def Simulate():
record_path = '/Users/matthewbakalar/projects/VASP/latticerecord2.dat'
simulation_steps = 100
initial_size = 10
max_size = 10000
c_steps = 10
c_multiplier = 10
c_range = sp.zeros(c_steps)
c_range[0] = .0001
for i in range(1,c_steps):
c_range[i] = c_range[i-1] * c_multiplier
error = sp.zeros(c_range.size)
a = sp.zeros(c_range.size)
b = sp.zeros(c_range.size)
count = 0
for conc in c_range:
lattice = LatticeModel(initial_size, max_size)
simulation = VaspSimulation(lattice)
record = SimulationRecord(record_path, simulation, 'w')
record.open_file()
VaspSimulation.VASP_ON = VaspSimulation.VASP_ON_BASE * conc
for i in range(0, simulation_steps):
simulation.advance_simulation()
record.save_state()
record.close_file()
record = SimulationRecord(record_path, simulation, 'r')
time_recon = TimeReconstruction(record)
lvt = time_recon.length_vs_time()
#Linear regressison -polyfit - polyfit can be used other orders polys
n = lvt[0].size
(ar,br)=polyfit(lvt[0],lvt[1],1)
xr=polyval([ar,br],lvt[0])
#compute the mean square error
err=sp.sqrt(sum((xr-lvt[1])**2)/n)
print('Linear regression using polyfit')
print('parameters: regression: a=%.2f b=%.2f, ms error= %.3f' % (ar,br,err))
pyplot.plot(lvt[0], lvt[1], 'g')
pyplot.plot(lvt[0], xr, 'r')
pyplot.show()
a[count] = ar
b[count] = br
error[count] = err
count+=1
print 'Count = %(count)d' % {'count':count}
def Simulate():
for sim, fname in Experiment.runs:
Experiment.Log('Starting: ' + fname)
for conc in Experiment.conc:
Experiment.Log('Concentration: ' + str(conc))
fname_conc = fname + '_c=' + str(conc)
pth = os.path.join(Experiment.datafolder, fname_conc)
record = SimulationRecord(pth, sim, 'w')
record.open_file()
VaspSimulation.VASP_ON = VaspSimulation.VASP_ON_BASE * conc
while sim.time <= Experiment.equilibrate:
sim.advance_simulation()
sim.time = 0
while sim.time <= Experiment.simulate:
if sim.time % 1 < 0.01:
Experiment.Log('Time: ' + str(sim.time))
sim.advance_simulation()
record.save_state()
record.close_file()
