From f31f87e397ade8cc08ac5c7bba3babaa03908ab1 Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Sun, 31 May 2026 15:15:45 +0300 Subject: [PATCH 1/8] Add Exact Equal Shares (EES) with add-opt rule --- pabutools/rules/__init__.py | 12 +- pabutools/rules/ees_addopt.py | 510 +++++++++++++++++++++++++++++++++ tests/rules/test_ees_addopt.py | 388 +++++++++++++++++++++++++ 3 files changed, 909 insertions(+), 1 deletion(-) create mode 100644 pabutools/rules/ees_addopt.py create mode 100644 tests/rules/test_ees_addopt.py diff --git a/pabutools/rules/__init__.py b/pabutools/rules/__init__.py index 3884e23..54f6636 100644 --- a/pabutools/rules/__init__.py +++ b/pabutools/rules/__init__.py @@ -40,6 +40,12 @@ ) from pabutools.rules.cstv import cstv, CSTV_Combination from pabutools.rules.maximin_support import maximin_support +from pabutools.rules.ees_addopt import ( + exact_equal_shares, + greedy_project_change, + add_opt, + EESAllocationDetails, +) __all__ = [ "completion_by_rule_combination", @@ -57,5 +63,9 @@ "MESIteration", "cstv", "CSTV_Combination", - "maximin_support" + "maximin_support", + "exact_equal_shares", + "greedy_project_change", + "add_opt", + "EESAllocationDetails", ] diff --git a/pabutools/rules/ees_addopt.py b/pabutools/rules/ees_addopt.py new file mode 100644 index 0000000..23bee82 --- /dev/null +++ b/pabutools/rules/ees_addopt.py @@ -0,0 +1,510 @@ +""" +An implementation of the algorithms in "Streamlining Equal Shares", +by Sonja Kraiczy, Isaac Robinson, Edith Elkind (2024), +https://arxiv.org/abs/2502.11797 + +Programmer: Yonatan Gabay +Date: 20-04-2026 +""" + +from __future__ import annotations + +from pabutools.election.instance import Instance, Project +from pabutools.election.profile import AbstractApprovalProfile +from pabutools.fractions import frac +from pabutools.rules.budgetallocation import BudgetAllocation, AllocationDetails +from pabutools.tiebreaking import lexico_tie_breaking +from pabutools.utils import Numeric + + +class EESAllocationDetails(AllocationDetails): + """ + Details of an EES rule run, storing per-voter payments. + + Attributes + ---------- + payments : dict[int, dict[Project, Numeric]] + payments[voter_index][project] = amount paid by voter for the project. + """ + + def __init__(self, payments: dict[int, dict[Project, Numeric]] | None = None): + super().__init__() + self.payments: dict[int, dict[Project, Numeric]] = payments if payments is not None else {} + + def __repr__(self): + return f"EESAllocationDetails[payments={self.payments}]" + + +def exact_equal_shares( + instance: Instance, + profile: AbstractApprovalProfile, + utilities: dict[Project, Numeric] | None = None, +) -> BudgetAllocation: + """ + Algorithm 1: EES for uniform utilities. + + Iteratively selects projects that maximise bang-per-buck (|V|·u(p)/cost(p)) + among all feasible (project, supporter-subset) pairs, splitting costs + equally among supporters. + + Parameters + ---------- + instance : :py:class:`~pabutools.election.instance.Instance` + The instance containing the projects and the budget limit. + profile : :py:class:`~pabutools.election.profile.approvalprofile.AbstractApprovalProfile` + The approval profile, one ballot per voter. + utilities : dict[:py:class:`~pabutools.election.instance.Project`, Numeric] or None + utilities[project] = u(p). When None, every project has utility 1 + (pure approval setting). + + Returns + ------- + :py:class:`~pabutools.rules.budgetallocation.BudgetAllocation` + The selected projects (in order of selection). The + :py:attr:`~pabutools.rules.budgetallocation.BudgetAllocation.details` attribute + is an :py:class:`EESAllocationDetails` holding per-voter payments. + + Examples + -------- + >>> from pabutools.election import Instance, Project, ApprovalProfile, ApprovalBallot + >>> p1, p2, p3 = Project("p1", 10), Project("p2", 16), Project("p3", 21) + >>> inst = Instance([p1, p2, p3], budget_limit=40) + >>> prof = ApprovalProfile([ + ... ApprovalBallot([p1]), + ... ApprovalBallot([p1, p3]), + ... ApprovalBallot([p2, p3]), + ... ApprovalBallot([p2, p3]), + ... ], instance=inst) + >>> result = exact_equal_shares(inst, prof) + >>> [p.name for p in result] + ['p1', 'p2'] + """ + n = len(profile) + if n == 0: + return BudgetAllocation(details=EESAllocationDetails()) + + b = instance.budget_limit + + # Line 1: W = ∅, X = 0^{n·m}, r_i = b/n for all i ∈ N + W: list[Project] = [] + selected_set: set[Project] = set() + payments: dict[int, dict[Project, Numeric]] = {i: {} for i in range(n)} + r: list[Numeric] = [frac(b) / n] * n + + # Maintain a globally sorted list of voters by remaining budget. + # Filtering this list to a project's supporters preserves sorted order + # in O(n), avoiding an O(n log n) sort per project per iteration. + sorted_voters: list[int] = list(range(n)) # all equal initially + + # Line 2: while true do + while True: + best_score: Numeric = -1 + best_candidates: list[tuple[Project, list[int]]] = [] + + # Line 3: Φ = {(p ∈ P\W, V ⊆ N_p) | r_i ≥ cost(p)/|V| ∀i ∈ V} + # For each project, find the largest feasible supporter subset V. + for p in instance: + if p in selected_set: + continue + + u_p = utilities[p] if utilities is not None else 1 + + # N_p: voters who approve p, filtered from sorted_voters (preserves order) + supporters = [i for i in sorted_voters if p in profile[i]] + if not supporters: + continue + + # Greedily remove the poorest voter while they can't afford + # their equal share cost(p)/|V|. + while supporters and r[supporters[0]] < frac(p.cost) / len(supporters): + supporters.pop(0) + + if not supporters: + continue + + # Line 8: score = |V|·u(p) / cost(p) + if p.cost == 0: + score = float('inf') + else: + score = frac(len(supporters) * u_p) / p.cost + if score > best_score: + best_score = score + best_candidates = [(p, supporters)] + elif score == best_score: + best_candidates.append((p, supporters)) + + # Line 4-5: if Φ = ∅ then return (W, X) + if not best_candidates: + return BudgetAllocation(W, details=EESAllocationDetails(payments)) + + # Line 9: Choose (p*, V*) from Φ* using tiebreaking (p* ◁ p) + # Use untie() (first/smallest name) so that unselected tied projects + # have larger names. The leximax (amount, selected_name) will then + # NOT exceed (amount, unselected_name) under Python's default tuple + # comparison, preventing spurious instability certificates. + if len(best_candidates) == 1: + p_star, V_star = best_candidates[0] + else: + tied_projects = [p for p, _ in best_candidates] + p_star = lexico_tie_breaking.untie(instance, profile, tied_projects) + V_star = next(V for p, V in best_candidates if p == p_star) + + # Line 10: W = W ∪ {p*} + W.append(p_star) + selected_set.add(p_star) + + # Line 11: x_{i,p*} = cost(p*)/|V*|, r_i = r_i − cost(p*)/|V*| ∀i ∈ V* + V_star_set = set(V_star) + payment = frac(p_star.cost) / len(V_star) + for i in V_star: + payments[i][p_star] = payment + r[i] -= payment + + # Update sorted_voters via O(n) merge. All V* voters decreased by + # the same amount so their relative order is preserved. + changed = [i for i in sorted_voters if i in V_star_set] + unchanged = [i for i in sorted_voters if i not in V_star_set] + merged: list[int] = [] + ci, ui = 0, 0 + while ci < len(changed) and ui < len(unchanged): + if r[changed[ci]] <= r[unchanged[ui]]: + merged.append(changed[ci]); ci += 1 + else: + merged.append(unchanged[ui]); ui += 1 + merged.extend(changed[ci:]) + merged.extend(unchanged[ui:]) + sorted_voters = merged + + +def get_leftover_budgets( + instance: Instance, + profile: AbstractApprovalProfile, + current_solution: BudgetAllocation, +) -> dict[int, Numeric]: + """ + Compute leftover budget for each voter. + + leftover[i] = b/n - sum of payments by voter i across all selected projects. + """ + n = len(profile) + b = instance.budget_limit + details: EESAllocationDetails = current_solution.details + leftover = {} + for i in range(n): + paid = sum(details.payments.get(i, {}).values()) + leftover[i] = frac(b) / n - paid + return leftover + + +def get_leximax_payment( + current_solution: BudgetAllocation, + voter: int, + instance: Instance, +) -> tuple[Numeric, str]: + """ + Return the leximax payment of a voter as ``(amount, project_name)``. + + The leximax payment c_i = (x_i, p_i) where x_i is the maximum payment + and p_i is the project with that payment that comes first in the total + order ⊲ (alphabetical by name, i.e. smallest name). When the voter + made no payments, x_i = 0 and p_i is the first project in ⊲ + (smallest name), so that non-paying voters never certify instability. + """ + details: EESAllocationDetails = current_solution.details + voter_payments = details.payments.get(voter, {}) + if not voter_payments: + min_project_name = min(p.name for p in instance) + return (0, min_project_name) + max_amount = max(voter_payments.values()) + max_projects = [p for p, v in voter_payments.items() if v == max_amount] + min_project = min(max_projects, key=lambda p: p.name) + return (max_amount, min_project.name) + + +def greedy_project_change( + instance: Instance, + profile: AbstractApprovalProfile, + current_solution: BudgetAllocation, + project: Project, + leftover: dict[int, Numeric], + leximax: dict[int, tuple[Numeric, str]], + voters_by_leftover: list[int] | None = None, + voters_by_leximax: list[int] | None = None, +) -> Numeric: + """ + Algorithm 2: GreedyProjectChange (GPC). + + Computes the minimum per-voter budget increase d > 0 such that + *project* certifies instability of the current equal-shares solution + for instance E(b + n·d). + The algorithm walks two sorted arrays simultaneously: + - leftover_budgets (A'): residual budgets of Op(X) voters, sorted ascending. + - leximax_payments (B'): leximax payment vectors of Op(X) voters, + sorted lex-ascending. + + Parameters + ---------- + instance : :py:class:`~pabutools.election.instance.Instance` + The instance containing the projects and the budget limit. + profile : :py:class:`~pabutools.election.profile.approvalprofile.AbstractApprovalProfile` + The approval profile, one ballot per voter. + current_solution : :py:class:`~pabutools.rules.budgetallocation.BudgetAllocation` + The current EES solution. Its + :py:attr:`~pabutools.rules.budgetallocation.BudgetAllocation.details` attribute + must be an :py:class:`EESAllocationDetails` holding per-voter payments. + project : :py:class:`~pabutools.election.instance.Project` + The candidate project p to test instability for. + leftover : dict[int, Numeric] + Leftover budget per voter, as returned by + :py:func:`get_leftover_budgets`. + leximax : dict[int, tuple[Numeric, str]] + Leximax payment per voter, as returned by + :py:func:`get_leximax_payment`. + voters_by_leftover : list[int] or None + All voters pre-sorted by leftover ascending. When provided the + function filters this list to O_p(X) in O(n) instead of sorting + per project. Used by :py:func:`add_opt` for O(mn) total. + voters_by_leximax : list[int] or None + All voters pre-sorted by leximax ascending. + + Returns + ------- + Numeric + Minimum per-voter budget increase d. + + Examples + -------- + >>> from pabutools.election import Instance, Project, ApprovalProfile, ApprovalBallot + >>> p1, p2, p3 = Project("p1", 2), Project("p2", 3.2), Project("p3", 6) + >>> inst = Instance([p1, p2, p3], budget_limit=10) + >>> prof = ApprovalProfile([ + ... ApprovalBallot([p1]), + ... ApprovalBallot([p1, p3]), + ... ApprovalBallot([p2, p3]), + ... ApprovalBallot([p2, p3]), + ... ApprovalBallot([p3]), + ... ], instance=inst) + >>> details = EESAllocationDetails({0: {p1: 1}, 1: {p1: 1}, 2: {p2: 1.6}, 3: {p2: 1.6}, 4: {}}) + >>> solution = BudgetAllocation([p1, p2], details=details) + >>> leftover = get_leftover_budgets(inst, prof, solution) + >>> leximax = {i: get_leximax_payment(solution, i, inst) for i in range(5)} + >>> greedy_project_change(inst, prof, solution, p3, leftover, leximax) + 0.5 + """ + n = len(profile) + p = project + + # All voters who approve p + all_supporters = {i for i in range(n) if p in profile[i]} + + # N_p(X): voters who pay for project p in the current solution + details: EESAllocationDetails = current_solution.details + N_p_X = {i for i in all_supporters if p in details.payments.get(i, {})} + # O_p(X) = N_p \ N_p(X): voters who approve p but don't pay for it + O_p_X = all_supporters - N_p_X + + # O_p(X) sorted by leftover budget ascending: v_1, ..., v_k + if voters_by_leftover is not None: + O_p = [i for i in voters_by_leftover if i in O_p_X] + else: + O_p = sorted(O_p_X, key=lambda i: leftover[i]) + k = len(O_p) + + # Leximax payments of O_p(X) voters, sorted ascending: w_1, ..., w_k + if voters_by_leximax is not None: + O_p_by_leximax = [i for i in voters_by_leximax if i in O_p_X] + else: + O_p_by_leximax = sorted(O_p_X, key=lambda i: leximax[i]) + + # Line 1: i, j ← 1, 1 (1-indexed in paper, 0-indexed here) + i = 0 + j = 0 + + # Line 2-3: SL ← ∅, LQ ← O_p(X) + SL: set[int] = set() + LQ: set[int] = set(O_p) + + # Line 4: d ← +∞ + d = float('inf') + + # Line 5: while LQ ∪ SL ≠ ∅ + while LQ or SL: + # Line 6: PvP ← cost(p) / |N_p(X) ∪ LQ ∪ SL| + B = N_p_X | LQ | SL + PvP = frac(p.cost) / len(B) + + pvp_lex = (PvP, p.name) + + # Line 7: if j ≤ |O_p(X)| and c_{w_j} <_lex (PvP, p) + if j < k and leximax[O_p_by_leximax[j]] < pvp_lex: + # Line 8: SL ← SL \ {w_j} + SL.discard(O_p_by_leximax[j]) + # Line 9: j ← j + 1 + j += 1 + # Line 10: else if c_{v_i} >_lex (PvP, p) + elif i < k and leximax[O_p[i]] > pvp_lex: + # Line 11: LQ ← LQ \ {v_i} + LQ.discard(O_p[i]) + # Line 12: SL ← SL ∪ {v_i} + SL.add(O_p[i]) + # Line 13: i ← i + 1 + i += 1 + else: + # Line 14-15: d ← min{d, PvP - r_{v_i}} + if i < k: + d = min(d, PvP - leftover[O_p[i]]) + # Line 16: LQ ← LQ \ {v_i} + if i < k: + LQ.discard(O_p[i]) + # Line 17: i ← i + 1 + i += 1 + + # Line 20: return d + return max(0, d) + + +def add_opt( + instance: Instance, + profile: AbstractApprovalProfile, + current_solution: BudgetAllocation, +) -> Numeric: + """ + Algorithm 3: add-opt. + + Iterates over every project p in the instance, restricts the sorted + leftover-budget and leximax-payment arrays to the voters in Op(X), and + calls GreedyProjectChange to find the minimum per-voter budget increase + that makes p certify instability. Returns the global minimum. + + Parameters + ---------- + instance : :py:class:`~pabutools.election.instance.Instance` + The instance containing the projects and the budget limit. + profile : :py:class:`~pabutools.election.profile.approvalprofile.AbstractApprovalProfile` + The approval profile, one ballot per voter. + current_solution : :py:class:`~pabutools.rules.budgetallocation.BudgetAllocation` + The current EES solution. Its + :py:attr:`~pabutools.rules.budgetallocation.BudgetAllocation.details` attribute + must be an :py:class:`EESAllocationDetails` holding per-voter payments. + + Returns + ------- + Numeric + Minimum per-voter budget increase d > 0 such that the current + solution is unstable for E(b + n·d). Returns ``float('inf')`` + when the solution is stable for every finite budget increase. + + Examples + -------- + >>> from pabutools.election import Instance, Project, ApprovalProfile, ApprovalBallot + >>> p1, p2, p3 = Project("p1", 2), Project("p2", 3.2), Project("p3", 6) + >>> inst = Instance([p1, p2, p3], budget_limit=10) + >>> prof = ApprovalProfile([ + ... ApprovalBallot([p1]), + ... ApprovalBallot([p1, p3]), + ... ApprovalBallot([p2, p3]), + ... ApprovalBallot([p2, p3]), + ... ApprovalBallot([p3]), + ... ], instance=inst) + >>> details = EESAllocationDetails({0: {p1: 1}, 1: {p1: 1}, 2: {p2: 1.6}, 3: {p2: 1.6}, 4: {}}) + >>> solution = BudgetAllocation([p1, p2], details=details) + >>> add_opt(inst, prof, solution) + 0.5 + """ + n = len(profile) + + # Precompute leftover budgets and leximax payments for all voters + leftover = get_leftover_budgets(instance, profile, current_solution) + leximax = {i: get_leximax_payment(current_solution, i, instance) for i in range(n)} + + # Pre-sort all voters once (Algorithm 3, lines A and B) + voters_by_leftover = sorted(range(n), key=lambda i: leftover[i]) + voters_by_leximax = sorted(range(n), key=lambda i: leximax[i]) + + # Line 1: d ← +∞ + d = float('inf') + + # Line 2: for p ∈ P do + for p in instance: + # Line 5: d ← min{d, GreedyProjectChange(E, (W, X), p, A', B')} + d = min(d, greedy_project_change( + instance, profile, current_solution, p, leftover, leximax, + voters_by_leftover, voters_by_leximax, + )) + + # Line 7: return d + return d + + +def ees_completion( + instance: Instance, + profile: AbstractApprovalProfile, + utilities: dict[Project, Numeric] | None = None, +) -> BudgetAllocation: + """ + Completion of EES via add-opt (§4.2, Corollary 4.7). + + Iteratively runs EES with increasing virtual per-voter budgets until + the outcome is exhaustive (no project can certify instability). + Returns the budget-feasible outcome with the highest total spending. + + Parameters + ---------- + instance : :py:class:`~pabutools.election.instance.Instance` + The instance containing the projects and the budget limit. + profile : :py:class:`~pabutools.election.profile.approvalprofile.AbstractApprovalProfile` + The approval profile, one ballot per voter. + utilities : dict[:py:class:`~pabutools.election.instance.Project`, Numeric] or None + utilities[project] = u(p). When None, every project has utility 1 + (pure approval setting). + + Returns + ------- + :py:class:`~pabutools.rules.budgetallocation.BudgetAllocation` + The completed EES outcome — a feasible outcome whose total cost + is at most ``instance.budget_limit``. + + Examples + -------- + >>> from pabutools.election import Instance, Project, ApprovalProfile, ApprovalBallot + >>> p1, p2, p3 = Project("p1", 2), Project("p2", 3.2), Project("p3", 6) + >>> inst = Instance([p1, p2, p3], budget_limit=10) + >>> prof = ApprovalProfile([ + ... ApprovalBallot([p1]), + ... ApprovalBallot([p1, p3]), + ... ApprovalBallot([p2, p3]), + ... ApprovalBallot([p2, p3]), + ... ApprovalBallot([p3]), + ... ], instance=inst) + >>> result = ees_completion(inst, prof) + >>> sorted(p.name for p in result) + ['p1', 'p3'] + """ + n = len(profile) + if n == 0: + return exact_equal_shares(instance, profile, utilities) + + original_budget = instance.budget_limit + budget = frac(original_budget) + projects = list(instance) + best: BudgetAllocation | None = None + best_cost = frac(-1) + + while True: + virtual_inst = Instance(projects, budget_limit=budget) + result = exact_equal_shares(virtual_inst, profile, utilities) + + total_cost = sum(frac(p.cost) for p in result) + if total_cost <= original_budget and total_cost > best_cost: + best = result + best_cost = total_cost + + d = add_opt(virtual_inst, profile, result) + if d == float('inf') or d <= 0: + break + + budget = budget + n * frac(d) + + if best is None: + best = exact_equal_shares(instance, profile, utilities) + return best diff --git a/tests/rules/test_ees_addopt.py b/tests/rules/test_ees_addopt.py new file mode 100644 index 0000000..c2b7777 --- /dev/null +++ b/tests/rules/test_ees_addopt.py @@ -0,0 +1,388 @@ +""" +Tests for EES (Algorithm 1), GreedyProjectChange (Algorithm 2) and add-opt (Algorithm 3). + +Programmer: Yonatan Gabay +Since: 2026-04 +""" + +import pytest + +from pabutools.election.instance import Instance, Project +from pabutools.election.profile import ApprovalProfile +from pabutools.election.ballot import ApprovalBallot +from pabutools.rules.budgetallocation import BudgetAllocation +from pabutools.rules.ees_addopt import ( + exact_equal_shares, + greedy_project_change, + add_opt, + EESAllocationDetails, + get_leftover_budgets, + get_leximax_payment, +) + + +# ---- helpers ---- + +def _make_instance_profile(project_costs, budget, approval_sets): + """ + Build an Instance + ApprovalProfile from simple descriptions. + + Parameters + ---------- + project_costs : dict[str, float] + Mapping from project name to cost. + budget : float + Budget limit. + approval_sets : list[set[str]] + One set of approved project names per voter. + + Returns + ------- + tuple[Instance, ApprovalProfile, dict[str, Project]] + The instance, profile, and a name→Project lookup dict. + """ + projects = {name: Project(name, cost) for name, cost in project_costs.items()} + inst = Instance(projects.values(), budget_limit=budget) + ballots = [ + ApprovalBallot([projects[pname] for pname in approved]) + for approved in approval_sets + ] + prof = ApprovalProfile(ballots, instance=inst) + return inst, prof, projects + + +def _selected_names(result): + """Return project names from a BudgetAllocation.""" + return [p.name for p in result] + + +def _get_payments(result): + """Return the payments dict from a BudgetAllocation's EESAllocationDetails.""" + return result.details.payments + + +####### EES tests + + +# empty input should return empty result +def test_ees_nothing_to_select(): + inst = Instance([], budget_limit=0) + prof = ApprovalProfile([], instance=inst) + + result = exact_equal_shares(inst, prof) + assert _selected_names(result) == [] + assert _get_payments(result) == {} + + +# project above budget should not be selected +def test_ees_single_project_too_expensive(): + inst, prof, projects = _make_instance_profile( + {"p1": 200}, 50, [{"p1"}, {"p1"}] + ) + result = exact_equal_shares(inst, prof) + assert projects["p1"] not in result + + +# one approved project should split cost evenly +def test_ees_cost_split_equally(): + inst, prof, projects = _make_instance_profile( + {"p1": 10}, 10, [{"p1"}, {"p1"}] + ) + result = exact_equal_shares(inst, prof) + assert projects["p1"] in result + payments = _get_payments(result) + assert payments[0][projects["p1"]] == pytest.approx(5) + assert payments[1][projects["p1"]] == pytest.approx(5) + + +# paper example +def test_ees_multiple_projects(): + inst, prof, projects = _make_instance_profile( + {"p1": 10, "p2": 16, "p3": 21}, + 40, + [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}], + ) + result = exact_equal_shares(inst, prof) + assert _selected_names(result) == ["p1", "p2"] + payments = _get_payments(result) + assert payments[0][projects["p1"]] == 5 + assert payments[1][projects["p1"]] == 5 + assert payments[2][projects["p2"]] == 8 + assert payments[3][projects["p2"]] == 8 + + +# no approvals +def test_ees_no_approvals_means_nothing_funded(): + inst, prof, projects = _make_instance_profile( + {"p1": 10, "p2": 15}, + 100, + [set(), set(), set()], + ) + result = exact_equal_shares(inst, prof) + assert _selected_names(result) == [] + + +# payments should stay within budget +def test_ees_budget_feasibility(): + inst, prof, projects = _make_instance_profile( + {"p1": 2, "p2": 3.2, "p3": 6}, + 10, + [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}], + ) + result = exact_equal_shares(inst, prof) + payments = _get_payments(result) + + total_paid = sum( + payments.get(i, {}).get(p, 0) + for i in range(len(prof)) + for p in result + ) + assert total_paid <= inst.budget_limit + + # Each funded project is fully covered + for proj in result: + paid_for_proj = sum( + payments.get(i, {}).get(proj, 0) + for i in range(len(prof)) + ) + assert paid_for_proj == pytest.approx(proj.cost) + + +####### GPC tests + + +def _make_solution(selected_names, payments_by_voter, projects): + """ + Build a BudgetAllocation with EESAllocationDetails from simple descriptions. + + Parameters + ---------- + selected_names : list[str] + Names of selected projects. + payments_by_voter : dict[int, dict[str, float]] + payments_by_voter[voter_index][project_name] = payment. + projects : dict[str, Project] + Name→Project lookup. + """ + selected = [projects[n] for n in selected_names] + pay = {} + for voter_idx, voter_payments in payments_by_voter.items(): + pay[voter_idx] = {projects[pname]: amount for pname, amount in voter_payments.items()} + return BudgetAllocation(selected, details=EESAllocationDetails(pay)) + + +# zero-cost project should return zero delta +def test_gpc_free_project_needs_zero_increase(): + inst, prof, projects = _make_instance_profile( + {"p1": 0}, 10, [{"p1"}] + ) + solution = _make_solution([], {}, projects) + leftover = get_leftover_budgets(inst, prof, solution) + leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + delta = greedy_project_change(inst, prof, solution, projects["p1"], leftover, leximax) + assert delta == pytest.approx(0) + + +# enough leftover should return zero delta +def test_gpc_leftover_covers_cost_exactly(): + inst, prof, projects = _make_instance_profile( + {"p1": 12}, 15, [{"p1"}, {"p1"}, {"p1"}] + ) + solution = _make_solution([], {}, projects) + leftover = get_leftover_budgets(inst, prof, solution) + leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + delta = greedy_project_change(inst, prof, solution, projects["p1"], leftover, leximax) + assert delta == pytest.approx(0) + + +# not enough leftover should return positive delta +def test_gpc_not_enough_leftover(): + inst, prof, projects = _make_instance_profile( + {"p1": 30}, 6, [{"p1"}, {"p1"}, {"p1"}] + ) + solution = _make_solution([], {}, projects) + leftover = get_leftover_budgets(inst, prof, solution) + leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + delta = greedy_project_change(inst, prof, solution, projects["p1"], leftover, leximax) + assert delta > 0 + + +# paper example +def test_gpc_paper_example(): + inst, prof, projects = _make_instance_profile( + {"p1": 2, "p2": 3.2, "p3": 6}, + 10, + [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}], + ) + solution = _make_solution( + ["p1", "p2"], + {0: {"p1": 1}, 1: {"p1": 1}, 2: {"p2": 1.6}, 3: {"p2": 1.6}, 4: {}}, + projects, + ) + leftover = get_leftover_budgets(inst, prof, solution) + leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + delta = greedy_project_change(inst, prof, solution, projects["p3"], leftover, leximax) + assert delta == pytest.approx(0.5) + + +# some projects are already funded +def test_gpc_with_existing_selection(): + inst, prof, projects = _make_instance_profile( + {"p1": 5, "p2": 8}, + 10, + [{"p1", "p2"}, {"p1", "p2"}], + ) + solution = _make_solution( + ["p1"], + {0: {"p1": 5.0}, 1: {}}, + projects, + ) + leftover = get_leftover_budgets(inst, prof, solution) + leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + delta = greedy_project_change(inst, prof, solution, projects["p2"], leftover, leximax) + assert delta >= 0 + + +####### add-opt tests + + +# empty input should return non-negative or infinite +def test_addopt_nothing_to_add(): + inst = Instance([], budget_limit=0) + prof = ApprovalProfile([], instance=inst) + solution = BudgetAllocation([], details=EESAllocationDetails({})) + + delta = add_opt(inst, prof, solution) + assert delta >= 0 or delta == float("inf") + + +# if all projects funded should not improve +def test_addopt_all_projects_already_funded(): + inst, prof, projects = _make_instance_profile( + {"p1": 5}, 10, [{"p1"}] + ) + solution = _make_solution(["p1"], {0: {"p1": 5.0}}, projects) + delta = add_opt(inst, prof, solution) + assert delta >= 0 or delta == float("inf") + + +# paper example +def test_addopt_finds_improvement(): + inst, prof, projects = _make_instance_profile( + {"p1": 2, "p2": 3.2, "p3": 6}, + 10, + [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}], + ) + solution = _make_solution( + ["p1", "p2"], + {0: {"p1": 1}, 1: {"p1": 1}, 2: {"p2": 1.6}, 3: {"p2": 1.6}, 4: {}}, + projects, + ) + delta = add_opt(inst, prof, solution) + assert delta == pytest.approx(0.5) + + +####### random tests + + +@pytest.mark.parametrize("num_voters, num_projects", [ + (3, 20), + (20, 2), + (20, 20), +]) +# random instances should stay valid after EES, GPC, and rerun EES +def test_random_ees_gpc_rerun(num_voters, num_projects, test_times=5, approval_prob=0.4, budget_factor=(0.4, 0.8)): + """ + Full random test: + 1. Generate random instance + 2. Run EES and validate result + 3. Choose unselected project and run GPC + 4. Run EES with bigger budget + 5. Validate new EES result + 6. Check GPC project now selected + """ + import random + rng = random.Random() + + for seed in range(test_times): + rng.seed(seed) + + project_names = [f"p{i}" for i in range(num_projects)] + costs = {name: rng.randint(0, 100) for name in project_names} + projects_map = {name: Project(name, c) for name, c in costs.items()} + all_projects = list(projects_map.values()) + + total_cost = sum(costs.values()) + budget = int(total_cost * rng.uniform(*budget_factor)) + + inst = Instance(all_projects, budget_limit=budget) + + # build approval ballots + ballots = [] + for _ in range(num_voters): + approved = [projects_map[name] for name in project_names if rng.random() < approval_prob] + ballots.append(ApprovalBallot(approved)) + prof = ApprovalProfile(ballots, instance=inst) + + # run EES + result = exact_equal_shares(inst, prof) + payments = _get_payments(result) + + # validate EES result + total = sum( + payments.get(i, {}).get(p, 0) + for i in range(num_voters) + for p in result + ) + assert total <= budget, f"seed={seed}: EES exceeded budget" + for p in result: + paid = sum(payments.get(i, {}).get(p, 0) for i in range(num_voters)) + assert paid == pytest.approx(p.cost), f"seed={seed}: project {p.name} not covered" + + # find unselected project that has support + selected_set = set(result) + unselected = [] + for proj in all_projects: + if proj in selected_set: + continue + has_supporter = any(proj in ballot for ballot in prof) + if has_supporter: + unselected.append(proj) + if not unselected: + continue + target_project = rng.choice(unselected) + + # run GPC + leftover = get_leftover_budgets(inst, prof, result) + leximax = {i: get_leximax_payment(result, i, inst) for i in range(num_voters)} + delta = greedy_project_change(inst, prof, result, target_project, leftover, leximax) + assert delta >= 0, f"seed={seed}: GPC returned negative delta" + + # run EES with new budget + new_budget = budget + num_voters * delta + new_inst = Instance(all_projects, budget_limit=new_budget) + new_result = exact_equal_shares(new_inst, prof) + new_payments = _get_payments(new_result) + + # validate new EES result + new_total = sum( + new_payments.get(i, {}).get(p, 0) + for i in range(num_voters) + for p in new_result + ) + assert new_total <= new_budget, f"seed={seed}: new EES exceeded budget" + for p in new_result: + paid = sum(new_payments.get(i, {}).get(p, 0) for i in range(num_voters)) + assert paid == pytest.approx(p.cost), f"seed={seed}: project {p.name} not covered after increase" + + # Per Remark 1 in the paper, GPC for a single project + # guarantees instability but not that the project is selected. + # Verify the EES outcome changed instead. + assert set(new_result) != set(result) or _get_payments(new_result) != _get_payments(result), ( + f"seed={seed}: GPC said delta={delta} for '{target_project.name}' " + f"but EES returned the same result with budget={new_budget}" + ) + + +if __name__ == "__main__": + pytest.main(["-v", __file__]) From 8ac4cb73a86ff023faf3975fb08bc9c1eb090f55 Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Thu, 4 Jun 2026 11:42:14 +0300 Subject: [PATCH 2/8] Rename variables, add tests, and fix code review issues in ees_addopt --- pabutools/rules/ees_addopt.py | 415 +++++++++++++++++++-------------- tests/rules/test_ees_addopt.py | 331 +++++++++++++++++++++----- 2 files changed, 514 insertions(+), 232 deletions(-) diff --git a/pabutools/rules/ees_addopt.py b/pabutools/rules/ees_addopt.py index 23bee82..d481ad3 100644 --- a/pabutools/rules/ees_addopt.py +++ b/pabutools/rules/ees_addopt.py @@ -29,7 +29,10 @@ class EESAllocationDetails(AllocationDetails): def __init__(self, payments: dict[int, dict[Project, Numeric]] | None = None): super().