def test_process_units_object(units_preparation):
natoms, frames, comment, conver_xyz, conver_cell = units_preparation
output = "objects"
filedesc, xyz, atom_names = xyz_gen.xyz_traj_filedesc(
natoms, frames, comment)
cell = mt.abc2h(1.0, 1.0, 1.0, np.pi / 2.0, np.pi / 2.0, np.pi / 2.0)
masses = []
_count = 0
for _at in atom_names:
print(Elements.mass(_at), _count, _at)
masses.append(Elements.mass(_at))
_count += 1
masses = np.array(masses)
res = testing.process_units(
comment,
cell.copy(),
xyz.copy(),
np.array(atom_names).copy(),
np.array(masses).copy(),
output=output,
)
npt.assert_array_almost_equal(res["atoms"].q, xyz * conver_xyz, 5)
npt.assert_array_almost_equal(res["atoms"].m, masses, 5)
npt.assert_array_almost_equal(res["cell"].h, cell * conver_cell, 5)
npt.assert_array_equal(res["atoms"].names, atom_names, 5)
def test_process_units_noobj(units_preparation):
natoms, frames, comment, conver_xyz, conver_cell = units_preparation
output = 'noobj'
filedesc, xyz, atom_names = xyz_gen.xyz_traj_filedesc(natoms,
frames, comment)
cell = mt.abc2h(1.0, 1.0, 1.0, np.pi/2.0, np.pi/2.0, np.pi/2.0)
masses = []
_count = 0
print 'atom_names', atom_names
for _at in atom_names:
print Elements.mass(_at), _count, _at
masses.append(Elements.mass(_at))
_count += 1
masses = np.array(masses)
type(masses)
res = testing.process_units(comment, cell.copy(), xyz.copy(), np.array(atom_names).copy(), np.array(masses).copy(), output=output)
print xyz,res['data']
npt.assert_array_almost_equal(res['data'], xyz * conver_xyz, 5)
npt.assert_array_almost_equal(res['masses'], masses, 5)
npt.assert_array_almost_equal(res['cell'], cell * conver_cell, 5)
npt.assert_array_equal(res['names'], atom_names, 5)
assert res['natoms'] == natoms
def test_process_units_noobj(units_preparation):
natoms, frames, comment, conver_xyz, conver_cell = units_preparation
output = "noobj"
filedesc, xyz, atom_names = xyz_gen.xyz_traj_filedesc(
natoms, frames, comment)
cell = mt.abc2h(1.0, 1.0, 1.0, np.pi / 2.0, np.pi / 2.0, np.pi / 2.0)
masses = []
_count = 0
print("atom_names", atom_names)
for _at in atom_names:
print(Elements.mass(_at), _count, _at)
masses.append(Elements.mass(_at))
_count += 1
masses = np.array(masses)
type(masses)
res = testing.process_units(
comment,
cell.copy(),
xyz.copy(),
np.array(atom_names).copy(),
np.array(masses).copy(),
output=output,
)
print(xyz, res["data"])
npt.assert_array_almost_equal(res["data"], xyz * conver_xyz, 5)
npt.assert_array_almost_equal(res["masses"], masses, 5)
npt.assert_array_almost_equal(res["cell"], cell * conver_cell, 5)
npt.assert_array_equal(res["names"], atom_names, 5)
assert res["natoms"] == natoms
def test_process_units_object(units_preparation):
natoms, frames, comment, conver_xyz, conver_cell = units_preparation
output = 'objects'
filedesc, xyz, atom_names = xyz_gen.xyz_traj_filedesc(natoms,
frames, comment)
cell = mt.abc2h(1.0, 1.0, 1.0, np.pi / 2.0, np.pi / 2.0, np.pi / 2.0)
masses = []
_count = 0
for _at in atom_names:
print Elements.mass(_at), _count, _at
masses.append(Elements.mass(_at))
_count += 1
masses = np.array(masses)
res = testing.process_units(comment, cell.copy(), xyz.copy(), np.array(atom_names).copy(), np.array(masses).copy(), output=output)
npt.assert_array_almost_equal(res['atoms'].q, xyz * conver_xyz, 5)
npt.assert_array_almost_equal(res['atoms'].m, masses, 5)
npt.assert_array_almost_equal(res['cell'].h, cell * conver_cell, 5)
