Source code for svvamp.rules.rule_condorcet_sum_defeats

# -*- coding: utf-8 -*-
"""
Created on 4 dec. 2018, 16:00
Copyright François Durand 2014-2018
fradurand@gmail.com

This file is part of SVVAMP.

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    it under the terms of the GNU General Public License as published by
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    SVVAMP is distributed in the hope that it will be useful,
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    along with SVVAMP.  If not, see <http://www.gnu.org/licenses/>.
"""
import numpy as np
from svvamp.rules.rule import Rule
from svvamp.utils.util_cache import cached_property
from svvamp.preferences.profile import Profile


[docs] class RuleCondorcetSumDefeats(Rule): """Condorcet with sum of defeats. Options ------- >>> RuleCondorcetSumDefeats.print_options_parameters() cm_option: ['lazy', 'exact']. Default: 'lazy'. icm_option: ['lazy']. Default: 'lazy'. iia_subset_maximum_size: is_number. Default: 2. im_option: ['lazy', 'exact']. Default: 'lazy'. tm_option: ['lazy', 'exact']. Default: 'exact'. um_option: ['lazy', 'exact']. Default: 'lazy'. Notes ----- An *elementary move* consists of reversing a voter's preference about a pair of candidate ``(c, d)`` (without demanding that her whole relation of preference stays transitive). The score for candidate ``c`` is minus the number of *elementary moves* needed so that ``c`` becomes a Condorcet winner. It is the same principle as Dodgson's method, but without looking for a transitive profile. In practice: .. math:: \\texttt{scores}[c] = - \\sum_{c \\text{ does not beat } d}\\left( \\left\\lfloor\\frac{V}{2}\\right\\rfloor + 1 - \\texttt{matrix_duels_rk}[c, d] \\right) In particular, for :attr:`n_v` odd: .. math:: \\texttt{scores}[c] = - \\sum_{c \\text{ does not beat } d}\\left( \\left\\lceil\\frac{V}{2}\\right\\rceil - \\texttt{matrix_duels_rk}[c, d] \\right) * :meth:`is_cm_`: Non-polynomial or non-exact algorithms from superclass :class:`Rule`. * :meth:`is_icm_`: Algorithm from superclass :class:`Rule`. It is polynomial and has a window of error of 1 manipulator. * :meth:`is_im_`: Non-polynomial or non-exact algorithms from superclass :class:`Rule`. * :meth:`is_iia_`: Non-polynomial or non-exact algorithms from superclass :class:`Rule`. If :attr:`iia_subset_maximum_size` = 2, it runs in polynomial time and is exact up to ties (which can occur only if :attr:`n_v` is even). * :meth:`is_tm_`: Exact in polynomial time. * :meth:`is_um_`: Non-polynomial or non-exact algorithms from superclass :class:`Rule`. Examples -------- >>> profile = Profile(preferences_ut=[ ... [ 0. , -0.5, -1. ], ... [ 1. , -1. , 0.5], ... [ 0.5, 0.5, -0.5], ... [ 0.5, 0. , 1. ], ... [-1. , -1. , 1. ], ... ], preferences_rk=[ ... [0, 1, 2], ... [0, 2, 1], ... [1, 0, 2], ... [2, 0, 1], ... [2, 1, 0], ... ]) >>> rule = RuleCondorcetSumDefeats()(profile) >>> rule.demo_results_(log_depth=0) # doctest: +NORMALIZE_WHITESPACE <BLANKLINE> ************************ * * * Election Results * * * ************************ <BLANKLINE> *************** * Results * *************** profile_.preferences_ut (reminder) = [[ 0. -0.5 -1. ] [ 1. -1. 0.5] [ 0.5 0.5 -0.5] [ 0.5 0. 1. ] [-1. -1. 1. ]] profile_.preferences_rk (reminder) = [[0 1 2] [0 2 1] [1 0 2] [2 0 1] [2 1 0]] ballots = [[0 1 2] [0 2 1] [1 0 2] [2 0 1] [2 1 0]] scores = [-0. -2. -1.] candidates_by_scores_best_to_worst [0 2 1] scores_best_to_worst [-0. -1. -2.] w = 0 score_w = -0.0 total_utility_w = 1.0 <BLANKLINE> ********************************* * Condorcet efficiency (rk) * ********************************* w (reminder) = 0 <BLANKLINE> condorcet_winner_rk_ctb = 0 w_is_condorcet_winner_rk_ctb = True w_is_not_condorcet_winner_rk_ctb = False w_missed_condorcet_winner_rk_ctb = False <BLANKLINE> condorcet_winner_rk = 0 w_is_condorcet_winner_rk = True w_is_not_condorcet_winner_rk = False w_missed_condorcet_winner_rk = False <BLANKLINE> *************************************** * Condorcet efficiency (relative) * *************************************** w (reminder) = 0 <BLANKLINE> condorcet_winner_ut_rel_ctb = 0 w_is_condorcet_winner_ut_rel_ctb = True w_is_not_condorcet_winner_ut_rel_ctb = False w_missed_condorcet_winner_ut_rel_ctb = False <BLANKLINE> condorcet_winner_ut_rel = 0 w_is_condorcet_winner_ut_rel = True w_is_not_condorcet_winner_ut_rel = False w_missed_condorcet_winner_ut_rel = False <BLANKLINE> *************************************** * Condorcet efficiency (absolute) * *************************************** w (reminder) = 0 <BLANKLINE> condorcet_admissible_candidates = [ True False False] w_is_condorcet_admissible = True w_is_not_condorcet_admissible = False w_missed_condorcet_admissible = False <BLANKLINE> weak_condorcet_winners = [ True False False] w_is_weak_condorcet_winner = True w_is_not_weak_condorcet_winner = False w_missed_weak_condorcet_winner = False <BLANKLINE> condorcet_winner_ut_abs_ctb = 0 w_is_condorcet_winner_ut_abs_ctb = True w_is_not_condorcet_winner_ut_abs_ctb = False w_missed_condorcet_winner_ut_abs_ctb = False <BLANKLINE> condorcet_winner_ut_abs = 0 w_is_condorcet_winner_ut_abs = True w_is_not_condorcet_winner_ut_abs = False w_missed_condorcet_winner_ut_abs = False <BLANKLINE> resistant_condorcet_winner = nan w_is_resistant_condorcet_winner = False w_is_not_resistant_condorcet_winner = True w_missed_resistant_condorcet_winner = False >>> rule.demo_manipulation_(log_depth=0) # doctest: +NORMALIZE_WHITESPACE <BLANKLINE> ***************************** * * * Election Manipulation * * * ***************************** <BLANKLINE> ********************************************* * Basic properties of the voting system * ********************************************* with_two_candidates_reduces_to_plurality = True is_based_on_rk = True is_based_on_ut_minus1_1 = False meets_iia = False <BLANKLINE> **************************************************** * Manipulation properties of the voting system * **************************************************** Condorcet_c_ut_rel_ctb (False) ==> Condorcet_c_ut_rel (False) || || || Condorcet_c_rk_ctb (False) ==> Condorcet_c_rk (True) || || || || || || || V V || || V V Condorcet_c_ut_abs_ctb (False) ==> Condorcet_ut_abs_c (True) || || || || || V V || || maj_fav_c_rk_ctb (False) ==> maj_fav_c_rk (True) || || || || || V V V V majority_favorite_c_ut_ctb (False) ==> majority_favorite_c_ut (True) || || V V IgnMC_c_ctb (False) ==> IgnMC_c (True) || || V V InfMC_c_ctb (True) ==> InfMC_c (True) <BLANKLINE> ***************************************************** * Independence of Irrelevant Alternatives (IIA) * ***************************************************** w (reminder) = 0 is_iia = True log_iia: iia_subset_maximum_size = 2.0 example_winner_iia = nan example_subset_iia = nan <BLANKLINE> ********************** * c-Manipulators * ********************** w (reminder) = 0 preferences_ut (reminder) = [[ 0. -0.5 -1. ] [ 1. -1. 0.5] [ 0.5 0.5 -0.5] [ 0.5 0. 1. ] [-1. -1. 1. ]] v_wants_to_help_c = [[False False False] [False False False] [False False False] [False False True] [False False True]] <BLANKLINE> ************************************ * Individual Manipulation (IM) * ************************************ is_im = nan log_im: im_option = lazy candidates_im = [ 0. 0. nan] <BLANKLINE> ********************************* * Trivial Manipulation (TM) * ********************************* is_tm = False log_tm: tm_option = exact candidates_tm = [0. 0. 0.] <BLANKLINE> ******************************** * Unison Manipulation (UM) * ******************************** is_um = nan log_um: um_option = lazy candidates_um = [ 0. 0. nan] <BLANKLINE> ********************************************* * Ignorant-Coalition Manipulation (ICM) * ********************************************* is_icm = False log_icm: icm_option = lazy candidates_icm = [0. 0. 0.] necessary_coalition_size_icm = [0. 6. 4.] sufficient_coalition_size_icm = [0. 6. 4.] <BLANKLINE> *********************************** * Coalition Manipulation (CM) * *********************************** is_cm = nan log_cm: cm_option = lazy, um_option = lazy, tm_option = exact candidates_cm = [ 0. 0. nan] necessary_coalition_size_cm = [0. 1. 1.] sufficient_coalition_size_cm = [0. 2. 3.] """ full_name = 'Condorcet Sum Defeats' abbreviation = 'CSD' options_parameters = Rule.options_parameters.copy() def __init__(self, **kwargs): super().__init__( with_two_candidates_reduces_to_plurality=True, is_based_on_rk=True, precheck_icm=False, log_identity="CONDORCET_SUM_DEFEATS", **kwargs ) @cached_property def scores_(self): """1d array of integers. .. math:: \\texttt{scores}[c] = - \\sum_{c \\text{ does not beat } d}\\left( \\left\\lfloor\\frac{V}{2}\\right\\rfloor + 1 - \\texttt{matrix_duels_rk}[c, d] \\right) """ self.mylog("Compute scores", 1) scores = np.zeros(self.profile_.n_c) for c in range(self.profile_.n_c): scores[c] = - np.sum(np.floor(self.profile_.n_v / 2) + 1 - self.profile_.matrix_duels_rk[c, self.profile_.matrix_victories_rk[:, c] > 0]) return scores @cached_property def meets_condorcet_c_rk(self): return True @cached_property def meets_infmc_c_ctb(self): return True