| |
| """Run multiple trials of iterative refinement to get statistics.""" |
|
|
| import json |
| import os |
| import shutil |
| import sys |
| from pathlib import Path |
|
|
| |
| os.chdir(Path(__file__).parent) |
|
|
| from iterative_agent import run_iterative_refinement, load_config |
|
|
|
|
| def run_trials(num_trials: int = 10, max_iterations: int = 100): |
| """Run multiple trials and collect statistics.""" |
| config = load_config("config.yaml") |
|
|
| results = [] |
| solutions_found = [] |
|
|
| for trial in range(num_trials): |
| print(f"\n{'#'*60}") |
| print(f"# TRIAL {trial + 1}/{num_trials}") |
| print('#'*60) |
|
|
| |
| output_dir = f"iterative_output_trial_{trial}" |
| if os.path.exists(output_dir): |
| shutil.rmtree(output_dir) |
|
|
| |
| result = run_iterative_refinement( |
| initial_program="initial_program.py", |
| evaluator_path="evaluator.py", |
| config=config, |
| max_iterations=max_iterations, |
| output_dir=output_dir, |
| ) |
|
|
| results.append({ |
| "trial": trial, |
| "solution_found_at": result["solution_found_at"], |
| "final_best_score": result["final_best_score"], |
| "total_iterations": result["total_iterations"], |
| }) |
|
|
| if result["solution_found_at"] is not None: |
| solutions_found.append(result["solution_found_at"]) |
|
|
| |
| success_rate = len(solutions_found) / num_trials |
| avg_iterations = sum(solutions_found) / len(solutions_found) if solutions_found else float('inf') |
| min_iterations = min(solutions_found) if solutions_found else None |
| max_iterations_found = max(solutions_found) if solutions_found else None |
|
|
| print(f"\n{'='*60}") |
| print("ITERATIVE REFINEMENT TRIAL RESULTS") |
| print('='*60) |
| print(f"Trials: {num_trials}") |
| print(f"Max iterations per trial: {max_iterations}") |
| print(f"Success rate: {success_rate:.1%} ({len(solutions_found)}/{num_trials})") |
| if solutions_found: |
| print(f"Avg iterations to solution: {avg_iterations:.1f}") |
| print(f"Min iterations: {min_iterations}") |
| print(f"Max iterations: {max_iterations_found}") |
| print('='*60) |
|
|
| |
| summary = { |
| "config": { |
| "num_trials": num_trials, |
| "max_iterations": max_iterations, |
| }, |
| "summary": { |
| "success_rate": success_rate, |
| "avg_iterations_to_solution": avg_iterations if solutions_found else None, |
| "min_iterations": min_iterations, |
| "max_iterations": max_iterations_found, |
| "solutions_found": len(solutions_found), |
| }, |
| "trials": results, |
| } |
|
|
| with open("iterative_trials_results.json", "w") as f: |
| json.dump(summary, f, indent=2) |
|
|
| print(f"\nResults saved to: iterative_trials_results.json") |
|
|
| return summary |
|
|
|
|
| if __name__ == "__main__": |
| import argparse |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--trials", type=int, default=10, help="Number of trials") |
| parser.add_argument("--iterations", type=int, default=100, help="Max iterations per trial") |
| args = parser.parse_args() |
|
|
| run_trials(num_trials=args.trials, max_iterations=args.iterations) |
|
|
