package com.trafficaudit.reportexport.calc;
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import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
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import com.trafficaudit.common.util.RegionUtil;
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import com.trafficaudit.dataimport.entity.PassengerEnterpriseMonthly;
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import com.trafficaudit.dataimport.entity.PassengerIndividualMonthly;
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import com.trafficaudit.dataimport.mapper.PassengerEnterpriseMonthlyMapper;
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import com.trafficaudit.dataimport.mapper.PassengerIndividualMonthlyMapper;
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import org.springframework.stereotype.Service;
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import javax.annotation.Resource;
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import java.util.HashMap;
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import java.util.LinkedHashMap;
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import java.util.List;
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import java.util.Map;
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/**
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* 公路班线（含个体）口径计算服务（汇总大表数据驱动改造 M1-班线包车，2026-09-08）。
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*
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* 口径（2026-07 与 _备份_2026年7月道路运输量汇总表_清理前_20260904.xlsx 班线包车页
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* 企业/个体行 1-7 月逐格回归 0 差异，350 格全中）：
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* 1. 班线包车页“客运量/旅客周转量”行 = h2031_enterprise_monthly 按 17 市州汇总
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* （passenger_total / turnover_total，人 / 人公里）除以 10000，再并入个体客运
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* （passenger_individual_monthly 同口径）；“其中个体客运量/周转量”行 = 个体数除以 10000
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* （当前仅黄石/襄阳/荆门/孝感/黄冈/随州有数）。
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* 2. 全省行 = 17 市州之和，与母版“全省行=城市行求和”公式一致；中口径分析页“公路班线”
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* = 本口径全省合计（当月 1631.2013、累计 11204.5406 与母版 0 差异）。
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* 3. 同比以母版缓存 2025 参照组为基准（Q1），不在本服务计算。
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*
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* 输出：月 → 市州（含 PROVINCE=湖北省） → double[4] =
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* [客运量(含个体), 周转量(含个体), 个体客运量, 个体周转量]，
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* 单位均为母版展示口径（万人 / 万人公里）；企业单独量 = arr[0]-arr[2] 与 arr[1]-arr[3]。
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*/
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@Service
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public class MidCalc {
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public static final String PROVINCE = "湖北省";
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@Resource
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private PassengerEnterpriseMonthlyMapper passengerMapper;
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@Resource
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private PassengerIndividualMonthlyMapper individualMapper;
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/** 班线包车页数值矩阵：月 → 市州/全省 → [客运量,周转量,个体客运量,个体周转量] */
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public Map<Integer, Map<String, double[]>> banxianMonthly(String yearPrefix, int limit) {
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Map<Integer, Map<String, double[]>> result = new LinkedHashMap<>();
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List<PassengerEnterpriseMonthly> entRows = passengerMapper.selectList(
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new LambdaQueryWrapper<PassengerEnterpriseMonthly>().likeRight(
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PassengerEnterpriseMonthly::getReportPeriod, yearPrefix));
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for (PassengerEnterpriseMonthly r : entRows) {
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int m = monthOf(r.getReportPeriod());
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if (m < 1 || m > limit) continue;
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String city = RegionUtil.cityByCode(r.getRegionCode());
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if (city == null) continue;
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double pax = nz(r.getPassengerTotal());
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double turn = nz(r.getTurnoverTotal());
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if (pax == 0.0 && turn == 0.0) {
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pax = nz(r.getPassengerClass1()) + nz(r.getPassengerClass2())
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+ nz(r.getPassengerClass3()) + nz(r.getPassengerClass4())
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+ nz(r.getPassengerCharter());
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turn = nz(r.getTurnoverClass1()) + nz(r.getTurnoverClass2())
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+ nz(r.getTurnoverClass3()) + nz(r.getTurnoverClass4())
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+ nz(r.getTurnoverCharter());
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}
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accumulate(result, m, city, pax / 10000.0, turn / 10000.0, 0.0, 0.0);
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}
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List<PassengerIndividualMonthly> indRows = individualMapper.selectList(
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new LambdaQueryWrapper<PassengerIndividualMonthly>().likeRight(
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PassengerIndividualMonthly::getReportPeriod, yearPrefix));
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for (PassengerIndividualMonthly r : indRows) {
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int m = monthOf(r.getReportPeriod());
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if (m < 1 || m > limit) continue;
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String city = RegionUtil.cityByCode(r.getRegionCode());
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if (city == null) continue;
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double pax = nz(r.getPassengerCount()) / 10000.0;
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double turn = nz(r.getTurnover()) / 10000.0;
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accumulate(result, m, city, pax, turn, pax, turn);
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}
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return result;
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}
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private void accumulate(Map<Integer, Map<String, double[]>> result, int m, String city,
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double paxAll, double turnAll, double paxIndi, double turnIndi) {
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Map<String, double[]> monthMap = result.computeIfAbsent(m, k -> new HashMap<>());
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add(monthMap.computeIfAbsent(city, k -> new double[4]), paxAll, turnAll, paxIndi, turnIndi);
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add(monthMap.computeIfAbsent(PROVINCE, k -> new double[4]), paxAll, turnAll, paxIndi, turnIndi);
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}
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private void add(double[] arr, double paxAll, double turnAll, double paxIndi, double turnIndi) {
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arr[0] += paxAll;
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arr[1] += turnAll;
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arr[2] += paxIndi;
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arr[3] += turnIndi;
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}
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private int monthOf(String reportPeriod) {
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if (reportPeriod == null) return 0;
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String[] parts = reportPeriod.split("-");
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if (parts.length < 2) return 0;
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try {
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return Integer.parseInt(parts[1]);
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} catch (NumberFormatException e) {
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return 0;
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}
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}
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private double nz(Double v) {
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return v == null ? 0.0 : v;
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}
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}
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