def molecular_frame_transformation(atomlist):
"""
The molecule is shifted to the center of mass and its principle axes of inertia are aligned
with the coordinate axes. This standard orientation defines the molecular frame.
The translation vector and Euler angles needed to transform the geometry from the
molecular frame to the original frame are also returned.
Returns:
========
atomlist_std: molecular geometry in standard orientation
(a,b,g): Euler angles in z-y-z convention
cm: 3D vector with center of mass
"""
pos = XYZ.atomlist2vector(atomlist)
masses = AtomicData.atomlist2masses(atomlist)
# shift center of mass to origin
Nat = len(atomlist)
pos_std = np.zeros(pos.shape)
cm = center_of_mass(masses, pos)
for i in range(0, Nat):
pos_std[3*i:3*i+3] = pos[3*i:3*i+3] - cm
(a,b,g) = euler_angles_inertia(masses, pos_std)
R = EulerAngles2Rotation(a,b,g)
for i in range(0, Nat):
pos_std[3*i:3*i+3] = np.dot(R, pos_std[3*i:3*i+3])
atomlist_std = XYZ.vector2atomlist(pos_std, atomlist)
# The MolecularCoord module uses a strange convention for Euler angles.
# Therefore we extract the Euler angles in z-y-z convention directly
# from the rotation matrix, that rotates the molecule from the standard
# orientation into the original orientation
Rinv = R.transpose()
a,b,g = rotation2EulerAngles(Rinv, convention="z-y-z")
return atomlist_std, (a,b,g), cm
def run_gaussian(atomlist, directory="."):
"""
run Gaussian input script in `neb.gjf` and read energy and gradient
from checkpoing file `grad.fchk`.
Parameters
----------
atomlist: list of tuples with atomic numbers and cartesian positions (Zat,[x,y,z])
for each atom
directory: directory where the calculation should be performed
Returns
-------
en : total energies of ground state (in Hartree)
grad : gradient of total energy (in a.u.)
"""
# create directory if it does not exist already
os.system("mkdir -p %s" % directory)
os.system("cp neb.gjf %s/neb.gjf" % directory)
# update geometry
XYZ.write_xyz("%s/geometry.xyz" % directory, [atomlist])
# remove number of atoms and comment
os.system("cd %s; tail -n +3 geometry.xyz > geom" % directory)
# calculate electronic structure
ret = os.system(r"cd %s; g09 < neb.gjf > neb.out" % directory)
ret &= os.system(r"cd %s; formchk grad.chk >> neb.out" % directory)
assert ret == 0, "Return status = %s, error in Gaussian calculation, see %s/neb.out!" % (
ret, directory)
# read checkpoint files
data = Checkpoint.parseCheckpointFile("%s/grad.fchk" % directory)
en = data["_Total_Energy"]
grad = data["_Cartesian_Gradient"]
return en, grad
def save_step():
"""function is called after each minimization"""
scan_coord = self.IC.coordinate_value(xi, IJKL)
print("current value of scan coordinate : %s" % scan_coord)
if i == 0:
mode = "w"
else:
mode = "a"
# save relaxed geometry of step i
XYZ.write_xyz(self.xyz_scan, [atomlist],
title="charge=%s energy=%s" %
(self.geom_kwds.get("charge", 0), self.enI),
mode=mode)
# save table with energies along scan
fh = open(self.dat_scan, mode)
if i == 0:
# write header
print("# Relaxed scan along %s defined by atoms %s" %
(coord_type[typ], [I + 1 for I in IJKL]),
file=fh)
print("# state of interest: %d" % self.state, file=fh)
print("# ", file=fh)
print("# Scan coordinate Energies ", file=fh)
print("# %s Hartree " % units[typ], file=fh)
print(" %8.5f " % scan_coord, end=' ', file=fh)
for en in self.energies:
print(" %e " % en, end=' ', file=fh)
print("", file=fh)
fh.close()
def velocities_finite_diff(atomlists, dt):
"""
compute the velocities from finite differences between two time-steps
Parameters:
===========
atomlists: list of geometries along trajectories for each time step
dt: nuclear time step in a.u.
