def print_file_path(mode, beads, cell, filedesc=sys.stdout, title="", key="", dimension="length", units="automatic", cell_units="automatic"):
"""Prints all the bead configurations, into a `mode` formatted file.
Prints all the replicas for each time step separately, rather than all at
once.
Args:
beads: A beads object giving the bead positions.
cell: A cell object giving the system box.
filedesc: An open writable file object. Defaults to standard output.
"""
if mode == "pdb": # special case for PDB
if dimension != "length":
raise ValueError("PDB Standard is only designed for atomic positions")
if units == "automatic": units = "angstrom"
if cell_units == "automatic": cell_units = "angstrom"
# in general, "automatic" units are actually "atomic_units"
else:
if units == "automatic": units = "atomic_unit"
if cell_units == "automatic": cell_units = "atomic_unit"
cell_conv = unit_to_user("length", cell_units, 1.0)
atoms_conv = unit_to_user(dimension, units, 1.0)
title = title + ("%s{%s} cell{%s}" % (key, units, cell_units))
return _get_io_function(mode, "print_path")(beads=beads, cell=cell, filedesc=filedesc, cell_conv=cell_conv, atoms_conv=atoms_conv)
def print_instanton_geo(prefix, step, nbeads, natoms, names, q, pots, cell, shift, output_maker):
outfile = output_maker.get_output(prefix + '_' + str(step) + '.ener', 'w')
print >> outfile, ('#Bead Energy (eV)')
for i in range(nbeads):
print >> outfile, (str(i) + ' ' + str(units.unit_to_user('energy', "electronvolt", pots[i] - shift)))
outfile.close()
# print_file("xyz", pos[0], cell, out, title='positions{angstrom}')
unit = 'angstrom'
a, b, c, alpha, beta, gamma = mt.h2abc_deg(cell.h)
outfile = output_maker.get_output(prefix + '_' + str(step) + '.xyz', 'w')
for i in range(nbeads):
print >> outfile, natoms
print >> outfile, ('CELL(abcABC): %f %f %f %f %f %f cell{atomic_unit} Traj: positions{%s} Bead: %i' % (a, b, c, alpha, beta, gamma, unit, i))
for j in range(natoms):
print >> outfile, names[j], \
str(units.unit_to_user('length', unit, q[i, 3 * j])), \
str(units.unit_to_user('length', unit, q[i, 3 * j + 1])), \
str(units.unit_to_user('length', unit, q[i, 3 * j + 2]))
outfile.close()
def print_file(mode, atoms, cell, filedesc=sys.stdout, title="", key="", dimension="length", units="automatic", cell_units="automatic"):
"""Prints atom positions, or atom-vector properties, into a `mode` formatted file,
using i-PI internal representation of atoms & cell. Does conversion and prepares
formatted title line.
Args:
mode: I/O file format (e.g. "xyz")
atoms: An atoms object containing the positions (or properties) of the atoms
cell: A cell object containing the system box.
filedesc: An open writable file object. Defaults to standard output.
title: This gives a string to be appended to the comment line.
key: Description of the property that is being output
dimension: Dimensions of the property (e.g. "length")
units: Units for the output (e.g. "angstrom")
cell_units: Units for the cell (dimension length, e.g. "angstrom")
"""
if mode == "pdb": # special case for PDB
if dimension != "length":
raise ValueError("PDB Standard is only designed for atomic positions")
if units == "automatic": units = "angstrom"
if cell_units == "automatic": cell_units = "angstrom"
if key == "": key = "positions"
# in general, "automatic" units are actually "atomic_units"
else:
if units == "automatic": units = "atomic_unit"
if cell_units == "automatic": cell_units = "atomic_unit"
cell_conv = unit_to_user("length", cell_units, 1.0)
atoms_conv = unit_to_user(dimension, units, 1.0)
title = title + ("%s{%s} cell{%s}" % (key, units, cell_units))
print_file_raw(mode=mode, atoms=atoms, cell=cell, filedesc=filedesc, title=title, cell_conv=cell_conv, atoms_conv=atoms_conv)
def __init__(self, init_file, args_str, param_file, latency=1.0e-3, name="", pars=None, dopbc=True, threaded=False):
"""Initialises QUIP.
Args:
pars: Mandatory dictionary, giving the parameters needed by QUIP.
"""
if quippy is None:
info("QUIPPY import failed", verbosity.low)
raise quippy_exc
# a socket to the communication library is created or linked
super(FFQUIP, self).__init__(latency, name, pars, dopbc, threaded=threaded)
self.init_file = init_file
self.args_str = args_str
self.param_file = param_file
# Initializes an atoms object and the interaction potential
self.atoms = quippy.Atoms(self.init_file)
self.pot = quippy.Potential(self.args_str, param_filename=self.param_file)
# Initializes the conversion factors from i-pi to QUIP
self.len_conv = unit_to_user("length", "angstrom", 1)
self.energy_conv = unit_to_user("energy", "electronvolt", 1)
self.force_conv = unit_to_user("force", "ev/ang", 1)
def store(self, value, units=""):
"""Converts the data to the appropriate data type and units and stores it.
Args:
value: The raw data to be stored.
units: Optional string giving the units that the data should be stored
in.
"""
super(InputValue, self).store(value)
if units != "":
self.units.store(units) # User can define in the code the units to be printed
self.value = value
if self._dimension != "undefined":
self.value *= unit_to_user(self._dimension, units, 1.0)
def write(self):
"""Outputs the required properties of the system.
Note that properties are outputted using the same format as for the
output to the xml checkpoint files, as specified in io_xml.
Raises:
KeyError: Raised if one of the properties specified in the output list
are not contained in the property_dict member of properties.
