def test_set_abc(self):
a = 4.3
b = 3.2
c = 8.1
alpha = 110
origin = [3.1, 1.4, 4.1]
box = am.Box(a=a, b=b, c=c, alpha=alpha, origin=origin)
assert np.isclose(box.a, a)
assert np.isclose(box.b, b)
assert np.isclose(box.c, c)
assert np.isclose(box.alpha, alpha)
assert np.isclose(box.beta , 90.0)
assert np.isclose(box.gamma, 90.0)
assert np.allclose(box.origin, origin)
a = 24.5
b = 236.2
c = 42.5
beta = 101
box = am.Box(a=a, b=b, c=c, beta=beta)
assert np.isclose(box.a, a)
assert np.isclose(box.b, b)
assert np.isclose(box.c, c)
assert np.isclose(box.alpha, 90.0)
assert np.isclose(box.beta , beta)
assert np.isclose(box.gamma, 90.0)
assert np.allclose(box.origin, np.zeros(3))
def test_set_hi_los(self):
xlo = -1
xhi = 5
ylo = -2.1
yhi = 5
zlo = 0.1
zhi = 3.1
xy = 0.5
box = am.Box(xlo=xlo,
xhi=xhi,
ylo=ylo,
yhi=yhi,
zlo=zlo,
zhi=zhi,
xy=xy)
assert np.isclose(box.xlo, xlo)
assert np.isclose(box.xhi, xhi)
assert np.isclose(box.ylo, ylo)
assert np.isclose(box.yhi, yhi)
assert np.isclose(box.zlo, zlo)
assert np.isclose(box.zhi, zhi)
assert np.isclose(box.xz, 0.0)
assert np.isclose(box.xy, xy)
assert np.isclose(box.yz, 0.0)
xlo = -143
xhi = 125
ylo = -124
yhi = 364
zlo = -172
zhi = 235
yz = 10
box = am.Box(xlo=xlo,
xhi=xhi,
ylo=ylo,
yhi=yhi,
zlo=zlo,
zhi=zhi,
yz=yz)
assert np.isclose(box.xlo, xlo)
assert np.isclose(box.xhi, xhi)
assert np.isclose(box.ylo, ylo)
assert np.isclose(box.yhi, yhi)
assert np.isclose(box.zlo, zlo)
assert np.isclose(box.zhi, zhi)
assert np.isclose(box.xz, 0.0)
assert np.isclose(box.xy, 0.0)
assert np.isclose(box.yz, yz)
def test_default(self):
box = am.Box()
assert np.allclose(box.avect, [1., 0., 0.])
assert np.allclose(box.bvect, [0., 1., 0.])
assert np.allclose(box.cvect, [0., 0., 1.])
assert np.allclose(box.origin, [0., 0., 0.])
assert np.allclose(box.vects, [[1., 0., 0.], [0., 1., 0.], [0., 0., 1.]])
assert np.isclose(box.a, 1.0)
assert np.isclose(box.b, 1.0)
assert np.isclose(box.c, 1.0)
assert np.isclose(box.alpha, 90.0)
assert np.isclose(box.beta , 90.0)
assert np.isclose(box.gamma, 90.0)
assert np.isclose(box.xlo, 0.0)
assert np.isclose(box.xhi, 1.0)
assert np.isclose(box.ylo, 0.0)
assert np.isclose(box.yhi, 1.0)
assert np.isclose(box.zlo, 0.0)
assert np.isclose(box.zhi, 1.0)
assert np.isclose(box.lx, 1.0)
assert np.isclose(box.ly, 1.0)
assert np.isclose(box.lz, 1.0)
assert np.isclose(box.xy, 0.0)
assert np.isclose(box.xz, 0.0)
assert np.isclose(box.yz, 0.0)
assert np.isclose(box.volume, 1.0)
def test_set_lengths(self):
lx=42
ly=57
lz=112
xz=15
origin=[1,2,3]
box = am.Box(lx=lx, ly=ly, lz=lz, xz=xz, origin=origin)
assert np.isclose(box.lx, lx)
assert np.isclose(box.ly, ly)
assert np.isclose(box.lz, lz)
assert np.isclose(box.xz, xz)
assert np.isclose(box.xy, 0.0)
assert np.isclose(box.yz, 0.0)
assert np.allclose(box.origin, origin)
lx=163
ly=347
lz=235
xy=19
box.set_lengths(lx=lx, ly=ly, lz=lz, xy=xy)
assert np.isclose(box.lx, lx)
assert np.isclose(box.ly, ly)
assert np.isclose(box.lz, lz)
assert np.isclose(box.xz, 0.0)
assert np.isclose(box.xy, xy)
assert np.isclose(box.yz, 0.0)
assert np.allclose(box.origin, np.zeros(3))
def test_dmag_and_dvect():
pos_0 = np.random.uniform(1.0, 10.0, size=(200, 3))
pos_0[10] = [12.1234, 12.1234, 12.1234]
pos_0[11] = [7.124, 132.15, 12.235]
pos_1 = np.random.uniform(1.0, 10.0, size=(200, 3))
pos_1[10] = [12.1234, 12.1234, 12.1234]
pos_1[11] = [18.124, 1.15, 1.235]
box = am.Box(vects=[[20.0, 0.0, 0.0], [0.0, 135.0, 0.0], [0.0, 0.0, 20.0]])
# Test for all periodic boundaries
pbc = [True, True, True]
dvect = am.dvect(pos_0, pos_1, box, pbc)
dmag = am.dmag(pos_0, pos_1, box, pbc)
assert np.allclose(np.linalg.norm(dvect, axis=1), dmag)
assert np.allclose(dvect[10], [0.0, 0.0, 0.0])
assert np.allclose(dvect[11], [-9., 4., 9.])