npt.assert_array_equal(res['atoms'].names, atom_names, 5)
def test_process_units_noobj(units_preparation):
natoms, frames, comment, conver_xyz, conver_cell = units_preparation
output = 'noobj'
filedesc, xyz, atom_names = xyz_gen.xyz_traj_filedesc(natoms,
frames, comment)
cell = mt.abc2h(1.0, 1.0, 1.0, np.pi / 2.0, np.pi / 2.0, np.pi / 2.0)
masses = []
_count = 0
print 'atom_names', atom_names
for _at in atom_names:
print Elements.mass(_at), _count, _at
masses.append(Elements.mass(_at))
_count += 1
masses = np.array(masses)
type(masses)
res = testing.process_units(comment, cell.copy(), xyz.copy(), np.array(atom_names).copy(), np.array(masses).copy(), output=output)
print xyz, res['data']
npt.assert_array_almost_equal(res['data'], xyz * conver_xyz, 5)
npt.assert_array_almost_equal(res['masses'], masses, 5)
npt.assert_array_almost_equal(res['cell'], cell * conver_cell, 5)
npt.assert_array_equal(res['names'], atom_names, 5)
assert res['natoms'] == natoms
def create_random_xyz_traj_to_write(request):
natoms, frames, comment, expected_cell, precision = request.param
a, b, c, alpha, beta, gamma = mt.h2abc_deg(expected_cell)
fmt_header = "# CELL(abcABC): %10.5f %10.5f %10.5f %10.5f %10.5f %10.5f %s"
comment = fmt_header % (a, b, c, alpha, beta, gamma, comment)
filedesc, xyz, atom_names = xyz_gen.xyz_traj_filedesc(natoms, frames, comment)
filedesc.seek(0)
masses = [Elements.mass(_am) for _am in atom_names]
cell_list = []
atoms_list = []
for _fr in xrange(frames):
cell = Cell(expected_cell)
atoms = Atoms(natoms)
atoms.q[:] = xyz[_fr * natoms * 3:(_fr + 1) * natoms * 3]
atoms.names = atom_names[_fr * natoms:(_fr + 1) * natoms]
atoms.m[:] = masses[_fr * natoms:(_fr + 1) * natoms]
atoms_list.append(atoms)
cell_list.append(cell)
return (filedesc, atoms_list, cell_list, comment, precision)
def read_pdb(filedesc, **kwargs):
"""Reads a PDB-style file and creates an Atoms and Cell object.
Args:
filedesc: An open readable file object from a pdb formatted file.
Returns:
An Atoms object with the appropriate atom labels, masses and positions,
and a Cell object with the appropriate cell dimensions and an estimate
of a reasonable cell mass.
"""
header = filedesc.readline()
comment = ''
if "TITLE" in header:
# skip the comment field
comment = copy.copy(header)
header = filedesc.readline()
if 'positions{' not in comment:
comment = comment.strip()
comment += ' positions{angstrom}\n'
if 'cell{' not in comment:
comment = comment.strip()
comment += ' cell{angstrom}\n'
if header == "":
raise EOFError("End of file or empty header in PDB file")
a = float(header[6:15])
b = float(header[15:24])
c = float(header[24:33])
alpha = float(header[33:40])
beta = float(header[40:47])
gamma = float(header[47:54])
alpha *= np.pi / 180.0
beta *= np.pi / 180.0
gamma *= np.pi / 180.0
h = mt.abc2h(a, b, c, alpha, beta, gamma)
cell = h
natoms = 0
body = filedesc.readline()
qatoms = []
names = []
masses = []
while (body.strip() != "" and body.strip() != "END"):
natoms += 1
name = body[12:16].strip()
names.append(name)
masses.append(Elements.mass(name))
x = float(body[31:39])
y = float(body[39:47])
z = float(body[47:55])
qatoms.append(x)
qatoms.append(y)
qatoms.append(z)
body = filedesc.readline()
return comment, cell, np.asarray(qatoms), np.asarray(
names, dtype='|S4'), np.asarray(masses)
def create_xyz_sample_file(request):
""" Create a fake xyz file and build the atoms and cell object from it.
