gemseo.algos.doe.scipy.scipy_doe module#

Design of experiments based on SciPy.

class SciPyDOE(algo_name)[source]#

Bases: BaseDOELibrary

The SciPy DOE algorithms library.

Parameters:

algo_name (str) -- The algorithm name.

Raises:

KeyError -- When the algorithm is not in the library.

class Hypersphere(*values)[source]#

Bases: StrEnum

The sampling strategy for the poisson disk algorithm.

SURFACE = 'surface'#
VOLUME = 'volume'#
class Optimizer(*values)[source]#

Bases: StrEnum

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

LLOYD = 'lloyd'#
NONE = ''#
RANDOM_CD = 'random-cd'#
ALGORITHM_INFOS: ClassVar[dict[str, DOEAlgorithmDescription]] = {'Halton': SciPyDOEAlgorithmDescription(algorithm_name='Halton', internal_algorithm_name='Halton', library_name='SciPy DOE', description='Halton sequence', website='', Settings=<class 'gemseo.algos.doe.scipy.settings.halton.Halton_Settings'>, handle_integer_variables=True, minimum_dimension=1), 'LHS': SciPyDOEAlgorithmDescription(algorithm_name='LHS', internal_algorithm_name='LatinHypercube', library_name='SciPy DOE', description='Latin hypercube sampling (LHS)', website='', Settings=<class 'gemseo.algos.doe.scipy.settings.lhs.LHS_Settings'>, handle_integer_variables=True, minimum_dimension=1), 'MC': SciPyDOEAlgorithmDescription(algorithm_name='MC', internal_algorithm_name='_MonteCarlo', library_name='SciPy DOE', description='Monte Carlo sampling', website='', Settings=<class 'gemseo.algos.doe.scipy.settings.mc.MC_Settings'>, handle_integer_variables=True, minimum_dimension=1), 'PoissonDisk': SciPyDOEAlgorithmDescription(algorithm_name='PoissonDisk', internal_algorithm_name='PoissonDisk', library_name='SciPy DOE', description='Poisson disk sampling', website='', Settings=<class 'gemseo.algos.doe.scipy.settings.poisson_disk.PoissonDisk_Settings'>, handle_integer_variables=True, minimum_dimension=1), 'Sobol': SciPyDOEAlgorithmDescription(algorithm_name='Sobol', internal_algorithm_name='Sobol', library_name='SciPy DOE', description="Engine for generating (scrambled) Sobol' sequences", website='', Settings=<class 'gemseo.algos.doe.scipy.settings.sobol.Sobol_Settings'>, handle_integer_variables=True, minimum_dimension=1)}#

The description of the algorithms contained in the library.

class SciPyDOEAlgorithmDescription(algorithm_name, internal_algorithm_name, library_name='SciPy DOE', description='', website='', Settings=<class 'gemseo.algos.doe.base_doe_settings.BaseDOESettings'>, handle_integer_variables=True, minimum_dimension=1)[source]#

Bases: DOEAlgorithmDescription

The description of a DOE algorithm from the SciPy library.

Parameters:
  • algorithm_name (str)

  • internal_algorithm_name (str)

  • library_name (str) --

    By default it is set to "SciPy DOE".

  • description (str) --

    By default it is set to "".

  • website (str) --

    By default it is set to "".

  • Settings (type[BaseDOESettings]) --

    By default it is set to <class 'gemseo.algos.doe.base_doe_settings.BaseDOESettings'>.

  • handle_integer_variables (bool) --

    By default it is set to True.

  • minimum_dimension (int) --

    By default it is set to 1.

library_name: str = 'SciPy DOE'#

The library name.