def testGlobalCMT(self):
def is_the_haiti_event(ev):
assert near(ev.magnitude, 7.0, 0.1)
assert near(ev.lat, 18.61, 0.01)
assert near(ev.lon, -72.62, 0.01)
assert near(ev.depth, 12000., 1.)
assert ev.region.lower() == 'haiti region'
cat = catalog.GlobalCMT()
tmin = util.str_to_time('2010-01-12 21:50:00')
tmax = util.str_to_time('2010-01-13 03:17:00')
names = cat.get_event_names(time_range=(tmin, tmax), magmin=5.)
ident = None
for name in names:
ev = cat.get_event(name)
if ev.magnitude > 7:
is_the_haiti_event(ev)
ident = ev.name
assert ident is not None
cat.flush()
ev = cat.get_event(ident)
is_the_haiti_event(ev)
def read_data(fn):
"""Read a buletin from the IG CAS website.
Creates objects of type ResidualMarker (subclass of pyrocko.gui_util.PhaseMarker) and pyrocko.model.Event.
"""
picks = []
events = []
with open(fn, 'r') as f:
for line in f.readlines():
odate, eventid, otime, lon, _, lat, _, _, depth, _, _, mag, stat, phase_id, polarity, date, t, a = line.split()
otime = util.str_to_time('%s %s'%(odate, otime))
event = model.Event(lat=float(lat),
lon=float(lon),
depth=float(depth),
time=otime)
t_pick = util.str_to_time('%s %s'%(date, t))
pick = ResidualMarker(event=event,
tmin=float(t_pick),
tmax=float(t_pick),
nslc_ids=[('', stat, '', '*'),],
phasename=phase_id,
polarity=int(polarity),
event_time=otime,
event_hash=event.get_hash())
if abs(t_pick-otime)>30:
continue
picks.append(pick)
events.append(event)
return picks, events
def testUSGS(self):
def is_the_haiti_event(ev):
assert near(ev.magnitude, 7.0, 0.1)
assert near(ev.lat, 18.443, 0.01)
assert near(ev.lon, -72.571, 0.01)
assert near(ev.depth, 13000., 1.)
cat = catalog.USGS()
tmin = util.str_to_time('2010-01-12 21:50:00')
tmax = util.str_to_time('2010-01-13 03:17:00')
names = cat.get_event_names(time_range=(tmin, tmax), magmin=5.)
assert len(names) == 13
for name in names:
ev = cat.get_event(name)
if ev.magnitude >= 7.:
is_the_haiti_event(ev)
ident = ev.name
assert ident is not None
cat.flush()
ev = cat.get_event(ident)
is_the_haiti_event(ev)
def testUSGS(self):
def is_the_haiti_event(ev):
assert near(ev.magnitude, 7.0, 0.1)
assert near(ev.lat, 18.443, 0.01)
assert near(ev.lon, -72.571, 0.01)
assert near(ev.depth, 13000., 1.)
cat = catalog.USGS()
tmin = util.str_to_time('2010-01-12 21:50:00')
tmax = util.str_to_time('2010-01-13 03:17:00')
names = cat.get_event_names(time_range=(tmin, tmax), magmin=5.)
assert len(names) == 13
for name in names:
ev = cat.get_event(name)
if ev.magnitude >= 7.:
is_the_haiti_event(ev)
ident = ev.name
assert ident is not None
cat.flush()
ev = cat.get_event(ident)
is_the_haiti_event(ev)
def read_enhanced_sac_pz(filename):
zeros, poles, constant, comments = pz.read_sac_zpk(filename=filename, get_comments=True)
d = {}
for line in comments:
toks = line.split(':', 1)
if len(toks) == 2:
temp = toks[0].strip('* \t')
for k in ('network', 'station', 'location', 'channel', 'start', 'end',
'latitude', 'longitude', 'depth', 'elevation', 'dip', 'azimuth',
'input unit', 'output unit'):
if temp.lower().startswith(k):
d[k] = toks[1].strip()
response = trace.PoleZeroResponse(zeros, poles, constant)
try:
channel = Channel(
nslc=(d['network'], d['station'], d['location'], d['channel']),
tmin=util.str_to_time(d['start'], format='%Y-%m-%dT%H:%M:%S'),
tmax=util.str_to_time(d['end'], format='%Y-%m-%dT%H:%M:%S'),
lat=float(d['latitude']),
lon=float(d['longitude']),
elevation=float(d['elevation']),
depth=float(d['depth']),
dip=float(d['dip']),
azimuth=float(d['azimuth']),
input_unit=d['input unit'],
output_unit=d['output unit'],
response=response)
except:
raise EnhancedSacPzError('cannot get all required information from file %s' % filename)
return channel
def gen_random_tectonic_event(
scenario_id,
magmin=-0.5,
magmax=3.,
depmin=5,
depmax=10,
latmin=49.09586,
latmax=49.25,
lonmin=8.0578,
lonmax=8.20578,
timemin=util.str_to_time('2007-01-01 16:10:00.000'),
timemax=util.str_to_time('2020-01-01 16:10:00.000')):
name = "scenario" + str(scenario_id)
depth = rand(depmin, depmax) * km
magnitude = rand(magmin, magmax)
lat = randlat(latmin, latmax)
lon = rand(lonmin, lonmax)
time = rand(timemin, timemax)
event = model.Event(name=name,
lat=lat,
lon=lon,
magnitude=magnitude,
depth=depth,
time=time)
return event
def testGlobalCMT(self):
def is_the_haiti_event(ev):
assert near(ev.magnitude, 7.0, 0.1)
assert near(ev.lat, 18.61, 0.01)
assert near(ev.lon, -72.62, 0.01)
assert near(ev.depth, 12000., 1.)
assert ev.region.lower() == 'haiti region'
cat = catalog.GlobalCMT()
tmin = util.str_to_time('2010-01-12 21:50:00')
tmax = util.str_to_time('2010-01-13 03:17:00')
names = cat.get_event_names(time_range=(tmin, tmax), magmin=5.)
ident = None
for name in names:
ev = cat.get_event(name)
if ev.magnitude > 7:
is_the_haiti_event(ev)
ident = ev.name
assert ident is not None
cat.flush()
ev = cat.get_event(ident)
is_the_haiti_event(ev)
def readandsplit(infile, box, stations):
'''
Load phase files and store data in a myStation.
Phasename is retrieved from file name: *_*_Phasename,
where * can be anything.
:param infile: name of the file which is to be read as string.
:param box: instance of myStationBox, containing myStation instances.
:param stations: File as used with snuffler to import station information.
'''
refevent = str_to_time("2010-04-11 22:08:15.500")
phasename = infile.split('_')[2]
phasename = phasename.split('.')[0]
phases = open(infile,'r').readlines()[1::]
for phase in phases:
date,time,length,NSLC = phase.split()
arrival = str_to_time(date+' '+time)-refevent
netw,stat,loc,comp = NSLC.split('.')