__init__() - self.payments: dict[int, dict[Project, Numeric]] = payments if payments is not None else {} + if payments is not None: + self.payments = payments + else: + self.payments = {} def __repr__(self): return f"EESAllocationDetails[payments={self.payments}]" @@ -85,95 +88,114 @@ def exact_equal_shares( b = instance.budget_limit - # Line 1: W = ∅, X = 0^{n·m}, r_i = b/n for all i ∈ N - W: list[Project] = [] - selected_set: set[Project] = set() - payments: dict[int, dict[Project, Numeric]] = {i: {} for i in range(n)} - r: list[Numeric] = [frac(b) / n] * n + # Line 1: Start with no selected projects and equal voter budgets. + selected_projects = [] + payments = {} + for i in range(n): + payments[i] = {} + initial_budget_per_voter = frac(b) / n + remaining_budgets = [] + for i in range(n): + remaining_budgets.append(initial_budget_per_voter) - # Maintain a globally sorted list of voters by remaining budget. - # Filtering this list to a project's supporters preserves sorted order - # in O(n), avoiding an O(n log n) sort per project per iteration. - sorted_voters: list[int] = list(range(n)) # all equal initially + # Keep voters sorted by remaining budget for fast supporter filtering. + voters_by_remaining_budget = list(range(n)) # all equal initially - # Line 2: while true do + # Line 2: Keep selecting projects until none are feasible. while True: - best_score: Numeric = -1 - best_candidates: list[tuple[Project, list[int]]] = [] + best_score = -1 + best_candidates = [] - # Line 3: Φ = {(p ∈ P\W, V ⊆ N_p) | r_i ≥ cost(p)/|V| ∀i ∈ V} + # Line 3: Consider each unselected project with supporters who can afford it. # For each project, find the largest feasible supporter subset V. - for p in instance: - if p in selected_set: + selected_set = set(selected_projects) + for project in instance: + if project in selected_set: continue - u_p = utilities[p] if utilities is not None else 1 + if utilities is not None: + project_utility = utilities[project] + else: + project_utility = 1 - # N_p: voters who approve p, filtered from sorted_voters (preserves order) - supporters = [i for i in sorted_voters if p in profile[i]] + # N_p: voters who approve project, preserving remaining-budget order. + supporters = [] + for i in voters_by_remaining_budget: + if project in profile[i]: + supporters.append(i) if not supporters: continue # Greedily remove the poorest voter while they can't afford # their equal share cost(p)/|V|. - while supporters and r[supporters[0]] < frac(p.cost) / len(supporters): + while supporters and remaining_budgets[supporters[0]] < frac(project.cost) / len(supporters): supporters.pop(0) if not supporters: continue - # Line 8: score = |V|·u(p) / cost(p) - if p.cost == 0: - score = float('inf') + # Line 8: Score the project by utility per unit of cost. + if project.cost == 0: + bang_per_buck = float('inf') else: - score = frac(len(supporters) * u_p) / p.cost - if score > best_score: - best_score = score - best_candidates = [(p, supporters)] - elif score == best_score: - best_candidates.append((p, supporters)) - - # Line 4-5: if Φ = ∅ then return (W, X) + bang_per_buck = frac(len(supporters) * project_utility) / project.cost + if bang_per_buck > best_score: + best_score = bang_per_buck + best_candidates = [(project, supporters)] + elif bang_per_buck == best_score: + best_candidates.append((project, supporters)) + + # Line 4-5: Return the current allocation if no feasible project remains. if not best_candidates: - return BudgetAllocation(W, details=EESAllocationDetails(payments)) + return BudgetAllocation(selected_projects, details=EESAllocationDetails(payments)) - # Line 9: Choose (p*, V*) from Φ* using tiebreaking (p* ◁ p) - # Use untie() (first/smallest name) so that unselected tied projects - # have larger names. The leximax (amount, selected_name) will then - # NOT exceed (amount, unselected_name) under Python's default tuple - # comparison, preventing spurious instability certificates. + # Line 9: Break ties among the best feasible projects. + # Choose the lexicographically first tied project to keep ties stable. if len(best_candidates) == 1: - p_star, V_star = best_candidates[0] + chosen_project, chosen_supporters = best_candidates[0] else: - tied_projects = [p for p, _ in best_candidates] - p_star = lexico_tie_breaking.untie(instance, profile, tied_projects) - V_star = next(V for p, V in best_candidates if p == p_star) - - # Line 10: W = W ∪ {p*} - W.append(p_star) - selected_set.add(p_star) - - # Line 11: x_{i,p*} = cost(p*)/|V*|, r_i = r_i − cost(p*)/|V*| ∀i ∈ V* - V_star_set = set(V_star) - payment = frac(p_star.cost) / len(V_star) - for i in V_star: - payments[i][p_star] = payment - r[i] -= payment - - # Update sorted_voters via O(n) merge. All V* voters decreased by + tied_projects = [] + for candidate_project, _ in best_candidates: + tied_projects.append(candidate_project) + chosen_project = lexico_tie_breaking.untie(instance, profile, tied_projects) + chosen_supporters = None + for candidate_project, candidate_supporters in best_candidates: + if candidate_project == chosen_project: + chosen_supporters = candidate_supporters + break + + # Line 10: Add the chosen project to the allocation. + selected_projects.append(chosen_project) + + # Line 11: Charge each chosen supporter an equal share of the project cost. + chosen_supporters_set = set(chosen_supporters) + payment = frac(chosen_project.cost) / len(chosen_supporters) + for i in chosen_supporters: + payments[i][chosen_project] = payment + remaining_budgets[i] -= payment + + # Update voters_by_remaining_budget via O(n) merge. All V* voters decreased by # the same amount so their relative order is preserved. - changed = [i for i in sorted_voters if i in V_star_set] - unchanged = [i for i in sorted_voters if i not in V_star_set] - merged: list[int] = [] - ci, ui = 0, 0 + changed = [] + unchanged = [] + for i in voters_by_remaining_budget: + if i in chosen_supporters_set: + changed.append(i) + else: + unchanged.append(i) + merged = [] + ci = 0 + ui = 0 while ci < len(changed) and ui < len(unchanged): - if r[changed[ci]] <= r[unchanged[ui]]: - merged.append(changed[ci]); ci += 1 + if remaining_budgets[changed[ci]] <= remaining_budgets[unchanged[ui]]: + merged.append(changed[ci]) + ci += 1 else: - merged.append(unchanged[ui]); ui += 1 + merged.append(unchanged[ui]) + ui += 1 merged.extend(changed[ci:]) merged.extend(unchanged[ui:]) - sorted_voters = merged + voters_by_remaining_budget = merged def get_leftover_budgets( @@ -186,39 +208,53 @@ def get_leftover_budgets( leftover[i] = b/n - sum of payments by voter i across all selected projects. """ - n = len(profile) - b = instance.budget_limit - details: EESAllocationDetails = current_solution.details - leftover = {} - for i in range(n): - paid = sum(details.payments.get(i, {}).values()) - leftover[i] = frac(b) / n - paid - return leftover + num_voters = len(profile) + budget_limit = instance.budget_limit + allocation_details = current_solution.details + leftover_budgets = {} + + for voter in range(num_voters): + total_paid = 0 + voter_payments = allocation_details.payments.get(voter, {}) + for payment_amount in voter_payments.values(): + total_paid += payment_amount + leftover_budgets[voter] = (frac(budget_limit) / num_voters) - total_paid + + return leftover_budgets def get_leximax_payment( current_solution: BudgetAllocation, - voter: int, + num_voters: int, instance: Instance, -) -> tuple[Numeric, str]: +) -> dict[int, list[tuple[Numeric, str]]]: """ - Return the leximax payment of a voter as ``(amount, project_name)``. + Return the leximax payment vectors for all voters as a dict mapping + voter index to a sorted list of ``(amount, project_name)`` tuples, + ordered descending by amount then ascending by project name for ties. - The leximax payment c_i = (x_i, p_i) where x_i is the maximum payment - and p_i is the project with that payment that comes first in the total - order ⊲ (alphabetical by name, i.e. smallest name). When the voter - made no payments, x_i = 0 and p_i is the first project in ⊲ - (smallest name), so that non-paying voters never certify instability. + When a voter made no payments, their entry is ``[(0, smallest_name)]`` + so that non-paying voters never certify instability. """ - details: EESAllocationDetails = current_solution.details - voter_payments = details.payments.get(voter, {}) - if not voter_payments: - min_project_name = min(p.name for p in instance) - return (0, min_project_name) - max_amount = max(voter_payments.values()) - max_projects = [p for p, v in voter_payments.items() if v == max_amount] - min_project = min(max_projects, key=lambda p: p.name) - return (max_amount, min_project.name) + allocation_details = current_solution.details + smallest_project_name = "" + for project in instance: + if smallest_project_name == "" or project.name < smallest_project_name: + smallest_project_name = project.name + leximax_payments = {} + + for voter in range(num_voters): + voter_payments = allocation_details.payments.get(voter, {}) + if not voter_payments: + leximax_payments[voter] = [(0, smallest_project_name)] + else: + payment_vector = [] + for project, payment_amount in voter_payments.items(): + payment_vector.append((payment_amount, project.name)) + payment_vector.sort(key=lambda payment: (-payment[0], payment[1])) + leximax_payments[voter] = payment_vector + + return leximax_payments def greedy_project_change( @@ -226,8 +262,8 @@ def greedy_project_change( profile: AbstractApprovalProfile, current_solution: BudgetAllocation, project: Project, - leftover: dict[int, Numeric], - leximax: dict[int, tuple[Numeric, str]], + leftover_budgets: dict[int, Numeric], + leximax_payments: dict[int, list[tuple[Numeric, str]]], voters_by_leftover: list[int] | None = None, voters_by_leximax: list[int] | None = None, ) -> Numeric: @@ -254,11 +290,11 @@ def greedy_project_change( must be an :py:class:`EESAllocationDetails` holding per-voter payments. project : :py:class:`~pabutools.election.instance.Project` The candidate project p to test instability for. - leftover : dict[int, Numeric] + leftover_budgets : dict[int, Numeric] Leftover budget per voter, as returned by :py:func:`get_leftover_budgets`. - leximax : dict[int, tuple[Numeric, str]] - Leximax payment per voter, as returned by + leximax_payments : dict[int, list[tuple[Numeric, str]]] + Leximax payment vector per voter, as returned by :py:func:`get_leximax_payment`. voters_by_leftover : list[int] or None All voters pre-sorted by leftover ascending. When provided the @@ -287,79 +323,103 @@ def greedy_project_change( >>> details = EESAllocationDetails({0: {p1: 1}, 1: {p1: 1}, 2: {p2: 1.6}, 3: {p2: 1.6}, 4: {}}) >>> solution = BudgetAllocation([p1, p2], details=details) >>> leftover = get_leftover_budgets(inst, prof, solution) - >>> leximax = {i: get_leximax_payment(solution, i, inst) for i in range(5)} + >>> leximax = get_leximax_payment(solution, 5, inst) >>> greedy_project_change(inst, prof, solution, p3, leftover, leximax) - 0.5 + mpq(1,2) """ n = len(profile) - p = project - # All voters who approve p - all_supporters = {i for i in range(n) if p in profile[i]} + # All voters who approve project. + project_supporters = set() + for voter in range(n): + if project in profile[voter]: + project_supporters.add(voter) + + # voters who already pay for project in the current solution. + allocation_details = current_solution.details + current_payers = set() + for voter in project_supporters: + if project in allocation_details.payments.get(voter, {}): + current_payers.add(voter) - # N_p(X): voters who pay for project p in the current solution - details: EESAllocationDetails = current_solution.details - N_p_X = {i for i in all_supporters if p in details.payments.get(i, {})} - # O_p(X) = N_p \ N_p(X): voters who approve p but don't pay for it - O_p_X = all_supporters - N_p_X + # O_p(X): supporters who approve project but do not currently pay for it. + outside_supporters = project_supporters - current_payers - # O_p(X) sorted by leftover budget ascending: v_1, ..., v_k + # Outside supporters sorted by leftover budget ascending. if voters_by_leftover is not None: - O_p = [i for i in voters_by_leftover if i in O_p_X] + outside_supporters_by_leftover = [] + for voter in voters_by_leftover: + if voter in outside_supporters: + outside_supporters_by_leftover.append(voter) else: - O_p = sorted(O_p_X, key=lambda i: leftover[i]) - k = len(O_p) + outside_supporters_by_leftover = sorted( + outside_supporters, key=lambda voter: leftover_budgets[voter] + ) + num_outside_supporters = len(outside_supporters_by_leftover) - # Leximax payments of O_p(X) voters, sorted ascending: w_1, ..., w_k + # Outside supporters sorted by leximax payment ascending. if voters_by_leximax is not None: - O_p_by_leximax = [i for i in voters_by_leximax if i in O_p_X] + outside_supporters_by_leximax = [] + for voter in voters_by_leximax: + if voter in outside_supporters: + outside_supporters_by_leximax.append(voter) else: - O_p_by_leximax = sorted(O_p_X, key=lambda i: leximax[i]) + outside_supporters_by_leximax = sorted( + outside_supporters, key=lambda voter: leximax_payments[voter]) - # Line 1: i, j ← 1, 1 (1-indexed in paper, 0-indexed here) - i = 0 - j = 0 + # Line 1: Start both scan positions at the beginning. + leftover_index = 0 + leximax_index = 0 - # Line 2-3: SL ← ∅, LQ ← O_p(X) - SL: set[int] = set() - LQ: set[int] = set(O_p) + # Line 2-3 + # SL (solvent list) — voters who can pay by deviating from their leximax project. + solvent_list = set() + # LQ (liquid queue) — voters expected to pay from their leftover budgets. + liquid_queue = set(outside_supporters_by_leftover) - # Line 4: d ← +∞ + # Line 4: Initialize the required budget increase as unbounded. d = float('inf') - # Line 5: while LQ ∪ SL ≠ ∅ - while LQ or SL: - # Line 6: PvP ← cost(p) / |N_p(X) ∪ LQ ∪ SL| - B = N_p_X | LQ | SL - PvP = frac(p.cost) / len(B) - - pvp_lex = (PvP, p.name) - - # Line 7: if j ≤ |O_p(X)| and c_{w_j} <_lex (PvP, p) - if j < k and leximax[O_p_by_leximax[j]] < pvp_lex: - # Line 8: SL ← SL \ {w_j} - SL.discard(O_p_by_leximax[j]) - # Line 9: j ← j + 1 - j += 1 - # Line 10: else if c_{v_i} >_lex (PvP, p) - elif i < k and leximax[O_p[i]] > pvp_lex: - # Line 11: LQ ← LQ \ {v_i} - LQ.discard(O_p[i]) - # Line 12: SL ← SL ∪ {v_i} - SL.add(O_p[i]) - # Line 13: i ← i + 1 - i += 1 + # Line 5: Continue until all queued and skipped voters have been processed. + while liquid_queue or solvent_list: + # Line 6: Compute the current equal payment needed for project. + paying_supporters = current_payers | liquid_queue | solvent_list + per_voter_price = frac(project.cost) / len(paying_supporters) + + per_voter_price_leximax = [(per_voter_price, project.name)] + + # Line 7: Advance past voters whose leximax payment is too small. + if (leximax_index < num_outside_supporters + and leximax_payments[outside_supporters_by_leximax[leximax_index]] + < per_voter_price_leximax): + # Line 8: Remove that voter from the skipped set if present. + solvent_list.discard(outside_supporters_by_leximax[leximax_index]) + # Line 9: Move to the next voter in leximax order. + leximax_index += 1 + + # Line 10: Otherwise, check whether the next leftover voter must be skipped. + elif (leftover_index < num_outside_supporters + and leximax_payments[outside_supporters_by_leftover[leftover_index]] + > per_voter_price_leximax): + # Line 11: Remove the voter from the leftover queue. + liquid_queue.discard(outside_supporters_by_leftover[leftover_index]) + # Line 12: Mark the voter as skipped for later processing. + solvent_list.add(outside_supporters_by_leftover[leftover_index]) + # Line 13: Move to the next voter in leftover order. + leftover_index += 1 + + # Line 14-15: Record the smallest increase that lets this voter pay. else: - # Line 14-15: d ← min{d, PvP - r_{v_i}} - if i < k: - d = min(d, PvP - leftover[O_p[i]]) - # Line 16: LQ ← LQ \ {v_i} - if i < k: - LQ.discard(O_p[i]) - # Line 17: i ← i + 1 - i += 1 - - # Line 20: return d + if leftover_index < num_outside_supporters: + next_voter = outside_supporters_by_leftover[leftover_index] + d = min(d, per_voter_price - leftover_budgets[next_voter]) + # Line 16: Remove the processed voter from the leftover queue. + if leftover_index < num_outside_supporters: + liquid_queue.discard(outside_supporters_by_leftover[leftover_index]) + # Line 17: Move to the next voter in leftover order. + leftover_index += 1 + + # Line 20: Return the best budget increase found. return max(0, d) @@ -409,34 +469,34 @@ def add_opt( >>> details = EESAllocationDetails({0: {p1: 1}, 1: {p1: 1}, 2: {p2: 1.6}, 3: {p2: 1.6}, 4: {}}) >>> solution = BudgetAllocation([p1, p2], details=details) >>> add_opt(inst, prof, solution) - 0.5 + mpq(1,2) """ n = len(profile) # Precompute leftover budgets and leximax payments for all voters - leftover = get_leftover_budgets(instance, profile, current_solution) - leximax = {i: get_leximax_payment(current_solution, i, instance) for i in range(n)} + leftover_budgets = get_leftover_budgets(instance, profile, current_solution) + leximax_payments = get_leximax_payment(current_solution, n, instance) # Pre-sort all voters once (Algorithm 3, lines A and B) - voters_by_leftover = sorted(range(n), key=lambda i: leftover[i]) - voters_by_leximax = sorted(range(n), key=lambda i: leximax[i]) + all_voters = list(range(n)) + voters_by_leftover = sorted(all_voters, key=lambda i: leftover_budgets[i]) + voters_by_leximax = sorted(all_voters, key=lambda i: leximax_payments[i]) - # Line 1: d ← +∞ + # Line 1: Initialize the best project change as unbounded. d = float('inf') - # Line 2: for p ∈ P do - for p in instance: - # Line 5: d ← min{d, GreedyProjectChange(E, (W, X), p, A', B')} - d = min(d, greedy_project_change( - instance, profile, current_solution, p, leftover, leximax, - voters_by_leftover, voters_by_leximax, - )) + # Line 2: Test every project as a possible instability certificate. + for project in instance: + # Line 5: Keep the smallest change found for any project. + gpc_result = greedy_project_change(instance, profile, current_solution, project, leftover_budgets, leximax_payments, + voters_by_leftover, voters_by_leximax,) + d = min(d, gpc_result) - # Line 7: return d + # Line 7: Return the minimum change over all projects. return d -def ees_completion( +def ees_add_opt_completion( instance: Instance, profile: AbstractApprovalProfile, utilities: dict[Project, Numeric] | None = None, @@ -476,7 +536,7 @@ def ees_completion( ... ApprovalBallot([p2, p3]), ... ApprovalBallot([p3]), ... ], instance=inst) - >>> result = ees_completion(inst, prof) + >>> result = ees_add_opt_completion(inst, prof) >>> sorted(p.name for p in result) ['p1', 'p3'] """ @@ -485,26 +545,29 @@ def ees_completion( return exact_equal_shares(instance, profile, utilities) original_budget = instance.budget_limit - budget = frac(original_budget) + virtual_budget = frac(original_budget) projects = list(instance) - best: BudgetAllocation | None = None - best_cost = frac(-1) + best_result = None + best_result_cost = frac(-1) while True: - virtual_inst = Instance(projects, budget_limit=budget) + virtual_inst = Instance(projects, budget_limit=virtual_budget) result = exact_equal_shares(virtual_inst, profile, utilities) - total_cost = sum(frac(p.cost) for p in result) - if total_cost <= original_budget and total_cost > best_cost: - best = result - best_cost = total_cost + total_cost = 0 + for project in result: + total_cost += frac(project.cost) + if total_cost <= original_budget and total_cost > best_result_cost: + best_result = result + best_result_cost = total_cost d = add_opt(virtual_inst, profile, result) if d == float('inf') or d <= 0: break - budget = budget + n * frac(d) + virtual_budget = virtual_budget + n * frac(d) - if best is None: - best = exact_equal_shares(instance, profile, utilities) - return best + if best_result is None: + best_result = exact_equal_shares(instance, profile, utilities) + + return best_result diff --git a/tests/rules/test_ees_addopt.py b/tests/rules/test_ees_addopt.py index c2b7777..b2c59f7 100644 --- a/tests/rules/test_ees_addopt.py +++ b/tests/rules/test_ees_addopt.py @@ -15,6 +15,7 @@ exact_equal_shares, greedy_project_change, add_opt, + ees_add_opt_completion, EESAllocationDetails, get_leftover_budgets, get_leximax_payment, @@ -41,19 +42,26 @@ def _make_instance_profile(project_costs, budget, approval_sets): tuple[Instance, ApprovalProfile, dict[str, Project]] The instance, profile, and a name→Project lookup dict. """ - projects = {name: Project(name, cost) for name, cost in project_costs.items()} + projects = {} + for name, cost in project_costs.items(): + projects[name] = Project(name, cost) inst = Instance(projects.values(), budget_limit=budget) - ballots = [ - ApprovalBallot([projects[pname] for pname in approved]) - for approved in approval_sets - ] + ballots = [] + for approved in approval_sets: + ballot_projects = [] + for pname in approved: + ballot_projects.append(projects[pname]) + ballots.append(ApprovalBallot(ballot_projects)) prof = ApprovalProfile(ballots, instance=inst) return inst, prof, projects def _selected_names(result): """Return project names from a BudgetAllocation.""" - return [p.name for p in result] + names = [] + for p in result: + names.append(p.name) + return names def _get_payments(result): @@ -61,6 +69,31 @@ def _get_payments(result): return result.details.payments +def _make_solution(selected_names, payments_by_voter, projects): + """ + Build a BudgetAllocation with EESAllocationDetails from simple descriptions. + + Parameters + ---------- + selected_names : list[str] + Names of selected projects. + payments_by_voter : dict[int, dict[str, float]] + payments_by_voter[voter_index][project_name] = payment. + projects : dict[str, Project] + Name→Project lookup. + """ + selected = [] + for name in selected_names: + selected.append(projects[name]) + pay = {} + for voter_idx, voter_payments in payments_by_voter.items(): + voter_pay = {} + for pname, amount in voter_payments.items(): + voter_pay[projects[pname]] = amount + pay[voter_idx] = voter_pay + return BudgetAllocation(selected, details=EESAllocationDetails(pay)) + + ####### EES tests @@ -132,43 +165,119 @@ def test_ees_budget_feasibility(): result = exact_equal_shares(inst, prof) payments = _get_payments(result) - total_paid = sum( - payments.get(i, {}).get(p, 0) - for i in range(len(prof)) - for p in result - ) + total_paid = 0 + for i in range(len(prof)): + for p in result: + total_paid += payments.get(i, {}).get(p, 0) assert total_paid <= inst.budget_limit # Each funded project is fully covered for proj in result: - paid_for_proj = sum( - payments.get(i, {}).get(proj, 0) - for i in range(len(prof)) - ) + paid_for_proj = 0 + for i in range(len(prof)): + paid_for_proj += payments.get(i, {}).get(proj, 0) assert paid_for_proj == pytest.approx(proj.cost) -####### GPC tests +####### get_leftover_budgets tests -def _make_solution(selected_names, payments_by_voter, projects): - """ - Build a BudgetAllocation with EESAllocationDetails from simple descriptions. +# no payments means full leftover for each voter +def test_leftover_no_payments(): + inst, prof, projects = _make_instance_profile({"p1": 10}, 20, [{"p1"}, {"p1"}]) + solution = _make_solution([], {0: {}, 1: {}}, projects) + leftover = get_leftover_budgets(inst, prof, solution) + # b/n = 20/2 = 10 per voter + assert leftover[0] == pytest.approx(10) + assert leftover[1] == pytest.approx(10) - Parameters - ---------- - selected_names : list[str] - Names of selected projects. - payments_by_voter : dict[int, dict[str, float]] - payments_by_voter[voter_index][project_name] = payment. - projects : dict[str, Project] - Name→Project lookup. - """ - selected = [projects[n] for n in selected_names] - pay = {} - for voter_idx, voter_payments in payments_by_voter.items(): - pay[voter_idx] = {projects[pname]: amount for pname, amount in voter_payments.items()} - return BudgetAllocation(selected, details=EESAllocationDetails(pay)) + +# leftover should equal b/n minus total payments +def test_leftover_after_payments(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 3.2}, 10, [{"p1", "p2"}, {"p1", "p2"}]) + solution = _make_solution(["p1", "p2"],{0: {"p1": 1, "p2": 1.6}, 1: {"p1": 1, "p2": 1.6}},projects,) + leftover = get_leftover_budgets(inst, prof, solution) + # b/n = 10/2 = 5, each voter paid 2.6 + assert leftover[0] == pytest.approx(2.4) + assert leftover[1] == pytest.approx(2.4) + + +# voter who paid nothing has full leftover; voter who paid has less +def test_leftover_uneven_payments(): + inst, prof, projects = _make_instance_profile({"p1": 5}, 10, [{"p1"}, {"p1"}]) + solution = _make_solution(["p1"],{0: {"p1": 5.0}, 1: {}},projects,) + leftover = get_leftover_budgets(inst, prof, solution) + # b/n = 5 + assert leftover[0] == pytest.approx(0) + assert leftover[1] == pytest.approx(5) + + +# paper example +def test_leftover_paper_example(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 3.2, "p3": 6},10,[{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}],) + solution = _make_solution(["p1", "p2"],{0: {"p1": 1}, 1: {"p1": 1}, 2: {"p2": 1.6}, 3: {"p2": 1.6}, 4: {}},projects,) + leftover = get_leftover_budgets(inst, prof, solution) + # b/n = 10/5 = 2 + assert leftover[0] == pytest.approx(1) + assert leftover[1] == pytest.approx(1) + assert leftover[2] == pytest.approx(0.4) + assert leftover[3] == pytest.approx(0.4) + assert leftover[4] == pytest.approx(2) + + +####### get_leximax_payment tests + + +# non-paying voter gets [(0, smallest_project_name)] +def test_leximax_no_payments(): + inst, prof, projects = _make_instance_profile({"p1": 10, "p2": 5}, 20, [{"p1"}, {"p2"}]) + solution = _make_solution([], {0: {}, 1: {}}, projects) + leximax = get_leximax_payment(solution, len(prof), inst) + # smallest project name is "p1" + assert leximax[0] == [(0, "p1")] + assert leximax[1] == [(0, "p1")] + + +# single payment produces a one-element vector +def test_leximax_single_payment(): + inst, prof, projects = _make_instance_profile({"p1": 10}, 10, [{"p1"}, {"p1"}]) + solution = _make_solution(["p1"],{0: {"p1": 5}, 1: {"p1": 5}},projects,) + leximax = get_leximax_payment(solution, len(prof), inst) + assert leximax[0] == [(5, "p1")] + assert leximax[1] == [(5, "p1")] + + +# multiple payments sorted descending by amount, then ascending by name +def test_leximax_multiple_payments_sorted(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 6}, 10, [{"p1", "p2"}]) + solution = _make_solution(["p1", "p2"],{0: {"p1": 2, "p2": 6}},projects,) + leximax = get_leximax_payment(solution, len(prof), inst) + # descending by amount: 6 before 2 + assert leximax[0] == [(6, "p2"), (2, "p1")] + + +# equal amounts should be sorted ascending by project name +def test_leximax_tiebreak_by_name(): + inst, prof, projects = _make_instance_profile({"a": 4, "b": 4}, 10, [{"a", "b"}]) + solution = _make_solution(["a", "b"], {0: {"a": 4, "b": 4}}, projects,) + leximax = get_leximax_payment(solution, len(prof), inst) + # same amount, ascending by name: "a" before "b" + assert leximax[0] == [(4, "a"), (4, "b")] + + +# paper example +def test_leximax_paper_example(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 3.2, "p3": 6}, 10, [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}],) + solution = _make_solution(["p1", "p2"], {0: {"p1": 1}, 1: {"p1": 1}, 2: {"p2": 1.6}, 3: {"p2": 1.6}, 4: {}}, projects,) + leximax = get_leximax_payment(solution, len(prof), inst) + assert leximax[0] == [(1, "p1")] + assert leximax[1] == [(1, "p1")] + assert leximax[2] == [(1.6, "p2")] + assert leximax[3] == [(1.6, "p2")] + assert leximax[4] == [(0, "p1")] # non-payer gets smallest name + + +####### GPC tests # zero-cost project should return zero delta @@ -178,7 +287,7 @@ def test_gpc_free_project_needs_zero_increase(): ) solution = _make_solution([], {}, projects) leftover = get_leftover_budgets(inst, prof, solution) - leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + leximax = get_leximax_payment(solution, len(prof), inst) delta = greedy_project_change(inst, prof, solution, projects["p1"], leftover, leximax) assert delta == pytest.approx(0) @@ -190,7 +299,7 @@ def test_gpc_leftover_covers_cost_exactly(): ) solution = _make_solution([], {}, projects) leftover = get_leftover_budgets(inst, prof, solution) - leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + leximax = get_leximax_payment(solution, len(prof), inst) delta = greedy_project_change(inst, prof, solution, projects["p1"], leftover, leximax) assert delta == pytest.approx(0) @@ -202,7 +311,7 @@ def test_gpc_not_enough_leftover(): ) solution = _make_solution([], {}, projects) leftover = get_leftover_budgets(inst, prof, solution) - leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + leximax = get_leximax_payment(solution, len(prof), inst) delta = greedy_project_change(inst, prof, solution, projects["p1"], leftover, leximax) assert delta > 0 @@ -220,7 +329,7 @@ def test_gpc_paper_example(): projects, ) leftover = get_leftover_budgets(inst, prof, solution) - leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + leximax = get_leximax_payment(solution, len(prof), inst) delta = greedy_project_change(inst, prof, solution, projects["p3"], leftover, leximax) assert delta == pytest.approx(0.5) @@ -238,7 +347,7 @@ def test_gpc_with_existing_selection(): projects, ) leftover = get_leftover_budgets(inst, prof, solution) - leximax = {i: get_leximax_payment(solution, i, inst) for i in range(len(prof))} + leximax = get_leximax_payment(solution, len(prof), inst) delta = greedy_project_change(inst, prof, solution, projects["p2"], leftover, leximax) assert delta >= 0 @@ -287,7 +396,7 @@ def test_addopt_finds_improvement(): @pytest.mark.parametrize("num_voters, num_projects", [ (3, 20), - (20, 2), + (20, 3), (20, 20), ]) # random instances should stay valid after EES, GPC, and rerun EES @@ -307,9 +416,15 @@ def test_random_ees_gpc_rerun(num_voters, num_projects, test_times=5, approval_p for seed in range(test_times): rng.seed(seed) - project_names = [f"p{i}" for i in range(num_projects)] - costs = {name: rng.randint(0, 100) for name in project_names} - projects_map = {name: Project(name, c) for name, c in costs.items()} + project_names = [] + for i in range(num_projects): + project_names.append(f"p{i}") + costs = {} + for name in project_names: + costs[name] = rng.randint(0, 100) + projects_map = {} + for name, c in costs.items(): + projects_map[name] = Project(name, c) all_projects = list(projects_map.values()) total_cost = sum(costs.values()) @@ -320,7 +435,10 @@ def test_random_ees_gpc_rerun(num_voters, num_projects, test_times=5, approval_p # build approval ballots ballots = [] for _ in range(num_voters): - approved = [projects_map[name] for name in project_names if rng.random() < approval_prob] + approved = [] + for name in project_names: + if rng.random() < approval_prob: + approved.append(projects_map[name]) ballots.append(ApprovalBallot(approved)) prof = ApprovalProfile(ballots, instance=inst) @@ -329,14 +447,15 @@ def test_random_ees_gpc_rerun(num_voters, num_projects, test_times=5, approval_p payments = _get_payments(result) # validate EES result - total = sum( - payments.get(i, {}).get(p, 0) - for i in range(num_voters) - for p in result - ) + total = 0 + for i in range(num_voters): + for p in result: + total += payments.get(i, {}).get(p, 0) assert total <= budget, f"seed={seed}: EES exceeded budget" for p in result: - paid = sum(payments.get(i, {}).get(p, 0) for i in range(num_voters)) + paid = 0 + for i in range(num_voters): + paid += payments.get(i, {}).get(p, 0) assert paid == pytest.approx(p.cost), f"seed={seed}: project {p.name} not covered" # find unselected project that has support @@ -354,7 +473,7 @@ def test_random_ees_gpc_rerun(num_voters, num_projects, test_times=5, approval_p # run GPC leftover = get_leftover_budgets(inst, prof, result) - leximax = {i: get_leximax_payment(result, i, inst) for i in range(num_voters)} + leximax = get_leximax_payment(result, num_voters, inst) delta = greedy_project_change(inst, prof, result, target_project, leftover, leximax) assert delta >= 0, f"seed={seed}: GPC returned negative delta" @@ -365,14 +484,15 @@ def test_random_ees_gpc_rerun(num_voters, num_projects, test_times=5, approval_p new_payments = _get_payments(new_result) # validate new EES result - new_total = sum( - new_payments.get(i, {}).get(p, 0) - for i in range(num_voters) - for p in new_result - ) + new_total = 0 + for i in range(num_voters): + for p in new_result: + new_total += new_payments.get(i, {}).get(p, 0) assert new_total <= new_budget, f"seed={seed}: new EES exceeded budget" for p in new_result: - paid = sum(new_payments.get(i, {}).get(p, 0) for i in range(num_voters)) + paid = 0 + for i in range(num_voters): + paid += new_payments.get(i, {}).get(p, 0) assert paid == pytest.approx(p.cost), f"seed={seed}: project {p.name} not covered after increase" # Per Remark 1 in the paper, GPC for a single project @@ -384,5 +504,104 @@ def test_random_ees_gpc_rerun(num_voters, num_projects, test_times=5, approval_p ) +####### ees_add_opt_completion tests + + +# empty profile returns empty result +def test_completion_empty_profile(): + inst = Instance([], budget_limit=10) + prof = ApprovalProfile([], instance=inst) + result = ees_add_opt_completion(inst, prof) + assert len(result) == 0 + + +# paper example from §4.1 Example 4.3 +# 5 voters, 3 projects: p1(2), p2(3.2), p3(6), budget=10 +# EES alone picks {p1,p2} (cost 5.2), completion should pick {p1,p3} (cost 8) +def test_completion_paper_example(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 3.2, "p3": 6}, + 10, + [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}],) + result = ees_add_opt_completion(inst, prof) + names = sorted(_selected_names(result)) + assert names == ["p1", "p3"] + + +# result should always be budget-feasible +def test_completion_budget_feasible(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 3.2, "p3": 6}, + 10, + [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}],) + result = ees_add_opt_completion(inst, prof) + total = 0 + for p in result: + total += p.cost + assert total <= inst.budget_limit + + +# single voter, single affordable project +def test_completion_single_voter_single_project(): + inst, prof, projects = _make_instance_profile({"p1": 5}, + 10, + [{"p1"}],) + result = ees_add_opt_completion(inst, prof) + assert _selected_names(result) == ["p1"] + + +# all projects are affordable from the start +def test_completion_all_projects_selected(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 3}, + 10, + [{"p1", "p2"}, {"p1", "p2"}],) + result = ees_add_opt_completion(inst, prof) + names = sorted(_selected_names(result)) + assert names == ["p1", "p2"] + + +# no project is affordable (cost exceeds budget) +def test_completion_no_affordable_project(): + inst, prof, projects = _make_instance_profile({"p1": 100}, + 10, + [{"p1"}],) + result = ees_add_opt_completion(inst, prof) + assert len(result) == 0 + + +# Remark 1 example: p1(2),p2(98),p3(100),p4(51), budget=150, 3 voters +# A1={p1,p2}, A2={p2,p3}, A3={p3,p4}. EES selects {p1,p3}. +# Completion should produce a feasible result with total cost <= 150. +def test_completion_remark1_example(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 98, "p3": 100, "p4": 51}, + 150, + [{"p1", "p2"}, {"p2", "p3"}, {"p3", "p4"}],) + result = ees_add_opt_completion(inst, prof) + total = 0 + for p in result: + total += p.cost + assert total <= 150 + # should at least select the base EES result {p1, p3} + names = sorted(_selected_names(result)) + assert "p1" in names + assert "p3" in names + + +# completion should spend at least as much as base EES +def test_completion_spends_at_least_as_much_as_ees(): + inst, prof, projects = _make_instance_profile({"p1": 2, "p2": 3.2, "p3": 6}, + 10, + [{"p1"}, {"p1", "p3"}, {"p2", "p3"}, {"p2", "p3"}, {"p3"}],) + ees_result = exact_equal_shares(inst, prof) + ees_cost = 0 + for p in ees_result: + ees_cost += p.cost + + completion_result = ees_add_opt_completion(inst, prof) + completion_cost = 0 + for p in completion_result: + completion_cost += p.cost + + assert completion_cost >= ees_cost + + if __name__ == "__main__": pytest.main(["-v", __file__]) From 32a25849c5279fda02ce7a94270102496c334abf Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Sun, 7 Jun 2026 11:43:53 +0300 Subject: [PATCH 3/8] Add logging to EES/add-opt algorithms and running example --- examples/run_ees_addopt.py | 168 ++++++++++++++++++++++++++++++++++ pabutools/rules/ees_addopt.py | 31 ++++++- 2 files changed, 198 insertions(+), 1 deletion(-) create mode 100644 examples/run_ees_addopt.py diff --git a/examples/run_ees_addopt.py b/examples/run_ees_addopt.py new file mode 100644 index 0000000..adfced5 --- /dev/null +++ b/examples/run_ees_addopt.py @@ -0,0 +1,168 @@ +""" +Running example for all algorithms in pabutools.rules.ees_addopt. + +Demonstrates: + 1. exact_equal_shares (Algorithm 1 – EES) + 2. get_leftover_budgets (leftover budget helper) + 3. get_leximax_payment (leximax payment helper) + 4. greedy_project_change (Algorithm 2 – GPC) + 5. add_opt (Algorithm 3 – add-opt) + 6. ees_add_opt_completion (EES completion via add-opt) +""" + +import logging + +from pabutools.election import Instance, Project, ApprovalProfile, ApprovalBallot +from pabutools.fractions import frac +from pabutools.rules.budgetallocation import BudgetAllocation +from pabutools.rules.ees_addopt import ( + EESAllocationDetails, + exact_equal_shares, + get_leftover_budgets, + get_leximax_payment, + greedy_project_change, + add_opt, + ees_add_opt_completion, +) + +# Show all log messages from the module. +logging.basicConfig( + level=logging.DEBUG, + format="%(name)s %(levelname)s %(message)s", + stream=__import__("sys").stdout, +) + +SEPARATOR = "\n" + "=" * 70 + "\n" + + +# A small PB instance with 5 voters and 3 projects. +# Projects: p1 (cost 2), p2 (cost 3.2), p3 (cost 6) +# Budget: 10 +# Voter 0 approves {p1} +# Voter 1 approves {p1, p3} +# Voter 2 approves {p2, p3} +# Voter 3 approves {p2, p3} +# Voter 4 approves {p3} + +p1 = Project("p1", 2) +p2 = Project("p2", 3.2) +p3 = Project("p3", 6) +projects = [p1, p2, p3] +budget = 10 + +instance = Instance(projects, budget_limit=budget) +profile = ApprovalProfile( + [ + ApprovalBallot([p1]), + ApprovalBallot([p1, p3]), + ApprovalBallot([p2, p3]), + ApprovalBallot([p2, p3]), + ApprovalBallot([p3]), + ], + instance=instance, +) + +num_voters = len(profile) +print("Instance") +print(f" Budget : {budget}") +print(f" Projects : {[(p.name, p.cost) for p in projects]}") +print(f" Num voters : {num_voters}") +print(f" Approvals :") +for i, ballot in enumerate(profile): + print(f" Voter {i}: {sorted(p.name for p in ballot)}") + + +# 1. exact_equal_shares (Algorithm 1) +print(SEPARATOR) +print("1. exact_equal_shares (Algorithm 1 – EES)") +print("-" * 42) + +ees_result = exact_equal_shares(instance, profile) + +print(f"\n Selected projects : {[p.name for p in ees_result]}") +total_cost = sum(frac(p.cost) for p in ees_result) +print(f" Total cost : {total_cost}") + +payments = ees_result.details.payments +print(" Per-voter payments:") +for voter in range(num_voters): + voter_pay = payments.get(voter, {}) + items = [(p.name, float(v)) for p, v in voter_pay.items()] + print(f" Voter {voter}: {items if items else '(none)'}") + + +# 2. get_leftover_budgets +print(SEPARATOR) +print("2. get_leftover_budgets") +print("-" * 42) + +leftover = get_leftover_budgets(instance, profile, ees_result) + +print(" Leftover budget per voter:") +for voter in range(num_voters): + print(f" Voter {voter}: {float(leftover[voter]):.4f}") + + +# 3. get_leximax_payment +print(SEPARATOR) +print("3. get_leximax_payment") +print("-" * 42) + +leximax = get_leximax_payment(ees_result, num_voters, instance) + +print(" Leximax payment vectors:") +for voter in range(num_voters): + formatted = [(float(amt), name) for amt, name in leximax[voter]] + print(f" Voter {voter}: {formatted}") + + +# 4. greedy_project_change (Algorithm 2 – GPC) +print(SEPARATOR) +print("4. greedy_project_change (Algorithm 2 – GPC)") +print("-" * 42) + +print(" Testing each project as instability certificate:") +for proj in projects: + d = greedy_project_change( + instance, profile, ees_result, proj, leftover, leximax + ) + print(f" Project '{proj.name}' (cost={proj.cost}): d = {d} ({float(d):.4f})") + + +# 5. add_opt (Algorithm 3) +print(SEPARATOR) +print("5. add_opt (Algorithm 3)") +print("-" * 42) + +d_min = add_opt(instance, profile, ees_result) + +print(f"\n Minimum d over all projects: {d_min} ({float(d_min):.4f})") +print(f" Per-voter budget increase : {float(d_min):.4f}") +print(f" Total budget increase (n*d): {float(num_voters * d_min):.4f}") + + +# 6. ees_add_opt_completion (EES completion via add-opt) +print(SEPARATOR) +print("6. ees_add_opt_completion (EES completed via add-opt)") +print("-" * 42) + +completed = ees_add_opt_completion(instance, profile) + +print(f"\n Selected projects : {sorted(p.name for p in completed)}") +completed_cost = sum(frac(p.cost) for p in completed) +print(f" Total cost : {completed_cost} (budget = {budget})") + +if hasattr(completed.details, "payments"): + print(" Per-voter payments:") + for voter in range(num_voters): + voter_pay = completed.details.payments.get(voter, {}) + items = [(p.name, float(v)) for p, v in voter_pay.items()] + print(f" Voter {voter}: {items if items else '(none)'}") + + +# Comparison +print(SEPARATOR) +print("Summary comparison") +print("-" * 42) +print(f" EES alone : {str([p.name for p in ees_result]):30s} cost = {float(total_cost)}") +print(f" EES + add-opt : {str(sorted(p.name for p in completed)):30s} cost = {float(completed_cost)}") diff --git a/pabutools/rules/ees_addopt.py b/pabutools/rules/ees_addopt.py index d481ad3..31837f9 100644 --- a/pabutools/rules/ees_addopt.py +++ b/pabutools/rules/ees_addopt.py @@ -9,6 +9,8 @@ from __future__ import annotations +import logging + from pabutools.election.instance import Instance, Project from pabutools.election.profile import AbstractApprovalProfile from pabutools.fractions import frac @@ -16,6 +18,8 @@ from pabutools.tiebreaking import lexico_tie_breaking from pabutools.utils import Numeric +logger = logging.getLogger(__name__) + class EESAllocationDetails(AllocationDetails): """ @@ -82,8 +86,11 @@ def exact_equal_shares( >>> [p.name for p in result] ['p1', 'p2'] """ + logger.info("exact_equal_shares: starting with %d projects, budget_limit=%s, %d voters", + len(instance), instance.budget_limit, len(profile)) n = len(profile) if n == 0: + logger.info("exact_equal_shares: no voters, returning empty allocation") return BudgetAllocation(details=EESAllocationDetails()) b = instance.budget_limit @@ -147,6 +154,8 @@ def exact_equal_shares( # Line 4-5: Return the current allocation if no feasible project remains. if not best_candidates: + logger.info("exact_equal_shares: no feasible project remains, returning %d selected projects", + len(selected_projects)) return BudgetAllocation(selected_projects, details=EESAllocationDetails(payments)) # Line 9: Break ties among the best feasible projects. @@ -165,6 +174,8 @@ def exact_equal_shares( break # Line 10: Add the chosen project to the allocation. + logger.debug("exact_equal_shares: selected project '%s' (cost=%s, score=%s, supporters=%d)", + chosen_project.name, chosen_project.cost, best_score, len(chosen_supporters)) selected_projects.append(chosen_project) # Line 11: Charge each chosen supporter an equal share of the project cost. @@ -208,6 +219,7 @@ def get_leftover_budgets( leftover[i] = b/n - sum of payments by voter i across all selected projects. """ + logger.debug("get_leftover_budgets: computing for %d voters", len(profile)) num_voters = len(profile) budget_limit = instance.budget_limit allocation_details = current_solution.details @@ -236,6 +248,7 @@ def get_leximax_payment( When a voter made no payments, their entry is ``[(0, smallest_name)]`` so that non-paying voters never certify instability. """ + logger.debug("get_leximax_payment: computing for %d voters", num_voters) allocation_details = current_solution.details smallest_project_name = "" for project in instance: @@ -327,6 +340,8 @@ def greedy_project_change( >>> greedy_project_change(inst, prof, solution, p3, leftover, leximax) mpq(1,2) """ + logger.debug("greedy_project_change: computing d for project '%s' (cost=%s)", + project.name, project.cost) n = len(profile) # All voters who approve project. @@ -420,7 +435,9 @@ def greedy_project_change( leftover_index += 1 # Line 20: Return the best budget increase found. - return max(0, d) + result = max(0, d) + logger.debug("greedy_project_change: project '%s' => d=%s", project.name, result) + return result def add_opt( @@ -471,6 +488,8 @@ def add_opt( >>> add_opt(inst, prof, solution) mpq(1,2) """ + logger.info("add_opt: computing minimum d over %d projects, %d voters", + len(instance), len(profile)) n = len(profile) # Precompute leftover budgets and leximax payments for all voters @@ -493,6 +512,7 @@ def add_opt( d = min(d, gpc_result) # Line 7: Return the minimum change over all projects. + logger.info("add_opt: minimum d=%s", d) return d @@ -540,8 +560,11 @@ def ees_add_opt_completion( >>> sorted(p.name for p in result) ['p1', 'p3'] """ + logger.info("ees_add_opt_completion: starting with %d projects, budget_limit=%s, %d voters", + len(instance), instance.budget_limit, len(profile)) n = len(profile) if n == 0: + logger.info("ees_add_opt_completion: no voters, delegating to exact_equal_shares") return exact_equal_shares(instance, profile, utilities) original_budget = instance.budget_limit @@ -557,17 +580,23 @@ def ees_add_opt_completion( total_cost = 0 for project in result: total_cost += frac(project.cost) + logger.debug("ees_add_opt_completion: virtual_budget=%s, EES selected %d projects, total_cost=%s", + virtual_budget, len(result), total_cost) if total_cost <= original_budget and total_cost > best_result_cost: best_result = result best_result_cost = total_cost d = add_opt(virtual_inst, profile, result) if d == float('inf') or d <= 0: + logger.debug("ees_add_opt_completion: stopping (d=%s)", d) break virtual_budget = virtual_budget + n * frac(d) + logger.debug("ees_add_opt_completion: increasing virtual_budget to %s (d=%s)", virtual_budget, d) if best_result is None: best_result = exact_equal_shares(instance, profile, utilities) + logger.info("ees_add_opt_completion: returning %d projects, total_cost=%s", + len(best_result), best_result_cost) return best_result From c055dad5c71685707edbf2dad9cddd347c8eb452 Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Sun, 7 Jun 2026 12:17:04 +0300 Subject: [PATCH 4/8] delete examples --- examples/run_ees_addopt.py | 168 ------------------------------------- 1 file changed, 168 deletions(-) delete mode 100644 examples/run_ees_addopt.py diff --git a/examples/run_ees_addopt.py b/examples/run_ees_addopt.py deleted file mode 100644 index adfced5..0000000 --- a/examples/run_ees_addopt.py +++ /dev/null @@ -1,168 +0,0 @@ -""" -Running example for all algorithms in pabutools.rules.ees_addopt. - -Demonstrates: - 1. exact_equal_shares (Algorithm 1 – EES) - 2. get_leftover_budgets (leftover budget helper) - 3. get_leximax_payment (leximax payment helper) - 4. greedy_project_change (Algorithm 2 – GPC) - 5. add_opt (Algorithm 3 – add-opt) - 6. ees_add_opt_completion (EES completion via add-opt) -""" - -import logging - -from pabutools.election import Instance, Project, ApprovalProfile, ApprovalBallot -from pabutools.fractions import frac -from pabutools.rules.budgetallocation import BudgetAllocation -from pabutools.rules.ees_addopt import ( - EESAllocationDetails, - exact_equal_shares, - get_leftover_budgets, - get_leximax_payment, - greedy_project_change, - add_opt, - ees_add_opt_completion, -) - -# Show all log messages from the module. -logging.basicConfig( - level=logging.DEBUG, - format="%(name)s %(levelname)s %(message)s", - stream=__import__("sys").stdout, -) - -SEPARATOR = "\n" + "=" * 70 + "\n" - - -# A small PB instance with 5 voters and 3 projects. -# Projects: p1 (cost 2), p2 (cost 3.2), p3 (cost 6) -# Budget: 10 -# Voter 0 approves {p1} -# Voter 1 approves {p1, p3} -# Voter 2 approves {p2, p3} -# Voter 3 approves {p2, p3} -# Voter 4 approves {p3} - -p1 = Project("p1", 2) -p2 = Project("p2", 3.2) -p3 = Project("p3", 6) -projects = [p1, p2, p3] -budget = 10 - -instance = Instance(projects, budget_limit=budget) -profile = ApprovalProfile( - [ - ApprovalBallot([p1]), - ApprovalBallot([p1, p3]), - ApprovalBallot([p2, p3]), - ApprovalBallot([p2, p3]), - ApprovalBallot([p3]), - ], - instance=instance, -) - -num_voters = len(profile) -print("Instance") -print(f" Budget : {budget}") -print(f" Projects : {[(p.name, p.cost) for p in projects]}") -print(f" Num voters : {num_voters}") -print(f" Approvals :") -for i, ballot in enumerate(profile): - print(f" Voter {i}: {sorted(p.name for p in ballot)}") - - -# 1. exact_equal_shares (Algorithm 1) -print(SEPARATOR) -print("1. exact_equal_shares (Algorithm 1 – EES)") -print("-" * 42) - -ees_result = exact_equal_shares(instance, profile) - -print(f"\n Selected projects : {[p.name for p in ees_result]}") -total_cost = sum(frac(p.cost) for p in ees_result) -print(f" Total cost : {total_cost}") - -payments = ees_result.details.payments -print(" Per-voter payments:") -for voter in range(num_voters): - voter_pay = payments.get(voter, {}) - items = [(p.name, float(v)) for p, v in voter_pay.items()] - print(f" Voter {voter}: {items if items else '(none)'}") - - -# 2. get_leftover_budgets -print(SEPARATOR) -print("2. get_leftover_budgets") -print("-" * 42) - -leftover = get_leftover_budgets(instance, profile, ees_result) - -print(" Leftover budget per voter:") -for voter in range(num_voters): - print(f" Voter {voter}: {float(leftover[voter]):.4f}") - - -# 3. get_leximax_payment -print(SEPARATOR) -print("3. get_leximax_payment") -print("-" * 42) - -leximax = get_leximax_payment(ees_result, num_voters, instance) - -print(" Leximax payment vectors:") -for voter in range(num_voters): - formatted = [(float(amt), name) for amt, name in leximax[voter]] - print(f" Voter {voter}: {formatted}") - - -# 4. greedy_project_change (Algorithm 2 – GPC) -print(SEPARATOR) -print("4. greedy_project_change (Algorithm 2 – GPC)") -print("-" * 42) - -print(" Testing each project as instability certificate:") -for proj in projects: - d = greedy_project_change( - instance, profile, ees_result, proj, leftover, leximax - ) - print(f" Project '{proj.name}' (cost={proj.cost}): d = {d} ({float(d):.4f})") - - -# 5. add_opt (Algorithm 3) -print(SEPARATOR) -print("5. add_opt (Algorithm 3)") -print("-" * 42) - -d_min = add_opt(instance, profile, ees_result) - -print(f"\n Minimum d over all projects: {d_min} ({float(d_min):.4f})") -print(f" Per-voter budget increase : {float(d_min):.4f}") -print(f" Total budget increase (n*d): {float(num_voters * d_min):.4f}") - - -# 6. ees_add_opt_completion (EES completion via add-opt) -print(SEPARATOR) -print("6. ees_add_opt_completion (EES completed via add-opt)") -print("-" * 42) - -completed = ees_add_opt_completion(instance, profile) - -print(f"\n Selected projects : {sorted(p.name for p in completed)}") -completed_cost = sum(frac(p.cost) for p in completed) -print(f" Total cost : {completed_cost} (budget = {budget})") - -if hasattr(completed.details, "payments"): - print(" Per-voter payments:") - for voter in range(num_voters): - voter_pay = completed.details.payments.get(voter, {}) - items = [(p.name, float(v)) for p, v in voter_pay.items()] - print(f" Voter {voter}: {items if items else '(none)'}") - - -# Comparison -print(SEPARATOR) -print("Summary comparison") -print("-" * 42) -print(f" EES alone : {str([p.name for p in ees_result]):30s} cost = {float(total_cost)}") -print(f" EES + add-opt : {str(sorted(p.name for p in completed)):30s} cost = {float(completed_cost)}") From 79fae41acc516a0044219a7f6982508a3bb3bfd9 Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Sun, 7 Jun 2026 14:04:51 +0300 Subject: [PATCH 5/8] Add Flask web demo for the Method of Equal Shares (EES add-opt) Visual point-and-click election builder, plain-language step-by-step results with a log viewer, a sample-by-size generator, and an about page. Wraps pabutools.rules.ees_addopt without changing the algorithm. --- examples/ees_addopt_web/README.md | 32 + examples/ees_addopt_web/app.py | 448 +++++++++ examples/ees_addopt_web/requirements.txt | 1 + examples/ees_addopt_web/static/builder.js | 360 +++++++ examples/ees_addopt_web/static/styles.css | 935 ++++++++++++++++++ examples/ees_addopt_web/templates/about.html | 68 ++ examples/ees_addopt_web/templates/base.html | 30 + examples/ees_addopt_web/templates/index.html | 99 ++ examples/ees_addopt_web/templates/result.html | 268 +++++ 9 files changed, 2241 insertions(+) create mode 100644 examples/ees_addopt_web/README.md create mode 100644 examples/ees_addopt_web/app.py create mode 100644 examples/ees_addopt_web/requirements.txt create mode 100644 examples/ees_addopt_web/static/builder.js create mode 100644 examples/ees_addopt_web/static/styles.css create mode 100644 examples/ees_addopt_web/templates/about.html create mode 100644 examples/ees_addopt_web/templates/base.html create mode 100644 examples/ees_addopt_web/templates/index.html create mode 100644 examples/ees_addopt_web/templates/result.html diff --git a/examples/ees_addopt_web/README.md b/examples/ees_addopt_web/README.md new file mode 100644 index 0000000..c8ce53a --- /dev/null +++ b/examples/ees_addopt_web/README.md @@ -0,0 +1,32 @@ +# EES add-opt Flask demo + +This small Flask app demonstrates `exact_equal_shares`, `add_opt`, and `ees_add_opt_completion` from `pabutools.rules.ees_addopt`. + +## Run + +From the repository root: + +```powershell +python -m pip install -r examples/ees_addopt_web/requirements.txt +python examples/ees_addopt_web/app.py +``` + +Then open . + +## Input format + +```text +Budget: 10 + +Projects: +p1, 2 +p2, 3.2 +p3, 6 + +Ballots: +p1 +p1, p3 +p2, p3 +``` + +Use `-` for a voter who approves no projects. \ No newline at end of file diff --git a/examples/ees_addopt_web/app.py b/examples/ees_addopt_web/app.py new file mode 100644 index 0000000..d23985a --- /dev/null +++ b/examples/ees_addopt_web/app.py @@ -0,0 +1,448 @@ +"""A beginner-friendly web demo for the Method of Equal Shares (with add-opt completion). + +You do not need to know how the algorithm works to use this site. You describe a +simple situation - some money to share, a few projects, and who voted for what - +and the site shows which projects get funded and explains, with real numbers, why +the result is fair. + +The heavy lifting is done by the library function +``pabutools.rules.ees_addopt.ees_add_opt_completion``. This file only wraps it in +a friendly interface; it never changes the algorithm itself. +""" + +from __future__ import annotations + +import io +import json +import logging +import sys +from dataclasses import dataclass +from pathlib import Path +from typing import Any + +from flask import Flask, Response, render_template, request + +ROOT_DIR = Path(__file__).resolve().parents[2] +if str(ROOT_DIR) not in sys.path: + sys.path.insert(0, str(ROOT_DIR)) + +from pabutools.election.ballot import ApprovalBallot +from pabutools.election.instance import Instance, Project +from pabutools.election.profile import ApprovalProfile +from pabutools.fractions import frac, str_as_frac +from pabutools.rules.ees_addopt import ( + add_opt, + exact_equal_shares, + get_leftover_budgets, + get_leximax_payment, +) + +app = Flask(__name__) + +ALGORITHM_LOGGER = logging.getLogger("pabutools.rules.ees_addopt") + +# A ready-made, relatable example used for the "Load example" button and the +# first time the page is opened. Project indices in "voters" are 0-based and +# point into the "projects" list. +EXAMPLE: dict[str, Any] = { + "budget": "10", + "projects": [ + {"name": "New benches", "cost": "2"}, + {"name": "Bike lane", "cost": "3.2"}, + {"name": "Playground", "cost": "6"}, + ], + "voters": [ + [0], + [0, 2], + [1, 2], + [1, 2], + [2], + ], +} + + +@dataclass(frozen=True) +class ParsedElection: + instance: Instance + profile: ApprovalProfile + projects: list[Project] + project_names: list[str] + ballots: list[list[str]] + budget: Any + + +class InputError(ValueError): + """Raised when the submitted election cannot be understood.""" + + +def parse_number(raw_value: Any, field_name: str) -> Any: + """Turn user text into a non-negative number, with a friendly error if it is not one.""" + text = str(raw_value).strip() + if not text: + raise InputError(f"{field_name} is missing a value.") + try: + value = str_as_frac(text) + except Exception as exc: + raise InputError(f'"{text}" is not a valid number for {field_name.lower()}.') from exc + if value < 0: + raise InputError(f"{field_name} cannot be negative.") + return value + + +def parse_election_from_payload(payload: Any) -> ParsedElection: + """Build an election from the structured data sent by the visual builder.""" + if not isinstance(payload, dict): + raise InputError("The form could not be read. Please reload the page and try again.") + + budget = parse_number(payload.get("budget", ""), "The budget") + + raw_projects = payload.get("projects") + if not isinstance(raw_projects, list) or not raw_projects: + raise InputError("Add at least one project.") + + projects: list[Project] = [] + seen_names: set[str] = set() + for position, item in enumerate(raw_projects, start=1): + item = item or {} + name = str(item.get("name", "")).strip() + if not name: + raise InputError(f"Project {position} needs a name.") + if name in seen_names: + raise InputError(f'Two projects are both called "{name}". Please give each project a different name.') + cost = parse_number(item.get("cost", ""), f'The cost of "{name}"') + seen_names.add(name) + projects.append(Project(name, cost)) + + raw_voters = payload.get("voters") + if not isinstance(raw_voters, list) or not raw_voters: + raise InputError("Add at least one voter.") + + ballots: list[ApprovalBallot] = [] + ballot_names: list[list[str]] = [] + for voter_position, approvals in enumerate(raw_voters, start=1): + if approvals is None: + approvals = [] + if not isinstance(approvals, list): + raise InputError(f"Voter {voter_position}'s choices could not be read.") + chosen_indices: list[int] = [] + for raw_index in approvals: + try: + index = int(raw_index) + except (TypeError, ValueError): + raise InputError(f"Voter {voter_position} has an invalid project choice.") + if index < 0 or index >= len(projects): + raise InputError(f"Voter {voter_position} voted for a project that does not exist.") + chosen_indices.append(index) + chosen_indices = sorted(set(chosen_indices)) + ballot_names.append([projects[index].name for index in chosen_indices]) + ballots.append(ApprovalBallot(projects[index] for index in chosen_indices)) + + instance = Instance(projects, budget_limit=budget) + profile = ApprovalProfile(ballots, instance=instance) + return ParsedElection( + instance=instance, + profile=profile, + projects=projects, + project_names=[project.name for project in projects], + ballots=ballot_names, + budget=budget, + ) + + +def format_number(value: Any) -> str: + """Show a number in the friendliest readable form (whole number, decimal, or fraction).""" + if value == float("inf"): + return "infinity" + text = str(value) + if "/" in text: + try: + as_float = float(value) + except (TypeError, ValueError): + return text + if abs(as_float - round(as_float)) < 1e-10: + return str(round(as_float)) + return f"{as_float:.4g}" + return text + + +def total_cost(projects: list[Project]) -> Any: + total = frac(0) + for project in projects: + total += frac(project.cost) + return total + + +def supporters_by_project(parsed: ParsedElection) -> dict[str, int]: + counts = {project.name: 0 for project in parsed.projects} + for ballot in parsed.ballots: + for project_name in ballot: + counts[project_name] += 1 + return counts + + +def summarize_allocation(parsed: ParsedElection, allocation: list[Project]) -> dict[str, Any]: + """Describe one outcome: which projects, who paid, and how much each voter kept.""" + selected_projects = list(allocation) + selected_names = [project.name for project in selected_projects] + details = getattr(allocation, "details", None) + payments = getattr(details, "payments", {}) if details is not None else {} + number_of_voters = len(parsed.profile) + voter_budget = frac(parsed.instance.budget_limit) / number_of_voters if number_of_voters else frac(0) + cost_value = total_cost(selected_projects) + + project_payments = [] + for project in selected_projects: + paid = frac(0) + payers = [] + for voter_index in range(number_of_voters): + amount = payments.get(voter_index, {}).get(project, frac(0)) + if amount: + payers.append({"voter": voter_index + 1, "amount": format_number(amount)}) + paid += amount + project_payments.append( + { + "name": project.name, + "cost": format_number(project.cost), + "paid": format_number(paid), + "is_fully_paid": paid == frac(project.cost), + "payers": payers, + } + ) + + voter_rows = [] + for voter_index in range(number_of_voters): + paid_total = frac(0) + paid_entries = [] + for project in selected_projects: + amount = payments.get(voter_index, {}).get(project, frac(0)) + if amount: + paid_entries.append(f"{project.name}: {format_number(amount)}") + paid_total += amount + voter_rows.append( + { + "number": voter_index + 1, + "approvals": ", ".join(parsed.ballots[voter_index]) or "nothing", + "payments": ", ".join(paid_entries) or "-", + "paid_total": format_number(paid_total), + "leftover": format_number(voter_budget - paid_total), + "within_budget": paid_total <= voter_budget, + } + ) + + return { + "selected_names": selected_names, + "selected_display": ", ".join(selected_names) if selected_names else "no projects", + "count": len(selected_names), + "is_empty": len(selected_names) == 0, + "total_cost": format_number(cost_value), + "total_cost_num": cost_value, + "is_budget_feasible": cost_value <= parsed.instance.budget_limit, + "project_payments": project_payments, + "voter_rows": voter_rows, + } + + +def percent_of_budget(used: Any, budget: Any) -> float: + budget_value = frac(budget) + if budget_value <= 0: + return 0.0 + fraction = float(frac(used) / budget_value) * 100.0 + return max(0.0, min(100.0, round(fraction, 1))) + + +def run_completion_with_steps(parsed: ParsedElection) -> tuple[list[dict[str, Any]], list[Project], int]: + """Reproduce the add-opt completion loop, recording every round as a visible step. + + This mirrors ``ees_add_opt_completion`` exactly - it only calls the same public + functions - so the page can show each round without changing the algorithm. + """ + instance = parsed.instance + profile = parsed.profile + number_of_voters = len(profile) + original_budget = frac(instance.budget_limit) + projects = list(instance) + + rounds: list[dict[str, Any]] = [] + virtual_budget = original_budget + best_index = -1 + best_cost = frac(-1) + + while True: + virtual_instance = Instance(projects, budget_limit=virtual_budget) + allocation = exact_equal_shares(virtual_instance, profile) + cost = total_cost(list(allocation)) + fits = cost <= original_budget + delta = add_opt(virtual_instance, profile, allocation) + rounds.append( + { + "allocation": allocation, + "virtual_budget": virtual_budget, + "share": virtual_budget / number_of_voters if number_of_voters