stb/stb_perlin.h

// stb_perlin.h - v0.2 - perlin noise
// public domain single-file C implementation by Sean Barrett
//
// to create the implementation,
//     #define STB_PERLIN_IMPLEMENTATION
// in *one* C/CPP file that includes this file.


// Documentation:
//
// float  stb_perlin_noise3( float x,
//                           float y,
//                           float z,
//                           int   x_wrap=0,
//                           int   y_wrap=0,
//                           int   z_wrap=0)
//
// This function computes a random value at the coordinate (x,y,z).
// Adjacent random values are continuous but the noise fluctuates
// its randomness with period 1, i.e. takes on wholly unrelated values
// at integer points. Specifically, this implements Ken Perlin's
// revised noise function from 2002.
//
// The "wrap" parameters can be used to create wraparound noise that
// wraps at powers of two. The numbers MUST be powers of two. Specify
// 0 to mean "don't care". (The noise always wraps every 256 due
// details of the implementation, even if you ask for larger or no
// wrapping.)


#ifdef __cplusplus
extern "C" float stb_perlin_noise3(float x, float y, float z, int x_wrap=0, int y_wrap=0, int z_wrap=0);
#else
extern float stb_perlin_noise3(float x, float y, float z, int x_wrap, int y_wrap, int z_wrap);
#endif

#ifdef STB_PERLIN_IMPLEMENTATION

#include <math.h> // floor()

// not same permutation table as Perlin's reference to avoid copyright issues;
// Perlin's table can be found at http://mrl.nyu.edu/~perlin/noise/
// @OPTIMIZE: should this be unsigned char instead of int for cache?
static int stb__perlin_randtab[512] =
{
   23, 125, 161, 52, 103, 117, 70, 37, 247, 101, 203, 169, 124, 126, 44, 123, 
   152, 238, 145, 45, 171, 114, 253, 10, 192, 136, 4, 157, 249, 30, 35, 72, 
   175, 63, 77, 90, 181, 16, 96, 111, 133, 104, 75, 162, 93, 56, 66, 240, 
   8, 50, 84, 229, 49, 210, 173, 239, 141, 1, 87, 18, 2, 198, 143, 57, 
   225, 160, 58, 217, 168, 206, 245, 204, 199, 6, 73, 60, 20, 230, 211, 233, 
   94, 200, 88, 9, 74, 155, 33, 15, 219, 130, 226, 202, 83, 236, 42, 172, 
   165, 218, 55, 222, 46, 107, 98, 154, 109, 67, 196, 178, 127, 158, 13, 243, 
   65, 79, 166, 248, 25, 224, 115, 80, 68, 51, 184, 128, 232, 208, 151, 122, 
   26, 212, 105, 43, 179, 213, 235, 148, 146, 89, 14, 195, 28, 78, 112, 76, 
   250, 47, 24, 251, 140, 108, 186, 190, 228, 170, 183, 139, 39, 188, 244, 246, 
   132, 48, 119, 144, 180, 138, 134, 193, 82, 182, 120, 121, 86, 220, 209, 3, 
   91, 241, 149, 85, 205, 150, 113, 216, 31, 100, 41, 164, 177, 214, 153, 231, 
   38, 71, 185, 174, 97, 201, 29, 95, 7, 92, 54, 254, 191, 118, 34, 221, 
   131, 11, 163, 99, 234, 81, 227, 147, 156, 176, 17, 142, 69, 12, 110, 62, 
   27, 255, 0, 194, 59, 116, 242, 252, 19, 21, 187, 53, 207, 129, 64, 135, 
   61, 40, 167, 237, 102, 223, 106, 159, 197, 189, 215, 137, 36, 32, 22, 5,  

   // and a second copy so we don't need an extra mask or static initializer
   23, 125, 161, 52, 103, 117, 70, 37, 247, 101, 203, 169, 124, 126, 44, 123, 
   152, 238, 145, 45, 171, 114, 253, 10, 192, 136, 4, 157, 249, 30, 35, 72, 
   175, 63, 77, 90, 181, 16, 96, 111, 133, 104, 75, 162, 93, 56, 66, 240, 
   8, 50, 84, 229, 49, 210, 173, 239, 141, 1, 87, 18, 2, 198, 143, 57, 
   225, 160, 58, 217, 168, 206, 245, 204, 199, 6, 73, 60, 20, 230, 211, 233, 
   94, 200, 88, 9, 74, 155, 33, 15, 219, 130, 226, 202, 83, 236, 42, 172, 
   165, 218, 55, 222, 46, 107, 98, 154, 109, 67, 196, 178, 127, 158, 13, 243, 
   65, 79, 166, 248, 25, 224, 115, 80, 68, 51, 184, 128, 232, 208, 151, 122, 
   26, 212, 105, 43, 179, 213, 235, 148, 146, 89, 14, 195, 28, 78, 112, 76, 
   250, 47, 24, 251, 140, 108, 186, 190, 228, 170, 183, 139, 39, 188, 244, 246, 
   132, 48, 119, 144, 180, 138, 134, 193, 82, 182, 120, 121, 86, 220, 209, 3, 
   91, 241, 149, 85, 205, 150, 113, 216, 31, 100, 41, 164, 177, 214, 153, 231, 
   38, 71, 185, 174, 97, 201, 29, 95, 7, 92, 54, 254, 191, 118, 34, 221, 
   131, 11, 163, 99, 234, 81, 227, 147, 156, 176, 17, 142, 69, 12, 110, 62, 
   27, 255, 0, 194, 59, 116, 242, 252, 19, 21, 187, 53, 207, 129, 64, 135, 
   61, 40, 167, 237, 102, 223, 106, 159, 197, 189, 215, 137, 36, 32, 22, 5,  
};

