我无法在Javascript中生成平滑的单纯形噪声
我已经尝试了一切,阅读了互联网上关于柏林噪声或单纯形噪声的每一个链接,甚至剖析了一些我认为可以正常工作的Javascript示例 但我仍然得到非常随机的图像。。。基本上只是电视静电 我的代码如下。我使用了一个随机数生成器,这样我就可以给一个值设定种子,但我也尝试了Math.random 据我所知,不同倍频程下生成的不同图像插值不正确,或者我从噪波函数转换为RGB值的方式是错误的(我已尝试解决这两个问题…)我无法在Javascript中生成平滑的单纯形噪声,javascript,textures,perlin-noise,simplex-noise,Javascript,Textures,Perlin Noise,Simplex Noise,我已经尝试了一切,阅读了互联网上关于柏林噪声或单纯形噪声的每一个链接,甚至剖析了一些我认为可以正常工作的Javascript示例 但我仍然得到非常随机的图像。。。基本上只是电视静电 我的代码如下。我使用了一个随机数生成器,这样我就可以给一个值设定种子,但我也尝试了Math.random 据我所知,不同倍频程下生成的不同图像插值不正确,或者我从噪波函数转换为RGB值的方式是错误的(我已尝试解决这两个问题…) if(!this.Prng){ var Prng=函数(){ var iMersenne=
if(!this.Prng){
var Prng=函数(){
var iMersenne=2147483647;
var rnd=函数(种子){
if(arguments.length){
that.seed=参数[0];
}
that.seed=that.seed*16807%iMersenne;
归还那颗种子;
};
var={
种子:123,
rnd:rnd,
随机:函数(种子){
if(arguments.length){
that.seed=参数[0];
}
返回rnd()/iMersenne;
}
};
归还;
}();
}
var CSimplexNoise=函数(r)
{
this.grad3=[[1,1,0],-1,1,0],[1,-1,0],-1,-1,0],[1,0,1],-1,0,1],
[1,0,-1],[-1,0,-1],[0,1,1],[0,-1,1],[0,1,-1],[0,-1,-1]];
var p=[];
对于(i=0;i<256;i++)
p[i]=数学层(r.random()*256);
this.perm=新数组();
对于(i=0;i<512;i++)
{
this.perm[i]=p[i&255];
}
}
CSimplexNoise.prototype.dot=函数(g,x,y)
{
返回g[0]*x+g[1]*y;
}
CSimplexNoise.prototype.GenerateSimplexNoise=函数(x、y、倍频程、持久性)
{
var合计=0;
对于(i=0;iy0)
{
i1=1;
j1=0;
}
其他的
{
i1=0;
j1=1;
}
var x1=x0-i1+G2;
变量y1=y0-j1+G2;
var x2=x0-1+2*G2;
变量y2=y0-1+2*G2;
var ii=i&255;
var jj=j&255;
var gi0=this.perm[ii+this.perm[jj]]%12;
var gi1=this.perm[ii+i1+this.perm[jj+j1]]%12;
var gi2=this.perm[ii+1+this.perm[jj+1]]%12;
var t0=0.5-x0*x0-y0*y0;
if(t0<0)
n0=0;
其他的
{
t0*=t0;
n0=t0*t0*this.dot(this.grad3[gi0],x0,y0)
}
var t1=0.5-x1*x1-y1*y1;
if(t1<0)
n1=0;
其他的
{
t1*=t1;
n1=t1*t1*this.dot(this.grad3[gi1],x1,y1);
}
变量t2=0.5-x2*x2-y2*y2;
如果(t2尝试采样simplexNoise。生成simplexNoise(x*0.05,y*0.05,5,0.5)
问题可能是样本之间的距离太远(这会导致明显的随机行为,因为单纯形噪声在采样之前可能会经过超过半个波长)
修订:更新以上数字。。。
实际上,您可能需要减少采样,以便在给定波长的单纯形噪声中有20个。大多数单纯形噪声的平均波长为1,因此0.05应该可以。此外,您可能希望首先只使用一个倍频程进行测试。我同意,看起来初始频率为1,并且只随每个倍频程而增加,因此如果您采样对于整数,你永远看不到任何相干性。
if (!this.Prng) {
var Prng = function() {
var iMersenne = 2147483647;
var rnd = function(seed) {
if (arguments.length) {
that.seed = arguments[0];
}
that.seed = that.seed*16807%iMersenne;
return that.seed;
};
var that = {
seed: 123,
rnd: rnd,
random: function(seed) {
if (arguments.length) {
that.seed = arguments[0];
}
return rnd()/iMersenne;
}
};
return that;
}();
}
var CSimplexNoise = function(r)
{
this.grad3 = [[1,1,0],[-1,1,0],[1,-1,0],[-1,-1,0],[1,0,1],[-1,0,1],
[1,0,-1],[-1,0,-1],[0,1,1],[0,-1,1],[0,1,-1],[0,-1,-1]];
var p = [];
for(i = 0; i < 256; i++)
p[i] = Math.floor(r.random()*256);
this.perm = new Array();
for(i = 0; i < 512; i++)
{
this.perm[i] = p[i & 255];
}
}
CSimplexNoise.prototype.dot = function(g,x,y)
{
return g[0]*x + g[1]*y;
}
CSimplexNoise.prototype.GenerateSimplexNoise = function(x,y,octaves,persistence)
{
var total = 0;
