def is_hbonded2(mybgf, atom1, atom2, d_crit=2.2):
"""
returns True if two atoms are h-bonded by a geometric definition.
This definition is introduced in Grishina, N., & Buch, V. (2004). J. Chem. Phys., 120(11), 5217.
20160608: Works only for O atoms.
"""
if not "O" in atom1.ffType or not "O" in atom2.ffType:
return False
d = np.array([atom1.x, atom1.y, atom1.z])
a = np.array([atom2.x, atom2.y, atom2.z])
if mybgf.CRYSTX:
pbc = mybgf.CRYSTX[:3]
else:
pbc = 0
# A1-H ... A2
for ano in atom1.CONECT:
atom = mybgf.getAtom(ano) # this should be an H atom
x = np.array([atom.x, atom.y, atom.z])
if pbc:
dist = nu.pbc_dist(x, a, pbc)
else:
dist = nu.dist(x, a)
if 1e-5 < dist < d_crit:
return x
# A1 ... H-A2
for ano in atom2.CONECT:
atom = mybgf.getAtom(ano) # this should be an H atom
x = np.array([atom.x, atom.y, atom.z])
if pbc:
dist = nu.pbc_dist(x, a, pbc)
else:
dist = nu.dist(x, a)
if 1e-5 < dist < d_crit:
return x
return []
def calc_hbonds():
# variables
A = []
D = []
hbonds = []
d_crit = 3.5
a_crit = 30.0
for atom in mybgf.a:
if selection:
if "O" in atom.ffType and eval(selection):
A.append(atom)
if "O" in atom.ffType and eval(selection):
D.append(atom)
else:
if "O" in atom.ffType:
A.append(atom)
if "O" in atom.ffType:
D.append(atom)
if not len(A) or not len(D):
nu.die(
"There are no atoms which can make H_bond (O atoms so far)!"
)
# find nearest neighbor from D atom
# calculate hbonds
for d_atom in D:
d = np.array([d_atom.x, d_atom.y, d_atom.z])
for a_atom in A:
a = np.array([a_atom.x, a_atom.y, a_atom.z])
if 1e-5 < nu.pbc_dist(a, d, mytrj.pbc[t]) < d_crit:
for ano in d_atom.CONECT:
h_atom = mybgf.getAtom(ano)
h = np.array([h_atom.x, h_atom.y, h_atom.z])
u = h - d
v = a - d
theta = np.dot(u, v) / norm(u) / norm(v)
theta = np.degrees(arccos(theta))
if theta < a_crit:
hbonds.append([
d_atom.aNo, a_atom.aNo, d_atom.z, a_atom.z
])
#donors.append(d_atom.aNo)
#acceptors.append(a_atom.aNo)
#hydrogens.append(h_atom.aNo)
#distances.append(dist)
return hbonds
def calc_hbonds():
# variables
A = []
D = []
hbonds = []
d_crit = 3.5
a_crit = 30.0
for atom in mybgf.a:
if selection:
if "O" in atom.ffType and eval(selection):
A.append(atom)
if "O" in atom.ffType and eval(selection):
D.append(atom)
else:
if "O" in atom.ffType:
A.append(atom)
if "O" in atom.ffType:
D.append(atom)
if not len(A) or not len(D):
nu.die(
"There are no atoms which can make H_bond (O atoms so far)!"
)
# calculate hbonds
for d_atom in D:
d = np.array([d_atom.x, d_atom.y, d_atom.z])
neigh_anos = bt.get_neighbors_aNo(A,
d,
r=d_crit,
pbc=mytrj.pbc[t])
for ano in neigh_anos:
a_atom = mybgf.getAtom(ano)
h = bt.is_hbonded2(mybgf, d_atom,
a_atom) # returns hbonded H coord
if len(h) != 0:
a = np.array([a_atom.x, a_atom.y, a_atom.z])
dist = nu.pbc_dist(a, d, mytrj.pbc[t])
u = h - d
v = a - d
theta = np.dot(u, v) / norm(u) / norm(v)
theta = np.degrees(arccos(theta))
hbonds.append(
[d_atom.aNo, a_atom.aNo, d, a, dist, theta])
return hbonds
def is_hbonded(mybgf, atom1, atom2, d_crit=3.5, a_crit=30.0):
"""
returns True if two atoms are h-bonded with a popular geometric definition d(O..O) = 3.5 and A(H-O-O) < 30'
20160529: Works only for O atoms.
