def fbeamformers():
bb = BeamformerBase(freq_data=f, steer=st, r_diag=True, cached=False)
be = BeamformerEig(freq_data=f, steer=st, r_diag=True, n=54, cached=False)
#frequency beamformers to test
bbase = BeamformerBase(freq_data=f, steer=st, r_diag=True, cached=False)
bc = BeamformerCapon(freq_data=f, steer=st, cached=False)
beig = BeamformerEig(freq_data=f,
steer=st,
r_diag=True,
n=54,
cached=False)
bm = BeamformerMusic(freq_data=f, steer=st, n=6, cached=False)
bd = BeamformerDamas(beamformer=bb, n_iter=10, cached=False)
bdp = BeamformerDamasPlus(beamformer=bb, n_iter=100, cached=False)
bo = BeamformerOrth(beamformer=be,
eva_list=list(range(38, 54)),
cached=False)
bs = BeamformerCleansc(freq_data=f, steer=st, r_diag=True, cached=False)
bcmf = BeamformerCMF(freq_data=f,
steer=st,
method='LassoLarsBIC',
cached=False)
bl = BeamformerClean(beamformer=bb, n_iter=10, cached=False)
bf = BeamformerFunctional(freq_data=f,
steer=st,
r_diag=False,
gamma=3,
cached=False)
bgib = BeamformerGIB(freq_data=f,
steer=st,
method='LassoLars',
n=2,
cached=False)
return (bbase, bc, beig, bm, bl, bo, bs, bd, bcmf, bf, bdp, bgib)
window='Hanning',
overlap='50%',
block_size=128, #FFT-parameters
ind_low=8,
ind_high=16) #to save computational effort, only
# frequencies with indices 8..15 are used
#===============================================================================
# different beamformers in frequency domain
#===============================================================================
bb = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04)
bc = BeamformerCapon(freq_data=f, grid=g, mpos=m, c=346.04, cached=False)
be = BeamformerEig(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, n=54)
bm = BeamformerMusic(freq_data=f, grid=g, mpos=m, c=346.04, n=6)
bd = BeamformerDamas(beamformer=bb, n_iter=100)
bo = BeamformerOrth(beamformer=be, eva_list=list(range(38, 54)))
bs = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04)
bcmf = BeamformerCMF(freq_data=f, grid=g, mpos=m, c=346.04, \
method='LassoLarsBIC')
bl = BeamformerClean(beamformer=bb, n_iter=100)
bf = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, \
gamma=4)
#===============================================================================
# plot result maps for different beamformers in frequency domain
#===============================================================================
figure(1, (10, 6))
i1 = 1 #no of subplot
for b in (bb, bc, be, bm, bl, bo, bs, bd, bcmf, bf):
subplot(3, 4, i1)
i1 += 1
st = SteeringVector(grid=g, mics=m, env=env)
f = PowerSpectra(
time_data=t1,
window='Hanning',
overlap='50%',
block_size=128, #FFT-parameters
cached=False) #cached = False
bb = BeamformerBase(freq_data=f, steer=st, r_diag=True, cached=False)
bc = BeamformerCapon(freq_data=f, steer=st, cached=False)
be = BeamformerEig(freq_data=f, steer=st, r_diag=True, n=54, cached=False)
bm = BeamformerMusic(freq_data=f, steer=st, n=6, cached=False)
bd = BeamformerDamas(beamformer=bb, n_iter=100, cached=False)
bdp = BeamformerDamasPlus(beamformer=bb, n_iter=100, cached=False)
bo = BeamformerOrth(beamformer=be, eva_list=list(range(38, 54)), cached=False)
bs = BeamformerCleansc(freq_data=f, steer=st, r_diag=True, cached=False)
