Ejemplo n.º 1
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def test_actual_data_confidence(name, filename, expected_meter,
                                expect_confident):
    pc = load('tests/testdata/' + filename)
    meter, confidence = get_stick_scale(pc)
    if expect_confident:
        assert_greater(confidence, .5, "confidence too low")
    else:
        assert_less(confidence, .5, "confidence too high")
Ejemplo n.º 2
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def test_stickscale(noise):
    s1 = make_red_stick([0, 0, 0], [0, 1, 0])
    s2 = make_red_stick([1, 2, 0], [1, 1, 0])
    s3 = make_red_stick([3, 3, 0], [3, 4, 0])
    pc = make_pointcloud((s1, s2, s3), noise)
    meter, confidence = get_stick_scale(pc)
    red_part_length = 0.25 + noise
    assert_with_error(meter, 4 * red_part_length / 0.8)
    assert_with_error(confidence, 1.0)
Ejemplo n.º 3
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 def test_stickscale_nocluster(noise):
     '''Cloud without clusters should return zero confidence.'''
     pc = pcl.PointCloudXYZRGB([[0, 0, 0], [10000, 10000, 10000]])
     meter, confidence = get_stick_scale(pc)
     np.testing.assert_almost_equal(confidence, 0.0)
Ejemplo n.º 4
0
 def test_stickscale_emptycloud(noise):
     '''Cloud with zero point should return zero confidence.'''
     pc = pcl.PointCloudXYZRGB()
     meter, confidence = get_stick_scale(pc)
     np.testing.assert_almost_equal(confidence, 0.0)