langspielplatte/measurement-scripts
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Moves bandwidth converters to serial format script.

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This commit is contained in:
Lukas Prause
2023-03-14 13:14:24 +01:00
parent a77425cfa2
commit 7bac2f7fd7
2 changed files with 192 additions and 21 deletions
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191
format_serial_txt_to_csv.py Normal file → Executable file
View File

@@ -0,0 +1,191 @@
#!/usr/bin/env python3
import csv
import datetime
from argparse import ArgumentParser
import pandas as pd
def convert_bandwidth(value):
try:
value = int(value)
except:
value = -1
if value == 0:
return 1.4
elif value == 1:
return 3
elif value == 2:
return 5
elif value == 3:
return 10
elif value == 4:
return 15
elif value == 5:
return 20
else:
return 0
if __name__ == "__main__":
parser = ArgumentParser()
parser.add_argument("-f", "--file", required=True, help="Input txt file.")
args = parser.parse_args()
file = open(args.file, "r")
content = file.read()
file.close()
all_csv_lines = list()
csv_header = ["time"]
h1 = False
h2 = False
h3 = False
for line in content.split("\n"):
if line == "" or line == "\n":
break
raw_columns = line.split(";")
csv_line = list()
csv_line.append(raw_columns[0])
for i in range(1, len(raw_columns)):
col = raw_columns[i]
if 'AT+QNWCFG="nr5g_csi"' in col:
if not h1:
csv_header += ["mcs_PDSCH", "ri_PDSCH", "downlink_cqi", "pmi"]
h1 = True
tmp = raw_columns[i + 1].replace('+QNWCFG: "nr5g_csi",', "")
csv_line += tmp.split(",")
elif "AT+QENDC" in col:
if not h2:
csv_header += [
"endc_avl",
"plmn_info_list_r15_avl",
"endc_rstr",
"5G_basic",
]
h2 = True
tmp = raw_columns[i + 1].replace("+QENDC: ", "")
csv_line += tmp.split(",")
elif 'AT+QENG="servingcell"' in col:
if not h3:
csv_header += [
"connection_state",
"is_tdd",
"mcc",
"mnc",
"cellID",
"PCID",
"earfcn",
"freq_band_ind",
"UL_bandwidth",
"DL_bandwidth",
"TAC",
"RSRP",
"RSRQ",
"RSSI",
"SINR",
"CQI_1-30",
"tx_power",
"srxlev",
"MCC",
"MNC",
"PCID",
"RSRP",
"SINR",
"RSRQ",
"ARFCN",
"band",
]
h3 = True
if "NOCONN" in raw_columns[i + 1]:
csv_line.append("NOCONN")
csv_line += raw_columns[i + 2].replace('+QENG: "LTE",', "").split(",")
csv_line += (
raw_columns[i + 3].replace('+QENG:"NR5G-NSA",', "").split(",")
)
elif "SEARCH" in raw_columns[i + 1]:
csv_line.append("SEARCH")
csv_line += [""] * 25
elif "OK" == raw_columns[i + 1]:
csv_line.append("OK")
csv_line += [""] * 25
else:
csv_line.append("undefined")
csv_line += [""] * 25
all_csv_lines.append(csv_line)
outputfile = open(args.file.replace("txt", "csv"), "w")
writer = csv.writer(outputfile, delimiter=",", lineterminator="\n", escapechar='\\')
writer.writerow(csv_header)
#print(all_csv_lines)
for l in all_csv_lines:
#print(l)
writer.writerow(l)
outputfile.close()
outputfile = open(args.file.replace("txt", "csv"), "r")
serial_df = pd.read_csv(outputfile,
converters={"UL_bandwidth": convert_bandwidth, "DL_bandwidth": convert_bandwidth},
)
serial_df = serial_df.drop(columns=["MCC", "MNC"])
serial_df["datetime"] = pd.to_datetime(
serial_df["time"].apply(lambda x: datetime.datetime.fromtimestamp(x))
)
serial_df.to_csv(args.file.replace("txt", "csv"))
outputfile.close()
exit()
delete_string = [
'AT+QNWCFG="nr5g_csi";',
'+QNWCFG: "nr5g_csi"',
'AT+QENG="servingcell";+QENG: "servingcell",',
"+QENG:",
"AT+QENDC;+QENDC:",
]
for d in delete_string:
content = content.replace(d, ",")
content = (
content.replace(";", "")
.replace(" ", "")
.replace(",,,", ",")
.replace('"', "")
.replace("LTE,", "")
.replace("NR5G-NSA,", "")
)
header = "time,mcs,ri,cqi,pmi,conn_state,is_tdd,MCC,MNC,cellID,PCID,earfcn,freq_band_ind,UL_bandwidth,DL_bandwidth,TAC,RSRP,RSRQ,RSSI,SINR,CQI,tx_power,srxlev,MCC,MNC,PCID,RSRP,SINR,RSRQ,ARFCN,band,endc_avl,plmn_info_list_r15_avl,endc_rstr,5G_basic\n"
csv_path = args.file.replace("txt", "csv")
print("Write to: {}".format(csv_path))
csv_string = header
for csv_line in content.split("\n"):
if len(header.split(",")) == len(csv_line.split(",")):
csv_string += csv_line + "\n"
else:
# print("{} found {}".format(len(header.split(",")), len(csv_line.split(","))))
print("Could not interpret string: {}".format(csv_line))
print(
"Expect {} columns got {}".format(
len(header.split(",")), len(csv_line.split(","))
)
)
csv_string_io = StringIO(csv_string)
serial_df = pd.read_csv(csv_string_io)
serial_df = serial_df
serial_df["datetime"] = pd.to_datetime(
serial_df["time"].apply(lambda x: datetime.datetime.fromtimestamp(x))
)
serial_df.to_csv(csv_path)
print(serial_df)

22
plot_single_transmission_timeline.py
View File

@@ -2,7 +2,6 @@
import math
import multiprocessing
import os
import pickle
from argparse import ArgumentParser
import matplotlib
@@ -10,23 +9,6 @@ import pandas as pd
import matplotlib.pyplot as plt
def convert_bandwidth(value):
if value == 0:
return 1.4
elif value == 1:
return 3
elif value == 2:
return 5
elif value == 3:
return 10
elif value == 4:
return 15
elif value == 5:
return 20
else:
return 0
if __name__ == "__main__":
parser = ArgumentParser()
parser.add_argument("-s", "--serial_file", required=True, help="Serial csv file.")
@@ -95,9 +77,7 @@ if __name__ == "__main__":
#transmission_df = transmission_df.filter(["goodput", "datetime", "ack_rtt", "goodput_rolling", "snd_cwnd"])
# read serial csv
serial_df = pd.read_csv(args.serial_file,
converters={"UL_bandwidth": convert_bandwidth, "DL_bandwidth": convert_bandwidth},
)
serial_df = pd.read_csv(args.serial_file)
serial_df["datetime"] = pd.to_datetime(serial_df["datetime"]) - pd.Timedelta(hours=1)
serial_df = serial_df.set_index("datetime")
serial_df.index = pd.to_datetime(serial_df.index)