def generate_vaspinput(ele1="Ti", ele2="O", a_ref=5.05):
# C1 CaF2
a = a_ref
atoms = crystal([ele1, ele2], [(0.0, 0.5, 0.5), (0.25, 0.25, 0.25)], spacegroup=225, cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("C1"):
os.mkdir("C1")
os.chdir("C1")
write_vasp("POSCAR", atoms, label="C1", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# C2 FeS2
a = a_ref
atoms = crystal(
[ele1, ele2], [(0.0, 0.0, 0.0), (0.38504, 0.38504, 0.38504)], spacegroup=205, cellpar=[a, a, a, 90, 90, 90]
)
if not os.path.exists("C2"):
os.mkdir("C2")
os.chdir("C2")
write_vasp("POSCAR", atoms, label="C2", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# C3 Cu2O
a = a_ref * 0.917
atoms = crystal([ele1, ele2], [(0.0, 0.0, 0.0), (0.25, 0.25, 0.25)], spacegroup=224, cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("C3"):
os.mkdir("C3")
os.chdir("C3")
write_vasp("POSCAR", atoms, label="C3", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# C4 TiO2 (rutile)
a = a_ref * 0.9278
c = a * 0.6440
atoms = crystal(
[ele1, ele2], [(0.0, 0.0, 0.0), (0.3057, 0.3057, 0.0)], spacegroup=136, cellpar=[a, a, c, 90, 90, 90]
)
if not os.path.exists("C4"):
os.mkdir("C4")
os.chdir("C4")
write_vasp("POSCAR", atoms, label="C4", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# C5 TiO2 (anatase)
a = a_ref * 0.7798
c = a * 2.514
atoms = crystal([ele1, ele2], [(0.0, 0.0, 0.0), (0.0, 0.0, 0.2081)], spacegroup=141, cellpar=[a, a, c, 90, 90, 90])
if not os.path.exists("C5"):
os.mkdir("C5")
os.chdir("C5")
write_vasp("POSCAR", atoms, label="C5", direct=True, long_format=True, vasp5=True)
os.chdir("..")
def __getitem__(self, name):
d = self.data[name]
# the index of label in labels less one
# (compound is already as key in d)
a = d[self.labels.index("aexp") - 1]
if name in ["Cr2CoGa", "Mn2CoAl", "Mn2CoGe", "Fe2CoSi"]:
# http://en.wikipedia.org/wiki/Space_group
sg = 216
else:
sg = 225
symbols = string2symbols(name)
symbols.pop(0)
b = crystal(
symbols=symbols,
basis=[(1.0 / 4, 1.0 / 4, 1.0 / 4), (0.0, 0.0, 0.0), (1.0 / 2, 1.0 / 2, 1.0 / 2)],
spacegroup=sg,
cellpar=[a, a, a, 90, 90, 90],
primitive_cell=True,
)
# set average moments on all atoms (add + 2.0)
magmom = d[self.labels.index("mexp") - 1] + 2.0
m = [magmom / len(b)] * len(b)
# break spin symmetry between atoms no. 1 and 2
m[1] = m[1] + m[2]
m[2] = -m[2]
b.set_initial_magnetic_moments(m)
if 0:
from ase.visualize import view
view(b)
return b
def generate_vaspinput(element="Li", a_ref=3.05):
# HCP
a = a_ref
c = 1.62 * a_ref
atoms = crystal(element, [(1.0 / 3.0, 2.0 / 3.0, 3.0 / 4.0)], spacegroup=194, cellpar=[a, a, c, 90, 90, 120])
if not os.path.exists("HCP"):
os.mkdir("HCP")
os.chdir("HCP")
write_vasp("POSCAR", atoms, label="HCP", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# FCC structure
a = a_ref * 1.42
atoms = crystal(element, [(0, 0, 0)], spacegroup=225, cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("FCC"):
os.mkdir("FCC")
os.chdir("FCC")
write_vasp("POSCAR", atoms, label="FCC", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# BCC structure
a = a_ref * 1.13
atoms = crystal(element, [(0, 0, 0)], spacegroup=229, cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("BCC"):
os.mkdir("BCC")
os.chdir("BCC")
write_vasp("POSCAR", atoms, label="BCC", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# SCC structure
a = a_ref * 0.90
atoms = crystal(element, [(0, 0, 0)], spacegroup=221, cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("SCC"):
os.mkdir("SCC")
os.chdir("SCC")
write_vasp("POSCAR", atoms, label="SCC", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# Diamond
a = a_ref * 1.93
atoms = crystal(element, [(0, 0, 0)], spacegroup=227, cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("DIAMOND"):
os.mkdir("DIAMOND")
os.chdir("DIAMOND")
write_vasp("POSCAR", atoms, label="DIAMOND", direct=True, long_format=True, vasp5=True)
os.chdir("..")
def lmp_structure(self):
if self.type=='rutile':
a = 4.584
c = 2.953
atoms =crystal(self.elements, basis=[(0, 0, 0), (0.3, 0.3, 0.0)],spacegroup='P4_2/mnm', cellpar=[a, a, c, 90, 90, 90])
elif self.type=='anatase':
a=3.7842
c=9.5146
atoms=crystal(self.elements, basis=[(0, 0, 0), (0 ,0 ,.2081)],spacegroup=141, cellpar=[a, a, c, 90, 90, 90])
else:
raise Exception('unkown TiO2 type!')
return atoms
def generate_vaspinput(ele1="Ca", ele2="O", a_ref=3.05):
# B1 NaCl
a = a_ref
atoms = crystal([ele1, ele2], [(0, 0, 0), (0.5, 0.5, 0.5)], spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("B1"):
os.mkdir("B1")
os.chdir("B1")
write_vasp("POSCAR", atoms, label="B1", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# B2 CsCl
a = a_ref * 0.6975
atoms = crystal([ele1, ele2], [(0, 0, 0), (0.5, 0.5, 0.5)], spacegroup=221,
cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("B2"):
os.mkdir("B2")
os.chdir("B2")
write_vasp("POSCAR", atoms, label="B2", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# B3 ZnS Sphalerite (F43m)
a = a_ref * 1.086
atoms = crystal([ele1, ele2], [(0, 0, 0), (0.25, 0.25, 0.25)], spacegroup=216,
cellpar=[a, a, a, 90, 90, 90])
if not os.path.exists("B3"):
os.mkdir("B3")
os.chdir("B3")
write_vasp("POSCAR", atoms, label="B3", direct=True, long_format=True, vasp5=True)
os.chdir("..")
# B4 ZnS Wurtzite (p6mc)
a = a_ref * 0.8272
c = a * 1.635
atoms = crystal([ele1, ele2], [(0.3333, 0.6667, 0), (0.3333, 0.6667, 0.3748)], spacegroup=186,
cellpar=[a, a, c, 90, 90, 120])
if not os.path.exists("B4"):
os.mkdir("B4")
os.chdir("B4")
write_vasp("POSCAR", atoms, label="B4", direct=True, long_format=True, vasp5=True)
os.chdir("..")
def cubic_perovskite(species,cell_par=[6,6,6,90,90,90],repetitions=[1,1,1]):
system = crystal((species),
basis=[(0,0,0), (0.5, 0.5, 0.5), (0.5, 0.5, 0)],
spacegroup=221, size = repetitions, cellpar=cell_par)
sites_list = []
oxidation_states = [[2]] + [[4]] + [[-2]]*3
for site in zip(system.get_scaled_positions(),oxidation_states):
sites_list.append(Site(site[0],site[1]))
return Lattice(sites_list, oxidation_states), system
def halfheusler(symbols, a):
# See page 21 of http://d-nb.info/1021065781/34
# The inequivalent “stuffing atom” (Wycoff position 4c) third.
b = crystal(symbols=symbols,
basis=[(0., 0., 0.),
(1./2, 1./2, 1./2),
(1./4, 1./4, 1./4)],
spacegroup=216,
cellpar=[a, a, a, 90, 90, 90],
primitive_cell=False)
return b.copy()
def wurtzite(species, cell_par=[2,2,6,90,90,120],repetitions=[1,1,1]):
system = crystal((species),
basis=[(2./3.,1./3.,0),(2./3.,1./3.,5./8.)],
spacegroup=186, size = repetitions, cellpar=[3, 3, 6, 90,90,120])
sites_list = []
oxidation_states = [[1],[2],[3],[4]] + [[-1],[-2],[-3],[-4]]
for site in zip(system.get_scaled_positions(),oxidation_states):
sites_list.append(Site(site[0],site[1]))
return Lattice(sites_list, oxidation_states), system
from ase.lattice.spacegroup import crystal
a = 4.05
al = crystal('Al', [(0,0,0)], spacegroup=225, cellpar=[a, a, a, 90, 90, 90])
def banner(msg):
print()
print(60*'=')
print(max(0,(60-len(msg))//2-1)*' ',msg)
print(60*'=')
def secban(msg):
print()
print(max(0,(60-len(msg))//2-1)*' ',msg)
print(60*'-')
banner('Structure optimization on MgO')
a = 4.291
MgO = crystal(['Mg', 'O'], [(0, 0, 0), (0.5, 0.5, 0.5)], spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
##################################
# Provide your own calculator here
##################################
calc=ClusterVasp(nodes=1,ppn=8)
# The calculator must be runnable in an isolated directory
# Without disturbing other running instances of the same calculator
# They are run in separate processes (not threads!)
MgO.set_calculator(calc)
calc.set(prec = 'Accurate', xc = 'PBE', lreal = False, isif=2, nsw=20, ibrion=2, kpts=[1,1,1])
print("Residual pressure: %.3f GPa" % (MgO.get_pressure()/GPa))
calc.clean()
def make_eta_c4(names,sizes):
#work out the expansion factor
#dist0 = furthest_dummy(mol0)
#dist1 = furthest_dummy(mol1)
factor = sum(sizes) #dist0 + dist1
factor = factor * 2
#factor = 3.0
print "factor = " , factor
a = 3.1018 * factor
b = 0.4373 * factor
#b = 0.5466 * factor #RCSR value, incorrect?
# C -> triangles, N => midpoints
#eta_c4 = crystal(['C', 'N' , 'N'], [(0.4069, 0.8138, 0.0), (0.5, 0.0, 0.0), (0.2965, 0.7035, 0.6667)], spacegroup=180, #P6(2)22 #RCSR incorrect?
eta_c4 = crystal(['C', 'N' , 'F'], [(0.4069, 0.8138, 0.0), (0.5, 0.0, 0.0), (0.7035, 0.4070, 0.5)], spacegroup=180, #P6(2)22
cellpar=[a, a, b, 90, 90, 120])
#write('test.xyz',eta_c4)
write('test.cif',eta_c4)
eps = 0.9
model_molecule={}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
cov_rad=[]
for atom in eta_c4:
#cov_rad.append(covalent_radii[atom.number])
cov_rad.append(factor / 4)
print cov_rad
nlist = NeighborList(cov_rad,skin=3.0,self_interaction=False,bothways=True)
nlist.build(eta_c4)
#To sort out tags, we need to label each bond
nbond = 1
bond_matrix = np.zeros( (len(eta_c4),len(eta_c4)) )
pbc_bond_matrix = np.zeros( (len(eta_c4),len(eta_c4)) )
bond_dict = {}
#Something funky, missing bonds,
#for atom in eta_c4:
# print "---------------------Atom",atom.index,"--------------------"
# for ind in range(len(eta_c4)):
# print atom.index, ind, eta_c4.get_distance(atom.index,ind,mic=True), eta_c4.get_distance(atom.index,ind)
for atom in eta_c4:
print "---------------------"
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
print atom.index, index, atom.symbol, eta_c4[index].symbol, offset, eta_c4.get_distance(atom.index,index,mic=True)
if atom.index <= index:# and eta_c4[index].symbol != 'F': #F require special treatment
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
#Now we need to find the same bond the other direction to get the offsets right
indices2,offsets2 = nlist.get_neighbors(index)
for i2,o2 in zip(indices2,offsets2):
if i2 == atom.index:
#print "sum of offsets = ", offset, o2, sum(offset + o2)
if sum(offset + o2) == 0: #same bond
this_bond = [index, atom.index]
for o in o2:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
nbond +=1
print "Bond dict:"
print nbond
for k,v in bond_dict.items():
print k,v
print "End Bond dict:"
#Now we want to delete C-F bonds that are not of length factor/2
for k,v in bond_dict.items():
i1,i2,o1,o2,o3 = k
position1 = eta_c4.positions[i1]
position2 = eta_c4.positions[i2]
position2_mic = eta_c4.positions[i2] + np.dot([o1,o2,o3], eta_c4.get_cell())
this_dist = np.linalg.norm(position1 - position2)
this_dist_mic = np.linalg.norm(position1 - position2_mic)
print i1,i2, this_dist, this_dist_mic, (this_dist - factor/2), this_dist_mic - factor/2
if abs(this_dist - factor/2) > eps and all(o == 0 for o in [o1,o2,o3]):
print "deleting", k
del bond_dict[k]
elif abs(this_dist_mic - factor/2) > eps and any(o != 0 for o in [o1,o2,o3]) :
print "deleting", k
del bond_dict[k]
#print "New Bond dict:"
#print len(bond_dict)
#for k,v in sorted(bond_dict.items()):
# i1,i2,o1,o2,o3 = k
# position1 = eta_c4.positions[i1]
# position2 = eta_c4.positions[i2]
# position2_mic = eta_c4.positions[i2] + np.dot([o1,o2,o3], eta_c4.get_cell())
# this_dist = np.linalg.norm(position1 - position2)
# this_dist_mic = np.linalg.norm(position1 - position2_mic)
# print k,v, this_dist,this_dist_mic
#print "End New Bond dict:"
#Start with C (triangles)
for atom in eta_c4:
if atom.symbol == 'C':
print'======================================='
print 'C Atom ',atom.index
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'F'
indices, offsets = nlist.get_neighbors(atom.index)
#Just checking the symbols here
print indices
print offsets
symbols = ([eta_c4[index].symbol for index in indices])
symbol_string = ''.join(sorted([eta_c4[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index,offset in zip(indices,offsets):
print atom.index, index, offset
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#print bond_dict[bond]
print abs(eta_c4.get_distance(atom.index,index,mic=True)), abs(eta_c4.get_distance(atom.index,index,mic=True) - factor)
#if eta_c4[index].symbol == 'N' and abs(eta_c4.get_distance(atom.index,index,mic=True) - factor) < eps: #necessary check, because some atoms are closer than unit distance:
if bond in bond_dict:
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj].positions[-1] = eta_c4.positions[index] + np.dot(offset, eta_c4.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[-1] = eta_c4.positions[index] + np.dot(offset, eta_c4.get_cell())
n_centers = n_obj
#
#
##Now we do the N (edges)
for atom in eta_c4:
if atom.symbol == 'N' or atom.symbol =='F':
#print'======================================='
#print 'N Atom ',atom.index, " finding edges"
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
print index, offset, eta_c4[index].symbol
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#if not bond_dict.has_key(bond):
#Then
#if eta_c4[index].symbol == 'C' and abs(eta_c4.get_distance(atom.index,index,mic=True) - factor) < eps: #necessary check, because some atoms are closer than unit distance:
if bond in bond_dict:
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj].positions[-1] = eta_c4.positions[index] + np.dot(offset, eta_c4.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[-1] = eta_c4.positions[index] + np.dot(offset, eta_c4.get_cell())
#
#
#
f = open('eta_c4.model','w')
g = open('control-mofgen.txt','w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' %('Number of objects =',n_obj+1))
f.write('%-20s\n' %('build = systre'))
f.write('%5s\n' %('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(eta_c4.get_cell()[0][0],
eta_c4.get_cell()[0][1],
eta_c4.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(eta_c4.get_cell()[1][0],
eta_c4.get_cell()[1][1],
eta_c4.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(eta_c4.get_cell()[2][0],
eta_c4.get_cell()[2][1],
eta_c4.get_cell()[2][2]))
g.write('%-20s\n' %('model = eta_c4'))
#Now write stuff
for obj in xrange(n_centers+1):
f.write('\n%-8s %-3d\n' %('Center: ', obj+1))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = triangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('center =', names[0]))
for obj in xrange(n_centers+1,n_obj+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = linear'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('linker =', names[1]))
"""Test the ase.utils.geometry module"""
import numpy as np
from ase.lattice.spacegroup import crystal
from ase.utils.geometry import get_layers, cut, stack
from ase.atoms import Atoms
np.set_printoptions(suppress=True)
al = crystal("Al", [(0, 0, 0)], spacegroup=225, cellpar=4.05)
# Cut out slab of 5 Al(001) layers
al001 = cut(al, nlayers=5)
correct_pos = np.array(
[
[0.0, 0.0, 0.0],
[0.0, 0.5, 0.2],
[0.5, 0.0, 0.2],
[0.5, 0.5, 0.0],
[0.0, 0.0, 0.4],
[0.0, 0.5, 0.6],
[0.5, 0.0, 0.6],
[0.5, 0.5, 0.4],
[0.0, 0.0, 0.8],
[0.5, 0.5, 0.8],
]
)
assert np.allclose(correct_pos, al001.get_scaled_positions())
#Test 2 - Test in all 3 dimensions
ssize=[2,2,2]
fsize=[4,4,4]
psize=[1,1,1]
defectstructure = BCC('Fe', size = ssize)
primordialstructure = BCC('Fe', size = psize)
f = BCC('Fe', size = fsize)
write('POSCAR_defect2',defectstructure)
write('POSCAR_prim2',primordialstructure)
final = finite_size_scale('POSCAR_defect2', ssize, 'POSCAR_prim2', fsize, psize)
write(fil,f,'xyz')
write(fil,final,'xyz')
fil.flush()
#Test 3 - Test for not cubic lattice
from ase.lattice.spacegroup import crystal
a = 3.21
c = 5.21
mg = crystal('Mg', [(1./3., 2./3., 3./4.)], spacegroup=194,cellpar=[a, a, c, 90, 90, 120])
defectstructure = mg.repeat(ssize)
primordialstructure = mg.repeat(psize)
f = mg.repeat(fsize)
write('POSCAR_defect3',defectstructure)
write('POSCAR_prim3',primordialstructure)
final = finite_size_scale('POSCAR_defect3', ssize, 'POSCAR_prim3', fsize, psize)
write(fil,f,'xyz')
write(fil,final,'xyz')
fil.flush()
fil.close()
import numpy as np
from ase.lattice.spacegroup import crystal
# A diamond unit cell
diamond = crystal('C', [(0,0,0)], spacegroup=227,
cellpar=[3.57, 3.57, 3.57, 90, 90, 90])
assert len(diamond) == 8
correct_pos = np.array([[ 0. , 0. , 0. ],
[ 0. , 0.5 , 0.5 ],
[ 0.5 , 0.5 , 0. ],
[ 0.5 , 0. , 0.5 ],
[ 0.75, 0.25, 0.75],
[ 0.25, 0.25, 0.25],
[ 0.25, 0.75, 0.75],
[ 0.75, 0.75, 0.25]])
assert np.allclose(diamond.get_scaled_positions(), correct_pos)
# A CoSb3 skutterudite unit cell containing 32 atoms
skutterudite = crystal(('Co', 'Sb'),
basis=[(0.25,0.25,0.25), (0.0, 0.335, 0.158)],
spacegroup=204, cellpar=[9.04, 9.04, 9.04, 90, 90, 90])
assert len(skutterudite) == 32
correct_pos = np.array([[ 0.25 , 0.25 , 0.25 ],
[ 0.75 , 0.75 , 0.25 ],
def make_mil53(names,sizes):
#work out the expansion factor
factor = sizes[1] #linker is the only thing that matters #sum(sizes)
#print sizes[0]
a = 6.6085 #We'll form the bondlist and then enlarge the cell.
