Traceback (most recent call last): File "D:\anaconda\11\lib\site-packages\IPython\core\interactiveshell.py", line 3444, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-2-2ea81b4438e6>", line 1, in <module> runfile('D:\\py\\scientificProject7\\main.py', wdir='D:\\py\\scientificProject7') File "D:\pycharm\PyCharm 2022.3.2\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 198, in runfile pydev_imports.execfile(filename, global_vars, local_vars) # execute the script File "D:\pycharm\PyCharm 2022.3.2\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "D:\py\scientificProject7\main.py", line 58, in <module> plt.plot(points[hull.vertices, 0], points[hull.vertices, 1], 'k--', lw=2) IndexError: index 18 is out of bounds for axis 0 with size 8

这个错误提示是因为凸包的顶点数量大于数据点数量，导致索引出错。可能是因为数据点分布不够紧密，或者数据点数量太少。可以尝试调整DBSCAN算法的参数，或者增加数据点数量，来解决这个问题。

另外，如果凸包顶点数量少于3个，也会导致绘图出错。在代码中可以添加一个判断，只对凸包顶点数量大于等于3的簇进行绘图。

修改代码示例：

from sklearn.cluster import DBSCAN
from scipy.spatial import ConvexHull
import matplotlib.pyplot as plt

# 生成一些随机数据
X = np.random.randn(20, 2)

# 运行DBSCAN算法
dbscan = DBSCAN(eps=0.5, min_samples=5)
labels = dbscan.fit_predict(X)

# 将数据点按簇标记分组
clusters = {}
for i, label in enumerate(labels):
    if label not in clusters:
        clusters[label] = []
    clusters[label].append(X[i])

# 画出每个簇的凸包
fig, ax = plt.subplots()
for label, points in clusters.items():
    if label == -1:
        continue
    points = np.array(points)
    hull = ConvexHull(points)
    if len(hull.vertices) >= 3:
        ax.scatter(points[:, 0], points[:, 1])
        ax.plot(points[hull.vertices, 0], points[hull.vertices, 1], 'k--', lw=2)
ax.set_aspect('equal')
plt.show()

在上述代码中，通过添加`if len(hull.vertices) >= 3:`的判断，只对凸包顶点数量大于等于3的簇进行绘图，避免了出现错误。