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Large graphs analysis and drawing

Project description

Module description

Graphs play an important role in many research areas, such as biology, microelectronics, social sciences, data mining, and computer science. Tulip ( [1] [2] [3] is an Information Visualization framework dedicated to the analysis and visualization of such relational data. Written in C++ the framework enables the development of algorithms, visual encodings, interaction techniques, data models, and domain-specific visualizations.

The Tulip core library is available to the Python community through the Tulip-Python bindings [4]. The bindings have been developed using the SIP tool [5] from Riverbank Computed Limited, allowing to easily create quality Python bindings for any C/C++ library. The main features provided by the bindings are the following ones:

  • Creation and manipulation of graphs : Tulip provides an efficient graph data structure for storing large and complex networks. It is also one of the few that offer the possibility to efficiently define and navigate graph hierarchies or cluster trees (nested subgraphs).

  • Storage of data on graph elements : Tulip allows to associate different kind of serializable data (boolean, integer, float, string, …) and visual attributes (layout, color, size, …) to graph elements. All these data can be easily accessed from the Tulip graph data structure facilitating the development of algorithms.

  • Application of algorithms of different types on graph : Tulip has been designed to be easily extensible and provides a variety of graph algorithms (layout, metric, clustering, …) implemented as C++ plugins. All these algorithms can be called from Python. As Tulip is dedicated to graph visualization, it is provided with numerous state of the art graph layout algorithms but also a bridge to the Open Graph Drawing Framework ( [6]


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