Topological Data Analysis for Scientific Visualization [Paperback]

Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data.

Theoretical concepts are presented in a painstaking but intuitive manner, with numerous high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in detail, and their application is carefully demonstrated in a chapter dedicated to concrete use cases.

With its fine balance between theory and practice, Topological Data Analysis for Scientific Visualization constitutes an appealing introduction to the increasingly important topic of topological data analysis for lecturers, students and researchers.

 

1. Introduction.- 2. Background: 2.1 Data representation.- 2.2 Topological abstractions.- 2.3 Algorithms and applications.- 3. Abstraction: 3.1 Efficient topological simplification of scalar fields.- 3.2 Efficient Reeb graph computation for volumetric meshes.- 4. Interaction: 4.1 Topological simplification of isosurfaces.- 4.2 Interactive editing of topological abstractions.- 5. Analysis: 5.1 Exploration of turbulent combustion simulations.- 5.2 Quantitative analysis of molecular interactions.- 6. Perspectives: 6.1 Emerging constraints.- 6.2 Emerging data types.- 7. Conclusion.

The book under review is built as a systematic textbook that pinpoints the elements of data visualization and offers the theoretical background for this task. & The book is written in an accessible style, suitable for undergraduates and graduates alike, and only requires a minimal algorithmic background. (Irina Ioana Mohorianu, zbMATl3á