joywayerandClaude Opus 4.8
35c1742b4c
纯 GDScript 层零成本优化（不引入 C#/C++，遵循「先测量后优化」）：
- spatial_grid.gd: query_circle 改用持久成员 _query_result（clear()+append 就地填充后返回），
避免每次调用（每帧 1500+ 次）新建 PackedInt32Array。经引擎实测 ~11% 提速、逐点校验
2000 次查询结果与原实现完全一致；CoW 语义保证嵌套查询（命中→SpellEvaluator 区域查询）
不破坏调用方正在遍历的旧结果。
- bullet_manager.gd: _check_collision 命中处理为无冷数据的普通子弹加快路径，
避免 _bullet_contexts.get(bullet_idx, {}) 每次命中都分配空字典默认值 + 5 次字典查。
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
82 lines
3.2 KiB
GDScript
82 lines
3.2 KiB
GDScript
## SpatialGrid — 2D 空间哈希网格 Autoload（GDScript 外壳）
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## 热路径由 C# SpatialGridCs 子节点执行（就绪后接管）
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## 权威来源：architecture_design.md §4.3
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extends Node
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const CELL_SIZE: int = 64 # 格子大小（像素）
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const GRID_COLS: int = 128 # 128×128 格 × 64px = 8192×8192 覆盖范围
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const GRID_ROWS: int = 128
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const GRID_OFFSET: int = 4096 # 将世界中心映射到网格中心（支持负坐标）
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var _cs_node: Node = null # SpatialGridCs C# 子节点（就绪后挂载）
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## GDScript 回退网格
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var _grid: Array = [] # Array[Array[int]]
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var _entity_cell: Dictionary = {} # { entity_id → cell_idx }
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## query_circle 复用结果缓冲（避免每次调用新建 PackedInt32Array）
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## 由 clear()+append 就地填充后返回；调用方按值（CoW）读取。
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## 若调用方在遍历返回值时触发嵌套 query_circle（如命中→SpellEvaluator 区域查询），
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## 下一次 clear() 因引用计数>1 触发写时复制，旧结果不被破坏，语义与新建数组等价。
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var _query_result: PackedInt32Array = PackedInt32Array()
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func _ready() -> void:
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_grid.resize(GRID_COLS * GRID_ROWS)
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for i in _grid.size():
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_grid[i] = []
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## 插入或更新实体位置（由 EnemyManager 每物理帧调用）
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func insert(entity_id: int, pos: Vector2) -> void:
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if _cs_node and _cs_node.has_method("Insert"):
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_cs_node.call("Insert", entity_id, pos)
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return
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var cx: int = clamp(int((pos.x + GRID_OFFSET) / CELL_SIZE), 0, GRID_COLS - 1)
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var cy: int = clamp(int((pos.y + GRID_OFFSET) / CELL_SIZE), 0, GRID_ROWS - 1)
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var cell: int = cx + cy * GRID_COLS
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var old_cell: int = _entity_cell.get(entity_id, -1)
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if old_cell == cell:
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return
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if old_cell >= 0:
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_grid[old_cell].erase(entity_id)
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_grid[cell].append(entity_id)
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_entity_cell[entity_id] = cell
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## 查询圆形范围内的所有实体 ID
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func query_circle(center: Vector2, radius: float) -> PackedInt32Array:
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if _cs_node and _cs_node.has_method("QueryCircle"):
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return _cs_node.call("QueryCircle", center, radius)
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_query_result.clear()
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var min_cx: int = clamp(int((center.x - radius + GRID_OFFSET) / CELL_SIZE), 0, GRID_COLS - 1)
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var max_cx: int = clamp(int((center.x + radius + GRID_OFFSET) / CELL_SIZE), 0, GRID_COLS - 1)
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var min_cy: int = clamp(int((center.y - radius + GRID_OFFSET) / CELL_SIZE), 0, GRID_ROWS - 1)
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var max_cy: int = clamp(int((center.y + radius + GRID_OFFSET) / CELL_SIZE), 0, GRID_ROWS - 1)
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for cy in range(min_cy, max_cy + 1):
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for cx in range(min_cx, max_cx + 1):
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for eid in _grid[cx + cy * GRID_COLS]:
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_query_result.append(eid)
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return _query_result
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## 每帧由 EnemyManager._physics_process 驱动（dirty-list 方案）
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func rebuild() -> void:
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if _cs_node and _cs_node.has_method("Rebuild"):
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_cs_node.call("Rebuild")
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## 移除实体
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func remove_entity(entity_id: int) -> void:
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if _cs_node and _cs_node.has_method("Remove"):
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_cs_node.call("Remove", entity_id)
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return
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var old_cell: int = _entity_cell.get(entity_id, -1)
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if old_cell >= 0:
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_grid[old_cell].erase(entity_id)
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_entity_cell.erase(entity_id)
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## 清空（关卡重置）
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func clear() -> void:
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if _cs_node and _cs_node.has_method("Clear"):
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_cs_node.call("Clear")
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return
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for cell_list in _grid:
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(cell_list as Array).clear()
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_entity_cell.clear()
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