def run():
from os import path
from acoular import __file__ as bpath, MicGeom, WNoiseGenerator, PointSource,\
Mixer, WriteH5, TimeSamples, PowerSpectra, RectGrid, SteeringVector,\
BeamformerBase, L_p
from pylab import figure, plot, axis, imshow, colorbar, show
# set up the parameters
sfreq = 51200
duration = 1
nsamples = duration * sfreq
micgeofile = path.join(path.split(bpath)[0], 'xml', 'array_64.xml')
h5savefile = 'three_sources.h5'
# generate test data, in real life this would come from an array measurement
mg = MicGeom(from_file=micgeofile)
n1 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, seed=1)
n2 = WNoiseGenerator(sample_freq=sfreq,
numsamples=nsamples,
seed=2,
rms=0.7)
n3 = WNoiseGenerator(sample_freq=sfreq,
numsamples=nsamples,
seed=3,
rms=0.5)
p1 = PointSource(signal=n1, mics=mg, loc=(-0.1, -0.1, 0.3))
p2 = PointSource(signal=n2, mics=mg, loc=(0.15, 0, 0.3))
p3 = PointSource(signal=n3, mics=mg, loc=(0, 0.1, 0.3))
pa = Mixer(source=p1, sources=[p2, p3])
wh5 = WriteH5(source=pa, name=h5savefile)
wh5.save()
# analyze the data and generate map
ts = TimeSamples(name=h5savefile)
ps = PowerSpectra(time_data=ts, block_size=128, window='Hanning')
rg = RectGrid( x_min=-0.2, x_max=0.2, y_min=-0.2, y_max=0.2, z=0.3, \
increment=0.01 )
st = SteeringVector(grid=rg, mics=mg)
bb = BeamformerBase(freq_data=ps, steer=st)
pm = bb.synthetic(8000, 3)
Lm = L_p(pm)
# show map
imshow( Lm.T, origin='lower', vmin=Lm.max()-10, extent=rg.extend(), \
interpolation='bicubic')
colorbar()
# plot microphone geometry
figure(2)
plot(mg.mpos[0], mg.mpos[1], 'o')
axis('equal')
show()
def get_sql_sources(cursor, sources_id, sfreq, mpos):
# sources_id -> id für eine Quellkartierung mit bestimmten Quellen
# source_id -> id jeder einzelnen source
# source ids -> liste aller ids der einzelnen sources einer sources id
source_ids = fetchall(cursor, get_source_ids, sources_id)
cursor.execute(sq(get_ap, 1))
(ap) = cursor.fetchone()
sourcelist = [] # list
for source_id in source_ids:
cursor.execute(
sq(get_source, sources_id,
source_id)) # get the source parameters one after the other
(signal_id, x1, x2, x3, pol_type, dipole_id, p_rms) = cursor.fetchone()
# generate harmonic or noise source...
sgnl = WNoiseGenerator(rms=p_rms,
sample_freq=sfreq,
numsamples=512000,
seed=(signal_id - 1))
# newsrc = PointSource(signal = sgnl,
# mpos = m_error,
# loc = (x1*ap, x2*ap, x3*ap))
newsrc = PointSource(signal=sgnl,
mpos=mpos,
loc=(x1 * ap[0], x2 * ap[0], x3 * ap[0]))
sourcelist.append(newsrc) # add the new source to the list
if len(source_ids
) > 1: # if there are multiple sources, they have to be mixed
src = Mixer(source=sourcelist[0], sources=sourcelist[1:])
else: # if there's only one source, it is the only one in the list
src = sourcelist[0]
return src
def test_timeconvolve(self):
"""compare results of timeconvolve with numpy convolve"""
# Parameters
NSAMPLES = 25
N1 = WNoiseGenerator(sample_freq=1000, numsamples=NSAMPLES, seed=1)
MGEOM = MicGeom(mpos_tot=[[1], [1], [1]])
P1 = PointSource(signal=N1, mics=MGEOM)
KERNEL = np.random.rand(20)
CONV = TimeConvolve(kernel=KERNEL, source=P1)
SIG = tools.return_result(P1, num=NSAMPLES)
RES = tools.return_result(CONV, num=100)
for i in range(P1.numchannels):
REF = np.convolve(np.squeeze(KERNEL), np.squeeze(SIG[:, i]))
np.testing.assert_allclose(np.squeeze(RES[:, i]),
REF,
rtol=1e-5,
atol=1e-8)
TimeCache, FiltOctave, BeamformerTime, TimePower, IntegratorSectorTime, \
PointSource, MovingPointSource, SineGenerator, WNoiseGenerator, Mixer, WriteWAV
from pylab import subplot, imshow, show, colorbar, plot, transpose, figure, \
psd, axis, xlim, ylim, title, tight_layout, text
freq = 48000
sfreq = freq / 2 #sampling frequency
duration = 1
nsamples = freq * duration
datafile = 'cry_n0000001.wav'
micgeofile = path.join(path.split(bpath)[0], 'xml', 'array_64_8mic.xml')
h5savefile = 'cry_n0000001.wav'
m = MicGeom(from_file=micgeofile)
n = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, seed=1) #1pascal
p = PointSource(signal=n, mpos=m, loc=(-0.1, -0.1, 0.3))
