def viewStructs(name, directory, kind = 'gen'):
"""
View collection of structures as a "trajectory"
Args:
- name (str): substring unique to structures (.gen, POSCAR, slab, etc)
- directory (str): Directory where the structures live
- kind: kind of output froim list of (vasp, gen)
Opens viewer with loaded trajectory (if remote, need X server)
"""
geometries = []
files = os.listdir(directory)
if kind == 'gen':
pattern = r"{}.*.gen".format(name)
elif kind == 'vasp':
pattern = r"{}".format(name)
else:
raise ValueError("file kind must be from (vasp, gen)")
for i in files:
key = re.search(pattern, i)
if key:
if kind == 'gen':
geometries += [gen.read_gen(directory + i)]
elif kind == 'vasp':
geometries += [vasp.read_vasp(directory + i)]
else:
raise ValueError("file kind must be from (vasp, gen)")
view(geometries)
def getabBondcountStructure(data, idx, element):
"""
Gets a struture with 'charges' equal to nbonds between a (fixed) and b(``element``)
data needs geom, coordlabels, and (optionally) wantedIndices columns
geom is Atoms object of structure
coordlabels is a raw output from the coordlabeller function (relcoords and raw bonds)
element is desired secondary element (primary element determined by input)
Calls view() on resulting geometry
Returns the structure
"""
coordlabels = data.loc[idx, 'coordlabels']
geometry = data.loc[idx, 'geom']
if 'wantedIndices' in data:
indices = data.loc[idx, 'wantedIndices']
else:
indices = np.arange(len(geometry))
bondcounts = {key: np.sum(
np.array([geometry[i].symbol for i in value]) == element
) for key, value in
pd.Series(coordlabels[1])[indices].items()
}
charges = [0] * len(geometry)
for i in range(len(charges)):
charges[i] = bondcounts.get(i, -1)
geometry.set_initial_charges(charges)
view(geometry)
return geometry
def test_03():
lammps_setting = {'data_lmp':'data.lmp',
'in_lmp':'in.min',
'lammps_exe' :'/opt/lmpizarro/GitHub/lammps/src/lmp_serial'}
setting ={'elements':['Al', 'Fe'], 'pot':'zhou', \
'pca':[20], 'nAtoms':250,\
#'structure':'bcc',\
#'positions':'rnd','a':3.0, 'period':[5,5,5]}
'structure':'rnd',\
'positions':'rnd','a':4.2, 'period':[5,5,5],\
'lammps_setting':lammps_setting }
sys = System(setting)
print sys.setting['elements']
print sys.setting['nAt']
print sys.setting['pca']
print 'atoms', sys.elsProps
print 'bulk', sys.bulk
view(sys.bulk)
print sys.Interaction()
def test_replay(testdir):
# Distance between Cu atoms on a (100) surface:
d = 3.6 / sqrt(2)
a = Atoms('Cu',
positions=[(0, 0, 0)],
cell=(d, d, 1.0),
pbc=(True, True, False))
a *= (2, 2, 1) # 2x2 (100) surface-cell
# Approximate height of Ag atom on Cu(100) surfece:
h0 = 2.0
a += Atom('Ag', (d / 2, d / 2, h0))
if 0:
view(a)
constraint = FixAtoms(range(len(a) - 1))
a.calc = EMT()
a.set_constraint(constraint)
with QuasiNewton(a, trajectory='AgCu1.traj', logfile='AgCu1.log') as dyn1:
dyn1.run(fmax=0.1)
a = read('AgCu1.traj')
a.calc = EMT()
print(a.constraints)
with QuasiNewton(a, trajectory='AgCu2.traj', logfile='AgCu2.log') as dyn2:
dyn2.replay_trajectory('AgCu1.traj')
dyn2.run(fmax=0.01)
def viewSuperCell(atoms):
P = build.find_optimal_cell_shape_pure_python(atoms.cell, 32, "sc")
atoms = build.make_supercell(atoms, P)
atoms[0].symbol = "Mg"
atoms[1].symbol = "Mg"
atoms[2].symbol = "Mg"
view(atoms, viewer="Avogadro")
def main():
cif_dir = "//data/GOO.cif"
zeolite = Zeotype.build_from_cif_with_labels(cif_dir)
view(zeolite)
iz = zeolite.get_imperfect_zeotype()
iz = iz.create_silanol_defect(95)
view(iz)
def main( uid ):
db_name = "ce_hydrostatic.db"
db_name = "almg_217.db"
db = connect( db_name )
atoms = db.get_atoms( id=uid )
print ( "Chemical formula {}".format(atoms.get_chemical_formula()) )
view(atoms)
def create_relaxed_Na_cluster(N, view=False):
print(f'************ Na{N} ************')
start = time.time()
#**** Initialize system ****#
if N==6:
clust = Atoms('Na'*6, positions=[(1,1,0),(1,-1,0),(-1,-1,0),(-1,1,0),(0,0,1),(0,0,-1)], cell=(d, d, d))
else:
clust = Atoms('Na'*N, positions=[np.random.randn(3) for i in range(N)], cell=(d, d, d)) # random initialization
clust.center()
if view:
view(clust)
#**** Define the calculator ****#
calc = GPAW(nbands=10,
h=0.25,
txt=f'Na{N}_out.txt',
occupations=FermiDirac(0.05),
setups={'Na': '1'},
mode='lcao',
basis='dzp')
#**** Relax the system ****#
clust.set_calculator(calc)
dyn = GPMin(clust, trajectory=f'Na{N}_relax_clust.traj', logfile='Na{N}_relax_clust.log')
print(f'**** Relaxing system of {N} atoms ****')
dyn.run(fmax=0.02, steps=100)
#**** Calculate energy and wavefunction ****#
e = clust.get_potential_energy() # Note opposite signa from ga.py
e_file = open(f'Na{N}_e_cluster.txt', 'w')
print(f'Na{N} cluster energy: {e} eV', file=e_file)
calc.write(f'Na{N}_cluster.gpw', mode='all')
end = time.time()
print(f'**** Elapsed time: {end-start} s ****')
print('*****************************\n')
def view_all():
a = 4.05
c = 6.0
cell = [[2.0 * a, 0, 0], [0.0, np.sqrt(3) * a, 0.0], [0.0, 0.0, c]]
hcp_sites = [
[a / 2.0, 0.0, 0.0], [3.0 * a / 2.0, 0.0, 0.0],
[0.0, np.sqrt(3.0) * a / 2.0, 0.0],
[2.0 * a, np.sqrt(3.0) * a / 2.0,
0.0], [a / 2.0, np.sqrt(3.0) * a,
0.0], [3.0 * a / 2.0, np.sqrt(3.0) * a, 0.0],
[a, np.sqrt(3.0) * a / 2.0,
0.0], [a, a * (0.5 * np.sqrt(3) - 1 / np.sqrt(3.0)), c / 2.0],
[a / 2.0, 0.5 * a * (np.sqrt(3) + 1.0 / np.sqrt(3.0)), c / 2.0],
[3.0 * a / 2.0, 0.5 * a * (np.sqrt(3) + 1.0 / np.sqrt(3.0)), c / 2.0]
]
bcc_sites = [[0.0, 0.0, 0.0], [2.0 * a, 0.0, 0.0],
[0.0, np.sqrt(3.0) * a, 0.0],
[2.0 * a, np.sqrt(3.0) * a, 0.0],
[a, 0.5 * np.sqrt(3) * a, c / 2.0]]
hcp_symbs = ["V" for _ in range(len(hcp_sites))]
bcc_symbs = ["Si" for _ in range(len(bcc_sites))]
symbs = hcp_symbs + bcc_symbs
sites = hcp_sites + bcc_sites
atoms = Atoms(symbs, sites)
atoms.set_cell(cell)
view(atoms)
def test_adsorbate_placer():
from ase.io import read
from ase.build import molecule
import numpy as np
from carmm.build.adsorbate_placer import place_adsorbate, rotate_and_place_adsorbate
from ase import Atoms
molecule = molecule('CH3CH2OH')
h_atom = Atoms('H', positions=[(0, 0, 0)])
site = read("data/H-Y_cluster/H-Y_cluster.xyz")
zeolite, rotated_ads = place_adsorbate(h_atom, site, 0, 0, 1.0)
ads_and_site, rotated_ads = rotate_and_place_adsorbate(
molecule, zeolite, 1.0, 2, 0, 0, rotation=[-45, 0, -45])
comp_pos1 = np.array([2.00311656e+01, 5.31509397e+00, 1.89702619e+00])
comp_pos2 = np.array([2.04405930e+01, 4.53669268e+00, 2.54385921e+00])
error_pos1 = np.linalg.norm(comp_pos1 - rotated_ads.positions[0], axis=-1)
