路段交通指标分析。 交通指标时间分布，交通指标排名，交通指标雷达图

zc-business/src/main/java/com/zc/business/controller/DcTrafficStatisticsController.java

@@ -175,6 +175,49 @@ public AjaxResult realTimeTrafficFlow(String startDate, String direction,String
     // 将查询结果封装为成功响应并返回
     return AjaxResult.success(mapList);
 }
+    /**
+     * 车流量时段分析
+     * @param startDate 时间
+     * @param direction 方向
+     * @param periodType 时间粒子
+     */
+    @ApiOperation("车流量时段分析")
+    @GetMapping("/history/trafficPeriodAnalysis")
+    public AjaxResult trafficPeriodAnalysis(String startDate, String direction,String periodType ){
+        List<Map<String,String>> mapList = dcGantryStatisticsDataService.trafficPeriodAnalysis(startDate,direction,periodType);
+        // 将查询结果封装为成功响应并返回
+        return AjaxResult.success(mapList);
+    }
+    /**
+     * sectionTrafficIndexAnalysis
+     * @param startDate 时间
+     * @param direction 方向
+     * @param periodType 时间粒子
+     * @param ranking 排名 1 饱和度 2拥挤度 3交通特征指数
+     *
+     */
+    @ApiOperation("路段交通指标分析")
+    @GetMapping("/history/sectionTrafficIndexAnalysis")
+    public AjaxResult sectionTrafficIndexAnalysis(String startDate, String direction,String periodType,int ranking ){
+       List<Map<String, Object>>  mapList = dcGantryMetricsStatisticsDataService.sectionTrafficIndexAnalysis(startDate,direction,periodType,ranking);
+        // 将查询结果封装为成功响应并返回
+        return AjaxResult.success(mapList);
+    }
+    @ApiOperation("通指标时间分布")
+    @GetMapping("/history/passIndicatorTimeDistribution")
+    public AjaxResult passIndicatorTimeDistribution(String startDate, String direction,String periodType ){
+       List<Map<String, Object>>  mapList = dcGantryMetricsStatisticsDataService.passIndicatorTimeDistribution(startDate,direction,periodType);
+        // 将查询结果封装为成功响应并返回
+        return AjaxResult.success(mapList);
+    }
+    @ApiOperation("交通指标雷达图")
+    @GetMapping("/history/radarMapOfTrafficIndicators")
+    public AjaxResult radarMapOfTrafficIndicators(String startDate, String direction,String periodType ){
+      Map<String, Object>  map = dcGantryMetricsStatisticsDataService.radarMapOfTrafficIndicators(startDate,direction,periodType);
+        // 将查询结果封装为成功响应并返回
+        return AjaxResult.success(map);
+    }
+
 
 
     /**

zc-business/src/main/java/com/zc/business/domain/DcEvent.java

@@ -58,7 +58,7 @@ public class DcEvent {
      * 2-中
      * 3-下
      */
-    @Excel(name = "方向", readConverterExp = "1=菏泽方向,3=济南方向")
+    @Excel(name = "方向")
     //@Excel(name = "方向")
     @ApiModelProperty("方向")
     private String direction;
@@ -69,6 +69,7 @@ public class DcEvent {
 
     @ApiModelProperty("处理人员")
     private Long userId;
+    @Excel(name = "事件子类")
     @ApiModelProperty("事件子类")
     private String eventSubclassName;
 
@@ -136,7 +137,7 @@ public class DcEvent {
      * 3-3 立交封闭和限行
      * 3-4 服务区封闭和限行
      */
-    @Excel(name = "事件类型字符串")
+
     @ApiModelProperty("事件子类 例：事件子类：* 1-1 追尾* 1-2 侧翻* 1-3 撞护栏* 1-4 自然* 1-5 其他事故* 2-1 车辆故障")
 
     private String eventSubclass;

zc-business/src/main/java/com/zc/business/mapper/DcGantryMetricsStatisticsDataMapper.java

@@ -3,8 +3,10 @@ package com.zc.business.mapper;
 import com.baomidou.mybatisplus.core.mapper.BaseMapper;
 import com.zc.business.domain.DcGantryMetricsStatisticsData;
 import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
 
 import java.util.List;
+import java.util.Map;
 