Returns:
========
positions: list of vectors with positions for each time step
velocities: list of vectors with velocities for each time step
"""
Nt = len(atomlists)
positions = []
velocities = []
pos0 = XYZ.atomlist2vector(atomlists[0])
positions.append(pos0)
for i in range(1, Nt):
pos1 = XYZ.atomlist2vector(atomlists[i])
vel = (pos1 - pos0) / dt
positions.append(pos1)
velocities.append(vel)
pos0 = pos1
velocities.append(vel)
return positions, velocities
def calc_gradients(xyzfile, optionfile):
"""calculates DFTB energies and gradients for a molecule in the xyz_file
with the options given in the optionfile"""
outputfile = open("output_dftb.txt", "a") # redirect output to file
sys.stdout = outputfile
try:
options = read_options(optionfile) # read options
atomlist = XYZ.read_xyz(xyzfile)[0] # read structure
init_options = extract_options(options, TD_INIT_OPTIONLIST)
td_options = extract_options(options, TD_OPTIONLIST)
grad_options = extract_options(options, GRAD_OPTIONS)
kwds = XYZ.extract_keywords_xyz(xyzfile)
tddftb = LR_TDDFTB(atomlist, **init_options) # create object
tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
tddftb.getEnergies(**td_options) # calculate energies
grad = Gradients(tddftb) # calculate gradients
grad.getGradients(**grad_options)
energies = list(tddftb.dftb2.getEnergies()) # get partial energies
if tddftb.dftb2.long_range_correction == 1: # add long range correction to partial energies
energies.append(tddftb.dftb2.E_HF_x)
return str(energies)
except:
print sys.exc_info()
return "error"
def _getPES(self):
"""calculate energies and gradients at the image positions"""
self.V = [None for Ri in self.R] # potential energies of each image
self.F = [None for Ri in self.R] # true forces acting on each image
if self.nr_processors > 1:
# parallelize over images
atomlists = [XYZ.vector2atomlist(x, self.atomlist) for x in self.R]
image_dirs = ["IMAGE_%2.2d" % i for i in range(0, len(self.R))]
pool = Pool(self.nr_processors)
results = pool.map(run_gaussian_map, zip(atomlists, image_dirs))
for i, (en, grad) in enumerate(results):
print "image %4.d energy= %+e |grad|= %e" % (i, en,
la.norm(grad))
self.V[i] = en
self.F[i] = -grad
else:
# sequential implementation
for i, Ri in enumerate(self.R):
atomlist = XYZ.vector2atomlist(Ri, self.atomlist)
en, grad = run_gaussian(atomlist, directory="IMAGE_%2.2d" % i)
self.V[i] = en
self.F[i] = -grad
print "image %4.d energy= %+e |grad|= %e" % (i, en,
la.norm(grad))
def flakes_to_xyz(grown_flakes, out_xyz, cc1=2.56, substitutions=[]):
generations = grown_flakes.keys()
generations.sort()
lat, unitcell, meso, beta = zn_porphene_lattice(
cc1=cc1, substitutions=substitutions)
a1, a2, a3 = lat.getLatticeVectors("real")
if out_xyz[-4:] == ".xyz":
try:
os.remove(opts.out_xyz)
except OSError as e:
print e
for gen in generations:
print "Generation %s (%s flakes)" % (gen, len(grown_flakes[gen]))
print "========================="
for fl in grown_flakes[gen]:
print "weight = %s" % fl.weight
print fl
flake_atomlist = fl.build_xyz(a1, a2, a3, unitcell, meso, beta)
# reorder atomlist so that all hydrogens are placed at the end of the file
flake_atomlist = XYZ.hydrogens_to_end(flake_atomlist)
XYZ.write_xyz(expandvars(expanduser(out_xyz)), [flake_atomlist],
title="weight=%d" % fl.weight,
mode="a")
def get_active_space(xyzfile, optionfile):
"""calculates the active space for a given molecule and excited state
(see http://www.dftbaby.chemie.uni-wuerzburg.de/DFTBaby/mdwiki.html#!WIKI/main_page.md, Active Space)
not implemented in CAST because no use for ground state calculations
for ground state calculations the active space can be set as small as desired"""
outputfile = open("output_dftb.txt", "a") # redirect output to file
sys.stdout = outputfile
try:
options = read_options(optionfile) # read options
atomlist = XYZ.read_xyz(xyzfile)[0] # read structure
init_options = extract_options(options, TD_INIT_OPTIONLIST)
td_options = extract_options(options, TD_OPTIONLIST)
kwds = XYZ.extract_keywords_xyz(xyzfile)
tddftb = LR_TDDFTB(atomlist, **init_options) # create object
tddftb.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
tddftb.getEnergies(**td_options) # calculate energies
occ, virt = tddftb.determineActiveSpace()
return str((occ, virt))
except:
print sys.exc_info()
return "error"
def eclipsed_oligomers():
# build eclipsed oligomers
for n in [2, 3, 4, 5, 6, 7, 8]:
distances = 2.5 / AtomicData.bohr_to_angs * np.ones(n)
angles = np.zeros(n)
Fn = build_polyfluoerene(distances, angles)
XYZ.write_xyz("F%d_eclipsed.xyz" % n, [Fn])
def _overlap_AB_f90(atomlist1, atomlist2, valorbs1, valorbs2, SKT):
"""
This function calls an external Fortran function that computes the matrix elements.
