127 lines
4.4 KiB
Python
127 lines
4.4 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 numpy as np
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import pandas as pd
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import plotly.graph_objects as go
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from stats.utils.extractor import load_data
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def _format_can_id_vec(s: pd.Series) -> pd.Series:
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s = s.astype('string').str.strip()
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s = s.str.replace(r'^0x', '', case=False, regex=True)
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s = s.str.upper()
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return s.fillna('UNKNOWN').replace('', 'UNKNOWN')
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def calculate_frequency(df: pd.DataFrame) -> pd.DataFrame:
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can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
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formatted = _format_can_id_vec(df[can_id_col])
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counts = formatted.value_counts()
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freq_df = pd.DataFrame({
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'Identifier': counts.index,
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'Count': counts.to_numpy(),
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})
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total = counts.sum()
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freq_df['Percentage'] = np.round(freq_df['Count'] / total * 100, 2) if total else 0.0
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return freq_df.sort_values('Count', ascending=True).reset_index(drop=True)
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def plot_frequency(stats_df: pd.DataFrame, title: str) -> go.Figure:
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n = len(stats_df)
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fig = go.Figure(go.Bar(
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y=stats_df['Identifier'],
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x=stats_df['Count'],
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orientation='h',
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marker=dict(
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color=stats_df['Count'],
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colorscale='Turbo',
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cmin=int(stats_df['Count'].min()) if n else 0,
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cmax=int(stats_df['Count'].max()) if n else 1,
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line_width=0,
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),
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customdata=stats_df[['Percentage']].to_numpy(),
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hovertemplate="<b>%{y}</b><br>Count: %{x:,}<br>Share: %{customdata[0]}%<extra></extra>",
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texttemplate='%{x:,}',
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textposition='outside',
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cliponaxis=False,
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))
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fig.update_layout(
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height=max(600, n * 18),
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autosize=True,
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template='plotly_white',
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xaxis=dict(
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type='log',
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title=dict(text="Message count [log scale]", font=dict(size=13, color="#1a1a1a")),
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side="top",
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dtick=1,
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showgrid=False,
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linecolor="#bdbdbd",
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tickfont=dict(size=12, color="#2a2a2a"),
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ticks="outside",
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ticklen=4,
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tickcolor="#cccccc",
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),
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yaxis=dict(
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title=dict(text="PGN or CAN ID", font=dict(size=13, color="#1a1a1a")),
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showgrid=False,
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linecolor="#bdbdbd",
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tickfont=dict(size=12, color="#2a2a2a"),
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ticks="outside",
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ticklen=4,
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tickcolor="#cccccc",
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automargin=True,
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type='category',
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),
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font=dict(family="Segoe UI, Arial, sans-serif", size=12, color='#2a2a2a'),
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hoverlabel=dict(bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor='#cccccc'),
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margin=dict(l=200, r=40, t=120, b=60),
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bargap=0.35,
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coloraxis_colorbar=dict(
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title=dict(text='Message Count', side='top'),
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orientation='h',
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thickness=15,
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len=0.35,
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x=1.0,
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xanchor='right',
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y=1.02,
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yanchor='bottom',
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tickformat=',',
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outlinecolor='#cccccc',
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outlinewidth=0.5,
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),
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title=dict(text=title, font=dict(size=20, color='#1a1a1a'), x=0.5, xanchor='center', pad=dict(b=20)),
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)
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fig.update_xaxes(
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showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
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zeroline=False, linecolor='#bdbdbd', mirror=False,
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tickformat=',',
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minor=dict(showgrid=True, gridcolor='#f4f4f4', gridwidth=0.5),
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)
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fig.update_yaxes(
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showgrid=False, zeroline=False, linecolor='#bdbdbd',
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ticks='outside', ticklen=4, tickcolor='#cccccc', automargin=True,
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)
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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"))
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parser.add_argument("title", nargs="?", default="Frequency")
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args = parser.parse_args()
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df = load_data(args.input)
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stats = calculate_frequency(df)
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fig = plot_frequency(stats, title=args.title)
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config = {
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'responsive': True,
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'displaylogo': False,
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'scrollZoom': True,
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'modeBarButtonsToAdd': ['toggleSpikelines'],
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'toImageButtonOptions': {'format': 'png', 'scale': 2},
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}
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fig.write_html(str(args.output), include_plotlyjs='cdn', config=config)
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