assert np.isclose(dmag[10], 0.0)
assert np.isclose(dmag[11], 13.341664064126334)
# Test for all nono-periodic boundaries
pbc = [False, False, False]
dvect = am.dvect(pos_0, pos_1, box, pbc)
dmag = am.dmag(pos_0, pos_1, box, pbc)
assert np.allclose(np.linalg.norm(dvect, axis=1), dmag)
assert np.allclose(dvect[10], [0.0, 0.0, 0.0])
assert np.allclose(dvect[11], [11., -131., -11.])
assert np.isclose(dmag[10], 0.0)
assert np.isclose(dmag[11], 131.92043056327552)
def test_vectortocartesian():
# Test 3 indices
box = am.Box(a=3, b=4, c=5, alpha=90, beta=90, gamma=90)
assert np.allclose(am.tools.miller.vectortocartesian([1, 2, 3], box),
np.array([3, 8, 15]))
box = am.Box(a=3, b=4, c=5, alpha=90, beta=90, gamma=80)
assert np.allclose(am.tools.miller.vectortocartesian([1, 1, 1], box),
np.array([[3.69459271, 3.93923101, 5.]]))
# Test 4 indices
box = am.Box(a=3, b=3, c=5, alpha=90, beta=90, gamma=120)
assert np.allclose(am.tools.miller.vectortocartesian([-2, 1, 1, 1], box),
np.array([-9, 0, 5]))
box = am.Box(a=3, b=4, c=5, alpha=90, beta=90, gamma=120)
with pytest.raises(AssertionError):
am.tools.miller.vectortocartesian([-2, 1, 1, 1], box)
def test_vector_crystal_to_cartesian():
# Test 3 indices
box = am.Box(a=3, b=4, c=5, alpha=90, beta=90, gamma=90)
assert np.allclose(vector_crystal_to_cartesian([1,2,3], box),
np.array([ 3, 8, 15]))
box = am.Box(a=3, b=4, c=5, alpha=90, beta=90, gamma=80)
assert np.allclose(vector_crystal_to_cartesian([1,1,1], box),
np.array([[3.69459271, 3.93923101, 5. ]]))
# Test 4 indices
box = am.Box(a=3, b=3, c=5, alpha=90, beta=90, gamma=120)
assert np.allclose(vector_crystal_to_cartesian([-2, 1, 1, 1], box),
np.array([-9, 0, 5]))
box = am.Box(a=3, b=4, c=5, alpha=90, beta=90, gamma=120)
with pytest.raises(ValueError):
vector_crystal_to_cartesian([-2, 1, 1, 1], box)
def test_is_lammps_norm(self):
vects = np.array([[123, 0, 0], [4, 142, 0], [7, -9, 145]])
box = am.Box(vects=vects)
assert box.is_lammps_norm()
vects = np.array([[123, 1, 0], [4, 142, 0], [7, -9, 145]])
box = am.Box(vects=vects)
assert not box.is_lammps_norm()
vects = np.array([[123, 0, 1], [4, 142, 0], [7, -9, 145]])
box = am.Box(vects=vects)
assert not box.is_lammps_norm()
vects = np.array([[123, 0, 0], [4, 142, 1], [7, -9, 145]])
box = am.Box(vects=vects)
assert not box.is_lammps_norm()
vects = np.array([[-123, 0, 0], [4, 142, 0], [7, -9, 145]])
box = am.Box(vects=vects)
assert not box.is_lammps_norm()
vects = np.array([[123, 0, 0], [4, -142, 0], [7, -9, 145]])
box = am.Box(vects=vects)
assert not box.is_lammps_norm()
vects = np.array([[123, 0, 0], [4, 142, 0], [7, -9, -145]])
box = am.Box(vects=vects)
assert not box.is_lammps_norm()
def fcc_edge(self):
axes = np.array([[1, 0, -1], [1, 1, 1], [1, -2, 1]])
alat = uc.set_in_units(4.0248, 'angstrom')
C11 = uc.set_in_units(113.76, 'GPa')
C12 = uc.set_in_units(61.71, 'GPa')
C44 = uc.set_in_units(31.25, 'GPa')
c = am.ElasticConstants(C11=C11, C12=C12, C44=C44)
burgers = alat / 2 * np.array([1., 0., -1.])
