def test_gps_utc_offset(self):
for t_utc_0 in [x[0] for x in util.read_leap_seconds2()]:
t_utc_0 = float(t_utc_0)
ts_utc = num.linspace(
t_utc_0 - 2.0, t_utc_0 + 2.0, 17)
for t_utc in ts_utc:
t_gps = t_utc + util.gps_utc_offset(t_utc)
t_utc2 = t_gps + util.utc_gps_offset(t_gps)
self.assertEqual(util.tts(t_utc), util.tts(t_utc2))
ts_gps = num.linspace(
ts_utc[0] + util.gps_utc_offset(ts_utc[0]),
ts_utc[-1] + util.gps_utc_offset(ts_utc[-1]), 17 + 4)
t_utc_wrapped = []
for t_gps in ts_gps:
t_utc = t_gps + util.utc_gps_offset(t_gps)
t_utc_wrapped.append(t_utc - t_utc_0)
num.testing.assert_almost_equal(
t_utc_wrapped,
num.concatenate((
num.linspace(-2.0, 0.75, 12),
num.linspace(0.0, 2.0, 9))))
def search_catalog(date, min_magnitude, dayrange=1.):
"""
Search the gcmt catalog for the specified date (+- 1 day), filtering the
events with given magnitude threshold.
Parameters
----------
date : str
'YYYY-MM-DD', date of the event
min_magnitude : float
approximate minimum Mw of the event
dayrange : float
temporal search interval [days] around date
Returns
-------
event : :class:`pyrocko.model.Event`
"""
gcmt = catalog.GlobalCMT()
time_s = util.stt(date + ' ' + seconds_str)
d1 = time_s - (dayrange * (sphr * hrpd))
d2 = time_s + (dayrange * (sphr * hrpd))
logger.info('Getting relevant events from the gCMT catalog for the dates:'
'%s - %s \n' % (util.tts(d1), util.tts(d2)))
events = gcmt.get_events((d1, d2), magmin=min_magnitude)
if len(events) < 1:
logger.warn('Found no event information in the gCMT catalog.')
event = None
if len(events) > 1:
logger.info(
'More than one event from that date with specified magnitude '
'found! Please copy the relevant event information to the '
'configuration file!')
for event in events:
print event
event = events[0]
elif len(events) == 1:
event = events[0]
return event
def get_time_format_eq(time):
time = util.tts(time)
time_year = time[0:4]
time_month = time[5:7]
time_day = time[8:10]
time_hour = time[11:13]
time_minute = time[14:16]
time_seconds = time[17:19]
date = time_year + time_month + time_day + "T" + time_hour + time_minute + time_seconds + "Z"
return date
def benchmark_stt_tts(self):
for x in range(2):
if x == 1:
util.util_ext = None
t = util.str_to_time('1999-03-20 20:10:10')
tt1 = time.time()
for i in range(10000):
s = util.tts(t)
util.stt(s)
tt2 = time.time()
print(tt2 - tt1)
def benchmark_stt_tts(self):
for x in xrange(2):
if x == 1:
util.util_ext = None
t = util.str_to_time('1999-03-20 20:10:10')
tt1 = time.time()
for i in xrange(10000):
s = util.tts(t)
t2 = util.stt(s)
tt2 = time.time()
print tt2 - tt1
def associate(path,
tmin,
tmax,
minlat=49.1379,
maxlat=49.1879,
minlon=8.1223,
maxlon=8.1723,
channels=["EH" + "[ZNE]"],
client_list=["BGR"],
iter=None,
pair_n=3,
moving_window=8):
import shutil
import os
from silvertine.detector.utils.associator import run_associator
if iter is None:
out_basepath = os.path.join(path, 'detections')
out_dir = os.path.join(path, 'asociation')
else:
out_basepath = os.path.join(path, 'detections_%s_%s' % (tmin, tmax))
out_dir = os.path.join(path, 'asociation_%s_%s' % (tmin, tmax))
try:
shutil.rmtree(out_dir)
except Exception:
pass
os.makedirs(out_dir)
if tmin is not None:
tmin = util.tts(tmin)
if tmax is not None:
tmax = util.tts(tmax)
run_associator(input_dir=out_basepath,
start_time=tmin,
end_time=tmax,
moving_window=moving_window,
pair_n=pair_n,
output_dir=out_dir,
consider_combination=False)
def test_gps_utc_offset(self):
for t_utc_0 in [x[0] for x in util.read_leap_seconds2()]:
t_utc_0 = float(t_utc_0)
ts_utc = num.linspace(t_utc_0 - 2.0, t_utc_0 + 2.0, 17)
for t_utc in ts_utc:
t_gps = t_utc + util.gps_utc_offset(t_utc)
t_utc2 = t_gps + util.utc_gps_offset(t_gps)
self.assertEqual(util.tts(t_utc), util.tts(t_utc2))
ts_gps = num.linspace(ts_utc[0] + util.gps_utc_offset(ts_utc[0]),
ts_utc[-1] + util.gps_utc_offset(ts_utc[-1]),
17 + 4)
t_utc_wrapped = []
for t_gps in ts_gps:
t_utc = t_gps + util.utc_gps_offset(t_gps)
t_utc_wrapped.append(t_utc - t_utc_0)
num.testing.assert_almost_equal(
t_utc_wrapped,
num.concatenate((num.linspace(-2.0, 0.75,
12), num.linspace(0.0, 2.0, 9))))
def call(self):
self.cleanup()
viewer = self.get_viewer()
vtmin, vtmax = viewer.get_time_range()
pile = self.get_pile()
traces = list(
pile.chopper(tmin=vtmin,
tmax=vtmax,
trace_selector=viewer.trace_selector))
event, _ = self.get_active_event_and_stations()
traces = [tr for trs in traces for tr in trs]
stations = []
for tr in traces:
if tr.nslc_id[:2] in viewer.stations.keys():
stations.append(viewer.get_station(viewer.station_key(tr)))
distances = [ortho.distance_accurate50m(event, s) for s in stations]
distances = [d / 1000. for d in distances]
maxd = max(distances)
mind = min(distances)
distances = dict(zip([s.nsl() for s in stations], distances))
matching_traces = [
x for x in traces
if util.match_nslc(self.get_station_patterns(stations), x.nslc_id)
]
if self.add_markers:
markers = self.get_markers()
markers = [
m for m in markers
if m.tmax <= vtmax and m.tmin >= vtmin and m.selected
]
markers = dict(zip([tuple(m.nslc_ids) for m in markers], markers))
if self.fig is None or self.fframe.closed is True or not self._live_update:
self.fframe = self.pylab(get='figure_frame')
self.fig = self.fframe.gcf()
if self._live_update:
self.fig.clf()
ymin = mind - 0.06 * (maxd - mind)
ymax = maxd + 0.06 * (maxd - mind)
ax = self.fig.add_subplot(111)
xmin = 9E9
xmax = -xmin
texts = []
manual_scale = 0.1 * (maxd - mind) * self.yscale
if self.ampl_scaler == 'total min/max':
max_trace = max(matching_traces,
key=lambda x: max(abs(x.get_ydata())))
tr_maxy = max(abs(max_trace.get_ydata()))
ampl_scale = float(tr_maxy)
for tr in matching_traces:
if viewer.highpass:
tr.highpass(4, viewer.highpass)
if viewer.lowpass:
tr.lowpass(4, viewer.lowpass)
if tr.nslc_id[:3] not in distances.keys():
continue
if self.t_red:
red = distances[tr.nslc_id[:3]] / self.t_red
else:
red = 0.
y_pos = distances[tr.nslc_id[:3]]
xdata = tr.get_xdata() - red - event.time
xmin = min(xmin, min(xdata))
xmax = max(xmax, max(xdata))
tr_ydata = tr.get_ydata()
if self.ampl_scaler == 'trace min/max':
ampl_scale = float(max(abs(tr_ydata)))
elif self.ampl_scaler == 'standard deviation':
ampl_scale = float(num.std(tr_ydata))
ydata = (tr_ydata / ampl_scale * manual_scale) + y_pos
ax.plot(xdata, ydata, c='black', linewidth=0.2)
if self.fill_between:
ax.fill_between(xdata,
y_pos,
ydata,
where=ydata > y_pos,
color='black',
alpha=0.5)
texts.append(
ax.text(xmax,
y_pos,
'%s.%s.%s.%s' % tr.nslc_id,
horizontalalignment='right',
fontsize=6.))
