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Merge branch 'develop' of ariadne.geophysik.ruhr-uni-bochum.de:/data/git/pylot into develop

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Sebastian Wehling-Benatelli 2015-11-26 05:18:10 +01:00
commit ae21c9a149
4 changed files with 61 additions and 62 deletions
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4
autoPyLoT.py
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@ -84,6 +84,7 @@ def autoPyLoT(inputfile):
ttpat = parameter.getParam('ttpatter') ttpat = parameter.getParam('ttpatter')
# pattern of NLLoc-output file # pattern of NLLoc-output file
nllocoutpatter = parameter.getParam('outpatter') nllocoutpatter = parameter.getParam('outpatter')
maxnumit = 3 # maximum number of iterations for re-picking
else: else:
locflag = 0 locflag = 0
print (" !!! ") print (" !!! ")
@ -133,7 +134,6 @@ def autoPyLoT(inputfile):
else: else:
# get theoretical P-onset times from NLLoc-location file # get theoretical P-onset times from NLLoc-location file
locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout) locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
maxnumit = 3 # maximum number of iterations
if len(glob.glob(locsearch)) > 0: if len(glob.glob(locsearch)) > 0:
# get latest file if several are available # get latest file if several are available
nllocfile = max(glob.glob(locsearch), key=os.path.getctime) nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
@ -213,8 +213,6 @@ def autoPyLoT(inputfile):
else: else:
# get theoretical P-onset times from NLLoc-location file # get theoretical P-onset times from NLLoc-location file
locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout) locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
maxnumit = 3 # maximum number of iterations
if len(glob.glob(locsearch)) > 0: if len(glob.glob(locsearch)) > 0:
# get latest file if several are available # get latest file if several are available
nllocfile = max(glob.glob(locsearch), key=os.path.getctime) nllocfile = max(glob.glob(locsearch), key=os.path.getctime)

17
autoPyLoT_local.in
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@ -7,7 +7,7 @@
/DATA/Insheim #rootpath# %project path /DATA/Insheim #rootpath# %project path
EVENT_DATA/LOCAL #datapath# %data path EVENT_DATA/LOCAL #datapath# %data path
2015.10_Insheim #database# %name of data base 2015.10_Insheim #database# %name of data base
e0011.280.15 #eventID# %event ID for single event processing #eventID# %event ID for single event processing
/DATA/Insheim/STAT_INFO #invdir# %full path to inventory or dataless-seed file /DATA/Insheim/STAT_INFO #invdir# %full path to inventory or dataless-seed file
PILOT #datastructure#%choose data structure PILOT #datastructure#%choose data structure
0 #iplot# %flag for plotting: 0 none, 1 partly, >1 everything 0 #iplot# %flag for plotting: 0 none, 1 partly, >1 everything
@ -42,7 +42,7 @@ AUTOFOCMEC_AIC_HOS4_ARH.in #focmecin# %name of focmec input file co
15.0 #pstart# %start time [s] for calculating CF for P-picking 15.0 #pstart# %start time [s] for calculating CF for P-picking
60.0 #pstop# %end time [s] for calculating CF for P-picking 60.0 #pstop# %end time [s] for calculating CF for P-picking
-1.0 #sstart# %start time [s] relative to P-onset for calculating CF for S-picking -1.0 #sstart# %start time [s] relative to P-onset for calculating CF for S-picking
12.0 #sstop# %end time [s] after P-onset for calculating CF for S-picking 10.0 #sstop# %end time [s] after P-onset for calculating CF for S-picking