static float stb__perlin_lerp(float a, float b, float t)
{
   return a + (b-a) * t;
}

// different grad function from Perlin's, but easy to modify to match reference
static float stb__perlin_grad(int hash, float x, float y, float z)
{
   static float basis[12][4] =
   {
      {  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 },
   };

   // perlin's gradient has 12 cases so some get used 1/16th of the time
   // and some 2/16ths. We reduce bias by changing those fractions
   // to 5/16ths and 6/16ths, and the same 4 cases get the extra weight.
   static unsigned char indices[64] =
   {
      0,1,2,3,4,5,6,7,8,9,10,11,
      0,9,1,11,
      0,1,2,3,4,5,6,7,8,9,10,11,
      0,1,2,3,4,5,6,7,8,9,10,11,
      0,1,2,3,4,5,6,7,8,9,10,11,
      0,1,2,3,4,5,6,7,8,9,10,11,
   };

   // if you use reference permutation table, change 63 below to 15 to match reference
   float *grad = basis[indices[hash & 63]];
   return grad[0]*x + grad[1]*y + grad[2]*z;
}

float stb_perlin_noise3(float x, float y, float z, int x_wrap, int y_wrap, int z_wrap)
{
   float u,v,w;
   float n000,n001,n010,n011,n100,n101,n110,n111;
   float n00,n01,n10,n11;
   float n0,n1;

   unsigned int x_mask = (x_wrap-1) & 255;
   unsigned int y_mask = (y_wrap-1) & 255;
   unsigned int z_mask = (z_wrap-1) & 255;
   int px = (int) floor(x);
   int py = (int) floor(y);
   int pz = (int) floor(z);
   int x0 = px & x_mask, x1 = (px+1) & x_mask;
   int y0 = py & y_mask, y1 = (py+1) & y_mask;
   int z0 = pz & z_mask, z1 = (pz+1) & z_mask;
   int r0,r1, r00,r01,r10,r11;

   #define stb__perlin_ease(a)   (((a*6-15)*a + 10) * a * a * a)

   x -= px; u = stb__perlin_ease(x);
   y -= py; v = stb__perlin_ease(y);
   z -= pz; w = stb__perlin_ease(z);

   r0 = stb__perlin_randtab[x0];
   r1 = stb__perlin_randtab[x1];

   r00 = stb__perlin_randtab[r0+y0];
   r01 = stb__perlin_randtab[r0+y1];
   r10 = stb__perlin_randtab[r1+y0];
   r11 = stb__perlin_randtab[r1+y1];

   n000 = stb__perlin_grad(stb__perlin_randtab[r00+z0], x  , y  , z   );
   n001 = stb__perlin_grad(stb__perlin_randtab[r00+z1], x  , y  , z-1 );
   n010 = stb__perlin_grad(stb__perlin_randtab[r01+z0], x  , y-1, z   );
   n011 = stb__perlin_grad(stb__perlin_randtab[r01+z1], x  , y-1, z-1 );
   n100 = stb__perlin_grad(stb__perlin_randtab[r10+z0], x-1, y  , z   );
   n101 = stb__perlin_grad(stb__perlin_randtab[r10+z1], x-1, y  , z-1 );
   n110 = stb__perlin_grad(stb__perlin_randtab[r11+z0], x-1, y-1, z   );
   n111 = stb__perlin_grad(stb__perlin_randtab[r11+z1], x-1, y-1, z-1 );

   n00 = stb__perlin_lerp(n000,n001,w);
   n01 = stb__perlin_lerp(n010,n011,w);
   n10 = stb__perlin_lerp(n100,n101,w);
   n11 = stb__perlin_lerp(n110,n111,w);

   n0 = stb__perlin_lerp(n00,n01,v);
   n1 = stb__perlin_lerp(n10,n11,v);

   return stb__perlin_lerp(n0,n1,u);
}
#endif  // STB_PERLIN_IMPLEMENTATION