From f853b02cb7b265379eceb2f0e3c38f9d63bb1b21 Mon Sep 17 00:00:00 2001
From: 潘志宝 <979469083@qq.com>
Date: 星期一, 06 一月 2025 17:55:25 +0800
Subject: [PATCH] 执行调度模型 默认时间

---
 iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/api/MdkApiImpl.java |  285 ++++++++++++++++++++++++++++++++++++++++++++++-----------
 1 files changed, 230 insertions(+), 55 deletions(-)

diff --git a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/api/MdkApiImpl.java b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/api/MdkApiImpl.java
index 8f73d14..9a07f72 100644
--- a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/api/MdkApiImpl.java
+++ b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/api/MdkApiImpl.java
@@ -1,38 +1,40 @@
 package com.iailab.module.model.api;
 
 import com.alibaba.fastjson.JSON;
-import com.iailab.framework.common.util.object.ConvertUtils;
+import com.alibaba.fastjson.JSONObject;
+import com.iailab.module.data.api.point.DataPointApi;
+import com.iailab.module.data.api.point.dto.ApiPointValueWriteDTO;
+import com.iailab.module.model.api.mcs.dto.StScheduleModelOutDTO;
 import com.iailab.module.model.api.mdk.MdkApi;
 import com.iailab.module.model.api.mdk.dto.*;
-import com.iailab.framework.common.pojo.CommonResult;
+import com.iailab.module.model.common.enums.IsWriteEnum;
+import com.iailab.module.model.common.enums.ModelOutResultType;
+import com.iailab.module.model.common.enums.OutResultType;
 import com.iailab.module.model.mcs.pre.entity.DmModuleEntity;
 import com.iailab.module.model.mcs.pre.service.DmModuleService;
 import com.iailab.module.model.mcs.pre.service.MmPredictItemService;
-import com.iailab.module.model.mdk.factory.ItemEntityFactory;
-import com.iailab.module.model.mdk.factory.PredictItemFactory;
-import com.iailab.module.model.mdk.predict.PredictItemHandler;
+import com.iailab.module.model.mcs.sche.service.StScheduleModelOutService;
+import com.iailab.module.model.mcs.sche.service.StScheduleRecordService;
+import com.iailab.module.model.mcs.sche.service.StScheduleSchemeService;
 import com.iailab.module.model.mdk.predict.PredictModuleHandler;
 import com.iailab.module.model.mdk.predict.PredictResultHandler;
+import com.iailab.module.model.mdk.schedule.ScheduleModelHandler;
 import com.iailab.module.model.mdk.vo.DataValueVO;
 import com.iailab.module.model.mdk.vo.ItemVO;
 import com.iailab.module.model.mdk.vo.PredictResultVO;
+import com.iailab.module.model.mdk.vo.ScheduleResultVO;
 import lombok.extern.slf4j.Slf4j;
 import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.data.redis.core.RedisTemplate;
 import org.springframework.util.CollectionUtils;
 import org.springframework.validation.annotation.Validated;
-import org.springframework.web.bind.annotation.RequestBody;
 import org.springframework.web.bind.annotation.RestController;
 
-import javax.validation.Valid;
-
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
+import java.util.*;
+import java.util.concurrent.TimeUnit;
 import java.util.stream.Collectors;
 
-import static com.iailab.framework.common.pojo.CommonResult.error;
-import static com.iailab.framework.common.pojo.CommonResult.success;
+import static com.iailab.module.model.common.enums.ModelOutResultType.D;
 
 /**
  * @author PanZhibao
@@ -54,13 +56,27 @@
     private PredictModuleHandler predictModuleHandler;
 
     @Autowired
-    private ItemEntityFactory itemEntityFactory;
-
-    @Autowired
-    private PredictItemFactory predictItemFactory;
-
-    @Autowired
     private PredictResultHandler predictResultHandler;
+
+    @Autowired
+    private ScheduleModelHandler scheduleModelHandler;
+
+    @Autowired
+    private StScheduleRecordService stScheduleRecordService;
+
+    @Autowired
+    private StScheduleSchemeService stScheduleSchemeService;
+
+    @Autowired
+    private StScheduleModelOutService stScheduleModelOutService;
+
+    @Autowired
+    private DataPointApi dataPointApi;
+
+    @Autowired
+    private RedisTemplate<String, Object> redisTemplate;
+
+    public static final long offset = 60 * 3L;
 