"""
from numpy import arccos
from numpy.linalg import norm
if not "O" in atom1.ffType or not "O" in atom2.ffType:
return False
d = np.array([atom1.x, atom1.y, atom1.z])
a = np.array([atom2.x, atom2.y, atom2.z])
if 1e-5 < nu.pbc_dist(a, d, mybgf.CRYSTX[:3]) < d_crit:
for ano in atom1.CONECT:
# atom1: donor, atom2: acceptor
h_atom = mybgf.getAtom(ano)
h = np.array([h_atom.x, h_atom.y, h_atom.z])
u = h - d
v = a - d
theta = np.dot(u, v) / norm(u) / norm(v)
theta = np.degrees(arccos(theta))
if theta < a_crit:
return True
for ano in atom2.CONECT:
# atom2: donor, atom1: acceptor
h_atom = mybgf.getAtom(ano)
h = np.array([h_atom.x, h_atom.y, h_atom.z])
u = h - d
v = a - d
theta = np.dot(u, v) / norm(u) / norm(v)
theta = np.degrees(arccos(theta))
if theta < a_crit:
return True
return False
def calc_hbonds():
hbonds = []
d_crit = 3.6
if selection:
for atom in mybgf.a:
if "O" in atom.ffType and eval(selection):
A.append(atom)
if "O" in atom.ffType and eval(selection):
D.append(atom)
# calculate hbonds
for d_atom in D:
d = np.array([d_atom.x, d_atom.y, d_atom.z]) # donor coord
neigh_anos = bt.get_neighbors_aNo(A,
d,
r=d_crit,
pbc=mytrj.pbc[t],
k=6)
for ano in neigh_anos:
a_atom = mybgf.getAtom(ano)
a = np.array([a_atom.x, a_atom.y,
a_atom.z]) # acceptor coord
dist = nu.pbc_dist(a, d, mytrj.pbc[t])
if dist > 2.0:
for ano in d_atom.CONECT:
h_atom = mybgf.getAtom(ano)
h = np.array([h_atom.x, h_atom.y, h_atom.z])
u = h - d
v = a - d
theta = np.dot(u, v) / norm(u) / norm(v)
#theta = np.degrees(arccos(theta))
if -0.17364817766693034885171662676931 < theta < 1.0:
hbonds.append([dist, np.degrees(theta)])
return hbonds
def calc_hbonds(mybgf, selection=""):
# variables
A = []
D = []
hbonds = []
d_crit = 3.5
a_crit = 30.0
for atom in mybgf.a:
if selection:
if "O" in atom.ffType and eval(selection):
A.append(atom)
if "O" in atom.ffType and eval(selection):
D.append(atom)
else:
if "O" in atom.ffType:
A.append(atom)
if "O" in atom.ffType:
D.append(atom)
if not len(A) or not len(D):
nu.die("There are no atoms which can make H_bond (O atoms so far)!")
