"""Adsorbate procreation operators that adds an adsorbate to the surface of
a particle or given structure."""
from ..settings import adsorbate_elements, adsorbate_molecule, site_heights
from ..utilities import is_list_or_tuple, atoms_too_close_after_addition
from ..adsorption_sites import ClusterAdsorptionSites, SlabAdsorptionSites
from ..adsorbate_coverage import ClusterAdsorbateCoverage, SlabAdsorbateCoverage
from ..build.action import add_adsorbate_to_site, remove_adsorbate_from_site
from ase.ga.offspring_creator import OffspringCreator
from ase.formula import Formula
from ase import Atoms, Atom
from asap3 import FullNeighborList
from asap3 import EMT as asapEMT
from itertools import chain
import numpy as np
import random
[docs]class AdsorbateOperator(OffspringCreator):
"""Base class for all operators that add, move or remove adsorbates.
Don't use this operator directly!"""
def __init__(self, adsorbate_species, num_muts=1):
OffspringCreator.__init__(self, num_muts=num_muts)
self.adsorbate_species = adsorbate_species if is_list_or_tuple(
adsorbate_species) else [adsorbate_species]
self.descriptor = 'AdsorbateOperator'
[docs] @classmethod
def initialize_individual(cls, parent, indi=None):
indi = OffspringCreator.initialize_individual(parent, indi=indi)
if 'unrelaxed_adsorbates' in parent.info['data']:
unrelaxed = list(parent.info['data']['unrelaxed_adsorbates'])
else:
unrelaxed = []
indi.info['data']['unrelaxed_adsorbates'] = unrelaxed
return indi
[docs] def get_new_individual(self, parents):
raise NotImplementedError
[docs] def add_adsorbate(self, atoms, hetero_site_list,
heights, adsorbate_species=None,
min_adsorbate_distance=2., tilt_angle=0.):
"""Adds the adsorbate in self.adsorbate to the supplied atoms
object at the first free site in the specified site_list. A site
is free if no other adsorbates can be found in a sphere of radius
min_adsorbate_distance around the chosen site.
Parameters
----------
atoms : ase.Atoms object
The atoms object that the adsorbate will be added to.
hetero_site_list : list
A list of dictionaries, each dictionary contains site
information given by acat.adsorbate_coverage module.
heights : dict
A dictionary that contains the adsorbate height for each site
type.
adsorbate_species : str or list of strs, default None
One or a list of adsorbate species to be added to the surface.
Use self.adsorbate_species if not specified.
min_adsorbate_distance : float, default 2.
The radius of the sphere inside which no other adsorbates
should be found.
tilt_angle : float, default 0.
Tilt the adsorbate with an angle (in degress) relative to the
surface normal.
"""
if not adsorbate_species:
adsorbate_species=self.adsorbate_species
i = 0
too_close = True
while too_close:
if i >= len(hetero_site_list):
return False
site = hetero_site_list[i]
if site['occupied']:
i += 1
continue
# Allow only single-atom species to enter subsurf 6fold sites
this_site = site['site']
if this_site == '6fold':
adsorbate_species = [s for s in adsorbate_species if len(s) == 1]
# Add a random adsorbate to the correct position
adsorbate = random.choice(adsorbate_species)
height = heights[this_site]
add_adsorbate_to_site(atoms, adsorbate, site, height,
tilt_angle=tilt_angle)
nads = len(list(Formula(adsorbate)))
ads_atoms = atoms[[a.index for a in atoms if
a.symbol in adsorbate_elements]]
if atoms_too_close_after_addition(ads_atoms, nads,
cutoff=min_adsorbate_distance):
atoms = atoms[:-nads]
i += 1
continue
too_close = False
# Setting the indices of the unrelaxed adsorbates for the cut-
# relax-paste function to be executed in the calculation script.
# There it should also reset the parameter to [], to indicate
# that the adsorbates have been relaxed.
ads_indices = sorted([len(atoms) - k - 1 for k in range(nads)])
if 'unrelaxed_adsorbates' not in atoms.info['data']:
atoms.info['data']['unrelaxed_adsorbates'] = []
atoms.info['data']['unrelaxed_adsorbates'].append(ads_indices)
return atoms
[docs] def remove_adsorbate(self, atoms, hetero_site_list, return_site_index=False):
"""Removes an adsorbate from the atoms object at the first occupied
site in hetero_site_list. If no adsorbates can be found, one will be
added instead.
