import numpy as np
from embedded_voting.rules.singlewinner_rules.rule import Rule
from embedded_voting.ratings.ratings import Ratings
[docs]class RuleApprovalProduct(Rule):
"""
Voting rule in which the score of a candidate is the number of approval (vote greater than 0)
that it gets. Ties are broken by the product of the positive ratings.
More precisely, her score is a tuple whose components are:
* The number of her nonzero ratings.
* The product of her nonzero ratings.
Note that this rule is well suited only if ratings are nonnegative.
No embeddings are used for this rule.
Parameters
----------
embeddings_from_ratings: EmbeddingsFromRatings
If no embeddings are specified in the call, this `EmbeddingsFromRatings` object is use to generate
the embeddings from the ratings. Default: `EmbeddingsFromRatingsIdentity()`.
Examples
--------
>>> ratings = Ratings(np.array([[.5, .6, .3], [.7, 0, .2], [.2, 1, .8]]))
>>> election = RuleApprovalProduct()(ratings)
>>> election.scores_
[(3, 0.06999999999999999), (2, 0.6), (3, 0.048)]
>>> election.ranking_
[0, 2, 1]
>>> election.winner_
0
>>> election.welfare_
[1.0, 0.0, 0.6857142857142858]
"""
def __init__(self, embeddings_from_ratings=None):
super().__init__(score_components=2, embeddings_from_ratings=embeddings_from_ratings)
def _score_(self, candidate):
candidate_ratings = self.ratings_.candidate_ratings(candidate)
mask = candidate_ratings > 0
n_nonzero_ratings = np.sum(mask)
prod_nonzero_ratings = np.prod(candidate_ratings[mask])
return n_nonzero_ratings, prod_nonzero_ratings