Merge branch 'develop' of ariadne.geophysik.ruhr-uni-bochum.de:/data/git/pylot into develop
Conflicts: pylot/core/pick/autopick.py
This commit is contained in:
commit
1a5eed5559
73
autoPyLoT.py
73
autoPyLoT.py
@ -88,9 +88,10 @@ def autoPyLoT(inputfile):
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maxnumit = 3 # maximum number of iterations for re-picking
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else:
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locflag = 0
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print (" !!! ")
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print ("!!No location routine available, autoPyLoT is running in non-location mode!!")
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print (" !!! ")
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print(" !!! ")
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print("!!No location routine available, autoPyLoT is running in non-location mode!!")
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print("!!No source parameter estimation possible!!")
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print(" !!! ")
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# multiple event processing
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@ -132,6 +133,18 @@ def autoPyLoT(inputfile):
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if len(badpicks) == 0:
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print("autoPyLoT: No bad onsets found, thus no iterative picking necessary!")
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# get NLLoc-location file
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locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
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if len(glob.glob(locsearch)) > 0:
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# get latest NLLoc-location file if several are available
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nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
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# calculating seismic moment Mo and moment magnitude Mw
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finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
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nllocfile, picks, parameter.getParam('rho'), \
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parameter.getParam('vp'), parameter.getParam('invdir'))
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else:
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print("autoPyLoT: No NLLoc-location file available!")
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print("No source parameter estimation possible!")
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else:
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# get theoretical P-onset times from NLLoc-location file
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locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
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@ -151,6 +164,9 @@ def autoPyLoT(inputfile):
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# locate the event
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locate(nlloccall, ctrfile)
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print("autoPyLoT: Iteration No. %d finished." % nlloccounter)
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# get updated NLLoc-location file
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nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
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# check for bad picks
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badpicks = []
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for key in picks:
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if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
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@ -159,23 +175,19 @@ def autoPyLoT(inputfile):
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len(badpicks)))
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if len(badpicks) == 0:
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print("autoPyLoT: No more bad onsets found, stop iterative picking!")
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break
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# calculating seismic moment Mo and corresponding moment
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# magnitude Mw after Hanks and Kanamori (1979) from reliable
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# picks/waveforms
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for key in picks:
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if picks[key]['P']['weight'] < 4 and picks[key]['P']['w0'] is not None:
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selwf = wfdat.select(station=key)
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w0 = picks[key]['P']['w0']
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sourcepara = M0Mw(selwf, None, None, None, w0, 5, \
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parameter.getParam('rho'), parameter.getParam('vp'))
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nlloccounter = maxnumit
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# calculating seismic moment Mo and moment magnitude Mw
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finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
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nllocfile, picks, parameter.getParam('rho'), \
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parameter.getParam('vp'), parameter.getParam('invdir'))
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else:
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print("autoPyLoT: No NLLoc-location file available! Stop iteration!")
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##########################################################
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# write phase files for various location routines
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# HYPO71
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hypo71file = '%s/%s/autoPyLoT_HYPO71.pha' % (datapath, evID)
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writephases(picks, 'HYPO71', hypo71file)
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writephases(finalpicks.getpicdic(), 'HYPO71', hypo71file)
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endsplash = '''------------------------------------------\n'
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-----Finished event %s!-----\n'
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@ -220,6 +232,18 @@ def autoPyLoT(inputfile):
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if len(badpicks) == 0:
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print("autoPyLoT: No bad onsets found, thus no iterative picking necessary!")
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# get NLLoc-location file
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locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
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if len(glob.glob(locsearch)) > 0:
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# get latest NLLOc-location file if several are available
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nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
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# calculating seismic moment Mo and moment magnitude Mw
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finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
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nllocfile, picks, parameter.getParam('rho'), \
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parameter.getParam('vp'), parameter.getParam('invdir'))
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else:
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print("autoPyLoT: No NLLoc-location file available!")
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print("No source parameter estimation possible!")
