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")
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")
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)
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)
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)
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)
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)
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)