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Topological Data Analysis for Scientific Visualization [electronic resource] / by Julien Tierny.

By: Contributor(s): Material type: TextTextSeries: Mathematics and VisualizationPublisher: Cham : Springer International Publishing : Imprint: Springer, 2017Description: XV, 150 p. 84 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319715070
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 004 23
LOC classification:
  • QA76.9.I52
Online resources:
Contents:
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.
In: Springer eBooksSummary: Combining theoretical and practical aspects of topology, this book delivers a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a thorough but intuitive manner, with many high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in details, and their application is carefully illustrated 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.
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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.

Combining theoretical and practical aspects of topology, this book delivers a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a thorough but intuitive manner, with many high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in details, and their application is carefully illustrated 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.

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