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1:洪水预报-将查询的整点过五分的数据，改为整点数据 

2：渗流同样将整点过五分数据改为整点(只改变时间）
不确定是否监测数据就为整点过五分数据还是别的
master
yangzhe123 2025-11-04 11:20:53 +08:00
parent de5eb202ae
commit d1d835ff02
6 changed files with 350 additions and 33 deletions
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9
src/main/java/com/gunshi/project/hsz/mapper/AttResBaseMapper.java
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@ -26,15 +26,16 @@ public interface AttResBaseMapper extends BaseMapper<AttResBase> {
select t.stcd,t.stnm,t.lgtd lgtd,t.lttd lttd,t.source,t.sttp,t.stlc,t.adcd,t.esstym,s.res_code,s.fl_low_lim_lev,
s.tot_cap,s.ben_res_cap,s.norm_wat_lev,s.crest_elev,s.des_flood_lev,s.dead_lev,s.cal_flood_lev,s.wat_shed_area,s.dead_cap,sad.adnm,
m.tm,m.rz,(m.rz-s.fl_low_lim_lev) as aFsltdz,sprr.tm as drpTm,sprr.h1,sprr.h3,sprr.h6,sprr.h12,sprr.h24,sprr.today,
case when s.cal_flood_lev is not null and m.rz-s.cal_flood_lev &gt; 0 then 1 else 0 end as calState,
case when s.des_flood_lev is not null and m.rz-s.des_flood_lev &gt; 0 then 1 else 0 end as desState,
case when s.fl_low_lim_lev is not null and m.rz-s.fl_low_lim_lev &gt; 0 then 1 else 0 end as flState
case when s.cal_flood_lev is not null and m.rz-s.cal_flood_lev >= 0 then 1 else 0 end as calState,
case when s.des_flood_lev is not null and m.rz-s.des_flood_lev >= 0 then 1 else 0 end as desState,
case when s.fl_low_lim_lev is not null and m.rz-s.fl_low_lim_lev >= 0 then 1 else 0 end as flState
from public.st_stbprp_b t
left join public.att_res_base s on 1=1
left join public.st_addvcd_d sad on t.adcd = sad.adcd
left join public.st_rsvr_r_real m on t.stcd = m.stcd
left join public.st_pptn_r_real sprr on t.stcd = sprr.stcd
where t.sttp = 'RR' and s.res_code = '42118130001' and t.stcd='232'
join public.st_stbprp_b_elem stbe on t.stcd = stbe.stcd
where stbe.elem ='rz' and s.res_code = '42118130001' and t.stcd='232'
order by aFsltdz desc nulls last
</script>
""")

4
src/main/java/com/gunshi/project/hsz/mapper/JcskSyRMapper.java
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@ -101,9 +101,9 @@ public interface JcskSyRMapper extends BaseMapper<JcskSyR> {
@Select("""
<script>
select to_char(t.tm,'YYYY-MM-DD HH24:MI:SS') as tm,t.rz
select to_char((t.tm - INTERVAL '5 minutes'),'YYYY-MM-DD HH24:MI:SS') as tm,t.rz
from public.st_rsvr_r t
where t.stcd = #{stcd} and to_char(t.tm, 'MI:SS') = '00:00'
where t.stcd = #{stcd} and to_char(t.tm, 'MI:SS') = '05:00'
<if test="obj.dateTimeRangeSo != null and obj.dateTimeRangeSo.start != null">
and t.tm <![CDATA[>=]]> #{obj.dateTimeRangeSo.start}
</if>

6
src/main/java/com/gunshi/project/hsz/model/AttResBuilding.java
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@ -29,8 +29,8 @@ public class AttResBuilding implements Serializable {
@TableId(value = "id", type = IdType.INPUT)
private Integer id;
// 主坝字段 (prefix: main_)
private String mainType; // 主坝-坝型
// 主坝字段 (prefix: main_) 挡水建筑物（大坝）
private String mainType; // 主坝-坝型 建筑物型式
private String mainFoundation; //主坝-地基特性
private String mainBasicIntensityOfAnEarthQuake; //主坝-地震基本烈度
private BigDecimal mainCrestElevation; // 主坝-坝顶高程(m)
@ -47,7 +47,7 @@ public class AttResBuilding implements Serializable {
