Added Reverse-Engineering Toolkit

Reverse-Engineering CAN-Bus/id_signal_explorer.py

@@ -0,0 +1,142 @@
+#!/usr/bin/env python3
+import re
+import sys
+import argparse
+from pathlib import Path
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+LOG_PATTERN = re.compile(r"(\d+)\s+(TX|RX)\s+0x([0-9A-Fa-f]+)\s+\d+\s+((?:[0-9A-Fa-f]{2}\s+)+)")
+
+def parse_trace(path: Path) -> pd.DataFrame:
+    rows = []
+    with open(path, "r", errors="ignore") as f:
+        for line in f:
+            m = LOG_PATTERN.match(line)
+            if not m:
+                continue
+            ts = int(m.group(1))
+            direction = m.group(2)
+            can_id = int(m.group(3), 16)
+            data = [int(x, 16) for x in m.group(4).split() if x.strip()]
+            rows.append((ts, direction, can_id, data))
+    df = pd.DataFrame(rows, columns=["ts","dir","id","data"])
+    if df.empty:
+        return df
+    df["time_s"] = (df["ts"] - df["ts"].min())/1000.0
+    return df
+
+def be16(b):
+    return (b[0]<<8) | b[1]
+
+def le16(b):
+    return b[0] | (b[1]<<8)
+
+def main():
+    ap = argparse.ArgumentParser(description="Per-ID explorer: generate plots for 8-bit and 16-bit combinations")
+    ap.add_argument("trace", help="Single-ID .trace file (from can_split_by_id.py)")
+    ap.add_argument("--outdir", default=None, help="Output directory; default: <trace>_explore")
+    ap.add_argument("--prefix", default="viz", help="File prefix for exports")
+    ap.add_argument("--rx-only", action="store_true", help="Use only RX frames")
+    args = ap.parse_args()
+
+    trace = Path(args.trace)
+    df = parse_trace(trace)
+    if df.empty:
+        print("No data in trace.", file=sys.stderr)
+        sys.exit(1)
+
+    if args.rx_only:
+        df = df[df["dir"]=="RX"].copy()
+        if df.empty:
+            print("No RX frames.", file=sys.stderr)
+            sys.exit(2)
+
+    outdir = Path(args.outdir) if args.outdir else trace.with_suffix("").parent / (trace.stem + "_explore")
+    outdir.mkdir(parents=True, exist_ok=True)
+
+    # --- 8-bit channels ---
+    for idx in range(8):
+        vals = [d[idx] if len(d)>idx else None for d in df["data"].tolist()]
+        times = [t for t, v in zip(df["time_s"].tolist(), vals) if v is not None]
+        series = [v for v in vals if v is not None]
+        if not series:
+            continue
+        plt.figure(figsize=(10,4))
+        plt.plot(times, series, marker=".", linestyle="-")
+        plt.xlabel("Zeit (s)")
+        plt.ylabel(f"Byte[{idx}] (8-bit)")
+        plt.title(f"{trace.name} – 8-bit Byte {idx}")
+        plt.grid(True)
+        fn = outdir / f"{args.prefix}_byte{idx}.png"
+        plt.tight_layout()
+        plt.savefig(fn, dpi=150)
+        plt.close()
+
+    # --- 16-bit combos ---
+    pairs = [(i,i+1) for i in range(7)]
+    # LE
+    for i,j in pairs:
+        times, series = [], []
+        for t, d in zip(df["time_s"].tolist(), df["data"].tolist()):
+            if len(d) > j:
+                series.append(le16([d[i], d[j]])); times.append(t)
+        if not series:
+            continue
+        plt.figure(figsize=(10,4))
+        plt.plot(times, series, marker=".", linestyle="-")
+        plt.xlabel("Zeit (s)")
+        plt.ylabel(f"LE16 @{i}-{j}")
+        plt.title(f"{trace.name} – LE16 Bytes {i}-{j}")
+        plt.grid(True)
+        fn = outdir / f"{args.prefix}_le16_{i}-{j}.png"
+        plt.tight_layout()
+        plt.savefig(fn, dpi=150)
+        plt.close()
+
+    # BE
+    for i,j in pairs:
+        times, series = [], []
+        for t, d in zip(df["time_s"].tolist(), df["data"].tolist()):
+            if len(d) > j:
+                series.append(be16([d[i], d[j]])); times.append(t)
+        if not series:
+            continue
+        plt.figure(figsize=(10,4))
+        plt.plot(times, series, marker=".", linestyle="-")
+        plt.xlabel("Zeit (s)")
+        plt.ylabel(f"BE16 @{i}-{j}")
+        plt.title(f"{trace.name} – BE16 Bytes {i}-{j}")
+        plt.grid(True)
+        fn = outdir / f"{args.prefix}_be16_{i}-{j}.png"
+        plt.tight_layout()
+        plt.savefig(fn, dpi=150)
+        plt.close()
+
+    # Summary stats
+    stats = []
+    # 8-bit stats
+    for idx in range(8):
+        vals = [d[idx] if len(d)>idx else None for d in df["data"].tolist()]
+        vals = [v for v in vals if v is not None]
+        if not vals:
+            continue
+        arr = np.array(vals, dtype=float)
+        stats.append({"type":"byte8", "slot":idx, "min":float(arr.min()), "max":float(arr.max()), "var":float(arr.var())})
+    # 16-bit stats
+    for i,j in pairs:
+        vals = [le16([d[i],d[j]]) for d in df["data"].tolist() if len(d)>j]
+        if vals:
+            arr = np.array(vals, dtype=float)
+            stats.append({"type":"le16", "slot":f"{i}-{j}", "min":float(arr.min()), "max":float(arr.max()), "var":float(arr.var())})
+        vals = [be16([d[i],d[j]]) for d in df["data"].tolist() if len(d)>j]
+        if vals:
+            arr = np.array(vals, dtype=float)
+            stats.append({"type":"be16", "slot":f"{i}-{j}", "min":float(arr.min()), "max":float(arr.max()), "var":float(arr.var())})
+
+    pd.DataFrame(stats).to_csv(outdir / "summary_stats.csv", index=False)
+    print(f"Exported 8-bit & 16-bit plots and summary_stats.csv to {outdir}")
+
+if __name__ == "__main__":
+    main()