def rotate_atoms(individual, max_natoms=0.20):
"""Randomly rotates a number of random atoms within the individual (in place).
Args:
individual (Individual): an individual
max_natoms (float or int): if float, the maximum number of atoms that will be rotated is max_natoms*len(individual)
if int, the maximum number of atoms that will be rotated is max_natoms
default: 0.20
"""
if len(individual):
if isinstance(max_natoms, float):
max_natoms = int(len(individual)*max_natoms)
max_natoms = max(max_natoms, 1)
natoms_to_rotate = random.randint(1, max_natoms)
atom_indices = list(range(len(individual)))
random.shuffle(atom_indices) # Using random.shuffle on the indices guarantees no duplicates
atom_indices = atom_indices[:natoms_to_rotate]
# Extract out the atoms to be rotated
atom_indices.sort(reverse=True)
atoms = Atoms()
for ind in atom_indices:
atoms.append(individual.pop(ind))
axis = random.choice(['x', '-x', 'y', '-y', 'z', '-z'])
angle = random.uniform(30, 180)
atoms.rotate(axis, a=angle, center='COM', rotate_cell=False)
individual.extend(atoms)
return None
def compareForces():
d = 0.9575
t = np.pi / 180 * 104.51
water = Atoms("H2O", positions=[(d, 0, 0), (d * np.cos(t), d * np.sin(t), 0), (0, 0, 0)], cell=np.eye(3) * 5.0)
water.calc = ElectronicMinimize(atoms=water, log=False)
print(water.get_forces())
print(water.calc.calculate_numerical_forces(water))
def die():
d = 0.9575
t = np.pi / 180 * 104.51
water = Atoms("H2O", positions=[(d, 0, 0), (d * np.cos(t), d * np.sin(t), 0), (0, 0, 0)])
water.calc = ElectronicMinimize(atoms=water, log=True)
dyn = LBFGS(water)
dyn.run(fmax=0.05)
def adjust_positions(self, atoms: Atoms, newpositions):
"""
:param atoms: structure to be adjusted
:param newpositions: positions from dft code
:return:
"""
# get Normal Vector
atoms.wrap(atoms.get_scaled_positions()[self.diffusing_i])
p1 = newpositions[self.plane_i[0]] # type: np.array
p2 = newpositions[self.plane_i[1]] # type: np.array
p3 = newpositions[self.plane_i[2]] # type: np.array
v1 = p2 - p1
v2 = p3 - p1
# Get equation of plane ax+by+cz+d = 0
normal = np.cross(v1, v2) / np.linalg.norm(np.cross(v1,v2))
d = np.dot(normal, p1)
a=normal[0]
b=normal[1]
c=normal[2]
# Get closest point on plane
p = newpositions[self.diffusing_i]
k = (a*p[0] + b*p[1] + c*p[2] - d) / (a**2 + b**2 + c**2) # distance between point and plane
position = [p[0] - k*a, p[1] - k*b, p[2] - k*c]
newpositions[self.diffusing_i] = position
def test_s22():
fragTest = Fragmentation(s22.s22)
minimize = False
#minimize = True
print 'Relaxed:', minimize
fragTest.molecules = []
fragTest.fragments = []
for moleculeName in s22.s22:
data = s22.data[moleculeName]
atoms = Atoms(data['symbols'], data['positions'])
dimer1End = data['dimer atoms'][0]
frag1Atoms = atoms.copy()[:dimer1End]
frag2Atoms = atoms.copy()[dimer1End:]
fragment1 = ReaxFFSystem(moleculeName + '_f1', frag1Atoms, minimize = minimize)
fragment2 = ReaxFFSystem(moleculeName + '_f2', frag2Atoms, minimize = minimize)
system = ReaxFFSystem(moleculeName, atoms, minimize = minimize,
fragment_list = [fragment1.name, fragment2.name])
fragTest.molecules.append(system)
fragTest.fragments += [fragment1, fragment2]
fragTest.fill_data_reference(data_type='s22')
fragTest.run(write=True)
def testSingle(molecule):
#TEST fragmentation
print "Test fragmentation with s22 set"
fragment_names = [molecule+'_f1',molecule+'_f2']
test_f = Fragmentation([molecule])
minimize = False
#minimize = True
print 'Relaxed:', minimize
sys = Atoms(s22_sim_data[molecule]['symbols'],
s22_sim_data[molecule]['positions'])
test_f.molecules = [ReaxFFSystem(molecule,atoms=sys,
fragment_list=fragment_names, minimize=minimize)]
n = s22_sim_data[molecule]['dimer atoms']
atom_fragments = [ sys.copy()[range(n[0])], sys.copy()[range(n[0],n[0]+n[1])] ]
test_f.fragments = [ ReaxFFSystem(name,atoms=a, minimize = minimize)
for name,a in zip(fragment_names,atom_fragments)]
test_f.fill_data_reference(data_type='s22')
test_f.run(write=True)
print test_f.data
def extract_calc(inp_file):
"""Constructs an ase atoms object with an attached Gaussian calculator from a gaussian input file
assumes the input file has format Route.... \n\nTitle...\n\ncoord_sect...\n\nconnect_sect"""
with open(inp_file, 'r') as fl:
data = fl.read()
section_names = ['route', 'title', 'coords', 'connects']
sections = data.split('\n\n')
no_sections = len(sections)
data_dict = dict(zip(section_names[:no_sections], sections))
label = data_dict.get('title')
route = data_dict.get('route')
coords = data_dict.get('coords')
#connects = data_dict.get('connects')
if coords:
charge, mult = coords.split('\n')[0].split()
coords = '\n'.join(coords.split('\n')[1:])
atoms = Atoms()
if coords:
for line in coords.split('\n'):
info = line.split()
is_bq = re.match('bq', info[0], re.I)
# H -> H, H(ISO=2) -> H
symbol = info[0].split('(')[0]
position = [float(info[1]), float(info[2]), float(info[3])]
#ignoring ghost atoms
if not is_bq:
atoms += Atom(symbol.split('(')[0], position=position)
if not label:
label = 'Default Gaussian Label'
route_args = route.split()[1:]
if 'oniom' in route_args[0]:
method = route_args[0]
basis = 'oniom'
route_args = route_args[1:]
else:
method, basis = route_args[0:2]
route_args = route_args[2:]
route_kwargs = {'method':method, 'basis':basis}
for route_arg in route_args:
if re.match('IOP', route_arg, re.I):
route_kwargs.update({'ioplist': route_arg[4:-1].split(',')})
elif '=' in route_arg:
route_arg_nm, route_arg_vl = route_arg.split('=')
route_kwargs.update({route_arg_nm: route_arg_vl})
else:
route_kwargs.update({route_arg:route_arg})
atoms.set_calculator(Gaussian(label=label, multiplicity=mult, **route_kwargs))
return atoms
def bcc100(symbol, a, layers, L):
"""Build a bcc(100) surface
symbol: chemical symbol ('H', 'Li', ...)
a : lattice constant
layers: number of layers
L : height of unit cell"""
a = float(a)
# Distance between layers:
z = a / 2
assert L > layers * z, 'Unit cell too small!'
# Start with an empty Atoms object with an orthorhombic unit cell:
atoms = Atoms(pbc=(True, True, False), cell=(a, a, L))
# Fill in the atoms:
for n in range(layers):
position = [a / 2 * (n % 2), a / 2 * (n % 2), n * z]
atoms.append(Atom(symbol, position))
atoms.center(axis=2)
return atoms
def structure(self): latysmall,latExtend,latxsmall,latxbig,bond=[int(self.latysmall),int(self.latExtend),int(self.latxsmall),int(self.latxbig),float(self.bond)] if(latxsmall%2==0):latxsmall+=1; if(latxbig%2==1):latxbig+=1; atoms=self.agnr(latysmall,latxsmall+1,0); unit=self.agnr(latysmall-1+2*latExtend,latxbig,0) unit.translate([latxsmall*1.5,-(latExtend-0.5)*sqrt(3),0]) atoms.extend(unit) unit=self.agnr(latysmall,latxsmall+1,0); unit.translate([(latxsmall+latxbig-1)*1.5,0,0]) atoms.extend(unit) temp=Atoms() for i in range(self.seg): unit=atoms.copy() unit.translate([(latxsmall+latxbig-1)*1.5*i,0,0]) temp.extend(unit) atoms.extend(temp) atoms=get_unique_atoms(atoms) lx,ly=self.extent(atoms) atoms.set_cell([lx,ly,100]) atoms.set_cell([lx*bond,ly*bond,100],scale_atoms=True) atoms.set_pbc([1,1,1]) atoms.center(vacuum=10*bond) self.atoms=atoms self.write() print 'read_data structure'
def testSingle(moleculeName = "Methane_dimer"):
#TEST fragmentation
print "Test fragmentation with s22 set"
minimize = False
minimize = True
print 'Relaxed:', minimize
fragTest = Fragmentation([moleculeName])
#atoms = s22.create_s22_system(moleculeName)
data = s22.data[moleculeName]
atoms = Atoms(data['symbols'], data['positions'])
dimer1End = s22.data[moleculeName]['dimer atoms'][0]
frag1Atoms = atoms.copy()[:dimer1End]
frag2Atoms = atoms.copy()[dimer1End:]
calculate_charges(frag1Atoms)
calculate_charges(frag2Atoms)
atoms.set_charges(np.append(frag1Atoms.get_charges(), frag2Atoms.get_charges()))
fragment1 = CHARMMSystem(moleculeName + '_f1', frag1Atoms, minimize = minimize)
fragment2 = CHARMMSystem(moleculeName + '_f2', frag2Atoms, minimize = minimize)
system = CHARMMSystem(moleculeName, atoms, minimize = minimize,
fragment_list = [fragment1.name, fragment2.name])
fragTest.molecules = [system]
fragTest.fragments = [fragment1, fragment2]
fragTest.fill_data_reference(data_type='s22')
fragTest.run(write=True)
import ase.io
ase.io.write('molecule.xyz', atoms)
print fragTest.data
def initialize_subsystem(self, info):
"""Initializes a SubsystemInternal from the given Subsystem.
Parameters:
info: SubSystem
"""
name = info.name
real_indices = self.generate_subsystem_indices(name)
# Create a copy of the subsystem
temp_atoms = Atoms()
index_map = {}
reverse_index_map = {}
counter = 0
for index in real_indices:
atom = self.atoms[index]
temp_atoms.append(atom)
index_map[index] = counter
reverse_index_map[counter] = index
counter += 1
atoms = temp_atoms.copy()
atoms.set_pbc(self.atoms.get_pbc())
atoms.set_cell(self.atoms.get_cell())
# Create the SubSystem
subsystem = SubSystemInternal(
atoms,
info,
index_map,
reverse_index_map,
len(self.atoms))
self.subsystems[name] = subsystem
def CCP_Oct_Tet(ind1, ind2, Optimizer):
"""CX Function underdevelopment for preferentially exchanging octahedral and tetrahedral defect sites
Non-Functional
"""
if 'CX' in Optimizer.debug:
debug = True
else:
debug = False
uc = numpy.maximum.reduce(Optimizer.solidbulk.get_cell()/Optimizer.supercell)[0]
interstitials = [[0.0,0.5,0.0],[0.5,0.0,0.0],[0.0,0.0,0.5],[0.5,0.5,0.5],
[0.25,0.25,0.25],[0.25,0.75,0.25],[0.75,0.25,0.25],[0.75,0.75,0.25],
[0.25,0.25,0.75],[0.25,0.75,0.75],[0.75,0.25,0.75],[0.75,0.75,0.75]]
sites=[]
for one in interstitials:
pos = [uc*p for p in one]
npos = [0,0,0]
for i in range(Optimizer.supercell[0]):
npos[0]=pos[0]+i*uc
for j in range(Optimizer.supercell[1]):
npos[1]=pos[1]+j*uc
for k in range(Optimizer.supercell[2]):
npos[2]=pos[2]+k*uc
sites.append(copy.copy(npos))
solidsites = Atoms()
for one in sites:
solidsites.append(Atom(position=one))
return ind1, ind2
def test_axis_layout():
system = Atoms('H')
a = 3.
system.cell = (a, a, a)
system.pbc = 1
for axis in range(3):
system.center()
system.positions[0, axis] = 0.0
calc = Octopus(**getkwargs(label='ink-%s' % 'xyz'[axis],
Output='density + potential + wfs'))
system.set_calculator(calc)
system.get_potential_energy()
rho = calc.get_pseudo_density(pad=False)
#for dim in rho.shape:
# assert dim % 2 == 1, rho.shape
maxpoint = np.unravel_index(rho.argmax(), rho.shape)
print('axis=%d: %s/%s' % (axis, maxpoint, rho.shape))
expected_max = [dim // 2 for dim in rho.shape]
expected_max[axis] = 0
assert maxpoint == tuple(expected_max), '%s vs %s' % (maxpoint,
expected_max)
errs = check_interface(calc)
for err in errs:
if err.code == 'not implemented':
continue
if err.methname == 'get_dipole_moment':
assert isinstance(err.error, OctopusIOError)
else:
raise AssertionError(err.error)
def build_sheet(nx, nz, symmetry=0):
nx=nx+1
nz=(nz+1)/2
basic_cell= Atoms('C4',
positions=[[3.11488, 2.50000, 0.71000],
[4.34463, 2.50000, 1.42000],
[4.34463, 2.50000, 2.84000],
[3.11488, 2.50000, 3.55000]],
cell=[[2.45951, 0, 0],
[0, 1, 0],
[0, 0, 4.26]])
atoms=basic_cell.repeat((nx,1,nz))
atoms.pop(basic_cell.get_number_of_atoms()*nz-1)
atoms.pop(0)
if symmetry == 1:
print "Making graphene sheet symmetric"
global to_be_removed
to_be_removed = []
sym_fix_int = nz-1
for i in xrange(2, nz+sym_fix_int, 2):
to_be_removed.append(2*i-2)
to_be_removed.append(2*i-1)
to_be_removed = to_be_removed[::-1]
for entry in to_be_removed:
atoms.pop(entry)
else:
print "Molecule was not made symmetric"
return atoms
def get_OH(rotate=0):
height = 1.8
atoms = Atoms([Atom('O', (-0.15, 0, 0), magmom=0),
Atom('H', (0.655, 0, 0.564), magmom=0)])
rad = rotate * pi/180
atoms.rotate('z', rad)
return atoms, height
def lmp_structure(self):
pos=np.array([
[ 0.0000000000000000, 0.0000000000000000, 0.0000000000000000],
[ 0.0000000000000000, 0.5000000000000000, 0.5000000000000000],
[ 0.5000000000000000, 0.0000000000000000, 0.5000000000000000],
[ 0.5000000000000000, 0.5000000000000000, 0.0000000000000000],
[ 0.5000000000000000, 0.5000000000000000, 0.5000000000000000],
[ 0.5000000000000000, 0.0000000000000000, 0.0000000000000000],
[ 0.0000000000000000, 0.5000000000000000, 0.0000000000000000],
[ 0.0000000000000000, 0.0000000000000000, 0.5000000000000000]
])
if self.modulation:
pos=np.array([
[ 0.0028042995364173 , 0.9974037352530641 , 0.0077352314347739],
[ 0.9976620421445513 , 0.4989145351814259 , 0.5063342423839297],
[ 0.4945930839448565 , 0.9984163204751321 , 0.5059643310587607],
[ 0.5058732577361121 , 0.4969055205467704 , 0.0045633420079164],
[ 0.5023379578554488 , 0.5015836795248679 , 0.4954366579920836],
[ 0.4971957004635827 , 0.0030944794532296 , 0.9940356689412393],
[ 0.9941267422638879 , 0.5025962647469360 , 0.9936657576160703],
[ 0.0054069160551436 , 0.0010854648185742 , 0.4922647685652261]
])
cell=4.8874939611242816*np.eye(3)
atoms = Atoms('P8',scaled_positions=pos, cell=cell)
atoms=atoms.repeat([self.latx,self.laty,self.latz])
atoms.set_pbc([self.xp,self.yp,self.zp])
return atoms
def get_OOH(rotate=0):
height = 1.8
atoms = Atoms([Atom('O', (-0.433, 0 , 0), magmom=0),
Atom('O', (0.648, 0, 0.964), magmom=0),
Atom('H', (0.112, 0, 1.79), magmom=0)])
rad = rotate * pi/180
atoms.rotate('z', rad)
return atoms, height
def __delitem__(self, i):
Atoms.__delitem__(self, i)
#Subtract one from all neighbor references that is greater than "index"
if self.has('neighbors'):
neighbors = self.get_neighbors()
neighbors = neighbors - (neighbors > i).astype(int)
self.set_neighbors(neighbors)
def create_random_atoms(gd, nmolecules=10, name='NH2', mindist=4.5 / Bohr):
"""Create gas-like collection of atoms from randomly placed molecules.
Applies rigid motions to molecules, translating the COM and/or rotating
by a given angle around an axis of rotation through the new COM. These
atomic positions obey the minimum distance requirement to zero-boundaries.
Warning: This is only intended for testing parallel grid/LFC consistency.
"""
atoms = Atoms(cell=gd.cell_cv * Bohr, pbc=gd.pbc_c)
# Store the original state of the random number generator
randstate = np.random.get_state()
seed = np.array([md5_array(data, numeric=True)
for data in
[nmolecules, gd.cell_cv, gd.pbc_c, gd.N_c]]).astype(int)
np.random.seed(seed % 4294967296)
for m in range(nmolecules):
amol = molecule(name)
amol.set_cell(gd.cell_cv * Bohr)
# Rotate the molecule around COM according to three random angles
# The rotation axis is given by spherical angles phi and theta
v,phi,theta = np.random.uniform(0.0, 2*np.pi, 3) # theta [0,pi[ really
axis = np.array([cos(phi)*sin(theta), sin(phi)*sin(theta), cos(theta)])
amol.rotate(axis, v)
# Find the scaled length we must transverse along the given axes such
# that the resulting displacement vector is `mindist` from the cell
# face corresponding to that direction (plane with unit normal n_v).
sdist_c = np.empty(3)
if not gd.orthogonal:
for c in range(3):
n_v = gd.xxxiucell_cv[c] / np.linalg.norm(gd.xxxiucell_cv[c])
sdist_c[c] = mindist / np.dot(gd.cell_cv[c], n_v)
else:
sdist_c[:] = mindist / gd.cell_cv.diagonal()
assert np.all(sdist_c > 0), 'Displacment vectors must be inside cell.'
# Scaled dimensions of the smallest possible box centered on the COM
spos_ac = amol.get_scaled_positions() # NB! must not do a "% 1.0"
scom_c = np.dot(gd.icell_cv, amol.get_center_of_mass())
sbox_c = np.abs(spos_ac-scom_c[np.newaxis,:]).max(axis=0)
sdelta_c = (1-np.array(gd.pbc_c)) * (sbox_c + sdist_c)
assert (sdelta_c < 1.0-sdelta_c).all(), 'Box is too tight to fit atoms.'
scenter_c = [np.random.uniform(d,1-d) for d in sdelta_c]
center_v = np.dot(scenter_c, gd.cell_cv)
# Translate the molecule such that COM is located at random center
offset_av = (center_v-amol.get_center_of_mass()/Bohr)[np.newaxis,:]
amol.set_positions(amol.get_positions()+offset_av*Bohr)
assert np.linalg.norm(center_v-amol.get_center_of_mass()/Bohr) < 1e-9
atoms.extend(amol)
# Restore the original state of the random number generator
np.random.set_state(randstate)
assert compare_atoms(atoms)
return atoms
def read_vasp_xdatcar(filename, index=-1):
"""Import XDATCAR file
Reads all positions from the XDATCAR and returns a list of
Atoms objects. Useful for viewing optimizations runs
from VASP5.x
Constraints ARE NOT stored in the XDATCAR, and as such, Atoms
objects retrieved from the XDATCAR will not have constraints set.
"""
import numpy as np
from ase import Atoms
images = list()
with open(filename, 'r') as xdatcar:
xdatcar.readline()
xdatcar.readline()
xx = [float(x) for x in xdatcar.readline().split()]
yy = [float(y) for y in xdatcar.readline().split()]
zz = [float(z) for z in xdatcar.readline().split()]
cell = np.array([xx, yy, zz])
symbols = xdatcar.readline().split()
numbers = [int(n) for n in xdatcar.readline().split()]
total = sum(numbers)
atomic_formula = str()
for n, sym in enumerate(symbols):
atomic_formula += '%s%s' % (sym, numbers[n])
count = 0
nimage = 0
coords = list()
for line in xdatcar:
if 'Direct configuration=' in line:
nimage += 1
else:
coord = [float(x) for x in line.split()]
coords.append(coord)
count += 1
if count == total:
image = Atoms(atomic_formula, cell=cell, pbc=True)
image.set_scaled_positions(coords)
images.append(image)
count = 0
coords = list()
if not index:
return images
else:
return images[index]
def build_system(self, name):
if name in extra:
mol = Atoms(*extra[name])
mol.cell = self.unit_cell
mol.center()
else:
self.bond_length = bondlengths.get(name, None)
mol = MoleculeTask.build_system(self, name)
return mol
def zhexian(self,n,p,type):
m=n*2+1;
atoms=Atoms()
for i in range(m):
y=i*sqrt(3)/2
x=0.5*(1+(type*2-1)*(i%2)-type)+p*1.5
atoms.append(Atom('C',(x,y,0.0)))
return atoms
def read_from_pickle(file, ts_est, geo_dict):
from pts.tools.pathtools import unpickle_path, PathTools
from ase import Atoms
from ase.io import write
from pts.ui.read_COS import set_atoms
from pts.searcher import new_abscissa
from numpy import savetxt
coord_b, energy_b, gradients_b, __, __, symbols, funcart = unpickle_path(file) # v2
mt.setup_metric(funcart)
startx = new_abscissa(coord_b, mt.metric)
pt2 = PathTools(coord_b, energy_b, gradients_b, startx)
if ts_est == "spline":
ts_int = pt2.ts_spl()
if len(ts_int) == 0:
print >> stderr, "Transition state estimate did not provide any results"
print >> stderr, "Aborting!"
exit()
est = ts_int[-1]
elif ts_est == "spl_avg":
ts_int = pt2.ts_splavg()
if len(ts_int) == 0:
print >> stderr, "Transition state estimate did not provide any results"
print >> stderr, "Aborting!"
exit()
est = ts_int[-1]
elif ts_est == "cubic":
ts_int = pt2.ts_splcub()
if len(ts_int) == 0:
print >> stderr, "Transition state estimate did not provide any results"
print >> stderr, "Aborting!"
exit()
est = ts_int[-1]
elif ts_est == "highest":
est = pt2.ts_highest()[-1]
elif ts_est == "bell":
ts_int = pt2.ts_bell()
if len(ts_int) == 0:
print >> stderr, "Transition state estimate did not provide any results"
print >> stderr, "Aborting!"
exit()
est = ts_int[-1]
else:
print >> stderr, "Transition state estimate not found", ts_est
print >> stderr, "Make sure that the name is written correctly"
exit()
energy, start_geo, __, __,s_ts, __, __ = est
init_mode = pt2.xs.fprime(s_ts)
atoms = Atoms(symbols)
atoms.set_positions(funcart(start_geo))
atoms = set_atoms(atoms, geo_dict)
write("start.xyz", atoms)
savetxt("mode.start", init_mode)
return start_geo, init_mode, funcart, atoms
def adjust_positions(self, atoms : Atoms, newpositions):
# get plane
atoms.wrap(atoms.get_scaled_positions()[self.diffusing_i])
(a, b, c, d) = self.get_plane(atoms) # ax + by + cz = d
# Get closest point on plane
p = atoms.positions[self.diffusing_i]
k = (a*p[0] + b*p[1] + c*p[2] - d) / (a**2 + b**2 + c**2) # distance between point and plane
position = [p[0] - k*a, p[1] - k*b, p[2] - k*c]
newpositions[self.diffusing_i] = position
def atomsfromlist(atomslist):
"""Takes in a list of atomic symbols and coordinates, as in
[atom1, atom2, ...] where atomX = (symbol, (x,y,z)), and symbol is the
atomic symbol (e.g. "Na") and x,y,z is the position, in Angstroms, of
the atom. Returns an ASE atoms object."""
atoms = Atoms()
for atom in atomslist:
atoms.append(Atom(atom[0], atom[1]))
return atoms
def mutate(self, atoms):
""" Does the actual mutation. """
tbm = random.choice(range(len(atoms)))
indi = Atoms()
for a in atoms:
if a.index == tbm:
a.position += self.random_vector(self.length)
indi.append(a)
return indi
def lmp_structure(self): ribbon=graphene(dict(latx=self.latx,laty=self.laty,latz=1,gnrtype=self.gnrtype)).lmp_structure() for atom in ribbon: atom.position=self.trans(atom.position) atoms=Atoms() atoms.extend(ribbon) atoms.center(vacuum=10) return atoms
def color(gui):
a = Atoms('C10', magmoms=np.linspace(1, -1, 10))
a.positions[:] = np.linspace(0, 9, 10)[:, None]
a.calc = SinglePointCalculator(a, forces=a.positions)
gui.new_atoms(a)
c = gui.colors_window()
c.toggle('force')
text = c.toggle('magmom')
assert [button.active for button in c.radio.buttons] == [1, 0, 1, 0, 0, 1]
assert text.rsplit('[', 1)[1].startswith('-1.000000,1.000000]')
def get_density(self, atom_indicees=None, gridrefinement=2):
"""Get sum of atomic densities from the given atom list.
All atoms are taken if the list is not given."""
all_atoms = self.calculator.get_atoms()
if atom_indicees is None:
atom_indicees = range(len(all_atoms))
density = self.calculator.density
spos_ac = all_atoms.get_scaled_positions()
rank_a = self.finegd.get_ranks_from_positions(spos_ac)
density.set_positions(all_atoms.get_scaled_positions(),
rank_a
)
# select atoms
atoms = []
D_asp = {}
rank_a = []
all_D_asp = self.calculator.density.D_asp
all_rank_a = self.calculator.density.rank_a
for a in atom_indicees:
if a in all_D_asp:
D_asp[len(atoms)] = all_D_asp.get(a)
atoms.append(all_atoms[a])
rank_a.append(all_rank_a[a])
atoms = Atoms(atoms,
cell=all_atoms.get_cell(), pbc=all_atoms.get_pbc())
spos_ac = atoms.get_scaled_positions()
Z_a = atoms.get_atomic_numbers()
par = self.calculator.input_parameters
setups = Setups(Z_a, par.setups, par.basis, par.lmax,
XC(par.xc),
self.calculator.wfs.world)
self.D_asp = D_asp
# initialize
self.initialize(setups,
self.calculator.timer,
np.zeros((len(atoms), 3)), False)
self.set_mixer(None)
# FIXME nparray causes partitionong.py test to fail
self.set_positions(spos_ac, np.array(rank_a))
basis_functions = BasisFunctions(self.gd,
[setup.phit_j
for setup in self.setups],
cut=True)
basis_functions.set_positions(spos_ac)
self.initialize_from_atomic_densities(basis_functions)
aed_sg, gd = self.get_all_electron_density(atoms,
gridrefinement)
return aed_sg[0], gd
def read_vasp_xdatcar(filename, index=-1):
"""Import XDATCAR file
Reads all positions from the XDATCAR and returns a list of
Atoms objects. Useful for viewing optimizations runs
from VASP5.x
Constraints ARE NOT stored in the XDATCAR, and as such, Atoms
objects retrieved from the XDATCAR will not have constraints set.
"""
import numpy as np
from ase import Atoms
images = list()
cell = np.eye(3)
atomic_formula = str()
with open(filename, 'r') as xdatcar:
while True:
comment_line = xdatcar.readline()
if "Direct configuration=" not in comment_line:
try:
lattice_constant = float(xdatcar.readline())
except:
break
xx = [float(x) for x in xdatcar.readline().split()]
yy = [float(y) for y in xdatcar.readline().split()]
zz = [float(z) for z in xdatcar.readline().split()]
cell = np.array([xx, yy, zz]) * lattice_constant
symbols = xdatcar.readline().split()
numbers = [int(n) for n in xdatcar.readline().split()]
total = sum(numbers)
atomic_formula = str()
for n, sym in enumerate(symbols):
atomic_formula += '%s%s' % (sym, numbers[n])
xdatcar.readline()
coords = [np.array(xdatcar.readline().split(), np.float)
for ii in range(total)]
image = Atoms(atomic_formula, cell=cell, pbc=True)
image.set_scaled_positions(np.array(coords))
images.append(image)
if not index:
return images
else:
return images[index]
from ase import Atoms
from ase.calculators.emt import EMT
from ase.calculators.test import numeric_forces
h2 = Atoms('H2', positions=[(0, 0, 0), (0, 0, 1.1)], calculator=EMT())
f1 = numeric_forces(h2, d=0.0001)
f2 = h2.get_forces()
assert abs(f1 - f2).max() < 1e-6
assert (f1 == h2.calc.calculate_numerical_forces(h2, 0.0001)).all()
def co(netCDF4):
return Atoms(
[Atom('C', (0, 0, 0)), Atom('O', (0, 0, 1.2))],
cell=[3, 3, 3],
pbc=True)
#===============================================================================
# Creating Cu (111) surface with 4 layers 2x2 supercell in orthogonal cell
# through Atomic Simulation Envirnoment https://wiki.fysik.dtu.dk/ase/ build.
# Total amount of vacuum between the slabs is 10 Ang. CO molecule is added
# on-top of one of the top-most copper atoms.Later the atoms are ordered, so
# the top-most goes as first. Finally the two bottom layers of the slab are
# constrained, so they cannot relax.
slab = fcc111('Cu',
size=(2, 2, 4),
a=3.62,
vacuum=5,
orthogonal=True,
periodic=True)
CO = Atoms('CO',
positions=[
slab.positions[-1] + [0, 0, 1.85],
slab.positions[-1] + [0, 0, 3.00]
])
slab += CO
slab = slab[np.argsort(-1 * slab.positions[:, 2])]
mask = [atom.tag > 2 for atom in slab]
slab.set_constraint(FixAtoms(mask=mask))
#===============================================================================
# If you want to directly visualize the created slab uncomment following lines:
#from ase.visualize import view
#view(slab)
#===============================================================================
# If you want to print important information about the created slab uncomment
# following lines:
OPTIONS = np.linspace(0.98, 1.02, 9)
volumes = []
energies = []
cr = 0.15
ni = 0.15
fe = 1.0 - cr - ni
for opt in OPTIONS:
l = 3.602 * opt
atoms = Atoms('Fe4',
scaled_positions=[(0, 0, 0), (0.5, 0.5, 0), (0.5, 0, 0.5),
(0, 0.5, 0.5)],
cell=[l, l, l],
pbc=(1, 1, 1))
atoms.set_tags([1, 1, 1, 1])
# view(atoms)
atoms = atoms + Atom('C', position=(0, 0, 0.5 * l), tag=2)
alloys = []
alloys.append(Alloy(1, 'Fe', 0.5, 1.0))
alloys.append(Alloy(1, 'Fe', 0.5, -1.0))
alloys.append(Alloy(2, 'N', 1.0, 0.0))
calc = EMTO()
import numpy as np
from ase import Atoms, Atom
from ase.parallel import barrier, rank, size
from gpaw.cluster import Cluster
from gpaw.test import equal
from ase.data.molecules import molecule
from math import pi, sqrt
R = 2.0
CO = Atoms([Atom('C', (1, 0, 0)), Atom('O', (1, 0, R))])
CO.rotate('y', pi/2)
equal(CO.positions[1, 0], R, 1e-10)
# translate
CO.translate(-CO.get_center_of_mass())
p = CO.positions.copy()
for i in range(2):
equal(p[i, 1], 0, 1e-10)
equal(p[i, 2], 0, 1e-10)
# rotate the nuclear axis to the direction (1,1,1)
CO.rotate(p[1] - p[0], (1, 1, 1))
q = CO.positions.copy()
for c in range(3):
equal(q[0, c], p[0, 0] / sqrt(3), 1e-10)
equal(q[1, c], p[1, 0] / sqrt(3), 1e-10)
# minimal box
b=4.0
import os
from ase import Atoms
from ase.io import read, write
from ase.calculators.exciting import Exciting
from ase.units import Bohr, Hartree
a = Atoms('N3O', [(0, 0, 0), (1, 0, 0), (0, 0, 1), (0.5, 0.5, 0.5)], pbc=True)
write('geo.exi', a)
b = read('geo.exi')
print a
print a.get_positions()
print b
print b.get_positions()
calculator = Exciting(
dir='excitingtestfiles',
kpts=(4, 4, 3),
maxscl=3,
#bin='/fshome/chm/git/exciting/bin/excitingser'
)
def test_external_force():
"""Tests for class ExternalForce in ase/constraints.py"""
f_ext = 0.2
atom1 = 0
atom2 = 1
atom3 = 2
atoms = Atoms('H3', positions=[(0, 0, 0), (0.751, 0, 0), (0, 1., 0)])
atoms.calc = EMT()
# Without external force
optimize(atoms)
dist1 = atoms.get_distance(atom1, atom2)
# With external force
con1 = ExternalForce(atom1, atom2, f_ext)
atoms.set_constraint(con1)
optimize(atoms)
dist2 = atoms.get_distance(atom1, atom2)
# Distance should increase due to the external force
assert dist2 > dist1
# Combine ExternalForce with FixBondLength
# Fix the bond on which the force acts
con2 = FixBondLength(atom1, atom2)
# ExternalForce constraint at the beginning of the list!!!
atoms.set_constraint([con1, con2])
optimize(atoms)
f_con = con2.constraint_forces
# It was already optimized with this external force, therefore
# the constraint force should be almost zero
assert norm(f_con[0]) <= fmax
# To get the complete constraint force (with external force),
# use only the FixBondLength constraint, after the optimization with
# ExternalForce
atoms.set_constraint(con2)
optimize(atoms)
f_con = con2.constraint_forces[0]
assert round(norm(f_con), 2) == round(abs(f_ext), 2)
# Fix another bond and incrase the external force
f_ext *= 2
con1 = ExternalForce(atom1, atom2, f_ext)
d1 = atoms.get_distance(atom1, atom3)
con2 = FixBondLength(atom1, atom3)
# ExternalForce constraint at the beginning of the list!!!
atoms.set_constraint([con1, con2])
optimize(atoms)
d2 = atoms.get_distance(atom1, atom3)
# Fixed distance should not change
assert round(d1, 5) == round(d2, 5)
from gpaw.xas import * #XAS, RecursionMethod
import numpy as np
from gpaw import setup_paths
#setup_paths.insert(0, '.')
# Generate setup for oxygen with half a core-hole:
gen('Si', name='hch1s', corehole=(1, 0, 0.5))
a = 5.43095
b = a / 2
c = b / 2
d = b + c
si_nonortho = Atoms(
[Atom('Si',
(0, 0, 0)), Atom('Si', (a / 4, a / 4, a / 4))],
cell=[(a / 2, a / 2, 0), (a / 2, 0, a / 2), (0, a / 2, a / 2)],
pbc=True)
# calculation with full symmetry
calc = GPAW(nbands=-10,
h=0.25,
kpts=(2, 2, 2),
occupations=FermiDirac(width=0.05),
setups={0: 'hch1s'})
si_nonortho.set_calculator(calc)
e = si_nonortho.get_potential_energy()
niter = calc.get_number_of_iterations()
calc.write('si_nonortho_xas_sym.gpw')
Power12Potential, LinearDielectric, KB51Volume,
GradientSurface, VolumeInteraction,
SurfaceInteraction, LeakedDensityInteraction)
import numpy as np
SKIP_ENERGY_CALCULATION = True
F_max_err = 0.005
h = 0.2
u0 = 0.180
epsinf = 80.
T = 298.15
atomic_radii = lambda atoms: [vdw_radii[n] for n in atoms.numbers]
atoms = Atoms('NaCl', positions=((5.6, 5.6, 6.8), (5.6, 5.6, 8.8)))
atoms.set_cell((11.2, 11.2, 14.4))
atoms.calc = SolvationGPAW(
mixer=Mixer(0.5, 7, 50.0),
xc='oldPBE',
h=h,
setups={'Na': '1'},
cavity=EffectivePotentialCavity(effective_potential=Power12Potential(
atomic_radii, u0),
temperature=T,
volume_calculator=KB51Volume(),
surface_calculator=GradientSurface()),
dielectric=LinearDielectric(epsinf=epsinf),
# parameters chosen to give ~ 1eV for each interaction
interactions=[
def make_system_at_shift(global_prefix,
subdir,
db,
syms,
c_sep,
vacuum_dist,
AB_stacking,
interlayer_relax,
soc,
xc,
pp,
Ds,
extra_bands_factor,
layer_shifts=None):
latvecs, at_syms, cartpos = make_cell(db, syms, c_sep, vacuum_dist,
AB_stacking, layer_shifts)
system = Atoms(symbols=at_syms, positions=cartpos, cell=latvecs, pbc=True)
system.center(axis=2)
wann_valence, num_wann = get_wann_valence(system.get_chemical_symbols(),
soc)
num_bands = get_num_bands(num_wann, extra_bands_factor)
prefixes = []
for D in Ds:
qe_config = make_qe_config(system, D, interlayer_relax, soc, num_bands,
xc, pp)
if D is None:
D_str = "0.0000"
else:
D_str = "{:.4f}".format(D)
if layer_shifts is not None:
da2, db2 = layer_shifts[1]
prefix = "{}_D_{}_da2_{:.4f}_db2_{:.4f}".format(
global_prefix, D_str, da2, db2)
else:
prefix = "{}_{}".format(global_prefix, D_str)
prefixes.append(prefix)
work = _get_work(subdir, prefix)
wannier_dir = os.path.join(work, "wannier")
if not os.path.exists(wannier_dir):
os.makedirs(wannier_dir)
bands_dir = os.path.join(work, "bands")
if not os.path.exists(bands_dir):
os.makedirs(bands_dir)
dirs = {
'relax': wannier_dir,
'scf': wannier_dir,
'nscf': wannier_dir,
'bands': bands_dir
}
qe_input = {}
if interlayer_relax:
calc_types = ['relax', 'scf', 'nscf', 'bands']
else:
calc_types = ['scf', 'nscf', 'bands']
for calc_type in calc_types:
# Turn off SOC for relaxation.
if calc_type == 'relax':
relax_soc = False
qe_config_no_soc = make_qe_config(system, D, interlayer_relax,
relax_soc, num_bands, xc, pp)
qe_input[calc_type] = build_qe(system, prefix, calc_type,
qe_config_no_soc)
else:
qe_input[calc_type] = build_qe(system, prefix, calc_type,
qe_config)
_write_qe_input(prefix, dirs[calc_type], qe_input, calc_type)
pw2wan_input = build_pw2wan(prefix, soc)
pw2wan_path = os.path.join(wannier_dir, "{}.pw2wan.in".format(prefix))
with open(pw2wan_path, 'w') as fp:
fp.write(pw2wan_input)
bands_post_input = build_bands(prefix)
bands_post_path = os.path.join(bands_dir,
"{}.bands_post.in".format(prefix))
with open(bands_post_path, 'w') as fp:
fp.write(bands_post_input)
wannier_input = Winfile(system, qe_config, wann_valence, num_wann)
win_path = os.path.join(wannier_dir, "{}.win".format(prefix))
with open(win_path, 'w') as fp:
fp.write(wannier_input)
return prefixes
from ase import Atoms, Atom
import numpy as np
from gpaw import GPAW, FermiDirac
from gpaw.test import equal
h = .4
q = 3
spin = True
s = Atoms([Atom('Fe')])
s.center(vacuum=2.5)
convergence = {'eigenstates': 0.01, 'density': 0.1, 'energy': 0.1}
# use Hunds rules
c = GPAW(charge=q,
h=h,
nbands=5,
hund=True,
eigensolver='rmm-diis',
occupations=FermiDirac(width=0.1),
convergence=convergence)
c.calculate(s)
equal(c.get_magnetic_moment(0), 5, 0.1)
# set magnetic moment
mm = [5]
s.set_initial_magnetic_moments(mm)
c = GPAW(charge=q,
from __future__ import print_function
from ase import Atoms
from gpaw import GPAW
from gpaw.test import equal
# ??? g = Generator('H', 'TPSS', scalarrel=True, nofiles=True)
atoms = Atoms('H', magmoms=[1], pbc=True)
atoms.center(vacuum=3)
calc = GPAW(gpts=(32, 32, 32), nbands=1, xc='PBE', txt='Hnsc.txt')
atoms.set_calculator(calc)
e1 = atoms.get_potential_energy()
niter1 = calc.get_number_of_iterations()
e1ref = calc.get_reference_energy()
de12t = calc.get_xc_difference('TPSS')
de12m = calc.get_xc_difference('M06-L')
de12r = calc.get_xc_difference('revTPSS')
print('================')
print('e1 = ', e1)
print('de12t = ', de12t)
print('de12m = ', de12m)
print('de12r = ', de12r)
print('tpss = ', e1 + de12t)
print('m06l = ', e1 + de12m)
print('revtpss = ', e1 + de12r)
print('================')
equal(e1 + de12t, -1.11723235592, 0.005)
equal(e1 + de12m, -1.18207312133, 0.005)
equal(e1 + de12r, -1.10093196353, 0.005)
def read_abinit_out(fd):
results = {}
def skipto(string):
for line in fd:
if string in line:
return line
raise RuntimeError('Not found: {}'.format(string))
line = skipto('Version')
m = re.match(r'\.*?Version\s+(\S+)\s+of ABINIT', line)
assert m is not None
results['version'] = m.group(1)
shape_vars = {}
skipto('echo values of preprocessed input variables')
for line in fd:
if '===============' in line:
break
tokens = line.split()
if not tokens:
continue
for key in ['natom', 'nkpt', 'nband', 'ntypat']:
if tokens[0] == key:
shape_vars[key] = int(tokens[1])
if line.lstrip().startswith('typat'): # Avoid matching ntypat
types = consume_multiline(fd, line, shape_vars['natom'], int)
if 'znucl' in line:
znucl = consume_multiline(fd, line, shape_vars['ntypat'], float)
if 'rprim' in line:
cell = consume_multiline(fd, line, 9, float)
cell = cell.reshape(3, 3)
natoms = shape_vars['natom']
# Skip ahead to results:
for line in fd:
if 'was not enough scf cycles to converge' in line:
raise RuntimeError(line)
if 'iterations are completed or convergence reached' in line:
break
else:
raise RuntimeError('Cannot find results section')
def read_array(fd, nlines):
arr = []
for i in range(nlines):
line = next(fd)
arr.append(line.split()[1:])
arr = np.array(arr).astype(float)
return arr
for line in fd:
if 'cartesian coordinates (angstrom) at end' in line:
positions = read_array(fd, natoms)
if 'cartesian forces (eV/Angstrom) at end' in line:
results['forces'] = read_array(fd, natoms)
if 'Cartesian components of stress tensor (hartree/bohr^3)' in line:
results['stress'] = read_stress(fd)
if 'Components of total free energy (in Hartree)' in line:
for line in fd:
if 'Etotal' in line:
energy = float(line.rsplit('=', 2)[1]) * Hartree
results['energy'] = results['free_energy'] = energy
break
# Which of the listed energies do we take ??
if 'END DATASET(S)' in line:
break
znucl_int = znucl.astype(int)
znucl_int[znucl_int != znucl] = 0 # (Fractional Z)
numbers = znucl_int[types - 1]
atoms = Atoms(numbers=numbers, positions=positions, cell=cell, pbc=True)
results['atoms'] = atoms
return results
def generate_hybrid_structure(ani_input: dict, tautomer_transformation: dict,
ANI1_force_and_energy: ANI1_force_and_energy):
"""
Generates a hybrid structure between two tautomers. The heavy atom frame is kept but a
hydrogen is added to the tautomer acceptor heavy atom.
Keys are added to the ani_input dict and tautomer_transformation dict:
ani_input['hybrid_atoms'] = ani_input['ligand_atoms'] + 'H'
ani_input['hybrid_coords'] = hybrid_coord
ani_input['min_e'] = min_e
ani_input['hybrid_topolog'] = hybrid_top
tautomer_transformation['donor_hydrogen_idx'] = tautomer_transformation['hydrogen_idx']
tautomer_transformation['acceptor_hydrogen_idx'] = len(ani_input['hybrid_atoms']) -1
Parameters
----------
ani_input : dict
tautomer_transformation : traj
ANI1_force_and_energy : ANI1_force_and_energy
"""
platform = 'cpu'
device = torch.device(platform)
model = LinearAlchemicalANI(alchemical_atoms=[],
ani_input={},
device=device,
pbc=False)
model = model.to(device)
torch.set_num_threads(2)
ani_input['hybrid_atoms'] = ani_input['ligand_atoms'] + 'H'
energy_function = ANI1_force_and_energy(
device=device,
model=model,
atom_list=ani_input['hybrid_atoms'],
platform=platform,
tautomer_transformation=None)
# TODO: check type consistency: here tautomer_transformation=None, but default is {}
hydrogen_mover = MC_Mover(tautomer_transformation['donor_idx'],
tautomer_transformation['hydrogen_idx'],
tautomer_transformation['acceptor_idx'],
ani_input['ligand_atoms'])
hybrid_top = copy.deepcopy(ani_input['ligand_topology'])
dummy_atom = hybrid_top.add_atom('H', md.element.hydrogen,
hybrid_top.residue(-1))
hybrid_top.add_bond(
hybrid_top.atom(tautomer_transformation['acceptor_idx']), dummy_atom)
min_e = 100 * unit.kilocalorie_per_mole
min_coordinates = None
for _ in range(1000):
hybrid_coord = hydrogen_mover._move_hydrogen_to_acceptor_idx(
ani_input['ligand_coords'], override=False)
e = energy_function.calculate_energy(hybrid_coord)
if e < min_e:
min_e = e
min_coordinates = hybrid_coord
tautomer_transformation['donor_hydrogen_idx'] = tautomer_transformation[
'hydrogen_idx']
tautomer_transformation['acceptor_hydrogen_idx'] = len(
ani_input['hybrid_atoms']) - 1
ani_input['hybrid_coords'] = min_coordinates
ani_input['min_e'] = min_e
ani_input['hybrid_topology'] = hybrid_top
atom_list = []
for e, c in zip(ani_input['hybrid_atoms'], ani_input['hybrid_coords']):
c_list = (c[0].value_in_unit(unit.angstrom),
c[1].value_in_unit(unit.angstrom),
c[2].value_in_unit(unit.angstrom))
atom_list.append(Atom(e, c_list))
mol = Atoms(atom_list)
ani_input['ase_hybrid_mol'] = mol
def getUnitCell(self):
sideLen = self.sideLen
edge = Atoms()
nAtom = 2 * sideLen + 1
for i in range(nAtom):
if i % 2 == 0:
label = 'C'
y = 0.5
else:
label = 'N'
if len(self.elements) == 1: label = 'C'
y = 1.0
x = (-sideLen + i) * 0.5 * sqrt(3)
y -= (sideLen + 1) * 1.5
atom = Atom(label, (x, y, 0.0))
edge.append(atom)
unitCell = Atoms()
for i in range(6):
newEdge = edge.copy()
newEdge.rotate('z', i * 2 * pi / 6.0)
unitCell.extend(newEdge)
#get cell
dist = (self.sideLen + 1) * 3.0 #the distance between 2 hole center
if self.cubic:
newAtoms = unitCell.copy()
newAtoms.translate([dist * sqrt(3) / 2, dist / 2.0, 0])
unitCell.extend(newAtoms)
unitCell.set_cell([dist * sqrt(3), dist, 10.0])
else:
cell = np.diag([dist * sqrt(3) / 2, dist, 10])
cell[0, 1] = dist / 2.0
unitCell.set_cell(cell)
return unitCell
voxel_gaussian = norm.pdf(r)
# put e density in voxel
ed = voxel_gaussian * atom.number
return ed
if __name__ == '__main__':
import matplotlib.pyplot as plt
from ase import Atoms
from ase.visualize import view
from ase.cluster import FaceCenteredCubic
import ase.io as aseio
# atoms = Atoms('Pt', [(0, 0, 0)])
atoms = Atoms(
FaceCenteredCubic('Pt', [[1, 0, 0], [1, 1, 0], [1, 1, 1]], (2, 3, 2)))
# atoms = atoms[[atom.index for atom in atoms if atom.position[2]< 1.5]]
view(atoms)
atoms.set_cell(atoms.get_cell() * 1.2)
atoms.center()
cell = atoms.get_cell()
print(cell, len(atoms))
resolution = .3 * np.ones(3)
c = np.diagonal(cell)
v = tuple(np.int32(np.ceil(c / resolution)))
voxels = np.zeros(v)
ed = np.zeros(v)
i = 0
for atom in atoms:
print(i)
ed += get_atomic_electron_density(atom, voxels, resolution)
def newclus(ind1, ind2, Optimizer):
"""Select a box in the cluster configuration"""
if 'CX' in Optimizer.debug:
debug = True
else:
debug = False
Optimizer.output.write('Box Cluster Cx between individual ' +
repr(ind1.index) + ' and individual ' +
repr(ind2.index) + '\n')
#Perserve starting conditions of individual
solid1 = ind1[0].copy()
solid2 = ind2[0].copy()
cello1 = ind1[0].get_cell()
cello2 = ind2[0].get_cell()
cell1 = numpy.maximum.reduce(solid1.get_positions())
cell1m = numpy.minimum.reduce(solid1.get_positions())
cell2 = numpy.maximum.reduce(solid2.get_positions())
cell2m = numpy.minimum.reduce(solid2.get_positions())
cell = numpy.minimum(cell1, cell2)
pbc1 = solid1.get_pbc()
pbc2 = solid2.get_pbc()
#Get starting concentrations and number of atoms
nat1 = len(solid1)
nat2 = len(solid2)
# Pick a origin point for box in the cell
pt1 = random.choice(solid1)
pt1f = [(pt1.position[i] - cell1m[i]) / cell1[i] for i in range(3)]
pt2 = [pt1f[i] * cell2[i] + cell2m[i] for i in range(3)]
solid2.append(Atom(position=pt2))
pt2 = solid2[len(solid2) - 1]
#Find max neighborsize of circle cut
r = random.uniform(0, min(nat1, nat2) / 5.0)
if debug:
print 'DEBUG CX: Point one =', pt1.position
print 'DEBUG CX: Point two =', pt2.position
#Find atoms within sphere of neighborsize r for both individuals
#Make sure that crossover is only selection of atoms not all
while True:
ctoff = [r for on in solid1]
nl = NeighborList(ctoff, bothways=True, self_interaction=False)
nl.update(solid1)
indices1, offsets = nl.get_neighbors(pt1.index)
if len(indices1) == 0:
r = r * 1.2
elif len(indices1) < nat1 * .75:
break
else:
r = r * 0.8
if debug:
print 'Neighborsize of box = ' + repr(
r) + '\nPosition in solid1 = ' + repr(
pt1.position) + '\nPosition in solid2 = ' + repr(pt2.position)
group1 = Atoms(cell=solid1.get_cell(), pbc=solid1.get_pbc())
group1.append(pt1)
indices1a = [pt1.index]
for index, d in zip(indices1, offsets):
if index not in indices1a:
index = int(index)
pos = solid1[index].position + numpy.dot(d, solid1.get_cell())
group1.append(Atom(symbol=solid1[index].symbol, position=pos))
indices1a.append(index)
indices1 = indices1a
ctoff = [r for on in solid2]
nl = NeighborList(ctoff, bothways=True, self_interaction=False)
nl.update(solid2)
indices2, offsets = nl.get_neighbors(pt2.index)
group2 = Atoms(cell=solid2.get_cell(), pbc=solid2.get_pbc())
indices2a = []
for index, d in zip(indices2, offsets):
if index not in indices2a:
index = int(index)
pos = solid2[index].position + numpy.dot(d, solid2.get_cell())
group2.append(Atom(symbol=solid2[index].symbol, position=pos))
indices2a.append(index)
indices2 = indices2a
if len(indices2) == 0:
for one in group1:
while True:
sel = random.choice(solid2)
if sel.symbol == one.symbol:
if sel.index not in indices2:
group2.append(sel)
indices2.append(sel.index)
break
if Optimizer.forcing == 'Concentration':
symlist = list(set(group1.get_chemical_symbols()))
seplist = [[atm for atm in group2 if atm.symbol == sym]
for sym in symlist]
group2n = Atoms(cell=group2.get_cell(), pbc=group2.get_pbc())
indices2n = []
dellist = []
for one in group1:
sym1 = one.symbol
listpos = [i for i, s in enumerate(symlist) if s == sym1][0]
if len(seplist[listpos]) > 0:
pos = random.choice(range(len(seplist[listpos])))
group2n.append(seplist[listpos][pos])
indices2n.append(indices2[seplist[listpos][pos].index])
del seplist[listpos][pos]
else:
dellist.append(one.index)
if len(dellist) != 0:
dellist.sort(reverse=True)
for one in dellist:
del group1[one]
del indices1[one]
indices2n.append(pt2.index)
indices2 = indices2n
group2 = group2n.copy()
else:
dellist = []
while len(group2) < len(group1) - len(dellist):
#Too many atoms in group 1
dellist.append(random.choice(group1).index)
if len(dellist) != 0:
dellist.sort(reverse=True)
for one in dellist:
del group1[one]
del indices1[one]
dellist = []
while len(group1) < len(group2) - len(dellist):
#Too many atoms in group 2
dellist.append(random.choice(group2).index)
if len(dellist) != 0:
dellist.sort(reverse=True)
for one in dellist:
del group2[one]
del indices2[one]
other2 = Atoms(cell=solid2.get_cell(), pbc=solid2.get_pbc())
for one in solid2:
if one.index not in indices2:
other2.append(one)
other1 = Atoms(cell=solid1.get_cell(), pbc=solid1.get_pbc())
for one in solid1:
if one.index not in indices1:
other1.append(one)
#Exchange atoms in sphere and build new solids
nsolid1 = other1.copy()
nsolid1.extend(group2.copy())
nsolid2 = other2.copy()
nsolid2.extend(group1.copy())
#DEBUG: Write crossover to file
if debug:
write_xyz(Optimizer.debugfile, nsolid1, 'CX(randalloybx):nsolid1')
write_xyz(Optimizer.debugfile, nsolid2, 'CX(randalloybx):nsolid2')
#DEBUG: Check structure of atoms exchanged
for sym, c, m, u in Optimizer.atomlist:
if Optimizer.structure == 'Defect':
nc = len([atm for atm in nsolid1 if atm.symbol == sym])
nc += len([atm for atm in ind1.bulki if atm.symbol == sym])
oc = len([atm for atm in solid1 if atm.symbol == sym])
oc += len([atm for atm in ind1.bulki if atm.symbol == sym])
else:
nc = len([atm for atm in nsolid1 if atm.symbol == sym])
oc = len([atm for atm in solid1 if atm.symbol == sym])
Optimizer.output.write('CX(clustbx):New solid1 contains ' + repr(nc) +
' ' + repr(sym) + ' atoms\n')
if debug:
print 'DEBUG CX: New solid1 contains ' + repr(nc) + ' ' + repr(
sym) + ' atoms'
if oc != nc:
#pdb.set_trace()
print 'CX: Issue in maintaining atom concentration\n Dropping new individual'
Optimizer.output.write(
'CX: Issue in maintaining atom concentration\n Dropping new individual 1\n'
)
nsolid1 = solid1
for sym, c, m, u in Optimizer.atomlist:
if Optimizer.structure == 'Defect':
nc = len([atm for atm in nsolid2 if atm.symbol == sym])
nc += len([atm for atm in ind2.bulki if atm.symbol == sym])
oc = len([atm for atm in solid2 if atm.symbol == sym])
oc += len([atm for atm in ind2.bulki if atm.symbol == sym])
else:
nc = len([atm for atm in nsolid2 if atm.symbol == sym])
oc = len([atm for atm in solid2 if atm.symbol == sym])
Optimizer.output.write('CX(clustbx):New solid2 contains ' + repr(nc) +
' ' + repr(sym) + ' atoms\n')
if debug:
print 'DEBUG CX: New solid2 contains ' + repr(nc) + ' ' + repr(
sym) + ' atoms'
if oc != nc:
#pdb.set_trace()
print 'CX: Issue in maintaining atom concentration\n Dropping new individual'
Optimizer.output.write(
'CX: Issue in maintaining atom concentration\n Dropping new individual 2\n'
)
solid2.pop()
nsolid2 = solid2
if Optimizer.forcing != 'Concentration':
for i in range(len(Optimizer.atomlist)):
atms1 = [
inds for inds in nsolid1
if inds.symbol == Optimizer.atomlist[i][0]
]
atms2 = [
inds for inds in nsolid2
if inds.symbol == Optimizer.atomlist[i][0]
]
if len(atms1) == 0:
if len(atms2) == 0:
nsolid1[random.randint(
0,
len(indi1) - 1)].symbol == Optimizer.atomlist[i][0]
nsolid2[random.randint(
0,
len(indi2) - 1)].symbol == Optimizer.atomlist[i][0]
else:
nsolid1.append(atms2[random.randint(0, len(atms2) - 1)])
nsolid1.pop(random.randint(0, len(nsolid1) - 2))
else:
if len(atms2) == 0:
nsolid2.append(atms1[random.randint(0, len(atms1) - 1)])
nsolid2.pop(random.randint(0, len(nsolid2) - 2))
nsolid1.set_cell(cello1)
nsolid2.set_cell(cello2)
nsolid1.set_pbc(pbc1)
nsolid2.set_pbc(pbc2)
ind1[0] = nsolid1.copy()
ind2[0] = nsolid2.copy()
return ind1, ind2
lambda_coeff = 1.0
name = 'lambda_{0}'.format(lambda_coeff)
filename = 'atoms_' + name + '.dat'
f = paropen(filename, 'w')
elements = ['N']
for symbol in elements:
mixer = Mixer()
eigensolver = CG(tw_coeff=lambda_coeff)
poissonsolver = PoissonSolver()
molecule = Atoms(symbol, positions=[(c, c, c)], cell=(a, a, a))
calc = GPAW(h=h,
xc=xcname,
maxiter=240,
eigensolver=eigensolver,
mixer=mixer,
setups=name,
poissonsolver=poissonsolver)
molecule.set_calculator(calc)
E = molecule.get_total_energy()
f.write('{0}\t{1}\n'.format(symbol, E))
def do_calculation(calculator):
'function to run a calculation through multiprocessing'
with calculator as calc:
atoms = calc.get_atoms()
e = atoms.get_potential_energy()
v = atoms.get_volume()
return v, e
# this only runs in the main script, not in processes on other cores
if __name__ == '__main__':
NCORES = 6 # number of cores to run processes on
# setup an atoms object
a = 3.6
atoms = Atoms(
[Atom('Cu', (0, 0, 0))],
cell=0.5 * a *
np.array([[1.0, 1.0, 0.0], [0.0, 1.0, 1.0], [1.0, 0.0, 1.0]]))
v0 = atoms.get_volume()
# Step 1
COUNTER = 0
calculators = [] # list of calculators to be run
factors = [-0.1, 0.05, 0.0, 0.05, 0.1]
for f in factors:
newatoms = atoms.copy()
newatoms.set_volume(v0 * (1 + f))
label = 'bulk/cu-mp/step1-{0}'.format(COUNTER)
COUNTER += 1
calc = jasp(label,
xc='PBE',
encut=350,
kpts=(6, 6, 6),
def read_abinit_in(fd):
"""Import ABINIT input file.
Reads cell, atom positions, etc. from abinit input file
"""
tokens = []
for line in fd:
meat = line.split('#', 1)[0]
tokens += meat.lower().split()
# note that the file can not be scanned sequentially
index = tokens.index("acell")
unit = 1.0
if (tokens[index + 4].lower()[:3] != 'ang'):
unit = Bohr
acell = [
unit * float(tokens[index + 1]), unit * float(tokens[index + 2]),
unit * float(tokens[index + 3])
]
index = tokens.index("natom")
natom = int(tokens[index + 1])
index = tokens.index("ntypat")
ntypat = int(tokens[index + 1])
index = tokens.index("typat")
typat = []
while len(typat) < natom:
token = tokens[index + 1]
if '*' in token: # e.g. typat 4*1 3*2 ...
nrepeat, typenum = token.split('*')
typat += [int(typenum)] * int(nrepeat)
else:
typat.append(int(token))
index += 1
assert natom == len(typat)
index = tokens.index("znucl")
znucl = []
for i in range(ntypat):
znucl.append(int(tokens[index + 1 + i]))
index = tokens.index("rprim")
rprim = []
for i in range(3):
rprim.append([
acell[i] * float(tokens[index + 3 * i + 1]),
acell[i] * float(tokens[index + 3 * i + 2]),
acell[i] * float(tokens[index + 3 * i + 3])
])
# create a list with the atomic numbers
numbers = []
for i in range(natom):
ii = typat[i] - 1
numbers.append(znucl[ii])
# now the positions of the atoms
if "xred" in tokens:
index = tokens.index("xred")
xred = []
for i in range(natom):
xred.append([
float(tokens[index + 3 * i + 1]),
float(tokens[index + 3 * i + 2]),
float(tokens[index + 3 * i + 3])
])
atoms = Atoms(cell=rprim,
scaled_positions=xred,
numbers=numbers,
pbc=True)
else:
if "xcart" in tokens:
index = tokens.index("xcart")
unit = Bohr
elif "xangst" in tokens:
unit = 1.0
index = tokens.index("xangst")
else:
raise IOError(
"No xred, xcart, or xangs keyword in abinit input file")
xangs = []
for i in range(natom):
xangs.append([
unit * float(tokens[index + 3 * i + 1]),
unit * float(tokens[index + 3 * i + 2]),
unit * float(tokens[index + 3 * i + 3])
])
atoms = Atoms(cell=rprim, positions=xangs, numbers=numbers, pbc=True)
try:
ii = tokens.index('nsppol')
except ValueError:
nsppol = None
else:
nsppol = int(tokens[ii + 1])
if nsppol == 2:
index = tokens.index('spinat')
magmoms = [float(tokens[index + 3 * i + 3]) for i in range(natom)]
atoms.set_initial_magnetic_moments(magmoms)
assert len(atoms) == natom
return atoms
atoms.get_potential_energy()
calc.write('Al1.gpw','all')
# Excited state calculation
q = np.array([1./4.,0.,0.])
w = np.linspace(0, 24, 241)
df = DF(calc='Al1.gpw', q=q, w=w, eta=0.2, ecut=50)
#df.write('Al.pckl')
df.get_EELS_spectrum(filename='EELS_Al_1')
atoms = Atoms('Al8',scaled_positions=[(0,0,0),
(0.5,0,0),
(0,0.5,0),
(0,0,0.5),
(0.5,0.5,0),
(0.5,0,0.5),
(0.,0.5,0.5),
(0.5,0.5,0.5)],
cell=[(0,a,a),(a,0,a),(a,a,0)],
pbc=True)
calc = GPAW(gpts=(24,24,24),
eigensolver=RMM_DIIS(),
mixer=Mixer(0.1,3),
kpts=(2,2,2),
xc='LDA')
atoms.set_calculator(calc)
atoms.get_potential_energy()
calc.write('Al2.gpw','all')
from distutils.version import LooseVersion
from ase.phonons import Phonons
from ase import Atoms, __version__
import numpy as np
from gpaw import GPAW
from gpaw.elph.electronphonon import ElectronPhononCoupling
if LooseVersion(__version__) < '3.18':
from unittest import SkipTest
raise SkipTest
a = 0.90
atoms = Atoms('H',
cell=np.diag([a, 2.1, 2.1]),
positions=[[0, 0, 0]],
pbc=(1, 0, 0))
atoms.center()
supercell = (2, 1, 1)
parameters = {
'mode': 'lcao',
'kpts': {
'size': (2, 1, 1),
'gamma': True
},
'txt': None,
'basis': 'dzp',
'symmetry': {
'point_group': False
},
import numpy as np
from ase import Atoms
from ase.calculators.test import FreeElectrons
from ase.geometry import crystal_structure_from_cell, cell_to_cellpar, cellpar_to_cell
from ase.dft.kpoints import get_special_points
mc1 = [[1, 0, 0], [0, 1, 0], [0, 0.2, 1]]
par = cell_to_cellpar(mc1)
mc2 = cellpar_to_cell(par)
mc3 = [[1, 0, 0], [0, 1, 0], [-0.2, 0, 1]]
mc4 = [[1, 0, 0], [-0.2, 1, 0], [0, 0, 1]]
path = 'GYHCEM1AXH1'
firsttime = True
for cell in [mc1, mc2, mc3, mc4]:
a = Atoms(cell=cell, pbc=True)
a.cell *= 3
a.calc = FreeElectrons(nvalence=1, kpts={'path': path})
cs = crystal_structure_from_cell(a.cell)
assert cs == 'monoclinic'
r = a.get_reciprocal_cell()
k = get_special_points(a.cell)['H']
print(np.dot(k, r))
a.get_potential_energy()
bs = a.calc.band_structure()
coords, labelcoords, labels = bs.get_labels()
assert ''.join(labels) == path
e_skn = bs.energies
# bs.plot()
if firsttime:
coords1 = coords
"""Check that we can read old version 1 PickleTrajectories."""
import cPickle as pickle
from StringIO import StringIO
import numpy as np
from ase.io.trajectory import PickleTrajectory
from ase.constraints import FixAtoms
from ase import Atoms
a = Atoms('FOO')
def v1(a):
"""Create old version-1 trajectory."""
fd = StringIO()
fd.write('PickleTrajectory')
d = {'pbc': a.pbc,
'numbers': a.numbers,
'tags': None,
'masses': None,
'constraints': a.constraints}
pickle.dump(d, fd, protocol=-1)
d = {'positions': a.positions,
'cell': a.cell,
'momenta': None}
pickle.dump(d, fd, protocol=-1)
return StringIO(fd.getvalue())
def v2(a):
import numpy as np
a1 = [2, 0, 0]
a2 = [1, 1, 0]
a3 = [0, 0, 10]
uc = np.array([a1, a2, a3])
print('V = {0} ang^3 from dot/cross'.format(np.dot(np.cross(a1, a2), a3)))
print('V = {0} ang^3 from det'.format(np.linalg.det(uc)))
from ase import Atoms
atoms = Atoms([], cell=uc) #empty list of atoms
print('V = {0} ang^3 from get_volume'.format(atoms.get_volume()))
def test_dynamic_neb():
# Global counter of force evaluations:
force_evaluations = [0]
class EMT(OrigEMT):
def calculate(self, *args, **kwargs):
force_evaluations[0] += 1
OrigEMT.calculate(self, *args, **kwargs)
# Build Pt(111) slab with six surface atoms and add oxygen adsorbate
initial = fcc111('Pt', size=(3, 2, 3), orthogonal=True)
initial.center(axis=2, vacuum=10)
oxygen = Atoms('O')
oxygen.translate(initial[7].position + (0., 0., 3.5))
initial.extend(oxygen)
# EMT potential
initial.calc = EMT()
# Optimize initial state
opt = BFGS(initial)
opt.run(fmax=0.03)
# Move oxygen adsorbate to neighboring hollow site
final = initial.copy()
final[18].x += 2.8
final[18].y += 1.8
final.calc = EMT()
opt = BFGS(final)
opt.run(fmax=0.03)
# NEB with seven interior images
images = [initial]
for i in range(7):
images.append(initial.copy())
images.append(final)
fmax = 0.03 # Same for NEB and optimizer
for i in range(1, len(images) - 1):
calc = EMT()
images[i].calc = calc
def run_NEB():
if method == 'dyn':
neb = NEB(images, fmax=fmax, dynamic_relaxation=True)
neb.interpolate()
elif method == 'dyn_scale':
neb = NEB(images,
fmax=fmax,
dynamic_relaxation=True,
scale_fmax=6.)
neb.interpolate()
else:
# Default NEB
neb = NEB(images)
neb.interpolate()
# Optimize and check number of calculations.
# We use a hack with a global counter to count the force evaluations:
force_evaluations[0] = 0
opt = BFGS(neb)
opt.run(fmax=fmax)
force_calls.append(force_evaluations[0])
# Get potential energy of transition state.
Emax.append(
np.sort([image.get_potential_energy()
for image in images[1:-1]])[-1])
force_calls, Emax = [], []
for method in ['def', 'dyn', 'dyn_scale']:
run_NEB()
# Check force calculation count for default and dynamic NEB implementations
print('\n# Force calls with default NEB: {}'.format(force_calls[0]))
print('# Force calls with dynamic NEB: {}'.format(force_calls[1]))
print('# Force calls with dynamic and scaled NEB: {}\n'.format(
force_calls[2]))
assert force_calls[2] < force_calls[1] < force_calls[0]
# Assert reaction barriers are within 1 meV of default NEB
assert (abs(Emax[1] - Emax[0]) < 1e-3)
assert (abs(Emax[2] - Emax[0]) < 1e-3)
def write(self, filename, **settings):
# Determine canvas width and height
ratio = float(self.w) / self.h
if self.canvas_width is None:
if self.canvas_height is None:
self.canvas_width = min(self.w * 15, 640)
else:
self.canvas_width = self.canvas_height * ratio
elif self.canvas_height is not None:
raise RuntimeError("Can't set *both* width and height!")
# Distance to image plane from camera
if self.image_plane is None:
if self.camera_type == 'orthographic':
self.image_plane = 1 - self.camera_dist
else:
self.image_plane = 0
self.image_plane += self.camera_dist
# Produce the .ini file
if filename.endswith('.pov'):
ini = open(filename[:-4] + '.ini', 'w').write
else:
ini = open(filename + '.ini', 'w').write
ini('Input_File_Name=%s\n' % filename)
ini('Output_to_File=True\n')
ini('Output_File_Type=N\n')
if self.transparent:
ini('Output_Alpha=on\n')
else:
ini('Output_Alpha=off\n')
ini('; if you adjust Height, and width, you must preserve the ratio\n')
ini('; Width / Height = %f\n' % ratio)
ini('Width=%s\n' % self.canvas_width)
ini('Height=%s\n' % (self.canvas_width / ratio))
ini('Antialias=True\n')
ini('Antialias_Threshold=0.1\n')
ini('Display=%s\n' % self.display)
ini('Pause_When_Done=%s\n' % self.pause)
ini('Verbose=False\n')
del ini
# Produce the .pov file
pov_fid = open(filename, 'w')
w = pov_fid.write
w('#include "colors.inc"\n')
w('#include "finish.inc"\n')
w('\n')
w('global_settings {assumed_gamma 1 max_trace_level 6}\n')
# The background must be transparent for a transparent image
if self.transparent:
w('background {%s transmit 1.0}\n' % pc(self.background))
else:
w('background {%s}\n' % pc(self.background))
w('camera {%s\n' % self.camera_type)
w(' right -%.2f*x up %.2f*y\n' % (self.w, self.h))
w(' direction %.2f*z\n' % self.image_plane)
w(' location <0,0,%.2f> look_at <0,0,0>}\n' % self.camera_dist)
for loc, rgb in self.point_lights:
w('light_source {%s %s}\n' % (pa(loc), pc(rgb)))
if self.area_light is not None:
loc, color, width, height, nx, ny = self.area_light
w('light_source {%s %s\n' % (pa(loc), pc(color)))
w(' area_light <%.2f, 0, 0>, <0, %.2f, 0>, %i, %i\n' %
(width, height, nx, ny))
w(' adaptive 1 jitter}\n')
# the depth cueing
if self.depth_cueing and (self.cue_density >= 1e-4):
# same way vmd does it
if self.cue_density > 1e4:
# larger does not make any sense
dist = 1e-4
else:
dist = 1. / self.cue_density
w('fog {fog_type 1 distance %.4f color %s}' %
(dist, pc(self.background)))
w('\n')
for key in self.material_styles_dict.keys():
w('#declare %s = %s\n' % (key, self.material_styles_dict[key]))
w('#declare Rcell = %.3f;\n' % self.celllinewidth)
w('#declare Rbond = %.3f;\n' % self.bondlinewidth)
w('\n')
w('#macro atom(LOC, R, COL, TRANS, FIN)\n')
w(' sphere{LOC, R texture{pigment{color COL transmit TRANS} '
'finish{FIN}}}\n')
w('#end\n')
w('#macro constrain(LOC, R, COL, TRANS FIN)\n')
w('union{torus{R, Rcell rotate 45*z '
'texture{pigment{color COL transmit TRANS} finish{FIN}}}\n')
w(' torus{R, Rcell rotate -45*z '
'texture{pigment{color COL transmit TRANS} finish{FIN}}}\n')
w(' translate LOC}\n')
w('#end\n')
w('\n')
z0 = self.positions[:, 2].max()
self.positions -= (self.w / 2, self.h / 2, z0)
# Draw unit cell
if self.cell_vertices is not None:
self.cell_vertices -= (self.w / 2, self.h / 2, z0)
self.cell_vertices.shape = (2, 2, 2, 3)
for c in range(3):
for j in ([0, 0], [1, 0], [1, 1], [0, 1]):
parts = []
for i in range(2):
j.insert(c, i)
parts.append(self.cell_vertices[tuple(j)])
del j[c]
distance = np.linalg.norm(parts[1] - parts[0])
if distance < 1e-12:
continue
w('cylinder {')
for i in range(2):
w(pa(parts[i]) + ', ')
w('Rcell pigment {Black}}\n')
# Draw atoms
a = 0
for loc, dia, color in zip(self.positions, self.d, self.colors):
tex = 'ase3'
trans = 0.
if self.textures is not None:
tex = self.textures[a]
if self.transmittances is not None:
trans = self.transmittances[a]
w('atom(%s, %.2f, %s, %s, %s) // #%i \n' %
(pa(loc), dia / 2., pc(color), trans, tex, a))
a += 1
# Draw atom bonds
for pair in self.bondatoms:
# Make sure that each pair has 4 componets: a, b, offset,
# bond_order, bond_offset
# a, b: atom index to draw bond
# offset: original meaning to make offset for mid-point.
# bond_oder: if not supplied, set it to 1 (single bond).
# It can be 1, 2, 3, corresponding to single,
# double, triple bond
# bond_offset: displacement from original bond position.
# Default is (bondlinewidth, bondlinewidth, 0)
# for bond_order > 1.
if len(pair) == 2:
a, b = pair
offset = (0, 0, 0)
bond_order = 1
bond_offset = (0, 0, 0)
elif len(pair) == 3:
a, b, offset = pair
bond_order = 1
bond_offset = (0, 0, 0)
elif len(pair) == 4:
a, b, offset, bond_order = pair
bond_offset = (self.bondlinewidth, self.bondlinewidth, 0)
elif len(pair) > 4:
a, b, offset, bond_order, bond_offset = pair
else:
raise RuntimeError('Each list in bondatom must have at least '
'2 entries. Error at %s' % pair)
if len(offset) != 3:
raise ValueError('offset must have 3 elements. '
'Error at %s' % pair)
if len(bond_offset) != 3:
raise ValueError('bond_offset must have 3 elements. '
'Error at %s' % pair)
if bond_order not in [0, 1, 2, 3]:
raise ValueError('bond_order must be either 0, 1, 2, or 3. '
'Error at %s' % pair)
# Up to here, we should have all a, b, offset, bond_order,
# bond_offset for all bonds.
# Rotate bond_offset so that its direction is 90 degree off the bond
# Utilize Atoms object to rotate
if bond_order > 1 and np.linalg.norm(bond_offset) > 1.e-9:
tmp_atoms = Atoms('H3')
tmp_atoms.set_cell(self.cell)
tmp_atoms.set_positions([
self.positions[a],
self.positions[b],
self.positions[b] + np.array(bond_offset),
])
tmp_atoms.center()
tmp_atoms.set_angle(0, 1, 2, 90)
bond_offset = tmp_atoms[2].position - tmp_atoms[1].position
R = np.dot(offset, self.cell)
mida = 0.5 * (self.positions[a] + self.positions[b] + R)
midb = 0.5 * (self.positions[a] + self.positions[b] - R)
if self.textures is not None:
texa = self.textures[a]
texb = self.textures[b]
else:
texa = texb = 'ase3'
if self.transmittances is not None:
transa = self.transmittances[a]
transb = self.transmittances[b]
else:
transa = transb = 0.
fmt = ('cylinder {%s, %s, Rbond texture{pigment '
'{color %s transmit %s} finish{%s}}}\n')
# draw bond, according to its bond_order.
# bond_order == 0: No bond is plotted
# bond_order == 1: use original code
# bond_order == 2: draw two bonds, one is shifted by bond_offset/2,
# and another is shifted by -bond_offset/2.
# bond_order == 3: draw two bonds, one is shifted by bond_offset,
# and one is shifted by -bond_offset, and the
# other has no shift.
# To shift the bond, add the shift to the first two coordinate in
# write statement.
if bond_order == 1:
w(fmt % (pa(self.positions[a]), pa(mida), pc(
self.colors[a]), transa, texa))
w(fmt % (pa(self.positions[b]), pa(midb), pc(
self.colors[b]), transb, texb))
elif bond_order == 2:
bondOffSetDB = [x / 2 for x in bond_offset]
w(fmt %
(pa(self.positions[a] - bondOffSetDB),
pa(mida - bondOffSetDB), pc(self.colors[a]), transa, texa))
w(fmt %
(pa(self.positions[b] - bondOffSetDB),
pa(midb - bondOffSetDB), pc(self.colors[b]), transb, texb))
w(fmt %
(pa(self.positions[a] + bondOffSetDB),
pa(mida + bondOffSetDB), pc(self.colors[a]), transa, texa))
w(fmt %
(pa(self.positions[b] + bondOffSetDB),
pa(midb + bondOffSetDB), pc(self.colors[b]), transb, texb))
elif bond_order == 3:
w(fmt % (pa(self.positions[a]), pa(mida), pc(
self.colors[a]), transa, texa))
w(fmt % (pa(self.positions[b]), pa(midb), pc(
self.colors[b]), transb, texb))
w(fmt %
(pa(self.positions[a] + bond_offset), pa(mida + bond_offset),
pc(self.colors[a]), transa, texa))
w(fmt %
(pa(self.positions[b] + bond_offset), pa(midb + bond_offset),
pc(self.colors[b]), transb, texb))
w(fmt %
(pa(self.positions[a] - bond_offset), pa(mida - bond_offset),
pc(self.colors[a]), transa, texa))
w(fmt %
(pa(self.positions[b] - bond_offset), pa(midb - bond_offset),
pc(self.colors[b]), transb, texb))
# Draw constraints if requested
if self.exportconstraints:
for a in self.constrainatoms:
dia = self.d[a]
loc = self.positions[a]
trans = 0.0
if self.transmittances is not None:
trans = self.transmittances[a]
w('constrain(%s, %.2f, Black, %s, %s) // #%i \n' %
(pa(loc), dia / 2., trans, tex, a))
return pov_fid
from vasp import Vasp
from ase import Atom, Atoms
atoms = Atoms([Atom('Cu', [0.000, 0.000, 0.000])],
cell=[[1.818, 0.000, 1.818], [1.818, 1.818, 0.000],
[0.000, 1.818, 1.818]])
calc = Vasp('bulk/alloy/cu',
xc='PBE',
encut=350,
kpts=[13, 13, 13],
ibrion=2,
isif=4,
nsw=10,
atoms=atoms)
calc.set_nbands(f=7)
calc.write_input() # you have to write out the input for it to take effect
print calc
import numpy as np
import torch
from ase import Atoms
from ase.calculators.emt import EMT
from amptorch.trainer import AtomsTrainer
### Construct test data
distances = np.linspace(2, 5, 100)
images = []
for dist in distances:
image = Atoms(
"CuCO",
[
(-dist * np.sin(0.65), dist * np.cos(0.65), 0),
(0, 0, 0),
(dist * np.sin(0.65), dist * np.cos(0.65), 0),
],
)
image.set_cell([10, 10, 10])
image.wrap(pbc=True)
image.set_calculator(EMT())
images.append(image)
### Construct parameters
Gs = {
"default": {
"G2": {
"etas": np.logspace(np.log10(0.05), np.log10(5.0), num=4),
"rs_s": [0],
},
def test_qmmm(testdir):
r = rOH
a = angleHOH * pi / 180
# From https://doi.org/10.1063/1.445869
eexp = 6.50 * units.kcal / units.mol
dexp = 2.74
aexp = 27
D = np.linspace(2.5, 3.5, 30)
i = LJInteractions({('O', 'O'): (epsilon0, sigma0)})
# General LJ interaction object
sigma_mm = np.array([0, 0, sigma0])
epsilon_mm = np.array([0, 0, epsilon0])
sigma_qm = np.array([0, 0, sigma0])
epsilon_qm = np.array([0, 0, epsilon0])
ig = LJInteractionsGeneral(sigma_qm, epsilon_qm, sigma_mm, epsilon_mm, 3)
for calc in [
TIP3P(),
SimpleQMMM([0, 1, 2], TIP3P(), TIP3P(), TIP3P()),
SimpleQMMM([0, 1, 2], TIP3P(), TIP3P(), TIP3P(), vacuum=3.0),
EIQMMM([0, 1, 2], TIP3P(), TIP3P(), i),
EIQMMM([3, 4, 5], TIP3P(), TIP3P(), i, vacuum=3.0),
EIQMMM([0, 1, 2], TIP3P(), TIP3P(), i, vacuum=3.0),
EIQMMM([0, 1, 2], TIP3P(), TIP3P(), ig),
EIQMMM([3, 4, 5], TIP3P(), TIP3P(), ig, vacuum=3.0),
EIQMMM([0, 1, 2], TIP3P(), TIP3P(), ig, vacuum=3.0)
]:
dimer = Atoms('H2OH2O',
[(r * cos(a), 0, r * sin(a)), (r, 0, 0), (0, 0, 0),
(r * cos(a / 2), r * sin(a / 2), 0),
(r * cos(a / 2), -r * sin(a / 2), 0), (0, 0, 0)])
dimer.calc = calc
E = []
F = []
for d in D:
dimer.positions[3:, 0] += d - dimer.positions[5, 0]
E.append(dimer.get_potential_energy())
F.append(dimer.get_forces())
F = np.array(F)
F1 = np.polyval(np.polyder(np.polyfit(D, E, 7)), D)
F2 = F[:, :3, 0].sum(1)
error = abs(F1 - F2).max()
assert error < 0.01
dimer.constraints = FixInternals(bonds=[(r, (0, 2)), (r, (1, 2)),
(r, (3, 5)), (r, (4, 5))],
angles_deg=[
(np.degrees(a), (0, 2, 1)),
(np.degrees(a), (3, 5, 4))
])
with GPMin(dimer,
trajectory=calc.name + '.traj',
logfile=calc.name + 'd.log') as opt:
opt.run(0.01)
e0 = dimer.get_potential_energy()
d0 = dimer.get_distance(2, 5)
R = dimer.positions
v1 = R[1] - R[5]
v2 = R[5] - (R[3] + R[4]) / 2
a0 = np.arccos(
np.dot(v1, v2) /
(np.dot(v1, v1) * np.dot(v2, v2))**0.5) / np.pi * 180
fmt = '{0:>20}: {1:.3f} {2:.3f} {3:.3f} {4:.1f}'
print(fmt.format(calc.name, -min(E), -e0, d0, a0))
assert abs(e0 + eexp) < 0.002
assert abs(d0 - dexp) < 0.01
assert abs(a0 - aexp) < 4
print(fmt.format('reference', 9.999, eexp, dexp, aexp))
