예제 #1
0
def test_new_deck_points():
    # Checks that the correct deck calibration points are being used
    # if feature_flag is set (or not)

    advs.set_adv_setting('deckCalibrationDots', True)
    calibration_points = get_calibration_points()
    expected_points1 = expected_points()
    # Check that old calibration points are used in cli
    assert calibration_points[1] == (12.13, 6.0)
    assert calibration_points[2] == (380.87, 6.0)
    assert calibration_points[3] == (12.13, 351.5)
    # Check that endpoints are now using slot 7 for dots
    assert expected_points1['1'] == (12.13, 6.0)
    assert expected_points1['2'] == (380.87, 6.0)
    assert expected_points1['3'] == (12.13, 261.0)

    advs.set_adv_setting('deckCalibrationDots', False)
    calibration_points2 = get_calibration_points()
    expected_points2 = expected_points()
    # Check that new calibration points are used
    assert calibration_points2[1] == (12.13, 9.0)
    assert calibration_points2[2] == (380.87, 9.0)
    assert calibration_points2[3] == (12.13, 348.5)
    # Check that endpoints are now using slot 7 for crosses
    assert expected_points2['1'] == (12.13, 9.0)
    assert expected_points2['2'] == (380.87, 9.0)
    assert expected_points2['3'] == (12.13, 258.0)
예제 #2
0
async def test_save_calibration_file(dc_session, monkeypatch):
    hardware = dc_session.adapter
    hardware.reset()
    expected_pos = endpoints.expected_points()
    dc_session.points = {
        k: (v[0], v[1] + 0.3)
        for k, v in expected_pos.items()
    }
    dc_session.z_value = 0.2

    persisted_data = []

    def dummy_save(config, filename=None, tag=None):
        nonlocal persisted_data
        persisted_data.append((config, filename, tag))

    monkeypatch.setattr(robot_configs, 'save_deck_calibration', dummy_save)

    await endpoints.save_transform({})

    in_memory = hardware.config.gantry_calibration
    assert len(persisted_data) == 1  # back up now happens at beginning of sess
    assert persisted_data[0][0].gantry_calibration == in_memory

    expected = [[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.3],
                [0.0, 0.0, 1.0, 0.2], [0.0, 0.0, 0.0, 1.0]]
    assert np.allclose(in_memory, expected)