def main(file_name):
xyz_file = XYZFile(file_name)
frames = xyz_file.geometries
# titles = xyz_file.titles
# Unit cell, decide how to make this general
matrix = np.array([[
1.4731497044857509E+01, 3.2189795740722255E-02, 4.5577626559295564E-02
], [
4.2775481701113616E-02, 2.1087874593411915E+01, -2.8531114198383896E-02
], [
6.4054385616337750E-02, 1.3315840416191497E-02, 1.4683043045316882E+01
]])
matrix *= angstrom
cell = UnitCell(matrix)
frac = UnitCell.to_fractional(cell, frames)
xmin = np.min(frac[:, :, 0])
ymin = np.min(frac[:, :, 1])
zmin = np.min(frac[:, :, 2])
frac[:, :, 0] -= -0.5 # xmin
frac[:, :, 1] -= -0.5 # ymin
frac[:, :, 2] -= -0.5 # zmin
decimals = np.modf(frac)[0]
# decimals[:,:,0] += xmin
# decimals[:,:,1] += ymin
# decimals[:,:,2] += zmin
frac_wrapped = np.where(decimals < 0, 1 + decimals, decimals)
# frac_wrapped[:,:,0] += xmin
# frac_wrapped[:,:,1] += ymin
# frac_wrapped[:,:,2] += zmin
cart_wrapped = UnitCell.to_cartesian(cell, frac_wrapped)
xyz_file.geometries = cart_wrapped
xyz_file.write_to_file(file_name.rsplit(".", 1)[0] + "_wrapped.xyz")
def test_distance_matrix_periodic(self):
for i in xrange(1000):
N = 6
unit_cell = UnitCell(
numpy.random.uniform(0,1,(3,3)),
numpy.random.randint(0,2,3).astype(bool),
)
fractional = numpy.random.uniform(0,1,(N,3))
coordinates = unit_cell.to_cartesian(fractional)
from molmod.ext import molecules_distance_matrix
dm = molecules_distance_matrix(coordinates, unit_cell.matrix,
unit_cell.reciprocal)
for i in xrange(N):
for j in xrange(i,N):
delta = coordinates[j]-coordinates[i]
delta = unit_cell.shortest_vector(delta)
distance = numpy.linalg.norm(delta)
self.assertAlmostEqual(dm[i,j], distance)
def test_distances_intra_random_periodic(self):
for i in xrange(10):
coordinates = numpy.random.uniform(0,1,(20,3))
while True:
unit_cell = UnitCell(
numpy.random.uniform(0,5,(3,3)),
numpy.random.randint(0,2,3).astype(bool),
)
if unit_cell.spacings.min() > 0.5:
break
coordinates = unit_cell.to_cartesian(coordinates)*3-unit_cell.matrix.sum(axis=1)
cutoff = numpy.random.uniform(1, 6)
pair_search = PairSearchIntra(coordinates, cutoff, unit_cell)
self.verify_bins_intra_periodic(pair_search.bins)
distances = [
(frozenset([i0, i1]), distance)
for i0, i1, delta, distance
in pair_search
]
self.verify_distances_intra(coordinates, cutoff, distances, unit_cell)
def get_random_ff(self):
N = 6
mask = numpy.zeros((N,N), bool)
for i in xrange(N):
for j in xrange(i):
mask[i,j] = True
from molmod.ext import molecules_distance_matrix
while True:
unit_cell = UnitCell(
numpy.random.uniform(0,3,(3,3)),
numpy.random.randint(0,2,3).astype(bool),
)
fractional = numpy.random.uniform(0,1,(N,3))
coordinates = unit_cell.to_cartesian(fractional)
if numpy.random.randint(0,2):
unit_cell = None
dm = molecules_distance_matrix(coordinates)
else:
dm = molecules_distance_matrix(coordinates, unit_cell.matrix, unit_cell.reciprocal)
if dm[mask].min() > 1.0:
break
edges = set([])
while len(edges) < 2*N:
v1 = numpy.random.randint(N)
while True:
v2 = numpy.random.randint(N)
if v2 != v1:
break
edges.add(frozenset([v1,v2]))
edges = tuple(edges)
numbers = numpy.random.randint(6, 10, N)
graph = MolecularGraph(edges, numbers)
ff = ToyFF(graph, unit_cell)
return ff, coordinates, dm, mask, unit_cell
def test_distances_inter_random_periodic(self):
for i in xrange(10):
fractional0 = numpy.random.uniform(0,1,(20,3))
fractional1 = numpy.random.uniform(0,1,(20,3))
while True:
unit_cell = UnitCell(
numpy.random.uniform(0,5,(3,3)),
numpy.random.randint(0,2,3).astype(bool),
)
if unit_cell.spacings.min() > 0.5:
break
coordinates0 = unit_cell.to_cartesian(fractional0)*3-unit_cell.matrix.sum(axis=1)
coordinates1 = unit_cell.to_cartesian(fractional1)*3-unit_cell.matrix.sum(axis=1)
cutoff = numpy.random.uniform(1, 6)
pair_search = PairSearchInter(coordinates0, coordinates1, cutoff, unit_cell)
self.verify_bins_inter_periodic(pair_search.bins0, pair_search.bins1)
distances = [
((i0, i1), distance)
for i0, i1, delta, distance
in pair_search
]
self.verify_distances_inter(coordinates0, coordinates1, cutoff, distances, unit_cell)
def load_molecule_vasp(contcar,
outcar_freq,
outcar_energy=None,
energy=None,
multiplicity=1,
is_periodic=True):
"""Load a molecule from VASP 4.6.X and 5.3.X output files
Arguments:
| contcar -- A CONTCAR file with the structure used as POSCAR file for the
Hessian/frequency calculation in VASP. Do not use the CONTCAR file
generated by the frequency calculation. Use the CONTCAR from the
preceding geometry optimization instead.
