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优化洪水预报接口

master
chenxiwang 2024-08-09 09:34:23 +08:00
parent 57190aa39b
commit 26ad44d4a0
4 changed files with 188 additions and 94 deletions
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4
src/main/java/com/gunshi/project/xyt/controller/ForecastProjectController.java
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@ -125,8 +125,8 @@ public class ForecastProjectController {
if (Objects.isNull(forecastProject)) {
throw new IllegalArgumentException("当前数据不存在");
}
List<ForecastResults> resultList = forecastResultsService.list(new QueryWrapper<ForecastResults>().eq("project_id", projectId));
if(CollectionUtils.isNotEmpty(resultList)) {
List<ForecastResults> resultList = forecastResultsService.list(new QueryWrapper<ForecastResults>().eq("project_id", projectId).orderBy(true, true, "tm"));
if (CollectionUtils.isNotEmpty(resultList)) {
forecastProject.setVoList(JSON.parseArray(JSON.toJSONString(resultList), ForecastResultVo.class));
forecastResultsService.handleVoList(forecastProject);
}

167
src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java
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@ -36,6 +36,7 @@ import java.util.ArrayList;
import java.util.Calendar;
import java.util.Comparator;
import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
@ -55,6 +56,8 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
private static SimpleDateFormat sdfDay = new SimpleDateFormat("yyyy-MM-dd");
private static SimpleDateFormat sdfMinute = new SimpleDateFormat("yyyy-MM-dd HH:mm");
private static SimpleDateFormat eightSdf = new SimpleDateFormat("yyyy-MM-dd 08");
private static SimpleDateFormat sixteenSdf = new SimpleDateFormat("yyyy-MM-dd 16");
@ -116,6 +119,7 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
Date nowHourTime = calendar.getTime();
forecastTask.setNowTime(nowHourTime);
List<ForecastResultVo> voList = excuteForecast(forecastTask);
voList.sort(Comparator.comparing(ForecastResultVo::getTm));
return voList;
}
@ -127,6 +131,8 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
* @date: 2024-08-05, 周一, 17:14:52
*/
private List<ForecastResultVo> excuteForecast(ForecastTask forecastTask) throws Exception {
// 获取系统当前的水库站编码、汛限水位
AttResBase attResBase = attResBaseService.getOne(new QueryWrapper<>());
List<ForecastResultVo> voList = new ArrayList<>();
Date nowHourTime = forecastTask.getNowTime();
Date startTime = forecastTask.getStartTime();
@ -137,53 +143,60 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
QueryWrapper<StPptnR> qwExisted = new QueryWrapper<>();
// 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", "716153201").ge("tm", startTime).le("tm", endTime).orderBy(true, true, "tm");
qwExisted = new QueryWrapper<StPptnR>().eq("stcd", attResBase.getStcd()).ge("tm", startTime).le("tm", endTime).orderBy(true, true, "tm");
} else {
qwExisted = new QueryWrapper<StPptnR>().eq("stcd", "716153201").ge("tm", startTime).le("tm", nowHourTime).orderBy(true, true, "tm");
pptnRFutureList = getForecastDrpData(nowHourTime, "716153201");
qwExisted = new QueryWrapper<StPptnR>().eq("stcd", attResBase.getStcd()).ge("tm", startTime).le("tm", nowHourTime).orderBy(true, true, "tm");
pptnRFutureList = getForecastDrpData(nowHourTime, attResBase.getStcd());
}
List<StPptnR> pptnRExistedList = stPptnRService.list(qwExisted);
pptnRAllList.addAll(pptnRExistedList);
pptnRAllList.addAll(pptnRFutureList);
if (CollectionUtils.isEmpty(pptnRAllList)) {
return voList;
}
// 获取配置参数
List<ForecastUseparam> paramList = forecastUseparamService.list(new QueryWrapper<ForecastUseparam>().isNotNull("param_code").isNotNull("param_value"));
List<ForecastU> uList = forecastUService.list();
if (CollectionUtils.isEmpty(paramList) || CollectionUtils.isEmpty(uList) || CollectionUtils.isEmpty(pptnRAllList)) {
return voList;
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。");
}
double dt = 0.0;
double Wm = 0.0;
// 每小时的单位径流量，单位m³/s
double[] u = uList.stream().mapToDouble(forecastU -> forecastU.getUValue().doubleValue()).toArray();
Map<String, String> paramMap = paramList.stream().collect(Collectors.toMap(ForecastUseparam::getParamCode, ForecastUseparam::getParamValue));
if (paramMap.get("dt").isEmpty() || paramMap.get("Im").isEmpty()) {
return voList;
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。");
}
dt = Double.parseDouble(paramMap.get("dt"));
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", "716153201").ge("tm", sdfDay.format(cal.getTime())).le("tm", sdfDay.format(endTime)));
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)) {
return voList;
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));
// 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", "716153201").le("tm", startTime).orderBy(true, false, "tm").last("limit 1"));
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 voList;
}
H1 = Double.parseDouble(rsvrR.getRz());
// 获取汛限水位
AttResBase attResBase = attResBaseService.getOne(new QueryWrapper<>());
// 泄流量
List<StZqrlB> stZqrlBList = stZqrlBService.list(new QueryWrapper<StZqrlB>().eq("stcd", "716153201"));
List<StZqrlB> stZqrlBList = stZqrlBService.list(new QueryWrapper<StZqrlB>().eq("stcd", attResBase.getStcd()));
// 水位历史数据
List<StRsvrR> rsvrRRealList = stRsvrRService.list(new QueryWrapper<StRsvrR>().eq("stcd", "716153201").ge("tm", startTime).le("tm", endTime));
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);
for (Date[] period : periods) {
@ -194,43 +207,40 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
cal.add(Calendar.DATE, -1);
}
ForecastPa forecastPa = paMap.get(sdfDay.format(cal.getTime()));
// 根据降雨数据，按照△t的颗粒度，均分
List<String> pResultList = new ArrayList<>();
// 筛选时间段内的降雨数据。第一个条件：时间大于等开始时间；第二个条件：时间小于等于结束时间（不包前但包后，比如从8点开始，就要拆下一个时间：9点的数据）
List<StPptnR> filterList = pptnRAllList.stream().filter(e -> e.getTm().compareTo(period[0]) >= 0).filter(e -> e.getTm().compareTo(period[1]) <= 0).collect(Collectors.toList());
// 从第二条数据开始
for (int i = 1; i < filterList.size(); i++) {
StPptnR stPptnRLast = filterList.get(i - 1);
StPptnR stPptnR = filterList.get(i);
String drp = stPptnR.getDrp();
// 两条数据的小时差
double diffHours = dateHourDifference(stPptnRLast.getTm(), stPptnR.getTm());
// 两条数据间需要增补几条
int floorNum = (int) Math.floor(diffHours / dt);
for (int j = 0; j < floorNum; j++) {
BigDecimal add = new BigDecimal(drp).divide(BigDecimal.valueOf(floorNum), 2, BigDecimal.ROUND_HALF_UP);
pResultList.add(add.toString());
}
if (ObjectUtils.isEmpty(forecastPa)) {
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。");
}
double[] PList = pResultList.stream().mapToDouble(Double::parseDouble).toArray();
// 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 = pptnRAllList.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]);
}
List<String> pForecastList = retMap.get("listForForecast").stream().map(s -> s.getDrp()).collect(Collectors.toList());
Map<String, String> pRealMap = retMap.get("listForReal").stream().collect(Collectors.toMap(pptnR -> sdfMinute.format(pptnR.getTm()), StPptnR::getDrp));
double[] PList = pForecastList.stream().mapToDouble(Double::parseDouble).toArray();
// 预测执行
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, "716153201");
forecastPa.getPa().doubleValue(), PList, u, attResBase.getStcd());
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());
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));
forecastVoList = forecastVoList.subList(0, PList.length);
for (int j = 0; j < forecastVoList.size(); j++) {
FloodAlgorithemVo floodAlgorithemVo = forecastVoList.get(j);
String dateStr = floodAlgorithemVo.getDateStr();
ForecastResultVo resultVo = new ForecastResultVo();
resultVo.setTm(floodAlgorithemVo.getDateStr());
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();// 先以预测水位作为下一次预测段起始值
if (j < realRsvrList.size()) {
