TTK becomes officially integrated in ParaView! TTK version 1.0 is out!

after 7 years of development, we are proud to announce that the Topology ToolKit (TTK, https://topology-tool-kit.github.io/) will be officially integrated in ParaView (a major data analysis and visualization application, https://www.paraview.org/), as of version 5.10.

To celebrate this milestone, we have released the version 1.0 of TTK

Kudos to the entire TTK community!

Beyond a simpler installation, this release includes several new features:

- Wasserstein Distances, Geodesics, Barycenters of Merge Trees (IEEE VIS 2021)

- Progressive Scalar Field Topology (IEEE TVCG 2021)

- Improved Persistence diagram clustering features

- Direct LTS-based persistence sensitive simplification

- Various performance improvements (explicit triangulation, discrete Morse theory)

- Morphological modules

- Improved ZFP integration (fixed accuracy instead of fixed rate)

- Support for WebSocketIO (web browser interaction)

etc.

About

TTK can handle scalar data defined either on regular grids or triangulations, in 2D, 3D, or more. It provides a substantial collection of generic, efficient and robust implementations of key algorithms in topological data analysis. It includes:

- For scalar data: critical points, integral lines, persistence diagrams, persistence curves, merge trees, contour trees, Reeb graphs, Morse-Smale complexes, topological simplification, topology-aware compression, harmonic design;

- For bivariate scalar data: fibers, fiber surfaces, continuous scatterplots, Jacobi sets, Reeb spaces;

- For uncertain scalar data: mandatory critical points;

- For ensemble scalar data: Bottleneck and Wasserstein distances between persistence diagrams (exact Munkres-based computation or fast Auction-based approximation), Wasserstein barycenters and clusters of persistence diagrams (fast progressive algorithms) and merge trees, distance matrices (Lp norm, Wasserstein distances), contour tree alignment;

- For time-varying scalar data: critical point tracking, nested tracking graphs;

- For high-dimensional / point cloud data: dimension reduction, persistence-based clustering;

- and more!

If you need to robustly analyze your data, you may want to use TTK.

Check out our gallery page to see visualizations we obtained with TTK:

https://topology-tool-kit.github.io/gallery.html

TTK makes topological data analysis accessible to end users thanks to easy-to-use plugins for the data analysis and visualization application ParaView. Thanks to ParaView, TTK supports a variety of input data formats.

Check out our video tutorials to see TTK in action:

https://topology-tool-kit.github.io/tutorials.html

TTK is written in C++ but comes with a variety of bindings (VTK/C++, Python) and standalone command-line programs. It is modular and easy to extend.

We have specifically developed it such that you can easily write your own data analysis tools as TTK modules.

Check out our developer documentation:

https://topology-tool-kit.github.io/documentation.html

TTK is open-source (BSD license). You can use it at your convenience, for open-source or proprietary projects. You are also welcome to contribute.

Check out our contribution page:

https://topology-tool-kit.github.io/contribute.html

To try out TTK, checkout our installation instructions:

https://topology-tool-kit.github.io/installation.html

If you have questions, need support regarding the usage of TTK, or just want to provide feedback, thanks for sending us an email at topology.tool.kit@gmail.com

We hope you'll enjoy TTK!