def update_qm_region(atoms, dis_type='edge', cut=3.0, rr=10.0, qr=1):
"""
Routine for updating qm region of dislocation.
Args:
dis_type: Dislocation type can be edge or screw.
rr: determines radius of quantum sphere.
qr: is the number of quantum regions.
"""
core[:] = atoms.params['core']
fixed_mask = (np.sqrt((atoms.positions[:,0]-core[0])**2 + (atoms.positions[:,1]-core[1])**2) < rr)
cl = atoms.select(mask=fixed_mask, orig_index=True)
print 'Number of Atoms in Cluster', cl.n
cl.set_cutoff(cut)
cl.calc_connect()
cl = Atoms(cl)
x0 = Atoms('ref_slab.xyz')
x0.set_cutoff(cut)
x0.calc_connect()
alpha = calc_nye_tensor(cl, x0, 3, 3, cl.n)
cl.screw = alpha[2,2,:]
cl.edge = alpha[2,0,:]
if dis_type == 'screw':
defect_pos = cl.screw
elif dis_type == 'edge':
defect_pos = cl.edge
total_def = 0.0
c = np.array([0.,0.,0.])
mom = [3.0 for at in range(len(atoms))]
atoms.set_initial_magnetic_moments(mom)
for i in range(cl.n):
defect_pos = defect_pos + cl.edge[i]
c[1] = c[1] + cl.positions[i,0]*defect_pos[i]
c[2] = c[2] + cl.pos[i,0]*defect_pos[i]
c[0] = c[0]/total_def
c[1] = c[1]/total_def
c[2] = atoms.lattice[2,2]/2.
core[:] = c.copy()
old_qm_list = atoms.hybrid_vec.nonzero()[0]
new_qm_list = update_hysteretic_qm_region(atoms, old_qm_list, core[:],
qm_inner_radius,
qm_outer_radius,
update_marks=False)
#Force Mixing Potential requires hybrid property:
atoms.hybrid[:] = 0
atoms.hybrid[new_qm_list] = 1
#Distributed Force Mixing Properties:
atoms.hybrid_vec[:] = 0
atoms.hybrid_vec[new_qm_list] = 1
atoms.hybrid_1[:] = atoms.hybrid_vec[:]
atoms.params['core'] = core[:]
return
def __init__(self,
source,
format=None,
start=None,
stop=None,
step=None,
cache_mem_limit=-1,
rename=None,
**kwargs):
def file_exists(f):
return f == "stdin" or os.path.exists(f) or len(glob.glob(f)) > 0
self.source = source
self.format = format
self._start = start
self._stop = stop
self._step = step
self.cache_mem_limit = cache_mem_limit
logging.debug('AtomsReader memory limit %r' % self.cache_mem_limit)
self._source_len = None
self._cache_dict = {}
self._cache_list = []
self._cache_mem_usage = []
self.opened = False
self.reader = source
self.rename = rename
if isinstance(self.reader, basestring):
if '@' in self.reader:
self.reader, frames = self.reader.split('@')
frames = parse_slice(frames)
if start is not None or stop is not None or step is not None:
raise ValueError(
'Conflicting frame references start=%r stop=%r step=%r and @-sytnax %r'
% (start, stop, step, frames))
if isinstance(frames, int):
if frames >= 0:
frames = slice(frames, frames + 1, +1)
else:
frames = slice(frames, frames - 1, -1)
self._start, self._stop, self._step = frames.start, frames.stop, frames.step
self.filename = self.reader
self.opened = True
if self.reader in AtomsReaders:
if format is None:
format = self.reader
elif format != 'string':
self.reader = os.path.expanduser(self.reader)
glob_list = sorted(glob.glob(self.reader))
if (len(glob_list) == 0):
raise IOError("input file '%s' not found" % self.reader)
if len(glob_list) > 1:
self.reader = glob_list
else:
self.reader = glob_list[0]
filename, self.reader, new_format = infer_format(
self.reader, format, AtomsReaders)
if format is None:
format = new_format
# special cases if source is a list or tuple of filenames or Atoms objects
is_filename_sequence = False
is_list_of_atoms = False
if isinstance(self.reader, list) or isinstance(self.reader, tuple):
is_filename_sequence = True
is_list_of_atoms = True
for item in self.reader:
if '@' in item:
item = item[:item.index('@')]
if not isinstance(item, basestring) or not file_exists(item):
is_filename_sequence = False
if not isinstance(item, Atoms):
is_list_of_atoms = False
if is_filename_sequence:
self.reader = AtomsSequenceReader(self.reader,
format=format,
**kwargs)
elif is_list_of_atoms:
# dummy reader which copies from an existing list or tuple of Atoms objects
self.reader = [at.copy() for at in self.reader]
else:
if format is None:
format = self.reader.__class__
if format in AtomsReaders:
self.reader = AtomsReaders[format](self.reader, **kwargs)
# check if reader is still a string or list of strings - indicates missing files or unknown format
if isinstance(self.reader, basestring):
raise IOError("Cannot read Atoms from file %s" % self.reader)
elif isinstance(self.reader, list):
is_list_of_strings = True
for item in self.reader:
if not isinstance(item, basestring):
is_list_of_strings = False
break
if is_list_of_strings:
raise IOError("Cannot read Atoms from files %s" % self.reader)
if isinstance(self.reader, AtomsReader):
self.reader = AtomsReaderCopier(self.reader)
if not hasattr(self.reader, '__iter__'):
# call Atoms constructor - this has beneficial side effect of making a copy
self.reader = [Atoms(self.reader)]
def CubeReader(f, property_name='charge', discard_repeat=True, format=None):
def convert_line(line, *fmts):
return (f(s) for f, s in zip(fmts, line.split()))
if type(f) == type(''):
f = open(f)
opened = True
# First two lines are comments
comment1 = f.readline()
comment2 = f.readline()
# Now number of atoms and origin
n_atom, origin_x, origin_y, origin_z = convert_line(
f.readline(), int, float, float, float)
origin = farray([origin_x, origin_y, origin_z]) * BOHR
# Next three lines define number of voxels and shape of each element
shape = [0, 0, 0]
voxel = fzeros((3, 3))
for i in (1, 2, 3):
shape[i - 1], voxel[1, i], voxel[2, i], voxel[3, i] = convert_line(
f.readline(), int, float, float, float)
at = Atoms(n=n_atom, lattice=voxel * BOHR * shape)
at.add_property(property_name, 0.0)
prop_array = getattr(at, property_name)
# Now there's one line per atom
for i in frange(at.n):
at.z[i], prop_array[i], at.pos[1,
i], at.pos[2,
i], at.pos[3,
i] = convert_line(
f.readline(),
int, float,
float, float,
float)
at.pos[:, i] *= BOHR
at.set_atoms(at.z)
# Rest of file is volumetric data
data = np.fromiter((float(x) for x in f.read().split()), float, count=-1)
if data.size != shape[0] * shape[1] * shape[2]:
raise IOError("Bad array length - expected shape %r, but got size %d" %
(shape, data.size))
# Save volumetric data in at.data
data = farray(data.reshape(shape))
# Discard periodic repeats?
if discard_repeat:
at.data = data[:-1, :-1, :-1]
shape = [s - 1 for s in shape]
at.set_lattice(voxel * BOHR * shape, False)
at.params['comment1'] = comment1
at.params['comment2'] = comment2
at.params['origin'] = origin
at.params['shape'] = shape
# save grids in at.grid_x, at.grid_y, at.grid_z
if at.is_orthorhombic:
at.grid_x, at.grid_y, at.grid_z = np.mgrid[origin[1]:origin[1] +
at.lattice[1, 1]:shape[0] *
1j, origin[2]:origin[2] +
at.lattice[2, 2]:shape[1] *
1j, origin[3]:origin[3] +
at.lattice[3, 3]:shape[2] *
1j]
if opened:
f.close()
yield at
del final[remove_index]
for (i, ii) in enumerate(initial.arrays['ind']):
if ii == remove_index_f:
new_remove_index_f = i
remove_index_f = new_remove_index_f
final.positions[remove_index_f] = orig_pos
final.set_calculator(model.calculator)
print 'relaxing final config'
final = relax_atoms(final, tol=tol, traj_file=None)
#final = ase.io.read(os.path.join("final-relax", "castep.castep"))
final.set_calculator(model.calculator)
# make chain
images = [Atoms(initial)]
images += [Atoms(initial.copy()) for i in range(n_images)]
images += [Atoms(final)]
neb = NEB(images, k=0.1)
neb.interpolate()
for img in images:
img.set_calculator(model.calculator)
ase.io.write(sys.stdout, img, 'extxyz')
# perturb intermediate images
for img in images[1:-1]:
img.rattle(0.05)
# optimizer = FIRE(neb)
optimizer = MDMin(neb, dt=0.05)
def CP2KDirectoryReader(run_dir,
at_ref=None,
proj='quip',
calc_qm_charges=None,
calc_virial=False,
out_i=None,
qm_vacuum=6.0,
run_suffix='_extended',
format=None):
if at_ref is None:
filepot_xyz = os.path.join(run_dir, 'filepot.xyz')
if not os.path.exists(filepot_xyz):
# try looking up one level
filepot_xyz = os.path.join(run_dir, '../filepot.xyz')
if os.path.exists(filepot_xyz):
at_ref = Atoms(filepot_xyz)
else:
at_ref = Atoms(os.path.join(run_dir, 'cp2k_output.out'),
format='cp2k_output')
at = at_ref.copy()
cp2k_output_filename, cp2k_output = read_text_file(
os.path.join(run_dir, 'cp2k_output.out'))
cp2k_params = CP2KInputHeader(
os.path.join(run_dir, 'cp2k_input.inp.header'))
at.params.update(cp2k_params)
run_type = cp2k_run_type(cp2k_output=cp2k_output,
cp2k_input_header=cp2k_params)
try:
cluster_mark = getattr(at, 'cluster_mark' + run_suffix)
qm_list_a = ((cluster_mark != HYBRID_NO_MARK).nonzero()[0]).astype(
np.int32)
except AttributeError:
qm_list_a = fzeros(0, dtype=np.int32)
if calc_qm_charges is None:
calc_qm_charges = ''
try:
cur_qmmm_qm_abc = [
float(cp2k_params['QMMM_ABC_X']),
float(cp2k_params['QMMM_ABC_Y']),
float(cp2k_params['QMMM_ABC_Z'])
]
except KeyError:
if 'QM_cell' + run_suffix in at.params:
cur_qmmm_qm_abc = at.params['QM_cell' + run_suffix]
else:
cur_qmmm_qm_abc = qmmm_qm_abc(at, qm_list_a, qm_vacuum)
quip_cp2k_at = Atoms(os.path.join(run_dir, 'quip_cp2k.xyz'))
rev_sort_index_file = os.path.join(run_dir, '../quip_rev_sort_index')
fields = [int(x) for x in open(rev_sort_index_file).read().split()]
rev_sort_index = farray(fields, dtype=np.int32)
#verbosity_push(PRINT_SILENT)
cp2k_energy, cp2k_force = read_output(quip_cp2k_at, qm_list_a,
cur_qmmm_qm_abc, run_dir, proj,
calc_qm_charges, calc_virial, True,
3, at.n, out_i)
#verbosity_pop()
qm_list = None
if os.path.exists(os.path.join(run_dir, 'cp2k_input.qmmm_qm_kind')):
qm_kind_grep_cmd = "grep MM_INDEX %s/cp2k_input.qmmm_qm_kind | awk '{print $2}'" % run_dir
qm_list = [int(i) for i in os.popen(qm_kind_grep_cmd).read().split()]
if qm_list is not None:
if run_type == 'QMMM':
reordering_index = getattr(at, 'reordering_index', None)
at.add_property('qm', False, overwrite=True)
if reordering_index is not None:
qm_list = reordering_index[qm_list]
at.qm[qm_list] = True
elif run_type == 'QS':
at.add_property('qm_orig_index', 0, overwrite=True)
for i, qm_at in fenumerate(qm_list):
at.qm_orig_index[i] = sort_index[qm_at]
at.add_property('force', cp2k_force, overwrite=True)
at.params['energy'] = cp2k_energy
yield at
def find_crack_tip_coordination(atoms, edge_tol=10.0,
strip_height=30.0, nneightol=1.3):
"""
Return position of crack tip in `atoms`, based on atomic coordination.
