def testEqualOneModelPTI(self):
calculator_pti = self.model_pti[0].ase()
calculator = self.model[0].ase()
atoms = Diamond(symbol="C", pbc=True)
atoms_pti = Diamond(symbol="C", pbc=True)
atoms.set_calculator(calculator)
atoms_pti.set_calculator(calculator_pti)
self.assertEqual(atoms.get_potential_energy(), atoms_pti.get_potential_energy())
def test_pbc(self):
a = Diamond('Si', latticeconstant=5.432, size=[2,2,2])
sx, sy, sz = a.get_cell().diagonal()
a.set_calculator(Tersoff())
e1 = a.get_potential_energy()
a.set_pbc([True,True,False])
e2 = a.get_potential_energy()
a.set_pbc(True)
a.set_cell([sx,sy,2*sz])
e3 = a.get_potential_energy()
self.assertEqual(e2, e3)
# This should give the unrelaxed surface energy
esurf = (e2-e1)/(2*sx*sy) * Jm2
self.assertTrue(abs(esurf-2.309) < 0.001)
def test_pbc(self):
a = Diamond('Si', latticeconstant=5.432, size=[2,2,2])
sx, sy, sz = a.get_cell().diagonal()
a.set_calculator(Tersoff())
e1 = a.get_potential_energy()
a.set_pbc([True,True,False])
e2 = a.get_potential_energy()
a.set_pbc(True)
a.set_cell([sx,sy,2*sz])
e3 = a.get_potential_energy()
self.assertEqual(e2, e3)
# This should give the unrelaxed surface energy
esurf = (e2-e1)/(2*sx*sy) * Jm2
self.assertTrue(abs(esurf-2.309) < 0.001)
def test_calculator():
"""
Take ASE structure, PySCF object,
and run through ASE calculator interface.
This allows other ASE methods to be used with PySCF;
here we try to compute an equation of state.
"""
ase_atom=Diamond(symbol='C', latticeconstant=3.5668)
# Set up a cell; everything except atom; the ASE calculator will
# set the atom variable
cell = pbcgto.Cell()
cell.h=ase_atom.cell
cell.basis = 'gth-szv'
cell.pseudo = 'gth-pade'
cell.gs=np.array([8,8,8])
cell.verbose = 0
# Set up the kind of calculation to be done
# Additional variables for mf_class are passed through mf_dict
mf_class=pbcdft.RKS
mf_dict = { 'xc' : 'lda,vwn' }
# Once this is setup, ASE is used for everything from this point on
ase_atom.set_calculator(pyscf_ase.PySCF(molcell=cell, mf_class=mf_class, mf_dict=mf_dict))
print "ASE energy", ase_atom.get_potential_energy()
print "ASE energy (should avoid re-evaluation)", ase_atom.get_potential_energy()
# Compute equation of state
ase_cell=ase_atom.cell
volumes = []
energies = []
for x in np.linspace(0.95, 1.2, 5):
ase_atom.set_cell(ase_cell * x, scale_atoms = True)
print "[x: %f, E: %f]" % (x, ase_atom.get_potential_energy())
volumes.append(ase_atom.get_volume())
energies.append(ase_atom.get_potential_energy())
eos = EquationOfState(volumes, energies)
v0, e0, B = eos.fit()
print(B / kJ * 1.0e24, 'GPa')
eos.plot('eos.png')
cell.verbose = 0
# Set up the kind of calculation to be done
# Additional variables for mf_class are passed through mf_dict
# E.g. gamma-point SCF calculation can be set to
mf_class = pbcdft.RKS
# SCF with k-point sampling can be set to
mf_class = lambda cell: pbcdft.KRKS(cell, kpts=cell.make_kpts([2, 2, 2]))
mf_dict = {'xc': 'lda,vwn'}
# Once this is setup, ASE is used for everything from this point on
ase_atom.set_calculator(
pyscf_ase.PySCF(molcell=cell, mf_class=mf_class, mf_dict=mf_dict))
print("ASE energy", ase_atom.get_potential_energy())
print("ASE energy (should avoid re-evaluation)",
ase_atom.get_potential_energy())
# Compute equation of state
ase_cell = ase_atom.cell
volumes = []
energies = []
for x in np.linspace(0.95, 1.2, 5):
ase_atom.set_cell(ase_cell * x, scale_atoms=True)
print "[x: %f, E: %f]" % (x, ase_atom.get_potential_energy())
volumes.append(ase_atom.get_volume())
