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由于水位和雨量有5分钟左右的时间差，所以选择时间间隔最接近的数据进行结合展示

master
yangzhe123 2025-11-04 14:54:36 +08:00
parent 56da4f7282
commit f5e3755e38
6 changed files with 143 additions and 30 deletions
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8
src/main/java/com/gunshi/project/hsz/controller/StZqrlBController.java
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@ -146,10 +146,10 @@ public class StZqrlBController {
@PostMapping("/list")
public R<List<StZqrlB>> list(@RequestBody StZqrlB dto) {
LambdaQueryChainWrapper<StZqrlB> q = service.lambdaQuery().orderByAsc(StZqrlB::getZ);
String stcd = dto.getStcd();
if (StringUtils.isNotBlank(stcd)){
q.eq(StZqrlB::getStcd, stcd);
}
// String stcd = dto.getStcd();
// if (StringUtils.isNotBlank(stcd)){
// q.eq(StZqrlB::getStcd, stcd);
// }
return R.ok(q.list());
}

11
src/main/java/com/gunshi/project/hsz/entity/vo/MentenceInfoCountVo.java
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@ -1,6 +1,8 @@
package com.gunshi.project.hsz.entity.vo;
import com.fasterxml.jackson.databind.annotation.JsonSerialize;
import com.fasterxml.jackson.databind.ser.std.ToStringSerializer;
import com.gunshi.project.hsz.model.FileAssociations;
import com.gunshi.project.hsz.model.HiddenInfo;
import io.swagger.v3.oas.annotations.media.Schema;
@ -15,10 +17,19 @@ public class MentenceInfoCountVo extends HiddenInfo {
@Schema(description = "维护对象名称")
private String mentenceStName;
@Schema(description = "维护项目Id")
@JsonSerialize(using = ToStringSerializer.class)
private Long mentenceStId;
@Schema(description = "维护项目名称")
private String mentenceStDetailName;
@Schema(description = "维护对象Id")
@JsonSerialize(using = ToStringSerializer.class)
private Long mentenceStDetailId;
@Schema(description = "维护人Id")
@JsonSerialize(using = ToStringSerializer.class)
private String mentencePersonId;
@Schema(description = "维护人名称")

2
src/main/java/com/gunshi/project/hsz/mapper/AttResBaseMapper.java
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@ -74,7 +74,7 @@ public interface AttResBaseMapper extends BaseMapper<AttResBase> {
@Select("""
<script>
select t.stcd,(t.tm - INTERVAL '5 minutes') as tm,
select t.stcd,t.tm,
t.rz from public.st_rsvr_r t
where t.stcd = #{obj.stcd}
<if test="obj.stm != null ">

2
src/main/java/com/gunshi/project/hsz/mapper/MentenceFarmerRecordMapper.java
View File

@ -32,7 +32,7 @@ public interface MentenceFarmerRecordMapper extends BaseMapper<MentenceFarmerRec
@Select("""
<script>
select t1.*,t2.mentence_person_id as mentencePersonId,t2.mentence_person_name as mentencePersonName,
t3.name as mentenceStDetailName,t4.st_name as mentenceStName
t3.name as mentenceStDetailName,t4.st_name as mentenceStName,t4.id as mentenceStId,t3.id as mentenceStDetailId
from hidden_info t1
join mentence_farmer_record t2 on t1.mentence_farmer_record_id = t2.id
join mentence_st_detail t3 on t2.mentence_st_detail_id = t3.id

48
src/main/java/com/gunshi/project/hsz/service/ReservoirWaterService.java
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@ -53,6 +53,7 @@ public class ReservoirWaterService {
private StRiverRRealService stRiverRRealServices;
//实时供水
@Autowired
private StWaterRRealService stWaterRRealService;
@ -178,7 +179,8 @@ public class ReservoirWaterService {
}
public List<StZvarlB> zvarl(String stcd) {
LambdaQueryWrapper<StZvarlB> queryWrapper = Wrappers.lambdaQuery();
LambdaQueryWrapper<StZvarlB> queryWrapper = new LambdaQueryWrapper<>();
queryWrapper.orderByAsc(StZvarlB::getRz);
return stZvarlBMapper.selectList(queryWrapper);
}
@ -191,7 +193,11 @@ public class ReservoirWaterService {
//获取库容曲线关系，算出库容
List<StZvarlB> zvarl = zvarl(stcd);
if(CollectionUtils.isNotEmpty(zvarl)){
calcTqData(rzData,zvarl);
//calcTqData(rzData,zvarl);
rzData.stream().forEach(o -> {
BigDecimal w = stZvarlBService.getWByZvarl(zvarl, o.getRz());
o.setW(w);
});
}
//根据监测时间合并雨量和水位数据
return bindData(stcd,drpData,rzData);
@ -228,26 +234,30 @@ public class ReservoirWaterService {
}
}
private List<AttResMonitorVo> bindData(String stcd,List<AttResMonitorVo> drpData, List<AttResMonitorVo> rzData) {
HashSet<Date> strings = new HashSet<>();
drpData.stream().forEach(v1 -> strings.add(v1.getTm()));
rzData.stream().forEach(v1 -> strings.add(v1.getTm()));
private List<AttResMonitorVo> bindData(String stcd, List<AttResMonitorVo> drpData, List<AttResMonitorVo> rzData) {
// 以水位数据的时间为基准（过五分钟的数据）
return rzData.stream().map(rzVo -> {
AttResMonitorVo resultVo = AttResMonitorVo.builder()
.stcd(stcd)
.tm(rzVo.getTm()) // 使用水位数据的时间
.rz(rzVo.getRz())
.w(rzVo.getW())
.build();
ArrayList<AttResMonitorVo> result = new ArrayList<>();
strings.stream().forEach(v1 -> result.add(AttResMonitorVo.builder().stcd(stcd).tm(v1).build()));
List<AttResMonitorVo> list = result.stream().map(v1 -> {
drpData.stream().filter(v2 -> v1.getTm().equals(v2.getTm())).forEach(v2 -> {
v1.setDrp(v2.getDrp());
// 为这个水位时间点查找最接近的降水数据
drpData.stream()
.min(Comparator.comparing(drpVo -> Math.abs(rzVo.getTm().getTime() - drpVo.getTm().getTime())))
.ifPresent(closestDrp -> {
long timeDiff = Math.abs(rzVo.getTm().getTime() - closestDrp.getTm().getTime());
if (timeDiff <= 30 * 60 * 1000) { // 30分钟容差
resultVo.setDrp(closestDrp.getDrp());
}
});
rzData.stream().filter(v2 -> v1.getTm().equals(v2.getTm())).forEach(v2 -> {
v1.setRz(v2.getRz());
v1.setW(v2.getW());
});
return v1;
}).collect(Collectors.toList());
return list.stream().sorted(Comparator.comparing(AttResMonitorVo::getTm).reversed()).collect(Collectors.toList());
return resultVo;
})
.sorted(Comparator.comparing(AttResMonitorVo::getTm).reversed())
.collect(Collectors.toList());
}
public StRsvrVo rz(ReservoirWaterCommonSo reservoirWaterCommonSo) {