# check if card exists, and if it does, add phase to that card:
if(box.stationInBox(netw,stat)):
tmpCard = box.getStationCardForNetworkStation(netw,stat)
tmpCard.setPhase(phasename,arrival)
# if not, create a new card:
else:
newCard=myStation(network=netw,station=stat)
newCard.setPhase(phasename,arrival)
newCard.setLatLonEleFromStation(stations)
box.addStationCard(newCard)
def testTimeError(self):
ok = False
try:
util.str_to_time('abc')
except util.TimeStrError:
ok = True
assert ok
def testTimeError(self):
ok = False
try:
util.str_to_time('abc')
except util.TimeStrError:
ok = True
assert ok
def dummy_aware_str_to_time(s, time_format='%Y-%m-%dT%H:%M:%S'):
try:
util.str_to_time(s, format=time_format)
except util.TimeStrError:
year = int(s[:4])
if year > this_year + 100:
return None # StationXML contained a dummy end date
raise
def testGeofonMT(self):
cat = catalog.Geofon()
tmin = util.str_to_time('2014-01-01 00:00:00')
tmax = util.str_to_time('2017-01-01 00:00:00')
events = cat.get_events((tmin, tmax), magmin=8)
self.assertEqual(len(events), 2)
mt1, mt2 = [ev.moment_tensor for ev in events]
angle = moment_tensor.kagan_angle(mt1, mt2)
self.assertEqual(round(angle - 7.7, 1), 0.0)
def testGeofonMT(self):
cat = catalog.Geofon()
tmin = util.str_to_time('2014-01-01 00:00:00')
tmax = util.str_to_time('2017-01-01 00:00:00')
events = cat.get_events((tmin, tmax), magmin=8)
self.assertEqual(len(events), 2)
mt1, mt2 = [ev.moment_tensor for ev in events]
angle = moment_tensor.kagan_angle(mt1, mt2)
self.assertEqual(round(angle - 7.7, 1), 0.0)
def dummy_aware_str_to_time(s):
try:
util.str_to_time(s, format='%Y-%m-%dT%H:%M:%S')
except util.TimeStrError:
year = int(s[:4])
if year > this_year + 100:
return None # StationXML contained a dummy end date
raise
def test_scenario_combinations(self):
generator = scenario.ScenarioGenerator(
seed=20,
center_lat=42.6,
center_lon=13.3,
radius=60*km,
target_generators=[
targets.WaveformGenerator(
store_id=ScenarioTestCase.store_id,
station_generator=targets.RandomStationGenerator(
avoid_water=False),
noise_generator=targets.waveform.WhiteNoiseGenerator(),
seismogram_quantity='velocity'),
targets.InSARGenerator(
resolution=(20, 20),
noise_generator=targets.insar.AtmosphericNoiseGenerator(
amplitude=1e-5)),
targets.GNSSCampaignGenerator(
station_generator=targets.RandomStationGenerator(
avoid_water=False,
channels=None))
],
source_generator=scenario.DCSourceGenerator(
time_min=util.str_to_time('2017-01-01 00:00:00'),
time_max=util.str_to_time('2017-01-01 02:00:00'),
radius=10*km,
depth_min=1*km,
depth_max=10*km,
magnitude_min=3.0,
magnitude_max=4.5,
strike=120.,
dip=45.,
rake=90.,
perturbation_angle_std=15.,
nevents=3)
)
engine = gf.get_engine()
generator.init_modelling(engine)
for src in scenario.sources.AVAILABLE_SOURCES:
generator.source_generator = src(
time_min=util.str_to_time('2017-01-01 00:00:00'),
time_max=util.str_to_time('2017-01-01 02:00:00'),
radius=1*km,
depth_min=1.5*km,
depth_max=5*km,
magnitude_min=3.0,
magnitude_max=4.5)
generator.source_generator.update_hierarchy(generator)
generator.get_stations()
generator.get_waveforms()
generator.get_insar_scenes()
generator.get_gnss_campaigns()
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)
class SourceGenerator(LocationGenerator):
nevents = Int.T(default=2)
avoid_water = Bool.T(
default=False, help='Avoid sources offshore under the ocean / lakes.')
radius = Float.T(default=10 * km)
time_min = Timestamp.T(default=util.str_to_time('2017-01-01 00:00:00'))
time_max = Timestamp.T(default=util.str_to_time('2017-01-03 00:00:00'))
magnitude_min = Float.T(default=4.0)
magnitude_max = Float.T(default=0.0)
b_value = Float.T(optional=True,
help='Gutenberg Richter magnitude distribution.')
def __init__(self, *args, **kwargs):
super(SourceGenerator, self).__init__(*args, **kwargs)
if self.b_value and self.magnitude_max:
raise Exception('b_value and magnitude_max are mutually exclusive')
def draw_magnitude(self, rstate):
if self.b_value is None:
return rstate.uniform(self.magnitude_min, self.magnitude_max)
else:
return moment_tensor.rand_to_gutenberg_richter(
rstate.rand(), self.b_value, magnitude_min=self.magnitude_min)
def get_sources(self):
sources = []
for ievent in range(self.nevents):
src = self.get_source(ievent)
src.name = 'scenario_ev%03d' % (ievent + 1)
sources.append(src)
return sources
def dump_data(self, path):
fn_sources = op.join(path, 'sources.yml')
with open(fn_sources, 'w') as f:
for src in self.get_sources():
f.write(src.dump())
fn_events = op.join(path, 'events.txt')
with open(fn_events, 'w') as f:
for isrc, src in enumerate(self.get_sources()):
f.write(src.pyrocko_event().dump())
return [fn_events, fn_sources]
def add_map_artists(self, automap):
pass
def testTime(self):
for fmt, accu in zip(
[ '%Y-%m-%d %H:%M:%S.3FRAC', '%Y-%m-%d %H:%M:%S.2FRAC', '%Y-%m-%d %H:%M:%S.1FRAC', '%Y-%m-%d %H:%M:%S' ],
[ 0.001, 0.01, 0.1, 1.] ):
ta = util.str_to_time('1960-01-01 10:10:10')
tb = util.str_to_time('2020-01-01 10:10:10')
for i in xrange(10000):
t1 = ta + random() * (tb-ta)
s = util.time_to_str(t1, format=fmt)
t2 = util.str_to_time(s, format=fmt)
assert abs( t1 - t2 ) < accu
def testIterTimes(self):
tmin = util.str_to_time('1999-03-20 20:10:10')
tmax = util.str_to_time('2001-05-20 10:00:05')
ii = 0
for ymin, ymax in util.iter_years(tmin, tmax):
for mmin, mmax in util.iter_months(ymin, ymax):
ii += 1
s1 = util.time_to_str(mmin)
s2 = util.time_to_str(mmax)
assert ii == 12 * 3
assert s1 == '2001-12-01 00:00:00.000'
assert s2 == '2002-01-01 00:00:00.000'
def testTime(self):
for fmt, accu in zip([
'%Y-%m-%d %H:%M:%S.3FRAC', '%Y-%m-%d %H:%M:%S.2FRAC',
'%Y-%m-%d %H:%M:%S.1FRAC', '%Y-%m-%d %H:%M:%S'
], [0.001, 0.01, 0.1, 1.]):
ta = util.str_to_time('1960-01-01 10:10:10')
tb = util.str_to_time('2020-01-01 10:10:10')
for i in xrange(10000):
t1 = ta + random() * (tb - ta)
s = util.time_to_str(t1, format=fmt)
t2 = util.str_to_time(s, format=fmt)
assert abs(t1 - t2) < accu
def testIterTimes(self):
tmin = util.str_to_time('1999-03-20 20:10:10')
tmax = util.str_to_time('2001-05-20 10:00:05')
ii = 0
for ymin, ymax in util.iter_years(tmin, tmax):
for mmin, mmax in util.iter_months(ymin, ymax):
ii += 1
s1 = util.time_to_str(mmin)
s2 = util.time_to_str(mmax)
assert ii == 12*3
assert s1 == '2001-12-01 00:00:00.000'
assert s2 == '2002-01-01 00:00:00.000'
def __init__(self):
# Set up receiver configuration.
tab = '''
HH1 58.500 12.5000 0
HH2 48.500 12.5000 0
HH3 48.500 3.5000 0
HH4 58.500 3.5000 0
'''.strip()
receivers = []
for line_tab in tab.split('\n'):
station, lat, lon, depth = line_tab.split()
r = receiver.Receiver(lat, lon, components='neu', name='.%s.' % station)
receivers.append(r)
stations = receivers_to_stations(receivers)
model.dump_stations(stations, 'reference_stations.txt')
# Composition of the source
self.olat, self.olon = 52.0000, 9.00000
self.otime = util.str_to_time('1986-08-22 07:00:00')