"""
if softexit.triggered: return # don't write if we are about to exit!
if not (self.system.simul.step + 1) % self.stride == 0:
return
self.out.write(" ")
for what in self.outlist:
try:
quantity, dimension, unit = self.system.properties[what]
if dimension != "" and unit != "":
quantity = unit_to_user(dimension, unit, quantity)
except KeyError:
raise KeyError(what + " is not a recognized property")
if not hasattr(quantity, "__len__"):
self.out.write(write_type(float, quantity) + " ")
else:
for el in quantity:
self.out.write(write_type(float, el) + " ")
self.out.write("\n")
self.nout += 1
if self.flush > 0 and self.nout >= self.flush:
self.out.flush()
os.fsync(self.out) # we REALLY want to print out! pretty please OS let us do it.
self.nout = 0
def totalEnergy(prefix, temp, ss=0):
"""
Computes the virial centroid estimator for the total energy and PPI correction.
"""
global temperature, skipSteps
temperature = unit_to_internal("temperature", "kelvin", float(temp))
skipSteps = int(ss)
f2_av, ePA_av, eVir_av, f2ePA_av = 0.0, 0.0, 0.0, 0.0 # average square forces, virial and primitive energy
# estimators, and the product of the primitive energy estimator and square forces
ipos = [] # input positions files
for filename in sorted(glob.glob(prefix + ".pos*")):
ipos.append(open(filename, "r"))
ifor = [] # input forces files
for filename in sorted(glob.glob(prefix + ".for*")):
ifor.append(open(filename, "r"))
iU = None # input potential energy and simulation time file
for filename in sorted(glob.glob(prefix + ".out")):
iU = open(filename, "r")
global potentialEnergyUnit, timeUnit
timeUnit, potentialEnergyUnit = extractUnits(iU) # extracting simulation time and potential energy units
iE = open(prefix + ".energy" + ".dat", "w")
iE.write("# Simulation time (in %s), virial total energy and PPI energy correction (in %s)\n" %
(timeUnit, potentialEnergyUnit))
nbeads = len(ipos)
if (nbeads != len(ifor)): raise ValueError("Mismatch between number of output files for forces and positions")
natoms = 0
ifr = 0
time0 = 0
q, f, m = None, None, None
while True: # Reading input files and calculating PPI correction
try:
for i in range(nbeads):
ret = read_file("xyz", ipos[i])
m, n = ret["masses"], ret["atoms"].natoms
pos = unit_to_internal(ret["units"][0], ret["units"][1], ret["atoms"].q)
ret = read_file("xyz", ifor[i])
force = unit_to_internal(ret["units"][0], ret["units"][1], ret["atoms"].q)
if natoms == 0:
natoms = n
q = np.zeros((nbeads, 3 * natoms))
f = np.zeros((nbeads, 3 * natoms))
q[i, :] = pos
f[i, :] = force
time, U = read_U(iU)
except EOFError: # finished reading files
sys.exit(0)
if ifr < skipSteps:
time0 = time
if ifr >= skipSteps: # PPI correction
time -= time0
ePA, f2, f2ePA = 0.0, 0.0, 0.0
eVir, rc = 0.0, np.zeros(3)
for j in range(nbeads):
for i in range(natoms):
f2 += np.dot(f[j, i * 3:i * 3 + 3], f[j, i * 3:i * 3 + 3]) / m[i]
for i in range(natoms):
ePA -= np.dot(q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3], q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3]) * m[i]
for j in range(nbeads - 1):
for i in range(natoms):
ePA -= np.dot(q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3], q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3]) * m[i]
for i in range(natoms):
rc[:] = 0.0
for j in range(nbeads):
rc[:] += q[j, i * 3:i * 3 + 3]
rc[:] /= nbeads
for j in range(nbeads):
eVir += np.dot(rc[:] - q[j, i * 3:i * 3 + 3], f[j, i * 3:i * 3 + 3])
ePA *= 0.5 * nbeads * (Constants.kb * temperature)**2 / Constants.hbar**2
ePA += 0.5 * nbeads * (3 * natoms) * Constants.kb * temperature + U
f2ePA = f2 * ePA
eVir /= 2.0 * nbeads
eVir += 0.5 * (3 * natoms) * Constants.kb * temperature + U
ePA_av += ePA
f2_av += f2
f2ePA_av += f2ePA
eVir_av += eVir
ifr += 1
print(ifr - skipSteps) # Printing current time frame (excluding thermalization)
dE = (3.0 * Constants.kb * temperature + ePA_av / float(ifr - skipSteps)) * f2_av / float(ifr - skipSteps) - \
f2ePA_av / float(ifr - skipSteps)
dE *= Constants.hbar**2 / (24.0 * (nbeads * Constants.kb * temperature)**3)
dE = unit_to_user("energy", potentialEnergyUnit, dE) # Output in the same unit as potential energy
eVir = unit_to_user("energy", potentialEnergyUnit, eVir_av / float(ifr - skipSteps)) # Output in the same unit
# as potential energy
iE.write("%f %f %f\n" % (time, eVir, dE))
else:
ifr += 1
def potentialEnergy(prefix, temp, ss=0, unit=''):
"""
Computes the estimator for the potential energy and PPI correction.