error_pos2 = np.linalg.norm(comp_pos2 - rotated_ads.positions[-1], axis=-1)
assert np.isclose(error_pos1, 0, rtol=0,
atol=1e-06), f"Error = {error_pos1}"
assert np.isclose(error_pos2, 0, rtol=0,
atol=1e-06), f"Error = {error_pos2}"
from ase.visualize import view
view(ads_and_site)
def open_file(self):
# select a file name in the selected folder :
name = askopenfilename(initialdir=self.dirname)
try:
datatype = name.split('.')[-1]
except:
datatype = 'error'
# text files
if datatype == 'txt' or datatype == 'dat' or datatype == 'out' or name.find(
'README') != -1:
with open(name, 'r') as UseFile:
s = UseFile.read()
self.text.delete("1.0", "end")
self.text.insert(END, s)
self.text.pack()
#self.display.pack()
#self.text.grid(column=0,row=0)
#self.columnconfigure(1, weight=1)
#self.columnconfigure(3, pad=7)
#self.rowconfigure(3, weight=1)
#self.rowconfigure(5, pad=7)
#self.text.grid(row=0, columnspan=2, rowspan=4,padx=5, sticky=E+W+S+N)
#self.display.grid(row=0, columnspan=2, rowspan=4,padx=5, sticky=E+W+S+N)
self.text.update()
self.newwin.update()
self.newwin.deiconify()
# material structural formats using ase
if datatype == 'xyz' or datatype == 'cif':
struct = read(name)
view(struct)
def convert_to_cubic(setting_prim):
conc_args = {
"conc_ratio_min_1":[[64,0,0]],
"conc_ratio_max_1":[[24,40,0]],
"conc_ratio_min_2":[[64,0,0]],
"conc_ratio_max_2":[[22,21,21]]
}
setting_cubic = BulkCrystal( crystalstructure="fcc", a=4.05, size=[3,3,3], basis_elements=[["Mg","Si","Al",]], \
conc_args=conc_args, db_name=db_name_cubic, max_cluster_size=4, cubic=True )
view(setting_cubic.atoms)
atoms = setting_prim.atoms.copy()
a = 4.05
atoms.set_cell([[4*a,0,0],[0,4*a,0],[0,0,4*a]])
atoms.wrap()
view(atoms)
print (setting_prim.atoms.get_cell())
exit()
out_file = "data/temp_out.xyz"
target_cell = setting_cubic.atoms.get_cell()
cubic_str_gen = struc_generator = GenerateStructures( setting_cubic, struct_per_gen=10 )
db = connect(db_name)
for row in db.select(converged=1):
energy = row.energy
atoms = row.toatoms()
atoms.set_cell(target_cell)
atoms.wrap()
write(out_file,atoms)
calc = SinglePointCalculator(atoms,energy=energy)
atoms.set_calculator(calc)
cubic_str_gen.insert_structure(init_struct=out_file,final_struct=atoms)
def prebeta_spacegroup(n_template_structs=0):
atoms = bulk("Al", cubic=True)
# Add one site at the center
L = atoms.get_cell()[0,0]
at = Atoms( "X", positions=[[L/2,L/2,L/2]] )
atoms.extend(at)
view(atoms)
sp_gr = get_spacegroup(atoms)
print(sp_gr)
print(atoms.get_scaled_positions())
sc = atoms*(6,6,6)
jump_moves = CollectiveJumpMove(mc_cell=sc)
jump_moves.view_columns()
temp_atoms = atoms*(2,2,2)
print(len(temp_atoms))
view(temp_atoms)
if n_template_structs > 0:
symbs = ["Al","Mg","Si"]
for i in range(n_template_structs):
atoms = bulk("Al",cubic=True,a=4.05)
selection = [symbs[randint(low=0,high=3)] for _ in range(len(atoms))]
for indx in range(len(atoms)):
atoms[indx].symbol = selection[indx]
at = Atoms( "X", positions=[[L/2,L/2,L/2]] )
atoms.extend(at)
atoms = atoms*(2,2,2)
fname = "data/prebeta_template{}.xyz".format(i)
write(fname,atoms)
print("Template structure written to {}".format(fname))
def remove_CO(CONTCAR_filename, view_flag=True):
'''
Read the old CONTCAR file with a CO onto it
remove the CO and save as a new CONTCAR
'''
old_name = CONTCAR_filename #'pd20-ceria-co-CONTCAR'
atoms = read(old_name)
# find number of Pd
# find C atom index
nPd = 0
for i, atom in enumerate(atoms):
if atom.symbol == 'Pd':
nPd = nPd + 1
if atom.symbol == 'C':
C_in_CO = i
C_O_Dist = []
O_in_CO = []
for k, atom in enumerate(atoms):
if atom.symbol == 'O':
dist = atoms.get_distance(C_in_CO, k)
C_O_Dist.append(dist)
O_in_CO.append(k)
O_in_CO = O_in_CO[C_O_Dist.index(min(C_O_Dist))]
del atoms[[O_in_CO, C_in_CO]]
write('pd' + str(nPd) + '-no-CO-CONTCAR', atoms)
# View the atom object if the flag is true
if view_flag:
view(atoms)
def plot_neb(self, show=True):
'''
retrieve the energies and atoms from the band
by default shows the plot figure
'''
import jasp
try:
images, energies = self.get_neb()
except (jasp.VaspQueued):
# let's get a snapshot of the progress
calc = read_neb_calculator()
images = calc.neb_images
energies = []
energies += [float(open('00/energy').readline())]
for i in range(1,len(images)-1):
f = open('0{0}/OUTCAR'.format(i))
elines = []
for line in f:
if 'energy w' in line:
elines += [line]
f.close()
# take last line
fields = elines[-1].split()
energies += [float(fields[-1])]
energies += [float(open('0{0}/energy'.format(len(images)-1)).readline())]
energies = np.array(energies) - energies[0]
# add fitted line to band energies. we make a cubic spline
# interpolating function of the negative energy so we can find the
# minimum which corresponds to the barrier
from scipy.interpolate import interp1d
from scipy.optimize import fmin
f = interp1d(range(len(energies)),
-energies,
kind='cubic', bounds_error=False)
x0 = len(energies)/2. #guess barrier is at half way
xmax = fmin(f, x0)
xfit = np.linspace(0,len(energies)-1)
bandfit = -f(xfit)
import matplotlib.pyplot as plt
p = plt.plot(energies-energies[0],'bo ',label='images')
plt.plot(xfit, bandfit,'r-',label='fit')
plt.plot(xmax,-f(xmax),'* ',label='max')
plt.xlabel('Image')
plt.ylabel('Energy (eV)')
s = ['$\Delta E$ = {0:1.3f} eV'.format(float(energies[-1]-energies[0])),
'$E^\ddag$ = {0:1.3f} eV'.format(float(-f(xmax)))]
plt.title('\n'.join(s))
plt.legend(loc='best', numpoints=1)
if show:
from ase.visualize import view
view(images)
plt.show()
return p
def __getitem__(self, name):
d = self.data[name]
# the index of label in labels less one
# (compound is already as key in d)
a = d[self.labels.index("aexp") - 1]
if name in ["Cr2CoGa", "Mn2CoAl", "Mn2CoGe", "Fe2CoSi"]:
# http://en.wikipedia.org/wiki/Space_group
sg = 216
else:
sg = 225
symbols = string2symbols(name)
symbols.pop(0)
b = crystal(
symbols=symbols,
basis=[(1.0 / 4, 1.0 / 4, 1.0 / 4), (0.0, 0.0, 0.0), (1.0 / 2, 1.0 / 2, 1.0 / 2)],
spacegroup=sg,
cellpar=[a, a, a, 90, 90, 90],
primitive_cell=True,
)
# set average moments on all atoms (add + 2.0)
magmom = d[self.labels.index("mexp") - 1] + 2.0
m = [magmom / len(b)] * len(b)
# break spin symmetry between atoms no. 1 and 2
m[1] = m[1] + m[2]
m[2] = -m[2]
b.set_initial_magnetic_moments(m)
if 0:
from ase.visualize import view
view(b)
return b
def _import_ase(filename, **kwargs):
"""
Imports a structure in a number of formats using the ASE routines.
