package data
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import (
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"fmt"
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"regexp"
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"ruleModelEngine/config"
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"ruleModelEngine/db"
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"strings"
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"time"
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)
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// 计算抓拍天数
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func CalculateCaptureDays(details []db.CaptureDetail) (int, int) {
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// 使用 map 来存储每天是否有抓拍记录
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captureMap := make(map[string]bool)
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//pointDate := ""
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//pointTime := ""
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//pointDirection := ""
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overnightCount := 0
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for i, detail := range details {
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// 解析抓拍日期
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layout := "2006-01-02 15:04:05"
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captureTime, err := time.Parse(layout, detail.CaptureDate)
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if err != nil {
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fmt.Println("解析抓拍日期时出错:", err)
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continue
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}
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//fmt.Println(captureTime, detail.Direction)
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// 获取日期部分
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date := captureTime.Format("2006-01-02")
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//time := captureTime.Format("15:04:05")
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// 在 map 中标记这一天有抓拍记录
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captureMap[date] = true
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if i == len(details)-1 {
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break
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}
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// 第一个验证条件：当前为 in，时间在下午 16 点以后
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currTime, _ := time.Parse("2006-01-02 15:04:05", detail.CaptureDate)
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if detail.Direction == "in" && currTime.Hour() >= 16 {
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// 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
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nextDetail := details[i+1]
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nextTime, _ := time.Parse("2006-01-02 15:04:05", nextDetail.CaptureDate)
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nextDay := nextTime.AddDate(0, 0, -1).Format("2006-01-02")
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if nextDetail.Direction == "out" && nextTime.Hour() >= 5 && nextTime.Hour() < 12 && nextDay == detail.CaptureDate[:10] {
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overnightCount++
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}
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}
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}
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// 统计有抓拍记录的天数
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captureDays := 0
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for range captureMap {
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captureDays++
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}
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return captureDays, overnightCount
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}
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// 设置状态
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func SetStatus(captureDays int, rules []db.PersonnelStatusRule) string {
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for _, rule := range rules {
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if captureDays >= rule.DetectionDaysStart && captureDays <= rule.DetectionDaysEnd {
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return rule.Name
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}
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}
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return rules[1].Name
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}
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// 获取常用地址
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func getfrAddress(pointAddress map[string]int) string {
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maxCount := 0
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maxCountAddress := ""
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re1F, _ := regexp.Compile(`\b1F\b`)
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reNoF, _ := regexp.Compile(`^[^F]*$`)
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reNegF := regexp.MustCompile(`-`)
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for address, count := range pointAddress {
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matchFlag1F := re1F.MatchString(address)
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matchFlagNoF := reNoF.MatchString(address)
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matchFlagNegF := reNegF.MatchString(address)
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if address == "" || matchFlag1F || matchFlagNoF || matchFlagNegF {
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continue
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}
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if count > maxCount {
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maxCount = count
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maxCountAddress = address
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}
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}
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return maxCountAddress
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}
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// SetFrequentAddress 方法计算出现最频繁的出行地址并设置为常用地址
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func GetFrequentAddress(captureDetail []db.CaptureDetail) string {
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// 统计每个出行地址的出现次数
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//pointDate 靶标日期，pointAddress靶标地址
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pointDate := ""
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pointAddress := make(map[string]int, 0)
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//dateAddress 按日期汇总单日常用地址
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dateAddress := make(map[string]string, 0)
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//floor1Address 后备地址，为1楼地址
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floor1Address := ""
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//captureDays 按日期去重统计总抓拍天数
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captureDays := make(map[string]int, 0)
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//frequentAddress 最终设置的常用地址
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var frequentAddress string
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//正则 判断地址是否包含1F字样，完全匹配
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re1F, _ := regexp.Compile(`\b1F\b`)
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reNoF, _ := regexp.Compile(`^[^F]*$`)
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// 遍历所有抓拍数据
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for index, detail := range captureDetail {
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//fmt.Println("抓拍地址：", detail.CaptureAddress)
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//fmt.Println("抓拍日期：", detail.CaptureDate)
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//dateStr截取的日期，为YYYY-MM-DD
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dateStr := strings.Split(detail.CaptureDate, " ")[0]
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//去重统计抓拍天数 captureDays
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captureDays[dateStr]++
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//匹配是否是1F
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matchFlag1F := re1F.MatchString(detail.CaptureAddress)
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matchFlagNoF := reNoF.MatchString(detail.CaptureAddress)
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if matchFlag1F {
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//如果是， 提前设置好备用地址 floor1Address = detail.CaptureAddress
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floor1Address = detail.CaptureAddress
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}
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if matchFlagNoF && floor1Address == "" {
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//如果是， 提前设置好备用地址 floor1Address = detail.CaptureAddress
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floor1Address = detail.CaptureAddress
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}
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//fmt.Println("now floor1Address:", floor1Address,"\tnow detail CaptureAddress",detail.CaptureAddress)
