emukit package

Subpackages

• emukit.bayesian_optimization package
  • Subpackages
    • emukit.bayesian_optimization.acquisitions package
      • Submodules
        • EntropySearch
          • EntropySearch.update_parameters()
          • EntropySearch.update_pmin()
          • EntropySearch.evaluate()
          • EntropySearch.has_gradients
        • MultiInformationSourceEntropySearch
        • ExpectedImprovement
          • ExpectedImprovement.evaluate()
          • ExpectedImprovement.evaluate_with_gradients()
          • ExpectedImprovement.has_gradients
        • MeanPluginExpectedImprovement
        • get_standard_normal_pdf_cdf()
        • MultipointExpectedImprovement
          • MultipointExpectedImprovement.evaluate()
          • MultipointExpectedImprovement.evaluate_with_gradients()
        • get_covariance_given_smallest()
        • get_covariance_given_value_of_i()
        • get_correlations_given_value_of_i()
        • decompose_mvn()
        • Phi_gradient()
        • Phi_hessian()
        • LocalPenalization
          • LocalPenalization.has_gradients
          • LocalPenalization.update_batches()
          • LocalPenalization.evaluate()
          • LocalPenalization.evaluate_with_gradients()
        • LogAcquisition
          • LogAcquisition.evaluate()
          • LogAcquisition.evaluate_with_gradients()
          • LogAcquisition.has_gradients
        • MaxValueEntropySearch
          • MaxValueEntropySearch.update_parameters()
          • MaxValueEntropySearch.evaluate()
          • MaxValueEntropySearch.has_gradients
        • MUMBO
          • MUMBO.update_parameters()
          • MUMBO.evaluate()
        • NegativeLowerConfidenceBound
          • NegativeLowerConfidenceBound.evaluate()
          • NegativeLowerConfidenceBound.evaluate_with_gradients()
          • NegativeLowerConfidenceBound.has_gradients
        • ProbabilityOfFeasibility
          • ProbabilityOfFeasibility.evaluate()
          • ProbabilityOfFeasibility.evaluate_with_gradients()
          • ProbabilityOfFeasibility.has_gradients
        • ProbabilityOfImprovement
          • ProbabilityOfImprovement.evaluate()
          • ProbabilityOfImprovement.evaluate_with_gradients()
          • ProbabilityOfImprovement.has_gradients
      • Module contents
    • emukit.bayesian_optimization.interfaces package
      • Submodules
        • IEntropySearchModel
          • IEntropySearchModel.predict_covariance()
          • IEntropySearchModel.get_covariance_between_points()
      • Module contents
    • emukit.bayesian_optimization.loops package
      • Submodules
        • BayesianOptimizationLoop
          • BayesianOptimizationLoop.get_results()
        • BayesianOptimizationResults
        • CostSensitiveBayesianOptimizationLoop
        • UnknownConstraintBayesianOptimizationLoop
      • Module contents
  • Submodules
    • joint_min()
    • min_factor()
    • lt_factor()
    • log_relative_gauss()
    • LocalPenalizationPointCalculator
      • LocalPenalizationPointCalculator.compute_next_points()
  • Module contents
• emukit.benchmarking package
  • Subpackages
    • emukit.benchmarking.loop_benchmarking package
      • Submodules
        • BenchmarkPlot
          • BenchmarkPlot.make_plot()
          • BenchmarkPlot.save_plot()
        • BenchmarkResult
          • BenchmarkResult.add_results()
          • BenchmarkResult.extract_metric_as_array()
        • Benchmarker
          • Benchmarker.run_benchmark()
        • Metric
          • Metric.evaluate()
          • Metric.reset()
        • MeanSquaredErrorMetric
          • MeanSquaredErrorMetric.evaluate()
        • MinimumObservedValueMetric
          • MinimumObservedValueMetric.evaluate()
        • TimeMetric
          • TimeMetric.evaluate()
          • TimeMetric.reset()
        • CumulativeCostMetric
          • CumulativeCostMetric.evaluate()
          • CumulativeCostMetric.reset()
        • RandomSearch
      • Module contents
  • Module contents
• emukit.core package
  • Subpackages
    • emukit.core.acquisition package
      • Submodules
        • Acquisition
          • Acquisition.evaluate()
          • Acquisition.has_gradients
          • Acquisition.evaluate_with_gradients()
          • Acquisition.update_parameters()
