Java 柏林噪声值范围

我使用柏林噪波生成二维高度贴图。起初，我手动尝试了一些参数，找到了振幅、持久性和，。。。为了我的工作

现在我正在开发这个程序，我为用户添加了一个功能，可以更改贴图参数并为自己制作一个新的贴图，但现在我发现某些参数（主要是倍频程和频率）的值不在我以前看到的范围内。我认为如果一个设定的振幅=20，我从中得到的值（高度）将在[0,20]或[-10,10]或[-20,20]范围内，但现在我看到振幅不是控制输出范围的唯一参数

我的问题是：是否有一个精确的数学公式（振幅、倍频程、频率和持续性的函数）来计算范围，或者我应该采集大量样本（如100000），检查它们的最小值和最大值，以猜测近似范围

注意：下面的代码是perlin noise的一个实现，stackoverflow的一个家伙用C编写了它，我将它移植到java

PerlinNoiseParameters.java

public class PerlinNoiseParameters {

    public double persistence;
    public double frequency;
    public double amplitude;
    public int octaves;
    public int randomseed;

    public PerlinNoiseParameters(double persistence, double frequency, double amplitude, int octaves, int randomseed) {
        this.ChangeParameters(persistence, frequency, amplitude, octaves, randomseed);
    }

    public void ChangeParameters(double persistence, double frequency, double amplitude, int octaves, int randomseed) {
        this.persistence = persistence;
        this.frequency = frequency;
        this.amplitude = amplitude;
        this.octaves = octaves;
        this.randomseed = 2 + randomseed * randomseed;
    }
}

public class PerlinNoiseGenerator {

    PerlinNoiseParameters parameters;

    public PerlinNoiseGenerator() {
    }

    public PerlinNoiseGenerator(PerlinNoiseParameters parameters) {
        this.parameters = parameters;
    }

    public void ChangeParameters(double persistence, double frequency, double amplitude, int octaves, int randomseed) {
        parameters.ChangeParameters(persistence, frequency, amplitude, octaves, randomseed);
    }

    public void ChangeParameters(PerlinNoiseParameters newParams) {
        parameters = newParams;
    }

    public double get(double x, double y) {
        return parameters.amplitude * Total(x, y);
    }

    private double Total(double i, double j) {
        double t = 0.0f;
        double _amplitude = 1;
        double freq = parameters.frequency;

        for (int k = 0; k < parameters.octaves; k++) {
            t += GetValue(j * freq + parameters.randomseed, i * freq + parameters.randomseed)
                    * _amplitude;
            _amplitude *= parameters.persistence;
            freq *= 2;
        }

        return t;
    }

    private double GetValue(double x, double y) {
        int Xint = (int) x;
        int Yint = (int) y;

        double Xfrac = x - Xint;
        double Yfrac = y - Yint;

        double n01 = Noise(Xint - 1, Yint - 1);
        double n02 = Noise(Xint + 1, Yint - 1);
        double n03 = Noise(Xint - 1, Yint + 1);
        double n04 = Noise(Xint + 1, Yint + 1);
        double n05 = Noise(Xint - 1, Yint);
        double n06 = Noise(Xint + 1, Yint);
        double n07 = Noise(Xint, Yint - 1);
        double n08 = Noise(Xint, Yint + 1);
        double n09 = Noise(Xint, Yint);
        double n12 = Noise(Xint + 2, Yint - 1);
        double n14 = Noise(Xint + 2, Yint + 1);
        double n16 = Noise(Xint + 2, Yint);
        double n23 = Noise(Xint - 1, Yint + 2);
        double n24 = Noise(Xint + 1, Yint + 2);
        double n28 = Noise(Xint, Yint + 2);
        double n34 = Noise(Xint + 2, Yint + 2);

        double x0y0 = 0.0625 * (n01 + n02 + n03 + n04) + 0.1250
                * (n05 + n06 + n07 + n08) + 0.2500 * n09;

        double x1y0 = 0.0625 * (n07 + n12 + n08 + n14) + 0.1250
                * (n09 + n16 + n02 + n04) + 0.2500 * n06;

