Formatting: Use default line-length of black

demos/demo_trifinger_platform.py

@@ -76,8 +76,7 @@ def main():
         if args.object == "cube":
             camera_observation = platform.get_camera_observation(t)
             print(
-                "Cube Position: %s"
-                % camera_observation.filtered_object_pose.position
+                "Cube Position: %s" % camera_observation.filtered_object_pose.position
             )
 
         if platform.enable_cameras:

docs/sim_finger_screenshots.py

@@ -76,9 +76,7 @@
     cube = collision_objects.ColoredCubeV2(
         position=config["cube_pos"],
         # rotate the cube a bit, so it looks nicer
-        orientation=Rotation.from_euler(
-            "xz", (90, -40), degrees=True
-        ).as_quat(),
+        orientation=Rotation.from_euler("xz", (90, -40), degrees=True).as_quat(),
     )
 
     # set the finger position

pyproject.toml

@@ -1,9 +1,6 @@
 [build-system]
 requires = ["setuptools>=42", "wheel"]
 
-[tool.black]
-line-length = 79
-
 [tool.ruff]
 lint.select = [
     "E",

scripts/playback_data.py

@@ -22,9 +22,7 @@ def main_finger(finger_type, data_file):
 
     def reset_finger(joint_position):
         for i, joint_id in enumerate(finger.pybullet_joint_indices):
-            pybullet.resetJointState(
-                finger.finger_id, joint_id, joint_position[i]
-            )
+            pybullet.resetJointState(finger.finger_id, joint_id, joint_position[i])
 
     with open(data_file, "rb") as file_handle:
         episodes = pickle.load(file_handle)
@@ -93,9 +91,7 @@ def main_trifinger(finger_type, data_file_0, data_file_120, data_file_240):
 
     def reset_finger(joint_position):
         for i, joint_id in enumerate(finger.pybullet_joint_indices):
-            pybullet.resetJointState(
-                finger.finger_id, joint_id, joint_position[i]
-            )
+            pybullet.resetJointState(finger.finger_id, joint_id, joint_position[i])
 
     data = []
     for filename in (data_file_0, data_file_120, data_file_240):

scripts/plot_tip_position_trajectories.py

@@ -105,9 +105,7 @@ def main():
                 trajectory = np.vstack(data["tip_positions"])
                 dist = trajectory - tip_goal
 
-                ax[a].plot(
-                    dist[:, x], dist[:, y], color=(0.3, 0.3, 0.3), linewidth=2
-                )
+                ax[a].plot(dist[:, x], dist[:, y], color=(0.3, 0.3, 0.3), linewidth=2)
                 ax[a].plot(dist[0, x], dist[0, y], "bo", zorder=40)
                 ax[a].plot(dist[-1, x], dist[-1, y], "g^", zorder=40)
 

scripts/rrc_evaluate.py

@@ -50,9 +50,7 @@ def main():
     # some basic checks of the input
     if not args.singularity_image.exists():
         print(
-            "The singularity image {} does not exist.".format(
-                args.singularity_image
-            ),
+            "The singularity image {} does not exist.".format(args.singularity_image),
             file=sys.stderr,
         )
         return 1

scripts/screenshot_mode.py

@@ -20,9 +20,7 @@ def main():
     parser.add_argument(
         "finger_type",
         choices=valid_finger_types,
-        help="Specify a valid finger type.  One of {}".format(
-            valid_finger_types
-        ),
+        help="Specify a valid finger type.  One of {}".format(valid_finger_types),
     )
     parser.add_argument(
         "--position", "-p", type=float, nargs="+", help="Joint positions."

scripts/view_camera_log_real_and_sim.py

@@ -20,12 +20,8 @@
 
 def main():
     parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument(
-        "log_dir", type=pathlib.Path, help="Path to the log files."
-    )
-    parser.add_argument(
-        "--rate", type=int, default=1, help="Time in ms per step."
-    )
+    parser.add_argument("log_dir", type=pathlib.Path, help="Path to the log files.")
+    parser.add_argument("--rate", type=int, default=1, help="Time in ms per step.")
     args = parser.parse_args()
 
     robot_log_file = str(args.log_dir / "robot_data.dat")
@@ -40,8 +36,7 @@ def main():
     cameras = camera.create_trifinger_camera_array_from_config(args.log_dir)
 
     cube_urdf_file = (
-        pathlib.Path(trifinger_simulation.__file__).parent
-        / "data/cube_v2/cube_v2.urdf"
+        pathlib.Path(trifinger_simulation.__file__).parent / "data/cube_v2/cube_v2.urdf"
     )
     cube = pybullet.loadURDF(
         fileName=str(cube_urdf_file),
@@ -50,31 +45,19 @@ def main():
 