"""
from os.path import abspath
from aiida.orm.data.structure import StructureData
try:
import ase.io
except ImportError:
echo.echo_critical("You have not installed the package ase. \n"
"You can install it with: pip install ase")
store = kwargs.pop('store')
view_in_ase = kwargs.pop('view')
echo.echo('importing structure from: \n {}'.format(abspath(filename)))
filepath = abspath(filename)
try:
asecell = ase.io.read(filepath)
new_structure = StructureData(ase=asecell)
if store:
new_structure.store()
if view_in_ase:
from ase.visualize import view
view(new_structure.get_ase())
echo.echo(' Succesfully imported structure {}, '
'(PK = {})'.format(new_structure.get_formula(),
new_structure.pk))
except ValueError as err:
echo.echo_critical(err)
def main():
aluminum = build.bulk("Al", crystalstructure="fcc") * 4
print(len(aluminum))
# Extract 3 111 planes
planes = build.cut(aluminum, (1, -1, 0), (1, 1, -2), nlayers=3)
view(planes, viewer="Avogadro")
def _import_pwi(filename, **kwargs):
"""
Imports a structure from a quantumespresso input file.
"""
from os.path import abspath
try:
from qe_tools.parsers.pwinputparser import PwInputFile
except ImportError:
echo.echo_critical("You have not installed the package qe-tools. \n"
"You can install it with: pip install qe-tools")
store = kwargs.pop('store')
view_in_ase = kwargs.pop('view')
echo.echo('importing structure from: \n {}'.format(abspath(filename)))
filepath = abspath(filename)
try:
inputparser = PwInputFile(filepath)
new_structure = inputparser.get_structuredata()
if store:
new_structure.store()
if view_in_ase:
from ase.visualize import view
view(new_structure.get_ase())
echo.echo(' Succesfully imported structure {}, '
'(PK = {})'.format(new_structure.get_formula(),
new_structure.pk))
except ValueError as err:
echo.echo_critical(err)
def main1():
traj = read('MFI_2Al_replaced.traj', ':')
traj_CuOCu = []
for atoms in traj:
inserted_atoms = insert_CuOCu(atoms)
traj_CuOCu.append(inserted_atoms)
view(traj_CuOCu)
def view_avo(atoms):
from ase.visualize import view
if atoms._calc and atoms.calc.__module__ == 'gausspy.gaussian':
os.system("avogadro {f}".format(f=atoms.calc.label + '.log'))
else:
print('Viewing xyz file')
view(atoms,viewer='avogadro')
def chemical_potential_sweep(ceBulk, eci, chem_pots=None):
solver = Solver(ceBulk, eci, verbose=True, chem_pot={"Mg": 0.0})
ceBulk.atoms[0].symbol = "Mg"
model = solver.get_model()
if (not chem_pots is None):
for chem in chem_pots:
print("Current: chemical potential {}".format(chem))
solver.update_chemical_potentials(model, {"Mg": chem})
solver.solve("gurobi", model)
view(ceBulk.atoms)
else:
lower = 0.0
upper = 0.1
# Find upper and lower bounds for pure phase
for i in range(0, 100):
current = (lower + upper) / 2.0
model = solver.update_chemical_potentials(model, {"Mg": current})
# Bisection
solver.solve("gurobi", model)
elms = solver.get_atoms_count()
if (elms["Mg"] >= 32):
lower = current
else:
upper = current
if (elms["Mg"] < 64 and elms["Mg"] > 16):
break
view(ceBulk.atoms)
print(lower, upper)
def view_avo(atoms):
from ase.visualize import view
if atoms._calc and atoms.calc.__module__ == 'gausspy.gaussian':
os.system("avogadro {f}".format(f=atoms.calc.label + '.log'))
else:
print('Viewing xyz file')
view(atoms, viewer='avogadro')
def addAdsorbate(constraint="1"):
constrnts = AND(COMPLETED, RELAX, SURFACE, SYMMETRIC(False), constraint)
ads = {'H': ['O1']}
output = db.query(['fwid', 'params_json', 'finaltraj_pckl'], constrnts)
question = 'Are you sure you want to add adsorbates to %d slabs?' % len(
output)
if ask(question):
for fw, paramStr, ftraj in output:
params = json.loads(paramStr)
newsurf = surfFuncs.adsorbedSurface(
ftraj, json.loads(params['facet_json']), ads)
if jobs.Job(params).spinpol():
newsurf.set_initial_magnetic_moments([
3 if e in misc.magElems else 0
for e in newsurf.get_chemical_symbols()
])
ase.visualize.view(newsurf)
params['name'] += '_' + printAds(ads)
params['surfparent'] = fw
params['inittraj_pckl'] = pickle.dumps(newsurf)
params['adsorbates_json'] = json.dumps(ads)
job = jobs.Job(params)
if job.new():
viz.view(newsurf)
question = 'Does this structure look right?\n' + abbreviateDict(
params)
if ask(question):
job.check()
job.submit()
misc.launch()
def wan(calc):
centers = [([0.125, 0.125, 0.125], 0, 1.5),
([0.125, 0.625, 0.125], 0, 1.5),
([0.125, 0.125, 0.625], 0, 1.5),
([0.625, 0.125, 0.125], 0, 1.5)]
w = Wannier(4, calc,
nbands=4,
verbose=False,
initialwannier=centers)
w.localize()
x = w.get_functional_value()
centers = (w.get_centers(1) * k) % 1
c = (centers - 0.125) * 2
#print w.get_radii() # broken! XXX
assert abs(c.round() - c).max() < 0.03
c = c.round().astype(int).tolist()
c.sort()
assert c == [[0, 0, 0], [0, 0, 1], [0, 1, 0], [1, 0, 0]]
if 0:
from ase.visualize import view
from ase import Atoms
watoms = calc.atoms + Atoms(symbols='X4',
scaled_positions=centers,
cell=calc.atoms.cell)
view(watoms)
return x
def hilighter(event):
# if we did not hit a node, bail
if not hasattr(event, 'nodes') or not event.nodes:
return
# pull out the graph,
graph = event.artist.graph
# clear any non-default color on nodes
for node, attributes in graph.nodes.data():
attributes.pop('color', None)
for u, v, attributes in graph.edges.data():
attributes.pop('width', None)
for node in event.nodes:
graph.nodes[node]['color'] = 'C1'
#print(node)
for edge_attribute in graph[node].values():
edge_attribute['width'] = 3
# update the screen
event.artist.stale = True
event.artist.figure.canvas.draw_idle()
print(event.nodes)
simulation_id = event.nodes[0]
simulation = simulations[str(simulation_id)]
pp(simulation)
print("simulation id", simulation_id)
atoms = atoms_dict_to_ase(simulation["atoms"])
view(atoms)
def test_diag_symmetries():
total_path = os.path.dirname(os.path.abspath(__file__))
os.chdir(total_path)
# Diagonalize the dynamical matrix in the supercell
dyn = CC.Phonons.Phonons("../TestDiagonalizeSupercell/prova", 4)
w, p = dyn.DiagonalizeSupercell()
view(dyn.structure.get_ase_atoms())
# Get the symmetries
supercell_s = dyn.structure.generate_supercell(dyn.GetSupercell())
spglib_syms = spglib.get_symmetry(dyn.structure.get_ase_atoms())
syms = CC.symmetries.GetSymmetriesFromSPGLIB(spglib_syms)
# Get the symmetries on the polarization vectors
pols_syms = CC.symmetries.GetSymmetriesOnModes(syms, supercell_s, p)
# Now complete the diagonalization of the polarization vectors
# To fully exploit symmetries
new_pols, syms_character = CC.symmetries.get_diagonal_symmetry_polarization_vectors(p, w, pols_syms)
# TODO: Test if these new polarization vectors really rebuild the dynamical matrix
# write the symmetry character
n_modes, n_syms = syms_character.shape
for i in range(n_modes):
print("Mode {} | ".format(i), np.angle(syms_character[i,:], deg = True))
def show_stable(ids):
atoms = []
db = connect(sa_db)
for i in ids:
atoms.append(db.get(id=int(i)).toatoms())
view(atoms)
def test_cap_atom(self):
with self.subTest(msg="test hydrogen capping"):
iz = Zeolite(
Atoms('OSiOSi',
positions=[[0, 0, 0], [0, 0, -1], [0, 0, 1], [1, 1, 1]]))