If `atoms` does not contain an `advance_map` property, then
:func:`make_crack_advance_map` is called to generate the map.
Parameters
----------
atoms : :class:`~.Atoms' object
The Atoms object containing the crack slab.
edge_tol : float
Distance from edge of system within which to exclude
undercoodinated atoms.
strip_height : float
Height of strip along centre of slab in which to look
for the track.
nneightol : float
Nearest neighbour tolerance, as a fraction of sum of
covalent radii of atomic species.
Returns
-------
crack_pos : array
x, y, and z coordinates of the crack tip. Also set in ``CrackPos``
in ``atoms.info`` dictionary.
tip_atoms : array
Indices of atoms near the tip Also set in ``crack_tip`` property.
"""
old_tip_pos_y = 0
if 'CrackPos' in atoms.info:
old_tip_pos_y = atoms.info['CrackPos'][1]
# Make a copy of atoms as a quippy.Atoms instance, overwriting
# positions with time-averages values if they are available, and
# then calculate connectivity using nneightol
tmp_atoms = Atoms(atoms)
if 'avgpos' in tmp_atoms.arrays:
tmp_atoms.set_positions(tmp_atoms.arrays['avgpos'])
tmp_atoms.calc_connect()
nn = tmp_atoms.n_neighb
x = tmp_atoms.positions[:, 0]
y = tmp_atoms.positions[:, 1]
# find undercoordinated atoms in a central strip, and not too
# close to the left or right edges
left = tmp_atoms.positions[:, 0].min()
right = tmp_atoms.positions[:, 0].max()
uc = ((nn < 4) &
(abs(y) < strip_height) &
(x > left + edge_tol) &
(x < right - edge_tol))
# position of furthest forward undercoordinated atom ABOVE old tip position
x_above = x[uc & (y > old_tip_pos_y)].max()
# position of furthest forward undercoordinated atom BELOW old tip position
x_below = x[uc & (y < old_tip_pos_y)].max()
# rightmost undercoordinated atoms, both above and below old tip
rightmost_uc = uc & (((y > old_tip_pos_y) & (x_above == x)) |
((y <= old_tip_pos_y) & (x_below == x)))
# we want the NEXT pair of atoms, so we use the saved mapping from
# atom indices to the indices of atoms one unit cell to the right
if 'advance_map' not in atoms.arrays:
print('Generating crack advance map...')
make_crack_advance_map(atoms)
advance_map = atoms.arrays['advance_map']
tip_atoms = advance_map[rightmost_uc]
tip_pos = tmp_atoms.positions[tip_atoms, :].mean(axis=0)
# Also save results in Atoms (useful for visualisation)
atoms.info['CrackPos'] = tip_pos
atoms.set_array('crack_tip', np.array([False]*len(atoms)))
crack_tip = atoms.arrays['crack_tip']
crack_tip[tip_atoms] = True
return tip_pos
#!/usr/bin/env python import sys import os from math import pi import numpy as np from quippy.atoms import Atoms from quippy.structures import void_analysis from quippy.farray import fzeros infile = sys.argv[1] basename = os.path.splitext(infile)[0] a = Atoms(infile) grid_size = 0.25 min_void_size = 2.0 nx = int((a.pos[1,:].max() - a.pos[1,:].min())/grid_size) ny = int((a.pos[2,:].max() - a.pos[2,:].min())/grid_size) nz = int((a.pos[3,:].max() - a.pos[3,:].min())/grid_size) n = nx*ny*nz grid = fzeros((3, n)) radii = fzeros(n) void_analysis(a, grid_size, min_void_size, grid, radii) extent = (grid[:,-1] - grid[:,1])
# additional parameters for the QM/MM simulation:
qm_init_args = 'TB DFTB' # Initialisation arguments for QM potential
qm_inner_radius = 8.0 * units.Ang # Inner hysteretic radius for QM region
qm_outer_radius = 10.0 * units.Ang # Inner hysteretic radius for QM region
extrapolate_steps = 10 # Number of steps for predictor-corrector
# interpolation and extrapolation
# ******* End of parameters *************
set_fortran_indexing(False)
# ********** Read input file ************
print 'Loading atoms from file %s' % input_file
atoms = Atoms(input_file)
orig_height = atoms.info['OrigHeight']
orig_crack_pos = atoms.info['CrackPos'].copy()
# ***** Setup constraints *******
top = atoms.positions[:, 1].max()
bottom = atoms.positions[:, 1].min()
left = atoms.positions[:, 0].min()
right = atoms.positions[:, 0].max()
# fix atoms in the top and bottom rows
fixed_mask = ((abs(atoms.positions[:, 1] - top) < 1.0) |
(abs(atoms.positions[:, 1] - bottom) < 1.0))
fix_atoms = FixAtoms(mask=fixed_mask)
def VASP_POSCAR_Reader(poscar, species=None, format=None):
"""Read a configuration from a VASP POSCAR file.
Following POSCAR, optionally also read a trajectory from an OUTCAR file."""
p = open(poscar, 'r')
comment = p.readline().rstrip()
l = p.readline().strip()
lc_factor = float(l)
l = p.readline().strip()
a1 = np.real(l.split())
l = p.readline().strip()
a2 = np.real(l.split())
l = p.readline().strip()
a3 = np.real(l.split())
l = p.readline().strip()
at_species = l.split()
try:
ns = [int(n) for n in at_species]
no_species = True
except:
no_species = False
have_species = True
if (no_species):
for i in range(len(ns)):
if (species is not None):
species_cli = species.split()
at_species[i] = species_cli[i - 1]
else:
have_species = False
at_species[i] = ("%d" % (i + 1))
else:
l = p.readline().strip()
ns = [int(n) for n in l.split()]
l = p.readline().strip()
if (re.compile("^\s*s", re.IGNORECASE).match(l)):
dyn_type = l
coord_type = p.readline().strip()
else:
coord_type = l
n = 0
for i in range(len(ns)):
n += ns[i]
lat = fzeros((3, 3))
lat[:, 1] = a1[0:3]
lat[:, 2] = a2[0:3]
lat[:, 3] = a3[0:3]
lat *= lc_factor
at = Atoms(n=n, lattice=lat)
if (len(comment) > 0):
at.params['VASP_Comment'] = comment
coord_direct = re.compile("^\s*d", re.IGNORECASE).match(coord_type)
ii = 1
for ti in range(len(ns)):
for i in range(ns[ti]):
l = p.readline().strip()
pos = np.array(l.split()[0:3], float)
if (coord_direct):
at.pos[:, ii] = np.dot(at.lattice[:, :], pos[:])
else:
at.pos[:, ii] = pos[:] * lc_factor
at.species[:, ii] = at_species[ti]
ii += 1
if (have_species):
at.set_zs()
else:
at.Z[:] = [int("".join(n)) for n in at.species[:]]
yield at
def VASP_XDATCAR_Reader(xdatcar, species=None, format=None):
p = open(xdatcar, 'r')
def read_header(xdatcar):
comment = p.readline().rstrip()
if comment.find("Direct configuration") == 0: # is the beginning of some positions
return (None, None, comment, None, None, None)
l = p.readline().strip(); lc_factor=float(l)
l = p.readline().strip(); a1 = np.real(l.split())
l = p.readline().strip(); a2 = np.real(l.split())
l = p.readline().strip(); a3 = np.real(l.split())
l = p.readline().strip(); at_species = l.split()
try:
ns = [ int(n) for n in at_species ]
no_species_read = True
except:
no_species_read = False
if species is not None:
at_species = species.split()
have_species = True
else:
if no_species_read:
have_species = False
for i in range(len(ns)):
at_species[i] = ("%d" % (i+1))
else:
have_species = True
if not no_species_read:
l = p.readline().strip();
ns = [ int(n) for n in l.split() ]
n=0
for i in range(len(ns)):
n += ns[i]
lat = fzeros( (3,3) )
lat[:,1] = a1[0:3]
lat[:,2] = a2[0:3]
lat[:,3] = a3[0:3]
lat *= lc_factor
return (lat, n, comment, ns, at_species, have_species)
(lat, n, comment, ns, at_species, have_species) = read_header(xdatcar)
# end of header
while True:
try:
(new_lat, new_n, new_comment, new_ns, new_at_species, new_have_species) = read_header(xdatcar)
except:
return
if new_lat is None: # wasn't another header
l = new_comment
else:
lat = new_lat # assume nothing else has changed
l=p.readline().strip()
if (re.compile("^\s*s", re.IGNORECASE).match(l)):
dyn_type = l
coord_type = p.readline().strip();
else:
coord_type = l
at = Atoms(n=n, lattice=lat)
if (len(comment) > 0):
at.params['VASP_Comment'] = comment
coord_direct=re.compile("^\s*d", re.IGNORECASE).match(coord_type);
ii = 1
for ti in range(len(ns)):
for i in range(ns[ti]):
l = p.readline().strip(); pos = np.array(l.split()[0:3], float);
if (coord_direct):
at.pos[:,ii] = np.dot(at.lattice[:,:],pos[:])
else:
at.pos[:,ii] = pos[:]*lc_factor
at.species[:,ii] = at_species[ti]
ii += 1
if (have_species):
at.set_zs()
else:
at.Z[:] = [ int("".join(n)) for n in at.species[:] ]
yield at
def VASP_POSCAR_Reader(outcar, species=None, format=None):
"""Read a configuration from a VASP OUTCAR file."""