 /**
  * 门架指标数据统计Mapper接口
@@ -29,4 +31,7 @@ public interface DcGantryMetricsStatisticsDataMapper extends BaseMapper<DcGantry
      * @return 影响的记录数（通常对于批量操作，这个值可能不准确，因为每个 INSERT/UPDATE 可能影响不同的记录数）
      */
     int insertOrUpdateBatch(List<DcGantryMetricsStatisticsData> gantryTrafficMetricsDataList);
+
+    List<Map<String, Object>> sectionTrafficIndexAnalysis(@Param("startDate") String startDate, @Param("direction") String direction,@Param("periodType")  String periodType);
+
 }

zc-business/src/main/java/com/zc/business/mapper/DcGantryStatisticsDataMapper.java

@@ -45,5 +45,7 @@ public interface DcGantryStatisticsDataMapper extends BaseMapper<DcGantryStatist
      * 全路段双向实时车流量
      */
     List<Map<String, String>> realTimeTrafficFlow(@Param("startDate") String startDate, @Param("direction")String direction, @Param("periodType")String periodType );
+
+    List<Map<String, Object>> trafficPeriodAnalysis(@Param("startDate") String startDate, @Param("direction")String direction, @Param("periodType")String periodType);
 }
 

zc-business/src/main/java/com/zc/business/service/IDcGantryMetricsStatisticsDataService.java

@@ -6,6 +6,7 @@ import com.zc.business.domain.DcGantryMetricsStatisticsData;
 import com.zc.business.domain.DcGantryMetricsStatisticsData;
 
 import java.util.List;
+import java.util.Map;
 
 /**
  * 门架指标统计服务接口，提供处理交通数据的相关方法
@@ -39,4 +40,10 @@ public interface IDcGantryMetricsStatisticsDataService extends IService<DcGantry
      * @return 门架指标统计数据列表
      */
     List<DcGantryMetricsStatisticsData> gantryMetricsData(DcGantryMetricsStatisticsData request);
+
+    List<Map<String, Object>>  sectionTrafficIndexAnalysis(String startDate, String direction, String periodType,int ranking);
+
+    List<Map<String, Object>> passIndicatorTimeDistribution(String startDate, String direction, String periodType);
+
+    Map<String, Object> radarMapOfTrafficIndicators(String startDate, String direction, String periodType);
 }

zc-business/src/main/java/com/zc/business/service/IDcGantryStatisticsDataService.java

@@ -47,5 +47,11 @@ public interface IDcGantryStatisticsDataService extends IService<DcGantryStatist
      * 全路段双向实时车流量
      */
     List<Map<String, String>> realTimeTrafficFlow(String startDate, String direction,String periodType );
+    /**
+     * 车流量时段分析
+     */
+    List<Map<String, String>> trafficPeriodAnalysis(String startDate, String direction, String periodType);
+
+
 
 }

zc-business/src/main/java/com/zc/business/service/impl/DcEventServiceImpl.java

@@ -229,9 +229,7 @@ public class DcEventServiceImpl extends ServiceImpl<DcEventMapper, DcEvent> impl
                         dcEvent.getDcEventAccident().setId(uuid);
 
                         int i1 = dcEventAccidentMapper.insertDcEventAccident(dcEvent.getDcEventAccident());
-                        if (dcEvent.getEventState() ==1){
-                            updateDcEventState(uuid,1);//直接确认
-                        }
+
                     }
                     break;
                 //车辆事故
@@ -239,9 +237,6 @@ public class DcEventServiceImpl extends ServiceImpl<DcEventMapper, DcEvent> impl
                     if (dcEvent.getDcEventVehicleAccident() != null) {
                         dcEvent.getDcEventVehicleAccident().setId(uuid);
                         int i5 = dcEventVehicleAccidentMapper.insertDcEventVehicleAccident(dcEvent.getDcEventVehicleAccident());
-                        if (dcEvent.getEventState() ==1){
-                            updateDcEventState(uuid,1);//直接确认
-                        }
                     }
                     break;
                 //交通管制
@@ -1224,10 +1219,10 @@ public class DcEventServiceImpl extends ServiceImpl<DcEventMapper, DcEvent> impl
             return 1;
         }
 
-        //事件状态已被修改 返回成功
+/*        //事件状态已被修改 返回成功
         if (dcEvent1.getEventState() == 1) {
             return 1;
-        }
+        }*/
 
 
         int i = dcEventMapper.updateDcEventState(id, state);

zc-business/src/main/java/com/zc/business/service/impl/DcGantryStatisticsDataImpl.java

