def threaded_simulate (self, thread):
half = int (POP_SIZE / 2)
start = 0 if thread == 1 else half
end = start + half
population = self.population [start:end]
for c in population:
c.fitness = simulate_model (c.genotype)
self.population[start:end] = population
def threaded_simulate(self, thread):
half = int(POP_SIZE / 2)
start = 0 if thread == 1 else half
end = start + half
population = self.population[start:end]
for c in population:
c.fitness = simulate_model(c.genotype)
self.population[start:end] = population
def unthreaded_simulate (self):
#print "inside unthreaded_simulate"
# Run population through simulation.
for c in self.population:
c.set_fitness (simulate_model (c.genotype,self.t_1,self.t_2))
print "simulate %s, %s" % (str(self.t_1),str(self.t_2))
for c in sorted(self.population, key= lambda c: c.fitness):
print "{: <12} {}".format (c.genotype, c.fitness)
print ""
def unthreaded_simulate(self):
#print "inside unthreaded_simulate"
# Run population through simulation.
for c in self.population:
c.set_fitness(simulate_model(c.genotype, self.t_1, self.t_2))
print "simulate %s, %s" % (str(self.t_1), str(self.t_2))
for c in sorted(self.population, key=lambda c: c.fitness):
print "{: <12} {}".format(c.genotype, c.fitness)
print ""
def run (self):
starti = self.starti
endi = self.endi
num_iter = len (self.population) / 2
for i in range (starti, endi):
c = self.population [i]
fitness = 0
try:
fitness = simulate_model (c.genotype,self.t_1,self.t_2)
except:
pass
if fitness >= 1:
self.population [i].fitness = fitness
else:
self.population [i].fitness = 1
def run(self):
starti = self.starti
endi = self.endi
num_iter = len(self.population) / 2
for i in range(starti, endi):
c = self.population[i]
fitness = 0
try:
fitness = simulate_model(c.genotype, self.t_1, self.t_2)
except:
pass
if fitness >= 1:
self.population[i].fitness = fitness
else:
self.population[i].fitness = 1
def run (self):
#print "inside MP run"
while True:
c = self.task_queue.get()
fitness = 0
if c is None:
break
try:
fitness = simulate_model (c[0].genotype,c[1],c[2])
except:
pass
if fitness >= 1:
c[0].fitness = fitness
else:
c[0].fitness = 1
self.result_queue.put (c[0])
def run(self):
#print "inside MP run"
while True:
c = self.task_queue.get()
fitness = 0
if c is None:
break
try:
fitness = simulate_model(c[0].genotype, c[1], c[2])
except:
pass
if fitness >= 1:
c[0].fitness = fitness
else:
c[0].fitness = 1
self.result_queue.put(c[0])
#!/usr/bin/env python
import simulate
import fit_data
import model_data
import pandas as pd
import tools
model = simulate.load_model('volume_reference.txt')
#df = model_data.get_model_parameters_as_dataframe(model)
#df.to_csv('used_model_parameters.csv')
#set paras
#param_list = ['V_b', 'V_os', '[c_e]', '[c_i]', 'k_deg', 'k_nutrient', 'modulus_adjustment', 'phi', 'pi_t0', 'pi_tc_0']
#df = pd.read_csv('used_model_parameters.csv')
#model = model_data.set_model_parameters_from_dataframe(model, df, param_list, row=1)
#run simu
simulation_result = simulate.simulate_model(model, end_time=7200)
simulate.plot((simulation_result, ), legend=True)
