A New Default Colormap for ParaView

Samsel, Francesca; Scott, W. Alan; Moreland, Kenneth

doi:10.1109/mcg.2024.3383137

A New Default Colormap for ParaView

Journal Article · 20 August 2024 · IEEE Computer Graphics and Applications

DOI:https://doi.org/10.1109/mcg.2024.3383137· OSTI ID:2438911

^[1]; Scott, W. Alan ^[2]; ^[3]

Texas Advanced Computing Center, Austin, TX (United States); Univ. of Texas, Austin, TX (United States)
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

ParaView is one of the most prominent software tools for scientific visualization used by scientists around the world. Color is a primary conduit to visually map data to its representation and, thus, enable investigation and interpretation of the data. Colormap selection has a significant impact on the data revealed; its design and selection is a critical aspect of scientific data visualization. A common choice for a user is the program’s default colormap, so careful consideration of this default is consequential. Although the current default colormap in ParaView, a succession of hues from cool blue to warm red, has served the community well, research shows that more nuanced colormap configurations increase discriminability while maintaining other critical metrics. These findings inspire us to revisit and update the default colors in ParaView. Here, in this study, we present a new ParaView default colormap, the criteria and methods of development, and example visualizations and analytic metrics.

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR). Scientific Discovery through Advanced Computing (SciDAC)

Grant/Contract Number:: AC05-00OR22725; NA0003525

OSTI ID:: 2438911

Journal Information:: IEEE Computer Graphics and Applications, Journal Name: IEEE Computer Graphics and Applications Journal Issue: 4 Vol. 44; ISSN 0272-1716

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

References (12)

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The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps Bujack, Roxana; Turton, Terece L.; Samsel, Francesca IEEE Transactions on Visualization and Computer Graphics, Vol. 24, Issue 1 https://doi.org/10.1109/TVCG.2017.2743978	journal	January 2018
Measuring and Modeling the Feature Detection Threshold Functions of Colormaps Ware, Colin; Turton, Terece L.; Bujack, Roxana IEEE Transactions on Visualization and Computer Graphics, Vol. 25, Issue 9 https://doi.org/10.1109/TVCG.2018.2855742	journal	September 2019
The Making of Continuous Colormaps Nardini, Pascal; Chen, Min; Samsel, Francesca IEEE Transactions on Visualization and Computer Graphics, Vol. 27, Issue 6 https://doi.org/10.1109/TVCG.2019.2961674	journal	June 2021
Colormaps that Improve Perception of High-Resolution Ocean Data Samsel, Francesca; Petersen, Mark; Geld, Terece Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems https://doi.org/10.1145/2702613.2702975	conference	April 2015
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