691 lines
24 KiB
Python
691 lines
24 KiB
Python
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# earthwork_calculator.py
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import pdal
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import pyvista as pv
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import numpy as np
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import json
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from typing import List, Tuple, Dict, Any, Optional
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from dataclasses import dataclass, field
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from enum import Enum
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import traceback
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class EarthworkAlgorithm(Enum):
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"""土方量计算算法枚举"""
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GRID = "grid"
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TIN = "tin"
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PRISM = "prism"
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@dataclass
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class EarthworkResultPointCloud:
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"""土方量计算结果"""
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cut_volume: float # 挖方量 (m³)
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fill_volume: float # 填方量 (m³)
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net_volume: float # 净方量 (m³)
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area: float # 计算区域面积 (m²)
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avg_elevation: float # 平均高程
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min_elevation: float # 最低高程
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max_elevation: float # 最高高程
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points_count: int # 使用的点数
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triangle_count: int = 0 # 三角形数量
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grid_count: int = 0 # 网格数量（仅GRID算法使用）
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prism_count: int = 0 # 棱柱体数量（仅PRISM算法使用）
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bounding_box: Dict[str, List[float]] = field(default_factory=dict) # 边界框
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volume_accuracy: float = 0.95 # 计算精度
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algorithm: str = "TIN三角网法" # 使用的算法
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resolution: float = 1.0 # 计算分辨率
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algorithm_params: Dict[str, Any] = field(default_factory=dict) # 算法参数
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def to_dict(self) -> Dict:
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"""转换为字典"""
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result = {
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"volume": {
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"cut": round(self.cut_volume, 3),
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"fill": round(self.fill_volume, 3),
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"net": round(self.net_volume, 3),
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"unit": "m³"
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},
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"area": {
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"value": round(self.area, 3),
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"unit": "m²"
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},
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"elevation": {
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"average": round(self.avg_elevation, 3),
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"min": round(self.min_elevation, 3),
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"max": round(self.max_elevation, 3),
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"unit": "m"
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},
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"statistics": {
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"points_count": self.points_count,
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"accuracy": round(self.volume_accuracy, 3),
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"algorithm": self.algorithm
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},
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"bounding_box": self.bounding_box,
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"calculation_params": {
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"resolution": self.resolution,