b = 16.0 #16.675
c = 12.0 #12.813
#These cell dimensions are rigged to a linker length of 5 (circa size of benzene)
# Al -> centre of mil53, N -> centre of rectangle linker , C -> dummies
mil53 = crystal(['Al', 'N', 'C'], [(0.25, 0.25, 0.25), (0.5, 0.0, 0.5), (0.5, 0.1292, 0.383 )], spacegroup=74, #Imma
cellpar=[a, b, c, 90, 90, 90])
write('test.xyz',mil53)
eps = 0.05
model_molecule={}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
#First detect global bonding
cov_rad=[]
for atom in mil53:
if atom.symbol == 'Al':
cov_rad.append(covalent_radii[atom.number]*2) #Rigged to suck in C, but not N
elif atom.symbol == 'N':
cov_rad.append(covalent_radii[atom.number]*3) #Rigged to suck in C, but not Al
else:
cov_rad.append(covalent_radii[atom.number])
#print cov_rad
nlist = NeighborList(cov_rad,skin=0.1,self_interaction=False,bothways=True)
nlist.build(mil53)
#Now we exapnd the cell. The factor given is half the hypotenuse of a right triangle with angle 35 deg
print "factor = " , factor
print b,c
a = 2* sizes[0]
b = b + (2*factor * sin(35*pi/180.0))
c = c + (2*factor * cos(35*pi/180.0))
print b,c
# Al -> centre of mil53, N -> centre of rectangle linker , C -> dummies
mil53 = crystal(['Al', 'N', 'C'], [(0.25, 0.25, 0.25), (0.5, 0.0, 0.5), (0.5, 0.1292, 0.383 )], spacegroup=74, #Imma
cellpar=[a, b, c, 90, 90, 90]) #a (height) is fixed
#To sort out tags, we need to label each bond
nbond = 1
#Now in this case, the C atoms directly represent our dummy atoms, so we number them
for atom in mil53:
if atom.symbol == 'C':
atom.tag = nbond
nbond += 1
#Al also need to be tagged to each other
for atom in mil53:
if atom.symbol == 'Al':
indices, offsets = nlist.get_neighbors(atom.index)
#symbol_string = ''.join(sorted([mil53[index].symbol for index in indices]))
#print symbol_string
for index,offset in zip(indices,offsets):
if mil53[index].symbol == 'Al' and all(o == 0 for o in offset) and index > atom.index: #interesting because it the same bond is both internal and pbc
#print "atom ", atom.index, " and atom ",index, " are bonded, non-pbc ", nbond
atom.tag = nbond
mil53[index].tag = nbond
nbond += 1
#Now we loop over the N, just to find which carbons go over PBC
for atom in mil53:
if atom.symbol == 'N':
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets): #Should only be C
if mil53[index].symbol == 'C':
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
mil53[index].tag = -mil53[index].tag
#print mil53.get_tags()
used_carbon = []
#Now we build the model
#Start with Al
for atom in mil53:
if atom.symbol == 'Al':
#print'======================================='
#print 'Al Atom ',atom.index
indices, offsets = nlist.get_neighbors(atom.index)
C_count = 0
for index,offset in zip(indices,offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(o == 0 for o in offset): # and mil53[index].tag not in model_molecule[n_obj].get_tags():
C_count += 1
#print "Al atom, ", atom.index, "has c-count in this cell", C_count
if C_count == 2:
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
for index,offset in zip(indices,offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(o == 0 for o in offset): # and mil53[index].tag not in model_molecule[n_obj].get_tags():
model_molecule[n_obj] += mil53[index]
model_molecule[n_obj][-1].tag = mil53[index].tag
model_molecule[n_obj].positions[-1] = mil53.positions[index] + np.dot(offset, mil53.get_cell())
used_carbon.append(index)
#We need to put the other Al as an anchor
for index,offset in zip(indices,offsets):
if mil53[index].symbol =='Al' and all(o == 0 for o in offset):
model_molecule[n_obj] += mil53[index]
#model_molecule[n_obj][-1].tag = None #No tag
model_molecule[n_obj].positions[-1] = mil53.positions[index] + np.dot(offset, mil53.get_cell())
#That gives us two Al centres, now the other two
#These are the two that have 4 in-cell C
for atom in mil53:
if atom.symbol == 'Al':
#print'======================================='
#print 'Al Atom ',atom.index
indices, offsets = nlist.get_neighbors(atom.index)
C_count = 0
for index,offset in zip(indices,offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(o == 0 for o in offset): # and mil53[index].tag not in model_molecule[n_obj].get_tags():
C_count += 1
#print "Al atom, ", atom.index, "has c-count in this cell", C_count
if C_count == 4:
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
for index,offset in zip(indices,offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(o == 0 for o in offset) and index not in used_carbon:
model_molecule[n_obj] += mil53[index]
model_molecule[n_obj][-1].tag = mil53[index].tag
model_molecule[n_obj].positions[-1] = mil53.positions[index] + np.dot(offset, mil53.get_cell())
#We need to put the other Al as an anchor
for index,offset in zip(indices,offsets):
if mil53[index].symbol =='Al' and any(o != 0 for o in offset):
model_molecule[n_obj] += mil53[index]
#model_molecule[n_obj][-1].tag = None #No tag
model_molecule[n_obj].positions[-1] = mil53.positions[index] + np.dot(offset, mil53.get_cell())
# #We need to interrogate our C further as two of them belong to both Al in the same cell
# C_indices,C_offsets = nlist.get_neighbors(index)
# symbol_string = ''.join(sorted([mil53[index].symbol for index in C_indices]))
# print symbol_string
#
# model_molecule[n_obj] += mil53[index]
# model_molecule[n_obj][-1].tag = mil53[index].tag
# model_molecule[n_obj].positions[-1] = mil53.positions[index] + np.dot(offset, mil53.get_cell())
n_centers = n_obj
#
#
##Now we do the N (linear)
for atom in mil53:
if atom.symbol == 'N':
#print'======================================='
#print 'N Atom ',atom.index, " finding squares1"
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets): #Should only be C
if mil53[index].symbol == 'C':
model_molecule[n_obj] += mil53[index]
model_molecule[n_obj][-1].tag = mil53[index].tag
model_molecule[n_obj].positions[-1] = mil53.positions[index] + np.dot(offset, mil53.get_cell())
#
#
#
f = open('mil53.model','w')
g = open('control-mofgen.txt','w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
test_mol = Atoms()
for obj in model_molecule:
test_mol += model_molecule[obj]
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' %('Number of objects =',n_obj+1))
f.write('%-20s\n' %('build = systre'))
f.write('%-13s\n' %('ExtraDummies'))
f.write('%5s\n' %('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(mil53.get_cell()[0][0],
mil53.get_cell()[0][1],
mil53.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(mil53.get_cell()[1][0],
mil53.get_cell()[1][1],
mil53.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(mil53.get_cell()[2][0],
mil53.get_cell()[2][1],
mil53.get_cell()[2][2]))
g.write('%-20s\n' %('model = mil53'))
# Print the centers and linkers
for obj in xrange(n_centers+1):
f.write('\n%-8s %-3d\n' %('Center: ', obj+1))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = mil53'))
#process positions to make it a bit more ideal
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(atom.index,0,2.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.symbol == 'C': #can't use tags as a marker here, because we've given a tag to 'Q' as well
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
elif atom.symbol == 'Al':
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('Q', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('center =', names[0]))
for obj in xrange(n_centers+1,n_obj+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = linear'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('linker =', names[1]))
#
#
test_mol = Atoms()
for obj in model_molecule:
test_mol += model_molecule[obj]
write('test_model2.xyz',test_mol)
def tags2atoms(tags, **kwargs):
"""Returns an Atoms object from a cif tags dictionary."""
