smart-fin-chart/scripts/normalize_ppmt_financials.mjs

import fs from 'node:fs';
import path from 'node:path';
import { fileURLToPath } from 'node:url';

const ROOT = path.resolve(path.dirname(fileURLToPath(import.meta.url)), '..');
const RAW_DIR = path.join(ROOT, 'data/ppmt/raw');
const OUTPUT_DIR = path.join(ROOT, 'data/ppmt');

const FILES = {
  cashflow: '泡泡玛特_现金流量表_合并报表_20260828_134646.csv',
  income: '泡泡玛特_利润表_合并报表_20260828_134510.csv',
  balance: '泡泡玛特_资产负债表_合并报表_20260828_134503.csv',
  indicators: '泡泡玛特_财务指标_合并报表_20260828_134712.csv',
  revenueComposition: '泡泡玛特_营收构成_20260828_134749.csv',
};

function clean(cell = '') {
  return cell.trim().replace(/^\uFEFF/, '').replace(/^="(.*)"$/, '$1');
}

function toNumber(cell) {
  const value = clean(cell).replace(/^=/, '');
  if (!value) return null;
  if (value.endsWith('%')) {
    const percentage = Number(value.slice(0, -1));
    return Number.isFinite(percentage) ? percentage / 100 : null;
  }
  const number = Number(value);
  return Number.isFinite(number) ? number : null;
}

function readStatement(filename) {
  const lines = fs.readFileSync(path.join(RAW_DIR, filename), 'utf8')
    .trim()
    .split(/\r?\n/)
    .map((line) => line.split(','));
  const dates = lines[1].slice(3).map(clean);
  const values = new Map(lines.slice(2).map((cells) => [clean(cells[0]), cells.slice(3)]));
  return { dates, values };
}

function row(statement, name) {
  const values = statement.values.get(name);
  if (!values) throw new Error(`原始报表缺少行：${name}`);
  return values.map(toNumber);
}

function periodFor(date) {
  const [year, month] = date.split('-');
  if (month === '06') return `${year}H1`;
  if (month === '12') return `${year}FY`;
  throw new Error(`不支持的报表日期：${date}`);
}

function periodForRevenue(date) {
  const [year, quarter] = date.split('-Q');
  if (quarter === '2') return `${year}H1`;
  if (quarter === '4') return `${year}FY`;
  throw new Error(`不支持的营收构成期间：${date}`);
}

function readRevenueComposition(filename) {
  const lines = fs.readFileSync(path.join(RAW_DIR, filename), 'utf8')
    .trim()
    .split(/\r?\n/)
    .map((line) => line.split(','));
  const dates = lines[0].slice(2).map(clean);
  const channels = new Map();
  let section = '';
  let isTotal = false;

  lines.slice(1).forEach((cells) => {
    const first = clean(cells[0]);
    const second = clean(cells[1]);
    if (first.startsWith('按服務類型分-')) {
      section = first.replace('按服務類型分-', '');
      isTotal = false;
      return;
    }
    if (first === '合計') {
      section = '合計';
      isTotal = true;
      return;
    }
    if (second !== '收入' && second !== '收入同比') return;
    const values = cells.slice(2).map(toNumber);
    if (isTotal) channels.set(second === '收入' ? 'totalRevenue' : 'revenueYoy', values);
    else if (section) channels.set(`${section}:${second}`, values);
  });
  return { dates, channels };
}

function writeCSV(filename, headers, rows) {
  const text = [headers.join(','), ...rows.map((values) => values.join(','))].join('\n').concat('\n');
  fs.writeFileSync(path.join(OUTPUT_DIR, filename), text);
}

const cashflow = readStatement(FILES.cashflow);
const income = readStatement(FILES.income);
const balance = readStatement(FILES.balance);
const indicators = readStatement(FILES.indicators);
const revenueComposition = readRevenueComposition(FILES.revenueComposition);

const operatingCashFlow = row(cashflow, '经营活动产生的现金流量净额');
const netProfit = row(income, '三、净利润');

