Updates

Things/Ant_Colony/ant_colony/main.py

@@ -5,8 +5,8 @@ Main entry point for the ant colony simulation.
 import argparse
 import yaml
 import numpy as np
-from ant_colony.visualization import SimulationRenderer
-from ant_colony.agents import Nestmate, Position, TaskType
+from visualization.renderer import SimulationRenderer
+from agents.nestmate import Nestmate, Position
 from dataclasses import dataclass
 from typing import List
 

Things/Ant_Colony/main.py

@@ -1,164 +0,0 @@
-"""
-Main entry point for the ant colony simulation.
-"""
-
-import argparse
-import yaml
-import numpy as np
-from visualization.renderer import SimulationRenderer
-from agents.nestmate import Nestmate, Position
-from dataclasses import dataclass
-from typing import List
-
-@dataclass
-class FoodSource:
-    """Represents a food source in the environment."""
-    position: Position
-    size: float
-    value: float
-    remaining: float
-
-@dataclass
-class Obstacle:
-    """Represents an obstacle in the environment."""
-    position: Position
-    size: float
-
-class Simulation:
-    """Main simulation class."""
-    
-    def __init__(self, config_path: str):
-        """Initialize simulation with configuration."""
-        with open(config_path, 'r') as f:
-            self.config = yaml.safe_load(f)
-            
-        # Set random seed
-        np.random.seed(self.config['simulation']['random_seed'])
-        
-        # Initialize environment
-        self.env_size = self.config['environment']['size']
-        self.nest_location = self.config['environment']['nest_location']
-        
-        # Initialize agents
-        self.agents = self._create_agents()
-        
-        # Initialize resources
-        self.food_sources = self._create_food_sources()
-        self.obstacles = self._create_obstacles()
-        
-        # Initialize pheromone grids
-        self.pheromones = {
-            'food': np.zeros(self.env_size),
-            'home': np.zeros(self.env_size)
-        }
-        
-        # Setup visualization if enabled
-        if self.config['visualization']['enabled']:
-            self.renderer = SimulationRenderer(self.config)
-        else:
-            self.renderer = None
-            
-    def _create_agents(self) -> List[Nestmate]:
-        """Create initial population of agents."""
-        agents = []
-        for _ in range(self.config['colony']['initial_population']):
-            # Start agents near nest
-            x = self.nest_location[0] + np.random.normal(0, 2)
-            y = self.nest_location[1] + np.random.normal(0, 2)
-            theta = np.random.uniform(0, 2 * np.pi)
-            
-            agent = Nestmate(self.config['agent'])
-            agent.position = Position(x, y, theta)
-            agents.append(agent)
-            
-        return agents
-        
-    def _create_food_sources(self) -> List[FoodSource]:
-        """Create initial food sources."""
-        sources = []
-        for _ in range(self.config['environment']['food_sources']['count']):
-            x = np.random.uniform(0, self.env_size[0])
-            y = np.random.uniform(0, self.env_size[1])
-            size = np.random.uniform(*self.config['environment']['food_sources']['size_range'])
-            value = np.random.uniform(*self.config['environment']['food_sources']['value_range'])
-            
-            source = FoodSource(
-                position=Position(x, y, 0),
-                size=size,
-                value=value,
-                remaining=value
-            )
-            sources.append(source)
-            
-        return sources
-        
-    def _create_obstacles(self) -> List[Obstacle]:
-        """Create initial obstacles."""
-        obstacles = []
-        for _ in range(self.config['environment']['obstacles']['count']):
-            x = np.random.uniform(0, self.env_size[0])
-            y = np.random.uniform(0, self.env_size[1])
-            size = np.random.uniform(*self.config['environment']['obstacles']['size_range'])
-            
-            obstacle = Obstacle(
-                position=Position(x, y, 0),
-                size=size
-            )
-            obstacles.append(obstacle)
-            
-        return obstacles
-        
-    def update(self) -> None:
-        """Update simulation state for one timestep."""
-        dt = self.config['simulation']['timestep']
-        
-        # Update agents
-        world_state = {
-            'agents': self.agents,
-            'resources': self.food_sources,
-            'obstacles': self.obstacles,
-            'pheromones': self.pheromones
-        }
-        
-        for agent in self.agents:
-            agent.update(dt, world_state)
-            
-        # Update pheromones
-        decay = self.config['environment']['pheromone_decay']
-        self.pheromones['food'] *= decay
-        self.pheromones['home'] *= decay
-        
-        # Update visualization
-        if self.renderer and self.config['visualization']['enabled']:
-            self.renderer.update(world_state)
-            
-    def run(self) -> None:
-        """Run the simulation."""
-        max_steps = self.config['simulation']['max_steps']
-        
-        try:
-            for step in range(max_steps):
-                self.update()
-                
-                if step % 100 == 0:
-                    print(f"Step {step}/{max_steps}")
-                    
-        except KeyboardInterrupt:
-            print("\nSimulation interrupted by user")
-            
-        finally:
-            if self.renderer:
-                self.renderer.show()
-                
-def main():
-    """Main entry point."""
-    parser = argparse.ArgumentParser(description="Ant Colony Simulation")
-    parser.add_argument('--config', type=str, required=True,
-                      help='Path to configuration file')
-    args = parser.parse_args()
-    
-    simulation = Simulation(args.config)
-    simulation.run()
-    
-if __name__ == '__main__':
-    main() 

