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 olddumpf(self, file):
file.write('name = %s\n' % self.name)
file.write('time = %s\n' % util.time_to_str(self.time))
if self.lat is not None:
file.write('latitude = %.12g\n' % self.lat)
if self.lon is not None:
file.write('longitude = %.12g\n' % self.lon)
if self.magnitude is not None:
file.write('magnitude = %g\n' % self.magnitude)
file.write('moment = %g\n' %
moment_tensor.magnitude_to_moment(self.magnitude))
if self.magnitude_type is not None:
file.write('magnitude_type = %s\n' % self.magnitude_type)
if self.depth is not None:
file.write('depth = %.10g\n' % self.depth)
if self.region is not None:
file.write('region = %s\n' % self.region)
if self.catalog is not None:
file.write('catalog = %s\n' % self.catalog)
if self.moment_tensor is not None:
m = self.moment_tensor.m()
sdr1, sdr2 = self.moment_tensor.both_strike_dip_rake()
file.write((
'mnn = %g\nmee = %g\nmdd = %g\nmne = %g\nmnd = %g\nmed = %g\n'
'strike1 = %g\ndip1 = %g\nrake1 = %g\n'
'strike2 = %g\ndip2 = %g\nrake2 = %g\n') % (
(m[0, 0], m[1, 1], m[2, 2], m[0, 1], m[0, 2], m[1, 2]) +
sdr1 + sdr2))
if self.duration is not None:
file.write('duration = %g\n' % self.duration)
def createMT_CLVD(mag):
exp = mtm.magnitude_to_moment(mag)
# init pyrocko moment tensor
cvld_matrix = np.array([[1, 0, 0], [0, 1, 0], [0, 0, -2]]) * exp
rotated_matrix = mtm.random_rotation() * cvld_matrix
return mtm.MomentTensor(rotated_matrix)
def olddumpf(self, file):
file.write('name = %s\n' % self.name)
file.write('time = %s\n' % util.time_to_str(self.time))
if self.lat is not None:
file.write('latitude = %.12g\n' % self.lat)
if self.lon is not None:
file.write('longitude = %.12g\n' % self.lon)
if self.magnitude is not None:
file.write('magnitude = %g\n' % self.magnitude)
file.write('moment = %g\n' %
moment_tensor.magnitude_to_moment(self.magnitude))
if self.magnitude_type is not None:
file.write('magnitude_type = %s\n' % self.magnitude_type)
if self.depth is not None:
file.write('depth = %.10g\n' % self.depth)
if self.region is not None:
file.write('region = %s\n' % self.region)
if self.catalog is not None:
file.write('catalog = %s\n' % self.catalog)
if self.moment_tensor is not None:
m = self.moment_tensor.m()
sdr1, sdr2 = self.moment_tensor.both_strike_dip_rake()
file.write(
('mnn = %g\nmee = %g\nmdd = %g\nmne = %g\nmnd = %g\nmed = %g\n'
'strike1 = %g\ndip1 = %g\nrake1 = %g\n'
'strike2 = %g\ndip2 = %g\nrake2 = %g\n') %
((m[0, 0], m[1, 1], m[2, 2], m[0, 1], m[0, 2], m[1, 2]) +
sdr1 + sdr2))
if self.duration is not None:
file.write('duration = %g\n' % self.duration)
def discretize_basesource(self, store, target=None):
times, amplitudes = self.effective_stf_pre().discretize_t(
store.config.deltat, self.time)
m0 = mtm.magnitude_to_moment(self.magnitude)
m6s = self.m6 * m0
return meta.DiscretizedMTSource(m6s=m6s[num.newaxis, :] *
amplitudes[:, num.newaxis],
**self._dparams_base_repeated(times))
def testMomentGetterSetter(self):
m1 = MomentTensor()
want_mom = 2E7
m1.moment = want_mom
sm2 = m1.scalar_moment()
assert(sm2 == m1.moment)
assert(abs(sm2 - want_mom) < 1E-8)
mag = moment_to_magnitude(want_mom)
assert(m1.magnitude == mag)
want_mag = 3.5
m1.magnitude = want_mag
mom = magnitude_to_moment(want_mag)
assert(m1.moment == mom)
def testMomentGetterSetter(self):
m1 = MomentTensor()
want_mom = 2E7
m1.moment = want_mom
sm2 = m1.scalar_moment()
assert (sm2 == m1.moment)
assert (abs(sm2 - want_mom) < 1E-8)
mag = moment_to_magnitude(want_mom)
assert (m1.magnitude == mag)
want_mag = 3.5
m1.magnitude = want_mag
mom = magnitude_to_moment(want_mag)
assert (m1.moment == mom)
def testMomentGetterSetter(self):
m1 = MomentTensor()
want_mom = 2e7
m1.moment = want_mom
sm2 = m1.scalar_moment()
assert sm2 == m1.moment
assert abs(sm2 - want_mom) < 1e-8
mag = moment_to_magnitude(want_mom)
assert m1.magnitude == mag
want_mag = 3.5
m1.magnitude = want_mag
mom = magnitude_to_moment(want_mag)
assert m1.moment == mom
def get_source(self, x):
d = self.get_parameter_dict(x)
rm6 = num.array([d.rmnn, d.rmee, d.rmdd, d.rmne, d.rmnd, d.rmed],
dtype=num.float)
m0 = mtm.magnitude_to_moment(d.magnitude)
m6 = rm6 * m0
p = {}
for k in self.base_source.keys():
if k in d:
p[k] = float(self.ranges[k].make_relative(
self.base_source[k], d[k]))
source = self.base_source.clone(m6=m6, stf=self.get_stf(d), **p)
return source
def olddumpf(self, file):
if self.extras:
raise EventExtrasDumpError(
'Event user-defined extras attributes cannot be dumped in the '
'"basic" event file format. Use '
'dump_events(..., format="yaml").')
file.write('name = %s\n' % self.name)
file.write('time = %s\n' % util.time_to_str(self.time))
if self.lat != 0.0:
file.write('latitude = %.12g\n' % self.lat)
if self.lon != 0.0:
file.write('longitude = %.12g\n' % self.lon)
if self.north_shift != 0.0:
file.write('north_shift = %.12g\n' % self.north_shift)
if self.east_shift != 0.0:
file.write('east_shift = %.12g\n' % self.east_shift)
if self.magnitude is not None:
file.write('magnitude = %g\n' % self.magnitude)
file.write('moment = %g\n' %
moment_tensor.magnitude_to_moment(self.magnitude))
if self.magnitude_type is not None:
file.write('magnitude_type = %s\n' % self.magnitude_type)
if self.depth is not None:
file.write('depth = %.10g\n' % self.depth)
if self.region is not None:
file.write('region = %s\n' % self.region)
if self.catalog is not None:
file.write('catalog = %s\n' % self.catalog)
if self.moment_tensor is not None:
m = self.moment_tensor.m()
sdr1, sdr2 = self.moment_tensor.both_strike_dip_rake()
file.write(
('mnn = %g\nmee = %g\nmdd = %g\nmne = %g\nmnd = %g\nmed = %g\n'
'strike1 = %g\ndip1 = %g\nrake1 = %g\n'
'strike2 = %g\ndip2 = %g\nrake2 = %g\n') %
((m[0, 0], m[1, 1], m[2, 2], m[0, 1], m[0, 2], m[1, 2]) +
sdr1 + sdr2))
if self.duration is not None:
file.write('duration = %g\n' % self.duration)
if self.tags:
file.write('tags = %s\n' % ', '.join(self.tags))
def get_source(self, ievent):
rstate = self.get_rstate(ievent)
time = rstate.uniform(self.time_min, self.time_max)
lat, lon = self.get_latlon(ievent)
depth = rstate.uniform(self.depth_min, self.depth_max)
magnitude = self.draw_magnitude(rstate)
moment = moment_tensor.magnitude_to_moment(magnitude)
# After Mai and Beroza (2000)
length = num.exp(-6.27 + 0.4*num.log(moment))
width = num.exp(-4.24 + 0.32*num.log(moment))
length = length if not self.length else self.length
width = width if not self.width else self.width
depth = depth if not self.depth else self.depth
if self.strike is None and self.dip is None and self.rake is None:
strike, rake = rstate.uniform(-180., 180., 2)
dip = rstate.uniform(0., 90.)
else:
if None in (self.strike, self.dip, self.rake):
raise ScenarioError(
'RectangularFaultGenerator: '
'strike, dip, rake'
' must be used in combination')
strike = self.strike
dip = self.dip
rake = self.rake
source = gf.RectangularSource(
time=float(time),
lat=float(lat),
lon=float(lon),
anchor='top',
depth=float(depth),
length=float(length),
width=float(width),
strike=float(strike),
dip=float(dip),
rake=float(rake),
magnitude=magnitude,
decimation_factor=self.decimation_factor)
return source
def add_map_artists(self, automap):
from pyrocko import gmtpy
for source in self.get_sources():
event = source.pyrocko_event()
mt = event.moment_tensor.m_up_south_east()
xx = num.trace(mt) / 3.
mc = num.matrix([[xx, 0., 0.], [0., xx, 0.], [0., 0., xx]])
mc = mt - mc
mc = mc / event.moment_tensor.scalar_moment() * \
moment_tensor.magnitude_to_moment(5.0)
m6 = tuple(moment_tensor.to6(mc))
symbol_size = 20.
automap.gmt.psmeca(
S='%s%g' % ('d', symbol_size / gmtpy.cm),
in_rows=[(source.lon, source.lat, 10) + m6 + (1, 0, 0)],
M=True,
*automap.jxyr)
def add_map_artists(self, automap):
from pyrocko import gmtpy
for source in self.get_sources():
event = source.pyrocko_event()
mt = event.moment_tensor.m_up_south_east()
xx = num.trace(mt) / 3.
mc = num.matrix([[xx, 0., 0.], [0., xx, 0.], [0., 0., xx]])
mc = mt - mc
mc = mc / event.moment_tensor.scalar_moment() * \
moment_tensor.magnitude_to_moment(5.0)
m6 = tuple(moment_tensor.to6(mc))
symbol_size = 20.
