import os
import pandas as pd
from libcity.data.dataset.trajectory_encoder.abstract_trajectory_encoder import AbstractTrajectoryEncoder
from libcity.utils import parse_time
parameter_list = ['dataset', 'min_session_len', 'min_sessions', 'traj_encoder', 'cut_method',
'window_size']
[docs]class CARATrajectoryEncoder(AbstractTrajectoryEncoder):
def __init__(self, config):
super().__init__(config)
self.uid = 0
self.location2id = {} # 因为原始数据集中的部分 loc id 不会被使用到因此这里需要重新编码一下
self.loc_id = 0
self.id2locid = {}
self.tim_max = 47 # 时间编码方式得改变
self.feature_dict = {'current_loc': 'int', 'current_tim': 'int',
'target': 'int', 'target_tim': 'int', 'uid': 'int'
}
parameters_str = ''
for key in parameter_list:
if key in self.config:
parameters_str += '_' + str(self.config[key])
self.cache_file_name = os.path.join(
'./libcity/cache/dataset_cache/', 'trajectory_{}.json'.format(parameters_str))
self.poi_profile = pd.read_csv('./raw_data/{}/{}.geo'.format(self.config['dataset'], self.config['dataset']))
[docs] def encode(self, uid, trajectories, negative_sample=None):
"""standard encoder use the same method as DeepMove
Recode poi id. Encode timestamp with its hour.
Args:
uid ([type]): same as AbstractTrajectoryEncoder
trajectories ([type]): same as AbstractTrajectoryEncoder
trajectory1 = [
(location ID, timestamp, timezone_offset_in_minutes),
(location ID, timestamp, timezone_offset_in_minutes),
.....
]
"""
# 直接对 uid 进行重编码
uid = self.uid
self.uid += 1
encoded_trajectories = []
for index, traj in enumerate(trajectories):
current_loc = []
current_tim = []
for point in traj:
loc = point[4]
now_time = parse_time(point[2])
if loc not in self.location2id:
self.location2id[loc] = self.loc_id
self.id2locid[str(self.loc_id)] = loc
self.loc_id += 1
current_loc.append(self.location2id[loc])
time_code = self._time_encode(now_time)
current_tim.append(time_code)
# 完成当前轨迹的编码，下面进行输入的形成
trace = []
target = current_loc[-1]
target_tim = current_tim[-1]
current_loc = current_loc[:-1]
current_tim = current_tim[:-1]
trace.append(current_loc)
trace.append(current_tim)
trace.append(target)
trace.append(target_tim)
trace.append(uid)
encoded_trajectories.append(trace)
return encoded_trajectories
[docs] def gen_data_feature(self):
loc_pad = self.loc_id
tim_pad = self.tim_max + 1
self.pad_item = {
'current_loc': loc_pad,
'current_tim': tim_pad
}
# 构建 poi 坐标字典
poi_coor = {}
for index, row in self.poi_profile.iterrows():
geo_id = row['geo_id']
coor = eval(row['coordinates'])
poi_coor[str(geo_id)] = coor
self.data_feature = {
'loc_size': self.loc_id + 1,
'tim_size': self.tim_max + 2,
'uid_size': self.uid,
'loc_pad': loc_pad,
'tim_pad': tim_pad,
'id2locid': self.id2locid,
'poi_coor': poi_coor
}
def _time_encode(self, time):
if time.weekday() in [0, 1, 2, 3, 4]:
return time.hour
else:
return time.hour + 24