iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/predict/PredictResultHandler.java

@@ -1,6 +1,7 @@
package com.iailab.module.model.mdk.predict;

import com.baomidou.dynamic.datasource.annotation.DSTransactional;
import com.iailab.module.model.common.enums.CommonDict;
import com.iailab.module.model.mcs.pre.entity.MmItemOutputEntity;
import com.iailab.module.model.mcs.pre.service.MmItemResultService;
import com.iailab.module.model.mdk.factory.ItemEntityFactory;
@@ -11,6 +12,7 @@
import org.springframework.stereotype.Service;
import org.springframework.util.CollectionUtils;

import java.math.BigDecimal;
import java.util.*;

@Service
@@ -52,6 +54,23 @@
            }
            resultMap.put(entry.getKey().getId(), predictDataList);
            predictLists.put(entry.getKey().getResultstr(), predictDataList);

            //处理累计计算
            if (entry.getKey().getIscumulant() == 1) {
                resultMap.put(entry.getKey().getId() + CommonDict.CUMULANT_SUFFIX, new ArrayList<DataValueVO>(){{
                    DataValueVO predictData = new DataValueVO();
                    // 时间 预测时间+预测长度*粒度
                    Calendar calendar = Calendar.getInstance();
                    calendar.setTime(predictResult.getPredictTime());
                    calendar.add(Calendar.SECOND, predictResult.getGranularity() * (rows - 1));
                    predictData.setDataTime(calendar.getTime());
                    //值 所有值相加/除数
                    BigDecimal sum = BigDecimal.valueOf(Arrays.stream(entry.getValue()).sum());
                    BigDecimal divisor = BigDecimal.valueOf(entry.getKey().getCumuldivisor());
                    predictData.setDataValue(sum.divide(divisor, 2, BigDecimal.ROUND_HALF_UP).doubleValue());
                    add(predictData);
                }});
            }
        }
        predictResult.setPredictLists(predictLists);
        return resultMap;
@@ -62,8 +81,8 @@
        if (!CollectionUtils.isEmpty(predictResult.getPredictList())) {
            return predictLists;
        }
        Map<com.iailab.module.model.mcs.pre.entity.MmItemOutputEntity, double[]> predictMatrixs = predictResult.getPredictMatrixs();
        for (Map.Entry<com.iailab.module.model.mcs.pre.entity.MmItemOutputEntity, double[]> entry : predictMatrixs.entrySet()) {
        Map<MmItemOutputEntity, double[]> predictMatrixs = predictResult.getPredictMatrixs();
        for (Map.Entry<MmItemOutputEntity, double[]> entry : predictMatrixs.entrySet()) {
            Integer rows = entry.getValue().length;
            List<DataValueVO> predictDataList = new ArrayList<>();
            Calendar calendar = Calendar.getInstance();
@@ -86,15 +105,10 @@
     *
     * @param predictResult
     */
    @Async
    @DSTransactional
    public void savePredictResult(PredictResultVO predictResult) {
        Map<String, List<DataValueVO>> resultMap = convertToPredictData(predictResult);
        mmItemResultService.savePredictValue(resultMap, predictResult.getLt(), "n", predictResult.getPredictTime());
        // 存double类型输出
        if (!CollectionUtils.isEmpty(predictResult.getPredictDoubleValues())) {
            mmItemResultService.savePredictValue(predictResult.getPredictDoubleValues(), predictResult.getPredictTime());
        }
    }

    public List<DataValueVO> getPredictValueByItemNo(String itemNo, Date start, Date end) {