@@ -21,9 +21,9 @@ import org.springframework.stereotype.Service;
 
 import javax.annotation.PostConstruct;
 import javax.annotation.Resource;
-import java.util.Date;
-import java.util.List;
-import java.util.Map;
+import java.time.LocalDateTime;
+import java.util.*;
+import java.util.stream.Collectors;
 
 /**
  * 门架数据统计服务实现类
@@ -206,4 +206,40 @@ public class DcGantryStatisticsDataImpl extends ServiceImpl<DcGantryStatisticsDa
     public List<Map<String, String>> realTimeTrafficFlow(String startDate, String direction, String periodType ) {
         return dcGantryStatisticsDataMapper.realTimeTrafficFlow(startDate,direction,periodType);
     }
+    /**
+     * 车流量时段分析
+     */
+    @Override
+    public List<Map<String, String>> trafficPeriodAnalysis(String startDate, String direction, String periodType) {
+
+        List<Map<String, Object>> mapList = dcGantryStatisticsDataMapper.trafficPeriodAnalysis(startDate, direction, periodType);
+        List<Map<String, String>> aggregatedList = aggregateTrafficVolume(mapList);
+        return aggregatedList;
+    }
+
+    public List<Map<String, String>> aggregateTrafficVolume(List<Map<String, Object>> dataList) {
+        // 创建一个Map，用于存储整点时间的流量数据
+        Map<Integer, Integer> aggregatedData = new HashMap<>();
+
+        // 遍历接口返回的数据列表
+        for (Map<String, Object> data : dataList) {
+            LocalDateTime statisticalDate = (LocalDateTime) data.get("statisticalDate");
+            int hour = statisticalDate.getHour();
+            // 获取该整点时间的流量数据并累加
+            int trafficVolume = (int) data.get("trafficVolume");
+            aggregatedData.put(hour,
+                    aggregatedData.getOrDefault(hour, 0) + trafficVolume);
+        }
+
+        // 将整点时间的流量数据重新构建为列表
+        List<Map<String, String>> aggregatedList = new ArrayList<>();
+        for (Map.Entry<Integer, Integer> entry : aggregatedData.entrySet()) {
+            Map<String, String> aggregatedItem = new HashMap<>();
+            aggregatedItem.put("statisticalHour", String.valueOf(entry.getKey())); // 整点时间
+            aggregatedItem.put("trafficVolume", String.valueOf(entry.getValue())); // 流量数据
+            aggregatedList.add(aggregatedItem);
+        }
+
+        return aggregatedList;
+    }
 }

zc-business/src/main/java/com/zc/business/service/impl/DcTrafficStatisticsServiceImpl.java

@@ -778,14 +778,28 @@ public class DcTrafficStatisticsServiceImpl implements IDcTrafficStatisticsServi
         return null;
     }
 
-    /**
-     *
-     * @param startDate
-     * @param direction
-     * @return
-     * @throws HttpException
-     * @throws IOException
-     */
+
+    private static String extract(String input) {
+        Pattern pattern = Pattern.compile("K(\\d{3})\\+(\\d{3})");
+        Matcher matcher = pattern.matcher(input);
+
+        if (matcher.find()) {
+            String part1 = matcher.group(1);
+            String part2 = matcher.group(2);
+            // 直接拼接两部分数字，无需格式化，这样得到的字符串自然没有前导零
+            return part1 + part2;
+        } else {
+            return "N/A";
+        }
+    }
+    public static String getDescriptionByIdentification(int identification) {
+        for (StakeMarkRange range : StakeMarkRange.values()) {
+            if (range.getIdentification() == identification) {
+                return range.getDescription();
+            }
+        }
+        return "";
+    }
     public List<Map<String, Object>> realTimeTrafficFlowHour2(String startDate,Long direction) throws HttpException, IOException {
         OkHttp okHttp = new OkHttp();
 
@@ -851,26 +865,4 @@ public class DcTrafficStatisticsServiceImpl implements IDcTrafficStatisticsServi
         return new ArrayList();
     }
 
