate( dot( viewDir, halfDir ) );
	vec3 F = F_Schlick( f0, f90, dotVH );
	#ifdef USE_IRIDESCENCE
		F = mix( F, material.iridescenceFresnel, material.iridescence );
	#endif
	#ifdef USE_ANISOTROPY
		float dotTL = dot( material.anisotropyT, lightDir );
		float dotTV = dot( material.anisotropyT, viewDir );
		float dotTH = dot( material.anisotropyT, halfDir );
		float dotBL = dot( material.anisotropyB, lightDir );
		float dotBV = dot( material.anisotropyB, viewDir );
		float dotBH = dot( material.anisotropyB, halfDir );
		float V = V_GGX_SmithCorrelated_Anisotropic( material.alphaT, alpha, dotTV, dotBV, dotTL, dotBL, dotNV, dotNL );
		float D = D_GGX_Anisotropic( material.alphaT, alpha, dotNH, dotTH, dotBH );
	#else
		float V = V_GGX_SmithCorrelated( alpha, dotNL, dotNV );
		float D = D_GGX( alpha, dotNH );
	#endif
	return F * ( V * D );
}
vec2 LTC_Uv( const in vec3 N, const in vec3 V, const in float roughness ) {
	const float LUT_SIZE = 64.0;
	const float LUT_SCALE = ( LUT_SIZE - 1.0 ) / LUT_SIZE;
	const float LUT_BIAS = 0.5 / LUT_SIZE;
	float dotNV = saturate( dot( N, V ) );
	vec2 uv = vec2( roughness, sqrt( 1.0 - dotNV ) );
	uv = uv * LUT_SCALE + LUT_BIAS;
	return uv;
}
float LTC_ClippedSphereFormFactor( const in vec3 f ) {
	float l = length( f );
	return max( ( l * l + f.z ) / ( l + 1.0 ), 0.0 );
}
vec3 LTC_EdgeVectorFormFactor( const in vec3 v1, const in vec3 v2 ) {
	float x = dot( v1, v2 );
	float y = abs( x );
	float a = 0.8543985 + ( 0.4965155 + 0.0145206 * y ) * y;
	float b = 3.4175940 + ( 4.1616724 + y ) * y;
	float v = a / b;
	float theta_sintheta = ( x > 0.0 ) ? v : 0.5 * inversesqrt( max( 1.0 - x * x, 1e-7 ) ) - v;
	return cross( v1, v2 ) * theta_sintheta;
}
vec3 LTC_Evaluate( const in vec3 N, const in vec3 V, const in vec3 P, const in mat3 mInv, const in vec3 rectCoords[ 4 ] ) {
	vec3 v1 = rectCoords[ 1 ] - rectCoords[ 0 ];
	vec3 v2 = rectCoords[ 3 ] - rectCoords[ 0 ];
	vec3 lightNormal = cross( v1, v2 );
	if( dot( lightNormal, P - rectCoords[ 0 ] ) < 0.0 ) return vec3( 0.0 );
	vec3 T1, T2;
	T1 = normalize( V - N * dot( V, N ) );
	T2 = - cross( N, T1 );
	mat3 mat = mInv * transposeMat3( mat3( T1, T2, N ) );
	vec3 coords[ 4 ];
	coords[ 0 ] = mat * ( rectCoords[ 0 ] - P );
	coords[ 1 ] = mat * ( rectCoords[ 1 ] - P );
	coords[ 2 ] = mat * ( rectCoords[ 2 ] - P );
	coords[ 3 ] = mat * ( rectCoords[ 3 ] - P );
	coords[ 0 ] = normalize( coords[ 0 ] );
	coords[ 1 ] = normalize( coords[ 1 ] );
	coords[ 2 ] = normalize( coords[ 2 ] );
	coords[ 3 ] = normalize( coords[ 3 ] );
	vec3 vectorFormFactor = vec3( 0.0 );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 0 ], coords[ 1 ] );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 1 ], coords[ 2 ] );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 2 ], coords[ 3 ] );
	vectorFormFactor += LTC_EdgeVectorFormFactor( coords[ 3 ], coords[ 0 ] );
	float result = LTC_ClippedSphereFormFactor( vectorFormFactor );
	return vec3( result );
}
#if defined( USE_SHEEN )
float D_Charlie( float roughness, float dotNH ) {
	float alpha = pow2( roughness );
	float invAlpha = 1.0 / alpha;
	float cos2h = dotNH * dotNH;
	float sin2h = max( 1.0 - cos2h, 0.0078125 );
	return ( 2.0 + invAlpha ) * pow( sin2h, invAlpha * 0.5 ) / ( 2.0 * PI );
}
float V_Neubelt( float dotNV, float dotNL ) {
	return saturate( 1.0 / ( 4.0 * ( dotNL + dotNV - dotNL * dotNV ) ) );
}
vec3 BRDF_Sheen( const in vec3 lightDir, const in vec3 viewDir, const in vec3 normal, vec3 sheenColor, const in float sheenRoughness ) {
	vec3 halfDir = normalize( lightDir + viewDir );
	float dotNL = saturate( dot( normal, lightDir ) );
	float dotNV = saturate( dot( normal, viewDir ) );
	float dotNH = saturate( dot( normal, halfDir ) );
	float D = D_Charlie( sheenRoughness, dotNH );
	float V = V_Neubelt( dotNV, dotNL );
	return sheenColor * ( D * V );
}
#endif
float IBLSheenBRDF( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {
	float dotNV = saturate( dot( normal, viewDir ) );
	float r2 = roughness * roughness;
	float a = roughness < 0.25 ? -339.2 * r2 + 161.4 * roughness - 25.9 : -8.48 * r2 + 14.3 * roughness - 9.95;
	float b = roughness < 0.25 ? 44.0 * r2 - 23.7 * roughness + 3.26 : 1.97 * r2 - 3.27 * roughness + 0.72;
	float DG = exp( a * dotNV + b ) + ( roughness < 0.25 ? 0.0 : 0.1 * ( roughness - 0.25 ) );
	return saturate( DG * RECIPROCAL_PI );
}
vec2 DFGApprox( const in vec3 normal, const in vec3 viewDir, const in float roughness ) {
	float dotNV = saturate( dot( normal, viewDir ) );
	const vec4 c0 = vec4( - 1, - 0.0275, - 0.572, 0.022 );
	const vec4 c1 = vec4( 1, 0.0425, 1.04, - 0.04 );
	vec4 r = roughness * c0 + c1;
	float a004 = min( r.x * r.x, exp2( - 9.28 * dotNV ) ) * r.x + r.y;
	vec2 fab = vec2( - 1.04, 1.04 ) * a004 + r.zw;
	return fab;
}
vec3 EnvironmentBRDF( const in vec3 normal, const in vec3 viewDir, const in vec3 specularColor, const in float specularF90, const in float roughness ) {
	vec2 fab = DFGApprox( normal, viewDir, roughness );
	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 ) {
#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 ) {
#endif
	vec2 fab = DFGApprox( normal, viewDir, roughness );
	#ifdef USE_IRIDESCENCE
		vec3 Fr = mix( specularColor, iridescenceF0, iridescence );
	#else
		vec3 Fr = specularColor;
	#endif
	vec3 FssEss = Fr * fab.x + specularF90 * fab.y;
	float Ess = fab.x + fab.y;
	float Ems = 1.0 - Ess;
	vec3 Favg = Fr + ( 1.0 - Fr ) * 0.047619;	vec3 Fms = FssEss * Favg / ( 1.0 - Ems * Favg );
	singleScatter += FssEss;
	multiScatter += Fms * Ems;
}
#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;
		vec3 viewDir = geometryViewDir;
		vec3 position = geometryPosition;
		vec3 lightPos = rectAreaLight.position;
		vec3 halfWidth = rectAreaLight.halfWidth;
		vec3 halfHeight = rectAreaLight.halfHeight;
		vec3 lightColor = rectAreaLight.color;
		float roughness = material.roughness;
		vec3 rectCoords[ 4 ];
		rectCoords[ 0 ] = lightPos + halfWidth - halfHeight;		rectCoords[ 1 ] = lightPos - halfWidth - halfHeight;
		rectCoords[ 2 ] = lightPos - halfWidth + halfHeight;
		rectCoords[ 3 ] = lightPos + halfWidth + halfHeight;
		vec2 uv = LTC_Uv( normal, viewDir, roughness );
		vec4 t1 = texture2D( ltc_1, uv );
		vec4 t2 = texture2D( ltc_2, uv );
		mat3 mInv = mat3(
			vec3( t1.x, 0, t1.y ),
			vec3(    0, 1,    0 ),
			vec3( t1.z, 0, t1.w )
		);
		vec3 fresnel = ( material.specularColor * t2.x + ( vec3( 1.0 ) - material.specularColor ) * t2.y );
		reflectedLight.directSpecular += lightColor * fresnel * LTC_Evaluate( normal, viewDir, position, mInv, rectCoords );
		reflectedLight.directDiffuse += lightColor * material.diffuseColor * LTC_Evaluate( normal, viewDir, position, mat3( 1.0 ), rectCoords );
	}
#endif
void RE_Direct_Physical( const in IncidentLight directLight, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight ) {
	float dotNL = saturate( dot( geometryNormal, directLight.direction ) );
	vec3 irradiance = dotNL * directLight.color;
	#ifdef USE_CLEARCOAT
		float dotNLcc = saturate( dot( geometryClearcoatNormal, directLight.direction ) );
		vec3 ccIrradiance = dotNLcc * directLight.color;
		clearcoatSpecularDirect += ccIrradiance * BRDF_GGX_Clearcoat( directLight.direction, geometryViewDir, geometryClearcoatNormal, material );
	#endif
	#ifdef USE_SHEEN
		sheenSpecularDirect += irradiance * BRDF_Sheen( directLight.direction, geometryViewDir, geometryNormal, material.sheenColor, material.sheenRoughness );
	#endif
	reflectedLight.directSpecular += irradiance * BRDF_GGX( directLight.direction, geometryViewDir, geometryNormal, material );
	reflectedLight.directDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
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 ) {
	reflectedLight.indirectDiffuse += irradiance * BRDF_Lambert( material.diffuseColor );
}
void RE_IndirectSpecular_Physical( const in vec3 radiance, const in vec3 irradiance, const in vec3 clearcoatRadiance, const in vec3 geometryPosition, const in vec3 geometryNormal, const in vec3 geometryViewDir, const in vec3 geometryClearcoatNormal, const in PhysicalMaterial material, inout ReflectedLight reflectedLight) {
	#ifdef USE_CLEARCOAT
		clearcoatSpecularIndirect += clearcoatRadiance * EnvironmentBRDF( geometryClearcoatNormal, geometryViewDir, material.clearcoatF0, material.clearcoatF90, material.clearcoatRoughness );
	#endif
	#ifdef USE_SHEEN
		sheenSpecularIndirect += irradiance * material.sheenColor * IBLSheenBRDF( geometryNormal, geometryViewDir, material.sheenRoughness );
	#endif
	vec3 singleScattering = vec3( 0.0 );
	vec3 multiScattering = vec3( 0.0 );
	vec3 cosineWeightedIrradiance = irradiance * RECIPROCAL_PI;
	#ifdef USE_IRIDESCENCE
		computeMultiscatteringIridescence( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.iridescence, material.iridescenceFresnel, material.roughness, singleScattering, multiScattering );
	#else
		computeMultiscattering( geometryNormal, geometryViewDir, material.specularColor, material.specularF90, material.roughness, singleScattering, multiScattering );
	#endif
	vec3 totalScattering = singleScattering + multiScattering;
	vec3 diffuse = material.diffuseColor * ( 1.0 - max( max( totalScattering.r, totalScattering.g ), totalScattering.b ) );
	reflectedLight.indirectSpecular += radiance * singleScattering;
	reflectedLight.indirectSpecular += multiScattering * cosineWeightedIrradiance;
	reflectedLight.indirectDiffuse += diffuse * cosineWeightedIrradiance;
}
#define RE_Direct				RE_Direct_Physical
#define RE_Direct_RectArea		RE_Direct_RectArea_Physical
#define RE_IndirectDiffuse		RE_IndirectDiffuse_Physical
#define RE_IndirectSpecular		RE_IndirectSpecular_Physical
float computeSpecularOcclusion( const in float dotNV, const in float ambientOcclusion, const in float roughness ) {
	return saturate( pow( dotNV + ambientOcclusion, exp2( - 16.0 * roughness - 1.0 ) ) - 1.0 + ambientOcclusion );
}`,sH=`
vec3 geometryPosition = - vViewPosition;
vec3 geometryNormal = normal;
vec3 geometryViewDir = ( isOrthographic ) ? vec3( 0, 0, 1 ) : normalize( vViewPosition );
vec3 geometryClearcoatNormal = vec3( 0.0 );
#ifdef USE_CLEARCOAT
	geometryClearcoatNormal = clearcoatNormal;
#endif
#ifdef USE_IRIDESCENCE
	float dotNVi = saturate( dot( normal, geometryViewDir ) );
	if ( material.iridescenceThickness == 0.0 ) {
		material.iridescence = 0.0;
	} else {
		material.iridescence = saturate( material.iridescence );
	}
	if ( material.iridescence > 0.0 ) {
		material.iridescenceFresnel = evalIridescence( 1.0, material.iridescenceIOR, dotNVi, material.iridescenceThickness, material.specularColor );
		material.iridescenceF0 = Schlick_to_F0( material.iridescenceFresnel, 1.0, dotNVi );
	}
#endif
IncidentLight directLight;
#if ( NUM_POINT_LIGHTS > 0 ) && defined( RE_Direct )
	PointLight pointLight;
	#if defined( USE_SHADOWMAP ) && NUM_POINT_LIGHT_SHADOWS > 0
	PointLightShadow pointLightShadow;
	#endif
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_POINT_LIGHTS; i ++ ) {
		pointLight = pointLights[ i ];
		getPointLightInfo( pointLight, geometryPosition, directLight );
		#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_POINT_LIGHT_SHADOWS )
		pointLightShadow = pointLightShadows[ i ];
		directLight.color *= ( directLight.visible && receiveShadow ) ? getPointShadow( pointShadowMap[ i ], pointLightShadow.shadowMapSize, pointLightShadow.shadowBias, pointLightShadow.shadowRadius, vPointShadowCoord[ i ], pointLightShadow.shadowCameraNear, pointLightShadow.shadowCameraFar ) : 1.0;
		#endif
		RE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
	}
	#pragma unroll_loop_end
#endif
#if ( NUM_SPOT_LIGHTS > 0 ) && defined( RE_Direct )
	SpotLight spotLight;
	vec4 spotColor;
	vec3 spotLightCoord;
	bool inSpotLightMap;
	#if defined( USE_SHADOWMAP ) && NUM_SPOT_LIGHT_SHADOWS > 0
	SpotLightShadow spotLightShadow;
	#endif
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_SPOT_LIGHTS; i ++ ) {
		spotLight = spotLights[ i ];
		getSpotLightInfo( spotLight, geometryPosition, directLight );
		#if ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )
		#define SPOT_LIGHT_MAP_INDEX UNROLLED_LOOP_INDEX
		#elif ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )
		#define SPOT_LIGHT_MAP_INDEX NUM_SPOT_LIGHT_MAPS
		#else
		#define SPOT_LIGHT_MAP_INDEX ( UNROLLED_LOOP_INDEX - NUM_SPOT_LIGHT_SHADOWS + NUM_SPOT_LIGHT_SHADOWS_WITH_MAPS )
		#endif
		#if ( SPOT_LIGHT_MAP_INDEX < NUM_SPOT_LIGHT_MAPS )
			spotLightCoord = vSpotLightCoord[ i ].xyz / vSpotLightCoord[ i ].w;
			inSpotLightMap = all( lessThan( abs( spotLightCoord * 2. - 1. ), vec3( 1.0 ) ) );
			spotColor = texture2D( spotLightMap[ SPOT_LIGHT_MAP_INDEX ], spotLightCoord.xy );
			directLight.color = inSpotLightMap ? directLight.color * spotColor.rgb : directLight.color;
		#endif
		#undef SPOT_LIGHT_MAP_INDEX
		#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )
		spotLightShadow = spotLightShadows[ i ];
		directLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( spotShadowMap[ i ], spotLightShadow.shadowMapSize, spotLightShadow.shadowBias, spotLightShadow.shadowRadius, vSpotLightCoord[ i ] ) : 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
	DirectionalLightShadow directionalLightShadow;
	#endif
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_DIR_LIGHTS; i ++ ) {
		directionalLight = directionalLights[ i ];
		getDirectionalLightInfo( directionalLight, directLight );
		#if defined( USE_SHADOWMAP ) && ( UNROLLED_LOOP_INDEX < NUM_DIR_LIGHT_SHADOWS )
		directionalLightShadow = directionalLightShadows[ i ];
		directLight.color *= ( directLight.visible && receiveShadow ) ? getShadow( directionalShadowMap[ i ], directionalLightShadow.shadowMapSize, directionalLightShadow.shadowBias, directionalLightShadow.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;
		#endif
		RE_Direct( directLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
	}
	#pragma unroll_loop_end
#endif
#if ( NUM_RECT_AREA_LIGHTS > 0 ) && defined( RE_Direct_RectArea )
	RectAreaLight rectAreaLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_RECT_AREA_LIGHTS; i ++ ) {
		rectAreaLight = rectAreaLights[ i ];
		RE_Direct_RectArea( rectAreaLight, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
	}
	#pragma unroll_loop_end
#endif
#if defined( RE_IndirectDiffuse )
	vec3 iblIrradiance = vec3( 0.0 );
	vec3 irradiance = getAmbientLightIrradiance( ambientLightColor );
	#if defined( USE_LIGHT_PROBES )
		irradiance += getLightProbeIrradiance( lightProbe, geometryNormal );
	#endif
	#if ( NUM_HEMI_LIGHTS > 0 )
		#pragma unroll_loop_start
		for ( int i = 0; i < NUM_HEMI_LIGHTS; i ++ ) {
			irradiance += getHemisphereLightIrradiance( hemisphereLights[ i ], geometryNormal );
		}
		#pragma unroll_loop_end
	#endif
#endif
#if defined( RE_IndirectSpecular )
	vec3 radiance = vec3( 0.0 );
	vec3 clearcoatRadiance = vec3( 0.0 );
#endif`,oH=`#if defined( RE_IndirectDiffuse )
	#ifdef USE_LIGHTMAP
		vec4 lightMapTexel = texture2D( lightMap, vLightMapUv );
		vec3 lightMapIrradiance = lightMapTexel.rgb * lightMapIntensity;
		irradiance += lightMapIrradiance;
	#endif
	#if defined( USE_ENVMAP ) && defined( STANDARD ) && defined( ENVMAP_TYPE_CUBE_UV )
		iblIrradiance += getIBLIrradiance( geometryNormal );
	#endif
#endif
#if defined( USE_ENVMAP ) && defined( RE_IndirectSpecular )
	#ifdef USE_ANISOTROPY
		radiance += getIBLAnisotropyRadiance( geometryViewDir, geometryNormal, material.roughness, material.anisotropyB, material.anisotropy );
	#else
		radiance += getIBLRadiance( geometryViewDir, geometryNormal, material.roughness );
	#endif
	#ifdef USE_CLEARCOAT
		clearcoatRadiance += getIBLRadiance( geometryViewDir, geometryClearcoatNormal, material.clearcoatRoughness );
	#endif
#endif`,aH=`#if defined( RE_IndirectDiffuse )
	RE_IndirectDiffuse( irradiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
#endif
#if defined( RE_IndirectSpecular )
	RE_IndirectSpecular( radiance, iblIrradiance, clearcoatRadiance, geometryPosition, geometryNormal, geometryViewDir, geometryClearcoatNormal, material, reflectedLight );
#endif`,lH=`#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )
	gl_FragDepthEXT = vIsPerspective == 0.0 ? gl_FragCoord.z : log2( vFragDepth ) * logDepthBufFC * 0.5;
#endif`,cH=`#if defined( USE_LOGDEPTHBUF ) && defined( USE_LOGDEPTHBUF_EXT )
	uniform float logDepthBufFC;
	varying float vFragDepth;
	varying float vIsPerspective;
#endif`,uH=`#ifdef USE_LOGDEPTHBUF
	#ifdef USE_LOGDEPTHBUF_EXT
		varying float vFragDepth;
		varying float vIsPerspective;
	#else
		uniform float logDepthBufFC;
	#endif
#endif`,hH=`#ifdef USE_LOGDEPTHBUF
	#ifdef USE_LOGDEPTHBUF_EXT
		vFragDepth = 1.0 + gl_Position.w;
		vIsPerspective = float( isPerspectiveMatrix( projectionMatrix ) );
	#else
		if ( isPerspectiveMatrix( projectionMatrix ) ) {
			gl_Position.z = log2( max( EPSILON, gl_Position.w + 1.0 ) ) * logDepthBufFC - 1.0;
			gl_Position.z *= gl_Position.w;
		}
	#endif
#endif`,pH=`#ifdef USE_MAP
	vec4 sampledDiffuseColor = texture2D( map, vMapUv );
	#ifdef DECODE_VIDEO_TEXTURE
		sampledDiffuseColor = vec4( mix( pow( sampledDiffuseColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), sampledDiffuseColor.rgb * 0.0773993808, vec3( lessThanEqual( sampledDiffuseColor.rgb, vec3( 0.04045 ) ) ) ), sampledDiffuseColor.w );
	
	#endif
	diffuseColor *= sampledDiffuseColor;
#endif`,fH=`#ifdef USE_MAP
	uniform sampler2D map;
#endif`,dH=`#if defined( USE_MAP ) || defined( USE_ALPHAMAP )
	#if defined( USE_POINTS_UV )
		vec2 uv = vUv;
	#else
		vec2 uv = ( uvTransform * vec3( gl_PointCoord.x, 1.0 - gl_PointCoord.y, 1 ) ).xy;
	#endif
#endif
#ifdef USE_MAP
	diffuseColor *= texture2D( map, uv );
#endif
#ifdef USE_ALPHAMAP
	diffuseColor.a *= texture2D( alphaMap, uv ).g;
#endif`,mH=`#if defined( USE_POINTS_UV )
	varying vec2 vUv;
#else
	#if defined( USE_MAP ) || defined( USE_ALPHAMAP )
		uniform mat3 uvTransform;
	#endif
#endif
#ifdef USE_MAP
	uniform sampler2D map;
#endif
#ifdef USE_ALPHAMAP
	uniform sampler2D alphaMap;
#endif`,SH=`float metalnessFactor = metalness;
#ifdef USE_METALNESSMAP
	vec4 texelMetalness = texture2D( metalnessMap, vMetalnessMapUv );
	metalnessFactor *= texelMetalness.b;
#endif`,gH=`#ifdef USE_METALNESSMAP
	uniform sampler2D metalnessMap;
#endif`,AH=`#if defined( USE_MORPHCOLORS ) && defined( MORPHTARGETS_TEXTURE )
	vColor *= morphTargetBaseInfluence;
	for ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {
		#if defined( USE_COLOR_ALPHA )
			if ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ) * morphTargetInfluences[ i ];
		#elif defined( USE_COLOR )
			if ( morphTargetInfluences[ i ] != 0.0 ) vColor += getMorph( gl_VertexID, i, 2 ).rgb * morphTargetInfluences[ i ];
		#endif
	}
#endif`,yH=`#ifdef USE_MORPHNORMALS
	objectNormal *= morphTargetBaseInfluence;
	#ifdef MORPHTARGETS_TEXTURE
		for ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {
			if ( morphTargetInfluences[ i ] != 0.0 ) objectNormal += getMorph( gl_VertexID, i, 1 ).xyz * morphTargetInfluences[ i ];
		}
	#else
		objectNormal += morphNormal0 * morphTargetInfluences[ 0 ];
		objectNormal += morphNormal1 * morphTargetInfluences[ 1 ];
		objectNormal += morphNormal2 * morphTargetInfluences[ 2 ];
		objectNormal += morphNormal3 * morphTargetInfluences[ 3 ];
	#endif
#endif`,EH=`#ifdef USE_MORPHTARGETS
	uniform float morphTargetBaseInfluence;
	#ifdef MORPHTARGETS_TEXTURE
		uniform float morphTargetInfluences[ MORPHTARGETS_COUNT ];
		uniform sampler2DArray morphTargetsTexture;
		uniform ivec2 morphTargetsTextureSize;
		vec4 getMorph( const in int vertexIndex, const in int morphTargetIndex, const in int offset ) {
			int texelIndex = vertexIndex * MORPHTARGETS_TEXTURE_STRIDE + offset;
			int y = texelIndex / morphTargetsTextureSize.x;
			int x = texelIndex - y * morphTargetsTextureSize.x;
			ivec3 morphUV = ivec3( x, y, morphTargetIndex );
			return texelFetch( morphTargetsTexture, morphUV, 0 );
		}
	#else
		#ifndef USE_MORPHNORMALS
			uniform float morphTargetInfluences[ 8 ];
		#else
			uniform float morphTargetInfluences[ 4 ];
		#endif
	#endif
#endif`,CH=`#ifdef USE_MORPHTARGETS
	transformed *= morphTargetBaseInfluence;
	#ifdef MORPHTARGETS_TEXTURE
		for ( int i = 0; i < MORPHTARGETS_COUNT; i ++ ) {
			if ( morphTargetInfluences[ i ] != 0.0 ) transformed += getMorph( gl_VertexID, i, 0 ).xyz * morphTargetInfluences[ i ];
		}
	#else
		transformed += morphTarget0 * morphTargetInfluences[ 0 ];
		transformed += morphTarget1 * morphTargetInfluences[ 1 ];
		transformed += morphTarget2 * morphTargetInfluences[ 2 ];
		transformed += morphTarget3 * morphTargetInfluences[ 3 ];
		#ifndef USE_MORPHNORMALS
			transformed += morphTarget4 * morphTargetInfluences[ 4 ];
			transformed += morphTarget5 * morphTargetInfluences[ 5 ];
			transformed += morphTarget6 * morphTargetInfluences[ 6 ];
			transformed += morphTarget7 * morphTargetInfluences[ 7 ];
		#endif
	#endif
#endif`,vH=`float faceDirection = gl_FrontFacing ? 1.0 : - 1.0;
#ifdef FLAT_SHADED
	vec3 fdx = dFdx( vViewPosition );
	vec3 fdy = dFdy( vViewPosition );
	vec3 normal = normalize( cross( fdx, fdy ) );
#else
	vec3 normal = normalize( vNormal );
	#ifdef DOUBLE_SIDED
		normal *= faceDirection;
	#endif
#endif
#if defined( USE_NORMALMAP_TANGENTSPACE ) || defined( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY )
	#ifdef USE_TANGENT
		mat3 tbn = mat3( normalize( vTangent ), normalize( vBitangent ), normal );
	#else
		mat3 tbn = getTangentFrame( - vViewPosition, normal,
		#if defined( USE_NORMALMAP )
			vNormalMapUv
		#elif defined( USE_CLEARCOAT_NORMALMAP )
			vClearcoatNormalMapUv
		#else
			vUv
		#endif
		);
	#endif
	#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )
		tbn[0] *= faceDirection;
		tbn[1] *= faceDirection;
	#endif
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	#ifdef USE_TANGENT
		mat3 tbn2 = mat3( normalize( vTangent ), normalize( vBitangent ), normal );
	#else
		mat3 tbn2 = getTangentFrame( - vViewPosition, normal, vClearcoatNormalMapUv );
	#endif
	#if defined( DOUBLE_SIDED ) && ! defined( FLAT_SHADED )
		tbn2[0] *= faceDirection;
		tbn2[1] *= faceDirection;
	#endif
#endif
vec3 nonPerturbedNormal = normal;`,UH=`#ifdef USE_NORMALMAP_OBJECTSPACE
	normal = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;
	#ifdef FLIP_SIDED
		normal = - normal;
	#endif
	#ifdef DOUBLE_SIDED
		normal = normal * faceDirection;
	#endif
	normal = normalize( normalMatrix * normal );
#elif defined( USE_NORMALMAP_TANGENTSPACE )
	vec3 mapN = texture2D( normalMap, vNormalMapUv ).xyz * 2.0 - 1.0;
	mapN.xy *= normalScale;
	normal = normalize( tbn * mapN );
#elif defined( USE_BUMPMAP )
	normal = perturbNormalArb( - vViewPosition, normal, dHdxy_fwd(), faceDirection );
#endif`,wH=`#ifndef FLAT_SHADED
	varying vec3 vNormal;
	#ifdef USE_TANGENT
		varying vec3 vTangent;
		varying vec3 vBitangent;
	#endif
#endif`,MH=`#ifndef FLAT_SHADED
	varying vec3 vNormal;
	#ifdef USE_TANGENT
		varying vec3 vTangent;
		varying vec3 vBitangent;
	#endif
#endif`,kH=`#ifndef FLAT_SHADED
	vNormal = normalize( transformedNormal );
	#ifdef USE_TANGENT
		vTangent = normalize( transformedTangent );
		vBitangent = normalize( cross( vNormal, vTangent ) * tangent.w );
	#endif
#endif`,xH=`#ifdef USE_NORMALMAP
	uniform sampler2D normalMap;
	uniform vec2 normalScale;
#endif
#ifdef USE_NORMALMAP_OBJECTSPACE
	uniform mat3 normalMatrix;
#endif
#if ! defined ( USE_TANGENT ) && ( defined ( USE_NORMALMAP_TANGENTSPACE ) || defined ( USE_CLEARCOAT_NORMALMAP ) || defined( USE_ANISOTROPY ) )
	mat3 getTangentFrame( vec3 eye_pos, vec3 surf_norm, vec2 uv ) {
		vec3 q0 = dFdx( eye_pos.xyz );
		vec3 q1 = dFdy( eye_pos.xyz );
		vec2 st0 = dFdx( uv.st );
		vec2 st1 = dFdy( uv.st );
		vec3 N = surf_norm;
		vec3 q1perp = cross( q1, N );
		vec3 q0perp = cross( N, q0 );
		vec3 T = q1perp * st0.x + q0perp * st1.x;
		vec3 B = q1perp * st0.y + q0perp * st1.y;
		float det = max( dot( T, T ), dot( B, B ) );
		float scale = ( det == 0.0 ) ? 0.0 : inversesqrt( det );
		return mat3( T * scale, B * scale, N );
	}
#endif`,TH=`#ifdef USE_CLEARCOAT
	vec3 clearcoatNormal = nonPerturbedNormal;
#endif`,JH=`#ifdef USE_CLEARCOAT_NORMALMAP
	vec3 clearcoatMapN = texture2D( clearcoatNormalMap, vClearcoatNormalMapUv ).xyz * 2.0 - 1.0;
	clearcoatMapN.xy *= clearcoatNormalScale;
	clearcoatNormal = normalize( tbn2 * clearcoatMapN );
#endif`,IH=`#ifdef USE_CLEARCOATMAP
	uniform sampler2D clearcoatMap;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	uniform sampler2D clearcoatNormalMap;
	uniform vec2 clearcoatNormalScale;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	uniform sampler2D clearcoatRoughnessMap;
#endif`,LH=`#ifdef USE_IRIDESCENCEMAP
	uniform sampler2D iridescenceMap;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	uniform sampler2D iridescenceThicknessMap;
#endif`,BH=`#ifdef OPAQUE
diffuseColor.a = 1.0;
#endif
#ifdef USE_TRANSMISSION
diffuseColor.a *= material.transmissionAlpha;
#endif
gl_FragColor = vec4( outgoingLight, diffuseColor.a );`,KH=`vec3 packNormalToRGB( const in vec3 normal ) {
	return normalize( normal ) * 0.5 + 0.5;
}
vec3 unpackRGBToNormal( const in vec3 rgb ) {
	return 2.0 * rgb.xyz - 1.0;
}
const float PackUpscale = 256. / 255.;const float UnpackDownscale = 255. / 256.;
const vec3 PackFactors = vec3( 256. * 256. * 256., 256. * 256., 256. );
const vec4 UnpackFactors = UnpackDownscale / vec4( PackFactors, 1. );
const float ShiftRight8 = 1. / 256.;
vec4 packDepthToRGBA( const in float v ) {
	vec4 r = vec4( fract( v * PackFactors ), v );
	r.yzw -= r.xyz * ShiftRight8;	return r * PackUpscale;
}
float unpackRGBAToDepth( const in vec4 v ) {
	return dot( v, UnpackFactors );
}
vec2 packDepthToRG( in highp float v ) {
	return packDepthToRGBA( v ).yx;
}
float unpackRGToDepth( const in highp vec2 v ) {
	return unpackRGBAToDepth( vec4( v.xy, 0.0, 0.0 ) );
}
vec4 pack2HalfToRGBA( vec2 v ) {
	vec4 r = vec4( v.x, fract( v.x * 255.0 ), v.y, fract( v.y * 255.0 ) );
	return vec4( r.x - r.y / 255.0, r.y, r.z - r.w / 255.0, r.w );
}
vec2 unpackRGBATo2Half( vec4 v ) {
	return vec2( v.x + ( v.y / 255.0 ), v.z + ( v.w / 255.0 ) );
}
float viewZToOrthographicDepth( const in float viewZ, const in float near, const in float far ) {
	return ( viewZ + near ) / ( near - far );
}
float orthographicDepthToViewZ( const in float depth, const in float near, const in float far ) {
	return depth * ( near - far ) - near;
}
float viewZToPerspectiveDepth( const in float viewZ, const in float near, const in float far ) {
	return ( ( near + viewZ ) * far ) / ( ( far - near ) * viewZ );
}
float perspectiveDepthToViewZ( const in float depth, const in float near, const in float far ) {
	return ( near * far ) / ( ( far - near ) * depth - far );
}`,RH=`#ifdef PREMULTIPLIED_ALPHA
	gl_FragColor.rgb *= gl_FragColor.a;
#endif`,DH=`vec4 mvPosition = vec4( transformed, 1.0 );
#ifdef USE_BATCHING
	mvPosition = batchingMatrix * mvPosition;
#endif
#ifdef USE_INSTANCING
	mvPosition = instanceMatrix * mvPosition;
#endif
mvPosition = modelViewMatrix * mvPosition;
gl_Position = projectionMatrix * mvPosition;`,bH=`#ifdef DITHERING
	gl_FragColor.rgb = dithering( gl_FragColor.rgb );
#endif`,OH=`#ifdef DITHERING
	vec3 dithering( vec3 color ) {
		float grid_position = rand( gl_FragCoord.xy );
		vec3 dither_shift_RGB = vec3( 0.25 / 255.0, -0.25 / 255.0, 0.25 / 255.0 );
		dither_shift_RGB = mix( 2.0 * dither_shift_RGB, -2.0 * dither_shift_RGB, grid_position );
		return color + dither_shift_RGB;
	}
#endif`,FH=`float roughnessFactor = roughness;
#ifdef USE_ROUGHNESSMAP
	vec4 texelRoughness = texture2D( roughnessMap, vRoughnessMapUv );
	roughnessFactor *= texelRoughness.g;
#endif`,PH=`#ifdef USE_ROUGHNESSMAP
	uniform sampler2D roughnessMap;
#endif`,NH=`#if NUM_SPOT_LIGHT_COORDS > 0
	varying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];
#endif
#if NUM_SPOT_LIGHT_MAPS > 0
	uniform sampler2D spotLightMap[ NUM_SPOT_LIGHT_MAPS ];
#endif
#ifdef USE_SHADOWMAP
	#if NUM_DIR_LIGHT_SHADOWS > 0
		uniform sampler2D directionalShadowMap[ NUM_DIR_LIGHT_SHADOWS ];
		varying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];
		struct DirectionalLightShadow {
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];
	#endif
	#if NUM_SPOT_LIGHT_SHADOWS > 0
		uniform sampler2D spotShadowMap[ NUM_SPOT_LIGHT_SHADOWS ];
		struct SpotLightShadow {
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
		uniform sampler2D pointShadowMap[ NUM_POINT_LIGHT_SHADOWS ];
		varying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];
		struct PointLightShadow {
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
			float shadowCameraNear;
			float shadowCameraFar;
		};
		uniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];
	#endif
	float texture2DCompare( sampler2D depths, vec2 uv, float compare ) {
		return step( compare, unpackRGBAToDepth( texture2D( depths, uv ) ) );
	}
	vec2 texture2DDistribution( sampler2D shadow, vec2 uv ) {
		return unpackRGBATo2Half( texture2D( shadow, uv ) );
	}
	float VSMShadow (sampler2D shadow, vec2 uv, float compare ){
		float occlusion = 1.0;
		vec2 distribution = texture2DDistribution( shadow, uv );
		float hard_shadow = step( compare , distribution.x );
		if (hard_shadow != 1.0 ) {
			float distance = compare - distribution.x ;
			float variance = max( 0.00000, distribution.y * distribution.y );
			float softness_probability = variance / (variance + distance * distance );			softness_probability = clamp( ( softness_probability - 0.3 ) / ( 0.95 - 0.3 ), 0.0, 1.0 );			occlusion = clamp( max( hard_shadow, softness_probability ), 0.0, 1.0 );
		}
		return occlusion;
	}
	float getShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord ) {
		float shadow = 1.0;
		shadowCoord.xyz /= shadowCoord.w;
		shadowCoord.z += shadowBias;
		bool inFrustum = shadowCoord.x >= 0.0 && shadowCoord.x <= 1.0 && shadowCoord.y >= 0.0 && shadowCoord.y <= 1.0;
		bool frustumTest = inFrustum && shadowCoord.z <= 1.0;
		if ( frustumTest ) {
		#if defined( SHADOWMAP_TYPE_PCF )
			vec2 texelSize = vec2( 1.0 ) / shadowMapSize;
			float dx0 = - texelSize.x * shadowRadius;
			float dy0 = - texelSize.y * shadowRadius;
			float dx1 = + texelSize.x * shadowRadius;
			float dy1 = + texelSize.y * shadowRadius;
			float dx2 = dx0 / 2.0;
			float dy2 = dy0 / 2.0;
			float dx3 = dx1 / 2.0;
			float dy3 = dy1 / 2.0;
			shadow = (
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy2 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy2 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy2 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, 0.0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, 0.0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, 0.0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, 0.0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx2, dy3 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy3 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx3, dy3 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx0, dy1 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( 0.0, dy1 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, shadowCoord.xy + vec2( dx1, dy1 ), shadowCoord.z )
			) * ( 1.0 / 17.0 );
		#elif defined( SHADOWMAP_TYPE_PCF_SOFT )
			vec2 texelSize = vec2( 1.0 ) / shadowMapSize;
			float dx = texelSize.x;
			float dy = texelSize.y;
			vec2 uv = shadowCoord.xy;
			vec2 f = fract( uv * shadowMapSize + 0.5 );
			uv -= f * texelSize;
			shadow = (
				texture2DCompare( shadowMap, uv, shadowCoord.z ) +
				texture2DCompare( shadowMap, uv + vec2( dx, 0.0 ), shadowCoord.z ) +
				texture2DCompare( shadowMap, uv + vec2( 0.0, dy ), shadowCoord.z ) +
				texture2DCompare( shadowMap, uv + texelSize, shadowCoord.z ) +
				mix( texture2DCompare( shadowMap, uv + vec2( -dx, 0.0 ), shadowCoord.z ),
					 texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 0.0 ), shadowCoord.z ),
					 f.x ) +
				mix( texture2DCompare( shadowMap, uv + vec2( -dx, dy ), shadowCoord.z ),
					 texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, dy ), shadowCoord.z ),
					 f.x ) +
				mix( texture2DCompare( shadowMap, uv + vec2( 0.0, -dy ), shadowCoord.z ),
					 texture2DCompare( shadowMap, uv + vec2( 0.0, 2.0 * dy ), shadowCoord.z ),
					 f.y ) +
				mix( texture2DCompare( shadowMap, uv + vec2( dx, -dy ), shadowCoord.z ),
					 texture2DCompare( shadowMap, uv + vec2( dx, 2.0 * dy ), shadowCoord.z ),
					 f.y ) +
				mix( mix( texture2DCompare( shadowMap, uv + vec2( -dx, -dy ), shadowCoord.z ),
						  texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, -dy ), shadowCoord.z ),
						  f.x ),
					 mix( texture2DCompare( shadowMap, uv + vec2( -dx, 2.0 * dy ), shadowCoord.z ),
						  texture2DCompare( shadowMap, uv + vec2( 2.0 * dx, 2.0 * dy ), shadowCoord.z ),
						  f.x ),
					 f.y )
			) * ( 1.0 / 9.0 );
		#elif defined( SHADOWMAP_TYPE_VSM )
			shadow = VSMShadow( shadowMap, shadowCoord.xy, shadowCoord.z );
		#else
			shadow = texture2DCompare( shadowMap, shadowCoord.xy, shadowCoord.z );
		#endif
		}
		return shadow;
	}
	vec2 cubeToUV( vec3 v, float texelSizeY ) {
		vec3 absV = abs( v );
		float scaleToCube = 1.0 / max( absV.x, max( absV.y, absV.z ) );
		absV *= scaleToCube;
		v *= scaleToCube * ( 1.0 - 2.0 * texelSizeY );
		vec2 planar = v.xy;
		float almostATexel = 1.5 * texelSizeY;
		float almostOne = 1.0 - almostATexel;
		if ( absV.z >= almostOne ) {
			if ( v.z > 0.0 )
				planar.x = 4.0 - v.x;
		} else if ( absV.x >= almostOne ) {
			float signX = sign( v.x );
			planar.x = v.z * signX + 2.0 * signX;
		} else if ( absV.y >= almostOne ) {
			float signY = sign( v.y );
			planar.x = v.x + 2.0 * signY + 2.0;
			planar.y = v.z * signY - 2.0;
		}
		return vec2( 0.125, 0.25 ) * planar + vec2( 0.375, 0.75 );
	}
	float getPointShadow( sampler2D shadowMap, vec2 shadowMapSize, float shadowBias, float shadowRadius, vec4 shadowCoord, float shadowCameraNear, float shadowCameraFar ) {
		vec2 texelSize = vec2( 1.0 ) / ( shadowMapSize * vec2( 4.0, 2.0 ) );
		vec3 lightToPosition = shadowCoord.xyz;
		float dp = ( length( lightToPosition ) - shadowCameraNear ) / ( shadowCameraFar - shadowCameraNear );		dp += shadowBias;
		vec3 bd3D = normalize( lightToPosition );
		#if defined( SHADOWMAP_TYPE_PCF ) || defined( SHADOWMAP_TYPE_PCF_SOFT ) || defined( SHADOWMAP_TYPE_VSM )
			vec2 offset = vec2( - 1, 1 ) * shadowRadius * texelSize.y;
			return (
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyy, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyy, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.xyx, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.yyx, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxy, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxy, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.xxx, texelSize.y ), dp ) +
				texture2DCompare( shadowMap, cubeToUV( bd3D + offset.yxx, texelSize.y ), dp )
			) * ( 1.0 / 9.0 );
		#else
			return texture2DCompare( shadowMap, cubeToUV( bd3D, texelSize.y ), dp );
		#endif
	}
#endif`,QH=`#if NUM_SPOT_LIGHT_COORDS > 0
	uniform mat4 spotLightMatrix[ NUM_SPOT_LIGHT_COORDS ];
	varying vec4 vSpotLightCoord[ NUM_SPOT_LIGHT_COORDS ];
#endif
#ifdef USE_SHADOWMAP
	#if NUM_DIR_LIGHT_SHADOWS > 0
		uniform mat4 directionalShadowMatrix[ NUM_DIR_LIGHT_SHADOWS ];
		varying vec4 vDirectionalShadowCoord[ NUM_DIR_LIGHT_SHADOWS ];
		struct DirectionalLightShadow {
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform DirectionalLightShadow directionalLightShadows[ NUM_DIR_LIGHT_SHADOWS ];
	#endif
	#if NUM_SPOT_LIGHT_SHADOWS > 0
		struct SpotLightShadow {
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
		};
		uniform SpotLightShadow spotLightShadows[ NUM_SPOT_LIGHT_SHADOWS ];
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
		uniform mat4 pointShadowMatrix[ NUM_POINT_LIGHT_SHADOWS ];
		varying vec4 vPointShadowCoord[ NUM_POINT_LIGHT_SHADOWS ];
		struct PointLightShadow {
			float shadowBias;
			float shadowNormalBias;
			float shadowRadius;
			vec2 shadowMapSize;
			float shadowCameraNear;
			float shadowCameraFar;
		};
		uniform PointLightShadow pointLightShadows[ NUM_POINT_LIGHT_SHADOWS ];
	#endif
#endif`,WH=`#if ( defined( USE_SHADOWMAP ) && ( NUM_DIR_LIGHT_SHADOWS > 0 || NUM_POINT_LIGHT_SHADOWS > 0 ) ) || ( NUM_SPOT_LIGHT_COORDS > 0 )
	vec3 shadowWorldNormal = inverseTransformDirection( transformedNormal, viewMatrix );
	vec4 shadowWorldPosition;
#endif
#if defined( USE_SHADOWMAP )
	#if NUM_DIR_LIGHT_SHADOWS > 0
		#pragma unroll_loop_start
		for ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {
			shadowWorldPosition = worldPosition + vec4( shadowWorldNormal * directionalLightShadows[ i ].shadowNormalBias, 0 );
			vDirectionalShadowCoord[ i ] = directionalShadowMatrix[ i ] * shadowWorldPosition;
		}
		#pragma unroll_loop_end
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
		#pragma unroll_loop_start
		for ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {
			shadowWorldPosition = worldPosition + vec4( shadowWorldNormal * pointLightShadows[ i ].shadowNormalBias, 0 );
			vPointShadowCoord[ i ] = pointShadowMatrix[ i ] * shadowWorldPosition;
		}
		#pragma unroll_loop_end
	#endif
#endif
#if NUM_SPOT_LIGHT_COORDS > 0
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_SPOT_LIGHT_COORDS; i ++ ) {
		shadowWorldPosition = worldPosition;
		#if ( defined( USE_SHADOWMAP ) && UNROLLED_LOOP_INDEX < NUM_SPOT_LIGHT_SHADOWS )
			shadowWorldPosition.xyz += shadowWorldNormal * spotLightShadows[ i ].shadowNormalBias;
		#endif
		vSpotLightCoord[ i ] = spotLightMatrix[ i ] * shadowWorldPosition;
	}
	#pragma unroll_loop_end
#endif`,HH=`float getShadowMask() {
	float shadow = 1.0;
	#ifdef USE_SHADOWMAP
	#if NUM_DIR_LIGHT_SHADOWS > 0
	DirectionalLightShadow directionalLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_DIR_LIGHT_SHADOWS; i ++ ) {
		directionalLight = directionalLightShadows[ i ];
		shadow *= receiveShadow ? getShadow( directionalShadowMap[ i ], directionalLight.shadowMapSize, directionalLight.shadowBias, directionalLight.shadowRadius, vDirectionalShadowCoord[ i ] ) : 1.0;
	}
	#pragma unroll_loop_end
	#endif
	#if NUM_SPOT_LIGHT_SHADOWS > 0
	SpotLightShadow spotLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_SPOT_LIGHT_SHADOWS; i ++ ) {
		spotLight = spotLightShadows[ i ];
		shadow *= receiveShadow ? getShadow( spotShadowMap[ i ], spotLight.shadowMapSize, spotLight.shadowBias, spotLight.shadowRadius, vSpotLightCoord[ i ] ) : 1.0;
	}
	#pragma unroll_loop_end
	#endif
	#if NUM_POINT_LIGHT_SHADOWS > 0
	PointLightShadow pointLight;
	#pragma unroll_loop_start
	for ( int i = 0; i < NUM_POINT_LIGHT_SHADOWS; i ++ ) {
		pointLight = pointLightShadows[ i ];
		shadow *= receiveShadow ? getPointShadow( pointShadowMap[ i ], pointLight.shadowMapSize, pointLight.shadowBias, pointLight.shadowRadius, vPointShadowCoord[ i ], pointLight.shadowCameraNear, pointLight.shadowCameraFar ) : 1.0;
	}
	#pragma unroll_loop_end
	#endif
	#endif
	return shadow;
}`,zH=`#ifdef USE_SKINNING
	mat4 boneMatX = getBoneMatrix( skinIndex.x );
	mat4 boneMatY = getBoneMatrix( skinIndex.y );
	mat4 boneMatZ = getBoneMatrix( skinIndex.z );
	mat4 boneMatW = getBoneMatrix( skinIndex.w );
#endif`,GH=`#ifdef USE_SKINNING
	uniform mat4 bindMatrix;
	uniform mat4 bindMatrixInverse;
	uniform highp sampler2D boneTexture;
	mat4 getBoneMatrix( const in float i ) {
		int size = textureSize( boneTexture, 0 ).x;
		int j = int( i ) * 4;
		int x = j % size;
		int y = j / size;
		vec4 v1 = texelFetch( boneTexture, ivec2( x, y ), 0 );
		vec4 v2 = texelFetch( boneTexture, ivec2( x + 1, y ), 0 );
		vec4 v3 = texelFetch( boneTexture, ivec2( x + 2, y ), 0 );
		vec4 v4 = texelFetch( boneTexture, ivec2( x + 3, y ), 0 );
		return mat4( v1, v2, v3, v4 );
	}
#endif`,VH=`#ifdef USE_SKINNING
	vec4 skinVertex = bindMatrix * vec4( transformed, 1.0 );
	vec4 skinned = vec4( 0.0 );
	skinned += boneMatX * skinVertex * skinWeight.x;
	skinned += boneMatY * skinVertex * skinWeight.y;
	skinned += boneMatZ * skinVertex * skinWeight.z;
	skinned += boneMatW * skinVertex * skinWeight.w;
	transformed = ( bindMatrixInverse * skinned ).xyz;
#endif`,qH=`#ifdef USE_SKINNING
	mat4 skinMatrix = mat4( 0.0 );
	skinMatrix += skinWeight.x * boneMatX;
	skinMatrix += skinWeight.y * boneMatY;
	skinMatrix += skinWeight.z * boneMatZ;
	skinMatrix += skinWeight.w * boneMatW;
	skinMatrix = bindMatrixInverse * skinMatrix * bindMatrix;
	objectNormal = vec4( skinMatrix * vec4( objectNormal, 0.0 ) ).xyz;
	#ifdef USE_TANGENT
		objectTangent = vec4( skinMatrix * vec4( objectTangent, 0.0 ) ).xyz;
	#endif
#endif`,YH=`float specularStrength;
#ifdef USE_SPECULARMAP
	vec4 texelSpecular = texture2D( specularMap, vSpecularMapUv );
	specularStrength = texelSpecular.r;
#else
	specularStrength = 1.0;
#endif`,ZH=`#ifdef USE_SPECULARMAP
	uniform sampler2D specularMap;
#endif`,jH=`#if defined( TONE_MAPPING )
	gl_FragColor.rgb = toneMapping( gl_FragColor.rgb );
#endif`,XH=`#ifndef saturate
#define saturate( a ) clamp( a, 0.0, 1.0 )
#endif
uniform float toneMappingExposure;
vec3 LinearToneMapping( vec3 color ) {
	return saturate( toneMappingExposure * color );
}
vec3 ReinhardToneMapping( vec3 color ) {
	color *= toneMappingExposure;
	return saturate( color / ( vec3( 1.0 ) + color ) );
}
vec3 OptimizedCineonToneMapping( vec3 color ) {
	color *= toneMappingExposure;
	color = max( vec3( 0.0 ), color - 0.004 );
	return pow( ( color * ( 6.2 * color + 0.5 ) ) / ( color * ( 6.2 * color + 1.7 ) + 0.06 ), vec3( 2.2 ) );
}
vec3 RRTAndODTFit( vec3 v ) {
	vec3 a = v * ( v + 0.0245786 ) - 0.000090537;
	vec3 b = v * ( 0.983729 * v + 0.4329510 ) + 0.238081;
	return a / b;
}
vec3 ACESFilmicToneMapping( vec3 color ) {
	const mat3 ACESInputMat = mat3(
		vec3( 0.59719, 0.07600, 0.02840 ),		vec3( 0.35458, 0.90834, 0.13383 ),
		vec3( 0.04823, 0.01566, 0.83777 )
	);
	const mat3 ACESOutputMat = mat3(
		vec3(  1.60475, -0.10208, -0.00327 ),		vec3( -0.53108,  1.10813, -0.07276 ),
		vec3( -0.07367, -0.00605,  1.07602 )
	);
	color *= toneMappingExposure / 0.6;
	color = ACESInputMat * color;
	color = RRTAndODTFit( color );
	color = ACESOutputMat * color;
	return saturate( color );
}
vec3 CustomToneMapping( vec3 color ) { return color; }`,_H=`#ifdef USE_TRANSMISSION
	material.transmission = transmission;
	material.transmissionAlpha = 1.0;
	material.thickness = thickness;
	material.attenuationDistance = attenuationDistance;
	material.attenuationColor = attenuationColor;
	#ifdef USE_TRANSMISSIONMAP
		material.transmission *= texture2D( transmissionMap, vTransmissionMapUv ).r;
	#endif
	#ifdef USE_THICKNESSMAP
		material.thickness *= texture2D( thicknessMap, vThicknessMapUv ).g;
	#endif
	vec3 pos = vWorldPosition;
	vec3 v = normalize( cameraPosition - pos );
	vec3 n = inverseTransformDirection( normal, viewMatrix );
	vec4 transmitted = getIBLVolumeRefraction(
		n, v, material.roughness, material.diffuseColor, material.specularColor, material.specularF90,
		pos, modelMatrix, viewMatrix, projectionMatrix, material.ior, material.thickness,
		material.attenuationColor, material.attenuationDistance );
	material.transmissionAlpha = mix( material.transmissionAlpha, transmitted.a, material.transmission );
	totalDiffuse = mix( totalDiffuse, transmitted.rgb, material.transmission );
#endif`,$H=`#ifdef USE_TRANSMISSION
	uniform float transmission;
	uniform float thickness;
	uniform float attenuationDistance;
	uniform vec3 attenuationColor;
	#ifdef USE_TRANSMISSIONMAP
		uniform sampler2D transmissionMap;
	#endif
	#ifdef USE_THICKNESSMAP
		uniform sampler2D thicknessMap;
	#endif
	uniform vec2 transmissionSamplerSize;
	uniform sampler2D transmissionSamplerMap;
	uniform mat4 modelMatrix;
	uniform mat4 projectionMatrix;
	varying vec3 vWorldPosition;
	float w0( float a ) {
		return ( 1.0 / 6.0 ) * ( a * ( a * ( - a + 3.0 ) - 3.0 ) + 1.0 );
	}
	float w1( float a ) {
		return ( 1.0 / 6.0 ) * ( a *  a * ( 3.0 * a - 6.0 ) + 4.0 );
	}
	float w2( float a ){
		return ( 1.0 / 6.0 ) * ( a * ( a * ( - 3.0 * a + 3.0 ) + 3.0 ) + 1.0 );
	}
	float w3( float a ) {
		return ( 1.0 / 6.0 ) * ( a * a * a );
	}
	float g0( float a ) {
		return w0( a ) + w1( a );
	}
	float g1( float a ) {
		return w2( a ) + w3( a );
	}
	float h0( float a ) {
		return - 1.0 + w1( a ) / ( w0( a ) + w1( a ) );
	}
	float h1( float a ) {
		return 1.0 + w3( a ) / ( w2( a ) + w3( a ) );
	}
	vec4 bicubic( sampler2D tex, vec2 uv, vec4 texelSize, float lod ) {
		uv = uv * texelSize.zw + 0.5;
		vec2 iuv = floor( uv );
		vec2 fuv = fract( uv );
		float g0x = g0( fuv.x );
		float g1x = g1( fuv.x );
		float h0x = h0( fuv.x );
		float h1x = h1( fuv.x );
		float h0y = h0( fuv.y );
		float h1y = h1( fuv.y );
		vec2 p0 = ( vec2( iuv.x + h0x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;
		vec2 p1 = ( vec2( iuv.x + h1x, iuv.y + h0y ) - 0.5 ) * texelSize.xy;
		vec2 p2 = ( vec2( iuv.x + h0x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;
		vec2 p3 = ( vec2( iuv.x + h1x, iuv.y + h1y ) - 0.5 ) * texelSize.xy;
		return g0( fuv.y ) * ( g0x * textureLod( tex, p0, lod ) + g1x * textureLod( tex, p1, lod ) ) +
			g1( fuv.y ) * ( g0x * textureLod( tex, p2, lod ) + g1x * textureLod( tex, p3, lod ) );
	}
	vec4 textureBicubic( sampler2D sampler, vec2 uv, float lod ) {
		vec2 fLodSize = vec2( textureSize( sampler, int( lod ) ) );
		vec2 cLodSize = vec2( textureSize( sampler, int( lod + 1.0 ) ) );
		vec2 fLodSizeInv = 1.0 / fLodSize;
		vec2 cLodSizeInv = 1.0 / cLodSize;
		vec4 fSample = bicubic( sampler, uv, vec4( fLodSizeInv, fLodSize ), floor( lod ) );
		vec4 cSample = bicubic( sampler, uv, vec4( cLodSizeInv, cLodSize ), ceil( lod ) );
		return mix( fSample, cSample, fract( lod ) );
	}
	vec3 getVolumeTransmissionRay( const in vec3 n, const in vec3 v, const in float thickness, const in float ior, const in mat4 modelMatrix ) {
		vec3 refractionVector = refract( - v, normalize( n ), 1.0 / ior );
		vec3 modelScale;
		modelScale.x = length( vec3( modelMatrix[ 0 ].xyz ) );
		modelScale.y = length( vec3( modelMatrix[ 1 ].xyz ) );
		modelScale.z = length( vec3( modelMatrix[ 2 ].xyz ) );
		return normalize( refractionVector ) * thickness * modelScale;
	}
	float applyIorToRoughness( const in float roughness, const in float ior ) {
		return roughness * clamp( ior * 2.0 - 2.0, 0.0, 1.0 );
	}
	vec4 getTransmissionSample( const in vec2 fragCoord, const in float roughness, const in float ior ) {
		float lod = log2( transmissionSamplerSize.x ) * applyIorToRoughness( roughness, ior );
		return textureBicubic( transmissionSamplerMap, fragCoord.xy, lod );
	}
	vec3 volumeAttenuation( const in float transmissionDistance, const in vec3 attenuationColor, const in float attenuationDistance ) {
		if ( isinf( attenuationDistance ) ) {
			return vec3( 1.0 );
		} else {
			vec3 attenuationCoefficient = -log( attenuationColor ) / attenuationDistance;
			vec3 transmittance = exp( - attenuationCoefficient * transmissionDistance );			return transmittance;
		}
	}
	vec4 getIBLVolumeRefraction( const in vec3 n, const in vec3 v, const in float roughness, const in vec3 diffuseColor,
		const in vec3 specularColor, const in float specularF90, const in vec3 position, const in mat4 modelMatrix,
		const in mat4 viewMatrix, const in mat4 projMatrix, const in float ior, const in float thickness,
		const in vec3 attenuationColor, const in float attenuationDistance ) {
		vec3 transmissionRay = getVolumeTransmissionRay( n, v, thickness, ior, modelMatrix );
		vec3 refractedRayExit = position + transmissionRay;
		vec4 ndcPos = projMatrix * viewMatrix * vec4( refractedRayExit, 1.0 );
		vec2 refractionCoords = ndcPos.xy / ndcPos.w;
		refractionCoords += 1.0;
		refractionCoords /= 2.0;
		vec4 transmittedLight = getTransmissionSample( refractionCoords, roughness, ior );
		vec3 transmittance = diffuseColor * volumeAttenuation( length( transmissionRay ), attenuationColor, attenuationDistance );
		vec3 attenuatedColor = transmittance * transmittedLight.rgb;
		vec3 F = EnvironmentBRDF( n, v, specularColor, specularF90, roughness );
		float transmittanceFactor = ( transmittance.r + transmittance.g + transmittance.b ) / 3.0;
		return vec4( ( 1.0 - F ) * attenuatedColor, 1.0 - ( 1.0 - transmittedLight.a ) * transmittanceFactor );
	}
#endif`,e4=`#if defined( USE_UV ) || defined( USE_ANISOTROPY )
	varying vec2 vUv;
#endif
#ifdef USE_MAP
	varying vec2 vMapUv;
#endif
#ifdef USE_ALPHAMAP
	varying vec2 vAlphaMapUv;
#endif
#ifdef USE_LIGHTMAP
	varying vec2 vLightMapUv;
#endif
#ifdef USE_AOMAP
	varying vec2 vAoMapUv;
#endif
#ifdef USE_BUMPMAP
	varying vec2 vBumpMapUv;
#endif
#ifdef USE_NORMALMAP
	varying vec2 vNormalMapUv;
#endif
#ifdef USE_EMISSIVEMAP
	varying vec2 vEmissiveMapUv;
#endif
#ifdef USE_METALNESSMAP
	varying vec2 vMetalnessMapUv;
#endif
#ifdef USE_ROUGHNESSMAP
	varying vec2 vRoughnessMapUv;
#endif
#ifdef USE_ANISOTROPYMAP
	varying vec2 vAnisotropyMapUv;
#endif
#ifdef USE_CLEARCOATMAP
	varying vec2 vClearcoatMapUv;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	varying vec2 vClearcoatNormalMapUv;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	varying vec2 vClearcoatRoughnessMapUv;
#endif
#ifdef USE_IRIDESCENCEMAP
	varying vec2 vIridescenceMapUv;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	varying vec2 vIridescenceThicknessMapUv;
#endif
#ifdef USE_SHEEN_COLORMAP
	varying vec2 vSheenColorMapUv;
#endif
#ifdef USE_SHEEN_ROUGHNESSMAP
	varying vec2 vSheenRoughnessMapUv;
#endif
#ifdef USE_SPECULARMAP
	varying vec2 vSpecularMapUv;
#endif
#ifdef USE_SPECULAR_COLORMAP
	varying vec2 vSpecularColorMapUv;
#endif
#ifdef USE_SPECULAR_INTENSITYMAP
	varying vec2 vSpecularIntensityMapUv;
#endif
#ifdef USE_TRANSMISSIONMAP
	uniform mat3 transmissionMapTransform;
	varying vec2 vTransmissionMapUv;
#endif
#ifdef USE_THICKNESSMAP
	uniform mat3 thicknessMapTransform;
	varying vec2 vThicknessMapUv;
#endif`,t4=`#if defined( USE_UV ) || defined( USE_ANISOTROPY )
	varying vec2 vUv;
#endif
#ifdef USE_MAP
	uniform mat3 mapTransform;
	varying vec2 vMapUv;
#endif
#ifdef USE_ALPHAMAP
	uniform mat3 alphaMapTransform;
	varying vec2 vAlphaMapUv;
#endif
#ifdef USE_LIGHTMAP
	uniform mat3 lightMapTransform;
	varying vec2 vLightMapUv;
#endif
#ifdef USE_AOMAP
	uniform mat3 aoMapTransform;
	varying vec2 vAoMapUv;
#endif
#ifdef USE_BUMPMAP
	uniform mat3 bumpMapTransform;
	varying vec2 vBumpMapUv;
#endif
#ifdef USE_NORMALMAP
	uniform mat3 normalMapTransform;
	varying vec2 vNormalMapUv;
#endif
#ifdef USE_DISPLACEMENTMAP
	uniform mat3 displacementMapTransform;
	varying vec2 vDisplacementMapUv;
#endif
#ifdef USE_EMISSIVEMAP
	uniform mat3 emissiveMapTransform;
	varying vec2 vEmissiveMapUv;
#endif
#ifdef USE_METALNESSMAP
	uniform mat3 metalnessMapTransform;
	varying vec2 vMetalnessMapUv;
#endif
#ifdef USE_ROUGHNESSMAP
	uniform mat3 roughnessMapTransform;
	varying vec2 vRoughnessMapUv;
#endif
#ifdef USE_ANISOTROPYMAP
	uniform mat3 anisotropyMapTransform;
	varying vec2 vAnisotropyMapUv;
#endif
#ifdef USE_CLEARCOATMAP
	uniform mat3 clearcoatMapTransform;
	varying vec2 vClearcoatMapUv;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	uniform mat3 clearcoatNormalMapTransform;
	varying vec2 vClearcoatNormalMapUv;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	uniform mat3 clearcoatRoughnessMapTransform;
	varying vec2 vClearcoatRoughnessMapUv;
#endif
#ifdef USE_SHEEN_COLORMAP
	uniform mat3 sheenColorMapTransform;
	varying vec2 vSheenColorMapUv;
#endif
#ifdef USE_SHEEN_ROUGHNESSMAP
	uniform mat3 sheenRoughnessMapTransform;
	varying vec2 vSheenRoughnessMapUv;
#endif
#ifdef USE_IRIDESCENCEMAP
	uniform mat3 iridescenceMapTransform;
	varying vec2 vIridescenceMapUv;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	uniform mat3 iridescenceThicknessMapTransform;
	varying vec2 vIridescenceThicknessMapUv;
#endif
#ifdef USE_SPECULARMAP
	uniform mat3 specularMapTransform;
	varying vec2 vSpecularMapUv;
#endif
#ifdef USE_SPECULAR_COLORMAP
	uniform mat3 specularColorMapTransform;
	varying vec2 vSpecularColorMapUv;
#endif
#ifdef USE_SPECULAR_INTENSITYMAP
	uniform mat3 specularIntensityMapTransform;
	varying vec2 vSpecularIntensityMapUv;
#endif
#ifdef USE_TRANSMISSIONMAP
	uniform mat3 transmissionMapTransform;
	varying vec2 vTransmissionMapUv;
#endif
#ifdef USE_THICKNESSMAP
	uniform mat3 thicknessMapTransform;
	varying vec2 vThicknessMapUv;
#endif`,n4=`#if defined( USE_UV ) || defined( USE_ANISOTROPY )
	vUv = vec3( uv, 1 ).xy;
#endif
#ifdef USE_MAP
	vMapUv = ( mapTransform * vec3( MAP_UV, 1 ) ).xy;
#endif
#ifdef USE_ALPHAMAP
	vAlphaMapUv = ( alphaMapTransform * vec3( ALPHAMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_LIGHTMAP
	vLightMapUv = ( lightMapTransform * vec3( LIGHTMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_AOMAP
	vAoMapUv = ( aoMapTransform * vec3( AOMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_BUMPMAP
	vBumpMapUv = ( bumpMapTransform * vec3( BUMPMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_NORMALMAP
	vNormalMapUv = ( normalMapTransform * vec3( NORMALMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_DISPLACEMENTMAP
	vDisplacementMapUv = ( displacementMapTransform * vec3( DISPLACEMENTMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_EMISSIVEMAP
	vEmissiveMapUv = ( emissiveMapTransform * vec3( EMISSIVEMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_METALNESSMAP
	vMetalnessMapUv = ( metalnessMapTransform * vec3( METALNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_ROUGHNESSMAP
	vRoughnessMapUv = ( roughnessMapTransform * vec3( ROUGHNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_ANISOTROPYMAP
	vAnisotropyMapUv = ( anisotropyMapTransform * vec3( ANISOTROPYMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_CLEARCOATMAP
	vClearcoatMapUv = ( clearcoatMapTransform * vec3( CLEARCOATMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_CLEARCOAT_NORMALMAP
	vClearcoatNormalMapUv = ( clearcoatNormalMapTransform * vec3( CLEARCOAT_NORMALMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_CLEARCOAT_ROUGHNESSMAP
	vClearcoatRoughnessMapUv = ( clearcoatRoughnessMapTransform * vec3( CLEARCOAT_ROUGHNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_IRIDESCENCEMAP
	vIridescenceMapUv = ( iridescenceMapTransform * vec3( IRIDESCENCEMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_IRIDESCENCE_THICKNESSMAP
	vIridescenceThicknessMapUv = ( iridescenceThicknessMapTransform * vec3( IRIDESCENCE_THICKNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SHEEN_COLORMAP
	vSheenColorMapUv = ( sheenColorMapTransform * vec3( SHEEN_COLORMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SHEEN_ROUGHNESSMAP
	vSheenRoughnessMapUv = ( sheenRoughnessMapTransform * vec3( SHEEN_ROUGHNESSMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SPECULARMAP
	vSpecularMapUv = ( specularMapTransform * vec3( SPECULARMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SPECULAR_COLORMAP
	vSpecularColorMapUv = ( specularColorMapTransform * vec3( SPECULAR_COLORMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_SPECULAR_INTENSITYMAP
	vSpecularIntensityMapUv = ( specularIntensityMapTransform * vec3( SPECULAR_INTENSITYMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_TRANSMISSIONMAP
	vTransmissionMapUv = ( transmissionMapTransform * vec3( TRANSMISSIONMAP_UV, 1 ) ).xy;
#endif
#ifdef USE_THICKNESSMAP
	vThicknessMapUv = ( thicknessMapTransform * vec3( THICKNESSMAP_UV, 1 ) ).xy;
#endif`,i4=`#if defined( USE_ENVMAP ) || defined( DISTANCE ) || defined ( USE_SHADOWMAP ) || defined ( USE_TRANSMISSION ) || NUM_SPOT_LIGHT_COORDS > 0
	vec4 worldPosition = vec4( transformed, 1.0 );
	#ifdef USE_BATCHING
		worldPosition = batchingMatrix * worldPosition;
	#endif
	#ifdef USE_INSTANCING
		worldPosition = instanceMatrix * worldPosition;
	#endif
	worldPosition = modelMatrix * worldPosition;
#endif`;const r4=`varying vec2 vUv;
uniform mat3 uvTransform;
void main() {
	vUv = ( uvTransform * vec3( uv, 1 ) ).xy;
	gl_Position = vec4( position.xy, 1.0, 1.0 );
}`,s4=`uniform sampler2D t2D;
uniform float backgroundIntensity;
varying vec2 vUv;
void main() {
	vec4 texColor = texture2D( t2D, vUv );
	#ifdef DECODE_VIDEO_TEXTURE
		texColor = vec4( mix( pow( texColor.rgb * 0.9478672986 + vec3( 0.0521327014 ), vec3( 2.4 ) ), texColor.rgb * 0.0773993808, vec3( lessThanEqual( texColor.rgb, vec3( 0.04045 ) ) ) ), texColor.w );
	#endif
	texColor.rgb *= backgroundIntensity;
	gl_FragColor = texColor;
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,o4=`varying vec3 vWorldDirection;
#include <common>
void main() {
	vWorldDirection = transformDirection( position, modelMatrix );
	#include <begin_vertex>
	#include <project_vertex>
	gl_Position.z = gl_Position.w;
}`,a4=`#ifdef ENVMAP_TYPE_CUBE
	uniform samplerCube envMap;
#elif defined( ENVMAP_TYPE_CUBE_UV )
	uniform sampler2D envMap;
#endif
uniform float flipEnvMap;
uniform float backgroundBlurriness;
uniform float backgroundIntensity;
varying vec3 vWorldDirection;
#include <cube_uv_reflection_fragment>
void main() {
	#ifdef ENVMAP_TYPE_CUBE
		vec4 texColor = textureCube( envMap, vec3( flipEnvMap * vWorldDirection.x, vWorldDirection.yz ) );
	#elif defined( ENVMAP_TYPE_CUBE_UV )
		vec4 texColor = textureCubeUV( envMap, vWorldDirection, backgroundBlurriness );
	#else
		vec4 texColor = vec4( 0.0, 0.0, 0.0, 1.0 );
	#endif
	texColor.rgb *= backgroundIntensity;
	gl_FragColor = texColor;
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,l4=`varying vec3 vWorldDirection;
#include <common>
void main() {
	vWorldDirection = transformDirection( position, modelMatrix );
	#include <begin_vertex>
	#include <project_vertex>
	gl_Position.z = gl_Position.w;
}`,c4=`uniform samplerCube tCube;
uniform float tFlip;
uniform float opacity;
varying vec3 vWorldDirection;
void main() {
	vec4 texColor = textureCube( tCube, vec3( tFlip * vWorldDirection.x, vWorldDirection.yz ) );
	gl_FragColor = texColor;
	gl_FragColor.a *= opacity;
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,u4=`#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
varying vec2 vHighPrecisionZW;
void main() {
	#include <uv_vertex>
	#include <batching_vertex>
	#include <skinbase_vertex>
	#ifdef USE_DISPLACEMENTMAP
		#include <beginnormal_vertex>
		#include <morphnormal_vertex>
		#include <skinnormal_vertex>
	#endif
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vHighPrecisionZW = gl_Position.zw;
}`,h4=`#if DEPTH_PACKING == 3200
	uniform float opacity;
#endif
#include <common>
#include <packing>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
varying vec2 vHighPrecisionZW;
void main() {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( 1.0 );
	#if DEPTH_PACKING == 3200
		diffuseColor.a = opacity;
	#endif
	#include <map_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <logdepthbuf_fragment>
	float fragCoordZ = 0.5 * vHighPrecisionZW[0] / vHighPrecisionZW[1] + 0.5;
	#if DEPTH_PACKING == 3200
		gl_FragColor = vec4( vec3( 1.0 - fragCoordZ ), opacity );
	#elif DEPTH_PACKING == 3201
		gl_FragColor = packDepthToRGBA( fragCoordZ );
	#endif
}`,p4=`#define DISTANCE
varying vec3 vWorldPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <batching_vertex>
	#include <skinbase_vertex>
	#ifdef USE_DISPLACEMENTMAP
		#include <beginnormal_vertex>
		#include <morphnormal_vertex>
		#include <skinnormal_vertex>
	#endif
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <worldpos_vertex>
	#include <clipping_planes_vertex>
	vWorldPosition = worldPosition.xyz;
}`,f4=`#define DISTANCE
uniform vec3 referencePosition;
uniform float nearDistance;
uniform float farDistance;
varying vec3 vWorldPosition;
#include <common>
#include <packing>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <clipping_planes_pars_fragment>
void main () {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( 1.0 );
	#include <map_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	float dist = length( vWorldPosition - referencePosition );
	dist = ( dist - nearDistance ) / ( farDistance - nearDistance );
	dist = saturate( dist );
	gl_FragColor = packDepthToRGBA( dist );
}`,d4=`varying vec3 vWorldDirection;
#include <common>
void main() {
	vWorldDirection = transformDirection( position, modelMatrix );
	#include <begin_vertex>
	#include <project_vertex>
}`,m4=`uniform sampler2D tEquirect;
varying vec3 vWorldDirection;
#include <common>
void main() {
	vec3 direction = normalize( vWorldDirection );
	vec2 sampleUV = equirectUv( direction );
	gl_FragColor = texture2D( tEquirect, sampleUV );
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
}`,S4=`uniform float scale;
attribute float lineDistance;
varying float vLineDistance;
#include <common>
#include <uv_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	vLineDistance = scale * lineDistance;
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <fog_vertex>
}`,g4=`uniform vec3 diffuse;
uniform float opacity;
uniform float dashSize;
uniform float totalSize;
varying float vLineDistance;
#include <common>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <fog_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	if ( mod( vLineDistance, totalSize ) > dashSize ) {
		discard;
	}
	vec3 outgoingLight = vec3( 0.0 );
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	outgoingLight = diffuseColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
}`,A4=`#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <envmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#if defined ( USE_ENVMAP ) || defined ( USE_SKINNING )
		#include <beginnormal_vertex>
		#include <morphnormal_vertex>
		#include <skinbase_vertex>
		#include <skinnormal_vertex>
		#include <defaultnormal_vertex>
	#endif
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <worldpos_vertex>
	#include <envmap_vertex>
	#include <fog_vertex>
}`,y4=`uniform vec3 diffuse;
uniform float opacity;
#ifndef FLAT_SHADED
	varying vec3 vNormal;
#endif
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_pars_fragment>
#include <fog_pars_fragment>
#include <specularmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <specularmap_fragment>
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	#ifdef USE_LIGHTMAP
		vec4 lightMapTexel = texture2D( lightMap, vLightMapUv );
		reflectedLight.indirectDiffuse += lightMapTexel.rgb * lightMapIntensity * RECIPROCAL_PI;
	#else
		reflectedLight.indirectDiffuse += vec3( 1.0 );
	#endif
	#include <aomap_fragment>
	reflectedLight.indirectDiffuse *= diffuseColor.rgb;
	vec3 outgoingLight = reflectedLight.indirectDiffuse;
	#include <envmap_fragment>
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,E4=`#define LAMBERT
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <envmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <envmap_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,C4=`#define LAMBERT
uniform vec3 diffuse;
uniform vec3 emissive;
uniform float opacity;
#include <common>
#include <packing>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_pars_fragment>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_lambert_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <specularmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( diffuse, opacity );
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <specularmap_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_lambert_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;
	#include <envmap_fragment>
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,v4=`#define MATCAP
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <color_pars_vertex>
#include <displacementmap_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <fog_vertex>
	vViewPosition = - mvPosition.xyz;
}`,U4=`#define MATCAP
uniform vec3 diffuse;
uniform float opacity;
uniform sampler2D matcap;
varying vec3 vViewPosition;
#include <common>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <fog_pars_fragment>
#include <normal_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	vec3 viewDir = normalize( vViewPosition );
	vec3 x = normalize( vec3( viewDir.z, 0.0, - viewDir.x ) );
	vec3 y = cross( viewDir, x );
	vec2 uv = vec2( dot( x, normal ), dot( y, normal ) ) * 0.495 + 0.5;
	#ifdef USE_MATCAP
		vec4 matcapColor = texture2D( matcap, uv );
	#else
		vec4 matcapColor = vec4( vec3( mix( 0.2, 0.8, uv.y ) ), 1.0 );
	#endif
	vec3 outgoingLight = diffuseColor.rgb * matcapColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,w4=`#define NORMAL
#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )
	varying vec3 vViewPosition;
#endif
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )
	vViewPosition = - mvPosition.xyz;
#endif
}`,M4=`#define NORMAL
uniform float opacity;
#if defined( FLAT_SHADED ) || defined( USE_BUMPMAP ) || defined( USE_NORMALMAP_TANGENTSPACE )
	varying vec3 vViewPosition;
#endif
#include <packing>
#include <uv_pars_fragment>
#include <normal_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	#include <logdepthbuf_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	gl_FragColor = vec4( packNormalToRGB( normal ), opacity );
	#ifdef OPAQUE
		gl_FragColor.a = 1.0;
	#endif
}`,k4=`#define PHONG
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <envmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <envmap_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,x4=`#define PHONG
uniform vec3 diffuse;
uniform vec3 emissive;
uniform vec3 specular;
uniform float shininess;
uniform float opacity;
#include <common>
#include <packing>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_pars_fragment>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_phong_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <specularmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( diffuse, opacity );
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <specularmap_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_phong_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + reflectedLight.directSpecular + reflectedLight.indirectSpecular + totalEmissiveRadiance;
	#include <envmap_fragment>
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,T4=`#define STANDARD
varying vec3 vViewPosition;
#ifdef USE_TRANSMISSION
	varying vec3 vWorldPosition;
#endif
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
#ifdef USE_TRANSMISSION
	vWorldPosition = worldPosition.xyz;
#endif
}`,J4=`#define STANDARD
#ifdef PHYSICAL
	#define IOR
	#define USE_SPECULAR
#endif
uniform vec3 diffuse;
uniform vec3 emissive;
uniform float roughness;
uniform float metalness;
uniform float opacity;
#ifdef IOR
	uniform float ior;
#endif
#ifdef USE_SPECULAR
	uniform float specularIntensity;
	uniform vec3 specularColor;
	#ifdef USE_SPECULAR_COLORMAP
		uniform sampler2D specularColorMap;
	#endif
	#ifdef USE_SPECULAR_INTENSITYMAP
		uniform sampler2D specularIntensityMap;
	#endif
#endif
#ifdef USE_CLEARCOAT
	uniform float clearcoat;
	uniform float clearcoatRoughness;
#endif
#ifdef USE_IRIDESCENCE
	uniform float iridescence;
	uniform float iridescenceIOR;
	uniform float iridescenceThicknessMinimum;
	uniform float iridescenceThicknessMaximum;
#endif
#ifdef USE_SHEEN
	uniform vec3 sheenColor;
	uniform float sheenRoughness;
	#ifdef USE_SHEEN_COLORMAP
		uniform sampler2D sheenColorMap;
	#endif
	#ifdef USE_SHEEN_ROUGHNESSMAP
		uniform sampler2D sheenRoughnessMap;
	#endif
#endif
#ifdef USE_ANISOTROPY
	uniform vec2 anisotropyVector;
	#ifdef USE_ANISOTROPYMAP
		uniform sampler2D anisotropyMap;
	#endif
#endif
varying vec3 vViewPosition;
#include <common>
#include <packing>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <iridescence_fragment>
#include <cube_uv_reflection_fragment>
#include <envmap_common_pars_fragment>
#include <envmap_physical_pars_fragment>
#include <fog_pars_fragment>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_physical_pars_fragment>
#include <transmission_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <clearcoat_pars_fragment>
#include <iridescence_pars_fragment>
#include <roughnessmap_pars_fragment>
#include <metalnessmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( diffuse, opacity );
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <roughnessmap_fragment>
	#include <metalnessmap_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <clearcoat_normal_fragment_begin>
	#include <clearcoat_normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_physical_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 totalDiffuse = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse;
	vec3 totalSpecular = reflectedLight.directSpecular + reflectedLight.indirectSpecular;
	#include <transmission_fragment>
	vec3 outgoingLight = totalDiffuse + totalSpecular + totalEmissiveRadiance;
	#ifdef USE_SHEEN
		float sheenEnergyComp = 1.0 - 0.157 * max3( material.sheenColor );
		outgoingLight = outgoingLight * sheenEnergyComp + sheenSpecularDirect + sheenSpecularIndirect;
	#endif
	#ifdef USE_CLEARCOAT
		float dotNVcc = saturate( dot( geometryClearcoatNormal, geometryViewDir ) );
		vec3 Fcc = F_Schlick( material.clearcoatF0, material.clearcoatF90, dotNVcc );
		outgoingLight = outgoingLight * ( 1.0 - material.clearcoat * Fcc ) + ( clearcoatSpecularDirect + clearcoatSpecularIndirect ) * material.clearcoat;
	#endif
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,I4=`#define TOON
varying vec3 vViewPosition;
#include <common>
#include <batching_pars_vertex>
#include <uv_pars_vertex>
#include <displacementmap_pars_vertex>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <normal_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <shadowmap_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <normal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <displacementmap_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	vViewPosition = - mvPosition.xyz;
	#include <worldpos_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,L4=`#define TOON
uniform vec3 diffuse;
uniform vec3 emissive;
uniform float opacity;
#include <common>
#include <packing>
#include <dithering_pars_fragment>
#include <color_pars_fragment>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <aomap_pars_fragment>
#include <lightmap_pars_fragment>
#include <emissivemap_pars_fragment>
#include <gradientmap_pars_fragment>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <normal_pars_fragment>
#include <lights_toon_pars_fragment>
#include <shadowmap_pars_fragment>
#include <bumpmap_pars_fragment>
#include <normalmap_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec4 diffuseColor = vec4( diffuse, opacity );
	ReflectedLight reflectedLight = ReflectedLight( vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ), vec3( 0.0 ) );
	vec3 totalEmissiveRadiance = emissive;
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <color_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	#include <normal_fragment_begin>
	#include <normal_fragment_maps>
	#include <emissivemap_fragment>
	#include <lights_toon_fragment>
	#include <lights_fragment_begin>
	#include <lights_fragment_maps>
	#include <lights_fragment_end>
	#include <aomap_fragment>
	vec3 outgoingLight = reflectedLight.directDiffuse + reflectedLight.indirectDiffuse + totalEmissiveRadiance;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
	#include <dithering_fragment>
}`,B4=`uniform float size;
uniform float scale;
#include <common>
#include <color_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
#ifdef USE_POINTS_UV
	varying vec2 vUv;
	uniform mat3 uvTransform;
#endif
void main() {
	#ifdef USE_POINTS_UV
		vUv = ( uvTransform * vec3( uv, 1 ) ).xy;
	#endif
	#include <color_vertex>
	#include <morphcolor_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <project_vertex>
	gl_PointSize = size;
	#ifdef USE_SIZEATTENUATION
		bool isPerspective = isPerspectiveMatrix( projectionMatrix );
		if ( isPerspective ) gl_PointSize *= ( scale / - mvPosition.z );
	#endif
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <worldpos_vertex>
	#include <fog_vertex>
}`,K4=`uniform vec3 diffuse;
uniform float opacity;
#include <common>
#include <color_pars_fragment>
#include <map_particle_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <fog_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec3 outgoingLight = vec3( 0.0 );
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <logdepthbuf_fragment>
	#include <map_particle_fragment>
	#include <color_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	outgoingLight = diffuseColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
	#include <premultiplied_alpha_fragment>
}`,R4=`#include <common>
#include <batching_pars_vertex>
#include <fog_pars_vertex>
#include <morphtarget_pars_vertex>
#include <skinning_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <shadowmap_pars_vertex>
void main() {
	#include <batching_vertex>
	#include <beginnormal_vertex>
	#include <morphnormal_vertex>
	#include <skinbase_vertex>
	#include <skinnormal_vertex>
	#include <defaultnormal_vertex>
	#include <begin_vertex>
	#include <morphtarget_vertex>
	#include <skinning_vertex>
	#include <project_vertex>
	#include <logdepthbuf_vertex>
	#include <worldpos_vertex>
	#include <shadowmap_vertex>
	#include <fog_vertex>
}`,D4=`uniform vec3 color;
uniform float opacity;
#include <common>
#include <packing>
#include <fog_pars_fragment>
#include <bsdfs>
#include <lights_pars_begin>
#include <logdepthbuf_pars_fragment>
#include <shadowmap_pars_fragment>
#include <shadowmask_pars_fragment>
void main() {
	#include <logdepthbuf_fragment>
	gl_FragColor = vec4( color, opacity * ( 1.0 - getShadowMask() ) );
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
}`,b4=`uniform float rotation;
uniform vec2 center;
#include <common>
#include <uv_pars_vertex>
#include <fog_pars_vertex>
#include <logdepthbuf_pars_vertex>
#include <clipping_planes_pars_vertex>
void main() {
	#include <uv_vertex>
	vec4 mvPosition = modelViewMatrix * vec4( 0.0, 0.0, 0.0, 1.0 );
	vec2 scale;
	scale.x = length( vec3( modelMatrix[ 0 ].x, modelMatrix[ 0 ].y, modelMatrix[ 0 ].z ) );
	scale.y = length( vec3( modelMatrix[ 1 ].x, modelMatrix[ 1 ].y, modelMatrix[ 1 ].z ) );
	#ifndef USE_SIZEATTENUATION
		bool isPerspective = isPerspectiveMatrix( projectionMatrix );
		if ( isPerspective ) scale *= - mvPosition.z;
	#endif
	vec2 alignedPosition = ( position.xy - ( center - vec2( 0.5 ) ) ) * scale;
	vec2 rotatedPosition;
	rotatedPosition.x = cos( rotation ) * alignedPosition.x - sin( rotation ) * alignedPosition.y;
	rotatedPosition.y = sin( rotation ) * alignedPosition.x + cos( rotation ) * alignedPosition.y;
	mvPosition.xy += rotatedPosition;
	gl_Position = projectionMatrix * mvPosition;
	#include <logdepthbuf_vertex>
	#include <clipping_planes_vertex>
	#include <fog_vertex>
}`,O4=`uniform vec3 diffuse;
uniform float opacity;
#include <common>
#include <uv_pars_fragment>
#include <map_pars_fragment>
#include <alphamap_pars_fragment>
#include <alphatest_pars_fragment>
#include <alphahash_pars_fragment>
#include <fog_pars_fragment>
#include <logdepthbuf_pars_fragment>
#include <clipping_planes_pars_fragment>
void main() {
	#include <clipping_planes_fragment>
	vec3 outgoingLight = vec3( 0.0 );
	vec4 diffuseColor = vec4( diffuse, opacity );
	#include <logdepthbuf_fragment>
	#include <map_fragment>
	#include <alphamap_fragment>
	#include <alphatest_fragment>
	#include <alphahash_fragment>
	outgoingLight = diffuseColor.rgb;
	#include <opaque_fragment>
	#include <tonemapping_fragment>
	#include <colorspace_fragment>
	#include <fog_fragment>
}`,bt={alphahash_fragment:sW,alphahash_pars_fragment:oW,alphamap_fragment:aW,alphamap_pars_fragment:lW,alphatest_fragment:cW,alphatest_pars_fragment:uW,aomap_fragment:hW,aomap_pars_fragment:pW,batching_pars_vertex:fW,batching_vertex:dW,begin_vertex:mW,beginnormal_vertex:SW,bsdfs:gW,iridescence_fragment:AW,bumpmap_pars_fragment:yW,clipping_planes_fragment:EW,clipping_planes_pars_fragment:CW,clipping_planes_pars_vertex:vW,clipping_planes_vertex:UW,color_fragment:wW,color_pars_fragment:MW,color_pars_vertex:kW,color_vertex:xW,common:TW,cube_uv_reflection_fragment:JW,defaultnormal_vertex:IW,displacementmap_pars_vertex:LW,displacementmap_vertex:BW,emissivemap_fragment:KW,emissivemap_pars_fragment:RW,colorspace_fragment:DW,colorspace_pars_fragment:bW,envmap_fragment:OW,envmap_common_pars_fragment:FW,envmap_pars_fragment:PW,envmap_pars_vertex:NW,envmap_physical_pars_fragment:_W,envmap_vertex:QW,fog_vertex:WW,fog_pars_vertex:HW,fog_fragment:zW,fog_pars_fragment:GW,gradientmap_pars_fragment:VW,lightmap_fragment:qW,lightmap_pars_fragment:YW,lights_lambert_fragment:ZW,lights_lambert_pars_fragment:jW,lights_pars_begin:XW,lights_toon_fragment:$W,lights_toon_pars_fragment:eH,lights_phong_fragment:tH,lights_phong_pars_fragment:nH,lights_physical_fragment:iH,lights_physical_pars_fragment:rH,lights_fragment_begin:sH,lights_fragment_maps:oH,lights_fragment_end:aH,logdepthbuf_fragment:lH,logdepthbuf_pars_fragment:cH,logdepthbuf_pars_vertex:uH,logdepthbuf_vertex:hH,map_fragment:pH,map_pars_fragment:fH,map_particle_fragment:dH,map_particle_pars_fragment:mH,metalnessmap_fragment:SH,metalnessmap_pars_fragment:gH,morphcolor_vertex:AH,morphnormal_vertex:yH,morphtarget_pars_vertex:EH,morphtarget_vertex:CH,normal_fragment_begin:vH,normal_fragment_maps:UH,normal_pars_fragment:wH,normal_pars_vertex:MH,normal_vertex:kH,normalmap_pars_fragment:xH,clearcoat_normal_fragment_begin:TH,clearcoat_normal_fragment_maps:JH,clearcoat_pars_fragment:IH,iridescence_pars_fragment:LH,opaque_fragment:BH,packing:KH,premultiplied_alpha_fragment:RH,project_vertex:DH,dithering_fragment:bH,dithering_pars_fragment:OH,roughnessmap_fragment:FH,roughnessmap_pars_fragment:PH,shadowmap_pars_fragment:NH,shadowmap_pars_vertex:QH,shadowmap_vertex:WH,shadowmask_pars_fragment:HH,skinbase_vertex:zH,skinning_pars_vertex:GH,skinning_vertex:VH,skinnormal_vertex:qH,specularmap_fragment:YH,specularmap_pars_fragment:ZH,tonemapping_fragment:jH,tonemapping_pars_fragment:XH,transmission_fragment:_H,transmission_pars_fragment:$H,uv_pars_fragment:e4,uv_pars_vertex:t4,uv_vertex:n4,worldpos_vertex:i4,background_vert:r4,background_frag:s4,backgroundCube_vert:o4,backgroundCube_frag:a4,cube_vert:l4,cube_frag:c4,depth_vert:u4,depth_frag:h4,distanceRGBA_vert:p4,distanceRGBA_frag:f4,equirect_vert:d4,equirect_frag:m4,linedashed_vert:S4,linedashed_frag:g4,meshbasic_vert:A4,meshbasic_frag:y4,meshlambert_vert:E4,meshlambert_frag:C4,meshmatcap_vert:v4,meshmatcap_frag:U4,meshnormal_vert:w4,meshnormal_frag:M4,meshphong_vert:k4,meshphong_frag:x4,meshphysical_vert:T4,meshphysical_frag:J4,meshtoon_vert:I4,meshtoon_frag:L4,points_vert:B4,points_frag:K4,shadow_vert:R4,shadow_frag:D4,sprite_vert:b4,sprite_frag:O4},Ze={common:{diffuse:{value:new ze(16777215)},opacity:{value:1},map:{value:null},mapTransform:{value:new Ot},alphaMap:{value:null},alphaMapTransform:{value:new Ot},alphaTest:{value:0}},specularmap:{specularMap:{value:null},specularMapTransform:{value:new Ot}},envmap:{envMap:{value:null},flipEnvMap:{value:-1},reflectivity:{value:1},ior:{value:1.5},refractionRatio:{value:.98}},aomap:{aoMap:{value:null},aoMapIntensity:{value:1},aoMapTransform:{value:new Ot}},lightmap:{lightMap:{value:null},lightMapIntensity:{value:1},lightMapTransform:{value:new Ot}},bumpmap:{bumpMap:{value:null},bumpMapTransform:{value:new Ot},bumpScale:{value:1}},normalmap:{normalMap:{value:null},normalMapTransform:{value:new Ot},normalScale:{value:new we(1,1)}},displacementmap:{displacementMap:{value:null},displacementMapTransform:{value:new Ot},displacementScale:{value:1},displacementBias:{value:0}},emissivemap:{emissiveMap:{value:null},emissiveMapTransform:{value:new Ot}},metalnessmap:{metalnessMap:{value:null},metalnessMapTransform:{value:new Ot}},roughnessmap:{roughnessMap:{value:null},roughnessMapTransform:{value:new Ot}},gradientmap:{gradientMap:{value:null}},fog:{fogDensity:{value:25e-5},fogNear:{value:1},fogFar:{value:2e3},fogColor:{value:new ze(16777215)}},lights:{ambientLightColor:{value:[]},lightProbe:{value:[]},directionalLights:{value:[],properties:{direction:{},color:{}}},directionalLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},directionalShadowMap:{value:[]},directionalShadowMatrix:{value:[]},spotLights:{value:[],properties:{color:{},position:{},direction:{},distance:{},coneCos:{},penumbraCos:{},decay:{}}},spotLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{}}},spotLightMap:{value:[]},spotShadowMap:{value:[]},spotLightMatrix:{value:[]},pointLights:{value:[],properties:{color:{},position:{},decay:{},distance:{}}},pointLightShadows:{value:[],properties:{shadowBias:{},shadowNormalBias:{},shadowRadius:{},shadowMapSize:{},shadowCameraNear:{},shadowCameraFar:{}}},pointShadowMap:{value:[]},pointShadowMatrix:{value:[]},hemisphereLights:{value:[],properties:{direction:{},skyColor:{},groundColor:{}}},rectAreaLights:{value:[],properties:{color:{},position:{},width:{},height:{}}},ltc_1:{value:null},ltc_2:{value:null}},points:{diffuse:{value:new 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Ff{constructor(e=-1,t=1,i=1,r=-1,s=.1,o=2e3){super(),this.isOrthographicCamera=!0,this.type="OrthographicCamera",this.zoom=1,this.view=null,this.left=e,this.right=t,this.top=i,this.bottom=r,this.near=s,this.far=o,this.updateProjectionMatrix()}copy(e,t){return super.copy(e,t),this.left=e.left,this.right=e.right,this.top=e.top,this.bottom=e.bottom,this.near=e.near,this.far=e.far,this.zoom=e.zoom,this.view=e.view===null?null:Object.assign({},e.view),this}setViewOffset(e,t,i,r,s,o){this.view===null&&(this.view={enabled:!0,fullWidth:1,fullHeight:1,offsetX:0,offsetY:0,width:1,height:1}),this.view.enabled=!0,this.view.fullWidth=e,this.view.fullHeight=t,this.view.offsetX=i,this.view.offsetY=r,this.view.width=s,this.view.height=o,this.updateProjectionMatrix()}clearViewOffset(){this.view!==null&&(this.view.enabled=!1),this.updateProjectionMatrix()}updateProjectionMatrix(){const e=(this.right-this.left)/(2*this.zoom),t=(this.top-this.bottom)/(2*this.zoom),i=(this.right+this.left)/2,r=(this.top+this.bottom)/2;let s=i-e,o=i+e,a=r+t,l=r-t;if(this.view!==null&&this.view.enabled){const c=(this.right-this.left)/this.view.fullWidth/this.zoom,h=(this.top-this.bottom)/this.view.fullHeight/this.zoom;s+=c*this.view.offsetX,o=s+c*this.view.width,a-=h*this.view.offsetY,l=a-h*this.view.height}this.projectionMatrix.makeOrthographic(s,o,a,l,this.near,this.far,this.coordinateSystem),this.projectionMatrixInverse.copy(this.projectionMatrix).invert()}toJSON(e){const t=super.toJSON(e);return t.object.zoom=this.zoom,t.object.left=this.left,t.object.right=this.right,t.object.top=this.top,t.object.bottom=this.bottom,t.object.near=this.near,t.object.far=this.far,this.view!==null&&(t.object.view=Object.assign({},this.view)),t}}const Eu=4,kT=[.125,.215,.35,.446,.526,.582],Cu=20,I0=new ws,xT=new ze;let L0=null,B0=0,K0=0;const Tl=(1+Math.sqrt(5))/2,Vc=1/Tl,TT=[new N(1,1,1),new N(-1,1,1),new N(1,1,-1),new N(-1,1,-1),new N(0,Tl,Vc),new N(0,Tl,-Vc),new N(Vc,0,Tl),new N(-Vc,0,Tl),new N(Tl,Vc,0),new N(-Tl,Vc,0)];class rv{constructor(e){this._renderer=e,this._pingPongRenderTarget=null,this._lodMax=0,this._cubeSize=0,this._lodPlanes=[],this._sizeLods=[],this._sigmas=[],this._blurMaterial=null,this._cubemapMaterial=null,this._equirectMaterial=null,this._compileMaterial(this._blurMaterial)}fromScene(e,t=0,i=.1,r=100){L0=this._renderer.getRenderTarget(),B0=this._renderer.getActiveCubeFace(),K0=this._renderer.getActiveMipmapLevel(),this._setSize(256);const s=this._allocateTargets();return s.depthBuffer=!0,this._sceneToCubeUV(e,i,r,s),t>0&&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 this._fromTexture(e,t)}compileCubemapShader(){this._cubemapMaterial===null&&(this._cubemapMaterial=LT(),this._compileMaterial(this._cubemapMaterial))}compileEquirectangularShader(){this._equirectMaterial===null&&(this._equirectMaterial=IT(),this._compileMaterial(this._equirectMaterial))}dispose(){this._dispose(),this._cubemapMaterial!==null&&this._cubemapMaterial.dispose(),this._equirectMaterial!==null&&this._equirectMaterial.dispose()}_setSize(e){this._lodMax=Math.floor(Math.log2(e)),this._cubeSize=Math.pow(2,this._lodMax)}_dispose(){this._blurMaterial!==null&&this._blurMaterial.dispose(),this._pingPongRenderTarget!==null&&this._pingPongRenderTarget.dispose();for(let e=0;e<this._lodPlanes.length;e++)this._lodPlanes[e].dispose()}_cleanup(e){this._renderer.setRenderTarget(L0,B0,K0),e.scissorTest=!1,bm(e,0,0,e.width,e.height)}_fromTexture(e,t){e.mapping===no||e.mapping===Pa?this._setSize(e.image.length===0?16:e.image[0].width||e.image[0].image.width):this._setSize(e.image.width/4),L0=this._renderer.getRenderTarget(),B0=this._renderer.getActiveCubeFace(),K0=this._renderer.getActiveMipmapLevel();const i=t||this._allocateTargets();return this._textureToCubeUV(e,i),this._applyPMREM(i),this._cleanup(i),i}_allocateTargets(){const e=3*Math.max(this._cubeSize,112),t=4*this._cubeSize,i={magFilter:pn,minFilter:pn,generateMipmaps:!1,type:ji,format:bi,colorSpace:so,depthBuffer:!1},r=JT(e,t,i);if(this._pingPongRenderTarget===null||this._pingPongRenderTarget.width!==e||this._pingPongRenderTarget.height!==t){this._pingPongRenderTarget!==null&&this._dispose(),this._pingPongRenderTarget=JT(e,t,i);const{_lodMax:s}=this;({sizeLods:this._sizeLods,lodPlanes:this._lodPlanes,sigmas:this._sigmas}=z4(s)),this._blurMaterial=G4(s,e,t)}return r}_compileMaterial(e){const t=new Gn(this._lodPlanes[0],e);this._renderer.compile(t,I0)}_sceneToCubeUV(e,t,i,r){const a=new xn(90,1,t,i),l=[1,-1,1,1,1,1],c=[1,1,1,-1,-1,-1],h=this._renderer,f=h.autoClear,d=h.toneMapping;h.getClearColor(xT),h.toneMapping=_s,h.autoClear=!1;const m=new Ir({name:"PMREM.Background",side:$i,depthWrite:!1,depthTest:!1}),g=new Gn(new fc,m);let E=!1;const C=e.background;C?C.isColor&&(m.color.copy(C),e.background=null,E=!0):(m.color.copy(xT),E=!0);for(let S=0;S<6;S++){const v=S%3;v===0?(a.up.set(0,l[S],0),a.lookAt(c[S],0,0)):v===1?(a.up.set(0,0,l[S]),a.lookAt(0,c[S],0)):(a.up.set(0,l[S],0),a.lookAt(0,0,c[S]));const y=this._cubeSize;bm(r,v*y,S>2?y:0,y,y),h.setRenderTarget(r),E&&h.render(g,a),h.render(e,a)}g.geometry.dispose(),g.material.dispose(),h.toneMapping=d,h.autoClear=f,e.background=C}_textureToCubeUV(e,t){const i=this._renderer,r=e.mapping===no||e.mapping===Pa;r?(this._cubemapMaterial===null&&(this._cubemapMaterial=LT()),this._cubemapMaterial.uniforms.flipEnvMap.value=e.isRenderTargetTexture===!1?-1:1):this._equirectMaterial===null&&(this._equirectMaterial=IT());const s=r?this._cubemapMaterial:this._equirectMaterial,o=new Gn(this._lodPlanes[0],s),a=s.uniforms;a.envMap.value=e;const l=this._cubeSize;bm(t,0,0,3*l,2*l),i.setRenderTarget(t),i.render(o,I0)}_applyPMREM(e){const t=this._renderer,i=t.autoClear;t.autoClear=!1;for(let r=1;r<this._lodPlanes.length;r++){const s=Math.sqrt(this._sigmas[r]*this._sigmas[r]-this._sigmas[r-1]*this._sigmas[r-1]),o=TT[(r-1)%TT.length];this._blur(e,r-1,r,s,o)}t.autoClear=i}_blur(e,t,i,r,s){const o=this._pingPongRenderTarget;this._halfBlur(e,o,t,i,r,"latitudinal",s),this._halfBlur(o,e,i,i,r,"longitudinal",s)}_halfBlur(e,t,i,r,s,o,a){const l=this._renderer,c=this._blurMaterial,h=3,f=new Gn(this._lodPlanes[r],c),d=c.uniforms,m=this._sizeLods[i]-1,g=isFinite(s)?Math.PI/(2*m):2*Math.PI/(2*Cu-1),E=s/g,C=isFinite(s)?1+Math.floor(h*E):Cu;C>Cu;const S=[];let v=0;for(let I=0;I<Cu;++I){const R=I/E,T=Math.exp(-R*R/2);S.push(T),I===0?v+=T:I<C&&(v+=2*T)}for(let I=0;I<S.length;I++)S[I]=S[I]/v;d.envMap.value=e.texture,d.samples.value=C,d.weights.value=S,d.latitudinal.value=o==="latitudinal",a&&(d.poleAxis.value=a);const{_lodMax:y}=this;d.dTheta.value=g,d.mipInt.value=y-i;const w=this._sizeLods[r],x=3*w*(r>y-Eu?r-y+Eu:0),k=4*(this._cubeSize-w);bm(t,x,k,3*w,2*w),l.setRenderTarget(t),l.render(f,I0)}}function z4(n){const e=[],t=[],i=[];let r=n;const s=n-Eu+1+kT.length;for(let o=0;o<s;o++){const a=Math.pow(2,r);t.push(a);let l=1/a;o>n-Eu?l=kT[o-n+Eu-1]:o===0&&(l=0),i.push(l);const c=1/(a-2),h=-c,f=1+c,d=[h,h,f,h,f,f,h,h,f,f,h,f],m=6,g=6,E=3,C=2,S=1,v=new Float32Array(E*g*m),y=new Float32Array(C*g*m),w=new Float32Array(S*g*m);for(let k=0;k<m;k++){const I=k%3*2/3-1,R=k>2?0:-1,T=[I,R,0,I+2/3,R,0,I+2/3,R+1,0,I,R,0,I+2/3,R+1,0,I,R+1,0];v.set(T,E*g*k),y.set(d,C*g*k);const L=[k,k,k,k,k,k];w.set(L,S*g*k)}const x=new Tt;x.setAttribute("position",new Xt(v,E)),x.setAttribute("uv",new Xt(y,C)),x.setAttribute("faceIndex",new Xt(w,S)),e.push(x),r>Eu&&r--}return{lodPlanes:e,sizeLods:t,sigmas:i}}function JT(n,e,t){const i=new Is(n,e,t);return i.texture.mapping=ah,i.texture.name="PMREM.cubeUv",i.scissorTest=!0,i}function bm(n,e,t,i,r){n.viewport.set(e,t,i,r),n.scissor.set(e,t,i,r)}function G4(n,e,t){const i=new Float32Array(Cu),r=new N(0,1,0);return new Ls({name:"SphericalGaussianBlur",defines:{n:Cu,CUBEUV_TEXEL_WIDTH:1/e,CUBEUV_TEXEL_HEIGHT:1/t,CUBEUV_MAX_MIP:`${n}.0`},uniforms:{envMap:{value:null},samples:{value:1},weights:{value:i},latitudinal:{value:!1},dTheta:{value:0},mipInt:{value:0},poleAxis:{value:r}},vertexShader:ow(),fragmentShader:`

