gemseo / algos / doe

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lib_pydoe module

PyDOE algorithms wrapper.

class gemseo.algos.doe.lib_pydoe.PyDOE

Bases: DOELibrary

PyDOE optimization library interface See DOELibrary.

ALGO_LIST: ClassVar[list[str]] = ['fullfact', 'ff2n', 'pbdesign', 'bbdesign', 'ccdesign', 'lhs']

ALPHA_KEYWORD = 'alpha'

CENTER_BB_KEYWORD = 'center_bb'

CENTER_CC_KEYWORD = 'center_cc'

CRITERION_KEYWORD = 'criterion'

DESC_LIST: ClassVar[list[str]] = ['Full-Factorial implemented in pyDOE', '2-Level Full-Factorial implemented in pyDOE', 'Plackett-Burman design implemented in pyDOE', 'Box-Behnken design implemented in pyDOE', 'Central Composite implemented in pyDOE', 'Latin Hypercube Sampling implemented in pyDOE']

FACE_KEYWORD = 'face'

ITERATION_KEYWORD = 'iterations'

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

The name of the interfaced library.

PYDOE_2LEVELFACT = 'ff2n'

PYDOE_2LEVELFACT_DESC = '2-Level Full-Factorial implemented in pyDOE'

PYDOE_2LEVELFACT_WEB = 'https://pythonhosted.org/pyDOE/factorial.html#level-full-factorial'

PYDOE_BBDESIGN = 'bbdesign'

PYDOE_BBDESIGN_DESC = 'Box-Behnken design implemented in pyDOE'

PYDOE_BBDESIGN_WEB = 'https://pythonhosted.org/pyDOE/rsm.html#box-behnken'

PYDOE_CCDESIGN = 'ccdesign'

PYDOE_CCDESIGN_DESC = 'Central Composite implemented in pyDOE'

PYDOE_CCDESIGN_WEB = 'https://pythonhosted.org/pyDOE/rsm.html#central-composite'

PYDOE_DOC = 'https://pythonhosted.org/pyDOE/'

PYDOE_FULLFACT = 'fullfact'

PYDOE_FULLFACT_DESC = 'Full-Factorial implemented in pyDOE'

PYDOE_FULLFACT_WEB = 'https://pythonhosted.org/pyDOE/factorial.html#general-full-factorial'

PYDOE_LHS = 'lhs'

PYDOE_LHS_DESC = 'Latin Hypercube Sampling implemented in pyDOE'

PYDOE_LHS_WEB = 'https://pythonhosted.org/pyDOE/randomized.html#latin-hypercube'

PYDOE_PBDESIGN = 'pbdesign'

PYDOE_PBDESIGN_DESC = 'Plackett-Burman design implemented in pyDOE'

PYDOE_PBDESIGN_WEB = 'https://pythonhosted.org/pyDOE/factorial.html#plackett-burman'

WEB_LIST: ClassVar[list[str]] = ['https://pythonhosted.org/pyDOE/factorial.html#general-full-factorial', 'https://pythonhosted.org/pyDOE/factorial.html#level-full-factorial', 'https://pythonhosted.org/pyDOE/factorial.html#plackett-burman', 'https://pythonhosted.org/pyDOE/rsm.html#box-behnken', 'https://pythonhosted.org/pyDOE/rsm.html#central-composite', 'https://pythonhosted.org/pyDOE/randomized.html#latin-hypercube']

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.