456 lines
16 KiB
Python
456 lines
16 KiB
Python
"""
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导航网格优化器
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提供自动优化导航网格的功能，包括多边形合并、简化和重构
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"""
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import math
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from typing import List, Dict, Set, Tuple, Optional
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from panda3d.core import Point3
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class NavMeshOptimizer:
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"""
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导航网格优化器
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提供自动优化导航网格的功能
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"""
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def __init__(self, navmesh_manager):
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"""
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初始化导航网格优化器
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Args:
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navmesh_manager: 导航网格管理器实例
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"""
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self.navmesh_manager = navmesh_manager
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self.optimization_settings = {
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'merge_threshold': 0.5, # 合并阈值
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'simplify_threshold': 0.1, # 简化阈值
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'min_polygon_area': 0.01, # 最小多边形面积
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'max_vertices_per_polygon': 8, # 每个多边形最大顶点数
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'preserve_boundaries': True, # 是否保留边界
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'preserve_portals': True # 是否保留门户点
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}
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def set_optimization_settings(self, settings: Dict):
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"""
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设置优化参数
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Args:
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settings: 优化参数字典
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"""
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self.optimization_settings.update(settings)
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def get_optimization_settings(self) -> Dict:
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"""
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获取优化参数
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Returns:
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优化参数字典
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"""
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return self.optimization_settings.copy()
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def merge_adjacent_polygons(self) -> int:
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"""
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合并相邻的多边形
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Returns:
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合并的多边形数量
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"""
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if not self.navmesh_manager or not self.navmesh_manager.polygons:
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return 0
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merged_count = 0
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processed_polygons = set()
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# 创建多边形ID列表的副本，避免在迭代时修改字典
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polygon_ids = list(self.navmesh_manager.polygons.keys())
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for polygon_id in polygon_ids:
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if polygon_id in processed_polygons:
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continue
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if polygon_id not in self.navmesh_manager.polygons:
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continue
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polygon = self.navmesh_manager.polygons[polygon_id]
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# 检查是否可以与其他多边形合并
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for neighbor_id in polygon.neighbors[:]: # 使用副本避免修改时的问题
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if neighbor_id in processed_polygons:
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continue
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if neighbor_id not in self.navmesh_manager.polygons:
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continue
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neighbor = self.navmesh_manager.polygons[neighbor_id]
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# 检查合并条件
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if self._can_merge_polygons(polygon, neighbor):
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# 执行合并
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if self._merge_two_polygons(polygon_id, neighbor_id):
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merged_count += 1
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processed_polygons.add(polygon_id)
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processed_polygons.add(neighbor_id)
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break
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# 重新计算连接关系
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if merged_count > 0:
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self.navmesh_manager._calculate_polygon_connections()
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self.navmesh_manager._calculate_portal_points()
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self.navmesh_manager._update_navmesh_visualization()
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return merged_count
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def _can_merge_polygons(self, polygon1, polygon2) -> bool:
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"""
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检查两个多边形是否可以合并
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Args:
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polygon1: 第一个多边形
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polygon2: 第二个多边形
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Returns:
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是否可以合并
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"""
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# 检查是否有共享边
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if not self._polygons_share_full_edge(polygon1, polygon2):
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return False
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# 检查合并后的多边形是否过于复杂
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merged_vertices = self._get_merged_vertices(polygon1, polygon2)
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if len(merged_vertices) > self.optimization_settings['max_vertices_per_polygon']:
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return False
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# 检查面积
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merged_area = self._calculate_polygon_area(merged_vertices)
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if merged_area < self.optimization_settings['min_polygon_area']:
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return False
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return True
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def _polygons_share_full_edge(self, polygon1, polygon2) -> bool:
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"""
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检查两个多边形是否共享完整的一条边
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Args:
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polygon1: 第一个多边形
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polygon2: 第二个多边形
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Returns:
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是否共享完整边
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"""
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threshold = 0.01 # 点重合阈值
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# 检查polygon1的每条边
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for i in range(len(polygon1.vertices)):
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v1_start = polygon1.vertices[i]
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v1_end = polygon1.vertices[(i + 1) % len(polygon1.vertices)]
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# 检查polygon2的每条边
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for j in range(len(polygon2.vertices)):
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v2_start = polygon2.vertices[j]
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v2_end = polygon2.vertices[(j + 1) % len(polygon2.vertices)]
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# 检查边是否重合（方向相同）
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if (self._points_equal(v1_start, v2_start, threshold) and
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self._points_equal(v1_end, v2_end, threshold)):
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return True
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# 检查边是否重合（方向相反）
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if (self._points_equal(v1_start, v2_end, threshold) and
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self._points_equal(v1_end, v2_start, threshold)):
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return True
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return False
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def _points_equal(self, p1: Point3, p2: Point3, threshold: float) -> bool:
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"""检查两点是否相等（在阈值范围内）"""
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return (p1 - p2).length() < threshold
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def _get_merged_vertices(self, polygon1, polygon2) -> List[Point3]:
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"""
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获取两个多边形合并后的顶点
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Args:
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polygon1: 第一个多边形
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polygon2: 第二个多边形
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Returns:
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合并后的顶点列表
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"""
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# 这是一个简化的实现
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# 实际应用中需要正确处理多边形合并的几何运算
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merged_vertices = []
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merged_vertices.extend(polygon1.vertices)
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merged_vertices.extend(polygon2.vertices)
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return merged_vertices
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def _calculate_polygon_area(self, vertices: List[Point3]) -> float:
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"""计算多边形面积（使用鞋带公式）"""
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if len(vertices) < 3:
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return 0.0
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area = 0.0
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n = len(vertices)
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for i in range(n):
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j = (i + 1) % n
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area += vertices[i].x * vertices[j].z
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area -= vertices[j].x * vertices[i].z
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return abs(area) / 2.0
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def _merge_two_polygons(self, polygon1_id: int, polygon2_id: int) -> bool:
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"""
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合并两个多边形
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Args:
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polygon1_id: 第一个多边形ID
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polygon2_id: 第二个多边形ID
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Returns:
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是否合并成功
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"""
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try:
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if (polygon1_id not in self.navmesh_manager.polygons or
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polygon2_id not in self.navmesh_manager.polygons):
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return False
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polygon1 = self.navmesh_manager.polygons[polygon1_id]
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polygon2 = self.navmesh_manager.polygons[polygon2_id]
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# 创建合并后的新多边形
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merged_vertices = self._merge_polygon_vertices(polygon1, polygon2)
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if not merged_vertices:
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return False
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# 移除旧的多边形
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self.navmesh_manager.remove_polygon(polygon2_id)
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# 更新第一个多边形
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polygon1.vertices = merged_vertices
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polygon1.center = polygon1._calculate_center()
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polygon1.area = polygon1._calculate_area()
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polygon1.bounding_box = polygon1._calculate_bounding_box()
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return True
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except Exception as e:
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print(f"合并多边形失败: {e}")
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return False
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def _merge_polygon_vertices(self, polygon1, polygon2) -> List[Point3]:
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"""
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合并两个多边形的顶点
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Args:
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polygon1: 第一个多边形
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polygon2: 第二个多边形
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Returns:
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合并后的顶点列表
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"""
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# 这是一个简化的实现
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# 实际应用中需要正确处理多边形合并的几何运算
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# 包括移除共享边，正确排序顶点等
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# 简单合并所有顶点
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merged_vertices = []
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merged_vertices.extend(polygon1.vertices)
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merged_vertices.extend(polygon2.vertices)
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# 去除重复顶点（简化处理）
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unique_vertices = []
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for vertex in merged_vertices:
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is_duplicate = False
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for existing_vertex in unique_vertices:
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if self._points_equal(vertex, existing_vertex, 0.01):
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is_duplicate = True
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break
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if not is_duplicate:
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unique_vertices.append(vertex)
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return unique_vertices[:self.optimization_settings['max_vertices_per_polygon']]
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def simplify_polygons(self) -> int:
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"""
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简化多边形（移除不必要的顶点）
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Returns:
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简化的顶点数量
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"""
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if not self.navmesh_manager or not self.navmesh_manager.polygons:
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return 0
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simplified_count = 0
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for polygon in self.navmesh_manager.polygons.values():
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original_vertex_count = len(polygon.vertices)
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simplified_vertices = self._simplify_polygon(polygon.vertices)
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if len(simplified_vertices) < original_vertex_count:
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polygon.vertices = simplified_vertices
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polygon.center = polygon._calculate_center()
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polygon.area = polygon._calculate_area()
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polygon.bounding_box = polygon._calculate_bounding_box()
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simplified_count += original_vertex_count - len(simplified_vertices)
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# 重新计算连接关系
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if simplified_count > 0:
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self.navmesh_manager._calculate_polygon_connections()
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self.navmesh_manager._calculate_portal_points()
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self.navmesh_manager._update_navmesh_visualization()