"""
# Adding fortran functions (when exist)
sys.path.append(os.path.abspath(os.path.dirname(sys.argv[0]))[:-2] + 'f90')
fast_code = True
try:
import fortran
except:
fast_code = False
print('WARNING: No compiled fortran module for fast calculations have been found.\n'
'Calculations will use a slower python script.')
temperature = unit_to_internal("temperature", "kelvin", float(temp)) # simulation temperature
skipSteps = int(ss) # steps to skip for thermalization
f2_av, U_av, f2U_av = 0.0, 0.0, 0.0 # some required sums
fns_for = sorted(glob.glob(prefix + ".for*"))
fns_iU = glob.glob(prefix + ".out")[0]
fn_out_en = prefix + ".potential_energy.dat"
# Extracting the number of beads
nbeads = len(fns_for)
# print some information
print 'temperature = {:f} K'.format(float(temp))
print
print 'number of beads = {:d}'.format(nbeads)
print
print 'forces file names:'
for fn_for in fns_for:
print '{:s}'.format(fn_for)
print
print 'potential energy file: {:s}'.format(fns_iU)
print
print 'output file name:'
print fn_out_en
print
# open input and output files
ifor = [open(fn, "r") for fn in fns_for]
iU = open(fns_iU, "r")
iE = open(fn_out_en, "w")
# Some constants
beta = 1.0 / (Constants.kb * temperature)
const = Constants.hbar**2 * beta**2 / (24.0 * nbeads**3)
timeUnit, potentialEnergyUnit, potentialEnergy_index, time_index = extractUnits(iU) # extracting simulation time
# and potential energy units
# Defining the output energy unit
if unit == '':
unit = potentialEnergyUnit
iE.write("# Simulation time (in %s), potential energy and PPI potential energy corrections (in %s)\n" %
(timeUnit, unit))
natoms = 0
ifr = 0
time0 = 0
f, m = None, None
while True: # 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", ifor[i], output='arrays')
if natoms == 0:
m, natoms = ret["masses"], ret["natoms"]
f = np.zeros((nbeads, 3 * natoms))
f[i, :] = ret["data"]
U, time = read_U(iU, potentialEnergyUnit, potentialEnergy_index, time_index)
except EOFError: # finished reading files
sys.exit(0)
if ifr < skipSteps:
time0 = time
if ifr >= skipSteps: # PPI correction
time -= time0
f2 = 0.0
if not fast_code:
for j in range(nbeads):
for i in range(natoms):
f2 += np.dot(f[j, i * 3:i * 3 + 3], f[j, i * 3:i * 3 + 3]) / m[i]
else:
f2 = fortran.f2divm(np.array(f, order='F'), np.array(m, order='F'), natoms, nbeads)
U_av += U
f2_av += f2
f2U_av += f2 * U
ifr += 1
norm = float(ifr - skipSteps)
dU = 2.0 * f2_av / norm - beta * (f2U_av / norm - f2_av * U_av / norm**2)
dU *= const
dU = unit_to_user("energy", unit, dU)
U = unit_to_user("energy", unit, U_av / float(ifr - skipSteps))
iE.write("%f %f %f\n" % (time, U, dU))
else:
ifr += 1
def totalEnergy(prefix, temp, ss=0, unit=''):
"""
Computes the virial centroid estimator for the total energy and PPI correction.
"""
# Adding fortran functions (when exist)
sys.path.append(os.path.abspath(os.path.dirname(sys.argv[0]))[:-2] + 'f90')
fast_code = True
try:
import fortran
except:
fast_code = False
print('WARNING: No compiled fortran module for fast calculations have been found.\n'
'Calculations will use a slower python script.')
temperature = unit_to_internal("temperature", "kelvin", float(temp)) # simulation temperature
skipSteps = int(ss) # steps to skip for thermalization
f2_av, ePA_av, eVir_av, f2ePA_av = 0.0, 0.0, 0.0, 0.0 # some required sums
fns_pos = sorted(glob.glob(prefix + ".pos*"))
fns_for = sorted(glob.glob(prefix + ".for*"))
fns_iU = glob.glob(prefix + ".out")[0]
fn_out_en = prefix + ".total_energy.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 'potential energy file: {:s}'.format(fns_iU)
print
print 'output file name:'
print fn_out_en
print
# open input and output files
ipos = [open(fn, "r") for fn in fns_pos]
ifor = [open(fn, "r") for fn in fns_for]
iU = open(fns_iU, "r")
iE = open(fn_out_en, "w")
# Some constants
beta = 1.0 / (Constants.kb * temperature)
const_1 = 0.5 * nbeads / (beta * Constants.hbar)**2
const_2 = 1.5 * nbeads / beta
const_3 = 1.5 / beta
const_4 = Constants.kb**2 / Constants.hbar**2
const_5 = Constants.hbar**2 * beta**3 / (24.0 * nbeads**3)
timeUnit, potentialEnergyUnit, potentialEnergy_index, time_index = extractUnits(iU) # extracting simulation time
# and potential energy units
# Defining the output energy unit
if unit == '':
unit = potentialEnergyUnit
iE.write("# Simulation time (in %s), virial total energy and PPI energy correction (in %s)\n" %
(timeUnit, unit))
natoms = 0
ifr = 0
time0 = 0
q, f, m = None, None, None
while True: # 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], output='arrays')
if natoms == 0:
m, natoms = ret["masses"], ret["natoms"]
q = np.zeros((nbeads, 3 * natoms))
f = np.zeros((nbeads, 3 * natoms))
q[i, :] = ret["data"]
f[i, :] = read_file("xyz", ifor[i], output='arrays')["data"]
U, time = read_U(iU, potentialEnergyUnit, potentialEnergy_index, time_index)
except EOFError: # finished reading files
sys.exit(0)
if ifr < skipSteps:
time0 = time
if ifr >= skipSteps: # PPI correction
time -= time0
ePA, f2, f2ePA, eVir = 0.0, 0.0, 0.0, 0.0
if not fast_code:
for j in range(nbeads):
for i in range(natoms):
f2 += np.dot(f[j, i * 3:i * 3 + 3], f[j, i * 3:i * 3 + 3]) / m[i]
for i in range(natoms):
ePA -= np.dot(q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3], q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3]) * m[i]
for j in range(nbeads - 1):
for i in range(natoms):
ePA -= np.dot(q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3], q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3]) * m[i]
rc = np.zeros(3)
for i in range(natoms):
rc[:] = 0.0
for j in range(nbeads):
rc[:] += q[j, i * 3:i * 3 + 3]
rc[:] /= nbeads
for j in range(nbeads):
eVir += np.dot(rc[:] - q[j, i * 3:i * 3 + 3], f[j, i * 3:i * 3 + 3])
ePA *= const_1
ePA += const_2 * natoms + U
f2ePA = f2 * ePA
eVir /= 2.0 * nbeads
eVir += const_3 * natoms + U
else:
f2 = fortran.f2divm(np.array(f, order='F'), np.array(m, order='F'), natoms, nbeads)