        • Quotient
          • Quotient.evaluate()
          • Quotient.evaluate_with_gradients()
          • Quotient.has_gradients
          • Quotient.update_parameters()
        • Product
          • Product.evaluate()
          • Product.evaluate_with_gradients()
          • Product.has_gradients
          • Product.update_parameters()
        • Sum
          • Sum.evaluate()
          • Sum.evaluate_with_gradients()
          • Sum.has_gradients
          • Sum.update_parameters()
        • acquisition_per_expected_cost()
        • CostAcquisition
          • CostAcquisition.evaluate()
          • CostAcquisition.has_gradients
          • CostAcquisition.evaluate_with_gradients()
        • IntegratedHyperParameterAcquisition
          • IntegratedHyperParameterAcquisition.evaluate()
          • IntegratedHyperParameterAcquisition.evaluate_with_gradients()
          • IntegratedHyperParameterAcquisition.update_parameters()
          • IntegratedHyperParameterAcquisition.has_gradients
          • IntegratedHyperParameterAcquisition.update_batches()
      • Module contents
    • emukit.core.initial_designs package
      • Submodules
        • InitialDesignBase
          • InitialDesignBase.get_samples()
        • RandomDesign
          • RandomDesign.get_samples()
      • Module contents
    • emukit.core.interfaces package
      • Submodules
        • IModel
          • IModel.predict()
          • IModel.set_data()
          • IModel.optimize()
          • IModel.X
          • IModel.Y
        • IDifferentiable
          • IDifferentiable.get_prediction_gradients()
        • IJointlyDifferentiable
          • IJointlyDifferentiable.predict_with_full_covariance()
          • IJointlyDifferentiable.get_joint_prediction_gradients()
        • IPriorHyperparameters
          • IPriorHyperparameters.generate_hyperparameters_samples()
          • IPriorHyperparameters.fix_model_hyperparameters()
        • IModelWithNoise
          • IModelWithNoise.predict_noiseless()
      • Module contents
    • emukit.core.loop package
      • Submodules
        • CandidatePointCalculator
          • CandidatePointCalculator.compute_next_points()
        • SequentialPointCalculator
          • SequentialPointCalculator.compute_next_points()
        • GreedyBatchPointCalculator
          • GreedyBatchPointCalculator.compute_next_points()
        • RandomSampling
          • RandomSampling.compute_next_points()
        • LoopState
          • LoopState.update()
          • LoopState.X
          • LoopState.Y
        • create_loop_state()
        • ModelUpdater
          • ModelUpdater.update()
        • NoopModelUpdater
          • NoopModelUpdater.update()
        • FixedIntervalUpdater
          • FixedIntervalUpdater.update()
        • OuterLoop
          • OuterLoop.run_loop()
          • OuterLoop.get_next_points()
        • StoppingCondition
          • StoppingCondition.should_stop()
        • And
          • And.should_stop()
        • Or
          • Or.should_stop()
        • FixedIterationsStoppingCondition
          • FixedIterationsStoppingCondition.should_stop()
        • ConvergenceStoppingCondition
          • ConvergenceStoppingCondition.should_stop()
        • UserFunction
          • UserFunction.evaluate()
        • UserFunctionWrapper
          • UserFunctionWrapper.evaluate()
        • MultiSourceFunctionWrapper
          • MultiSourceFunctionWrapper.evaluate()
        • UserFunctionResult
      • Module contents
    • emukit.core.optimization package
      • Submodules
        • AcquisitionOptimizerBase
          • AcquisitionOptimizerBase.optimize()
        • AnchorPointsGenerator
          • AnchorPointsGenerator.get_anchor_point_scores()
          • AnchorPointsGenerator.get()
        • ObjectiveAnchorPointsGenerator
          • ObjectiveAnchorPointsGenerator.get_anchor_point_scores()
        • ContextManager
          • ContextManager.expand_vector()
        • GradientAcquisitionOptimizer
        • LocalSearchAcquisitionOptimizer
        • MultiSourceAcquisitionOptimizer
          • MultiSourceAcquisitionOptimizer.optimize()
        • Optimizer
          • Optimizer.optimize()
        • OptLbfgs
          • OptLbfgs.optimize()
        • apply_optimizer()
