#!/usr/bin/env python3 """ This program is used to read in a LANforge Dataplane CSV file and output a csv file that works with a customer's RvRvO visualization tool. Example use case: Read in ~/text-csv-0-candela.csv, output is stored at outfile.csv ./py-scripts/csv_convert.py -i ~/text-csv-0-candela.csv Output is csv file with mixxed columns, top part: Test Run,Position [Deg],Attenuation 1 [dB], Pal Stats Endpoint 1 Control Rssi [dBm], Pal Stats Endpoint 1 Data Rssi [dBm] Second part: Step Index,Position [Deg],Attenuation [dB],Traffic Pair 1 Throughput [Mbps] """ import sys import os import argparse if sys.version_info[0] != 3: print("This script requires Python 3") exit(1) sys.path.append(os.path.join(os.path.abspath(__file__ + "../../../"))) class CSVParser: def __init__(self, csv_infile=None, csv_infile2=None, csv_outfile=None): i_atten = -1 i_rotation = -1 i_rxbps = -1 i_beacon_rssi = -1 i_data_rssi = -1 i_rx_mcs = -1 i_tx_mcs = -1 rate_with_units = False fpo = open(csv_outfile, "w") fp = open(csv_infile) fp2 = None if csv_infile2: fp2 = open(csv_infile2) if True: line = fp.readline() if not line: exit(1) # Concat lines so we can read data from both csv files. if fp2: l2 = fp2.readline() if l2: line = "%s,%s" %(line, l2) # Read in initial line, this is the CSV headers. Parse it to find the column indices for # the columns we care about. x = line.split(",") cni = 0 for cn in x: #print("cn: " + cn) # This works with the 'brief' csv output. if cn == "Attenuation [dB]": i_atten = cni if cn == "Position [Deg]": i_rotation = cni if cn == "Throughput [Mbps]": i_rxbps = cni if cn == "Beacon RSSI [dBm]": i_beacon_rssi = cni if cn == "Data RSSI [dBm]": i_data_rssi = cni # This is for parsing the more complete csv output. if cn == "Atten": i_atten = cni if cn == "Rotation": i_rotation = cni if cn == "Rx-Bps": rate_with_units = True i_rxbps = cni # NOTE: Beacon RSSI does not exist in the 'full' csv if cn == "RSSI": i_data_rssi = cni if cn == "Tx-Rate": i_tx_mcs = cni if cn == "Rx-Rate": i_rx_mcs = cni cni += 1 # Write out out header for the new file. fpo.write("Test Run,Position [Deg],Attenuation 1 [dB],Pal Stats Endpoint 1 Control Rssi [dBm],Pal Stats Endpoint 1 Data Rssi [dBm] Mean,Pal Stats Endpoint 1 RX rate [Mbps] Mode,Pal Stats Endpoint 1 TX rate [Mbps] Mode\n") # Read rest of the input lines, processing one at a time. Covert the columns as # needed, and write out new data to the output file. line = fp.readline() # Concat lines so we can read data from both csv files. if fp2: l2 = fp2.readline() if l2: line = "%s,%s" %(line, l2) bottom_half = "Step Index,Position [Deg],Attenuation [dB],Traffic Pair 1 Throughput [Mbps]\n" test_run = "1" step_i = 0 while line: x = line.split(",") beacon_rssi = "0" if (i_beacon_rssi >= 0): beacon_rssi = x[i_beacon_rssi] tx_rate = "0" rx_rate = "0" if (i_tx_mcs >= 0): tx_rate = self.convert_to_mbps(x[i_tx_mcs]) if (i_rx_mcs >= 0): rx_rate = self.convert_to_mbps(x[i_rx_mcs]) fpo.write("%s,%s,%s,%s,%s,%s,%s\n" % (test_run, x[i_rotation], x[i_atten], beacon_rssi, x[i_data_rssi], tx_rate, rx_rate)) bottom_half += ("%s,%s,%s,%s\n" % (step_i, x[i_rotation], x[i_atten], self.convert_to_mbps(x[i_rxbps]))) line = fp.readline() # Concat lines so we can read data from both csv files. if fp2: l2 = fp2.readline() if l2: line = "%s,%s" %(line, l2) step_i += 1 # First half is written out now, and second half is stored... fpo.write("\n\n# RvRvO Data\n\n") fpo.write(bottom_half) def convert_to_mbps(self, val): tokens = val.split(" ") rv = float(tokens[0]) try: units = tokens[1] if units == "Gbps": rv = rv * 1000.0; if units == "Kbps": rv = rv / 1000.0 return int(rv) except: # Assume no units and that it is already mbps return int(rv) def main(): parser = argparse.ArgumentParser( prog='csv_convert.py', formatter_class=argparse.RawTextHelpFormatter, epilog='''\ Useful Information: ''', description=''' csv_convert.py: converts the candela brief csv and/or more complete csv into the data for specific customer. Both csv files need to be passed in order to have beacon rssi and phy rates since neither csv file contains all of that data. Example: ./csv_convert.py -i ~/dataplane-2022-02-08-12-18-45/text-csv-2.csv -I ~/dataplane-2022-02-08-12-18-45/text-csv-0.csv ''') parser.add_argument('-i', '--infile', help="input file of csv data", required=True) parser.add_argument('-I', '--infile2', help="secondary input file of csv data", required=True) parser.add_argument('-o', '--outfile', help="output file in .csv format", default='outfile.csv') args = parser.parse_args() csv_outfile_name = None csv_infile_name = None csv_infile_name2 = None if args.infile: csv_infile_name = args.infile if args.infile2: csv_infile_name2 = args.infile2 if args.outfile: csv_outfile_name = args.outfile print("infile: %s infile2: %s outfile: %s" % (csv_infile_name, csv_infile_name2, csv_outfile_name)) CSVParser(csv_infile_name, csv_infile_name2, csv_outfile_name) if __name__ == "__main__": main()