def main(self): ############ generate model from data ################## data = earthquakedata.dataremodel() path = 'data.dat' ######## map setting ####### data.longitudemax = 145 data.longitudemin = 140 data.latitudemax = 35 data.latitudemin = 30 data.Interval = 0.5 data.datareader(path) ######## setting end ###### data.selectyear = 2010 data.selectmonths = 1 data.selectmonthe = 12 data.setnum() data.findhappentimes() #data.setmodel() best = -100000 GAf = GA.GA() for i in range(0, 200 * 200): rf = randommodel.generatemodel(self.latitudenum,self.longitudebinnum) intPopulation = np.zeros((data.latitudenum , data.longitudebinnum ),float) intPopulation = randommodel.intergermodel(rf,self.latitudenum,self.longitudebinnum) score = GAf.Evalate(intPopulation,data) if score > best : best = score print "R best = ", best return best
def main(self):
############ generate model from data ##################
data = earthquakedata.dataremodel()
path = 'data.dat'
######## map setting #######
data.longitudemax = 145
data.longitudemin = 140
data.latitudemax = 35
data.latitudemin = 30
data.Interval = 0.5
data.datareader(path)
######## setting end ######
data.selectyear = 2010
data.selectmonths = 1
data.selectmonthe = 12
data.setnum()
data.findhappentimes()
#data.setmodel()
best = -100000
GAf = GA.GA()
for i in range(0, 200 * 200):
rf = randommodel.generatemodel(self.latitudenum,
self.longitudebinnum)
intPopulation = np.zeros((data.latitudenum, data.longitudebinnum),
float)
intPopulation = randommodel.intergermodel(rf, self.latitudenum,
self.longitudebinnum)
score = GAf.Evalate(intPopulation, data)
if score > best:
best = score
print "R best = ", best
return best
def main(self):
############ generate model from data ##################
data = earthquakedata.dataremodel()
path = 'data.dat'
######## map setting #######
data.longitudemax = 145
data.longitudemin = 140
data.latitudemax = 35
data.latitudemin = 30
data.Interval = 0.5
data.datareader(path)
######## setting end ######
data.selectyear = 2010
data.selectmonths = 1
data.selectmonthe = 12
data.setnum()
data.findhappentimes()
#data.setmodel()
#here's our data to plot, all normal Python lists
############# from data model end ########################
####################### GA start ########################
#n = 1 ###set n times
#best = Evalate(integerrandomforecat)
############# first Population ############################
newPopulation = np.zeros((self.Population_size, data.latitudenum , data.longitudebinnum ),float)
for i in range(0, self.Population_size):
newPopulation[i] = randommodel.generatemodel(data.latitudenum , data.longitudebinnum );
for i in range(0, self.Population_size):
self.Population.append(newPopulation[i])
######### loop ########################
best = -100000
for g in range(0,self.Generation):
score = np.zeros(len(self.Population),float)
for i in range(0, len(self.Population) ):
intPopulation = randommodel.intergermodel(self.Population[i], data.latitudenum , data.longitudebinnum );
score[i] = self.Evalate(intPopulation,data)
for i in range(0,len(score)):
if score[i] > best :
best = score[i]
self.P_sort(score)
while len(self.Population) > self.Population_size:
self.Population.pop()
score = np.zeros(len(self.Population),float)
for i in range(0, len(self.Population) ):
intPopulation = randommodel.intergermodel(self.Population[i], data.latitudenum , data.longitudebinnum )
score[i] = self.Evalate(intPopulation,data)
self.P_sort(score)
self.newpoolclear()
self.tournament_selection()
self.Corssover()
self.Mutation()
print "GAwithoutUNDX best = " , best
return best
def main(self):
############ generate model from data ##################
data = earthquakedata.dataremodel()
path = 'data.dat'
######## map setting #######
data.longitudemax = 145
data.longitudemin = 140
data.latitudemax = 35
data.latitudemin = 30
data.Interval = 0.5
data.datareader(path)
######## setting end ######
data.selectyear = 2010
data.selectmonths = 1
data.selectmonthe = 12
data.setnum()
data.findhappentimes()
#data.setmodel()
#here's our data to plot, all normal Python lists
############# from data model end ########################
####################### GA start ########################
#n = 1 ###set n times
#best = Evalate(integerrandomforecat)
############# first Population ############################
newPopulation = np.zeros((self.Population_size, data.latitudenum , data.longitudebinnum ),float)
for i in range(0, self.Population_size):
newPopulation[i] = randommodel.generatemodel(data.latitudenum , data.longitudebinnum );
for i in range(0, self.Population_size):
self.Population.append(newPopulation[i])
######### loop ########################
best = -100000
for g in range(0,self.Generation):
score = np.zeros(len(self.Population),float)
for i in range(0, len(self.Population) ):
intPopulation = randommodel.intergermodel(self.Population[i], data.latitudenum , data.longitudebinnum );
score[i] = self.Evalate(intPopulation,data)
for i in range(0,len(score)):
if score[i] > best :
best = score[i]
self.P_sort(score)
while len(self.Population) > self.Population_size:
self.Population.pop()
score = np.zeros(len(self.Population),float)
for i in range(0, len(self.Population) ):
intPopulation = randommodel.intergermodel(self.Population[i], data.latitudenum , data.longitudebinnum )
score[i] = self.Evalate(intPopulation,data)
self.P_sort(score)
self.newpoolclear()
self.tournament_selection()
self.Corssover()
self.Mutation()
print "GA best = " , best
return best