lib_pydoe module¶
PyDOE algorithms wrapper.
- class gemseo.algos.doe.lib_pydoe.PyDOE[source]
Bases:
DOELibrary
PyDOE optimization library interface See DOELibrary.
- 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'
- 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']
- 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.
- lock: RLock
The lock protecting database storage in multiprocessing.
- 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
.