-    private static String extract(String input) {
-        Pattern pattern = Pattern.compile("K(\\d{3})\\+(\\d{3})");
-        Matcher matcher = pattern.matcher(input);
-
-        if (matcher.find()) {
-            String part1 = matcher.group(1);
-            String part2 = matcher.group(2);
-            // 直接拼接两部分数字，无需格式化，这样得到的字符串自然没有前导零
-            return part1 + part2;
-        } else {
-            return "N/A";
-        }
-    }
-    public static String getDescriptionByIdentification(int identification) {
-        for (StakeMarkRange range : StakeMarkRange.values()) {
-            if (range.getIdentification() == identification) {
-                return range.getDescription();
-            }
-        }
-        return "";
-    }
-
 }

zc-business/src/main/java/com/zc/business/service/impl/IDcGantryMetricsStatisticsDataServiceImpl.java

@@ -8,8 +8,8 @@ import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
 import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
 import com.ruoyi.common.exception.ServiceException;
 import com.zc.business.domain.DcGantryMetricsStatisticsData;
-import com.zc.business.domain.DcGantryStatisticsData;
 import com.zc.business.enums.ChannelCongestionLevelEnum;
+import com.zc.business.enums.StakeMarkRange;
 import com.zc.business.enums.TrafficCompositionRateEnum;
 import com.zc.business.enums.TrafficDataPeriodTypeEnum;
 import com.zc.business.mapper.DcGantryMetricsStatisticsDataMapper;
@@ -28,9 +28,11 @@ import org.springframework.stereotype.Service;
 import javax.annotation.PostConstruct;
 import javax.annotation.Resource;
 import java.io.IOException;
-import java.util.ArrayList;
-import java.util.Date;
-import java.util.List;
+import java.time.LocalDateTime;
+import java.util.*;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+import java.util.stream.Collectors;
 
 /**
  * 门架指标统计服务实现类，负责处理实时设备消息、缓存数据、定时任务以及数据保存等功能。
@@ -162,6 +164,226 @@ public class IDcGantryMetricsStatisticsDataServiceImpl
         return list(queryWrapper);
     }
 
