#!/usr/bin/python
# -*- coding: utf-8 -*-
"""
Script to run autoPyLoT-script "run_makeCF.py".
Only for test purposes!
"""
import argparse
import glob
from obspy.core import read
from pylot.core.pick.utils import *
def run_makeCF(project, database, event, iplot, station=None):
# parameters for CF calculation
t2 = 7 # length of moving window for HOS calculation [sec]
p = 4 # order of HOS
cuttimes = [10, 50] # start and end time for CF calculation
bpz = [2, 30] # corner frequencies of bandpass filter, vertical component
bph = [2, 15] # corner frequencies of bandpass filter, horizontal components
tdetz = 1.2 # length of AR-determination window [sec], vertical component
tdeth = 0.8 # length of AR-determination window [sec], horizontal components
tpredz = 0.4 # length of AR-prediction window [sec], vertical component
tpredh = 0.4 # length of AR-prediction window [sec], horizontal components
addnoise = 0.001 # add noise to seismogram for stable AR prediction
arzorder = 2 # chosen order of AR process, vertical component
arhorder = 4 # chosen order of AR process, horizontal components
TSNRhos = [5, 0.5, 1, .6] # window lengths [s] for calculating SNR for earliest/latest pick and quality assessment
# from HOS-CF [noise window, safety gap, signal window, slope determination window]
TSNRarz = [5, 0.5, 1, 1.0] # window lengths [s] for calculating SNR for earliest/lates pick and quality assessment
# from ARZ-CF
# get waveform data
if station:
dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HZ.msd' % (project, database, event, station)
dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HE.msd' % (project, database, event, station)
dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HN.msd' % (project, database, event, station)
# dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_z.gse' % (project, database, event, station)
# dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_e.gse' % (project, database, event, station)
# dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_n.gse' % (project, database, event, station)
else:
dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HZ.msd' % (project, database, event)
dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HE.msd' % (project, database, event)
dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HN.msd' % (project, database, event)
wfzfiles = glob.glob(dpz)
wfefiles = glob.glob(dpe)
wfnfiles = glob.glob(dpn)
if wfzfiles:
for i in range(len(wfzfiles)):
print
'Vertical component data found ...'
print
wfzfiles[i]
st = read('%s' % wfzfiles[i])
st_copy = st.copy()
# filter and taper data
tr_filt = st[0].copy()
tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
tr_filt.taper(max_percentage=0.05, type='hann')
st_copy[0].data = tr_filt.data
##############################################################
# calculate HOS-CF using subclass HOScf of class CharacteristicFunction
hoscf = HOScf(st_copy, cuttimes, t2, p) # instance of HOScf
##############################################################
# calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction
# class needs stream object => build it
tr_aic = tr_filt.copy()
tr_aic.data = hoscf.getCF()
st_copy[0].data = tr_aic.data
aiccf = AICcf(st_copy, cuttimes) # instance of AICcf
##############################################################
# get prelimenary onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking
aicpick = AICPicker(aiccf, TSNRhos, 3, 10, None, 0.1)
##############################################################
# get refined onset time from HOS-CF using class Picker
hospick = PragPicker(hoscf, TSNRhos, 2, 10, 0.001, 0.2, aicpick.getpick())
#############################################################
# get earliest and latest possible picks
st_copy[0].data = tr_filt.data
[lpickhos, epickhos, pickerrhos] = earllatepicker(st_copy, 1.5, TSNRhos, hospick.getpick(), 10)
#############################################################
# get SNR
[SNR, SNRdB] = getSNR(st_copy, TSNRhos, hospick.getpick())
print
'SNR:', SNR, 'SNR[dB]:', SNRdB
##########################################################
# get first motion of onset
hosfm = fmpicker(st, st_copy, 0.2, hospick.getpick(), 11)
##############################################################
# calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction
arzcf = ARZcf(st, cuttimes, tpredz, arzorder, tdetz, addnoise) # instance of ARZcf
##############################################################
# calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction
# class needs stream object => build it
tr_arzaic = tr_filt.copy()
tr_arzaic.data = arzcf.getCF()
st_copy[0].data = tr_arzaic.data
araiccf = AICcf(st_copy, cuttimes, tpredz, 0, tdetz) # instance of AICcf
##############################################################
# get onset time from AIC-ARZ-CF using subclass AICPicker of class AutoPicking
aicarzpick = AICPicker(araiccf, TSNRarz, 2, 10, None, 0.1)
##############################################################
# get refined onset time from ARZ-CF using class Picker
arzpick = PragPicker(arzcf, TSNRarz, 2.0, 10, 0.1, 0.05, aicarzpick.getpick())
# get earliest and latest possible picks
st_copy[0].data = tr_filt.data
[lpickarz, epickarz, pickerrarz] = earllatepicker(st_copy, 1.5, TSNRarz, arzpick.getpick(), 10)
elif not wfzfiles:
print
'No vertical component data found!'
