refactor: Enhance type hints and documentation for distance calculation functions in playground.py

- Updated the return type of `perpendicular_distance_point_to_line_two_points` to `Float[Array, ""]` for improved type clarity.
- Added detailed docstrings to `perpendicular_distance_point_to_line_two_points`, specifying arguments and return values for better understanding.
- Streamlined the distance calculation in `perpendicular_distance_camera_2d_points_to_tracking_raycasting` by removing unnecessary type casting, enhancing code readability.

playground.py

@@ -620,11 +620,18 @@ def calculate_affinity_2d(
 @jaxtyped(typechecker=beartype)
 def perpendicular_distance_point_to_line_two_points(
     point: Num[Array, "3"], line: tuple[Num[Array, "3"], Num[Array, "3"]]
-) -> jnp.floating[Any]:
+) -> Float[Array, ""]:
     """
     Calculate the perpendicular distance between a point and a line.
-
     where `line` is represented by two points: `(line_start, line_end)`
+
+    Args:
+        point: The point to calculate the distance to
+        line: The line to calculate the distance to, represented by two points
+
+    Returns:
+        The perpendicular distance between the point and the line
+        (should be a scalar in `float`)
     """
     line_start, line_end = line
     distance = jnp.linalg.norm(
@@ -652,21 +659,16 @@ def perpendicular_distance_camera_2d_points_to_tracking_raycasting(
         Array of perpendicular distances for each keypoint
     """
     camera = detection.camera
-    # Convert timedelta to seconds for prediction
     delta_t_s = delta_t.total_seconds()
-
-    # Predict the 3D pose based on tracking and delta_t
     predicted_pose = predict_pose_3d(tracking, delta_t_s)
 
-    # Back-project the 2D points to 3D space (assuming z=0 plane)
+    # Back-project the 2D points to 3D space
+    # intersection with z=0 plane
     back_projected_points = detection.camera.unproject_points_to_z_plane(
         detection.keypoints, z=0.0
     )
-
-    # Get camera center from the camera parameters
     camera_center = camera.params.location
 
-    # Define function to calculate distance between a predicted point and its corresponding ray
     def calc_distance(predicted_point, back_projected_point):
         return perpendicular_distance_point_to_line_two_points(
             predicted_point, (camera_center, back_projected_point)
@@ -674,8 +676,8 @@ def perpendicular_distance_camera_2d_points_to_tracking_raycasting(
 
     # Vectorize over all keypoints
     vmap_calc_distance = jax.vmap(calc_distance)
-    distances: Float[Array, "J"] = cast(
-        Any, vmap_calc_distance(predicted_pose, back_projected_points)
+    distances: Float[Array, "J"] = vmap_calc_distance(
+        predicted_pose, back_projected_points
     )
 
     return distances