# The gfdb can be chosen within snuffler.
# This refers to the 'add_parameter' method.
db = gfdb.Gfdb('fomostos/local1/local1')
seis = seismosizer.Seismosizer(hosts=['localhost'])
seis.set_database(db)
seis.set_effective_dt(db.dt)
seis.set_local_interpolation('bilinear')
seis.set_receivers(receivers)
seis.set_source_location(self.olat, self.olon, self.otime)
seis.set_source_constraints(0, 0, 0, 0, 0, -1)
self.seis = seis
def runParallel(inmodel):
print 'does not work properly. EXIT'
sys.exit(0)
ProBar = progressbar.ProgressBar(maxval=iterations).start()
misfits={}
misfits['pMF']=[]; misfits['sMF']=[]
misfits['ScsMF']=[]; misfits['ScssMF']=[]
loadmod=cake.load_model(inmodel)
for latindx, lat in enumerate(_lats):
for lonindx, lon in enumerate(_lons):
for zindex, z in enumerate(_depths):
#iteration+=1
# Start prozess with one event (depth), and one model:
eve=model.Event(lat,lon,str_to_time("2010-04-11 22:08:15.500"),
"Spain_Durcal" , z,6.3)
[ttpdiff, ttsdiff, ttScsdiff, ttScssdiff] = depthfinder.startup(loadmod, eve, maxdist)
pMF, sMF, ScsMF, ScssMF= map(
lambda x: calculateMisfit(x,maxdist), [ttpdiff,ttsdiff,ttScsdiff,ttScssdiff])
resultArray[latindx][lonindx][zindex] = [pMF, sMF, ScsMF, ScssMF]
# update progressbar
ProBar.update(iteration)
identifierstring = inmodel+'.%s.%s.%s'%(lat, lon, z)
results[identifierstring]=misfits
try:
output = open('results.p','w')
pickle.dump(results, output)
finally:
output.close()
def test_evalresp(self, plot=False):
resp_fpath = common.test_data_file('test2.resp')
freqs = num.logspace(num.log10(0.001), num.log10(10.), num=1000)
transfer = evalresp.evalresp(
sta_list='BSEG',
cha_list='BHZ',
net_code='GR',
locid='',
instant=util.str_to_time('2012-01-01 00:00:00'),
freqs=freqs,
units='DIS',
file=resp_fpath,
rtype='CS')[0][4]
pz_fpath = common.test_data_file('test2.sacpz')
zeros, poles, constant = pz.read_sac_zpk(pz_fpath)
resp = trace.PoleZeroResponse(zeros, poles, constant)
transfer2 = resp.evaluate(freqs)
if plot:
plot_tfs(freqs, [transfer, transfer2])
assert numeq(transfer, transfer2, 1e-4)
def __init__(self,
structures=[],
name='',
date=0.,
inversion_type='space',
m=1.,
sigmam=0.,
prior_dist='Unif'):
pattern.__init__(self, name, date, inversion_type, m, sigmam,
prior_dist)
self.t0 = time2dec(date)[0]
self.seismo = True
# segments associated to kernel
self.structures = structures
if len(self.structures) > 0:
inversion_type = 'space'
self.Mstr = len(self.structures)
# each structures can have several segments
self.Mseg = sum(map((lambda x: getattr(x, 'Mseg')), self.structures))
segments = []
segments.append(
map((lambda x: getattr(x, 'segments')), self.structures))
self.segments = flatten(segments)
# set time event for all patch
map((lambda x: setattr(x, 'time', util.str_to_time(self.date))),
self.segments)
def pdate(s):
if s.startswith('2599') or s.startswith('2999'):
return None
elif s.lower().startswith('no'):
return None
else:
return util.str_to_time(s, format='%Y,%j,%H:%M:%S.OPTFRAC')
def iload_fh(f, time_format='%Y-%m-%dT%H:%M:%S'):
zeros, poles, constant, comments = pz.read_sac_zpk(file=f,
get_comments=True)
d = {}
for line in comments:
toks = line.split(':', 1)
if len(toks) == 2:
temp = toks[0].strip('* \t')
for k in ('network', 'station', 'location', 'channel', 'start',
'end', 'latitude', 'longitude', 'depth', 'elevation',
'dip', 'azimuth', 'input unit', 'output unit'):
if temp.lower().startswith(k):
d[k] = toks[1].strip()
response = trace.PoleZeroResponse(zeros, poles, constant)
try:
yield EnhancedSacPzResponse(
codes=(d['network'], d['station'], d['location'], d['channel']),
tmin=util.str_to_time(d['start'], format=time_format),
tmax=dummy_aware_str_to_time(d['end']),
lat=float(d['latitude']),
lon=float(d['longitude']),
elevation=float(d['elevation']),
depth=float(d['depth']),
dip=float(d['dip']),
azimuth=float(d['azimuth']),
input_unit=d['input unit'],
output_unit=d['output unit'],
response=response)
except KeyError as e:
raise EnhancedSacPzError(
'cannot get all required information "%s"' % e.args[0])
def window(lat, lon, lat_source, lon_source, depth_source, nsta, store):
center = Array_center(lat, lon)
source_reciever_dis = orthodrome.distance_accurate50m_numpy(
lat_source, lon_source, lat, lon)
t_p = np.array([
store.t("first(p|P)", (depth_source, int(source_reciever_dis[i])))
for i in range(0, nsta)])
t_s = np.array([
store.t("first(s|S)", (depth_source, int(source_reciever_dis[i])))
for i in range(0, nsta)])
t_origin = util.str_to_time('2008-02-17 11:06:01.10')
def win_(t_, t_l , t_r, center):
wind_i = t_origin + t_ - t_l
wind_e = t_origin + t_ + t_r
t_o = - t_ + t_[center]
return wind_i, wind_e, t_o
P_wind_i, P_wind_e, t_op = win_(t_p, 5.0 , 20.0, center)
S_wind_i, S_wind_e, t_os = win_(t_s, 2.0 , 18.0, center)
return P_wind_i, P_wind_e, t_op , center#, S_wind_i, S_wind_e, t_os