BigDecimal realSwHValue = new BigDecimal(realRsvrList.get(j).getRz());
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
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
@ -246,7 +256,12 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
}
}
}
resultVo.setDrp(floodAlgorithemVo.getDrp());
BigDecimal drp = new BigDecimal(pRealMap.get(dateMinuteStr));// 根据时间取更准确
if (drp.compareTo(BigDecimal.ZERO) < 0) {
resultVo.setDrp(null);
} else {
resultVo.setDrp(drp);
}
Date dateTm = sdf.parse(floodAlgorithemVo.getDateStr());
resultVo.setIspreDrp(dateTm.compareTo(nowHourTime) <= 0 ? "0" : "1");// 0：真实 1：预测
resultVo.setR(floodAlgorithemVo.getR());
@ -357,6 +372,76 @@ public class ForecastResultsService extends ServiceImpl<ForecastResultsMapper, F
return resultList;
}
/**
* @description: 根据△T来整编雨量数据
* @param filterList
* @param dt
* @return: java.util.List<com.gunshi.project.xyt.model.StPptnR>
* @auther: cxw
*/
private Map<String, List<StPptnR>> reorganizePptnRData(List<StPptnR> filterList, double dt, Date startTm, Date endTm) {
Map<String, List<StPptnR>> retMap = new HashMap<>();
Map<String, String> tmDrpMap = filterList.stream().collect(Collectors.toMap(pptnR -> sdfMinute.format(pptnR.getTm()), StPptnR::getDrp));
List<StPptnR> listForForecast = new ArrayList<>();// 传给预测程序使用，缺失的数据为0
List<StPptnR> listForReal = new ArrayList<>();// 返回给前端数据使用，缺失的数据为null
Calendar calendar = Calendar.getInstance();
calendar.setTime(startTm);
Date dataTm = calendar.getTime();
// 使用时间一直往后加时间
while (dataTm.compareTo(endTm) < 0) {
// 时间加1小时，得到应该拆数据的时间，后面往前推
calendar.add(Calendar.HOUR_OF_DAY, 1);
String shareDrp = "";// 应该分的drp
// 如果下一小时不为空
if (tmDrpMap.containsKey(sdfMinute.format(calendar.getTime()))) {
StPptnR stPptnRHalf = new StPptnR();
StPptnR stPptnRHour = new StPptnR();
stPptnRHour.setTm(calendar.getTime());// 整点时间
String dataTmDrpHalf = tmDrpMap.get(sdfMinute.format(calendar.getTime()));
BigDecimal drp = new BigDecimal(dataTmDrpHalf).divide(new BigDecimal(2), 2, BigDecimal.ROUND_HALF_UP);
shareDrp = String.valueOf(drp);
stPptnRHalf.setDrp(shareDrp);
stPptnRHour.setDrp(shareDrp);
// 往前推半小时
calendar.add(Calendar.MINUTE, -(int) (dt * 60));
stPptnRHalf.setTm(calendar.getTime());
// 先存半小时数据
listForForecast.add(stPptnRHalf);
listForReal.add(stPptnRHalf);
// 再存整小时数据
listForForecast.add(stPptnRHour);
listForReal.add(stPptnRHour);
} else {
StPptnR stPptnRHalfForecast = new StPptnR();
StPptnR stPptnRHourForecast = new StPptnR();
StPptnR stPptnRHalfReal = new StPptnR();
StPptnR stPptnRHourReal = new StPptnR();
stPptnRHourForecast.setTm(calendar.getTime());// 整点时间
stPptnRHourReal.setTm(calendar.getTime());// 整点时间
// 往前推半小时
calendar.add(Calendar.MINUTE, -(int) (dt * 60));
stPptnRHalfForecast.setTm(calendar.getTime());
stPptnRHalfReal.setTm(calendar.getTime());
// 先存半小时数据
stPptnRHalfForecast.setDrp("0.00");
listForForecast.add(stPptnRHalfForecast);
stPptnRHalfReal.setDrp("-1");
listForReal.add(stPptnRHalfReal);
// 再存整小时数据
stPptnRHourForecast.setDrp("0.00");
listForForecast.add(stPptnRHourForecast);
stPptnRHourReal.setDrp("-1");
listForReal.add(stPptnRHourReal);
}
// 往后推半小时复位
calendar.add(Calendar.MINUTE, (int) (dt * 60));
dataTm = calendar.getTime();
}
retMap.put("listForForecast", listForForecast);
retMap.put("listForReal", listForReal);
return retMap;
}
/**
* @description: 将两个时间按照早八点分割成多段
* @param startDate

8
src/main/java/com/gunshi/project/xyt/timetask/DataTask.java
View File

@ -190,7 +190,7 @@ public class DataTask {
calendar.add(Calendar.DATE, -40);
} else {
calendar.setTime(stm);
calendar.add(Calendar.HOUR, 1);
calendar.add(Calendar.HOUR_OF_DAY, 1);
}
stm = calendar.getTime();
Response resp = client.newCall(new Request.Builder().url(owrsvrPath + hbskpphisRoute)
@ -227,7 +227,7 @@ public class DataTask {
* @date: 2024-07-11, 周四, 14:21:35
*/
@Async
@Scheduled(fixedRate = 5, timeUnit = TimeUnit.MINUTES)
@Scheduled(cron = "0 30 8 * * ?")