a = tags['_cell_length_a']
b = tags['_cell_length_b']
c = tags['_cell_length_c']
alpha = tags['_cell_angle_alpha']
beta = tags['_cell_angle_beta']
gamma = tags['_cell_angle_gamma']
scaled_positions = np.array([
tags['_atom_site_fract_x'], tags['_atom_site_fract_y'],
tags['_atom_site_fract_z']
]).T
symbols = []
if '_atom_site_type_symbol' in tags:
labels = tags['_atom_site_type_symbol']
else:
labels = tags['_atom_site_label']
for s in labels:
# Strip off additional labeling on chemical symbols
m = re.search(r'([A-Z][a-z]?)', s)
symbol = m.group(0)
symbols.append(symbol)
# Symmetry specification, see
# http://www.iucr.org/resources/cif/dictionaries/cif_sym for a
# complete list of official keys. In addition we also try to
# support some commonly used depricated notations
no = None
if '_space_group.IT_number' in tags:
no = tags['_space_group.IT_number']
elif '_symmetry_int_tables_number' in tags:
no = tags['_symmetry_int_tables_number']
symbolHM = None
if '_space_group.Patterson_name_H-M' in tags:
symbolHM = tags['_space_group.Patterson_name_H-M']
elif '_symmetry_space_group_name_H-M' in tags:
symbolsHM = tags['_symmetry_space_group_name_H-M']
sitesym = None
if '_space_group_symop.operation_xyz' in tags:
sitesym = tags['_space_group_symop.operation_xyz']
elif '_symmetry_equiv_pos_as_xyz' in tags:
sitesym = tags['_symmetry_equiv_pos_as_xyz']
spacegroup = 1
if sitesym is not None:
spacegroup = spacegroup_from_data(no=no,
symbol=symbolHM,
sitesym=sitesym)
elif no is not None:
spacegroup = no
elif symbolHM is not None:
spacegroup = symbolHM
else:
spacegroup = 1
atoms = crystal(symbols,
basis=scaled_positions,
cellpar=[a, b, c, alpha, beta, gamma],
spacegroup=spacegroup,
**kwargs)
return atoms
def wait_for_results(systems):
for n, r in enumerate(systems):
print(n + 1, end='')
while not r.get_calculator().calc_finished():
print('.', end='')
sys.stdout.flush()
sleep(10)
print(end=' ')
sys.stdout.flush()
print()
a = 4
c = crystal('Si', [(0, 0, 0)], spacegroup=221, cellpar=[a, a, a, 90, 90, 90])
spglib.get_spacegroup(c)
block = False
calc = ClusterVasp(block=block)
calc.set(prec='Accurate',
xc='PBE',
lreal=False,
nsw=30,
ediff=1e-8,
ibrion=2,
kpts=[3, 3, 3])
calc.set(isif=3)
#!/usr/bin/env python
from ase import io
from ase.lattice import bulk
from ase.lattice.surface import surface
from ase.io.trajectory import Trajectory
from ase.lattice.spacegroup import crystal
from ase.optimize import QuasiNewton
import numpy as np
from ase.io.trajectory import PickleTrajectory
from ase.build import cut
#import cut
a = 8.171
Bulk = crystal(('Mg', 'Al', 'O'),
basis=[(0, 0, 0), (0.625, 0.625, 0.625), (0.375, 0.375, 0.375)],
spacegroup=227,
cellpar=[a, a, a, 90, 90, 90])
Bulk.set_initial_magnetic_moments([0.0 for atom in Bulk])
#atoms = Bulk.repeat((2,2,2))
#atoms.rattle(stdev=0.001, seed=42)
io.write('1_1_1.traj', Bulk)
#al111 = surface(Bulk, (1,1,1),4, vacuum = 7.5)
#al111 = cut(Bulk,(1,0,0),(0,1,0),(0,0,1),nlayers=3)
#io.write('surface_111.traj',al111)
from ase.lattice.spacegroup import crystal
# FCC aluminum
a = 4.05
al = crystal('Al', [(0, 0, 0)], spacegroup=225, cellpar=[a, a, a, 90, 90, 90])
print(al)
def make_sqp_B2(names, sizes):
#ax110628-sr (ax110826.cif) personal communication from Prof. Dr. Jens Beckmann
a = 10.9770
b = 18.569
c = 21.098
alpha = 79.640
beta = 76.060
gamma = 85.670
# P => central Si
# Si => peripheral Si, actually using carbons from the original cif
# N => centre of 4 Si/O
# C => peripheral Si
sqp_B2 = crystal(
['P', 'Si', 'Si', 'Si', 'Si', 'N', 'C', 'C', 'C', 'C'],
[(0.65363, 0.82095, 0.14843), (0.4953, 0.8025, 0.2043),
(0.7693, 0.7437, 0.1638), (0.7189, 0.9026, 0.1681),
(0.6395, 0.8366, 0.0605), (0.240400, 0.263825, 0.376473),
(-0.26884, 0.7000, 0.46936), (1.37428, 0.43072, 0.28200),
(0.99881, 1.28479, 0.29492), (0.66767, 0.91355, -0.37629)],
spacegroup=2, #P-1
cellpar=[a, b, c, alpha, beta, gamma])
write('test.xyz', sqp_B2)
write('test.cif', sqp_B2)
eps = 0.10
model_molecule = {}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
# First detect global bonding
# N-C distance is 3.5A
cov_rad = []
for atom in sqp_B2:
if atom.symbol == 'P':
cov_rad.append(covalent_radii[atom.number])
elif atom.symbol == 'Si':
cov_rad.append(covalent_radii[atom.number])
elif atom.symbol == 'N':
cov_rad.append(2.0)
elif atom.symbol == 'C':
cov_rad.append(2.0)
nlist = NeighborList(cov_rad,
skin=0.01,
self_interaction=False,
bothways=True)
nlist.build(sqp_B2)
#To sort out tags, we need to label each bond, we get a bunch of extra bonds here that we need to filter out
bond_matrix = np.zeros((len(sqp_B2), len(sqp_B2)), dtype=bool)
for atom in sqp_B2:
indices, offsets = nlist.get_neighbors(atom.index)
if atom.symbol == 'P': #Here we go, suck in all Si
for index, offset in zip(indices, offsets):
if sqp_B2[
index].symbol == 'Si': # and sqp_B2.get_distance(atom.index,index,mic=True) >10.0:
print "Atom ", atom.index, atom.symbol, " bonded to atom ", index, sqp_B2[
index].symbol, " distance = ", sqp_B2.get_distance(
atom.index, index, mic=True), "offset = ", offset
bond_matrix[index, atom.index] = True
bond_matrix[atom.index, index] = True
if atom.symbol == 'N': #Here we go, suck in all Si
for index, offset in zip(indices, offsets):
if sqp_B2[
index].symbol == 'C': #and sqp_B2.get_distance(atom.index,index,mic=True) >10.0:
print "Atom ", atom.index, atom.symbol, " bonded to atom ", index, sqp_B2[
index].symbol, " distance = ", sqp_B2.get_distance(
atom.index, index, mic=True), "offset = ", offset
bond_matrix[index, atom.index] = True
bond_matrix[atom.index, index] = True
#Now we have a dirty trick, expand all the P-Si4 tetrahedra and find Si-C bonds
for atom in sqp_B2:
if atom.symbol == 'P':
print '======================================='
print 'P Atom ', atom.index
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
#for i,o in zip(indices, offsets):
# print i,o
for index, offset in zip(indices, offsets):
sqp_B2.set_distance(index, atom.index, 10.0, fix=1)
write('test2.xyz', sqp_B2)
write('test2.cif', sqp_B2)
nlist_CSi = NeighborList(cov_rad,
skin=0.01,
self_interaction=False,
bothways=True)
nlist_CSi.build(sqp_B2)
print "Here"
nbond = 1
for atom in sqp_B2:
indices, offsets = nlist_CSi.get_neighbors(atom.index)
if atom.symbol == 'C': #Here we go, suck in all Si
for index, offset in zip(indices, offsets):
print "Atom ", atom.index, atom.symbol, " bonded to atom ", index, sqp_B2[
index].symbol, " distance = ", sqp_B2.get_distance(
atom.index, index, mic=True), "offset = ", offset
if sqp_B2[
index].symbol == 'Si': # and sqp_B2.get_distance(atom.index,index,mic=True) >10.0:
print "Adding bond"
bond_matrix[index, atom.index] = True
bond_matrix[atom.index, index] = True
atom.tag = -nbond
sqp_B2[index].tag = -nbond
nbond += 1
tags = sqp_B2.get_tags()
print tags
#Now build scaled model
#base size
factor = sum(sizes) #(sizes[0] + sizes[2])/2.0
print "factor = ", factor
orig_a = a
scale = factor / orig_a
b = b * scale
c = c * scale
# P => central Si
# Si => peripheral Si, actually using carbons from the original cif
# N => centre of 4 Si/O
# C => peripheral Si
sqp_B2 = crystal(
['P', 'Si', 'Si', 'Si', 'Si', 'N', 'C', 'C', 'C', 'C'],
[(0.65363, 0.82095, 0.14843), (0.4953, 0.8025, 0.2043),
(0.7693, 0.7437, 0.1638), (0.7189, 0.9026, 0.1681),
(0.6395, 0.8366, 0.0605), (0.240400, 0.263825, 0.376473),
(-0.26884, 0.7000, 0.46936), (1.37428, 0.43072, 0.28200),
(0.99881, 1.28479, 0.29492), (0.66767, 0.91355, -0.37629)],
spacegroup=2, #P-1
cellpar=[a, b, c, alpha, beta, gamma])
sqp_B2.set_tags(tags)
n_obj = -1 #re-initialise to -1 such that it can be indexed at start of add
#Now we start assembling the model
#We have only tetrahedra
for atom in sqp_B2:
if atom.symbol == 'P':
print '======================================='
print 'P Atom ', atom.index
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'P'
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
symbols = ([sqp_B2[index].symbol for index in indices])
symbol_string = ''.join(
sorted([sqp_B2[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index, offset in zip(indices, offsets):
if bond_matrix[index, atom.index]:
model_molecule[n_obj] += sqp_B2[index]
model_molecule[n_obj].positions[
-1] = sqp_B2.positions[index] + np.dot(
offset, sqp_B2.get_cell())
model_molecule[n_obj][-1].tag = sqp_B2[index].tag
print sqp_B2[index].symbol, sqp_B2[index].position, sqp_B2[
index].tag
print sqp_B2[index].index, sqp_B2[index].symbol, sqp_B2[
index].position, sqp_B2[index].tag
n_centers = n_obj
# H-bond "square pyramids" are actually tetrahedra wrt centre of mass
for atom in sqp_B2:
if atom.symbol == 'N':
print '======================================='
print 'N Atom ', atom.index
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'N'
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
symbols = ([sqp_B2[index].symbol for index in indices])
symbol_string = ''.join(
sorted([sqp_B2[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index, offset in zip(indices, offsets):
if bond_matrix[index, atom.index]:
model_molecule[n_obj] += sqp_B2[index]
model_molecule[n_obj].positions[
-1] = sqp_B2.positions[index] + np.dot(
offset, sqp_B2.get_cell())
model_molecule[n_obj][-1].tag = sqp_B2[index].tag
print sqp_B2[index].symbol, sqp_B2[index].position, sqp_B2[
index].tag
print sqp_B2[index].index, sqp_B2[index].symbol, sqp_B2[
index].position, sqp_B2[index].tag
f = open('sqp_B2.model', 'w')
g = open('control-mofgen.txt', 'w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' % ('Number of objects =', n_obj + 1))
f.write('%-20s\n' % ('build = systre'))
f.write('%5s\n' % ('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(sqp_B2.get_cell()[0][0], sqp_B2.get_cell()[0][1],
sqp_B2.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(sqp_B2.get_cell()[1][0], sqp_B2.get_cell()[1][1],
sqp_B2.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(sqp_B2.get_cell()[2][0], sqp_B2.get_cell()[2][1],
sqp_B2.get_cell()[2][2]))
g.write('%-20s\n' % ('model = sqp_B2'))
#
for obj in xrange(n_centers + 1):
f.write('\n%-8s %-3d\n' % ('Center: ', obj + 1))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = tetrahedral'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('center =', names[0]))
for obj in xrange(n_centers + 1, n_obj + 1):
f.write('\n%-8s %-3d\n' % ('Linker: ', obj - n_centers))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = tetrahedral'))
#process positions to make it a bit more ideal
#this_dist = model_molecule[obj].get_distance(0,1)
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(0,atom.index,this_dist+1.0,fix=0)
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(0,atom.index,1.0,fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('linker =', names[1]))
#
#
test_mol = Atoms()
for obj in model_molecule:
#for obj in xrange(n_centers+1):#,n_obj+1): #triangles only
test_mol += model_molecule[obj]
test_mol.set_cell(sqp_B2.get_cell())
test_mol.set_pbc(sqp_B2.get_pbc())
write('test_model2.xyz', test_mol)
write('test_model2.cif', test_mol)
#!/Users/michalplucinski/Virtualenvs/ase-3.6.0.2515/bin/python
from ase.lattice.spacegroup import crystal
a = 5.431
diamond = crystal('C', [(0,0,0)], spacegroup=227, cellpar=[a, a, a, 90, 90, 90])
print diamond.positions
def make_sqp_B2(names,sizes):
#ax110628-sr (ax110826.cif) personal communication from Prof. Dr. Jens Beckmann
a = 10.9770
b = 18.569
c = 21.098
alpha = 79.640
beta = 76.060
gamma = 85.670
# P => central Si
# Si => peripheral Si, actually using carbons from the original cif
# N => centre of 4 Si/O
# C => peripheral Si
sqp_B2 = crystal(['P', 'Si', 'Si', 'Si', 'Si', 'N', 'C', 'C', 'C', 'C'],
[(0.65363, 0.82095, 0.14843), (0.4953, 0.8025, 0.2043), (0.7693, 0.7437, 0.1638), (0.7189, 0.9026, 0.1681), (0.6395, 0.8366, 0.0605),
(0.240400, 0.263825, 0.376473), (-0.26884, 0.7000, 0.46936), (1.37428, 0.43072, 0.28200), (0.99881, 1.28479, 0.29492), (0.66767, 0.91355, -0.37629)],
spacegroup=2, #P-1
cellpar=[a, b, c, alpha, beta, gamma])
write('test.xyz',sqp_B2)
write('test.cif',sqp_B2)
eps = 0.10
model_molecule={}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
# First detect global bonding
# N-C distance is 3.5A
cov_rad=[]
for atom in sqp_B2:
if atom.symbol == 'P':
cov_rad.append(covalent_radii[atom.number])
elif atom.symbol == 'Si':
cov_rad.append(covalent_radii[atom.number])
elif atom.symbol == 'N':
cov_rad.append(2.0)
elif atom.symbol == 'C':
cov_rad.append(2.0)
nlist = NeighborList(cov_rad,skin=0.01,self_interaction=False,bothways=True)
nlist.build(sqp_B2)
#To sort out tags, we need to label each bond, we get a bunch of extra bonds here that we need to filter out
bond_matrix = np.zeros( (len(sqp_B2),len(sqp_B2)) , dtype=bool)
for atom in sqp_B2:
indices, offsets = nlist.get_neighbors(atom.index)
if atom.symbol == 'P': #Here we go, suck in all Si
for index,offset in zip(indices,offsets):
if sqp_B2[index].symbol == 'Si':# and sqp_B2.get_distance(atom.index,index,mic=True) >10.0:
print "Atom ",atom.index, atom.symbol, " bonded to atom ", index, sqp_B2[index].symbol, " distance = ", sqp_B2.get_distance(atom.index,index,mic=True), "offset = ", offset
bond_matrix[index,atom.index] = True
bond_matrix[atom.index,index] = True
if atom.symbol == 'N': #Here we go, suck in all Si
for index,offset in zip(indices,offsets):
if sqp_B2[index].symbol == 'C': #and sqp_B2.get_distance(atom.index,index,mic=True) >10.0:
print "Atom ",atom.index, atom.symbol, " bonded to atom ", index, sqp_B2[index].symbol, " distance = ", sqp_B2.get_distance(atom.index,index,mic=True), "offset = ", offset
bond_matrix[index,atom.index] = True
bond_matrix[atom.index,index] = True
#Now we have a dirty trick, expand all the P-Si4 tetrahedra and find Si-C bonds
for atom in sqp_B2:
if atom.symbol == 'P':
print'======================================='
print 'P Atom ',atom.index
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
#for i,o in zip(indices, offsets):
# print i,o
for index,offset in zip(indices,offsets):
sqp_B2.set_distance(index,atom.index,10.0,fix=1)
write('test2.xyz',sqp_B2)
write('test2.cif',sqp_B2)
nlist_CSi = NeighborList(cov_rad,skin=0.01,self_interaction=False,bothways=True)
nlist_CSi.build(sqp_B2)
print "Here"
nbond = 1
for atom in sqp_B2:
indices, offsets = nlist_CSi.get_neighbors(atom.index)
if atom.symbol == 'C': #Here we go, suck in all Si
for index,offset in zip(indices,offsets):
print "Atom ",atom.index, atom.symbol, " bonded to atom ", index, sqp_B2[index].symbol, " distance = ", sqp_B2.get_distance(atom.index,index,mic=True), "offset = ", offset
if sqp_B2[index].symbol == 'Si':# and sqp_B2.get_distance(atom.index,index,mic=True) >10.0:
print "Adding bond"
bond_matrix[index,atom.index] = True
bond_matrix[atom.index,index] = True
atom.tag = -nbond
sqp_B2[index].tag = -nbond
nbond += 1
tags = sqp_B2.get_tags()
print tags
#Now build scaled model
#base size
factor = sum(sizes) #(sizes[0] + sizes[2])/2.0
print "factor = ",factor
orig_a = a
scale = factor/orig_a
b = b * scale
c = c * scale
# P => central Si
# Si => peripheral Si, actually using carbons from the original cif
# N => centre of 4 Si/O
# C => peripheral Si
sqp_B2 = crystal(['P', 'Si', 'Si', 'Si', 'Si', 'N', 'C', 'C', 'C', 'C'],
[(0.65363, 0.82095, 0.14843), (0.4953, 0.8025, 0.2043), (0.7693, 0.7437, 0.1638), (0.7189, 0.9026, 0.1681), (0.6395, 0.8366, 0.0605),
(0.240400, 0.263825, 0.376473), (-0.26884, 0.7000, 0.46936), (1.37428, 0.43072, 0.28200), (0.99881, 1.28479, 0.29492), (0.66767, 0.91355, -0.37629)],
spacegroup=2, #P-1
cellpar=[a, b, c, alpha, beta, gamma])
sqp_B2.set_tags(tags)
n_obj = -1 #re-initialise to -1 such that it can be indexed at start of add
#Now we start assembling the model
#We have only tetrahedra
for atom in sqp_B2:
if atom.symbol == 'P':
print'======================================='
print 'P Atom ',atom.index
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'P'
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
symbols = ([sqp_B2[index].symbol for index in indices])
symbol_string = ''.join(sorted([sqp_B2[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index,offset in zip(indices,offsets):
if bond_matrix[index,atom.index]:
model_molecule[n_obj] += sqp_B2[index]
model_molecule[n_obj].positions[-1] = sqp_B2.positions[index] + np.dot(offset, sqp_B2.get_cell())
model_molecule[n_obj][-1].tag = sqp_B2[index].tag
print sqp_B2[index].symbol, sqp_B2[index].position, sqp_B2[index].tag
print sqp_B2[index].index, sqp_B2[index].symbol, sqp_B2[index].position, sqp_B2[index].tag
n_centers = n_obj
# H-bond "square pyramids" are actually tetrahedra wrt centre of mass
for atom in sqp_B2:
if atom.symbol == 'N':
print'======================================='
print 'N Atom ',atom.index
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'N'
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
symbols = ([sqp_B2[index].symbol for index in indices])
symbol_string = ''.join(sorted([sqp_B2[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index,offset in zip(indices,offsets):
if bond_matrix[index,atom.index]:
model_molecule[n_obj] += sqp_B2[index]
model_molecule[n_obj].positions[-1] = sqp_B2.positions[index] + np.dot(offset, sqp_B2.get_cell())
model_molecule[n_obj][-1].tag = sqp_B2[index].tag
print sqp_B2[index].symbol, sqp_B2[index].position, sqp_B2[index].tag
print sqp_B2[index].index, sqp_B2[index].symbol, sqp_B2[index].position, sqp_B2[index].tag
f = open('sqp_B2.model','w')
g = open('control-mofgen.txt','w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' %('Number of objects =',n_obj+1))
f.write('%-20s\n' %('build = systre'))
f.write('%5s\n' %('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(sqp_B2.get_cell()[0][0],
sqp_B2.get_cell()[0][1],
sqp_B2.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(sqp_B2.get_cell()[1][0],
sqp_B2.get_cell()[1][1],
sqp_B2.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(sqp_B2.get_cell()[2][0],
sqp_B2.get_cell()[2][1],
sqp_B2.get_cell()[2][2]))
g.write('%-20s\n' %('model = sqp_B2'))
#
for obj in xrange(n_centers+1):
f.write('\n%-8s %-3d\n' %('Center: ', obj+1))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = tetrahedral'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('center =', names[0]))
for obj in xrange(n_centers+1,n_obj+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = tetrahedral'))
#process positions to make it a bit more ideal
#this_dist = model_molecule[obj].get_distance(0,1)
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(0,atom.index,this_dist+1.0,fix=0)
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(0,atom.index,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('linker =', names[1]))
#
#
test_mol = Atoms()
for obj in model_molecule:
#for obj in xrange(n_centers+1):#,n_obj+1): #triangles only
test_mol += model_molecule[obj]
test_mol.set_cell(sqp_B2.get_cell())
test_mol.set_pbc(sqp_B2.get_pbc())
write('test_model2.xyz',test_mol)
write('test_model2.cif',test_mol)
print(60 * '=')
print(max(0, (60 - len(msg)) // 2 - 1) * ' ', msg)
print(60 * '=')
def secban(msg):
print()
print(max(0, (60 - len(msg)) // 2 - 1) * ' ', msg)
print(60 * '-')
banner('Structure optimization on MgO')
a = 4.291
MgO = crystal(['Mg', 'O'], [(0, 0, 0), (0.5, 0.5, 0.5)],
spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
##################################
# Provide your own calculator here
##################################
calc = ClusterVasp(nodes=1, ppn=8)
