def dump_to_asdf(self, outputfile):
"""
Dump self.adjoin_sources into adjoint file
"""
print("=" * 15 + "\nWrite to file: %s" % outputfile)
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(self.events)
event = self.events[0]
origin = event.preferred_origin()
event_time = origin.time
for adj_id in sorted(self.adjoint_sources):
adj = self.adjoint_sources[adj_id]
sta_tag = "%s_%s" % (adj.network, adj.station)
sta_info = self.stations[sta_tag]
adj_array, adj_path, parameters = \
dump_adjsrc(adj, sta_info, event_time)
ds.add_auxiliary_data(adj_array,
data_type="AdjointSources",
path=adj_path,
parameters=parameters)
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_str_method_of_aux_data(tmpdir):
asdf_filename = os.path.join(tmpdir.strpath, "test.h5")
data_set = ASDFDataSet(asdf_filename)
# With provenance id.
data = np.random.random((10, 10))
# The data must NOT start with a number.
data_type = "RandomArray"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
provenance_id = "{http://example.org}test"
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters,
provenance_id=provenance_id)
assert \
str(data_set.auxiliary_data.RandomArray.test_data) == (
"Auxiliary Data of Type 'RandomArray'\n"
"\tTag: 'test_data'\n"
"\tProvenance ID: '{http://example.org}test'\n"
"\tData shape: '(10, 10)', dtype: 'float64'\n"
"\tParameters:\n"
"\t\ta: 1\n"
"\t\tb: 2.0\n"
"\t\te: hallo")
# Without.
data = np.random.random((10, 10))
# The data must NOT start with a number.
data_type = "RandomArray"
tag = "test_data_2"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters)
assert \
str(data_set.auxiliary_data.RandomArray.test_data_2) == (
"Auxiliary Data of Type 'RandomArray'\n"
"\tTag: 'test_data_2'\n"
"\tData shape: '(10, 10)', dtype: 'float64'\n"
"\tParameters:\n"
"\t\ta: 1\n"
"\t\tb: 2.0\n"
"\t\te: hallo")
def test_reading_and_writing_auxiliary_data_with_provenance_id(tmpdir):
asdf_filename = os.path.join(tmpdir.strpath, "test.h5")
data_set = ASDFDataSet(asdf_filename)
data = np.random.random((10, 10))
# The data must NOT start with a number.
data_type = "RandomArray"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
provenance_id = "{http://example.org}test"
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters,
provenance_id=provenance_id)
data_set.__del__()
del data_set
new_data_set = ASDFDataSet(asdf_filename)
assert new_data_set.auxiliary_data.RandomArray.test_data.provenance_id \
== provenance_id
def test_adding_auxiliary_data_with_invalid_data_type_name_raises(tmpdir):
asdf_filename = os.path.join(tmpdir.strpath, "test.h5")
data_set = ASDFDataSet(asdf_filename)
data = np.random.random((10, 10))
# The data must NOT start with a number.
data_type = "2DRandomArray"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
try:
with pytest.raises(ASDFValueError) as err:
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters)
assert err.value.args[0] == (
"Data type name '2DRandomArray' is invalid. It must validate "
"against the regular expression '^[A-Z][A-Za-z0-9]*$'.")
finally:
data_set.__del__()
def test_adding_auxiliary_data_with_wrong_tag_name_raises(tmpdir):
asdf_filename = os.path.join(tmpdir.strpath, "test.h5")
data_set = ASDFDataSet(asdf_filename)
# With provenance id.
data = np.random.random((10, 10))
# The data must NOT start with a number.
data_type = "RandomArray"
tag = "A.B.C"
with pytest.raises(ASDFValueError) as err:
data_set.add_auxiliary_data(
data=data, data_type=data_type,
tag=tag, parameters={})
assert err.value.args[0] == (
"Tag name 'A.B.C' is invalid. It must validate "
"against the regular expression "
"'^[a-zA-Z0-9][a-zA-Z0-9_]*[a-zA-Z0-9]$'.")
data_set.__del__()
def test_item_access_of_auxiliary_data(tmpdir):
"""
Make sure all auxiliary data types, and the data itsself can be accessed
via dictionary like accesses.