98
src/main/java/com/gunshi/project/hsz/service/RiverWaterService.java
View File

@ -17,6 +17,7 @@ import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
import java.math.BigDecimal;
import java.math.RoundingMode;
import java.time.LocalDateTime;
import java.time.ZoneId;
import java.util.*;
@ -76,6 +77,94 @@ public class RiverWaterService {
return stZqrlBMapper.selectList(queryWrapper);
}
public BigDecimal getQByRz(List<StZqR> zqr,BigDecimal rz){
// 1. 参数校验
if (zqr == null || zqr.isEmpty()) {
throw new IllegalArgumentException("水位-流量关系列表不能为空");
}
if (rz == null) {
throw new IllegalArgumentException("水位值不能为空");
}
// 2. 检查边界情况：如果目标水位低于最低水位或高于最高水位
BigDecimal minRz = zqr.get(0).getZ();
BigDecimal maxRz = zqr.get(zqr.size() - 1).getZ();
if (rz.compareTo(minRz) < 0) {
// 低于最低水位，返回0流量
return BigDecimal.ZERO;
}
if (rz.compareTo(maxRz) > 0) {
// 高于最高水位，返回0流量
return BigDecimal.ZERO;
}
// 3. 二分查找水位区间
int l = 0;
int r = zqr.size() - 1;
while (l <= r) {
int mid = l + (r - l) / 2;
BigDecimal midRz = zqr.get(mid).getZ();
int compareResult = midRz.compareTo(rz);
if (compareResult == 0) {
// 找到完全匹配的水位，直接返回对应的流量
return zqr.get(mid).getQ();
} else if (compareResult < 0) {
l = mid + 1;
} else {
r = mid - 1;
}
}
/**
* 此时：
* l 指向第一个大于rz的位置
* r 指向最后一个小于rz的位置
* 即：r为 (x1, y1) - 下限水位和流量
* l为 (x2, y2) - 上限水位和流量
*/
if (l >= zqr.size() || r < 0) {
return BigDecimal.ZERO;
}
// 获取前后相邻的两个点
StZqR lowerPoint = zqr.get(r);
StZqR upperPoint = zqr.get(l);
// 使用线性插值计算流量
return linearInterpolation(
lowerPoint.getZ(), lowerPoint.getQ(),
upperPoint.getZ(), upperPoint.getQ(),
rz
).setScale(3, RoundingMode.HALF_UP);
}
/**
* 线性插值辅助方法（可以复用之前的）
* @param x1 已知点1的水位
* @param y1 已知点1的流量
* @param x2 已知点2的水位
* @param y2 已知点2的流量
* @param x 目标水位
* @return 目标水位对应的流量
*/
private BigDecimal linearInterpolation(BigDecimal x1, BigDecimal y1,
BigDecimal x2, BigDecimal y2,
BigDecimal x) {
// 使用公式: y = y1 + ( (y2 - y1) / (x2 - x1) ) * (x - x1)
// 计算斜率: (y2 - y1) / (x2 - x1)
BigDecimal slope = y2.subtract(y1)
.divide(x2.subtract(x1), 10, RoundingMode.HALF_UP);
// 计算: slope * (x - x1)
BigDecimal xDiff = x.subtract(x1);
BigDecimal product = slope.multiply(xDiff);
// 计算最终结果: y1 + product
return y1.add(product);
}
public List<AttRvMonitorVo> monitorData(DataQueryCommonSo dataQueryCommonSo) {
String stcd = dataQueryCommonSo.getStcd();
@ -84,9 +173,12 @@ public class RiverWaterService {
//水位数据
List<AttRvMonitorVo> rzData = attRvBaseMapper.rz(dataQueryCommonSo);
//获取水位流量关系，算出转换流量
List<StZqrlB> zqrl = zqrl(stcd);
if(CollectionUtils.isNotEmpty(zqrl)){
calcTqData(rzData,zqrl);
//List<StZqrlB> zqrl = zqrl(stcd);
List<StZqR> zqr = zqr(stcd);
if(CollectionUtils.isNotEmpty(zqr)){
rzData.stream().forEach(o->{
o.setQ(getQByRz(zqr,o.getZ()));
});
}
//根据监测时间合并雨量和水位数据
return bindData(stcd,drpData,rzData);