def main():
stations = 'PB03 PB04'
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-01-01')
t1 = UTC('2007-11-10')
t2 = UTC()
t2 = UTC('2007-11-20')
shift = 500
correlations = get_correlations(stations, components, stations2, only_cross=True)
method = 'filter4-6_water_env2_whitening_1bit'
# method = 'filter0.01-1_1bit_whitening0.01'
# method = 'filter0.005_rm20'
# method = 'filter0.005_1bit'
data = IPOC(xcorr_append='/Tocopilla/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
# prepare(data, stations.split(), t1, t2, component=components,
# filter=(4, 6), downsample=None,
# eventremoval='waterlevel_env2', param_removal=(10, 0),
# #whitening=True,
# normalize='1bit', param_norm=None)
correlations = get_correlations(stations, components, stations2, only_auto=True)
# noisexcorr(data, correlations, t1, t2, shift)
plotXcorrs(data, correlations, t1, t2, start= -150, end=150, plot_overview=True, plot_years=False, use_dlognorm=True,
plot_stack=True, plot_psd=True, add_to_title=method, show=True)
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 HMBCX MNMCX PATCX PSGCX'
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-07-01')
t2 = UTC('2008-12-31')
shift = 500
correlations = get_correlations(stations, components)
method = 'FINAL_filter0.005-10_1bit_Tocopilla'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
pool = Pool()
prepare(data, stations.split(), t1, t2, component=components,
filter=(0.005, 10, 2, True), downsample=20,
whitening=False,
normalize='1bit', param_norm=None,
pool=pool)
noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
pool.close()
pool.join()
stack(data, correlations, dt=10 * 24 * 3600, shift=5 * 24 * 3600)
stack(data, correlations, dt= -1)
filters = None
#filters = getFilters((0.005, 0.01, 0.1, 1, 5, 10), zerophase=True, corners=2)
# plotXcorrs(data, correlations, t1, t2, start=None, end=None, filters=filters, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=True, add_to_title='', downsample=None)
plotXcorrs(data, correlations, t1=None, t2=None, start=None, end=None, filters=filters, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=True, add_to_title='', downsample=None, stack=('10days', '5days'))
def main():
stations = 'PB01 PB02 PB03 PB04 PB04 PB05 PB06'
stations2 = 'PB01 PB02 PB03 PB04 PB04 PB05 PB06 PB07 PB08 HMBCX PATCX'
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2007-09-01')
t2 = UTC('2008-01-31')
shift = 200
correlations = get_correlations(stations, components, stations2)
# method = 'filter0.01-1_1bit'
# method = 'filter0.01-1_1bit_whitening0.01'
# method = 'filter2-20_1bit'
# method = 'filter0.005_1bit'
# period = 'day'
#
# data = IPOC(xcorr_append='/Tocopilla/' + method, use_local_LVC=True)
# data.setXLogger('_' + method)
# prepare(data, stations.split(), t1, t2, filter=(0.005, 1.), downsample=5, whitening=True,
# component=components, normalize='1bit', norm_param=None)
# noisexcorr(data, correlations, t1, t2, shift_sec=shift, period=period)
# correlations = (('PB03Z', 'PB04Z'),)
# data.x_plot_day = data.x_res + '/plots2/%s_day_%s'
# plotXcorrs(data, correlations, t1, t2, start=9, end=15, plot_overview=True, filter=(2, None, 2, True), stack_lim=(-0.01, 0.01), downsample=None, plot_years=False,
# plot_stack=True, plot_psd=True, add_to_title=method + '_filter2_9-15', add_to_file='_filter2_9-15.png', show=False)
method = 'filter4-6_1bit'
period = 'day'
data = IPOC(xcorr_append='/Tocopilla/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
# prepare(data, stations.split(), t1, t2, filter=(4, 6), downsample=None, whitening=None,
# component=components, normalize='1bit', norm_param=None)
# noisexcorr(data, correlations, t1, t2, shift_sec=shift, period=period)
plotXcorrs(data,
correlations,
t1,
t2,
start=-50,
end=50,
plot_overview=True,
filter=None,
stack_lim=(-0.1, 0.1),
plot_years=False,
plot_stack=True,
plot_psd=False,
add_to_title=method + '_wodlognorm_50s',
add_to_file='_wodlognorm_50s.png',
show=True,
landscape=True,
use_dlognorm=False)
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 HMBCX MNMCX PATCX PSGCX LVC'
stations = 'PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16'
stations = 'PB02 PB03 PB04 PB05 HMBCX MNMCX PSGCX'
