Interactive Visual Analysis of Spatial Sensitivities

TL;DR

This paper introduces an interactive visual analytics method for analyzing localized spatial sensitivities in 3D simulation ensembles, enabling detailed exploration of parameter influences across regions.

Contribution

It presents a novel visualization approach for multi-field spatial sensitivity data, combining space-filling curves, horizon graphs, and line charts for interactive analysis.

Findings

Effective visualization of multi-field sensitivity data

Enhanced understanding of parameter influences in spatial regions

Validated approach on synthetic and real-world data

Abstract

Sensitivity analyses of simulation ensembles determine how simulation parameters influence the simulation's outcome. Commonly, one global numerical sensitivity value is computed per simulation parameter. However, when considering 3D spatial simulations, the analysis of localized sensitivities in different spatial regions is of importance in many applications. For analyzing the spatial variation of parameter sensitivity, one needs to compute a spatial sensitivity scalar field per simulation parameter. Given $n$ simulation parameters, we obtain multi-field data consisting of $n$ scalar fields when considering all simulation parameters. We propose an interactive visual analytics solution to analyze the multi-field sensitivity data. It supports the investigation of how strongly and in what way individual parameters influence the simulation outcome, in which spatial regions this is happening, and what the interplay of the simulation parameters is. Its central component is an overview visualization of all sensitivity fields that avoids 3D occlusions by linearizing the data using an adapted scheme of data-driven space-filling curves. The spatial sensitivity values are visualized in a combination of a Horizon Graph and a line chart. We validate our approach by applying it to synthetic and real-world ensemble data.