import csv
import re
#import matplotlib
#import matplotlib.pyplot as plt
import datetime
#import pandas
#from dateutil.parser import parse
#def parse_csv_file():
timestamp = datetime.datetime.strptime('00:00:00.000', '%H:%M:%S.%f')
timestamp_list = []
snr_list = []
freq_list = []
rssi_list = []
dab_present_list = []
counter = 0
f = open("output.txt","w")
with open('test_log_20150325_gps.csv', encoding='cp1252') as csvfile:
reader = csv.reader(csvfile, delimiter=';')
for row in reader:
#timestamp = datetime.datetime.strptime(row[0], '%M:%S.%f')
#timestamp.split(" ",1)
timestamp = row[0]
timestamp_list.append(timestamp)
#timestamp = row[0]
details = row[-1]
counter += 1
print (counter)
#if(counter > 25000):
# break
#timestamp = datetime.datetime.strptime(row[0], '%M:%S.%f')
#timestamp_list.append(float(timestamp))
#search for SNRLevel=\d+
snr = re.findall('SNRLevel=(\d+)', details)
if snr == []:
snr = 0
else:
snr = snr[0]
snr_list.append(int(snr))
#search for Frequency=09ABC
freq = re.findall('Frequency=([0-9a-fA-F]+)', details)
if freq == []:
freq = 0
else:
freq = int(freq[0], 16)
freq_list.append(int(freq))
#search for RSSI=\d+
rssi = re.findall('RSSI=(\d+)', details)
if rssi == []:
rssi = 0
else:
rssi = rssi[0]
rssi_list.append(int(rssi))
#search for DABSignalPresent=\d+
dab_present = re.findall('DABSignalPresent=(\d+)', details)
if dab_present== []:
dab_present = 0
else:
dab_present = dab_present[0]
dab_present_list.append(int(dab_present))
f.write(str(timestamp) + "\t")
f.write(str(freq) + "\t")
f.write(str(snr) + "\t")
f.write(str(rssi) + "\t")
f.write(str(dab_present) + "\n")
print (timestamp, freq, snr, rssi, dab_present)
#print (index+1)
#print(timestamp,freq,snr)
#print (counter)
#print(timestamp_list,freq_list,snr_list,rssi_list)
'''if snr != []:
if freq != []:
timestamp_list.append(timestamp)
snr_list.append(snr)
freq_list.append(freq)
f.write(str(timestamp_list) + "\t")
f.write(str(freq_list) + "\t")
f.write(str(snr_list) + "\n")
print(timestamp_list,freq_list,snr_list)'''
f.close()
#for i in timestamp:
# timestamp
#return plt.plot(timestamp , freq)
#print (timestamp)
#timestamp.plot()
#search for RSSI'''
#return [timestamp, snr, freq]
#main
'''mydata = []
mydata= parse_csv_file()
'''
'''time = mydata[0]
snr = mydata[1]
freq = mydata[2]
'''