# calculate hbonds
for d_atom in D:
d = np.array([d_atom.x, d_atom.y, d_atom.z]) # donor coord
neigh_anos = bt.get_neighbors_aNo(A,
d,
r=d_crit,
pbc=mytrj.pbc[t],
k=6)
donors = [d_atom.aNo] + d_atom.CONECT
for ano in neigh_anos:
a_atom = mybgf.getAtom(ano)
a = np.array([a_atom.x, a_atom.y, a_atom.z]) # acceptor coord
acceptors = [a_atom.aNo] + a_atom.CONECT
for ano in d_atom.CONECT:
h_atom = mybgf.getAtom(ano)
h = np.array([h_atom.x, h_atom.y, h_atom.z])
u = h - d
v = a - d
theta = np.dot(u, v) / norm(u) / norm(v)
theta = np.degrees(arccos(theta))
if theta < a_crit: # HBond exists
dist = nu.pbc_dist(a, d, mytrj.pbc[t])
dist_ah = nu.pbc_dist(d, h, mytrj.pbc[t])
# E_vdw
sigma_r = O_sigma / dist
sigma_r_6 = sigma_r**6
sigma_r_12 = sigma_r**12
E_vdw = 4.0 * O_epsilon * (sigma_r_12 - sigma_r_6)
# E_vdw in kcal/mol
# E_coul
E_coul = 0.0
for i, j in itertools.product(donors, acceptors):
atom1 = mybgf.getAtom(i)
atom2 = mybgf.getAtom(j)
a1 = [atom1.x, atom1.y, atom1.z]
a2 = [atom2.x, atom2.y, atom2.z]
dist_ij = nu.pbc_dist(a1, a2, mytrj.pbc[t])
E_coul += 332.06371 * atom1.charge * atom2.charge / dist_ij # E_coul in kcal/mol
# E_hbond
E_hbond = E_coul + E_vdw # E_hbond = E_vdw + E_coul
# update for v4
# angle between H-O-H plane and O..O vector
H1 = mybgf.getAtom(d_atom.CONECT[0])
h1 = [H1.x, H1.y, H1.z] # H1
H2 = mybgf.getAtom(d_atom.CONECT[1])
h2 = [H2.x, H2.y, H2.z] # H2
p = d - h1
q = d - h2
n = np.cross(p, q) # normal vector of the H1-O-H2 plane
m = a - d
# O..O vector
alpha = np.dot(n, m) / norm(n) / norm(m)
alpha = np.degrees(arcsin(
alpha)) # angle between H-O-H plane and O..O vector
hbonds.append([
d_atom.aNo, a_atom.aNo, d, a, dist, theta,
[E_coul, E_vdw, E_hbond], dist_ah, alpha
]) # v4
return hbonds
def make_infinite(self, *args):
'''
args: filename to save
'''
print("CNT.py: make_infinite()")
if len(args) > 1:
nu.warn("make_infinite(): Too many arguments.")
if not self.isPBCadjusted:
nu.warn(
"make_infinite(): You are trying to make infinite NT without adjusting PBC."
)
#return 0;
print("\t* Found " + str(len(self.NTatoms)) +
" atoms for the nanotube.")
print("\t* Found " + str(len(self.WATatoms)) + " atoms for water.")
if self.type == "BNT":
self.detach_hydrogen()
aNo_pair = []
for atom in self.NTatoms:
if len(atom.CONECT) == 3:
continue
x = np.array([atom.x, atom.y, atom.z])
min_atom_aNo = 100000
# placeholder
min_atom_d = 10000.0
for atom2 in self.NTatoms:
if (not atom2.aNo in atom.CONECT) and len(atom2.CONECT) == 2:
if (atom.rName == atom2.rName) and (
self.type == "CNT" or atom.ffType != atom2.ffType):
y = np.array([atom2.x, atom2.y, atom2.z])
if -1.0 < ((x - y) * self.axismask).sum() < 1.0:
continue
# prevent adjacent atoms
d = nu.pbc_dist(x, y, self.pbc)
if d < min_atom_d:
min_atom_aNo = atom2.aNo
min_atom_d = d
aNo_pair.append([atom.aNo, min_atom_aNo])
for i in aNo_pair:
self.bgfmodel.connectAtoms(i[0], i[1])
self.check_connectivity()
self.bgfmodel.renumber()
if len(args) == 0:
value = raw_input(
"Do you want to save the infinite Nanotube structure to BGF file [N]? "
)
if "y" in value.lower():
filename = self.model_filename[:-4] + ".infinite.bgf"
value = raw_input("Filename to save [" + filename +
"]? ") or filename
self.bgfmodel.saveBGF(value)
elif len(args) == 1:
self.bgfmodel.saveBGF(args[0])
def countWaterCNT(bgf_file,
trj_file,
d_crit=3.5,
selection='',
nsample=0,
silent=False):
### init
# constants
deg_109p47 = math.radians(109.47)
# variables
timestep = 0
l_timestep = []
line = []
n_header = 0
avg_angles = []
avg_diheds = []
bin = np.arange(0.0, 181.0, 1.0)
t1 = 0
t2 = 0
# clock
myBGF = bgf.BgfFile(bgf_file)
myTRJ = open(trj_file)
myTRJ.seek(0)
myDAT = open(bgf_file[:-4] + ".AOP.dat", "w")
myDAT.write("#timestep\tAOP\tF4\n")
# how many steps to go?
#mytrj = lt.lammpstrj(trj_file)
mytrj = Trj(trj_file)
l_timestep = mytrj.load()
n_timestep = len(l_timestep)
l_timestep.sort()
requested_timesteps = l_timestep[-nsample:]
print(
"Using neighboring water distance criteria %4.1f A (should be consistent with the coordination number)"
% d_crit)
print("The trajectory contains " + str(n_timestep) + " timesteps.")