			precision mediump float;
			precision mediump int;

			varying vec3 vOutputDirection;

			uniform sampler2D envMap;
			uniform int samples;
			uniform float weights[ n ];
			uniform bool latitudinal;
			uniform float dTheta;
			uniform float mipInt;
			uniform vec3 poleAxis;

			#define ENVMAP_TYPE_CUBE_UV
			#include <cube_uv_reflection_fragment>

			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 );

			}

			void main() {

				vec3 axis = latitudinal ? poleAxis : cross( poleAxis, vOutputDirection );

				if ( all( equal( axis, vec3( 0.0 ) ) ) ) {

					axis = vec3( vOutputDirection.z, 0.0, - vOutputDirection.x );

				}

				axis = normalize( axis );

				gl_FragColor = vec4( 0.0, 0.0, 0.0, 1.0 );
				gl_FragColor.rgb += weights[ 0 ] * getSample( 0.0, axis );

				for ( int i = 1; i < n; i++ ) {

					if ( i >= samples ) {

						break;

					}

					float theta = dTheta * float( i );
					gl_FragColor.rgb += weights[ i ] * getSample( -1.0 * theta, axis );
					gl_FragColor.rgb += weights[ i ] * getSample( theta, axis );

				}

			}
		`,blending:Oo,depthTest:!1,depthWrite:!1})}function IT(){return new Ls({name:"EquirectangularToCubeUV",uniforms:{envMap:{value:null}},vertexShader:ow(),fragmentShader:`

			precision mediump float;
			precision mediump int;

			varying vec3 vOutputDirection;

			uniform sampler2D envMap;

			#include <common>

			void main() {

				vec3 outputDirection = normalize( vOutputDirection );
				vec2 uv = equirectUv( outputDirection );

				gl_FragColor = vec4( texture2D ( envMap, uv ).rgb, 1.0 );

			}
		`,blending:Oo,depthTest:!1,depthWrite:!1})}function LT(){return new Ls({name:"CubemapToCubeUV",uniforms:{envMap:{value:null},flipEnvMap:{value:-1}},vertexShader:ow(),fragmentShader:`

			precision mediump float;
			precision mediump int;

			uniform float flipEnvMap;

			varying vec3 vOutputDirection;

			uniform samplerCube envMap;

			void main() {

				gl_FragColor = textureCube( envMap, vec3( flipEnvMap * vOutputDirection.x, vOutputDirection.yz ) );

			}
		`,blending:Oo,depthTest:!1,depthWrite:!1})}function ow(){return`

		precision mediump float;
		precision mediump int;

		attribute float faceIndex;

		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 );
			gl_Position = vec4( position, 1.0 );

