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Simple audio filters #5230
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2dcb414
Add IIR Filter and Butterworth design functions
Martmists-GH 01574c8
naming conventions and missing type hints
Martmists-GH 9770407
Link wikipedia in IIRFilter
Martmists-GH adc612d
Add doctests and None return types
Martmists-GH ce8bf6d
More doctests
Martmists-GH 92e58da
Requested changes
Martmists-GH 4fe509d
run pre-commit
Martmists-GH 3f71475
Make mypy stop complaining about ints vs floats
Martmists-GH 6a69c43
Use slower listcomp to make it more readable
Martmists-GH 72ab283
Make doctests happy
Martmists-GH fb839f5
Remove scipy
Martmists-GH 05e8e1b
Test coefficients from bw filters
Martmists-GH 0fdd49e
Protocol test
Martmists-GH dedc0d5
Make requested change
Martmists-GH ef2b952
Types
Martmists-GH 9848caf
Apply suggestions from code review
cclauss 2d9ccc4
Apply suggestions from code review
cclauss 6cb4e2c
Update butterworth_filter.py
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from math import cos, sin, sqrt, tau | ||
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from audio_filters.iir_filter import IIRFilter | ||
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""" | ||
Create 2nd-order IIR filters with Butterworth design. | ||
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Code based on https://webaudio.github.io/Audio-EQ-Cookbook/audio-eq-cookbook.html | ||
Alternatively you can use scipy.signal.butter, which should yield the same results. | ||
""" | ||
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def make_lowpass( | ||
frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2) | ||
) -> IIRFilter: | ||
""" | ||
Creates a low-pass filter | ||
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>>> filter = make_lowpass(1000, 48000) | ||
>>> filter.a_coeffs + filter.b_coeffs # doctest: +NORMALIZE_WHITESPACE | ||
[1.0922959556412573, -1.9828897227476208, 0.9077040443587427, 0.004277569313094809, | ||
0.008555138626189618, 0.004277569313094809] | ||
""" | ||
w0 = tau * frequency / samplerate | ||
_sin = sin(w0) | ||
_cos = cos(w0) | ||
alpha = _sin / (2 * q_factor) | ||
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b0 = (1 - _cos) / 2 | ||
b1 = 1 - _cos | ||
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a0 = 1 + alpha | ||
a1 = -2 * _cos | ||
a2 = 1 - alpha | ||
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filt = IIRFilter(2) | ||
filt.set_coefficients([a0, a1, a2], [b0, b1, b0]) | ||
return filt | ||
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def make_highpass( | ||
frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2) | ||
) -> IIRFilter: | ||
""" | ||
Creates a high-pass filter | ||
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>>> filter = make_highpass(1000, 48000) | ||
>>> filter.a_coeffs + filter.b_coeffs # doctest: +NORMALIZE_WHITESPACE | ||
[1.0922959556412573, -1.9828897227476208, 0.9077040443587427, 0.9957224306869052, | ||
-1.9914448613738105, 0.9957224306869052] | ||
""" | ||
w0 = tau * frequency / samplerate | ||
_sin = sin(w0) | ||
_cos = cos(w0) | ||
alpha = _sin / (2 * q_factor) | ||
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b0 = (1 + _cos) / 2 | ||
b1 = -1 - _cos | ||
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a0 = 1 + alpha | ||
a1 = -2 * _cos | ||
a2 = 1 - alpha | ||
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filt = IIRFilter(2) | ||
filt.set_coefficients([a0, a1, a2], [b0, b1, b0]) | ||
return filt | ||
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def make_bandpass( | ||
frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2) | ||
) -> IIRFilter: | ||
""" | ||
Creates a band-pass filter | ||
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>>> filter = make_bandpass(1000, 48000) | ||
>>> filter.a_coeffs + filter.b_coeffs # doctest: +NORMALIZE_WHITESPACE | ||
[1.0922959556412573, -1.9828897227476208, 0.9077040443587427, 0.06526309611002579, | ||
0, -0.06526309611002579] | ||
""" | ||
w0 = tau * frequency / samplerate | ||
_sin = sin(w0) | ||
_cos = cos(w0) | ||
alpha = _sin / (2 * q_factor) | ||
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b0 = _sin / 2 | ||
b1 = 0 | ||
b2 = -b0 | ||
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a0 = 1 + alpha | ||