const cashConversionRows = cashflow.dates.map((date, index) => ({
  date,
  operatingCashFlow: operatingCashFlow[index],
  netProfit: netProfit[index],
})).filter(({ date, operatingCashFlow: cfo, netProfit: profit }) => (
  date >= '2020-01-01' && date.endsWith('-12-31') && cfo !== null && profit !== null
)).map(({ date, operatingCashFlow: cfo, netProfit: profit }) => [
  periodFor(date),
  (cfo / 100000000).toFixed(2),
  (profit / 100000000).toFixed(2),
  (cfo / profit * 100).toFixed(1),
]).reverse();

writeCSV('ppmt_cash_conversion.csv', [
  'period', 'operating_cash_flow', 'net_profit', 'cash_conversion',
], cashConversionRows);

const cash = row(balance, '货币资金');
const liabilities = row(balance, '二、负债合计');
const currentAssets = row(balance, '流动资产合计');
const currentLiabilities = row(balance, '流动负债合计');

const liquidityRows = balance.dates.map((date, index) => ({
  date,
  cash: cash[index],
  liabilities: liabilities[index],
  currentAssets: currentAssets[index],
  currentLiabilities: currentLiabilities[index],
})).filter((item) => (
  item.date >= '2020-01-01'
  && item.cash !== null
  && item.liabilities !== null
  && item.currentAssets !== null
  && item.currentLiabilities !== null
)).map((item) => [
  periodFor(item.date),
  (item.cash / 100000000).toFixed(2),
  (item.liabilities / 100000000).toFixed(2),
  ((item.currentAssets - item.currentLiabilities) / 100000000).toFixed(2),
]).reverse();

writeCSV('ppmt_liquidity_working_capital.csv', [
  'period', 'cash', 'total_liabilities', 'net_working_capital',
], liquidityRows);

const investingCashFlow = row(cashflow, '投资活动产生的现金流量净额');
const financingCashFlow = row(cashflow, '筹资活动产生的现金流量净额');
const netCashIncrease = row(cashflow, '现金及现金等价物的净增加额');
const cashflowCompositionRows = cashflow.dates.map((date, index) => ({
  date,
  operating: operatingCashFlow[index],
  investing: investingCashFlow[index],
  financing: financingCashFlow[index],
  netIncrease: netCashIncrease[index],
})).filter((item) => (
  item.date >= '2020-01-01' && item.date.endsWith('-12-31')
  && Object.values(item).every((value) => value !== null)
)).map((item) => [
  periodFor(item.date),
  (item.operating / 100000000).toFixed(2),
  (item.investing / 100000000).toFixed(2),
  (item.financing / 100000000).toFixed(2),
  (item.netIncrease / 100000000).toFixed(2),
]).reverse();

writeCSV('ppmt_cashflow_composition.csv', [
  'period', 'operating_cash_flow', 'investing_cash_flow', 'financing_cash_flow', 'net_cash_increase',
], cashflowCompositionRows);

const inventoryDays = row(indicators, '存货周转天数');
const receivableDays = row(indicators, '应收票据和应收账款周转天数');
const payableDays = row(indicators, '应付票据和应付账款周转天数');
const workingCapitalDaysRows = indicators.dates.map((date, index) => ({
  date,
  inventory: inventoryDays[index],
  receivable: receivableDays[index],
  payable: payableDays[index],
})).filter((item) => (
  item.date >= '2020-01-01'
  && item.inventory !== null && item.receivable !== null && item.payable !== null
)).map((item) => {
  const period = periodFor(item.date);
  // 原始指标表按半年 180 天、全年 360 天计算；此处统一换算为自然日 181/365 天。
  const factor = period.endsWith('H1') ? 181 / 180 : 365 / 360;
  const inventory = item.inventory * factor;
  const receivable = item.receivable * factor;
  const payable = item.payable * factor;
  return [
    period,
    inventory.toFixed(1),
    receivable.toFixed(1),
    payable.toFixed(1),
    (inventory + receivable - payable).toFixed(1),
  ];
}).reverse();

