Computation times

02:40.974 total execution time for 105 files from all galleries:

Example	Time	Mem (MB)
Cumulative subsidence on a satellite-style map (examples/figure_generation/plot_geo_cumulative.py)	00:12.908	0.0
Ablations and sensitivities: learning where the model behaves well in lambda space (examples/figure_generation/plot_core_ablation.py)	00:10.629	0.0
SM3 identifiability: learning when recovery is accurate and when parameters slide along a ridge (examples/figure_generation/plot_sm3_identifiability.py)	00:08.175	0.0
Physics profiles: reducing a 2D lambda landscape into readable 1D lessons (examples/figure_generation/plot_physics_profiles.py)	00:06.066	0.0
Transfer impact: what transfer changes for retention, risk, and hotspot stability (examples/figure_generation/plot_xfer_impact.py)	00:05.837	0.0
Plot physics payload values as maps and histograms (examples/model_inspection/plot_physics_values_in.py)	00:05.586	0.0
External validation: comparing inferred effective fields against independent site evidence (examples/figure_generation/plot_external_validation.py)	00:05.517	0.0
Physics sanity: checking closure agreement and residual behavior (examples/figure_generation/plot_physics_sanity.py)	00:05.299	0.0
Physics sensitivity: learning how lambda choices reshape the physics diagnostics (examples/figure_generation/plot_physics_sensitivity.py)	00:05.203	0.0
Hotspot analytics: turning future forecasts into decision-ready priority maps (examples/figure_generation/plot_hotspot_analytics.py)	00:04.400	0.0
SM3 bounds versus ridge: learning the two main failure modes (examples/figure_generation/plot_sm3_bounds_ridge_summary.py)	00:03.545	0.0
Driver-response plots: learning how the response moves with the drivers (examples/figure_generation/plot_driver_response.py)	00:03.355	0.0
Read smoothed spatial structure with gridded heatmaps (examples/spatial/plot_spatial_heatmap_overview.py)	00:03.310	0.0
Cross-city transferability (v3.2): what survives when a workflow moves to the other city (examples/figure_generation/plot_xfer_transferability.py)	00:03.135	0.0
Cross-city transferability: learning what survives transfer between cities (examples/figure_generation/plot_transfer.py)	00:02.729	0.0
Focus on a local map window with plot_spatial_roi (examples/spatial/plot_spatial_roi_overview.py)	00:02.379	0.0
Build non-overlapping spatial sample batches (examples/tables_and_summaries/build_batch_spatial_sampling.py)	00:02.291	0.0
Read smooth spatial structure with plot_spatial_contours (examples/spatial/plot_spatial_contours_overview.py)	00:02.285	0.0
Forecast by horizon step with plot_forecast_by_step (examples/forecasting/plot_forecast_by_step.py)	00:02.188	0.0
Read spatial forecast patterns with plot_spatial (examples/spatial/plot_spatial_overview.py)	00:02.146	0.0
Core ablation: learning what physics adds to the workflow (examples/figure_generation/plot_ablation.py)	00:02.103	0.0
From raw model outputs to forecast tables with format_and_forecast (examples/forecasting/plot_format_and_forecast.py)	00:01.866	0.0
Lithology parity: comparing the geological composition of the two cities (examples/figure_generation/plot_litho_parity.py)	00:01.846	0.0
Read nearest-observation spatial influence with Voronoi maps (examples/spatial/plot_spatial_voronoi_overview.py)	00:01.810	0.0
Learn to compare forecasts visually with plot_forecast_comparison (examples/evaluation/plot_forecast_comparison_overview.py)	00:01.726	0.0
Compare independent regression pairs with plot_r2_in (examples/diagnostics/plot_r2_in_overview.py)	00:01.680	0.0
Find and read spatial hotspots before acting on a map (examples/spatial/plot_hotspots_overview.py)	00:01.655	0.0
Inspect interpretable evaluation physics before reporting results (examples/inspection/plot_eval_physics_overview.py)	00:01.628	0.0
Inspect ablation records before choosing a configuration (examples/inspection/plot_ablation_record_overview.py)	00:01.599	0.0
Inspect a training summary before trusting a Stage-2 run (examples/inspection/plot_training_summary_overview.py)	00:01.556	0.0
Read ensemble forecast quality with plot_crps (examples/evaluation/plot_crps_overview.py)	00:01.371	0.0
Read forecast quality horizon by horizon with plot_metric_over_horizon (examples/evaluation/plot_metric_over_horizon_overview.py)	00:01.365	0.0
Build a stratified spatial sample table (examples/tables_and_summaries/build_spatial_sampling.py)	00:01.362	0.0
