Convert trace for metrics visualization (jsonl to mf4)

scripts/convert_trace/.gitignore

@@ -0,0 +1 @@
+./mf4

scripts/convert_trace/README.md

@@ -0,0 +1,13 @@
+# Jsonl to MDF
+
+Convert a [JSON lines](https://github.com/macformula/hil/blob/main/canlink/jsonl.go) log file from our [CAN tracer](https://github.com/macformula/hil/blob/main/canlink/tracer.go) to an MDF file.
+
+For developers to convert JSON lines log format to MDF for integration with [`asammdf`](https://asammdf.readthedocs.io/en/latest/). With this format, visualization tools such as [Asammdf GUI](https://canlogger.csselectronics.com/canedge-getting-started/ce2/log-file-tools/asammdf-gui/) can be used to view and debug traces.
+
+# Usage
+
+It is recommended to use uv python package manager.
+
+```bash
+python ./jsonl_to_mdf.py ./trace.jsonl
+```

scripts/convert_trace/jsonl_to_mf4.py

@@ -0,0 +1,33 @@
+from asammdf import MDF, Signal
+import sys
+import numpy as np
+import pandas as pd
+
+input = sys.argv[1] # .jsonl
+output = input + ".mdf" # .mf4
+mdf = MDF(version="4.10")
+
+# read jsonl file into pandas dataframe
+dataframe = pd.read_json(input, lines=True)
+
+# convert each can id to mdf signal
+for can_id, group in dataframe.groupby("id"):
+    # convert time to seconds from start
+    times = pd.to_datetime(group["time"], format="%H:%M:%S.%f")
+    t0 = times.iloc[0]
+    timestamps = (times - t0).dt.total_seconds().to_numpy(dtype=np.float64)
+
+    # bytes is tuple, make 2D uint8 array [n samples, n bytes]
+    samples = np.array(group["bytes"].tolist(), dtype=np.uint8)
+
+    # generate signal & append mdf file
+    sig = Signal(
+        name = str(can_id),
+        samples = samples,
+        timestamps = timestamps,
+    )
+    mdf.append(sig)
+
+# save mdf file (.mf4)
+mdf.save(output)
+mdf.close()

scripts/convert_trace/requirements.txt

@@ -0,0 +1 @@
+asammdf