writeCSV('ppmt_working_capital_days.csv', [
  'period', 'inventory_days', 'receivable_days', 'payable_days', 'cash_conversion_cycle',
], workingCapitalDaysRows);

const revenue = row(income, '一、营业总收入');
const salesExpense = row(income, '减：销售费用');
const adminExpense = row(income, '管理费用');
const financialExpense = row(income, '财务费用');
const fourExpenseRate = row(income, '四项费用率');
const expenseRows = income.dates.map((date, index) => ({
  date,
  revenue: revenue[index],
  sales: salesExpense[index],
  admin: adminExpense[index],
  financial: financialExpense[index],
  rate: fourExpenseRate[index],
})).filter((item) => (
  item.date >= '2020-01-01' && item.date.endsWith('-12-31')
  && Object.values(item).every((value) => value !== null)
)).map((item) => [
  periodFor(item.date),
  (item.sales / 100000000).toFixed(2),
  (item.admin / 100000000).toFixed(2),
  (item.financial / 100000000).toFixed(2),
  (item.rate * 100).toFixed(1),
]).reverse();

writeCSV('ppmt_expense_structure.csv', [
  'period', 'sales_expense', 'admin_expense', 'financial_expense', 'four_expense_rate',
], expenseRows);

const channelKeys = [
  ['零售店銷售收益', 'retail'],
  ['線上銷售收益', 'online'],
  ['機器人商店銷售收益', 'robot_store'],
  ['批發收益', 'wholesale'],
];
const channelRows = revenueComposition.dates.map((date, index) => {
  const values = Object.fromEntries(channelKeys.map(([name, key]) => [
    key,
    revenueComposition.channels.get(`${name}:收入`)?.[index] ?? null,
  ]));
  return {
    date,
    ...values,
    totalRevenue: revenueComposition.channels.get('totalRevenue')?.[index] ?? null,
    revenueYoy: revenueComposition.channels.get('revenueYoy')?.[index] ?? null,
  };
}).filter((item) => (
  item.date >= '2020-Q2'
  && Object.values(item).every((value) => value !== null)
)).map((item) => [
  periodForRevenue(item.date),
  (item.retail / 100000000).toFixed(2),
  (item.online / 100000000).toFixed(2),
  (item.robot_store / 100000000).toFixed(2),
  (item.wholesale / 100000000).toFixed(2),
  (item.totalRevenue / 100000000).toFixed(2),
  (item.revenueYoy * 100).toFixed(1),
]).reverse();

writeCSV('ppmt_channel_revenue.csv', [
  'period', 'retail', 'online', 'robot_store', 'wholesale', 'total_revenue', 'revenue_yoy',
], channelRows);

console.log(`已生成现金转换 ${cashConversionRows.length}、流动性 ${liquidityRows.length}、现金流 ${cashflowCompositionRows.length}、营运资本 ${workingCapitalDaysRows.length}、费用 ${expenseRows.length}、渠道 ${channelRows.length} 行数据。`);

// 多维度图表：FY 为全年，H1/H2 为独立半年。所有拆分和同比均在数据层完成。
const VIEW_YEARS = Array.from({ length: 8 }, (_, index) => 2019 + index);
const OUTPUT_START_YEAR = 2020;
const HUNDRED_MILLION = 100000000;

function isComplete(values) {
  return values && Object.values(values).every((value) => Number.isFinite(value));
}

function subtractPeriod(fullYear, firstHalf) {
  if (!isComplete(fullYear) || !isComplete(firstHalf)) return null;
  return Object.fromEntries(Object.keys(fullYear).map((key) => [key, fullYear[key] - firstHalf[key]]));
}