ePA = fortran.findcoupling(np.array(q, order='F'), np.array(m, order='F'), temperature, natoms, nbeads)
eVir = fortran.findcentroidvirialkineticenergy(np.array(f, order='F'), np.array(q, order='F'), natoms, nbeads)
ePA *= const_4
ePA += const_2 * natoms + U
f2ePA = f2 * ePA
eVir += const_3 * natoms + U
ePA_av += ePA
f2_av += f2
f2ePA_av += f2ePA
eVir_av += eVir
ifr += 1
norm = float(ifr - skipSteps)
dE = (3.0 * Constants.kb * temperature + ePA_av / norm) * f2_av / norm - f2ePA_av / norm
dE *= const_5
dE = unit_to_user("energy", unit, dE)
eVir = unit_to_user("energy", unit, eVir_av / norm)
iE.write("%f %f %f\n" % (time, eVir, dE))
else:
ifr += 1
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), end=' ')
sys.stdout.flush()
try:
for i in range(nbeads):
ret = read_file("xyz", ipos[i], dimension='length')
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], dimension='force')["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
if ifr > skipSteps and ifr % 100 == 0:
# 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 = np.copy(rdf)
_f2rdf = np.copy(f2rdf)
_frdf = np.copy(frdf)
_rdf[:, 1] *= const / nbeads
_f2 = 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 energies(prefix, temp, ss=0, unit=''):
"""
Computes the virial centroid estimator for the total energy and PPI correction.
"""
# Adding fortran functions (when exist)
sys.path.append(os.path.abspath(os.path.dirname(sys.argv[0]))[:-2] + 'f90')
fast_code = True
try:
import fortran
except:
fast_code = False
print('WARNING: No compiled fortran module for fast calculations have been found.\n'
'Calculations will use a slower python script.')
temperature = unit_to_internal("temperature", "kelvin", float(temp)) # simulation temperature
skipSteps = int(ss) # steps to skip for thermalization
KPa_av, KVir_av, U_av, f2_av, f2KPa_av, f2U_av = 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 # some required sums
fns_pos = sorted(glob.glob(prefix + ".pos*"))
fns_for = sorted(glob.glob(prefix + ".for*"))
fns_iU = glob.glob(prefix + ".out")[0]
fn_out_en = prefix + ".energies.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 'potential energy file: {:s}'.format(fns_iU)
print
print 'output file name:'
print fn_out_en
print
# open input and output files
ipos = [open(fn, "r") for fn in fns_pos]
ifor = [open(fn, "r") for fn in fns_for]
iU = open(fns_iU, "r")
iE = open(fn_out_en, "w")
# Some constants
beta = 1.0 / (Constants.kb * temperature)
const_1 = 0.5 * nbeads / (beta * Constants.hbar)**2
const_2 = 1.5 * nbeads / beta
const_3 = 1.5 / beta
const_4 = Constants.kb**2 / Constants.hbar**2
const_5 = Constants.hbar**2 * beta**3 / (24.0 * nbeads**3)
const_6 = Constants.hbar**2 * beta**2 / (24.0 * nbeads**3)
timeUnit, potentialEnergyUnit, potentialEnergy_index, time_index = extractUnits(iU) # extracting simulation time
# and potential energy units
# Defining the output energy unit
if unit == '':
unit = potentialEnergyUnit
iE.write("# Simulation time (in %s), improved total energy estimator, virial total energy estimator, and PPI "
"correction for the total energy; improved potential energy estimator, potential energy estimatorand, "
"PPI correction for the potential energy; improved kinetic energy estimator, virial kinetic energy "
"estimator, and PPI correction for the kinetic energy (all in %s)\n" % (timeUnit, unit))
iE.close()
natoms = 0
ifr = 0
time0 = 0
q, f, m = None, None, None
while True: # 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], dimension='length')["atoms"]
if natoms == 0:
m, natoms = ret.m, ret.natoms
q = np.zeros((nbeads, 3 * natoms))
f = np.zeros((nbeads, 3 * natoms))
q[i, :] = ret.q
f[i, :] = read_file("xyz", ifor[i], dimension='force')["atoms"].q
U, time = read_U(iU, potentialEnergyUnit, potentialEnergy_index, time_index)
except EOFError: # finished reading files
sys.exit(0)
if ifr < skipSteps:
time0 = time
if ifr >= skipSteps: # PPI correction
time -= time0
KPa, f2, KVir = 0.0, 0.0, 0.0
if not fast_code:
for j in range(nbeads):
for i in range(natoms):
f2 += np.dot(f[j, i * 3:i * 3 + 3], f[j, i * 3:i * 3 + 3]) / m[i]
for i in range(natoms):
KPa -= np.dot(q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3], q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3]) * m[i]
for j in range(nbeads - 1):
for i in range(natoms):
KPa -= np.dot(q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3], q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3]) * m[i]
rc = np.zeros(3)
for i in range(natoms):
rc[:] = 0.0
for j in range(nbeads):
rc[:] += q[j, i * 3:i * 3 + 3]
rc[:] /= nbeads
for j in range(nbeads):
KVir += np.dot(rc[:] - q[j, i * 3:i * 3 + 3], f[j, i * 3:i * 3 + 3])
KPa *= const_1
KPa += const_2 * natoms
KVir /= 2.0 * nbeads
KVir += const_3 * natoms
else:
f2 = fortran.f2divm(np.array(f, order='F'), np.array(m, order='F'), natoms, nbeads)
KPa = fortran.findcoupling(np.array(q, order='F'), np.array(m, order='F'), temperature, natoms, nbeads)
KVir = fortran.findcentroidvirialkineticenergy(np.array(f, order='F'), np.array(q, order='F'), natoms, nbeads)
KPa *= const_4
KPa += const_2 * natoms
KVir += const_3 * natoms
f2_av += f2
KPa_av += KPa
f2KPa_av += f2 * KPa
U_av += U
f2U_av += f2 * U
KVir_av += KVir
ifr += 1
norm = float(ifr - skipSteps)
dU = 2 * f2_av / norm - beta * (f2U_av / norm - f2_av * U_av / norm**2)
dU *= const_6
dU = unit_to_user("energy", unit, dU)
dK = (Constants.kb * temperature + KPa_av / norm) * f2_av / norm - f2KPa_av / norm
dK *= const_5
dK = unit_to_user("energy", unit, dK)
U = unit_to_user("energy", unit, U_av / norm)
KVir = unit_to_user("energy", unit, KVir_av / norm)
iE = open(fn_out_en, "a")
iE.write("%f %f %f %f %f %f %f %f %f %f\n"
% (time, KVir + U + dK + dU, KVir + U, dK + dU, U + dU, U, dU, KVir + dK, KVir, dK))
iE.close()
else:
ifr += 1
def step(self, step=None):
""" Does one simulation time step."""
