Source code for dymos.run_problem

import warnings

import openmdao
import openmdao.api as om
from import Case
from ._options import options as dymos_options
from dymos.trajectory.trajectory import Trajectory
from dymos.visualization.timeseries_plots import timeseries_plots

from .grid_refinement.refinement import _refine_iter

[docs]def run_problem(problem, refine_method='hp', refine_iteration_limit=0, run_driver=True, simulate=False, restart=None, solution_record_file='dymos_solution.db', simulation_record_file='dymos_simulation.db', make_plots=False, plot_dir="plots", case_prefix=None, reset_iter_counts=True, simulate_kwargs=None, plot_kwargs=None, ): """ A Dymos-specific interface to execute an OpenMDAO problem containing Dymos Trajectories or Phases. This function can iteratively call run_driver to perform grid refinement, and automatically call simulate following a run to check the validity of a result. Parameters ---------- problem : om.Problem The OpenMDAO problem object to be run, presumed to contain one or more dymos phases. refine_method : String The choice of refinement algorithm to use for grid refinement. Current options are 'hp' for h-then-p adaptive or 'ph' for 'p-then-h' adaptive. refine_iteration_limit : int The maximum number of passes through the grid refinement algorithm to be made. run_driver : bool If True, run the driver attached to the problem, otherwise just run the model one time. simulate : bool If True, perform a simulation of any Trajectories found in the Problem model after the driver has been run and grid refinement is complete. restart : str, Case, or None If given as a dict returned by om.CaseReader.get_case, automatically load the states, controls, and parameters as given in the provided case as the initial guess for the next run. If given as a string, assume the user is providing the path to a CaseRecorder file that contains a case named "final" that the user wants to use as the guess for the case. make_plots : bool If True, automatically generate plots of all timeseries outputs. These are stored in the reports subdirectory generated by OpenMDAO. solution_record_file : str Path to case recorder file use to store results from solution. simulation_record_file : str Path to case recorder file use to store results from simulation. plot_dir : str Name of the plot directory to be created. simulate_kwargs : dict A dictionary of argument: value pairs to be passed to simulate. These are ignored when simulate=False. plot_kwargs : dict A dictionary of argument: value pairs that are passed to `timeseries_plots`. Only used when make_plots=True. case_prefix : str or None Prefix to prepend to coordinates when recording. reset_iter_counts : bool If True and model has been run previously, reset all iteration counters. """ if restart is not None: if isinstance(restart, str): case = om.CaseReader(restart).get_case('final') elif isinstance(restart, Case): case = restart else: raise ValueError('If given, option restart must specify a string to the filepath of a valid dymos ' 'output case, or a case dictionary returned from om.CaseReader.get_case.') if solution_record_file not in [rec._filepath for rec in iter(problem._rec_mgr)]: recorder = om.SqliteRecorder(solution_record_file) problem.add_recorder(recorder) # record_outputs is need to capture the timeseries outputs problem.recording_options['record_outputs'] = True problem.final_setup() if restart is not None: om_version = tuple([int(s) for s in openmdao.__version__.split('-')[0].split('.')]) if om_version < (3, 27, 1): from dymos.load_case import load_case load_case(problem, case, deprecation_warning=False) else: problem.load_case(case) for traj in problem.model.system_iter(include_self=True, recurse=True, typ=Trajectory): traj._check_phase_graph() if run_driver: failed = _refine_iter(problem, refine_iteration_limit, refine_method, case_prefix=case_prefix, reset_iter_counts=reset_iter_counts) else: failed = problem.run_model() if refine_iteration_limit > 0: warnings.warn("Refinement not performed. Set run_driver to True to perform refinement.") _case_prefix = '' if case_prefix is None else f'{case_prefix}_' problem.record(f'{_case_prefix}final') # save case for potential restart problem.cleanup() if simulate: _simulate_kwargs = simulate_kwargs if simulate_kwargs is not None else {} if 'record_file' in _simulate_kwargs: raise ValueError('Key "record_file" was found in simulate_kwargs but should instead by provided by the ' 'argument "simulation_record_file".') if 'case_prefix' in _simulate_kwargs: raise ValueError('Key "case_prefix" was found in simulate_kwargs but should instead by provided by the ' 'argument "case_prefix", not part of the simulate_kwargs dictionary.') for subsys in problem.model.system_iter(include_self=True, recurse=True): if isinstance(subsys, Trajectory): subsys.simulate(record_file=simulation_record_file, case_prefix=case_prefix, **_simulate_kwargs) if make_plots: if dymos_options['plots'] == 'bokeh': from dymos.visualization.timeseries.bokeh_timeseries_report import make_timeseries_report make_timeseries_report(prob=problem, solution_record_file=solution_record_file, simulation_record_file=simulation_record_file) else: _sim_record_file = None if not simulate else simulation_record_file _plot_kwargs = plot_kwargs if plot_kwargs is not None else {} timeseries_plots(solution_record_file, simulation_record_file=_sim_record_file, plot_dir=plot_dir, problem=problem, **_plot_kwargs) return failed