def delaunay_from_points(points, polygon=None, polygons=None):
"""Computes the delaunay triangulation for a list of points.
Parameters:
points (sequence of tuple): XYZ coordinates of the original points.
polygon (sequence of tuples): list of ordered points describing the outer boundary (optional)
polygons (list of sequences of tuples): list of polygons (ordered points describing internal holes (optional)
Returns:
list of lists: list of faces (face = list of vertex indices as integers)
References:
Sloan, S. W. (1987) A fast algorithm for constructing Delaunay triangulations in the plane
Example:
.. plot::
:include-source:
import compas
from compas.datastructures.mesh import Mesh
from compas.datastructures.mesh.algorithms import delaunay_from_points
mesh = Mesh.from_obj(compas.get_data('faces.obj'))
vertices = [mesh.vertex_coordinates(key) for key in mesh]
faces = delaunay_from_points(vertices)
delaunay = Mesh.from_vertices_and_faces(vertices, faces)
delaunay.plot(
vertexsize=0.1
)
"""
def super_triangle(coords):
centpt = centroid_points(coords)
bbpts = bounding_box(coords)
dis = distance_point_point(bbpts[0], bbpts[2])
dis = dis * 300
v1 = (0 * dis, 2 * dis, 0)
v2 = (1.73205 * dis, -1.0000000000001 * dis, 0
) # due to numerical issues
v3 = (-1.73205 * dis, -1 * dis, 0)
pt1 = add_vectors(centpt, v1)
pt2 = add_vectors(centpt, v2)
pt3 = add_vectors(centpt, v3)
return pt1, pt2, pt3
mesh = Mesh()
# to avoid numerical issues for perfectly structured point sets
tiny = 1e-8
pts = [(point[0] + random.uniform(-tiny, tiny),
point[1] + random.uniform(-tiny, tiny), 0.0) for point in points]
# create super triangle
pt1, pt2, pt3 = super_triangle(points)
# add super triangle vertices to mesh
n = len(points)
super_keys = n, n + 1, n + 2
mesh.add_vertex(super_keys[0], {'x': pt1[0], 'y': pt1[1], 'z': pt1[2]})
mesh.add_vertex(super_keys[1], {'x': pt2[0], 'y': pt2[1], 'z': pt2[2]})
mesh.add_vertex(super_keys[2], {'x': pt3[0], 'y': pt3[1], 'z': pt3[2]})
mesh.add_face(super_keys)
# iterate over points
for i, pt in enumerate(pts):
key = i
# check in which triangle this point falls
for fkey in list(mesh.faces()):
# abc = mesh.face_coordinates(fkey) #This is slower
# This is faster:
keya, keyb, keyc = mesh.face_vertices(fkey)
dicta = mesh.vertex[keya]
dictb = mesh.vertex[keyb]
dictc = mesh.vertex[keyc]
a = [dicta['x'], dicta['y']]
b = [dictb['x'], dictb['y']]
c = [dictc['x'], dictc['y']]
if is_point_in_triangle_2d(pt, [a, b, c]):
# generate 3 new triangles (faces) and delete surrounding triangle
newtris = mesh.insert_vertex(fkey, key=key, xyz=pt)
break
while newtris:
fkey = newtris.pop()
# get opposite_face
keys = mesh.face_vertices(fkey)
s = list(set(keys) - set([key]))
u, v = s[0], s[1]
fkey1 = mesh.halfedge[u][v]
if fkey1 != fkey:
fkey_op, u, v = fkey1, u, v
else:
fkey_op, u, v = mesh.halfedge[v][u], u, v
if fkey_op:
keya, keyb, keyc = mesh.face_vertices(fkey_op)
dicta = mesh.vertex[keya]
a = [dicta['x'], dicta['y']]
dictb = mesh.vertex[keyb]
b = [dictb['x'], dictb['y']]
dictc = mesh.vertex[keyc]
c = [dictc['x'], dictc['y']]
circle = circle_from_points_2d(a, b, c)
if is_point_in_circle_2d(pt, circle):
fkey, fkey_op = swap_edge_trimesh(mesh, u, v)
newtris.append(fkey)
newtris.append(fkey_op)
# Delete faces adjacent to supertriangle
for key in super_keys:
mesh.remove_vertex(key)
# Delete faces outside of boundary
if polygon:
for fkey in list(mesh.faces()):
cent = mesh.face_centroid(fkey)
if not is_point_in_polygon_2d(cent, polygon):
mesh.delete_face(fkey)
# Delete faces inside of inside boundaries
if polygons:
for polygon in polygons:
for fkey in list(mesh.faces()):
cent = mesh.face_centroid(fkey)
if is_point_in_polygon_2d(cent, polygon):
mesh.delete_face(fkey)
return [[int(key) for key in mesh.face_vertices(fkey, True)]
for fkey in mesh.faces()]
def delaunay_from_points_2(points, boundary=None, holes=None, tiny=1e-12):
"""Computes the delaunay triangulation for a list of points.
Difference from compas version: faces outside the boundaries are detected based on the position of their circumcircle.
