/// <summary>
/// Recursively split node across its pivot axis.
/// </summary>
/// <param name="node">KDTreeNode to split</param>
/// <param name="depth">Current recursion depth, set lower if you get stack overflow</param>
/// <returns>True if split was a success or max_depth/max_node_size criterion met</returns>
bool BuildNode(KDNodeJeremyC node, int depth)
{
if (depth >= MaxNodeDepth)
{
return(true);
}
if (node.Indices.Count <= MaxNodeSize)
{
return(true);
}
foreach (var index in node.Indices)
{
VertexKDTree vertex = TreeVectors[index];
if (!node.IsBuilt)
{
node.Build();
}
KDNodeJeremyC child = node.GetSplitNode(vertex);
child.AddVertex(index, vertex);
}
// TODO: Do we need to check if either child is empty? Since we're calculating the split axis
// using raw data it's unlikely.
node.Clear();
node.ChildLeft.Build();
node.ChildRight.Build();
BuildNode(node.ChildLeft, depth + 1);
BuildNode(node.ChildRight, depth + 1);
return(true);
}
/// <summary>
/// Find closest point using an axis aligned search boundary
/// </summary>
/// <param name="node"></param>
/// <param name="point"></param>
/// <returns></returns>
VertexKDTree FindClosestPoint_Recursive(KDNodeJeremyC node, VertexKDTree vertex, BoundingBoxAxisAligned search_bounds, ref int nearest_index)
{
int tmp_index = -1;
if (node.IsLeaf)
{
tmp_index = -1;
VertexKDTree result = GetClosestVertexFromIndices(node.Indices, vertex, ref tmp_index);
if (result != null)
{
nearest_index = tmp_index;
return(result);
}
else
{
return(null);
}
}
tmp_index = -1;
KDNodeJeremyC near_child = node.GetSplitNode(vertex);
VertexKDTree retV = FindClosestPoint_Recursive(near_child, vertex, search_bounds, ref tmp_index);
//Edgar - TakenVector implementation - have to go one level up if vector is taken
float near_distance = float.MaxValue;
if (retV != null)
{
//near_distance = retV.Vector.Distance(vertex.Vector);
near_distance = retV.Vector.DistanceSquared(vertex.Vector);
nearest_index = tmp_index;
}
KDNodeJeremyC far_child = near_child.Sibling;
if (search_bounds != null && far_child.BoundingBox.Intersects(search_bounds))
{
VertexKDTree far_result = FindClosestPoint_Recursive(far_child, vertex, search_bounds, ref tmp_index);
//Edgar - TakenVector implementation - have to go one level up if vector is taken
if (far_result != null)
{
//float far_distance = far_result.Vector.Distance(vertex.Vector);
float far_distance = far_result.Vector.DistanceSquared(vertex.Vector);
if (far_distance < near_distance)
{
nearest_index = tmp_index;
retV = far_result;
}
}
}
if (retV == null)
{
}
return(retV);
}
/// <summary>
/// Find closest point using a centered bounding sphere
/// </summary>
/// <param name="node"></param>
/// <param name="vertex"></param>
/// <param name="search_bounds"></param>
/// <param name="nearest_index"></param>
/// <returns></returns>
VertexKDTree FindClosestPoint(KDNodeJeremyC node, VertexKDTree vertex, BoundingSphere search_bounds, ref int nearest_index)
{
int tmp_index = -1;
if (node.IsLeaf)
{
tmp_index = -1;
VertexKDTree result = GetClosestVertexFromIndices(node.Indices, vertex, ref tmp_index);
nearest_index = tmp_index;
return(result);
}
tmp_index = -1;
KDNodeJeremyC near_child = node.GetSplitNode(vertex);
VertexKDTree near_result = FindClosestPoint(near_child, vertex, search_bounds, ref tmp_index);
VertexKDTree ret = near_result;
//float near_distance = near_result.Vector.Distance(vertex.Vector);
float near_distance = near_result.Vector.DistanceSquared(vertex.Vector);
nearest_index = tmp_index;
KDNodeJeremyC far_child = near_child.Sibling;
if (far_child.BoundingBox.Intersects(search_bounds))
{
VertexKDTree far_result = FindClosestPoint(far_child, vertex, search_bounds, ref tmp_index);
float far_distance = far_result.Vector.DistanceSquared(vertex.Vector);
//float far_distance = far_result.Vector.Distance(vertex.Vector);
if (far_distance < near_distance)
{
nearest_index = tmp_index;
ret = far_result;
}
}
return(ret);
}