def test_water():
from ase.calculators.gaussian import Gaussian
from ase.atoms import Atoms
from ase.optimize.lbfgs import LBFGS
from ase.io import read
# First test to make sure Gaussian works
calc = Gaussian(xc='pbe', chk='water.chk', label='water')
calc.clean()
water = Atoms('OHH',
positions=[(0, 0, 0), (1, 0, 0), (0, 1, 0)],
calculator=calc)
opt = LBFGS(water)
opt.run(fmax=0.05)
forces = water.get_forces()
energy = water.get_potential_energy()
positions = water.get_positions()
# Then test the IO routines
water2 = read('water.log')
forces2 = water2.get_forces()
energy2 = water2.get_potential_energy()
positions2 = water2.get_positions()
# Compare distances since positions are different in standard orientation.
dist = water.get_all_distances()
dist2 = read('water.log', index=-1).get_all_distances()
assert abs(energy - energy2) < 1e-7
assert abs(forces - forces2).max() < 1e-9
assert abs(positions - positions2).max() < 1e-6
assert abs(dist - dist2).max() < 1e-6
def __init__(self, calculator, params, max_iterations,
geometry_rmsd_manager):
self.params = params
self.max_iterations = max_iterations
self.calculator = calculator
self.geometry_rmsd_manager = geometry_rmsd_manager
self.ase_atoms = calculator.ase_atoms
self.ase_atoms.set_positions(flex.vec3_double(self.calculator.x))
self.opt = LBFGS(atoms=self.ase_atoms)
self.number_of_function_and_gradients_evaluations = 0
self.b_rmsd = self._get_bond_rmsd(
sites_cart=flex.vec3_double(self.calculator.x))
print(" step: %3d bond rmsd: %8.6f" %
(self.number_of_function_and_gradients_evaluations, self.b_rmsd))
self.run(nstep=max_iterations)
# Syncing and cross-checking begin
e = 1.e-4
assert approx_equal(self.ase_atoms.get_positions(),
self.opt.atoms.get_positions(), e)
self.calculator.update(x=self.opt.atoms.get_positions())
assert approx_equal(self.calculator.x, self.opt.atoms.get_positions(),
e)
if (params.refine.mode == "refine"):
assert approx_equal(
flex.vec3_double(self.calculator.x),
self.calculator.fmodel.xray_structure.sites_cart(), e)
else:
assert approx_equal(flex.vec3_double(self.calculator.x),
self.calculator.xray_structure.sites_cart(), e)
b_rmsd = self._get_bond_rmsd(
sites_cart=flex.vec3_double(self.calculator.x))
assert approx_equal(self.b_rmsd, b_rmsd, e)
def opt_emt_lbfgs(atoms):
from ase.calculators.emt import EMT
from ase.optimize.lbfgs import LBFGS
tmpAtoms = atoms.copy()
tmpAtoms.calc = EMT()
geomOpt = LBFGS(tmpAtoms, maxstep=0.1, trajectory=None, logfile=None)
geomOpt.run(fmax=0.01, steps=1000)
return tmpAtoms
def optimize(self, name, atoms):
mask = [t in self.constrain_tags for t in atoms.get_tags()]
if mask:
constrain = FixAtoms(mask=mask)
atoms.constraints = [constrain]
optimizer = LBFGS(atoms, trajectory=self.get_filename(name, ".traj"), logfile=None)
optimizer.run(self.fmax)
def optimize(self, name, atoms):
mask = [t in self.constrain_tags for t in atoms.get_tags()]
if mask:
constrain = FixAtoms(mask=mask)
atoms.constraints = [constrain]
optimizer = LBFGS(atoms,
trajectory=self.get_filename(name, '.traj'),
logfile=None)
optimizer.run(self.fmax)
def opt_xtb_lbfgs(atoms):