Parameters
----------
points : sequence of tuple
XYZ coordinates of the original points.
boundary : sequence of tuples
list of ordered points describing the outer boundary (optional)
holes : list of sequences of tuples
list of polygons (ordered points describing internal holes (optional)
Returns
-------
list
The faces of the triangulation.
Each face is a triplet of indices referring to the list of point coordinates.
Notes
-----
For more info, see [1]_.
References
----------
.. [1] Sloan, S. W., 1987 *A fast algorithm for constructing Delaunay triangulations in the plane*
Advances in Engineering Software 9(1): 34-55, 1978.
Example
-------
.. plot::
:include-source:
from compas.geometry import pointcloud_xy
from compas.datastructures import Mesh
from compas.topology import delaunay_from_points
from compas.plotters import MeshPlotter
points = pointcloud_xy(10, (0, 10))
faces = delaunay_from_points(points)
delaunay = Mesh.from_vertices_and_faces(points, faces)
plotter = MeshPlotter(delaunay)
plotter.draw_vertices(radius=0.1)
plotter.draw_faces()
plotter.show()
"""
from compas.datastructures import Mesh
def super_triangle(coords):
centpt = centroid_points(coords)
bbpts = bounding_box(coords)
dis = distance_point_point(bbpts[0], bbpts[2])
dis = dis * 300
v1 = (0 * dis, 2 * dis, 0)
v2 = (1.73205 * dis, -1.0000000000001 * dis, 0
) # due to numerical issues
v3 = (-1.73205 * dis, -1 * dis, 0)
pt1 = add_vectors(centpt, v1)
pt2 = add_vectors(centpt, v2)
pt3 = add_vectors(centpt, v3)
return pt1, pt2, pt3
mesh = Mesh()
# to avoid numerical issues for perfectly structured point sets
points = [(point[0] + random.uniform(-tiny, tiny),
point[1] + random.uniform(-tiny, tiny), 0.0)
for point in points]
# create super triangle
pt1, pt2, pt3 = super_triangle(points)
# add super triangle vertices to mesh
n = len(points)
super_keys = n, n + 1, n + 2
mesh.add_vertex(super_keys[0], {'x': pt1[0], 'y': pt1[1], 'z': pt1[2]})
mesh.add_vertex(super_keys[1], {'x': pt2[0], 'y': pt2[1], 'z': pt2[2]})
mesh.add_vertex(super_keys[2], {'x': pt3[0], 'y': pt3[1], 'z': pt3[2]})
mesh.add_face(super_keys)
# iterate over points
for i, pt in enumerate(points):
key = i
# newtris should be intialised here
# check in which triangle this point falls
for fkey in list(mesh.faces()):
# abc = mesh.face_coordinates(fkey) #This is slower
# This is faster:
keya, keyb, keyc = mesh.face_vertices(fkey)
dicta = mesh.vertex[keya]
dictb = mesh.vertex[keyb]
dictc = mesh.vertex[keyc]
a = [dicta['x'], dicta['y']]
b = [dictb['x'], dictb['y']]
c = [dictc['x'], dictc['y']]
if is_point_in_triangle_xy(pt, [a, b, c], True):
# generate 3 new triangles (faces) and delete surrounding triangle
key, newtris = mesh.insert_vertex(fkey,
key=key,
xyz=pt,
return_fkeys=True)
break
while newtris:
fkey = newtris.pop()
# get opposite_face
keys = mesh.face_vertices(fkey)
s = list(set(keys) - set([key]))
u, v = s[0], s[1]
fkey1 = mesh.halfedge[u][v]
if fkey1 != fkey:
fkey_op, u, v = fkey1, u, v
else:
fkey_op, u, v = mesh.halfedge[v][u], u, v
if fkey_op:
keya, keyb, keyc = mesh.face_vertices(fkey_op)
dicta = mesh.vertex[keya]
a = [dicta['x'], dicta['y']]
dictb = mesh.vertex[keyb]
b = [dictb['x'], dictb['y']]
dictc = mesh.vertex[keyc]
c = [dictc['x'], dictc['y']]
circle = circle_from_points_xy(a, b, c)
if is_point_in_circle_xy(pt, circle):
fkey, fkey_op = mesh.swap_edge_tri(u, v)
newtris.append(fkey)
newtris.append(fkey_op)
# Delete faces adjacent to supertriangle
for key in super_keys:
mesh.delete_vertex(key)
# Delete faces outside of boundary
if boundary:
for fkey in list(mesh.faces()):
#centroid = mesh.face_centroid(fkey)
centre, radius, normal = face_circle(mesh, fkey)
if not is_point_in_polygon_xy(centre, boundary):
mesh.delete_face(fkey)
# Delete faces inside of inside boundaries
if holes:
for polygon in holes:
for fkey in list(mesh.faces()):
#centroid = mesh.face_centroid(fkey)
centre, radius, normal = face_circle(mesh, fkey)
if is_point_in_polygon_xy(centre, polygon):
mesh.delete_face(fkey)
return [mesh.face_vertices(fkey) for fkey in mesh.faces()]