for(i=0; i < octaves-1; i++)
{
var freq = Math.pow(2,i);
var amp = Math.pow(persistence,i);
total += this.InterpolatedNoise(x*freq,y*freq) * amp;
}
return total;
}
CSimplexNoise.prototype.InterpolatedNoise = function(x,y)
{
var xInt = Math.floor(x);
var xFrac = x - xInt;
var yInt = Math.floor(y);
var yFrac = y - yInt;
var v1 = this.SmoothNoise(xInt,yInt);
var v2 = this.SmoothNoise(xInt + 1,yInt)
var v3 = this.SmoothNoise(xInt,yInt+1)
var v4 = this.SmoothNoise(xInt + 1, yInt + 1);
var i1 = this.LinearInterpolate(v1,v2,xFrac);
var i2 = this.LinearInterpolate(v3,v4,xFrac);
return this.CosineInterpolate(i1,i2,yFrac);
}
CSimplexNoise.prototype.LinearInterpolate = function(a,b,x)
{
return a*(1-x) + b*x;
}
CSimplexNoise.prototype.CosineInterpolate = function(a,b,x)
{
var f = (1 - Math.cos(x*Math.PI)) * 0.5;
return a*(1-f) + b*f;
}
CSimplexNoise.prototype.SmoothNoise = function(x,y)
{
var corners = (this.Noise(x-1,y-1) + this.Noise(x+1,y-1) + this.Noise(x-1,y+1) + this.Noise(x+1,y+1)) / 16;
var sides = (this.Noise(x-1,y) + this.Noise(x+1,y) + this.Noise(x,y-1) + this.Noise(x+1,y+1)) / 8;
var center = this.Noise(x,y) / 4;
return corners + sides + center;
}
CSimplexNoise.prototype.Noise = function(xin, yin)
{
var n0, n1, n2;
var F2 = 0.5*(Math.sqrt(3)-1);
var s = (xin+yin)*F2;
var i = Math.floor(xin+s);
var j = Math.floor(yin+s);
var G2 = (3-Math.sqrt(3))/6;
var t = (i+j)*G2;
var X0 = i-t;
var Y0 = j-t;
var x0 = xin-X0;
var y0 = yin-Y0;
var i1,j1;
if(x0 > y0)
{
i1 = 1;
j1 = 0;
}
else
{
i1 = 0;
j1 = 1;
}
var x1 = x0 - i1 + G2;
var y1 = y0 - j1 + G2;
var x2 = x0 - 1 + 2 * G2;
var y2 = y0 - 1 + 2 * G2;
var ii = i & 255;
var jj = j & 255;
var gi0 = this.perm[ii + this.perm[jj]] % 12;
var gi1 = this.perm[ii + i1 + this.perm[jj + j1]] % 12;
var gi2 = this.perm[ii + 1 + this.perm[jj + 1]] % 12;
var t0 = 0.5 - x0 * x0 - y0 * y0;
if(t0 < 0)
n0 = 0;
else
{
t0 *= t0;
n0 = t0 * t0 * this.dot(this.grad3[gi0],x0,y0)
}
var t1 = 0.5 - x1 * x1 - y1 * y1;
if(t1 < 0)
n1 = 0;
else
{
t1 *= t1;
n1 = t1 * t1 * this.dot(this.grad3[gi1],x1,y1);
}
var t2 = 0.5 - x2 * x2 - y2 * y2;
if(t2 <0 )
n2 = 0;
else
{
t2 *= t2;
n2 = t2 * t2 * this.dot(this.grad3[gi2],x2,y2);
}
return 70 * (n0 + n1 + n2);
}
$(document).ready(function(){
var context = $('#screen')[0].getContext("2d");
var w = 100;
var h = 100;
var data = context.createImageData(w,h);
var simplexNoise = new CSimplexNoise(Prng);
for(y = 0; y < h; y++)
{
for(x = 0; x < w; x++)
{
// var newVal = ((simplexNoise.GenerateSimplexNoise(x,y,5,0.25) - -1) / (1 - -1)) * (255 - 0);
var newVal2 = simplexNoise.GenerateSimplexNoise(x,y,5,0.5)
var newVal = Math.floor(newVal2*256);
newVal = Math.abs(newVal * 2)-0.5;
data.data[((h * y) + x) * 4] = newVal;
data.data[((h * y) + x) * 4+1] = newVal;
data.data[((h * y) + x) * 4+2] = newVal;
data.data[((h * y) + x) * 4+3] = 255;
}
}
context.putImageData(data,0,0);
})