# The calculator must be runnable in an isolated directory
# Without disturbing other running instances of the same calculator
# They are run in separate processes (not threads!)
MgO.set_calculator(calc)
calc.set(prec='Accurate',
xc='PBE',
lreal=False,
isif=2,
return [r for ns,s in enumerate(sysl) for nr,r in res if nr==ns]
# Testing routines using VASP as a calculator in the cluster environment.
# TODO: Make it calculator/environment agnostic
if __name__ == '__main__':
from ase.lattice.spacegroup import crystal
from ase.units import GPa
import elastic
from elastic.parcalc import ParCalculate, ClusterVasp
import numpy
from pylab import *
a = 4.291
MgO = crystal(['Mg', 'O'], [(0, 0, 0), (0.5, 0.5, 0.5)], spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
##################################
# Provide your own calculator here
##################################
calc=ClusterVasp(nodes=1,ppn=8)
# The calculator must be runnable in an isolated directory
# Without disturbing other running instances of the same calculator
# They are run in separate processes (not threads!)
MgO.set_calculator(calc)
calc.set(prec = 'Accurate', xc = 'PBE', lreal = False, isif=2, nsw=20, ibrion=2, kpts=[1,1,1])
print("Residual pressure: %.3f GPa" % (MgO.get_pressure()/GPa))
calc.clean()
def make_eta_c4(names, sizes):
#work out the expansion factor
#dist0 = furthest_dummy(mol0)
#dist1 = furthest_dummy(mol1)
factor = sum(sizes) #dist0 + dist1
factor = factor * 2
#factor = 3.0
print "factor = ", factor
a = 3.1018 * factor
b = 0.4373 * factor
#b = 0.5466 * factor #RCSR value, incorrect?
# C -> triangles, N => midpoints
#eta_c4 = crystal(['C', 'N' , 'N'], [(0.4069, 0.8138, 0.0), (0.5, 0.0, 0.0), (0.2965, 0.7035, 0.6667)], spacegroup=180, #P6(2)22 #RCSR incorrect?
eta_c4 = crystal(
['C', 'N', 'F'],
[(0.4069, 0.8138, 0.0), (0.5, 0.0, 0.0), (0.7035, 0.4070, 0.5)],
spacegroup=180, #P6(2)22
cellpar=[a, a, b, 90, 90, 120])
#write('test.xyz',eta_c4)
write('test.cif', eta_c4)
eps = 0.9
model_molecule = {}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
cov_rad = []
for atom in eta_c4:
#cov_rad.append(covalent_radii[atom.number])
cov_rad.append(factor / 4)
print cov_rad
nlist = NeighborList(cov_rad,
skin=3.0,
self_interaction=False,
bothways=True)
nlist.build(eta_c4)
#To sort out tags, we need to label each bond
nbond = 1
bond_matrix = np.zeros((len(eta_c4), len(eta_c4)))
pbc_bond_matrix = np.zeros((len(eta_c4), len(eta_c4)))
bond_dict = {}
#Something funky, missing bonds,
#for atom in eta_c4:
# print "---------------------Atom",atom.index,"--------------------"
# for ind in range(len(eta_c4)):
# print atom.index, ind, eta_c4.get_distance(atom.index,ind,mic=True), eta_c4.get_distance(atom.index,ind)
for atom in eta_c4:
print "---------------------"
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
print atom.index, index, atom.symbol, eta_c4[
index].symbol, offset, eta_c4.get_distance(atom.index,
index,
mic=True)
if atom.index <= index: # and eta_c4[index].symbol != 'F': #F require special treatment
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
#Now we need to find the same bond the other direction to get the offsets right
indices2, offsets2 = nlist.get_neighbors(index)
for i2, o2 in zip(indices2, offsets2):
if i2 == atom.index:
#print "sum of offsets = ", offset, o2, sum(offset + o2)
if sum(offset + o2) == 0: #same bond
this_bond = [index, atom.index]
for o in o2:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
nbond += 1
print "Bond dict:"
print nbond
for k, v in bond_dict.items():
print k, v
print "End Bond dict:"
#Now we want to delete C-F bonds that are not of length factor/2
for k, v in bond_dict.items():
i1, i2, o1, o2, o3 = k
position1 = eta_c4.positions[i1]
position2 = eta_c4.positions[i2]
position2_mic = eta_c4.positions[i2] + np.dot([o1, o2, o3],
eta_c4.get_cell())
this_dist = np.linalg.norm(position1 - position2)
this_dist_mic = np.linalg.norm(position1 - position2_mic)
print i1, i2, this_dist, this_dist_mic, (
this_dist - factor / 2), this_dist_mic - factor / 2
if abs(this_dist - factor / 2) > eps and all(o == 0
for o in [o1, o2, o3]):
print "deleting", k
del bond_dict[k]
elif abs(this_dist_mic - factor / 2) > eps and any(
o != 0 for o in [o1, o2, o3]):
print "deleting", k
del bond_dict[k]
#print "New Bond dict:"
#print len(bond_dict)
#for k,v in sorted(bond_dict.items()):
# i1,i2,o1,o2,o3 = k
# position1 = eta_c4.positions[i1]
# position2 = eta_c4.positions[i2]
# position2_mic = eta_c4.positions[i2] + np.dot([o1,o2,o3], eta_c4.get_cell())
# this_dist = np.linalg.norm(position1 - position2)
# this_dist_mic = np.linalg.norm(position1 - position2_mic)
# print k,v, this_dist,this_dist_mic
#print "End New Bond dict:"
#Start with C (triangles)
for atom in eta_c4:
if atom.symbol == 'C':
print '======================================='
print 'C Atom ', atom.index
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'F'
indices, offsets = nlist.get_neighbors(atom.index)
#Just checking the symbols here
print indices
print offsets
symbols = ([eta_c4[index].symbol for index in indices])
symbol_string = ''.join(
sorted([eta_c4[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index, offset in zip(indices, offsets):
print atom.index, index, offset
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#print bond_dict[bond]
print abs(eta_c4.get_distance(
atom.index, index, mic=True)), abs(
eta_c4.get_distance(atom.index, index, mic=True) -
factor)
#if eta_c4[index].symbol == 'N' and abs(eta_c4.get_distance(atom.index,index,mic=True) - factor) < eps: #necessary check, because some atoms are closer than unit distance:
if bond in bond_dict:
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj].positions[
-1] = eta_c4.positions[index] + np.dot(
offset, eta_c4.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[
-1] = eta_c4.positions[index] + np.dot(
offset, eta_c4.get_cell())
n_centers = n_obj
#
#
##Now we do the N (edges)
for atom in eta_c4:
if atom.symbol == 'N' or atom.symbol == 'F':
#print'======================================='
#print 'N Atom ',atom.index, " finding edges"
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
print index, offset, eta_c4[index].symbol
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#if not bond_dict.has_key(bond):
#Then
#if eta_c4[index].symbol == 'C' and abs(eta_c4.get_distance(atom.index,index,mic=True) - factor) < eps: #necessary check, because some atoms are closer than unit distance:
if bond in bond_dict:
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj].positions[
-1] = eta_c4.positions[index] + np.dot(
offset, eta_c4.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += eta_c4[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[
-1] = eta_c4.positions[index] + np.dot(
offset, eta_c4.get_cell())
#
#
#
f = open('eta_c4.model', 'w')
g = open('control-mofgen.txt', 'w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' % ('Number of objects =', n_obj + 1))
f.write('%-20s\n' % ('build = systre'))
f.write('%5s\n' % ('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(eta_c4.get_cell()[0][0], eta_c4.get_cell()[0][1],
eta_c4.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(eta_c4.get_cell()[1][0], eta_c4.get_cell()[1][1],
eta_c4.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(eta_c4.get_cell()[2][0], eta_c4.get_cell()[2][1],
eta_c4.get_cell()[2][2]))
g.write('%-20s\n' % ('model = eta_c4'))
#Now write stuff
for obj in xrange(n_centers + 1):
f.write('\n%-8s %-3d\n' % ('Center: ', obj + 1))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = triangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('center =', names[0]))
for obj in xrange(n_centers + 1, n_obj + 1):
f.write('\n%-8s %-3d\n' % ('Linker: ', obj - n_centers))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = linear'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('linker =', names[1]))
alat3=alat2/2
from aiida.orm.data.array.kpoints import KpointsData
kpoints = KpointsData()
kpoints_mesh = 2
kpoints.set_kpoints_mesh([kpoints_mesh,kpoints_mesh,kpoints_mesh])
StructureData = DataFactory("structure")
the_cell = [[alat/2,alat/2,0.],[alat/2,0.,alat/2],[0.,alat/2,alat/2]]
structure = StructureData(cell=the_cell)
structure.cell
structure.append_atom(position=(alat/4.,alat/4.,alat/4.),symbols="Si")
structure.sites
from ase.lattice.spacegroup import crystal
ase_structure = crystal('Si', [(0,0,0)], spacegroup=227,
cellpar=[alat, alat, alat, 90, 90, 90],primitive_cell=True)
structure=StructureData(ase=ase_structure)
structure.store()
nameCode='pw@local-seb'
code=Code.get_from_string(nameCode)
calc=code.new_calc()
calc.label="PW test"
calc.description="First calculus on BaTiO3"
calc.set_resources({"num_machines": 1})
calc.set_max_wallclock_seconds(30*60)
calc.use_structure(structure)
calc.use_kpoints(kpoints)
def make_spn(names, sizes):
#work out the expansion factor
factor = sum(sizes)
a = 4.8990 * factor
# C -> triangles, N => octahedra
spn = crystal(['C', 'N'], [(0.16667, 0.16667, 0.16667), (0.0, 0.0, 0.0)],
spacegroup=227,
setting=2,
cellpar=[a, a, a, 90, 90, 90])
#write('test.xyz',spn)
eps = 0.05
model_molecule = {}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
cov_rad = []
for atom in spn:
#cov_rad.append(covalent_radii[atom.number])
cov_rad.append(factor / 2)
print cov_rad
nlist = NeighborList(cov_rad,
skin=0.1,
self_interaction=False,
bothways=True)
nlist.build(spn)
#To sort out tags, we need to label each bond
nbond = 1
bond_matrix = np.zeros((len(spn), len(spn)))
pbc_bond_matrix = np.zeros((len(spn), len(spn)))
bond_dict = {}
for atom in spn:
print "---------------------"
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
print atom.index, index, atom.symbol, spn[
index].symbol, offset, spn.get_distance(atom.index,
index,
mic=True)
if atom.index < index:
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
#Now we need to find the same bond the other direction to get the offsets right
indices2, offsets2 = nlist.get_neighbors(index)
for i2, o2 in zip(indices2, offsets2):
if i2 == atom.index:
#print "sum of offsets = ", offset, o2, sum(offset + o2)
if sum(offset + o2) == 0: #same bond
this_bond = [index, atom.index]
for o in o2:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
nbond += 1
print nbond
for k, v in bond_dict.items():
print k, v
#Now we look for all the things with unit*factor bondlengths
#Start with N (octahedra)
for atom in spn:
if atom.symbol == 'N':
print '======================================='
print 'N Atom ', atom.index
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'F'
indices, offsets = nlist.get_neighbors(atom.index)
#Just checking the symbols here
print indices
print offsets
symbols = ([spn[index].symbol for index in indices])
symbol_string = ''.join(
sorted([spn[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index, offset in zip(indices, offsets):
print atom.index, index, offset
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond_dict[bond]
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += spn[index]
model_molecule[n_obj].positions[
-1] = spn.positions[index] + np.dot(
offset, spn.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += spn[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[
-1] = spn.positions[index] + np.dot(
offset, spn.get_cell())
n_centers = n_obj
#
#
##Now we do the C (triangles)
for atom in spn:
if atom.symbol == 'C':
#print'======================================='
#print 'N Atom ',atom.index, " finding squares1"
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
print index, offset, spn[index].symbol
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#if not bond_dict.has_key(bond):
#Then
if spn[index].symbol == 'N':
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += spn[index]
model_molecule[n_obj].positions[
-1] = spn.positions[index] + np.dot(
offset, spn.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += spn[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[
-1] = spn.positions[index] + np.dot(
offset, spn.get_cell())
#
#
#
f = open('spn.model', 'w')
g = open('control-mofgen.txt', 'w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' % ('Number of objects =', n_obj + 1))
f.write('%-20s\n' % ('build = systre'))
f.write('%5s\n' % ('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(spn.get_cell()[0][0], spn.get_cell()[0][1], spn.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(spn.get_cell()[1][0], spn.get_cell()[1][1], spn.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(spn.get_cell()[2][0], spn.get_cell()[2][1], spn.get_cell()[2][2]))
g.write('%-20s\n' % ('model = spn'))
#
for obj in xrange(n_centers + 1):
f.write('\n%-8s %-3d\n' % ('Center: ', obj + 1))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = octahedral_2'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('center =', names[0]))
for obj in xrange(n_centers + 1, n_obj + 1):
f.write('\n%-8s %-3d\n' % ('Linker: ', obj - n_centers))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = triangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('linker =', names[1]))
from ase.lattice.spacegroup import crystal
from ase.calculators.emt import EMT
from ase.optimize import QuasiNewton
from ase.phonons import Phonons
from ase.thermochemistry import CrystalThermo
# Set up gold bulk and attach EMT calculator
a = 4.078
atoms = crystal('Au', (0.,0.,0.),
spacegroup = 225,
cellpar = [a, a, a, 90, 90, 90],
pbc = (1, 1, 1))
calc = EMT()
atoms.set_calculator(calc)
qn = QuasiNewton(atoms)
qn.run(fmax = 0.05)
electronicenergy = atoms.get_potential_energy()
# Phonon analysis
N = 5
ph = Phonons(atoms, calc, supercell=(N, N, N), delta=0.05)
ph.run()
ph.read(acoustic=True)
phonon_energies, phonon_DOS = ph.dos(kpts=(40, 40, 40), npts=3000,
delta=5e-4)
# Calculate the Helmholtz free energy
thermo = CrystalThermo(phonon_energies=phonon_energies,
phonon_DOS = phonon_DOS,
electronicenergy = electronicenergy,
formula_units = 4)
from ase.lattice.spacegroup import crystal
a = 3.21
c = 5.21
mg = crystal('Mg', [(1./3., 2./3., 3./4.)], spacegroup=194,
cellpar=[a, a, c, 90, 90, 120])
Example of elastic tensor calculation using VASP calculator and
elastic module.