     /**
      * 按模块预测
@@ -69,8 +85,11 @@
      * @return
      */
     @Override
-    public CommonResult<MdkPredictModuleRespDTO> predictModule(MdkPredictReqDTO reqDTO) {
+    public MdkPredictModuleRespDTO predictModule(MdkPredictReqDTO reqDTO) {
         MdkPredictModuleRespDTO resp = new MdkPredictModuleRespDTO();
+        resp.setPredictTime(reqDTO.getPredictTime());
+        resp.setModuleType(reqDTO.getModuleType());
+
         Map<String, MdkPredictItemRespDTO> predictItemRespMap = new HashMap<>();
         try {
             if (reqDTO.getPredictTime() == null) {
@@ -79,6 +98,11 @@
             if (reqDTO.getModuleType() == null) {
                 throw new Exception("ModuleType不能为空");
             }
+            Calendar calendar = Calendar.getInstance();
+            calendar.setTime(reqDTO.getPredictTime());
+            calendar.set(Calendar.MILLISECOND, 0);
+            calendar.set(Calendar.SECOND, 0);
+            reqDTO.setPredictTime(calendar.getTime());
             log.info("预测参数:" + JSON.toJSONString(reqDTO));
             MdkPredictModuleRespDTO result = new MdkPredictModuleRespDTO();
             result.setPredictTime(reqDTO.getPredictTime());
@@ -91,26 +115,48 @@
                     intervalTime = (int) (reqDTO.getPredictTime().getTime() - module.getPredicttime().getTime()) / (1000 * 60);
                 }
                 List<ItemVO> predictItemList = mmPredictItemService.getByModuleId(module.getId());
-                Map<String, PredictResultVO> predictResultMap = predictModuleHandler.predict(predictItemList, reqDTO.getPredictTime(), intervalTime);
+                Map<String, PredictResultVO> predictResultMap = new HashMap<>(predictItemList.size());
+                // 分组,先运行normal预测项,再将结果传递给merge预测项
+                List<ItemVO> normalItems = predictItemList.stream().filter(e -> e.getItemType().equals("NormalItem")).collect(Collectors.toList());
+                if (!CollectionUtils.isEmpty(normalItems)) {
+                    predictModuleHandler.predict(normalItems, reqDTO.getPredictTime(), intervalTime, predictResultMap);
+                    List<ItemVO> mergeItems = predictItemList.stream().filter(e -> e.getItemType().equals("MergeItem")).collect(Collectors.toList());
+                    if (!CollectionUtils.isEmpty(mergeItems)) {
+                        predictModuleHandler.predict(mergeItems, reqDTO.getPredictTime(), intervalTime, predictResultMap);
+                    }
+                }
+                // 更新Module时间
+                dmModuleService.updatePredictTime(module.getId(), reqDTO.getPredictTime());
+                if (reqDTO.getIsResult() == null || !reqDTO.getIsResult()) {
+                    return resp;
+                }
                 for (Map.Entry<String, PredictResultVO> entry : predictResultMap.entrySet()) {
-                    List<MdkPredictDataDTO> predictData = entry.getValue().getPredictList().stream().map(t-> {
-                        MdkPredictDataDTO dto1 = new MdkPredictDataDTO();
-                        dto1.setDataTime(t.getDataTime());
-                        dto1.setDataValue(t.getDataValue());
-                        return dto1;
-                    }).collect(Collectors.toList());
                     MdkPredictItemRespDTO itemResp = new MdkPredictItemRespDTO();
-                    itemResp.setItemId(entry.getValue().getPredictId());
-                    itemResp.setPredictData(predictData);
+                    itemResp.setItemId(entry.getKey());
+                    itemResp.setPredictTime(reqDTO.getPredictTime());
+                    Map<String, List<MdkPredictDataDTO>> itemPredictData = new HashMap<>();
+
+                    Map<String, List<DataValueVO>> predictLists = predictResultHandler.convertToPredictData2(entry.getValue());
+                    for (Map.Entry<String, List<DataValueVO>> dataListEntry : predictLists.entrySet()) {
+                        List<MdkPredictDataDTO> predictData = dataListEntry.getValue().stream().map(t -> {
+                            MdkPredictDataDTO dto1 = new MdkPredictDataDTO();
+                            dto1.setDataTime(t.getDataTime());
+                            dto1.setDataValue(t.getDataValue());
+                            return dto1;
+                        }).collect(Collectors.toList());
+                        itemPredictData.put(dataListEntry.getKey(), predictData);
+                    }
+                    itemResp.setPredictData(itemPredictData);
                     predictItemRespMap.put(entry.getKey(), itemResp);
                 }
             }
             log.info("预测计算结束: " + System.currentTimeMillis());
         } catch (Exception ex) {
-            return error(999, ex.getMessage());
+            ex.printStackTrace();
+            return resp;
         }
         resp.setPredictItemRespMap(predictItemRespMap);
-        return success(resp);
+        return resp;
     }
 