Since hashes and tuples cannot be used easily in Fortran, the arguments are brought
into a form that can be fed into the Fortran function.
"""
atom_type_dic, spline_deg, tab_filled_SH0, tab_filled_D, \
(S_knots, S_coefs, H_knots, H_coefs, D_knots, D_coefs) = \
combine_slako_tables_f90(SKT)
# number of atoms
Nat1 = len(atomlist1)
Nat2 = len(atomlist2)
# orbitals
atom_indeces1, atom_types1, ls1, ms1 = atomlist2orbitals(
atomlist1, valorbs1, atom_type_dic)
atom_indeces2, atom_types2, ls2, ms2 = atomlist2orbitals(
atomlist2, valorbs2, atom_type_dic)
assert atom_indeces1 == atom_indeces2, "atomlist1 and atomlist2 should contain the same atoms in the same order!"
# count valence orbitals
Norb1 = len(ls1)
Norb2 = len(ls2)
# distances and direction
pos1 = XYZ.atomlist2vector(atomlist1)
pos1 = np.reshape(
pos1, (Nat1, 3)).transpose() # pos(:,i) is the 3d position of atom i
pos2 = XYZ.atomlist2vector(atomlist2)
pos2 = np.reshape(pos2, (Nat2, 3)).transpose()
r, x, y, z = slako.slako.directional_cosines(pos1, pos2)
# call Fortran function
S = slako.slako.overlap12(atom_indeces1, atom_types1, ls1, ms1,
atom_indeces2, atom_types2, ls2, ms2, r, x, y, z,
spline_deg, tab_filled_SH0, S_knots, S_coefs)
return S
def calc_energies(xyzfile, optionfile):
"""calculates DFTB energies for a molecule in the xyz_file
with the options given in the optionfile"""
outputfile = open("output_dftb.txt", "a") # redirect output to file
sys.stdout = outputfile
try:
options = read_options(optionfile) # read options
atomlist = XYZ.read_xyz(xyzfile)[0] # read structure
kwds = XYZ.extract_keywords_xyz(xyzfile)
dftb2 = DFTB2(atomlist, **options) # create dftb object
dftb2.setGeometry(atomlist, charge=kwds.get("charge", 0.0))
scf_options = extract_options(options,
SCF_OPTIONLIST) # calculate energy
dftb2.getEnergy(**scf_options)
energies = list(dftb2.getEnergies()) # get partial energies
if dftb2.long_range_correction == 1: # add long range correction to partial energies
energies.append(dftb2.E_HF_x)
return str(energies)
except:
print sys.exc_info()
return "error"
def capped_uff_nanotube(cnt,NcapN=0, NcapS=0, optimize_uff=1, out_xyz="/tmp/cnt.xyz"):
"""
build capped nanotube and optimize it with UFF
"""
nC,nT = cnt.NrCapAtoms()
print "Expected number of Thomson points nT = %s" % nT
print "If the caps have holes or very close atoms, you should try increasing"
print "or reducing the number of Thomson points (by changing the options NcapN or NcapS)"
if NcapN == 0:
NcapN = nT
if NcapS == 0:
NcapS = nT
"""
Different number of Thomson points are tested to find
a pair (NcapN,NcapS)
"""
dcap = []
dnmin=0
dnmax=1
ntrial=5
for dnN in range(dnmin, dnmax):
for dnS in range(dnmin, dnmax):
# try for 5 times
for n in range(0, ntrial):
dcap.append( (dnN,dnS) )
dcap = sorted(dcap, key=lambda (a,b): abs(a)+abs(b))
for (dnN,dnS) in dcap:
print "north cap: %s points, south cap: %s points" % (NcapN+dnN,NcapS+dnS)
atomlist_carbons = capped_nanotube(cnt,NcapN+dnN,NcapS+dnS)
if optimize_uff == 1:
print "CNT will be optimized further with the Universal Force Field of G09"
tmp_dir="/tmp"
com_file = join(tmp_dir, "cnt_uff_opt.com")
chk_file = join(tmp_dir, "cnt_uff_opt.chk")
fchk_file = chk_file.replace(".chk", ".fchk")
Gaussian.write_input(com_file, atomlist_carbons, \
route="# UFF Opt", \
title="Optimize (%s,%s)-Nanotube with UFF" % (cnt.n1,cnt.n2), chk=chk_file,mem=1000)
try:
Gaussian.run(com_file)
# format checkpoint file
Gaussian.formchk(chk_file, fchk_file)
Data = Checkpoint.parseCheckpointFile(fchk_file)
pos = Data["_Current_cartesian_coordinates"]
atomlist_uff = XYZ.vector2atomlist(pos, atomlist_carbons)
atomlist_carbons = atomlist_uff
except Gaussian.GaussianError:
print "UFF-optimization failed!"