+    /**
+     * 路段交通指标分析
+     *
+     * @param startDate
+     * @param direction
+     * @param periodType
+     * @return
+     */
+    @Override
+    public List<Map<String, Object>> sectionTrafficIndexAnalysis(String startDate, String direction, String periodType, int ranking) {
+        List<Map<String, Object>> mapListOne = gantryMetricsStatisticsDataMapper.sectionTrafficIndexAnalysis(startDate, direction, periodType);
+        List<Map<String, Object>> mapList = new ArrayList<>();
+        Map<Integer, List<Map<String, Object>>> result = mapListOne.stream()
+                .collect(Collectors.groupingBy(map -> {
+                    String stakeMark = map.get("stakeMark").toString();
+                    int extractedNumber = Integer.parseInt(extract(stakeMark));
+                    return Arrays.stream(StakeMarkRange.values())
+                            .filter(smRange -> extractedNumber >= smRange.getStakeMark() && extractedNumber <= smRange.getEndMark())
+                            .mapToInt(StakeMarkRange::getIdentification)
+                            .findFirst()
+                            .orElse(0);
+                }));
+// 处理每个组
+        for (Map.Entry<Integer, List<Map<String, Object>>> entry : result.entrySet()) {
+            Integer groupId = entry.getKey();
+            List<Map<String, Object>> groupData = entry.getValue();
+
+            // 计算crowdingRate和trafficCompositionRate的众数，以及saturationRate的平均值
+            int[] rates = {0, 0}; // 用于存储众数，第一个元素为crowdingRate众数，第二个为trafficCompositionRate众数
+            float sumSaturationRate = 0;
+            int count = groupData.size();
+            String id = "";
+            Map<Integer, Integer> crowdingRateCounts = new HashMap<>();
+            Map<Integer, Integer> trafficCompositionRateCounts = new HashMap<>();
+
+            for (Map<String, Object> item : groupData) {
+                Integer crowdingRate = (Integer) item.get("crowdingRate");
+                Integer trafficCompositionRate = (Integer) item.get("trafficCompositionRate");
+                Float saturationRate = (Float) item.get("saturationRate");
+                id = (String) item.get("id");
+
+                //  Double saturationRate = (Double) item.get("saturationRate");
+
+                sumSaturationRate += saturationRate;
+
+                crowdingRateCounts.put(crowdingRate, crowdingRateCounts.getOrDefault(crowdingRate, 0) + 1);
+                trafficCompositionRateCounts.put(trafficCompositionRate, trafficCompositionRateCounts.getOrDefault(trafficCompositionRate, 0) + 1);
+            }
+
+            // 找到众数
+            rates[0] = findMaxCountKey(crowdingRateCounts);
+            rates[1] = findMaxCountKey(trafficCompositionRateCounts);
+
+            // 计算平均saturationRate
+            double avgSaturationRate = count > 0 ? sumSaturationRate / count : 0;
+
+// 格式化保留4位小数
+            String formattedAvgSaturationRate = String.format("%.4f", avgSaturationRate);
+            Map<String, Object> map = new HashMap<>();
+            String description = getDescriptionByIdentification(groupId);
+
+            map.put("groupId", groupId);
+            map.put("Id", id);
+            map.put("groupName", description);
+            map.put("crowdingRate", rates[0]);
+            map.put("trafficCompositionRate", rates[1]);
+            map.put("saturationRate", formattedAvgSaturationRate);
+            mapList.add(map);
+            // System.out.println("集团: " + groupId);
+            //  System.out.println("拥堵度" + rates[0]);
+            //  System.out.println("交通组成特征指数" + rates[1]);
+            //   System.out.println("平均饱和度:" + formattedAvgSaturationRate);
+
+        }
+        if (ranking == 1) {
+            mapList.sort(Comparator.comparingInt(map -> (Integer) ((Map<String, Object>) map).get("saturationRate")).reversed());
+        }
+        if (ranking == 2) {
+            mapList.sort(Comparator.comparingInt(map -> (Integer) ((Map<String, Object>) map).get("crowdingRate")).reversed());
+        }
+        if (ranking == 3) {
+            mapList.sort(Comparator.comparingInt(map -> (Integer) ((Map<String, Object>) map).get("trafficCompositionRate")).reversed());
+        }
+        return mapList;
+    }
+
+    /**
+     * 交通指标时间分布
+     *
+     * @param startDate
+     * @param direction
+     * @param periodType
+     * @return
+     */
+    @Override
+    public List<Map<String, Object>> passIndicatorTimeDistribution(String startDate, String direction, String periodType) {
+        List<Map<String, Object>> mapList = gantryMetricsStatisticsDataMapper.sectionTrafficIndexAnalysis(startDate, direction, periodType);
+        List<Map<String, Object>> mapTime = new ArrayList<>();
+
+// 使用 Java流按照相同时间分组
+        Map<LocalDateTime, List<Map<String, Object>>> result = mapList.stream()
+                .collect(Collectors.groupingBy(
+                        map -> (LocalDateTime) map.get("statisticalDate"),
+                        Collectors.toList()
+                ));
+        // 处理每个组
+        for (Map.Entry<LocalDateTime, List<Map<String, Object>>> entry : result.entrySet()) {
+            LocalDateTime groupId = entry.getKey();
