def test_dump_adjsrc():
array = np.array([1., 2., 3., 4., 5.])
adj = AdjointSource("cc_traveltime_misfit",
2.0,
1.0,
17,
40,
"BHZ",
adjoint_source=array,
network="II",
station="AAK",
location="",
starttime=UTCDateTime(1990, 1, 1))
station_info = {
"latitude": 1.0,
"longitude": 2.0,
"depth_in_m": 3.0,
"elevation_in_m": 4.0
}
adj_array, adj_path, parameters = sa.dump_adjsrc(adj, station_info)
npt.assert_array_almost_equal(adj_array, array)
for key in station_info:
npt.assert_almost_equal(station_info[key], parameters[key])
assert adj_path == "II_AAK_BHZ"
npt.assert_almost_equal(parameters["misfit"], 2.0)
npt.assert_almost_equal(parameters["dt"], 1.0)
npt.assert_almost_equal(parameters["min_period"], 17.0)
npt.assert_almost_equal(parameters["max_period"], 40.0)
assert parameters["adjoint_source_type"] == "cc_traveltime_misfit"
assert parameters["station_id"] == "II.AAK"
assert parameters["component"], "BHZ"
assert UTCDateTime(parameters["starttime"]) == UTCDateTime(1990, 1, 1)
assert parameters["units"] == "m"
def save_adjoint_to_asdf(outputfile, events, adjoint_sources, stations):
"""
Save events(obspy.Catalog) and adjoint sources, together with
staiton information, to asdf file on disk.
"""
print("=" * 15 + "\nWrite to file: %s" % outputfile)
outputdir = os.path.dirname(outputfile)
if not os.path.exists(outputdir):
os.makedirs(outputdir)
if os.path.exists(outputfile):
print("Output file exists and removed:%s" % outputfile)
os.remove(outputfile)
ds = ASDFDataSet(outputfile, mode='a', compression=None)
ds.add_quakeml(events)
for adj_id in sorted(adjoint_sources):
adj = adjoint_sources[adj_id]
sta_tag = "%s_%s" % (adj.network, adj.station)
sta_info = stations[sta_tag]
adj_array, adj_path, parameters = \
dump_adjsrc(adj, sta_info)
ds.add_auxiliary_data(adj_array,
data_type="AdjointSources",
path=adj_path,
parameters=parameters)
def test_load_to_adjsrc():
array = np.array([1., 2., 3., 4., 5.])
adj = AdjointSource(
"cc_traveltime_misfit", 2.0, 1.0, 17, 40, "BHZ",
adjoint_source=array, network="II", station="AAK",
location="", starttime=UTCDateTime(1990, 1, 1))
station_info = {"latitude": 1.0, "longitude": 2.0, "depth_in_m": 3.0,
"elevation_in_m": 4.0}
adj_array, adj_path, parameters = sa.dump_adjsrc(adj, station_info)
# ensemble a faked adjoint source from hdf5
hdf5_adj = namedtuple("HDF5Adj", ['data', 'parameters'])
hdf5_adj.data = array
hdf5_adj.parameters = parameters
# load and check
loaded_adj, loaded_station_info = sa.load_to_adjsrc(hdf5_adj)
adjoint_equal(loaded_adj, adj)
for k in station_info:
npt.assert_almost_equal(station_info[k], loaded_station_info[k])
assert loaded_station_info["station"] == "AAK"
assert loaded_station_info["network"] == "II"
assert loaded_station_info["location"] == ""
def test_dump_adjsrc():
array = np.array([1., 2., 3., 4., 5.])
adj = AdjointSource(
"cc_traveltime_misfit", 2.0, 1.0, 17, 40, "BHZ",
adjoint_source=array, network="II", station="AAK",
location="", starttime=UTCDateTime(1990, 1, 1))
station_info = {"latitude": 1.0, "longitude": 2.0, "depth_in_m": 3.0,
"elevation_in_m": 4.0}
adj_array, adj_path, parameters = sa.dump_adjsrc(adj, station_info)
npt.assert_array_almost_equal(adj_array, array)
for key in station_info:
npt.assert_almost_equal(station_info[key], parameters[key])
assert adj_path == "II_AAK_BHZ"
npt.assert_almost_equal(parameters["misfit"], 2.0)
npt.assert_almost_equal(parameters["dt"], 1.0)
npt.assert_almost_equal(parameters["min_period"], 17.0)
npt.assert_almost_equal(parameters["max_period"], 40.0)
assert parameters["adjoint_source_type"] == "cc_traveltime_misfit"
assert parameters["station_id"] == "II.AAK"
assert parameters["component"], "BHZ"
assert UTCDateTime(parameters["starttime"]) == UTCDateTime(1990, 1, 1)
assert parameters["units"] == "m"
def test_load_to_adjsrc():
array = np.array([1., 2., 3., 4., 5.])
adj = AdjointSource("cc_traveltime_misfit",
2.0,
1.0,
17,
40,
"BHZ",
adjoint_source=array,
network="II",
station="AAK",
location="",
starttime=UTCDateTime(1990, 1, 1))
station_info = {
"latitude": 1.0,
"longitude": 2.0,
"depth_in_m": 3.0,
"elevation_in_m": 4.0
}
adj_array, adj_path, parameters = sa.dump_adjsrc(adj, station_info)
# ensemble a faked adjoint source from hdf5
hdf5_adj = namedtuple("HDF5Adj", ['data', 'parameters'])
hdf5_adj.data = array
hdf5_adj.parameters = parameters
# load and check
loaded_adj, loaded_station_info = sa.load_to_adjsrc(hdf5_adj)
adjoint_equal(loaded_adj, adj)
for k in station_info:
npt.assert_almost_equal(station_info[k], loaded_station_info[k])
assert loaded_station_info["station"] == "AAK"
assert loaded_station_info["network"] == "II"
assert loaded_station_info["location"] == ""
def save_adjoint_to_asdf(outputfile, events, adjoint_sources, stations):
"""
Save events(obspy.Catalog) and adjoint sources, together with
staiton information, to asdf file on disk.
"""
print("="*15 + "\nWrite to file: %s" % outputfile)
outputdir = os.path.dirname(outputfile)
if not os.path.exists(outputdir):
os.makedirs(outputdir)
if os.path.exists(outputfile):
print("Output file exists and removed:%s" % outputfile)
os.remove(outputfile)
ds = ASDFDataSet(outputfile, mode='a', compression=None)
ds.add_quakeml(events)
for adj_id in sorted(adjoint_sources):
adj = adjoint_sources[adj_id]
sta_tag = "%s_%s" % (adj.network, adj.station)
sta_info = stations[sta_tag]
adj_array, adj_path, parameters = \
dump_adjsrc(adj, sta_info)
ds.add_auxiliary_data(adj_array, data_type="AdjointSources",
path=adj_path, parameters=parameters)