		}
	`}function V4(n){let e=new WeakMap,t=null;function i(a){if(a&&a.isTexture){const l=a.mapping,c=l===$l||l===af,h=l===no||l===Pa;if(c||h)if(a.isRenderTargetTexture&&a.needsPMREMUpdate===!0){a.needsPMREMUpdate=!1;let f=e.get(a);return t===null&&(t=new rv(n)),f=c?t.fromEquirectangular(a,f):t.fromCubemap(a,f),e.set(a,f),f.texture}else{if(e.has(a))return e.get(a).texture;{const f=a.image;if(c&&f&&f.height>0||h&&f&&r(f)){t===null&&(t=new rv(n));const d=c?t.fromEquirectangular(a):t.fromCubemap(a);return e.set(a,d),a.addEventListener("dispose",s),d.texture}else return null}}}return a}function r(a){let l=0;const c=6;for(let h=0;h<c;h++)a[h]!==void 0&&l++;return l===c}function s(a){const l=a.target;l.removeEventListener("dispose",s);const c=e.get(l);c!==void 0&&(e.delete(l),c.dispose())}function o(){e=new WeakMap,t!==null&&(t.dispose(),t=null)}return{get:i,dispose:o}}function q4(n){const e={};function t(i){if(e[i]!==void 0)return e[i];let r;switch(i){case"WEBGL_depth_texture":r=n.getExtension("WEBGL_depth_texture")||n.getExtension("MOZ_WEBGL_depth_texture")||n.getExtension("WEBKIT_WEBGL_depth_texture");break;case"EXT_texture_filter_anisotropic":r=n.getExtension("EXT_texture_filter_anisotropic")||n.getExtension("MOZ_EXT_texture_filter_anisotropic")||n.getExtension("WEBKIT_EXT_texture_filter_anisotropic");break;case"WEBGL_compressed_texture_s3tc":r=n.getExtension("WEBGL_compressed_texture_s3tc")||n.getExtension("MOZ_WEBGL_compressed_texture_s3tc")||n.getExtension("WEBKIT_WEBGL_compressed_texture_s3tc");break;case"WEBGL_compressed_texture_pvrtc":r=n.getExtension("WEBGL_compressed_texture_pvrtc")||n.getExtension("WEBKIT_WEBGL_compressed_texture_pvrtc");break;default:r=n.getExtension(i)}return e[i]=r,r}return{has:function(i){return t(i)!==null},init:function(i){i.isWebGL2?t("EXT_color_buffer_float"):(t("WEBGL_depth_texture"),t("OES_texture_float"),t("OES_texture_half_float"),t("OES_texture_half_float_linear"),t("OES_standard_derivatives"),t("OES_element_index_uint"),t("OES_vertex_array_object"),t("ANGLE_instanced_arrays")),t("OES_texture_float_linear"),t("EXT_color_buffer_half_float"),t("WEBGL_multisampled_render_to_texture")},get:function(i){const r=t(i);return r}}}function Y4(n,e,t,i){const r={},s=new WeakMap;function o(f){const d=f.target;d.index!==null&&e.remove(d.index);for(const g in d.attributes)e.remove(d.attributes[g]);for(const g in d.morphAttributes){const E=d.morphAttributes[g];for(let C=0,S=E.length;C<S;C++)e.remove(E[C])}d.removeEventListener("dispose",o),delete r[d.id];const m=s.get(d);m&&(e.remove(m),s.delete(d)),i.releaseStatesOfGeometry(d),d.isInstancedBufferGeometry===!0&&delete d._maxInstanceCount,t.memory.geometries--}function a(f,d){return r[d.id]===!0||(d.addEventListener("dispose",o),r[d.id]=!0,t.memory.geometries++),d}function l(f){const d=f.attributes;for(const g in d)e.update(d[g],n.ARRAY_BUFFER);const m=f.morphAttributes;for(const g in m){const E=m[g];for(let C=0,S=E.length;C<S;C++)e.update(E[C],n.ARRAY_BUFFER)}}function c(f){const d=[],m=f.index,g=f.attributes.position;let E=0;if(m!==null){const v=m.array;E=m.version;for(let y=0,w=v.length;y<w;y+=3){const x=v[y+0],k=v[y+1],I=v[y+2];d.push(x,k,k,I,I,x)}}else if(g!==void 0){const v=g.array;E=g.version;for(let y=0,w=v.length/3-1;y<w;y+=3){const x=y+0,k=y+1,I=y+2;d.push(x,k,k,I,I,x)}}else return;const C=new(rR(d)?rw:rA)(d,1);C.version=E;const S=s.get(f);S&&e.remove(S),s.set(f,C)}function h(f){const d=s.get(f);if(d){const m=f.index;m!==null&&d.version<m.version&&c(f)}else c(f);return s.get(f)}return{get:a,update:l,getWireframeAttribute:h}}function Z4(n,e,t,i){const r=i.isWebGL2;let s;function o(m){s=m}let a,l;function c(m){a=m.type,l=m.bytesPerElement}function h(m,g){n.drawElements(s,g,a,m*l),t.update(g,s,1)}function f(m,g,E){if(E===0)return;let C,S;if(r)C=n,S="drawElementsInstanced";else if(C=e.get("ANGLE_instanced_arrays"),S="drawElementsInstancedANGLE",C===null)return;C[S](s,g,a,m*l,E),t.update(g,s,E)}function d(m,g,E){if(E===0)return;const C=e.get("WEBGL_multi_draw");if(C===null)for(let S=0;S<E;S++)this.render(m[S]/l,g[S]);else{C.multiDrawElementsWEBGL(s,g,0,a,m,0,E);let S=0;for(let v=0;v<E;v++)S+=g[v];t.update(S,s,1)}}this.setMode=o,this.setIndex=c,this.render=h,this.renderInstances=f,this.renderMultiDraw=d}function j4(n){const e={geometries:0,textures:0},t={frame:0,calls:0,triangles:0,points:0,lines:0};function i(s,o,a){switch(t.calls++,o){case n.TRIANGLES:t.triangles+=a*(s/3);break;case n.LINES:t.lines+=a*(s/2);break;case n.LINE_STRIP:t.lines+=a*(s-1);break;case n.LINE_LOOP:t.lines+=a*s;break;case n.POINTS:t.points+=a*s;break;default:break}}function 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`),C.length>0&&(C+=`
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SPECULAR_COLORMAP_UV "+t.specularColorMapUv:"",t.specularIntensityMapUv?"#define SPECULAR_INTENSITYMAP_UV "+t.specularIntensityMapUv:"",t.transmissionMapUv?"#define TRANSMISSIONMAP_UV "+t.transmissionMapUv:"",t.thicknessMapUv?"#define THICKNESSMAP_UV "+t.thicknessMapUv:"",t.vertexTangents&&t.flatShading===!1?"#define USE_TANGENT":"",t.vertexColors?"#define USE_COLOR":"",t.vertexAlphas?"#define USE_COLOR_ALPHA":"",t.vertexUv1s?"#define USE_UV1":"",t.vertexUv2s?"#define USE_UV2":"",t.vertexUv3s?"#define USE_UV3":"",t.pointsUvs?"#define USE_POINTS_UV":"",t.flatShading?"#define FLAT_SHADED":"",t.skinning?"#define USE_SKINNING":"",t.morphTargets?"#define USE_MORPHTARGETS":"",t.morphNormals&&t.flatShading===!1?"#define USE_MORPHNORMALS":"",t.morphColors&&t.isWebGL2?"#define USE_MORPHCOLORS":"",t.morphTargetsCount>0&&t.isWebGL2?"#define MORPHTARGETS_TEXTURE":"",t.morphTargetsCount>0&&t.isWebGL2?"#define MORPHTARGETS_TEXTURE_STRIDE 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`].filter(gp).join(`
`),S=[m,HT(t),"#define SHADER_TYPE "+t.shaderType,"#define SHADER_NAME "+t.shaderName,g,t.useFog&&t.fog?"#define USE_FOG":"",t.useFog&&t.fogExp2?"#define FOG_EXP2":"",t.map?"#define USE_MAP":"",t.matcap?"#define USE_MATCAP":"",t.envMap?"#define USE_ENVMAP":"",t.envMap?"#define "+c:"",t.envMap?"#define "+h:"",t.envMap?"#define "+f:"",d?"#define CUBEUV_TEXEL_WIDTH "+d.texelWidth:"",d?"#define CUBEUV_TEXEL_HEIGHT "+d.texelHeight:"",d?"#define CUBEUV_MAX_MIP "+d.maxMip+".0":"",t.lightMap?"#define USE_LIGHTMAP":"",t.aoMap?"#define USE_AOMAP":"",t.bumpMap?"#define USE_BUMPMAP":"",t.normalMap?"#define USE_NORMALMAP":"",t.normalMapObjectSpace?"#define USE_NORMALMAP_OBJECTSPACE":"",t.normalMapTangentSpace?"#define USE_NORMALMAP_TANGENTSPACE":"",t.emissiveMap?"#define USE_EMISSIVEMAP":"",t.anisotropy?"#define USE_ANISOTROPY":"",t.anisotropyMap?"#define USE_ANISOTROPYMAP":"",t.clearcoat?"#define USE_CLEARCOAT":"",t.clearcoatMap?"#define USE_CLEARCOATMAP":"",t.clearcoatRoughnessMap?"#define USE_CLEARCOAT_ROUGHNESSMAP":"",t.clearcoatNormalMap?"#define USE_CLEARCOAT_NORMALMAP":"",t.iridescence?"#define USE_IRIDESCENCE":"",t.iridescenceMap?"#define USE_IRIDESCENCEMAP":"",t.iridescenceThicknessMap?"#define USE_IRIDESCENCE_THICKNESSMAP":"",t.specularMap?"#define USE_SPECULARMAP":"",t.specularColorMap?"#define USE_SPECULAR_COLORMAP":"",t.specularIntensityMap?"#define USE_SPECULAR_INTENSITYMAP":"",t.roughnessMap?"#define USE_ROUGHNESSMAP":"",t.metalnessMap?"#define USE_METALNESSMAP":"",t.alphaMap?"#define USE_ALPHAMAP":"",t.alphaTest?"#define USE_ALPHATEST":"",t.alphaHash?"#define USE_ALPHAHASH":"",t.sheen?"#define USE_SHEEN":"",t.sheenColorMap?"#define USE_SHEEN_COLORMAP":"",t.sheenRoughnessMap?"#define USE_SHEEN_ROUGHNESSMAP":"",t.transmission?"#define USE_TRANSMISSION":"",t.transmissionMap?"#define USE_TRANSMISSIONMAP":"",t.thicknessMap?"#define USE_THICKNESSMAP":"",t.vertexTangents&&t.flatShading===!1?"#define USE_TANGENT":"",t.vertexColors||t.instancingColor?"#define USE_COLOR":"",t.vertexAlphas?"#define USE_COLOR_ALPHA":"",t.vertexUv1s?"#define USE_UV1":"",t.vertexUv2s?"#define USE_UV2":"",t.vertexUv3s?"#define USE_UV3":"",t.pointsUvs?"#define USE_POINTS_UV":"",t.gradientMap?"#define USE_GRADIENTMAP":"",t.flatShading?"#define FLAT_SHADED":"",t.doubleSided?"#define DOUBLE_SIDED":"",t.flipSided?"#define FLIP_SIDED":"",t.shadowMapEnabled?"#define USE_SHADOWMAP":"",t.shadowMapEnabled?"#define "+l:"",t.premultipliedAlpha?"#define PREMULTIPLIED_ALPHA":"",t.numLightProbes>0?"#define USE_LIGHT_PROBES":"",t.useLegacyLights?"#define LEGACY_LIGHTS":"",t.decodeVideoTexture?"#define DECODE_VIDEO_TEXTURE":"",t.logarithmicDepthBuffer?"#define USE_LOGDEPTHBUF":"",t.logarithmicDepthBuffer&&t.rendererExtensionFragDepth?"#define USE_LOGDEPTHBUF_EXT":"","uniform mat4 viewMatrix;","uniform vec3 cameraPosition;","uniform bool isOrthographic;",t.toneMapping!==_s?"#define TONE_MAPPING":"",t.toneMapping!==_s?bt.tonemapping_pars_fragment:"",t.toneMapping!==_s?jz("toneMapping",t.toneMapping):"",t.dithering?"#define DITHERING":"",t.opaque?"#define OPAQUE":"",bt.colorspace_pars_fragment,Zz("linearToOutputTexel",t.outputColorSpace),t.useDepthPacking?"#define DEPTH_PACKING "+t.depthPacking:"",`
`].filter(gp).join(`
`)),o=sv(o),o=NT(o,t),o=QT(o,t),a=sv(a),a=NT(a,t),a=QT(a,t),o=WT(o),a=WT(a),t.isWebGL2&&t.isRawShaderMaterial!==!0&&(v=`#version 300 es
`,C=["precision mediump sampler2DArray;","#define attribute in","#define varying out","#define texture2D texture"].join(`
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`+C,S=["precision mediump sampler2DArray;","#define varying in",t.glslVersion===nv?"":"layout(location = 0) out highp vec4 pc_fragColor;",t.glslVersion===nv?"":"#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(`
`)+`
`+S);const y=v+C+o,w=v+S+a,x=FT(r,r.VERTEX_SHADER,y),k=FT(r,r.FRAGMENT_SHADER,w);r.attachShader(E,x),r.attachShader(E,k),t.index0AttributeName!==void 0?r.bindAttribLocation(E,0,t.index0AttributeName):t.morphTargets===!0&&r.bindAttribLocation(E,0,"position"),r.linkProgram(E);function I(O){if(n.debug.checkShaderErrors){const V=r.getProgramInfoLog(E).trim(),ie=r.getShaderInfoLog(x).trim(),W=r.getShaderInfoLog(k).trim();let _=!0,ne=!0;if(r.getProgramParameter(E,r.LINK_STATUS)===!1)if(_=!1,typeof n.debug.onShaderError=="function")n.debug.onShaderError(r,E,x,k);else{const oe=PT(r,x,"vertex"),H=PT(r,k,"fragment")}else V!==""||(ie===""||W==="")&&(ne=!1);ne&&(O.diagnostics={runnable:_,programLog:V,vertexShader:{log:ie,prefix:C},fragmentShader:{log:W,prefix:S}})}r.deleteShader(x),r.deleteShader(k),R=new NS(r,E),T=$z(r,E)}let R;this.getUniforms=function(){return R===void 0&&I(this),R};let T;this.getAttributes=function(){return T===void 0&&I(this),T};let L=t.rendererExtensionParallelShaderCompile===!1;return this.isReady=function(){return L===!1&&(L=r.getProgramParameter(E,Gz)),L},this.destroy=function(){i.releaseStatesOfProgram(this),r.deleteProgram(E),this.program=void 0},this.type=t.shaderType,this.name=t.shaderName,this.id=Vz++,this.cacheKey=e,this.usedTimes=1,this.program=E,this.vertexShader=x,this.fragmentShader=k,this}let hG=0;class pG{constructor(){this.shaderCache=new Map,this.materialCache=new Map}update(e){const t=e.vertexShader,i=e.fragmentShader,r=this._getShaderStage(t),s=this._getShaderStage(i),o=this._getShaderCacheForMaterial(e);return o.has(r)===!1&&(o.add(r),r.usedTimes++),o.has(s)===!1&&(o.add(s),s.usedTimes++),this}remove(e){const t=this.materialCache.get(e);for(const i of t)i.usedTimes--,i.usedTimes===0&&this.shaderCache.delete(i.code);return this.materialCache.delete(e),this}getVertexShaderID(e){return this._getShaderStage(e.vertexShader).id}getFragmentShaderID(e){return 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C(T,L,O,V,ie){const W=V.fog,_=ie.geometry,ne=T.isMeshStandardMaterial?V.environment:null,oe=(T.isMeshStandardMaterial?t:e).get(T.envMap||ne),H=oe&&oe.mapping===ah?oe.image.height:null,Z=g[T.type];T.precision!==null&&(m=r.getMaxPrecision(T.precision),T.precision);const te=_.morphAttributes.position||_.morphAttributes.normal||_.morphAttributes.color,ae=te!==void 0?te.length:0;let fe=0;_.morphAttributes.position!==void 0&&(fe=1),_.morphAttributes.normal!==void 0&&(fe=2),_.morphAttributes.color!==void 0&&(fe=3);let ce,me,Te,Me;if(Z){const dn=vs[Z];ce=dn.vertexShader,me=dn.fragmentShader}else ce=T.vertexShader,me=T.fragmentShader,l.update(T),Te=l.getVertexShaderID(T),Me=l.getFragmentShaderID(T);const Fe=n.getRenderTarget(),rt=ie.isInstancedMesh===!0,ft=ie.isBatchedMesh===!0,st=!!T.map,_e=!!T.matcap,Y=!!oe,Ie=!!T.aoMap,Ce=!!T.lightMap,De=!!T.bumpMap,xe=!!T.normalMap,ct=!!T.displacementMap,Ye=!!T.emissiveMap,je=!!T.metalnessMap,dt=!!T.roughnessMap,vt=T.anisotropy>0,_t=T.clearcoat>0,F=T.iridescence>0,b=T.sheen>0,ue=T.transmission>0,Be=vt&&!!T.anisotropyMap,Je=_t&&!!T.clearcoatMap,Re=_t&&!!T.clearcoatNormalMap,$e=_t&&!!T.clearcoatRoughnessMap,Qe=F&&!!T.iridescenceMap,Ge=F&&!!T.iridescenceThicknessMap,At=b&&!!T.sheenColorMap,kt=b&&!!T.sheenRoughnessMap,Le=!!T.specularMap,Dt=!!T.specularColorMap,$=!!T.specularIntensityMap,de=ue&&!!T.transmissionMap,ke=ue&&!!T.thicknessMap,be=!!T.gradientMap,Ue=!!T.alphaMap,re=T.alphaTest>0,qe=!!T.alphaHash,We=!!T.extensions,ve=!!_.attributes.uv1,Pe=!!_.attributes.uv2,pt=!!_.attributes.uv3;let It=_s;return T.toneMapped&&(Fe===null||Fe.isXRRenderTarget===!0)&&(It=n.toneMapping),{isWebGL2:h,shaderID:Z,shaderType:T.type,shaderName:T.name,vertexShader:ce,fragmentShader:me,defines:T.defines,customVertexShaderID:Te,customFragmentShaderID:Me,isRawShaderMaterial:T.isRawShaderMaterial===!0,glslVersion:T.glslVersion,precision:m,batching:ft,instancing:rt,instancingColor:rt&&ie.instanceColor!==null,supportsVertexTextures:d,outputColorSpace:Fe===null?n.outputColorSpace:Fe.isXRRenderTarget===!0?Fe.texture.colorSpace:so,map:st,matcap:_e,envMap:Y,envMapMode:Y&&oe.mapping,envMapCubeUVHeight:H,aoMap:Ie,lightMap:Ce,bumpMap:De,normalMap:xe,displacementMap:d&&ct,emissiveMap:Ye,normalMapObjectSpace:xe&&T.normalMapType===jK,normalMapTangentSpace:xe&&T.normalMapType===Za,metalnessMap:je,roughnessMap:dt,anisotropy:vt,anisotropyMap:Be,clearcoat:_t,clearcoatMap:Je,clearcoatNormalMap:Re,clearcoatRoughnessMap:$e,iridescence:F,iridescenceMap:Qe,iridescenceThicknessMap:Ge,sheen:b,sheenColorMap:At,sheenRoughnessMap:kt,specularMap:Le,specularColorMap:Dt,specularIntensityMap:$,transmission:ue,transmissionMap:de,thicknessMap:ke,gradientMap:be,opaque:T.transparent===!1&&T.blending===Ql,alphaMap:Ue,alphaTest:re,alphaHash:qe,combine:T.combine,mapUv:st&&E(T.map.channel),aoMapUv:Ie&&E(T.aoMap.channel),lightMapUv:Ce&&E(T.lightMap.channel),bumpMapUv:De&&E(T.bumpMap.channel),normalMapUv:xe&&E(T.normalMap.channel),displacementMapUv:ct&&E(T.displacementMap.channel),emissiveMapUv:Ye&&E(T.emissiveMap.channel),metalnessMapUv:je&&E(T.metalnessMap.channel),roughnessMapUv:dt&&E(T.roughnessMap.channel),anisotropyMapUv:Be&&E(T.anisotropyMap.channel),clearcoatMapUv:Je&&E(T.clearcoatMap.channel),clearcoatNormalMapUv:Re&&E(T.clearcoatNormalMap.channel),clearcoatRoughnessMapUv:$e&&E(T.clearcoatRoughnessMap.channel),iridescenceMapUv:Qe&&E(T.iridescenceMap.channel),iridescenceThicknessMapUv:Ge&&E(T.iridescenceThicknessMap.channel),sheenColorMapUv:At&&E(T.sheenColorMap.channel),sheenRoughnessMapUv:kt&&E(T.sheenRoughnessMap.channel),specularMapUv:Le&&E(T.specularMap.channel),specularColorMapUv:Dt&&E(T.specularColorMap.channel),specularIntensityMapUv:$&&E(T.specularIntensityMap.channel),transmissionMapUv:de&&E(T.transmissionMap.channel),thicknessMapUv:ke&&E(T.thicknessMap.channel),alphaMapUv:Ue&&E(T.alphaMap.channel),vertexTangents:!!_.attributes.tangent&&(xe||vt),vertexColors:T.vertexColors,vertexAlphas:T.vertexColors===!0&&!!_.attributes.color&&_.attributes.color.itemSize===4,vertexUv1s:ve,vertexUv2s:Pe,vertexUv3s:pt,pointsUvs:ie.isPoints===!0&&!!_.attributes.uv&&(st||Ue),fog:!!W,useFog:T.fog===!0,fogExp2:W&&W.isFogExp2,flatShading:T.flatShading===!0,sizeAttenuation:T.sizeAttenuation===!0,logarithmicDepthBuffer:f,skinning:ie.isSkinnedMesh===!0,morphTargets:_.morphAttributes.position!==void 0,morphNormals:_.morphAttributes.normal!==void 0,morphColors:_.morphAttributes.color!==void 0,morphTargetsCount:ae,morphTextureStride:fe,numDirLights:L.directional.length,numPointLights:L.point.length,numSpotLights:L.spot.length,numSpotLightMaps:L.spotLightMap.length,numRectAreaLights:L.rectArea.length,numHemiLights:L.hemi.length,numDirLightShadows:L.directionalShadowMap.length,numPointLightShadows:L.pointShadowMap.length,numSpotLightShadows:L.spotShadowMap.length,numSpotLightShadowsWithMaps:L.numSpotLightShadowsWithMaps,numLightProbes:L.numLightProbes,numClippingPlanes:o.numPlanes,numClipIntersection:o.numIntersection,dithering:T.dithering,shadowMapEnabled:n.shadowMap.enabled&&O.length>0,shadowMapType:n.shadowMap.type,toneMapping:It,useLegacyLights:n._useLegacyLights,decodeVideoTexture:st&&T.map.isVideoTexture===!0&&an.getTransfer(T.map.colorSpace)===gn,premultipliedAlpha:T.premultipliedAlpha,doubleSided:T.side===es,flipSided:T.side===$i,useDepthPacking:T.depthPacking>=0,depthPacking:T.depthPacking||0,index0AttributeName:T.index0AttributeName,extensionDerivatives:We&&T.extensions.derivatives===!0,extensionFragDepth:We&&T.extensions.fragDepth===!0,extensionDrawBuffers:We&&T.extensions.drawBuffers===!0,extensionShaderTextureLOD:We&&T.extensions.shaderTextureLOD===!0,rendererExtensionFragDepth:h||i.has("EXT_frag_depth"),rendererExtensionDrawBuffers:h||i.has("WEBGL_draw_buffers"),rendererExtensionShaderTextureLod:h||i.has("EXT_shader_texture_lod"),rendererExtensionParallelShaderCompile:i.has("KHR_parallel_shader_compile"),customProgramCacheKey:T.customProgramCacheKey()}}function S(T){const L=[];if(T.shaderID?L.push(T.shaderID):(L.push(T.customVertexShaderID),L.push(T.customFragmentShaderID)),T.defines!==void 0)for(const O in T.defines)L.push(O),L.push(T.defines[O]);return T.isRawShaderMaterial===!1&&(v(L,T),y(L,T),L.push(n.outputColorSpace)),L.push(T.customProgramCacheKey),L.join()}function v(T,L){T.push(L.precision),T.push(L.outputColorSpace),T.push(L.envMapMode),T.push(L.envMapCubeUVHeight),T.push(L.mapUv),T.push(L.alphaMapUv),T.push(L.lightMapUv),T.push(L.aoMapUv),T.push(L.bumpMapUv),T.push(L.normalMapUv),T.push(L.displacementMapUv),T.push(L.emissiveMapUv),T.push(L.metalnessMapUv),T.push(L.roughnessMapUv),T.push(L.anisotropyMapUv),T.push(L.clearcoatMapUv),T.push(L.clearcoatNormalMapUv),T.push(L.clearcoatRoughnessMapUv),T.push(L.iridescenceMapUv),T.push(L.iridescenceThicknessMapUv),T.push(L.sheenColorMapUv),T.push(L.sheenRoughnessMapUv),T.push(L.specularMapUv),T.push(L.specularColorMapUv),T.push(L.specularIntensityMapUv),T.push(L.transmissionMapUv),T.push(L.thicknessMapUv),T.push(L.combine),T.push(L.fogExp2),T.push(L.sizeAttenuation),T.push(L.morphTargetsCount),T.push(L.morphAttributeCount),T.push(L.numDirLights),T.push(L.numPointLights),T.push(L.numSpotLights),T.push(L.numSpotLightMaps),T.push(L.numHemiLights),T.push(L.numRectAreaLights),T.push(L.numDirLightShadows),T.push(L.numPointLightShadows),T.push(L.numSpotLightShadows),T.push(L.numSpotLightShadowsWithMaps),T.push(L.numLightProbes),T.push(L.shadowMapType),T.push(L.toneMapping),T.push(L.numClippingPlanes),T.push(L.numClipIntersection),T.push(L.depthPacking)}function y(T,L){a.disableAll(),L.isWebGL2&&a.enable(0),L.supportsVertexTextures&&a.enable(1),L.instancing&&a.enable(2),L.instancingColor&&a.enable(3),L.matcap&&a.enable(4),L.envMap&&a.enable(5),L.normalMapObjectSpace&&a.enable(6),L.normalMapTangentSpace&&a.enable(7),L.clearcoat&&a.enable(8),L.iridescence&&a.enable(9),L.alphaTest&&a.enable(10),L.vertexColors&&a.enable(11),L.vertexAlphas&&a.enable(12),L.vertexUv1s&&a.enable(13),L.vertexUv2s&&a.enable(14),L.vertexUv3s&&a.enable(15),L.vertexTangents&&a.enable(16),L.anisotropy&&a.enable(17),L.alphaHash&&a.enable(18),L.batching&&a.enable(19),T.push(a.mask),a.disableAll(),L.fog&&a.enable(0),L.useFog&&a.enable(1),L.flatShading&&a.enable(2),L.logarithmicDepthBuffer&&a.enable(3),L.skinning&&a.enable(4),L.morphTargets&&a.enable(5),L.morphNormals&&a.enable(6),L.morphColors&&a.enable(7),L.premultipliedAlpha&&a.enable(8),L.shadowMapEnabled&&a.enable(9),L.useLegacyLights&&a.enable(10),L.doubleSided&&a.enable(11),L.flipSided&&a.enable(12),L.useDepthPacking&&a.enable(13),L.dithering&&a.enable(14),L.transmission&&a.enable(15),L.sheen&&a.enable(16),L.opaque&&a.enable(17),L.pointsUvs&&a.enable(18),L.decodeVideoTexture&&a.enable(19),T.push(a.mask)}function w(T){const L=g[T.type];let O;if(L){const V=vs[L];O=cR.clone(V.uniforms)}else O=T.uniforms;return O}function x(T,L){let O;for(let V=0,ie=c.length;V<ie;V++){const W=c[V];if(W.cacheKey===L){O=W,++O.usedTimes;break}}return O===void 0&&(O=new uG(n,L,T,s),c.push(O)),O}function k(T){if(--T.usedTimes===0){const L=c.indexOf(T);c[L]=c[c.length-1],c.pop(),T.destroy()}}function I(T){l.remove(T)}function R(){l.dispose()}return{getParameters:C,getProgramCacheKey:S,getUniforms:w,acquireProgram:x,releaseProgram:k,releaseShaderCache:I,programs:c,dispose:R}}function mG(){let n=new WeakMap;function e(s){let o=n.get(s);return o===void 0&&(o={},n.set(s,o)),o}function t(s){n.delete(s)}function i(s,o,a){n.get(s)[o]=a}function r(){n=new WeakMap}return{get:e,remove:t,update:i,dispose:r}}function SG(n,e){return n.groupOrder!==e.groupOrder?n.groupOrder-e.groupOrder:n.renderOrder!==e.renderOrder?n.renderOrder-e.renderOrder:n.material.id!==e.material.id?n.material.id-e.material.id:n.z!==e.z?n.z-e.z:n.id-e.id}function zT(n,e){return n.groupOrder!==e.groupOrder?n.groupOrder-e.groupOrder:n.renderOrder!==e.renderOrder?n.renderOrder-e.renderOrder:n.z!==e.z?e.z-n.z:n.id-e.id}function GT(){const n=[];let e=0;const t=[],i=[],r=[];function s(){e=0,t.length=0,i.length=0,r.length=0}function o(f,d,m,g,E,C){let S=n[e];return S===void 0?(S={id:f.id,object:f,geometry:d,material:m,groupOrder:g,renderOrder:f.renderOrder,z:E,group:C},n[e]=S):(S.id=f.id,S.object=f,S.geometry=d,S.material=m,S.groupOrder=g,S.renderOrder=f.renderOrder,S.z=E,S.group=C),e++,S}function a(f,d,m,g,E,C){const S=o(f,d,m,g,E,C);m.transmission>0?i.push(S):m.transparent===!0?r.push(S):t.push(S)}function l(f,d,m,g,E,C){const S=o(f,d,m,g,E,C);m.transmission>0?i.unshift(S):m.transparent===!0?r.unshift(S):t.unshift(S)}function c(f,d){t.length>1&&t.sort(f||SG),i.length>1&&i.sort(d||zT),r.length>1&&r.sort(d||zT)}function h(){for(let f=e,d=n.length;f<d;f++){const m=n[f];if(m.id===null)break;m.id=null,m.object=null,m.geometry=null,m.material=null,m.group=null}}return{opaque:t,transmissive:i,transparent:r,init:s,push:a,unshift:l,finish:h,sort:c}}function gG(){let n=new WeakMap;function e(i,r){const s=n.get(i);let o;return s===void 0?(o=new GT,n.set(i,[o])):r>=s.length?(o=new GT,s.push(o)):o=s[r],o}function t(){n=new WeakMap}return{get:e,dispose:t}}function AG(){const n={};return{get:function(e){if(n[e.id]!==void 0)return n[e.id];let t;switch(e.type){case"DirectionalLight":t={direction:new N,color:new ze};break;case"SpotLight":t={position:new N,direction:new N,color:new ze,distance:0,coneCos:0,penumbraCos:0,decay:0};break;case"PointLight":t={position:new N,color:new ze,distance:0,decay:0};break;case"HemisphereLight":t={direction:new N,skyColor:new ze,groundColor:new ze};break;case"RectAreaLight":t={color:new ze,position:new N,halfWidth:new N,halfHeight:new N};break}return n[e.id]=t,t}}}function yG(){const n={};return{get:function(e){if(n[e.id]!==void 0)return n[e.id];let t;switch(e.type){case"DirectionalLight":t={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new we};break;case"SpotLight":t={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new we};break;case"PointLight":t={shadowBias:0,shadowNormalBias:0,shadowRadius:1,shadowMapSize:new we,shadowCameraNear:1,shadowCameraFar:1e3};break}return n[e.id]=t,t}}}let EG=0;function CG(n,e){return(e.castShadow?2:0)-(n.castShadow?2:0)+(e.map?1:0)-(n.map?1:0)}function vG(n,e){const t=new AG,i=yG(),r={version:0,hash:{directionalLength:-1,pointLength:-1,spotLength:-1,rectAreaLength:-1,hemiLength:-1,numDirectionalShadows:-1,numPointShadows:-1,numSpotShadows:-1,numSpotMaps:-1,numLightProbes:-1},ambient:[0,0,0],probe:[],directional:[],directionalShadow:[],directionalShadowMap:[],directionalShadowMatrix:[],spot:[],spotLightMap:[],spotShadow:[],spotShadowMap:[],spotLightMatrix:[],rectArea:[],rectAreaLTC1:null,rectAreaLTC2:null,point:[],pointShadow:[],pointShadowMap:[],pointShadowMatrix:[],hemi:[],numSpotLightShadowsWithMaps:0,numLightProbes:0};for(let h=0;h<9;h++)r.probe.push(new N);const s=new N,o=new tt,a=new tt;function l(h,f){let d=0,m=0,g=0;for(let V=0;V<9;V++)r.probe[V].set(0,0,0);let E=0,C=0,S=0,v=0,y=0,w=0,x=0,k=0,I=0,R=0,T=0;h.sort(CG);const L=f===!0?Math.PI:1;for(let V=0,ie=h.length;V<ie;V++){const W=h[V],_=W.color,ne=W.intensity,oe=W.distance,H=W.shadow&&W.shadow.map?W.shadow.map.texture:null;if(W.isAmbientLight)d+=_.r*ne*L,m+=_.g*ne*L,g+=_.b*ne*L;else if(W.isLightProbe){for(let Z=0;Z<9;Z++)r.probe[Z].addScaledVector(W.sh.coefficients[Z],ne);T++}else if(W.isDirectionalLight){const Z=t.get(W);if(Z.color.copy(W.color).multiplyScalar(W.intensity*L),W.castShadow){const te=W.shadow,ae=i.get(W);ae.shadowBias=te.bias,ae.shadowNormalBias=te.normalBias,ae.shadowRadius=te.radius,ae.shadowMapSize=te.mapSize,r.directionalShadow[E]=ae,r.directionalShadowMap[E]=H,r.directionalShadowMatrix[E]=W.shadow.matrix,w++}r.directional[E]=Z,E++}else if(W.isSpotLight){const Z=t.get(W);Z.position.setFromMatrixPosition(W.matrixWorld),Z.color.copy(_).multiplyScalar(ne*L),Z.distance=oe,Z.coneCos=Math.cos(W.angle),Z.penumbraCos=Math.cos(W.angle*(1-W.penumbra)),Z.decay=W.decay,r.spot[S]=Z;const te=W.shadow;if(W.map&&(r.spotLightMap[I]=W.map,I++,te.updateMatrices(W),W.castShadow&&R++),r.spotLightMatrix[S]=te.matrix,W.castShadow){const ae=i.get(W);ae.shadowBias=te.bias,ae.shadowNormalBias=te.normalBias,ae.shadowRadius=te.radius,ae.shadowMapSize=te.mapSize,r.spotShadow[S]=ae,r.spotShadowMap[S]=H,k++}S++}else if(W.isRectAreaLight){const Z=t.get(W);Z.color.copy(_).multiplyScalar(ne),Z.halfWidth.set(W.width*.5,0,0),Z.halfHeight.set(0,W.height*.5,0),r.rectArea[v]=Z,v++}else if(W.isPointLight){const Z=t.get(W);if(Z.color.copy(W.color).multiplyScalar(W.intensity*L),Z.distance=W.distance,Z.decay=W.decay,W.castShadow){const te=W.shadow,ae=i.get(W);ae.shadowBias=te.bias,ae.shadowNormalBias=te.normalBias,ae.shadowRadius=te.radius,ae.shadowMapSize=te.mapSize,ae.shadowCameraNear=te.camera.near,ae.shadowCameraFar=te.camera.far,r.pointShadow[C]=ae,r.pointShadowMap[C]=H,r.pointShadowMatrix[C]=W.shadow.matrix,x++}r.point[C]=Z,C++}else if(W.isHemisphereLight){const Z=t.get(W);Z.skyColor.copy(W.color).multiplyScalar(ne*L),Z.groundColor.copy(W.groundColor).multiplyScalar(ne*L),r.hemi[y]=Z,y++}}v>0&&(e.isWebGL2||n.has("OES_texture_float_linear")===!0?(r.rectAreaLTC1=Ze.LTC_FLOAT_1,r.rectAreaLTC2=Ze.LTC_FLOAT_2):n.has("OES_texture_half_float_linear")===!0&&(r.rectAreaLTC1=Ze.LTC_HALF_1,r.rectAreaLTC2=Ze.LTC_HALF_2)),r.ambient[0]=d,r.ambient[1]=m,r.ambient[2]=g;const O=r.hash;(O.directionalLength!==E||O.pointLength!==C||O.spotLength!==S||O.rectAreaLength!==v||O.hemiLength!==y||O.numDirectionalShadows!==w||O.numPointShadows!==x||O.numSpotShadows!==k||O.numSpotMaps!==I||O.numLightProbes!==T)&&(r.directional.length=E,r.spot.length=S,r.rectArea.length=v,r.point.length=C,r.hemi.length=y,r.directionalShadow.length=w,r.directionalShadowMap.length=w,r.pointShadow.length=x,r.pointShadowMap.length=x,r.spotShadow.length=k,r.spotShadowMap.length=k,r.directionalShadowMatrix.length=w,r.pointShadowMatrix.length=x,r.spotLightMatrix.length=k+I-R,r.spotLightMap.length=I,r.numSpotLightShadowsWithMaps=R,r.numLightProbes=T,O.directionalLength=E,O.pointLength=C,O.spotLength=S,O.rectAreaLength=v,O.hemiLength=y,O.numDirectionalShadows=w,O.numPointShadows=x,O.numSpotShadows=k,O.numSpotMaps=I,O.numLightProbes=T,r.version=EG++)}function c(h,f){let d=0,m=0,g=0,E=0,C=0;const S=f.matrixWorldInverse;for(let v=0,y=h.length;v<y;v++){const w=h[v];if(w.isDirectionalLight){const x=r.directional[d];x.direction.setFromMatrixPosition(w.matrixWorld),s.setFromMatrixPosition(w.target.matrixWorld),x.direction.sub(s),x.direction.transformDirection(S),d++}else if(w.isSpotLight){const x=r.spot[g];x.position.setFromMatrixPosition(w.matrixWorld),x.position.applyMatrix4(S),x.direction.setFromMatrixPosition(w.matrixWorld),s.setFromMatrixPosition(w.target.matrixWorld),x.direction.sub(s),x.direction.transformDirection(S),g++}else if(w.isRectAreaLight){const x=r.rectArea[E];x.position.setFromMatrixPosition(w.matrixWorld),x.position.applyMatrix4(S),a.identity(),o.copy(w.matrixWorld),o.premultiply(S),a.extractRotation(o),x.halfWidth.set(w.width*.5,0,0),x.halfHeight.set(0,w.height*.5,0),x.halfWidth.applyMatrix4(a),x.halfHeight.applyMatrix4(a),E++}else if(w.isPointLight){const x=r.point[m];x.position.setFromMatrixPosition(w.matrixWorld),x.position.applyMatrix4(S),m++}else if(w.isHemisphereLight){const x=r.hemi[C];x.direction.setFromMatrixPosition(w.matrixWorld),x.direction.transformDirection(S),C++}}}return{setup:l,setupView:c,state:r}}function VT(n,e){const t=new vG(n,e),i=[],r=[];function s(){i.length=0,r.length=0}function o(f){i.push(f)}function a(f){r.push(f)}function l(f){t.setup(i,f)}function c(f){t.setupView(i,f)}return{init:s,state:{lightsArray:i,shadowsArray:r,lights:t},setupLights:l,setupLightsView:c,pushLight:o,pushShadow:a}}function UG(n,e){let t=new WeakMap;function i(s,o=0){const a=t.get(s);let l;return a===void 0?(l=new VT(n,e),t.set(s,[l])):o>=a.length?(l=new VT(n,e),a.push(l)):l=a[o],l}function r(){t=new WeakMap}return{get:i,dispose:r}}class lw extends ti{constructor(e){super(),this.isMeshDepthMaterial=!0,this.type="MeshDepthMaterial",this.depthPacking=YK,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}}class cw extends ti{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}}const wG=`void main() {
	gl_Position = vec4( position, 1.0 );
}`,MG=`uniform sampler2D shadow_pass;
uniform vec2 resolution;
uniform float radius;
#include <packing>
void main() {
	const float samples = float( VSM_SAMPLES );
	float mean = 0.0;
	float squared_mean = 0.0;
	float uvStride = samples <= 1.0 ? 0.0 : 2.0 / ( samples - 1.0 );
	float uvStart = samples <= 1.0 ? 0.0 : - 1.0;
	for ( float i = 0.0; i < samples; i ++ ) {
		float uvOffset = uvStart + i * uvStride;
		#ifdef HORIZONTAL_PASS
			vec2 distribution = unpackRGBATo2Half( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( uvOffset, 0.0 ) * radius ) / resolution ) );
			mean += distribution.x;
			squared_mean += distribution.y * distribution.y + distribution.x * distribution.x;
		#else
			float depth = unpackRGBAToDepth( texture2D( shadow_pass, ( gl_FragCoord.xy + vec2( 0.0, uvOffset ) * radius ) / resolution ) );
			mean += depth;
			squared_mean += depth * depth;
		#endif
	}
	mean = mean / samples;
	squared_mean = squared_mean / samples;
	float std_dev = sqrt( squared_mean - mean * mean );
	gl_FragColor = pack2HalfToRGBA( vec2( mean, std_dev ) );
}`;function kG(n,e,t){let i=new Nf;const r=new we,s=new we,o=new $t,a=new lw({depthPacking:ZK}),l=new cw,c={},h=t.maxTextureSize,f={[to]:$i,[$i]:to,[es]:es},d=new Ls({defines:{VSM_SAMPLES:8},uniforms:{shadow_pass:{value:null},resolution:{value:new we},radius:{value:4}},vertexShader:wG,fragmentShader:MG}),m=d.clone();m.defines.HORIZONTAL_PASS=1;const g=new Tt;g.setAttribute("position",new Xt(new Float32Array([-1,-1,.5,3,-1,.5,-1,3,.5]),3));const E=new Gn(g,d),C=this;this.enabled=!1,this.autoUpdate=!0,this.needsUpdate=!1,this.type=Xg;let S=this.type;this.render=function(x,k,I){if(C.enabled===!1||C.autoUpdate===!1&&C.needsUpdate===!1||x.length===0)return;const R=n.getRenderTarget(),T=n.getActiveCubeFace(),L=n.getActiveMipmapLevel(),O=n.state;O.setBlending(Oo),O.buffers.color.setClear(1,1,1,1),O.buffers.depth.setTest(!0),O.setScissorTest(!1);const V=S!==ys&&this.type===ys,ie=S===ys&&this.type!==ys;for(let W=0,_=x.length;W<_;W++){const ne=x[W],oe=ne.shadow;if(oe===void 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I=e.update(E);d.defines.VSM_SAMPLES!==x.blurSamples&&(d.defines.VSM_SAMPLES=x.blurSamples,m.defines.VSM_SAMPLES=x.blurSamples,d.needsUpdate=!0,m.needsUpdate=!0),x.mapPass===null&&(x.mapPass=new Is(r.x,r.y)),d.uniforms.shadow_pass.value=x.map.texture,d.uniforms.resolution.value=x.mapSize,d.uniforms.radius.value=x.radius,n.setRenderTarget(x.mapPass),n.clear(),n.renderBufferDirect(k,null,I,d,E,null),m.uniforms.shadow_pass.value=x.mapPass.texture,m.uniforms.resolution.value=x.mapSize,m.uniforms.radius.value=x.radius,n.setRenderTarget(x.map),n.clear(),n.renderBufferDirect(k,null,I,m,E,null)}function y(x,k,I,R){let T=null;const L=I.isPointLight===!0?x.customDistanceMaterial:x.customDepthMaterial;if(L!==void 0)T=L;else if(T=I.isPointLight===!0?l:a,n.localClippingEnabled&&k.clipShadows===!0&&Array.isArray(k.clippingPlanes)&&k.clippingPlanes.length!==0||k.displacementMap&&k.displacementScale!==0||k.alphaMap&&k.alphaTest>0||k.map&&k.alphaTest>0){const O=T.uuid,V=k.uuid;let ie=c[O];ie===void 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kt=Math.max(1,b.width>>Re),Le=Math.max(1,b.height>>Re);Je===n.TEXTURE_3D||Je===n.TEXTURE_2D_ARRAY?t.texImage3D(Je,Re,Ge,kt,Le,b.depth,0,$e,Qe,null):t.texImage2D(Je,Re,Ge,kt,Le,0,$e,Qe,null)}t.bindFramebuffer(n.FRAMEBUFFER,F),dt(b)?d.framebufferTexture2DMultisampleEXT(n.FRAMEBUFFER,Be,Je,i.get(ue).__webglTexture,0,je(b)):(Je===n.TEXTURE_2D||Je>=n.TEXTURE_CUBE_MAP_POSITIVE_X&&Je<=n.TEXTURE_CUBE_MAP_NEGATIVE_Z)&&n.framebufferTexture2D(n.FRAMEBUFFER,Be,Je,i.get(ue).__webglTexture,Re),t.bindFramebuffer(n.FRAMEBUFFER,null)}function Y(F,b,ue){if(n.bindRenderbuffer(n.RENDERBUFFER,F),b.depthBuffer&&!b.stencilBuffer){let Be=a===!0?n.DEPTH_COMPONENT24:n.DEPTH_COMPONENT16;if(ue||dt(b)){const Je=b.depthTexture;Je&&Je.isDepthTexture&&(Je.type===Ei?Be=n.DEPTH_COMPONENT32F:Je.type===Do&&(Be=n.DEPTH_COMPONENT24));const Re=je(b);dt(b)?d.renderbufferStorageMultisampleEXT(n.RENDERBUFFER,Re,Be,b.width,b.height):n.renderbufferStorageMultisample(n.RENDERBUFFER,Re,Be,b.width,b.height)}else 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Be=i.get(b.depthTexture).__webglTexture,Je=je(b);if(b.depthTexture.format===Ra)dt(b)?d.framebufferTexture2DMultisampleEXT(n.FRAMEBUFFER,n.DEPTH_ATTACHMENT,n.TEXTURE_2D,Be,0,Je):n.framebufferTexture2D(n.FRAMEBUFFER,n.DEPTH_ATTACHMENT,n.TEXTURE_2D,Be,0);else if(b.depthTexture.format===ec)dt(b)?d.framebufferTexture2DMultisampleEXT(n.FRAMEBUFFER,n.DEPTH_STENCIL_ATTACHMENT,n.TEXTURE_2D,Be,0,Je):n.framebufferTexture2D(n.FRAMEBUFFER,n.DEPTH_STENCIL_ATTACHMENT,n.TEXTURE_2D,Be,0);else throw new Error("Unknown depthTexture format")}function Ce(F){const b=i.get(F),ue=F.isWebGLCubeRenderTarget===!0;if(F.depthTexture&&!b.__autoAllocateDepthBuffer){if(ue)throw new Error("target.depthTexture not supported in Cube render targets");Ie(b.__webglFramebuffer,F)}else if(ue){b.__webglDepthbuffer=[];for(let Be=0;Be<6;Be++)t.bindFramebuffer(n.FRAMEBUFFER,b.__webglFramebuffer[Be]),b.__webglDepthbuffer[Be]=n.createRenderbuffer(),Y(b.__webglDepthbuffer[Be],F,!1)}else t.bindFramebuffer(n.FRAMEBUFFER,b.__webglFramebuffer),b.__webglDepthbuffer=n.createRenderbuffer(),Y(b.__webglDepthbuffer,F,!1);t.bindFramebuffer(n.FRAMEBUFFER,null)}function De(F,b,ue){const Be=i.get(F);b!==void 0&&_e(Be.__webglFramebuffer,F,F.texture,n.COLOR_ATTACHMENT0,n.TEXTURE_2D,0),ue!==void 0&&Ce(F)}function xe(F){const b=F.texture,ue=i.get(F),Be=i.get(b);F.addEventListener("dispose",V),F.isWebGLMultipleRenderTargets!==!0&&(Be.__webglTexture===void 0&&(Be.__webglTexture=n.createTexture()),Be.__version=b.version,o.memory.textures++);const Je=F.isWebGLCubeRenderTarget===!0,Re=F.isWebGLMultipleRenderTargets===!0,$e=w(F)||a;if(Je){ue.__webglFramebuffer=[];for(let Qe=0;Qe<6;Qe++)if(a&&b.mipmaps&&b.mipmaps.length>0){ue.__webglFramebuffer[Qe]=[];for(let Ge=0;Ge<b.mipmaps.length;Ge++)ue.__webglFramebuffer[Qe][Ge]=n.createFramebuffer()}else ue.__webglFramebuffer[Qe]=n.createFramebuffer()}else{if(a&&b.mipmaps&&b.mipmaps.length>0){ue.__webglFramebuffer=[];for(let 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kt=s.convert(At.format,At.colorSpace),Le=s.convert(At.type),Dt=R(At.internalFormat,kt,Le,At.colorSpace,F.isXRRenderTarget===!0),$=je(F);n.renderbufferStorageMultisample(n.RENDERBUFFER,$,Dt,F.width,F.height),n.framebufferRenderbuffer(n.FRAMEBUFFER,n.COLOR_ATTACHMENT0+Ge,n.RENDERBUFFER,ue.__webglColorRenderbuffer[Ge])}n.bindRenderbuffer(n.RENDERBUFFER,null),F.depthBuffer&&(ue.__webglDepthRenderbuffer=n.createRenderbuffer(),Y(ue.__webglDepthRenderbuffer,F,!0)),t.bindFramebuffer(n.FRAMEBUFFER,null)}}if(Je){t.bindTexture(n.TEXTURE_CUBE_MAP,Be.__webglTexture),Fe(n.TEXTURE_CUBE_MAP,b,$e);for(let Qe=0;Qe<6;Qe++)if(a&&b.mipmaps&&b.mipmaps.length>0)for(let Ge=0;Ge<b.mipmaps.length;Ge++)_e(ue.__webglFramebuffer[Qe][Ge],F,b,n.COLOR_ATTACHMENT0,n.TEXTURE_CUBE_MAP_POSITIVE_X+Qe,Ge);else _e(ue.__webglFramebuffer[Qe],F,b,n.COLOR_ATTACHMENT0,n.TEXTURE_CUBE_MAP_POSITIVE_X+Qe,0);k(b,$e)&&I(n.TEXTURE_CUBE_MAP),t.unbindTexture()}else if(Re){const Qe=F.texture;for(let Ge=0,At=Qe.length;Ge<At;Ge++){const kt=Qe[Ge],Le=i.get(kt);t.bindTexture(n.TEXTURE_2D,Le.__webglTexture),Fe(n.TEXTURE_2D,kt,$e),_e(ue.__webglFramebuffer,F,kt,n.COLOR_ATTACHMENT0+Ge,n.TEXTURE_2D,0),k(kt,$e)&&I(n.TEXTURE_2D)}t.unbindTexture()}else{let Qe=n.TEXTURE_2D;if((F.isWebGL3DRenderTarget||F.isWebGLArrayRenderTarget)&&a&&(Qe=F.isWebGL3DRenderTarget?n.TEXTURE_3D:n.TEXTURE_2D_ARRAY),t.bindTexture(Qe,Be.__webglTexture),Fe(Qe,b,$e),a&&b.mipmaps&&b.mipmaps.length>0)for(let Ge=0;Ge<b.mipmaps.length;Ge++)_e(ue.__webglFramebuffer[Ge],F,b,n.COLOR_ATTACHMENT0,Qe,Ge);else _e(ue.__webglFramebuffer,F,b,n.COLOR_ATTACHMENT0,Qe,0);k(b,$e)&&I(Qe),t.unbindTexture()}F.depthBuffer&&Ce(F)}function ct(F){const b=w(F)||a,ue=F.isWebGLMultipleRenderTargets===!0?F.texture:[F.texture];for(let Be=0,Je=ue.length;Be<Je;Be++){const Re=ue[Be];if(k(Re,b)){const $e=F.isWebGLCubeRenderTarget?n.TEXTURE_CUBE_MAP:n.TEXTURE_2D,Qe=i.get(Re).__webglTexture;t.bindTexture($e,Qe),I($e),t.unbindTexture()}}}function Ye(F){if(a&&F.samples>0&&dt(F)===!1){const b=F.isWebGLMultipleRenderTargets?F.texture:[F.texture],ue=F.width,Be=F.height;let Je=n.COLOR_BUFFER_BIT;const Re=[],$e=F.stencilBuffer?n.DEPTH_STENCIL_ATTACHMENT:n.DEPTH_ATTACHMENT,Qe=i.get(F),Ge=F.isWebGLMultipleRenderTargets===!0;if(Ge)for(let At=0;At<b.length;At++)t.bindFramebuffer(n.FRAMEBUFFER,Qe.__webglMultisampledFramebuffer),n.framebufferRenderbuffer(n.FRAMEBUFFER,n.COLOR_ATTACHMENT0+At,n.RENDERBUFFER,null),t.bindFramebuffer(n.FRAMEBUFFER,Qe.__webglFramebuffer),n.framebufferTexture2D(n.DRAW_FRAMEBUFFER,n.COLOR_ATTACHMENT0+At,n.TEXTURE_2D,null,0);t.bindFramebuffer(n.READ_FRAMEBUFFER,Qe.__webglMultisampledFramebuffer),t.bindFramebuffer(n.DRAW_FRAMEBUFFER,Qe.__webglFramebuffer);for(let At=0;At<b.length;At++){Re.push(n.COLOR_ATTACHMENT0+At),F.depthBuffer&&Re.push($e);const kt=Qe.__ignoreDepthValues!==void 0?Qe.__ignoreDepthValues:!1;if(kt===!1&&(F.depthBuffer&&(Je|=n.DEPTH_BUFFER_BIT),F.stencilBuffer&&(Je|=n.STENCIL_BUFFER_BIT)),Ge&&n.framebufferRenderbuffer(n.READ_FRAMEBUFFER,n.COLOR_ATTACHMENT0,n.RENDERBUFFER,Qe.__webglColorRenderbuffer[At]),kt===!0&&(n.invalidateFramebuffer(n.READ_FRAMEBUFFER,[$e]),n.invalidateFramebuffer(n.DRAW_FRAMEBUFFER,[$e])),Ge){const Le=i.get(b[At]).__webglTexture;n.framebufferTexture2D(n.DRAW_FRAMEBUFFER,n.COLOR_ATTACHMENT0,n.TEXTURE_2D,Le,0)}n.blitFramebuffer(0,0,ue,Be,0,0,ue,Be,Je,n.NEAREST),m&&n.invalidateFramebuffer(n.READ_FRAMEBUFFER,Re)}if(t.bindFramebuffer(n.READ_FRAMEBUFFER,null),t.bindFramebuffer(n.DRAW_FRAMEBUFFER,null),Ge)for(let At=0;At<b.length;At++){t.bindFramebuffer(n.FRAMEBUFFER,Qe.__webglMultisampledFramebuffer),n.framebufferRenderbuffer(n.FRAMEBUFFER,n.COLOR_ATTACHMENT0+At,n.RENDERBUFFER,Qe.__webglColorRenderbuffer[At]);const kt=i.get(b[At]).__webglTexture;t.bindFramebuffer(n.FRAMEBUFFER,Qe.__webglFramebuffer),n.framebufferTexture2D(n.DRAW_FRAMEBUFFER,n.COLOR_ATTACHMENT0+At,n.TEXTURE_2D,kt,0)}t.bindFramebuffer(n.DRAW_FRAMEBUFFER,Qe.__webglMultisampledFramebuffer)}}function je(F){return Math.min(f,F.samples)}function dt(F){const b=i.get(F);return a&&F.samples>0&&e.has("WEBGL_multisampled_render_to_texture")===!0&&b.__useRenderToTexture!==!1}function vt(F){const b=o.render.frame;g.get(F)!==b&&(g.set(F,b),F.update())}function _t(F,b){const ue=F.colorSpace,Be=F.format,Je=F.type;return F.isCompressedTexture===!0||F.isVideoTexture===!0||F.format===gg||ue!==so&&ue!==Tr&&an.getTransfer(ue)===gn&&a===!1&&(e.has("EXT_sRGB")===!0&&Be===bi?(F.format=gg,F.minFilter=pn,F.generateMipmaps=!1):b=nw.sRGBToLinear(b)),b}this.allocateTextureUnit=H,this.resetTextureUnits=oe,this.setTexture2D=te,this.setTexture2DArray=ae,this.setTexture3D=fe,this.setTextureCube=ce,this.rebindTextures=De,this.setupRenderTarget=xe,this.updateRenderTargetMipmap=ct,this.updateMultisampleRenderTarget=Ye,this.setupDepthRenderbuffer=Ce,this.setupFrameBufferTexture=_e,this.useMultisampledRTT=dt}function gR(n,e,t){const i=t.isWebGL2;function r(s,o=Tr){let a;const l=an.getTransfer(o);if(s===$s)return n.UNSIGNED_BYTE;if(s===zU)return n.UNSIGNED_SHORT_4_4_4_4;if(s===GU)return n.UNSIGNED_SHORT_5_5_5_1;if(s===OK)return n.BYTE;if(s===FK)return n.SHORT;if(s===eA)return n.UNSIGNED_SHORT;if(s===HU)return n.INT;if(s===Do)return n.UNSIGNED_INT;if(s===Ei)return n.FLOAT;if(s===ji)return i?n.HALF_FLOAT:(a=e.get("OES_texture_half_float"),a!==null?a.HALF_FLOAT_OES:null);if(s===PK)return n.ALPHA;if(s===bi)return n.RGBA;if(s===NK)return n.LUMINANCE;if(s===QK)return n.LUMINANCE_ALPHA;if(s===Ra)return n.DEPTH_COMPONENT;if(s===ec)return n.DEPTH_STENCIL;if(s===gg)return a=e.get("EXT_sRGB"),a!==null?a.SRGB_ALPHA_EXT:null;if(s===VU)return n.RED;if(s===qU)return n.RED_INTEGER;if(s===WK)return n.RG;if(s===YU)return n.RG_INTEGER;if(s===ZU)return n.RGBA_INTEGER;if(s===RS||s===DS||s===bS||s===OS)if(l===gn)if(a=e.get("WEBGL_compressed_texture_s3tc_srgb"),a!==null){if(s===RS)return a.COMPRESSED_SRGB_S3TC_DXT1_EXT;if(s===DS)return a.COMPRESSED_SRGB_ALPHA_S3TC_DXT1_EXT;if(s===bS)return a.COMPRESSED_SRGB_ALPHA_S3TC_DXT3_EXT;if(s===OS)return a.COMPRESSED_SRGB_ALPHA_S3TC_DXT5_EXT}else return null;else if(a=e.get("WEBGL_compressed_texture_s3tc"),a!==null){if(s===RS)return a.COMPRESSED_RGB_S3TC_DXT1_EXT;if(s===DS)return a.COMPRESSED_RGBA_S3TC_DXT1_EXT;if(s===bS)return a.COMPRESSED_RGBA_S3TC_DXT3_EXT;if(s===OS)return a.COMPRESSED_RGBA_S3TC_DXT5_EXT}else return null;if(s===IC||s===LC||s===BC||s===KC)if(a=e.get("WEBGL_compressed_texture_pvrtc"),a!==null){if(s===IC)return a.COMPRESSED_RGB_PVRTC_4BPPV1_IMG;if(s===LC)return a.COMPRESSED_RGB_PVRTC_2BPPV1_IMG;if(s===BC)return a.COMPRESSED_RGBA_PVRTC_4BPPV1_IMG;if(s===KC)return a.COMPRESSED_RGBA_PVRTC_2BPPV1_IMG}else return null;if(s===jU)return a=e.get("WEBGL_compressed_texture_etc1"),a!==null?a.COMPRESSED_RGB_ETC1_WEBGL:null;if(s===RC||s===DC)if(a=e.get("WEBGL_compressed_texture_etc"),a!==null){if(s===RC)return l===gn?a.COMPRESSED_SRGB8_ETC2:a.COMPRESSED_RGB8_ETC2;if(s===DC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ETC2_EAC:a.COMPRESSED_RGBA8_ETC2_EAC}else return null;if(s===bC||s===OC||s===FC||s===PC||s===NC||s===QC||s===WC||s===HC||s===zC||s===GC||s===VC||s===qC||s===YC||s===ZC)if(a=e.get("WEBGL_compressed_texture_astc"),a!==null){if(s===bC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_4x4_KHR:a.COMPRESSED_RGBA_ASTC_4x4_KHR;if(s===OC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_5x4_KHR:a.COMPRESSED_RGBA_ASTC_5x4_KHR;if(s===FC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_5x5_KHR:a.COMPRESSED_RGBA_ASTC_5x5_KHR;if(s===PC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_6x5_KHR:a.COMPRESSED_RGBA_ASTC_6x5_KHR;if(s===NC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_6x6_KHR:a.COMPRESSED_RGBA_ASTC_6x6_KHR;if(s===QC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_8x5_KHR:a.COMPRESSED_RGBA_ASTC_8x5_KHR;if(s===WC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_8x6_KHR:a.COMPRESSED_RGBA_ASTC_8x6_KHR;if(s===HC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_8x8_KHR:a.COMPRESSED_RGBA_ASTC_8x8_KHR;if(s===zC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_10x5_KHR:a.COMPRESSED_RGBA_ASTC_10x5_KHR;if(s===GC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_10x6_KHR:a.COMPRESSED_RGBA_ASTC_10x6_KHR;if(s===VC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_10x8_KHR:a.COMPRESSED_RGBA_ASTC_10x8_KHR;if(s===qC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_10x10_KHR:a.COMPRESSED_RGBA_ASTC_10x10_KHR;if(s===YC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_12x10_KHR:a.COMPRESSED_RGBA_ASTC_12x10_KHR;if(s===ZC)return l===gn?a.COMPRESSED_SRGB8_ALPHA8_ASTC_12x12_KHR:a.COMPRESSED_RGBA_ASTC_12x12_KHR}else return null;if(s===FS||s===jC||s===XC)if(a=e.get("EXT_texture_compression_bptc"),a!==null){if(s===FS)return l===gn?a.COMPRESSED_SRGB_ALPHA_BPTC_UNORM_EXT:a.COMPRESSED_RGBA_BPTC_UNORM_EXT;if(s===jC)return a.COMPRESSED_RGB_BPTC_SIGNED_FLOAT_EXT;if(s===XC)return a.COMPRESSED_RGB_BPTC_UNSIGNED_FLOAT_EXT}else return null;if(s===HK||s===_C||s===$C||s===ev)if(a=e.get("EXT_texture_compression_rgtc"),a!==null){if(s===FS)return a.COMPRESSED_RED_RGTC1_EXT;if(s===_C)return a.COMPRESSED_SIGNED_RED_RGTC1_EXT;if(s===$C)return a.COMPRESSED_RED_GREEN_RGTC2_EXT;if(s===ev)return a.COMPRESSED_SIGNED_RED_GREEN_RGTC2_EXT}else return null;return s===Ka?i?n.UNSIGNED_INT_24_8:(a=e.get("WEBGL_depth_texture"),a!==null?a.UNSIGNED_INT_24_8_WEBGL:null):n[s]!==void 0?n[s]:null}return{convert:r}}class AR extends xn{constructor(e=[]){super(),this.isArrayCamera=!0,this.cameras=e}}class Ms extends Wt{constructor(){super(),this.isGroup=!0,this.type="Group"}}const JG={type:"move"};class D0{constructor(){this._targetRay=null,this._grip=null,this._hand=null}getHandSpace(){return this._hand===null&&(this._hand=new Ms,this._hand.matrixAutoUpdate=!1,this._hand.visible=!1,this._hand.joints={},this._hand.inputState={pinching:!1}),this._hand}getTargetRaySpace(){return this._targetRay===null&&(this._targetRay=new Ms,this._targetRay.matrixAutoUpdate=!1,this._targetRay.visible=!1,this._targetRay.hasLinearVelocity=!1,this._targetRay.linearVelocity=new N,this._targetRay.hasAngularVelocity=!1,this._targetRay.angularVelocity=new N),this._targetRay}getGripSpace(){return this._grip===null&&(this._grip=new Ms,this._grip.matrixAutoUpdate=!1,this._grip.visible=!1,this._grip.hasLinearVelocity=!1,this._grip.linearVelocity=new N,this._grip.hasAngularVelocity=!1,this._grip.angularVelocity=new N),this._grip}dispatchEvent(e){return this._targetRay!==null&&this._targetRay.dispatchEvent(e),this._grip!==null&&this._grip.dispatchEvent(e),this._hand!==null&&this._hand.dispatchEvent(e),this}connect(e){if(e&&e.hand){const t=this._hand;if(t)for(const i of e.hand.values())this._getHandJoint(t,i)}return this.dispatchEvent({type:"connected",data:e}),this}disconnect(e){return this.dispatchEvent({type:"disconnected",data:e}),this._targetRay!==null&&(this._targetRay.visible=!1),this._grip!==null&&(this._grip.visible=!1),this._hand!==null&&(this._hand.visible=!1),this}update(e,t,i){let r=null,s=null,o=null;const a=this._targetRay,l=this._grip,c=this._hand;if(e&&t.session.visibilityState!=="visible-blurred"){if(c&&e.hand){o=!0;for(const E of e.hand.values()){const C=t.getJointPose(E,i),S=this._getHandJoint(c,E);C!==null&&(S.matrix.fromArray(C.transform.matrix),S.matrix.decompose(S.position,S.rotation,S.scale),S.matrixWorldNeedsUpdate=!0,S.jointRadius=C.radius),S.visible=C!==null}const h=c.joints["index-finger-tip"],f=c.joints["thumb-tip"],d=h.position.distanceTo(f.position),m=.02,g=.005;c.inputState.pinching&&d>m+g?(c.inputState.pinching=!1,this.dispatchEvent({type:"pinchend",handedness:e.handedness,target:this})):!c.inputState.pinching&&d<=m-g&&(c.inputState.pinching=!0,this.dispatchEvent({type:"pinchstart",handedness:e.handedness,target:this}))}else l!==null&&e.gripSpace&&(s=t.getPose(e.gripSpace,i),s!==null&&(l.matrix.fromArray(s.transform.matrix),l.matrix.decompose(l.position,l.rotation,l.scale),l.matrixWorldNeedsUpdate=!0,s.linearVelocity?(l.hasLinearVelocity=!0,l.linearVelocity.copy(s.linearVelocity)):l.hasLinearVelocity=!1,s.angularVelocity?(l.hasAngularVelocity=!0,l.angularVelocity.copy(s.angularVelocity)):l.hasAngularVelocity=!1));a!==null&&(r=t.getPose(e.targetRaySpace,i),r===null&&s!==null&&(r=s),r!==null&&(a.matrix.fromArray(r.transform.matrix),a.matrix.decompose(a.position,a.rotation,a.scale),a.matrixWorldNeedsUpdate=!0,r.linearVelocity?(a.hasLinearVelocity=!0,a.linearVelocity.copy(r.linearVelocity)):a.hasLinearVelocity=!1,r.angularVelocity?(a.hasAngularVelocity=!0,a.angularVelocity.copy(r.angularVelocity)):a.hasAngularVelocity=!1,this.dispatchEvent(JG)))}return a!==null&&(a.visible=r!==null),l!==null&&(l.visible=s!==null),c!==null&&(c.visible=o!==null),this}_getHandJoint(e,t){if(e.joints[t.jointName]===void 0){const i=new Ms;i.matrixAutoUpdate=!1,i.visible=!1,e.joints[t.jointName]=i,e.add(i)}return e.joints[t.jointName]}}class IG extends co{constructor(e,t){super();const i=this;let r=null,s=1,o=null,a="local-floor",l=1,c=null,h=null,f=null,d=null,m=null,g=null;const E=t.getContextAttributes();let C=null,S=null;const v=[],y=[],w=new we;let x=null;const k=new xn;k.layers.enable(1),k.viewport=new $t;const I=new xn;I.layers.enable(2),I.viewport=new $t;const R=[k,I],T=new AR;T.layers.enable(1),T.layers.enable(2);let L=null,O=null;this.cameraAutoUpdate=!0,this.enabled=!1,this.isPresenting=!1,this.getController=function(ce){let me=v[ce];return me===void 0&&(me=new D0,v[ce]=me),me.getTargetRaySpace()},this.getControllerGrip=function(ce){let me=v[ce];return me===void 0&&(me=new D0,v[ce]=me),me.getGripSpace()},this.getHand=function(ce){let me=v[ce];return me===void 0&&(me=new D0,v[ce]=me),me.getHandSpace()};function V(ce){const me=y.indexOf(ce.inputSource);if(me===-1)return;const Te=v[me];Te!==void 0&&(Te.update(ce.inputSource,ce.frame,c||o),Te.dispatchEvent({type:ce.type,data:ce.inputSource}))}function ie(){r.removeEventListener("select",V),r.removeEventListener("selectstart",V),r.removeEventListener("selectend",V),r.removeEventListener("squeeze",V),r.removeEventListener("squeezestart",V),r.removeEventListener("squeezeend",V),r.removeEventListener("end",ie),r.removeEventListener("inputsourceschange",W);for(let ce=0;ce<v.length;ce++){const me=y[ce];me!==null&&(y[ce]=null,v[ce].disconnect(me))}L=null,O=null,e.setRenderTarget(C),m=null,d=null,f=null,r=null,S=null,fe.stop(),i.isPresenting=!1,e.setPixelRatio(x),e.setSize(w.width,w.height,!1),i.dispatchEvent({type:"sessionend"})}this.setFramebufferScaleFactor=function(ce){s=ce,i.isPresenting},this.setReferenceSpaceType=function(ce){a=ce,i.isPresenting},this.getReferenceSpace=function(){return c||o},this.setReferenceSpace=function(ce){c=ce},this.getBaseLayer=function(){return d!==null?d:m},this.getBinding=function(){return 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me=null,Te=null,Me=null;E.depth&&(Me=E.stencil?t.DEPTH24_STENCIL8:t.DEPTH_COMPONENT24,me=E.stencil?ec:Ra,Te=E.stencil?Ka:Do);const Fe={colorFormat:t.RGBA8,depthFormat:Me,scaleFactor:s};f=new XRWebGLBinding(r,t),d=f.createProjectionLayer(Fe),r.updateRenderState({layers:[d]}),e.setPixelRatio(1),e.setSize(d.textureWidth,d.textureHeight,!1),S=new Is(d.textureWidth,d.textureHeight,{format:bi,type:$s,depthTexture:new aw(d.textureWidth,d.textureHeight,Te,void 0,void 0,void 0,void 0,void 0,void 0,me),stencilBuffer:E.stencil,colorSpace:e.outputColorSpace,samples:E.antialias?4:0});const rt=e.properties.get(S);rt.__ignoreDepthValues=d.ignoreDepthValues}S.isXRRenderTarget=!0,this.setFoveation(l),c=null,o=await r.requestReferenceSpace(a),fe.setContext(r),fe.start(),i.isPresenting=!0,i.dispatchEvent({type:"sessionstart"})}},this.getEnvironmentBlendMode=function(){if(r!==null)return r.environmentBlendMode};function W(ce){for(let me=0;me<ce.removed.length;me++){const 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Q=B.target;Q.removeEventListener("dispose",We),ve(Q)}function ve(B){Pe(B),Ye.remove(B)}function Pe(B){const Q=Ye.get(B).programs;Q!==void 0&&(Q.forEach(function(z){ue.releaseProgram(z)}),B.isShaderMaterial&&ue.releaseShaderCache(B))}this.renderBufferDirect=function(B,Q,z,X,q,pe){Q===null&&(Q=st);const Se=q.isMesh&&q.matrixWorld.determinant()<0,ye=D(B,Q,z,X,q);xe.setMaterial(X,Se);let Ae=z.index,nt=1;if(X.wireframe===!0){if(Ae=F.getWireframeAttribute(z),Ae===void 0)return;nt=2}const Ke=z.drawRange,Oe=z.attributes.position;let at=Ke.start*nt,gt=(Ke.start+Ke.count)*nt;pe!==null&&(at=Math.max(at,pe.start*nt),gt=Math.min(gt,(pe.start+pe.count)*nt)),Ae!==null?(at=Math.max(at,0),gt=Math.min(gt,Ae.count)):Oe!=null&&(at=Math.max(at,0),gt=Math.min(gt,Oe.count));const yt=gt-at;if(yt<0||yt===1/0)return;$.setup(q,X,ye,z,Ae);let 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pt(B,Q,z){B.transparent===!0&&B.side===es&&B.forceSinglePass===!1?(B.side=$i,B.needsUpdate=!0,Kt(B,Q,z),B.side=to,B.needsUpdate=!0,Kt(B,Q,z),B.side=es):Kt(B,Q,z)}this.compile=function(B,Q,z=null){z===null&&(z=B),C=Re.get(z),C.init(),v.push(C),z.traverseVisible(function(q){q.isLight&&q.layers.test(Q.layers)&&(C.pushLight(q),q.castShadow&&C.pushShadow(q))}),B!==z&&B.traverseVisible(function(q){q.isLight&&q.layers.test(Q.layers)&&(C.pushLight(q),q.castShadow&&C.pushShadow(q))}),C.setupLights(y._useLegacyLights);const X=new Set;return B.traverse(function(q){const pe=q.material;if(pe)if(Array.isArray(pe))for(let Se=0;Se<pe.length;Se++){const ye=pe[Se];pt(ye,z,q),X.add(ye)}else pt(pe,z,q),X.add(pe)}),v.pop(),C=null,X},this.compileAsync=function(B,Q,z=null){const X=this.compile(B,Q,z);return new Promise(q=>{function pe(){if(X.forEach(function(Se){Ye.get(Se).currentProgram.isReady()&&X.delete(Se)}),X.size===0){q(B);return}setTimeout(pe,10)}Ce.get("KHR_parallel_shader_compile")!==null?pe():setTimeout(pe,10)})};let It=null;function sn(B){It&&It(B)}function dn(){ni.stop()}function Yt(){ni.start()}const ni=new hR;ni.setAnimationLoop(sn),typeof self<"u"&&ni.setContext(self),this.setAnimationLoop=function(B){It=B,be.setAnimationLoop(B),B===null?ni.stop():ni.start()},be.addEventListener("sessionstart",dn),be.addEventListener("sessionend",Yt),this.render=function(B,Q){if(Q!==void 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0?(B.boundingSphere===null&&B.computeBoundingSphere(),ft.copy(B.boundingSphere.center)):(Se.boundingSphere===null&&Se.computeBoundingSphere(),ft.copy(Se.boundingSphere.center)),ft.applyMatrix4(B.matrixWorld).applyMatrix4(Fe)),Array.isArray(ye)){const Ae=Se.groups;for(let nt=0,Ke=Ae.length;nt<Ke;nt++){const Oe=Ae[nt],at=ye[Oe.materialIndex];at&&at.visible&&E.push(B,Se,at,z,ft.z,Oe)}}else ye.visible&&E.push(B,Se,ye,z,ft.z,null)}}const pe=B.children;for(let Se=0,ye=pe.length;Se<ye;Se++)nr(pe[Se],Q,z,X)}function bs(B,Q,z,X){const q=B.opaque,pe=B.transmissive,Se=B.transparent;C.setupLightsView(z),me===!0&&$e.setGlobalState(y.clippingPlanes,z),pe.length>0&&_a(q,pe,Q,z),X&&xe.viewport(L.copy(X)),q.length>0&&Fr(q,Q,z),pe.length>0&&Fr(pe,Q,z),Se.length>0&&Fr(Se,Q,z),xe.buffers.depth.setTest(!0),xe.buffers.depth.setMask(!0),xe.buffers.color.setMask(!0),xe.setPolygonOffset(!1)}function _a(B,Q,z,X){if((z.isScene===!0?z.overrideMaterial:null)!==null)return;const pe=De.isWebGL2;Me===null&&(Me=new Is(1,1,{generateMipmaps:!0,type:Ce.has("EXT_color_buffer_half_float")?ji:$s,minFilter:ro,samples:pe?4:0})),y.getDrawingBufferSize(rt),pe?Me.setSize(rt.x,rt.y):Me.setSize(Ag(rt.x),Ag(rt.y));const Se=y.getRenderTarget();y.setRenderTarget(Me),y.getClearColor(ie),W=y.getClearAlpha(),W<1&&y.setClearColor(16777215,.5),y.clear();const ye=y.toneMapping;y.toneMapping=_s,Fr(B,z,X),je.updateMultisampleRenderTarget(Me),je.updateRenderTargetMipmap(Me);let Ae=!1;for(let nt=0,Ke=Q.length;nt<Ke;nt++){const Oe=Q[nt],at=Oe.object,gt=Oe.geometry,yt=Oe.material,Jt=Oe.group;if(yt.side===es&&at.layers.test(X.layers)){const it=yt.side;yt.side=$i,yt.needsUpdate=!0,ir(at,z,X,gt,yt,Jt),yt.side=it,yt.needsUpdate=!0,Ae=!0}}Ae===!0&&(je.updateMultisampleRenderTarget(Me),je.updateRenderTargetMipmap(Me)),y.setRenderTarget(Se),y.setClearColor(ie,W),y.toneMapping=ye}function Fr(B,Q,z){const X=Q.isScene===!0?Q.overrideMaterial:null;for(let q=0,pe=B.length;q<pe;q++){const 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Oe=X.uniforms;return(!B.isShaderMaterial&&!B.isRawShaderMaterial||B.clipping===!0)&&(Oe.clippingPlanes=$e.uniform),Ac(B,ye),X.needsLights=ee(B),X.lightsStateVersion=Se,X.needsLights&&(Oe.ambientLightColor.value=q.state.ambient,Oe.lightProbe.value=q.state.probe,Oe.directionalLights.value=q.state.directional,Oe.directionalLightShadows.value=q.state.directionalShadow,Oe.spotLights.value=q.state.spot,Oe.spotLightShadows.value=q.state.spotShadow,Oe.rectAreaLights.value=q.state.rectArea,Oe.ltc_1.value=q.state.rectAreaLTC1,Oe.ltc_2.value=q.state.rectAreaLTC2,Oe.pointLights.value=q.state.point,Oe.pointLightShadows.value=q.state.pointShadow,Oe.hemisphereLights.value=q.state.hemi,Oe.directionalShadowMap.value=q.state.directionalShadowMap,Oe.directionalShadowMatrix.value=q.state.directionalShadowMatrix,Oe.spotShadowMap.value=q.state.spotShadowMap,Oe.spotLightMatrix.value=q.state.spotLightMatrix,Oe.spotLightMap.value=q.state.spotLightMap,Oe.pointShadowMap.value=q.state.pointShadowMap,Oe.pointShadowMatrix.value=q.state.pointShadowMatrix),X.currentProgram=Ke,X.uniformsList=null,Ke}function $a(B){if(B.uniformsList===null){const Q=B.currentProgram.getUniforms();B.uniformsList=NS.seqWithValue(Q.seq,B.uniforms)}return B.uniformsList}function Ac(B,Q){const z=Ye.get(B);z.outputColorSpace=Q.outputColorSpace,z.batching=Q.batching,z.instancing=Q.instancing,z.instancingColor=Q.instancingColor,z.skinning=Q.skinning,z.morphTargets=Q.morphTargets,z.morphNormals=Q.morphNormals,z.morphColors=Q.morphColors,z.morphTargetsCount=Q.morphTargetsCount,z.numClippingPlanes=Q.numClippingPlanes,z.numIntersection=Q.numClipIntersection,z.vertexAlphas=Q.vertexAlphas,z.vertexTangents=Q.vertexTangents,z.toneMapping=Q.toneMapping}function D(B,Q,z,X,q){Q.isScene!==!0&&(Q=st),je.resetTextureUnits();const pe=Q.fog,Se=X.isMeshStandardMaterial?Q.environment:null,ye=I===null?y.outputColorSpace:I.isXRRenderTarget===!0?I.texture.colorSpace:so,Ae=(X.isMeshStandardMaterial?vt:dt).get(X.envMap||Se),nt=X.vertexColors===!0&&!!z.attributes.color&&z.attributes.color.itemSize===4,Ke=!!z.attributes.tangent&&(!!X.normalMap||X.anisotropy>0),Oe=!!z.morphAttributes.position,at=!!z.morphAttributes.normal,gt=!!z.morphAttributes.color;let yt=_s;X.toneMapped&&(I===null||I.isXRRenderTarget===!0)&&(yt=y.toneMapping);const Jt=z.morphAttributes.position||z.morphAttributes.normal||z.morphAttributes.color,it=Jt!==void 0?Jt.length:0,Ve=Ye.get(X),Nt=C.state.lights;if(me===!0&&(Te===!0||B!==T)){const Rt=B===T&&X.id===R;$e.setState(X,B,Rt)}let Ut=!1;X.version===Ve.__version?(Ve.needsLights&&Ve.lightsStateVersion!==Nt.state.version||Ve.outputColorSpace!==ye||q.isBatchedMesh&&Ve.batching===!1||!q.isBatchedMesh&&Ve.batching===!0||q.isInstancedMesh&&Ve.instancing===!1||!q.isInstancedMesh&&Ve.instancing===!0||q.isSkinnedMesh&&Ve.skinning===!1||!q.isSkinnedMesh&&Ve.skinning===!0||q.isInstancedMesh&&Ve.instancingColor===!0&&q.instanceColor===null||q.isInstancedMesh&&Ve.instancingColor===!1&&q.instanceColor!==null||Ve.envMap!==Ae||X.fog===!0&&Ve.fog!==pe||Ve.numClippingPlanes!==void 0&&(Ve.numClippingPlanes!==$e.numPlanes||Ve.numIntersection!==$e.numIntersection)||Ve.vertexAlphas!==nt||Ve.vertexTangents!==Ke||Ve.morphTargets!==Oe||Ve.morphNormals!==at||Ve.morphColors!==gt||Ve.toneMapping!==yt||De.isWebGL2===!0&&Ve.morphTargetsCount!==it)&&(Ut=!0):(Ut=!0,Ve.__version=X.version);let Mt=Ve.currentProgram;Ut===!0&&(Mt=Kt(X,Q,q));let on=!1,Fn=!1,Un=!1;const jt=Mt.getUniforms(),Ht=Ve.uniforms;if(xe.useProgram(Mt.program)&&(on=!0,Fn=!0,Un=!0),X.id!==R&&(R=X.id,Fn=!0),on||T!==B){jt.setValue(Y,"projectionMatrix",B.projectionMatrix),jt.setValue(Y,"viewMatrix",B.matrixWorldInverse);const Rt=jt.map.cameraPosition;Rt!==void 0&&Rt.setValue(Y,ft.setFromMatrixPosition(B.matrixWorld)),De.logarithmicDepthBuffer&&jt.setValue(Y,"logDepthBufFC",2/(Math.log(B.far+1)/Math.LN2)),(X.isMeshPhongMaterial||X.isMeshToonMaterial||X.isMeshLambertMaterial||X.isMeshBasicMaterial||X.isMeshStandardMaterial||X.isShaderMaterial)&&jt.setValue(Y,"isOrthographic",B.isOrthographicCamera===!0),T!==B&&(T=B,Fn=!0,Un=!0)}if(q.isSkinnedMesh){jt.setOptional(Y,q,"bindMatrix"),jt.setOptional(Y,q,"bindMatrixInverse");const Rt=q.skeleton;Rt&&De.floatVertexTextures&&(Rt.boneTexture===null&&Rt.computeBoneTexture(),jt.setValue(Y,"boneTexture",Rt.boneTexture,je))}q.isBatchedMesh&&(jt.setOptional(Y,q,"batchingTexture"),jt.setValue(Y,"batchingTexture",q._matricesTexture,je));const Tn=z.morphAttributes;if((Tn.position!==void 0||Tn.normal!==void 0||Tn.color!==void 0&&De.isWebGL2===!0)&&At.update(q,z,Mt),(Fn||Ve.receiveShadow!==q.receiveShadow)&&(Ve.receiveShadow=q.receiveShadow,jt.setValue(Y,"receiveShadow",q.receiveShadow)),X.isMeshGouraudMaterial&&X.envMap!==null&&(Ht.envMap.value=Ae,Ht.flipEnvMap.value=Ae.isCubeTexture&&Ae.isRenderTargetTexture===!1?-1:1),Fn&&(jt.setValue(Y,"toneMappingExposure",y.toneMappingExposure),Ve.needsLights&&P(Ht,Un),pe&&X.fog===!0&&Be.refreshFogUniforms(Ht,pe),Be.refreshMaterialUniforms(Ht,X,oe,ne,Me),NS.upload(Y,$a(Ve),Ht,je)),X.isShaderMaterial&&X.uniformsNeedUpdate===!0&&(NS.upload(Y,$a(Ve),Ht,je),X.uniformsNeedUpdate=!1),X.isSpriteMaterial&&jt.setValue(Y,"center",q.center),jt.setValue(Y,"modelViewMatrix",q.modelViewMatrix),jt.setValue(Y,"normalMatrix",q.normalMatrix),jt.setValue(Y,"modelMatrix",q.matrixWorld),X.isShaderMaterial||X.isRawShaderMaterial){const Rt=X.uniformsGroups;for(let Vt=0,mn=Rt.length;Vt<mn;Vt++)if(De.isWebGL2){const Pr=Rt[Vt];de.update(Pr,Mt),de.bind(Pr,Mt)}}return Mt}function P(B,Q){B.ambientLightColor.needsUpdate=Q,B.lightProbe.needsUpdate=Q,B.directionalLights.needsUpdate=Q,B.directionalLightShadows.needsUpdate=Q,B.pointLights.needsUpdate=Q,B.pointLightShadows.needsUpdate=Q,B.spotLights.needsUpdate=Q,B.spotLightShadows.needsUpdate=Q,B.rectAreaLights.needsUpdate=Q,B.hemisphereLights.needsUpdate=Q}function ee(B){return B.isMeshLambertMaterial||B.isMeshToonMaterial||B.isMeshPhongMaterial||B.isMeshStandardMaterial||B.isShadowMaterial||B.isShaderMaterial&&B.lights===!0}this.getActiveCubeFace=function(){return x},this.getActiveMipmapLevel=function(){return k},this.getRenderTarget=function(){return I},this.setRenderTargetTextures=function(B,Q,z){Ye.get(B.texture).__webglTexture=Q,Ye.get(B.depthTexture).__webglTexture=z;const X=Ye.get(B);X.__hasExternalTextures=!0,X.__hasExternalTextures&&(X.__autoAllocateDepthBuffer=z===void 0,X.__autoAllocateDepthBuffer||Ce.has("WEBGL_multisampled_render_to_texture")===!0&&(X.__useRenderToTexture=!1))},this.setRenderTargetFramebuffer=function(B,Q){const z=Ye.get(B);z.__webglFramebuffer=Q,z.__useDefaultFramebuffer=Q===void 0},this.setRenderTarget=function(B,Q=0,z=0){I=B,x=Q,k=z;let X=!0,q=null,pe=!1,Se=!1;if(B){const Ae=Ye.get(B);Ae.__useDefaultFramebuffer!==void 0?(xe.bindFramebuffer(Y.FRAMEBUFFER,null),X=!1):Ae.__webglFramebuffer===void 0?je.setupRenderTarget(B):Ae.__hasExternalTextures&&je.rebindTextures(B,Ye.get(B.texture).__webglTexture,Ye.get(B.depthTexture).__webglTexture);const nt=B.texture;(nt.isData3DTexture||nt.isDataArrayTexture||nt.isCompressedArrayTexture)&&(Se=!0);const Ke=Ye.get(B).__webglFramebuffer;B.isWebGLCubeRenderTarget?(Array.isArray(Ke[Q])?q=Ke[Q][z]:q=Ke[Q],pe=!0):De.isWebGL2&&B.samples>0&&je.useMultisampledRTT(B)===!1?q=Ye.get(B).__webglMultisampledFramebuffer:Array.isArray(Ke)?q=Ke[z]:q=Ke,L.copy(B.viewport),O.copy(B.scissor),V=B.scissorTest}else L.copy(te).multiplyScalar(oe).floor(),O.copy(ae).multiplyScalar(oe).floor(),V=fe;if(xe.bindFramebuffer(Y.FRAMEBUFFER,q)&&De.drawBuffers&&X&&xe.drawBuffers(B,q),xe.viewport(L),xe.scissor(O),xe.setScissorTest(V),pe){const Ae=Ye.get(B.texture);Y.framebufferTexture2D(Y.FRAMEBUFFER,Y.COLOR_ATTACHMENT0,Y.TEXTURE_CUBE_MAP_POSITIVE_X+Q,Ae.__webglTexture,z)}else if(Se){const Ae=Ye.get(B.texture),nt=Q||0;Y.framebufferTextureLayer(Y.FRAMEBUFFER,Y.COLOR_ATTACHMENT0,Ae.__webglTexture,z||0,nt)}R=-1},this.readRenderTargetPixels=function(B,Q,z,X,q,pe,Se){if(!(B&&B.isWebGLRenderTarget))return;let ye=Ye.get(B).__webglFramebuffer;if(B.isWebGLCubeRenderTarget&&Se!==void 0&&(ye=ye[Se]),ye){xe.bindFramebuffer(Y.FRAMEBUFFER,ye);try{const Ae=B.texture,nt=Ae.format,Ke=Ae.type;if(nt!==bi&&Dt.convert(nt)!==Y.getParameter(Y.IMPLEMENTATION_COLOR_READ_FORMAT))return;const Oe=Ke===ji&&(Ce.has("EXT_color_buffer_half_float")||De.isWebGL2&&Ce.has("EXT_color_buffer_float"));if(Ke!==$s&&Dt.convert(Ke)!==Y.getParameter(Y.IMPLEMENTATION_COLOR_READ_TYPE)&&!(Ke===Ei&&(De.isWebGL2||Ce.has("OES_texture_float")||Ce.has("WEBGL_color_buffer_float")))&&!Oe)return;Q>=0&&Q<=B.width-X&&z>=0&&z<=B.height-q&&Y.readPixels(Q,z,X,q,Dt.convert(nt),Dt.convert(Ke),pe)}finally{const Ae=I!==null?Ye.get(I).