fix ruff formatting

Author: atonderski

zod/cli/extract_tsr_patches.py

@@ -78,9 +78,9 @@ def extract_tsr_patches(
     print("Will save dataset to", output_dir)
     output_dir.mkdir(parents=True, exist_ok=True)
 
-    assert not (
-        padding_factor is not None and (padding_px_x is not None or padding_px_y is not None)
-    ), "Cannot specify both padding and padding_factor"
+    assert not (padding_factor is not None and (padding_px_x is not None or padding_px_y is not None)), (
+        "Cannot specify both padding and padding_factor"
+    )
 
     padding = (padding_px_x, padding_px_y) if (padding_px_x is not None and padding_px_y is not None) else None
 

zod/cli/generate_coco_json.py

@@ -135,9 +135,7 @@ def convert_to_coco(
         if cls not in OBJECT_CLASSES:
             typer.echo(f"ERROR: Invalid class: {cls}.")
             raise typer.Exit(1)
-    typer.echo(
-        "Converting ZOD to COCO format. " f"Version: {version}, anonymization: {anonymization}, classes: {classes}"
-    )
+    typer.echo(f"Converting ZOD to COCO format. Version: {version}, anonymization: {anonymization}, classes: {classes}")
 
     zod_frames = ZodFrames(str(dataset_root), version.value)
 

zod/data_classes/box.py

@@ -244,9 +244,9 @@ def crop_from_image(
             tuple: padding in all four directions | (left,  top,  right, bottom)
         """
 
-        assert not (
-            padding is not None and padding_factor is not None
-        ), "Cannot specify both padding and padding_factor"
+        assert not (padding is not None and padding_factor is not None), (
+            "Cannot specify both padding and padding_factor"
+        )
 
         if padding is not None:
             padding_x, padding_y = padding

zod/data_classes/ego_motion.py

@@ -33,9 +33,9 @@ def get_poses(self, target_ts: Union[np.ndarray, float]) -> np.ndarray:
             [N, 4, 4] array of interpolated poses for each timestamp.
         """
         selfmin, selfmax = np.min(self.timestamps), np.max(self.timestamps)
-        assert (selfmin <= np.min(target_ts)) and (
-            selfmax >= np.max(target_ts)
-        ), f"targets not between pose timestamps, must be [{selfmin}, {selfmax}]"
+        assert (selfmin <= np.min(target_ts)) and (selfmax >= np.max(target_ts)), (
+            f"targets not between pose timestamps, must be [{selfmin}, {selfmax}]"
+        )
 
         if np.isin(target_ts, self.timestamps).all():
             return self.poses[self.timestamps.searchsorted(target_ts)]

zod/data_classes/info.py

@@ -67,9 +67,9 @@ def get_camera_lidar_map(
             A tuple of the camera frame and the closest lidar frame.
         """
         camera_name = f"{camera.value}_{anonymization.value}"
-        assert (
-            camera_name in self.camera_frames
-        ), f"Camera {camera_name} not found. Available cameras: {self.camera_frames.keys()}"
+        assert camera_name in self.camera_frames, (
+            f"Camera {camera_name} not found. Available cameras: {self.camera_frames.keys()}"
+        )
         assert lidar in self.lidar_frames, f"Lidar {lidar} not found. Available lidars: {self.lidar_frames.keys()}"
 
         for camera_frame in self.camera_frames[camera_name]:

zod/eval/detection/_experimental/matching.py

@@ -285,12 +285,12 @@ def match_one_frame(
         A list of tuples. Each tuple contains the ground truth object and the prediction.
     """
     # check that all objects are in the evaluation frame
-    assert all(
-        gt.box3d.frame == EVALUATION_FRAME for gt in ground_truth if gt.box3d is not None
-    ), "All ground truth objects must be in the evaluation frame."
-    assert all(
-        pred.box3d.frame == EVALUATION_FRAME for pred in predictions
-    ), "All predictions must be in the evaluation frame."
+    assert all(gt.box3d.frame == EVALUATION_FRAME for gt in ground_truth if gt.box3d is not None), (
+        "All ground truth objects must be in the evaluation frame."
+    )
+    assert all(pred.box3d.frame == EVALUATION_FRAME for pred in predictions), (
+        "All predictions must be in the evaluation frame."
+    )
 
     if method == "greedy":
         return greedy_match(