package data

import (
	"fmt"
	"regexp"
	"ruleModelEngine/config"
	"ruleModelEngine/db"
	"strings"
	"time"
)

// 计算抓拍天数
func CalculateCaptureDays(details []db.CaptureDetail) (int, int) {
	// 使用 map 来存储每天是否有抓拍记录
	captureMap := make(map[string]bool)
	//pointDate := ""
	//pointTime := ""
	//pointDirection := ""
	overnightCount := 0
	for i, detail := range details {
		// 解析抓拍日期
		layout := "2006-01-02 15:04:05"
		captureTime, err := time.Parse(layout, detail.CaptureDate)
		if err != nil {
			fmt.Println("解析抓拍日期时出错:", err)
			continue
		}
		//fmt.Println(captureTime, detail.Direction)
		// 获取日期部分
		date := captureTime.Format("2006-01-02")
		//time := captureTime.Format("15:04:05")
		// 在 map 中标记这一天有抓拍记录
		captureMap[date] = true
		if i == len(details)-1 {
			break
		}

		// 第一个验证条件：当前为 in，时间在下午 16 点以后
		currTime, _ := time.Parse("2006-01-02 15:04:05", detail.CaptureDate)
		if detail.Direction == "in" && currTime.Hour() >= 16 {
			// 第二个验证条件：下一个为 out，时间在上午 5 点之后 12 点之前
			nextDetail := details[i+1]
			nextTime, _ := time.Parse("2006-01-02 15:04:05", nextDetail.CaptureDate)
			nextDay := nextTime.AddDate(0, 0, -1).Format("2006-01-02")
			if nextDetail.Direction == "out" && nextTime.Hour() >= 5 && nextTime.Hour() < 12 && nextDay == detail.CaptureDate[:10] {
				overnightCount++
			}
		}
	}

	// 统计有抓拍记录的天数
	captureDays := 0
	for range captureMap {
		captureDays++
	}

	return captureDays, overnightCount
}

// 设置状态
func SetStatus(captureDays int, rules []db.PersonnelStatusRule) string {
	for _, rule := range rules {
		if captureDays >= rule.DetectionDaysStart && captureDays <= rule.DetectionDaysEnd {
			return rule.Name
		}
	}
	return rules[1].Name
}

// 获取常用地址
func getfrAddress(pointAddress map[string]int) string {
	maxCount := 0
	maxCountAddress := ""
	re1F, _ := regexp.Compile(`\b1F\b`)
	reNoF, _ := regexp.Compile(`^[^F]*$`)
	reNegF := regexp.MustCompile(`-`)
	for address, count := range pointAddress {
		matchFlag1F := re1F.MatchString(address)
		matchFlagNoF := reNoF.MatchString(address)
		matchFlagNegF := reNegF.MatchString(address)
		if address == "" || matchFlag1F || matchFlagNoF || matchFlagNegF {
			continue
		}
		if count > maxCount {
			maxCount = count
			maxCountAddress = address
		}
	}
	return maxCountAddress
}