if wfefiles and wfnfiles:
for i in range(len(wfefiles)):
print
'Horizontal component data found ...'
print
wfefiles[i]
print
wfnfiles[i]
# merge streams
H = read('%s' % wfefiles[i])
H += read('%s' % wfnfiles[i])
H_copy = H.copy()
# filter and taper data
trH1_filt = H[0].copy()
trH2_filt = H[1].copy()
trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
trH1_filt.taper(max_percentage=0.05, type='hann')
trH2_filt.taper(max_percentage=0.05, type='hann')
H_copy[0].data = trH1_filt.data
H_copy[1].data = trH2_filt.data
##############################################################
# calculate ARH-CF using subclass ARHcf of class CharcteristicFunction
arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) # instance of ARHcf
##############################################################
# calculate AIC-ARH-CF using subclass AICcf of class CharacteristicFunction
# class needs stream object => build it
tr_arhaic = trH1_filt.copy()
tr_arhaic.data = arhcf.getCF()
H_copy[0].data = tr_arhaic.data
# calculate ARH-AIC-CF
arhaiccf = AICcf(H_copy, cuttimes, tpredh, 0, tdeth) # instance of AICcf
##############################################################
# get onset time from AIC-ARH-CF using subclass AICPicker of class AutoPicking
aicarhpick = AICPicker(arhaiccf, TSNRarz, 4, 10, None, 0.1)
###############################################################
# get refined onset time from ARH-CF using class Picker
arhpick = PragPicker(arhcf, TSNRarz, 2.5, 10, 0.1, 0.05, aicarhpick.getpick())
# get earliest and latest possible picks
H_copy[0].data = trH1_filt.data
[lpickarh1, epickarh1, pickerrarh1] = earllatepicker(H_copy, 1.5, TSNRarz, arhpick.getpick(), 10)
H_copy[0].data = trH2_filt.data
[lpickarh2, epickarh2, pickerrarh2] = earllatepicker(H_copy, 1.5, TSNRarz, arhpick.getpick(), 10)
# get earliest pick of both earliest possible picks
epick = [epickarh1, epickarh2]
lpick = [lpickarh1, lpickarh2]
pickerr = [pickerrarh1, pickerrarh2]
ipick = np.argmin([epickarh1, epickarh2])
epickarh = epick[ipick]
lpickarh = lpick[ipick]
pickerrarh = pickerr[ipick]
# create stream with 3 traces
# merge streams
AllC = read('%s' % wfefiles[i])
AllC += read('%s' % wfnfiles[i])
AllC += read('%s' % wfzfiles[i])
# filter and taper data
All1_filt = AllC[0].copy()
All2_filt = AllC[1].copy()
All3_filt = AllC[2].copy()
All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
All1_filt.taper(max_percentage=0.05, type='hann')
All2_filt.taper(max_percentage=0.05, type='hann')
All3_filt.taper(max_percentage=0.05, type='hann')
AllC[0].data = All1_filt.data
AllC[1].data = All2_filt.data
AllC[2].data = All3_filt.data
# calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) # instance of AR3Ccf
##############################################################
if iplot:
# plot vertical trace
plt.figure()
tr = st[0]
tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
p1, = plt.plot(tdata, tr_filt.data / max(tr_filt.data), 'k')
p2, = plt.plot(hoscf.getTimeArray(), hoscf.getCF() / max(hoscf.getCF()), 'r')
p3, = plt.plot(aiccf.getTimeArray(), aiccf.getCF() / max(aiccf.getCF()), 'b')
p4, = plt.plot(arzcf.getTimeArray(), arzcf.getCF() / max(arzcf.getCF()), 'g')
p5, = plt.plot(araiccf.getTimeArray(), araiccf.getCF() / max(araiccf.getCF()), 'y')
plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b--')
plt.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([hospick.getpick(), hospick.getpick()], [-1.3, 1.3], 'r', linewidth=2)
plt.plot([hospick.getpick() - 0.5, hospick.getpick() + 0.5], [1.3, 1.3], 'r')
