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Modofied checksignallength: uses RMS trace of all components (if available) to check signal length. This avoids skipping of P pick, if P coda is very weak. If only vertical trace is available, rms of vertical trace is used instead with smaller required minimum signal length.

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This commit is contained in:
Ludger Küperkoch 2015-09-04 11:16:34 +02:00
parent de608798b9
commit 23430c9d90
1 changed files with 27 additions and 20 deletions
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47
pylot/core/pick/utils.py
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@ -7,7 +7,7 @@
:author: Ludger Kueperkoch / MAGS2 EP3 working group
"""
import pdb
import numpy as np
import scipy as sc
import matplotlib.pyplot as plt
@ -562,9 +562,9 @@ def wadaticheck(pickdic, dttolerance, iplot):
def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
'''
Function to detect spuriously picked noise peaks.
Uses envelope to determine, how many samples [per cent] after
P onset are below certain threshold, calculated from noise
level times noise factor.
Uses RMS trace of all 3 components (if available) to determine,
how many samples [per cent] after P onset are below certain
threshold, calculated from noise level times noise factor.
: param: X, time series (seismogram)
: type: `~obspy.core.stream.Stream`
@ -594,23 +594,32 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
print ("Checking signal length ...")
x = X[0].data
t = np.arange(0, X[0].stats.npts / X[0].stats.sampling_rate,
if len(X) > 1:
# all three components available
# make sure, all components have equal lengths
ilen = min([len(X[0].data), len(X[1].data), len(X[2].data)])
x1 = X[0][0:ilen]
x2 = X[1][0:ilen]
x3 = X[2][0:ilen]
# get RMS trace
rms = np.sqrt((np.power(x1, 2) + np.power(x2, 2) + np.power(x3, 2)) / 3)
else:
x1 = X[0].data
rms = np.sqrt(np.power(2, x1))
t = np.arange(0, ilen / X[0].stats.sampling_rate,
X[0].stats.delta)
# generate envelope function from Hilbert transform
y = np.imag(sc.signal.hilbert(x))
e = np.sqrt(np.power(x, 2) + np.power(y, 2))
# get noise window in front of pick plus saftey gap
inoise = getnoisewin(t, pick - 0.5, TSNR[0], TSNR[1])
# get signal window
isignal = getsignalwin(t, pick, TSNR[2])
isignal = getsignalwin(t, pick, minsiglength)
# calculate minimum adjusted signal level
minsiglevel = max(e[inoise]) * nfac
minsiglevel = max(rms[inoise]) * nfac
# minimum adjusted number of samples over minimum signal level
minnum = len(isignal) * minpercent/100
# get number of samples above minimum adjusted signal level
numoverthr = len(np.where(e[isignal] >= minsiglevel)[0])
numoverthr = len(np.where(rms[isignal] >= minsiglevel)[0])
if numoverthr >= minnum:
print ("checksignallength: Signal reached required length.")
@ -623,16 +632,14 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
if iplot == 2:
plt.figure(iplot)
p1, = plt.plot(t,x, 'k')
p2, = plt.plot(t[inoise], e[inoise], 'c')
p3, = plt.plot(t[isignal],e[isignal], 'r')
p2, = plt.plot(t[inoise], e[inoise])
p3, = plt.plot(t[isignal],e[isignal], 'r')
p1, = plt.plot(t,rms, 'k')
p2, = plt.plot(t[inoise], rms[inoise], 'c')
p3, = plt.plot(t[isignal],rms[isignal], 'r')
p4, = plt.plot([t[isignal[0]], t[isignal[len(isignal)-1]]], \
[minsiglevel, minsiglevel], 'g', linewidth=2)
p5, = plt.plot([pick, pick], [min(x), max(x)], 'b', linewidth=2)
plt.legend([p1, p2, p3, p4, p5], ['Data', 'Envelope Noise Window', \
'Envelope Signal Window', 'Minimum Signal Level', \
p5, = plt.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2)
plt.legend([p1, p2, p3, p4, p5], ['RMS Data', 'RMS Noise Window', \
'RMS Signal Window', 'Minimum Signal Level', \
'Onset'], loc='best')
plt.xlabel('Time [s] since %s' % X[0].stats.starttime)
plt.ylabel('Counts')