gemseo / algos / opt

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lib_scipy_linprog module

SciPy linear programming library wrapper.

class gemseo.algos.opt.lib_scipy_linprog.ScipyLinProgAlgorithmDescription(algorithm_name, internal_algorithm_name, library_name='SciPy', description='', website='', handle_integer_variables=False, require_gradient=False, handle_equality_constraints=True, handle_inequality_constraints=True, handle_multiobjective=False, positive_constraints=False, problem_type=ProblemType.LINEAR)[source]

Bases: OptimizationAlgorithmDescription

The description of a linear optimization algorithm from the SciPy library.

Parameters:

  • algorithm_name (str) –

  • internal_algorithm_name (str) –

  • library_name (str) –

    By default it is set to “SciPy”.

  • description (str) –

    By default it is set to “”.

  • website (str) –

    By default it is set to “”.

  • handle_integer_variables (bool) –

    By default it is set to False.

  • require_gradient (bool) –

    By default it is set to False.

  • handle_equality_constraints (bool) –

    By default it is set to True.

  • handle_inequality_constraints (bool) –

    By default it is set to True.

  • handle_multiobjective (bool) –

    By default it is set to False.

  • positive_constraints (bool) –

    By default it is set to False.

  • problem_type (ProblemType) –

    By default it is set to “linear”.

algorithm_name: str

The name of the algorithm in GEMSEO.

handle_equality_constraints: bool = True

Whether the optimization algorithm handles equality constraints.

handle_inequality_constraints: bool = True

Whether the optimization algorithm handles inequality constraints.

internal_algorithm_name: str

The name of the algorithm in the wrapped library.

library_name: str = 'SciPy'

The name of the wrapped library.

problem_type: ProblemType = 'linear'

The type of problem (see OptimizationProblem.ProblemType).

class gemseo.algos.opt.lib_scipy_linprog.ScipyLinprog[source]

Bases: OptimizationLibrary

SciPy linear programming library interface.

See OptimizationLibrary.

Notes

The missing current values of the DesignSpace attached to the OptimizationProblem are automatically initialized with the method DesignSpace.initialize_missing_current_values().

Constructor.

Generate the library dictionary that contains the list of algorithms with their characteristics.

LIBRARY_NAME: ClassVar[str | None] = 'SciPy'

The name of the interfaced library.

LIB_COMPUTE_GRAD = True
OPTIONS_MAP: ClassVar[dict[Any, str]] = {'max_iter': 'maxiter', 'redundancy removal': 'rr', 'verbose': 'disp'}

The names of the options in GEMSEO mapping to those in the wrapped library.

REDUNDANCY_REMOVAL = 'redundancy removal'
REVISED_SIMPLEX = 'REVISED_SIMPLEX'
algo_name: str | None

The name of the algorithm used currently.

descriptions: dict[str, AlgorithmDescription]

The description of the algorithms contained in the library.

internal_algo_name: str | None

The internal name of the algorithm used currently.

It typically corresponds to the name of the algorithm in the wrapped library if any.

opt_grammar: JSONGrammar | None

The grammar defining the options of the current algorithm.

problem: OptimizationProblem

The optimization problem the driver library is bonded to.