# ISTFT
recons = simmch.istft_mch(out_spec, win, step)
simmch.save_mch_wave(recons * 32767.0, "recons_eigen.wav")
quit()
#print spec1_temp.shape
#print spec2_temp.shape
#win_size=50
# spec[ch, frame, freq_bin]
# w[ch2,ch1]
w, _, _ = wiener_filter_freq(spec1_temp,
spec2_temp,
win_size=nframe,
r_step=1)
print "# filter:", w.shape
if options.tf is not None:
tf_config = read_hark_tf(options.tf)
if (len(w.shape) == 3):
for i in xrange(len(w.shape)):
save_sidelobe("sidelobe_wiener%i.png" % (i + 1), tf_config,
w[:, :, i], sidelobe_freq_bin)
else:
save_sidelobe("sidelobe_wiener.png", tf_config, w,
sidelobe_freq_bin)
# filter
out_spec = apply_filter_freq(spec1_temp, w)
# ISTFT
recons = simmch.istft_mch(out_spec, win, step)
#recons.reshape((recons.shape[0],1))
simmch.save_mch_wave(recons * 32767.0, "recons_wiener.wav")
w=wiener_filter_eigen(spec1_temp,spec2_temp,win_size=nframe,r_step=1)
print "# filter:",w.shape
out_spec=apply_filter_eigen(spec1_temp,w)
# ISTFT
recons=simmch.istft_mch(out_spec, win, step)
simmch.save_mch_wave(recons*32767.0,"recons_eigen.wav")
quit()
#print spec1_temp.shape
#print spec2_temp.shape
#win_size=50
# spec[ch, frame, freq_bin]
# w[ch2,ch1]
w,_,_=wiener_filter_freq(spec1_temp,spec2_temp,win_size=nframe,r_step=1)
print "# filter:",w.shape
if options.tf is not None:
tf_config=read_hark_tf(options.tf)
if(len(w.shape)==3):
for i in xrange(len(w.shape)):
save_sidelobe("sidelobe_wiener%i.png"%(i+1),tf_config,w[:,:,i],sidelobe_freq_bin)
else:
save_sidelobe("sidelobe_wiener.png",tf_config,w,sidelobe_freq_bin)
# filter
out_spec=apply_filter_freq(spec1_temp,w)
# ISTFT
recons=simmch.istft_mch(out_spec, win, step)
#recons.reshape((recons.shape[0],1))
simmch.save_mch_wave(recons*32767.0,"recons_wiener.wav")
nch=spec1.shape[0]
nframe=spec1.shape[1]
nfreq_bin=spec1.shape[2]
sidelobe_freq_bin=int(np.floor(2000/df))
### DS beamformer & blocked signals
ds_freq=np.zeros((nframe,nfreq_bin),dtype=complex)
blocked_freq=np.zeros((spec1.shape[0]-1,spec1.shape[1],spec1.shape[2]),dtype=complex)
for t in xrange(spec1.shape[1]):
for freq_bin in xrange(spec1.shape[2]):
blocked_freq[:,t,freq_bin]=B.dot(A[freq_bin,:,:].dot(spec1[:,t,freq_bin]))
ds_freq[t,freq_bin]=np.dot(a_vec[freq_bin,:],spec1[:,t,freq_bin])/nch
ds_freq=np.array([ds_freq])
### GSC for DS beamformer
w_a,_,_=wiener_filter.wiener_filter_freq(blocked_freq,ds_freq)
y_ds=wiener_filter.apply_filter_freq(blocked_freq,w_a)
save_sidelobe("sidelobe_ds.png",tf_config,a_vec,sidelobe_freq_bin)
w_gsc_ds=np.zeros((nfreq_bin,nch),dtype=complex)
for freq_bin in xrange(nfreq_bin):
w_gsc_ds[freq_bin,:]=a_vec[freq_bin,:]-w_a[freq_bin,:].dot(B.dot(A[freq_bin,:,:]))
save_sidelobe("sidelobe_gsc_ds.png",tf_config,w_gsc_ds,sidelobe_freq_bin,clear_flag=False)
### MV beamformer
#rz=estimate_correlation(spec1,spec1,nframe,1)
rz=estimate_self_correlation(spec1)
#rz=np.array([rz])
w_mv=np.zeros((nfreq_bin,nch),dtype=complex)
for freq_bin in xrange(nfreq_bin):
rz_inv=np.linalg.inv(rz[0,freq_bin,:,:])
av=a_vec[freq_bin,:].reshape((nch,1))
temp=rz_inv.dot(av)
po=av.T.conj().dot(temp)
#w[freq_bin,:]=temp.dot(np.linalg.inv(po))
