From b4b4596887770a34f80c31ab849068893094dab5 Mon Sep 17 00:00:00 2001
From: 潘志宝 <979469083@qq.com>
Date: 星期一, 24 二月 2025 10:47:08 +0800
Subject: [PATCH] Merge branch 'master' of http://dlindusit.com:53929/r/iailab-plat

---
 iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/sample/PredictSampleDataConstructor.java |  223 ++++++++++++++++++++++++++++++++++++++++---------------
 1 files changed, 161 insertions(+), 62 deletions(-)

diff --git a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/sample/PredictSampleDataConstructor.java b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/sample/PredictSampleDataConstructor.java
index bb4171f..c7792e8 100644
--- a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/sample/PredictSampleDataConstructor.java
+++ b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/sample/PredictSampleDataConstructor.java
@@ -1,22 +1,35 @@
 package com.iailab.module.model.mdk.sample;
 
-import com.iailab.framework.common.util.object.ConvertUtils;
+import cn.hutool.core.date.DateUtil;
+import com.iailab.module.data.api.ind.IndItemApi;
+import com.iailab.module.data.api.ind.dto.ApiIndItemDTO;
+import com.iailab.module.data.api.ind.dto.ApiIndItemQueryDTO;
+import com.iailab.module.data.api.ind.dto.ApiIndItemValueDTO;
+import com.iailab.module.data.api.plan.PlanItemApi;
+import com.iailab.module.data.api.plan.dto.ApiPlanItemDTO;
 import com.iailab.module.data.api.point.DataPointApi;
 import com.iailab.module.data.api.point.dto.ApiPointDTO;
 import com.iailab.module.data.api.point.dto.ApiPointValueDTO;
 import com.iailab.module.data.api.point.dto.ApiPointValueQueryDTO;
+import com.iailab.module.data.common.ApiDataQueryDTO;
+import com.iailab.module.data.common.ApiDataValueDTO;
+import com.iailab.module.model.common.utils.ASCIIUtil;
+import com.iailab.module.model.mcs.pre.service.MmItemOutputService;
+import com.iailab.module.model.mcs.pre.service.MmItemResultJsonService;
 import com.iailab.module.model.mcs.pre.service.MmItemResultService;
-import com.iailab.module.model.mdk.factory.ItemEntityFactory;
+import com.iailab.module.model.mcs.pre.service.MmItemTypeService;
+import com.iailab.module.model.mdk.common.enums.ModelParamType;
 import com.iailab.module.model.mdk.sample.dto.ColumnItem;
 import com.iailab.module.model.mdk.sample.dto.ColumnItemPort;
 import com.iailab.module.model.mdk.sample.dto.SampleData;
 import com.iailab.module.model.mdk.sample.dto.SampleInfo;
 import com.iailab.module.model.mdk.vo.DataValueVO;
-import com.iailab.module.model.mdk.vo.MmItemOutputVO;
+import lombok.extern.slf4j.Slf4j;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Component;
+import org.springframework.util.CollectionUtils;
 
 import java.math.BigDecimal;
 import java.util.*;
@@ -25,6 +38,7 @@
 /**
  * 预测样本数据构造
  */
+@Slf4j
 @Component
 public class PredictSampleDataConstructor extends SampleDataConstructor {
 
@@ -34,10 +48,22 @@
     private DataPointApi dataPointApi;
 
     @Autowired
+    private PlanItemApi planItemApi;
+
+    @Autowired
+    private IndItemApi indItemApi;
+
+    @Autowired
     private MmItemResultService mmItemResultService;
 
     @Autowired
-    private ItemEntityFactory itemEntityFactory;
+    private MmItemResultJsonService mmItemResultJsonService;
+
+    @Autowired
+    private MmItemTypeService mmItemTypeService;
+
+    @Autowired
+    private MmItemOutputService mmItemOutputService;
 
