Note
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Airfoil in open jet – Covariance matrix fitting (CMF).¶
Demonstrates the inverse CMF method with different solvers. Uses measured data in file example_data.h5, calibration in file example_calib.xml, microphone geometry in array_56.xml (part of Acoular).
from pathlib import Path
import acoular as ac
The 4 kHz third-octave band is used for the example.
cfreq = 4000
num = 3
Setting up the processing chain for acoular.fbeamform.BeamformerCMF methods.
Hint
A step-by-step explanation for setting up the processing chain is given in the example Airfoil in open jet – steering vectors..
ts = ac.MaskedTimeSamples(
name='../data/example_data.h5',
invalid_channels=[1, 7],
start=0,
stop=16000,
calib=ac.Calib(from_file='../data/example_calib.xml'),
)
mics = ac.MicGeom(from_file=Path(ac.__file__).parent / 'xml' / 'array_56.xml', invalid_channels=[1, 7])
grid = ac.RectGrid(x_min=-0.6, x_max=-0.0, y_min=-0.3, y_max=0.3, z=0.68, increment=0.05)
env = ac.Environment(c=346.04)
st = ac.SteeringVector(grid=grid, mics=mics, env=env)
f = ac.PowerSpectra(time_data=ts, window='Hanning', overlap='50%', block_size=128)
b = ac.BeamformerCMF(freq_data=f, steer=st, alpha=1e-8)
Plot result maps for CMF with different solvers from SciPy and scikit-learn, including:
LassoLars
LassoLarsBIC
OMPCV
NNLS
fmin_l_bfgs_b
from pylab import colorbar, figure, imshow, show, subplot, tight_layout, title
figure(1, (10, 7)) # no of figure
i1 = 1 # no of subplot
for method in ('LassoLars', 'LassoLarsBIC', 'OMPCV', 'NNLS', 'fmin_l_bfgs_b'):
b.method = method
subplot(2, 3, i1)
i1 += 1
map = b.synthetic(cfreq, 1)
mx = ac.L_p(map.max())
imshow(ac.L_p(map.T), vmax=mx, vmin=mx - 15, origin='lower', interpolation='nearest', extent=grid.extend())
colorbar(shrink=0.5)
title(b.method)
tight_layout()
show()
[('example_data_cache.h5', 1)]
[('example_data_cache.h5', 2)]
Total running time of the script: (0 minutes 3.580 seconds)