Source code for

Module for building OpenMDAO problem from configuration file
#  This file is part of FAST-OAD : A framework for rapid Overall Aircraft Design
#  Copyright (C) 2022 ONERA & ISAE-SUPAERO
#  FAST is free software: you can redistribute it and/or modify
#  it under the terms of the GNU General Public License as published by
#  the Free Software Foundation, either version 3 of the License, or
#  (at your option) any later version.
#  This program is distributed in the hope that it will be useful,
#  but WITHOUT ANY WARRANTY; without even the implied warranty of
#  GNU General Public License for more details.
#  You should have received a copy of the GNU General Public License
#  along with this program.  If not, see <>.

import json
import logging
import os.path as pth
from abc import ABC, abstractmethod
from importlib.resources import open_text
from typing import Dict

import numpy as np
import openmdao.api as om
import tomlkit
from jsonschema import validate
from ruamel.yaml import YAML

from fastoad._utils.files import make_parent_dir
from import DataFile, IVariableIOFormatter
from fastoad.module_management.service_registry import RegisterOpenMDAOSystem, RegisterSubmodel
from fastoad.openmdao.problem import FASTOADProblem
from fastoad.openmdao.variables import VariableList
from . import resources
from .exceptions import (

_LOGGER = logging.getLogger(__name__)  # Logger for this module

KEY_FOLDERS = "module_folders"
KEY_INPUT_FILE = "input_file"
KEY_OUTPUT_FILE = "output_file"
KEY_CONNECTION_ID = "connections"
KEY_MODEL = "model"
KEY_SUBMODELS = "submodels"
KEY_DRIVER = "driver"
KEY_OPTIMIZATION = "optimization"
KEY_DESIGN_VARIABLES = "design_variables"
KEY_CONSTRAINTS = "constraints"
KEY_OBJECTIVE = "objective"
JSON_SCHEMA_NAME = "configuration.json"