if self.add_markers:
for ids, m in markers.items():
if m.match_nslc(tr.nslc_id) or ids == ():
c = m.select_color(m.color_b)
c = [ci / 255. for ci in c]
t = m.tmin
x = [t - red - event.time, t - red - event.time]
y = [
y_pos - (maxd - mind) * 0.025,
y_pos + (maxd - mind) * 0.025
]
ax.plot(x, y, linewidth=1, color=c)
label = m.get_label()
if not label:
label = ''
ax.text(x[1] - x[1] * 0.005,
y[1],
label,
color=c,
fontsize=6,
verticalalignment='top',
horizontalalignment='right')
for txt in texts:
txt.set_x(xmax)
vred_str = '= '+str(round(self.t_red, 2)) + 'km/s' if self.t_red \
else 'off'
ax.text(0.5,
0.01,
'time window: %s - %s | Reduction velocity %s' %
(util.tts(vtmin), util.tts(vtmax), vred_str),
verticalalignment='bottom',
horizontalalignment='center',
transform=self.fig.transFigure)
ax.set_ylim([ymin, ymax])
ax.set_xlim([xmin, xmax])
ax.set_ylabel('Distance [km]')
ax.set_xlabel('(red.) Time [s]')
self.fig.canvas.draw()
def main():
parser = OptionParser(usage=usage, description=description)
parser.add_option('--force',
dest='force',
action='store_true',
default=False,
help='allow recreation of output <directory>')
parser.add_option('--debug',
dest='debug',
action='store_true',
default=False,
help='print debugging information to stderr')
parser.add_option('--dry-run',
dest='dry_run',
action='store_true',
default=False,
help='show available stations/channels and exit '
'(do not download waveforms)')
parser.add_option('--continue',
dest='continue_',
action='store_true',
default=False,
help='continue download after a accident')
parser.add_option('--local-data',
dest='local_data',
action='append',
help='add file/directory with local data')
parser.add_option('--local-stations',
dest='local_stations',
action='append',
help='add local stations file')
parser.add_option('--selection',
dest='selection_file',
action='append',
help='add local stations file')
parser.add_option(
'--local-responses-resp',
dest='local_responses_resp',
action='append',
help='add file/directory with local responses in RESP format')
parser.add_option('--local-responses-pz',
dest='local_responses_pz',
action='append',
help='add file/directory with local pole-zero responses')
parser.add_option(
'--local-responses-stationxml',
dest='local_responses_stationxml',
help='add file with local response information in StationXML format')
parser.add_option(
'--window',
dest='window',
default='full',
help='set time window to choose [full, p, "<time-start>,<time-end>"'
'] (time format is YYYY-MM-DD HH:MM:SS)')
parser.add_option(
'--out-components',
choices=['enu', 'rtu'],
dest='out_components',
default='rtu',
help='set output component orientations to radial-transverse-up [rtu] '
'(default) or east-north-up [enu]')
parser.add_option('--out-units',
choices=['M', 'M/S', 'M/S**2'],
dest='output_units',
default='M',
help='set output units to displacement "M" (default),'
' velocity "M/S" or acceleration "M/S**2"')
parser.add_option(
'--padding-factor',
type=float,
default=3.0,
dest='padding_factor',
help='extend time window on either side, in multiples of 1/<fmin_hz> '
'(default: 5)')
parser.add_option(
'--zero-padding',
dest='zero_pad',
action='store_true',
default=False,
help='Extend traces by zero-padding if clean restitution requires'
'longer windows')
parser.add_option(
'--credentials',
dest='user_credentials',
action='append',
default=[],
metavar='SITE,USER,PASSWD',
help='user credentials for specific site to access restricted data '
'(this option can be repeated)')
parser.add_option(
'--token',
dest='auth_tokens',
metavar='SITE,FILENAME',
action='append',
default=[],
help='user authentication token for specific site to access '
'restricted data (this option can be repeated)')
parser.add_option(
'--sites',
dest='sites',
metavar='SITE1,SITE2,...',
default='geofon,iris,orfeus',
help='sites to query (available: %s, default: "%%default"' %
', '.join(g_sites_available))
parser.add_option(
'--band-codes',
dest='priority_band_code',
metavar='V,L,M,B,H,S,E,...',
default='B,H',
help='select and prioritize band codes (default: %default)')
parser.add_option(
'--instrument-codes',
dest='priority_instrument_code',
metavar='H,L,G,...',
default='H,L',
help='select and prioritize instrument codes (default: %default)')
parser.add_option('--radius-min',
dest='radius_min',
metavar='VALUE',
default=0.0,
type=float,
help='minimum radius [km]')
parser.add_option('--nstations-wanted',
dest='nstations_wanted',
metavar='N',
type=int,
help='number of stations to select initially')
(options, args) = parser.parse_args(sys.argv[1:])
print('Parsed arguments:', args)
if len(args) not in (10, 7, 6):
parser.print_help()
sys.exit(1)
if options.debug:
util.setup_logging(program_name, 'debug')
else:
util.setup_logging(program_name, 'info')
if options.local_responses_pz and options.local_responses_resp:
logger.critical('cannot use local responses in PZ and RESP '
'format at the same time')
sys.exit(1)
n_resp_opt = 0
for resp_opt in (options.local_responses_pz, options.local_responses_resp,
options.local_responses_stationxml):
if resp_opt:
n_resp_opt += 1
if n_resp_opt > 1:
logger.critical('can only handle local responses from either PZ or '
'RESP or StationXML. Cannot yet merge different '
'response formats.')
sys.exit(1)
if options.local_responses_resp and not options.local_stations:
logger.critical('--local-responses-resp can only be used '
'when --stations is also given.')
sys.exit(1)
try:
ename = ''
magnitude = None
mt = None
if len(args) == 10:
time = util.str_to_time(args[1] + ' ' + args[2])
lat = float(args[3])
lon = float(args[4])
depth = float(args[5]) * km
iarg = 6
elif len(args) == 7:
if args[2].find(':') == -1:
sname_or_date = None
lat = float(args[1])
lon = float(args[2])
event = None
time = None
else:
sname_or_date = args[1] + ' ' + args[2]
iarg = 3
elif len(args) == 6:
sname_or_date = args[1]
iarg = 2
if len(args) in (7, 6) and sname_or_date is not None:
events = get_events_by_name_or_date([sname_or_date],
catalog=geofon)
if len(events) == 0:
logger.critical('no event found')
sys.exit(1)
elif len(events) > 1:
logger.critical('more than one event found')
sys.exit(1)
event = events[0]
time = event.time
lat = event.lat
lon = event.lon
depth = event.depth
ename = event.name
magnitude = event.magnitude
mt = event.moment_tensor
radius = float(args[iarg]) * km
fmin = float(args[iarg + 1])
sample_rate = float(args[iarg + 2])
eventname = args[iarg + 3]
cwd = str(sys.argv[1])
event_dir = op.join(cwd, 'data', 'events', eventname)
output_dir = op.join(event_dir, 'waveforms')
except:
raise
parser.print_help()
sys.exit(1)
if options.force and op.isdir(event_dir):
if not options.continue_:
shutil.rmtree(event_dir)
if op.exists(event_dir) and not options.continue_:
logger.critical(
'directory "%s" exists. Delete it first or use the --force option'
% event_dir)
sys.exit(1)
util.ensuredir(output_dir)
if time is not None:
event = model.Event(time=time,
lat=lat,
lon=lon,
depth=depth,
name=ename,
magnitude=magnitude,
moment_tensor=mt)
if options.window == 'full':
if event is None:
logger.critical('need event for --window=full')
sys.exit(1)
low_velocity = 1500.
timewindow = VelocityWindow(low_velocity,
tpad=options.padding_factor / fmin)
tmin, tmax = timewindow(time, radius, depth)
elif options.window == 'p':
if event is None:
logger.critical('need event for --window=p')
sys.exit(1)
phases = list(map(cake.PhaseDef, 'P p'.split()))
emod = cake.load_model()
tpad = options.padding_factor / fmin
timewindow = PhaseWindow(emod, phases, -tpad, tpad)
arrivaltimes = []
for dist in num.linspace(0, radius, 20):
try:
arrivaltimes.extend(timewindow(time, dist, depth))
except NoArrival:
pass
if not arrivaltimes:
logger.error('required phase arrival not found')
sys.exit(1)
tmin = min(arrivaltimes)
tmax = max(arrivaltimes)
else:
try:
stmin, stmax = options.window.split(',')
tmin = util.str_to_time(stmin.strip())
tmax = util.str_to_time(stmax.strip())
timewindow = FixedWindow(tmin, tmax)
except ValueError:
logger.critical('invalid argument to --window: "%s"' %
options.window)
sys.exit(1)
if event is not None:
event.name = eventname
tfade = tfade_factor / fmin
tpad = tfade
tmin -= tpad
tmax += tpad
tinc = None
priority_band_code = options.priority_band_code.split(',')
for s in priority_band_code:
if len(s) != 1:
logger.critical('invalid band code: %s' % s)
priority_instrument_code = options.priority_instrument_code.split(',')
for s in priority_instrument_code:
if len(s) != 1:
logger.critical('invalid instrument code: %s' % s)
station_query_conf = dict(latitude=lat,
longitude=lon,
minradius=options.radius_min * km * cake.m2d,
maxradius=radius * cake.m2d,
channel=','.join('%s??' % s
for s in priority_band_code))
target_sample_rate = sample_rate
fmax = target_sample_rate
# target_sample_rate = None
# priority_band_code = ['H', 'B', 'M', 'L', 'V', 'E', 'S']
priority_units = ['M/S', 'M', 'M/S**2']
# output_units = 'M'
sites = [x.strip() for x in options.sites.split(',') if x.strip()]
for site in sites:
if site not in g_sites_available:
logger.critical('unknown FDSN site: %s' % site)
sys.exit(1)
for s in options.user_credentials:
try:
site, user, passwd = s.split(',')
g_user_credentials[site] = user, passwd
except ValueError:
logger.critical('invalid format for user credentials: "%s"' % s)
sys.exit(1)
for s in options.auth_tokens:
try:
site, token_filename = s.split(',')
with open(token_filename, 'r') as f:
g_auth_tokens[site] = f.read()
except (ValueError, OSError, IOError):
logger.critical('cannot get token from file: %s' % token_filename)
sys.exit(1)
fn_template0 = \
'data_%(network)s.%(station)s.%(location)s.%(channel)s_%(tmin)s.mseed'
fn_template_raw = op.join(output_dir, 'raw', fn_template0)
fn_stations_raw = op.join(output_dir, 'stations.raw.txt')
fn_template_rest = op.join(output_dir, 'rest', fn_template0)
fn_commandline = op.join(output_dir, 'beatdown.command')
ftap = (ffade_factors[0] * fmin, fmin, fmax, ffade_factors[1] * fmax)
# chapter 1: download
sxs = []
for site in sites:
try:
extra_args = {
'iris': dict(matchtimeseries=True),
}.get(site, {})
extra_args.update(station_query_conf)
if site == 'geonet':
extra_args.update(starttime=tmin, endtime=tmax)
else:
extra_args.update(startbefore=tmax,
endafter=tmin,
includerestricted=(site in g_user_credentials
or site in g_auth_tokens))
logger.info('downloading channel information (%s)' % site)
sx = fdsn.station(site=site,
format='text',
level='channel',
**extra_args)
except fdsn.EmptyResult:
logger.error('No stations matching given criteria. (%s)' % site)
sx = None
if sx is not None:
sxs.append(sx)
if all(sx is None for sx in sxs) and not options.local_data:
sys.exit(1)
nsl_to_sites = defaultdict(list)
nsl_to_station = {}
if options.selection_file:
logger.info('using stations from stations file!')
stations = []
for fn in options.selection_file:
stations.extend(model.load_stations(fn))
nsls_selected = set(s.nsl() for s in stations)
else:
nsls_selected = None
for sx, site in zip(sxs, sites):
site_stations = sx.get_pyrocko_stations()
for s in site_stations:
nsl = s.nsl()
nsl_to_sites[nsl].append(site)
if nsl not in nsl_to_station:
if nsls_selected:
if nsl in nsls_selected:
nsl_to_station[nsl] = s
else:
nsl_to_station[
nsl] = s # using first site with this station
logger.info('number of stations found: %i' % len(nsl_to_station))
# station weeding
if options.nstations_wanted:
nsls_selected = None
stations_all = [
nsl_to_station[nsl_] for nsl_ in sorted(nsl_to_station.keys())
]
for s in stations_all:
s.set_event_relative_data(event)
stations_selected = weeding.weed_stations(stations_all,
options.nstations_wanted)[0]
nsls_selected = set(s.nsl() for s in stations_selected)
logger.info('number of stations selected: %i' % len(nsls_selected))
if tinc is None:
tinc = 3600.
