package com.ycl.calculate;
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import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
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import com.ycl.platform.domain.entity.CheckIndexCar;
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import com.ycl.platform.domain.entity.TMonitor;
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import com.ycl.platform.domain.result.HK.DataIntegrityMonitoringResult;
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import com.ycl.platform.domain.result.HK.VehicleDeviceSamplingResult;
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import com.ycl.platform.domain.vo.TMonitorVO;
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import com.ycl.platform.mapper.CheckIndexCarMapper;
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import com.ycl.platform.mapper.TMonitorMapper;
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import com.ycl.platform.service.ICheckIndexCarService;
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import com.ycl.platform.service.ITMonitorService;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Component;
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import org.springframework.util.CollectionUtils;
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import utils.DateUtils;
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import java.math.BigDecimal;
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import java.math.RoundingMode;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.function.Function;
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import java.util.stream.Collectors;
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/**
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* 计算车辆属性识别准确率、url可用性、大图可用性
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* 车辆数据抽检接口
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* 获取分省厅、区域的map<k,v> k为deptId或者Province_deptId
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* 更新或新增
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*/
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@Component
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public class CarDeviceSampleCalculation extends IndexCalculationServe implements CalculationStrategy<VehicleDeviceSamplingResult> {
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@Autowired
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private CheckIndexCarMapper checkIndexCarMapper;
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@Autowired
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private TMonitorMapper monitorMapper;
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@Autowired
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private ICheckIndexCarService checkIndexCarService;
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//区域车辆抽检指标
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private static class AreaStats {
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int totalSites = 0;
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int importantTotalSites = 0;
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//属性识别准确的点位数
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int accuracySites = 0;
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//属性识别准确的重点点位数
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int importantAccuracySites = 0;
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//url可访问的点位数
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int urlUsabilitySites = 0;
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//图片可用的点位数
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int picUsabilitySites = 0;
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}
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@Override
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public void calculate(List<VehicleDeviceSamplingResult> list) {
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if (CollectionUtils.isEmpty(list)) {
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return;
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}
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//返回以国标码为key的设备map
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Map<String, TMonitorVO> monitorMap = monitorMapper.selectListByIds(list.stream().map(VehicleDeviceSamplingResult::getExternalIndexCode).collect(Collectors.toList()))
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.stream().collect(Collectors.toMap(TMonitorVO::getSerialNumber, Function.identity()));
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//获取省厅国标码集合
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List<String> provinceIds = getProvince();
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//获取重点点位集合
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List<String> importantIds = getImportant();
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Map<String, AreaStats> areaStatsMap = new HashMap<>();
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for (VehicleDeviceSamplingResult result : list) {
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TMonitorVO monitor = monitorMap.get(result.getExternalIndexCode());
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if (monitor == null) continue;
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String deptId = monitor.getDeptId().toString();
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updateAreaStats(areaStatsMap, deptId, result, importantIds);
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// 处理省厅数据
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if (!CollectionUtils.isEmpty(provinceIds) && provinceIds.contains(monitor.getSerialNumber())) {
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String provinceKey = ApiConstants.Province + deptId;
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updateAreaStats(areaStatsMap, provinceKey, result, importantIds);
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}
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}
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// 查询是否index表已经存在今日数据
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List<CheckIndexCar> checkIndexCarList = checkIndexCarMapper.selectToday(DateUtils.getDate());
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List<CheckIndexCar> checkIndexCars = new ArrayList<>();
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areaStatsMap.forEach((deptId, stats) -> {
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if (stats.totalSites > 0) {
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CheckIndexCar checkIndexCar = createOrUpdateCheckIndexCar(deptId, stats, checkIndexCarList);
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if (checkIndexCar != null) {
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checkIndexCars.add(checkIndexCar);
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}
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}
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});
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checkIndexCarService.saveOrUpdateBatch(checkIndexCars);
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}
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/**
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* 累计抓拍数据准确设备数和设备总数，区分重点点位
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*/
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private void updateAreaStats(Map<String, AreaStats> areaStatsMap, String key, VehicleDeviceSamplingResult result, List<String> importantIds) {
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//返回对象的引用，如果不存在会放入新的key,value
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AreaStats stats = areaStatsMap.computeIfAbsent(key, k -> new AreaStats());
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VehicleDeviceSamplingResult.VehicleDifference vehDiff = result.getVehDiff();
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VehicleDeviceSamplingResult.BigUsefulness bigUseful = result.getBigUseful();
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stats.totalSites++;
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//90%及以上数据合格则此车辆卡口设备被视为抓拍数据准确
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if (vehDiff.getMajorConPercent() >= 0.9) {
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stats.accuracySites++;
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}
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//重点点位为六项属性
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if (importantIds.contains(key)) {
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stats.importantTotalSites++;
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if (vehDiff.getImportantConPercent() >= 0.9) {
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stats.importantAccuracySites++;
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}
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}
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//大图可用率大于90%视为合格
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if (bigUseful.getBigUsefulPercent() >= 0.9) {
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stats.picUsabilitySites++;
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}
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//图片访问正常量 = 抽检量-异常量
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BigDecimal picNormalCount = new BigDecimal(bigUseful.getSampleCount() - bigUseful.getBigPicExpCount());
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//图片抽检量
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BigDecimal sampleCount = new BigDecimal(bigUseful.getSampleCount());
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//图片访问率>=90% 视为合格
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if (picNormalCount.divide(sampleCount, 4, RoundingMode.HALF_UP).compareTo(new BigDecimal("0.9")) >= 0) {
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stats.urlUsabilitySites++;
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}
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}
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/**
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* 车辆信息采集正确率、url可用性、大图可用性
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*/
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private CheckIndexCar createOrUpdateCheckIndexCar(String key, AreaStats stats, List<CheckIndexCar> checkIndexCarList) {
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CheckIndexCar checkIndexCar = getCheckIndex(key, checkIndexCarList, CheckIndexCar.class);
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if (checkIndexCar == null) {
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return null;
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}
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//调用信息采集正确率计算方法
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Map<String, Object> accuracyParam = new HashMap<>();
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accuracyParam.put("totalSites", stats.totalSites);
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accuracyParam.put("importantTotalSites", stats.importantTotalSites);
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accuracyParam.put("accuracySites", stats.accuracySites);
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accuracyParam.put("importantAccuracySites", stats.importantAccuracySites);
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BigDecimal dataAccuracy = dataAccuracy(accuracyParam);
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checkIndexCar.setVehicleCaptureAccuracy(dataAccuracy);
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//调用url可用性计算方法
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Map<String, Object> urlParam = new HashMap<>();
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urlParam.put("totalSites", stats.totalSites);
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urlParam.put("urlQualifySites", stats.urlUsabilitySites);
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BigDecimal urlUsability = urlUsability(urlParam);
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checkIndexCar.setVehicleUrlAvailability(urlUsability);
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//调用大图可用性计算方法
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Map<String, Object> usabilityParam = new HashMap<>();
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urlParam.put("totalSites", stats.totalSites);
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urlParam.put("picUsabilitySites", stats.picUsabilitySites);
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BigDecimal picUsability = picUsability(usabilityParam);
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checkIndexCar.setVehiclePictureAvailability(picUsability);
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return checkIndexCar;
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}
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}
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