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

@@ -4,9 +4,12 @@
import com.alibaba.fastjson.JSONObject;
import com.iail.IAILMDK;
import com.iail.model.IAILModel;
import com.iailab.module.model.mcs.pre.controller.admin.MmItemOutputController;
import com.iailab.module.model.mcs.pre.entity.MmItemOutputEntity;
import com.iailab.module.model.mcs.pre.entity.MmModelArithSettingsEntity;
import com.iailab.module.model.mcs.pre.entity.MmModelResultstrEntity;
import com.iailab.module.model.mcs.pre.entity.MmPredictModelEntity;
import com.iailab.module.model.mcs.pre.service.MmItemOutputService;
import com.iailab.module.model.mcs.pre.service.MmModelArithSettingsService;
import com.iailab.module.model.mcs.pre.service.MmModelResultstrService;
import com.iailab.module.model.mdk.common.enums.TypeA;
@@ -15,14 +18,13 @@
import com.iailab.module.model.mdk.sample.SampleConstructor;
import com.iailab.module.model.mdk.sample.dto.SampleData;
import com.iailab.module.model.mdk.vo.PredictResultVO;
import com.iailab.module.model.mpk.common.utils.DllUtils;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.security.core.parameters.P;
import org.springframework.stereotype.Component;

import java.util.ArrayList;
import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.*;

/**
 * @author PanZhibao
@@ -38,6 +40,8 @@

    @Autowired
    private MmModelResultstrService mmModelResultstrService;
    @Autowired
    private MmItemOutputService mmItemOutputService;

    @Autowired
    private SampleConstructor sampleConstructor;
@@ -80,16 +84,49 @@
            log.info(String.valueOf(jsonObjParam2Values));

            //IAILMDK.run
            HashMap<String, Object> modelResult = IAILMDK.run(newModelBean, param2Values);
//            HashMap<String, Object> modelResult = IAILMDK.run(newModelBean, param2Values);
            HashMap<String, Object> modelResult = DllUtils.run(newModelBean, param2Values, predictModel.getMpkprojectid());
            if(!modelResult.containsKey("status_code") || !modelResult.containsKey("result") || Integer.parseInt(modelResult.get("status_code").toString()) != 100) {
                throw new RuntimeException("模型结果异常：" + modelResult);
            }

            modelResult = (HashMap<String, Object>) modelResult.get("result");
            //打印结果
            JSONObject jsonObjResult = new JSONObject();
            jsonObjResult.put("result", result);
            jsonObjResult.put("result", modelResult);
            log.info(String.valueOf(jsonObjResult));

            MmModelResultstrEntity modelResultstr = mmModelResultstrService.getInfo(predictModel.getResultstrid());
            log.info("模型计算完成：modelId=" + modelId + result);
            double[][] temp = (double[][]) modelResult.get(modelResultstr.getResultstr());
            result.setPredictMatrix(temp);
            List<MmItemOutputEntity> ItemOutputList = mmItemOutputService.getByItemid(predictModel.getItemid());
            log.info("模型计算完成：modelId=" + modelId + modelResult);

            Map<MmItemOutputEntity,double[]> predictMatrixs = new HashMap<>(ItemOutputList.size());

            for (MmItemOutputEntity outputEntity : ItemOutputList) {
                String resultStr = outputEntity.getResultstr();
                if (modelResult.containsKey(resultStr)) {
                    if (outputEntity.getResultType() == 1) {
                        // 一维数组
                        Double[] temp = (Double[]) modelResult.get(resultStr);
                        double[] temp1 = new double[temp.length];
                        for (int i = 0; i < temp.length; i++) {
                            temp1[i] = temp[i].doubleValue();
                        }
                        predictMatrixs.put(outputEntity,temp1);
                    }else if (outputEntity.getResultType() == 2) {
                        // 二维数组
                        Double[][] temp = (Double[][]) modelResult.get(resultStr);
                        Double[] temp2 = temp[outputEntity.getResultIndex()];
                        double[] temp1 = new double[temp2.length];
                        for (int i = 0; i < temp2.length; i++) {
                            temp1[i] = temp2[i].doubleValue();
                        }
                        predictMatrixs.put(outputEntity,temp1);
                    }
                }
            }

            result.setPredictMatrixs(predictMatrixs);
            result.setModelResult(modelResult);
            result.setPredictTime(predictTime);
        } catch (Exception ex) {
            log.error("IAILModel对象构造失败，modelId=" + modelId);
@@ -124,7 +161,7 @@
        newModelBean.setParamsArray(paramsArray);
        HashMap<String, Object> dataMap = new HashMap<>();
        HashMap<String, String> models = new HashMap<>(1);
        models.put("paramFile", predictModel.getModelpath());
        models.put("model_path", predictModel.getModelpath());
        dataMap.put("models", models);
        newModelBean.setDataMap(dataMap);
        return newModelBean;