have_data = set()
if options.continue_:
fns = glob.glob(fn_template_raw % starfill())
p = pile.make_pile(fns)
else:
fns = []
have_data_site = {}
could_have_data_site = {}
for site in sites:
have_data_site[site] = set()
could_have_data_site[site] = set()
available_through = defaultdict(set)
it = 0
nt = int(math.ceil((tmax - tmin) / tinc))
for it in range(nt):
tmin_win = tmin + it * tinc
tmax_win = min(tmin + (it + 1) * tinc, tmax)
logger.info('time window %i/%i (%s - %s)' %
(it + 1, nt, util.tts(tmin_win), util.tts(tmax_win)))
have_data_this_window = set()
if options.continue_:
trs_avail = p.all(tmin=tmin_win, tmax=tmax_win, load_data=False)
for tr in trs_avail:
have_data_this_window.add(tr.nslc_id)
for site, sx in zip(sites, sxs):
if sx is None:
continue
selection = []
channels = sx.choose_channels(
target_sample_rate=target_sample_rate,
priority_band_code=priority_band_code,
priority_units=priority_units,
priority_instrument_code=priority_instrument_code,
timespan=(tmin_win, tmax_win))
for nslc in sorted(channels.keys()):
if nsls_selected is not None and nslc[:3] not in nsls_selected:
continue
could_have_data_site[site].add(nslc)
if nslc not in have_data_this_window:
channel = channels[nslc]
if event:
lat_, lon_ = event.lat, event.lon
else:
lat_, lon_ = lat, lon
try:
dist = orthodrome.distance_accurate50m_numpy(
lat_, lon_, channel.latitude.value,
channel.longitude.value)
except:
dist = orthodrome.distance_accurate50m_numpy(
lat_, lon_, channel.latitude, channel.longitude)
if event:
depth_ = event.depth
time_ = event.time
else:
depth_ = None
time_ = None
tmin_, tmax_ = timewindow(time_, dist, depth_)
tmin_this = tmin_ - tpad
tmax_this = float(tmax_ + tpad)
tmin_req = max(tmin_win, tmin_this)
tmax_req = min(tmax_win, tmax_this)
if channel.sample_rate:
try:
deltat = 1.0 / int(channel.sample_rate.value)
except:
deltat = 1.0 / int(channel.sample_rate)
else:
deltat = 1.0
if tmin_req < tmax_req:
logger.debug('deltat %f' % deltat)
# extend time window by some samples because otherwise
# sometimes gaps are produced
# apparently the WS are only sensitive to full seconds
# round to avoid gaps, increase safetiy window
selection.append(nslc +
(math.floor(tmin_req - deltat * 20.0),
math.ceil(tmax_req + deltat * 20.0)))
if options.dry_run:
for (net, sta, loc, cha, tmin, tmax) in selection:
available_through[net, sta, loc, cha].add(site)
else:
neach = 100
i = 0
nbatches = ((len(selection) - 1) // neach) + 1
while i < len(selection):
selection_now = selection[i:i + neach]
f = tempfile.NamedTemporaryFile()
try:
sbatch = ''
if nbatches > 1:
sbatch = ' (batch %i/%i)' % (
(i // neach) + 1, nbatches)
logger.info('downloading data (%s)%s' % (site, sbatch))
data = fdsn.dataselect(site=site,
selection=selection_now,
**get_user_credentials(site))
while True:
buf = data.read(1024)
if not buf:
break
f.write(buf)
f.flush()
trs = io.load(f.name)
for tr in trs:
tr.fix_deltat_rounding_errors()
logger.debug('cutting window: %f - %f' %
(tmin_win, tmax_win))
logger.debug(
'available window: %f - %f, nsamples: %g' %
(tr.tmin, tr.tmax, tr.ydata.size))
try:
logger.debug('tmin before snap %f' % tr.tmin)
tr.snap(interpolate=True)
logger.debug('tmin after snap %f' % tr.tmin)
tr.chop(tmin_win,
tmax_win,
snap=(math.floor, math.ceil),
include_last=True)
logger.debug(
'cut window: %f - %f, nsamles: %g' %
(tr.tmin, tr.tmax, tr.ydata.size))
have_data.add(tr.nslc_id)
have_data_site[site].add(tr.nslc_id)
except trace.NoData:
pass
fns2 = io.save(trs, fn_template_raw)
for fn in fns2:
if fn in fns:
logger.warn('overwriting file %s', fn)
fns.extend(fns2)
except fdsn.EmptyResult:
pass
except HTTPError:
logger.warn('an error occurred while downloading data '
'for channels \n %s' %
'\n '.join('.'.join(x[:4])
for x in selection_now))
f.close()
i += neach
if options.dry_run:
nslcs = sorted(available_through.keys())
all_channels = defaultdict(set)
all_stations = defaultdict(set)
def plural_s(x):
return '' if x == 1 else 's'
for nslc in nslcs:
sites = tuple(sorted(available_through[nslc]))
logger.info('selected: %s.%s.%s.%s from site%s %s' %
(nslc + (plural_s(len(sites)), '+'.join(sites))))
all_channels[sites].add(nslc)
all_stations[sites].add(nslc[:3])
nchannels_all = 0
nstations_all = 0
for sites in sorted(all_channels.keys(),
key=lambda sites: (-len(sites), sites)):
nchannels = len(all_channels[sites])
nstations = len(all_stations[sites])
nchannels_all += nchannels
nstations_all += nstations
logger.info('selected (%s): %i channel%s (%i station%s)' %
('+'.join(sites), nchannels, plural_s(nchannels),
nstations, plural_s(nstations)))
logger.info('selected total: %i channel%s (%i station%s)' %
(nchannels_all, plural_s(nchannels_all), nstations_all,
plural_s(nstations_all)))
logger.info('dry run done.')
sys.exit(0)
for nslc in have_data:
# if we are in continue mode, we have to guess where the data came from
if not any(nslc in have_data_site[site] for site in sites):
for site in sites:
if nslc in could_have_data_site[site]:
have_data_site[site].add(nslc)
sxs = {}
for site in sites:
selection = []
for nslc in sorted(have_data_site[site]):
selection.append(nslc + (tmin - tpad, tmax + tpad))
if selection:
logger.info('downloading response information (%s)' % site)
sxs[site] = fdsn.station(site=site,
level='response',
selection=selection)
sxs[site].dump_xml(filename=op.join(output_dir, 'stations.%s.xml' %
site))
# chapter 1.5: inject local data
if options.local_data:
have_data_site['local'] = set()
plocal = pile.make_pile(options.local_data, fileformat='detect')
logger.info(
'Importing local data from %s between %s (%f) and %s (%f)' %
(options.local_data, util.time_to_str(tmin), tmin,
util.time_to_str(tmax), tmax))
for traces in plocal.chopper_grouped(gather=lambda tr: tr.nslc_id,
tmin=tmin,
tmax=tmax,
tinc=tinc):
for tr in traces:
if tr.nslc_id not in have_data:
fns.extend(io.save(traces, fn_template_raw))
have_data_site['local'].add(tr.nslc_id)
have_data.add(tr.nslc_id)
sites.append('local')
if options.local_responses_pz:
sxs['local'] = epz.make_stationxml(
epz.iload(options.local_responses_pz))
if options.local_responses_resp:
local_stations = []
for fn in options.local_stations:
local_stations.extend(model.load_stations(fn))
sxs['local'] = resp.make_stationxml(
local_stations, resp.iload(options.local_responses_resp))
if options.local_responses_stationxml:
sxs['local'] = stationxml.load_xml(
filename=options.local_responses_stationxml)
# chapter 1.6: dump raw data stations file
nsl_to_station = {}
for site in sites:
if site in sxs:
stations = sxs[site].get_pyrocko_stations(timespan=(tmin, tmax))
for s in stations:
nsl = s.nsl()
if nsl not in nsl_to_station:
nsl_to_station[nsl] = s
stations = [nsl_to_station[nsl_] for nsl_ in sorted(nsl_to_station.keys())]
util.ensuredirs(fn_stations_raw)
model.dump_stations(stations, fn_stations_raw)
dump_commandline(sys.argv, fn_commandline)
# chapter 2: restitution
if not fns:
logger.error('no data available')
sys.exit(1)
p = pile.make_pile(fns, show_progress=False)
p.get_deltatmin()
otinc = None
if otinc is None:
otinc = nice_seconds_floor(p.get_deltatmin() * 500000.)
otinc = 3600.
otmin = math.floor(p.tmin / otinc) * otinc
otmax = math.ceil(p.tmax / otinc) * otinc
otpad = tpad * 2
fns = []
rest_traces_b = []
win_b = None
for traces_a in p.chopper_grouped(gather=lambda tr: tr.nslc_id,
tmin=otmin,
tmax=otmax,
tinc=otinc,
tpad=otpad):
rest_traces_a = []
win_a = None
for tr in traces_a:
win_a = tr.wmin, tr.wmax
if win_b and win_b[0] >= win_a[0]:
fns.extend(cut_n_dump(rest_traces_b, win_b, fn_template_rest))
rest_traces_b = []
win_b = None
response = None
failure = []
for site in sites:
try:
if site not in sxs:
continue
logger.debug('Getting response for %s' % tr.__str__())
response = sxs[site].get_pyrocko_response(
tr.nslc_id,
timespan=(tr.tmin, tr.tmax),
fake_input_units=options.output_units)
break
except stationxml.NoResponseInformation:
failure.append('%s: no response information' % site)
except stationxml.MultipleResponseInformation:
failure.append('%s: multiple response information' % site)
if response is None:
failure = ', '.join(failure)
else:
failure = ''
try:
if tr.tmin > tmin and options.zero_pad:
logger.warning(
'Trace too short for clean restitution in '
'desired frequency band -> zero-padding!')
tr.extend(tr.tmin - tfade, tr.tmax + tfade, 'repeat')
rest_tr = tr.transfer(tfade, ftap, response, invert=True)
rest_traces_a.append(rest_tr)
except (trace.TraceTooShort, trace.NoData):
failure = 'trace too short'
if failure:
logger.warn('failed to restitute trace %s.%s.%s.%s (%s)' %
(tr.nslc_id + (failure, )))
if rest_traces_b:
rest_traces = trace.degapper(rest_traces_b + rest_traces_a,
deoverlap='crossfade_cos')
fns.extend(cut_n_dump(rest_traces, win_b, fn_template_rest))
rest_traces_a = []
if win_a:
for tr in rest_traces:
try:
rest_traces_a.append(
tr.chop(win_a[0], win_a[1] + otpad, inplace=False))
except trace.NoData:
pass
rest_traces_b = rest_traces_a
win_b = win_a
fns.extend(cut_n_dump(rest_traces_b, win_b, fn_template_rest))
# chapter 3: rotated restituted traces for inspection
if not event:
sys.exit(0)
fn_template1 = \
'DISPL.%(network)s.%(station)s.%(location)s.%(channel)s'
fn_waveforms = op.join(output_dir, 'prepared', fn_template1)
fn_stations = op.join(output_dir, 'stations.prepared.txt')
fn_event = op.join(event_dir, 'event.txt')
fn_event_yaml = op.join(event_dir, 'event.yaml')
nsl_to_station = {}
for site in sites:
if site in sxs:
stations = sxs[site].get_pyrocko_stations(timespan=(tmin, tmax))
for s in stations:
nsl = s.nsl()
if nsl not in nsl_to_station:
nsl_to_station[nsl] = s
p = pile.make_pile(fns, show_progress=False)
deltat = None
if sample_rate is not None:
deltat = 1.0 / sample_rate
traces_beat = []
used_stations = []
for nsl, s in nsl_to_station.items():
s.set_event_relative_data(event)
traces = p.all(trace_selector=lambda tr: tr.nslc_id[:3] == nsl)
if options.out_components == 'rtu':
pios = s.guess_projections_to_rtu(out_channels=('R', 'T', 'Z'))
elif options.out_components == 'enu':
pios = s.guess_projections_to_enu(out_channels=('E', 'N', 'Z'))
else:
assert False
for (proj, in_channels, out_channels) in pios:
proc = trace.project(traces, proj, in_channels, out_channels)
for tr in proc:
tr_beat = heart.SeismicDataset.from_pyrocko_trace(tr)
traces_beat.append(tr_beat)
for ch in out_channels:
if ch.name == tr.channel:
s.add_channel(ch)
if proc:
io.save(proc, fn_waveforms)
used_stations.append(s)
stations = list(used_stations)
util.ensuredirs(fn_stations)
model.dump_stations(stations, fn_stations)
model.dump_events([event], fn_event)
from pyrocko.guts import dump
dump([event], filename=fn_event_yaml)
utility.dump_objects(op.join(cwd, 'seismic_data.pkl'),
outlist=[stations, traces_beat])
logger.info('prepared waveforms from %i stations' % len(stations))
fns = []
have_data_site = {}
could_have_data_site = {}
for site in sites:
have_data_site[site] = set()
could_have_data_site[site] = set()
available_through = defaultdict(set)
it = 0
nt = int(math.ceil((tmax - tmin) / tinc))
for it in range(nt):
tmin_win = tmin + it * tinc
tmax_win = min(tmin + (it + 1) * tinc, tmax)
logger.info('time window %i/%i (%s - %s)' %
(it + 1, nt, util.tts(tmin_win), util.tts(tmax_win)))
have_data_this_window = set()
if options.continue_:
trs_avail = p.all(tmin=tmin_win, tmax=tmax_win, load_data=False)
for tr in trs_avail:
have_data_this_window.add(tr.nslc_id)
for site, sx in zip(sites, sxs):
if sx is None:
continue
selection = []
channels = sx.choose_channels(
target_sample_rate=target_sample_rate,
priority_band_code=priority_band_code,
priority_units=priority_units,
origin_id=evq_ml.origin_list[0].public_id,
type="Mw",
mag=quakeml.RealQuantity(value=emw.magnitude)))
evq_ml.magnitude_list = magnitude_list
qml_blank.event_parameters.event_list.append(evq_ml)
dist_ins = orthodrome.distance_accurate50m(insheim_lat,
insheim_lon, eml.lat,
eml.lon)
dist_land = orthodrome.distance_accurate50m(
landau_lat, landau_lon, eml.lat, eml.lon)
if dist_ins < 4500.:
ins_events.append(eml)
event_params_ins.append([
str(util.tts(eml.time)),
str(eml.time),
str(eml.lat),
str(eml.lon),
str(eml.depth),
str(eml.magnitude),
str(emw.magnitude)
])
if dist_land < 4500.:
land_events.append
event_params_land.append([
str(util.tts(eml.time)),
str(eml.time),
str(eml.lat),
str(eml.lon),
def main():
parser = OptionParser(usage=usage, description=description)
parser.add_option(
"--force",
dest="force",
action="store_true",
default=False,
help="allow recreation of output <directory>",
)
parser.add_option(
"--debug",
dest="debug",
action="store_true",
default=False,
help="print debugging information to stderr",
)
parser.add_option(
"--dry-run",
dest="dry_run",
action="store_true",
default=False,
help="show available stations/channels and exit "
"(do not download waveforms)",
)
parser.add_option(
"--continue",
dest="continue_",
action="store_true",
default=False,
help="continue download after a accident",
)
parser.add_option(
"--local-data",
dest="local_data",
action="append",
help="add file/directory with local data",
)
parser.add_option(
"--local-stations",
dest="local_stations",
action="append",
help="add local stations file",
)
parser.add_option(
"--local-responses-resp",
dest="local_responses_resp",
action="append",
help="add file/directory with local responses in RESP format",
)
parser.add_option(
"--local-responses-pz",
dest="local_responses_pz",
action="append",
help="add file/directory with local pole-zero responses",
)
parser.add_option(
"--local-responses-stationxml",
dest="local_responses_stationxml",
help="add file with local response information in StationXML format",
)
parser.add_option(
"--window",
dest="window",
default="full",
help='set time window to choose [full, p, "<time-start>,<time-end>"'
"] (time format is YYYY-MM-DD HH:MM:SS)",
)
parser.add_option(
"--out-components",
choices=["enu", "rtu"],
dest="out_components",
default="rtu",
help="set output component orientations to radial-transverse-up [rtu] "
"(default) or east-north-up [enu]",
)
parser.add_option(
"--padding-factor",
type=float,
default=3.0,
dest="padding_factor",
help="extend time window on either side, in multiples of 1/<fmin_hz> "
"(default: 5)",
)
parser.add_option(
"--credentials",
dest="user_credentials",
action="append",
default=[],
metavar="SITE,USER,PASSWD",
help="user credentials for specific site to access restricted data "
"(this option can be repeated)",
)
parser.add_option(
"--token",
dest="auth_tokens",
metavar="SITE,FILENAME",
action="append",
default=[],
help="user authentication token for specific site to access "
"restricted data (this option can be repeated)",
)
parser.add_option(
"--sites",
dest="sites",
metavar="SITE1,SITE2,...",
# default='bgr',
default="http://ws.gpi.kit.edu,bgr,http://188.246.25.142:8080",
help='sites to query (available: %s, default: "%%default"' %
", ".join(g_sites_available),
)
parser.add_option(
"--band-codes",
dest="priority_band_code",
metavar="V,L,M,B,H,S,E,...",
default="V,L,M,B,H,E",
help="select and prioritize band codes (default: %default)",
)
parser.add_option(
"--instrument-codes",
dest="priority_instrument_code",
metavar="H,L,G,...",
default="H,L,O,",
help="select and prioritize instrument codes (default: %default)",
)
parser.add_option(
"--radius-min",
dest="radius_min",
metavar="VALUE",
default=0.0,
type=float,
help="minimum radius [km]",
)
parser.add_option(
"--tinc",
dest="tinc",
metavar="VALUE",
default=3600.0 * 12.0,
type=float,
help="length of seperate saved files in s",
)
parser.add_option(
"--nstations-wanted",
dest="nstations_wanted",
metavar="N",
type=int,
help="number of stations to select initially",
)
(options, args) = parser.parse_args(sys.argv[1:])
if len(args) not in (9, 6, 5):
parser.print_help()
sys.exit(1)
if options.debug:
util.setup_logging(program_name, "debug")
else:
util.setup_logging(program_name, "info")
if options.local_responses_pz and options.local_responses_resp:
logger.critical("cannot use local responses in PZ and RESP "
"format at the same time")
sys.exit(1)
n_resp_opt = 0
for resp_opt in (
options.local_responses_pz,
options.local_responses_resp,
options.local_responses_stationxml,
):
if resp_opt:
n_resp_opt += 1
if n_resp_opt > 1:
logger.critical("can only handle local responses from either PZ or "
"RESP or StationXML. Cannot yet merge different "
"response formats.")
sys.exit(1)
if options.local_responses_resp and not options.local_stations:
logger.critical("--local-responses-resp can only be used "
"when --stations is also given.")