function buildViews(readPeriod) {
  const views = { all: [], annual: [], halfyear: [] };
  VIEW_YEARS.forEach((year) => {
    const h1 = readPeriod(year, 'H1');
    const fy = readPeriod(year, 'FY');
    const h2 = subtractPeriod(fy, h1);
    if (h1) {
      const row = { period: `${year}H1`, ...h1 };
      views.halfyear.push(row);
      views.all.push(row);
    }
    if (h2) {
      const row = { period: `${year}H2`, ...h2 };
      views.halfyear.push(row);
      views.all.push(row);
    }
    if (fy) {
      const row = { period: `${year}FY`, ...fy };
      views.annual.push(row);
      views.all.push(row);
    }
  });
  return views;
}

function addPeriods(firstHalf, secondHalf) {
  if (!isComplete(firstHalf) || !isComplete(secondHalf)) return null;
  return Object.fromEntries(Object.keys(firstHalf).map((key) => [key, firstHalf[key] + secondHalf[key]]));
}

// IP、品类等运营数据的 H2 已是单独半年，年度值应由 H1 + H2 汇总。
function buildViewsFromHalfYears(readPeriod) {
  const views = { all: [], annual: [], halfyear: [] };
  VIEW_YEARS.forEach((year) => {
    const h1 = readPeriod(year, 'H1');
    const h2 = readPeriod(year, 'H2');
    const fy = addPeriods(h1, h2);
    if (h1) {
      const row = { period: `${year}H1`, ...h1 };
      views.halfyear.push(row);
      views.all.push(row);
    }
    if (h2) {
      const row = { period: `${year}H2`, ...h2 };
      views.halfyear.push(row);
      views.all.push(row);
    }
    if (fy) {
      const row = { period: `${year}FY`, ...fy };
      views.annual.push(row);
      views.all.push(row);
    }
  });
  return views;
}

function yoyFor(rows, key, outputKey = key) {
  const byPeriod = new Map(rows.map((row) => [row.period, row]));
  return rows.map((row) => {
    const year = Number(row.period.slice(0, 4));
    const prior = byPeriod.get(`${year - 1}${row.period.slice(4)}`);
    return {
      ...row,
      [outputKey]: prior && prior[key] !== 0 ? (row[key] / prior[key] - 1) * 100 : null,
    };
  });
}

function toOutputRows(rows, headers, digits = {}, startYear = OUTPUT_START_YEAR) {
  return rows
    .filter((row) => Number(row.period.slice(0, 4)) >= startYear)
    .map((row) => headers.map((header) => {
      if (header === 'period') return row.period;
      const value = row[header];
      return Number.isFinite(value) ? value.toFixed(digits[header] ?? 2) : '';
    }));
}

function writeViewFiles(base, headers, views, digits, startYear = OUTPUT_START_YEAR) {
  const filenames = {
    all: `${base}.csv`,
    annual: `${base}_annual.csv`,
    halfyear: `${base}_halfyear.csv`,
  };
  Object.entries(filenames).forEach(([view, filename]) => {
    writeCSV(filename, headers, toOutputRows(views[view], headers, digits, startYear));
  });
}

const incomeDateIndex = new Map(income.dates.map((date, index) => [date, index]));
const incomeColumns = {
  revenue: row(income, '一、营业总收入'),
  cost: row(income, '营业成本'),
  sales_expense: row(income, '减：销售费用'),
  admin_expense: row(income, '管理费用'),
  net_profit: row(income, '三、净利润'),
  non_gaap_net_profit: row(income, '非国际公认会计准则净利润'),
};

function incomePeriod(year, type) {
  const date = `${year}-${type === 'H1' ? '06-30' : '12-31'}`;
  const index = incomeDateIndex.get(date);
  if (index === undefined) return null;
  const result = Object.fromEntries(Object.entries(incomeColumns).map(([key, values]) => [key, values[index]]));
  // 2020 年非 GAAP 净利未披露，沿用现有图表的归母净利替代口径。
  result.non_gaap_net_profit ??= result.net_profit;
  return isComplete(result) ? result : null;
}

