Index A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y A abs_() (in module prophys.symbolic) accepted (prophys.engine.AmortizationCard attribute) act (prophys.nn.DPOTNet attribute) Activation (class in prophys.nn.layers) ACTIVATIONS (in module prophys.nn.layers) ad (prophys.engine.CalibrationReport attribute) Affine (class in prophys.transformations) aic (prophys.engine.InformationCriteria attribute) aicc (prophys.engine.InformationCriteria attribute) align() (prophys.frames.FrameRegistry method) alloc() (prophys.nn.layers.Builder method) alpha (prophys.engine.TailRiskEstimate attribute) (prophys.nn.LinearPosterior attribute) AmortizationCard (class in prophys.engine) amortize() (in module prophys) answer() (prophys.engine.OperationalSurrogate method) apply() (prophys.frames.FrameTransform method) (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) arctan2() (in module prophys.symbolic) area() (prophys.structures.Ellipse method) (prophys.structures.EllipseList method) (prophys.structures.Mesh method) (prophys.structures.Polygon method) as_function() (in module prophys.explain) as_lines() (prophys.structures.Network method) (prophys.structures.Polyline method) as_observations() (in module prophys.domain) assess() (in module prophys.engine) (prophys.engine.CompiledModel method) attribute (prophys.engine.AmortizationCard attribute) (prophys.engine.CalibrationReport attribute) (prophys.engine.CrpsScore attribute) (prophys.engine.EstimateWithError attribute) (prophys.engine.LocalSensitivity attribute) (prophys.engine.OperationalSurrogate attribute) (prophys.engine.PosteriorPredictiveCheck attribute) (prophys.engine.SobolSensitivity attribute) (prophys.engine.TailRiskEstimate attribute) (prophys.explain.SystemShapley attribute) attribute() (prophys.domain.ProbabilityModel method) (prophys.export.ModelPackage method) AttributeExport (class in prophys.export) AttributeInteractions (class in prophys.domain) attributes (prophys.export.ModelPackage attribute) audit_rate (prophys.engine.OperationalSurrogate attribute) audits (prophys.engine.OperationalSurrogate attribute) autocorrelation_time (prophys.engine.EstimateWithError attribute) Autoregressive (class in prophys) average_distance() (prophys.structures.PointList method) B BarDistribution (class in prophys.nn) base (prophys.explain.ShapValues attribute) batch_inputs() (prophys.nn.SurrogateCall method) Bernoulli (class in prophys.distributions) best_step (prophys.nn.PretrainResult attribute) Beta (class in prophys.distributions) beta (prophys.nn.LinearPosterior attribute) beta_nll() (in module prophys.nn.losses) bias (prophys.engine.CalibrationReport property) bic (prophys.engine.InformationCriteria attribute) BinaryState (class in prophys.symbolic) BLOB_MAGIC (in module prophys.export.surrogate) borders (prophys.export.surrogate.SurrogateExport attribute) Bounded (class in prophys.nn.layers) box (prophys.engine.OperationalSurrogate attribute) break_even() (in module prophys) (prophys.engine.OperationalSurrogate method) break_even_queries (prophys.engine.BreakEvenEstimate attribute) BreakEvenEstimate (class in prophys.engine) build_manifest() (in module prophys.export) Builder (class in prophys.nn.layers) C calibrate() (in module prophys.engine) calibration() (in module prophys.engine) (in module prophys.plot) CalibrationReport (class in prophys.engine) CalibrationResult (class in prophys.engine) card (prophys.engine.OperationalSurrogate attribute) (prophys.export.surrogate.SurrogateExport attribute) Categorical (class in prophys.distributions) CategoricalState (class in prophys.symbolic) cdf() (prophys.distributions.Distribution method) (prophys.distributions.Exponential method) (prophys.distributions.Gaussian method) (prophys.distributions.Gumbel method) (prophys.distributions.LogNormal method) (prophys.distributions.Mixture method) (prophys.distributions.Uniform method) (prophys.distributions.Weibull method) (prophys.engine.CompiledModel method) cdf_to_probs() (in module prophys.nn.losses) censored (prophys.io.tabular.Column attribute) CENSORED_PREFIXES (in module prophys.io.tabular) center (prophys.nn.SupportRegion attribute) centroid() (prophys.structures.PointList method) (prophys.structures.Polygon method) check() (prophys.frames.Frame method) (prophys.nn.DPOTNet method) check_compatible() (in module prophys.units) check_identifiability() (in module prophys.engine) checksum (prophys.export.surrogate.SurrogateExport attribute) Choice (class in prophys.nn.layers) Circular (class in prophys) circular_autoregressive() (in module prophys) clip() (in module prophys.symbolic) closest_distance() (prophys.structures.EllipseList method) (prophys.structures.LineList method) (prophys.structures.PointList method) (prophys.structures.PolygonList method) (prophys.structures.PolyhedronList method) (prophys.structures.RayList method) closest_point() (prophys.structures.PointList method) CODES (in module prophys.diagnostics) codes (prophys.diagnostics.ProphysError property) codes() (prophys.diagnostics.Diagnostics method) collinear_pairs() (prophys.engine.ParameterUncertainty method) Column (class in prophys.io.tabular) compare() (in module prophys.engine) compatible() (in module prophys.units) compile() (prophys.domain.ProbabilityModel method) compile_model() (in module prophys.engine) compile_reason() (prophys.nn.layers.Physics method) compiled (prophys.engine.OperationalSurrogate attribute) CompiledModel (class in prophys.engine) component() (prophys.domain.JointRandomVariable method) compound_distribution() (in module prophys.physics) concatenate() (in module prophys.symbolic) conditional_expectation() (prophys.engine.CompiledModel method) confidence_interval() (in module prophys.engine) Const (class in prophys.symbolic) constant() (prophys.nn.Surrogate method) constrained_params() (prophys.engine.CompiledModel method) contains() (prophys.structures.Ellipse method) (prophys.structures.Polygon method) (prophys.structures.Polyhedron method) converged (prophys.engine.CalibrationResult