maad.spl.apply_attenuation

maad.spl.apply_attenuation(p0, fs, r, r0=1, t=20, rh=60, pa=101325, a0=0.02)[source]

Apply attenuation of a temporal signal p0 after propagation between the reference distance r0 and the final distance r taken into account the geometric, atmospheric and habitat attenuation contributions.

Parameters:

p0array-like (vector 1d): temporal signal p0 in Pa (time domain)
fs: scalar: sampling frequency Hz
r: scalar: distance of propagation (in m) of the signal p0
r0scalar: distance at which the temporal signal p0 was measured
t: scalar, optional, default is 20: temperature in °C
rh: scalar, optional, default is 60: relative humidity in %
pa: scalar, optional, default is 101325: atmospheric pressure in Pa
a0scalar, optional, default is 0.02: attenuation coefficient of the habitat in dB/kHz/m

Returns:

parray-like (vector 1d): temporal signal (time domain) after attenuation

Examples

Prepare the spinetail sound (Sound level @1m = 85dB SPL).

>>> w, fs = maad.sound.load('../data/spinetail.wav') 
>>> p0 = maad.spl.wav2pressure(wave=w, gain=42)
>>> p0_sig = p0[int(5.68*fs):int(7.48*fs)] 
>>> p0_noise = p0[int(8.32*fs):int(10.12*fs)] 
>>> Sxx_power, tn, fn, ext = maad.sound.spectrogram(p0_sig ,fs)
>>> Sxx_power_noise, tn, fn, ext = maad.sound.spectrogram(p0_noise ,fs)
>>> Sxx_dB = maad.util.power2dB(Sxx_power, db_range=96) + 96
>>> Sxx_dB_noise = maad.util.power2dB(Sxx_power_noise, db_range=96) + 96

Get the sound level of the spinetail song (sound between 4900-7500 Hz).

>>> p0_sig_4900_7500 = maad.sound.select_bandwidth(p0_sig,fs,fcut=[4900,7300],forder=10, ftype='bandpass')
>>> L = maad.spl.pressure2leq(p0_sig_4900_7500, fs) 
>>> print ('Sound Level measured : %2.2fdB SPL' %L)

Estimate maximum distance from the source.

>>> r = maad.spl.active_distance(L, 85, f=(7500+4900)/2) 

plot original spectrogram

>>> import matplotlib.pyplot as plt
>>> fig, (ax1, ax2, ax3, ax4, ax5) = plt.subplots(1,5, sharex=True, figsize=(15,3))
>>> maad.util.plot2d(Sxx_dB, ax=ax1, extent=ext, vmin=0, vmax=70, figsize=[3,3])

Compute the audio attenuation at 10m.

>>> p_att = maad.spl.apply_attenuation(p0_sig, fs, r0=5, r =10)
>>> Sxx_power_att, tn, fn, ext = maad.sound.spectrogram(p_att,fs)
>>> Sxx_dB_att_10m = maad.util.power2dB(Sxx_power_att,db_range=96) + 96 

>>> p_att = maad.spl.apply_attenuation(p0_sig, fs, r0=5, r =20)
>>> Sxx_power_att, tn, fn, ext = maad.sound.spectrogram(p_att,fs)
>>> Sxx_dB_att_20m = maad.util.power2dB(Sxx_power_att,db_range=96) + 96 

>>> p_att = maad.spl.apply_attenuation(p0_sig, fs, r0=5, r =40)
>>> Sxx_power_att, tn, fn, ext = maad.sound.spectrogram(p_att,fs)
>>> Sxx_dB_att_40m = maad.util.power2dB(Sxx_power_att,db_range=96) + 96 

>>> p_att = maad.spl.apply_attenuation(p0_sig, fs, r0=5, r =80)
>>> Sxx_power_att, tn, fn, ext = maad.sound.spectrogram(p_att,fs)
>>> Sxx_dB_att_80m = maad.util.power2dB(Sxx_power_att,db_range=96) + 96 

Add noise to the signal.

>>> Sxx_dB_att_10m = maad.util.add_dB(Sxx_dB_att_10m,Sxx_dB_noise) - 3 
>>> Sxx_dB_att_20m = maad.util.add_dB(Sxx_dB_att_20m,Sxx_dB_noise) - 3 
>>> Sxx_dB_att_40m = maad.util.add_dB(Sxx_dB_att_40m,Sxx_dB_noise) - 3 
>>> Sxx_dB_att_80m = maad.util.add_dB(Sxx_dB_att_80m,Sxx_dB_noise) - 3 

Plot attenuated spectrogram.

>>> maad.util.plot2d(Sxx_dB_att_10m, ax=ax2, extent=ext, vmin=0, vmax=70, figsize=[3,3])
>>> maad.util.plot2d(Sxx_dB_att_20m, ax=ax3, extent=ext, vmin=0, vmax=70, figsize=[3,3])
>>> maad.util.plot2d(Sxx_dB_att_40m, ax=ax4, extent=ext, vmin=0, vmax=70, figsize=[3,3])
>>> maad.util.plot2d(Sxx_dB_att_80m, ax=ax5, extent=ext, vmin=0, vmax=70, figsize=[3,3])     