const cashflowDateIndex = new Map(cashflow.dates.map((date, index) => [date, index]));
const cashflowColumns = {
  operating_cash_flow: row(cashflow, '经营活动产生的现金流量净额'),
  investing_cash_flow: row(cashflow, '投资活动产生的现金流量净额'),
  financing_cash_flow: row(cashflow, '筹资活动产生的现金流量净额'),
  net_cash_increase: row(cashflow, '现金及现金等价物的净增加额'),
};

function cashflowPeriod(year, type) {
  const date = `${year}-${type === 'H1' ? '06-30' : '12-31'}`;
  const index = cashflowDateIndex.get(date);
  if (index === undefined) return null;
  const result = Object.fromEntries(Object.entries(cashflowColumns).map(([key, values]) => [key, values[index]]));
  return isComplete(result) ? result : null;
}

function inBillion(values) {
  return Object.fromEntries(Object.entries(values).map(([key, value]) => [key, value / HUNDRED_MILLION]));
}

const growthViews = buildViews((year, type) => {
  const values = incomePeriod(year, type);
  return values && {
    non_gaap_net_profit: values.non_gaap_net_profit,
    gross_profit: values.revenue - values.cost,
    revenue: values.revenue,
    cost: values.cost,
  };
});
Object.keys(growthViews).forEach((view) => {
  ['non_gaap_net_profit', 'gross_profit', 'revenue', 'cost'].forEach((key) => {
    growthViews[view] = yoyFor(growthViews[view], key);
  });
});
writeViewFiles('ppmt_growth', ['period', 'non_gaap_net_profit', 'gross_profit', 'revenue', 'cost'], growthViews, {
  non_gaap_net_profit: 1, gross_profit: 1, revenue: 1, cost: 1,
});

const coreProfitViews = buildViews((year, type) => {
  const values = incomePeriod(year, type);
  return values && { core_profit: (values.revenue - values.cost - values.sales_expense - values.admin_expense) / HUNDRED_MILLION };
});
Object.keys(coreProfitViews).forEach((view) => {
  coreProfitViews[view] = yoyFor(coreProfitViews[view], 'core_profit', 'yoy');
});
writeViewFiles('ppmt_core_profit', ['period', 'core_profit', 'yoy'], coreProfitViews, { core_profit: 2, yoy: 1 });

const marginAmountViews = buildViews((year, type) => {
  const values = incomePeriod(year, type);
  return values && {
    revenue: values.revenue,
    gross_profit: values.revenue - values.cost,
    sales_expense: values.sales_expense,
    admin_expense: values.admin_expense,
    non_gaap_net_profit: values.non_gaap_net_profit,
  };
});
const marginsViews = Object.fromEntries(Object.entries(marginAmountViews).map(([view, rows]) => [
  view,
  rows.map((values) => {
    if (values.revenue === 0) return values;
    return {
      period: values.period,
      gross_margin: values.gross_profit / values.revenue * 100,
      sales_expense_rate: values.sales_expense / values.revenue * 100,
      admin_expense_rate: values.admin_expense / values.revenue * 100,
      non_gaap_net_margin: values.non_gaap_net_profit / values.revenue * 100,
    };
  }),
]));
writeViewFiles('ppmt_margins', ['period', 'gross_margin', 'sales_expense_rate', 'admin_expense_rate', 'non_gaap_net_margin'], marginsViews, {
  gross_margin: 2, sales_expense_rate: 2, admin_expense_rate: 2, non_gaap_net_margin: 2,
});

const cashConversionViews = buildViews((year, type) => {
  const flow = cashflowPeriod(year, type);
  const incomeValues = incomePeriod(year, type);
  if (!flow || !incomeValues) return null;
  return inBillion({
    operating_cash_flow: flow.operating_cash_flow,
    net_profit: incomeValues.net_profit,
  });
});
Object.values(cashConversionViews).forEach((rows) => rows.forEach((row) => {
  row.cash_conversion = row.net_profit === 0 ? null : row.operating_cash_flow / row.net_profit * 100;
}));
writeViewFiles('ppmt_cash_conversion', ['period', 'operating_cash_flow', 'net_profit', 'cash_conversion'], cashConversionViews, {
  operating_cash_flow: 2, net_profit: 2, cash_conversion: 1,
});