'''
from ase.lattice.spacegroup import crystal
from parcalc import ClusterVasp, ParCalculate
from elastic import Crystal
import ase.units as units
from numpy import array, linspace
import matplotlib.pyplot as plt
import numpy
# Create the MgO crystal
a = 4.194
cryst = Crystal(crystal(['Mg', 'O'],
[(0, 0, 0), (0.5, 0.5, 0.5)],
spacegroup=225,
cellpar=[a, a, a, 90, 90, 90]))
# Create the calculator running on one, eight-core node.
# This is specific to the setup on my cluster.
# You have to adapt this part to your environment
calc=ClusterVasp(nodes=1,ppn=8)
# Assign the calculator to the crystal
cryst.set_calculator(calc)
# Set the calculation parameters
calc.set(prec = 'Accurate',
xc = 'PBE',
lreal = False,
nsw=30,
from ase.lattice.spacegroup import crystal
a = 4.6
c = 2.95
rutile = crystal(['Ti', 'O'],
basis=[(0, 0, 0), (0.3, 0.3, 0.0)],
spacegroup=136,
cellpar=[a, a, c, 90, 90, 90])
print rutile
from ase.lattice.spacegroup import crystal
from gpaw import GPAW, PW
a = 4.0351 # Experimental lattice constant in Angstrom
Ecut = 250 # Energy cut off for PW calculation
k = 5 # Number of kpoints per each direction
# This gives the typical NaCl structure:
LiF = crystal(['Li', 'F'],
[(0, 0, 0), (0.5, 0.5, 0.5)],
spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
calc = GPAW(mode=PW(Ecut),
xc='LDA',
kpts=(k, k, k),
txt='LiF_out_gs.txt')
LiF.set_calculator(calc)
LiF.get_potential_energy()
# With the full diagonalization we calculate all the single particle states
# needed for the response calculation:
calc.diagonalize_full_hamiltonian(nbands=100)
calc.write('LiF_fulldiag.gpw', 'all')
def make_chs1(names, sizes):
#CRYSTAL
# NAME "UHM-7 - simplified - 12 - classiified as chs-1"
# GROUP I4/mmm
# CELL 4.14300 4.14300 4.66569 90.0000 90.0000 90.0000
# NODE 5 4 0.00000 0.26972 0.00000
# NODE 1 3 0.06146 0.28112 0.20686
# NODE 4 4 0.10690 0.10690 0.21827
# NODE 2 3 0.00000 0.19156 0.39361
# EDGE 0.06146 0.28112 0.20686 0.21888 0.43854 0.29314
# EDGE 0.00000 0.26972 0.00000 0.06146 0.28112 0.20686
# EDGE 0.00000 0.19156 0.39361 0.00000 0.19156 0.60639
# EDGE 0.00000 0.19156 0.39361 0.10690 0.10690 0.21827
# EDGE 0.10690 0.10690 0.21827 0.28112 -0.06146 0.20686
## EDGE_CENTER 0.14017 0.35983 0.25000
## EDGE_CENTER 0.03073 0.27542 0.10343
## EDGE_CENTER 0.00000 0.19156 0.50000
## EDGE_CENTER 0.05345 0.14923 0.30594
## EDGE_CENTER 0.19401 0.02272 0.21257
#END
# So the node numbering above sucks...
# The edges go between (using the above numbering)
# 1-1
# 5-1
# 2-2
# 2-4
# 4-1
# The same-same edges between triangles are where we need to dump the SiH2X2 units
# Even though SiH2X2 is "linear" (two dummy atoms), in reality it is tetrahedral, and we need to orient it, three points on a line isn't enough
# We'll use some H atoms to give the direction
#So the cgd coordinates actually suck if you want ot build a framework...
#work out the expansion factor
#print "sizes =",sizes
#factor = sizes[2]#/2.0
a = 28.7527
c = 35.4316 #uhm-7 crystal dimensions
# Ne => centre of PW
# C => corner of PW
# N => triangles, first two corresponds to C1 linker, second one to Cs linker
# Ca => corners of triangles (base end) i.e. adjacent to C_PW
# F => SiH2X2 locations, (COM)
# H => SiH2H2 dummies
chs1 = crystal(
[
'Ne', 'Ne', 'N', 'N', 'N', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'F',
'F', 'H', 'H', 'H'
],
[(0.451210, 0.820105, 0.5), (0.311875, 0.630620, 0.317373),
(0.5465, 0.0705, 0.8418), (0.3923, 0.1906, 0.8322),
(0.22825, 0.05125, 0.344895), (0.990100, 0.816000, 0.238990),
(0.072300, 0.830500, 0.236450), (0.306260, 0.914300, 0.135060),
(0.339440, 0.960790, 0.085750), (0.177400, 0.748400, 0.129220),
(0.141300, 0.699100, 0.082930), (0.429660, 0.821690, 0.288870),
(0.648970, 0.890710, 0.5), (0.093000, 0.684300, 0.457300),
(0.115400, 0.430400, 0.304160), (0.185300, 0.478500, 0.254260)],
# chs1 = crystal(['Ne', 'Ne', 'C', 'C', 'C', 'C', 'C', 'C', 'N', 'N', 'N', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'F', 'F', 'H', 'H', 'H'],
# [(0.451210, 0.820105, 0.5), (0.311875, 0.630620, 0.317373),
# (0.893560, 0.736500, 0.153530), (0.991400, 0.666667, 0.052070), (0.845300, 0.885700, 0.215570), (0.795100, 0.815000, 0.146220), (0.692700, 0.891700, 0.050790), (0.944500, 0.813800, 0.219330),
# (0.5465, 0.0705, 0.8418), (0.3923, 0.1906, 0.8322), (0.22825, 0.05125, 0.344895),
# (0.990100, 0.816000, 0.238990), (0.072300, 0.830500, 0.236450), (0.306260, 0.914300, 0.135060), (0.339440, 0.960790, 0.085750), (0.177400, 0.748400, 0.129220), (0.141300, 0.699100, 0.082930),
# (0.429660, 0.821690, 0.288870), (0.648970, 0.890710, 0.5),
# (0.093000, 0.684300, 0.457300), (0.115400, 0.430400, 0.304160), (0.185300, 0.478500, 0.254260)],
spacegroup=87, #I4/m
cellpar=[a, a, c, 90, 90, 90])
write('test.xyz', chs1)
write('test.cif', chs1)
eps = 0.10
model_molecule = {}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
#Rigged such that each
cov_rad = []
for atom in chs1:
#if atom.symbol == 'C':
# cov_rad.append(1.8)
if atom.symbol == 'H':
cov_rad.append(1.4)
elif atom.symbol == 'N':
cov_rad.append(3.7)
elif atom.symbol == 'Ne':
cov_rad.append(1.0)
elif atom.symbol == 'Ca':
cov_rad.append(3.0)
elif atom.symbol == 'F':
cov_rad.append(0.6)
else:
cov_rad.append(covalent_radii[atom.number])
print cov_rad
nlist = NeighborList(cov_rad,
skin=0.01,
self_interaction=False,
bothways=True)
nlist.build(chs1)
#To sort out tags, we need to label each bond, we get a bunch of extra bonds here that we need to filter out
bond_matrix = np.zeros((len(chs1), len(chs1)), dtype=bool)
for atom in chs1:
indices, offsets = nlist.get_neighbors(atom.index)
if atom.symbol == 'Ne': #or atom.symbol == 'F': #these two aren't affected by evil crossover business
for index in indices:
if chs1[index].symbol == 'Ca':
bond_matrix[index, atom.index] = True
bond_matrix[atom.index, index] = True
elif atom.symbol == 'F': #or atom.symbol == 'F': #these two aren't affected by evil crossover business
for index in indices:
if chs1[index].symbol == 'H':
bond_matrix[index, atom.index] = True
bond_matrix[atom.index, index] = True
elif atom.symbol == 'N': #Here we go, suck in both Ca
for index in indices:
if chs1[index].symbol == 'Ca' and chs1.get_distance(
atom.index, index, mic=True
) < 5.0: #Fudgy, but rigging the covalent radii was a pain
bond_matrix[index, atom.index] = True
bond_matrix[atom.index, index] = True
elif chs1[index].symbol == 'H' and chs1.get_distance(
atom.index, index, mic=True
) > 4.8: #This is a fudge that works. Better test would be take max H distance
bond_matrix[index, atom.index] = True
bond_matrix[atom.index, index] = True
else:
pass #No other bonds get counted
##Now we loop over the N, just to find which carbons go over PBC
#for atom in chs1:
# if atom.symbol == 'N':
# indices, offsets = nlist.get_neighbors(atom.index)
# for index,offset in zip(indices,offsets): #Should only be C
# if chs1[index].symbol == 'C':
# if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# chs1[index].tag = -chs1[index].tag
factor = sum(sizes) / 2.0 + 2 #(sizes[0] + sizes[2])/2.0
print "factor = ", factor
a = 4.14300 * factor
c = 4.66569 * factor
# Ne => centre of PW
# N => triangles, first two corresponds to C1 linker, second one to Cs linker
# Ca => corners of triangles (base end) i.e. adjacent to C_PW
# F => SiH2X2 locations, (COM)
# H => SiH2H2 dummies
chs1 = crystal(
[
'Ne', 'Ne', 'N', 'N', 'N', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'F',
'F', 'H', 'H', 'H'
],
[(0.451210, 0.820105, 0.5), (0.311875, 0.630620, 0.317373),
(0.5465, 0.0705, 0.8418), (0.3923, 0.1906, 0.8322),
(0.22825, 0.05125, 0.344895), (0.990100, 0.816000, 0.238990),
(0.072300, 0.830500, 0.236450), (0.306260, 0.914300, 0.135060),
(0.339440, 0.960790, 0.085750), (0.177400, 0.748400, 0.129220),
(0.141300, 0.699100, 0.082930), (0.429660, 0.821690, 0.288870),
(0.648970, 0.890710, 0.5), (0.093000, 0.684300, 0.457300),
(0.115400, 0.430400, 0.304160), (0.185300, 0.478500, 0.254260)],
spacegroup=87, #I4/m
cellpar=[a, a, c, 90, 90, 90])
#Now that we've decided the bonds on the master structure, move them across to the scaled structure
nbond = 1
#Now our test will involve using indices,offsets and bond_matrix=True
#In this case, the Ca and H atoms directly represent our dummy atoms, so we number them
for atom in chs1:
if atom.symbol == 'Ca' or atom.symbol == 'H':
atom.tag = nbond
nbond += 1
#Now that we have our t/f matrix, we need to number the bonds, taking into account PBC
bond_ids = np.zeros((len(chs1), len(chs1)))
for atom in chs1:
if atom.symbol == 'Ca' or atom.symbol == 'H':
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
if bond_matrix[
index,
atom.index]: #If we've already identified it a a bond
if any(o != 0 for o in offset): #Then we're going over PBC
atom.tag = -atom.tag
#for atom in chs1:
# print atom.index, atom.symbol, atom.position, atom.tag
#Now we start assembling the model
#Start with Ne (rectangles)
for atom in chs1:
if atom.symbol == 'Ne':
print '======================================='
print 'Ne Atom ', atom.index
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'Ne'
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
symbols = ([chs1[index].symbol for index in indices])
symbol_string = ''.join(
sorted([chs1[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index, offset in zip(indices, offsets):
if bond_matrix[index, atom.index]:
model_molecule[n_obj] += chs1[index]
model_molecule[n_obj].positions[
-1] = chs1.positions[index] + np.dot(
offset, chs1.get_cell())
model_molecule[n_obj][-1].tag = chs1[index].tag
print chs1[index].symbol, chs1[index].position, chs1[
index].tag
print chs1[index].index, chs1[index].symbol, chs1[
index].position, chs1[index].tag
#if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
# model_molecule[n_obj][-1].tag = -bond_dict[bond]
#else:
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj][-1].tag = bond_dict[bond]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
n_centers = n_obj
#
#
##Now we do the F (SiX2H2)
for atom in chs1:
if atom.symbol == 'F':
#print'======================================='
#print 'F Atom ',atom.index, " finding SiH2X2 anchor points"
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
if bond_matrix[index, atom.index]:
model_molecule[n_obj] += chs1[index]
model_molecule[n_obj].positions[
-1] = chs1.positions[index] + np.dot(
offset, chs1.get_cell())
model_molecule[n_obj][-1].tag = chs1[index].tag
#if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
# model_molecule[n_obj][-1].tag = -bond_dict[bond]
#else:
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj][-1].tag = bond_dict[bond]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
n_linkers = n_obj
##Now we do the N (triangles)
for atom in chs1:
if atom.symbol == 'N':
#print'======================================='
#print 'N Atom ',atom.index, " finding triangles"
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
if bond_matrix[index, atom.index]:
model_molecule[n_obj] += chs1[index]
model_molecule[n_obj].positions[
-1] = chs1.positions[index] + np.dot(
offset, chs1.get_cell())
model_molecule[n_obj][-1].tag = chs1[index].tag
#if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
# model_molecule[n_obj][-1].tag = -bond_dict[bond]
#else:
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj][-1].tag = bond_dict[bond]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
#
#
#
f = open('chs1.model', 'w')
g = open('control-mofgen.txt', 'w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' % ('Number of objects =', n_obj + 1))
f.write('%-20s\n' % ('build = systre'))
f.write('%5s\n' % ('Cell:'))
f.write(
'%8.3f %8.3f %8.3f \n' %
(chs1.get_cell()[0][0], chs1.get_cell()[0][1], chs1.get_cell()[0][2]))
f.write(
'%8.3f %8.3f %8.3f \n' %
(chs1.get_cell()[1][0], chs1.get_cell()[1][1], chs1.get_cell()[1][2]))
f.write(
'%8.3f %8.3f %8.3f \n' %
(chs1.get_cell()[2][0], chs1.get_cell()[2][1], chs1.get_cell()[2][2]))
g.write('%-20s\n' % ('model = chs1'))
#
for obj in xrange(n_centers + 1):
f.write('\n%-8s %-3d\n' % ('Center: ', obj + 1))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = rectangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('center =', names[0]))
for obj in xrange(n_centers + 1, n_linkers + 1):
f.write('\n%-8s %-3d\n' % ('Linker: ', obj - n_centers))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = linear_triangle'))
#process positions to make it a bit more ideal
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
elif atom.symbol == 'F':
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
elif atom.symbol == 'H':
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Bq', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('linker =', names[1]))
#
for obj in xrange(n_linkers + 1, n_obj + 1):
f.write('\n%-8s %-3d\n' % ('Linker: ', obj - n_centers))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = triangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 2.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('linker =', names[2]))
#
#
test_mol = Atoms()
for obj in model_molecule:
#for obj in xrange(n_linkers+1,n_obj+1): #triangles only
test_mol += model_molecule[obj]
test_mol.set_cell(chs1.get_cell())
test_mol.set_pbc(chs1.get_pbc())
write('test_model2.xyz', test_mol)
write('test_model2.cif', test_mol)
def make_mil53(names, sizes):
#work out the expansion factor
factor = sizes[1] #linker is the only thing that matters #sum(sizes)
#print sizes[0]
a = 6.6085 #We'll form the bondlist and then enlarge the cell.