stations = 'PATCX'
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2007-01-01')
#t1 = UTC('2007-12-01')
#t2 = UTC('2008-12-31')
#t2 = UTC('2012-10-01')
t2 = UTC('2011-12-31')
#t2 = UTC('2007-02-03')
# t1 = UTC('2009-05-01')
# t2 = UTC('2009-05-03')
shift = 100
shift = 60
correlations = get_correlations(stations, components, stations2, only_auto=True)
#correlations = get_correlations(stations, components, stations2)
print correlations
method = 'FINAL_filter4-6_1bit_auto'
method = 'FINAL_filter4-6_1bit_auto_3C'
method = 'FINAL_filter4-6_1bit_auto_hour2'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
# pool = Pool()
pool = None
prepare(data, stations.split(), t1, t2, component=components,
filter=(4, 6, 2, True), downsample=50,
eventremoval='waterlevel_env2', param_removal=(10, 0),
whitening=False,
normalize='1bit', param_norm=None,
pool=pool, discard=0.1 * 24 * 3600, freq_domain=False, trim='day')
noisexcorrf(data, correlations, t1, t2, shift, period=3600, pool=pool, overlap=1800)
# noisexcorrf(data, correlations, t1, t2, shift, period=5 * 60, pool=pool,
# max_preload=1000)
# pool.close()
# pool.join()
# plotXcorrs(data, correlations, t1, t2, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=False, add_to_title='', downsample=None)
plotXcorrs(data, correlations, t1, t2, start= -20, end=20, plot_overview=True, plot_years=True, use_dlognorm=False,
plot_stack=True, plot_psd=False, add_to_title='', downsample=None, ext='_hg.png', vmax=0.1,
period=3600)
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 HMBCX MNMCX PATCX PSGCX'
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-07-01')
t2 = UTC('2008-12-31')
shift = 500
correlations = get_correlations(stations, components)
method = 'FINAL_filter0.005-10_1bit_Tocopilla'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
pool = Pool()
prepare(data,
stations.split(),
t1,
t2,
component=components,
filter=(0.005, 10, 2, True),
downsample=20,
whitening=False,
normalize='1bit',
param_norm=None,
pool=pool)
noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
pool.close()
pool.join()
stack(data, correlations, dt=10 * 24 * 3600, shift=5 * 24 * 3600)
stack(data, correlations, dt=-1)
filters = None
#filters = getFilters((0.005, 0.01, 0.1, 1, 5, 10), zerophase=True, corners=2)
# plotXcorrs(data, correlations, t1, t2, start=None, end=None, filters=filters, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=True, add_to_title='', downsample=None)
plotXcorrs(data,
correlations,
t1=None,
t2=None,
start=None,
end=None,
filters=filters,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=True,
add_to_title='',
downsample=None,
stack=('10days', '5days'))
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 HMBCX MNMCX PATCX PSGCX LVC'
#stations = 'PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16'
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-02-01')
t2 = UTC('2012-10-01')
shift = 100
correlations = get_correlations(stations,
components,
stations2,
only_auto=True)
method = 'FINAL_filter1-3_1bit_auto'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
# pool = Pool()
# prepare(data, stations.split(), t1, t2, component=components,
# filter=(1, 3, 2, True), downsample=20,
# eventremoval='waterlevel_env2', param_removal=(10, 0),
# whitening=False,
# normalize='1bit', param_norm=None,
# pool=pool)
# noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
# pool.close()
# pool.join()
# plotXcorrs(data, correlations, t1, t2, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=False, add_to_title='', downsample=None)
plt.rc('font', size=16)
plotXcorrs(data,
correlations,
t1,
t2,
start=0,
end=20,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=False,
downsample=None,
ext='_hg_dis.pdf',
vmax=0.1,
ylabel=None,
add_to_title='1-3Hz')
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 HMBCX MNMCX PATCX PSGCX LVC'
stations = 'PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16'
stations = 'PATCX'
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2007-10-01')
t2 = UTC('2007-11-30')
#t2 = UTC('2012-10-01')
#t2 = UTC('2011-12-31')
# t1 = UTC('2009-05-01')
# t2 = UTC('2009-05-03')
shift = 100
shift = 60