Parameters
----------
atoms : ase.Atoms object
The atoms object that the adsorbate will be added to
hetero_site_list : list
A list of dictionaries, each dictionary contains site
information given by acat.adsorbate_coverage module.
return_site_index : bool, default False
Whether to return the site index of the hetero_site_list instead
of the site. Useful for moving or replacing adsorbate.
"""
i = 0
occupied = True
while occupied:
site = hetero_site_list[i]
if not site['occupied']:
i += 1
continue
if i >= len(hetero_site_list):
if return_site_index:
return False
print('Removal not possible, will add instead')
return self.add_adsorbate(atoms, hetero_site_list, site_heights)
# Remove adsorbate from the correct position
remove_adsorbate_from_site(atoms, site)
if return_site_index:
return i
occupied = False
return atoms
def get_all_adsorbate_indices(self, atoms):
ac = atoms.copy()
ads_ind = [a.index for a in ac if
a.symbol in adsorbate_elements]
mbl = 1.5 # max_bond_length
nl = FullNeighborList(rCut=mbl / 2., atoms=ac)
adsorbates = []
while len(ads_ind) != 0:
i = int(ads_ind[0])
mol_ind = self._get_indices_in_adsorbate(ac, nl, i)
for ind in mol_ind:
if int(ind) in ads_ind:
ads_ind.remove(int(ind))
adsorbates.append(sorted(mol_ind))
return adsorbates
[docs] def get_adsorbate_indices(self, atoms, position):
"""Returns the indices of the adsorbate at the supplied position."""
dmin = 1000.
for a in atoms:
if a.symbol in adsorbate_elements:
d = np.linalg.norm(a.position - position)
if d < dmin:
dmin = d
ind = a.index
for ads in self.get_all_adsorbate_indices(atoms):
if ind in ads:
return ads[:]
def _get_indices_in_adsorbate(self, atoms, neighborlist,
index, molecule_indices=None):
"""Internal recursive function that help
determine adsorbate indices."""
if molecule_indices is None:
molecule_indices = []
mi = molecule_indices
nl = neighborlist
mi.append(index)
# neighbors, _ = nl.get_neighbors(index)
neighbors = nl[index]
for n in neighbors:
if int(n) not in mi:
if atoms[int(n)].symbol in adsorbate_elements:
mi = self._get_indices_in_adsorbate(atoms, nl, n, mi)
return mi
[docs]class AddAdsorbate(AdsorbateOperator):
"""
Use this operator to add adsorbates to the surface.
The surface is allowed to change during the algorithm run.
There is no limit of adsorbate species. You can either provide one
species or a list of species.
Site and surface preference can be supplied. If both are supplied site
will be considered first.
Supplying a tilt angle will tilt the adsorbate with an angle relative
to the standard perpendicular to the surface.
The operator is generalized for both periodic and non-periodic systems
(distinguished by atoms.pbc).
Parameters
----------
adsorbate_species : str or list of strs
One or a list of adsorbate species to be added to the surface.
heights : dict, default acat.settings.site_heights
A dictionary that contains the adsorbate height for each site
type. Use the default height settings if the height for a site
type is not specified.
min_adsorbate_distance : float, default 2.
The radius of the sphere inside which no other adsorbates
should be found.
surface : str, default None
The surface type (crystal structure + Miller indices).
Only required if the structure is a periodic surface slab.
allow_6fold : bool, default False
Whether to allow the adsorption on 6-fold subsurf sites
underneath fcc hollow sites.
composition_effect : bool, default True
Whether to consider sites with different elemental compositions
as different sites. It is recommended to set composition=False
for monometallics. Since GA is commonly used for bimetallics,
the default is set to True.
site_preference : str, defualt None
The site type that has higher priority to attach adsorbates.
surface_preference : str, default None
The surface type that has higher priority to attach adsorbates.
Please only use this for nanoparticles.
tilt_angle : float, default 0.
Tilt the adsorbate with an angle (in degress) relative to the
surface normal.
num_muts : int, default 1
The number of times to perform this operation.
dmax : float, default 2.5
The maximum bond length (in Angstrom) between the site and the
bonding atom that should be considered as an adsorbate.
