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import numpy as np |
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import pandas as pd |
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def get_physical_db(): |
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""" |
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Reads the physical_database.csv file from the physical_db directory and |
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returns a pandas DataFrame containing only the columns 'Code_Sector', |
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'Azimut', 'Longitude', 'Latitude', and 'Hauteur'. |
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Returns: |
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pd.DataFrame: A DataFrame containing the filtered columns. |
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""" |
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physical = pd.read_csv(r"physical_db\physical_database.csv") |
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physical = physical[["Code_Sector", "Azimut", "Longitude", "Latitude", "Hauteur"]] |
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return physical |
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class UtilsVars: |
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sector_mapping = {4: 1, 5: 2, 6: 3, 11: 1, 12: 2, 13: 3} |
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channeltype_mapping = {4: "BCCH", 3: "TCH"} |
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final_lte_database = "" |
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final_gsm_database = "" |
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final_wcdma_database = "" |
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physisal_db = get_physical_db() |
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def get_band(text): |
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""" |
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Extract the band from the given string. |
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Parameters |
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---------- |
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text : str |
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The string to extract the band from. |
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Returns |
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------- |
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str or np.nan |
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The extracted band, or NaN if the text was not a string or did not contain |
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any of the recognized bands (L1800, L2300, L800). |
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""" |
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if isinstance(text, str): |
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if "L1800" in text: |
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return "L1800" |
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elif "L2300" in text: |
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return "L2300" |
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elif "L800" in text: |
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return "L800" |
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return np.nan |
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