from poisson_approval.constants.basic_constants import *
from poisson_approval.iterables.IterableSimplexGrid import IterableSimplexGrid
from poisson_approval.profiles.ProfileNoisyDiscrete import ProfileNoisyDiscrete
[docs]class IterableProfileNoisyDiscreteGrid:
"""Iterate over noisy discrete profiles (:class:`ProfileNoisyDiscrete`) defined on a grid.
Parameters
----------
denominator : int or iterable
The grain(s) of the grid.
types : iterable
These types will have a variable share. They can be noisy discrete types, e.g. ``('abc', 0.9, 0.01)``,
or discrete types, e.g. ``('abc', 0.9)`` (in which case the argument `noise` must be given in the additional
parameters), or weak orders, e.g. ``'a~b>c'``.
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. :meth:`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 ``ProfileNoisyDiscrete -> bool``. Only profiles meeting this test are given.
kwargs
Additional parameters are passed to :class:`ProfileNoisyDiscrete` when creating the profile.
Examples
--------
Basic usage:
>>> for profile in IterableProfileNoisyDiscreteGrid(denominator=3, types=[('abc', 0.9, 0.01), 'a~b>c']):
... print(profile)
<abc 0.9 ± 0.01: 1> (Condorcet winner: a)
<abc 0.9 ± 0.01: 2/3, a~b>c: 1/3> (Condorcet winner: a)
<abc 0.9 ± 0.01: 1/3, a~b>c: 2/3> (Condorcet winner: a)
<a~b>c: 1> (Condorcet winner: a, b)
Or, equivalently:
>>> for profile in IterableProfileNoisyDiscreteGrid(denominator=3, types=[('abc', 0.9), 'a~b>c'], noise=0.01):
... print(profile)
<abc 0.9 ± 0.01: 1> (Condorcet winner: a)
<abc 0.9 ± 0.01: 2/3, a~b>c: 1/3> (Condorcet winner: a)
<abc 0.9 ± 0.01: 1/3, a~b>c: 2/3> (Condorcet winner: a)
<a~b>c: 1> (Condorcet winner: a, b)
For more examples, cf. :class:`IterableSimplexGrid`.
"""
def __init__(self, denominator, types, d_type_fixed_share=None, standardized=False, test=None, **kwargs):
self.standardized = standardized
self._base_iterator = IterableSimplexGrid(cls=ProfileNoisyDiscrete, denominator=denominator, keys=types,
d_key_fixed_share=d_type_fixed_share, test=test, **kwargs)
def __iter__(self):
return (profile for profile in self._base_iterator
if not self.standardized or profile.is_standardized)