``` from stl import mesh import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D class STLAnalyzer: def __init__(self, filepath): self.mesh = mesh.Mesh.from_file(filepath) self.vertices = self.mesh.vectors.reshape(-1, 3) # 所有顶点坐标 self.triangles = self.mesh.vectors # 三角形面片数据 self.edge_map = {} # 边到面片的映射表 def build_edge_map(self): for i, tri in enumerate(self.triangles): for j in range(3): v1 = tuple(tri[j]) v2 = tuple(tri[(j + 1) % 3]) edge = tuple(sorted([v1, v2])) # 标准化边表示 if edge not in self.edge_map: self.edge_map[edge] = [] self.edge_map[edge].append(i) def detect_features(self, angle_threshold=30): features = [] for edge, tri_indices in self.edge_map.items(): if len(tri_indices) == 2: # 仅处理共享边 n1 = self.mesh.normals[tri_indices[0]] n2 = self.mesh.normals[tri_indices[1]] dot = np.dot(n1, n2) angle = np.degrees(np.arccos(np.clip(dot, -1, 1))) if angle > angle_threshold: features.append(edge) return features def visualize_features(vertices, features): plt.rcParams['font.family'] = ['Microsoft YaHei'] plt.rcParams['axes.unicode_minus'] = False fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.set_box_aspect([1, 1, 0.1]) # z轴缩小10倍 # 绘制所有三角形 ax.plot_trisurf(vertices[:, 0], vertices[:, 1], vertices[:, 2], alpha=0.2) # 绘制特征边 for edge in features: line = np.array([edge[0], edge[1]]) ax.plot(line[:, 0], line[:, 1], line[:, 2], c='r', lw=2) plt.show() if __name__ == "__main__": analyzer = STLAnalyzer("1model.stl") analyzer.build_edge_map() features = analyzer.detect_features(angle_threshold=30) # 直接调用独立的 visualize_features 函数 visualize_features(analyzer.vertices, features)```请解释这段代码的内容