a1 = -2 * _cos | ||
a2 = 1 - alpha | ||
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filt = IIRFilter(2) | ||
filt.set_coefficients([a0, a1, a2], [b0, b1, b2]) | ||
return filt | ||
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def make_allpass( | ||
frequency: int, samplerate: int, q_factor: float = 1 / sqrt(2) | ||
) -> IIRFilter: | ||
""" | ||
Creates an all-pass filter | ||
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>>> filter = make_allpass(1000, 48000) | ||
>>> filter.a_coeffs + filter.b_coeffs # doctest: +NORMALIZE_WHITESPACE | ||
[1.0922959556412573, -1.9828897227476208, 0.9077040443587427, 0.9077040443587427, | ||
-1.9828897227476208, 1.0922959556412573] | ||
""" | ||
w0 = tau * frequency / samplerate | ||
_sin = sin(w0) | ||
_cos = cos(w0) | ||
alpha = _sin / (2 * q_factor) | ||
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b0 = 1 - alpha | ||
b1 = -2 * _cos | ||
b2 = 1 + alpha | ||
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filt = IIRFilter(2) | ||
filt.set_coefficients([b2, b1, b0], [b0, b1, b2]) | ||
return filt | ||
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def make_peak( | ||
frequency: int, samplerate: int, gain_db: float, q_factor: float = 1 / sqrt(2) | ||
) -> IIRFilter: | ||
""" | ||
Creates a peak filter | ||
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>>> filter = make_peak(1000, 48000, 6) | ||
>>> filter.a_coeffs + filter.b_coeffs # doctest: +NORMALIZE_WHITESPACE | ||
[1.0653405327119334, -1.9828897227476208, 0.9346594672880666, 1.1303715025601122, | ||
-1.9828897227476208, 0.8696284974398878] | ||
""" | ||
w0 = tau * frequency / samplerate | ||
_sin = sin(w0) | ||
_cos = cos(w0) | ||
alpha = _sin / (2 * q_factor) | ||
big_a = 10 ** (gain_db / 40) | ||
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b0 = 1 + alpha * big_a | ||
b1 = -2 * _cos | ||
b2 = 1 - alpha * big_a | ||
a0 = 1 + alpha / big_a | ||
a1 = -2 * _cos | ||
a2 = 1 - alpha / big_a | ||
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filt = IIRFilter(2) | ||
filt.set_coefficients([a0, a1, a2], [b0, b1, b2]) | ||
return filt | ||
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def make_lowshelf( | ||
frequency: int, samplerate: int, gain_db: float, q_factor: float = 1 / sqrt(2) | ||
) -> IIRFilter: | ||
""" | ||
Creates a low-shelf filter | ||
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>>> filter = make_lowshelf(1000, 48000, 6) | ||
>>> filter.a_coeffs + filter.b_coeffs # doctest: +NORMALIZE_WHITESPACE | ||
[3.0409336710888786, -5.608870992220748, 2.602157875636628, 3.139954022810743, | ||
-5.591841778072785, 2.5201667380627257] | ||
""" | ||
w0 = tau * frequency / samplerate | ||
_sin = sin(w0) | ||
_cos = cos(w0) | ||
alpha = _sin / (2 * q_factor) | ||
big_a = 10 ** (gain_db / 40) | ||
pmc = (big_a + 1) - (big_a - 1) * _cos | ||
ppmc = (big_a + 1) + (big_a - 1) * _cos | ||
mpc = (big_a - 1) - (big_a + 1) * _cos | ||
pmpc = (big_a - 1) + (big_a + 1) * _cos | ||
aa2 = 2 * sqrt(big_a) * alpha | ||
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b0 = big_a * (pmc + aa2) | ||
b1 = 2 * big_a * mpc | ||
b2 = big_a * (pmc - aa2) | ||
a0 = ppmc + aa2 | ||
a1 = -2 * pmpc | ||
a2 = ppmc - aa2 | ||
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filt = IIRFilter(2) | ||
filt.set_coefficients([a0, a1, a2], [b0, b1, b2]) | ||
return filt | ||
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def make_highshelf( | ||
frequency: int, samplerate: int, gain_db: float, q_factor: float = 1 / sqrt(2) | ||
) -> IIRFilter: | ||
""" | ||
Creates a high-shelf filter | ||
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>>> filter = make_highshelf(1000, 48000, 6) | ||
>>> filter.a_coeffs + filter.b_coeffs # doctest: +NORMALIZE_WHITESPACE | ||
[2.2229172136088806, -3.9587208137297303, 1.7841414181566304, 4.295432981120543, | ||
-7.922740859457287, 3.6756456963725253] | ||
""" | ||
w0 = tau * frequency / samplerate | ||
_sin = sin(w0) | ||
_cos = cos(w0) | ||
alpha = _sin / (2 * q_factor) | ||
big_a = 10 ** (gain_db / 40) | ||
pmc = (big_a + 1) - (big_a - 1) * _cos | ||
ppmc = (big_a + 1) + (big_a - 1) * _cos | ||
mpc = (big_a - 1) - (big_a + 1) * _cos | ||
pmpc = (big_a - 1) + (big_a + 1) * _cos | ||
aa2 = 2 * sqrt(big_a) * alpha | ||
