def main_process():
KNN, zone_int_dict = get_model()
# no duplicate value, so reverse this dictionary
int_zone_dict = dict(zip(zone_int_dict.values(), zone_int_dict.keys()))
file_list = glob.glob(SRC_FOLDER + '/*csv.gz')
# mac_sn_dict : { (mac_address,time_accurate_to_10_seconds):[signal_strength according to the routers] }
mac_sn_dict = {}
for f in file_list:
placement_name = re.findall("\d{7}", f)[0]
router_bssid = PLC_ROUTER_DICT[placement_name]
try:
with gzip.open(f, 'rb') as fp:
reader = csv.reader(fp)
for row in reader:
# jump first row
if reader.line_num == 1:
continue
# process each ros
mac = str(row[3]).lower()
ssid = str(row[7])
time = int(row[0]) / 10 * 10
sn = int(row[6])
if router_bssid in ROUTERS:
index = ROUTERS.index(router_bssid)
tmp_key = (mac, time)
if tmp_key not in mac_sn_dict:
mac_sn_dict[tmp_key] = [-100] * ROUTERS_NUM
mac_sn_dict[tmp_key][index] = sn
except Exception as e:
print e
print f
fout = open(RESULT_CSV, 'w')
writer = csv.writer(fout)
writer.writerow(['mac', 'time'] + ROUTERS + ['zone'])
vender_checker = get_vendor_checker()
data_row_cache = []
for key in mac_sn_dict:
mac = key[0]
if str(mac) in ROUTERS:
continue
vender = vender_checker.get_manuf(str(mac))
time = datetime.datetime.utcfromtimestamp(key[1] + 8 * 60 * 60) # transfer to local time
x_data = numpy.array([map(int, mac_sn_dict[key])])
predict_result = int_zone_dict[int((KNN.predict(x_data)[0]))]
tmp_probability = max(KNN.predict_proba(x_data)[0])
data_row_cache.append([mac, time] + mac_sn_dict[key] + [predict_result, vender])
print 'sort the result'
data_row_cache = sorted(data_row_cache, key=lambda x: (x[0], x[1]))
for row in data_row_cache:
writer.writerow(row)
print 'finished'
from wifi_util.download_csv import download_csv
from wifi_tracking_training import number_to_char,get_model
LOCAL_DIR = '../data/'
REMOTE_DIR = 'data/combined/wifi/'
LOCATION_ID = '39'
placements = ['8100109','8100110','8100111','8100112']
BUCKET = 'percolata-data'
DATE_TIME = '2015-12-14'
curr_start = 16*4
next_end = 3*4
ROUTERS = ['2c:5d:93:3b:40:59', 'f2:14:24:07:bf:90', 'f0:99:bf:07:24:14', '2c:5d:93:3b:40:58', 'c0:a0:bb:c5:61:56']
SSID_MAP = {'PPS Guest Network':'f2:14:24:07:bf:90','BaySensors':'c0:a0:bb:c5:61:56','Percolata':'2c:5d:93:3b:40:58',\
'PPS Network':'f0:99:bf:07:24:14','Field Architecture':'0e:18:d6:53:bf:90'}
RESULT_CSV = 'result.csv'
KNN = get_model()
def download_data():
download_csv(LOCATION_ID,placements,DATE_TIME,BUCKET,curr_start,next_end,LOCAL_DIR,REMOTE_DIR)
def generate_csv():
# mac_sn_dict : { (mac_address,time_accurate_to_10_seconds):[signal_strength according to the routers] }
mac_sn_dict = {}
fl = os.listdir(LOCAL_DIR+str(LOCATION_ID)+'/'+DATE_TIME+'/')
ROUTERS_NUM = len(ROUTERS)
for f in fl:
try:
with gzip.open(LOCAL_DIR+str(LOCATION_ID)+'/'+DATE_TIME+'/'+f,'rb') as fp:
reader = csv.reader(fp)
for row in reader:
# jump first row