/** * Série de odds Polymarket + divergência mercado × pesquisa da Colômbia 2026, a partir do RAW * já buscado (data/colombia-poly-raw.json) via função Vercel standalone (EUA resolve gamma-api/clob). * market-odds inclui TODOS os candidatos do mercado; a divergência casa com as pesquisas (canon). * * Saída: * data/colombia-market-odds-timeseries.csv (date, candidate, polymarket_pct, volume_usd) * data/colombia-divergence-timeseries.csv (poll_date, pollster, candidate, poll_pct, polymarket_pct, polymarket_date, divergence_pp) */ import { readFileSync, writeFileSync, mkdirSync } from 'fs' import { join } from 'path' const ROOT = process.cwd() const OUT = join(ROOT, 'data'); mkdirSync(OUT, { recursive: true }) const csv = (rows) => rows.map((r) => r.map((v) => { const s = String(v ?? ''); return /[",\n]/.test(s) ? `"${s.replace(/"/g, '""')}"` : s }).join(',')).join('\n') + '\n' const num = (s) => { const m = String(s).replace(/,/g, '').match(/-?\d+(?:\.\d+)?/); return m ? parseFloat(m[0]) : null } const isoOf = (t) => new Date(t * 1000).toISOString().slice(0, 10) const cleanName = (s) => String(s || '').replace(/\s*\([^)]*\)\s*$/, '').trim() // tira sufixo " (IND)" // canon p/ casar mercado × pesquisa (nome completo da pesquisa) const CANON = [['cepeda', 'Iván Cepeda'], ['espriella', 'Abelardo de la Espriella'], ['fajardo', 'Sergio Fajardo'], ['valencia', 'Paloma Valencia'], ['dávila', 'Vicky Dávila'], ['davila', 'Vicky Dávila'], ['quintero', 'Daniel Quintero'], ['vargas lleras', 'Germán Vargas Lleras'], ['galán', 'Juan Manuel Galán'], ['galan', 'Juan Manuel Galán'], ['pizarro', 'María José Pizarro'], ['pinzón', 'Juan Carlos Pinzón'], ['pinzon', 'Juan Carlos Pinzón'], ['barreras', 'Roy Barreras']] const canon = (s) => { const t = String(s || '').toLowerCase(); for (const [k, v] of CANON) if (t.includes(k)) return v; return null } // 1) odds diárias — TODOS os candidatos do mercado const raw = JSON.parse(readFileSync(join(OUT, 'colombia-poly-raw.json'), 'utf-8')) const odds = [] for (const m of raw.odds || []) { const name = cleanName(m.candidate) // descarta placeholders do mercado (Other/Person X/Candidate Y) explicitamente — não depender de history vazio if (!name || /^(Other|Person|Candidate)\b/i.test(name) || !Array.isArray(m.history) || !m.history.length) continue const byDay = new Map() for (const pt of m.history) byDay.set(isoOf(pt.t), pt.p) for (const [date, p] of byDay) odds.push({ date, candidate: name, pct: Math.round(p * 1000) / 10, volume: Math.round(m.volume || 0) }) } odds.sort((a, b) => a.date === b.date ? b.pct - a.pct : a.date.localeCompare(b.date)) writeFileSync(join(OUT, 'colombia-market-odds-timeseries.csv'), csv([['date', 'candidate', 'polymarket_pct', 'volume_usd'], ...odds.map((o) => [o.date, o.candidate, o.pct, o.volume])])) console.log(`📈 market-odds: ${odds.length} linhas, ${new Set(odds.map((o) => o.date)).size} datas, ${new Set(odds.map((o) => o.candidate)).size} candidatos (${raw.startDate?.slice(0, 10)}→${raw.endDate?.slice(0, 10)})`) // 2) divergência: pesquisa de 1º turno × odd do candidato na data (canon, nearest on-or-before) const idx = {} for (const o of odds) { const k = canon(o.candidate); if (k) (idx[k] ||= []).push({ date: o.date, pct: o.pct }) } for (const k in idx) idx[k].sort((a, b) => a.date.localeCompare(b.date)) const mAt = (k, d) => { const a = idx[k]; if (!a) return null; let best = null; for (const e of a) { if (e.date <= d) best = e; else break } return best } const lines = readFileSync(join(ROOT, 'polls', 'colombia-first-round-polls.csv'), 'utf-8').trim().split('\n').slice(1) const dv = [['poll_date', 'pollster', 'candidate', 'poll_pct', 'polymarket_pct', 'polymarket_date', 'divergence_pp']] let matched = 0 for (const ln of lines) { const c = ln.split(','); const poll_date = c[0], pollster = c[2], candidate = c[4], poll = num(c[6]) const k = canon(candidate); if (!k || poll == null) continue const m = mAt(k, poll_date); if (!m) continue dv.push([poll_date, pollster, k, poll, m.pct, m.date, Math.round((m.pct - poll) * 100) / 100]); matched++ } writeFileSync(join(OUT, 'colombia-divergence-timeseries.csv'), csv(dv)) console.log(`📊 divergence: ${matched} linhas (pesquisa 1T × mercado)`)