"""
natoms, frames, comment, expected_cell, units_conv_at, units_conv_cell = request.param
filedesc, xyz, atoms_names = xyz_gen.xyz_traj_filedesc(natoms, frames, comment)
# init_file needs to read from a real file...
tmp_file = tmp.NamedTemporaryFile(mode='wr', prefix='ipi_testing-tmp', delete=False)
tmp_file.seek(0)
tmp_file.write(filedesc.read())
tmp_file.close()
filedesc.close()
masses = np.zeros(natoms * frames)
for _ii, _at in enumerate(atoms_names):
masses[_ii] = Elements.mass(_at)
ratoms = []
for _fr in range(frames):
ratoms.append(Atoms(natoms))
ratoms[-1].q = xyz[_fr * natoms * 3:3 * (_fr + 1) * natoms] * units_conv_at
ratoms[-1].m = masses[_fr * natoms:(_fr + 1) * natoms]
ratoms[-1].names = atoms_names[_fr * natoms:(_fr + 1) * natoms]
cell = Cell(expected_cell * units_conv_cell)
# remove temp file created during this test
def delete_files_after_testing():
if os.path.isfile(tmp_file.name):
os.remove(tmp_file.name)
request.addfinalizer(delete_files_after_testing)
return tmp_file, cell, ratoms
def read_xyz(filedesc):
"""Reads an XYZ-style file with i-PI style comments and returns data in raw format for further units transformation
and other post processing.
Args:
filedesc: An open readable file object from a xyz formatted file with i-PI header comments.
Returns:
i-Pi comment line, cell array, data (positions, forces, etc.), atoms names and masses
"""
try:
natoms = int(filedesc.next())
except (StopIteration, ValueError):
raise EOFError
comment = filedesc.next()
# Extracting cell
cell = [key.search(comment) for key in cell_re]
usegenh = False
if cell[0] is not None: # abcABC
a, b, c = [float(x) for x in cell[0].group(1).split()[:3]]
alpha, beta, gamma = [float(x) * deg2rad
for x in cell[0].group(1).split()[3:6]]
h = mt.abc2h(a, b, c, alpha, beta, gamma)
elif cell[1] is not None: # GENH
h = np.array(cell[1].group(1).split()[:9], float)
h.resize((3, 3))
elif cell[2] is not None: # H
genh = np.array(cell[2].group(1).split()[:9], float)
genh.resize((3, 3))
invgenh = np.linalg.inv(genh)
# convert back & forth from abcABC representation to get an upper triangular h
h = mt.abc2h(*mt.genh2abc(genh))
usegenh = True
else: # defaults to unit box
h = np.array([[-1.0, 0.0, 0.0], [0.0, -1.0, 0.0], [0.0, 0.0, -1.0]])
cell = h
qatoms = np.zeros(3 * natoms)
names = np.zeros(natoms, dtype='|S4')
masses = np.zeros(natoms)
# Extracting a time-frame information
atom_counter = 0
for iat, line in enumerate(filedesc):
body = line.split()
names[iat], masses[iat] = body[0], Elements.mass(body[0])
x, y, z = float(body[1]), float(body[2]), float(body[3])
# TODO: The following in matrices would use vectorial computaiton
if usegenh:
# must convert from the input cell parameters to the internal convention
u = np.array([x, y, z])
us = np.dot(u, invgenh)
u = np.dot(h, us)
x, y, z = u
qatoms[3 * iat], qatoms[3 * iat + 1], qatoms[3 * iat + 2] = x, y, z
atom_counter += 1
if atom_counter == natoms:
break
if natoms != len(names):
raise ValueError("The number of atom records does not match the header of the xyz file.")
return comment, cell, qatoms, names, masses
def RDF(prefix, temp, A, B, nbins, r_min, r_max, ss=0, unit='angstrom'):
# Adding fortran functions (when exist)
sys.path.append(os.path.abspath(os.path.dirname(sys.argv[0]))[:-2] + 'f90')
try:
import fortran
except:
print(
'WARNING: No compiled fortran module for fast calculations have been found.\n'
'Proceeding the calculations is not possible.')
sys.exit(0)
temperature = unit_to_internal("temperature", "kelvin",
float(temp)) # simulation temperature
skipSteps = int(ss) # steps to skip
nbins = int(nbins)
fns_pos = sorted(glob.glob(prefix + ".pos*"))
fns_for = sorted(glob.glob(prefix + ".for*"))
fn_out_rdf, fn_out_rdf_q = prefix + '.' + A + B + ".rdf.dat", prefix + '.' + A + B + ".rdf-ppi.dat"
# check that we found the same number of positions and forces files
nbeads = len(fns_pos)
if nbeads != len(fns_for):
print fns_pos
print fns_for
raise ValueError(
"Mismatch between number of input files for forces and positions.")
