def test_find_indexing_with_non_orthogonal_cell(self):
cell = UnitCell(1, 1, 1, 90, 95, 103)
cart_cell = cell.getB()
qs = np.array([
[.5, 0, 0],
[0, .5, 0],
[0, 0, .5],
[0, 0, .25],
])
qs = np.dot(qs, cart_cell)
indices = indexing.index_q_vectors(qs)
expected_indexing = np.array([[0, 0, 1], [0, 1, 0], [2, 0, 0],
[1, 0, 0]])
npt.assert_equal(indices,
expected_indexing,
err_msg="Indexing does not match expected.")
def test_find_bases_with_non_orthogonal_cell(self):
cell = UnitCell(1, 1, 1, 90, 95, 103)
cart_cell = cell.getB()
qs = np.array([
[.5, 0, 0],
[0, .5, 0],
[0, 0, .5],
[0, 0, .25],
])
qs = np.dot(qs, cart_cell)
ndim, bases = indexing.find_bases(qs, 1e-5)
self.assertEqual(ndim, 3, "Number of dimensions must be 3")
expected_bases = np.array([[0., 0., 0.25], [0., .5, 0.],
[0.51521732, 0.11589868, 0.04490415]])
npt.assert_almost_equal(bases,
expected_bases,
err_msg="Basis vectors do not match")
def test_find_bases_with_non_orthogonal_cell(self):
cell = UnitCell(1, 1, 1, 90, 95, 103)
cart_cell = cell.getB()
qs = np.array([
[.5, 0, 0],
[0, .5, 0],
[0, 0, .5],
[0, 0, .25],
])
qs = np.dot(qs, cart_cell)
ndim, bases = indexing.find_bases(qs, 1e-5)
self.assertEqual(ndim, 3, "Number of dimensions must be 3")
expected_bases = np.array([
[0., 0., 0.25],
[0., .5, 0.],
[0.51521732, 0.11589868, 0.04490415]
])
npt.assert_almost_equal(bases, expected_bases, err_msg="Basis vectors do not match")
def test_find_indexing_with_non_orthogonal_cell(self):
cell = UnitCell(1, 1, 1, 90, 95, 103)
cart_cell = cell.getB()
qs = np.array([
[.5, 0, 0],
[0, .5, 0],
[0, 0, .5],
[0, 0, .25],
])
qs = np.dot(qs, cart_cell)
indices = indexing.index_q_vectors(qs)
expected_indexing = np.array([
[0, 0, 1],
[0, 1, 0],
[2, 0, 0],
[1, 0, 0]
])
npt.assert_equal(indices, expected_indexing, err_msg="Indexing does not match expected.")
