diff --git a/stat/frequency.py b/stat/frequency.py
index 9766cbe..d92c8fc 100644
--- a/stat/frequency.py
+++ b/stat/frequency.py
@@ -3,54 +3,28 @@
# SPDX-License-Identifier: AGPL-3.0-or-later
import argparse
-import json
from pathlib import Path
-import fastparquet
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
+from utils.extractor import load_data
-
-def _extract_identifier(row: pd.Series) -> str:
- """Extracts PGN from metadata or falls back to CAN ID."""
- meta = row.get('j1939_metadata')
- if pd.isna(meta):
- return f"{row['ID']} "
- if isinstance(meta, str):
- try:
- meta = json.loads(meta)
- except json.JSONDecodeError:
- return f"{row['ID']}"
- if isinstance(meta, dict) and 'PGN' in meta:
- return f"PGN: {meta['PGN']} "
- return f"{row['ID']}"
-
-
-def load_data(file_path: Path) -> pd.DataFrame:
- """Loads Parquet file and adds an Identifier column."""
- df = pd.read_parquet(file_path)
- df['Identifier'] = df.apply(_extract_identifier, axis=1)
- return df
-
-
-def calculate_frequency(df: pd.DataFrame) -> pd.DataFrame:
+def calc_freq(df: pd.DataFrame) -> pd.DataFrame:
"""Calculates frequency counts and percentages for identifiers."""
freq_df = df['Identifier'].value_counts().reset_index()
freq_df.columns = ['Identifier', 'Count']
- total_messages = freq_df['Count'].sum()
- freq_df['Percentage'] = (freq_df['Count'] / total_messages * 100).round(2)
+ total = freq_df['Count'].sum()
+ freq_df['Percentage'] = (freq_df['Count'] / total * 100).round(2)
return freq_df.sort_values('Count', ascending=True)
-
-def visualize_frequency(stats_df: pd.DataFrame, title: str = "CAN Bus Message Frequency") -> go.Figure:
- """Generates an interactive Plotly horizontal bar chart with a logarithmic x-axis."""
+def plot_freq(stats_df: pd.DataFrame, title: str) -> go.Figure:
+ """Generates interactive horizontal bar chart with log x-axis."""
fig = px.bar(
stats_df, y='Identifier', x='Count', orientation='h', title=title, log_x=True,
labels={'Identifier': 'PGN / CAN ID', 'Count': 'Message Count'},
color='Count', color_continuous_scale='Turbo',
hover_data={'Percentage': ':.2f', 'Count': True, 'Identifier': True}
)
-
fig.update_layout(
height=max(600, len(stats_df) * 18), width=1000,
xaxis_title='Total Message Count (Log Scale)', yaxis_title='PGN or CAN ID',
@@ -61,20 +35,17 @@ def visualize_frequency(stats_df: pd.DataFrame, title: str = "CAN Bus Message Fr
margin=dict(l=250, r=50, t=80, b=50),
title=dict(font=dict(size=20), x=0.5)
)
-
- fig.update_traces(
- hovertemplate="%{y}
Count: %{x:,}
Share: %{customdata[0]}%"
- )
+ fig.update_traces(hovertemplate="%{y}
Count: %{x:,}
Share: %{customdata[0]}%")
return fig
if __name__ == "__main__":
- parser = argparse.ArgumentParser(description="Analyze CAN bus Parquet data.")
+ parser = argparse.ArgumentParser(description="Analyze CAN bus frequency.")
parser.add_argument("-i", "--input", type=Path, required=True)
- parser.add_argument("-o", "--output", type=Path, default=Path("can_analysis_report.html"))
- parser.add_argument("-t", "--title", type=str, default="CAN Bus Message Frequency by PGN / ID")
+ parser.add_argument("-o", "--output", type=Path, default=Path("freq_report.html"))
+ parser.add_argument("-t", "--title", type=str, default="CAN Bus Message Frequency")
args = parser.parse_args()
df = load_data(args.input)
- stats_df = calculate_frequency(df)
- fig = visualize_frequency(stats_df, title=args.title)
+ stats = calc_freq(df)
+ fig = plot_freq(stats, title=args.title)
fig.write_html(str(args.output), include_plotlyjs='cdn')
diff --git a/utils/extractor.py b/utils/extractor.py
new file mode 100644
index 0000000..8cdd07e
--- /dev/null
+++ b/utils/extractor.py
@@ -0,0 +1,27 @@
+# File: extractor.py
+# Copyright (C) 2026 Erick Ahmed
+# SPDX-License-Identifier: AGPL-3.0-or-later
+
+import json
+from pathlib import Path
+import pandas as pd
+
+def extract_id(row: pd.Series) -> str:
+ """Extracts PGN from metadata or falls back to CAN ID."""
+ meta = row.get('j1939_metadata')
+ if pd.isna(meta):
+ return f"ID: {row['ID']}"
+ if isinstance(meta, str):
+ try:
+ meta = json.loads(meta)
+ except json.JSONDecodeError:
+ return f"ID: {row['ID']}"
+ if isinstance(meta, dict) and 'PGN' in meta:
+ return f"PGN: {meta['PGN']}"
+ return f"ID: {row['ID']}"
+
+def load_data(file_path: Path) -> pd.DataFrame:
+ """Loads Parquet file and adds an Identifier column."""
+ df = pd.read_parquet(file_path)
+ df['Identifier'] = df.apply(extract_id, axis=1)
+ return df