def goAlign(): s1,s2,g = getImage() g = slog(g) n1,n2 = len(g[0]),len(g) fse = FaultSemblance() p = fse.slopes(g) ref = RecursiveExponentialFilter(4) sn,sd = fse.semblanceNumDen(p,g) ref.apply1(sn,sn) ref.apply1(sd,sd) s = fse.semblanceFromNumDen(sn,sd) plot2(s1,s2,g,s,gmin=0,gmax=1,title="semblance with alignment") p = zerofloat(n1,n2) # semblance with zero slopes sn,sd = fse.semblanceNumDen(p,g) ref.apply1(sn,sn) ref.apply1(sd,sd) s = fse.semblanceFromNumDen(sn,sd) plot2(s1,s2,g,s,gmin=0,gmax=1,title="semblance without alignment")
def goAlign(): s1,s2,g = getImage() g = slog(g) n1,n2 = len(g[0]),len(g) fse = FaultSemblance() p = fse.slopes(g) ref = RecursiveExponentialFilter(4) sn,sd = fse.semblanceNumDen(p,g) ref.apply1(sn,sn) ref.apply1(sd,sd) s = fse.semblanceFromNumDen(sn,sd) plot2(s1,s2,g,s,gmin=0,gmax=1,title="semblance with alignment") p = zerofloat(n1,n2) # semblance with zero slopes sn,sd = fse.semblanceNumDen(p,g) ref.apply1(sn,sn) ref.apply1(sd,sd) s = fse.semblanceFromNumDen(sn,sd) plot2(s1,s2,g,s,gmin=0,gmax=1,title="semblance without alignment")
def goSemblance():
s1,s2,g = getImage()
g = slog(g)
fse = FaultSemblance()
g = fse.taper(10,g)
p = fse.slopes(g)
sn0,sd0 = fse.semblanceNumDen(p,g)
print "semblances for different vertical smoothings:"
for sigma in [0,2,4,8]:
ref = RecursiveExponentialFilter(sigma)
sn = copy(sn0)
sd = copy(sd0)
ref.apply1(sn,sn)
ref.apply1(sd,sd)
s = fse.semblanceFromNumDen(sn,sd)
print "sigma =",sigma," s min =",min(s)," max =",max(s)
title = "semblance: sigma = "+str(sigma)
plot2(s1,s2,g,s,gmin=0,gmax=1,title=title)
def goSemblance():
s1,s2,g = getImage()
g = slog(g)
fse = FaultSemblance()
g = fse.taper(10,g)
p = fse.slopes(g)
sn0,sd0 = fse.semblanceNumDen(p,g)
print "semblances for different vertical smoothings:"
for sigma in [0,2,4,8]:
ref = RecursiveExponentialFilter(sigma)
sn = copy(sn0)
sd = copy(sd0)
ref.apply1(sn,sn)
ref.apply1(sd,sd)
s = fse.semblanceFromNumDen(sn,sd)
print "sigma =",sigma," s min =",min(s)," max =",max(s)
title = "semblance: sigma = "+str(sigma)
plot2(s1,s2,g,s,gmin=0,gmax=1,title=title)
