private bool[,] GenerateWalkabilityMatrix(int xSize, int ySize)
{
var walkability = new bool[xSize, ySize];
float perlinScale = .5f;
for (int x = 0; x < xSize; x++)
{
for (int y = 0; y < ySize; y++)
{
float xScaled = x * perlinScale;
float yScaled = y * perlinScale;
float threshold = _density == GridDensity.Sparse ? 0.6f : _density == GridDensity.Medium ? 0.55f : 0.5f;
float value = _noise.NoiseComplex(xScaled, yScaled);
if (value < threshold)
{
walkability[x, y] = true;
}
}
}
if (_hasWalls)
{
for (int x = 0; x < xSize; x++)
{
for (int y = 0; y < ySize; y++)
{
float xScaled = x * perlinScale * 0.08f;
float yScaled = y * perlinScale;
float value = _noise.Noise(xScaled, yScaled);
float value2 = _noise.Noise(yScaled + 3, xScaled + 42);
if (value < 0.3f)
{
walkability[x, y] = false;
}
if (value2 < 0.3f)
{
walkability[y, x] = false;
}
}
}
}
return(walkability);
}
public void Noise2D_Test()
{
var noise = new Noise2D(333);
float [,] values = new float[100, 100];
for (int i = 0; i < 100; i++)
{
for (int j = 0; j < 100; j++)
{
values[i, j] = noise.Noise(i, j);
}
}
IDictionary <float, int> widmo = new SortedDictionary <float, int>();
for (int i = 0; i < 100; i++)
{
for (int j = 0; j < 100; j++)
{
float val = values[i, j];
string value = val < 0.2f ? " " : val < 0.4f ? "." : val < 0.6f ? ":" : val < 0.8f ? "|" : "#";
//Console.Write(value);
float przedzial = (float)Math.Ceiling(val * 10) / 10f;
if (!widmo.ContainsKey(przedzial))
{
widmo[przedzial] = 1;
}
else
{
++widmo[przedzial];
}
}
//Console.Write("\r\n");
}
foreach (KeyValuePair <float, int> keyValuePair in widmo)
{
Console.WriteLine(keyValuePair.Key + ": " + keyValuePair.Value);
}
}