automap.gmt.psmeca(S='%s%g' % ('d', symbol_size / gmtpy.cm),
in_rows=[(source.lon, source.lat, 10) + m6 +
(1, 0, 0)],
M=True,
*automap.jxyr)
def test_rect_source(self):
store = self.dummy_homogeneous_store()
rect1 = gf.RectangularSource(depth=10 * km,
magnitude=5.0,
width=5 * km,
length=5 * km)
rect2 = gf.RectangularSource(
depth=10 * km,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
store.config.earthmodel_1d.material(10 * km).shear_modulus()),
width=5 * km,
length=5 * km)
self.assertAlmostEqual(
rect1.get_magnitude(),
rect2.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
def test_rect_source(self):
store = self.dummy_homogeneous_store()
rect1 = gf.RectangularSource(
depth=10*km,
magnitude=5.0,
width=5*km,
length=5*km)
rect2 = gf.RectangularSource(
depth=10*km,
slip=pmt.magnitude_to_moment(5.0) / (
5*km * 5*km * store.config.earthmodel_1d.material(
10*km).shear_modulus()),
width=5*km,
length=5*km)
self.assertAlmostEqual(
rect1.get_magnitude(),
rect2.get_magnitude(
store, gf.Target(interpolation='nearest_neighbor')))
from pyrocko import moment_tensor as mtm
magnitude = 6.3 # Magnitude of the earthquake
exp = mtm.magnitude_to_moment(magnitude) # convert the mag to moment in [Nm]
# init pyrocko moment tensor
m = mtm.MomentTensor(
mnn = 2.34*exp,
mee = -2.64*exp,
mdd = 0.295*exp,
mne = 1.49*exp,
mnd = 0.182*exp,
med = -0.975*exp)
print(m) # print moment tensor
# gives out both nodal planes:
(s1, d1, r1), (s2, d2, r2) = m.both_strike_dip_rake()
print('strike1=%s, dip1=%s, rake1=%s' % (s1, d1, r1))
print('strike2=%s, dip2=%s, rake2=%s' % (s2, d2, r2))
def model(
engine,
store_id,
magnitude_min, magnitude_max,
moment_tensor,
stress_drop_min, stress_drop_max,
rupture_velocity_min, rupture_velocity_max,
depth_min, depth_max,
distance_min, distance_max,
measures,
nsources=400,
nreceivers=1,
apply_source_response_via_spectra=True,
debug=True):
d2r = math.pi / 180.
components = set()
for measure in measures:
if not measure.components:
raise Exception('no components given in measurement rule')
for component in measure.components:
components.add(component)
components = list(components)
data = []
nerrors = 0
traces_debug = []
markers_debug = []
for isource in xrange(nsources):
magnitude = num.random.uniform(
magnitude_min, magnitude_max)
stress_drop = num.random.uniform(
stress_drop_min, stress_drop_max)
rupture_velocity = num.random.uniform(
rupture_velocity_min, rupture_velocity_max)
radius = (pmt.magnitude_to_moment(magnitude) * 7./16. /
stress_drop)**(1./3.)
duration = 1.5 * radius / rupture_velocity
if moment_tensor is None:
mt = pmt.MomentTensor.random_dc(magnitude=magnitude)
else:
mt = copy.deepcopy(moment_tensor)
mt.magnitude = magnitude
depth = num.random.uniform(depth_min, depth_max)
if apply_source_response_via_spectra:
source = gf.MTSource(
m6=mt.m6(),
depth=depth)
extra_responses = [
wmeasure.BruneResponse(duration=duration)]
else:
source = gf.MTSource(
m6=mt.m6(),
depth=depth,
stf=gf.HalfSinusoidSTF(effective_duration=duration))
extra_responses = []
for ireceiver in xrange(nreceivers):
angle = num.random.uniform(0., 360.)
distance = num.exp(num.random.uniform(
math.log(distance_min), math.log(distance_max)))
targets = []
for comp in components:
targets.append(gf.Target(
quantity='displacement',
codes=('', '%i_%i' % (isource, ireceiver), '', comp),
north_shift=distance*math.cos(d2r*angle),
east_shift=distance*math.sin(d2r*angle),
depth=0.,
store_id=store_id))
resp = engine.process(source, targets)
amps = []
for measure in measures:
comp_to_tt = {}
for (source, target, tr) in resp.iter_results():
comp_to_tt[target.codes[-1]] = (target, tr)
targets, trs = zip(*(
comp_to_tt[c] for c in measure.components))
try:
result = wmeasure.evaluate(
engine, source, targets, trs,
extra_responses,
debug=debug)
if not debug:
amps.append(result)
else:
amp, trs, marker = result
amps.append(amp)
traces_debug.extend(trs)
markers_debug.append(marker)
except wmeasure.AmplitudeMeasurementFailed:
nerrors += 1
amps.append(None)
data.append([magnitude, duration, depth, distance] + amps)
if debug:
trace.snuffle(traces_debug, markers=markers_debug)
return num.array(data, dtype=num.float)
def rho(self):
return mtm.magnitude_to_moment(self.magnitude) * sqrt2
def PRIOR(self, stream, inventory=False):
if inventory:
if self.cat == None:
raise ValueError('No path for xml file specified!')
else:
inv = read_events(self.inv)
trace = stream.traces[0]
PRIOR = {}
PRIOR['PLOT'] = False
PRIOR['save_name'] = 'TAYAK' + trace.id.replace('.', '_')
PRIOR['save_dir'] = self.directory + 'Output' #'/home/nienke/MSS'
if not os.path.exists(PRIOR['save_dir']):
os.makedirs(PRIOR['save_dir'])
# = Radius of the body used =
PRIOR['radius'] = 3389.5 # Mars
# PRIOR['radius'] = 6378137.0 # Earth
# = Flattening planet =
PRIOR['f'] = 0 # Mars
# PRIOR['f'] = 1 / 298.257223563 # Earth
# = Receiver =
if inventory == False:
print('Location of InSight is used!')
PRIOR['la_r'] = 4.5 # InSight
PRIOR['lo_r'] = 136 # InSight
else:
PRIOR['la_r'] = inv._networks[0].stations[
0]._latitude #4.5 # InSight
PRIOR['lo_r'] = inv._networks[0].stations[
0]._longitude #136 # InSight
PRIOR['network'] = trace.stats.network
PRIOR['station'] = trace.stats.channel
PRIOR['location'] = trace.stats.location
PRIOR['rec_depth'] = 0 #589 # For BFO station
# = Source =
## Catalogue:
if inventory == False:
PRIOR['origin_time'] = obspy.UTCDateTime(2019, 5, 23, 2, 19, 33)
PRIOR['P_pick'] = obspy.UTCDateTime(2019, 5, 23, 2, 22,
59.1) # If not know: None
PRIOR['S_pick'] = obspy.UTCDateTime(2019, 5, 23, 2, 25,
53.8) # If not know: None
PRIOR['depth_s'] = 45000
PRIOR['la_s'] = 3.45
PRIOR['lo_s'] = 164.68
Mw = 2.7
else:
PRIOR['la_s'] = inv.events[0].origins[0].latitude
PRIOR['lo_s'] = inv.events[0].origins[0].longitude
PRIOR['depth_s'] = inv.events[0].origins[0].depth
PRIOR['origin_time'] = inv.events[0].origins[0].time
Mw = None
PRIOR['M0'] = self.Magnitude2Scalarmoment(Mw) # Scalar Moment
exp = mtm.magnitude_to_moment(Mw) # Using Pyrocko package....
# self.M0 = PRIOR['M0']
PRIOR['components'] = ["Z", "R", "T"]
PRIOR['kind'] = 'displacement'
dist, az, baz = gps2dist_azimuth(lat1=PRIOR['la_s'],
lon1=PRIOR['lo_s'],
lat2=PRIOR['la_r'],
lon2=PRIOR['lo_r'],
a=PRIOR['radius'],
f=PRIOR['f'])
PRIOR['baz'] = baz
PRIOR['az'] = az
PRIOR['epi_s'] = kilometer2degrees(dist, radius=PRIOR['radius'])
# PRIOR['baz'] = 243
# PRIOR['epi_s'] = 86
# = Velocity model =
# -Mars-
# PRIOR['VELOC'] = 'http://instaseis.ethz.ch/blindtest_1s/TAYAK_1s/'
PRIOR['VELOC'] = '/opt/databases/Mars/TAYAK_1s'
# PRIOR['VELOC_taup'] = '/home/nienke/Documents/Master/Data/Database/TAYAK.npz'
PRIOR['VELOC_taup'] = '/home/nienke/MARSQUAKES/TAYAK.npz'
# -Earth-
# PRIOR['VELOC'] = 'syngine://iasp91_2s'
# PRIOR['VELOC_taup'] = 'iasp91'
# = Noise model =
# PRIOR['noise_model'] = 'Tcompact' #'STS2' #
# = Sample information =
PRIOR['npts'] = 30000
PRIOR['Temperature'] = 1
PRIOR['sample_number'] = 300000
# PRIOR['sampling_rate'] = 20 # [Hz]
PRIOR[
'sampling_rate'] = trace.stats.sampling_rate # [Hz] InSight Mission
PRIOR['directory'] = self.directory
# = Filter information =
PRIOR['P_LP'] = 1.0 / 1.0
PRIOR['P_HP'] = 1.0 / 8.0 # could also be 1.0/10.0
PRIOR['S_LP'] = 1.0 / 1.0
PRIOR['S_HP'] = 1.0 / 10.
