Poisson Approval studies the Poisson Game of Approval Voting.

## Poisson Approval

Poisson Approval studies the Poisson Game of Approval Voting.

### 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.

## History

### 0.3.0 (2020-01-08)

• 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)

• 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.

### 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.