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