__webglFramebuffer:null;xe.bindFramebuffer(Y.FRAMEBUFFER,Ae)}}},this.copyFramebufferToTexture=function(B,Q,z=0){const X=Math.pow(2,-z),q=Math.floor(Q.image.width*X),pe=Math.floor(Q.image.height*X);je.setTexture2D(Q,0),Y.copyTexSubImage2D(Y.TEXTURE_2D,z,0,0,B.x,B.y,q,pe),xe.unbindTexture()},this.copyTextureToTexture=function(B,Q,z,X=0){const q=Q.image.width,pe=Q.image.height,Se=Dt.convert(z.format),ye=Dt.convert(z.type);je.setTexture2D(z,0),Y.pixelStorei(Y.UNPACK_FLIP_Y_WEBGL,z.flipY),Y.pixelStorei(Y.UNPACK_PREMULTIPLY_ALPHA_WEBGL,z.premultiplyAlpha),Y.pixelStorei(Y.UNPACK_ALIGNMENT,z.unpackAlignment),Q.isDataTexture?Y.texSubImage2D(Y.TEXTURE_2D,X,B.x,B.y,q,pe,Se,ye,Q.image.data):Q.isCompressedTexture?Y.compressedTexSubImage2D(Y.TEXTURE_2D,X,B.x,B.y,Q.mipmaps[0].width,Q.mipmaps[0].height,Se,Q.mipmaps[0].data):Y.texSubImage2D(Y.TEXTURE_2D,X,B.x,B.y,Se,ye,Q.image),X===0&&z.generateMipmaps&&Y.generateMipmap(Y.TEXTURE_2D),xe.unbindTexture()},this.copyTextureToTexture3D=function(B,Q,z,X,q=0){if(y.isWebGL1Renderer)return;const pe=B.max.x-B.min.x+1,Se=B.max.y-B.min.y+1,ye=B.max.z-B.min.z+1,Ae=Dt.convert(X.format),nt=Dt.convert(X.type);let Ke;if(X.isData3DTexture)je.setTexture3D(X,0),Ke=Y.TEXTURE_3D;else if(X.isDataArrayTexture)je.setTexture2DArray(X,0),Ke=Y.TEXTURE_2D_ARRAY;else return;Y.pixelStorei(Y.UNPACK_FLIP_Y_WEBGL,X.flipY),Y.pixelStorei(Y.UNPACK_PREMULTIPLY_ALPHA_WEBGL,X.premultiplyAlpha),Y.pixelStorei(Y.UNPACK_ALIGNMENT,X.unpackAlignment);const Oe=Y.getParameter(Y.UNPACK_ROW_LENGTH),at=Y.getParameter(Y.UNPACK_IMAGE_HEIGHT),gt=Y.getParameter(Y.UNPACK_SKIP_PIXELS),yt=Y.getParameter(Y.UNPACK_SKIP_ROWS),Jt=Y.getParameter(Y.UNPACK_SKIP_IMAGES),it=z.isCompressedTexture?z.mipmaps[0]:z.image;Y.pixelStorei(Y.UNPACK_ROW_LENGTH,it.width),Y.pixelStorei(Y.UNPACK_IMAGE_HEIGHT,it.height),Y.pixelStorei(Y.UNPACK_SKIP_PIXELS,B.min.x),Y.pixelStorei(Y.UNPACK_SKIP_ROWS,B.min.y),Y.pixelStorei(Y.UNPACK_SKIP_IMAGES,B.min.z),z.isDataTexture||z.isData3DTexture?Y.texSubImage3D(Ke,q,Q.x,Q.y,Q.z,pe,Se,ye,Ae,nt,it.data):z.isCompressedArrayTexture?Y.compressedTexSubImage3D(Ke,q,Q.x,Q.y,Q.z,pe,Se,ye,Ae,it.data):Y.texSubImage3D(Ke,q,Q.x,Q.y,Q.z,pe,Se,ye,Ae,nt,it),Y.pixelStorei(Y.UNPACK_ROW_LENGTH,Oe),Y.pixelStorei(Y.UNPACK_IMAGE_HEIGHT,at),Y.pixelStorei(Y.UNPACK_SKIP_PIXELS,gt),Y.pixelStorei(Y.UNPACK_SKIP_ROWS,yt),Y.pixelStorei(Y.UNPACK_SKIP_IMAGES,Jt),q===0&&X.generateMipmaps&&Y.generateMipmap(Ke),xe.unbindTexture()},this.initTexture=function(B){B.isCubeTexture?je.setTextureCube(B,0):B.isData3DTexture?je.setTexture3D(B,0):B.isDataArrayTexture||B.isCompressedArrayTexture?je.setTexture2DArray(B,0):je.setTexture2D(B,0),xe.unbindTexture()},this.resetState=function(){x=0,k=0,I=null,xe.reset(),$.reset()},typeof __THREE_DEVTOOLS__<"u"&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}get coordinateSystem(){return Us}get outputColorSpace(){return this._outputColorSpace}set outputColorSpace(e){this._outputColorSpace=e;const t=this.getContext();t.drawingBufferColorSpace=e===nA?"display-p3":"srgb",t.unpackColorSpace=an.workingColorSpace===Of?"display-p3":"srgb"}get physicallyCorrectLights(){return!this.useLegacyLights}set physicallyCorrectLights(e){this.useLegacyLights=!e}get outputEncoding(){return this.outputColorSpace===si?Da:$U}set outputEncoding(e){this.outputColorSpace=e===Da?si:so}get useLegacyLights(){return this._useLegacyLights}set useLegacyLights(e){this._useLegacyLights=e}}class yR extends uw{}yR.prototype.isWebGL1Renderer=!0;class oA{constructor(e,t=25e-5){this.isFogExp2=!0,this.name="",this.color=new ze(e),this.density=t}clone(){return new oA(this.color,this.density)}toJSON(){return{type:"FogExp2",name:this.name,color:this.color.getHex(),density:this.density}}}class aA{constructor(e,t=1,i=1e3){this.isFog=!0,this.name="",this.color=new ze(e),this.near=t,this.far=i}clone(){return new aA(this.color,this.near,this.far)}toJSON(){return{type:"Fog",name:this.name,color:this.color.getHex(),near:this.near,far:this.far}}}class mf extends Wt{constructor(){super(),this.isScene=!0,this.type="Scene",this.background=null,this.environment=null,this.fog=null,this.backgroundBlurriness=0,this.backgroundIntensity=1,this.overrideMaterial=null,typeof __THREE_DEVTOOLS__<"u"&&__THREE_DEVTOOLS__.dispatchEvent(new CustomEvent("observe",{detail:this}))}copy(e,t){return super.copy(e,t),e.background!==null&&(this.background=e.background.clone()),e.environment!==null&&(this.environment=e.environment.clone()),e.fog!==null&&(this.fog=e.fog.clone()),this.backgroundBlurriness=e.backgroundBlurriness,this.backgroundIntensity=e.backgroundIntensity,e.overrideMaterial!==null&&(this.overrideMaterial=e.overrideMaterial.clone()),this.matrixAutoUpdate=e.matrixAutoUpdate,this}toJSON(e){const t=super.toJSON(e);return this.fog!==null&&(t.object.fog=this.fog.toJSON()),this.backgroundBlurriness>0&&(t.object.backgroundBlurriness=this.backgroundBlurriness),this.backgroundIntensity!==1&&(t.object.backgroundIntensity=this.backgroundIntensity),t}}class Wf{constructor(e,t){this.isInterleavedBuffer=!0,this.array=e,this.stride=t,this.count=e!==void 0?e.length/t:0,this.usage=ff,this._updateRange={offset:0,count:-1},this.updateRanges=[],this.version=0,this.uuid=Br()}onUploadCallback(){}set needsUpdate(e){e===!0&&this.version++}get updateRange(){return this._updateRange}setUsage(e){return this.usage=e,this}addUpdateRange(e,t){this.updateRanges.push({start:e,count:t})}clearUpdateRanges(){this.updateRanges.length=0}copy(e){return this.array=new e.array.constructor(e.array),this.count=e.count,this.stride=e.stride,this.usage=e.usage,this}copyAt(e,t,i){e*=this.stride,i*=t.stride;for(let r=0,s=this.stride;r<s;r++)this.array[e+r]=t.array[i+r];return this}set(e,t=0){return this.array.set(e,t),this}clone(e){e.arrayBuffers===void 0&&(e.arrayBuffers={}),this.array.buffer._uuid===void 0&&(this.array.buffer._uuid=Br()),e.arrayBuffers[this.array.buffer._uuid]===void 0&&(e.arrayBuffers[this.array.buffer._uuid]=this.array.slice(0).buffer);const t=new this.array.constructor(e.arrayBuffers[this.array.buffer._uuid]),i=new this.constructor(t,this.stride);return i.setUsage(this.usage),i}onUpload(e){return this.onUploadCallback=e,this}toJSON(e){return e.arrayBuffers===void 0&&(e.arrayBuffers={}),this.array.buffer._uuid===void 0&&(this.array.buffer._uuid=Br()),e.arrayBuffers[this.array.buffer._uuid]===void 0&&(e.arrayBuffers[this.array.buffer._uuid]=Array.from(new Uint32Array(this.array.buffer))),{uuid:this.uuid,buffer:this.array.buffer._uuid,type:this.array.constructor.name,stride:this.stride}}}const Gi=new N;class Na{constructor(e,t,i,r=!1){this.isInterleavedBufferAttribute=!0,this.name="",this.data=e,this.itemSize=t,this.offset=i,this.normalized=r}get count(){return this.data.count}get array(){return this.data.array}set needsUpdate(e){this.data.needsUpdate=e}applyMatrix4(e){for(let t=0,i=this.data.count;t<i;t++)Gi.fromBufferAttribute(this,t),Gi.applyMatrix4(e),this.setXYZ(t,Gi.x,Gi.y,Gi.z);return this}applyNormalMatrix(e){for(let t=0,i=this.count;t<i;t++)Gi.fromBufferAttribute(this,t),Gi.applyNormalMatrix(e),this.setXYZ(t,Gi.x,Gi.y,Gi.z);return this}transformDirection(e){for(let t=0,i=this.count;t<i;t++)Gi.fromBufferAttribute(this,t),Gi.transformDirection(e),this.setXYZ(t,Gi.x,Gi.y,Gi.z);return this}setX(e,t){return this.normalized&&(t=Ft(t,this.array)),this.data.array[e*this.data.stride+this.offset]=t,this}setY(e,t){return this.normalized&&(t=Ft(t,this.array)),this.data.array[e*this.data.stride+this.offset+1]=t,this}setZ(e,t){return this.normalized&&(t=Ft(t,this.array)),this.data.array[e*this.data.stride+this.offset+2]=t,this}setW(e,t){return this.normalized&&(t=Ft(t,this.array)),this.data.array[e*this.data.stride+this.offset+3]=t,this}getX(e){let t=this.data.array[e*this.data.stride+this.offset];return this.normalized&&(t=fr(t,this.array)),t}getY(e){let t=this.data.array[e*this.data.stride+this.offset+1];return this.normalized&&(t=fr(t,this.array)),t}getZ(e){let t=this.data.array[e*this.data.stride+this.offset+2];return this.normalized&&(t=fr(t,this.array)),t}getW(e){let t=this.data.array[e*this.data.stride+this.offset+3];return this.normalized&&(t=fr(t,this.array)),t}setXY(e,t,i){return e=e*this.data.stride+this.offset,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=i,this}setXYZ(e,t,i,r){return e=e*this.data.stride+this.offset,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array),r=Ft(r,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=i,this.data.array[e+2]=r,this}setXYZW(e,t,i,r,s){return e=e*this.data.stride+this.offset,this.normalized&&(t=Ft(t,this.array),i=Ft(i,this.array),r=Ft(r,this.array),s=Ft(s,this.array)),this.data.array[e+0]=t,this.data.array[e+1]=i,this.data.array[e+2]=r,this.data.array[e+3]=s,this}clone(e){if(e===void 0){const t=[];for(let i=0;i<this.count;i++){const r=i*this.data.stride+this.offset;for(let s=0;s<this.itemSize;s++)t.push(this.data.array[r+s])}return new Xt(new this.array.constructor(t),this.itemSize,this.normalized)}else return e.interleavedBuffers===void 0&&(e.interleavedBuffers={}),e.interleavedBuffers[this.data.uuid]===void 0&&(e.interleavedBuffers[this.data.uuid]=this.data.clone(e)),new Na(e.interleavedBuffers[this.data.uuid],this.itemSize,this.offset,this.normalized)}toJSON(e){if(e===void 0){const t=[];for(let i=0;i<this.count;i++){const r=i*this.data.stride+this.offset;for(let s=0;s<this.itemSize;s++)t.push(this.data.array[r+s])}return{itemSize:this.itemSize,type:this.array.constructor.name,array:t,normalized:this.normalized}}else return e.interleavedBuffers===void 0&&(e.interleavedBuffers={}),e.interleavedBuffers[this.data.uuid]===void 0&&(e.interleavedBuffers[this.data.uuid]=this.data.toJSON(e)),{isInterleavedBufferAttribute:!0,itemSize:this.itemSize,data:this.data.uuid,offset:this.offset,normalized:this.normalized}}}class hw extends ti{constructor(e){super(),this.isSpriteMaterial=!0,this.type="SpriteMaterial",this.color=new ze(16777215),this.map=null,this.alphaMap=null,this.rotation=0,this.sizeAttenuation=!0,this.transparent=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.alphaMap=e.alphaMap,this.rotation=e.rotation,this.sizeAttenuation=e.sizeAttenuation,this.fog=e.fog,this}}let qc;const _h=new N,Yc=new N,Zc=new N,jc=new we,$h=new we,ER=new tt,Om=new N,ep=new N,Fm=new N,qT=new we,b0=new we,YT=new we;class CR extends Wt{constructor(e=new hw){if(super(),this.isSprite=!0,this.type="Sprite",qc===void 0){qc=new Tt;const t=new Float32Array([-.5,-.5,0,0,0,.5,-.5,0,1,0,.5,.5,0,1,1,-.5,.5,0,0,1]),i=new Wf(t,5);qc.setIndex([0,1,2,0,2,3]),qc.setAttribute("position",new Na(i,3,0,!1)),qc.setAttribute("uv",new Na(i,2,3,!1))}this.geometry=qc,this.material=e,this.center=new we(.5,.5)}raycast(e,t){e.camera,Yc.setFromMatrixScale(this.matrixWorld),ER.copy(e.camera.matrixWorld),this.modelViewMatrix.multiplyMatrices(e.camera.matrixWorldInverse,this.matrixWorld),Zc.setFromMatrixPosition(this.modelViewMatrix),e.camera.isPerspectiveCamera&&this.material.sizeAttenuation===!1&&Yc.multiplyScalar(-Zc.z);const i=this.material.rotation;let r,s;i!==0&&(s=Math.cos(i),r=Math.sin(i));const o=this.center;Pm(Om.set(-.5,-.5,0),Zc,o,Yc,r,s),Pm(ep.set(.5,-.5,0),Zc,o,Yc,r,s),Pm(Fm.set(.5,.5,0),Zc,o,Yc,r,s),qT.set(0,0),b0.set(1,0),YT.set(1,1);let a=e.ray.intersectTriangle(Om,ep,Fm,!1,_h);if(a===null&&(Pm(ep.set(-.5,.5,0),Zc,o,Yc,r,s),b0.set(0,1),a=e.ray.intersectTriangle(Om,Fm,ep,!1,_h),a===null))return;const l=e.ray.origin.distanceTo(_h);l<e.near||l>e.far||t.push({distance:l,point:_h.clone(),uv:pr.getInterpolation(_h,Om,ep,Fm,qT,b0,YT,new we),face:null,object:this})}copy(e,t){return super.copy(e,t),e.center!==void 0&&this.center.copy(e.center),this.material=e.material,this}}function Pm(n,e,t,i,r,s){jc.subVectors(n,t).addScalar(.5).multiply(i),r!==void 0?($h.x=s*jc.x-r*jc.y,$h.y=r*jc.x+s*jc.y):$h.copy(jc),n.copy(e),n.x+=$h.x,n.y+=$h.y,n.applyMatrix4(ER)}const Nm=new N,ZT=new N;class vR extends Wt{constructor(){super(),this._currentLevel=0,this.type="LOD",Object.defineProperties(this,{levels:{enumerable:!0,value:[]},isLOD:{value:!0}}),this.autoUpdate=!0}copy(e){super.copy(e,!1);const t=e.levels;for(let i=0,r=t.length;i<r;i++){const s=t[i];this.addLevel(s.object.clone(),s.distance,s.hysteresis)}return this.autoUpdate=e.autoUpdate,this}addLevel(e,t=0,i=0){t=Math.abs(t);const r=this.levels;let s;for(s=0;s<r.length&&!(t<r[s].distance);s++);return r.splice(s,0,{distance:t,hysteresis:i,object:e}),this.add(e),this}getCurrentLevel(){return this._currentLevel}getObjectForDistance(e){const t=this.levels;if(t.length>0){let i,r;for(i=1,r=t.length;i<r;i++){let s=t[i].distance;if(t[i].object.visible&&(s-=s*t[i].hysteresis),e<s)break}return t[i-1].object}return null}raycast(e,t){if(this.levels.length>0){Nm.setFromMatrixPosition(this.matrixWorld);const r=e.ray.origin.distanceTo(Nm);this.getObjectForDistance(r).raycast(e,t)}}update(e){const t=this.levels;if(t.length>1){Nm.setFromMatrixPosition(e.matrixWorld),ZT.setFromMatrixPosition(this.matrixWorld);const i=Nm.distanceTo(ZT)/e.zoom;t[0].object.visible=!0;let r,s;for(r=1,s=t.length;r<s;r++){let o=t[r].distance;if(t[r].object.visible&&(o-=o*t[r].hysteresis),i>=o)t[r-1].object.visible=!1,t[r].object.visible=!0;else break}for(this._currentLevel=r-1;r<s;r++)t[r].object.visible=!1}}toJSON(e){const t=super.toJSON(e);this.autoUpdate===!1&&(t.object.autoUpdate=!1),t.object.levels=[];const i=this.levels;for(let r=0,s=i.length;r<s;r++){const o=i[r];t.object.levels.push({object:o.object.uuid,distance:o.distance,hysteresis:o.hysteresis})}return t}}const jT=new N,XT=new $t,_T=new $t,KG=new N,$T=new tt,Qm=new N,O0=new vi,e1=new tt,F0=new pc;class lA extends Gn{constructor(e,t){super(e,t),this.isSkinnedMesh=!0,this.type="SkinnedMesh",this.bindMode=JC,this.bindMatrix=new tt,this.bindMatrixInverse=new tt,this.boundingBox=null,this.boundingSphere=null}computeBoundingBox(){const e=this.geometry;this.boundingBox===null&&(this.boundingBox=new Pi),this.boundingBox.makeEmpty();const t=e.getAttribute("position");for(let i=0;i<t.count;i++)this.getVertexPosition(i,Qm),this.boundingBox.expandByPoint(Qm)}computeBoundingSphere(){const e=this.geometry;this.boundingSphere===null&&(this.boundingSphere=new vi),this.boundingSphere.makeEmpty();const t=e.getAttribute("position");for(let i=0;i<t.count;i++)this.getVertexPosition(i,Qm),this.boundingSphere.expandByPoint(Qm)}copy(e,t){return super.copy(e,t),this.bindMode=e.bindMode,this.bindMatrix.copy(e.bindMatrix),this.bindMatrixInverse.copy(e.bindMatrixInverse),this.skeleton=e.skeleton,e.boundingBox!==null&&(this.boundingBox=e.boundingBox.clone()),e.boundingSphere!==null&&(this.boundingSphere=e.boundingSphere.clone()),this}raycast(e,t){const i=this.material,r=this.matrixWorld;i!==void 0&&(this.boundingSphere===null&&this.computeBoundingSphere(),O0.copy(this.boundingSphere),O0.applyMatrix4(r),e.ray.intersectsSphere(O0)!==!1&&(e1.copy(r).invert(),F0.copy(e.ray).applyMatrix4(e1),!(this.boundingBox!==null&&F0.intersectsBox(this.boundingBox)===!1)&&this._computeIntersections(e,t,F0)))}getVertexPosition(e,t){return super.getVertexPosition(e,t),this.applyBoneTransform(e,t),t}bind(e,t){this.skeleton=e,t===void 0&&(this.updateMatrixWorld(!0),this.skeleton.calculateInverses(),t=this.matrixWorld),this.bindMatrix.copy(t),this.bindMatrixInverse.copy(t).invert()}pose(){this.skeleton.pose()}normalizeSkinWeights(){const e=new $t,t=this.geometry.attributes.skinWeight;for(let i=0,r=t.count;i<r;i++){e.fromBufferAttribute(t,i);const s=1/e.manhattanLength();s!==1/0?e.multiplyScalar(s):e.set(1,0,0,0),t.setXYZW(i,e.x,e.y,e.z,e.w)}}updateMatrixWorld(e){super.updateMatrixWorld(e),this.bindMode===JC?this.bindMatrixInverse.copy(this.matrixWorld).invert():this.bindMode===bK&&this.bindMatrixInverse.copy(this.bindMatrix).invert()}applyBoneTransform(e,t){const i=this.skeleton,r=this.geometry;XT.fromBufferAttribute(r.attributes.skinIndex,e),_T.fromBufferAttribute(r.attributes.skinWeight,e),jT.copy(t).applyMatrix4(this.bindMatrix),t.set(0,0,0);for(let s=0;s<4;s++){const o=_T.getComponent(s);if(o!==0){const a=XT.getComponent(s);$T.multiplyMatrices(i.bones[a].matrixWorld,i.boneInverses[a]),t.addScaledVector(KG.copy(jT).applyMatrix4($T),o)}}return t.applyMatrix4(this.bindMatrixInverse)}boneTransform(e,t){return this.applyBoneTransform(e,t)}}class ju extends Wt{constructor(){super(),this.isBone=!0,this.type="Bone"}}class zl extends fn{constructor(e=null,t=1,i=1,r,s,o,a,l,c=Wn,h=Wn,f,d){super(null,o,a,l,c,h,r,s,f,d),this.isDataTexture=!0,this.image={data:e,width:t,height:i},this.generateMipmaps=!1,this.flipY=!1,this.unpackAlignment=1}}const t1=new tt,RG=new tt;class ch{constructor(e=[],t=[]){this.uuid=Br(),this.bones=e.slice(0),this.boneInverses=t,this.boneMatrices=null,this.boneTexture=null,this.init()}init(){const e=this.bones,t=this.boneInverses;if(this.boneMatrices=new Float32Array(e.length*16),t.length===0)this.calculateInverses();else if(e.length!==t.length){this.boneInverses=[];for(let i=0,r=this.bones.length;i<r;i++)this.boneInverses.push(new tt)}}calculateInverses(){this.boneInverses.length=0;for(let e=0,t=this.bones.length;e<t;e++){const i=new tt;this.bones[e]&&i.copy(this.bones[e].matrixWorld).invert(),this.boneInverses.push(i)}}pose(){for(let e=0,t=this.bones.length;e<t;e++){const i=this.bones[e];i&&i.matrixWorld.copy(this.boneInverses[e]).invert()}for(let e=0,t=this.bones.length;e<t;e++){const i=this.bones[e];i&&(i.parent&&i.parent.isBone?(i.matrix.copy(i.parent.matrixWorld).invert(),i.matrix.multiply(i.matrixWorld)):i.matrix.copy(i.matrixWorld),i.matrix.decompose(i.position,i.quaternion,i.scale))}}update(){const e=this.bones,t=this.boneInverses,i=this.boneMatrices,r=this.boneTexture;for(let s=0,o=e.length;s<o;s++){const a=e[s]?e[s].matrixWorld:RG;t1.multiplyMatrices(a,t[s]),t1.toArray(i,s*16)}r!==null&&(r.needsUpdate=!0)}clone(){return new ch(this.bones,this.boneInverses)}computeBoneTexture(){let e=Math.sqrt(this.bones.length*4);e=Math.ceil(e/4)*4,e=Math.max(e,4);const t=new Float32Array(e*e*4);t.set(this.boneMatrices);const i=new zl(t,e,e,bi,Ei);return i.needsUpdate=!0,this.boneMatrices=t,this.boneTexture=i,this}getBoneByName(e){for(let t=0,i=this.bones.length;t<i;t++){const r=this.bones[t];if(r.name===e)return r}}dispose(){this.boneTexture!==null&&(this.boneTexture.dispose(),this.boneTexture=null)}fromJSON(e,t){this.uuid=e.uuid;for(let i=0,r=e.bones.length;i<r;i++){const s=e.bones[i];let o=t[s];o===void 0&&(o=new ju),this.bones.push(o),this.boneInverses.push(new tt().fromArray(e.boneInverses[i]))}return this.init(),this}toJSON(){const e={metadata:{version:4.6,type:"Skeleton",generator:"Skeleton.toJSON"},bones:[],boneInverses:[]};e.uuid=this.uuid;const t=this.bones,i=this.boneInverses;for(let r=0,s=t.length;r<s;r++){const o=t[r];e.bones.push(o.uuid);const a=i[r];e.boneInverses.push(a.toArray())}return e}}class Xu extends Xt{constructor(e,t,i,r=1){super(e,t,i),this.isInstancedBufferAttribute=!0,this.meshPerAttribute=r}copy(e){return super.copy(e),this.meshPerAttribute=e.meshPerAttribute,this}toJSON(){const e=super.toJSON();return e.meshPerAttribute=this.meshPerAttribute,e.isInstancedBufferAttribute=!0,e}}const Xc=new tt,n1=new tt,Wm=[],i1=new Pi,DG=new tt,tp=new Gn,np=new vi;class pw extends Gn{constructor(e,t,i){super(e,t),this.isInstancedMesh=!0,this.instanceMatrix=new Xu(new Float32Array(i*16),16),this.instanceColor=null,this.count=i,this.boundingBox=null,this.boundingSphere=null;for(let r=0;r<i;r++)this.setMatrixAt(r,DG)}computeBoundingBox(){const e=this.geometry,t=this.count;this.boundingBox===null&&(this.boundingBox=new Pi),e.boundingBox===null&&e.computeBoundingBox(),this.boundingBox.makeEmpty();for(let i=0;i<t;i++)this.getMatrixAt(i,Xc),i1.copy(e.boundingBox).applyMatrix4(Xc),this.boundingBox.union(i1)}computeBoundingSphere(){const e=this.geometry,t=this.count;this.boundingSphere===null&&(this.boundingSphere=new vi),e.boundingSphere===null&&e.computeBoundingSphere(),this.boundingSphere.makeEmpty();for(let i=0;i<t;i++)this.getMatrixAt(i,Xc),np.copy(e.boundingSphere).applyMatrix4(Xc),this.boundingSphere.union(np)}copy(e,t){return super.copy(e,t),this.instanceMatrix.copy(e.instanceMatrix),e.instanceColor!==null&&(this.instanceColor=e.instanceColor.clone()),this.count=e.count,e.boundingBox!==null&&(this.boundingBox=e.boundingBox.clone()),e.boundingSphere!==null&&(this.boundingSphere=e.boundingSphere.clone()),this}getColorAt(e,t){t.fromArray(this.instanceColor.array,e*3)}getMatrixAt(e,t){t.fromArray(this.instanceMatrix.array,e*16)}raycast(e,t){const i=this.matrixWorld,r=this.count;if(tp.geometry=this.geometry,tp.material=this.material,tp.material!==void 0&&(this.boundingSphere===null&&this.computeBoundingSphere(),np.copy(this.boundingSphere),np.applyMatrix4(i),e.ray.intersectsSphere(np)!==!1))for(let s=0;s<r;s++){this.getMatrixAt(s,Xc),n1.multiplyMatrices(i,Xc),tp.matrixWorld=n1,tp.raycast(e,Wm);for(let o=0,a=Wm.length;o<a;o++){const l=Wm[o];l.instanceId=s,l.object=this,t.push(l)}Wm.length=0}}setColorAt(e,t){this.instanceColor===null&&(this.instanceColor=new Xu(new Float32Array(this.instanceMatrix.count*3),3)),t.toArray(this.instanceColor.array,e*3)}setMatrixAt(e,t){t.toArray(this.instanceMatrix.array,e*16)}updateMorphTargets(){}dispose(){this.dispatchEvent({type:"dispose"})}}function bG(n,e){return n.z-e.z}function OG(n,e){return e.z-n.z}class FG{constructor(){this.index=0,this.pool=[],this.list=[]}push(e,t){const i=this.pool,r=this.list;this.index>=i.length&&i.push({start:-1,count:-1,z:-1});const s=i[this.index];r.push(s),this.index++,s.start=e.start,s.count=e.count,s.z=t}reset(){this.list.length=0,this.index=0}}const _c="batchId",ha=new tt,r1=new tt,PG=new tt,s1=new tt,P0=new Nf,Hm=new Pi,fl=new vi,ip=new N,N0=new FG,Ri=new Gn,zm=[];function NG(n,e,t=0){const i=e.itemSize;if(n.isInterleavedBufferAttribute||n.array.constructor!==e.array.constructor){const r=n.count;for(let s=0;s<r;s++)for(let o=0;o<i;o++)e.setComponent(s+t,o,n.getComponent(s,o))}else e.array.set(n.array,t*i);e.needsUpdate=!0}class UR extends Gn{get maxGeometryCount(){return this._maxGeometryCount}constructor(e,t,i=t*2,r){super(new Tt,r),this.isBatchedMesh=!0,this.perObjectFrustumCulled=!0,this.sortObjects=!0,this.boundingBox=null,this.boundingSphere=null,this.customSort=null,this._drawRanges=[],this._reservedRanges=[],this._visibility=[],this._active=[],this._bounds=[],this._maxGeometryCount=e,this._maxVertexCount=t,this._maxIndexCount=i,this._geometryInitialized=!1,this._geometryCount=0,this._multiDrawCounts=new Int32Array(e),this._multiDrawStarts=new Int32Array(e),this._multiDrawCount=0,this._visibilityChanged=!0,this._matricesTexture=null,this._initMatricesTexture()}_initMatricesTexture(){let e=Math.sqrt(this._maxGeometryCount*4);e=Math.ceil(e/4)*4,e=Math.max(e,4);const t=new Float32Array(e*e*4),i=new zl(t,e,e,bi,Ei);this._matricesTexture=i}_initializeGeometry(e){const t=this.geometry,i=this._maxVertexCount,r=this._maxGeometryCount,s=this._maxIndexCount;if(this._geometryInitialized===!1){for(const a in e.attributes){const l=e.getAttribute(a),{array:c,itemSize:h,normalized:f}=l,d=new c.constructor(i*h),m=new l.constructor(d,h,f);m.setUsage(l.usage),t.setAttribute(a,m)}if(e.getIndex()!==null){const a=i>65536?new Uint32Array(s):new Uint16Array(s);t.setIndex(new Xt(a,1))}const o=r>65536?new Uint32Array(i):new Uint16Array(i);t.setAttribute(_c,new Xt(o,1)),this._geometryInitialized=!0}}_validateGeometry(e){if(e.getAttribute(_c))throw new Error(`BatchedMesh: Geometry cannot use attribute "${_c}"`);const t=this.geometry;if(!!e.getIndex()!=!!t.getIndex())throw new Error('BatchedMesh: All geometries must consistently have "index".');for(const i in t.attributes){if(i===_c)continue;if(!e.hasAttribute(i))throw new Error(`BatchedMesh: Added geometry missing "${i}". All geometries must have consistent attributes.`);const r=e.getAttribute(i),s=t.getAttribute(i);if(r.itemSize!==s.itemSize||r.normalized!==s.normalized)throw new Error("BatchedMesh: All attributes must have a consistent itemSize and normalized value.")}}setCustomSort(e){return this.customSort=e,this}computeBoundingBox(){this.boundingBox===null&&(this.boundingBox=new Pi);const e=this._geometryCount,t=this.boundingBox,i=this._active;t.makeEmpty();for(let r=0;r<e;r++)i[r]!==!1&&(this.getMatrixAt(r,ha),this.getBoundingBoxAt(r,Hm).applyMatrix4(ha),t.union(Hm))}computeBoundingSphere(){this.boundingSphere===null&&(this.boundingSphere=new vi);const e=this._geometryCount,t=this.boundingSphere,i=this._active;t.makeEmpty();for(let r=0;r<e;r++)i[r]!==!1&&(this.getMatrixAt(r,ha),this.getBoundingSphereAt(r,fl).applyMatrix4(ha),t.union(fl))}addGeometry(e,t=-1,i=-1){if(this._initializeGeometry(e),this._validateGeometry(e),this._geometryCount>=this._maxGeometryCount)throw new Error("BatchedMesh: Maximum geometry count reached.");const r={vertexStart:-1,vertexCount:-1,indexStart:-1,indexCount:-1};let s=null;const o=this._reservedRanges,a=this._drawRanges,l=this._bounds;this._geometryCount!==0&&(s=o[o.length-1]),t===-1?r.vertexCount=e.getAttribute("position").count:r.vertexCount=t,s===null?r.vertexStart=0:r.vertexStart=s.vertexStart+s.vertexCount;const c=e.getIndex(),h=c!==null;if(h&&(i===-1?r.indexCount=c.count:r.indexCount=i,s===null?r.indexStart=0:r.indexStart=s.indexStart+s.indexCount),r.indexStart!==-1&&r.indexStart+r.indexCount>this._maxIndexCount||r.vertexStart+r.vertexCount>this._maxVertexCount)throw new Error("BatchedMesh: Reserved space request exceeds the maximum buffer size.");const f=this._visibility,d=this._active,m=this._matricesTexture,g=this._matricesTexture.image.data;f.push(!0),d.push(!0);const E=this._geometryCount;this._geometryCount++,PG.toArray(g,E*16),m.needsUpdate=!0,o.push(r),a.push({start:h?r.indexStart:r.vertexStart,count:-1}),l.push({boxInitialized:!1,box:new Pi,sphereInitialized:!1,sphere:new vi});const C=this.geometry.getAttribute(_c);for(let S=0;S<r.vertexCount;S++)C.setX(r.vertexStart+S,E);return C.needsUpdate=!0,this.setGeometryAt(E,e),E}setGeometryAt(e,t){if(e>=this._geometryCount)throw new Error("BatchedMesh: Maximum geometry count reached.");this._validateGeometry(t);const i=this.geometry,r=i.getIndex()!==null,s=i.getIndex(),o=t.getIndex(),a=this._reservedRanges[e];if(r&&o.count>a.indexCount||t.attributes.position.count>a.vertexCount)throw new Error("BatchedMesh: Reserved space not large enough for provided geometry.");const l=a.vertexStart,c=a.vertexCount;for(const m in i.attributes){if(m===_c)continue;const g=t.getAttribute(m),E=i.getAttribute(m);NG(g,E,l);const C=g.itemSize;for(let S=g.count,v=c;S<v;S++){const y=l+S;for(let w=0;w<C;w++)E.setComponent(y,w,0)}E.needsUpdate=!0}if(r){const m=a.indexStart;for(let g=0;g<o.count;g++)s.setX(m+g,l+o.getX(g));for(let g=o.count,E=a.indexCount;g<E;g++)s.setX(m+g,l);s.needsUpdate=!0}const h=this._bounds[e];t.boundingBox!==null?(h.box.copy(t.boundingBox),h.boxInitialized=!0):h.boxInitialized=!1,t.boundingSphere!==null?(h.sphere.copy(t.boundingSphere),h.sphereInitialized=!0):h.sphereInitialized=!1;const f=this._drawRanges[e],d=t.getAttribute("position");return f.count=r?o.count:d.count,this._visibilityChanged=!0,e}deleteGeometry(e){const t=this._active;return e>=t.length||t[e]===!1?this:(t[e]=!1,this._visibilityChanged=!0,this)}getBoundingBoxAt(e,t){if(this._active[e]===!1)return this;const r=this._bounds[e],s=r.box,o=this.geometry;if(r.boxInitialized===!1){s.makeEmpty();const a=o.index,l=o.attributes.position,c=this._drawRanges[e];for(let h=c.start,f=c.start+c.count;h<f;h++){let d=h;a&&(d=a.getX(d)),s.expandByPoint(ip.fromBufferAttribute(l,d))}r.boxInitialized=!0}return t.copy(s),t}getBoundingSphereAt(e,t){if(this._active[e]===!1)return this;const r=this._bounds[e],s=r.sphere,o=this.geometry;if(r.sphereInitialized===!1){s.makeEmpty(),this.getBoundingBoxAt(e,Hm),Hm.getCenter(s.center);const a=o.index,l=o.attributes.position,c=this._drawRanges[e];let h=0;for(let f=c.start,d=c.start+c.count;f<d;f++){let m=f;a&&(m=a.getX(m)),ip.fromBufferAttribute(l,m),h=Math.max(h,s.center.distanceToSquared(ip))}s.radius=Math.sqrt(h),r.sphereInitialized=!0}return t.copy(s),t}setMatrixAt(e,t){const i=this._active,r=this._matricesTexture,s=this._matricesTexture.image.data,o=this._geometryCount;return e>=o||i[e]===!1?this:(t.toArray(s,e*16),r.needsUpdate=!0,this)}getMatrixAt(e,t){const i=this._active,r=this._matricesTexture.image.data,s=this._geometryCount;return e>=s||i[e]===!1?null:t.fromArray(r,e*16)}setVisibleAt(e,t){const i=this._visibility,r=this._active,s=this._geometryCount;return e>=s||r[e]===!1||i[e]===t?this:(i[e]=t,this._visibilityChanged=!0,this)}getVisibleAt(e){const t=this._visibility,i=this._active,r=this._geometryCount;return e>=r||i[e]===!1?!1:t[e]}raycast(e,t){const i=this._visibility,r=this._active,s=this._drawRanges,o=this._geometryCount,a=this.matrixWorld,l=this.geometry;Ri.material=this.material,Ri.geometry.index=l.index,Ri.geometry.attributes=l.attributes,Ri.geometry.boundingBox===null&&(Ri.geometry.boundingBox=new Pi),Ri.geometry.boundingSphere===null&&(Ri.geometry.boundingSphere=new vi);for(let c=0;c<o;c++){if(!i[c]||!r[c])continue;const h=s[c];Ri.geometry.setDrawRange(h.start,h.count),this.getMatrixAt(c,Ri.matrixWorld).premultiply(a),this.getBoundingBoxAt(c,Ri.geometry.boundingBox),this.getBoundingSphereAt(c,Ri.geometry.boundingSphere),Ri.raycast(e,zm);for(let f=0,d=zm.length;f<d;f++){const m=zm[f];m.object=this,m.batchId=c,t.push(m)}zm.length=0}Ri.material=null,Ri.geometry.index=null,Ri.geometry.attributes={},Ri.geometry.setDrawRange(0,1/0)}copy(e){return super.copy(e),this.geometry=e.geometry.clone(),this.perObjectFrustumCulled=e.perObjectFrustumCulled,this.sortObjects=e.sortObjects,this.boundingBox=e.boundingBox!==null?e.boundingBox.clone():null,this.boundingSphere=e.boundingSphere!==null?e.boundingSphere.clone():null,this._drawRanges=e._drawRanges.map(t=>({...t})),this._reservedRanges=e._reservedRanges.map(t=>({...t})),this._visibility=e._visibility.slice(),this._active=e._active.slice(),this._bounds=e._bounds.map(t=>({boxInitialized:t.boxInitialized,box:t.box.clone(),sphereInitialized:t.sphereInitialized,sphere:t.sphere.clone()})),this._maxGeometryCount=e._maxGeometryCount,this._maxVertexCount=e._maxVertexCount,this._maxIndexCount=e._maxIndexCount,this._geometryInitialized=e._geometryInitialized,this._geometryCount=e._geometryCount,this._multiDrawCounts=e._multiDrawCounts.slice(),this._multiDrawStarts=e._multiDrawStarts.slice(),this._matricesTexture=e._matricesTexture.clone(),this._matricesTexture.image.data=this._matricesTexture.image.slice(),this}dispose(){return this.geometry.dispose(),this._matricesTexture.dispose(),this._matricesTexture=null,this}onBeforeRender(e,t,i,r,s){if(!this._visibilityChanged&&!this.perObjectFrustumCulled&&!this.sortObjects)return;const o=r.getIndex(),a=o===null?1:o.array.BYTES_PER_ELEMENT,l=this._visibility,c=this._multiDrawStarts,h=this._multiDrawCounts,f=this._drawRanges,d=this.perObjectFrustumCulled;d&&(s1.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse).multiply(this.matrixWorld),P0.setFromProjectionMatrix(s1,e.isWebGPURenderer?qu:Us));let m=0;if(this.sortObjects){r1.copy(this.matrixWorld).invert(),ip.setFromMatrixPosition(i.matrixWorld).applyMatrix4(r1);for(let C=0,S=l.length;C<S;C++)if(l[C]){this.getMatrixAt(C,ha),this.getBoundingSphereAt(C,fl).applyMatrix4(ha);let v=!1;if(d&&(v=!P0.intersectsSphere(fl)),!v){const y=ip.distanceTo(fl.center);N0.push(f[C],y)}}const g=N0.list,E=this.customSort;E===null?g.sort(s.transparent?OG:bG):E.call(this,g,i);for(let C=0,S=g.length;C<S;C++){const v=g[C];c[m]=v.start*a,h[m]=v.count,m++}N0.reset()}else for(let g=0,E=l.length;g<E;g++)if(l[g]){let C=!1;if(d&&(this.getMatrixAt(g,ha),this.getBoundingSphereAt(g,fl).applyMatrix4(ha),C=!P0.intersectsSphere(fl)),!C){const S=f[g];c[m]=S.start*a,h[m]=S.count,m++}}this._multiDrawCount=m,this._visibilityChanged=!1}onBeforeShadow(e,t,i,r,s,o){this.onBeforeRender(e,null,r,s,o)}}class wi extends ti{constructor(e){super(),this.isLineBasicMaterial=!0,this.type="LineBasicMaterial",this.color=new ze(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}}const o1=new N,a1=new N,l1=new tt,Q0=new pc,Gm=new vi;class oo extends Wt{constructor(e=new Tt,t=new wi){super(),this.isLine=!0,this.type="Line",this.geometry=e,this.material=t,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(){const e=this.geometry;if(e.index===null){const t=e.attributes.position,i=[0];for(let r=1,s=t.count;r<s;r++)o1.fromBufferAttribute(t,r-1),a1.fromBufferAttribute(t,r),i[r]=i[r-1],i[r]+=o1.distanceTo(a1);e.setAttribute("lineDistance",new ot(i,1))}return this}raycast(e,t){const i=this.geometry,r=this.matrixWorld,s=e.params.Line.threshold,o=i.drawRange;if(i.boundingSphere===null&&i.computeBoundingSphere(),Gm.copy(i.boundingSphere),Gm.applyMatrix4(r),Gm.radius+=s,e.ray.intersectsSphere(Gm)===!1)return;l1.copy(r).invert(),Q0.copy(e.ray).applyMatrix4(l1);const a=s/((this.scale.x+this.scale.y+this.scale.z)/3),l=a*a,c=new N,h=new N,f=new N,d=new N,m=this.isLineSegments?2:1,g=i.index,C=i.attributes.position;if(g!==null){const S=Math.max(0,o.start),v=Math.min(g.count,o.start+o.count);for(let y=S,w=v-1;y<w;y+=m){const x=g.getX(y),k=g.getX(y+1);if(c.fromBufferAttribute(C,x),h.fromBufferAttribute(C,k),Q0.distanceSqToSegment(c,h,d,f)>l)continue;d.applyMatrix4(this.matrixWorld);const R=e.ray.origin.distanceTo(d);R<e.near||R>e.far||t.push({distance:R,point:f.clone().applyMatrix4(this.matrixWorld),index:y,face:null,faceIndex:null,object:this})}}else{const S=Math.max(0,o.start),v=Math.min(C.count,o.start+o.count);for(let y=S,w=v-1;y<w;y+=m){if(c.fromBufferAttribute(C,y),h.fromBufferAttribute(C,y+1),Q0.distanceSqToSegment(c,h,d,f)>l)continue;d.applyMatrix4(this.matrixWorld);const k=e.ray.origin.distanceTo(d);k<e.near||k>e.far||t.push({distance:k,point:f.clone().applyMatrix4(this.matrixWorld),index:y,face:null,faceIndex:null,object:this})}}}updateMorphTargets(){const t=this.geometry.morphAttributes,i=Object.keys(t);if(i.length>0){const r=t[i[0]];if(r!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let s=0,o=r.length;s<o;s++){const a=r[s].name||String(s);this.morphTargetInfluences.push(0),this.morphTargetDictionary[a]=s}}}}}const c1=new N,u1=new N;class Ks extends oo{constructor(e,t){super(e,t),this.isLineSegments=!0,this.type="LineSegments"}computeLineDistances(){const e=this.geometry;if(e.index===null){const t=e.attributes.position,i=[];for(let r=0,s=t.count;r<s;r+=2)c1.fromBufferAttribute(t,r),u1.fromBufferAttribute(t,r+1),i[r]=r===0?0:i[r-1],i[r+1]=i[r]+c1.distanceTo(u1);e.setAttribute("lineDistance",new ot(i,1))}return this}}class fw extends oo{constructor(e,t){super(e,t),this.isLineLoop=!0,this.type="LineLoop"}}class cA extends ti{constructor(e){super(),this.isPointsMaterial=!0,this.type="PointsMaterial",this.color=new ze(16777215),this.map=null,this.alphaMap=null,this.size=1,this.sizeAttenuation=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.map=e.map,this.alphaMap=e.alphaMap,this.size=e.size,this.sizeAttenuation=e.sizeAttenuation,this.fog=e.fog,this}}const h1=new tt,ov=new pc,Vm=new vi,qm=new N;class dw extends Wt{constructor(e=new Tt,t=new cA){super(),this.isPoints=!0,this.type="Points",this.geometry=e,this.material=t,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}raycast(e,t){const i=this.geometry,r=this.matrixWorld,s=e.params.Points.threshold,o=i.drawRange;if(i.boundingSphere===null&&i.computeBoundingSphere(),Vm.copy(i.boundingSphere),Vm.applyMatrix4(r),Vm.radius+=s,e.ray.intersectsSphere(Vm)===!1)return;h1.copy(r).invert(),ov.copy(e.ray).applyMatrix4(h1);const a=s/((this.scale.x+this.scale.y+this.scale.z)/3),l=a*a,c=i.index,f=i.attributes.position;if(c!==null){const d=Math.max(0,o.start),m=Math.min(c.count,o.start+o.count);for(let g=d,E=m;g<E;g++){const C=c.getX(g);qm.fromBufferAttribute(f,C),p1(qm,C,l,r,e,t,this)}}else{const d=Math.max(0,o.start),m=Math.min(f.count,o.start+o.count);for(let g=d,E=m;g<E;g++)qm.fromBufferAttribute(f,g),p1(qm,g,l,r,e,t,this)}}updateMorphTargets(){const t=this.geometry.morphAttributes,i=Object.keys(t);if(i.length>0){const r=t[i[0]];if(r!==void 0){this.morphTargetInfluences=[],this.morphTargetDictionary={};for(let s=0,o=r.length;s<o;s++){const a=r[s].name||String(s);this.morphTargetInfluences.push(0),this.morphTargetDictionary[a]=s}}}}}function p1(n,e,t,i,r,s,o){const a=ov.distanceSqToPoint(n);if(a<t){const l=new N;ov.closestPointToPoint(n,l),l.applyMatrix4(i);const c=r.ray.origin.distanceTo(l);if(c<r.near||c>r.far)return;s.push({distance:c,distanceToRay:Math.sqrt(a),point:l,index:e,face:null,object:o})}}class QG extends fn{constructor(e,t,i,r,s,o,a,l,c){super(e,t,i,r,s,o,a,l,c),this.isVideoTexture=!0,this.minFilter=o!==void 0?o:pn,this.magFilter=s!==void 0?s:pn,this.generateMipmaps=!1;const h=this;function f(){h.needsUpdate=!0,e.requestVideoFrameCallback(f)}"requestVideoFrameCallback"in e&&e.requestVideoFrameCallback(f)}clone(){return new this.constructor(this.image).copy(this)}update(){const e=this.image;"requestVideoFrameCallback"in e===!1&&e.readyState>=e.HAVE_CURRENT_DATA&&(this.needsUpdate=!0)}}class WG extends fn{constructor(e,t){super({width:e,height:t}),this.isFramebufferTexture=!0,this.magFilter=Wn,this.minFilter=Wn,this.generateMipmaps=!1,this.needsUpdate=!0}}class uA extends fn{constructor(e,t,i,r,s,o,a,l,c,h,f,d){super(null,o,a,l,c,h,r,s,f,d),this.isCompressedTexture=!0,this.image={width:t,height:i},this.mipmaps=e,this.flipY=!1,this.generateMipmaps=!1}}class HG extends uA{constructor(e,t,i,r,s,o){super(e,t,i,s,o),this.isCompressedArrayTexture=!0,this.image.depth=r,this.wrapR=oi}}class zG extends uA{constructor(e,t,i){super(void 0,e[0].width,e[0].height,t,i,no),this.isCompressedCubeTexture=!0,this.isCubeTexture=!0,this.image=e}}class GG extends fn{constructor(e,t,i,r,s,o,a,l,c){super(e,t,i,r,s,o,a,l,c),this.isCanvasTexture=!0,this.needsUpdate=!0}}class ls{constructor(){this.type="Curve",this.arcLengthDivisions=200}getPoint(){return null}getPointAt(e,t){const i=this.getUtoTmapping(e);return this.getPoint(i,t)}getPoints(e=5){const t=[];for(let i=0;i<=e;i++)t.push(this.getPoint(i/e));return t}getSpacedPoints(e=5){const t=[];for(let i=0;i<=e;i++)t.push(this.getPointAt(i/e));return t}getLength(){const e=this.getLengths();return e[e.length-1]}getLengths(e=this.arcLengthDivisions){if(this.cacheArcLengths&&this.cacheArcLengths.length===e+1&&!this.needsUpdate)return this.cacheArcLengths;this.needsUpdate=!1;const t=[];let i,r=this.getPoint(0),s=0;t.push(0);for(let o=1;o<=e;o++)i=this.getPoint(o/e),s+=i.distanceTo(r),t.push(s),r=i;return this.cacheArcLengths=t,t}updateArcLengths(){this.needsUpdate=!0,this.getLengths()}getUtoTmapping(e,t){const i=this.getLengths();let r=0;const s=i.length;let o;t?o=t:o=e*i[s-1];let a=0,l=s-1,c;for(;a<=l;)if(r=Math.floor(a+(l-a)/2),c=i[r]-o,c<0)a=r+1;else if(c>0)l=r-1;else{l=r;break}if(r=l,i[r]===o)return r/(s-1);const h=i[r],d=i[r+1]-h,m=(o-h)/d;return(r+m)/(s-1)}getTangent(e,t){let r=e-1e-4,s=e+1e-4;r<0&&(r=0),s>1&&(s=1);const o=this.getPoint(r),a=this.getPoint(s),l=t||(o.isVector2?new we:new N);return l.copy(a).sub(o).normalize(),l}getTangentAt(e,t){const i=this.getUtoTmapping(e);return this.getTangent(i,t)}computeFrenetFrames(e,t){const i=new N,r=[],s=[],o=[],a=new N,l=new tt;for(let m=0;m<=e;m++){const g=m/e;r[m]=this.getTangentAt(g,new N)}s[0]=new N,o[0]=new N;let c=Number.MAX_VALUE;const h=Math.abs(r[0].x),f=Math.abs(r[0].y),d=Math.abs(r[0].z);h<=c&&(c=h,i.set(1,0,0)),f<=c&&(c=f,i.set(0,1,0)),d<=c&&i.set(0,0,1),a.crossVectors(r[0],i).normalize(),s[0].crossVectors(r[0],a),o[0].crossVectors(r[0],s[0]);for(let m=1;m<=e;m++){if(s[m]=s[m-1].clone(),o[m]=o[m-1].clone(),a.crossVectors(r[m-1],r[m]),a.length()>Number.EPSILON){a.normalize();const g=Math.acos(Hn(r[m-1].dot(r[m]),-1,1));s[m].applyMatrix4(l.makeRotationAxis(a,g))}o[m].crossVectors(r[m],s[m])}if(t===!0){let m=Math.acos(Hn(s[0].dot(s[e]),-1,1));m/=e,r[0].dot(a.crossVectors(s[0],s[e]))>0&&(m=-m);for(let g=1;g<=e;g++)s[g].applyMatrix4(l.makeRotationAxis(r[g],m*g)),o[g].crossVectors(r[g],s[g])}return{tangents:r,normals:s,binormals:o}}clone(){return new this.constructor().copy(this)}copy(e){return this.arcLengthDivisions=e.arcLengthDivisions,this}toJSON(){const e={metadata:{version:4.6,type:"Curve",generator:"Curve.toJSON"}};return e.arcLengthDivisions=this.arcLengthDivisions,e.type=this.type,e}fromJSON(e){return this.arcLengthDivisions=e.arcLengthDivisions,this}}class hA extends ls{constructor(e=0,t=0,i=1,r=1,s=0,o=Math.PI*2,a=!1,l=0){super(),this.isEllipseCurve=!0,this.type="EllipseCurve",this.aX=e,this.aY=t,this.xRadius=i,this.yRadius=r,this.aStartAngle=s,this.aEndAngle=o,this.aClockwise=a,this.aRotation=l}getPoint(e,t){const i=t||new we,r=Math.PI*2;let s=this.aEndAngle-this.aStartAngle;const o=Math.abs(s)<Number.EPSILON;for(;s<0;)s+=r;for(;s>r;)s-=r;s<Number.EPSILON&&(o?s=0:s=r),this.aClockwise===!0&&!o&&(s===r?s=-r:s=s-r);const a=this.aStartAngle+e*s;let l=this.aX+this.xRadius*Math.cos(a),c=this.aY+this.yRadius*Math.sin(a);if(this.aRotation!==0){const h=Math.cos(this.aRotation),f=Math.sin(this.aRotation),d=l-this.aX,m=c-this.aY;l=d*h-m*f+this.aX,c=d*f+m*h+this.aY}return i.set(l,c)}copy(e){return super.copy(e),this.aX=e.aX,this.aY=e.aY,this.xRadius=e.xRadius,this.yRadius=e.yRadius,this.aStartAngle=e.aStartAngle,this.aEndAngle=e.aEndAngle,this.aClockwise=e.aClockwise,this.aRotation=e.aRotation,this}toJSON(){const e=super.toJSON();return e.aX=this.aX,e.aY=this.aY,e.xRadius=this.xRadius,e.yRadius=this.yRadius,e.aStartAngle=this.aStartAngle,e.aEndAngle=this.aEndAngle,e.aClockwise=this.aClockwise,e.aRotation=this.aRotation,e}fromJSON(e){return super.fromJSON(e),this.aX=e.aX,this.aY=e.aY,this.xRadius=e.xRadius,this.yRadius=e.yRadius,this.aStartAngle=e.aStartAngle,this.aEndAngle=e.aEndAngle,this.aClockwise=e.aClockwise,this.aRotation=e.aRotation,this}}class wR extends hA{constructor(e,t,i,r,s,o){super(e,t,i,i,r,s,o),this.isArcCurve=!0,this.type="ArcCurve"}}function mw(){let n=0,e=0,t=0,i=0;function r(s,o,a,l){n=s,e=a,t=-3*s+3*o-2*a-l,i=2*s-2*o+a+l}return{initCatmullRom:function(s,o,a,l,c){r(o,a,c*(a-s),c*(l-o))},initNonuniformCatmullRom:function(s,o,a,l,c,h,f){let d=(o-s)/c-(a-s)/(c+h)+(a-o)/h,m=(a-o)/h-(l-o)/(h+f)+(l-a)/f;d*=h,m*=h,r(o,a,d,m)},calc:function(s){const o=s*s,a=o*s;return n+e*s+t*o+i*a}}}const Ym=new N,W0=new mw,H0=new mw,z0=new mw;class MR extends ls{constructor(e=[],t=!1,i="centripetal",r=.5){super(),this.isCatmullRomCurve3=!0,this.type="CatmullRomCurve3",this.points=e,this.closed=t,this.curveType=i,this.tension=r}getPoint(e,t=new N){const i=t,r=this.points,s=r.length,o=(s-(this.closed?0:1))*e;let a=Math.floor(o),l=o-a;this.closed?a+=a>0?0:(Math.floor(Math.abs(a)/s)+1)*s:l===0&&a===s-1&&(a=s-2,l=1);let c,h;this.closed||a>0?c=r[(a-1)%s]:(Ym.subVectors(r[0],r[1]).add(r[0]),c=Ym);const f=r[a%s],d=r[(a+1)%s];if(this.closed||a+2<s?h=r[(a+2)%s]:(Ym.subVectors(r[s-1],r[s-2]).add(r[s-1]),h=Ym),this.curveType==="centripetal"||this.curveType==="chordal"){const m=this.curveType==="chordal"?.5:.25;let g=Math.pow(c.distanceToSquared(f),m),E=Math.pow(f.distanceToSquared(d),m),C=Math.pow(d.distanceToSquared(h),m);E<1e-4&&(E=1),g<1e-4&&(g=E),C<1e-4&&(C=E),W0.initNonuniformCatmullRom(c.x,f.x,d.x,h.x,g,E,C),H0.initNonuniformCatmullRom(c.y,f.y,d.y,h.y,g,E,C),z0.initNonuniformCatmullRom(c.z,f.z,d.z,h.z,g,E,C)}else this.curveType==="catmullrom"&&(W0.initCatmullRom(c.x,f.x,d.x,h.x,this.tension),H0.initCatmullRom(c.y,f.y,d.y,h.y,this.tension),z0.initCatmullRom(c.z,f.z,d.z,h.z,this.tension));return i.set(W0.calc(l),H0.calc(l),z0.calc(l)),i}copy(e){super.copy(e),this.points=[];for(let t=0,i=e.points.length;t<i;t++){const r=e.points[t];this.points.push(r.clone())}return this.closed=e.closed,this.curveType=e.curveType,this.tension=e.tension,this}toJSON(){const e=super.toJSON();e.points=[];for(let t=0,i=this.points.length;t<i;t++){const r=this.points[t];e.points.push(r.toArray())}return e.closed=this.closed,e.curveType=this.curveType,e.tension=this.tension,e}fromJSON(e){super.fromJSON(e),this.points=[];for(let t=0,i=e.points.length;t<i;t++){const r=e.points[t];this.points.push(new N().fromArray(r))}return this.closed=e.closed,this.curveType=e.curveType,this.tension=e.tension,this}}function f1(n,e,t,i,r){const s=(i-e)*.5,o=(r-t)*.5,a=n*n,l=n*a;return(2*t-2*i+s+o)*l+(-3*t+3*i-2*s-o)*a+s*n+t}function VG(n,e){const t=1-n;return t*t*e}function qG(n,e){return 2*(1-n)*n*e}function YG(n,e){return n*n*e}function Kp(n,e,t,i){return VG(n,e)+qG(n,t)+YG(n,i)}function ZG(n,e){const t=1-n;return t*t*t*e}function jG(n,e){const t=1-n;return 3*t*t*n*e}function XG(n,e){return 3*(1-n)*n*n*e}function _G(n,e){return n*n*n*e}function Rp(n,e,t,i,r){return ZG(n,e)+jG(n,t)+XG(n,i)+_G(n,r)}class Sw extends ls{constructor(e=new we,t=new we,i=new we,r=new we){super(),this.isCubicBezierCurve=!0,this.type="CubicBezierCurve",this.v0=e,this.v1=t,this.v2=i,this.v3=r}getPoint(e,t=new we){const i=t,r=this.v0,s=this.v1,o=this.v2,a=this.v3;return i.set(Rp(e,r.x,s.x,o.x,a.x),Rp(e,r.y,s.y,o.y,a.y)),i}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this.v3.copy(e.v3),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e.v3=this.v3.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this.v3.fromArray(e.v3),this}}class kR extends ls{constructor(e=new N,t=new N,i=new N,r=new N){super(),this.isCubicBezierCurve3=!0,this.type="CubicBezierCurve3",this.v0=e,this.v1=t,this.v2=i,this.v3=r}getPoint(e,t=new N){const i=t,r=this.v0,s=this.v1,o=this.v2,a=this.v3;return i.set(Rp(e,r.x,s.x,o.x,a.x),Rp(e,r.y,s.y,o.y,a.y),Rp(e,r.z,s.z,o.z,a.z)),i}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this.v3.copy(e.v3),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e.v3=this.v3.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this.v3.fromArray(e.v3),this}}class gw extends ls{constructor(e=new we,t=new we){super(),this.isLineCurve=!0,this.type="LineCurve",this.v1=e,this.v2=t}getPoint(e,t=new we){const i=t;return e===1?i.copy(this.v2):(i.copy(this.v2).sub(this.v1),i.multiplyScalar(e).add(this.v1)),i}getPointAt(e,t){return this.getPoint(e,t)}getTangent(e,t=new we){return t.subVectors(this.v2,this.v1).normalize()}getTangentAt(e,t){return this.getTangent(e,t)}copy(e){return super.copy(e),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class xR extends ls{constructor(e=new N,t=new N){super(),this.isLineCurve3=!0,this.type="LineCurve3",this.v1=e,this.v2=t}getPoint(e,t=new N){const i=t;return e===1?i.copy(this.v2):(i.copy(this.v2).sub(this.v1),i.multiplyScalar(e).add(this.v1)),i}getPointAt(e,t){return this.getPoint(e,t)}getTangent(e,t=new N){return t.subVectors(this.v2,this.v1).normalize()}getTangentAt(e,t){return this.getTangent(e,t)}copy(e){return super.copy(e),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class Aw extends ls{constructor(e=new we,t=new we,i=new we){super(),this.isQuadraticBezierCurve=!0,this.type="QuadraticBezierCurve",this.v0=e,this.v1=t,this.v2=i}getPoint(e,t=new we){const i=t,r=this.v0,s=this.v1,o=this.v2;return i.set(Kp(e,r.x,s.x,o.x),Kp(e,r.y,s.y,o.y)),i}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class yw extends ls{constructor(e=new N,t=new N,i=new N){super(),this.isQuadraticBezierCurve3=!0,this.type="QuadraticBezierCurve3",this.v0=e,this.v1=t,this.v2=i}getPoint(e,t=new N){const i=t,r=this.v0,s=this.v1,o=this.v2;return i.set(Kp(e,r.x,s.x,o.x),Kp(e,r.y,s.y,o.y),Kp(e,r.z,s.z,o.z)),i}copy(e){return super.copy(e),this.v0.copy(e.v0),this.v1.copy(e.v1),this.v2.copy(e.v2),this}toJSON(){const e=super.toJSON();return e.v0=this.v0.toArray(),e.v1=this.v1.toArray(),e.v2=this.v2.toArray(),e}fromJSON(e){return super.fromJSON(e),this.v0.fromArray(e.v0),this.v1.fromArray(e.v1),this.v2.fromArray(e.v2),this}}class Ew extends ls{constructor(e=[]){super(),this.isSplineCurve=!0,this.type="SplineCurve",this.points=e}getPoint(e,t=new we){const i=t,r=this.points,s=(r.length-1)*e,o=Math.floor(s),a=s-o,l=r[o===0?o:o-1],c=r[o],h=r[o>r.length-2?r.length-1:o+1],f=r[o>r.length-3?r.length-1:o+2];return i.set(f1(a,l.x,c.x,h.x,f.x),f1(a,l.y,c.y,h.y,f.y)),i}copy(e){super.copy(e),this.points=[];for(let t=0,i=e.points.length;t<i;t++){const r=e.points[t];this.points.push(r.clone())}return this}toJSON(){const e=super.toJSON();e.points=[];for(let t=0,i=this.points.length;t<i;t++){const r=this.points[t];e.points.push(r.toArray())}return e}fromJSON(e){super.fromJSON(e),this.points=[];for(let t=0,i=e.points.length;t<i;t++){const r=e.points[t];this.points.push(new we().fromArray(r))}return this}}var yg=Object.freeze({__proto__:null,ArcCurve:wR,CatmullRomCurve3:MR,CubicBezierCurve:Sw,CubicBezierCurve3:kR,EllipseCurve:hA,LineCurve:gw,LineCurve3:xR,QuadraticBezierCurve:Aw,QuadraticBezierCurve3:yw,SplineCurve:Ew});class TR extends ls{constructor(){super(),this.type="CurvePath",this.curves=[],this.autoClose=!1}add(e){this.curves.push(e)}closePath(){const e=this.curves[0].getPoint(0),t=this.curves[this.curves.length-1].getPoint(1);if(!e.equals(t)){const i=e.isVector2===!0?"LineCurve":"LineCurve3";this.curves.push(new yg[i](t,e))}return this}getPoint(e,t){const i=e*this.getLength(),r=this.getCurveLengths();let s=0;for(;s<r.length;){if(r[s]>=i){const o=r[s]-i,a=this.curves[s],l=a.getLength(),c=l===0?0:1-o/l;return a.getPointAt(c,t)}s++}return null}getLength(){const e=this.getCurveLengths();return e[e.length-1]}updateArcLengths(){this.needsUpdate=!0,this.cacheLengths=null,this.getCurveLengths()}getCurveLengths(){if(this.cacheLengths&&this.cacheLengths.length===this.curves.length)return this.cacheLengths;const e=[];let t=0;for(let i=0,r=this.curves.length;i<r;i++)t+=this.curves[i].getLength(),e.push(t);return this.cacheLengths=e,e}getSpacedPoints(e=40){const t=[];for(let i=0;i<=e;i++)t.push(this.getPoint(i/e));return this.autoClose&&t.push(t[0]),t}getPoints(e=12){const t=[];let i;for(let r=0,s=this.curves;r<s.length;r++){const o=s[r],a=o.isEllipseCurve?e*2:o.isLineCurve||o.isLineCurve3?1:o.isSplineCurve?e*o.points.length:e,l=o.getPoints(a);for(let c=0;c<l.length;c++){const h=l[c];i&&i.equals(h)||(t.push(h),i=h)}}return this.autoClose&&t.length>1&&!t[t.length-1].equals(t[0])&&t.push(t[0]),t}copy(e){super.copy(e),this.curves=[];for(let t=0,i=e.curves.length;t<i;t++){const r=e.curves[t];this.curves.push(r.clone())}return this.autoClose=e.autoClose,this}toJSON(){const e=super.toJSON();e.autoClose=this.autoClose,e.curves=[];for(let t=0,i=this.curves.length;t<i;t++){const r=this.curves[t];e.curves.push(r.toJSON())}return e}fromJSON(e){super.fromJSON(e),this.autoClose=e.autoClose,this.curves=[];for(let t=0,i=e.curves.length;t<i;t++){const r=e.curves[t];this.curves.push(new yg[r.type]().fromJSON(r))}return this}}class Sf extends TR{constructor(e){super(),this.type="Path",this.currentPoint=new we,e&&this.setFromPoints(e)}setFromPoints(e){this.moveTo(e[0].x,e[0].y);for(let t=1,i=e.length;t<i;t++)this.lineTo(e[t].x,e[t].y);return this}moveTo(e,t){return this.currentPoint.set(e,t),this}lineTo(e,t){const i=new gw(this.currentPoint.clone(),new we(e,t));return this.curves.push(i),this.currentPoint.set(e,t),this}quadraticCurveTo(e,t,i,r){const s=new Aw(this.currentPoint.clone(),new we(e,t),new we(i,r));return this.curves.push(s),this.currentPoint.set(i,r),this}bezierCurveTo(e,t,i,r,s,o){const a=new Sw(this.currentPoint.clone(),new we(e,t),new we(i,r),new we(s,o));return this.curves.push(a),this.currentPoint.set(s,o),this}splineThru(e){const t=[this.currentPoint.clone()].concat(e),i=new Ew(t);return this.curves.push(i),this.currentPoint.copy(e[e.length-1]),this}arc(e,t,i,r,s,o){const a=this.currentPoint.x,l=this.currentPoint.y;return this.absarc(e+a,t+l,i,r,s,o),this}absarc(e,t,i,r,s,o){return this.absellipse(e,t,i,i,r,s,o),this}ellipse(e,t,i,r,s,o,a,l){const c=this.currentPoint.x,h=this.currentPoint.y;return this.absellipse(e+c,t+h,i,r,s,o,a,l),this}absellipse(e,t,i,r,s,o,a,l){const c=new hA(e,t,i,r,s,o,a,l);if(this.curves.length>0){const f=c.getPoint(0);f.equals(this.currentPoint)||this.lineTo(f.x,f.y)}this.curves.push(c);const h=c.getPoint(1);return this.currentPoint.copy(h),this}copy(e){return super.copy(e),this.currentPoint.copy(e.currentPoint),this}toJSON(){const e=super.toJSON();return e.currentPoint=this.currentPoint.toArray(),e}fromJSON(e){return super.fromJSON(e),this.currentPoint.fromArray(e.currentPoint),this}}class Hf extends Tt{constructor(e=[new we(0,-.5),new we(.5,0),new we(0,.5)],t=12,i=0,r=Math.PI*2){super(),this.type="LatheGeometry",this.parameters={points:e,segments:t,phiStart:i,phiLength:r},t=Math.floor(t),r=Hn(r,0,Math.PI*2);const s=[],o=[],a=[],l=[],c=[],h=1/t,f=new N,d=new we,m=new N,g=new N,E=new N;let C=0,S=0;for(let v=0;v<=e.length-1;v++)switch(v){case 0:C=e[v+1].x-e[v].x,S=e[v+1].y-e[v].y,m.x=S*1,m.y=-C,m.z=S*0,E.copy(m),m.normalize(),l.push(m.x,m.y,m.z);break;case e.length-1:l.push(E.x,E.y,E.z);break;default:C=e[v+1].x-e[v].x,S=e[v+1].y-e[v].y,m.x=S*1,m.y=-C,m.z=S*0,g.copy(m),m.x+=E.x,m.y+=E.y,m.z+=E.z,m.normalize(),l.push(m.x,m.y,m.z),E.copy(g)}for(let v=0;v<=t;v++){const y=i+v*h*r,w=Math.sin(y),x=Math.cos(y);for(let k=0;k<=e.length-1;k++){f.x=e[k].x*w,f.y=e[k].y,f.z=e[k].x*x,o.push(f.x,f.y,f.z),d.x=v/t,d.y=k/(e.length-1),a.push(d.x,d.y);const I=l[3*k+0]*w,R=l[3*k+1],T=l[3*k+0]*x;c.push(I,R,T)}}for(let v=0;v<t;v++)for(let y=0;y<e.length-1;y++){const w=y+v*e.length,x=w,k=w+e.length,I=w+e.length+1,R=w+1;s.push(x,k,R),s.push(I,R,k)}this.setIndex(s),this.setAttribute("position",new ot(o,3)),this.setAttribute("uv",new ot(a,2)),this.setAttribute("normal",new ot(c,3))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Hf(e.points,e.segments,e.phiStart,e.phiLength)}}class pA extends Hf{constructor(e=1,t=1,i=4,r=8){const s=new Sf;s.absarc(0,-t/2,e,Math.PI*1.5,0),s.absarc(0,t/2,e,0,Math.PI*.5),super(s.getPoints(i),r),this.type="CapsuleGeometry",this.parameters={radius:e,length:t,capSegments:i,radialSegments:r}}static fromJSON(e){return new pA(e.radius,e.length,e.capSegments,e.radialSegments)}}class fA extends Tt{constructor(e=1,t=32,i=0,r=Math.PI*2){super(),this.type="CircleGeometry",this.parameters={radius:e,segments:t,thetaStart:i,thetaLength:r},t=Math.max(3,t);const s=[],o=[],a=[],l=[],c=new N,h=new we;o.push(0,0,0),a.push(0,0,1),l.push(.5,.5);for(let f=0,d=3;f<=t;f++,d+=3){const m=i+f/t*r;c.x=e*Math.cos(m),c.y=e*Math.sin(m),o.push(c.x,c.y,c.z),a.push(0,0,1),h.x=(o[d]/e+1)/2,h.y=(o[d+1]/e+1)/2,l.push(h.x,h.y)}for(let f=1;f<=t;f++)s.push(f,f+1,0);this.setIndex(s),this.setAttribute("position",new ot(o,3)),this.setAttribute("normal",new ot(a,3)),this.setAttribute("uv",new ot(l,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new fA(e.radius,e.segments,e.thetaStart,e.thetaLength)}}class uh extends Tt{constructor(e=1,t=1,i=1,r=32,s=1,o=!1,a=0,l=Math.PI*2){super(),this.type="CylinderGeometry",this.parameters={radiusTop:e,radiusBottom:t,height:i,radialSegments:r,heightSegments:s,openEnded:o,thetaStart:a,thetaLength:l};const c=this;r=Math.floor(r),s=Math.floor(s);const h=[],f=[],d=[],m=[];let g=0;const E=[],C=i/2;let S=0;v(),o===!1&&(e>0&&y(!0),t>0&&y(!1)),this.setIndex(h),this.setAttribute("position",new ot(f,3)),this.setAttribute("normal",new ot(d,3)),this.setAttribute("uv",new ot(m,2));function v(){const w=new N,x=new N;let k=0;const I=(t-e)/i;for(let R=0;R<=s;R++){const T=[],L=R/s,O=L*(t-e)+e;for(let V=0;V<=r;V++){const ie=V/r,W=ie*l+a,_=Math.sin(W),ne=Math.cos(W);x.x=O*_,x.y=-L*i+C,x.z=O*ne,f.push(x.x,x.y,x.z),w.set(_,I,ne).normalize(),d.push(w.x,w.y,w.z),m.push(ie,1-L),T.push(g++)}E.push(T)}for(let R=0;R<r;R++)for(let T=0;T<s;T++){const L=E[T][R],O=E[T+1][R],V=E[T+1][R+1],ie=E[T][R+1];h.push(L,O,ie),h.push(O,V,ie),k+=6}c.addGroup(S,k,0),S+=k}function y(w){const x=g,k=new we,I=new N;let R=0;const T=w===!0?e:t,L=w===!0?1:-1;for(let V=1;V<=r;V++)f.push(0,C*L,0),d.push(0,L,0),m.push(.5,.5),g++;const O=g;for(let V=0;V<=r;V++){const W=V/r*l+a,_=Math.cos(W),ne=Math.sin(W);I.x=T*ne,I.y=C*L,I.z=T*_,f.push(I.x,I.y,I.z),d.push(0,L,0),k.x=_*.5+.5,k.y=ne*.5*L+.5,m.push(k.x,k.y),g++}for(let V=0;V<r;V++){const ie=x+V,W=O+V;w===!0?h.push(W,W+1,ie):h.push(W+1,W,ie),R+=3}c.addGroup(S,R,w===!0?1:2),S+=R}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new uh(e.radiusTop,e.radiusBottom,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class dA extends uh{constructor(e=1,t=1,i=32,r=1,s=!1,o=0,a=Math.PI*2){super(0,e,t,i,r,s,o,a),this.type="ConeGeometry",this.parameters={radius:e,height:t,radialSegments:i,heightSegments:r,openEnded:s,thetaStart:o,thetaLength:a}}static fromJSON(e){return new dA(e.radius,e.height,e.radialSegments,e.heightSegments,e.openEnded,e.thetaStart,e.thetaLength)}}class ja extends Tt{constructor(e=[],t=[],i=1,r=0){super(),this.type="PolyhedronGeometry",this.parameters={vertices:e,indices:t,radius:i,detail:r};const s=[],o=[];a(r),c(i),h(),this.setAttribute("position",new ot(s,3)),this.setAttribute("normal",new ot(s.slice(),3)),this.setAttribute("uv",new ot(o,2)),r===0?this.computeVertexNormals():this.normalizeNormals();function a(v){const y=new N,w=new N,x=new N;for(let k=0;k<t.length;k+=3)m(t[k+0],y),m(t[k+1],w),m(t[k+2],x),l(y,w,x,v)}function l(v,y,w,x){const k=x+1,I=[];for(let R=0;R<=k;R++){I[R]=[];const T=v.clone().lerp(w,R/k),L=y.clone().lerp(w,R/k),O=k-R;for(let V=0;V<=O;V++)V===0&&R===k?I[R][V]=T:I[R][V]=T.clone().lerp(L,V/O)}for(let R=0;R<k;R++)for(let T=0;T<2*(k-R)-1;T++){const L=Math.floor(T/2);T%2===0?(d(I[R][L+1]),d(I[R+1][L]),d(I[R][L])):(d(I[R][L+1]),d(I[R+1][L+1]),d(I[R+1][L]))}}function c(v){const y=new N;for(let w=0;w<s.length;w+=3)y.x=s[w+0],y.y=s[w+1],y.z=s[w+2],y.normalize().multiplyScalar(v),s[w+0]=y.x,s[w+1]=y.y,s[w+2]=y.z}function h(){const v=new N;for(let y=0;y<s.length;y+=3){v.x=s[y+0],v.y=s[y+1],v.z=s[y+2];const w=C(v)/2/Math.PI+.5,x=S(v)/Math.PI+.5;o.push(w,1-x)}g(),f()}function f(){for(let v=0;v<o.length;v+=6){const y=o[v+0],w=o[v+2],x=o[v+4],k=Math.max(y,w,x),I=Math.min(y,w,x);k>.9&&I<.1&&(y<.2&&(o[v+0]+=1),w<.2&&(o[v+2]+=1),x<.2&&(o[v+4]+=1))}}function d(v){s.push(v.x,v.y,v.z)}function m(v,y){const w=v*3;y.x=e[w+0],y.y=e[w+1],y.z=e[w+2]}function g(){const v=new N,y=new N,w=new N,x=new N,k=new we,I=new we,R=new we;for(let T=0,L=0;T<s.length;T+=9,L+=6){v.set(s[T+0],s[T+1],s[T+2]),y.set(s[T+3],s[T+4],s[T+5]),w.set(s[T+6],s[T+7],s[T+8]),k.set(o[L+0],o[L+1]),I.set(o[L+2],o[L+3]),R.set(o[L+4],o[L+5]),x.copy(v).add(y).add(w).divideScalar(3);const O=C(x);E(k,L+0,v,O),E(I,L+2,y,O),E(R,L+4,w,O)}}function E(v,y,w,x){x<0&&v.x===1&&(o[y]=v.x-1),w.x===0&&w.z===0&&(o[y]=x/2/Math.PI+.5)}function C(v){return Math.atan2(v.z,-v.x)}function S(v){return Math.atan2(-v.y,Math.sqrt(v.x*v.x+v.z*v.z))}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new ja(e.vertices,e.indices,e.radius,e.details)}}class mA extends ja{constructor(e=1,t=0){const i=(1+Math.sqrt(5))/2,r=1/i,s=[-1,-1,-1,-1,-1,1,-1,1,-1,-1,1,1,1,-1,-1,1,-1,1,1,1,-1,1,1,1,0,-r,-i,0,-r,i,0,r,-i,0,r,i,-r,-i,0,-r,i,0,r,-i,0,r,i,0,-i,0,-r,i,0,-r,-i,0,r,i,0,r],o=[3,11,7,3,7,15,3,15,13,7,19,17,7,17,6,7,6,15,17,4,8,17,8,10,17,10,6,8,0,16,8,16,2,8,2,10,0,12,1,0,1,18,0,18,16,6,10,2,6,2,13,6,13,15,2,16,18,2,18,3,2,3,13,18,1,9,18,9,11,18,11,3,4,14,12,4,12,0,4,0,8,11,9,5,11,5,19,11,19,7,19,5,14,19,14,4,19,4,17,1,12,14,1,14,5,1,5,9];super(s,o,e,t),this.type="DodecahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new mA(e.radius,e.detail)}}const Zm=new N,jm=new N,G0=new N,Xm=new pr;class JR extends Tt{constructor(e=null,t=1){if(super(),this.type="EdgesGeometry",this.parameters={geometry:e,thresholdAngle:t},e!==null){const r=Math.pow(10,4),s=Math.cos(Wl*t),o=e.getIndex(),a=e.getAttribute("position"),l=o?o.count:a.count,c=[0,0,0],h=["a","b","c"],f=new Array(3),d={},m=[];for(let 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super.copy(e),this.parameters=Object.assign({},e.parameters),this}}class Gl extends Sf{constructor(e){super(e),this.uuid=Br(),this.type="Shape",this.holes=[]}getPointsHoles(e){const t=[];for(let i=0,r=this.holes.length;i<r;i++)t[i]=this.holes[i].getPoints(e);return t}extractPoints(e){return{shape:this.getPoints(e),holes:this.getPointsHoles(e)}}copy(e){super.copy(e),this.holes=[];for(let t=0,i=e.holes.length;t<i;t++){const r=e.holes[t];this.holes.push(r.clone())}return this}toJSON(){const e=super.toJSON();e.uuid=this.uuid,e.holes=[];for(let t=0,i=this.holes.length;t<i;t++){const r=this.holes[t];e.holes.push(r.toJSON())}return e}fromJSON(e){super.fromJSON(e),this.uuid=e.uuid,this.holes=[];for(let t=0,i=e.holes.length;t<i;t++){const r=e.holes[t];this.holes.push(new Sf().fromJSON(r))}return this}}const $G={triangulate:function(n,e,t=2){const i=e&&e.length,r=i?e[0]*t:n.length;let s=IR(n,0,r,t,!0);const o=[];if(!s||s.next===s.prev)return o;let 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n.next.i!==e.i&&n.prev.i!==e.i&&!f5(n,e)&&(Af(n,e)&&Af(e,n)&&d5(n,e)&&(Kn(n.prev,n,e.prev)||Kn(n,e.prev,e))||SA(n,e)&&Kn(n.prev,n,n.next)>0&&Kn(e.prev,e,e.next)>0)}function Kn(n,e,t){return(e.y-n.y)*(t.x-e.x)-(e.x-n.x)*(t.y-e.y)}function SA(n,e){return n.x===e.x&&n.y===e.y}function LR(n,e,t,i){const r=$m(Kn(n,e,t)),s=$m(Kn(n,e,i)),o=$m(Kn(t,i,n)),a=$m(Kn(t,i,e));return!!(r!==s&&o!==a||r===0&&_m(n,t,e)||s===0&&_m(n,i,e)||o===0&&_m(t,n,i)||a===0&&_m(t,e,i))}function _m(n,e,t){return e.x<=Math.max(n.x,t.x)&&e.x>=Math.min(n.x,t.x)&&e.y<=Math.max(n.y,t.y)&&e.y>=Math.min(n.y,t.y)}function $m(n){return n>0?1:n<0?-1:0}function f5(n,e){let t=n;do{if(t.i!==n.i&&t.next.i!==n.i&&t.i!==e.i&&t.next.i!==e.i&&LR(t,t.next,n,e))return!0;t=t.next}while(t!==n);return!1}function Af(n,e){return Kn(n.prev,n,n.next)<0?Kn(n,e,n.next)>=0&&Kn(n,n.prev,e)>=0:Kn(n,e,n.prev)<0||Kn(n,n.next,e)<0}function d5(n,e){let t=n,i=!1;const r=(n.x+e.x)/2,s=(n.y+e.y)/2;do 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0?t.bevelOffset:0,C=t.bevelSegments!==void 0?t.bevelSegments:3;const S=t.extrudePath,v=t.UVGenerator!==void 0?t.UVGenerator:S5;let y,w=!1,x,k,I,R;S&&(y=S.getSpacedPoints(h),w=!0,d=!1,x=S.computeFrenetFrames(h,!1),k=new N,I=new N,R=new N),d||(C=0,m=0,g=0,E=0);const T=a.extractPoints(c);let L=T.shape;const O=T.holes;if(!eo.isClockWise(L)){L=L.reverse();for(let Y=0,Ie=O.length;Y<Ie;Y++){const Ce=O[Y];eo.isClockWise(Ce)&&(O[Y]=Ce.reverse())}}const ie=eo.triangulateShape(L,O),W=L;for(let Y=0,Ie=O.length;Y<Ie;Y++){const Ce=O[Y];L=L.concat(Ce)}function _(Y,Ie,Ce){return Y.clone().addScaledVector(Ie,Ce)}const ne=L.length,oe=ie.length;function H(Y,Ie,Ce){let De,xe,ct;const Ye=Y.x-Ie.x,je=Y.y-Ie.y,dt=Ce.x-Y.x,vt=Ce.y-Y.y,_t=Ye*Ye+je*je,F=Ye*vt-je*dt;if(Math.abs(F)>Number.EPSILON){const b=Math.sqrt(_t),ue=Math.sqrt(dt*dt+vt*vt),Be=Ie.x-je/b,Je=Ie.y+Ye/b,Re=Ce.x-vt/ue,$e=Ce.y+dt/ue,Qe=((Re-Be)*vt-($e-Je)*dt)/(Ye*vt-je*dt);De=Be+Ye*Qe-Y.x,xe=Je+je*Qe-Y.y;const Ge=De*De+xe*xe;if(Ge<=2)return new we(De,xe);ct=Math.sqrt(Ge/2)}else{let b=!1;Ye>Number.EPSILON?dt>Number.EPSILON&&(b=!0):Ye<-Number.EPSILON?dt<-Number.EPSILON&&(b=!0):Math.sign(je)===Math.sign(vt)&&(b=!0),b?(De=-je,xe=Ye,ct=Math.sqrt(_t)):(De=Ye,xe=je,ct=Math.sqrt(_t/2))}return new we(De/ct,xe/ct)}const Z=[];for(let Y=0,Ie=W.length,Ce=Ie-1,De=Y+1;Y<Ie;Y++,Ce++,De++)Ce===Ie&&(Ce=0),De===Ie&&(De=0),Z[Y]=H(W[Y],W[Ce],W[De]);const te=[];let ae,fe=Z.concat();for(let Y=0,Ie=O.length;Y<Ie;Y++){const Ce=O[Y];ae=[];for(let De=0,xe=Ce.length,ct=xe-1,Ye=De+1;De<xe;De++,ct++,Ye++)ct===xe&&(ct=0),Ye===xe&&(Ye=0),ae[De]=H(Ce[De],Ce[ct],Ce[Ye]);te.push(ae),fe=fe.concat(ae)}for(let Y=0;Y<C;Y++){const Ie=Y/C,Ce=m*Math.cos(Ie*Math.PI/2),De=g*Math.sin(Ie*Math.PI/2)+E;for(let xe=0,ct=W.length;xe<ct;xe++){const Ye=_(W[xe],Z[xe],De);Fe(Ye.x,Ye.y,-Ce)}for(let xe=0,ct=O.length;xe<ct;xe++){const Ye=O[xe];ae=te[xe];for(let je=0,dt=Ye.length;je<dt;je++){const vt=_(Ye[je],ae[je],De);Fe(vt.x,vt.y,-Ce)}}}const ce=g+E;for(let Y=0;Y<ne;Y++){const Ie=d?_(L[Y],fe[Y],ce):L[Y];w?(I.copy(x.normals[0]).multiplyScalar(Ie.x),k.copy(x.binormals[0]).multiplyScalar(Ie.y),R.copy(y[0]).add(I).add(k),Fe(R.x,R.y,R.z)):Fe(Ie.x,Ie.y,0)}for(let Y=1;Y<=h;Y++)for(let Ie=0;Ie<ne;Ie++){const Ce=d?_(L[Ie],fe[Ie],ce):L[Ie];w?(I.copy(x.normals[Y]).multiplyScalar(Ce.x),k.copy(x.binormals[Y]).multiplyScalar(Ce.y),R.copy(y[Y]).add(I).add(k),Fe(R.x,R.y,R.z)):Fe(Ce.x,Ce.y,f/h*Y)}for(let Y=C-1;Y>=0;Y--){const Ie=Y/C,Ce=m*Math.cos(Ie*Math.PI/2),De=g*Math.sin(Ie*Math.PI/2)+E;for(let xe=0,ct=W.length;xe<ct;xe++){const Ye=_(W[xe],Z[xe],De);Fe(Ye.x,Ye.y,f+Ce)}for(let xe=0,ct=O.length;xe<ct;xe++){const Ye=O[xe];ae=te[xe];for(let je=0,dt=Ye.length;je<dt;je++){const vt=_(Ye[je],ae[je],De);w?Fe(vt.x,vt.y+y[h-1].y,y[h-1].x+Ce):Fe(vt.x,vt.y,f+Ce)}}}me(),Te();function me(){const Y=r.length/3;if(d){let Ie=0,Ce=ne*Ie;for(let De=0;De<oe;De++){const xe=ie[De];rt(xe[2]+Ce,xe[1]+Ce,xe[0]+Ce)}Ie=h+C*2,Ce=ne*Ie;for(let De=0;De<oe;De++){const xe=ie[De];rt(xe[0]+Ce,xe[1]+Ce,xe[2]+Ce)}}else{for(let Ie=0;Ie<oe;Ie++){const Ce=ie[Ie];rt(Ce[2],Ce[1],Ce[0])}for(let Ie=0;Ie<oe;Ie++){const Ce=ie[Ie];rt(Ce[0]+ne*h,Ce[1]+ne*h,Ce[2]+ne*h)}}i.addGroup(Y,r.length/3-Y,0)}function Te(){const Y=r.length/3;let Ie=0;Me(W,Ie),Ie+=W.length;for(let Ce=0,De=O.length;Ce<De;Ce++){const xe=O[Ce];Me(xe,Ie),Ie+=xe.length}i.addGroup(Y,r.length/3-Y,1)}function Me(Y,Ie){let Ce=Y.length;for(;--Ce>=0;){const De=Ce;let xe=Ce-1;xe<0&&(xe=Y.length-1);for(let ct=0,Ye=h+C*2;ct<Ye;ct++){const je=ne*ct,dt=ne*(ct+1),vt=Ie+De+je,_t=Ie+xe+je,F=Ie+xe+dt,b=Ie+De+dt;ft(vt,_t,F,b)}}}function Fe(Y,Ie,Ce){l.push(Y),l.push(Ie),l.push(Ce)}function rt(Y,Ie,Ce){st(Y),st(Ie),st(Ce);const De=r.length/3,xe=v.generateTopUV(i,r,De-3,De-2,De-1);_e(xe[0]),_e(xe[1]),_e(xe[2])}function ft(Y,Ie,Ce,De){st(Y),st(Ie),st(De),st(Ie),st(Ce),st(De);const xe=r.length/3,ct=v.generateSideWallUV(i,r,xe-6,xe-3,xe-2,xe-1);_e(ct[0]),_e(ct[1]),_e(ct[3]),_e(ct[1]),_e(ct[2]),_e(ct[3])}function st(Y){r.push(l[Y*3+0]),r.push(l[Y*3+1]),r.push(l[Y*3+2])}function _e(Y){s.push(Y.x),s.push(Y.y)}}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}toJSON(){const e=super.toJSON(),t=this.parameters.shapes,i=this.parameters.options;return g5(t,i,e)}static fromJSON(e,t){const i=[];for(let s=0,o=e.shapes.length;s<o;s++){const a=t[e.shapes[s]];i.push(a)}const r=e.options.extrudePath;return r!==void 0&&(e.options.extrudePath=new yg[r.type]().fromJSON(r)),new gA(i,e.options)}}const S5={generateTopUV:function(n,e,t,i,r){const s=e[t*3],o=e[t*3+1],a=e[i*3],l=e[i*3+1],c=e[r*3],h=e[r*3+1];return[new we(s,o),new we(a,l),new we(c,h)]},generateSideWallUV:function(n,e,t,i,r,s){const o=e[t*3],a=e[t*3+1],l=e[t*3+2],c=e[i*3],h=e[i*3+1],f=e[i*3+2],d=e[r*3],m=e[r*3+1],g=e[r*3+2],E=e[s*3],C=e[s*3+1],S=e[s*3+2];return Math.abs(a-h)<Math.abs(o-c)?[new we(o,1-l),new we(c,1-f),new we(d,1-g),new we(E,1-S)]:[new we(a,1-l),new we(h,1-f),new we(m,1-g),new we(C,1-S)]}};function g5(n,e,t){if(t.shapes=[],Array.isArray(n))for(let i=0,r=n.length;i<r;i++){const s=n[i];t.shapes.push(s.uuid)}else t.shapes.push(n.uuid);return t.options=Object.assign({},e),e.extrudePath!==void 0&&(t.options.extrudePath=e.extrudePath.toJSON()),t}class zf extends ja{constructor(e=1,t=0){const i=(1+Math.sqrt(5))/2,r=[-1,i,0,1,i,0,-1,-i,0,1,-i,0,0,-1,i,0,1,i,0,-1,-i,0,1,-i,i,0,-1,i,0,1,-i,0,-1,-i,0,1],s=[0,11,5,0,5,1,0,1,7,0,7,10,0,10,11,1,5,9,5,11,4,11,10,2,10,7,6,7,1,8,3,9,4,3,4,2,3,2,6,3,6,8,3,8,9,4,9,5,2,4,11,6,2,10,8,6,7,9,8,1];super(r,s,e,t),this.type="IcosahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new zf(e.radius,e.detail)}}class Gf extends ja{constructor(e=1,t=0){const i=[1,0,0,-1,0,0,0,1,0,0,-1,0,0,0,1,0,0,-1],r=[0,2,4,0,4,3,0,3,5,0,5,2,1,2,5,1,5,3,1,3,4,1,4,2];super(i,r,e,t),this.type="OctahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new Gf(e.radius,e.detail)}}class AA extends Tt{constructor(e=.5,t=1,i=32,r=1,s=0,o=Math.PI*2){super(),this.type="RingGeometry",this.parameters={innerRadius:e,outerRadius:t,thetaSegments:i,phiSegments:r,thetaStart:s,thetaLength:o},i=Math.max(3,i),r=Math.max(1,r);const a=[],l=[],c=[],h=[];let f=e;const d=(t-e)/r,m=new N,g=new we;for(let E=0;E<=r;E++){for(let C=0;C<=i;C++){const S=s+C/i*o;m.x=f*Math.cos(S),m.y=f*Math.sin(S),l.push(m.x,m.y,m.z),c.push(0,0,1),g.x=(m.x/t+1)/2,g.y=(m.y/t+1)/2,h.push(g.x,g.y)}f+=d}for(let E=0;E<r;E++){const C=E*(i+1);for(let S=0;S<i;S++){const v=S+C,y=v,w=v+i+1,x=v+i+2,k=v+1;a.push(y,w,k),a.push(w,x,k)}}this.setIndex(a),this.setAttribute("position",new ot(l,3)),this.setAttribute("normal",new ot(c,3)),this.setAttribute("uv",new ot(h,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new AA(e.innerRadius,e.outerRadius,e.thetaSegments,e.phiSegments,e.thetaStart,e.thetaLength)}}class yA extends Tt{constructor(e=new Gl([new we(0,.5),new we(-.5,-.5),new we(.5,-.5)]),t=12){super(),this.type="ShapeGeometry",this.parameters={shapes:e,curveSegments:t};const i=[],r=[],s=[],o=[];let a=0,l=0;if(Array.isArray(e)===!1)c(e);else for(let h=0;h<e.length;h++)c(e[h]),this.addGroup(a,l,h),a+=l,l=0;this.setIndex(i),this.setAttribute("position",new ot(r,3)),this.setAttribute("normal",new ot(s,3)),this.setAttribute("uv",new ot(o,2));function c(h){const f=r.length/3,d=h.extractPoints(t);let m=d.shape;const g=d.holes;eo.isClockWise(m)===!1&&(m=m.reverse());for(let C=0,S=g.length;C<S;C++){const v=g[C];eo.isClockWise(v)===!0&&(g[C]=v.reverse())}const E=eo.triangulateShape(m,g);for(let C=0,S=g.length;C<S;C++){const v=g[C];m=m.concat(v)}for(let C=0,S=m.length;C<S;C++){const v=m[C];r.push(v.x,v.y,0),s.push(0,0,1),o.push(v.x,v.y)}for(let C=0,S=E.length;C<S;C++){const v=E[C],y=v[0]+f,w=v[1]+f,x=v[2]+f;i.push(y,w,x),l+=3}}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}toJSON(){const e=super.toJSON(),t=this.parameters.shapes;return A5(t,e)}static fromJSON(e,t){const i=[];for(let r=0,s=e.shapes.length;r<s;r++){const o=t[e.shapes[r]];i.push(o)}return new yA(i,e.curveSegments)}}function A5(n,e){if(e.shapes=[],Array.isArray(n))for(let t=0,i=n.length;t<i;t++){const r=n[t];e.shapes.push(r.uuid)}else e.shapes.push(n.uuid);return e}class Vf extends Tt{constructor(e=1,t=32,i=16,r=0,s=Math.PI*2,o=0,a=Math.PI){super(),this.type="SphereGeometry",this.parameters={radius:e,widthSegments:t,heightSegments:i,phiStart:r,phiLength:s,thetaStart:o,thetaLength:a},t=Math.max(3,Math.floor(t)),i=Math.max(2,Math.floor(i));const l=Math.min(o+a,Math.PI);let c=0;const h=[],f=new N,d=new N,m=[],g=[],E=[],C=[];for(let S=0;S<=i;S++){const v=[],y=S/i;let w=0;S===0&&o===0?w=.5/t:S===i&&l===Math.PI&&(w=-.5/t);for(let x=0;x<=t;x++){const k=x/t;f.x=-e*Math.cos(r+k*s)*Math.sin(o+y*a),f.y=e*Math.cos(o+y*a),f.z=e*Math.sin(r+k*s)*Math.sin(o+y*a),g.push(f.x,f.y,f.z),d.copy(f).normalize(),E.push(d.x,d.y,d.z),C.push(k+w,1-y),v.push(c++)}h.push(v)}for(let S=0;S<i;S++)for(let v=0;v<t;v++){const y=h[S][v+1],w=h[S][v],x=h[S+1][v],k=h[S+1][v+1];(S!==0||o>0)&&m.push(y,w,k),(S!==i-1||l<Math.PI)&&m.push(w,x,k)}this.setIndex(m),this.setAttribute("position",new ot(g,3)),this.setAttribute("normal",new ot(E,3)),this.setAttribute("uv",new ot(C,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new Vf(e.radius,e.widthSegments,e.heightSegments,e.phiStart,e.phiLength,e.thetaStart,e.thetaLength)}}class EA extends ja{constructor(e=1,t=0){const i=[1,1,1,-1,-1,1,-1,1,-1,1,-1,-1],r=[2,1,0,0,3,2,1,3,0,2,3,1];super(i,r,e,t),this.type="TetrahedronGeometry",this.parameters={radius:e,detail:t}}static fromJSON(e){return new EA(e.radius,e.detail)}}class CA extends Tt{constructor(e=1,t=.4,i=12,r=48,s=Math.PI*2){super(),this.type="TorusGeometry",this.parameters={radius:e,tube:t,radialSegments:i,tubularSegments:r,arc:s},i=Math.floor(i),r=Math.floor(r);const o=[],a=[],l=[],c=[],h=new N,f=new N,d=new N;for(let m=0;m<=i;m++)for(let g=0;g<=r;g++){const E=g/r*s,C=m/i*Math.PI*2;f.x=(e+t*Math.cos(C))*Math.cos(E),f.y=(e+t*Math.cos(C))*Math.sin(E),f.z=t*Math.sin(C),a.push(f.x,f.y,f.z),h.x=e*Math.cos(E),h.y=e*Math.sin(E),d.subVectors(f,h).normalize(),l.push(d.x,d.y,d.z),c.push(g/r),c.push(m/i)}for(let m=1;m<=i;m++)for(let g=1;g<=r;g++){const E=(r+1)*m+g-1,C=(r+1)*(m-1)+g-1,S=(r+1)*(m-1)+g,v=(r+1)*m+g;o.push(E,C,v),o.push(C,S,v)}this.setIndex(o),this.setAttribute("position",new ot(a,3)),this.setAttribute("normal",new ot(l,3)),this.setAttribute("uv",new ot(c,2))}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new CA(e.radius,e.tube,e.radialSegments,e.tubularSegments,e.arc)}}class vA extends Tt{constructor(e=1,t=.4,i=64,r=8,s=2,o=3){super(),this.type="TorusKnotGeometry",this.parameters={radius:e,tube:t,tubularSegments:i,radialSegments:r,p:s,q:o},i=Math.floor(i),r=Math.floor(r);const a=[],l=[],c=[],h=[],f=new N,d=new N,m=new N,g=new N,E=new N,C=new N,S=new N;for(let y=0;y<=i;++y){const w=y/i*s*Math.PI*2;v(w,s,o,e,m),v(w+.01,s,o,e,g),C.subVectors(g,m),S.addVectors(g,m),E.crossVectors(C,S),S.crossVectors(E,C),E.normalize(),S.normalize();for(let x=0;x<=r;++x){const k=x/r*Math.PI*2,I=-t*Math.cos(k),R=t*Math.sin(k);f.x=m.x+(I*S.x+R*E.x),f.y=m.y+(I*S.y+R*E.y),f.z=m.z+(I*S.z+R*E.z),l.push(f.x,f.y,f.z),d.subVectors(f,m).normalize(),c.push(d.x,d.y,d.z),h.push(y/i),h.push(x/r)}}for(let y=1;y<=i;y++)for(let w=1;w<=r;w++){const x=(r+1)*(y-1)+(w-1),k=(r+1)*y+(w-1),I=(r+1)*y+w,R=(r+1)*(y-1)+w;a.push(x,k,R),a.push(k,I,R)}this.setIndex(a),this.setAttribute("position",new ot(l,3)),this.setAttribute("normal",new ot(c,3)),this.setAttribute("uv",new ot(h,2));function v(y,w,x,k,I){const R=Math.cos(y),T=Math.sin(y),L=x/w*y,O=Math.cos(L);I.x=k*(2+O)*.5*R,I.y=k*(2+O)*T*.5,I.z=k*Math.sin(L)*.5}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}static fromJSON(e){return new vA(e.radius,e.tube,e.tubularSegments,e.radialSegments,e.p,e.q)}}class UA extends Tt{constructor(e=new yw(new N(-1,-1,0),new N(-1,1,0),new N(1,1,0)),t=64,i=1,r=8,s=!1){super(),this.type="TubeGeometry",this.parameters={path:e,tubularSegments:t,radius:i,radialSegments:r,closed:s};const o=e.computeFrenetFrames(t,s);this.tangents=o.tangents,this.normals=o.normals,this.binormals=o.binormals;const a=new N,l=new N,c=new we;let h=new N;const f=[],d=[],m=[],g=[];E(),this.setIndex(g),this.setAttribute("position",new ot(f,3)),this.setAttribute("normal",new ot(d,3)),this.setAttribute("uv",new ot(m,2));function E(){for(let y=0;y<t;y++)C(y);C(s===!1?t:0),v(),S()}function C(y){h=e.getPointAt(y/t,h);const w=o.normals[y],x=o.binormals[y];for(let k=0;k<=r;k++){const I=k/r*Math.PI*2,R=Math.sin(I),T=-Math.cos(I);l.x=T*w.x+R*x.x,l.y=T*w.y+R*x.y,l.z=T*w.z+R*x.z,l.normalize(),d.push(l.x,l.y,l.z),a.x=h.x+i*l.x,a.y=h.y+i*l.y,a.z=h.z+i*l.z,f.push(a.x,a.y,a.z)}}function S(){for(let y=1;y<=t;y++)for(let w=1;w<=r;w++){const x=(r+1)*(y-1)+(w-1),k=(r+1)*y+(w-1),I=(r+1)*y+w,R=(r+1)*(y-1)+w;g.push(x,k,R),g.push(k,I,R)}}function v(){for(let y=0;y<=t;y++)for(let w=0;w<=r;w++)c.x=y/t,c.y=w/r,m.push(c.x,c.y)}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}toJSON(){const e=super.toJSON();return e.path=this.parameters.path.toJSON(),e}static fromJSON(e){return new UA(new yg[e.path.type]().fromJSON(e.path),e.tubularSegments,e.radius,e.radialSegments,e.closed)}}class KR extends Tt{constructor(e=null){if(super(),this.type="WireframeGeometry",this.parameters={geometry:e},e!==null){const t=[],i=new Set,r=new N,s=new N;if(e.index!==null){const o=e.attributes.position,a=e.index;let l=e.groups;l.length===0&&(l=[{start:0,count:a.count,materialIndex:0}]);for(let c=0,h=l.length;c<h;++c){const f=l[c],d=f.start,m=f.count;for(let g=d,E=d+m;g<E;g+=3)for(let C=0;C<3;C++){const S=a.getX(g+C),v=a.getX(g+(C+1)%3);r.fromBufferAttribute(o,S),s.fromBufferAttribute(o,v),g1(r,s,i)===!0&&(t.push(r.x,r.y,r.z),t.push(s.x,s.y,s.z))}}}else{const o=e.attributes.position;for(let a=0,l=o.count/3;a<l;a++)for(let c=0;c<3;c++){const h=3*a+c,f=3*a+(c+1)%3;r.fromBufferAttribute(o,h),s.fromBufferAttribute(o,f),g1(r,s,i)===!0&&(t.push(r.x,r.y,r.z),t.push(s.x,s.y,s.z))}}this.setAttribute("position",new ot(t,3))}}copy(e){return super.copy(e),this.parameters=Object.assign({},e.parameters),this}}function g1(n,e,t){const i=`${n.x},${n.y},${n.z}-${e.x},${e.y},${e.z}`,r=`${e.x},${e.y},${e.z}-${n.x},${n.y},${n.z}`;return t.has(i)===!0||t.has(r)===!0?!1:(t.add(i),t.add(r),!0)}var A1=Object.freeze({__proto__:null,BoxGeometry:fc,CapsuleGeometry:pA,CircleGeometry:fA,ConeGeometry:dA,CylinderGeometry:uh,DodecahedronGeometry:mA,EdgesGeometry:JR,ExtrudeGeometry:gA,IcosahedronGeometry:zf,LatheGeometry:Hf,OctahedronGeometry:Gf,PlaneGeometry:Qf,PolyhedronGeometry:ja,RingGeometry:AA,ShapeGeometry:yA,SphereGeometry:Vf,TetrahedronGeometry:EA,TorusGeometry:CA,TorusKnotGeometry:vA,TubeGeometry:UA,WireframeGeometry:KR});class RR extends ti{constructor(e){super(),this.isShadowMaterial=!0,this.type="ShadowMaterial",this.color=new ze(0),this.transparent=!0,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.color.copy(e.color),this.fog=e.fog,this}}class DR extends Ls{constructor(e){super(e),this.isRawShaderMaterial=!0,this.type="RawShaderMaterial"}}class qf extends ti{constructor(e){super(),this.isMeshStandardMaterial=!0,this.defines={STANDARD:""},this.type="MeshStandardMaterial",this.color=new ze(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 ze(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Za,this.normalScale=new we(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.roughnessMap=null,this.metalnessMap=null,this.alphaMap=null,this.envMap=null,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.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}}class uo extends qf{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 we(1,1),this.clearcoatNormalMap=null,this.ior=1.5,Object.defineProperty(this,"reflectivity",{get:function(){return Hn(2.5*(this.ior-1)/(this.ior+1),0,1)},set:function(t){this.ior=(1+.4*t)/(1-.4*t)}}),this.iridescenceMap=null,this.iridescenceIOR=1.3,this.iridescenceThicknessRange=[100,400],this.iridescenceThicknessMap=null,this.sheenColor=new ze(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 ze(1,1,1),this.specularIntensity=1,this.specularIntensityMap=null,this.specularColor=new ze(1,1,1),this.specularColorMap=null,this._anisotropy=0,this._clearcoat=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 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.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}}class Dp extends ti{constructor(e){super(),this.isMeshPhongMaterial=!0,this.type="MeshPhongMaterial",this.color=new ze(16777215),this.specular=new ze(1118481),this.shininess=30,this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ze(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Za,this.normalScale=new we(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.combine=bf,this.reflectivity=1,this.refractionRatio=.98,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.color.copy(e.color),this.specular.copy(e.specular),this.shininess=e.shininess,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.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,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.flatShading=e.flatShading,this.fog=e.fog,this}}class bR extends ti{constructor(e){super(),this.isMeshToonMaterial=!0,this.defines={TOON:""},this.type="MeshToonMaterial",this.color=new ze(16777215),this.map=null,this.gradientMap=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ze(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Za,this.normalScale=new we(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,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.gradientMap=e.gradientMap,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.alphaMap=e.alphaMap,this.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.wireframeLinecap=e.wireframeLinecap,this.wireframeLinejoin=e.wireframeLinejoin,this.fog=e.fog,this}}class OR extends ti{constructor(e){super(),this.isMeshNormalMaterial=!0,this.type="MeshNormalMaterial",this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Za,this.normalScale=new we(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.wireframe=!1,this.wireframeLinewidth=1,this.flatShading=!1,this.setValues(e)}copy(e){return super.copy(e),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.wireframe=e.wireframe,this.wireframeLinewidth=e.wireframeLinewidth,this.flatShading=e.flatShading,this}}class Cw extends ti{constructor(e){super(),this.isMeshLambertMaterial=!0,this.type="MeshLambertMaterial",this.color=new ze(16777215),this.map=null,this.lightMap=null,this.lightMapIntensity=1,this.aoMap=null,this.aoMapIntensity=1,this.emissive=new ze(0),this.emissiveIntensity=1,this.emissiveMap=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Za,this.normalScale=new we(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.specularMap=null,this.alphaMap=null,this.envMap=null,this.combine=bf,this.reflectivity=1,this.refractionRatio=.98,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.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.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.specularMap=e.specularMap,this.alphaMap=e.alphaMap,this.envMap=e.envMap,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.flatShading=e.flatShading,this.fog=e.fog,this}}class FR extends ti{constructor(e){super(),this.isMeshMatcapMaterial=!0,this.defines={MATCAP:""},this.type="MeshMatcapMaterial",this.color=new ze(16777215),this.matcap=null,this.map=null,this.bumpMap=null,this.bumpScale=1,this.normalMap=null,this.normalMapType=Za,this.normalScale=new we(1,1),this.displacementMap=null,this.displacementScale=1,this.displacementBias=0,this.alphaMap=null,this.flatShading=!1,this.fog=!0,this.setValues(e)}copy(e){return super.copy(e),this.defines={MATCAP:""},this.color.copy(e.color),this.matcap=e.matcap,this.map=e.map,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.alphaMap=e.alphaMap,this.flatShading=e.flatShading,this.fog=e.fog,this}}class PR extends wi{constructor(e){super(),this.isLineDashedMaterial=!0,this.type="LineDashedMaterial",this.scale=1,this.dashSize=3,this.gapSize=1,this.setValues(e)}copy(e){return super.copy(e),this.scale=e.scale,this.dashSize=e.dashSize,this.gapSize=e.gapSize,this}}function bl(n,e,t){return!n||!t&&n.constructor===e?n:typeof e.BYTES_PER_ELEMENT=="number"?new e(n):Array.prototype.slice.call(n)}function NR(n){return ArrayBuffer.isView(n)&&!(n instanceof DataView)}function QR(n){function e(r,s){return n[r]-n[s]}const t=n.length,i=new Array(t);for(let r=0;r!==t;++r)i[r]=r;return i.sort(e),i}function cv(n,e,t){const i=n.length,r=new n.constructor(i);for(let s=0,o=0;o!==i;++s){const a=t[s]*e;for(let l=0;l!==e;++l)r[o++]=n[a+l]}return r}function vw(n,e,t,i){let r=1,s=n[0];for(;s!==void 0&&s[i]===void 0;)s=n[r++];if(s===void 0)return;let o=s[i];if(o!==void 0)if(Array.isArray(o))do o=s[i],o!==void 0&&(e.push(s.time),t.push.apply(t,o)),s=n[r++];while(s!==void 0);else if(o.toArray!==void 0)do o=s[i],o!==void 0&&(e.push(s.time),o.toArray(t,t.length)),s=n[r++];while(s!==void 0);else do o=s[i],o!==void 0&&(e.push(s.time),t.push(o)),s=n[r++];while(s!==void 0)}function y5(n,e,t,i,r=30){const s=n.clone();s.name=e;const o=[];for(let l=0;l<s.tracks.length;++l){const c=s.tracks[l],h=c.getValueSize(),f=[],d=[];for(let m=0;m<c.times.length;++m){const g=c.times[m]*r;if(!(g<t||g>=i)){f.push(c.times[m]);for(let E=0;E<h;++E)d.push(c.values[m*h+E])}}f.length!==0&&(c.times=bl(f,c.times.constructor),c.values=bl(d,c.values.constructor),o.push(c))}s.tracks=o;let a=1/0;for(let l=0;l<s.tracks.length;++l)a>s.tracks[l].times[0]&&(a=s.tracks[l].times[0]);for(let l=0;l<s.tracks.length;++l)s.tracks[l].shift(-1*a);return s.resetDuration(),s}function E5(n,e=0,t=n,i=30){i<=0&&(i=30);const r=t.tracks.length,s=e/i;for(let o=0;o<r;++o){const a=t.tracks[o],l=a.ValueTypeName;if(l==="bool"||l==="string")continue;const c=n.tracks.find(function(S){return S.name===a.name&&S.ValueTypeName===l});if(c===void 0)continue;let h=0;const f=a.getValueSize();a.createInterpolant.isInterpolantFactoryMethodGLTFCubicSpline&&(h=f/3);let d=0;const m=c.getValueSize();c.createInterpolant.isInterpolantFactoryMethodGLTFCubicSpline&&(d=m/3);const g=a.times.length-1;let E;if(s<=a.times[0]){const S=h,v=f-h;E=a.values.slice(S,v)}else if(s>=a.times[g]){const S=g*f+h,v=S+f-h;E=a.values.slice(S,v)}else{const S=a.createInterpolant(),v=h,y=f-h;S.evaluate(s),E=S.resultBuffer.slice(v,y)}l==="quaternion"&&new zn().fromArray(E).normalize().conjugate().toArray(E);const C=c.times.length;for(let S=0;S<C;++S){const v=S*m+d;if(l==="quaternion")zn.multiplyQuaternionsFlat(c.values,v,E,0,c.values,v);else{const y=m-d*2;for(let w=0;w<y;++w)c.values[v+w]-=E[w]}}}return n.blendMode=XU,n}const C5={convertArray:bl,isTypedArray:NR,getKeyframeOrder:QR,sortedArray:cv,flattenJSON:vw,subclip:y5,makeClipAdditive:E5};class hh{constructor(e,t,i,r){this.parameterPositions=e,this._cachedIndex=0,this.resultBuffer=r!==void 0?r:new t.constructor(i),this.sampleValues=t,this.valueSize=i,this.settings=null,this.DefaultSettings_={}}evaluate(e){const t=this.parameterPositions;let i=this._cachedIndex,r=t[i],s=t[i-1];e:{t:{let o;n:{i:if(!(e<r)){for(let a=i+2;;){if(r===void 0){if(e<s)break i;return i=t.length,this._cachedIndex=i,this.copySampleValue_(i-1)}if(i===a)break;if(s=r,r=t[++i],e<r)break t}o=t.length;break n}if(!(e>=s)){const a=t[1];e<a&&(i=2,s=a);for(let l=i-2;;){if(s===void 0)return this._cachedIndex=0,this.copySampleValue_(0);if(i===l)break;if(r=s,s=t[--i-1],e>=s)break t}o=i,i=0;break n}break e}for(;i<o;){const a=i+o>>>1;e<t[a]?o=a:i=a+1}if(r=t[i],s=t[i-1],s===void 0)return this._cachedIndex=0,this.copySampleValue_(0);if(r===void 0)return i=t.length,this._cachedIndex=i,this.copySampleValue_(i-1)}this._cachedIndex=i,this.intervalChanged_(i,s,r)}return this.interpolate_(i,s,e,r)}getSettings_(){return this.settings||this.DefaultSettings_}copySampleValue_(e){const t=this.resultBuffer,i=this.sampleValues,r=this.valueSize,s=e*r;for(let o=0;o!==r;++o)t[o]=i[s+o];return t}interpolate_(){throw new Error("call to abstract method")}intervalChanged_(){}}class WR extends hh{constructor(e,t,i,r){super(e,t,i,r),this._weightPrev=-0,this._offsetPrev=-0,this._weightNext=-0,this._offsetNext=-0,this.DefaultSettings_={endingStart:Bl,endingEnd:Bl}}intervalChanged_(e,t,i){const r=this.parameterPositions;let s=e-2,o=e+1,a=r[s],l=r[o];if(a===void 0)switch(this.getSettings_().endingStart){case Kl:s=e,a=2*t-i;break;case cf:s=r.length-2,a=t+r[s]-r[s+1];break;default:s=e,a=i}if(l===void 0)switch(this.getSettings_().endingEnd){case Kl:o=e,l=2*i-t;break;case cf:o=1,l=i+r[1]-r[0];break;default:o=e-1,l=t}const c=(i-t)*.5,h=this.valueSize;this._weightPrev=c/(t-a),this._weightNext=c/(l-i),this._offsetPrev=s*h,this._offsetNext=o*h}interpolate_(e,t,i,r){const s=this.resultBuffer,o=this.sampleValues,a=this.valueSize,l=e*a,c=l-a,h=this._offsetPrev,f=this._offsetNext,d=this._weightPrev,m=this._weightNext,g=(i-t)/(r-t),E=g*g,C=E*g,S=-d*C+2*d*E-d*g,v=(1+d)*C+(-1.5-2*d)*E+(-.5+d)*g+1,y=(-1-m)*C+(1.5+m)*E+.5*g,w=m*C-m*E;for(let x=0;x!==a;++x)s[x]=S*o[h+x]+v*o[c+x]+y*o[l+x]+w*o[f+x];return s}}class Uw extends hh{constructor(e,t,i,r){super(e,t,i,r)}interpolate_(e,t,i,r){const s=this.resultBuffer,o=this.sampleValues,a=this.valueSize,l=e*a,c=l-a,h=(i-t)/(r-t),f=1-h;for(let d=0;d!==a;++d)s[d]=o[c+d]*f+o[l+d]*h;return s}}class HR extends hh{constructor(e,t,i,r){super(e,t,i,r)}interpolate_(e){return this.copySampleValue_(e-1)}}class Rs{constructor(e,t,i,r){if(e===void 0)throw new Error("THREE.KeyframeTrack: track name is undefined");if(t===void 0||t.length===0)throw new Error("THREE.KeyframeTrack: no keyframes in track named "+e);this.name=e,this.times=bl(t,this.TimeBufferType),this.values=bl(i,this.ValueBufferType),this.setInterpolation(r||this.DefaultInterpolation)}static toJSON(e){const t=e.constructor;let i;if(t.toJSON!==this.toJSON)i=t.toJSON(e);else{i={name:e.name,times:bl(e.times,Array),values:bl(e.values,Array)};const r=e.getInterpolation();r!==e.DefaultInterpolation&&(i.interpolation=r)}return i.type=e.ValueTypeName,i}InterpolantFactoryMethodDiscrete(e){return new HR(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodLinear(e){return new Uw(this.times,this.values,this.getValueSize(),e)}InterpolantFactoryMethodSmooth(e){return new WR(this.times,this.values,this.getValueSize(),e)}setInterpolation(e){let t;switch(e){case Vu:t=this.InterpolantFactoryMethodDiscrete;break;case tc:t=this.InterpolantFactoryMethodLinear;break;case PS:t=this.InterpolantFactoryMethodSmooth;break}if(t===void 0){const i="unsupported interpolation for "+this.ValueTypeName+" keyframe track named "+this.name;if(this.createInterpolant===void 0)if(e!==this.DefaultInterpolation)this.setInterpolation(this.DefaultInterpolation);else throw new Error(i);return this}return this.createInterpolant=t,this}getInterpolation(){switch(this.createInterpolant){case this.InterpolantFactoryMethodDiscrete:return Vu;case this.InterpolantFactoryMethodLinear:return tc;case this.InterpolantFactoryMethodSmooth:return PS}}getValueSize(){return this.values.length/this.times.length}shift(e){if(e!==0){const t=this.times;for(let i=0,r=t.length;i!==r;++i)t[i]+=e}return this}scale(e){if(e!==1){const t=this.times;for(let i=0,r=t.length;i!==r;++i)t[i]*=e}return this}trim(e,t){const i=this.times,r=i.length;let s=0,o=r-1;for(;s!==r&&i[s]<e;)++s;for(;o!==-1&&i[o]>t;)--o;if(++o,s!==0||o!==r){s>=o&&(o=Math.max(o,1),s=o-1);const a=this.getValueSize();this.times=i.slice(s,o),this.values=this.values.slice(s*a,o*a)}return this}validate(){let e=!0;const t=this.getValueSize();t-Math.floor(t)!==0&&(e=!1);const i=this.times,r=this.values,s=i.length;s===0&&(e=!1);let o=null;for(let a=0;a!==s;a++){const l=i[a];if(typeof l=="number"&&isNaN(l)){e=!1;break}if(o!==null&&o>l){e=!1;break}o=l}if(r!==void 0&&NR(r))for(let a=0,l=r.length;a!==l;++a){const c=r[a];if(isNaN(c)){e=!1;break}}return e}optimize(){const e=this.times.slice(),t=this.values.slice(),i=this.getValueSize(),r=this.getInterpolation()===PS,s=e.length-1;let o=1;for(let a=1;a<s;++a){let l=!1;const c=e[a],h=e[a+1];if(c!==h&&(a!==1||c!==e[0]))if(r)l=!0;else{const f=a*i,d=f-i,m=f+i;for(let g=0;g!==i;++g){const E=t[f+g];if(E!==t[d+g]||E!==t[m+g]){l=!0;break}}}if(l){if(a!==o){e[o]=e[a];const f=a*i,d=o*i;for(let m=0;m!==i;++m)t[d+m]=t[f+m]}++o}}if(s>0){e[o]=e[s];for(let a=s*i,l=o*i,c=0;c!==i;++c)t[l+c]=t[a+c];++o}return o!==e.length?(this.times=e.slice(0,o),this.values=t.slice(0,o*i)):(this.times=e,this.values=t),this}clone(){const e=this.times.slice(),t=this.values.slice(),i=this.constructor,r=new i(this.name,e,t);return r.createInterpolant=this.createInterpolant,r}}Rs.prototype.TimeBufferType=Float32Array;Rs.prototype.ValueBufferType=Float32Array;Rs.prototype.DefaultInterpolation=tc;class dc extends Rs{}dc.prototype.ValueTypeName="bool";dc.prototype.ValueBufferType=Array;dc.prototype.DefaultInterpolation=Vu;dc.prototype.InterpolantFactoryMethodLinear=void 0;dc.prototype.InterpolantFactoryMethodSmooth=void 0;class ww extends Rs{}ww.prototype.ValueTypeName="color";class ic extends Rs{}ic.prototype.ValueTypeName="number";class zR extends hh{constructor(e,t,i,r){super(e,t,i,r)}interpolate_(e,t,i,r){const s=this.resultBuffer,o=this.sampleValues,a=this.valueSize,l=(i-t)/(r-t);let c=e*a;for(let h=c+a;c!==h;c+=4)zn.slerpFlat(s,0,o,c-a,o,c,l);return s}}class Ho extends Rs{InterpolantFactoryMethodLinear(e){return new zR(this.times,this.values,this.getValueSize(),e)}}Ho.prototype.ValueTypeName="quaternion";Ho.prototype.DefaultInterpolation=tc;Ho.prototype.InterpolantFactoryMethodSmooth=void 0;class mc extends Rs{}mc.prototype.ValueTypeName="string";mc.prototype.ValueBufferType=Array;mc.prototype.DefaultInterpolation=Vu;mc.prototype.InterpolantFactoryMethodLinear=void 0;mc.prototype.InterpolantFactoryMethodSmooth=void 0;class rc extends Rs{}rc.prototype.ValueTypeName="vector";class sc{constructor(e,t=-1,i,r=tA){this.name=e,this.tracks=i,this.duration=t,this.blendMode=r,this.uuid=Br(),this.duration<0&&this.resetDuration()}static parse(e){const t=[],i=e.tracks,r=1/(e.fps||1);for(let o=0,a=i.length;o!==a;++o)t.push(U5(i[o]).scale(r));const s=new this(e.name,e.duration,t,e.blendMode);return s.uuid=e.uuid,s}static toJSON(e){const t=[],i=e.tracks,r={name:e.name,duration:e.duration,tracks:t,uuid:e.uuid,blendMode:e.blendMode};for(let s=0,o=i.length;s!==o;++s)t.push(Rs.toJSON(i[s]));return r}static CreateFromMorphTargetSequence(e,t,i,r){const s=t.length,o=[];for(let a=0;a<s;a++){let l=[],c=[];l.push((a+s-1)%s,a,(a+1)%s),c.push(0,1,0);const h=QR(l);l=cv(l,1,h),c=cv(c,1,h),!r&&l[0]===0&&(l.push(s),c.push(c[0])),o.push(new ic(".morphTargetInfluences["+t[a].name+"]",l,c).scale(1/i))}return new this(e,-1,o)}static findByName(e,t){let i=e;if(!Array.isArray(e)){const r=e;i=r.geometry&&r.geometry.animations||r.animations}for(let r=0;r<i.length;r++)if(i[r].name===t)return i[r];return null}static CreateClipsFromMorphTargetSequences(e,t,i){const r={},s=/^([\w-]*?)([\d]+)$/;for(let a=0,l=e.length;a<l;a++){const c=e[a],h=c.name.match(s);if(h&&h.length>1){const f=h[1];let d=r[f];d||(r[f]=d=[]),d.push(c)}}const o=[];for(const a in r)o.push(this.CreateFromMorphTargetSequence(a,r[a],t,i));return o}static parseAnimation(e,t){if(!e)return null;const i=function(f,d,m,g,E){if(m.length!==0){const C=[],S=[];vw(m,C,S,g),C.length!==0&&E.push(new f(d,C,S))}},r=[],s=e.name||"default",o=e.fps||30,a=e.blendMode;let l=e.length||-1;const c=e.hierarchy||[];for(let f=0;f<c.length;f++){const d=c[f].keys;if(!(!d||d.length===0))if(d[0].morphTargets){const m={};let g;for(g=0;g<d.length;g++)if(d[g].morphTargets)for(let E=0;E<d[g].morphTargets.length;E++)m[d[g].morphTargets[E]]=-1;for(const E in m){const C=[],S=[];for(let v=0;v!==d[g].morphTargets.length;++v){const y=d[g];C.push(y.time),S.push(y.morphTarget===E?1:0)}r.push(new ic(".morphTargetInfluence["+E+"]",C,S))}l=m.length*o}else{const m=".bones["+t[f].name+"]";i(rc,m+".position",d,"pos",r),i(Ho,m+".quaternion",d,"rot",r),i(rc,m+".scale",d,"scl",r)}}return r.length===0?null:new this(s,l,r,a)}resetDuration(){const e=this.tracks;let t=0;for(let i=0,r=e.length;i!==r;++i){const s=this.tracks[i];t=Math.max(t,s.times[s.times.length-1])}return this.duration=t,this}trim(){for(let e=0;e<this.tracks.length;e++)this.tracks[e].trim(0,this.duration);return this}validate(){let e=!0;for(let t=0;t<this.tracks.length;t++)e=e&&this.tracks[t].validate();return e}optimize(){for(let e=0;e<this.tracks.length;e++)this.tracks[e].optimize();return this}clone(){const e=[];for(let t=0;t<this.tracks.length;t++)e.push(this.tracks[t].clone());return new this.constructor(this.name,this.duration,e,this.blendMode)}toJSON(){return this.constructor.toJSON(this)}}function v5(n){switch(n.toLowerCase()){case"scalar":case"double":case"float":case"number":case"integer":return ic;case"vector":case"vector2":case"vector3":case"vector4":return rc;case"color":return ww;case"quaternion":return Ho;case"bool":case"boolean":return dc;case"string":return mc}throw new Error("THREE.KeyframeTrack: Unsupported typeName: "+n)}function U5(n){if(n.type===void 0)throw new Error("THREE.KeyframeTrack: track type undefined, can not parse");const e=v5(n.type);if(n.times===void 0){const t=[],i=[];vw(n.keys,t,i,"value"),n.times=t,n.values=i}return e.parse!==void 0?e.parse(n):new e(n.name,n.times,n.values,n.interpolation)}const oc={enabled:!1,files:{},add:function(n,e){this.enabled!==!1&&(this.files[n]=e)},get:function(n){if(this.enabled!==!1)return this.files[n]},remove:function(n){delete this.files[n]},clear:function(){this.files={}}};class Mw{constructor(e,t,i){const r=this;let s=!1,o=0,a=0,l;const c=[];this.onStart=void 0,this.onLoad=e,this.onProgress=t,this.onError=i,this.itemStart=function(h){a++,s===!1&&r.onStart!==void 0&&r.onStart(h,o,a),s=!0},this.itemEnd=function(h){o++,r.onProgress!==void 0&&r.onProgress(h,o,a),o===a&&(s=!1,r.onLoad!==void 0&&r.onLoad())},this.itemError=function(h){r.onError!==void 0&&r.onError(h)},this.resolveURL=function(h){return l?l(h):h},this.setURLModifier=function(h){return l=h,this},this.addHandler=function(h,f){return c.push(h,f),this},this.removeHandler=function(h){const f=c.indexOf(h);return f!==-1&&c.splice(f,2),this},this.getHandler=function(h){for(let f=0,d=c.length;f<d;f+=2){const m=c[f],g=c[f+1];if(m.global&&(m.lastIndex=0),m.test(h))return g}return null}}}const GR=new Mw;class Mi{constructor(e){this.manager=e!==void 0?e:GR,this.crossOrigin="anonymous",this.withCredentials=!1,this.path="",this.resourcePath="",this.requestHeader={}}load(){}loadAsync(e,t){const i=this;return new Promise(function(r,s){i.load(e,r,t,s)})}parse(){}setCrossOrigin(e){return this.crossOrigin=e,this}setWithCredentials(e){return this.withCredentials=e,this}setPath(e){return this.path=e,this}setResourcePath(e){return this.resourcePath=e,this}setRequestHeader(e){return this.requestHeader=e,this}}Mi.DEFAULT_MATERIAL_NAME="__DEFAULT";const wo={};class w5 extends Error{constructor(e,t){super(e),this.response=t}}class yr extends Mi{constructor(e){super(e)}load(e,t,i,r){e===void 0&&(e=""),this.path!==void 0&&(e=this.path+e),e=this.manager.resolveURL(e);const s=oc.get(e);if(s!==void 0)return this.manager.itemStart(e),setTimeout(()=>{t&&t(s),this.manager.itemEnd(e)},0),s;if(wo[e]!==void 0){wo[e].push({onLoad:t,onProgress:i,onError:r});return}wo[e]=[],wo[e].push({onLoad:t,onProgress:i,onError:r});const o=new Request(e,{headers:new 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i=0;i<e.length;i++){const r=sc.parse(e[i]);t.push(r)}return t}}class k5 extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=this,o=[],a=new uA,l=new yr(this.manager);l.setPath(this.path),l.setResponseType("arraybuffer"),l.setRequestHeader(this.requestHeader),l.setWithCredentials(s.withCredentials);let c=0;function h(f){l.load(e[f],function(d){const m=s.parse(d,!0);o[f]={width:m.width,height:m.height,format:m.format,mipmaps:m.mipmaps},c+=1,c===6&&(m.mipmapCount===1&&(a.minFilter=pn),a.image=o,a.format=m.format,a.needsUpdate=!0,t&&t(a))},i,r)}if(Array.isArray(e))for(let f=0,d=e.length;f<d;++f)h(f);else l.load(e,function(f){const d=s.parse(f,!0);if(d.isCubemap){const m=d.mipmaps.length/d.mipmapCount;for(let g=0;g<m;g++){o[g]={mipmaps:[]};for(let E=0;E<d.mipmapCount;E++)o[g].mipmaps.push(d.mipmaps[g*d.mipmapCount+E]),o[g].format=d.format,o[g].width=d.width,o[g].height=d.height}a.image=o}else a.image.width=d.width,a.image.height=d.height,a.mipmaps=d.mipmaps;d.mipmapCount===1&&(a.minFilter=pn),a.format=d.format,a.needsUpdate=!0,t&&t(a)},i,r);return a}}class Ef extends Mi{constructor(e){super(e)}load(e,t,i,r){this.path!==void 0&&(e=this.path+e),e=this.manager.resolveURL(e);const s=this,o=oc.get(e);if(o!==void 0)return s.manager.itemStart(e),setTimeout(function(){t&&t(o),s.manager.itemEnd(e)},0),o;const a=df("img");function l(){h(),oc.add(e,this),t&&t(this),s.manager.itemEnd(e)}function c(f){h(),r&&r(f),s.manager.itemError(e),s.manager.itemEnd(e)}function h(){a.removeEventListener("load",l,!1),a.removeEventListener("error",c,!1)}return a.addEventListener("load",l,!1),a.addEventListener("error",c,!1),e.slice(0,5)!=="data:"&&this.crossOrigin!==void 0&&(a.crossOrigin=this.crossOrigin),s.manager.itemStart(e),a.src=e,a}}class VR extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=new Pf;s.colorSpace=si;const o=new Ef(this.manager);o.setCrossOrigin(this.crossOrigin),o.setPath(this.path);let a=0;function l(c){o.load(e[c],function(h){s.images[c]=h,a++,a===6&&(s.needsUpdate=!0,t&&t(s))},void 0,r)}for(let c=0;c<e.length;++c)l(c);return s}}class kw extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=this,o=new zl,a=new yr(this.manager);return a.setResponseType("arraybuffer"),a.setRequestHeader(this.requestHeader),a.setPath(this.path),a.setWithCredentials(s.withCredentials),a.load(e,function(l){let c;try{c=s.parse(l)}catch(h){if(r!==void 0)r(h);else return}c.image!==void 0?o.image=c.image:c.data!==void 0&&(o.image.width=c.width,o.image.height=c.height,o.image.data=c.data),o.wrapS=c.wrapS!==void 0?c.wrapS:oi,o.wrapT=c.wrapT!==void 0?c.wrapT:oi,o.magFilter=c.magFilter!==void 0?c.magFilter:pn,o.minFilter=c.minFilter!==void 0?c.minFilter:pn,o.anisotropy=c.anisotropy!==void 0?c.anisotropy:1,c.colorSpace!==void 0?o.colorSpace=c.colorSpace:c.encoding!==void 0&&(o.encoding=c.encoding),c.flipY!==void 0&&(o.flipY=c.flipY),c.format!==void 0&&(o.format=c.format),c.type!==void 0&&(o.type=c.type),c.mipmaps!==void 0&&(o.mipmaps=c.mipmaps,o.minFilter=ro),c.mipmapCount===1&&(o.minFilter=pn),c.generateMipmaps!==void 0&&(o.generateMipmaps=c.generateMipmaps),o.needsUpdate=!0,t&&t(o,c)},i,r),o}}class ph extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=new fn,o=new Ef(this.manager);return o.setCrossOrigin(this.crossOrigin),o.setPath(this.path),o.load(e,function(a){s.image=a,s.needsUpdate=!0,t!==void 0&&t(s)},i,r),s}}class Xa extends Wt{constructor(e,t=1){super(),this.isLight=!0,this.type="Light",this.color=new ze(e),this.intensity=t}dispose(){}copy(e,t){return super.copy(e,t),this.color.copy(e.color),this.intensity=e.intensity,this}toJSON(e){const t=super.toJSON(e);return t.object.color=this.color.getHex(),t.object.intensity=this.intensity,this.groundColor!==void 0&&(t.object.groundColor=this.groundColor.getHex()),this.distance!==void 0&&(t.object.distance=this.distance),this.angle!==void 0&&(t.object.angle=this.angle),this.decay!==void 0&&(t.object.decay=this.decay),this.penumbra!==void 0&&(t.object.penumbra=this.penumbra),this.shadow!==void 0&&(t.object.shadow=this.shadow.toJSON()),t}}class qR extends Xa{constructor(e,t,i){super(e,i),this.isHemisphereLight=!0,this.type="HemisphereLight",this.position.copy(Wt.DEFAULT_UP),this.updateMatrix(),this.groundColor=new ze(t)}copy(e,t){return super.copy(e,t),this.groundColor.copy(e.groundColor),this}}const V0=new tt,y1=new N,E1=new N;class xw{constructor(e){this.camera=e,this.bias=0,this.normalBias=0,this.radius=1,this.blurSamples=8,this.mapSize=new we(512,512),this.map=null,this.mapPass=null,this.matrix=new tt,this.autoUpdate=!0,this.needsUpdate=!1,this._frustum=new Nf,this._frameExtents=new we(1,1),this._viewportCount=1,this._viewports=[new $t(0,0,1,1)]}getViewportCount(){return this._viewportCount}getFrustum(){return this._frustum}updateMatrices(e){const t=this.camera,i=this.matrix;y1.setFromMatrixPosition(e.matrixWorld),t.position.copy(y1),E1.setFromMatrixPosition(e.target.matrixWorld),t.lookAt(E1),t.updateMatrixWorld(),V0.multiplyMatrices(t.projectionMatrix,t.matrixWorldInverse),this._frustum.setFromProjectionMatrix(V0),i.set(.5,0,0,.5,0,.5,0,.5,0,0,.5,.5,0,0,0,1),i.multiply(V0)}getViewport(e){return this._viewports[e]}getFrameExtents(){return this._frameExtents}dispose(){this.map&&this.map.dispose(),this.mapPass&&this.mapPass.dispose()}copy(e){return this.camera=e.camera.clone(),this.bias=e.bias,this.radius=e.radius,this.mapSize.copy(e.mapSize),this}clone(){return new this.constructor().copy(this)}toJSON(){const e={};return this.bias!==0&&(e.bias=this.bias),this.normalBias!==0&&(e.normalBias=this.normalBias),this.radius!==1&&(e.radius=this.radius),(this.mapSize.x!==512||this.mapSize.y!==512)&&(e.mapSize=this.mapSize.toArray()),e.camera=this.camera.toJSON(!1).object,delete e.camera.matrix,e}}class x5 extends xw{constructor(){super(new xn(50,1,.5,500)),this.isSpotLightShadow=!0,this.focus=1}updateMatrices(e){const t=this.camera,i=Yu*2*e.angle*this.focus,r=this.mapSize.width/this.mapSize.height,s=e.distance||t.far;(i!==t.fov||r!==t.aspect||s!==t.far)&&(t.fov=i,t.aspect=r,t.far=s,t.updateProjectionMatrix()),super.updateMatrices(e)}copy(e){return super.copy(e),this.focus=e.focus,this}}class wA extends Xa{constructor(e,t,i=0,r=Math.PI/3,s=0,o=2){super(e,t),this.isSpotLight=!0,this.type="SpotLight",this.position.copy(Wt.DEFAULT_UP),this.updateMatrix(),this.target=new Wt,this.distance=i,this.angle=r,this.penumbra=s,this.decay=o,this.map=null,this.shadow=new x5}get power(){return this.intensity*Math.PI}set power(e){this.intensity=e/Math.PI}dispose(){this.shadow.dispose()}copy(e,t){return super.copy(e,t),this.distance=e.distance,this.angle=e.angle,this.penumbra=e.penumbra,this.decay=e.decay,this.target=e.target.clone(),this.shadow=e.shadow.clone(),this}}const C1=new tt,rp=new N,q0=new N;class T5 extends xw{constructor(){super(new xn(90,1,.5,500)),this.isPointLightShadow=!0,this._frameExtents=new we(4,2),this._viewportCount=6,this._viewports=[new $t(2,1,1,1),new $t(0,1,1,1),new $t(3,1,1,1),new $t(1,1,1,1),new $t(3,0,1,1),new $t(1,0,1,1)],this._cubeDirections=[new N(1,0,0),new N(-1,0,0),new N(0,0,1),new N(0,0,-1),new N(0,1,0),new N(0,-1,0)],this._cubeUps=[new N(0,1,0),new N(0,1,0),new N(0,1,0),new N(0,1,0),new N(0,0,1),new N(0,0,-1)]}updateMatrices(e,t=0){const i=this.camera,r=this.matrix,s=e.distance||i.far;s!==i.far&&(i.far=s,i.updateProjectionMatrix()),rp.setFromMatrixPosition(e.matrixWorld),i.position.copy(rp),q0.copy(i.position),q0.add(this._cubeDirections[t]),i.up.copy(this._cubeUps[t]),i.lookAt(q0),i.updateMatrixWorld(),r.makeTranslation(-rp.x,-rp.y,-rp.z),C1.multiplyMatrices(i.projectionMatrix,i.matrixWorldInverse),this._frustum.setFromProjectionMatrix(C1)}}class Cf extends Xa{constructor(e,t,i=0,r=2){super(e,t),this.isPointLight=!0,this.type="PointLight",this.distance=i,this.decay=r,this.shadow=new T5}get power(){return this.intensity*4*Math.PI}set power(e){this.intensity=e/(4*Math.PI)}dispose(){this.shadow.dispose()}copy(e,t){return super.copy(e,t),this.distance=e.distance,this.decay=e.decay,this.shadow=e.shadow.clone(),this}}class J5 extends xw{constructor(){super(new ws(-5,5,5,-5,.5,500)),this.isDirectionalLightShadow=!0}}class MA extends Xa{constructor(e,t){super(e,t),this.isDirectionalLight=!0,this.type="DirectionalLight",this.position.copy(Wt.DEFAULT_UP),this.updateMatrix(),this.target=new Wt,this.shadow=new J5}dispose(){this.shadow.dispose()}copy(e){return super.copy(e),this.target=e.target.clone(),this.shadow=e.shadow.clone(),this}}class Tw extends Xa{constructor(e,t){super(e,t),this.isAmbientLight=!0,this.type="AmbientLight"}}class YR extends Xa{constructor(e,t,i=10,r=10){super(e,t),this.isRectAreaLight=!0,this.type="RectAreaLight",this.width=i,this.height=r}get power(){return this.intensity*this.width*this.height*Math.PI}set power(e){this.intensity=e/(this.width*this.height*Math.PI)}copy(e){return super.copy(e),this.width=e.width,this.height=e.height,this}toJSON(e){const t=super.toJSON(e);return t.object.width=this.width,t.object.height=this.height,t}}class ZR{constructor(){this.isSphericalHarmonics3=!0,this.coefficients=[];for(let e=0;e<9;e++)this.coefficients.push(new N)}set(e){for(let t=0;t<9;t++)this.coefficients[t].copy(e[t]);return this}zero(){for(let e=0;e<9;e++)this.coefficients[e].set(0,0,0);return this}getAt(e,t){const i=e.x,r=e.y,s=e.z,o=this.coefficients;return t.copy(o[0]).multiplyScalar(.282095),t.addScaledVector(o[1],.488603*r),t.addScaledVector(o[2],.488603*s),t.addScaledVector(o[3],.488603*i),t.addScaledVector(o[4],1.092548*(i*r)),t.addScaledVector(o[5],1.092548*(r*s)),t.addScaledVector(o[6],.315392*(3*s*s-1)),t.addScaledVector(o[7],1.092548*(i*s)),t.addScaledVector(o[8],.546274*(i*i-r*r)),t}getIrradianceAt(e,t){const i=e.x,r=e.y,s=e.z,o=this.coefficients;return t.copy(o[0]).multiplyScalar(.886227),t.addScaledVector(o[1],2*.511664*r),t.addScaledVector(o[2],2*.511664*s),t.addScaledVector(o[3],2*.511664*i),t.addScaledVector(o[4],2*.429043*i*r),t.addScaledVector(o[5],2*.429043*r*s),t.addScaledVector(o[6],.743125*s*s-.247708),t.addScaledVector(o[7],2*.429043*i*s),t.addScaledVector(o[8],.429043*(i*i-r*r)),t}add(e){for(let t=0;t<9;t++)this.coefficients[t].add(e.coefficients[t]);return this}addScaledSH(e,t){for(let i=0;i<9;i++)this.coefficients[i].addScaledVector(e.coefficients[i],t);return this}scale(e){for(let t=0;t<9;t++)this.coefficients[t].multiplyScalar(e);return this}lerp(e,t){for(let i=0;i<9;i++)this.coefficients[i].lerp(e.coefficients[i],t);return this}equals(e){for(let t=0;t<9;t++)if(!this.coefficients[t].equals(e.coefficients[t]))return!1;return!0}copy(e){return this.set(e.coefficients)}clone(){return new this.constructor().copy(this)}fromArray(e,t=0){const i=this.coefficients;for(let r=0;r<9;r++)i[r].fromArray(e,t+r*3);return this}toArray(e=[],t=0){const i=this.coefficients;for(let r=0;r<9;r++)i[r].toArray(e,t+r*3);return e}static getBasisAt(e,t){const i=e.x,r=e.y,s=e.z;t[0]=.282095,t[1]=.488603*r,t[2]=.488603*s,t[3]=.488603*i,t[4]=1.092548*i*r,t[5]=1.092548*r*s,t[6]=.315392*(3*s*s-1),t[7]=1.092548*i*s,t[8]=.546274*(i*i-r*r)}}class jR extends Xa{constructor(e=new ZR,t=1){super(void 0,t),this.isLightProbe=!0,this.sh=e}copy(e){return super.copy(e),this.sh.copy(e.sh),this}fromJSON(e){return this.intensity=e.intensity,this.sh.fromArray(e.sh),this}toJSON(e){const t=super.toJSON(e);return t.object.sh=this.sh.toArray(),t}}class kA extends Mi{constructor(e){super(e),this.textures={}}load(e,t,i,r){const s=this,o=new yr(s.manager);o.setPath(s.path),o.setRequestHeader(s.requestHeader),o.setWithCredentials(s.withCredentials),o.load(e,function(a){try{t(s.parse(JSON.parse(a)))}catch(l){r&&r(l),s.manager.itemError(e)}},i,r)}parse(e){const t=this.textures;function i(s){return t[s],t[s]}const r=kA.createMaterialFromType(e.type);if(e.uuid!==void 0&&(r.uuid=e.uuid),e.name!==void 0&&(r.name=e.name),e.color!==void 0&&r.color!==void 0&&r.color.setHex(e.color),e.roughness!==void 0&&(r.roughness=e.roughness),e.metalness!==void 0&&(r.metalness=e.metalness),e.sheen!==void 0&&(r.sheen=e.sheen),e.sheenColor!==void 0&&(r.sheenColor=new ze().setHex(e.sheenColor)),e.sheenRoughness!==void 0&&(r.sheenRoughness=e.sheenRoughness),e.emissive!==void 0&&r.emissive!==void 0&&r.emissive.setHex(e.emissive),e.specular!==void 0&&r.specular!==void 0&&r.specular.setHex(e.specular),e.specularIntensity!==void 0&&(r.specularIntensity=e.specularIntensity),e.specularColor!==void 0&&r.specularColor!==void 0&&r.specularColor.setHex(e.specularColor),e.shininess!==void 0&&(r.shininess=e.shininess),e.clearcoat!==void 0&&(r.clearcoat=e.clearcoat),e.clearcoatRoughness!==void 0&&(r.clearcoatRoughness=e.clearcoatRoughness),e.iridescence!==void 0&&(r.iridescence=e.iridescence),e.iridescenceIOR!==void 0&&(r.iridescenceIOR=e.iridescenceIOR),e.iridescenceThicknessRange!==void 0&&(r.iridescenceThicknessRange=e.iridescenceThicknessRange),e.transmission!==void 0&&(r.transmission=e.transmission),e.thickness!==void 0&&(r.thickness=e.thickness),e.attenuationDistance!==void 0&&(r.attenuationDistance=e.attenuationDistance),e.attenuationColor!==void 0&&r.attenuationColor!==void 0&&r.attenuationColor.setHex(e.attenuationColor),e.anisotropy!==void 0&&(r.anisotropy=e.anisotropy),e.anisotropyRotation!==void 0&&(r.anisotropyRotation=e.anisotropyRotation),e.fog!==void 0&&(r.fog=e.fog),e.flatShading!==void 0&&(r.flatShading=e.flatShading),e.blending!==void 0&&(r.blending=e.blending),e.combine!==void 0&&(r.combine=e.combine),e.side!==void 0&&(r.side=e.side),e.shadowSide!==void 0&&(r.shadowSide=e.shadowSide),e.opacity!==void 0&&(r.opacity=e.opacity),e.transparent!==void 0&&(r.transparent=e.transparent),e.alphaTest!==void 0&&(r.alphaTest=e.alphaTest),e.alphaHash!==void 0&&(r.alphaHash=e.alphaHash),e.depthFunc!==void 0&&(r.depthFunc=e.depthFunc),e.depthTest!==void 0&&(r.depthTest=e.depthTest),e.depthWrite!==void 0&&(r.depthWrite=e.depthWrite),e.colorWrite!==void 0&&(r.colorWrite=e.colorWrite),e.blendSrc!==void 0&&(r.blendSrc=e.blendSrc),e.blendDst!==void 0&&(r.blendDst=e.blendDst),e.blendEquation!==void 0&&(r.blendEquation=e.blendEquation),e.blendSrcAlpha!==void 0&&(r.blendSrcAlpha=e.blendSrcAlpha),e.blendDstAlpha!==void 0&&(r.blendDstAlpha=e.blendDstAlpha),e.blendEquationAlpha!==void 0&&(r.blendEquationAlpha=e.blendEquationAlpha),e.blendColor!==void 0&&r.blendColor!==void 0&&r.blendColor.setHex(e.blendColor),e.blendAlpha!==void 0&&(r.blendAlpha=e.blendAlpha),e.stencilWriteMask!==void 0&&(r.stencilWriteMask=e.stencilWriteMask),e.stencilFunc!==void 0&&(r.stencilFunc=e.stencilFunc),e.stencilRef!==void 0&&(r.stencilRef=e.stencilRef),e.stencilFuncMask!==void 0&&(r.stencilFuncMask=e.stencilFuncMask),e.stencilFail!==void 0&&(r.stencilFail=e.stencilFail),e.stencilZFail!==void 0&&(r.stencilZFail=e.stencilZFail),e.stencilZPass!==void 0&&(r.stencilZPass=e.stencilZPass),e.stencilWrite!==void 0&&(r.stencilWrite=e.stencilWrite),e.wireframe!==void 0&&(r.wireframe=e.wireframe),e.wireframeLinewidth!==void 0&&(r.wireframeLinewidth=e.wireframeLinewidth),e.wireframeLinecap!==void 0&&(r.wireframeLinecap=e.wireframeLinecap),e.wireframeLinejoin!==void 0&&(r.wireframeLinejoin=e.wireframeLinejoin),e.rotation!==void 0&&(r.rotation=e.rotation),e.linewidth!==void 0&&(r.linewidth=e.linewidth),e.dashSize!==void 0&&(r.dashSize=e.dashSize),e.gapSize!==void 0&&(r.gapSize=e.gapSize),e.scale!==void 0&&(r.scale=e.scale),e.polygonOffset!==void 0&&(r.polygonOffset=e.polygonOffset),e.polygonOffsetFactor!==void 0&&(r.polygonOffsetFactor=e.polygonOffsetFactor),e.polygonOffsetUnits!==void 0&&(r.polygonOffsetUnits=e.polygonOffsetUnits),e.dithering!==void 0&&(r.dithering=e.dithering),e.alphaToCoverage!==void 0&&(r.alphaToCoverage=e.alphaToCoverage),e.premultipliedAlpha!==void 0&&(r.premultipliedAlpha=e.premultipliedAlpha),e.forceSinglePass!==void 0&&(r.forceSinglePass=e.forceSinglePass),e.visible!==void 0&&(r.visible=e.visible),e.toneMapped!==void 0&&(r.toneMapped=e.toneMapped),e.userData!==void 0&&(r.userData=e.userData),e.vertexColors!==void 0&&(typeof e.vertexColors=="number"?r.vertexColors=e.vertexColors>0:r.vertexColors=e.vertexColors),e.uniforms!==void 0)for(const s in e.uniforms){const o=e.uniforms[s];switch(r.uniforms[s]={},o.type){case"t":r.uniforms[s].value=i(o.value);break;case"c":r.uniforms[s].value=new ze().setHex(o.value);break;case"v2":r.uniforms[s].value=new we().fromArray(o.value);break;case"v3":r.uniforms[s].value=new N().fromArray(o.value);break;case"v4":r.uniforms[s].value=new $t().fromArray(o.value);break;case"m3":r.uniforms[s].value=new Ot().fromArray(o.value);break;case"m4":r.uniforms[s].value=new tt().fromArray(o.value);break;default:r.uniforms[s].value=o.value}}if(e.defines!==void 0&&(r.defines=e.defines),e.vertexShader!==void 0&&(r.vertexShader=e.vertexShader),e.fragmentShader!==void 0&&(r.fragmentShader=e.fragmentShader),e.glslVersion!==void 0&&(r.glslVersion=e.glslVersion),e.extensions!==void 0)for(const s in e.extensions)r.extensions[s]=e.extensions[s];if(e.lights!==void 0&&(r.lights=e.lights),e.clipping!==void 0&&(r.clipping=e.clipping),e.size!==void 0&&(r.size=e.size),e.sizeAttenuation!==void 0&&(r.sizeAttenuation=e.sizeAttenuation),e.map!==void 0&&(r.map=i(e.map)),e.matcap!==void 0&&(r.matcap=i(e.matcap)),e.alphaMap!==void 0&&(r.alphaMap=i(e.alphaMap)),e.bumpMap!==void 0&&(r.bumpMap=i(e.bumpMap)),e.bumpScale!==void 0&&(r.bumpScale=e.bumpScale),e.normalMap!==void 0&&(r.normalMap=i(e.normalMap)),e.normalMapType!==void 0&&(r.normalMapType=e.normalMapType),e.normalScale!==void 0){let s=e.normalScale;Array.isArray(s)===!1&&(s=[s,s]),r.normalScale=new we().fromArray(s)}return e.displacementMap!==void 0&&(r.displacementMap=i(e.displacementMap)),e.displacementScale!==void 0&&(r.displacementScale=e.displacementScale),e.displacementBias!==void 0&&(r.displacementBias=e.displacementBias),e.roughnessMap!==void 0&&(r.roughnessMap=i(e.roughnessMap)),e.metalnessMap!==void 0&&(r.metalnessMap=i(e.metalnessMap)),e.emissiveMap!==void 0&&(r.emissiveMap=i(e.emissiveMap)),e.emissiveIntensity!==void 0&&(r.emissiveIntensity=e.emissiveIntensity),e.specularMap!==void 0&&(r.specularMap=i(e.specularMap)),e.specularIntensityMap!==void 0&&(r.specularIntensityMap=i(e.specularIntensityMap)),e.specularColorMap!==void 0&&(r.specularColorMap=i(e.specularColorMap)),e.envMap!==void 0&&(r.envMap=i(e.envMap)),e.envMapIntensity!==void 0&&(r.envMapIntensity=e.envMapIntensity),e.reflectivity!==void 0&&(r.reflectivity=e.reflectivity),e.refractionRatio!==void 0&&(r.refractionRatio=e.refractionRatio),e.lightMap!==void 0&&(r.lightMap=i(e.lightMap)),e.lightMapIntensity!==void 0&&(r.lightMapIntensity=e.lightMapIntensity),e.aoMap!==void 0&&(r.aoMap=i(e.aoMap)),e.aoMapIntensity!==void 0&&(r.aoMapIntensity=e.aoMapIntensity),e.gradientMap!==void 0&&(r.gradientMap=i(e.gradientMap)),e.clearcoatMap!==void 0&&(r.clearcoatMap=i(e.clearcoatMap)),e.clearcoatRoughnessMap!==void 0&&(r.clearcoatRoughnessMap=i(e.clearcoatRoughnessMap)),e.clearcoatNormalMap!==void 0&&(r.clearcoatNormalMap=i(e.clearcoatNormalMap)),e.clearcoatNormalScale!==void 0&&(r.clearcoatNormalScale=new we().fromArray(e.clearcoatNormalScale)),e.iridescenceMap!==void 0&&(r.iridescenceMap=i(e.iridescenceMap)),e.iridescenceThicknessMap!==void 0&&(r.iridescenceThicknessMap=i(e.iridescenceThicknessMap)),e.transmissionMap!==void 0&&(r.transmissionMap=i(e.transmissionMap)),e.thicknessMap!==void 0&&(r.thicknessMap=i(e.thicknessMap)),e.anisotropyMap!==void 0&&(r.anisotropyMap=i(e.anisotropyMap)),e.sheenColorMap!==void 0&&(r.sheenColorMap=i(e.sheenColorMap)),e.sheenRoughnessMap!==void 0&&(r.sheenRoughnessMap=i(e.sheenRoughnessMap)),r}setTextures(e){return this.textures=e,this}static createMaterialFromType(e){const t={ShadowMaterial:RR,SpriteMaterial:hw,RawShaderMaterial:DR,ShaderMaterial:Ls,PointsMaterial:cA,MeshPhysicalMaterial:uo,MeshStandardMaterial:qf,MeshPhongMaterial:Dp,MeshToonMaterial:bR,MeshNormalMaterial:OR,MeshLambertMaterial:Cw,MeshDepthMaterial:lw,MeshDistanceMaterial:cw,MeshBasicMaterial:Ir,MeshMatcapMaterial:FR,LineDashedMaterial:PR,LineBasicMaterial:wi,Material:ti};return new t[e]}}class Kr{static decodeText(e){if(typeof TextDecoder<"u")return new TextDecoder().decode(e);let t="";for(let i=0,r=e.length;i<r;i++)t+=String.fromCharCode(e[i]);try{return decodeURIComponent(escape(t))}catch{return t}}static extractUrlBase(e){const t=e.lastIndexOf("/");return t===-1?"./":e.slice(0,t+1)}static resolveURL(e,t){return typeof e!="string"||e===""?"":(/^https?:\/\//i.test(t)&&/^\//.test(e)&&(t=t.replace(/(^https?:\/\/[^\/]+).*/i,"$1")),/^(https?:)?\/\//i.test(e)||/^data:.*,.*$/i.test(e)||/^blob:.*$/i.test(e)?e:t+e)}}class XR extends Tt{constructor(){super(),this.isInstancedBufferGeometry=!0,this.type="InstancedBufferGeometry",this.instanceCount=1/0}copy(e){return super.copy(e),this.instanceCount=e.instanceCount,this}toJSON(){const e=super.toJSON();return e.instanceCount=this.instanceCount,e.isInstancedBufferGeometry=!0,e}}class _R extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=this,o=new yr(s.manager);o.setPath(s.path),o.setRequestHeader(s.requestHeader),o.setWithCredentials(s.withCredentials),o.load(e,function(a){try{t(s.parse(JSON.parse(a)))}catch(l){r&&r(l),s.manager.itemError(e)}},i,r)}parse(e){const t={},i={};function r(m,g){if(t[g]!==void 0)return t[g];const C=m.interleavedBuffers[g],S=s(m,C.buffer),v=yu(C.type,S),y=new Wf(v,C.stride);return y.uuid=C.uuid,t[g]=y,y}function s(m,g){if(i[g]!==void 0)return i[g];const C=m.arrayBuffers[g],S=new Uint32Array(C).buffer;return i[g]=S,S}const o=e.isInstancedBufferGeometry?new XR:new Tt,a=e.data.index;if(a!==void 0){const m=yu(a.type,a.array);o.setIndex(new Xt(m,1))}const l=e.data.attributes;for(const m in l){const g=l[m];let E;if(g.isInterleavedBufferAttribute){const C=r(e.data,g.data);E=new Na(C,g.itemSize,g.offset,g.normalized)}else{const C=yu(g.type,g.array),S=g.isInstancedBufferAttribute?Xu:Xt;E=new S(C,g.itemSize,g.normalized)}g.name!==void 0&&(E.name=g.name),g.usage!==void 0&&E.setUsage(g.usage),o.setAttribute(m,E)}const c=e.data.morphAttributes;if(c)for(const m in c){const g=c[m],E=[];for(let C=0,S=g.length;C<S;C++){const v=g[C];let y;if(v.isInterleavedBufferAttribute){const w=r(e.data,v.data);y=new Na(w,v.itemSize,v.offset,v.normalized)}else{const w=yu(v.type,v.array);y=new Xt(w,v.itemSize,v.normalized)}v.name!==void 0&&(y.name=v.name),E.push(y)}o.morphAttributes[m]=E}e.data.morphTargetsRelative&&(o.morphTargetsRelative=!0);const f=e.data.groups||e.data.drawcalls||e.data.offsets;if(f!==void 0)for(let m=0,g=f.length;m!==g;++m){const E=f[m];o.addGroup(E.start,E.count,E.materialIndex)}const d=e.data.boundingSphere;if(d!==void 0){const m=new N;d.center!==void 0&&m.fromArray(d.center),o.boundingSphere=new vi(m,d.radius)}return e.name&&(o.name=e.name),e.userData&&(o.userData=e.userData),o}}class I5 extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=this,o=this.path===""?Kr.extractUrlBase(e):this.path;this.resourcePath=this.resourcePath||o;const a=new yr(this.manager);a.setPath(this.path),a.setRequestHeader(this.requestHeader),a.setWithCredentials(this.withCredentials),a.load(e,function(l){let c=null;try{c=JSON.parse(l)}catch(f){r!==void 0&&r(f);return}const h=c.metadata;if(h===void 0||h.type===void 0||h.type.toLowerCase()==="geometry"){r!==void 0&&r(new Error("THREE.ObjectLoader: Can't load "+e));return}s.parse(c,t)},i,r)}async loadAsync(e,t){const i=this,r=this.path===""?Kr.extractUrlBase(e):this.path;this.resourcePath=this.resourcePath||r;const s=new yr(this.manager);s.setPath(this.path),s.setRequestHeader(this.requestHeader),s.setWithCredentials(this.withCredentials);const o=await s.loadAsync(e,t),a=JSON.parse(o),l=a.metadata;if(l===void 0||l.type===void 0||l.type.toLowerCase()==="geometry")throw new Error("THREE.ObjectLoader: Can't load "+e);return await i.parseAsync(a)}parse(e,t){const i=this.parseAnimations(e.animations),r=this.parseShapes(e.shapes),s=this.parseGeometries(e.geometries,r),o=this.parseImages(e.images,function(){t!==void 0&&t(c)}),a=this.parseTextures(e.textures,o),l=this.parseMaterials(e.materials,a),c=this.parseObject(e.object,s,l,a,i),h=this.parseSkeletons(e.skeletons,c);if(this.bindSkeletons(c,h),t!==void 0){let f=!1;for(const d in o)if(o[d].data instanceof HTMLImageElement){f=!0;break}f===!1&&t(c)}return c}async parseAsync(e){const t=this.parseAnimations(e.animations),i=this.parseShapes(e.shapes),r=this.parseGeometries(e.geometries,i),s=await this.parseImagesAsync(e.images),o=this.parseTextures(e.textures,s),a=this.parseMaterials(e.materials,o),l=this.parseObject(e.object,r,a,o,t),c=this.parseSkeletons(e.skeletons,l);return this.bindSkeletons(l,c),l}parseShapes(e){const t={};if(e!==void 0)for(let i=0,r=e.length;i<r;i++){const s=new Gl().fromJSON(e[i]);t[s.uuid]=s}return t}parseSkeletons(e,t){const i={},r={};if(t.traverse(function(s){s.isBone&&(r[s.uuid]=s)}),e!==void 0)for(let s=0,o=e.length;s<o;s++){const a=new ch().fromJSON(e[s],r);i[a.uuid]=a}return i}parseGeometries(e,t){const i={};if(e!==void 0){const r=new _R;for(let s=0,o=e.length;s<o;s++){let a;const l=e[s];switch(l.type){case"BufferGeometry":case"InstancedBufferGeometry":a=r.parse(l);break;default:l.type in A1&&(a=A1[l.type].fromJSON(l,t))}a.uuid=l.uuid,l.name!==void 0&&(a.name=l.name),l.userData!==void 0&&(a.userData=l.userData),i[l.uuid]=a}}return i}parseMaterials(e,t){const i={},r={};if(e!==void 0){const s=new kA;s.setTextures(t);for(let o=0,a=e.length;o<a;o++){const l=e[o];i[l.uuid]===void 0&&(i[l.uuid]=s.parse(l)),r[l.uuid]=i[l.uuid]}}return r}parseAnimations(e){const t={};if(e!==void 0)for(let i=0;i<e.length;i++){const r=e[i],s=sc.parse(r);t[s.uuid]=s}return t}parseImages(e,t){const i=this,r={};let s;function o(l){return i.manager.itemStart(l),s.load(l,function(){i.manager.itemEnd(l)},void 0,function(){i.manager.itemError(l),i.manager.itemEnd(l)})}function a(l){if(typeof l=="string"){const c=l,h=/^(\/\/)|([a-z]+:(\/\/)?)/i.test(c)?c:i.resourcePath+c;return o(h)}else return l.data?{data:yu(l.type,l.data),width:l.width,height:l.height}:null}if(e!==void 0&&e.length>0){const l=new Mw(t);s=new Ef(l),s.setCrossOrigin(this.crossOrigin);for(let c=0,h=e.length;c<h;c++){const f=e[c],d=f.url;if(Array.isArray(d)){const m=[];for(let g=0,E=d.length;g<E;g++){const C=d[g],S=a(C);S!==null&&(S instanceof HTMLImageElement?m.push(S):m.push(new zl(S.data,S.width,S.height)))}r[f.uuid]=new Rl(m)}else{const m=a(f.url);r[f.uuid]=new Rl(m)}}}return r}async parseImagesAsync(e){const t=this,i={};let r;async function s(o){if(typeof o=="string"){const a=o,l=/^(\/\/)|([a-z]+:(\/\/)?)/i.test(a)?a:t.resourcePath+a;return await r.loadAsync(l)}else return o.data?{data:yu(o.type,o.data),width:o.width,height:o.height}:null}if(e!==void 0&&e.length>0){r=new Ef(this.manager),r.setCrossOrigin(this.crossOrigin);for(let o=0,a=e.length;o<a;o++){const l=e[o],c=l.url;if(Array.isArray(c)){const h=[];for(let f=0,d=c.length;f<d;f++){const m=c[f],g=await s(m);g!==null&&(g instanceof HTMLImageElement?h.push(g):h.push(new zl(g.data,g.width,g.height)))}i[l.uuid]=new Rl(h)}else{const h=await s(l.url);i[l.uuid]=new Rl(h)}}}return i}parseTextures(e,t){function i(s,o){return typeof s=="number"?s:o[s]}const r={};if(e!==void 0)for(let s=0,o=e.length;s<o;s++){const a=e[s];a.image,t[a.image];const l=t[a.image],c=l.data;let h;Array.isArray(c)?(h=new Pf,c.length===6&&(h.needsUpdate=!0)):(c&&c.data?h=new zl:h=new fn,c&&(h.needsUpdate=!0)),h.source=l,h.uuid=a.uuid,a.name!==void 0&&(h.name=a.name),a.mapping!==void 0&&(h.mapping=i(a.mapping,L5)),a.channel!==void 0&&(h.channel=a.channel),a.offset!==void 0&&h.offset.fromArray(a.offset),a.repeat!==void 0&&h.repeat.fromArray(a.repeat),a.center!==void 0&&h.center.fromArray(a.center),a.rotation!==void 0&&(h.rotation=a.rotation),a.wrap!==void 0&&(h.wrapS=i(a.wrap[0],v1),h.wrapT=i(a.wrap[1],v1)),a.format!==void 0&&(h.format=a.format),a.internalFormat!==void 0&&(h.internalFormat=a.internalFormat),a.type!==void 0&&(h.type=a.type),a.colorSpace!==void 0&&(h.colorSpace=a.colorSpace),a.encoding!==void 0&&(h.encoding=a.encoding),a.minFilter!==void 0&&(h.minFilter=i(a.minFilter,U1)),a.magFilter!==void 0&&(h.magFilter=i(a.magFilter,U1)),a.anisotropy!==void 0&&(h.anisotropy=a.anisotropy),a.flipY!==void 0&&(h.flipY=a.flipY),a.generateMipmaps!==void 0&&(h.generateMipmaps=a.generateMipmaps),a.premultiplyAlpha!==void 0&&(h.premultiplyAlpha=a.premultiplyAlpha),a.unpackAlignment!==void 0&&(h.unpackAlignment=a.unpackAlignment),a.compareFunction!==void 0&&(h.compareFunction=a.compareFunction),a.userData!==void 0&&(h.userData=a.userData),r[a.uuid]=h}return r}parseObject(e,t,i,r,s){let o;function a(d){return t[d],t[d]}function l(d){if(d!==void 0){if(Array.isArray(d)){const m=[];for(let g=0,E=d.length;g<E;g++){const C=d[g];i[C],m.push(i[C])}return m}return i[d],i[d]}}function c(d){return r[d],r[d]}let h,f;switch(e.type){case"Scene":o=new mf,e.background!==void 0&&(Number.isInteger(e.background)?o.background=new ze(e.background):o.background=c(e.background)),e.environment!==void 0&&(o.environment=c(e.environment)),e.fog!==void 0&&(e.fog.type==="Fog"?o.fog=new aA(e.fog.color,e.fog.near,e.fog.far):e.fog.type==="FogExp2"&&(o.fog=new oA(e.fog.color,e.fog.density)),e.fog.name!==""&&(o.fog.name=e.fog.name)),e.backgroundBlurriness!==void 0&&(o.backgroundBlurriness=e.backgroundBlurriness),e.backgroundIntensity!==void 0&&(o.backgroundIntensity=e.backgroundIntensity);break;case"PerspectiveCamera":o=new xn(e.fov,e.aspect,e.near,e.far),e.focus!==void 0&&(o.focus=e.focus),e.zoom!==void 0&&(o.zoom=e.zoom),e.filmGauge!==void 0&&(o.filmGauge=e.filmGauge),e.filmOffset!==void 0&&(o.filmOffset=e.filmOffset),e.view!==void 0&&(o.view=Object.assign({},e.view));break;case"OrthographicCamera":o=new ws(e.left,e.right,e.top,e.bottom,e.near,e.far),e.zoom!==void 0&&(o.zoom=e.zoom),e.view!==void 0&&(o.view=Object.assign({},e.view));break;case"AmbientLight":o=new Tw(e.color,e.intensity);break;case"DirectionalLight":o=new MA(e.color,e.intensity);break;case"PointLight":o=new Cf(e.color,e.intensity,e.distance,e.decay);break;case"RectAreaLight":o=new YR(e.color,e.intensity,e.width,e.height);break;case"SpotLight":o=new wA(e.color,e.intensity,e.distance,e.angle,e.penumbra,e.decay);break;case"HemisphereLight":o=new qR(e.color,e.groundColor,e.intensity);break;case"LightProbe":o=new jR().fromJSON(e);break;case"SkinnedMesh":h=a(e.geometry),f=l(e.material),o=new lA(h,f),e.bindMode!==void 0&&(o.bindMode=e.bindMode),e.bindMatrix!==void 0&&o.bindMatrix.fromArray(e.bindMatrix),e.skeleton!==void 0&&(o.skeleton=e.skeleton);break;case"Mesh":h=a(e.geometry),f=l(e.material),o=new Gn(h,f);break;case"InstancedMesh":h=a(e.geometry),f=l(e.material);const d=e.count,m=e.instanceMatrix,g=e.instanceColor;o=new pw(h,f,d),o.instanceMatrix=new Xu(new Float32Array(m.array),16),g!==void 0&&(o.instanceColor=new Xu(new Float32Array(g.array),g.itemSize));break;case"BatchedMesh":h=a(e.geometry),f=l(e.material),o=new UR(e.maxGeometryCount,e.maxVertexCount,e.maxIndexCount,f),o.geometry=h,o.perObjectFrustumCulled=e.perObjectFrustumCulled,o.sortObjects=e.sortObjects,o._drawRanges=e.drawRanges,o._reservedRanges=e.reservedRanges,o._visibility=e.visibility,o._active=e.active,o._bounds=e.bounds.map(E=>{const C=new Pi;C.min.fromArray(E.boxMin),C.max.fromArray(E.boxMax);const S=new vi;return S.radius=E.sphereRadius,S.center.fromArray(E.sphereCenter),{boxInitialized:E.boxInitialized,box:C,sphereInitialized:E.sphereInitialized,sphere:S}}),o._maxGeometryCount=e.maxGeometryCount,o._maxVertexCount=e.maxVertexCount,o._maxIndexCount=e.maxIndexCount,o._geometryInitialized=e.geometryInitialized,o._geometryCount=e.geometryCount,o._matricesTexture=c(e.matricesTexture.uuid);break;case"LOD":o=new vR;break;case"Line":o=new oo(a(e.geometry),l(e.material));break;case"LineLoop":o=new fw(a(e.geometry),l(e.material));break;case"LineSegments":o=new Ks(a(e.geometry),l(e.material));break;case"PointCloud":case"Points":o=new dw(a(e.geometry),l(e.material));break;case"Sprite":o=new CR(l(e.material));break;case"Group":o=new Ms;break;case"Bone":o=new ju;break;default:o=new Wt}if(o.uuid=e.uuid,e.name!==void 0&&(o.name=e.name),e.matrix!==void 0?(o.matrix.fromArray(e.matrix),e.matrixAutoUpdate!==void 0&&(o.matrixAutoUpdate=e.matrixAutoUpdate),o.matrixAutoUpdate&&o.matrix.decompose(o.position,o.quaternion,o.scale)):(e.position!==void 0&&o.position.fromArray(e.position),e.rotation!==void 0&&o.rotation.fromArray(e.rotation),e.quaternion!==void 0&&o.quaternion.fromArray(e.quaternion),e.scale!==void 0&&o.scale.fromArray(e.scale)),e.up!==void 0&&o.up.fromArray(e.up),e.castShadow!==void 0&&(o.castShadow=e.castShadow),e.receiveShadow!==void 0&&(o.receiveShadow=e.receiveShadow),e.shadow&&(e.shadow.bias!==void 0&&(o.shadow.bias=e.shadow.bias),e.shadow.normalBias!==void 0&&(o.shadow.normalBias=e.shadow.normalBias),e.shadow.radius!==void 0&&(o.shadow.radius=e.shadow.radius),e.shadow.mapSize!==void 0&&o.shadow.mapSize.fromArray(e.shadow.mapSize),e.shadow.camera!==void 0&&(o.shadow.camera=this.parseObject(e.shadow.camera))),e.visible!==void 0&&(o.visible=e.visible),e.frustumCulled!==void 0&&(o.frustumCulled=e.frustumCulled),e.renderOrder!==void 0&&(o.renderOrder=e.renderOrder),e.userData!==void 0&&(o.userData=e.userData),e.layers!==void 0&&(o.layers.mask=e.layers),e.children!==void 0){const d=e.children;for(let m=0;m<d.length;m++)o.add(this.parseObject(d[m],t,i,r,s))}if(e.animations!==void 0){const d=e.animations;for(let m=0;m<d.length;m++){const g=d[m];o.animations.push(s[g])}}if(e.type==="LOD"){e.autoUpdate!==void 0&&(o.autoUpdate=e.autoUpdate);const d=e.levels;for(let m=0;m<d.length;m++){const g=d[m],E=o.getObjectByProperty("uuid",g.object);E!==void 0&&o.addLevel(E,g.distance,g.hysteresis)}}return o}bindSkeletons(e,t){Object.keys(t).length!==0&&e.traverse(function(i){if(i.isSkinnedMesh===!0&&i.skeleton!==void 0){const r=t[i.skeleton];r===void 0||i.bind(r,i.bindMatrix)}})}}const L5={UVMapping:_g,CubeReflectionMapping:no,CubeRefractionMapping:Pa,EquirectangularReflectionMapping:$l,EquirectangularRefractionMapping:af,CubeUVReflectionMapping:ah},v1={RepeatWrapping:io,ClampToEdgeWrapping:oi,MirroredRepeatWrapping:Gu},U1={NearestFilter:Wn,NearestMipmapNearestFilter:lf,NearestMipmapLinearFilter:Bu,LinearFilter:pn,LinearMipmapNearestFilter:$g,LinearMipmapLinearFilter:ro};class $R extends Mi{constructor(e){super(e),this.isImageBitmapLoader=!0,this.options={premultiplyAlpha:"none"}}setOptions(e){return this.options=e,this}load(e,t,i,r){e===void 0&&(e=""),this.path!==void 0&&(e=this.path+e),e=this.manager.resolveURL(e);const s=this,o=oc.get(e);if(o!==void 0)return s.manager.itemStart(e),setTimeout(function(){t&&t(o),s.manager.itemEnd(e)},0),o;const a={};a.credentials=this.crossOrigin==="anonymous"?"same-origin":"include",a.headers=this.requestHeader,fetch(e,a).then(function(l){return l.blob()}).then(function(l){return createImageBitmap(l,Object.assign(s.options,{colorSpaceConversion:"none"}))}).then(function(l){oc.add(e,l),t&&t(l),s.manager.itemEnd(e)}).catch(function(l){r&&r(l),s.manager.itemError(e),s.manager.itemEnd(e)}),s.manager.itemStart(e)}}let eS,Jw=class{static getContext(){return eS===void 0&&(eS=new(window.AudioContext||window.webkitAudioContext)),eS}static setContext(e){eS=e}};class B5 extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=this,o=new yr(this.manager);o.setResponseType("arraybuffer"),o.setPath(this.path),o.setRequestHeader(this.requestHeader),o.setWithCredentials(this.withCredentials),o.load(e,function(l){try{const c=l.slice(0);Jw.getContext().decodeAudioData(c,function(f){t(f)}).catch(a)}catch(c){a(c)}},i,r);function a(l){r&&r(l),s.manager.itemError(e)}}}const w1=new tt,M1=new tt,dl=new tt;class K5{constructor(){this.type="StereoCamera",this.aspect=1,this.eyeSep=.064,this.cameraL=new xn,this.cameraL.layers.enable(1),this.cameraL.matrixAutoUpdate=!1,this.cameraR=new xn,this.cameraR.layers.enable(2),this.cameraR.matrixAutoUpdate=!1,this._cache={focus:null,fov:null,aspect:null,near:null,far:null,zoom:null,eyeSep:null}}update(e){const t=this._cache;if(t.focus!==e.focus||t.fov!==e.fov||t.aspect!==e.aspect*this.aspect||t.near!==e.near||t.far!==e.far||t.zoom!==e.zoom||t.eyeSep!==this.eyeSep){t.focus=e.focus,t.fov=e.fov,t.aspect=e.aspect*this.aspect,t.near=e.near,t.far=e.far,t.zoom=e.zoom,t.eyeSep=this.eyeSep,dl.copy(e.projectionMatrix);const r=t.eyeSep/2,s=r*t.near/t.focus,o=t.near*Math.tan(Wl*t.fov*.5)/t.zoom;let a,l;M1.elements[12]=-r,w1.elements[12]=r,a=-o*t.aspect+s,l=o*t.aspect+s,dl.elements[0]=2*t.near/(l-a),dl.elements[8]=(l+a)/(l-a),this.cameraL.projectionMatrix.copy(dl),a=-o*t.aspect-s,l=o*t.aspect-s,dl.elements[0]=2*t.near/(l-a),dl.elements[8]=(l+a)/(l-a),this.cameraR.projectionMatrix.copy(dl)}this.cameraL.matrixWorld.copy(e.matrixWorld).multiply(M1),this.cameraR.matrixWorld.copy(e.matrixWorld).multiply(w1)}}class Iw{constructor(e=!0){this.autoStart=e,this.startTime=0,this.oldTime=0,this.elapsedTime=0,this.running=!1}start(){this.startTime=k1(),this.oldTime=this.startTime,this.elapsedTime=0,this.running=!0}stop(){this.getElapsedTime(),this.running=!1,this.autoStart=!1}getElapsedTime(){return this.getDelta(),this.elapsedTime}getDelta(){let e=0;if(this.autoStart&&!this.running)return this.start(),0;if(this.running){const t=k1();e=(t-this.oldTime)/1e3,this.oldTime=t,this.elapsedTime+=e}return e}}function k1(){return(typeof performance>"u"?Date:performance).now()}const ml=new N,x1=new zn,R5=new N,Sl=new N;class D5 extends Wt{constructor(){super(),this.type="AudioListener",this.context=Jw.getContext(),this.gain=this.context.createGain(),this.gain.connect(this.context.destination),this.filter=null,this.timeDelta=0,this._clock=new Iw}getInput(){return this.gain}removeFilter(){return this.filter!==null&&(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination),this.gain.connect(this.context.destination),this.filter=null),this}getFilter(){return this.filter}setFilter(e){return this.filter!==null?