# print some information
print 'temperature = {:f} K'.format(float(temp))
print
print 'number of beads = {:d}'.format(nbeads)
print
print 'positions and forces file names:'
for fn_pos, fn_for in zip(fns_pos, fns_for):
print '{:s} {:s}'.format(fn_pos, fn_for)
print
print 'output file names:'
print fn_out_rdf
print fn_out_rdf_q
print
# open input and output files
ipos = [open(fn, "r") for fn in fns_pos]
ifor = [open(fn, "r") for fn in fns_for]
#iRDF, iRDFq = open(fn_out_rdf, "w"), open(fn_out_rdf_q, "w")
# Species for RDF
species = (A, B)
speciesMass = np.array(
[Elements.mass(species[0]),
Elements.mass(species[1])], order='F')
r_min = unit_to_internal('length', unit,
float(r_min)) # Minimal distance for RDF
r_max = unit_to_internal('length', unit,
float(r_max)) # Maximal distance for RDF
dr = (r_max - r_min) / nbins # RDF step
rdf = np.array([[r_min + (0.5 + i) * dr, 0] for i in range(nbins)],
order='F') # conventional RDF
# RDF auxiliary variables
cell = None # simulation cell matrix
inverseCell = None # inverse simulation sell matrix
cellVolume = None # simulation cell volume
natomsA = 0 # the total number of A type particles in the system
natomsB = 0 # the total number of B type particles in the system
# Here A and B are the types of elements used for RDF calculations
# temp variables
f2 = 0.0 # the sum of square forces divided by corresponding masses (f2/m)
f2rdf = np.zeros(
nbins,
order='F') # the sum f2/m multiplied by the rdf at each time step
frdf = np.zeros(
nbins, order='F'
) # the sum of f/m multiplied by the rdf derivative at each time step
natoms = 0 # total number of atoms
ifr = 0 # time frame number
pos, force, mass = None, None, None # positions, forces, and mass arrays
noteof = True # end of file test variable
while noteof: # Reading input files and calculating PPI correction
if ifr % 100 == 0:
print '\rProcessing frame {:d}'.format(ifr),
sys.stdout.flush()
try:
for i in range(nbeads):
ret = read_file("xyz", ipos[i])
if natoms == 0:
mass, natoms = ret["atoms"].m, ret["atoms"].natoms
pos = np.zeros((nbeads, 3 * natoms), order='F')
force = np.zeros((nbeads, 3 * natoms), order='F')
cell = ret["cell"].h
inverseCell = ret["cell"].get_ih()
cellVolume = ret["cell"].get_volume()
pos[i, :] = ret["atoms"].q
force[i, :] = read_file("xyz", ifor[i])["atoms"].q
except EOFError: # finished reading files
noteof = False
if noteof:
if ifr >= skipSteps: # RDF calculations
species_A = [
3 * i + j for i in np.where(mass == speciesMass[0])[0]
for j in range(3)
]
species_B = [
3 * i + j for i in np.where(mass == speciesMass[1])[0]
for j in range(3)
]
natomsA = len(species_A)
natomsB = len(species_B)
posA = np.zeros((nbeads, natomsA), order='F')
posB = np.zeros((nbeads, natomsB), order='F')
forA = np.zeros((nbeads, natomsA), order='F')
forB = np.zeros((nbeads, natomsB), order='F')
for bead in range(nbeads):
posA[bead, :] = pos[bead, species_A]
forA[bead, :] = force[bead, species_A]
posB[bead, :] = pos[bead, species_B]
forB[bead, :] = force[bead, species_B]
# RDF amd PPI RDF calculations
f2temp = fortran.f2divm(force, mass, natoms, nbeads)
f2 += f2temp
fortran.updateqrdf(rdf, f2rdf, frdf, posA, posB, forA, forB,
