77 lines
3.0 KiB
Python
77 lines
3.0 KiB
Python
import argparse
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import json
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from pathlib import Path
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import fastparquet
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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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def _extract_identifier(row: pd.Series) -> str:
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"""Extracts PGN from metadata or falls back to CAN ID."""
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meta = row.get('j1939_metadata')
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if pd.isna(meta):
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return f"{row['ID']} "
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if isinstance(meta, str):
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try:
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meta = json.loads(meta)
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except json.JSONDecodeError:
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return f"{row['ID']}"
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if isinstance(meta, dict) and 'PGN' in meta:
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return f"PGN: {meta['PGN']} "
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return f"{row['ID']}"
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def load_data(file_path: Path) -> pd.DataFrame:
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"""Loads Parquet file and adds an Identifier column."""
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df = pd.read_parquet(file_path)
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df['Identifier'] = df.apply(_extract_identifier, axis=1)
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return df
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def calculate_frequency(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_messages = freq_df['Count'].sum()
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freq_df['Percentage'] = (freq_df['Count'] / total_messages * 100).round(2)
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return freq_df.sort_values('Count', ascending=True)
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def visualize_frequency(stats_df: pd.DataFrame, title: str = "CAN Bus Message Frequency") -> go.Figure:
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"""Generates an interactive Plotly horizontal bar chart with a logarithmic 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(
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hovertemplate="<b>%{y}</b><br>Count: %{x:,}<br>Share: %{customdata[0]}%<extra></extra>"
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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 Parquet data.")
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parser.add_argument("-i", "--input", type=Path, required=True)
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parser.add_argument("-o", "--output", type=Path, default=Path("can_analysis_report.html"))
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parser.add_argument("-t", "--title", type=str, default="CAN Bus Message Frequency by PGN / ID")
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args = parser.parse_args()
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df = load_data(args.input)
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stats_df = calculate_frequency(df)
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fig = visualize_frequency(stats_df, title=args.title)
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fig.write_html(str(args.output), include_plotlyjs='cdn')
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