支持主机桥接后固定δt与旋转先验，并落盘运动对供可视化直读。

Co-authored-by: Cursor <cursoragent@cursor.com>

imu_lidar/lidar_io.py

@@ -19,10 +19,7 @@ import numpy as np
 from .contracts import LidarFrame
 
 
-def load_lidar_frames(path: Path | str) -> list[LidarFrame]:
-    """Load all LiDAR frames listed by ``frames_index.csv`` under ``path``."""
-
-    root = Path(path)
+def _read_frames_index(root: Path) -> tuple[np.ndarray, str]:
     index_path = root / "frames_index.csv"
     if not index_path.exists():
         raise FileNotFoundError(f"missing frames_index.csv under {root}")
@@ -38,6 +35,54 @@ def load_lidar_frames(path: Path | str) -> list[LidarFrame]:
         raise ValueError(
             f"frames_index.csv must contain frame_id,{file_key}/filename,t_start,t_end; got {sorted(names)}"
         )
+    return rows, file_key
+
+
+def list_lidar_frame_entries(path: Path | str) -> list[tuple[str, float, float, Path]]:
+    """Return ``(frame_id, t_start, t_end, npz_path)`` sorted by mid time (same as ``load_lidar_frames``)."""
+
+    root = Path(path)
+    rows, file_key = _read_frames_index(root)
+    entries: list[tuple[str, float, float, Path]] = []
+    for row in rows:
+        t0 = float(row["t_start"])
+        t1 = float(row["t_end"])
+        entries.append((str(row["frame_id"]), t0, t1, root / str(row[file_key])))
+    entries.sort(key=lambda item: 0.5 * (item[1] + item[2]))
+    return entries
+
+
+def load_lidar_frame_at(root: Path | str, index: int) -> LidarFrame:
+    """Load one frame by index in mid-time-sorted order (matches motion-pair ``i``/``j``)."""
+
+    entries = list_lidar_frame_entries(root)
+    if index < 0 or index >= len(entries):
+        raise IndexError(f"frame index {index} outside [0, {len(entries) - 1}] for {root}")
+    frame_id, t0, t1, npz_path = entries[index]
+    with np.load(npz_path) as payload:
+        if "points" not in payload.files:
+            raise ValueError(f"{npz_path} must contain array 'points'")
+        points = np.asarray(payload["points"], dtype=float)
+    if points.ndim != 2 or points.shape[1] < 3:
+        raise ValueError(f"{npz_path}: points must have shape (N, 3[+])")
+    return LidarFrame(
+        frame_id=frame_id,
+        t_start_s=t0,
+        t_end_s=t1,
+        points_xyz=points[:, :3],
+        path=npz_path,
+    )
+
+
+def lidar_frame_count(path: Path | str) -> int:
+    return len(list_lidar_frame_entries(path))
+
+
+def load_lidar_frames(path: Path | str) -> list[LidarFrame]:
+    """Load all LiDAR frames listed by ``frames_index.csv`` under ``path``."""
+
+    root = Path(path)
+    rows, file_key = _read_frames_index(root)
 
     frames: list[LidarFrame] = []
     for row in rows: