def __init__(self, atoms, indices=None, name='ir', delta=0.01,
nfree=2, directions=None):
assert nfree in [2, 4]
self.atoms = atoms
if indices is None:
indices = range(len(atoms))
self.indices = np.asarray(indices)
self.nfree = nfree
self.name = name + '-d%.3f' % delta
self.delta = delta
self.H = None
if directions is None:
self.directions = np.asarray([0, 1, 2])
else:
self.directions = np.asarray(directions)
self.ir = True
self.ram = False
if str(type(self.atoms[0])) == "<class 'ase.atoms.Atoms'>":
self.imagetype='atoms'
fixed_atoms = constraints.constrained_indices(atoms[0])
allatoms = np.array(range(0,len(atoms[0])))
self.free_atoms = [i for i in allatoms if i not in fixed_atoms]
self.free_list = range(0,len(self.free_atoms))
self.atom = atoms[0].copy()
else:
self.imagetype='pickle'
if atoms.constraints:
print('WARNING! \n Your Atoms object is constrained. '
'Some forces may be unintended set to zero. \n')
self.calc = atoms.get_calculator()
def test_getindices():
from ase.build import fcc111
from ase.constraints import (FixAtoms, FixBondLengths, FixLinearTriatomic,
FixInternals, Hookean, constrained_indices)
slab = fcc111('Pt', (4, 4, 4))
C1 = FixAtoms([0, 2, 4])
C2 = FixBondLengths([[0, 1], [0, 2]])
C3 = FixInternals(bonds=[[1, [7, 8]], [1, [8, 9]]])
C4 = Hookean(a1=30, a2=40, rt=1.79, k=5.)
C5 = FixLinearTriatomic(triples=[(0, 1, 2), (3, 4, 5)])
slab.set_constraint([C1, C2, C3, C4, C5])
assert all(
constrained_indices(slab, (FixAtoms, FixBondLengths)) == [0, 1, 2, 4])
assert all(
constrained_indices(slab, (FixBondLengths,
FixLinearTriatomic)) == [0, 1, 2, 3, 4, 5])
assert all(
constrained_indices(slab) == [0, 1, 2, 3, 4, 5, 7, 8, 9, 30, 40])
def main():
arg = sys.argv
paras = readinputs(arg[1])
print paras
start_atom = int(paras['start_atom'])
end_atom = int(paras['end_atom'])
shift_targets = numpy.array(
[int(field) for field in paras['shift_targets'].split()])
dstrain = float(paras['dstrain'])
fixed_direction = paras['fix_direction']
#read geometry
p1 = read(filename=paras['start_structure'], index=0, format='vasp')
bond_length = p1.get_distance(start_atom, end_atom)
fixed_atoms = constrained_indices(p1)
working_dir = os.getcwd()
#move atoms based on the given strain and submit jobs
drs = interpolate(p1[start_atom], p1[end_atom], dstrain,
int(paras['njobs']))
#print new_atoms
i = 0
log = open('stretch.dat', 'w')
for dr in drs:
for target in shift_targets:
p1[target].position += dr
job_i = working_dir + '/' + str(i)
make_dir(job_i)
write(filename=job_i + '/POSCAR', images=p1, format='vasp')
fix_atoms(filename=job_i + '/POSCAR',
fixed_atoms=[end_atom],
fixed_direction=fixed_direction)
log.write("%4d %8.6f\n" % (i, i * dstrain * bond_length))
i += 1
os.system('cp POTCAR ' + job_i)
os.system('cp KPOINTS ' + job_i)
os.system('cp INCAR ' + job_i)
os.system('cp ' + paras['job_submit_script'] + ' ' + job_i)
with cd(job_i):
os.system(paras['job_submit_cmd'] + ' ' +
paras['job_submit_script'])
print os.getcwd(), 'is submitted'
print 'Back to directory', os.getcwd()
def __init__(self, atoms, indices=None, name='vib', delta=0.01, nfree=2):
assert nfree in [2, 4]
self.atoms = atoms
if indices is None:
indices = range(len(atoms))
self.indices = np.asarray(indices)
self.name = name
self.delta = delta
self.nfree = nfree
self.H = None
self.ir = None
self.ram = None
if str(type(self.atoms[0])) == "<class 'ase.atoms.Atoms'>":
self.imagetype = 'atoms'
fixed_atoms = constraints.constrained_indices(atoms[0])
allatoms = np.array(range(0, len(atoms[0])))
self.free_atoms = [i for i in allatoms if i not in fixed_atoms]
self.free_list = range(0, len(self.free_atoms))
self.atom = atoms[0].copy()
else:
self.imagetype = 'pickle'
def main():
arg = sys.argv
paras = readinputs(arg[1])
print paras
target_atom = int(paras['target_atom'])
#set strain
fixed_direction = [int(field) for field in paras['fix_direction'].split()]
#read geometry
p1 = read(filename=paras['start_structure'], index=0, format='vasp')
p2 = read(filename=paras['end_structure'], index=0, format='vasp')
fixed_atoms = constrained_indices(p1)
working_dir = os.getcwd()
#move atoms based on the given strain and submit jobs
print p1[target_atom]
new_atoms = interpolate(p1[target_atom], p2[target_atom],
int(paras['image_numb']))
#print new_atoms
i = 0
for atom in new_atoms:
p1[target_atom].position = atom
job_i = working_dir + '/' + str(i)
make_dir(job_i)
write(filename=job_i + '/POSCAR', images=p1, format='vasp')
fix_atoms(filename=job_i + '/POSCAR',
fixed_atoms=[target_atom],
fixed_directions=fixed_direction)
i += 1
os.system('cp POTCAR ' + job_i)
os.system('cp KPOINTS ' + job_i)
os.system('cp INCAR ' + job_i)
os.system('cp ' + paras['job_submit_script'] + ' ' + job_i)
with cd(job_i):
os.system(paras['job_submit_cmd'] + ' ' +
paras['job_submit_script'])
print os.getcwd(), 'is submitted'
print 'Back to directory', os.getcwd()
from ase.build import fcc111
from ase.constraints import (FixAtoms, FixBondLengths, FixInternals, Hookean,
constrained_indices)
slab = fcc111('Pt', (4, 4, 4))
C1 = FixAtoms([0, 2, 4])
C2 = FixBondLengths([[0, 1], [0, 2]])
C3 = FixInternals(bonds=[[1, [7, 8]], [1, [8, 9]]])
C4 = Hookean(a1=30, a2=40, rt=1.79, k=5.)
slab.set_constraint([C1, C2, C3, C4])
assert all(
constrained_indices(slab, (FixAtoms, FixBondLengths)) == [0, 1, 2, 4])
assert all(constrained_indices(slab) == [0, 1, 2, 4, 7, 8, 9, 30, 40])
def pca_xyz(traj_dict, fig_title=None):
"""Perform a PCA analysis for the trajectories.
Parameters
----------
traj_dict: dict
Dictionary of calculation types and trajectories.
e.g.: {'oal': oal_traj}, where oal_traj is an ASE Trajectory
object or the path to the trajectory.
or {'oal': [path_to_oal_traj, path_to_oal_db]}, where path_to_oal_traj
is the path to the trajectory and path_to_oal_db is the path to the ase Database.
or {'oal': [list_of_atoms]}, where the list of atoms serves as a trajectory to be read
fig_title: str
Title of the PCA plot.
"""
types = []
trajs = []
pos = []
energy = []
for key, value in traj_dict.items():
types.append(key)
if isinstance(value, str):
value = Trajectory(value)
trajs.append(value)
elif type(value) is list and type(value[0]) is Atoms:
trajs.append(value)
elif isinstance(value, list):
traj = Trajectory(value[0])
db = connect(value[1])
dft_call = [i.id - 1 for i in db.select(check=True)]
dft_traj = [traj[i] for i in dft_call]
trajs.append(dft_traj)
else:
trajs.append(value)
# assuming constraints (FixAtom) are applied to the same atoms
constrained_id = constrained_indices(trajs[0][0])
for i in trajs:
all_pos = [j.get_positions() for j in i]
free_atom_pos = [np.delete(i, constrained_id, 0) for i in all_pos]
pos.append([j.get_positions() for j in i])
energy.append([j.get_potential_energy() for j in i])
label = []
for i in range(len(types)):
label += [types[i]] * len(pos[i])
attr = []
for i in range(1, np.shape(pos[0])[1] + 1):
attr.append("%dx" % i)
attr.append("%dy" % i)
attr.append("%dz" % i)
df = []
for i in range(len(pos)):
reshape = np.array(pos[i]).reshape(np.shape(pos[i])[0], np.shape(pos[i])[1] * 3)
df.append(pd.DataFrame(reshape, columns=attr))
df = pd.concat([df[i] for i in range(len(df))], ignore_index=True)
df.insert(len(df.columns), "label", label)
x = df.loc[:, attr].values
x = StandardScaler().fit_transform(x)
pca = PCA(n_components=2)
principalComponents = pca.fit_transform(x)
principalDf = pd.DataFrame(
data=principalComponents,
columns=["principal component 1", "principal component 2"],
)
finalDf = pd.concat([principalDf, df[["label"]]], axis=1)
fig = plt.figure(figsize=(8, 8))
ax = fig.add_subplot(1, 1, 1)
ax.set_xlabel("Principal Component 1", fontsize=15)
ax.set_ylabel("Principal Component 2", fontsize=15)
if fig_title is not None:
ax.set_title(fig_title, fontsize=20)
else:
ax.set_title("Principal Component Analysis", fontsize=20)
targets = types
colors = energy
mark = ["x", "s", "o", "^", "v", "<", ">", "D"]
for target, color, mark in zip(targets, colors, mark):
indicesToKeep = finalDf["label"] == target
# if target == 'oal':
ax.scatter(
finalDf.loc[indicesToKeep, "principal component 1"],
finalDf.loc[indicesToKeep, "principal component 2"],
c=color,
marker=mark,
cmap="viridis",
s=50,
label=target,
)
ax.plot(
finalDf.loc[indicesToKeep, "principal component 1"],
finalDf.loc[indicesToKeep, "principal component 2"],
)
sm = plt.cm.ScalarMappable(cmap="viridis")
colorbar = fig.colorbar(sm)
colorbar.set_label("-log(abs(energy))")
ax.legend()
plt.savefig("pca.png")
bothways=True,
skin=skin_arg)
nl.update(atoms)
adsorbate_atoms = [
index for index, atom in enumerate(atoms)
if atom.symbol not in surface_atoms
]
normals, mask = generate_normals(atoms,
adsorbate_atoms=adsorbate_atoms,
normalize_final=True)
### make sure to manually set the normals for 2-D materials, all atoms should have a normal pointing up, as all atoms are surface atoms
#normals, mask = np.ones((len(atoms), 3)) * (0, 0, 1), list(range(len(atoms)))
constrained = constrained_indices(atoms)
mask = [index for index in mask if index not in constrained]
#for index in mask:
# atoms[index].tag = 1
atoms.set_velocities(normals / 10)
all_sites = []
full_graph, envs = process_atoms(atoms,
nl=nl,
adsorbate_atoms=adsorbate_atoms,
radius=3)
### here the default radii as well as grid are considered, these can also be added as args.
for coord in [1, 2, 3]:
from ase.build import fcc111
from ase.constraints import (FixAtoms, FixBondLengths, FixInternals, Hookean,
constrained_indices)
slab = fcc111('Pt', (4, 4, 4))
C1 = FixAtoms([0, 2, 4])
C2 = FixBondLengths([[0, 1], [0, 2]])
C3 = FixInternals(bonds=[[1, [7, 8]], [1, [8, 9]]])
C4 = Hookean(a1=30, a2=40, rt=1.79, k=5.)
slab.set_constraint([C1, C2, C3, C4])
assert all(constrained_indices(slab, (FixAtoms, FixBondLengths)) ==
[0, 1, 2, 4])
assert all(constrained_indices(slab) == [0, 1, 2, 4, 7, 8, 9, 30, 40])
def main():
arg = sys.argv
paras = readinputs(arg[1])
print paras
boundary_atoms = numpy.array(
[float(field) for field in paras['boundary_atoms'].split()])
#numpy.array([0, 1, 2, 38, 39])
boundary = numpy.array(
[float(field) for field in paras['boundary'].split()])
#([0, 4.407, 0])
strain = numpy.array([float(field) for field in paras['strain'].split()])
strain_direction = paras['strain_direction']
span = float(paras['span'])
active_space = ([field for field in paras['active_space'].split()])
#initialize strain for each direction
dx = numpy.zeros(len(strain))
dy = dx
dz = dx
#set strain
if strain_direction == 'x':
dx = strain
fixed_direction = 1
if strain_direction == 'y':
dy = strain
fixed_direction = 2
if strain_direction == 'z':
dz = strain
fixed_direction = 3
#read geometry
p1 = read(filename=paras['structure_file'], index=0, format='vasp')
fixed_atoms = constrained_indices(p1)
working_dir = os.getcwd()
#move atoms based on the given strain and submit jobs
stretched = open('streched.dat', 'w')
for i in range(0, len(strain)):
p2 = p1.copy()
for atom in p2:
if atom.index in fixed_atoms or atom.symbol not in active_space:
continue
#move atoms at the boundary. Keep the original shape of the boundary
if atom.index in boundary_atoms:
atom.position = atom.position + (span * dx[i], span * dy[i],
span * dz[i])
continue
#move other atoms.
#atom.position = tuple(boundary + (numpy.array(atom.position) - boundary)*numpy.array([1+dx[i],1+dy[i],1+dz[i]]))
if strain[i] < 0:
job_i = working_dir + '/' + 'c_' + str(i)
else:
job_i = working_dir + '/' + str(i)
stretched.write("%4d %12.8f \n" % (i, span * strain[i]))
make_dir(job_i)
write(filename=job_i + '/POSCAR', images=p2, format='vasp')
fix_atoms(filename=job_i + '/POSCAR',
fixed_atoms=boundary_atoms,
fixed_direction=fixed_direction)
os.system('cp POTCAR ' + job_i)
os.system('cp KPOINTS ' + job_i)
os.system('cp INCAR ' + job_i)
os.system('cp ' + paras['job_submit_script'] + ' ' + job_i)
with cd(job_i):
os.system(paras['job_submit_cmd'] + ' ' +
paras['job_submit_script'])
print os.getcwd(), 'is submitted'
print 'Back to directory', os.getcwd()
from ase.build import fcc111
from ase.constraints import (FixAtoms, FixBondLengths, FixLinearTriatomic,
FixInternals, Hookean, constrained_indices)
slab = fcc111('Pt', (4, 4, 4))
C1 = FixAtoms([0, 2, 4])
C2 = FixBondLengths([[0, 1], [0, 2]])
C3 = FixInternals(bonds=[[1, [7, 8]], [1, [8, 9]]])
C4 = Hookean(a1=30, a2=40, rt=1.79, k=5.)
C5 = FixLinearTriatomic(triples=[(0, 1, 2), (3, 4, 5)])
slab.set_constraint([C1, C2, C3, C4, C5])
assert all(
constrained_indices(slab, (FixAtoms, FixBondLengths)) == [0, 1, 2, 4])
assert all(
constrained_indices(slab, (FixBondLengths,
FixLinearTriatomic)) == [0, 1, 2, 3, 4, 5])
assert all(constrained_indices(slab) == [0, 1, 2, 3, 4, 5, 7, 8, 9, 30, 40])