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import numpy as np
import pandas as pd
def get_physical_db():
"""
Reads the physical_database.csv file from the physical_db directory and
returns a pandas DataFrame containing only the columns 'Code_Sector',
'Azimut', 'Longitude', 'Latitude', and 'Hauteur'.
Returns:
pd.DataFrame: A DataFrame containing the filtered columns.
"""
physical = pd.read_csv(r"physical_db\physical_database.csv")
physical = physical[["Code_Sector", "Azimut", "Longitude", "Latitude", "Hauteur"]]
return physical
class UtilsVars:
sector_mapping = {4: 1, 5: 2, 6: 3, 11: 1, 12: 2, 13: 3}
channeltype_mapping = {4: "BCCH", 3: "TCH"}
final_lte_database = ""
final_gsm_database = ""
final_wcdma_database = ""
physisal_db = get_physical_db()
# print(UtilsVars.physisal_db)
def get_band(text):
"""
Extract the band from the given string.
Parameters
----------
text : str
The string to extract the band from.
Returns
-------
str or np.nan
The extracted band, or NaN if the text was not a string or did not contain
any of the recognized bands (L1800, L2300, L800).
"""
if isinstance(text, str): # Check if text is a string
if "L1800" in text:
return "L1800"
elif "L2300" in text:
return "L2300"
elif "L800" in text:
return "L800"
return np.nan # or return None
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