Debugging.
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@ -183,10 +183,17 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
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else:
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else:
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li1 = index1[0]
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li1 = index1[0]
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if np.size(xraw[ipick[0][1]:ipick[0][li1]]) == 0:
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if np.size(xraw[ipick[0][1]:ipick[0][li1]]) == 0:
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print 'earllatepicker: Onset on unfiltered trace too emergent for first motion determination!'
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print 'fmpicker: Onset on unfiltered trace too emergent for first motion determination!'
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P1 = None
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P1 = None
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else:
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else:
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imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][li1]]))
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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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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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islope1 = np.where((t >= Pick) & (t <= Pick + t[imax1]))
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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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# calculate slope as polynomal fit of order 1
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xslope1 = np.arange(0, len(xraw[islope1]), 1)
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xslope1 = np.arange(0, len(xraw[islope1]), 1)
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@ -218,10 +225,17 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
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else:
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else:
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li2 = index2[0]
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li2 = index2[0]
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if np.size(xfilt[ipick[0][1]:ipick[0][li2]]) == 0:
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if np.size(xfilt[ipick[0][1]:ipick[0][li2]]) == 0:
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print 'earllatepicker: Onset on filtered trace too emergent for first motion determination!'
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print 'fmpicker: Onset on filtered trace too emergent for first motion determination!'
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P2 = None
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P2 = None
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else:
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else:
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imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][li2]]))
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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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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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islope2 = np.where((t >= Pick) & (t <= Pick + t[imax2]))
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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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# calculate slope as polynomal fit of order 1
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xslope2 = np.arange(0, len(xfilt[islope2]), 1)
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xslope2 = np.arange(0, len(xfilt[islope2]), 1)
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@ -459,14 +473,17 @@ def wadaticheck(pickdic, dttolerance, iplot):
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pickdic[key]['S']['marked'] = marker
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pickdic[key]['S']['marked'] = marker
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if len(checkedPpicks) >= 3:
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# calculate new slope
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p2 = np.polyfit(checkedPpicks, checkedSPtimes, 1)
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wdfit2 = np.polyval(p2, checkedPpicks)
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# calculate new slope
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# calculate vp/vs ratio after check
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p2 = np.polyfit(checkedPpicks, checkedSPtimes, 1)
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cvpvsr = p2[0] + 1
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wdfit2 = np.polyval(p2, checkedPpicks)
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print 'wadaticheck: Average Vp/Vs ratio after check:', cvpvsr
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else:
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# calculate vp/vs ratio after check
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print 'wadatacheck: Not enough checked S-P times available!'
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cvpvsr = p2[0] + 1
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print 'Skip Wadati check!'
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print 'wadaticheck: Average Vp/Vs ratio after check:', cvpvsr
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checkedonsets = pickdic
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checkedonsets = pickdic
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@ -476,6 +493,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
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wfitflag = 1
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wfitflag = 1
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# plot results
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# plot results
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iplot=2
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if iplot > 1:
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if iplot > 1:
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plt.figure(iplot)
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plt.figure(iplot)
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f1, = plt.plot(Ppicks, SPtimes, 'ro')
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f1, = plt.plot(Ppicks, SPtimes, 'ro')
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