ant_colony/main.py

@@ -0,0 +1,59 @@
+"""
+Main entry point for the ant colony simulation.
+"""
+
+import argparse
+import yaml
+import numpy as np
+from ant_colony.visualization.renderer import SimulationRenderer
+from ant_colony.agents.nestmate import Nestmate, Position, TaskType
+from dataclasses import dataclass
+from typing import List
+
+@dataclass
+class FoodSource:
+    """Represents a food source in the environment."""
+    position: Position
+    size: float
+    value: float
+    remaining: float
+
+@dataclass
+class Obstacle:
+    """Represents an obstacle in the environment."""
+    position: Position
+    size: float
+
+class Simulation:
+    """Main simulation class."""
+    
+    def __init__(self, config_path: str):
+        """Initialize simulation with configuration."""
+        with open(config_path, 'r') as f:
+            self.config = yaml.safe_load(f)
+            
+        # Set random seed
+        np.random.seed(self.config['simulation']['random_seed'])
+        
+        # Initialize environment
+        self.env_size = self.config['environment']['size']
+        self.nest_location = self.config['environment']['nest_location']
+        
+        # Initialize agents
+        self.agents = self._create_agents()
+        
+        # Initialize resources
+        self.food_sources = self._create_food_sources()
+        self.obstacles = self._create_obstacles()
+        
+        # Initialize pheromone grids
+        self.pheromones = {
+            'food': np.zeros(self.env_size),
+            'home': np.zeros(self.env_size)
+        }
+        
+        # Setup visualization if enabled
+        if self.config['visualization']['realtime']['enabled']:
+            self.renderer = SimulationRenderer(self.config)
+        else:
+            self.renderer = None 

config/simulation_config.yaml

@@ -0,0 +1,19 @@
+# Visualization settings
+visualization:
+  enabled: true
+  update_interval: 1  # Update every N timesteps
+  trail_length: 50  # Number of positions to keep for trails
+  colors:
+    background: [255, 255, 255]
+    obstacles: [100, 100, 100]
+    food: [0, 255, 0]
+    nest: [139, 69, 19]
+    agents:
+      foraging: [255, 0, 0]
+      maintenance: [0, 0, 255]
+      nursing: [255, 192, 203]
+      defense: [128, 0, 0]
+      exploration: [255, 165, 0]
+    pheromones:
+      food: [0, 255, 0, 128]
+      home: [255, 0, 0, 128] 

main.py

@@ -0,0 +1,13 @@
+"""
+Main entry point for the ant colony simulation.
+"""
+
+import argparse
+import yaml
+import numpy as np
+from ant_colony.visualization.renderer import SimulationRenderer
+from ant_colony.agents.nestmate import Nestmate, Position, TaskType
+from dataclasses import dataclass
+from typing import List
+
+# ... existing code ...