def startup(self, group):
super(SqliteRecorder, self).startup(group)
# Need this for use when recording the metadata
# Can't do this in the record_metadata method because it only gets
# called for rank 0 when running in parallel and so the MPI gather
# that is called in that function won't work. All processes
# need to participate in that collective call
self.model_viewer_data = get_model_viewer_data(group)
def record_metadata(self, group):
"""Stores the metadata of the given group in a HDF5 file using
the variable name for the key.
Args
----
group : `System`
`System` containing vectors
"""
params = group.params.iteritems()
resids = group.resids.iteritems()
unknowns = group.unknowns.iteritems()
metadata_group = self.out['metadata']
# The group metadata could be anything so need to pickle it
# There are other ways of storing any kind of Python object in HDF5 but this is the simplest
system_metadata_val = np.array(
pickle.dumps(group.metadata, pickle.HIGHEST_PROTOCOL))
metadata_group.create_dataset('system_metadata',
data=system_metadata_val)
# Also store the model_viewer_data
model_viewer_data = get_model_viewer_data(group)
model_viewer_data_val = np.array(
pickle.dumps(model_viewer_data, pickle.HIGHEST_PROTOCOL))
metadata_group.create_dataset('model_viewer_data',
data=model_viewer_data_val)
pairings = (
(metadata_group.create_group("Parameters"), params),
(metadata_group.create_group("Unknowns"), unknowns),
)
for grp, data in pairings:
for key, val in data:
meta_group = grp.create_group(key)
for mkey, mval in iteritems(val):
meta_group.create_dataset(mkey, data=mval)
def record_metadata(self, group):
"""Stores the metadata of the given group in a HDF5 file using
the variable name for the key.
Args
----
group : `System`
`System` containing vectors
"""
params = group.params.iteritems()
resids = group.resids.iteritems()
unknowns = group.unknowns.iteritems()
metadata_group = self.out["metadata"]
# The group metadata could be anything so need to pickle it
# There are other ways of storing any kind of Python object in HDF5 but this is the simplest
system_metadata_val = np.array(pickle.dumps(group.metadata, pickle.HIGHEST_PROTOCOL))
metadata_group.create_dataset("system_metadata", data=system_metadata_val)
# Also store the model_viewer_data
model_viewer_data = get_model_viewer_data(group)
model_viewer_data_val = np.array(pickle.dumps(model_viewer_data, pickle.HIGHEST_PROTOCOL))
metadata_group.create_dataset("model_viewer_data", data=model_viewer_data_val)
pairings = (
(metadata_group.create_group("Parameters"), params),
(metadata_group.create_group("Unknowns"), unknowns),
)
for grp, data in pairings:
for key, val in data:
meta_group = grp.create_group(key)
for mkey, mval in iteritems(val):
meta_group.create_dataset(mkey, data=mval)
