Gallery#
This section collects the example-driven lessons of GeoPrior-v3.
Unlike the API reference, these pages are organized around practical workflows, interpretation tasks, decision support, and deployment questions. Each subsection shows executable examples, generated outputs, and guided explanations that help users understand not only how to run a helper, but also how to read what it produced.
Use this gallery to move from running GeoPrior to interpreting GeoPrior with confidence.
Start here#
Follow scientific case studies that show how GeoPrior supports validation, identifiability audits, action prioritization, and transfer-aware deployment.
Learn the basic forecasting workflow, future quantile mapping, and holdout-versus-forecast comparisons.
Explore calibration, reliability, coverage-versus- sharpness, raw-versus-calibrated reliability, and exceedance-oriented uncertainty diagnostics.
Read forecast quality through horizon-wise metrics, stability, interval scores, calibration summaries, and multi-metric comparison plots.
Inspect stage-oriented data checks, training curves, tuning summaries, and regression-style fit diagnostics such as R² comparison views.
Learn how to read mapped outputs through full-domain scatter maps, ROI zooms, contours, hotspot views, Voronoi partitions, and heatmap-style summaries.
Read saved workflow artifacts as evidence: audits, manifests, scaling sidecars, training summaries, evaluation bundles, transfer results, and ablation logs.
Build the paper-ready and analysis-ready figures used to communicate GeoPrior results.
Build tidy metric tables, hotspot summaries, extended forecasts, and lightweight spatial support layers.
Inspect training histories, epsilon and physics-loss trends, payload values, coordinates, and learned parameters.
How this gallery is organized#
The gallery is split by purpose so you can navigate the documentation according to the kind of task you want to do.
Applications focuses on scientific and operational stories. These pages connect multiple GeoPrior outputs into one case study so you can see how the framework supports validation, interpretation guardrails, intervention prioritization, and cross-city deployment.
Forecasting focuses on what was predicted and how forecast outputs are structured.
Uncertainty focuses on probabilistic trust questions such as reliability, calibration, coverage, sharpness, raw-versus- calibrated comparison, and exceedance behavior.
Evaluation focuses on judging forecast quality once results already exist: error over horizon, weighted metrics, stability, interval scores, calibration summaries, and compact model comparison views.
Diagnostics focuses on whether the workflow behaved cleanly: stage checks, training health, tuning summaries, and regression-style fit views such as R² diagnostics.
Spatial focuses on where patterns happen and how mapped results should be read: sampled points, local regions of interest, smoothed surfaces, hotspots, support partitions, and gridded summaries.
Inspection focuses on reading the saved workflow artifacts that connect those stages together: audits, manifests, configuration sidecars, summaries, evaluation JSONs, transfer bundles, and experiment logs. It is the best place to go when you already have an artifact on disk and want to decide whether to continue, recalibrate, compare, export, or re-run.
Figure generation focuses on producing polished visual outputs for analysis, reporting, and publication.
Tables and summaries focuses on reusable artifacts such as metric tables, summaries, and lightweight support layers.
Model inspection focuses on deeper checks of training behavior, physics diagnostics, and learned quantities inside the model itself.
A practical reading rule#
If you are not sure where to begin, use this guide:
Go to Applications when your main question is why this result matters scientifically or operationally, and how several GeoPrior outputs combine into one decision story.
Go to Forecasting when your main question is what was predicted?
Go to Uncertainty when your main question is how reliable are the intervals, quantiles, or exceedance estimates?
Go to Evaluation when your main question is how good is the forecast once I quantify it across horizons, metrics, and calibration views?
Go to Diagnostics when your main question is did the workflow run cleanly and do the staged checks or fit summaries look healthy?
Go to Spatial when your main question is where are the mapped patterns, support zones, hotspots, or local regional structures?
Go to Inspection when your main question is what does this saved artifact mean, and is it trustworthy enough for the next decision?
Go to Figure generation when your main question is how do I communicate the result clearly?
Go to Tables and summaries when your main question is how do I export a reusable metric or spatial summary?
Go to Model inspection when your main question is what did the model learn internally and how did the physics terms behave?
How to use these pages#
Each subsection is designed as a set of small lessons.
A typical page will help you:
build or load a compact example input,
run a real GeoPrior helper or plotting routine,
inspect the resulting figure, table, or artifact,
understand what the output means,
and decide what to do next.
That means the gallery is not only for copying code. It is also a practical guide to reading outputs with confidence.
See also#
Review execution-time summaries for the generated gallery examples.