energies.append(ase_atom.get_potential_energy())
eos = EquationOfState(volumes, energies)
v0, e0, B = eos.fit()
print(B / kJ * 1.0e24, 'GPa')
if not hasattr(model, 'bulk_reference_216'):
# set up the a
bulk = Diamond(symbol='Si', latticeconstant=a0)
# specify that we will use model.calculator to compute forces, energies and stresses
bulk.set_calculator(model.calculator)
# use one of the routines from utilities module to relax the initial
# unit cell and atomic positions
bulk = relax_config(bulk,
relax_pos=True,
relax_cell=True,
tol=tol,
traj_file=None)
bulk *= (N, N, N)
bulk_energy = bulk.get_potential_energy()
else:
bulk = model.bulk_reference_216
bulk_energy = bulk.get_potential_energy()
def dumbbell_interstitial_energy(bulk):
Nat = bulk.get_number_of_atoms()
int_struct = bulk.copy()
int_struct.set_calculator(bulk.get_calculator())
# add an atom to introduce an interstitial
int_struct.append(Atom('Si', (-0.5, 0.5, 5.44 / 2.0 + 1.0)))
p = int_struct.get_positions()
p[149, 0] -= 1.0
p[149, 1] += 1.0
if not hasattr(model, 'bulk_reference'):
# set up the a
bulk = Diamond(symbol='Si', latticeconstant=a0)
# specify that we will use model.calculator to compute forces, energies and stresses
bulk.set_calculator(model.calculator)
# use one of the routines from utilities module to relax the initial
# unit cell and atomic positions
bulk = relax_atoms_cell(bulk, tol=fmax, traj_file=None)
else:
bulk = model.bulk_reference.copy()
bulk.set_calculator(model.bulk_reference.calc)
print "BOB doing bulk pot en"
e0 = bulk.get_potential_energy()/float(len(bulk))
print "got e0 ", e0
def interface_energy(e0, filename):
interface = ase.io.read(os.path.join(os.path.dirname(__file__),filename), format='extxyz')
# adjust lattice constant
interface.set_calculator(model.calculator)
# relax atom positions, holding cell fixed
interface.positions += 0.01*np.random.random_sample((len(interface),3))
print "pre relax config"
ase.io.write(sys.stdout, interface, format='extxyz')
print "BOB doing gb relax"
# use one of the routines from utilities module to relax the initial
# unit cell and atomic positions
bulk = relax_atoms_cell(bulk, tol=fmax, traj_file=None)
else:
bulk = model.bulk_reference.copy()
bulk.set_calculator(model.calculator)
a0 = bulk.cell[0, 0] # get lattice constant from relaxed bulk
print "got a0 ", a0
bulk = Diamond(symbol="Si",
latticeconstant=a0,
directions=[[1, -1, 0], [1, 0, -1], [1, 1, 1]])
bulk.set_calculator(model.calculator)
# compute surface formation energy as difference of periodic and curface cell
ebulk_per_atom = bulk.get_potential_energy() / bulk.get_number_of_atoms()
print 'bulk per atom energy', ebulk_per_atom
bulk *= (1, 1, 10)
ebulk = bulk.get_potential_energy()
print 'bulk 1x1x10 cell energy', ebulk
# now calculate the relaxed unreconstructed 111 surface energy
bulk.positions[:, 2] += 2.0 # select shuffle plane to be cut
bulk.wrap()
bulk.cell[2, :] += [0.0, 0.0, 10.0]
np.random.seed(75)
bulkNat = bulk.get_number_of_atoms()
#bulk.positions += (np.random.rand((bulkNat*3))*0.1).reshape([bulkNat,3])
#bulk = relax_atoms(bulk, tol=fmax, traj_file="model-"+model.name+"-surface-energy-111-expanded-bulk-relaxed.opt.xyz")
eexp = bulk.get_potential_energy()
print 'expanded cell energy', eexp
e111 = 0.5 * (eexp - ebulk) / np.linalg.norm(
if not hasattr(model, 'bulk_reference'):
# set up the a
bulk = Diamond(symbol='Si', latticeconstant=5.43)
# specify that we will use model.calculator to compute forces, energies and stresses
bulk.set_calculator(model.calculator)