if (outcar == 'stdin' or outcar == '-'):
p = sys.stdin
else:
p = open(outcar, 'r')
re_comment = re.compile("\s*POSCAR:\s*(.+)")
re_potcar = re.compile("\s*POTCAR:\s*\S+\s+(\S+)")
re_n_atoms = re.compile("\s*ions per type =\s*((?:\d+\s*)*)")
energy_i = -1
at_i = -1
lat_i = -1
elements = []
n_at = -1
at_cur = None
for lr in p:
l = lr.rstrip()
if (n_at <= 0):
# parse header type things
m = re_comment.match(l)
if (m is not None):
VASP_Comment = m.group(1)
# print "got VASP_Comment '%s'" % VASP_Comment
m = re_potcar.match(l)
if (m is not None):
elements.append(m.group(1))
m = re_n_atoms.match(l)
if (m is not None):
# print "got ions per type, groups are:"
# print m.groups()
lat = fzeros((3, 3))
n_types = [int(f) for f in m.group(1).split()]
n_at = sum(n_types)
at = Atoms(n=n_at, latttice=lat)
i_at = 0
for type_i in range(len(n_types)):
for j in range(n_types[type_i]):
i_at += 1
# print "set species of atom %d to '%s'" % (i_at, elements[type_i])
at.species[i_at] = elements[type_i]
at.set_zs()
else:
# parse per-config lattice/pos/force
if (l.find("direct lattice vectors") >=
0): # get ready to read lattice vectors
at_cur = at.copy()
lat_cur = fzeros((3, 3))
lat_i = 1
elif (lat_i >= 1 and lat_i <= 3): # read lattice vectors
lat_cur[:, lat_i] = [
float(r) for r in l.replace("-", " -").split()[0:3]
]
lat_i += 1
elif (l.find("TOTAL-FORCE (eV/Angst)") >=
0): # get ready to read atomic positions and forces
if (not hasattr(at_cur, "force")):
at_cur.add_property("force", 0.0, n_cols=3)
at_i = 1
p.next()
elif (at_i >= 1
and at_i <= at_cur.n): # read atomic positions and forces
pos_force = [
float(r) for r in l.replace("-", " -").split()[0:6]
]
at_cur.pos[:, at_i] = pos_force[0:3]
at_cur.force[:, at_i] = pos_force[3:6]
at_i += 1
elif (l.find("free energy") >= 0): # get ready to read energy
at_cur.params['Energy'] = float(l.split()[4])
energy_i = 1
p.next()
elif (energy_i == 1): # read energy
# print "energy(sigma->0) line"
# print l.split()
at_cur.params['Energy_sigma_to_zero'] = float(l.split()[6])
energy_i += 1
yield at_cur
if (at_cur is not None and at_i
== at_cur.n): # at end of configuration, set lattice
at_cur.set_lattice(lat_cur, False)
__all__ = ['VASP_POSCAR_Reader', 'VASP_OUTCAR_Reader', 'VASPWriter']
def __iter__(self):
if type(self.filename) == type(''):
f = open(self.filename)
opened = True
# First eight lines are header
header = [f.readline() for i in range(8)]
# Rest of file is data array
data = np.loadtxt(f)
lattice = fzeros((3, 3))
for i in [1, 2, 3]:
lattice[:, i] = [float(x) for x in header[i + 1].split()[1:]]
if self.vacuum is not None:
lattice += np.diag(self.vacuum)
at = Atoms(n=len(data), lattice=lattice)
at.pos[...] = data[:, 3:6].T
at.set_atoms(self.z)
at.add_property('tag', data[:, 1].astype(int))
at.add_property('mass', data[:, 2])
at.add_property('velo', data[:, 6:9].T)
at.add_property('epot', data[:, 9])
if self.fix_tags is not None:
at.add_property('move_mask', 1)
for tag in self.fix_tags:
at.move_mask[at.tag == tag] = 0
if opened:
f.close()
yield at
clients.append(client)
print 'All calculations queued, waiting for results.'
t_clientstart = time.time()
# wait for input queues to empty
for input_q in input_qs:
input_q.join()
t_clientrun = time.time()
print 'Input queues drained. Shutting down clients.'
# stop the clients by sending them a calculation with zero atoms
dummy_at = Atoms(n=0, lattice=np.eye(3))
dummy_data = pack_atoms_to_reftraj_str(dummy_at, 0)
for input_q in input_qs:
input_q.put(dummy_data)
# wait for them all to shutdown
for client in clients:
client.wait()
print 'Clients terminated.'
for stdout in stdouts:
stdout.flush()
stdout.close()
print 'Client logs flushed.'
if MOLPRO_TEMPLATE[-4:] != '.xml':
# Read template input file
try:
datafile = molpro.MolproDatafile(MOLPRO_TEMPLATE)
#datafile.write()
except IOError:
die("Can't open input file %s" % MOLPRO_TEMPLATE)
except ValueError, message:
die(str(message))
# need to add XML handling here
# Read extended XYZ input file containing cluster
cluster = Atoms(xyzfile)
# remove old output file, if it's there
if os.path.exists(outfile):
os.remove(outfile)
path = WORKING_DIR+'/'+stem
# Make working directory if necessary
if not os.path.isdir(path):
os.mkdir(path)
os.chdir(path)
if not BATCH_READ:
# Load up old cluster, if it's there
def __init__(self,
atoms,
timestep,
trajectory,
trajectoryinterval=10,
initialtemperature=None,
logfile='-',
loginterval=1,
loglabel='D'):
# we will do the calculation in place, to minimise number of copies,
# unless atoms is not a quippy Atoms
if not isinstance(atoms, Atoms):
warnings.warn(
'Dynamics atoms is not quippy.Atoms instance, copy forced!')
atoms = Atoms(atoms)
self.atoms = atoms
if self.atoms.has('masses'):
if self.atoms.has_property('mass'):
if np.max(
np.abs(self.atoms.mass / MASSCONVERT -
self.atoms.get_masses())) > 1e-3:
raise RuntimeError(
'Dynamics confused as atoms has inconsistent "mass" and "masses" arrays'
)
else:
self.atoms.add_property('mass',
self.atoms.get_masses() * MASSCONVERT)
else:
if self.atoms.has_property('mass'):
self.atoms.set_masses(self.atoms.mass / MASSCONVERT)
else:
self.atoms.set_masses('defaults')
if self.atoms.has('momenta'):
if self.atoms.has_property('velo'):
if np.max(
np.abs(self.atoms.velo * sqrt(MASSCONVERT) -
self.atoms.get_velocities().T)) > 1e-3:
raise RuntimeError(
'Dynamics confused as atoms has inconsistent "velo" and "momenta" arrays'
)
else:
self.atoms.add_property('velo', (self.atoms.get_velocities() /
sqrt(MASSCONVERT)).T)
else:
if self.atoms.has_property('velo'):
self.atoms.set_velocities(self.atoms.velo.T *
sqrt(MASSCONVERT))
else:
# start with zero momenta
self.atoms.set_momenta(np.zeros_like(self.atoms.positions))
self.atoms.add_property('velo', 0., n_cols=3)
self._ds = DynamicalSystem(self.atoms)
if initialtemperature is not None:
if np.max(np.abs(self._ds.atoms.velo)) > 1e-3:
msg = ('initialtemperature given but Atoms already ' +
'has non-zero velocities!')
raise RuntimeError(msg)
self._ds.rescale_velo(initialtemperature)
# now self._ds.atoms is either a Fortran shallowcopy of atoms,
# or a copy if input atoms was not an instance of quippy.Atoms
if 'time' in atoms.info:
self.set_time(atoms.info['time']) # from ASE units to fs
self.observers = []
self.set_timestep(timestep)
if trajectory is not None:
if isinstance(trajectory, basestring):
trajectory = AtomsWriter(trajectory)
self.attach(trajectory, trajectoryinterval, self._ds.atoms)
self.loglabel = loglabel
if logfile is not None:
if isinstance(logfile, basestring):
logfile = InOutput(logfile, OUTPUT)
self.attach(self.print_status, loginterval, logfile)
self._calc_virial = False
self._virial = np.zeros((3, 3))
def PosCelReader(basename=None,
pos='pos.in',
cel='cel.in',
force='force.in',
energy='energy.in',
stress='stress.in',
species_map={
'O': 1,
'Si': 2
},
cel_angstrom=False,
pos_angstrom=False,
rydberg=True,
format=None):
if basename is not None:
basename = os.path.splitext(basename)[0]
pos = '%s.pos' % basename
cel = '%s.cel' % basename
energy = '%s.ene' % basename
stress = '%s.str' % basename
force = '%s.for' % basename
doenergy = os.path.exists(energy)
doforce = os.path.exists(force)
dostress = os.path.exists(stress)
if isinstance(pos, str): pos = open(pos)
if isinstance(cel, str): cel = open(cel)
if doenergy and isinstance(energy, str): energy = open(energy)
if doforce and isinstance(force, str): force = open(force)
if dostress and isinstance(stress, str): stress = open(stress)
pos = iter(pos)
cel = iter(cel)
if doenergy: energy = iter(energy)
if doforce: force = iter(force)
if dostress: stress = iter(stress)
pos.next() # throw away blank line at start
if doforce: force.next()
rev_species_map = dict(zip(species_map.values(), species_map.keys()))
while True:
poslines = list(
itertools.takewhile(
lambda L: L.strip() != '' and not L.strip().startswith('STEP'),
pos))
if poslines == []:
break
cellines = list(itertools.islice(cel, 4))
#lattice = farray([ [float(x) for x in L.split()] for L in cellines[1:4] ]).T
lattice = fzeros((3, 3))
for i in (1, 2, 3):
lattice[:, i] = [float(x) for x in cellines[i].split()]
if not cel_angstrom: lattice *= BOHR
at = Atoms(n=len(poslines), lattice=lattice)
at.pos[:] = farray([[float(x) for x in L.split()[0:3]]
for L in poslines]).T
if not pos_angstrom: at.pos[:] *= BOHR
species = [rev_species_map[int(L.split()[3])] for L in poslines]
elements = [
not el.isdigit() and atomic_number(el) or el for el in species
]
at.set_atoms(elements)
if doenergy:
at.params['energy'] = float(energy.next().split()[0])
if rydberg:
at.params['energy'] *= RYDBERG
if dostress:
stress_lines = list(itertools.islice(stress, 4))
virial = farray([[float(x) for x in L.split()]
for L in stress_lines[1:4]])
virial *= at.cell_volume() / (10.0 * GPA)
at.params['virial'] = virial
if doforce:
at.add_property('force', 0.0, n_cols=3)
force_lines = list(
itertools.takewhile(lambda L: L.strip() != '', force))
if len(force_lines) != at.n:
raise ValueError("len(force_lines) (%d) != at.n (%d)" %
(len(force_lines), at.n))
at.force[:] = farray([[float(x) for x in L.split()[0:3]]
for L in force_lines]).T
if rydberg:
at.force[:] *= RYDBERG / BOHR
yield at
strain_rate = 1e-5*(1/units.fs) # Strain rate
traj_file = 'traj.nc' # Trajectory output file (NetCDF format)
traj_interval = 10 # Number of time steps between
# writing output frames
param_file = 'params.xml' # Filename of XML file containing
# potential parameters
mm_init_args = 'IP SW' # Initialisation arguments for
# classical potential
# ******* End of parameters *************
# ********** Read input file ************
print 'Loading atoms from file %s' % input_file
atoms = Atoms(input_file, fortran_indexing=False)
orig_height = atoms.info['OrigHeight']
orig_crack_pos = atoms.info['CrackPos'].copy()
# ***** Setup constraints *******
top = atoms.positions[:, 1].max()
bottom = atoms.positions[:, 1].min()
left = atoms.positions[:, 0].min()
right = atoms.positions[:, 0].max()
# fix atoms in the top and bottom rows
fixed_mask = ((abs(atoms.positions[:, 1] - top) < 1.0) |
(abs(atoms.positions[:, 1] - bottom) < 1.0))
fix_atoms = FixAtoms(mask=fixed_mask)
param_file = 'params.xml' # XML file containing interatomic potential parameters
mm_init_args = 'IP SW' # Initialisation arguments for the classical potential
output_file = 'crack.xyz' # File to which structure will be written
# ******* End of parameters *************
set_fortran_indexing(False)
# ********** Build unit cell ************
# 8-atom diamond cubic unit cell for silicon, with guess at lattice
# constant of 5.44 A
si_bulk = bulk('Si', 'diamond', a=5.44, cubic=True)
si_bulk = Atoms(si_bulk)
# ********** Setup potential ************
# Stillinger-Weber (SW) classical interatomic potential, from QUIP
mm_pot = Potential(mm_init_args, param_filename=param_file, cutoff_skin=0.)