p1 = Mixer(source=p)
wh5 = WriteH5(source=p, name=h5savefile)
wh5.save()
#definition the different source signal
r = 52.5
nsamples = long(sfreq * 0.3)
n1 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples)
s1 = SineGenerator(sample_freq=sfreq, numsamples=nsamples, freq=freq)
s2 = SineGenerator(sample_freq=sfreq, numsamples=nsamples, freq=freq, \
phase=pi)
#define a circular array of 8 microphones
m = MicGeom('array_64_8mic.xml')
m.mpos_tot = array([(r*sin(2*pi*i+pi/8), r*cos(2*pi*i+pi/8), 0) \
Mixer, WriteH5, TimeSamples, PowerSpectra, RectGrid, BeamformerBase, L_p from pylab import figure, plot, axis, imshow, colorbar, show # set up the parameters sfreq = 51200 duration = 1 nsamples = duration*sfreq micgeofile = path.join(path.split(bpath)[0],'xml','array_64.xml') h5savefile = 'three_sources.h5' # generate test data, in real life this would come from an array measurement mg = MicGeom( from_file=micgeofile ) n1 = WNoiseGenerator( sample_freq=sfreq, numsamples=nsamples, seed=1 ) n2 = WNoiseGenerator( sample_freq=sfreq, numsamples=nsamples, seed=2, rms=0.7 ) n3 = WNoiseGenerator( sample_freq=sfreq, numsamples=nsamples, seed=3, rms=0.5 ) p1 = PointSource( signal=n1, mpos=mg, loc=(-0.1,-0.1,0.3) ) p2 = PointSource( signal=n2, mpos=mg, loc=(0.15,0,0.3) ) p3 = PointSource( signal=n3, mpos=mg, loc=(0,0.1,0.3) ) pa = Mixer( source=p1, sources=[p2,p3] ) wh5 = WriteH5( source=pa, name=h5savefile ) wh5.save() # analyze the data and generate map ts = TimeSamples( name=h5savefile ) ps = PowerSpectra( time_data=ts, block_size=128, window='Hanning' ) rg = RectGrid( x_min=-0.2, x_max=0.2, y_min=-0.2, y_max=0.2, z=0.3, \ increment=0.01 ) bb = BeamformerBase( freq_data=ps, grid=rg, mpos=mg ) pm = bb.synthetic( 8000, 3 ) Lm = L_p( pm )
from numpy import array
from pylab import figure,plot,show,xlim,ylim,xscale,xticks,xlabel,ylabel,\
grid,real, title, legend
# constants
sfreq = 12800 # sample frequency
band = 3 # octave: 1 ; 1/3-octave: 3 (for plotting)
# set up microphone at (0,0,0)
m = MicGeom()
m.mpos_tot = array([[0, 0, 0]])
# create noise source
n1 = WNoiseGenerator(sample_freq=sfreq, numsamples=10 * sfreq, seed=1)
t = PointSource(signal=n1, mics=m, loc=(1, 0, 1))
# create power spectrum
f = PowerSpectra(time_data=t, window='Hanning', overlap='50%', block_size=4096)
# get spectrum data
spectrum_data = real(f.csm[:, 0,
0]) # get power spectrum from cross-spectral matrix
freqs = f.fftfreq() # FFT frequencies
# use barspectrum from acoular.tools to create third octave plot data
(f_borders, p, f_center) = barspectrum(spectrum_data, freqs, band, bar=True)
(f_borders_, p_, f_center_) = barspectrum(spectrum_data,
freqs,
band,
bar=False)
#===============================================================================
if sys.version_info > (3, ):
long = int
nsamples = long(sfreq * tmax)
n1 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples)
s1 = SineGenerator(sample_freq=sfreq, numsamples=nsamples, freq=freq)
s2 = SineGenerator(sample_freq=sfreq, numsamples=nsamples, freq=freq, \
phase=pi)
#===============================================================================
# define the moving source and one fixed source
#===============================================================================
p0 = MovingPointSource(signal=s1, mpos=m, trajectory=tr1)
#t = p0 # use only moving source
p1 = PointSource(signal=n1, mpos=m, loc=(0, R, Z))
t = Mixer(source=p0, sources=[
p1,
]) # mix both signals
#t = p1 # use only fix source
# uncomment to save the signal to a wave file
#ww = WriteWAV(source = t)
#ww.channels = [0,14]
#ww.save()
#===============================================================================
# fixed focus frequency domain beamforming
#===============================================================================
f = PowerSpectra(time_data=t, window='Hanning', overlap='50%', block_size=128, \
micgeofile = path.join(path.split(bpath)[0], 'xml', 'array_64.xml')
# generate test data, in real life this would come from an array measurement
m = MicGeom(from_file=micgeofile)