        • OptimizationWithContext
          • OptimizationWithContext.f_no_context()
          • OptimizationWithContext.df_no_context()
          • OptimizationWithContext.f_df_no_context()
        • OptTrustRegionConstrained
          • OptTrustRegionConstrained.optimize()
        • RandomSearchAcquisitionOptimizer
      • Module contents
  • Submodules
    • CategoricalParameter
      • CategoricalParameter.encodings
      • CategoricalParameter.model_parameters
      • CategoricalParameter.round()
      • CategoricalParameter.bounds
      • CategoricalParameter.dimension
      • CategoricalParameter.check_in_domain()
      • CategoricalParameter.sample_uniform()
    • IConstraint
      • IConstraint.evaluate()
    • InequalityConstraint
    • LinearInequalityConstraint
      • LinearInequalityConstraint.evaluate()
    • NonlinearInequalityConstraint
      • NonlinearInequalityConstraint.evaluate()
    • ContinuousParameter
      • ContinuousParameter.check_in_domain()
      • ContinuousParameter.bounds
      • ContinuousParameter.sample_uniform()
    • DiscreteParameter
      • DiscreteParameter.check_in_domain()
      • DiscreteParameter.bounds
      • DiscreteParameter.round()
      • DiscreteParameter.sample_uniform()
    • InformationSourceParameter
    • Encoding
      • Encoding.dimension
      • Encoding.round()
      • Encoding.round_row()
      • Encoding.get_category()
      • Encoding.get_encoding()
    • OneHotEncoding
      • OneHotEncoding.round_row()
    • OrdinalEncoding
      • OrdinalEncoding.round_row()
    • EventHandler
    • Parameter
      • Parameter.dimension
      • Parameter.model_parameters
      • Parameter.bounds
      • Parameter.round()
      • Parameter.check_in_domain()
      • Parameter.sample_uniform()
    • ParameterSpace
      • ParameterSpace.find_parameter_index_in_model()
      • ParameterSpace.dimensionality
      • ParameterSpace.parameters
      • ParameterSpace.parameter_names
      • ParameterSpace.get_parameter_by_name()
      • ParameterSpace.get_bounds()
      • ParameterSpace.round()
      • ParameterSpace.check_points_in_domain()
      • ParameterSpace.sample_uniform()
  • Module contents
• emukit.experimental_design package
  • Subpackages
    • emukit.experimental_design.acquisitions package
      • Submodules
        • IntegratedVarianceReduction
          • IntegratedVarianceReduction.evaluate()
          • IntegratedVarianceReduction.has_gradients
        • ModelVariance
          • ModelVariance.evaluate()
          • ModelVariance.evaluate_with_gradients()
          • ModelVariance.has_gradients
      • Module contents
    • emukit.experimental_design.interfaces package
      • Submodules
        • ICalculateVarianceReduction
          • ICalculateVarianceReduction.calculate_variance_reduction()
      • Module contents
  • Submodules
    • ExperimentalDesignLoop
  • Module contents
• emukit.model_wrappers package
  • Submodules
    • GPyModelWrapper
      • GPyModelWrapper.predict()
      • GPyModelWrapper.predict_noiseless()
      • GPyModelWrapper.predict_with_full_covariance()
      • GPyModelWrapper.get_prediction_gradients()
      • GPyModelWrapper.get_joint_prediction_gradients()
      • GPyModelWrapper.set_data()
      • GPyModelWrapper.optimize()
      • GPyModelWrapper.calculate_variance_reduction()
      • GPyModelWrapper.predict_covariance()
      • GPyModelWrapper.get_covariance_between_points()
      • GPyModelWrapper.X
      • GPyModelWrapper.Y
      • GPyModelWrapper.generate_hyperparameters_samples()
      • GPyModelWrapper.fix_model_hyperparameters()
    • dSigma()
    • dmean()
    • GPyMultiOutputWrapper
      • GPyMultiOutputWrapper.calculate_variance_reduction()
      • GPyMultiOutputWrapper.get_prediction_gradients()
      • GPyMultiOutputWrapper.predict()
      • GPyMultiOutputWrapper.set_data()
      • GPyMultiOutputWrapper.optimize()
      • GPyMultiOutputWrapper.X
      • GPyMultiOutputWrapper.Y
      • GPyMultiOutputWrapper.predict_covariance()
      • GPyMultiOutputWrapper.get_covariance_between_points()
      • GPyMultiOutputWrapper.generate_hyperparameters_samples()
      • GPyMultiOutputWrapper.fix_model_hyperparameters()
    • BaseGaussianProcessGPy
      • BaseGaussianProcessGPy.X