"""
def __init__(self, adsorbate_species,
heights=site_heights,
min_adsorbate_distance=2.,
surface=None,
allow_6fold=False,
composition_effect=True,
site_preference=None,
surface_preference=None,
tilt_angle=None,
num_muts=1,
dmax=2.5):
AdsorbateOperator.__init__(self, adsorbate_species,
num_muts=num_muts)
self.descriptor = 'AddAdsorbate'
self.heights = heights
self.min_adsorbate_distance = min_adsorbate_distance
self.surface = surface
self.allow_6fold = allow_6fold
self.composition_effect = composition_effect
self.site_preference = site_preference
self.surface_preference = surface_preference
self.tilt_angle = tilt_angle or 0.
self.min_inputs = 1
self.dmax = dmax
[docs] def get_new_individual(self, parents):
"""Returns the new individual as an atoms object."""
f = parents[0]
#print('Add adsorbate')
indi = self.initialize_individual(f)
indi.info['data']['parents'] = [f.info['confid']]
for atom in f:
indi.append(atom)
if True in indi.pbc:
sas = SlabAdsorptionSites(indi, self.surface,
self.allow_6fold,
self.composition_effect)
sac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
sas = ClusterAdsorptionSites(indi, self.allow_6fold,
self.composition_effect)
sac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = sac.hetero_site_list
nsac = None
for _ in range(self.num_muts):
random.shuffle(ads_sites)
if self.surface_preference is not None:
def func(x):
return x['surface'] == self.surface_preference
ads_sites.sort(key=func, reverse=True)
if self.site_preference is not None:
def func(x):
return x['site'] == self.site_preference
ads_sites.sort(key=func, reverse=True)
nindi = self.add_adsorbate(indi, ads_sites, self.heights,
self.adsorbate_species,
self.min_adsorbate_distance,
tilt_angle=self.tilt_angle)
if not nindi:
break
indi = nindi
if True in indi.pbc:
nsac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
nsac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = nsac.hetero_site_list
if nsac is not None:
indi.info['data']['adsorbates'] = nsac.get_adsorbates()
return (self.finalize_individual(indi),
self.descriptor + ': {0}'.format(f.info['confid']))
[docs]class RemoveAdsorbate(AdsorbateOperator):
"""This operator removes an adsorbate from the surface. It works
exactly (but doing the opposite) as the AddAdsorbate operator.
The operator is generalized for both periodic and non-periodic systems
(distinguished by atoms.pbc).
Parameters
----------
adsorbate_species : str or list of strs
One or a list of adsorbate species to be removed from the surface.
surface : str, default None
The surface type (crystal structure + Miller indices).
Only required if the structure is a periodic surface slab.
allow_6fold : bool, default False
Whether to allow the adsorption on 6-fold subsurf sites underneath
fcc hollow sites.
composition_effect : bool, default True
Whether to consider sites with different elemental compositions as
different sites. It is recommended to set composition=False for
monometallics. Since GA is commonly used for bimetallics, the
default is set to True.
site_preference : str, defualt None
The site type that has higher priority to attach adsorbates.
surface_preference : str, default None
The surface type that has higher priority to attach adsorbates.
Please only use this for nanoparticles.
tilt_angle : float, default 0.
Tilt the adsorbate with an angle (in degress) relative to the
surface normal.
num_muts : int, default 1
The number of times to perform this operation.
dmax : float, default 2.5
The maximum bond length (in Angstrom) between the site and the
bonding atom that should be considered as an adsorbate.
"""
def __init__(self, adsorbate_species,
surface=None,
allow_6fold=False,
composition_effect=True,
site_preference=None,
surface_preference=None,
num_muts=1,
dmax=2.5):
AdsorbateOperator.__init__(self, adsorbate_species,
num_muts=num_muts)
self.descriptor = 'RemoveAdsorbate'
self.surface = surface
self.allow_6fold = allow_6fold
self.composition_effect = composition_effect
self.site_preference = site_preference
self.surface_preference = surface_preference
self.min_inputs = 1
self.dmax = dmax
[docs] def get_new_individual(self, parents):
f = parents[0]
#print('Remove adsorbate')
indi = self.initialize_individual(f)
indi.info['data']['parents'] = [f.info['confid']]
for atom in f:
indi.append(atom)
if True in indi.pbc:
sas = SlabAdsorptionSites(indi, self.surface,
self.allow_6fold,
self.composition_effect)
sac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
sas = ClusterAdsorptionSites(indi, self.allow_6fold,
self.composition_effect)
sac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = sac.hetero_site_list
nsac = None
for _ in range(self.num_muts):
random.shuffle(ads_sites)
if self.surface_preference is not None:
def func(x):
return x['surface'] == self.surface_preference
ads_sites.sort(key=func, reverse=True)
if self.site_preference is not None:
def func(x):
return x['site'] == self.site_preference
ads_sites.sort(key=func, reverse=True)
indi = self.remove_adsorbate(indi, ads_sites)
# Make sure there are still adsorbates to remove
if not [a for a in indi if a.symbol in adsorbate_elements]:
break
if True in indi.pbc:
nsac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
nsac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = nsac.hetero_site_list
if nsac is not None:
indi.info['data']['adsorbates'] = nsac.get_adsorbates()
return (self.finalize_individual(indi),
self.descriptor + ': {0}'.format(f.info['confid']))
[docs]class MoveAdsorbate(AdsorbateOperator):
"""This operator removes an adsorbate from the surface and adds it
again to a different site, i.e. effectively moving the adsorbate.