iz = iz.delete_atoms(2) # delete Si
iz = iz.cap_atoms()
x = 0
# self.assertEqual(len(iz), 3)
for atom in iz:
if atom.symbol == "H":
pass
# self.assertTrue(np.all(atom.position == np.array([0, 0, 1])))
if atom.symbol == "O":
pass
# self.assertTrue(np.all(atom.position == np.array([0, 0, -1])))
with self.subTest('oxygen and hydrogen capping'):
cha = Zeolite.make('CHA')
cha = cha.delete_atoms([i for i in range(0, 10)])
for atom in cha:
if atom.symbol == 'O':
atom.symbol = 'Po'
cha = cha.cap_atoms()
view(cha)
def plot(self, out_folder='.', unit_cell='POSCAR', code_name='vasp'):
try:
from ase.io.trajectory import Trajectory
from ase.io import read, iread
from ase.visualize import view
except ImportError:
raise ImportError(
"\nThe parent directory of ase package must be included in 'sys.path'"
)
if code_name == 'espresso':
code_name = 'espresso-in' # aims, espresso-in, vasp
atom = read(unit_cell, format=code_name)
_current_position_true = atom.positions.copy()[
self.process.unit_cell.atom_true]
_mass_weight = self.process.unit_cell.mass_true.reshape(
(-1, 3)) / self.process.unit_cell.mass_true.max()
for mode_ind in self.mode_inds:
traj = Trajectory(
out_folder + "/Trajectory_{0}.traj".format(mode_ind), 'w')
for ind, x in enumerate(
np.linspace(0, 2 * np.pi, self.num_images, endpoint=False),
1):
atom.positions[self.process.unit_cell.atom_true] = _current_position_true \
+ np.sin(x) * self.mode[mode_ind, :].reshape((-1, 3)).real / np.sqrt(_mass_weight)
traj.write(atom)
traj.close()
atoms = iread(out_folder + "/Trajectory_{0}.traj".format(mode_ind))
view(atoms)
def main():
database = "aluminum.db"
# Parse parameters from the database
con = sqdb.connect(database)
cur = con.cursor()
cur.execute(
"SELECT VIEW,CUTOFF,KPTS,LATTICEPARAM,_rowid_,STRUCTURE FROM PARAMS WHERE STATUS=?",
("RUN", ))
jobs = cur.fetchall()
con.close()
print(jobs)
for job in jobs:
stamp = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
structure = job[5]
a = job[3]
show = job[0]
b = a / 2.0
if (structure == "FCC"):
bulk = Atoms("Al",
cell=[[0, b, b], [b, 0, b], [b, b, 0]],
pbc=True)
elif (structure == "BCC"):
bulk = Atoms("Al",
cell=[[b, b, b], [b, b, -b], [b, -b, b]],
pbc=True)
else:
print("Unknown lattice type")
continue
if (show == 1):
view(bulk)
calcfile = "data/alum" + structure + stamp + ".txt"
cutoff = job[1]
k = job[2]
calc = gp.GPAW(mode=gp.PW(cutoff),
kpts=(k, k, k),
txt=calcfile,
xc="LDA")
bulk.set_calculator(calc)
energy = bulk.get_potential_energy()
gpwfile = "data/alum" + structure + stamp + ".gpw"
calc.write(gpwfile)
# Update the database
aseDB = db.connect(database)
lastID = aseDB.write(bulk)
con = sqdb.connect(database)
cur = con.cursor()
row = int(job[4])
cur.execute(
"UPDATE PARAMS SET GPWFILE=?,TXTFILE=?,STATUS=?,ID=? WHERE _rowid_=?",
(gpwfile, calcfile, "FINISHED", lastID, row))
con.commit()
con.close()
def main(argv):
fname = argv[0]
with open(fname, 'r') as infile:
data = json.load(infile)
pickle_name = fname.split(".")[0] + ".pkl"
pickle_name = "data/bc_10x10x10_linvib.pkl"
with open(pickle_name, 'rb') as infile:
bc, cf, eci = pck.load(infile)
# Plot heat capacities
gr_spec = {"hspace": 0.0}
fig, ax = plt.subplots(nrows=2, sharex=True, gridspec_kw=gr_spec)
colors = [
'#a6cee3', '#1f78b4', '#b2df8a', '#33a02c', '#fb9a99', '#e31a1c',
'#fdbf6f', '#ff7f00', '#cab2d6'
]
counter = 0
mu = []
max_T = []
max_conc = []
for key, value in data.iteritems():
value = sort_based_on_temp(value)
color = colors[counter % len(colors)]
mu.append(value["mu_c1_0"])
U = np.array(value["energy"]) * mol / (len(bc.atoms) * kJ)
energy_interp = UnivariateSpline(value["temperature"], U, k=3, s=1)
ax[0].plot(value["temperature"], U, "o", mfc="none", color=color)
T = np.linspace(np.min(value["temperature"]),
np.max(value["temperature"]), 500)
ax[0].plot(T, energy_interp(T), color=color)
singl = np.array(value["singlet_c1_0"])
x = 0.5 * (1.0 + singl)
ax[1].plot(value["temperature"],
x,
label="{}".format(value["mu_c1_0"]),
color=color,
marker="o",
mfc="none")
counter += 1
#indx_max = np.argmax( Cv(T) )
#max_T.append( T[indx_max] )
#interp_conc = UnivariateSpline( value["temperature"], x, k=3, s=1 )
#x_interp = interp_conc(T)
#max_conc.append( x_interp[indx_max] )
fig.subplots_adjust(wspace=0)
ax[1].set_xlabel("Temperature (K)")
ax[0].set_ylabel("Internal energy (kJ/mol)")
ax[1].set_ylabel("Al conc.")
ax[1].legend(frameon=False)
isochemical_potential(data, max_T, max_conc)
#mu_T_phase_diag( mu, max_T, 200.0, 900.0 )
print(cf)
calc = ClusterExpansion(bc, cluster_name_eci=eci, init_cf=cf, logfile=None)
bc.atoms.set_calculator(calc)
view(bc.atoms)
free_energy(data, bc, eci)
plt.show()
def wulff(fname):
from ase.io import read, write
from ase.visualize import view
from cemc.tools import WulffConstruction
from matplotlib import pyplot as plt
atoms = read(fname)
atoms = extract_largest_cluster(fname)
surface_file = fname.rpartition(".")[0] + "_onlycluster.xyz"
wulff = WulffConstruction(cluster=atoms, max_dist_in_element=5.0)
wulff.filter_neighbours(num_neighbours=9, elements=["Mg", "Si"], cutoff=4.5)
write(surface_file, wulff.cluster)
print("Cluster written to {}".format(surface_file))
surface = wulff.surface_atoms
view(surface)
mesh_file = fname.rpartition(".")[0]+"_surfmesh.msh"
# wulff.fit_harmonics(show=True, order=100, penalty=0.1)
wulff.interface_energy_poly_expansion(order=12, show=True, spg=225,
average_cutoff=20.0, penalty=0.1)
wulff.save_surface_mesh(mesh_file)
ref_dir = [0.57735027, 0.57735027, -0.57735027]
gamma = 86.37379010832926/2.0
theta = np.arccos(ref_dir[2])
phi = np.arctan2(ref_dir[1], ref_dir[0])
value = wulff.eval(theta, phi)
wulff.wulff_plot(show=True, n_angles=60)
wulff.path_plot(path=[90, 45], normalization=gamma/value)
wulff.wulff_plot_plane(tol=5.0)
plt.show()
def test(size, R, nk):
atoms_flat = get_square_uCell(size)
view(atoms_flat)
# CALCULATOR FLAT
calc_f = Hotbit(SCC=False, kpts=(nk,nk,1), \
txt= path + 'test_consistency/optimization_flat.cal')
atoms_flat.set_calculator(calc_f)
opt_f = BFGS(atoms_flat)
opt_f.run(fmax = 0.05)
e_flat = atoms_flat.get_potential_energy()
atoms_c = atoms_flat.copy()
L = atoms_c.get_cell().diagonal()
atoms_c.set_cell(L)
angle = L[1]/R
atoms_c.rotate('y', np.pi/2)
atoms_c.translate((-atoms_c[0].x, 0, 0) )
for a in atoms_c:
r0 = a.position
phi = r0[1]/L[1]*angle
a.position[0] = R*np.cos(phi)
a.position[1] = R*np.sin(phi)
atoms_c = Atoms(atoms = atoms_c, container = 'Wedge')
atoms_c.set_container(angle = angle, height = L[0], physical = False, pbcz = True)
if R < 100:
view(atoms_c.extended_copy((8,1,3)))
# CALCULATOR Cyl
calc_c = Hotbit(SCC=False, kpts=(nk,1, nk), physical_k = False, \
txt= path + 'test_consistency/optimization_cyl.cal')
atoms_c.set_calculator(calc_c)
opt_c = BFGS(atoms_c)
opt_c.run(fmax = 0.05)
e_cyl = atoms_c.get_potential_energy()
print 'R = %.2f' %R
print 'energy flat = %.6f' %e_flat
print 'energy cylinder = %.6f' %e_cyl
print 'energy dif (e_cylinder - eflat)/nAtoms = %.6f \n' %(-(e_flat - e_cyl)/len(atoms_flat))
return e_flat, e_cyl, len(atoms_flat)
def view(self, index=None):
"""Visualize the calculation.