# initializing a new Stroh object using the data
stroh = am.defect.Stroh(c, burgers, axes=axes)
pos_test = uc.set_in_units(np.array([12.4, 13.5, -10.6]), 'angstrom')
disp = stroh.displacement(pos_test)
print("displacement =", uc.get_in_units(disp, 'angstrom'), 'angstrom')
# monopole system
box = am.Box(a=alat, b=alat, c=alat)
atoms = am.Atoms(natoms=4,
prop={
'atype':
1,
'pos': [[0.0, 0.0, 0.0], [0.5, 0.5, 0.0],
[0.0, 0.5, 0.5], [0.5, 0.0, 0.5]]
})
ucell = am.System(atoms=atoms, box=box, scale=True)
system = am.rotate_cubic(ucell, axes)
shift = np.array(
[0.12500000000000, 0.50000000000000, 0.00000000000000])
new_pos = system.atoms_prop(key='pos', scale=True) + shift
system.atoms_prop(key='pos', value=new_pos, scale=True)
system.supersize((-7, 7), (-6, 6), (0, 1))
disp = stroh.displacement(system.atoms_prop(key='pos'))
system.atoms_prop(key='pos', value=system.atoms_prop(key='pos') + disp)
system.pbc = (False, False, True)
system.wrap()
pos = system.atoms_prop(key='pos')
x = uc.get_in_units(pos[:, 0], 'angstrom')
y = uc.get_in_units(pos[:, 1], 'angstrom')
plt.figure(figsize=(8, 8))
plt.scatter(x, y, s=30)
plt.xlim(min(x), max(x))
plt.ylim(min(y), max(y))
plt.xlabel('x-position (Angstrom)', fontsize='large')
plt.ylabel('y-position (Angstrom)', fontsize='large')
plt.show()
def test_model(self):
box = am.Box.cubic(5.42)
model = box.model()
assert np.allclose(uc.value_unit(model['box']['avect']), np.array([5.42, 0.0, 0.0]))
assert np.allclose(uc.value_unit(model['box']['bvect']), np.array([0.0, 5.42, 0.0]))
assert np.allclose(uc.value_unit(model['box']['cvect']), np.array([0.0, 0.0, 5.42]))
assert np.allclose(uc.value_unit(model['box']['origin']), np.array([0.0, 0.0, 0.0]))
box = am.Box(model=model)
assert np.allclose(box.vects, np.array([[5.42, 0.0, 0.0],
[0.0, 5.42, 0.0],
[0.0, 0.0, 5.42]]))
def load_model(self, model, name=None):
"""
Loads record contents from a given model.
Parameters
----------
model : str or DataModelDict
The model contents of the record to load.
name : str, optional
The name to assign to the record. Often inferred from other
attributes if not given.
"""
# Load universal and subset content
super().load_model(model, name=name)
calc = self.model[self.modelroot]
# Load calculation-specific content
run_params = calc['calculation']['run-parameter']
self.strainrange = run_params['strain-range']
# Load phase-state info
self.pressure_xx = uc.value_unit(calc['phase-state']['pressure-xx'])
self.pressure_yy = uc.value_unit(calc['phase-state']['pressure-yy'])
self.pressure_zz = uc.value_unit(calc['phase-state']['pressure-zz'])
# Load results
if self.status == 'finished':
self.__initial_dump = {
'filename': calc['initial-system']['artifact']['file'],
'symbols': calc['initial-system']['symbols']
}
self.__final_dump = {
'filename': calc['final-system']['artifact']['file'],
'symbols': calc['final-system']['symbols']
}
lx = uc.value_unit(calc['measured-box-parameter']['lx'])
ly = uc.value_unit(calc['measured-box-parameter']['ly'])
lz = uc.value_unit(calc['measured-box-parameter']['lz'])
xy = uc.value_unit(calc['measured-box-parameter']['xy'])
xz = uc.value_unit(calc['measured-box-parameter']['xz'])
yz = uc.value_unit(calc['measured-box-parameter']['yz'])
self.__final_box = am.Box(lx=lx, ly=ly, lz=lz, xy=xy, xz=xz, yz=yz)
self.__potential_energy = uc.value_unit(calc['cohesive-energy'])
mps = calc['measured-phase-state']
self.__measured_pressure_xx = uc.value_unit(mps['pressure-xx'])
self.__measured_pressure_yy = uc.value_unit(mps['pressure-yy'])
self.__measured_pressure_zz = uc.value_unit(mps['pressure-zz'])
self.__measured_pressure_xy = uc.value_unit(mps['pressure-xy'])
self.__measured_pressure_xz = uc.value_unit(mps['pressure-xz'])
self.__measured_pressure_yz = uc.value_unit(mps['pressure-yz'])
def load(poscar):
"""
Reads a poscar-style coordination file for a system.
Returns an atomman.System, and a list of elements if the file gives them.
"""
#Read in all lines of the file
with uber_open_rmode(poscar) as f:
lines = f.read().split('\n')
#Interpret box information
box_scale = float(lines[1])
avect = np.array(lines[2].split(), dtype='float64') * box_scale
bvect = np.array(lines[3].split(), dtype='float64') * box_scale
cvect = np.array(lines[4].split(), dtype='float64') * box_scale
box = am.Box(avect=avect, bvect=bvect, cvect=cvect)
#Read in elements, number of types, and style info
try:
typenums = np.array(lines[5].split(), dtype='int32')
elements = [None for n in xrange(len(typenums))]
style = lines[6]
start_i = 7
except:
elements = lines[5].split()
typenums = np.array(lines[6].split(), dtype='int32')
style = lines[7]
start_i = 8
#Build atype list
atype = np.array([], dtype='int32')
for i in xrange(len(typenums)):
atype = np.hstack((atype, np.full(typenums[i], i + 1, dtype='int32')))
#Check which coordinate style to use
if style[0] in 'cCkK':
scale = False
else:
scale = True
#Read in positions
natoms = np.sum(typenums)
pos = np.empty((natoms, 3), dtype='float64')
count = 0
for i in xrange(start_i, len(lines)):
terms = lines[i].split()
if len(terms) > 0:
pos[count, :] = np.array(terms, dtype='float64')
count += 1
atoms = am.Atoms(natoms=natoms, prop={'atype': atype, 'pos': pos})
system = am.System(atoms=atoms, box=box, scale=scale)
return system, elements
def load(ase_atoms):
"""Convert an ase.Atoms into an atomman.System and list of elements."""