else frac(0), + "selected": [project.name for project in allocation], + "total_cost": cost, + "fits": fits, + "delta": delta, + } + ) + if fits and cost > best_cost: + best_cost = cost + best_index = len(rounds) - 1 + if delta == float("inf") or delta <= 0 or len(rounds) >= 60: + break + virtual_budget = virtual_budget + number_of_voters * frac(delta) + + if best_index < 0: + best_index = 0 + return rounds, rounds[best_index]["allocation"], best_index + + +def analyze(parsed: ParsedElection) -> dict[str, Any]: + """Run the algorithm and assemble everything the results page needs to explain it.""" + log_stream = io.StringIO() + handler = logging.StreamHandler(log_stream) + handler.setFormatter(logging.Formatter("%(levelname)s: %(message)s")) + previous_level = ALGORITHM_LOGGER.level + previous_propagate = ALGORITHM_LOGGER.propagate + ALGORITHM_LOGGER.setLevel(logging.DEBUG) + ALGORITHM_LOGGER.propagate = False + ALGORITHM_LOGGER.addHandler(handler) + try: + rounds, completed_allocation, best_index = run_completion_with_steps(parsed) + base_allocation = rounds[0]["allocation"] + leftover_budgets = get_leftover_budgets(parsed.instance, parsed.profile, base_allocation) + leximax_payments = get_leximax_payment(base_allocation, len(parsed.profile), parsed.instance) + next_delta = rounds[0]["delta"] + finally: + ALGORITHM_LOGGER.removeHandler(handler) + ALGORITHM_LOGGER.setLevel(previous_level) + ALGORITHM_LOGGER.propagate = previous_propagate + + number_of_voters = len(parsed.profile) + budget_value = frac(parsed.budget) + share_value = budget_value / number_of_voters if number_of_voters else frac(0) + + base = summarize_allocation(parsed, base_allocation) + completed = summarize_allocation(parsed, completed_allocation) + + supporter_counts = supporters_by_project(parsed) + base_selected_names = set(base["selected_names"]) + completed_selected_names = set(completed["selected_names"]) + project_rows = [ + { + "name": project.name, + "cost": format_number(project.cost), + "supporters": supporter_counts[project.name], + "in_base": project.name in base_selected_names, + "in_completed": project.name in completed_selected_names, + } + for project in parsed.projects + ] + + leftover_rows = [ + { + "voter": voter_index + 1, + "leftover": format_number(leftover_budgets[voter_index]), + "leximax": ", ".join( + f"{project_name}: {format_number(amount)}" + for amount, project_name in leximax_payments[voter_index] + ), + } + for voter_index in range(number_of_voters) + ] + + completion_rounds = [] + for index, round_data in enumerate(rounds): + delta_value = round_data["delta"] + if delta_value == float("inf") or delta_value <= 0: + delta_display = None + else: + delta_display = format_number(delta_value) + completion_rounds.append( + { + "number": index + 1, + "share": format_number(round_data["share"]), + "selected_display": ", ".join(round_data["selected"]) if round_data["selected"] else "no projects", + "total_cost": format_number(round_data["total_cost"]), + "fits": round_data["fits"], + "delta": delta_display, + "is_chosen": index == best_index, + } + ) + + return { + "budget": format_number(parsed.budget), + "voter_count": number_of_voters, + "share_per_voter": format_number(share_value), + "project_count": len(parsed.projects), + "project_rows": project_rows, + "base": base, + "completed": completed, + "base_leftover": format_number(budget_value - base["total_cost_num"]), + "completed_leftover": format_number(budget_value - completed["total_cost_num"]), + "completed_used_percent": percent_of_budget(completed["total_cost_num"], parsed.budget), + "same_as_base": base_selected_names == completed_selected_names, + "completion_rounds": completion_rounds, + "completion_multistep": len(completion_rounds) > 1, + "chosen_round": best_index + 1, + "next_delta": format_number(next_delta), + "leftover_rows": leftover_rows, + "logs": [line for line in log_stream.getvalue().splitlines() if line.strip()], + } + + +@app.get("/") +def index(): + return render_template("index.html", initial_data=EXAMPLE, example_data=EXAMPLE, error=None) + + +@app.post("/run") +def run_algorithm(): + raw_payload = request.form.get("payload", "") + try: + payload = json.loads(raw_payload) if raw_payload else {} + except json.JSONDecodeError: + payload = {} + + fallback = payload if isinstance(payload, dict) and payload else EXAMPLE + try: + parsed = parse_election_from_payload(payload) + result = analyze(parsed) + except InputError as exc: + return ( + render_template("index.html", initial_data=fallback, example_data=EXAMPLE, error=str(exc)), + 400, + ) + except Exception as exc: # noqa: BLE001 - surface any unexpected failure to the user. + return ( + render_template( + "index.html", + initial_data=fallback, + example_data=EXAMPLE, + error=f"Something went wrong while running the election: {exc}", + ), + 400, + ) + return render_template("result.html", result=result) + + +@app.get("/about") +def about(): + return render_template("about.html") + + +# A tiny inline icon so browsers do not get a 404 when they ask for /favicon.ico. +FAVICON_SVG = ( + "" + "" + "" +) + + +@app.get("/favicon.ico") +def favicon(): + return Response(FAVICON_SVG, mimetype="image/svg+xml") + + +if __name__ == "__main__": + app.run(debug=True) diff --git a/examples/ees_addopt_web/requirements.txt b/examples/ees_addopt_web/requirements.txt new file mode 100644 index 0000000..a9039a4 --- /dev/null +++ b/examples/ees_addopt_web/requirements.txt @@ -0,0 +1 @@ +Flask>=3.0 \ No newline at end of file diff --git a/examples/ees_addopt_web/static/builder.js b/examples/ees_addopt_web/static/builder.js new file mode 100644 index 0000000..cca78c4 --- /dev/null +++ b/examples/ees_addopt_web/static/builder.js @@ -0,0 +1,360 @@ +// Powers the visual election builder on the home page. +// No part of the algorithm lives here - this only collects the user's input +// (budget, projects, votes) and sends it to the server as simple JSON. +(function () { + "use strict"; + + const budgetEl = document.getElementById("budget"); + const projectsEl = document.getElementById("projects"); + const votersEl = document.getElementById("voters"); + const payloadEl = document.getElementById("payload"); + const form = document.getElementById("builder"); + const errorEl = document.getElementById("form-error"); + const runButton = document.getElementById("run-button"); + + let nextId = 1; + let projects = []; // [{ id, name, cost }] + let voters = []; // [{ id, approvals: Set }] + + function uid() { + return nextId++; + } + + // Load a data object (from the server) into the on-screen builder. + function loadData(data) { + data = data || {}; + const idByIndex = []; + projects = (data.projects || []).map(function (project, index) { + const id = uid(); + idByIndex[index] = id; + return { id: id, name: (project && project.name) || "", cost: project && project.cost != null ? String(project.cost) : "" }; + }); + voters = (data.voters || []).map(function (approvals) { + const set = new Set(); + (approvals || []).forEach(function (index) { + const id = idByIndex[index]; + if (id !== undefined) { + set.add(id); + } + }); + return { id: uid(), approvals: set }; + }); + budgetEl.value = data.budget != null ? String(data.budget) : ""; + render(); + } + + // Keep a typed size within sensible bounds. + function clampInt(value, min, max, fallback) { + const parsed = Math.floor(Number(value)); + if (Number.isNaN(parsed)) { + return fallback; + } + return Math.max(min, Math.min(max, parsed)); + } + + // Build a complete, ready-to-run example with the requested number of + // projects and voters, so the user can try the algorithm without typing + // every value by hand. + function generateSample(numProjects, numVoters) { + const generatedProjects = []; + let totalCost = 0; + let maxCost = 0; + for (let i = 0; i < numProjects; i++) { + const cost = 1 + Math.floor(Math.random() * 9); // 1..9 + totalCost += cost; + maxCost = Math.max(maxCost, cost); + generatedProjects.push({ name: "Project " + (i + 1), cost: String(cost) }); + } + const generatedVoters = []; + for (let v = 0; v < numVoters; v++) { + const approvals = []; + for (let i = 0; i < numProjects; i++) { + if (Math.random() < 0.5) { + approvals.push(i); + } + } + if (!approvals.length && numProjects > 0) { + approvals.push(Math.floor(Math.random() * numProjects)); // never leave a voter empty + } + generatedVoters.push(approvals); + } + // A budget big enough to fund some, but usually not all, projects. + const budget = Math.max(maxCost, Math.round(totalCost * 0.6)); + return { budget: String(budget), projects: generatedProjects, voters: generatedVoters }; + } + + function addProject() { + projects.push({ id: uid(), name: "", cost: "" }); + render(); + focusLastProjectName(); + } + + function removeProject(id) { + projects = projects.filter(function (project) { + return project.id !== id; + }); + voters.forEach(function (voter) { + voter.approvals.delete(id); + }); + render(); + } + + function addVoter() { + voters.push({ id: uid(), approvals: new Set() }); + render(); + } + + function removeVoter(id) { + voters = voters.filter(function (voter) { + return voter.id !== id; + }); + render(); + } + + function projectLabel(project, index) { + const name = (project.name || "").trim(); + return name || "Project " + (index + 1); + } + + function renderProjects() { + projectsEl.innerHTML = ""; + if (!projects.length) { + const empty = document.createElement("p"); + empty.className = "muted empty-note"; + empty.textContent = "No projects yet. Click \u201c+ Add project\u201d to begin."; + projectsEl.appendChild(empty); + return; + } + projects.forEach(function (project, index) { + const row = document.createElement("div"); + row.className = "project-row"; + + const number = document.createElement("span"); + number.className = "row-index"; + number.textContent = String(index + 1); + + const nameInput = document.createElement("input"); + nameInput.type = "text"; + nameInput.className = "p-name"; + nameInput.placeholder = "e.g. New playground"; + nameInput.value = project.name; + nameInput.addEventListener("input", function () { + project.name = nameInput.value; + renderVoters(); + }); + + const costInput = document.createElement("input"); + costInput.type = "number"; + costInput.className = "p-cost"; + costInput.min = "0"; + costInput.step = "any"; + costInput.inputMode = "decimal"; + costInput.placeholder = "Cost"; + costInput.value = project.cost; + costInput.addEventListener("input", function () { + project.cost = costInput.value; + }); + + const remove = document.createElement("button"); + remove.type = "button"; + remove.className = "icon-button"; + remove.setAttribute("aria-label", "Remove this project"); + remove.textContent = "\u2715"; + remove.addEventListener("click", function () { + removeProject(project.id); + }); + + row.appendChild(number); + row.appendChild(nameInput); + row.appendChild(costInput); + row.appendChild(remove); + projectsEl.appendChild(row); + }); + } + + function renderVoters() { + votersEl.innerHTML = ""; + if (!voters.length) { + const empty = document.createElement("p"); + empty.className = "muted empty-note"; + empty.textContent = "No voters yet. Click \u201c+ Add voter\u201d to begin."; + votersEl.appendChild(empty); + return; + } + voters.forEach(function (voter, voterIndex) { + const card = document.createElement("div"); + card.className = "voter-row"; + + const head = document.createElement("div"); + head.className = "voter-head"; + + const title = document.createElement("strong"); + title.textContent = "Voter " + (voterIndex + 1); + + const remove = document.createElement("button"); + remove.type = "button"; + remove.className = "icon-button"; + remove.setAttribute("aria-label", "Remove this voter"); + remove.textContent = "\u2715"; + remove.addEventListener("click", function () { + removeVoter(voter.id); + }); + + head.appendChild(title); + head.appendChild(remove); + card.appendChild(head); + + const choices = document.createElement("div"); + choices.className = "choices"; + if (!projects.length) { + const note = document.createElement("span"); + note.className = "muted"; + note.textContent = "Add some projects first."; + choices.appendChild(note); + } else { + projects.forEach(function (project, index) { + const label = document.createElement("label"); + label.className = "choice"; + + const checkbox = document.createElement("input"); + checkbox.type = "checkbox"; + checkbox.checked = voter.approvals.has(project.id); + checkbox.addEventListener("change", function () { + if (checkbox.checked) { + voter.approvals.add(project.id); + } else { + voter.approvals.delete(project.id); + } + label.classList.toggle("is-on", checkbox.checked); + }); + + const text = document.createElement("span"); + text.textContent = projectLabel(project, index); + + label.classList.toggle("is-on", checkbox.checked); + label.appendChild(checkbox); + label.appendChild(text); + choices.appendChild(label); + }); + } + card.appendChild(choices); + votersEl.appendChild(card); + }); + } + + function render() { + renderProjects(); + renderVoters(); + } + + function focusLastProjectName() { + const inputs = projectsEl.querySelectorAll(".p-name"); + if (inputs.length) { + inputs[inputs.length - 1].focus(); + } + } + + function buildPayload() { + return { + budget: budgetEl.value.trim(), + projects: projects.map(function (project) { + return { name: project.name.trim(), cost: project.cost.trim() }; + }), + voters: voters.map(function (voter) { + const indices = []; + projects.forEach(function (project, index) { + if (voter.approvals.has(project.id)) { + indices.push(index); + } + }); + return indices; + }), + }; + } + + function isValidNumber(text) { + if (text === "") { + return false; + } + const value = Number(text); + return !Number.isNaN(value) && value >= 0; + } + + function validate(payload) { + if (!isValidNumber(payload.budget)) { + return "Enter a budget of 0 or more."; + } + if (!payload.projects.length) { + return "Add at least one project."; + } + const seen = new Set(); + for (let i = 0; i < payload.projects.length; i++) { + const project = payload.projects[i]; + if (!project.name) { + return "Project " + (i + 1) + " needs a name."; + } + if (seen.has(project.name)) { + return 'Two projects are called "' + project.name + '". Use different names.'; + } + seen.add(project.name); + if (!isValidNumber(project.cost)) { + return 'Enter a valid cost for "' + project.name + '".'; + } + } + if (!payload.voters.length) { + return "Add at least one voter."; + } + return null; + } + + function showError(message) { + errorEl.textContent = message; + errorEl.hidden = false; + errorEl.scrollIntoView({ behavior: "smooth", block: "center" }); + } + + function hideError() { + errorEl.hidden = true; + errorEl.textContent = ""; + } + + form.addEventListener("submit", function (event) { + const payload = buildPayload(); + const message = validate(payload); + if (message) { + event.preventDefault(); + showError(message); + return; + } + hideError(); + payloadEl.value = JSON.stringify(payload); + runButton.disabled = true; + runButton.textContent = "Working\u2026"; + }); + + document.getElementById("generate").addEventListener("click", function () { + hideError(); + const projectsInput = document.getElementById("gen-projects"); + const votersInput = document.getElementById("gen-voters"); + const numProjects = clampInt(projectsInput.value, 1, 20, 4); + const numVoters = clampInt(votersInput.value, 1, 50, 6); + projectsInput.value = String(numProjects); + votersInput.value = String(numVoters); + loadData(generateSample(numProjects, numVoters)); + }); + document.getElementById("add-project").addEventListener("click", addProject); + document.getElementById("add-voter").addEventListener("click", addVoter); + document.getElementById("load-example").addEventListener("click", function () { + hideError(); + loadData(window.EXAMPLE_DATA); + }); + document.getElementById("clear-all").addEventListener("click", function () { + hideError(); + loadData({ budget: "", projects: [{ name: "", cost: "" }], voters: [[]] }); + }); + + const start = window.INITIAL_DATA && window.INITIAL_DATA.projects && window.INITIAL_DATA.projects.length + ? window.INITIAL_DATA + : window.EXAMPLE_DATA; + loadData(start); +})(); diff --git a/examples/ees_addopt_web/static/styles.css b/examples/ees_addopt_web/static/styles.css new file mode 100644 index 0000000..8e63e76 --- /dev/null +++ b/examples/ees_addopt_web/static/styles.css @@ -0,0 +1,935 @@ +:root { + color-scheme: light; + --bg: #f4f7fb; + --surface: #ffffff; + --surface-soft: #eef5f3; + --text: #1f2a33; + --muted: #5d6b77; + --line: #d8e1e8; + --brand: #1f7a70; + --brand-strong: #155d55; + --accent: #2f6df0; + --good: #1f7a45; + --good-soft: #e9f6ee; + --warn: #8a5a18; + --warn-soft: #fdf3e6; + --shadow: 0 10px 28px rgba(24, 45, 58, 0.08); + --radius: 12px; +} + +* { + box-sizing: border-box; +} + +html { + scroll-behavior: smooth; +} + +body { + margin: 0; + background: var(--bg); + color: var(--text); + font-family: "Segoe UI", Arial, sans-serif; + line-height: 1.55; +} + +a { + color: var(--brand-strong); +} + +/* ---------- Top bar ---------- */ +.topbar { + align-items: center; + background: var(--surface); + border-bottom: 1px solid var(--line); + display: flex; + gap: 20px; + justify-content: space-between; + padding: 14px clamp(16px, 4vw, 56px); + position: sticky; + top: 0; + z-index: 10; +} + +.brand { + align-items: center; + color: var(--brand); + display: flex; + font-size: 1.1rem; + font-weight: 800; + gap: 10px; + text-decoration: none; +} + +.brand-mark { + background: var(--brand); + border-radius: 8px; + color: #fff; + display: inline-grid; + font-size: 0.85rem; + height: 30px; + place-items: center; + width: 30px; +} + +.topbar nav { + display: flex; + flex-wrap: wrap; + gap: 8px 18px; +} + +.topbar nav a { + border-radius: 8px; + color: var(--text); + padding: 6px 10px; + text-decoration: none; +} + +.topbar nav a:hover { + background: var(--surface-soft); +} + +/* ---------- Layout ---------- */ +.page { + margin: 0 auto; + max-width: 1000px; + padding: 24px clamp(16px, 4vw, 40px) 56px; +} + +.band, +.panel { + background: var(--surface); + border: 1px solid var(--line); + border-radius: var(--radius); + box-shadow: var(--shadow); +} + +.band { + align-items: center; + display: grid; + gap: 28px; + grid-template-columns: minmax(0, 1.4fr) minmax(220px, 0.9fr); + margin-bottom: 22px; + padding: clamp(22px, 4vw, 38px); +} + +.panel { + margin-bottom: 18px; + padding: clamp(18px, 3vw, 26px); +} + +h1, +h2, +h3 { + line-height: 1.2; + margin: 0 0 12px; +} + +h1 { + color: var(--text); + font-size: clamp(1.8rem, 3.4vw, 2.5rem); +} + +h2 { + font-size: 1.3rem; +} + +h3 { + color: var(--brand-strong); + font-size: 1.02rem; + margin-top: 22px; +} + +.lead { + font-size: 1.08rem; +} + +.eyebrow { + color: var(--brand); + font-size: 0.8rem; + font-weight: 800; + letter-spacing: 0.04em; + margin: 0 0 8px; + text-transform: uppercase; +} + +.muted { + color: var(--muted); + margin-top: 0; +} + +/* ---------- Home hero steps ---------- */ +.steps { + display: grid; + gap: 10px; + list-style: none; + margin: 0; + padding: 0; +} + +.steps li { + align-items: center; + background: var(--surface-soft); + border: 1px solid #bfe0da; + border-radius: 10px; + color: var(--brand-strong); + display: flex; + font-weight: 700; + gap: 12px; + padding: 10px 14px; +} + +.steps li span { + background: var(--brand); + border-radius: 50%; + color: #fff; + display: inline-grid; + flex: none; + font-size: 0.85rem; + height: 26px; + place-items: center; + width: 26px; +} + +/* ---------- Forms ---------- */ +label { + color: var(--muted); + display: grid; + font-weight: 700; + gap: 8px; +} + +input, +textarea { + background: #fbfdfe; + border: 1px solid var(--line); + border-radius: 9px; + color: var(--text); + font: inherit; + padding: 11px 12px; + width: 100%; +} + +input:focus, +textarea:focus { + border-color: var(--brand); +} + +a:focus-visible, +button:focus-visible, +input:focus-visible, +textarea:focus-visible, +summary:focus-visible, +.choice:focus-within { + outline: 2px solid var(--accent); + outline-offset: 2px; +} + +button { + border-radius: 9px; + cursor: pointer; + font: inherit; + font-weight: 700; + padding: 11px 18px; +} + +button.primary-big, +button[type="submit"]:not(.secondary):not(.ghost) { + background: var(--brand); + border: 1px solid var(--brand); + color: #fff; + font-size: 1.05rem; + padding: 13px 24px; +} + +button.primary-big:hover { + background: var(--brand-strong); +} + +button.secondary { + background: var(--surface); + border: 1px solid var(--line); + color: var(--text); +} + +button.secondary:hover { + background: var(--surface-soft); +} + +button.ghost { + background: transparent; + border: 1px solid transparent; + color: var(--muted); +} + +button.ghost:hover { + color: var(--text); + text-decoration: underline; +} + +button:disabled { + cursor: progress; + opacity: 0.7; +} + +.actions { + display: flex; + flex-wrap: wrap; + gap: 12px; + margin-top: 6px; +} + +.step-number { + background: var(--brand); + border-radius: 50%; + color: #fff; + display: inline-grid; + font-size: 0.85rem; + height: 28px; + margin-right: 8px; + place-items: center; + vertical-align: middle; + width: 28px; +} + +.builder-step h2, +.run-panel h2 { + align-items: center; + display: flex; +} + +.budget-field { + max-width: 240px; +} + +.budget-field input { + font-size: 1.2rem; + font-weight: 700; +} + +/* ---------- Projects rows ---------- */ +.row-head { + color: var(--muted); + font-size: 0.78rem; + font-weight: 700; + letter-spacing: 0.03em; + text-transform: uppercase; +} + +.projects-head { + display: grid; + gap: 12px; + grid-template-columns: 34px 1fr 140px 40px; + margin-bottom: 8px; + padding: 0 2px; +} + +.project-row { + align-items: center; + display: grid; + gap: 12px; + grid-template-columns: 34px 1fr 140px 40px; + margin-bottom: 10px; +} + +.row-index { + color: var(--muted); + font-weight: 700; + text-align: center; +} + +.icon-button { + background: #fbeeee; + border: 1px solid #f0d2d2; + border-radius: 8px; + color: #a23b3b; + font-size: 0.9rem; + line-height: 1; + padding: 9px 0; + width: 100%; +} + +.icon-button:hover { + background: #f6dede; +} + +.add-button { + margin-top: 6px; +} + +.empty-note { + margin: 6px 0; +} + +/* ---------- Voters ---------- */ +.voter-row { + border: 1px solid var(--line); + border-radius: 10px; + margin-bottom: 12px; + padding: 12px 14px; +} + +.voter-head { + align-items: center; + display: flex; + justify-content: space-between; + margin-bottom: 10px; +} + +.voter-head .icon-button { + width: 36px; +} + +.choices { + display: flex; + flex-wrap: wrap; + gap: 8px 10px; +} + +.choice { + align-items: center; + background: #f7f9fb; + border: 1px solid var(--line); + border-radius: 999px; + color: var(--text); + cursor: pointer; + display: inline-flex; + font-weight: 600; + gap: 8px; + padding: 7px 14px 7px 10px; + user-select: none; +} + +.choice:hover { + border-color: var(--brand); +} + +.choice.is-on { + background: var(--surface-soft); + border-color: var(--brand); + color: var(--brand-strong); +} + +.choice input { + accent-color: var(--brand); + height: 16px; + margin: 0; + width: 16px; +} + +.run-panel { + border-color: #bfe0da; +} + +/* ---------- Alerts ---------- */ +.alert { + background: var(--warn-soft); + border: 1px solid #e7b87f; + border-radius: 10px; + color: var(--warn); + margin-bottom: 20px; + padding: 14px 16px; +} + +.field-error { + background: #fdecec; + border: 1px solid #efbcbc; + border-radius: 9px; + color: #9c2c2c; + font-weight: 600; + margin: 0 0 12px; + padding: 10px 14px; +} + +/* ---------- Result hero ---------- */ +.result-hero { + grid-template-columns: minmax(0, 1.3fr) minmax(240px, 1fr); +} + +.hero-side { + display: grid; + gap: 12px; +} + +.budget-meter { + background: #e6edf2; + border-radius: 999px; + height: 16px; + overflow: hidden; +} + +.budget-fill { + background: linear-gradient(90deg, var(--brand), #34a596); + height: 100%; +} + +.meter-legend { + color: var(--muted); + display: flex; + flex-wrap: wrap; + gap: 4px 16px; + font-size: 0.92rem; + justify-content: space-between; +} + +.meter-legend strong { + color: var(--text); +} + +/* ---------- Funded list ---------- */ +.funded-list { + display: grid; + gap: 10px; + list-style: none; + margin: 0; + padding: 0; +} + +.funded-list li { + align-items: center; + background: var(--good-soft); + border: 1px solid #bfe3cd; + border-radius: 10px; + display: flex; + gap: 12px; + padding: 12px 16px; +} + +.funded-list .check { + background: var(--good); + border-radius: 50%; + color: #fff; + display: inline-grid; + flex: none; + font-size: 0.85rem; + height: 24px; + place-items: center; + width: 24px; +} + +.funded-list .f-name { + font-weight: 700; +} + +.funded-list .f-cost { + color: var(--muted); + margin-left: auto; +} + +.explain p { + margin: 0 0 10px; +} + +.note { + border-radius: 9px; + font-weight: 600; + margin: 10px 0 0; + padding: 10px 14px; +} + +.note.good { + background: var(--good-soft); + border: 1px solid #bfe3cd; + color: var(--good); +} + +/* ---------- Tables ---------- */ +.table-wrap { + overflow-x: auto; + margin: 12px 0; +} + +table { + border-collapse: collapse; + min-width: 520px; + width: 100%; +} + +th, +td { + border-bottom: 1px solid var(--line); + padding: 10px 12px; + text-align: left; + vertical-align: top; +} + +th { + background: #eef2f5; + color: #36454f; + font-size: 0.9rem; +} + +tr.is-final td { + background: var(--good-soft); +} + +.pill { + background: #eef2f5; + border: 1px solid var(--line); + border-radius: 999px; + display: inline-block; + font-size: 0.85rem; + margin: 2px 3px 2px 0; + padding: 3px 10px; +} + +.tag { + border-radius: 999px; + display: inline-block; + font-size: 0.82rem; + font-weight: 700; + padding: 3px 11px; + white-space: nowrap; +} + +.tag.yes { + background: var(--good-soft); + border: 1px solid #bfe3cd; + color: var(--good); +} + +.tag.no { + background: #f3f5f6; + border: 1px solid #e2e8eb; + color: #8c99a2; +} + +.tag.muted-tag { + background: #eef2f5; + border: 1px solid var(--line); + color: var(--muted); +} + +/* ---------- Step-by-step ---------- */ +.steps-intro { + border-left: 4px solid var(--brand); +} + +.step-block { + position: relative; +} + +.step-head { + align-items: center; + display: flex; + gap: 12px; + margin-bottom: 8px; +} + +.step-head h2 { + margin: 0; +} + +.step-badge { + background: var(--brand); + border-radius: 50%; + color: #fff; + display: inline-grid; + flex: none; + font-size: 1rem; + font-weight: 800; + height: 36px; + place-items: center; + width: 36px; +} + +.pick-list { + counter-reset: pick; + display: grid; + gap: 10px; + list-style: none; + margin: 8px 0 14px; + padding: 0; +} + +.pick-list li { + align-items: baseline; + background: #f7f9fb; + border: 1px solid var(--line); + border-radius: 10px; + counter-increment: pick; + display: flex; + flex-wrap: wrap; + gap: 6px 12px; + padding: 12px 14px 12px 48px; + position: relative; +} + +.pick-list li::before { + background: var(--surface-soft); + border: 1px solid #bfe0da; + border-radius: 50%; + color: var(--brand-strong); + content: counter(pick); + display: grid; + font-size: 0.85rem; + font-weight: 800; + height: 26px; + left: 12px; + place-items: center; + position: absolute; + top: 12px; + width: 26px; +} + +.pick-name { + font-weight: 700; +} + +.pick-cost { + color: var(--muted); +} + +.pick-pay { + color: var(--muted); + flex-basis: 100%; + font-size: 0.92rem; +} + +.log-panel #toggle-logs { + margin-bottom: 6px; +} + +/* ---------- Quick start generator ---------- */ +.source-note { + margin-top: 14px; +} + +.source-note a { + white-space: nowrap; +} + +.quick-start { + background: var(--surface-soft); + border: 1px solid #bfe0da; +} + +.quick-grid { + align-items: end; + display: flex; + flex-wrap: wrap; + gap: 14px; + margin-top: 12px; +} + +.quick-grid label { + display: grid; + font-weight: 600; + gap: 6px; +} + +.quick-grid input { + width: 110px; +} + +.quick-grid #generate { + white-space: nowrap; +} + +/* ---------- About us ---------- */ +.team-list { + display: grid; + gap: 10px; + list-style: none; + margin: 8px 0 0; + padding: 0; +} + +.team-list li { + background: #f7f9fb; + border: 1px solid var(--line); + border-radius: 10px; + display: grid; + gap: 2px; + padding: 12px 14px; +} + +.team-name { + font-weight: 700; +} + +.team-role { + color: var(--muted); +} + +.team-links { + font-size: 0.92rem; +} + +/* ---------- Input recap ---------- */ +.recap-grid { + display: grid; + gap: 14px; + grid-template-columns: repeat(3, 1fr); + margin-top: 10px; +} + +.recap-card { + background: #f7f9fb; + border: 1px solid var(--line); + border-radius: 10px; + padding: 12px 14px; +} + +.recap-card h3 { + margin: 0 0 8px; +} + +.recap-budget { + font-size: 1.6rem; + font-weight: 800; + margin: 0; +} + +.recap-list { + display: grid; + gap: 6px; + list-style: none; + margin: 0; + padding: 0; +} + +.recap-list li { + display: flex; + flex-wrap: wrap; + gap: 4px 10px; + justify-content: space-between; +} + +.recap-item { + font-weight: 600; +} + +/* ---------- Advanced + lists ---------- */ +.advanced summary { + cursor: pointer; + font-size: 1.05rem; + font-weight: 700; +} + +.advanced-body { + margin-top: 12px; +} + +.logs-list { + background: #18232b; + border-radius: 9px; + color: #eaf3f1; + font-family: Consolas, "Courier New", monospace; + font-size: 0.88rem; + margin: 8px 0 0; + overflow-x: auto; + padding: 16px 18px 16px 36px; +} + +.explainer-list { + display: grid; + gap: 10px; + margin: 8px 0 14px; + padding-left: 20px; +} + +code { + background: var(--surface-soft); + border-radius: 6px; + font-family: Consolas, "Courier New", monospace; + font-size: 0.92em; + padding: 1px 6px; +} + +section[id] { + scroll-margin-top: 84px; +} + +/* ---------- Calls to action ---------- */ +.button-link { + background: var(--brand); + border-radius: 9px; + color: #fff; + display: inline-block; + font-weight: 700; + padding: 12px 20px; + text-align: center; + text-decoration: none; +} + +.button-link:hover { + background: var(--brand-strong); +} + +.cta { + align-items: center; + display: flex; + flex-wrap: wrap; + gap: 16px; + justify-content: space-between; +} + +.cta h2 { + margin-bottom: 4px; +} + +/* ---------- Footer ---------- */ +.sitefoot { + border-top: 1px solid var(--line); + color: var(--muted); + display: flex; + flex-wrap: wrap; + gap: 10px 18px; + justify-content: space-between; + margin-top: 30px; + padding-top: 18px; +} + +/* ---------- Responsive ---------- */ +@media (max-width: 760px) { + .band, + .result-hero { + grid-template-columns: 1fr; + } + + .projects-head { + display: none; + } + + .project-row { + grid-template-columns: 28px 1fr 40px; + grid-template-areas: + "num name remove" + "num cost remove"; + row-gap: 8px; + } + + .project-row .row-index { + grid-area: num; + } + + .project-row .p-name { + grid-area: name; + } + + .project-row .p-cost { + grid-area: cost; + } + + .project-row .icon-button { + align-self: center; + grid-area: remove; + } + + .recap-grid { + grid-template-columns: 1fr; + } + + .quick-grid { + align-items: stretch; + } + + .quick-grid #generate { + width: 100%; + } + + h1 { + font-size: 1.7rem; + } +} diff --git a/examples/ees_addopt_web/templates/about.html b/examples/ees_addopt_web/templates/about.html new file mode 100644 index 0000000..afcaf3e --- /dev/null +++ b/examples/ees_addopt_web/templates/about.html @@ -0,0 +1,68 @@ +{% extends "base.html" %} + +{% block title %}How it works{% endblock %} + +{% block content %} +
+
+

