plot_utility_thresholds

poisson_approval.plot_utility_thresholds(results, voting_rule=None, **kwargs)[source]

Plot the distribution (CDF) of the utility threshold.

Parameters

results (dict) – Results of monte_carlo_fictitious_play(), with at least the setting MCS_UTILITY_THRESHOLDS.
voting_rule (str) – The voting rule (or None if this parameter was not given to monte_carlo_fictitious_play()).
kwargs – Other keyword arguments are passed to the function step of matplotlib.

Examples

>>> meta_results = monte_carlo_fictitious_play(
...     factory=RandProfileHistogramUniform(n_bins=1),
...     n_samples=1,
...     n_max_episodes=10,
...     monte_carlo_settings=[MCS_UTILITY_THRESHOLDS],
... )
>>> plot_utility_thresholds(meta_results)