def solve(self):
#Create the initial particle from the defining string/number atoms
self.particle = genParticle(self.definingString,int(self.numberOfAtoms))
# self.definingString looks like: "Pt50Au30"
#print "my defining string is " + self.definingString
# self.numberOfAtoms looks like: "80" (you'll need to call int(self.numberOfAtoms))
#print "my number of atoms is " + self.numberOfAtoms
#do all of your solving stuff you want...
#FINAL_SOLUTION = IMPLEMENT_FINAL_SOLUTION()
a = {"symbol": "Pt", "x": 1, "y": 2, "z": 3}
b = {"symbol": "Au", "x": 2, "y": 1, "z": -2}
c = {"symbol": "Pt", "x": 1, "y": 1, "z": -2}
listOfAtoms = [a, b, c]
potentialEnergy = -325.43
dictionary_to_be_turned_into_json = {"atoms": listOfAtoms, "potentialEnergy": potentialEnergy}
actually_json = json.dumps(dictionary_to_be_turned_into_json)
# this gets returned to the parent class and shoved into the database as a string, then
# parsed as JSON on the page and displayed/drawn for the user
return actually_json
def solve(self):
#Create the initial particle from the defining string/number atoms
temp = 1750
mintemp = 150
self.particle = genParticle(self.definingString,int(self.numberOfAtoms))
if (len(self.particle) < 16):
temp = 1250
maxtemp = temp
berendsen = Langevin(self.particle, 2.5 * units.fs, units.kB * temp, 0.02)
# the 5.0 * units.fs is used instead of 0.1 * units.fs b/c it makes the program run faster
MaxwellBoltzmannDistribution(self.particle,units.kB * temp)
self.bestEnergy = self.particle.get_potential_energy()
self.bestParticle = deepcopy(self.particle)
self.reCenter()
self.getAnswer()
while (temp > mintemp):
berendsen = Langevin(self.particle, 2.5 * units.fs, units.kB * temp, 0.02)
berendsen.run(100)
testEnergy = self.particle.get_potential_energy()
self.bestEnergy = self.particle.get_potential_energy()
self.bestParticle = deepcopy(self.particle)
self.reCenter()
self.getAnswer()
temp -= 10
if (temp % 50 == 0):
self.bestEnergy = self.particle.get_potential_energy()
self.bestParticle = deepcopy(self.particle)
self.reCenter()
self.checkTimeout()
self.setSolution(self.getAnswer())
pDone=float(maxtemp - temp)/(maxtemp-mintemp)
self.setStatusDone(str(math.floor(pDone*100))+"% | "+self.remainingTime(pDone))
elif (temp <= mintemp):
dyn = FIRE(atoms=self.particle)
dyn.run(fmax=0.01)
self.bestEnergy = self.particle.get_potential_energy()
self.bestParticle = deepcopy(self.particle)
self.reCenter()
self.setSolution(self.getAnswer())
pDone=float(temp)/(maxtemp-mintemp)
self.setStatusDone(str(math.floor(pDone*100))+"% | "+self.remainingTime(pDone))
return self.getAnswer()
def solve(self):
#Create the initial particle from the defining string/number atoms
self.particle = genParticle(self.definingString,int(self.numberOfAtoms)); #Generates the base particle
self.bestParticles = []; #Initializes the list of bestParticles
self.bestEnergy = self.particle.get_potential_energy(); #Initializes best energy
self.bestParticle = deepcopy(self.particle); #Best particle is a copy of particle
heapq.heappush(self.bestParticles, (self.particle.get_potential_energy(), self.particle)); #Pushes particle to bestParticles
self.startTime = self.millis()
for i in range(100): #Mutates particle 100 times and pushes results into a heap
if i%5==0:
pDone=float(i)/100
self.setStatusDone(str(math.floor(pDone*100))+"% | Stage 1 | "+self.remainingTime(pDone))
self.checkTimeout()
self.bestParticle = self.mutate(self.particle);
heapq.heappush(self.bestParticles, (self.bestParticle.get_potential_energy(), self.bestParticle));
self.currentEnergy = 0;
self.currentParticle = None;
self.startTime = self.millis()
CALCULATIONS=2;
self.setStatusDone("100% | Stage 1 | Starting stage 2")
for i in range(CALCULATIONS):
if i%1==0 and i>0:
pDone=float(i)/CALCULATIONS
self.setStatusDone(str(math.floor(pDone*100))+"% | Stage 2 | "+self.remainingTime(pDone))
self.checkTimeout()
self.setSolution(self.getAnswer())
self.currentEnergy = 1000000;
self.newBestParticles = [];
for l in range(5):
self.newBestParticles.append(heapq.heappop(self.bestParticles));
self.bestParticles = deepcopy(self.newBestParticles);
self.children = self.breed(self.bestParticles);
for j in range(len(self.bestParticles)):
newparticle = self.mutate((self.bestParticles[j])[1]);
self.bestParticles[j] = (newparticle.get_potential_energy(), newparticle);
if((self.bestParticles[j])[0] < self.currentEnergy):
self.currentParticle = (self.bestParticles[j])[1];
self.currentEnergy = (self.bestParticles[j])[0];
for index in range(len(self.children)):
newparticle = (self.children[index]);
heapq.heappush(self.bestParticles, (newparticle.get_potential_energy(), newparticle));
self.veryBestParticle = heapq.heappop(self.bestParticles);
return self.getAnswer();