const cashflowCompositionViews = buildViews((year, type) => {
  const values = cashflowPeriod(year, type);
  return values && inBillion(values);
});
writeViewFiles('ppmt_cashflow_composition', ['period', 'operating_cash_flow', 'investing_cash_flow', 'financing_cash_flow', 'net_cash_increase'], cashflowCompositionViews, {
  operating_cash_flow: 2, investing_cash_flow: 2, financing_cash_flow: 2, net_cash_increase: 2,
});

const channelKeysForViews = [
  ['零售店銷售收益', 'retail'],
  ['線上銷售收益', 'online'],
  ['機器人商店銷售收益', 'robot_store'],
  ['批發收益', 'wholesale'],
];
const revenueDateIndex = new Map(revenueComposition.dates.map((date, index) => [date, index]));
function channelPeriod(year, type) {
  const index = revenueDateIndex.get(`${year}-Q${type === 'H1' ? 2 : 4}`);
  if (index === undefined) return null;
  const values = Object.fromEntries(channelKeysForViews.map(([name, key]) => [
    key, revenueComposition.channels.get(`${name}:收入`)?.[index] ?? null,
  ]));
  const total = revenueComposition.channels.get('totalRevenue')?.[index] ?? null;
  return isComplete({ ...values, total }) ? inBillion({ ...values, total_revenue: total }) : null;
}

const channelRevenueViews = buildViews(channelPeriod);
Object.keys(channelRevenueViews).forEach((view) => {
  channelRevenueViews[view] = yoyFor(channelRevenueViews[view], 'total_revenue', 'revenue_yoy');
});
writeViewFiles('ppmt_channel_revenue', ['period', 'retail', 'online', 'robot_store', 'wholesale', 'total_revenue', 'revenue_yoy'], channelRevenueViews, {
  retail: 2, online: 2, robot_store: 2, wholesale: 2, total_revenue: 2, revenue_yoy: 1,
});

console.log('已生成首批六图的全部、年度、半年 CSV。');

const profitViews = buildViews((year, type) => {
  const values = incomePeriod(year, type);
  return values && inBillion({
    revenue: values.revenue,
    gross_profit: values.revenue - values.cost,
    net_profit: values.net_profit,
  });
});
Object.values(profitViews).forEach((rows) => rows.forEach((item) => {
  item.gross_margin = item.revenue === 0 ? null : item.gross_profit / item.revenue * 100;
}));
writeViewFiles('ppmt_profit', ['period', 'revenue', 'gross_profit', 'gross_margin', 'net_profit'], profitViews, {
  revenue: 2, gross_profit: 2, gross_margin: 2, net_profit: 2,
});

const coreMarginViews = buildViews((year, type) => {
  const values = incomePeriod(year, type);
  return values && {
    revenue: values.revenue,
    core_profit: values.revenue - values.cost - values.sales_expense - values.admin_expense,
  };
});
Object.values(coreMarginViews).forEach((rows) => rows.forEach((item) => {
  item.core_margin = item.revenue === 0 ? null : item.core_profit / item.revenue * 100;
}));
writeViewFiles('ppmt_core_margin', ['period', 'core_margin'], coreMarginViews, { core_margin: 1 });

const expenseAmountViews = buildViews((year, type) => {
  const values = incomePeriod(year, type);
  if (!values) return null;
  const financialExpense = row(income, '财务费用')[incomeDateIndex.get(`${year}-${type === 'H1' ? '06-30' : '12-31'}`)];
  return {
    revenue: values.revenue,
    sales_expense: values.sales_expense,
    admin_expense: values.admin_expense,
    financial_expense: financialExpense,
  };
});
const expenseViews = Object.fromEntries(Object.entries(expenseAmountViews).map(([view, rows]) => [
  view,
  rows.map((item) => ({
    ...inBillion(item),
    period: item.period,
    four_expense_rate: (item.sales_expense + item.admin_expense + item.financial_expense) / item.revenue * 100,
  })),
]));
writeViewFiles('ppmt_expense_structure', ['period', 'sales_expense', 'admin_expense', 'financial_expense', 'four_expense_rate'], expenseViews, {
  sales_expense: 2, admin_expense: 2, financial_expense: 2, four_expense_rate: 1,
});

