gemseo / algos / doe

Show inherited members

lib_scipy module

Design of experiments based on SciPy.

class gemseo.algos.doe.lib_scipy.SciPyDOE

Bases: DOELibrary

A library of designs of experiments based on SciPy.

class Hypersphere(value)

Bases: StrEnum

The sampling strategy for the poisson disk algorithm.

SURFACE = 'surface'

VOLUME = 'volume'

class Optimizer(value)

Bases: StrEnum

The optimization scheme to improve the quality of the DOE after sampling.

LLOYD = 'lloyd'

NONE = ''

RANDOM_CD = 'random-cd'

LIBRARY_NAME: ClassVar[str] = 'SciPy'

The name of the interfaced library.

OPTIONS_DIR: ClassVar[Path] = PosixPath('options/scipy')

The name of the directory containing the files of the grammars of the options.

algo_name: str | None

The name of the algorithm used currently.

descriptions: dict[str, AlgorithmDescription]

The description of the algorithms contained in the library.

eval_jac: bool

Whether to evaluate the Jacobian.

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.

samples: RealArray

The design vector samples in the design space.

The design space variable types stored as dtype metadata.

To access those in the unit hypercube, use unit_samples.

unit_samples: RealArray

The design vector samples projected in the unit hypercube.

In the case of a design space of dimension \(d\), the unit hypercube is \([0,1]^d\).

To access those in the design space, use samples.