implemented a much faster calculation of the zero crossing beside an average calculation over the whole signal window of the dominant period
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@ -53,32 +53,22 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
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#get signal window
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isignal = getsignalwin(t, Pick1, TSNR[2])
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#calculate noise level
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nlevel = max(abs(x[inoise])) * nfac
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nlevel = np.sqrt(np.mean(np.square(x[inoise]))) * nfac
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#get time where signal exceeds nlevel
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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 len(ilup[0]) <= 1 and len(ildown[0]) <= 1:
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print 'earllatepicker: Signal lower than noise level, misspick?'
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return
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il = min([ilup[0][0], ildown[0][0]])
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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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raise ValueError('earllatepicker: Signal lower than noise level')
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il = min(np.min(ilup) if ilup.size else float('inf'),
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np.min(ildown) if ildown.size else float('inf'))
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LPick = t[isignal][il]
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#get earliest possible pick
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#get next 2 zero crossings after most likely pick
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#initial onset is assumed to be the first zero crossing
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zc = []
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zc.append(Pick1)
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i = 0
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for j in range(isignal[0][1], isignal[0][len(t[isignal]) - 1]):
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i = i + 1
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if x[j - 1] <= 0 and x[j] >= 0:
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zc.append(t[isignal][i])
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elif x[j - 1] > 0 and x[j] <= 0:
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zc.append(t[isignal][i])
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if len(zc) == 3:
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break
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#calculate maximum period T0 of signal out of zero crossings
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T0 = max(np.diff(zc)) #this is half wave length!
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#determine all zero crossings in signal window
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zc = crossings_nonzero_all(x[isignal])
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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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#T0/4 is assumed as time difference between most likely and earliest possible pick!
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EPick = Pick1 - T0 / 2
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@ -288,6 +278,10 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
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return FM
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def crossings_nonzero_all(data):
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pos = data > 0
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npos = ~pos
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return ((pos[:-1] & npos[1:]) | (npos[:-1] & pos[1:])).nonzero()[0]
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def getSNR(X, TSNR, t1):
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'''
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