gemseo / uncertainty / sensitivity

Show inherited members

factory module

Module with a factory to create an instance of SensitivityAnalysis.

class gemseo.uncertainty.sensitivity.factory.SensitivityAnalysisFactory

Bases: BaseFactory

Factory to build instances of SensitivityAnalysis.

At initialization, this factory scans the following modules to search for subclasses of this class:

• the modules located in gemseo.uncertainty.sensitivity and its sub-packages,

• the modules referenced in the GEMSEO_PATH,

• the modules referenced in the PYTHONPATH and starting with gemseo_.

Then, it can check if a class is present or return the list of available classes.

Lastly, it can create an instance of a class.

Examples

>>> from numpy import pi
>>> from gemseo import create_discipline, create_parameter_space
>>> from gemseo.uncertainty.sensitivity.factory import (
...     SensitivityAnalysisFactory,
... )
>>>
>>> expressions = {"y": "sin(x1)+7*sin(x2)**2+0.1*x3**4*sin(x1)"}
>>> discipline = create_discipline(
...     "AnalyticDiscipline", expressions=expressions
... )
>>>
>>> parameter_space = create_parameter_space()
>>> parameter_space.add_random_variable(
...     "x1", "OTUniformDistribution", minimum=-pi, maximum=pi
... )
>>> parameter_space.add_random_variable(
...     "x2", "OTUniformDistribution", minimum=-pi, maximum=pi
... )
>>> parameter_space.add_random_variable(
...     "x3", "OTUniformDistribution", minimum=-pi, maximum=pi
... )
>>>
>>> factory = SensitivityAnalysisFactory()
>>> analysis = factory.create(
...     "MorrisIndices", discipline, parameter_space, n_replicates=5
... )
>>> indices = analysis.compute_indices()

Return type:

Any

create(sensitivity_analysis, disciplines, parameter_space, n_samples=None, output_names=(), algo='', algo_options=mappingproxy({}), formulation='MDF', **formulation_options)

Create the sensitivity analysis.

Parameters:

• sensitivity_analysis (str) – The name of a class defining a sensitivity analysis.

• disciplines (Collection[MDODiscipline]) – The discipline or disciplines to use for the analysis.

• parameter_space (ParameterSpace) – A parameter space.

• n_samples (int | None) – A number of samples. If None, the number of samples is computed by the algorithm.

• output_names (Iterable[str]) –

  The disciplines’ outputs to be considered for the analysis. If empty, use all the outputs.

  By default it is set to ().

• algo (str) –

  The name of the DOE algorithm. If empty, use the SensitivityAnalysis.DEFAULT_DRIVER.

  By default it is set to “”.

• algo_options (Mapping[str, DOELibraryOptionType]) –

  The options of the DOE algorithm.

  By default it is set to {}.

• formulation (str) –

  The name of the MDOFormulation to sample the disciplines.

  By default it is set to “MDF”.

• **formulation_options (Any) – The options of the MDOFormulation.

Returns:

A sensitivity analysis.

Raises:

TypeError – If the class cannot be instantiated.

Return type:

SensitivityAnalysis

property available_sensitivity_analyses: list[str]

The available classes for sensitivity analysis.

failed_imports: dict[str, str]

The class names bound to the import errors.