bcmf = BeamformerCMF(freq_data=f,
steer=st,
method='LassoLarsBIC',
cached=False)
bl = BeamformerClean(beamformer=bb, n_iter=100, cached=False)
bf = BeamformerFunctional(freq_data=f,
steer=st,
r_diag=False,
gamma=4,
cached=False)
bgib = BeamformerGIB(freq_data=f,
steer=st,
method='LassoLars',
n=10,
bcsc4Full = BeamformerCleansc(freq_data=f,
grid=g,
mpos=m,
r_diag=False,
c=346.04,
steer='true location')
Lbcsc1Rem = L_p(bcsc1Rem.synthetic(4000, 1))
Lbcsc2Rem = L_p(bcsc2Rem.synthetic(4000, 1))
Lbcsc3Rem = L_p(bcsc3Rem.synthetic(4000, 1))
Lbcsc4Rem = L_p(bcsc4Rem.synthetic(4000, 1))
Lbcsc1Full = L_p(bcsc1Full.synthetic(4000, 1))
Lbcsc2Full = L_p(bcsc2Full.synthetic(4000, 1))
Lbcsc3Full = L_p(bcsc3Full.synthetic(4000, 1))
Lbcsc4Full = L_p(bcsc4Full.synthetic(4000, 1))
bort1Rem = BeamformerOrth(beamformer=be1Rem, eva_list=list(range(4, 8)))
bort2Rem = BeamformerOrth(beamformer=be2Rem, eva_list=list(range(4, 8)))
bort3Rem = BeamformerOrth(beamformer=be3Rem, eva_list=list(range(4, 8)))
bort4Rem = BeamformerOrth(beamformer=be4Rem, eva_list=list(range(4, 8)))
bort1Full = BeamformerOrth(beamformer=be1Full, eva_list=list(range(4, 8)))
bort2Full = BeamformerOrth(beamformer=be2Full, eva_list=list(range(4, 8)))
bort3Full = BeamformerOrth(beamformer=be3Full, eva_list=list(range(4, 8)))
bort4Full = BeamformerOrth(beamformer=be4Full, eva_list=list(range(4, 8)))
Lbort1Rem = L_p(bort1Rem.synthetic(4000, 1))
Lbort2Rem = L_p(bort2Rem.synthetic(4000, 1))
Lbort3Rem = L_p(bort3Rem.synthetic(4000, 1))
Lbort4Rem = L_p(bort4Rem.synthetic(4000, 1))
Lbort1Full = L_p(bort1Full.synthetic(4000, 1))
Lbort2Full = L_p(bort2Full.synthetic(4000, 1))
Lbort3Full = L_p(bort3Full.synthetic(4000, 1))
Lbort4Full = L_p(bort4Full.synthetic(4000, 1))
bcsc3Rem = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='true level') bcsc4Rem = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='true location') bcsc1Full = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='classic') bcsc2Full = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='inverse') bcsc3Full = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='true level') bcsc4Full = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='true location') Lbcsc1Rem = L_p(bcsc1Rem.synthetic(4000,1)) Lbcsc2Rem = L_p(bcsc2Rem.synthetic(4000,1)) Lbcsc3Rem = L_p(bcsc3Rem.synthetic(4000,1)) Lbcsc4Rem = L_p(bcsc4Rem.synthetic(4000,1)) Lbcsc1Full = L_p(bcsc1Full.synthetic(4000,1)) Lbcsc2Full = L_p(bcsc2Full.synthetic(4000,1)) Lbcsc3Full = L_p(bcsc3Full.synthetic(4000,1)) Lbcsc4Full = L_p(bcsc4Full.synthetic(4000,1)) bort1Rem = BeamformerOrth(beamformer=be1Rem, eva_list=list(range(4,8))) bort2Rem = BeamformerOrth(beamformer=be2Rem, eva_list=list(range(4,8))) bort3Rem = BeamformerOrth(beamformer=be3Rem, eva_list=list(range(4,8))) bort4Rem = BeamformerOrth(beamformer=be4Rem, eva_list=list(range(4,8))) bort1Full = BeamformerOrth(beamformer=be1Full, eva_list=list(range(4,8))) bort2Full = BeamformerOrth(beamformer=be2Full, eva_list=list(range(4,8))) bort3Full = BeamformerOrth(beamformer=be3Full, eva_list=list(range(4,8))) bort4Full = BeamformerOrth(beamformer=be4Full, eva_list=list(range(4,8))) Lbort1Rem = L_p(bort1Rem.synthetic(4000,1)) Lbort2Rem = L_p(bort2Rem.synthetic(4000,1)) Lbort3Rem = L_p(bort3Rem.synthetic(4000,1)) Lbort4Rem = L_p(bort4Rem.synthetic(4000,1)) Lbort1Full = L_p(bort1Full.synthetic(4000,1)) Lbort2Full = L_p(bort2Full.synthetic(4000,1)) Lbort3Full = L_p(bort3Full.synthetic(4000,1)) Lbort4Full = L_p(bort4Full.synthetic(4000,1))
