package com.iailab.module.model.mcs.pre.service.impl;

import com.baomidou.mybatisplus.core.metadata.IPage;
import com.iailab.framework.common.pojo.PageResult;
import com.iailab.framework.common.service.impl.BaseServiceImpl;
import com.iailab.module.data.api.point.DataPointApi;
import com.iailab.module.data.api.point.dto.ApiPointDTO;
import com.iailab.module.data.api.point.dto.ApiPointValueDTO;
import com.iailab.module.data.api.point.dto.ApiPointValueQueryDTO;
import com.iailab.module.model.common.enums.DataTypeEnum;
import com.iailab.module.model.influxdb.pojo.InfluxModelResultLastSimPOJO;
import com.iailab.module.model.influxdb.pojo.InfluxModelResultPOJO;
import com.iailab.module.model.influxdb.service.InfluxDBService;
import com.iailab.module.model.influxdb.vo.InfluxModelResultVO;
import com.iailab.module.model.mcs.pre.dao.MmPredictAutoAdjustConfigDao;
import com.iailab.module.model.mcs.pre.entity.MmPredictAutoAdjustConfigEntity;
import com.iailab.module.model.mcs.pre.enums.AutoAdjustTriggerRuleEnum;
import com.iailab.module.model.mcs.pre.enums.AutoAdjustValueRuleEnum;
import com.iailab.module.model.mcs.pre.service.MmPredictAutoAdjustConfigService;
import com.iailab.module.model.mcs.pre.service.MmPredictItemService;
import com.iailab.module.model.mcs.pre.vo.MmPredictAutoAdjustConfigPageReqVO;
import com.iailab.module.model.mcs.pre.vo.MmPredictAutoAdjustConfigVO;
import com.iailab.module.model.mdk.vo.ItemVO;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Service;
import org.springframework.util.CollectionUtils;

import java.math.BigDecimal;
import java.util.*;
import java.util.function.Predicate;
import java.util.stream.Collectors;

/**
 * @author PanZhibao
 * @Description
 * @createTime 2024年11月19日
 */
@Slf4j
@Service
public class MmPredictAutoAdjustConfigServiceImpl extends BaseServiceImpl<MmPredictAutoAdjustConfigDao, MmPredictAutoAdjustConfigEntity>
        implements MmPredictAutoAdjustConfigService {

    @Autowired
    private MmPredictItemService mmPredictItemService;
    @Autowired
    private InfluxDBService influxDBService;
    @Autowired
    private DataPointApi dataPointApi;

    @Override
    public PageResult<MmPredictAutoAdjustConfigVO> page(MmPredictAutoAdjustConfigPageReqVO params) {
        IPage<MmPredictAutoAdjustConfigVO> page = baseDao.selectPage(params);
        return new PageResult<>(page.getRecords(), page.getTotal());
    }

    @Override
    public MmPredictAutoAdjustConfigEntity getInfo(String id) {
        return baseDao.selectById(id);
    }

    @Override
    public List<MmPredictAutoAdjustConfigEntity> getByCode(String code) {
        return baseDao.selectList(MmPredictAutoAdjustConfigEntity::getConfigCode,code,MmPredictAutoAdjustConfigEntity::getIsEnable,1);
    }

    @Override
    public void create(MmPredictAutoAdjustConfigEntity entity) {
        entity.setId(UUID.randomUUID().toString());
        entity.setCreateTime(new Date());
        baseDao.insert(entity);
    }

    @Override
    public void update(MmPredictAutoAdjustConfigEntity entity) {
        baseDao.updateById(entity);
    }

    @Override
    public void delete(String id) {
        baseDao.deleteById(id);
    }

    @Override
    public boolean autoAdjustByCode(String configCode,long adjustStartTime) {
        log.info("开始自动调整：configCode：" + configCode + ",adjustStartTime:" + new Date(adjustStartTime));
        // 查询调整配置
        List<MmPredictAutoAdjustConfigEntity> configEntityList = getByCode(configCode);
        if (CollectionUtils.isEmpty(configEntityList)) {
            log.info("自动调整失败原因：configEntityList为空");
            return false;
        }

        // 根据outputId分组
        Map<String, List<MmPredictAutoAdjustConfigEntity>> outputIdMap = configEntityList.stream().collect(Collectors.groupingBy(MmPredictAutoAdjustConfigEntity::getOutputId));
        for (Map.Entry<String, List<MmPredictAutoAdjustConfigEntity>> entry : outputIdMap.entrySet()) {
            String outputId = entry.getKey();
            // 查询调整用户adjustStartTime 至 adjustStartTime - 预测长度 * 预测粒度 范围的值
            Calendar calendar = Calendar.getInstance();
            calendar.setTimeInMillis(adjustStartTime);
            Date endTime = calendar.getTime();
            ItemVO item = mmPredictItemService.getItemByOutPutId(outputId);
            if (item == null) {
                log.info("自动调整失败原因：getItemByOutPutId为null，outputId：" + outputId);
                continue;
            }
            calendar.add(Calendar.SECOND,item.getPredictLength() * item.getGranularity() * -1);
            Date startTime = calendar.getTime();