assert has_ase, 'ase not imported'
box = am.Box(vects=ase_atoms.get_cell())
atoms = am.Atoms(natoms=len(ase_atoms))
atoms.prop(key='pos', value=ase_atoms.get_positions())
all_elements = np.array(ase_atoms.get_chemical_symbols())
elements, atype = np.unique(all_elements, return_inverse=True)
atype += 1
atoms.prop(key='atype', value=atype)
return am.System(atoms=atoms, box=box), elements
def test_atomic_no_imageflags(self):
box = am.Box(vects=[[1.25694013, 0. , 0. ],
[1.17551244, 4.01690452, 0. ],
[0.23122344, 0.0768582 , 0.76391945]])
pos = [[0.53342537, 0.70899278, 0.21800393],
[0.8766086 , 0.98893671, 0.57889022],
[0.78898178, 0.44740662, 0.49997271],
[0.78302097, 0.06197394, 0.77049739]]
atoms = am.Atoms(pos=pos, atype=1)
symbols = 'Al'
pbc = (True, True, True)
system = am.System(atoms=atoms, box=box, scale=True,
symbols=symbols, pbc=pbc)
self.load_dump(system, atom_style='atomic', units='metal')
def load(cif):
"""Reads in a CIF crystal file and returns an atomman.System and list of elements."""
assert has_diffpy, 'diffpy.Structure not imported'
dps = diffpy.Structure.structure.Structure()
#load from an open file-like object
if hasattr(cif, 'read'):
dps.readStr(cif.read())
#load using a file name
elif os.path.isfile(cif):
dps.read(cif)
#load from a string
else:
dps.readStr(cif)
all_elements = dps.element
elements, all_atype = np.unique(all_elements, return_inverse=True)
all_atype += 1
all_pos = dps.xyz
atype = []
pos = []
for a1, p1 in zip(all_atype, all_pos):
noMatch = True
for a2, p2 in zip(atype, pos):
if a1 == a2 and np.allclose(p1, p2):
noMatch = False
break
if noMatch:
atype.append(a1)
pos.append(p1)
atoms = am.Atoms(natoms=len(pos), prop={'atype':atype, 'pos':pos})
box = am.Box(a=dps.lattice.a,
b=dps.lattice.b,
c=dps.lattice.c,
alpha=dps.lattice.alpha,
beta=dps.lattice.beta,
gamma=dps.lattice.gamma)
return am.System(atoms=atoms, box=box, pbc=(True,True,True), scale=True), list(elements)
def test_set_vectors(self):
avect = [3.2, 0.0, 0.0]
bvect = [0.1, 3.2, 0.0]
cvect = [-0.2, 0.15, 3.2]
origin = [3.1, 1.4, 4.1]
box = am.Box(avect=avect, bvect=bvect, cvect=cvect, origin=origin)
assert np.allclose(box.avect, avect)
assert np.allclose(box.bvect, bvect)
assert np.allclose(box.cvect, cvect)
assert np.allclose(box.origin, origin)
avect = [6.2, 0.0, 0.0]
bvect = [0.0, 4.2, 0.0]
cvect = [0.0, 0.1, 5.2]
box.set_vectors(avect=avect, bvect=bvect, cvect=cvect)
assert np.allclose(box.avect, avect)
assert np.allclose(box.bvect, bvect)
assert np.allclose(box.cvect, cvect)
assert np.allclose(box.origin, np.zeros(3))
def process_results(self, results_dict):
"""
Processes calculation results and saves them to the object's results
attributes.
Parameters
----------
results_dict: dict
The dictionary returned by the calc() method.
"""
self.__initial_dump = {
'filename': results_dict['dumpfile_initial'],
'symbols': results_dict['symbols_initial']
}
self.__final_dump = {
'filename': results_dict['dumpfile_final'],
'symbols': results_dict['symbols_final']
}
lx = results_dict['lx'] / (self.system_mods.a_mults[1] -
self.system_mods.a_mults[0])
ly = results_dict['ly'] / (self.system_mods.b_mults[1] -
self.system_mods.b_mults[0])
lz = results_dict['lz'] / (self.system_mods.c_mults[1] -
self.system_mods.c_mults[0])
xy = results_dict['xy'] / (self.system_mods.b_mults[1] -
self.system_mods.b_mults[0])
xz = results_dict['xz'] / (self.system_mods.c_mults[1] -
self.system_mods.c_mults[0])
yz = results_dict['yz'] / (self.system_mods.c_mults[1] -
self.system_mods.c_mults[0])
self.__final_box = am.Box(lx=lx, ly=ly, lz=lz, xy=xy, xz=xz, yz=yz)
self.__potential_energy = results_dict['E_pot']
self.__measured_pressure_xx = results_dict['measured_pxx']
self.__measured_pressure_yy = results_dict['measured_pyy']
self.__measured_pressure_zz = results_dict['measured_pzz']
self.__measured_pressure_xy = results_dict['measured_pxy']
self.__measured_pressure_xz = results_dict['measured_pxz']
self.__measured_pressure_yz = results_dict['measured_pyz']
def ucell(self, a_scale, c_scale):
"""
Generates a bct unit cell for intermediate structures based on the
given bcc and fcc lattice constants.
For the scaling parameters, values of a_scale = c_scale = 0 corresponds
to the given fcc lattice, and values of a_scale = c_scale = 1
corresponds to the given bcc lattice.
Parameters
----------
a_scale : float
Scaling parameter for the bct structure's a lattice parameter.
c_scale : float
Scaling parameter for the bct structure's c lattice parameter.
Returns
-------
ucell : atomman.System
The corresponding bct unit cell.