2 20 #bpz1# %lower/upper corner freq. of first band pass filter Z-comp. [Hz] 2 20 #bpz1# %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
2 30 #bpz2# %lower/upper corner freq. of second band pass filter Z-comp. [Hz] 2 30 #bpz2# %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
2 15 #bph1# %lower/upper corner freq. of first band pass filter H-comp. [Hz] 2 15 #bph1# %lower/upper corner freq. of first band pass filter H-comp. [Hz]
@ -74,13 +74,12 @@ ARH #algoS# %choose algorithm for S-onset
0.6 #tdet2h# %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick 0.6 #tdet2h# %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick
0.3 #tpred2h# %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick 0.3 #tpred2h# %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick
4 #Sarorder# %for AR-picker, order of AR process of H-components 4 #Sarorder# %for AR-picker, order of AR process of H-components
6.0 #Srecalcwin# %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H) 5.0 #Srecalcwin# %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
3.0 #pickwinS# %for initial AIC pick, length of S-pick window [s] 3.0 #pickwinS# %for initial AIC pick, length of S-pick window [s]
2 0.2 1.5 0.5 #tsnrh# %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s] 2 0.2 1.5 0.5 #tsnrh# %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
0.05 #aictsmoothS# %for AIC-picker, take average of samples for smoothing of AIC-function [s] 0.5 #aictsmoothS# %for AIC-picker, take average of samples for smoothing of AIC-function [s]
0.02 #tsmoothS# %for AR-picker, take average of samples for smoothing CF [s] (S) 0.7 #tsmoothS# %for AR-picker, take average of samples for smoothing CF [s] (S)
0.2 #pepsS# %for AR-picker, artificial uplift of samples of CF (S) 0.9 #ausS# %for HOS/AR, artificial uplift of samples (aus) of CF (S)
0.4 #ausS# %for HOS/AR, artificial uplift of samples (aus) of CF (S)
1.5 #nfacS# %for AR-picker, noise factor for noise level determination (S) 1.5 #nfacS# %for AR-picker, noise factor for noise level determination (S)
%first-motion picker% %first-motion picker%
1 #minfmweight# %minimum required P weight for first-motion determination 1 #minfmweight# %minimum required P weight for first-motion determination
@ -90,9 +89,9 @@ ARH #algoS# %choose algorithm for S-onset
#inital AIC onset# #inital AIC onset#
0.01 0.02 0.04 0.08 #timeerrorsP# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P 0.01 0.02 0.04 0.08 #timeerrorsP# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P
0.04 0.08 0.16 0.32 #timeerrorsS# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S 0.04 0.08 0.16 0.32 #timeerrorsS# %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S
10 #minAICPslope# %below this slope [counts/s] the initial P pick is rejected 4 #minAICPslope# %below this slope [counts/s] the initial P pick is rejected
1.2 #minAICPSNR# %below this SNR the initial P pick is rejected 1.2 #minAICPSNR# %below this SNR the initial P pick is rejected
3 #minAICSslope# %below this slope [counts/s] the initial S pick is rejected 2 #minAICSslope# %below this slope [counts/s] the initial S pick is rejected
1.5 #minAICSSNR# %below this SNR the initial S pick is rejected 1.5 #minAICSSNR# %below this SNR the initial S pick is rejected
#check duration of signal using envelope function# #check duration of signal using envelope function#
4 #minsiglength# %minimum required length of signal [s] 4 #minsiglength# %minimum required length of signal [s]

2
pylot/core/pick/Picker.py
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@ -364,7 +364,7 @@ class PragPicker(AutoPicking):