# ***** Find eqm. lattice constant ******
# find the equilibrium lattice constant by minimising atoms wrt virial
# tensor given by SW pot (possibly replace this with parabola fit in
# another script and hardcoded a0 here)
si_bulk.set_calculator(mm_pot)
print('Minimising bulk unit cell...')
minim = Minim(si_bulk, relax_positions=True, relax_cell=True)
def read_xml_output(xmlfile,energy_from=None, extract_forces=False, extract_dipole=False, datafile=None, cluster=None):
#parse an xml output file and return cluster with updated info
# datafile tells which energies, forces to look for, cluster Atoms object which gets returned, this is echoed in the xml file so can be left out
# If extract_forces is not given and the FORCE keyword is found in datafile, the default is to set extract_forces=True
log = logging.getLogger('molpro_driver')
if datafile is None:
datafile=MolproDatafile(xml=xmlfile)
if 'FORCE' in datafile:
extract_forces=True
energy_names = OrderedDict()
energy_names['CCSD(T)-F12'] = ["total energy"]
energy_names['CCSD(T)'] = ["total energy"]
energy_names['MP2'] = ["total energy"]
energy_names['DF-MP2'] = ["total energy"]
energy_names['DF-RMP2'] = ["energy"]
energy_names['RKS'] = ["Energy"]
energy_names['RHF'] = ["Energy"]
energy_names['DF-RHF'] = ["Energy"]
energy_names['HF'] = ["Energy"]
energy_names['DF-HF'] = ["Energy"]
#etc
gradient_names = OrderedDict()
gradient_names['CCSD(T)'] =[""]
gradient_names['RKS'] =['RKS GRADIENT']
gradient_names['MP2'] =['MP2 GRADIENT']
all_methods=OrderedDict()
all_methods['HF']=["RHF"]
all_methods['DF-HF']=["RHF"]
all_methods['RHF']=["RHF"]
all_methods['DF-RHF']=["RHF"]
all_methods['MP2']=["MP2"]
all_methods['DF-MP2']=["MP2"]
all_methods['DF-RMP2']=["DF-RMP2"]
all_methods['RKS']=["RKS"]
all_methods['CCSD(T)-F12']=["CCSD(T)-F12a","CCSD(T)-F12b"]
all_methods['CCSD(T)']=["CCSD(T)"]
if energy_from is None:
log.critical("don't know which energy to extract, use keyword energy_from with options "+str([all_methods[k] for k in iter(all_methods)]).replace('[','').replace(']',''))
#loop through datafile to look for methods.
calcs=[] #holds the keys for getting correct method, energy_name, gradient_name
data_keys_upper = [key.upper() for key in datafile._keys]
for key in all_methods._keys:
if key in data_keys_upper:
calcs.append(key)
dom = minidom.parse(xmlfile)
elements=[]
position_matrix=[]
cml = dom.documentElement.getElementsByTagName('cml:atomArray')
for l in cml[0].childNodes:
if l.nodeType== 1:
element=l.attributes['elementType'].value.encode('ascii','ignore')
elements.append(atomic_number(element))
posx = l.attributes['x3'].value.encode('ascii','ignore')
posy = l.attributes['y3'].value.encode('ascii','ignore')
posz = l.attributes['z3'].value.encode('ascii','ignore')
position_matrix.append([float(posx),float(posy),float(posz)])
if cluster is None:
cluster = Atoms(n=len(elements))
cluster.set_atoms(elements)
position_matrix=farray(position_matrix).T
if not 'ANGSTROM' in datafile._keys and not 'angstrom' in datafile._keys:
position_matrix = position_matrix * (1.0/0.529177249)
cluster.pos[:,:]=position_matrix
#note this leaves the lattice undefined
#now look for each of these energies in xml file
energy_found=False
props = dom.documentElement.getElementsByTagName('property')
for prop in props:
prop_name = prop.attributes['name'].value.encode('ascii','ignore')
prop_method = prop.attributes['method'].value.encode('ascii','ignore')
for calc in calcs:
if prop_name in energy_names[calc] and prop_method in all_methods[calc]:
energy_param_name="_".join([prop_method,prop_name])
energy_param_name=energy_param_name.replace(" ","_")
#log.info("found "+energy_param_name)
# dated routines for finding monomer pairs, triplets in Topology module
energy_param=prop.attributes['value'].value.encode('ascii','ignore')
my_energy=energy_param_name
i_en=1
while my_energy in cluster.params.iterkeys():
i_en+=1
my_energy='_'.join([energy_param_name,str(i_en)])
cluster.params[my_energy] = float(energy_param) * HARTREE
if prop_method == energy_from:
cluster.params['Energy']=float(energy_param) * HARTREE
energy_found=True
elif extract_dipole and prop_name=='Dipole moment':
dipole_param_name="_".join([prop_method,prop_name])
dipole_param_name=dipole_param_name.replace(" ","_")
log.info("found dipole moment: "+dipole_param_name)
dipole_param=prop.attributes['value'].value.encode('ascii','ignore')
cluster.params[dipole_param_name]=dipole_param
if not energy_found:
log.critical("couldn't find energy from "+energy_from+" prop method : "+prop_method)
# read gradients if requested
if extract_forces:
if not cluster.has_property('force'):
cluster.add_property('force', 0.0, n_cols=3)
grads = dom.documentElement.getElementsByTagName('gradient')
force_matrix = grads[0].childNodes[0].data.split('\n')
force_matrix = [str(i).split() for i in force_matrix]
for i in force_matrix:
try:
force_matrix.remove([])
except ValueError:
break
force_matrix = [[(-1.0 * HARTREE / BOHR) * float(j) for j in i]
for i in force_matrix]
cluster.force[:] =farray(force_matrix).T
if len(grads) != 1:
for k in range(1,len(grads)):
my_force='force%s'%str(k+1)
force_matrix = grads[k].childNodes[0].data.split('\n')
force_matrix = [str(i).split() for i in force_matrix]
for i in force_matrix:
try:
force_matrix.remove([])
except ValueError:
break
force_matrix = [[(-1.0 * HARTREE / BOHR) * float(j) for j in i]
for i in force_matrix]
cluster.add_property(my_force,farray(force_matrix).T)
return cluster
def calculate(self, atoms, properties, system_changes):
Calculator.calculate(self, atoms, properties, system_changes)
# we will do the calculation in place, to minimise number of copies,
# unless atoms is not a quippy Atoms
if isinstance(atoms, Atoms):
self.quippy_atoms = weakref.proxy(atoms)
else:
potlog.debug(
'Potential atoms is not quippy.Atoms instance, copy forced!')