# = Pick information in seconds =
PRIOR['Pre_P'] = 4 #10
PRIOR['Pre_S'] = 5
PRIOR['Post_P'] = 20
PRIOR['Post_S'] = 20 #40
return PRIOR
def save_rapid_dataset(acc, stations, traces, event, config):
if config.has('data_dir'):
data_dir = config.path('data_dir')
if os.path.exists(data_dir):
shutil.rmtree(data_dir)
if config.has('skeleton_dir'):
copy_files(config.path('skeleton_dir'), config.path('main_dir'))
if config.has('raw_trace_path'):
trace_selector = None
if config.has('station_filter'):
trace_selector = lambda tr: get_nsl(tr) in stations and config.station_filter(stations[get_nsl(tr)])
for raw_traces in acc.iter_traces(trace_selector=trace_selector):
io.save(raw_traces, config.path('raw_trace_path'))
dstations = stations.values()
dstations.sort( lambda a,b: cmp(a.dist_m, b.dist_m) )
save_event_info_file(config.path('event_info_path'), event)
used_traces = []
have = set()
used_stations = []
for station in dstations:
if station.station in have:
continue
used_stations.append(station)
have.add(station.station)
for tr in traces:
if get_nsl(tr) == get_nsl(station):
tr = tr.copy()
if config.trace_time_zero == 'event':
tr.shift(-event.time)
ydata = tr.get_ydata()
ydata *= config.trace_factor
used_traces.append(tr)
save_rapid_station_table(config.path('stations_path'), used_stations)
io.save(used_traces, config.path('displacement_trace_path'))
dss = util.time_to_str(event.time, format='%Y %m %d %H %M %S').split()
moment = moment_tensor.magnitude_to_moment(event.magnitude)
work_dir = pjoin(config.path('main_dir'), 'work')
rapidinp = '''
INVERSION_DIR %s
DATA_DIR %s
DATA_FILE %s
LATITUDE_NORTH %g
LONGITUDE_EAST %g
YEAR %s
MONTH %s
DAY %s
HOUR %s
MIN %s
SEC %s
DEPTH_1 %g
DEPTH_2 %g
SCAL_MOM_1 %g
SCAL_MOM_2 %g
''' % ((
pjoin('..', 'result'),
pjoin('..', 'data'),
util.time_to_str(event.time, format='%Y-%m-%d_%H-%M-S'),
event.lat, event.lon) + tuple(dss) +
(event.depth/km, event.depth/km, moment, moment))
f = open(pjoin(work_dir, 'rapidinv.inp'), 'w')
f.write(rapidinp)
f.close()
def moment(self):
return mt.magnitude_to_moment(self.magnitude)
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 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('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))
def make_time_line(self, events):
if self.cli_mode:
import matplotlib.pyplot as plt
self.fig = plt.figure()
else:
fframe = self.figure_frame()
self.fig = fframe.gcf()
gs = gridspec.GridSpec(
2, 1, figure=self.fig, hspace=0.005, top=0.95)
gs1 = gridspec.GridSpec(
2, 2, figure=self.fig)
ax = self.fig.add_subplot(gs[0])
ax1 = ax.twinx()
ax2 = self.fig.add_subplot(gs1[-1])
ax3 = self.fig.add_subplot(gs1[-2])
events.sort(key=lambda x: x.time)
magnitudes = []
i_has_magnitude = []
for i, e in enumerate(events):
if e.moment_tensor is not None:
magnitude = e.moment_tensor.magnitude
else:
magnitude = e.magnitude
if magnitude is not None:
magnitudes.append(magnitude)
i_has_magnitude.append(i)
cum_events = num.cumsum(num.ones(len(i_has_magnitude)))
moments = moment_tensor.magnitude_to_moment(num.array(magnitudes))
cum_events_magnitude = num.cumsum(moments)
times = num.array([events[i].time for i in i_has_magnitude])
timeslabels = [datetime.datetime(1970, 1, 1) +
datetime.timedelta(seconds=t) for t in times]
ax.plot(timeslabels, cum_events)
ax.set_ylabel('Cumulative number of events')
ax.axes.get_xaxis().set_ticklabels([])
ax1.plot(timeslabels, cum_events_magnitude, '-b')
ax1.set_ylabel('Cumulative moment [Nm]')
xfmt = md.DateFormatter('%Y-%m-%d')
ax1.xaxis.set_major_formatter(xfmt)
ax.yaxis.label.set_color('r')
ax1.yaxis.label.set_color('b')
ax.grid(True)
ax1.grid(True)
t0 = min(times)
if self.variation == 'daily':
normalization = 60 * 60
nbins = 24
t0_day = util.day_start(t0)
ax2.set_xlabel('hour of day')
elif self.variation == 'annual':
normalization = 60 * 60 * 24
nbins = 365
t0_day = util.year_start(t0)
ax2.set_xlabel('day of year')
binned = (times - t0_day) % (nbins * normalization)
ax2.hist(binned/normalization, bins=nbins, color='grey')
ax2.set_ylabel('Number of events')
ax2.set_xlim((0, nbins))
ax3.hist(magnitudes, bins=21, histtype='stepfilled')
ax3.set_xlabel('Magnitude')
ax3.set_ylabel('Number of events')
if self.cli_mode:
plt.show()
else:
self.fig.canvas.draw()
def make_time_line(self, events):
if self.cli_mode:
import matplotlib.pyplot as plt
self.fig = plt.figure()
else:
fframe = self.figure_frame()
self.fig = fframe.gcf()
gs = gridspec.GridSpec(2, 1)
gs.update(hspace=0.005, top=0.95)
gs1 = gridspec.GridSpec(2, 1)
gs1.update(bottom=0.06, hspace=0.01)
ax = self.fig.add_subplot(gs[0])
ax1 = ax.twinx()
ax2 = self.fig.add_subplot(gs1[-1])
events.sort(key=lambda x: x.time)
magnitudes = []
cum_events = num.cumsum(num.ones(len(events)))
for e in events:
if e.moment_tensor is not None:
magnitudes.append(e.moment_tensor.magnitude)
else:
magnitudes.append(e.magnitude)
if magnitudes[-1] is None:
magnitudes.pop()
magnitudes.append(0.)
magnitudes = moment_tensor.magnitude_to_moment(num.array(magnitudes))
cum_events_magnitude = num.cumsum(magnitudes)
times = num.array([e.time for e in events])
timeslabels = [datetime.datetime(1970, 1, 1) +
datetime.timedelta(seconds=t) for t in times]
ax.plot(timeslabels, cum_events)
ax.set_ylabel('Cumulative number of events')
ax.axes.get_xaxis().set_ticklabels([])
ax1.plot(timeslabels, cum_events_magnitude, '-b')
ax1.set_ylabel('Cumulative moment [Nm]')
xfmt = md.DateFormatter('%Y-%m-%d')
ax1.xaxis.set_major_formatter(xfmt)
ax.yaxis.label.set_color('r')
ax1.yaxis.label.set_color('b')
ax.grid(True)
ax1.grid(True)
t0 = min(times)
if self.variation == 'daily':
normalization = 60 * 60
nbins = 24
t0_day = util.day_start(t0)
ax2.set_xlabel('hour of day')
elif self.variation == 'annual':
normalization = 60 * 60 * 24
nbins = 365
t0_day = util.year_start(t0)
ax2.set_xlabel('day of year')
binned = (times - t0_day) % (nbins * normalization)
ax2.hist(binned/normalization, bins=nbins, color='grey')
ax2.set_ylabel('Number of events')
ax2.set_xlim((0, nbins))
if self.cli_mode:
plt.show()
else:
self.fig.canvas.draw()
factor_symbl_size = 5.0
for ev in events:
mag = ev.magnitude
if ev.moment_tensor is None:
ev_symb = 'c' + str(mag * factor_symbl_size) + 'p'
m.gmt.psxy(in_rows=[[ev.lon, ev.lat]],
S=ev_symb,
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
beachball_size = mag * factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(M=True,
S='%s%g' % (beachball_symbol[0],
(beachball_size) / gmtpy.cm))
else:
kwargs = dict(S='%s%g' % (beachball_symbol[0],
(beachball_size) * 2 / gmtpy.cm))
m.gmt.psmeca(in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
from matplotlib import pyplot as plt
from pyrocko import moment_tensor as pmt, cake, orthodrome
from pyrocko.plot import beachball
from pyrocko import moment_tensor as mtm
km = 1000.
# source position and mechanism
slat, slon, sdepth = 43, 32, 21 * km
magnitude = 6.5
strike = 231
dip = 43
rake = 22
m0 = mtm.magnitude_to_moment(magnitude) # Convert MW to M0 [Nm]
mt = mtm.MomentTensor(strike=strike, dip=dip, rake=rake,
scalar_moment=m0) # Create Moment tensor
m6 = [mt.mnn, mt.mee, mt.mdd, mt.mne, mt.mnd,
mt.med] # Six identical components
Mt = (m6 / mt.scalar_moment()) # Normalize the six identical components
# receiver positions
rdepth = 0.0
rlatlons = [
(35, 45),
(33, 48),
(32, 45),
]
# earth model and phase for takeoff angle computations
def PRIOR(self,stream,inventory=False):
if inventory:
if self.cat == None:
raise ValueError('No path for xml file specified!')
else:
inv = read_events(self.inv)
trace = stream.traces[0]
PRIOR = {}
PRIOR['PLOT'] = False
PRIOR['save_name'] = 'MAAK_' + trace.id.replace('.','_')
PRIOR['save_dir'] = self.directory + 'Output' #'/home/nienke/MSS'
if not os.path.exists(PRIOR['save_dir']):
os.makedirs(PRIOR['save_dir'])
# = Radius of the body used =
PRIOR['radius'] = 3389.5 # Mars
# PRIOR['radius'] = 6378137.0 # Earth
# = Flattening planet =
PRIOR['f']= 0 # Mars
# PRIOR['f'] = 1 / 298.257223563 # Earth
# = Receiver =
if inventory == False:
print('Location of InSight is used!')
PRIOR['la_r'] = 4.5 # InSight
PRIOR['lo_r'] = 136 # InSight
else:
PRIOR['la_r'] = inv._networks[0].stations[0]._latitude #4.5 # InSight
PRIOR['lo_r'] = inv._networks[0].stations[0]._longitude #136 # InSight
PRIOR['network'] = trace.stats.network
PRIOR['station'] = trace.stats.channel
PRIOR['location'] = trace.stats.location
PRIOR['rec_depth'] = 0#589 # For BFO station
# = Source =
## Catalogue:
if inventory == False:
PRIOR['origin_time'] = obspy.UTCDateTime(2019, 1, 3, 15, 00, 30)
PRIOR['depth_s'] = 38438
PRIOR['la_s'] = - 26.443
PRIOR['lo_s'] = 50.920
Mw = 4.46
else:
PRIOR['la_s'] = inv.events[0].origins[0].latitude
PRIOR['lo_s'] = inv.events[0].origins[0].longitude
PRIOR['depth_s'] = inv.events[0].origins[0].depth
PRIOR['origin_time'] = inv.events[0].origins[0].time
Mw = 4.46
PRIOR['M0'] = self.Magnitude2Scalarmoment(Mw) # Scalar Moment --> 6165950018614810.0
exp = mtm.magnitude_to_moment(Mw) # Using Pyrocko package.... --> 5495408738576270.0
# self.M0 = PRIOR['M0']
PRIOR['components'] = ["Z", "R", "T"]
PRIOR['kind'] = 'velocity'
dist, az, baz = gps2dist_azimuth(lat1=PRIOR['la_s'], lon1=PRIOR['lo_s'],
lat2=PRIOR['la_r'], lon2=PRIOR['lo_r'], a=PRIOR['radius'], f=PRIOR['f'])
PRIOR['baz'] = baz
PRIOR['az'] = az
PRIOR['epi_s'] = kilometer2degrees(dist, radius=PRIOR['radius'])
# = Velocity model =
# -Mars-
# PRIOR['VELOC'] = 'http://instaseis.ethz.ch/blindtest_1s/MAAK_1s/'
PRIOR['VELOC'] = 'http://instaseis.ethz.ch/blindtest_1s/MAAK_1s/'
# PRIOR['VELOC'] = '/home/nienke/mnt_databases/databases/blindtestmodels_1s/MAAK_1s'
# PRIOR['VELOC'] = 'mnt_databases/databases/blindtestmodels_1s/EH45TcoldCrust1'
# PRIOR['VELOC_taup'] = 'EH45TcoldCrust1b.npz'
PRIOR['VELOC_taup'] = '/home/nienke/Documents/Master/Data/Database/maak.npz'
# -Earth-
# PRIOR['VELOC'] = 'syngine://iasp91_2s'
# PRIOR['VELOC_taup'] = 'iasp91'
# = Noise model =
# PRIOR['noise_model'] = 'Tcompact' #'STS2' #
# = Sample information =
PRIOR['npts'] = 30000
PRIOR['Temperature'] = 1
PRIOR['sample_number'] = 50000
# PRIOR['sampling_rate'] = 20 # [Hz]
PRIOR['sampling_rate'] = trace.stats.sampling_rate # [Hz] InSight Mission
PRIOR['directory'] = self.directory
# = Filter information =
PRIOR['P_LP'] = 0.75
PRIOR['P_HP'] = 1.0 / 10.0
PRIOR['S_LP'] = 1.0 / 7.0
PRIOR['S_HP'] = 1.0 / 30.0
return PRIOR
def testMagnitudeMoment(self):
for i in range(1, 10):
mag = float(i)
assert abs(mag - moment_to_magnitude(magnitude_to_moment(mag))) \
< 1e-6, 'Magnitude to moment to magnitude test failed.'