natomsA / 3, natomsB / 3, nbins, r_min,
r_max, cell, inverseCell, nbeads, f2temp,
speciesMass[0], speciesMass[1])
ifr += 1
else:
ifr += 1
# Some constants
const = 1.0 / float(ifr - skipSteps)
alpha = Constants.hbar**2 / (24.0 * nbeads**3 *
(temperature * Constants.kb)**3)
beta = Constants.hbar**2 / (12.0 * nbeads**3 *
(temperature * Constants.kb)**2)
# Normalization
rdf[:, 1] *= const / nbeads
f2 *= alpha * const
f2rdf[:] *= alpha * const
frdf[:] *= beta * const
# PPI correction
rdfQ = np.copy(rdf)
for bin in range(nbins):
rdfQ[bin, 1] += (rdf[bin, 1] * f2 - f2rdf[bin] / nbeads)
rdfQ[bin, 1] -= frdf[bin] / 2.0
# Creating RDF from N(r)
const, dr = cellVolume / (4 * np.pi / 3.0), rdf[1, 0] - rdf[0, 0]
for bin in range(nbins):
rdf[bin, 1] = const * rdf[bin, 1] / ((rdf[bin, 0] + 0.5 * dr)**3 -
(rdf[bin, 0] - 0.5 * dr)**3)
rdfQ[bin, 1] = const * rdfQ[bin, 1] / ((rdfQ[bin, 0] + 0.5 * dr)**3 -
(rdfQ[bin, 0] - 0.5 * dr)**3)
for bin in range(nbins):
rdf[bin, 0] = unit_to_user('length', unit, rdf[bin, 0])
rdfQ[bin, 0] = unit_to_user('length', unit, rdfQ[bin, 0])
# Writing the results into files
np.savetxt(fn_out_rdf, rdf)
np.savetxt(fn_out_rdf_q, rdfQ)
def read_xyz(filedesc):
"""Reads an XYZ-style file with i-PI style comments and returns data in raw format for further units transformation
and other post processing.
Args:
filedesc: An open readable file object from a xyz formatted file with i-PI header comments.
Returns:
i-Pi comment line, cell array, data (positions, forces, etc.), atoms names and masses
"""
try:
natoms = int(filedesc.next())
except (StopIteration, ValueError):
raise EOFError
comment = filedesc.next()
# Extracting cell
cell = [key.search(comment) for key in cell_re]
usegenh = False
if cell[0] is not None: # abcABC
a, b, c = [float(x) for x in cell[0].group(1).split()[:3]]
alpha, beta, gamma = [float(x) * deg2rad
for x in cell[0].group(1).split()[3:6]]
h = mt.abc2h(a, b, c, alpha, beta, gamma)
elif cell[1] is not None: # H
h = np.array(cell[1].group(1).split()[:9], float)
h.resize((3, 3))
elif cell[2] is not None: # GENH
genh = np.array(cell[2].group(1).split()[:9], float)
genh.resize((3, 3))
invgenh = np.linalg.inv(genh)
# convert back & forth from abcABC representation to get an upper triangular h
h = mt.abc2h(*mt.genh2abc(genh))
usegenh = True
else: # defaults to unit box
h = np.array([[-1.0, 0.0, 0.0], [0.0, -1.0, 0.0], [0.0, 0.0, -1.0]])
cell = h
qatoms = np.zeros(3 * natoms)
names = np.zeros(natoms, dtype='|S4')
masses = np.zeros(natoms)
# Extracting a time-frame information
atom_counter = 0
for iat, line in enumerate(filedesc):
body = line.split()
names[iat], masses[iat] = body[0], Elements.mass(body[0])
x, y, z = float(body[1]), float(body[2]), float(body[3])
if usegenh:
# must convert from the input cell parameters to the internal convention
u = np.array([x, y, z])
us = np.dot(u, invgenh)
u = np.dot(h, us)
x, y, z = u
qatoms[3 * iat], qatoms[3 * iat + 1], qatoms[3 * iat + 2] = x, y, z
atom_counter += 1
if atom_counter == natoms:
break
if natoms != len(names):
raise ValueError("The number of atom records does not match the header of the xyz file.")
return comment, cell, qatoms, names, masses