design_space module

Define an object to hold variables and constraints.

class DesignSpace(variables, constraints)

Bases: object

Hold variables and constraints of an optimisation problem.

Parameters:

• variables (list[Variable])

• constraints (list[Constraint])

variables: list[Variable]

constraints: list[Constraint]

classmethod from_files(elements_names, filepath_variables, variables_names, filepath_constraints=None, constraints_names=None, delimiter=',')

Generate design space from files.

Parameters:

• elements_names (Sequence[str]) – Name of the elements with variables and constraints.

• filepath_variables (Path) – Path to the variables.csv file.

• variables_names (Sequence[str]) – Name of the variables to create.

• filepath_constraints (Path | None, default: None) – Path to the constraints.csv file.

• constraints_names (Sequence[str] | None, default: None) – Name of the constraints to create.

• delimiter (str, default: ',') – Delimiter in the files.

Return type:

Self

compute_constraints(simulation_output)

Compute constraint violation for simulation_output.

Parameters:

simulation_output (SimulationOutput)

Return type:

ndarray[tuple[Any, ...], dtype[double]]

__str__()

Give nice output of the variables and constraints.

Return type:

str

_str_variables()

Generate information on the variables that were created.

Return type:

str

_str_constraints()

Generate information on the constraints that were created.

Return type:

str

to_pandas_dataframe()

Convert list of variables to a pandas dataframe.

Return type:

DataFrame

to_files(basepath, variables_filename=PosixPath('variables'), constraints_filename=PosixPath('constraints'), overwrite=False, **to_csv_kw)

Save variables and constraints in files.

Parameters:

• basepath (Path) – Folder where the files will be stored.

• variables_filename (str | Path, default: PosixPath('variables')) – Name of the output files without extension.

• constraints_filename (str | Path, default: PosixPath('constraints')) – Name of the output files without extension.

• overwrite (bool, default: False) – To overwrite an existing file with the same name or not. The default is False.

• to_csv_kw (Any) – Keyword arguments given to the pandas to_csv method.

Return type:

None

_to_file(parameters, filepath, delimiter=',', **to_csv_kw)

Save all the design space parameters in a compact file.

Parameters:

• parameters (list[DesignSpaceParameter]) – All the defined parameters.

• filepath (Path) – Where file will be stored.

• delimiter (str, default: ',') – Delimiter between two columns. The default is ','.

• to_csv_kw (Any) – Keyword arguments given to the pandas to_csv method.

Return type:

None

_parameters_to_single_file_line(element_name, parameters)

Prepare a dict containing all info of a single element.

Parameters:

• element_name (str) – Name of the element, which will be inserted in the output dict.

• parameters (list[DesignSpaceParameter]) – Parameters concerning the element, which limits (x_0 if appliable) will be inserted in the dict.

Return type:

dict[str, float | None | tuple[float, float]]

Returns:

Contains all Variable or Constraint information of the element.

_check_dimensions(parameters)

Ensure that all elements have the same number of var or const.

Parameters:

parameters (list[Variable] | list[Constraint])

Return type:

int

__init__(variables, constraints)

Parameters:

• variables (list[Variable])

• constraints (list[Constraint])

Return type:

None

_gather_dicts_by_key(parameters, key)

Gather parameters with the same key attribute value in lists.

Parameters:

• parameters (list[DesignSpaceParameter]) – Objects to study.

• key (str) – Name of the attribute against which parameters should be gathered.

Return type:

dict[str, list[DesignSpaceParameter]]

Returns:

Keys are all existing values of attribute key from parameters. Values are lists of DesignSpaceParameter with key attribute equaling the dict key.

_parameters_to_dict(parameters, to_get)

Convert several design space parameters to dict.

We use the prepend_parameter_name argument to prepend the name of each parameter.name to the name of the values to_get. This way, we avoid dictionaries sharing the same keys in the output list.

Parameters:

• parameters (list[DesignSpaceParameter]) – Where to_get will be looked for.

• to_get (Sequence[str]) – Values to get.

Return type:

list[dict]

Returns:

Contains to_get values in dictionaries for every parameter.

_merge(dicts)

Merge a list of dicts in a single dict.

Parameters:

dicts (list[dict])

Return type:

dict

_from_file(parameter_class, filepath, elements_names, parameters_names, delimiter=',')

Overloads:

• parameter_class (type[Variable]), filepath (Path), elements_names (Sequence[str]), parameters_names (Sequence[str]), delimiter (str) → list[Variable]

• parameter_class (type[Constraint]), filepath (Path), elements_names (Sequence[str]), parameters_names (Sequence[str]), delimiter (str) → list[Constraint]

Parameters:

• parameter_class (type[Constraint] | type[Variable])

• filepath (Path)

• elements_names (Sequence[str])

• parameters_names (Sequence[str])

• delimiter (str)

Return type:

list[Variable] | list[Constraint]

Generate list of variables or constraints from a given CSV.

Todo

Add support for when all element do not have the same variables/constraints.

Parameters:

• parameter_class (type[Constraint] | type[Variable]) – Object which from_pd_series method will be called.

• filepath (Path) – Path to the CSV.

• elements_names (Sequence[str]) – Name of the elements.

• parameters_names (Sequence[str]) – Name of the parameters.

• delimiter (str, default: ',') – Delimiter in the CSV.

Returns:

List of variables or constraints.

Return type:

list[Variable] | list[Constraint]