def test_scenario_map(self):
tempdir = mkdtemp(prefix='pyrocko-scenario')
self.tempdirs.append(tempdir)
generator = self.generator
engine = gf.get_engine()
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('plot', generator)
s = collection.get_scenario('plot')
s.get_map()
def test_scenario_gnss(self):
tempdir = mkdtemp(prefix='pyrocko-scenario')
self.tempdirs.append(tempdir)
generator = self.generator
engine = gf.get_engine()
generator.init_modelling(engine)
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('gnss', generator)
s = collection.get_scenario('gnss')
assert len(s.get_gnss_campaigns()) == 1
def test_scenario_insar(self):
tempdir = mkdtemp(prefix='pyrocko-scenario')
self.tempdirs.append(tempdir)
generator = self.generator
engine = gf.get_engine()
generator.init_modelling(engine)
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('insar', generator)
s = collection.get_scenario('insar')
s.ensure_insar_scenes()
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 test_scenario_gnss(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.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)
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('gnss', generator)
s = collection.get_scenario('gnss')
assert len(s.get_gnss_campaigns()) == 1
def test_scenario_insar(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.InSARGenerator(
resolution=(20, 20),
noise_generator=targets.insar.AtmosphericNoiseGenerator(
amplitude=1e-5))
],
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)
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('insar', generator)
s = collection.get_scenario('insar')
s.ensure_data()
def test_scenario_waveforms(self):
tempdir = mkdtemp(prefix='pyrocko-scenario')
self.tempdirs.append(tempdir)
vmin = 2500.
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(
nstations=5,
avoid_water=False),
noise_generator=targets.waveform.WhiteNoiseGenerator(),
seismogram_quantity='velocity'),
],
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)
)
def twin(source):
tmin = source.time
tmax = source.time + 100*km / vmin
return tmin, tmax
engine = gf.get_engine()
generator.init_modelling(engine)
ref_sources = generator.get_sources()
ref_trs_list = []
for source in ref_sources:
trs = generator.get_waveforms(*twin(source))
trs.sort(key=lambda tr: tr.nslc_id)
ref_trs_list.append(trs)
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('one', generator)
with self.assertRaises(scenario.ScenarioError):
collection.add_scenario('one', generator)
assert len(collection.list_scenarios()) == 1
assert collection.list_scenarios()[0].scenario_id == 'one'
s = collection.get_scenario('one')
for ref_trs, source in zip(
ref_trs_list,
s.get_generator().get_sources()):
trs = generator.get_waveforms(*twin(source))
trs.sort(key=lambda tr: tr.nslc_id)
self.assert_traces_almost_equal(trs, ref_trs)
collection2 = scenario.ScenarioCollection(tempdir, engine)
assert len(collection2.list_scenarios()) == 1
assert collection2.list_scenarios()[0].scenario_id == 'one'
s = collection2.get_scenario('one')
for ref_trs, source in zip(
ref_trs_list,
s.get_generator().get_sources()):
trs = generator.get_waveforms(*twin(source))
trs.sort(key=lambda tr: tr.nslc_id)
self.assert_traces_almost_equal(trs, ref_trs)
tmin, tmax = s.get_time_range()
s.ensure_data(tmin, tmax)
p = s.get_waveform_pile()
for ref_trs, source in zip(
ref_trs_list,
s.get_generator().get_sources()):
tmin, tmax = twin(source)
trs = p.all(tmin=tmin, tmax=tmax, include_last=False)
trs.sort(key=lambda tr: tr.nslc_id)
self.assert_traces_almost_equal(trs, ref_trs)
def test_scenario_waveforms(self):
tempdir = mkdtemp(prefix='pyrocko-scenario')
self.tempdirs.append(tempdir)
vmin = 2500.
generator = self.generator
def twin(source):
tmin = source.time
tmax = source.time + 100*km / vmin
return tmin, tmax
engine = gf.get_engine()
generator.init_modelling(engine)
ref_sources = generator.get_sources()
ref_trs_list = []
for source in ref_sources:
trs = generator.get_waveforms(*twin(source))
trs.sort(key=lambda tr: tr.nslc_id)
ref_trs_list.append(trs)
collection = scenario.ScenarioCollection(tempdir, engine)
collection.add_scenario('one', generator)
with self.assertRaises(scenario.ScenarioError):
collection.add_scenario('one', generator)
assert len(collection.list_scenarios()) == 1
assert collection.list_scenarios()[0].scenario_id == 'one'
s = collection.get_scenario('one')
for ref_trs, source in zip(
ref_trs_list,
s.get_generator().get_sources()):
trs = generator.get_waveforms(*twin(source))
trs.sort(key=lambda tr: tr.nslc_id)
self.assert_traces_almost_equal(trs, ref_trs)
collection2 = scenario.ScenarioCollection(tempdir, engine)
assert len(collection2.list_scenarios()) == 1
assert collection2.list_scenarios()[0].scenario_id == 'one'
s = collection2.get_scenario('one')
for ref_trs, source in zip(
ref_trs_list,
s.get_generator().get_sources()):
trs = generator.get_waveforms(*twin(source))
trs.sort(key=lambda tr: tr.nslc_id)
self.assert_traces_almost_equal(trs, ref_trs)
tmin, tmax = s.get_time_range()
s.ensure_waveforms(tmin, tmax)
p = s.get_waveform_pile()
for ref_trs, source in zip(
ref_trs_list,
s.get_generator().get_sources()):
tmin, tmax = twin(source)
trs = p.all(tmin=tmin, tmax=tmax, include_last=False)
trs.sort(key=lambda tr: tr.nslc_id)
self.assert_traces_almost_equal(trs, ref_trs)