The operator is generalized for both periodic and non-periodic systems
(distinguished by atoms.pbc).
Parameters
----------
adsorbate_species : str or list of strs
One or a list of adsorbate species to be added to the surface.
heights : dict, default acat.settings.site_heights
A dictionary that contains the adsorbate height for each site
type. Use the default height settings if the height for a site
type is not specified.
min_adsorbate_distance : float, default 2.
The radius of the sphere inside which no other adsorbates
should be found.
surface : str, default None
The surface type (crystal structure + Miller indices).
Only required if the structure is a periodic surface slab.
allow_6fold : bool, default False
Whether to allow the adsorption on 6-fold subsurf sites
underneath fcc hollow sites.
composition_effect : bool, default True
Whether to consider sites with different elemental compositions
as different sites. It is recommended to set composition=False
for monometallics. Since GA is commonly used for bimetallics,
the default is set to True.
site_preference_from : str, defualt None
The site type that has higher priority to detach adsorbates.
surface_preference_from : str, default None
The surface type that has higher priority to detach adsorbates.
Please only use this for nanoparticles.
site_preference_to : str, defualt None
The site type that has higher priority to attach adsorbates.
surface_preference_to : str, default None
The surface type that has higher priority to attach adsorbates.
Please only use this for nanoparticles.
tilt_angle : float, default 0.
Tilt the adsorbate with an angle (in degress) relative to the
surface normal.
num_muts : int, default 1
The number of times to perform this operation.
dmax : float, default 2.5
The maximum bond length (in Angstrom) between the site and the
bonding atom that should be considered as an adsorbate.
"""
def __init__(self, adsorbate_species,
heights=site_heights,
min_adsorbate_distance=2.,
surface=None,
allow_6fold=False,
composition_effect=True,
site_preference_from=None,
surface_preference_from=None,
site_preference_to=None,
surface_preference_to=None,
tilt_angle=None,
num_muts=1,
dmax=2.5):
AdsorbateOperator.__init__(self, adsorbate_species,
num_muts=num_muts)
self.descriptor = 'MoveAdsorbate'
self.heights = heights
self.min_adsorbate_distance = min_adsorbate_distance
self.surface = surface
self.allow_6fold = allow_6fold
self.composition_effect = composition_effect
self.site_preference_from = site_preference_from
self.surface_preference_from = surface_preference_from
self.site_preference_to = site_preference_to
self.surface_preference_to = surface_preference_to
self.tilt_angle = tilt_angle or 0.
