/// <summary>
/// returns the target (tree) points found for the input (source) points
/// </summary>
/// <param name="source"></param>
/// <returns></returns>
public PointCloud FindClosestPointCloud_Parallel(PointCloud source)
{
this.source = source;
this.ResetTaken();
VertexKDTree[] resultArray = new VertexKDTree[source.Count];
//shuffle points for the "Taken" algorithm
PointCloud sourceShuffled;
if (this.TakenAlgorithm)
{
sourceShuffled = source.Clone();
sourceShuffled.SetDefaultIndices();
sourceShuffled = PointCloud.Shuffle(sourceShuffled);
}
else
{
sourceShuffled = source;
}
int nearest_index = 0;
float nearest_distance = 0f;
System.Threading.Tasks.Parallel.For(0, source.Count, i =>
//for (int i = 0; i < sourceShuffled.Count; i++)
{
VertexKDTree vSource = new VertexKDTree(sourceShuffled.Vectors[i], i);
VertexKDTree vTargetFound = FindClosestPoint(vSource, ref nearest_distance, ref nearest_index);
//resultArray[i] = vTargetFound.Clone();
resultArray[i] = vTargetFound;
});
List <VertexKDTree> resultList = new List <VertexKDTree>(resultArray);
result = PointCloud.FromListVertexKDTree(resultList);
//shuffle back
PointCloud pcResultShuffledBack;
if (this.TakenAlgorithm)
{
pcResultShuffledBack = result.Clone();
for (int i = 0; i < pcResultShuffledBack.Count; i++)
{
//pcResultShuffled.Vectors[i] = pcResult.Vectors[Convert.ToInt32(sourceShuffled.Indices[i])];
pcResultShuffledBack.Vectors[Convert.ToInt32(sourceShuffled.Indices[i])] = result.Vectors[i];
}
}
else
{
pcResultShuffledBack = result;
}
//this.MeanDistance = PointCloud.MeanDistance(source, pcResultShuffledBack);
return(pcResultShuffledBack);
}