| outcar_freq -- The OUTCAR file of the Hessian/frequency calculation. Also the
gradient and the energy are read from this file. The energy
without entropy (but not the extrapolation to sigma=0) is used.
Optional arguments:
| outcar_energy -- When given, the (first) energy without entropy is read from
this file (not the extrapolation to sigma=0) instead of
reading the energy from the freq output
| energy -- The potential energy, which overrides the contents of outcar_freq.
| multiplicity -- The spin multiplicity of the electronic system
[default=1]
| is_periodic -- True when the system is periodic in three dimensions.
False when the systen is nonperiodic. [default=True].
"""
# auxiliary function to read energy:
def read_energy_without_entropy(f):
# Go to the first energy
for line in f:
if line.startswith(
' FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)'):
break
# Skip three lines and read energy
next(f)
next(f)
next(f)
return float(next(f).split()[3]) * electronvolt
# Read atomic symbols, coordinates and cell vectors from CONTCAR
symbols = []
coordinates = []
with open(contcar) as f:
# Skip title.
next(f).strip()
# Read scale for rvecs.
rvec_scale = float(next(f))
# Read rvecs. VASP uses one row per cell vector.
rvecs = np.fromstring(next(f) + next(f) + next(f),
sep=' ').reshape(3, 3)
rvecs *= rvec_scale * angstrom
unit_cell = UnitCell(rvecs)
# Read symbols
unique_symbols = next(f).split()
# Read atom counts per symbol
symbol_counts = [int(w) for w in next(f).split()]
assert len(symbol_counts) == len(unique_symbols)
natom = sum(symbol_counts)
# Construct array with atomic numbers.
numbers = []
for iunique in range(len(unique_symbols)):
number = periodic[unique_symbols[iunique]].number
numbers.extend([number] * symbol_counts[iunique])
numbers = np.array(numbers)
# Check next line
while next(f) != 'Direct\n':
continue
# Load fractional coordinates
fractional = np.zeros((natom, 3), float)
for iatom in range(natom):
words = next(f).split()
fractional[iatom, 0] = float(words[0])
fractional[iatom, 1] = float(words[1])
fractional[iatom, 2] = float(words[2])
coordinates = unit_cell.to_cartesian(fractional)
if outcar_energy is not None and energy is None:
with open(outcar_energy) as f:
energy = read_energy_without_entropy(f)
# Read energy, gradient, Hessian and masses from outcar_freq. Note that the first
# energy/force calculation is done on the unperturbed input structure.
with open(outcar_freq) as f:
# Loop over the POTCAR sections in the OUTCAR file
number = None
masses = np.zeros(natom, float)
while True:
line = next(f)
if line.startswith(' VRHFIN ='):
symbol = line[11:line.find(':')].strip()
number = periodic[symbol].number
elif line.startswith(' POMASS ='):
mass = float(line[11:line.find(';')]) * amu
masses[numbers == number] = mass
elif number is not None and line.startswith(
'------------------------------'):
assert masses.min() > 0
break
# Go to the first gradient
for line in f:
if line.startswith(' POSITION'):
break
# Skip one line and read the gradient
next(f)
gradient = np.zeros((natom, 3), float)
gunit = electronvolt / angstrom
for iatom in range(natom):
words = next(f).split()
gradient[iatom, 0] = -float(words[3]) * gunit
gradient[iatom, 1] = -float(words[4]) * gunit
gradient[iatom, 2] = -float(words[5]) * gunit
if energy is None:
energy = read_energy_without_entropy(f)
# Go to the second derivatives
for line in f:
if line.startswith(' SECOND DERIVATIVES (NOT SYMMETRIZED)'): break
# Skip one line.
next(f)
