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)