      • BaseGaussianProcessGPy.Y
      • BaseGaussianProcessGPy.observation_noise_variance
      • BaseGaussianProcessGPy.set_data()
      • BaseGaussianProcessGPy.predict()
      • BaseGaussianProcessGPy.predict_with_full_covariance()
      • BaseGaussianProcessGPy.solve_linear()
      • BaseGaussianProcessGPy.graminv_residual()
      • BaseGaussianProcessGPy.optimize()
    • RBFGPy
      • RBFGPy.lengthscales
      • RBFGPy.variance
      • RBFGPy.K()
    • ProductMatern12GPy
      • ProductMatern12GPy.lengthscales
      • ProductMatern12GPy.variance
      • ProductMatern12GPy.K()
      • ProductMatern12GPy.dK_dx1()
    • ProductMatern32GPy
      • ProductMatern32GPy.lengthscales
      • ProductMatern32GPy.variance
      • ProductMatern32GPy.K()
      • ProductMatern32GPy.dK_dx1()
    • ProductMatern52GPy
      • ProductMatern52GPy.lengthscales
      • ProductMatern52GPy.variance
      • ProductMatern52GPy.K()
      • ProductMatern52GPy.dK_dx1()
    • BrownianGPy
      • BrownianGPy.variance
      • BrownianGPy.K()
    • ProductBrownianGPy
      • ProductBrownianGPy.variance
      • ProductBrownianGPy.offset
      • ProductBrownianGPy.K()
      • ProductBrownianGPy.dK_dx1()
      • ProductBrownianGPy.dKdiag_dx()
    • create_emukit_model_from_gpy_model()
    • SimpleGaussianProcessModel
      • SimpleGaussianProcessModel.optimize()
      • SimpleGaussianProcessModel.predict()
      • SimpleGaussianProcessModel.set_data()
      • SimpleGaussianProcessModel.X
      • SimpleGaussianProcessModel.Y
  • Module contents
• emukit.multi_fidelity package
  • Subpackages
    • emukit.multi_fidelity.kernels package
      • Submodules
        • LinearMultiFidelityKernel
          • LinearMultiFidelityKernel.K()
          • LinearMultiFidelityKernel.Kdiag()
          • LinearMultiFidelityKernel.gradients_X()
          • LinearMultiFidelityKernel.gradients_X_diag()
          • LinearMultiFidelityKernel.update_gradients_diag()
          • LinearMultiFidelityKernel.update_gradients_full()
      • Module contents
    • emukit.multi_fidelity.models package
      • Submodules
        • GPyLinearMultiFidelityModel
        • make_non_linear_kernels()
        • NonLinearMultiFidelityModel
          • NonLinearMultiFidelityModel.set_data()
          • NonLinearMultiFidelityModel.X
          • NonLinearMultiFidelityModel.Y
          • NonLinearMultiFidelityModel.n_samples
          • NonLinearMultiFidelityModel.predict()
          • NonLinearMultiFidelityModel.get_prediction_gradients()
          • NonLinearMultiFidelityModel.optimize()
          • NonLinearMultiFidelityModel.get_f_minimum()
      • Module contents
  • Submodules
    • convert_x_list_to_array()
    • convert_y_list_to_array()
    • convert_xy_lists_to_arrays()
  • Module contents
• emukit.quadrature package
  • Module contents
  • Subpackages
    • emukit.quadrature.acquisitions package
      • Module contents
        • MutualInformation
          • MutualInformation.has_gradients
          • MutualInformation.evaluate()
          • MutualInformation.evaluate_with_gradients()
        • IntegralVarianceReduction
        • SquaredCorrelation
          • SquaredCorrelation.has_gradients
          • SquaredCorrelation.evaluate()
          • SquaredCorrelation.evaluate_with_gradients()
        • UncertaintySampling
          • UncertaintySampling.has_gradients
          • UncertaintySampling.evaluate()
          • UncertaintySampling.evaluate_with_gradients()
    • emukit.quadrature.interfaces package
      • Module contents
        • IBaseGaussianProcess
          • IBaseGaussianProcess.observation_noise_variance
          • IBaseGaussianProcess.predict_with_full_covariance()
          • IBaseGaussianProcess.solve_linear()
          • IBaseGaussianProcess.graminv_residual()
          • IBaseGaussianProcess.get_prediction_gradients()
        • IStandardKernel
          • IStandardKernel.K()
          • IStandardKernel.dK_dx1()
          • IStandardKernel.dKdiag_dx()
        • IBrownian
          • IBrownian.variance
          • IBrownian.dK_dx1()
          • IBrownian.dKdiag_dx()
        • IRBF
          • IRBF.lengthscales
          • IRBF.variance
          • IRBF.dK_dx1()
          • IRBF.dKdiag_dx()
        • IProductBrownian
