public static void GenerateNoiseMapTexture(GraphicsDevice Device, int width, int height, ref Texture2D noiseTexture, int octaves)
{
var data = new float[width * height];
/// track min and max noise value. Used to normalize the result to the 0 to 1.0 range.
var min = float.MaxValue;
var max = float.MinValue;
/// rebuild the permutation table to get a different noise pattern.
/// Leave this out if you want to play with changing the number of octaves while
/// maintaining the same overall pattern.
Noise2d.Reseed();
var frequency = 0.5f;
var amplitude = 1f;
for (var octave = 0; octave < octaves; octave++)
{
/// parallel loop - easy and fast.
Parallel.For(0
, width * height
, (offset) =>
{
var i = offset % width;
var j = offset / width;
var noise = Noise2d.Noise(i * frequency * 1f / width, j * frequency * 1f / height);
noise = data[j * width + i] += noise * amplitude;
min = Math.Min(min, noise);
max = Math.Max(max, noise);
}
);
frequency *= 2;
amplitude /= 2;
}
if (noiseTexture != null && (noiseTexture.Width != width || noiseTexture.Height != height))
{
noiseTexture.Dispose();
noiseTexture = null;
}
if (noiseTexture == null)
{
noiseTexture = new Texture2D(Device, width, height, false, SurfaceFormat.Color);
}
var colors = data.Select(
(f) =>
{
var norm = (f - min) / (max - min);
return(new Microsoft.Xna.Framework.Color(norm, norm, norm, 1));
}
).ToArray();
noiseTexture.SetData(colors);
}
public static float[,] GenerateNoiseMap(int width, int height, int octaves, float frequency = 0.5f, float amplitude = 1f)
{
var data = new float[width * height];
/// Track min and max noise value. Used to normalize the result to the 0 to 1.0 range.
var min = float.MaxValue;
var max = float.MinValue;
/// Rebuild the permutation table to get a different noise pattern.
/// Leave this out if you want to play with changing the number of octaves while
/// maintaining the same overall pattern.
//Noise2d.Reseed();
for (var octave = 0; octave < octaves; octave++)
{
/// parallel loop - easy and fast.
Parallel.For(0
, width * height
, (offset) =>
{
var i = offset % width;
var j = offset / width;
var noise = Noise2d.Noise(i * frequency * 1f / width, j * frequency * 1f / height);
noise = data[j * width + i] += noise * amplitude;
min = Math.Min(min, noise);
max = Math.Max(max, noise);
}
);
frequency *= 2;
amplitude /= 2;
}
var r = new float[width, height];
var c = 0;
for (var y = 0; y < height; y++)
{
for (var x = 0; x < width; x++)
{
var norm = (data[c] - min) / (max - min);
r[x, y] = norm;
//r[x, y] = data[c];
c += 1;
}
}
return(r);
}
//public static float NoiseN(float x, float y)
//{
// var n = Noise(x, y);
// var min = float.MaxValue;
// var max = float.MinValue;
// var norm = (n - min) / (max - min);
// return norm;
//}
public static float GenerateNoisePoint(int x, int y, int width, int height, int octaves, float frequency = 0.5f, float amplitude = 1f)
{
var min = float.MaxValue;
var max = float.MinValue;
float noise = 0;
for (var octave = 0; octave < octaves; octave++)
{
var n = Noise2d.Noise(x * frequency * 1f / width, y * frequency * 1f / height);
noise += n * amplitude;
min = Math.Min(min, noise);
max = Math.Max(max, noise);
frequency *= 2;
amplitude /= 2;
}
var norm = (noise - min) / (max - min);
return(norm);
}