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else:
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# get theoretical P-onset times from NLLoc-location file
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locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
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@ -239,6 +263,9 @@ def autoPyLoT(inputfile):
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# locate the event
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locate(nlloccall, ctrfile)
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print("autoPyLoT: Iteration No. %d finished." % nlloccounter)
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# get updated NLLoc-location file
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nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
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# check for bad picks
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badpicks = []
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for key in picks:
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if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
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@ -247,25 +274,19 @@ def autoPyLoT(inputfile):
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len(badpicks)))
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if len(badpicks) == 0:
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print("autoPyLoT: No more bad onsets found, stop iterative picking!")
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break
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# calculating seismic moment Mo and corresponding moment
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# magnitude Mw after Hanks and Kanamori (1979) from reliable
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# picks/waveforms
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for key in picks:
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if picks[key]['P']['weight'] < 4 and picks[key]['P']['w0'] is not None:
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selwf = wfdat.select(station=key)
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w0 = picks[key]['P']['w0']
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sourcepara = M0Mw(selwf, None, None, None, w0, 5, \
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parameter.getParam('rho'), parameter.getParam('vp'))
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nlloccounter = maxnumit
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# calculating seismic moment Mo and moment magnitude Mw
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finalpicks = M0Mw(wfdat, None, None, parameter.getParam('iplot'), \
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nllocfile, picks, parameter.getParam('rho'), \
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parameter.getParam('vp'), parameter.getParam('invdir'))
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else:
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print("autoPyLoT: No NLLoc-location file available! Stop iteration!")
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##########################################################
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# write phase files for various location routines
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# HYPO71
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hypo71file = '%s/%s/autoPyLoT_HYPO71.pha' % (datapath, parameter.getParam('eventID'))
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writephases(picks, 'HYPO71', hypo71file)
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writephases(finalpicks.getpicdic(), 'HYPO71', hypo71file)
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endsplash = '''------------------------------------------\n'
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-----Finished event %s!-----\n'
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@ -8,17 +8,22 @@ Created August/September 2015.
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import matplotlib.pyplot as plt
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import numpy as np
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from obspy.core import Stream
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from pylot.core.pick.utils import getsignalwin
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from obspy.core import Stream, UTCDateTime
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from pylot.core.pick.utils import getsignalwin, crossings_nonzero_all
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from pylot.core.util.utils import getPatternLine
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from scipy.optimize import curve_fit
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from scipy import integrate
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from pylot.core.read.data import Data
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class Magnitude(object):
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'''
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Superclass for calculating Wood-Anderson peak-to-peak
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amplitudes, local magnitudes and moment magnitudes.
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amplitudes, local magnitudes, seismic moments
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and moment magnitudes.
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'''
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def __init__(self, wfstream, To, pwin, iplot, w0=None, delta=None, rho=None, vp=None):
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def __init__(self, wfstream, To, pwin, iplot, NLLocfile=None, \
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picks=None, rho=None, vp=None, invdir=None):
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'''
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:param: wfstream
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:type: `~obspy.core.stream.Stream
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@ -28,12 +33,27 @@ class Magnitude(object):
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:param: pwin, pick window [To To+pwin] to get maximum
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peak-to-peak amplitude (WApp) or to calculate
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source spectrum (DCfc)
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source spectrum (DCfc) around P onset
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:type: float
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:param: iplot, no. of figure window for plotting interims results
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:type: integer
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:type: integer
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:param: NLLocfile, name and full path to NLLoc-location file
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needed when calling class MoMw
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:type: string
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:param: picks, dictionary containing picking results
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:type: dictionary
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:param: rho [kg/m³], rock density, parameter from autoPyLoT.in
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:type: integer
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:param: vp [m/s], P-velocity
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:param: integer
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:param: invdir, path to inventory or dataless-SEED file
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:type: string
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'''
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assert isinstance(wfstream, Stream), "%s is not a stream object" % str(wfstream)
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@ -42,13 +62,14 @@ class Magnitude(object):
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self.setTo(To)
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self.setpwin(pwin)
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self.setiplot(iplot)
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self.setw0(w0)
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self.setNLLocfile(NLLocfile)
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self.setrho(rho)
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self.setdelta(delta)
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self.setpicks(picks)
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self.setvp(vp)
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self.setinvdir(invdir)
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self.calcwapp()
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self.calcsourcespec()
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self.calcMoMw()
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self.run_calcMoMw()
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def getwfstream(self):
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@ -75,11 +96,11 @@ class Magnitude(object):
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def setiplot(self, iplot):
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self.iplot = iplot
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def setw0(self, w0):
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self.w0 = w0