self.quippy_atoms = Atoms(atoms)
initial_arrays = self.quippy_atoms.arrays.keys()
initial_info = self.quippy_atoms.info.keys()
if properties is None:
properties = ['energy', 'forces', 'stress']
# Add any default properties
properties = set(self.get_default_properties() + properties)
if len(properties) == 0:
raise RuntimeError('Nothing to calculate')
if not self.calculation_required(atoms, properties):
return
args_map = {
'energy': {
'energy': None
},
'energies': {
'local_energy': None
},
'forces': {
'force': None
},
'stress': {
'virial': None
},
'numeric_forces': {
'force': 'numeric_force',
'force_using_fd': True,
'force_fd_delta': 1.0e-5
},
'stresses': {
'local_virial': None
},
'elastic_constants': {},
'unrelaxed_elastic_constants': {}
}
# list of properties that require a call to Potential.calc()
calc_properties = [
'energy', 'energies', 'forces', 'numeric_forces', 'stress',
'stresses'
]
# list of other properties we know how to calculate
other_properties = ['elastic_constants', 'unrelaxed_elastic_constants']
calc_args = {}
calc_required = False
for property in properties:
if property in calc_properties:
calc_required = True
calc_args.update(args_map[property])
elif property not in other_properties:
raise RuntimeError(
"Don't know how to calculate property '%s'" % property)
if calc_required:
self.calc(self.quippy_atoms, args_str=dict_to_args_str(calc_args))
if 'energy' in properties:
self.results['energy'] = float(self.quippy_atoms.energy)
if 'energies' in properties:
self.results['energies'] = self.quippy_atoms.local_energy.copy(
).view(np.ndarray)
if 'forces' in properties:
self.results['forces'] = self.quippy_atoms.force.copy().view(
np.ndarray).T
if 'numeric_forces' in properties:
self.results[
'numeric_forces'] = self.quippy_atoms.numeric_force.copy(
).view(np.ndarray).T
if 'stress' in properties:
stress = -self.quippy_atoms.virial.copy().view(
np.ndarray) / self.quippy_atoms.get_volume()
# convert to 6-element array in Voigt order
self.results['stress'] = np.array([
stress[0, 0], stress[1, 1], stress[2, 2], stress[1, 2],
stress[0, 2], stress[0, 1]
])
if 'stresses' in properties:
lv = np.array(self.quippy_atoms.local_virial) # make a copy
vol_per_atom = self.get(
'vol_per_atom',
self.quippy_atoms.get_volume() / len(atoms))
if isinstance(vol_per_atom, basestring):
vol_per_atom = self.quippy_atoms.arrays[vol_per_atom]
self.results['stresses'] = -lv.T.reshape(
(len(atoms), 3, 3), order='F') / vol_per_atom
if 'elastic_constants' in properties:
cij_dx = self.get('cij_dx', 1e-2)
cij = fzeros((6, 6))
self.calc_elastic_constants(self.quippy_atoms,
fd=cij_dx,
args_str=self.get_calc_args_str(),
c=cij,
relax_initial=False,
return_relaxed=False)
if not get_fortran_indexing():
cij = cij.view(np.ndarray)
self.results['elastic_constants'] = cij
if 'unrelaxed_elastic_constants' in properties:
cij_dx = self.get('cij_dx', 1e-2)
c0ij = fzeros((6, 6))
self.calc_elastic_constants(self.quippy_atoms,
fd=cij_dx,
args_str=self.get_calc_args_str(),
c0=c0ij,
relax_initial=False,
return_relaxed=False)
if not get_fortran_indexing():
c0ij = c0ij.view(np.ndarray)
self.results['unrelaxed_elastic_constants'] = c0ij
# copy back any additional output data to results dictionary
skip_keys = ['energy', 'force', 'virial', 'numeric_force']
for key in self.quippy_atoms.arrays.keys():
if key not in initial_arrays and key not in skip_keys:
self.results[key] = self.quippy_atoms.arrays[key].copy()
for key in self.quippy_atoms.info.keys():
if key not in initial_info and key not in skip_keys:
if isinstance(self.quippy_atoms.info[key], np.ndarray):
self.results[key] = self.quippy_atoms.info[key].copy()
else:
self.results[key] = self.quippy_atoms.info[key]
def crack_strain_energy_release_rate(at, bulk=None, f_min=.8, f_max=.9, stem=None, avg_pos=False):
"""
Compute strain energy release rate G from elastic potential energy in a strip
"""
print 'Analytical effective elastic modulus E\' = ', at.YoungsModulus/(1-at.PoissonRatio_yx**2), 'GPa'
print 'Analytical energy release rate G = ', crack_measure_g(at, at.YoungsModulus, at.PoissonRatio_yx, at.OrigHeight), 'J/m^2'
if bulk is None:
if stem is None: raise ValueError('Either "bulk" or "stem" must be present')
bulk = Atoms(stem+'_bulk.xyz')
if not hasattr(at, 'local_energy') or not hasattr(bulk, 'energy'):
if stem is None: raise ValueError('local_energy property not found in Atoms and "stem" is missing')
xmlfile = stem+'.xml'
params = CrackParams(xmlfile)
pot = Potential(params.classical_args, param_filename=stem+'.xml')
pot.print_()
if not hasattr(at, 'local_energy'):
if avg_pos:
tmp_pos = at.pos.copy()
at.pos[...] = at.avgpos
at.set_cutoff(pot.cutoff()+1.)
at.calc_connect()
pot.calc(at, args_str="local_energy")
if avg_pos:
at.pos[...] = tmp_pos
if not hasattr(bulk, 'energy'):
bulk.set_cutoff(pot.cutoff()+1.)
bulk.calc_connect()
pot.calc(bulk, args_str='energy')
h = at.pos[2,:].max() - at.pos[2,:].min()
h0 = at.OrigHeight
strain = (h - h0)/h0
print 'Applied strain', strain
x_min = f_min*at.OrigWidth - at.OrigWidth/2.
x_max = f_max*at.OrigWidth - at.OrigWidth/2.
strip = np.logical_and(at.move_mask == 1, np.logical_and(at.pos[1,:] > x_min, at.pos[1,:] < x_max))
at.add_property('strip', strip, overwrite=True)
strip_depth = at.lattice[3,3]
strip_width = at.pos[1,strip].max() - at.pos[1,strip].min()
strip_height = at.pos[2,strip].max() - at.pos[2,strip].min()
strip_volume = strip_width*strip_height*strip_depth
print 'Strip contains', strip.sum(), 'atoms', 'width', strip_width, 'height', strip_height, 'volume', strip_volume
strain_energy_density = (at.local_energy[strip].sum() - bulk.energy/bulk.n*strip.sum())/strip_volume
print 'Strain energy density in strip', strain_energy_density, 'eV/A**3'
E_effective = 2*strain_energy_density/strain**2*GPA
print 'Effective elastic modulus E =', E_effective, 'GPa'
G_effective = strain_energy_density*strip_height*J_PER_M2
print 'Effective energy release rate G =', G_effective, 'J/m^2'
return G_effective
class Potential(_potential.Potential, Calculator):
__doc__ = update_doc_string(
_potential.Potential.__doc__,
r"""
The :class:`Potential` class also implements the ASE
:class:`ase.calculators.interface.Calculator` interface via the
the :meth:`get_forces`, :meth:`get_stress`, :meth:`get_stresses`,
:meth:`get_potential_energy`, :meth:`get_potential_energies`
methods. For example::
atoms = diamond(5.44, 14)
atoms.rattle(0.01)
atoms.set_calculator(pot)
forces = atoms.get_forces()
print forces
Note that the ASE force array is the transpose of the QUIP force
array, so has shape (len(atoms), 3) rather than (3, len(atoms)).
The optional arguments `pot1`, `pot2` and `bulk_scale` are
used by ``Sum`` and ``ForceMixing`` potentials (see also
wrapper class :class:`ForceMixingPotential`)
An :class:`quippy.mpi_context.MPI_context` object can be
passed as the `mpi_obj` argument to restrict the
parallelisation of this potential to a subset of the
The `callback` argument is used to implement the calculation of
the :class:`Potential` in a Python function: see :meth:`set_callback` for
an example.
In addition to the builtin QUIP potentials, it is possible to
use any ASE calculator as a QUIP potential by passing it as
the `calculator` argument to the :class:`Potential` constructor, e.g.::
from ase.calculators.morse import MorsePotential
pot = Potential(calculator=MorsePotential)
`atoms` if given, is used to set the calculator associated
with `atoms` to the new :class:`Potential` instance, by calling
:meth:'.Atoms.set_calculator`.
.. note::
QUIP potentials do not compute stress and per-atom stresses
directly, but rather the virial tensor which has units of stress
:math:`\times` volume, i.e. energy. If the total stress is
requested, it is computed by dividing the virial by the atomic
volume, obtained by calling :meth:`.Atoms.get_volume`. If per-atom
stresses are requested, a per-atom volume is needed. By default
this is taken to be the total volume divided by the number of
atoms. In some cases, e.g. for systems containing large amounts of
vacuum, this is not reasonable. The ``vol_per_atom`` calc_arg can
be used either to give a single per-atom volume, or the name of an
array in :attr:`.Atoms.arrays` containing volumes for each atom.
""",
signature=
'Potential(init_args[, pot1, pot2, param_str, param_filename, bulk_scale, mpi_obj, callback, calculator, atoms, calculation_always_required])'
)
callback_map = {}
implemented_properties = [
'energy', 'energies', 'forces', 'stress', 'stresses', 'numeric_forces',
'elastic_constants', 'unrelaxed_elastic_constants'
]
def __init__(self,
init_args=None,
pot1=None,
pot2=None,
param_str=None,
param_filename=None,
bulk_scale=None,
mpi_obj=None,
callback=None,
calculator=None,
atoms=None,
calculation_always_required=False,
fpointer=None,
finalise=True,
error=None,
**kwargs):
self._calc_args = {}
self._default_properties = []
self.calculation_always_required = calculation_always_required
Calculator.__init__(self, atoms=atoms)
if callback is not None or calculator is not None:
if init_args is None:
init_args = 'callbackpot'
param_dirname = None
if param_filename is not None:
param_str = open(param_filename).read()
param_dirname = path.dirname(param_filename) or None
if init_args is None and param_str is None:
raise ValueError('Need one of init_args,param_str,param_filename')
if init_args is not None:
if init_args.lower().startswith('callbackpot'):
if not 'label' in init_args:
init_args = init_args + ' label=%d' % id(self)
else:
# if param_str missing, try to find default set of QUIP params,
# falling back on a do-nothing parameter string.
if param_str is None and pot1 is None and pot2 is None:
try:
param_str = quip_xml_parameters(init_args)
except IOError:
param_str = r'<params></params>'
if kwargs != {}:
if init_args is not None:
init_args = init_args + ' ' + dict_to_args_str(kwargs)
else:
init_args = dict_to_args_str(kwargs)
# Change to the xml directory to initialise, so that extra files
# like sparseX can be found.
old_dir = os.getcwd()
try:
if param_dirname is not None:
os.chdir(param_dirname)
_potential.Potential.__init__(self,
init_args,
pot1=pot1,
pot2=pot2,
param_str=param_str,
bulk_scale=bulk_scale,
mpi_obj=mpi_obj,
fpointer=fpointer,
finalise=finalise,
error=error)
finally:
os.chdir(old_dir)
if init_args is not None and init_args.lower().startswith(
'callbackpot'):
_potential.Potential.set_callback(self, Potential.callback)
if callback is not None:
self.set_callback(callback)
if calculator is not None:
self.set_callback(calculator_callback_factory(calculator))
if atoms is not None:
atoms.set_calculator(self)
self.name = init_args
__init__.__doc__ = _potential.Potential.__init__.__doc__
def calc(self,
at,
energy=None,
force=None,
virial=None,
local_energy=None,
local_virial=None,
args_str=None,
error=None,
**kwargs):
if not isinstance(args_str, basestring):
args_str = dict_to_args_str(args_str)
kw_args_str = dict_to_args_str(kwargs)
args_str = ' '.join((self.get_calc_args_str(), kw_args_str, args_str))
if isinstance(energy, basestring):
args_str = args_str + ' energy=%s' % energy
energy = None
if isinstance(energy, bool) and energy:
args_str = args_str + ' energy'
energy = None
if isinstance(force, basestring):
args_str = args_str + ' force=%s' % force
force = None
if isinstance(force, bool) and force:
args_str = args_str + ' force'
force = None
if isinstance(virial, basestring):
args_str = args_str + ' virial=%s' % virial
virial = None
if isinstance(virial, bool) and virial:
args_str = args_str + ' virial'
virial = None
if isinstance(local_energy, basestring):
args_str = args_str + ' local_energy=%s' % local_energy
local_energy = None
if isinstance(local_energy, bool) and local_energy:
args_str = args_str + ' local_energy'
local_energy = None
if isinstance(local_virial, basestring):
args_str = args_str + ' local_virial=%s' % local_virial
local_virial = None
if isinstance(local_virial, bool) and local_virial:
args_str = args_str + ' local_virial'
local_virial = None
potlog.debug(
'Potential invoking calc() on n=%d atoms with args_str "%s"' %
(len(at), args_str))
_potential.Potential.calc(self, at, energy, force, virial,
local_energy, local_virial, args_str, error)
calc.__doc__ = update_doc_string(
_potential.Potential.calc.__doc__,
"""In Python, this method is overloaded to set the final args_str to
:meth:`get_calc_args_str`, followed by any keyword arguments,
followed by an explicit `args_str` argument if present. This ordering
ensures arguments explicitly passed to :meth:`calc` will override any
default arguments.""")