def oldloadf(file):
d = {}
try:
for line in file:
if line.lstrip().startswith('#'):
continue
toks = line.split(' = ', 1)
if len(toks) == 2:
k, v = toks[0].strip(), toks[1].strip()
if k in ('name', 'region', 'catalog', 'magnitude_type'):
d[k] = v
if k in (('latitude longitude magnitude depth duration '
'north_shift east_shift '
'mnn mee mdd mne mnd med strike1 dip1 rake1 '
'strike2 dip2 rake2 duration').split()):
d[k] = float(v)
if k == 'time':
d[k] = util.str_to_time(v)
if k == 'tags':
d[k] = [x.strip() for x in v.split(',')]
if line.startswith('---'):
d['have_separator'] = True
break
except Exception as e:
raise FileParseError(e)
if not d:
raise EOF()
if 'have_separator' in d and len(d) == 1:
raise EmptyEvent()
mt = None
m6 = [d[x] for x in 'mnn mee mdd mne mnd med'.split() if x in d]
if len(m6) == 6:
mt = moment_tensor.MomentTensor(m=moment_tensor.symmat6(*m6))
else:
sdr = [d[x] for x in 'strike1 dip1 rake1'.split() if x in d]
if len(sdr) == 3:
moment = 1.0
if 'moment' in d:
moment = d['moment']
elif 'magnitude' in d:
moment = moment_tensor.magnitude_to_moment(d['magnitude'])
mt = moment_tensor.MomentTensor(strike=sdr[0],
dip=sdr[1],
rake=sdr[2],
scalar_moment=moment)
return (d.get('latitude', 0.0), d.get('longitude', 0.0),
d.get('north_shift', 0.0), d.get('east_shift', 0.0),
d.get('time', 0.0), d.get('name', ''), d.get('depth', None),
d.get('magnitude', None), d.get('magnitude_type',
None), d.get('region', None),
d.get('catalog', None), mt, d.get('duration',
None), d.get('tags', []))
def test_evalresp(self, plot=False):
testdir = os.path.dirname(__file__)
freqs = num.logspace(num.log10(0.001), num.log10(10.), num=1000)
transfer = evalresp.evalresp(sta_list='BSEG',
cha_list='BHZ',
net_code='GR',
locid='',
instant=util.str_to_time('2012-01-01 00:00:00'),
freqs=freqs,
units='DIS',
file=os.path.join(testdir, 'response', 'RESP.GR.BSEG..BHZ'),
rtype='CS')[0][4]
pzfn = 'SAC_PZs_GR_BSEG_BHZ__2008.254.00.00.00.0000_2599.365.23.59.59.99999'
zeros, poles, constant = pz.read_sac_zpk(filename=os.path.join(
testdir, 'response', pzfn))
resp = trace.PoleZeroResponse(zeros, poles, constant)
transfer2 = resp.evaluate(freqs)
if plot:
import pylab as lab
lab.plot(freqs, num.imag(transfer))
lab.plot(freqs, num.imag(transfer2))
lab.gca().loglog()
lab.show()
assert numeq(transfer, transfer2, 1e-4)
def pdate(s):
if s.startswith('2599') or s.startswith('2999'):
return None
elif s.lower().startswith('no'):
return None
else:
return util.str_to_time(s, format='%Y,%j,%H:%M:%S.OPTFRAC')
def get_all_scn_mechs():
mechs = np.loadtxt("ridgecrest/scn_plot.mech", dtype="str")
dates = []
strikes = []
rakes = []
dips = []
depths = []
lats = []
lons = []
events = []
for i in mechs:
dates.append(i[1][0:4] + "-" + i[1][5:7] + "-" + i[1][8:] + " " + i[2])
strikes.append(float(i[16]))
dips.append(float(i[17]))
rakes.append(float(i[18]))
lats.append(float(i[7]))
lons.append(float(i[8]))
depths.append(float(i[9]))
mt = pmt.MomentTensor(strike=float(i[16]),
dip=float(i[17]),
rake=float(i[18]),
magnitude=float(i[5]))
event = model.event.Event(
lat=float(i[7]),
lon=float(i[8]),
depth=float(i[9]),
moment_tensor=mt,
magnitude=float(i[5]),
time=util.str_to_time(i[1][0:4] + "-" + i[1][5:7] + "-" +
i[1][8:] + " " + i[2]))
events.append(event)
return events
def from_attributes(vals):
if len(vals) == 14:
nbasicvals = 7
else:
nbasicvals = 4
nslc_ids, tmin, tmax, kind = Marker.parse_attributes(
vals[1:1+nbasicvals])
i = 8
if len(vals) == 14:
i = 11
event_hash = str_to_str_or_none(vals[i-3])
event_sdate = str_to_str_or_none(vals[i-2])
event_stime = str_to_str_or_none(vals[i-1])
if event_sdate is not None and event_stime is not None:
event_time = util.str_to_time(event_sdate + ' ' + event_stime)
else:
event_time = None
phasename = str_to_str_or_none(vals[i])
polarity = str_to_int_or_none(vals[i+1])
automatic = str_to_bool(vals[i+2])
marker = PhaseMarker(nslc_ids, tmin, tmax, kind, event=None,
event_hash=event_hash, event_time=event_time,
phasename=phasename, polarity=polarity,
automatic=automatic)
return marker
def get_events_by_name_or_date(event_names_or_dates, catalog=geofon, magmin=0.):
stimes = []
for sev in event_names_or_dates:
if sev in aliases:
if isinstance(aliases[sev], str):
stimes.append(aliases[sev])
else:
stimes.extend(aliases[sev])
else:
stimes.append(sev)
events_out = []
for stime in stimes:
if op.isfile(stime):
events_out.extend(model.Event.load_catalog(stime))
elif stime.startswith('gfz'):
event = geofon.get_event(stime)
events_out.append(event)
else:
t = util.str_to_time(stime)
try:
events = get_events(
time_range=(t - 60., t + 60.), magmin=magmin, catalog=catalog)
events.sort(key=lambda ev: abs(ev.time - t))
event = events[0]
except IndexError:
logger.info('Nothing found in geofon! Trying gCMT!')