property) (prophys.inference.PosteriorSummary property) (prophys.nn.PretrainResult attribute) convergence() (in module prophys.diagnostics) conversion_factor() (in module prophys.units) convert() (in module prophys.units) (prophys.domain.UncertainAttribute method) convex_preserving (prophys.nn.layers.Layer attribute) corr_cholesky_from_raw() (in module prophys.distributions) correlated_uniforms() (in module prophys.distributions) Correlation (class in prophys.distributions) correlation (prophys.engine.ParameterUncertainty attribute) (prophys.export.ModelPackage attribute) correlation_between() (prophys.engine.ParameterUncertainty method) cos() (in module prophys.symbolic) count_within() (prophys.structures.PointList method) counts() (prophys.domain.Observations method) covariance (prophys.engine.DerivedUncertainty attribute) (prophys.engine.ParameterUncertainty attribute) coverage (prophys.engine.AmortizationCard attribute) (prophys.nn.PretrainResult attribute) coverage90 (prophys.nn.PretrainResult attribute) created (prophys.nn.PretrainResult attribute) created_utc (prophys.export.RunManifest attribute) credible_interval() (prophys.inference.PosteriorSummary method) criterion (prophys.engine.ModelComparison attribute) (prophys.engine.PredictiveScore attribute) cross_entropy() (in module prophys.nn.losses) CrossAttention (class in prophys.nn.layers) crps (prophys.engine.AmortizationCard attribute) (prophys.nn.PretrainResult attribute) crps() (in module prophys.engine) crps_ensemble() (in module prophys.nn.losses) crps_floor (prophys.engine.AmortizationCard attribute) crps_gaussian() (in module prophys.nn.losses) crps_mixture() (in module prophys.nn.losses) CrpsScore (class in prophys.engine) cvar (prophys.engine.TailRiskEstimate attribute) cvar() (prophys.engine.CompiledModel method) cvar_error() (in module prophys.engine) cvm (prophys.engine.CalibrationReport attribute) D d() (prophys.nn.Derivatives method) data_hash (prophys.engine.AmortizationCard attribute) (prophys.nn.PretrainResult attribute) data_init() (prophys.nn.TreeEnsemble method) data_seconds (prophys.engine.AmortizationCard attribute) (prophys.engine.BreakEvenEstimate attribute) dd() (prophys.nn.Derivatives method) Decay (class in prophys.transformations) default_params() (prophys.engine.CompiledModel method) default_values() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) deg2rad() (in module prophys.symbolic) delta (prophys.engine.ModelComparison attribute) delta_se (prophys.engine.ModelComparison attribute) Dense (class in prophys.nn.layers) depth (prophys.nn.DPOTNet attribute) Derivatives (class in prophys.nn) derivatives() (prophys.nn.Surrogate method) DerivedUncertainty (class in prophys.engine) describe() (in module prophys.units) description (prophys.export.surrogate.SurrogateExport attribute) detection_limit() (prophys.domain.Observations class method) deviance (prophys.engine.PredictiveScore attribute) Diagnostic (class in prophys.diagnostics) Diagnostics (class in prophys.diagnostics) diagnostics (prophys.engine.CalibrationResult attribute) (prophys.export.ModelPackage attribute) (prophys.export.RunManifest attribute) (prophys.nn.PretrainResult attribute) Dimension (class in prophys.units) DIMENSIONLESS (in module prophys.units) directional_mixture() (in module prophys.io.tabular) directional_sweep() (in module prophys.physics) DirectionalMixture (class in prophys.distributions) disagreement (prophys.engine.Guard attribute) disagreement_threshold (prophys.engine.AmortizationCard attribute) discounted_sum() (in module prophys) dispersion (prophys.engine.CalibrationReport property) distance() (prophys.nn.SupportRegion method) (prophys.structures.Ellipse method) (prophys.structures.Polygon method) distance_matrix() (prophys.structures.LineList method) (prophys.structures.RayList method) Distribution (class in prophys.distributions) distribution() (in module prophys.plot) (prophys.engine.OperationalSurrogate method) (prophys.export.surrogate.SurrogateExport method) (prophys.nn.FieldSurrogate method) (prophys.nn.Surrogate method) divergences (prophys.inference.PosteriorSummary attribute) domain (prophys.export.AttributeExport attribute) dot() (in module prophys.symbolic) DPOT() (in module prophys.nn) dpot_config() (in module prophys.nn) dpot_state() (in module prophys.nn) dpot_tokens() (in module prophys.nn) DPOTNet (class in prophys.nn) DPOTSurrogate (class in prophys.nn) draws (prophys.inference.Posterior attribute) E edge_lengths() (prophys.structures.Network method) edges (prophys.export.AttributeExport attribute) effective_query_seconds (prophys.engine.BreakEvenEstimate attribute) effective_sample_size (prophys.engine.EstimateWithError attribute) elasticities (prophys.engine.LocalSensitivity attribute) Ellipse (class in prophys.structures) EllipseList (class in prophys.structures) elpd (prophys.engine.ModelComparison attribute) (prophys.engine.PredictiveScore attribute) elpd_se (prophys.engine.PredictiveScore attribute) embed_dim (prophys.nn.DPOTNet attribute) emit() (in module prophys.diagnostics) (prophys.nn.DPOTNet method) (prophys.nn.layers.Activation method) (prophys.nn.layers.Bounded method) (prophys.nn.layers.Choice method) (prophys.nn.layers.CrossAttention method) (prophys.nn.layers.Dense method) (prophys.nn.layers.Fourier method) (prophys.nn.layers.GaussianHead method) (prophys.nn.layers.HistogramHead method) (prophys.nn.layers.InputConvex method) (prophys.nn.layers.Layer method) (prophys.nn.layers.LayerNorm method) (prophys.nn.layers.Lipschitz method) (prophys.nn.layers.MixtureHead method) (prophys.nn.layers.Monotone method) (prophys.nn.layers.Physics method) (prophys.nn.layers.PoolAttention method) (prophys.nn.layers.PoolMean method) (prophys.nn.layers.PrefixAttention method) (prophys.nn.layers.QuantileHead method) (prophys.nn.layers.Reshape method) (prophys.nn.layers.Residual method) (prophys.nn.layers.RFF method) (prophys.nn.layers.SelfAttention method) (prophys.nn.layers.SetBlock method) (prophys.nn.layers.SliceAttention