            // 获取预测历史结果
            InfluxModelResultPOJO pojo = new InfluxModelResultPOJO();
            pojo.setType(DataTypeEnum.FLOAT_LAST_BAK.getCode());
            pojo.setOutPutId(outputId);
            List<InfluxModelResultVO> influxModelResult = influxDBService.queryModelResults(pojo, new Date(adjustStartTime), new Date(adjustStartTime));
            if (CollectionUtils.isEmpty(influxModelResult)) {
                log.info("自动调整失败原因：预测历史结果为空。itemNo：" + item.getItemNo() + "，itemName:" + item.getItemName() + "，outputId:" + outputId + "，time:" + adjustStartTime);
                continue;
            }

            // 计算所有影响用户的最终调整值
            Double finalAdjustValue = 0.0;
            for (MmPredictAutoAdjustConfigEntity configEntity : entry.getValue()) {
                Double adjustValue = null;
                // 查询影响用户历史值
                ApiPointValueQueryDTO queryDTO = new ApiPointValueQueryDTO();
                ApiPointDTO pointInfo = dataPointApi.getInfoById(configEntity.getPointId());
                queryDTO.setPointNo(pointInfo.getPointNo());
                queryDTO.setEnd(endTime);
                queryDTO.setStart(startTime);
                List<ApiPointValueDTO> apiPointValueDTOS = dataPointApi.queryPointHistoryValue(queryDTO);
                if (CollectionUtils.isEmpty(apiPointValueDTOS)) {
                    log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：测点数据长度为0。queryDTO：" + queryDTO);
                    continue;
                }
                // 过滤掉-2
                apiPointValueDTOS = apiPointValueDTOS.stream().filter(e -> !Double.valueOf(e.getV()).equals(-2.0)).collect(Collectors.toList());
                if (CollectionUtils.isEmpty(apiPointValueDTOS)) {
                    log.info("影响用户调整失败原因：过滤掉-2之后测点数据长度为0。queryDTO：" + queryDTO);
                    continue;
                }

                // 触发规则
                AutoAdjustTriggerRuleEnum triggerRuleEnum = AutoAdjustTriggerRuleEnum.fromCode(configEntity.getTriggerRule());
                // 判断是否符合触发条件 并计算调整值
                switch (triggerRuleEnum) {
                    case SLOPE:
                        // 计算每个△t的斜率，任意一个大于触发值则认为该区间有调整
                        Calendar slopeCalendar = Calendar.getInstance();
                        slopeCalendar.setTime(startTime);
                        Date slopeStartTime = slopeCalendar.getTime();
                        slopeCalendar.add(Calendar.MINUTE,configEntity.getT());
                        Date slopeEndTime = slopeCalendar.getTime();
                        if (slopeEndTime.after(endTime)) {
                            log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：△t设置过大，大于模型预测长度 * 预测粒度。△t：" + configEntity.getT());
                            continue;
                        }
                        while (!slopeEndTime.after(endTime)) {
                            //计算斜率
                            //△t开始时间测点值
                            Date finalSlopeStartTime = slopeStartTime;
                            Optional<ApiPointValueDTO> startOptional = apiPointValueDTOS.stream().filter(apiPointValueDTO -> apiPointValueDTO.getT().equals(finalSlopeStartTime)).findFirst();
                            //△t结束时间测点值
                            Date finalSlopeEndTime = slopeEndTime;
                            Optional<ApiPointValueDTO> endOptional = apiPointValueDTOS.stream().filter(e -> e.getT().equals(finalSlopeEndTime)).findFirst();
                            if (startOptional.isPresent() && endOptional.isPresent()) {
                                ApiPointValueDTO startPointValue = startOptional.get();
                                ApiPointValueDTO endPointValue = endOptional.get();
                                // 计算斜率
                                double slope = BigDecimal.valueOf(endPointValue.getV() - startPointValue.getV()).divide(BigDecimal.valueOf(configEntity.getT())).doubleValue();
                                // 斜率大于等于触发值则进行调整
                                if (Double.valueOf(Math.abs(slope)).compareTo(configEntity.getTriggerValue()) >= 0) {
                                    // 计算调整值 并跳出循环
                                    adjustValue = AutoAdjustValueRuleEnum.getAdjustValue(configEntity.getAdjustValueRule(), apiPointValueDTOS);
                                    log.info("计算调整值：" + adjustValue + "，斜率：" + slope + "，pointNo：" + pointInfo.getPointNo() + "，pointName：" + pointInfo.getPointName() + "，slopeStartTime：" + slopeStartTime + "，slopeEndTime：" + slopeEndTime);
                                    break;
                                }
                                log.info("斜率不满足条件，斜率：" + slope);
                            }
                            // 下一个△t
                            slopeStartTime = slopeCalendar.getTime();
                            slopeCalendar.add(Calendar.MINUTE,configEntity.getT());
                            slopeEndTime = slopeCalendar.getTime();
                        }
                        break;
                    case AVERAGE_GAP:
                        // 计算每两个△t的平均差，任意一个大于触发值则认为该区间有调整
                        Calendar averageCalendar = Calendar.getInstance();
                        averageCalendar.setTime(startTime);
                        Date averageStartTime = averageCalendar.getTime();
                        averageCalendar.add(Calendar.MINUTE,configEntity.getT());
                        Date averageMiddleTime = averageCalendar.getTime();
                        averageCalendar.add(Calendar.MINUTE,configEntity.getT());
                        Date averageEndTime = averageCalendar.getTime();

