kopia lustrzana https://github.com/erdewit/HiFiScan
Add minimum-phase filter, issue #9
Ewald de Wit
rodzic
6650420b9c
commit
ef0f1cea7e
|
|
@ -1,6 +1,6 @@
|
|||
"""'Optimize the frequency response spectrum of an audio system"""
|
||||
|
||||
from hifiscan.analyzer import (
|
||||
Analyzer, XY, geom_chirp, linear_chirp, resample, smooth, taper,
|
||||
tone, window)
|
||||
Analyzer, XY, geom_chirp, linear_chirp, minimum_phase, resample,
|
||||
smooth, taper, tone, window)
|
||||
from hifiscan.audio import Audio, read_correction, write_wav
|
||||
|
|
|
|||
|
|
@ -3,9 +3,9 @@ import types
|
|||
from functools import lru_cache
|
||||
from typing import List, NamedTuple, Optional, Tuple
|
||||
|
||||
from numba import njit
|
||||
|
||||
import numpy as np
|
||||
from numba import njit
|
||||
from numpy.fft import fft, ifft, irfft, rfft
|
||||
|
||||
|
||||
class XY(NamedTuple):
|
||||
|
|
@ -103,9 +103,9 @@ class Analyzer:
|
|||
sz = len(recording)
|
||||
self.time = sz / self.rate
|
||||
if sz >= self.x.size:
|
||||
Y = np.fft.fft(recording)
|
||||
X = np.fft.fft(np.flip(self.x), n=sz)
|
||||
corr = np.fft.ifft(X * Y).real
|
||||
Y = fft(recording)
|
||||
X = fft(np.flip(self.x), n=sz)
|
||||
corr = ifft(X * Y).real
|
||||
idx = int(corr.argmax()) - self.x.size + 1
|
||||
if idx >= 0:
|
||||
self.y = np.array(recording[idx:idx + self.x.size])
|
||||
|
|
@ -159,10 +159,10 @@ class Analyzer:
|
|||
return interp
|
||||
|
||||
def X(self) -> np.ndarray:
|
||||
return np.fft.rfft(self.x)
|
||||
return rfft(self.x)
|
||||
|
||||
def Y(self) -> np.ndarray:
|
||||
return np.fft.rfft(self.y)
|
||||
return rfft(self.y)
|
||||
|
||||
def calcH(self) -> np.ndarray:
|
||||
"""
|
||||
|
|
@ -171,7 +171,7 @@ class Analyzer:
|
|||
X = self.X()
|
||||
Y = self.Y()
|
||||
# H = Y / X
|
||||
H = Y * np.conj(X) / (np.abs(X) ** 2 + 1e-3)
|
||||
H = Y * np.conj(X) / (np.abs(X) ** 2 + 1e-6)
|
||||
if self._calibration:
|
||||
H *= 10 ** (-self.calibration() / 20)
|
||||
H = np.abs(H)
|
||||
|
|
@ -199,7 +199,7 @@ class Analyzer:
|
|||
def h(self) -> XY:
|
||||
"""Calculate impulse response ``h`` in the time domain."""
|
||||
_, H = self.H()
|
||||
h = np.fft.irfft(H)
|
||||
h = irfft(H)
|
||||
h = np.hstack([h[h.size // 2:], h[0:h.size // 2]])
|
||||
t = np.linspace(0, h.size / self.rate, h.size)
|
||||
return XY(t, h)
|
||||
|
|
@ -223,7 +223,8 @@ class Analyzer:
|
|||
secs: float = 0.05,
|
||||
dbRange: float = 24,
|
||||
kaiserBeta: float = 5,
|
||||
smoothing: float = 0) -> XY:
|
||||
smoothing: float = 0,
|
||||
minPhase: bool = False) -> XY:
|
||||
"""
|
||||
Calculate the inverse impulse response.
|
||||
|
||||
|
|
@ -232,6 +233,7 @@ class Analyzer:
|
|||
dbRange: Maximum attenuation in dB (power).
|
||||
kaiserBeta: Shape parameter of the Kaiser tapering window.
|
||||
smoothing: Strength of frequency-dependent smoothing.
|
||||
minPhase: Use minimal-phase if True or linear-phase if False
|
||||
"""
|
||||
freq, H2 = self.H2(smoothing)
|
||||
# Apply target curve.
|
||||
|
|
@ -239,6 +241,9 @@ class Analyzer:
|
|||
H2 = H2 * 10 ** (-self.target() / 10)
|
||||
# Re-sample to halve the number of samples needed.
|
||||
n = int(secs * self.rate / 2)
|
||||
if minPhase:
|
||||
# Later minimum phase filter will halve the size.
|
||||
n *= 2
|
||||
H = resample(H2, n) ** 0.5
|
||||
# Accommodate the given dbRange from the top.
|
||||
H /= H.max()
|
||||
|
|
@ -251,14 +256,16 @@ class Analyzer:
|
|||
Z = Z * phase
|
||||
|
||||
# Calculate the inverse impulse response z.
|
||||
z = np.fft.irfft(Z)
|
||||
z = irfft(Z)
|
||||
z = z[:-1]
|
||||
z *= window(z.size, kaiserBeta)
|
||||
if minPhase:
|
||||
z = minimum_phase(z)
|
||||
|
||||
# Normalize using a fractal dimension for scaling.
|
||||
dim = 1.5
|
||||
dim = 1.25 if minPhase else 1.5
|
||||
norm = (np.abs(z) ** dim).sum() ** (1 / dim)
|
||||
z /= norm
|
||||
# assert np.allclose(z[-(z.size // 2):][::-1], z[:z.size // 2])
|
||||
|
||||
t = np.linspace(0, z.size / self.rate, z.size)
|
||||
return XY(t, z)
|
||||
|
|
@ -268,7 +275,7 @@ class Analyzer:
|
|||
Calculate correction factor for each frequency, given the
|
||||
inverse impulse response.
