本文整理汇总了Python中fault.FaultSemblance.taper方法的典型用法代码示例。如果您正苦于以下问题：Python FaultSemblance.taper方法的具体用法？Python FaultSemblance.taper怎么用？Python FaultSemblance.taper使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类fault.FaultSemblance的用法示例。
在下文中一共展示了FaultSemblance.taper方法的9个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: goShifts
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goShifts():
s1, s2, g = getImage()
g = slog(g)
plot2(s1, s2, g, title="log input")
fse = FaultSemblance()
g = fse.taper(10, g)
p = fse.slopes(g)
sn, sd = fse.semblanceNumDen(p, g)
fsc = FaultScanner2(sigmaTheta, [sn, sd], smoother)
f, t = fsc.scan(-15, 15)
# plot2(s1,s2,g,f,gmin=0,gmax=1,title="fault likelihood")
# ff,tt = fsc.thin([f,t])
# plot2(s1,s2,g,ff,gmin=0,gmax=1,title="fault likelihood")
shiftMin, shiftMax = -20, 20
faults = fsc.findFaults([f, t], shiftMax - shiftMin)
ff = faults.getLikelihoods()
# plot2(s1,s2,g,ff,gmin=0,gmax=1,title="fault likelihood")
# plot2(s1,s2,g,ff,gmin=0,gmax=1,label="Fault likelihood",png="flg")
g = fsc.smooth(4, p, ff, g)
# plot2(s1,s2,g,ff,gmin=0,gmax=1,title="input smoothed")
# plot2(s1,s2,g,ff,gmin=0,gmax=1,label="Fault likelihood",png="flgs")
plot2(s1, s2, g, label="Log amplitude", png="gs")
p = fse.slopes(g)
faults.findShifts(g, p, shiftMin, shiftMax)
faults.clean()
s = faults.getShifts()
s = mul(s1.delta * 1000.0, s)
print "s min =", min(s), " max =", max(s)示例2: goThin
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goThin():
s1, s2, g = getImage()
g = slog(g)
# plot2(s1,s2,g,title="log input")
fse = FaultSemblance()
g = fse.taper(10, g)
for iter in range(1):
p = fse.slopes(g)
# p = zerofloat(len(p[0]),len(p))
sn, sd = fse.semblanceNumDen(p, g)
fsc = FaultScanner2(sigmaTheta, [sn, sd], smoother)
f, t = fsc.scan(-15, 15)
# plot2(s1,s2,g,f,gmin=0,gmax=1,title="fault likelihood")
# plot2(s1,s2,g,t,title="fault dip (degrees)")
fs = copy(f)
RecursiveGaussianFilter(1.0).apply00(fs, fs)
# plot2(s1,s2,g,fs,gmin=0,gmax=1,title="fault likelihood smoothed")
plot2(s1, s2, g, fs, gmin=0.5, gmax=1, gmap=jetr, label="Fault likelihood")
ft, tt = fsc.thin([f, t])
# plot2(s1,s2,g,ft,gmin=0,gmax=1,title="fault likelihood thinned")
# plot2(s1,s2,g,tt,title="fault dip (degrees) thinned")
plot2(s1, s2, g, ft, gmin=0.5, gmax=1, gmap=jetr, label="Fault likelihood", png="flt")
plot2(s1, s2, g, tt, gmap=bwrn, label="Fault dip (degrees)", png="ftt")
g = fsc.smooth(8, p, ft, g)
# plot2(s1,s2,g,title="input smoothed")
plot2(s1, s2, g, label="Log amplitude", png="gs")示例3: goShifts
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goShifts():
s1,s2,g = getImage()
g = slog(g)
plot2(s1,s2,g,title="log input")
fse = FaultSemblance()
g = fse.taper(10,g)
p = fse.slopes(g)
sn,sd = fse.semblanceNumDen(p,g)
fsc = FaultScanner2(sigmaTheta,[sn,sd],smoother)
f,t = fsc.scan(-15,15)
plot2(s1,s2,g,f,gmin=0,gmax=1,title="fault likelihood")
#ff,tt = fsc.thin([f,t])
#plot2(s1,s2,g,ff,gmin=0,gmax=1,title="fault likelihood")
shiftMin,shiftMax = -20,20
faults = fsc.findFaults([f,t],shiftMax-shiftMin);
ff = faults.getLikelihoods()
plot2(s1,s2,g,ff,gmin=0,gmax=1,title="fault likelihood")
g = fsc.smooth(4,p,ff,g)
plot2(s1,s2,g,ff,gmin=0,gmax=1,title="input smoothed")
p = fse.slopes(g)
faults.findShifts(g,p,shiftMin,shiftMax)
faults.clean()
s = faults.getShifts()
print "s min =",min(s)," max =",max(s)
plot2(s1,s2,g,s,gmin=-8,gmax=8,title="fault throws")示例4: goShifts
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goShifts():
s1,s2,g = getImage()