method) (prophys.nn.layers.TransolverBlock method) Empirical (class in prophys.distributions) empirical_from_column() (in module prophys.io.tabular) empty (prophys.explain.SystemShapley attribute) energy_score() (in module prophys.nn.losses) epistemic() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) erf() (in module prophys.symbolic) erfc() (in module prophys.symbolic) erfcx() (in module prophys.symbolic) error() (in module prophys.diagnostics) errors (prophys.diagnostics.Diagnostics property) ess (prophys.inference.PosteriorSummary attribute) estimate (prophys.engine.ProfileLikelihood attribute) estimates (prophys.engine.ParameterUncertainty attribute) EstimateWithError (class in prophys.engine) evaluate() (prophys.export.surrogate.SurrogateExport method) (prophys.symbolic.Expr method) evenly_spaced() (prophys.distributions.DirectionalMixture class method) exact() (prophys.domain.Observations class method) exp() (in module prophys.symbolic) exp1() (in module prophys.symbolic) expectation() (prophys.engine.CompiledModel method) expected_gradients() (in module prophys.explain) Exponential (class in prophys.distributions) export() (prophys.engine.CompiledModel method) (prophys.engine.OperationalSurrogate method) export_model() (in module prophys.export) export_surrogate() (in module prophys.export.surrogate) Expr (class in prophys.symbolic) extra (prophys.inference.Posterior attribute) F fail() (prophys.nn.layers.Builder method) fallback_rate (prophys.engine.BreakEvenEstimate attribute) (prophys.engine.OperationalSurrogate property) FALLBACK_REASONS (in module prophys.engine) fallback_summary() (prophys.engine.OperationalSurrogate method) family (prophys.nn.PriorTask attribute) farthest_distance() (prophys.structures.PointList method) farthest_point() (prophys.structures.PointList method) fatigue_damage() (in module prophys.physics) features() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) Field (class in prophys.structures) field() (in module prophys.plot) Field3D (class in prophys.structures) field_tokens() (in module prophys.nn) fields() (prophys.engine.Report method) (prophys.nn.DPOTSurrogate method) FieldSurrogate (class in prophys.nn) final_loss (prophys.engine.CalibrationResult attribute) final_objective (prophys.engine.OptimizationResult attribute) find_random_variables() (in module prophys.domain) find_surrogates() (in module prophys.nn) finetune() (in module prophys.engine) finite_difference_check() (in module prophys.engine) first_order (prophys.engine.SobolSensitivity attribute) fit() (prophys.nn.InContextRegressor method) fit_distribution() (in module prophys.engine) fit_linear_posterior() (in module prophys.nn) fit_support() (in module prophys.nn) fn (prophys.nn.PhysicsResidual attribute) fnv1a64() (in module prophys.export.surrogate) FORMAT_VERSION (in module prophys.export) format_version (prophys.export.ModelPackage attribute) forward() (prophys.symbolic.Param method) Fourier (class in prophys.nn.layers) Frame (class in prophys.frames) FrameError FrameRegistry (class in prophys.frames) FrameTransform (class in prophys.frames) free_tier_limit() (in module prophys) from_arrays() (prophys.domain.Observations class method) from_bytes() (prophys.export.surrogate.SurrogateExport class method) from_dict() (prophys.export.surrogate.SurrogateExport class method) (prophys.nn.LinearPosterior class method) (prophys.nn.SupportRegion class method) from_dpot() (in module prophys.nn) from_lightgbm() (prophys.nn.TreeEnsemble class method) from_xgboost() (prophys.nn.TreeEnsemble class method) full() (prophys.engine.OperationalSurrogate method) full_query_seconds (prophys.engine.AmortizationCard attribute) (prophys.engine.BreakEvenEstimate attribute) FunctionTransform (class in prophys.transformations) G Gamma (class in prophys.distributions) Gaussian (class in prophys.distributions) gaussian_nll() (in module prophys.nn.losses) gaussian_polygon_probability() (in module prophys.physics) GaussianCopula (class in prophys.distributions) GaussianHead (class in prophys.nn.layers) Geometry (class in prophys) geometry_tokens() (in module prophys.nn) get() (prophys.frames.FrameRegistry method) glorot() (prophys.nn.layers.Builder method) gradient() (prophys.structures.Field method) gradients (prophys.engine.LocalSensitivity attribute) graph() (in module prophys.plot) Grid (class in prophys.structures) grid (prophys.engine.ProfileLikelihood attribute) (prophys.export.AttributeExport attribute) (prophys.nn.DPOTNet attribute) Grid3 (class in prophys.structures) Guard (class in prophys.engine) guard() (prophys.engine.OperationalSurrogate method) Gumbel (class in prophys.distributions) H head (prophys.export.surrogate.SurrogateExport attribute) HEAD_CODES (in module prophys.export.surrogate) head_matrix() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) head_names() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) head_params (prophys.export.surrogate.SurrogateExport attribute) hi (prophys.nn.SupportRegion attribute) Histogram (class in prophys.distributions) histogram (prophys.engine.CalibrationReport attribute) HistogramHead (class in prophys.nn.layers) history (prophys.nn.PretrainResult attribute) hl_gauss_probs() (in module prophys.nn.losses) I i0e() (in module prophys.symbolic) i1e() (in module prophys.symbolic) importance() (prophys.explain.ShapValues method) in_channels (prophys.nn.DPOTNet attribute) in_strength() (prophys.structures.Network method) in_support (prophys.engine.Guard attribute) in_support() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) in_timesteps (prophys.nn.DPOTNet attribute) InContextRegressor (class in prophys.nn) Independent (class in prophys.distributions) info() (in module prophys.diagnostics) information_criteria() (in module prophys.engine) InformationCriteria (class in prophys.engine) innovations() (prophys.Autoregressive method) Input (class in prophys.symbolic) input() (prophys.nn.Derivatives method) input_units (prophys.export.surrogate.SurrogateExport attribute) InputConvex (class in