ecclesia/dist/election/attribution.cjs

Framework for political and electoral simulations

"use strict";
var __create = Object.create;
var __defProp = Object.defineProperty;
var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
var __getOwnPropNames = Object.getOwnPropertyNames;
var __getProtoOf = Object.getPrototypeOf;
var __hasOwnProp = Object.prototype.hasOwnProperty;
var __export = (target, all) => {
  for (var name in all)
    __defProp(target, name, { get: all[name], enumerable: true });
};
var __copyProps = (to, from, except, desc) => {
  if (from && typeof from === "object" || typeof from === "function") {
    for (let key of __getOwnPropNames(from))
      if (!__hasOwnProp.call(to, key) && key !== except)
        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
  }
  return to;
};
var __toESM = (mod, isNodeMode, target) => (target = mod != null ? __create(__getProtoOf(mod)) : {}, __copyProps(
  // If the importer is in node compatibility mode or this is not an ESM
  // file that has been converted to a CommonJS file using a Babel-
  // compatible transform (i.e. "__esModule" has not been set), then set
  // "default" to the CommonJS "module.exports" for node compatibility.
  isNodeMode || !mod || !mod.__esModule ? __defProp(target, "default", { value: mod, enumerable: true }) : target,
  mod
));
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);

// src/election/attribution.ts
var attribution_exports = {};
__export(attribution_exports, {
  AttributionFailure: () => AttributionFailure,
  addThresholdToSimpleAttribution: () => addThresholdToSimpleAttribution,
  averageScore: () => averageScore,
  bordaCount: () => bordaCount,
  boundedRankIndexMethod: () => boundedRankIndexMethod,
  condorcet: () => condorcet,
  dHondt: () => dHondt,
  hamilton: () => hamilton,
  hareLargestRemainders: () => hareLargestRemainders,
  highestAverages: () => highestAverages,
  huntingtonHill: () => huntingtonHill,
  instantRunoff: () => instantRunoff,
  jefferson: () => jefferson,
  largestRemainders: () => largestRemainders,
  medianScore: () => medianScore,
  plurality: () => plurality,
  proportionalFromDivisorFunction: () => proportionalFromDivisorFunction,
  proportionalFromRankIndexFunction: () => proportionalFromRankIndexFunction,
  randomize: () => randomize,
  rankIndexFunctionFromDivisorFunction: () => rankIndexFunctionFromDivisorFunction,
  sainteLague: () => sainteLague,
  superMajority: () => superMajority,
  webster: () => webster
});
module.exports = __toCommonJS(attribution_exports);

// src/election/attribution/base.ts
var AttributionFailure = class extends Error {
};

// src/election/attribution/transform.ts
var import_collections = require("@gouvernathor/python/collections");
function addThresholdToSimpleAttribution({ threshold, attribution, contingency = attribution }) {
  const attrib = (votes, rest = {}) => {
    if (threshold > 0) {
      const original_votes = votes;
      const votes_threshold = threshold * votes.total;
      votes = new import_collections.Counter([...votes.entries()].filter(([_, v]) => v >= votes_threshold));
      if (votes.size === 0) {
        if (contingency === null) {
          throw new AttributionFailure("No party reached the threshold");
        }
        return contingency(original_votes, rest);
      }
    }
    return attribution(votes, rest);
  };
  return attrib;
}

// src/election/attribution/proportionalBase.ts
var import_collections2 = require("@gouvernathor/python/collections");

// src/election/attribution/metrics.ts
function defaultMetric({ votes, seats }) {
  const allVotes = votes.total;
  const allSeats = seats.total;
  let suum = 0;
  for (const party of seats.keys()) {
    const partyVotes = votes.get(party);
    const partySeats = seats.get(party);
    suum += Math.abs(allSeats * partyVotes / allVotes - partySeats);
  }
  return suum / seats.size;
}