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def setNLLocfile(self, NLLocfile):
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self.NLLocfile = NLLocfile
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def getw0(self):
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return self.w0
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def getNLLocfile(self):
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return self.NLLocfile
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def setrho(self, rho):
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self.rho = rho
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@ -93,11 +114,11 @@ class Magnitude(object):
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def getvp(self):
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return self.vp
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def setdelta(self, delta):
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self.delta = delta
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def setpicks(self, picks):
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self.picks = picks
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def getdelta(self):
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return self.delta
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def getpicks(self):
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return self.picks
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def getwapp(self):
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return self.wapp
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@ -108,11 +129,14 @@ class Magnitude(object):
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def getfc(self):
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return self.fc
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def getMo(self):
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return self.Mo
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def setinvdir(self, invdir):
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self.invdir = invdir
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def getMw(self):
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return self.Mw
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def getinvdir(self):
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return self.invdir
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def getpicdic(self):
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return self.picdic
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def calcwapp(self):
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self.wapp = None
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@ -120,9 +144,8 @@ class Magnitude(object):
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def calcsourcespec(self):
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self.sourcespek = None
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def calcMoMw(self):
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self.Mo = None
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self.Mw = None
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def run_calcMoMw(self):
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self.pickdic = None
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class WApp(Magnitude):
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'''
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@ -177,116 +200,209 @@ class WApp(Magnitude):
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class M0Mw(Magnitude):
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'''
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Method to calculate seismic moment Mo and moment magnitude Mw.
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Uses class w0fc for calculating plateau wo and corner frequency
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fc of source spectrum, respectively.
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Requires results of class w0fc for calculating plateau w0
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and corner frequency fc of source spectrum, respectively. Uses
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subfunction calcMoMw.py. Returns modified dictionary of picks including
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Dc-value, corner frequency fc, seismic moment Mo and
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corresponding moment magntiude Mw.
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'''
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def calcMoMw(self):
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def run_calcMoMw(self):
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stream = self.getwfstream()
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tr = stream[0]
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picks = self.getpicks()
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nllocfile = self.getNLLocfile()
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wfdat = self.getwfstream()
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# get vertical component data only
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zdat = wfdat.select(component="Z")
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if len(zdat) == 0: # check for other components
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zdat = wfdat.select(component="3")
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print("Calculating seismic moment Mo and moment magnitude Mw for station %s ..." \
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% tr.stats.station)
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for key in picks:
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if picks[key]['P']['weight'] < 4:
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# select waveform
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selwf = zdat.select(station=key)
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# get hypocentral distance of station
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# from NLLoc-location file
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if len(key) > 4:
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Ppattern = '%s ? ? ? P' % key
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elif len(key) == 4:
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Ppattern = '%s ? ? ? P' % key
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elif len(key) < 4:
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Ppattern = '%s ? ? ? P' % key
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nllocline = getPatternLine(nllocfile, Ppattern)
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delta = float(nllocline.split(None)[21])
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# call subfunction to estimate source spectrum
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# and to derive w0 and fc
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[w0, fc] = calcsourcespec(selwf, picks[key]['P']['mpp'], \
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self.getiplot(), self.getinvdir())
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# additional common parameters for calculating Mo
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rP = 2 / np.sqrt(15) # average radiation pattern of P waves (Aki & Richards, 1980)
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freesurf = 2.0 # free surface correction, assuming vertical incidence
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if w0 is not None:
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# call subfunction to calculate Mo and Mw
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[Mo, Mw] = calcMoMw(selwf, w0, self.getrho(), self.getvp(), \
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delta, self.getinvdir())
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else:
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Mo = None
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Mw = None
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self.Mo = (self.getw0() * 4 * np.pi * self.getrho() * np.power(self.getvp(), 3) * \
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self.getdelta()) / (rP * freesurf)
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# add w0, fc, Mo and Mw to dictionary
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picks[key]['P']['w0'] = w0
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picks[key]['P']['fc'] = fc
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picks[key]['P']['Mo'] = Mo
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picks[key]['P']['Mw'] = Mw
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self.picdic = picks
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self.Mw = 2/3 * np.log10(self.Mo) - 6
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print("MoMw: Calculated seismic moment Mo = %e Nm => Mw = %3.1f " % (self.Mo, self.Mw))
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class w0fc(Magnitude):
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def calcMoMw(wfstream, w0, rho, vp, delta, inv):
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'''
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Method to calculate the source spectrum and to derive from that the plateau
|
||||
Subfunction of run_calcMoMw to calculate individual
|
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seismic moments and corresponding moment magnitudes.
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'''
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tr = wfstream[0]
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||||
print("calcMoMw: Calculating seismic moment Mo and moment magnitude Mw for station %s ..." \
|
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% tr.stats.station)
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||||
# additional common parameters for calculating Mo
|
||||
rP = 2 / np.sqrt(15) # average radiation pattern of P waves (Aki & Richards, 1980)
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freesurf = 2.0 # free surface correction, assuming vertical incidence
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||||
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||||
Mo = w0 * 4 * np.pi * rho * np.power(vp, 3) * delta / (rP * freesurf)
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Mw = np.log10(Mo * 1e07) * 2 / 3 - 10.7 #after Hanks & Kanamori (1979), defined for [dyn*cm]!
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||||
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||||
print("calcMoMw: Calculated seismic moment Mo = %e Nm => Mw = %3.1f " % (Mo, Mw))
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||||
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return Mo, Mw
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||||
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||||
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||||
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||||
def calcsourcespec(wfstream, onset, iplot, inventory):
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'''
|
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Subfunction to calculate the source spectrum and to derive from that the plateau
|
||||
(usually called omega0) and the corner frequency assuming Aki's omega-square
|
||||
source model. Has to be derived from instrument corrected displacement traces!
|
||||
source model. Has to be derived from instrument corrected displacement traces,
|
||||
thus restitution and integration necessary!
|
||||
'''
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||||
print ("Calculating source spectrum ....")
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||||
|
||||
def calcsourcespec(self):
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||||
print ("Calculating source spectrum ....")
|
||||
fc = None
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||||
w0 = None
|
||||
data = Data()
|
||||
z_copy = wfstream.copy()
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||||
|
||||
self.w0 = None # DC-value
|
||||
self.fc = None # corner frequency
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||||
|
||||
stream = self.getwfstream()
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||||
tr = stream[0]
|
||||
[corzdat, restflag] = data.restituteWFData(inventory, z_copy)
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||||
|
||||
if restflag == 1:
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||||
# integrate to displacment
|
||||
corintzdat = integrate.cumtrapz(corzdat[0], None, corzdat[0].stats.delta)
|
||||
z_copy[0].data = corintzdat
|
||||
tr = z_copy[0]
|
||||
# get window after P pulse for
|
||||
# calculating source spectrum
|
||||
if tr.stats.sampling_rate <= 100:
|
||||
winzc = tr.stats.sampling_rate
|
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elif tr.stats.sampling_rate > 100 and \
|
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tr.stats.sampling_rate <= 200:
|
||||
winzc = 0.5 * tr.stats.sampling_rate
|
||||
elif tr.stats.sampling_rate > 200 and \
|
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tr.stats.sampling_rate <= 400:
|
||||
winzc = 0.2 * tr.stats.sampling_rate
|
||||
elif tr.stats.sampling_rate > 400:
|
||||
winzc = tr.stats.sampling_rate
|
||||
tstart = UTCDateTime(tr.stats.starttime)
|
||||
tonset = onset.timestamp -tstart.timestamp
|
||||
impickP = tonset * tr.stats.sampling_rate
|
||||
wfzc = tr.data[impickP : impickP + winzc]
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||||
# get time array
|
||||
t = np.arange(0, len(tr) * tr.stats.delta, tr.stats.delta)
|
||||
iwin = getsignalwin(t, self.getTo(), self.getpwin())
|
||||
xdat = tr.data[iwin]
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||||
# calculate spectrum using only first cycles of
|
||||
# waveform after P onset!
|
||||
zc = crossings_nonzero_all(wfzc)
|
||||
if np.size(zc) == 0 or len(zc) <= 3:
|
||||
print ("Something is wrong with the waveform, "
|
||||
"no zero crossings derived!")
|
||||
print ("No calculation of source spectrum possible!")
|
||||
plotflag = 0
|
||||
else:
|
||||
plotflag = 1
|
||||
index = min([3, len(zc) - 1])
|
||||
calcwin = (zc[index] - zc[0]) * z_copy[0].stats.delta
|
||||
iwin = getsignalwin(t, tonset, calcwin)
|
||||
xdat = tr.data[iwin]
|
||||
|
||||
# fft
|
||||
fny = tr.stats.sampling_rate / 2
|
||||
l = len(xdat) / tr.stats.sampling_rate
|
||||
n = tr.stats.sampling_rate * l # number of fft bins after Bath
|
||||
# find next power of 2 of data length
|
||||
m = pow(2, np.ceil(np.log(len(xdat)) / np.log(2)))
|
||||
N = int(np.power(m, 2))
|
||||
y = tr.stats.delta * np.fft.fft(xdat, N)
|
||||
Y = abs(y[: N/2])
|
||||
L = (N - 1) / tr.stats.sampling_rate
|
||||
f = np.arange(0, fny, 1/L)
|
||||
# fft
|
||||
fny = tr.stats.sampling_rate / 2
|
||||
l = len(xdat) / tr.stats.sampling_rate
|
||||
n = tr.stats.sampling_rate * l # number of fft bins after Bath
|
||||
# find next power of 2 of data length
|
||||
m = pow(2, np.ceil(np.log(len(xdat)) / np.log(2)))
|
||||
N = int(np.power(m, 2))
|
||||
y = tr.stats.delta * np.fft.fft(xdat, N)
|
||||
Y = abs(y[: N/2])
|
||||
L = (N - 1) / tr.stats.sampling_rate
|
||||
f = np.arange(0, fny, 1/L)
|
||||
|
||||
# remove zero-frequency and frequencies above
|
||||
# corner frequency of seismometer (assumed
|
||||
# to be 100 Hz)
|
||||
fi = np.where((f >= 1) & (f < 100))
|
||||
F = f[fi]
|
||||
YY = Y[fi]
|
||||
# get plateau (DC value) and corner frequency
|
||||
# initial guess of plateau
|
||||
w0in = np.mean(YY[0:100])
|
||||
# initial guess of corner frequency
|
||||
# where spectral level reached 50% of flat level
|
||||
iin = np.where(YY >= 0.5 * w0in)
|
||||
Fcin = F[iin[0][np.size(iin) - 1]]
|
||||
# remove zero-frequency and frequencies above
|
||||
# corner frequency of seismometer (assumed
|
||||
# to be 100 Hz)
|
||||
fi = np.where((f >= 1) & (f < 100))
|
||||
F = f[fi]
|
||||
YY = Y[fi]
|
||||
# get plateau (DC value) and corner frequency
|
||||
# initial guess of plateau
|
||||
w0in = np.mean(YY[0:100])
|
||||
# initial guess of corner frequency
|
||||
# where spectral level reached 50% of flat level
|
||||
iin = np.where(YY >= 0.5 * w0in)
|
||||
Fcin = F[iin[0][np.size(iin) - 1]]
|
||||
|
||||
# use of implicit scipy otimization function
|
||||
fit = synthsourcespec(F, w0in, Fcin)
|
||||
[optspecfit, pcov] = curve_fit(synthsourcespec, F, YY.real, [w0in, Fcin])
|
||||
w01 = optspecfit[0]
|
||||
fc1 = optspecfit[1]
|
||||
print ("w0fc: Determined w0-value: %e m/Hz, \n"
|
||||
"Determined corner frequency: %f Hz" % (w01, fc1))
|
||||
# use of implicit scipy otimization function
|
||||
fit = synthsourcespec(F, w0in, Fcin)
|
||||
[optspecfit, pcov] = curve_fit(synthsourcespec, F, YY.real, [w0in, Fcin])
|
||||
w01 = optspecfit[0]
|
||||
fc1 = optspecfit[1]
|
||||
print ("w0fc: Determined w0-value: %e m/Hz, \n"
|
||||
"Determined corner frequency: %f Hz" % (w01, fc1))
|
||||
|
||||
# use of conventional fitting
|
||||
[w02, fc2] = fitSourceModel(F, YY.real, Fcin, self.getiplot())
|
||||
# use of conventional fitting
|
||||
[w02, fc2] = fitSourceModel(F, YY.real, Fcin, iplot)
|
||||
|
||||
# get w0 and fc as median
|
||||
self.w0 = np.median([w01, w02])
|
||||
self.fc = np.median([fc1, fc2])
|
||||
print("w0fc: Using w0-value = %e m/Hz and fc = %f Hz" % (self.w0, self.fc))
|
||||
# get w0 and fc as median
|
||||
w0 = np.median([w01, w02])
|
||||
fc = np.median([fc1, fc2])
|
||||
print("w0fc: Using w0-value = %e m/Hz and fc = %f Hz" % (w0, fc))
|
||||
|
||||
if self.getiplot() > 1:
|
||||
f1 = plt.figure()
|
||||
plt.subplot(2,1,1)
|
||||
# show displacement in mm
|
||||
plt.plot(t, np.multiply(tr, 1000), 'k')
|
||||
if iplot > 1:
|
||||
f1 = plt.figure()
|
||||
plt.subplot(2,1,1)
|
||||
# show displacement in mm
|
||||
plt.plot(t, np.multiply(tr, 1000), 'k')
|
||||
if plotflag == 1:
|
||||
plt.plot(t[iwin], np.multiply(xdat, 1000), 'g')
|
||||
plt.title('Seismogram and P pulse, station %s' % tr.stats.station)
|
||||
plt.xlabel('Time since %s' % tr.stats.starttime)
|
||||
plt.ylabel('Displacement [mm]')
|
||||
plt.title('Seismogram and P Pulse, Station %s-%s' \
|
||||
% (tr.stats.station, tr.stats.channel))
|
||||
else:
|
||||
plt.title('Seismogram, Station %s-%s' \
|
||||
% (tr.stats.station, tr.stats.channel))
|
||||
plt.xlabel('Time since %s' % tr.stats.starttime)
|
||||
plt.ylabel('Displacement [mm]')
|
||||
|
||||
if plotflag == 1:
|
||||
plt.subplot(2,1,2)
|
||||
plt.loglog(f, Y.real, 'k')
|
||||
plt.loglog(F, YY.real)
|
||||
plt.loglog(F, fit, 'g')
|
||||
plt.loglog([self.fc, self.fc], [self.w0/100, self.w0], 'g')
|
||||
plt.loglog([fc, fc], [w0/100, w0], 'g')
|
||||
plt.title('Source Spectrum from P Pulse, w0=%e m/Hz, fc=%6.2f Hz' \
|
||||
% (self.w0, self.fc))
|
||||
% (w0, fc))
|
||||
plt.xlabel('Frequency [Hz]')
|
||||
plt.ylabel('Amplitude [m/Hz]')
|
||||
plt.grid()
|
||||
plt.show()
|
||||
raw_input()
|
||||
plt.close(f1)
|
||||
plt.show()
|
||||
raw_input()
|
||||
plt.close(f1)
|
||||
|
||||
return w0, fc
|
||||
|
||||
|
||||
def synthsourcespec(f, omega0, fcorner):
|
||||
|
||||
@ -15,10 +15,10 @@ from scipy import integrate
|
||||
from pylot.core.pick.Picker import AICPicker, PragPicker
|
||||
from pylot.core.pick.CharFuns import HOScf, AICcf, ARZcf, ARHcf, AR3Ccf
|
||||
from pylot.core.pick.utils import checksignallength, checkZ4S, earllatepicker,\
|
||||
getSNR, fmpicker, checkPonsets, wadaticheck, crossings_nonzero_all
|
||||
getSNR, fmpicker, checkPonsets, wadaticheck
|
||||