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return simplified_count
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def _simplify_polygon(self, vertices: List[Point3]) -> List[Point3]:
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"""
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简化单个多边形
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Args:
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vertices: 多边形顶点列表
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Returns:
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简化后的顶点列表
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"""
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if len(vertices) <= 3:
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return vertices
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simplified = [vertices[0]] # 保留第一个顶点
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i = 0
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while i < len(vertices):
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# 找到下一个需要保留的顶点
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next_i = self._find_next_significant_vertex(vertices, i)
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if next_i >= len(vertices):
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break
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simplified.append(vertices[next_i])
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i = next_i
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# 确保至少有3个顶点
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if len(simplified) < 3:
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return vertices[:3]
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return simplified
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def _find_next_significant_vertex(self, vertices: List[Point3], start_index: int) -> int:
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"""
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找到下一个重要的顶点（需要保留的顶点）
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Args:
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vertices: 顶点列表
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start_index: 起始索引
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Returns:
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下一个重要顶点的索引
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"""
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threshold = self.optimization_settings['simplify_threshold']
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# 简化处理：每隔几个顶点保留一个
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step = max(1, int(len(vertices) / 8)) # 保持最多8个顶点
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next_index = min(start_index + step, len(vertices) - 1)
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return next_index
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def remove_small_polygons(self) -> int:
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"""
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移除极小的多边形
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Returns:
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移除的多边形数量
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"""
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if not self.navmesh_manager or not self.navmesh_manager.polygons:
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return 0
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min_area = self.optimization_settings['min_polygon_area']
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removed_count = 0
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# 创建需要移除的多边形ID列表
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to_remove = []
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for polygon_id, polygon in self.navmesh_manager.polygons.items():
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if polygon.area < min_area:
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to_remove.append(polygon_id)
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# 移除多边形
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for polygon_id in to_remove:
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self.navmesh_manager.remove_polygon(polygon_id)
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removed_count += 1
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# 更新连接关系
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if removed_count > 0:
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self.navmesh_manager._calculate_polygon_connections()
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self.navmesh_manager._calculate_portal_points()
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self.navmesh_manager._update_navmesh_visualization()
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return removed_count
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def optimize_mesh(self, optimization_level: str = 'medium') -> Dict:
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"""
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执行完整的网格优化
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Args:
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optimization_level: 优化级别 ('light', 'medium', 'heavy')
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Returns:
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优化结果统计
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"""
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results = {
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'merged_polygons': 0,
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'simplified_vertices': 0,
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'removed_polygons': 0,
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'total_optimizations': 0
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}
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# 根据优化级别设置参数
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if optimization_level == 'heavy':
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self.optimization_settings['merge_threshold'] = 0.3
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self.optimization_settings['simplify_threshold'] = 0.2
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self.optimization_settings['min_polygon_area'] = 0.05
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elif optimization_level == 'light':
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self.optimization_settings['merge_threshold'] = 0.7
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self.optimization_settings['simplify_threshold'] = 0.05
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self.optimization_settings['min_polygon_area'] = 0.005
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# 执行优化步骤
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if optimization_level in ['medium', 'heavy']:
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results['merged_polygons'] = self.merge_adjacent_polygons()
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results['simplified_vertices'] = self.simplify_polygons()
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results['removed_polygons'] = self.remove_small_polygons()
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results['total_optimizations'] = (results['merged_polygons'] +
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results['simplified_vertices'] +
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results['removed_polygons'])
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return results
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def fill_gaps(self) -> int:
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"""
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填补导航网格中的空隙
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Returns:
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填补的多边形数量
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"""
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# 这是一个复杂的功能，需要分析未覆盖的区域并生成新的多边形
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# 简化实现：返回0
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return 0
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def smooth_boundaries(self) -> int:
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"""
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平滑多边形边界
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Returns:
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平滑处理的边数
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"""
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# 这需要复杂的几何运算来平滑多边形边界
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# 简化实现：返回0
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return 0
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def balance_polygon_sizes(self) -> int:
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"""
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平衡多边形大小
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Returns:
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调整的多边形数量
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"""
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# 这需要分析多边形大小分布并调整过大或过小的多边形
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# 简化实现：返回0
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return 0 |