b = 16.0 #16.675
c = 12.0 #12.813
#These cell dimensions are rigged to a linker length of 5 (circa size of benzene)
# Al -> centre of mil53, N -> centre of rectangle linker , C -> dummies
mil53 = crystal(
['Al', 'N', 'C'],
[(0.25, 0.25, 0.25), (0.5, 0.0, 0.5), (0.5, 0.1292, 0.383)],
spacegroup=74, #Imma
cellpar=[a, b, c, 90, 90, 90])
write('test.xyz', mil53)
eps = 0.05
model_molecule = {}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
#First detect global bonding
cov_rad = []
for atom in mil53:
if atom.symbol == 'Al':
cov_rad.append(covalent_radii[atom.number] *
2) #Rigged to suck in C, but not N
elif atom.symbol == 'N':
cov_rad.append(covalent_radii[atom.number] *
3) #Rigged to suck in C, but not Al
else:
cov_rad.append(covalent_radii[atom.number])
#print cov_rad
nlist = NeighborList(cov_rad,
skin=0.1,
self_interaction=False,
bothways=True)
nlist.build(mil53)
#Now we exapnd the cell. The factor given is half the hypotenuse of a right triangle with angle 35 deg
print "factor = ", factor
print b, c
a = 2 * sizes[0]
b = b + (2 * factor * sin(35 * pi / 180.0))
c = c + (2 * factor * cos(35 * pi / 180.0))
print b, c
# Al -> centre of mil53, N -> centre of rectangle linker , C -> dummies
mil53 = crystal(
['Al', 'N', 'C'],
[(0.25, 0.25, 0.25), (0.5, 0.0, 0.5), (0.5, 0.1292, 0.383)],
spacegroup=74, #Imma
cellpar=[a, b, c, 90, 90, 90]) #a (height) is fixed
#To sort out tags, we need to label each bond
nbond = 1
#Now in this case, the C atoms directly represent our dummy atoms, so we number them
for atom in mil53:
if atom.symbol == 'C':
atom.tag = nbond
nbond += 1
#Al also need to be tagged to each other
for atom in mil53:
if atom.symbol == 'Al':
indices, offsets = nlist.get_neighbors(atom.index)
#symbol_string = ''.join(sorted([mil53[index].symbol for index in indices]))
#print symbol_string
for index, offset in zip(indices, offsets):
if mil53[index].symbol == 'Al' and all(
o == 0 for o in offset
) and index > atom.index: #interesting because it the same bond is both internal and pbc
#print "atom ", atom.index, " and atom ",index, " are bonded, non-pbc ", nbond
atom.tag = nbond
mil53[index].tag = nbond
nbond += 1
#Now we loop over the N, just to find which carbons go over PBC
for atom in mil53:
if atom.symbol == 'N':
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets): #Should only be C
if mil53[index].symbol == 'C':
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
mil53[index].tag = -mil53[index].tag
#print mil53.get_tags()
used_carbon = []
#Now we build the model
#Start with Al
for atom in mil53:
if atom.symbol == 'Al':
#print'======================================='
#print 'Al Atom ',atom.index
indices, offsets = nlist.get_neighbors(atom.index)
C_count = 0
for index, offset in zip(indices,
offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(
o == 0 for o in offset
): # and mil53[index].tag not in model_molecule[n_obj].get_tags():
C_count += 1
#print "Al atom, ", atom.index, "has c-count in this cell", C_count
if C_count == 2:
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
for index, offset in zip(indices,
offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(
o == 0 for o in offset
): # and mil53[index].tag not in model_molecule[n_obj].get_tags():
model_molecule[n_obj] += mil53[index]
model_molecule[n_obj][-1].tag = mil53[index].tag
model_molecule[n_obj].positions[
-1] = mil53.positions[index] + np.dot(
offset, mil53.get_cell())
used_carbon.append(index)
#We need to put the other Al as an anchor
for index, offset in zip(indices, offsets):
if mil53[index].symbol == 'Al' and all(o == 0
for o in offset):
model_molecule[n_obj] += mil53[index]
#model_molecule[n_obj][-1].tag = None #No tag
model_molecule[n_obj].positions[
-1] = mil53.positions[index] + np.dot(
offset, mil53.get_cell())
#That gives us two Al centres, now the other two
#These are the two that have 4 in-cell C
for atom in mil53:
if atom.symbol == 'Al':
#print'======================================='
#print 'Al Atom ',atom.index
indices, offsets = nlist.get_neighbors(atom.index)
C_count = 0
for index, offset in zip(indices,
offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(
o == 0 for o in offset
): # and mil53[index].tag not in model_molecule[n_obj].get_tags():
C_count += 1
#print "Al atom, ", atom.index, "has c-count in this cell", C_count
if C_count == 4:
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
for index, offset in zip(indices,
offsets): #Should only be C or Al
if mil53[index].symbol == 'C' and all(
o == 0
for o in offset) and index not in used_carbon:
model_molecule[n_obj] += mil53[index]
model_molecule[n_obj][-1].tag = mil53[index].tag
model_molecule[n_obj].positions[
-1] = mil53.positions[index] + np.dot(
offset, mil53.get_cell())
#We need to put the other Al as an anchor
for index, offset in zip(indices, offsets):
if mil53[index].symbol == 'Al' and any(o != 0
for o in offset):
model_molecule[n_obj] += mil53[index]
#model_molecule[n_obj][-1].tag = None #No tag
model_molecule[n_obj].positions[
-1] = mil53.positions[index] + np.dot(
offset, mil53.get_cell())
# #We need to interrogate our C further as two of them belong to both Al in the same cell
# C_indices,C_offsets = nlist.get_neighbors(index)
# symbol_string = ''.join(sorted([mil53[index].symbol for index in C_indices]))
# print symbol_string
#
# model_molecule[n_obj] += mil53[index]
# model_molecule[n_obj][-1].tag = mil53[index].tag
# model_molecule[n_obj].positions[-1] = mil53.positions[index] + np.dot(offset, mil53.get_cell())
n_centers = n_obj
#
#
##Now we do the N (linear)
for atom in mil53:
if atom.symbol == 'N':
#print'======================================='
#print 'N Atom ',atom.index, " finding squares1"
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets): #Should only be C
if mil53[index].symbol == 'C':
model_molecule[n_obj] += mil53[index]
model_molecule[n_obj][-1].tag = mil53[index].tag
model_molecule[n_obj].positions[
-1] = mil53.positions[index] + np.dot(
offset, mil53.get_cell())
#
#
#
f = open('mil53.model', 'w')
g = open('control-mofgen.txt', 'w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
test_mol = Atoms()
for obj in model_molecule:
test_mol += model_molecule[obj]
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' % ('Number of objects =', n_obj + 1))
f.write('%-20s\n' % ('build = systre'))
f.write('%-13s\n' % ('ExtraDummies'))
f.write('%5s\n' % ('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(mil53.get_cell()[0][0], mil53.get_cell()[0][1],
mil53.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(mil53.get_cell()[1][0], mil53.get_cell()[1][1],
mil53.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(mil53.get_cell()[2][0], mil53.get_cell()[2][1],
mil53.get_cell()[2][2]))
g.write('%-20s\n' % ('model = mil53'))
# Print the centers and linkers
for obj in xrange(n_centers + 1):
f.write('\n%-8s %-3d\n' % ('Center: ', obj + 1))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = mil53'))
#process positions to make it a bit more ideal
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(atom.index,0,2.0,fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.symbol == 'C': #can't use tags as a marker here, because we've given a tag to 'Q' as well
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
elif atom.symbol == 'Al':
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('Q', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('center =', names[0]))
for obj in xrange(n_centers + 1, n_obj + 1):
f.write('\n%-8s %-3d\n' % ('Linker: ', obj - n_centers))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = linear'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('linker =', names[1]))
#
#
test_mol = Atoms()
for obj in model_molecule:
test_mol += model_molecule[obj]
write('test_model2.xyz', test_mol)
def make_nbo(names, sizes):
#work out the expansion factor
#dist0 = furthest_dummy(mol0)
#dist1 = furthest_dummy(mol1)
factor = sum(sizes) #dist0 + dist1
factor = factor * 2
a = 2.0 * factor
#a = 4.0
# C -> squares, N => midpoints
nbo = crystal(['C', 'N'], [(0.0, 0.5, 0.5), (0.25, 0.0, 0.5)],
spacegroup=229,
cellpar=[a, a, a, 90, 90, 90])
#write('test.xyz',nbo)
eps = 0.05
model_molecule = {}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
cov_rad = []
for atom in nbo:
#cov_rad.append(covalent_radii[atom.number])
cov_rad.append(factor / 4)
nlist = NeighborList(cov_rad, self_interaction=False, bothways=True)
nlist.build(nbo)
#To sort out tags, we need to label each bond
nbond = 1
bond_matrix = np.zeros((len(nbo), len(nbo)))
for atom in nbo:
indices, offsets = nlist.get_neighbors(atom.index)
for index in indices:
if atom.index < index:
bond_matrix[index, atom.index] = nbond
bond_matrix[atom.index, index] = nbond
print atom.index, index, nbond
nbond += 1
print nbond
print bond_matrix
#Now we look for all the things with unit*factor bondlengths
#Start with C (squares)
for atom in nbo:
if atom.symbol == 'C':
print '======================================='
print 'C Atom ', atom.index
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'F'
indices, offsets = nlist.get_neighbors(atom.index)
#Just checking the symbols here
symbols = ([nbo[index].symbol for index in indices])
symbol_string = ''.join(
sorted([nbo[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index, offset in zip(indices, offsets):
dist_mic = nbo.get_distance(atom.index, index, mic=True)
dist_no_mic = nbo.get_distance(atom.index, index, mic=False)
print index, dist_no_mic
##Cell expands by the factor, but we're halving it because the N represesnt midpoints of CC bonds. Default systre bondlength is 1.0
if (abs(dist_mic - dist_no_mic) <=
eps) and (abs(dist_mic - factor / 2.0) < eps):
model_molecule[n_obj] += nbo[index]
model_molecule[n_obj][-1].tag = bond_matrix[atom.index,
index]
elif abs(dist_mic - factor / 2.0) < eps:
#If we're going over a periodic boundary, we need to negate the tag
print "Tag, ", nbo[index].tag, " goes over pbc"
nbo[index].tag = -(nbo[index].tag)
model_molecule[n_obj] += nbo[index]
model_molecule[n_obj].positions[
-1] = nbo.positions[index] + np.dot(
offset, nbo.get_cell())
model_molecule[n_obj][-1].tag = -bond_matrix[atom.index,
index]
n_centers = n_obj
#
#
##Now we do the edges / N/ (linear things)
for atom in nbo:
if atom.symbol == 'N':
print '======================================='
print 'N Atom ', atom.index, " finding edges"
n_obj += 1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index, offset in zip(indices, offsets):
dist_mic = nbo.get_distance(atom.index, index, mic=True)
dist_no_mic = nbo.get_distance(atom.index, index, mic=False)
##Cell expands by the factor, but we're halving it because the N represesnt midpoints of CC bonds. Default systre bondlength is 1.0
if (abs(dist_mic - dist_no_mic) <=
eps) and (abs(dist_mic - factor / 2.0) < eps):
model_molecule[n_obj] += nbo[index]
model_molecule[n_obj][-1].tag = bond_matrix[atom.index,
index]
elif abs(dist_mic - factor / 2.0) < eps:
#If we're going over a periodic boundary, we need to negate the tag
print "Tag, ", nbo[index].tag, " goes over pbc"
nbo[index].tag = -(nbo[index].tag)
model_molecule[n_obj] += nbo[index]
model_molecule[n_obj].positions[
-1] = nbo.positions[index] + np.dot(
offset, nbo.get_cell())
model_molecule[n_obj][-1].tag = -bond_matrix[atom.index,
index]
f = open('nbo.model', 'w')
g = open('control-mofgen.txt', 'w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' % ('Number of objects =', n_obj + 1))
f.write('%-20s\n' % ('build = systre'))
f.write('%5s\n' % ('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(nbo.get_cell()[0][0], nbo.get_cell()[0][1], nbo.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(nbo.get_cell()[1][0], nbo.get_cell()[1][1], nbo.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(nbo.get_cell()[2][0], nbo.get_cell()[2][1], nbo.get_cell()[2][2]))
g.write('%-20s\n' % ('model = nbo'))
for obj in xrange(n_centers + 1):
f.write('\n%-8s %-3d\n' % ('Centre: ', obj + 1))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = square'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
if atom.symbol == 'N':
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('center =', names[0]))
for obj in xrange(n_centers + 1, n_obj + 1):
f.write('\n%-8s %-3d\n' % ('Linker: ', obj - n_centers))
f.write('%-3d\n' % (len(model_molecule[obj])))
f.write('%-20s\n' % ('type = linear'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
if atom.symbol == 'C':
model_molecule[obj].set_distance(atom.index, 0, 1.0, fix=1)
for atom in model_molecule[obj]:
(x, y, z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' %
('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' % ('linker =', names[1]))
# Spacegroup/symmetry library
from pyspglib import spglib
# The qe-util package
from qeutil import QuantumEspresso
# iPython utility function
from IPython.core.display import Image
# Configure qe-util for local execution of the Quantum Espresso on four processors
# QuantumEspresso.pw_cmd='mpiexec -n 4 pw.x < pw.in > pw.out'
a=4.3596 # Lattice constant in Angstrom
cryst = crystal(['Si', 'C'], # Atoms in the crystal
[(0, 0, 0), (0.25, 0.25, 0.25)], # Atomic positions (fractional coordinates)
spacegroup=216, # International number of the spacegroup of the crystal
cellpar=[a, a, a, 90, 90, 90]) # Unit cell (a, b, c, alpha, beta, gamma) in Angstrom, Degrees
# Write the image to disk file
ase.io.write('crystal.png', # The file where the picture get stored
cryst, # The object holding the crystal definition
format='png', # Format of the file
show_unit_cell=2, # Draw the unit cell boundaries
rotation='115y,15x', # Rotate the scene by 115deg around Y axis and 15deg around X axis
scale=30) # Scale of the picture
# Display the image
Image(filename='crystal.png')
print 'Space group:', spglib.get_spacegroup(cryst)
# You should have received a copy of the GNU General Public License
# along with Elastic. If not, see <http://www.gnu.org/licenses/>.
'''
Example of parallel volume scan using VASP calculator and parcalc module.
