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Introduced saftey factor for jackknife test to be less conservative.

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This commit is contained in:
Ludger Küperkoch 2015-07-06 15:52:25 +02:00
parent 29de650b4e
commit 8463a87507
1 changed files with 12 additions and 7 deletions
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19
pylot/core/pick/utils.py
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@ -13,7 +13,7 @@ import scipy as sc
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from obspy.core import Stream, UTCDateTime from obspy.core import Stream, UTCDateTime
import warnings import warnings
import pdb
def earllatepicker(X, nfac, TSNR, Pick1, iplot=None): def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
''' '''
Function to derive earliest and latest possible pick after Diehl & Kissling (2009) Function to derive earliest and latest possible pick after Diehl & Kissling (2009)
@ -482,6 +482,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
# calculate vp/vs ratio before check # calculate vp/vs ratio before check
vpvsr = p1[0] + 1 vpvsr = p1[0] + 1
print '###############################################'
print 'wadaticheck: Average Vp/Vs ratio before check:', vpvsr print 'wadaticheck: Average Vp/Vs ratio before check:', vpvsr
checkedPpicks = [] checkedPpicks = []
@ -519,6 +520,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
cvpvsr = p2[0] + 1 cvpvsr = p2[0] + 1
print 'wadaticheck: Average Vp/Vs ratio after check:', cvpvsr print 'wadaticheck: Average Vp/Vs ratio after check:', cvpvsr
else: else:
print '###############################################'
print 'wadatacheck: Not enough checked S-P times available!' print 'wadatacheck: Not enough checked S-P times available!'
print 'Skip Wadati check!' print 'Skip Wadati check!'
@ -528,7 +530,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
print 'wadaticheck: Not enough S-P times available for reliable regression!' print 'wadaticheck: Not enough S-P times available for reliable regression!'
print 'Skip wadati check!' print 'Skip wadati check!'
wfitflag = 1 wfitflag = 1
iplot=2
# plot results # plot results
if iplot > 1: if iplot > 1:
plt.figure(iplot) plt.figure(iplot)
@ -668,14 +670,16 @@ def checkPonsets(pickdic, dttolerance, iplot):
stations.append(key) stations.append(key)
# apply jackknife bootstrapping on variance of P onsets # apply jackknife bootstrapping on variance of P onsets
print '###############################################'
print 'checkPonsets: Apply jackknife bootstrapping on P-onset times ...' print 'checkPonsets: Apply jackknife bootstrapping on P-onset times ...'
[xjack,PHI_pseudo,PHI_sub] = jackknife(Ppicks, 'VAR', 1) [xjack,PHI_pseudo,PHI_sub] = jackknife(Ppicks, 'VAR', 1)
# get pseudo variances smaller than average variances # get pseudo variances smaller than average variances
# these picks passed jackknife test # (times safety factor), these picks passed jackknife test
ij = np.where(PHI_pseudo <= xjack) ij = np.where(PHI_pseudo <= 2 * xjack)
# these picks did not pass jackknife test # these picks did not pass jackknife test
badjk = np.where(PHI_pseudo > xjack) badjk = np.where(PHI_pseudo > 2 * xjack)
badjkstations = np.array(stations)[badjk] badjkstations = np.array(stations)[badjk]
print 'checkPonsets: %d picks did not pass jackknife test!' % len(badjkstations)
# calculate median from these picks # calculate median from these picks
pmedian = np.median(np.array(Ppicks)[ij]) pmedian = np.median(np.array(Ppicks)[ij])
@ -687,7 +691,8 @@ def checkPonsets(pickdic, dttolerance, iplot):
goodstations = np.array(stations)[igood] goodstations = np.array(stations)[igood]
badstations = np.array(stations)[ibad] badstations = np.array(stations)[ibad]
print 'checkPonset: Skipped %d P onsets out of %d' % (len(badstations) \ print 'checkPonsets: %d picks deviate too much from median!' % len(ibad)
print 'checkPonsets: Skipped %d P onsets out of %d' % (len(badstations) \
+ len(badjkstations), len(stations)) + len(badjkstations), len(stations))
goodmarker = 'goodPonsetcheck' goodmarker = 'goodPonsetcheck'
@ -867,7 +872,7 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
if zcodalevel < minsiglevel: if zcodalevel < minsiglevel:
print 'checkZ4S: Maybe S onset? Skip this P pick!' print 'checkZ4S: Maybe S onset? Skip this P pick!'
else: else:
print 'checkZ4S: P onset passed checkZ4S test!' print 'checkZ4S: P onset passes checkZ4S test!'
returnflag = 1 returnflag = 1
if iplot > 1: if iplot > 1: