分析代码： def read_stop_line(self): features = load_data.load_json_file(self.all_Line_path)["features"] stop_polygon = [] pedestrian_crossing_polygon = [] for feature in features: if feature["properties"]["subtype"] == 101 or \ feature["properties"]["subtype"] == 105 or \ feature["properties"]["subtype"] == 104: my_polygon = MyPolygon(coordinates=feature["geometry"]["coordinates"][0], properties=feature["properties"]) my_polygon.temporary_properties = {} tree_polygon = my_polygon.polygon tree_polygon.id = feature["properties"]["id"] stop_polygon.append(tree_polygon) stop_line = LineString(fit_polygon(tree_polygon)) my_polygon.temporary_properties["line_string"] = stop_line self.stop_polygon[tree_polygon.id] = my_polygon elif feature["properties"]["subtype"] == 102: my_polygon = MyPolygon(coordinates=feature["geometry"]["coordinates"][0], properties=feature["properties"]) my_polygon.temporary_properties = {} tree_polygon = my_polygon.polygon tree_polygon.id = feature["properties"]["id"] pedestrian_crossing_polygon.append(tree_polygon) self.pedestrian_crossing[tree_polygon.id] = my_polygon self.stop_line_tree = STRtree(stop_polygon) self.pedestrian_crossing_tree = STRtree(pedestrian_crossing_polygon)

这是一个类的方法，用于读取停止线和人行横道线的信息，并构建相应的数据结构（STRtree）以便于后续查询。

在方法中，首先调用load_data模块中的load_json_file函数读取所有的线信息。然后，遍历所有的线特征，如果该特征是停止线、人行横道线或者过街天桥，就将其转换为对应的MyPolygon对象，并将其加入到stop_polygon或pedestrian_crossing_polygon列表中，同时将其对应的LineString对象（如果是停止线或人行横道线）存储到MyPolygon对象的temporary_properties属性中。最后，使用stop_polygon和pedestrian_crossing_polygon构建STRtree对象，并存储到类的self.stop_line_tree和self.pedestrian_crossing_tree属性中。

这样做的好处是，通过构建STRtree，可以在后续的查询中实现高效的空间索引，提高查询效率。