# The plotter
def invisible_atoms(a):
"""Return True for atoms that should be invisible."""
r = atoms.get_positions()
centerofmass = r.sum(axis=0) / len(atoms)
return (r[:,2] < centerofmass[2])
plotter = PrimiPlotter(atoms)
plotter.set_invisibility_function(invisible_atoms)
plotter.set_colors(mycolors) # Map tags to colors
# plotter.set_output(X11Window()) # Plot in a window on the screen
plotter.set_output(JpegFile("ptm")) # Save plots in files plt0000.gif ...
plotter.set_rotation((10.0, 5.0, 0))
# Attach the plotter to the PTMobserver object. That guarantees
# that the plotter is called AFTER the PTM analysis has been done.
# Similarly, a Trajectory should be attached to the PTMobserver
# object. By using interval=1 (the default), the plotter is called
# every time PTMobserver is called, i.e. every plotinterval
# timesteps.
ptm.attach(plotter.plot)
# The main loop
for t in temperatures:
dyn.set_temperature(units.kB*t)
for i in range(nsteps/100):
dyn.run(100)
print "E_total = %-10.5f T = %.0f K (goal: %.0f K, step %d of %d)" %\
(atoms.get_total_energy()/len(atoms), atoms.get_temperature(), t, i, nsteps/100)
else:
atoms = None
atoms = MakeParallelAtoms(atoms, cpulayout)
atoms.set_calculator(EMT())
print "Number of atoms:", atoms.get_number_of_atoms()
print "Heating to %d K using Langevin" % T_goal
lgv = Langevin(atoms, 5 * units.fs, temperature=2*T_goal*units.kB, friction=0.05)
while atoms.get_kinetic_energy() < 1.5 * atoms.get_number_of_atoms() * T_goal * units.kB:
lgv.run(5)
T = atoms.get_kinetic_energy() / (1.5 * atoms.get_number_of_atoms() * units.kB)
print "Temperature is now %.2f K" % (T,)
print "Desired temperature reached!"
lgv.set_temperature(T_goal*units.kB)
for i in range(2):
lgv.run(20)
s = atoms.get_stress()
p = -(s[0] + s[1] + s[2])/3.0 / units.GPa
T = atoms.get_kinetic_energy() / (1.5 * atoms.get_number_of_atoms() * units.kB)
print "Pressure is %f GPa, desired pressure is %f GPa (T = %.2f K)" % (p, p_goal, T)
dv = (p - p_goal) / bulk
print "Adjusting volume by", dv
cell = atoms.get_cell()
atoms.set_cell(cell * (1.0 + dv/3.0))
T = atoms.get_kinetic_energy() / (1.5 * atoms.get_number_of_atoms() * units.kB)
print "Temperature is now %.2f K" % (T,)
# Make a trajectory
traj = PickleTrajectory('MD_Cluster.traj', "w", atoms)
dyn.attach(traj,
interval=500) # Automatically writes the initial configuration
# Print the energies
def printenergy(a, step=[
0,
]):
n = len(a)
ekin = a.get_kinetic_energy() / n
epot = a.get_potential_energy() / n
print("%4d: E_kin = %-9.5f E_pot = %-9.5f E_tot = %-9.5f T = %.1f K" %
(step[0], ekin, epot, ekin + epot, 2.0 / 3.0 * ekin / units.kB))
step[0] += 1
printenergy(atoms)
view(atoms) #If computer is busy, the plot will appear with some delay.
# Now do the dynamics, doing 5000 timesteps, writing energies every 50 steps
dyn.attach(printenergy, 50, atoms)
dyn.run(5000)
view(atoms)
# Now increase the temperature to 2000 K and continue
dyn.set_temperature(2000 * units.kB)
dyn.run(5000)
view(atoms)
print "Heating to %d K using Langevin" % T_goal
lgv = Langevin(atoms,
5 * units.fs,
temperature=2 * T_goal * units.kB,
friction=0.05)
while atoms.get_kinetic_energy(
) < 1.5 * atoms.get_number_of_atoms() * T_goal * units.kB:
lgv.run(5)
T = atoms.get_kinetic_energy() / (1.5 * atoms.get_number_of_atoms() *
units.kB)
print "Temperature is now %.2f K" % (T, )
print "Desired temperature reached!"
lgv.set_temperature(T_goal * units.kB)
for i in range(2):
lgv.run(20)
s = atoms.get_stress()
p = -(s[0] + s[1] + s[2]) / 3.0 / units.GPa
T = atoms.get_kinetic_energy() / (1.5 * atoms.get_number_of_atoms() *
units.kB)
print "Pressure is %f GPa, desired pressure is %f GPa (T = %.2f K)" % (
p, p_goal, T)
dv = (p - p_goal) / bulk
print "Adjusting volume by", dv
cell = atoms.get_cell()
atoms.set_cell(cell * (1.0 + dv / 3.0))
T = atoms.get_kinetic_energy() / (1.5 * atoms.get_number_of_atoms() *
# Set the momenta corresponding to T=1600K. The temperature will
# quickly drop to half of that as the energy is distributed evenly
# among the kinetic and potential energy.
MaxwellBoltzmannDistribution(atoms, 1600*units.kB)
# Make a trajectory
traj = PickleTrajectory('MD_Cluster.traj', "w", atoms)
dyn.attach(traj, interval=500) # Automatically writes the initial configuration
# Print the energies
def printenergy(a, step=[0,]):
n = len(a)
ekin = a.get_kinetic_energy() / n
epot = a.get_potential_energy() / n
print ("%4d: E_kin = %-9.5f E_pot = %-9.5f E_tot = %-9.5f T = %.1f K" %
(step[0], ekin, epot, ekin+epot, 2.0/3.0*ekin/units.kB))
step[0] += 1
printenergy(atoms)
view(atoms) #If computer is busy, the plot will appear with some delay.
# Now do the dynamics, doing 5000 timesteps, writing energies every 50 steps
dyn.attach(printenergy, 50, atoms)
dyn.run(5000)
view(atoms)
# Now increase the temperature to 2000 K and continue
dyn.set_temperature(2000 * units.kB)
dyn.run(5000)
view(atoms)
# Interval between plots
plotinterval = 500
# Make the Langevin dynamics module
dyn = Langevin(atoms, 5*units.fs, units.kB*temperatures[0], 0.002)
# The plotter
plotter = PrimiPlotter(atoms)
plotter.set_output(X11Window())
plotter.set_rotation((10.0, 5.0, 0))
dyn.attach(plotter.plot, interval=plotinterval)
# Some functions for calculating the actual temperature, energy, ...
def temperature(a):
return 2.0/3.0 * a.get_kinetic_energy() / (len(a) * units.kB)
def etotal(a):
return (a.get_kinetic_energy() + a.get_potential_energy()) / len(a)
# The main loop
for t in temperatures:
dyn.set_temperature(units.kB*t)
for i in range(nsteps/100):
dyn.run(100)
print "E_total = %-10.5f T = %.0f K (goal: %.0f K, step %d of %d)" %\
(etotal(atoms), temperature(atoms), t, i, nsteps/100)