prophys.nn.layers) inputs (prophys.engine.AmortizationCard attribute) (prophys.export.surrogate.SurrogateExport attribute) inputs() (prophys.symbolic.Expr method) integral() (prophys.structures.Mesh method) integrated_gradients() (in module prophys.explain) interactions (prophys.engine.SobolSensitivity property) (prophys.explain.ShapValues attribute) (prophys.explain.SystemShapley attribute) interp() (prophys.structures.Field method) (prophys.structures.Field3D method) (prophys.structures.Mesh method) interval (prophys.engine.ProfileLikelihood attribute) interval() (prophys.domain.Observations class method) (prophys.engine.DerivedUncertainty method) (prophys.engine.EstimateWithError method) (prophys.engine.ParameterUncertainty method) (prophys.engine.TailRiskEstimate method) intervals() (prophys.engine.ParameterUncertainty method) inverse() (prophys.frames.FrameTransform method) (prophys.transformations.Affine method) (prophys.transformations.Linear method) (prophys.transformations.RecurrenceRate method) (prophys.transformations.ReturnPeriod method) (prophys.transformations.Transform method) is_adequate() (prophys.engine.EstimateWithError method) (prophys.engine.TailRiskEstimate method) is_affine (prophys.units.Unit property) is_dimensionless (prophys.units.Dimension property) is_distinguishable() (prophys.engine.ModelComparison method) J JointComponent (class in prophys.domain) JointProcess (class in prophys) JointRandomVariable (class in prophys.domain) K k0e() (in module prophys.symbolic) k1e() (in module prophys.symbolic) kernel_shap() (in module prophys.explain) kind (prophys.export.surrogate.SurrogateExport attribute) kl (prophys.nn.PretrainResult attribute) kl_divergence() (in module prophys.nn.losses) ks (prophys.engine.CalibrationReport attribute) L laplace_covariance() (in module prophys.engine) laplacian() (prophys.nn.Derivatives method) Layer (class in prophys.nn.layers) LayerNorm (class in prophys.nn.layers) length() (prophys.structures.LineList method) (prophys.structures.Polyline method) level (prophys.engine.EstimateWithError attribute) (prophys.engine.ProfileLikelihood attribute) license_binding() (in module prophys) license_status() (in module prophys) licensed (prophys.export.RunManifest attribute) licensee (prophys.export.RunManifest attribute) Line (class in prophys.structures) Linear (class in prophys.transformations) LinearGeometry (class in prophys) LinearPosterior (class in prophys.nn) LineList (class in prophys.structures) link (prophys.export.surrogate.SurrogateExport attribute) Lipschitz (class in prophys.nn.layers) lipschitz_bound() (prophys.nn.Surrogate method) lo (prophys.nn.SupportRegion attribute) load() (prophys.export.ModelPackage class method) (prophys.nn.InContextRegressor class method) load_state_dict() (in module prophys.nn) local_sensitivity() (in module prophys.engine) LocalSensitivity (class in prophys.engine) log (prophys.engine.OperationalSurrogate attribute) log() (in module prophys.symbolic) log10() (in module prophys.symbolic) log_det_jacobian() (prophys.transformations.Affine method) (prophys.transformations.Linear method) (prophys.transformations.ReturnPeriod method) (prophys.transformations.Transform method) log_evidence (prophys.nn.LinearPosterior attribute) log_likelihood (prophys.engine.InformationCriteria attribute) (prophys.engine.ParameterUncertainty attribute) (prophys.engine.ProfileLikelihood attribute) log_ndtr() (in module prophys.symbolic) log_prob() (prophys.Autoregressive method) (prophys.distributions.Bernoulli method) (prophys.distributions.Beta method) (prophys.distributions.Categorical method) (prophys.distributions.Correlation method) (prophys.distributions.DirectionalMixture method) (prophys.distributions.Distribution method) (prophys.distributions.Empirical method) (prophys.distributions.Exponential method) (prophys.distributions.Gamma method) (prophys.distributions.Gaussian method) (prophys.distributions.GaussianCopula method) (prophys.distributions.Gumbel method) (prophys.distributions.Histogram method) (prophys.distributions.Independent method) (prophys.distributions.LogNormal method) (prophys.distributions.Mixture method) (prophys.distributions.MultivariateGaussian method) (prophys.distributions.Poisson method) (prophys.distributions.TruncatedGaussian method) (prophys.distributions.Uniform method) (prophys.distributions.VonMises method) (prophys.distributions.Weibull method) (prophys.distributions.WrappedGaussian method) (prophys.domain.AttributeInteractions method) (prophys.domain.Observations method) (prophys.domain.RandomVariable method) (prophys.engine.CompiledModel method) (prophys.JointProcess method) (prophys.nn.QuantileDistribution method) Logistic (class in prophys.transformations) LogNormal (class in prophys.distributions) logsumexp() (in module prophys.symbolic) loo() (in module prophys.engine) loss (prophys.nn.PretrainResult attribute) loss_history (prophys.engine.CalibrationResult attribute) (prophys.engine.OptimizationResult attribute) M machine_fingerprint() (in module prophys) mae (prophys.nn.PretrainResult attribute) manifest (prophys.export.ModelPackage attribute) manifest_from_dict() (in module prophys.export) MANIFEST_VERSION (in module prophys.export) manifest_version (prophys.export.RunManifest attribute) margin (prophys.engine.OperationalSurrogate attribute) mask() (prophys.structures.Grid method) matches() (prophys.export.RunManifest method) max() (prophys.structures.Field method) (prophys.structures.Field3D method) max_log_likelihood (prophys.engine.ProfileLikelihood attribute) maximum() (in module prophys.symbolic) mean (prophys.engine.CrpsScore attribute) (prophys.export.AttributeExport attribute) (prophys.inference.PosteriorSummary attribute) (prophys.nn.LinearPosterior attribute) mean() (in module prophys.symbolic) (prophys.Autoregressive method) (prophys.distributions.Bernoulli method) (prophys.distributions.Beta method) (prophys.distributions.Distribution method) (prophys.distributions.Empirical method) (prophys.distributions.Exponential