(this.gain.disconnect(this.filter),this.filter.disconnect(this.context.destination)):this.gain.disconnect(this.context.destination),this.filter=e,this.gain.connect(this.filter),this.filter.connect(this.context.destination),this}getMasterVolume(){return this.gain.gain.value}setMasterVolume(e){return this.gain.gain.setTargetAtTime(e,this.context.currentTime,.01),this}updateMatrixWorld(e){super.updateMatrixWorld(e);const t=this.context.listener,i=this.up;if(this.timeDelta=this._clock.getDelta(),this.matrixWorld.decompose(ml,x1,R5),Sl.set(0,0,-1).applyQuaternion(x1),t.positionX){const r=this.context.currentTime+this.timeDelta;t.positionX.linearRampToValueAtTime(ml.x,r),t.positionY.linearRampToValueAtTime(ml.y,r),t.positionZ.linearRampToValueAtTime(ml.z,r),t.forwardX.linearRampToValueAtTime(Sl.x,r),t.forwardY.linearRampToValueAtTime(Sl.y,r),t.forwardZ.linearRampToValueAtTime(Sl.z,r),t.upX.linearRampToValueAtTime(i.x,r),t.upY.linearRampToValueAtTime(i.y,r),t.upZ.linearRampToValueAtTime(i.z,r)}else t.setPosition(ml.x,ml.y,ml.z),t.setOrientation(Sl.x,Sl.y,Sl.z,i.x,i.y,i.z)}}let eD=class extends Wt{constructor(e){super(),this.type="Audio",this.listener=e,this.context=e.context,this.gain=this.context.createGain(),this.gain.connect(e.getInput()),this.autoplay=!1,this.buffer=null,this.detune=0,this.loop=!1,this.loopStart=0,this.loopEnd=0,this.offset=0,this.duration=void 0,this.playbackRate=1,this.isPlaying=!1,this.hasPlaybackControl=!0,this.source=null,this.sourceType="empty",this._startedAt=0,this._progress=0,this._connected=!1,this.filters=[]}getOutput(){return this.gain}setNodeSource(e){return this.hasPlaybackControl=!1,this.sourceType="audioNode",this.source=e,this.connect(),this}setMediaElementSource(e){return this.hasPlaybackControl=!1,this.sourceType="mediaNode",this.source=this.context.createMediaElementSource(e),this.connect(),this}setMediaStreamSource(e){return this.hasPlaybackControl=!1,this.sourceType="mediaStreamNode",this.source=this.context.createMediaStreamSource(e),this.connect(),this}setBuffer(e){return this.buffer=e,this.sourceType="buffer",this.autoplay&&this.play(),this}play(e=0){if(this.isPlaying===!0||this.hasPlaybackControl===!1)return;this._startedAt=this.context.currentTime+e;const t=this.context.createBufferSource();return t.buffer=this.buffer,t.loop=this.loop,t.loopStart=this.loopStart,t.loopEnd=this.loopEnd,t.onended=this.onEnded.bind(this),t.start(this._startedAt,this._progress+this.offset,this.duration),this.isPlaying=!0,this.source=t,this.setDetune(this.detune),this.setPlaybackRate(this.playbackRate),this.connect()}pause(){if(this.hasPlaybackControl!==!1)return this.isPlaying===!0&&(this._progress+=Math.max(this.context.currentTime-this._startedAt,0)*this.playbackRate,this.loop===!0&&(this._progress=this._progress%(this.duration||this.buffer.duration)),this.source.stop(),this.source.onended=null,this.isPlaying=!1),this}stop(){if(this.hasPlaybackControl!==!1)return this._progress=0,this.source!==null&&(this.source.stop(),this.source.onended=null),this.isPlaying=!1,this}connect(){if(this.filters.length>0){this.source.connect(this.filters[0]);for(let e=1,t=this.filters.length;e<t;e++)this.filters[e-1].connect(this.filters[e]);this.filters[this.filters.length-1].connect(this.getOutput())}else this.source.connect(this.getOutput());return this._connected=!0,this}disconnect(){if(this._connected!==!1){if(this.filters.length>0){this.source.disconnect(this.filters[0]);for(let e=1,t=this.filters.length;e<t;e++)this.filters[e-1].disconnect(this.filters[e]);this.filters[this.filters.length-1].disconnect(this.getOutput())}else this.source.disconnect(this.getOutput());return this._connected=!1,this}}getFilters(){return this.filters}setFilters(e){return e||(e=[]),this._connected===!0?(this.disconnect(),this.filters=e.slice(),this.connect()):this.filters=e.slice(),this}setDetune(e){if(this.detune=e,this.source.detune!==void 0)return this.isPlaying===!0&&this.source.detune.setTargetAtTime(this.detune,this.context.currentTime,.01),this}getDetune(){return this.detune}getFilter(){return this.getFilters()[0]}setFilter(e){return this.setFilters(e?[e]:[])}setPlaybackRate(e){if(this.hasPlaybackControl!==!1)return this.playbackRate=e,this.isPlaying===!0&&this.source.playbackRate.setTargetAtTime(this.playbackRate,this.context.currentTime,.01),this}getPlaybackRate(){return this.playbackRate}onEnded(){this.isPlaying=!1}getLoop(){return this.hasPlaybackControl===!1?!1:this.loop}setLoop(e){if(this.hasPlaybackControl!==!1)return this.loop=e,this.isPlaying===!0&&(this.source.loop=this.loop),this}setLoopStart(e){return this.loopStart=e,this}setLoopEnd(e){return this.loopEnd=e,this}getVolume(){return this.gain.gain.value}setVolume(e){return this.gain.gain.setTargetAtTime(e,this.context.currentTime,.01),this}};const gl=new N,T1=new zn,b5=new N,Al=new N;class O5 extends eD{constructor(e){super(e),this.panner=this.context.createPanner(),this.panner.panningModel="HRTF",this.panner.connect(this.gain)}connect(){super.connect(),this.panner.connect(this.gain)}disconnect(){super.disconnect(),this.panner.disconnect(this.gain)}getOutput(){return this.panner}getRefDistance(){return this.panner.refDistance}setRefDistance(e){return this.panner.refDistance=e,this}getRolloffFactor(){return this.panner.rolloffFactor}setRolloffFactor(e){return this.panner.rolloffFactor=e,this}getDistanceModel(){return this.panner.distanceModel}setDistanceModel(e){return this.panner.distanceModel=e,this}getMaxDistance(){return this.panner.maxDistance}setMaxDistance(e){return this.panner.maxDistance=e,this}setDirectionalCone(e,t,i){return this.panner.coneInnerAngle=e,this.panner.coneOuterAngle=t,this.panner.coneOuterGain=i,this}updateMatrixWorld(e){if(super.updateMatrixWorld(e),this.hasPlaybackControl===!0&&this.isPlaying===!1)return;this.matrixWorld.decompose(gl,T1,b5),Al.set(0,0,1).applyQuaternion(T1);const t=this.panner;if(t.positionX){const i=this.context.currentTime+this.listener.timeDelta;t.positionX.linearRampToValueAtTime(gl.x,i),t.positionY.linearRampToValueAtTime(gl.y,i),t.positionZ.linearRampToValueAtTime(gl.z,i),t.orientationX.linearRampToValueAtTime(Al.x,i),t.orientationY.linearRampToValueAtTime(Al.y,i),t.orientationZ.linearRampToValueAtTime(Al.z,i)}else t.setPosition(gl.x,gl.y,gl.z),t.setOrientation(Al.x,Al.y,Al.z)}}class F5{constructor(e,t=2048){this.analyser=e.context.createAnalyser(),this.analyser.fftSize=t,this.data=new Uint8Array(this.analyser.frequencyBinCount),e.getOutput().connect(this.analyser)}getFrequencyData(){return this.analyser.getByteFrequencyData(this.data),this.data}getAverageFrequency(){let e=0;const t=this.getFrequencyData();for(let i=0;i<t.length;i++)e+=t[i];return e/t.length}}class tD{constructor(e,t,i){this.binding=e,this.valueSize=i;let r,s,o;switch(t){case"quaternion":r=this._slerp,s=this._slerpAdditive,o=this._setAdditiveIdentityQuaternion,this.buffer=new Float64Array(i*6),this._workIndex=5;break;case"string":case"bool":r=this._select,s=this._select,o=this._setAdditiveIdentityOther,this.buffer=new Array(i*5);break;default:r=this._lerp,s=this._lerpAdditive,o=this._setAdditiveIdentityNumeric,this.buffer=new Float64Array(i*5)}this._mixBufferRegion=r,this._mixBufferRegionAdditive=s,this._setIdentity=o,this._origIndex=3,this._addIndex=4,this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,this.useCount=0,this.referenceCount=0}accumulate(e,t){const i=this.buffer,r=this.valueSize,s=e*r+r;let o=this.cumulativeWeight;if(o===0){for(let a=0;a!==r;++a)i[s+a]=i[a];o=t}else{o+=t;const a=t/o;this._mixBufferRegion(i,s,0,a,r)}this.cumulativeWeight=o}accumulateAdditive(e){const t=this.buffer,i=this.valueSize,r=i*this._addIndex;this.cumulativeWeightAdditive===0&&this._setIdentity(),this._mixBufferRegionAdditive(t,r,0,e,i),this.cumulativeWeightAdditive+=e}apply(e){const t=this.valueSize,i=this.buffer,r=e*t+t,s=this.cumulativeWeight,o=this.cumulativeWeightAdditive,a=this.binding;if(this.cumulativeWeight=0,this.cumulativeWeightAdditive=0,s<1){const l=t*this._origIndex;this._mixBufferRegion(i,r,l,1-s,t)}o>0&&this._mixBufferRegionAdditive(i,r,this._addIndex*t,1,t);for(let l=t,c=t+t;l!==c;++l)if(i[l]!==i[l+t]){a.setValue(i,r);break}}saveOriginalState(){const e=this.binding,t=this.buffer,i=this.valueSize,r=i*this._origIndex;e.getValue(t,r);for(let s=i,o=r;s!==o;++s)t[s]=t[r+s%i];this._setIdentity(),this.cumulativeWeight=0,this.cumulativeWeightAdditive=0}restoreOriginalState(){const e=this.valueSize*3;this.binding.setValue(this.buffer,e)}_setAdditiveIdentityNumeric(){const e=this._addIndex*this.valueSize,t=e+this.valueSize;for(let i=e;i<t;i++)this.buffer[i]=0}_setAdditiveIdentityQuaternion(){this._setAdditiveIdentityNumeric(),this.buffer[this._addIndex*this.valueSize+3]=1}_setAdditiveIdentityOther(){const e=this._origIndex*this.valueSize,t=this._addIndex*this.valueSize;for(let i=0;i<this.valueSize;i++)this.buffer[t+i]=this.buffer[e+i]}_select(e,t,i,r,s){if(r>=.5)for(let o=0;o!==s;++o)e[t+o]=e[i+o]}_slerp(e,t,i,r){zn.slerpFlat(e,t,e,t,e,i,r)}_slerpAdditive(e,t,i,r,s){const o=this._workIndex*s;zn.multiplyQuaternionsFlat(e,o,e,t,e,i),zn.slerpFlat(e,t,e,t,e,o,r)}_lerp(e,t,i,r,s){const o=1-r;for(let a=0;a!==s;++a){const l=t+a;e[l]=e[l]*o+e[i+a]*r}}_lerpAdditive(e,t,i,r,s){for(let o=0;o!==s;++o){const a=t+o;e[a]=e[a]+e[i+o]*r}}}const Lw="\\[\\]\\.:\\/",P5=new RegExp("["+Lw+"]","g"),Bw="[^"+Lw+"]",N5="[^"+Lw.replace("\\.","")+"]",Q5=/((?:WC+[\/:])*)/.source.replace("WC",Bw),W5=/(WCOD+)?/.source.replace("WCOD",N5),H5=/(?:\.(WC+)(?:\[(.+)\])?)?/.source.replace("WC",Bw),z5=/\.(WC+)(?:\[(.+)\])?/.source.replace("WC",Bw),G5=new RegExp("^"+Q5+W5+H5+z5+"$"),V5=["material","materials","bones","map"];class q5{constructor(e,t,i){const r=i||zt.parseTrackName(t);this._targetGroup=e,this._bindings=e.subscribe_(t,r)}getValue(e,t){this.bind();const i=this._targetGroup.nCachedObjects_,r=this._bindings[i];r!==void 0&&r.getValue(e,t)}setValue(e,t){const i=this._bindings;for(let r=this._targetGroup.nCachedObjects_,s=i.length;r!==s;++r)i[r].setValue(e,t)}bind(){const e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,i=e.length;t!==i;++t)e[t].bind()}unbind(){const e=this._bindings;for(let t=this._targetGroup.nCachedObjects_,i=e.length;t!==i;++t)e[t].unbind()}}class zt{constructor(e,t,i){this.path=t,this.parsedPath=i||zt.parseTrackName(t),this.node=zt.findNode(e,this.parsedPath.nodeName),this.rootNode=e,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}static create(e,t,i){return e&&e.isAnimationObjectGroup?new zt.Composite(e,t,i):new zt(e,t,i)}static sanitizeNodeName(e){return e.replace(/\s/g,"_").replace(P5,"")}static parseTrackName(e){const t=G5.exec(e);if(t===null)throw new Error("PropertyBinding: Cannot parse trackName: "+e);const i={nodeName:t[2],objectName:t[3],objectIndex:t[4],propertyName:t[5],propertyIndex:t[6]},r=i.nodeName&&i.nodeName.lastIndexOf(".");if(r!==void 0&&r!==-1){const s=i.nodeName.substring(r+1);V5.indexOf(s)!==-1&&(i.nodeName=i.nodeName.substring(0,r),i.objectName=s)}if(i.propertyName===null||i.propertyName.length===0)throw new Error("PropertyBinding: can not parse propertyName from trackName: "+e);return i}static findNode(e,t){if(t===void 0||t===""||t==="."||t===-1||t===e.name||t===e.uuid)return e;if(e.skeleton){const i=e.skeleton.getBoneByName(t);if(i!==void 0)return i}if(e.children){const i=function(s){for(let o=0;o<s.length;o++){const a=s[o];if(a.name===t||a.uuid===t)return a;const l=i(a.children);if(l)return l}return null},r=i(e.children);if(r)return r}return null}_getValue_unavailable(){}_setValue_unavailable(){}_getValue_direct(e,t){e[t]=this.targetObject[this.propertyName]}_getValue_array(e,t){const i=this.resolvedProperty;for(let r=0,s=i.length;r!==s;++r)e[t++]=i[r]}_getValue_arrayElement(e,t){e[t]=this.resolvedProperty[this.propertyIndex]}_getValue_toArray(e,t){this.resolvedProperty.toArray(e,t)}_setValue_direct(e,t){this.targetObject[this.propertyName]=e[t]}_setValue_direct_setNeedsUpdate(e,t){this.targetObject[this.propertyName]=e[t],this.targetObject.needsUpdate=!0}_setValue_direct_setMatrixWorldNeedsUpdate(e,t){this.targetObject[this.propertyName]=e[t],this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_array(e,t){const i=this.resolvedProperty;for(let r=0,s=i.length;r!==s;++r)i[r]=e[t++]}_setValue_array_setNeedsUpdate(e,t){const i=this.resolvedProperty;for(let r=0,s=i.length;r!==s;++r)i[r]=e[t++];this.targetObject.needsUpdate=!0}_setValue_array_setMatrixWorldNeedsUpdate(e,t){const i=this.resolvedProperty;for(let r=0,s=i.length;r!==s;++r)i[r]=e[t++];this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_arrayElement(e,t){this.resolvedProperty[this.propertyIndex]=e[t]}_setValue_arrayElement_setNeedsUpdate(e,t){this.resolvedProperty[this.propertyIndex]=e[t],this.targetObject.needsUpdate=!0}_setValue_arrayElement_setMatrixWorldNeedsUpdate(e,t){this.resolvedProperty[this.propertyIndex]=e[t],this.targetObject.matrixWorldNeedsUpdate=!0}_setValue_fromArray(e,t){this.resolvedProperty.fromArray(e,t)}_setValue_fromArray_setNeedsUpdate(e,t){this.resolvedProperty.fromArray(e,t),this.targetObject.needsUpdate=!0}_setValue_fromArray_setMatrixWorldNeedsUpdate(e,t){this.resolvedProperty.fromArray(e,t),this.targetObject.matrixWorldNeedsUpdate=!0}_getValue_unbound(e,t){this.bind(),this.getValue(e,t)}_setValue_unbound(e,t){this.bind(),this.setValue(e,t)}bind(){let e=this.node;const t=this.parsedPath,i=t.objectName,r=t.propertyName;let s=t.propertyIndex;if(e||(e=zt.findNode(this.rootNode,t.nodeName),this.node=e),this.getValue=this._getValue_unavailable,this.setValue=this._setValue_unavailable,!e)return;if(i){let c=t.objectIndex;switch(i){case"materials":if(!e.material||!e.material.materials)return;e=e.material.materials;break;case"bones":if(!e.skeleton)return;e=e.skeleton.bones;for(let h=0;h<e.length;h++)if(e[h].name===c){c=h;break}break;case"map":if("map"in e){e=e.map;break}if(!e.material||!e.material.map)return;e=e.material.map;break;default:if(e[i]===void 0)return;e=e[i]}if(c!==void 0){if(e[c]===void 0)return;e=e[c]}}const o=e[r];if(o===void 0){const c=t.nodeName;return}let a=this.Versioning.None;this.targetObject=e,e.needsUpdate!==void 0?a=this.Versioning.NeedsUpdate:e.matrixWorldNeedsUpdate!==void 0&&(a=this.Versioning.MatrixWorldNeedsUpdate);let l=this.BindingType.Direct;if(s!==void 0){if(r==="morphTargetInfluences"){if(!e.geometry||!e.geometry.morphAttributes)return;e.morphTargetDictionary[s]!==void 0&&(s=e.morphTargetDictionary[s])}l=this.BindingType.ArrayElement,this.resolvedProperty=o,this.propertyIndex=s}else o.fromArray!==void 0&&o.toArray!==void 0?(l=this.BindingType.HasFromToArray,this.resolvedProperty=o):Array.isArray(o)?(l=this.BindingType.EntireArray,this.resolvedProperty=o):this.propertyName=r;this.getValue=this.GetterByBindingType[l],this.setValue=this.SetterByBindingTypeAndVersioning[l][a]}unbind(){this.node=null,this.getValue=this._getValue_unbound,this.setValue=this._setValue_unbound}}zt.Composite=q5;zt.prototype.BindingType={Direct:0,EntireArray:1,ArrayElement:2,HasFromToArray:3};zt.prototype.Versioning={None:0,NeedsUpdate:1,MatrixWorldNeedsUpdate:2};zt.prototype.GetterByBindingType=[zt.prototype._getValue_direct,zt.prototype._getValue_array,zt.prototype._getValue_arrayElement,zt.prototype._getValue_toArray];zt.prototype.SetterByBindingTypeAndVersioning=[[zt.prototype._setValue_direct,zt.prototype._setValue_direct_setNeedsUpdate,zt.prototype._setValue_direct_setMatrixWorldNeedsUpdate],[zt.prototype._setValue_array,zt.prototype._setValue_array_setNeedsUpdate,zt.prototype._setValue_array_setMatrixWorldNeedsUpdate],[zt.prototype._setValue_arrayElement,zt.prototype._setValue_arrayElement_setNeedsUpdate,zt.prototype._setValue_arrayElement_setMatrixWorldNeedsUpdate],[zt.prototype._setValue_fromArray,zt.prototype._setValue_fromArray_setNeedsUpdate,zt.prototype._setValue_fromArray_setMatrixWorldNeedsUpdate]];class Y5{constructor(){this.isAnimationObjectGroup=!0,this.uuid=Br(),this._objects=Array.prototype.slice.call(arguments),this.nCachedObjects_=0;const e={};this._indicesByUUID=e;for(let i=0,r=arguments.length;i!==r;++i)e[arguments[i].uuid]=i;this._paths=[],this._parsedPaths=[],this._bindings=[],this._bindingsIndicesByPath={};const t=this;this.stats={objects:{get total(){return t._objects.length},get inUse(){return this.total-t.nCachedObjects_}},get bindingsPerObject(){return t._bindings.length}}}add(){const e=this._objects,t=this._indicesByUUID,i=this._paths,r=this._parsedPaths,s=this._bindings,o=s.length;let a,l=e.length,c=this.nCachedObjects_;for(let h=0,f=arguments.length;h!==f;++h){const d=arguments[h],m=d.uuid;let g=t[m];if(g===void 0){g=l++,t[m]=g,e.push(d);for(let E=0,C=o;E!==C;++E)s[E].push(new zt(d,i[E],r[E]))}else if(g<c){a=e[g];const E=--c,C=e[E];t[C.uuid]=g,e[g]=C,t[m]=E,e[E]=d;for(let S=0,v=o;S!==v;++S){const y=s[S],w=y[E];let x=y[g];y[g]=w,x===void 0&&(x=new zt(d,i[S],r[S])),y[E]=x}}else e[g]}this.nCachedObjects_=c}remove(){const e=this._objects,t=this._indicesByUUID,i=this._bindings,r=i.length;let s=this.nCachedObjects_;for(let o=0,a=arguments.length;o!==a;++o){const l=arguments[o],c=l.uuid,h=t[c];if(h!==void 0&&h>=s){const f=s++,d=e[f];t[d.uuid]=h,e[h]=d,t[c]=f,e[f]=l;for(let m=0,g=r;m!==g;++m){const E=i[m],C=E[f],S=E[h];E[h]=C,E[f]=S}}}this.nCachedObjects_=s}uncache(){const e=this._objects,t=this._indicesByUUID,i=this._bindings,r=i.length;let s=this.nCachedObjects_,o=e.length;for(let a=0,l=arguments.length;a!==l;++a){const c=arguments[a],h=c.uuid,f=t[h];if(f!==void 0)if(delete t[h],f<s){const d=--s,m=e[d],g=--o,E=e[g];t[m.uuid]=f,e[f]=m,t[E.uuid]=d,e[d]=E,e.pop();for(let C=0,S=r;C!==S;++C){const v=i[C],y=v[d],w=v[g];v[f]=y,v[d]=w,v.pop()}}else{const d=--o,m=e[d];d>0&&(t[m.uuid]=f),e[f]=m,e.pop();for(let g=0,E=r;g!==E;++g){const C=i[g];C[f]=C[d],C.pop()}}}this.nCachedObjects_=s}subscribe_(e,t){const i=this._bindingsIndicesByPath;let r=i[e];const s=this._bindings;if(r!==void 0)return s[r];const o=this._paths,a=this._parsedPaths,l=this._objects,c=l.length,h=this.nCachedObjects_,f=new Array(c);r=s.length,i[e]=r,o.push(e),a.push(t),s.push(f);for(let d=h,m=l.length;d!==m;++d){const g=l[d];f[d]=new zt(g,e,t)}return f}unsubscribe_(e){const t=this._bindingsIndicesByPath,i=t[e];if(i!==void 0){const r=this._paths,s=this._parsedPaths,o=this._bindings,a=o.length-1,l=o[a],c=e[a];t[c]=i,o[i]=l,o.pop(),s[i]=s[a],s.pop(),r[i]=r[a],r.pop()}}}class nD{constructor(e,t,i=null,r=t.blendMode){this._mixer=e,this._clip=t,this._localRoot=i,this.blendMode=r;const s=t.tracks,o=s.length,a=new Array(o),l={endingStart:Bl,endingEnd:Bl};for(let c=0;c!==o;++c){const h=s[c].createInterpolant(null);a[c]=h,h.settings=l}this._interpolantSettings=l,this._interpolants=a,this._propertyBindings=new Array(o),this._cacheIndex=null,this._byClipCacheIndex=null,this._timeScaleInterpolant=null,this._weightInterpolant=null,this.loop=GK,this._loopCount=-1,this._startTime=null,this.time=0,this.timeScale=1,this._effectiveTimeScale=1,this.weight=1,this._effectiveWeight=1,this.repetitions=1/0,this.paused=!1,this.enabled=!0,this.clampWhenFinished=!1,this.zeroSlopeAtStart=!0,this.zeroSlopeAtEnd=!0}play(){return this._mixer._activateAction(this),this}stop(){return this._mixer._deactivateAction(this),this.reset()}reset(){return this.paused=!1,this.enabled=!0,this.time=0,this._loopCount=-1,this._startTime=null,this.stopFading().stopWarping()}isRunning(){return this.enabled&&!this.paused&&this.timeScale!==0&&this._startTime===null&&this._mixer._isActiveAction(this)}isScheduled(){return this._mixer._isActiveAction(this)}startAt(e){return this._startTime=e,this}setLoop(e,t){return this.loop=e,this.repetitions=t,this}setEffectiveWeight(e){return this.weight=e,this._effectiveWeight=this.enabled?e:0,this.stopFading()}getEffectiveWeight(){return this._effectiveWeight}fadeIn(e){return this._scheduleFading(e,0,1)}fadeOut(e){return this._scheduleFading(e,1,0)}crossFadeFrom(e,t,i){if(e.fadeOut(t),this.fadeIn(t),i){const r=this._clip.duration,s=e._clip.duration,o=s/r,a=r/s;e.warp(1,o,t),this.warp(a,1,t)}return this}crossFadeTo(e,t,i){return e.crossFadeFrom(this,t,i)}stopFading(){const e=this._weightInterpolant;return e!==null&&(this._weightInterpolant=null,this._mixer._takeBackControlInterpolant(e)),this}setEffectiveTimeScale(e){return this.timeScale=e,this._effectiveTimeScale=this.paused?0:e,this.stopWarping()}getEffectiveTimeScale(){return this._effectiveTimeScale}setDuration(e){return this.timeScale=this._clip.duration/e,this.stopWarping()}syncWith(e){return this.time=e.time,this.timeScale=e.timeScale,this.stopWarping()}halt(e){return this.warp(this._effectiveTimeScale,0,e)}warp(e,t,i){const r=this._mixer,s=r.time,o=this.timeScale;let a=this._timeScaleInterpolant;a===null&&(a=r._lendControlInterpolant(),this._timeScaleInterpolant=a);const l=a.parameterPositions,c=a.sampleValues;return l[0]=s,l[1]=s+i,c[0]=e/o,c[1]=t/o,this}stopWarping(){const e=this._timeScaleInterpolant;return e!==null&&(this._timeScaleInterpolant=null,this._mixer._takeBackControlInterpolant(e)),this}getMixer(){return this._mixer}getClip(){return this._clip}getRoot(){return this._localRoot||this._mixer._root}_update(e,t,i,r){if(!this.enabled){this._updateWeight(e);return}const s=this._startTime;if(s!==null){const l=(e-s)*i;l<0||i===0?t=0:(this._startTime=null,t=i*l)}t*=this._updateTimeScale(e);const o=this._updateTime(t),a=this._updateWeight(e);if(a>0){const l=this._interpolants,c=this._propertyBindings;switch(this.blendMode){case XU:for(let h=0,f=l.length;h!==f;++h)l[h].evaluate(o),c[h].accumulateAdditive(a);break;case tA:default:for(let h=0,f=l.length;h!==f;++h)l[h].evaluate(o),c[h].accumulate(r,a)}}}_updateWeight(e){let t=0;if(this.enabled){t=this.weight;const i=this._weightInterpolant;if(i!==null){const r=i.evaluate(e)[0];t*=r,e>i.parameterPositions[1]&&(this.stopFading(),r===0&&(this.enabled=!1))}}return this._effectiveWeight=t,t}_updateTimeScale(e){let t=0;if(!this.paused){t=this.timeScale;const i=this._timeScaleInterpolant;if(i!==null){const r=i.evaluate(e)[0];t*=r,e>i.parameterPositions[1]&&(this.stopWarping(),t===0?this.paused=!0:this.timeScale=t)}}return this._effectiveTimeScale=t,t}_updateTime(e){const t=this._clip.duration,i=this.loop;let r=this.time+e,s=this._loopCount;const o=i===VK;if(e===0)return s===-1?r:o&&(s&1)===1?t-r:r;if(i===zK){s===-1&&(this._loopCount=0,this._setEndings(!0,!0,!1));e:{if(r>=t)r=t;else if(r<0)r=0;else{this.time=r;break e}this.clampWhenFinished?this.paused=!0:this.enabled=!1,this.time=r,this._mixer.dispatchEvent({type:"finished",action:this,direction:e<0?-1:1})}}else{if(s===-1&&(e>=0?(s=0,this._setEndings(!0,this.repetitions===0,o)):this._setEndings(this.repetitions===0,!0,o)),r>=t||r<0){const a=Math.floor(r/t);r-=t*a,s+=Math.abs(a);const l=this.repetitions-s;if(l<=0)this.clampWhenFinished?this.paused=!0:this.enabled=!1,r=e>0?t:0,this.time=r,this._mixer.dispatchEvent({type:"finished",action:this,direction:e>0?1:-1});else{if(l===1){const c=e<0;this._setEndings(c,!c,o)}else this._setEndings(!1,!1,o);this._loopCount=s,this.time=r,this._mixer.dispatchEvent({type:"loop",action:this,loopDelta:a})}}else this.time=r;if(o&&(s&1)===1)return t-r}return r}_setEndings(e,t,i){const r=this._interpolantSettings;i?(r.endingStart=Kl,r.endingEnd=Kl):(e?r.endingStart=this.zeroSlopeAtStart?Kl:Bl:r.endingStart=cf,t?r.endingEnd=this.zeroSlopeAtEnd?Kl:Bl:r.endingEnd=cf)}_scheduleFading(e,t,i){const r=this._mixer,s=r.time;let o=this._weightInterpolant;o===null&&(o=r._lendControlInterpolant(),this._weightInterpolant=o);const a=o.parameterPositions,l=o.sampleValues;return a[0]=s,l[0]=t,a[1]=s+e,l[1]=i,this}}const Z5=new Float32Array(1);class iD extends co{constructor(e){super(),this._root=e,this._initMemoryManager(),this._accuIndex=0,this.time=0,this.timeScale=1}_bindAction(e,t){const i=e._localRoot||this._root,r=e._clip.tracks,s=r.length,o=e._propertyBindings,a=e._interpolants,l=i.uuid,c=this._bindingsByRootAndName;let h=c[l];h===void 0&&(h={},c[l]=h);for(let f=0;f!==s;++f){const d=r[f],m=d.name;let g=h[m];if(g!==void 0)++g.referenceCount,o[f]=g;else{if(g=o[f],g!==void 0){g._cacheIndex===null&&(++g.referenceCount,this._addInactiveBinding(g,l,m));continue}const E=t&&t._propertyBindings[f].binding.parsedPath;g=new tD(zt.create(i,m,E),d.ValueTypeName,d.getValueSize()),++g.referenceCount,this._addInactiveBinding(g,l,m),o[f]=g}a[f].resultBuffer=g.buffer}}_activateAction(e){if(!this._isActiveAction(e)){if(e._cacheIndex===null){const i=(e._localRoot||this._root).uuid,r=e._clip.uuid,s=this._actionsByClip[r];this._bindAction(e,s&&s.knownActions[0]),this._addInactiveAction(e,r,i)}const t=e._propertyBindings;for(let i=0,r=t.length;i!==r;++i){const s=t[i];s.useCount++===0&&(this._lendBinding(s),s.saveOriginalState())}this._lendAction(e)}}_deactivateAction(e){if(this._isActiveAction(e)){const t=e._propertyBindings;for(let i=0,r=t.length;i!==r;++i){const s=t[i];--s.useCount===0&&(s.restoreOriginalState(),this._takeBackBinding(s))}this._takeBackAction(e)}}_initMemoryManager(){this._actions=[],this._nActiveActions=0,this._actionsByClip={},this._bindings=[],this._nActiveBindings=0,this._bindingsByRootAndName={},this._controlInterpolants=[],this._nActiveControlInterpolants=0;const 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 e._controlInterpolants.length},get inUse(){return e._nActiveControlInterpolants}}}}_isActiveAction(e){const t=e._cacheIndex;return t!==null&&t<this._nActiveActions}_addInactiveAction(e,t,i){const r=this._actions,s=this._actionsByClip;let o=s[t];if(o===void 0)o={knownActions:[e],actionByRoot:{}},e._byClipCacheIndex=0,s[t]=o;else{const a=o.knownActions;e._byClipCacheIndex=a.length,a.push(e)}e._cacheIndex=r.length,r.push(e),o.actionByRoot[i]=e}_removeInactiveAction(e){const t=this._actions,i=t[t.length-1],r=e._cacheIndex;i._cacheIndex=r,t[r]=i,t.pop(),e._cacheIndex=null;const s=e._clip.uuid,o=this._actionsByClip,a=o[s],l=a.knownActions,c=l[l.length-1],h=e._byClipCacheIndex;c._byClipCacheIndex=h,l[h]=c,l.pop(),e._byClipCacheIndex=null;const f=a.actionByRoot,d=(e._localRoot||this._root).uuid;delete f[d],l.length===0&&delete o[s],this._removeInactiveBindingsForAction(e)}_removeInactiveBindingsForAction(e){const t=e._propertyBindings;for(let i=0,r=t.length;i!==r;++i){const s=t[i];--s.referenceCount===0&&this._removeInactiveBinding(s)}}_lendAction(e){const t=this._actions,i=e._cacheIndex,r=this._nActiveActions++,s=t[r];e._cacheIndex=r,t[r]=e,s._cacheIndex=i,t[i]=s}_takeBackAction(e){const t=this._actions,i=e._cacheIndex,r=--this._nActiveActions,s=t[r];e._cacheIndex=r,t[r]=e,s._cacheIndex=i,t[i]=s}_addInactiveBinding(e,t,i){const r=this._bindingsByRootAndName,s=this._bindings;let o=r[t];o===void 0&&(o={},r[t]=o),o[i]=e,e._cacheIndex=s.length,s.push(e)}_removeInactiveBinding(e){const t=this._bindings,i=e.binding,r=i.rootNode.uuid,s=i.path,o=this._bindingsByRootAndName,a=o[r],l=t[t.length-1],c=e._cacheIndex;l._cacheIndex=c,t[c]=l,t.pop(),delete a[s],Object.keys(a).length===0&&delete o[r]}_lendBinding(e){const t=this._bindings,i=e._cacheIndex,r=this._nActiveBindings++,s=t[r];e._cacheIndex=r,t[r]=e,s._cacheIndex=i,t[i]=s}_takeBackBinding(e){const t=this._bindings,i=e._cacheIndex,r=--this._nActiveBindings,s=t[r];e._cacheIndex=r,t[r]=e,s._cacheIndex=i,t[i]=s}_lendControlInterpolant(){const e=this._controlInterpolants,t=this._nActiveControlInterpolants++;let i=e[t];return i===void 0&&(i=new Uw(new Float32Array(2),new Float32Array(2),1,Z5),i.__cacheIndex=t,e[t]=i),i}_takeBackControlInterpolant(e){const t=this._controlInterpolants,i=e.__cacheIndex,r=--this._nActiveControlInterpolants,s=t[r];e.__cacheIndex=r,t[r]=e,s.__cacheIndex=i,t[i]=s}clipAction(e,t,i){const r=t||this._root,s=r.uuid;let o=typeof e=="string"?sc.findByName(r,e):e;const a=o!==null?o.uuid:e,l=this._actionsByClip[a];let c=null;if(i===void 0&&(o!==null?i=o.blendMode:i=tA),l!==void 0){const f=l.actionByRoot[s];if(f!==void 0&&f.blendMode===i)return f;c=l.knownActions[0],o===null&&(o=c._clip)}if(o===null)return null;const h=new nD(this,o,t,i);return this._bindAction(h,c),this._addInactiveAction(h,a,s),h}existingAction(e,t){const i=t||this._root,r=i.uuid,s=typeof e=="string"?sc.findByName(i,e):e,o=s?s.uuid:e,a=this._actionsByClip[o];return a!==void 0&&a.actionByRoot[r]||null}stopAllAction(){const e=this._actions,t=this._nActiveActions;for(let i=t-1;i>=0;--i)e[i].stop();return this}update(e){e*=this.timeScale;const t=this._actions,i=this._nActiveActions,r=this.time+=e,s=Math.sign(e),o=this._accuIndex^=1;for(let c=0;c!==i;++c)t[c]._update(r,e,s,o);const a=this._bindings,l=this._nActiveBindings;for(let c=0;c!==l;++c)a[c].apply(o);return this}setTime(e){this.time=0;for(let t=0;t<this._actions.length;t++)this._actions[t].time=0;return this.update(e)}getRoot(){return this._root}uncacheClip(e){const t=this._actions,i=e.uuid,r=this._actionsByClip,s=r[i];if(s!==void 0){const o=s.knownActions;for(let a=0,l=o.length;a!==l;++a){const c=o[a];this._deactivateAction(c);const h=c._cacheIndex,f=t[t.length-1];c._cacheIndex=null,c._byClipCacheIndex=null,f._cacheIndex=h,t[h]=f,t.pop(),this._removeInactiveBindingsForAction(c)}delete r[i]}}uncacheRoot(e){const t=e.uuid,i=this._actionsByClip;for(const o in i){const a=i[o].actionByRoot,l=a[t];l!==void 0&&(this._deactivateAction(l),this._removeInactiveAction(l))}const r=this._bindingsByRootAndName,s=r[t];if(s!==void 0)for(const o in s){const a=s[o];a.restoreOriginalState(),this._removeInactiveBinding(a)}}uncacheAction(e,t){const i=this.existingAction(e,t);i!==null&&(this._deactivateAction(i),this._removeInactiveAction(i))}}class Kw{constructor(e){this.value=e}clone(){return new Kw(this.value.clone===void 0?this.value:this.value.clone())}}let j5=0;class X5 extends co{constructor(){super(),this.isUniformsGroup=!0,Object.defineProperty(this,"id",{value:j5++}),this.name="",this.usage=ff,this.uniforms=[]}add(e){return this.uniforms.push(e),this}remove(e){const t=this.uniforms.indexOf(e);return t!==-1&&this.uniforms.splice(t,1),this}setName(e){return this.name=e,this}setUsage(e){return this.usage=e,this}dispose(){return this.dispatchEvent({type:"dispose"}),this}copy(e){this.name=e.name,this.usage=e.usage;const t=e.uniforms;this.uniforms.length=0;for(let i=0,r=t.length;i<r;i++)this.uniforms.push(t[i].clone());return this}clone(){return new this.constructor().copy(this)}}class _5 extends Wf{constructor(e,t,i=1){super(e,t),this.isInstancedInterleavedBuffer=!0,this.meshPerAttribute=i}copy(e){return super.copy(e),this.meshPerAttribute=e.meshPerAttribute,this}clone(e){const t=super.clone(e);return t.meshPerAttribute=this.meshPerAttribute,t}toJSON(e){const t=super.toJSON(e);return t.isInstancedInterleavedBuffer=!0,t.meshPerAttribute=this.meshPerAttribute,t}}class $5{constructor(e,t,i,r,s){this.isGLBufferAttribute=!0,this.name="",this.buffer=e,this.type=t,this.itemSize=i,this.elementSize=r,this.count=s,this.version=0}set needsUpdate(e){e===!0&&this.version++}setBuffer(e){return this.buffer=e,this}setType(e,t){return this.type=e,this.elementSize=t,this}setItemSize(e){return this.itemSize=e,this}setCount(e){return this.count=e,this}}class Rw{constructor(e,t,i=0,r=1/0){this.ray=new pc(e,t),this.near=i,this.far=r,this.camera=null,this.layers=new Hl,this.params={Mesh:{},Line:{threshold:1},LOD:{},Points:{threshold:1},Sprite:{}}}set(e,t){this.ray.set(e,t)}setFromCamera(e,t){t.isPerspectiveCamera?(this.ray.origin.setFromMatrixPosition(t.matrixWorld),this.ray.direction.set(e.x,e.y,.5).unproject(t).sub(this.ray.origin).normalize(),this.camera=t):t.isOrthographicCamera&&(this.ray.origin.set(e.x,e.y,(t.near+t.far)/(t.near-t.far)).unproject(t),this.ray.direction.set(0,0,-1).transformDirection(t.matrixWorld),this.camera=t)}intersectObject(e,t=!0,i=[]){return uv(e,this,i,t),i.sort(J1),i}intersectObjects(e,t=!0,i=[]){for(let r=0,s=e.length;r<s;r++)uv(e[r],this,i,t);return i.sort(J1),i}}function J1(n,e){return n.distance-e.distance}function uv(n,e,t,i){if(n.layers.test(e.layers)&&n.raycast(e,t),i===!0){const r=n.children;for(let s=0,o=r.length;s<o;s++)uv(r[s],e,t,!0)}}class hv{constructor(e=1,t=0,i=0){return this.radius=e,this.phi=t,this.theta=i,this}set(e,t,i){return this.radius=e,this.phi=t,this.theta=i,this}copy(e){return this.radius=e.radius,this.phi=e.phi,this.theta=e.theta,this}makeSafe(){return this.phi=Math.max(1e-6,Math.min(Math.PI-1e-6,this.phi)),this}setFromVector3(e){return this.setFromCartesianCoords(e.x,e.y,e.z)}setFromCartesianCoords(e,t,i){return this.radius=Math.sqrt(e*e+t*t+i*i),this.radius===0?(this.theta=0,this.phi=0):(this.theta=Math.atan2(e,i),this.phi=Math.acos(Hn(t/this.radius,-1,1))),this}clone(){return new this.constructor().copy(this)}}class e3{constructor(e=1,t=0,i=0){return this.radius=e,this.theta=t,this.y=i,this}set(e,t,i){return this.radius=e,this.theta=t,this.y=i,this}copy(e){return this.radius=e.radius,this.theta=e.theta,this.y=e.y,this}setFromVector3(e){return this.setFromCartesianCoords(e.x,e.y,e.z)}setFromCartesianCoords(e,t,i){return this.radius=Math.sqrt(e*e+i*i),this.theta=Math.atan2(e,i),this.y=t,this}clone(){return new this.constructor().copy(this)}}const I1=new we;class t3{constructor(e=new we(1/0,1/0),t=new we(-1/0,-1/0)){this.isBox2=!0,this.min=e,this.max=t}set(e,t){return this.min.copy(e),this.max.copy(t),this}setFromPoints(e){this.makeEmpty();for(let t=0,i=e.length;t<i;t++)this.expandByPoint(e[t]);return this}setFromCenterAndSize(e,t){const i=I1.copy(t).multiplyScalar(.5);return this.min.copy(e).sub(i),this.max.copy(e).add(i),this}clone(){return new this.constructor().copy(this)}copy(e){return this.min.copy(e.min),this.max.copy(e.max),this}makeEmpty(){return this.min.x=this.min.y=1/0,this.max.x=this.max.y=-1/0,this}isEmpty(){return this.max.x<this.min.x||this.max.y<this.min.y}getCenter(e){return this.isEmpty()?e.set(0,0):e.addVectors(this.min,this.max).multiplyScalar(.5)}getSize(e){return this.isEmpty()?e.set(0,0):e.subVectors(this.max,this.min)}expandByPoint(e){return this.min.min(e),this.max.max(e),this}expandByVector(e){return this.min.sub(e),this.max.add(e),this}expandByScalar(e){return this.min.addScalar(-e),this.max.addScalar(e),this}containsPoint(e){return!(e.x<this.min.x||e.x>this.max.x||e.y<this.min.y||e.y>this.max.y)}containsBox(e){return this.min.x<=e.min.x&&e.max.x<=this.max.x&&this.min.y<=e.min.y&&e.max.y<=this.max.y}getParameter(e,t){return t.set((e.x-this.min.x)/(this.max.x-this.min.x),(e.y-this.min.y)/(this.max.y-this.min.y))}intersectsBox(e){return!(e.max.x<this.min.x||e.min.x>this.max.x||e.max.y<this.min.y||e.min.y>this.max.y)}clampPoint(e,t){return t.copy(e).clamp(this.min,this.max)}distanceToPoint(e){return this.clampPoint(e,I1).distanceTo(e)}intersect(e){return this.min.max(e.min),this.max.min(e.max),this.isEmpty()&&this.makeEmpty(),this}union(e){return this.min.min(e.min),this.max.max(e.max),this}translate(e){return this.min.add(e),this.max.add(e),this}equals(e){return e.min.equals(this.min)&&e.max.equals(this.max)}}const L1=new N,tS=new N;class n3{constructor(e=new N,t=new N){this.start=e,this.end=t}set(e,t){return this.start.copy(e),this.end.copy(t),this}copy(e){return this.start.copy(e.start),this.end.copy(e.end),this}getCenter(e){return e.addVectors(this.start,this.end).multiplyScalar(.5)}delta(e){return e.subVectors(this.end,this.start)}distanceSq(){return this.start.distanceToSquared(this.end)}distance(){return this.start.distanceTo(this.end)}at(e,t){return this.delta(t).multiplyScalar(e).add(this.start)}closestPointToPointParameter(e,t){L1.subVectors(e,this.start),tS.subVectors(this.end,this.start);const i=tS.dot(tS);let s=tS.dot(L1)/i;return t&&(s=Hn(s,0,1)),s}closestPointToPoint(e,t,i){const r=this.closestPointToPointParameter(e,t);return this.delta(i).multiplyScalar(r).add(this.start)}applyMatrix4(e){return this.start.applyMatrix4(e),this.end.applyMatrix4(e),this}equals(e){return e.start.equals(this.start)&&e.end.equals(this.end)}clone(){return new this.constructor().copy(this)}}const B1=new N;class i3 extends Wt{constructor(e,t){super(),this.light=e,this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1,this.color=t,this.type="SpotLightHelper";const i=new Tt,r=[0,0,0,0,0,1,0,0,0,1,0,1,0,0,0,-1,0,1,0,0,0,0,1,1,0,0,0,0,-1,1];for(let o=0,a=1,l=32;o<l;o++,a++){const c=o/l*Math.PI*2,h=a/l*Math.PI*2;r.push(Math.cos(c),Math.sin(c),1,Math.cos(h),Math.sin(h),1)}i.setAttribute("position",new ot(r,3));const s=new wi({fog:!1,toneMapped:!1});this.cone=new Ks(i,s),this.add(this.cone),this.update()}dispose(){this.cone.geometry.dispose(),this.cone.material.dispose()}update(){this.light.updateWorldMatrix(!0,!1),this.light.target.updateWorldMatrix(!0,!1);const e=this.light.distance?this.light.distance:1e3,t=e*Math.tan(this.light.angle);this.cone.scale.set(t,t,e),B1.setFromMatrixPosition(this.light.target.matrixWorld),this.cone.lookAt(B1),this.color!==void 0?this.cone.material.color.set(this.color):this.cone.material.color.copy(this.light.color)}}const pa=new N,nS=new tt,Y0=new tt;class r3 extends Ks{constructor(e){const t=rD(e),i=new Tt,r=[],s=[],o=new ze(0,0,1),a=new ze(0,1,0);for(let c=0;c<t.length;c++){const h=t[c];h.parent&&h.parent.isBone&&(r.push(0,0,0),r.push(0,0,0),s.push(o.r,o.g,o.b),s.push(a.r,a.g,a.b))}i.setAttribute("position",new ot(r,3)),i.setAttribute("color",new ot(s,3));const l=new wi({vertexColors:!0,depthTest:!1,depthWrite:!1,toneMapped:!1,transparent:!0});super(i,l),this.isSkeletonHelper=!0,this.type="SkeletonHelper",this.root=e,this.bones=t,this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1}updateMatrixWorld(e){const t=this.bones,i=this.geometry,r=i.getAttribute("position");Y0.copy(this.root.matrixWorld).invert();for(let s=0,o=0;s<t.length;s++){const a=t[s];a.parent&&a.parent.isBone&&(nS.multiplyMatrices(Y0,a.matrixWorld),pa.setFromMatrixPosition(nS),r.setXYZ(o,pa.x,pa.y,pa.z),nS.multiplyMatrices(Y0,a.parent.matrixWorld),pa.setFromMatrixPosition(nS),r.setXYZ(o+1,pa.x,pa.y,pa.z),o+=2)}i.getAttribute("position").needsUpdate=!0,super.updateMatrixWorld(e)}dispose(){this.geometry.dispose(),this.material.dispose()}}function rD(n){const e=[];n.isBone===!0&&e.push(n);for(let t=0;t<n.children.length;t++)e.push.apply(e,rD(n.children[t]));return e}class s3 extends Gn{constructor(e,t,i){const r=new Vf(t,4,2),s=new Ir({wireframe:!0,fog:!1,toneMapped:!1});super(r,s),this.light=e,this.color=i,this.type="PointLightHelper",this.matrix=this.light.matrixWorld,this.matrixAutoUpdate=!1,this.update()}dispose(){this.geometry.dispose(),this.material.dispose()}update(){this.light.updateWorldMatrix(!0,!1),this.color!==void 0?this.material.color.set(this.color):this.material.color.copy(this.light.color)}}const o3=new N,K1=new ze,R1=new ze;class a3 extends Wt{constructor(e,t,i){super(),this.light=e,this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1,this.color=i,this.type="HemisphereLightHelper";const r=new Gf(t);r.rotateY(Math.PI*.5),this.material=new Ir({wireframe:!0,fog:!1,toneMapped:!1}),this.color===void 0&&(this.material.vertexColors=!0);const s=r.getAttribute("position"),o=new Float32Array(s.count*3);r.setAttribute("color",new Xt(o,3)),this.add(new Gn(r,this.material)),this.update()}dispose(){this.children[0].geometry.dispose(),this.children[0].material.dispose()}update(){const e=this.children[0];if(this.color!==void 0)this.material.color.set(this.color);else{const t=e.geometry.getAttribute("color");K1.copy(this.light.color),R1.copy(this.light.groundColor);for(let i=0,r=t.count;i<r;i++){const s=i<r/2?K1:R1;t.setXYZ(i,s.r,s.g,s.b)}t.needsUpdate=!0}this.light.updateWorldMatrix(!0,!1),e.lookAt(o3.setFromMatrixPosition(this.light.matrixWorld).negate())}}class l3 extends Ks{constructor(e=10,t=10,i=4473924,r=8947848){i=new ze(i),r=new ze(r);const s=t/2,o=e/t,a=e/2,l=[],c=[];for(let d=0,m=0,g=-a;d<=t;d++,g+=o){l.push(-a,0,g,a,0,g),l.push(g,0,-a,g,0,a);const E=d===s?i:r;E.toArray(c,m),m+=3,E.toArray(c,m),m+=3,E.toArray(c,m),m+=3,E.toArray(c,m),m+=3}const h=new Tt;h.setAttribute("position",new ot(l,3)),h.setAttribute("color",new ot(c,3));const f=new wi({vertexColors:!0,toneMapped:!1});super(h,f),this.type="GridHelper"}dispose(){this.geometry.dispose(),this.material.dispose()}}class c3 extends Ks{constructor(e=10,t=16,i=8,r=64,s=4473924,o=8947848){s=new ze(s),o=new ze(o);const a=[],l=[];if(t>1)for(let f=0;f<t;f++){const d=f/t*(Math.PI*2),m=Math.sin(d)*e,g=Math.cos(d)*e;a.push(0,0,0),a.push(m,0,g);const E=f&1?s:o;l.push(E.r,E.g,E.b),l.push(E.r,E.g,E.b)}for(let f=0;f<i;f++){const d=f&1?s:o,m=e-e/i*f;for(let g=0;g<r;g++){let E=g/r*(Math.PI*2),C=Math.sin(E)*m,S=Math.cos(E)*m;a.push(C,0,S),l.push(d.r,d.g,d.b),E=(g+1)/r*(Math.PI*2),C=Math.sin(E)*m,S=Math.cos(E)*m,a.push(C,0,S),l.push(d.r,d.g,d.b)}}const c=new Tt;c.setAttribute("position",new ot(a,3)),c.setAttribute("color",new ot(l,3));const h=new wi({vertexColors:!0,toneMapped:!1});super(c,h),this.type="PolarGridHelper"}dispose(){this.geometry.dispose(),this.material.dispose()}}const D1=new N,iS=new N,b1=new N;class u3 extends Wt{constructor(e,t,i){super(),this.light=e,this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1,this.color=i,this.type="DirectionalLightHelper",t===void 0&&(t=1);let r=new Tt;r.setAttribute("position",new ot([-t,t,0,t,t,0,t,-t,0,-t,-t,0,-t,t,0],3));const s=new wi({fog:!1,toneMapped:!1});this.lightPlane=new oo(r,s),this.add(this.lightPlane),r=new Tt,r.setAttribute("position",new ot([0,0,0,0,0,1],3)),this.targetLine=new oo(r,s),this.add(this.targetLine),this.update()}dispose(){this.lightPlane.geometry.dispose(),this.lightPlane.material.dispose(),this.targetLine.geometry.dispose(),this.targetLine.material.dispose()}update(){this.light.updateWorldMatrix(!0,!1),this.light.target.updateWorldMatrix(!0,!1),D1.setFromMatrixPosition(this.light.matrixWorld),iS.setFromMatrixPosition(this.light.target.matrixWorld),b1.subVectors(iS,D1),this.lightPlane.lookAt(iS),this.color!==void 0?(this.lightPlane.material.color.set(this.color),this.targetLine.material.color.set(this.color)):(this.lightPlane.material.color.copy(this.light.color),this.targetLine.material.color.copy(this.light.color)),this.targetLine.lookAt(iS),this.targetLine.scale.z=b1.length()}}const rS=new N,Nn=new Ff;class h3 extends Ks{constructor(e){const t=new Tt,i=new wi({color:16777215,vertexColors:!0,toneMapped:!1}),r=[],s=[],o={};a("n1","n2"),a("n2","n4"),a("n4","n3"),a("n3","n1"),a("f1","f2"),a("f2","f4"),a("f4","f3"),a("f3","f1"),a("n1","f1"),a("n2","f2"),a("n3","f3"),a("n4","f4"),a("p","n1"),a("p","n2"),a("p","n3"),a("p","n4"),a("u1","u2"),a("u2","u3"),a("u3","u1"),a("c","t"),a("p","c"),a("cn1","cn2"),a("cn3","cn4"),a("cf1","cf2"),a("cf3","cf4");function a(g,E){l(g),l(E)}function l(g){r.push(0,0,0),s.push(0,0,0),o[g]===void 0&&(o[g]=[]),o[g].push(r.length/3-1)}t.setAttribute("position",new ot(r,3)),t.setAttribute("color",new ot(s,3)),super(t,i),this.type="CameraHelper",this.camera=e,this.camera.updateProjectionMatrix&&this.camera.updateProjectionMatrix(),this.matrix=e.matrixWorld,this.matrixAutoUpdate=!1,this.pointMap=o,this.update();const c=new ze(16755200),h=new ze(16711680),f=new ze(43775),d=new ze(16777215),m=new ze(3355443);this.setColors(c,h,f,d,m)}setColors(e,t,i,r,s){const a=this.geometry.getAttribute("color");a.setXYZ(0,e.r,e.g,e.b),a.setXYZ(1,e.r,e.g,e.b),a.setXYZ(2,e.r,e.g,e.b),a.setXYZ(3,e.r,e.g,e.b),a.setXYZ(4,e.r,e.g,e.b),a.setXYZ(5,e.r,e.g,e.b),a.setXYZ(6,e.r,e.g,e.b),a.setXYZ(7,e.r,e.g,e.b),a.setXYZ(8,e.r,e.g,e.b),a.setXYZ(9,e.r,e.g,e.b),a.setXYZ(10,e.r,e.g,e.b),a.setXYZ(11,e.r,e.g,e.b),a.setXYZ(12,e.r,e.g,e.b),a.setXYZ(13,e.r,e.g,e.b),a.setXYZ(14,e.r,e.g,e.b),a.setXYZ(15,e.r,e.g,e.b),a.setXYZ(16,e.r,e.g,e.b),a.setXYZ(17,e.r,e.g,e.b),a.setXYZ(18,e.r,e.g,e.b),a.setXYZ(19,e.r,e.g,e.b),a.setXYZ(20,e.r,e.g,e.b),a.setXYZ(21,e.r,e.g,e.b),a.setXYZ(22,e.r,e.g,e.b),a.setXYZ(23,e.r,e.g,e.b),a.setXYZ(24,t.r,t.g,t.b),a.setXYZ(25,t.r,t.g,t.b),a.setXYZ(26,t.r,t.g,t.b),a.setXYZ(27,t.r,t.g,t.b),a.setXYZ(28,t.r,t.g,t.b),a.setXYZ(29,t.r,t.g,t.b),a.setXYZ(30,t.r,t.g,t.b),a.setXYZ(31,t.r,t.g,t.b),a.setXYZ(32,i.r,i.g,i.b),a.setXYZ(33,i.r,i.g,i.b),a.setXYZ(34,i.r,i.g,i.b),a.setXYZ(35,i.r,i.g,i.b),a.setXYZ(36,i.r,i.g,i.b),a.setXYZ(37,i.r,i.g,i.b),a.setXYZ(38,r.r,r.g,r.b),a.setXYZ(39,r.r,r.g,r.b),a.setXYZ(40,s.r,s.g,s.b),a.setXYZ(41,s.r,s.g,s.b),a.setXYZ(42,s.r,s.g,s.b),a.setXYZ(43,s.r,s.g,s.b),a.setXYZ(44,s.r,s.g,s.b),a.setXYZ(45,s.r,s.g,s.b),a.setXYZ(46,s.r,s.g,s.b),a.setXYZ(47,s.r,s.g,s.b),a.setXYZ(48,s.r,s.g,s.b),a.setXYZ(49,s.r,s.g,s.b),a.needsUpdate=!0}update(){const e=this.geometry,t=this.pointMap,i=1,r=1;Nn.projectionMatrixInverse.copy(this.camera.projectionMatrixInverse),Yn("c",t,e,Nn,0,0,-1),Yn("t",t,e,Nn,0,0,1),Yn("n1",t,e,Nn,-i,-r,-1),Yn("n2",t,e,Nn,i,-r,-1),Yn("n3",t,e,Nn,-i,r,-1),Yn("n4",t,e,Nn,i,r,-1),Yn("f1",t,e,Nn,-i,-r,1),Yn("f2",t,e,Nn,i,-r,1),Yn("f3",t,e,Nn,-i,r,1),Yn("f4",t,e,Nn,i,r,1),Yn("u1",t,e,Nn,i*.7,r*1.1,-1),Yn("u2",t,e,Nn,-i*.7,r*1.1,-1),Yn("u3",t,e,Nn,0,r*2,-1),Yn("cf1",t,e,Nn,-i,0,1),Yn("cf2",t,e,Nn,i,0,1),Yn("cf3",t,e,Nn,0,-r,1),Yn("cf4",t,e,Nn,0,r,1),Yn("cn1",t,e,Nn,-i,0,-1),Yn("cn2",t,e,Nn,i,0,-1),Yn("cn3",t,e,Nn,0,-r,-1),Yn("cn4",t,e,Nn,0,r,-1),e.getAttribute("position").needsUpdate=!0}dispose(){this.geometry.dispose(),this.material.dispose()}}function Yn(n,e,t,i,r,s,o){rS.set(r,s,o).unproject(i);const a=e[n];if(a!==void 0){const l=t.getAttribute("position");for(let c=0,h=a.length;c<h;c++)l.setXYZ(a[c],rS.x,rS.y,rS.z)}}const sS=new Pi;class p3 extends Ks{constructor(e,t=16776960){const i=new Uint16Array([0,1,1,2,2,3,3,0,4,5,5,6,6,7,7,4,0,4,1,5,2,6,3,7]),r=new Float32Array(8*3),s=new Tt;s.setIndex(new Xt(i,1)),s.setAttribute("position",new Xt(r,3)),super(s,new wi({color:t,toneMapped:!1})),this.object=e,this.type="BoxHelper",this.matrixAutoUpdate=!1,this.update()}update(e){if(this.object!==void 0&&sS.setFromObject(this.object),sS.isEmpty())return;const t=sS.min,i=sS.max,r=this.geometry.attributes.position,s=r.array;s[0]=i.x,s[1]=i.y,s[2]=i.z,s[3]=t.x,s[4]=i.y,s[5]=i.z,s[6]=t.x,s[7]=t.y,s[8]=i.z,s[9]=i.x,s[10]=t.y,s[11]=i.z,s[12]=i.x,s[13]=i.y,s[14]=t.z,s[15]=t.x,s[16]=i.y,s[17]=t.z,s[18]=t.x,s[19]=t.y,s[20]=t.z,s[21]=i.x,s[22]=t.y,s[23]=t.z,r.needsUpdate=!0,this.geometry.computeBoundingSphere()}setFromObject(e){return this.object=e,this.update(),this}copy(e,t){return super.copy(e,t),this.object=e.object,this}dispose(){this.geometry.dispose(),this.material.dispose()}}class f3 extends Ks{constructor(e,t=16776960){const i=new Uint16Array([0,1,1,2,2,3,3,0,4,5,5,6,6,7,7,4,0,4,1,5,2,6,3,7]),r=[1,1,1,-1,1,1,-1,-1,1,1,-1,1,1,1,-1,-1,1,-1,-1,-1,-1,1,-1,-1],s=new Tt;s.setIndex(new Xt(i,1)),s.setAttribute("position",new ot(r,3)),super(s,new wi({color:t,toneMapped:!1})),this.box=e,this.type="Box3Helper",this.geometry.computeBoundingSphere()}updateMatrixWorld(e){const t=this.box;t.isEmpty()||(t.getCenter(this.position),t.getSize(this.scale),this.scale.multiplyScalar(.5),super.updateMatrixWorld(e))}dispose(){this.geometry.dispose(),this.material.dispose()}}class d3 extends oo{constructor(e,t=1,i=16776960){const r=i,s=[1,-1,0,-1,1,0,-1,-1,0,1,1,0,-1,1,0,-1,-1,0,1,-1,0,1,1,0],o=new Tt;o.setAttribute("position",new ot(s,3)),o.computeBoundingSphere(),super(o,new wi({color:r,toneMapped:!1})),this.type="PlaneHelper",this.plane=e,this.size=t;const a=[1,1,0,-1,1,0,-1,-1,0,1,1,0,-1,-1,0,1,-1,0],l=new Tt;l.setAttribute("position",new ot(a,3)),l.computeBoundingSphere(),this.add(new Gn(l,new Ir({color:r,opacity:.2,transparent:!0,depthWrite:!1,toneMapped:!1})))}updateMatrixWorld(e){this.position.set(0,0,0),this.scale.set(.5*this.size,.5*this.size,1),this.lookAt(this.plane.normal),this.translateZ(-this.plane.constant),super.updateMatrixWorld(e)}dispose(){this.geometry.dispose(),this.material.dispose(),this.children[0].geometry.dispose(),this.children[0].material.dispose()}}const O1=new N;let oS,Z0;class m3 extends Wt{constructor(e=new N(0,0,1),t=new N(0,0,0),i=1,r=16776960,s=i*.2,o=s*.2){super(),this.type="ArrowHelper",oS===void 0&&(oS=new Tt,oS.setAttribute("position",new ot([0,0,0,0,1,0],3)),Z0=new uh(0,.5,1,5,1),Z0.translate(0,-.5,0)),this.position.copy(t),this.line=new oo(oS,new wi({color:r,toneMapped:!1})),this.line.matrixAutoUpdate=!1,this.add(this.line),this.cone=new Gn(Z0,new Ir({color:r,toneMapped:!1})),this.cone.matrixAutoUpdate=!1,this.add(this.cone),this.setDirection(e),this.setLength(i,s,o)}setDirection(e){if(e.y>.99999)this.quaternion.set(0,0,0,1);else if(e.y<-.99999)this.quaternion.set(1,0,0,0);else{O1.set(e.z,0,-e.x).normalize();const t=Math.acos(e.y);this.quaternion.setFromAxisAngle(O1,t)}}setLength(e,t=e*.2,i=t*.2){this.line.scale.set(1,Math.max(1e-4,e-t),1),this.line.updateMatrix(),this.cone.scale.set(i,t,i),this.cone.position.y=e,this.cone.updateMatrix()}setColor(e){this.line.material.color.set(e),this.cone.material.color.set(e)}copy(e){return super.copy(e,!1),this.line.copy(e.line),this.cone.copy(e.cone),this}dispose(){this.line.geometry.dispose(),this.line.material.dispose(),this.cone.geometry.dispose(),this.cone.material.dispose()}}class S3 extends Ks{constructor(e=1){const t=[0,0,0,e,0,0,0,0,0,0,e,0,0,0,0,0,0,e],i=[1,0,0,1,.6,0,0,1,0,.6,1,0,0,0,1,0,.6,1],r=new Tt;r.setAttribute("position",new ot(t,3)),r.setAttribute("color",new ot(i,3));const s=new wi({vertexColors:!0,toneMapped:!1});super(r,s),this.type="AxesHelper"}setColors(e,t,i){const r=new ze,s=this.geometry.attributes.color.array;return r.set(e),r.toArray(s,0),r.toArray(s,3),r.set(t),r.toArray(s,6),r.toArray(s,9),r.set(i),r.toArray(s,12),r.toArray(s,15),this.geometry.attributes.color.needsUpdate=!0,this}dispose(){this.geometry.dispose(),this.material.dispose()}}class g3{constructor(){this.type="ShapePath",this.color=new ze,this.subPaths=[],this.currentPath=null}moveTo(e,t){return this.currentPath=new Sf,this.subPaths.push(this.currentPath),this.currentPath.moveTo(e,t),this}lineTo(e,t){return this.currentPath.lineTo(e,t),this}quadraticCurveTo(e,t,i,r){return this.currentPath.quadraticCurveTo(e,t,i,r),this}bezierCurveTo(e,t,i,r,s,o){return this.currentPath.bezierCurveTo(e,t,i,r,s,o),this}splineThru(e){return this.currentPath.splineThru(e),this}toShapes(e){function t(S){const v=[];for(let y=0,w=S.length;y<w;y++){const x=S[y],k=new Gl;k.curves=x.curves,v.push(k)}return v}function i(S,v){const y=v.length;let w=!1;for(let x=y-1,k=0;k<y;x=k++){let 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f=c&&c.as||a,{props:d,deferredInjector:m}=o(c);return delete d.as,d.ref=h,m?j.createElement(j.Fragment,null,j.createElement(f,d),j.createElement(m,null)):j.createElement(f,d)});return l.className=o.className,l.displayName=`Styled.${a.displayName||a.name||a}`,l.selector=o.selector,l.toString=()=>o.selector,l[Vl]=o[Vl],l}}))(e),e};function $V(n,e,t){return Math.max(e,Math.min(n,t))}const Fi={toVector(n,e){return n===void 0&&(n=e),Array.isArray(n)?n:[n,n]},add(n,e){return[n[0]+e[0],n[1]+e[1]]},sub(n,e){return[n[0]-e[0],n[1]-e[1]]},addTo(n,e){n[0]+=e[0],n[1]+=e[1]},subTo(n,e){n[0]-=e[0],n[1]-=e[1]}};function lJ(n,e,t){return e===0||Math.abs(e)===1/0?Math.pow(n,t*5):n*e*t/(e+t*n)}function cJ(n,e,t,i=.15){return i===0?$V(n,e,t):n<e?-lJ(e-n,t-e,i)+e:n>t?+lJ(n-t,t-e,i)+t:n}function eq(n,[e,t],[i,r]){const[[s,o],[a,l]]=n;return[cJ(e,s,o,i),cJ(t,a,l,r)]}function tq(n,e){if(typeof n!="object"||n===null)return n;var t=n[Symbol.toPrimitive];if(t!==void 0){var i=t.call(n,e||"default");if(typeof i!="object")return i;throw new TypeError("@@toPrimitive must return a primitive value.")}return(e==="string"?String:Number)(n)}function nq(n){var e=tq(n,"string");return typeof e=="symbol"?e:String(e)}function cr(n,e,t){return e=nq(e),e in n?Object.defineProperty(n,e,{value:t,enumerable:!0,configurable:!0,writable:!0}):n[e]=t,n}function uJ(n,e){var t=Object.keys(n);if(Object.getOwnPropertySymbols){var i=Object.getOwnPropertySymbols(n);e&&(i=i.filter(function(r){return Object.getOwnPropertyDescriptor(n,r).enumerable})),t.push.apply(t,i)}return t}function Rn(n){for(var e=1;e<arguments.length;e++){var t=arguments[e]!=null?arguments[e]:{};e%2?uJ(Object(t),!0).forEach(function(i){cr(n,i,t[i])}):Object.getOwnPropertyDescriptors?Object.defineProperties(n,Object.getOwnPropertyDescriptors(t)):uJ(Object(t)).forEach(function(i){Object.defineProperty(n,i,Object.getOwnPropertyDescriptor(t,i))})}return n}const bD={pointer:{start:"down",change:"move",end:"up"},mouse:{start:"down",change:"move",end:"up"},touch:{start:"start",change:"move",end:"end"},gesture:{start:"start",change:"change",end:"end"}};function hJ(n){return n?n[0].toUpperCase()+n.slice(1):""}const iq=["enter","leave"];function rq(n=!1,e){return n&&!iq.includes(e)}function sq(n,e="",t=!1){const i=bD[n],r=i&&i[e]||e;return"on"+hJ(n)+hJ(r)+(rq(t,r)?"Capture":"")}const oq=["gotpointercapture","lostpointercapture"];function aq(n){let e=n.substring(2).toLowerCase();const t=!!~e.indexOf("passive");t&&(e=e.replace("passive",""));const i=oq.includes(e)?"capturecapture":"capture",r=!!~e.indexOf(i);return r&&(e=e.replace("capture","")),{device:e,capture:r,passive:t}}function lq(n,e=""){const t=bD[n],i=t&&t[e]||e;return n+i}function TA(n){return"touches"in n}function OD(n){return TA(n)?"touch":"pointerType"in n?n.pointerType:"mouse"}function cq(n){return Array.from(n.touches).filter(e=>{var t,i;return e.target===n.currentTarget||((t=n.currentTarget)===null||t===void 0||(i=t.contains)===null||i===void 0?void 0:i.call(t,e.target))})}function uq(n){return n.type==="touchend"||n.type==="touchcancel"?n.changedTouches:n.targetTouches}function FD(n){return TA(n)?uq(n)[0]:n}function hq(n){return cq(n).map(e=>e.identifier)}function sE(n){const e=FD(n);return TA(n)?e.identifier:e.pointerId}function pJ(n){const e=FD(n);return[e.clientX,e.clientY]}function pq(n){const e={};if("buttons"in n&&(e.buttons=n.buttons),"shiftKey"in n){const{shiftKey:t,altKey:i,metaKey:r,ctrlKey:s}=n;Object.assign(e,{shiftKey:t,altKey:i,metaKey:r,ctrlKey:s})}return e}function Cg(n,...e){return typeof n=="function"?n(...e):n}function fq(){}function dq(...n){return n.length===0?fq:n.length===1?n[0]:function(){let e;for(const t of n)e=t.apply(this,arguments)||e;return e}}function fJ(n,e){return Object.assign({},e,n||{})}const mq=32;class Sq{constructor(e,t,i){this.ctrl=e,this.args=t,this.key=i,this.state||(this.state={},this.computeValues([0,0]),this.computeInitial(),this.init&&this.init(),this.reset())}get state(){return this.ctrl.state[this.key]}set state(e){this.ctrl.state[this.key]=e}get shared(){return this.ctrl.state.shared}get eventStore(){return this.ctrl.gestureEventStores[this.key]}get timeoutStore(){return this.ctrl.gestureTimeoutStores[this.key]}get config(){return this.ctrl.config[this.key]}get sharedConfig(){return this.ctrl.config.shared}get handler(){return this.ctrl.handlers[this.key]}reset(){const{state:e,shared:t,ingKey:i,args:r}=this;t[i]=e._active=e.active=e._blocked=e._force=!1,e._step=[!1,!1],e.intentional=!1,e._movement=[0,0],e._distance=[0,0],e._direction=[0,0],e._delta=[0,0],e._bounds=[[-1/0,1/0],[-1/0,1/0]],e.args=r,e.axis=void 0,e.memo=void 0,e.elapsedTime=e.timeDelta=0,e.direction=[0,0],e.distance=[0,0],e.overflow=[0,0],e._movementBound=[!1,!1],e.velocity=[0,0],e.movement=[0,0],e.delta=[0,0],e.timeStamp=0}start(e){const t=this.state,i=this.config;t._active||(this.reset(),this.computeInitial(),t._active=!0,t.target=e.target,t.currentTarget=e.currentTarget,t.lastOffset=i.from?Cg(i.from,t):t.offset,t.offset=t.lastOffset,t.startTime=t.timeStamp=e.timeStamp)}computeValues(e){const t=this.state;t._values=e,t.values=this.config.transform(e)}computeInitial(){const e=this.state;e._initial=e._values,e.initial=e.values}compute(e){const{state:t,config:i,shared:r}=this;t.args=this.args;let s=0;if(e&&(t.event=e,i.preventDefault&&e.cancelable&&t.event.preventDefault(),t.type=e.type,r.touches=this.ctrl.pointerIds.size||this.ctrl.touchIds.size,r.locked=!!document.pointerLockElement,Object.assign(r,pq(e)),r.down=r.pressed=r.buttons%2===1||r.touches>0,s=e.timeStamp-t.timeStamp,t.timeStamp=e.timeStamp,t.elapsedTime=t.timeStamp-t.startTime),t._active){const k=t._delta.map(Math.abs);Fi.addTo(t._distance,k)}this.axisIntent&&this.axisIntent(e);const[o,a]=t._movement,[l,c]=i.threshold,{_step:h,values:f}=t;if(i.hasCustomTransform?(h[0]===!1&&(h[0]=Math.abs(o)>=l&&f[0]),h[1]===!1&&(h[1]=Math.abs(a)>=c&&f[1])):(h[0]===!1&&(h[0]=Math.abs(o)>=l&&Math.sign(o)*l),h[1]===!1&&(h[1]=Math.abs(a)>=c&&Math.sign(a)*c)),t.intentional=h[0]!==!1||h[1]!==!1,!t.intentional)return;const d=[0,0];if(i.hasCustomTransform){const[k,I]=f;d[0]=h[0]!==!1?k-h[0]:0,d[1]=h[1]!==!1?I-h[1]:0}else d[0]=h[0]!==!1?o-h[0]:0,d[1]=h[1]!==!1?a-h[1]:0;this.restrictToAxis&&!t._blocked&&this.restrictToAxis(d);const m=t.offset,g=t._active&&!t._blocked||t.active;g&&(t.first=t._active&&!t.active,t.last=!t._active&&t.active,t.active=r[this.ingKey]=t._active,e&&(t.first&&("bounds"in i&&(t._bounds=Cg(i.bounds,t)),this.setup&&this.setup()),t.movement=d,this.computeOffset()));const[E,C]=t.offset,[[S,v],[y,w]]=t._bounds;t.overflow=[E<S?-1:E>v?1:0,C<y?-1:C>w?1:0],t._movementBound[0]=t.overflow[0]?t._movementBound[0]===!1?t._movement[0]:t._movementBound[0]:!1,t._movementBound[1]=t.overflow[1]?t._movementBound[1]===!1?t._movement[1]:t._movementBound[1]:!1;const x=t._active?i.rubberband||[0,0]:[0,0];if(t.offset=eq(t._bounds,t.offset,x),t.delta=Fi.sub(t.offset,m),this.computeMovement(),g&&(!t.last||s>mq)){t.delta=Fi.sub(t.offset,m);const k=t.delta.map(Math.abs);Fi.addTo(t.distance,k),t.direction=t.delta.map(Math.sign),t._direction=t._delta.map(Math.sign),!t.first&&s>0&&(t.velocity=[k[0]/s,k[1]/s],t.timeDelta=s)}}emit(){const e=this.state,t=this.shared,i=this.config;if(e._active||this.clean(),(e._blocked||!e.intentional)&&!e._force&&!i.triggerAllEvents)return;const r=this.handler(Rn(Rn(Rn({},t),e),{},{[this.aliasKey]:e.values}));r!==void 0&&(e.memo=r)}clean(){this.eventStore.clean(),this.timeoutStore.clean()}}function gq([n,e],t){const i=Math.abs(n),r=Math.abs(e);if(i>r&&i>t)return"x";if(r>i&&r>t)return"y"}class Aq extends Sq{constructor(...e){super(...e),cr(this,"aliasKey","xy")}reset(){super.reset(),this.state.axis=void 0}init(){this.state.offset=[0,0],this.state.lastOffset=[0,0]}computeOffset(){this.state.offset=Fi.add(this.state.lastOffset,this.state.movement)}computeMovement(){this.state.movement=Fi.sub(this.state.offset,this.state.lastOffset)}axisIntent(e){const t=this.state,i=this.config;if(!t.axis&&e){const r=typeof i.axisThreshold=="object"?i.axisThreshold[OD(e)]:i.axisThreshold;t.axis=gq(t._movement,r)}t._blocked=(i.lockDirection||!!i.axis)&&!t.axis||!!i.axis&&i.axis!==t.axis}restrictToAxis(e){if(this.config.axis||this.config.lockDirection)switch(this.state.axis){case"x":e[1]=0;break;case"y":e[0]=0;break}}}const yq=n=>n,dJ=.15,PD={enabled(n=!0){return n},eventOptions(n,e,t){return Rn(Rn({},t.shared.eventOptions),n)},preventDefault(n=!1){return n},triggerAllEvents(n=!1){return n},rubberband(n=0){switch(n){case!0:return[dJ,dJ];case!1:return[0,0];default:return Fi.toVector(n)}},from(n){if(typeof n=="function")return n;if(n!=null)return Fi.toVector(n)},transform(n,e,t){const i=n||t.shared.transform;return this.hasCustomTransform=!!i,i||yq},threshold(n){return Fi.toVector(n,0)}},Eq=0,jf=Rn(Rn({},PD),{},{axis(n,e,{axis:t}){if(this.lockDirection=t==="lock",!this.lockDirection)return t},axisThreshold(n=Eq){return n},bounds(n={}){if(typeof n=="function")return s=>jf.bounds(n(s));if("current"in n)return()=>n.current;if(typeof HTMLElement=="function"&&n instanceof HTMLElement)return n;const{left:e=-1/0,right:t=1/0,top:i=-1/0,bottom:r=1/0}=n;return[[e,t],[i,r]]}}),mJ={ArrowRight:(n,e=1)=>[n*e,0],ArrowLeft:(n,e=1)=>[-1*n*e,0],ArrowUp:(n,e=1)=>[0,-1*n*e],ArrowDown:(n,e=1)=>[0,n*e]};class Cq extends Aq{constructor(...e){super(...e),cr(this,"ingKey","dragging")}reset(){super.reset();const e=this.state;e._pointerId=void 0,e._pointerActive=!1,e._keyboardActive=!1,e._preventScroll=!1,e._delayed=!1,e.swipe=[0,0],e.tap=!1,e.canceled=!1,e.cancel=this.cancel.bind(this)}setup(){const e=this.state;if(e._bounds instanceof HTMLElement){const t=e._bounds.getBoundingClientRect(),i=e.currentTarget.getBoundingClientRect(),r={left:t.left-i.left+e.offset[0],right:t.right-i.right+e.offset[0],top:t.top-i.top+e.offset[1],bottom:t.bottom-i.bottom+e.offset[1]};e._bounds=jf.bounds(r)}}cancel(){const e=this.state;e.canceled||(e.canceled=!0,e._active=!1,setTimeout(()=>{this.compute(),this.emit()},0))}setActive(){this.state._active=this.state._pointerActive||this.state._keyboardActive}clean(){this.pointerClean(),this.state._pointerActive=!1,this.state._keyboardActive=!1,super.clean()}pointerDown(e){const t=this.config,i=this.state;if(e.buttons!=null&&(Array.isArray(t.pointerButtons)?!t.pointerButtons.includes(e.buttons):t.pointerButtons!==-1&&t.pointerButtons!==e.buttons))return;const r=this.ctrl.setEventIds(e);t.pointerCapture&&e.target.setPointerCapture(e.pointerId),!(r&&r.size>1&&i._pointerActive)&&(this.start(e),this.setupPointer(e),i._pointerId=sE(e),i._pointerActive=!0,this.computeValues(pJ(e)),this.computeInitial(),t.preventScrollAxis&&OD(e)!=="mouse"?(i._active=!1,this.setupScrollPrevention(e)):t.delay>0?(this.setupDelayTrigger(e),t.triggerAllEvents&&(this.compute(e),this.emit())):this.startPointerDrag(e))}startPointerDrag(e){const t=this.state;t._active=!0,t._preventScroll=!0,t._delayed=!1,this.compute(e),this.emit()}pointerMove(e){const t=this.state,i=this.config;if(!t._pointerActive)return;const r=sE(e);if(t._pointerId!==void 0&&r!==t._pointerId)return;const s=pJ(e);if(document.pointerLockElement===e.target?t._delta=[e.movementX,e.movementY]:(t._delta=Fi.sub(s,t._values),this.computeValues(s)),Fi.addTo(t._movement,t._delta),this.compute(e),t._delayed&&t.intentional){this.timeoutStore.remove("dragDelay"),t.active=!1,this.startPointerDrag(e);return}if(i.preventScrollAxis&&!t._preventScroll)if(t.axis)if(t.axis===i.preventScrollAxis||i.preventScrollAxis==="xy"){t._active=!1,this.clean();return}else{this.timeoutStore.remove("startPointerDrag"),this.startPointerDrag(e);return}else return;this.emit()}pointerUp(e){this.ctrl.setEventIds(e);try{this.config.pointerCapture&&e.target.hasPointerCapture(e.pointerId)&&e.target.releasePointerCapture(e.pointerId)}catch{}const t=this.state,i=this.config;if(!t._active||!t._pointerActive)return;const r=sE(e);if(t._pointerId!==void 0&&r!==t._pointerId)return;this.state._pointerActive=!1,this.setActive(),this.compute(e);const[s,o]=t._distance;if(t.tap=s<=i.tapsThreshold&&o<=i.tapsThreshold,t.tap&&i.filterTaps)t._force=!0;else{const[a,l]=t._delta,[c,h]=t._movement,[f,d]=i.swipe.velocity,[m,g]=i.swipe.distance,E=i.swipe.duration;if(t.elapsedTime<E){const C=Math.abs(a/t.timeDelta),S=Math.abs(l/t.timeDelta);C>f&&Math.abs(c)>m&&(t.swipe[0]=Math.sign(a)),S>d&&Math.abs(h)>g&&(t.swipe[1]=Math.sign(l))}}this.emit()}pointerClick(e){!this.state.tap&&e.detail>0&&(e.preventDefault(),e.stopPropagation())}setupPointer(e){const t=this.config,i=t.device;t.pointerLock&&e.currentTarget.requestPointerLock(),t.pointerCapture||(this.eventStore.add(this.sharedConfig.window,i,"change",this.pointerMove.bind(this)),this.eventStore.add(this.sharedConfig.window,i,"end",this.pointerUp.bind(this)),this.eventStore.add(this.sharedConfig.window,i,"cancel",this.pointerUp.bind(this)))}pointerClean(){this.config.pointerLock&&document.pointerLockElement===this.state.currentTarget&&document.exitPointerLock()}preventScroll(e){this.state._preventScroll&&e.cancelable&&e.preventDefault()}setupScrollPrevention(e){this.state._preventScroll=!1,vq(e);const t=this.eventStore.add(this.sharedConfig.window,"touch","change",this.preventScroll.bind(this),{passive:!1});this.eventStore.add(this.sharedConfig.window,"touch","end",t),this.eventStore.add(this.sharedConfig.window,"touch","cancel",t),this.timeoutStore.add("startPointerDrag",this.startPointerDrag.bind(this),this.config.preventScrollDelay,e)}setupDelayTrigger(e){this.state._delayed=!0,this.timeoutStore.add("dragDelay",()=>{this.state._step=[0,0],this.startPointerDrag(e)},this.config.delay)}keyDown(e){const t=mJ[e.key];if(t){const i=this.state,r=e.shiftKey?10:e.altKey?.1:1;this.start(e),i._delta=t(this.config.keyboardDisplacement,r),i._keyboardActive=!0,Fi.addTo(i._movement,i._delta),this.compute(e),this.emit()}}keyUp(e){e.key in mJ&&(this.state._keyboardActive=!1,this.setActive(),this.compute(e),this.emit())}bind(e){const t=this.config.device;e(t,"start",this.pointerDown.bind(this)),this.config.pointerCapture&&(e(t,"change",this.pointerMove.bind(this)),e(t,"end",this.pointerUp.bind(this)),e(t,"cancel",this.pointerUp.bind(this)),e("lostPointerCapture","",this.pointerUp.bind(this))),this.config.keys&&(e("key","down",this.keyDown.bind(this)),e("key","up",this.keyUp.bind(this))),this.config.filterTaps&&e("click","",this.pointerClick.bind(this),{capture:!0,passive:!1})}}function vq(n){"persist"in n&&typeof n.persist=="function"&&n.persist()}const Xf=typeof window<"u"&&window.document&&window.document.createElement;function ND(){return Xf&&"ontouchstart"in window}function Uq(){return ND()||Xf&&window.navigator.maxTouchPoints>1}function wq(){return Xf&&"onpointerdown"in window}function Mq(){return Xf&&"exitPointerLock"in window.document}function kq(){try{return"constructor"in GestureEvent}catch{return!1}}const $r={isBrowser:Xf,gesture:kq(),touch:ND(),touchscreen:Uq(),pointer:wq(),pointerLock:Mq()},xq=250,Tq=180,Jq=.5,Iq=50,Lq=250,Bq=10,SJ={mouse:0,touch:0,pen:8},Kq=Rn(Rn({},jf),{},{device(n,e,{pointer:{touch:t=!1,lock:i=!1,mouse:r=!1}={}}){return this.pointerLock=i&&$r.pointerLock,$r.touch&&t?"touch":this.pointerLock?"mouse":$r.pointer&&!r?"pointer":$r.touch?"touch":"mouse"},preventScrollAxis(n,e,{preventScroll:t}){if(this.preventScrollDelay=typeof t=="number"?t:t||t===void 0&&n?xq:void 0,!(!$r.touchscreen||t===!1))return n||(t!==void 0?"y":void 0)},pointerCapture(n,e,{pointer:{capture:t=!0,buttons:i=1,keys:r=!0}={}}){return this.pointerButtons=i,this.keys=r,!this.pointerLock&&this.device==="pointer"&&t},threshold(n,e,{filterTaps:t=!1,tapsThreshold:i=3,axis:r=void 0}){const s=Fi.toVector(n,t?i:r?1:0);return this.filterTaps=t,this.tapsThreshold=i,s},swipe({velocity:n=Jq,distance:e=Iq,duration:t=Lq}={}){return{velocity:this.transform(Fi.toVector(n)),distance:this.transform(Fi.toVector(e)),duration:t}},delay(n=0){switch(n){case!0:return Tq;case!1:return 0;default:return n}},axisThreshold(n){return n?Rn(Rn({},SJ),n):SJ},keyboardDisplacement(n=Bq){return n}});Rn(Rn({},PD),{},{device(n,e,{shared:t,pointer:{touch:i=!1}={}}){if(t.target&&!$r.touch&&$r.gesture)return"gesture";if($r.touch&&i)return"touch";if($r.touchscreen){if($r.pointer)return"pointer";if($r.touch)return"touch"}},bounds(n,e,{scaleBounds:t={},angleBounds:i={}}){const r=o=>{const a=fJ(Cg(t,o),{min:-1/0,max:1/0});return[a.min,a.max]},s=o=>{const a=fJ(Cg(i,o),{min:-1/0,max:1/0});return[a.min,a.max]};return typeof t!="function"&&typeof i!="function"?[r(),s()]:o=>[r(o),s(o)]},threshold(n,e,t){return this.lockDirection=t.axis==="lock",Fi.toVector(n,this.lockDirection?[.1,3]:0)},modifierKey(n){return n===void 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        varying vec3 vWorldPosition;
        void main() 
        {
            vec4 worldPosition = ( modelMatrix * vec4( position, 1.0 ) );
            vWorldPosition = worldPosition.xyz;
            
