243 lines
14 KiB
Python
Executable File
243 lines
14 KiB
Python
Executable File
#!/usr/bin/python
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# -*- coding: utf-8 -*-
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"""
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Script to run autoPyLoT-script "makeCF.py".
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Only for test purposes!
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"""
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from obspy.core import read
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import matplotlib.pyplot as plt
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import numpy as np
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from CharFuns import *
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from Picker import *
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import glob
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import argparse
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import pdb
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def run_makeCF(project, database, event, iplot, station=None):
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#parameters for CF calculation
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t2 = 7 #length of moving window for HOS calculation [sec]
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p = 4 #order of statistics
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cuttimes = [5, 40] #start and end time for CF calculation
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bpz = [2, 30] #corner frequencies of bandpass filter, vertical component
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bph = [2, 15] #corner frequencies of bandpass filter, horizontal components
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tdetz= 1.2 #length of AR-determination window [sec], vertical component
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tdeth= 0.8 #length of AR-determination window [sec], horizontal components
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tpredz = 0.4 #length of AR-prediction window [sec], vertical component
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tpredh = 0.4 #length of AR-prediction window [sec], horizontal components
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addnoise = 0.001 #add noise to seismogram for stable AR prediction
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arzorder = 2 #chosen order of AR process, vertical component
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arhorder = 4 #chosen order of AR process, horizontal components
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#get waveform data
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if station:
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dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHZ.msd' % (project, database, event, station)
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dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHE.msd' % (project, database, event, station)
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dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*EHN.msd' % (project, database, event, station)
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#dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_z.gse' % (project, database, event, station)
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#dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_e.gse' % (project, database, event, station)
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#dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_n.gse' % (project, database, event, station)
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else:
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dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHZ.msd' % (project, database, event)
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dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHE.msd' % (project, database, event)
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dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*EHN.msd' % (project, database, event)
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wfzfiles = glob.glob(dpz)
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wfefiles = glob.glob(dpe)
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wfnfiles = glob.glob(dpn)
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if wfzfiles:
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for i in range(len(wfzfiles)):
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print 'Vertical component data found ...'
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print wfzfiles[i]
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st = read('%s' % wfzfiles[i])
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st_copy = st.copy()
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#filter and taper data
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tr_filt = st[0].copy()
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tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
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tr_filt.taper(max_percentage=0.05, type='hann')
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st_copy[0].data = tr_filt.data
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##############################################################
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#calculate HOS-CF using subclass HOScf of class CharacteristicFunction
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hoscf = HOScf(st_copy, cuttimes, t2, p) #instance of HOScf
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##############################################################
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#calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction
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#class needs stream object => build it
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tr_aic = tr_filt.copy()
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tr_aic.data = hoscf.getCF()
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st_copy[0].data = tr_aic.data
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aiccf = AICcf(st_copy, cuttimes, t2) #instance of AICcf
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##############################################################
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#get prelimenary onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking
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aicpick = AICPicker(aiccf, 2, 70, [1, 0.5, 0.2], 3)
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##############################################################
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#get refined onset time from HOS-CF using class Picker
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hospick = PragPicker(hoscf, 2, 70, [1, 0.5, 0.2], 2, 0.001, 0.2, aicpick.getpick())
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##############################################################
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#calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction
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#get stream object of filtered data
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st_copy[0].data = tr_filt.data
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arzcf = ARZcf(st_copy, cuttimes, tpredz, arzorder, tdetz, addnoise) #instance of ARZcf
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##############################################################
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#calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction
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#class needs stream object => build it
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tr_arzaic = tr_filt.copy()
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tr_arzaic.data = arzcf.getCF()
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st_copy[0].data = tr_arzaic.data
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araiccf = AICcf(st_copy, cuttimes, tpredz, 0, tdetz) #instance of AICcf
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##############################################################
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#get onset time from AIC-ARZ-CF using subclass AICPicker of class AutoPicking
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aicarzpick = AICPicker(araiccf, 2, 70, [1, 0.5, 0.2], 2)
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##############################################################
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#get refined onset time from ARZ-CF using class Picker
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arzpick = PragPicker(arzcf, 2, 70, [1, 0.5, 0.2], 2, 0, 0.2, aicarzpick.getpick())
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elif not wfzfiles:
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print 'No vertical component data found!'
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if wfefiles and wfnfiles:
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for i in range(len(wfefiles)):
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print 'Horizontal component data found ...'