public void getSkYqDayData() {
Date now = new Date();
System.out.println("雨情按天定时任务，执行时间：" + sdf.format(now));
@ -352,7 +352,7 @@ public class DataTask {
calendar.add(Calendar.DATE, -40);
} else {
calendar.setTime(stm);
calendar.add(Calendar.HOUR, 1);
calendar.add(Calendar.HOUR_OF_DAY, 1);
}
stm = calendar.getTime();
Response resp = client.newCall(new Request.Builder().url(owrsvrPath + hbskzzhisRoute)
@ -453,7 +453,7 @@ public class DataTask {
calendar.add(Calendar.DATE, -40);
} else {
calendar.setTime(stm);
calendar.add(Calendar.HOUR, 1);
calendar.add(Calendar.HOUR_OF_DAY, 1);
}
stm = calendar.getTime();
Response resp = client.newCall(new Request.Builder().url(owrsvrPath + hbskpichisRoute)

103
src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java
View File

@ -7,10 +7,12 @@ import com.gunshi.algorithm.RunoffService;
import com.gunshi.project.xyt.model.ForecastK;
import com.gunshi.project.xyt.model.ForecastPa;
import com.gunshi.project.xyt.model.ForecastUseparam;
import com.gunshi.project.xyt.model.StStbprpB;
import com.gunshi.project.xyt.service.ForecastKService;
import com.gunshi.project.xyt.service.ForecastPaService;
import com.gunshi.project.xyt.service.ForecastUseparamService;
import com.gunshi.project.xyt.service.StPptnRService;
import com.gunshi.project.xyt.service.StStbprpBService;
import jakarta.annotation.PostConstruct;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
@ -56,6 +58,9 @@ public class PaDataTask {
@Autowired
private StPptnRService stPptnRService;
@Autowired
private StStbprpBService stStbprpBService;
/**
* @description: 每天8点30计算的Pa
* @param
@ -73,54 +78,58 @@ public class PaDataTask {
// 获取配置参数
List<ForecastUseparam> paramList = forecastUseparamService.list(new QueryWrapper<ForecastUseparam>().isNotNull("param_code").isNotNull("param_value"));
List<ForecastK> kList = forecastKService.list();
// 获取最新pa
ForecastPa forecastPaLast = forecastPaService.getOne(new QueryWrapper<ForecastPa>().orderBy(true, false, "tm").last("limit 1"));
if (CollectionUtils.isNotEmpty(paramList) && CollectionUtils.isNotEmpty(kList) && ObjectUtils.isNotEmpty(forecastPaLast) && !forecastPaLast.getTm().equals(sdfDay.format(nowTime))) {
String lastTm = forecastPaLast.getTm();
// 获取空缺时间的所有降雨，当天8点到第二天8点间的drp和
List<Map<String, Object>> mapList = stPptnRService.getPptnRDataList("716153201", lastTm);
Map<String, Object> pptnrMap;
if (CollectionUtils.isNotEmpty(mapList)) {
pptnrMap = mapList.stream().collect(Collectors.toMap(map -> (String) map.get("tm"), map -> map.get("drp")));
} else {
return;
}
Map<Integer, BigDecimal> kMap = kList.stream().collect(Collectors.toMap(ForecastK::getMonth, ForecastK::getKValue));
Map<String, String> paramMap = paramList.stream().collect(Collectors.toMap(ForecastUseparam::getParamCode, ForecastUseparam::getParamValue));
double Im = Double.parseDouble(paramMap.get("Im"));// 土壤含水量最大值(最大初损值)Im
// 第一次的pa0是最新一条的pa
List<ForecastPa> list = new ArrayList<>();
ForecastPa forecastPa = null;
int i = 0;
while (!lastTm.equals(sdfDay.format(nowTime))){
double lastPa0 = forecastPaLast.getPa().doubleValue();
double lastPt0;
// 第一次使用最新一条的降雨
if(i == 0){
lastPt0 = forecastPaLast.getPt0().doubleValue();
i ++;
} else {
lastPt0 = Double.valueOf(ObjectUtils.isEmpty(pptnrMap.get(lastTm)) ? "0.0" : pptnrMap.get(lastTm).toString());
// 查询所有需要统计pa值的站点
