queens package#
The QUEENS package.
Subpackages#
- queens.data_processor package
- Submodules
- queens.data_processor.data_processor module
- queens.data_processor.data_processor_csv module
DataProcessorCsv
DataProcessorCsv.use_cols_lst
DataProcessorCsv.filter_type
DataProcessorCsv.header_row
DataProcessorCsv.skip_rows
DataProcessorCsv.index_column
DataProcessorCsv.use_rows_lst
DataProcessorCsv.filter_range
DataProcessorCsv.filter_target_values
DataProcessorCsv.filter_tol
DataProcessorCsv.returned_filter_format
DataProcessorCsv.check_valid_filter_options()
DataProcessorCsv.expected_filter_by_range
DataProcessorCsv.expected_filter_by_row_index
DataProcessorCsv.expected_filter_by_target_values
DataProcessorCsv.expected_filter_entire_file
DataProcessorCsv.filter_and_manipulate_raw_data()
DataProcessorCsv.get_raw_data_from_file()
- queens.data_processor.data_processor_ensight module
DataProcessorEnsight
DataProcessorEnsight.experimental_data
DataProcessorEnsight.coordinates_label_experimental
DataProcessorEnsight.time_label_experimental
DataProcessorEnsight.external_geometry
DataProcessorEnsight.target_time_lst
DataProcessorEnsight.time_tol
DataProcessorEnsight.vtk_field_label
DataProcessorEnsight.vtk_field_components
DataProcessorEnsight.vtk_array_type
DataProcessorEnsight.geometric_target
DataProcessorEnsight.geometric_set_data
DataProcessorEnsight.filter_and_manipulate_raw_data()
DataProcessorEnsight.get_raw_data_from_file()
DataProcessorEnsight.read_geometry_coordinates()
- queens.data_processor.data_processor_ensight_interface module
DataProcessorEnsightInterfaceDiscrepancy
DataProcessorEnsightInterfaceDiscrepancy.time_tol
DataProcessorEnsightInterfaceDiscrepancy.visualization_bool
DataProcessorEnsightInterfaceDiscrepancy.displacement_fields
DataProcessorEnsightInterfaceDiscrepancy.problem_dimension
DataProcessorEnsightInterfaceDiscrepancy.experimental_ref_data_lst
DataProcessorEnsightInterfaceDiscrepancy.compute_distance()
DataProcessorEnsightInterfaceDiscrepancy.deformed_grid()
DataProcessorEnsightInterfaceDiscrepancy.filter_and_manipulate_raw_data()
DataProcessorEnsightInterfaceDiscrepancy.get_raw_data_from_file()
DataProcessorEnsightInterfaceDiscrepancy.read_monitorfile()
DataProcessorEnsightInterfaceDiscrepancy.stretch_vector()
- queens.data_processor.data_processor_numpy module
- queens.data_processor.data_processor_pvd module
- queens.data_processor.data_processor_txt module
- queens.distributions package
- Submodules
- queens.distributions.bernoulli module
- queens.distributions.beta module
- queens.distributions.categorical module
- queens.distributions.distributions module
ContinuousDistribution
ContinuousDistribution.mean
ContinuousDistribution.covariance
ContinuousDistribution.dimension
ContinuousDistribution.cdf()
ContinuousDistribution.check_1d()
ContinuousDistribution.check_bounds()
ContinuousDistribution.draw()
ContinuousDistribution.grad_logpdf()
ContinuousDistribution.logpdf()
ContinuousDistribution.pdf()
ContinuousDistribution.ppf()
DiscreteDistribution
DiscreteDistribution.mean
DiscreteDistribution.covariance
DiscreteDistribution.dimension
DiscreteDistribution.probabilities
DiscreteDistribution.sample_space
DiscreteDistribution.cdf()
DiscreteDistribution.check_1d()
DiscreteDistribution.check_duplicates_in_sample_space()
DiscreteDistribution.draw()
DiscreteDistribution.logpdf()
DiscreteDistribution.pdf()
DiscreteDistribution.ppf()
Distribution
- queens.distributions.exponential module
ExponentialDistribution
ExponentialDistribution.rate
ExponentialDistribution.scale
ExponentialDistribution.pdf_const
ExponentialDistribution.logpdf_const
ExponentialDistribution.cdf()
ExponentialDistribution.draw()
ExponentialDistribution.grad_logpdf()
ExponentialDistribution.logpdf()
ExponentialDistribution.pdf()
ExponentialDistribution.ppf()
- queens.distributions.free module
- queens.distributions.lognormal module
- queens.distributions.mean_field_normal module
MeanFieldNormalDistribution
MeanFieldNormalDistribution.standard_deviation
MeanFieldNormalDistribution.cdf()
MeanFieldNormalDistribution.draw()
MeanFieldNormalDistribution.get_check_array_dimension_and_reshape()
MeanFieldNormalDistribution.grad_logpdf()
MeanFieldNormalDistribution.grad_logpdf_var()
MeanFieldNormalDistribution.logpdf()
MeanFieldNormalDistribution.pdf()
MeanFieldNormalDistribution.ppf()
MeanFieldNormalDistribution.update_mean()
MeanFieldNormalDistribution.update_variance()
- queens.distributions.mixture module
- queens.distributions.multinomial module
- queens.distributions.normal module
- queens.distributions.particles module
ParticleDiscreteDistribution
ParticleDiscreteDistribution.mean
ParticleDiscreteDistribution.covariance
ParticleDiscreteDistribution.dimension
ParticleDiscreteDistribution.probabilities
ParticleDiscreteDistribution.sample_space
ParticleDiscreteDistribution.cdf()
ParticleDiscreteDistribution.draw()
ParticleDiscreteDistribution.logpdf()
ParticleDiscreteDistribution.pdf()
