iailab-plat.git

潘志宝

2024-09-30 536b8e85745a42806214ee708297642f493d3cd8

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7fd198	1	package com.iailab.module.model.mdk.sample;
潘	2
	3	import com.iailab.framework.common.util.object.ConvertUtils;
	4	import com.iailab.module.data.api.point.DataPointApi;
	5	import com.iailab.module.data.api.point.dto.ApiPointDTO;
	6	import com.iailab.module.data.api.point.dto.ApiPointValueDTO;
	7	import com.iailab.module.data.api.point.dto.ApiPointValueQueryDTO;
	8	import com.iailab.module.model.mcs.pre.service.MmItemResultService;
	9	import com.iailab.module.model.mdk.factory.ItemEntityFactory;
	10	import com.iailab.module.model.mdk.sample.dto.ColumnItem;
	11	import com.iailab.module.model.mdk.sample.dto.ColumnItemPort;
	12	import com.iailab.module.model.mdk.sample.dto.SampleData;
	13	import com.iailab.module.model.mdk.sample.dto.SampleInfo;
	14	import com.iailab.module.model.mdk.vo.DataValueVO;
	15	import com.iailab.module.model.mdk.vo.MmItemOutputVO;
	16	import org.slf4j.Logger;
	17	import org.slf4j.LoggerFactory;
	18	import org.springframework.beans.factory.annotation.Autowired;
	19	import org.springframework.stereotype.Component;
	20
	21	import java.math.BigDecimal;
	22	import java.util.*;
	23
	24	/**
	25	* 预测样本数据构造
	26	*/
	27	@Component
	28	public class PredictSampleDataConstructor extends SampleDataConstructor {
	29
	30	private Logger logger = LoggerFactory.getLogger(getClass());
	31
	32	@Autowired
	33	private DataPointApi dataPointApi;
	34
	35	@Autowired
	36	private MmItemResultService mmItemResultService;
	37
	38	@Autowired
	39	private ItemEntityFactory itemEntityFactory;
	40
	41	/**
	42	* 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，
	43	* 对爪内数据样本拼接：先基于modelParamOrder对项进行排序（重写comparator匿名函数），再逐项拼接
	44	*
	45	* @param sampleInfo
	46	* @return
	47	*/
	48	@Override
	49	public List<SampleData> prepareSampleData(SampleInfo sampleInfo) {
	50	List<SampleData> sampleDataList = new ArrayList<>();
	51	//对每个爪分别进行计算
	52	int deviationIndex = 0;
	53	for (ColumnItemPort entry : sampleInfo.getColumnInfo()) {
	54	//先依据爪内数据项的modelParamOrder进行排序——重写comparator匿名函数
	55	Collections.sort(entry.getColumnItemList(), new Comparator<ColumnItem>() {
	56	@Override
	57	public int compare(ColumnItem o1, ColumnItem o2) {
	58	return o1.getModelParamOrder() - o2.getModelParamOrder();
	59	}
	60	});
	61
	62	//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
	63	double[][] matrix = new double[entry.getDataLength()][entry.getColumnItemList().size()];
	64	for (int i = 0; i < entry.getColumnItemList().size(); i++) {
	65	for (int j = 0; j < entry.getDataLength(); j++) {
	66	matrix[j][i] = -2.0;
	67	}
	68	}
	69
	70	//找出对应的调整值
	71	BigDecimal[] deviationItem = null;
	72	if (sampleInfo.getDeviation() != null && sampleInfo.getDeviation().length > 0) {
	73	deviationItem = sampleInfo.getDeviation()[deviationIndex];
	74	}
	75	deviationIndex++;
	76
	77	//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
	78	for (int i = 0; i < entry.getColumnItemList().size(); i++) {
	79	try {
	80	List<DataValueVO> dataEntityList = getData(entry.getColumnItemList().get(i));
	81	//设置调整值
	82	if (deviationItem != null && deviationItem.length > 0) {
	83	logger.info("设置调整值, i = " + i);
	84	if (deviationItem[i] != null && deviationItem[i].compareTo(BigDecimal.ZERO) != 0) {
	85	for (int dataKey = 1; dataKey < dataEntityList.size(); dataKey++) {
	86	DataValueVO item = dataEntityList.get(dataKey);
	87	item.setDataValue(item.getDataValue() + deviationItem[i].doubleValue());
	88	}
	89	}
	90	}
	91	//补全数据
	92	ColumnItem columnItem = entry.getColumnItemList().get(i);
	93	dataEntityList = super.completionData(matrix.length, dataEntityList, columnItem.startTime, columnItem.getEndTime(), columnItem.granularity);
	94
	95	/** 如果数据取不满，把缺失的数据点放在后面 */
	96	if (dataEntityList != null && dataEntityList.size() != 0) {
	97	logger.info("设置matrix, i = " + i + ", size = " + dataEntityList.size());
	98	for (int k = 0; k < dataEntityList.size(); k++) {
	99	matrix[k][i] = dataEntityList.get(k).getDataValue();
	100	}
	101	}
	102	} catch (Exception e) {
	103	e.printStackTrace();
	104	}
	105	}
	106	SampleData sampleData = new SampleData();
	107	sampleData.setMatrix(matrix);
	108	sampleDataList.add(sampleData);
	109	}
	110	return sampleDataList;
	111	}
	112
	113	/**
	114	* getData
	115	*
	116	* @param columnItem
	117	* @return
	118	* @throws Exception
	119	*/
	120	private List<DataValueVO> getData(ColumnItem columnItem) throws Exception {
	121	List<DataValueVO> dataList = new ArrayList<>();
	122	String paramType = columnItem.getParamType();
	123	switch (paramType) {
	124	case "DATAPOINT":
536b8e	125	ApiPointDTO point = dataPointApi.getInfoById(columnItem.getId());
7fd198	126	ApiPointValueQueryDTO queryDto = new ApiPointValueQueryDTO();
潘	127	queryDto.setPointNo(point.getPointNo());
	128	queryDto.setStart(columnItem.getStartTime());
	129	queryDto.setEnd(columnItem.getEndTime());
536b8e	130	List<ApiPointValueDTO> pointValueList = dataPointApi.queryPointHistoryValue(queryDto);
7fd198	131	dataList = ConvertUtils.sourceToTarget(pointValueList, DataValueVO.class);
潘	132	break;
	133	case "PREDICTITEM":
	134	MmItemOutputVO outPut = itemEntityFactory.getItemOutPutById(columnItem.getId());
	135	dataList = mmItemResultService.getPredictValue(outPut.getId(),
	136	columnItem.getStartTime(), columnItem.getEndTime());
	137	if (dataList == null) {
	138	throw new Exception("没有预测值");
	139	}
	140	break;
	141
	142
	143	default:
	144	break;
	145	}
	146	return dataList;
	147	}
	148	}