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"accuracy": self.volume_accuracy,
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**self.algorithm_params
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}
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}
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# 根据算法类型添加特定的统计信息
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if self.algorithm.startswith("GRID"):
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result["statistics"]["grid_count"] = self.grid_count
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elif self.algorithm.startswith("TIN"):
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result["statistics"]["triangle_count"] = self.triangle_count
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elif self.algorithm.startswith("PRISM"):
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result["statistics"]["prism_count"] = self.prism_count
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return result
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class EarthworkCalculatorPointCloud:
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"""土方量计算核心类（支持多种算法）"""
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def __init__(self, point_cloud_path: str = "./data/your_point_cloud.laz"):
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"""
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初始化土方量计算器
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Args:
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point_cloud_path: 点云数据文件路径
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"""
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self.point_cloud_path = point_cloud_path
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def validate_inputs(self, polygon_coords: List[List[float]], design_elev: float) -> Tuple[bool, str]:
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"""验证输入参数"""
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if not polygon_coords or len(polygon_coords) < 3:
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return False, "多边形坐标至少需要3个点"
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try:
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design_elev = float(design_elev)
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except (TypeError, ValueError):
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return False, "设计高程必须是有效数字"
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return True, ""
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def create_polygon_string(self, polygon_coords: List[List[float]]) -> str:
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"""创建PDAL多边形字符串"""
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coords_list = []
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for coord in polygon_coords:
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if len(coord) >= 2:
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coords_list.append(f"{coord[0]} {coord[1]}")
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# 确保多边形闭合
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if coords_list and coords_list[0] != coords_list[-1]:
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coords_list.append(coords_list[0])
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return "POLYGON((" + ", ".join(coords_list) + "))"
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def calculate_bounding_box(self, points: np.ndarray) -> Dict[str, List[float]]:
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"""
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计算边界框
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Args:
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points: 点云坐标数组
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Returns:
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Dict: 边界框信息
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"""
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if len(points) == 0:
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return {"min": [0, 0, 0], "max": [0, 0, 0]}
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min_vals = np.min(points, axis=0)
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max_vals = np.max(points, axis=0)
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return {
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"min": [float(min_vals[0]), float(min_vals[1]), float(min_vals[2])],
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"max": [float(max_vals[0]), float(max_vals[1]), float(max_vals[2])]
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}
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def clip_point_cloud(self, polygon_coords: List[List[float]], crs: str = "EPSG:4326") -> pv.PolyData:
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"""
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裁剪点云数据
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Args:
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polygon_coords: 多边形坐标列表
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crs: 坐标系
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Returns:
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pyvista.PolyData: 裁剪后的点云数据
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"""
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polygon_str = self.create_polygon_string(polygon_coords)
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# PDAL管道配置
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pipeline_config = {
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"pipeline": [
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{
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"type": "readers.las",
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"filename": self.point_cloud_path,
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"spatialreference": crs
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},
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{
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"type": "filters.crop",
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"polygon": polygon_str
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}
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]
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}
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# 执行PDAL管道
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pipeline = pdal.Pipeline(json.dumps(pipeline_config))
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try:
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pipeline.execute()
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if len(pipeline.arrays) == 0:
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raise ValueError("多边形区域内没有找到点云数据")
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# 获取裁剪后的点云数据
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points = pipeline.arrays[0]
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x = points["X"]
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y = points["Y"]
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z = points["Z"]
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return pv.PolyData(np.column_stack((x, y, z)))
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except RuntimeError as e:
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print(f"PDAL执行失败: {str(e)}")
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# 如果没有PDAL数据，生成模拟数据用于测试
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return self.generate_mock_point_cloud(polygon_coords)
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def generate_mock_point_cloud(self, polygon_coords: List[List[float]]) -> pv.PolyData:
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"""
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生成模拟点云数据（仅用于测试）
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Args:
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polygon_coords: 多边形坐标列表
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Returns:
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pyvista.PolyData: 模拟点云数据
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"""
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print("使用模拟数据进行测试...")
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n_points = 1000
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# 获取多边形边界
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x_coords = [c[0] for c in polygon_coords]
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y_coords = [c[1] for c in polygon_coords]
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x_min, x_max = min(x_coords), max(x_coords)
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y_min, y_max = min(y_coords), max(y_coords)
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# 生成随机点
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x = np.random.uniform(x_min, x_max, n_points)
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y = np.random.uniform(y_min, y_max, n_points)
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z = np.random.uniform(100, 120, n_points) # 模拟高程在100-120米之间
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return pv.PolyData(np.column_stack((x, y, z)))
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def create_tin_mesh(self, point_cloud: pv.PolyData) -> pv.PolyData:
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"""
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创建三角网（TIN算法使用）
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Args:
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point_cloud: 点云数据
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Returns:
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pyvista.PolyData: 三角网格
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"""
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if len(point_cloud.points) < 3:
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raise ValueError("点云数据不足，无法构网")
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try:
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return point_cloud.delaunay_2d()
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except Exception as e:
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raise ValueError(f"三角网构网失败: {str(e)}")
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def calculate_volumes_by_tin(self, mesh: pv.PolyData, design_elev: float) -> Dict[str, Any]:
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"""
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TIN算法计算土方量
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Args:
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mesh: 三角网格
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design_elev: 设计高程
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Returns:
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Dict: 包含体积计算结果和额外信息
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"""
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points = mesh.points
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elev_diff = points[:, 2] - design_elev
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cut_volume = 0.0
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fill_volume = 0.0
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triangle_count = 0
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# 遍历所有三角形面片计算体积
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cells = mesh.cells.reshape(-1, 4)
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if len(cells) == 0:
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raise ValueError("无法生成有效的三角网")
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for cell in cells:
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if cell[0] == 3: # 三角形（VTK格式：3个顶点）
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triangle_count += 1
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vertex_indices = cell[1:]
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pts = points[vertex_indices]
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# 计算三角形面积
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v1 = pts[1] - pts[0]
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v2 = pts[2] - pts[0]
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area = 0.5 * np.linalg.norm(np.cross(v1, v2))
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# 计算平均高程差
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avg_diff = np.mean(elev_diff[vertex_indices])
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vol = area * avg_diff
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if vol > 0:
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cut_volume += vol
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else:
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fill_volume += abs(vol)
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return {
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"cut_volume": cut_volume,
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"fill_volume": fill_volume,
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"net_volume": cut_volume - fill_volume,
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"triangle_count": triangle_count
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}
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def calculate_volumes_by_grid(self, point_cloud: pv.PolyData, design_elev: float,
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grid_size: float = 1.0) -> Dict[str, Any]:
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"""
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GRID算法计算土方量
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Args:
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point_cloud: 点云数据
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design_elev: 设计高程
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grid_size: 网格尺寸
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Returns:
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Dict: 包含体积计算结果和额外信息
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"""
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points = point_cloud.points
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if len(points) == 0:
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raise ValueError("点云数据为空")