     pybullet.configureDebugVisualizer(lightPosition=(0, 0, 1.0))
     pybullet.configureDebugVisualizer(pybullet.COV_ENABLE_SHADOWS, 1)
-    pybullet.configureDebugVisualizer(
-        pybullet.COV_ENABLE_RGB_BUFFER_PREVIEW, 0
-    )
-    pybullet.configureDebugVisualizer(
-        pybullet.COV_ENABLE_DEPTH_BUFFER_PREVIEW, 0
-    )
+    pybullet.configureDebugVisualizer(pybullet.COV_ENABLE_RGB_BUFFER_PREVIEW, 0)
+    pybullet.configureDebugVisualizer(pybullet.COV_ENABLE_DEPTH_BUFFER_PREVIEW, 0)
     # yes, it is really a segmentation maRk...
-    pybullet.configureDebugVisualizer(
-        pybullet.COV_ENABLE_SEGMENTATION_MARK_PREVIEW, 0
-    )
+    pybullet.configureDebugVisualizer(pybullet.COV_ENABLE_SEGMENTATION_MARK_PREVIEW, 0)
 
-    for t in range(
-        log.get_first_timeindex(), log.get_last_timeindex() + 1, 100
-    ):
+    for t in range(log.get_first_timeindex(), log.get_last_timeindex() + 1, 100):
         robot_observation = log.get_robot_observation(t)
-        simulation.reset_finger_positions_and_velocities(
-            robot_observation.position
-        )
+        simulation.reset_finger_positions_and_velocities(robot_observation.position)
 
         # get rendered images from simulation
         sim_images = cameras.get_images()
         # images are rgb --> convert to bgr for opencv
-        sim_images = [
-            cv2.cvtColor(img, cv2.COLOR_RGB2BGR) for img in sim_images
-        ]
+        sim_images = [cv2.cvtColor(img, cv2.COLOR_RGB2BGR) for img in sim_images]
         sim_images = np.hstack(sim_images)
 
         # get real images from cameras
@@ -88,8 +71,7 @@ def main():
             )
 
             real_images = [
-                utils.convert_image(cam.image)
-                for cam in camera_observation.cameras
+                utils.convert_image(cam.image) for cam in camera_observation.cameras
             ]
             real_images = np.hstack(real_images)
         except Exception as e:

tests/test_camera.py

@@ -19,9 +19,7 @@ def test_calib_data_to_matrix_1x1():
     }
     expected = np.array([[42]])
 
-    np.testing.assert_array_equal(
-        sim_camera.calib_data_to_matrix(data), expected
-    )
+    np.testing.assert_array_equal(sim_camera.calib_data_to_matrix(data), expected)
 
 
 def test_calib_data_to_matrix_3x3():
@@ -32,9 +30,7 @@ def test_calib_data_to_matrix_3x3():
     }
     expected = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
 
-    np.testing.assert_array_equal(
-        sim_camera.calib_data_to_matrix(data), expected
-    )
+    np.testing.assert_array_equal(sim_camera.calib_data_to_matrix(data), expected)
 
 
 def test_calib_data_to_matrix_2x4():
@@ -45,9 +41,7 @@ def test_calib_data_to_matrix_2x4():
     }
     expected = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
 
-    np.testing.assert_array_equal(
-        sim_camera.calib_data_to_matrix(data), expected
-    )
+    np.testing.assert_array_equal(sim_camera.calib_data_to_matrix(data), expected)
 
 
 def test_camera_parameters_load():
@@ -61,9 +55,7 @@ def test_camera_parameters_load():
         ]
     )
 
-    expected_dist_coeffs = np.array(
-        [-0.2373, 0.1466, -0.0033, 0.0002, -0.1356]
-    )
+    expected_dist_coeffs = np.array([-0.2373, 0.1466, -0.0033, 0.0002, -0.1356])
 
     expected_tf_mat = np.array(
         [
@@ -81,15 +73,11 @@ def test_camera_parameters_load():
     assert params.name == "camera180"
     assert params.width == 720
     assert params.height == 540
-    np.testing.assert_array_almost_equal(
-        params.camera_matrix, expected_camera_matrix
-    )
+    np.testing.assert_array_almost_equal(params.camera_matrix, expected_camera_matrix)
     np.testing.assert_array_almost_equal(
         params.distortion_coefficients, expected_dist_coeffs
     )
-    np.testing.assert_array_almost_equal(
-        params.tf_world_to_camera, expected_tf_mat
-    )
+    np.testing.assert_array_almost_equal(params.tf_world_to_camera, expected_tf_mat)
 
 
 def test_camera_parameters_dump(tmpdir):
@@ -110,9 +98,7 @@ def test_camera_parameters_dump(tmpdir):
     assert params.name == params2.name
     assert params.width == params2.width
     assert params.height == params2.height
-    np.testing.assert_array_almost_equal(
-        params.camera_matrix, params2.camera_matrix
-    )
+    np.testing.assert_array_almost_equal(params.camera_matrix, params2.camera_matrix)
     np.testing.assert_array_almost_equal(
         params.distortion_coefficients, params2.distortion_coefficients
     )

