def _read(self):
if self._names:
return
bigdct = read_json(self.filename)
for id in bigdct["ids"]:
dct = bigdct[id]
kvp = dct["key_value_pairs"]
name = str(kvp["name"])
self._names.append(name)
self._systems[name] = AtomsRow(dct).toatoms()
del kvp["name"]
self._data[name] = dict((str(k), v) for k, v in kvp.items())
def _read_json(self):
bigdct = read_json(self.filename)
ids = bigdct['ids']
if not isinstance(ids, list):
ids = ids.tolist()
return bigdct, ids, bigdct['nextid']
# hubbard value = U = IE - EA = 13.59844 - 0.75497 = 12.84347 [eV]
U_p = 12.84347 / Ha
else:
U_p = atom.get_hubbard_value(nls, scheme='central', maxstep=1.)
atom.info['hubbardvalues'] = {'s': U_p}
atom.info['occupations'] = occupations
# Creating a DFTB+ band structure evaluator and
# supplying it with a reference (DFT) band structure
dpbs = DftbPlusBandStructure(Hamiltonian_SCC='Yes',
Hamiltonian_OrbitalResolvedSCC='No',
Hamiltonian_MaxAngularMomentum_='',
Hamiltonian_MaxAngularMomentum_Br=lmax,
Hamiltonian_PolynomialRepulsive='SetForAll {Yes}')
bs_gpaw = read_json('bs_gpaw.json') # the reference band structure (DFT)
atoms = bulk(element, struct, a=La, b=Lb, c=Lc, alpha=Lalpha)
# see hotcent.tools.DftbPlusBandStructure for more information
# on the various keyword arguments used below
dpbs.add_reference_bandstructure(bs_gpaw,
atoms=atoms,
kpts_scf=kpts,
reference_level='vbm',
nsemicore=0,
weight=1.,
distribution={
'type': 'Boltzmann',
'kBT': 1.5
})
# Setting up and running the actual optimizer
# hubbard value = U = IE - EA = 13.59844 - 0.75497 = 12.84347 [eV]
U_p = 12.84347/Ha
else:
U_p = atom.get_hubbard_value(nls, scheme='central', maxstep=1.)
atom.info['hubbardvalues'] = {'s': U_p}
atom.info['occupations'] = occupations
# Creating a DFTB+ band structure evaluator and
# supplying it with a reference (DFT) band structure
dpbs = DftbPlusBandStructure(Hamiltonian_SCC='Yes',
Hamiltonian_OrbitalResolvedSCC='No',
Hamiltonian_MaxAngularMomentum_='',
Hamiltonian_MaxAngularMomentum_As=lmax,
Hamiltonian_PolynomialRepulsive='SetForAll {Yes}')
bs_qe = read_json('bs_qe.json') # the reference band structure (DFT)
atoms = bulk(element,struct,a=La,b=Lb,c=Lc,alpha=Lalpha)
# see hotcent.tools.DftbPlusBandStructure for more information
# on the various keyword arguments used below
dpbs.add_reference_bandstructure(bs_qe, atoms=atoms, kpts_scf=kpts,
reference_level='vbm', nsemicore=0, weight=1.,
distribution={'type': 'Boltzmann', 'kBT': 1.5})
# Setting up and running the actual optimizer
# (the keyword arguments are known from hotcent.slako.SlaterKosterTable)
confopt = ConfinementOptimizer(atom, N=500, rmin=0.4, dr=0.02, stride=4,
superposition='density', xc=xc)
# The initial confinement parameters are the same as in Tutorial #1.
# The additional 'adjustable' keyword argument serves to indicate
# which parameters are allowed to vary. Here we keep the quadratic
from ase.test import cli, require
from ase.db import connect
from ase.io.jsonio import read_json
from ase.calculators.gaussian import Gaussian
require('gaussian')
cli("""\
ase-build O | ase-run gaussian -d gaussian_cmdline.json &&
ase-build O2 | ase-run gaussian -d gaussian_cmdline.json""")
c = connect('gaussian_cmdline.json')
dct = read_json('gaussian_cmdline.json')
for name in ['O2', 'O']:
d = c.get([('name', '=', name)])
id = d.id
e1 = d.energy
e2 = c.get_atoms(id).get_potential_energy()
e3 = Gaussian.read_atoms(name).get_potential_energy()
e4 = dct[id]['energy']
assert e1 == e2 == e3 == e4
print(e1)
ae = 2 * c.get('name=O').energy - c.get('name=O2').energy
assert abs(ae - 1.060) < 1e-3
from ase.test import cli, require
from ase.db import connect
from ase.io.jsonio import read_json
from ase.calculators.nwchem import NWChem
require('nwchem')
cli("""\
ase build O O.traj &&
ase run nwchem O.traj -o nwchem_cmdline.json &&
ase build O2 O2.traj &&
ase run nwchem O2.traj -o nwchem_cmdline.json""")
c = connect('nwchem_cmdline.json')
dct = read_json('nwchem_cmdline.json')
for name in ['O2', 'O']:
d = c.get([('formula', '=', name)])
id = d.id
e1 = d.energy
e2 = c.get_atoms(id).get_potential_energy()
e3 = NWChem.read_atoms(name).get_potential_energy()
e4 = dct[id]['energy']
assert e1 == e2 == e3 == e4
print(e1)
ae = 2 * c.get('formula=O').energy - c.get('formula=O2').energy
assert abs(ae - 6.6053) < 1e-4
def read_json(self, filename):
"""Load Calculator state from an exported JSON Vasp2 file."""
