def findPeriodicallyEqualAtoms(atoms, other_atoms):
center = atoms.positions.mean(axis=0)
center, remain = convertToBasis(center, other_atoms.cell)
center = (np.array([.5, .5, .5]) - center)[0]
other_atoms = wrap(other_atoms, center=center)
cell = other_atoms.get_cell()
pbc = atoms.get_pbc()
cell = atoms.cell[pbc]
group = -np.ones(len(other_atoms), dtype=np.int)
for i, atom in enumerate(atoms):
diff = other_atoms.get_positions() - atom.position
pos = minimalDistance(diff, cell)
mask = vectorLength(pos, 1) < 1e-5
indices = np.arange(len(other_atoms))[mask]
group[indices] = i
return group
def makeAtomsRelaxed(atoms, relaxed_atoms, tolerance=1.0, cell=None, change=None, correct_drift=False):
atoms = atoms.copy()
if relaxed_atoms is None:
return atoms
if change is None:
change = np.ones(len(atoms), np.bool)
if cell is None:
cell = atoms.get_cell()
cell[relaxed_atoms.pbc] = relaxed_atoms.cell[relaxed_atoms.pbc]
drift = np.zeros(3, np.float)
used = np.zeros(len(relaxed_atoms), np.bool)
changed = []
if relaxed_atoms is not None:
# Find relaxed atoms closest to originals.
for i, atom in enumerate(atoms):
if not change[i]:
continue
mask = np.array([r_atom.symbol == atom.symbol for r_atom in relaxed_atoms])
mask = np.logical_and(mask, np.logical_not(used))
if mask.sum() == 0:
continue
diff = relaxed_atoms.positions[mask] - atom.position
diff = minimalDistance(diff, cell[relaxed_atoms.pbc])
index = vectorLength(diff, 1).argmin()
adjustment = diff[index]
if vectorLength(adjustment) < tolerance:
drift += adjustment
real_index = np.arange(len(relaxed_atoms))[mask][index]
used[real_index] = False
changed.append(i)
atom.position += adjustment
if correct_drift:
changed = np.array(changed)
drift /= len(changed)
atoms.positions[changed] -= drift
return atoms
def substitutionalDopingOfMiddleLayer(atoms, n_dopants=1, dopant_element='P', centers=None):
assert isinstance(n_dopants, int)
assert n_dopants > 0
atoms = atoms.copy()
middle_layer = list(findMiddleLayer(atoms))
symbols = np.array(atoms.get_chemical_symbols())
make_dopants = []
for i in range(n_dopants):
if centers is None:
middle_layer_index = 0
centers = []
else:
pos = atoms.positions[np.array(middle_layer, int)]
for center in centers:
middle_layer_index = vectorLength(minimalDistance(pos - center, atoms.cell), 1).argmax()
index = middle_layer.pop(middle_layer_index)
make_dopants.append(index)
centers.append(atoms[index].position)
symbols[np.array(make_dopants, int)] = dopant_element
atoms.set_chemical_symbols(symbols)
return atoms