List<StStbprpB> stStbprpBList = stStbprpBService.list(new QueryWrapper<StStbprpB>().eq("source", "SK"));
if (CollectionUtils.isNotEmpty(stStbprpBList)) {
for (StStbprpB stb : stStbprpBList) {
String stcd = stb.getStcd();
// 获取最新pa
ForecastPa forecastPaLast = forecastPaService.getOne(new QueryWrapper<ForecastPa>().eq("stcd", stcd).orderBy(true, false, "tm").last("limit 1"));
if (CollectionUtils.isNotEmpty(paramList) && CollectionUtils.isNotEmpty(kList) && ObjectUtils.isNotEmpty(forecastPaLast) && !forecastPaLast.getTm().equals(sdfDay.format(nowTime))) {
Calendar calendar2 = Calendar.getInstance();
calendar2.setTime(sdfDay.parse(forecastPaLast.getTm()));
calendar2.add(Calendar.DAY_OF_MONTH, -3);
String searchTm = sdfDay.format(calendar2.getTime());
String lastTm = forecastPaLast.getTm();
// 获取空缺时间的所有降雨，当天8点到第二天8点间的drp和
List<Map<String, Object>> mapList = stPptnRService.getPptnRDataList(stcd, searchTm);
Map<String, Object> pptnrMap;
if (CollectionUtils.isNotEmpty(mapList)) {
pptnrMap = mapList.stream().collect(Collectors.toMap(map -> (String) map.get("tm"), map -> map.get("drp")));
} else {
return;
}
Map<Integer, BigDecimal> kMap = kList.stream().collect(Collectors.toMap(ForecastK::getMonth, ForecastK::getKValue));
Map<String, String> paramMap = paramList.stream().collect(Collectors.toMap(ForecastUseparam::getParamCode, ForecastUseparam::getParamValue));
double Im = Double.parseDouble(paramMap.get("Im"));// 土壤含水量最大值(最大初损值)Im
// 第一次的pa0是最新一条的pa
List<ForecastPa> list = new ArrayList<>();
ForecastPa forecastPa = null;
int i = 0;
while (!lastTm.equals(sdfDay.format(nowTime))) {
double lastPa0 = forecastPaLast.getPa().doubleValue();
double lastPt0 = Double.valueOf(ObjectUtils.isEmpty(pptnrMap.get(lastTm)) ? "0.0" : pptnrMap.get(lastTm).toString());
forecastPa = new ForecastPa();
// 最新加1天
calendar.setTime(sdfDay.parse(lastTm));
calendar.add(Calendar.DAY_OF_MONTH, 1);
lastTm = sdfDay.format(calendar.getTime());
double k = kMap.get(Integer.valueOf(lastTm.substring(5, 7))).doubleValue();
double pa = RunoffService.PaCaculate(k, lastPa0, lastPt0, Im);
forecastPa.setStcd(stcd);
forecastPa.setTm(lastTm);
forecastPa.setK(new BigDecimal(k).setScale(2, BigDecimal.ROUND_HALF_UP));
forecastPa.setPa0(new BigDecimal(lastPa0));
forecastPa.setIm(new BigDecimal(Im));
forecastPa.setPt0(new BigDecimal(lastPt0).setScale(2, BigDecimal.ROUND_HALF_UP));
forecastPa.setPa(new BigDecimal(pa));
list.add(forecastPa);
forecastPaLast = forecastPa;
}
if (CollectionUtils.isNotEmpty(list)) {
forecastPaService.saveBatch(list);
}
}
forecastPa = new ForecastPa();
// 最新加1天
calendar.setTime(sdfDay.parse(lastTm));
calendar.add(Calendar.DAY_OF_MONTH, 1);
lastTm = sdfDay.format(calendar.getTime());
double k = kMap.get(Integer.valueOf(lastTm.substring(5, 7))).doubleValue();
double pa = RunoffService.PaCaculate(k, lastPa0, lastPt0, Im);
forecastPa.setStcd("716153201");
forecastPa.setTm(lastTm);
forecastPa.setK(new BigDecimal(k).setScale(2, BigDecimal.ROUND_HALF_UP));
forecastPa.setPa0(new BigDecimal(lastPa0));
forecastPa.setIm(new BigDecimal(Im));
forecastPa.setPt0(new BigDecimal(lastPt0).setScale(2, BigDecimal.ROUND_HALF_UP));
forecastPa.setPa(new BigDecimal(pa));
list.add(forecastPa);
forecastPaLast = forecastPa;
}
if(CollectionUtils.isNotEmpty(list)){
forecastPaService.saveBatch(list);
}
}
}