// src/election/attribution/proportionalBase.ts
function proportionalFromRankIndexFunction({ nSeats, rankIndexFunction }) {
  const attrib = (votes, rest = {}) => {
    const allVotes = votes.total;
    const fractions = new Map([...votes.entries()].map(([party, v]) => [party, v / allVotes]));
    const rankIndexValues = new Map([...fractions.entries()].map(([party, f]) => [party, rankIndexFunction(f, 0)]));
    const parties = [...votes.keys()].sort((a, b) => rankIndexValues.get(a) - rankIndexValues.get(b));
    const seats = new import_collections2.Counter();
    s: for (let sn = 0; sn < nSeats; sn++) {
      const winner = parties.pop();
      seats.increment(winner);
      rankIndexValues.set(winner, rankIndexFunction(fractions.get(winner), seats.get(winner)));
      for (let pn = 0; pn < parties.length; pn++) {
        if (rankIndexValues.get(parties[pn]) >= rankIndexValues.get(winner)) {
          parties.splice(pn, 0, winner);
          continue s;
        }
      }
      parties.push(winner);
    }
    return seats;
  };
  attrib.nSeats = nSeats;
  return attrib;
}
function boundedRankIndexMethod({ minNSeats, maxNSeats, rankIndexFunction, metric = defaultMetric }) {
  const attrib = (votes, rest = {}) => {
    const allVotes = votes.total;
    const fractions = new Map([...votes.entries()].map(([party, v]) => [party, v / allVotes]));
    const rankIndexValues = new Map([...fractions.entries()].map(([party, f]) => [party, rankIndexFunction(f, 0)]));
    const parties = [...votes.keys()].sort((a, b) => rankIndexValues.get(a) - rankIndexValues.get(b));
    const seats = new import_collections2.Counter();
    let bestSeats = seats.pos;
    let bestSeatsMetric = Infinity;
    s: for (let sn = 1; sn <= maxNSeats; sn++) {
      const winner = parties.pop();
      seats.increment(winner);
      if (sn >= minNSeats) {
        const newMetric = metric({ votes, seats });
        if (newMetric < bestSeatsMetric) {
          bestSeats = seats.pos;
          bestSeatsMetric = newMetric;
        }
      }
      rankIndexValues.set(winner, rankIndexFunction(fractions.get(winner), seats.get(winner)));
      for (let pn = 0; pn < parties.length; pn++) {
        if (rankIndexValues.get(parties[pn]) >= rankIndexValues.get(winner)) {
          parties.splice(pn, 0, winner);
          continue s;
        }
      }
      parties.push(winner);
    }
    return bestSeats;
  };
  attrib.minNSeats = minNSeats;
  attrib.maxNSeats = maxNSeats;
  return attrib;
}
function stationaryDivisorFunction(r) {
  return (k) => k + r;
}
function rankIndexFunctionFromDivisorFunction(divisorFunction) {
  return (t, a) => t / divisorFunction(a);
}
function proportionalFromDivisorFunction({ nSeats, divisorFunction }) {
  return proportionalFromRankIndexFunction({
    nSeats,
    rankIndexFunction: rankIndexFunctionFromDivisorFunction(divisorFunction)
  });
}

// src/election/attribution/majorityFactory.ts
var import_python = require("@gouvernathor/python");
var import_collections3 = require("@gouvernathor/python/collections");
function plurality({ nSeats }) {
  const attrib = (votes, rest = {}) => {
    const win = (0, import_python.max)(votes.keys(), (p) => votes.get(p));
    if (votes.get(win) > 0) {
      return new import_collections3.Counter([[win, nSeats]]);
    }
    throw new AttributionFailure("No party won any vote");
  };
  attrib.nSeats = nSeats;
  return attrib;
}
function superMajority({ nSeats, threshold, contingency = null }) {
  const attrib = (votes, rest = {}) => {
    const win = (0, import_python.max)(votes.keys(), (p) => votes.get(p));
    if (votes.get(win) / votes.total > threshold) {
      return new import_collections3.Counter([[win, nSeats]]);
    }
    if (contingency === null) {
      throw new AttributionFailure("No party reached the threshold");
    }
    return contingency(votes, rest);
  };
  attrib.nSeats = nSeats;
  return attrib;
}