Plot training history with robust grouping and scale handling (examples/model_inspection/plot_history_in.py)	00:01.341	0.0
Compare compact score profiles with plot_radar_scores (examples/evaluation/plot_radar_scores_overview.py)	00:01.312	0.0
Holdout versus future forecast with plot_eval_future (examples/forecasting/plot_holdout_vs_forecast.py)	00:01.272	0.0
Inspect compact evaluation diagnostics before trusting forecast quality (examples/inspection/plot_eval_diagnostics_overview.py)	00:01.186	0.0
Inspect a Stage-1 audit before Stage-2 (examples/inspection/plot_stage1_audit_overview.py)	00:01.180	0.0
Understand regression agreement with plot_r2 (examples/diagnostics/plot_r2_overview.py)	00:01.050	0.0
Expanded uncertainty diagnostics: learning what the main uncertainty figure still hides (examples/figure_generation/plot_uncertainty_extras.py)	00:01.036	0.0
Future quantile maps with forecast_view (examples/forecasting/plot_future_quantiles_map.py)	00:00.994	0.0
Inspect a model-initialization manifest before training (examples/inspection/plot_model_init_manifest_overview.py)	00:00.987	0.0
Spatial forecasts: how to read observed maps, fitted maps, and future forecast maps together (examples/figure_generation/plot_spatial_forecasts.py)	00:00.976	0.0
Physics maps: turning pointwise payloads into readable spatial fields (examples/figure_generation/plot_physics_maps.py)	00:00.906	0.0
Build a compact forecast-ready panel sample (examples/tables_and_summaries/build_forecast_ready_sample.py)	00:00.877	0.0
Read quantile reliability with plot_quantile_calibration (examples/evaluation/plot_quantile_calibration_overview.py)	00:00.852	0.0
Automatically save the standard GeoPrior history diagnostics (examples/model_inspection/plot_autoplot_geoprior_history.py)	00:00.835	0.0
Forecast uncertainty: learning how calibration behaves across cities and horizons (examples/figure_generation/plot_uncertainty.py)	00:00.820	0.0
Compare forecast quality across groups with plot_metric_radar (examples/evaluation/plot_metric_radar_overview.py)	00:00.797	0.0
From calibrated forecasts to action-first zones (examples/applications/app_hotspot_prioritization.py)	00:00.771	0.0
Stage-2 training curves and physics-aware learning dynamics (examples/diagnostics/plot_stage2_training_curves.py)	00:00.767	0.0
Physics diagnostics bridge: from evaluate_physics to payload inspection (examples/diagnostics/plot_physics_diagnostic_bridge.py)	00:00.720	0.0
Learn how horizon emphasis changes the score with plot_time_weighted_metric (examples/evaluation/plot_time_weighted_metric_overview.py)	00:00.710	0.0
Stage-3 tuning summary and best-trial diagnostics (examples/diagnostics/plot_stage3_tuning_summary.py)	00:00.700	0.0
Exceedance probabilities and Brier score (examples/uncertainty/plot_brier_exceedance.py)	00:00.699	0.0
Stage-2 training curves and physics diagnostics (examples/diagnostics/plot_physics_diagnostic.py)	00:00.693	0.0
Auditing identifiability before reading learned physics fields (examples/applications/app_bounds_ridge.py)	00:00.686	0.0
Enrich main datasets with surface elevation (examples/tables_and_summaries/build_add_zsurf_from_coords.py)	00:00.665	0.0
When cross-city reuse is useful, and when it is not (examples/applications/app_transferability.py)	00:00.656	0.0
Plot physics loss terms from a GeoPrior training history (examples/model_inspection/plot_physics_losses_in.py)	00:00.645	0.0
Coverage versus sharpness in probabilistic forecasts (examples/uncertainty/plot_coverage_vs_sharpness.py)	00:00.645	0.0
Inspect calibration statistics before trusting interval forecasts (examples/inspection/plot_calibration_stats_overview.py)	00:00.642	0.0
Read quantile miscalibration with plot_qce_donut (examples/evaluation/plot_qce_donut_overview.py)	00:00.627	0.0
Quantile recalibration with calibrate_forecasts (examples/uncertainty/plot_calibrate_forecasts.py)	00:00.614	0.0
Plot epsilon diagnostics from a GeoPrior training history (examples/model_inspection/plot_epsilons_in.py)	00:00.564	0.0
Inspect transfer-learning results before trusting cross-city conclusions (examples/inspection/plot_xfer_results_overview.py)	00:00.563	0.0
Forecast quick-look with plot_forecasts (examples/forecasting/plot_forecast.py)	00:00.544	0.0
Build city boundary polygons from forecast points (examples/tables_and_summaries/make_boundary.py)	00:00.543	0.0
SM3 log offsets: learning where the inferred fields drift from their priors (examples/figure_generation/plot_sm3_log_offsets.py)	00:00.535	0.0