private BigDecimal auxCrestWidth; // 副坝-坝顶宽度(m)
private BigDecimal auxMaxHeight; // 副坝-最大坝高(m)
// 溢洪道字段 (prefix: spillway_)
// 溢洪道字段 (prefix: spillway_) 泄水建筑物
private String spillwayType; // 溢洪道-型式
private String spillwayCrestType; // 溢洪道-堰顶型式
private String spillwayFoundation; // 溢洪道-地基特性

355
src/main/java/com/gunshi/project/hsz/service/ForecastResultsService.java
View File

@ -8,25 +8,12 @@ import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import com.gunshi.algorithm.RrainfallForecast;
import com.gunshi.algorithm.RunoffService;
import com.gunshi.model.vo.FloodAlgorithemVo;
import com.gunshi.project.hsz.service.*;
import com.gunshi.project.hsz.entity.vo.ForeRainStatVo;
import com.gunshi.project.hsz.entity.vo.ForeRainTimeVo;
import com.gunshi.project.hsz.entity.vo.ForecastResultVo;
import com.gunshi.project.hsz.grb.RainGrib2Layer;
import com.gunshi.project.hsz.mapper.ForecastResultsMapper;
import com.gunshi.project.hsz.model.AttResBase;
import com.gunshi.project.hsz.model.ForecastPa;
import com.gunshi.project.hsz.model.ForecastProject;
import com.gunshi.project.hsz.model.ForecastResults;
import com.gunshi.project.hsz.model.ForecastTask;
import com.gunshi.project.hsz.model.ForecastU;
import com.gunshi.project.hsz.model.ForecastUseparam;
import com.gunshi.project.hsz.model.StPptnR;
import com.gunshi.project.hsz.model.StPptnRAverage;
import com.gunshi.project.hsz.model.StRsvrR;
import com.gunshi.project.hsz.model.StStbprpB;
import com.gunshi.project.hsz.model.StZqrlB;
import com.gunshi.project.hsz.model.StZvarlB;
import com.gunshi.project.hsz.model.*;
import com.gunshi.project.hsz.util.DataHandleUtil;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
@ -45,7 +32,6 @@ import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.function.Function;
import java.util.stream.Collectors;
@ -171,6 +157,28 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
List<StPptnR> pptnRFutureList = new ArrayList<>();
QueryWrapper<StPptnR> qwExisted = new QueryWrapper<>();
Boolean isHaveFuturePPtn = true;
// 檀树岗修改：实测降雨查询表数据，预测降雨使用geom参数。最后按时间算数平均
// for(StStbprpB b : stbs){
// String stcd = b.getStcd();
// // 如果结束时间在当前时间之前，降雨序列从历史降雨表获取
// if (endTime.compareTo(nowHourTime) <= 0) {
// qwExisted = new QueryWrapper<StPptnR>().eq("stcd", stcd).ge("tm", startTime).le("tm", endTime).orderBy(true, true, "tm");
// } else {
// qwExisted = new QueryWrapper<StPptnR>().eq("stcd", stcd).ge("tm", startTime).le("tm", nowHourTime).orderBy(true, true, "tm");
// try {
// // 获取预报数据
// pptnRFutureList = getForecastDrpData(nowHourTime, stcd);
// } catch (IllegalArgumentException e) {
// if(stcd.equals(attResBase.getStcd())){
// isHaveFuturePPtn = false;
// }
// log.error("该时间无预报数据");
// }
// }
// List<StPptnR> pptnRExistedList = stPptnRService.list(qwExisted);
// pptnRAllList.addAll(pptnRExistedList);
// pptnRAllList.addAll(pptnRFutureList);
// }
if (endTime.compareTo(nowHourTime) <= 0) {
qwExisted = new QueryWrapper<StPptnR>().in("stcd", stbs.stream().map(StStbprpB::getStcd).toArray(String[]::new)).ge("tm", startTime).le("tm", endTime).orderBy(true, true, "tm");
} else {
@ -271,7 +279,7 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
Date[] period = periods.get(k);
Calendar calNew = Calendar.getInstance();
calNew.setTime(period[0]);
// 根据每段时间的开始时间，如果在08点05分前，则采用前一天的pa值计算
// 根据每段时间的开始时间，如果在08点前，则采用前一天的pa值计算
if (isBeforeEightAM(period[0])) {
// 将日期往前推一天
calNew.add(Calendar.DATE, -1);
@ -406,7 +414,297 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
private List<Map<String, Object>> excuteForecastDebug(ForecastTask forecastTask) throws Exception {
List<ForecastResultVo> voList = new ArrayList<>();
// 获取配置参数
List<ForecastUseparam> paramList = forecastUseparamService.list(new QueryWrapper<ForecastUseparam>().isNotNull("param_code").isNotNull("param_value"));
if (CollectionUtils.isEmpty(paramList)) {
throw new IllegalArgumentException("温馨提示：当前洪水预报所依赖的数据尚不完整，请检查入参是否缺失。");
}
// 获取系统当前的水库站编码、汛限水位
AttResBase attResBase = attResBaseService.getOne(new QueryWrapper<>());
// 多站点水库面雨量
// List<StStbprpB> stbs = stStbprpBService.list(new QueryWrapper<StStbprpB>().eq("res_code", attResBase.getResCode()));
// 单站点
List<StStbprpB> stbs = stStbprpBService.list(new QueryWrapper<StStbprpB>().eq("stcd", attResBase.getStcd()));
if (CollectionUtils.isEmpty(stbs)) {
return null;
}
Date nowHourTime = forecastTask.getNowTime();
Date startTime = forecastTask.getStartTime();
Date endTime = forecastTask.getEndTime();
// 获取整个时间线的降雨数据
List<StPptnR> pptnRAllList = new ArrayList<>();
List<StPptnR> pptnRFutureList = new ArrayList<>();
QueryWrapper<StPptnR> qwExisted = new QueryWrapper<>();
Boolean isHaveFuturePPtn = true;
// 檀树岗修改：实测降雨查询表数据，预测降雨使用geom参数。最后按时间算数平均
// for(StStbprpB b : stbs){
// String stcd = b.getStcd();
// // 如果结束时间在当前时间之前，降雨序列从历史降雨表获取
// if (endTime.compareTo(nowHourTime) <= 0) {
// qwExisted = new QueryWrapper<StPptnR>().eq("stcd", stcd).ge("tm", startTime).le("tm", endTime).orderBy(true, true, "tm");
// } else {
// qwExisted = new QueryWrapper<StPptnR>().eq("stcd", stcd).ge("tm", startTime).le("tm", nowHourTime).orderBy(true, true, "tm");
// try {
// // 获取预报数据
// pptnRFutureList = getForecastDrpData(nowHourTime, stcd);
// } catch (IllegalArgumentException e) {
// if(stcd.equals(attResBase.getStcd())){
// isHaveFuturePPtn = false;
// }
// log.error("该时间无预报数据");
// }
// }
// List<StPptnR> pptnRExistedList = stPptnRService.list(qwExisted);
// pptnRAllList.addAll(pptnRExistedList);
// pptnRAllList.addAll(pptnRFutureList);
// }
if (endTime.compareTo(nowHourTime) <= 0) {
qwExisted = new QueryWrapper<StPptnR>().in("stcd", stbs.stream().map(StStbprpB::getStcd).toArray(String[]::new)).ge("tm", startTime).le("tm", endTime).orderBy(true, true, "tm");
} else {
qwExisted = new QueryWrapper<StPptnR>().in("stcd", stbs.stream().map(StStbprpB::getStcd).toArray(String[]::new)).ge("tm", startTime).le("tm", nowHourTime).orderBy(true, true, "tm");
// 获取预报数据
try {
pptnRFutureList = getForecastDrpData(nowHourTime, attResBase.getStcd());
if(CollectionUtils.isEmpty(pptnRFutureList)) {
isHaveFuturePPtn = false;
log.error("该时间无预报数据");
}
} catch (IllegalArgumentException e) {
isHaveFuturePPtn = false;
log.error("该时间无预报数据");
}
}
List<StPptnR> pptnRExistedList = stPptnRService.list(qwExisted);
pptnRAllList.addAll(pptnRExistedList);
pptnRAllList.addAll(pptnRFutureList);