#correlations = get_correlations(stations, components, stations2, only_auto=True)
correlations = get_correlations(stations, components, stations2)
print correlations
method = 'zerotest_nozero'
#method = 'FINAL_filter4-6_1bit_auto_3C'
#method = 'FINAL_filter3-5'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
pool = Pool()
prepare(data, stations.split(), t1, t2, component=components,
filter=(4, 6, 2, True), downsample=50,
#eventremoval='waterlevel_env2', param_removal=(10, 0),
eventremoval=None, param_removal=None,
whitening=False,
normalize='1bit', param_norm=None,
pool=pool)
noisexcorrf(data, correlations, t1, t2, shift, period=24 * 3600, pool=pool)
# noisexcorrf(data, correlations, t1, t2, shift, period=5 * 60, pool=pool,
# max_preload=1000)
pool.close()
pool.join()
# plotXcorrs(data, correlations, t1, t2, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=False, add_to_title='', downsample=None)
#plt.rc('font', size=16)
plotXcorrs(data, correlations, t1, t2, start=-20, end=20, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=False, downsample=None, ext='_hg0.02_dis.pdf', vmax=0.02,
add_to_title='4-6Hz', ylabel=None)
def main():
stations = 'PB03 PB04'
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-01-01')
t1 = UTC('2007-11-10')
t2 = UTC()
t2 = UTC('2007-11-20')
shift = 500
correlations = get_correlations(stations,
components,
stations2,
only_cross=True)
method = 'filter4-6_water_env2_whitening_1bit'
# method = 'filter0.01-1_1bit_whitening0.01'
# method = 'filter0.005_rm20'
# method = 'filter0.005_1bit'
data = IPOC(xcorr_append='/Tocopilla/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
# prepare(data, stations.split(), t1, t2, component=components,
# filter=(4, 6), downsample=None,
# eventremoval='waterlevel_env2', param_removal=(10, 0),
# #whitening=True,
# normalize='1bit', param_norm=None)
correlations = get_correlations(stations,
components,
stations2,
only_auto=True)
# noisexcorr(data, correlations, t1, t2, shift)
plotXcorrs(data,
correlations,
t1,
t2,
start=-150,
end=150,
plot_overview=True,
plot_years=False,
use_dlognorm=True,
plot_stack=True,
plot_psd=True,
add_to_title=method,
show=True)
def main():
stations = 'PB01 PB02 PB03 PB04 PB04 PB05 PB06'
stations2 = 'PB01 PB02 PB03 PB04 PB04 PB05 PB06 PB07 PB08 HMBCX PATCX'
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2007-09-01')
t2 = UTC('2008-01-31')
shift = 200
correlations = get_correlations(stations, components, stations2)
# method = 'filter0.01-1_1bit'
# method = 'filter0.01-1_1bit_whitening0.01'
# method = 'filter2-20_1bit'
# method = 'filter0.005_1bit'
# period = 'day'
#
# data = IPOC(xcorr_append='/Tocopilla/' + method, use_local_LVC=True)
# data.setXLogger('_' + method)
# prepare(data, stations.split(), t1, t2, filter=(0.005, 1.), downsample=5, whitening=True,
# component=components, normalize='1bit', norm_param=None)
# noisexcorr(data, correlations, t1, t2, shift_sec=shift, period=period)
# correlations = (('PB03Z', 'PB04Z'),)
# data.x_plot_day = data.x_res + '/plots2/%s_day_%s'
# plotXcorrs(data, correlations, t1, t2, start=9, end=15, plot_overview=True, filter=(2, None, 2, True), stack_lim=(-0.01, 0.01), downsample=None, plot_years=False,
# plot_stack=True, plot_psd=True, add_to_title=method + '_filter2_9-15', add_to_file='_filter2_9-15.png', show=False)
method = 'filter4-6_1bit'
period = 'day'
data = IPOC(xcorr_append='/Tocopilla/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
# prepare(data, stations.split(), t1, t2, filter=(4, 6), downsample=None, whitening=None,
# component=components, normalize='1bit', norm_param=None)
# noisexcorr(data, correlations, t1, t2, shift_sec=shift, period=period)
plotXcorrs(data, correlations, t1, t2, start= -50, end=50, plot_overview=True, filter=None, stack_lim=(-0.1, 0.1), plot_years=False,
plot_stack=True, plot_psd=False, add_to_title=method + '_wodlognorm_50s', add_to_file='_wodlognorm_50s.png', show=True, landscape=True, use_dlognorm=False)
def main():
data = IPOC(xcorr_append='/tests/1bit_filter0.1-1', use_local_LVC=True)
data.setXLogger('_1bit')
stations = 'PB01 PB03'
stations2 = 'PB03'
components = 'Z'
t1 = UTC('2010-01-01')