@staticmethod
def callback(at_ptr):
from quippy import Atoms
at = Atoms(fpointer=at_ptr, finalise=False)
if 'label' not in at.params or at.params[
'label'] not in Potential.callback_map:
raise ValueError('Unknown Callback label %s' % at.params['label'])
Potential.callback_map[at.params['label']](at)
def set_callback(self, callback):
"""
For a :class:`Potential` of type `CallbackPot`, this method is
used to set the callback function. `callback` should be a Python
function (or other callable, such as a bound method or class
instance) which takes a single argument, of type
:class:`~quippy.atoms.Atoms`. Information about which properties should be
computed can be obtained from the `calc_energy`, `calc_local_e`,
`calc_force`, and `calc_virial` keys in `at.params`. Results
should be returned either as `at.params` entries (for energy and
virial) or by adding new atomic properties (for forces and local
energy).
Here's an example implementation of a simple callback::
def example_callback(at):
if at.calc_energy:
at.params['energy'] = ...
if at.calc_force:
at.add_property('force', 0.0, n_cols=3)
at.force[:,:] = ...
p = Potential('CallbackPot')
p.set_callback(example_callback)
p.calc(at, energy=True)
print at.energy
...
"""
Potential.callback_map[str(id(self))] = callback
def check_state(self, atoms, tol=1e-15):
if self.calculation_always_required:
return all_changes
return Calculator.check_state(self, atoms, tol)
def calculate(self, atoms, properties, system_changes):
Calculator.calculate(self, atoms, properties, system_changes)
# we will do the calculation in place, to minimise number of copies,
# unless atoms is not a quippy Atoms
if isinstance(atoms, Atoms):
self.quippy_atoms = weakref.proxy(atoms)
else:
potlog.debug(
'Potential atoms is not quippy.Atoms instance, copy forced!')
self.quippy_atoms = Atoms(atoms)
initial_arrays = self.quippy_atoms.arrays.keys()
initial_info = self.quippy_atoms.info.keys()
if properties is None:
properties = ['energy', 'forces', 'stress']
# Add any default properties
properties = set(self.get_default_properties() + properties)
if len(properties) == 0:
raise RuntimeError('Nothing to calculate')
if not self.calculation_required(atoms, properties):
return
args_map = {
'energy': {
'energy': None
},
'energies': {
'local_energy': None
},
'forces': {
'force': None
},
'stress': {
'virial': None
},
'numeric_forces': {
'force': 'numeric_force',
'force_using_fd': True,
'force_fd_delta': 1.0e-5
},
'stresses': {
'local_virial': None
},
'elastic_constants': {},
'unrelaxed_elastic_constants': {}
}
# list of properties that require a call to Potential.calc()
calc_properties = [
'energy', 'energies', 'forces', 'numeric_forces', 'stress',
'stresses'
]
# list of other properties we know how to calculate
other_properties = ['elastic_constants', 'unrelaxed_elastic_constants']
calc_args = {}
calc_required = False
for property in properties:
if property in calc_properties:
calc_required = True
calc_args.update(args_map[property])
elif property not in other_properties:
raise RuntimeError(
"Don't know how to calculate property '%s'" % property)
if calc_required:
self.calc(self.quippy_atoms, args_str=dict_to_args_str(calc_args))
if 'energy' in properties:
self.results['energy'] = float(self.quippy_atoms.energy)
if 'energies' in properties:
self.results['energies'] = self.quippy_atoms.local_energy.copy(
).view(np.ndarray)
if 'forces' in properties:
self.results['forces'] = self.quippy_atoms.force.copy().view(
np.ndarray).T
if 'numeric_forces' in properties:
self.results[
'numeric_forces'] = self.quippy_atoms.numeric_force.copy(
).view(np.ndarray).T
if 'stress' in properties:
stress = -self.quippy_atoms.virial.copy().view(
np.ndarray) / self.quippy_atoms.get_volume()
# convert to 6-element array in Voigt order
self.results['stress'] = np.array([
stress[0, 0], stress[1, 1], stress[2, 2], stress[1, 2],
stress[0, 2], stress[0, 1]
])
if 'stresses' in properties:
lv = np.array(self.quippy_atoms.local_virial) # make a copy
vol_per_atom = self.get(
'vol_per_atom',
self.quippy_atoms.get_volume() / len(atoms))
if isinstance(vol_per_atom, basestring):
vol_per_atom = self.quippy_atoms.arrays[vol_per_atom]
self.results['stresses'] = -lv.T.reshape(
(len(atoms), 3, 3), order='F') / vol_per_atom
if 'elastic_constants' in properties:
cij_dx = self.get('cij_dx', 1e-2)
cij = fzeros((6, 6))
self.calc_elastic_constants(self.quippy_atoms,
fd=cij_dx,
args_str=self.get_calc_args_str(),
c=cij,
relax_initial=False,
return_relaxed=False)
if not get_fortran_indexing():
cij = cij.view(np.ndarray)
self.results['elastic_constants'] = cij
if 'unrelaxed_elastic_constants' in properties:
cij_dx = self.get('cij_dx', 1e-2)
c0ij = fzeros((6, 6))
self.calc_elastic_constants(self.quippy_atoms,
fd=cij_dx,
args_str=self.get_calc_args_str(),
c0=c0ij,
relax_initial=False,
return_relaxed=False)
if not get_fortran_indexing():
c0ij = c0ij.view(np.ndarray)
self.results['unrelaxed_elastic_constants'] = c0ij
# copy back any additional output data to results dictionary
skip_keys = ['energy', 'force', 'virial', 'numeric_force']
for key in self.quippy_atoms.arrays.keys():
if key not in initial_arrays and key not in skip_keys:
self.results[key] = self.quippy_atoms.arrays[key].copy()
for key in self.quippy_atoms.info.keys():
if key not in initial_info and key not in skip_keys:
if isinstance(self.quippy_atoms.info[key], np.ndarray):
self.results[key] = self.quippy_atoms.info[key].copy()
else:
self.results[key] = self.quippy_atoms.info[key]
def get_potential_energies(self, atoms):
"""
Return array of atomic energies calculated with this Potential
"""
return self.get_property('energies', atoms)
def get_numeric_forces(self, atoms):
"""
Return forces on `atoms` computed with finite differences of the energy
"""
return self.get_property('numeric_forces', atoms)
def get_stresses(self, atoms):
"""
Return the per-atoms virial stress tensors for `atoms` computed with this Potential
"""
return self.get_property('stresses', atoms)
def get_elastic_constants(self, atoms):
"""
Calculate elastic constants of `atoms` using this Potential.
Returns 6x6 matrix :math:`C_{ij}` of elastic constants.
The elastic contants are calculated as finite difference
derivatives of the virial stress tensor using positive and
negative strains of magnitude the `cij_dx` entry in
``calc_args``.
"""
return self.get_property('elastic_constants', atoms)
def get_unrelaxed_elastic_constants(self, atoms):
"""
Calculate unrelaxed elastic constants of `atoms` using this Potential
Returns 6x6 matrix :math:`C^0_{ij}` of unrelaxed elastic constants.
The elastic contants are calculated as finite difference
derivatives of the virial stress tensor using positive and
negative strains of magnitude the `cij_dx` entry in
:attr:`calc_args`.
"""
return self.get_property('unrelaxed_elastic_constants', atoms)
def get_default_properties(self):
"Get the list of properties to be calculated by default"
return self._default_properties[:]
def set_default_properties(self, properties):
"Set the list of properties to be calculated by default"
self._default_properties = properties[:]
def get(self, param, default=None):
"""
Get the value of a ``calc_args`` parameter for this :class:`Potential`
Returns ``None`` if `param` is not in the current ``calc_args`` dictionary.
All calc_args are passed to :meth:`calc` whenever energies,
forces or stresses need to be re-computed.
"""
return self._calc_args.get(param, default)
def set(self, **kwargs):
"""
Set one or more calc_args parameters for this Potential
All calc_args are passed to :meth:`calc` whenever energies,
forces or stresses need to be computed.
After updating the calc_args, :meth:`set` calls :meth:`reset`
to mark all properties as needing to be recaculated.