from xtb.ase.calculator import XTB
from ase.optimize.lbfgs import LBFGS
tmpAtoms = atoms.copy()
tmpAtoms.calc = XTB(method='GFN1-xTB')
geomOpt = LBFGS(
tmpAtoms,
maxstep=0.1,
trajectory=None,
# logfile=None
)
geomOpt.run(fmax=0.05, steps=400)
return tmpAtoms
class lbfgs_gradient(object):
def __init__(self, atoms, restraints):
self.restraints = restraints
self.opt = LBFGS(atoms=atoms)
def step(self):
pos = self.opt.atoms.get_positions()
sites_cart = flex.vec3_double(pos)
e, g = self.restraints.target_and_gradients(sites_cart)
forces = np.array(g) * -1
self.opt.step(forces)
def write(self, file):
write(file, self.opt.atoms)
def run(self, nstep):
for i in range(nstep):
self.step()
def test_gfn2xtb_lbfgs():
"""Perform geometry optimization with GFN2-xTB and L-BFGS"""
thr = 1.0e-5
atoms = Atoms(
symbols="NHCHC2H3OC2H3ONHCH3",
positions=np.array([
[1.40704587284727, -1.26605342016611, -1.93713466561923],
[1.85007200612454, -0.46824072777417, -1.50918242392545],
[-0.03362432532150, -1.39269245193812, -1.74003582081606],
[-0.56857009928108, -1.01764444489068, -2.61263467107342],
[-0.44096297340282, -2.84337808903410, -1.48899734014499],
[-0.47991761226058, -0.55230954385212, -0.55520222968656],
[-1.51566045903090, -2.89187354810876, -1.32273881320610],
[-0.18116520746778, -3.45187805987944, -2.34920431470368],
[0.06989722340461, -3.23298998903001, -0.60872832703814],
[-1.56668253918793, 0.00552120970194, -0.52884675001441],
[1.99245341064342, -1.73097165236442, -3.08869239114486],
[3.42884244212567, -1.30660069291348, -3.28712665743189],
[3.87721962540768, -0.88843123009431, -2.38921453037869],
[3.46548545761151, -0.56495308290988, -4.08311788302584],
[4.00253374168514, -2.16970938132208, -3.61210068365649],
[1.40187968630565, -2.43826111827818, -3.89034127398078],
[0.40869198386066, -0.49101709352090, 0.47992424955574],
[1.15591901335007, -1.16524842262351, 0.48740266650199],
[0.00723492494701, 0.11692276177442, 1.73426297572793],
[0.88822128447468, 0.28499001838229, 2.34645658013686],
[-0.47231557768357, 1.06737634000561, 1.52286682546986],
[-0.70199987915174, -0.50485938116399, 2.28058247845421],
]),
)
calc = XTB(method="GFN2-xTB", solvent="water", accuracy=0.1)
atoms.set_calculator(calc)
opt = LBFGS(atoms)
opt.run(fmax=0.1)
assert approx(atoms.get_potential_energy(), thr) == -897.4533662470938
assert approx(np.linalg.norm(atoms.get_forces(), ord=2),
thr) == 0.19359647527783497
def calculate(self, filename):
"""Run calculation and write results to file."""
self.log('Calculating', self.name, '...')
config = self.atoms.copy()
self.set_calculator(config, filename)
traj = PickleTrajectory(filename, 'w', backup=False)
cell = config.get_cell()
self.energies = []
if self.fmax is not None:
if (not config.constraints and
not config.positions.any(axis=1).all()):
# one atom is at (0,0,0) - fix it:
mask = np.logical_not(config.positions.any(axis=1))
config.constraints = FixAtoms(mask=mask)
dyn = LBFGS(config)
dyn.attach(traj, 1, config)
dyn.run(fmax=self.fmax)
e = config.get_potential_energy()
self.post_process(config)
self.energies.append(e)
elif not config.pbc.any() and len(config) == 2:
# This is a dimer.
self.bondlengths = []
d0 = config.get_distance(0, 1)
for strain in self.strains:
d = d0 * strain
config.set_distance(0, 1, d)
self.bondlengths.append(d)
e = config.get_potential_energy()
self.energies.append(e)
self.post_process(config)
traj.write(config)
else:
self.volumes = []
for strain in self.strains:
config.set_cell(strain * cell, scale_atoms=True)
self.volumes.append(config.get_volume())
e = config.get_potential_energy()
self.energies.append(e)
self.post_process(config)
traj.write(config)
return config
class minimizer_ase(object):
def __init__(self, calculator, params, max_iterations,
geometry_rmsd_manager):
self.params = params
self.max_iterations = max_iterations
self.calculator = calculator
self.geometry_rmsd_manager = geometry_rmsd_manager
self.ase_atoms = calculator.ase_atoms
self.ase_atoms.set_positions(flex.vec3_double(self.calculator.x))
self.opt = LBFGS(atoms=self.ase_atoms)
self.number_of_function_and_gradients_evaluations = 0
self.b_rmsd = self._get_bond_rmsd(
sites_cart=flex.vec3_double(self.calculator.x))
print(" step: %3d bond rmsd: %8.6f" %
(self.number_of_function_and_gradients_evaluations, self.b_rmsd))
self.run(nstep=max_iterations)
# Syncing and cross-checking begin
e = 1.e-4
assert approx_equal(self.ase_atoms.get_positions(),
self.opt.atoms.get_positions(), e)
self.calculator.update(x=self.opt.atoms.get_positions())
assert approx_equal(self.calculator.x, self.opt.atoms.get_positions(),
e)
if (params.refine.mode == "refine"):
assert approx_equal(
flex.vec3_double(self.calculator.x),
self.calculator.fmodel.xray_structure.sites_cart(), e)
else:
assert approx_equal(flex.vec3_double(self.calculator.x),
self.calculator.xray_structure.sites_cart(), e)
b_rmsd = self._get_bond_rmsd(
sites_cart=flex.vec3_double(self.calculator.x))
assert approx_equal(self.b_rmsd, b_rmsd, e)
# Syncing and cross-checking end
def _get_bond_rmsd(self, sites_cart):
b_mean = None
if (self.geometry_rmsd_manager is not None):
energies_sites = \
self.geometry_rmsd_manager.geometry.energies_sites(
sites_cart = sites_cart.select(s),
compute_gradients = False)
b_mean = energies_sites.bond_deviations()[2]
return b_mean
def step(self):
sites_cart = flex.vec3_double(self.opt.atoms.get_positions())
t, g = self.calculator.target_and_gradients(x=sites_cart)
forces = numpy.array(g) * (-1)
self.opt.step(forces)
self.number_of_function_and_gradients_evaluations += 1
self.calculator.update(x=self.opt.atoms.get_positions())
#
self.b_rmsd = self._get_bond_rmsd(
sites_cart=flex.vec3_double(self.opt.atoms.get_positions()))
print(" step: %3d bond rmsd: %8.6f" %
(self.number_of_function_and_gradients_evaluations, self.b_rmsd))
if (self.params.refine.mode == "refine"
and self.b_rmsd > self.params.refine.max_bond_rmsd
and self.number_of_function_and_gradients_evaluations > 20):
return False
#
return True
def run(self, nstep):
for i in range(nstep):
v = self.step()
if (not v): return
from ase.optimize.lbfgs import LBFGS
from ase.constraints import StrainFilter, UnitCellFilter
from ase.io import PickleTrajectory
from ase.optimize.lbfgs import LBFGS
from ase.optimize.mdmin import MDMin
try:
from asap3 import EMT
except ImportError:
pass
else:
a = 3.6
b = a / 2
cu = Atoms('Cu', cell=[(0, b, b), (b, 0, b), (b, b, 0)], pbc=1) * (6, 6, 6)
cu.set_calculator(EMT())
f = UnitCellFilter(cu, [1, 1, 1, 0, 0, 0])
opt = LBFGS(f)
t = PickleTrajectory('Cu-fcc.traj', 'w', cu)
opt.attach(t)
opt.run(5.0)
# HCP:
from ase.lattice.surface import hcp0001
cu = hcp0001('Cu', (1, 1, 2), a=a / sqrt(2))
cu.cell[1, 0] += 0.05
cu *= (6, 6, 3)
cu.set_calculator(EMT())
print cu.get_forces()
print cu.get_stress()
f = UnitCellFilter(cu)
opt = MDMin(f, dt=0.01)
t = PickleTrajectory('Cu-hcp.traj', 'w', cu)
from ase.optimize.lbfgs import LBFGS
# First test to make sure Gaussian works
calc = Gaussian(method='pbepbe',
basis='sto-3g',
force='force',
nproc=1,
chk='water.chk',
label='water')
calc.clean()
water = Atoms('OHH',
positions=[(0, 0, 0), (1, 0, 0), (0, 1, 0)],
