class svvamp.RuleSTAR(**kwargs)[source]

STAR (Scoring Then Automatic Runoff).

Parameters:

  • min_grade (number) – Minimal grade allowed.

  • max_grade (number) – Maximal grade allowed.

  • step_grade (number) –

    Interval between two consecutive allowed grades.

    • If step_grade = 0, all grades in the interval [min_grade, max_grade] are allowed (‘continuous’ set of grades).

    • If step_grade > 0, authorized grades are the multiples of step_grade lying in the interval [min_grade, max_grade]. In addition, the grades min_grade and max_grade are always authorized, even if they are not multiples of step_grade.

  • rescale_grades (bool) –

    Whether sincere voters rescale their utilities to produce grades.

    • If rescale_grades = True, then each sincere voter v applies an affine transformation to send her utilities into the interval [min_grade, max_grade].

    • If rescale_grades = False, then each sincere voter v clips her utilities into the interval [min_grade, max_grade].

    See ballots for more details.

Options

>>> RuleSTAR.print_options_parameters()
cm_option: ['exact']. Default: 'exact'.
icm_option: ['exact']. Default: 'exact'.
iia_subset_maximum_size: is_number. Default: 2.
im_option: ['exact']. Default: 'exact'.
max_grade: isfinite. Default: 1.
min_grade: isfinite. Default: 0.
rescale_grades: is_bool. Default: True.
step_grade: isfinite. Default: 0.
tm_option: ['exact']. Default: 'exact'.
um_option: ['exact']. Default: 'exact'.

Notes

Each voter attributes a grade to each candidate. By default, authorized grades are all numbers in the interval [min_grade, max_grade]. To use a discrete set of notes, modify attribute step_grade.

The two candidates with highest average grades are selected for a virtual second round. During this second round, the two candidates are compared by majority voting: the score of one candidate is the number of voters who gave her a strictly larger grade than to the other candidate.

Default behavior of sincere voters: voter v applies an affine transformation to her utilities preferences_ut[v, :] to get her grades, such that her least-liked candidate receives min_grade and her most-liked candidate receives max_grade. To modify this behavior, use attribute rescale_grades. For more details about the behavior of sincere voters, see ballots.

  • is_cm_(), is_icm_(), is_im_(), is_tm_(), is_um_(): Exact in polynomial time.

STAR does not meets_majority_favorite_c_ut:

>>> profile = Profile(preferences_ut=[
...     [ 0. ,  0. ,  0. , -1. , -0.5,  0. ],
...     [ 0.5,  0.5,  0.5,  1. ,  0. , -1. ],
...     [ 0. , -0.5, -1. ,  1. , -1. , -1. ],
... ], preferences_rk=[
...     [2, 0, 5, 1, 4, 3],
...     [3, 0, 1, 2, 4, 5],
...     [3, 0, 1, 4, 5, 2],
... ])
>>> RuleSTAR()(profile).w_
0
>>> profile.majority_favorite_ut
3

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 = RuleSTAR()(profile)
>>> rule.demo_results_(log_depth=0)  

************************
*                      *
*   Election Results   *
*                      *
************************

***************
*   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 =
[[1.   0.5  0.  ]
 [1.   0.   0.75]
 [1.   1.   0.  ]
 [0.5  0.   1.  ]
 [0.   0.   1.  ]]
scores =
[[3.5  1.5  2.75]
 [3.   0.   2.  ]]
candidates_by_scores_best_to_worst
[0 2 1]
scores_best_to_worst
[[3.5  2.75 1.5 ]
 [3.   2.   0.  ]]
w = 0
score_w = [3.5 3. ]
total_utility_w = 1.0

*********************************
*   Condorcet efficiency (rk)   *
*********************************
w (reminder) = 0

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

condorcet_winner_rk = 0
w_is_condorcet_winner_rk = True
w_is_not_condorcet_winner_rk = False
w_missed_condorcet_winner_rk = False

***************************************
*   Condorcet efficiency (relative)   *
***************************************
w (reminder) = 0

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

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

***************************************
*   Condorcet efficiency (absolute)   *
***************************************
w (reminder) = 0

condorcet_admissible_candidates =
[ True False False]
w_is_condorcet_admissible = True
w_is_not_condorcet_admissible = False
w_missed_condorcet_admissible = False

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

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

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

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)  

*****************************
*                           *
*   Election Manipulation   *
*                           *
*****************************

*********************************************
*   Basic properties of the voting system   *
*********************************************
with_two_candidates_reduces_to_plurality =  False
is_based_on_rk =  False
is_based_on_ut_minus1_1 =  False
meets_iia =  False

****************************************************
*   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 (False)     ||
 ||           ||               ||       ||             ||         ||
 V            V                ||       ||             V          V
Condorcet_c_ut_abs_ctb (False)     ==>     Condorcet_ut_abs_c (False)
 ||                            ||       ||                        ||
 ||                            V        V                         ||
 ||       maj_fav_c_rk_ctb (False) ==> maj_fav_c_rk (False)       ||
 ||           ||                                       ||         ||
 V            V                                        V          V
majority_favorite_c_ut_ctb (False) ==> majority_favorite_c_ut (False)
 ||                                                               ||
 V                                                                V
IgnMC_c_ctb (True)                 ==>                IgnMC_c (True)
 ||                                                               ||
 V                                                                V
InfMC_c_ctb (True)                 ==>                InfMC_c (True)

*****************************************************
*   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

**********************
*   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]]

************************************
*   Individual Manipulation (IM)   *
************************************
is_im = False
log_im: im_option = exact
candidates_im =
[0. 0. 0.]

*********************************
*   Trivial Manipulation (TM)   *
*********************************
is_tm = False
log_tm: tm_option = exact
candidates_tm =
[0. 0. 0.]

********************************
*   Unison Manipulation (UM)   *
********************************
is_um = False
log_um: um_option = exact
candidates_um =
[0. 0. 0.]

*********************************************
*   Ignorant-Coalition Manipulation (ICM)   *
*********************************************
is_icm = False
log_icm: icm_option = exact
candidates_icm =
[0. 0. 0.]
necessary_coalition_size_icm =
[0. 6. 4.]
sufficient_coalition_size_icm =
[0. 6. 4.]

***********************************
*   Coalition Manipulation (CM)   *
***********************************
is_cm = False
log_cm: cm_option = exact
candidates_cm =
[0. 0. 0.]
necessary_coalition_size_cm =
[0. 3. 3.]
sufficient_coalition_size_cm =
[0. 3. 3.]
property candidates_by_scores_best_to_worst_

1d array of integers. candidates_by_scores_best_to_worst[k] is the candidate with k-th best score. Finalists are sorted by their score at second round. Other candidates are sorted by their score at first round.

property scores_

2d array of numbers. scores_[0, c] is the total grade of candidate c. scores_[1, c] the number of voters who vote for c during the second round (and 0 if c is not selected for the second round).

property w_

Integer (winning candidate).

Default behavior: the candidate with highest value in vector scores_ is declared the winner. In case of a tie, the tied candidate with lowest index wins.