for ev in events:
mag = ev.magnitude
if ev.moment_tensor is None:
ev_symb = 'c'+str(mag*factor_symbl_size)+'p'
m.gmt.psxy(
in_rows=[[ev.lon, ev.lat]],
S=ev_symb,
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
beachball_size = mag*factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)#
if m.gmt.is_gmt5():
kwargs = dict(
M=True,
S='%s%g' % (beachball_symbol[0], (beachball_size) / gmtpy.cm))
else:
kwargs = dict(
S='%s%g' % (beachball_symbol[0],
(beachball_size)*2 / gmtpy.cm))
m.gmt.psmeca(
in_rows=[data],
G=gmtpy.color('chocolate1'),
def call(self):
if not self.viewer_connected:
self.get_viewer().about_to_close.connect(
self.file_serving_worker.stop)
self.viewer_connected = True
try:
from OpenGL import GL # noqa
except ImportError:
logger.warn(
'Could not find package OpenGL, '
'if the map does not work try installing OpenGL\n'
'e.g. sudo pip install PyOpenGL')
self.cleanup()
try:
viewer = self.get_viewer()
cli_mode = False
except NoViewerSet:
viewer = None
cli_mode = True
if not cli_mode:
if self.only_active:
_, active_stations = \
self.get_active_event_and_stations()
else:
active_stations = viewer.stations.values()
elif cli_mode:
active_stations = self.stations
station_list = []
if active_stations:
for stat in active_stations:
is_blacklisted = util.match_nslc(viewer.blacklist, stat.nsl())
if (viewer and not is_blacklisted) or cli_mode:
xml_station_marker = XMLStationMarker(
nsl='.'.join(stat.nsl()),
longitude=float(stat.lon),
latitude=float(stat.lat),
active='yes')
station_list.append(xml_station_marker)
active_station_list = StationMarkerList(stations=station_list)
if self.only_active:
markers = [viewer.get_active_event_marker()]
else:
if cli_mode:
markers = self.markers
else:
markers = self.get_selected_markers()
if len(markers) == 0:
tmin, tmax = self.get_selected_time_range(fallback=True)
markers = [m for m in viewer.get_markers()
if isinstance(m, gui_util.EventMarker) and
m.tmin >= tmin and m.tmax <= tmax]
ev_marker_list = []
for m in markers:
if not isinstance(m, gui_util.EventMarker):
continue
xmleventmarker = convert_event_marker(m)
if xmleventmarker is None:
continue
ev_marker_list.append(xmleventmarker)
event_list = EventMarkerList(events=ev_marker_list)
event_station_list = MarkerLists(
station_marker_list=active_station_list,
event_marker_list=event_list)
event_station_list.validate()
if self.map_kind != 'GMT':
tempdir = self.marker_tempdir
if self.map_kind == 'Google Maps':
map_fn = 'map_googlemaps.html'
elif self.map_kind == 'OpenStreetMap':
map_fn = 'map_osm.html'
url = 'http://localhost:' + str(self.port) + '/%s' % map_fn
files = ['loadxmldoc.js', 'map_util.js', 'plates.kml', map_fn]
snuffling_dir = op.dirname(op.abspath(__file__))
for entry in files:
shutil.copy(os.path.join(snuffling_dir, entry),
os.path.join(tempdir, entry))
logger.debug('copied data to %s' % tempdir)
markers_fn = os.path.join(self.marker_tempdir, 'markers.xml')
self.data_proxy.content_to_serve.emit(self.port)
dump_xml(event_station_list, filename=markers_fn)
if self.open_external:
qg.QDesktopServices.openUrl(qc.QUrl(url))
else:
global g_counter
g_counter += 1
self.web_frame(
url,
name='Map %i (%s)' % (g_counter, self.map_kind))
else:
lats_all = []
lons_all = []
slats = []
slons = []
slabels = []
for s in active_stations:
slats.append(s.lat)
slons.append(s.lon)
slabels.append('.'.join(s.nsl()))
elats = []
elons = []
elats = []
elons = []
psmeca_input = []
markers = self.get_selected_markers()
for m in markers:
if isinstance(m, gui_util.EventMarker):
e = m.get_event()
elats.append(e.lat)
elons.append(e.lon)
if e.moment_tensor is not None:
mt = e.moment_tensor.m6()
psmeca_input.append(
(e.lon, e.lat, e.depth/1000., mt[0], mt[1],
mt[2], mt[3], mt[4], mt[5],
1., e.lon, e.lat, e.name))
else:
if e.magnitude is None:
moment = -1.
else:
moment = moment_tensor.magnitude_to_moment(
e.magnitude)
psmeca_input.append(
(e.lon, e.lat, e.depth/1000.,
moment/3., moment/3., moment/3.,
0., 0., 0., 1., e.lon, e.lat, e.name))
lats_all.extend(elats)
lons_all.extend(elons)
lats_all.extend(slats)
lons_all.extend(slons)
lats_all = num.array(lats_all)
lons_all = num.array(lons_all)
if len(lats_all) == 0:
return
center_lat, center_lon = ortho.geographic_midpoint(
lats_all, lons_all)
ntotal = len(lats_all)
clats = num.ones(ntotal) * center_lat
clons = num.ones(ntotal) * center_lon
dists = ortho.distance_accurate50m_numpy(
clats, clons, lats_all, lons_all)
maxd = num.max(dists) or 0.
m = Map(
lat=center_lat, lon=center_lon,
radius=max(10000., maxd) * 1.1,
width=35, height=25,
show_grid=True,
show_topo=True,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=False)
m.gmt.psxy(in_columns=(slons, slats), S='t15p', G='black', *m.jxyr)
for i in range(len(active_stations)):
m.add_label(slats[i], slons[i], slabels[i])
m.gmt.psmeca(
in_rows=psmeca_input, S='m1.0', G='red', C='5p,0/0/0', *m.jxyr)
tmpdir = self.tempdir()
self.outfn = os.path.join(tmpdir, '%i.png' % self.figcount)
m.save(self.outfn)
f = self.pixmap_frame(self.outfn) # noqa
def main(args=None):
if args is None:
args = sys.argv[1:]
parser = OptionParser(
usage=usage,
description=description)
parser.add_option(
'--width',
dest='width',
type='float',
default=20.0,
metavar='FLOAT',
help='set width of output image [cm] (%default)')
parser.add_option(
'--height',
dest='height',
type='float',
default=15.0,
metavar='FLOAT',
help='set height of output image [cm] (%default)')
parser.add_option(
'--topo-resolution-min',
dest='topo_resolution_min',
type='float',
default=40.0,
metavar='FLOAT',
help='minimum resolution of topography [dpi] (%default)')
parser.add_option(
'--topo-resolution-max',
dest='topo_resolution_max',
type='float',
default=200.0,
metavar='FLOAT',
help='maximum resolution of topography [dpi] (%default)')
parser.add_option(
'--no-grid',
dest='show_grid',
default=True,
action='store_false',
help='don\'t show grid lines')
parser.add_option(
'--no-topo',
dest='show_topo',
default=True,
action='store_false',
help='don\'t show topography')
parser.add_option(
'--no-cities',
dest='show_cities',
default=True,
action='store_false',
help='don\'t show cities')
parser.add_option(
'--no-illuminate',
dest='illuminate',
default=True,
action='store_false',
help='deactivate artificial illumination of topography')
parser.add_option(
'--illuminate-factor-land',
dest='illuminate_factor_land',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of land (0.5)')
parser.add_option(
'--illuminate-factor-ocean',
dest='illuminate_factor_ocean',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of ocean (0.25)')
parser.add_option(
'--theme',
choices=['topo', 'soft'],
default='topo',
help='select color theme, available: topo, soft (topo)"')
parser.add_option(
'--download-etopo1',
dest='download_etopo1',
action='store_true',
help='download full ETOPO1 topography dataset')
parser.add_option(
'--download-srtmgl3',
dest='download_srtmgl3',
action='store_true',
help='download full SRTMGL3 topography dataset')
parser.add_option(
'--make-decimated-topo',
dest='make_decimated',
action='store_true',
help='pre-make all decimated topography datasets')
parser.add_option(
'--stations',
dest='stations_fn',
metavar='FILENAME',
help='load station coordinates from FILENAME')
parser.add_option(
'--events',
dest='events_fn',
metavar='FILENAME',
help='load event coordinates from FILENAME')
parser.add_option(
'--debug',
dest='debug',
action='store_true',
default=False,
help='print debugging information to stderr')
(options, args) = parser.parse_args(args)
if options.debug:
util.setup_logging(program_name, 'debug')
else:
util.setup_logging(program_name, 'info')
if options.download_etopo1:
import pyrocko.datasets.topo.etopo1
pyrocko.datasets.topo.etopo1.download()
if options.download_srtmgl3:
import pyrocko.datasets.topo.srtmgl3
pyrocko.datasets.topo.srtmgl3.download()
if options.make_decimated:
import pyrocko.datasets.topo
pyrocko.datasets.topo.make_all_missing_decimated()
if (options.download_etopo1 or options.download_srtmgl3 or
options.make_decimated) and len(args) == 0:
sys.exit(0)
if options.theme == 'soft':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.2,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.15,
'color_wet': (216, 242, 254),
'color_dry': (238, 236, 230),
'topo_cpt_wet': 'light_sea_uniform',
'topo_cpt_dry': 'light_land_uniform'}
elif options.theme == 'topo':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.5,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.25}
events = []
if options.events_fn:
events = model.load_events(options.events_fn)
stations = []
if options.stations_fn:
stations = model.load_stations(options.stations_fn)
if not (len(args) == 4 or (
len(args) == 1 and (events or stations))):
parser.print_help()
sys.exit(1)
if len(args) == 4:
try:
lat = float(args[0])
lon = float(args[1])
radius = float(args[2])*km
except Exception:
parser.print_help()
sys.exit(1)
else:
lats, lons = latlon_arrays(stations+events)
lat, lon = map(float, od.geographic_midpoint(lats, lons))
radius = float(
num.max(od.distance_accurate50m_numpy(lat, lon, lats, lons)))
radius *= 1.1
m = automap.Map(
width=options.width,
height=options.height,
lat=lat,
lon=lon,
radius=radius,
topo_resolution_max=options.topo_resolution_max,
topo_resolution_min=options.topo_resolution_min,
show_topo=options.show_topo,
show_grid=options.show_grid,
illuminate=options.illuminate,
**color_kwargs)
logger.debug('map configuration:\n%s' % str(m))
if options.show_cities:
m.draw_cities()
if stations:
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
m.gmt.psxy(
in_columns=(lons, lats),
S='t8p',
G='black',
*m.jxyr)
for s in stations:
m.add_label(s.lat, s.lon, '%s' % '.'.join(
x for x in s.nsl() if x))
if events:
beachball_symbol = 'mt'
beachball_size = 20.0
for ev in events:
if ev.moment_tensor is None:
m.gmt.psxy(
in_rows=[[ev.lon, ev.lat]],
S='c12p',
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(
M=True,
S='%s%g' % (
beachball_symbol[0], beachball_size / gmtpy.cm))
else:
kwargs = dict(
S='%s%g' % (
beachball_symbol[0], beachball_size*2 / gmtpy.cm))
m.gmt.psmeca(
in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
*m.jxyr,
**kwargs)
m.save(args[-1])
def plot_map(stations, center, events=None, savename=None):
from pyrocko.plot.automap import Map
from pyrocko.example import get_example_data
from pyrocko import model, gmtpy
from pyrocko import moment_tensor as pmt
gmtpy.check_have_gmt()
# Generate the basic map
m = Map(lat=center[0],
lon=center[1],
radius=150000.,
width=30.,
height=30.,
show_grid=False,
show_topo=True,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=False)
# Draw some larger cities covered by the map area
m.draw_cities()
# Generate with latitute, longitude and labels of the stations
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
labels = ['.'.join(s.nsl()) for s in stations]