# Find header of the trajectory file
while 1:
templine = myTRJ.readline()
line.append(templine.strip('\n').strip('ITEM: '))
n_header += 1
if "ITEM: ATOMS" in templine:
break
# INITIAL trajectory information
timestep = int(line[1])
natoms = int(line[3])
boxsize = [
line[5].split(' ')[0], line[5].split(' ')[1], line[6].split(' ')[0],
line[6].split(' ')[1], line[7].split(' ')[0], line[7].split(' ')[1]
]
boxsize = [float(i) for i in boxsize]
keywords = line[8].strip('ATOMS ')
# for every shot in the trajectory file update BGF and manipulate
dumpatom = get_line(trj_file)
processed_step = 0
t1 = t2 = 0
elapsed_time = 0
while 1:
### Show progress
t1 = time.time()
remaining_time = elapsed_time * (len(requested_timesteps) -
processed_step)
sys.stdout.write('\r' + "Reading timestep.. " + str(timestep) +
" (Remaining time: " +
"{0:4.1f}".format(remaining_time) + " seconds, " +
"{0:4.1f} minutes".format(remaining_time / 60) + ")")
sys.stdout.flush()
### Read
try:
chunk = [next(dumpatom) for i in range(natoms + n_header)]
except StopIteration:
break
timestep = int(chunk[1])
natoms = int(chunk[3])
boxsize = [
chunk[5].split(' ')[0], chunk[5].split(' ')[1],
chunk[6].split(' ')[0], chunk[6].split(' ')[1],
chunk[7].split(' ')[0], chunk[7].split(' ')[1]
]
boxsize = [float(i) for i in boxsize]
boxsize = [(boxsize[1] - boxsize[0]), (boxsize[3] - boxsize[2]),
(boxsize[5] - boxsize[4])]
keywords = chunk[8].split('ATOMS ')[1].strip('\n').split(' ')
if not timestep in requested_timesteps:
continue
### update myBGF with trajectory information ###
natom_bgf = len(myBGF.a) # number of atoms in BGF file
if not natom_bgf == natoms:
nu.die(
"Number of atoms in trajectory file does not match with BGF file."
)
mode = ""
if 'xs' in keywords or 'ys' in keywords or 'zs' in keywords:
mode = 'scaled'
elif 'x' in keywords or 'y' in keywords or 'z' in keywords:
mode = 'normal'
elif 'xu' in keywords or 'yu' in keywords or 'zu' in keywords:
mode = 'unwrapped'
# actual coordinate
coordinfo = chunk[9:]
# assume that coordinfo is similar to ['id', 'type', 'xs', 'ys', 'zs', 'ix', 'iy', 'iz']
for atomline in coordinfo:
atomcoord = atomline.split(' ')
atom = myBGF.getAtom(int(atomcoord[0]))
if mode == 'scaled':
atom.x = float(atomcoord[2]) * boxsize[0]
atom.y = float(atomcoord[3]) * boxsize[1]
atom.z = float(atomcoord[4]) * boxsize[2]
elif mode == 'unwrapped':
atom.x = float(atomcoord[2])
atom.y = float(atomcoord[3])
atom.z = float(atomcoord[4])
elif mode == 'normal':
try:
ix_index = keywords.index('ix')
iy_index = keywords.index('iy')
iz_index = keywords.index('iz')
except ValueError:
nu.warn(
"No image information no the trajectory file. Will be treated as unwrapped."
