我正在尝试适应在stackoverflow上发现的this code,以创建具有有限边界的voronoi单元。
但是我的问题是我不知道如何获取与给定点关联的区域。这是在普通的Voronoi中使用point_region
方法完成的,但由于区域已更改,因此在这里不起作用。
我正在使用的数据点是:
points = array([[289255.176 , 921667.461 ],
[289296.31699, 921687.13826],
[289463.30305, 921770.12504],
[289725.08002, 921905.75745],
[289960.48198, 922099.46056],
[290106.98928, 922361.79529],
[289255.184 , 921646.244 ],
[289307.48677, 921627.05485],
[289500.80493, 921555.50067],
[289825.14532, 921435.65147],
[290141.79326, 921322.77935],
[290454.91721, 921211.09355],
[289255.187 , 921635.627 ],
[289327.07776, 921558.85263],
[289565.21795, 921298.17707],
[289875.40176, 920978.013 ],
[290192.86361, 920656.82017],
[289255.185 , 921630.386 ],
[289318.54181, 921453.18492],
[289421.06861, 921167.57934],
[289565.42462, 920770.1386 ],
[289701.83141, 920376.28627],
[289833.6501 , 919990.66467]])
vor = Voronoi(points)
min_x = vor.min_bound[0] - 100
max_x = vor.max_bound[0] + 100
min_y = vor.min_bound[1] - 100
max_y = vor.max_bound[1] + 100
regions, vertices, pts = voronoi_finite_polygons_2d(vor)
答案 0 :(得分:0)
此代码使用多边形中的点分析为您提供与给定的有限 Voronoi区域关联的点。让我们假设我们希望找到与vor_regions列表上第二个Voronoi地区相关的点。
vor = Voronoi(points)
vor_regions = vor.regions
vor_vertices = vor.vertices
from shapely.geometry import MultiPoint
from shapely.geometry import Point
region = vor_regions[1]
coords = tuple(map(tuple, vor_vertices[region]))
poly = MultiPoint(coords).convex_hull
for i in range(0,len(points)):
pt = Point(tuple(map(tuple, points[i:i+1])))
if poly.contains(pt) == True:
print('The input region is ')
print(region)
print('Index of the associated point in the vor_vertices list is '+str(i))
print('The coordinates of the associated point is ')
print(pt)
输出:
The input region is
[6, 2, 1, 0, 5]
Index of the associated point in the vor_vertices list is 4
The coordinates of the associated point is
POINT (289960.48198 922099.46056)