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

[Julien J Tierny]

Dear colleagues,

(sorry for cross-posting)

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...@gmail.com

We hope you'll enjoy TTK!
--
Dr Julien Tierny
CNRS Researcher
Sorbonne Universite
http://lip6.fr/Julien.Tierny