+            List<Map<String, Object>> groupData = entry.getValue();
+
+            // 计算crowdingRate和trafficCompositionRate的众数，以及saturationRate的平均值
+            int[] rates = {0, 0}; // 用于存储众数，第一个元素为crowdingRate众数，第二个为trafficCompositionRate众数
+            float sumSaturationRate = 0;
+            int count = groupData.size();
+            String id = "";
+            Map<Integer, Integer> crowdingRateCounts = new HashMap<>();
+            Map<Integer, Integer> trafficCompositionRateCounts = new HashMap<>();
+
+            for (Map<String, Object> item : groupData) {
+                Integer crowdingRate = (Integer) item.get("crowdingRate");
+                Integer trafficCompositionRate = (Integer) item.get("trafficCompositionRate");
+                Float saturationRate = (Float) item.get("saturationRate");
+                id = (String) item.get("id");
+
+                //  Double saturationRate = (Double) item.get("saturationRate");
+
+                sumSaturationRate += saturationRate;
+
+                crowdingRateCounts.put(crowdingRate, crowdingRateCounts.getOrDefault(crowdingRate, 0) + 1);
+                trafficCompositionRateCounts.put(trafficCompositionRate, trafficCompositionRateCounts.getOrDefault(trafficCompositionRate, 0) + 1);
+            }
+
+            // 找到众数
+            rates[0] = findMaxCountKey(crowdingRateCounts);
+            rates[1] = findMaxCountKey(trafficCompositionRateCounts);
+
+            // 计算平均saturationRate
+            double avgSaturationRate = count > 0 ? sumSaturationRate / count : 0;
+
+// 格式化保留4位小数
+            String formattedAvgSaturationRate = String.format("%.4f", avgSaturationRate);
+            Map<String, Object> map = new HashMap<>();
+            map.put("groupTime", groupId);
+            map.put("Id", id);
+            map.put("crowdingRate", rates[0]);
+            map.put("trafficCompositionRate", rates[1]);
+            map.put("saturationRate", formattedAvgSaturationRate);
+            mapTime.add(map);
+        }
+
+        // 输出结果
+        result.forEach((date, data) -> {
+            System.out.println("统计日期:" + date);
+            data.forEach(entry -> {
+                entry.forEach((key, value) -> {
+                    System.out.println(key + ": " + value);
+                });
+            });
+        });
+        return mapTime;
+    }
+
+    /**
+     * 交通指标雷达图
+     * @param startDate
+     * @param direction
+     * @param periodType
+     * @return
+     */
+    @Override
+    public Map<String, Object> radarMapOfTrafficIndicators(String startDate, String direction, String periodType) {
+        List<Map<String, Object>> mapOne = gantryMetricsStatisticsDataMapper.sectionTrafficIndexAnalysis(startDate, direction, periodType);
+        // 计算crowdingRate和trafficCompositionRate的众数，以及saturationRate的平均值
+        int[] rates = {0, 0}; // 用于存储众数，第一个元素为crowdingRate众数，第二个为trafficCompositionRate众数
+        float sumSaturationRate = 0;
+        int count = mapOne.size();
+        Map<Integer, Integer> crowdingRateCounts = new HashMap<>();
+        Map<Integer, Integer> trafficCompositionRateCounts = new HashMap<>();
+
+        for (Map<String, Object> item : mapOne) {
+            Integer crowdingRate = (Integer) item.get("crowdingRate");
+            Integer trafficCompositionRate = (Integer) item.get("trafficCompositionRate");
+            Float saturationRate = (Float) item.get("saturationRate");
+            //  Double saturationRate = (Double) item.get("saturationRate");
+            sumSaturationRate += saturationRate;
+
+            crowdingRateCounts.put(crowdingRate, crowdingRateCounts.getOrDefault(crowdingRate, 0) + 1);
+            trafficCompositionRateCounts.put(trafficCompositionRate, trafficCompositionRateCounts.getOrDefault(trafficCompositionRate, 0) + 1);
+        }
+        // 找到众数
+        rates[0] = findMaxCountKey(crowdingRateCounts);
+        rates[1] = findMaxCountKey(trafficCompositionRateCounts);
+        // 计算平均saturationRate
+        double avgSaturationRate = count > 0 ? sumSaturationRate / count : 0;
+
+// 格式化保留4位小数
+        String formattedAvgSaturationRate = String.format("%.4f", avgSaturationRate);
+        Map<String, Object> map = new HashMap<>();
+        map.put("crowdingRate", rates[0]);
+        map.put("trafficCompositionRate", rates[1]);
+        map.put("saturationRate", formattedAvgSaturationRate);
+        return map;
+    }
+
+
+    private static int findMaxCountKey(Map<Integer, Integer> counts) {
+        // 初始化一个 Pair 类型来存储当前的最大计数及对应的键
+        Pair<Integer, Integer> maxPair = null;
+
+        for (Map.Entry<Integer, Integer> entry : counts.entrySet()) {
+            if (maxPair == null || entry.getValue() > maxPair.getValue() ||
+                    (entry.getValue().equals(maxPair.getValue()) && entry.getKey() > maxPair.getKey())) {
+                maxPair = new Pair<>(entry.getKey(), entry.getValue());
+            }
+        }
+
+        // 确保maxPair不为null，这里假设输入的counts非空且至少有一个元素
+        return maxPair.getKey();
+    }
+
     /**
      * 恢复小时缓存数据的方法
      * 该方法首先会获取当前月份的门架入口数据，
@@ -272,4 +494,44 @@ public class IDcGantryMetricsStatisticsDataServiceImpl
     }
 