self.min_inputs = 1
self.dmax = dmax
[docs] def get_new_individual(self, parents):
f = parents[0]
#print('Move adsorbate')
indi = self.initialize_individual(f)
indi.info['data']['parents'] = [f.info['confid']]
for atom in f:
indi.append(atom)
if True in indi.pbc:
sas = SlabAdsorptionSites(indi, self.surface,
self.allow_6fold,
self.composition_effect)
sac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
sas = ClusterAdsorptionSites(indi, self.allow_6fold,
self.composition_effect)
sac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = sac.hetero_site_list
nsac = None
for _ in range(self.num_muts):
random.shuffle(ads_sites)
if self.surface_preference_from is not None:
def func(x):
return x['surface'] == self.surface_preference_from
ads_sites.sort(key=func, reverse=True)
if self.site_preference_from is not None:
def func(x):
return x['site'] == self.site_preference_from
ads_sites.sort(key=func, reverse=True)
removed = self.remove_adsorbate(indi, ads_sites,
return_site_index=True)
if not removed:
removed_species = random.choice(self.adsorbate_species)
else:
removed_species = ads_sites[removed]['adsorbate']
random.shuffle(ads_sites)
if self.surface_preference_to is not None:
def func(x):
return x['surface'] == self.surface_preference_to
ads_sites.sort(key=func, reverse=True)
if self.site_preference_to is not None:
def func(x):
return x['site'] == self.site_preference_to
ads_sites.sort(key=func, reverse=True)
nindi = self.add_adsorbate(indi, ads_sites,
self.heights, removed_species,
self.min_adsorbate_distance,
tilt_angle=self.tilt_angle)
if not nindi:
break
indi = nindi
if True in indi.pbc:
nsac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
nsac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = nsac.hetero_site_list
if nsac is not None:
indi.info['data']['adsorbates'] = nsac.get_adsorbates()
return (self.finalize_individual(indi),
self.descriptor + ': {0}'.format(f.info['confid']))
[docs]class ReplaceAdsorbate(AdsorbateOperator):
"""This operator removes an adsorbate from the surface and adds another
species to the same site, i.e. effectively replacing the adsorbate.
The operator is generalized for both periodic and non-periodic systems
(distinguished by atoms.pbc).
Parameters
----------
adsorbate_species : str or list of strs
One or a list of adsorbate species to be added to the surface.
heights : dict, default acat.settings.site_heights
A dictionary that contains the adsorbate height for each site
type. Use the default height settings if the height for a site
type is not specified.
min_adsorbate_distance : float, default 2.
The radius of the sphere inside which no other adsorbates
should be found.
surface : str, default None
The surface type (crystal structure + Miller indices).
Only required if the structure is a periodic surface slab.
allow_6fold : bool, default False
Whether to allow the adsorption on 6-fold subsurf sites
underneath fcc hollow sites.
composition_effect : bool, default True
Whether to consider sites with different elemental compositions
as different sites. It is recommended to set composition=False
for monometallics. Since GA is commonly used for bimetallics,
the default is set to True.
site_preference_from : str, defualt None
The site type that has higher priority to replace adsorbates.
surface_preference_from : str, default None
The surface type that has higher priority to replace adsorbates.
Please only use this for nanoparticles.
tilt_angle : float, default 0.
Tilt the adsorbate with an angle (in degress) relative to the
surface normal.
num_muts : int, default 1
The number of times to perform this operation.
dmax : float, default 2.5
The maximum bond length (in Angstrom) between the site and the
bonding atom that should be considered as an adsorbate.
"""
def __init__(self, adsorbate_species,
heights=site_heights,
min_adsorbate_distance=2.,
surface=None,
allow_6fold=False,
composition_effect=True,
site_preference_from=None,
surface_preference_from=None,
tilt_angle=None,
num_muts=1,
dmax=2.5):
AdsorbateOperator.__init__(self, adsorbate_species,
num_muts=num_muts)
self.descriptor = 'ReplaceAdsorbate'
self.heights = heights
self.min_adsorbate_distance = min_adsorbate_distance
self.surface = surface
self.allow_6fold = allow_6fold
self.composition_effect = composition_effect
self.site_preference_from = site_preference_from
self.surface_preference_from = surface_preference_from
self.tilt_angle = tilt_angle or 0.
