poisson-approval 0.5.0

Poisson Approval studies the Poisson Game of Approval Voting.

Poisson Approval

Poisson Approval studies the Poisson Game of Approval Voting.

• Free software: GNU General Public License v3

• Documentation: https://poisson-approval.readthedocs.io.

Features

• Implement only the case of 3 candidates.

• Deal with ordinal or cardinal profiles.

• Compute the asymptotic developments of the probability of pivot events when the number of players tends to infinity.

• Compute the best response to a given tau-vector.

• Explore automatically a grid of ordinal profiles or a grid of tau-vectors.

• Perform Monte-Carlo experiments on profiles or tau-vectors.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.5.0 (2020-01-11)

• In iterated voting, implement the possibility to move only progressively towards the best response:

  • Add ProfileCardinal.iterated_voting_taus: at each iteration, a given ratio of voters update their ballot.

  • Replace the former method ProfileCardinal.iterated_voting by ProfileCardinal.iterated_voting_strategies: as in former versions, at each iteration, the threshold utility of each ranking’s strategy is moved in the direction of the best response’s threshold utility. The method now returns a cycle of tau-vectors and the corresponding cycle of best response strategies, in order to be consistent with ProfileCardinal.iterated_voting_taus.

  • Add the utility barycenter: compute a barycenter while respecting the type of one input if the other input has weight 0.

  • Accelerate the algorithm used in iterated voting.

• In ProfileCardinal, add the possibility of partial sincere voting:

  • Add parameter ratio_sincere: ratio of sincere voters.

  • Add property tau_sincere: the tau-vector if all voters vote sincerely.

  • The former method tau is renamed tau_strategic: the tau_vector if all voters vote strategically.

  • The new method tau takes both sincere and strategic voting into account.

  • The method is_equilibrium has a new implementation to take this feature into account.

• Add TauVector.isclose: whether the tau-vector is close to another tau-vector (in the sense of math.isclose). This method is used by the new version of ProfileCardinal.is_equilibrium.

• Add Profile.best_responses_to_strategy: convert a dictionary of best responses to a StrategyThreshold that mentions only the rankings that are present in the profile.

• In random generators of profiles (GeneratorProfileOrdinalUniform, GeneratorProfileOrdinalGridUniform, GeneratorProfileOrdinalVariations, GeneratorProfileHistogramUniform): instead of having explicit arguments like well_informed_voters or ratio_sincere, there are **kwargs that are directly passed to the __init__ of the relevant Profile subclass.

• Update the tutorials with these new features.

0.4.0 (2020-01-08)

• Add image_distribution: estimate the distribution of f(something) for a random something.

• Update the tutorial on mass simulations with this new feature.

0.3.0 (2020-01-08)

• Add new random generators:

  • GeneratorExamples: run another generator until the generated object meets a given test.

  • GeneratorStrategyOrdinalUniform: draw a StrategyOrdinal uniformly.

  • GeneratorProfileOrdinalGridUniform: draw a ProfileOrdinal uniformly on a grid of rational numbers.

  • GeneratorTauVectorGridUniform: draw a TauVector uniformly on a grid of rational numbers.

• Utilities:

  • Add rand_integers_fixed_sum: draw an array of integers with a given sum.

  • Add rand_simplex_grid: draw a random point in the simplex, with rational coordinates of a given denominator.

  • Update probability: allow for a tuple of generators.

• Tutorials:

  • Add a tutorial on asymptotic developments.

  • Update the tutorial on mass simulations with the new features.

0.2.1 (2020-01-05)

• Relaunch deployment.

0.2.0 (2020-01-05)

• Add GeneratorProfileStrategyThreshold.

• Add ProfileHistogram.plot_cdf.

• Modify masks_distribution: remove the trailing zeros. This has the same impact on ProfileOrdinal.distribution_equilibria.

• Modify NiceStatsProfileOrdinal.plot_cutoff: center the textual indications.

• Replace all notations r with profile and sigma with strategy.

• Add tutorials.

0.1.1 (2019-12-24)

• Convert all the documentation to NumPy format, making it more readable in plain text.

0.1.0 (2019-12-20)

• First release on PyPI.

• Implement only the case of 3 candidates.

• Deal with ordinal or cardinal profiles.

• Compute the asymptotic developments of the probability of pivot events when the number of players tends to infinity.

• Compute the best response to a given tau-vector.

• Explore automatically a grid of ordinal profiles or a grid of tau-vectors.

• Perform Monte-Carlo experiments on profiles or tau-vectors.