if (CollectionUtils.isEmpty(pptnRAllList)) {
return null;
}
// 多站点面雨量结果list
List<StPptnR> polyPptnRList = pptnRAllList.stream()
.collect(Collectors.groupingBy(
StPptnR::getTm,
Collectors.mapping(
pptn -> Double.parseDouble(pptn.getDrp()), // 将String转换为double
Collectors.averagingDouble(d -> d) // 计算平均值
)
))
.entrySet().stream()
.map(entry -> new StPptnRAverage(entry.getKey(), String.valueOf(entry.getValue())))
.sorted(Comparator.comparing(StPptnRAverage::getTm))
.collect(Collectors.toList());
double dt = 0.0;
double Wm = 0.0;
double qOther = 0.0;
Map<String, String> paramMap = paramList.stream().collect(Collectors.toMap(ForecastUseparam::getParamCode, ForecastUseparam::getParamValue, (existing, replacement) -> existing));
if (paramMap.get("dt").isEmpty()) {
throw new IllegalArgumentException("温馨提示：当前洪水预报所依赖的数据尚不完整，请检查时间单元△T是否缺失。");
}
if (paramMap.get("Im").isEmpty()) {
throw new IllegalArgumentException("温馨提示：当前洪水预报所依赖的数据尚不完整，请检查最大初损值Im是否缺失。");
}
if (!paramMap.get("qOther").isEmpty()) {
qOther = Double.parseDouble(paramMap.get("qOther"));
}
dt = Double.parseDouble(paramMap.get("dt"));
// dt = Double.parseDouble("1.0");
Wm = Double.parseDouble(paramMap.get("Im"));
List<ForecastU> uList = forecastUService.list();
if (CollectionUtils.isEmpty(uList)) {
throw new IllegalArgumentException("温馨提示：当前洪水预报所依赖的数据尚不完整，请检查U(I)单位线是否缺失。");
}
// 每小时的单位径流量，单位m³/s
double[] u = uList.stream().mapToDouble(forecastU -> forecastU.getUValue().doubleValue()).toArray();
// 根据开始结束时间查询pa
Calendar cal = Calendar.getInstance();
cal.setTime(startTime);
// 将日期往前推一天
cal.add(Calendar.DATE, -1);
List<ForecastPa> paList = forecastPaService.list(new QueryWrapper<ForecastPa>().eq("stcd", attResBase.getStcd()).ge("tm", sdfDay.format(cal.getTime())).le("tm", sdfDay.format(endTime)));
if (CollectionUtils.isEmpty(paList)) {
throw new IllegalArgumentException("温馨提示：当前洪水预报所依赖的数据尚不完整，请检查每日土壤含水量Pa是否缺失。");
}
Map<String, ForecastPa> paMap = paList.stream().collect(Collectors.toMap(ForecastPa::getTm, entity -> entity, (existing, replacement) -> existing));
// 获取预测开始时间前的最后水库水位
double H1 = 0.0;// 初始水库水位，可以根据H1->V1,H1->q1得到初始的水库库容和下泄流量
StRsvrR rsvrR = stRsvrRService.getOne(new QueryWrapper<StRsvrR>().eq("stcd", attResBase.getStcd()).le("tm", startTime).orderBy(true, false, "tm").last("limit 1"));
if (ObjectUtils.isEmpty(rsvrR)) {
return null;
}
H1 = Double.parseDouble(rsvrR.getRz());
// 泄流量
List<StZqrlB> stZqrlBList = stZqrlBService.list(new QueryWrapper<StZqrlB>().eq("stcd", attResBase.getStcd()).orderBy(true, true, "z"));
// 库容曲线
List<StZvarlB> zvarlBS = stZvarlBService.list(new QueryWrapper<StZvarlB>().eq("stcd", attResBase.getStcd()).orderBy(true, true, "rz"));
// 水位历史数据
List<StRsvrR> rsvrRRealList = stRsvrRService.list(new QueryWrapper<StRsvrR>().eq("stcd", attResBase.getStcd()).ge("tm", startTime).le("tm", endTime));
List<StRsvrR> resultList = reorganizeRsvrRData(rsvrRRealList, dt);
List<Date[]> periods = splitByDay8To8(startTime, endTime);
// v：累计降雨
BigDecimal vValue = BigDecimal.ZERO;
BigDecimal vSum = BigDecimal.ZERO;
// Rsum：累计径流深
BigDecimal Rsum = BigDecimal.ZERO;
BigDecimal Psum = BigDecimal.ZERO;
List<Map<String, Object>> res = new ArrayList<>();
// 存储最后u的长度-1个r值