                        if (averageEndTime.after(endTime)) {
                            log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：△t设置过大，△t*2大于模型预测长度 * 预测粒度。△t：" + configEntity.getT());
                            continue;
                        }
                        while (!averageEndTime.after(endTime)) {
                            //计算均值差
                            //前△t测点平均值
                            Date finalAverageStartTime = averageStartTime;
                            Date finalAverageMiddleTime = averageMiddleTime;
                            OptionalDouble startAverage = apiPointValueDTOS.stream().filter(e -> e.getT().after(finalAverageStartTime) && !e.getT().after(finalAverageMiddleTime)).mapToDouble(ApiPointValueDTO::getV).average();
                            //后△t测点平均值
                            Date finalAverageEndTime = averageEndTime;
                            OptionalDouble endAverage = apiPointValueDTOS.stream().filter(e -> e.getT().after(finalAverageMiddleTime) && !e.getT().after(finalAverageEndTime)).mapToDouble(ApiPointValueDTO::getV).average();
                            if (startAverage.isPresent() && endAverage.isPresent()) {
                                double averageGapValue = startAverage.getAsDouble() - endAverage.getAsDouble();
                                // 均值差，大于等于触发值则进行调整
                                if (Double.valueOf(Math.abs(averageGapValue)).compareTo(configEntity.getTriggerValue()) >= 0) {
                                    // 计算调整值 并跳出循环
                                    adjustValue = AutoAdjustValueRuleEnum.getAdjustValue(configEntity.getAdjustValueRule(), apiPointValueDTOS);
                                    log.info("计算调整值：" + adjustValue + "，均值差：" + averageGapValue + "，pointNo：" + pointInfo.getPointNo() + "，pointName：" + pointInfo.getPointName() + "，averageStartTime：" + averageStartTime + "，averageMiddleTime：" + averageMiddleTime + "，averageEndTime：" + averageEndTime);
                                    break;
                                }
                                log.info("均值差不满足条件，均值差：" + averageGapValue);
                            }

                            // 下一个△t
                            averageStartTime = averageMiddleTime;
                            averageMiddleTime = averageEndTime;
                            averageCalendar.add(Calendar.MINUTE,configEntity.getT());
                            averageEndTime = averageCalendar.getTime();
                        }
                        break;
                    default:
                        log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：未知触发规则,triggerRule" + configEntity.getTriggerRule());
                        continue;
                }
                if (adjustValue == null) {
                    log.info("影响用户[" + pointInfo.getPointName() + "]调整失败原因：未达到触发条件");
                    continue;
                }

                // 调整系数
                adjustValue = adjustValue * configEntity.getAdjustCoefficient();
                // 调整方向
                adjustValue = adjustValue * configEntity.getAdjustDirection();
                // 累加到最终调整值
                finalAdjustValue += adjustValue;
            }
            // 执行调整
            if (finalAdjustValue.equals(0.0)) {
                log.info("自动调整失败原因：finalAdjustValue为0，outputId：" + outputId + "，configCode:" + configCode);
                continue;
            }
            List<InfluxModelResultPOJO> lastList = new ArrayList<>();
            for (InfluxModelResultVO resultVO : influxModelResult) {
                InfluxModelResultLastSimPOJO adjustPojo = new InfluxModelResultLastSimPOJO();
                // 设置新的调整值
                adjustPojo.setValue(Double.parseDouble(resultVO.getValue().toString()) + finalAdjustValue);
                adjustPojo.setTimestamp(resultVO.getTimestamp());
                adjustPojo.setOutPutId(outputId);
                lastList.add(adjustPojo);
            }
            // 相同时间直接覆盖旧值
            influxDBService.asyncWriteModelResults(lastList);
            log.info("t+l自动调整。configCode:" + configCode + ",adjustValue:" + finalAdjustValue + "，itemNo：" + item.getItemNo() + "，itemName：" + item.getItemName() + "，outputId：" + outputId + ",adjustTime：" + adjustStartTime);
        }

        return true;
    }
}