From f93760ef25c2a15259b567c87db1f4900b0a42c2 Mon Sep 17 00:00:00 2001
From: 潘志宝 <979469083@qq.com>
Date: 星期二, 04 三月 2025 10:07:51 +0800
Subject: [PATCH] 打印异常
---
iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/predict/impl/PredictModelHandlerImpl.java | 115 ++++++++++++++++++++++++++++++++++++++++++++++++++++-----
1 files changed, 104 insertions(+), 11 deletions(-)
diff --git a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/predict/impl/PredictModelHandlerImpl.java b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/predict/impl/PredictModelHandlerImpl.java
index 368ad04..7e0ac4b 100644
--- a/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/predict/impl/PredictModelHandlerImpl.java
+++ b/iailab-module-model/iailab-module-model-biz/src/main/java/com/iailab/module/model/mdk/predict/impl/PredictModelHandlerImpl.java
@@ -3,6 +3,7 @@
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONArray;
import com.iail.model.IAILModel;
+import com.iailab.module.model.mdk.vo.StAdjustDeviationDTO;
import com.iailab.module.model.enums.CommonConstant;
import com.iailab.module.model.common.enums.OutResultType;
import com.iailab.module.model.common.exception.ModelResultErrorException;
@@ -55,7 +56,7 @@
* @throws ModelInvokeException
*/
@Override
- public synchronized PredictResultVO predictByModel(Date predictTime, MmPredictModelEntity predictModel,String itemName,String itemNo) throws ModelInvokeException {
+ public PredictResultVO predictByModel(Date predictTime, MmPredictModelEntity predictModel, String itemName, String itemNo) throws ModelInvokeException {
PredictResultVO result = new PredictResultVO();
if (predictModel == null) {
throw new ModelInvokeException("modelEntity is null");
@@ -72,7 +73,7 @@
HashMap<String, Object> settings = getPredictSettingsByModelId(modelId);
// 校验setting必须有pyFile，否则可能导致程序崩溃
if (!settings.containsKey(MdkConstant.PY_FILE_KEY)) {
- throw new RuntimeException("模型设置参数缺少必要信息【" + MdkConstant.PY_FILE_KEY + "】,请重新上传模型！");
+ throw new RuntimeException("模型设置参数缺少必要信息【" + MdkConstant.PY_FILE_KEY + "】,请重新上传模型！");
}
if (settings == null) {
@@ -87,12 +88,7 @@
param2Values[portLength] = newModelBean.getDataMap().get("models");
param2Values[portLength + 1] = settings;
- log.info("####################### 预测模型 "+ "【itemId:" + predictModel.getItemid() + ",itemName：" + itemName + ",itemNo：" + itemNo + "】 ##########################");
-// JSONObject jsonObjNewModelBean = new JSONObject();
-// jsonObjNewModelBean.put("newModelBean", newModelBean);
-// log.info(String.valueOf(jsonObjNewModelBean));
-// JSONObject jsonObjParam2Values = new JSONObject();
-// jsonObjParam2Values.put("param2Values", param2Values);
+ log.info("####################### 预测模型 " + "【itemId:" + predictModel.getItemid() + ",itemName：" + itemName + ",itemNo：" + itemNo + "】 ##########################");
log.info("参数： " + JSON.toJSONString(param2Values));
//IAILMDK.run
@@ -108,7 +104,6 @@
List<MmItemOutputEntity> itemOutputList = mmItemOutputService.getByItemid(predictModel.getItemid());
Map<MmItemOutputEntity, double[]> predictMatrixs = new HashMap<>();
- Map<MmItemOutputEntity, Double> predictDoubleValues = new HashMap<>();
for (MmItemOutputEntity output : itemOutputList) {
if (!modelResult.containsKey(output.getResultstr())) {
continue;
@@ -129,14 +124,13 @@
break;
case D:
Double temp3 = (Double) modelResult.get(output.getResultstr());
- predictDoubleValues.put(output, temp3);
+ predictMatrixs.put(output, new double[]{temp3});
break;
default:
break;
}
}
result.setPredictMatrixs(predictMatrixs);
- result.setPredictDoubleValues(predictDoubleValues);
result.setModelResult(modelResult);
result.setPredictTime(predictTime);
} catch (ModelResultErrorException ex) {
@@ -153,6 +147,105 @@
}
/**
+ * 预测，模拟调整
+ *
+ * @param predictTime
+ * @param predictModel
+ * @param itemName
+ * @param itemNo
