132 lines
3.8 KiB
C#
132 lines
3.8 KiB
C#
using System;
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namespace Utils
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{
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public class PerlinNoise : Utils.Singleton<PerlinNoise>
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{
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private int[] _p; // 混淆表
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private const int DefaultSeed = 0; // 默认种子
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public PerlinNoise()
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{
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Initialize(DefaultSeed);
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}
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// 初始化混淆表
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private void Initialize(int seed)
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{
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_p = new int[512]; // 混淆表加倍以方便使用
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var permutation = new int[256];
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var random = new Random(seed);
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// 填充数组为0-255
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for (var i = 0; i < 256; i++) permutation[i] = i;
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// 使用Fisher-Yates算法打乱数组
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for (var i = 0; i < 256; i++)
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{
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var swapIndex = random.Next(256);
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var temp = permutation[i];
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permutation[i] = permutation[swapIndex];
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permutation[swapIndex] = temp;
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}
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// 将打乱后的数组复制两次，生成512个元素的混淆表
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for (var i = 0; i < 256; i++)
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{
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_p[i] = permutation[i];
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_p[i + 256] = permutation[i];
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}
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}
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// 重新指定种子
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public void Reinitialize(int seed)
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{
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Initialize(seed);
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}
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// 平滑函数 (6t^5 - 15t^4 + 10t^3)
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private static double Fade(double t)
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{
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return t * t * t * (t * (t * 6 - 15) + 10);
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}
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// 线性插值
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private static double Lerp(double t, double a, double b)
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{
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return a + t * (b - a);
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}
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// 计算梯度向量和距离向量的点积
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private static double Grad(int hash, double x, double y, double z)
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{
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return (hash & 0xF) switch // 取hash值的最后4位
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{
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0x0 => x + y,
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0x1 => -x + y,
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0x2 => x - y,
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0x3 => -x - y,
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0x4 => x + z,
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0x5 => -x + z,
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0x6 => x - z,
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0x7 => -x - z,
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0x8 => y + z,
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0x9 => -y + z,
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0xA => y - z,
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0xB => -y - z,
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0xC => y + x,
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0xD => -y + x,
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0xE => y - x,
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0xF => -y - x,
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_ => 0
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};
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}
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/// <summary>
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/// 为给定的(x, y, z)坐标生成3D Perlin噪声。
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/// 输出值通常在-1到1之间。
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/// </summary>
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public double Noise(double x, double y=0, double z = 0)
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{
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var X = (int)Math.Floor(x) & 255;
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var Y = (int)Math.Floor(y) & 255;
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var Z = (int)Math.Floor(z) & 255;
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x -= Math.Floor(x);
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y -= Math.Floor(y);
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z -= Math.Floor(z);
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var u = Fade(x);
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var v = Fade(y);
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var w = Fade(z);
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var A = _p[X] + Y;
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var AA = _p[A] + Z;
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var AB = _p[A + 1] + Z;
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var B = _p[X + 1] + Y;
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var BA = _p[B] + Z;
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var BB = _p[B + 1] + Z;
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var H000 = _p[AA];
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var H100 = _p[BA];
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var H010 = _p[AB];
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var H110 = _p[BB];
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var H001 = _p[AA + 1];
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var H101 = _p[BA + 1];
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var H011 = _p[AB + 1];
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var H111 = _p[BB + 1];
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double x0, x1, y0, y1;
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x0 = Lerp(u, Grad(H000, x, y, z), Grad(H100, x - 1, y, z));
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x1 = Lerp(u, Grad(H010, x, y - 1, z), Grad(H110, x - 1, y - 1, z));
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y0 = Lerp(v, x0, x1);
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x0 = Lerp(u, Grad(H001, x, y, z - 1), Grad(H101, x - 1, y, z - 1));
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x1 = Lerp(u, Grad(H011, x, y - 1, z - 1), Grad(H111, x - 1, y - 1, z - 1));
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y1 = Lerp(v, x0, x1);
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return Lerp(w, y0, y1);
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}
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}
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} |