Moves bandwidth converters to serial format script.

format_serial_txt_to_csv.py

+#!/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)

plot_single_transmission_timeline.py

 import math
 import multiprocessing
 import os
-import pickle
 from argparse import ArgumentParser
 
 import matplotlib
 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.")
             #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)