add mono c# (using dotnet9.0 from https://github.com/dotnet/runtime), add ECS (entt), add some c# code, add fastNoise
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112
ExampleApp/Src/Noise.cs
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112
ExampleApp/Src/Noise.cs
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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using Prism;
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namespace Example
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{
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public static class Noise
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{
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public static float[,] GenerateNoiseMap(int mapWidth, int mapHeight, float scale)
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{
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float[,] noiseMap = new float[mapWidth, mapHeight];
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if (scale <= 0)
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scale = 0.0001f;
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for (int y = 0; y < mapHeight; y++)
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{
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for (int x = 0; x < mapWidth; x++)
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{
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float sampleX = x / scale;
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float sampleY = y / scale;
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float perlinValue = Prism.Noise.PerlinNoise(sampleX, sampleY);
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noiseMap[x, y] = perlinValue;
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}
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}
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return noiseMap;
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}
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public static float InverseLerp(float min, float max, float value)
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{
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if (Math.Abs(max - min) < 0.000001f) return min;
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return (value - min) / (max - min);
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}
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public static float[,] GenerateNoiseMap(int mapWidth, int mapHeight, int seed, float scale, int octaves, float persistance, float lacunarity, Vec2 offset)
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{
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float[,] noiseMap = new float[mapWidth, mapHeight];
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System.Random prng = new System.Random(seed);
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Vec2[] octaveOffsets = new Vec2[octaves];
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for (int i = 0; i < octaves; i++)
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{
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float offsetX = prng.Next(-100000, 100000) + offset.X;
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float offsetY = prng.Next(-100000, 100000) + offset.Y;
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octaveOffsets[i] = new Vec2(offsetX, offsetY);
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}
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if (scale <= 0)
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{
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scale = 0.0001f;
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}
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float maxNoiseHeight = float.MinValue;
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float minNoiseHeight = float.MaxValue;
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float halfWidth = mapWidth / 2f;
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float halfHeight = mapHeight / 2f;
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for (int y = 0; y < mapHeight; y++)
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{
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for (int x = 0; x < mapWidth; x++)
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{
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float amplitude = 1;
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float frequency = 1;
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float noiseHeight = 0;
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for (int i = 0; i < octaves; i++)
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{
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float sampleX = (x - halfWidth) / scale * frequency + octaveOffsets[i].X;
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float sampleY = (y - halfHeight) / scale * frequency + octaveOffsets[i].Y;
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float perlinValue = Prism.Noise.PerlinNoise(sampleX, sampleY);// * 2 - 1; // 0->1 // -1 -> 1
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noiseHeight += perlinValue * amplitude;
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amplitude *= persistance;
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frequency *= lacunarity;
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}
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if (noiseHeight > maxNoiseHeight)
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{
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maxNoiseHeight = noiseHeight;
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}
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else if (noiseHeight < minNoiseHeight)
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{
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minNoiseHeight = noiseHeight;
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}
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noiseMap[x, y] = noiseHeight;
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}
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}
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for (int y = 0; y < mapHeight; y++)
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{
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for (int x = 0; x < mapWidth; x++)
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{
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noiseMap[x, y] = InverseLerp(minNoiseHeight, maxNoiseHeight, noiseMap[x, y]);
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}
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}
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return noiseMap;
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}
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}
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}
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