def save_all(events, eventsclusters, clusters, conf, resdir):
'''
Save all results of the clustering analysis
'''
# save clustered events
fn = os.path.join(resdir, 'clustered_events.pf')
if os.path.isfile(fn):
os.remove(fn)
for iev, ev in enumerate(events):
tag = 'cluster:' + str(eventsclusters[iev])
if ev.tags is not None:
ev.tags.append(tag)
else:
ev.tags = [tag]
model.dump_events(events, fn)
# save events of each cluster
for cluster_id in clusters:
wished_events = []
fn = os.path.join(resdir, 'cluster.' + str(cluster_id) + '.events.pf')
for iev, evcl in enumerate(eventsclusters):
if evcl == cluster_id:
wished_events.append(events[iev])
model.dump_events(wished_events, fn)
# save clusters
fn = os.path.join(resdir, 'processed.clusters')
save_obj(clusters, fn)
# save eventsclusters
fn = os.path.join(resdir, 'processed.eventsclusters')
save_obj(eventsclusters, fn)
def dump(x, gm, indices):
if type == 'vector':
print(' ',
' '.join('%16.7g' % problem.extract(x, i) for i in indices),
'%16.7g' % gm,
file=out)
elif type == 'source':
source = problem.get_source(x)
if effective_lat_lon:
source.set_origin(*source.effective_latlon)
guts.dump(source, stream=out)
elif type == 'event':
ev = problem.get_source(x).pyrocko_event()
if effective_lat_lon:
ev.set_origin(*ev.effective_latlon)
model.dump_events([ev], stream=out)
elif type == 'event-yaml':
ev = problem.get_source(x).pyrocko_event()
if effective_lat_lon:
ev.set_origin(*ev.effective_latlon)
guts.dump_all([ev], stream=out)
else:
raise GrondError('Invalid argument: type=%s' % repr(type))
def testEventExtras(self):
tempdir = self.make_tempdir()
eextra = model.Event(lat=12., lon=12.)
data = [
(dict(i=1, f=1.0, n=None, b=True, s='abc', e=eextra), None),
({1: 'abc'}, guts.ValidationError),
({'e': model.Event(lat=1, lon=1)}, guts.ValidationError)]
for d, exc in data:
ev1 = model.Event(
lat=10.,
lon=11.,
depth=4000.,
magnitude=5.,
extras=d)
fn = pjoin(tempdir, 'test.events')
with self.assertRaises(model.EventExtrasDumpError):
model.dump_events([ev1], fn)
if exc is None:
ev1.validate()
ev2 = guts.load(string=ev1.dump())
for k in d:
assert isinstance(ev2.extras[k], type(d[k]))
else:
with self.assertRaises(exc):
ev1.validate()
def call(self):
markers = self.get_selected_event_markers()
events = [m.get_event() for m in markers]
if len(events) == 0:
self.fail('no events found')
out_filename = self.output_filename('Template for output files')
model.dump_events(events, filename=out_filename)
def call(self):
markers = self.get_selected_event_markers()
events = [m.get_event() for m in markers]
if len(events) == 0:
self.fail('no events found')
out_filename = self.output_filename('Template for output files')
model.dump_events(events, filename=out_filename)
def save(synthetic_traces, event, stations, savedir, noise_events=False):
model.dump_stations(stations, savedir + 'model.txt')
io.save(synthetic_traces, savedir + 'traces.mseed')
model.dump_events(event, savedir + 'event.txt')
model.dump_stations(stations, savedir + 'stations.pf')
st_xml = stationxml.FDSNStationXML.from_pyrocko_stations(
stations, add_flat_responses_from='M')
st_xml.dump_xml(filename=savedir + 'stations.xml')
if noise_events is not False:
model.dump_events(noise_events, savedir + 'events_noise.txt')
def command_init(args):
'''
Execution of command init
'''
def setup(parser):
parser.add_option('--force',
dest='force',
action='store_true',
help='overwrite existing project directory')
parser, options, args = cl_parse('init', args, setup)
if len(args) != 1:
help_and_die(parser, 'missing argument')
else:
fn_config = args[0]
if not os.path.isfile(fn_config):
die('config file missing: %s' % fn_config)
conf = load(filename=fn_config)
config.check(conf)
if ((not options.force) and (os.path.isdir(conf.project_dir))):
die('project dir exists: %s; use force option' % conf.project_dir)
else:
if os.path.isdir(conf.project_dir):
shutil.rmtree(conf.project_dir)
os.mkdir(conf.project_dir)
conf.dump(filename=os.path.join(conf.project_dir, 'seiscloud.config'))
dst = os.path.join(conf.project_dir, 'catalog.pf')