"""
from ase.visualize import view
if index is not None:
return view(self.traj[index])
else:
return view(self.traj)
def gui_view():
horizontal_dimension = int(horizon_sheet_variable.get())
vertical_dimension = int(vertical_sheet_variable.get())
symmetry_int = int(symmetry_var.get())
atoms = build_sheet(horizontal_dimension, vertical_dimension, symmetry=symmetry_int)
unsat_int = int(unsat_var.get())
if unsat_int==0:
daves_super_saturate(atoms)
elif unsat_int==1:
pass
view(atoms, viewer="avogadro")
def bp(info=None):
"""A breakpoint to view something and stop the rest of the script."""
if isinstance(info, Atoms):
view(info)
elif isinstance(info, list) and info:
if all(isinstance(i, Atoms) for i in info):
view(info)
else:
print(info)
elif info is not None:
print(info)
sys.exit()
def hyster_study(edge, folder = None):
if folder == None: folder = os.getcwd()
print folder
for fileC in os.listdir(folder):
if fileC[-6:] == '.simul':
fileC = folder + fileC
_, length, _, _, v, T, dt, fric, dtheta, \
thresZ, interval, deltaY, theta, M, edge = read_simul_params_file(fileC)
mdfile = fileC[:-6] + '.traj'
traj = PickleTrajectory(mdfile, 'r')
atoms_init = traj[0]
constraints, _, twist, rend_b, rend_t = get_constraints(atoms_init, edge, \
bond, None, key = 'twist_p')
#constraints, _, rend_b, rend_t = get_constraints(atoms_init, edge, \
# bond, None, key = 'twist_p')
atoms = traj[-1]
atoms.set_constraint(constraints)
vels = (traj[-2].positions - traj[-1].positions) / (interval * dt)
atoms.set_velocities(vels)
calc = LAMMPS(parameters=get_lammps_params())
atoms.set_calculator(calc)
view(atoms)
dyn = Langevin(atoms, dt*units.fs, T*units.kB, fric)
twist.set_angle(theta)
dyn.run(10 * interval)
view(atoms)
traj_new= PickleTrajectory(fileC[:-6] + '_hyst.traj', 'w', atoms)
mdlogf = fileC[:-6] + '_hyst.log'
do_dynamics(mdlogf, atoms, dyn, rend_b, rend_t, v, dt, deltaY, \
theta, dtheta, length, thresZ, \
interval, traj_new, M, twist)
mdhystf = fileC[:-6] + '_hyst.traj'
logfile = fileC[:-6] + '.log'
append_files(logfile, mdlogf, logfile[:-4] + '_comp.log')
call(['ase-gui', mdfile, mdhystf, '-o', logfile[:-4] + '_comp.traj'])
def run(self, names):
"""Run task far all names.
The task will be one of these four:
* Open ASE's GUI
* Write configuration to file
* Write summary
* Do the actual calculation
"""
names = self.expand(names)
names = names[self.slice]
names = self.exclude(names)
if self.gui:
for name in names:
view(self.create_system(name))
return
if self.write_to_file:
if self.write_to_file[0] == ".":
for name in names:
filename = self.get_filename(name, self.write_to_file)
write(filename, self.create_system(name))
else:
assert len(names) == 1
write(self.write_to_file, self.create_system(names[0]))
return
if self.write_summary:
self.read(names)
self.analyse()
self.summarize(names)
return
atoms = None
for name in names:
if self.use_lock_files:
lockfilename = self.get_filename(name, ".json")
fd = opencew(lockfilename)
if fd is None:
self.log("Skipping", name)
continue
fd.close()
atoms = self.run_single(name)
return atoms
def plot_neb(self, show=True):
"""Return a list of the energies and atoms objects for each image in
the band.
by default shows the plot figure
"""
images, energies = self.get_neb()
# add fitted line to band energies. we make a cubic spline
# interpolating function of the negative energy so we can find the
# minimum which corresponds to the barrier
from scipy.interpolate import interp1d
from scipy.optimize import fmin
f = interp1d(range(len(energies)),
-energies,
kind='cubic', bounds_error=False)
x0 = len(energies) / 2. # guess barrier is at half way
xmax = fmin(f, x0)
xfit = np.linspace(0, len(energies) - 1)
bandfit = -f(xfit)
import matplotlib.pyplot as plt
p = plt.plot(energies - energies[0], 'bo ', label='images')
plt.plot(xfit, bandfit, 'r-', label='fit')
plt.plot(xmax, -f(xmax), '* ', label='max')
plt.xlabel('Image')
plt.ylabel('Energy (eV)')
s = ['$\Delta E$ = {0:1.3f} eV'.format(float(energies[-1]
- energies[0])),
'$E^\ddag$ = {0:1.3f} eV'.format(float(-f(xmax)))]
plt.title('\n'.join(s))
plt.legend(loc='best', numpoints=1)
if show:
from ase.calculators.singlepoint import SinglePointCalculator
from ase.visualize import view
# It seems there might be some info on the atoms that causes
# an error here. Making a copy seems to get rid of the
# issue. Hacky.
tatoms = [x.copy() for x in images]
for i, x in enumerate(tatoms):
x.set_calculator(SinglePointCalculator(x, energy=energies[i]))
view(tatoms)
plt.show()
return p
def plot_fig1():
mdfile = '/space/tohekorh/ShearSlide/files/LJ_10/ac_twistTaito/w=7/md_L=24_v=0.20_00.traj'
#mdfile = '/space/tohekorh/ShearSlide/files/KC_10/ac_stickTaito/w=7/r=20/md_L=145_stL=27_00.traj'
traj = PickleTrajectory(mdfile)
z_init = np.average(traj[0].positions[:,2])
xrange = [np.min(traj[0].positions[:,0]), np.max(traj[0].positions[:,0])]
yrange = [np.min(traj[0].positions[:,1]), np.max(traj[0].positions[:,1])]
from ase.structure import graphene_nanoribbon
from ase.visualize import view
from ase import Atoms
base = graphene_nanoribbon(70, 50, type='armchair', saturated=False,
C_C=bond, main_element='N')
base.rotate([1,0,0], np.pi/2)
base.positions[:,2] = z_init - 3.8
atoms_v = Atoms()
n = int(len(traj)/1.3)
#n =
nsnap = 3
atoms_use = [traj[i] for i in np.array(range(nsnap))*n/nsnap]
for i, atoms in enumerate(atoms_use):
atoms.positions[:,1] = -atoms.positions[:,1] - i*20
#atoms.positions[:,0] = -atoms.positions[:,0]
atoms_v += atoms
cent_atoms = np.array([np.average(atoms_v.positions[:,0]), np.average(atoms_v.positions[:,1]), 0])
cent_base = np.array([np.average(base.positions[:,0]), np.average(base.positions[:,1]), 0])
base.translate(cent_atoms - cent_base)
#atoms_v += base
view(atoms_v, viewer = 'vmd')
def run(args, parser):
if args.vacuum0:
parser.error('Please use -V or --vacuum instead!')
