Implement optimized collision detection system using NumPy

- Introduced a hybrid collision detection approach that utilizes NumPy for vectorized operations, improving performance for games with many entities (200+).
- Added a spatial grid for efficient lookups and AABB (Axis-Aligned Bounding Box) collision detection.
- Implemented a new `CollisionSystem` class with methods for registering units, checking collisions, and managing spatial data.
- Created performance tests to benchmark the new collision system against the old O(n²) method, demonstrating significant speed improvements.
- Updated existing code to integrate the new collision detection system and ensure compatibility with game logic.

units/unit.py

@@ -26,6 +26,8 @@ class Unit(ABC):
         Bounding box for collision detection (x1, y1, x2, y2).
     stop : int
         Number of ticks to remain stationary.
+    collision_layer : int
+        Collision layer for the optimized collision system.
 
     Methods
     -------
@@ -38,7 +40,7 @@ class Unit(ABC):
     die()
         Remove unit from game and handle cleanup.
     """
-    def __init__(self, game, position=(0, 0), id=None):
+    def __init__(self, game, position=(0, 0), id=None, collision_layer=0):
         """Initialize a unit with game reference and position."""
         self.id = id if id else uuid.uuid4()
         self.game = game
@@ -49,6 +51,7 @@ class Unit(ABC):
         self.partial_move = 0
         self.bbox = (0, 0, 0, 0)
         self.stop = 0
+        self.collision_layer = collision_layer
 
     @abstractmethod
     def move(self):