Initial commit

src/concat.py

@@ -0,0 +1,80 @@
+import pandas as pd
+from pathlib import Path
+import argparse
+
+
+def concat_pair(r_file: Path, s_file: Path) -> pd.DataFrame:
+    crank_df = pd.read_csv(r_file)
+    cam_df = pd.read_csv(s_file)
+
+    crank_values = crank_df.iloc[:, 0]
+    cam_values = cam_df.iloc[:, 0]
+
+    start_time = min(crank_values.iloc[0], cam_values.iloc[0])
+
+    crank_values = crank_values - start_time
+    cam_values = cam_values - start_time
+
+    rows = max(crank_values.max(), cam_values.max()) + 1
+
+    final_df = pd.DataFrame(index=range(rows), columns=["crank", "cam"])
+
+    final_df["crank"] = final_df.index.isin(crank_values).astype(int)
+    final_df["cam"] = final_df.index.isin(cam_values).astype(int)
+    final_df.index.name = "time_us"
+
+    return final_df
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument("directory", type=Path, help="Source data directory")
+
+args = parser.parse_args()
+
+directory: Path = args.directory
+
+if not directory.is_dir():
+    parser.error(f"{directory} is not a valid directory")
+
+print(f"Processing data in: {directory}")
+
+file_groups: dict[str, dict[str, Path]] = {}
+
+for path in directory.glob("*.csv"):
+    stem = path.stem
+
+    try:
+        base_name, channel = stem.rsplit("_", 1)
+    except ValueError:
+        print(f"Skipping badly named file: {path}")
+        continue
+
+    if channel not in ("R", "S"):
+        print(f"Skipping unknown file: {path}")
+        continue
+
+    file_groups.setdefault(base_name, {})[channel] = path
+
+file_pairs: list[tuple[Path, Path]] = []
+
+for base_name, files in sorted(file_groups.items()):
+    if "R" not in files:
+        print(f"Missing R file for {base_name}")
+        continue
+
+    if "S" not in files:
+        print(f"Missing S file for {base_name}")
+        continue
+
+    file_pairs.append((files["R"], files["S"]))
+
+for r_file, s_file in file_pairs:
+    df = concat_pair(r_file, s_file)
+
+    base_name, _ = r_file.stem.rsplit("_", 1)
+    output = r_file.parent / f"{base_name}_concat.csv"
+
+    df.to_csv(output)
+
+
+exit(0)