Index _ | A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | R | S | T | U | V | W | X | Y _ _check_convergence_parallel() (run.Runner method) _construct_convergence_criterion() (run.Runner method) _construct_gp_acquisition() (run.Runner method) _construct_gpr() (run.Runner method) _construct_initial_proposer() (run.Runner method) _construct_mc_options() (run.Runner method) _diff_threshold_if_keep_n_finite() (gpr.GaussianProcessRegressor static method) _eval_truth_parallel() (run.Runner method) _get_new_mean_and_cov_from_acquisition() (convergence.GaussianKL method) _kernel_inverse() (gpr.GaussianProcessRegressor method) _share_convergence_from_main() (run.Runner method) _share_gpr() (run.Runner method) _update_model() (gpr.GaussianProcessRegressor method) _update_noise_level() (gpr.GaussianProcessRegressor method) _validate_noise_level() (gpr.GaussianProcessRegressor method) A abs_finite_threshold (gpr.GaussianProcessRegressor property) abs_threshold (svm.SVM property) add() (gp_acquisition.RankedPool method) add_acquisition() (progress.Progress method) add_bulk() (gp_acquisition.RankedPool method) add_convergence() (progress.Progress method) add_current_n_truth() (progress.Progress method) add_fit() (progress.Progress method) add_iteration() (progress.Progress method) add_one() (gp_acquisition.RankedPool method) add_truth() (progress.Progress method) allgather() (in module mpi) anisotropic (kernels.ExpSineSquared property) (kernels.RationalQuadratic property) append_to_data() (gpr.GaussianProcessRegressor method) B banner() (run.Runner method), [1] BatchOptimizer (class in gp_acquisition) bcast() (in module mpi) bcast_last_max() (progress.Progress method) bcast_root() (progress.Progress method) bcast_sum() (progress.Progress method) bounds (kernels.Kernel property) builtin_names() (in module gp_acquisition) C cache_model() (gp_acquisition.RankedPool method) CentroidsProposer (class in proposal) check_and_return_bounds() (in module tools) check_candidates() (in module tools) check_checkpoint() (in module gpry.io) check_in_bounds() (in module proposal) check_random_state() (in module tools) cobaya_generate_gp_model_input() (in module mc) CobayaWrapper (class in gpry.cobaya) compute_mean_cov() (preprocessing.Whitening static method) compute_threshold_given_sigma() (gpr.GaussianProcessRegressor static method) compute_y_parallel() (in module mpi) ConstantKernel (class in kernels) convergence module convergence_policy (convergence.ConvergenceCriterion property) convergence_policy_MPI (convergence.ConvergenceCriterion property) ConvergenceCheckError ConvergenceCriterion (class in convergence) copy() (gp_acquisition.RankedPool method) CorrectCounter (class in convergence) create_path() (in module gpry.io) credibility_of_nstd() (in module tools) criterion_value() (convergence.ConvergenceCriterion method) (convergence.CorrectCounter method) (convergence.DontConverge method) (convergence.GaussianKL method) (convergence.GaussianKLTrain method) (convergence.TrainAlignment method) D d (gpr.GaussianProcessRegressor property) (proposal.CentroidsProposer property) (run.Runner property), [1] (svm.SVM property) delta_logp_of_1d_nstd() (in module tools) diagnose_last_mc_sample() (run.Runner method), [1] do_initial_training() (run.Runner method), [1] do_MC_sample() (gp_acquisition.NORA method) do_plots() (gpry.cobaya.CobayaWrapper method) do_surrogate_sample() (gpry.cobaya.CobayaWrapper method) DontConverge (class in convergence) DotProduct (class in kernels) DummyPreprocessor (class in preprocessing) E ensure_gpr() (in module gpry.io) ensure_paths() (run.Runner method), [1] Exponentiation (class in kernels) ExpSineSquared (class in kernels) F fit() (preprocessing.DummyPreprocessor class method) (preprocessing.Normalize_bounds method) (preprocessing.Normalize_y method) (preprocessing.NormalizeChi2_y method) (preprocessing.Pipeline_X method) (preprocessing.Pipeline_y method) (preprocessing.Whitening method) (svm.SVM method) fit_gpr_hyperparameters() (gpr.GaussianProcessRegressor method) fitted (gpr.GaussianProcessRegressor property) (preprocessing.Normalize_y property) G gather() (in module mpi) gaussian_distance() (in module tools) GaussianKL (class in convergence) GaussianKLTrain (class in convergence) GaussianProcessRegressor (class in gpr) generate_mc_sample() (run.Runner method), [1] generic_params_names() (in module tools) GenericGPAcquisition (class in gp_acquisition) get() (proposal.CentroidsProposer method) (proposal.MeanAutoCovProposer method) (proposal.MeanCovProposer method) (proposal.PartialProposer method) (proposal.PriorProposer