     /**
      * alter by zfc 2020.11.24 修改数据样本构造方案:sampleInfo中数据已按爪子进行分类,但爪内数据为无序的,
@@ -47,62 +73,94 @@
      * @return
      */
     @Override
-    public List<SampleData> prepareSampleData(SampleInfo sampleInfo) {
+    public List<SampleData> prepareSampleData(SampleInfo sampleInfo) throws Exception {
         List<SampleData> sampleDataList = new ArrayList<>();
-        //对每个爪分别进行计算
+        Map<String, ApiPointDTO> pointMap = sampleInfo.getPointMap();
+        Map<String, ApiPlanItemDTO> planMap = sampleInfo.getPlanMap();
+        Map<String, ApiIndItemDTO> indMap = sampleInfo.getIndMap();
+        // 校验数据
+        for (ColumnItemPort itemPort : sampleInfo.getColumnInfo()) {
+            for (ColumnItem columnItem : itemPort.getColumnItemList()) {
+                if (columnItem.getParamType().equals(ModelParamType.IND_ASCII.getCode())) {
+                    if (columnItem.getModelParamOrder() != 1 || itemPort.getColumnItemList().size() != 1) {
+                        throw new RuntimeException("模型输入数据异常:IND_ASCII类型输入独占一个端口;ParamPortOrder:" + columnItem.getModelParamPortOrder() + ",ParamOrder:" + columnItem.getModelParamOrder());
+                    }
+                }
+            }
+        }
+
         int deviationIndex = 0;
+
+        //对每个爪分别进行计算
         for (ColumnItemPort entry : sampleInfo.getColumnInfo()) {
-            //先依据爪内数据项的modelParamOrder进行排序——重写comparator匿名函数
-            Collections.sort(entry.getColumnItemList(), new Comparator<ColumnItem>() {
-                @Override
-                public int compare(ColumnItem o1, ColumnItem o2) {
-                    return o1.getModelParamOrder() - o2.getModelParamOrder();
+            double[][] matrix = new double[0][0];
+            // 特殊处理IND_ASCII类型
+            if (entry.getColumnItemList().get(0).getParamType().equals(ModelParamType.IND_ASCII.getCode())) {
+                // 获取指标数据
+                ColumnItem columnItem = entry.getColumnItemList().get(0);
+                ApiIndItemQueryDTO queryIndItemDTO = new ApiIndItemQueryDTO();
+                ApiIndItemDTO intItem = indMap.get(columnItem.getParamId());
+                queryIndItemDTO.setItemNo(intItem.getItemNo());
+                queryIndItemDTO.setStart(columnItem.getStartTime());
+                queryIndItemDTO.setEnd(columnItem.getEndTime());
+                List<ApiIndItemValueDTO> indItemValueList = indItemApi.queryIndItemHistoryValue(queryIndItemDTO);
+                if (!CollectionUtils.isEmpty(indItemValueList)) {
+                    matrix = new double[entry.getDataLength()][0];
+                    if (indItemValueList.size() > entry.getDataLength()) {
+                        indItemValueList = indItemValueList.subList(0,entry.getDataLength());
+                    }
+                    for (int i = 0; i < indItemValueList.size(); i++) {
+                        String stringValue = indItemValueList.get(i).getDataValue().toString();
+                        double[] asciiArray = ASCIIUtil.stringToAsciiArray(stringValue);
+                        matrix[i] = asciiArray;
+                    }
                 }
-            });
+            }else {
+                //先依据爪内数据项的modelParamOrder进行排序——重写comparator匿名函数
+                Collections.sort(entry.getColumnItemList(), new Comparator<ColumnItem>() {
+                    @Override
+                    public int compare(ColumnItem o1, ColumnItem o2) {
+                        return o1.getModelParamOrder() - o2.getModelParamOrder();
+                    }
+                });
 
-            //默认都是double类型的数据,且按列向量进行拼接,默认初始值为0.0
-            double[][] matrix = new double[entry.getDataLength()][entry.getColumnItemList().size()];
-            for (int i = 0; i < entry.getColumnItemList().size(); i++) {
-                for (int j = 0; j < entry.getDataLength(); j++) {
-                    matrix[j][i] = -2.0;
+                //默认都是double类型的数据,且按列向量进行拼接,默认初始值为0.0
+                matrix = new double[entry.getDataLength()][entry.getColumnItemList().size()];
+                for (int i = 0; i < entry.getColumnItemList().size(); i++) {
+                    for (int j = 0; j < entry.getDataLength(); j++) {
+                        matrix[j][i] = -2.0;
+                    }
                 }
-            }
 
