public Mountains(int seed, int width, int height, int minMountainRadius, int maxMountainRadius, int minMuntainDistance, int numSamplesBeforeAbort) : base(seed, width, height)
{
noiseMap = new float[width * height];
float side = minMountainRadius / (float)Math.Sqrt(2);
List <Vector2> points = PoissonSample.GeneratePoints(Random, minMuntainDistance, new Vector2(width, height), numSamplesBeforeAbort);
for (int i = 0; i < points.Count; i++)
{
int cx = (int)points[i].X;
int cy = (int)points[i].Y;
int rnd = Random.Next(minMountainRadius, maxMountainRadius);
int buildStartX = Math.Max(0, cx - rnd);
int buildEndX = Math.Min(width, cx + rnd);
int buildStartY = Math.Max(0, cy - rnd);
int buildEndY = Math.Min(height, cy + rnd);
int center = Math.Min((buildStartX + buildEndX) / 2 - buildStartX, (buildStartY + buildEndY) / 2 - buildStartY);
float MountainHeight = (float)Random.NextDouble();
float h = 0f;
for (int c = 0; c < center; c++)
{
h += MountainHeight / center * 2;
for (int y = buildStartY + c; y < buildEndY - c; y++)
{
for (int x = buildStartX + c; x < buildEndX - c; x++)
{
noiseMap[y * width + x] = h;
}
}
}
}
}
public Planet(int id, int seed, GraphicsDeviceManager graphics, PlanetTypes planetType, PlanetSizes planetSize)
{
Id = id;
PlanetType = planetType;
PlanetSize = planetSize;
ChunksWidth = PlanetSizeDImensions[(int)planetSize][0];
ChunksHeight = PlanetSizeDImensions[(int)planetSize][1];
CellsWidth = ChunksWidth * CHUNK_WIDTH;
CellsHeight = ChunksHeight * CHUNK_HEIGHT;
noiseGenerator = new NoiseGenerator(planetType, seed, CellsWidth, CellsHeight);
Map = new Map.Map(id, seed, ChunksWidth, ChunksHeight, noiseGenerator, graphics, planetType);
List <Vector2> greens = PoissonSample.GeneratePoints(new Random(seed), 15, new Vector2(CellsWidth, CellsHeight));
List <Vector2> blues = PoissonSample.GeneratePoints(new Random(seed), 20, new Vector2(CellsWidth, CellsHeight));
List <Vector2> reds = PoissonSample.GeneratePoints(new Random(seed), 25, new Vector2(CellsWidth, CellsHeight));
for (int i = 0; i < greens.Count; i++)
{
Structures.Add(new Ore(GetCellAtPosition(greens[i]), Ore.OreTypes.Green));
}
for (int i = 0; i < blues.Count; i++)
{
Structures.Add(new Ore(GetCellAtPosition(blues[i]), Ore.OreTypes.Blue));
}
for (int i = 0; i < reds.Count; i++)
{
Structures.Add(new Ore(GetCellAtPosition(reds[i]), Ore.OreTypes.Red));
}
}
public MergeCandidate(PoissonSample s, int src)
{
sample = s;
sourceDist = src;
}
private static void MakeProgressive(ref List<PoissonSample> distribution)
{
if (distribution.Count < 2) return;
distribution.Sort(); // PossionSample implements IComparable
#region fix equal-ranking samples by random interleaving
Random random = new Random();
for (int i = 0; i < distribution.Count; i++)
{
int rankingFixStart = i;
float ranking = distribution[i].ranking;
while (i + 1 < distribution.Count && distribution[i + 1].ranking == ranking)
{
i++;
}
if (rankingFixStart < i)
{
int fixLength = i - rankingFixStart + 1;
int[] shuffle = new int[fixLength];
for (int j = 0; j < fixLength; j++) shuffle[j] = rankingFixStart + j;
for (int j = 0; j < fixLength; j++)
{
int a = random.Next(fixLength);
int b = random.Next(fixLength);
if (a == b) continue;
int aux = shuffle[a];
shuffle[a] = shuffle[b];
shuffle[b] = aux;
}
PoissonSample[] interleavedSamples = new PoissonSample[fixLength];
for (int j = 0; j < fixLength; j++)
{
interleavedSamples[j] = distribution[shuffle[j]];
}
for (int j = 0; j < fixLength; j++)
{
distribution[rankingFixStart + j] = interleavedSamples[j];
}
}
}
for (int i = 0; i < distribution.Count; i++) distribution[i].ranking = (float)i / distribution.Count;
#endregion
#region fix seam-neighbors
const float alpha = 0.5f;
for (int i = 2; i < distribution.Count - 1; i++)
{
int j = i;
float threshold = alpha * (float)Math.Sqrt(i);
for (; j < distribution.Count - 1; j++)
{
float d = float.MaxValue;
for (int k = 0; k < i; k++)
{
float dist = distribution[j].DistSquared(distribution[k]);
if (dist < d)
{
d = dist;
}
}
if ((float)Math.Sqrt(d) > threshold) break;
}
if (j != i)
{
PoissonSample aux = distribution[i];
distribution[i] = distribution[j];
distribution[j] = aux;
}
}
#endregion
}
public MergeCandidate(PoissonSample s, int src)
{
sample = s;
sourceDist = src;
}
private static void MakeProgressive(ref List <PoissonSample> distribution)
{
if (distribution.Count < 2)
{
return;
}
distribution.Sort(); // PossionSample implements IComparable
#region fix equal-ranking samples by random interleaving
Random random = new Random();
for (int i = 0; i < distribution.Count; i++)
{
int rankingFixStart = i;
float ranking = distribution[i].ranking;
while (i + 1 < distribution.Count && distribution[i + 1].ranking == ranking)
{
i++;
}
if (rankingFixStart < i)
{
int fixLength = i - rankingFixStart + 1;
int[] shuffle = new int[fixLength];
for (int j = 0; j < fixLength; j++)
{
shuffle[j] = rankingFixStart + j;
}
for (int j = 0; j < fixLength; j++)
{
int a = random.Next(fixLength);
int b = random.Next(fixLength);
if (a == b)
{
continue;
}
int aux = shuffle[a];
shuffle[a] = shuffle[b];
shuffle[b] = aux;
}
PoissonSample[] interleavedSamples = new PoissonSample[fixLength];
for (int j = 0; j < fixLength; j++)
{
interleavedSamples[j] = distribution[shuffle[j]];
}
for (int j = 0; j < fixLength; j++)
{
distribution[rankingFixStart + j] = interleavedSamples[j];
}
}
}
for (int i = 0; i < distribution.Count; i++)
{
distribution[i].ranking = (float)i / distribution.Count;
}
#endregion
#region fix seam-neighbors
const float alpha = 0.5f;
for (int i = 2; i < distribution.Count - 1; i++)
{
int j = i;
float threshold = alpha * (float)Math.Sqrt(i);
for (; j < distribution.Count - 1; j++)
{
float d = float.MaxValue;
for (int k = 0; k < i; k++)
{
float dist = distribution[j].DistSquared(distribution[k]);
if (dist < d)
{
d = dist;
}
}
if ((float)Math.Sqrt(d) > threshold)
{
break;
}
}
if (j != i)
{
PoissonSample aux = distribution[i];
distribution[i] = distribution[j];
distribution[j] = aux;
}
}
#endregion
}