if conf.catalog_origin == 'file':
src = conf.catalog_fn
shutil.copyfile(src, dst)
else:
if conf.catalog_origin == 'globalcmt':
orig_catalog = catalog.GlobalCMT()
else: # geofon
orig_catalog = catalog.Geofon()
events = orig_catalog.get_events(time_range=(util.str_to_time(
conf.tmin), util.str_to_time(conf.tmax)),
magmin=conf.magmin,
latmin=conf.latmin,
latmax=conf.latmax,
lonmin=conf.lonmin,
lonmax=conf.lonmax)
selevents = [ev for ev in events if ev.magnitude <= conf.magmax]
model.dump_events(selevents, dst)
print('Project directory prepared "%s"' % conf.project_dir)
def save_all(events,eventsclusters,clusters,conf,resdir):
'''
Save all results of the clustering analysis
'''
# save events of each cluster
for cluster_id in clusters:
wished_events=[]
fn=os.path.join(resdir,'cluster.'+str(cluster_id)+'.events.pf')
for iev,evcl in enumerate(eventsclusters):
if evcl==cluster_id:
wished_events.append(events[iev])
model.dump_events(wished_events,fn)
# save clusters
fn=os.path.join(resdir,'processed.clusters')
save_obj(clusters, fn)
# save eventsclusters
fn=os.path.join(resdir,'processed.eventsclusters')
save_obj(eventsclusters, fn)
from pyrocko.client import fdsn
from pyrocko import util, io, trace, model
from pyrocko.io import quakeml
tmin = util.stt('2014-01-01 16:10:00.000')
tmax = util.stt('2014-01-01 16:39:59.000')
# request events at IRIS for the given time span
request_event = fdsn.event(site='iris', starttime=tmin, endtime=tmax)
# parse QuakeML and extract pyrocko events
events = quakeml.QuakeML.load_xml(request_event).get_pyrocko_events()
model.dump_events(events, 'iris-events.pf')
# select stations by their NSLC id and wildcards (asterisk) for waveform
# download
selection = [
('*', 'HMDT', '*', '*', tmin, tmax), # all available components
('GE', 'EIL', '*', '*Z', tmin, tmax), # all vertical components
]
# Restricted access token
# token = open('token.asc', 'rb').read()
# request_waveform = fdsn.dataselect(site='geofon', selection=selection,
# token=token)
# setup a waveform data request
request_waveform = fdsn.dataselect(site='geofon', selection=selection)
# write the incoming data stream to 'traces.mseed'
with open('traces.mseed', 'wb') as file:
from pyrocko import util, model
from pyrocko.client import catalog
tmin = util.str_to_time ('2017-01-02 13:00:00')
tmax = util.str_to_time ('2017-01-02 14:00:00')
# create an instance of the global CMT catalog
global_cmt_catalog = catalog.GlobalCMT()
# query the catalog
events = global_cmt_catalog.get_events(
time_range=(tmin, tmax),
magmin=4.0,
latmin=-5.0,
latmax=-4.0,
lonmin=-77,
lonmax=-76)
# dump events to catalog
model.dump_events(events, 'GCMT.EQ.txt')
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")
phasename=phasename,
event=event)
picks.append(m)
progbar.update(i)
progbar.finish()
with open(fn, 'w') as f:
f.write(datastr)
gui_util.save_markers(picks, 'picks.pf')
def reduce_stf(self, event, t):
t -= self.interp_stf(event.magnitude)/2.
return t
if __name__=='__main__':
stations = model.load_stations('/media/usb/webnet/meta/stations.pf')
events = []
for efile in glob.glob('/home/marius/src/swarming/unperturbed/*/event.pf'):
events.append(model.Event(load=efile))
#events = model.load_events('/home/marius/src/swarming/events_swarm.pf')
want_phases = {'p':('p', 'P'), 's':('s', 'S')}
e = LocalEngine(use_config=True)
s = e.get_store('vogtland_fischer_horalek_2000_vpvs169_minus4p')
m = s.config.earthmodel_1d
b = Bakery(stations=stations,
events=events,
wanted_phases=want_phases,
model=m)
model.dump_events(events, 'dumped_catalog.pf')
b.run_n_write('picks.dat')
with open(fn, 'r') as f:
# windows empty line separation
events = f.read().split('\r\n\r\n')
py_events = []
pattern = re.compile(r'((?P<mid>\D{3}\d{2}) (?P<t>\d{6}.\d) (?P<place>\D*\(\d{3}\)) (?P<lat>\d{2}.\d{2})N (?P<lon>\d{2}.\d{2})E h=(?P<depth>\d*)km mb=(?P<mb>\d.\d)', flags=re.IGNORECASE)
for e in events:
m = pattern.findall(e)
if m:
groupdict = m.groupdict()
t = groupdict['t']
#mb = groupdict['mb']
#mw = groupdict['mw']
#print '...................'
