#!/usr/bin/env python3 """ Maze Visualization Utility This script provides easy-to-use functions for visualizing mazes with optimal paths and model solutions. Supports multiple visualization modes: - Empty maze (just structure) - Optimal path only - Model path only - Side-by-side comparison Usage Examples: # Side-by-side comparison (default) python maze_visualizer_utility.py --maze_id 91 --result_file results/.../91_run3.json # Individual plots python maze_visualizer_utility.py --maze_id 91 --mode empty python maze_visualizer_utility.py --maze_id 91 --mode optimal python maze_visualizer_utility.py --maze_id 91 --result_file results/.../91_run3.json --mode model """ import sys import os sys.path.append(os.path.join(os.path.dirname(__file__), '..')) sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'core')) import json import ast import argparse from pathlib import Path from core.maze_loader import MazeLoader from plot import pretty_plot_maze def load_maze_data(maze_id, data_dir="data/emnlp/maze_40_40_2_True"): """Load maze data from pickle file.""" maze_file = os.path.join(data_dir, f"{maze_id}.pkl") if not os.path.exists(maze_file): raise FileNotFoundError(f"Maze file not found: {maze_file}") loader = MazeLoader(maze_file, removed_key_count=0) return loader, maze_file def get_optimal_solution_room_names(loader): """Get optimal solution in room name format (the correct format for plot.py).""" return loader.solution_with_room_names def load_model_solution_from_json(json_file): """Load model solution from JSON result file (already in room name format).""" with open(json_file, 'r') as f: result_data = json.load(f) solution_str = result_data['response'] solution_list = ast.literal_eval(solution_str) return solution_list, result_data def visualize_maze(maze_id, result_file=None, output_path=None, mode="comparison", data_dir="data/emnlp/maze_40_40_2_True"): """ Main visualization function with support for different modes. Args: maze_id: ID of the maze (e.g., '91') result_file: Path to JSON result file with model solution output_path: Where to save the visualization (auto-generated if None) mode: Visualization mode ("comparison", "empty", "optimal", "model") data_dir: Directory containing maze .pkl files """ print(f"Loading maze {maze_id}...") loader, maze_file = load_maze_data(maze_id, data_dir) print(f"Getting optimal solution...") optimal_solution = get_optimal_solution_room_names(loader) model_solution = None model_info = "optimal_only" if result_file and mode in ["comparison", "model"]: print(f"Loading model solution from {result_file}...") model_solution, result_data = load_model_solution_from_json(result_file) provider = result_data.get('provider', 'unknown') model_name = result_data.get('model_name', 'unknown') model_info = f"{provider}_{model_name}" # Generate output path if not provided if output_path is None: if mode == "empty": output_path = f"maze_{maze_id}_empty.png" elif mode == "optimal": output_path = f"maze_{maze_id}_optimal.png" elif mode == "model": output_path = f"maze_{maze_id}_model_{model_info}.png" else: # comparison output_path = f"maze_{maze_id}_comparison_{model_info}.png" print(f"Creating {mode} visualization...") print(f" • Maze: {maze_id}") print(f" • Mode: {mode}") print(f" • Start: {loader.data['start_room']} ({loader.room_name[loader.data['start_room']]})") print(f" • End: {loader.data['end_room']} ({loader.room_name[loader.data['end_room']]})") if mode in ["comparison", "optimal"]: print(f" • Optimal steps: {len(optimal_solution)}") if mode in ["comparison", "model"] and model_solution: print(f" • Model steps: {len(model_solution)}") pretty_plot_maze( loader, save_path=output_path, model_solution=model_solution, ground_truth_solution=optimal_solution, mode=mode ) print(f"Visualization saved: {output_path}") return output_path # Convenience functions for each mode def plot_empty_maze(maze_id, output_path=None, data_dir="data/emnlp/maze_40_40_2_True"): """Plot just the maze structure without any paths.""" return visualize_maze(maze_id, mode="empty", output_path=output_path, data_dir=data_dir) def plot_optimal_path(maze_id, output_path=None, data_dir="data/emnlp/maze_40_40_2_True"): """Plot maze with optimal path only.""" return visualize_maze(maze_id, mode="optimal", output_path=output_path, data_dir=data_dir) def plot_model_path(maze_id, result_file, output_path=None, data_dir="data/emnlp/maze_40_40_2_True"): """Plot maze with model path only.""" return visualize_maze(maze_id, result_file=result_file, mode="model", output_path=output_path, data_dir=data_dir) def plot_comparison(maze_id, result_file, output_path=None, data_dir="data/emnlp/maze_40_40_2_True"): """Plot side-by-side comparison of optimal vs model paths.""" return visualize_maze(maze_id, result_file=result_file, mode="comparison", output_path=output_path, data_dir=data_dir) def main(): parser = argparse.ArgumentParser(description="Visualize maze solutions with different modes") parser.add_argument("--maze_id", required=True, help="Maze ID (e.g., '91')") parser.add_argument("--result_file", help="Path to JSON result file") parser.add_argument("--output_path", help="Output path for visualization") parser.add_argument("--mode", default="comparison", choices=["comparison", "empty", "optimal", "model"], help="Visualization mode") parser.add_argument("--data_dir", default="data/emnlp/maze_40_40_2_True", help="Directory containing maze files") args = parser.parse_args() # Validate mode requirements if args.mode == "model" and not args.result_file: print("Error: --result_file is required for 'model' mode") return if args.mode == "comparison" and not args.result_file: print("Error: --result_file is required for 'comparison' mode") return visualize_maze( maze_id=args.maze_id, result_file=args.result_file, output_path=args.output_path, mode=args.mode, data_dir=args.data_dir ) if __name__ == "__main__": main() # Convenience functions for interactive use def quick_visualize(maze_id, result_file=None, mode="comparison"): """Quick visualization function for interactive use.""" return visualize_maze(maze_id, result_file, mode=mode) def show_available_mazes(data_dir="data/emnlp/maze_40_40_2_True"): """List available maze IDs.""" maze_files = list(Path(data_dir).glob("*.pkl")) maze_ids = [f.stem for f in maze_files] return sorted(maze_ids, key=int) def demo_all_modes(): """Demonstrate all visualization modes.""" print("MAZE VISUALIZATION MODES DEMO") print("=" * 50) maze_id = "91" result_file = "results/openai_gpt5_3shot_guided_cot_effectiveB2_origB2/maze_40_40_2_True/openai/gpt-5/91_removed_keys0_locked_doors2_shuffle0.0_noise0.0_run3.json" modes = ["empty", "optimal", "model", "comparison"] for mode in modes: print(f"\nCreating {mode} visualization...") try: if mode in ["model", "comparison"] and not os.path.exists(result_file): print(f" Skipping {mode} - result file not found") continue output_path = visualize_maze(maze_id, result_file if mode in ["model", "comparison"] else None, mode=mode) print(f" Created: {output_path}") except Exception as e: print(f" Error: {e}") print(f"\nDemo completed!") if __name__ == "__main__": if len(sys.argv) == 1: print("\n" + "=" * 50) demo_all_modes() else: main()