          • IProductBrownian.variance
          • IProductBrownian.offset
        • IProductMatern12
          • IProductMatern12.nu
          • IProductMatern12.lengthscales
          • IProductMatern12.variance
          • IProductMatern12.dKdiag_dx()
        • IProductMatern32
          • IProductMatern32.nu
          • IProductMatern32.lengthscales
          • IProductMatern32.variance
          • IProductMatern32.dKdiag_dx()
        • IProductMatern52
          • IProductMatern52.nu
          • IProductMatern52.lengthscales
          • IProductMatern52.variance
          • IProductMatern52.dKdiag_dx()
    • emukit.quadrature.kernels package
      • Module contents
        • QuadratureKernel
          • QuadratureKernel.K()
          • QuadratureKernel.qK()
          • QuadratureKernel.Kq()
          • QuadratureKernel.qKq()
          • QuadratureKernel.dK_dx1()
          • QuadratureKernel.dK_dx2()
          • QuadratureKernel.dKdiag_dx()
          • QuadratureKernel.dqK_dx()
          • QuadratureKernel.dKq_dx()
        • QuadratureProductKernel
          • QuadratureProductKernel.qK()
          • QuadratureProductKernel.qKq()
          • QuadratureProductKernel.dqK_dx()
        • LebesgueEmbedding
          • LebesgueEmbedding.from_integral_bounds()
        • GaussianEmbedding
          • GaussianEmbedding.from_measure_params()
        • QuadratureBrownian
          • QuadratureBrownian.variance
        • QuadratureBrownianLebesgueMeasure
          • QuadratureBrownianLebesgueMeasure.qK()
          • QuadratureBrownianLebesgueMeasure.qKq()
          • QuadratureBrownianLebesgueMeasure.dqK_dx()
        • QuadratureRBF
          • QuadratureRBF.lengthscales
          • QuadratureRBF.variance
        • QuadratureRBFLebesgueMeasure
          • QuadratureRBFLebesgueMeasure.qK()
          • QuadratureRBFLebesgueMeasure.qKq()
          • QuadratureRBFLebesgueMeasure.dqK_dx()
        • QuadratureRBFGaussianMeasure
          • QuadratureRBFGaussianMeasure.qK()
          • QuadratureRBFGaussianMeasure.qKq()
          • QuadratureRBFGaussianMeasure.dqK_dx()
        • QuadratureProductMatern52
          • QuadratureProductMatern52.nu
          • QuadratureProductMatern52.lengthscales
          • QuadratureProductMatern52.variance
        • QuadratureProductMatern52LebesgueMeasure
        • QuadratureProductMatern32
          • QuadratureProductMatern32.nu
          • QuadratureProductMatern32.lengthscales
          • QuadratureProductMatern32.variance
        • QuadratureProductMatern32LebesgueMeasure
        • QuadratureProductMatern12
          • QuadratureProductMatern12.nu
          • QuadratureProductMatern12.lengthscales
          • QuadratureProductMatern12.variance
        • QuadratureProductMatern12LebesgueMeasure
        • QuadratureProductBrownian
          • QuadratureProductBrownian.variance
          • QuadratureProductBrownian.offset
        • QuadratureProductBrownianLebesgueMeasure
    • emukit.quadrature.loop package
      • Module contents
        • BayesianMonteCarlo
        • VanillaBayesianQuadratureLoop
        • WSABILLoop
      • Submodules
        • BayesianMonteCarloPointCalculator
          • BayesianMonteCarloPointCalculator.compute_next_points()
    • emukit.quadrature.measures package
      • Module contents
        • BoxDomain
          • BoxDomain.bounds
          • BoxDomain.convert_to_list_of_continuous_parameters()
        • IntegrationMeasure
          • IntegrationMeasure.input_dim
          • IntegrationMeasure.can_sample
          • IntegrationMeasure.compute_density()
          • IntegrationMeasure.compute_density_gradient()
          • IntegrationMeasure.reasonable_box()
          • IntegrationMeasure.sample()
        • GaussianMeasure
          • GaussianMeasure.input_dim
          • GaussianMeasure.full_covariance_matrix
          • GaussianMeasure.can_sample
          • GaussianMeasure.compute_density()
          • GaussianMeasure.compute_density_gradient()
          • GaussianMeasure.reasonable_box()
          • GaussianMeasure.sample()
        • LebesgueMeasure
          • LebesgueMeasure.input_dim
          • LebesgueMeasure.can_sample
          • LebesgueMeasure.compute_density()
          • LebesgueMeasure.compute_density_gradient()