dct = jsonio.read_json(filename)
self.fromdict(dct)
def read_band_structure(filename):
bs = read_json(filename)
if not isinstance(bs, BandStructure):
raise CLIError(f'Expected band structure, but file contains: {bs}')
return bs
kpts={
'path': 'WGKL',
'npoints': 20
},
convergence={'bands': 'all'},
)
calc.get_potential_energy()
path = bandpath('WGKL', atoms.get_cell(), npoints=20)
bs_dft = get_band_structure(atoms=atoms,
calc=calc,
path=path,
reference=evbm)
write_json('bs_dft.json', bs_dft)
bs_dft = read_json('bs_dft.json')
bs_dft.plot(filename='bs_dft.png',
show=False,
emax=bs_dft.reference + 10,
emin=bs_dft.reference - 20)
dpbs = DftbPlusBandStructure(Hamiltonian_SCC='Yes',
Hamiltonian_OrbitalResolvedSCC='No',
Hamiltonian_MaxAngularMomentum_='',
Hamiltonian_MaxAngularMomentum_N='p',
Hamiltonian_MaxAngularMomentum_O='p',
Hamiltonian_PolynomialRepulsive='SetForAll {Yes}',
Hamiltonian_SpinPolarisation='Colinear {',
Hamiltonian_SpinPolarisation_UnpairedElectrons=1,
Hamiltonian_SpinConstants_='',
Hamiltonian_SpinConstants_O=-0.028,
def load(cls, path):
# XXX Very hacky this one
cache = cls(path, {})
dct = read_json(cache._filename, always_array=False)
cache._dct.update(dct)
return cache
def read_object(filename):
try:
return read(filename)
except UnknownFileTypeError:
# Probably a bandpath/bandstructure:
return read_json(filename)
def _read_json(self):
bigdct = read_json(self.filename)
ids = bigdct['ids']
if not isinstance(ids, list):
ids = ids.tolist()
return bigdct, ids, bigdct['nextid']
from datetime import datetime
import numpy as np
import io
from ase.io.jsonio import encode, decode, read_json, write_json
assert decode(encode(np.int64(42))) == 42
c = np.array([0.1j])
assert (decode(encode(c)) == c).all()
fd = io.StringIO()
obj1 = {'hello': 'world'}
write_json(fd, obj1)
fd.seek(0)
obj2 = read_json(fd)
print(obj1)
print(obj2)
for obj in [0.5 + 1.5j, datetime.now()]:
s = encode(obj)
o = decode(s)
print(obj)
print(s)
print(obj)
assert obj == o, (obj, o, s)
from ase.test import cli, require
from ase.db import connect
from ase.io.jsonio import read_json
from ase.calculators.nwchem import NWChem
require('nwchem')
cli("""ase build O | ase run nwchem -d nwchem_cmdline.json &&
ase build O2 | ase run nwchem -d nwchem_cmdline.json""")
c = connect('nwchem_cmdline.json')
dct = read_json('nwchem_cmdline.json')
for name in ['O2', 'O']:
d = c.get([('name', '=', name)])
id = d.id
e1 = d.energy
e2 = c.get_atoms(id).get_potential_energy()
e3 = NWChem.read_atoms(name).get_potential_energy()
e4 = dct[id]['energy']
assert e1 == e2 == e3 == e4
print(e1)
ae = 2 * c.get('name=O').energy - c.get('name=O2').energy
assert abs(ae - 6.6053) < 1e-4
from ase.build import bulk
from ase.dft.band_structure import calculate_band_structure
from ase.io.jsonio import read_json
from ase.calculators.test import FreeElectrons
atoms = bulk('Au')
lat, _ = atoms.cell.bravais()
path = lat.bandpath(npoints=100)
atoms.calc = FreeElectrons()
bs = calculate_band_structure(atoms, path)
bs.write('bs.json')
bs.path.write('path.json')
bs1 = read_json('bs.json')
path1 = read_json('path.json')
print(bs1)
print(path1)
assert type(bs1) == type(bs)
assert type(path1) == type(bs.path)