for (int k = 0; k < periods.size(); k++) {
Date[] period = periods.get(k);
Calendar calNew = Calendar.getInstance();
calNew.setTime(period[0]);
// 根据每段时间的开始时间，如果在08点前，则采用前一天的pa值计算
if (isBeforeEightAM(period[0])) {
// 将日期往前推一天
calNew.add(Calendar.DATE, -1);
}
ForecastPa forecastPa = paMap.get(sdfDay.format(calNew.getTime()));
if (ObjectUtils.isEmpty(forecastPa)) {
continue;
// throw new IllegalArgumentException("温馨提示：当前洪水预报所依赖的数据尚不完整，请检查每日土壤含水量Pa、K值是否缺失。");
}
// 根据降雨数据，按照△t的颗粒度，均分
// 筛选时间段内的降雨数据。不包前但包后
List<StPptnR> filterList = polyPptnRList.stream().filter(e -> e.getTm().compareTo(period[0]) >= 0).filter(e -> e.getTm().compareTo(period[1]) <= 0).collect(Collectors.toList());
Map<String, List<StPptnR>> retMap = new HashMap<>();
if (CollectionUtils.isNotEmpty(filterList)) {
retMap = reorganizePptnRData(filterList, dt, period[0], period[1], nowHourTime, isHaveFuturePPtn);
}
if (ObjectUtils.isEmpty(retMap.get("listForForecast"))) {
continue;
}
List<String> pForecastList = retMap.get("listForForecast").stream().map(s -> s.getDrp()).collect(Collectors.toList());
if (pForecastList.size() == 0) {
continue;
}
if (ObjectUtils.isEmpty(retMap.get("listForReal"))) {
continue;
}
Map<String, String> pRealMap = retMap.get("listForReal").stream().collect(Collectors.toMap(pptnR -> sdfMinute.format(pptnR.getTm()), StPptnR::getDrp, (existing, replacement) -> existing));
double[] PList = pForecastList.stream().mapToDouble(Double::parseDouble).toArray();
vSum = vSum.add(vValue);
vValue = BigDecimal.ZERO;
for (double value : PList) {
BigDecimal bd = BigDecimal.valueOf(value);
// 累加到总和中
vValue = vValue.add(bd);
}
// 存储上一次的径流深r，最开始默认全部为0
List<Double> lastRArr = new ArrayList<>();
for (int i = 0; i < u.length - 1; i++) {
lastRArr.add(0.0); // 填充初始值
}
// 从后往前遍历不定长的实体列表
for (int i = voList.size() - 1; i >= 0; i--) {
int index = lastRArr.size() - 1 - (voList.size() - 1 - i);
lastRArr.set(index, voList.get(i).getR().doubleValue());
if(index <= 0){
break;
}
}
// 预测执行
Map<String,Object> map = new HashMap<>();
map.put("in period" + k, sdf.format(period[0]));
map.put("in K" + k, forecastPa.getK().doubleValue());
map.put("in pa0" + k, forecastPa.getPa0().doubleValue());
map.put("in Wm" + k, Wm);
map.put("in pt0" + k, forecastPa.getPt0().doubleValue());
map.put("in H1" + k, H1);
map.put("in dt" + k, dt);
map.put("in pa" + k, forecastPa.getPa().doubleValue());
map.put("in PList" + k, PList);
map.put("in u" + k, u);
map.put("in stcd" + k, attResBase.getStcd());
map.put("in qOther" + k, qOther);
map.put("in vSum" + k, vSum.doubleValue());
map.put("in Rsum" + k, Rsum.doubleValue());
map.put("in lastRArr" + k, lastRArr);
List<FloodAlgorithemVo> forecastVoList = RrainfallForecast.getData(sdf.format(period[0]), forecastPa.getK().doubleValue(), forecastPa.getPa0().doubleValue(), Wm, forecastPa.getPt0().doubleValue(), H1, dt,
forecastPa.getPa().doubleValue(), PList, u, attResBase.getStcd(), qOther, vSum.doubleValue(), Rsum.doubleValue(), lastRArr);
map.put("out res" + k, forecastVoList);
res.add(map);
if (CollectionUtils.isNotEmpty(forecastVoList)) {
// 筛选同时段的真实水位数据
List<StRsvrR> realRsvrList = resultList.stream().filter(item -> item.getTm().compareTo(period[0]) >= 0 && item.getTm().compareTo(period[1]) <= 0).collect(Collectors.toList());
