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# endolith/A_weighting.py

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A-weighting audio files in Python
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 #!/usr/bin/env python # -*- coding: utf-8 -*- """ Translated from a MATLAB script (which also includes C-weighting, octave and one-third-octave digital filters). Author: Christophe Couvreur, Faculte Polytechnique de Mons (Belgium) couvreur@thor.fpms.ac.be Last modification: Aug. 20, 1997, 10:00am. BSD license http://www.mathworks.com/matlabcentral/fileexchange/69 Translated from adsgn.m to Python 2009-07-14 endolith@gmail.com """ from numpy import pi, polymul from scipy.signal import bilinear def A_weighting(fs): """Design of an A-weighting filter. b, a = A_weighting(fs) designs a digital A-weighting filter for sampling frequency `fs`. Usage: y = scipy.signal.lfilter(b, a, x). Warning: `fs` should normally be higher than 20 kHz. For example, fs = 48000 yields a class 1-compliant filter. References: [1] IEC/CD 1672: Electroacoustics-Sound Level Meters, Nov. 1996. """ # Definition of analog A-weighting filter according to IEC/CD 1672. f1 = 20.598997 f2 = 107.65265 f3 = 737.86223 f4 = 12194.217 A1000 = 1.9997 NUMs = [(2*pi * f4)**2 * (10**(A1000/20)), 0, 0, 0, 0] DENs = polymul([1, 4*pi * f4, (2*pi * f4)**2], [1, 4*pi * f1, (2*pi * f1)**2]) DENs = polymul(polymul(DENs, [1, 2*pi * f3]), [1, 2*pi * f2]) # Use the bilinear transformation to get the digital filter. # (Octave, MATLAB, and PyLab disagree about Fs vs 1/Fs) return bilinear(NUMs, DENs, fs)
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 import sys from scipy.signal import lfilter import numpy as np from A_weighting import A_weighting try: import soundfile as sf except ImportError: from scikits.audiolab import wavread # (scipy.io.wavfile can't read 24-bit WAV) def rms_flat(a): # from matplotlib.mlab """ Return the root mean square of all the elements of *a*, flattened out. """ return np.sqrt(np.mean(np.absolute(a)**2)) if len(sys.argv) == 2: filename = sys.argv[1] else: filename = 'noise.wav' try: x, fs = sf.read(filename) except NameError: x, fs, bits = wavread(filename) print(filename) print('Original: {:+.2f} dB'.format(20*np.log10(rms_flat(x)))) b, a = A_weighting(fs) y = lfilter(b, a, x) print('A-weighted: {:+.2f} dB'.format(20*np.log10(rms_flat(y))))

### rickou commented Sep 14, 2023

hum.. i think i understand.. to be honest i'm not so comfortable with digital filtering.
i have implemented this filter in embedded software and i will made some tests in next weeks in real situation comparing my implementation and sonometer.
but my preliminary tests on bench shows nothing bad. (i'm using 20k sample rate)