sys.exit(1)
try:
ename = ""
magnitude = None
mt = None
if len(args) == 9:
time = util.str_to_time(args[0] + " " + args[1])
lat = float(args[2])
lon = float(args[3])
depth = float(args[4]) * km
iarg = 5
elif len(args) == 6:
if args[1].find(":") == -1:
sname_or_date = None
lat = float(args[0])
lon = float(args[1])
event = None
time = None
else:
sname_or_date = args[0] + " " + args[1]
iarg = 2
elif len(args) == 5:
sname_or_date = args[0]
iarg = 1
if len(args) in (6, 5) and sname_or_date is not None:
events = get_events_by_name_or_date([sname_or_date],
catalog=geofon)
if len(events) == 0:
logger.critical("no event found")
sys.exit(1)
elif len(events) > 1:
logger.critical("more than one event found")
sys.exit(1)
event = events[0]
time = event.time
lat = event.lat
lon = event.lon
depth = event.depth
ename = event.name
magnitude = event.magnitude
mt = event.moment_tensor
radius = float(args[iarg]) * km
fmin = float(args[iarg + 1])
sample_rate = float(args[iarg + 2])
eventname = args[iarg + 3]
event_dir = op.join("data", "events", eventname)
output_dir = op.join(event_dir, "waveforms")
except:
raise
parser.print_help()
sys.exit(1)
if options.force and op.isdir(event_dir):
if not options.continue_:
shutil.rmtree(event_dir)
if op.exists(event_dir) and not options.continue_:
logger.critical(
'directory "%s" exists. Delete it first or use the --force option'
% event_dir)
sys.exit(1)
util.ensuredir(output_dir)
if time is not None:
event = model.Event(
time=time,
lat=lat,
lon=lon,
depth=depth,
name=ename,
magnitude=magnitude,
moment_tensor=mt,
)
if options.window == "full":
if event is None:
logger.critical("need event for --window=full")
sys.exit(1)
low_velocity = 1500.0
timewindow = VelocityWindow(low_velocity,
tpad=options.padding_factor / fmin)
tmin, tmax = timewindow(time, radius, depth)
elif options.window == "p":
if event is None:
logger.critical("need event for --window=p")
sys.exit(1)
phases = list(map(cake.PhaseDef, "P p".split()))
emod = cake.load_model()
tpad = options.padding_factor / fmin
timewindow = PhaseWindow(emod, phases, -tpad, tpad)
arrivaltimes = []
for dist in num.linspace(0, radius, 20):
try:
arrivaltimes.extend(timewindow(time, dist, depth))
except NoArrival:
pass
if not arrivaltimes:
logger.error("required phase arrival not found")
sys.exit(1)
tmin = min(arrivaltimes)
tmax = max(arrivaltimes)
else:
try:
stmin, stmax = options.window.split(",")
tmin = util.str_to_time(stmin.strip())
tmax = util.str_to_time(stmax.strip())
timewindow = FixedWindow(tmin, tmax)
except ValueError:
logger.critical('invalid argument to --window: "%s"' %
options.window)
sys.exit(1)
if event is not None:
event.name = eventname
tlen = tmax - tmin
tfade = tfade_factor / fmin
tpad = tfade
tmin -= tpad
tmax += tpad
priority_band_code = options.priority_band_code.split(",")
for s in priority_band_code:
if len(s) != 1:
logger.critical("invalid band code: %s" % s)
priority_instrument_code = options.priority_instrument_code.split(",")
for s in priority_instrument_code:
if len(s) != 1:
logger.critical("invalid instrument code: %s" % s)
station_query_conf = dict(
latitude=lat,
longitude=lon,
minradius=options.radius_min * km * cake.m2d,
maxradius=radius * cake.m2d,
channel=",".join("?%s?" % s for s in priority_band_code),
)
target_sample_rate = sample_rate
fmax = target_sample_rate
# target_sample_rate = None
# priority_band_code = ['H', 'B', 'M', 'L', 'V', 'E', 'S']
priority_units = ["M/S", "M", "M/S**2"]
output_units = "M"
sites = [x.strip() for x in options.sites.split(",") if x.strip()]
tinc = options.tinc
# for site in sites:
# if site not in g_sites_available:
# logger.critical('unknown FDSN site: %s' % site)
# sys.exit(1)
for s in options.user_credentials:
try:
site, user, passwd = s.split(",")
g_user_credentials[site] = user, passwd
except ValueError:
logger.critical('invalid format for user credentials: "%s"' % s)
sys.exit(1)
for s in options.auth_tokens:
try:
site, token_filename = s.split(",")
with open(token_filename, "r") as f:
g_auth_tokens[site] = f.read()
except (ValueError, OSError, IOError):
logger.critical("cannot get token from file: %s" % token_filename)
sys.exit(1)
fn_template0 = (
"data_%(network)s.%(station)s.%(location)s.%(channel)s_%(tmin)s.mseed")
fn_template_raw = op.join(output_dir, "raw", fn_template0)
fn_template_raw_folder = op.join(output_dir, "raw/", "traces.mseed")
fn_stations_raw = op.join(output_dir, "stations.raw.txt")
fn_template_rest = op.join(output_dir, "rest", fn_template0)
fn_commandline = op.join(output_dir, "seigerdown.command")
ftap = (ffade_factors[0] * fmin, fmin, fmax, ffade_factors[1] * fmax)
# chapter 1: download
sxs = []
for site in sites:
try:
extra_args = {
"iris": dict(matchtimeseries=True),
}.get(site, {})
extra_args.update(station_query_conf)
if site == "geonet":
extra_args.update(starttime=tmin, endtime=tmax)
else:
extra_args.update(
startbefore=tmax,
endafter=tmin,
includerestricted=(site in g_user_credentials
or site in g_auth_tokens),
)
logger.info("downloading channel information (%s)" % site)
sx = fdsn.station(site=site,
format="text",
level="channel",
**extra_args)
except fdsn.EmptyResult:
logger.error("No stations matching given criteria. (%s)" % site)
sx = None
if sx is not None:
sxs.append(sx)
if all(sx is None for sx in sxs) and not options.local_data:
sys.exit(1)
nsl_to_sites = defaultdict(list)
nsl_to_station = {}
for sx, site in zip(sxs, sites):
site_stations = sx.get_pyrocko_stations()
for s in site_stations:
nsl = s.nsl()
nsl_to_sites[nsl].append(site)
if nsl not in nsl_to_station:
nsl_to_station[nsl] = s # using first site with this station
logger.info("number of stations found: %i" % len(nsl_to_station))
# station weeding
nsls_selected = None
if options.nstations_wanted:
stations_all = [
nsl_to_station[nsl_] for nsl_ in sorted(nsl_to_station.keys())
]
for s in stations_all:
s.set_event_relative_data(event)
stations_selected = weeding.weed_stations(stations_all,
options.nstations_wanted)[0]
nsls_selected = set(s.nsl() for s in stations_selected)
logger.info("number of stations selected: %i" % len(nsls_selected))
have_data = set()
if options.continue_:
fns = glob.glob(fn_template_raw % starfill())
p = pile.make_pile(fns)
else:
fns = []
have_data_site = {}
could_have_data_site = {}
for site in sites:
have_data_site[site] = set()
could_have_data_site[site] = set()
available_through = defaultdict(set)
it = 0
nt = int(math.ceil((tmax - tmin) / tinc))
for it in range(nt):
tmin_win = tmin + it * tinc
tmax_win = min(tmin + (it + 1) * tinc, tmax)
logger.info("time window %i/%i (%s - %s)" %
(it + 1, nt, util.tts(tmin_win), util.tts(tmax_win)))
have_data_this_window = set()
if options.continue_:
trs_avail = p.all(tmin=tmin_win, tmax=tmax_win, load_data=False)
for tr in trs_avail:
have_data_this_window.add(tr.nslc_id)
for site, sx in zip(sites, sxs):
if sx is None:
continue
selection = []
channels = sx.choose_channels(
target_sample_rate=target_sample_rate,
priority_band_code=priority_band_code,
priority_units=priority_units,
priority_instrument_code=priority_instrument_code,
timespan=(tmin_win, tmax_win),
)
for nslc in sorted(channels.keys()):
if nsls_selected is not None and nslc[:3] not in nsls_selected:
continue
could_have_data_site[site].add(nslc)
if nslc not in have_data_this_window:
channel = channels[nslc]
if event:
lat_, lon_ = event.lat, event.lon
else:
lat_, lon_ = lat, lon
dist = orthodrome.distance_accurate50m_numpy(
lat_, lon_, channel.latitude.value,
channel.longitude.value)
if event:
depth_ = event.depth
time_ = event.time
else:
depth_ = None
time_ = None
tmin_, tmax_ = timewindow(time_, dist, depth_)
tmin_this = tmin_ - tpad
tmax_this = tmax_ + tpad
tmin_req = max(tmin_win, tmin_this)
tmax_req = min(tmax_win, tmax_this)
if channel.sample_rate:
deltat = 1.0 / channel.sample_rate.value
else:
deltat = 1.0
if tmin_req < tmax_req:
# extend time window by some samples because otherwise
# sometimes gaps are produced
selection.append(nslc + (tmin_req - deltat * 10.0,
tmax_req + deltat * 10.0))
if options.dry_run:
for (net, sta, loc, cha, tmin, tmax) in selection:
available_through[net, sta, loc, cha].add(site)
else:
neach = 100
i = 0
nbatches = ((len(selection) - 1) // neach) + 1
while i < len(selection):
selection_now = selection[i:i + neach]
f = tempfile.NamedTemporaryFile()
try:
sbatch = ""
if nbatches > 1:
sbatch = " (batch %i/%i)" % (
(i // neach) + 1, nbatches)
logger.info("downloading data (%s)%s" % (site, sbatch))
data = fdsn.dataselect(site=site,
selection=selection_now,
**get_user_credentials(site))
while True:
buf = data.read(1024)
if not buf:
break
f.write(buf)
f.flush()
trs = io.load(f.name)
for tr in trs:
if tr.station == "7869":
tr.station = "MOER"
tr.network = "LE"
tr.location = ""
try:
tr.chop(tmin_win, tmax_win)
have_data.add(tr.nslc_id)
have_data_site[site].add(tr.nslc_id)
except trace.NoData:
pass
fns2 = io.save(trs, fn_template_raw)
io.save(trs, fn_template_raw_folder)
for fn in fns2:
if fn in fns:
logger.warn("overwriting file %s", fn)
fns.extend(fns2)
except fdsn.EmptyResult:
pass
except HTTPError:
logger.warn("an error occurred while downloading data "
"for channels \n %s" %
"\n ".join(".".join(x[:4])
for x in selection_now))
f.close()
i += neach
if options.dry_run:
nslcs = sorted(available_through.keys())
all_channels = defaultdict(set)
all_stations = defaultdict(set)
def plural_s(x):
return "" if x == 1 else "s"
for nslc in nslcs:
sites = tuple(sorted(available_through[nslc]))
logger.info("selected: %s.%s.%s.%s from site%s %s" %
(nslc + (plural_s(len(sites)), "+".join(sites))))
all_channels[sites].add(nslc)
all_stations[sites].add(nslc[:3])
nchannels_all = 0
nstations_all = 0
for sites in sorted(all_channels.keys(),
key=lambda sites: (-len(sites), sites)):
nchannels = len(all_channels[sites])
nstations = len(all_stations[sites])
nchannels_all += nchannels
nstations_all += nstations
logger.info("selected (%s): %i channel%s (%i station%s)" % (
"+".join(sites),
nchannels,
plural_s(nchannels),
nstations,
plural_s(nstations),
))
logger.info("selected total: %i channel%s (%i station%s)" % (
nchannels_all,
plural_s(nchannels_all),
nstations_all,
plural_s(nstations_all),
))
logger.info("dry run done.")
