2014-05-30 22:15:51 +01:00
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// stb_perlin.h - v0.2 - perlin noise
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2014-05-25 18:18:03 +01:00
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// public domain single-file C implementation by Sean Barrett
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//
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2015-08-01 19:54:57 +01:00
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// LICENSE
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//
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2016-02-10 22:48:59 +00:00
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// This software is dual-licensed to the public domain and under the following
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// license: you are granted a perpetual, irrevocable license to copy, modify,
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// publish, and distribute this file as you see fit.
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2015-08-01 19:54:57 +01:00
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//
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//
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2014-05-25 18:18:03 +01:00
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// to create the implementation,
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// #define STB_PERLIN_IMPLEMENTATION
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// in *one* C/CPP file that includes this file.
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// Documentation:
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//
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// float stb_perlin_noise3( float x,
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// float y,
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// float z,
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// int x_wrap=0,
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// int y_wrap=0,
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// int z_wrap=0)
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//
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// This function computes a random value at the coordinate (x,y,z).
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// Adjacent random values are continuous but the noise fluctuates
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// its randomness with period 1, i.e. takes on wholly unrelated values
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// at integer points. Specifically, this implements Ken Perlin's
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// revised noise function from 2002.
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//
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// The "wrap" parameters can be used to create wraparound noise that
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// wraps at powers of two. The numbers MUST be powers of two. Specify
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// 0 to mean "don't care". (The noise always wraps every 256 due
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// details of the implementation, even if you ask for larger or no
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// wrapping.)
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#ifdef __cplusplus
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extern "C" float stb_perlin_noise3(float x, float y, float z, int x_wrap=0, int y_wrap=0, int z_wrap=0);
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#else
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extern float stb_perlin_noise3(float x, float y, float z, int x_wrap, int y_wrap, int z_wrap);
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#endif
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#ifdef STB_PERLIN_IMPLEMENTATION
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#include <math.h> // floor()
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// not same permutation table as Perlin's reference to avoid copyright issues;
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// Perlin's table can be found at http://mrl.nyu.edu/~perlin/noise/
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// @OPTIMIZE: should this be unsigned char instead of int for cache?
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static int stb__perlin_randtab[512] =
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{
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23, 125, 161, 52, 103, 117, 70, 37, 247, 101, 203, 169, 124, 126, 44, 123,
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152, 238, 145, 45, 171, 114, 253, 10, 192, 136, 4, 157, 249, 30, 35, 72,
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175, 63, 77, 90, 181, 16, 96, 111, 133, 104, 75, 162, 93, 56, 66, 240,
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8, 50, 84, 229, 49, 210, 173, 239, 141, 1, 87, 18, 2, 198, 143, 57,
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225, 160, 58, 217, 168, 206, 245, 204, 199, 6, 73, 60, 20, 230, 211, 233,
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94, 200, 88, 9, 74, 155, 33, 15, 219, 130, 226, 202, 83, 236, 42, 172,
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165, 218, 55, 222, 46, 107, 98, 154, 109, 67, 196, 178, 127, 158, 13, 243,
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65, 79, 166, 248, 25, 224, 115, 80, 68, 51, 184, 128, 232, 208, 151, 122,
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26, 212, 105, 43, 179, 213, 235, 148, 146, 89, 14, 195, 28, 78, 112, 76,
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250, 47, 24, 251, 140, 108, 186, 190, 228, 170, 183, 139, 39, 188, 244, 246,
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132, 48, 119, 144, 180, 138, 134, 193, 82, 182, 120, 121, 86, 220, 209, 3,
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91, 241, 149, 85, 205, 150, 113, 216, 31, 100, 41, 164, 177, 214, 153, 231,
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38, 71, 185, 174, 97, 201, 29, 95, 7, 92, 54, 254, 191, 118, 34, 221,
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131, 11, 163, 99, 234, 81, 227, 147, 156, 176, 17, 142, 69, 12, 110, 62,
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27, 255, 0, 194, 59, 116, 242, 252, 19, 21, 187, 53, 207, 129, 64, 135,
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61, 40, 167, 237, 102, 223, 106, 159, 197, 189, 215, 137, 36, 32, 22, 5,
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// and a second copy so we don't need an extra mask or static initializer
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23, 125, 161, 52, 103, 117, 70, 37, 247, 101, 203, 169, 124, 126, 44, 123,
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152, 238, 145, 45, 171, 114, 253, 10, 192, 136, 4, 157, 249, 30, 35, 72,
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175, 63, 77, 90, 181, 16, 96, 111, 133, 104, 75, 162, 93, 56, 66, 240,
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8, 50, 84, 229, 49, 210, 173, 239, 141, 1, 87, 18, 2, 198, 143, 57,
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225, 160, 58, 217, 168, 206, 245, 204, 199, 6, 73, 60, 20, 230, 211, 233,
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94, 200, 88, 9, 74, 155, 33, 15, 219, 130, 226, 202, 83, 236, 42, 172,
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165, 218, 55, 222, 46, 107, 98, 154, 109, 67, 196, 178, 127, 158, 13, 243,
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65, 79, 166, 248, 25, 224, 115, 80, 68, 51, 184, 128, 232, 208, 151, 122,
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26, 212, 105, 43, 179, 213, 235, 148, 146, 89, 14, 195, 28, 78, 112, 76,
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250, 47, 24, 251, 140, 108, 186, 190, 228, 170, 183, 139, 39, 188, 244, 246,
