def goSinoTraces(): na,ka = 41,-20 # sampling for inverse A nh,kh = 41,-20 # sampling for wavelet H 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) f,g,u = getSinoTraces(16) # PP trace f(t), PS trace g(u), and warping u(t) ww = WaveletWarpingAH() ww.setTimeRange(100,500) # PP time window ww.setStabilityFactor(0.001) # stability factor ww.setMaxIterations(100) # max Gauss-Newton iterations a,h = ww.getAHGaussNewton(na,ka,nh,kh,u,f,g) sg = ww.warp(u,g) ag = ww.convolve(na,ka,a,g) sag = ww.warp(u,ag) hsag = ww.convolve(nh,kh,h,sag) dump(a) g = copy(nt,g) sg = copy(nt,sg) sag = copy(nt,sag) hsag = copy(nt,hsag) fmhsag= sub(f,hsag) plotWavelets(sa,[a],title="A") plotWavelets(sh,[h],title="H") plotTraces(st,[f,hsag,fmhsag],labels=["f","HSAg","f-HSAg"])
def goSinoImages(): na,ka = 21,-10 # sampling for inverse A nh,kh = 81,-40 # sampling for wavelet H nt,dt,ft = 501,0.004,0.000 # used for plotting only #nx,dx,fx = 721,0.015,0.000 nx,dx,fx = 101,0.015,0.000 sa = Sampling(na,dt,ka*dt) sh = Sampling(nh,dt,kh*dt) st = Sampling(nt,dt,ft) sx = Sampling(nx,dx,fx) tmin,tmax = 100,500 # PP time window f,g,u = getSinoImages() # PP image, PS image, and warping u(t,x) ww = WaveletWarpingAH() ww.setTimeRange(100,400) # PP time window ww.setStabilityFactor(0.0001) # stability factor ww.setMaxIterations(20) # max Gauss-Newton iterations a,h = ww.getAHGaussNewton(na,ka,nh,kh,u,f,g) dump(a) sg = ww.warp(u,g) ag = ww.convolve(na,ka,a,g) sag = ww.warp(u,ag) hsag = ww.convolve(nh,kh,h,sag) normalizeRms(f) normalizeRms(sg) normalizeRms(hsag) plotImage(st,sx,f,zoom=True,png="f") plotWavelets(sa,[a],title="A") plotWavelets(sh,[h],title="H") plotImage(st,sx,sg,zoom=True,png="Sg") plotImage(st,sx,hsag,zoom=True,png="HSAg")
def goSinoTraces():
na, ka = 41, -20 # sampling for inverse A
nh, kh = 41, -20 # sampling for wavelet H
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)
f, g, u = getSinoTraces(
16) # PP trace f(t), PS trace g(u), and warping u(t)
ww = WaveletWarpingAH()
ww.setTimeRange(100, 500) # PP time window
ww.setStabilityFactor(0.001) # stability factor
ww.setMaxIterations(100) # max Gauss-Newton iterations
a, h = ww.getAHGaussNewton(na, ka, nh, kh, u, f, g)
sg = ww.warp(u, g)
ag = ww.convolve(na, ka, a, g)
sag = ww.warp(u, ag)
hsag = ww.convolve(nh, kh, h, sag)
dump(a)
g = copy(nt, g)
sg = copy(nt, sg)
sag = copy(nt, sag)
hsag = copy(nt, hsag)
fmhsag = sub(f, hsag)
plotWavelets(sa, [a], title="A")
plotWavelets(sh, [h], title="H")
plotTraces(st, [f, hsag, fmhsag], labels=["f", "HSAg", "f-HSAg"])
def goSinoImages():
na, ka = 21, -10 # sampling for inverse A
nh, kh = 81, -40 # sampling for wavelet H
nt, dt, ft = 501, 0.004, 0.000 # used for plotting only
#nx,dx,fx = 721,0.015,0.000
nx, dx, fx = 101, 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, 500 # PP time window
f, g, u = getSinoImages() # PP image, PS image, and warping u(t,x)