# Stations as black triangles.
m.gmt.psxy(in_columns=(lons, lats), S='t20p', G='black', *m.jxyr)
# Station labels
for i in range(len(stations)):
m.add_label(lats[i], lons[i], labels[i])
beachball_symbol = 'd'
factor_symbl_size = 5.0
if events is not None:
for ev in events:
mag = ev.magnitude
if ev.moment_tensor is None:
ev_symb = 'c' + str(mag * factor_symbl_size) + 'p'
m.gmt.psxy(in_rows=[[ev.lon, ev.lat]],
S=ev_symb,
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
beachball_size = mag * factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(M=True,
S='%s%g' % (beachball_symbol[0],
(beachball_size) / gmtpy.cm))
else:
kwargs = dict(S='%s%g' % (beachball_symbol[0],
(beachball_size) * 2 / gmtpy.cm))
m.gmt.psmeca(in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
*m.jxyr,
**kwargs)
if savename is None:
if events is None:
m.save('pics/stations_ridgecrest.png')
else:
m.save('pics/mechanisms_scedc_ridgecrest.png')
else:
m.save(savename)
def get_factor(self):
return mt.magnitude_to_moment(self.magnitude)
shutil.rmtree(output_root)
print('[' + sys._getframe().f_code.co_name +
'] Output files root folder \'' + output_root +
'\' existed and has been deleted, as required by script.')
else:
sys.exit(
'[' + sys._getframe().f_code.co_name +
'] Output files root folder \'' + output_root +
'\' exists, and script is not set to overwrite. Rename or delete it before running again.'
)
os.makedirs(output_root)
# Plot sources' beachballs.
for source in options_source['sources']:
mw = source['mag']
m0 = mtm.magnitude_to_moment(mw) # convert the mag to moment
strike, dip, rake = source['strike'], source['dip'], source['rake']
mt = mtm.MomentTensor(strike=strike, dip=dip, rake=rake, scalar_moment=m0)
fig = plt.figure()
ax = fig.add_subplot(111)
aa = (mt.m6_up_south_east() * m0).tolist()
bball = beach(aa, xy=(0., 0.), width=200, linewidth=1, axes=ax)
bball.set_zorder(100)
ax.add_collection(bball)
plt.title('$M_w$ ' + str(round(mw, 2)) + ' - $f_0 = ' +
str(round(options_source['f0'], 3)) + '$ Hz' + ' - depth $ = ' +
str(round(source['depth'], 3)) + '$ km')
plt.xlim([-0.5, 0.5])
from pyrocko import moment_tensor as pmt magnitude = 6.3 # Magnitude of the earthquake m0 = pmt.magnitude_to_moment(magnitude) # convert the mag to moment strike = 130 dip = 40 rake = 110 mt = pmt.MomentTensor(strike=strike, dip=dip, rake=rake, scalar_moment=m0) m6 = [mt.mnn, mt.mee, mt.mdd, mt.mne, mt.mnd, mt.med] # The six MT components print(m6/mt.scalar_moment()) # normalized MT components
def main(args=None):
if args is None:
args = sys.argv[1:]
parser = OptionParser(
usage=usage,
description=description)
parser.add_option(
'--width',
dest='width',
type='float',
default=20.0,
metavar='FLOAT',
help='set width of output image [cm] (%default)')
parser.add_option(
'--height',
dest='height',
type='float',
default=15.0,
metavar='FLOAT',
help='set height of output image [cm] (%default)')
parser.add_option(
'--topo-resolution-min',
dest='topo_resolution_min',
type='float',
default=40.0,
metavar='FLOAT',
help='minimum resolution of topography [dpi] (%default)')
parser.add_option(
'--topo-resolution-max',
dest='topo_resolution_max',
type='float',
default=200.0,
metavar='FLOAT',
help='maximum resolution of topography [dpi] (%default)')
parser.add_option(
'--no-grid',
dest='show_grid',
default=True,
action='store_false',
help='don\'t show grid lines')
parser.add_option(
'--no-topo',
dest='show_topo',
default=True,
action='store_false',
help='don\'t show topography')
parser.add_option(
'--no-cities',
dest='show_cities',
default=True,
action='store_false',
help='don\'t show cities')
parser.add_option(
'--no-illuminate',
dest='illuminate',
default=True,
action='store_false',
help='deactivate artificial illumination of topography')
parser.add_option(
'--illuminate-factor-land',
dest='illuminate_factor_land',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of land (0.5)')
parser.add_option(
'--illuminate-factor-ocean',
dest='illuminate_factor_ocean',
type='float',
metavar='FLOAT',
help='set factor for artificial illumination of ocean (0.25)')
parser.add_option(
'--theme',
choices=['topo', 'soft'],
default='topo',
help='select color theme, available: topo, soft (topo)"')
parser.add_option(
'--download-etopo1',
dest='download_etopo1',
action='store_true',
help='download full ETOPO1 topography dataset')
parser.add_option(
'--download-srtmgl3',
dest='download_srtmgl3',
action='store_true',
help='download full SRTMGL3 topography dataset')
parser.add_option(
'--make-decimated-topo',
dest='make_decimated',
action='store_true',
help='pre-make all decimated topography datasets')
parser.add_option(
'--stations',
dest='stations_fn',
metavar='FILENAME',
help='load station coordinates from FILENAME')
parser.add_option(
'--events',
dest='events_fn',
metavar='FILENAME',
help='load event coordinates from FILENAME')
parser.add_option(
'--debug',
dest='debug',
action='store_true',
default=False,
help='print debugging information to stderr')
(options, args) = parser.parse_args(args)
if options.debug:
util.setup_logging(program_name, 'debug')
else:
util.setup_logging(program_name, 'info')
if options.download_etopo1:
import pyrocko.datasets.topo.etopo1
pyrocko.datasets.topo.etopo1.download()
if options.download_srtmgl3:
import pyrocko.datasets.topo.srtmgl3
pyrocko.datasets.topo.srtmgl3.download()
if options.make_decimated:
import pyrocko.datasets.topo
pyrocko.datasets.topo.make_all_missing_decimated()
if (options.download_etopo1 or options.download_srtmgl3 or
options.make_decimated) and len(args) == 0:
sys.exit(0)
if options.theme == 'soft':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.2,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.15,
'color_wet': (216, 242, 254),
'color_dry': (238, 236, 230),
'topo_cpt_wet': 'light_sea_uniform',
'topo_cpt_dry': 'light_land_uniform'}
elif options.theme == 'topo':
color_kwargs = {
'illuminate_factor_land': options.illuminate_factor_land or 0.5,
'illuminate_factor_ocean': options.illuminate_factor_ocean or 0.25}
events = []
if options.events_fn:
events = model.load_events(options.events_fn)
stations = []
if options.stations_fn:
stations = model.load_stations(options.stations_fn)
if not (len(args) == 4 or (
len(args) == 1 and (events or stations))):
parser.print_help()
sys.exit(1)
if len(args) == 4:
try:
lat = float(args[0])
lon = float(args[1])
radius = float(args[2])*km
except Exception:
parser.print_help()
sys.exit(1)
else:
lats, lons = latlon_arrays(stations+events)
lat, lon = map(float, od.geographic_midpoint(lats, lons))
radius = float(
num.max(od.distance_accurate50m_numpy(lat, lon, lats, lons)))
radius *= 1.1
m = automap.Map(
width=options.width,
height=options.height,
lat=lat,
lon=lon,
radius=radius,
topo_resolution_max=options.topo_resolution_max,
topo_resolution_min=options.topo_resolution_min,
show_topo=options.show_topo,
show_grid=options.show_grid,
illuminate=options.illuminate,
**color_kwargs)
logger.debug('map configuration:\n%s' % str(m))
if options.show_cities:
m.draw_cities()
if stations:
lats = [s.lat for s in stations]
lons = [s.lon for s in stations]
m.gmt.psxy(
in_columns=(lons, lats),
S='t8p',
G='black',
*m.jxyr)
for s in stations:
m.add_label(s.lat, s.lon, '%s' % '.'.join(
x for x in s.nsl() if x))
if events:
beachball_symbol = 'mt'
beachball_size = 20.0
for ev in events:
if ev.moment_tensor is None:
m.gmt.psxy(
in_rows=[[ev.lon, ev.lat]],
S='c12p',
G=gmtpy.color('scarletred2'),
W='1p,black',
*m.jxyr)
else:
devi = ev.moment_tensor.deviatoric()
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
if m.gmt.is_gmt5():
kwargs = dict(
M=True,
S='%s%g' % (
beachball_symbol[0], beachball_size / gmtpy.cm))
else:
kwargs = dict(
S='%s%g' % (
beachball_symbol[0], beachball_size*2 / gmtpy.cm))
m.gmt.psmeca(
in_rows=[data],
G=gmtpy.color('chocolate1'),
E='white',
W='1p,%s' % gmtpy.color('chocolate3'),
*m.jxyr,
**kwargs)
m.save(args[-1])
from pyrocko import moment_tensor as mtm magnitude = 6.3 # Magnitude of the earthquake m0 = mtm.magnitude_to_moment(magnitude) # convert the mag to moment strike = 130 dip = 40 rake = 110 mt = mtm.MomentTensor(strike=strike, dip=dip, rake=rake, scalar_moment=m0) m6 = [mt.mnn, mt.mee, mt.mdd, mt.mne, mt.mnd, mt.med] # The six MT components print(m6/mt.scalar_moment()) # normalized MT components
def plot_spatial_with_dcs(events, eventsclusters, clusters, conf, plotdir):
'''
Plot map of seismicity clusters, with focal mechanisms
'''
lats = [ev.lat for ev in events]
lons = [ev.lon for ev in events]
# deps = [ev.depth for ev in events]
# colors = [cluster_to_color(clid) for clid in eventsclusters]
if conf.sw_filterevent:
latmin, latmax = conf.latmin, conf.latmax
lonmin, lonmax = conf.lonmin, conf.lonmax
# depmin, depmax = conf.depthmin, conf.depthmax
if latmin > latmax:
print('cases over lon +-180 still to be implemented')
sys.exit()
center = model.event(0.5 * (latmin + latmax), 0.5 * (lonmin + lonmax))
else:
latmin, latmax = min(lats) - 0.1, max(lats) + 0.1
lonmin, lonmax = min(lons) - 0.1, max(lons) + 0.1
# depmin = 0.*km
# depmax = 1.05*max(deps)
center = od.Loc(0.5 * (latmin + latmax), 0.5 * (lonmin + lonmax))
# Map size
if conf.sw_manual_radius:
safe_radius = conf.map_radius
else:
corners = [od.Loc(latmin, lonmin), od.Loc(latmin, lonmax)]
dist1 = od.distance_accurate50m(center, corners[0])
dist2 = od.distance_accurate50m(center, corners[1])
safe_radius = max(dist1, dist2)
# Generate the basic map
m = Map(lat=center.lat,
lon=center.lon,
radius=safe_radius,
width=30.,
height=30.,
show_grid=False,
show_topo=False,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=False)
if conf.sw_filterevent:
rectlons = [lonmin, lonmin, lonmax, lonmax, lonmin]
rectlats = [latmin, latmax, latmax, latmin, latmin]
m.gmt.psxy(in_columns=(rectlons, rectlats),
W='thin,0/0/0,dashed',
*m.jxyr)
# Draw some larger cities covered by the map area
m.draw_cities()
# Events in clusters
factor_symbl_size = 5.
