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)