ww = WaveletWarpingAH()
ww.setTimeRange(100, 400) # PP time window
ww.setStabilityFactor(0.0001) # stability factor
ww.setMaxIterations(20) # max Gauss-Newton iterations
a, h = ww.getAHGaussNewton(na, ka, nh, kh, u, f, g)
dump(a)
sg = ww.warp(u, g)
ag = ww.convolve(na, ka, a, g)
sag = ww.warp(u, ag)
hsag = ww.convolve(nh, kh, h, sag)
normalizeRms(f)
normalizeRms(sg)
normalizeRms(hsag)
plotImage(st, sx, f, zoom=True, png="f")
plotWavelets(sa, [a], title="A")
plotWavelets(sh, [h], title="H")
plotImage(st, sx, sg, zoom=True, png="Sg")
plotImage(st, sx, hsag, zoom=True, png="HSAg")
def goTest():
nt, ni = 981, 500 # number of time samples; number of impulses
ffreq, fdecay = 0.08, 0.05 # peak frequency and decay for wavelet
gfreq, gdecay = 0.08, 0.05 # peak frequency and decay for wavelet
na, ka = 11, -5 # sampling for inverse wavelet A
nb, kb = 11, -5 # 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
st = Sampling(nt, dt, ft)
for mp in [False]: # True, for minimum-phase; False for mixed-phase
ck = getWavelet(ffreq, fdecay, nc, kc, mp) # known wavelet C
dk = getWavelet(gfreq, gdecay, 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)
u, p, q = logupq(r0, r1, nt, ni)
f = addWavelet(ffreq, fdecay, p, mp)
g = addWavelet(gfreq, fdecay, q, mp)
ww = WaveletWarpingAH()
ww.setTimeRange(0, nt / 2)
ww.setStabilityFactor(0.0001)
ww.setMaxIterations(40)
#bw,cw = ww.getAHSimple(nb,kb,nc,kc,u,f,g);
bw, cw = ww.getAHNewton(nb, kb, nc, kc, u, f, g)
#bw,cw = ww.getAHGaussNewton(nb,kb,nc,kc,u,f,g);
print "rmse =", ww.rms(
sub(f, ww.applyHSA(nb, kb, bw, nc, kc, cw, u, g)))
dump(bw)
dw = ww.getWavelet(nd, kd, nb, kb, bw)
sg = ww.warp(u, g)
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, [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")
def goTest():
nt,ni = 981,500 # number of time samples; number of impulses
ffreq,fdecay = 0.08,0.05 # peak frequency and decay for wavelet
gfreq,gdecay = 0.08,0.05 # peak frequency and decay for wavelet
na,ka = 11,-5 # sampling for inverse wavelet A
nb,kb = 11,-5 # 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
st = Sampling(nt,dt,ft)
for mp in [False]: # True, for minimum-phase; False for mixed-phase
ck = getWavelet(ffreq,fdecay,nc,kc,mp) # known wavelet C
dk = getWavelet(gfreq,gdecay,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)
u,p,q = logupq(r0,r1,nt,ni)
f = addWavelet(ffreq,fdecay,p,mp)
g = addWavelet(gfreq,fdecay,q,mp)
ww = WaveletWarpingAH()
ww.setTimeRange(0,nt/2)
ww.setStabilityFactor(0.0001)
ww.setMaxIterations(40)
#bw,cw = ww.getAHSimple(nb,kb,nc,kc,u,f,g);
bw,cw = ww.getAHNewton(nb,kb,nc,kc,u,f,g);
#bw,cw = ww.getAHGaussNewton(nb,kb,nc,kc,u,f,g);
print "rmse =",ww.rms(sub(f,ww.applyHSA(nb,kb,bw,nc,kc,cw,u,g)))
dump(bw);
dw = ww.getWavelet(nd,kd,nb,kb,bw)
sg = ww.warp(u,g)
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,[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")