So far, only the core utility logic and backend GUI are implemented. The EloEverything-style ranking interface isn't implemented yet.
Run gui.py to play with the algorithm.

To use elo_optimizer.py from your own file:

• Import it. It is a stateful module with globals:

  ITEMS: list[Item]  
  LOTTERIES: list[Lottery]  
  RESULTS: list[Result]  
  PARAMETERS: list[torch.Tensor]  
  MODE = "compound" # "compound" or "overwrite" (mode for adding results for pairs that have already been played)  
  

• Interact with it as follows:

  • Use the Item() and Lottery() constructors to create items and lotteries
  • Use add_result() to add results (don't use the Result constuctor directly)
  • Items, Lotteries, and Results have delete() methods. The delete() method removes an object, its dependents, and its parameters from global lists.
  • Call optimization methods as needed to recompute the best fit utilities and temperatures. Currently only full_batch_optimize() exists.
  • Interact directly with the global lists for other operations