)
atom.x = float(atomcoord[2])
atom.y = float(atomcoord[3])
atom.z = float(atomcoord[4])
else:
atom.x = (int(atomcoord[ix_index]) * boxsize[0]) + float(
atomcoord[2])
atom.y = (int(atomcoord[iy_index]) * boxsize[1]) + float(
atomcoord[3])
atom.z = (int(atomcoord[iz_index]) * boxsize[2]) + float(
atomcoord[4])
try:
for i in range(0, 3):
myBGF.CRYSTX[i] = boxsize[i]
except:
pass
# apply periodic condition
myBGF = bgftools.periodicMoleculeSort(myBGF, myBGF.CRYSTX, silent=True)
### myBGF update complete! ###
# get water OW
O = []
anos_O = []
for atom in myBGF.a:
if selection:
if "O" in atom.ffType and eval(selection):
O.append(atom)
anos_O.append(atom.aNo)
else:
if "O" in atom.ffType:
O.append(atom)
anos_O.append(atom.aNo)
if not len(O):
nu.die("There are no O atoms which satisfies %s!" % selection)
### calculate AOP and F4
sys.stdout.write('AOP..... ')
sys.stdout.flush()
coords = []
anos = []
for atom in O:
coords.append([atom.x, atom.y, atom.z])
anos.append(atom.aNo)
pbc = np.array(myBGF.CRYSTX[:3])
coords = np.array(coords)
tree = pkdtree.PeriodicKDTree(
pbc, coords) # KDtree for distance calculation
# analyze local water structures for a timestep
n_neighbors = []
angles = []
diheds = []
for atom in O:
# local variables
# find neighbors
neighbors = []
# list of O atoms near centerO
centerO = np.array([atom.x, atom.y, atom.z])
d, ndx = tree.query(centerO, k=6)
index = np.where((d >= 1e-4) & (d <= d_crit)) # discard self
for i in ndx[index]:
neighbors.append(myBGF.getAtom(anos[i]))
# calculate O1-O-O2 angle
for i, j in itertools.combinations(neighbors, 2):
if not "O" in i.ffType or not "O" in j.ffType:
nu.die("Wrong atom found.")
x = [i.x, i.y, i.z]
y = [j.x, j.y, j.z]
pbc_dist = nu.pbc_dist(x, y, pbc)
dist = nu.dist(x, y)
if abs(pbc_dist - dist) > 0.1:
continue
# discard atoms over pbc boundaries
# angle
angle = nu.angle(x, centerO, y, radians=False)
angles.append(angle)
n_neighbors.append(
len(neighbors)) # number of neighboring water molecules
# calculate dihedral
for i in neighbors:
# find aNos of H located farthest among all combinations
hO_anos = atom.CONECT
hi_anos = i.CONECT
max_dist_pair = []
max_dist = 0.0
for k, l in itertools.product(hO_anos, hi_anos):
h1 = myBGF.getAtom(k) # H atom connected with atom
h2 = myBGF.getAtom(l) # H atom connected with i
dist = bgf.distance(h1, h2)
if dist > max_dist:
max_dist = dist
max_dist_pair = [
h1, h2
] # now we have two H atoms in maximum distance connected with atom and i
# dihedral angle
phi = bgf.dihedral(max_dist_pair[0],
atom,
i,
max_dist_pair[1],
radians=False)
diheds.append(phi)
hist_angle, _ = np.histogram(angles, bins=bin, normed=True)
hist_dihed, _ = np.histogram(diheds, bins=bin, normed=True)
avg_angles.append(hist_angle)
avg_diheds.append(hist_dihed)
sys.stdout.write(
'Done ')
sys.stdout.flush()
# write output
processed_step += 1
t2 = time.time() # time mark
elapsed_time = t2 - t1
avg_angles = np.mean(np.array(avg_angles), axis=0)
avg_diheds = np.mean(np.array(avg_diheds), axis=0)
#print(avg_diheds)
myDAT.write("#angles population\n")
for index, i in enumerate(avg_angles):
myDAT.write("%8.2f %8.5f\n" % (_[index], avg_angles[index]))
