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
.