break break
# now decide which pick: left or right? # now decide which pick: left or right?
if flagpick_l > 0 and flagpick_r > 0 and cfpick_l <= cfpick_r: if flagpick_l > 0 and flagpick_r > 0 and cfpick_l <= 3 * cfpick_r:
self.Pick = pick_l self.Pick = pick_l
pickflag = 1 pickflag = 1
elif flagpick_l > 0 and flagpick_r > 0 and cfpick_l >= cfpick_r: elif flagpick_l > 0 and flagpick_r > 0 and cfpick_l >= cfpick_r:

100
pylot/core/pick/autopick.py
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@ -500,58 +500,60 @@ def autopickstation(wfstream, pickparam):
[lpickS2, epickS2, Serror2] = earllatepicker(h_copy, nfacS, [lpickS2, epickS2, Serror2] = earllatepicker(h_copy, nfacS,
tsnrh, tsnrh,
mpickS, iplot) mpickS, iplot)
if algoS == 'ARH': if epickS1 is not None and epickS2 is not None:
# get earliest pick of both earliest possible picks if algoS == 'ARH':
epick = [epickS1, epickS2] # get earliest pick of both earliest possible picks
lpick = [lpickS1, lpickS2] epick = [epickS1, epickS2]
pickerr = [Serror1, Serror2] lpick = [lpickS1, lpickS2]
if epickS1 == None and epickS2 is not None: pickerr = [Serror1, Serror2]
ipick = 1 if epickS1 == None and epickS2 is not None:
elif epickS1 is not None and epickS2 == None: ipick = 1
ipick = 0 elif epickS1 is not None and epickS2 == None:
elif epickS1 is not None and epickS2 is not None: ipick = 0
ipick = np.argmin([epickS1, epickS2]) elif epickS1 is not None and epickS2 is not None:
elif algoS == 'AR3': ipick = np.argmin([epickS1, epickS2])
[lpickS3, epickS3, Serror3] = earllatepicker(h_copy, nfacS, elif algoS == 'AR3':
tsnrh, [lpickS3, epickS3, Serror3] = earllatepicker(h_copy, nfacS,
mpickS, iplot) tsnrh,
# get earliest pick of all three picks mpickS, iplot)
epick = [epickS1, epickS2, epickS3] # get earliest pick of all three picks
lpick = [lpickS1, lpickS2, lpickS3] epick = [epickS1, epickS2, epickS3]
pickerr = [Serror1, Serror2, Serror3] lpick = [lpickS1, lpickS2, lpickS3]
if epickS1 == None and epickS2 is not None \ pickerr = [Serror1, Serror2, Serror3]
and epickS3 is not None: if epickS1 == None and epickS2 is not None \
ipick = np.argmin([epickS2, epickS3]) and epickS3 is not None:
elif epickS1 is not None and epickS2 == None \ ipick = np.argmin([epickS2, epickS3])
and epickS3 is not None: elif epickS1 is not None and epickS2 == None \
ipick = np.argmin([epickS2, epickS3]) and epickS3 is not None:
elif epickS1 is not None and epickS2 is not None \ ipick = np.argmin([epickS2, epickS3])
and epickS3 == None: elif epickS1 is not None and epickS2 is not None \
ipick = np.argmin([epickS1, epickS2]) and epickS3 == None:
elif epickS1 is not None and epickS2 is not None \ ipick = np.argmin([epickS1, epickS2])
and epickS3 is not None: elif epickS1 is not None and epickS2 is not None \
ipick = np.argmin([epickS1, epickS2, epickS3]) and epickS3 is not None:
epickS = epick[ipick] ipick = np.argmin([epickS1, epickS2, epickS3])
lpickS = lpick[ipick]
Serror = pickerr[ipick]
# get SNR epickS = epick[ipick]
[SNRS, SNRSdB, Snoiselevel] = getSNR(h_copy, tsnrh, mpickS) lpickS = lpick[ipick]
Serror = pickerr[ipick]
# weight S-onset using symmetric error # get SNR
if Serror <= timeerrorsS[0]: [SNRS, SNRSdB, Snoiselevel] = getSNR(h_copy, tsnrh, mpickS)
Sweight = 0
elif timeerrorsS[0] < Serror <= timeerrorsS[1]:
Sweight = 1
elif Perror > timeerrorsS[1] and Serror <= timeerrorsS[2]:
Sweight = 2
elif timeerrorsS[2] < Serror <= timeerrorsS[3]:
Sweight = 3
elif Serror > timeerrorsS[3]:
Sweight = 4
print 'autopickstation: S-weight: %d, SNR: %f, SNR[dB]: %f' % ( # weight S-onset using symmetric error
Sweight, SNRS, SNRSdB) if Serror <= timeerrorsS[0]:
Sweight = 0
elif timeerrorsS[0] < Serror <= timeerrorsS[1]:
Sweight = 1
elif Perror > timeerrorsS[1] and Serror <= timeerrorsS[2]:
Sweight = 2
elif timeerrorsS[2] < Serror <= timeerrorsS[3]:
Sweight = 3
elif Serror > timeerrorsS[3]:
Sweight = 4
print 'autopickstation: S-weight: %d, SNR: %f, SNR[dB]: %f' % (
Sweight, SNRS, SNRSdB)
################################################################## ##################################################################
# get Wood-Anderson peak-to-peak amplitude # get Wood-Anderson peak-to-peak amplitude
print "################################################" print "################################################"