def goSimpleTest():
nt,ni = 481,2 # number of time samples; number of impulses
freq,decay = 0.08,0.05 # peak frequency and decay for wavelet
na,ka = 81,-20 # sampling for inverse wavelet A
#na,ka = 5,-2 # sampling for inverse wavelet A
nh,kh = 181,-90 # sampling for wavelet H
dt,ft = 0.004,0.000 # used for plotting only
tmin,tmax = 0,nt-1
sfac = 1.000
st = Sampling(nt,dt,ft)
for mp in [True,False]: # True, for minimum-phase; False for other
hk = getWavelet(freq,decay,nh,kh,mp) # known wavelet
for r in [0.5,2.0]: # 0.5 for stretch; 2.0 for squeeze
aw = zerofloat(na); aw[-ka] = 1.0
hw = zerofloat(nh); hw[-kh] = 1.0
p,q = makeImpulses(r,nt,ni)
f = addWavelet(freq,decay,p,mp)
g = addWavelet(freq,decay,q,mp)
u = rampfloat(0.0,r,nt)
bpf = None
if r<=1.0:
u = add((1.0-r)*(nt-1),u)
bpf = BandPassFilter(0,0.5*r,0.10*r,0.01)
ww = WaveletWarpingH()
ww.setTimeRange(tmin,tmax)
ww.setStabilityFactor(sfac)
ak = ww.getWaveletH(nh,kh,hk,na,ka) # known inverse wavelet
#dump(ak)
for iter in range(5):
#if bpf: bpf.apply(hw,hw)
aw = ww.getInverseA(na,ka,nh,kh,hw,u,f,g) # estimated inverse
#hw = ww.getWaveletH(nh,kh,na,ka,aw,u,f,g) # estimated wavelet
hw = ww.getWaveletH(na,ka,aw,nh,kh) # estimated wavelet
#dump(aw)
sg = ww.applyS(u,g)
hslag = ww.applyHSLA(na,ka,aw,nh,kh,hw,u,g)
nhw = normalize(hw)
nhk = normalize(hk)
title = "r = "+str(r)
#plotSequences(st,[f,g],labels=["f","g"],title=title)
#plotSequences(st,[f,sg],labels=["f","Sg"],title=title)
plotSequences(st,[f,g],labels=["f","g"],title=title)
plotSequences(st,[f,hslag],labels=["f","HSLAg"],title=title)
plotWavelets(Sampling(nh,dt,kh*dt),[nhw,nhk],title=title)
def goSimpleTest():
nt,ni = 481,2 # number of time samples; number of impulses
freq,decay = 0.08,0.05 # peak frequency and decay for wavelet
na,ka = 81,-20 # sampling for inverse wavelet A
#na,ka = 5,-2 # sampling for inverse wavelet A
nh,kh = 181,-90 # sampling for wavelet H
dt,ft = 0.004,0.000 # used for plotting only
tmin,tmax = 0,nt-1
sfac = 1.000
st = Sampling(nt,dt,ft)
for mp in [True,False]: # True, for minimum-phase; False for other
hk = getWavelet(freq,decay,nh,kh,mp) # known wavelet
for r in [0.5,2.0]: # 0.5 for stretch; 2.0 for squeeze
aw = zerofloat(na); aw[-ka] = 1.0
hw = zerofloat(nh); hw[-kh] = 1.0
p,q = makeImpulses(r,nt,ni)
f = addWavelet(freq,decay,p,mp)
g = addWavelet(freq,decay,q,mp)
u = rampfloat(0.0,r,nt)
bpf = None
if r<=1.0:
u = add((1.0-r)*(nt-1),u)
bpf = BandPassFilter(0,0.5*r,0.10*r,0.01)
ww = WaveletWarpingH()
ww.setTimeRange(tmin,tmax)
ww.setStabilityFactor(sfac)
ak = ww.getWaveletH(nh,kh,hk,na,ka) # known inverse wavelet
#dump(ak)
for iter in range(5):
if bpf: bpf.apply(hw,hw)
aw = ww.getInverseA(na,ka,nh,kh,hw,u,f,g) # estimated inverse
hw = ww.getWaveletH(na,ka,aw,nh,kh) # estimated wavelet
#dump(aw)
sg = ww.applyS(u,g)
hslag = ww.applyHSLA(na,ka,aw,nh,kh,hw,u,g)
nhw = normalizeMax(hw)
nhk = normalizeMax(hk)
title = "r = "+str(r)
#plotSequences(st,[f,g],labels=["f","g"],title=title)
#plotSequences(st,[f,sg],labels=["f","Sg"],title=title)
plotSequences(st,[f,g],labels=["f","g"],title=title)
plotSequences(st,[f,hslag],labels=["f","HSLAg"],title=title)
plotWavelets(Sampling(nh,dt,kh*dt),[nhw,nhk],title=title)
def goSino():
na,ka = 21,-10 # sampling for inverse A of wavelet in PS image
nh,kh = 21,-10 # sampling for wavelet H in PP image
nt,dt,ft = 501,0.004,0.000 # used for plotting only
nx,dx,fx = 721,0.015,0.000
sa = Sampling(na,dt,ka*dt)
sh = Sampling(nh,dt,kh*dt)
st = Sampling(nt,dt,ft)
sx = Sampling(nx,dx,fx)
tmin,tmax = 100,400 # PP time window
sfac = 1.000 # stabilization factor
f,g,u = getSinoImages() # PP image, PS image, and warping u(t,x)
ww = WaveletWarpingH()
ww.setTimeRange(tmin,tmax)
ww.setStabilityFactor(sfac)
slg = ww.applyS(u,ww.applyL(u,g)) # PS warping without wavelets
plotImage(st,sx,f,zoom=True,png="pp")
plotImage(st,sx,slg,zoom=True,png="psw1")
e1 = ww.rms(sub(f,slg))
for niter in [0]:
print "niter =",niter
suffix = str(niter)
hf = zerofloat(nh); hf[-kh] = 1.0 # initial wavelet h in f
ag = ww.getInverseA(na,ka,nh,kh,hf,u,f,g) # inverse a in g
for jiter in range(niter):
hf = ww.getWaveletH(na,ka,ag,nh,kh) # wavelet h in f
ag = ww.getInverseA(na,ka,nh,kh,hf,u,f,g) # inverse a in g
hg = ww.getWaveletH(na,ka,ag,nh,kh) # wavelet in g
hslag = ww.applyHSLA(na,ka,ag,nh,kh,hf,u,g) # PS warping with wavelets
hslag = mul(hslag,ww.rms(f)/ww.rms(hslag))
ew = ww.rms(sub(f,hslag))
print " e1 =",e1," ew =",ew
plotImage(st,sx,hslag,zoom=True,png="psww"+suffix)
plotWaveletsPpPs(sh,hf,hg,png="wavelets"+suffix)