        double x0y1 = 0.0625 * (n05 + n06 + n23 + n24) + 0.1250
                * (n03 + n04 + n09 + n28) + 0.2500 * n08;

        double x1y1 = 0.0625 * (n09 + n16 + n28 + n34) + 0.1250
                * (n08 + n14 + n06 + n24) + 0.2500 * n04;

        double v1 = Interpolate(x0y0, x1y0, Xfrac);
        double v2 = Interpolate(x0y1, x1y1, Xfrac);

        double fin = Interpolate(v1, v2, Yfrac);

        return fin;
    }

    private double Interpolate(double x, double y, double a) {
        double negA = 1.0 - a;
        double negASqr = negA * negA;
        double fac1 = 3.0 * (negASqr) - 2.0 * (negASqr * negA);
        double aSqr = a * a;
        double fac2 = 3.0 * aSqr - 2.0 * (aSqr * a);

        return x * fac1 + y * fac2;
    }

    private double Noise(int x, int y) {
        int n = x + y * 57;
        n = (n << 13) ^ n;
        int t = (n * (n * n * 15731 + 789221) + 1376312589) & 0x7fffffff;
        return 1.0 - (double) t * 0.931322574615478515625e-9;
    }
}

PerlinNoiseGenerator.java

public class PerlinNoiseParameters {

    public double persistence;
    public double frequency;
    public double amplitude;
    public int octaves;
    public int randomseed;

    public PerlinNoiseParameters(double persistence, double frequency, double amplitude, int octaves, int randomseed) {
        this.ChangeParameters(persistence, frequency, amplitude, octaves, randomseed);
    }

    public void ChangeParameters(double persistence, double frequency, double amplitude, int octaves, int randomseed) {
        this.persistence = persistence;
        this.frequency = frequency;
        this.amplitude = amplitude;
        this.octaves = octaves;
        this.randomseed = 2 + randomseed * randomseed;
    }
}

public class PerlinNoiseGenerator {

    PerlinNoiseParameters parameters;

    public PerlinNoiseGenerator() {
    }

    public PerlinNoiseGenerator(PerlinNoiseParameters parameters) {
        this.parameters = parameters;
    }

    public void ChangeParameters(double persistence, double frequency, double amplitude, int octaves, int randomseed) {
        parameters.ChangeParameters(persistence, frequency, amplitude, octaves, randomseed);
    }

    public void ChangeParameters(PerlinNoiseParameters newParams) {
        parameters = newParams;
    }

    public double get(double x, double y) {
        return parameters.amplitude * Total(x, y);
    }

    private double Total(double i, double j) {
        double t = 0.0f;
        double _amplitude = 1;
        double freq = parameters.frequency;

        for (int k = 0; k < parameters.octaves; k++) {
            t += GetValue(j * freq + parameters.randomseed, i * freq + parameters.randomseed)
                    * _amplitude;
            _amplitude *= parameters.persistence;
            freq *= 2;
        }

        return t;
    }

    private double GetValue(double x, double y) {
        int Xint = (int) x;
        int Yint = (int) y;

        double Xfrac = x - Xint;
        double Yfrac = y - Yint;

        double n01 = Noise(Xint - 1, Yint - 1);
        double n02 = Noise(Xint + 1, Yint - 1);
        double n03 = Noise(Xint - 1, Yint + 1);
        double n04 = Noise(Xint + 1, Yint + 1);
        double n05 = Noise(Xint - 1, Yint);
        double n06 = Noise(Xint + 1, Yint);
        double n07 = Noise(Xint, Yint - 1);
        double n08 = Noise(Xint, Yint + 1);
        double n09 = Noise(Xint, Yint);
        double n12 = Noise(Xint + 2, Yint - 1);
        double n14 = Noise(Xint + 2, Yint + 1);
        double n16 = Noise(Xint + 2, Yint);
        double n23 = Noise(Xint - 1, Yint + 2);
        double n24 = Noise(Xint + 1, Yint + 2);
        double n28 = Noise(Xint, Yint + 2);
        double n34 = Noise(Xint + 2, Yint + 2);