#print mb
#print mw
date_str = '%s-%s-%s %s:%s:%s' % (year, month, groupdict['mid'][3:],
t[0:2], t[2:4], t[4:])
t = str_to_time(date_str)
py_events.append(Event(name=groupdict['place'],
time=t,
lat=float(groupdict['lat']),
lon=float(groupdict['lon']),
depth=float(groupdict['depth'])))
else:
#print 'skipping ', e
continue
dump_events(py_events, 'events_crawled.pf')
from pyrocko import util, model
from pyrocko.client import catalog
tmin = util.str_to_time('2011-01-01 00:00:00') # beginning time of query
tmax = util.str_to_time('2011-12-31 23:59:59')
# create an instance of the global CMT catalog
global_cmt_catalog = catalog.GlobalCMT()
# query the catalog
events = global_cmt_catalog.get_events(
time_range=(tmin, tmax),
magmin=2.,
latmin=-35.,
latmax=-20.,
lonmin=-76.,
lonmax=-65.)
print('Downloaded %s events' % len(events))
print('The last one is:')
print(events[-1])
# dump events to catalog
model.dump_events(events, 'northern_chile_events.txt')
mechanisms=mechanisms,
magnitudes=magnitudes,
stf=stf)
# setup stations/targets:
#stats = load_stations(webnet+'/meta/stations.pf')
stats = load_stations('stations.pf')
#stats = []
# Scrutinize the swarm using matplotlib
noise = Noise(files='/media/usb/webnet/mseed/2008')
# convert loaded stations to targets (see function at the top).
#targets = guess_targets_from_stations(stats)
targets = get_targets(stations, noise.data_pile, store_id=store_id)
Visualizer(swarm, stats)
# Processing that data will return a pyrocko.gf.seismosizer.Reponse object.
response = engine.process(sources=swarm.get_sources(),
targets=targets)
# Save the events
dump_events(swarm.get_events(), 'events_swarm.pf')
io.save(response.pyrocko_traces(), 'swarm.mseed')
convolved_traces = stf.post_process(response)
# Save traces:
io.save(convolved_traces.traces_list(), 'swarm_stf.mseed')
def report(env,
report_config=None,
update_without_plotting=True,
make_index=True,
make_archive=True,
nthreads=0):
if report_config is None:
report_config = ReportConfig()
report_config.set_basepath('.')
event_name = env.get_current_event_name()
logger.info('Creating report entry for run "%s"...' % event_name)
fp = report_config.expand_path
entry_path = expand_template(
op.join(fp(report_config.report_base_path),
report_config.entries_sub_path),
dict(event_name=event_name, problem_name=event_name))
if op.exists(entry_path) and not update_without_plotting:
shutil.rmtree(entry_path)
util.ensuredir(entry_path)
plots_dir_out = op.join(entry_path, 'plots')
util.ensuredir(plots_dir_out)
configs_dir = op.join(op.split(__file__)[0], 'app/configs/')
rundir_path = env.get_rundir_path()
try:
os.system("cp -r %s/grun/plots/* %s" % (rundir_path, plots_dir_out))
except:
pass
os.system("cp %s/plot_collection.yaml %s" % (configs_dir, plots_dir_out))
util.ensuredir("%s/shakemap/default/" % (plots_dir_out))
os.system(
"cp %s/*shakemap.png %s/shakemap/default/shakemap.default.gf_shakemap.d100.png"
% (rundir_path, plots_dir_out))
os.system("cp %s/shakemap.default.plot_group.yaml %s/shakemap/default/" %