'''
from ase.lattice.spacegroup import crystal
from parcalc import ClusterVasp, ParCalculate
import ase.units as units
import numpy
import matplotlib.pyplot as plt
a = 4.194
cryst = crystal(['Mg', 'O'],
[(0, 0, 0), (0.5, 0.5, 0.5)],
spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
# Create the calculator running on one, eight-core node.
# This is specific to the setup on my cluster.
# You have to adapt this part to your environment
calc=ClusterVasp(nodes=1,ppn=8)
# Assign the calculator to the crystal
cryst.set_calculator(calc)
# Set the calculation parameters
calc.set(prec = 'Accurate',
xc = 'PBE',
lreal = False,
nsw=30,
from ase.lattice.spacegroup import crystal
a = 2.87
fe = crystal('Fe', [(0,0,0)], spacegroup=229, cellpar=[a, a, a, 90, 90, 90])
elastic module.
'''
from ase.lattice.spacegroup import crystal
from parcalc import ClusterVasp, ParCalculate
from elastic import Crystal
import ase.units as units
from numpy import array, linspace
import matplotlib.pyplot as plt
import numpy
# Create the MgO crystal
a = 4.194
cryst = Crystal(
crystal(['Mg', 'O'], [(0, 0, 0), (0.5, 0.5, 0.5)],
spacegroup=225,
cellpar=[a, a, a, 90, 90, 90]))
# Create the calculator running on one, eight-core node.
# This is specific to the setup on my cluster.
# You have to adapt this part to your environment
calc = ClusterVasp(nodes=1, ppn=8)
# Assign the calculator to the crystal
cryst.set_calculator(calc)
# Set the calculation parameters
calc.set(prec='Accurate',
xc='PBE',
lreal=False,
nsw=30,
def make_iac(names,sizes):
#work out the expansion factor
factor = sum(sizes) #
a = 3.5777 * factor
# C -> tetrahedra, N => octahedra
iac = crystal(['C', 'N'], [(0.125, 0.0, 0.25), (0.0,0.0,0.0)], spacegroup=230,
cellpar=[a, a, a, 90, 90, 90])
#write('test.xyz',iac)
eps = 0.05
model_molecule={}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
cov_rad=[]
for atom in iac:
#cov_rad.append(covalent_radii[atom.number])
cov_rad.append(factor / 2)
print cov_rad
nlist = NeighborList(cov_rad,skin=0.1,self_interaction=False,bothways=True)
nlist.build(iac)
#To sort out tags, we need to label each bond
nbond = 1
bond_matrix = np.zeros( (len(iac),len(iac)) )
pbc_bond_matrix = np.zeros( (len(iac),len(iac)) )
bond_dict = {}
for atom in iac:
print "---------------------"
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
print atom.index, index, atom.symbol, iac[index].symbol, offset, iac.get_distance(atom.index,index,mic=True)
if atom.index < index:
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
#Now we need to find the same bond the other direction to get the offsets right
indices2,offsets2 = nlist.get_neighbors(index)
for i2,o2 in zip(indices2,offsets2):
if i2 == atom.index:
#print "sum of offsets = ", offset, o2, sum(offset + o2)
if sum(offset + o2) == 0: #same bond
this_bond = [index, atom.index]
for o in o2:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
nbond +=1
#print nbond
#for k,v in bond_dict.items():
# print k,v
#Now we look for all the things with unit*factor bondlengths
#Start with N (octahedra)
for atom in iac:
if atom.symbol == 'N':
print'======================================='
print 'N Atom ',atom.index
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'F'
indices, offsets = nlist.get_neighbors(atom.index)
#Just checking the symbols here
print indices
print offsets
symbols = ([iac[index].symbol for index in indices])
symbol_string = ''.join(sorted([iac[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index,offset in zip(indices,offsets):
print atom.index, index, offset
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond_dict[bond]
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += iac[index]
model_molecule[n_obj].positions[-1] = iac.positions[index] + np.dot(offset, iac.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += iac[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[-1] = iac.positions[index] + np.dot(offset, iac.get_cell())
n_centers = n_obj
#
#
##Now we do the C (tetrahedra)
for atom in iac:
if atom.symbol == 'C':
#print'======================================='
#print 'N Atom ',atom.index, " finding squares1"
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
print index, offset, iac[index].symbol
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#if not bond_dict.has_key(bond):
#Then
if iac[index].symbol == 'N':
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += iac[index]
model_molecule[n_obj].positions[-1] = iac.positions[index] + np.dot(offset, iac.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += iac[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[-1] = iac.positions[index] + np.dot(offset, iac.get_cell())
#
#
#
f = open('iac.model','w')
g = open('control-mofgen.txt','w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' %('Number of objects =',n_obj+1))
f.write('%-20s\n' %('build = systre'))
f.write('%5s\n' %('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(iac.get_cell()[0][0],
iac.get_cell()[0][1],
iac.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(iac.get_cell()[1][0],
iac.get_cell()[1][1],
iac.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(iac.get_cell()[2][0],
iac.get_cell()[2][1],
iac.get_cell()[2][2]))
g.write('%-20s\n' %('model = iac'))
#
for obj in xrange(n_centers+1):
f.write('\n%-8s %-3d\n' %('Center: ', obj+1))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = octahedral_2'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('center =', names[0]))
for obj in xrange(n_centers+1,n_obj+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = tetrahedral'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('linker =', names[1]))
def make_chs1(names,sizes):
#CRYSTAL
# NAME "UHM-7 - simplified - 12 - classiified as chs-1"
# GROUP I4/mmm
# CELL 4.14300 4.14300 4.66569 90.0000 90.0000 90.0000
# NODE 5 4 0.00000 0.26972 0.00000
# NODE 1 3 0.06146 0.28112 0.20686
# NODE 4 4 0.10690 0.10690 0.21827
# NODE 2 3 0.00000 0.19156 0.39361
# EDGE 0.06146 0.28112 0.20686 0.21888 0.43854 0.29314
# EDGE 0.00000 0.26972 0.00000 0.06146 0.28112 0.20686
# EDGE 0.00000 0.19156 0.39361 0.00000 0.19156 0.60639
# EDGE 0.00000 0.19156 0.39361 0.10690 0.10690 0.21827
# EDGE 0.10690 0.10690 0.21827 0.28112 -0.06146 0.20686
## EDGE_CENTER 0.14017 0.35983 0.25000
## EDGE_CENTER 0.03073 0.27542 0.10343
## EDGE_CENTER 0.00000 0.19156 0.50000
## EDGE_CENTER 0.05345 0.14923 0.30594
## EDGE_CENTER 0.19401 0.02272 0.21257
#END
# So the node numbering above sucks...
# The edges go between (using the above numbering)
# 1-1
# 5-1
# 2-2
# 2-4
# 4-1
# The same-same edges between triangles are where we need to dump the SiH2X2 units
# Even though SiH2X2 is "linear" (two dummy atoms), in reality it is tetrahedral, and we need to orient it, three points on a line isn't enough
# We'll use some H atoms to give the direction
#So the cgd coordinates actually suck if you want ot build a framework...
#work out the expansion factor
#print "sizes =",sizes
#factor = sizes[2]#/2.0
a = 28.7527
c = 35.4316 #uhm-7 crystal dimensions
# Ne => centre of PW
# C => corner of PW
# N => triangles, first two corresponds to C1 linker, second one to Cs linker
# Ca => corners of triangles (base end) i.e. adjacent to C_PW
# F => SiH2X2 locations, (COM)
# H => SiH2H2 dummies
chs1 = crystal(['Ne', 'Ne', 'N', 'N', 'N', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'F', 'F', 'H', 'H', 'H'],
[(0.451210, 0.820105, 0.5), (0.311875, 0.630620, 0.317373),
(0.5465, 0.0705, 0.8418), (0.3923, 0.1906, 0.8322), (0.22825, 0.05125, 0.344895),
(0.990100, 0.816000, 0.238990), (0.072300, 0.830500, 0.236450), (0.306260, 0.914300, 0.135060), (0.339440, 0.960790, 0.085750), (0.177400, 0.748400, 0.129220), (0.141300, 0.699100, 0.082930),
(0.429660, 0.821690, 0.288870), (0.648970, 0.890710, 0.5),
(0.093000, 0.684300, 0.457300), (0.115400, 0.430400, 0.304160), (0.185300, 0.478500, 0.254260)],
# chs1 = crystal(['Ne', 'Ne', 'C', 'C', 'C', 'C', 'C', 'C', 'N', 'N', 'N', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'F', 'F', 'H', 'H', 'H'],
# [(0.451210, 0.820105, 0.5), (0.311875, 0.630620, 0.317373),
# (0.893560, 0.736500, 0.153530), (0.991400, 0.666667, 0.052070), (0.845300, 0.885700, 0.215570), (0.795100, 0.815000, 0.146220), (0.692700, 0.891700, 0.050790), (0.944500, 0.813800, 0.219330),
# (0.5465, 0.0705, 0.8418), (0.3923, 0.1906, 0.8322), (0.22825, 0.05125, 0.344895),
# (0.990100, 0.816000, 0.238990), (0.072300, 0.830500, 0.236450), (0.306260, 0.914300, 0.135060), (0.339440, 0.960790, 0.085750), (0.177400, 0.748400, 0.129220), (0.141300, 0.699100, 0.082930),
# (0.429660, 0.821690, 0.288870), (0.648970, 0.890710, 0.5),
# (0.093000, 0.684300, 0.457300), (0.115400, 0.430400, 0.304160), (0.185300, 0.478500, 0.254260)],
spacegroup=87, #I4/m
cellpar=[a, a, c, 90, 90, 90])
write('test.xyz',chs1)
write('test.cif',chs1)
eps = 0.10
model_molecule={}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
#Rigged such that each
cov_rad=[]
for atom in chs1:
#if atom.symbol == 'C':
# cov_rad.append(1.8)
if atom.symbol == 'H':
cov_rad.append(1.4)
elif atom.symbol == 'N':
cov_rad.append(3.7)
elif atom.symbol == 'Ne':
cov_rad.append(1.0)
elif atom.symbol == 'Ca':
cov_rad.append(3.0)
elif atom.symbol == 'F':
cov_rad.append(0.6)
else:
cov_rad.append(covalent_radii[atom.number])
print cov_rad
nlist = NeighborList(cov_rad,skin=0.01,self_interaction=False,bothways=True)
nlist.build(chs1)
#To sort out tags, we need to label each bond, we get a bunch of extra bonds here that we need to filter out
bond_matrix = np.zeros( (len(chs1),len(chs1)) , dtype=bool)
for atom in chs1:
indices, offsets = nlist.get_neighbors(atom.index)
if atom.symbol == 'Ne': #or atom.symbol == 'F': #these two aren't affected by evil crossover business
for index in indices:
if chs1[index].symbol == 'Ca':
bond_matrix[index,atom.index] = True
bond_matrix[atom.index,index] = True
elif atom.symbol == 'F': #or atom.symbol == 'F': #these two aren't affected by evil crossover business
for index in indices:
if chs1[index].symbol == 'H':
bond_matrix[index,atom.index] = True
bond_matrix[atom.index,index] = True
elif atom.symbol == 'N': #Here we go, suck in both Ca
for index in indices:
if chs1[index].symbol == 'Ca' and chs1.get_distance(atom.index,index,mic=True) <5.0: #Fudgy, but rigging the covalent radii was a pain
bond_matrix[index,atom.index] = True
bond_matrix[atom.index,index] = True
elif chs1[index].symbol == 'H' and chs1.get_distance(atom.index,index,mic=True) >4.8: #This is a fudge that works. Better test would be take max H distance
bond_matrix[index,atom.index] = True
bond_matrix[atom.index,index] = True
else:
pass #No other bonds get counted
##Now we loop over the N, just to find which carbons go over PBC
#for atom in chs1:
# if atom.symbol == 'N':
# indices, offsets = nlist.get_neighbors(atom.index)
# for index,offset in zip(indices,offsets): #Should only be C
# if chs1[index].symbol == 'C':
# if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# chs1[index].tag = -chs1[index].tag
factor = sum(sizes)/2.0 + 2#(sizes[0] + sizes[2])/2.0
print "factor = ",factor
a = 4.14300 * factor
c = 4.66569 * factor
# Ne => centre of PW
# N => triangles, first two corresponds to C1 linker, second one to Cs linker
# Ca => corners of triangles (base end) i.e. adjacent to C_PW
# F => SiH2X2 locations, (COM)
# H => SiH2H2 dummies
chs1 = crystal(['Ne', 'Ne', 'N', 'N', 'N', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'Ca', 'F', 'F', 'H', 'H', 'H'],
[(0.451210, 0.820105, 0.5), (0.311875, 0.630620, 0.317373),
(0.5465, 0.0705, 0.8418), (0.3923, 0.1906, 0.8322), (0.22825, 0.05125, 0.344895),
(0.990100, 0.816000, 0.238990), (0.072300, 0.830500, 0.236450), (0.306260, 0.914300, 0.135060), (0.339440, 0.960790, 0.085750), (0.177400, 0.748400, 0.129220), (0.141300, 0.699100, 0.082930),
(0.429660, 0.821690, 0.288870), (0.648970, 0.890710, 0.5),
(0.093000, 0.684300, 0.457300), (0.115400, 0.430400, 0.304160), (0.185300, 0.478500, 0.254260)],
spacegroup=87, #I4/m
cellpar=[a, a, c, 90, 90, 90])
#Now that we've decided the bonds on the master structure, move them across to the scaled structure
nbond = 1
#Now our test will involve using indices,offsets and bond_matrix=True
#In this case, the Ca and H atoms directly represent our dummy atoms, so we number them
for atom in chs1:
if atom.symbol == 'Ca' or atom.symbol == 'H':
atom.tag = nbond
nbond += 1
#Now that we have our t/f matrix, we need to number the bonds, taking into account PBC
bond_ids = np.zeros( (len(chs1),len(chs1)) )
for atom in chs1:
if atom.symbol == 'Ca' or atom.symbol == 'H':
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
if bond_matrix[index,atom.index]: #If we've already identified it a a bond
if any(o != 0 for o in offset): #Then we're going over PBC
atom.tag = -atom.tag
#for atom in chs1:
# print atom.index, atom.symbol, atom.position, atom.tag
#Now we start assembling the model
#Start with Ne (rectangles)
for atom in chs1:
if atom.symbol == 'Ne':
print'======================================='
print 'Ne Atom ',atom.index
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'Ne'
indices, offsets = nlist.get_neighbors(atom.index)
#print offsets
symbols = ([chs1[index].symbol for index in indices])
symbol_string = ''.join(sorted([chs1[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index,offset in zip(indices,offsets):
if bond_matrix[index,atom.index]:
model_molecule[n_obj] += chs1[index]
model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
model_molecule[n_obj][-1].tag = chs1[index].tag
print chs1[index].symbol, chs1[index].position, chs1[index].tag
print chs1[index].index, chs1[index].symbol, chs1[index].position, chs1[index].tag
#if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
# model_molecule[n_obj][-1].tag = -bond_dict[bond]
#else:
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj][-1].tag = bond_dict[bond]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
n_centers = n_obj
#
#
##Now we do the F (SiX2H2)
for atom in chs1:
if atom.symbol == 'F':
#print'======================================='
#print 'F Atom ',atom.index, " finding SiH2X2 anchor points"
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
if bond_matrix[index,atom.index]:
model_molecule[n_obj] += chs1[index]
model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
model_molecule[n_obj][-1].tag = chs1[index].tag
#if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
# model_molecule[n_obj][-1].tag = -bond_dict[bond]
#else:
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj][-1].tag = bond_dict[bond]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
n_linkers = n_obj
##Now we do the N (triangles)
for atom in chs1:
if atom.symbol == 'N':
#print'======================================='
#print 'N Atom ',atom.index, " finding triangles"
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
if bond_matrix[index,atom.index]:
model_molecule[n_obj] += chs1[index]
model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
model_molecule[n_obj][-1].tag = chs1[index].tag
#if any(o != 0 for o in offset):
# #If we're going over a periodic boundary, we need to negate the tag
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
# model_molecule[n_obj][-1].tag = -bond_dict[bond]
#else:
# model_molecule[n_obj] += chs1[index]
# model_molecule[n_obj][-1].tag = bond_dict[bond]
# model_molecule[n_obj].positions[-1] = chs1.positions[index] + np.dot(offset, chs1.get_cell())
#
#
#
f = open('chs1.model','w')
g = open('control-mofgen.txt','w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' %('Number of objects =',n_obj+1))
f.write('%-20s\n' %('build = systre'))
f.write('%5s\n' %('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(chs1.get_cell()[0][0],
chs1.get_cell()[0][1],
chs1.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(chs1.get_cell()[1][0],
chs1.get_cell()[1][1],
chs1.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(chs1.get_cell()[2][0],
chs1.get_cell()[2][1],
chs1.get_cell()[2][2]))
g.write('%-20s\n' %('model = chs1'))
#
for obj in xrange(n_centers+1):
f.write('\n%-8s %-3d\n' %('Center: ', obj+1))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = rectangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('center =', names[0]))
for obj in xrange(n_centers+1,n_linkers+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = linear_triangle'))
#process positions to make it a bit more ideal
#for atom in model_molecule[obj]:
# #if atom.symbol == 'C':
# if atom.index != 0:
# model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
elif atom.symbol == 'F':
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
elif atom.symbol == 'H':
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Bq', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('linker =', names[1]))
#
for obj in xrange(n_linkers+1,n_obj+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = triangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,2.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('linker =', names[2]))
#
#
test_mol = Atoms()
for obj in model_molecule:
#for obj in xrange(n_linkers+1,n_obj+1): #triangles only
test_mol += model_molecule[obj]
test_mol.set_cell(chs1.get_cell())
test_mol.set_pbc(chs1.get_pbc())
write('test_model2.xyz',test_mol)
write('test_model2.cif',test_mol)
from ase.calculators.vasp import Vasp
from ase.lattice.spacegroup import crystal
import matplotlib.pyplot as plt
def primitive_from_conventional_cell(atoms, spacegroup=1, setting=1):
"""Returns primitive cell given an Atoms object for a conventional
cell and it's spacegroup."""