method) (prophys.distributions.Gamma method) (prophys.distributions.Gaussian method) (prophys.distributions.LogNormal method) (prophys.distributions.Mixture method) (prophys.distributions.MultivariateGaussian method) (prophys.distributions.Poisson method) (prophys.distributions.Uniform method) (prophys.distributions.VonMises method) (prophys.distributions.Weibull method) (prophys.structures.Field method) (prophys.structures.Field3D method) mean_direction() (prophys.distributions.DirectionalMixture method) mean_error() (in module prophys.engine) mean_intensity() (prophys.distributions.DirectionalMixture method) measurement_unit (prophys.domain.UncertainAttribute property) members (prophys.export.surrogate.SurrogateExport attribute) members_output() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) Mesh (class in prophys.structures) method (prophys.explain.ShapValues attribute) min() (prophys.structures.Field method) (prophys.structures.Field3D method) minimum() (in module prophys.symbolic) missing (prophys.io.tabular.Column attribute) MISSING_TOKENS (in module prophys.io.tabular) Mixture (class in prophys.distributions) MixtureHead (class in prophys.nn.layers) mlp_ratio (prophys.nn.DPOTNet attribute) mode (prophys.engine.CompiledModel attribute) (prophys.export.RunManifest attribute) model (prophys.engine.CompiledModel attribute) (prophys.engine.OperationalSurrogate attribute) model_name (prophys.export.ModelPackage attribute) (prophys.export.RunManifest attribute) ModelComparison (class in prophys.engine) ModelPackage (class in prophys.export) modes (prophys.nn.DPOTNet attribute) module prophys.diagnostics prophys.distributions prophys.domain prophys.engine prophys.explain prophys.export prophys.export.surrogate prophys.frames prophys.inference prophys.io prophys.io.tabular prophys.nn prophys.nn.layers prophys.nn.losses prophys.physics prophys.plot prophys.processes prophys.structures prophys.symbolic prophys.transformations prophys.units Monotone (class in prophys.nn.layers) monotone_preserving (prophys.nn.layers.Bounded attribute) (prophys.nn.layers.Dense property) (prophys.nn.layers.Layer attribute) (prophys.nn.layers.Monotone attribute) monotone_violation() (prophys.nn.TreeEnsemble method) monte_carlo_rmse (prophys.engine.AmortizationCard attribute) MultivariateGaussian (class in prophys.distributions) N n (prophys.nn.LinearPosterior attribute) n_blocks (prophys.nn.DPOTNet attribute) n_chains (prophys.inference.Posterior attribute) (prophys.inference.PosteriorSummary attribute) n_draws (prophys.engine.AmortizationCard attribute) (prophys.inference.PosteriorSummary attribute) n_ensemble (prophys.engine.CrpsScore attribute) n_equivalent (prophys.engine.AmortizationCard attribute) n_harmonics() (prophys.transformations.Periodic method) n_informative (prophys.domain.Observations property) n_inner (prophys.explain.SystemShapley attribute) n_inputs (prophys.export.surrogate.SurrogateExport attribute) n_nodes (prophys.structures.Network property) n_observations (prophys.engine.CalibrationReport attribute) (prophys.engine.CrpsScore attribute) (prophys.engine.InformationCriteria attribute) (prophys.engine.ParameterUncertainty attribute) (prophys.engine.PredictiveScore attribute) n_outer (prophys.explain.SystemShapley attribute) n_outputs (prophys.export.surrogate.SurrogateExport attribute) n_parameters (prophys.engine.InformationCriteria attribute) n_params (prophys.nn.Surrogate property) (prophys.nn.TreeEnsemble property) n_points (prophys.engine.AmortizationCard attribute) n_queries (prophys.engine.OperationalSurrogate attribute) n_replicates (prophys.engine.PosteriorPredictiveCheck attribute) n_samples (prophys.engine.AmortizationCard attribute) (prophys.engine.CompiledModel attribute) (prophys.engine.EstimateWithError attribute) (prophys.engine.SobolSensitivity attribute) (prophys.engine.TailRiskEstimate attribute) (prophys.export.AttributeExport attribute) (prophys.export.RunManifest attribute) n_steps (prophys.engine.CalibrationResult attribute) (prophys.engine.OptimizationResult attribute) n_tail (prophys.engine.TailRiskEstimate attribute) n_train (prophys.nn.PretrainResult attribute) n_validation (prophys.engine.AmortizationCard attribute) (prophys.nn.PretrainResult attribute) name (prophys.engine.ProfileLikelihood attribute) (prophys.export.AttributeExport attribute) (prophys.export.surrogate.SurrogateExport attribute) (prophys.io.tabular.Column attribute) (prophys.nn.PhysicsResidual attribute) named() (prophys.nn.Surrogate method) names (prophys.engine.LocalSensitivity attribute) (prophys.engine.ModelComparison attribute) (prophys.engine.OperationalSurrogate attribute) (prophys.engine.ParameterUncertainty attribute) (prophys.engine.SobolSensitivity attribute) (prophys.explain.ShapValues attribute) (prophys.inference.PosteriorSummary attribute) ndtr() (in module prophys.symbolic) negative_log_likelihood() (in module prophys.engine) Network (class in prophys.structures) network_potentials() (in module prophys.physics) nll (prophys.nn.PretrainResult attribute) noise_std (prophys.nn.LinearPosterior property) (prophys.nn.PretrainResult attribute) norm() (in module prophys.symbolic) normalize (prophys.nn.DPOTNet attribute) notes (prophys.export.RunManifest attribute) O Observations (class in prophys.domain) observations (prophys.export.RunManifest attribute) observed (prophys.engine.PosteriorPredictiveCheck attribute) ok (prophys.diagnostics.Diagnostics property) Op (class in prophys.symbolic) op() (in module prophys.symbolic) (prophys.nn.layers.Builder method) OperationalAnswer (class in prophys.engine) OperationalSurrogate (class in prophys.engine) OptimizationResult (class in prophys.engine) optimize() (in module prophys.engine) ornstein_uhlenbeck() (in module prophys) out_channels (prophys.nn.DPOTNet attribute) out_layer_dim (prophys.nn.DPOTNet attribute) out_timesteps (prophys.nn.DPOTNet attribute) output_scale() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) output_units (prophys.export.surrogate.SurrogateExport