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#!/usr/bin/env python3
"""Run multiple trials of iterative refinement to get statistics."""
import json
import os
import shutil
import sys
from pathlib import Path
# Run from the example directory
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)
# Clean output directory for each trial
output_dir = f"iterative_output_trial_{trial}"
if os.path.exists(output_dir):
shutil.rmtree(output_dir)
# Run trial
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"])
# Calculate statistics
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)
# Save summary
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)
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