scripts/batch_experiment.py

import sys
import os
import json
import time
import numpy as np
from datetime import datetime

# Adicionar o diretório raiz ao path para importar o core
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from core.logic import SVCA_Core

def run_batch(n_runs=1000):
    print(f"Starting batch experiment: {n_runs} runs...")
    results = []
    start_time = time.time()
    
    core = SVCA_Core()
    
    for i in range(n_runs):
        res = core.compute_algebra(f"run_{i}")
        results.append(res)
        if (i + 1) % 200 == 0:
            print(f"Progress: {i+1}/{n_runs}")
            
    end_time = time.time()
    duration = end_time - start_time
    
    # Calcular métricas
    psi_values = [r['psi'] for r in results]
    omega_values = [r['omega'] for r in results]
    
    metrics = {
        "n_runs": n_runs,
        "duration_sec": duration,
        "avg_psi": np.mean(psi_values),
        "std_psi": np.std(psi_values),
        "avg_omega": np.mean(omega_values),
        "std_omega": np.std(omega_values),
        "success_rate": sum(1 for r in results if r['status'] == "VALID") / n_runs,
        "timestamp": datetime.now().isoformat()
    }
    
    # Salvar resultados
    os.makedirs('data', exist_ok=True)
    with open('data/experiment_results.json', 'w') as f:
        json.dump({"metrics": metrics, "raw": results}, f, indent=2)
        
    print(f"Experiment completed in {duration:.2f}s")
    print(f"Average PSI: {metrics['avg_psi']:.4f}")
    print(f"Average OMEGA: {metrics['avg_omega']:.4f}")
    print(f"Success Rate: {metrics['success_rate']*100:.2f}%")
    
    return metrics

if __name__ == "__main__":
    run_batch(1024) # Usando 1024 como sugerido no BULK.txt