sys.exit(0)
for nslc in have_data:
# if we are in continue mode, we have to guess where the data came from
if not any(nslc in have_data_site[site] for site in sites):
for site in sites:
if nslc in could_have_data_site[site]:
have_data_site[site].add(nslc)
sxs = {}
for site in sites:
selection = []
for nslc in sorted(have_data_site[site]):
selection.append(nslc + (tmin - tpad, tmax + tpad))
if selection:
logger.info("downloading response information (%s)" % site)
sxs[site] = fdsn.station(site=site,
level="response",
selection=selection)
sited = site
if site == "http://192.168.11.220:8080":
sited = "bgr_internal"
elif site == "http://ws.gpi.kit.edu":
sited = "kit"
if site == "http://188.246.25.142:8080":
sited = "moer"
sxs[site].dump_xml(filename=op.join(output_dir, "stations.%s.xml" %
sited))
# chapter 1.5: inject local data
if options.local_data:
have_data_site["local"] = set()
plocal = pile.make_pile(options.local_data, fileformat="detect")
for traces in plocal.chopper_grouped(gather=lambda tr: tr.nslc_id,
tmin=tmin,
tmax=tmax,
tinc=tinc):
for tr in traces:
if tr.station == "7869":
tr.station = "MOER"
tr.network = "LE"
tr.location = ""
if tr.nslc_id not in have_data:
fns.extend(io.save(traces, fn_template_raw))
have_data_site["local"].add(tr.nslc_id)
have_data.add(tr.nslc_id)
sites.append("local")
if options.local_responses_pz:
sxs["local"] = epz.make_stationxml(
epz.iload(options.local_responses_pz))
if options.local_responses_resp:
local_stations = []
for fn in options.local_stations:
local_stations.extend(model.load_stations(fn))
sxs["local"] = resp.make_stationxml(
local_stations, resp.iload(options.local_responses_resp))
if options.local_responses_stationxml:
sxs["local"] = stationxml.load_xml(
filename=options.local_responses_stationxml)
# chapter 1.6: dump raw data stations file
nsl_to_station = {}
for site in sites:
if site in sxs:
stations = sxs[site].get_pyrocko_stations(timespan=(tmin, tmax))
for s in stations:
nsl = s.nsl()
if nsl not in nsl_to_station:
nsl_to_station[nsl] = s
stations = [nsl_to_station[nsl_] for nsl_ in sorted(nsl_to_station.keys())]
util.ensuredirs(fn_stations_raw)
model.dump_stations(stations, fn_stations_raw)
dump_commandline(sys.argv, fn_commandline)
# chapter 2: restitution
if not fns:
logger.error("no data available")
sys.exit(1)
p = pile.make_pile(fns, show_progress=False)
p.get_deltatmin()
otinc = None
if otinc is None:
otinc = nice_seconds_floor(p.get_deltatmin() * 500000.0)
otinc = 3600.0
otmin = math.floor(p.tmin / otinc) * otinc
otmax = math.ceil(p.tmax / otinc) * otinc
otpad = tpad * 2
fns = []
rest_traces_b = []
win_b = None
for traces_a in p.chopper_grouped(gather=lambda tr: tr.nslc_id,
tmin=otmin,
tmax=otmax,
tinc=otinc,
tpad=otpad):
rest_traces_a = []
win_a = None
for tr in traces_a:
if tr.station == "7869":
tr.station = "MOER"
tr.network = "LE"
tr.location = ""
win_a = tr.wmin, tr.wmax
if win_b and win_b[0] >= win_a[0]:
fns.extend(cut_n_dump(rest_traces_b, win_b, fn_template_rest))
rest_traces_b = []
win_b = None
response = None
failure = []
for site in sites:
try:
if site not in sxs:
continue
response = sxs[site].get_pyrocko_response(
tr.nslc_id,
timespan=(tr.tmin, tr.tmax),
fake_input_units=output_units,
)
break
except stationxml.NoResponseInformation:
failure.append("%s: no response information" % site)
except stationxml.MultipleResponseInformation:
failure.append("%s: multiple response information" % site)
if response is None:
failure = ", ".join(failure)
else:
failure = ""
try:
rest_tr = tr.transfer(tfade, ftap, response, invert=True)
rest_traces_a.append(rest_tr)
except (trace.TraceTooShort, trace.NoData):
failure = "trace too short"
if failure:
logger.warn("failed to restitute trace %s.%s.%s.%s (%s)" %
(tr.nslc_id + (failure, )))
if rest_traces_b:
rest_traces = trace.degapper(rest_traces_b + rest_traces_a,
deoverlap="crossfade_cos")
fns.extend(cut_n_dump(rest_traces, win_b, fn_template_rest))
rest_traces_a = []
if win_a:
for tr in rest_traces:
if tr.station == "7869":
tr.station = "MOER"
tr.network = "LE"
tr.location = ""
try:
rest_traces_a.append(
tr.chop(win_a[0], win_a[1] + otpad, inplace=False))
except trace.NoData:
pass
rest_traces_b = rest_traces_a
win_b = win_a
fns.extend(cut_n_dump(rest_traces_b, win_b, fn_template_rest))
# chapter 3: rotated restituted traces for inspection
if not event:
sys.exit(0)
fn_template1 = "DISPL.%(network)s.%(station)s.%(location)s.%(channel)s"
fn_waveforms = op.join(output_dir, "prepared", fn_template1)
fn_stations = op.join(output_dir, "stations.prepared.txt")
fn_event = op.join(event_dir, "event.txt")
nsl_to_station = {}
for site in sites:
if site in sxs:
stations = sxs[site].get_pyrocko_stations(timespan=(tmin, tmax))
for s in stations:
nsl = s.nsl()
if nsl not in nsl_to_station:
nsl_to_station[nsl] = s
p = pile.make_pile(fns, show_progress=False)
deltat = None
if sample_rate is not None:
deltat = 1.0 / sample_rate
used_stations = []
for nsl, s in nsl_to_station.items():
s.set_event_relative_data(event)
traces = p.all(trace_selector=lambda tr: tr.nslc_id[:3] == nsl)
keep = []
for tr in traces:
if deltat is not None:
try:
tr.downsample_to(deltat, snap=True, allow_upsample_max=5)
keep.append(tr)
except util.UnavailableDecimation as e:
logger.warn("Cannot downsample %s.%s.%s.%s: %s" %
(tr.nslc_id + (e, )))
continue
if options.out_components == "rtu":
pios = s.guess_projections_to_rtu(out_channels=("R", "T", "Z"))
elif options.out_components == "enu":
pios = s.guess_projections_to_enu(out_channels=("E", "N", "Z"))
else:
assert False
for (proj, in_channels, out_channels) in pios:
proc = trace.project(traces, proj, in_channels, out_channels)
for tr in proc:
for ch in out_channels:
if ch.name == tr.channel:
s.add_channel(ch)
if proc:
io.save(proc, fn_waveforms)
used_stations.append(s)
stations = list(used_stations)
util.ensuredirs(fn_stations)
model.dump_stations(stations, fn_stations)
model.dump_events([event], fn_event)
logger.info("prepared waveforms from %i stations" % len(stations))
def search(config,
override_tmin=None,
override_tmax=None,
show_detections=False,
show_movie=False,
show_window_traces=False,
force=False,
stop_after_first=False,
nparallel=6,
save_imax=False,
bark=False):
fp = config.expand_path
run_path = fp(config.run_path)
# if op.exists(run_path):
# if force:
# shutil.rmtree(run_path)
# else:
# raise common.LassieError(
# 'run directory already exists: %s' %
# run_path)
util.ensuredir(run_path)
write_config(config, op.join(run_path, 'config.yaml'))
ifm_path_template = config.get_ifm_path_template()
detections_path = config.get_detections_path()
events_path = config.get_events_path()
figures_path_template = config.get_figures_path_template()
config.setup_image_function_contributions()
ifcs = config.image_function_contributions
grid = config.get_grid()
receivers = config.get_receivers()
norm_map = gridmod.geometrical_normalization(grid, receivers)
data_paths = fp(config.data_paths)
for data_path in fp(data_paths):
if not op.exists(data_path):
pass
p = pile.make_pile(data_paths, fileformat='detect')
if p.is_empty():
raise common.LassieError('no usable waveforms found')
for ifc in ifcs:
ifc.prescan(p)
shift_tables = []
tshift_minmaxs = []
for ifc in ifcs:
shift_tables.append(ifc.get_table(grid, receivers))
tshift_minmaxs.append(num.nanmin(shift_tables[-1]))
tshift_minmaxs.append(num.nanmax(shift_tables[-1]))
fsmooth_min = min(ifc.get_fsmooth() for ifc in ifcs)
tshift_min = min(tshift_minmaxs)
tshift_max = max(tshift_minmaxs)
if config.detector_tpeaksearch is not None:
tpeaksearch = config.detector_tpeaksearch
else:
tpeaksearch = (tshift_max - tshift_min) + 1.0 / fsmooth_min
tpad = max(ifc.get_tpad() for ifc in ifcs) + \
(tshift_max - tshift_min) + tpeaksearch
tinc = (tshift_max - tshift_min) * 10. + 3.0 * tpad
tavail = p.tmax - p.tmin
tinc = min(tinc, tavail - 2.0 * tpad)
if tinc <= 0:
raise common.LassieError('available waveforms too short \n'
'required: %g s\n'
'available: %g s\n' % (2. * tpad, tavail))
blacklist = set(tuple(s.split('.')) for s in config.blacklist)
whitelist = set(tuple(s.split('.')) for s in config.whitelist)
distances = grid.distances(receivers)
distances_to_grid = num.min(distances, axis=0)
distance_min = num.min(distances)
distance_max = num.max(distances)
station_index = dict(
(rec.codes, i) for (i, rec) in enumerate(receivers)
if rec.codes not in blacklist and (
not whitelist or rec.codes in whitelist) and (
config.distance_max is None
or distances_to_grid[i] <= config.distance_max))
check_data_consistency(p, config)
deltat_cf = max(p.deltats.keys())
assert deltat_cf > 0.0
while True:
if not all(ifc.deltat_cf_is_available(deltat_cf * 2) for ifc in ifcs):
break
deltat_cf *= 2
logger.info('CF lassie sampling interval (rate): %g s (%g Hz)' %
(deltat_cf, 1.0 / deltat_cf))
ngridpoints = grid.size()
logger.info('number of grid points: %i' % ngridpoints)
logger.info('minimum source-receiver distance: %g m' % distance_min)
logger.info('maximum source-receiver distance: %g m' % distance_max)
logger.info('minimum travel-time: %g s' % tshift_min)
logger.info('maximum travel-time: %g s' % tshift_max)
idetection = 0
tmin = override_tmin or config.tmin or p.tmin + tpad
tmax = override_tmax or config.tmax or p.tmax - tpad
events = config.get_events()
twindows = []
if events is not None:
for ev in events:
if tmin <= ev.time <= tmax:
twindows.append(
(ev.time + tshift_min - (tshift_max - tshift_min) *
config.event_time_window_factor,
ev.time + tshift_min + (tshift_max - tshift_min) *
config.event_time_window_factor))
else:
twindows.append((tmin, tmax))