self.min_inputs = 1
self.dmax = dmax
[docs] def get_new_individual(self, parents):
f = parents[0]
#print('Replace adsorbate')
indi = self.initialize_individual(f)
indi.info['data']['parents'] = [f.info['confid']]
for atom in f:
indi.append(atom)
if True in indi.pbc:
sas = SlabAdsorptionSites(indi, self.surface,
self.allow_6fold,
self.composition_effect)
sac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
sas = ClusterAdsorptionSites(indi, self.allow_6fold,
self.composition_effect)
sac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = sac.hetero_site_list
nsac = None
for _ in range(self.num_muts):
random.shuffle(ads_sites)
if self.surface_preference_from is not None:
def func(x):
return x['surface'] == self.surface_preference_from
ads_sites.sort(key=func, reverse=True)
if self.site_preference_from is not None:
def func(x):
return x['site'] == self.site_preference_from
ads_sites.sort(key=func, reverse=True)
removed = self.remove_adsorbate(indi, ads_sites,
return_site_index=True)
if not removed:
removed = random.choice(range(len(ads_sites)))
removed_species = 'x'
else:
removed_species = ads_sites[removed]['adsorbate']
ads_sites[removed]['occupied'] = 0
other_species = [s for s in self.adsorbate_species if
s != removed_species]
nindi = self.add_adsorbate(indi, [ads_sites[removed]],
self.heights, other_species,
self.min_adsorbate_distance,
tilt_angle=self.tilt_angle)
if not nindi:
break
indi = nindi
if True in indi.pbc:
nsac = SlabAdsorbateCoverage(indi, sas, dmax=self.dmax)
else:
nsac = ClusterAdsorbateCoverage(indi, sas, dmax=self.dmax)
ads_sites = nsac.hetero_site_list
if nsac is not None:
indi.info['data']['adsorbates'] = nsac.get_adsorbates()
return (self.finalize_individual(indi),
self.descriptor + ': {0}'.format(f.info['confid']))
[docs]class CutSpliceCrossoverWithAdsorbates(AdsorbateOperator):
"""Crossover that cuts two particles with adsorbates through a plane
in space and merges two halfes from different particles together.
It keeps the correct composition by randomly assigning elements in
the new particle. If some of the atoms in the two particle halves
are too close, the halves are moved away from each other perpendicular
to the cutting plane.
The complexity of crossover with adsorbates makes this operator not
robust enough. The adsorption site identification will fail once the
nanoparticle shape becomes too irregular after crossover.
Parameters
----------
adsorbate_species : str or list of strs
One or a list of adsorbate species to be added to the surface.
blmin : dict
Dictionary of minimum distance between atomic numbers.
e.g. {(28,29): 1.5}
keep_composition : bool, default True
Should the composition be the same as in the parents.
fix_coverage : bool, default False
Should the adsorbate coverage be the same as in the parents.
min_adsorbate_distance : float, default 2.
The radius of the sphere inside which no other adsorbates
should be found.
allow_6fold : bool, default False
Whether to allow the adsorption on 6-fold subsurf sites
underneath fcc hollow sites.
composition_effect : bool, default True
Whether to consider sites with different elemental compositions
as different sites. It is recommended to set composition=False
for monometallics. Since GA is commonly used for bimetallics,
the default is set to True.
rotate_vectors : list, default None
A list of vectors that the part of the structure that is cut
is able to rotate around, the size of rotation is set in
rotate_angles. Default None meaning no rotation is performed.
rotate_angles : list, default None
A list of angles that the structure cut can be rotated. The
vector being rotated around is set in rotate_vectors. Default
None meaning no rotation is performed.
dmax : float, default 2.5
The maximum bond length (in Angstrom) between the site and the
bonding atom that should be considered as an adsorbate.
"""
def __init__(self, adsorbate_species, blmin,
keep_composition=True,
fix_coverage=False,
min_adsorbate_distance=2.,
allow_6fold=False,
composition_effect=True,
rotate_vectors=None,
rotate_angles=None,
dmax=2.5):
AdsorbateOperator.__init__(self, adsorbate_species)
self.blmin = blmin
self.keep_composition = keep_composition
self.fix_coverage = fix_coverage
self.min_adsorbate_distance = min_adsorbate_distance
self.allow_6fold = allow_6fold
self.composition_effect = composition_effect
self.rvecs = rotate_vectors
self.rangs = rotate_angles
self.descriptor = 'CutSpliceCrossoverWithAdsorbates'
self.min_inputs = 2
self.dmax = dmax
[docs] def get_new_individual(self, parents):
f, m = parents
#print('Crossover with adsorbates')
if self.fix_coverage:
# Count number of adsorbates
adsorbates_in_parents = len(self.get_all_adsorbate_indices(f))
indi = self.initialize_individual(f)
indi.info['data']['parents'] = [i.info['confid'] for i in parents]
fna = self.get_atoms_without_adsorbates(f)
mna = self.get_atoms_without_adsorbates(m)
fna_geo_mid = np.average(fna.get_positions(), 0)
mna_geo_mid = np.average(mna.get_positions(), 0)
if self.rvecs is not None:
if not isinstance(self.rvecs, list):
print('Rotation vectors are not a list, skipping rotation')
else:
vec = random.choice(self.rvecs)
try:
angle = random.choice(self.rangs)
except TypeError:
angle = self.rangs
f.rotate(angle, vec, center=fna_geo_mid)
vec = random.choice(self.rvecs)
try:
angle = random.choice(self.rangs)
except TypeError:
angle = self.rangs
m.rotate(angle, vec, center=mna_geo_mid)
theta = random.random() * 2 * np.pi # 0,2pi
phi = random.random() * np.pi # 0,pi
e = np.asarray((np.sin(phi) * np.cos(theta),
np.sin(theta) * np.sin(phi),
np.cos(phi)))
eps = 0.0001
# Move each particle to origo with their respective geometrical
# centers, without adsorbates
common_mid = (fna_geo_mid + mna_geo_mid) / 2.