ParticleDiscreteDistribution.ppf()
- queens.distributions.uniform module
UniformDistribution
UniformDistribution.lower_bound
UniformDistribution.upper_bound
UniformDistribution.width
UniformDistribution.pdf_const
UniformDistribution.logpdf_const
UniformDistribution.cdf()
UniformDistribution.draw()
UniformDistribution.grad_logpdf()
UniformDistribution.logpdf()
UniformDistribution.pdf()
UniformDistribution.ppf()
- queens.distributions.uniform_discrete module
- queens.drivers package
- Submodules
- queens.drivers.driver module
- queens.drivers.fourc_driver module
- queens.drivers.function_driver module
- queens.drivers.jobscript_driver module
JobOptions
JobscriptDriver
JobscriptDriver.input_templates
JobscriptDriver.data_processor
JobscriptDriver.gradient_data_processor
JobscriptDriver.jobscript_template
JobscriptDriver.jobscript_options
JobscriptDriver.jobscript_file_name
JobscriptDriver.raise_error_on_jobscript_failure
JobscriptDriver.create_input_templates_dict()
JobscriptDriver.get_read_in_jobscript_template()
JobscriptDriver.prepare_input_files()
JobscriptDriver.run()
- queens.drivers.mpi_driver module
- queens.example_simulator_functions package
example_simulator_function_by_name()
- Submodules
- queens.example_simulator_functions.agawal09 module
- queens.example_simulator_functions.borehole83 module
- queens.example_simulator_functions.branin78 module
- queens.example_simulator_functions.currin88 module
- queens.example_simulator_functions.executable_park91a_hifi_on_grid_with_gradients module
- queens.example_simulator_functions.gardner14a module
- queens.example_simulator_functions.gaussian_logpdf module
- queens.example_simulator_functions.gaussian_mixture_logpdf module
- queens.example_simulator_functions.ishigami90 module
- queens.example_simulator_functions.ma09 module
- queens.example_simulator_functions.oakley_ohagan04 module
- queens.example_simulator_functions.parabola_residual module
- queens.example_simulator_functions.paraboloid module
- queens.example_simulator_functions.park91a module
- queens.example_simulator_functions.park91b module
- queens.example_simulator_functions.perdikaris17 module
- queens.example_simulator_functions.rezende15 module
- queens.example_simulator_functions.rosenbrock60 module
- queens.example_simulator_functions.sinus module
- queens.example_simulator_functions.sobol_g_function module
- queens.external_geometry package
- Submodules
- queens.external_geometry.external_geometry module
- queens.external_geometry.fourc_dat_geometry module
FourcDatExternalGeometry
FourcDatExternalGeometry.path_to_dat_file
FourcDatExternalGeometry.path_to_preprocessed_dat_file
FourcDatExternalGeometry.coords_dict
FourcDatExternalGeometry.list_geometric_sets
FourcDatExternalGeometry.current_dat_section
FourcDatExternalGeometry.desired_dat_sections
FourcDatExternalGeometry.nodes_of_interest
FourcDatExternalGeometry.new_nodes_lst
FourcDatExternalGeometry.node_topology
FourcDatExternalGeometry.line_topology
FourcDatExternalGeometry.surface_topology
FourcDatExternalGeometry.volume_topology
FourcDatExternalGeometry.node_coordinates
FourcDatExternalGeometry.element_centers
FourcDatExternalGeometry.element_topology
FourcDatExternalGeometry.original_materials_in_dat
FourcDatExternalGeometry.list_associated_material_numbers
FourcDatExternalGeometry.new_material_numbers
FourcDatExternalGeometry.random_dirich_flag
FourcDatExternalGeometry.random_transport_dirich_flag
FourcDatExternalGeometry.random_neumann_flag
FourcDatExternalGeometry.nodes_written
FourcDatExternalGeometry.random_fields
FourcDatExternalGeometry.check_if_in_desired_dat_section()
FourcDatExternalGeometry.dat_sections
FourcDatExternalGeometry.finish_and_clean()
FourcDatExternalGeometry.get_coordinates_of_desired_geometric_sets()
FourcDatExternalGeometry.get_current_dat_section()
FourcDatExternalGeometry.get_desired_dat_sections()
FourcDatExternalGeometry.get_elements_belonging_to_desired_material()
FourcDatExternalGeometry.get_materials()
FourcDatExternalGeometry.get_nodes_of_interest()
FourcDatExternalGeometry.get_only_desired_coordinates()
FourcDatExternalGeometry.get_only_desired_topology()
FourcDatExternalGeometry.get_topology()
FourcDatExternalGeometry.organize_sections()
FourcDatExternalGeometry.read_external_data()
FourcDatExternalGeometry.read_geometry_from_dat_file()
FourcDatExternalGeometry.section_match_dict
FourcDatExternalGeometry.write_random_fields_to_dat()
- queens.iterators package
- Subpackages
- queens.iterators.sobol_index_gp_uncertainty package
- Submodules
- queens.iterators.sobol_index_gp_uncertainty.estimator module
- queens.iterators.sobol_index_gp_uncertainty.predictor module
- queens.iterators.sobol_index_gp_uncertainty.sampler module
- queens.iterators.sobol_index_gp_uncertainty.statistics module
- queens.iterators.sobol_index_gp_uncertainty.utils_estimate_indices module
- queens.iterators.sobol_index_gp_uncertainty package
- Submodules
