mirror of
https://github.com/majmongoose/ARRLFieldDayTools.git
synced 2024-09-16 10:46:34 -04:00
71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
import re
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import pandas as pd
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import argparse
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# Define the frequency to band conversion
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frequency_to_band = {
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'1800': '160m',
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'3500': '80m',
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'7000': '40m',
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'14000': '20m',
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'21000': '15m',
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'28000': '10m',
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}
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# Define a function to parse the QSO lines
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def parse_qso_line(line):
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# Use regex to match the QSO line and extract the mode and frequency
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match = re.match(r"QSO:\s+(\d+)\s+(\w+)\s+\d{4}-\d{2}-\d{2}\s+\d{4}\s+\w+\s+\w+\s+\w+\s+\w+", line)
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if match:
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frequency, mode = match.groups()
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band = frequency_to_band.get(frequency, None) # Convert frequency to band
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if band:
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return mode, band
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return None, None
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# Define a function to read the log file and count QSOs
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def read_log_file(file_path):
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# Initialize counters for QSOs
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counts = {'CW': {}, 'PH': {}, 'RY': {}, 'DG': {}}
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# Read the log file
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with open(file_path, 'r') as file:
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for line in file:
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if line.startswith('QSO:'):
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mode, band = parse_qso_line(line.strip())
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if mode and mode in counts:
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if band not in counts[mode]:
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counts[mode][band] = 0
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counts[mode][band] += 1
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# Convert counts to a DataFrame for better display
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# Define all possible bands
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all_bands = ['160m', '80m', '40m', '20m', '15m', '10m']
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# Initialize the DataFrame with all bands and modes
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data = {band: {mode: counts[mode].get(band, 0) for mode in ['CW', 'DG', 'PH', 'RY']} for band in all_bands}
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df = pd.DataFrame(data).T.fillna(0).astype(int)
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return df
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# Define a function to print the results
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def print_summary(df):
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print("QSO Counts by Band and Mode:")
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print(df)
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# Main function to run the script
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def main():
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# Set up command line argument parsing
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parser = argparse.ArgumentParser(description="Process a log file to count QSOs by band and mode.")
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parser.add_argument('file_path', help="Path to the log file")
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args = parser.parse_args()
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# Read the log file and get QSO counts
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df = read_log_file(args.file_path)
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# Print the summary
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print_summary(df)
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if __name__ == "__main__":
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main()
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