"""
# Set the ideal constants based on a_fcc and a_bcc
a_0 = self.a_fcc * 2**0.5 / 2
c_0 = self.a_fcc
a_1 = c_1 = self.a_bcc
# Compute the bct lattice constants using the scale parameters
a = a_0 * (1 - a_scale) + a_1 * a_scale
c = c_0 * (1 - c_scale) + c_1 * c_scale
# Generate box, atoms and system for the bct unit cell
box = am.Box().tetragonal(a=a, c=c)
atoms = am.Atoms(pos=[[0.0, 0.0, 0.0], [0.5, 0.5, 0.5]])
ucell = am.System(atoms=atoms, box=box, symbols=self.symbol, scale=True)
return ucell
def boxhexagonal(self):
return am.Box(a=3, b=3, c=8, alpha=90, beta=90, gamma=120)
def calc_cij(lammps_command,
system,
potential,
symbols,
p_xx=0.0,
p_yy=0.0,
p_zz=0.0,
delta=1e-5,
cycle=0):
"""Runs cij_script and returns current Cij, stress, Ecoh, and new system guess."""
#Get lammps units
lammps_units = lmp.style.unit(potential.units)
#Define lammps variables
lammps_variables = {}
lammps_variables['atomman_system_info'] = lmp.sys_gen(
units=potential.units,
atom_style=potential.atom_style,
ucell=system,
size=np.array([[0, 3], [0, 3], [0, 3]]))
lammps_variables['atomman_pair_info'] = potential.pair_info(symbols)
lammps_variables['delta'] = delta
lammps_variables['steps'] = 2
#Write lammps input script
template_file = 'cij.template'
lammps_script = 'cij.in'
with open(template_file) as f:
template = f.read()
with open(lammps_script, 'w') as f:
f.write(iprPy.tools.filltemplate(template, lammps_variables, '<', '>'))
#Run lammps
output = lmp.run(lammps_command, lammps_script)
shutil.move('log.lammps', 'cij-' + str(cycle) + '-log.lammps')
#Extract LAMMPS thermo data. Each term ranges i=0-12 where i=0 is undeformed
#The remaining values are for -/+ strain pairs in the six unique directions
lx = uc.set_in_units(np.array(output.finds('Lx')), lammps_units['length'])
ly = uc.set_in_units(np.array(output.finds('Ly')), lammps_units['length'])
lz = uc.set_in_units(np.array(output.finds('Lz')), lammps_units['length'])
xy = uc.set_in_units(np.array(output.finds('Xy')), lammps_units['length'])
xz = uc.set_in_units(np.array(output.finds('Xz')), lammps_units['length'])
yz = uc.set_in_units(np.array(output.finds('Yz')), lammps_units['length'])
pxx = uc.set_in_units(np.array(output.finds('Pxx')),
lammps_units['pressure'])
pyy = uc.set_in_units(np.array(output.finds('Pyy')),
lammps_units['pressure'])
pzz = uc.set_in_units(np.array(output.finds('Pzz')),
lammps_units['pressure'])
pxy = uc.set_in_units(np.array(output.finds('Pxy')),
lammps_units['pressure'])
pxz = uc.set_in_units(np.array(output.finds('Pxz')),
lammps_units['pressure'])
pyz = uc.set_in_units(np.array(output.finds('Pyz')),
lammps_units['pressure'])
try:
pe = uc.set_in_units(np.array(output.finds('v_peatom')),
lammps_units['energy'])
assert len(pe) > 0
except:
pe = uc.set_in_units(np.array(output.finds('peatom')),
lammps_units['energy'])
#Set the six non-zero strain values
strains = np.array([(lx[2] - lx[1]) / lx[0], (ly[4] - ly[3]) / ly[0],
(lz[6] - lz[5]) / lz[0], (yz[8] - yz[7]) / lz[0],
(xz[10] - xz[9]) / lz[0], (xy[12] - xy[11]) / ly[0]])
#calculate cij using stress changes associated with each non-zero strain
cij = np.empty((6, 6))
for i in xrange(6):
delta_stress = np.array([
pxx[2 * i + 1] - pxx[2 * i + 2], pyy[2 * i + 1] - pyy[2 * i + 2],
pzz[2 * i + 1] - pzz[2 * i + 2], pyz[2 * i + 1] - pyz[2 * i + 2],
pxz[2 * i + 1] - pxz[2 * i + 2], pxy[2 * i + 1] - pxy[2 * i + 2]
])
cij[i] = delta_stress / strains[i]
for i in xrange(6):
for j in xrange(i):
cij[i, j] = cij[j, i] = (cij[i, j] + cij[j, i]) / 2
C = am.ElasticConstants(Cij=cij)
if np.allclose(C.Cij, 0.0):
raise RuntimeError('Divergence of elastic constants to <= 0')
try:
S = C.Sij
except:
raise RuntimeError('singular C:\n' + str(C.Cij))
#extract the current stress state
stress = -1 * np.array([[pxx[0], pxy[0], pxz[0]], [pxy[0], pyy[0], pyz[0]],
[pxz[0], pyz[0], pzz[0]]])
s_xx = stress[0, 0] + p_xx
s_yy = stress[1, 1] + p_yy
s_zz = stress[2, 2] + p_zz
new_a = system.box.a / (S[0, 0] * s_xx + S[0, 1] * s_yy + S[0, 2] * s_zz +
1)
new_b = system.box.b / (S[1, 0] * s_xx + S[1, 1] * s_yy + S[1, 2] * s_zz +
1)
new_c = system.box.c / (S[2, 0] * s_xx + S[2, 1] * s_yy + S[2, 2] * s_zz +
1)
if new_a <= 0 or new_b <= 0 or new_c <= 0:
raise RuntimeError('Divergence of box dimensions to <= 0')
newbox = am.Box(a=new_a, b=new_b, c=new_c)
system_new = deepcopy(system)
system_new.box_set(vects=newbox.vects, scale=True)
return {'C': C, 'stress': stress, 'ecoh': pe[0], 'system_new': system_new}
def rotate_cubic(system, axes):
"""
Rotate a cubic system according to the specified crystallographic axes.
Returns an orthogonal system whose box lengths are:
a * sqrt(i^2+j^2+k^2)
where a is the original cubic box length, and ijk are the crystallographic
indicies for the specific direction.
"""
# rotate system generically
system = rotate(system, axes)
# test for cubic
a = system.box.a
try:
assert np.isclose(a, system.box.b), str(a) + ' ' + str(system.box.b)
assert np.isclose(a, system.box.c), str(a) + ' ' + str(system.box.c)
assert np.isclose(90.0, system.box.alpha), str(system.box.alpha)
assert np.isclose(90.0, system.box.beta), str(system.box.beta)
assert np.isclose(90.0, system.box.gamma), str(system.box.gamma)
except:
raise ValueError('Cubic system not given')
# Test for integer axes values
try:
for ax_val in axes.flat:
assert np.isclose(ax_val, int(ax_val))
except:
raise ValueError('axes values must be integers')
# Get magnitudes of the axes
mag = np.linalg.norm(axes, axis=1)
# compute number of atoms for the new system
natoms = system.natoms * mag[0] * mag[1] * mag[2]
if np.isclose(int(round(natoms)), natoms):
natoms = int(round(natoms))
else:
raise ValueError(
'not an integer number of atoms associated with the axes.')
# create a new box with scaled lattice parameters
box = am.Box(a=a * mag[0],
b=a * mag[1],
c=a * mag[2],
origin=system.box.origin)
# supersize the rotated box
m = int(ceil(max(mag)))
system = am.tools.supersize(system, (-m, m), (-m, m), (-m, m))
# filter atoms for only those in the new box
data = system.atoms.data
# round x-positions near xlo, xhi and only keep data for atoms where xlo
# <= x < xhi
data[np.where(np.isclose(data.T[1], box.xlo, atol=1e-8, rtol=0)),
1] = box.xlo
data = data[data.T[1] >= box.xlo]
data[np.where(np.isclose(data.T[1], box.xhi, atol=1e-8, rtol=0)),
1] = box.xhi
data = data[data.T[1] < box.xhi]
# round y-positions near ylo, yhi and only keep data for atoms where ylo
# <= y < yhi
data[np.where(np.isclose(data.T[2], box.ylo, atol=1e-8, rtol=0)),
2] = box.ylo
data = data[data.T[2] >= box.ylo]
data[np.where(np.isclose(data.T[2], box.yhi, atol=1e-8, rtol=0)),
2] = box.yhi
data = data[data.T[2] < box.yhi]
# round z-positions near zlo, zhi and only keep data for atoms where zlo
# <= z < zhi
data[np.where(np.isclose(data.T[3], box.zlo, atol=1e-8, rtol=0)),
3] = box.zlo
data = data[data.T[3] >= box.zlo]
data[np.where(np.isclose(data.T[3], box.zhi, atol=1e-8, rtol=0)),
3] = box.zhi
data = data[data.T[3] < box.zhi]
# deepcopy the data array to guarantee that it is new and separate
data = deepcopy(data)
# rebuild views
start = 0
view = OrderedDict()
for k in system.atoms.view:
vshape = (len(data), ) + system.atoms.view[k].shape[1:]
view[k] = data[:, start:start + system.atoms.view[k][0].size]
view[k].shape = vshape
start = start + system.atoms.view[k][0].size
# create atoms from natoms, data, view and dtype
atoms = am.Atoms(natoms=natoms,
data=data,
view=view,
prop_dtype=system.atoms.dtype)
# return new system
return am.System(box=box, atoms=atoms)
def boxcubic(self):
return am.Box(a=3, b=3, c=3, alpha=90, beta=90, gamma=90)
def quick_a_Cij(lammps_command,
system,
potential,
symbols,
mpi_command=None,
p_xx=0.0,
p_yy=0.0,
p_zz=0.0,
delta=1e-5,
tol=1e-10,
diverge_scale=3.):
"""
Quickly refines static orthorhombic system by evaluating the elastic constants and the virial pressure.
Arguments:
lammps_command -- directory location for lammps executable
system -- atomman.System to statically deform and evaluate a,b,c and Cij at a given pressure
potential -- atomman.lammps.Potential representation of a LAMMPS implemented potential
symbols -- list of element-model symbols for the Potential that correspond to the System's atypes
Keyword Arguments:
p_xx, p_yy, p_zz -- tensile pressures to equilibriate to. Default is 0.0 for all.
delta -- the strain range to use in calculating the elastic constants. Default is 1e-5.
tol -- the relative tolerance criterion for identifying box size convergence. Default is 1e-10.
diverge_scale -- identifies a divergent system if x / diverge_scale < x < x * diverge_scale is not True for x = a,b,c.