continue
if check_connectivity(atomlist_carbons) == True:
# no holes, correct connectivity
break
XYZ.write_xyz("/tmp/trials.xyz", [atomlist_carbons], mode="a")
else:
print ""
XYZ.write_xyz(expandvars(expanduser(out_xyz)), [atomlist_carbons])
print "Geometry of capped CNT written to %s" % out_xyz
def add_polyatomic_curve(self, geometries, forces_wo_frep, forces_with_frep, \
curve_name="polyatomic", weight=1.0, max_error=0.01, active_atoms=None):
"""
compute generalized forces that act along the bond lengths and
calculate repulsive forces for arbitrary non-linear molecule with more
than 2 atoms.
Parameters:
===========
geometries: list of geometries (in atomlist format)
forces_wo_frep: list of forces (in atomlist format) containing the DFTB forces only
from the electronic hamiltonian
forces_with_frep: list of forces (in atomlist format) containing the forces from a
higher level method (including nuclear repulsion)
curve_name: some identifier for plotting
weight: assign a weight of this data set during fitting
max_error: for large bond lengths and repulsive potentials that cannot be represented
as a sum of pairwise potentials, the error incurred from a pairwise decomposition
can be large. Those geometries where the error per atom exceeds max_error
are not included in the fit.
active_atoms: list of atomic indeces. Only atoms in this list take part in the fit.
If set to [], all atoms are included.
"""
for atomlist, f_wo_rep, f_with_rep in zip(geometries, forces_wo_frep,
forces_with_frep):
# repulsive potential is the difference between true forces and electronic DFTB forces
# in cartesian coordinates
frep = XYZ.atomlist2vector(f_with_rep) - XYZ.atomlist2vector(
f_wo_rep)
forcelist = XYZ.vector2atomlist(frep, atomlist)
from numpy.linalg.linalg import LinAlgError
if active_atoms == []:
# by default all atoms are included into the fit
active_atoms = [i for i in range(0, len(atomlist))]
try:
bond_lengths, pair_forces, error = pairwise_decomposition(
atomlist, forcelist)
except LinAlgError:
print "LINALG ERROR => do not include this geometry"
continue
if error > max_error:
print "Error (%s) from pairwise decomposition too large (threshold: %s) => do not include this geometry!" % (
error, max_error)
continue
for (i, j) in bond_lengths.keys():
if (i not in active_atoms) or (j not in active_atoms):
continue
Zi = atomlist[i][0]
Zj = atomlist[j][0]
if (Zi == self.Z1 and Zj == self.Z2) or (Zi == self.Z2
and Zj == self.Z1):
self.nuclear_separation.append(bond_lengths[(i, j)])
self.repulsive_gradient.append(-pair_forces[(i, j)])
# each point is weighted by 1/sigma
self.weights.append(weight / max(error, 1.0e-2))
self.curve_ID.append(self.curve_counter)
self.curve_names.append(curve_name)
self.curve_counter += 1
def alternately_rotated_oligomers():
# neighbouring fluorenes are rotated by +-10.5 degrees
for n in [2, 3, 4, 5, 6, 7, 8]:
distances = 2.5 / AtomicData.bohr_to_angs * np.ones(n)
# alternate fluorenes with + or - 10.5 degrees
angles = 21.0 / 2.0 * np.pi / 180.0 * pow(-1, np.arange(n))
Fn = build_polyfluoerene(distances, angles)
XYZ.write_xyz("F%d_rotated.xyz" % n, [Fn])
def load_fitpaths_it(self, fit_dir):
"""
load geometries of all fit paths from the folder `fit_dir`
and return an iterator to the fit steps. Each fit step consists of the tuple
(atomlist, en_rep, force_rep)
The meaning of the elements of a fit step are as follows:
atomlist : geometry of of fit step, list of tuples (Zi,[xi,yi,zi])
en_rep : energy difference (E_ref - E_elec) in Hartree
force_rep: vector with force difference (F_ref - F_elec) in Hartree/bohr,
force_rep[3*i:3*(i+1)] is the force [Fx(i),Fy(i),Fz(i)] on atom i.
