Source code for openmdao.recorders.recording_manager

"""
RecordingManager class definition.
"""
import time

from openmdao.utils.om_warnings import issue_warning


[docs] class RecordingManager(object): """ Object that routes function calls to all attached recorders. Attributes ---------- _recorders : list of CaseRecorder All of the recorders attached to the current object. """
[docs] def __init__(self): """ init. """ self._recorders = []
[docs] def __getitem__(self, index): """ Get a particular recorder in the manager. Parameters ---------- index : int an index into _recorders. Returns ------- recorder : CaseRecorder a recorder from _recorders """ return self._recorders[index]
[docs] def __iter__(self): """ Iterate. Returns ------- iter : CaseRecorder a recorder from _recorders. """ return iter(self._recorders)
[docs] def append(self, recorder): """ Add a recorder for recording. Parameters ---------- recorder : CaseRecorder Recorder instance to be added to the manager. """ self._recorders.append(recorder)
[docs] def startup(self, recording_requester, comm=None): """ Run startup on each recorder in the manager. Parameters ---------- recording_requester : object The object that needs an iteration of itself recorded. comm : MPI.Comm or <FakeComm> or None The communicator for recorders (should be the comm for the Problem). """ for recorder in self._recorders: recorder.startup(recording_requester, comm)
[docs] def shutdown(self): """ Shut down and remove all recorders. """ for recorder in self._recorders: recorder.shutdown() self._recorders = []
[docs] def record_iteration(self, recording_requester, data, metadata): """ Call record_iteration on all recorders. Parameters ---------- recording_requester : object The object that needs an iteration of itself recorded. data : dict Dictionary containing desvars, objectives, constraints, responses, and System vars. metadata : dict Metadata for iteration coordinate. """ if not self._recorders: return if metadata is not None: metadata['timestamp'] = time.perf_counter() for recorder in self._recorders: recorder.record_iteration(recording_requester, data, metadata)
[docs] def record_derivatives(self, recording_requester, data, metadata): """ Call record_derivatives on all recorders. Parameters ---------- recording_requester : object The object that needs an iteration of itself recorded. data : dict Dictionary containing derivatives keyed by 'of,wrt' to be recorded. metadata : dict Metadata for iteration coordinate. """ if not self._recorders: return if metadata is not None: metadata['timestamp'] = time.perf_counter() for recorder in self._recorders: recorder.record_derivatives(recording_requester, data, metadata)
[docs] def has_recorders(self): """ Are there any recorders managed by this RecordingManager. Returns ------- True/False: bool True if RecordingManager is managing at least one recorder. """ return True if self._recorders else False
def _check_parallel(self): pset = {bool(r.parallel) for r in self._recorders} # check to make sure we don't have mixed parallel/non-parallel, because that # currently won't work properly. if len(pset) > 1: raise RuntimeError("OpenMDAO currently does not support a mixture of parallel " "and non-parallel recorders.") return pset.pop()
def _get_all_requesters(problem): yield problem yield problem.driver for system in problem.model.system_iter(include_self=True, recurse=True): yield system nl = system._nonlinear_solver if nl: yield nl if nl.linesearch: yield nl.linesearch def _get_all_viewer_data_recorders(problem): for req in _get_all_requesters(problem): for r in req._rec_mgr._recorders: if r._record_viewer_data: yield r def _get_all_recorders(problem): for req in _get_all_requesters(problem): for r in req._rec_mgr._recorders: yield r
[docs] def record_viewer_data(problem): """ Record model viewer data for all recorders that have that option enabled. We don't want to collect the viewer data if it's not needed though, so first we'll find all recorders that need the data (if any) and then record it for those recorders. Parameters ---------- problem : Problem The problem for which model viewer data is to be recorded. """ # get all recorders that need to record the viewer data recorders = set(_get_all_viewer_data_recorders(problem)) # if any recorders were found, get the viewer data and record it if recorders: from openmdao.visualization.n2_viewer.n2_viewer import _get_viewer_data try: viewer_data = _get_viewer_data(problem, values=True) except TypeError as err: viewer_data = {} issue_warning(str(err)) viewer_data['md5_hash'] = problem.model._generate_md5_hash() viewer_data.pop('abs2prom', None) # abs2prom already recorded in metadata table for recorder in recorders: recorder.record_viewer_data(viewer_data)
[docs] def record_model_options(problem, run_number): """ Record the options for all systems and solvers in the model. Parameters ---------- problem : Problem The problem for which all its system and solver options are to be recorded. run_number : int or None Number indicating which run the metadata is associated with. Zero or None for the first run, 1 for the second, etc. """ # for backward compatibility, the first run does not have a run number if run_number is not None and run_number < 1: run_number = None recorders = set(_get_all_recorders(problem)) for system in problem.model.system_iter(recurse=True, include_self=True): for recorder in recorders: # record system metadata (options) recorder.record_metadata_system(system, run_number) # record solver metadata (options) for this system's solvers nl = system._nonlinear_solver if nl: recorder.record_metadata_solver(nl, run_number) if nl.linesearch: recorder.record_metadata_solver(nl.linesearch, run_number) ln = system._linear_solver if ln: recorder.record_metadata_solver(ln, run_number)