from ase.lattice.spacegroup import Spacegroup
from ase.utils.geometry import cut
sg = Spacegroup(spacegroup, setting)
prim_cell = sg.scaled_primitive_cell # Check if we need to transpose
return cut(atoms, a=prim_cell[0], b=prim_cell[1], c=prim_cell[2])
#Define the coordinates
a = 5.459
si_c = crystal('Si', [(0,0,0)], spacegroup=227, cellpar=[a, a, a, 90, 90, 90])
si = primitive_from_conventional_cell(si_c,spacegroup=227, setting=1)
# Define KPOINTS for special points
points = ibz_points['fcc']
G = points['Gamma']
X = points['X']
W = points['W']
K = points['K']
L = points['L']
#kpoints, x, X = get_bandpath(['L','G','W','K'], si.cell,10)
kpoints, x, X = get_bandpath([W, L, G, X, W, K], si.cell, npoints=60)
# Point names for plot axis
point_names = ['W','L','G','W','K']
# FROM HERE ON NO REAL INPUT IS NEEDED, UNLESS ONE WISHES TO
# CHANGE SOME VASP INCAR PARAMETERS
"Test the ase.utils.geometry module"
import numpy as np
import ase
from ase.lattice.spacegroup import crystal
from ase.utils.geometry import get_layers, cut, stack
np.set_printoptions(suppress=True)
al = crystal('Al', [(0,0,0)], spacegroup=225, cellpar=4.05)
# Cut out slab of 5 Al(001) layers
al001 = cut(al, nlayers=5)
correct_pos = np.array([[ 0. , 0. , 0. ],
[ 0. , 0.5, 0.2],
[ 0.5, 0. , 0.2],
[ 0.5, 0.5, 0. ],
[ 0. , 0. , 0.4],
[ 0. , 0.5, 0.6],
[ 0.5, 0. , 0.6],
[ 0.5, 0.5, 0.4],
[ 0. , 0. , 0.8],
[ 0.5, 0.5, 0.8]])
assert np.allclose(correct_pos, al001.get_scaled_positions())
# Check layers along 001
tags, levels = get_layers(al001, (0, 0, 1))
assert np.allclose(tags, [0, 1, 1, 0, 2, 3, 3, 2, 4, 4])
assert np.allclose(levels, [ 0., 2.025, 4.05, 6.075, 8.1])
def make_ntt(names,sizes):
#factor = sum(sizes) #dist0 + dist1
factor = sizes[0] +sizes[1]
factor = factor
a = 7.3485 * factor
# C -> rectangle (square), N => central triangles, O => outer triangles
ntt = crystal(['C', 'N', 'O'], [(0.0, 0.16667, 0.16667), (0.1668, 0.1668, 0.3332), (0.1111, 0.1111, 0.2222 )],
spacegroup=225, #Fm-3m
cellpar=[a, a, a, 90, 90, 90])
#write('test.xyz',ntt)
eps = 0.05
model_molecule={}
n_obj = -1 #initialise to -1 such that it can be indexed at start of add
n_tags = 0
#First detect global bonding
cov_rad=[]
for atom in ntt:
#cov_rad.append(covalent_radii[atom.number])
cov_rad.append(factor / 2)
print cov_rad
nlist = NeighborList(cov_rad,skin=0.1,self_interaction=False,bothways=True)
nlist.build(ntt)
#To sort out tags, we need to label each bond
nbond = 1
bond_matrix = np.zeros( (len(ntt),len(ntt)) )
pbc_bond_matrix = np.zeros( (len(ntt),len(ntt)) )
bond_dict = {}
for atom in ntt:
print "---------------------"
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
print atom.index, index, atom.symbol, ntt[index].symbol, offset, ntt.get_distance(atom.index,index,mic=True)
if atom.index < index:
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
#Now we need to find the same bond the other direction to get the offsets right
indices2,offsets2 = nlist.get_neighbors(index)
for i2,o2 in zip(indices2,offsets2):
if i2 == atom.index:
#print "sum of offsets = ", offset, o2, sum(offset + o2)
if sum(offset + o2) == 0: #same bond
this_bond = [index, atom.index]
for o in o2:
this_bond.append(o)
bond = tuple(this_bond)
print bond
bond_dict[bond] = nbond
nbond +=1
print nbond
for k,v in bond_dict.items():
print k,v
#Start with C (rectangles)
for atom in ntt:
if atom.symbol == 'C':
print'======================================='
print 'C Atom ',atom.index
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
model_molecule[n_obj][0].original_index = atom.index
model_molecule[n_obj][0].symbol = 'F'
indices, offsets = nlist.get_neighbors(atom.index)
#Just checking the symbols here
print indices
print offsets
symbols = ([ntt[index].symbol for index in indices])
symbol_string = ''.join(sorted([ntt[index].symbol for index in indices]))
#print symbol_string
#for i,o in zip(indices, offsets):
# print i,o
for index,offset in zip(indices,offsets):
print atom.index, index, offset
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
print bond_dict[bond]
if ntt[index].symbol == 'O': #C is only bound to O, (outer triangles)
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += ntt[index]
model_molecule[n_obj].positions[-1] = ntt.positions[index] + np.dot(offset, ntt.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += ntt[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[-1] = ntt.positions[index] + np.dot(offset, ntt.get_cell())
n_centers = n_obj
#
#
##Now we do the N (inner triangles)
for atom in ntt:
if atom.symbol == 'N':
#print'======================================='
#print 'N Atom ',atom.index, " finding edges"
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
print index, offset, ntt[index].symbol
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#if not bond_dict.has_key(bond):
#Then
if ntt[index].symbol == 'O':
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += ntt[index]
model_molecule[n_obj].positions[-1] = ntt.positions[index] + np.dot(offset, ntt.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += ntt[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[-1] = ntt.positions[index] + np.dot(offset, ntt.get_cell())
n_inner_triangle = n_obj
#
##Now we do the O (outer triangles)
for atom in ntt:
if atom.symbol == 'O':
#print'======================================='
#print 'N Atom ',atom.index, " finding edges"
n_obj+=1
model_molecule[n_obj] = Atoms()
model_molecule[n_obj] += atom
indices, offsets = nlist.get_neighbors(atom.index)
for index,offset in zip(indices,offsets):
print index, offset, ntt[index].symbol
this_bond = [atom.index, index]
for o in offset:
this_bond.append(o)
bond = tuple(this_bond)
#if not bond_dict.has_key(bond):
#Then
if ntt[index].symbol == 'N' or ntt[index].symbol =='C':
if any(o != 0 for o in offset):
#If we're going over a periodic boundary, we need to negate the tag
model_molecule[n_obj] += ntt[index]
model_molecule[n_obj].positions[-1] = ntt.positions[index] + np.dot(offset, ntt.get_cell())
model_molecule[n_obj][-1].tag = -bond_dict[bond]
else:
model_molecule[n_obj] += ntt[index]
model_molecule[n_obj][-1].tag = bond_dict[bond]
model_molecule[n_obj].positions[-1] = ntt.positions[index] + np.dot(offset, ntt.get_cell())
#
#
#
f = open('ntt.model','w')
g = open('control-mofgen.txt','w')
#Just for checking, now lets gather everything in the model_molecule dict into one big thing and print it
#test_mol = Atoms()
#for obj in model_molecule:
# test_mol += model_molecule[obj]
#write('test_model.xyz',test_mol)
#print n_centers, n_model, n_obj
#Headers and cell
f.write('%-20s %-3d\n' %('Number of objects =',n_obj+1))
f.write('%-20s\n' %('build = systre'))
f.write('%5s\n' %('Cell:'))
f.write('%8.3f %8.3f %8.3f \n' %
(ntt.get_cell()[0][0],
ntt.get_cell()[0][1],
ntt.get_cell()[0][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(ntt.get_cell()[1][0],
ntt.get_cell()[1][1],
ntt.get_cell()[1][2]))
f.write('%8.3f %8.3f %8.3f \n' %
(ntt.get_cell()[2][0],
ntt.get_cell()[2][1],
ntt.get_cell()[2][2]))
g.write('%-20s\n' %('model = ntt'))
#Now write stuff
for obj in xrange(n_centers+1):
f.write('\n%-8s %-3d\n' %('Center: ', obj+1))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = rectangle')) #Yep it's a rectangle
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('center =', names[0]))
for obj in xrange(n_centers+1,n_inner_triangle+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = triangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
g.write('%-9s %-50s\n' %('linker =', names[1]))
for obj in xrange(n_inner_triangle+1,n_obj+1):
f.write('\n%-8s %-3d\n' %('Linker: ', obj-n_centers))
f.write('%-3d\n' %(len(model_molecule[obj])))
f.write('%-20s\n' %('type = triangle'))
#process positions to make it a bit more ideal
for atom in model_molecule[obj]:
#if atom.symbol == 'C':
if atom.index != 0:
model_molecule[obj].set_distance(atom.index,0,1.0,fix=1)
for atom in model_molecule[obj]:
(x,y,z) = atom.position
#print atom.symbol, atom.position, atom.tag
if atom.tag:
f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % ('X', x, y, z, atom.tag))
#f.write('%-2s %15.8f %15.8f %15.8f %-4s\n' % (atom.symbol, x, y, z, atom.tag))
else:
f.write('%-2s %15.8f %15.8f %15.8f\n' % ('Q', x, y, z))
#f.write('%-2s %15.8f %15.8f %15.8f\n' % (atom.symbol, x, y, z))
if(len(names)) == 3:
g.write('%-9s %-50s\n' %('linker =', names[2]))
else:
g.write('%-9s %-50s\n' %('linker =', names[1]))
from ase.lattice.spacegroup import crystal
from gpaw import GPAW, PW
a = 4.0351 # Experimental lattice constant in Angstrom
Ecut = 250 # Energy cut off for PW calculation
k = 4 # Number of kpoints per each direction
# This gives the typical NaCl structure:
LiF = crystal(['Li', 'F'], [(0, 0, 0), (0.5, 0.5, 0.5)],
spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
calc = GPAW(mode=PW(Ecut), xc='LDA', kpts=(k, k, k), txt='LiF_out_gs.txt')
LiF.set_calculator(calc)
LiF.get_potential_energy()
# With the full diagonalization we calculate all the single particle states
# needed for the response calculation:
calc.diagonalize_full_hamiltonian(nbands=100)
calc.write('LiF_fulldiag.gpw', 'all')
if __name__ == '__main__':
'''
file = sys.argv[1]
q_dict = {'Cu':1, 'Sn':4, 'S':-2, 'Zn':2, 'In':3, 'O':-2}
str = io.read(file, format = 'vasp_out')
U = get_lattice_energy(str, q_dict)
Utot = np.sum(U)
import pickle
print Utot
f = open('madelung.pckl', 'w')
pickle.dump([Utot, U], f)
f.close()
'''
from ase.lattice.spacegroup import crystal
a = 4.6
c = 2.95
str =crystal(['Ti', 'O'], basis=[(0, 0, 0), (0.3, 0.3, 0.0)],
spacegroup=136, cellpar=[a, a, c, 90, 90, 90])
q_dict = {'Ti': 4, 'O':-2}
U = get_lattice_energy(str, q_dict)
print 'TiO2', U
a = 5.64
str = crystal(['Na', 'Cl'], [(0, 0, 0), (0.5, 0.5, 0.5)], spacegroup=225,
cellpar=[a, a, a, 90, 90, 90])
q_dict = {'Na': 1, 'Cl':-1}
U = get_lattice_energy(str, q_dict)
print 'NaCl', U
def wurtzite(species, cell_par=[2,2,6,90,90,120],repititions=[1,1,1]):
system = crystal((species),
basis=[(2./3.,1./3.,0),(2./3.,1./3.,5./8.)],
spacegroup=186, size = repititions, cellpar=cell_par)
return system
from ase.lattice.spacegroup import crystal
from gpaw import GPAW
from gpaw import PW
from gpaw.test import equal
name = 'quartz'
# no. 152 - trigonal
a = 5.032090
c = a * 1.0968533
p0 = (0.4778763, 0.0, 1. / 3.)
p1 = (0.4153076, 0.2531340, 0.2029893)
atoms = crystal(['Si', 'O'], basis=[p0, p1],
spacegroup=152, cellpar=[a, a, c, 90, 90, 120])
## with fractional translations
calc = GPAW(mode=PW(),
xc='LDA',
kpts=(3, 3, 3),
nbands=42,
symmetry={'symmorphic': False},
gpts=(20, 20, 24),
eigensolver='rmm-diis')
atoms.set_calculator(calc)
energy_fractrans = atoms.get_potential_energy()
assert(len(calc.wfs.kd.ibzk_kc) == 7)
assert(len(calc.wfs.kd.symmetry.op_scc) == 6)
print "n2:", n2 est_nnd = 2.5 # assume cubic packing to estimate lp from nnd, down 0.9 vpa = 0.95 * est_nnd * est_nnd * est_nnd # per cell vpc = abs(np.linalg.det(primc)) numatpc = len(elems) lp = pow(vpa * numatpc / vpc, 1 / 3.) print "initlp:", lp print "initvpa:", vpa lat0 = lp * primc mys = crystal(elems, poss, cell=lat0) mys.set_calculator(calc) epa0 = mys.get_potential_energy() / mys.get_number_of_atoms() vpa0 = mys.get_volume() / mys.get_number_of_atoms() print "epa0:", epa0 print "vpa0:", vpa0, "\n" from ase.units import kJ from ase.utils.eos import EquationOfState lestim = lat0 volumes = [] energies = [] elstr = el1 + el2 + '-' + str for x in np.linspace(0.98, 1.02, 5):