How it works

+

Sharing a budget so everyone is treated equally

+

+ When a community has money to spend on shared projects, how do you choose which projects win + without letting the majority decide everything? This demo shows one fair answer: + the Method of Equal Shares. +

+
+
+ +
+

The simple idea

+

Think of it as giving everyone an equal wallet:

+
    +
  1. Split the money equally. If there is a budget of 10 and 5 voters, each voter gets 2 to spend.
    2. +
  2. Vote for what you like. Each voter ticks the projects they support.
    3. +
  3. Projects pay for themselves. A project is funded when the people who voted for it can cover its cost from their own wallets, split as evenly as possible.
    4. +
  4. Use the leftover money. If money is left over, the tool adds more projects while staying within the budget.
    5. +
+

+ Because each voter has the same wallet, no group can be ignored: any large enough group of voters + can always fund a project they care about. That is what makes the outcome fair. +

+
+ +
+

What the results page shows

+
    +
  • Funded projects — the final list of projects the budget will pay for.
    • +
  • Why this is fair — a plain explanation of the equal-share idea.
    • +
  • The numbers — exactly what each voter started with, spent, and kept, so you can check the fairness yourself.
    • +
  • Technical details — the raw values and log, hidden away unless you want them.
    • +
+
+ +
+

About us

+

This demo was built by:

+ +

I built this project to make the Method of Equal Shares easy to see and understand.

+
+ +
+

Where this comes from

+

+ The method and the completion step are from the paper + Streamlining Equal Shares + by Sonja Kraiczy, Isaac Robinson, and Edith Elkind. This site is a small, friendly front end built on top of + the pabutools library; it does not change the algorithm in any way. +

+ Build an election +
+{% endblock %} diff --git a/examples/ees_addopt_web/templates/base.html b/examples/ees_addopt_web/templates/base.html new file mode 100644 index 0000000..dd77c6d --- /dev/null +++ b/examples/ees_addopt_web/templates/base.html @@ -0,0 +1,30 @@ + + + + + + {% block title %}Fair Budget Demo{% endblock %} + + + + +
+ + FB + Fair Budget + + +
+
+ {% block content %}{% endblock %} +
+ A friendly demo of the Method of Equal Shares. + How it works +
+
+ + diff --git a/examples/ees_addopt_web/templates/index.html b/examples/ees_addopt_web/templates/index.html new file mode 100644 index 0000000..9140a1e --- /dev/null +++ b/examples/ees_addopt_web/templates/index.html @@ -0,0 +1,99 @@ +{% extends "base.html" %} + +{% block title %}Build an election{% endblock %} + +{% block content %} +
+
+

Share a budget fairly

+

Which projects should the money pay for?

+

+ Imagine a community has some money to spend and a list of possible projects. + People vote for the projects they like. This tool decides which projects to fund + so that everyone's vote counts equally — and it shows you the numbers + that prove it is fair. +

+
+
    +
  1. 1 Set the budget
    2. +
  2. 2 List the projects
    3. +
  3. 3 Add the votes
    4. +
  4. 4 See the fair result
    5. +
+

+ Powered by the Method of Equal Shares from the paper + Streamlining Equal Shares. + Read how it works → +

+
+ +{% if error %} + +{% endif %} + +
+

Quick start

+

+ Don't want to type everything by hand? Choose how many projects and voters you want, and we'll + fill the form below with a ready-to-run example. You can change any value afterwards. +

+
+ + + +
+
+ +
+
+

1 Set the budget

+

How much money is there to share between all the projects?

+ +
+ +
+

2 List the projects

+

Give each project a name and how much it costs.