beachball_symbol = 'd'
for id_cluster in clusters:
col = cluster_to_color(id_cluster)
g_col = color2rgb(col)
for iev, evcl in enumerate(eventsclusters):
if evcl == id_cluster:
ev = events[iev]
if ev.moment_tensor is not None:
factor_symbl_size = ev.magnitude
devi = ev.moment_tensor.deviatoric()
beachball_size = 3. * factor_symbl_size
mt = devi.m_up_south_east()
mt = mt / ev.moment_tensor.scalar_moment() \
* pmt.magnitude_to_moment(5.0)
m6 = pmt.to6(mt)
if m.gmt.is_gmt5():
kwargs = dict(M=True,
S='%s%g' % (beachball_symbol[0],
(beachball_size) / gmtpy.cm))
else:
kwargs = dict(S='%s%g' %
(beachball_symbol[0],
(beachball_size) * 2 / gmtpy.cm))
data = (ev.lon, ev.lat, 10) + tuple(m6) + (1, 0, 0)
m.gmt.psmeca(in_rows=[data],
G=g_col,
E='white',
W='1p,%s' % g_col,
*m.jxyr,
**kwargs)
figname = os.path.join(plotdir, 'plot_map_with_dcs.' + conf.figure_format)
m.save(figname)
def plot_tm(events, eventsclusters, clusters, conf, plotdir):
'''
Plot magnitude vs time for the seismicity clusters.
Plot cumulative moment vs time for the seismicity clusters.
'''
times = [ev.time for ev in events]
orig_dates = [datetime.datetime.fromtimestamp(ev.time) for ev in events]
mpl_dates = dates.date2num(orig_dates)
mags = [ev.magnitude for ev in events]
colors = [cluster_to_color(clid) for clid in eventsclusters]
dates_format = dates.DateFormatter('%Y-%m-%d')
if conf.sw_filterevent:
tmin, tmax = conf.tmin, conf.tmax
magmin, magmax = conf.magmin, conf.magmax
else:
if (max(times) - min(times)) / 86400. > 720.:
dt = 86400.
dates_loc = dates.YearLocator()
elif (max(times) - min(times)) / 86400. > 10.:
dt = 86400.
dates_loc = dates.MonthLocator()
elif (max(times) - min(times)) / 3600. > 10.:
dt = 3600.
dates_loc = dates.DayLocator()
else:
dt = 1.
dates_loc = dates.HourLocator()
dates_format = dates.DateFormatter('%Y-%m-%d %h:%m:%s')
tmin, tmax = min(times) - dt, max(times) + dt
magmin, magmax = min(mags) - 0.1, max(mags) + 0.1
dmin = dates.date2num(datetime.datetime.fromtimestamp(tmin))
dmax = dates.date2num(datetime.datetime.fromtimestamp(tmax))
f = plt.figure()
f.suptitle('Temporal evolution of seismicity clusters', fontsize=14)
ax = f.add_subplot(111)
ax.scatter(mpl_dates, mags, s=15., c=colors, alpha=0.5)
ax.xaxis.set_major_locator(dates_loc)
ax.xaxis.set_major_formatter(dates_format)
plt.xlim(xmax=dmax, xmin=dmin)
plt.ylim(ymax=magmax, ymin=magmin)
plt.xticks(rotation=45.)
plt.xlabel("Time")
plt.ylabel("Magnitude")
plt.subplots_adjust(bottom=.3)
figname = os.path.join(plotdir, 'plot_tm.' + conf.figure_format)
f.savefig(figname)
times = [ev.time for ev in events]
orig_dates = [datetime.datetime.fromtimestamp(ev.time) for ev in events]
mpl_dates = dates.date2num(orig_dates)
colors = [cluster_to_color(clid) for clid in eventsclusters]
dates_format = dates.DateFormatter('%Y-%m-%d')
if conf.sw_filterevent:
tmin, tmax = conf.tmin, conf.tmax
magmin, magmax = conf.magmin, conf.magmax
else:
if (max(times) - min(times)) / 86400. > 720.:
dt = 86400.
dates_loc = dates.YearLocator()
elif (max(times) - min(times)) / 86400. > 10.:
dt = 86400.
dates_loc = dates.MonthLocator()
elif (max(times) - min(times)) / 3600. > 10.:
dt = 3600.
dates_loc = dates.DayLocator()
else:
dt = 1.
dates_loc = dates.HourLocator()
dates_format = dates.DateFormatter('%Y-%m-%d %h:%m:%s')
tmin, tmax = min(times) - dt, max(times) + dt
dmin = dates.date2num(datetime.datetime.fromtimestamp(tmin))
dmax = dates.date2num(datetime.datetime.fromtimestamp(tmax))
f = plt.figure()
f.suptitle('Cumulative moment release of seismicity clusters', fontsize=14)
ax = f.add_subplot(111)
cum_dates = []
d1 = dates.date2num(datetime.datetime.fromtimestamp(tmin))
cum_dates.append(d1)
cum_m0s = []
cm0 = 0.
cum_m0s.append(cm0)
for ev in events:
print(ev.name, ev.time)
new_date = dates.date2num(datetime.datetime.fromtimestamp(ev.time))
cum_dates.append(new_date)
cum_dates.append(new_date)
cum_m0s.append(cm0)
cm0 = cm0 + pmt.magnitude_to_moment(ev.magnitude)
cum_m0s.append(cm0)
cum_dates.append(dmax)
cum_m0s.append(cm0)
cm0max = cm0
cm0min = pmt.magnitude_to_moment(min(mags) - 0.5)
cm0max = 2. * cm0
ax.plot(cum_dates, cum_m0s, color='black', alpha=0.5)
for irun in clusters:
cl_events = []
for iev, ev in enumerate(events):
if irun == eventsclusters[iev]:
cl_events.append(ev)
# cl_events = [events[iev] for iev in len(events)
# if irun == eventsclusters[iev]]
print('A', irun, cl_events)
cum_dates = []
d1 = dates.date2num(datetime.datetime.fromtimestamp(tmin))
cum_dates.append(d1)
cum_m0s = []
cm0 = 0.
cum_m0s.append(cm0)
color = cluster_to_color(irun)
for ev in cl_events:
print(ev.name, ev.time)
new_date = dates.date2num(datetime.datetime.fromtimestamp(ev.time))
cum_dates.append(new_date)
cum_dates.append(new_date)
cum_m0s.append(cm0)
cm0 = cm0 + pmt.magnitude_to_moment(ev.magnitude)
cum_m0s.append(cm0)
cum_dates.append(dmax)
cum_m0s.append(cm0)
ax.plot(cum_dates, cum_m0s, color=color, alpha=0.5)
ax.xaxis.set_major_locator(dates_loc)
ax.xaxis.set_major_formatter(dates_format)
plt.xlim(xmax=dmax, xmin=dmin)
plt.ylim(ymax=cm0max, ymin=cm0min)
plt.xticks(rotation=45.)
