package com.iailab.module.model.mdk.predict.impl;
|
|
import com.iailab.module.data.api.point.DataPointApi;
|
import com.iailab.module.data.api.point.dto.ApiPointDTO;
|
import com.iailab.module.data.enums.DataPointFreqEnum;
|
import com.iailab.module.model.mdk.common.enums.ItemPredictStatus;
|
import com.iailab.module.model.mdk.common.exceptions.ItemInvokeException;
|
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.mdk.predict.PredictResultHandler;
|
import com.iailab.module.model.mdk.vo.DataValueVO;
|
import com.iailab.module.model.mdk.vo.ItemVO;
|
import com.iailab.module.model.mdk.vo.MmItemOutputVO;
|
import com.iailab.module.model.mdk.vo.PredictResultVO;
|
import lombok.extern.slf4j.Slf4j;
|
import org.springframework.beans.factory.annotation.Autowired;
|
import org.springframework.stereotype.Component;
|
|
import java.sql.Timestamp;
|
import java.util.*;
|
|
/**
|
* @author PanZhibao
|
* @Description
|
* @createTime 2024年09月01日
|
*/
|
@Slf4j
|
@Component
|
public class PredictItemMergeHandlerImpl implements PredictItemHandler {
|
|
@Autowired
|
private ItemEntityFactory itemEntityFactory;
|
|
@Autowired
|
private DataPointApi dataPointApi;
|
|
@Autowired
|
private PredictItemFactory predictItemFactory;
|
|
@Autowired
|
private PredictResultHandler predictResultHandler;
|
|
@Override
|
public PredictResultVO predict(Date predictTime, ItemVO predictItemDto)
|
throws ItemInvokeException {
|
PredictResultVO predictResult = new PredictResultVO();
|
ItemPredictStatus itemStatus = ItemPredictStatus.PREDICTING;
|
String itemId = predictItemDto.getId();
|
try {
|
String expression = itemEntityFactory.getMergeItem(itemId).getExpression();
|
int predictLength = itemEntityFactory.getItemById(itemId).getPredictLength();
|
double[][] predictResultMat = new double[predictLength][1];
|
Map<String, List<DataValueVO>> predictValueMap = new HashMap<>();
|
String[] mathItem = expression.split("[\\+ \\-]");
|
ArrayList<Character> operator = new ArrayList<>();
|
for (int i = 0; i < expression.length(); i++) {
|
if (expression.charAt(i)=='+' || expression.charAt(i)=='-'){
|
operator.add(expression.charAt(i));
|
}
|
}
|
String[] compositionItem = expression.split(String.valueOf("&".toCharArray()));
|
//是否为计算预测项
|
if (mathItem.length > 1) {
|
for (String itemNo : mathItem) {
|
if (itemNo.length() > 4) {
|
Date endTime = predictTime;
|
ItemVO itemEntity = itemEntityFactory.getItemByItemNo(itemNo);
|
List<MmItemOutputVO> outPutList = itemEntityFactory.getOutPutByItemId(itemEntity.getId());
|
ApiPointDTO pointEntity = dataPointApi.getInfoById(outPutList.get(0).getPointId());
|
|
Calendar calendar = Calendar.getInstance();
|
calendar.setTime(endTime);
|
calendar.add(Calendar.SECOND, (predictLength - 1) * DataPointFreqEnum.getEumByCode(pointEntity.getMinfreqid()).getValue());
|
endTime = new Timestamp(calendar.getTime().getTime());
|
List<DataValueVO> predictValueList = predictResultHandler.getPredictValueByItemNo(itemNo, predictTime, endTime);
|
if (predictValueList.size() != predictLength) {
|
log.debug("merge项融合失败:缺少子项预测数据,对应子项ItemNo=" + itemNo);
|
return null;
|
}
|
predictValueMap.put(itemNo, predictValueList);
|
}
|
}
|
for (Integer i = 0; i < predictLength; i++) {
|
double sum =0.0;
|
sum = predictValueMap.get(mathItem[0]).get(i).getDataValue();
|
for (int j = 1; j < mathItem.length; j++) {
|
if (operator.get(j-1)=='+')
|
{sum += predictValueMap.get(mathItem[j]).get(i).getDataValue();}
|
if (operator.get(j-1)=='-')
|
{sum -= predictValueMap.get(mathItem[j]).get(i).getDataValue();}
|
}
|
predictResultMat[i][0] = sum;
|
}
|
}
|
//是否为组合预测项
|
if (compositionItem.length > 1) {
|
Map<String, PredictResultVO> predictResultMap = new HashMap<>();
|
Integer columnTotalNumber = 0;
|
Integer rowNumber = 0;
|
for (String itemNo : compositionItem) {
|
PredictItemHandler predictItem = (PredictItemHandler) predictItemFactory.create(itemEntityFactory.
|
getItemByItemNo(itemNo).getId());
|
predictResult = predictItem.predict(predictTime, predictItemDto);
|
columnTotalNumber += Integer.valueOf(predictResult.getPredictMatrix().length);
|
predictResultMap.put(itemNo, predictItem.predict(predictTime, predictItemDto));
|
}
|
double[][] matrix = new double[columnTotalNumber][1];
|
for (String itemNo : compositionItem) {
|
for (Integer i = 0; i < predictResultMap.get(itemNo).getPredictMatrix().length; i++) {
|
matrix[rowNumber][0] = predictResultMap.get(itemNo).getPredictMatrix()[i][0];
|
rowNumber++;
|
}
|
}
|
predictResult.setPredictMatrix(matrix);
|
}
|
predictResult.setPredictId(itemId);
|
predictResult.setPredictMatrix(predictResultMat);
|
predictResult.setPredictTime(predictTime);
|
//预测项预测成功的状态
|
itemStatus = ItemPredictStatus.SUCCESS;
|
} catch (Exception e) {
|
//预测项预测失败的状态
|
itemStatus = ItemPredictStatus.FAILED;
|
log.debug("merge项预测失败,itemId:" + itemId);
|
throw e;
|
}
|
log.debug("预测完成,itemId:" + itemId + ",itemStatus:" + itemStatus.getValue());
|
return predictResult;
|
}
|
}
|