我有一个由七个重叠的圆和椭圆组成的集群，我想把它们合并成一个形状，但当我运行cascaded_union()时，会出现错误：
ValueError: No Shapely geometry can be created from null value
以下是我目前所写的内容：
import numpy as np
import matplotlib.pyplot as plt
from shapely.geometry import Polygon
from shapely.ops import cascaded_union
x = [-1.86203523, -1.91255406, -2.03575331, -2.16247874, -2.22159676, -2.17992322,
-2.06085035, -1.93121615, -1.86378696, -1.89641216, -1.838166, -1.88166833,
-1.98775658, -2.09688125, -2.14778844, -2.1119029, -2.00936791, -1.89773847,
-1.83967446, -1.86776838, -1.55136662, -1.60188546, -1.72508471, -1.85181013,
-1.91092815, -1.86925461, -1.75018174, -1.62054755, -1.55311836, -1.58574355,
-1.29187795, -1.33538028, -1.44146853, -1.5505932, -1.60150039, -1.56561485,
-1.46307986, -1.35145041, -1.2933864, -1.32148032, -1.07173048, -1.11382951,
-1.21649555, -1.32210007, -1.37136508, -1.33663714, -1.23740975, -1.12938125,
-1.07319027, -1.10037793, -1.87340556, -1.79563936, -1.5818673, -1.35208399,
-1.23527147, -1.29699902, -1.50261769, -1.73670954, -1.86787402, -1.82248584,
-1.98180156, -1.89591919, -1.66476691, -1.4180952, -1.29436593, -1.36303087,
-1.58554696, -1.83701142, -1.97627207, -1.92515911]
y = [0.80459679, 0.9296353, 0.98448714, 0.93836285, 0.81715295, 0.68889502,
0.62558285, 0.66275485, 0.77954562, 0.91039814, 0.63006386, 0.73773591,
0.78496944, 0.74525131, 0.6408761, 0.53043177, 0.47591296, 0.50792219,
0.60849203, 0.72117057, 0.6981317, 0.82317021, 0.87802205, 0.83189777,
0.71068786, 0.58242993, 0.51911776, 0.55628977, 0.67308054, 0.80393305,
0.60213859, 0.70981064, 0.75704417, 0.71732605, 0.61295084, 0.50250651,
0.44798769, 0.47999693, 0.58056676, 0.6932453, 0.77841685, 0.8826156,
0.92832546, 0.88988856, 0.78888032, 0.6819987, 0.62923856, 0.66021523,
0.75754088, 0.86658463, 0.84706981, 0.76282008, 0.69418295, 0.67968584,
0.7274663, 0.81070415, 0.88267631, 0.90298332, 0.86022645, 0.77840601,
0.56517702, 0.48654992, 0.41794253, 0.39786557, 0.43758864, 0.51481438,
0.5861944, 0.61166165, 0.57692084, 0.50147268]
m = 7
n = 10
x_1 = np.zeros(shape=(m,n))
y_1 = np.zeros(shape=(m,n))
for i in range(m):
for j in range(n):
x_1[i][j] = x[j+(n*i)]
y_1[i][j] = y[j+(n*i)]
plt.plot(x_1[i],y_1[i])
plt.axis('scaled')
plt.show()
Poly1 = Polygon(zip(x_1[0],y_1[0]))
Poly2 = Polygon(zip(x_1[1],y_1[1]))
Poly3 = Polygon(zip(x_1[2],y_1[2]))
Poly4 = Polygon(zip(x_1[3],y_1[3]))
Poly5 = Polygon(zip(x_1[4],y_1[4]))
Poly6 = Polygon(zip(x_1[5],y_1[5]))
Poly7 = Polygon(zip(x_1[6],y_1[6]))
polygons = [Poly1,Poly2,Poly3,Poly4,Poly5,Poly6,Poly7]
boundary = cascaded_union(polygons)
我的目标是获得类似右侧图片的效果：
我的其余代码将确定随机分布中有多少点落在不规则形状的边界内。当它返回“null value”注释时，我对错误指向的内容感到困惑。我是否没有以正确的方式考虑个体形状之间的重叠？从我已经搜索过的内容来看，cascaded_union需要输入一个形状数组，但出于某种原因，在这种情况下它不起作用。