"""
self._calc_args.update(kwargs)
self.reset()
def get_calc_args(self):
"""
Get the current ``calc_args``
"""
return self._calc_args.copy()
def set_calc_args(self, calc_args):
"""
Set the ``calc_args`` to be used subsequent :meth:`calc` calls
"""
self._calc_args = calc_args.copy()
def get_calc_args_str(self):
"""
Get the ``calc_args`` to be passed to :meth:`calc` as a string
"""
return dict_to_args_str(self._calc_args)
def CP2KOutputReader(fh,
module=None,
type_map=None,
kind_map=None,
format=None):
# mapping from run type to (default module index, list of available module)
run_types = {
'QS': ['QUICKSTEP'],
'QMMM': ['FIST', 'QM/MM', 'QUICKSTEP'],
'MM': ['FIST']
}
filename, lines = read_text_file(fh)
run_type = cp2k_run_type(cp2k_output=lines)
if type_map is None:
type_map = {}
if kind_map is None:
kind_map = {}
try:
available_modules = run_types[run_type]
except KeyError:
raise ValueError('Unknown CP2K run type %s' % run_type)
if module is None:
module = available_modules[0]
try:
cell_index = available_modules.index(module)
except ValueError:
raise ValueError("Don't know how to read module %s from file %s" %
(module, filename))
cell_lines = [
i for i, line in enumerate(lines) if line.startswith(" CELL| Vector a")
]
if cell_lines == []:
raise ValueError("Cannot find cell in file %s" % filename)
try:
cell_line = cell_lines[cell_index]
except IndexError:
raise ValueError(
"Cannot find cell with index %d in file %s for module %s" %
(cell_index, filename, module))
lattice = fzeros((3, 3))
for i in [0, 1, 2]:
lattice[:,
i + 1] = [float(c) for c in lines[cell_line + i].split()[4:7]]
try:
start_line = lines.index(
" MODULE %s: ATOMIC COORDINATES IN angstrom\n" % module)
except ValueError:
raise ValueError(
"Cannot find atomic positions for module %s in file %s" %
(module, filename))
kinds = []
species = []
Zs = []
pos = []
masses = []
Zeffs = []
types = []
qeffs = []
for line in lines[start_line + 4:]:
if line.strip() == '':
break
if module == 'FIST':
atom, kind, typ, x, y, z, qeff, mass = line.split()
types.append(typ)
Z = type_map.get(typ, 0)
kind = int(kind)
if Z == 0:
Z = kind_map.get(kind, 0)
Zs.append(Z)
qeffs.append(float(qeff))
else:
atom, kind, sp, Z, x, y, z, Zeff, mass = line.split()
species.append(sp)
Zs.append(int(Z))
Zeffs.append(float(Zeff))
kinds.append(int(kind))
pos.append([float(x), float(y), float(z)])
masses.append(float(mass))
at = Atoms(n=len(kinds), lattice=lattice)
at.pos[...] = farray(pos).T
at.set_atoms(Zs)
at.add_property('mass', farray(masses) * MASSCONVERT)
at.add_property('kind', kinds)
if module == 'FIST':
at.add_property('type', ' ' * TABLE_STRING_LENGTH)
at.add_property('qm', False)
at.qm[:] = (at.type.stripstrings()
== '_QM_') | (at.type.stripstrings() == '_LNK')
at.type[...] = s2a(types, TABLE_STRING_LENGTH)
at.add_property('qeff', qeffs)
else:
at.species[...] = s2a(species, TABLE_STRING_LENGTH)
at.add_property('zeff', Zeffs)
yield at
parser.add_argument("-st", "--sim_T", help='Simulation Temperature in Kelvin. Default is 300 K.', type=float, required=True)
parser.add_argument("-cfe", "--check_force_error", help='Perform a DFT calculation at each step in the trajectory.', action='store_true')
args = parser.parse_args()
# parse args string:
if args.input_file == '':
input_file = params.input_file
else:
input_file = args.input_file
# ParseArguements
sim_T = args.sim_T*units.kB
geom = args.geom
check_force_error = args.check_force_error
print 'Loading atoms from file %s' % input_file
atoms = Atoms(input_file)
atoms = Atoms(atoms)
if params.continuation:
# restart from last frame of most recent trajectory file
traj_files = sorted(glob.glob('[0-9]*.traj.xyz'))
if len(traj_files) > 0:
last_traj = traj_files[-1]
input_file = last_traj + '@-1'
# loading reference configuration for Nye tensor evaluation
# convert to quippy Atoms - FIXME in long term, this should not be necesary
x0 = Atoms(params.reference_file)
x0 = Atoms(x0)
x0.set_cutoff(3.0)
x0.calc_connect()
sim_T = 300.0*units.kB # Simulation temperature
nsteps = 10000 # Total number of timesteps to run for
timestep = 1.0*units.fs # Timestep (NB: time base units are not fs!)
cutoff_skin = 2.0*units.Ang # Amount by which potential cutoff is increased
# for neighbour calculations
tip_move_tol = 10.0 # Distance tip has to move before crack
# is taken to be running
strain_rate = 1e-5*(1/units.fs) # Strain rate
traj_file = 'traj.nc' # Trajectory output file (NetCDF format)
traj_interval = 10 # Number of time steps between
# writing output frames
set_fortran_indexing(False)
atoms = Atoms(input_file)
orig_height = atoms.info['OrigHeight']
orig_crack_pos = atoms.info['CrackPos'].copy()
top = atoms.positions[:, 1].max()
bottom = atoms.positions[:, 1].min()
left = atoms.positions[:, 0].min()
right = atoms.positions[:, 0].max()
fixed_mask = ((abs(atoms.positions[:, 1] - top) < 1.0) |
(abs(atoms.positions[:, 1] - bottom) < 1.0))
fix_atoms = FixAtoms(mask=fixed_mask)
strain_atoms = ConstantStrainRate(orig_height, strain_rate*timestep)
atoms.set_constraint([fix_atoms, strain_atoms])
class Potential(_potential.Potential):
__doc__ = update_doc_string(
_potential.Potential.__doc__,
r"""
The :class:`Potential` class also implements the ASE
:class:`ase.calculators.interface.Calculator` interface via the
the :meth:`get_forces`, :meth:`get_stress`, :meth:`get_stresses`,
:meth:`get_potential_energy`, :meth:`get_potential_energies`
methods. This simplifies calculation since there is no need
to set the cutoff or to call :meth:`~quippy.atoms.Atoms.calc_connect`,
as this is done internally. The example above reduces to::
atoms = diamond(5.44, 14)
atoms.rattle(0.01)
atoms.set_calculator(pot)
forces = atoms.get_forces()
print forces
Note that the ASE force array is the transpose of the QUIP force
array, so has shape (len(atoms), 3) rather than (3, len(atoms)).
The optional arguments `pot1`, `pot2` and `bulk_scale` are
used by ``Sum`` and ``ForceMixing`` potentials (see also
wrapper class :class:`ForceMixingPotential`)
An :class:`quippy.mpi_context.MPI_context` object can be
passed as the `mpi_obj` argument to restrict the
parallelisation of this potential to a subset of the
The `callback` argument is used to implement the calculation of
the :class:`Potential` in a Python function: see :meth:`set_callback` for
an example.
In addition to the builtin QUIP potentials, it is possible to
use any ASE calculator as a QUIP potential by passing it as
the `calculator` argument to the :class:`Potential` constructor, e.g.::
from ase.calculators.morse import MorsePotential
pot = Potential(calculator=MorsePotential)
`cutoff_skin` is used to set the :attr:`cutoff_skin` attribute.
`atoms` if given, is used to set the calculator associated
with `atoms` to the new :class:`Potential` instance, by calling
:meth:'.Atoms.set_calculator`.
.. note::
QUIP potentials do not compute stress and per-atom stresses
directly, but rather the virial tensor which has units of stress
:math:`\times` volume, i.e. energy. If the total stress is
requested, it is computed by dividing the virial by the atomic
volume, obtained by calling :meth:`.Atoms.get_volume`. If per-atom
stresses are requested, a per-atom volume is needed. By default
this is taken to be the total volume divided by the number of
atoms. In some cases, e.g. for systems containing large amounts of
vacuum, this is not reasonable. The ``vol_per_atom`` calc_arg can
be used either to give a single per-atom volume, or the name of an
array in :attr:`.Atoms.arrays` containing volumes for each atom.
""",
signature=
'Potential(init_args[, pot1, pot2, param_str, param_filename, bulk_scale, mpi_obj, callback, calculator, cutoff_skin, atoms])'
)
callback_map = {}
def __init__(self,
init_args=None,
pot1=None,
pot2=None,
param_str=None,
param_filename=None,
bulk_scale=None,
mpi_obj=None,
callback=None,
calculator=None,
cutoff_skin=1.0,
atoms=None,
fpointer=None,
finalise=True,
error=None,
**kwargs):
self.atoms = None
self._prev_atoms = None
self.energy = None
self.energies = None
self.forces = None
self.stress = None
self.stresses = None
self.elastic_constants = None
self.unrelaxed_elastic_constants = None
self.numeric_forces = None
self._calc_args = {}
self._default_quantities = []
self.cutoff_skin = cutoff_skin
if callback is not None or calculator is not None:
if init_args is None:
init_args = 'callbackpot'
if param_filename is not None:
param_str = open(param_filename).read()
if init_args is None and param_str is None:
raise ValueError('Need one of init_args,param_str,param_filename')
if init_args is not None:
if init_args.lower().startswith('callbackpot'):
if not 'label' in init_args:
init_args = init_args + ' label=%d' % id(self)
else:
# if param_str missing, try to find default set of QUIP params
if param_str is None and pot1 is None and pot2 is None:
param_str = quip_xml_parameters(init_args)
if kwargs != {}:
if init_args is not None:
init_args = init_args + ' ' + dict_to_args_str(kwargs)
else:
init_args = dict_to_args_str(kwargs)
_potential.Potential.__init__(self,
init_args,
pot1=pot1,
pot2=pot2,
param_str=param_str,
bulk_scale=bulk_scale,
mpi_obj=mpi_obj,
fpointer=fpointer,
finalise=finalise,
error=error)
if init_args is not None and init_args.lower().startswith(
'callbackpot'):
_potential.Potential.set_callback(self, Potential.callback)
if callback is not None:
self.set_callback(callback)
if calculator is not None:
self.set_callback(calculator_callback_factory(calculator))
if atoms is not None:
atoms.set_calculator(self)
__init__.__doc__ = _potential.Potential.__init__.__doc__
def calc(self,
at,
energy=None,
force=None,
virial=None,
local_energy=None,
local_virial=None,
args_str=None,
error=None,
**kwargs):
if not isinstance(args_str, basestring):
args_str = dict_to_args_str(args_str)
kw_args_str = dict_to_args_str(kwargs)
args_str = ' '.join((self.get_calc_args_str(), kw_args_str, args_str))
if isinstance(energy, basestring):
args_str = args_str + ' energy=%s' % energy
energy = None
if isinstance(energy, bool) and energy:
args_str = args_str + ' energy'
energy = None
if isinstance(force, basestring):
args_str = args_str + ' force=%s' % force
force = None
if isinstance(force, bool) and force:
args_str = args_str + ' force'
force = None
if isinstance(virial, basestring):
args_str = args_str + ' virial=%s' % virial
virial = None
if isinstance(virial, bool) and virial:
args_str = args_str + ' virial'
virial = None
if isinstance(local_energy, basestring):
args_str = args_str + ' local_energy=%s' % local_energy
local_energy = None
if isinstance(local_energy, bool) and local_energy:
args_str = args_str + ' local_energy'
local_energy = None
if isinstance(local_virial, basestring):
args_str = args_str + ' local_virial=%s' % local_virial
local_virial = None
if isinstance(local_virial, bool) and local_virial:
args_str = args_str + ' local_virial'
local_virial = None
potlog.debug(
'Potential invoking calc() on n=%d atoms with args_str "%s"' %
(len(at), args_str))
_potential.Potential.calc(self, at, energy, force, virial,
local_energy, local_virial, args_str, error)
calc.__doc__ = update_doc_string(
_potential.Potential.calc.__doc__,
"""In Python, this method is overloaded to set the final args_str to
:meth:`get_calc_args_str`, followed by any keyword arguments,
followed by an explicit `args_str` argument if present. This ordering
ensures arguments explicitly passed to :meth:`calc` will override any
default arguments.""")
@staticmethod
def callback(at_ptr):
from quippy import Atoms
at = Atoms(fpointer=at_ptr, finalise=False)
if 'label' not in at.params or at.params[
'label'] not in Potential.callback_map:
raise ValueError('Unknown Callback label %s' % at.params['label'])
Potential.callback_map[at.params['label']](at)
def set_callback(self, callback):
"""
For a :class:`Potential` of type `CallbackPot`, this method is
used to set the callback function. `callback` should be a Python
function (or other callable, such as a bound method or class
instance) which takes a single argument, of type
:class:`~quippy.atoms.Atoms`. Information about which quantities should be
computed can be obtained from the `calc_energy`, `calc_local_e`,
`calc_force`, and `calc_virial` keys in `at.params`. Results
should be returned either as `at.params` entries (for energy and
virial) or by adding new atomic properties (for forces and local
energy).