[docs]class FASTOADProblemConfigurator: """ class for configuring an OpenMDAO problem from a configuration file See :ref:`description of configuration file <configuration-file>`. :param conf_file_path: if provided, configuration will be read directly from it """ def __init__(self, conf_file_path=None): self._conf_file = None self._serializer = _YAMLSerializer() # self._configuration_modifier offers a way to modify problems after # they have been generated from configuration (private usage for now) self._configuration_modifier: "_IConfigurationModifier" = None if conf_file_path: self.load(conf_file_path) @property def input_file_path(self): """path of file with input variables of the problem""" path = str([KEY_INPUT_FILE]) if not pth.isabs(path): path = pth.normpath(pth.join(pth.dirname(self._conf_file), path)) return path @input_file_path.setter def input_file_path(self, file_path: str):[KEY_INPUT_FILE] = file_path @property def output_file_path(self): """path of file where output variables will be written""" path = str([KEY_OUTPUT_FILE]) if not pth.isabs(path): path = pth.normpath(pth.join(pth.dirname(self._conf_file), path)) return path @output_file_path.setter def output_file_path(self, file_path: str):[KEY_OUTPUT_FILE] = file_path
[docs] def get_problem(self, read_inputs: bool = False, auto_scaling: bool = False) -> FASTOADProblem: """ Builds the OpenMDAO problem from current configuration. :param read_inputs: if True, the created problem will already be fed with variables from the input file :param auto_scaling: if True, automatic scaling is performed for design variables and constraints :return: the problem instance """ if is None: raise RuntimeError("read configuration file first") problem = FASTOADProblem() self._build_model(problem) problem.input_file_path = self.input_file_path problem.output_file_path = self.output_file_path if read_inputs: problem.read_inputs() driver =, "") if driver: problem.driver = _om_eval(driver) if self.get_optimization_definition(): self._add_constraints(problem.model, auto_scaling) self._add_objectives(problem.model) if read_inputs: self._add_design_vars(problem.model, auto_scaling) if self._configuration_modifier: self._configuration_modifier.modify(problem) return problem
[docs] def load(self, conf_file): """ Reads the problem definition :param conf_file: Path to the file to open or a file descriptor """ self._conf_file = pth.abspath(conf_file) # for resolving relative paths conf_dirname = pth.dirname(self._conf_file) if pth.splitext(self._conf_file)[-1] == ".toml": self._serializer = _TOMLSerializer() _LOGGER.warning( "TOML-formatted configuration files are deprecated. Please use YAML format." ) else: self._serializer = _YAMLSerializer() # Syntax validation with open_text(resources, JSON_SCHEMA_NAME) as json_file: json_schema = json.loads( validate(, json_schema) # Issue a simple warning for unknown keys at root level for key in if key not in json_schema["properties"].keys(): _LOGGER.warning('Configuration file: "%s" is not a FAST-OAD key.', key) # Looking for modules to register module_folder_paths = if isinstance(module_folder_paths, str): module_folder_paths = [module_folder_paths] if module_folder_paths: for folder_path in module_folder_paths: folder_path = pth.join(conf_dirname, str(folder_path)) if not pth.exists(folder_path): _LOGGER.warning("SKIPPED %s: it does not exist.", folder_path) else: RegisterOpenMDAOSystem.explore_folder(folder_path) # Settings submodels RegisterSubmodel.cancel_submodel_deactivations() submodel_specs =, {}) for submodel_requirement, submodel_id in submodel_specs.items(): RegisterSubmodel.active_models[submodel_requirement] = submodel_id
[docs] def save(self, filename: str = None): """ Saves the current configuration If no filename is provided, the initially read file is used. :param filename: file where to save configuration """ if not filename: filename = self._conf_file make_parent_dir(filename) self._serializer.write(filename)
[docs] def write_needed_inputs( self, source_file_path: str = None, source_formatter: IVariableIOFormatter = None ): """ Writes the input file of the problem with unconnected inputs of the configured problem. Written value of each variable will be taken: 1. from input_data if it contains the variable 2. from defined default values in component definitions :param source_file_path: if provided, variable values will be read from it :param source_formatter: the class that defines format of input file. if not provided, expected format will be the default one. """ problem = self.get_problem(read_inputs=False) problem.setup() variables = DataFile(self.input_file_path, load_data=False) unconnected_inputs = VariableList.from_problem( problem, use_initial_values=True, get_promoted_names=True, promoted_only=True, io_status="inputs", ) variables.update( unconnected_inputs, add_variables=True, ) if source_file_path: ref_vars = DataFile(source_file_path, formatter=source_formatter) variables.update(ref_vars, add_variables=False) nan_variable_names = [] for var in variables: var.is_input = True # Checking if variables have NaN values if np.any(np.isnan(var.value)): nan_variable_names.append( if nan_variable_names: _LOGGER.warning("The following variables have NaN values: %s", nan_variable_names)
[docs] def get_optimization_definition(self) -> Dict: """ Returns information related to the optimization problem: - Design Variables - Constraints - Objectives :return: dict containing optimization settings for current problem """ optimization_definition = {} conf_dict = if conf_dict: for sec, elements in conf_dict.items(): optimization_definition[sec] = {elem["name"]: elem for elem in elements} return optimization_definition
[docs] def set_optimization_definition(self, optimization_definition: Dict): """ Updates configuration with the list of design variables, constraints, objectives contained in the optimization_definition dictionary. Keys of the dictionary are: "design_var", "constraint", "objective". Configuration file will not be modified until :meth:`save` is used. :param optimization_definition: dict containing the optimization problem definition """ subpart = {} for key, value in optimization_definition.items(): subpart[key] = [value for _, value in optimization_definition[key].items()] subpart = {"optimization": subpart}