for iwindow_group, (tmin_win, tmax_win) in enumerate(twindows):
nwin = int(math.ceil((tmax_win - tmin_win) / tinc))
logger.info('start processing time window group %i/%i: %s - %s' %
(iwindow_group + 1, len(twindows),
util.time_to_str(tmin_win), util.time_to_str(tmax_win)))
logger.info('number of time windows: %i' % nwin)
logger.info('time window length: %g s' % (tinc + 2.0 * tpad))
logger.info('time window payload: %g s' % tinc)
logger.info('time window padding: 2 x %g s' % tpad)
logger.info('time window overlap: %g%%' % (100.0 * 2.0 * tpad /
(tinc + 2.0 * tpad)))
iwin = -1
for trs in p.chopper(
tmin=tmin_win,
tmax=tmax_win,
tinc=tinc,
tpad=tpad,
want_incomplete=config.fill_incomplete_with_zeros,
trace_selector=lambda tr: tr.nslc_id[:3] in station_index):
iwin += 1
trs_ok = []
for tr in trs:
if tr.ydata.size == 0:
logger.warn('skipping empty trace: %s.%s.%s.%s' %
tr.nslc_id)
continue
if not num.all(num.isfinite(tr.ydata)):
logger.warn('skipping trace because of invalid values: '
'%s.%s.%s.%s' % tr.nslc_id)
continue
trs_ok.append(tr)
trs = trs_ok
if not trs:
continue
logger.info('processing time window %i/%i: %s - %s' %
(iwin + 1, nwin, util.time_to_str(
trs[0].wmin), util.time_to_str(trs[0].wmax)))
wmin = trs[0].wmin
wmax = trs[0].wmax
if config.fill_incomplete_with_zeros:
trs = zero_fill(trs, wmin - tpad, wmax + tpad)
t0 = math.floor(wmin / deltat_cf) * deltat_cf
iwmin = int(round((wmin - tpeaksearch - t0) / deltat_cf))
iwmax = int(round((wmax + tpeaksearch - t0) / deltat_cf))
lengthout = iwmax - iwmin + 1
pdata = []
trs_debug = []
parstack_params = []
for iifc, ifc in enumerate(ifcs):
dataset = ifc.preprocess(trs, wmin - tpeaksearch,
wmax + tpeaksearch,
tshift_max - tshift_min, deltat_cf)
if not dataset:
continue
nstations_selected = len(dataset)
nsls_selected, trs_selected = zip(*dataset)
for tr in trs_selected:
tr.meta = {'tabu': True}
trs_debug.extend(trs + list(trs_selected))
istations_selected = num.array(
[station_index[nsl] for nsl in nsls_selected],
dtype=num.int)
arrays = [tr.ydata.astype(num.float) for tr in trs_selected]
offsets = num.array([
int(round((tr.tmin - t0) / deltat_cf))
for tr in trs_selected
],
dtype=num.int32)
w = ifc.get_weights(nsls_selected)
weights = num.ones((ngridpoints, nstations_selected))
weights *= w[num.newaxis, :]
weights *= ifc.weight
shift_table = shift_tables[iifc]
ok = num.isfinite(shift_table[:, istations_selected])
bad = num.logical_not(ok)
shifts = -num.round(shift_table[:, istations_selected] /
deltat_cf).astype(num.int32)
weights[bad] = 0.0
shifts[bad] = num.max(shifts[ok])
pdata.append((list(trs_selected), shift_table, ifc))
parstack_params.append((arrays, offsets, shifts, weights))
if config.stacking_blocksize is not None:
ipstep = config.stacking_blocksize
frames = None
else:
ipstep = lengthout
frames = num.zeros((ngridpoints, lengthout))
twall_start = time.time()
frame_maxs = num.zeros(lengthout)
frame_argmaxs = num.zeros(lengthout, dtype=num.int)
ipmin = iwmin
while ipmin < iwmin + lengthout:
ipsize = min(ipstep, iwmin + lengthout - ipmin)
if ipstep == lengthout:
frames_p = frames
else:
frames_p = num.zeros((ngridpoints, ipsize))
for (arrays, offsets, shifts, weights) in parstack_params:
frames_p, _ = parstack(arrays,
offsets,
shifts,
weights,
0,
offsetout=ipmin,
lengthout=ipsize,
result=frames_p,
nparallel=nparallel,
impl='openmp')
if config.sharpness_normalization:
frame_p_maxs = frames_p.max(axis=0)
frame_p_means = num.abs(frames_p).mean(axis=0)
frames_p *= (frame_p_maxs / frame_p_means)[num.newaxis, :]
frames_p *= norm_map[:, num.newaxis]
if config.ifc_count_normalization:
frames_p *= 1.0 / len(ifcs)
frame_maxs[ipmin-iwmin:ipmin-iwmin+ipsize] = \
frames_p.max(axis=0)
frame_argmaxs[ipmin-iwmin:ipmin-iwmin+ipsize] = \
pargmax(frames_p)
ipmin += ipstep
del frames_p
twall_end = time.time()
logger.info('wallclock time for stacking: %g s' %
(twall_end - twall_start))
tmin_frames = t0 + iwmin * deltat_cf
tr_stackmax = trace.Trace('',
'SMAX',
'',
'',
tmin=tmin_frames,
deltat=deltat_cf,
ydata=frame_maxs)
tr_stackmax.meta = {'tabu': True}
trs_debug.append(tr_stackmax)
if show_window_traces:
trace.snuffle(trs_debug)
ydata_window = tr_stackmax.chop(wmin, wmax,
inplace=False).get_ydata()
logger.info('CF stats: min %g, max %g, median %g' %
(num.min(ydata_window), num.max(ydata_window),
num.median(ydata_window)))
if nstations_selected != 17:
logger.info(
'Warning, station outage detected! Nr of station operable: %s'
% nstations_selected)
detector_threshold_seiger = config.detector_threshold - (
(17 - nstations_selected) * 4
) # 17 is maximum number of seiger stations, 4 is a mean baseline for noise
if nstations_selected != 17:
logger.info(
'Warning, station outage detected! Nr of station operable: %s, threshold now: %s'
% (nstations_selected, detector_threshold_seiger))
tpeaks, apeaks = list(
zip(*[(tpeak, apeak) for (tpeak, apeak) in zip(
*tr_stackmax.peaks(detector_threshold_seiger, tpeaksearch))
if wmin <= tpeak and tpeak < wmax])) or ([], [])
tr_stackmax_indx = tr_stackmax.copy(data=False)
tr_stackmax_indx.set_ydata(frame_argmaxs.astype(num.int32))
tr_stackmax_indx.set_location('i')
for (tpeak, apeak) in zip(tpeaks, apeaks):
iframe = int(round((tpeak - tmin_frames) / deltat_cf))
imax = frame_argmaxs[iframe]
latpeak, lonpeak, xpeak, ypeak, zpeak = \
grid.index_to_location(imax)
idetection += 1
detection = Detection(id='%06i' % idetection,
time=tpeak,
location=geo.Point(lat=float(latpeak),
lon=float(lonpeak),
x=float(xpeak),
y=float(ypeak),
z=float(zpeak)),
ifm=float(apeak))
if bark:
common.bark()
logger.info('detection found: %s' % str(detection))
f = open(detections_path, 'a')
f.write(
'%06i %s %g %g %g %g %g %g\n' %
(idetection,
util.time_to_str(tpeak, format='%Y-%m-%d %H:%M:%S.6FRAC'),
apeak, latpeak, lonpeak, xpeak, ypeak, zpeak))
f.close()
ev = detection.get_event()
f = open(events_path, 'a')
model.dump_events([ev], stream=f)
f.close()
if show_detections or config.save_figures:
fmin = min(ifc.fmin for ifc in ifcs)
fmax = min(ifc.fmax for ifc in ifcs)
fn = figures_path_template % {
'id': util.tts(t0).replace(" ", "T"),
'format': 'png'
}
util.ensuredirs(fn)
if frames is not None:
frames_p = frames
tmin_frames_p = tmin_frames
iframe_p = iframe
else:
iframe_min = max(
0, int(round(iframe - tpeaksearch / deltat_cf)))
iframe_max = min(
lengthout - 1,
int(round(iframe + tpeaksearch / deltat_cf)))
ipsize = iframe_max - iframe_min + 1
frames_p = num.zeros((ngridpoints, ipsize))
tmin_frames_p = tmin_frames + iframe_min * deltat_cf
iframe_p = iframe - iframe_min
for (arrays, offsets, shifts, weights) \
in parstack_params:
frames_p, _ = parstack(arrays,
offsets,
shifts,
weights,
0,
offsetout=iwmin +
iframe_min,
lengthout=ipsize,
result=frames_p,
nparallel=nparallel,
impl='openmp')
if config.sharpness_normalization:
frame_p_maxs = frames_p.max(axis=0)
frame_p_means = num.abs(frames_p).mean(axis=0)
frames_p *= (frame_p_maxs /
frame_p_means)[num.newaxis, :]
frames_p *= norm_map[:, num.newaxis]
if config.ifc_count_normalization:
frames_p *= 1.0 / len(ifcs)
try:
plot.plot_detection(grid,
receivers,
frames_p,
tmin_frames_p,
deltat_cf,
imax,
iframe_p,
xpeak,
ypeak,
zpeak,
tr_stackmax,
tpeaks,
apeaks,
detector_threshold_seiger,
wmin,
wmax,
pdata,
trs,
fmin,
fmax,
idetection,
tpeaksearch,
movie=show_movie,
show=show_detections,
save_filename=fn,
event=ev)
except:
pass
del frames_p
if stop_after_first:
return
tr_stackmax.chop(wmin, wmax)
tr_stackmax_indx.chop(wmin, wmax)
if save_imax is True:
io.save([tr_stackmax, tr_stackmax_indx], ifm_path_template)
del frames
logger.info('end processing time window group: %s - %s' %
(util.time_to_str(tmin_win), util.time_to_str(tmax_win)))
cat = Catalog()
files = glob("%s/../figures/*qml*" % run_path)
files.sort(key=os.path.getmtime)
for file in files:
cat_read = read_events(file)
for event in cat_read:
cat.append(event)
cat.write("%s/../all_events_stacking.qml" % run_path, format="QUAKEML")
def call(self):
'''Main work routine of the snuffling.'''
self.cleanup()
viewer = self.get_viewer()
figs = {}
fig_width_inch = viewer.width()
npixel_hori = float(fig_width_inch * 50)
xminutes = int(self.xminutes)
xseconds = xminutes * 60
self.nhours = 24
nrows = int(self.nhours) * 60 / xminutes
ynormalizations = {}
lines_data = {}
for traces in self.chopper_selected_traces(tinc=60 * 60,
fallback=True):
for tr in traces:
t0 = util.day_start(tr.tmin)
key = (tr.nslc_id, t0)
if key not in figs:
fig = self.pylab(get='figure')
ax = fig.add_subplot(111)
figs[key] = (fig, ax)
ynormalizations[key] = 0
lines_data[key] = []
tr = tr.copy(data=True)
ndecimate = int((xseconds / tr.deltat) / npixel_hori)
tr.downsample(ndecimate)
if self.prescale == 'max':
ynormalizations[key] = max(num.max(tr.ydata),
ynormalizations[key])
else:
ynormalizations[key] = max(num.std(tr.ydata),
ynormalizations[key])
if viewer.highpass:
tr.highpass(4, viewer.highpass)
if viewer.lowpass and 1. / tr.deltat > 2. * viewer.lowpass:
tr.lowpass(4, viewer.lowpass)
t = tr.get_xdata() - t0
y = num.asarray(tr.get_ydata(), dtype=num.float)
nskip = t / 3600.
x = t % xseconds
xdiff = num.diff(x)
itmp = num.where(
num.logical_or(xdiff < 0,
num.abs(xdiff - tr.deltat) > 1E-4))[0]
indices = num.zeros(len(itmp) + 2, dtype=num.int)
indices[1:-1] = itmp
indices[-1] = len(y) - 1
for i in range(len(indices) - 1):
istart = indices[i] + 1
istop = indices[i + 1]
lines_data[key].append(
(t0, x[istart:istop], y[istart:istop],
nskip[istart:istop]))
ynorm = None
if self.scale_global:
ynorm = max(ynormalizations.values())
for key, lines in lines_data.items():
if not self.scale_global:
ynorm = float(ynormalizations.get(key, 1.))