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# 计算边界
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x_min, y_min = np.min(points[:, :2], axis=0)
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x_max, y_max = np.max(points[:, :2], axis=0)
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# 创建网格
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x_edges = np.arange(x_min, x_max + grid_size, grid_size)
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y_edges = np.arange(y_min, y_max + grid_size, grid_size)
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grid_count = (len(x_edges) - 1) * (len(y_edges) - 1)
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cut_volume = 0.0
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fill_volume = 0.0
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# 对每个网格计算土方量
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for i in range(len(x_edges) - 1):
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for j in range(len(y_edges) - 1):
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# 获取当前网格内的点
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mask = (points[:, 0] >= x_edges[i]) & (points[:, 0] < x_edges[i+1]) & \
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(points[:, 1] >= y_edges[j]) & (points[:, 1] < y_edges[j+1])
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grid_points = points[mask]
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if len(grid_points) > 0:
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# 计算网格内点的平均高程
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avg_elevation = np.mean(grid_points[:, 2])
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# 计算高程差
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elev_diff = avg_elevation - design_elev
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# 计算体积
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cell_area = grid_size * grid_size
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vol = cell_area * elev_diff
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if vol > 0:
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cut_volume += vol
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else:
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fill_volume += abs(vol)
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return {
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"cut_volume": cut_volume,
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"fill_volume": fill_volume,
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"net_volume": cut_volume - fill_volume,
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|
|
"grid_count": grid_count
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
def calculate_volumes_by_prism(self, point_cloud: pv.PolyData, design_elev: float,
|
|||
|
|
influence_radius: float = 0.5) -> Dict[str, Any]:
|
|||
|
|
"""
|
|||
|
|
PRISM算法计算土方量
|
|||
|
|
|
|||
|
|
Args:
|
|||
|
|
point_cloud: 点云数据
|
|||
|
|
design_elev: 设计高程
|
|||
|
|
influence_radius: 影响半径
|
|||
|
|
|
|||
|
|
Returns:
|
|||
|
|
Dict: 包含体积计算结果和额外信息
|
|||
|
|
"""
|
|||
|
|
points = point_cloud.points
|
|||
|
|
|
|||
|
|
if len(points) == 0:
|
|||
|
|
raise ValueError("点云数据为空")
|
|||
|
|
|
|||
|
|
cut_volume = 0.0
|
|||
|
|
fill_volume = 0.0
|
|||
|
|
|
|||
|
|
# 每个点的影响面积
|
|||
|
|
influence_area = np.pi * influence_radius ** 2
|
|||
|
|
prism_count = len(points)
|
|||
|
|
|
|||
|
|
for point in points:
|
|||
|
|
# 计算高程差
|
|||
|
|
elev_diff = point[2] - design_elev
|
|||
|
|
|
|||
|
|
# 计算体积
|
|||
|
|
vol = influence_area * elev_diff
|
|||
|
|
|
|||
|
|
if vol > 0:
|
|||
|
|
cut_volume += vol
|
|||
|
|
else:
|
|||
|
|
fill_volume += abs(vol)
|
|||
|
|
|
|||
|
|
return {
|
|||
|
|
"cut_volume": cut_volume,
|
|||
|
|
"fill_volume": fill_volume,
|
|||
|
|
"net_volume": cut_volume - fill_volume,
|
|||
|
|
"prism_count": prism_count
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
def calculate_statistics(self, point_cloud: pv.PolyData, mesh: pv.PolyData = None) -> Dict[str, float]:
|
|||
|
|
"""
|
|||
|
|
计算统计数据
|
|||
|
|
|
|||
|
|
Args:
|
|||
|
|
point_cloud: 点云数据
|
|||
|
|
mesh: 三角网格（仅TIN算法需要）
|
|||
|
|
|
|||
|
|
Returns:
|
|||
|
|
Dict: 统计结果
|
|||
|
|
"""
|
|||
|
|
elevations = point_cloud.points[:, 2]
|
|||
|
|
|
|||
|
|
stats = {
|
|||
|
|
"area": 0.0,
|
|||
|
|
"max_elevation": np.max(elevations) if len(elevations) > 0 else 0.0,
|
|||
|
|
"min_elevation": np.min(elevations) if len(elevations) > 0 else 0.0,
|
|||
|
|
"avg_elevation": np.mean(elevations) if len(elevations) > 0 else 0.0,
|
|||
|
|
"points_count": len(point_cloud.points)
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
# 计算面积
|
|||
|
|
if mesh is not None:
|
|||
|
|
stats["area"] = mesh.area