// src/election/attribution/orderingFactory.ts
var import_python2 = require("@gouvernathor/python");
var import_collections4 = require("@gouvernathor/python/collections");
function instantRunoff({ nSeats }) {
  const attrib = (votes, rest = {}) => {
    const blacklisted = /* @__PURE__ */ new Set();
    const nParties = new Set(votes.flat()).size;
    for (let pn = 0; pn < nParties; pn++) {
      const firstPlaces = new import_collections4.Counter();
      for (const ballot of votes) {
        for (const party of ballot) {
          if (!blacklisted.has(party)) {
            firstPlaces.increment(party);
            break;
          }
        }
      }
      const total = firstPlaces.total;
      for (const [party, score] of firstPlaces) {
        if (score / total > 0.5) {
          return new import_collections4.Counter([[party, nSeats]]);
        }
      }
      blacklisted.add((0, import_python2.min)(firstPlaces.keys(), (p) => firstPlaces.get(p)));
    }
    throw new Error("Should not happen");
  };
  attrib.nSeats = nSeats;
  return attrib;
}
function bordaCount({ nSeats }) {
  const attrib = (votes, rest = {}) => {
    const scores = new import_collections4.Counter();
    for (const ballot of votes) {
      for (const [i, party] of (0, import_python2.enumerate)(ballot.slice().reverse(), 1)) {
        scores.increment(party, i);
      }
    }
    return new import_collections4.Counter([[(0, import_python2.max)(scores.keys(), (p) => scores.get(p)), nSeats]]);
  };
  attrib.nSeats = nSeats;
  return attrib;
}
function condorcet({ nSeats, contingency = null }) {
  const attrib = (votes, rest = {}) => {
    const counts = new import_collections4.DefaultMap(() => new import_collections4.Counter());
    const majority = votes.length / 2;
    for (const ballot of votes) {
      for (const [i, party1] of (0, import_python2.enumerate)(ballot)) {
        for (const party2 of ballot.slice(i + 1)) {
          counts.get(party1).increment(party2);
        }
      }
    }
    const win = new Set(counts.keys());
    for (const [party, partyCounter] of counts) {
      for (const value of partyCounter.pos.values()) {
        if (value > majority) {
          win.delete(party);
          break;
        }
      }
    }
    if (win.size !== 1) {
      if (win.size !== 0) {
        throw new Error("Bad attribution");
      }
      if (contingency === null) {
        throw new condorcet.Standoff("No Condorcet winner");
      }
      return contingency(votes, rest);
    }
    const [winner] = win;
    return new import_collections4.Counter([[winner, nSeats]]);
  };
  attrib.nSeats = nSeats;
  return attrib;
}
condorcet.Standoff = class CondorcetStandoff extends AttributionFailure {
};

// src/election/attribution/scoreFactory.ts
var import_python3 = require("@gouvernathor/python");
var import_collections5 = require("@gouvernathor/python/collections");
var import_statistics = require("@gouvernathor/python/statistics");

// src/election/ballots.ts
var Scores;
((Scores2) => {
  function get(key) {
    const value = this.get(key);
    if (value === void 0) {
      return Array(this.ngrades).fill(0);
    }
    return value;
  }
  function fromEntries(elements) {
    if (elements.length === 0) {
      throw new Error("Use the fromGrades method to create an empty Scores instance");
    }
    const ths = new Map(elements);
    ths.ngrades = elements[0][1].length;
    ths.get = get.bind(ths);
    return ths;
  }
  Scores2.fromEntries = fromEntries;
  function fromGrades(ngrades) {
    const ths = /* @__PURE__ */ new Map();
    ths.ngrades = ngrades;
    ths.get = get.bind(ths);
    return ths;
  }
  Scores2.fromGrades = fromGrades;
})(Scores || (Scores = {}));

// src/election/attribution/scoreFactory.ts
function averageScore({ nSeats }) {
  const attrib = (votes, rest = {}) => {
    const counts = new import_collections5.DefaultMap(() => []);
    for (const [party, grades] of votes) {
      for (const [grade, qty] of (0, import_python3.enumerate)(grades)) {
        counts.get(party).push(...Array(qty).fill(grade));
      }
    }
    return new import_collections5.Counter([[(0, import_python3.max)(counts.keys(), (party) => (0, import_statistics.fmean)(counts.get(party))), nSeats]]);
  };
  attrib.nSeats = nSeats;
  return attrib;
}
function medianScore({ nSeats, contingency }) {
  if (contingency === void 0) {
    contingency = averageScore({ nSeats });
  }
  const attrib = (votes, rest = {}) => {
    const counts = new import_collections5.DefaultMap(() => []);
    for (const [party, grades] of votes) {
      for (const [grade, qty] of (0, import_python3.enumerate)(grades)) {
        counts.get(party).push(...Array(qty).fill(grade));
      }
    }
    const medians = new Map([...counts.entries()].map(([party, partigrades]) => [party, (0, import_statistics.median)(partigrades)]));
    const winScore = Math.max(...medians.values());
    const [winner, ...winners] = [...medians.keys()].filter((p) => medians.get(p) === winScore);
    if (winners.length === 0) {
      return new import_collections5.Counter([[winner, nSeats]]);
    }
    winners.unshift(winner);
    const trimmedResults = Scores.fromEntries(winners.map((party) => [party, counts.get(party)]));
    return contingency(trimmedResults, rest);
  };
  attrib.nSeats = nSeats;
  return attrib;
}