+ * @param deviationList
+ * @return
+ * @throws ModelInvokeException
+ */
+ @Override
+ public PredictResultVO predictByModel(Date predictTime, MmPredictModelEntity predictModel, String itemName, String itemNo, List<StAdjustDeviationDTO> deviationList) throws ModelInvokeException {
+ PredictResultVO result = new PredictResultVO();
+ if (predictModel == null) {
+ throw new ModelInvokeException("modelEntity is null");
+ }
+ String modelId = predictModel.getId();
+ try {
+ List<SampleData> sampleDataList = sampleConstructor.constructSample(TypeA.Predict.name(), modelId, predictTime, itemName, new HashMap<>(), deviationList);
+ String modelPath = predictModel.getModelpath();
+ if (modelPath == null) {
+ log.info("模型路径不存在，modelId=" + modelId);
+ return null;
+ }
+ IAILModel newModelBean = composeNewModelBean(predictModel);
+ HashMap<String, Object> settings = getPredictSettingsByModelId(modelId);
+ // 校验setting必须有pyFile，否则可能导致程序崩溃
+ if (!settings.containsKey(MdkConstant.PY_FILE_KEY)) {
+ throw new RuntimeException("模型设置参数缺少必要信息【" + MdkConstant.PY_FILE_KEY + "】,请重新上传模型！");
+ }
+
+ if (settings == null) {
+ log.error("模型setting不存在，modelId=" + modelId);
+ return null;
+ }
+ int portLength = sampleDataList.size();
+ Object[] param2Values = new Object[portLength + 2];
+ for (int i = 0; i < portLength; i++) {
+ param2Values[i] = sampleDataList.get(i).getMatrix();
+ }
+ param2Values[portLength] = newModelBean.getDataMap().get("models");
+ param2Values[portLength + 1] = settings;
+
+ log.info("####################### 模拟调整 " + "【itemId:" + predictModel.getItemid() + ",itemName：" + itemName + ",itemNo：" + itemNo + "】 ##########################");
+ log.info("参数： " + JSON.toJSONString(param2Values));
+
+ //IAILMDK.run
+ HashMap<String, Object> modelResult = DllUtils.run(newModelBean, param2Values, predictModel.getMpkprojectid());
+ //打印结果
+ log.info("预测模型计算完成：modelId=" + modelId + ",modelName=" + predictModel.getMethodname() + "，modelResult=" + JSON.toJSONString(modelResult));
+ //判断模型结果
+ if (!modelResult.containsKey(CommonConstant.MDK_STATUS_CODE) || !modelResult.containsKey(CommonConstant.MDK_RESULT) ||
+ !modelResult.get(CommonConstant.MDK_STATUS_CODE).toString().equals(CommonConstant.MDK_STATUS_100)) {
+ throw new ModelResultErrorException("模型结果异常：" + modelResult);
+ }
+ modelResult = (HashMap<String, Object>) modelResult.get(CommonConstant.MDK_RESULT);
+
+ List<MmItemOutputEntity> itemOutputList = mmItemOutputService.getByItemid(predictModel.getItemid());
+ Map<MmItemOutputEntity, double[]> predictMatrixs = new HashMap<>();
+ for (MmItemOutputEntity output : itemOutputList) {
+ if (!modelResult.containsKey(output.getResultstr())) {
+ continue;
+ }
+ OutResultType outResultType = OutResultType.getEumByCode(output.getResultType());
+ switch (outResultType) {
+ case D1:
+ double[] temp1 = (double[]) modelResult.get(output.getResultstr());
+ predictMatrixs.put(output, temp1);
+ break;
+ case D2:
+ double[][] temp2 = (double[][]) modelResult.get(output.getResultstr());
+ double[] tempColumn = new double[temp2.length];
+ for (int i = 0; i < tempColumn.length; i++) {
+ tempColumn[i] = temp2[i][output.getResultIndex()];
+ }
+ predictMatrixs.put(output, tempColumn);
+ break;
+ case D:
+ Double temp3 = (Double) modelResult.get(output.getResultstr());
+ predictMatrixs.put(output, new double[]{temp3});
+ break;
+ default:
+ break;
+ }
+ }
+ result.setPredictMatrixs(predictMatrixs);
+ result.setModelResult(modelResult);
+ result.setPredictTime(predictTime);
+ } catch (ModelResultErrorException ex) {
+ log.error("模型结果异常", ex);
+ throw ex;
+ } catch (Exception ex) {
+ log.error("调用发生异常，异常信息为:{0}", ex.getMessage());
+ throw new ModelInvokeException(ex.getMessage());
+ }
+ return result;
+ }
+
+ /**
* 构造IAILMDK.run()方法的newModelBean参数
*
* @param predictModel
--
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