"""
self.names = [
os.path.basename(xyz)[:-4]
for xyz in glob.glob("%s/FIT_PATHS/*.xyz" % fit_dir)
]
for name in self.names:
print("Loading fit path '%s' " % name)
geom_xyz = os.path.join(fit_dir, "FIT_PATHS", "%s.xyz" % name)
en_dftb_dat = os.path.join(fit_dir, "DFTB",
"%s.energies.dat" % name)
en_ref_dat = os.path.join(fit_dir, "REFERENCE",
"%s.energies.dat" % name)
forces_dftb_xyz = os.path.join(fit_dir, "DFTB",
"%s.forces.xyz" % name)
forces_ref_xyz = os.path.join(fit_dir, "REFERENCE",
"%s.forces.xyz" % name)
try:
geometries = XYZ.read_xyz(geom_xyz)
energies_dftb = np.loadtxt(en_dftb_dat)
energies_ref = np.loadtxt(en_ref_dat)
forces_dftb = XYZ.read_xyz(forces_dftb_xyz)
forces_ref = XYZ.read_xyz(forces_ref_xyz)
for atomlist, en_dftb, en_ref, f_dftb, f_ref in zip(
geometries, energies_dftb, energies_ref, forces_dftb,
forces_ref):
# compute E_rep = E_ref - E_el
en_rep = en_ref - en_dftb
# compute E_rep = F_ref - F_el
force_rep = XYZ.atomlist2vector(
f_ref) - XYZ.atomlist2vector(f_dftb)
yield atomlist, en_rep, force_rep
except IOError as e:
print("Loading of fit path '%s' failed!" % name)
def plot(self, images=[], energies=[], istep=0):
geometries = [XYZ.vector2atomlist(im, self.atomlist) for im in images]
xyz_out = "neb_%s_%d.xyz" % (self.name, istep)
XYZ.write_xyz(xyz_out, geometries)
print("wrote path for iteration %d to %s" % (istep, xyz_out))
if energies != []:
# first column: index of image
# second column: energy of image
data = np.vstack((np.arange(0, len(images)), energies)).transpose()
np.savetxt("path_energies_%s_%d.dat" % (self.name, istep), data)
def scan_angle_F2():
n = 2
distances = 2.5 / AtomicData.bohr_to_angs * np.ones(n)
scan_geometries = []
for a in np.linspace(0.0, np.pi, 80.0):
print(a * 180.0 / np.pi)
angles = [a / 2.0, -a / 2.0]
F2 = build_polyfluoerene(distances, angles)
scan_geometries.append(F2)
XYZ.write_xyz("F2_angle_scan.xyz", scan_geometries)
def wigner_from_G09_hessian(g09_file, Nsample=100, zero_threshold=1.0e-9):
"""
create Wigner ensemble based on hessian matrix from Gaussian 09 calculation
"""
suffix = g09_file.split(".")[-1]
if suffix in ["out", "log"]:
print("Reading Gaussian 09 log file %s" % g09_file)
atomlist = Gaussian.read_geometry(g09_file)
forces = Gaussian.read_forces(g09_file)
hess = Gaussian.read_force_constants(g09_file)
elif suffix in ["fchk"]:
print("Reading formatted Gaussian 09 checkpoint file %s" % g09_file)
Data = Checkpoint.parseCheckpointFile(g09_file)
# cartesian coordinates
pos = Data["_Current_cartesian_coordinates"]
atnos = Data["_Atomic_numbers"]
# forces
frc = -Data["_Cartesian_Gradient"]
atomlist = []
forces = []
for i, Zi in enumerate(atnos):
atomlist.append((Zi, tuple(pos[3 * i:3 * (i + 1)])))
forces.append((Zi, tuple(frc[3 * i:3 * (i + 1)])))
# Hessian
hess = Data["_Cartesian_Force_Constants"]
masses = np.array(AtomicData.atomlist2masses(atomlist))
x0 = XYZ.atomlist2vector(atomlist)
x0 = shift_to_com(x0, masses)
grad = -XYZ.atomlist2vector(forces)
grad_nrm = la.norm(grad)
print(" gradient norm = %s" % grad_nrm)