events = get_events(
time_range=(t - 60., t + 60.), magmin=magmin, catalog=gcmt)
events.sort(key=lambda ev: abs(ev.time - t))
event = events[0]
events_out.append(event)
return events_out
def regularize_extra(self, val):
if isinstance(val, datetime.datetime):
tt = val.utctimetuple()
val = calendar.timegm(tt) + val.microsecond * 1e-6
elif isinstance(val, datetime.date):
tt = val.timetuple()
val = float(calendar.timegm(tt))
elif isinstance(val, str) or isinstance(val, unicode):
val = val.strip()
val = re.sub(r'(Z|\+00(:?00)?)$', '', val)
if val[10] == 'T':
val = val.replace('T', ' ', 1)
try:
val = util.str_to_time(val)
except util.TimeStrError:
year = int(val[:4])
if year > this_year + 100:
return None # StationXML contained a dummy end date
raise
elif isinstance(val, int):
val = float(val)
else:
raise ValidationError(
'%s: cannot convert "%s" to float' % (self.xname(), val))
return val
def iload_fh(f):
zeros, poles, constant, comments = pz.read_sac_zpk(file=f,
get_comments=True)
d = {}
for line in comments:
toks = line.split(':', 1)
if len(toks) == 2:
temp = toks[0].strip('* \t')
for k in ('network', 'station', 'location', 'channel', 'start',
'end', 'latitude', 'longitude', 'depth', 'elevation',
'dip', 'azimuth', 'input unit', 'output unit'):
if temp.lower().startswith(k):
d[k] = toks[1].strip()
response = trace.PoleZeroResponse(zeros, poles, constant)
try:
yield EnhancedSacPzResponse(
codes=(d['network'], d['station'], d['location'], d['channel']),
tmin=util.str_to_time(d['start'], format='%Y-%m-%dT%H:%M:%S'),
tmax=dummy_aware_str_to_time(d['end']),
lat=float(d['latitude']),
lon=float(d['longitude']),
elevation=float(d['elevation']),
depth=float(d['depth']),
dip=float(d['dip']),
azimuth=float(d['azimuth']),
input_unit=d['input unit'],
output_unit=d['output unit'],
response=response)
except:
raise EnhancedSacPzError('cannot get all required information')
def from_attributes(vals):
if len(vals) == 14:
nbasicvals = 7
else:
nbasicvals = 4
nslc_ids, tmin, tmax, kind = Marker.parse_attributes(
vals[1:1+nbasicvals])
i = 8
if len(vals) == 14:
i = 11
event_hash = str_to_str_or_none(vals[i-3])
event_sdate = str_to_str_or_none(vals[i-2])
event_stime = str_to_str_or_none(vals[i-1])
if event_sdate is not None and event_stime is not None:
event_time = util.str_to_time(event_sdate + ' ' + event_stime)
else:
event_time = None
phasename = str_to_str_or_none(vals[i])
polarity = str_to_int_or_none(vals[i+1])
automatic = str_to_bool(vals[i+2])
marker = PhaseMarker(nslc_ids, tmin, tmax, kind, event=None,
event_hash=event_hash, event_time=event_time,
phasename=phasename, polarity=polarity,
automatic=automatic)
return marker
def get_events_by_name_or_date(event_names_or_dates, catalog=geofon):
stimes = []
for sev in event_names_or_dates:
if sev in aliases:
if isinstance(aliases[sev], str):
stimes.append(aliases[sev])
else:
stimes.extend(aliases[sev])
else:
stimes.append(sev)
events_out = []
for stime in stimes:
if op.isfile(stime):
events_out.extend(model.Event.load_catalog(stime))
elif stime.startswith('gfz'):
event = geofon.get_event(stime)
events_out.append(event)
else:
t = util.str_to_time(stime)
events = get_events(time_range=(t - 60., t + 60.), catalog=catalog)
events.sort(key=lambda ev: abs(ev.time - t))
event = events[0]
events_out.append(event)
return events_out
def regularize_extra(self, val):
if isinstance(val, datetime.datetime):
tt = val.utctimetuple()
val = calendar.timegm(tt) + val.microsecond * 1e-6
elif isinstance(val, datetime.date):
tt = val.timetuple()
val = float(calendar.timegm(tt))
elif isinstance(val, str) or isinstance(val, unicode):
val = val.strip()
val = re.sub(r'(Z|\+00(:?00)?)$', '', val)
if val[10] == 'T':
val = val.replace('T', ' ', 1)
try:
val = util.str_to_time(val)
except util.TimeStrError:
year = int(val[:4])
if year > this_year + 100:
return None # StationXML contained a dummy end date
raise
elif isinstance(val, int):
val = float(val)
else:
raise ValidationError('%s: cannot convert "%s" to float' %
(self.xname(), val))
return val
def test_evalresp(self, plot=False):
resp_fpath = common.test_data_file('test2.resp')
freqs = num.logspace(num.log10(0.001), num.log10(10.), num=1000)
transfer = evalresp.evalresp(
sta_list='BSEG',
cha_list='BHZ',
net_code='GR',
locid='',
instant=util.str_to_time('2012-01-01 00:00:00'),
freqs=freqs,
units='DIS',
file=resp_fpath,
rtype='CS')[0][4]
pz_fpath = common.test_data_file('test2.sacpz')
zeros, poles, constant = pz.read_sac_zpk(pz_fpath)
resp = trace.PoleZeroResponse(zeros, poles, constant)
transfer2 = resp.evaluate(freqs)
if plot:
plot_tfs(freqs, [transfer, transfer2])
assert numeq(transfer, transfer2, 1e-4)
def oldloadf(file):
d = {}
try:
for line in file:
if line.lstrip().startswith('#'):
continue
toks = line.split(' = ', 1)
if len(toks) == 2:
k, v = toks[0].strip(), toks[1].strip()
if k in ('name', 'region', 'catalog', 'magnitude_type'):
d[k] = v
if k in (('latitude longitude magnitude depth duration '
'mnn mee mdd mne mnd med strike1 dip1 rake1 '
'strike2 dip2 rake2 duration').split()):
d[k] = float(v)
if k == 'time':
d[k] = util.str_to_time(v)
if line.startswith('---'):
d['have_separator'] = True
break
except Exception, e:
raise FileParseError(e)
def test_scenario_map(self):
tempdir = mkdtemp(prefix='pyrocko-scenario')
self.tempdirs.append(tempdir)
generator = scenario.ScenarioGenerator(
seed=20,
center_lat=42.6,
center_lon=13.3,
radius=60*km,
target_generators=[
targets.WaveformGenerator(
store_id=ScenarioTestCase.store_id,
station_generator=targets.RandomStationGenerator(
avoid_water=False),
noise_generator=targets.waveform.WhiteNoiseGenerator(),
seismogram_quantity='velocity'),
targets.InSARGenerator(
resolution=(20, 20),
noise_generator=targets.insar.AtmosphericNoiseGenerator(
amplitude=1e-5)),
targets.GNSSCampaignGenerator(
station_generator=targets.RandomStationGenerator(
avoid_water=False,
channels=None))
],
source_generator=scenario.DCSourceGenerator(
time_min=util.str_to_time('2017-01-01 00:00:00'),
time_max=util.str_to_time('2017-01-01 02:00:00'),
radius=10*km,
depth_min=1*km,
depth_max=10*km,
magnitude_min=3.0,
magnitude_max=4.5,
strike=120.,
dip=45.,
rake=90.,
perturbation_angle_std=15.,
nevents=3)
)
engine = gf.get_engine()
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('plot', generator)
s = collection.get_scenario('plot')
s.get_map()
def plot():
'''
PLOT PARAMETERS CAN BE ADJUSTED IN THIS METHOD
'''
# initialize plotter-instance with pickled stationbox:
stationBoxFile = open('stationBox.p','r')
pplotter = plotter(pickle.load(stationBoxFile))
cmt_lat = 37.10
cmt_lon = -3.69
# plot picks (Event coordinates needed to get relative distance):
CMTevent=model.Event(cmt_lat, cmt_lon, str_to_time("2010-04-11 22:08:15.500"),
"Spain_Durcal" , 625500 ,6.3)
pplotter.plotpicks(CMTevent)
# plot misfits:
try:
pickledResults = open('numpy_results.p','r')
resultArray = pickle.load(pickledResults)
finally:
pickledResults.close()
#pplotter.plotMisfits(data, _depths)
#.............................................................
# plot contour misfits for each model:
# 1st: load misfit array:
for phaseKey in ['p', 's', 'Scs', 'Scss']:
pplotter.plotContourMisfit(resultArray, _lats, _lons, _depths, phaseKey, _models[3])
#.............................................................
# set time shift file:
tShiftFiles = glob.glob('map/t_shift*.txt')
if tShiftFiles==[] or (tShiftFiles!=[] and (os.stat(tShiftFiles[0])[8] < os.stat('numpy_results.p')[8])):
for phase in ['p','s']:
for testmodel in _models:
print '(re)setting t-shift files for model: {0} and phase:{1}'.format(testmodel, phase)
depthfinder.setTshiftFile(CMTevent, np.searchsorted(_lats, CMTevent.lat, ),
np.searchsorted(_lons, CMTevent.lon), resultArray, testmodel, phase, _depths, maxdist )
else:
pass
for shiftmodel in _models:
pplotter.plotMisfitShiftMap('s',shiftmodel)
#.............................................................