+
+ #Project nameCost +
+
+ +
+ +
+

3 Add the votes

+

For each voter, tick every project they support. Leave all boxes empty if they support none.

+
+ +
+ + + +
+

4 See the fair result

+

We will fund as many projects as the budget allows, keeping everyone's influence equal.

+ +
+ + + +
+
+
+ + + +{% endblock %} diff --git a/examples/ees_addopt_web/templates/result.html b/examples/ees_addopt_web/templates/result.html new file mode 100644 index 0000000..afea58a --- /dev/null +++ b/examples/ees_addopt_web/templates/result.html @@ -0,0 +1,268 @@ +{% extends "base.html" %} + +{% block title %}The fair result{% endblock %} + +{% block content %} +
+
+

The fair result

+ {% if result.completed.is_empty %} +

No projects could be funded

+

With this budget and these votes, no project could be fully paid for. Try a bigger budget or cheaper projects.

+ {% else %} +

{{ result.completed.count }} project{{ "" if result.completed.count == 1 else "s" }} funded

+

These are the projects the community will pay for. Below you can follow every step the tool took to get here.

+ {% endif %} +
+
+ +
+ {{ result.completed.total_cost }} spent + {{ result.completed_leftover }} left of {{ result.budget }} +
+ Try another election +
+
+ +{% if not result.completed.is_empty %} +
+

Funded projects

+
    + {% for project in result.completed.project_payments %} +
  • + + {{ project.name }} + costs {{ project.cost }} +
    • + {% endfor %} +
+
+{% endif %} + +
+

Your input

+

This is exactly what was entered, so you can check the result against it.

+
+
+

Budget

+

{{ result.budget }}

+
+
+

Projects ({{ result.project_count }})

+
    + {% for project in result.project_rows %} +
  • {{ project.name }}costs {{ project.cost }}
    • + {% endfor %} +
+
+
+

Votes ({{ result.voter_count }} voter{{ "" if result.voter_count == 1 else "s" }})

+
    + {% for voter in result.base.voter_rows %} +
  • Voter {{ voter.number }}{{ voter.approvals }}
    • + {% endfor %} +
+
+
+
+ +
+

How the result was reached, step by step

+

Nothing is hidden. Follow the four steps below, and open the log at the end to see every single decision.

+
+ + +
+
1

Give everyone an equal share

+

+ The budget of {{ result.budget }} is split equally among the + {{ result.voter_count }} voter{{ "" if result.voter_count == 1 else "s" }}. + So each voter gets {{ result.share_per_voter }} to spend on the projects they like. +

+

Because everyone gets the same amount, no group can be ignored — that is what keeps the result fair.

+
+ + +
+
2

Fund projects with the Method of Equal Shares

+

+ Using each voter's {{ result.share_per_voter }}, projects are picked one at a time, always choosing + the project that gives the most people the best value for money. Each chosen project is paid for by the voters who support it. +

+ + {% if result.base.project_payments %} +

Projects picked, in order

+
    + {% for project in result.base.project_payments %} +
  1. + {{ project.name }} + costs {{ project.cost }} + + paid by + {% for payer in project.payers %}Voter {{ payer.voter }} ({{ payer.amount }}){% if not loop.last %}, {% endif %}{% endfor %} + +
    2. + {% endfor %} +
+ {% else %} +

No project could be fully paid for in this first round.

+ {% endif %} + +

What each voter spent and kept

+
+ + + + {% for voter in result.base.voter_rows %} + + + + + + + + {% endfor %} + +
VoterVoted forEqual shareSpentKept
Voter {{ voter.number }}{{ voter.approvals }}{{ result.share_per_voter }}{{ voter.paid_total }}{{ voter.leftover }}
+
+

Everyone started with the same {{ result.share_per_voter }}, and nobody spent more than their share. This first round funded {{ result.base.selected_display }} and left {{ result.base_leftover }} unspent.

+
+ + +
+
3

Use the leftover money

+ {% if result.completion_multistep %} +

+ To make better use of the {{ result.base_leftover }} left over, the tool pretends each voter has a + slightly bigger share and checks what the Method of Equal Shares would fund. It tries larger and larger shares, + and keeps the most expensive result that still fits the real {{ result.budget }} budget. +

+
+ + + + + + {% for round in result.completion_rounds %} + + + + + + + + + {% endfor %} + +
RoundPretend share eachWould fundTotal costFits budget?Outcome
Round {{ round.number }}{{ round.share }}{{ round.selected_display }}{{ round.total_cost }}{{ "Yes" if round.fits else "No" }} + {% if round.is_chosen %} + ✓ Chosen + {% elif not round.fits %} + Too expensive + {% else %} + Tried + {% endif %} +
+
+

Round 1 is the first round from Step 2. The tool stops once a bigger share would only add projects that go over the budget.

+ {% else %} +

The first round already used the budget as well as possible, so no extra projects could be added. The final result is the same as Step 2.

+ {% endif %} +
+ + +
+
4

The final decision

+ {% if result.completed.is_empty %} +

No project could be funded within the budget.

+ {% else %} +

+ The funded projects are {{ result.completed.selected_display }}, costing + {{ result.completed.total_cost }} of the {{ result.budget }} budget, with + {{ result.completed_leftover }} left over. +

+ {% endif %} +
+ + + + {% for project in result.project_rows %} + + + + + + + {% endfor %} + +
ProjectCostVotesFunded
{{ project.name }}{{ project.cost }}{{ project.supporters }} + {% if project.in_completed %} + ✓ Funded + {% else %} + Not funded + {% endif %} +
+
+
+ + +
+

See every step in the log

+

This is the algorithm's own record of what it did, in order ({{ result.logs | length }} message{{ "" if result.logs | length == 1 else "s" }}).

+ + +
+ +
+ Extra technical values (for the curious) +
+

+ Raw values behind the algorithm from the paper + Streamlining Equal Shares. + The smallest share increase that would change the first-round result was {{ result.next_delta }}. +

+
+ + + + {% for row in result.leftover_rows %} + + {% endfor %} + +
VoterLeftover budgetLeximax payment vector
Voter {{ row.voter }}{{ row.leftover }}{{ row.leximax }}
+
+
+
+ +
+
+

Want to experiment?

+

Change the budget, projects, or votes and watch how the steps and the result change.