# use one of the routines from utilities module to relax the initial
# unit cell and atomic positions
bulk = relax_atoms_cell(bulk, tol=fmax, traj_file=None)
else:
bulk = model.bulk_reference.copy()
bulk.set_calculator(model.calculator)
print "calling bulk.get_potential_energy()"
e0_per_atom = bulk.get_potential_energy() / len(bulk)
print "got e0_per_atom ", e0_per_atom
def traj_energy(e0_per_atom, traj):
ats = ase.io.read(os.path.dirname(__file__) + "/" + traj,
index=':',
format='extxyz')
orig_Es = []
model_Es = []
for at in ats:
# save reference energy
orig_Es.append(at.get_potential_energy() / len(at))
# calc new energy
at.set_calculator(model.calculator)
cell.pseudo = 'gth-pade'
cell.verbose = 0
# Set up the kind of calculation to be done
# Additional variables for mf_class are passed through mf_dict
# E.g. gamma-point SCF calculation can be set to
mf_class = pbcdft.RKS
# SCF with k-point sampling can be set to
mf_class = lambda cell: pbcdft.KRKS(cell, kpts=cell.make_kpts([2,2,2]))
mf_dict = { 'xc' : 'lda,vwn' }
# Once this is setup, ASE is used for everything from this point on
ase_atom.set_calculator(pyscf_ase.PySCF(molcell=cell, mf_class=mf_class, mf_dict=mf_dict))
print("ASE energy", ase_atom.get_potential_energy())
print("ASE energy (should avoid re-evaluation)", ase_atom.get_potential_energy())
# Compute equation of state
ase_cell=ase_atom.cell
volumes = []
energies = []
for x in np.linspace(0.95, 1.2, 5):
ase_atom.set_cell(ase_cell * x, scale_atoms = True)
print "[x: %f, E: %f]" % (x, ase_atom.get_potential_energy())
volumes.append(ase_atom.get_volume())
energies.append(ase_atom.get_potential_energy())
eos = EquationOfState(volumes, energies)
v0, e0, B = eos.fit()
print(B / kJ * 1.0e24, 'GPa')
eos.plot('eos.png')
print liquid_traj_filename
try:
liquid_traj = quippy.AtomsList(liquid_traj_filename)
if __builtin__.do_io:
print "read %s from file" % liquid_traj_filename
except:
if __builtin__.do_io:
print "generating %s" % liquid_traj_filename
if 'LIQUID_NO_RUN' in os.environ:
sys.exit(1)
# specify that we will use model.calculator to compute forces, energies and stresses
bulk.set_calculator(model.calculator)
print "doing bulk"
print bulk.get_potential_energy()
print "done"
try:
model.calculator.print_()
except:
pass
####################################################################################################
# initial heating
dyn_heat = quippy.Dynamics(bulk,
0.5 * ase.units.fs,
trajectory=None,
initialtemperature=T_melt,
loginterval=10,
logfile="model-" + model.name +
"-test-liquid-heat.log")
# set up the a
bulk = Diamond(symbol='Si', latticeconstant=a0)
# specify that we will use model.calculator to compute forces, energies and stresses
bulk.set_calculator(model.calculator)
# use one of the routines from utilities module to relax the initial
# unit cell and atomic positions
bulk = relax_atoms_cell(bulk, tol=fmax, traj_file=None)
else:
bulk = model.bulk_reference.copy()
print("Found bulk_reference, lattice constant", bulk.get_cell()[0,0] )
bulk.set_calculator(model.bulk_reference.calc)
a0 = bulk.cell[0,0] # get lattice constant from relaxed bulk
e0 = bulk.get_potential_energy()/8.0
print "got a0 ", a0
print "got e0 ", e0
def defect_energy(a0, e0, filename):
tmp = ase.io.read(os.path.dirname(__file__)+"/"+filename, index=':', format='extxyz')
defect = tmp[0]
# adjust lattice constant
# defect.set_cell([2*a0, 2*a0, 2*a0], scale_atoms=True)
defect.set_calculator(model.calculator)
# relax atom positions and cell