# "SlotJet.plane item assignment": (SlotJet(), "obj.plane[0] = 1."),
"SlotJet.plane array assignment": (SlotJet(),
"obj.plane = array((1., 0., 0.))"),
# "OpenJet.origin item assignment": (OpenJet(), "obj.origin[0] = 1."),
"OpenJet.origin array assignment": (OpenJet(),
"obj.origin = array((1., 0., 0.))"),
# "RotatingFlow.origin item assignment": (RotatingFlow(), "obj.origin[0] = 1."),
"RotatingFlow.origin array assignment":
(RotatingFlow(), "obj.origin = array((1., 0., 0.))"),
#fbeamform.py
# "SteeringVector.ref item assignment": (SteeringVector(), "obj.ref[0] = 1."),
"SteeringVector.ref array assignment": (SteeringVector(),
"obj.ref = array((1., 1., 1.))"),
# "BeamformerOrth.eva_list item assignment": (BeamformerOrth(eva_list=array((0, 1))), "obj.eva_list[0] = 2"),
"BeamformerOrth.eva_list array assignment":
(BeamformerOrth(eva_list=array((0, 1))), "obj.eva_list = array((2))"),
#grids.py
"MergeGrid.grids item assignment": (MergeGrid(grids=[RectGrid()]),
"obj.grids[0] = RectGrid()"),
"MergeGrid.grids list assignment": (MergeGrid(),
"obj.grids = [RectGrid()]"),
# signals.py
# "FiltWNoiseGenerator.ar item assignment": (FiltWNoiseGenerator(ar=[1.,2.,3.]), "obj.ar[0] = 0."),
"FiltWNoiseGenerator.ar array assignment":
(FiltWNoiseGenerator(ar=[1., 2., 3.]), "obj.ar = array((0., 0., 0.))"),
# "FiltWNoiseGenerator.ma item assignment": (FiltWNoiseGenerator(ma=[1.,2.,3.]), "obj.ma[0] = 0."),
"FiltWNoiseGenerator.mar array assignment":
(FiltWNoiseGenerator(ma=[1., 2., 3.]), "obj.ma = array((0., 0., 0.))"),
#sources.py
"MaskedTimeSamples.invalid_channels item assignment":
(MaskedTimeSamples(invalid_channels=[1]), "obj.invalid_channels[0] = 0"),
# eigenvalues and eigenvectors, if only the matrix is needed then class
# PowerSpectra can be used instead
#===============================================================================
f = EigSpectra(
time_data=t1,
window='Hanning',
overlap='50%',
block_size=128, #FFT-parameters
ind_low=4,
ind_high=15) #to save computational effort, only
# frequencies with index 1-30 are used
#===============================================================================
# different beamformers in frequency domain
#===============================================================================
# first, some simple delay and sum beamformers,
# but with different steering vector types
#===============================================================================
bb0 = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, \
steer='true level', cached = False) # this is the default
bs0 = BeamformerCleansc(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, \
steer='true level', cached=False, n=200)
be0 = BeamformerEig(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, n=-1, \
steer='true level', cached=False)
bo0 = BeamformerOrth(beamformer=be0, eva_list=range(38, 54), cached=False)
from time import time
ti = time()
map = bs0.result[:]
print time() - ti, g.size