myDAT.write("\n\n")
myDAT.write("#diheds population\n")
for index, i in enumerate(avg_diheds):
myDAT.write("%8.2f %8.5f\n" % (_[index], avg_diheds[index]))
myDAT.close()
print('')
return 1
if len(sys.argv) < 2:
print(usage)
sys.exit(0)
bgffile = bgf.BgfFile(sys.argv[1])
if sys.argv[2]:
delta = float(sys.argv[2])
else:
delta = 0.001
c = [atom for atom in bgffile.a if "C_2G" in atom.ffType]
dist = []
for atom in tqdm.tqdm(c, ncols=120, desc="Calculating"):
x = [atom.x, atom.y, atom.z]
for ano in atom.CONECT:
atom2 = bgffile.getAtom(ano)
y = [atom2.x, atom2.y, atom2.z]
dist.append(nu.pbc_dist(x, y, bgffile.CRYSTX[:3]))
dist = np.array(dist)
if delta < (dist.max() - dist.min()):
print(dist.min(), dist.max(), dist.max()-dist.min())
bin = np.arange(dist.min(), dist.max(), delta)
distr, _ = np.histogram(dist, bins=bin)
norm_distr = distr / float(distr.sum())
pprint(norm_distr)
else:
print("average: %s, stdev: %s" % (dist.mean(), dist.std()))
def calc_hbonds():
# variables
A = []
D = []
hbonds = []
d_crit = 3.5
a_crit = 30.0
for atom in mybgf.a:
if selection:
if "O" in atom.ffType and eval(selection):
A.append(atom)
if "O" in atom.ffType and eval(selection):
D.append(atom)
else:
if "O" in atom.ffType:
A.append(atom)
if "O" in atom.ffType:
D.append(atom)
if not len(A) or not len(D):
nu.die(
"There are no atoms which can make H_bond (O atoms so far)!"
)
# calculate hbonds
for d_atom in D:
d = np.array([d_atom.x, d_atom.y, d_atom.z]) # donor coord
neigh_anos = bt.get_neighbors_aNo(A,
d,
r=d_crit,
pbc=mytrj.pbc[t],
k=6)
donors = [d_atom.aNo] + d_atom.CONECT
for ano in neigh_anos:
a_atom = mybgf.getAtom(ano)
a = np.array([a_atom.x, a_atom.y,
a_atom.z]) # acceptor coord
acceptors = [a_atom.aNo] + a_atom.CONECT
for ano in d_atom.CONECT:
h_atom = mybgf.getAtom(ano)
h = np.array([h_atom.x, h_atom.y, h_atom.z])
u = h - d
v = a - d
theta = np.dot(u, v) / norm(u) / norm(v)
theta = np.degrees(arccos(theta))
if theta < a_crit:
dist = nu.pbc_dist(a, d, mytrj.pbc[t])
dist_dh = nu.pbc_dist(d, h, mytrj.pbc[t])
# E_vdw
sigma_r = O_sigma / dist
sigma_r_6 = sigma_r**6
sigma_r_12 = sigma_r**12
E_vdw = 4.0 * O_epsilon * (sigma_r_12 - sigma_r_6)
# Evdw in kcal/mol
# E_coul
E_coul = 0.0
for i, j in itertools.product(donors, acceptors):
atom1 = mybgf.getAtom(i)
atom2 = mybgf.getAtom(j)
a1 = [atom1.x, atom1.y, atom1.z]
a2 = [atom2.x, atom2.y, atom2.z]
dist_ij = nu.pbc_dist(a1, a2, mytrj.pbc[t])
E_coul += 332.06371 * atom1.charge * atom2.charge / dist_ij
#E_coul /= 2.0
E_hbond = E_coul + E_vdw # E_hbond = E_vdw + E_coul
#print("e_coul: %f, e_coul2: %f, E_coul: %f, E_vdw: %f, E_hbond: %f, O-O dist: %f, O-H dist: %f" % (e_coul, e_coul2, E_coul, E_vdw, E_hbond, dist, dist_a_dh))
#print("E_coul: %f, E_vdw: %f, E_hbond: %f, O-O dist: %f" % (E_coul, E_vdw, E_hbond, dist))
#hbonds.append([d_atom.aNo, a_atom.aNo, d, a, dist, theta, [E_coul, E_vdw, E_hbond]])
hbonds.append([
d_atom.aNo, a_atom.aNo, d, a, dist, theta,
[E_coul, E_vdw, E_hbond], dist_dh
])
return hbonds
if "S" in atom.ffType:
if atom.z > avg_mo_z:
atom.ffType = "S_3a"
else:
atom.ffType = "S_3b"
# remove infinite boundary
n_del = 0
for atom in tqdm.tqdm(moslayer.a, ncols=120, desc='Removing pbc bonds'):