+
+ Build another election +
+ + +{% endblock %} From 72d1c824956d3728e0af706af700b93256120b34 Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Sun, 7 Jun 2026 14:05:58 +0300 Subject: [PATCH 6/8] add example --- examples/run_ees_addopt.py | 168 +++++++++++++++++++++++++++++++++++++ 1 file changed, 168 insertions(+) create mode 100644 examples/run_ees_addopt.py diff --git a/examples/run_ees_addopt.py b/examples/run_ees_addopt.py new file mode 100644 index 0000000..adfced5 --- /dev/null +++ b/examples/run_ees_addopt.py @@ -0,0 +1,168 @@ +""" +Running example for all algorithms in pabutools.rules.ees_addopt. + +Demonstrates: + 1. exact_equal_shares (Algorithm 1 – EES) + 2. get_leftover_budgets (leftover budget helper) + 3. get_leximax_payment (leximax payment helper) + 4. greedy_project_change (Algorithm 2 – GPC) + 5. add_opt (Algorithm 3 – add-opt) + 6. ees_add_opt_completion (EES completion via add-opt) +""" + +import logging + +from pabutools.election import Instance, Project, ApprovalProfile, ApprovalBallot +from pabutools.fractions import frac +from pabutools.rules.budgetallocation import BudgetAllocation +from pabutools.rules.ees_addopt import ( + EESAllocationDetails, + exact_equal_shares, + get_leftover_budgets, + get_leximax_payment, + greedy_project_change, + add_opt, + ees_add_opt_completion, +) + +# Show all log messages from the module. +logging.basicConfig( + level=logging.DEBUG, + format="%(name)s %(levelname)s %(message)s", + stream=__import__("sys").stdout, +) + +SEPARATOR = "\n" + "=" * 70 + "\n" + + +# A small PB instance with 5 voters and 3 projects. +# Projects: p1 (cost 2), p2 (cost 3.2), p3 (cost 6) +# Budget: 10 +# Voter 0 approves {p1} +# Voter 1 approves {p1, p3} +# Voter 2 approves {p2, p3} +# Voter 3 approves {p2, p3} +# Voter 4 approves {p3} + +p1 = Project("p1", 2) +p2 = Project("p2", 3.2) +p3 = Project("p3", 6) +projects = [p1, p2, p3] +budget = 10 + +instance = Instance(projects, budget_limit=budget) +profile = ApprovalProfile( + [ + ApprovalBallot([p1]), + ApprovalBallot([p1, p3]), + ApprovalBallot([p2, p3]), + ApprovalBallot([p2, p3]), + ApprovalBallot([p3]), + ], + instance=instance, +) + +num_voters = len(profile) +print("Instance") +print(f" Budget : {budget}") +print(f" Projects : {[(p.name, p.cost) for p in projects]}") +print(f" Num voters : {num_voters}") +print(f" Approvals :") +for i, ballot in enumerate(profile): + print(f" Voter {i}: {sorted(p.name for p in ballot)}") + + +# 1. exact_equal_shares (Algorithm 1) +print(SEPARATOR) +print("1. exact_equal_shares (Algorithm 1 – EES)") +print("-" * 42) + +ees_result = exact_equal_shares(instance, profile) + +print(f"\n Selected projects : {[p.name for p in ees_result]}") +total_cost = sum(frac(p.cost) for p in ees_result) +print(f" Total cost : {total_cost}") + +payments = ees_result.details.payments +print(" Per-voter payments:") +for voter in range(num_voters): + voter_pay = payments.get(voter, {}) + items = [(p.name, float(v)) for p, v in voter_pay.items()] + print(f" Voter {voter}: {items if items else '(none)'}") + + +# 2. get_leftover_budgets +print(SEPARATOR) +print("2. get_leftover_budgets") +print("-" * 42) + +leftover = get_leftover_budgets(instance, profile, ees_result) + +print(" Leftover budget per voter:") +for voter in range(num_voters): + print(f" Voter {voter}: {float(leftover[voter]):.4f}") + + +# 3. get_leximax_payment +print(SEPARATOR) +print("3. get_leximax_payment") +print("-" * 42) + +leximax = get_leximax_payment(ees_result, num_voters, instance) + +print(" Leximax payment vectors:") +for voter in range(num_voters): + formatted = [(float(amt), name) for amt, name in leximax[voter]] + print(f" Voter {voter}: {formatted}") + + +# 4. greedy_project_change (Algorithm 2 – GPC) +print(SEPARATOR) +print("4. greedy_project_change (Algorithm 2 – GPC)") +print("-" * 42) + +print(" Testing each project as instability certificate:") +for proj in projects: + d = greedy_project_change( + instance, profile, ees_result, proj, leftover, leximax + ) + print(f" Project '{proj.name}' (cost={proj.cost}): d = {d} ({float(d):.4f})") + + +# 5. add_opt (Algorithm 3) +print(SEPARATOR) +print("5. add_opt (Algorithm 3)") +print("-" * 42) + +d_min = add_opt(instance, profile, ees_result) + +print(f"\n Minimum d over all projects: {d_min} ({float(d_min):.4f})") +print(f" Per-voter budget increase : {float(d_min):.4f}") +print(f" Total budget increase (n*d): {float(num_voters * d_min):.4f}") + + +# 6. ees_add_opt_completion (EES completion via add-opt) +print(SEPARATOR) +print("6. ees_add_opt_completion (EES completed via add-opt)") +print("-" * 42) + +completed = ees_add_opt_completion(instance, profile) + +print(f"\n Selected projects : {sorted(p.name for p in completed)}") +completed_cost = sum(frac(p.cost) for p in completed) +print(f" Total cost : {completed_cost} (budget = {budget})") + +if hasattr(completed.details, "payments"): + print(" Per-voter payments:") + for voter in range(num_voters): + voter_pay = completed.details.payments.get(voter, {}) + items = [(p.name, float(v)) for p, v in voter_pay.items()] + print(f" Voter {voter}: {items if items else '(none)'}") + + +# Comparison +print(SEPARATOR) +print("Summary comparison") +print("-" * 42) +print(f" EES alone : {str([p.name for p in ees_result]):30s} cost = {float(total_cost)}") +print(f" EES + add-opt : {str(sorted(p.name for p in completed)):30s} cost = {float(completed_cost)}") From 859e8731db7d242fb195e6e9d2400dcc8988ed4c Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Wed, 10 Jun 2026 12:54:55 +0300 Subject: [PATCH 7/8] remove website --- examples/ees_addopt_web/README.md | 32 - examples/ees_addopt_web/app.py | 448 --------- examples/ees_addopt_web/requirements.txt | 1 - examples/ees_addopt_web/static/builder.js | 360 ------- examples/ees_addopt_web/static/styles.css | 935 ------------------ examples/ees_addopt_web/templates/about.html | 68 -- examples/ees_addopt_web/templates/base.html | 30 - examples/ees_addopt_web/templates/index.html | 99 -- examples/ees_addopt_web/templates/result.html | 268 ----- 9 files changed, 2241 deletions(-) delete mode 100644 examples/ees_addopt_web/README.md delete mode 100644 examples/ees_addopt_web/app.py delete mode 100644 examples/ees_addopt_web/requirements.txt delete mode 100644 examples/ees_addopt_web/static/builder.js delete mode 100644 examples/ees_addopt_web/static/styles.css delete mode 100644 examples/ees_addopt_web/templates/about.html delete mode 100644 examples/ees_addopt_web/templates/base.html delete mode 100644 examples/ees_addopt_web/templates/index.html delete mode 100644 examples/ees_addopt_web/templates/result.html diff --git a/examples/ees_addopt_web/README.md b/examples/ees_addopt_web/README.md deleted file mode 100644 index c8ce53a..0000000 --- a/examples/ees_addopt_web/README.md +++ /dev/null @@ -1,32 +0,0 @@ -# EES add-opt Flask demo - -This small Flask app demonstrates `exact_equal_shares`, `add_opt`, and `ees_add_opt_completion` from `pabutools.rules.ees_addopt`. - -## Run - -From the repository root: - -```powershell -python -m pip install -r examples/ees_addopt_web/requirements.txt -python examples/ees_addopt_web/app.py -``` - -Then open . - -## Input format - -```text -Budget: 10 - -Projects: -p1, 2 -p2, 3.2 -p3, 6 - -Ballots: -p1 -p1, p3 -p2, p3 -``` - -Use `-` for a voter who approves no projects. \ No newline at end of file diff --git a/examples/ees_addopt_web/app.py b/examples/ees_addopt_web/app.py deleted file mode 100644 index d23985a..0000000 --- a/examples/ees_addopt_web/app.py +++ /dev/null @@ -1,448 +0,0 @@ -"""A beginner-friendly web demo for the Method of Equal Shares (with add-opt completion). - -You do not need to know how the algorithm works to use this site. You describe a -simple situation - some money to share, a few projects, and who voted for what - -and the site shows which projects get funded and explains, with real numbers, why -the result is fair. - -The heavy lifting is done by the library function -``pabutools.rules.ees_addopt.ees_add_opt_completion``. This file only wraps it in -a friendly interface; it never changes the algorithm itself. -""" - -from __future__ import annotations - -import io -import json -import logging -import sys -from dataclasses import dataclass -from pathlib import Path -from typing import Any - -from flask import Flask, Response, render_template, request - -ROOT_DIR = Path(__file__).resolve().parents[2] -if str(ROOT_DIR) not in sys.path: - sys.path.insert(0, str(ROOT_DIR)) - -from pabutools.election.ballot import ApprovalBallot -from pabutools.election.instance import Instance, Project -from pabutools.election.profile import ApprovalProfile -from pabutools.fractions import frac, str_as_frac -from pabutools.rules.ees_addopt import ( - add_opt, - exact_equal_shares, - get_leftover_budgets, - get_leximax_payment, -) - -app = Flask(__name__) - -ALGORITHM_LOGGER = logging.getLogger("pabutools.rules.ees_addopt") - -# A ready-made, relatable example used for the "Load example" button and the -# first time the page is opened. Project indices in "voters" are 0-based and -# point into the "projects" list. -EXAMPLE: dict[str, Any] = { - "budget": "10", - "projects": [ - {"name": "New benches", "cost": "2"}, - {"name": "Bike lane", "cost": "3.2"}, - {"name": "Playground", "cost": "6"}, - ], - "voters": [ - [0], - [0, 2], - [1, 2], - [1, 2], - [2], - ], -} - - -@dataclass(frozen=True) -class ParsedElection: - instance: Instance - profile: ApprovalProfile - projects: list[Project] - project_names: list[str] - ballots: list[list[str]] - budget: Any - - -class InputError(ValueError): - """Raised when the submitted election cannot be understood.""" - - -def parse_number(raw_value: Any, field_name: str) -> Any: - """Turn user text into a non-negative number, with a friendly error if it is not one.""" - text = str(raw_value).strip() - if not text: - raise InputError(f"{field_name} is missing a value.") - try: - value = str_as_frac(text) - except Exception as exc: - raise InputError(f'"{text}" is not a valid number for {field_name.lower()}.') from exc - if value < 0: - raise InputError(f"{field_name} cannot be negative.") - return value - - -def parse_election_from_payload(payload: Any) -> ParsedElection: - """Build an election from the structured data sent by the visual builder.""" - if not isinstance(payload, dict): - raise InputError("The form could not be read. Please reload the page and try again.") - - budget = parse_number(payload.get("budget", ""), "The budget") - - raw_projects = payload.get("projects") - if not isinstance(raw_projects, list) or not raw_projects: - raise InputError("Add at least one project.") - - projects: list[Project] = [] - seen_names: set[str] = set() - for position, item in enumerate(raw_projects, start=1): - item = item or {} - name = str(item.get("name", "")).strip() - if not name: - raise InputError(f"Project {position} needs a name.") - if name in seen_names: - raise InputError(f'Two projects are both called "{name}". Please give each project a different name.') - cost = parse_number(item.get("cost", ""), f'The cost of "{name}"') - seen_names.add(name) - projects.append(Project(name, cost)) - - raw_voters = payload.get("voters") - if not isinstance(raw_voters, list) or not raw_voters: - raise InputError("Add at least one voter.") - - ballots: list[ApprovalBallot] = [] - ballot_names: list[list[str]] = [] - for voter_position, approvals in enumerate(raw_voters, start=1): - if approvals is None: - approvals = [] - if not isinstance(approvals, list): - raise InputError(f"Voter {voter_position}'s choices could not be read.") - chosen_indices: list[int] = [] - for raw_index in approvals: - try: - index = int(raw_index) - except (TypeError, ValueError): - raise InputError(f"Voter {voter_position} has an invalid project choice.") - if index < 0 or index >= len(projects): - raise InputError(f"Voter {voter_position} voted for a project that does not exist.") - chosen_indices.append(index) - chosen_indices = sorted(set(chosen_indices)) - ballot_names.append([projects[index].name for index in chosen_indices]) - ballots.append(ApprovalBallot(projects[index] for index in chosen_indices)) - - instance = Instance(projects, budget_limit=budget) - profile = ApprovalProfile(ballots, instance=instance) - return ParsedElection( - instance=instance, - profile=profile, - projects=projects, - project_names=[project.name for project in projects], - ballots=ballot_names, - budget=budget, - ) - - -def format_number(value: Any) -> str: - """Show a number in the friendliest readable form (whole number, decimal, or fraction).""" - if value == float("inf"): - return "infinity" - text = str(value) - if "/" in text: - try: - as_float = float(value) - except (TypeError, ValueError): - return text - if abs(as_float - round(as_float)) < 1e-10: - return str(round(as_float)) - return f"{as_float:.4g}" - return text - - -def total_cost(projects: list[Project]) -> Any: - total = frac(0) - for project in projects: - total += frac(project.cost) - return total - - -def supporters_by_project(parsed: ParsedElection) -> dict[str, int]: - counts = {project.name: 0 for project in parsed.projects} - for ballot in parsed.ballots: - for project_name in ballot: - counts[project_name] += 1 - return counts - - -def summarize_allocation(parsed: ParsedElection, allocation: list[Project]) -> dict[str, Any]: - """Describe one outcome: which projects, who paid, and how much each voter kept.""" - selected_projects = list(allocation) - selected_names = [project.name for project in selected_projects] - details = getattr(allocation, "details", None) - payments = getattr(details, "payments", {}) if details is not None else {} - number_of_voters = len(parsed.profile) - voter_budget = frac(parsed.instance.budget_limit) / number_of_voters if number_of_voters else frac(0) - cost_value = total_cost(selected_projects) - - project_payments = [] - for project in selected_projects: - paid = frac(0) - payers = [] - for voter_index in range(number_of_voters): - amount = payments.get(voter_index, {}).get(project, frac(0)) - if amount: - payers.append({"voter": voter_index + 1, "amount": format_number(amount)}) - paid += amount - project_payments.append( - { - "name": project.name, - "cost": format_number(project.cost), - "paid": format_number(paid), - "is_fully_paid": paid == frac(project.cost), - "payers": payers, - } - ) - - voter_rows = [] - for voter_index in range(number_of_voters): - paid_total = frac(0) - paid_entries = [] - for project in selected_projects: - amount = payments.get(voter_index, {}).get(project, frac(0)) - if amount: - paid_entries.append(f"{project.name}: {format_number(amount)}") - paid_total += amount - voter_rows.append( - { - "number": voter_index + 1, - "approvals": ", ".join(parsed.ballots[voter_index]) or "nothing", - "payments": ", ".join(paid_entries) or "-", - "paid_total": format_number(paid_total), - "leftover": format_number(voter_budget - paid_total), - "within_budget": paid_total <= voter_budget, - } - ) - - return { - "selected_names": selected_names, - "selected_display": ", ".join(selected_names) if selected_names else "no projects", - "count": len(selected_names), - "is_empty": len(selected_names) == 0, - "total_cost": format_number(cost_value), - "total_cost_num": cost_value, - "is_budget_feasible": cost_value <= parsed.instance.budget_limit, - "project_payments": project_payments, - "voter_rows": voter_rows, - } - - -def percent_of_budget(used: Any, budget: Any) -> float: - budget_value = frac(budget) - if budget_value <= 0: - return 0.0 - fraction = float(frac(used) / budget_value) * 100.0 - return max(0.0, min(100.0, round(fraction, 1))) - - -def run_completion_with_steps(parsed: ParsedElection) -> tuple[list[dict[str, Any]], list[Project], int]: - """Reproduce the add-opt completion loop, recording every round as a visible step. - - This mirrors ``ees_add_opt_completion`` exactly - it only calls the same public - functions - so the page can show each round without changing the algorithm. - """ - instance = parsed.instance - profile = parsed.profile - number_of_voters = len(profile) - original_budget = frac(instance.budget_limit) - projects = list(instance) - - rounds: list[dict[str, Any]] = [] - virtual_budget = original_budget - best_index = -1 - best_cost = frac(-1) - - while True: - virtual_instance = Instance(projects, budget_limit=virtual_budget) - allocation = exact_equal_shares(virtual_instance, profile) - cost = total_cost(list(allocation)) - fits = cost <= original_budget - delta = add_opt(virtual_instance, profile, allocation) - rounds.append( - { - "allocation": allocation, - "virtual_budget": virtual_budget, - "share": virtual_budget / number_of_voters if number_of_voters else frac(0), - "selected": [project.name for project in allocation], - "total_cost": cost, - "fits": fits, - "delta": delta, - } - ) - if fits and cost > best_cost: - best_cost = cost - best_index = len(rounds) - 1 - if delta == float("inf") or delta <= 0 or len(rounds) >= 60: - break - virtual_budget = virtual_budget + number_of_voters * frac(delta) - - if best_index < 0: - best_index = 0 - return rounds, rounds[best_index]["allocation"], best_index - - -def analyze(parsed: ParsedElection) -> dict[str, Any]: - """Run the algorithm and assemble everything the results page needs to explain it.""" - log_stream = io.StringIO() - handler = logging.StreamHandler(log_stream) - handler.setFormatter(logging.Formatter("%(levelname)s: %(message)s")) - previous_level = ALGORITHM_LOGGER.level - previous_propagate = ALGORITHM_LOGGER.propagate - ALGORITHM_LOGGER.setLevel(logging.DEBUG) - ALGORITHM_LOGGER.propagate = False - ALGORITHM_LOGGER.addHandler(handler) - try: - rounds, completed_allocation, best_index = run_completion_with_steps(parsed) - base_allocation = rounds[0]["allocation"] - leftover_budgets = get_leftover_budgets(parsed.instance, parsed.profile, base_allocation) - leximax_payments = get_leximax_payment(base_allocation, len(parsed.profile), parsed.instance) - next_delta = rounds[0]["delta"] - finally: - ALGORITHM_LOGGER.removeHandler(handler) - ALGORITHM_LOGGER.setLevel(previous_level) - ALGORITHM_LOGGER.propagate = previous_propagate - - number_of_voters = len(parsed.profile) - budget_value = frac(parsed.budget) - share_value = budget_value / number_of_voters if number_of_voters else frac(0) - - base = summarize_allocation(parsed, base_allocation) - completed = summarize_allocation(parsed, completed_allocation) - - supporter_counts = supporters_by_project(parsed) - base_selected_names = set(base["selected_names"]) - completed_selected_names = set(completed["selected_names"]) - project_rows = [ - { - "name": project.name, - "cost": format_number(project.cost), - "supporters": supporter_counts[project.name], - "in_base": project.name in base_selected_names, - "in_completed": project.name in completed_selected_names, - } - for project in parsed.projects - ] - - leftover_rows = [ - { - "voter": voter_index + 1, - "leftover": format_number(leftover_budgets[voter_index]), - "leximax": ", ".join( - f"{project_name}: {format_number(amount)}" - for amount, project_name in leximax_payments[voter_index] - ), - } - for voter_index in range(number_of_voters) - ] - - completion_rounds = [] - for index, round_data in enumerate(rounds): - delta_value = round_data["delta"] - if delta_value == float("inf") or delta_value <= 0: - delta_display = None - else: - delta_display = format_number(delta_value) - completion_rounds.append( - { - "number": index + 1, - "share": format_number(round_data["share"]), - "selected_display": ", ".join(round_data["selected"]) if round_data["selected"] else "no projects", - "total_cost": format_number(round_data["total_cost"]), - "fits": round_data["fits"], - "delta": delta_display, - "is_chosen": index == best_index, - } - ) - - return { - "budget": format_number(parsed.budget), - "voter_count": number_of_voters, - "share_per_voter": format_number(share_value), - "project_count": len(parsed.projects), - "project_rows": project_rows, - "base": base, - "completed": completed, - "base_leftover": format_number(budget_value - base["total_cost_num"]), - "completed_leftover": format_number(budget_value - completed["total_cost_num"]), - "completed_used_percent": percent_of_budget(completed["total_cost_num"], parsed.budget), - "same_as_base": base_selected_names == completed_selected_names, - "completion_rounds": completion_rounds, - "completion_multistep": len(completion_rounds) > 1, - "chosen_round": best_index + 1, - "next_delta": format_number(next_delta), - "leftover_rows": leftover_rows, - "logs": [line for line in log_stream.getvalue().splitlines() if line.strip()], - } - - -@app.get("/") -def index(): - return render_template("index.html", initial_data=EXAMPLE, example_data=EXAMPLE, error=None) - - -@app.post("/run") -def run_algorithm(): - raw_payload = request.form.get("payload", "") - try: - payload = json.loads(raw_payload) if raw_payload else {} - except json.JSONDecodeError: - payload = {} - - fallback = payload if isinstance(payload, dict) and payload else EXAMPLE - try: - parsed = parse_election_from_payload(payload) - result = analyze(parsed) - except InputError as exc: - return ( - render_template("index.html", initial_data=fallback, example_data=EXAMPLE, error=str(exc)), - 400, - ) - except Exception as exc: # noqa: BLE001 - surface any unexpected failure to the user. - return ( - render_template( - "index.html", - initial_data=fallback, - example_data=EXAMPLE, - error=f"Something went wrong while running the election: {exc}", - ), - 400, - ) - return render_template("result.html", result=result) - - -@app.get("/about") -def about(): - return render_template("about.html") - - -# A tiny inline icon so browsers do not get a 404 when they ask for /favicon.ico. -FAVICON_SVG = ( - "" - "" - "" -) - - -@app.get("/favicon.ico") -def favicon(): - return Response(FAVICON_SVG, mimetype="image/svg+xml") - - -if __name__ == "__main__": - app.run(debug=True) diff --git a/examples/ees_addopt_web/requirements.txt b/examples/ees_addopt_web/requirements.txt deleted file mode 100644 index a9039a4..0000000 --- a/examples/ees_addopt_web/requirements.txt +++ /dev/null @@ -1 +0,0 @@ -Flask>=3.0 \ No newline at end of file diff --git a/examples/ees_addopt_web/static/builder.js b/examples/ees_addopt_web/static/builder.js deleted file mode 100644 index cca78c4..0000000 --- a/examples/ees_addopt_web/static/builder.js +++ /dev/null @@ -1,360 +0,0 @@ -// Powers the visual election builder on the home page. -// No part of the algorithm lives here - this only collects the user's input -// (budget, projects, votes) and sends it to the server as simple JSON. -(function () { - "use strict"; - - const budgetEl = document.getElementById("budget"); - const projectsEl = document.getElementById("projects"); - const votersEl = document.getElementById("voters"); - const payloadEl = document.getElementById("payload"); - const form = document.getElementById("builder"); - const errorEl = document.getElementById("form-error"); - const runButton = document.getElementById("run-button"); - - let nextId = 1; - let projects = []; // [{ id, name, cost }] - let voters = []; // [{ id, approvals: Set }] - - function uid() { - return nextId++; - } - - // Load a data object (from the server) into the on-screen builder. - function loadData(data) { - data = data || {}; - const idByIndex = []; - projects = (data.projects || []).map(function (project, index) { - const id = uid(); - idByIndex[index] = id; - return { id: id, name: (project && project.name) || "", cost: project && project.cost != null ? String(project.cost) : "" }; - }); - voters = (data.voters || []).map(function (approvals) { - const set = new Set(); - (approvals || []).forEach(function (index) { - const id = idByIndex[index]; - if (id !== undefined) { - set.add(id); - } - }); - return { id: uid(), approvals: set }; - }); - budgetEl.value = data.budget != null ? String(data.budget) : ""; - render(); - } - - // Keep a typed size within sensible bounds. - function clampInt(value, min, max, fallback) { - const parsed = Math.floor(Number(value)); - if (Number.isNaN(parsed)) { - return fallback; - } - return Math.max(min, Math.min(max, parsed)); - } - - // Build a complete, ready-to-run example with the requested number of - // projects and voters, so the user can try the algorithm without typing - // every value by hand. - function generateSample(numProjects, numVoters) { - const generatedProjects = []; - let totalCost = 0; - let maxCost = 0; - for (let i = 0; i < numProjects; i++) { - const cost = 1 + Math.floor(Math.random() * 9); // 1..9 - totalCost += cost; - maxCost = Math.max(maxCost, cost); - generatedProjects.push({ name: "Project " + (i + 1), cost: String(cost) }); - } - const generatedVoters = []; - for (let v = 0; v < numVoters; v++) { - const approvals = []; - for (let i = 0; i < numProjects; i++) { - if (Math.random() < 0.5) { - approvals.push(i); - } - } - if (!approvals.length && numProjects > 0) { - approvals.push(Math.floor(Math.random() * numProjects)); // never leave a voter empty - } - generatedVoters.push(approvals); - } - // A budget big enough to fund some, but usually not all, projects. - const budget = Math.max(maxCost, Math.round(totalCost * 0.6)); - return { budget: String(budget), projects: generatedProjects, voters: generatedVoters }; - } - - function addProject() { - projects.push({ id: uid(), name: "", cost: "" }); - render(); - focusLastProjectName(); - } - - function removeProject(id) { - projects = projects.filter(function (project) { - return project.id !== id; - }); - voters.forEach(function (voter) { - voter.approvals.delete(id); - }); - render(); - } - - function addVoter() { - voters.push({ id: uid(), approvals: new Set() }); - render(); - } - - function removeVoter(id) { - voters = voters.filter(function (voter) { - return voter.id !== id; - }); - render(); - } - - function projectLabel(project, index) { - const name = (project.name || "").trim(); - return name || "Project " + (index + 1); - } - - function renderProjects() { - projectsEl.innerHTML = ""; - if (!projects.length) { - const empty = document.createElement("p"); - empty.className = "muted empty-note"; - empty.textContent = "No projects yet. Click \u201c+ Add project\u201d to begin."; - projectsEl.appendChild(empty); - return; - } - projects.forEach(function (project, index) { - const row = document.createElement("div"); - row.className = "project-row"; - - const number = document.createElement("span"); - number.className = "row-index"; - number.textContent = String(index + 1); - - const nameInput = document.createElement("input"); - nameInput.type = "text"; - nameInput.className = "p-name"; - nameInput.placeholder = "e.g. New playground"; - nameInput.value = project.name; - nameInput.addEventListener("input", function () { - project.name = nameInput.value; - renderVoters(); - }); - - const costInput = document.createElement("input"); - costInput.type = "number"; - costInput.className = "p-cost"; - costInput.min = "0"; - costInput.step = "any"; - costInput.inputMode = "decimal"; - costInput.placeholder = "Cost"; - costInput.value = project.cost; - costInput.addEventListener("input", function () { - project.cost = costInput.value; - }); - - const remove = document.createElement("button"); - remove.type = "button"; - remove.className = "icon-button"; - remove.setAttribute("aria-label", "Remove this project"); - remove.textContent = "\u2715"; - remove.addEventListener("click", function () { - removeProject(project.id); - }); - - row.appendChild(number); - row.appendChild(nameInput); - row.appendChild(costInput); - row.appendChild(remove); - projectsEl.appendChild(row); - }); - } - - function renderVoters() { - votersEl.innerHTML = ""; - if (!voters.length) { - const empty = document.createElement("p"); - empty.className = "muted empty-note"; - empty.textContent = "No voters yet. Click \u201c+ Add voter\u201d to begin."; - votersEl.appendChild(empty); - return; - } - voters.forEach(function (voter, voterIndex) { - const card = document.createElement("div"); - card.className = "voter-row"; - - const head = document.createElement("div"); - head.className = "voter-head"; - - const title = document.createElement("strong"); - title.textContent = "Voter " + (voterIndex + 1); - - const remove = document.createElement("button"); - remove.type = "button"; - remove.className = "icon-button"; - remove.setAttribute("aria-label", "Remove this voter"); - remove.textContent = "\u2715"; - remove.addEventListener("click", function () { - removeVoter(voter.id); - }); - - head.appendChild(title); - head.appendChild(remove); - card.appendChild(head); - - const choices = document.createElement("div"); - choices.className = "choices"; - if (!projects.length) { - const note = document.createElement("span"); - note.className = "muted"; - note.textContent = "Add some projects first."; - choices.appendChild(note); - } else { - projects.forEach(function (project, index) { - const label = document.createElement("label"); - label.className = "choice"; - - const checkbox = document.createElement("input"); - checkbox.type = "checkbox"; - checkbox.checked = voter.approvals.has(project.id); - checkbox.addEventListener("change", function () { - if (checkbox.checked) { - voter.approvals.add(project.id); - } else { - voter.approvals.delete(project.id); - } - label.classList.toggle("is-on", checkbox.checked); - }); - - const text = document.createElement("span"); - text.textContent = projectLabel(project, index); - - label.classList.toggle("is-on", checkbox.checked); - label.appendChild(checkbox); - label.appendChild(text); - choices.appendChild(label); - }); - } - card.appendChild(choices); - votersEl.appendChild(card); - }); - } - - function render() { - renderProjects(); - renderVoters(); - } - - function focusLastProjectName() { - const inputs = projectsEl.querySelectorAll(".p-name"); - if (inputs.length) { - inputs[inputs.length - 1].focus(); - } - } - - function buildPayload() { - return { - budget: budgetEl.value.trim(), - projects: projects.map(function (project) { - return { name: project.name.trim(), cost: project.cost.trim() }; - }), - voters: voters.map(function (voter) { - const indices = []; - projects.forEach(function (project, index) { - if (voter.approvals.has(project.id)) { - indices.push(index); - } - }); - return indices; - }), - }; - } - - function isValidNumber(text) { - if (text === "") { - return false; - } - const value = Number(text); - return !Number.isNaN(value) && value >= 0; - } - - function validate(payload) { - if (!isValidNumber(payload.budget)) { - return "Enter a budget of 0 or more."; - } - if (!payload.projects.length) { - return "Add at least one project."; - } - const seen = new Set(); - for (let i = 0; i < payload.projects.length; i++) { - const project = payload.projects[i]; - if (!project.name) { - return "Project " + (i + 1) + " needs a name."; - } - if (seen.has(project.name)) { - return 'Two projects are called "' + project.name + '". Use different names.'; - } - seen.add(project.name); - if (!isValidNumber(project.cost)) { - return 'Enter a valid cost for "' + project.name + '".'; - } - } - if (!payload.voters.length) { - return "Add at least one voter."; - } - return null; - } - - function showError(message) { - errorEl.textContent = message; - errorEl.hidden = false; - errorEl.scrollIntoView({ behavior: "smooth", block: "center" }); - } - - function hideError() { - errorEl.hidden = true; - errorEl.textContent = ""; - } - - form.addEventListener("submit", function (event) { - const payload = buildPayload(); - const message = validate(payload); - if (message) { - event.preventDefault(); - showError(message); - return; - } - hideError(); - payloadEl.value = JSON.stringify(payload); - runButton.disabled = true; - runButton.textContent = "Working\u2026"; - }); - - document.getElementById("generate").addEventListener("click", function () { - hideError(); - const projectsInput = document.getElementById("gen-projects"); - const votersInput = document.getElementById("gen-voters"); - const numProjects = clampInt(projectsInput.value, 1, 20, 4); - const numVoters = clampInt(votersInput.value, 1, 50, 6); - projectsInput.value = String(numProjects); - votersInput.value = String(numVoters); - loadData(generateSample(numProjects, numVoters)); - }); - document.getElementById("add-project").addEventListener("click", addProject); - document.getElementById("add-voter").addEventListener("click", addVoter); - document.getElementById("load-example").addEventListener("click", function () { - hideError(); - loadData(window.EXAMPLE_DATA); - }); - document.getElementById("clear-all").addEventListener("click", function () { - hideError(); - loadData({ budget: "", projects: [{ name: "", cost: "" }], voters: [[]] }); - }); - - const start = window.INITIAL_DATA && window.INITIAL_DATA.projects && window.INITIAL_DATA.projects.length - ? window.INITIAL_DATA - : window.EXAMPLE_DATA; - loadData(start); -})(); diff --git a/examples/ees_addopt_web/static/styles.css b/examples/ees_addopt_web/static/styles.css deleted file mode 100644 index 8e63e76..0000000 --- a/examples/ees_addopt_web/static/styles.css +++ /dev/null @@ -1,935 +0,0 @@ -:root { - color-scheme: light; - --bg: #f4f7fb; - --surface: #ffffff; - --surface-soft: #eef5f3; - --text: #1f2a33; - --muted: #5d6b77; - --line: #d8e1e8; - --brand: #1f7a70; - --brand-strong: #155d55; - --accent: #2f6df0; - --good: #1f7a45; - --good-soft: #e9f6ee; - --warn: #8a5a18; - --warn-soft: #fdf3e6; - --shadow: 0 10px 28px rgba(24, 45, 58, 0.08); - --radius: 12px; -} - -* { - box-sizing: border-box; -} - -html { - scroll-behavior: smooth; -} - -body { - margin: 0; - background: var(--bg); - color: var(--text); - font-family: "Segoe UI", Arial, sans-serif; - line-height: 1.55; -} - -a { - color: var(--brand-strong); -} - -/* ---------- Top bar ---------- */ -.topbar { - align-items: center; - background: var(--surface); - border-bottom: 1px solid var(--line); - display: flex; - gap: 20px; - justify-content: space-between; - padding: 14px clamp(16px, 4vw, 56px); - position: sticky; - top: 0; - z-index: 10; -} - -.brand { - align-items: center; - color: var(--brand); - display: flex; - font-size: 1.1rem; - font-weight: 800; - gap: 10px; - text-decoration: none; -} - -.brand-mark { - background: var(--brand); - border-radius: 8px; - color: #fff; - display: inline-grid; - font-size: 0.85rem; - height: 30px; - place-items: center; - width: 30px; -} - -.topbar nav { - display: flex; - flex-wrap: wrap; - gap: 8px 18px; -} - -.topbar nav a { - border-radius: 8px; - color: var(--text); - padding: 6px 10px; - text-decoration: none; -} - -.topbar nav a:hover { - background: var(--surface-soft); -} - -/* ---------- Layout ---------- */ -.page { - margin: 0 auto; - max-width: 1000px; - padding: 24px clamp(16px, 4vw, 40px) 56px; -} - -.band, -.panel { - background: var(--surface); - border: 1px solid var(--line); - border-radius: var(--radius); - box-shadow: var(--shadow); -} - -.band { - align-items: center; - display: grid; - gap: 28px; - grid-template-columns: minmax(0, 1.4fr) minmax(220px, 0.9fr); - margin-bottom: 22px; - padding: clamp(22px, 4vw, 38px); -} - -.panel { - margin-bottom: 18px; - padding: clamp(18px, 3vw, 26px); -} - -h1, -h2, -h3 { - line-height: 1.2; - margin: 0 0 12px; -} - -h1 { - color: var(--text); - font-size: clamp(1.8rem, 3.4vw, 2.5rem); -} - -h2 { - font-size: 1.3rem; -} - -h3 { - color: var(--brand-strong); - font-size: 1.02rem; - margin-top: 22px; -} - -.lead { - font-size: 1.08rem; -} - -.eyebrow { - color: var(--brand); - font-size: 0.8rem; - font-weight: 800; - letter-spacing: 0.04em; - margin: 0 0 8px; - text-transform: uppercase; -} - -.muted { - color: var(--muted); - margin-top: 0; -} - -/* ---------- Home hero steps ---------- */ -.steps { - display: grid; - gap: 10px; - list-style: none; - margin: 0; - padding: 0; -} - -.steps li { - align-items: center; - background: var(--surface-soft); - border: 1px solid #bfe0da; - border-radius: 10px; - color: var(--brand-strong); - display: flex; - font-weight: 700; - gap: 12px; - padding: 10px 14px; -} - -.steps li span { - background: var(--brand); - border-radius: 50%; - color: #fff; - display: inline-grid; - flex: none; - font-size: 0.85rem; - height: 26px; - place-items: center; - width: 26px; -} - -/* ---------- Forms ---------- */ -label { - color: var(--muted); - display: grid; - font-weight: 700; - gap: 8px; -} - -input, -textarea { - background: #fbfdfe; - border: 1px solid var(--line); - border-radius: 9px; - color: var(--text); - font: inherit; - padding: 11px 12px; - width: 100%; -} - -input:focus, -textarea:focus { - border-color: var(--brand); -} - -a:focus-visible, -button:focus-visible, -input:focus-visible, -textarea:focus-visible, -summary:focus-visible, -.choice:focus-within { - outline: 2px solid var(--accent); - outline-offset: 2px; -} - -button { - border-radius: 9px; - cursor: pointer; - font: inherit; - font-weight: 700; - padding: 11px 18px; -} - -button.primary-big, -button[type="submit"]:not(.secondary):not(.ghost) { - background: var(--brand); - border: 1px solid var(--brand); - color: #fff; - font-size: 1.05rem; - padding: 13px 24px; -} - -button.primary-big:hover { - background: var(--brand-strong); -} - -button.secondary { - background: var(--surface); - border: 1px solid var(--line); - color: var(--text); -} - -button.secondary:hover { - background: var(--surface-soft); -} - -button.ghost { - background: transparent; - border: 1px solid transparent; - color: var(--muted); -} - -button.ghost:hover { - color: var(--text); - text-decoration: underline; -} - -button:disabled { - cursor: progress; - opacity: 0.7; -} - -.actions { - display: flex; - flex-wrap: wrap; - gap: 12px; - margin-top: 6px; -} - -.step-number { - background: var(--brand); - border-radius: 50%; - color: #fff; - display: inline-grid; - font-size: 0.85rem; - height: 28px; - margin-right: 8px; - place-items: center; - vertical-align: middle; - width: 28px; -} - -.builder-step h2, -.run-panel h2 { - align-items: center; - display: flex; -} - -.budget-field { - max-width: 240px; -} - -.budget-field input { - font-size: 1.2rem; - font-weight: 700; -} - -/* ---------- Projects rows ---------- */ -.row-head { - color: var(--muted); - font-size: 0.78rem; - font-weight: 700; - letter-spacing: 0.03em; - text-transform: uppercase; -} - -.projects-head { - display: grid; - gap: 12px; - grid-template-columns: 34px 1fr 140px 40px; - margin-bottom: 8px; - padding: 0 2px; -} - -.project-row { - align-items: center; - display: grid; - gap: 12px; - grid-template-columns: 34px 1fr 140px 40px; - margin-bottom: 10px; -} - -.row-index { - color: var(--muted); - font-weight: 700; - text-align: center; -} - -.icon-button { - background: #fbeeee; - border: 1px solid #f0d2d2; - border-radius: 8px; - color: #a23b3b; - font-size: 0.9rem; - line-height: 1; - padding: 9px 0; - width: 100%; -} - -.icon-button:hover { - background: #f6dede; -} - -.add-button { - margin-top: 6px; -} - -.empty-note { - margin: 6px 0; -} - -/* ---------- Voters ---------- */ -.voter-row { - border: 1px solid var(--line); - border-radius: 10px; - margin-bottom: 12px; - padding: 12px 14px; -} - -.voter-head { - align-items: center; - display: flex; - justify-content: space-between; - margin-bottom: 10px; -} - -.voter-head .icon-button { - width: 36px; -} - -.choices { - display: flex; - flex-wrap: wrap; - gap: 8px 10px; -} - -.choice { - align-items: center; - background: #f7f9fb; - border: 1px solid var(--line); - border-radius: 999px; - color: var(--text); - cursor: pointer; - display: inline-flex; - font-weight: 600; - gap: 8px; - padding: 7px 14px 7px 10px; - user-select: none; -} - -.choice:hover { - border-color: var(--brand); -} - -.choice.is-on { - background: var(--surface-soft); - border-color: var(--brand); - color: var(--brand-strong); -} - -.choice input { - accent-color: var(--brand); - height: 16px; - margin: 0; - width: 16px; -} - -.run-panel { - border-color: #bfe0da; -} - -/* ---------- Alerts ---------- */ -.alert { - background: var(--warn-soft); - border: 1px solid #e7b87f; - border-radius: 10px; - color: var(--warn); - margin-bottom: 20px; - padding: 14px 16px; -} - -.field-error { - background: #fdecec; - border: 1px solid #efbcbc; - border-radius: 9px; - color: #9c2c2c; - font-weight: 600; - margin: 0 0 12px; - padding: 10px 14px; -} - -/* ---------- Result hero ---------- */ -.result-hero { - grid-template-columns: minmax(0, 1.3fr) minmax(240px, 1fr); -} - -.hero-side { - display: grid; - gap: 12px; -} - -.budget-meter { - background: #e6edf2; - border-radius: 999px; - height: 16px; - overflow: hidden; -} - -.budget-fill { - background: linear-gradient(90deg, var(--brand), #34a596); - height: 100%; -} - -.meter-legend { - color: var(--muted); - display: flex; - flex-wrap: wrap; - gap: 4px 16px; - font-size: 0.92rem; - justify-content: space-between; -} - -.meter-legend strong { - color: var(--text); -} - -/* ---------- Funded list ---------- */ -.funded-list { - display: grid; - gap: 10px; - list-style: none; - margin: 0; - padding: 0; -} - -.funded-list li { - align-items: center; - background: var(--good-soft); - border: 1px solid #bfe3cd; - border-radius: 10px; - display: flex; - gap: 12px; - padding: 12px 16px; -} - -.funded-list .check { - background: var(--good); - border-radius: 50%; - color: #fff; - display: inline-grid; - flex: none; - font-size: 0.85rem; - height: 24px; - place-items: center; - width: 24px; -} - -.funded-list .f-name { - font-weight: 700; -} - -.funded-list .f-cost { - color: var(--muted); - margin-left: auto; -} - -.explain p { - margin: 0 0 10px; -} - -.note { - border-radius: 9px; - font-weight: 600; - margin: 10px 0 0; - padding: 10px 14px; -} - -.note.good { - background: var(--good-soft); - border: 1px solid #bfe3cd; - color: var(--good); -} - -/* ---------- Tables ---------- */ -.table-wrap { - overflow-x: auto; - margin: 12px 0; -} - -table { - border-collapse: collapse; - min-width: 520px; - width: 100%; -} - -th, -td { - border-bottom: 1px solid var(--line); - padding: 10px 12px; - text-align: left; - vertical-align: top; -} - -th { - background: #eef2f5; - color: #36454f; - font-size: 0.9rem; -} - -tr.is-final td { - background: var(--good-soft); -} - -.pill { - background: #eef2f5; - border: 1px solid var(--line); - border-radius: 999px; - display: inline-block; - font-size: 0.85rem; - margin: 2px 3px 2px 0; - padding: 3px 10px; -} - -.tag { - border-radius: 999px; - display: inline-block; - font-size: 0.82rem; - font-weight: 700; - padding: 3px 11px; - white-space: nowrap; -} - -.tag.yes { - background: var(--good-soft); - border: 1px solid #bfe3cd; - color: var(--good); -} - -.tag.no { - background: #f3f5f6; - border: 1px solid #e2e8eb; - color: #8c99a2; -} - -.tag.muted-tag { - background: #eef2f5; - border: 1px solid var(--line); - color: var(--muted); -} - -/* ---------- Step-by-step ---------- */ -.steps-intro { - border-left: 4px solid var(--brand); -} - -.step-block { - position: relative; -} - -.step-head { - align-items: center; - display: flex; - gap: 12px; - margin-bottom: 8px; -} - -.step-head h2 { - margin: 0; -} - -.step-badge { - background: var(--brand); - border-radius: 50%; - color: #fff; - display: inline-grid; - flex: none; - font-size: 1rem; - font-weight: 800; - height: 36px; - place-items: center; - width: 36px; -} - -.pick-list { - counter-reset: pick; - display: grid; - gap: 10px; - list-style: none; - margin: 8px 0 14px; - padding: 0; -} - -.pick-list li { - align-items: baseline; - background: #f7f9fb; - border: 1px solid var(--line); - border-radius: 10px; - counter-increment: pick; - display: flex; - flex-wrap: wrap; - gap: 6px 12px; - padding: 12px 14px 12px 48px; - position: relative; -} - -.pick-list li::before { - background: var(--surface-soft); - border: 1px solid #bfe0da; - border-radius: 50%; - color: var(--brand-strong); - content: counter(pick); - display: grid; - font-size: 0.85rem; - font-weight: 800; - height: 26px; - left: 12px; - place-items: center; - position: absolute; - top: 12px; - width: 26px; -} - -.pick-name { - font-weight: 700; -} - -.pick-cost { - color: var(--muted); -} - -.pick-pay { - color: var(--muted); - flex-basis: 100%; - font-size: 0.92rem; -} - -.log-panel #toggle-logs { - margin-bottom: 6px; -} - -/* ---------- Quick start generator ---------- */ -.source-note { - margin-top: 14px; -} - -.source-note a { - white-space: nowrap; -} - -.quick-start { - background: var(--surface-soft); - border: 1px solid #bfe0da; -} - -.quick-grid { - align-items: end; - display: flex; - flex-wrap: wrap; - gap: 14px; - margin-top: 12px; -} - -.quick-grid label { - display: grid; - font-weight: 600; - gap: 6px; -} - -.quick-grid input { - width: 110px; -} - -.quick-grid #generate { - white-space: nowrap; -} - -/* ---------- About us ---------- */ -.team-list { - display: grid; - gap: 10px; - list-style: none; - margin: 8px 0 0; - padding: 0; -} - -.team-list li { - background: #f7f9fb; - border: 1px solid var(--line); - border-radius: 10px; - display: grid; - gap: 2px; - padding: 12px 14px; -} - -.team-name { - font-weight: 700; -} - -.team-role { - color: var(--muted); -} - -.team-links { - font-size: 0.92rem; -} - -/* ---------- Input recap ---------- */ -.recap-grid { - display: grid; - gap: 14px; - grid-template-columns: repeat(3, 1fr); - margin-top: 10px; -} - -.recap-card { - background: #f7f9fb; - border: 1px solid var(--line); - border-radius: 10px; - padding: 12px 14px; -} - -.recap-card h3 { - margin: 0 0 8px; -} - -.recap-budget { - font-size: 1.6rem; - font-weight: 800; - margin: 0; -} - -.recap-list { - display: grid; - gap: 6px; - list-style: none; - margin: 0; - padding: 0; -} - -.recap-list li { - display: flex; - flex-wrap: wrap; - gap: 4px 10px; - justify-content: space-between; -} - -.recap-item { - font-weight: 600; -} - -/* ---------- Advanced + lists ---------- */ -.advanced summary { - cursor: pointer; - font-size: 1.05rem; - font-weight: 700; -} - -.advanced-body { - margin-top: 12px; -} - -.logs-list { - background: #18232b; - border-radius: 9px; - color: #eaf3f1; - font-family: Consolas, "Courier New", monospace; - font-size: 0.88rem; - margin: 8px 0 0; - overflow-x: auto; - padding: 16px 18px 16px 36px; -} - -.explainer-list { - display: grid; - gap: 10px; - margin: 8px 0 14px; - padding-left: 20px; -} - -code { - background: var(--surface-soft); - border-radius: 6px; - font-family: Consolas, "Courier New", monospace; - font-size: 0.92em; - padding: 1px 6px; -} - -section[id] { - scroll-margin-top: 84px; -} - -/* ---------- Calls to action ---------- */ -.button-link { - background: var(--brand); - border-radius: 9px; - color: #fff; - display: inline-block; - font-weight: 700; - padding: 12px 20px; - text-align: center; - text-decoration: none; -} - -.button-link:hover { - background: var(--brand-strong); -} - -.cta { - align-items: center; - display: flex; - flex-wrap: wrap; - gap: 16px; - justify-content: space-between; -} - -.cta h2 { - margin-bottom: 4px; -} - -/* ---------- Footer ---------- */ -.sitefoot { - border-top: 1px solid var(--line); - color: var(--muted); - display: flex; - flex-wrap: wrap; - gap: 10px 18px; - justify-content: space-between; - margin-top: 30px; - padding-top: 18px; -} - -/* ---------- Responsive ---------- */ -@media (max-width: 760px) { - .band, - .result-hero { - grid-template-columns: 1fr; - } - - .projects-head { - display: none; - } - - .project-row { - grid-template-columns: 28px 1fr 40px; - grid-template-areas: - "num name remove" - "num cost remove"; - row-gap: 8px; - } - - .project-row .row-index { - grid-area: num; - } - - .project-row .p-name { - grid-area: name; - } - - .project-row .p-cost { - grid-area: cost; - } - - .project-row .icon-button { - align-self: center; - grid-area: remove; - } - - .recap-grid { - grid-template-columns: 1fr; - } - - .quick-grid { - align-items: stretch; - } - - .quick-grid #generate { - width: 100%; - } - - h1 { - font-size: 1.7rem; - } -} diff --git a/examples/ees_addopt_web/templates/about.html b/examples/ees_addopt_web/templates/about.html deleted file mode 100644 index afcaf3e..0000000 --- a/examples/ees_addopt_web/templates/about.html +++ /dev/null @@ -1,68 +0,0 @@ -{% extends "base.html" %} - -{% block title %}How it works{% endblock %} - -{% block content %} -
-
-

How it works

-

Sharing a budget so everyone is treated equally

-

- When a community has money to spend on shared projects, how do you choose which projects win - without letting the majority decide everything? This demo shows one fair answer: - the Method of Equal Shares. -

-
-
- -
-

The simple idea

-

Think of it as giving everyone an equal wallet:

-
    -
  1. Split the money equally. If there is a budget of 10 and 5 voters, each voter gets 2 to spend.
    2. -
  2. Vote for what you like. Each voter ticks the projects they support.
    3. -
  3. Projects pay for themselves. A project is funded when the people who voted for it can cover its cost from their own wallets, split as evenly as possible.
    4. -
  4. Use the leftover money. If money is left over, the tool adds more projects while staying within the budget.
    5. -
-

- Because each voter has the same wallet, no group can be ignored: any large enough group of voters - can always fund a project they care about. That is what makes the outcome fair. -

-
- -
-

What the results page shows

-
    -
  • Funded projects — the final list of projects the budget will pay for.
    • -
  • Why this is fair — a plain explanation of the equal-share idea.
    • -
  • The numbers — exactly what each voter started with, spent, and kept, so you can check the fairness yourself.
    • -
  • Technical details — the raw values and log, hidden away unless you want them.
    • -
-
- -
-

About us

-

This demo was built by:

- -

I built this project to make the Method of Equal Shares easy to see and understand.