        double x0y0 = 0.0625 * (n01 + n02 + n03 + n04) + 0.1250
                * (n05 + n06 + n07 + n08) + 0.2500 * n09;

        double x1y0 = 0.0625 * (n07 + n12 + n08 + n14) + 0.1250
                * (n09 + n16 + n02 + n04) + 0.2500 * n06;

        double x0y1 = 0.0625 * (n05 + n06 + n23 + n24) + 0.1250
                * (n03 + n04 + n09 + n28) + 0.2500 * n08;

        double x1y1 = 0.0625 * (n09 + n16 + n28 + n34) + 0.1250
                * (n08 + n14 + n06 + n24) + 0.2500 * n04;

        double v1 = Interpolate(x0y0, x1y0, Xfrac);
        double v2 = Interpolate(x0y1, x1y1, Xfrac);

        double fin = Interpolate(v1, v2, Yfrac);

        return fin;
    }

    private double Interpolate(double x, double y, double a) {
        double negA = 1.0 - a;
        double negASqr = negA * negA;
        double fac1 = 3.0 * (negASqr) - 2.0 * (negASqr * negA);
        double aSqr = a * a;
        double fac2 = 3.0 * aSqr - 2.0 * (aSqr * a);

        return x * fac1 + y * fac2;
    }

    private double Noise(int x, int y) {
        int n = x + y * 57;
        n = (n << 13) ^ n;
        int t = (n * (n * n * 15731 + 789221) + 1376312589) & 0x7fffffff;
        return 1.0 - (double) t * 0.931322574615478515625e-9;
    }
}

公共类PerlinNoiseGenerator{
PerlinNoiseParameters参数；
公共噪声发生器（）{
}
公共PerlinNoiseGenerator（PerlinNoiseParameters参数）{
此参数=参数；
}
公共参数（双持续、双频率、双振幅、整数倍频程、整数随机种子）{
参数。更改参数（持续性、频率、振幅、倍频程、随机种子）；
}
公共void ChangeParameters（PerlinNoiseParameters newParams）{
参数=新参数；
}
公共双get（双x，双y）{
返回参数。振幅*总计（x，y）；
}
私人双倍总计（双倍i，双倍j）{
双t=0.0f；
双振幅=1；
双频=参数。频率；
对于（int k=0；kn=（n这不是八度音阶和频率影响振幅的问题，至少不是直接影响振幅的问题。这是整数溢出的问题。因为您通过将随机种子添加到x和y坐标来引入随机种子（这是不寻常的，我认为这不是通常的实现）

随机种子可能是巨大的（可能接近整数的全尺寸），因为

因此，如果为j和i输入较大的值，则在调用时，在
GetValue（double x，double y）
处传递的双精度大于int的最大值

int Xint = (int) x;
int Yint = (int) y;

Xint和YInt不会像x和y那样（因为x和y可能是巨大的！）等等

可以比1大很多，允许返回不在-1和1之间的值

使用合理且较小的值，我使用代码的范围在-1和1之间（对于振幅1）



作为辅助，在java中，方法名通常是
methodName
，而不是
methodName

如果有用，请在此处找到perlin noise的其他java实现：
单个柏林噪声阶跃的范围为：

N是维度的数量。在你的例子中是2

倍频程、持续性和振幅加上：

double range = 0.0;
double _amplitude = parameters.;
for (int k = 0; k < parameters.octaves; k++) {
    range += sqrt(N/4) * _amplitude;
    _amplitude *= parameters.persistence;
}
return range;

双量程=0.0；
双振幅=参数。；
对于（int k=0；k

可能有某种方法可以作为一个数学表达式来实现这一点。涉及pow（），但我现在无法通过大脑来实现。
值得注意的是，柏林噪声的结果非常接近于0，因此即使[-10,10]是你的完整范围
-sqrt(N/4), sqrt(N/4)

double range = 0.0;
double _amplitude = parameters.;
for (int k = 0; k < parameters.octaves; k++) {
    range += sqrt(N/4) * _amplitude;
    _amplitude *= parameters.persistence;
}
return range;