a = [atom.x, atom.y, atom.z]
connected_ano = atom.CONECT
for ano in connected_ano:
atom2 = moslayer.getAtom(ano)
a2 = [atom2.x, atom2.y, atom2.z]
dist = nu.dist(a, a2)
pbc_dist = nu.pbc_dist(a, a2, moslayer.CRYSTX[:3])
if dist != pbc_dist:
moslayer.disconnect(moslayer.a2i[atom.aNo],
moslayer.a2i[atom2.aNo])
n_del += 1
print("%d bonds are disconnected." % n_del)
# remove infinite boundary
n_del = 0
for atom in tqdm.tqdm(moslayer.a, ncols=120, desc='Removing pbc bonds 2'):
a = [atom.x, atom.y, atom.z]
connected_ano = atom.CONECT
for ano in connected_ano:
atom2 = moslayer.getAtom(ano)
a2 = [atom2.x, atom2.y, atom2.z]
dist = nu.dist(a, a2)
def make_infinite(mybgf):
def calc_bond_dist(pbc=False):
dist = []
for atom in mybgf.a:
if not "C_2G" in atom.ffType:
continue
for ano in atom.CONECT:
atom2 = mybgf.getAtom(ano)
if not "C_2G" in atom2.ffType:
continue
if pbc:
dist.append(bgf.pbc_distance(atom, atom2,
mybgf.CRYSTX[:3]))
else:
dist.append(bgf.distance(atom, atom2))
return np.average(dist), np.std(dist)
distance, _ = calc_bond_dist()
# TODO: need to distinguish armchair and zigzag boundaries
minmax_x = bgftools.atoms_minmax(mybgf,
"x",
selection="'C_2G' in atom.ffType")
minmax_y = bgftools.atoms_minmax(mybgf,
"y",
selection="'C_2G' in atom.ffType")
pbc_x = (minmax_x[1] - minmax_x[0]) + distance * np.cos(
np.radians(30)) # in 5nm x 5nm graphene, x boundaries are armchair
pbc_y = (minmax_y[1] - minmax_y[0]
) + distance # in 5nm x 5nm graphene, y boundaries are zigzag
mybgf.PERIOD = "111"
mybgf.AXES = "ZYX"
mybgf.SGNAME = "P 1 1 1"
mybgf.CELLS = [-1, 1, -1, 1, -1, 1]
mybgf.CRYSTX = [pbc_x, pbc_y, 10.0, 90.0, 90.0, 90.0]
print("Assigning new pbc: %s" % mybgf.CRYSTX)
# init
aNo_pair = []
pbc = mybgf.CRYSTX[:3]
edge_atoms = []
# loop
for atom in tqdm(mybgf.a, ncols=80, miniters=100, desc="Analyzing atoms"):
if not "C" in atom.ffType:
continue
if len(atom.CONECT) == 3:
continue
x = np.array([atom.x, atom.y, atom.z])
min_atom_aNo = 100000
# placeholder
min_atom_d = 10000.0
for atom2 in mybgf.a:
if len(atom2.CONECT) == 3:
continue
if atom.aNo != atom2.aNo:
if (not atom2.aNo in atom.CONECT) and len(
atom2.CONECT) != 3 and (atom.rName == atom2.rName):
y = np.array([atom2.x, atom2.y, atom2.z])
d = nu.pbc_dist(x, y, pbc)
if d < min_atom_d:
min_atom_aNo = atom2.aNo
min_atom_d = d
#aNo_pair.append([atom.aNo, min_atom_aNo])
if min_atom_aNo == 100000:
nu.die("Failed to find the closest atom for atom number " +
str(atom.aNo))
mybgf.connectAtoms(atom.aNo, min_atom_aNo)
#for i in aNo_pair:
# mybgf.connectAtoms(i[0], i[1])
check_connectivity()
# check bond distance stdev
_, stdev = calc_bond_dist(pbc=True)
if stdev <= 1e5:
print("The structure seems to have regular distance over pbc.")
else:
nu.die("PBC assignment does not give a regular distances over pbc.")
if out_file == "":
filename = bgf_file.split(".bgf")[0] + ".infinite.bgf"
else:
filename = out_file
value = raw_input("Filename to save [" + filename + "]? ") or filename
mybgf.saveBGF(value)
def hbonds(mybgf, selection = ""):
'''
This function calculates Hydrogen bonds(hbonds) between O(donor) and O(acceptor), especially for water molecules.
