def test_squeeze(self):
x = np.linspace(0, 4 * np.pi, 101)
h = np.sin(x)
surface = UniformLineScan(h, 4 * np.pi).scale(2.0)
surface2 = surface.squeeze()
self.assertTrue(isinstance(surface2, UniformLineScan))
np.testing.assert_allclose(surface.heights(), surface2.heights())
def test_window_line_scan():
nx = 27
sx = 1.3
h = np.ones((nx, ))
t = UniformLineScan(h, physical_sizes=(sx, ), periodic=True).window()
np.testing.assert_almost_equal(t.heights()[0], 1.0)
np.testing.assert_almost_equal((t.heights()**2).sum() / nx, 1.0)
t = UniformLineScan(h, physical_sizes=(sx, ), periodic=False).window()
np.testing.assert_almost_equal(t.heights()[0], 0.0)
np.testing.assert_almost_equal((t.heights()**2).sum() / nx, 1.0)
with pytest.raises(ValueError):
UniformLineScan(h, physical_sizes=(sx, ),
periodic=False).window(direction='y').window_data
with pytest.raises(ValueError):
UniformLineScan(h, physical_sizes=(sx, ),
periodic=False).window(direction='radial').window_data
def test_positions_and_heights(self):
h = np.array((0, 1, 2, 3, 4))
t = UniformLineScan(h, 4)
assert_array_equal(t.heights(), h)
expected_x = np.array((0., 0.8, 1.6, 2.4, 3.2))
np.testing.assert_allclose(t.positions(), expected_x)
x2, h2 = t.positions_and_heights()
np.testing.assert_allclose(x2, expected_x)
assert_array_equal(h2, h)
def test_lbfgsb_1D(dx, n):
# test the 1D periodic objective is working
s = n * dx
Es = 1.
substrate = PeriodicFFTElasticHalfSpace((n,), young=Es,
physical_sizes=(s,), fft='serial')
surface = UniformLineScan(np.cos(2 * np.pi * np.arange(n) / n), (s,))
system = make_system(substrate, surface)
offset = 0.005
lbounds = np.zeros(n)
bnds = system._reshape_bounds(lbounds, )
init_gap = np.zeros(n, ) # .flatten()
disp = init_gap + surface.heights() + offset
res = optim.minimize(system.primal_objective(offset, gradient=True),
disp,
method='L-BFGS-B', jac=True,
bounds=bnds,
options=dict(gtol=1e-5 * Es * surface.rms_slope_from_profile()
* surface.area_per_pt,
ftol=0))
forces = res.jac
gap = res.x
converged = res.success
assert converged
if hasattr(res.message, "decode"):
decoded_message = res.message.decode()
else:
decoded_message = res.message
assert decoded_message == \
'CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL'
x = np.arange(n) * s / n
mean_pressure = np.mean(forces) / substrate.area_per_pt
assert mean_pressure > 0
pth = mean_pressure * _pressure(
x / s,
mean_pressure=s * mean_pressure / Es)
if False:
import matplotlib.pyplot as plt
plt.figure()
# plt.plot(np.arange(n)*s/n, surface.heights())
plt.plot(x, gap + (surface.heights()[:] + offset), 'r-')
plt.plot(x, (surface.heights()[:] + offset), 'k-')
plt.figure()
plt.plot(x, forces / substrate.area_per_pt, 'k-')
plt.plot(x, pth, 'r-')
plt.show()
assert (np.allclose(
forces /
substrate.area_per_pt, pth, atol=1e-2))