能不能换一个库，如open3d

当然可以，Open3D也是一个非常优秀的点云库，以下是基于Open3D的代码示例：

import open3d as o3d
import numpy as np
import matplotlib.pyplot as plt

# Step 1: 数据预处理
road_cloud = o3d.io.read_point_cloud("road_cloud.txt")
gps_cloud = o3d.io.read_point_cloud("gps_cloud.txt")

# Step 2: 构建octree
octree = o3d.geometry.Octree(max_depth=10)
octree.convert_from_point_cloud(road_cloud)

# Step 3: 计算视距和可视范围
svm = cv2.ml.SVM_load('svm_model.xml')  # 加载SVM模型
view_distances = []
view_ranges = []
for i in range(len(gps_cloud.points)):
    view_range = []
    view_distance = 0
    gps_point = gps_cloud.points[i]
    [k, idx, _] = octree.search_knn_vector_3d(gps_point, 1000)
    for j in range(len(idx)):
        road_point = road_cloud.points[idx[j]]
        if svm.predict(road_point) == 1:
            view_range.append(road_point)
            dist = np.linalg.norm(np.asarray(gps_point) - np.asarray(road_point))
            if dist > view_distance:
                view_distance = dist
    view_distances.append(view_distance)
    view_ranges.append(view_range)

# Step 4: 计算视距距离
view_distance_curve = []
for i in range(len(view_ranges)):
    if len(view_ranges[i]) > 0:
        view_range_array = np.asarray(view_ranges[i])
        curve_fit = np.polyfit(view_range_array[:, 0], view_range_array[:, 1], 2)  # 二次曲线拟合
        curve = np.poly1d(curve_fit)
        view_distance_curve.append(curve(view_ranges[i][0][0]) - gps_cloud.points[i][1])
    else:
        view_distance_curve.append(0)

# Step 5: 可视化结果
fig, axs = plt.subplots(2, 1)
axs[0].scatter(gps_cloud.points[:, 0], gps_cloud.points[:, 1], s=1, c=view_distances)
axs[0].set_title('View distance')
axs[1].scatter(gps_cloud.points[:, 0], gps_cloud.points[:, 1], s=1, c=view_distance_curve)
axs[1].set_title('View distance curve')
plt.show()

同样需要注意的是，上述代码仅作为参考，具体实现可能需要根据实际情况进行适当的修改和调整。另外，Open3D的API与PCL略有不同，需要注意函数的调用和参数的传递。