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 = MBTR(
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, :]
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]))
assumed_ints[0] *= 2 # There are two periodic distances at 2Å
assumed_ints[0] /= 2 # The periodic distances ar halved because they belong to different cells
# Check the H-C peaks
hc_feat = features[desc.get_location(("H", "C"))]
hc_peak_indices = find_peaks(hc_feat, prominence=0.001)[0]
hc_peak_locs = x[hc_peak_indices]
hc_peak_ints = hc_feat[hc_peak_indices]
self.assertTrue(np.allclose(hc_peak_locs, assumed_locs, rtol=0, atol=1e-2))
self.assertTrue(np.allclose(hc_peak_ints, assumed_ints, rtol=0, atol=1e-2))
# Check that everything else is zero
features[desc.get_location(("H", "C"))] = 0
self.assertEqual(features.sum(), 0)
def test_k2_peaks_finite(self):
"""Tests the correct peak locations and intensities are found for the
k=2 term in finite systems.
"""
desc = MBTR(
species=[1, 8],
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, :]
pos = H2O.get_positions()
x = desc.get_k2_axis()
# Check the H-H peaks
hh_feat = features[desc.get_location(("H", "H"))]
hh_peak_indices = find_peaks(hh_feat, prominence=0.5)[0]
hh_peak_locs = x[hh_peak_indices]
hh_peak_ints = hh_feat[hh_peak_indices]
self.assertTrue(np.allclose(hh_peak_locs, [np.linalg.norm(pos[0] - pos[2])], rtol=0, atol=1e-2))
self.assertTrue(np.allclose(hh_peak_ints, [1], rtol=0, atol=1e-2))
# Check the O-H peaks
ho_feat = features[desc.get_location(("H", "O"))]
ho_peak_indices = find_peaks(ho_feat, prominence=0.5)[0]
ho_peak_locs = x[ho_peak_indices]
ho_peak_ints = ho_feat[ho_peak_indices]
self.assertTrue(np.allclose(ho_peak_locs, np.linalg.norm(pos[0] - pos[1]), rtol=0, atol=1e-2))
self.assertTrue(np.allclose(ho_peak_ints, [2], rtol=0, atol=1e-2))
# Check that everything else is zero
features[desc.get_location(("H", "H"))] = 0
features[desc.get_location(("H", "O"))] = 0
self.assertEqual(features.sum(), 0)
