def get_source(self, x):
d = self.get_parameter_dict(x)
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]))
stf1 = gf.HalfSinusoidSTF(duration=float(d.duration1))
stf2 = gf.HalfSinusoidSTF(duration=float(d.duration2))
source = self.base_source.clone(stf1=stf1, stf2=stf2, **p)
return source
def test_discretize_rect_source_stf(self):
store = self.dummy_homogeneous_store()
target = gf.Target(interpolation='nearest_neighbor')
stf = gf.HalfSinusoidSTF(duration=3.)
for source in [
gf.RectangularSource(depth=10 * km,
slip=0.5,
width=5 * km,
length=5 * km,
stf=stf,
stf_mode='pre'),
gf.RectangularSource(depth=10 * km,
magnitude=5.0,
width=5 * km,
length=5 * km,
decimation_factor=2,
stf=stf,
stf_mode='pre')
]:
dsource = source.discretize_basesource(store, target)
amplitudes = source._discretize(store, target)[2]
assert amplitudes[0] != amplitudes[1]
m1 = source.get_moment(store, target)
m2 = dsource.centroid().pyrocko_moment_tensor().scalar_moment()
assert abs(m1 - m2) < abs(m1 + m2) * 1e-6
def test_effective_durations(self):
deltat = 1e-4
for stf in [
gf.HalfSinusoidSTF(duration=2.0),
gf.HalfSinusoidSTF(duration=2.0, exponent=2),
gf.TriangularSTF(duration=2.0, peak_ratio=0.),
gf.TriangularSTF(duration=2.0, peak_ratio=1.),
gf.TriangularSTF(duration=2.0, peak_ratio=0.5),
gf.BoxcarSTF(duration=2.0)
]:
t, a = stf.discretize_t(deltat, 0.0)
t0 = stf.centroid_time(0.0)
edur = num.sqrt(num.sum((t - t0)**2 * a)) * 2. * num.sqrt(3.)
assert abs(edur - stf.effective_duration) < 1e-3
def __init__(self):
Snuffling.__init__(self)
self.stf_types = ['half sin', 'triangular', 'boxcar', 'None']
self.stf_instances = [
gf.HalfSinusoidSTF(),
gf.TriangularSTF(),
gf.BoxcarSTF(), None
]
def get_source(self, x):
d = self.get_parameter_dict(x)
p = {
k: float(self.ranges[k].make_relative(self.base_source[k], d[k]))
for k in self.base_source.keys() if k in d
}
stf = None
if self.has_waveforms:
stf = gf.HalfSinusoidSTF(duration=float(d.duration))
source = self.base_source.clone(stf=stf, **p)
return source
def test_stf_half_sinusoid(self, plot=False):
from matplotlib import pyplot as plt
for duration in [0., 1., 2., 3.]:
tref = 10.02
stf = gf.HalfSinusoidSTF(duration=duration, anchor=0.)
t, a = stf.discretize_t(deltat=0.1, tref=tref)
assert numeq(stf.centroid_time(tref), tref, 1e-5)
if plot:
plt.plot(t, a)
plt.plot(t, a, 'o')
if plot:
plt.show()
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]))
stf = gf.HalfSinusoidSTF(duration=float(d.duration))
source = self.base_source.clone(m6=m6, stf=stf, **p)
return source
def get_problem(self, event, target_groups, targets):
if event.depth is None:
event.depth = 0.
base_source = gf.MTSource.from_pyrocko_event(event)
base_source.stf = gf.HalfSinusoidSTF(duration=event.duration or 0.0)
subs = dict(event_name=event.name,
event_time=util.time_to_str(event.time))
problem = CMTProblem(name=expand_template(self.name_template, subs),
base_source=base_source,
target_groups=target_groups,
targets=targets,
ranges=self.ranges,
distance_min=self.distance_min,
mt_type=self.mt_type,
norm_exponent=self.norm_exponent)
return problem
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)
[stations, targets, event, data_traces] = inputf.load_seism_data(datadir)
engine = gf.LocalEngine(store_superdirs=storehomedir)
sources = [
gf.RectangularSource(lat=29.124977942689519,
lon=34.871469702014863,
width=24 * km,
length=58 * km,
time=817013725.5571846,
depth=12 * km,
strike=206.3701904106799,
dip=73.0785305323845,
rake=-8.135103051434966,
magnitude=7.01,
stf=gf.HalfSinusoidSTF(duration=3., anchor=-1.))
]
## gf.RectangularSource(
## lat=29.0,
## lon=35.0,
## width=4 * km,
## length=5 * km,
## time=817013720.5571846,
## depth=5 * km,
## strike=180.0,
## dip=70.,
## rake=-7.,
## magnitude=4.01,
## stf=gf.HalfSinusoidSTF(duration=2., anchor=-1.))]
