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* @module CIA/ElectionPredictions
* @category Intelligence Platform - Electoral Forecasting Engine
*
* @description
* Election 2026 Predictions Module – Swedish Electoral Forecasting & Coalition Analysis.
* Implements sophisticated electoral forecasting and coalition scenario analysis for the
* Swedish parliamentary elections scheduled for 2026. Transforms raw polling data,
* historical voting patterns, and demographic trends into probabilistic seat distribution
* predictions and viable coalition formation scenarios.
*
* @author Hack23 AB - Electoral Intelligence
* @license Apache-2.0
* @version 1.0.0
* @since 2024-01-15
*
* @intelligence Electoral Forecasting Engine — sophisticated seat prediction algorithms for Swedish parliamentary elections (2026). Implements probabilistic seat distribution, coalition scenario analysis, and confidence interval calculations. Transforms polling data, historical voting patterns, and demographic trends into actionable electoral intelligence.
*
* @business Flagship forecasting product — election predictions are the highest-traffic, highest-engagement feature during election periods. Forecasting accuracy builds reputational capital. Prediction data is monetizable through media licensing, API access, and custom reporting.
*
* @marketing Peak virality content — election prediction charts and coalition probability visualizations achieve maximum social media engagement and press coverage. Each forecast update is a content marketing event. Prediction accuracy tracking builds long-term brand credibility.
* */
import type { ElectionAnalysis } from './data-loader.js';
/* ------------------------------------------------------------------ */
/* Global library reference (loaded via <script> tag) */
/* ------------------------------------------------------------------ */
const Chart = (globalThis as any).Chart;
/* ------------------------------------------------------------------ */
/* Interfaces */
/* ------------------------------------------------------------------ */
/** Party forecast entry used in seat prediction rendering. */
export interface PartyForecast {
name: string;
currentSeats: number;
predictedSeats: number;
change: number;
voteShare: number;
confidenceInterval?: { min: number; max: number };
}
/** Coalition scenario entry. */
export interface CoalitionScenario {
name: string;
composition: string[];
totalSeats: number;
probability: number;
majority: boolean;
riskLevel: string;
}
/** Summary statistics from election forecast. */
export interface SummaryStats {
totalSeats: number;
gainers: number;
losers: number;
stable: number;
biggestGain: PartyForecast | null;
biggestLoss: PartyForecast | null;
}
/* ------------------------------------------------------------------ */
/* Election2026Predictions class */
/* ------------------------------------------------------------------ */
export class Election2026Predictions {
readonly data: ElectionAnalysis;
constructor(electionData: ElectionAnalysis) {
this.data = electionData;
}
/** Render seat predictions for all parties. */
renderSeatPredictions(): void {
const container = document.getElementById('seat-predictions');
if (!container) return;
if (!this.data || !this.data.forecast || !Array.isArray(this.data.forecast.parties)) {
console.warn('Invalid or missing election forecast data');
return;
}
const { parties } = this.data.forecast;
container.textContent = '';
const fragment = document.createDocumentFragment();
parties.forEach((party: PartyForecast) => {
const changeClass = party.change >= 0 ? 'positive' : 'negative';
const changeSymbol = party.change >= 0 ? '+' : '';
const cardClass = party.change >= 0 ? 'gain' : 'loss';
const card = document.createElement('div');
card.className = `prediction-card ${cardClass}`;
const partyName = document.createElement('h3');
partyName.className = 'prediction-party';
partyName.textContent = party.name;
const seatsDiv = document.createElement('div');
seatsDiv.className = 'prediction-seats';
// Current seats
const currentDiv = document.createElement('div');
currentDiv.className = 'seats-current';
const currentLabel = document.createElement('div');
currentLabel.className = 'seats-label';
currentLabel.textContent = 'Current';
const currentValue = document.createElement('strong');
currentValue.textContent = String(party.currentSeats);
currentDiv.appendChild(currentLabel);
currentDiv.appendChild(currentValue);
// Arrow
const arrowDiv = document.createElement('div');
arrowDiv.className = 'seats-arrow';
arrowDiv.textContent = '→';
// Predicted seats
const predictedDiv = document.createElement('div');
predictedDiv.className = 'seats-predicted';
const predictedLabel = document.createElement('div');
predictedLabel.className = 'seats-label';
predictedLabel.textContent = 'Predicted';
const predictedValue = document.createElement('strong');
predictedValue.textContent = String(party.predictedSeats);
predictedDiv.appendChild(predictedLabel);
predictedDiv.appendChild(predictedValue);
seatsDiv.appendChild(currentDiv);
seatsDiv.appendChild(arrowDiv);
seatsDiv.appendChild(predictedDiv);
// Change
const changeDiv = document.createElement('div');
changeDiv.className = `seats-change ${changeClass}`;
changeDiv.textContent = `${changeSymbol}${party.change} seats (${party.voteShare}%)`;
// Confidence interval with defensive check
const confidenceDiv = document.createElement('div');