if '.' in args.name:
# Read from file:
atoms = read(args.name)
elif args.crystal_structure:
atoms = build_bulk(args)
else:
atoms = build_molecule(args)
if args.magnetic_moment:
magmoms = np.array(
[float(m) for m in args.magnetic_moment.split(',')])
atoms.set_initial_magnetic_moments(
np.tile(magmoms, len(atoms) // len(magmoms)))
if args.modify:
exec(args.modify, {'atoms': atoms})
if args.repeat is not None:
r = args.repeat.split(',')
if len(r) == 1:
r = 3 * r
atoms = atoms.repeat([int(c) for c in r])
if args.gui:
view(atoms)
if args.output:
write(args.output, atoms)
elif sys.stdout.isatty():
write(args.name + '.json', atoms)
else:
con = connect(sys.stdout, type='json')
con.write(atoms, name=args.name)
# initial approximation:
n = int(mc.L/2)
# hollow core-shell initial structure
s = 4
mc.GRID[(n-s):(n+s), (n-s):(n+s), (n-s):(n+s)] = mc.chems[0]
s = 3
mc.GRID[(n-s):(n+s), (n-s):(n+s), (n-s):(n+s)] = mc.chems[1] # mc.chems[0]
s = 2
mc.GRID[(n-s):(n+s), (n-s):(n+s), (n-s):(n+s)] = mc.chems[1] # 0
if True: # test move change 13
print('Test MoveChange13')
move = MoveChange13()
move.setup(mc.GRID, n, n, n, mc.chems[0])
move()
from ase.visualize import view
view(mc.get_atoms())
raw_input('Press enter')
print('Test reject')
move.reject()
view(mc.get_atoms())
raw_input('Press enter')
target_CN = np.zeros(4)
target_CN[0] = 2.8 # Cu-Cu
target_CN[1] = 4.0 # Pt-Cu
target_CN[2] = 1.8 # Cu-Pt
target_CN[3] = 6.2 # Pt-Pt
#i = 0
#for B in mc.chems:
# for A in mc.chems:
# print('CN [',A,'-',B,'] = ', target_CN[i])
from __future__ import print_function
from ase.visualize import view
from ase.constraints import FixAtoms
from ase.optimize import QuasiNewton
from ase.lattice.surface import fcc100, add_adsorbate
from gpaw import GPAW, PW
# Initial state:
# 2x2-Al(001) surface with 1 layer and an
# Au atom adsorbed in a hollow site:
slab = fcc100('Al', size=(2, 2, 2))
slab.center(axis=2, vacuum=3.0)
add_adsorbate(slab, 'Au', 1.6, 'hollow')
# Make sure the structure is correct:
view(slab)
# Fix the Al atoms:
mask = [atom.symbol == 'Al' for atom in slab]
print(mask)
fixlayer = FixAtoms(mask=mask)
slab.set_constraint(fixlayer)
# Use GPAW:
calc = GPAW(mode=PW(200), kpts=(2, 2, 1), xc='PBE', txt='hollow.txt')
slab.set_calculator(calc)
qn = QuasiNewton(slab, trajectory='hollow.traj')
# Find optimal height. The stopping criterion is: the force on the
# Au atom should be less than 0.05 eV/Ang
cell = [[1,0,0],[0,1,0],[0,0,1]]
atoms = BodyCenteredCubic('Fe', directions=cell)
atoms.set_initial_magnetic_moments([5,5])
atoms.set_cell([a, a, a], scale_atoms=True)
carbon = Atom('C', position=(0,0.5*a,0.75*a), charge=0.4)
atoms = atoms*(2,2,2) + carbon
constraint = FixAtoms(indices=[3,5,7,8,10,11,12,13,14,15,16])
atoms.set_constraint(constraint)
atoms[-1].position = [0, 0.5*a, 0.25*a]
init = atoms.copy()
view(init)
atoms[-1].position = [0, 0.5*a, 0.75*a]
final = atoms.copy()
view(final)
def save( filename, arg ):
f = open(filename, 'a+t')
f.write('{0} \n'.format(arg))
f.close()
os.system('mkdir result')
print atoms.get_cell()
mol = atoms[mask]
del atoms[mask]
mol.cell[0:2, ] = mol.cell[0:2, ]*1/3.0
mol.cell[2][2] = 3
mol[-1].z = mol[-3].z
mol[-1].position = mol[-1].position + mol.cell[0]/6 + mol.cell[1]/6
mol.translate([0, 0, -mol[1].z])
mol = mol*[3, 3, 2]
mol = sortz(mol)
mol1 = mol.copy()
mol1.translate([0, 0, atoms[-1].z + 2.0])
atoms = atoms + mol1
view(atoms)
constraint = FixAtoms(mask=[atom.symbol != 'O' and atom.symbol != 'C'
for atom in atoms])
atoms.set_constraint(constraint)
with jasp('442-coo2-sm5',
xc='PBE',
encut=350,
kpts=[1, 1, 1],
gamma='true',
ismear=0,
sigma=0.1, # this is small for a molecule
prec='normal',
algo='fast',
lreal='atuo',
fmax = 0.05
nimages = 3
print([a.get_potential_energy() for a in Trajectory('H.traj')])
images = [Trajectory('H.traj')[-1]]
for i in range(nimages):
images.append(images[0].copy())
images[-1].positions[6, 1] = 2 - images[0].positions[6, 1]
neb = NEB(images)
neb.interpolate()
if 0: # verify that initial images make sense
from ase.visualize import view
view(neb.images)
for image in images:
image.set_calculator(MorsePotential())
dyn = BFGS(neb, trajectory='mep.traj') # , logfile='mep.log')
dyn.run(fmax=fmax)
for a in neb.images:
print(a.positions[-1], a.get_potential_energy())
neb.climb = True
dyn.run(fmax=fmax)
# Check NEB tools.
def run(argv=None):
if argv is None:
argv = sys.argv[1:]
elif isinstance(argv, str):
argv = argv.split()
parser = build_parser()
opt, args = parser.parse_args(argv)
if len(args) != 1:
parser.error("incorrect number of arguments")
name = args[0]
if world.rank == 0:
out = sys.stdout#open('%s-%s.results' % (name, opt.identifier), 'w')
else:
out = devnull
a = None
try:
symbols = string2symbols(name)
except ValueError:
# name was not a chemical formula - must be a file name:
atoms = read(name)
else:
if opt.crystal_structure:
a = opt.lattice_constant
if a is None:
a = estimate_lattice_constant(name, opt.crystal_structure,
opt.c_over_a)
out.write('Using an estimated lattice constant of %.3f Ang\n' %
a)
atoms = bulk(name, opt.crystal_structure, a, covera=opt.c_over_a,
orthorhombic=opt.orthorhombic, cubic=opt.cubic)
else:
try:
