From afd6dfbd0029e9a758d7896500d54d265f4185fc Mon Sep 17 00:00:00 2001
From: 潘志宝 <979469083@qq.com>
Date: 星期一, 17 三月 2025 16:22:37 +0800
Subject: [PATCH] long oneMin = granularity * 1000L
---
iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/sample/PredictSampleDataConstructor.java | 122 +++++++++++++++++++++++++---------------
1 files changed, 75 insertions(+), 47 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 6668705..b08e5a7 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
@@ -13,6 +13,7 @@
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;
@@ -77,68 +78,90 @@
Map<String, ApiPointDTO> pointMap = sampleInfo.getPointMap();
Map<String, ApiPlanItemDTO> planMap = sampleInfo.getPlanMap();
Map<String, ApiIndItemDTO> indMap = sampleInfo.getIndMap();
- int deviationIndex = 0;
+ // 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 portIdx = 1;
//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
- 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), pointMap, planMap, indMap);
- //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());
- //设置调整值
- if (deviationItem != null && deviationItem.length > 0) {
- logger.info("设置调整值, i = " + i);
- if (deviationItem[i] <= 0) {
+ /** 如果数据取不满，把缺失的数据点放在后面 */
+ if (CollectionUtils.isEmpty(dataEntityList)) {
continue;
}
- for(int dataKey = 1; dataKey < dataEntityList.size(); dataKey ++) {
- DataValueVO item = dataEntityList.get(dataKey);
- item.setDataValue(item.getDataValue() + deviationItem[i]);
- }
- }
-
- // 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());
+ // 调整值
+ double adjustVal = SampleInfo.getAdjustValueFromDeviation(portIdx, i + 1, sampleInfo.getDeviation());
for (int k = 0; k < dataEntityList.size(); k++) {
Double dataValue = dataEntityList.get(k).getDataValue();
- if (null != dataValue) {
- matrix[k][i] = dataValue;
+ if (null == dataValue) {
+ continue;
}
+ // 用BigDecimal计算，解决double精度问题
+ matrix[k][i] = BigDecimal.valueOf(dataValue).add(BigDecimal.valueOf(adjustVal)).doubleValue();
}
+ } catch (Exception e) {
+ e.printStackTrace();
+ throw e;
}
- } catch (Exception e) {
- e.printStackTrace();
- throw e;
}
+
+ portIdx++;
}
SampleData sampleData = new SampleData();
sampleData.setMatrix(matrix);
@@ -179,8 +202,12 @@
break;
case NORMALITEM:
case MERGEITEM:
- List<DataValueVO> predictValue = mmItemResultService.getPredictValue(columnItem.getParamId(), columnItem.getStartTime(), columnItem.getEndTime());
-
+ List<DataValueVO> predictValue = new ArrayList<>();
+ if (columnItem.getStartTime().getTime() == columnItem.getEndTime().getTime()) {
+ predictValue = mmItemResultService.getPredictValueLast(columnItem.getParamId(), columnItem.getStartTime(), 2);
+ } else {
+ predictValue = mmItemResultService.getPredictValue(columnItem.getParamId(), columnItem.getStartTime(), columnItem.getEndTime());
+ }
if (CollectionUtils.isEmpty(predictValue)) {
break;
}
@@ -216,9 +243,10 @@
dataList = indItemValueList.stream().map(t -> {
DataValueVO vo = new DataValueVO();
vo.setDataTime(DateUtil.parse(t.getDataTime()));
- vo.setDataValue(t.getDataValue());
+ vo.setDataValue(Double.valueOf(t.getDataValue().toString()));
return vo;
}).collect(Collectors.toList());
+ break;
default:
break;
}
--
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