t2 = UTC('2010-12-31')
shift = 500
prepare(data, stations.split(), t1, t2, filter=(0.1, 1.), downsample=10,
component=components, normalize='1bit', param_norm=None,
use_floating_stream=True)
correlations = get_correlations(stations, components, stations2)
xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data, correlations, t1, t2)
def main():
data = IPOC(xcorr_append='/tests/1bit_filter0.01', use_local_LVC=True)
data.setXLogger('_1bit0.01Hz')
stations = 'PB01 PB03'
stations2 = 'PB03'
components = 'Z'
t1 = UTC('2010-01-01')
t2 = UTC('2010-01-02')
shift = 500
# prepare(data, stations.split(), t1, t2, filter=(0.01, None), downsample=None,
# component=components, normalize='1bit', norm_param=None,
# use_floating_stream=True)
correlations = get_correlations(stations, components, stations2)
# xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data, correlations, t1, t2, plot_overview=False, plot_stack=True, plot_psd=True)
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16 HMBCX MNMCX PATCX PSGCX LVC'
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-02-01')
t2 = UTC('2012-10-01')
shift = 500
correlations = get_correlations(stations, components, stations2, only_auto=True)
method = 'FINAL_filter0.01-0.5_1bit_auto'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
# pool = Pool()
# prepare(data, stations.split(), t1, t2, component=components,
# filter=(0.01, 0.5, 2, True), downsample=5,
# eventremoval='waterlevel_env2', param_removal=(10, 0),
# whitening=False,
# normalize='1bit', param_norm=None,
# pool=pool)
# noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
# pool.close()
# pool.join()
# plotXcorrs(data, correlations, t1, t2, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=False, add_to_title='', downsample=None)
plotXcorrs(data, correlations, t1, t2, start=0, end=200, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=False, add_to_title='', downsample=None, ext='_hg.png', vmax=0.1)
# stack(data, correlations, dt= -1)
# stack(data, correlations, dt=10 * 24 * 3600, shift=2 * 24 * 3600)
# plotXcorrs(data, correlations, t1=None, t2=None, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=False, add_to_title='', downsample=None,
# stack=('10days', '2days'))
plotXcorrs(data, correlations, t1=None, t2=None, start=0, end=200, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=False, add_to_title='', downsample=None,
stack=('10days', '2days'), ext='_hg.png', vmax=0.1)
def main():
data = IPOC(xcorr_append='/tests/1bit_filter0.01', use_local_LVC=True)
data.setXLogger('_1bit0.01Hz')
stations = 'PB01 PB03'
stations2 = 'PB03'
components = 'Z'
t1 = UTC('2010-01-01')
t2 = UTC('2010-01-02')
shift = 500
# prepare(data, stations.split(), t1, t2, filter=(0.01, None), downsample=None,
# component=components, normalize='1bit', norm_param=None,
# use_floating_stream=True)
correlations = get_correlations(stations, components, stations2)
# xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data,
correlations,
t1,
t2,
plot_overview=False,
plot_stack=True,
plot_psd=True)
def main():
#stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16 HMBCX MNMCX PATCX PSGCX LVC TAIQ'
stations = 'PB01 PB02 PB03 PB04 PB05'
stations2 = None
components = 'Z'
# TOcopilla earthquake:
#t_Toco=UTC('2007-11-14 15:14:00')
t1 = UTC('2006-01-01')
#t2 = UTC('2011-09-01')
#t1 = UTC('2007-01-01')
#t2 = UTC('2009-01-01')
t2 = UTC('2012-01-01')
shift = 500
correlations = get_correlations(stations, components, stations2, only_cross=True)
# method = 'FINAL_filter0.005-5_1bit_whitening_2011+2012'
# method = 'filter0.01-1_1bit_whitening0.01'
# method = 'filter0.005_rm20'
# method = 'filter0.005_1bit'
method = 'filter0.01-1_water_env2_whitening_1bit_fft'
data = IPOC(xcorr_append='/Tocopilla/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
# pool = Pool()
# prepare(data, stations.split(), t1, t2, component=components,
# filter=(0.005, 5, 2, True), downsample=20,
## filter=(1, 10), downsample=None,
## eventremoval=None, #'waterlevel_env2', param_removal=(10, 0),
# whitening=True,
# use_this_filter_after_whitening=(0.005, 5, 2),
# normalize='1bit', param_norm=None,
# pool=pool)
# noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
# pool.close()
# pool.join()
#
# stack(data, correlations, dt=10 * 24 * 3600, shift=5 * 24 * 3600)
# stack(data, correlations, dt= -1)
t1p, t2p = t1, t2
