fix error: 'numpy.ndarray' object has no attribute 'append'

[jsbyysheng]

Reference issue

fix error: 'numpy.ndarray' object has no attribute 'append'

What does this implement/fix?

When running grid_based_sweep_coverage_path_planner.py and giving ox and oy without ox[0] == ox[-1], you will get fix error: 'numpy.ndarray' object has no attribute 'append'

Additional information

CheckList

-[] Did you add an unittest for your new example or defect fix?
-[] Did you add documents for your new example?
-[] All CIs are green? (You can check it after submitting)

[AtsushiSakai]

Thank you for your PR. is it possible to add a test for this change in this file? https://github.com/AtsushiSakai/PythonRobotics/blob/master/tests/test_grid_map_lib.py

[jsbyysheng]

After my survey, the error occurs in grid_based_sweep_coverage_path_planner.py because the function convert_grid_coordinate returns numpy.ndarray. I think it more suitable to modify grid_based_sweep_coverage_path_planner.py:

from

def convert_grid_coordinate(ox, oy, sweep_vec, sweep_start_position):
    tx = [ix - sweep_start_position[0] for ix in ox]
    ty = [iy - sweep_start_position[1] for iy in oy]
    th = math.atan2(sweep_vec[1], sweep_vec[0])
    rot = Rot.from_euler('z', th).as_matrix()[0:2, 0:2]
    converted_xy = np.stack([tx, ty]).T @ rot

    return converted_xy[:, 0], converted_xy[:, 1]

to

def convert_grid_coordinate(ox, oy, sweep_vec, sweep_start_position):
    tx = [ix - sweep_start_position[0] for ix in ox]
    ty = [iy - sweep_start_position[1] for iy in oy]
    th = math.atan2(sweep_vec[1], sweep_vec[0])
    rot = Rot.from_euler('z', th).as_matrix()[0:2, 0:2]
    converted_xy = np.stack([tx, ty]).T @ rot

    return converted_xy[:, 0].tolist(), converted_xy[:, 1].tolist()

In this case, we do not need to change the algorithm file and the pytest file. What do you think about it?

[AtsushiSakai]

I prefer to use np.array instead of build-in list in codes. So I love this PR change.

[jsbyysheng]

Alright. I think test should be add to https://github.com/AtsushiSakai/PythonRobotics/blob/master/tests/test_grid_based_sweep_coverage_path_planner.py because in https://github.com/AtsushiSakai/PythonRobotics/blob/master/tests/test_grid_map_lib.py, ox[0] != ox[-1] and oy[0]!=oy[-1] make np.append effective.

def test_polygon_set():
    ox = [0.0, 20.0, 50.0, 100.0, 130.0, 40.0]
    oy = [0.0, -20.0, 0.0, 30.0, 60.0, 80.0]

    grid_map = GridMap(600, 290, 0.7, 60.0, 30.5)

    grid_map.set_value_from_polygon(ox, oy, 1.0, inside=False)

[AtsushiSakai]

The test looks good to me!

[AtsushiSakai]

I added a test. So LGTM. thank you!!