# Molecule?
atoms = molecule(name)
except NotImplementedError:
if len(symbols) == 1:
# Atom
atoms = Atoms(name)
elif len(symbols) == 2:
# Dimer
atoms = Atoms(name, positions=[(0, 0, 0),
(opt.bond_length, 0, 0)])
else:
raise ValueError('Unknown molecule: ' + name)
if opt.magnetic_moment:
magmom = opt.magnetic_moment.split(',')
atoms.set_initial_magnetic_moments(np.tile(magmom,
len(atoms) // len(magmom)))
if opt.repeat is not None:
r = opt.repeat.split(',')
if len(r) == 1:
r = 3 * r
atoms = atoms.repeat([int(c) for c in r])
if opt.gui:
view(atoms)
return
if opt.write_to_file:
write(opt.write_to_file, atoms)
return
if opt.effective_medium_theory:
Runner = EMTRunner
else:
Runner = GPAWRunner
if opt.fit:
strains = np.linspace(0.98, 1.02, 5)
else:
strains = None
if opt.constrain_tags:
tags = [int(t) for t in opt.constrain_tags.split(',')]
constrain = FixAtoms(mask=[t in tags for t in atoms.get_tags()])
atoms.constraints = [constrain]
runner = Runner(name, atoms, strains, tag=opt.identifier,
clean=not opt.read,
fmax=opt.relax, out=out)
if not opt.effective_medium_theory:
# Import stuff that eval() may need to know:
from gpaw.wavefunctions.pw import PW
from gpaw.occupations import FermiDirac, MethfesselPaxton
if opt.parameters:
input_parameters = eval(open(opt.parameters).read())
else:
input_parameters = {}
for key in defaults:
value = getattr(opt, key)
if value is not None:
try:
input_parameters[key] = eval(value)
except (NameError, SyntaxError):
input_parameters[key] = value
runner.set_parameters(vacuum=opt.vacuum,
write_gpw_file=opt.write_gpw_file,
**input_parameters)
runner.run()
runner.summary(plot=opt.plot, a0=a)
return runner
from ase import Atoms
from ase.visualize import view
from ase.calculators.aims import Aims, AimsCube
from ase.optimize import QuasiNewton
water = Atoms('HOH', [(1,0,0), (0,0,0), (0,1,0)])
water_cube = AimsCube(points=(29,29,29),
plots=('total_density','delta_density',
'eigenstate 5','eigenstate 6'))
calc=Aims(xc='pbe',
sc_accuracy_etot=1e-6,
sc_accuracy_eev=1e-3,
sc_accuracy_rho=1e-6,
sc_accuracy_forces=1e-4,
species_dir='/home/hanke/codes/fhi-aims/fhi-aims.workshop/species_defaults/light/',
run_command='aims.workshop.serial.x',
cubes=water_cube)
water.set_calculator(calc)
dynamics = QuasiNewton(water,trajectory='square_water.traj')
dynamics.run(fmax=0.01)
view(water)
import ase.build as ab
from pyramids.io.output import writeSiesta
from ase.visualize import view
atom = ab.mx2()
view(atom)
writeSiesta('structure.fdf',atom)
def main():
parser = optparse.OptionParser(usage="%prog [options] name/input-file [output-file]")
add = parser.add_option
add("-M", "--magnetic-moment", metavar="M1,M2,...", help="Magnetic moment(s). " + 'Use "-M 1" or "-M 2.3,-2.3".')
add(
"--modify",
metavar="...",
help="Modify atoms with Python statement. " + 'Example: --modify="atoms.positions[-1,2]+=0.1".',
)
add(
"-v",
"--vacuum",
type=float,
default=3.0,
help="Amount of vacuum to add around isolated atoms " "(in Angstrom).",
)
add("--unit-cell", help='Unit cell. Examples: "10.0" or "9,10,11" ' + "(in Angstrom).")
add("--bond-length", type=float, help="Bond length of dimer in Angstrom.")
add(
"-x",
"--crystal-structure",
help="Crystal structure.",
choices=[
"sc",
"fcc",
"bcc",
"hcp",
"diamond",
"zincblende",
"rocksalt",
"cesiumchloride",
"fluorite",
"wurtzite",
],
)
add("-a", "--lattice-constant", default="", help="Lattice constant(s) in Angstrom.")
add("--orthorhombic", action="store_true", help="Use orthorhombic unit cell.")
add("--cubic", action="store_true", help="Use cubic unit cell.")
add("-r", "--repeat", help='Repeat unit cell. Use "-r 2" or "-r 2,3,1".')
add("-g", "--gui", action="store_true")
opts, args = parser.parse_args()
if len(args) == 0 or len(args) > 2:
parser.error("Wrong number of arguments!")
name = args.pop(0)
if "." in name:
# Read from file:
atoms = read(name)
elif opts.crystal_structure:
atoms = build_bulk(name, opts)
else:
atoms = build_molecule(name, opts)
if opts.magnetic_moment:
magmoms = np.array([float(m) for m in opts.magnetic_moment.split(",")])
atoms.set_initial_magnetic_moments(np.tile(magmoms, len(atoms) // len(magmoms)))
if opts.modify:
exec(opts.modify, {"atoms": atoms})
if opts.repeat is not None:
r = opts.repeat.split(",")
if len(r) == 1:
r = 3 * r
atoms = atoms.repeat([int(c) for c in r])
if opts.gui:
view(atoms)
if args:
write(args[0], atoms)
elif sys.stdout.isatty():
write(name + ".json", atoms)
else:
con = connect(sys.stdout, type="json")
con.write(atoms, name=name)
def run_moldy(N, save = False):
#
params = {'bond':bond, 'a':a, 'h':h}
# DEFINE FILES
mdfile, mdlogfile, mdrelax = get_fileName(N, 'tear_E_rebo+KC_v', taito, v, edge)
# GRAPHENE SLAB
atoms = make_graphene_slab(a,h,width,length,N, \
edge_type = edge, h_pass = True, \
stacking = 'abc')[3]
view(atoms)
#exit()
params['ncores'] = ncores
params['positions'] = atoms.positions.copy()
params['pbc'] = atoms.get_pbc()
params['cell'] = atoms.get_cell().diagonal()
params['ia_dist'] = 10
params['chemical_symbols'] \
= atoms.get_chemical_symbols()
# FIX
constraints = []
print 'hii'
left = get_ind(atoms.positions.copy(), 'left', 2, bond)
top = get_ind(atoms.positions.copy(), 'top', fixtop - 1, left)
rend_t = get_ind(atoms.positions.copy(), 'rend', atoms.get_chemical_symbols(), 1, edge)
rend = get_ind(atoms.positions.copy(), 'rend', atoms.get_chemical_symbols(), fixtop, edge)
print rend
print 'hoo'
exit()
fix_left = FixAtoms(indices = left)
fix_top = FixAtoms(indices = top)
add_kc = KC_potential_p(params)
for ind in rend:
fix_deform = FixedPlane(ind, (0., 0., 1.))
constraints.append(fix_deform)
for ind in rend_t:
fix_deform = FixedPlane(ind, (0., 0., 1.))
