import pandas as pd, numpy as np
RUN = '/mnt/d/Resonance_Engine/traj/tension_20260608T061636'
A = pd.read_parquet(f'{RUN}/arm_A_no_inject.parquet')
T = pd.read_parquet(f'{RUN}/arm_T_tension.parquet')

print('cols A:', list(A.columns))
print(f'A rows={len(A)}  T rows={len(T)}')
print()

print('=== tension columns finite-count in arm T ===')
for c in ['funding_bps', 'bs_ratio_signed', 'activity_excess', 'cvd_divergence',
          'funding_bps_level', 'bs_ratio_signed_level', 'activity_excess_level', 'cvd_divergence_level',
          'funding_bps_vel', 'bs_ratio_signed_vel', 'activity_excess_vel', 'cvd_divergence_vel']:
    if c in T.columns:
        v = T[c].values
        fin = np.isfinite(v).sum()
        print(f'  {c:32s} fin={fin}/{len(v)}  mean={np.nanmean(v):+.4g}  std={np.nanstd(v):+.4g}')
    else:
        print(f'  {c:32s} MISSING')

print()
print('=== arm A vs T telemetry channel deltas (last 500 rows, skip warmup) ===')
chans = ['asymmetry', 'coherence', 'stress_xx', 'stress_yy', 'stress_xy', 'vorticity_mean', 'vel_mean', 'vel_max', 'vel_var']
A2 = A.iloc[300:]
T2 = T.iloc[300:]
hdr = f'{"channel":<18} {"A mean":>14} {"T mean":>14} {"A std":>14} {"T std":>14}  {"delta/A_std":>14}'
print(hdr)
for c in chans:
    am, asd = A2[c].mean(), A2[c].std()
    tm, tsd = T2[c].mean(), T2[c].std()
    d = (tm - am) / asd if asd > 0 else 0
    print(f'  {c:<16} {am:>14.4g} {tm:>14.4g} {asd:>14.4g} {tsd:>14.4g}  {d:>14.2f}')

print()
print('snap_age_ms p50/p95/p99 arm A:', np.percentile(A.snap_age_ms, [50, 95, 99]))
print('snap_age_ms p50/p95/p99 arm T:', np.percentile(T.snap_age_ms, [50, 95, 99]))
print('snap_age_ms max arm A:', A.snap_age_ms.max(), '  arm T:', T.snap_age_ms.max())