from pylot.core.util.utils import getPatternLine
|
||||
from pylot.core.read.data import Data
|
||||
from pylot.core.analysis.magnitude import WApp, w0fc
|
||||
from pylot.core.analysis.magnitude import WApp
|
||||
|
||||
def autopickevent(data, param):
|
||||
stations = []
|
||||
@ -138,8 +138,6 @@ def autopickstation(wfstream, pickparam, verbose=False):
|
||||
Sflag = 0
|
||||
Pmarker = []
|
||||
Ao = None # Wood-Anderson peak-to-peak amplitude
|
||||
w0 = None # plateau of source spectrum
|
||||
fc = None # corner frequancy of source spectrum
|
||||
|
||||
# split components
|
||||
zdat = wfstream.select(component="Z")
|
||||
@ -317,38 +315,6 @@ def autopickstation(wfstream, pickparam, verbose=False):
|
||||
else:
|
||||
FM = 'N'
|
||||
|
||||
##############################################################
|
||||
# get DC value and corner frequency (fc) of source spectrum
|
||||
# from P pulse
|
||||
# initialize Data object
|
||||
data = Data()
|
||||
z_copy = zdat.copy()
|
||||
[corzdat, restflag] = data.restituteWFData(invdir, z_copy)
|
||||
if restflag == 1:
|
||||
# integrate to displacement
|
||||
corintzdat = integrate.cumtrapz(corzdat[0], None, corzdat[0].stats.delta)
|
||||
z_copy[0].data = corintzdat
|
||||
# largest detectable period == window length
|
||||
# after P pulse for calculating source spectrum
|
||||
winzc = (1 / bpz2[0]) * z_copy[0].stats.sampling_rate
|
||||
impickP = mpickP * z_copy[0].stats.sampling_rate
|
||||
wfzc = z_copy[0].data[impickP : impickP + winzc]
|
||||
# calculate spectrum using only first cycles of
|
||||
# waveform after P onset!
|
||||
zc = crossings_nonzero_all(wfzc)
|
||||
if np.size(zc) == 0 or len(zc) <= 3:
|
||||
msg = "Something is wrong with the waveform, " \
|
||||
"no zero crossings derived!\nCannot " \
|
||||
"calculate source spectrum!"
|
||||
if verbose: print(msg)
|
||||
else:
|
||||
index = min([3, len(zc) - 1])
|
||||
calcwin = (zc[index] - zc[0]) * z_copy[0].stats.delta
|
||||
# calculate source spectrum and get w0 and fc
|
||||
specpara = w0fc(z_copy, mpickP, calcwin, iplot)
|
||||
w0 = specpara.getw0()
|
||||
fc = specpara.getfc()
|
||||
|
||||
msg = "autopickstation: P-weight: {0}, " \
|
||||
"SNR: {1}, SNR[dB]: {2}, Polarity: {3}".format(Pweight,
|
||||
SNRP,
|
||||
@ -808,8 +774,7 @@ def autopickstation(wfstream, pickparam, verbose=False):
|
||||
# for P phase
|
||||
phase = 'P'
|
||||
phasepick = {'lpp': lpickP, 'epp': epickP, 'mpp': mpickP, 'spe': Perror,
|
||||
'snr': SNRP, 'snrdb': SNRPdB, 'weight': Pweight, 'fm': FM,
|
||||
'w0': w0, 'fc': fc}
|
||||
'snr': SNRP, 'snrdb': SNRPdB, 'weight': Pweight, 'fm': FM}
|
||||
picks = {phase: phasepick}
|
||||
# add P marker
|
||||
picks[phase]['marked'] = Pmarker
|
||||
|
||||
Loading…
Reference in New Issue
Block a user