            gl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );
        }
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        #define ENVMAP_TYPE_CUBE_UV
        varying vec3 vWorldPosition;
        uniform float radius;
        uniform float height;
        uniform float angle;
        #ifdef ENVMAP_TYPE_CUBE
            uniform samplerCube map;
        #else
            uniform sampler2D map;
        #endif
        // From: https://www.shadertoy.com/view/4tsBD7
        float diskIntersectWithBackFaceCulling( vec3 ro, vec3 rd, vec3 c, vec3 n, float r ) 
        {
            float d = dot ( rd, n );
            
            if( d > 0.0 ) { return 1e6; }
            
            vec3  o = ro - c;
            float t = - dot( n, o ) / d;
            vec3  q = o + rd * t;
            
            return ( dot( q, q ) < r * r ) ? t : 1e6;
        }
        // From: https://www.iquilezles.org/www/articles/intersectors/intersectors.htm
        float sphereIntersect( vec3 ro, vec3 rd, vec3 ce, float ra ) 
        {
            vec3 oc = ro - ce;
            float b = dot( oc, rd );
            float c = dot( oc, oc ) - ra * ra;
            float h = b * b - c;
            
            if( h < 0.0 ) { return -1.0; }
            
            h = sqrt( h );
            
            return - b + h;
        }
        vec3 project() 
        {
            vec3 p = normalize( vWorldPosition );
            vec3 camPos = cameraPosition;
            camPos.y -= height;
            float intersection = sphereIntersect( camPos, p, vec3( 0.0 ), radius );
            if( intersection > 0.0 ) {
                
                vec3 h = vec3( 0.0, - height, 0.0 );
                float intersection2 = diskIntersectWithBackFaceCulling( camPos, p, h, vec3( 0.0, 1.0, 0.0 ), radius );
                p = ( camPos + min( intersection, intersection2 ) * p ) / radius;
            } else {
                p = vec3( 0.0, 1.0, 0.0 );
            }
            return p;
        }
        #include <common>
        #include <cube_uv_reflection_fragment>
        void main() 
        {
            vec3 projectedWorldPosition = project();
            
