KDTree Utilities (mathutils.kdtree)#
Generic 3-dimensional kd-tree to perform spatial searches.
import mathutils
# create a kd-tree from a mesh
from bpy import context
obj = context.object
mesh = obj.data
size = len(mesh.vertices)
kd = mathutils.kdtree.KDTree(size)
for i, v in enumerate(mesh.vertices):
kd.insert(v.co, i)
kd.balance()
# Find the closest point to the center
co_find = (0.0, 0.0, 0.0)
co, index, dist = kd.find(co_find)
print("Close to center:", co, index, dist)
# 3d cursor relative to the object data
co_find = obj.matrix_world.inverted() @ context.scene.cursor.location
# Find the closest 10 points to the 3d cursor
print("Close 10 points")
for (co, index, dist) in kd.find_n(co_find, 10):
print(" ", co, index, dist)
# Find points within a radius of the 3d cursor
print("Close points within 0.5 distance")
for (co, index, dist) in kd.find_range(co_find, 0.5):
print(" ", co, index, dist)
- class mathutils.kdtree.KDTree#
KdTree(size) -> new kd-tree initialized to hold
size
items.Note
KDTree.balance
must have been called before using any of thefind
methods.- balance()#
Balance the tree.
Note
This builds the entire tree, avoid calling after each insertion.
- find(co, filter=None)#
Find nearest point to
co
.- Parameters:
co (float triplet) – 3d coordinates.
filter (callable) – function which takes an index and returns True for indices to include in the search.
- Returns:
Returns (
Vector
, index, distance).- Return type:
tuple
- find_n(co, n)#
Find nearest
n
points toco
.- Parameters:
co (float triplet) – 3d coordinates.
n (int) – Number of points to find.
- Returns:
Returns a list of tuples (
Vector
, index, distance).- Return type:
list
- find_range(co, radius)#
Find all points within
radius
ofco
.- Parameters:
co (float triplet) – 3d coordinates.
radius (float) – Distance to search for points.
- Returns:
Returns a list of tuples (
Vector
, index, distance).- Return type:
list
- insert(co, index)#
Insert a point into the KDTree.
- Parameters:
co (float triplet) – Point 3d position.
index (int) – The index of the point.