(configs_dir, plots_dir_out))
util.ensuredir("%s/location/default/" % (plots_dir_out))
os.system(
"cp %s/*location.png %s/location/default/location.default.location.d100.png"
% (rundir_path, plots_dir_out))
os.system("cp %s/location.default.plot_group.yaml %s/location/default/" %
(configs_dir, plots_dir_out))
util.ensuredir("%s/production_data/default/" % (plots_dir_out))
os.system(
"cp %s/*production_data.png %s/production_data/default/production_data.default.production_data.d100.png"
% (rundir_path, plots_dir_out))
os.system(
"cp %s/production_data.default.plot_group.yaml %s/production_data/default/"
% (configs_dir, plots_dir_out))
util.ensuredir("%s/waveforms/default/" % (plots_dir_out))
os.system(
"cp %s/waveforms_1.png %s/waveforms/default/waveforms.default.waveforms_1.d100.png"
% (rundir_path, plots_dir_out))
os.system(
"cp %s/waveforms_2.png %s/waveforms/default/waveforms.default.waveforms_2.d100.png"
% (rundir_path, plots_dir_out))
os.system(
"cp %s/waveforms_3.png %s/waveforms/default/waveforms.default.waveforms_3.d100.png"
% (rundir_path, plots_dir_out))
os.system("cp %s/waveforms.default.plot_group.yaml %s/waveforms/default/" %
(configs_dir, plots_dir_out))
os.system("cp %s/grun/config.yaml %s/config.yaml" %
(rundir_path, entry_path))
try:
event = model.load_events(rundir_path + "event.txt")
model.dump_events(event,
filename=op.join(entry_path, 'event_reference.yaml'),
format="yaml")
event = event[0]
from silvertine import plot
pcc = report_config.plot_config_collection.get_weeded(env)
plot.make_plots(env,
plots_path=op.join(entry_path, 'plots'),
plot_config_collection=pcc)
try:
run_info = env.get_run_info()
except environment.NoRundirAvailable:
run_info = None
rie = ReportIndexEntry(path='.',
problem_name=event_name,
silvertine_version="0.01",
run_info=run_info)
fn = op.join(entry_path, 'event_reference.yaml')
if op.exists(fn):
rie.event_best = guts.load(filename=fn)
fn = op.join(entry_path, 'event_reference.yaml')
if op.exists(fn):
rie.event_reference = guts.load(filename=fn)
fn = op.join(entry_path, 'index.yaml')
guts.dump(rie, filename=fn)
logger.info('Done creating report entry for run "%s".' % "test")
# report_index(report_config)
# if make_archive:
# report_archive(report_config)
except FileNotFoundError:
pass
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))
Origin = C.parseConfig('origin')
Conf = globalConf()
Config = C.parseConfig('config')
filter = FilterCfg(Config)
cfg = ConfigObj(dict=Config)
minDist, maxDist = cfg.FloatRange('mindist', 'maxdist')
ev = Event(Origin['lat'],Origin['lon'],Origin['depth'],Origin['time'] )
event = model.Event(lat=float(ev.lat), lon=float(ev.lon), depth=float(ev.depth)*1000., time=util.str_to_time(ev.time))
newFreq = float(filter.newFrequency())
options.time = Origin ['time']
options.duration = int(Conf['duration'])
sdspath = os.path.join(options.eventpath,'data')
model.dump_events([event], sdspath+'event.pf')
tmin = util.str_to_time(ev.time)-600.
tmax = util.str_to_time(ev.time)+1800.