#write horizontal layers to image files;
#pplotter.saveMisfitLayersAsImages(resultArray, _lats, _lons, _depths, 'models/premlocal1_Stich.nd','p', 630000, 600000 )
#asdf
CMTeventIndexLongitude = getIndexOfValueInArray(_lons, cmt_lon)
CMTeventIndexLatitude = getIndexOfValueInArray(_lats, cmt_lat)
pplotter.plotMisfitsForLocation(_models[0], CMTeventIndexLatitude, CMTeventIndexLongitude, resultArray, _depths)
#.............................................................
# create map
subprocess.call("map/durcal_stations.sh&", shell=True)
def call(self):
self.cleanup()
# Set up receiver configuration.
tab = '''
HH 3. 3. 0
'''.strip()
receivers = []
station, lat, lon, depth = tab.split()
d_north=self.d_north
d_east=self.d_east
origin_lat, origin_lon = orthodrome.ne_to_latlon_alternative_method(float(lat), float(lon), d_north, d_east)
r = receiver.Receiver(lat,lon, components='neu', name='.%s.' % station)
receivers.append(r)
# Composition of the source
otime = util.str_to_time('2000-01-1 00:00:00')
db = self.db
seis = seismosizer.Seismosizer(hosts=['localhost'])
seis.set_database(db)
seis.set_effective_dt(db.dt)
seis.set_local_interpolation('bilinear')
seis.set_receivers(receivers)
seis.set_source_location( origin_lat, origin_lon, otime)
seis.set_source_constraints (0, 0, 0, 0 ,0 ,-1)
self.seis = seis
seis = None
risetime=3; moment=1.
s = source.Source('bilateral',
sourceparams_str='0 0 0 %g %g %g %g %g 0 0 0 0 1 %g' % (self.source_depth, moment, self.strike, self.dip, self.rake, risetime))
self.seis.set_source(s)
recs = self.seis.get_receivers_snapshot( which_seismograms = ('syn',), which_spectra=(), which_processing='tapered')
trs = []
for rec in recs:
if self.save_mseed is True:
rec.save_traces_mseed(filename_tmpl='%(whichset)s_%(network)s_%(station)s_%(location)s_%(channel)s.mseed' )
trs.extend(rec.get_traces())
self.add_traces(trs)
# Define fade in and out, band pass filter and cut off fader for the TF.
tfade = self.tfade
freqlimit = (0.005,.006,1,1.2)
cut_off_fading = 50
ntraces = []
for tr in trs:
TF = STS2()
# Save synthetic trace after transfer function was applied.
trace_filtered = tr.transfer(tfade, freqlimit, TF, cut_off_fading)
# Set new codes to the filtered trace to make it identifiable.
rename={'e':'BHE','n':'BHN','u':'BHZ'}
trace_filtered.set_codes(channel=rename[trace_filtered.channel], network='STS2', station='HH', location='syn')
ntraces.append(trace_filtered)
def test_conversions(self):
from pyrocko import model
from pyrocko.fdsn import station, resp, enhanced_sacpz
t = util.str_to_time('2014-01-01 00:00:00')
codes = 'GE', 'EIL', '', 'BHZ'
resp_fpath = common.test_data_file('test1.resp')
stations = [
model.Station(*codes[:3],
lat=29.669901,
lon=34.951199,
elevation=210.0,
depth=0.0)
]
sx_resp = resp.make_stationxml(stations,
resp.iload_filename(resp_fpath))
pr_sx_resp = sx_resp.get_pyrocko_response(codes,
time=t,
fake_input_units='M/S')
pr_evresp = trace.Evalresp(resp_fpath,
nslc_id=codes,
target='vel',
time=t)
sacpz_fpath = common.test_data_file('test1.sacpz')
sx_sacpz = enhanced_sacpz.make_stationxml(
enhanced_sacpz.iload_filename(sacpz_fpath))
pr_sx_sacpz = sx_sacpz.get_pyrocko_response(codes,
time=t,
fake_input_units='M/S')
pr_sacpz = trace.PoleZeroResponse(*pz.read_sac_zpk(sacpz_fpath))
try:
pr_sacpz.zeros.remove(0.0j)
except ValueError:
pr_sacpz.poles.append(0.0j)
sxml_geofon_fpath = common.test_data_file('test1.stationxml')
sx_geofon = station.load_xml(filename=sxml_geofon_fpath)
pr_sx_geofon = sx_geofon.get_pyrocko_response(codes,
time=t,
fake_input_units='M/S')
sxml_iris_fpath = common.test_data_file('test2.stationxml')
sx_iris = station.load_xml(filename=sxml_iris_fpath)
pr_sx_iris = sx_iris.get_pyrocko_response(codes,
time=t,
fake_input_units='M/S')
freqs = num.logspace(num.log10(0.001), num.log10(1.0), num=1000)
tf_ref = pr_evresp.evaluate(freqs)
for pr in [
pr_sx_resp, pr_sx_sacpz, pr_sacpz, pr_sx_geofon, pr_sx_iris
]:
tf = pr.evaluate(freqs)
# plot_tfs(freqs, [tf_ref, tf])
assert cnumeqrel(tf_ref, tf, 0.01)
def testGeofonMT(self):
cat = catalog.Geofon()
tmin = util.str_to_time('2014-01-01 00:00:00')
tmax = util.str_to_time('2017-01-01 00:00:00')
events_a = cat.get_events((tmin, tmax), magmin=8)
events_b = [
cat.get_event('gfz2015sfdd'),
cat.get_event('gfz2014gkgf')]
for events in [events_a, events_b]:
self.assertEqual(len(events), 2)
mt1, mt2 = [ev.moment_tensor for ev in events]
angle = moment_tensor.kagan_angle(mt1, mt2)
self.assertEqual(round(angle - 7.7, 1), 0.0)
ev = cat.get_event('gfz2020vimx')
assert isinstance(ev.moment_tensor, moment_tensor.MomentTensor)
def parse_attributes(vals):
tmin = util.str_to_time(vals[0] + ' ' + vals[1])
i = 2
tmax = tmin
if len(vals) == 7:
tmax = util.str_to_time(vals[2] + ' ' + vals[3])
i = 5
kind = int(vals[i])
traces = vals[i+1]
if traces == 'None':
nslc_ids = []
else:
nslc_ids = tuple(
[tuple(nslc_id.split('.')) for nslc_id in traces.split(',')])
return nslc_ids, tmin, tmax, kind
def parse_attributes(vals):
tmin = util.str_to_time(vals[0] + ' ' + vals[1])
i = 2
tmax = tmin
if len(vals) == 7:
tmax = util.str_to_time(vals[2] + ' ' + vals[3])
i = 5
kind = int(vals[i])
traces = vals[i+1]
if traces == 'None':
nslc_ids = []
else:
nslc_ids = tuple(
[tuple(nslc_id.split('.')) for nslc_id in traces.split(',')])
return nslc_ids, tmin, tmax, kind
def runSerial(models=None):
'''
Execute serial processing (1 CPU).
:param models: list of models to investigate
if no models are given, all models will be investigated.