activearrays = self.pre_step(step)
fff = activearrays["old_f"] * (self.im.coef[1:] + self.im.coef[:-1]) / 2
f = (fff + self.im.f).reshape(self.im.dbeads.natoms * 3 * self.im.dbeads.nbeads, 1)
banded = False
banded = True
if banded:
# BANDED Version
# MASS-scaled
dyn_mat = get_dynmat(activearrays["hessian"], self.im.dbeads.m3, self.im.dbeads.nbeads)
h_up_band = banded_hessian(dyn_mat, self.im, masses=False, shift=0.000000001) # create upper band matrix
f = np.multiply(f, self.im.dbeads.m3.reshape(f.shape)**-0.5)
# CARTESIAN
# h_up_band = banded_hessian(activearrays["hessian"], self.im,masses=True) # create upper band matrix
d = diag_banded(h_up_band)
else:
# FULL dimensions version
h_0 = red2comp(activearrays["hessian"], self.im.dbeads.nbeads, self.im.dbeads.natoms, self.im.coef)
h_test = np.add(self.im.h, h_0) # add spring terms to the physical hessian
d, w = clean_hessian(h_test, self.im.dbeads.q, self.im.dbeads.natoms,
self.im.dbeads.nbeads, self.im.dbeads.m, self.im.dbeads.m3, None)
# CARTESIAN
# d,w =np.linalg.eigh(h_test) #Cartesian
info('\n@Lanczos: 1st freq {} cm^-1'.format(units.unit_to_user('frequency', 'inversecm', np.sign(d[0]) * np.sqrt(np.absolute(d[0])))), verbosity.medium)
info('@Lanczos: 2nd freq {} cm^-1'.format(units.unit_to_user('frequency', 'inversecm', np.sign(d[1]) * np.sqrt(np.absolute(d[1])))), verbosity.medium)
info('@Lanczos: 3rd freq {} cm^-1\n'.format(units.unit_to_user('frequency', 'inversecm', np.sign(d[2]) * np.sqrt(np.absolute(d[2])))), verbosity.medium)
if d[0] > 0:
if d[1] / 2 > d[0]:
alpha = 1
lamb = (2 * d[0] + d[1]) / 4
else:
alpha = (d[1] - d[0]) / d[1]
lamb = (3 * d[0] + d[1]) / 4 # midpoint between b[0] and b[1]*(1-alpha/2)
elif d[1] < 0: # Jeremy Richardson
if (d[1] >= d[0] / 2):
alpha = 1
lamb = (d[0] + 2 * d[1]) / 4
else:
alpha = (d[0] - d[1]) / d[1]
lamb = (d[0] + 3 * d[1]) / 4
# elif d[1] < 0: #Litman for Second Order Saddle point
# alpha = 1
# lamb = (d[1] + d[2]) / 4
# print 'WARNING: We are not using the standard Nichols'
# print 'd_x', d_x[0],d_x[1]
else: # Only d[0] <0
alpha = 1
lamb = (d[0] + d[1]) / 4
if banded:
h_up_band[-1, :] += - np.ones(h_up_band.shape[1]) * lamb
d_x = invmul_banded(h_up_band, f)
else:
h_test = alpha * (h_test - np.eye(h_test.shape[0]) * lamb)
d_x = np.linalg.solve(h_test, f)
d_x.shape = self.im.dbeads.q.shape
# MASS-scaled
d_x = np.multiply(d_x, self.im.dbeads.m3**-0.5)
# Rescale step if necessary
if np.amax(np.absolute(d_x)) > activearrays["big_step"]:
info("Step norm, scaled down to {}".format(activearrays["big_step"]), verbosity.low)
d_x *= activearrays["big_step"] / np.amax(np.absolute(d_x))
# Get the new full-position
d_x_full = self.fix.get_full_vector(d_x, t=1)
new_x = self.optarrays["old_x"].copy() + d_x_full
self.post_step(step, new_x, d_x, activearrays)
def totalEnergy(prefix, temp, ss=0, unit=''):
"""
Computes the virial centroid estimator for the total energy and PPI correction.
