def main_loop():
global energies, plt1_x_data, plt1_y_data, plt2_x_data, plt2_y_data, old_pressure
integrate.integrate(int_steps)
mayavi.update()
# make sure the parameters are valid
# not sure if this is necessary after using limit_range
if controls.volume == 0:
controls.volume = controls.min_vol
if controls.number_of_particles == 0:
controls.number_of_particles = 1
if controls.pressure == 0:
controls.pressure = controls.min_press
pressure = analyze.pressure(system)
# update the parameters set in the GUI
system.thermostat.set_langevin(kT=controls.temperature, gamma=1.0)
if controls.ensemble == 'NPT':
# reset Vkappa when target pressure has changed
if old_pressure != controls.pressure:
analyze.Vkappa(system, 'reset')
old_pressure = controls.pressure
newVkappa = analyze.Vkappa(system, 'read')['Vk1']
newVkappa = newVkappa if newVkappa > 0. else 4.0/(NPTGamma0*NPTGamma0*NPTInitPistonMass)
pistonMass = limit_range(4.0/(NPTGamma0*NPTGamma0*newVkappa), NPTMinPistonMass, NPTMaxPistonMass)
integrate.set_integrator_isotropic_npt(controls.pressure, pistonMass, cubic_box=True)
controls.volume = system.box_l[0]**3.
else:
integrate.set_integrator_nvt()
controls.pressure = pressure['total']
new_box = numpy.ones(3) * controls.volume**(1./3.)
if numpy.any(numpy.array(system.box_l) != new_box):
for i in range(system.n_part):
system.part[i].pos *= new_box / system.box_l[0]
system.box_l = new_box
new_part = controls.number_of_particles
if new_part > system.n_part:
for i in range(system.n_part, new_part):
system.part.add(id=i, pos=numpy.random.random(3) * system.box_l)
elif new_part < system.n_part:
for i in range(new_part, system.n_part):
system.part[i].delete()
# There should be no gaps in particle numbers
assert system.n_part == system.max_part + 1
plt1_x_data = plot1.get_xdata()
plt1_y_data = plot1.get_ydata()
plt2_x_data = plot2.get_xdata()
plt2_y_data = plot2.get_ydata()
plt1_x_data = numpy.append(plt1_x_data[-plot_max_data_len+1:], system.time)
if show_real_system_temperature:
plt1_y_data = numpy.append(plt1_y_data[-plot_max_data_len+1:], 2./(3. * system.n_part)*analyze.energy(system)["ideal"])
else:
plt1_y_data = numpy.append(plt1_y_data[-plot_max_data_len+1:], system.temperature)
plt2_x_data = numpy.append(plt2_x_data[-plot_max_data_len+1:], system.time)
plt2_y_data = numpy.append(plt2_y_data[-plot_max_data_len+1:], pressure['total'])
#
# # Increase LJ cap
# lj_cap = lj_cap + 10
# system.non_bonded_inter.set_force_cap(lj_cap)
# mayavi.update()
#############################################################
# Integration #
#############################################################
# remove force capping
#lj_cap = 0
# system.non_bonded_inter.set_force_cap(lj_cap)
# get initial observables
pressure = analyze.pressure(system)
temperature = system.temperature
# TODO: this is some terrible polynomial fit, replace it with a better expression
# equation of state
pyplot.subplot(131)
pyplot.semilogy()
pyplot.title("Phase diagram")
pyplot.xlabel("Temperature")
pyplot.ylabel("Pressure")
pyplot.xlim(0.5, 2.0)
pyplot.ylim(5e-5, 2e1)
xx = numpy.linspace(0.5, 0.7, 200)
pyplot.plot(xx, -6.726 * xx**4 + 16.92 * xx**3 -
15.85 * xx**2 + 6.563 * xx - 1.015, 'k-')
xx = numpy.linspace(0.7, 1.3, 600)
