def test_k2_peaks_finite(self):
"""Tests the correct peak locations and intensities are found for the
k=2 term in finite systems.
"""
desc = LMBTR(
species=["H", "O"],
k2={
"geometry": {
"function": "distance"
},
"grid": {
"min": -1,
"max": 3,
"sigma": 0.5,
"n": 1000
},
"weighting": {
"function": "unity"
},
},
normalize_gaussians=False,
periodic=False,
flatten=True,
sparse=False,
)
features = desc.create(H2O, [0])[0, :]
pos = H2O.get_positions()
x = desc.get_k2_axis()
# Check the X-H peaks
xh_feat = features[desc.get_location(("X", "H"))]
xh_peak_indices = find_peaks(xh_feat, prominence=0.5)[0]
xh_peak_locs = x[xh_peak_indices]
xh_peak_ints = xh_feat[xh_peak_indices]
self.assertTrue(
np.allclose(xh_peak_locs, [np.linalg.norm(pos[0] - pos[2])],
rtol=0,
atol=1e-2))
self.assertTrue(np.allclose(xh_peak_ints, [1], rtol=0, atol=1e-2))
# Check the X-O peaks
xo_feat = features[desc.get_location(("X", "O"))]
xo_peak_indices = find_peaks(xo_feat, prominence=0.5)[0]
xo_peak_locs = x[xo_peak_indices]
xo_peak_ints = xo_feat[xo_peak_indices]
self.assertTrue(
np.allclose(xo_peak_locs,
np.linalg.norm(pos[0] - pos[1]),
rtol=0,
atol=1e-2))
self.assertTrue(np.allclose(xo_peak_ints, [1], rtol=0, atol=1e-2))
# Check that everything else is zero
features[desc.get_location(("X", "H"))] = 0
features[desc.get_location(("X", "O"))] = 0
self.assertEqual(features.sum(), 0)
def test_k2_peaks_periodic(self):
"""Tests the correct peak locations and intensities are found for the
k=2 term in periodic systems.
"""
atoms = Atoms(cell=[
[10, 0, 0],
[10, 10, 0],
[10, 0, 10],
],
symbols=["H", "C"],
scaled_positions=[
[0.1, 0.5, 0.5],
[0.9, 0.5, 0.5],
])
desc = LMBTR(species=["H", "C"],
k2={
"geometry": {
"function": "distance"
},
"grid": {
"min": 0,
"max": 10,
"sigma": 0.5,
"n": 1000
},
"weighting": {
"function": "exp",
"scale": 0.8,
"cutoff": 1e-3
},
},
normalize_gaussians=False,
periodic=True,
flatten=True,
sparse=False)
features = desc.create(atoms, [0])[0, :]
x = desc.get_k2_axis()
# Calculate assumed locations and intensities.
assumed_locs = np.array([2, 8])
assumed_ints = np.exp(-0.8 * np.array([2, 8]))
# Check the X-C peaks
xc_feat = features[desc.get_location(("X", "C"))]
xc_peak_indices = find_peaks(xc_feat, prominence=0.001)[0]
xc_peak_locs = x[xc_peak_indices]
xc_peak_ints = xc_feat[xc_peak_indices]
self.assertTrue(
np.allclose(xc_peak_locs, assumed_locs, rtol=0, atol=1e-2))
self.assertTrue(
np.allclose(xc_peak_ints, assumed_ints, rtol=0, atol=1e-2))
# Check that everything else is zero
features[desc.get_location(("X", "C"))] = 0
self.assertEqual(features.sum(), 0)
"max": 5,
"n": 200,
"sigma": 0.05
},
"weighting": {
"function": "exponential",
"scale": 1,
"cutoff": 1e-2
},
},
periodic=True,
normalization="none",
)
# Create output for each site
sites = lmbtr.create(
slab_pure,
positions=[ontop_pos, bridge_pos, hcp_pos, fcc_pos],
)
# Plot the site-aluminum distributions for each site
al_slice = lmbtr.get_location(("X", "Al"))
x = lmbtr.get_k2_axis()
mpl.plot(x, sites[0, al_slice], label="top")
mpl.plot(x, sites[1, al_slice], label="bridge")
mpl.plot(x, sites[2, al_slice], label="hcp")
mpl.plot(x, sites[3, al_slice], label="fcc")
mpl.xlabel("Site-Al distance (Å)")
mpl.legend()
mpl.show()