     /**
@@ -120,31 +166,36 @@
      * @return
      */
     @Override
-    public CommonResult<MdkPredictItemRespDTO> predictItem(@Valid @RequestBody MdkPredictReqDTO reqDTO) {
+    public MdkPredictItemRespDTO predictItem(MdkPredictReqDTO reqDTO) {
         MdkPredictItemRespDTO resp = new MdkPredictItemRespDTO();
-
         try {
-            log.info("预测计算开始: " + System.currentTimeMillis());
-            List<MdkPredictDataDTO> predictData = new ArrayList<>();
-            ItemVO predictItem = itemEntityFactory.getItemByItemNo(reqDTO.getItemNo());
-            PredictItemHandler predictItemHandler = (PredictItemHandler)predictItemFactory.create(predictItem.getId());
-            PredictResultVO predictResult = predictItemHandler.predict(reqDTO.getPredictTime(), predictItem);
-            Map<String, List<DataValueVO>> resultMap = predictResultHandler.convertToPredictData(predictResult);
-            if (!CollectionUtils.isEmpty(resultMap)) {
-                for (Map.Entry<String, List<DataValueVO>> entry : resultMap.entrySet()) {
-                    predictData = ConvertUtils.sourceToTarget(entry.getValue(), MdkPredictDataDTO.class);
-                }
+
+            ItemVO itemByItemNo = mmPredictItemService.getItemByItemNo(reqDTO.getItemNo());
+            List<ItemVO> predictItemList = new ArrayList<>();
+            predictItemList.add(itemByItemNo);
+            Map<String, PredictResultVO> predictResultMap = new HashMap<>(predictItemList.size());
+            predictModuleHandler.predict(predictItemList, reqDTO.getPredictTime(), 0, predictResultMap);
+
+            Map<String, List<MdkPredictDataDTO>> itemPredictData = new HashMap<>();
+
+            Map<String, List<DataValueVO>> predictLists = predictResultHandler.convertToPredictData2(predictResultMap.get(reqDTO.getItemNo()));
+            for (Map.Entry<String, List<DataValueVO>> dataListEntry : predictLists.entrySet()) {
+                List<MdkPredictDataDTO> predictData = dataListEntry.getValue().stream().map(t -> {
+                    MdkPredictDataDTO dto1 = new MdkPredictDataDTO();
+                    dto1.setDataTime(t.getDataTime());
+                    dto1.setDataValue(t.getDataValue());
+                    return dto1;
+                }).collect(Collectors.toList());
+                itemPredictData.put(dataListEntry.getKey(), predictData);
             }
-            resp.setPredictData(predictData);
-            resp.setItemId(predictItem.getId());
+            resp.setItemId(reqDTO.getItemNo());
             resp.setPredictTime(reqDTO.getPredictTime());
-            log.info("预测计算结束: " + System.currentTimeMillis());
-        } catch (Exception ex) {
-            log.info("预测计算异常: " + System.currentTimeMillis());
-            ex.printStackTrace();
+            resp.setPredictData(itemPredictData);
+        } catch (Exception e) {
+            throw new RuntimeException(e);
         }
 
