from numpy import array, linspace, interp, empty
[docs]
def spectrum2dBA(spectrum, fs):
"""A_weighting dB ponderation
This function does the dBA weighting of a spectrum according to CEI 61672:2014.
Parameters
----------
spectrum: array_like
Input spectrum in [dB].
fs: integer
Sampling frequency in [Hz].
Returns
-------
spectrum_dba: array_like
dBA spectrum.
Notes
-----
Third-octave spectrum are directly calculated, other are calculated
using linear interpolation.
See Also
--------
noct_spectrum : N-th octave band spectrum computation from a time signal
Examples
--------
.. plot::
:include-source:
>>> from mosqito.sound_level_meter import noct_synthesis
>>> from mosqito.utils import amp2db
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> f=1000
>>> fs=48000
>>> d=0.2
>>> dB=60
>>> time = np.arange(0, d, 1/fs)
>>> stimulus = np.sin(2 * np.pi * f * time) + 0.5 * np.sin(6 * np.pi * f * time)
>>> rms = np.sqrt(np.mean(np.power(stimulus, 2)))
>>> ampl = 0.00002 * np.power(10, dB / 20) / rms
>>> stimulus = stimulus * ampl
>>> n = len(stimulus)
>>> spec = np.abs(2/np.sqrt(2)/n*np.fft.fft(stimulus)[:n//2])
>>> freqs = np.linspace(0, fs//2,n//2)
>>> spec_3, freq_axis = noct_synthesis(spec, freqs, fmin=90, fmax=14000)
>>> spec_3db = amp2db(spec_3, ref=2e-5)
>>> plt.step(freq_axis, spec_3db)
>>> plt.ylim(0,60)
>>> plt.xlabel("Center frequency [Hz]")
>>> plt.ylabel("Amplitude [dB]")
"""
# Ponderation coefficients from the standard
A_standard = array(
[
-70.4,
-63.4,
-56.7,
-50.5,
-44.7,
-39.4,
-34.6,
-30.2,
-26.2,
-22.5,
-19.1,
-16.1,
-13.4,
-10.9,
-8.6,
-6.6,
-4.8,
-3.2,
-1.9,
-0.8,
0,
0.6,
1,
1.2,
1.3,
1.2,
1,
0.5,
-0.1,
-1.1,
-2.5,
-4.3,
-6.6,
-9.3,
]
)
freq_standard = array(
[
10,
12.5,
16,
20,
25,
31.5,
40,
50,
63,
80,
100,
125,
160,
200,
250,
315,
400,
500,
630,
800,
1000,
1250,
1600,
2000,
2500,
3150,
4000,
5000,
6300,
8000,
10000,
12500,
16000,
20000,
]
)
# Linear interpolation on the spectrum axis
spectrum_freq_axis = linspace(0, int(fs / 2), spectrum.size)
A_pond = interp(spectrum_freq_axis, freq_standard, A_standard)
# Ponderation of the given spectrum
spectrum_dBA = empty(spectrum.shape)
for i in range(spectrum.shape[0]):
spectrum_dBA[i] = spectrum[i] + A_pond[i]
return spectrum_dBA