"""
#initial parameter setup
converged = False #flag for if values have converged
#define boxes for iterating
system_current = deepcopy(
system) #system with box parameters being evaluated
system_old = None #system with previous box parameters evaluated
for cycle in xrange(100):
#Run LAMMPS and evaluate results based on system_old
results = calc_cij(lammps_command, system_current, potential, symbols,
p_xx, p_yy, p_zz, delta, cycle)
system_new = results['system_new']
#Test if box has converged to a single size
if np.allclose(system_new.box.vects,
system_current.box.vects,
rtol=tol,
atol=0):
converged = True
break
#Test if box has converged to two sizes
elif system_old is not None and np.allclose(
system_new.box.vects, system_old.box.vects, rtol=tol, atol=0):
#Run LAMMPS Cij script using average between alat0 and alat1
box = am.Box(a=(system_new.box.a + system_old.box.a) / 2.,
b=(system_new.box.b + system_old.box.b) / 2.,
c=(system_new.box.c + system_old.box.c) / 2.)
system_current.box_set(vects=box.vects, scale=True)
results = calc_cij(lammps_command, system_current, potential,
symbols, p_xx, p_yy, p_zz, delta, cycle + 1)
converged = True
break
#Test if values have diverged from initial guess
elif system_new.box.a < system.box.a / diverge_scale or system_new.box.a > system.box.a * diverge_scale:
raise RuntimeError('Divergence of box dimensions')
elif system_new.box.b < system.box.b / diverge_scale or system_new.box.b > system.box.b * diverge_scale:
raise RuntimeError('Divergence of box dimensions')
elif system_new.box.c < system.box.c / diverge_scale or system_new.box.c > system.box.c * diverge_scale:
raise RuntimeError('Divergence of box dimensions')
elif results['ecoh'] == 0.0:
raise RuntimeError('Divergence: cohesive energy is 0')
#if not converged or diverged, update system_old and system_current
else:
system_old, system_current = system_current, system_new
#Return values if converged
if converged:
return results
else:
raise RuntimeError('Failed to converge after 100 cycles')
def supersize(system, a_size, b_size, c_size):
"""
Builds a large system based on a seed system and multipliers.
Keyword Arguments:
system -- atomman.System to use as the seed.
a_size -- int or tuple of 2 ints for multiplying along the avect direction.
b_size -- int or tuple of 2 ints for multiplying along the bvect direction.
c_size -- int or tuple of 2 ints for multiplying along the cvect direction.
The multiplier values *_size are taken to be integer tuples (m, n) where m <= 0 and n >= 0.
The system multiplication works such that if n = -m, then the seed system's origin will be at the center of the new system.
If only one integer is given, then it is assigned to m or n depending on its sign, and the other value is taken to be 0.
"""
#initial parameter setup
sizes = [a_size, b_size, c_size]
mults = np.array([0, 0, 0], dtype=int)
vects = system.box.vects
origin = system.box.origin
spos = system.atoms_prop(key='pos', scale=True)
for i in xrange(3):
#check values in sizes
if isinstance(sizes[i], (int, long)):
if sizes[i] > 0:
sizes[i] = (0, sizes[i])
elif sizes[i] < 0:
sizes[i] = (sizes[i], 0)
elif isinstance(sizes[i], tuple):
assert len(sizes[i]) == 2, 'Invalid system multipliers'
assert isinstance(
sizes[i][0],
(int, long)) and sizes[i][0] <= 0, 'Invalid system multipliers'
assert isinstance(
sizes[i][1],
(int, long)) and sizes[i][1] >= 0, 'Invalid system multipliers'
else:
raise TypeError('Invalid system multipliers')
#calculate multipliers and scale box and first set of positions accordingly
mults[i] = sizes[i][1] - sizes[i][0]
assert mults[i] != 0, 'Cannot multiply system dimension by zero'
spos[:, i] /= mults[i]
origin += vects[i] * sizes[i][0]
vects[i] *= mults[i]
#initilize new Box and Atoms
box = atomman.Box(vects=vects, origin=origin)
natoms = system.natoms * mults[0] * mults[1] * mults[2]
atoms = atomman.Atoms(natoms=natoms)
#Copy over all property values using numpy broadcasting
for prop in system.atoms_prop():
o_values = system.atoms_prop(key=prop)
n_values = np.empty(
(mults[0] * mults[1] * mults[2], ) + o_values.shape,
dtype=o_values.dtype)
n_values[:] = system.atoms_prop(key=prop)
n_shape = n_values.shape
n_shape = (n_shape[0] * n_shape[1], ) + n_shape[2:]
atoms.prop(key=prop, value=n_values.reshape(n_shape))
#Expand spos using broadcasting
n_spos = np.empty((mults[0] * mults[1] * mults[2], ) + spos.shape)
n_spos[:] = spos
n_shape = n_spos.shape
n_shape = (n_shape[0] * n_shape[1], ) + n_shape[2:]
n_spos = n_spos.reshape(n_shape)
#use broadcasting to create arrays to add to spos
test = np.empty(mults[0] * system.natoms)
test.shape = (system.natoms, mults[0])
test[:] = np.arange(mults[0])
x = test.T.flatten()
test = np.empty(mults[1] * len(x))
test.shape = (len(x), mults[1])
test[:] = np.arange(mults[1])
y = test.T.flatten()
test.shape = (mults[1], len(x))
test[:] = x
x = test.flatten()
test = np.empty(mults[2] * len(x))
test.shape = (len(x), mults[2])
test[:] = np.arange(mults[2])
z = test.T.flatten()
test.shape = (mults[2], len(x))
test[:] = x
x = test.flatten()
test[:] = y
y = test.flatten()
#xyz is displacement values to add to spos
xyz = np.hstack(
(x[:, np.newaxis], y[:, np.newaxis], z[:, np.newaxis])) * np.array(
[1. / mults[0], 1. / mults[1], 1. / mults[2]])
#save pos values, return new System
atoms.prop(key='pos', value=n_spos + xyz)
return atomman.System(box=box, atoms=atoms, scale=True)
def boxrhombohedral(self):
return am.Box(a=3, b=3, c=3, alpha=84, beta=84, gamma=84)
def boxorthorhombic(self):
return am.Box(a=3, b=4, c=5, alpha=90, beta=90, gamma=90)
def boxtriclinic(self):
return am.Box(a=3, b=4, c=5, alpha=74, beta=87, gamma=105)
def boxmonoclinic(self):
return am.Box(a=3, b=4, c=5, alpha=90, beta=105, gamma=90)
def make_screw_plate_old(self,
size=[40, 60, 3],
rad=[100, 115],
move=[0., 0., 0.],
filename="lmp_init.txt",
opt=None):
alat = uc.set_in_units(self.pot['lattice'], 'angstrom')
C11 = uc.set_in_units(self.pot['c11'], 'GPa')
C12 = uc.set_in_units(self.pot['c12'], 'GPa')
C44 = uc.set_in_units(self.pot['c44'], 'GPa')
axes = np.array([[1, -2, 1], [1, 0, -1], [1, 1, 1]])
unitx = alat * np.sqrt(6)
unity = alat * np.sqrt(2)
sizex = size[0]
sizey = size[1]
sizez = size[2]
c = am.ElasticConstants(C11=C11, C12=C12, C44=C44)
burgers = 0.5 * alat * -np.array([1., 1., 1.])