f.translate(-common_mid)
m.translate(-common_mid)
off = 1
while off != 0:
fna = self.get_atoms_without_adsorbates(f)
mna = self.get_atoms_without_adsorbates(m)
# Get the signed distance to the cutting plane
# We want one side from f and the other side from m
fmap = [np.dot(x, e) for x in fna.get_positions()]
mmap = [-np.dot(x, e) for x in mna.get_positions()]
ain = sorted([i for i in chain(fmap, mmap) if i > 0],
reverse=True)
aout = sorted([i for i in chain(fmap, mmap) if i < 0],
reverse=True)
off = len(ain) - len(fna)
# Translating f and m to get the correct number of atoms
# in the offspring
if off < 0:
# too few
# move f and m away from the plane
dist = abs(aout[abs(off) - 1]) + eps
f.translate(e * dist)
m.translate(-e * dist)
elif off > 0:
# too many
# move f and m towards the plane
dist = abs(ain[-abs(off)]) + eps
f.translate(-e * dist)
m.translate(e * dist)
eps /= 5.
fna = self.get_atoms_without_adsorbates(f)
mna = self.get_atoms_without_adsorbates(m)
# Determine the contributing parts from f and m
tmpf, tmpm = Atoms(), Atoms()
for atom in fna:
if np.dot(atom.position, e) > 0:
atom.tag = 1
tmpf.append(atom)
for atom in mna:
if np.dot(atom.position, e) < 0:
atom.tag = 2
tmpm.append(atom)
# Place adsorbates from f and m in tmpf and tmpm
f_ads = self.get_all_adsorbate_indices(f)
m_ads = self.get_all_adsorbate_indices(m)
for ads in f_ads:
if np.dot(f[ads[0]].position, e) > 0:
for i in ads:
f[i].tag = 1
tmpf.append(f[i])
for ads in m_ads:
pos = m[ads[0]].position
if np.dot(pos, e) < 0:
# If the adsorbate will sit too close to another adsorbate
# (below self.min_adsorbate_distance) do not add it.
dists = [np.linalg.norm(pos - a.position)
for a in tmpf if a.tag == 1]
for d in dists:
if d < self.min_adsorbate_distance:
break
else:
for i in ads:
m[i].tag = 2
tmpm.append(m[i])
tmpfna = self.get_atoms_without_adsorbates(tmpf)
tmpmna = self.get_atoms_without_adsorbates(tmpm)
# Check that the correct composition is employed
if self.keep_composition:
opt_sm = sorted(fna.numbers)
tmpf_numbers = list(tmpfna.numbers)
tmpm_numbers = list(tmpmna.numbers)
cur_sm = sorted(tmpf_numbers + tmpm_numbers)
# correct_by: dictionary that specifies how many
# of the atom_numbers should be removed (a negative number)
# or added (a positive number)
correct_by = dict([(j, opt_sm.count(j)) for j in set(opt_sm)])
for n in cur_sm:
correct_by[n] -= 1
correct_in = random.choice([tmpf, tmpm])
to_add, to_rem = [], []
for num, amount in correct_by.items():
if amount > 0:
to_add.extend([num] * amount)
elif amount < 0:
to_rem.extend([num] * abs(amount))
for add, rem in zip(to_add, to_rem):
tbc = [a.index for a in correct_in if a.number == rem]
if len(tbc) == 0:
pass
ai = random.choice(tbc)
correct_in[ai].number = add
# Move the contributing apart if any distance is below blmin
maxl = 0.