tests/test_finger_types_data.py

@@ -27,9 +27,7 @@ def test_check_finger_type():
 
 def test_get_finger_urdf():
     for name in ftd.finger_types_data.keys():
-        assert (
-            ftd.get_finger_urdf(name) == ftd.finger_types_data[name].urdf_file
-        )
+        assert ftd.get_finger_urdf(name) == ftd.finger_types_data[name].urdf_file
 
     with pytest.raises(ValueError):
         ftd.check_finger_type("invalid")

tests/test_loading_urdfs.py

@@ -27,9 +27,7 @@ def test_loading_urdfs(self):
 
             except pybullet.error as e:
                 self.fail(
-                    "Failed to create SimFinger(finger_type={}): {}".format(
-                        key, e
-                    )
+                    "Failed to create SimFinger(finger_type={}): {}".format(key, e)
                 )
 
     def test_loading_urdfs_locally(self):

tests/test_reset_joints.py

@@ -25,9 +25,7 @@ def test_reproduce_reset_state(self):
         )
 
         for _ in range(100):
-            state_positions = sample.random_joint_positions(
-                finger.number_of_fingers
-            )
+            state_positions = sample.random_joint_positions(finger.number_of_fingers)
             state_velocities = [pos * 10 for pos in state_positions]
 
             reset_state = finger.reset_finger_positions_and_velocities(

tests/test_sample.py

@@ -30,17 +30,13 @@ def test_random_point_positions(self):
 
         # one finger
         for i in range(100):
-            result = sample.random_joint_positions(
-                1, lower_bounds, upper_bounds
-            )
+            result = sample.random_joint_positions(1, lower_bounds, upper_bounds)
             assert_array_less_equal(lower_bounds, result)
             assert_array_less_equal(result, upper_bounds)
 
         # three finger
         for i in range(100):
-            result = sample.random_joint_positions(
-                3, lower_bounds, upper_bounds
-            )
+            result = sample.random_joint_positions(3, lower_bounds, upper_bounds)
             assert_array_less_equal(lower_bounds * 3, result)
             assert_array_less_equal(result, upper_bounds * 3)
 

tests/test_sim_finger.py

@@ -20,41 +20,27 @@ def test_SimFinger_sanitise_torqes():
     max_torque = 0.5
 
     # without velocity damping
-    t = SimFinger._sanitise_torques(
-        [-0.2, 0.4], max_torque, 0, np.array([0, 0])
-    )
+    t = SimFinger._sanitise_torques([-0.2, 0.4], max_torque, 0, np.array([0, 0]))
     np.testing.assert_array_equal(t, [-0.2, 0.4])
 
-    t = SimFinger._sanitise_torques(
-        [-1.2, 0.4], max_torque, 0, np.array([0, 0])
-    )
+    t = SimFinger._sanitise_torques([-1.2, 0.4], max_torque, 0, np.array([0, 0]))
     np.testing.assert_array_equal(t, [-0.5, 0.4])
 
-    t = SimFinger._sanitise_torques(
-        [-0.2, 0.6], max_torque, 0, np.array([0, 0])
-    )
+    t = SimFinger._sanitise_torques([-0.2, 0.6], max_torque, 0, np.array([0, 0]))
     np.testing.assert_array_equal(t, [-0.2, 0.5])
 
-    t = SimFinger._sanitise_torques(
-        [-0.8, 0.6], max_torque, 0, np.array([0, 0])
-    )
+    t = SimFinger._sanitise_torques([-0.8, 0.6], max_torque, 0, np.array([0, 0]))
     np.testing.assert_array_equal(t, [-0.5, 0.5])
 
     # with velocity damping
-    t = SimFinger._sanitise_torques(
-        [0, 0], max_torque, 0.2, np.array([1, -0.5])
-    )
+    t = SimFinger._sanitise_torques([0, 0], max_torque, 0.2, np.array([1, -0.5]))
     np.testing.assert_array_almost_equal(t, [-0.2, 0.1])
 
     t = SimFinger._sanitise_torques([0, 0], max_torque, 1, np.array([1, -0.6]))
     np.testing.assert_array_almost_equal(t, [-0.5, 0.5])
 
-    t = SimFinger._sanitise_torques(
-        [0.1, 0.2], max_torque, 0.2, np.array([1, -0.5])
-    )
+    t = SimFinger._sanitise_torques([0.1, 0.2], max_torque, 0.2, np.array([1, -0.5]))
     np.testing.assert_array_almost_equal(t, [-0.1, 0.3])
 
-    t = SimFinger._sanitise_torques(
-        [1, -1], max_torque, 0.2, np.array([1, -0.5])
-    )
+    t = SimFinger._sanitise_torques([1, -1], max_torque, 0.2, np.array([1, -0.5]))
     np.testing.assert_array_almost_equal(t, [0.3, -0.4])