IterableProfileTwelveGrid

class poisson_approval.IterableProfileTwelveGrid(denominator, types=None, d_type_fixed_share=None, standardized=False, test=None, **kwargs)[source]

Iterate over twelve-type profiles (ProfileTwelve) defined on a grid.

Parameters:
  • denominator (int or iterable) – The grain(s) of the grid.
  • types (iterable, optional) – These types will have a variable share. They can be twelve-like types, e.g. 'a_bc' or 'ab_c', or weak orders, e.g. 'a~b>c'. Default: all twelve-like types.
  • d_type_fixed_share (dict, optional) – A dictionary. For each entry type: fixed_share, this type will have at least this fixed share. The total must be lower or equal to 1.
  • standardized (bool, optional) – If True, then only standardized profiles are given. Cf. Profile.is_standardized(). You should probably use this option if the arguments types, d_type_fixed_share and test treat the candidates symmetrically.
  • test (callable, optional) – A function ProfileTwelve -> bool. Only profiles meeting this test are given.
  • kwargs – Additional parameters are passed to ProfileTwelve when creating the profile.

Examples

Basic usage:

>>> for profile in IterableProfileTwelveGrid(denominator=3, types=['a_bc', 'bc_a', 'a~b>c']):
...     print(profile)
<a_bc: 1> (Condorcet winner: a)
<a_bc: 2/3, bc_a: 1/3> (Condorcet winner: a)
<a_bc: 2/3, a~b>c: 1/3> (Condorcet winner: a)
<a_bc: 1/3, bc_a: 2/3> (Condorcet winner: b)
<a_bc: 1/3, bc_a: 1/3, a~b>c: 1/3> (Condorcet winner: a, b)
<a_bc: 1/3, a~b>c: 2/3> (Condorcet winner: a)
<bc_a: 1> (Condorcet winner: b)
<bc_a: 2/3, a~b>c: 1/3> (Condorcet winner: b)
<bc_a: 1/3, a~b>c: 2/3> (Condorcet winner: b)
<a~b>c: 1> (Condorcet winner: a, b)

For more examples, cf. IterableSimplexGrid.