def solve(self):
#Create the initial particle from the defining string/number atoms
self.particle = NanoClass.genParticle(self.definingString, int(self.numberOfAtoms))
self.reCenter()
self.bestEnergy = self.particle.get_potential_energy()
self.bestParticle = deepcopy(self.particle)
# berendsen = NVTBerendsen(self.particle, 2.5 * units.fs, 2000, taut=0.5*100*units.fs)
berendsen = Langevin(self.particle, 5 * units.fs, units.kB * 2000, 0.005)
dyn = FIRE(atoms=self.particle)
MaxwellBoltzmannDistribution(self.particle,2000*units.kB)
CALCULATIONS=100
for i in range(CALCULATIONS):
if i%1==0:
pDone=float(i)/CALCULATIONS
self.setStatusDone(str(math.floor(pDone*100))+"% | "+self.remainingTime(pDone))
self.checkTimeout()
self.setSolution(self.getAnswer())
MaxwellBoltzmannDistribution(self.particle,2000*units.kB)
self.particle.get_potential_energy()
berendsen.run(500)
dyn.run()
self.reCenter()
testEnergy = self.particle.get_potential_energy()
if (testEnergy < self.bestEnergy):
self.bestEnergy = testEnergy
self.bestParticle = deepcopy(self.particle)
elif ((testEnergy + .5) > self.bestEnergy):
self.particle = NanoClass.genParticle(self.definingString, int(self.numberOfAtoms))
MaxwellBoltzmannDistribution(self.particle,2000*units.kB)
self.particle.get_potential_energy()
if (testEnergy < self.bestEnergy):
self.bestEnergy = testEnergy
self.bestParticle = deepcopy(self.particle)
return self.getAnswer()
def solve(self):
self.setStatusDone("Initializing configuration...")
self.particle = NanoClass.genParticle(self.definingString, int(self.numberOfAtoms))
self.reCenter()
self.bestEnergy = self.particle.get_potential_energy()
self.bestParticle = self.particle.copy()
berendsen = Langevin(self.particle, 5*units.fs, units.kB*2000,0.005)
dyn = FIRE(atoms=self.particle)
dyn.run(500)
MaxwellBoltzmannDistribution(self.particle,2000*units.kB)
MAXIMUM_ITERATIONS = 20
ITERATION = 0
BEST_POTENTIAL_ENERGY = 999999
BEST_PARTICLE = None
queue = [( self.particle.get_potential_energy(), self.particle)]
pDone=float(ITERATION)/MAXIMUM_ITERATIONS
self.setStatusDone(str(math.floor(pDone*100))+"% | "+self.remainingTime(pDone))
self.checkTimeout()
current_particle = self.bestParticle.copy()
calc = EMT()
current_particle.set_calculator(calc)
self.setSolution(self.getAnswer(current_particle, current_particle.get_potential_energy()))
while ITERATION < MAXIMUM_ITERATIONS:
new_parent = heappop(queue)[1].copy()
calc = EMT()
new_parent.set_calculator(calc)
#print new_parent.get_positions()
#print new_parent.get_potential_energy()
for x in range(5):
new_child = self.create_child_from(new_parent)
potential_energy = copy.deepcopy(new_child.get_potential_energy())
heappush(queue, (potential_energy, new_child))
if potential_energy < BEST_POTENTIAL_ENERGY:
#print "--------------- NEW BEST FOUND ---------------"
#print "POTENTIAL ENERGY = ", potential_energy
BEST_POTENTIAL_ENERGY = potential_energy
self.bestParticle = new_child
#print new_child.positions
pDone=float(ITERATION)/MAXIMUM_ITERATIONS
self.setStatusDone(str(math.floor(pDone*100))+"% | "+self.remainingTime(pDone))
self.checkTimeout()
self.setSolution(self.getAnswer(self.bestParticle, BEST_POTENTIAL_ENERGY))
ITERATION += 1
return self.getAnswer(self.bestParticle, BEST_POTENTIAL_ENERGY)