From 75968f74bc7b2c66d0eb7089ea0ed049b8b8f305 Mon Sep 17 00:00:00 2001 From: chenxiwang <1520264117@qq.com> Date: Fri, 16 Aug 2024 16:50:06 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E5=A4=8D=E6=B4=AA=E6=B0=B4=E9=A2=84?= =?UTF-8?q?=E6=8A=A5=E9=94=99=E8=AF=AF?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../project/xyt/schedule/TaskGroupJob.java | 5 +- .../xyt/service/ForecastResultsService.java | 12 ++-- .../project/xyt/timetask/PaDataTask.java | 70 ++++++++++++++++++- 3 files changed, 79 insertions(+), 8 deletions(-) diff --git a/src/main/java/com/gunshi/project/xyt/schedule/TaskGroupJob.java b/src/main/java/com/gunshi/project/xyt/schedule/TaskGroupJob.java index 9132604..b0eb0ae 100644 --- a/src/main/java/com/gunshi/project/xyt/schedule/TaskGroupJob.java +++ b/src/main/java/com/gunshi/project/xyt/schedule/TaskGroupJob.java @@ -60,13 +60,14 @@ public class TaskGroupJob implements Job { @Override public void execute(JobExecutionContext context) throws JobExecutionException { + Date nowDate = new Date(); JobDataMap jdMap = context.getJobDetail().getJobDataMap(); String jobId = (String) jdMap.get("jobId"); ForecastTask forecastTask = (ForecastTask) jdMap.get("forecastTask"); - log.info("{}----TaskGroupJob-计划执行开始===>jobId:{}", sdf.format(LocalDateTime.now()), jobId); + log.info("{}----TaskGroupJob-计划执行开始===>jobId:{}", sdf.format(nowDate), jobId); try { // 根据执行时间、预热期、预见期获取对应的预报、开始、结束时间 - Date nowTime = sdfMinute.parse(sdf.format(new Date())); + Date nowTime = sdfMinute.parse(sdf.format(nowDate)); Date forecastTime = nowTime; Date startTime; Date endTime; diff --git a/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java b/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java index 867411e..4090186 100644 --- a/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java +++ b/src/main/java/com/gunshi/project/xyt/service/ForecastResultsService.java @@ -200,15 +200,17 @@ public class ForecastResultsService extends ServiceImpl resultList = reorganizeRsvrRData(rsvrRRealList, dt); List periods = splitByDay8To8(startTime, endTime); for (Date[] period : periods) { + 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])) { - cal.setTime(period[0]); // 将日期往前推一天 - cal.add(Calendar.DATE, -1); + calNew.add(Calendar.DATE, -1); } - ForecastPa forecastPa = paMap.get(sdfDay.format(cal.getTime())); + ForecastPa forecastPa = paMap.get(sdfDay.format(calNew.getTime())); 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。"); + 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 @@ -290,7 +292,7 @@ public class ForecastResultsService extends ServiceImpl getForecastDrpData(Date now, String stcd) { + public List getForecastDrpData(Date now, String stcd) { List pptnRFutureList = new ArrayList<>(); StStbprpB stStbprpB = stStbprpBService.getOne(new QueryWrapper().eq("stcd", stcd)); String tm = "";// 时间格式应为：YYYYMMDDHH其中HH只能为08或20，例如2023062908 diff --git a/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java b/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java index b01a4cd..551a56e 100644 --- a/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java +++ b/src/main/java/com/gunshi/project/xyt/timetask/PaDataTask.java @@ -7,9 +7,11 @@ 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.StPptnR; 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.ForecastResultsService; import com.gunshi.project.xyt.service.ForecastUseparamService; import com.gunshi.project.xyt.service.StPptnRService; import com.gunshi.project.xyt.service.StStbprpBService; @@ -44,8 +46,12 @@ import java.util.stream.Collectors; @Profile("prod") public class PaDataTask { + private static SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss"); + private static SimpleDateFormat sdfDay = new SimpleDateFormat("yyyy-MM-dd"); + private static SimpleDateFormat eightSdf = new SimpleDateFormat("yyyy-MM-dd 08:00:00"); + @Autowired private ForecastUseparamService forecastUseparamService; @@ -61,6 +67,9 @@ public class PaDataTask { @Autowired private StStbprpBService stStbprpBService; + @Autowired + private ForecastResultsService forecastResultsService; + /** * @description: 每天8点30计算的Pa * @param @@ -81,6 +90,8 @@ public class PaDataTask { // 查询所有需要统计pa值的站点 List stStbprpBList = stStbprpBService.list(new QueryWrapper().eq("source", "SK")); if (CollectionUtils.isNotEmpty(stStbprpBList)) { + // 先删除站点当天的pa，假如已经存在的话（有另一任务，提前算了第二天（此处为当天）的） + forecastPaService.remove(new QueryWrapper().eq("tm", sdfDay.format(nowTime))); for (StStbprpB stb : stStbprpBList) { String stcd = stb.getStcd(); // 获取最新pa @@ -105,7 +116,6 @@ public class PaDataTask { // 第一次的pa0是最新一条的pa List 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()); @@ -134,4 +144,62 @@ public class PaDataTask { } } + /** + * @description: 每天19点到24点每5分钟计算一次第二天的Pa + * @param + * @return: void + * @auther: cxw + * @date: 2024-08-16, 周五, 15:42:13 + */ + @Async + @Scheduled(cron ="0 0/5 20-23 * * ?") + @PostConstruct + public void PaNextDataCalc() throws ParseException { + Date nowTime = new Date(); + // 查询所有需要统计pa值的站点 + List stStbprpBList = stStbprpBService.list(new QueryWrapper().eq("source", "SK")); + if (CollectionUtils.isNotEmpty(stStbprpBList)) { + // 获取配置参数 + List paramList = forecastUseparamService.list(new QueryWrapper().isNotNull("param_code").isNotNull("param_value")); + List kList = forecastKService.list(); + + for (StStbprpB stb : stStbprpBList) { + String stcd = stb.getStcd(); + // 查询第二天的是否已经生成了 + Calendar calendarNext = Calendar.getInstance(); + calendarNext.setTime(nowTime); + calendarNext.add(Calendar.DAY_OF_MONTH, 1); + String nextTimeStr = sdfDay.format(calendarNext.getTime()); + ForecastPa hasPa = forecastPaService.getOne(new QueryWrapper().eq("stcd", stcd).eq("tm", nextTimeStr)); + if(ObjectUtils.isNotEmpty(hasPa)){ + return; + } + // 获取最新pa（当天） + ForecastPa forecastPaLast = forecastPaService.getOne(new QueryWrapper().eq("stcd", stcd).eq("tm", sdfDay.format(nowTime)).last("limit 1")); + if (CollectionUtils.isNotEmpty(paramList) && CollectionUtils.isNotEmpty(kList) && ObjectUtils.isNotEmpty(forecastPaLast)) { + // 获取当天大于08点到执行时间的真实降雨 + List qwExisted = stPptnRService.list(new QueryWrapper().eq("stcd", stcd).gt("tm", sdf.parse(eightSdf.format(nowTime))).le("tm", nowTime).orderBy(true, true, "tm")); + // 获取当天的预测降雨 + List pptnRFutureList = forecastResultsService.getForecastDrpData(nowTime, stcd); + qwExisted.addAll(pptnRFutureList); + Double totalDrp = qwExisted.stream().mapToDouble(x -> Double.valueOf(x.getDrp())).sum(); + ForecastPa forecastPa = new ForecastPa(); + Map kMap = kList.stream().collect(Collectors.toMap(ForecastK::getMonth, ForecastK::getKValue)); + Map 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 + double k = kMap.get(Integer.valueOf(nextTimeStr.substring(5, 7))).doubleValue(); + double pa = RunoffService.PaCaculate(k, Double.parseDouble(forecastPaLast.getPa().toString()), totalDrp, Im); + forecastPa.setStcd(stcd); + forecastPa.setTm(nextTimeStr); + forecastPa.setK(new BigDecimal(k).setScale(2, BigDecimal.ROUND_HALF_UP)); + forecastPa.setPa0(forecastPaLast.getPa()); + forecastPa.setIm(new BigDecimal(Im)); + forecastPa.setPt0(new BigDecimal(totalDrp).setScale(2, BigDecimal.ROUND_HALF_UP)); + forecastPa.setPa(new BigDecimal(pa)); + forecastPaService.save(forecastPa); + } + } + } + } + }