-        return success(resp);
+        return resp;
     }
 
     /**
@@ -154,10 +205,10 @@
      * @return
      */
     @Override
-    public CommonResult<Boolean> predictAutoAdjust(@Valid @RequestBody MdkPredictReqDTO reqDTO) {
+    public Boolean predictAutoAdjust(MdkPredictReqDTO reqDTO) {
 
 
-        return success(true);
+        return true;
     }
 
     /**
@@ -167,9 +218,133 @@
      * @return
      */
     @Override
-    public CommonResult<MdkScheduleRespDTO> doSchedule(@Valid @RequestBody MdkScheduleReqDTO reqDTO) {
+    public MdkScheduleRespDTO doSchedule(MdkScheduleReqDTO reqDTO) {
         MdkScheduleRespDTO resp = new MdkScheduleRespDTO();
+        resp.setScheduleCode(reqDTO.getScheduleCode());
+        resp.setScheduleTime(reqDTO.getScheduleTime());
+        try {
+            log.info("调度计算开始: " + System.currentTimeMillis());
+            log.info("reqDTO=" + JSON.toJSONString(reqDTO));
+            ScheduleResultVO scheduleResult = scheduleModelHandler.doSchedule(reqDTO.getScheduleCode(), reqDTO.getScheduleTime(),
+                    reqDTO.getDynamicDataLength(), reqDTO.getDynamicSettings());
+            resp.setStatusCode(scheduleResult.getResultCode());
+            resp.setResult(scheduleResult.getResult());
+            stScheduleRecordService.create(scheduleResult);
+            stScheduleSchemeService.updateTime(scheduleResult.getSchemeId(), scheduleResult.getScheduleTime(), scheduleResult.getResultCode());
+            log.info("预测计算结束: " + System.currentTimeMillis());
+        } catch (Exception ex) {
+            log.info("调度计算异常: " + System.currentTimeMillis());
+            ex.printStackTrace();
+            return resp;
+        }
+        return resp;
+    }
 
