package com.iailab.module.model.mdk.predict.impl;

import com.alibaba.fastjson.JSONArray;
import com.alibaba.fastjson.JSONObject;
import com.iail.IAILMDK;
import com.iail.model.IAILModel;
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.MmModelArithSettingsService;
import com.iailab.module.model.mcs.pre.service.MmModelResultstrService;
import com.iailab.module.model.mdk.common.enums.TypeA;
import com.iailab.module.model.mdk.common.exceptions.ModelInvokeException;
import com.iailab.module.model.mdk.predict.PredictModelHandler;
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.stereotype.Component;

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

/**
 * @author PanZhibao
 * @Description
 * @createTime 2024年09月01日
 */
@Slf4j
@Component
public class PredictModelHandlerImpl implements PredictModelHandler {

    @Autowired
    private MmModelArithSettingsService mmModelArithSettingsService;

    @Autowired
    private MmModelResultstrService mmModelResultstrService;

    @Autowired
    private SampleConstructor sampleConstructor;

    @Override
    public PredictResultVO predictByModel(Date predictTime, MmPredictModelEntity predictModel) 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);
            String modelPath = predictModel.getModelpath();
            if (modelPath == null) {
                System.out.println("模型路径不存在，modelId=" + modelId);
                return null;
            }
            IAILModel newModelBean = composeNewModelBean(predictModel);
            HashMap<String, Object> settings = getPredictSettingsByModelId(modelId);
            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("#######################预测模型 " + predictModel.getItemid() + " ##########################");
            JSONObject jsonObjNewModelBean = new JSONObject();
            jsonObjNewModelBean.put("newModelBean", newModelBean);
            log.info(String.valueOf(jsonObjNewModelBean));
            JSONObject jsonObjParam2Values = new JSONObject();
            jsonObjParam2Values.put("param2Values", param2Values);
            log.info(String.valueOf(jsonObjParam2Values));

            //IAILMDK.run
//            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", modelResult);
            log.info(String.valueOf(jsonObjResult));

            MmModelResultstrEntity modelResultstr = mmModelResultstrService.getInfo(predictModel.getResultstrid());
            log.info("模型计算完成：modelId=" + modelId + result);
            if (modelResult.containsKey(modelResultstr.getResultstr())) {
                Double[][] temp = (Double[][]) modelResult.get(modelResultstr.getResultstr());
                double[][] temp1 = new double[temp.length][temp[0].length];
                for (int i = 0; i < temp.length; i++) {
                    for (int j = 0; j < temp[i].length; j++) {
                        temp1[i][j] = temp[i][j].doubleValue();
                    }
                }
                result.setPredictMatrix(temp1);
            }
            result.setModelResult(modelResult);
            result.setPredictTime(predictTime);
        } catch (Exception ex) {
            log.error("IAILModel对象构造失败，modelId=" + modelId);
            log.error(ex.getMessage());
            log.error("调用发生异常，异常信息为:{}" , ex);
            ex.printStackTrace();

        }
        return result;
    }

    /**
     * 构造IAILMDK.run()方法的newModelBean参数
     *
     * @param predictModel
     * @return
     */
    private IAILModel composeNewModelBean(MmPredictModelEntity predictModel) {
        IAILModel newModelBean = new IAILModel();
        newModelBean.setClassName(predictModel.getClassname().trim());
        newModelBean.setMethodName(predictModel.getMethodname().trim());
        //构造参数类型
        String[] paArStr = predictModel.getModelparamstructure().trim().split(",");
        Class<?>[] paramsArray = new Class[paArStr.length];
        for (int i = 0; i < paArStr.length; i++) {
            if ("[[D".equals(paArStr[i])) {
                paramsArray[i] = double[][].class;
            } else if ("Map".equals(paArStr[i]) || "java.util.HashMap".equals(paArStr[i])) {
                paramsArray[i] = HashMap.class;
            }
        }
        newModelBean.setParamsArray(paramsArray);
        HashMap<String, Object> dataMap = new HashMap<>();
        HashMap<String, String> models = new HashMap<>(1);
        models.put("model_path", predictModel.getModelpath());
        dataMap.put("models", models);
        newModelBean.setDataMap(dataMap);
        return newModelBean;
    }

    /**
     * 根据模型id获取参数map
     *
     * @param modelId
     * @return
     */
    private HashMap<String, Object> getPredictSettingsByModelId(String modelId) {
        List<MmModelArithSettingsEntity> list = mmModelArithSettingsService.getByModelId(modelId);
        HashMap<String, Object> result = new HashMap<>();
        for (MmModelArithSettingsEntity entry : list) {
            String valueType = entry.getValuetype().trim(); //去除两端空格
            if ("int".equals(valueType)) {
                int value = Integer.parseInt(entry.getValue());
                result.put(entry.getKey(), value);
            } else if ("double".equals(valueType)) {
                double value = Double.parseDouble(entry.getValue());
                result.put(entry.getKey(), value);
            } else if ("string".equals(valueType)) {
                String value = entry.getValue();
                result.put(entry.getKey(), value);
            } else if ("decimalArray".equals(valueType)) {
                JSONArray valueArray = JSONArray.parseArray(entry.getValue());
                double[] value = new double[valueArray.size()];
                for (int i = 0; i < valueArray.size(); i++) {
                    value[i] = Double.parseDouble(valueArray.get(i).toString());
                }
                result.put(entry.getKey(), value);
            } else if ("decimal".equals(valueType)) {
                double value = Double.parseDouble(entry.getValue());
                result.put(entry.getKey(), value);
            }
        }
        return result;
    }
}