style: update pre-commit (black 26.1.0, pre-commit-hooks-ros 0.10.2)

.pre-commit-config.yaml

@@ -47,7 +47,7 @@ repos:
       - id: check-package-depends
 
   - repo: https://github.com/tier4/pre-commit-hooks-ros
-    rev: v0.10.0
+    rev: v0.10.2
     hooks:
       - id: flake8-ros
       - id: prettier-xacro
@@ -74,7 +74,7 @@ repos:
         args: [--profile=black, --line-length=100]
 
   - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 25.12.0
+    rev: 26.1.0
     hooks:
       - id: black
         args: [--line-length=100]

control/autoware_smart_mpc_trajectory_follower/autoware_smart_mpc_trajectory_follower/scripts/drive_controller.py

@@ -16,6 +16,7 @@
 
 
 """Define a drive_controller class that calculates the final input of the Proxima-side MPC."""
+
 from functools import partial
 from importlib import reload as ir
 import threading

control/autoware_smart_mpc_trajectory_follower/autoware_smart_mpc_trajectory_follower/scripts/drive_functions.py

@@ -16,6 +16,7 @@
 
 
 """Define primary parameters and functions to be used elsewhere."""
+
 from functools import partial
 import os
 from pathlib import Path

control/autoware_smart_mpc_trajectory_follower/autoware_smart_mpc_trajectory_follower/scripts/drive_iLQR.py

@@ -16,7 +16,6 @@
 
 """Optimize input based on iLQR."""
 
-
 from importlib import reload as ir
 import time
 from typing import Callable

control/autoware_smart_mpc_trajectory_follower/autoware_smart_mpc_trajectory_follower/training_and_data_check/train_drive_NN_model.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Class for training neural nets from driving data."""
+
 from autoware_smart_mpc_trajectory_follower.scripts import drive_functions
 from autoware_smart_mpc_trajectory_follower.training_and_data_check import (
     train_drive_NN_model_with_memory,

control/autoware_smart_mpc_trajectory_follower/autoware_smart_mpc_trajectory_follower/training_and_data_check/train_drive_NN_model_with_memory.py

@@ -15,6 +15,7 @@
 # cspell: ignore optim savez suptitle
 
 """Class for training neural nets with memory from driving data."""
+
 from autoware_smart_mpc_trajectory_follower.scripts import drive_NN
 from autoware_smart_mpc_trajectory_follower.scripts import drive_functions
 from autoware_smart_mpc_trajectory_follower.training_and_data_check import (

control/autoware_smart_mpc_trajectory_follower/autoware_smart_mpc_trajectory_follower/training_and_data_check/train_drive_NN_model_without_memory.py

@@ -15,6 +15,7 @@
 # cspell: ignore optim savez suptitle
 
 """Class for training neural nets from driving data."""
+
 from autoware_smart_mpc_trajectory_follower.scripts import drive_NN
 from autoware_smart_mpc_trajectory_follower.scripts import drive_functions
 from autoware_smart_mpc_trajectory_follower.training_and_data_check import (

planning/autoware_freespace_planning_algorithms/test/debug_plot.py

@@ -61,7 +61,7 @@ def from_rosbag_path(cls, path: str) -> "ProblemDescription":
         message_map = {}
 
         while reader.has_next():
-            (topic, data, t) = reader.read_next()
+            topic, data, t = reader.read_next()
             msg_type = get_message(type_map[topic])
             msg = deserialize_message(data, msg_type)
             message_map[topic] = msg

planning/behavior_velocity_planner/autoware_behavior_velocity_intersection_module/scripts/ttc.py

@@ -222,7 +222,7 @@ def cleanup(self):
             max_size_total = 0
             max_size = None
             for image in self.images:
-                (w, h) = image.size
+                w, h = image.size
                 if w * h > max_size_total:
                     max_size = image.size
                     max_size_total = w * h

planning/behavior_velocity_planner/autoware_behavior_velocity_roundabout_module/scripts/ttc.py

@@ -222,7 +222,7 @@ def cleanup(self):
             max_size_total = 0
             max_size = None
             for image in self.images:
-                (w, h) = image.size
+                w, h = image.size
                 if w * h > max_size_total:
                     max_size = image.size
                     max_size_total = w * h

vehicle/autoware_accel_brake_map_calibrator/scripts/calc_utils.py

@@ -38,17 +38,13 @@ class CalcUtils:
     @staticmethod
     def average_filter(data, average_num):
         if not isinstance(average_num, int):
-            print(
-                "Error in average_filter(data, average_num):\
-                Type of average_num must be int"
-            )
+            print("Error in average_filter(data, average_num):\
+                Type of average_num must be int")
             sys.exit(1)
 
         if average_num % 2 == 0:
-            print(
-                "Error in average_filter(data, average_num):\
-                average_num must be odd number"
-            )
+            print("Error in average_filter(data, average_num):\
+                average_num must be odd number")
             sys.exit(1)
 
         average_filter = np.ones(average_num) / float(average_num)