Implement CAN ID visualization at the bit level

2026-07-14 14:14:09 +02:00
parent 2408c7a963
commit c9461868cc
1 changed files with 111 additions and 0 deletions
@@ -0,0 +1,111 @@
+import argparse
+from pathlib import Path
+import pandas as pd
+import plotly.graph_objects as go
+from utils.extractor import load_data
+
+def _format_can_id(x):
+    if pd.isna(x):
+        return "UNKNOWN"
+    s = str(x).strip()
+    if not s:
+        return "UNKNOWN"
+    if s.lower().startswith('0x'):
+        s = s[2:]
+    return s.upper()
+
+def prepare_data(df, target_id):
+    can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
+    df['Formatted_ID'] = df[can_id_col].apply(_format_can_id)
+    target_id_clean = _format_can_id(target_id)
+    filtered = df[df['Formatted_ID'] == target_id_clean].copy()
+
+    byte_cols = [f"b{i}" for i in range(8)]
+    for col in byte_cols:
+        filtered[col] = pd.to_numeric(
+            filtered[col].apply(lambda x: int(x, 16) if pd.notna(x) else None),
+            errors='coerce'
+        )
+
+    filtered = filtered.sort_values('Timestamp')
+    mask = (filtered[byte_cols] != filtered[byte_cols].shift()).any(axis=1)
+    filtered = filtered[mask]
+
+    return filtered, byte_cols
+
+def plot_bits(df, byte_cols, can_id, title):
+    fig = go.Figure()
+
+    colors = ['#e41a1c', '#377eb8', '#4daf4a', '#984ea3', '#ff7f00', '#ffff33', '#a65628', '#f781bf']
+
+    for i, col in enumerate(byte_cols):
+        fig.add_trace(go.Scatter(
+            x=df['Timestamp'],
+            y=df[col],
+            mode='lines',
+            line=dict(shape='hv', width=2, color=colors[i]),
+            name=col.upper(),
+            hovertemplate=f"<b>{col.upper()}</b><br>Time: %{{x}}<br>Value: %{{y}}<extra></extra>"
+        ))
+
+    fig.update_layout(
+        height=600,
+        autosize=True,
+        template='plotly_white',
+        title=dict(
+            text=f"{title} - ID: {can_id}",
+            font=dict(size=20, color='#1a1a1a'),
+            x=0.5, xanchor='center',
+            pad=dict(b=20)
+        ),
+        font=dict(family="Segoe UI, Arial, sans-serif", size=12, color='#2a2a2a'),
+        hoverlabel=dict(
+            bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor='#cccccc'
+        ),
+        margin=dict(l=60, r=40, t=120, b=60),
+        legend=dict(
+            title=dict(text="Bytes"),
+            bgcolor="rgba(255,255,255,0.8)",
+            bordercolor="#cccccc",
+            borderwidth=1,
+            font=dict(size=12, color="#2a2a2a")
+        ),
+        xaxis=dict(
+            title=dict(text="Timestamp", font=dict(size=13, color="#1a1a1a")),
+            showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
+            zeroline=False, linecolor="#bdbdbd",
+            tickfont=dict(size=12, color="#2a2a2a"),
+            ticks="outside", ticklen=4, tickcolor="#cccccc",
+            minor=dict(showgrid=True, gridcolor='#f4f4f4', gridwidth=0.5)
+        ),
+        yaxis=dict(
+            title=dict(text="Byte Value", font=dict(size=13, color="#1a1a1a")),
+            showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
+            zeroline=False, linecolor="#bdbdbd",
+            tickfont=dict(size=12, color="#2a2a2a"),
+            ticks="outside", ticklen=4, tickcolor="#cccccc"
+        )
+    )
+
+    return fig
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Visualize CAN bus byte changes over time")
+    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
+    parser.add_argument("can_id", type=str, help="CAN ID to visualize")
+    parser.add_argument("output", type=Path, nargs="?", default=Path("bits_report.html"), help="Path to the output HTML report")
+    parser.add_argument("title", nargs="?", default="Byte Visualization", help="Title for the HTML report")
+    args = parser.parse_args()
+
+    df = load_data(args.input)
+    filtered_df, byte_cols = prepare_data(df, args.can_id)
+    fig = plot_bits(filtered_df, byte_cols, args.can_id, title=args.title)
+
+    config = {
+        'responsive': True,
+        'displaylogo': False,
+        'scrollZoom': True,
+        'modeBarButtonsToAdd': ['toggleSpikelines'],
+        'toImageButtonOptions': {'format': 'png', 'scale': 2}
+    }
+    fig.write_html(str(args.output), include_plotlyjs='cdn', config=config)