Map<String, String> realRsvrMap = realRsvrList.stream().collect(Collectors.toMap(rsvr -> sdfMinute.format(rsvr.getTm()), StRsvrR::getRz, (existing, replacement) -> existing));
forecastVoList = forecastVoList.subList(0, PList.length + 1);
// 去除预测出来的最后一条与第二次实际的相同时间的数据
if (voList.size() > 0 && voList.get(voList.size() - 1).getTm().equals(forecastVoList.get(0).getDateStr())) {
voList.remove(voList.size() - 1);
}
for (int j = 0; j < forecastVoList.size(); j++) {
FloodAlgorithemVo floodAlgorithemVo = forecastVoList.get(j);
// dt不同，预测结果的条数不同（跟new_q参数有关）
if (floodAlgorithemVo.getDateStr().substring(0, 15).compareTo(sdfMinute.format(period[1])) > 0) {
break;
}
String dateStr = floodAlgorithemVo.getDateStr();
ForecastResultVo resultVo = new ForecastResultVo();
resultVo.setTm(dateStr);
resultVo.setYcRkQValue(floodAlgorithemVo.getRq());// 预测入库流量
// resultVo.setRealRkQValue();// 暂无真实入库流量
resultVo.setYcCkQValue(floodAlgorithemVo.getCq());// 预测出库流量
resultVo.setYcSwHValue(floodAlgorithemVo.getKh());// 预测水库水位
H1 = resultVo.getYcSwHValue().doubleValue();// 以预测水位作为下一次预测段起始值
String dateMinuteStr = dateStr.substring(0, dateStr.length() - 3);// 年月日 时分
if (realRsvrMap.containsKey(dateMinuteStr)) {
BigDecimal realSwHValue = new BigDecimal(realRsvrMap.get(dateMinuteStr));// 根据时间取更准确
resultVo.setRealSwHValue(realSwHValue);// 真实水库水位
calculateCap(zvarlBS, resultVo, realSwHValue);// 有真实水位就用真实水位算（作为实测库容）
resultVo.setSwHDValue(resultVo.getYcSwHValue().subtract(resultVo.getRealSwHValue()));// 预测与真实水位差
// 注释：修复跨8点时的陡升陡降
// H1 = realSwHValue.doubleValue();// 如果有真实水位，将最后一条的真实水位作为下一次预测段的初始水位
// 真实出库流量=真实水库水位与泄流量曲线差值法
if (realSwHValue != null && CollectionUtils.isNotEmpty(stZqrlBList)) {
BigDecimal maxZ = stZqrlBList.stream().max(Comparator.comparing(StZqrlB::getZ)).get().getZ();
BigDecimal minZ = stZqrlBList.stream().min(Comparator.comparing(StZqrlB::getZ)).get().getZ();
if (realSwHValue.compareTo(minZ) < 0 || realSwHValue.compareTo(maxZ) > 0) {
resultVo.setRealCkQValue(BigDecimal.ZERO);// 真实出库流量
} else {
Map<BigDecimal, BigDecimal> stZvalMap = stZqrlBList.stream().collect(Collectors.toMap(StZqrlB::getZ, StZqrlB::getQ, (existing, replacement) -> existing));
List<BigDecimal> list = stZqrlBList.stream().map(StZqrlB::getZ).collect(Collectors.toList());
resultVo.setRealCkQValue(DataHandleUtil.calcData(realSwHValue, stZvalMap, list));// 真实出库流量
}
}
} else {
// 没有真实水位就用预测水位算（作为预测库容）
calculateCap(zvarlBS, resultVo, resultVo.getYcSwHValue());
}
String pRealDrp = "0.0";
if (pRealMap.containsKey(dateMinuteStr)) {
pRealDrp = pRealMap.get(dateMinuteStr);
}
BigDecimal drp = new BigDecimal(pRealDrp);// 根据时间取更准确
if (drp.compareTo(BigDecimal.ZERO) < 0) {
resultVo.setDrp(BigDecimal.ZERO);
} else {
resultVo.setDrp(drp);
}
Psum = Psum.add(resultVo.getDrp());
resultVo.setPSum(Psum);
Date dateTm = sdf.parse(floodAlgorithemVo.getDateStr());
resultVo.setIspreDrp(dateTm.compareTo(nowHourTime) <= 0 ? "0" : "1");// 0：真实 1：预测
resultVo.setR(floodAlgorithemVo.getR());
if (resultVo.getR() != null) {
Rsum = Rsum.add(resultVo.getR());
} else {
continue;
}
resultVo.setRSum(Rsum);
resultVo.setFlLowLimLev(attResBase.getFlLowLimLev());