method) (proposal.Proposer method) (proposal.ReferenceProposer method) (proposal.SmallChainProposer method) (proposal.UniformProposer method) get_checkpoint_dir_and_surr_prefix() (gpry.cobaya.CobayaWrapper class method) get_cobaya_log_level() (in module mc) get_history() (convergence.ConvergenceCriterion method) get_random_generator() (in module mpi) get_Xnumber() (in module tools) getdist_add_training() (in module plots) gp_acquisition module gpr module gpry.io module gradient_x() (kernels.ConstantKernel method) (kernels.DotProduct method) (kernels.Exponentiation method) (kernels.ExpSineSquared method) (kernels.Kernel method) (kernels.Matern method) (kernels.Product method) (kernels.RationalQuadratic method) (kernels.RBF method) (kernels.Sum method) (kernels.WhiteKernel method) H help_column_names() (progress.Progress method) Hyperparameter (class in kernels) hyperparameter_alpha (kernels.RationalQuadratic property) hyperparameter_constant_value (kernels.ConstantKernel property) hyperparameter_length_scale (kernels.ExpSineSquared property) (kernels.Matern property) (kernels.RationalQuadratic property) (kernels.RBF property) hyperparameter_noise_level (kernels.WhiteKernel property) hyperparameter_periodicity (kernels.ExpSineSquared property) hyperparameter_sigma_0 (kernels.DotProduct property) hyperparameters (kernels.Exponentiation property) (kernels.Kernel property) (kernels.KernelOperator property) (kernels.Product property) (kernels.Sum property) I initialize() (gpry.cobaya.CobayaWrapper method) InitialPointProposer (class in proposal) inverse_transform() (preprocessing.DummyPreprocessor class method) (preprocessing.Normalize_bounds method) (preprocessing.Normalize_y method) (preprocessing.Pipeline_X method) (preprocessing.Pipeline_y method) (preprocessing.Whitening method) inverse_transform_scale() (preprocessing.DummyPreprocessor class method) (preprocessing.Normalize_bounds method) (preprocessing.Normalize_y method) (preprocessing.Pipeline_X method) (preprocessing.Pipeline_y method) is_converged() (convergence.ConvergenceCriterion method) (convergence.CorrectCounter method) (convergence.DontConverge method) (convergence.GaussianKL method) is_converged_MPIwrapped() (convergence.ConvergenceCriterion method) is_finite() (gpr.GaussianProcessRegressor method) (svm.SVM method) is_in_bounds() (in module tools) is_linear (preprocessing.DummyPreprocessor attribute) (preprocessing.Normalize_y property) is_mc_sampled (gpry.cobaya.CobayaWrapper property) is_MPI_aware (convergence.ConvergenceCriterion property) (convergence.GaussianKL property) is_nora() (gpry.cobaya.CobayaWrapper static method) is_valid_covmat() (in module tools) K Kernel (class in kernels) KernelOperator (class in kernels) kernels module kl_mc() (in module tools) kl_norm() (in module tools) L labels (run.Runner property), [1] last_appended (gpr.GaussianProcessRegressor property) last_appended_finite (gpr.GaussianProcessRegressor property) last_MC_sample() (gp_acquisition.NORA method) last_MC_sample_getdist() (gp_acquisition.NORA method) last_mc_samples() (run.Runner method), [1] last_value (convergence.ConvergenceCriterion property) limit (convergence.CorrectCounter property) log() (gp_acquisition.NORA method) (gp_acquisition.RankedPool method) (run.Runner method), [1] log_marginal_likelihood() (gpr.GaussianProcessRegressor method) log_pool() (gp_acquisition.RankedPool method) logL() (run.Runner method), [1] logL_truth() (run.Runner method), [1] logp() (run.Runner method), [1] logp_truth() (run.Runner method), [1] logpost_eval_and_report() (run.Runner method), [1] logprior() (run.Runner method), [1] M Matern (class in kernels) mc module mc_sample_from_gp_cobaya() (in module mc) mc_sample_from_gp_ns() (in module mc) mcmc_info_from_run() (in module mc) mean_covmat_from_evals() (in module tools) mean_covmat_from_samples() (in module tools) MeanAutoCovProposer (class in proposal) MeanCovProposer (class in proposal) merge_step_split() (in module mpi) min_acq (gp_acquisition.RankedPool property) module convergence gp_acquisition gpr gpry.io kernels mc mpi plots preprocessing progress proposal run svm tools mpi module mpi_sync() (progress.Progress method) multi_add() (gp_acquisition.BatchOptimizer method) (gp_acquisition.GenericGPAcquisition method) (gp_acquisition.NORA method) multi_gather_array() (in module mpi) N n (gpr.GaussianProcessRegressor property) (svm.SVM property) n_finite (gpr.GaussianProcessRegressor property) n_finite_left (run.Runner property), [1] n_total (gpr.GaussianProcessRegressor property) n_total_left (run.Runner property), [1] NORA (class in gp_acquisition) Normalize_bounds (class in preprocessing) Normalize_y (class in preprocessing) NormalizeChi2_y (class in preprocessing) nstd_of_1d_nstd() (in module tools) NumpyErrorHandling (class in tools) O optimize_acquisition_function() (gp_acquisition.BatchOptimizer method) output_files_regexps() (gpry.cobaya.CobayaWrapper class method) P param_samples_for_slices() (in module plots) params (run.Runner property), [1] PartialProposer (class in proposal) Pipeline_X (class in preprocessing) Pipeline_y (class in preprocessing) plot_convergence() (in module plots) plot_corner_getdist() (in module plots) plot_distance_distribution() (in module plots) (run.Runner method), [1] plot_mc() (run.Runner method), [1] plot_progress() (run.Runner method), [1] plot_slices() (in module plots) plot_slices_func() (in module plots) plot_slices_reference() (in module plots) plot_timing() (progress.Progress method) plot_trace() (in module plots) plots module polychord_info_from_run() (in module mc) pool_size (gp_acquisition.NORA property) predict() (gpr.GaussianProcessRegressor method) (svm.SVM method) predict_is_finite() (gpr.GaussianProcessRegressor method) predict_std() (gpr.GaussianProcessRegressor method) prepare_slices_func() (in module plots) prepare_transform() (preprocessing.Whitening static method) preprocessing module PriorProposer (class in proposal) process_gdsamples() (in module mc) Product (class in kernels) products() (gpry.cobaya.CobayaWrapper method) progress module Progress (class in progress) proposal module Proposer (class in proposal) R RankedPool (class in gp_acquisition) RationalQuadratic (class in kernels) RBF (class in kernels) read_checkpoint() (in module gpry.io) (run.Runner method), [1] ReferenceProposer (class in proposal) remove_0_weight_samples() (in module tools) remove_from_data() (gpr.GaussianProcessRegressor method) resample() (proposal.SmallChainProposer method) reset_cache() (gp_acquisition.RankedPool method) run module run() (gpry.cobaya.CobayaWrapper method) (run.Runner method), [1] Runner (class in run), [1] S samples() (gpry.cobaya.CobayaWrapper method) samples_dict_to_getdist() (in module mc) save_checkpoint() (in module gpry.io) (run.Runner method), [1] scales (gpr.GaussianProcessRegressor property) set_fiducial_MC() (run.Runner method), [1] set_fiducial_point() (run.Runner method), [1] set_fit_request() (svm.SVM method) set_predict_request() (gpr.GaussianProcessRegressor method) (svm.SVM method) set_random_state() (gpr.GaussianProcessRegressor method) set_score_request() (gpr.GaussianProcessRegressor method) (svm.SVM method) share_attr() (in module mpi) shrink_bounds() (in module tools) simple_latex_sci_notation() (in module plots) SmallChainProposer (class in proposal) sort() (gp_acquisition.RankedPool method) split_number_for_parallel_processes() (in module mpi) step_split() (in module mpi) str_point() (gp_acquisition.RankedPool method) str_pool() (gp_acquisition.RankedPool method) Sum (class in kernels) svm module SVM (class in svm) sync_processes() (in module mpi) T Timer (class in progress) TimerCounter (class in progress) tools module TrainAlignment (class in convergence) training_set_as_df() (gpr.GaussianProcessRegressor method) transform() (preprocessing.DummyPreprocessor class method) (preprocessing.Normalize_bounds method) (preprocessing.Normalize_y method) (preprocessing.Pipeline_X method) (preprocessing.Pipeline_y method) (preprocessing.Whitening method) transform_bounds() (preprocessing.DummyPreprocessor class method) (preprocessing.Normalize_bounds method) (preprocessing.Pipeline_X method) (preprocessing.Whitening method) transform_scale() (preprocessing.DummyPreprocessor class method) (preprocessing.Normalize_y method) (preprocessing.Pipeline_X method) (preprocessing.Pipeline_y method) U UniformProposer (class in proposal) update() (proposal.CentroidsProposer method) (proposal.PartialProposer method) (proposal.Proposer method) (proposal.SmallChainProposer method) update_bounds() (preprocessing.Normalize_bounds method) (proposal.CentroidsProposer method) (proposal.PartialProposer method) (proposal.Proposer method) (proposal.SmallChainProposer method) (proposal.UniformProposer method) update_mean_cov() (run.Runner method), [1] update_NS_precision() (gp_acquisition.NORA method) update_trust_region() (gpr.GaussianProcessRegressor method) V volume_sphere() (in module tools) W WhiteKernel (class in kernels) Whitening (class in preprocessing) wrap_likelihood() (in module tools) X X_train_infinite (gpr.GaussianProcessRegressor property) Y y_max (gpr.GaussianProcessRegressor property) y_train_infinite (gpr.GaussianProcessRegressor property)