# initializing a new Stroh object using the data
stroh = am.defect.Stroh(c, burgers, axes=axes)
# monopole system
box = am.Box(a=alat, b=alat, c=alat)
atoms = am.Atoms(natoms=2,
prop={
'atype': 2,
'pos': [[0.0, 0.0, 0.0], [0.5, 0.5, 0.5]]
})
ucell = am.System(atoms=atoms, box=box, scale=True)
system = am.rotate_cubic(ucell, axes)
# shftx = 0.5 * alat * np.sqrt(6.) / 3.
shftx = 0.0
shfty = -1. / 3. * alat * np.sqrt(2) / 2.
# shfty = 2. / 3. * alat * np.sqrt(2) / 2.
center = [0.5 * unitx * sizex, 0.5 * unity * sizey]
new_pos = system.atoms_prop(key='pos') + np.array([shftx, shfty, 0.0])
system.atoms_prop(key='pos', value=new_pos)
system.supersize((0, sizex), (0, sizey), (0, sizez))
# to make a plate #
radius2 = rad[0] * rad[0]
radiusout2 = rad[1] * rad[1]
elements = []
for atom in system.atoms:
elements.append('Nb')
ase_atoms = am.convert.ase_Atoms.dump(system, elements)
pos = ase_atoms.get_positions()
delindex = []
for i in range(len(pos)):
atom = ase_atoms[i]
dx = pos[i, 0] - center[0]
dy = pos[i, 1] - center[1]
r = dx * dx + dy * dy
if r > radiusout2:
delindex.append(atom.index)
if r < radius2:
atom.symbol = 'W'
del ase_atoms[delindex]
(system, elements) = am.convert.ase_Atoms.load(ase_atoms)
# use neb, it's to generate init configuration
if opt in ['neb']:
system_init = copy.deepcopy(system)
shift = np.array([-0.5, -0.5, 0.0])
new_pos = system_init.atoms_prop(key='pos', scale=True) + shift
system_init.atoms_prop(key='pos', value=new_pos, scale=True)
disp = stroh.displacement(system_init.atoms_prop(key='pos'))
system_init.atoms_prop(key='pos',
value=system_init.atoms_prop(key='pos') +
disp)
shift = np.array([0.5, 0.50, 0.0])
new_pos = system_init.atoms_prop(key='pos', scale=True) + shift
system_init.atoms_prop(key='pos', value=new_pos, scale=True)
# for lammps read structure
lmp.atom_data.dump(system_init, "init.txt")
# for dd map plot
ase.io.write("lmp_perf.cfg", images=ase_atoms, format='cfg')
lmp.atom_data.dump(system, "lmp_perf.txt")
shift = np.array([-0.5, -0.5, 0.0])
new_pos = system.atoms_prop(key='pos', scale=True) + shift
system.atoms_prop(key='pos', value=new_pos, scale=True)
new_pos = system.atoms_prop(key='pos') + move
system.atoms_prop(key='pos', value=new_pos)
disp = stroh.displacement(system.atoms_prop(key='pos'))
# pull
pull = False
if pull is True:
core_rows = [disp[:, 2].argsort()[-3:][::-1]]
print(disp[core_rows])
exclus = np.arange(len(disp), dtype=int)
unitburger = np.mean(disp[core_rows][:, 2])
print(unitburger)
exclus = np.delete(exclus, core_rows)
disp[core_rows] -= 1. / 3. * unitburger
# disp[exclus] -= 1. / 3. * unitburger
system.atoms_prop(key='pos', value=system.atoms_prop(key='pos') + disp)
new_pos = system.atoms_prop(key='pos') - move
system.atoms_prop(key='pos', value=new_pos)
shift = np.array([0.500000, 0.500000, 0.000000])
new_pos = system.atoms_prop(key='pos', scale=True) + shift
system.atoms_prop(key='pos', value=new_pos, scale=True)
new_pos = system.atoms_prop(key='pos', scale=False)
# for lammps read structure
lmp.atom_data.dump(system, filename)
dis_atoms = am.convert.ase_Atoms.dump(system, elements)
return (ase_atoms, dis_atoms)
def boxtetragonal(self):
return am.Box(a=3, b=3, c=8, alpha=90, beta=90, gamma=90)
