52 lines
2.3 KiB
Python
52 lines
2.3 KiB
Python
# File: frequency.py
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# Copyright (C) 2026 Erick Ahmed
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# SPDX-License-Identifier: AGPL-3.0-or-later
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import argparse
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from pathlib import Path
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import pandas as pd
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import plotly.express as px
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import plotly.graph_objects as go
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from utils.extractor import load_data
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def calc_freq(df: pd.DataFrame) -> pd.DataFrame:
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"""Calculates frequency counts and percentages for identifiers."""
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freq_df = df['Identifier'].value_counts().reset_index()
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freq_df.columns = ['Identifier', 'Count']
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total = freq_df['Count'].sum()
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freq_df['Percentage'] = (freq_df['Count'] / total * 100).round(2)
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return freq_df.sort_values('Count', ascending=True)
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def plot_freq(stats_df: pd.DataFrame, title: str) -> go.Figure:
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"""Generates interactive horizontal bar chart with log x-axis."""
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fig = px.bar(
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stats_df, y='Identifier', x='Count', orientation='h', title=title, log_x=True,
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labels={'Identifier': 'PGN / CAN ID', 'Count': 'Message Count'},
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color='Count', color_continuous_scale='Turbo',
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hover_data={'Percentage': ':.2f', 'Count': True, 'Identifier': True}
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)
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fig.update_layout(
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height=max(600, len(stats_df) * 18), width=1000,
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xaxis_title='Total Message Count (Log Scale)', yaxis_title='PGN or CAN ID',
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yaxis={'categoryorder': 'total ascending'},
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plot_bgcolor='rgba(0,0,0,0)', paper_bgcolor='white',
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font=dict(family="Segoe UI, Arial, sans-serif", size=12),
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hoverlabel=dict(bgcolor="white", font_size=13, font_family="Segoe UI"),
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margin=dict(l=250, r=50, t=80, b=50),
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title=dict(font=dict(size=20), x=0.5)
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)
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fig.update_traces(hovertemplate="<b>%{y}</b><br>Count: %{x:,}<br>Share: %{customdata[0]}%<extra></extra>")
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return fig
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Analyze CAN bus message frequency")
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parser.add_argument("input", type=Path, help="Path to the input CAN log file")
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parser.add_argument("output", type=Path, nargs="?", default=Path("freq_report.html"), help="Path to the output HTML report")
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parser.add_argument("title", nargs="?", default="CAN Bus Message Frequency", help="Title for the HTML report")
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args = parser.parse_args()
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df = load_data(args.input)
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stats = calc_freq(df)
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fig = plot_freq(stats, title=args.title)
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fig.write_html(str(args.output), include_plotlyjs='cdn')
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