- queens.iterators.adaptive_sampling_iterator module
AdaptiveSamplingIterator
AdaptiveSamplingIterator.likelihood_model
AdaptiveSamplingIterator.initial_train_iterator
AdaptiveSamplingIterator.solving_iterator
AdaptiveSamplingIterator.num_new_samples
AdaptiveSamplingIterator.num_steps
AdaptiveSamplingIterator.seed
AdaptiveSamplingIterator.restart_file
AdaptiveSamplingIterator.cs_div_criterion
AdaptiveSamplingIterator.x_train
AdaptiveSamplingIterator.x_train_new
AdaptiveSamplingIterator.y_train
AdaptiveSamplingIterator.model_outputs
AdaptiveSamplingIterator.choose_new_samples()
AdaptiveSamplingIterator.core_run()
AdaptiveSamplingIterator.eval_log_likelihood()
AdaptiveSamplingIterator.get_particles_and_weights()
AdaptiveSamplingIterator.post_run()
AdaptiveSamplingIterator.pre_run()
AdaptiveSamplingIterator.write_results()
cauchy_schwarz_divergence()
- queens.iterators.black_box_variational_bayes module
BBVIIterator
BBVIIterator.control_variates_scaling_type
BBVIIterator.loo_cv_bool
BBVIIterator.random_seed
BBVIIterator.max_feval
BBVIIterator.memory
BBVIIterator.model_eval_iteration_period
BBVIIterator.resample
BBVIIterator.log_variational_mat
BBVIIterator.grad_params_log_variational_mat
BBVIIterator.log_posterior_unnormalized
BBVIIterator.samples_list
BBVIIterator.parameter_list
BBVIIterator.log_posterior_unnormalized_list
BBVIIterator.ess
BBVIIterator.sampling_bool
BBVIIterator.sample_set
BBVIIterator.core_run()
BBVIIterator.eval_log_likelihood()
BBVIIterator.get_importance_sampling_weights()
BBVIIterator.get_log_posterior_unnormalized()
BBVIIterator.get_log_prior()
- queens.iterators.bmfia_iterator module
BMFIAIterator
BMFIAIterator.X_train
BMFIAIterator.Y_LF_train
BMFIAIterator.Y_HF_train
BMFIAIterator.Z_train
BMFIAIterator.features_config
BMFIAIterator.hf_model
BMFIAIterator.lf_model
BMFIAIterator.coords_experimental_data
BMFIAIterator.time_vec
BMFIAIterator.y_obs_vec
BMFIAIterator.x_cols
BMFIAIterator.num_features
BMFIAIterator.coord_cols
BMFIAIterator.calculate_initial_x_train()
BMFIAIterator.core_run()
BMFIAIterator.eval_model()
BMFIAIterator.evaluate_HF_model_for_X_train()
BMFIAIterator.evaluate_LF_model_for_X_train()
BMFIAIterator.expand_training_data()
BMFIAIterator.get_design_method()
BMFIAIterator.random_design()
BMFIAIterator.set_feature_strategy()
BMFIAIterator.update_probabilistic_mapping_with_features()
- queens.iterators.bmfmc_iterator module
BMFMCIterator
BMFMCIterator.model
BMFMCIterator.result_description
BMFMCIterator.X_train
BMFMCIterator.Y_LFs_train
BMFMCIterator.output
BMFMCIterator.initial_design
BMFMCIterator.visualization
BMFMCIterator.calculate_optimal_X_train()
BMFMCIterator.core_run()
BMFMCIterator.diverse_subset_design()
BMFMCIterator.get_design_method()
BMFMCIterator.post_run()
BMFMCIterator.random_design()
- queens.iterators.classification module
ClassificationIterator
ClassificationIterator.result_description
ClassificationIterator.num_sample_points
ClassificationIterator.num_model_calls
ClassificationIterator.random_sampling_frequency
ClassificationIterator.classifier
ClassificationIterator.visualization_obj
ClassificationIterator.classification_function
ClassificationIterator.samples
ClassificationIterator.classified_outputs
ClassificationIterator.binarize()
ClassificationIterator.core_run()
ClassificationIterator.post_run()
default_classification_function()
- queens.iterators.control_variates_iterator module
ControlVariatesIterator
ControlVariatesIterator.model
ControlVariatesIterator.control_variate
ControlVariatesIterator.seed
ControlVariatesIterator.num_samples
ControlVariatesIterator.expectation_cv
ControlVariatesIterator.output
ControlVariatesIterator.num_samples_cv
ControlVariatesIterator.samples
ControlVariatesIterator.use_optimal_num_samples
ControlVariatesIterator.cost_model
ControlVariatesIterator.cost_cv
ControlVariatesIterator.variance_cv_mean_estimator
ControlVariatesIterator.core_run()
ControlVariatesIterator.post_run()
ControlVariatesIterator.pre_run()
- queens.iterators.data_iterator module
- queens.iterators.elementary_effects_iterator module
ElementaryEffectsIterator
ElementaryEffectsIterator.num_trajectories
ElementaryEffectsIterator.local_optimization
ElementaryEffectsIterator.num_optimal_trajectories
ElementaryEffectsIterator.num_levels
ElementaryEffectsIterator.seed
ElementaryEffectsIterator.confidence_level
ElementaryEffectsIterator.num_bootstrap_samples
ElementaryEffectsIterator.result_description
ElementaryEffectsIterator.samples
ElementaryEffectsIterator.output
ElementaryEffectsIterator.salib_problem
ElementaryEffectsIterator.si
ElementaryEffectsIterator.visualization
ElementaryEffectsIterator.core_run()
ElementaryEffectsIterator.post_run()
ElementaryEffectsIterator.pre_run()
ElementaryEffectsIterator.print_results()
ElementaryEffectsIterator.process_results()
- queens.iterators.grid_iterator module
- queens.iterators.hmc_iterator module
- queens.iterators.iterator module
- queens.iterators.lhs_iterator module
