def _get_metadata_system(self, system):
# Cannot handle PETScVector yet
from openmdao.api import PETScVector
if PETScVector and isinstance(system._outputs, PETScVector):
return None, None # Cannot handle PETScVector yet
# collect scaling arrays
scaling_vecs = {}
for kind, odict in system._vectors.items():
scaling_vecs[kind] = scaling = {}
for vecname, vec in odict.items():
scaling[vecname] = vec._scaling
# create a copy of the system's metadata excluding what is in 'options_excludes'
excludes = system.recording_options['options_excludes']
if excludes:
user_options = OptionsDictionary()
user_options._all_recordable = system.options._all_recordable
for key in system.options._dict:
if check_path(key, [], excludes, True):
user_options._dict[key] = system.options._dict[key]
user_options._read_only = system.options._read_only
return scaling_vecs, user_options
else:
return scaling_vecs, system.options
def record_metadata_system(self, recording_requester):
"""
Record system metadata.
Parameters
----------
recording_requester : System
The System that would like to record its metadata.
"""
if self.connection:
# Cannot handle PETScVector yet
from openmdao.api import PETScVector
if PETScVector and isinstance(recording_requester._outputs,
PETScVector):
return # Cannot handle PETScVector yet
# collect scaling arrays
scaling_vecs = {}
for kind, odict in iteritems(recording_requester._vectors):
scaling_vecs[kind] = scaling = {}
for vecname, vec in iteritems(odict):
scaling[vecname] = vec._scaling
scaling_factors = pickle.dumps(scaling_vecs, self._pickle_version)
# create a copy of the system's metadata excluding what is in 'options_excludes'
user_options = OptionsDictionary()
excludes = recording_requester.recording_options[
'options_excludes']
for key in recording_requester.options._dict:
if check_path(key, [], excludes, True):
user_options._dict[
key] = recording_requester.options._dict[key]
user_options._read_only = recording_requester.options._read_only
# try to pickle the metadata, report if it failed
try:
pickled_metadata = pickle.dumps(user_options,
self._pickle_version)
except Exception:
pickled_metadata = pickle.dumps(OptionsDictionary(),
self._pickle_version)
warnings.warn(
"Trying to record options which cannot be pickled "
"on system with name: %s. Use the 'options_excludes' "
"recording option on system objects to avoid attempting "
"to record options which cannot be pickled. Skipping "
"recording options for this system." %
recording_requester.name, RuntimeWarning)
path = recording_requester.pathname
if not path:
path = 'root'
scaling_factors = sqlite3.Binary(scaling_factors)
pickled_metadata = sqlite3.Binary(pickled_metadata)
with self.connection as c:
c.execute(
"INSERT INTO system_metadata(id, scaling_factors, component_metadata) "
"VALUES(?,?,?)", (path, scaling_factors, pickled_metadata))
def record_metadata_system(self, recording_requester):
"""
Record system metadata.
Parameters
----------
recording_requester : System
The System that would like to record its metadata.
"""
if self.con:
# Cannot handle PETScVector yet
from openmdao.api import PETScVector
if PETScVector and isinstance(recording_requester._outputs,
PETScVector):
return # Cannot handle PETScVector yet
# collect scaling arrays
scaling_vecs = {}
for kind, odict in iteritems(recording_requester._vectors):
scaling_vecs[kind] = scaling = {}
for vecname, vec in iteritems(odict):
scaling[vecname] = vec._scaling
scaling_factors = pickle.dumps(scaling_vecs, self._pickle_version)
# create a copy of the system's metadata excluding what is in 'metadata_excludes'
user_metadata = OptionsDictionary()
excludes = recording_requester.recording_options[
'metadata_excludes']
for key in recording_requester.options._dict:
if check_path(key, [], excludes, True):
user_metadata._dict[
key] = recording_requester.options._dict[key]
user_metadata._read_only = recording_requester.options._read_only
pickled_metadata = pickle.dumps(user_metadata,
self._pickle_version)
path = recording_requester.pathname
if not path:
path = 'root'
with self.con:
self.con.execute(
"INSERT INTO system_metadata(id, scaling_factors, component_metadata) \
VALUES(?,?, ?)",
(path, sqlite3.Binary(scaling_factors),
sqlite3.Binary(pickled_metadata)))
def _get_metadata_system(self, recording_requester):
# Cannot handle PETScVector yet
from openmdao.api import PETScVector
if PETScVector and isinstance(recording_requester._outputs, PETScVector):
return None, None # Cannot handle PETScVector yet
# collect scaling arrays
scaling_vecs = {}
for kind, odict in iteritems(recording_requester._vectors):
scaling_vecs[kind] = scaling = {}
for vecname, vec in iteritems(odict):
scaling[vecname] = vec._scaling
# create a copy of the system's metadata excluding what is in 'options_excludes'
user_options = OptionsDictionary()
excludes = recording_requester.recording_options['options_excludes']
for key in recording_requester.options._dict:
if check_path(key, [], excludes, True):
user_options._dict[key] = recording_requester.options._dict[key]
user_options._read_only = recording_requester.options._read_only
return scaling_vecs, user_options
def _get_metadata_system(self, recording_requester):
# Cannot handle PETScVector yet
from openmdao.api import PETScVector
if PETScVector and isinstance(recording_requester._outputs,
PETScVector):
return None, None # Cannot handle PETScVector yet
# collect scaling arrays
scaling_vecs = {}
for kind, odict in iteritems(recording_requester._vectors):
scaling_vecs[kind] = scaling = {}
for vecname, vec in iteritems(odict):
scaling[vecname] = vec._scaling
# create a copy of the system's metadata excluding what is in 'options_excludes'
user_options = OptionsDictionary()
excludes = recording_requester.recording_options['options_excludes']
for key in recording_requester.options._dict:
if check_path(key, [], excludes, True):
user_options._dict[key] = recording_requester.options._dict[
key]
user_options._read_only = recording_requester.options._read_only
return scaling_vecs, user_options