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07encode_plot_bak.py
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07encode_plot_bak.py
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import numpy as np
import re
from datetime import datetime
from tqdm import tqdm
import os
import time
from tools import general
def statistics_sensors(data_dir, data_name, debuge=True):
sensor_set = set()
print('dataset: %s' % os.path.join(data_dir, data_name))
list_activitydata = os.listdir(os.path.join(data_dir, data_name))
for str_activitydata in list_activitydata:
print('activity: %s : %s' % (data_name, str_activitydata))
with open(os.path.join(data_dir, data_name, str_activitydata), 'r') as fr:
lines = fr.readlines()
for i, line in enumerate(lines):
f_info = line.split()
if len(f_info) >= 5:
sensor = f_info[3]
sensor_set.add(sensor)
print('The returned is the sensor list, which can be coded after numbering and adding the status code')
return sensor_set
# Input: sensor list
# Return: sensor code dictionary
def conver_sensor2dict(set_sensors, data_name, distant_int, opts):
serial_number = 1
dict_sensor2serial_number = {}
for sensor in sorted(set_sensors):
if sensor[0] == 'A' or sensor[0] == 'P' or sensor[0] == 'T':
dict_sensor2serial_number.update({sensor: str(serial_number)})
serial_number += 1
elif sensor[0] == 'M': # ON/OFF
dict_sensor2serial_number.update({sensor + 'ON': str(serial_number)})
serial_number += 1
dict_sensor2serial_number.update({sensor + 'OFF': str(serial_number)})
serial_number += 1
elif sensor[0] == 'L': # ON/OFF
dict_sensor2serial_number.update({sensor + 'ON': str(serial_number)})
serial_number += 1
dict_sensor2serial_number.update({sensor + 'OFF': str(serial_number)})
serial_number += 1
elif sensor[0] == 'D': # OPEN/CLOSE
dict_sensor2serial_number.update({sensor + 'OPEN': str(serial_number)})
serial_number += 1
dict_sensor2serial_number.update({sensor + 'CLOSE': str(serial_number)})
serial_number += 1
elif sensor[0] == 'I': # PRESENT/ABSENT
dict_sensor2serial_number.update({sensor + 'PRESENT': str(serial_number)})
serial_number += 1
dict_sensor2serial_number.update({sensor + 'ABSENT': str(serial_number)})
serial_number += 1
opdir = os.path.join(opts["datasets"]["base_dir"], 'ende', data_name, str(distant_int))
general.create_folder(opdir)
opdoc = os.path.join(opdir, 'sensor2dict.npy')
np.save(opdoc, dict_sensor2serial_number)
print('Save in: %s \n' % (opdoc))
return dict_sensor2serial_number
# Input: dictionary, data directory, dataset name
# Return: save the encoded file to
def encoder_sensors(read_sensor2dict, data_dir, data_name, distant_int, opts, debuge=True):
print('\n' + '*' * 40)
print("data_name location: %s" % (os.path.join(data_dir, data_name)))
dict_ids = {}
list_activitydata = os.listdir(os.path.join(data_dir, data_name))
for str_activitydata in list_activitydata:
list_ids = []
with open(os.path.join(data_dir, data_name, str_activitydata), 'r') as fr:
lines = fr.readlines()
list_id = []
for i, line in enumerate(lines):
f_info = line.split()
if len(f_info) >= 5:
sensor = f_info[3]
if sensor[0] == 'M' or sensor[0] == 'D' or sensor[0] == 'I' or sensor[
0] == 'L':
if f_info[4] in ['ON', 'OFF', 'ABSENT', 'PRESENT', 'OPEN', 'CLOSE']:
list_id.append(read_sensor2dict[f_info[3] + f_info[4]])
else:
print('This data is abnormal status data, which may be marked incorrectly. The data is: %s' % line)
elif sensor[0] == 'A' or sensor[0] == 'P' or sensor[0] == 'T':
list_id.append(read_sensor2dict[f_info[3]])
elif sensor[0] == 'E':
pass
else:
print('dataset：%s\tactivity:%s\trow:%d data:%s\n' % (data_name, str_activitydata, i, line))