#===============================================================================
# Now, the sources (signals and types/positions) are defined.
#===============================================================================
sfreq = 51200
duration = 1
nsamples = duration * sfreq
n1 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, seed=1)
n2 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, seed=2, rms=0.5)
n3 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, seed=3, rms=0.25)
p1 = PointSource(signal=n1, mics=m, loc=(-0.1, -0.1, 0.3))
p2 = PointSource(signal=n2, mics=m, loc=(0.15, 0, 0.17))
p3 = PointSource(signal=n3, mics=m, loc=(0, 0.1, 0.25))
pa = SourceMixer(sources=[p1, p2, p3])
#===============================================================================
# the 3D grid (very coarse to enable fast computation for this example)
#===============================================================================
g = RectGrid3D(x_min=-0.2,
x_max=0.2,
y_min=-0.2,
y_max=0.2,
z_min=0.1,
z_max=0.36,
increment=0.02)
#===============================================================================
ufe = UniformFlowEnvironment(ma=0.5, fdv=(0, 1, 0))
g = RectGrid(x_min=-3.0,
x_max=+3.0,
y_min=-3.0,
y_max=+3.0,
z=Z,
increment=0.2)
#===============================================================================
# define some sources
#===============================================================================
mp = MovingPointSource(signal=s1, env=ufe, mpos=m, trajectory=tr1)
ps = PointSource(signal=s1, mpos=m, loc=(0, R, Z))
pd = PointSourceDipole(signal=s1,
mpos=m,
direction=(0.5, 0, 0),
loc=(0, -2, Z))
un = UncorrelatedNoiseSource(signal=n1, mpos=mg)
mix = SourceMixer(sources=[ps, pd])
#===============================================================================
# 3rd Octave Filter
#===============================================================================
fi = FiltFiltOctave(source=un, band=freq, fraction='Third octave')
#==============================================================================
#write to H5 File
nsamples = duration * sfreq # 采样点个数
#micgeofile = path.join(path.split(bpath)[0], 'xml', 'MyMicArray_56.xml') # 麦克风阵列的位置数据
micgeofile = '/home3/zengwh/VoiceRec/data/compute/MyMicArray_56.xml'
num_single_sound_data = 100 # 单声源训练集数目
m = MicGeom(from_file=micgeofile)
# 设置声源位置信息和声压强度
# n2 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, seed=2, rms=0.7)
# n3 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, seed=3, rms=0.5)
for i in range(num_single_sound_data):
print(i)
[Rms] = np.around(np.random.random(1), 2)
n1 = WNoiseGenerator(sample_freq=sfreq, numsamples=nsamples, rms=Rms)
# 随机产生0-1的数作为声源坐标并进行四舍五入操作
[source_x, source_y] = np.dot(np.around(np.random.random(2), 2), 3) - 1.5
p1 = PointSource(signal=n1, mpos=m, loc=(source_x, source_y, 2.5))
# p2 = PointSource(signal=n2, mpos=m, loc=(0.15,0,0.3))
# p3 = PointSource(signal=n3, mpos=m, loc=(0,0.1,0.3))
# p = Mixer(source = p1, sources = [p2])
p = Mixer(source=p1)
# 保存文件名
os.makedirs(
'/home3/zengwh/VoiceRec/data/compute/100000_data/Val/one_source',
exist_ok=True)
h5savefile = '/home3/zengwh/VoiceRec/data/compute/100000_data/Val/one_source/x_{:.2f}_y_{:.2f}_rms_{:.2f}_sources.h5'.format(
source_x, source_y, Rms)
wh5 = WriteH5(source=p, name=h5savefile)
#print(wh5)
wh5.save()
h5 = h5py.File(h5savefile)
h5 = h5['time_data'][::50, :]