"""
# Adding fortran functions (when exist)
sys.path.append(os.path.abspath(os.path.dirname(sys.argv[0]))[:-2] + 'f90')
fast_code = True
try:
import fortran
except:
fast_code = False
print(
'WARNING: No compiled fortran module for fast calculations have been found.\n'
'Calculations will use a slower python script.')
temperature = unit_to_internal("temperature", "kelvin",
float(temp)) # simulation temperature
skipSteps = int(ss) # steps to skip for thermalization
f2_av, ePA_av, eVir_av, f2ePA_av = 0.0, 0.0, 0.0, 0.0 # some required sums
fns_pos = sorted(glob.glob(prefix + ".pos*"))
fns_for = sorted(glob.glob(prefix + ".for*"))
fns_iU = glob.glob(prefix + ".out")[0]
fn_out_en = prefix + ".total_energy.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 'potential energy file: {:s}'.format(fns_iU)
print
print 'output file name:'
print fn_out_en
print
# open input and output files
ipos = [open(fn, "r") for fn in fns_pos]
ifor = [open(fn, "r") for fn in fns_for]
iU = open(fns_iU, "r")
iE = open(fn_out_en, "w")
# Some constants
beta = 1.0 / (Constants.kb * temperature)
const_1 = 0.5 * nbeads / (beta * Constants.hbar)**2
const_2 = 1.5 * nbeads / beta
const_3 = 1.5 / beta
const_4 = Constants.kb**2 / Constants.hbar**2
const_5 = Constants.hbar**2 * beta**3 / (24.0 * nbeads**3)
timeUnit, potentialEnergyUnit, potentialEnergy_index, time_index = extractUnits(
iU) # extracting simulation time
# and potential energy units
# Defining the output energy unit
if unit == '':
unit = potentialEnergyUnit
iE.write(
"# Simulation time (in %s), virial total energy and PPI energy correction (in %s)\n"
% (timeUnit, unit))
natoms = 0
ifr = 0
time0 = 0
q, f, m = None, None, None
while True: # 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], output='arrays')
if natoms == 0:
m, natoms = ret["masses"], ret["natoms"]
q = np.zeros((nbeads, 3 * natoms))
f = np.zeros((nbeads, 3 * natoms))
q[i, :] = ret["data"]
f[i, :] = read_file("xyz", ifor[i], output='arrays')["data"]
U, time = read_U(iU, potentialEnergyUnit, potentialEnergy_index,
time_index)
except EOFError: # finished reading files
sys.exit(0)
if ifr < skipSteps:
time0 = time
if ifr >= skipSteps: # PPI correction
time -= time0
ePA, f2, f2ePA, eVir = 0.0, 0.0, 0.0, 0.0
if not fast_code:
for j in range(nbeads):
for i in range(natoms):
f2 += np.dot(f[j, i * 3:i * 3 + 3],
f[j, i * 3:i * 3 + 3]) / m[i]
for i in range(natoms):
ePA -= np.dot(
q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3],
q[0, i * 3:i * 3 + 3] -
q[nbeads - 1, i * 3:i * 3 + 3]) * m[i]
for j in range(nbeads - 1):
for i in range(natoms):
ePA -= np.dot(
q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3],
q[j + 1, i * 3:i * 3 + 3] -
q[j, i * 3:i * 3 + 3]) * m[i]
rc = np.zeros(3)
for i in range(natoms):
rc[:] = 0.0
for j in range(nbeads):
rc[:] += q[j, i * 3:i * 3 + 3]
rc[:] /= nbeads
for j in range(nbeads):
eVir += np.dot(rc[:] - q[j, i * 3:i * 3 + 3],
f[j, i * 3:i * 3 + 3])
ePA *= const_1
ePA += const_2 * natoms + U
f2ePA = f2 * ePA
eVir /= 2.0 * nbeads
eVir += const_3 * natoms + U
else:
f2 = fortran.f2divm(np.array(f, order='F'),
np.array(m, order='F'), natoms, nbeads)
ePA = fortran.findcoupling(np.array(q, order='F'),
np.array(m, order='F'), temperature,
natoms, nbeads)
eVir = fortran.findcentroidvirialkineticenergy(
np.array(f, order='F'), np.array(q, order='F'), natoms,
nbeads)
ePA *= const_4
ePA += const_2 * natoms + U
f2ePA = f2 * ePA
eVir += const_3 * natoms + U
ePA_av += ePA
f2_av += f2
f2ePA_av += f2ePA
eVir_av += eVir
ifr += 1
norm = float(ifr - skipSteps)
dE = (3.0 * Constants.kb * temperature +
ePA_av / norm) * f2_av / norm - f2ePA_av / norm
dE *= const_5
dE = unit_to_user("energy", unit, dE)
eVir = unit_to_user("energy", unit, eVir_av / norm)
iE.write("%f %f %f\n" % (time, eVir, dE))
else:
ifr += 1
def totalEnergy(prefix, temp, ss=0):
"""
Computes the virial centroid estimator for the total energy and PPI correction.
