## for every plane, find mid-oxygen sites
for pl in planes:
## if something did not work upstream, then short-circuit
if broken: break
## get the mobile-ion sites for this plane
site_pts = cu.get_mobile_ion_sites(atoms, pl, cell)
num_sites = len(site_pts)
## find the graph distances to Mg defects above & below the plane
## get all the mid-oxygen sites in this plane
mid_oxs, edges, midpts = cu.get_mid_oxygen_sites_freud(site_pts,
cell,
viz=False)
## create a proper networkx graph from site-edge list for this plane
site_graph = nx.from_edgelist(edges)
path_lengths = cu.path_lengths(site_graph)
## find the defect closest to each mobile-ion site in this plane
## max distance serves to downselect the defects in the closest block
e0, e1, d0, d1 = cu.get_nearest_points(site_pts,
defect_pts,
cell,
num_nn=6)
e0 = np.array(e0)[np.array(d0) < dz]
e1 = np.array(e1)[np.array(d1) < dz]
viz=False)
num_sites = len(site_pts)
print(
f'Identified {num_sites} mobile-ion sites in plane {input_plane_name}'
)
## auto-get BR sites - this just yields a list of false for beta-doubleprime
site_types = cu.auto_get_BR_sites(all_atoms,
cell,
site_pts,
atoms_are_frac=frac)
BR_sites = [i for i in range(len(site_types)) if site_types[i] == 'BR']
# compose network of mobile-ion sites, calculate paths. Both beta and beta"
# This can create and save a figure when viz=True. Pass cell if fractional was false
_, edges, _ = cu.get_mid_oxygen_sites_freud(
site_pts, cell if not frac else np.eye(3), viz=True)
nxg = nx.from_edgelist(edges)
path_lengths = cu.path_lengths(nxg)
## DEFECTS
# find the interstitial defects in this plane: make an array and set z=0
# the sites will be found below with the same query that counts hops
try:
oi_defects = ointers.query(f'z == {plane}')
oi_defect_pts = oi_defects[['x', 'y', 'z']].values
# oi_defect_pts[:,-1] = 0
oi_adjacent_sites, _ = cu.get_defect_adjacent_sites(
cell, site_pts, oi_defect_pts)
print(f'sites next to O_i in plane {input_plane_name}: ',
oi_adjacent_sites)
## find all conduction planes in the input file
planes = cu.get_conduction_planes(atoms, metal)
## initialize data structures
new_atoms = atoms.copy(deep=True)
all_interstitial_indices = list()
all_paths_to_oi = list() ## plotting only
## for every plane, find mid-oxygen sites
for pl in planes:
## get the mobile-ion sites for this plane
mobile_sites = cu.get_mobile_ion_sites(atoms, pl, cell)
## get all the mid-oxygen sites in this plane
mid_oxs, edges, midpts = cu.get_mid_oxygen_sites_freud(mobile_sites, cell, viz=True)
plt.gca().set(aspect=1, title=f'z={pl:.3f} $\AA$', ylim=np.array([-0.59,0.59])*cell[1,1],
xlim=np.array([-0.55,0.55])*cell[0,0])
plt.gcf().tight_layout()
## Pick mid-oxygen sites quasi-randomly, independent of coordinates
if packed:
picked, fresh, past = cu.generate_mid_oxygens_packed(mid_oxs, num_ois_per_plane, exclude)
else:
picked, fresh, past = cu.generate_mid_oxygens(mid_oxs, num_ois_per_plane, exclude)
print(f'{len(picked)} picked, {len(past)} excluded, {len(fresh)} sites remain')
## Plot the mid-oxygen sites where interstitials are going
xs = []; ys = []
for mo in mid_oxs:
for p4 in picked:
all_ois = inters.copy(deep=True)
Lx, Ly, Lz = np.diag(cell) if not frac else np.ones(3) ## box size for freud.
## find the conduction planes
planes = cu.get_conduction_planes(atoms, metal)
## hard-coded names for planes. Will be different for beta-doubleprime
plane_names = ['{:03d}'.format(x) for x in ((planes/Lz+0.5) * 100).astype(int)]
## iterate through planes
for pl, pname in zip(planes, plane_names):
## get and plot the mobile-ion sites for this plane
mobile_sites = cu.get_mobile_ion_sites(atoms, pl, cell)
_, edges, _ = cu.get_mid_oxygen_sites_freud(mobile_sites, cell, viz=False)
## try auto-getting BR sites
site_types = cu.auto_get_BR_sites(atoms, cell, mobile_sites,atoms_are_frac=frac)
BR_sites = [i for i in range(len(site_types)) if site_types[i] == 'BR']
fig, ax = plt.subplots()
box = freud.box.Box(Lx=Lx, Ly=Ly, is2D = True)
site_vor = freud.locality.Voronoi(box)
mobile_sites[:,-1] = 0
site_vor.compute((box, mobile_sites))
cu.draw_voronoi(box, mobile_sites, [site_vor.polytopes[i] for i in BR_sites],cell_numbers=BR_sites)
plt.gca().set(aspect = 1 if not frac else cell[1,1]/cell[0,0], title=f'z={pname}')
plt.gcf().tight_layout()
## read the input .CONFIG file & add symmetry elements
phase, intro_line, cell, atoms = cu.read_poly(prod_file, fractional=False)
# atoms = cu.add_symmetry_beta(atoms, cell, mobile=metal, frac=False)
## find all conduction planes in the input file
planes = cu.get_conduction_planes(atoms, metal)
## generate networks and path lengths for every plane, only once
mid_ox_dict = dict()
path_length_dict = dict()
mobile_site_dict = dict()
for pl in planes :
these_mobile_sites = cu.get_mobile_ion_sites(atoms, pl, cell)
these_mid_oxs, these_edges, _ = cu.get_mid_oxygen_sites_freud(these_mobile_sites, cell, viz=False)
path_length_dict[pl] = cu.path_lengths(nx.from_edgelist(these_edges))
mid_ox_dict[pl] = these_mid_oxs
mobile_site_dict[pl] = these_mobile_sites
print(f'Made networks in plane z={pl:.4f}, total {(dt.now()-start).total_seconds():4.1f} sec.')
dict_of_excludes = dict()
print(f'Setup took {(dt.now()-start).total_seconds():4.1f} sec.')
# =============================================================================
# %% Generate a bunch of random structures and count their sites
# =============================================================================
start = dt.now()
for exclude in [1,4] :