- queens.iterators.lm_iterator module
LMIterator
LMIterator.initial_guess
LMIterator.bounds
LMIterator.havebounds
LMIterator.param_current
LMIterator.jac_rel_step
LMIterator.max_feval
LMIterator.result_description
LMIterator.jac_abs_step
LMIterator.reg_param
LMIterator.init_reg
LMIterator.update_reg
LMIterator.tolerance
LMIterator.verbose_output
LMIterator.iter_opt
LMIterator.lowesterror
LMIterator.param_opt
LMIterator.solution
LMIterator.checkbounds()
LMIterator.core_run()
LMIterator.get_positions_raw_2pointperturb()
LMIterator.jacobian_and_residual()
LMIterator.post_run()
LMIterator.pre_run()
LMIterator.printstep()
- queens.iterators.metropolis_hastings_iterator module
MetropolisHastingsIterator
MetropolisHastingsIterator.num_chains
MetropolisHastingsIterator.num_samples
MetropolisHastingsIterator.proposal_distribution
MetropolisHastingsIterator.result_description
MetropolisHastingsIterator.as_smc_rejuvenation_step
MetropolisHastingsIterator.tune
MetropolisHastingsIterator.scale_covariance
MetropolisHastingsIterator.num_burn_in
MetropolisHastingsIterator.temper
MetropolisHastingsIterator.gamma
MetropolisHastingsIterator.tune_interval
MetropolisHastingsIterator.tot_num_samples
MetropolisHastingsIterator.chains
MetropolisHastingsIterator.log_likelihood
MetropolisHastingsIterator.log_prior
MetropolisHastingsIterator.log_posterior
MetropolisHastingsIterator.seed
MetropolisHastingsIterator.accepted
MetropolisHastingsIterator.accepted_interval
MetropolisHastingsIterator.core_run()
MetropolisHastingsIterator.do_mh_step()
MetropolisHastingsIterator.eval_log_likelihood()
MetropolisHastingsIterator.eval_log_prior()
MetropolisHastingsIterator.post_run()
MetropolisHastingsIterator.pre_run()
- queens.iterators.metropolis_hastings_pymc_iterator module
MetropolisHastingsPyMCIterator
MetropolisHastingsPyMCIterator.covariance
MetropolisHastingsPyMCIterator.tune_interval
MetropolisHastingsPyMCIterator.scaling
MetropolisHastingsPyMCIterator.eval_log_likelihood()
MetropolisHastingsPyMCIterator.eval_log_likelihood_grad()
MetropolisHastingsPyMCIterator.eval_log_prior_grad()
MetropolisHastingsPyMCIterator.init_distribution_wrapper()
MetropolisHastingsPyMCIterator.init_mcmc_method()
MetropolisHastingsPyMCIterator.post_run()
- queens.iterators.mlmc_iterator module
- queens.iterators.monte_carlo_iterator module
- queens.iterators.nuts_iterator module
- queens.iterators.optimization_iterator module
OptimizationIterator
OptimizationIterator.algorithm
OptimizationIterator.bounds
OptimizationIterator.cons
OptimizationIterator.initial_guess
OptimizationIterator.jac_method
OptimizationIterator.jac_rel_step
OptimizationIterator.max_feval
OptimizationIterator.result_description
OptimizationIterator.verbose_output
OptimizationIterator.precalculated_positions
OptimizationIterator.solution
OptimizationIterator.objective_and_jacobian
OptimizationIterator.check_precalculated()
OptimizationIterator.core_run()
OptimizationIterator.eval_model()
OptimizationIterator.evaluate_fd_positions()
OptimizationIterator.jacobian()
OptimizationIterator.objective()
OptimizationIterator.post_run()
OptimizationIterator.pre_run()
- queens.iterators.points_iterator module
- queens.iterators.polynomial_chaos_iterator module
PolynomialChaosIterator
PolynomialChaosIterator.seed
PolynomialChaosIterator.num_collocation_points
PolynomialChaosIterator.sampling_rule
PolynomialChaosIterator.polynomial_order
PolynomialChaosIterator.result_description
PolynomialChaosIterator.sparse
PolynomialChaosIterator.polynomial_chaos_approach
PolynomialChaosIterator.distribution
PolynomialChaosIterator.samples
PolynomialChaosIterator.result_dict
PolynomialChaosIterator.core_run()
PolynomialChaosIterator.post_run()
PolynomialChaosIterator.pre_run()
create_chaospy_distribution()
create_chaospy_joint_distribution()
- queens.iterators.pymc_iterator module
PyMCIterator
PyMCIterator.result_description
PyMCIterator.discard_tuned_samples
PyMCIterator.num_chains
PyMCIterator.num_burn_in
PyMCIterator.num_samples
PyMCIterator.chains
PyMCIterator.seed
PyMCIterator.pymc_model
PyMCIterator.step
PyMCIterator.use_queens_prior
PyMCIterator.progressbar
PyMCIterator.log_prior
PyMCIterator.log_like
PyMCIterator.results
PyMCIterator.results_dict
PyMCIterator.summary
PyMCIterator.pymc_sampler_stats
PyMCIterator.as_inference_dict
PyMCIterator.initvals
PyMCIterator.model_fwd_evals
PyMCIterator.model_grad_evals
PyMCIterator.buffered_samples
PyMCIterator.buffered_gradients
PyMCIterator.buffered_likelihoods
PyMCIterator.core_run()
PyMCIterator.eval_log_likelihood()
PyMCIterator.eval_log_likelihood_grad()
PyMCIterator.eval_log_prior()
PyMCIterator.eval_log_prior_grad()
PyMCIterator.init_distribution_wrapper()
PyMCIterator.init_mcmc_method()
PyMCIterator.post_run()
PyMCIterator.pre_run()
- queens.iterators.reparameteriztion_based_variational_inference module
- queens.iterators.sequential_monte_carlo_chopin module
ParticlesChopinDistribution
SequentialMonteCarloChopinIterator