def _build_model(self, problem: FASTOADProblem): """ Builds the problem model as defined in the configuration file. The problem model is populated with subsystems indicated in configuration file. """ model = problem.model model.active_submodels =, {}) model_definition = try: if KEY_COMPONENT_ID in model_definition: # The defined model is only one system system_id = model_definition[KEY_COMPONENT_ID] sub_component = RegisterOpenMDAOSystem.get_system(system_id) model.add_subsystem("system", sub_component, promotes=["*"]) else: # The defined model is a group self._parse_problem_table(model, model_definition) except FASTConfigurationBaseKeyBuildingError as err: log_err = err.__class__(err, KEY_MODEL) _LOGGER.error(log_err) raise log_err def _parse_problem_table(self, group: om.Group, table: dict): """ Feeds provided *group*, using definition in provided TOML *table*. :param group: :param table: """ # assert isinstance(table, dict), "table should be a dictionary" for key, value in table.items(): if isinstance(value, dict): # value defines a sub-component if KEY_COMPONENT_ID in value: # It is a non-group component, that should be registered with its ID options = value.copy() identifier = options.pop(KEY_COMPONENT_ID) # Process option values that are relative paths conf_dirname = pth.dirname(self._conf_file) for name, option_value in options.items(): option_is_path = ( name.endswith("file") or name.endswith("path") or name.endswith("dir") or name.endswith("directory") or name.endswith("folder") ) if ( isinstance(option_value, str) and option_is_path and not pth.isabs(option_value) ): options[name] = pth.join(conf_dirname, option_value) sub_component = RegisterOpenMDAOSystem.get_system(identifier, options=options) group.add_subsystem(key, sub_component, promotes=["*"]) else: # It is a Group sub_component = group.add_subsystem(key, om.Group(), promotes=["*"]) try: self._parse_problem_table(sub_component, value) except FASTConfigurationBadOpenMDAOInstructionError as err: # There has been an error while parsing an attribute. # Error is relayed with key added for context raise FASTConfigurationBadOpenMDAOInstructionError(err, key) elif key == KEY_CONNECTION_ID and isinstance(value, list): # a list of dict currently defines only connections for connection_def in value: group.connect(connection_def["source"], connection_def["target"]) else: # value is an attribute of current component and will be literally interpreted try: setattr(group, key, _om_eval(str(value))) # pylint:disable=eval-used except Exception as err: raise FASTConfigurationBadOpenMDAOInstructionError(err, key, value) def _add_constraints(self, model, auto_scaling): """ Adds constraints to provided model as instructed in current configuration :param model: :param auto_scaling: :return: """ optimization_definition = self.get_optimization_definition() # Constraints constraint_tables = optimization_definition.get(KEY_CONSTRAINTS, {}) for constraint_table in constraint_tables.values(): if ( auto_scaling and "lower" in constraint_table and "upper" in constraint_table and constraint_table.get("ref0") is not None and constraint_table.get("ref") is not None and constraint_table["lower"] != constraint_table["upper"] ): constraint_table["ref0"] = constraint_table["lower"] constraint_table["ref"] = constraint_table["upper"] model.add_constraint(**constraint_table) def _add_objectives(self, model): """ Adds objectives to provided model as instructed in current configuration :param model: :return: """ optimization_definition = self.get_optimization_definition() objective_tables = optimization_definition.get(KEY_OBJECTIVE, {}) for objective_table in objective_tables.values(): model.add_objective(**objective_table) def _add_design_vars(self, model, auto_scaling): """ Adds design variables to provided model as instructed in current configuration :param model: :param auto_scaling: :return: """ optimization_definition = self.get_optimization_definition() design_var_tables = optimization_definition.get(KEY_DESIGN_VARIABLES, {}) for design_var_table in design_var_tables.values(): if ( auto_scaling and "lower" in design_var_table and "upper" in design_var_table and design_var_table.get("ref0") is not None and design_var_table.get("ref") is not None and design_var_table["lower"] != design_var_table["upper"] ): design_var_table["ref0"] = design_var_table["lower"] design_var_table["ref"] = design_var_table["upper"] model.add_design_var(**design_var_table) def _set_configuration_modifier(self, modifier: "_IConfigurationModifier"): self._configuration_modifier = modifier
def _om_eval(string_to_eval: str): """ Evaluates strings that assume `import openmdao.api as om` is done. eval() is used for that, as safely as possible. :param string_to_eval: :return: result of eval() """ if "__" in string_to_eval: raise ValueError("No double underscore allowed in evaluated string for security reasons") return eval(string_to_eval, {"__builtins__": {}}, {"om": om}) class _IDictSerializer(ABC): """Interface for reading and writing dict-like data""" @property @abstractmethod def data(self) -> dict: """ The data that have been read, or will be written. """ @abstractmethod def read(self, file_path: str): """ Reads data from provided file. :param file_path: """ @abstractmethod def write(self, file_path: str): """ Writes data to provided file. :param file_path: """ class _TOMLSerializer(_IDictSerializer): """TOML-format serializer.""" def __init__(self): self._data = None @property def data(self): return self._data def read(self, file_path: str): with open(file_path, "r") as toml_file: self._data = tomlkit.loads( def write(self, file_path: str): with open(file_path, "w") as file: file.write(tomlkit.dumps(self._data)) class _YAMLSerializer(_IDictSerializer): """YAML-format serializer.""" def __init__(self): self._data = None @property def data(self): return self._data def read(self, file_path: str): yaml = YAML(typ="safe") with open(file_path) as yaml_file: self._data = yaml.load(yaml_file) def write(self, file_path: str): yaml = YAML() yaml.default_flow_style = False with open(file_path, "w") as file: yaml.dump(self._data, file) class _IConfigurationModifier(ABC): """ Interface for a configuration modifier used in FASTOADProblemConfigurator. """ @abstractmethod def modify(self, problem: om.Problem): """ This method will do operations on the provided problem. problem.setup() is assumed NOT called. """