else:
list_ids.append(list_id)
list_id = []
dict_ids.update({str_activitydata: list_ids})
opdir = os.path.join(opts["datasets"]["base_dir"], 'ende', data_name, str(distant_int))
opdoc = os.path.join(opdir, data_name + '-dict_ids.npy')
np.save(opdoc, dict_ids)
print('save in: %s ' % opdir)
# Input: dictionary, data directory, dataset name
# Return: the decoded file is saved to
def decoder_sensors(read_sensor2dict, data_dir, data_name, opts, debuge=True):
data_dir = os.path.join(opts["datasets"]["base_dir"], 'ende', data_name, str(distant_int))
print('location: %s' % data_dir)
dict_sensors = {}
dict_ids = np.load(os.path.join(data_dir, data_name + '-dict_ids.npy'), allow_pickle=True).item()
for str_activities in dict_ids:
list_sensors = []
for list_activities in dict_ids[str_activities]:
list_sensor = []
for str_id in list_activities:
try:
str_sensor = list(read_sensor2dict.keys())[
list(read_sensor2dict.values()).index(str_id)]
except IndexError:
print('%s:Illegal code value exists, please check the data...' % (str_id))
list_sensor.append(str_sensor)
list_sensors.append(list_sensor)
dict_sensors.update({str_activities: list_sensors})
opdir = os.path.join(opts["datasets"]["base_dir"], 'ende', data_name, str(distant_int))
opname = os.path.join(opdir, data_name + '-dict_sensors.npy')
np.save(opname, dict_sensors)
print('save in: %s ' % opdir)
# Input: code dictionary, list_ id
# Return: List sensors
def list_id2sensor(read_sensor2dict, list_ids):
list_sensor = []
for str_id in list_ids:
str_sensor = list(read_sensor2dict.keys())[list(read_sensor2dict.values()).index(str_id)]
# print(str_sensor)
list_sensor.append(str_sensor)
return list_sensor
if __name__ == '__main__':
opts = general.load_config()
for i in range(6):
distant_int = i
if distant_int == 0:
data_dir = os.path.join(opts["datasets"]["base_dir"], 'cutdata')
elif str(distant_int) in os.listdir(os.path.join(opts["datasets"]["base_dir"], 'constraintdata')):
data_dir = os.path.join(opts["datasets"]["base_dir"], 'constraintdata', str(distant_int))
else:
print('The current distance limit is incorrect, please re-enter')
exit(-1000)
data_names = ['cairo', 'milan', 'kyoto7', 'kyoto8', 'kyoto11']
for data_name in data_names:
# Setp 1: Count the sensor data and save the sensor dictionary
set_sensors = statistics_sensors(data_dir, data_name)
sensor2dict = conver_sensor2dict(set_sensors, data_name, distant_int, opts)
encoder_dict_path = os.path.join(opts["datasets"]["base_dir"], 'ende', data_name, str(distant_int), 'sensor2dict.npy')
read_sensor2dict = np.load(encoder_dict_path, allow_pickle=True).item()
# Setp 2: Encode data
encoder_sensors(read_sensor2dict, data_dir, data_name, distant_int, opts, debuge=True)
# Setp 3: Decode data(Optional)
decoder_sensors(read_sensor2dict, data_dir, data_name, opts, debuge=True)
# Decoded data test view
# ids_dir = r'D:\Anaconda3\workspace\py36TF\dpcnnfdal\processdata\09-encodersensors'
# ids_name = r'kyoto7-dict_sensors.npy'
# dict_ids = np.load(ids_dir + '\\' + ids_name, allow_pickle=True).item()
# for activity_name in dict_ids:
# for list_sensors in dict_ids[activity_name]:
# print(list_sensors)
# Test and decode a single piece of data
ids_dir = os.path.join(opts["datasets"]["base_dir"], 'ende', data_name, str(distant_int))
ids_name = data_name + r'-dict_ids.npy'
dict_ids = np.load(os.path.join(ids_dir, ids_name), allow_pickle=True).item()
for str_activity in dict_ids:
for list_ids in dict_ids[str_activity]:
# list_sensor = list_id2sensor(read_sensor2dict, list_ids)
# print(list_sensor)
pass
print('success, all finished!')