"""
global temperature, skipSteps
temperature = unit_to_internal("temperature", "kelvin", float(temp))
skipSteps = int(ss)
f2_av, ePA_av, eVir_av, f2ePA_av = (
0.0,
0.0,
0.0,
0.0,
) # average square forces, virial and primitive energy
# estimators, and the product of the primitive energy estimator and square forces
ipos = [] # input positions files
for filename in sorted(glob.glob(prefix + ".pos*")):
ipos.append(open(filename, "r"))
ifor = [] # input forces files
for filename in sorted(glob.glob(prefix + ".for*")):
ifor.append(open(filename, "r"))
iU = None # input potential energy and simulation time file
for filename in sorted(glob.glob(prefix + ".out")):
iU = open(filename, "r")
global potentialEnergyUnit, timeUnit
timeUnit, potentialEnergyUnit = extractUnits(
iU
) # extracting simulation time and potential energy units
iE = open(prefix + ".energy" + ".dat", "w")
iE.write(
"# Simulation time (in %s), virial total energy and PPI energy correction (in %s)\n"
% (timeUnit, potentialEnergyUnit)
)
nbeads = len(ipos)
if nbeads != len(ifor):
raise ValueError(
"Mismatch between number of output files for forces and positions"
)
natoms = 0
ifr = 0
time0 = 0
q, f, m = None, None, None
while True: # Reading input files and calculating PPI correction
try:
for i in range(nbeads):
ret = read_file("xyz", ipos[i])
m, n = ret["masses"], ret["atoms"].natoms
pos = unit_to_internal(ret["units"][0], ret["units"][1], ret["atoms"].q)
ret = read_file("xyz", ifor[i])
force = unit_to_internal(
ret["units"][0], ret["units"][1], ret["atoms"].q
)
if natoms == 0:
natoms = n
q = np.zeros((nbeads, 3 * natoms))
f = np.zeros((nbeads, 3 * natoms))
q[i, :] = pos
f[i, :] = force
time, U = read_U(iU)
except EOFError: # finished reading files
sys.exit(0)
if ifr < skipSteps:
time0 = time
if ifr >= skipSteps: # PPI correction
time -= time0
ePA, f2, f2ePA = 0.0, 0.0, 0.0
eVir, rc = 0.0, np.zeros(3)
for j in range(nbeads):
for i in range(natoms):
f2 += (
np.dot(f[j, i * 3 : i * 3 + 3], f[j, i * 3 : i * 3 + 3]) / m[i]
)
for i in range(natoms):
ePA -= (
np.dot(
q[0, i * 3 : i * 3 + 3] - q[nbeads - 1, i * 3 : i * 3 + 3],
q[0, i * 3 : i * 3 + 3] - q[nbeads - 1, i * 3 : i * 3 + 3],
)
* m[i]
)
for j in range(nbeads - 1):
for i in range(natoms):
ePA -= (
np.dot(
q[j + 1, i * 3 : i * 3 + 3] - q[j, i * 3 : i * 3 + 3],
q[j + 1, i * 3 : i * 3 + 3] - q[j, i * 3 : i * 3 + 3],
)
* m[i]
)
for i in range(natoms):
rc[:] = 0.0
for j in range(nbeads):
rc[:] += q[j, i * 3 : i * 3 + 3]
rc[:] /= nbeads
for j in range(nbeads):
eVir += np.dot(
rc[:] - q[j, i * 3 : i * 3 + 3], f[j, i * 3 : i * 3 + 3]
)
ePA *= (
0.5 * nbeads * (Constants.kb * temperature) ** 2 / Constants.hbar ** 2
)
ePA += 0.5 * nbeads * (3 * natoms) * Constants.kb * temperature + U
f2ePA = f2 * ePA
eVir /= 2.0 * nbeads
eVir += 0.5 * (3 * natoms) * Constants.kb * temperature + U
ePA_av += ePA
f2_av += f2
f2ePA_av += f2ePA
eVir_av += eVir
ifr += 1
print(
(ifr - skipSteps)
) # Printing current time frame (excluding thermalization)
dE = (
3.0 * Constants.kb * temperature + ePA_av / float(ifr - skipSteps)
) * f2_av / float(ifr - skipSteps) - f2ePA_av / float(ifr - skipSteps)
dE *= Constants.hbar ** 2 / (
24.0 * (nbeads * Constants.kb * temperature) ** 3
)
dE = unit_to_user(
"energy", potentialEnergyUnit, dE
) # Output in the same unit as potential energy
eVir = unit_to_user(
"energy", potentialEnergyUnit, eVir_av / float(ifr - skipSteps)
) # Output in the same unit
# as potential energy
iE.write("%f %f %f\n" % (time, eVir, dE))
else:
ifr += 1
def energies(prefix, temp, ss=0, unit=""):
"""
Computes the virial centroid estimator for the total energy and PPI correction.
"""
# Adding fortran functions (when exist)
sys.path.append(os.path.abspath(os.path.dirname(sys.argv[0]))[:-2] + "f90")
fast_code = True
try:
import fortran
except ImportError:
fast_code = False
print(
"WARNING: No compiled fortran module for fast calculations have been found.\n"
"Calculations will use a slower python script.")
temperature = unit_to_internal("temperature", "kelvin",
float(temp)) # simulation temperature
skipSteps = int(ss) # steps to skip for thermalization
KPa_av, KVir_av, U_av, f2_av, f2KPa_av, f2U_av = (
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
) # some required sums
fns_pos = sorted(glob.glob(prefix + ".pos*"))
fns_for = sorted(glob.glob(prefix + ".for*"))
fns_iU = glob.glob(prefix + ".out")[0]
fn_out_en = prefix + ".energies.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("potential energy file: {:s}".format(fns_iU))
print()
print("output file name:")
print(fn_out_en)
print()
# open input and output files
ipos = [open(fn, "r") for fn in fns_pos]
ifor = [open(fn, "r") for fn in fns_for]
iU = open(fns_iU, "r")
iE = open(fn_out_en, "w")
# Some constants
beta = 1.0 / (Constants.kb * temperature)
const_1 = 0.5 * nbeads / (beta * Constants.hbar)**2
const_2 = 1.5 * nbeads / beta
const_3 = 1.5 / beta
const_4 = Constants.kb**2 / Constants.hbar**2
const_5 = Constants.hbar**2 * beta**3 / (24.0 * nbeads**3)
const_6 = Constants.hbar**2 * beta**2 / (24.0 * nbeads**3)
timeUnit, potentialEnergyUnit, potentialEnergy_index, time_index = extractUnits(
