sensitivity_analysis
¶
Module Contents¶
Classes¶
Functions¶
Attributes¶
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class
SensitivityResults
[source]¶ Bases:
optimeed.core.SaveableObject
Abstract class for dynamically type-hinted objects. This class is to solve the special case where the exact type of an attribute is not known before runtime, yet has to be saved.
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class
SensitivityParameters
(param_values, list_of_optimization_variables, theDevice, theMathsToPhys, theCharacterization)[source]¶ Bases:
optimeed.core.SaveableObject
Abstract class for dynamically type-hinted objects. This class is to solve the special case where the exact type of an attribute is not known before runtime, yet has to be saved.
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class
Restrained_SensitivityParameters
(*args)[source]¶ Bases:
SensitivityParameters
Class to perform Sensitivty Analysis on a subset of the full parameters
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class
SensitivityAnalysis_LibInterface
(theSensitivityParameters: SensitivityParameters, theObjectives)[source]¶ Interface a library for sensitivity analysis
Parameters: - theSensitivityParameters –
optimeed.consolidate.sensitivity_analysis.SensitivityParameters
- theObjectives – array-like objective associated to evaluation, using Sobol sampling
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get_convergence_S1
(stepsize=1)[source]¶ Create dictionary for convergence plot - First order index
Parameters: stepsize – increments of sampling size Returns: Dictionary
- theSensitivityParameters –
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_get_job_args
(theSensitivityParameters, index)[source]¶ Convert sensitivityparameters at index to args used in “evaluate” function
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prepare_embarrassingly_parallel_sensitivity
(theSensitivityParameters, studyname)[source]¶ Initialize sensitivity analysis folder :param theSensitivityParameters: :param studyname: Folder to be created in Workspace :return:
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launch_embarrassingly_parallel_sensitivity
(theSensitivityParameters, studyname, base_index, mult_factor=1)[source]¶ Single job launcher for an embarrassingly parallel evaluation :param theSensitivityParameters: :param studyname: Name of the folder in Workspace in which the study is performed :param base_index: start index (Formula: index to evaluate = base_index*mult_factor) :param mult_factor: Multiplication factor of the base_index. Allows to overcome QOSMaxJobPerUserLimit in clusters. :return:
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launch_missing_embarrassingly_parallel_sensitivity
(theSensitivityParameters, studyname, missing_list, base_index, mult_factor=1)[source]¶ Same as launch_embarrassingly_parallel_sensitivity, but using the ‘missing_list’ arg used for mapping
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gather_embarrassingly_parallel_sensitivity
(theSensitivityParameters, studyname)[source]¶ Gather the results. If some are missing, display the indices.
Parameters: - theSensitivityParameters –
- studyname –
Returns:
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evaluate_sensitivities
(theSensitivityParameters: SensitivityParameters, numberOfCores=2, studyname='sensitivity', indices_to_evaluate=None)[source]¶ Evaluate the sensitivities
Parameters: - theSensitivityParameters – class`~SensitivityParameters`
- numberOfCores – number of core for multicore evaluation
- studyname – Name of the study, that will be the subfolder name in workspace
- indices_to_evaluate – if None, evaluate all param_values, otherwise if list: evaluate subset of param_values defined by indices_to_evaluate
Returns: collection of class`~SensitivityResults`