for sv, min_dist in self.get_vectors_below_min_dist(tmpf + tmpm):
lsv = np.linalg.norm(sv) # length of shortest vector
d = [-np.dot(e, sv)] * 2
d[0] += np.sqrt(np.dot(e, sv)**2 - lsv**2 + min_dist**2)
d[1] -= np.sqrt(np.dot(e, sv)**2 - lsv**2 + min_dist**2)
l = sorted([abs(i) for i in d])[0] / 2. + eps
if l > maxl:
maxl = l
tmpf.translate(e * maxl)
tmpm.translate(-e * maxl)
# Translate particles halves back to the center
tmpf.translate(common_mid)
tmpm.translate(common_mid)
# Put the two parts together
for atom in chain(tmpf, tmpm):
indi.append(atom)
pcas = ClusterAdsorptionSites(indi, self.allow_6fold,
self.composition_effect)
pcac = ClusterAdsorbateCoverage(indi, pcas, dmax=self.dmax)
pads_sites = pcac.hetero_site_list
adsi_dict = {}
adsorbate_ids = set()
for st in pads_sites:
if st['occupied']:
adsi = st['adsorbate_indices']
if set(adsi).issubset(adsorbate_ids):
continue
adsorbate_ids.update(adsi)
si = st['indices']
adsi_dict[si] = {}
adsi_dict[si]['height'] = st['bond_length']
adsi_dict[si]['adsorbate'] = st['adsorbate']
adsi_dict[si]['adsorbate_indices'] = st['adsorbate_indices']
indi = pcas.atoms
indi.positions = pcas.ref_atoms.positions
cas = ClusterAdsorptionSites(indi, self.allow_6fold,
self.composition_effect)
nori = len(indi)
for st in cas.site_list:
si = st['indices']
if si in adsi_dict:
adsorbate = adsi_dict[si]['adsorbate']
height = adsi_dict[si]['height']
add_adsorbate_to_site(indi, adsorbate, st, height)
# Make sure no adsorbates too close to each other
# after each adsorbate addition
nads = len(adsi_dict[si]['adsorbate_indices'])
if atoms_too_close_after_addition(indi, nads,
self.min_adsorbate_distance, mic=False):
indi = indi[:-nads]
# Add adsorbate if no adsorbate is present
if len(indi) == nori:
st = random.choice(cas.site_list)
ads_spec = random.choice(self.adsorbate_species)
add_adsorbate_to_site(indi, ads_spec, site=st)
cac = ClusterAdsorbateCoverage(indi, cas, dmax=self.dmax)
ads_sites = cac.hetero_site_list
if self.fix_coverage:
# Remove or add adsorbates as needed
adsorbates_in_child = self.get_all_adsorbate_indices(indi)
diff = len(adsorbates_in_child) - adsorbates_in_parents
if diff < 0:
# Add adsorbates
for _ in range(abs(diff)):
self.add_adsorbate(indi, ads_sites, site_heights,
self.adsorbate_species,
self.min_adsorbate_distance)
cac = ClusterAdsorbateCoverage(indi, cas, dmax=self.dmax)
elif diff > 0:
# Remove adsorbates
tbr = random.sample(adsorbates_in_child, diff) # to be removed
for adsorbate_indices in sorted(tbr, reverse=True):
for i in adsorbate_indices[::-1]:
indi.pop(i)
cac = ClusterAdsorbateCoverage(indi, cas, dmax=self.dmax)
indi.info['data']['adsorbates'] = cac.get_adsorbates()
return (self.finalize_individual(indi),
self.descriptor + ': {0} {1}'.format(f.info['confid'],
m.info['confid']))
def get_numbers(self, atoms):
"""Returns the atomic numbers of the atoms object
without adsorbates"""
ac = atoms.copy()
del ac[[a.index for a in ac
if a.symbol in adsorbate_elements]]
return ac.numbers
def get_atoms_without_adsorbates(self, atoms):
ac = atoms.copy()
del ac[[a.index for a in ac
if a.symbol in adsorbate_elements]]
return ac
[docs] def get_vectors_below_min_dist(self, atoms):
"""Generator function that returns each vector (between atoms)
that is shorter than the minimum distance for those atom types
(set during the initialization in blmin)."""
ap = atoms.get_positions()
an = atoms.numbers
for i in range(len(atoms)):
pos = atoms[i].position
for j, d in enumerate([np.linalg.norm(k - pos) for k in ap[i:]]):
if d == 0:
continue
min_dist = self.blmin[tuple(sorted((an[i], an[j + i])))]
if d < min_dist:
yield atoms[i].position - atoms[j + i].position, min_dist