Here's an example implementation of a simple callback::
def example_callback(at):
if at.calc_energy:
at.params['energy'] = ...
if at.calc_force:
at.add_property('force', 0.0, n_cols=3)
at.force[:,:] = ...
p = Potential('CallbackPot')
p.set_callback(example_callback)
p.calc(at, energy=True)
print at.energy
...
"""
Potential.callback_map[str(id(self))] = callback
def wipe(self):
"""
Mark all quantities as needing to be recalculated
"""
self.energy = None
self.energies = None
self.forces = None
self.stress = None
self.stresses = None
self.numeric_forces = None
self.elastic_constants = None
self.unrelaxed_elastic_constants = None
def update(self, atoms):
"""
Set the :class:`~quippy.atoms.Atoms` object associated with this :class:`Potential` to `atoms`.
Called internally by :meth:`get_potential_energy`,
:meth:`get_forces`, etc. Only a weak reference to `atoms` is
kept, to prevent circular references. If `atoms` is not a
:class:`quippy.atoms.Atoms` instance, then a copy is made and a
warning will be printed.
"""
# we will do the calculation in place, to minimise number of copies,
# unless atoms is not a quippy Atoms
if isinstance(atoms, Atoms):
self.atoms = weakref.proxy(atoms)
else:
potlog.debug(
'Potential atoms is not quippy.Atoms instance, copy forced!')
self.atoms = Atoms(atoms)
# check if atoms has changed since last call
if self._prev_atoms is not None and self._prev_atoms.equivalent(
self.atoms):
return
# Mark all quantities as needing to be recalculated
self.wipe()
# do we need to reinitialise _prev_atoms?
if self._prev_atoms is None or len(self._prev_atoms) != len(
self.atoms) or not self.atoms.connect.initialised:
self._prev_atoms = Atoms()
self._prev_atoms.copy_without_connect(self.atoms)
self._prev_atoms.add_property('orig_pos', self.atoms.pos)
else:
# _prev_atoms is OK, update it in place
self._prev_atoms.z[...] = self.atoms.z
self._prev_atoms.pos[...] = self.atoms.pos
self._prev_atoms.lattice[...] = self.atoms.lattice
# do a calc_connect(), setting cutoff_skin so full reconnect will only be done when necessary
self.atoms.set_cutoff(self.cutoff(), cutoff_skin=self.cutoff_skin)
potlog.debug(
'Potential doing calc_connect() with cutoff %f cutoff_skin %r' %
(self.atoms.cutoff, self.cutoff_skin))
self.atoms.calc_connect()
# Synonyms for `update` for compatibility with ASE calculator interface
def initialize(self, atoms):
self.update(atoms)
def set_atoms(self, atoms):
self.update(atoms)
def calculation_required(self, atoms, quantities):
self.update(atoms)
for quantity in quantities:
if getattr(self, quantity) is None:
return True
return False
def calculate(self, atoms, quantities=None):
"""
Perform a calculation of `quantities` for `atoms` using this Potential.
Automatically determines if a new calculation is required or if previous
results are still appliciable (i.e. if the atoms haven't moved since last call)
Called internally by :meth:`get_potential_energy`, :meth:`get_forces`, etc.
"""
if quantities is None:
quantities = ['energy', 'forces', 'stress']
# Add any default quantities
quantities = set(self.get_default_quantities() + quantities)
if len(quantities) == 0:
raise RuntimeError('Nothing to calculate')
if not self.calculation_required(atoms, quantities):
return
args_map = {
'energy': {
'energy': None
},
'energies': {
'local_energy': None
},
'forces': {
'force': None
},
'stress': {
'virial': None
},
'numeric_forces': {
'force': 'numeric_force',
'force_using_fd': True,
'force_fd_delta': 1.0e-5
},
'stresses': {
'local_virial': None
},
'elastic_constants': {},
'unrelaxed_elastic_constants': {}
}
# list of quantities that require a call to Potential.calc()
calc_quantities = [
'energy', 'energies', 'forces', 'numeric_forces', 'stress',
'stresses'
]
# list of other quantities we know how to calculate
other_quantities = ['elastic_constants', 'unrelaxed_elastic_constants']
calc_args = {}
calc_required = False
for quantity in quantities:
if quantity in calc_quantities:
calc_required = True
calc_args.update(args_map[quantity])
elif quantity not in other_quantities:
raise RuntimeError(
"Don't know how to calculate quantity '%s'" % quantity)
if calc_required:
self.calc(self.atoms, args_str=dict_to_args_str(calc_args))
if 'energy' in quantities:
self.energy = float(self.atoms.energy)
if 'energies' in quantities:
self.energies = self.atoms.local_energy.view(np.ndarray)
if 'forces' in quantities:
self.forces = self.atoms.force.view(np.ndarray).T
if 'numeric_forces' in quantities:
self.numeric_forces = self.atoms.numeric_force.view(np.ndarray).T
if 'stress' in quantities:
stress = -self.atoms.virial.view(
np.ndarray) / self.atoms.get_volume()
# convert to 6-element array in Voigt order
self.stress = np.array([
stress[0, 0], stress[1, 1], stress[2, 2], stress[1, 2],
stress[0, 2], stress[0, 1]
])
if 'stresses' in quantities:
lv = np.array(self.atoms.local_virial) # make a copy
vol_per_atom = self.get('vol_per_atom',
self.atoms.get_volume() / len(atoms))
if isinstance(vol_per_atom, basestring):
vol_per_atom = self.atoms.arrays[vol_per_atom]
self.stresses = -lv.T.reshape(
(len(atoms), 3, 3), order='F') / vol_per_atom
if 'elastic_constants' in quantities:
cij_dx = self.get('cij_dx', 1e-2)
cij = fzeros((6, 6))
self.calc_elastic_constants(self.atoms,
fd=cij_dx,
args_str=self.get_calc_args_str(),
c=cij,
relax_initial=False,
return_relaxed=False)
if not get_fortran_indexing():
cij = cij.view(np.ndarray)
self.elastic_constants = cij
if 'unrelaxed_elastic_constants' in quantities:
cij_dx = self.get('cij_dx', 1e-2)
c0ij = fzeros((6, 6))
self.calc_elastic_constants(self.atoms,
fd=cij_dx,
args_str=self.get_calc_args_str(),
c0=c0ij,
relax_initial=False,
return_relaxed=False)
if not get_fortran_indexing():
c0ij = c0ij.view(np.ndarray)
self.unrelaxed_elastic_constants = c0ij
def get_potential_energy(self, atoms):
"""
Return potential energy of `atoms` calculated with this Potential
"""
self.calculate(atoms, ['energy'])
return self.energy
def get_potential_energies(self, atoms):
"""
Return array of atomic energies calculated with this Potential
"""
self.calculate(atoms, ['energies'])
return self.energies.copy()
def get_forces(self, atoms):
"""
Return forces on `atoms` calculated with this Potential
"""
self.calculate(atoms, ['forces'])
return self.forces.copy()
def get_numeric_forces(self, atoms):
"""
Return forces on `atoms` computed with finite differences of the energy
"""
self.calculate(atoms, ['numeric_forces'])
return self.numeric_forces.copy()
def get_stress(self, atoms):
"""
Return stress tensor for `atoms` computed with this Potential
Result is a 6-element array in Voigt notation:
[sigma_xx, sigma_yy, sigma_zz, sigma_yz, sigma_xz, sigma_xy]
"""
self.calculate(atoms, ['stress'])
return self.stress.copy()
def get_stresses(self, atoms):
"""
Return the per-atoms virial stress tensors for `atoms` computed with this Potential
"""
self.calculate(atoms, ['stresses'])
return self.stresses.copy()
def get_elastic_constants(self, atoms):
"""
Calculate elastic constants of `atoms` using this Potential.
Returns 6x6 matrix :math:`C_{ij}` of elastic constants.
The elastic contants are calculated as finite difference
derivatives of the virial stress tensor using positive and
negative strains of magnitude the `cij_dx` entry in
``calc_args``.
"""
self.calculate(atoms, ['elastic_constants'])
return self.elastic_constants.copy()
def get_unrelaxed_elastic_constants(self, atoms):
"""
Calculate unrelaxed elastic constants of `atoms` using this Potential
Returns 6x6 matrix :math:`C^0_{ij}` of unrelaxed elastic constants.
The elastic contants are calculated as finite difference
derivatives of the virial stress tensor using positive and
negative strains of magnitude the `cij_dx` entry in
:attr:`calc_args`.
"""
self.calculate(atoms, ['unrelaxed_elastic_constants'])
return self.unrelaxed_elastic_constants.copy()
def get_default_quantities(self):
"Get the list of quantities to be calculated by default"
return self._default_quantities[:]
def set_default_quantities(self, quantities):
"Set the list of quantities to be calculated by default"
self._default_quantities = quantities[:]
def get(self, param, default=None):
"""
Get the value of a ``calc_args`` parameter for this :class:`Potential`
Returns ``None`` if `param` is not in the current ``calc_args`` dictionary.
All calc_args are passed to :meth:`calc` whenever energies,
forces or stresses need to be re-computed.
"""
return self._calc_args.get(param, default)
def set(self, **kwargs):
"""
Set one or more calc_args parameters for this Potential
All calc_args are passed to :meth:`calc` whenever energies,
forces or stresses need to be computed.
After updating the calc_args, :meth:`set` calls :meth:`wipe`
to mark all quantities as needing to be recaculated.
"""
self._calc_args.update(kwargs)
self.wipe()
def get_calc_args(self):
"""
Get the current ``calc_args``
"""
return self._calc_args.copy()
def set_calc_args(self, calc_args):
"""
Set the ``calc_args`` to be used subsequent :meth:`calc` calls
"""
self._calc_args = calc_args.copy()
def get_calc_args_str(self):
"""
Get the ``calc_args`` to be passed to :meth:`calc` as a string
"""
return dict_to_args_str(self._calc_args)
def get_cutoff_skin(self):
return self._cutoff_skin
def set_cutoff_skin(self, cutoff_skin):
self._cutoff_skin = cutoff_skin
self._prev_atoms = None # force a recalculation
cutoff_skin = property(get_cutoff_skin,
set_cutoff_skin,
doc="""
The `cutoff_skin` attribute is only relevant when the ASE-style
interface to the Potential is used, via the :meth:`get_forces`,
:meth:`get_potential_energy` etc. methods. In this case the
connectivity of the :class:`~quippy.atoms.Atoms` object for which
the calculation is requested is automatically kept up to date by
using a neighbour cutoff of :meth:`cutoff` + `cutoff_skin`, and
recalculating the neighbour lists whenever the maximum displacement
since the last :meth:`Atoms.calc_connect` exceeds `cutoff_skin`.
""")