for (t0, x, y, shifts) in lines:
fig, ax = figs[key]
ax.plot(x / 60.,
y / (ynorm / self.yscale) + shifts,
color='black')
ax.set_title(util.tts(t0, format='%Y-%m-%d'))
yticks = range(0, self.nhours + 2, 2)
xticks = range(0, xminutes + 1, 1)
for key, (fig, ax) in figs.items():
ax.set_xlim(0, xminutes)
ax.set_ylabel('Hour')
ax.set_xlabel('Minute')
ax.yaxis.set_ticks(yticks)
ax.xaxis.set_ticks(xticks)
ax.set_ylim(-0.1, 24.1)
fig.canvas.draw()
def call(self):
'''Main work routine of the snuffling.'''
self.cleanup()
viewer = self.get_viewer()
figs = {}
fig_width_inch = viewer.width()
npixel_hori = float(fig_width_inch*50)
xminutes = int(self.xminutes)
xseconds = xminutes * 60
self.nhours = 24
nrows = int(self.nhours) * 60 / xminutes
ynormalizations = {}
lines_data = {}
for traces in self.chopper_selected_traces(tinc=60*60, fallback=True):
for tr in traces:
t0 = util.day_start(tr.tmin)
key = (tr.nslc_id, t0)
if key not in figs:
fig = self.pylab(get='figure')
ax = fig.add_subplot(111)
figs[key] = (fig, ax)
ynormalizations[key] = 0
lines_data[key] = []
tr = tr.copy(data=True)
ndecimate = int((xseconds/tr.deltat) / npixel_hori)
tr.downsample(ndecimate)
if self.prescale == 'max':
ynormalizations[key] = max(num.max(tr.ydata), ynormalizations[key])
else:
ynormalizations[key] = max(num.std(tr.ydata), ynormalizations[key])
if viewer.highpass:
tr.highpass(4, viewer.highpass)
if viewer.lowpass and 1./tr.deltat>2.*viewer.lowpass:
tr.lowpass(4, viewer.lowpass)
t = tr.get_xdata() - t0
y = num.asarray(tr.get_ydata(), dtype=num.float)
nskip = t / 3600.
x = t % xseconds
xdiff = num.diff(x)
itmp = num.where(num.logical_or(xdiff < 0, num.abs(xdiff-tr.deltat) > 1E-4))[0]
indices = num.zeros(len(itmp)+2, dtype=num.int)
indices[1:-1] = itmp
indices[-1] = len(y)-1
for i in range(len(indices)-1):
istart = indices[i] + 1
istop = indices[i+1]
lines_data[key].append(
(t0, x[istart: istop], y[istart: istop],
nskip[istart: istop])
)
ynorm = None
if self.scale_global:
ynorm = max(ynormalizations.values())
for key, lines in lines_data.items():
if not self.scale_global:
ynorm = float(ynormalizations.get(key, 1.))
for (t0, x, y, shifts) in lines:
fig, ax = figs[key]
ax.plot(
x/60.,
y/(ynorm/self.yscale) + shifts,
color='black')
ax.set_title(util.tts(t0, format='%Y-%m-%d'))
yticks = range(0, self.nhours+2, 2)
xticks = range(0, xminutes+1, 1)
for key, (fig, ax) in figs.items():
ax.set_xlim(0, xminutes)
ax.set_ylabel('Hour')
ax.set_xlabel('Minute')
ax.yaxis.set_ticks(yticks)
ax.xaxis.set_ticks(xticks)
ax.set_ylim(-0.1, 24.1)
fig.canvas.draw()
def call(self):
self.cleanup()
viewer = self.get_viewer()
vtmin, vtmax = viewer.get_time_range()
pile = self.get_pile()
traces = [
tr for tr in pile.chopper(
tmin=vtmin, tmax=vtmax, trace_selector=viewer.trace_selector)]
event, stations = self.get_active_event_and_stations()
traces = [tr for trs in traces for tr in trs]
stations_by_nsl = {s.nsl(): s for s in self.get_stations()}
stations = [
stations_by_nsl.get(station_key(tr), None) for tr in traces]
distances = [
ortho.distance_accurate50m(event, s) for s in stations if
s is not None]
distances = [d/1000. for d in distances]
maxd = max(distances)
mind = min(distances)
distances = dict(zip([s.nsl() for s in stations], distances))
matching_traces = [x for x in traces if util.match_nslc(
self.get_station_patterns(stations), x.nslc_id)]
if self.add_markers:
markers = self.get_markers()
markers = [
m for m in markers if m.tmax <= vtmax and
m.tmin >= vtmin and m.selected]
markers = dict(zip([tuple(m.nslc_ids) for m in markers], markers))
if self.fig is None or self.fframe.closed or not self._live_update:
self.fframe = self.pylab(get='figure_frame')
self.fig = self.fframe.gcf()
if self._live_update:
self.fig.clf()
ymin = mind-0.06*(maxd-mind)
ymax = maxd+0.06*(maxd-mind)
ax = self.fig.add_subplot(111)
xmin = 9E9
xmax = -xmin
texts = []
manual_scale = 0.1 * (maxd-mind)*self.yscale
if self.ampl_scaler == 'total min/max':
max_trace = max(
matching_traces, key=lambda x: max(abs(x.get_ydata())))
tr_maxy = max(abs(max_trace.get_ydata()))
ampl_scale = float(tr_maxy)
for tr in matching_traces:
if viewer.highpass:
tr.highpass(4, viewer.highpass)
if viewer.lowpass:
tr.lowpass(4, viewer.lowpass)
if tr.nslc_id[:3] not in distances.keys():
continue
if self.t_red:
red = distances[tr.nslc_id[:3]]/self.t_red
else:
red = 0.
y_pos = distances[tr.nslc_id[:3]]
xdata = tr.get_xdata()-red-event.time
xmin = min(xmin, min(xdata))
xmax = max(xmax, max(xdata))
tr_ydata = tr.get_ydata()
if self.ampl_scaler == 'trace min/max':
ampl_scale = float(max(abs(tr_ydata)))
elif self.ampl_scaler == 'standard deviation':
ampl_scale = float(num.std(tr_ydata))
ydata = (tr_ydata/ampl_scale * manual_scale) + y_pos
ax.plot(xdata, ydata, c='black', linewidth=0.2)
if self.fill_between:
ax.fill_between(
xdata, y_pos, ydata, where=ydata > y_pos, color='black',
alpha=0.5)
texts.append(
ax.text(
xmax, y_pos, '%s.%s.%s.%s' % tr.nslc_id,
horizontalalignment='right', fontsize=6.))
if self.add_markers:
for ids, m in markers.items():
if m.match_nslc(tr.nslc_id) or ids == ():
c = m.select_color(m.color_b)
c = [ci/255. for ci in c]
t = m.tmin
x = [t-red-event.time, t-red-event.time]
y = [y_pos-(maxd-mind)*0.025, y_pos+(maxd-mind)*0.025]
ax.plot(x, y, linewidth=1, color=c)
label = m.get_label()
if not label:
label = ''
ax.text(x[1]-x[1]*0.005, y[1], label, color=c,
fontsize=6,
verticalalignment='top',
horizontalalignment='right')
for txt in texts:
txt.set_x(xmax)
vred_str = '= '+str(round(self.t_red, 2)) + 'km/s' if self.t_red \
else 'off'
ax.text(0.5, 0.01, 'time window: %s - %s | Reduction velocity %s' %
(util.tts(vtmin), util.tts(vtmax), vred_str),
verticalalignment='bottom', horizontalalignment='center',
transform=self.fig.transFigure)
ax.set_ylim([ymin, ymax])
ax.set_xlim([xmin, xmax])
ax.set_ylabel('Distance [km]')
ax.set_xlabel('(red.) Time [s]')
self.fig.canvas.draw()
def tts(t):
if t is None:
return '?'
else:
return util.tts(t, format='%Y-%m-%d')
def tts(t):
if t is None:
return '?'
else:
return util.tts(t, format='%Y-%m-%d')
def load_data_archieve(validation_data,
gf_freq,
duration=4,
wanted_start=None,
wanted_end=None):
folder = validation_data
pathlist = Path(folder).glob('day*')
waveforms = []
stations = []
if wanted_start is not None:
try:
wanted_start = util.stt(wanted_start)
wanted_end = util.stt(wanted_end)
except:
pass
from pyrocko import pile
paths = []
safecon = 0
for path in sorted(pathlist):
path = str(path)
d2 = float(str(path)[-12:])
d1 = float(str(path)[-25:-13])
if wanted_start is not None:
do_safety_files = False
if (d1 >= wanted_start
and d2 <= wanted_end) or (d2 - wanted_end < 86400.
and d2 - wanted_end > 0.
and safecon == 0):
st = model.load_stations(path + "/waveforms/stations.raw.txt")
d_diff = d2 - d1
tr_packages = int(d_diff / duration)
#for tr in traces:
# tr.downsample_to(gf_freq)
# if safecon == 0:
pathlist_waveform_files = Path(path + "/waveforms/rest/").glob(
'*.mseed')
wanted_start_str = util.tts(wanted_start)[14:16]
diff_to_full = float(wanted_start_str)
max_diff = 55.
min_diff = 5.
if diff_to_full > max_diff or diff_to_full < min_diff:
do_safety_files = True
for path_wave in sorted(pathlist_waveform_files):
path_wave = str(path_wave)
p1 = path_wave[-25:-15]
p2 = path_wave[-14:-12]
p3 = path_wave[-11:-9]
p4 = path_wave[-8:-6]
try:
file_time = util.stt(p1 + " " + p2 + ":" + p3 + ":" +
p4)
tdiff = file_time - wanted_start
if do_safety_files is True:
if float(p2) - float(
util.tts(wanted_start)[11:13]) == 0:
paths.append(str(path_wave))
if diff_to_full > max_diff and float(p2) - float(
util.tts(wanted_start)[11:13]) == 1.:
paths.append(str(path_wave))
if diff_to_full < min_diff and float(p2) - float(
util.tts(wanted_start)[11:13]) == -1.:
paths.append(str(path_wave))
else:
if float(p2) - float(
util.tts(wanted_start)[11:13]) == 0:
paths.append(str(path_wave))
except:
pass
safecon += 1
p = pile.make_pile(paths)
for traces in p.chopper(tmin=wanted_start, tinc=duration):
if traces:
if traces[0].tmax < wanted_end:
# for i in range(0, tr_packages):
# traces = traces
#for tr in traces:
# tr.chop(tr.tmin+i*duration,
# tr.tmin+i*duration+duration)
#tr.downsample_to(gf_freq)
waveforms.append(traces)
stations.append(st)
# else:
# traces = io.load(path+"/waveforms/rest/traces.mseed")
# st = model.load_stations(path+"/waveforms/stations.raw.txt")
# for tr in traces:
# tr.downsample_to(gf_freq)
# waveforms.append(traces)
# stations.append(st)
return waveforms, stations
