internal void AddSample(Sample_t s)
{
int hashX = (int)(s.x * HashCells);
int hashY = (int)(s.y * HashCells);
lock (stipplingData) // prevent the collection from being modified while we may be baking a preview
{
stipplingData.samples.Add(s);
}
sampleHash[hashX, hashY].Add(s);
}
internal List<Sample_t> GetConflictSamples(Sample_t s)
{
List<Sample_t> conflict = new List<Sample_t>();
double radius = 0;
for (int c = 0; c < NumClasses; ++c) radius = Math.Max(radius, MinDistance((int)(s.x * OutputImageWidth), (int)(s.y * OutputImageHeight), s.c, c));
double cellSize = 1.0 / HashCells;
int cellSpan = (int)Math.Ceiling(radius / cellSize);
int hashX = (int)(s.x * HashCells);
int hashY = (int)(s.y * HashCells);
for (int j = Math.Max(0, hashY - cellSpan); j <= Math.Min(HashCells - 1, hashY + cellSpan); ++j)
for (int i = Math.Max(0, hashX - cellSpan); i <= Math.Min(HashCells - 1, hashX + cellSpan); ++i)
foreach (Sample_t s_ in sampleHash[i, j])
{
double dx = s.x - s_.x;
double dy = s.y - s_.y;
double d = Math.Sqrt(dx * dx + dy * dy);
double radiusS = MinDistance((int)(s.x * OutputImageWidth), (int)(s.y * OutputImageHeight), s.c, s_.c);
double radiusS_ = MinDistance((int)(s_.x * OutputImageWidth), (int)(s_.y * OutputImageHeight), s_.c, s.c);
if (d <= (radiusS + radiusS_) * 0.5) conflict.Add(s_);
}
return conflict;
}
private bool Removable(List<Sample_t> conflict, Sample_t s, float[] fillRate)
{
int sx = (int)(s.x * imageWidth);
int sy = (int)(s.y * imageHeight);
foreach (Sample_t s_ in conflict)
{
int sx_ = (int)(s_.x * imageWidth);
int sy_ = (int)(s_.y * imageHeight);
if (r[sx_, sy_, s_.c, s_.c] >= r[sx, sy, s.c, s.c] ||
fillRate[s_.c] < fillRate[s.c]) return false;
}
return true;
}
private bool AcceptSample(Sample_t s)
{
int sx = (int)(s.x * imageWidth);
int sy = (int)(s.y * imageHeight);
double radius = MinDistance(sx, sy, s.c, s.c);
List<Sample_t> nearby = NearbySamples(s.x, s.y, radius);
return nearby.Count == 0;
}
private bool AcceptSample(Sample_t s)
{
double radius = 0;
for (int c = 0; c < numClasses; ++c) radius = Math.Max(radius, r[(int)(s.x * imageWidth), (int)(s.y * imageHeight), s.c, c]);
int sx = (int)(s.x * imageWidth);
int sy = (int)(s.y * imageHeight);
List<Sample_t> nearby = NearbySamples(s.x, s.y, radius);
foreach (Sample_t s_ in nearby)
{
double dx = s_.x - s.x;
double dy = s_.y - s.y;
double d = Math.Sqrt(dx * dx + dy * dy);
if (d <= r[sx, sy, s.c, s_.c]) return false;
}
return true;
}