Input:
- bgf.BgfFile mybgf
- string selection: a region to search donor and acceptor atoms in mybgf
Output:
- int n_sel_atoms: number of hbond-able atoms in the selection region
- list hbonds: self-descriptive
'''
# variables
pbc = mybgf.CRYSTX[:3]
d_crit = 3.5; a_crit = 30.0 # Chandler's criteria
if selection:
A = [atom for atom in mybgf.a if "O" in atom.ffType and eval(selection)]
D = [atom for atom in mybgf.a if "O" in atom.ffType and eval(selection)]
else:
A = [atom for atom in mybgf.a if "O" in atom.ffType]
D = [atom for atom in mybgf.a if "O" in atom.ffType]
if not len(A) or not len(D):
nu.warn("There are no atoms which can make hbonds (O atoms so far)!")
return
# calculate hbonds
hbonds = [];
for d_atom in D:
d = np.array([d_atom.x, d_atom.y, d_atom.z]) # donor coord
neigh_anos = bt.get_neighbors_aNo(A, d, r=d_crit, pbc=pbc, k=5)
donors = [d_atom.aNo] + d_atom.CONECT
for ano in neigh_anos:
a_atom = mybgf.getAtom(ano)
a = np.array([a_atom.x, a_atom.y, a_atom.z]) # acceptor coord
acceptors = [a_atom.aNo] + a_atom.CONECT
for ano in d_atom.CONECT:
h_atom = mybgf.getAtom(ano)
h = np.array([h_atom.x, h_atom.y, h_atom.z])
u = h - d; v = a - d;
theta = np.dot(u, v) / norm(u) / norm(v); theta = np.degrees(arccos(theta))
if theta < a_crit: # HBond exists
# calculate pair energy as Hbond energy
dist = nu.pbc_dist(a, d, pbc)
dist_ah = nu.pbc_dist(d, h, pbc)
# E_vdw
sigma_r = O_sigma / dist; sigma_r_6 = sigma_r**6; sigma_r_12 = sigma_r**12
E_vdw = 4.0 * O_epsilon * (sigma_r_12 - sigma_r_6); # E_vdw in kcal/mol
# E_coul
E_coul = 0.0
for i, j in itertools.product(donors, acceptors):
atom1 = mybgf.getAtom(i)
atom2 = mybgf.getAtom(j)
a1 = [atom1.x, atom1.y, atom1.z]
a2 = [atom2.x, atom2.y, atom2.z]
dist_ij = nu.pbc_dist(a1, a2, pbc)
E_coul += 332.06371 * atom1.charge * atom2.charge / dist_ij # E_coul in kcal/mol
# E_hbond
E_hbond = E_coul + E_vdw # E_hbond = E_vdw + E_coul
'''
# calculate dreiding style hbond energy: http://lammps.sandia.gov/doc/pair_hbond_dreiding.html
# REMARK: tested on bulk water, ice, and confined water between MoS2 but achieved suspicious values:
# 6.0 $\AA$ maximum: -7.925 kcal/mol
# 8.0 $\AA$ maximum: -7.875 kcal/mol
# 11.0 $\AA$ maximum: -8.025 kcal/mol
# ice maximum: -8.325 kcal/mol
# water maximum: -7.775 kcal/mol
sigma = 2.75 # in A
epsilon = 9.0 # in kcal/mol
u = d - h; v = a - h; cos_theta = np.dot(u, v) / norm(u) / norm(v); #cos_theta = np.cos(theta)
sigma_r = sigma / dist; sigma_r_2 = sigma_r**2; sigma_r_12 = sigma_r_2**6; sigma_r_10 = sigma_r_2**5
E_hbond = epsilon * ( 5 * sigma_r_12 - 6 * sigma_r_10 ) * cos_theta**4
'''
hbonds.append([d_atom.aNo, a_atom.aNo, dist, theta, E_hbond]) # v5
return hbonds