SequentialMonteCarloChopinIterator.result_description
SequentialMonteCarloChopinIterator.seed
SequentialMonteCarloChopinIterator.num_particles
SequentialMonteCarloChopinIterator.num_variables
SequentialMonteCarloChopinIterator.n_sims
SequentialMonteCarloChopinIterator.max_feval
SequentialMonteCarloChopinIterator.prior
SequentialMonteCarloChopinIterator.smc_obj
SequentialMonteCarloChopinIterator.resampling_threshold
SequentialMonteCarloChopinIterator.resampling_method
SequentialMonteCarloChopinIterator.feynman_kac_model
SequentialMonteCarloChopinIterator.num_rejuvenation_steps
SequentialMonteCarloChopinIterator.waste_free
SequentialMonteCarloChopinIterator.core_run()
SequentialMonteCarloChopinIterator.eval_log_likelihood()
SequentialMonteCarloChopinIterator.initialize_feynman_kac()
SequentialMonteCarloChopinIterator.post_run()
SequentialMonteCarloChopinIterator.pre_run()
- queens.iterators.sequential_monte_carlo_iterator module
SequentialMonteCarloIterator
SequentialMonteCarloIterator.plot_trace_every
SequentialMonteCarloIterator.result_description
SequentialMonteCarloIterator.seed
SequentialMonteCarloIterator.mcmc_kernel
SequentialMonteCarloIterator.num_particles
SequentialMonteCarloIterator.num_variables
SequentialMonteCarloIterator.particles
SequentialMonteCarloIterator.weights
SequentialMonteCarloIterator.log_likelihood
SequentialMonteCarloIterator.log_prior
SequentialMonteCarloIterator.log_posterior
SequentialMonteCarloIterator.ess
SequentialMonteCarloIterator.ess_cur
SequentialMonteCarloIterator.temper
SequentialMonteCarloIterator.gamma_cur
SequentialMonteCarloIterator.gammas
SequentialMonteCarloIterator.a
SequentialMonteCarloIterator.b
SequentialMonteCarloIterator.calc_new_ess()
SequentialMonteCarloIterator.calc_new_gamma()
SequentialMonteCarloIterator.calc_new_weights()
SequentialMonteCarloIterator.core_run()
SequentialMonteCarloIterator.draw_trace()
SequentialMonteCarloIterator.eval_log_likelihood()
SequentialMonteCarloIterator.eval_log_prior()
SequentialMonteCarloIterator.post_run()
SequentialMonteCarloIterator.pre_run()
SequentialMonteCarloIterator.resample()
SequentialMonteCarloIterator.update_ess()
SequentialMonteCarloIterator.update_gamma()
SequentialMonteCarloIterator.update_weights()
- queens.iterators.sobol_index_gp_uncertainty_iterator module
SobolIndexGPUncertaintyIterator
SobolIndexGPUncertaintyIterator.result_description
SobolIndexGPUncertaintyIterator.num_procs
SobolIndexGPUncertaintyIterator.sampler
SobolIndexGPUncertaintyIterator.predictor
SobolIndexGPUncertaintyIterator.index_estimator
SobolIndexGPUncertaintyIterator.statistics
SobolIndexGPUncertaintyIterator.calculate_second_order
SobolIndexGPUncertaintyIterator.calculate_third_order
SobolIndexGPUncertaintyIterator.results
SobolIndexGPUncertaintyIterator.calculate_index()
SobolIndexGPUncertaintyIterator.core_run()
SobolIndexGPUncertaintyIterator.evaluate_statistics()
SobolIndexGPUncertaintyIterator.post_run()
SobolIndexGPUncertaintyIterator.pre_run()
- queens.iterators.sobol_index_iterator module
SobolIndexIterator
SobolIndexIterator.seed
SobolIndexIterator.num_samples
SobolIndexIterator.calc_second_order
SobolIndexIterator.skip_values
SobolIndexIterator.num_bootstrap_samples
SobolIndexIterator.confidence_level
SobolIndexIterator.result_description
SobolIndexIterator.samples
SobolIndexIterator.output
SobolIndexIterator.salib_problem
SobolIndexIterator.num_params
SobolIndexIterator.parameter_names
SobolIndexIterator.sensitivity_indices
SobolIndexIterator.core_run()
SobolIndexIterator.get_all_samples()
SobolIndexIterator.plot_results()
SobolIndexIterator.post_run()
SobolIndexIterator.pre_run()
SobolIndexIterator.print_results()
SobolIndexIterator.process_results()
extract_parameters_of_parameter_distributions()
- queens.iterators.sobol_sequence_iterator module
- queens.iterators.variational_inference module
VariationalInferenceIterator
VariationalInferenceIterator.result_description
VariationalInferenceIterator.variational_params_initialization_approach
VariationalInferenceIterator.n_samples_per_iter
VariationalInferenceIterator.variational_transformation
VariationalInferenceIterator.natural_gradient_bool
VariationalInferenceIterator.fim_decay_start_iter
VariationalInferenceIterator.fim_dampening_coefficient
VariationalInferenceIterator.fim_dampening_lower_bound
VariationalInferenceIterator.fim_dampening_bool
VariationalInferenceIterator.random_seed
VariationalInferenceIterator.max_feval
VariationalInferenceIterator.num_parameters
VariationalInferenceIterator.stochastic_optimizer
VariationalInferenceIterator.variational_distribution
VariationalInferenceIterator.n_sims
VariationalInferenceIterator.variational_params
VariationalInferenceIterator.elbo
VariationalInferenceIterator.nan_in_gradient_counter
VariationalInferenceIterator.iteration_data
VariationalInferenceIterator.verbose_every_n_iter
VariationalInferenceIterator.core_run()
VariationalInferenceIterator.get_gradient_function()
