marcel/pylot
3
0
Fork 0
Code Issues 7 Pull Requests 1 Releases Wiki Activity

Modified for using TimeArray object for plotting and expanded for picking on ARH-CF.

Browse Source
This commit is contained in:
Ludger Küperkoch 2014-12-11 15:57:25 +01:00
parent 112e0bc7fa
commit 201c34a85b
1 changed files with 37 additions and 20 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

57
pylot/core/pick/run_makeCF.py
View File

@ -58,24 +58,19 @@ def run_makeCF(project, database, event, iplot, station=None):
############################################################## ##############################################################
#calculate HOS-CF using subclass HOScf of class CharacteristicFunction #calculate HOS-CF using subclass HOScf of class CharacteristicFunction
hoscf = HOScf(st_copy, cuttimes, t2, p) #instance of HOScf hoscf = HOScf(st_copy, cuttimes, t2, p) #instance of HOScf
#get corresponding time array -> unnecessary because implemented in CharacteristicFunction
# thoscf = np.arange(0, len(hoscf.getCF()) / tr_filt.stats.sampling_rate, tr_filt.stats.delta) + cuttimes[0]
############################################################## ##############################################################
#get onset time from HOS-CF using class Picker #get onset time from HOS-CF using class Picker
#hospick = PragPicker(hoscf.getCF(), thoscf, 2, 70, [1, 0.5, 0.2], 2, 0.001, 0.2) #hospick = PragPicker(hoscf, 2, 70, [1, 0.5, 0.2], 2, 0.001, 0.2)
#pdb.set_trace()
############################################################## ##############################################################
#calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction #calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction
#class needs stream object => build it #class needs stream object => build it
tr_aic = tr_filt.copy() tr_aic = tr_filt.copy()
tr_aic.data = hoscf.getCF() tr_aic.data = hoscf.getCF()
st_copy[0].data = tr_aic.data st_copy[0].data = tr_aic.data
aiccf = AICcf(st_copy, cuttimes, t2, p) #instance of AICcf aiccf = AICcf(st_copy, cuttimes, t2) #instance of AICcf
#get corresponding time array
#taiccf = np.arange(0, len(aiccf.getCF()) / tr_filt.stats.sampling_rate, tr_filt.stats.delta) + cuttimes[0]
############################################################## ##############################################################
#get onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking #get onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking
aicpick = AICPicker(aiccf, 2, 70, [1, 0.5, 0.2], 2, 0.001, 2.5) aicpick = AICPicker(aiccf, 2, 70, [1, 0.5, 0.2], 3)
############################################################## ##############################################################
#calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction #calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction
#get stream object of filtered data #get stream object of filtered data
@ -87,7 +82,10 @@ def run_makeCF(project, database, event, iplot, station=None):
tr_arzaic = tr_filt.copy() tr_arzaic = tr_filt.copy()
tr_arzaic.data = arzcf.getCF() tr_arzaic.data = arzcf.getCF()
st_copy[0].data = tr_arzaic.data st_copy[0].data = tr_arzaic.data
araiccf = AICcf(st_copy, cuttimes, t2, p) #instance of AICcf araiccf = AICcf(st_copy, cuttimes, tpredz, 0, tdetz) #instance of AICcf
##############################################################
#get onset time from AIC-ARZ-CF using subclass AICPicker of class AutoPicking
aicarzpick = AICPicker(araiccf, 2, 70, [1, 0.5, 0.2], 2)
elif not wfzfiles: elif not wfzfiles:
print 'No vertical component data found!' print 'No vertical component data found!'
@ -113,6 +111,17 @@ def run_makeCF(project, database, event, iplot, station=None):
#calculate ARH-CF using subclass ARHcf of class CharcteristicFunction #calculate ARH-CF using subclass ARHcf of class CharcteristicFunction
arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) #instance of ARHcf arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) #instance of ARHcf
############################################################## ##############################################################
#calculate AIC-ARH-CF using subclass AICcf of class CharacteristicFunction
#class needs stream object => build it
tr_arhaic = trH1_filt.copy()
tr_arhaic.data = arhcf.getCF()
H_copy[0].data = tr_arhaic.data
#calculate ARH-AIC-CF
arhaiccf = AICcf(H_copy, cuttimes, tpredh, 0, tdeth) #instance of AICcf
##############################################################
#get onset time from AIC-ARH-CF using subclass AICPicker of class AutoPicking
aicarhpick = AICPicker(arhaiccf, 2, 70, [1, 0.5, 0.2], 2)
###############################################################
#create stream with 3 traces #create stream with 3 traces
#merge streams #merge streams
AllC = read('%s' % wfefiles[i]) AllC = read('%s' % wfefiles[i])
@ -138,18 +147,18 @@ def run_makeCF(project, database, event, iplot, station=None):
#plot vertical trace #plot vertical trace
plt.figure() plt.figure()
tr = st[0] tr = st[0]
tstepz = tpredz / 16
tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta) tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
tarzcf = np.arange(0, len(arzcf.getCF()) * tstepz, tstepz) + cuttimes[0] + tdetz +tpredz
taraiccf = np.arange(0, len(araiccf.getCF()) * tstepz, tstepz) + cuttimes[0] +tdetz + tpredz
p1 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k') p1 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
p2 = plt.plot(thoscf, hoscf.getCF()/max(hoscf.getCF()), 'r') p2 = plt.plot(hoscf.getTimeArray(), hoscf.getCF() / max(hoscf.getCF()), 'r')
p3 = plt.plot(taiccf, aiccf.getCF()/max(aiccf.getCF()), 'b') p3 = plt.plot(aiccf.getTimeArray(), aiccf.getCF()/max(aiccf.getCF()), 'b')
p4 = plt.plot(tarzcf, arzcf.getCF()/max(arzcf.getCF()), 'g') p4 = plt.plot(arzcf.getTimeArray(), arzcf.getCF()/max(arzcf.getCF()), 'g')
p5 = plt.plot(taraiccf, araiccf.getCF()/max(araiccf.getCF()), 'y') p5 = plt.plot(araiccf.getTimeArray(), araiccf.getCF()/max(araiccf.getCF()), 'y')
plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b') plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b--')
plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [1, 1], 'b') plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [-1, -1], 'b') plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([aicarzpick.getpick(), aicarzpick.getpick()], [-1.2, 1.2], 'y--')
plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [1.2, 1.2], 'y')
plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [-1.2, -1.2], 'y')
plt.yticks([]) plt.yticks([])
plt.xlabel('Time [s]') plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts') plt.ylabel('Normalized Counts')
@ -165,14 +174,22 @@ def run_makeCF(project, database, event, iplot, station=None):
tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth +tpredh tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth +tpredh
p21 = plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k') p21 = plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
p22 = plt.plot(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r') p22 = plt.plot(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r')
p23 = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b--')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
plt.yticks([]) plt.yticks([])
plt.ylabel('Normalized Counts') plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel]) plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.suptitle(trH1_filt.stats.starttime) plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p21, p22], ['Data', 'ARH-CF']) plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.subplot(212) plt.subplot(212)
p23 = plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k') plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
p24 = plt.plot(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r') plt.plot(tarhcf, arhcf.getCF()/max(arhcf.getCF()), 'r')
plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b--')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel]) plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.yticks([]) plt.yticks([])
plt.xlabel('Time [s]') plt.xlabel('Time [s]')