def main():
#download_file()
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(local_path + date_time + '/*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)
# routers a,b,c if phone send 2 pkgs(c,d) c is detected by a, d is detected by b,c ,can get good result without seqid as key
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 = np.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'
def main_process():
KNN, path_int_dict = get_model()
# no duplicate value, so reverse this dictionary
int_path_dict = dict(zip(path_int_dict.values(), path_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 + ['path', 'probability', 'vendor'])
data_row_cache = []
for key in mac_sn_dict:
mac = key[0]
if str(mac) in ROUTERS:
continue
time = datetime.datetime.utcfromtimestamp(key[1] + 8 * 60 * 60) # transfer to local time
data_row_cache.append([mac, time] + mac_sn_dict[key])
print 'sort the result'
data_row_cache = sorted(data_row_cache, key=lambda x: (x[0], x[1]))
row_len = len(data_row_cache)
diff_sn_cache = []
new_data_row_cache = []
for i in range(row_len - 2):
mac_a = data_row_cache[i][0]
mac_b = data_row_cache[i + 1][0]
# delete last row, save the info in new_data_row_cache
if mac_a != mac_b:
continue
start_sn_list = data_row_cache[i][-3:]
end_sn_list = data_row_cache[i + 1][-3:]
# A to B
diff_sn = [x - y for (x, y) in zip(end_sn_list, start_sn_list)]
diff_sn_cache.append(diff_sn)
new_data_row_cache.append(data_row_cache[i])
# predict
predict_result = KNN.predict(numpy.array(diff_sn_cache))
proba_result = KNN.predict_proba(numpy.array(diff_sn_cache))
# add path,probability,vendor
row_len = len(new_data_row_cache)
vender_checker = get_vendor_checker()
for i in range(row_len - 1):
mac = new_data_row_cache[i][0]
tmp_path = int_path_dict[predict_result[i]]
tmp_proba = max(proba_result[i])
vender = vender_checker.get_manuf(str(mac))
new_data_row_cache[i] += [str(tmp_path), tmp_proba, vender]
# save in csv
for row in new_data_row_cache:
writer.writerow(row)
print 'finished'