attribute) outputs() (prophys.nn.layers.Physics method) over_time() (in module prophys) overlap_area() (in module prophys.physics) owens_t() (in module prophys.symbolic) P p_eff (prophys.engine.PredictiveScore attribute) p_value (prophys.engine.PosteriorPredictiveCheck attribute) pairwise_distance() (prophys.structures.PointList method) Param (class in prophys.symbolic) param_leaves() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) param_specs (prophys.engine.CompiledModel attribute) parameter_uncertainty() (in module prophys.engine) ParameterUncertainty (class in prophys.engine) params (prophys.engine.CalibrationResult attribute) (prophys.engine.OptimizationResult attribute) (prophys.export.ModelPackage attribute) (prophys.export.RunManifest attribute) (prophys.export.surrogate.SurrogateExport attribute) params() (prophys.distributions.Distribution method) (prophys.domain.ProbabilityModel method) (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) (prophys.symbolic.Expr method) pareto_k (prophys.engine.PredictiveScore attribute) parse() (in module prophys.units) passed (prophys.engine.AmortizationCard property) patch_size (prophys.nn.DPOTNet attribute) path_from_innovations() (prophys.Autoregressive method) path_from_uniforms() (prophys.Autoregressive method) (prophys.Process method) pays_off (prophys.engine.BreakEvenEstimate attribute) perimeter() (prophys.structures.Ellipse method) (prophys.structures.Polygon method) Periodic (class in prophys.transformations) Phase (class in prophys.transformations) Physics (class in prophys.nn.layers) physics_attention_mapping() (in module prophys.nn) physics_exprs() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) PhysicsResidual (class in prophys.nn) piecewise_polynomial() (in module prophys.physics) PiecewiseLinear (class in prophys.transformations) pinball() (in module prophys.nn.losses) pit (prophys.engine.AmortizationCard attribute) (prophys.nn.PretrainResult attribute) pit_mean (prophys.engine.CalibrationReport attribute) pit_variance (prophys.engine.CalibrationReport attribute) platform (prophys.export.RunManifest attribute) players (prophys.explain.SystemShapley attribute) Point (class in prophys.structures) point_at() (prophys.structures.Ellipse method) (prophys.structures.Polygon method) (prophys.structures.Polyline method) (prophys.structures.RayList method) point_tokens() (in module prophys.nn) PointList (class in prophys.structures) points (prophys.nn.PhysicsResidual attribute) pointwise (prophys.engine.CrpsScore attribute) (prophys.engine.PredictiveScore attribute) pointwise_log_likelihood() (in module prophys.engine) Poisson (class in prophys.distributions) Polygon (class in prophys.structures) PolygonList (class in prophys.structures) Polyhedron (class in prophys.structures) PolyhedronList (class in prophys.structures) Polyline (class in prophys.structures) Polynomial (class in prophys.transformations) PoolAttention (class in prophys.nn.layers) PoolMean (class in prophys.nn.layers) positions() (prophys.structures.Grid method) (prophys.structures.Grid3 method) Positive() (in module prophys.nn.layers) post_step() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) Posterior (class in prophys.inference) posterior (prophys.export.surrogate.SurrogateExport attribute) posterior_predictive_check() (in module prophys.engine) PosteriorPredictiveCheck (class in prophys.engine) PosteriorSummary (class in prophys.inference) potential_function() (in module prophys.inference) precision (prophys.nn.SupportRegion attribute) precision() (prophys.nn.LinearPosterior method) predict() (prophys.nn.InContextRegressor method) predict_distribution() (prophys.nn.InContextRegressor method) predict_quantiles() (prophys.nn.InContextRegressor method) PredictiveScore (class in prophys.engine) PrefixAttention (class in prophys.nn.layers) pretrain() (in module prophys.nn) pretrained() (prophys.nn.InContextRegressor class method) PretrainResult (class in prophys.nn) prior_borders() (in module prophys.nn.pfn) PriorTask (class in prophys.nn) prob() (prophys.engine.CompiledModel method) ProbabilityModel (class in prophys.domain) probe_inputs (prophys.export.surrogate.SurrogateExport attribute) probe_outputs (prophys.export.surrogate.SurrogateExport attribute) probs (prophys.export.AttributeExport attribute) Process (class in prophys) prod() (in module prophys.symbolic) profile_likelihood() (in module prophys.engine) ProfileLikelihood (class in prophys.engine) program() (prophys.nn.layers.Builder method) propagate() (in module prophys.engine) (prophys.structures.Network method) propagate_linear() (in module prophys.physics) prophys.diagnostics module prophys.distributions module prophys.domain module prophys.engine module prophys.explain module prophys.export module prophys.export.surrogate module prophys.frames module prophys.frames.default_registry (built-in variable) prophys.inference module prophys.io module prophys.io.tabular module prophys.nn module prophys.nn.layers module prophys.nn.losses module prophys.physics module prophys.plot module prophys.processes module prophys.structures module prophys.symbolic module prophys.symbolic.Env (built-in variable) prophys.transformations module prophys.units module prophys_version (prophys.export.RunManifest attribute) ProphysError ProphysWarning python_version (prophys.export.RunManifest attribute) Q quantile() (prophys.distributions.Distribution method) (prophys.distributions.Exponential method) (prophys.distributions.Gaussian method) (prophys.distributions.Gumbel method) (prophys.distributions.LogNormal method) (prophys.distributions.Uniform method) (prophys.distributions.Weibull method) (prophys.engine.CompiledModel method) quantile_error() (in module prophys.engine) quantile_levels (prophys.export.surrogate.SurrogateExport attribute) QuantileDistribution (class in prophys.nn) QuantileHead (class in prophys.nn.layers) quantiles (prophys.inference.PosteriorSummary attribute) queries (prophys.engine.BreakEvenEstimate