[Bugfix]: Check for key S and be sure to get element weight for pick
dictionary.
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@ -269,6 +269,14 @@ def picksdict_from_picks(evt):
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msg = str(e) + ',\n falling back to symmetric uncertainties'
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msg = str(e) + ',\n falling back to symmetric uncertainties'
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lpp = mpp + spe
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lpp = mpp + spe
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epp = mpp - spe
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epp = mpp - spe
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warnings.warn(msg)
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phase['mpp'] = mpp
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phase['epp'] = epp
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phase['lpp'] = lpp
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phase['spe'] = spe
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try:
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phase['weight'] = weight
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except:
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# get onset weight from uncertainty
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# get onset weight from uncertainty
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infile = os.path.join(os.path.expanduser('~'), '.pylot', 'pylot.in')
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infile = os.path.join(os.path.expanduser('~'), '.pylot', 'pylot.in')
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print('Using default input file {}'.format(infile))
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print('Using default input file {}'.format(infile))
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@ -278,11 +286,6 @@ def picksdict_from_picks(evt):
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elif pick.phase_hint == 'S':
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elif pick.phase_hint == 'S':
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errors = parameter['timeerrorsS']
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errors = parameter['timeerrorsS']
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weight = get_quality_class(spe, errors)
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weight = get_quality_class(spe, errors)
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warnings.warn(msg)
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phase['mpp'] = mpp
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phase['epp'] = epp
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phase['lpp'] = lpp
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phase['spe'] = spe
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phase['weight'] = weight
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phase['weight'] = weight
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phase['channel'] = channel
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phase['channel'] = channel
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phase['network'] = network
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phase['network'] = network
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@ -782,6 +785,7 @@ def writephases(arrivals, fformat, filename, parameter=None, eventinfo=None):
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Ponset = arrivals[key]['P']['mpp']
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Ponset = arrivals[key]['P']['mpp']
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Prt = Ponset - stime # onset time relative to source time
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Prt = Ponset - stime # onset time relative to source time
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fid.write('%s %6.3f 1 P\n' % (key, Prt))
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fid.write('%s %6.3f 1 P\n' % (key, Prt))
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if arrivals[key].has_key('S'):
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# S onsets
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# S onsets
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if arrivals[key]['S']['weight'] < 4:
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if arrivals[key]['S']['weight'] < 4:
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Sonset = arrivals[key]['S']['mpp']
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Sonset = arrivals[key]['S']['mpp']
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@ -316,8 +316,13 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None, linecolor='k'):
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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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try:
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P2 = np.polyfit(xslope2, xfilt[islope2], 1)
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P2 = np.polyfit(xslope2, xfilt[islope2], 1)
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datafit2 = np.polyval(P2, xslope2)
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datafit2 = np.polyval(P2, xslope2)
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except ValueError as e:
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emsg = 'fmpicker: polyfit failed: {}'.format(e)
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print(emsg)
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return FM
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# compare results
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# compare results
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if P1 is not None and P2 is not None:
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if P1 is not None and P2 is not None:
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