plt.plot([hospick.getpick() - 0.5, hospick.getpick() + 0.5], [-1.3, -1.3], 'r')
plt.plot([lpickhos, lpickhos], [-1.1, 1.1], 'r--')
plt.plot([epickhos, epickhos], [-1.1, 1.1], 'r--')
plt.plot([aicarzpick.getpick(), aicarzpick.getpick()], [-1.2, 1.2], 'y', linewidth=2)
plt.plot([aicarzpick.getpick() - 0.5, aicarzpick.getpick() + 0.5], [1.2, 1.2], 'y')
plt.plot([aicarzpick.getpick() - 0.5, aicarzpick.getpick() + 0.5], [-1.2, -1.2], 'y')
plt.plot([arzpick.getpick(), arzpick.getpick()], [-1.4, 1.4], 'g', linewidth=2)
plt.plot([arzpick.getpick() - 0.5, arzpick.getpick() + 0.5], [1.4, 1.4], 'g')
plt.plot([arzpick.getpick() - 0.5, arzpick.getpick() + 0.5], [-1.4, -1.4], 'g')
plt.plot([lpickarz, lpickarz], [-1.2, 1.2], 'g--')
plt.plot([epickarz, epickarz], [-1.2, 1.2], 'g--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station,
tr.stats.channel, aicpick.getSNR(),
aicpick.getSlope()))
plt.suptitle(tr.stats.starttime)
plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
# plot horizontal traces
plt.figure(2)
plt.subplot(2, 1, 1)
tsteph = tpredh / 4
th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth + tpredh
p21, = plt.plot(th1data, trH1_filt.data / max(trH1_filt.data), 'k')
p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF() / max(arhcf.getCF()), 'r')
p23, = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF() / max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'r')
plt.plot([lpickarh, lpickarh], [-0.8, 0.8], 'r--')
plt.plot([epickarh, epickarh], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + pickerrarh, arhpick.getpick() + pickerrarh], [-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - pickerrarh, arhpick.getpick() - pickerrarh], [-0.2, 0.2], 'r--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.subplot(2, 1, 2)
plt.plot(th2data, trH2_filt.data / max(trH2_filt.data), 'k')
plt.plot(arhcf.getTimeArray(), arhcf.getCF() / max(arhcf.getCF()), 'r')
plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF() / max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'r')
plt.plot([lpickarh, lpickarh], [-0.8, 0.8], 'r--')
plt.plot([epickarh, epickarh], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + pickerrarh, arhpick.getpick() + pickerrarh], [-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - pickerrarh, arhpick.getpick() - pickerrarh], [-0.2, 0.2], 'r--')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
# plot 3-component window
plt.figure(3)
plt.subplot(3, 1, 1)
p31, = plt.plot(tdata, tr_filt.data / max(tr_filt.data), 'k')
p32, = plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([tr.stats.station, tr.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
plt.subplot(3, 1, 2)
plt.plot(th1data, trH1_filt.data / max(trH1_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.subplot(3, 1, 3)
plt.plot(th2data, trH2_filt.data / max(trH2_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.yticks([])
plt.ylabel('Normalized Counts')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.xlabel('Time [s]')
plt.show()
raw_input()
plt.close()
parser = argparse.ArgumentParser()
parser.add_argument('--project', type=str, help='project name (e.g. Insheim)')
parser.add_argument('--database', type=str, help='event data base (e.g. 2014.09_Insheim)')
parser.add_argument('--event', type=str, help='event ID (e.g. e0010.015.14)')
parser.add_argument('--iplot', help='anything, if set, figure occurs')
parser.add_argument('--station', type=str, help='Station ID (e.g. INS3) (optional)')
args = parser.parse_args()
run_makeCF(args.project, args.database, args.event, args.iplot, args.station)