# assert grad_nrm < 1.0e-3, "Gradient norm too large for minimum!"
vib_freq, vib_modes = vibrational_analysis(hess,
masses,
zero_threshold=zero_threshold)
Aw, Bw = wigner_distribution(x0,
hess,
masses,
zero_threshold=zero_threshold)
gw = GaussianWavepacket.Gaussian(Aw, Bw)
qs, ps = gw.sample(Nsample)
mx = np.outer(masses, np.ones(Nsample)) * qs
avg_com = np.mean(np.sum(mx[::3, :], axis=0)), np.mean(
np.sum(mx[1::3, :], axis=0)), np.mean(np.sum(mx[2::3, :], axis=0))
print(avg_com)
geometries = [
XYZ.vector2atomlist(qs[:, i], atomlist) for i in range(0, Nsample)
]
return geometries
def save_xyz(x, mode="a"):
global step
if step % opts.save_every != 0:
step += 1
return
step += 1
atomlist_opt = XYZ.vector2atomlist(x, atomlist)
atomlist_opt, dummy = enlarged_unitcell(atomlist_opt,
lattice_vectors,
nmax=opts.nr_unit_cells)
XYZ.write_xyz(xyz_opt, [atomlist_opt], \
mode=mode)
def f(x):
thomson_cap = XYZ.vector2atomlist(x, thomson_cap_ref)
# thomson_cap = enforce_constaints(thomson_cap)
print "thomson_cap"
print thomson_cap
thomson_pts = thomson_tube + thomson_cap
XYZ.write_xyz("/tmp/thomson_minimization.xyz", [thomson_cap], mode="a")
en = potential_energy(thomson_pts)
# gradient of potential energy
grad = XYZ.atomlist2vector(gradient_energy(thomson_pts))
print "en = %s" % en
return en #, grad
def addCap(self):
#
x_cap = initial_distribution_cap(
self.Ncap) # positions of Thomson points on the cap
# for points in the cap x[i,:] = (theta_i, phi_i)
# and for points in the tube x[i,:] = (z_i, phi_i)
s_cap = ["C" for i in range(0, self.Ncap)] # segment of carbo-nanotube
# to which the Thomson point belongs, 'C' for cap and 'T' for tube
o_cap = np.ones(self.Ncap, dtype=int)
# o[i] == 1, position of i-th Thomson point is optimized
# o[i] == 0, position is held constant
#
x_tube, o_tube, s_tube = thomson_tube(self.cnt.chiral_vector,
self.cnt.tube_vector,
self.cnt.a1, self.cnt.a2)
# These unit vectors define the orientation of the
# coordinate system
ex = np.array([1, 0, 0])
ey = np.array([0, 1, 0])
ez = np.array([0, 0, 1])
self.axes = [ex, ey, ez]
self.Z0 = 0.0
# combine Thomson point of cap with those of the tube
self.x = np.vstack((x_cap, x_tube))
self.s = np.array(s_cap + s_tube)
self.o = np.hstack((o_cap, o_tube))
self.N = len(self.x)
if self.north_south == "N":
pass
elif self.north_south == "S":
self.x = reflect_tube_xy(self.x, self.s, self.cnt.L)
atomlist = self.thomson2atomlist()
XYZ.write_xyz("/tmp/thomson_opt.xyz", [atomlist], mode="w")
active, inactive = active_layers(self.x, self.s, self.cnt.a1,
self.cnt.a2)
def savexyz():
atomlist = self.thomson2atomlist()
XYZ.write_xyz("/tmp/thomson_opt.xyz", [atomlist], mode="a")
self.x[active, :], self.s[active], self.o[
active], self.en, self.grad = optimize_thomson(self.x[active, :],
self.s[active],
self.o[active],
R=self.cnt.R,
callback=savexyz)
return (self.en, self.grad)
def build_xyz(self, a1, a2, a3, unitcell, meso, beta):
n, m = self.grid.shape
center = (n / 2, m / 2)
flake_atomlist = []
unitcell_vec = XYZ.atomlist2vector(unitcell)
for i in range(0, n):
for j in range(0, m):
if self.grid[i, j] == 1:
if self.orientation[i, j] != 0:
axis, angle = self.rotations[self.orientation[i, j]]
Rot = axis_angle2rotation(axis, angle)
else:
Rot = np.identity(3)
R = (i - n / 2) * a1 + (j - m / 2) * a2 + 0.0 * a3
shifted_unitcell_vec = np.zeros(unitcell_vec.shape)
for at in range(0, len(unitcell)):
# rotate and translate
shifted_unitcell_vec[3*at:3*(at+1)] = \
np.dot(Rot, unitcell_vec[3*at:3*(at+1)]) + R
flake_atomlist += XYZ.vector2atomlist(
shifted_unitcell_vec, unitcell)
# hydrogenize or add meso/beta substituents
for (lr, tb) in self.moves:
i_hyd = i + lr
j_hyd = j + tb
direction = lr * a1 + tb * a2
direction /= la.norm(direction)
if 0 <= i_hyd < n and 0 <= j_hyd < m:
if self.grid[i_hyd, j_hyd] != 1:
# no neighbouring porphine in that direction => add both meso and beta hydrogens
hydrogens = meso + beta # hydrogens can also contain protecting groups, so it's not only H-atoms!
