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)
# 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
map = b.synthetic(cfreq, 1)
mx = L_p(map.max())
imshow(L_p(map.T),
origin='lower',
vmin=mx - 15,
interpolation='nearest',
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,
cached=False)
class acoular_test(unittest.TestCase):
#test if microfon positions are correct
def test_mic_positions(self):
self.assertAlmostEqual(m.mpos.sum() / mpos_num.sum(), 1, 3)
csm32 = f32.csm[:] eva32 = f32.eva[:] psf32 = PointSpreadFunction(grid=g, mpos=m, c=346.04, precision='float32') psf32Res = psf32.psf[:] psf64 = PointSpreadFunction(grid=g, mpos=m, c=346.04, precision='float64') psf64Res = psf64.psf[:] bb32 = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, precision='float32') bb32Res = bb32.synthetic(cfreq,1) bb64 = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, precision='float64') bb64Res = bb64.synthetic(cfreq,1) bf = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, gamma = 60, precision='float32') bfRes = bf.synthetic(cfreq,1) # 32 Bit PSF precision bd3232 = BeamformerDamas(beamformer=bb32, n_iter=100, psf_precision='float32') bd3232Res = bd3232.synthetic(cfreq,1) bc3232 = BeamformerClean(beamformer=bb32, psf_precision='float32') bc3232Res = bc3232.synthetic(cfreq,1) bdp3232 = BeamformerDamasPlus(beamformer=bb32, n_iter=100, psf_precision='float32') bdp3232Res = bdp3232.synthetic(cfreq,1) #64 Bit bd3264 = BeamformerDamas(beamformer=bb32, n_iter=100, psf_precision='float64') bd3264Res = bd3264.synthetic(cfreq,1) bc3264 = BeamformerClean(beamformer=bb32, psf_precision='float64') bc3264Res = bc3264.synthetic(cfreq,1)
r_diag=False,
c=346.04,
steer='true location')
Lbb1Rem = L_p(bb1Rem.synthetic(4000, 1))
Lbb2Rem = L_p(bb2Rem.synthetic(4000, 1))
Lbb3Rem = L_p(bb3Rem.synthetic(4000, 1))
Lbb4Rem = L_p(bb4Rem.synthetic(4000, 1))
Lbb1Full = L_p(bb1Full.synthetic(4000, 1))
Lbb2Full = L_p(bb2Full.synthetic(4000, 1))
Lbb3Full = L_p(bb3Full.synthetic(4000, 1))
Lbb4Full = L_p(bb4Full.synthetic(4000, 1))
bf1Rem = BeamformerFunctional(freq_data=f,
grid=g,
mpos=m,
r_diag=True,
c=346.04,
steer='classic',
gamma=3)
bf2Rem = BeamformerFunctional(freq_data=f,
grid=g,
mpos=m,
r_diag=True,
c=346.04,
steer='inverse',
gamma=3)
bf3Rem = BeamformerFunctional(freq_data=f,
grid=g,
mpos=m,
r_diag=True,
c=346.04,
bb3Rem = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='true level') bb4Rem = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='true location') bb1Full = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='classic') bb2Full = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='inverse') bb3Full = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='true level') bb4Full = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='true location') Lbb1Rem = L_p(bb1Rem.synthetic(4000,1)) Lbb2Rem = L_p(bb2Rem.synthetic(4000,1)) Lbb3Rem = L_p(bb3Rem.synthetic(4000,1)) Lbb4Rem = L_p(bb4Rem.synthetic(4000,1)) Lbb1Full = L_p(bb1Full.synthetic(4000,1)) Lbb2Full = L_p(bb2Full.synthetic(4000,1)) Lbb3Full = L_p(bb3Full.synthetic(4000,1)) Lbb4Full = L_p(bb4Full.synthetic(4000,1)) bf1Rem = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='classic', gamma=3) bf2Rem = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='inverse', gamma=3) bf3Rem = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='true level', gamma=3) bf4Rem = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, steer='true location', gamma=3) bf1Full = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='classic', gamma=3) bf2Full = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='inverse', gamma=3) bf3Full = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='true level', gamma=3) bf4Full = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=False, c=346.04, steer='true location', gamma=3) Lbf1Rem = L_p(bf1Rem.synthetic(4000,1)) Lbf2Rem = L_p(bf2Rem.synthetic(4000,1)) Lbf3Rem = L_p(bf3Rem.synthetic(4000,1)) Lbf4Rem = L_p(bf4Rem.synthetic(4000,1)) Lbf1Full = L_p(bf1Full.synthetic(4000,1)) Lbf2Full = L_p(bf2Full.synthetic(4000,1)) Lbf3Full = L_p(bf3Full.synthetic(4000,1)) Lbf4Full = L_p(bf4Full.synthetic(4000,1))
#===============================================================================
f = EigSpectra(time_data=t1,
window='Hanning', overlap='50%', block_size=128, #FFT-parameters
ind_low=7, ind_high=15) #to save computational effort, only
# frequencies with index 1-30 are used
#===============================================================================
# beamformers in frequency domain
#===============================================================================
bb = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04)
bd = BeamformerDamas(beamformer=bb, n_iter=100)
be = BeamformerEig(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, n=54)
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)
bf = BeamformerFunctional(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, gamma = 60)
#===============================================================================
# plot result maps for different beamformers in frequency domain
#===============================================================================
fi = 1 #no of figure
for r_diag in (True,False):
figure(fi)
suptitle('Old Implementation | R_diag=' + str(r_diag))
fi +=1
bb.r_diag = r_diag
be.r_diag = r_diag
bs.r_diag = r_diag
block_size=128, #FFT-parameters
ind_low=7,
ind_high=15) #to save computational effort, only
# frequencies with index 1-30 are used
#===============================================================================
# beamformers in frequency domain
#===============================================================================
bb = BeamformerBase(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04)
bd = BeamformerDamas(beamformer=bb, n_iter=100)
be = BeamformerEig(freq_data=f, grid=g, mpos=m, r_diag=True, c=346.04, n=54)
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)
bf = BeamformerFunctional(freq_data=f,
grid=g,
mpos=m,
r_diag=True,
c=346.04,
gamma=60)
#===============================================================================
# plot result maps for different beamformers in frequency domain
#===============================================================================
fi = 1 #no of figure
for r_diag in (True, False):
figure(fi)
suptitle('Old Implementation | R_diag=' + str(r_diag))
fi += 1
bb.r_diag = r_diag
be.r_diag = r_diag
bs.r_diag = r_diag