def parse_inputs(name="config"):
"""Convert the string values of the diciontary to the appropriate types"""
inputs = complete_config(name)
inputs["bond_thresh"] = float(inputs["bond_thresh"])
if type(inputs["atom_label"]) == str:
inputs["atom_label"] = [int(inputs["atom_label"]) - 1]
else:
inputs["atom_label"] = [int(i) - 1 for i in inputs["atom_label"]]
inputs["ewald"] = bool_cast(inputs["ewald"])
inputs["nchk"] = int(inputs["nchk"])
inputs["nat"] = int(inputs["nat"])
inputs["an"] = int(inputs["an"])
inputs["bn"] = int(inputs["bn"])
inputs["cn"] = int(inputs["cn"])
inputs["clust_rad"] = float(inputs["clust_rad"])
inputs["traan"] = int(inputs["traan"])
inputs["trabn"] = int(inputs["trabn"])
inputs["tracn"] = int(inputs["tracn"])
inputs["self_consistent"] = bool_cast(inputs["self_consistent"])
inputs["dev_tol"] = float(inputs["dev_tol"])
inputs["a_vec"] = np.array([float(i) for i in inputs["a_vec"]])
inputs["b_vec"] = np.array([float(i) for i in inputs["b_vec"]])
inputs["c_vec"] = np.array([float(i) for i in inputs["c_vec"]])
inputs["damping"] = float(inputs["damping"])
inputs["print_tweak"] = bool_cast(inputs["print_tweak"])
# specified in config
inputs["vectors"] = np.zeros((3, 3))
if all(
len(i) == 3
for i in [inputs["a_vec"], inputs["b_vec"], inputs["c_vec"]]):
a_vec = inputs["a_vec"]
b_vec = inputs["b_vec"]
c_vec = inputs["c_vec"]
inputs["vectors"][0] = a_vec
inputs["vectors"][1] = b_vec
inputs["vectors"][2] = c_vec
else: # from external file
inputs["vectors"] = rf.read_vectors(inputs["vectors_file"])
return inputs
def main(args):
# read input file
all_atoms = fro.mol_from_file(args.input)
# specify bonding
all_atoms.set_bonding(bonding=args.bonding, thresh=args.thresh)
# if the bonding is specified all in one string
if args.bonding_string:
all_atoms.set_bonding_str(args.bonding_string)
# if periodic
if args.vectors:
prints("Vectors detected")
vectors = rf.read_vectors(args.vectors)
all_atoms.vectors = vectors
# if we are forbidding some atoms
if args.no_atom_label:
forbidden_kinds = []
# for each atom to forbid
for label in args.no_atom_label:
mol_of_interest = all_atoms.per_select(label - 1)
mol_of_interest.set_connectivity()
for atom in mol_of_interest:
if atom == all_atoms[label - 1]:
forbidden_kinds.append(atom.kind)
all_atoms, molecules = all_atoms.complete_cell()
prints("{} molecules detected after reconstitution".format(
len(molecules)))
else:
# if we are forbidding some atoms
if args.no_atom_label:
forbidden_kinds = []
# for each atom to forbid
for label in args.no_atom_label:
mol_of_interest = all_atoms.select(label - 1)
mol_of_interest.set_connectivity()
for atom in mol_of_interest:
if atom == all_atoms[label - 1]:
forbidden_kinds.append(atom.kind)
# separate into molecules
molecules = all_atoms.segregate(diff_mols=False)
prints("{} molecules detected".format(len(molecules)))
# ignore hydrogens
if args.no_hydrogens:
for mol in molecules:
mol.geom.ignore_hydrogens = True
# ignore certain atoms
if args.no_atom_label:
zero_vectors = np.array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]])
for mol in molecules:
mol.vectors = zero_vectors
mol.set_connectivity()
mol.geom.ignore_kinds = forbidden_kinds
# get dimers
dimers_raw = all_dimers(molecules)
prints("{} dimers in the input geometry".format(len(dimers_raw)))
# if periodic
if args.vectors:
# get all the dimers generated by extra periodic images
dimers_per = []
for dimer in dimers_raw:
images = dimer.images(vectors)
dimers_per.extend(images)
dimers_raw = dimers_per
prints("{} dimers considering periodicity".format(len(dimers_raw)))
if args.linear:
for dimer in dimers_raw:
dimer.mols_are_linear()
# filter out dimers
if args.dimtype == 'centroid':
method = 'centroid'
mode = 'dis'
else:
method = 'atomic'
if args.dimtype == 'dis':
mode = 'dis'
elif args.dimtype == 'cov':
mode = 'cov'
elif args.dimtype == 'vdw':
mode = 'vdw'
selected_dimers = []
for dimer in dimers_raw:
if dimer.inter_distance(method=method, mode=mode) <= args.dist:
selected_dimers.append(dimer)
prints("{} dimers selected from distance criterion".format(
len(selected_dimers)))
# remove repeated dimers
keep_these = []
for i, dimer_i in enumerate(selected_dimers[:-1]):
keep = True
for dimer_j in selected_dimers[i + 1:]:
if dimer_i.same_geom(dimer_j, tol=args.tol_duplicate):
keep = False
break
if keep:
keep_these.append(dimer_i)
# don't forget that the last one was not included in the parent loop
keep_these.append(selected_dimers[-1])
