VRGrid: Efficient Transformation of 2D Data into Pixel Grid Layout

VRGrid: Transformation Efficace de Données 2D en Grille de Pixels

Adrien Halnaut (1) , Romain Giot (1) , Romain Bourqui (1) , David Auber (1)

1 LaBRI - Laboratoire Bordelais de Recherche en Informatique

Projecting a set of n points on a grid of size √ n× √ n provides the best possible information density in two dimensions without overlap. We leverage the Voronoi Relaxation method to devise a novel and versatile post-processing algorithm called VRGrid: it enables the arrangement of any 2D data on a grid while preserving its initial positions. We apply VRGrid to generate compact and overlap-free visualization of popular and overlap-prone projection methods (e.g., t-SNE). We prove that our method complexity is O (√ n.i.n.log(n)), with i a determined maximum number of iterations and n the input dataset size. It is thus usable for visualization of several thousands of points. We evaluate VRGrid's efficiency with several metrics: distance preservation (DP), neighborhood preservation (NP), pairwise relative positioning preservation (RPP) and global positioning preservation (GPP). We benchmark VRGrid against two stateof-the-art methods: Self-Sorting Maps (SSM) and Distancepreserving Grid (DGrid). VRGrid outperforms these two methods, given enough iterations, on DP, RPP and GPP which we identify to be the key metrics to preserve the positions of the original set of points.

Mots clés: visualization; compact visualization; evaluation

Domaines: Autre [cs.OH]

Adrien Halnaut, Romain Giot, Romain Bourqui, David Auber. VRGrid: Efficient Transformation of 2D Data into Pixel Grid Layout. 26th International Conference Information Visualisation, Jul 2022, Vienna, Austria. pp.11-20. ⟨hal-03700588⟩