-            //找出对应的调整值
-            BigDecimal[] deviationItem = null;
-            if (sampleInfo.getDeviation() != null && sampleInfo.getDeviation().length > 0) {
-                deviationItem = sampleInfo.getDeviation()[deviationIndex];
-            }
-            deviationIndex++;
+                //找出对应的调整值
+                double[] deviationItem = null;
+                if (sampleInfo.getDeviation() != null && sampleInfo.getDeviation().length > 0) {
+                    deviationItem = sampleInfo.getDeviation()[deviationIndex];
+                }
+                deviationIndex ++;
 
-            //对每一项依次进行数据查询,然后将查询出的值赋给matrix对应的位置
-            for (int i = 0; i < entry.getColumnItemList().size(); i++) {
-                try {
-                    List<DataValueVO> dataEntityList = getData(entry.getColumnItemList().get(i));
-                    //设置调整值
-                    if (deviationItem != null && deviationItem.length > 0) {
-                        logger.info("设置调整值, i = " + i);
-                        if (deviationItem[i] != null && deviationItem[i].compareTo(BigDecimal.ZERO) != 0) {
-                            for (int dataKey = 1; dataKey < dataEntityList.size(); dataKey++) {
-                                DataValueVO item = dataEntityList.get(dataKey);
-                                item.setDataValue(item.getDataValue() + deviationItem[i].doubleValue());
+                //对每一项依次进行数据查询,然后将查询出的值赋给matrix对应的位置
+                for (int i = 0; i < entry.getColumnItemList().size(); i++) {
+                    try {
+                        List<DataValueVO> dataEntityList = getData(entry.getColumnItemList().get(i), pointMap, planMap,indMap);
+                        //补全数据
+                        ColumnItem columnItem = entry.getColumnItemList().get(i);
+                        dataEntityList = super.completionData(matrix.length, dataEntityList, columnItem.startTime, columnItem.endTime, columnItem.getParamType(),columnItem.getGranularity());
+
+                        /** 如果数据取不满,把缺失的数据点放在后面 */
+                        if (dataEntityList != null && dataEntityList.size() != 0) {
+                            logger.info("设置matrix, i = " + i + ", size = " + dataEntityList.size());
+                            for (int k = 0; k < dataEntityList.size(); k++) {
+                                Double dataValue = dataEntityList.get(k).getDataValue();
+                                if (null != dataValue) {
+                                    matrix[k][i] = dataValue;
+                                }
                             }
                         }
+                    } catch (Exception e) {
+                        e.printStackTrace();
+                        throw e;
                     }
-                    //补全数据
-                    ColumnItem columnItem = entry.getColumnItemList().get(i);
-//                    dataEntityList = super.completionData(matrix.length, dataEntityList, columnItem.startTime, columnItem.getEndTime(), columnItem.granularity);
-                    dataEntityList = super.completionData(matrix.length, dataEntityList, columnItem.startTime, columnItem.endTime, columnItem.paramId,columnItem.getParamType());
-
-                    /** 如果数据取不满,把缺失的数据点放在后面 */
-                    if (dataEntityList != null && dataEntityList.size() != 0) {
-                        logger.info("设置matrix, i = " + i + ", size = " + dataEntityList.size());
-                        for (int k = 0; k < dataEntityList.size(); k++) {
-                            matrix[k][i] = dataEntityList.get(k).getDataValue();
-                        }
-                    }
-                } catch (Exception e) {
-                    e.printStackTrace();
                 }
             }
             SampleData sampleData = new SampleData();
@@ -116,40 +174,81 @@
      * getData
      *
      * @param columnItem
+     * @param pointMap
+     * @param planMap
+     * @param indMap
      * @return
      * @throws Exception
      */
-    private List<DataValueVO> getData(ColumnItem columnItem) throws Exception {
+    private List<DataValueVO> getData(ColumnItem columnItem, Map<String, ApiPointDTO> pointMap, Map<String, ApiPlanItemDTO> planMap, Map<String, ApiIndItemDTO> indMap) throws Exception {
