measurement-scripts/format_serial_txt_to_csv_EM9190.py

#!/usr/bin/env python3
import datetime
import re
from argparse import ArgumentParser
import pandas as pd

KEY_VALUE_REGEX = r"(.+):(.+)"

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()

    serial_df = None
    p = re.compile(KEY_VALUE_REGEX)

    for part in content.split(";;;"):
        if part == "":
            break
        part = part.replace("\t", "\n").strip()
        time = None
        line_dict = dict(time=None)
        for line in part.split("\n"):
            if not line.startswith("!") or line == "" or line == "\n":
                if line_dict["time"] is None:
                    time = line
                    line_dict["time"] = [time]
                m = p.match(line)
                if m:
                    key = m.group(1).strip().replace(" ", "_")
                    value = m.group(2).replace("MHz", "").replace("---", "").strip()

                    line_dict[key] = [value]

        if len(line_dict) > 1:
            #print("line:")
            #print(line_dict)
            #print("serial_df:")
            #print(serial_df)
            if serial_df is None:
                serial_df = pd.DataFrame.from_dict(line_dict, orient="columns",)
            else:
                serial_df = pd.concat([serial_df, pd.DataFrame.from_dict(line_dict, orient="columns")])

    serial_df = serial_df.copy()
    serial_df["datetime"] = pd.to_datetime(
        serial_df["time"].apply(lambda x: datetime.datetime.fromtimestamp(int(x)))
    )
    serial_df.to_csv(args.file.replace("txt", "csv"))

    #serial_df = serial_df.filter(["datetime", "LTE_bw", "LTE_SCC2_bw", "LTE_SCC3_bw", "LTE_SCC4_bw", "SCC1_NR5G_bw", "NR5G_dl_bw", "NR5G_ul_bw", "LTE_SCC1_bw", "NR5G_bw"])
    #print(serial_df.to_string())