def goSino(): na,ka = 1,0 # sampling for inverse A of wavelet in PP image nb,kb = 1,0 # sampling for inverse B of wavelet in PS image nc,kc = 201,-100 # sampling for wavelet C in PP image nd,kd = 201,-100 # sampling for wavelet D in PS image nt,dt,ft = 501,0.004,0.000 # used for plotting only nx,dx,fx = 21,0.015,0.000 #nx,dx,fx = 721,0.015,0.000 sa = Sampling(na,dt,ka*dt) sb = Sampling(nb,dt,kb*dt) sc = Sampling(nc,dt,kc*dt) sd = Sampling(nd,dt,kd*dt) st = Sampling(nt,dt,ft) sx = Sampling(nx,dx,fx) tmin,tmax = 100,400 # PP time window sfac = 0.0 # stabilization factor f,g,u = getSinoImages() # PP image, PS image, and warping u(t,x) ww = WaveletWarpingAB() ww.setTimeRange(tmin,tmax) ww.setStabilityFactor(sfac) aw,bw = ww.getInverseAB(na,ka,nb,kb,u,f,g) # estimated inverses A & B dump(aw); dump(bw) cw = ww.getInverse(na,ka,aw,nc,kc) # estimated wavelet C dw = ww.getInverse(nb,kb,bw,nd,kd) # estimated wavelet D sg = ww.warp(u,g) af = ww.convolve(na,ka,aw,f) bg = ww.convolve(nb,kb,bw,g) sbg = ww.warp(u,bg) csbg = ww.convolve(nc,kc,cw,sbg) plotImage(st,sx,f,zoom=True,png="f") plotImage(st,sx,sg,zoom=True,png="sg") plotImage(st,sx,csbg,zoom=True,png="csbg") plotWaveletsPpPs(sc,cw,dw,png="cd")
def goSimpleTest():
nt,ni = 981,50 # number of time samples; number of impulses
freq,decay = 0.08,0.05 # peak frequency and decay for wavelet
na,ka = 3,0 # sampling for inverse wavelet A
nb,kb = 3,0 # sampling for inverse wavelet B
nc,kc = 181,-90 # sampling for wavelet C
nd,kd = 181,-90 # sampling for wavelet D
dt,ft = 0.004,0.000 # used for plotting only
tmin,tmax = 0,nt-1
st = Sampling(nt,dt,ft)
for mp in [True]: # True, for minimum-phase; False for other
ck = getWavelet(freq,decay,nc,kc,mp) # known wavelet C
dk = getWavelet(freq,decay,nc,kc,mp) # known wavelet D
normalizeMax(ck)
normalizeMax(dk)
#for r0,r1 in [(3.0,1.5),(2.0,2.0)]: # <1 for stretch; >1 for squeeze
for r0,r1 in [(3.0,1.5)]: # <1 for stretch; >1 for squeeze
title = "r0 = "+str(r0)+" r1 = "+str(r1)
if r0>1.0:
u,p,q = logupq(r0,r1,nt,ni)
else:
u,p,q = nmoupq(r0,r1,nt,ni)
f = addWavelet(freq,decay,p,mp)
g = addWavelet(freq,decay,q,mp)
ww = WaveletWarpingAB()
ww.setTimeRange(tmin,tmax)
aw,bw = ww.getInverseAB(na,ka,nb,kb,u,f,g) # estimated inverses A & B
ak = ww.getInverse(nc,kc,ck,na,ka) # known inverse wavelet A
bk = ww.getInverse(nd,kd,dk,nb,kb) # known inverse wavelet B
#dump(ak); dump(bk);
dump(aw); dump(bw)
cw = ww.getInverse(na,ka,aw,nc,kc) # estimated wavelet C
dw = ww.getInverse(nb,kb,bw,nd,kd) # estimated wavelet D
sg = ww.warp(u,g)
af = ww.convolve(na,ka,aw,f)
bg = ww.convolve(nb,kb,bw,g)
sbg = ww.warp(u,bg)
csbg = ww.convolve(nc,kc,cw,sbg)
normalizeMax(cw)
normalizeMax(dw)
plotSequences(st,[f,g],labels=["f","g"],title=title)
plotSequences(st,[af,bg],labels=["Af","Bg"],title=title)
plotSequences(st,[af,sbg],labels=["Af","SBg"],title=title)
plotSequences(st,[f,sg],labels=["f","Sg"],title=title)
plotSequences(st,[f,csbg],labels=["f","CSBg"],title=title)
plotWavelets(Sampling(nc,dt,kc*dt),[cw,ck],title=title+" C")
plotWavelets(Sampling(nd,dt,kd*dt),[dw,dk],title=title+" D")