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print wfefiles[i]
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print wfnfiles[i]
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#merge streams
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H = read('%s' % wfefiles[i])
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H += read('%s' % wfnfiles[i])
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H_copy = H.copy()
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#filter and taper data
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trH1_filt = H[0].copy()
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trH2_filt = H[1].copy()
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trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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trH1_filt.taper(max_percentage=0.05, type='hann')
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trH2_filt.taper(max_percentage=0.05, type='hann')
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H_copy[0].data = trH1_filt.data
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H_copy[1].data = trH2_filt.data
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##############################################################
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#calculate ARH-CF using subclass ARHcf of class CharcteristicFunction
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arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) #instance of ARHcf
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##############################################################
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#calculate AIC-ARH-CF using subclass AICcf of class CharacteristicFunction
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#class needs stream object => build it
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tr_arhaic = trH1_filt.copy()
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tr_arhaic.data = arhcf.getCF()
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H_copy[0].data = tr_arhaic.data
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#calculate ARH-AIC-CF
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arhaiccf = AICcf(H_copy, cuttimes, tpredh, 0, tdeth) #instance of AICcf
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##############################################################
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#get onset time from AIC-ARH-CF using subclass AICPicker of class AutoPicking
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aicarhpick = AICPicker(arhaiccf, 2, 70, [1, 0.5, 0.2], 2)
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###############################################################
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#create stream with 3 traces
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#merge streams
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AllC = read('%s' % wfefiles[i])
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AllC += read('%s' % wfnfiles[i])
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AllC += read('%s' % wfzfiles[i])
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#filter and taper data
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All1_filt = AllC[0].copy()
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All2_filt = AllC[1].copy()
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All3_filt = AllC[2].copy()
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All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
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All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
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All1_filt.taper(max_percentage=0.05, type='hann')
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All2_filt.taper(max_percentage=0.05, type='hann')
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All3_filt.taper(max_percentage=0.05, type='hann')
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AllC[0].data = All1_filt.data
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AllC[1].data = All2_filt.data
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AllC[2].data = All3_filt.data
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#calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
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ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) #instance of AR3Ccf
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##############################################################
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if iplot:
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#plot vertical trace
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plt.figure()
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tr = st[0]
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tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
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p1 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
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p2 = plt.plot(hoscf.getTimeArray(), hoscf.getCF() / max(hoscf.getCF()), 'r')
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p3 = plt.plot(aiccf.getTimeArray(), aiccf.getCF()/max(aiccf.getCF()), 'b')
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p4 = plt.plot(arzcf.getTimeArray(), arzcf.getCF()/max(arzcf.getCF()), 'g')
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p5 = plt.plot(araiccf.getTimeArray(), araiccf.getCF()/max(araiccf.getCF()), 'y')
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plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b--')
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plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [1, 1], 'b')
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plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [-1, -1], 'b')
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plt.plot([hospick.getpick(), hospick.getpick()], [-1.3, 1.3], 'r--')
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plt.plot([hospick.getpick()-0.5, hospick.getpick()+0.5], [1.3, 1.3], 'r')
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plt.plot([hospick.getpick()-0.5, hospick.getpick()+0.5], [-1.3, -1.3], 'r')
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plt.plot([aicarzpick.getpick(), aicarzpick.getpick()], [-1.2, 1.2], 'y--')
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plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [1.2, 1.2], 'y')
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plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [-1.2, -1.2], 'y')
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plt.plot([arzpick.getpick(), arzpick.getpick()], [-1.4, 1.4], 'g--')
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plt.plot([arzpick.getpick()-0.5, arzpick.getpick()+0.5], [1.4, 1.4], 'g')
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plt.plot([arzpick.getpick()-0.5, arzpick.getpick()+0.5], [-1.4, -1.4], 'g')
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plt.yticks([])
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plt.xlabel('Time [s]')
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plt.ylabel('Normalized Counts')
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plt.title([tr.stats.station, tr.stats.channel])
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plt.suptitle(tr.stats.starttime)
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plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
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#plot horizontal traces
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plt.figure(2)
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plt.subplot(211)
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tsteph = tpredh / 4
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th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
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th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
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tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth +tpredh
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p21 = plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
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p22 = plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
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p23 = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
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plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b--')
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plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
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plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
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plt.yticks([])
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plt.ylabel('Normalized Counts')
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plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
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plt.suptitle(trH1_filt.stats.starttime)
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plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
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plt.subplot(212)
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plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
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plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
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plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b--')
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plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
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plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
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plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
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plt.yticks([])
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plt.xlabel('Time [s]')
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plt.ylabel('Normalized Counts')
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#plot 3-component window
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plt.figure(3)
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tar3ccf = np.arange(0, len(ar3ccf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdetz +tpredz
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plt.subplot(311)
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p31 = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
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p32 = plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
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plt.yticks([])
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plt.xticks([])
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plt.ylabel('Normalized Counts')
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plt.title([tr.stats.station, tr.stats.channel])
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plt.legend([p31, p32], ['Data', 'AR3C-CF'])
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plt.subplot(312)
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plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
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plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
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plt.yticks([])
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plt.xticks([])
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plt.ylabel('Normalized Counts')
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plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
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plt.subplot(313)
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plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
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plt.plot(tar3ccf, ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
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plt.yticks([])
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plt.ylabel('Normalized Counts')
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plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
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plt.xlabel('Time [s]')
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plt.show()
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raw_input()
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plt.close()
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parser = argparse.ArgumentParser()
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parser.add_argument('--project', type=str, help='project name (e.g. Insheim)')
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parser.add_argument('--database', type=str, help='event data base (e.g. 2014.09_Insheim)')
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parser.add_argument('--event', type=str, help='event ID (e.g. e0010.015.14)')
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parser.add_argument('--iplot', help='anything, if set, figure occurs')
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parser.add_argument('--station', type=str, help='Station ID (e.g. INS3) (optional)')
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args = parser.parse_args()
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run_makeCF(args.project, args.database, args.event, args.iplot, args.station)
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