martinlackner/abcvoting

AI Summary: Implement functions to calculate the proportionality degree of a committee, including both the standard and '+' variants, within the existing abcvoting Python library. This involves determining appropriate placement within the library's structure (scoring or properties) and potentially adding new functions or modifying existing ones.

AI Summary: Optimize the `full_analysis` function in the abcvoting Python library by leveraging logical implications between axiomatic properties to reduce redundant computations. This involves incorporating existing implication tests into the main function to avoid unnecessary checks.

AI Summary: Implement a function or method within the abcvoting Python library to compute the smallest quota for which specific proportionality properties (JR, EJR+, PJR, EJR, FJR, core) are satisfied for a given committee election. This involves modifying existing algorithms or integrating with the ILP solver to find the optimal quota value. The output should indicate the smallest quota and whether the property holds for that quota.

AI Summary: Integrate the PULP linear programming solver into the abcvoting Python library as an alternative to the currently used MIP solver, enhancing the library's functionality and robustness.