selected_dimers = keep_these
prints("{} dimers remaining after removing duplicates".format(
len(selected_dimers)))
if args.output_geometry_data:
data_file = open(args.output_geometry_data, "w")
header_str = "{:>13}{:>10}{:>10}{:>10}{:>17}{:>13}{:>11}\n".format(
"Dimer number", "Alpha", "Beta", "Gamma", "Centroid dist",
"Slip angle", "Category")
data_file.write(header_str)
for i, dimer in enumerate(selected_dimers):
if args.output_geometry_data:
cen_dist = dimer.inter_distance(method='centroid')
angles = dimer.angles()
slip_angle = dimer.slip_angle()
# classify
if 20 < angles[2] < 160:
category = "E-F"
elif slip_angle > 60:
category = "S-S"
else:
category = "F-F"
data_file.write(
"{:>7}{:17.3f}{:10.3f}{:10.3f}{:12.3f}{:15.3f}{:>10}\n".format(
i + 1, angles[0], angles[1], angles[2], cen_dist,
slip_angle, category))
if args.print_dimers:
out_name = str(args.input[:-4]) + "_dimer_" + str(i + 1) + ".xyz"
dimer.write_xyz(out_name)
if args.output_geometry_data:
data_file.close()
def pery_cell():
"""Return a Mol object of the uncharged perylene cell"""
out_cell = rf.mol_from_file("perylene_cell.xyz")
out_cell.vectors = rf.read_vectors("perylene_vectors")
return out_cell
def main(in_xyz, vectors_file, complete, confine, frac, dupli, output, bonding,
thresh, bonding_str, print_mono, trans, clust_rad, inclusivity,
center_label):
vectors = rf.read_vectors(vectors_file)
atoms = rf.mol_from_file(in_xyz, vectors=vectors)
if thresh == 999:
thresh = None
atoms.set_bonding(bonding=bonding, thresh=thresh)
# if the bonding is specified all in one string
if bonding_str:
atoms.set_bonding_str(bonding_str)
if print_mono and not complete:
print("-c is required for -m")
return
if sum([complete, confine, frac]) > 1:
print("-c, -C and -f are mutually exclusive")
return
print_now = True
centered = False
if center_label:
central_mol, atoms = atoms.centered_mols(center_label -
1) # -1 for Python index
centered = True
if complete:
# get the modified (uncropped) unit cell
mod_cell, mols = atoms.complete_cell()
elif confine:
# get the cell confined to primitive
mod_cell = atoms.confined()
elif frac:
# get the cell in fractional coordinates
mod_cell = atoms.dir_to_frac_pos()
elif centered:
mod_cell = atoms.copy()
else:
mod_cell = deepcopy(atoms)
print_now = False
if dupli:
# purge duplicate atoms
mod_cell.remove_duplicates()
print_now = True
if print_now:
mod_cell.write_xyz(output)
if trans:
translation = np.array(trans)
new_atoms = mod_cell.supercell(translation)
new_vec = (vectors.T * translation.transpose()).T
new_atoms.write_xyz("supercell_out.xyz")
ef.write_lat_vec("supercell_vectors", new_vec)
if clust_rad > 0.0:
clust = atoms.make_cluster(clust_rad, mode=inclusivity)
clust.write_xyz("cluster_out.xyz")
if print_mono:
identities = []
# for each molecule of the modified unit cell
for mol_i in mols:
# get the rest of the molecules
rest = []
for mol_j in mols:
if mol_j != mol_i:
rest.append(mol_j)
identity = []
# for each dimer including the selected molecule
for mol_j in rest:
dimer_distances = []
# get all of the interatomic distances across the dimer using the
# shortest lattice distance
for at_i in mol_i:
for at_j in mol_j:
dimer_distances.append(at_i.per_dist(at_j, vectors))
dimer_distances.sort()
identity.append(dimer_distances)
identity.sort()
identities.append(identity)
identities = np.array(identities)
# list of each molecules paired with its identity
# in Python 2 we could just use a zip but for compatibility with Python3
# we need a list of tuples
mols_ids = [(mol_i, iden_i) for mol_i, iden_i in zip(mols, identities)]
# list of each molecule paired with its identity separated by equivalent
# molecule
sep_mols_ids = []
while len(mols_ids) > 0:
sep_mol_id = [mols_ids[0]]
for mol_i, id_i in mols_ids[1:]:
comp = compare_id(mols_ids[0][1], id_i)
# if the identities being compared don't have the same dimension,
# the comparison will return None. This implies that the molecules
# are not equivalent. This case only happens in crystals with
# different monomers
if comp:
if comp < 0.001:
sep_mol_id.append((mol_i, id_i))
mols_ids.remove((mol_i, id_i))
del mols_ids[0]
sep_mols_ids.append(sep_mol_id)
for counter, equimols in enumerate(sep_mols_ids):
# only the list of lists of atoms i.e. list of molecules which are
# equivalent
fequimols = [i[0] for i in equimols]
# make it a flat list
fequimols = [inner for outer in fequimols for inner in outer]
ef.write_xyz("mono_" + str(counter + 1) + ".xyz", fequimols)
return
