[READ-ONLY] Mirror of https://github.com/jmrplens/PyOctaveBand. [Python3] Octave-Band and Fractional Octave-Band filter. For signal in time domain.
jmrplens.github.io/PyOctaveBand/
acoustics
audio
filter
frequency
frequency-analysis
frequency-domain
octave
python3
signal
time-domain
feat(aircraft): EPNL flyover figure (x4 variants)
José M. Requena Plens
(Jul 12, 2026, 5:30 PM +0200)
9905f609
c66b5132
+2219
+542
.github/images/epnl.svg
+542
.github/images/epnl.svg
···
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+51
scripts/generate_graphs.py
+51
scripts/generate_graphs.py
···
525
525
"Pressure [Pa]": "Presión [Pa]",
526
526
"Number of strikes N": "Número de golpes N",
527
527
"Cumulative SEL [dB re 1 µPa²·s]": "SEL acumulado [dB re 1 µPa²·s]",
528
+
"ICAO Aircraft Flyover — Effective Perceived Noise Level (Annex 16)":
529
+
"Sobrevuelo de aeronave ICAO — Nivel efectivo de ruido percibido (Anexo 16)",
530
+
"Level [PNdB]": "Nivel [PNdB]",
531
+
"10 dB-down window": "Ventana 10 dB por debajo",
528
532
# Building acoustics (EN 12354-1 flanking prediction, ISO 12999-1 uncertainty)
529
533
"EN 12354-1 Flanking Transmission (Annex H.3 example)":
530
534
"Transmisión por flancos EN 12354-1 (ejemplo del Anexo H.3)",
···
3308
3312
plt.close()
3309
3313
3310
3314
3315
+
def generate_epnl(output_dir: str) -> None:
3316
+
"""ICAO aircraft-flyover EPNL: PNL/PNLT time history with the 10 dB-down window."""
3317
+
print("Generating epnl...")
3318
+
from phonometry import NOY_BANDS, effective_perceived_noise_level
3319
+
3320
+
k = 41
3321
+
dt = 0.5
3322
+
idx = np.arange(k)
3323
+
# Broadband flyover spectrum with a mid-frequency emphasis, modulated by a
3324
+
# Gaussian overall-level envelope; a fan tone in the 2500 Hz band adds a
3325
+
# tone correction near the closest-point-of-approach.
3326
+
shape = 15.0 * np.exp(-((np.log10(NOY_BANDS) - np.log10(400.0)) ** 2) / 0.5)
3327
+
gain = 30.0 * np.exp(-((idx - 20.0) ** 2) / (2 * 5.0**2)) - 5.0
3328
+
spectra = (55.0 + shape)[None, :] + gain[:, None]
3329
+
spectra[:, 17] += 12.0 * np.exp(-((idx - 20.0) ** 2) / (2 * 6.0**2))
3330
+
res = effective_perceived_noise_level(spectra, dt)
3331
+
kf, kl = res.band_limits
3332
+
3333
+
fig, ax = plt.subplots(figsize=(10, 6))
3334
+
ax.axvspan(res.times[kf], res.times[kl], color=COLOR_TERTIARY, alpha=0.15,
3335
+
label="10 dB-down window")
3336
+
ax.plot(res.times, res.pnl, color="#8c8c8c", linestyle="--", linewidth=1.4,
3337
+
label="PNL")
3338
+
ax.plot(res.times, res.pnlt, color=COLOR_PRIMARY, linewidth=2.2, label="PNLT")
3339
+
km = int(np.argmax(res.pnlt))
3340
+
ax.plot([res.times[km]], [res.pnltm], "o", color=COLOR_SECONDARY, markersize=9,
3341
+
label=f"PNLTM = {res.pnltm:.1f} PNdB")
3342
+
ax.set_xlabel("Time [s]")
3343
+
ax.set_ylabel("Level [PNdB]")
3344
+
ax.set_title(
3345
+
"ICAO Aircraft Flyover — Effective Perceived Noise Level (Annex 16)",
3346
+
fontweight="bold", pad=12)
3347
+
ax.grid(color=COLOR_GRID, linestyle="--", alpha=0.5)
3348
+
ax.set_axisbelow(True)
3349
+
ax.legend(loc="upper right", fontsize=9)
3350
+
ax.text(0.02, 0.95,
3351
+
f"EPNL = {res.epnl:.1f} EPNdB\nD = {res.duration_correction:+.1f} dB",
3352
+
transform=ax.transAxes, va="top", fontsize=10,
3353
+
bbox={"boxstyle": "round", "facecolor": COLOR_GRID, "alpha": 0.6})
3354
+
plt.tight_layout()
3355
+
save_figure(output_dir, "epnl.svg")
3356
+
plt.close()
3357
+
3358
+
3311
3359
@lru_cache(maxsize=None)
3312
3360
def _time_loudness_data() -> tuple[np.ndarray, np.ndarray, np.ndarray]:
3313
3361
"""ISO 532-3 STL(t)/LTL(t) for a 1 kHz / 60 dB burst (on 200-400 ms)."""
···
5725
5773
# level (ISO 17208) and pile-driving sound exposure (ISO 18406).
5726
5774
generate_ship_source_level(img_dir)
5727
5775
generate_pile_driving(img_dir)
5776
+
5777
+
# Aircraft noise (plan-19B): ICAO Annex 16 Effective Perceived Noise Level.
5778
+
generate_epnl(img_dir)
5728
5779
5729
5780
5730
5781
# ===========================================================================