plt.xlabel("Time")
plt.ylabel("Cumulative Scalar Moment [Nm]")
plt.yscale('log')
plt.subplots_adjust(bottom=.3)
figname = os.path.join(plotdir, 'plot_tcm0.' + conf.figure_format)
f.savefig(figname)
from pyrocko import moment_tensor as pmt
import numpy as num
r2d = 180. / num.pi
magnitude = 6.3 # Magnitude of the earthquake
exp = pmt.magnitude_to_moment(magnitude) # convert the mag to moment in [Nm]
# init pyrocko moment tensor
m = pmt.MomentTensor(mnn=2.34 * exp,
mee=-2.64 * exp,
mdd=0.295 * exp,
mne=1.49 * exp,
mnd=0.182 * exp,
med=-0.975 * exp)
print(m) # print moment tensor
# gives out both nodal planes:
(s1, d1, r1), (s2, d2, r2) = m.both_strike_dip_rake()
print('strike1=%g, dip1=%g, rake1=%g' % (s1, d1, r1))
print('strike2=%g, dip2=%g, rake2=%g' % (s2, d2, r2))
# p-axis normal vector in north-east-down coordinates
p_ned = m.p_axis().A[0]
print('p_ned=(%g, %g, %g)' % tuple(p_ned))
# convert to azimuth and dip
def test_rect_source(self):
store = self.dummy_homogeneous_store()
depth = 10 * km
# shear
rect1 = gf.RectangularSource(depth=10 * km,
magnitude=5.0,
width=5 * km,
length=5 * km)
rect2 = gf.RectangularSource(
depth=depth,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
store.config.earthmodel_1d.material(depth).shear_modulus()),
width=5 * km,
length=5 * km)
self.assertAlmostEqual(
rect1.get_magnitude(),
rect2.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
# tensile
rect3 = gf.RectangularSource(depth=depth,
magnitude=5.0,
width=5 * km,
length=5 * km,
opening_fraction=1.)
rect4 = gf.RectangularSource(
depth=depth,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
store.config.earthmodel_1d.material(depth).bulk()),
width=5 * km,
length=5 * km,
opening_fraction=1.)
self.assertAlmostEqual(
rect3.get_magnitude(),
rect4.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
# mixed
of = -0.4
rect5 = gf.RectangularSource(depth=depth,
magnitude=5.0,
width=5 * km,
length=5 * km,
opening_fraction=of)
rect6 = gf.RectangularSource(
depth=depth,
slip=pmt.magnitude_to_moment(5.0) /
(5 * km * 5 * km *
(store.config.earthmodel_1d.material(depth).bulk() * abs(of) +
store.config.earthmodel_1d.material(depth).shear_modulus() *
(1 - abs(of)))),
width=5 * km,
length=5 * km,
opening_fraction=of)
self.assertAlmostEqual(
rect5.get_magnitude(),
rect6.get_magnitude(store,
gf.Target(interpolation='nearest_neighbor')))
class Event(Object):
'''Seismic event representation
:param lat: latitude of hypocenter (default 0.0)
:param lon: longitude of hypocenter (default 0.0)
:param time: origin time as float in seconds after '1970-01-01 00:00:00
:param name: event identifier as string (optional)
:param depth: source depth (optional)
:param magnitude: magnitude of event (optional)
:param region: source region (optional)
:param catalog: name of catalog that lists this event (optional)
:param moment_tensor: moment tensor as
:py:class:`moment_tensor.MomentTensor` instance (optional)
:param duration: source duration as float (optional)
'''
lat = Float.T(default=0.0)
lon = Float.T(default=0.0)
time = Timestamp.T(default=util.str_to_time('1970-01-01 00:00:00'))
name = String.T(default='', optional=True)
depth = Float.T(optional=True)
magnitude = Float.T(optional=True)
magnitude_type = String.T(optional=True)
region = String.T(optional=True)
catalog = String.T(optional=True)
moment_tensor = moment_tensor.MomentTensor.T(optional=True)
duration = Float.T(optional=True)
def __init__(self,
lat=0.,
lon=0.,
time=0.,
name='',
depth=None,
magnitude=None,
magnitude_type=None,
region=None,
load=None,
loadf=None,
catalog=None,
moment_tensor=None,
duration=None):
vals = None
if load is not None:
vals = Event.oldload(load)
elif loadf is not None:
vals = Event.oldloadf(loadf)
if vals:
lat, lon, time, name, depth, magnitude, magnitude_type, region, \
catalog, moment_tensor, duration = vals
Object.__init__(self,
lat=lat,
lon=lon,
time=time,
name=name,
depth=depth,
magnitude=magnitude,
magnitude_type=magnitude_type,
region=region,
catalog=catalog,
moment_tensor=moment_tensor,
duration=duration)
def time_as_string(self):
return util.time_to_str(self.time)
def set_name(self, name):
self.name = name
def olddump(self, filename):
file = open(filename, 'w')
self.olddumpf(file)
file.close()
def olddumpf(self, file):
file.write('name = %s\n' % self.name)
file.write('time = %s\n' % util.time_to_str(self.time))
if self.lat is not None:
file.write('latitude = %.12g\n' % self.lat)
if self.lon is not None:
file.write('longitude = %.12g\n' % self.lon)
if self.magnitude is not None:
file.write('magnitude = %g\n' % self.magnitude)
file.write('moment = %g\n' %
moment_tensor.magnitude_to_moment(self.magnitude))
if self.magnitude_type is not None:
file.write('magnitude_type = %s\n' % self.magnitude_type)
if self.depth is not None:
file.write('depth = %.10g\n' % self.depth)
if self.region is not None:
file.write('region = %s\n' % self.region)
if self.catalog is not None:
file.write('catalog = %s\n' % self.catalog)
if self.moment_tensor is not None:
m = self.moment_tensor.m()
sdr1, sdr2 = self.moment_tensor.both_strike_dip_rake()
file.write(
('mnn = %g\nmee = %g\nmdd = %g\nmne = %g\nmnd = %g\nmed = %g\n'
'strike1 = %g\ndip1 = %g\nrake1 = %g\n'
'strike2 = %g\ndip2 = %g\nrake2 = %g\n') %
((m[0, 0], m[1, 1], m[2, 2], m[0, 1], m[0, 2], m[1, 2]) +
sdr1 + sdr2))
if self.duration is not None:
file.write('duration = %g\n' % self.duration)
@staticmethod
def unique(events,
deltat=10.,
group_cmp=(lambda a, b: cmp(a.catalog, b.catalog))):
groups = Event.grouped(events, deltat)
events = []
for group in groups:
if group:
group.sort(group_cmp)
events.append(group[-1])
return events
@staticmethod
def grouped(events, deltat=10.):
events = list(events)
groups = []
for ia, a in enumerate(events):
groups.append([])
haveit = False
for ib, b in enumerate(events[:ia]):
if abs(b.time - a.time) < deltat:
groups[ib].append(a)
haveit = True
break
if not haveit:
groups[ia].append(a)
groups = [g for g in groups if g]
groups.sort(key=lambda g: sum(e.time for e in g) / len(g))
return groups
@staticmethod
def dump_catalog(events, filename=None, stream=None):
if filename is not None:
file = open(filename, 'w')
else:
file = stream
try:
i = 0
for ev in events:
ev.olddumpf(file)
file.write('--------------------------------------------\n')
i += 1
finally:
if filename is not None:
file.close()
@staticmethod
def oldload(filename):
with open(filename, 'r') as file:
return Event.oldloadf(file)
@staticmethod
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)
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('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))
def testMagnitudeMoment(self):
for i in range(1, 10):
mag = float(i)
assert (
abs(mag - moment_to_magnitude(magnitude_to_moment(mag))) < 1e-6
), "Magnitude to moment to magnitude test failed."
def call(self):
if not self.viewer_connected:
self.get_viewer().about_to_close.connect(
self.file_serving_worker.stop)
self.viewer_connected = True
try:
from OpenGL import GL # noqa
except ImportError:
logger.warn('Could not find package OpenGL, '
'if the map does not work try installing OpenGL\n'
'e.g. sudo pip install PyOpenGL')
self.cleanup()
try:
viewer = self.get_viewer()
cli_mode = False
except NoViewerSet:
viewer = None
cli_mode = True
if not cli_mode:
if self.only_active:
_, active_stations = \
self.get_active_event_and_stations()
else:
active_stations = viewer.stations.values()
elif cli_mode:
active_stations = self.stations
station_list = []
if active_stations:
for stat in active_stations:
is_blacklisted = util.match_nslc(viewer.blacklist, stat.nsl())
if (viewer and not is_blacklisted) or cli_mode:
xml_station_marker = XMLStationMarker(
nsl='.'.join(stat.nsl()),
longitude=float(stat.lon),
latitude=float(stat.lat),
active='yes')
station_list.append(xml_station_marker)
active_station_list = StationMarkerList(stations=station_list)
if self.only_active:
markers = [viewer.get_active_event_marker()]
else:
if cli_mode:
markers = self.markers
else:
markers = self.get_selected_markers()
if len(markers) == 0:
tmin, tmax = self.get_selected_time_range(fallback=True)
markers = [
m for m in viewer.get_markers()
if isinstance(m, gui_util.EventMarker)
and m.tmin >= tmin and m.tmax <= tmax
]
ev_marker_list = []
for m in markers:
if not isinstance(m, gui_util.EventMarker):
continue
xmleventmarker = convert_event_marker(m)
if xmleventmarker is None:
continue
ev_marker_list.append(xmleventmarker)
event_list = EventMarkerList(events=ev_marker_list)
event_station_list = MarkerLists(
station_marker_list=active_station_list,
event_marker_list=event_list)
event_station_list.validate()
if self.map_kind != 'GMT':
tempdir = self.marker_tempdir
if self.map_kind == 'Google Maps':
map_fn = 'map_googlemaps.html'
elif self.map_kind == 'OpenStreetMap':
map_fn = 'map_osm.html'
url = 'http://localhost:' + str(self.port) + '/%s' % map_fn
files = ['loadxmldoc.js', 'map_util.js', 'plates.kml', map_fn]
snuffling_dir = op.dirname(op.abspath(__file__))
for entry in files:
shutil.copy(os.path.join(snuffling_dir, entry),
os.path.join(tempdir, entry))
logger.debug('copied data to %s' % tempdir)
markers_fn = os.path.join(self.marker_tempdir, 'markers.xml')
self.data_proxy.content_to_serve.emit(self.port)
dump_xml(event_station_list, filename=markers_fn)
if self.open_external:
qg.QDesktopServices.openUrl(qc.QUrl(url))
else:
global g_counter
g_counter += 1
self.web_frame(url,
name='Map %i (%s)' % (g_counter, self.map_kind))
else:
lats_all = []
lons_all = []
slats = []
slons = []
slabels = []
for s in active_stations:
slats.append(s.lat)
slons.append(s.lon)
slabels.append('.'.join(s.nsl()))
elats = []
elons = []
elats = []
elons = []
psmeca_input = []
markers = self.get_selected_markers()
for m in markers:
if isinstance(m, gui_util.EventMarker):
e = m.get_event()
elats.append(e.lat)
elons.append(e.lon)
if e.moment_tensor is not None:
mt = e.moment_tensor.m6()
psmeca_input.append((e.lon, e.lat, e.depth / 1000.,
mt[0], mt[1], mt[2], mt[3], mt[4],
mt[5], 1., e.lon, e.lat, e.name))
else:
if e.magnitude is None:
moment = -1.