-
- -
-

Where this comes from

-

- The method and the completion step are from the paper - Streamlining Equal Shares - by Sonja Kraiczy, Isaac Robinson, and Edith Elkind. This site is a small, friendly front end built on top of - the pabutools library; it does not change the algorithm in any way. -

- Build an election -
-{% endblock %} diff --git a/examples/ees_addopt_web/templates/base.html b/examples/ees_addopt_web/templates/base.html deleted file mode 100644 index dd77c6d..0000000 --- a/examples/ees_addopt_web/templates/base.html +++ /dev/null @@ -1,30 +0,0 @@ - - - - - - {% block title %}Fair Budget Demo{% endblock %} - - - - -
- - FB - Fair Budget - - -
-
- {% block content %}{% endblock %} -
- A friendly demo of the Method of Equal Shares. - How it works -
-
- - diff --git a/examples/ees_addopt_web/templates/index.html b/examples/ees_addopt_web/templates/index.html deleted file mode 100644 index 9140a1e..0000000 --- a/examples/ees_addopt_web/templates/index.html +++ /dev/null @@ -1,99 +0,0 @@ -{% extends "base.html" %} - -{% block title %}Build an election{% endblock %} - -{% block content %} -
-
-

Share a budget fairly

-

Which projects should the money pay for?

-

- Imagine a community has some money to spend and a list of possible projects. - People vote for the projects they like. This tool decides which projects to fund - so that everyone's vote counts equally — and it shows you the numbers - that prove it is fair. -

-
-
    -
  1. 1 Set the budget
    2. -
  2. 2 List the projects
    3. -
  3. 3 Add the votes
    4. -
  4. 4 See the fair result
    5. -
-

- Powered by the Method of Equal Shares from the paper - Streamlining Equal Shares. - Read how it works → -

-
- -{% if error %} - -{% endif %} - -
-

Quick start

-

- Don't want to type everything by hand? Choose how many projects and voters you want, and we'll - fill the form below with a ready-to-run example. You can change any value afterwards. -

-
- - - -
-
- -
-
-

1 Set the budget

-

How much money is there to share between all the projects?

- -
- -
-

2 List the projects

-

Give each project a name and how much it costs.

-
- #Project nameCost -
-
- -
- -
-

3 Add the votes

-

For each voter, tick every project they support. Leave all boxes empty if they support none.

-
- -
- - - -
-

4 See the fair result

-

We will fund as many projects as the budget allows, keeping everyone's influence equal.

- -
- - - -
-
-
- - - -{% endblock %} diff --git a/examples/ees_addopt_web/templates/result.html b/examples/ees_addopt_web/templates/result.html deleted file mode 100644 index afea58a..0000000 --- a/examples/ees_addopt_web/templates/result.html +++ /dev/null @@ -1,268 +0,0 @@ -{% extends "base.html" %} - -{% block title %}The fair result{% endblock %} - -{% block content %} -
-
-

The fair result

- {% if result.completed.is_empty %} -

No projects could be funded

-

With this budget and these votes, no project could be fully paid for. Try a bigger budget or cheaper projects.

- {% else %} -

{{ result.completed.count }} project{{ "" if result.completed.count == 1 else "s" }} funded

-

These are the projects the community will pay for. Below you can follow every step the tool took to get here.

- {% endif %} -
-
- -
- {{ result.completed.total_cost }} spent - {{ result.completed_leftover }} left of {{ result.budget }} -
- Try another election -
-
- -{% if not result.completed.is_empty %} -
-

Funded projects

-
    - {% for project in result.completed.project_payments %} -
  • - - {{ project.name }} - costs {{ project.cost }} -
    • - {% endfor %} -
-
-{% endif %} - -
-

Your input

-

This is exactly what was entered, so you can check the result against it.

-
-
-

Budget

-

{{ result.budget }}

-
-
-

Projects ({{ result.project_count }})

-
    - {% for project in result.project_rows %} -
  • {{ project.name }}costs {{ project.cost }}
    • - {% endfor %} -
-
-
-

Votes ({{ result.voter_count }} voter{{ "" if result.voter_count == 1 else "s" }})

-
    - {% for voter in result.base.voter_rows %} -
  • Voter {{ voter.number }}{{ voter.approvals }}
    • - {% endfor %} -
-
-
-
- -
-

How the result was reached, step by step

-

Nothing is hidden. Follow the four steps below, and open the log at the end to see every single decision.

-
- - -
-
1

Give everyone an equal share

-

- The budget of {{ result.budget }} is split equally among the - {{ result.voter_count }} voter{{ "" if result.voter_count == 1 else "s" }}. - So each voter gets {{ result.share_per_voter }} to spend on the projects they like. -

-

Because everyone gets the same amount, no group can be ignored — that is what keeps the result fair.

-
- - -
-
2

Fund projects with the Method of Equal Shares

-

- Using each voter's {{ result.share_per_voter }}, projects are picked one at a time, always choosing - the project that gives the most people the best value for money. Each chosen project is paid for by the voters who support it. -

- - {% if result.base.project_payments %} -

Projects picked, in order

-
    - {% for project in result.base.project_payments %} -
  1. - {{ project.name }} - costs {{ project.cost }} - - paid by - {% for payer in project.payers %}Voter {{ payer.voter }} ({{ payer.amount }}){% if not loop.last %}, {% endif %}{% endfor %} - -
    2. - {% endfor %} -
- {% else %} -

No project could be fully paid for in this first round.

- {% endif %} - -

What each voter spent and kept

-
- - - - {% for voter in result.base.voter_rows %} - - - - - - - - {% endfor %} - -
VoterVoted forEqual shareSpentKept
Voter {{ voter.number }}{{ voter.approvals }}{{ result.share_per_voter }}{{ voter.paid_total }}{{ voter.leftover }}
-
-

Everyone started with the same {{ result.share_per_voter }}, and nobody spent more than their share. This first round funded {{ result.base.selected_display }} and left {{ result.base_leftover }} unspent.

-
- - -
-
3

Use the leftover money

- {% if result.completion_multistep %} -

- To make better use of the {{ result.base_leftover }} left over, the tool pretends each voter has a - slightly bigger share and checks what the Method of Equal Shares would fund. It tries larger and larger shares, - and keeps the most expensive result that still fits the real {{ result.budget }} budget. -

-
- - - - - - {% for round in result.completion_rounds %} - - - - - - - - - {% endfor %} - -
RoundPretend share eachWould fundTotal costFits budget?Outcome
Round {{ round.number }}{{ round.share }}{{ round.selected_display }}{{ round.total_cost }}{{ "Yes" if round.fits else "No" }} - {% if round.is_chosen %} - ✓ Chosen - {% elif not round.fits %} - Too expensive - {% else %} - Tried - {% endif %} -
-
-

Round 1 is the first round from Step 2. The tool stops once a bigger share would only add projects that go over the budget.

- {% else %} -

The first round already used the budget as well as possible, so no extra projects could be added. The final result is the same as Step 2.

- {% endif %} -
- - -
-
4

The final decision

- {% if result.completed.is_empty %} -

No project could be funded within the budget.

- {% else %} -

- The funded projects are {{ result.completed.selected_display }}, costing - {{ result.completed.total_cost }} of the {{ result.budget }} budget, with - {{ result.completed_leftover }} left over. -

- {% endif %} -
- - - - {% for project in result.project_rows %} - - - - - - - {% endfor %} - -
ProjectCostVotesFunded
{{ project.name }}{{ project.cost }}{{ project.supporters }} - {% if project.in_completed %} - ✓ Funded - {% else %} - Not funded - {% endif %} -
-
-
- - -
-

See every step in the log

-

This is the algorithm's own record of what it did, in order ({{ result.logs | length }} message{{ "" if result.logs | length == 1 else "s" }}).

- - -
- -
- Extra technical values (for the curious) -
-

- Raw values behind the algorithm from the paper - Streamlining Equal Shares. - The smallest share increase that would change the first-round result was {{ result.next_delta }}. -

-
- - - - {% for row in result.leftover_rows %} - - {% endfor %} - -
VoterLeftover budgetLeximax payment vector
Voter {{ row.voter }}{{ row.leftover }}{{ row.leximax }}
-
-
-
- -
-
-

Want to experiment?

-

Change the budget, projects, or votes and watch how the steps and the result change.

-
- Build another election -
- - -{% endblock %} From c2d1629edc8511115ef7a788b82748f098e0d77f Mon Sep 17 00:00:00 2001 From: Yonatan Gabay Date: Wed, 10 Jun 2026 14:58:52 +0300 Subject: [PATCH 8/8] Add experiments directory with comparison experiment --- experiments/__init__.py | 0 experiments/experiment_comparison.py | 184 ++++++++++++++++++ experiments/results/comparison.csv | 49 +++++ experiments/results/comparison_report.md | 101 ++++++++++ .../results/num_selected_voters_50.png | Bin 0 -> 97391 bytes .../results/remaining_budget_voters_50.png | Bin 0 -> 73673 bytes experiments/results/runtime_voters_50.png | Bin 0 -> 53793 bytes .../results/social_welfare_voters_50.png | Bin 0 -> 103039 bytes experiments/results/total_cost_voters_50.png | Bin 0 -> 93761 bytes 9 files changed, 334 insertions(+) create mode 100644 experiments/__init__.py create mode 100644 experiments/experiment_comparison.py create mode 100644 experiments/results/comparison.csv create mode 100644 experiments/results/comparison_report.md create mode 100644 experiments/results/num_selected_voters_50.png create mode 100644 experiments/results/remaining_budget_voters_50.png create mode 100644 experiments/results/runtime_voters_50.png create mode 100644 experiments/results/social_welfare_voters_50.png create mode 100644 experiments/results/total_cost_voters_50.png diff --git a/experiments/__init__.py b/experiments/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/experiments/experiment_comparison.py b/experiments/experiment_comparison.py new file mode 100644 index 0000000..3cc29a5 --- /dev/null +++ b/experiments/experiment_comparison.py @@ -0,0 +1,184 @@ +""" +Section A – Performance comparison of EES algorithms vs. other PB rules. + +Compares: + - exact_equal_shares (EES, Algorithm 1) + - ees_add_opt_completion (EES + add-opt, Corollary 4.7) + - method_of_equal_shares (MES, the standard library implementation) + - greedy_utilitarian_welfare (Greedy welfare) + +Metrics: + - runtime (seconds) + - total_cost (budget utilisation) + - num_selected (number of selected projects) + - social_welfare (total approval score of selected projects) + +Uses the experiments-csv library. +""" + +import logging +import sys +import time + +import experiments_csv + +# ── make the repo root importable ────────────────────────────────────── +sys.path.insert(0, ".") + +from pabutools.election import ( + Instance, + Project, + ApprovalProfile, + ApprovalBallot, + Cost_Sat, +) +from pabutools.election.instance import get_random_instance +from pabutools.election.profile.approvalprofile import get_random_approval_profile +from pabutools.rules import greedy_utilitarian_welfare, method_of_equal_shares +from pabutools.rules.ees_addopt import exact_equal_shares, ees_add_opt_completion + +TIME_LIMIT = 60 # seconds per single run + +# ── algorithm registry ───────────────────────────────────────────────── +ALGORITHMS = { + "EES": lambda inst, prof: exact_equal_shares(inst, prof), + "EES_AddOpt": lambda inst, prof: ees_add_opt_completion(inst, prof), + "MES": lambda inst, prof: method_of_equal_shares( + inst, prof, sat_class=Cost_Sat, resoluteness=True + ), + "Greedy": lambda inst, prof: greedy_utilitarian_welfare( + inst, prof, sat_class=Cost_Sat, resoluteness=True + ), +} + + +# ── single experiment function ───────────────────────────────────────── +def run_single(num_projects: int, num_voters: int, algorithm: str, seed: int): + """Run a single experiment: generate a random instance, run the algorithm, + and return measured outputs.""" + import random as _random + + _random.seed(seed) + + # Generate random instance (same style as test_ees_addopt random tests) + approval_prob = 0.4 + budget_factor_low, budget_factor_high = 0.4, 0.8 + + projects = [] + for i in range(num_projects): + projects.append(Project(str(i), _random.randint(0, 100))) + total_project_cost = sum(p.cost for p in projects) + if total_project_cost == 0: + total_project_cost = 1 + budget = int(total_project_cost * _random.uniform(budget_factor_low, budget_factor_high)) + budget = max(budget, 1) + instance = Instance(projects, budget_limit=budget) + + ballots = [] + for v in range(num_voters): + approved = [p for p in projects if _random.random() < approval_prob] + ballots.append(ApprovalBallot(approved)) + profile = ApprovalProfile(ballots, instance=instance) + + algo_fn = ALGORITHMS[algorithm] + + start = time.perf_counter() + result = algo_fn(instance, profile) + elapsed = time.perf_counter() - start + + total_cost = sum(p.cost for p in result) + num_selected = len(result) + + # Social welfare: total number of approvals for the selected projects + social_welfare = 0 + for project in result: + social_welfare += profile.approval_score(project) + + return { + "runtime": round(elapsed, 4), + "total_cost": int(total_cost), + "num_selected": num_selected, + "social_welfare": social_welfare, + "budget_limit": int(instance.budget_limit), + "remaining_budget": int(instance.budget_limit) - int(total_cost), + } + + +# ── main ─────────────────────────────────────────────────────────────── +RESULTS_DIR = "experiments/results" +CSV_FILE = "comparison.csv" +BACKUPS_DIR = "experiments/results/backups" + + +def run_experiments(): + """Run the full comparison experiment.""" + ex = experiments_csv.Experiment(RESULTS_DIR, CSV_FILE, BACKUPS_DIR) + ex.logger.setLevel(logging.INFO) + + input_ranges = { + "num_projects": [10, 30, 60, 100], + "num_voters": [50], + "algorithm": list(ALGORITHMS.keys()), + "seed": [1, 2, 3], + } + + ex.run(run_single, input_ranges) + print(f"\nExperiment data saved to {RESULTS_DIR}/{CSV_FILE}") + + +def plot_results(): + """Generate comparison plots from the CSV results.""" + import pandas as pd + from matplotlib import pyplot as plt + + csv_path = f"{RESULTS_DIR}/{CSV_FILE}" + df = pd.read_csv(csv_path) + + # Compute remaining_budget if not already in CSV (backward compat) + if "remaining_budget" not in df.columns: + df["remaining_budget"] = df["budget_limit"] - df["total_cost"] + + VOTER_COUNTS = [50] + metrics = [ + ("runtime", "Runtime (seconds)"), + ("total_cost", "Total Cost"), + ("remaining_budget", "Remaining Budget (unused)"), + ("social_welfare", "Social Welfare (total approvals)"), + ("num_selected", "Number of Selected Projects"), + ] + + for metric, ylabel in metrics: + for n_voters in VOTER_COUNTS: + plt.figure(figsize=(8, 5)) + subset = df[df["num_voters"] == n_voters] + grouped = subset.groupby(["num_projects", "algorithm"])[metric].mean().reset_index() + + for algo in sorted(grouped["algorithm"].unique()): + algo_data = grouped[grouped["algorithm"] == algo] + plt.plot( + algo_data["num_projects"], + algo_data[metric], + marker="o", + label=algo, + ) + + plt.title(f"{ylabel} vs. Number of Projects (voters={n_voters})") + plt.xlabel("Number of Projects") + plt.ylabel(ylabel) + plt.legend() + plt.grid(True, alpha=0.3) + plt.tight_layout() + save_path = f"{RESULTS_DIR}/{metric}_voters_{n_voters}.png" + plt.savefig(save_path, dpi=150) + plt.close() + print(f"Saved {save_path}") + + print("\nAll plots saved.") + + +if __name__ == "__main__": + if len(sys.argv) > 1 and sys.argv[1] == "plot": + plot_results() + else: + run_experiments() + plot_results() diff --git a/experiments/results/comparison.csv b/experiments/results/comparison.csv new file mode 100644 index 0000000..283b1d9 --- /dev/null +++ b/experiments/results/comparison.csv @@ -0,0 +1,49 @@ +num_projects,num_voters,algorithm,seed,runtime,total_cost,num_selected,social_welfare,budget_limit,remaining_budget +10,50,EES,1,0.0025,135,5,115,342,207 +10,50,EES,2,0.002,120,6,122,204,84 +10,50,EES,3,0.0018,178,5,107,344,166 +10,50,EES_AddOpt,1,0.063,324,8,168,342,18 +10,50,EES_AddOpt,2,0.0735,166,7,141,204,38 +10,50,EES_AddOpt,3,0.2167,332,7,148,344,12 +10,50,MES,1,0.0043,207,6,136,342,135 +10,50,MES,2,0.003,120,6,122,204,84 +10,50,MES,3,0.0036,258,6,129,344,86 +10,50,Greedy,1,0.0011,304,7,157,342,38 +10,50,Greedy,2,0.0016,197,7,146,204,7 +10,50,Greedy,3,0.0014,332,7,148,344,12 +30,50,EES,1,0.0314,973,23,458,1229,256 +30,50,EES,2,0.0368,804,22,461,1109,305 +30,50,EES,3,0.0231,820,20,425,1096,276 +30,50,EES_AddOpt,1,1.4754,1168,25,504,1229,61 +30,50,EES_AddOpt,2,1.3436,1107,26,540,1109,2 +30,50,EES_AddOpt,3,1.6663,1096,24,497,1096,0 +30,50,MES,1,0.0064,1105,22,451,1229,124 +30,50,MES,2,0.0113,964,23,491,1109,145 +30,50,MES,3,0.0121,995,22,474,1096,101 +30,50,Greedy,1,0.0015,1224,24,497,1229,5 +30,50,Greedy,2,0.0015,1106,23,498,1109,3 +30,50,Greedy,3,0.0029,1082,22,476,1096,14 +60,50,EES,1,0.0673,1998,48,1009,2340,342 +60,50,EES,2,0.076,1937,48,940,2316,379 +60,50,EES,3,0.0626,1253,36,742,1550,297 +60,50,EES_AddOpt,1,7.2866,2324,52,1093,2340,16 +60,50,EES_AddOpt,2,7.5881,2313,53,1028,2316,3 +60,50,EES_AddOpt,3,14.6037,1526,40,817,1550,24 +60,50,MES,1,0.019,2205,47,1012,2340,135 +60,50,MES,2,0.0173,2203,50,987,2316,113 +60,50,MES,3,0.0175,1490,36,774,1550,60 +60,50,Greedy,1,0.0064,2338,49,1055,2340,2 +60,50,Greedy,2,0.0043,2305,48,969,2316,11 +60,50,Greedy,3,0.0066,1550,30,674,1550,0 +100,50,EES,1,0.1872,3351,77,1593,3591,240 +100,50,EES,2,0.1853,3026,70,1430,3299,273 +100,50,EES,3,0.1786,2992,71,1493,3217,225 +100,50,EES_AddOpt,1,41.6526,3544,79,1634,3591,47 +100,50,EES_AddOpt,2,52.6927,3288,74,1497,3299,11 +100,50,EES_AddOpt,3,55.2711,3158,73,1535,3217,59 +100,50,MES,1,0.0455,3494,73,1550,3591,97 +100,50,MES,2,0.0621,3192,66,1393,3299,107 +100,50,MES,3,0.0562,3175,64,1415,3217,42 +100,50,Greedy,1,0.0132,3590,68,1474,3591,1 +100,50,Greedy,2,0.0093,3284,64,1372,3299,15 +100,50,Greedy,3,0.0125,3217,61,1361,3217,0 diff --git a/experiments/results/comparison_report.md b/experiments/results/comparison_report.md new file mode 100644 index 0000000..469df9c --- /dev/null +++ b/experiments/results/comparison_report.md @@ -0,0 +1,101 @@ +# Section A – Performance Comparison + +### Algorithms Tested + +| Algorithm | Description | Source | +|-----------|-------------|--------| +| **EES** | Exact Equal Shares (Algorithm 1) – selects projects by bang-per-buck ratio, splitting costs equally among supporters | Paper, `ees_addopt.py` | +| **EES_AddOpt** | EES + Add-Opt Completion (Corollary 4.7) – repeatedly runs EES with increasing virtual budgets until the outcome exhausts the budget | Paper, `ees_addopt.py` | +| **MES** | Method of Equal Shares – the standard library implementation with Cost Satisfaction | `pabutools.rules.mes` | +| **Greedy** | Greedy Utilitarian Welfare – greedy algorithm selecting projects by approval score | `pabutools.rules.greedywelfare` | + +### Metrics Measured + +1. **runtime** – execution time in seconds +2. **remaining_budget** – unused budget (budget_limit − total_cost) +3. **total_cost** – total cost of selected projects +4. **social_welfare** – sum of approval scores for selected projects +5. **num_selected** – number of selected projects + +### Experiment Parameters + +All 4 algorithms run on **exactly the same inputs**: + +- **Number of projects**: 10, 30, 60, 100 +- **Number of voters**: 50 +- **Repetitions**: 3 runs (seeds: 1, 2, 3) – averages shown in plots +- **Input generation**: random costs between 0 and 100, budget = 40%–80% of total cost, approval probability = 0.4 + +--- + +## Results + +### Runtime + +![Runtime](runtime_voters_50.png) + +| Algorithm | 10 projects | 30 projects | 60 projects | 100 projects | +|-----------|------------|------------|------------|-------------| +| **EES** | 0.002s | 0.03s | 0.07s | 0.18s | +| **EES_AddOpt** | 0.12s | 1.50s | 9.83s | **49.87s** | +| **MES** | 0.004s | 0.01s | 0.02s | 0.05s | +| **Greedy** | 0.001s | 0.002s | 0.006s | 0.01s | + +**Findings:** +- **Greedy** is the fastest, followed by **MES** +- **EES** (Algorithm 1 alone) is relatively fast – 0.18s at 100 projects +- **EES_AddOpt** is significantly slower: ~50 seconds at 100 projects, because it runs EES + add_opt multiple times with increasing virtual budgets + +### Remaining Budget + +![Remaining Budget](remaining_budget_voters_50.png) + +| Algorithm | 10 projects | 30 projects | 60 projects | 100 projects | +|-----------|------------|------------|------------|-------------| +| **EES** | 152 | 279 | 339 | 246 | +| **EES_AddOpt** | **23** | **21** | **14** | **39** | +| **MES** | 102 | 123 | 103 | 82 | +| **Greedy** | 19 | 7 | 4 | 5 | + +**Findings:** +- **EES** leaves the most budget unused – it stops as soon as no project can be funded equally among supporters +- **EES_AddOpt** dramatically improves budget utilization: only 14–39 remaining, compared to 152–339 for plain EES +- **MES** is in between: 82–123 remaining +- **Greedy** has the best budget utilization (4–19) but does not guarantee fairness + +### Social Welfare + +![Social Welfare](social_welfare_voters_50.png) + +| Algorithm | 10 projects | 30 projects | 60 projects | 100 projects | +|-----------|------------|------------|------------|-------------| +| **EES** | 115 | 448 | 897 | 1505 | +| **EES_AddOpt** | **152** | **514** | **979** | **1555** | +| **MES** | 129 | 472 | 924 | 1453 | +| **Greedy** | 150 | 490 | 899 | 1402 | + +**Findings:** +- **EES_AddOpt** achieves the highest social welfare at every input size +- At 100 projects: EES_AddOpt (1555) > EES (1505) > MES (1453) > Greedy (1402) +- The gap between EES_AddOpt and MES grows with input size + +### Total Cost and Number of Selected Projects + +![Total Cost](total_cost_voters_50.png) +![Num Selected](num_selected_voters_50.png) + +--- + +## Conclusions + +| | Runtime | Budget Utilization | Social Welfare | Fairness | +|---|---|---|---|---| +| **EES** | Fast | Low | Medium | ✓ | +| **EES_AddOpt** | **Very slow** | **High** | **Highest** | ✓ | +| **MES** | Fast | Medium | Medium-High | ✓ | +| **Greedy** | **Fastest** | **Highest** | Relatively low | ✗ | + +1. **EES_AddOpt** achieves the best outcomes (social welfare + budget utilization) while maintaining fairness – but at a very high runtime cost (~50s 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