'''
if models==None:
models2use = _models
else:
models2use = [models]
iteration=0
iterations = len(models2use)*len(_depths)*len(_lats)*len(_lons)
sys.stdout.write('calculating misfits... ')
ProBar = progressbar.ProgressBar(maxval=iterations).start()
# instantiate result array as numpy nd array:
resultArray = np.ndarray(shape=(len(_lats), len(_lons), len(_depths), 4))
for mod in models2use:
misfits={}
misfits['pMF']=[]; misfits['sMF']=[]
misfits['ScsMF']=[]; misfits['ScssMF']=[]
loadmod=cake.load_model(mod)
for latindx, lat in enumerate(_lats):
for lonindx, lon in enumerate(_lons):
for zindex, z in enumerate(_depths):
iteration+=1
eve=model.Event(lat,lon,str_to_time("2010-04-11 22:08:15.500"),
"Spain_Durcal" , z,6.3)
[ttpdiff, ttsdiff, ttScsdiff, ttScssdiff] = depthfinder.startup(loadmod, eve, maxdist)
[pMF, sMF, ScsMF, ScssMF]= map(
lambda x: calculateMisfit(x,maxdist), [ttpdiff,ttsdiff,ttScsdiff,ttScssdiff])
# update progressbar
ProBar.update(iteration)
# write data to numpy array:
resultArray[latindx][lonindx][zindex] = [pMF, sMF, ScsMF, ScssMF]
results[mod]=resultArray
depthfinder.storeStationBox()
# finish progressbar:
ProBar.finish()
# write dict to pickled data:
try:
output = open('numpy_results.p','w')
pickle.dump(results, output)
finally:
output.close()
# write used stations file:
depthfinder._myStationBox.writeUsedStationsFile()
def load_ev_dict_list(path=None, nevent=0):
events = num.loadtxt("data/geres_epi.csv", delimiter="\t", dtype='str')
event_marker_out = []
ev_dict_list = []
if nevent is not None:
events = events[0:nevent]
for ev in events:
date = str(ev[1])
time = str(ev[2])
try:
h, m = [int(s) for s in time.split('.')]
except Exception:
h = time
m = 0.
if len(str(h)) == 5:
time = "0" + time[0] + ":" + time[1:3] + ":" + time[3:5] + time[5:]
elif len(str(h)) == 4:
time = "00" + ":" + time[0:2] + ":" + time[3:5] + time[5:]
elif len(str(h)) == 3:
time = "00" + ":" + "0" + time[0] + ":" + time[1:4] + time[4:]
else:
time = time[0:2] + ":" + time[2:4] + ":" + time[4:5] + time[5:]
date = str(date[0:4]) + "-" + str(date[4:6] + "-" + date[6:8] + " ")
ev_time = util.str_to_time(date + time)
try:
ev_dict_list.append(
dict(id=ev[0],
time=ev_time,
lat=float(ev[3]),
lon=float(ev[4]),
mag=float(ev[5]),
mag_type=ev[6],
source=ev[7],
phases=[],
depth=[],
rms=[],
error_h=[],
error_z=[]))
except:
ev_dict_list.append(
dict(id=ev[0],
time=ev_time,
lat=float(ev[3]),
lon=float(ev[4]),
mag=None,
mag_type=None,
source=ev[5],
phases=[],
depth=[],
rms=[],
error_h=[],
error_z=[]))
picks = num.loadtxt("data/geres_phas.csv", delimiter="\t", dtype='str')
return ev_dict_list, picks
def context(fn):
from pyrocko import datacube_ext
dpath = os.path.dirname(os.path.abspath(fn))
mtimes = [os.stat(dpath)[8]]
dentries = sorted([
os.path.join(dpath, f) for f in os.listdir(dpath)
if os.path.isfile(os.path.join(dpath, f))
])
for dentry in dentries:
fn2 = os.path.join(dpath, dentry)
mtimes.append(os.stat(fn2)[8])
mtime = float(max(mtimes))
if dpath in g_dir_contexts:
dir_context = g_dir_contexts[dpath]
if dir_context.mtime == mtime:
return dir_context
del g_dir_contexts[dpath]
entries = []
for dentry in dentries:
fn2 = os.path.join(dpath, dentry)
if not os.path.isfile(fn2):
continue
with open(fn2, 'rb') as f:
first512 = f.read(512)
if not detect(first512):
continue
with open(fn2, 'rb') as f:
try:
header, data_arrays, gps_tags, nsamples, _ = \
datacube_ext.load(f.fileno(), 3, 0, -1, None)
except datacube_ext.DataCubeError as e:
e = DataCubeError(str(e))
e.set_context('filename', fn)
raise e
header = dict(header)
entries.append(
DirContextEntry(
path=os.path.abspath(fn2),
tstart=util.str_to_time('20' + header['S_DATE'] + ' ' +
header['S_TIME'],
format='%Y/%m/%d %H:%M:%S'),
ifile=int(header['DAT_NO'])))
dir_context = DirContext(mtime=mtime, path=dpath, entries=entries)
return dir_context
def testTime(self):
for fmt, accu in zip(
['%Y-%m-%d %H:%M:%S.3FRAC', '%Y-%m-%d %H:%M:%S.2FRAC',
'%Y-%m-%d %H:%M:%S.1FRAC', '%Y-%m-%d %H:%M:%S',
'%Y-%m-%d %H.%M.%S.3FRAC'],
[0.001, 0.01, 0.1, 1., 0.001, 0.001]):
ta = util.str_to_time('1960-01-01 10:10:10')
tb = util.str_to_time('2020-01-01 10:10:10')
for i in range(10000):
t1 = ta + random() * (tb-ta)
s = util.time_to_str(t1, format=fmt)
t2 = util.str_to_time(s, format=fmt)
assert abs(t1 - t2) < accu
fmt_opt = re.sub(r'\.[0-9]FRAC$', '', fmt) + '.OPTFRAC'
t3 = util.str_to_time(s, format=fmt_opt)
assert abs(t1 - t3) < accu
def subset_events_dist_cat(catalog, mag_min, mag_max,
tmin, tmax, st_lat, st_lon,
dist_min=None, dist_max=None):
"""
Extract a subset of events from event catalog
:param catalog: Event catalog in pyrocko format
:param mag_min: Min. magnitude
:param mag_max: Max. magnitude
:param tmin: string representing UTC time
:param tmax: string representing UTC time
:param format tmin: time string format ('%Y-%m-%d %H:%M:%S.OPTFRAC')
:param format tmax: time string format ('%Y-%m-%d %H:%M:%S.OPTFRAC')
:param dist_min: min. distance (km)
:param dist_max: max. distance (km)
:param depth_min
:param depth_max
:returns: list of events
"""
use_events = []
events = model.load_events(catalog)
for ev in events:
if ev.magnitude < mag_max and\
ev.magnitude > mag_min and\
ev.time < util.str_to_time(tmax) and\
ev.time > util.str_to_time(tmin):
if dist_min or dist_max:
dist = orthodrome.distance_accurate50m_numpy(
ev.lat, ev.lon, st_lat, st_lon)/1000.
if dist_min and dist_max and\
dist > dist_min and dist < dist_max:
use_events.append(ev)
if dist_min and not dist_max and dist > dist_min:
use_events.append(ev)
if dist_max and not dist_min and dist < dist_max:
use_events.append(ev)
return(use_events)
def well_geometry_sparrow_export(file, folder, name):
import utm
from pyproj import Proj
from pyrocko.model import Geometry
data = num.loadtxt(file, delimiter=",")
utmx = data[:, 0]
utmy = data[:, 1]
z = data[:, 2]
proj_gk4 = Proj(init="epsg:31467") # GK-projection
lons, lats = proj_gk4(utmx, utmy, inverse=True)
ev = event.Event(lat=num.mean(lats), lon=num.mean(lons), depth=num.mean(z),
time=util.str_to_time("2000-01-01 01:01:01"))
ncorners = 4
verts = []
xs = []
ys = []
dist = 200.