else:
moment = moment_tensor.magnitude_to_moment(
e.magnitude)
psmeca_input.append(
(e.lon, e.lat, e.depth / 1000., moment / 3.,
moment / 3., moment / 3., 0., 0., 0., 1.,
e.lon, e.lat, e.name))
lats_all.extend(elats)
lons_all.extend(elons)
lats_all.extend(slats)
lons_all.extend(slons)
lats_all = num.array(lats_all)
lons_all = num.array(lons_all)
if len(lats_all) == 0:
return
center_lat, center_lon = ortho.geographic_midpoint(
lats_all, lons_all)
ntotal = len(lats_all)
clats = num.ones(ntotal) * center_lat
clons = num.ones(ntotal) * center_lon
dists = ortho.distance_accurate50m_numpy(clats, clons, lats_all,
lons_all)
maxd = num.max(dists) or 0.
m = Map(lat=center_lat,
lon=center_lon,
radius=max(10000., maxd) * 1.1,
width=35,
height=25,
show_grid=True,
show_topo=True,
color_dry=(238, 236, 230),
topo_cpt_wet='light_sea_uniform',
topo_cpt_dry='light_land_uniform',
illuminate=True,
illuminate_factor_ocean=0.15,
show_rivers=False,
show_plates=False)
m.gmt.psxy(in_columns=(slons, slats), S='t15p', G='black', *m.jxyr)
for i in range(len(active_stations)):
m.add_label(slats[i], slons[i], slabels[i])
m.gmt.psmeca(in_rows=psmeca_input,
S='m1.0',
G='red',
C='5p,0/0/0',
*m.jxyr)
tmpdir = self.tempdir()
self.outfn = os.path.join(tmpdir, '%i.png' % self.figcount)
m.save(self.outfn)
f = self.pixmap_frame(self.outfn) # noqa
def plot_gnss(gnss_target, result, ifig, vertical=False):
campaign = gnss_target.campaign
item = PlotItem(
name='fig_%i' % ifig,
attributes={'targets': gnss_target.path},
title=u'Static GNSS Surface Displacements - Campaign %s' %
campaign.name,
description=u'''
Static surface displacement from GNSS campaign %s (black vectors) and
displacements derived from best model (red).
''' % campaign.name)
event = source.pyrocko_event()
locations = campaign.stations + [event]
lat, lon = od.geographic_midpoint_locations(locations)
if self.radius is None:
coords = num.array([loc.effective_latlon for loc in locations])
radius = od.distance_accurate50m_numpy(lat[num.newaxis],
lon[num.newaxis],
coords[:, 0].max(),
coords[:, 1]).max()
radius *= 1.1
if radius < 30. * km:
logger.warn('Radius of GNSS campaign %s too small, defaulting'
' to 30 km' % campaign.name)
radius = 30 * km
model_camp = gnss.GNSSCampaign(stations=copy.deepcopy(
campaign.stations),
name='grond model')
for ista, sta in enumerate(model_camp.stations):
sta.north.shift = result.statics_syn['displacement.n'][ista]
sta.north.sigma = 0.
sta.east.shift = result.statics_syn['displacement.e'][ista]
sta.east.sigma = 0.
if sta.up:
sta.up.shift = -result.statics_syn['displacement.d'][ista]
sta.up.sigma = 0.
m = automap.Map(width=self.size_cm[0],
height=self.size_cm[1],
lat=lat,
lon=lon,
radius=radius,
show_topo=self.show_topo,
show_grid=self.show_grid,
show_rivers=self.show_rivers,
color_wet=(216, 242, 254),
color_dry=(238, 236, 230))
all_stations = campaign.stations + model_camp.stations
offset_scale = num.zeros(len(all_stations))
for ista, sta in enumerate(all_stations):
for comp in sta.components.values():
offset_scale[ista] += comp.shift
offset_scale = num.sqrt(offset_scale**2).max()
m.add_gnss_campaign(campaign,
psxy_style={
'G': 'black',
'W': '0.8p,black',
},
offset_scale=offset_scale,
vertical=vertical)
m.add_gnss_campaign(model_camp,
psxy_style={
'G': 'red',
'W': '0.8p,red',
't': 30,
},
offset_scale=offset_scale,
vertical=vertical,
labels=False)
if isinstance(problem, CMTProblem) \
or isinstance(problem, VLVDProblem):
from pyrocko import moment_tensor
from pyrocko.plot import gmtpy
mt = event.moment_tensor.m_up_south_east()
ev_lat, ev_lon = event.effective_latlon
xx = num.trace(mt) / 3.
mc = num.matrix([[xx, 0., 0.], [0., xx, 0.], [0., 0., xx]])
mc = mt - mc
mc = mc / event.moment_tensor.scalar_moment() * \
moment_tensor.magnitude_to_moment(5.0)
m6 = tuple(moment_tensor.to6(mc))
symbol_size = 20.
m.gmt.psmeca(S='%s%g' % ('d', symbol_size / gmtpy.cm),
in_rows=[(ev_lon, ev_lat, 10) + m6 + (1, 0, 0)],
M=True,
*m.jxyr)
elif isinstance(problem, RectangularProblem):
m.gmt.psxy(in_rows=source.outline(cs='lonlat'),
L='+p2p,black',
W='1p,black',
G='black',
t=60,
*m.jxyr)
elif isinstance(problem, VolumePointProblem):
ev_lat, ev_lon = event.effective_latlon
dV = abs(source.volume_change)
sphere_radius = num.cbrt(dV / (4. / 3. * num.pi))
volcanic_circle = [ev_lon, ev_lat, '%fe' % sphere_radius]
m.gmt.psxy(S='E-',
in_rows=[volcanic_circle],
W='1p,black',
G='orange3',
*m.jxyr)
return (item, m)
def make_time_line(self, markers, stations=None, cmap=cmap):
events = [m.get_event() for m in markers]
kinds = num.array([m.kind for m in markers])
if self.cli_mode:
self.fig = plt.figure()
else:
fframe = self.figure_frame()
self.fig = fframe.gcf()
ax = self.fig.add_subplot(311)
ax_cum = ax.twinx()
ax1 = self.fig.add_subplot(323)
ax2 = self.fig.add_subplot(325, sharex=ax1)
ax3 = self.fig.add_subplot(324, sharey=ax1)
num_events = len(events)
data = num.zeros((num_events, 6))
column_to_index = dict(zip(['magnitude', 'latitude', 'longitude', 'depth', 'time', 'kind'],
range(6)))
c2i = column_to_index
for i, e in enumerate(events):
if e.magnitude:
mag = e.magnitude
else:
mag = 0.
data[i, :] = mag, e.lat, e.lon, e.depth, e.time, kinds[i]
s_coords = num.array([])
s_labels = []
if stations is not None:
s_coords = num.array([(s.lon, s.lat, s.elevation-s.depth) for s in stations])
s_labels = ['.'.join(s.nsl()) for s in stations]
isorted = num.argsort(data[:, c2i['time']])
data = data[isorted]
def _D(key):
return data[:, c2i[key]]
tmin = _D('time').min()
tmax = _D('time').max()
lon_max = _D('longitude').max()
lon_min = _D('longitude').min()
lat_max = _D('latitude').max()
lat_min = _D('latitude').min()
depths_min = _D('depth').min()
depths_max = _D('depth').max()
mags_min = _D('magnitude').min()
mags_max = _D('magnitude').max()
moments = moment_tensor.magnitude_to_moment(_D('magnitude'))
dates = list(map(datetime.fromtimestamp, _D('time')))
fds = mdates.date2num(dates)
tday = 3600*24
tweek = tday*7
if tmax-tmin < 1*tday:
hfmt = mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
elif tmax-tmin < tweek*52:
hfmt = mdates.DateFormatter('%Y-%m-%d')
else:
hfmt = mdates.DateFormatter('%Y/%m')
color_values = _D(self.color_by)
color_args = dict(c=color_values, vmin=color_values.min(),
vmax=color_values.max(), cmap=cmap)
ax.scatter(fds, _D('magnitude'), s=20, **color_args)
ax.xaxis.set_major_formatter(hfmt)
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.set_ylim((mags_min, mags_max*1.10))
ax.set_xlim(map(datetime.fromtimestamp, (tmin, tmax)))
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.set_ylabel('Magnitude')
init_pos = ax.get_position()
ax_cum.plot(fds, num.cumsum(moments), 'grey')
ax_cum.xaxis.set_major_formatter(hfmt)
ax_cum.spines['top'].set_color('none')
ax_cum.spines['right'].set_color('grey')
ax_cum.set_ylabel('Cumulative seismic moment')
lats_min = num.array([lat_min for x in range(num_events)])
lons_min = num.array([lon_min for x in range(num_events)])
if self.coord_system == 'cartesian':
lats, lons = orthodrome.latlon_to_ne_numpy(
lats_min, lons_min, _D('latitude'), _D('longitude'))
_x = num.empty((len(s_coords), 3))
for i, (slon, slat, sele) in enumerate(s_coords):
n, e = orthodrome.latlon_to_ne(lat_min, lon_min, slat, slon)
_x[i, :] = (e, n, sele)
s_coords = _x
else:
lats = _D('latitude')
lons = _D('longitude')
s_coords = s_coords.T
ax1.scatter(lons, lats, s=20, **color_args)
ax1.set_aspect('equal')
ax1.grid(True, which='both')
ax1.set_ylabel('Northing [m]')
ax1.get_yaxis().tick_left()
if len(s_coords):
ax1.scatter(s_coords[0], s_coords[1], marker='v', s=40, color='black')
for c, sl in zip(s_coords.T, s_labels):
ax1.text(c[0], c[1], sl, color='black')
# bottom left plot
ax2.scatter(lons, _D('depth'), s=20, **color_args)
ax2.grid(True)
ax2.set_xlabel('Easting [m]')
ax2.set_ylabel('Depth [m]')
ax2.get_yaxis().tick_left()
ax2.get_xaxis().tick_bottom()
ax2.invert_yaxis()
ax2.text(1.1, 0, 'Origin at:\nlat=%1.3f, lon=%1.3f' %
(lat_min, lon_min), transform=ax2.transAxes)
# top right plot
ax3.scatter(_D('depth'), lats, s=20, **color_args)
ax3.set_xlim((depths_min, depths_max))
ax3.grid(True)
ax3.set_xlabel('Depth [m]')
ax3.get_xaxis().tick_bottom()
ax3.get_yaxis().tick_right()
self.fig.subplots_adjust(
bottom=0.05, right=0.95, left=0.075, top=0.95, wspace=0.02, hspace=0.02)
init_pos.y0 += 0.05
ax.set_position(init_pos)
ax_cum.set_position(init_pos)
if self.cli_mode:
plt.show()
else:
self.fig.canvas.draw()