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132, 48, 119, 144, 180, 138, 134, 193, 82, 182, 120, 121, 86, 220, 209, 3,
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91, 241, 149, 85, 205, 150, 113, 216, 31, 100, 41, 164, 177, 214, 153, 231,
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38, 71, 185, 174, 97, 201, 29, 95, 7, 92, 54, 254, 191, 118, 34, 221,
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131, 11, 163, 99, 234, 81, 227, 147, 156, 176, 17, 142, 69, 12, 110, 62,
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27, 255, 0, 194, 59, 116, 242, 252, 19, 21, 187, 53, 207, 129, 64, 135,
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61, 40, 167, 237, 102, 223, 106, 159, 197, 189, 215, 137, 36, 32, 22, 5,
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};
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static float stb__perlin_lerp(float a, float b, float t)
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{
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return a + (b-a) * t;
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}
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// different grad function from Perlin's, but easy to modify to match reference
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static float stb__perlin_grad(int hash, float x, float y, float z)
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{
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static float basis[12][4] =
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{
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{ 1, 1, 0 },
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{ -1, 1, 0 },
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{ 1,-1, 0 },
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{ -1,-1, 0 },
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{ 1, 0, 1 },
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{ -1, 0, 1 },
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{ 1, 0,-1 },
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{ -1, 0,-1 },
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{ 0, 1, 1 },
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{ 0,-1, 1 },
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{ 0, 1,-1 },
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{ 0,-1,-1 },
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};
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// perlin's gradient has 12 cases so some get used 1/16th of the time
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// and some 2/16ths. We reduce bias by changing those fractions
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// to 5/16ths and 6/16ths, and the same 4 cases get the extra weight.
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static unsigned char indices[64] =
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{
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0,1,2,3,4,5,6,7,8,9,10,11,
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0,9,1,11,
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0,1,2,3,4,5,6,7,8,9,10,11,
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0,1,2,3,4,5,6,7,8,9,10,11,
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0,1,2,3,4,5,6,7,8,9,10,11,
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0,1,2,3,4,5,6,7,8,9,10,11,
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};
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// if you use reference permutation table, change 63 below to 15 to match reference
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float *grad = basis[indices[hash & 63]];
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return grad[0]*x + grad[1]*y + grad[2]*z;
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}
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float stb_perlin_noise3(float x, float y, float z, int x_wrap, int y_wrap, int z_wrap)
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{
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float u,v,w;
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float n000,n001,n010,n011,n100,n101,n110,n111;
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float n00,n01,n10,n11;
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float n0,n1;
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unsigned int x_mask = (x_wrap-1) & 255;
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unsigned int y_mask = (y_wrap-1) & 255;
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unsigned int z_mask = (z_wrap-1) & 255;
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int px = (int) floor(x);
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int py = (int) floor(y);
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int pz = (int) floor(z);
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int x0 = px & x_mask, x1 = (px+1) & x_mask;
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int y0 = py & y_mask, y1 = (py+1) & y_mask;
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int z0 = pz & z_mask, z1 = (pz+1) & z_mask;
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int r0,r1, r00,r01,r10,r11;
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#define stb__perlin_ease(a) (((a*6-15)*a + 10) * a * a * a)
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x -= px; u = stb__perlin_ease(x);
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y -= py; v = stb__perlin_ease(y);
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z -= pz; w = stb__perlin_ease(z);
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r0 = stb__perlin_randtab[x0];
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r1 = stb__perlin_randtab[x1];
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r00 = stb__perlin_randtab[r0+y0];
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r01 = stb__perlin_randtab[r0+y1];
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r10 = stb__perlin_randtab[r1+y0];
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r11 = stb__perlin_randtab[r1+y1];
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n000 = stb__perlin_grad(stb__perlin_randtab[r00+z0], x , y , z );
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n001 = stb__perlin_grad(stb__perlin_randtab[r00+z1], x , y , z-1 );
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n010 = stb__perlin_grad(stb__perlin_randtab[r01+z0], x , y-1, z );
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n011 = stb__perlin_grad(stb__perlin_randtab[r01+z1], x , y-1, z-1 );
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n100 = stb__perlin_grad(stb__perlin_randtab[r10+z0], x-1, y , z );
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n101 = stb__perlin_grad(stb__perlin_randtab[r10+z1], x-1, y , z-1 );
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n110 = stb__perlin_grad(stb__perlin_randtab[r11+z0], x-1, y-1, z );
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n111 = stb__perlin_grad(stb__perlin_randtab[r11+z1], x-1, y-1, z-1 );
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n00 = stb__perlin_lerp(n000,n001,w);
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n01 = stb__perlin_lerp(n010,n011,w);
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n10 = stb__perlin_lerp(n100,n101,w);
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n11 = stb__perlin_lerp(n110,n111,w);
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n0 = stb__perlin_lerp(n00,n01,v);
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n1 = stb__perlin_lerp(n10,n11,v);
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return stb__perlin_lerp(n0,n1,u);
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}
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#endif // STB_PERLIN_IMPLEMENTATION
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