// SetFrequentAddress 方法计算出现最频繁的出行地址并设置为常用地址
func GetFrequentAddress(captureDetail []db.CaptureDetail) string {
	// 统计每个出行地址的出现次数
	//pointDate 靶标日期，pointAddress靶标地址
	pointDate := ""
	pointAddress := make(map[string]int, 0)
	//dateAddress 按日期汇总单日常用地址
	dateAddress := make(map[string]string, 0)
	//floor1Address 后备地址，为1楼地址
	floor1Address := ""
	//captureDays 按日期去重统计总抓拍天数
	captureDays := make(map[string]int, 0)
	//frequentAddress 最终设置的常用地址
	var frequentAddress string
	//正则 判断地址是否包含1F字样，完全匹配
	re1F, _ := regexp.Compile(`\b1F\b`)
	reNoF, _ := regexp.Compile(`^[^F]*$`)
	// 遍历所有抓拍数据
	for index, detail := range captureDetail {
		//fmt.Println("抓拍地址：", detail.CaptureAddress)
		//fmt.Println("抓拍日期：", detail.CaptureDate)
		//dateStr截取的日期，为YYYY-MM-DD
		dateStr := strings.Split(detail.CaptureDate, " ")[0]
		//去重统计抓拍天数 captureDays
		captureDays[dateStr]++
		//匹配是否是1F
		matchFlag1F := re1F.MatchString(detail.CaptureAddress)
		matchFlagNoF := reNoF.MatchString(detail.CaptureAddress)
		if matchFlag1F {
			//如果是， 提前设置好备用地址 floor1Address = detail.CaptureAddress
			floor1Address = detail.CaptureAddress
		}
		if matchFlagNoF && floor1Address == "" {
			//如果是， 提前设置好备用地址 floor1Address = detail.CaptureAddress
			floor1Address = detail.CaptureAddress
		}
		//fmt.Println("now floor1Address:", floor1Address,"\tnow detail CaptureAddress",detail.CaptureAddress)
		//判断日期标是否满足条件 判断日期标是否为空，若为空表示是第一个元素，初始化日期靶标
		if pointDate == "" {
			//初始化日期靶标为当前日期
			pointDate = dateStr
			//把当前日期的
			pointAddress[detail.CaptureAddress]++
			//若为最后一条则计算单日常用地址
			if index == len(captureDetail)-1 {
				//fmt.Println("处理前pointAddress表：", pointAddress)
				//这代表仅有一条数据，将会直接把当前地址加入dateAddress 日期汇总单日常用地址表内 下方continue会直接结束循环
				//否则会初始化pointDate和pointAddress
				dateAddress[pointDate] = detail.CaptureAddress
			}
			continue
		}
		//若日期标相等则为同一天
		if pointDate == dateStr {
			//pointAddress靶标日期数组对应楼层地址数+1
			pointAddress[detail.CaptureAddress]++
			//若为最后一条则计算单日常用地址
			if index == len(captureDetail)-1 {
				//fmt.Println("处理前pointAddress表：", pointAddress)
				//计算单日常用地址 若地址内都为1F或者空地址，会返回空地址
				dateAddress[pointDate] = getfrAddress(pointAddress)
				continue
			}
			//不相等则为新的日期，首先计算出当日的常用地址，然后重新初始化日期标和地址标数组
		} else {
			//若为最后一条则计算单日常用地址
			if index == len(captureDetail)-1 {
				//把当前最后一条加入	pointAddress靶标地址
				pointAddress[detail.CaptureAddress]++
				//
				//fmt.Println("处理前pointAddress表：", pointAddress)
				//计算单日常用地址 若地址内都为1F或者空地址，会返回空地址
				dateAddress[pointDate] = getfrAddress(pointAddress)
				continue
			}
			//不为最后一条表示这是新的一天的抓拍地址数据，需要计算之前一天的单日常用地址
			dateAddress[pointDate] = getfrAddress(pointAddress)
			//初始化新的一天的靶标日期和pointAddress 靶标地址数组
			pointDate = dateStr
			pointAddress = make(map[string]int, 0)
		}
	}
	//fmt.Println("抓拍地址待处理结构表：", dateAddress)
	//fmt.Println("dareAddress len: ", len(dateAddress))
	//判断抓拍的非1楼非空非地下的天数占比总天数
	if float64(len(dateAddress))/float64(len(captureDays))*100 >= float64(config.Api.CapAddrDaysThreshold) {
		//fmt.Println("非1楼非空抓拍占比: ", float64(len(dateAddress))/float64(len(captureDays))*100)
		//初始化地址列表，按地址计数
		addressCount := make(map[string]int)
		//遍历之前汇总的单日常用地址列表
		for _, address := range dateAddress {
			//对应地址数+1
			addressCount[address]++
		}
		//复制常用地址给最终结果，若地址内都为1F或者空地址，会返回空地址
		frequentAddress = getfrAddress(addressCount)
	} else {
		//若不满足非1楼非空抓拍占比，则直接把备用地址（1F）赋值给最终结果
		frequentAddress = floor1Address
	}
	//若存在满足非1楼非空抓拍占比，但是最终结果是空地址，则赋值备用地址（1F）为最终结果
	if frequentAddress == "" {
		frequentAddress = floor1Address
	}
	//fmt.Println("in address: ", inAddressCounts)
	//fmt.Println("out address: ", outAddressCounts)
	//fmt.Println("final address: ", frequentAddress)
	return frequentAddress
}

// processData 函数处理数据，根据要求过滤掉数据并根据规则更新状态
func ProcessData(captureInfos []db.CaptureInfo, personStatus []*db.PersonStatus, ruleInfos []db.PersonnelStatusRule, communityID string) []db.PersonStatus {
	filteredInfos := make([]db.PersonStatus, 0)

	// 构建快速查找索引，方便查找对应的人员状态和规则
	statusIndex := make(map[string]db.PersonStatus)
	ruleIndex := make(map[string]db.PersonnelStatusRule)

	for _, person := range personStatus {
		statusIndex[person.DocumentNumber] = *person
	}

	for _, rule := range ruleInfos {
		ruleIndex[rule.Name] = rule
	}
	//fmt.Println("statusIndex: ", statusIndex)
	//fmt.Println("ruleIndex: ", ruleIndex)
	// 处理每个抓拍信息
	for _, info := range captureInfos {
		//fmt.Println("info", info.DocumentNumber, info.Status, info.FrequentAddress)
		//fmt.Println("person", statusIndex[info.DocumentNumber].DocumentNumber, statusIndex[info.DocumentNumber].Status, statusIndex[info.DocumentNumber].FrequentAddress)
		// 检查是否存在对应的人员状态
		person := statusIndex[info.DocumentNumber]
		//fmt.Println("person: ", person.DocumentNumber, person.Status, person.FrequentAddress, person.LastAppearanceTime, person.LastAppearanceStatusTime)
		// 判断状态和常用地址是否相等，如果相等则忽略
		//if (info.Status == person.Status || info.CaptureDays <= ruleIndex[person.DocumentNumber].DetectionDaysEnd) &&
		//	info.FrequentAddress == person.FrequentAddress {
		//	continue
		//}
		// 更新过滤后的信息列表
		//fmt.Println("LastAppearanceTime: ", person.LastAppearanceTime)
		filteredInfos = append(filteredInfos, db.PersonStatus{CommunityID: communityID, DocumentNumber: info.DocumentNumber, Status: info.Status, FrequentAddress: info.FrequentAddress, LastAppearanceStatusTime: person.LastAppearanceTime})

	}
	//fmt.Println("filteredInfos: ", filteredInfos)
	return filteredInfos
}