function readRuntimeRows(filename) {
  const [header, ...lines] = fs.readFileSync(path.join(OUTPUT_DIR, filename), 'utf8').trim().split(/\r?\n/);
  const headers = header.split(',');
  return lines.map((line) => Object.fromEntries(line.split(',').map((cell, index) => {
    const value = Number(cell);
    return [headers[index], cell !== '' && Number.isFinite(value) ? value : cell];
  })));
}

function writeRuntimeViews(base, headers, views, digits = {}) {
  writeViewFiles(base, headers, views, digits);
}

function buildWideIpViews(filename) {
  const rows = readRuntimeRows(filename);
  const id = Object.keys(rows[0])[0];
  const sourcePeriods = Object.keys(rows[0]).slice(1).filter((period) => /H[12]$/.test(period));
  const years = [...new Set(sourcePeriods.map((period) => period.slice(0, 4)))];
  const halfyear = sourcePeriods;
  const annual = years.filter((year) => sourcePeriods.includes(`${year}H1`) && sourcePeriods.includes(`${year}H2`)).map((year) => `${year}FY`);
  const all = years.flatMap((year) => [
    ...(sourcePeriods.includes(`${year}H1`) ? [`${year}H1`] : []),
    ...(sourcePeriods.includes(`${year}H2`) ? [`${year}H2`, `${year}FY`] : []),
  ]);
  const valuesFor = (periods) => rows.map((row) => [row[id], ...periods.map((period) => {
    if (!period.endsWith('FY')) return row[period];
    return row[`${period.slice(0, 4)}H1`] + row[`${period.slice(0, 4)}H2`];
  })]);
  writeCSV(filename, [id, ...all], valuesFor(all));
  writeCSV(filename.replace('.csv', '_annual.csv'), [id, ...annual], valuesFor(annual));
  writeCSV(filename.replace('.csv', '_halfyear.csv'), [id, ...halfyear], valuesFor(halfyear));
}

buildWideIpViews('ppmt_ip.csv');
buildWideIpViews('ppmt_ip_share_history.csv');

const ipExMonstersRows = readRuntimeRows('ppmt_ip_ex_monsters.csv');
function ipExMonstersPeriod(year, type) {
  const row = ipExMonstersRows.find((item) => item.period === `${year}${type}`);
  return row ? { revenue: row.revenue } : null;
}
const ipExMonstersViews = buildViewsFromHalfYears(ipExMonstersPeriod);
Object.keys(ipExMonstersViews).forEach((view) => {
  ipExMonstersViews[view] = yoyFor(ipExMonstersViews[view], 'revenue', 'yoy');
});
writeRuntimeViews('ppmt_ip_ex_monsters', ['period', 'revenue', 'yoy'], ipExMonstersViews, { revenue: 2, yoy: 1 });

const categoryRows = readRuntimeRows('ppmt_category.csv').filter((item) => item.period !== '品类');
function categoryPeriod(year, type) {
  const row = categoryRows.find((item) => item.period === `${year}${type}`);
  return row && { plush: row.plush, figure: row.figure, mega: row.mega, other: row.other };
}
const categoryViews = buildViewsFromHalfYears(categoryPeriod);
writeRuntimeViews('ppmt_category', ['period', 'plush', 'figure', 'mega', 'other'], categoryViews, {
  plush: 2, figure: 2, mega: 2, other: 2,
});

