Perlin noise: Difference between revisions
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Either by using a dedicated library or by implementing the algorithm, show that the Perlin noise (as defined in 2002 in the java implementation below) of the point in 3D-space with coordinates 3.14, 42, 7 is 0.13691995878400012. |
Either by using a dedicated library or by implementing the algorithm, show that the Perlin noise (as defined in 2002 in the java implementation below) of the point in 3D-space with coordinates 3.14, 42, 7 is 0.13691995878400012. |
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=={{header|D}}== |
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<lang d>import std.stdio, std.math; |
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struct PerlinNoise { |
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private static double fade(in double t) pure nothrow { |
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return t ^^ 3 * (t * (t * 6 - 15) + 10); |
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} |
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private static double lerp(in double t, in double a, in double b) |
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pure nothrow { |
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return a + t * (b - a); |
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} |
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private static double grad(in ubyte hash, |
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in double x, in double y, in double z) |
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pure nothrow { |
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// Convert lo 4 bits of hash code into 12 gradient directions. |
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immutable h = hash & 0xF; |
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immutable double u = (h < 8) ? x : y, |
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v = (h < 4) ? y : (h == 12 || h == 14 ? x : z); |
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return ((h & 1) == 0 ? u : -u) + ((h & 2) == 0 ? v : -v); |
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} |
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static immutable ubyte[512] p; |
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pure nothrow static this() { |
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static immutable ubyte[256] permutation = [151,160,137,91,90, |
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15,131,13,201,95,96,53,194,233,7,225,140,36,103,30,69,142, |
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8,99,37,240,21,10,23,190,6,148,247,120,234,75,0,26,197,62, |
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94,252,219,203,117,35,11,32,57,177,33,88,237,149,56,87,174, |
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20,125,136,171,168,68,175,74,165,71,134,139,48,27,166,77, |
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146,158,231,83,111,229,122,60,211,133,230,220,105,92,41,55, |
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46,245,40,244,102,143,54,65,25,63,161,1,216,80,73,209,76, |
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132,187,208,89,18,169,200,196,135,130,116,188,159,86,164, |
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100,109,198,173,186,3,64,52,217,226,250,124,123,5,202,38, |
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147,118,126,255,82,85,212,207,206,59,227,47,16,58,17,182, |
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189,28,42,223,183,170,213,119,248,152,2,44,154,163,70,221, |
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153,101,155,167,43,172,9,129,22,39,253,19,98,108,110,79, |
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113,224,232,178,185,112,104,218,246,97,228,251,34,242,193, |
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238,210,144,12,191,179,162,241,81,51,145,235,249,14,239, |
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107,49,192,214,31,181,199,106,157,184,84,204,176,115,121, |
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50,45,127,4,150,254,138,236,205,93,222,114,67,29,24,72, |
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243,141,128,195,78,66,215,61,156,180]; |
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// Two copies of permutation. |
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p[0 .. permutation.length] = permutation[]; |
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p[permutation.length .. $] = permutation[]; |
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} |
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static double opCall(in double x0, in double y0, in double z0) |
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pure nothrow { |
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// Find unit cube that contains point. |
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immutable ubyte X = cast(int)x0.floor & 0xFF, |
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Y = cast(int)y0.floor & 0xFF, |
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Z = cast(int)z0.floor & 0xFF; |
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// Find relative x,y,z of point in cube. |
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immutable x = x0 - x0.floor, |
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y = y0 - y0.floor, |
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z = z0 - z0.floor; |
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// Compute fade curves for each of x,y,z. |
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immutable u = fade(x), |
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v = fade(y), |
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w = fade(z); |
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// Hash coordinates of the 8 cube corners. |
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immutable A = p[X ] + Y, |
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AA = p[A] + Z, |
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AB = p[A + 1] + Z, |
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B = p[X + 1] + Y, |
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BA = p[B] + Z, |
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BB = p[B + 1] + Z; |
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// And add blended results from 8 corners of cube. |
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return lerp(w, lerp(v, lerp(u, grad(p[AA ], x , y , z ), |
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grad(p[BA ], x-1, y , z )), |
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lerp(u, grad(p[AB ], x , y-1, z ), |
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grad(p[BB ], x-1, y-1, z ))), |
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lerp(v, lerp(u, grad(p[AA+1], x , y , z-1), |
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grad(p[BA+1], x-1, y , z-1)), |
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lerp(u, grad(p[AB+1], x , y-1, z-1), |
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grad(p[BB+1], x-1, y-1, z-1)))); |
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} |
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} |
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void main() { |
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writefln("%1.17f", PerlinNoise(3.14, 42, 7)); |
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/* |
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// Generate a demo image using the Gray Scale task module. |
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import grayscale_image; |
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enum N = 200; |
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auto im = new Image!Gray(N, N); |
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foreach (immutable y; 0 .. N) |
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foreach (immutable x; 0 .. N) { |
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immutable p = PerlinNoise(x / 30.0, y / 30.0, 0.1); |
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im[x, y] = Gray(cast(ubyte)(p * 256)); |
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} |
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im.savePGM("perlin_noise.pgm"); |
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*/ |
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}</lang> |
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{{out}} |
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<pre>0.13691995878400012</pre> |
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=={{header|Java}}== |
=={{header|Java}}== |