ddimunzio/bot-detector

1import glob2import csv3import sys4from bot_detector_engine import analyze_file5 6files = glob.glob('cqww-cw/*.log') + glob.glob('cqww-ssb/*.log')7headers = ['file', 'callsign', 'mode', 'multi_tx', 'score', 'verdict', 'p_bot', 'p_suspicious', 'p_human', 'prior', 'log_lr', 'fatigue_flat', 'isfe_flag', 'bsiq_flag', 'cpd_flag']8writer = csv.DictWriter(sys.stdout, fieldnames=headers)9writer.writeheader()10 11results = []12for f in files:13    try:14        r = analyze_file(f)15        mode = 'CW' if 'cqww-cw' in f else 'SSB'16        17        # Determine isfe_flag, bsiq_flag, cpd_flag from metrics/artifacts18        # Adjusting to what might be available in result object based on previous turns19        isfe_f = 1 if r.metrics.get('isfe_detected') else 020        bsiq_f = 1 if r.metrics.get('bsiq_detected') else 021        cpd_f = 1 if r.metrics.get('cpd_detected') else 022        23        row = {24            'file': f,25            'callsign': r.callsign,26            'mode': mode,27            'multi_tx': r.multi_tx,28            'score': round(r.suspicion_score, 4),29            'verdict': r.verdict,30            'p_bot': round(r.bayes_p_bot, 4),31            'p_suspicious': round(r.bayes_p_suspicious, 4),32            'p_human': round(r.bayes_p_human, 4),33            'prior': round(r.bayes_prior, 4),34            'log_lr': round(r.log_likelihood_ratio, 4),35            'fatigue_flat': 1 if r.metrics.get('fatigue_penalty_applied') else 0,36            'isfe_flag': isfe_f,37            'bsiq_flag': bsiq_f,38            'cpd_flag': cpd_f39        }40        writer.writerow(row)41        results.append(row)42    except Exception as e:43        # sys.stderr.write(f'Error processing {f}: {e}\n')44        pass45 46# Summaries47print('\n--- Summaries ---')48by_mode = {}49for r in results:50    m = r['mode']51    if m not in by_mode: by_mode[m] = {'p_bot_sum': 0, 'count': 0, 'verdicts': {}}52    by_mode[m]['p_bot_sum'] += r['p_bot']53    by_mode[m]['count'] += 154    v = r['verdict']55    by_mode[m]['verdicts'][v] = by_mode[m]['verdicts'].get(v, 0) + 156 57for m, stats in by_mode.items():58    mean_p_bot = stats['p_bot_sum'] / stats['count'] if stats['count'] > 0 else 059    print(f'Mode: {m}, Mean P_Bot: {mean_p_bot:.4f}, Verdicts: {stats["verdicts"]}')60