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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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Sebastian Wehling-Benatelli 2015-04-21 08:14:26 +02:00
parent 4d268da435
commit bb84e27e54
1 changed files with 16 additions and 22 deletions
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38
pylot/core/pick/utils.py
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@ -53,32 +53,22 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None):
#get signal window #get signal window
isignal = getsignalwin(t, Pick1, TSNR[2]) isignal = getsignalwin(t, Pick1, TSNR[2])
#calculate noise level #calculate noise level
nlevel = max(abs(x[inoise])) * nfac nlevel = np.sqrt(np.mean(np.square(x[inoise]))) * nfac
#get time where signal exceeds nlevel #get time where signal exceeds nlevel
ilup = np.where(x[isignal] > nlevel) ilup, = np.where(x[isignal] > nlevel)
ildown = np.where(x[isignal] < -nlevel) ildown, = np.where(x[isignal] < -nlevel)
if len(ilup[0]) <= 1 and len(ildown[0]) <= 1: if not ilup.size and not ildown.size:
print 'earllatepicker: Signal lower than noise level, misspick?' raise ValueError('earllatepicker: Signal lower than noise level')
return il = min(np.min(ilup) if ilup.size else float('inf'),
il = min([ilup[0][0], ildown[0][0]]) np.min(ildown) if ildown.size else float('inf'))
LPick = t[isignal][il] LPick = t[isignal][il]
#get earliest possible pick #get earliest possible pick
#get next 2 zero crossings after most likely pick
#initial onset is assumed to be the first zero crossing #determine all zero crossings in signal window
zc = [] zc = crossings_nonzero_all(x[isignal])
zc.append(Pick1) #calculate mean half period T0 of signal as the average of the
i = 0 T0 = np.mean(np.diff(zc)) * X[0].stats.delta #this is half wave length!
for j in range(isignal[0][1], isignal[0][len(t[isignal]) - 1]):
i = i + 1
if x[j - 1] <= 0 and x[j] >= 0:
zc.append(t[isignal][i])
elif x[j - 1] > 0 and x[j] <= 0:
zc.append(t[isignal][i])
if len(zc) == 3:
break
#calculate maximum period T0 of signal out of zero crossings
T0 = max(np.diff(zc)) #this is half wave length!
#T0/4 is assumed as time difference between most likely and earliest possible pick! #T0/4 is assumed as time difference between most likely and earliest possible pick!
EPick = Pick1 - T0 / 2 EPick = Pick1 - T0 / 2
@ -288,6 +278,10 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None):
return FM return FM
def crossings_nonzero_all(data):
pos = data > 0
npos = ~pos
return ((pos[:-1] & npos[1:]) | (npos[:-1] & pos[1:])).nonzero()[0]
def getSNR(X, TSNR, t1): def getSNR(X, TSNR, t1):
''' '''