// If the number of points is less than the grainSize, the Run method
// simply finds the lower hull by going through all points from right to
// left, as described in the sequential convex hull algorithm.
// Otherwise we split the points in two and find the lower hulls
// concurrently.
// Finally we merge the two lower hulls and return the lower hull.
public override List <Point> Run()
{
int length = end - start + 1;
if (length < grainSize)
{
List <Point> L = new List <Point>(length);
int j = end;
while (j > end - 2 && j >= start)
{
L.Add(points[j]);
j--;
}
for (int i = end - 2; i >= start; i--)
{
while (L.Count > 1 && STL.Turn(L[L.Count - 2], L[L.Count - 1], points[i]) <= 0)
{
L.RemoveAt(L.Count - 1);
}
L.Add(points[i]);
}
return(L);
}
else
{
int middle = (length / 2) + start;
List <Point>[] res = Parallel.Gather(
new LowerHull(points, start, middle, grainSize),
new LowerHull(points, middle + 1, end, grainSize));
return(MergeLowerHulls(res[0], res[1]));
}
}
// Find the convex hull
public List <Point> ConvexHull(List <Point> points)
{
int length = points.Count;
if (length < 3)
{
return(points);
}
// Sort the points
points.Sort();
// Find upper hull
List <Point> U = new List <Point>(length);
U.Insert(0, points[0]);
U.Insert(1, points[1]);
for (int i = 2; i < length; i++)
{
while (U.Count > 1 && STL.Turn(U[U.Count - 2], U[U.Count - 1], points[i]) <= 0)
{
U.RemoveAt(U.Count - 1);
}
U.Add(points[i]);
}
// Find lower hull
List <Point> L = new List <Point>(length);
L.Insert(0, points[length - 1]);
L.Insert(1, points[length - 2]);
for (int j = length - 3; j >= 0; j--)
{
while (L.Count > 1 && STL.Turn(L[L.Count - 2], L[L.Count - 1], points[j]) <= 0)
{
L.RemoveAt(L.Count - 1);
}
L.Add(points[j]);
}
// Combine upper hull and lower hull
U.RemoveAt(U.Count - 1);
U.AddRange(L);
U.RemoveAt(U.Count - 1);
return(U);
}
// MergeLowerHulls merge two lower hulls in O(n) time.
private List <Point> MergeLowerHulls(List <Point> P1, List <Point> P2)
{
int lengthP1 = P1.Count;
int lengthP2 = P2.Count;
int currentP1Index = 0;
int currentP2Index = lengthP2 - 1;
bool done = false;
while (!done)
{
done = true;
if (currentP2Index > 0 && STL.Turn(P1[currentP1Index], P2[currentP2Index], P2[currentP2Index - 1]) > 0)
{
done = false;
currentP2Index--;
while (currentP2Index > 0 && !LowerTangent(P1[currentP1Index], P2[currentP2Index], P2[currentP2Index - 1], P2[currentP2Index + 1]))
{
currentP2Index--;
}
}
if (currentP1Index < lengthP1 - 1 && STL.Turn(P2[currentP2Index], P1[currentP1Index], P1[currentP1Index + 1]) < 0)
{
done = false;
currentP1Index++;
while (currentP1Index < lengthP1 - 1 && !LowerTangent(P2[currentP2Index], P1[currentP1Index], P1[currentP1Index + 1], P1[currentP1Index - 1]))
{
currentP1Index++;
}
}
}
List <Point> L = new List <Point>();
L.AddRange(P2.GetRange(0, currentP2Index + 1));
L.AddRange(P1.GetRange(currentP1Index, lengthP1 - currentP1Index));
return(L);
}
// If the number of points is less than the grainSize, the Run method
// simply finds the upper hull by going through all points from left to
// right, as described in the sequential convex hull algorithm.
// Otherwise we split the points in two and find the upper hulls
// concurrently.
// Finally we merge the two upper hulls and return the upper hull.
public override List <Point> Run()
{
int length = end - start + 1;
if (length < grainSize)
{
List <Point> U = new List <Point>(length);
int j = start;
while (j < start + 2 && j <= end)
{
U.Add(points[j]);
j++;
}
for (int i = start + 2; i <= end; i++)
{
while (U.Count > 1 && STL.Turn(U[U.Count - 2], U[U.Count - 1], points[i]) <= 0)
{
U.RemoveAt(U.Count - 1);
}
U.Add(points[i]);
}
return(U);
}
else
{
int middle = (length / 2) + start;
// The Parallel.Gather is similar to the Parallel.Run method. It runs the submitted
// tasks concurrently, gather the result from each task and returns array containing
// all results.
List <Point>[] res = Parallel.Gather(
new UpperHull(points, start, middle, grainSize),
new UpperHull(points, middle + 1, end, grainSize));
return(MergeUpperHulls(res[0], res[1]));
}
}
// The main algorithm is fairly simple. We simply
// sort the points and find the lower and upper hulls
// concurrently. Finally we combine them and return
// the points in the convex hull.
public List <Point> ConvexHull(List <Point> points)
{
int length = points.Count;
// Sort the points, see the STL class
// for more information on the
// parallel quicksort implementation.
STL.QuickSort(points, 10);
// Find Upper and Lower hull
// The Parallel.Gather is similar to the Parallel.Run method. It runs the submitted
// tasks concurrently, gather the result from each task and returns array containing
// all results.
List <Point>[] LU = Parallel.Gather(
new UpperHull(points, 0, length - 1, 10),
new LowerHull(points, 0, length - 1, 10));
// Combine Upper and Lower hull
LU[0].RemoveAt(LU[0].Count - 1);
LU[0].AddRange(LU[1]);
LU[0].RemoveAt(LU[0].Count - 1);
return(LU[0]);
}
// Returns true if the tangent p0p1 is the lower tangent.
// p0p1 is the tangent, p2 and p3 are the neighbors of p1.
// p2 is the next point in the lower hull and p2 is the previous point.
private bool LowerTangent(Point p0, Point p1, Point p2, Point p3)
{
return(!(STL.Turn(p0, p1, p2) < 0 && STL.Turn(p0, p1, p3) > 0));
}