iU) # extracting simulation time
# and potential energy units
# Defining the output energy unit
if unit == "":
unit = potentialEnergyUnit
iE.write(
"# Simulation time (in %s), improved total energy estimator, virial total energy estimator, and PPI "
"correction for the total energy; improved potential energy estimator, potential energy estimatorand, "
"PPI correction for the potential energy; improved kinetic energy estimator, virial kinetic energy "
"estimator, and PPI correction for the kinetic energy (all in %s)\n" %
(timeUnit, unit))
iE.close()
natoms = 0
ifr = 0
time0 = 0
q, f, m = None, None, None
while True: # Reading input files and calculating PPI correction
if ifr % 100 == 0:
print("\rProcessing frame {:d}".format(ifr), end=" ")
sys.stdout.flush()
try:
for i in range(nbeads):
ret = read_file("xyz", ipos[i], dimension="length")["atoms"]
if natoms == 0:
m, natoms = ret.m, ret.natoms
q = np.zeros((nbeads, 3 * natoms))
f = np.zeros((nbeads, 3 * natoms))
q[i, :] = ret.q
f[i, :] = read_file("xyz", ifor[i],
dimension="force")["atoms"].q
U, time = read_U(iU, potentialEnergyUnit, potentialEnergy_index,
time_index)
except EOFError: # finished reading files
sys.exit(0)
if ifr < skipSteps:
time0 = time
if ifr >= skipSteps: # PPI correction
time -= time0
KPa, f2, KVir = 0.0, 0.0, 0.0
if not fast_code:
for j in range(nbeads):
for i in range(natoms):
f2 += (np.dot(f[j, i * 3:i * 3 + 3],
f[j, i * 3:i * 3 + 3]) / m[i])
for i in range(natoms):
KPa -= (np.dot(
q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3],
q[0, i * 3:i * 3 + 3] - q[nbeads - 1, i * 3:i * 3 + 3],
) * m[i])
for j in range(nbeads - 1):
for i in range(natoms):
KPa -= (np.dot(
q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3],
q[j + 1, i * 3:i * 3 + 3] - q[j, i * 3:i * 3 + 3],
) * m[i])
rc = np.zeros(3)
for i in range(natoms):
rc[:] = 0.0
for j in range(nbeads):
rc[:] += q[j, i * 3:i * 3 + 3]
rc[:] /= nbeads
for j in range(nbeads):
KVir += np.dot(rc[:] - q[j, i * 3:i * 3 + 3],
f[j, i * 3:i * 3 + 3])
KPa *= const_1
KPa += const_2 * natoms
KVir /= 2.0 * nbeads
KVir += const_3 * natoms
else:
f2 = fortran.f2divm(np.array(f, order="F"),
np.array(m, order="F"), natoms, nbeads)
KPa = fortran.findcoupling(
np.array(q, order="F"),
np.array(m, order="F"),
temperature,
natoms,
nbeads,
)
KVir = fortran.findcentroidvirialkineticenergy(
np.array(f, order="F"), np.array(q, order="F"), natoms,
nbeads)
KPa *= const_4
KPa += const_2 * natoms
KVir += const_3 * natoms
f2_av += f2
KPa_av += KPa
f2KPa_av += f2 * KPa
U_av += U
f2U_av += f2 * U
KVir_av += KVir
ifr += 1
norm = float(ifr - skipSteps)
dU = 2 * f2_av / norm - beta * (f2U_av / norm -
f2_av * U_av / norm**2)
dU *= const_6
dU = unit_to_user("energy", unit, dU)
dK = (Constants.kb * temperature +
KPa_av / norm) * f2_av / norm - f2KPa_av / norm
dK *= const_5
dK = unit_to_user("energy", unit, dK)
U = unit_to_user("energy", unit, U_av / norm)
KVir = unit_to_user("energy", unit, KVir_av / norm)
iE = open(fn_out_en, "a")
iE.write(
"%f %f %f %f %f %f %f %f %f %f\n"
% (
time,
KVir + U + dK + dU,
KVir + U,
dK + dU,
U + dU,
U,
dU,
KVir + dK,
KVir,
dK,
))
iE.close()
else:
ifr += 1
def effectiveTemperatures(prefix, temp, ss=0):
"""
Computes effective temperatures for a given (PI)MD dynamics.
"""
temperature = unit_to_internal("temperature", "kelvin", float(temp)) # simulation temperature
skipSteps = int(ss) # steps to skip for thermalization
f2_av = None # average square forces array
names = None
fns_for = sorted(glob.glob(prefix + ".for*"))
fn_out = prefix + ".effective_temperatures.dat"
nbeads = len(fns_for)
# print some information
print 'temperature = {:f} K'.format(float(temp))
print
print 'number of beads = {:d}'.format(nbeads)
print
print 'forces file names:'
for fn_for in fns_for:
print '{:s}'.format(fn_for)
print
print 'output file name:'
print fn_out
print
# open input and output files
ifor = [open(fn, "r") for fn in fns_for]
iOut = open(fn_out, "w")
# Some constants
const = Constants.hbar**2 / (12.0 * (nbeads * Constants.kb * temperature)**3)
iOut.write("# Atom, Cartesian components of the effective temperature, average effective temperature (in Kelvin)\n")
natoms = 0
ifr = 0
f, m = None, None
while True: # 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", ifor[i], dimension='force')["atoms"]
if natoms == 0:
m, natoms, names = ret.m, ret.natoms, ret.names
f = np.zeros((nbeads, 3 * natoms))
f2_av = np.zeros(3 * natoms)
f[i, :] = ret.q
except EOFError: # finished reading files
break
if ifr >= skipSteps: # PPI correction
f2 = np.zeros(3 * natoms)
for i in range(natoms):
for j in range(nbeads):
f2[i * 3:i * 3 + 3] += f[j, i * 3:i * 3 + 3]**2 / m[i]
f2_av[:] += f2[:]
ifr += 1
else:
ifr += 1
dT = const * f2_av / float(ifr - skipSteps)
temperature = unit_to_user("temperature", "kelvin", temperature)
for i in range(natoms):
iOut.write("%s %f %f %f %f\n" % (names[i], temperature * (1 + dT[i * 3]), temperature * (1 + dT[i * 3 + 1]),
temperature * (1 + dT[i * 3 + 2]), temperature * (1 + np.sum(dT[i * 3:i * 3 + 3]) / 3.0)))
for f in ifor:
f.close()
iOut.close()