attribute) query() (prophys.engine.OperationalSurrogate method) R r2 (prophys.nn.PretrainResult attribute) r_hat (prophys.inference.PosteriorSummary attribute) rad2deg() (in module prophys.symbolic) random_variables() (prophys.domain.ProbabilityModel method) RandomVariable (class in prophys.domain) RandomWalk (class in prophys) ranked() (prophys.engine.LocalSensitivity method) (prophys.engine.SobolSensitivity method) raw() (prophys.nn.FieldSurrogate method) (prophys.nn.Surrogate method) raw_draws (prophys.inference.Posterior attribute) raw_params (prophys.engine.CalibrationResult attribute) (prophys.export.RunManifest attribute) Ray (class in prophys.structures) ray_integral() (in module prophys.physics) RayList (class in prophys.structures) read_csv() (in module prophys.io.tabular) read_netcdf() (in module prophys.io.tabular) read_observations() (in module prophys.io.tabular) read_raster() (in module prophys.io.tabular) read_table() (in module prophys.io.tabular) read_wind_rose() (in module prophys.io.tabular) reasons (prophys.engine.Guard attribute) (prophys.engine.OperationalAnswer attribute) recommendation (prophys.engine.BreakEvenEstimate attribute) record_layer (prophys.nn.layers.Builder attribute) Recurrence (class in prophys) RecurrenceRate (class in prophys.transformations) reference_draws (prophys.engine.AmortizationCard attribute) register() (prophys.frames.FrameRegistry method) register_unit() (in module prophys.units) relative_error (prophys.engine.EstimateWithError property) (prophys.engine.TailRiskEstimate property) relative_errors (prophys.engine.ParameterUncertainty property) reliability_index (prophys.engine.CalibrationReport attribute) relu() (in module prophys.symbolic) render() (prophys.diagnostics.Diagnostic method) (prophys.diagnostics.Diagnostics method) replicate_mean (prophys.engine.PosteriorPredictiveCheck attribute) replicate_std (prophys.engine.PosteriorPredictiveCheck attribute) Report (class in prophys.engine) report_card() (in module prophys.engine) representation (prophys.export.AttributeExport attribute) reproduce() (in module prophys.export) reproduces_the_data (prophys.engine.PosteriorPredictiveCheck property) ReproducibilityError required_samples() (in module prophys.engine) Reshape (class in prophys.nn.layers) Residual (class in prophys.nn.layers) residual() (prophys.Geometry method) ReturnPeriod (class in prophys.transformations) RFF (class in prophys.nn.layers) right_censored (prophys.io.tabular.Column attribute) right_censored() (prophys.domain.Observations class method) risk_map() (in module prophys.plot) rmse (prophys.nn.PretrainResult attribute) route (prophys.engine.Guard property) (prophys.engine.OperationalAnswer attribute) RunManifest (class in prophys.export) S s2 (prophys.nn.LinearPosterior attribute) same_unit() (in module prophys.units) sample() (prophys.distributions.Bernoulli method) (prophys.distributions.Beta method) (prophys.distributions.Categorical method) (prophys.distributions.Correlation method) (prophys.distributions.DirectionalMixture method) (prophys.distributions.Distribution method) (prophys.distributions.Empirical method) (prophys.distributions.Exponential method) (prophys.distributions.Gamma method) (prophys.distributions.Gaussian method) (prophys.distributions.GaussianCopula method) (prophys.distributions.Gumbel method) (prophys.distributions.Independent method) (prophys.distributions.LogNormal method) (prophys.distributions.Mixture method) (prophys.distributions.MultivariateGaussian method) (prophys.distributions.Poisson method) (prophys.distributions.Uniform method) (prophys.distributions.VonMises method) (prophys.distributions.Weibull method) (prophys.engine.CompiledModel method) (prophys.JointProcess method) (prophys.Process method) sample_parameters() (in module prophys.engine) sample_points() (prophys.structures.Polyline method) sample_posterior() (in module prophys.inference) sample_prior_task() (in module prophys.nn) sample_set() (in module prophys.nn) samples (prophys.export.AttributeExport attribute) samples_to_probs() (in module prophys.nn.losses) SampleSet (class in prophys.nn) save() (prophys.export.ModelPackage method) (prophys.nn.InContextRegressor method) schedule() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) seconds (prophys.engine.OperationalAnswer attribute) seed (prophys.engine.CompiledModel attribute) (prophys.export.RunManifest attribute) SelfAttention (class in prophys.nn.layers) set_constant() (prophys.nn.Surrogate method) set_standardization() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) set_values() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) SetBlock (class in prophys.nn.layers) shape() (prophys.structures.Grid method) (prophys.structures.Grid3 method) ShapeError shapley_effects() (in module prophys.explain) shapley_values() (in module prophys.explain) ShapValues (class in prophys.explain) shares() (prophys.explain.SystemShapley method) sigmoid() (in module prophys.symbolic) sign() (in module prophys.symbolic) signed_distance() (prophys.structures.Ellipse method) (prophys.structures.EllipseList method) (prophys.structures.Polygon method) (prophys.structures.PolygonList method) (prophys.structures.Polyhedron method) sin() (in module prophys.symbolic) SliceAttention (class in prophys.nn.layers) slot() (prophys.nn.layers.Builder method) sobol_sensitivity() (in module prophys.engine) SobolSensitivity (class in prophys.engine) softmax() (in module prophys.symbolic) softmin() (in module prophys.symbolic) softplus() (in module prophys.symbolic) spectral_random_field() (in module prophys.physics) speedup (prophys.engine.BreakEvenEstimate attribute) sqrt() (in module prophys.symbolic) stack() (in module prophys.symbolic) stale (prophys.engine.OperationalSurrogate attribute) state_space_loglik() (in module prophys.physics) statistic (prophys.engine.EstimateWithError attribute) (prophys.engine.LocalSensitivity attribute) (prophys.engine.PosteriorPredictiveCheck attribute) (prophys.explain.SystemShapley attribute) stats (prophys.engine.AmortizationCard attribute) (prophys.engine.OperationalSurrogate attribute) std (prophys.inference.PosteriorSummary attribute) std_error (prophys.engine.CrpsScore attribute) (prophys.engine.EstimateWithError attribute) (prophys.engine.TailRiskEstimate attribute) (prophys.export.AttributeExport attribute) std_errors (prophys.engine.DerivedUncertainty attribute) (prophys.engine.ParameterUncertainty attribute) steps (prophys.nn.PretrainResult attribute) structure_description() (in module prophys.export) structure_hash (prophys.engine.AmortizationCard attribute) (prophys.export.RunManifest attribute) structure_hash() (in module prophys.export) sum_() (in module prophys.symbolic) summary() (prophys.inference.Posterior method) (prophys.io.tabular.Column method) superpose() (in module prophys.physics) support (prophys.export.AttributeExport attribute) (prophys.export.surrogate.SurrogateExport attribute) support_distance() (prophys.nn.Surrogate method) (prophys.nn.TreeEnsemble method) SUPPORTED_VERSIONS (in module prophys.export) SupportRegion (class in prophys.nn) Surrogate (class in prophys.nn) (class in prophys.symbolic) surrogate (prophys.engine.OperationalSurrogate attribute) (prophys.nn.PretrainResult attribute) surrogate() (prophys.export.ModelPackage method) surrogate_priors (prophys.engine.CalibrationResult attribute) surrogate_query_seconds (prophys.engine.AmortizationCard attribute) (prophys.engine.BreakEvenEstimate attribute) surrogate_rmse (prophys.engine.AmortizationCard attribute) surrogate_shift() (prophys.engine.CalibrationResult method) surrogate_values (prophys.engine.OperationalAnswer attribute) SurrogateCall (class in prophys.nn) SurrogateExport (class in prophys.export.surrogate) surrogates (prophys.export.ModelPackage attribute) SystemShapley (class in prophys.explain) T T (prophys.symbolic.Expr property) TableLookup1D (class in prophys.transformations) TableLookup2D (class in prophys.transformations) tail_pinball (prophys.nn.PretrainResult attribute) TailRiskEstimate (class in prophys.engine) tails (prophys.export.surrogate.SurrogateExport attribute) tan() (in module prophys.symbolic) tanh() (in module prophys.symbolic) target_kind (prophys.nn.PretrainResult attribute) tau (prophys.engine.CompiledModel attribute) (prophys.export.RunManifest attribute) then() (prophys.transformations.Transform method) thin() (prophys.inference.Posterior method) threshold (prophys.nn.SupportRegion attribute) threshold_margin (prophys.engine.Guard attribute) thresholds (prophys.engine.OperationalSurrogate attribute) time_agg (prophys.nn.DPOTNet attribute) time_diff() (in module prophys) time_mean() (in module prophys) time_sum() (in module prophys) title (prophys.diagnostics.Diagnostic property) to() (prophys.io.tabular.Column method) to_bytes() (prophys.export.surrogate.SurrogateExport method) to_dict() (prophys.diagnostics.Diagnostic method) (prophys.engine.Report method) (prophys.explain.ShapValues method) (prophys.explain.SystemShapley method) (prophys.export.ModelPackage method) (prophys.export.RunManifest method) (prophys.export.surrogate.SurrogateExport method) (prophys.nn.LinearPosterior method) (prophys.nn.SupportRegion method) to_json() (prophys.export.ModelPackage method) to_observations() (prophys.io.tabular.Column method) tokens() (prophys.nn.DPOTSurrogate method) total (prophys.explain.SystemShapley attribute) total_length() (prophys.structures.Network method) total_order (prophys.engine.SobolSensitivity attribute) train_loss (prophys.nn.PretrainResult attribute) train_pfn() (in module prophys.nn) train_seconds (prophys.engine.AmortizationCard attribute) (prophys.engine.BreakEvenEstimate attribute) Transform (class in prophys.transformations) TransformedDistribution (class in prophys.distributions) transolver_mapping() (in module prophys.nn) TransolverBlock (class in prophys.nn.layers) tree_shap() (in module prophys.explain) TreeEnsemble (class in prophys.nn) TruncatedGaussian (class in prophys.distributions) U UncertainAttribute (class in prophys.domain) unconstrained_init() (prophys.symbolic.Param method) unexplained (prophys.engine.SobolSensitivity property) Uniform (class in prophys.distributions) Unit (class in prophys.units) unit (prophys.export.AttributeExport attribute) (prophys.frames.Frame property) (prophys.io.tabular.Column attribute) unit_description (prophys.export.AttributeExport attribute) unit_scale (prophys.frames.FrameTransform property) UnitError unreliable_points (prophys.engine.PredictiveScore property) upstream_random_variables() (prophys.domain.UncertainAttribute method) V v (prophys.nn.LinearPosterior attribute) validate() (prophys.symbolic.Surrogate method) validation_loss (prophys.nn.PretrainResult attribute) value (prophys.engine.EstimateWithError attribute) (prophys.engine.LocalSensitivity attribute) values (prophys.engine.DerivedUncertainty attribute) (prophys.engine.OperationalAnswer attribute) (prophys.explain.ShapValues attribute) (prophys.explain.SystemShapley attribute) (prophys.io.tabular.Column attribute) var (prophys.engine.TailRiskEstimate attribute) variance() (prophys.distributions.Beta method) (prophys.distributions.Distribution method) (prophys.distributions.Exponential method) (prophys.distributions.Gamma method) (prophys.distributions.Gaussian method) (prophys.nn.LinearPosterior method) verify() (in module prophys.export) (prophys.export.ModelPackage method) (prophys.export.surrogate.SurrogateExport method) volume() (prophys.structures.Polyhedron method) VonMises (class in prophys.distributions) W waic() (in module prophys.engine) warning() (in module prophys.diagnostics) warnings (prophys.diagnostics.Diagnostics property) Weibull (class in prophys.distributions) weight (prophys.nn.PhysicsResidual attribute) where (prophys.nn.layers.Builder attribute) where() (in module prophys.symbolic) wrap() (in module prophys.symbolic) (prophys.Geometry method) WrappedGaussian (class in prophys.distributions) X x (prophys.nn.PriorTask attribute) Y y (prophys.nn.PriorTask attribute)
