Poisson Approval studies the Poisson Game of Approval Voting.
Project description
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
0.3.0 (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.
Project details
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