|
||||
"""
|
||||
Z = np.abs(np.fft.rfft(invResp))
|
||||
Z = np.abs(rfft(invResp))
|
||||
Z /= Z.max()
|
||||
freq = np.linspace(0, self.rate / 2, Z.size)
|
||||
return XY(freq, Z)
|
||||
|
|
@ -388,3 +395,33 @@ def taper(y0: float, y1: float, size: int) -> np.ndarray:
|
|||
"""Create a smooth transition from y0 to y1 of given size."""
|
||||
tp = (y0 + y1 - (y1 - y0) * np.cos(np.linspace(0, np.pi, size))) / 2
|
||||
return tp
|
||||
|
||||
|
||||
def minimum_phase(x: np.ndarray) -> np.ndarray:
|
||||
"""
|
||||
Homomorphic filter to create a minimum-phase impulse from the given
|
||||
symmetric odd-sized linear-phase impulse.
|
||||
|
||||
https://www.rle.mit.edu/dspg/documents/AVOHomoorphic75.pdf
|
||||
https://www.katjaas.nl/minimumphase/minimumphase.html
|
||||
"""
|
||||
mid = x.size // 2
|
||||
if not (x.size % 2 and np.allclose(x[:mid], x[-1:mid:-1])):
|
||||
raise ValueError('Symmetric odd-sized array required')
|
||||
# Go to frequency domain, oversampling 4x to avoid aliasing.
|
||||
X = np.abs(fft(x, 4 * x.size))
|
||||
# Non-linear mapping.
|
||||
XX = np.log(np.fmax(X, 1e-9))
|
||||
# Linear filter selects minimum phase part in the complex cepstrum.
|
||||
xx = ifft(XX).real
|
||||
yy = np.zeros_like(xx)
|
||||
yy[0] = xx[0]
|
||||
yy[1:mid + 1] = 2 * xx[1:mid + 1]
|
||||
YY = fft(yy)
|
||||
# Non-linear mapping back.
|
||||
Y = np.exp(YY)
|
||||
# Go back to time domain.
|
||||
y = ifft(Y).real
|
||||
# Take the valid part.
|
||||
y_min = y[:mid + 1]
|
||||
return y_min
|
||||
|
|
|
|||
|
|
@ -100,8 +100,9 @@ class App(qt.QMainWindow):
|
|||
dbRange = self.dbRange.value()
|
||||
beta = self.kaiserBeta.value()
|
||||
smoothing = self.irSmoothing.value()
|
||||
minPhase = self.typeBox.currentIndex() == 1
|
||||
|
||||
t, ir = analyzer.h_inv(secs, dbRange, beta, smoothing)
|
||||
t, ir = analyzer.h_inv(secs, dbRange, beta, smoothing, minPhase)
|
||||
self.irPlot.setData(1000 * t, ir)
|
||||
|
||||
logIr = np.log10(1e-8 + np.abs(ir))
|
||||
|
|
@ -139,9 +140,11 @@ class App(qt.QMainWindow):
|
|||
db = int(self.dbRange.value())
|
||||
beta = int(self.kaiserBeta.value())
|
||||
smoothing = int(self.irSmoothing.value())
|
||||
_, irInv = analyzer.h_inv(ms / 1000, db, beta, smoothing)
|
||||
minPhase = self.typeBox.currentIndex() == 1
|
||||
_, irInv = analyzer.h_inv(ms / 1000, db, beta, smoothing, minPhase)
|
||||
|
||||
name = f'IR_{ms}ms_{db}dB_{beta}t_{smoothing}s.wav'
|
||||
name = (f'IR_{ms}ms_{db}dB_{beta}t_{smoothing}s'
|
||||
f'{"_minphase" if minPhase else ""}.wav')
|
||||
filename, _ = qt.QFileDialog.getSaveFileName(
|
||||
self, 'Save inverse impulse response',
|
||||
str(self.saveDir / name), 'WAV (*.wav)')
|
||||
|
|
@ -276,6 +279,10 @@ class App(qt.QMainWindow):
|
|||
self.useBox.addItems(['Stored measurements', 'Last measurement'])
|
||||
self.useBox.currentIndexChanged.connect(self.plot)
|
||||
|
||||
self.typeBox = qt.QComboBox()
|
||||
self.typeBox.addItems(['Zero phase', 'Zero latency'])
|
||||
self.typeBox.currentIndexChanged.connect(self.plot)
|
||||
|
||||
exportButton = qt.QPushButton('Export as WAV')
|
||||
exportButton.setShortcut('E')
|
||||
exportButton.setToolTip('<Key E>')
|
||||
|
|
@ -295,6 +302,9 @@ class App(qt.QMainWindow):
|
|||
hbox.addWidget(qt.QLabel('Smoothing: '))
|
||||
hbox.addWidget(self.irSmoothing)
|
||||
hbox.addSpacing(32)
|
||||
hbox.addWidget(qt.QLabel('Type: '))
|
||||
hbox.addWidget(self.typeBox)
|
||||
hbox.addSpacing(32)
|
||||
hbox.addWidget(qt.QLabel('Use: '))
|
||||
hbox.addWidget(self.useBox)
|
||||
hbox.addStretch(1)
|
||||
|
|
|
|||
Ładowanie…
Reference in New Issue