          • LebesgueMeasure.reasonable_box()
          • LebesgueMeasure.sample()
          • LebesgueMeasure.from_bounds()
    • emukit.quadrature.methods package
      • Module contents
        • WarpedBayesianQuadratureModel
          • WarpedBayesianQuadratureModel.X
          • WarpedBayesianQuadratureModel.Y
          • WarpedBayesianQuadratureModel.integral_bounds
          • WarpedBayesianQuadratureModel.reasonable_box_bounds
          • WarpedBayesianQuadratureModel.measure
          • WarpedBayesianQuadratureModel.transform()
          • WarpedBayesianQuadratureModel.inverse_transform()
          • WarpedBayesianQuadratureModel.predict_base()
          • WarpedBayesianQuadratureModel.predict_base_with_full_covariance()
          • WarpedBayesianQuadratureModel.predict_with_full_covariance()
          • WarpedBayesianQuadratureModel.predict()
          • WarpedBayesianQuadratureModel.set_data()
          • WarpedBayesianQuadratureModel.compute_warping_params()
          • WarpedBayesianQuadratureModel.optimize()
          • WarpedBayesianQuadratureModel.integrate()
          • WarpedBayesianQuadratureModel.symmetrize_matrix()
        • VanillaBayesianQuadrature
          • VanillaBayesianQuadrature.predict_base()
          • VanillaBayesianQuadrature.predict_base_with_full_covariance()
          • VanillaBayesianQuadrature.integrate()
          • VanillaBayesianQuadrature.get_prediction_gradients()
        • BoundedBayesianQuadrature
          • BoundedBayesianQuadrature.bound
          • BoundedBayesianQuadrature.is_lower_bounded
          • BoundedBayesianQuadrature.predict_base()
          • BoundedBayesianQuadrature.predict_base_with_full_covariance()
          • BoundedBayesianQuadrature.integrate()
          • BoundedBayesianQuadrature.get_prediction_gradients()
        • WSABIL
          • WSABIL.compute_warping_params()
      • Submodules
        • Warping
          • Warping.transform()
          • Warping.inverse_transform()
          • Warping.update_parameters()
        • IdentityWarping
          • IdentityWarping.transform()
          • IdentityWarping.inverse_transform()
        • SquareRootWarping
          • SquareRootWarping.transform()
          • SquareRootWarping.inverse_transform()
• emukit.samplers package
  • Submodules
    • McmcSampler
      • McmcSampler.get_samples()
    • AffineInvariantEnsembleSampler
      • AffineInvariantEnsembleSampler.get_samples()
  • Module contents
• emukit.sensitivity package
  • Subpackages
    • emukit.sensitivity.monte_carlo package
      • Submodules
        • ModelFreeMonteCarloSensitivity
          • ModelFreeMonteCarloSensitivity.saltelli_estimators()
          • ModelFreeMonteCarloSensitivity.compute_statistics()
          • ModelFreeMonteCarloSensitivity.compute_effects()
        • MonteCarloSensitivity
      • Module contents
  • Module contents
• emukit.test_functions package
  • Subpackages
    • emukit.test_functions.multi_fidelity package
      • Submodules
        • multi_fidelity_borehole_function()
        • multi_fidelity_branin_function()
        • multi_fidelity_currin_function()
        • multi_fidelity_hartmann_3d()
        • multi_fidelity_park_function()
      • Module contents
    • emukit.test_functions.quadrature package
      • Submodules
        • univariate_approximate_ground_truth_integral()
        • bivariate_approximate_ground_truth_integral()
        • circular_gaussian()
        • hennig1D()
        • sombrero2D()
      • Module contents
    • emukit.test_functions.sensitivity package
      • Submodules
        • Ishigami
          • Ishigami.fidelity1()
          • Ishigami.fidelity2()
          • Ishigami.fidelity3()
          • Ishigami.fidelity4()
          • Ishigami.f0()
          • Ishigami.f1()
          • Ishigami.f2()
          • Ishigami.f3()
          • Ishigami.f12()
          • Ishigami.f13()
          • Ishigami.f23()
          • Ishigami.f123()
      • Module contents
  • Submodules
    • branin_function()
    • multi_fidelity_forrester_function()
    • forrester_function()
    • forrester()
    • forrester_low()
    • multi_fidelity_non_linear_sin()
    • nonlinear_sin_low()
    • nonlinear_sin_high()
    • sixhumpcamel_function()
  • Module contents

Module contents