"""
asdf_filename = os.path.join(tmpdir.strpath, "test.h5")
data_set = ASDFDataSet(asdf_filename)
assert str(data_set.auxiliary_data) == (
"Data set contains no auxiliary data.")
data = np.random.random((10, 10))
data_type = "RandomArray"
tag = "test_data_1"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters)
assert data_set.auxiliary_data["RandomArray"]["test_data_1"].tag == \
data_set.auxiliary_data.RandomArray.test_data_1.tag
def test_reading_and_writing_auxiliary_data(tmpdir):
"""
Tests reading and writing auxiliary data.
"""
asdf_filename = os.path.join(tmpdir.strpath, "test.h5")
data_set = ASDFDataSet(asdf_filename)
# Define some auxiliary data and add it.
data = np.random.random(100)
data_type = "RandomArrays"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type, tag=tag, parameters=parameters)
del data_set
new_data_set = ASDFDataSet(asdf_filename)
aux_data = new_data_set.auxiliary_data.RandomArrays.test_data
np.testing.assert_equal(data, aux_data.data)
aux_data.data_type == data_type
aux_data.tag == tag
aux_data.parameters == parameters
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_str_of_auxiliary_data(tmpdir):
"""
Test the various __str__ method of auxiliary data types.
"""
asdf_filename = os.path.join(tmpdir.strpath, "test.h5")
data_set = ASDFDataSet(asdf_filename)
assert str(data_set.auxiliary_data) == (
"Data set contains no auxiliary data.")
data = np.random.random((10, 10))
data_type = "RandomArray"
tag = "test_data_1"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters)
data = np.random.random((10, 10))
data_type = "RandomArray"
tag = "test_data_2"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters)
data = np.random.random((10, 10))
data_type = "SomethingElse"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type,
tag=tag, parameters=parameters)
assert str(data_set.auxiliary_data) == (
"Data set contains the following auxiliary data types:\n"
"\tRandomArray (2 item(s))\n"
"\tSomethingElse (1 item(s))"
)
assert str(data_set.auxiliary_data.RandomArray) == (
"2 auxiliary data item(s) of type 'RandomArray' available:\n"
"\ttest_data_1\n"
"\ttest_data_2"
)
def test_reading_and_writing_n_dimensional_auxiliary_data(tmpdir):
"""
Tests reading and writing n-dimensional auxiliary data.
"""
# 2D.
asdf_filename = os.path.join(tmpdir.strpath, "test_2D.h5")
data_set = ASDFDataSet(asdf_filename)
data = np.random.random((10, 10))
data_type = "RandomArrays"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type, tag=tag,
parameters=parameters)
del data_set
new_data_set = ASDFDataSet(asdf_filename)
aux_data = new_data_set.auxiliary_data.RandomArrays.test_data
np.testing.assert_equal(data, aux_data.data)
aux_data.data_type == data_type
aux_data.tag == tag
aux_data.parameters == parameters
del new_data_set
# 3D.
asdf_filename = os.path.join(tmpdir.strpath, "test_3D.h5")
data_set = ASDFDataSet(asdf_filename)
data = np.random.random((5, 5, 5))
data_type = "RandomArrays"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type, tag=tag,
parameters=parameters)
del data_set
new_data_set = ASDFDataSet(asdf_filename)
aux_data = new_data_set.auxiliary_data.RandomArrays.test_data
np.testing.assert_equal(data, aux_data.data)
aux_data.data_type == data_type
aux_data.tag == tag
aux_data.parameters == parameters
del new_data_set
# 4D.
asdf_filename = os.path.join(tmpdir.strpath, "test_4D.h5")
data_set = ASDFDataSet(asdf_filename)
data = np.random.random((2, 3, 4, 5))
data_type = "RandomArrays"
tag = "test_data"
parameters = {"a": 1, "b": 2.0, "e": "hallo"}
data_set.add_auxiliary_data(data=data, data_type=data_type, tag=tag,
parameters=parameters)
del data_set
new_data_set = ASDFDataSet(asdf_filename)
aux_data = new_data_set.auxiliary_data.RandomArrays.test_data
np.testing.assert_equal(data, aux_data.data)
aux_data.data_type == data_type
aux_data.tag == tag
aux_data.parameters == parameters
del new_data_set