VariationalInferenceIterator.handle_gradient_nan()
VariationalInferenceIterator.post_run()
VariationalInferenceIterator.pre_run()
- Subpackages
- queens.models package
- Subpackages
- queens.models.likelihood_models package
- queens.models.surrogate_models package
- Subpackages
- Submodules
- queens.models.surrogate_models.bayesian_neural_network module
- queens.models.surrogate_models.gaussian_neural_network module
- queens.models.surrogate_models.gp_approximation_gpflow module
- queens.models.surrogate_models.gp_approximation_gpflow_svgp module
- queens.models.surrogate_models.gp_approximation_jitted module
- queens.models.surrogate_models.gp_heteroskedastic_gpflow module
- queens.models.surrogate_models.surrogate_model module
- Submodules
- queens.models.bmfmc_model module
BMFMCModel
BMFMCModel.parameters
BMFMCModel.interface
BMFMCModel.features_config
BMFMCModel.X_cols
BMFMCModel.num_features
BMFMCModel.high_fidelity_model
BMFMCModel.X_train
BMFMCModel.Y_HF_train
BMFMCModel.Y_LFs_train
BMFMCModel.X_mc
BMFMCModel.Y_LFs_mc
BMFMCModel.Y_HF_mc
BMFMCModel.gammas_ext_mc
BMFMCModel.gammas_ext_train
BMFMCModel.Z_train
BMFMCModel.Z_mc
BMFMCModel.m_f_mc
BMFMCModel.var_y_mc
BMFMCModel.p_yhf_mean
BMFMCModel.p_yhf_var
BMFMCModel.predictive_var_bool
BMFMCModel.p_yhf_mc
BMFMCModel.p_ylf_mc
BMFMCModel.no_features_comparison_bool
BMFMCModel.eigenfunc_random_fields
BMFMCModel.eigenvals
BMFMCModel.f_mean_train
BMFMCModel.y_pdf_support
BMFMCModel.lf_data_iterators
BMFMCModel.hf_data_iterator
BMFMCModel.training_indices
BMFMCModel.uncertain_parameters
BMFMCModel.visualization
BMFMCModel.build_approximation()
BMFMCModel.calculate_extended_gammas()
BMFMCModel.calculate_p_yhf_mean()
BMFMCModel.calculate_p_yhf_var()
BMFMCModel.compute_pyhf_statistics()
BMFMCModel.compute_pymc_reference()
BMFMCModel.evaluate()
BMFMCModel.get_hf_training_data()
BMFMCModel.get_random_fields_and_truncated_basis()
BMFMCModel.grad()
BMFMCModel.input_dim_red()
BMFMCModel.load_sampling_data()
BMFMCModel.run_BMFMC()
BMFMCModel.run_BMFMC_without_features()
BMFMCModel.set_feature_strategy()
BMFMCModel.update_probabilistic_mapping_with_features()
BmfmcInterface
assemble_x_red_stdizd()
linear_scale_a_to_b()
project_samples_on_truncated_basis()
- queens.models.differentiable_simulation_model_adjoint module
- queens.models.differentiable_simulation_model_fd module
- queens.models.logpdf_gp_model module
LogpdfGPModel
LogpdfGPModel.approx_type
LogpdfGPModel.num_hyper
LogpdfGPModel.num_optimizations
LogpdfGPModel.hmc_burn_in
LogpdfGPModel.hmc_steps
LogpdfGPModel.prior_rate
LogpdfGPModel.prior_gp_mean
LogpdfGPModel.upper_bound
LogpdfGPModel.quantile
LogpdfGPModel.jitter
LogpdfGPModel.x_train
LogpdfGPModel.y_train
LogpdfGPModel.scaler_x
LogpdfGPModel.scaler_y
LogpdfGPModel.num_dim
LogpdfGPModel.hyperparameters
LogpdfGPModel.chol_k_train_train
LogpdfGPModel.v_train
LogpdfGPModel.jit_func_generate_output
LogpdfGPModel.partial_hyperparameter_log_prob
LogpdfGPModel.batch_size
LogpdfGPModel.calc_train_factor()
LogpdfGPModel.evaluate()
LogpdfGPModel.evaluate_mean_and_std()
LogpdfGPModel.generate_output_cfbgp()
LogpdfGPModel.generate_output_cgpmap_2()
LogpdfGPModel.generate_output_gpmap_1()
LogpdfGPModel.grad()
LogpdfGPModel.hyperparameter_log_likelihood()
LogpdfGPModel.hyperparameter_log_prior()
LogpdfGPModel.hyperparameter_log_prob()
LogpdfGPModel.initialize()
LogpdfGPModel.optimize_hyperparameters()
LogpdfGPModel.sample_hyperparameters()
distances()
rbf()
rbf_by_dists()
- queens.models.model module
- queens.models.simulation_model module
- Subpackages
- queens.parameters package
- Subpackages
- Submodules
- queens.parameters.parameters module
Parameters
Parameters.dict
Parameters.parameters_keys
Parameters.num_parameters
Parameters.random_field_flag
Parameters.names
Parameters.draw_samples()
Parameters.expand_random_field_realization()
Parameters.grad_joint_logpdf()
Parameters.inverse_cdf_transform()
Parameters.joint_logpdf()
Parameters.latent_grad()
Parameters.sample_as_dict()
Parameters.to_distribution_list()
Parameters.to_list()
from_config_create_parameters()
- queens.schedulers package
- queens.stochastic_optimizers package
- Submodules
- queens.stochastic_optimizers.adam module
- queens.stochastic_optimizers.adamax module
- queens.stochastic_optimizers.learning_rate_decay module
- queens.stochastic_optimizers.rms_prop module
- queens.stochastic_optimizers.sgd module
- queens.stochastic_optimizers.stochastic_optimizer module
StochasticOptimizer
StochasticOptimizer.learning_rate
StochasticOptimizer.clip_by_l2_norm_threshold
StochasticOptimizer.clip_by_value_threshold
StochasticOptimizer.max_iteration
StochasticOptimizer.precoefficient
StochasticOptimizer.rel_l1_change_threshold
StochasticOptimizer.rel_l2_change_threshold
StochasticOptimizer.iteration
StochasticOptimizer.done
StochasticOptimizer.rel_l2_change
StochasticOptimizer.rel_l1_change
StochasticOptimizer.current_variational_parameters