// src/election/attribution/proportionalFactory.ts
var import_python4 = require("@gouvernathor/python");
var import_collections6 = require("@gouvernathor/python/collections");
var divisor1 = stationaryDivisorFunction(1);
function jefferson({ nSeats }) {
  return proportionalFromDivisorFunction({
    nSeats,
    divisorFunction: divisor1
  });
}
var dHondt = jefferson;
var divisorPoint5 = (k) => 2 * k + 1;
function webster({ nSeats }) {
  return proportionalFromDivisorFunction({
    nSeats,
    divisorFunction: divisorPoint5
  });
}
var sainteLague = webster;
function hamilton({ nSeats }) {
  const attrib = (votes, rest = {}) => {
    const seats = new import_collections6.Counter();
    const remainders = /* @__PURE__ */ new Map();
    const sumVotes = votes.total;
    for (const [party, scores] of votes) {
      const [i, r] = (0, import_python4.divmod)(scores * nSeats, sumVotes);
      seats.set(party, i);
      remainders.set(party, r);
    }
    seats.update([...remainders.keys()].sort((a, b) => remainders.get(b) - remainders.get(a)).slice(0, nSeats - seats.total));
    return seats;
  };
  attrib.nSeats = nSeats;
  return attrib;
}
var hareLargestRemainders = hamilton;
var huntingtonHillBaseRankIndexFunction = rankIndexFunctionFromDivisorFunction((k) => Math.sqrt(k * (k + 1)));
var huntingtonHillRankIndexFunction = (t, a) => {
  if (a <= 0) {
    return Infinity;
  }
  return huntingtonHillBaseRankIndexFunction(t, a);
};
function huntingtonHill({ nSeats, threshold, contingency = null }) {
  const attrib = addThresholdToSimpleAttribution({
    threshold,
    contingency,
    attribution: proportionalFromRankIndexFunction({
      nSeats,
      rankIndexFunction: huntingtonHillRankIndexFunction
    })
  });
  attrib.nSeats = nSeats;
  return attrib;
}
var highestAverages = webster;
var largestRemainders = hamilton;

// src/election/attribution/randomFactory.ts
var import_collections7 = require("@gouvernathor/python/collections");

// src/utils.ts
var import_rng = __toESM(require("@gouvernathor/rng"), 1);
function createRandomObj({ randomObj, randomSeed } = {}) {
  if (randomObj === void 0) {
    randomObj = new import_rng.default(randomSeed);
  }
  return randomObj;
}

// src/election/attribution/randomFactory.ts
function randomize({ nSeats, ...randomParam }) {
  const attrib = (votes, rest = {}) => {
    const randomObj = createRandomObj(randomParam);
    return new import_collections7.Counter(randomObj.choices([...votes.keys()], { weights: [...votes.values()], k: nSeats }));
  };
  attrib.nSeats = nSeats;
  return attrib;
}
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
  AttributionFailure,
  addThresholdToSimpleAttribution,
  averageScore,
  bordaCount,
  boundedRankIndexMethod,
  condorcet,
  dHondt,
  hamilton,
  hareLargestRemainders,
  highestAverages,
  huntingtonHill,
  instantRunoff,
  jefferson,
  largestRemainders,
  medianScore,
  plurality,
  proportionalFromDivisorFunction,
  proportionalFromRankIndexFunction,
  randomize,
  rankIndexFunctionFromDivisorFunction,
  sainteLague,
  superMajority,
  webster
});
//# sourceMappingURL=attribution.cjs.map