elif self.grid[i_hyd,j_hyd] == 1 \
and (((self.orientation[i,j] == 0) and (self.orientation[i_hyd,j_hyd] in [5,6])) \
or ((self.orientation[i_hyd,j_hyd] == 0) and (self.orientation[i,j] in [5,6]))):
hydrogens = beta
else:
hydrogens = []
# add hydrogens
hydadd = []
for at in range(0, len(hydrogens)):
(Zat, pos) = hydrogens[at]
hyddir = np.array(pos)
hyddir /= la.norm(hyddir)
angle = np.arccos(np.dot(hyddir, direction))
if abs(angle) < np.pi / 4.0:
hydadd += [
(Zat, np.dot(Rot, np.array(pos)) + R)
]
flake_atomlist += hydadd
# meso-meso
return flake_atomlist
def changeTrajectory(self):
selected = self.trajSelection.selectedItems()
trajs = map(int, [s.text() for s in selected])
self.geometries = []
self.nsteps = 0
print "Selected: %s" % map(str, trajs)
print "Plot trajectories %s" % trajs
for ax in self.axes:
ax.clear()
for t in trajs:
trajdir = self.trajdirs[t]
print trajdir
try:
self.plotTrajectory(trajdir, t)
self.geometries.append( XYZ.read_xyz(os.path.join(trajdir, "dynamics.xyz")) )
self.nsteps = max(len(self.geometries[-1]), self.nsteps)
except (ValueError, IOError) as e:
print "Unable to load %s" % trajdir
print "ERROR: %s" % e
for canvas in self.canvases:
canvas.draw()
self.animationSlider.setMinimum(0)
self.animationSlider.setMaximum(self.nsteps)
self.animationTime.setText("Time: %7.2f fs" % 0.0)
self.showMolecules()
def showMolecules(self):
tstep = self.animationSlider.value()
self.animationTime.setText("Time: %7.2f fs" % (tstep * self.dt))
self.mol.clear()
for geoms in self.geometries:
geom_time = geoms[min(tstep, len(geoms)-1)]
# atoms
atoms = []
for (Z,pos) in geom_time:
a = self.mol.addAtom()
a.pos = np.array(pos, dtype=float)
a.atomicNumber = Z
atoms.append(a)
# bond
C = XYZ.connectivity_matrix(geom_time)
Nat = len(geom_time)
for i in range(0, Nat):
for j in range(i+1,Nat):
if C[i,j] == 1:
bond = self.mol.addBond()
bond.setBegin(atoms[i])
bond.setEnd(atoms[j])
bond.order = 1
self.glWidget.mol = self.mol
self.glWidget.updateGeometry()
Avogadro.toPyQt(self.glWidget).update()
def __init__(self, atomlist):
# convert the list of atoms into a list of 3d points
nat = len(atomlist)
pos = XYZ.atomlist2vector(atomlist)
points = []
for i in range(0, nat):
points.append(pos[3 * i:3 * (i + 1)])
