Merge branch 'develop' of ariadne.geophysik.ruhr-uni-bochum.de:/data/git/pylot into develop
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@ -1057,17 +1057,21 @@ def iteratepicker(wf, NLLocfile, picks, badpicks, pickparameter, fig_dict=None):
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Precalcwin_old = pickparameter.get('Precalcwin')
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Precalcwin_old = pickparameter.get('Precalcwin')
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noisefactor_old = pickparameter.get('noisefactor')
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noisefactor_old = pickparameter.get('noisefactor')
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zfac_old = pickparameter.get('zfac')
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zfac_old = pickparameter.get('zfac')
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pickparameter.setParam(
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twindows = pickparameter.get('tsnrz')
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pstart=max([0, badpicks[i][1] - wf2pick[0].stats.starttime \
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tsafety = twindows[1]
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- pickparameter.get('tlta')]))
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pstart = max([0, badpicks[i][1] - wf2pick[0].stats.starttime - pickparameter.get('tlta')])
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pickparameter.setParam(pstop=pickparameter.get('pstart') + \
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if abs(float(res)) <= tsafety / 2 or pstart == 0:
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(pickparameter.get('Precalcwin')))
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print("iteratepicker: Small residuum, leave parameters unchanged for this phase!")
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pickparameter.setParam(sstop=pickparameter.get('sstop') / 2)
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else:
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pickparameter.setParam(pickwinP=pickparameter.get('pickwinP') / 2)
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pickparameter.setParam(pstart=pstart)
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pickparameter.setParam(
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pickparameter.setParam(pstop=pickparameter.get('pstart') + \
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Precalcwin=pickparameter.get('Precalcwin') / 2)
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(pickparameter.get('Precalcwin')))
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pickparameter.setParam(noisefactor=1.0)
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pickparameter.setParam(sstop=pickparameter.get('sstop') / 2)
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pickparameter.setParam(zfac=1.0)
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pickparameter.setParam(pickwinP=pickparameter.get('pickwinP') / 2)
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pickparameter.setParam(Precalcwin=pickparameter.get('Precalcwin') / 2)
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pickparameter.setParam(noisefactor=1.0)
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pickparameter.setParam(zfac=1.0)
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print(
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print(
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"iteratepicker: The following picking parameters have been modified for iterative picking:")
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"iteratepicker: The following picking parameters have been modified for iterative picking:")
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print(
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print(
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@ -754,7 +754,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
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# get signal window
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# get signal window
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isignal = getsignalwin(t, pick, minsiglength)
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isignal = getsignalwin(t, pick, minsiglength)
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# calculate minimum adjusted signal level
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# calculate minimum adjusted signal level
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minsiglevel = max(rms[inoise]) * nfac
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minsiglevel = np.mean(rms[inoise]) * nfac
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# minimum adjusted number of samples over minimum signal level
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# minimum adjusted number of samples over minimum signal level
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minnum = len(isignal) * minpercent / 100
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minnum = len(isignal) * minpercent / 100
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# get number of samples above minimum adjusted signal level
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# get number of samples above minimum adjusted signal level
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