-        return success(resp);
+    /**
+     * 执行调度模型
+     *
+     * @param reqDTO
+     * @return
+     */
+    @Override
+    public MdkScheduleRespDTO runSchedule(MdkScheduleReqDTO reqDTO) {
+        MdkScheduleRespDTO resp = new MdkScheduleRespDTO();
+        if (reqDTO.getScheduleTime() == null) {
+            Calendar calendar = Calendar.getInstance();
+            calendar.set(Calendar.MILLISECOND, 0);
+            calendar.set(Calendar.SECOND, 0);
+            reqDTO.setScheduleTime(calendar.getTime());
+        }
+        resp.setScheduleCode(reqDTO.getScheduleCode());
+        resp.setScheduleTime(reqDTO.getScheduleTime());
+        String catchKey = "ScheduleResult:" + reqDTO.getScheduleCode();
+        try {
+            if (redisTemplate.hasKey(catchKey)) {
+                log.info("查找调度结果缓存: " + catchKey);
+                return JSON.parseObject(JSONObject.toJSONString(redisTemplate.opsForValue().get(catchKey)), MdkScheduleRespDTO.class);
+            }
+            log.info("调度计算开始: " + System.currentTimeMillis());
+            log.info("reqDTO=" + JSON.toJSONString(reqDTO));
+            ScheduleResultVO scheduleResult = scheduleModelHandler.doSchedule(reqDTO.getScheduleCode(), reqDTO.getScheduleTime(),
+                    reqDTO.getDynamicDataLength(), reqDTO.getDynamicSettings());
+            resp.setStatusCode(scheduleResult.getResultCode());
+            resp.setResult(scheduleResult.getResult());
+            redisTemplate.opsForValue().set(catchKey, JSON.toJSONString(resp), offset, TimeUnit.SECONDS);
+            stScheduleSchemeService.updateTime(scheduleResult.getSchemeId(), scheduleResult.getScheduleTime(), scheduleResult.getResultCode());
+            log.info("预测计算结束: " + System.currentTimeMillis());
+        } catch (Exception ex) {
+            log.info("调度计算异常: " + System.currentTimeMillis());
+            ex.printStackTrace();
+            return resp;
+        }
+        return resp;
+    }
+
+    @Override
+    public Boolean scheduleModelOut(MdkScheduleRespDTO dto) {
+        String modelId = stScheduleSchemeService.getByCode(dto.getScheduleCode()).getModelId();
+        Map<String, Object> result = dto.getResult();
+        List<StScheduleModelOutDTO> list = stScheduleModelOutService.list(modelId);
+        try {
+            for (StScheduleModelOutDTO stScheduleModelOutDTO : list) {
+                double value = 0;
+                //判断点位是否下发
+                if (stScheduleModelOutDTO.getIsWrite().equals(IsWriteEnum.NOTWRITE.value())) {
+                    continue;
+                }
+                //返回结果是否存在
+                if (result.get(stScheduleModelOutDTO.getResultKey()) == null) {
+                    log.error(result.get(stScheduleModelOutDTO.getResultKey()) + "resultKey匹配失败");
+                    continue;
+                }
+                Object resultValue = result.get(stScheduleModelOutDTO.getResultKey());
+                //判断解析方式
+                ModelOutResultType modelOutResultType = ModelOutResultType.getEumByCode(stScheduleModelOutDTO.getResultType());
+                switch (modelOutResultType) {
+                    case D:
+                        value = (Double) resultValue;
+                        break;
+                    case D1:
+                        ArrayList<Double> doubleList = (ArrayList<Double>) resultValue;
+                        double[] array1 = new double[doubleList.size()];
+                        for (int i = 0; i < doubleList.size(); i++) {
+                            array1[i] = doubleList.get(i);
+                        }
+                        if (stScheduleModelOutDTO.getResultPort() < array1.length) {
+                            value = array1[stScheduleModelOutDTO.getResultPort()];
+                        } else {
+                            log.error(result.get(stScheduleModelOutDTO.getResultKey()) + "下角标超限");
+                        }
+                        break;
+                    case D2:
+                        ArrayList<ArrayList<Double>> doubleListList = (ArrayList<ArrayList<Double>>) resultValue;
+                        double[][] array2 = new double[doubleListList.size()][];
+                        for (int i = 0; i < doubleListList.size(); i++) {
+                            ArrayList<Double> doubleList2 = doubleListList.get(i);
+                            array2[i] = new double[doubleList2.size()];
+                            for (int j = 0; j < doubleList2.size(); j++) {
+                                array2[i][j] = doubleList2.get(j);
+                            }
+                        }
+                        if (stScheduleModelOutDTO.getResultPort() < array2.length && stScheduleModelOutDTO.getResultIndex() < array2[stScheduleModelOutDTO.getResultPort()].length) {
+                            value = array2[stScheduleModelOutDTO.getResultPort()][stScheduleModelOutDTO.getResultIndex()];
+                        } else {
+                            log.error(result.get(stScheduleModelOutDTO.getResultKey()) + "下标超限");
+                        }
+                        break;
+                }
+                //下发到point点位
+                ApiPointValueWriteDTO ApiPointValueWriteDTO = new ApiPointValueWriteDTO();
+                ApiPointValueWriteDTO.setPointNo(stScheduleModelOutDTO.getPointNo());
+                ApiPointValueWriteDTO.setValue(value);
+                if (!dataPointApi.writePointRealValue(ApiPointValueWriteDTO)) {
+                    log.error(result.get(stScheduleModelOutDTO.getResultKey()) + "下发数据异常");
+                }
+            }
+        } catch (Exception ex) {
+            log.error("下发数据异常");
+            ex.printStackTrace();
+        }
+        return true;
     }
 }
\ No newline at end of file

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