# t1p, t2p = None, None
filters = None
filters = getFilters((0.025, 0.05, 0.1, 0.25, 0.5, 1))
plotXcorrs(data, correlations, t1=t1p, t2=t2p, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=False, add_to_title='', downsample=None, filters=filters, filter_now=False)
plotXcorrs(data, correlations, t1=t1p, t2=t2p, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=False, add_to_title='', downsample=None, stack=('10days', 'day'), filters=filters, filter_now=False)
plotXcorrs(data, correlations, t1=t1p, t2=t2p, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=False, add_to_title='', downsample=None, stack=('50days', '5days'), filters=filters, filter_now=False)
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 HMBCX MNMCX PATCX PSGCX LVC'
#stations = 'PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16'
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-02-01')
t2 = UTC('2012-10-01')
shift = 100
correlations = get_correlations(stations, components, stations2, only_auto=True)
method = 'FINAL_filter1-3_1bit_auto'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
# pool = Pool()
# prepare(data, stations.split(), t1, t2, component=components,
# filter=(1, 3, 2, True), downsample=20,
# eventremoval='waterlevel_env2', param_removal=(10, 0),
# whitening=False,
# normalize='1bit', param_norm=None,
# pool=pool)
# noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
# pool.close()
# pool.join()
# plotXcorrs(data, correlations, t1, t2, start=None, end=None, plot_overview=True, plot_years=False, use_dlognorm=False,
# plot_stack=True, plot_psd=False, add_to_title='', downsample=None)
plt.rc('font', size=16)
plotXcorrs(data, correlations, t1, t2, start=0, end=20, plot_overview=True, plot_years=False, use_dlognorm=False,
plot_stack=True, plot_psd=False, downsample=None, ext='_hg_dis.pdf', vmax=0.1, ylabel=None,
add_to_title='1-3Hz')
def main():
stations = 'PB01 PB03'
stations2 = 'PB03'
components = 'Z'
t1 = UTC('2010-01-01')
t2 = UTC('2010-12-31')
shift = 500
correlations = get_correlations(stations, components, stations2)
method = 'filter0.1-1_1bit_whitening0.01'
data = IPOC(xcorr_append='/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
prepare(data, stations.split(), t1, t2, filter=(0.1, 1), downsample=10, whitening=0.01,
component=components, normalize='1bit', param_norm=None,
use_floating_stream=True)
xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data, correlations, t1, t2, plot_overview=False, plot_stack=True, plot_psd=True, add_to_title=method)
method = 'filter0.1-1_1bit_whitening0.001'
data = IPOC(xcorr_append='/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
prepare(data, stations.split(), t1, t2, filter=(0.1, 1), downsample=10, whitening=0.001,
component=components, normalize='1bit', param_norm=None,
use_floating_stream=True)
xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data, correlations, t1, t2, plot_overview=False, plot_stack=True, plot_psd=True, add_to_title=method)
method = 'filter0.1-1_1bit_whitening0.1'
data = IPOC(xcorr_append='/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
prepare(data, stations.split(), t1, t2, filter=(0.1, 1), downsample=10, whitening=0.1,
component=components, normalize='1bit', param_norm=None,
use_floating_stream=True)
xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data, correlations, t1, t2, plot_overview=False, plot_stack=True, plot_psd=True, add_to_title=method)
def main():
stations = 'PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16 HMBCX MNMCX PATCX PSGCX LVC'
# TAIQ
stations2 = None
components = 'Z'
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC('2006-01-01')
#t2 = UTC('2011-09-01')
#t1 = UTC('2007-01-01')
#t2 = UTC('2009-01-01')
t2 = UTC('2012-09-01')
shift = 500
correlations = get_correlations(stations, components, stations2)
method = 'FINAL_filter0.01-1_1bit'
data = IPOC(xcorr_append='/' + method, use_local_LVC=False)
data.setXLogger('_' + method)
pool = Pool()
prepare(data,
stations.split(),
t1,
t2,