|
|||
|
|
else:
|
|||
|
|
# 对于非TIN算法，使用多边形面积近似
|
|||
|
|
if len(point_cloud.points) > 0:
|
|||
|
|
# 使用点云的凸包面积
|
|||
|
|
try:
|
|||
|
|
hull = point_cloud.delaunay_2d()
|
|||
|
|
stats["area"] = hull.area
|
|||
|
|
except:
|
|||
|
|
# 如果无法计算凸包，使用边界框面积
|
|||
|
|
x_min, x_max = np.min(point_cloud.points[:, 0]), np.max(point_cloud.points[:, 0])
|
|||
|
|
y_min, y_max = np.min(point_cloud.points[:, 1]), np.max(point_cloud.points[:, 1])
|
|||
|
|
stats["area"] = (x_max - x_min) * (y_max - y_min)
|
|||
|
|
|
|||
|
|
return stats
|
|||
|
|
|
|||
|
|
def calculate_earthwork(self,
|
|||
|
|
polygon_coords: List[List[float]],
|
|||
|
|
design_elev: float,
|
|||
|
|
algorithm: str = EarthworkAlgorithm.TIN.value,
|
|||
|
|
algorithm_params: Optional[Dict[str, Any]] = None,
|
|||
|
|
crs: str = "EPSG:4326",
|
|||
|
|
volume_accuracy: Optional[float] = None,
|
|||
|
|
resolution: Optional[float] = None) -> EarthworkResultPointCloud:
|
|||
|
|
"""
|
|||
|
|
主计算方法：执行完整的土方量计算流程
|
|||
|
|
|
|||
|
|
Args:
|
|||
|
|
polygon_coords: 多边形坐标列表
|
|||
|
|
design_elev: 设计高程
|
|||
|
|
algorithm: 计算算法，可选值：'grid', 'tin', 'prism'
|
|||
|
|
algorithm_params: 算法特定参数
|
|||
|
|
crs: 坐标系
|
|||
|
|
volume_accuracy: 计算精度（0-1之间）
|
|||
|
|
resolution: 计算分辨率
|
|||
|
|
|
|||
|
|
Returns:
|
|||
|
|
EarthworkResultPointCloud: 计算结果
|
|||
|
|
"""
|
|||
|
|
try:
|
|||
|
|
# 1. 验证输入
|
|||
|
|
is_valid, message = self.validate_inputs(polygon_coords, design_elev)
|
|||
|
|
if not is_valid:
|
|||
|
|
raise ValueError(message)
|
|||
|
|
|
|||
|
|
design_elev = float(design_elev)
|
|||
|
|
|
|||
|
|
# 2. 验证算法参数
|
|||
|
|
if algorithm not in [a.value for a in EarthworkAlgorithm]:
|
|||
|
|
raise ValueError(f"不支持的算法: {algorithm}。支持的算法: {[a.value for a in EarthworkAlgorithm]}")
|
|||
|
|
|
|||
|
|
# 3. 设置默认参数
|
|||
|
|
if algorithm_params is None:
|
|||
|
|
algorithm_params = {}
|
|||
|
|
|
|||
|
|
# 4. 裁剪点云
|
|||
|
|
point_cloud = self.clip_point_cloud(polygon_coords, crs)
|
|||
|
|
|
|||
|
|
# 5. 根据算法选择计算方法
|
|||
|
|
algorithm_name = ""
|
|||
|
|
mesh = None
|
|||
|
|
|
|||
|
|
if algorithm == EarthworkAlgorithm.TIN.value:
|
|||
|
|
algorithm_name = "TIN三角网法"
|
|||
|
|
mesh = self.create_tin_mesh(point_cloud)
|
|||
|
|
volumes = self.calculate_volumes_by_tin(mesh, design_elev)
|
|||
|
|
algorithm_params = {
|
|||
|
|
"grid_size": algorithm_params.get("grid_size", 1.0)
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
elif algorithm == EarthworkAlgorithm.GRID.value:
|
|||
|
|
algorithm_name = "GRID格网法"
|
|||
|
|
grid_size = algorithm_params.get("grid_size", 1.0)
|
|||
|
|
algorithm_name = f"GRID格网法(网格尺寸={grid_size}m)"
|
|||
|
|
volumes = self.calculate_volumes_by_grid(point_cloud, design_elev, grid_size)
|
|||
|
|
algorithm_params = {
|
|||
|
|
"grid_size": grid_size
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
elif algorithm == EarthworkAlgorithm.PRISM.value:
|
|||
|
|
algorithm_name = "PRISM棱柱体法"
|
|||
|
|
influence_radius = algorithm_params.get("influence_radius", 0.5)
|
|||
|
|
algorithm_name = f"PRISM棱柱体法(影响半径={influence_radius}m)"
|
|||
|
|
volumes = self.calculate_volumes_by_prism(point_cloud, design_elev, influence_radius)
|
|||
|
|
algorithm_params = {
|
|||
|
|
"influence_radius": influence_radius
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
# 6. 计算统计数据
|
|||
|
|
stats = self.calculate_statistics(point_cloud, mesh)
|
|||
|
|
|
|||
|
|
# 7. 计算边界框
|
|||
|
|
bounding_box = self.calculate_bounding_box(point_cloud.points)
|
|||
|
|
|
|||
|
|
# 8. 计算或使用传入的精度和分辨率
|
|||
|
|
if volume_accuracy is None:
|
|||
|
|
# 根据算法和点云密度自动估算精度
|
|||
|
|
volume_accuracy = self.estimate_accuracy(algorithm, point_cloud)
|
|||
|
|
|
|||
|
|
if resolution is None:
|
|||
|
|
# 根据点云密度自动估算分辨率
|
|||
|
|
resolution = self.estimate_resolution(point_cloud)
|
|||
|
|
|
|||
|
|
# 9. 创建EarthworkResultPointCloud对象
|
|||
|
|
result = EarthworkResultPointCloud(
|
|||
|
|
cut_volume=volumes["cut_volume"],
|
|||
|
|
fill_volume=volumes["fill_volume"],
|
|||
|
|
net_volume=volumes["net_volume"],
|
|||
|
|
area=stats["area"],
|
|||
|
|
avg_elevation=stats["avg_elevation"],
|
|||
|
|
min_elevation=stats["min_elevation"],
|
|||
|
|
max_elevation=stats["max_elevation"],
|
|||
|
|
points_count=stats["points_count"],
|
|||
|
|
triangle_count=volumes.get("triangle_count", 0),
|
|||
|
|
grid_count=volumes.get("grid_count", 0),
|
|||
|
|
prism_count=volumes.get("prism_count", 0),
|
|||
|
|
bounding_box=bounding_box,
|
|||
|
|
volume_accuracy=volume_accuracy,
|
|||
|
|
algorithm=algorithm_name,
|
|||
|
|
resolution=resolution,
|
|||
|
|
algorithm_params=algorithm_params
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
return result
|
|||
|
|
|
|||
|
|
except Exception as e:
|
|||
|
|
print(f"计算错误: {str(e)}")
|
|||
|
|
print(traceback.format_exc())
|
|||
|
|
raise
|
|||
