def test_detrend_heights_call(self):
""" tests if the call of heights make no mistake
"""
n = 10
dx = 0.5
h = np.random.normal(size=n)
t = UniformLineScan(h, dx * n)
for mode in ["height", "curvature", "slope"]:
detrended = t.detrend(detrend_mode=mode)
detrended.heights()
def test_detrend_curvature(self):
n = 10
dx = 0.5
x = np.arange(n) * dx
R = 4.
h = x ** 2 / R
t = UniformLineScan(h, dx * n)
detrended = t.detrend(detrend_mode="curvature")
assert abs(detrended.coeffs[-1] / detrended.physical_sizes[0] ** 2 - 1 / R) < 1e-12
def test_detrend_same_positions(self):
"""asserts that the detrended topography has the same x
"""
n = 10
dx = 0.5
h = np.random.normal(size=n)
t = UniformLineScan(h, dx * n)
for mode in ["curvature", "slope", "height"]:
detrended = t.detrend(detrend_mode=mode)
np.testing.assert_allclose(detrended.positions(), t.positions())
np.testing.assert_allclose(detrended.positions_and_heights()[0],
t.positions_and_heights()[0])
def test_detrend_reduces(self):
""" tests if detrending really reduces the heights (or slope) as claimed
"""
n = 10
dx = 0.5
h = [0.82355941, -1.32205074, 0.77084813, 0.49928252, 0.57872149,
2.80200331, 0.09551251, -1.11616977,
2.07630937, -0.65408072]
t = UniformLineScan(h, dx * n)
for mode in ['height', 'curvature', 'slope']:
detrended = t.detrend(detrend_mode=mode)
self.assertAlmostEqual(detrended.mean(), 0)
if mode == 'slope':
self.assertGreater(t.rms_slope_from_profile(),
detrended.rms_slope_from_profile(),
msg=mode)
else:
self.assertGreater(t.rms_height_from_profile(),
detrended.rms_height_from_profile(),
msg=mode)