Inspect a Stage-1 manifest before downstream stages (examples/inspection/plot_manifest_overview.py)	00:00.529	0.0
Extract threshold-based spatial zones with extract-zones (examples/tables_and_summaries/build_extract_zones.py)	00:00.526	0.0
Stage-1 data checks with group masks and holdout splitting (examples/diagnostics/plot_stage1_data_checks.py)	00:00.523	0.0
Physics fields: learning to read the physical story in a map (examples/figure_generation/plot_physics_fields.py)	00:00.517	0.0
Learn how to read interval reliability with plot_coverage (examples/evaluation/plot_coverage_overview.py)	00:00.509	0.0
Assign boreholes to the nearest city cloud (examples/tables_and_summaries/build_assign_boreholes.py)	00:00.505	0.0
Learn how to read forecast sharpness with plot_mean_interval_width (examples/evaluation/plot_mean_interval_width_overview.py)	00:00.498	0.0
Extract a rectangular region of interest with spatial-roi (examples/tables_and_summaries/build_spatial_roi.py)	00:00.495	0.0
Build spatial cluster tables with spatial-clusters (examples/tables_and_summaries/build_spatial_clusters.py)	00:00.491	0.0
Learn how to judge interval forecasts with plot_weighted_interval_score (examples/evaluation/plot_weighted_interval_score_overview.py)	00:00.486	0.0
Spatial-block holdout as a Stage-1 diagnostic (examples/diagnostics/plot_spatial_block_holdout.py)	00:00.475	0.0
Inspect a scaling_kwargs.json configuration (examples/inspection/plot_scaling_kwargs_overview.py)	00:00.435	0.0
Create exposure weights from forecast point density (examples/tables_and_summaries/make_exposure.py)	00:00.392	0.0
Create district grid layers from forecast points (examples/tables_and_summaries/make_district_grid.py)	00:00.390	0.0
Why physics matters in core forecasting (examples/applications/app_core_ablation.py)	00:00.382	0.0
Extend forecast CSVs to later years (examples/tables_and_summaries/extend_forecast.py)	00:00.378	0.0
Build ablation tables from sensitivity records (examples/tables_and_summaries/build_ablation_table.py)	00:00.376	0.0
Inspect a Stage-2 run manifest before downstream workflow steps (examples/inspection/plot_run_manifest_overview.py)	00:00.367	0.0
Inspect physics-payload metadata before opening the full payload (examples/inspection/plot_physics_payload_meta_overview.py)	00:00.348	0.0
Compare raw and calibrated reliability with plot_calibration_comparison (examples/uncertainty/plot_calibration_comparison_overview.py)	00:00.339	0.0
Tag hotspot clusters with district Zone IDs (examples/tables_and_summaries/tag_clusters_with_zones.py)	00:00.321	0.0
Learn how forecast smoothness behaves with plot_prediction_stability (examples/evaluation/plot_prediction_stability_overview.py)	00:00.318	0.0
Evaluate forecast tables with evaluate_forecast (examples/forecasting/plot_evaluate_forecast.py)	00:00.312	0.0
Summarize hotspot point clouds into tidy group tables (examples/tables_and_summaries/summarize_hotspots.py)	00:00.311	0.0
Compute hotspot summary tables from forecast CSVs (examples/tables_and_summaries/compute_hotspots.py)	00:00.311	0.0
Reliability diagrams for probabilistic forecasts (examples/uncertainty/plot_reliability_diagram.py)	00:00.304	0.0
Interval calibration with calibrate_quantile_forecasts (examples/uncertainty/plot_interval_calibration.py)	00:00.303	0.0
Learn how to benchmark a forecast against a naive baseline with plot_theils_u_score (examples/evaluation/plot_theils_u_score_overview.py)	00:00.295	0.0
External validation of inferred effective fields (examples/applications/app_external_validation.py)	00:00.294	0.0
Compute exceedance Brier scores from calibrated forecasts (examples/tables_and_summaries/compute_brier_exceedance.py)	00:00.291	0.0
Build one merged full_inputs.npz from Stage-1 split artifacts (examples/tables_and_summaries/build_full_inputs_npz.py)	00:00.271	0.0
Build unified model-metrics tables from GeoPrior runs (examples/tables_and_summaries/build_model_metrics.py)	00:00.261	0.0
Read forecast reliability with plot_reliability_diagram (examples/uncertainty/plot_reliability_diagram_overview.py)	00:00.244	0.0
Group-validity masks for Stage-1 diagnostics (examples/diagnostics/plot_holdout_group_masks.py)	00:00.192	0.0
Extract learned physical parameters from a trained model (examples/model_inspection/tag_extract_physical_parameters.py)	00:00.020	0.0
Flatten (t, x, y) coordinates from dataset batches (examples/model_inspection/make_gather_coords_flat.py)	00:00.005	0.0