A python library that uses simulated annealing and gradient descent to find the most visually appealing configuration of a given graph.
Configurable to graphs of any number of vertices and edges.
Made simple for developers to implement and run the algorithms with their existing graphs.
WHAT I DID
- Implemented the Simulated Annealing and Gradient Descent algorithms.
- Designed the heuristics for the cost function.
- Created a wrapper for the algorithm for developer ease of use.