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94 lines
3.0 KiB
C#
94 lines
3.0 KiB
C#
// ClassicalSharp copyright 2014-2016 UnknownShadow200 | Licensed under MIT
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// Source from http://mrl.nyu.edu/~perlin/noise/
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// Optimised form as we can always treat Z as being = 0.
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// Octave and combined noise based on:
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// https://github.com/UnknownShadow200/ClassicalSharp/wiki/Minecraft-Classic-map-generation-algorithm
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using System;
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namespace ClassicalSharp.Generator {
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public abstract class Noise {
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public abstract double Compute( double x, double y );
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}
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public sealed class ImprovedNoise : Noise {
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public ImprovedNoise( Random rnd ) {
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// shuffle randomly using fisher-yates
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for( int i = 0; i < 256; i++ )
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p[i] = (byte)i;
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for( int i = 0; i < 256; i++ ) {
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int j = rnd.Next( i, 256 );
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byte temp = p[i]; p[i] = p[j]; p[j] = temp;
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}
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for( int i = 0; i < 256; i++ )
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p[i + 256] = p[i];
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}
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public override double Compute( double x, double y ) {
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int xFloor = x >= 0 ? (int)x : (int)x - 1;
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int yFloor = y >= 0 ? (int)y : (int)y - 1;
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int X = xFloor & 0xFF, Y = yFloor & 0xFF;
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x -= xFloor; y -= yFloor;
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double u = x * x * x * (x * (x * 6 - 15) + 10); // Fade(x)
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double v = y * y * y * (y * (y * 6 - 15) + 10); // Fade(y)
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int A = p[X] + Y, B = p[X + 1] + Y;
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const int xFlags = 0x46552222, yFlags = 0x2222550A;
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int hash = (p[p[A]] & 0xF) << 1;
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double g22 = (((xFlags >> hash) & 3) - 1) * x + (((yFlags >> hash) & 3) - 1) * y; // Grad(p[p[A], x, y)
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hash = (p[p[B]] & 0xF) << 1;
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double g12 = (((xFlags >> hash) & 3) - 1) * (x - 1) + (((yFlags >> hash) & 3) - 1) * y; // Grad(p[p[B], x - 1, y)
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double c1 = g22 + u * (g12 - g22);
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hash = (p[p[A + 1]] & 0xF) << 1;
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double g21 = (((xFlags >> hash) & 3) - 1) * x + (((yFlags >> hash) & 3) - 1) * (y - 1); // Grad(p[p[A + 1], x, y - 1)
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hash = (p[p[B + 1]] & 0xF) << 1;
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double g11 = (((xFlags >> hash) & 3) - 1) * (x - 1) + (((yFlags >> hash) & 3) - 1) * (y - 1); // Grad(p[p[B + 1], x - 1, y - 1)
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double c2 = g21 + u * (g11 - g21);
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return c1 + v * (c2 - c1);
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}
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byte[] p = new byte[512];
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}
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public sealed class OctaveNoise : Noise {
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readonly ImprovedNoise[] baseNoise;
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public OctaveNoise( int octaves, Random rnd ) {
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baseNoise = new ImprovedNoise[octaves];
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for( int i = 0; i < octaves; i++ )
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baseNoise[i] = new ImprovedNoise( rnd );
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}
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public override double Compute( double x, double y ) {
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double amplitude = 1, frequency = 1;
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double sum = 0;
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for( int i = 0; i < baseNoise.Length; i++ ) {
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sum += baseNoise[i].Compute( x * frequency, y * frequency ) * amplitude;
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amplitude *= 2;
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frequency /= 2;
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}
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return sum;
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}
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}
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public sealed class CombinedNoise : Noise {
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readonly Noise noise1, noise2;
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public CombinedNoise( Noise noise1, Noise noise2 ) {
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this.noise1 = noise1;
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this.noise2 = noise2;
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}
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public override double Compute( double x, double y ) {
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double offset = noise2.Compute( x, y );
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return noise1.Compute( x + offset, y );
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}
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}
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}
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