for i in range(0, len(z)):
try:
x = lats[i]
y = lons[i]
x1 = lats[i+1]
y1 = lons[i+1]
depth = z[i]
depth1 = z[i+1]
xyz = ([dist/2.8, dist/2.8, depth], [dist/2.8, dist/2.8, depth1],
[dist/2.8, -dist/2.8, depth1], [dist/2.8, -dist/2.8, depth])
latlon = ([x, y], [x1, y1], [x1, y1], [x, y])
patchverts = num.hstack((latlon, xyz))
verts.append(patchverts)
except Exception:
pass
vertices = num.vstack(verts)
npatches = int(len(vertices))
faces1 = num.arange(ncorners * npatches, dtype='int64').reshape(
npatches, ncorners)
faces2 = num.fliplr(faces1)
faces = num.hstack((faces2, faces1))
srf_semblance_list = []
srf_semblance = num.ones(num.shape(data[:, 2]))
srf_semblance = duplicate_property(srf_semblance)
srf_semblance_list.append(srf_semblance)
srf_semblance = num.asarray(srf_semblance_list).T
srf_times = num.linspace(0, 1, 1)
geom = Geometry(times=srf_times, event=ev)
geom.setup(vertices, faces)
sub_headers = tuple([str(i) for i in srf_times])
geom.add_property((('semblance', 'float64', sub_headers)), srf_semblance)
dump(geom, filename='geom_gtla1.yaml')
def test_source_times(self):
store = self.dummy_store()
for S in gf.source_classes:
if not hasattr(S, 'discretize_basesource'):
continue
for t in [0.0, util.str_to_time('2014-01-01 10:00:00')]:
source = S(time=t)
dsource = source.discretize_basesource(store)
cent = dsource.centroid()
assert numeq(cent.time + source.get_timeshift(), t, 0.0001)
def context(fn):
from pyrocko import datacube_ext
dpath = os.path.dirname(os.path.abspath(fn))
mtimes = [os.stat(dpath)[8]]
dentries = sorted([os.path.join(dpath, f) for f in os.listdir(dpath)
if os.path.isfile(os.path.join(dpath, f))])
for dentry in dentries:
fn2 = os.path.join(dpath, dentry)
mtimes.append(os.stat(fn2)[8])
mtime = float(max(mtimes))
if dpath in g_dir_contexts:
dir_context = g_dir_contexts[dpath]
if dir_context.mtime == mtime:
return dir_context
del g_dir_contexts[dpath]
entries = []
for dentry in dentries:
fn2 = os.path.join(dpath, dentry)
if not os.path.isfile(fn2):
continue
with open(fn2, 'rb') as f:
first512 = f.read(512)
if not detect(first512):
continue
with open(fn2, 'rb') as f:
try:
header, data_arrays, gps_tags, nsamples, _ = \
datacube_ext.load(f.fileno(), 3, 0, -1, None)
except datacube_ext.DataCubeError as e:
e = DataCubeError(str(e))
e.set_context('filename', fn)
raise e
header = dict(header)
entries.append(DirContextEntry(
path=os.path.abspath(fn2),
tstart=util.str_to_time(
'20' + header['S_DATE'] + ' ' + header['S_TIME'],
format='%Y/%m/%d %H:%M:%S'),
ifile=int(header['DAT_NO'])))
dir_context = DirContext(mtime=mtime, path=dpath, entries=entries)
return dir_context
def testGeofon(self):
cat = catalog.Geofon()
tmin = util.str_to_time('2010-01-12 21:50:00')
tmax = util.str_to_time('2010-01-13 03:17:00')
names = cat.get_event_names(
time_range=(tmin, tmax), nmax=10, magmin=5.)
assert len(names) > 0
ident = None
for name in names:
ev = cat.get_event(name)
if ev.magnitude >= 7:
is_the_haiti_event_geofon(ev)
ident = ev.name
assert ident is not None
cat.flush()
def test_conversions(self):
from pyrocko import model
from pyrocko.io import resp, enhanced_sacpz
from pyrocko.io import stationxml
t = util.str_to_time('2014-01-01 00:00:00')
codes = 'GE', 'EIL', '', 'BHZ'
resp_fpath = common.test_data_file('test1.resp')
stations = [model.Station(
*codes[:3],
lat=29.669901,
lon=34.951199,
elevation=210.0,
depth=0.0)]
sx_resp = resp.make_stationxml(
stations, resp.iload_filename(resp_fpath))
pr_sx_resp = sx_resp.get_pyrocko_response(
codes, time=t, fake_input_units='M/S')
pr_evresp = trace.Evalresp(
resp_fpath, nslc_id=codes, target='vel', time=t)
sacpz_fpath = common.test_data_file('test1.sacpz')
sx_sacpz = enhanced_sacpz.make_stationxml(
enhanced_sacpz.iload_filename(sacpz_fpath))
pr_sx_sacpz = sx_sacpz.get_pyrocko_response(
codes, time=t, fake_input_units='M/S')
pr_sacpz = trace.PoleZeroResponse(*pz.read_sac_zpk(sacpz_fpath))
try:
pr_sacpz.zeros.remove(0.0j)
except ValueError:
pr_sacpz.poles.append(0.0j)
sxml_geofon_fpath = common.test_data_file('test1.stationxml')
sx_geofon = stationxml.load_xml(filename=sxml_geofon_fpath)
pr_sx_geofon = sx_geofon.get_pyrocko_response(
codes, time=t, fake_input_units='M/S')
sxml_iris_fpath = common.test_data_file('test2.stationxml')
sx_iris = stationxml.load_xml(filename=sxml_iris_fpath)
pr_sx_iris = sx_iris.get_pyrocko_response(
codes, time=t, fake_input_units='M/S')
freqs = num.logspace(num.log10(0.001), num.log10(1.0), num=1000)
tf_ref = pr_evresp.evaluate(freqs)
for pr in [pr_sx_resp, pr_sx_sacpz, pr_sacpz, pr_sx_geofon,
pr_sx_iris]:
tf = pr.evaluate(freqs)
# plot_tfs(freqs, [tf_ref, tf])
assert cnumeqrel(tf_ref, tf, 0.01)
def regularize_extra(self, val):
if isinstance(val, datetime.datetime):
tt = val.utctimetuple()
val = calendar.timegm(tt) + val.microsecond * 1e-6
elif isinstance(val, str) or isinstance(val, unicode):
val = str_to_time(val, format='%Y-%m-%d')
if not isinstance(val, float):
val = float(val)
return val
def test_scenario_combinations(self):
import copy
generator = copy.deepcopy(self.generator)
engine = gf.get_engine()
generator.init_modelling(engine)
for src in scenario.sources.AVAILABLE_SOURCES:
generator.source_generator = src(
time_min=util.str_to_time('2017-01-01 00:00:00'),
time_max=util.str_to_time('2017-01-01 02:00:00'),
radius=1*km,
depth_min=1.5*km,
depth_max=5*km,
magnitude_min=3.0,
magnitude_max=4.5)
generator.source_generator.update_hierarchy(generator)
generator.get_stations()
generator.get_waveforms()
generator.get_insar_scenes()
generator.get_gnss_campaigns()