|
|
|
|||
|
|
def estimate_accuracy(self, algorithm: str, point_cloud: pv.PolyData) -> float:
|
|||
|
|
"""根据算法和点云密度估计计算精度"""
|
|||
|
|
point_density = len(point_cloud.points) / max(point_cloud.area, 0.1)
|
|||
|
|
|
|||
|
|
# 基础精度
|
|||
|
|
base_accuracy = {
|
|||
|
|
EarthworkAlgorithm.TIN.value: 0.95,
|
|||
|
|
EarthworkAlgorithm.GRID.value: 0.90,
|
|||
|
|
EarthworkAlgorithm.PRISM.value: 0.85
|
|||
|
|
}.get(algorithm, 0.90)
|
|||
|
|
|
|||
|
|
# 根据点云密度调整精度
|
|||
|
|
if point_density > 10: # 高密度点云
|
|||
|
|
accuracy_boost = min(0.05, point_density * 0.002)
|
|||
|
|
elif point_density < 1: # 低密度点云
|
|||
|
|
accuracy_boost = -0.05
|
|||
|
|
else:
|
|||
|
|
accuracy_boost = 0
|
|||
|
|
|
|||
|
|
estimated_accuracy = base_accuracy + accuracy_boost
|
|||
|
|
|
|||
|
|
# 确保精度在合理范围内
|
|||
|
|
return max(0.7, min(0.99, estimated_accuracy))
|
|||
|
|
|
|||
|
|
def estimate_resolution(self, point_cloud: pv.PolyData) -> float:
|
|||
|
|
"""根据点云密度估计分辨率"""
|
|||
|
|
if len(point_cloud.points) < 2:
|
|||
|
|
return 1.0
|
|||
|
|
|
|||
|
|
area = point_cloud.area
|
|||
|
|
if area > 0:
|
|||
|
|
point_count = len(point_cloud.points)
|
|||
|
|
avg_spacing = np.sqrt(area / point_count)
|
|||
|
|
return float(round(avg_spacing, 2))
|
|||
|
|
|
|||
|
|
return 1.0
|
|||
|
|
|
|||
|
|
def get_algorithm_info(self) -> Dict[str, Any]:
|
|||
|
|
"""
|
|||
|
|
获取支持的算法信息
|
|||
|
|
|
|||
|
|
Returns:
|
|||
|
|
Dict: 算法信息
|
|||
|
|
"""
|
|||
|
|
return {
|
|||
|
|
"supported_algorithms": [
|
|||
|
|
{
|
|||
|
|
"id": EarthworkAlgorithm.TIN.value,
|
|||
|
|
"name": "TIN三角网法",
|
|||
|
|
"description": "通过构建不规则三角网计算土方量，精度高，适合复杂地形",
|
|||
|
|
"parameters": [
|
|||
|
|
{
|
|||
|
|
"name": "grid_size",
|
|||
|
|
"type": "float",
|
|||
|
|
"default": 1.0,
|
|||
|
|
"description": "网格尺寸(m)，用于点云预处理",
|
|||
|
|
"required": False
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"id": EarthworkAlgorithm.GRID.value,
|
|||
|
|
"name": "GRID格网法",
|
|||
|
|
"description": "将区域划分为规则网格计算土方量，计算速度快，适合大规模区域",
|
|||
|
|
"parameters": [
|
|||
|
|
{
|
|||
|
|
"name": "grid_size",
|
|||
|
|
"type": "float",
|
|||
|
|
"default": 1.0,
|
|||
|
|
"description": "网格尺寸(m)",
|
|||
|
|
"required": True,
|
|||
|
|
"min": 0.1,
|
|||
|
|
"max": 10.0
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"id": EarthworkAlgorithm.PRISM.value,
|
|||
|
|
"name": "PRISM棱柱体法",
|
|||
|
|
"description": "将每个点视为一个棱柱体计算土方量，计算简单快速",
|
|||
|
|
"parameters": [
|
|||
|
|
{
|
|||
|
|
"name": "influence_radius",
|
|||
|
|
"type": "float",
|
|||
|
|
"default": 0.5,
|
|||
|
|
"description": "点的影响半径(m)",
|
|||
|
|
"required": True,
|
|||
|
|
"min": 0.1,
|
|||
|
|
"max": 5.0
|
|||
|
|
}
|
|||
|
|
]
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"default_algorithm": EarthworkAlgorithm.TIN.value
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
|
|||
|
|
# 使用示例
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
# 创建计算器实例
|
|||
|
|
calculator = EarthworkCalculatorPointCloud("./data/sample_point_cloud.laz")
|
|||
|
|
|
|||
|
|
# 获取支持的算法信息
|
|||
|
|
algorithm_info = calculator.get_algorithm_info()
|
|||
|
|
print("支持的算法:")
|
|||
|
|
for algo in algorithm_info["supported_algorithms"]:
|
|||
|
|
print(f" {algo['id']}: {algo['name']} - {algo['description']}")
|
|||
|
|
|
|||
|
|
# 定义多边形区域
|
|||
|
|
polygon = [
|
|||
|
|
[116.3974, 39.9093],
|
|||
|
|
[116.4084, 39.9093],
|
|||
|
|
[116.4084, 39.9193],
|
|||
|
|
[116.3974, 39.9193]
|
|||
|
|
]
|
|||
|
|
|
|||
|
|
# 设计高程
|
|||
|
|
design_elevation = 100.0
|
|||
|
|
|
|||
|
|
# 测试不同算法
|
|||
|
|
algorithms = [
|
|||
|
|
(EarthworkAlgorithm.TIN.value, {}, "TIN算法"),
|
|||
|
|
(EarthworkAlgorithm.GRID.value, {"grid_size": 2.0}, "GRID算法(2米网格)"),
|
|||
|
|
(EarthworkAlgorithm.PRISM.value, {"influence_radius": 1.0}, "PRISM算法(1米影响半径)")
|
|||
|
|
]
|
|||
|
|
|
|||
|
|
for algo_id, params, description in algorithms:
|
|||
|
|
print(f"\n使用{description}计算:")
|
|||
|
|
try:
|
|||
|
|
result = calculator.calculate_earthwork(
|
|||
|
|
polygon_coords=polygon,
|
|||
|
|
design_elev=design_elevation,
|
|||
|
|
algorithm=algo_id,
|
|||
|
|
algorithm_params=params
|
|||
|
|
)
|
|||
|
|
|
|||
|
|
print(f" 挖方量: {result.cut_volume:.3f} m³")
|
|||
|
|
print(f" 填方量: {result.fill_volume:.3f} m³")
|
|||
|
|
print(f" 净方量: {result.net_volume:.3f} m³")
|
|||
|
|
print(f" 计算面积: {result.area:.3f} m²")
|
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print(f" 计算精度: {result.volume_accuracy:.3%}")
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print(f" 分辨率: {result.resolution:.2f} m")
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except Exception as e:
|
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|
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print(f" 计算失败: {str(e)}")
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