【python】信令数据判断是否为澳门居民areYouMacanese.py

阳光穿透心脏的1/2处 2023-06-25 11:28 3阅读 0赞

需要将澳门居民从珠海信令中筛选出来，主要分析手机信令特殊时间点特征，整体思路：

1.  对手机信令数据按ID排序；
2.  以一个ID的所有记录作为一个data\_batch进行判别；
3.  识别一个data\_batch中各记录的时间点是否为特殊时间点，生成特征点序列（普通点、入珠点、出珠点）；
4.  根据特征点对，统计在珠停留时间频数；如果出珠点大于等于2，则为澳门居民。

示例数据下载：`https://download.csdn.net/download/baidu_26646129/12060934`

#!/usr/bin/env python3
    # -*- coding: utf-8 -*-
    
    import os, time, math
    
    
    class MacaneseDistinguisher:
    
        def __init__(self, data_path, data_range):
            self.data_path = data_path
            self.data_range = data_range
            self.__data_sort_path = "./data_sort.txt"
            self.__data_start_time = 1569859200
            self.__data_end_time = 1570723200
    
        def sort_data(self):
            data_unsort = []
            with open(self.data_path, "r") as rf:
                lines = rf.readlines()
                data_unsort = lines
            
            data_sort = sorted(data_unsort, key = lambda x: x[0])
    
            with open(self.__data_sort_path, "w") as wf:
                for data in data_sort:
                    wf.write(data)
    
        def generate_data_batches(self):
            data_batch = []
            with open(self.__data_sort_path, "r") as rf:
                data_batch.append(rf.readline())
                for line in rf:
                    if line[0] == data_batch[0][0]:
                        data_batch.append(line)
                    else:
                        yield data_batch
                        data_batch = []
                        data_batch.append(line)
            yield data_batch
    
    
        def __convert_to_time_stamp(self, date_str, time_str):
            whole_time_str = "2019年"+date_str+" "+time_str
            time_array = time.strptime(whole_time_str, "%Y年%m月%d日 %H:%M")
            time_stamp = int(time.mktime(time_array))
            return time_stamp
    
        def __distinguish_timing(self, data_batch_sort):
            in_or_out_timing = []  # 0：普通点 1：入珠海点 2：出珠海点
            
            for i, d in enumerate(data_batch_sort):
                x = d[2]
                y = d[3]
                if x*x + y*y<=0.3:
                    time_current = d[1]
                    if i>0:
                        time_previous = data_batch_sort[i-1][1]
                    else:
                        time_previous = self.__data_start_time
    
                    if i<len(data_batch_sort)-1:
                        time_next = data_batch_sort[i+1][1]
                    else:
                        time_next = self.__data_end_time
                    
                    if time_current - time_previous >= 3 * 3600:  # 入珠
                        in_or_out_timing.append(1)
                    elif time_next - time_current >= 3 * 3600:  # 出珠
                        in_or_out_timing.append(-1)
                    else:
                        in_or_out_timing.append(0)
                else:
                    in_or_out_timing.append(0)
            
            return in_or_out_timing
    
        
        def distinguish_data(self, data_batch):
            data_batch_split = [d.split("\t") for d in data_batch]
            data_batch_alter = [[d[0], self.__convert_to_time_stamp(d[1], d[2]), float(d[3]), float(d[4])] for d in data_batch_split]
            data_batch_sort = sorted(data_batch_alter, key = lambda x:x[1])
    
            # {"id":1, "isMacanese": True, "stayFrequency:":[0,1,2,3,4,5,6,7,8,9,10]}
            distinguish_result = { }
            distinguish_result["id"] = data_batch_sort[0][0]
            distinguish_result["isMacanese"] = False
            distinguish_result["stayFrequency"] = [0] * (self.data_range + 1)
    
            in_or_out_timing = self.__distinguish_timing(data_batch_sort)
    
            # 如果第一个时间点为普通时间点的话，停留时间窗口开始时间为其时间戳
            if in_or_out_timing[0] == 0:
                stay_time_window = [data_batch_sort[0][1]]
            else:
                stay_time_window = []
    
            for i, ioot in enumerate(in_or_out_timing):
                # stay_time_window还未配对成功
                if len(stay_time_window)!=2 and ioot!=0:
                    stay_time_window.append(data_batch_sort[i][1])
    
                if len(stay_time_window)==2:
                    stay_start = math.floor(stay_time_window[0] * 1.0 / 86400)
                    stay_end = math.floor(stay_time_window[1] * 1.0 / 86400)
                    days = stay_end - stay_start
                    distinguish_result["stayFrequency"][days] += 1
                    stay_time_window = []
    
            if len(stay_time_window)==1:
                stay_start = math.floor(stay_time_window[0] * 1.0 / 86400)
                stay_end = math.floor(data_batch_sort[-1][1] * 1.0 / 86400)
                days = stay_end - stay_start
                distinguish_result["stayFrequency"][days] += 1
    
            # 如果出珠到澳时间点大于等于2，说明是澳门人
            count_out = in_or_out_timing.count(-1)
            if count_out>=2:
                distinguish_result["isMacanese"] = True
    
            print(distinguish_result)
            return distinguish_result
    
    
    
    if __name__ == "__main__": 
        data_path = "./data.txt"
        data_range = 10
        md = MacaneseDistinguisher(data_path, data_range)
        md.sort_data()
        data_batches = md.generate_data_batches()
    
        while True:
            try:
                data_batch = next(data_batches)
                md.distinguish_data(data_batch)
            except StopIteration as e:
                print('Generator return value:', e.value)
                break