emukit package¶
Subpackages¶
- emukit.bayesian_optimization package
- Subpackages
- emukit.bayesian_optimization.acquisitions package
- Submodules
EntropySearch
MultiInformationSourceEntropySearch
ExpectedImprovement
MeanPluginExpectedImprovement
get_standard_normal_pdf_cdf()
MultipointExpectedImprovement
get_covariance_given_smallest()
get_covariance_given_value_of_i()
get_correlations_given_value_of_i()
decompose_mvn()
Phi_gradient()
Phi_hessian()
LocalPenalization
LogAcquisition
MaxValueEntropySearch
MUMBO
NegativeLowerConfidenceBound
ProbabilityOfFeasibility
ProbabilityOfImprovement
- Module contents
- Submodules
- emukit.bayesian_optimization.interfaces package
- emukit.bayesian_optimization.loops package
- emukit.bayesian_optimization.acquisitions package
- Submodules
- Module contents
- Subpackages
- emukit.benchmarking package
- emukit.core package
- Subpackages
- emukit.core.acquisition package
- emukit.core.initial_designs package
- emukit.core.interfaces package
- emukit.core.loop package
- Submodules
CandidatePointCalculator
SequentialPointCalculator
GreedyBatchPointCalculator
RandomSampling
LoopState
create_loop_state()
ModelUpdater
NoopModelUpdater
FixedIntervalUpdater
OuterLoop
StoppingCondition
And
Or
FixedIterationsStoppingCondition
ConvergenceStoppingCondition
UserFunction
UserFunctionWrapper
MultiSourceFunctionWrapper
UserFunctionResult
- Module contents
- Submodules
- emukit.core.optimization package
- Submodules
AcquisitionOptimizerBase
AnchorPointsGenerator
ObjectiveAnchorPointsGenerator
ContextManager
GradientAcquisitionOptimizer
LocalSearchAcquisitionOptimizer
MultiSourceAcquisitionOptimizer
Optimizer
OptLbfgs
apply_optimizer()
OptimizationWithContext
OptTrustRegionConstrained
RandomSearchAcquisitionOptimizer
- Module contents
- Submodules
- Submodules
- Module contents
- Subpackages
- emukit.experimental_design package
- 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
ProductMatern12GPy
ProductMatern32GPy
ProductMatern52GPy
BrownianGPy
ProductBrownianGPy
create_emukit_model_from_gpy_model()
SimpleGaussianProcessModel
- Module contents
- Submodules
- emukit.multi_fidelity package
- Subpackages
- emukit.multi_fidelity.kernels package
- 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
- Submodules
- Module contents
- Subpackages
- emukit.quadrature package
- Module contents
- Subpackages
- emukit.quadrature.acquisitions package
- emukit.quadrature.interfaces package
- emukit.quadrature.kernels package
- Module contents
QuadratureKernel
QuadratureProductKernel
LebesgueEmbedding
GaussianEmbedding
QuadratureBrownian
QuadratureBrownianLebesgueMeasure
QuadratureRBF
QuadratureRBFLebesgueMeasure
QuadratureRBFGaussianMeasure
QuadratureProductMatern52
QuadratureProductMatern52LebesgueMeasure
QuadratureProductMatern32
QuadratureProductMatern32LebesgueMeasure
QuadratureProductMatern12
QuadratureProductMatern12LebesgueMeasure
QuadratureProductBrownian
QuadratureProductBrownianLebesgueMeasure
- Module contents
- emukit.quadrature.loop package
- emukit.quadrature.measures package
- 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
BoundedBayesianQuadrature
WSABIL
- Submodules
- Module contents
- emukit.samplers package
- emukit.sensitivity package
- emukit.test_functions package