# QHull needs at least 4 point to construct the initial
# simplex.
if nat < 4:
# If there are less than 4 atoms,
# we add the center of mass as an additional point
masses = AtomicData.atomlist2masses(atomlist)
com = MolCo.center_of_mass(masses, pos)
points.append(com)
if nat < 3:
# If there are less than 3 atoms we add
# an arbitrary point on the x-axis
points.append(com + np.array([0.0005, 0.0, 0.0]))
if nat < 2:
# If there is only one atom, we add another arbitrary
# point on the y-axis
points.append(com + np.array([0.0, 0.0005, 0.0]))
# We add small random numbers to the input coordinates, so that
# we get a 3D convex hull even if the molecule is planar
points = np.array(points) + 0.0001 * np.random.rand(len(points), 3)
# find the convex hull using the qhull code
hull = ConvexHull(points, qhull_options="QbB Qt")
# call the constructor of the parent class (MinimalEnclosingBox)
super(MoleculeBox, self).__init__(hull)
def get_unique_atomtypes(fit_dir):
"""
given a list of xyz-files, determine the atomic numbers that are present
in any file. For each atom combination a repulsive potential is fitted.
"""
xyz_filenames = glob.glob("%s/FIT_PATHS/*.xyz" % fit_dir)
unique_atomtypes = []
for f in xyz_filenames:
for atomlist in XYZ.read_xyz_it(f):
# atomic numbers in first frame
for Zi, posi in atomlist:
if not Zi in unique_atomtypes:
unique_atomtypes.append(Zi)
unique_atomtypes = np.sort(unique_atomtypes)
print("")
print("Atom Types:")
print("-----------")
for Zi in unique_atomtypes:
print(" %s" % AtomicData.atom_names[Zi - 1])
print("")
return unique_atomtypes
def _electrostatics(self):
"""
computes the electrostatic interaction between the MM charges,
enCoul = - sum_i<j qi*qj/|Ri-Rj|
and the gradient w/r/t to the positions of the individual atoms
"""
Nat = len(self.atomlist)
x = XYZ.atomlist2vector(self.atomlist)
#
enCoul = 0.0
gradCoul = np.zeros(3 * Nat) # gradient
for i in range(0, Nat):
for j in range(i + 1, Nat):
Rij_vec = x[3 * i:3 * (i + 1)] - x[3 * j:3 * (j + 1)]
Rij = la.norm(Rij_vec)
# contribution to energy
Vij = self.mm_charges[i] * self.mm_charges[j] / Rij
enCoul += Vij
# contribution to the gradient
eij = Rij_vec / Rij # unit vector
gij = Vij / Rij * eij
gradCoul[3 * i:3 * (i + 1)] -= gij
gradCoul[3 * j:3 * (j + 1)] += gij
if self.verbose > 0:
print "MM electrostatic energy: %e" % enCoul
return enCoul, gradCoul
def remove_overlapping_atoms(atomlist, tol=1.0e-4):
print("remove overlapping atoms")
nat = len(atomlist)
# The i-th atom should be removed if duplicate[i] == 1
# Fortran
rs = XYZ.atomlist2vector(atomlist)
rs = np.reshape(rs, (nat, 3))
duplicate = thomson.thomson.remove_overlapping(rs, tol)
# python
"""
duplicate_py = np.zeros(nat, dtype=int)
for i in range(0, nat):
for j in range(i+1,nat):
posi = np.array(atomlist[i][1])
posj = np.array(atomlist[j][1])
Rij = la.norm(posi-posj)
if Rij < tol:
duplicate_py[j] = 1
assert np.sum(abs(duplicate - duplicate_py)) < 1.0e-10
"""
# only copy unique atoms
atomlist_unique = []
for i in range(0, nat):
if duplicate[i] == 0:
atomlist_unique.append( atomlist[i] )
return atomlist_unique
def load_fragments(frag_links_file):
"""
Load xyz-files for each fragment. To map the fragment names to the fragment
xyz-files a file with the links has to be provided.
Example for a fragments.lnk file:
C60 C60.xyz
Et ethylene.xyz
Parameters:
===========
frag_links_file: path that links fragment names with geometry definitions
Returns:
========
fragments: dictionary with e.g. d["C60"] = (geometry of C60)
"""
frag_dir = dirname(frag_links_file)
fh = open(frag_links_file)
fragments = {}
for l in fh:
frag_name, frag_xyz_path = l.split()
if not exists(frag_xyz_path):
# not an absolute path, try relative path toe frag_dir
frag_xyz_path = join(frag_dir, frag_xyz_path)
fragments[frag_name] = XYZ.read_xyz(frag_xyz_path)[0]
fh.close()
return fragments
def getCenterOfMass(self):
pos = XYZ.atomlist2vector(self.atomlist)
com = center_of_mass(self.masses, pos)
print("Center of Mass")
print("==============")
print(com)
return com