component=components,
filter=(0.01, 1, 2, True),
downsample=10,
eventremoval='waterlevel_env2',
param_removal=(10, 0),
whitening=False,
normalize='1bit',
param_norm=None,
pool=pool)
noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
pool.close()
pool.join()
stack(data, correlations, dt=10 * 24 * 3600, shift=5 * 24 * 3600)
stack(data, correlations, dt=50 * 24 * 3600, shift=5 * 24 * 3600)
stack(data, correlations, dt=-1)
plotXcorrs(data,
correlations,
t1,
t2,
start=None,
end=None,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=False,
add_to_title='',
downsample=None)
plotXcorrs(data,
correlations,
t1=None,
t2=None,
start=None,
end=None,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=False,
add_to_title='',
downsample=None,
stack=('10days', '5days'))
plotXcorrs(data,
correlations,
t1=None,
t2=None,
start=None,
end=None,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=False,
add_to_title='',
downsample=None,
stack=('50days', '5days'))
def main():
stations = 'PB01 PB03'
stations2 = 'PB03'
components = 'Z'
t1 = UTC('2010-01-01')
t2 = UTC('2010-12-31')
shift = 500
correlations = get_correlations(stations, components, stations2)
method = 'filter0.1-1_1bit_whitening0.01'
data = IPOC(xcorr_append='/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
prepare(data,
stations.split(),
t1,
t2,
filter=(0.1, 1),
downsample=10,
whitening=0.01,
component=components,
normalize='1bit',
param_norm=None,
use_floating_stream=True)
xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data,
correlations,
t1,
t2,
plot_overview=False,
plot_stack=True,
plot_psd=True,
add_to_title=method)
method = 'filter0.1-1_1bit_whitening0.001'
data = IPOC(xcorr_append='/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
prepare(data,
stations.split(),
t1,
t2,
filter=(0.1, 1),
downsample=10,
whitening=0.001,
component=components,
normalize='1bit',
param_norm=None,
use_floating_stream=True)
xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data,
correlations,
t1,
t2,
plot_overview=False,
plot_stack=True,
plot_psd=True,
add_to_title=method)
method = 'filter0.1-1_1bit_whitening0.1'
data = IPOC(xcorr_append='/tests/' + method, use_local_LVC=True)
data.setXLogger('_' + method)
prepare(data,
stations.split(),
t1,
t2,
filter=(0.1, 1),
downsample=10,
whitening=0.1,
component=components,
normalize='1bit',
param_norm=None,
use_floating_stream=True)
xcorr_day(data, correlations, t1, t2, shift, use_floating_stream=True)
plotXcorrs(data,
correlations,
t1,
t2,
plot_overview=False,
plot_stack=True,
plot_psd=True,
add_to_title=method)
def main():
stations = (
"PB01 PB02 PB03 PB04 PB05 PB06 PB07 PB08 PB09 PB10 PB11 PB12 PB13 PB14 PB15 PB16 HMBCX MNMCX PATCX PSGCX LVC"
)
# TAIQ
stations2 = None
components = "Z"
# TOcopilla earthquake: 2007-11-14 15:14
t1 = UTC("2006-01-01")
# t2 = UTC('2011-09-01')
# t1 = UTC('2007-01-01')
# t2 = UTC('2009-01-01')
t2 = UTC("2012-09-01")
shift = 500
correlations = get_correlations(stations, components, stations2)
method = "FINAL_filter0.01-1_1bit"
data = IPOC(xcorr_append="/" + method, use_local_LVC=False)
data.setXLogger("_" + method)
pool = Pool()
prepare(
data,
stations.split(),
t1,
t2,
component=components,
filter=(0.01, 1, 2, True),
downsample=10,
eventremoval="waterlevel_env2",
param_removal=(10, 0),
whitening=False,
normalize="1bit",
param_norm=None,
pool=pool,
)
noisexcorrf(data, correlations, t1, t2, shift, pool=pool)
pool.close()
pool.join()
stack(data, correlations, dt=10 * 24 * 3600, shift=5 * 24 * 3600)
stack(data, correlations, dt=50 * 24 * 3600, shift=5 * 24 * 3600)
stack(data, correlations, dt=-1)
plotXcorrs(
data,
correlations,
t1,
t2,
start=None,
end=None,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=False,
add_to_title="",
downsample=None,
)
plotXcorrs(
data,
correlations,
t1=None,
t2=None,
start=None,
end=None,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=False,
add_to_title="",
downsample=None,
stack=("10days", "5days"),
)
plotXcorrs(
data,
correlations,
t1=None,
t2=None,
start=None,
end=None,
plot_overview=True,
plot_years=False,
use_dlognorm=False,
plot_stack=True,
plot_psd=False,
add_to_title="",
downsample=None,
stack=("50days", "5days"),
)