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 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()
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) \
for i in linspace(0.0, 1.0, 8, False)]).T
# 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 ) # show map imshow( Lm.T, origin='lower', vmin=Lm.max()-10, extent=rg.extend(), \ interpolation='bicubic')
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, \
ind_low=1,ind_high=30) # CSM calculation
g = RectGrid(x_min=-3.0,
# "ChannelMixer.weights item assignment" : (ChannelMixer(weights=[[1.,2.,3.]]), "obj.weights[0] = 0."),
"ChannelMixer.weights new array assignment": (ChannelMixer(
weights=[[1., 2., 3.]]), "obj.weights = array([0.])"),
# "SpatialInterpolator.Q item assignment": (SpatialInterpolator(), "obj.Q[0] = 0."),
"SpatialInterpolator.Q array assignment":
(SpatialInterpolator(),
"obj.Q = array([[0.,0.,0.],[0.,0.,0.],[0.,0.,0.]])"),
# "SpatialInterpolatorRotation.Q item assignment": (SpatialInterpolatorRotation(), "obj.Q[0] = 0."),
"SpatialInterpolatorRotation.Q array assignment":
(SpatialInterpolatorRotation(),
"obj.Q = array([[0.,0.,0.],[0.,0.,0.],[0.,0.,0.]])"),
# "SpatialInterpolatorConstantRotation.Q item assignment": (SpatialInterpolatorConstantRotation(), "obj.Q[0] = 0."),
"SpatialInterpolatorConstantRotation.Q array assignment":
(SpatialInterpolatorConstantRotation(),
"obj.Q = array([[0.,0.,0.],[0.,0.,0.],[0.,0.,0.]])"),
"Mixer.sources item assignment": (Mixer(sources=[SamplesGenerator()]),
"obj.sources[0] = SamplesGenerator()"),
"Mixer.sources list assignment": (Mixer(sources=[SamplesGenerator()]),
"obj.sources = [SamplesGenerator()]"),
"WriteWAV.channels item assignment": (WriteWAV(channels=[1]),
"obj.channels[0] = 0"),
"WriteWAV.channels list assignment": (WriteWAV(), "obj.channels = [0]"),
}
class Test_DigestChange(TestCase):
"""Test that ensures that digest of Acoular classes changes correctly on
changes of CArray and List attributes.
"""
def get_digests(self, obj, statement):
"""A function that collects the digest of the obj before (d1) and
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, :]
os.system("rm {}".format(h5savefile))
np.save(h5savefile[:-2] + 'npy', h5)