# Load free atoms (not fixed in space).
keys = next(f).split()
nfree_dof = len(keys)
indices_free = [
3 * int(key[:-1]) + {
'X': 0,
'Y': 1,
'Z': 2
}[key[-1]] - 3 for key in keys
]
assert nfree_dof % 3 == 0
# Load the actual Hessian
hunit = electronvolt / angstrom**2
hessian = np.zeros((3 * natom, 3 * natom), float)
for ifree0 in range(nfree_dof):
line = next(f)
irow = indices_free[ifree0]
# skip first col
words = line.split()[1:]
assert len(words) == nfree_dof
for ifree1 in range(nfree_dof):
icol = indices_free[ifree1]
hessian[irow, icol] = -float(words[ifree1]) * hunit
# Symmetrize the Hessian
hessian = 0.5 * (hessian + hessian.T)
return Molecule(numbers,
coordinates,
masses,
energy,
gradient,
hessian,
multiplicity=multiplicity,
periodic=is_periodic,
unit_cell=unit_cell)
def test_radius_indexes_2d_graphical(self):
#uc = UnitCell(numpy.array([
# [2.0, 1.0, 0.0],
# [0.0, 0.2, 0.0],
# [0.0, 0.0, 10.0],
#]))
#radius = 0.8
uc = UnitCell(numpy.array([
[1.0, 1.0, 0.0],
[0.0, 1.0, 0.0],
[0.0, 0.0, 10.0],
]))
radius = 5.3
#uc = UnitCell(numpy.array([
# [1.0, 1.0, 0.0],
# [0.0, 1.0, 0.0],
# [0.0, 0.0, 1.0],
#]))
#radius = 0.9
fracs = numpy.arange(-0.5, 0.55, 0.1)
import pylab
from matplotlib.patches import Circle, Polygon
from matplotlib.lines import Line2D
pylab.clf()
for i0 in fracs:
for i1 in fracs:
center = uc.to_cartesian([i0,i1,0.0])
pylab.gca().add_artist(Circle((center[0], center[1]), radius, fill=True, fc='#7777AA', ec='none'))
pylab.gca().add_artist(Circle((0, 0), radius, fill=True, fc='#0000AA', ec='none'))
ranges = uc.get_radius_ranges(radius)
indexes = uc.get_radius_indexes(radius)
for i in xrange(-ranges[0]-1, ranges[0]+1):
start = uc.to_cartesian([i+0.5, -ranges[1]-0.5, 0])
end = uc.to_cartesian([i+0.5, ranges[1]+0.5, 0])
pylab.gca().add_artist(Line2D([start[0], end[0]], [start[1], end[1]], color="k", linewidth=1))
for i in xrange(-ranges[1]-1, ranges[1]+1):
start = uc.to_cartesian([-ranges[0]-0.5, i+0.5, 0])
end = uc.to_cartesian([ranges[0]+0.5, i+0.5, 0])
pylab.gca().add_artist(Line2D([start[0], end[0]], [start[1], end[1]], color="k", linewidth=1))
for i in xrange(-ranges[0], ranges[0]+1):
start = uc.to_cartesian([i, -ranges[1]-0.5, 0])
end = uc.to_cartesian([i, ranges[1]+0.5, 0])
pylab.gca().add_artist(Line2D([start[0], end[0]], [start[1], end[1]], color="k", linewidth=0.5, linestyle="--"))
for i in xrange(-ranges[1], ranges[1]+1):
start = uc.to_cartesian([-ranges[0]-0.5, i, 0])
end = uc.to_cartesian([ranges[0]+0.5, i, 0])
pylab.gca().add_artist(Line2D([start[0], end[0]], [start[1], end[1]], color="k", linewidth=0.5, linestyle="--"))
for i0,i1,i2 in indexes:
if i2 != 0:
continue
corners = uc.to_cartesian(numpy.array([
[i0-0.5, i1-0.5, 0.0],
[i0-0.5, i1+0.5, 0.0],
[i0+0.5, i1+0.5, 0.0],
[i0+0.5, i1-0.5, 0.0],
]))
pylab.gca().add_artist(Polygon(corners[:,:2], fill=True, ec='none', fc='r', alpha=0.5))
corners = uc.to_cartesian(numpy.array([
[-ranges[0]-0.5, -ranges[1]-0.5, 0.0],
[-ranges[0]-0.5, +ranges[1]+0.5, 0.0],
[+ranges[0]+0.5, +ranges[1]+0.5, 0.0],
[+ranges[0]+0.5, -ranges[1]-0.5, 0.0],
]))
pylab.xlim(1.1*corners[:,:2].min(), 1.1*corners[:,:2].max())
pylab.ylim(1.1*corners[:,:2].min(), 1.1*corners[:,:2].max())
#pylab.xlim(-1.5*radius, 1.5*radius)
#pylab.ylim(-1.5*radius, 1.5*radius)
pylab.savefig("output/radius_indexes_2d.png")
def load_molecule_vasp(contcar, outcar_freq, energy=None, multiplicity=1, is_periodic=True):
"""Load a molecule from VASP 4.6.X and 5.3.X output files
Arguments:
| contcar -- A CONTCAR file with the structure used as POSCAR file for the
Hessian/frequency calculation in VASP. Do not use the CONTCAR file
generated by the frequency calculation. Use the CONTCAR from the
preceding geometry optimization instead. The energy without
entropy (but not the extrapolation to sigma=0) is used.
| outcar_freq -- The OUTCAR file of the Hessian/frequency calculation.