resultVo.setCurrentYdgdyjz(MapUtil.get(paramMap, "ydgdyjz", BigDecimal.class, BigDecimal.ZERO));
resultVo.setPa(floodAlgorithemVo.getPa());
voList.add(resultVo);
}
}
}
return res;
}
/**
* @description: 根据水位计算库容
@ -498,10 +796,10 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
* @auther: cxw
*/
private List<StRsvrR> reorganizeRsvrRData(List<StRsvrR> rsvrRRealList, double dt) {
//TODO 只保留整小时的数据(这里得看监测时间来分析，檀树岗是整点记录，目前我观测到的黑石咀的是每小时过5分钟记录一次 比如08:05:00 ~ 09:05:00
// 只保留整小时的数据
rsvrRRealList = rsvrRRealList.stream().filter(entity -> {
Date date = entity.getTm();
return date.getMinutes() ==0 && date.getSeconds() == 0;
return date.getMinutes() == 0 && date.getSeconds() == 0;
}).collect(Collectors.toMap(
e -> e.getStcd() + "_" + e.getTm(), // 使用属性组合作为键
Function.identity(),
@ -642,7 +940,7 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
}
/**
* @description: 将两个时间按照早八点五分分割成多段
* @description: 将两个时间按照早八点分割成多段
* @param startDate
* @param endDate
* @return: java.util.List<java.util.Date[]>
@ -675,7 +973,7 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
cal.add(Calendar.DAY_OF_MONTH, 1); // 移到下一天
}
cal.set(Calendar.HOUR_OF_DAY, 8);
cal.set(Calendar.MINUTE, 5);
cal.set(Calendar.MINUTE, 0);
cal.set(Calendar.SECOND, 0);
cal.set(Calendar.MILLISECOND, 0);
Date currentEnd = cal.getTime();
@ -816,4 +1114,21 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
return jsonBuilder.toString();
}
public List<Map<String, Object>> getHumanForecastResultDebug(ForecastTask forecastTask) {
// 当前时间整点，作为获取雨量数据历史、预测分隔点
Calendar calendar = Calendar.getInstance();
calendar.set(Calendar.MINUTE, 0);
calendar.set(Calendar.SECOND, 0);
calendar.set(Calendar.MILLISECOND, 0);
Date nowHourTime = calendar.getTime();
forecastTask.setNowTime(nowHourTime);
List<Map<String, Object>> maps;
try {
maps = excuteForecastDebug(forecastTask);
} catch (Exception e) {
e.printStackTrace();
throw new IllegalArgumentException(e.getMessage());
}
return maps;
}
}

1
src/main/java/com/gunshi/project/hsz/service/JcskSyRService.java
View File

@ -396,6 +396,7 @@ public class JcskSyRService extends ServiceImpl<JcskSyRMapper, JcskSyR> {
List<OsmoticStationVo2> resList = new ArrayList<>();
String stcd = jcskGnssRService.getStcd();
//查询库水位
//TODO 数据是每整点过五分监测一次(暂时修改，看后续实际数据来了之后会怎么样）
List<StRzVo> list = baseMapper.queryLineRz(osmoticQuerySo,stcd);
Map<String, BigDecimal> rzMap = list.stream().collect(Collectors.toMap(StRzVo::getTm, StRzVo::getRz));
//查询测站管水位

8
src/main/java/com/gunshi/project/hsz/timetask/AlarmTask.java
View File

@ -54,8 +54,8 @@ public class AlarmTask {
@Autowired
private StRiverRRealService stRiverRRealService;
//@Scheduled(fixedRate = 10, timeUnit = TimeUnit.SECONDS)
//
// @Scheduled(fixedRate = 10, timeUnit = TimeUnit.SECONDS)
public void updateAlarmSet(){
//查询告警设置中所有的配置的站点
List<AlarmSet> alarmSets = alarmSetMapper.selectList(null);
@ -66,8 +66,8 @@ public class AlarmTask {
}
}
//@Async
//@Scheduled(fixedRate = 30, timeUnit = TimeUnit.SECONDS)
// @Async
// @Scheduled(fixedRate = 30, timeUnit = TimeUnit.SECONDS)
public void updateWaterAlarm(){
List<AttResBaseVo> attResBaseVos = attResBaseMapper.queryList();
AttResBaseVo attResBaseVo = attResBaseVos.get(0);