         List<DataValueVO> dataList = new ArrayList<>();
         String paramType = columnItem.getParamType();
-        switch (paramType) {
-            case "DATAPOINT":
-                ApiPointDTO point = dataPointApi.getInfoById(columnItem.getParamId());
+        switch (ModelParamType.getEumByCode(paramType)) {
+            case DATAPOINT:
                 ApiPointValueQueryDTO queryDto = new ApiPointValueQueryDTO();
-                queryDto.setPointNo(point.getPointNo());
+                queryDto.setPointNo(pointMap.get(columnItem.getParamId()).getPointNo());
                 queryDto.setStart(columnItem.getStartTime());
                 queryDto.setEnd(columnItem.getEndTime());
                 List<ApiPointValueDTO> pointValueList = dataPointApi.queryPointHistoryValue(queryDto);
-                dataList = pointValueList.stream().map( t-> {
+                if (CollectionUtils.isEmpty(pointValueList)) {
+                    break;
+                }
+                dataList = pointValueList.stream().map(t -> {
                     DataValueVO vo = new DataValueVO();
                     vo.setDataTime(t.getT());
                     vo.setDataValue(t.getV());
                     return vo;
                 }).collect(Collectors.toList());
                 break;
-            case "PREDICTITEM":
-                MmItemOutputVO outPut = itemEntityFactory.getItemOutPutById(columnItem.getId());
-                dataList = mmItemResultService.getPredictValue(outPut.getId(),
-                        columnItem.getStartTime(), columnItem.getEndTime());
-                if (dataList == null) {
-                    throw new Exception("没有预测值");
+            case NORMALITEM:
+            case MERGEITEM:
+                List<DataValueVO> predictValue = mmItemResultService.getPredictValue(columnItem.getParamId(), columnItem.getStartTime(), columnItem.getEndTime());
+
+                if (CollectionUtils.isEmpty(predictValue)) {
+                    break;
                 }
+                dataList = predictValue;
                 break;
+            case PLAN:
+                ApiDataQueryDTO queryPlanItemDto = new ApiDataQueryDTO();
+                queryPlanItemDto.setItemNo(planMap.get(columnItem.getParamId()).getItemNo());
+                queryPlanItemDto.setStart(columnItem.getStartTime());
+                queryPlanItemDto.setEnd(columnItem.getEndTime());
+                List<ApiDataValueDTO> planValueList = planItemApi.queryPlanItemHistoryValue(queryPlanItemDto);
+                if (CollectionUtils.isEmpty(planValueList)) {
+                    break;
+                }
+                dataList = planValueList.stream().map(t -> {
+                    DataValueVO vo = new DataValueVO();
+                    vo.setDataTime(t.getDataTime());
+                    vo.setDataValue(t.getDataValue());
+                    return vo;
+                }).collect(Collectors.toList());
+                break;
+            case IND:
+                ApiIndItemQueryDTO queryIndItemDTO = new ApiIndItemQueryDTO();
+                ApiIndItemDTO intItem = indMap.get(columnItem.getParamId());
+                queryIndItemDTO.setItemNo(intItem.getItemNo());
+                queryIndItemDTO.setStart(columnItem.getStartTime());
+                queryIndItemDTO.setEnd(columnItem.getEndTime());
+                List<ApiIndItemValueDTO> indItemValueList = indItemApi.queryIndItemHistoryValue(queryIndItemDTO);
+                if (CollectionUtils.isEmpty(indItemValueList)) {
+                    break;
+                }
 
-
+                dataList = indItemValueList.stream().map(t -> {
+                    DataValueVO vo = new DataValueVO();
+                    vo.setDataTime(DateUtil.parse(t.getDataTime()));
+                    vo.setDataValue(Double.valueOf(t.getDataValue().toString()));
+                    return vo;
+                }).collect(Collectors.toList());
+                break;
             default:
                 break;
         }
+        // 避免生产环境日志过多,分级打印
+        log.debug("数据获取,columnItem:" + columnItem + ",dataList:" + dataList);
+        log.info("数据获取,columnItem:" + columnItem + ",dataListLength:" + dataList.size());
         return dataList;
     }
 }

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