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//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
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if pointDate == "" {
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//初始化日期靶标为当前日期
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pointDate = dateStr
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//把当前日期的
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pointAddress[detail.CaptureAddress]++
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//若为最后一条则计算单日常用地址
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if index == len(captureDetail)-1 {
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//fmt.Println("处理前pointAddress表：", pointAddress)
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//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
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//否则会初始化pointDate和pointAddress
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dateAddress[pointDate] = detail.CaptureAddress
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}
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continue
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}
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//若日期标相等则为同一天
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if pointDate == dateStr {
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//pointAddress靶标日期数组对应楼层地址数+1
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pointAddress[detail.CaptureAddress]++
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//若为最后一条则计算单日常用地址
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if index == len(captureDetail)-1 {
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//fmt.Println("处理前pointAddress表：", pointAddress)
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//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
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dateAddress[pointDate] = getfrAddress(pointAddress)
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continue
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}
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//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
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} else {
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//若为最后一条则计算单日常用地址
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if index == len(captureDetail)-1 {
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//把当前最后一条加入 pointAddress靶标地址
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pointAddress[detail.CaptureAddress]++
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//
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//fmt.Println("处理前pointAddress表：", pointAddress)
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//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
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dateAddress[pointDate] = getfrAddress(pointAddress)
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continue
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}
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//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
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dateAddress[pointDate] = getfrAddress(pointAddress)
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//初始化新的一天的靶标日期和pointAddress 靶标地址数组
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pointDate = dateStr
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pointAddress = make(map[string]int, 0)
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}
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}
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//fmt.Println("抓拍地址待处理结构表：", dateAddress)
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//fmt.Println("dareAddress len: ", len(dateAddress))
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//判断抓拍的非1楼非空非地下的天数占比总天数
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if float64(len(dateAddress))/float64(len(captureDays))*100 >= float64(config.Api.CapAddrDaysThreshold) {
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//fmt.Println("非1楼非空抓拍占比: ", float64(len(dateAddress))/float64(len(captureDays))*100)
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//初始化地址列表，按地址计数
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addressCount := make(map[string]int)
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//遍历之前汇总的单日常用地址列表
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for _, address := range dateAddress {
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//对应地址数+1
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addressCount[address]++
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}
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//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
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frequentAddress = getfrAddress(addressCount)
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} else {
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//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
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frequentAddress = floor1Address
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}
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//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
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if frequentAddress == "" {
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frequentAddress = floor1Address
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}
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//fmt.Println("in address: ", inAddressCounts)
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//fmt.Println("out address: ", outAddressCounts)
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//fmt.Println("final address: ", frequentAddress)
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return frequentAddress
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}
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// 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
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func ProcessData(captureInfos []db.CaptureInfo, personStatus []*db.PersonStatus, ruleInfos []db.PersonnelStatusRule, statusNo map[string]int, communityID string) []db.PersonStatus {
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filteredInfos := make([]db.PersonStatus, 0)
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// 构建快速查找索引，方便查找对应的人员状态和规则
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statusIndex := make(map[string]db.PersonStatus)
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ruleIndex := make(map[string]db.PersonnelStatusRule)
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for _, person := range personStatus {
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statusIndex[person.DocumentNumber] = *person
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}
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for _, rule := range ruleInfos {
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ruleIndex[rule.Name] = rule
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}
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//fmt.Println("statusIndex: ", statusIndex)
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//fmt.Println("ruleIndex: ", ruleIndex)
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// 处理每个抓拍信息
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for _, info := range captureInfos {
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//fmt.Println("info", info.DocumentNumber, info.Status, info.FrequentAddress)
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//fmt.Println("person", statusIndex[info.DocumentNumber].DocumentNumber, statusIndex[info.DocumentNumber].Status, statusIndex[info.DocumentNumber].FrequentAddress)
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// 检查是否存在对应的人员状态
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person := statusIndex[info.DocumentNumber]
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//fmt.Println("person: ", person.DocumentNumber, person.Status, person.FrequentAddress, person.LastAppearanceTime, person.LastAppearanceStatusTime)
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// 判断状态和常用地址是否相等，如果相等则忽略
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//if (info.Status == person.Status || info.CaptureDays <= ruleIndex[person.DocumentNumber].DetectionDaysEnd) &&
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// info.FrequentAddress == person.FrequentAddress {
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// continue
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//}
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// 更新过滤后的信息列表
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//fmt.Println("LastAppearanceTime: ", person.LastAppearanceTime)
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if statusNo[person.Status] > statusNo[info.Status] {
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continue
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}
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filteredInfos = append(filteredInfos, db.PersonStatus{CommunityID: communityID, DocumentNumber: info.DocumentNumber, Status: info.Status, FrequentAddress: info.FrequentAddress, LastAppearanceStatusTime: person.LastAppearanceTime})
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}
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//fmt.Println("filteredInfos: ", filteredInfos)
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return filteredInfos
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}
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