'''
##############################################################
# Created Date: Monday, April 14th 2025
# Contact Info: luoxiangyong01@gmail.com
# Author/Copyright: Mr. Xiangyong Luo
##############################################################
'''
from pathlib import Path
from loguru import logger
import pandas as pd
from pyufunc import str_strip
def remove_stripe_values(value):
"""Remove stripe values from a string."""
if isinstance(value, str):
return (
value.replace("\\r", "")
.replace("\\n", "")
.replace("\n", "")
.replace("b'", "")
.replace("'", "")
)
return value
[docs]
def vissim_fhz(path_vissim_fhz: str, output_dir: str = "") -> pd.DataFrame:
"""Convert vissim fhz file to pandas dataframe.
Args:
path_vissim_fhz (str): the path to the vissim fhz file.
output_dir (str): the directory to save the output file. Defaults to "".
Example:
>>> import vissim2gmns as vg
>>> path_vissim_fhz = "./vissim_data/xl_002_001.fhz"
>>> output_dir = "./output"
>>> # get the fhz data as a pandas dataframe without saving to file.
>>> df_fhz = vg.vissim_fhz(path_vissim_fhz)
>>>
>>> # get the fhz data as a pandas dataframe and save to csv file in the output_dir.
>>> df_fhz = vg.vissim_fhz(path_vissim_fhz, output_dir=output_dir)
Returns:
pd.DataFrame: converted pandas dataframe.
"""
with open(path_vissim_fhz, 'rb') as f:
df_fhz = pd.DataFrame(f.readlines())
# Retrieve the VISSIM running date from a specific row.
fhz_date = str(df_fhz.iloc[5, :])
start_fhz = next((i for i in range(len(df_fhz)) if str(df_fhz.iloc[i, :])[11:15] == "Time"), 0)
# remove \\r and \\n, \n characters from staring values
fhz_date = remove_stripe_values(fhz_date)
vissim_fhz_data = df_fhz.iloc[start_fhz:] # fhz file starts from row 8
fhz_data = pd.DataFrame([str(jj).split(';') for jj in vissim_fhz_data.iloc[:, 0]])
fhz_data.columns = fhz_data.iloc[0]
fhz_data = fhz_data.iloc[1:]
fhz_data = fhz_data.reset_index(drop=True)
for j in range(len(fhz_data.iloc[:, 0])):
fhz_data.iloc[j, 0] = str(fhz_data.iloc[j, 0]).split("'")[1]
# strip values for the whole table
fhz_data = fhz_data.map(str_strip)
# Convert the first (time offset) column to numeric safely.
time_col = fhz_data.columns[0]
fhz_data[time_col] = pd.to_numeric(fhz_data[time_col], errors="coerce")
# add datetime
fhz_data["datetime"] = pd.to_datetime(
fhz_date.split("Name")[0].split("Date:")[1].lstrip()) + pd.to_timedelta(fhz_data[time_col], unit="s")
# Save to csv file if output_dir is provided
if output_dir:
output_fhz_csv = pd.DataFrame(fhz_data)
output_fhz_csv.to_csv(f"{output_dir}/{Path(path_vissim_fhz).stem}_fhz.csv", index=False)
logger.info(f"Successfully save fhz file to csv: {output_dir}\n")
return fhz_data
if __name__ == "__main__":
path_vissim_fhz = r"C:\Users\xyluo25\anaconda3_workspace\001_GitHub\vissim2gmns\datasets\aveiro_port_net\Aveiro_Port_Train_Network_25_03_2026_001.fhz"
output_dir = "./"
df_fhz = vissim_fhz(path_vissim_fhz, output_dir=output_dir)