g = slog(g)
#plot2(s1,s2,g,title="log input")
fse = FaultSemblance()
g = fse.taper(10,g)
p = fse.slopes(g)
sn,sd = fse.semblanceNumDen(p,g)
fsc = FaultScanner2(sigmaTheta,[sn,sd],smoother)
f,t = fsc.scan(-15,15)
shiftMin,shiftMax = -20,20
faults = fsc.findFaults([f,t],shiftMax-shiftMin);
ff = faults.getLikelihoods()
plot2(s1,s2,g,ff,gmin=0,gmax=1,gmap=jetr,label="Fault likelihood",png="flg")
g = fsc.smooth(4,p,ff,g)
plot2(s1,s2,g,ff,gmin=0,gmax=1,gmap=jetr,label="Fault likelihood",png="flgs")
plot2(s1,s2,g,label="Log amplitude",png="gs")
p = fse.slopes(g)
faults.findShifts(g,p,shiftMin,shiftMax)
faults.clean()
s = faults.getShifts()
s = mul(s1.delta*1000.0,s)
s = neg(s)
print "s min =",min(s)," max =",max(s)
plot2(s1,s2,g,s,gmin=0,gmax=28,gmap=jetr,
label="Vertical component of throw (ms)",png="fs")
plot2(s1,s2,g,s,gmin=0,gmax=15,gmap=jetr,
label="Vertical component of throw (ms)",png="fs15")示例5: goScan
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goScan():
s1,s2,g = getImage()
g = slog(g)
fse = FaultSemblance()
g = fse.taper(10,g)
p = fse.slopes(g)
sn,sd = fse.semblanceNumDen(p,g)
fsc = FaultScanner2(sigmaTheta,[sn,sd])
st = Sampling(31,1.0,-15.0)
for theta in st.values:
f = fsc.likelihood(theta)
plot2(s1,s2,g,f,gmin=0,gmax=1,title="theta = "+str(int(theta)))
tmin,tmax = st.first,st.last
f,t = fsc.scan(tmin,tmax)
plot2(s1,s2,g,f,gmin=0,gmax=1,title="fault likelihood")
plot2(s1,s2,g,t,gmin=tmin,gmax=tmax,title="fault dip (degrees)")示例6: goScan
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goScan():
s1,s2,g = getImage()
g = slog(g)
fse = FaultSemblance()
g = fse.taper(10,g)
p = fse.slopes(g)
sn,sd = fse.semblanceNumDen(p,g)
fsc = FaultScanner2(sigmaTheta,[sn,sd])
st = Sampling(31,1.0,-15.0)
for theta in st.values:
f = fsc.likelihood(theta)
png = "fl"+str(int(theta))
plot2(s1,s2,g,f,gmin=0,gmax=1,gmap=jetr,label="Fault likelihood",png=png)
tmin,tmax = st.first,st.last
f,t = fsc.scan(tmin,tmax)
plot2(s1,s2,g,f,gmin=0,gmax=1,gmap=jetr,label="Fault likelihood",png="fl")示例7: goScan
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goScan():
s1,s2,g = getImage()
g = slog(g)
fse = FaultSemblance()
g = fse.taper(10,g)
#p = fse.slopes(g)
p = getSlopes(g)
sn,sd = fse.semblanceNumDen(p,g)
fsc = FaultScanner2(sigmaTheta,[sn,sd],FaultScanner2.Smoother.FFT)
st = Sampling(25,2.0,-25.0)
for theta in st.values:
f = fsc.likelihood(theta)
plot2(s1,s2,g,f,gmin=0.2,gmax=0.7,gmap=jetr,
title="theta = "+str(int(theta)))
tmin,tmax = st.first,st.last
f,t = fsc.scan(tmin,tmax)
plot2(s1,s2,g,f,gmin=0.2,gmax=0.7,gmap=jetr,title="fault likelihood")示例8: goSemblance
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
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)示例9: goThin
# 需要导入模块: from fault import FaultSemblance [as 别名]
# 或者: from fault.FaultSemblance import taper [as 别名]
def goThin():
s1,s2,g = getImage()
plot2(s1,s2,g,title="input")
g = slog(mul(2.0,g))
plot2(s1,s2,g,title="log input")
fse = FaultSemblance()
g = fse.taper(10,g)
for iter in range(1):
#p = fse.slopes(g)
p = getSlopes(g)
#p = zerofloat(len(p[0]),len(p))
sn,sd = fse.semblanceNumDen(p,g)
fsc = FaultScanner2(sigmaTheta,[sn,sd],smoother)
f,t = fsc.scan(-25,25)
plot2(s1,s2,g,f,gmin=0,gmax=1,title="fault likelihood")
#plot2(s1,s2,g,t,title="fault dip (degrees)")
ft,tt = fsc.thin([f,t])
plot2(s1,s2,g,ft,gmin=0,gmax=1,title="fault likelihood thinned")
#plot2(s1,s2,g,tt,title="fault dip (degrees) thinned")
g = fsc.smooth(16,p,ft,g)
plot2(s1,s2,g,title="input smoothed")