StochasticOptimizer.current_gradient_value
StochasticOptimizer.gradient
StochasticOptimizer.learning_rate_decay
StochasticOptimizer.clip_gradient()
StochasticOptimizer.do_single_iteration()
StochasticOptimizer.run_optimization()
StochasticOptimizer.scheme_specific_gradient()
StochasticOptimizer.set_gradient_function()
clip_by_l2_norm()
clip_by_value()
- queens.utils package
- Submodules
- queens.utils.ascii_art module
- queens.utils.classifier module
- queens.utils.cli_utils module
- queens.utils.collection_utils module
- queens.utils.config_directories module
- queens.utils.exceptions module
- queens.utils.experimental_data_reader module
- queens.utils.fcc_utils module
- queens.utils.fd_jacobian module
- queens.utils.gpf_utils module
- queens.utils.import_utils module
- queens.utils.injector module
- queens.utils.input_to_script module
QueensPythonCode
QueensPythonCode.imports
QueensPythonCode.run_iterator
QueensPythonCode.load_results
QueensPythonCode.global_settings_context
QueensPythonCode.code
QueensPythonCode.parameters
QueensPythonCode.global_settings
QueensPythonCode.extern_imports
QueensPythonCode.create_main
QueensPythonCode.create_code_section()
QueensPythonCode.generate_code()
QueensPythonCode.generate_script()
VariableName
assign_variable_value()
create_initialization_call()
create_initialization_call_from_class_and_arguments()
create_script_from_input_file()
dict_replace_infs()
from_config_create_fields_code()
from_config_create_parameters()
from_config_create_script()
get_module_class()
insert_new_obj()
list_replace_infs()
stringify()
- queens.utils.io_utils module
- queens.utils.iterative_averaging_utils module
- queens.utils.jax_minimize_wrapper module
- queens.utils.logger_settings module
- queens.utils.mcmc_utils module
- queens.utils.metadata module
- queens.utils.numpy_utils module
- queens.utils.path_utils module
- queens.utils.pdf_estimation module
- queens.utils.pickle_utils module
- queens.utils.plot_outputs module
- queens.utils.pool_utils module
- queens.utils.print_utils module
- queens.utils.process_outputs module
- queens.utils.pymc module
- queens.utils.random_process_scaler module
- queens.utils.remote_build module
- queens.utils.remote_operations module
RemoteConnection
RemoteConnection.remote_python
RemoteConnection.remote_queens_repository
RemoteConnection.build_remote_environment()
RemoteConnection.copy_to_remote()
RemoteConnection.create_remote_directory()
RemoteConnection.get_free_local_port()
RemoteConnection.get_free_remote_port()
RemoteConnection.open()
RemoteConnection.open_port_forwarding()
RemoteConnection.run_function()
RemoteConnection.start_cluster()
RemoteConnection.sync_remote_repository()
get_port()
- queens.utils.rsync module
- queens.utils.run_subprocess module
- queens.utils.smc_utils module
- queens.utils.sobol_sequence module
- queens.utils.start_dask_cluster module
- queens.utils.tensorflow_utils module
- queens.utils.valid_options_utils module
- queens.variational_distributions package
- Submodules
- queens.variational_distributions.full_rank_normal module
FullRankNormalVariational
FullRankNormalVariational.n_parameters
FullRankNormalVariational.conduct_reparameterization()
FullRankNormalVariational.construct_variational_parameters()
FullRankNormalVariational.draw()
FullRankNormalVariational.export_dict()
FullRankNormalVariational.fisher_information_matrix()
FullRankNormalVariational.grad_params_logpdf()
FullRankNormalVariational.grad_params_reparameterization()
FullRankNormalVariational.grad_sample_logpdf()
FullRankNormalVariational.initialize_variational_parameters()
FullRankNormalVariational.logpdf()
FullRankNormalVariational.pdf()
FullRankNormalVariational.reconstruct_distribution_parameters()
FullRankNormalVariational.total_grad_params_logpdf()
- queens.variational_distributions.joint module
JointVariational
JointVariational.distributions
JointVariational.n_parameters
JointVariational.distributions_n_parameters
JointVariational.distributions_dimension
JointVariational.construct_variational_parameters()
JointVariational.draw()
JointVariational.export_dict()
JointVariational.fisher_information_matrix()
JointVariational.grad_params_logpdf()
JointVariational.initialize_variational_parameters()
JointVariational.logpdf()
JointVariational.pdf()
JointVariational.reconstruct_distribution_parameters()
split_array_by_chunk_sizes()
- queens.variational_distributions.mean_field_normal module
MeanFieldNormalVariational
MeanFieldNormalVariational.n_parameters
MeanFieldNormalVariational.conduct_reparameterization()
MeanFieldNormalVariational.construct_variational_parameters()
MeanFieldNormalVariational.draw()
MeanFieldNormalVariational.export_dict()
MeanFieldNormalVariational.fisher_information_matrix()
MeanFieldNormalVariational.grad_params_logpdf()
MeanFieldNormalVariational.grad_params_reparameterization()
MeanFieldNormalVariational.grad_sample_logpdf()
MeanFieldNormalVariational.initialize_variational_parameters()
