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[hotfix] earllatepicker recursively modifies isignal to obtain zero-crossing also for low frequency onsets

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This commit is contained in:
Sebastian Wehling-Benatelli 2015-09-22 12:29:42 +02:00
parent dedf6eff00
commit 844708bbac
1 changed files with 23 additions and 22 deletions
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45
pylot/core/pick/utils.py
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@ -59,7 +59,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
ilup, = np.where(x[isignal] > nlevel)
ildown, = np.where(x[isignal] < -nlevel)
if not ilup.size and not ildown.size:
print ("earllatepicker: Signal lower than noise level!")
print ("earllatepicker: Signal lower than noise level!")
print ("Skip this trace!")
return LPick, EPick, PickError
il = min(np.min(ilup) if ilup.size else float('inf'),
@ -69,24 +69,25 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
# get earliest possible pick
EPick = np.nan
pis = isignal[:len(isignal) / 2] if not len(isignal) % 2 else \
isignal[:len(isignal) / 2 + 1]
while np.isnan(EPick):
print("earllatepicker: Doubled signal window size because of NaN for "
"earliest pick.")
isigDoubleWinStart = pis[-1] + 1
isignalDoubleWin = np.arange(isigDoubleWinStart,
isigDoubleWinStart + len(pis))
if (isigDoubleWinStart + len(pis)) < X[0].data.size:
pis = np.concatenate((pis, isignalDoubleWin))
else:
print("Could not double signal window. Index out of bounds.")
break
# determine all zero crossings in signal window (demeaned)
zc = crossings_nonzero_all(x[isignal] - x[isignal].mean())
zc = crossings_nonzero_all(x[pis] - x[pis].mean())
# calculate mean half period T0 of signal as the average of the
T0 = np.mean(np.diff(zc)) * X[0].stats.delta # this is half wave length!
T0 = np.mean(np.diff(zc)) * X[0].stats.delta # this is half wave length
# T0/4 is assumed as time difference between most likely and earliest possible pick!
EPick = Pick1 - T0 / 2
if np.isnan(EPick):
print "earllatepicker: Doubled signal window size because of NaN for earliest pick."
isigDoubleWinStart = isignal[-1] + 1
isignalDoubleWin = np.arange(isigDoubleWinStart, isigDoubleWinStart + len(isignal))
if (isigDoubleWinStart + len(isignal)) < X[0].data.size:
isignal = np.concatenate((isignal, isignalDoubleWin))
else:
isignalDoubleWin = np.arange(isigDoubleWinStart, X[0].data.size)
isignal = np.concatenate((isignal, isignalDoubleWin))
print "Could not double signal window. Index out of bounds."
break
# get symmetric pick error as mean from earliest and latest possible pick
@ -200,11 +201,11 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
else:
imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][li1]]))
if imax1 == 0:
imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][index1[1]]]))
imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][index1[1]]]))
if imax1 == 0:
print ("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!")
return FM
print ("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!")
return FM
islope1 = np.where((t >= Pick) & (t <= Pick + t[imax1]))
# calculate slope as polynomal fit of order 1
@ -242,11 +243,11 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
else:
imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][li2]]))
if imax2 == 0:
imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][index2[1]]]))
imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][index2[1]]]))
if imax2 == 0:
print ("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!")
return FM
print ("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!")
return FM
islope2 = np.where((t >= Pick) & (t <= Pick + t[imax2]))
# calculate slope as polynomal fit of order 1