calculator=calc)
opt = LBFGS(water)
opt.run(fmax=0.05)
forces = water.get_forces()
energy = water.get_potential_energy()
positions = water.get_positions()
# Then test the IO routines
from ase.io import read
water2 = read('water.log')
forces2 = water2.get_forces()
energy2 = water2.get_potential_energy()
positions2 = water2.get_positions()
#compare distances since positions are different in standard orientation
dist = water.get_all_distances()
dist2 = read('water.log', quantity='structures')[-1].get_all_distances()
import sys
from ase.io import read, write
from ase.units import Hartree
from ase.optimize.lbfgs import LBFGS
from xtb.ase.calculator import XTB
from ase.db import connect
inpName = sys.argv[1]
slab = read(inpName)
slab.calc = XTB(method='GFN1-xTB', max_iterations=1000)
relax = LBFGS(
slab,
maxstep=0.1,
# logfile=None,
# trajectory='ase.traj'
)
relax.run(fmax=0.05)
# get the final single point energy
e = slab.get_potential_energy()
print("Final energy: eV, Eh", e, e/Hartree)
# write final geometry to file
write('out-'+inpName, slab)
from pyscf import gto, scf, grad, mp
import numpy as np
import matplotlib.pyplot as plt
# Read initial and final states:
print(" -> read xyz")
initial = io.read('react.xyz')
final = io.read('prod.xyz')
initial.set_calculator(PySCF_simple(initial, method='MP2', basis='6-31g*'))
final.set_calculator(PySCF_simple(final, method='MP2', basis='6-31g*'))
print(" -> opt react prod")
dyn_react = LBFGS(initial)
dyn_react.run(fmax=0.05)
#
dyn_prod = LBFGS(final)
dyn_prod.run(fmax=0.05)
# write output geometries of GO
io.write("initial.xyz", initial)
io.write("final.xyz", final)
# Make a band consisting of N images:
images = [initial]
images += [initial.copy() for i in range(17)]
images += [final]
print(" -> set calculator")
from gpaw import GPAW, Mixer, FermiDirac
tag = 'Ru001_Ru8'
adsorbate_heights = {'H': 1.0, 'N': 1.108, 'O': 1.257}
slab = hcp0001('Ru', size=(2, 2, 4), a=2.72, c=1.58*2.72, vacuum=7.0,
orthogonal=True)
slab.center(axis=2)
if len(argv) > 1:
adsorbate = argv[1]
tag = adsorbate + tag
add_adsorbate(slab, adsorbate, adsorbate_heights[adsorbate], 'hcp')
slab.set_constraint(FixAtoms(mask=slab.get_tags() >= 3))
calc = GPAW(xc='PBE',
h=0.2,
mixer=Mixer(0.1, 5, weight=100.0),
stencils=(3, 3),
occupations=FermiDirac(width=0.1),
kpts=[4, 4, 1],
setups={'Ru': '8'},
txt=tag + '.txt')
slab.set_calculator(calc)
opt = LBFGS(slab, logfile=tag + '.log', trajectory=tag + '.traj')
opt.run(fmax=0.05)
calc.write(tag)
from ase.optimize.lbfgs import LBFGS
from ase.constraints import StrainFilter, UnitCellFilter
from ase.io import Trajectory
from ase.optimize.lbfgs import LBFGS
from ase.optimize.mdmin import MDMin
try:
from asap3 import EMT
except ImportError:
pass
else:
a = 3.6
b = a / 2
cu = Atoms('Cu', cell=[(0,b,b),(b,0,b),(b,b,0)], pbc=1) * (6, 6, 6)
cu.set_calculator(EMT())
f = UnitCellFilter(cu, [1, 1, 1, 0, 0, 0])
opt = LBFGS(f)
t = Trajectory('Cu-fcc.traj', 'w', cu)
opt.attach(t)
opt.run(5.0)
# HCP:
from ase.lattice.surface import hcp0001
cu = hcp0001('Cu', (1, 1, 2), a=a / sqrt(2))
cu.cell[1,0] += 0.05
cu *= (6, 6, 3)
cu.set_calculator(EMT())
print(cu.get_forces())
print(cu.get_stress())
f = UnitCellFilter(cu)
opt = MDMin(f,dt=0.01)
t = Trajectory('Cu-hcp.traj', 'w', cu)
adsorbate_heights = {'H': 1.0, 'N': 1.108, 'O': 1.257}
slab = hcp0001('Ru',
size=(2, 2, 4),
a=2.72,
c=1.58 * 2.72,
vacuum=7.0,
orthogonal=True)
slab.center(axis=2)
if len(argv) > 1:
adsorbate = argv[1]
tag = adsorbate + tag
add_adsorbate(slab, adsorbate, adsorbate_heights[adsorbate], 'hcp')
slab.set_constraint(FixAtoms(mask=slab.get_tags() >= 3))
calc = GPAW(xc='PBE',
h=0.2,
mixer=Mixer(0.1, 5, weight=100.0),
stencils=(3, 3),
occupations=FermiDirac(width=0.1),
kpts=[4, 4, 1],
setups={'Ru': '8'},
txt=tag + '.txt')
slab.set_calculator(calc)
opt = LBFGS(slab, logfile=tag + '.log', trajectory=tag + '.traj')
opt.run(fmax=0.05)
calc.write(tag)
def __init__(self, atoms, restraints):
self.restraints = restraints
self.opt = LBFGS(atoms=atoms)