            #ifdef ENVMAP_TYPE_CUBE
                vec3 outcolor = textureCube( map, projectedWorldPosition ).rgb;
            #else
                vec3 direction = normalize( projectedWorldPosition );
                vec2 uv = equirectUv( direction );
                vec3 outcolor = texture2D( map, uv ).rgb;
            #endif
            gl_FragColor = vec4( outcolor, 1.0 );
            #include <tonemapping_fragment>
            #include <${parseInt(oh.replace(/\D+/g,""))>=154?"colorspace_fragment":"encodings_fragment"}>
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Zt={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_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_TEXTURE_WEBP:"EXT_texture_webp",EXT_TEXTURE_AVIF:"EXT_texture_avif",EXT_MESHOPT_COMPRESSION:"EXT_meshopt_compression",EXT_MESH_GPU_INSTANCING:"EXT_mesh_gpu_instancing"};class f9{constructor(e){this.parser=e,this.name=Zt.KHR_LIGHTS_PUNCTUAL,this.cache={refs:{},uses:{}}}_markDefs(){const e=this.parser,t=this.parser.json.nodes||[];for(let i=0,r=t.length;i<r;i++){const s=t[i];s.extensions&&s.extensions[this.name]&&s.extensions[this.name].light!==void 0&&e._addNodeRef(this.cache,s.extensions[this.name].light)}}_loadLight(e){const t=this.parser,i="light:"+e;let r=t.cache.get(i);if(r)return r;const s=t.json,l=((s.extensions&&s.extensions[this.name]||{}).lights||[])[e];let c;const h=new ze(16777215);l.color!==void 0&&h.fromArray(l.color);const f=l.range!==void 0?l.range:0;switch(l.type){case"directional":c=new MA(h),c.target.position.set(0,0,-1),c.add(c.target);break;case"point":c=new Cf(h),c.distance=f;break;case"spot":c=new wA(h),c.distance=f,l.spot=l.spot||{},l.spot.innerConeAngle=l.spot.innerConeAngle!==void 0?l.spot.innerConeAngle:0,l.spot.outerConeAngle=l.spot.outerConeAngle!==void 0?l.spot.outerConeAngle:Math.PI/4,c.angle=l.spot.outerConeAngle,c.penumbra=1-l.spot.innerConeAngle/l.spot.outerConeAngle,c.target.position.set(0,0,-1),c.add(c.target);break;default:throw new Error("THREE.GLTFLoader: Unexpected light type: "+l.type)}return c.position.set(0,0,0),c.decay=2,Aa(c,l),l.intensity!==void 0&&(c.intensity=l.intensity),c.name=t.createUniqueName(l.name||"light_"+e),r=Promise.resolve(c),t.cache.add(i,r),r}getDependency(e,t){if(e==="light")return this._loadLight(t)}createNodeAttachment(e){const t=this,i=this.parser,s=i.json.nodes[e],a=(s.extensions&&s.extensions[this.name]||{}).light;return a===void 0?null:this._loadLight(a).then(function(l){return i._getNodeRef(t.cache,a,l)})}}class d9{constructor(){this.name=Zt.KHR_MATERIALS_UNLIT}getMaterialType(){return Ir}extendParams(e,t,i){const r=[];e.color=new ze(1,1,1),e.opacity=1;const s=t.pbrMetallicRoughness;if(s){if(Array.isArray(s.baseColorFactor)){const o=s.baseColorFactor;e.color.fromArray(o),e.opacity=o[3]}s.baseColorTexture!==void 0&&r.push(i.assignTexture(e,"map",s.baseColorTexture,3001))}return Promise.all(r)}}class m9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_EMISSIVE_STRENGTH}extendMaterialParams(e,t){const r=this.parser.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=r.extensions[this.name].emissiveStrength;return s!==void 0&&(t.emissiveIntensity=s),Promise.resolve()}}class S9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_CLEARCOAT}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const i=this.parser,r=i.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=[],o=r.extensions[this.name];if(o.clearcoatFactor!==void 0&&(t.clearcoat=o.clearcoatFactor),o.clearcoatTexture!==void 0&&s.push(i.assignTexture(t,"clearcoatMap",o.clearcoatTexture)),o.clearcoatRoughnessFactor!==void 0&&(t.clearcoatRoughness=o.clearcoatRoughnessFactor),o.clearcoatRoughnessTexture!==void 0&&s.push(i.assignTexture(t,"clearcoatRoughnessMap",o.clearcoatRoughnessTexture)),o.clearcoatNormalTexture!==void 0&&(s.push(i.assignTexture(t,"clearcoatNormalMap",o.clearcoatNormalTexture)),o.clearcoatNormalTexture.scale!==void 0)){const a=o.clearcoatNormalTexture.scale;t.clearcoatNormalScale=new we(a,a)}return Promise.all(s)}}class g9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_IRIDESCENCE}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const i=this.parser,r=i.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=[],o=r.extensions[this.name];return o.iridescenceFactor!==void 0&&(t.iridescence=o.iridescenceFactor),o.iridescenceTexture!==void 0&&s.push(i.assignTexture(t,"iridescenceMap",o.iridescenceTexture)),o.iridescenceIor!==void 0&&(t.iridescenceIOR=o.iridescenceIor),t.iridescenceThicknessRange===void 0&&(t.iridescenceThicknessRange=[100,400]),o.iridescenceThicknessMinimum!==void 0&&(t.iridescenceThicknessRange[0]=o.iridescenceThicknessMinimum),o.iridescenceThicknessMaximum!==void 0&&(t.iridescenceThicknessRange[1]=o.iridescenceThicknessMaximum),o.iridescenceThicknessTexture!==void 0&&s.push(i.assignTexture(t,"iridescenceThicknessMap",o.iridescenceThicknessTexture)),Promise.all(s)}}class A9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_SHEEN}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const i=this.parser,r=i.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=[];t.sheenColor=new ze(0,0,0),t.sheenRoughness=0,t.sheen=1;const o=r.extensions[this.name];return o.sheenColorFactor!==void 0&&t.sheenColor.fromArray(o.sheenColorFactor),o.sheenRoughnessFactor!==void 0&&(t.sheenRoughness=o.sheenRoughnessFactor),o.sheenColorTexture!==void 0&&s.push(i.assignTexture(t,"sheenColorMap",o.sheenColorTexture,3001)),o.sheenRoughnessTexture!==void 0&&s.push(i.assignTexture(t,"sheenRoughnessMap",o.sheenRoughnessTexture)),Promise.all(s)}}class y9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_TRANSMISSION}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const i=this.parser,r=i.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=[],o=r.extensions[this.name];return o.transmissionFactor!==void 0&&(t.transmission=o.transmissionFactor),o.transmissionTexture!==void 0&&s.push(i.assignTexture(t,"transmissionMap",o.transmissionTexture)),Promise.all(s)}}class E9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_VOLUME}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const i=this.parser,r=i.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=[],o=r.extensions[this.name];t.thickness=o.thicknessFactor!==void 0?o.thicknessFactor:0,o.thicknessTexture!==void 0&&s.push(i.assignTexture(t,"thicknessMap",o.thicknessTexture)),t.attenuationDistance=o.attenuationDistance||1/0;const a=o.attenuationColor||[1,1,1];return t.attenuationColor=new ze(a[0],a[1],a[2]),Promise.all(s)}}class C9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_IOR}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const r=this.parser.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=r.extensions[this.name];return t.ior=s.ior!==void 0?s.ior:1.5,Promise.resolve()}}class v9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_SPECULAR}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const i=this.parser,r=i.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=[],o=r.extensions[this.name];t.specularIntensity=o.specularFactor!==void 0?o.specularFactor:1,o.specularTexture!==void 0&&s.push(i.assignTexture(t,"specularIntensityMap",o.specularTexture));const a=o.specularColorFactor||[1,1,1];return t.specularColor=new ze(a[0],a[1],a[2]),o.specularColorTexture!==void 0&&s.push(i.assignTexture(t,"specularColorMap",o.specularColorTexture,3001)),Promise.all(s)}}class U9{constructor(e){this.parser=e,this.name=Zt.KHR_MATERIALS_ANISOTROPY}getMaterialType(e){const i=this.parser.json.materials[e];return!i.extensions||!i.extensions[this.name]?null:uo}extendMaterialParams(e,t){const i=this.parser,r=i.json.materials[e];if(!r.extensions||!r.extensions[this.name])return Promise.resolve();const s=[],o=r.extensions[this.name];return o.anisotropyStrength!==void 0&&(t.anisotropy=o.anisotropyStrength),o.anisotropyRotation!==void 0&&(t.anisotropyRotation=o.anisotropyRotation),o.anisotropyTexture!==void 0&&s.push(i.assignTexture(t,"anisotropyMap",o.anisotropyTexture)),Promise.all(s)}}class w9{constructor(e){this.parser=e,this.name=Zt.KHR_TEXTURE_BASISU}loadTexture(e){const t=this.parser,i=t.json,r=i.textures[e];if(!r.extensions||!r.extensions[this.name])return null;const s=r.extensions[this.name],o=t.options.ktx2Loader;if(!o){if(i.extensionsRequired&&i.extensionsRequired.indexOf(this.name)>=0)throw new Error("THREE.GLTFLoader: setKTX2Loader must be called before loading KTX2 textures");return null}return t.loadTextureImage(e,s.source,o)}}class M9{constructor(e){this.parser=e,this.name=Zt.EXT_TEXTURE_WEBP,this.isSupported=null}loadTexture(e){const t=this.name,i=this.parser,r=i.json,s=r.textures[e];if(!s.extensions||!s.extensions[t])return null;const o=s.extensions[t],a=r.images[o.source];let l=i.textureLoader;if(a.uri){const c=i.options.manager.getHandler(a.uri);c!==null&&(l=c)}return this.detectSupport().then(function(c){if(c)return i.loadTextureImage(e,o.source,l);if(r.extensionsRequired&&r.extensionsRequired.indexOf(t)>=0)throw new Error("THREE.GLTFLoader: WebP required by asset but unsupported.");return i.loadTexture(e)})}detectSupport(){return this.isSupported||(this.isSupported=new Promise(function(e){const t=new Image;t.src="data:image/webp;base64,UklGRiIAAABXRUJQVlA4IBYAAAAwAQCdASoBAAEADsD+JaQAA3AAAAAA",t.onload=t.onerror=function(){e(t.height===1)}})),this.isSupported}}class k9{constructor(e){this.parser=e,this.name=Zt.EXT_TEXTURE_AVIF,this.isSupported=null}loadTexture(e){const t=this.name,i=this.parser,r=i.json,s=r.textures[e];if(!s.extensions||!s.extensions[t])return null;const o=s.extensions[t],a=r.images[o.source];let l=i.textureLoader;if(a.uri){const c=i.options.manager.getHandler(a.uri);c!==null&&(l=c)}return this.detectSupport().then(function(c){if(c)return i.loadTextureImage(e,o.source,l);if(r.extensionsRequired&&r.extensionsRequired.indexOf(t)>=0)throw new Error("THREE.GLTFLoader: AVIF required by asset but unsupported.");return i.loadTexture(e)})}detectSupport(){return this.isSupported||(this.isSupported=new Promise(function(e){const t=new Image;t.src="data:image/avif;base64,AAAAIGZ0eXBhdmlmAAAAAGF2aWZtaWYxbWlhZk1BMUIAAADybWV0YQAAAAAAAAAoaGRscgAAAAAAAAAAcGljdAAAAAAAAAAAAAAAAGxpYmF2aWYAAAAADnBpdG0AAAAAAAEAAAAeaWxvYwAAAABEAAABAAEAAAABAAABGgAAABcAAAAoaWluZgAAAAAAAQAAABppbmZlAgAAAAABAABhdjAxQ29sb3IAAAAAamlwcnAAAABLaXBjbwAAABRpc3BlAAAAAAAAAAEAAAABAAAAEHBpeGkAAAAAAwgICAAAAAxhdjFDgQAMAAAAABNjb2xybmNseAACAAIABoAAAAAXaXBtYQAAAAAAAAABAAEEAQKDBAAAAB9tZGF0EgAKCBgABogQEDQgMgkQAAAAB8dSLfI=",t.onload=t.onerror=function(){e(t.height===1)}})),this.isSupported}}class x9{constructor(e){this.name=Zt.EXT_MESHOPT_COMPRESSION,this.parser=e}loadBufferView(e){const t=this.parser.json,i=t.bufferViews[e];if(i.extensions&&i.extensions[this.name]){const r=i.extensions[this.name],s=this.parser.getDependency("buffer",r.buffer),o=this.parser.options.meshoptDecoder;if(!o||!o.supported){if(t.extensionsRequired&&t.extensionsRequired.indexOf(this.name)>=0)throw new Error("THREE.GLTFLoader: setMeshoptDecoder must be called before loading compressed files");return null}return s.then(function(a){const l=r.byteOffset||0,c=r.byteLength||0,h=r.count,f=r.byteStride,d=new Uint8Array(a,l,c);return o.decodeGltfBufferAsync?o.decodeGltfBufferAsync(h,f,d,r.mode,r.filter).then(function(m){return m.buffer}):o.ready.then(function(){const m=new ArrayBuffer(h*f);return o.decodeGltfBuffer(new Uint8Array(m),h,f,d,r.mode,r.filter),m})})}else return null}}class T9{constructor(e){this.name=Zt.EXT_MESH_GPU_INSTANCING,this.parser=e}createNodeMesh(e){const t=this.parser.json,i=t.nodes[e];if(!i.extensions||!i.extensions[this.name]||i.mesh===void 0)return null;const r=t.meshes[i.mesh];for(const c of r.primitives)if(c.mode!==jr.TRIANGLES&&c.mode!==jr.TRIANGLE_STRIP&&c.mode!==jr.TRIANGLE_FAN&&c.mode!==void 0)return null;const o=i.extensions[this.name].attributes,a=[],l={};for(const c in o)a.push(this.parser.getDependency("accessor",o[c]).then(h=>(l[c]=h,l[c])));return a.length<1?null:(a.push(this.parser.createNodeMesh(e)),Promise.all(a).then(c=>{const h=c.pop(),f=h.isGroup?h.children:[h],d=c[0].count,m=[];for(const g of f){const E=new tt,C=new N,S=new zn,v=new N(1,1,1),y=new pw(g.geometry,g.material,d);for(let w=0;w<d;w++)l.TRANSLATION&&C.fromBufferAttribute(l.TRANSLATION,w),l.ROTATION&&S.fromBufferAttribute(l.ROTATION,w),l.SCALE&&v.fromBufferAttribute(l.SCALE,w),y.setMatrixAt(w,E.compose(C,S,v));for(const w in l)w!=="TRANSLATION"&&w!=="ROTATION"&&w!=="SCALE"&&g.geometry.setAttribute(w,l[w]);Wt.prototype.copy.call(y,g),this.parser.assignFinalMaterial(y),m.push(y)}return h.isGroup?(h.clear(),h.add(...m),h):m[0]}))}}const MO="glTF",up=12,UI={JSON:1313821514,BIN:5130562};class J9{constructor(e){this.name=Zt.KHR_BINARY_GLTF,this.content=null,this.body=null;const t=new DataView(e,0,up);if(this.header={magic:Kr.decodeText(new Uint8Array(e.slice(0,4))),version:t.getUint32(4,!0),length:t.getUint32(8,!0)},this.header.magic!==MO)throw new Error("THREE.GLTFLoader: Unsupported glTF-Binary header.");if(this.header.version<2)throw new Error("THREE.GLTFLoader: Legacy binary file detected.");const i=this.header.length-up,r=new DataView(e,up);let s=0;for(;s<i;){const o=r.getUint32(s,!0);s+=4;const a=r.getUint32(s,!0);if(s+=4,a===UI.JSON){const l=new Uint8Array(e,up+s,o);this.content=Kr.decodeText(l)}else if(a===UI.BIN){const l=up+s;this.body=e.slice(l,l+o)}s+=o}if(this.content===null)throw new Error("THREE.GLTFLoader: JSON content not found.")}}class I9{constructor(e,t){if(!t)throw new Error("THREE.GLTFLoader: No DRACOLoader instance provided.");this.name=Zt.KHR_DRACO_MESH_COMPRESSION,this.json=e,this.dracoLoader=t,this.dracoLoader.preload()}decodePrimitive(e,t){const i=this.json,r=this.dracoLoader,s=e.extensions[this.name].bufferView,o=e.extensions[this.name].attributes,a={},l={},c={};for(const h in o){const f=Wv[h]||h.toLowerCase();a[f]=o[h]}for(const h in e.attributes){const f=Wv[h]||h.toLowerCase();if(o[h]!==void 0){const d=i.accessors[e.attributes[h]],m=bu[d.componentType];c[f]=m.name,l[f]=d.normalized===!0}}return t.getDependency("bufferView",s).then(function(h){return new Promise(function(f){r.decodeDracoFile(h,function(d){for(const m in d.attributes){const g=d.attributes[m],E=l[m];E!==void 0&&(g.normalized=E)}f(d)},a,c)})})}}class L9{constructor(){this.name=Zt.KHR_TEXTURE_TRANSFORM}extendTexture(e,t){return(t.texCoord===void 0||t.texCoord===e.channel)&&t.offset===void 0&&t.rotation===void 0&&t.scale===void 0||(e=e.clone(),t.texCoord!==void 0&&(e.channel=t.texCoord),t.offset!==void 0&&e.offset.fromArray(t.offset),t.rotation!==void 0&&(e.rotation=t.rotation),t.scale!==void 0&&e.repeat.fromArray(t.scale),e.needsUpdate=!0),e}}class B9{constructor(){this.name=Zt.KHR_MESH_QUANTIZATION}}class kO extends hh{constructor(e,t,i,r){super(e,t,i,r)}copySampleValue_(e){const t=this.resultBuffer,i=this.sampleValues,r=this.valueSize,s=e*r*3+r;for(let o=0;o!==r;o++)t[o]=i[s+o];return t}interpolate_(e,t,i,r){const s=this.resultBuffer,o=this.sampleValues,a=this.valueSize,l=a*2,c=a*3,h=r-t,f=(i-t)/h,d=f*f,m=d*f,g=e*c,E=g-c,C=-2*m+3*d,S=m-d,v=1-C,y=S-d+f;for(let w=0;w!==a;w++){const x=o[E+w+a],k=o[E+w+l]*h,I=o[g+w+a],R=o[g+w]*h;s[w]=v*x+y*k+C*I+S*R}return s}}const K9=new zn;class R9 extends kO{interpolate_(e,t,i,r){const s=super.interpolate_(e,t,i,r);return K9.fromArray(s).normalize().toArray(s),s}}const jr={FLOAT:5126,FLOAT_MAT3:35675,FLOAT_MAT4:35676,FLOAT_VEC2:35664,FLOAT_VEC3:35665,FLOAT_VEC4:35666,LINEAR:9729,REPEAT:10497,SAMPLER_2D:35678,POINTS:0,LINES:1,LINE_LOOP:2,LINE_STRIP:3,TRIANGLES:4,TRIANGLE_STRIP:5,TRIANGLE_FAN:6,UNSIGNED_BYTE:5121,UNSIGNED_SHORT:5123},bu={5120:Int8Array,5121:Uint8Array,5122:Int16Array,5123:Uint16Array,5125:Uint32Array,5126:Float32Array},wI={9728:Wn,9729:pn,9984:lf,9985:$g,9986:Bu,9987:ro},MI={33071:oi,33648:Gu,10497:io},SE={SCALAR:1,VEC2:2,VEC3:3,VEC4:4,MAT2:4,MAT3:9,MAT4:16},Wv={POSITION:"position",NORMAL:"normal",TANGENT:"tangent",...V7>=152?{TEXCOORD_0:"uv",TEXCOORD_1:"uv1",TEXCOORD_2:"uv2",TEXCOORD_3:"uv3"}:{TEXCOORD_0:"uv",TEXCOORD_1:"uv2"},COLOR_0:"color",WEIGHTS_0:"skinWeight",JOINTS_0:"skinIndex"},da={scale:"scale",translation:"position",rotation:"quaternion",weights:"morphTargetInfluences"},D9={CUBICSPLINE:void 0,LINEAR:tc,STEP:Vu},gE={OPAQUE:"OPAQUE",MASK:"MASK",BLEND:"BLEND"};function b9(n){return n.DefaultMaterial===void 0&&(n.DefaultMaterial=new qf({color:16777215,emissive:0,metalness:1,roughness:1,transparent:!1,depthTest:!0,side:to})),n.DefaultMaterial}function yl(n,e,t){for(const i in t.extensions)n[i]===void 0&&(e.userData.gltfExtensions=e.userData.gltfExtensions||{},e.userData.gltfExtensions[i]=t.extensions[i])}function Aa(n,e){e.extras!==void 0&&typeof e.extras=="object"&&Object.assign(n.userData,e.extras)}function O9(n,e,t){let i=!1,r=!1,s=!1;for(let c=0,h=e.length;c<h;c++){const f=e[c];if(f.POSITION!==void 0&&(i=!0),f.NORMAL!==void 0&&(r=!0),f.COLOR_0!==void 0&&(s=!0),i&&r&&s)break}if(!i&&!r&&!s)return Promise.resolve(n);const o=[],a=[],l=[];for(let c=0,h=e.length;c<h;c++){const f=e[c];if(i){const d=f.POSITION!==void 0?t.getDependency("accessor",f.POSITION):n.attributes.position;o.push(d)}if(r){const d=f.NORMAL!==void 0?t.getDependency("accessor",f.NORMAL):n.attributes.normal;a.push(d)}if(s){const d=f.COLOR_0!==void 0?t.getDependency("accessor",f.COLOR_0):n.attributes.color;l.push(d)}}return Promise.all([Promise.all(o),Promise.all(a),Promise.all(l)]).then(function(c){const h=c[0],f=c[1],d=c[2];return i&&(n.morphAttributes.position=h),r&&(n.morphAttributes.normal=f),s&&(n.morphAttributes.color=d),n.morphTargetsRelative=!0,n})}function F9(n,e){if(n.updateMorphTargets(),e.weights!==void 0)for(let t=0,i=e.weights.length;t<i;t++)n.morphTargetInfluences[t]=e.weights[t];if(e.extras&&Array.isArray(e.extras.targetNames)){const t=e.extras.targetNames;if(n.morphTargetInfluences.length===t.length){n.morphTargetDictionary={};for(let i=0,r=t.length;i<r;i++)n.morphTargetDictionary[t[i]]=i}}}function P9(n){let e;const t=n.extensions&&n.extensions[Zt.KHR_DRACO_MESH_COMPRESSION];if(t?e="draco:"+t.bufferView+":"+t.indices+":"+AE(t.attributes):e=n.indices+":"+AE(n.attributes)+":"+n.mode,n.targets!==void 0)for(let i=0,r=n.targets.length;i<r;i++)e+=":"+AE(n.targets[i]);return e}function AE(n){let e="";const t=Object.keys(n).sort();for(let i=0,r=t.length;i<r;i++)e+=t[i]+":"+n[t[i]]+";";return e}function Hv(n){switch(n){case Int8Array:return 1/127;case Uint8Array:return 1/255;case Int16Array:return 1/32767;case Uint16Array:return 1/65535;default:throw new Error("THREE.GLTFLoader: Unsupported normalized accessor component type.")}}function N9(n){return n.search(/\.jpe?g($|\?)/i)>0||n.search(/^data\:image\/jpeg/)===0?"image/jpeg":n.search(/\.webp($|\?)/i)>0||n.search(/^data\:image\/webp/)===0?"image/webp":"image/png"}const Q9=new tt;class W9{constructor(e={},t={}){this.json=e,this.extensions={},this.plugins={},this.options=t,this.cache=new p9,this.associations=new Map,this.primitiveCache={},this.nodeCache={},this.meshCache={refs:{},uses:{}},this.cameraCache={refs:{},uses:{}},this.lightCache={refs:{},uses:{}},this.sourceCache={},this.textureCache={},this.nodeNamesUsed={};let i=!1,r=!1,s=-1;typeof navigator<"u"&&typeof navigator.userAgent<"u"&&(i=/^((?!chrome|android).)*safari/i.test(navigator.userAgent)===!0,r=navigator.userAgent.indexOf("Firefox")>-1,s=r?navigator.userAgent.match(/Firefox\/([0-9]+)\./)[1]:-1),typeof createImageBitmap>"u"||i||r&&s<98?this.textureLoader=new ph(this.options.manager):this.textureLoader=new $R(this.options.manager),this.textureLoader.setCrossOrigin(this.options.crossOrigin),this.textureLoader.setRequestHeader(this.options.requestHeader),this.fileLoader=new yr(this.options.manager),this.fileLoader.setResponseType("arraybuffer"),this.options.crossOrigin==="use-credentials"&&this.fileLoader.setWithCredentials(!0)}setExtensions(e){this.extensions=e}setPlugins(e){this.plugins=e}parse(e,t){const i=this,r=this.json,s=this.extensions;this.cache.removeAll(),this.nodeCache={},this._invokeAll(function(o){return o._markDefs&&o._markDefs()}),Promise.all(this._invokeAll(function(o){return o.beforeRoot&&o.beforeRoot()})).then(function(){return Promise.all([i.getDependencies("scene"),i.getDependencies("animation"),i.getDependencies("camera")])}).then(function(o){const a={scene:o[0][r.scene||0],scenes:o[0],animations:o[1],cameras:o[2],asset:r.asset,parser:i,userData:{}};yl(s,a,r),Aa(a,r),Promise.all(i._invokeAll(function(l){return l.afterRoot&&l.afterRoot(a)})).then(function(){e(a)})}).catch(t)}_markDefs(){const e=this.json.nodes||[],t=this.json.skins||[],i=this.json.meshes||[];for(let r=0,s=t.length;r<s;r++){const o=t[r].joints;for(let a=0,l=o.length;a<l;a++)e[o[a]].isBone=!0}for(let r=0,s=e.length;r<s;r++){const o=e[r];o.mesh!==void 0&&(this._addNodeRef(this.meshCache,o.mesh),o.skin!==void 0&&(i[o.mesh].isSkinnedMesh=!0)),o.camera!==void 0&&this._addNodeRef(this.cameraCache,o.camera)}}_addNodeRef(e,t){t!==void 0&&(e.refs[t]===void 0&&(e.refs[t]=e.uses[t]=0),e.refs[t]++)}_getNodeRef(e,t,i){if(e.refs[t]<=1)return i;const r=i.clone(),s=(o,a)=>{const l=this.associations.get(o);l!=null&&this.associations.set(a,l);for(const[c,h]of o.children.entries())s(h,a.children[c])};return s(i,r),r.name+="_instance_"+e.uses[t]++,r}_invokeOne(e){const t=Object.values(this.plugins);t.push(this);for(let i=0;i<t.length;i++){const r=e(t[i]);if(r)return r}return null}_invokeAll(e){const t=Object.values(this.plugins);t.unshift(this);const i=[];for(let r=0;r<t.length;r++){const s=e(t[r]);s&&i.push(s)}return i}getDependency(e,t){const i=e+":"+t;let r=this.cache.get(i);if(!r){switch(e){case"scene":r=this.loadScene(t);break;case"node":r=this._invokeOne(function(s){return s.loadNode&&s.loadNode(t)});break;case"mesh":r=this._invokeOne(function(s){return s.loadMesh&&s.loadMesh(t)});break;case"accessor":r=this.loadAccessor(t);break;case"bufferView":r=this._invokeOne(function(s){return s.loadBufferView&&s.loadBufferView(t)});break;case"buffer":r=this.loadBuffer(t);break;case"material":r=this._invokeOne(function(s){return s.loadMaterial&&s.loadMaterial(t)});break;case"texture":r=this._invokeOne(function(s){return s.loadTexture&&s.loadTexture(t)});break;case"skin":r=this.loadSkin(t);break;case"animation":r=this._invokeOne(function(s){return s.loadAnimation&&s.loadAnimation(t)});break;case"camera":r=this.loadCamera(t);break;default:if(r=this._invokeOne(function(s){return s!=this&&s.getDependency&&s.getDependency(e,t)}),!r)throw new Error("Unknown type: "+e);break}this.cache.add(i,r)}return r}getDependencies(e){let t=this.cache.get(e);if(!t){const i=this,r=this.json[e+(e==="mesh"?"es":"s")]||[];t=Promise.all(r.map(function(s,o){return i.getDependency(e,o)})),this.cache.add(e,t)}return t}loadBuffer(e){const t=this.json.buffers[e],i=this.fileLoader;if(t.type&&t.type!=="arraybuffer")throw new Error("THREE.GLTFLoader: "+t.type+" buffer type is not supported.");if(t.uri===void 0&&e===0)return Promise.resolve(this.extensions[Zt.KHR_BINARY_GLTF].body);const r=this.options;return new Promise(function(s,o){i.load(Kr.resolveURL(t.uri,r.path),s,void 0,function(){o(new Error('THREE.GLTFLoader: Failed to load buffer "'+t.uri+'".'))})})}loadBufferView(e){const t=this.json.bufferViews[e];return this.getDependency("buffer",t.buffer).then(function(i){const r=t.byteLength||0,s=t.byteOffset||0;return i.slice(s,s+r)})}loadAccessor(e){const t=this,i=this.json,r=this.json.accessors[e];if(r.bufferView===void 0&&r.sparse===void 0){const o=SE[r.type],a=bu[r.componentType],l=r.normalized===!0,c=new a(r.count*o);return Promise.resolve(new Xt(c,o,l))}const s=[];return r.bufferView!==void 0?s.push(this.getDependency("bufferView",r.bufferView)):s.push(null),r.sparse!==void 0&&(s.push(this.getDependency("bufferView",r.sparse.indices.bufferView)),s.push(this.getDependency("bufferView",r.sparse.values.bufferView))),Promise.all(s).then(function(o){const a=o[0],l=SE[r.type],c=bu[r.componentType],h=c.BYTES_PER_ELEMENT,f=h*l,d=r.byteOffset||0,m=r.bufferView!==void 0?i.bufferViews[r.bufferView].byteStride:void 0,g=r.normalized===!0;let E,C;if(m&&m!==f){const S=Math.floor(d/m),v="InterleavedBuffer:"+r.bufferView+":"+r.componentType+":"+S+":"+r.count;let y=t.cache.get(v);y||(E=new c(a,S*m,r.count*m/h),y=new Wf(E,m/h),t.cache.add(v,y)),C=new Na(y,l,d%m/h,g)}else a===null?E=new c(r.count*l):E=new c(a,d,r.count*l),C=new Xt(E,l,g);if(r.sparse!==void 0){const S=SE.SCALAR,v=bu[r.sparse.indices.componentType],y=r.sparse.indices.byteOffset||0,w=r.sparse.values.byteOffset||0,x=new v(o[1],y,r.sparse.count*S),k=new c(o[2],w,r.sparse.count*l);a!==null&&(C=new Xt(C.array.slice(),C.itemSize,C.normalized));for(let I=0,R=x.length;I<R;I++){const T=x[I];if(C.setX(T,k[I*l]),l>=2&&C.setY(T,k[I*l+1]),l>=3&&C.setZ(T,k[I*l+2]),l>=4&&C.setW(T,k[I*l+3]),l>=5)throw new Error("THREE.GLTFLoader: Unsupported itemSize in sparse BufferAttribute.")}}return C})}loadTexture(e){const t=this.json,i=this.options,s=t.textures[e].source,o=t.images[s];let a=this.textureLoader;if(o.uri){const l=i.manager.getHandler(o.uri);l!==null&&(a=l)}return this.loadTextureImage(e,s,a)}loadTextureImage(e,t,i){const r=this,s=this.json,o=s.textures[e],a=s.images[t],l=(a.uri||a.bufferView)+":"+o.sampler;if(this.textureCache[l])return this.textureCache[l];const c=this.loadImageSource(t,i).then(function(h){h.flipY=!1,h.name=o.name||a.name||"",h.name===""&&typeof a.uri=="string"&&a.uri.startsWith("data:image/")===!1&&(h.name=a.uri);const d=(s.samplers||{})[o.sampler]||{};return h.magFilter=wI[d.magFilter]||pn,h.minFilter=wI[d.minFilter]||ro,h.wrapS=MI[d.wrapS]||io,h.wrapT=MI[d.wrapT]||io,r.associations.set(h,{textures:e}),h}).catch(function(){return null});return this.textureCache[l]=c,c}loadImageSource(e,t){const i=this,r=this.json,s=this.options;if(this.sourceCache[e]!==void 0)return this.sourceCache[e].then(f=>f.clone());const o=r.images[e],a=self.URL||self.webkitURL;let l=o.uri||"",c=!1;if(o.bufferView!==void 0)l=i.getDependency("bufferView",o.bufferView).then(function(f){c=!0;const d=new Blob([f],{type:o.mimeType});return l=a.createObjectURL(d),l});else if(o.uri===void 0)throw new Error("THREE.GLTFLoader: Image "+e+" is missing URI and bufferView");const h=Promise.resolve(l).then(function(f){return new Promise(function(d,m){let g=d;t.isImageBitmapLoader===!0&&(g=function(E){const C=new fn(E);C.needsUpdate=!0,d(C)}),t.load(Kr.resolveURL(f,s.path),g,void 0,m)})}).then(function(f){return c===!0&&a.revokeObjectURL(l),f.userData.mimeType=o.mimeType||N9(o.uri),f}).catch(function(f){throw f});return this.sourceCache[e]=h,h}assignTexture(e,t,i,r){const s=this;return this.getDependency("texture",i.index).then(function(o){if(!o)return null;if(i.texCoord!==void 0&&i.texCoord>0&&(o=o.clone(),o.channel=i.texCoord),s.extensions[Zt.KHR_TEXTURE_TRANSFORM]){const a=i.extensions!==void 0?i.extensions[Zt.KHR_TEXTURE_TRANSFORM]:void 0;if(a){const l=s.associations.get(o);o=s.extensions[Zt.KHR_TEXTURE_TRANSFORM].extendTexture(o,a),s.associations.set(o,l)}}return r!==void 0&&("colorSpace"in o?o.colorSpace=r===3001?"srgb":"srgb-linear":o.encoding=r),e[t]=o,o})}assignFinalMaterial(e){const t=e.geometry;let i=e.material;const r=t.attributes.tangent===void 0,s=t.attributes.color!==void 0,o=t.attributes.normal===void 0;if(e.isPoints){const a="PointsMaterial:"+i.uuid;let l=this.cache.get(a);l||(l=new cA,ti.prototype.copy.call(l,i),l.color.copy(i.color),l.map=i.map,l.sizeAttenuation=!1,this.cache.add(a,l)),i=l}else if(e.isLine){const a="LineBasicMaterial:"+i.uuid;let l=this.cache.get(a);l||(l=new wi,ti.prototype.copy.call(l,i),l.color.copy(i.color),l.map=i.map,this.cache.add(a,l)),i=l}if(r||s||o){let a="ClonedMaterial:"+i.uuid+":";r&&(a+="derivative-tangents:"),s&&(a+="vertex-colors:"),o&&(a+="flat-shading:");let l=this.cache.get(a);l||(l=i.clone(),s&&(l.vertexColors=!0),o&&(l.flatShading=!0),r&&(l.normalScale&&(l.normalScale.y*=-1),l.clearcoatNormalScale&&(l.clearcoatNormalScale.y*=-1)),this.cache.add(a,l),this.associations.set(l,this.associations.get(i))),i=l}e.material=i}getMaterialType(){return qf}loadMaterial(e){const t=this,i=this.json,r=this.extensions,s=i.materials[e];let o;const a={},l=s.extensions||{},c=[];if(l[Zt.KHR_MATERIALS_UNLIT]){const f=r[Zt.KHR_MATERIALS_UNLIT];o=f.getMaterialType(),c.push(f.extendParams(a,s,t))}else{const f=s.pbrMetallicRoughness||{};if(a.color=new ze(1,1,1),a.opacity=1,Array.isArray(f.baseColorFactor)){const d=f.baseColorFactor;a.color.fromArray(d),a.opacity=d[3]}f.baseColorTexture!==void 0&&c.push(t.assignTexture(a,"map",f.baseColorTexture,3001)),a.metalness=f.metallicFactor!==void 0?f.metallicFactor:1,a.roughness=f.roughnessFactor!==void 0?f.roughnessFactor:1,f.metallicRoughnessTexture!==void 0&&(c.push(t.assignTexture(a,"metalnessMap",f.metallicRoughnessTexture)),c.push(t.assignTexture(a,"roughnessMap",f.metallicRoughnessTexture))),o=this._invokeOne(function(d){return d.getMaterialType&&d.getMaterialType(e)}),c.push(Promise.all(this._invokeAll(function(d){return d.extendMaterialParams&&d.extendMaterialParams(e,a)})))}s.doubleSided===!0&&(a.side=es);const h=s.alphaMode||gE.OPAQUE;if(h===gE.BLEND?(a.transparent=!0,a.depthWrite=!1):(a.transparent=!1,h===gE.MASK&&(a.alphaTest=s.alphaCutoff!==void 0?s.alphaCutoff:.5)),s.normalTexture!==void 0&&o!==Ir&&(c.push(t.assignTexture(a,"normalMap",s.normalTexture)),a.normalScale=new we(1,1),s.normalTexture.scale!==void 0)){const f=s.normalTexture.scale;a.normalScale.set(f,f)}return s.occlusionTexture!==void 0&&o!==Ir&&(c.push(t.assignTexture(a,"aoMap",s.occlusionTexture)),s.occlusionTexture.strength!==void 0&&(a.aoMapIntensity=s.occlusionTexture.strength)),s.emissiveFactor!==void 0&&o!==Ir&&(a.emissive=new ze().fromArray(s.emissiveFactor)),s.emissiveTexture!==void 0&&o!==Ir&&c.push(t.assignTexture(a,"emissiveMap",s.emissiveTexture,3001)),Promise.all(c).then(function(){const f=new o(a);return s.name&&(f.name=s.name),Aa(f,s),t.associations.set(f,{materials:e}),s.extensions&&yl(r,f,s),f})}createUniqueName(e){const t=zt.sanitizeNodeName(e||"");return t in this.nodeNamesUsed?t+"_"+ ++this.nodeNamesUsed[t]:(this.nodeNamesUsed[t]=0,t)}loadGeometries(e){const t=this,i=this.extensions,r=this.primitiveCache;function s(a){return i[Zt.KHR_DRACO_MESH_COMPRESSION].decodePrimitive(a,t).then(function(l){return kI(l,a,t)})}const o=[];for(let a=0,l=e.length;a<l;a++){const c=e[a],h=P9(c),f=r[h];if(f)o.push(f.promise);else{let d;c.extensions&&c.extensions[Zt.KHR_DRACO_MESH_COMPRESSION]?d=s(c):d=kI(new Tt,c,t),r[h]={primitive:c,promise:d},o.push(d)}}return Promise.all(o)}loadMesh(e){const t=this,i=this.json,r=this.extensions,s=i.meshes[e],o=s.primitives,a=[];for(let l=0,c=o.length;l<c;l++){const h=o[l].material===void 0?b9(this.cache):this.getDependency("material",o[l].material);a.push(h)}return a.push(t.loadGeometries(o)),Promise.all(a).then(function(l){const c=l.slice(0,l.length-1),h=l[l.length-1],f=[];for(let m=0,g=h.length;m<g;m++){const E=h[m],C=o[m];let S;const v=c[m];if(C.mode===jr.TRIANGLES||C.mode===jr.TRIANGLE_STRIP||C.mode===jr.TRIANGLE_FAN||C.mode===void 0)S=s.isSkinnedMesh===!0?new lA(E,v):new Gn(E,v),S.isSkinnedMesh===!0&&S.normalizeSkinWeights(),C.mode===jr.TRIANGLE_STRIP?S.geometry=EI(S.geometry,_U):C.mode===jr.TRIANGLE_FAN&&(S.geometry=EI(S.geometry,Sg));else if(C.mode===jr.LINES)S=new Ks(E,v);else if(C.mode===jr.LINE_STRIP)S=new oo(E,v);else if(C.mode===jr.LINE_LOOP)S=new fw(E,v);else if(C.mode===jr.POINTS)S=new dw(E,v);else throw new Error("THREE.GLTFLoader: Primitive mode unsupported: "+C.mode);Object.keys(S.geometry.morphAttributes).length>0&&F9(S,s),S.name=t.createUniqueName(s.name||"mesh_"+e),Aa(S,s),C.extensions&&yl(r,S,C),t.assignFinalMaterial(S),f.push(S)}for(let m=0,g=f.length;m<g;m++)t.associations.set(f[m],{meshes:e,primitives:m});if(f.length===1)return s.extensions&&yl(r,f[0],s),f[0];const d=new Ms;s.extensions&&yl(r,d,s),t.associations.set(d,{meshes:e});for(let m=0,g=f.length;m<g;m++)d.add(f[m]);return d})}loadCamera(e){let t;const i=this.json.cameras[e],r=i[i.type];if(r)return i.type==="perspective"?t=new xn(Oi.radToDeg(r.yfov),r.aspectRatio||1,r.znear||1,r.zfar||2e6):i.type==="orthographic"&&(t=new ws(-r.xmag,r.xmag,r.ymag,-r.ymag,r.znear,r.zfar)),i.name&&(t.name=this.createUniqueName(i.name)),Aa(t,i),Promise.resolve(t)}loadSkin(e){const t=this.json.skins[e],i=[];for(let r=0,s=t.joints.length;r<s;r++)i.push(this._loadNodeShallow(t.joints[r]));return t.inverseBindMatrices!==void 0?i.push(this.getDependency("accessor",t.inverseBindMatrices)):i.push(null),Promise.all(i).then(function(r){const s=r.pop(),o=r,a=[],l=[];for(let c=0,h=o.length;c<h;c++){const f=o[c];if(f){a.push(f);const d=new tt;s!==null&&d.fromArray(s.array,c*16),l.push(d)}}return new ch(a,l)})}loadAnimation(e){const i=this.json.animations[e],r=i.name?i.name:"animation_"+e,s=[],o=[],a=[],l=[],c=[];for(let h=0,f=i.channels.length;h<f;h++){const d=i.channels[h],m=i.samplers[d.sampler],g=d.target,E=g.node,C=i.parameters!==void 0?i.parameters[m.input]:m.input,S=i.parameters!==void 0?i.parameters[m.output]:m.output;g.node!==void 0&&(s.push(this.getDependency("node",E)),o.push(this.getDependency("accessor",C)),a.push(this.getDependency("accessor",S)),l.push(m),c.push(g))}return Promise.all([Promise.all(s),Promise.all(o),Promise.all(a),Promise.all(l),Promise.all(c)]).then(function(h){const f=h[0],d=h[1],m=h[2],g=h[3],E=h[4],C=[];for(let S=0,v=f.length;S<v;S++){const y=f[S],w=d[S],x=m[S],k=g[S],I=E[S];if(y===void 0)continue;y.updateMatrix();let R;switch(da[I.path]){case da.weights:R=ic;break;case da.rotation:R=Ho;break;case da.position:case da.scale:default:R=rc;break}const T=y.name?y.name:y.uuid,L=k.interpolation!==void 0?D9[k.interpolation]:tc,O=[];da[I.path]===da.weights?y.traverse(function(ie){ie.morphTargetInfluences&&O.push(ie.name?ie.name:ie.uuid)}):O.push(T);let V=x.array;if(x.normalized){const ie=Hv(V.constructor),W=new Float32Array(V.length);for(let _=0,ne=V.length;_<ne;_++)W[_]=V[_]*ie;V=W}for(let ie=0,W=O.length;ie<W;ie++){const _=new R(O[ie]+"."+da[I.path],w.array,V,L);k.interpolation==="CUBICSPLINE"&&(_.createInterpolant=function(oe){const H=this instanceof Ho?R9:kO;return new H(this.times,this.values,this.getValueSize()/3,oe)},_.createInterpolant.isInterpolantFactoryMethodGLTFCubicSpline=!0),C.push(_)}}return new sc(r,void 0,C)})}createNodeMesh(e){const t=this.json,i=this,r=t.nodes[e];return r.mesh===void 0?null:i.getDependency("mesh",r.mesh).then(function(s){const o=i._getNodeRef(i.meshCache,r.mesh,s);return r.weights!==void 0&&o.traverse(function(a){if(a.isMesh)for(let l=0,c=r.weights.length;l<c;l++)a.morphTargetInfluences[l]=r.weights[l]}),o})}loadNode(e){const t=this.json,i=this,r=t.nodes[e],s=i._loadNodeShallow(e),o=[],a=r.children||[];for(let c=0,h=a.length;c<h;c++)o.push(i.getDependency("node",a[c]));const l=r.skin===void 0?Promise.resolve(null):i.getDependency("skin",r.skin);return Promise.all([s,Promise.all(o),l]).then(function(c){const h=c[0],f=c[1],d=c[2];d!==null&&h.traverse(function(m){m.isSkinnedMesh&&m.bind(d,Q9)});for(let m=0,g=f.length;m<g;m++)h.add(f[m]);return h})}_loadNodeShallow(e){const t=this.json,i=this.extensions,r=this;if(this.nodeCache[e]!==void 0)return this.nodeCache[e];const s=t.nodes[e],o=s.name?r.createUniqueName(s.name):"",a=[],l=r._invokeOne(function(c){return c.createNodeMesh&&c.createNodeMesh(e)});return l&&a.push(l),s.camera!==void 0&&a.push(r.getDependency("camera",s.camera).then(function(c){return r._getNodeRef(r.cameraCache,s.camera,c)})),r._invokeAll(function(c){return c.createNodeAttachment&&c.createNodeAttachment(e)}).forEach(function(c){a.push(c)}),this.nodeCache[e]=Promise.all(a).then(function(c){let h;if(s.isBone===!0?h=new ju:c.length>1?h=new Ms:c.length===1?h=c[0]:h=new Wt,h!==c[0])for(let f=0,d=c.length;f<d;f++)h.add(c[f]);if(s.name&&(h.userData.name=s.name,h.name=o),Aa(h,s),s.extensions&&yl(i,h,s),s.matrix!==void 0){const f=new tt;f.fromArray(s.matrix),h.applyMatrix4(f)}else s.translation!==void 0&&h.position.fromArray(s.translation),s.rotation!==void 0&&h.quaternion.fromArray(s.rotation),s.scale!==void 0&&h.scale.fromArray(s.scale);return r.associations.has(h)||r.associations.set(h,{}),r.associations.get(h).nodes=e,h}),this.nodeCache[e]}loadScene(e){const t=this.extensions,i=this.json.scenes[e],r=this,s=new Ms;i.name&&(s.name=r.createUniqueName(i.name)),Aa(s,i),i.extensions&&yl(t,s,i);const o=i.nodes||[],a=[];for(let l=0,c=o.length;l<c;l++)a.push(r.getDependency("node",o[l]));return Promise.all(a).then(function(l){for(let h=0,f=l.length;h<f;h++)s.add(l[h]);const c=h=>{const f=new Map;for(const[d,m]of r.associations)(d instanceof ti||d instanceof fn)&&f.set(d,m);return h.traverse(d=>{const m=r.associations.get(d);m!=null&&f.set(d,m)}),f};return r.associations=c(s),s})}}function H9(n,e,t){const i=e.attributes,r=new Pi;if(i.POSITION!==void 0){const a=t.json.accessors[i.POSITION],l=a.min,c=a.max;if(l!==void 0&&c!==void 0){if(r.set(new N(l[0],l[1],l[2]),new N(c[0],c[1],c[2])),a.normalized){const h=Hv(bu[a.componentType]);r.min.multiplyScalar(h),r.max.multiplyScalar(h)}}else return}else return;const s=e.targets;if(s!==void 0){const a=new N,l=new N;for(let c=0,h=s.length;c<h;c++){const f=s[c];if(f.POSITION!==void 0){const d=t.json.accessors[f.POSITION],m=d.min,g=d.max;if(m!==void 0&&g!==void 0){if(l.setX(Math.max(Math.abs(m[0]),Math.abs(g[0]))),l.setY(Math.max(Math.abs(m[1]),Math.abs(g[1]))),l.setZ(Math.max(Math.abs(m[2]),Math.abs(g[2]))),d.normalized){const E=Hv(bu[d.componentType]);l.multiplyScalar(E)}a.max(l)}}}r.expandByVector(a)}n.boundingBox=r;const o=new vi;r.getCenter(o.center),o.radius=r.min.distanceTo(r.max)/2,n.boundingSphere=o}function kI(n,e,t){const i=e.attributes,r=[];function s(o,a){return t.getDependency("accessor",o).then(function(l){n.setAttribute(a,l)})}for(const o in i){const a=Wv[o]||o.toLowerCase();a in n.attributes||r.push(s(i[o],a))}if(e.indices!==void 0&&!n.index){const o=t.getDependency("accessor",e.indices).then(function(a){n.setIndex(a)});r.push(o)}return Aa(n,e),H9(n,e,t),Promise.all(r).then(function(){return e.targets!==void 0?O9(n,e.targets,t):n})}function xO(n,e,t){const i=t.length-n-1;if(e>=t[i])return i-1;if(e<=t[n])return n;let r=n,s=i,o=Math.floor((r+s)/2);for(;e<t[o]||e>=t[o+1];)e<t[o]?s=o:r=o,o=Math.floor((r+s)/2);return o}function z9(n,e,t,i){const r=[],s=[],o=[];r[0]=1;for(let a=1;a<=t;++a){s[a]=e-i[n+1-a],o[a]=i[n+a]-e;let l=0;for(let c=0;c<a;++c){const h=o[c+1],f=s[a-c],d=r[c]/(h+f);r[c]=l+h*d,l=f*d}r[a]=l}return r}function G9(n,e,t,i){const r=xO(n,i,e),s=z9(r,i,n,e),o=new $t(0,0,0,0);for(let a=0;a<=n;++a){const l=t[r-n+a],c=s[a],h=l.w*c;o.x+=l.x*h,o.y+=l.y*h,o.z+=l.z*h,o.w+=l.w*c}return o}function V9(n,e,t,i,r){const s=[];for(let f=0;f<=t;++f)s[f]=0;const o=[];for(let f=0;f<=i;++f)o[f]=s.slice(0);const a=[];for(let f=0;f<=t;++f)a[f]=s.slice(0);a[0][0]=1;const l=s.slice(0),c=s.slice(0);for(let f=1;f<=t;++f){l[f]=e-r[n+1-f],c[f]=r[n+f]-e;let d=0;for(let m=0;m<f;++m){const g=c[m+1],E=l[f-m];a[f][m]=g+E;const C=a[m][f-1]/a[f][m];a[m][f]=d+g*C,d=E*C}a[f][f]=d}for(let f=0;f<=t;++f)o[0][f]=a[f][t];for(let f=0;f<=t;++f){let d=0,m=1;const g=[];for(let E=0;E<=t;++E)g[E]=s.slice(0);g[0][0]=1;for(let E=1;E<=i;++E){let C=0;const S=f-E,v=t-E;f>=E&&(g[m][0]=g[d][0]/a[v+1][S],C=g[m][0]*a[S][v]);const y=S>=-1?1:-S,w=f-1<=v?E-1:t-f;for(let k=y;k<=w;++k)g[m][k]=(g[d][k]-g[d][k-1])/a[v+1][S+k],C+=g[m][k]*a[S+k][v];f<=v&&(g[m][E]=-g[d][E-1]/a[v+1][f],C+=g[m][E]*a[f][v]),o[E][f]=C;const x=d;d=m,m=x}}let h=t;for(let f=1;f<=i;++f){for(let d=0;d<=t;++d)o[f][d]*=h;h*=t-f}return o}function q9(n,e,t,i,r){const s=r<n?r:n,o=[],a=xO(n,i,e),l=V9(a,i,n,s,e),c=[];for(let h=0;h<t.length;++h){const f=t[h].clone(),d=f.w;f.x*=d,f.y*=d,f.z*=d,c[h]=f}for(let h=0;h<=s;++h){const f=c[a-n].clone().multiplyScalar(l[h][0]);for(let d=1;d<=n;++d)f.add(c[a-n+d].clone().multiplyScalar(l[h][d]));o[h]=f}for(let h=s+1;h<=r+1;++h)o[h]=new $t(0,0,0);return o}function Y9(n,e){let t=1;for(let r=2;r<=n;++r)t*=r;let i=1;for(let r=2;r<=e;++r)i*=r;for(let r=2;r<=n-e;++r)i*=r;return t/i}function Z9(n){const e=n.length,t=[],i=[];for(let s=0;s<e;++s){const o=n[s];t[s]=new N(o.x,o.y,o.z),i[s]=o.w}const r=[];for(let s=0;s<e;++s){const o=t[s].clone();for(let a=1;a<=s;++a)o.sub(r[s-a].clone().multiplyScalar(Y9(s,a)*i[a]));r[s]=o.divideScalar(i[0])}return r}function j9(n,e,t,i,r){const s=q9(n,e,t,i,r);return Z9(s)}class xI extends ls{constructor(e,t,i,r,s){super(),this.degree=e,this.knots=t,this.controlPoints=[],this.startKnot=r||0,this.endKnot=s||this.knots.length-1;for(let o=0;o<i.length;++o){const a=i[o];this.controlPoints[o]=new $t(a.x,a.y,a.z,a.w)}}getPoint(e,t){const i=t||new N,r=this.knots[this.startKnot]+e*(this.knots[this.endKnot]-this.knots[this.startKnot]),s=G9(this.degree,this.knots,this.controlPoints,r);return s.w!=1&&s.divideScalar(s.w),i.set(s.x,s.y,s.z)}getTangent(e,t){const i=t||new N,r=this.knots[0]+e*(this.knots[this.knots.length-1]-this.knots[0]),s=j9(this.degree,this.knots,this.controlPoints,r,1);return i.copy(s[1]).normalize(),i}}let Gt,Zn,lr;class cM extends Mi{constructor(e){super(e)}load(e,t,i,r){const s=this,o=s.path===""?Kr.extractUrlBase(e):s.path,a=new yr(this.manager);a.setPath(s.path),a.setResponseType("arraybuffer"),a.setRequestHeader(s.requestHeader),a.setWithCredentials(s.withCredentials),a.load(e,function(l){try{t(s.parse(l,o))}catch(c){r&&r(c),s.manager.itemError(e)}},i,r)}parse(e,t){if(n_(e))Gt=new t_().parse(e);else{const r=LO(e);if(!i_(r))throw new Error("THREE.FBXLoader: Unknown format.");if(JI(r)<7e3)throw new Error("THREE.FBXLoader: FBX version not supported, FileVersion: "+JI(r));Gt=new e_().parse(r)}const i=new ph(this.manager).setPath(this.resourcePath||t).setCrossOrigin(this.crossOrigin);return new X9(i,this.manager).parse(Gt)}}class X9{constructor(e,t){this.textureLoader=e,this.manager=t}parse(){Zn=this.parseConnections();const e=this.parseImages(),t=this.parseTextures(e),i=this.parseMaterials(t),r=this.parseDeformers(),s=new _9().parse(r);return this.parseScene(r,s,i),lr}parseConnections(){const e=new Map;return"Connections"in Gt&&Gt.Connections.connections.forEach(function(i){const r=i[0],s=i[1],o=i[2];e.has(r)||e.set(r,{parents:[],children:[]});const a={ID:s,relationship:o};e.get(r).parents.push(a),e.has(s)||e.set(s,{parents:[],children:[]});const l={ID:r,relationship:o};e.get(s).children.push(l)}),e}parseImages(){const e={},t={};if("Video"in Gt.Objects){const i=Gt.Objects.Video;for(const r in i){const s=i[r],o=parseInt(r);if(e[o]=s.RelativeFilename||s.Filename,"Content"in s){const a=s.Content instanceof ArrayBuffer&&s.Content.byteLength>0,l=typeof s.Content=="string"&&s.Content!=="";if(a||l){const c=this.parseImage(i[r]);t[s.RelativeFilename||s.Filename]=c}}}}for(const i in e){const r=e[i];t[r]!==void 0?e[i]=t[r]:e[i]=e[i].split("\\").pop()}return e}parseImage(e){const t=e.Content,i=e.RelativeFilename||e.Filename,r=i.slice(i.lastIndexOf(".")+1).toLowerCase();let s;switch(r){case"bmp":s="image/bmp";break;case"jpg":case"jpeg":s="image/jpeg";break;case"png":s="image/png";break;case"tif":s="image/tiff";break;case"tga":this.manager.getHandler(".tga"),s="image/tga";break;default:return}if(typeof t=="string")return"data:"+s+";base64,"+t;{const o=new Uint8Array(t);return window.URL.createObjectURL(new Blob([o],{type:s}))}}parseTextures(e){const t=new Map;if("Texture"in Gt.Objects){const i=Gt.Objects.Texture;for(const r in i){const s=this.parseTexture(i[r],e);t.set(parseInt(r),s)}}return t}parseTexture(e,t){const i=this.loadTexture(e,t);i.ID=e.id,i.name=e.attrName;const r=e.WrapModeU,s=e.WrapModeV,o=r!==void 0?r.value:0,a=s!==void 0?s.value:0;if(i.wrapS=o===0?io:oi,i.wrapT=a===0?io:oi,"Scaling"in e){const l=e.Scaling.value;i.repeat.x=l[0],i.repeat.y=l[1]}return i}loadTexture(e,t){let i;const r=this.textureLoader.path,s=Zn.get(e.id).children;s!==void 0&&s.length>0&&t[s[0].ID]!==void 0&&(i=t[s[0].ID],(i.indexOf("blob:")===0||i.indexOf("data:")===0)&&this.textureLoader.setPath(void 0));let o;const a=e.FileName.slice(-3).toLowerCase();if(a==="tga"){const l=this.manager.getHandler(".tga");l===null?o=new fn:(l.setPath(this.textureLoader.path),o=l.load(i))}else a==="psd"?o=new fn:o=this.textureLoader.load(i);return this.textureLoader.setPath(r),o}parseMaterials(e){const t=new Map;if("Material"in Gt.Objects){const i=Gt.Objects.Material;for(const r in i){const s=this.parseMaterial(i[r],e);s!==null&&t.set(parseInt(r),s)}}return t}parseMaterial(e,t){const i=e.id,r=e.attrName;let s=e.ShadingModel;if(typeof s=="object"&&(s=s.value),!Zn.has(i))return null;const o=this.parseParameters(e,t,i);let a;switch(s.toLowerCase()){case"phong":a=new Dp;break;case"lambert":a=new Cw;break;default:a=new Dp;break}return a.setValues(o),a.name=r,a}parseParameters(e,t,i){const r={};e.BumpFactor&&(r.bumpScale=e.BumpFactor.value),e.Diffuse?r.color=new ze().fromArray(e.Diffuse.value):e.DiffuseColor&&(e.DiffuseColor.type==="Color"||e.DiffuseColor.type==="ColorRGB")&&(r.color=new ze().fromArray(e.DiffuseColor.value)),e.DisplacementFactor&&(r.displacementScale=e.DisplacementFactor.value),e.Emissive?r.emissive=new ze().fromArray(e.Emissive.value):e.EmissiveColor&&(e.EmissiveColor.type==="Color"||e.EmissiveColor.type==="ColorRGB")&&(r.emissive=new ze().fromArray(e.EmissiveColor.value)),e.EmissiveFactor&&(r.emissiveIntensity=parseFloat(e.EmissiveFactor.value)),e.Opacity&&(r.opacity=parseFloat(e.Opacity.value)),r.opacity<1&&(r.transparent=!0),e.ReflectionFactor&&(r.reflectivity=e.ReflectionFactor.value),e.Shininess&&(r.shininess=e.Shininess.value),e.Specular?r.specular=new ze().fromArray(e.Specular.value):e.SpecularColor&&e.SpecularColor.type==="Color"&&(r.specular=new ze().fromArray(e.SpecularColor.value));const s=this;return Zn.get(i).children.forEach(function(o){switch(o.relationship){case"Bump":r.bumpMap=s.getTexture(t,o.ID);break;case"Maya|TEX_ao_map":r.aoMap=s.getTexture(t,o.ID);break;case"DiffuseColor":case"Maya|TEX_color_map":r.map=s.getTexture(t,o.ID),r.map!==void 0&&("colorSpace"in r.map?r.map.colorSpace="srgb":r.map.encoding=3001);break;case"DisplacementColor":r.displacementMap=s.getTexture(t,o.ID);break;case"EmissiveColor":r.emissiveMap=s.getTexture(t,o.ID),r.emissiveMap!==void 0&&("colorSpace"in r.emissiveMap?r.emissiveMap.colorSpace="srgb":r.emissiveMap.encoding=3001);break;case"NormalMap":case"Maya|TEX_normal_map":r.normalMap=s.getTexture(t,o.ID);break;case"ReflectionColor":r.envMap=s.getTexture(t,o.ID),r.envMap!==void 0&&(r.envMap.mapping=$l,"colorSpace"in r.envMap?r.envMap.colorSpace="srgb":r.envMap.encoding=3001);break;case"SpecularColor":r.specularMap=s.getTexture(t,o.ID),r.specularMap!==void 0&&("colorSpace"in r.specularMap?r.specularMap.colorSpace="srgb":r.specularMap.encoding=3001);break;case"TransparentColor":case"TransparencyFactor":r.alphaMap=s.getTexture(t,o.ID),r.transparent=!0;break;case"AmbientColor":case"ShininessExponent":case"SpecularFactor":case"VectorDisplacementColor":default:break}}),r}getTexture(e,t){return"LayeredTexture"in Gt.Objects&&t in Gt.Objects.LayeredTexture&&(t=Zn.get(t).children[0].ID),e.get(t)}parseDeformers(){const e={},t={};if("Deformer"in Gt.Objects){const i=Gt.Objects.Deformer;for(const r in i){const s=i[r],o=Zn.get(parseInt(r));if(s.attrType==="Skin"){const a=this.parseSkeleton(o,i);a.ID=r,o.parents.length>1,a.geometryID=o.parents[0].ID,e[r]=a}else if(s.attrType==="BlendShape"){const a={id:r};a.rawTargets=this.parseMorphTargets(o,i),a.id=r,o.parents.length>1,t[r]=a}}}return{skeletons:e,morphTargets:t}}parseSkeleton(e,t){const i=[];return e.children.forEach(function(r){const s=t[r.ID];if(s.attrType!=="Cluster")return;const o={ID:r.ID,indices:[],weights:[],transformLink:new tt().fromArray(s.TransformLink.a)};"Indexes"in s&&(o.indices=s.Indexes.a,o.weights=s.Weights.a),i.push(o)}),{rawBones:i,bones:[]}}parseMorphTargets(e,t){const i=[];for(let r=0;r<e.children.length;r++){const s=e.children[r],o=t[s.ID],a={name:o.attrName,initialWeight:o.DeformPercent,id:o.id,fullWeights:o.FullWeights.a};if(o.attrType!=="BlendShapeChannel")return;a.geoID=Zn.get(parseInt(s.ID)).children.filter(function(l){return l.relationship===void 0})[0].ID,i.push(a)}return i}parseScene(e,t,i){lr=new Ms;const r=this.parseModels(e.skeletons,t,i),s=Gt.Objects.Model,o=this;r.forEach(function(l){const c=s[l.ID];o.setLookAtProperties(l,c),Zn.get(l.ID).parents.forEach(function(f){const d=r.get(f.ID);d!==void 0&&d.add(l)}),l.parent===null&&lr.add(l)}),this.bindSkeleton(e.skeletons,t,r),this.createAmbientLight(),lr.traverse(function(l){if(l.userData.transformData){l.parent&&(l.userData.transformData.parentMatrix=l.parent.matrix,l.userData.transformData.parentMatrixWorld=l.parent.matrixWorld);const c=JO(l.userData.transformData);l.applyMatrix4(c),l.updateWorldMatrix()}});const a=new $9().parse();lr.children.length===1&&lr.children[0].isGroup&&(lr.children[0].animations=a,lr=lr.children[0]),lr.animations=a}parseModels(e,t,i){const r=new Map,s=Gt.Objects.Model;for(const o in s){const a=parseInt(o),l=s[o],c=Zn.get(a);let h=this.buildSkeleton(c,e,a,l.attrName);if(!h){switch(l.attrType){case"Camera":h=this.createCamera(c);break;case"Light":h=this.createLight(c);break;case"Mesh":h=this.createMesh(c,t,i);break;case"NurbsCurve":h=this.createCurve(c,t);break;case"LimbNode":case"Root":h=new ju;break;case"Null":default:h=new Ms;break}h.name=l.attrName?zt.sanitizeNodeName(l.attrName):"",h.ID=a}this.getTransformData(h,l),r.set(a,h)}return r}buildSkeleton(e,t,i,r){let s=null;return e.parents.forEach(function(o){for(const a in t){const l=t[a];l.rawBones.forEach(function(c,h){if(c.ID===o.ID){const f=s;s=new ju,s.matrixWorld.copy(c.transformLink),s.name=r?zt.sanitizeNodeName(r):"",s.ID=i,l.bones[h]=s,f!==null&&s.add(f)}})}}),s}createCamera(e){let t,i;if(e.children.forEach(function(r){const s=Gt.Objects.NodeAttribute[r.ID];s!==void 0&&(i=s)}),i===void 0)t=new Wt;else{let r=0;i.CameraProjectionType!==void 0&&i.CameraProjectionType.value===1&&(r=1);let s=1;i.NearPlane!==void 0&&(s=i.NearPlane.value/1e3);let o=1e3;i.FarPlane!==void 0&&(o=i.FarPlane.value/1e3);let a=window.innerWidth,l=window.innerHeight;i.AspectWidth!==void 0&&i.AspectHeight!==void 0&&(a=i.AspectWidth.value,l=i.AspectHeight.value);const c=a/l;let h=45;i.FieldOfView!==void 0&&(h=i.FieldOfView.value);const f=i.FocalLength?i.FocalLength.value:null;switch(r){case 0:t=new xn(h,c,s,o),f!==null&&t.setFocalLength(f);break;case 1:t=new ws(-a/2,a/2,l/2,-l/2,s,o);break;default:t=new Wt;break}}return t}createLight(e){let t,i;if(e.children.forEach(function(r){const s=Gt.Objects.NodeAttribute[r.ID];s!==void 0&&(i=s)}),i===void 0)t=new Wt;else{let r;i.LightType===void 0?r=0:r=i.LightType.value;let s=16777215;i.Color!==void 0&&(s=new ze().fromArray(i.Color.value));let o=i.Intensity===void 0?1:i.Intensity.value/100;i.CastLightOnObject!==void 0&&i.CastLightOnObject.value===0&&(o=0);let a=0;i.FarAttenuationEnd!==void 0&&(i.EnableFarAttenuation!==void 0&&i.EnableFarAttenuation.value===0?a=0:a=i.FarAttenuationEnd.value);const l=1;switch(r){case 0:t=new Cf(s,o,a,l);break;case 1:t=new MA(s,o);break;case 2:let c=Math.PI/3;i.InnerAngle!==void 0&&(c=Oi.degToRad(i.InnerAngle.value));let h=0;i.OuterAngle!==void 0&&(h=Oi.degToRad(i.OuterAngle.value),h=Math.max(h,1)),t=new wA(s,o,a,c,h,l);break;default:t=new Cf(s,o);break}i.CastShadows!==void 0&&i.CastShadows.value===1&&(t.castShadow=!0)}return t}createMesh(e,t,i){let r,s=null,o=null;const a=[];return e.children.forEach(function(l){t.has(l.ID)&&(s=t.get(l.ID)),i.has(l.ID)&&a.push(i.get(l.ID))}),a.length>1?o=a:a.length>0?o=a[0]:(o=new Dp({color:13421772}),a.push(o)),"color"in s.attributes&&a.forEach(function(l){l.vertexColors=!0}),s.FBX_Deformer?(r=new lA(s,o),r.normalizeSkinWeights()):r=new Gn(s,o),r}createCurve(e,t){const i=e.children.reduce(function(s,o){return t.has(o.ID)&&(s=t.get(o.ID)),s},null),r=new wi({color:3342591,linewidth:1});return new oo(i,r)}getTransformData(e,t){const i={};"InheritType"in t&&(i.inheritType=parseInt(t.InheritType.value)),"RotationOrder"in t?i.eulerOrder=IO(t.RotationOrder.value):i.eulerOrder="ZYX","Lcl_Translation"in t&&(i.translation=t.Lcl_Translation.value),"PreRotation"in t&&(i.preRotation=t.PreRotation.value),"Lcl_Rotation"in t&&(i.rotation=t.Lcl_Rotation.value),"PostRotation"in t&&(i.postRotation=t.PostRotation.value),"Lcl_Scaling"in t&&(i.scale=t.Lcl_Scaling.value),"ScalingOffset"in t&&(i.scalingOffset=t.ScalingOffset.value),"ScalingPivot"in t&&(i.scalingPivot=t.ScalingPivot.value),"RotationOffset"in t&&(i.rotationOffset=t.RotationOffset.value),"RotationPivot"in t&&(i.rotationPivot=t.RotationPivot.value),e.userData.transformData=i}setLookAtProperties(e,t){"LookAtProperty"in t&&Zn.get(e.ID).children.forEach(function(r){if(r.relationship==="LookAtProperty"){const s=Gt.Objects.Model[r.ID];if("Lcl_Translation"in s){const o=s.Lcl_Translation.value;e.target!==void 0?(e.target.position.fromArray(o),lr.add(e.target)):e.lookAt(new N().fromArray(o))}}})}bindSkeleton(e,t,i){const r=this.parsePoseNodes();for(const s in e){const o=e[s];Zn.get(parseInt(o.ID)).parents.forEach(function(l){if(t.has(l.ID)){const c=l.ID;Zn.get(c).parents.forEach(function(f){i.has(f.ID)&&i.get(f.ID).bind(new ch(o.bones),r[f.ID])})}})}}parsePoseNodes(){const e={};if("Pose"in Gt.Objects){const t=Gt.Objects.Pose;for(const i in t)if(t[i].attrType==="BindPose"&&t[i].NbPoseNodes>0){const r=t[i].PoseNode;Array.isArray(r)?r.forEach(function(s){e[s.Node]=new tt().fromArray(s.Matrix.a)}):e[r.Node]=new tt().fromArray(r.Matrix.a)}}return e}createAmbientLight(){if("GlobalSettings"in Gt&&"AmbientColor"in Gt.GlobalSettings){const e=Gt.GlobalSettings.AmbientColor.value,t=e[0],i=e[1],r=e[2];if(t!==0||i!==0||r!==0){const s=new ze(t,i,r);lr.add(new Tw(s,1))}}}}class _9{parse(e){const t=new Map;if("Geometry"in Gt.Objects){const i=Gt.Objects.Geometry;for(const r in i){const s=Zn.get(parseInt(r)),o=this.parseGeometry(s,i[r],e);t.set(parseInt(r),o)}}return t}parseGeometry(e,t,i){switch(t.attrType){case"Mesh":return this.parseMeshGeometry(e,t,i);case"NurbsCurve":return this.parseNurbsGeometry(t)}}parseMeshGeometry(e,t,i){const r=i.skeletons,s=[],o=e.parents.map(function(f){return Gt.Objects.Model[f.ID]});if(o.length===0)return;const a=e.children.reduce(function(f,d){return r[d.ID]!==void 0&&(f=r[d.ID]),f},null);e.children.forEach(function(f){i.morphTargets[f.ID]!==void 0&&s.push(i.morphTargets[f.ID])});const l=o[0],c={};"RotationOrder"in l&&(c.eulerOrder=IO(l.RotationOrder.value)),"InheritType"in l&&(c.inheritType=parseInt(l.InheritType.value)),"GeometricTranslation"in l&&(c.translation=l.GeometricTranslation.value),"GeometricRotation"in l&&(c.rotation=l.GeometricRotation.value),"GeometricScaling"in l&&(c.scale=l.GeometricScaling.value);const h=JO(c);return this.genGeometry(t,a,s,h)}genGeometry(e,t,i,r){const s=new Tt;e.attrName&&(s.name=e.attrName);const o=this.parseGeoNode(e,t),a=this.genBuffers(o),l=new ot(a.vertex,3);if(l.applyMatrix4(r),s.setAttribute("position",l),a.colors.length>0&&s.setAttribute("color",new ot(a.colors,3)),t&&(s.setAttribute("skinIndex",new rA(a.weightsIndices,4)),s.setAttribute("skinWeight",new ot(a.vertexWeights,4)),s.FBX_Deformer=t),a.normal.length>0){const c=new Ot().getNormalMatrix(r),h=new ot(a.normal,3);h.applyNormalMatrix(c),s.setAttribute("normal",h)}if(a.uvs.forEach(function(c,h){let f="uv"+(h+1).toString();h===0&&(f="uv"),s.setAttribute(f,new ot(a.uvs[h],2))}),o.material&&o.material.mappingType!=="AllSame"){let c=a.materialIndex[0],h=0;if(a.materialIndex.forEach(function(f,d){f!==c&&(s.addGroup(h,d-h,c),c=f,h=d)}),s.groups.length>0){const f=s.groups[s.groups.length-1],d=f.start+f.count;d!==a.materialIndex.length&&s.addGroup(d,a.materialIndex.length-d,c)}s.groups.length===0&&s.addGroup(0,a.materialIndex.length,a.materialIndex[0])}return this.addMorphTargets(s,e,i,r),s}parseGeoNode(e,t){const i={};if(i.vertexPositions=e.Vertices!==void 0?e.Vertices.a:[],i.vertexIndices=e.PolygonVertexIndex!==void 0?e.PolygonVertexIndex.a:[],e.LayerElementColor&&(i.color=this.parseVertexColors(e.LayerElementColor[0])),e.LayerElementMaterial&&(i.material=this.parseMaterialIndices(e.LayerElementMaterial[0])),e.LayerElementNormal&&(i.normal=this.parseNormals(e.LayerElementNormal[0])),e.LayerElementUV){i.uv=[];let r=0;for(;e.LayerElementUV[r];)e.LayerElementUV[r].UV&&i.uv.push(this.parseUVs(e.LayerElementUV[r])),r++}return i.weightTable={},t!==null&&(i.skeleton=t,t.rawBones.forEach(function(r,s){r.indices.forEach(function(o,a){i.weightTable[o]===void 0&&(i.weightTable[o]=[]),i.weightTable[o].push({id:s,weight:r.weights[a]})})})),i}genBuffers(e){const t={vertex:[],normal:[],colors:[],uvs:[],materialIndex:[],vertexWeights:[],weightsIndices:[]};let i=0,r=0,s=!1,o=[],a=[],l=[],c=[],h=[],f=[];const d=this;return e.vertexIndices.forEach(function(m,g){let E,C=!1;m<0&&(m=m^-1,C=!0);let S=[],v=[];if(o.push(m*3,m*3+1,m*3+2),e.color){const y=gS(g,i,m,e.color);l.push(y[0],y[1],y[2])}if(e.skeleton){if(e.weightTable[m]!==void 0&&e.weightTable[m].forEach(function(y){v.push(y.weight),S.push(y.id)}),v.length>4){s||(s=!0);const y=[0,0,0,0],w=[0,0,0,0];v.forEach(function(x,k){let I=x,R=S[k];w.forEach(function(T,L,O){if(I>T){O[L]=I,I=T;const V=y[L];y[L]=R,R=V}})}),S=y,v=w}for(;v.length<4;)v.push(0),S.push(0);for(let y=0;y<4;++y)h.push(v[y]),f.push(S[y])}if(e.normal){const y=gS(g,i,m,e.normal);a.push(y[0],y[1],y[2])}e.material&&e.material.mappingType!=="AllSame"&&(E=gS(g,i,m,e.material)[0]),e.uv&&e.uv.forEach(function(y,w){const x=gS(g,i,m,y);c[w]===void 0&&(c[w]=[]),c[w].push(x[0]),c[w].push(x[1])}),r++,C&&(d.genFace(t,e,o,E,a,l,c,h,f,r),i++,r=0,o=[],a=[],l=[],c=[],h=[],f=[])}),t}genFace(e,t,i,r,s,o,a,l,c,h){for(let f=2;f<h;f++)e.vertex.push(t.vertexPositions[i[0]]),e.vertex.push(t.vertexPositions[i[1]]),e.vertex.push(t.vertexPositions[i[2]]),e.vertex.push(t.vertexPositions[i[(f-1)*3]]),e.vertex.push(t.vertexPositions[i[(f-1)*3+1]]),e.vertex.push(t.vertexPositions[i[(f-1)*3+2]]),e.vertex.push(t.vertexPositions[i[f*3]]),e.vertex.push(t.vertexPositions[i[f*3+1]]),e.vertex.push(t.vertexPositions[i[f*3+2]]),t.skeleton&&(e.vertexWeights.push(l[0]),e.vertexWeights.push(l[1]),e.vertexWeights.push(l[2]),e.vertexWeights.push(l[3]),e.vertexWeights.push(l[(f-1)*4]),e.vertexWeights.push(l[(f-1)*4+1]),e.vertexWeights.push(l[(f-1)*4+2]),e.vertexWeights.push(l[(f-1)*4+3]),e.vertexWeights.push(l[f*4]),e.vertexWeights.push(l[f*4+1]),e.vertexWeights.push(l[f*4+2]),e.vertexWeights.push(l[f*4+3]),e.weightsIndices.push(c[0]),e.weightsIndices.push(c[1]),e.weightsIndices.push(c[2]),e.weightsIndices.push(c[3]),e.weightsIndices.push(c[(f-1)*4]),e.weightsIndices.push(c[(f-1)*4+1]),e.weightsIndices.push(c[(f-1)*4+2]),e.weightsIndices.push(c[(f-1)*4+3]),e.weightsIndices.push(c[f*4]),e.weightsIndices.push(c[f*4+1]),e.weightsIndices.push(c[f*4+2]),e.weightsIndices.push(c[f*4+3])),t.color&&(e.colors.push(o[0]),e.colors.push(o[1]),e.colors.push(o[2]),e.colors.push(o[(f-1)*3]),e.colors.push(o[(f-1)*3+1]),e.colors.push(o[(f-1)*3+2]),e.colors.push(o[f*3]),e.colors.push(o[f*3+1]),e.colors.push(o[f*3+2])),t.material&&t.material.mappingType!=="AllSame"&&(e.materialIndex.push(r),e.materialIndex.push(r),e.materialIndex.push(r)),t.normal&&(e.normal.push(s[0]),e.normal.push(s[1]),e.normal.push(s[2]),e.normal.push(s[(f-1)*3]),e.normal.push(s[(f-1)*3+1]),e.normal.push(s[(f-1)*3+2]),e.normal.push(s[f*3]),e.normal.push(s[f*3+1]),e.normal.push(s[f*3+2])),t.uv&&t.uv.forEach(function(d,m){e.uvs[m]===void 0&&(e.uvs[m]=[]),e.uvs[m].push(a[m][0]),e.uvs[m].push(a[m][1]),e.uvs[m].push(a[m][(f-1)*2]),e.uvs[m].push(a[m][(f-1)*2+1]),e.uvs[m].push(a[m][f*2]),e.uvs[m].push(a[m][f*2+1])})}addMorphTargets(e,t,i,r){if(i.length===0)return;e.morphTargetsRelative=!0,e.morphAttributes.position=[];const s=this;i.forEach(function(o){o.rawTargets.forEach(function(a){const l=Gt.Objects.Geometry[a.geoID];l!==void 0&&s.genMorphGeometry(e,t,l,r,a.name)})})}genMorphGeometry(e,t,i,r,s){const o=t.PolygonVertexIndex!==void 0?t.PolygonVertexIndex.a:[],a=i.Vertices!==void 0?i.Vertices.a:[],l=i.Indexes!==void 0?i.Indexes.a:[],c=e.attributes.position.count*3,h=new Float32Array(c);for(let g=0;g<l.length;g++){const E=l[g]*3;h[E]=a[g*3],h[E+1]=a[g*3+1],h[E+2]=a[g*3+2]}const f={vertexIndices:o,vertexPositions:h},d=this.genBuffers(f),m=new ot(d.vertex,3);m.name=s||i.attrName,m.applyMatrix4(r),e.morphAttributes.position.push(m)}parseNormals(e){const t=e.MappingInformationType,i=e.ReferenceInformationType,r=e.Normals.a;let s=[];return i==="IndexToDirect"&&("NormalIndex"in e?s=e.NormalIndex.a:"NormalsIndex"in e&&(s=e.NormalsIndex.a)),{dataSize:3,buffer:r,indices:s,mappingType:t,referenceType:i}}parseUVs(e){const t=e.MappingInformationType,i=e.ReferenceInformationType,r=e.UV.a;let s=[];return i==="IndexToDirect"&&(s=e.UVIndex.a),{dataSize:2,buffer:r,indices:s,mappingType:t,referenceType:i}}parseVertexColors(e){const t=e.MappingInformationType,i=e.ReferenceInformationType,r=e.Colors.a;let s=[];return i==="IndexToDirect"&&(s=e.ColorIndex.a),{dataSize:4,buffer:r,indices:s,mappingType:t,referenceType:i}}parseMaterialIndices(e){const t=e.MappingInformationType,i=e.ReferenceInformationType;if(t==="NoMappingInformation")return{dataSize:1,buffer:[0],indices:[0],mappingType:"AllSame",referenceType:i};const r=e.Materials.a,s=[];for(let o=0;o<r.length;++o)s.push(o);return{dataSize:1,buffer:r,indices:s,mappingType:t,referenceType:i}}parseNurbsGeometry(e){if(xI===void 0)return new Tt;const t=parseInt(e.Order);if(isNaN(t))return new Tt;const i=t-1,r=e.KnotVector.a,s=[],o=e.Points.a;for(let f=0,d=o.length;f<d;f+=4)s.push(new $t().fromArray(o,f));let a,l;if(e.Form==="Closed")s.push(s[0]);else if(e.Form==="Periodic"){a=i,l=r.length-1-a;for(let f=0;f<i;++f)s.push(s[f])}const h=new xI(i,r,s,a,l).getPoints(s.length*12);return new Tt().setFromPoints(h)}}class $9{parse(){const e=[],t=this.parseClips();if(t!==void 0)for(const i in t){const r=t[i],s=this.addClip(r);e.push(s)}return e}parseClips(){if(Gt.Objects.AnimationCurve===void 0)return;const e=this.parseAnimationCurveNodes();this.parseAnimationCurves(e);const t=this.parseAnimationLayers(e);return this.parseAnimStacks(t)}parseAnimationCurveNodes(){const e=Gt.Objects.AnimationCurveNode,t=new Map;for(const i in e){const r=e[i];if(r.attrName.match(/S|R|T|DeformPercent/)!==null){const s={id:r.id,attr:r.attrName,curves:{}};t.set(s.id,s)}}return t}parseAnimationCurves(e){const t=Gt.Objects.AnimationCurve;for(const i in t){const r={id:t[i].id,times:t[i].KeyTime.a.map(r_),values:t[i].KeyValueFloat.a},s=Zn.get(r.id);if(s!==void 0){const o=s.parents[0].ID,a=s.parents[0].relationship;a.match(/X/)?e.get(o).curves.x=r:a.match(/Y/)?e.get(o).curves.y=r:a.match(/Z/)?e.get(o).curves.z=r:a.match(/d|DeformPercent/)&&e.has(o)&&(e.get(o).curves.morph=r)}}}parseAnimationLayers(e){const t=Gt.Objects.AnimationLayer,i=new Map;for(const r in t){const s=[],o=Zn.get(parseInt(r));o!==void 0&&(o.children.forEach(function(l,c){if(e.has(l.ID)){const h=e.get(l.ID);if(h.curves.x!==void 0||h.curves.y!==void 0||h.curves.z!==void 0){if(s[c]===void 0){const f=Zn.get(l.ID).parents.filter(function(d){return d.relationship!==void 0})[0].ID;if(f!==void 0){const d=Gt.Objects.Model[f.toString()];if(d===void 0)return;const m={modelName:d.attrName?zt.sanitizeNodeName(d.attrName):"",ID:d.id,initialPosition:[0,0,0],initialRotation:[0,0,0],initialScale:[1,1,1]};lr.traverse(function(g){g.ID===d.id&&(m.transform=g.matrix,g.userData.transformData&&(m.eulerOrder=g.userData.transformData.eulerOrder))}),m.transform||(m.transform=new tt),"PreRotation"in d&&(m.preRotation=d.PreRotation.value),"PostRotation"in d&&(m.postRotation=d.PostRotation.value),s[c]=m}}s[c]&&(s[c][h.attr]=h)}else if(h.curves.morph!==void 0){if(s[c]===void 0){const f=Zn.get(l.ID).parents.filter(function(S){return S.relationship!==void 0})[0].ID,d=Zn.get(f).parents[0].ID,m=Zn.get(d).parents[0].ID,g=Zn.get(m).parents[0].ID,E=Gt.Objects.Model[g],C={modelName:E.attrName?zt.sanitizeNodeName(E.attrName):"",morphName:Gt.Objects.Deformer[f].attrName};s[c]=C}s[c][h.attr]=h}}}),i.set(parseInt(r),s))}return i}parseAnimStacks(e){const t=Gt.Objects.AnimationStack,i={};for(const r in t){const s=Zn.get(parseInt(r)).children;s.length>1;const o=e.get(s[0].ID);i[r]={name:t[r].attrName,layer:o}}return i}addClip(e){let t=[];const i=this;return e.layer.forEach(function(r){t=t.concat(i.generateTracks(r))}),new sc(e.name,-1,t)}generateTracks(e){const t=[];let i=new N,r=new zn,s=new N;if(e.transform&&e.transform.decompose(i,r,s),i=i.toArray(),r=new Zs().setFromQuaternion(r,e.eulerOrder).toArray(),s=s.toArray(),e.T!==void 0&&Object.keys(e.T.curves).length>0){const o=this.generateVectorTrack(e.modelName,e.T.curves,i,"position");o!==void 0&&t.push(o)}if(e.R!==void 0&&Object.keys(e.R.curves).length>0){const o=this.generateRotationTrack(e.modelName,e.R.curves,r,e.preRotation,e.postRotation,e.eulerOrder);o!==void 0&&t.push(o)}if(e.S!==void 0&&Object.keys(e.S.curves).length>0){const o=this.generateVectorTrack(e.modelName,e.S.curves,s,"scale");o!==void 0&&t.push(o)}if(e.DeformPercent!==void 0){const o=this.generateMorphTrack(e);o!==void 0&&t.push(o)}return t}generateVectorTrack(e,t,i,r){const s=this.getTimesForAllAxes(t),o=this.getKeyframeTrackValues(s,t,i);return new rc(e+"."+r,s,o)}generateRotationTrack(e,t,i,r,s,o){t.x!==void 0&&(this.interpolateRotations(t.x),t.x.values=t.x.values.map(Oi.degToRad)),t.y!==void 0&&(this.interpolateRotations(t.y),t.y.values=t.y.values.map(Oi.degToRad)),t.z!==void 0&&(this.interpolateRotations(t.z),t.z.values=t.z.values.map(Oi.degToRad));const a=this.getTimesForAllAxes(t),l=this.getKeyframeTrackValues(a,t,i);r!==void 0&&(r=r.map(Oi.degToRad),r.push(o),r=new Zs().fromArray(r),r=new zn().setFromEuler(r)),s!==void 0&&(s=s.map(Oi.degToRad),s.push(o),s=new Zs().fromArray(s),s=new zn().setFromEuler(s).invert());const c=new zn,h=new Zs,f=[];for(let d=0;d<l.length;d+=3)h.set(l[d],l[d+1],l[d+2],o),c.setFromEuler(h),r!==void 0&&c.premultiply(r),s!==void 0&&c.multiply(s),c.toArray(f,d/3*4);return new Ho(e+".quaternion",a,f)}generateMorphTrack(e){const t=e.DeformPercent.curves.morph,i=t.values.map(function(s){return s/100}),r=lr.getObjectByName(e.modelName).morphTargetDictionary[e.morphName];return new ic(e.modelName+".morphTargetInfluences["+r+"]",t.times,i)}getTimesForAllAxes(e){let t=[];if(e.x!==void 0&&(t=t.concat(e.x.times)),e.y!==void 0&&(t=t.concat(e.y.times)),e.z!==void 0&&(t=t.concat(e.z.times)),t=t.sort(function(i,r){return i-r}),t.length>1){let i=1,r=t[0];for(let s=1;s<t.length;s++){const o=t[s];o!==r&&(t[i]=o,r=o,i++)}t=t.slice(0,i)}return t}getKeyframeTrackValues(e,t,i){const r=i,s=[];let o=-1,a=-1,l=-1;return e.forEach(function(c){if(t.x&&(o=t.x.times.indexOf(c)),t.y&&(a=t.y.times.indexOf(c)),t.z&&(l=t.z.times.indexOf(c)),o!==-1){const h=t.x.values[o];s.push(h),r[0]=h}else s.push(r[0]);if(a!==-1){const h=t.y.values[a];s.push(h),r[1]=h}else s.push(r[1]);if(l!==-1){const h=t.z.values[l];s.push(h),r[2]=h}else s.push(r[2])}),s}interpolateRotations(e){for(let t=1;t<e.values.length;t++){const i=e.values[t-1],r=e.values[t]-i,s=Math.abs(r);if(s>=180){const o=s/180,a=r/o;let l=i+a;const 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e.length>1&&(i=e[1].replace(/^(\w+)::/,""),r=e[2]),{id:t,name:i,type:r}}parseNodeProperty(e,t,i){let r=t[1].replace(/^"/,"").replace(/"$/,"").trim(),s=t[2].replace(/^"/,"").replace(/"$/,"").trim();r==="Content"&&s===","&&(s=i.replace(/"/g,"").replace(/,$/,"").trim());const o=this.getCurrentNode();if(o.name==="Properties70"){this.parseNodeSpecialProperty(e,r,s);return}if(r==="C"){const l=s.split(",").slice(1),c=parseInt(l[0]),h=parseInt(l[1]);let f=s.split(",").slice(3);f=f.map(function(d){return d.trim().replace(/^"/,"")}),r="connections",s=[c,h],o_(s,f),o[r]===void 0&&(o[r]=[])}r==="Node"&&(o.id=s),r in o&&Array.isArray(o[r])?o[r].push(s):r!=="a"?o[r]=s:o.a=s,this.setCurrentProp(o,r),r==="a"&&s.slice(-1)!==","&&(o.a=EE(s))}parseNodePropertyContinued(e){const t=this.getCurrentNode();t.a+=e,e.slice(-1)!==","&&(t.a=EE(t.a))}parseNodeSpecialProperty(e,t,i){const r=i.split('",').map(function(h){return h.trim().replace(/^\"/,"").replace(/\s/,"_")}),s=r[0],o=r[1],a=r[2],l=r[3];let 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jt=0;jt<X;++jt)Ut[jt]=Mt.getUint16(Ht+jt*2*Fn,!0);for(var jt=0;jt<X;++jt)Mt.setFloat32(Ht+jt*2*Fn,Ue(Ut[jt]),!0)}}}function ct(D,P,ee){for(var B,Q=1;Q<64;)B=P[D.value],B==65280?Q=64:B>>8==255?Q+=B&255:(ee[Q]=B,Q++),D.value++}function Ye(D,P){P[0]=Ue(D[0]),P[1]=Ue(D[1]),P[2]=Ue(D[5]),P[3]=Ue(D[6]),P[4]=Ue(D[14]),P[5]=Ue(D[15]),P[6]=Ue(D[27]),P[7]=Ue(D[28]),P[8]=Ue(D[2]),P[9]=Ue(D[4]),P[10]=Ue(D[7]),P[11]=Ue(D[13]),P[12]=Ue(D[16]),P[13]=Ue(D[26]),P[14]=Ue(D[29]),P[15]=Ue(D[42]),P[16]=Ue(D[3]),P[17]=Ue(D[8]),P[18]=Ue(D[12]),P[19]=Ue(D[17]),P[20]=Ue(D[25]),P[21]=Ue(D[30]),P[22]=Ue(D[41]),P[23]=Ue(D[43]),P[24]=Ue(D[9]),P[25]=Ue(D[11]),P[26]=Ue(D[18]),P[27]=Ue(D[24]),P[28]=Ue(D[31]),P[29]=Ue(D[40]),P[30]=Ue(D[44]),P[31]=Ue(D[53]),P[32]=Ue(D[10]),P[33]=Ue(D[19]),P[34]=Ue(D[23]),P[35]=Ue(D[32]),P[36]=Ue(D[39]),P[37]=Ue(D[45]),P[38]=Ue(D[52]),P[39]=Ue(D[54]),P[40]=Ue(D[20]),P[41]=Ue(D[22]),P[42]=Ue(D[33]),P[43]=Ue(D[38]),P[44]=Ue(D[46]),P[45]=Ue(D[51]),P[46]=Ue(D[55]),P[47]=Ue(D[60]),P[48]=Ue(D[21]),P[49]=Ue(D[34]),P[50]=Ue(D[37]),P[51]=Ue(D[47]),P[52]=Ue(D[50]),P[53]=Ue(D[56]),P[54]=Ue(D[59]),P[55]=Ue(D[61]),P[56]=Ue(D[35]),P[57]=Ue(D[36]),P[58]=Ue(D[48]),P[59]=Ue(D[49]),P[60]=Ue(D[57]),P[61]=Ue(D[58]),P[62]=Ue(D[62]),P[63]=Ue(D[63])}function je(D){const P=.5*Math.cos(.7853975),ee=.5*Math.cos(3.14159/16),B=.5*Math.cos(3.14159/8),Q=.5*Math.cos(3*3.14159/16),z=.5*Math.cos(5*3.14159/16),X=.5*Math.cos(3*3.14159/8),q=.5*Math.cos(7*3.14159/16);for(var pe=new Array(4),Se=new Array(4),ye=new Array(4),Ae=new Array(4),nt=0;nt<8;++nt){var Ke=nt*8;pe[0]=B*D[Ke+2],pe[1]=X*D[Ke+2],pe[2]=B*D[Ke+6],pe[3]=X*D[Ke+6],Se[0]=ee*D[Ke+1]+Q*D[Ke+3]+z*D[Ke+5]+q*D[Ke+7],Se[1]=Q*D[Ke+1]-q*D[Ke+3]-ee*D[Ke+5]-z*D[Ke+7],Se[2]=z*D[Ke+1]-ee*D[Ke+3]+q*D[Ke+5]+Q*D[Ke+7],Se[3]=q*D[Ke+1]-z*D[Ke+3]+Q*D[Ke+5]-ee*D[Ke+7],ye[0]=P*(D[Ke+0]+D[Ke+4]),ye[3]=P*(D[Ke+0]-D[Ke+4]),ye[1]=pe[0]+pe[3],ye[2]=pe[1]-pe[2],Ae[0]=ye[0]+ye[1],Ae[1]=ye[3]+ye[2],Ae[2]=ye[3]-ye[2],Ae[3]=ye[0]-ye[1],D[Ke+0]=Ae[0]+Se[0],D[Ke+1]=Ae[1]+Se[1],D[Ke+2]=Ae[2]+Se[2],D[Ke+3]=Ae[3]+Se[3],D[Ke+4]=Ae[3]-Se[3],D[Ke+5]=Ae[2]-Se[2],D[Ke+6]=Ae[1]-Se[1],D[Ke+7]=Ae[0]-Se[0]}for(var Oe=0;Oe<8;++Oe)pe[0]=B*D[16+Oe],pe[1]=X*D[16+Oe],pe[2]=B*D[48+Oe],pe[3]=X*D[48+Oe],Se[0]=ee*D[8+Oe]+Q*D[24+Oe]+z*D[40+Oe]+q*D[56+Oe],Se[1]=Q*D[8+Oe]-q*D[24+Oe]-ee*D[40+Oe]-z*D[56+Oe],Se[2]=z*D[8+Oe]-ee*D[24+Oe]+q*D[40+Oe]+Q*D[56+Oe],Se[3]=q*D[8+Oe]-z*D[24+Oe]+Q*D[40+Oe]-ee*D[56+Oe],ye[0]=P*(D[Oe]+D[32+Oe]),ye[3]=P*(D[Oe]-D[32+Oe]),ye[1]=pe[0]+pe[3],ye[2]=pe[1]-pe[2],Ae[0]=ye[0]+ye[1],Ae[1]=ye[3]+ye[2],Ae[2]=ye[3]-ye[2],Ae[3]=ye[0]-ye[1],D[0+Oe]=Ae[0]+Se[0],D[8+Oe]=Ae[1]+Se[1],D[16+Oe]=Ae[2]+Se[2],D[24+Oe]=Ae[3]+Se[3],D[32+Oe]=Ae[3]-Se[3],D[40+Oe]=Ae[2]-Se[2],D[48+Oe]=Ae[1]-Se[1],D[56+Oe]=Ae[0]-Se[0]}function dt(D){for(var P=0;P<64;++P){var ee=D[0][P],B=D[1][P],Q=D[2][P];D[0][P]=ee+1.5747*Q,D[1][P]=ee-.1873*B-.4682*Q,D[2][P]=ee+1.8556*B}}function vt(D,P,ee){for(var B=0;B<64;++B)P[ee+B]=Dl.toHalfFloat(_t(D[B]))}function _t(D){return D<=1?Math.sign(D)*Math.pow(Math.abs(D),2.2):Math.sign(D)*Math.pow(T,Math.abs(D)-1)}function F(D){return new DataView(D.array.buffer,D.offset.value,D.size)}function b(D){var P=D.viewer.buffer.slice(D.offset.value,D.offset.value+D.size),ee=new Uint8Array(De(P)),B=new Uint8Array(ee.length);return Ie(ee),Ce(ee,B),new DataView(B.buffer)}function ue(D){var P=D.array.slice(D.offset.value,D.offset.value+D.size),ee=yp(P),B=new Uint8Array(ee.length);return Ie(ee),Ce(ee,B),new DataView(B.buffer)}function Be(D){for(var P=D.viewer,ee={value:D.offset.value},B=new Uint16Array(D.width*D.scanlineBlockSize*(D.channels*D.type)),Q=new Uint8Array(8192),z=0,X=new Array(D.channels),q=0;q<D.channels;q++)X[q]={},X[q].start=z,X[q].end=X[q].start,X[q].nx=D.width,X[q].ny=D.lines,X[q].size=D.type,z+=X[q].nx*X[q].ny*X[q].size;var pe=re(P,ee),Se=re(P,ee);if(Se>=8192)throw"Something is wrong with PIZ_COMPRESSION BITMAP_SIZE";if(pe<=Se)for(var q=0;q<Se-pe+1;q++)Q[q+pe]=$(P,ee);var ye=new Uint16Array(65536),Ae=L(Q,ye),nt=Le(P,ee);_e(D.array,P,ee,nt,B,z);for(var q=0;q<D.channels;++q)for(var Ke=X[q],Oe=0;Oe<X[q].size;++Oe)ft(B,Ke.start+Oe,Ke.nx,Ke.size,Ke.ny,Ke.nx*Ke.size,Ae);Y(ye,B,z);for(var at=0,gt=new Uint8Array(B.buffer.byteLength),yt=0;yt<D.lines;yt++)for(var Jt=0;Jt<D.channels;Jt++){var Ke=X[Jt],it=Ke.nx*Ke.size,Ve=new Uint8Array(B.buffer,Ke.end*2,it*2);gt.set(Ve,at),at+=it*2,Ke.end+=it}return new DataView(gt.buffer)}function Je(D){var P=D.array.slice(D.offset.value,D.offset.value+D.size),ee=yp(P);const B=D.lines*D.channels*D.width,Q=D.type==1?new Uint16Array(B):new Uint32Array(B);let z=0,X=0;const q=new Array(4);for(let pe=0;pe<D.lines;pe++)for(let Se=0;Se<D.channels;Se++){let ye=0;switch(D.type){case 1:q[0]=z,q[1]=q[0]+D.width,z=q[1]+D.width;for(let Ae=0;Ae<D.width;++Ae){const nt=ee[q[0]++]<<8|ee[q[1]++];ye+=nt,Q[X]=ye,X++}break;case 2:q[0]=z,q[1]=q[0]+D.width,q[2]=q[1]+D.width,z=q[2]+D.width;for(let Ae=0;Ae<D.width;++Ae){const nt=ee[q[0]++]<<24|ee[q[1]++]<<16|ee[q[2]++]<<8;ye+=nt,Q[X]=ye,X++}break}}return new DataView(Q.buffer)}function Re(D){var P=D.viewer,ee={value:D.offset.value},B=new Uint8Array(D.width*D.lines*(D.channels*D.type*2)),Q={version:de(P,ee),unknownUncompressedSize:de(P,ee),unknownCompressedSize:de(P,ee),acCompressedSize:de(P,ee),dcCompressedSize:de(P,ee),rleCompressedSize:de(P,ee),rleUncompressedSize:de(P,ee),rleRawSize:de(P,ee),totalAcUncompressedCount:de(P,ee),totalDcUncompressedCount:de(P,ee),acCompression:de(P,ee)};if(Q.version<2)throw"EXRLoader.parse: "+ir.compression+" version "+Q.version+" is unsupported";for(var z=new Array,X=re(P,ee)-2;X>0;){var q=$e(P.buffer,ee),pe=$(P,ee),Se=pe>>2&3,ye=(pe>>4)-1,Ae=new Int8Array([ye])[0],nt=$(P,ee);z.push({name:q,index:Ae,type:nt,compression:Se}),X-=q.length+3}for(var Ke=ir.channels,Oe=new Array(D.channels),at=0;at<D.channels;++at){var gt=Oe[at]={},yt=Ke[at];gt.name=yt.name,gt.compression=0,gt.decoded=!1,gt.type=yt.pixelType,gt.pLinear=yt.pLinear,gt.width=D.width,gt.height=D.lines}for(var Jt={idx:new Array(3)},it=0;it<D.channels;++it)for(var gt=Oe[it],at=0;at<z.length;++at){var Ve=z[at];gt.name==Ve.name&&(gt.compression=Ve.compression,Ve.index>=0&&(Jt.idx[Ve.index]=it),gt.offset=it)}if(Q.acCompressedSize>0)switch(Q.acCompression){case 0:var Mt=new Uint16Array(Q.totalAcUncompressedCount);_e(D.array,P,ee,Q.acCompressedSize,Mt,Q.totalAcUncompressedCount);break;case 1:var Nt=D.array.slice(ee.value,ee.value+Q.totalAcUncompressedCount),Ut=yp(Nt),Mt=new Uint16Array(Ut.buffer);ee.value+=Q.totalAcUncompressedCount;break}if(Q.dcCompressedSize>0){var on={array:D.array,offset:ee,size:Q.dcCompressedSize},Fn=new Uint16Array(ue(on).buffer);ee.value+=Q.dcCompressedSize}if(Q.rleRawSize>0){var Nt=D.array.slice(ee.value,ee.value+Q.rleCompressedSize),Ut=yp(Nt),Un=De(Ut.buffer);ee.value+=Q.rleCompressedSize}for(var jt=0,Ht=new Array(Oe.length),at=0;at<Ht.length;++at)Ht[at]=new Array;for(var Tn=0;Tn<D.lines;++Tn)for(var Rt=0;Rt<Oe.length;++Rt)Ht[Rt].push(jt),jt+=Oe[Rt].width*D.type*2;xe(Jt,Ht,Oe,Mt,Fn,B);for(var at=0;at<Oe.length;++at){var gt=Oe[at];if(!gt.decoded)switch(gt.compression){case 2:for(var Vt=0,mn=0,Tn=0;Tn<D.lines;++Tn){for(var Pr=Ht[at][Vt],Wi=0;Wi<gt.width;++Wi){for(var Os=0;Os<2*gt.type;++Os)B[Pr++]=Un[mn+Os*gt.width*gt.height];mn++}Vt++}break;case 1:default:throw"EXRLoader.parse: unsupported channel compression"}}return new DataView(B.buffer)}function $e(D,P){for(var ee=new Uint8Array(D),B=0;ee[P.value+B]!=0;)B+=1;var Q=new TextDecoder().decode(ee.slice(P.value,P.value+B));return P.value=P.value+B+1,Q}function Qe(D,P,ee){var B=new TextDecoder().decode(new Uint8Array(D).slice(P.value,P.value+ee));return P.value=P.value+ee,B}function Ge(D,P){var ee=kt(D,P),B=Le(D,P);return[ee,B]}function At(D,P){var ee=Le(D,P),B=Le(D,P);return[ee,B]}function kt(D,P){var ee=D.getInt32(P.value,!0);return P.value=P.value+4,ee}function Le(D,P){var ee=D.getUint32(P.value,!0);return P.value=P.value+4,ee}function Dt(D,P){var ee=D[P.value];return P.value=P.value+1,ee}function $(D,P){var ee=D.getUint8(P.value);return P.value=P.value+1,ee}const de=function(D,P){let ee;return"getBigInt64"in DataView.prototype?ee=Number(D.getBigInt64(P.value,!0)):ee=D.getUint32(P.value+4,!0)+Number(D.getUint32(P.value,!0)<<32),P.value+=8,ee};function ke(D,P){var ee=D.getFloat32(P.value,!0);return P.value+=4,ee}function be(D,P){return Dl.toHalfFloat(ke(D,P))}function Ue(D){var P=(D&31744)>>10,ee=D&1023;return(D>>15?-1:1)*(P?P===31?ee?NaN:1/0:Math.pow(2,P-15)*(1+ee/1024):6103515625e-14*(ee/1024))}function re(D,P){var ee=D.getUint16(P.value,!0);return P.value+=2,ee}function qe(D,P){return Ue(re(D,P))}function We(D,P,ee,B){for(var Q=ee.value,z=[];ee.value<Q+B-1;){var X=$e(P,ee),q=kt(D,ee),pe=$(D,ee);ee.value+=3;var Se=kt(D,ee),ye=kt(D,ee);z.push({name:X,pixelType:q,pLinear:pe,xSampling:Se,ySampling:ye})}return ee.value+=1,z}function ve(D,P){var ee=ke(D,P),B=ke(D,P),Q=ke(D,P),z=ke(D,P),X=ke(D,P),q=ke(D,P),pe=ke(D,P),Se=ke(D,P);return{redX:ee,redY:B,greenX:Q,greenY:z,blueX:X,blueY:q,whiteX:pe,whiteY:Se}}function Pe(D,P){var ee=["NO_COMPRESSION","RLE_COMPRESSION","ZIPS_COMPRESSION","ZIP_COMPRESSION","PIZ_COMPRESSION","PXR24_COMPRESSION","B44_COMPRESSION","B44A_COMPRESSION","DWAA_COMPRESSION","DWAB_COMPRESSION"],B=$(D,P);return ee[B]}function pt(D,P){var ee=Le(D,P),B=Le(D,P),Q=Le(D,P),z=Le(D,P);return{xMin:ee,yMin:B,xMax:Q,yMax:z}}function It(D,P){var ee=["INCREASING_Y"],B=$(D,P);return ee[B]}function sn(D,P){var ee=ke(D,P),B=ke(D,P);return[ee,B]}function dn(D,P){var ee=ke(D,P),B=ke(D,P),Q=ke(D,P);return[ee,B,Q]}function Yt(D,P,ee,B,Q){if(B==="string"||B==="stringvector"||B==="iccProfile")return Qe(P,ee,Q);if(B==="chlist")return We(D,P,ee,Q);if(B==="chromaticities")return ve(D,ee);if(B==="compression")return Pe(D,ee);if(B==="box2i")return pt(D,ee);if(B==="lineOrder")return It(D,ee);if(B==="float")return ke(D,ee);if(B==="v2f")return sn(D,ee);if(B==="v3f")return dn(D,ee);if(B==="int")return kt(D,ee);if(B==="rational")return Ge(D,ee);if(B==="timecode")return At(D,ee);if(B==="preview")return ee.value+=Q,"skipped";ee.value+=Q}function ni(D,P,ee){const B={};if(D.getUint32(0,!0)!=20000630)throw"THREE.EXRLoader: provided file doesn't appear to be in OpenEXR format.";B.version=D.getUint8(4);const Q=D.getUint8(5);B.spec={singleTile:!!(Q&2),longName:!!(Q&4),deepFormat:!!(Q&8),multiPart:!!(Q&16)},ee.value=8;for(var z=!0;z;){var X=$e(P,ee);if(X==0)z=!1;else{var q=$e(P,ee),pe=Le(D,ee),Se=Yt(D,P,ee,q,pe);Se===void 0||(B[X]=Se)}}if(Q!=0)throw"THREE.EXRLoader: provided file is currently unsupported.";return B}function nr(D,P,ee,B,Q){const z={size:0,viewer:P,array:ee,offset:B,width:D.dataWindow.xMax-D.dataWindow.xMin+1,height:D.dataWindow.yMax-D.dataWindow.yMin+1,channels:D.channels.length,bytesPerLine:null,lines:null,inputSize:null,type:D.channels[0].pixelType,uncompress:null,getter:null,format:null,[hp?"colorSpace":"encoding"]:null};switch(D.compression){case"NO_COMPRESSION":z.lines=1,z.uncompress=F;break;case"RLE_COMPRESSION":z.lines=1,z.uncompress=b;break;case"ZIPS_COMPRESSION":z.lines=1,z.uncompress=ue;break;case"ZIP_COMPRESSION":z.lines=16,z.uncompress=ue;break;case"PIZ_COMPRESSION":z.lines=32,z.uncompress=Be;break;case"PXR24_COMPRESSION":z.lines=16,z.uncompress=Je;break;case"DWAA_COMPRESSION":z.lines=32,z.uncompress=Re;break;case"DWAB_COMPRESSION":z.lines=256,z.uncompress=Re;break;default:throw"EXRLoader.parse: "+D.compression+" is unsupported"}if(z.scanlineBlockSize=z.lines,z.type==1)switch(Q){case Ei:z.getter=qe,z.inputSize=2;break;case ji:z.getter=re,z.inputSize=2;break}else if(z.type==2)switch(Q){case Ei:z.getter=ke,z.inputSize=4;break;case ji:z.getter=be,z.inputSize=4}else throw"EXRLoader.parse: unsupported pixelType "+z.type+" for "+D.compression+".";z.blockCount=(D.dataWindow.yMax+1)/z.scanlineBlockSize;for(var X=0;X<z.blockCount;X++)de(P,B);z.outputChannels=z.channels==3?4:z.channels;const q=z.width*z.height*z.outputChannels;switch(Q){case Ei:z.byteArray=new Float32Array(q),z.channels<z.outputChannels&&z.byteArray.fill(1,0,q);break;case ji:z.byteArray=new Uint16Array(q),z.channels<z.outputChannels&&z.byteArray.fill(15360,0,q);break;default:break}return z.bytesPerLine=z.width*z.inputSize*z.channels,z.outputChannels==4?z.format=bi:z.format=VU,hp?z.colorSpace="srgb-linear":z.encoding=3e3,z}const bs=new DataView(e),_a=new Uint8Array(e),Fr={value:0},ir=ni(bs,e,Fr),Kt=nr(ir,bs,_a,Fr,this.type),$a={value:0},Ac={R:0,G:1,B:2,A:3,Y:0};for(let D=0;D<Kt.height/Kt.scanlineBlockSize;D++){const P=Le(bs,Fr);Kt.size=Le(bs,Fr),Kt.lines=P+Kt.scanlineBlockSize>Kt.height?Kt.height-P:Kt.scanlineBlockSize;const B=Kt.size<Kt.lines*Kt.bytesPerLine?Kt.uncompress(Kt):F(Kt);Fr.value+=Kt.size;for(let Q=0;Q<Kt.scanlineBlockSize;Q++){const z=Q+D*Kt.scanlineBlockSize;if(z>=Kt.height)break;for(let X=0;X<Kt.channels;X++){const q=Ac[ir.channels[X].name];for(let pe=0;pe<Kt.width;pe++){$a.value=(Q*(Kt.channels*Kt.width)+X*Kt.width+pe)*Kt.inputSize;const Se=(Kt.height-1-z)*(Kt.width*Kt.outputChannels)+pe*Kt.outputChannels+q;Kt.byteArray[Se]=Kt.getter(B,$a)}}}}return{header:ir,width:Kt.width,height:Kt.height,data:Kt.byteArray,format:Kt.format,[hp?"colorSpace":"encoding"]:Kt[hp?"colorSpace":"encoding"],type:this.type}}setDataType(e){return this.type=e,this}load(e,t,i,r){function s(o,a){hp?o.colorSpace=a.colorSpace:o.encoding=a.encoding,o.minFilter=pn,o.magFilter=pn,o.generateMipmaps=!1,o.flipY=!1,t&&t(o,a)}return super.load(e,s,i,r)}}const CE=new WeakMap;class u_ extends Mi{constructor(e){super(e),this.decoderPath="",this.decoderConfig={},this.decoderBinary=null,this.decoderPending=null,this.workerLimit=4,this.workerPool=[],this.workerNextTaskID=1,this.workerSourceURL="",this.defaultAttributeIDs={position:"POSITION",normal:"NORMAL",color:"COLOR",uv:"TEX_COORD"},this.defaultAttributeTypes={position:"Float32Array",normal:"Float32Array",color:"Float32Array",uv:"Float32Array"}}setDecoderPath(e){return this.decoderPath=e,this}setDecoderConfig(e){return this.decoderConfig=e,this}setWorkerLimit(e){return this.workerLimit=e,this}load(e,t,i,r){const s=new yr(this.manager);s.setPath(this.path),s.setResponseType("arraybuffer"),s.setRequestHeader(this.requestHeader),s.setWithCredentials(this.withCredentials),s.load(e,o=>{const a={attributeIDs:this.defaultAttributeIDs,attributeTypes:this.defaultAttributeTypes,useUniqueIDs:!1};this.decodeGeometry(o,a).then(t).catch(r)},i,r)}decodeDracoFile(e,t,i,r){const s={attributeIDs:i||this.defaultAttributeIDs,attributeTypes:r||this.defaultAttributeTypes,useUniqueIDs:!!i};this.decodeGeometry(e,s).then(t)}decodeGeometry(e,t){for(const l in t.attributeTypes){const c=t.attributeTypes[l];c.BYTES_PER_ELEMENT!==void 0&&(t.attributeTypes[l]=c.name)}const i=JSON.stringify(t);if(CE.has(e)){const l=CE.get(e);if(l.key===i)return l.promise;if(e.byteLength===0)throw new Error("THREE.DRACOLoader: Unable to re-decode a buffer with different settings. Buffer has already been transferred.")}let r;const s=this.workerNextTaskID++,o=e.byteLength,a=this._getWorker(s,o).then(l=>(r=l,new Promise((c,h)=>{r._callbacks[s]={resolve:c,reject:h},r.postMessage({type:"decode",id:s,taskConfig:t,buffer:e},[e])}))).then(l=>this._createGeometry(l.geometry));return a.catch(()=>!0).then(()=>{r&&s&&this._releaseTask(r,s)}),CE.set(e,{key:i,promise:a}),a}_createGeometry(e){const t=new Tt;e.index&&t.setIndex(new Xt(e.index.array,1));for(let i=0;i<e.attributes.length;i++){const r=e.attributes[i],s=r.name,o=r.array,a=r.itemSize;t.setAttribute(s,new Xt(o,a))}return t}_loadLibrary(e,t){const i=new yr(this.manager);return i.setPath(this.decoderPath),i.setResponseType(t),i.setWithCredentials(this.withCredentials),new Promise((r,s)=>{i.load(e,r,void 0,s)})}preload(){return this._initDecoder(),this}_initDecoder(){if(this.decoderPending)return this.decoderPending;const e=typeof WebAssembly!="object"||this.decoderConfig.type==="js",t=[];return e?t.push(this._loadLibrary("draco_decoder.js","text")):(t.push(this._loadLibrary("draco_wasm_wrapper.js","text")),t.push(this._loadLibrary("draco_decoder.wasm","arraybuffer"))),this.decoderPending=Promise.all(t).then(i=>{const r=i[0];e||(this.decoderConfig.wasmBinary=i[1]);const s=h_.toString(),o=["/* draco decoder */",r,"","/* worker */",s.substring(s.indexOf("{")+1,s.lastIndexOf("}"))].join(`
`);this.workerSourceURL=URL.createObjectURL(new Blob([o]))}),this.decoderPending}_getWorker(e,t){return this._initDecoder().then(()=>{if(this.workerPool.length<this.workerLimit){const r=new Worker(this.workerSourceURL);r._callbacks={},r._taskCosts={},r._taskLoad=0,r.postMessage({type:"init",decoderConfig:this.decoderConfig}),r.onmessage=function(s){const o=s.data;switch(o.type){case"decode":r._callbacks[o.id].resolve(o);break;case"error":r._callbacks[o.id].reject(o);break;default:}},this.workerPool.push(r)}else this.workerPool.sort(function(r,s){return r._taskLoad>s._taskLoad?-1:1});const i=this.workerPool[this.workerPool.length-1];return i._taskCosts[e]=t,i._taskLoad+=t,i})}_releaseTask(e,t){e._taskLoad-=e._taskCosts[t],delete e._callbacks[t],delete e._taskCosts[t]}debug(){}dispose(){for(let e=0;e<this.workerPool.length;++e)this.workerPool[e].terminate();return this.workerPool.length=0,this}}function h_(){let n,e;onmessage=function(o){const a=o.data;switch(a.type){case"init":n=a.decoderConfig,e=new Promise(function(h){n.onModuleLoaded=function(f){h({draco:f})},DracoDecoderModule(n)});break;case"decode":const l=a.buffer,c=a.taskConfig;e.then(h=>{const f=h.draco,d=new f.Decoder,m=new f.DecoderBuffer;m.Init(new Int8Array(l),l.byteLength);try{const g=t(f,d,m,c),E=g.attributes.map(C=>C.array.buffer);g.index&&E.push(g.index.array.buffer),self.postMessage({type:"decode",id:a.id,geometry:g},E)}catch(g){self.postMessage({type:"error",id:a.id,error:g.message})}finally{f.destroy(m),f.destroy(d)}});break}};function t(o,a,l,c){const h=c.attributeIDs,f=c.attributeTypes;let d,m;const g=a.GetEncodedGeometryType(l);if(g===o.TRIANGULAR_MESH)d=new o.Mesh,m=a.DecodeBufferToMesh(l,d);else if(g===o.POINT_CLOUD)d=new o.PointCloud,m=a.DecodeBufferToPointCloud(l,d);else throw new Error("THREE.DRACOLoader: Unexpected geometry type.");if(!m.ok()||d.ptr===0)throw new Error("THREE.DRACOLoader: Decoding failed: "+m.error_msg());const E={index:null,attributes:[]};for(const C in h){const S=self[f[C]];let v,y;if(c.useUniqueIDs)y=h[C],v=a.GetAttributeByUniqueId(d,y);else{if(y=a.GetAttributeId(d,o[h[C]]),y===-1)continue;v=a.GetAttribute(d,y)}E.attributes.push(r(o,a,d,C,S,v))}return g===o.TRIANGULAR_MESH&&(E.index=i(o,a,d)),o.destroy(d),E}function i(o,a,l){const h=l.num_faces()*3,f=h*4,d=o._malloc(f);a.GetTrianglesUInt32Array(l,f,d);const m=new Uint32Array(o.HEAPF32.buffer,d,h).slice();return o._free(d),{array:m,itemSize:1}}function r(o,a,l,c,h,f){const d=f.num_components(),g=l.num_points()*d,E=g*h.BYTES_PER_ELEMENT,C=s(o,h),S=o._malloc(E);a.GetAttributeDataArrayForAllPoints(l,f,C,E,S);const v=new h(o.HEAPF32.buffer,S,g).slice();return o._free(S),{name:c,array:v,itemSize:d}}function s(o,a){switch(a){case Float32Array:return o.DT_FLOAT32;case Int8Array:return o.DT_INT8;case Int16Array:return o.DT_INT16;case Int32Array:return o.DT_INT32;case Uint8Array:return o.DT_UINT8;case Uint16Array:return o.DT_UINT16;case Uint32Array:return o.DT_UINT32}}}let AS;const vE=()=>{if(AS)return AS;const n="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",e="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",M_=n=>{const e=uM(w_),t=ur(i=>i.viewport);return Mn.jsxs(Mn.Fragment,{children:[Mn.jsx(p_,{enabled:n.orbitControl}),Mn.jsx(U_,{position:[0,-3,5],scale:2,subject:n.subject}),Mn.jsx(y_,{preset:"sunset"}),Mn.jsxs("mesh",{children:[Mn.jsx("planeGeometry",{args:[t.width,t.height]}),Mn.jsx("meshBasicMaterial",{map:e})]})]})};function k_(n){const e=new qv;return IE.createRoot(n).render(Mn.jsxs(j.StrictMode,{children:[Mn.jsx(AO,{hidden:!0}),Mn.jsxs(fV,{shadows:!0,camera:{position:[0,.5,8],fov:21},children:[Mn.jsx("color",{attach:"background",args:["#ececec"]}),Mn.jsx(M_,{orbitControl:!1,subject:e})]})]})),e}const x_=zv({name:"VirtualHuman",__name:"VirtualHuman",setup(n,{expose:e}){const t=xo(),i=xo();function r(){t.value&&(i.value=k_(t.value))}return IF(()=>{r()}),e({say:o=>{var a;(a=i.value)==null||a.next({data:JSON.stringify({visemes:o})})}}),(o,a)=>(Ep(),LF("section",{class:vl([o.$style["personal-appearance"]]),ref_key:"renderRef",ref:t},null,2))}}),T_={"personal-appearance":"_personal-appearance_vqx35_2"},J_={$style:T_},I_=bI(x_,[["__cssModules",J_]]);function L_(n){const e=new AudioContext;let t=e.currentTime,i;async function r(o){const a=o.size,l=e.createBuffer(1,a/Int16Array.BYTES_PER_ELEMENT,16e3),c=l.getChannelData(0),h=await o.arrayBuffer(),f=new Int16Array(h,0,Math.floor(h.byteLength/2));for(let m=0;m<f.length;m++)c[m]=f[m]/32768;const d=e.createBufferSource();d.buffer=l,d.connect(e.destination),d.start(t),t=Math.max(t,e.currentTime)+l.duration,d.onended=()=>{n!=null&&n.container&&(i&&i.destroy(),i=new kF({container:n.container,waveColor:"rgb(200, 0, 200)",progressColor:"rgb(100, 0, 100)",media:new Audio(URL.createObjectURL(o)),height:3*16}))}}const s=new qv;return s.pipe(gP(r)).subscribe(o=>{}),s}const B_={class:"main-header 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DI(c,v=>{v&&(f.value=zk[v][0].name)},{immediate:!0}),(v,y)=>{const w=RF,x=OF,k=KI;return Ep(),ES(KF,null,{default:Fh(()=>[Zr("header",B_,[K_,Zr("aside",R_,[Ao(w,{severity:"secondary",label:"Escape",onClick:y[0]||(y[0]=()=>v.$router.push({name:"home"}))},{icon:Fh(()=>[Ao(Cl(Gk),{class:"p-icon un-mr-3"})]),_:1})])]),Zr("main",{class:vl(["main-body",[v.$style.main]])},[Zr("aside",D_,[Ao(I_,{ref_key:"virtualHumanRef",ref:l},null,512)]),Zr("section",{class:vl([v.$style["main-view"]])},[Zr("audio",{ref_key:"audioRef",ref:o,style:{position:"absolute",left:"0",top:"0",opacity:"0"}},null,512),Zr("section",{class:vl([v.$style["text-content"]])},[Ao(Vk,{class:"un-flex-1",contents:Cl(g),current:Cl(m)},null,8,["contents","current"]),Ao(Vk,{contents:Cl(E),class:"un-flex-1"},null,8,["contents"])],2),Zr("section",{class:vl([v.$style.bar])},[Ao(x,{class:"un-flex-1","model-value":c.value,"onUpdate:modelValue":y[1]||(y[1]=I=>c.value=I),disabled:s.value==="connected"},null,8,["model-value","disabled"]),Ao(k,{class:"un-flex-1","model-value":f.value,"onUpdate:modelValue":y[2]||(y[2]=I=>f.value=I),options:h.value,"option-label":"name","option-value":"name",disabled:s.value==="connected"},{option:Fh(I=>[Zr("section",null,Yk(I.option.name)+"("+Yk(I.option.gender)+")",1)]),_:1},8,["model-value","options","disabled"])],2),Zr("section",{class:vl([v.$style.bar])},[s.value!=="connected"?(Ep(),ES(w,{key:0,label:"Start",onClick:S},{icon:Fh(()=>[Ao(Cl(bF),{class:"p-icon"})]),_:1})):(Ep(),ES(w,{key:1,label:"Stop",onClick:C},{icon:Fh(()=>[Ao(Cl(Gk),{class:"p-icon un-mr-4"})]),_:1})),Zr("section",{class:vl(["un-flex-1",[v.$style["bar-inner"]]]),ref_key:"waveRef",ref:i},null,2)],2)],2)],2)]),_:1})}}}),O_="_main_15lo4_2",F_="_options_15lo4_13",P_="_bar_15lo4_26",N_={main:O_,"main-header":"_main-header_15lo4_9",options:F_,"main-view":"_main-view_15lo4_20",bar:P_,"bar-inner":"_bar-inner_15lo4_37","text-content":"_text-content_15lo4_41"},Q_={$style:N_},e$=bI(b_,[["__cssModules",Q_]]);export{e$ as default};