Optional arguments:
| energy -- The potential energy, which overrides the contents of outcar_freq.
| multiplicity -- The spin multiplicity of the electronic system
[default=1]
| is_periodic -- True when the system is periodic in three dimensions.
False when the systen is nonperiodic. [default=True].
"""
# Read atomic symbols, coordinates and cell vectors from CONTCAR
symbols = []
coordinates = []
with open(contcar) as f:
# Skip title.
f.next().strip()
# Read scale for rvecs.
rvec_scale = float(f.next())
# Read rvecs. VASP uses one row per cell vector.
rvecs = np.fromstring(f.next()+f.next()+f.next(), sep=' ').reshape(3, 3)
rvecs *= rvec_scale*angstrom
unit_cell = UnitCell(rvecs)
# Read symbols
unique_symbols = f.next().split()
# Read atom counts per symbol
symbol_counts = [int(w) for w in f.next().split()]
assert len(symbol_counts) == len(unique_symbols)
natom = sum(symbol_counts)
# Construct array with atomic numbers.
numbers = []
for iunique in xrange(len(unique_symbols)):
number = periodic[unique_symbols[iunique]].number
numbers.extend([number]*symbol_counts[iunique])
numbers = np.array(numbers)
# Check next line
while f.next() != 'Direct\n':
continue
# Load fractional coordinates
fractional = np.zeros((natom, 3), float)
for iatom in xrange(natom):
words = f.next().split()
fractional[iatom, 0] = float(words[0])
fractional[iatom, 1] = float(words[1])
fractional[iatom, 2] = float(words[2])
coordinates = unit_cell.to_cartesian(fractional)
# Read energy, gradient, Hessian and masses from outcar_freq. Note that the first
# energy/force calculation is done on the unperturbed input structure.
with open(outcar_freq) as f:
# Loop over the POTCAR sections in the OUTCAR file
number = None
masses = np.zeros(natom, float)
while True:
line = f.next()
if line.startswith(' VRHFIN ='):
symbol = line[11:line.find(':')].strip()
number = periodic[symbol].number
elif line.startswith(' POMASS ='):
mass = float(line[11:line.find(';')])*amu
masses[numbers==number] = mass
elif number is not None and line.startswith('------------------------------'):
assert masses.min() > 0
break
# Go to the first gradient
for line in f:
if line.startswith(' POSITION'):
break
# Skip one line and read the gradient
f.next()
gradient = np.zeros((natom, 3), float)
gunit = electronvolt/angstrom
for iatom in xrange(natom):
words = f.next().split()
gradient[iatom, 0] = -float(words[3])*gunit
gradient[iatom, 1] = -float(words[4])*gunit
gradient[iatom, 2] = -float(words[5])*gunit
if energy is None:
# Go to the first energy
for line in f:
if line.startswith(' FREE ENERGIE OF THE ION-ELECTRON SYSTEM (eV)'):
break
# Skip three lines and read energy
f.next()
f.next()
f.next()
energy = float(f.next().split()[3])*electronvolt
# Go to the second derivatives
for line in f:
if line.startswith(' SECOND DERIVATIVES (NOT SYMMETRIZED)'): break
# Skip one line.
f.next()
# Load free atoms (not fixed in space).
keys = f.next().split()
nfree_dof = len(keys)
indices_free = [3*int(key[:-1])+{'X': 0, 'Y': 1, 'Z': 2}[key[-1]]-3 for key in keys]
assert nfree_dof % 3 == 0
# Load the actual Hessian
hunit = electronvolt/angstrom**2
hessian = np.zeros((3*natom, 3*natom), float)
for ifree0 in xrange(nfree_dof):
line = f.next()
irow = indices_free[ifree0]
# skip first col
words = line.split()[1:]
assert len(words) == nfree_dof
for ifree1 in xrange(nfree_dof):
icol = indices_free[ifree1]
hessian[irow, icol] = -float(words[ifree1])*hunit
# Symmetrize the Hessian
hessian = 0.5*(hessian + hessian.T)
return Molecule(
numbers, coordinates, masses, energy, gradient, hessian,
multiplicity=multiplicity, periodic=is_periodic, unit_cell=unit_cell)