confidenceDiv.className = 'confidence-interval';
let ciText = '95% CI: N/A';
if (
party.confidenceInterval &&
typeof party.confidenceInterval.min === 'number' &&
typeof party.confidenceInterval.max === 'number'
) {
ciText = `95% CI: ${party.confidenceInterval.min}-${party.confidenceInterval.max} seats`;
} else {
console.warn('Missing or invalid confidenceInterval for party', party.name, party);
}
confidenceDiv.textContent = ciText;
card.appendChild(partyName);
card.appendChild(seatsDiv);
card.appendChild(changeDiv);
card.appendChild(confidenceDiv);
fragment.appendChild(card);
});
container.appendChild(fragment);
}
/** Render coalition scenarios. */
renderCoalitionScenarios(): void {
const container = document.getElementById('coalition-scenarios');
if (!container) return;
if (!this.data || !Array.isArray(this.data.coalitionScenarios)) {
console.warn('Invalid or missing coalition scenarios data');
return;
}
const { coalitionScenarios } = this.data;
container.textContent = '';
const fragment = document.createDocumentFragment();
coalitionScenarios.forEach((scenario: CoalitionScenario) => {
const majorityClass = scenario.majority ? 'yes' : 'no';
const majorityText = scenario.majority ? 'Majority ✓' : 'No Majority';
const card = document.createElement('div');
card.className = 'scenario-card';
const probability = document.createElement('div');
probability.className = 'scenario-probability';
probability.textContent = `${scenario.probability}%`;
const name = document.createElement('h3');
name.className = 'scenario-name';
name.textContent = scenario.name;
const composition = document.createElement('div');
composition.className = 'scenario-composition';
if (Array.isArray(scenario.composition)) {
scenario.composition.forEach((partyId: string) => {
const badge = document.createElement('span');
badge.className = 'party-badge';
badge.textContent = partyId;
composition.appendChild(badge);
});
} else {
console.warn('Missing or invalid composition for scenario', scenario.name);
}
const seats = document.createElement('div');
seats.className = 'scenario-seats';
const seatsStrong = document.createElement('strong');
seatsStrong.textContent = String(scenario.totalSeats);
seats.appendChild(seatsStrong);
seats.appendChild(document.createTextNode(' seats (175 required for majority)'));
const majority = document.createElement('span');
majority.className = `scenario-majority ${majorityClass}`;
majority.textContent = majorityText;
const riskLevel = document.createElement('div');
riskLevel.className = 'scenario-risk-level';
riskLevel.textContent = 'Risk Level: ';
const riskStrong = document.createElement('strong');
riskStrong.textContent = scenario.riskLevel;
riskLevel.appendChild(riskStrong);
card.appendChild(probability);
card.appendChild(name);
card.appendChild(composition);
card.appendChild(seats);
card.appendChild(majority);
card.appendChild(riskLevel);
fragment.appendChild(card);
});
container.appendChild(fragment);
}
/**
* Render key factors affecting the election.
* NOTE: Requires `<div id="key-factors"></div>` in the HTML.
*/
renderKeyFactors(): void {
const container = document.getElementById('key-factors');
if (!container) return;
if (!this.data || !Array.isArray(this.data.keyFactors)) {
console.warn('Invalid or missing key factors data');
return;
}
const { keyFactors } = this.data;
container.textContent = '';
const wrapper = document.createElement('div');
wrapper.className = 'key-factors';
const heading = document.createElement('h3');
heading.textContent = 'Key Election Factors';
wrapper.appendChild(heading);
const list = document.createElement('ul');
keyFactors.forEach((factor: string) => {
const listItem = document.createElement('li');
listItem.textContent = String(factor);
list.appendChild(listItem);
});
wrapper.appendChild(list);
container.appendChild(wrapper);
}
/**
* Get election date formatted.
* @returns Formatted election date or empty string if invalid.
*/
getFormattedElectionDate(): string {
if (!this.data || !this.data.electionDate) {
console.warn('Invalid or missing election date data');
return '';
}
const date = new Date(this.data.electionDate);
if (Number.isNaN(date.getTime())) {
console.warn('Election date is not a valid date:', this.data.electionDate);
return '';
}
try {
return date.toLocaleDateString('en-US', {
year: 'numeric',
month: 'long',
day: 'numeric',
});
} catch (error) {
console.warn('Failed to format election date', error);
return '';
}
}
/**
* Calculate and return summary statistics.
* @returns Summary statistics object.
*/
getSummaryStats(): SummaryStats {
if (!this.data || !this.data.forecast || !Array.isArray(this.data.forecast.parties)) {
console.warn('Invalid or missing election forecast data for summary stats');
return {
totalSeats: 0,
gainers: 0,
losers: 0,
stable: 0,
biggestGain: null,
biggestLoss: null,
};
}
const { parties } = this.data.forecast;
if (parties.length === 0) {
return {
totalSeats: 0,
gainers: 0,
losers: 0,
stable: 0,
biggestGain: null,
biggestLoss: null,
};
}
return {
totalSeats: parties.reduce((sum, p) => sum + p.predictedSeats, 0),
gainers: parties.filter(p => p.change > 0).length,
losers: parties.filter(p => p.change < 0).length,
stable: parties.filter(p => p.change === 0).length,
biggestGain: parties.reduce((max, p) => (p.change > max.change ? p : max), parties[0]),
biggestLoss: parties.reduce((min, p) => (p.change < min.change ? p : min), parties[0]),
};
}
}
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