MeanFieldNormalVariational.logpdf()
MeanFieldNormalVariational.pdf()
MeanFieldNormalVariational.reconstruct_distribution_parameters()
MeanFieldNormalVariational.total_grad_params_logpdf()
- queens.variational_distributions.mixture_model module
MixtureModelVariational
MixtureModelVariational.n_components
MixtureModelVariational.base_distribution
MixtureModelVariational.n_parameters
MixtureModelVariational.construct_variational_parameters()
MixtureModelVariational.draw()
MixtureModelVariational.export_dict()
MixtureModelVariational.fisher_information_matrix()
MixtureModelVariational.grad_params_logpdf()
MixtureModelVariational.initialize_variational_parameters()
MixtureModelVariational.logpdf()
MixtureModelVariational.pdf()
MixtureModelVariational.reconstruct_distribution_parameters()
- queens.variational_distributions.particle module
ParticleVariational
ParticleVariational.particles_obj
ParticleVariational.dimension
ParticleVariational.construct_variational_parameters()
ParticleVariational.draw()
ParticleVariational.export_dict()
ParticleVariational.fisher_information_matrix()
ParticleVariational.grad_params_logpdf()
ParticleVariational.initialize_variational_parameters()
ParticleVariational.logpdf()
ParticleVariational.pdf()
ParticleVariational.reconstruct_distribution_parameters()
- queens.variational_distributions.variational_distribution module
VariationalDistribution
VariationalDistribution.dimension
VariationalDistribution.draw()
VariationalDistribution.export_dict()
VariationalDistribution.fisher_information_matrix()
VariationalDistribution.grad_params_logpdf()
VariationalDistribution.initialize_variational_parameters()
VariationalDistribution.logpdf()
VariationalDistribution.pdf()
VariationalDistribution.reconstruct_distribution_parameters()
- queens.visualization package
- Submodules
- queens.visualization.bmfia_visualization module
- queens.visualization.bmfmc_visualization module
BMFMCVisualization
BMFMCVisualization.paths
BMFMCVisualization.save_bools
BMFMCVisualization.animation_bool
BMFMCVisualization.predictive_var
BMFMCVisualization.no_features_ref
BMFMCVisualization.plot_booleans
BMFMCVisualization.from_config_create()
BMFMCVisualization.plot_feature_ranking()
BMFMCVisualization.plot_manifold()
BMFMCVisualization.plot_pdfs()
- queens.visualization.classification module
- queens.visualization.gaussian_neural_network_vis module
- queens.visualization.gnuplot_vis module
- queens.visualization.grid_iterator_visualization module
GridIteratorVisualization
GridIteratorVisualization.saving_paths_list
GridIteratorVisualization.save_bools
GridIteratorVisualization.plot_booleans
GridIteratorVisualization.scale_types_list
GridIteratorVisualization.var_names_list
GridIteratorVisualization.from_config_create()
GridIteratorVisualization.get_plotter()
GridIteratorVisualization.plot_one_d()
GridIteratorVisualization.plot_qoi_grid()
GridIteratorVisualization.plot_two_d()
- queens.visualization.sa_visualization module
- queens.visualization.surrogate_visualization module
SurrogateVisualization
SurrogateVisualization.saving_paths
SurrogateVisualization.should_be_saved
SurrogateVisualization.should_be_displayed
SurrogateVisualization.parameter_names
SurrogateVisualization.figures
SurrogateVisualization.from_config_create()
SurrogateVisualization.plot()
SurrogateVisualization.plot_1d()
SurrogateVisualization.plot_2d()
SurrogateVisualization.plot_gp_from_gpflow()
convert_to_dict()
- queens.visualization.variational_inference_visualization module
Submodules#
queens.global_settings module#
Global Settings.
This module provides a context for QUEENS runs with exit functionality for logging and working with remote resources.
- class GlobalSettings(experiment_name, output_dir, debug=False)[source]#
Bases:
object
Class for global settings in Queens.
- experiment_name#
Experiment name of queens run
- Type:
str
- output_dir#
Output directory for queens run
- Type:
Path
- git_hash#
Hash of active git commit
- Type:
str
- debug#
True if debug mode is to be used
- Type:
bool
- result_file(extension: str, suffix: str = None) Path [source]#
Create path to a result file with a given extension.
- Parameters:
extension (str) – The extension of the file.
suffix (str, optional) – The suffix to be appended to the experiment_name i.e. the default stem of the filename.
- Returns:
Path – Path of the file.
queens.main module#
QUEENS main.
Main module of QUEENS containing the high-level control routine for input file workflow.
- run(input_file, output_dir, debug=False)[source]#
Do a QUEENS run.
- Parameters:
input_file (Path) – Path object to the input file
output_dir (Path) – Path object to the output directory
debug (bool) – True if debug mode is to be used
- run_iterator(iterator, global_settings)[source]#
Run the main queens iterator.
- Parameters:
iterator (Iterator) – Main queens iterator
global_settings (GlobalSettings) – settings of the QUEENS experiment including its name and the output directory