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Bayesia Graph Layout Engine
Powerful Graph Layout Algorithms available for your applications
With Bayesia Graph Layout Engine (BGLE), Bayesia allows you exploiting the power and the flexibility of genetic algorithms for the automatic layout of your graphs and the effectivemess of an original symmetric layout algorithm.
Genetic algorithm
The genetic algorithm of BGLE is extremely flexible since it will allow you describing your own criteria to define what a good graph layout for your application is. The examples below show the results of the automatic graph layout on BayesiaLab networks. The evaluation function used to describe a good network layout uses the following criteria:
- Nodes should not overlap
- Parents should be placed above their children
- No arc intersection with other arcs or nodes
- Arc should be as vertical as possible
- Arcs should have a given length
Symmetric algorithm
The symmetric algorithm uses repulsive and attrative forces to define the graph layout. It's a very effective algorithm that returns good graph layouts for moderately connected graphs.
More details
BGLE comes with an Application Program Interface (API) available as a pure Java class library (jar file).
We invite you to consult the Java Documentation and to try the automatic layout algorithm thanks to the Demonstration applet. This applet will allow you designing graphs, changing the size of the vertex, choosing some weights of the evaluation function and then launching the BGLE to see dynamically how the graph layout evolves.
Demonstration applet