def get_stations(site, lat, lon, rmin, rmax, tmin, tmax, channel_pattern='BH*'):
extra = {}
if site == 'iris':
extra.update(matchtimeseries=True)
sx = fdsn.station(
site=site, latitude=lat, longitude=lon,
minradius=rmin, maxradius=rmax,
startbefore=tmin, endafter=tmax, channel=channel_pattern,
format='text', level='channel', includerestricted=False)
str(eml.lon),
str(eml.depth),
str(eml.magnitude),
str(emw.magnitude)
])
event_params.append([
str(util.tts(eml.time)),
str(eml.time),
str(eml.lat),
str(eml.lon),
str(eml.depth),
str(eml.magnitude),
str(emw.magnitude)
])
model.dump_events(land_events, "landau_events.pf")
model.dump_events(ins_events, "ins_events.pf")
with open('seiger_catalog_alpha.csv', 'w', newline='') as csvfile:
spamwriter = csv.writer(csvfile,
delimiter=',',
quotechar='"',
quoting=csv.QUOTE_MINIMAL)
spamwriter.writerow(
["Time", "Time(s)unix time", "Lat", "Lon", "Tiefe", "Ml", "Mw"])
for p in event_params:
spamwriter.writerow(p)
with open('seiger_catalog_alpha_landau.csv', 'w', newline='') as csvfile:
spamwriter = csv.writer(csvfile,
delimiter=',',
"mt3",
"mt4",
"mt5",
"dc?",
"_",
"_",
]
order_mapping = dict(zip(order, range(len(order))))
wanted = ["name", "lat", "lon", "depth"]
events = []
with open(fn, "r") as f:
for line in f.readlines():
data = line.split()
kwargs = {}
for kw in wanted:
val = data[order_mapping[kw]]
val = float(val) if kw is not "name" else val
val = float(val) * 1000.0 if kw is "depth" else val
kwargs.update({kw: val})
time = str_to_time("%s %s" % (data[order_mapping["date"]].replace("/", "-"), data[order_mapping["time"]]))
kwargs.update({"time": time})
m = num.array([num.float(data[order_mapping["mt%i" % i]]) for i in range(6)])
mt = MomentTensor(m=symmat6(*m) * float(data[order_mapping["moment"]]))
kwargs.update({"moment_tensor": mt})
e = Event(**kwargs)
events.append(e)
dump_events(events, "events2008_mt.pf")
def command_matrix(args):
'''
Execution of command matrix
'''
def setup(parser):
parser.add_option('--force',
dest='force',
action='store_true',
help='overwrite existing project directory')
parser.add_option('--view',
dest='view',
action='store_true',
help='view similarity matrix')
parser.add_option('--savefig',
dest='savefig',
action='store_true',
help='save figure of similarity matrix')
parser, options, args = cl_parse('matrix', args, setup)
if len(args) != 1:
help_and_die(parser, 'missing argument')
else:
fn_config = args[0]
if not os.path.isfile(fn_config):
die('config file missing: %s' % fn_config)
conf = load(filename=fn_config)
config.check(conf)
if not os.path.isdir(conf.project_dir):
die('project directory missing: %s' % conf.project_dir)
simmat_temporal_fn = os.path.join(conf.project_dir, 'simmat_temporal.npy')
if ((not options.force) and (os.path.isfile(simmat_temporal_fn))):
die('similarity matrix exists: %s; use force option' %
simmat_temporal_fn)
catalog_ref_fn = os.path.join(conf.project_dir, 'catalog.pf')
if os.path.isfile(catalog_ref_fn):
allevents = model.load_events(catalog_ref_fn)
else:
die('catalog missing: %s' % catalog_ref_fn)
if conf.sw_simmat:
if not os.path.isfile(conf.sim_mat_fn):
die('similarity matrix missing: %s' % conf.sim_mat_fn)
if conf.sim_mat_type == 'binary':
if os.path.isfile(conf.sim_mat_fn):
simmat = sccluster.load_similarity_matrix(conf.sim_mat_fn)
else:
die('cannot read similarity matrix: %s' % conf.sim_mat_fn)
else:
die('ascii format for similarity matrix not yet implemented')
if len(allevents) != len(simmat):
print(len(allevents), len(simmat))
die('clustering stopped, number of events ' +
'differs from matrix size')
new_catalog_fn = os.path.join(conf.project_dir,
'events_to_be_clustered.pf')
model.dump_events(allevents, new_catalog_fn)
else:
if conf.metric in config.acceptable_mt_based_metrics:
events = [ev for ev in allevents if ev.moment_tensor is not None]
else:
events = [ev for ev in allevents]
new_catalog_fn = os.path.join(conf.project_dir,
'events_to_be_clustered.pf')
model.dump_events(events, new_catalog_fn)
simmat = sccluster.compute_similarity_matrix(events, conf.metric)
sccluster.save_similarity_matrix(simmat, simmat_temporal_fn)
simmat_fig_fn = os.path.join(conf.project_dir,
'simmat_temporal.' + conf.figure_format)
if options.view and options.savefig:
scplot.view_and_savefig_similarity_matrix(simmat, simmat_fig_fn,