constraints.append(fix_deform)
constraints.append(fix_left)
constraints.append(fix_top)
constraints.append(add_kc)
# END FIX
# CALCULATOR LAMMPS
parameters = {'pair_style':'rebo',
'pair_coeff':['* * CH.airebo C H'],
'mass' :['1 12.0', '2 1.0'],
'units' :'metal',
'boundary' :'f p f'}
calc = LAMMPS(parameters=parameters)
atoms.set_calculator(calc)
# END CALCULATOR
#view(atoms)
# TRAJECTORY
if save: traj = PickleTrajectory(mdfile, 'w', atoms)
else: traj = None
#data = np.zeros((M/interval, 5))
# RELAX
atoms.set_constraint(add_kc)
dyn = BFGS(atoms, trajectory = mdrelax)
dyn.run(fmax=0.05)
# FIX AFTER RELAXATION
atoms.set_constraint(constraints)
# DYNAMICS
dyn = Langevin(atoms, dt*units.fs, T*units.kB, fric)
n = 0
header = '#t [fs], d [Angstrom], epot_tot [eV], ekin_tot [eV], etot_tot [eV] \n'
log_f = open(mdlogfile, 'w')
log_f.write(header)
log_f.close()
if T != 0:
# put initial MaxwellBoltzmann velocity distribution
mbd(atoms, T*units.kB)
print 'Start the dynamics for N = %i' %N
for i in range(0, M):
if T == 0:
for ind in rend:
atoms[ind].position[2] -= dz
elif T != 0:
if tau < i*dt:
hw = i*dz
for ind in rend:
atoms[ind].position[2] -= dz
dyn.run(1)
if i%interval == 0:
epot, ekin = saveAndPrint(atoms, traj, False)[:2]
if T != 0:
if tau < i*dt: hw = i*dz - tau*v
else: hw = 0
else: hw = i*dz
data = [i*dt, hw, epot, ekin, epot + ekin]
if save:
log_f = open(mdlogfile, 'a')
stringi = ''
for k,d in enumerate(data):
if k == 0:
stringi += '%.2f ' %d
elif k == 1:
stringi += '%.6f ' %d
else:
stringi += '%.12f ' %d
log_f.write(stringi + '\n')
log_f.close()
n += 1
if save and T != 0 and i*dt == tau:
log_f = open(mdlogfile, 'a')
log_f.write('# Thermalization complete. ' + '\n')
log_f.close()
if 1e2 <= M:
if i%(int(M/100)) == 0: print 'ready = %.1f' %(i/(int(M/100))) + '%'
def check_nuts(self, value):
"""
Test NUTS simulation
Parameters
----------
value: list or tuple
The values to use in the tests
"""
print(self.traj_file)
ideal_atoms, _ = value[0]
ideal_atoms.set_velocities(np.zeros((len(ideal_atoms), 3)))
s = ElasticScatter(verbose=True)
if value[1] == 'PDF':
target_data = s.get_pdf(ideal_atoms)
exp_func = s.get_pdf
exp_grad = s.get_grad_pdf
calc = Calc1D(target_data=target_data,
exp_function=exp_func, exp_grad_function=exp_grad,
potential='rw', conv=30)
elif value[1] == 'FQ':
target_data = s.get_pdf(ideal_atoms)
exp_func = s.get_pdf
exp_grad = s.get_grad_pdf
calc = Calc1D(target_data=target_data,
exp_function=exp_func, exp_grad_function=exp_grad,
potential='rw', conv=30)
else:
calc = value[1]
ideal_atoms.positions *= 1.02
ideal_atoms.set_calculator(calc)
start_pe = ideal_atoms.get_potential_energy()
if value[2]:
traj_name = self.traj_file.name
else:
traj_name = None
nuts = NUTSCanonicalEnsemble(ideal_atoms, escape_level=4, verbose=True,
seed=seed, trajectory=traj_name)
traj, metadata = nuts.run(5)
print(traj[0].get_momenta())
pe_list = []
for atoms in traj:
pe_list.append(atoms.get_potential_energy())
min_pe = np.min(pe_list)
print(len(traj))
print(min_pe, start_pe)
if start_pe != 0.0:
if not min_pe < start_pe:
view(traj)
assert min_pe < start_pe
self.traj_file.close()
if value[2]:
assert os.path.exists(self.traj_file.name)
read_traj = TrajectoryReader(self.traj_file.name)
print(len(traj), len(read_traj))
assert len(traj) == len(read_traj)
for i, (atoms1, atoms2) in enumerate(zip(read_traj, traj)):
for att in ['get_positions', 'get_potential_energy',
'get_forces', 'get_momenta']:
print(i, att)
assert_allclose(*[getattr(a, att)() for a in [atoms1, atoms2]])
del traj
def gui(id):
if open_ase_gui:
atoms = connection.get_atoms(id)
view(atoms)
return '', 204, []
def run(self, names=None):
"""Run task for all names.
The task will be one of these four:
* Open ASE's GUI
* Write configuration to file
* Write summary
* Do the actual calculation
"""
if self.lock is None:
# Create lock object:
self.lock = Lock(self.get_filename(ext='lock'))
if self.clean:
self.clean_json_file(names)
return
if names is None or len(names) == 0:
names = self.collection.keys()
names = self.expand(names)
names = names[self.slice]
names = self.exclude(names)
if self.gui:
for name in names:
view(self.create_system(name))
return
if self.write_to_file:
if self.write_to_file[0] == '.':
for name in names:
filename = self.get_filename(name, self.write_to_file)
write(filename, self.create_system(name))
else:
assert len(names) == 1
write(self.write_to_file, self.create_system(names[0]))
return
if self.write_summary:
self.read()
self.analyse()
self.summarize(names)
return
atoms = None
for name in names:
if self.use_lock_files:
try:
filename = self.get_filename(ext='json')
self.lock.acquire()
if os.path.isfile(filename):
data = read_json(filename)
if name not in data:
data[name] = {}
write_json(filename, data)
else:
self.log('Skipping', name)
continue
else:
write_json(filename, {name: {}})
finally:
self.lock.release()
if atoms is not None:
del atoms.calc
atoms = self.run_single(name)
return atoms
from ase.lattice import surface
from ase.constraints import FixAtoms
from ase.calculators.vasp import Vasp
from ase.visualize import view
from ase.io import write
from ase.io import read
#sigma=0.01 for gases and edif=13-8
calc = Vasp(xc='PBE', kpts=(3,3,1), lwave=False, lcharg=False,lvtot=False, nwrite=1
, encut=400, algo='Fast', ismear=0, sigma=0.0031, voskown=1, istart=0, nelm=400, nelmdl=-10, ediff=1e-8, ispin=2
,nsw=1, isif=2, ibrion=5, nfree=2, potim=0.015, ediffg=-0.05, isym=0
,lvdw=True, vdw_version=3
,lreal='Auto')
slab = read('../CONTCAR')
slab.center(vacuum=20.0,axis=2)
view(slab) # View the slab, frozen atoms will be marked with a "X"
#slab.set_calculator(calc)
calc.initialize(slab)
calc.write_incar(slab)
calc.write_potcar()
calc.write_kpoints()
write('POSCAR', calc.atoms_sorted) # this will write a "sorted" POSCAR
a = 4.0614
b = a / sqrt(2)
h = b / 2
initial = Atoms('Al2',
positions=[(0, 0, 0),
(a / 2, b / 2, -h)],
cell=(a, b, 2 * h),
pbc=(1, 1, 0))
initial *= (2, 2, 2)
initial.append(Atom('Al', (a / 2, b / 2, 3 * h)))
initial.center(vacuum=4.0, axis=2)
final = initial.copy()
final.positions[-1, 0] += a
view([initial, final])
# Construct a list of images:
images = [initial]
for i in range(5):
images.append(initial.copy())
images.append(final)
# Make a mask of zeros and ones that select fixed atoms (the
# two bottom layers):
mask = initial.positions[:, 2] - min(initial.positions[:, 2]) < 1.5 * h
constraint = FixAtoms(mask=mask)
print(mask)
for image in images:
# Let all images use an EMT calculator:
from ase.optimize import QuasiNewton, BFGS
from ase.visualize import view
# http://jcp.aip.org/resource/1/jcpsa6/v97/i10/p7507_s1
doo = 2.74
doht = 0.957
doh = 0.977
angle = radians(104.5)
initial = Atoms('HOHOH',
positions=[(-sin(angle) * doht, 0., cos(angle) * doht),
(0., 0., 0.),
(0., 0., doh),
(0., 0., doo),
(sin(angle) * doht, 0., doo - cos(angle) * doht)])
if 0:
view(initial)
final = Atoms('HOHOH',
positions=[(-sin(angle) * doht, 0., cos(angle) * doht),
(0., 0., 0.),
(0., 0., doo - doh),
(0., 0., doo),
(sin(angle) * doht, 0., doo - cos(angle) * doht)])
if 0:
view(final)
# Make band:
images = [initial.copy()]
for i in range(3):
images.append(initial.copy())
images.append(final.copy())
from ase.optimize import LBFGS
from ase.calculators.vasp import Vasp
from ase.io.vasp import write_vasp
from ase.visualize import view
from ase.io import write
calc = Vasp(xc='PBE', kpts=(1,1,1), nwrite=1, lwave=False, lcharg=False,lvtot=False
, encut=400, algo='Fast', ismear=0, sigma=0.003, voskown=1, istart=0, nelm=400, nelmdl=-10, ediff=1e-6, ispin=2
,nsw=1000, isif=2, ibrion=1, nfree=2, potim=0.2,lvdw=True, vdw_version=3
,isym=0
,lreal='Auto')
# Create a c(2x2) surface with 4 layers and 14 Angstrom of vacuum
d=0.9575
t = np.pi/180*104.51
molecule = Atoms('H2O',
positions=[(d, 0, 0),(d * np.cos(t), d * np.sin(t), 0),(0, 0, 0)])
molecule.center(vacuum=20.0)
view(molecule) # View the slab, frozen atoms will be marked with a "X"
#slab.set_calculator(calc)
calc.initialize(molecule)
calc.write_incar(molecule)
calc.write_potcar()
calc.write_kpoints()
write('POSCAR', calc.atoms_sorted) # this will write a "sorted" POSCAR
