ternary_plot_winning_frequencies

poisson_approval.ternary_plot_winning_frequencies(simplex_to_profile, scale, n_max_episodes, init='sincere', samples_per_point=1, perception_update_ratio=<function one_over_log_t_plus_one>, ballot_update_ratio=<function one_over_log_t_plus_one>, winning_frequency_update_ratio=<function one_over_log_t_plus_one>, title='Winning frequencies', legend_title='Winners', meth='fictitious_play', file_save_data=None, **kwargs)[source]

Shortcut: ternary plot for the winning frequencies in fictitious play / iterated voting.

Parameters

  • simplex_to_profile (SimplexToProfile) – This is responsible for generating the profiles.

  • scale (Number) – Scale of the plot (resolution).

  • n_max_episodes (int) – Maximum number of episodes for the fictitious play / iterated voting.

  • init (Strategy or TauVector or str) – Cf. fictitious_play() or iterated_voting().

  • samples_per_point (int) – How many trials are made for each point drawn. Useful only when initialization is random.

  • perception_update_ratio (callable or Number) – Cf. fictitious_play() or iterated_voting().

  • ballot_update_ratio (callable or Number) – Cf. fictitious_play() or iterated_voting().

  • winning_frequency_update_ratio (callable or Number) – Cf. fictitious_play() or iterated_voting().

  • title (str) – Title of the plot.

  • legend_title (str) – Title of the legend of the plot.

  • meth (str) – The name of the method ('fictitious_play' or 'iterated_voting').

  • file_save_data (str) – File where the computed data will be saved (using pickle).

  • kwargs – Other keyword arguments are passed to the function TernaryAxesSubplotPoisson.heatmap_candidates().

Examples

>>> simplex_to_profile = SimplexToProfile(
...     ProfileNoisyDiscrete,
...     left_type=('abc', 0.5, 0.01), right_type=('bac', 0.5, 0.01), top_type=('cab', 0.5, 0.01))
>>> figure, tax = ternary_plot_winning_frequencies(simplex_to_profile, scale=10, n_max_episodes=10)