 
+    private static String extract(String input) {
+        Pattern pattern = Pattern.compile("K(\\d{3})\\+(\\d{3})");
+        Matcher matcher = pattern.matcher(input);
+
+        if (matcher.find()) {
+            String part1 = matcher.group(1);
+            String part2 = matcher.group(2);
+            // 直接拼接两部分数字，无需格式化，这样得到的字符串自然没有前导零
+            return part1 + part2;
+        } else {
+            return "N/A";
+        }
+    }
+
+    public static String getDescriptionByIdentification(int identification) {
+        for (StakeMarkRange range : StakeMarkRange.values()) {
+            if (range.getIdentification() == identification) {
+                return range.getDescription();
+            }
+        }
+        return "";
+    }
+
+    public static class Pair<K, V> {
+        private K key;
+        private V value;
+
+        public Pair(K key, V value) {
+            this.key = key;
+            this.value = value;
+        }
+
+        public K getKey() {
+            return key;
+        }
+
+        public V getValue() {
+            return value;
+        }
+    }
 }

zc-business/src/main/resources/mapper/business/DcGantryMetricsStatisticsDataMapper.xml

@@ -3,7 +3,17 @@
 PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
 "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
 <mapper namespace="com.zc.business.mapper.DcGantryMetricsStatisticsDataMapper">
-
+    <resultMap type="map" id="countMap">
+        <result property="id" column="id"/>
+        <result property="facilityName" column="facility_name"/>
+        <result property="stakeMark" column="stake_mark"/>
+        <result property="direction" column="direction"/>
+        <result property="gantryCode" column="gantry_code"/>
+        <result property="trafficCompositionRate" column="traffic_composition_rate"/>
+        <result property="crowdingRate" column="crowding_rate"/>
+        <result property="saturationRate" column="saturation_rate"/>
+        <result property="statisticalDate" column="statistical_date"/>
+    </resultMap>
     <!-- 插入或更新门架指标数据 -->
     <insert id="insertOrUpdate" parameterType="com.zc.business.domain.DcGantryMetricsStatisticsData">
         INSERT INTO
@@ -74,4 +84,23 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
             update_time = NOW()
     </insert>
 
+    <select id="sectionTrafficIndexAnalysis" resultMap="countMap" resultType="map" >
+        SELECT fa.facility_name,
+               fa.stake_mark,
+               fa.direction,
+               dg.statistical_date,
+               dg.gantry_code,
+               dg.id,
+               dg.traffic_composition_rate,
+               dg.crowding_rate,
+               dg.saturation_rate
+        FROM dc_gantry_metrics_statistics_data as dg
+                 LEFT JOIN dc_facility as fa on fa.facility_code = dg.gantry_code
+        WHERE DATE(dg.statistical_date) = #{startDate}
+          AND fa.direction = #{direction}
+          AND dg.period_type = #{periodType}
+    </select>
+
+
+
 </mapper>

zc-business/src/main/resources/mapper/business/DcGantryStatisticsDataMapper.xml

@@ -7,6 +7,14 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
         <result property="volume" column="total_traffic_volume"/>
         <result property="name" column="interval_name"/>
     </resultMap>
+    <resultMap type="map" id="trafficPeriodAnalysisMap">
+        <result property="gantryCode" column="gantry_code"/>
+        <result property="trafficVolume" column="traffic_volume"/>
+        <result property="facilityName" column="facility_name"/>
+        <result property="stakeMark" column="stake_mark"/>
+        <result property="direction" column="direction"/>
+        <result property="statisticalDate" column="statistical_date"/>
+    </resultMap>
     <!-- 插入或更新交通路段数据 -->
     <insert id="insertOrUpdate" parameterType="com.zc.business.domain.DcGantryStatisticsData">
         INSERT INTO
@@ -213,4 +221,34 @@ PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
 
     </select>
 
+
+    <select id="trafficPeriodAnalysis" resultMap="trafficPeriodAnalysisMap" resultType="map" >
+            SELECT
+            dg.gantry_code,
+            dg.traffic_volume,
+            fa.facility_name,
+            fa.stake_mark,
+            fa.direction,
+            dg.statistical_date
+            FROM
+            dc_gantry_statistics_data AS dg
+            LEFT JOIN
+            dc_facility AS fa
+            ON
+            fa.facility_code = dg.gantry_code
+            WHERE
+            <if test="periodType == 1">
+                YEAR(dg.statistical_date) = #{startDate}
+            </if>
+            <if test="periodType == 2">
+                DATE_FORMAT(dg.statistical_date, '%Y-%m') = #{startDate}
+            </if>
+            <if test="periodType == 4">
+                DATE(dg.statistical_date) = DATE(#{startDate})
+            </if>
+            AND fa.direction = #{direction}
+            AND dg.period_type = '5'
+        </select>
+
+
 </mapper>