'Sorted chronologically')
else:
if options.view:
scplot.view_similarity_matrix(simmat, 'Sorted chronologically')
if options.savefig:
scplot.savefig_similarity_matrix(simmat, simmat_fig_fn,
'Sorted chronologically')
print('Similarity matrix computed and stored as "%s"' % simmat_temporal_fn)
if options.savefig:
print('Similarity matrix figure saved as "%s"' % simmat_fig_fn)
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))
def command_cluster(args):
'''
Execution of command cluster
'''
def setup(parser):
parser.add_option('--force',
dest='force',
action='store_true',
help='overwrite existing project directory')
parser.add_option('--view',
dest='view',
action='store_true',
help='view similarity matrix after clustering')
parser.add_option(
'--savefig',
dest='savefig',
action='store_true',
help='save figure of similarity matrix after clustering')
parser, options, args = cl_parse('cluster', args, setup)
if len(args) != 1:
help_and_die(parser, 'missing argument')
else:
fn_config = args[0]
if not os.path.isfile(fn_config):
die('config file missing: %s' % fn_config)
conf = load(filename=fn_config)
config.check(conf)
if not os.path.isdir(conf.project_dir):
die('project directory missing: %s' % conf.project_dir)
resdir = os.path.join(conf.project_dir, 'clustering_results')
if not (options.force):
if (os.path.isdir(resdir)):
die('clustering result directory exists; use force option')
if options.force:
if (os.path.isdir(resdir)):
shutil.rmtree(resdir)
os.mkdir(resdir)
simmat_temporal_fn = os.path.join(conf.project_dir, 'simmat_temporal.npy')
if not os.path.isfile(simmat_temporal_fn):
die('similarity matrix does not exists: %s; ' +
'use seiscloud matrix first' % simmat_temporal_fn)
new_catalog_fn = os.path.join(conf.project_dir,
'events_to_be_clustered.pf')
if not os.path.isfile(new_catalog_fn):
die('catalog of selected events does not exists: %s; ' +
'use seiscloud matrix first' % new_catalog_fn)
simmat_temp = sccluster.load_similarity_matrix(simmat_temporal_fn)
events = model.load_events(new_catalog_fn)
eventsclusters = sccluster.dbscan(simmat_temp, conf.dbscan_nmin,
conf.dbscan_eps,
conf.sw_force_cluster_all)
clusters = sccluster.get_clusters(events, eventsclusters)
if min(eventsclusters) == -1:
noise_cluster_empty = False
else:
noise_cluster_empty = True
sccluster.save_all(events, eventsclusters, clusters, conf, resdir)
simmat_clus = sccluster.get_simmat_clustered(events, eventsclusters,
clusters, conf, resdir,
simmat_temp)
simmat_clustered_fn = os.path.join(conf.project_dir,
'simmat_clustered.npy')
sccluster.save_similarity_matrix(simmat_clus, simmat_clustered_fn)
print('I run seiscloud for the project in "%s"' % conf.project_dir)
n_clusters = len(clusters)
if not noise_cluster_empty:
n_clusters = n_clusters - 1
print(str(n_clusters) + ' cluster(s) found')
simmat_fig_fn = os.path.join(conf.project_dir,
'simmat_clustered.' + conf.figure_format)
if options.view and options.savefig:
scplot.view_and_savefig_similarity_matrix(simmat_clus, simmat_fig_fn,
'Sorted after clustering')
else:
if options.view:
scplot.view_similarity_matrix(simmat_clus,
'Sorted after clustering')
if options.savefig:
scplot.savefig_similarity_matrix(simmat_clus, simmat_fig_fn,
'Sorted after clustering')
for cluster in clusters:
selevents = clusters[cluster]
median = sccluster.get_median(selevents, conf)
fn_median = os.path.join(resdir,
'median_cluster' + str(cluster) + '.pf')
model.dump_events([median], fn_median)
# print(cluster,len(selevents))
print('Similarity matrix after clustering computed and stored as "%s"' %
simmat_clustered_fn)
if options.savefig:
print('Similarity matrix figure saved as "%s"' % simmat_fig_fn)
from pyrocko import util, model
from pyrocko.client import catalog
tmin = util.str_to_time('2011-01-01 00:00:00') # beginning time of query
tmax = util.str_to_time('2011-12-31 23:59:59')
# create an instance of the global CMT catalog
global_cmt_catalog = catalog.GlobalCMT()
# query the catalog
events = global_cmt_catalog.get_events(time_range=(tmin, tmax),
magmin=2.,
latmin=-35.,
latmax=-20.,
lonmin=-76.,
lonmax=-65.)
print('Downloaded %s events' % len(events))
print('The last one is:')
print(events[-1])
# dump events to catalog
model.dump_events(events, 'northern_chile_events.txt')
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))