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b0 = big_a * (ppmc + aa2) | ||
b1 = -2 * big_a * pmpc | ||
b2 = big_a * (ppmc - aa2) | ||
a0 = pmc + aa2 | ||
a1 = 2 * mpc | ||
a2 = pmc - aa2 | ||
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filt = IIRFilter(2) | ||
filt.set_coefficients([a0, a1, a2], [b0, b1, b2]) | ||
return filt |
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from __future__ import annotations | ||
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class IIRFilter: | ||
r""" | ||
N-Order IIR filter | ||
Assumes working with float samples normalized on [-1, 1] | ||
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--- | ||
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Implementation details: | ||
Based on the 2nd-order function from | ||
https://en.wikipedia.org/wiki/Digital_biquad_filter, | ||
this generalized N-order function was made. | ||
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Using the following transfer function | ||
H(z)=\frac{b_{0}+b_{1}z^{-1}+b_{2}z^{-2}+...+b_{k}z^{-k}}{a_{0}+a_{1}z^{-1}+a_{2}z^{-2}+...+a_{k}z^{-k}} | ||
we can rewrite this to | ||
y[n]={\frac{1}{a_{0}}}\left(\left(b_{0}x[n]+b_{1}x[n-1]+b_{2}x[n-2]+...+b_{k}x[n-k]\right)-\left(a_{1}y[n-1]+a_{2}y[n-2]+...+a_{k}y[n-k]\right)\right) | ||
""" | ||
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def __init__(self, order: int) -> None: | ||
self.order = order | ||
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# a_{0} ... a_{k} | ||
self.a_coeffs = [1.0] + [0.0] * order | ||
# b_{0} ... b_{k} | ||
self.b_coeffs = [1.0] + [0.0] * order | ||
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# x[n-1] ... x[n-k] | ||
self.input_history = [0.0] * self.order | ||
# y[n-1] ... y[n-k] | ||
self.output_history = [0.0] * self.order | ||
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def set_coefficients(self, a_coeffs: list[float], b_coeffs: list[float]) -> None: | ||
""" | ||
Set the coefficients for the IIR filter. These should both be of size order + 1. | ||
a_0 may be left out, and it will use 1.0 as default value. | ||
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This method works well with scipy's filter design functions | ||
>>> # Make a 2nd-order 1000Hz butterworth lowpass filter | ||
>>> import scipy.signal | ||
>>> b_coeffs, a_coeffs = scipy.signal.butter(2, 1000, | ||
... btype='lowpass', | ||
... fs=48000) | ||
>>> filt = IIRFilter(2) | ||
>>> filt.set_coefficients(a_coeffs, b_coeffs) | ||
""" | ||
if len(a_coeffs) < self.order: | ||
a_coeffs = [1.0] + a_coeffs | ||
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if len(a_coeffs) != self.order + 1: | ||
raise ValueError( | ||
f"Expected a_coeffs to have {self.order + 1} elements for {self.order}" | ||
f"-order filter, got {len(a_coeffs)}" | ||
) | ||
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if len(b_coeffs) != self.order + 1: | ||
raise ValueError( | ||
f"Expected b_coeffs to have {self.order + 1} elements for {self.order}" | ||
f"-order filter, got {len(a_coeffs)}" | ||
) | ||
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self.a_coeffs = a_coeffs | ||
self.b_coeffs = b_coeffs | ||
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def process(self, sample: float) -> float: | ||
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""" | ||
Calculate y[n] | ||
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>>> filt = IIRFilter(2) | ||
>>> filt.process(0) | ||
0.0 | ||
""" | ||
result = 0.0 | ||
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# Start at index 1 and do index 0 at the end. | ||
for i in range(1, self.order + 1): | ||
result += ( | ||
self.b_coeffs[i] * self.input_history[i - 1] | ||
- self.a_coeffs[i] * self.output_history[i - 1] | ||
) | ||
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result = (result + self.b_coeffs[0] * sample) / self.a_coeffs[0] | ||
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self.input_history[1:] = self.input_history[:-1] | ||
self.output_history[1:] = self.output_history[:-1] | ||
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self.input_history[0] = sample | ||
self.output_history[0] = result | ||
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return result |
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