// 2024H1 起门店披露可将中国内地与港澳台合并，并按全球总数归一化为地区占比。
const retailStoreRows = readRuntimeRows('ppmt_stores_retail.csv');
const retailStoreShareViews = { all: [], annual: [], halfyear: [] };
retailStoreRows.filter((row) => (
  Number(row.period.slice(0, 4)) >= 2024
  && ['mainland', 'hkmtw', 'apac', 'americas', 'europe', 'global'].every((key) => Number.isFinite(row[key]))
)).forEach((row) => {
  const china = row.mainland + row.hkmtw;
  const other = row.global - china - row.apac - row.americas - row.europe;
  const shareRow = {
    period: row.period,
    global: row.global,
    china: china / row.global * 100,
    apac: row.apac / row.global * 100,
    americas: row.americas / row.global * 100,
    europe: row.europe / row.global * 100,
    other: other / row.global * 100,
  };
  retailStoreShareViews.all.push(shareRow);
  retailStoreShareViews[row.period.endsWith('FY') ? 'annual' : 'halfyear'].push(shareRow);
});
writeRuntimeViews('ppmt_stores_retail_share', ['period', 'global', 'china', 'apac', 'americas', 'europe', 'other'], retailStoreShareViews, {
  global: 0, china: 1, apac: 1, americas: 1, europe: 1, other: 1,
});

// 资产负债表为时点指标：H2 是年末时点，而非“全年累计”。
function buildSnapshotViews(base, headers, digits) {
  const source = readRuntimeRows(`${base}.csv`);
  const views = { all: [], annual: [], halfyear: [] };
  VIEW_YEARS.forEach((year) => {
    const h1 = source.find((row) => row.period === `${year}H1`);
    const yearEnd = source.find((row) => row.period === `${year}H2` || row.period === `${year}FY`);
    if (h1) {
      const row = { ...h1, period: `${year}H1` };
      views.all.push(row);
      views.halfyear.push(row);
    }
    if (yearEnd) {
      const halfyearRow = { ...yearEnd, period: `${year}H2` };
      views.all.push(halfyearRow);
      views.halfyear.push(halfyearRow);
      views.annual.push({ ...yearEnd, period: `${year}FY` });
    }
  });
  writeRuntimeViews(base, headers, views, digits);
}

buildSnapshotViews('ppmt_assets', ['period', 'total_assets', 'cash_like', 'receivables', 'investment', 'operating_assets'], {
  total_assets: 2, cash_like: 2, receivables: 2, investment: 2, operating_assets: 2,
});
buildSnapshotViews('ppmt_liquidity_working_capital', ['period', 'cash', 'total_liabilities', 'net_working_capital'], {
  cash: 2, total_liabilities: 2, net_working_capital: 2,
});

// 存货为资产负债表期末时点数：半年仅取中报期末，年度仅取年报期末。
// 同比严格按相同报告期（H1 对 H1、FY 对 FY）计算，不把中报与年报交叉比较。
const inventoryBalances = row(balance, '存货');
const inventoryViews = { all: [], annual: [], halfyear: [] };
balance.dates.map((date, index) => ({
  date,
  inventory: inventoryBalances[index],
})).filter(({ date, inventory }) => (
  date >= '2017-01-01' && inventory > 0 && (date.endsWith('-06-30') || date.endsWith('-12-31'))
)).sort((a, b) => a.date.localeCompare(b.date)).forEach(({ date, inventory }) => {
  const row = { period: periodFor(date), inventory: inventory / HUNDRED_MILLION };
  inventoryViews.all.push(row);
  inventoryViews[row.period.endsWith('FY') ? 'annual' : 'halfyear'].push(row);
});
Object.keys(inventoryViews).forEach((view) => {
  inventoryViews[view] = yoyFor(inventoryViews[view], 'inventory', 'yoy');
});
writeViewFiles('ppmt_inventory', ['period', 'inventory', 'yoy'], inventoryViews, {
  inventory: 2, yoy: 1,
}, 2017);

console.log('已生成第二批连续图表的全部、年度、半年 CSV。');