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energy_cooling.py
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energy_cooling.py
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import operator
import random
import csv
import cProfile
import numpy as np
import eaneatGP
import init_conf
import os.path
from deap import base
from deap import creator
from deap import tools
from deap import gp
#from deap import algorithms
import gp_conf as neat_gp
from my_operators import safe_div, mylog, mypower2, mypower3, mysqrt, myexp
pset = gp.PrimitiveSet("MAIN", 8)
pset.addPrimitive(operator.add, 2)
pset.addPrimitive(operator.sub, 2)
pset.addPrimitive(operator.mul, 2)
pset.addPrimitive(safe_div, 2)
pset.addPrimitive(np.cos, 1)
pset.addPrimitive(np.sin, 1)
#pset.addPrimitive(myexp, 1)
pset.addPrimitive(mylog, 1)
pset.addPrimitive(mypower2, 1)
pset.addPrimitive(mypower3, 1)
pset.addPrimitive(mysqrt, 1)
pset.addPrimitive(np.tan, 1)
pset.addPrimitive(np.tanh, 1)
pset.addEphemeralConstant("rand101", lambda: random.uniform(-1, 1))
pset.renameArguments(ARG0='x0',ARG1='x1', ARG2='x2', ARG3='x3', ARG4='x4', ARG5='x5', ARG6='x6', ARG7='x7', ARG8='x8')
creator.create("FitnessMin", base.Fitness, weights=(-1.0,))
creator.create("FitnessTest", base.Fitness, weights=(-1.0,))
creator.create("Individual", neat_gp.PrimitiveTree, fitness=creator.FitnessMin, fitness_test=creator.FitnessTest)
toolbox = base.Toolbox()
toolbox.register("expr", gp.genFull, pset=pset, min_=1, max_=3)
toolbox.register("individual", tools.initIterate, creator.Individual, toolbox.expr)
toolbox.register("population", init_conf.initRepeat, list, toolbox.individual)
toolbox.register("compile", gp.compile, pset=pset)
def evalSymbReg(individual, test, points):
func = toolbox.compile(expr=individual)
vector = points[8]#[data[8] for data in points]
result = np.sum((func(*np.asarray(points)[:8]) - vector)**2)
return np.sqrt(result/len(points[0])),
def energy_coolng(n_corr,p):
n_archivot = './data_corridas/EnergyCooling/test_%d_%d.txt' % (p, n_corr)
n_archivo = './data_corridas/EnergyCooling/train_%d_%d.txt' % (p, n_corr)
if not (os.path.exists(n_archivo) or os.path.exists(n_archivot)):
direccion = "./data_corridas/EnergyCooling/energy_efficiency_Cooling.txt"
with open(direccion) as spambase:
spamReader = csv.reader(spambase, delimiter=' ', skipinitialspace=True)
num_c = sum(1 for line in open(direccion))
num_r = len(next(csv.reader(open(direccion), delimiter=' ', skipinitialspace=True)))
Matrix = np.empty((num_r, num_c,))
for row, c in zip(spamReader, range(num_c)):
for r in range(num_r):
try:
Matrix[r, c] = row[r]
except ValueError:
print 'Line {r} is corrupt', r
break
if not os.path.exists(n_archivo):
long_train=int(len(Matrix.T)*.7)
data_train = random.sample(Matrix.T, long_train)
np.savetxt(n_archivo, data_train, delimiter=",", fmt="%s")
if not os.path.exists(n_archivot):
long_test=int(len(Matrix.T)*.3)
data_test = random.sample(Matrix.T, long_test)
np.savetxt(n_archivot, data_test, delimiter=",", fmt="%s")
with open(n_archivo) as spambase:
spamReader = csv.reader(spambase, delimiter=',', skipinitialspace=True)
num_c = sum(1 for line in open(n_archivo))
num_r = len(next(csv.reader(open(n_archivo), delimiter=',', skipinitialspace=True)))
Matrix = np.empty((num_r, num_c,))
for row, c in zip(spamReader, range(num_c)):
for r in range(num_r):
try:
Matrix[r, c] = row[r]
except ValueError:
print 'Line {r} is corrupt' , r
break
data_train=Matrix[:]
with open(n_archivot) as spambase:
spamReader = csv.reader(spambase, delimiter=',', skipinitialspace=True)
num_c = sum(1 for line in open(n_archivot))
num_r = len(next(csv.reader(open(n_archivot), delimiter=',', skipinitialspace=True)))
Matrix = np.empty((num_r, num_c,))
for row, c in zip(spamReader, range(num_c)):
for r in range(num_r):
try:
Matrix[r, c] = row[r]
except ValueError:
print 'Line {r} is corrupt' , r
break
data_test=Matrix[:]
toolbox.register("evaluate", evalSymbReg, test=False, points=data_train)
toolbox.register("evaluate_test", evalSymbReg, test=True, points=data_test)
def main(n_corr, p):
energy_coolng(n_corr, p)
pop_size=500
#toolbox.register("select",selElitistAndTournament, k_elitist=int(0.1*pop_size), k_tournament=pop_size - int(0.1*pop_size), tournsize=3)
toolbox.register("select",tools.selTournament, tournsize=3)
toolbox.register("mate", gp.cxOnePoint)
toolbox.register("expr_mut", gp.genFull, min_=0, max_=3)
toolbox.register("mutate", gp.mutUniform, expr=toolbox.expr_mut, pset=pset)
toolbox.decorate("mate", gp.staticLimit(key=operator.attrgetter("height"), max_value=17))
toolbox.decorate("mutate", gp.staticLimit(key=operator.attrgetter("height"), max_value=17))
pop = toolbox.population(n=pop_size)
hof = tools.HallOfFame(3)
stats_fit = tools.Statistics(lambda ind: ind.fitness.values)
stats_size = tools.Statistics(len)
mstats = tools.MultiStatistics(fitness=stats_fit, size=stats_size)
mstats.register("avg", np.mean)
mstats.register("std", np.std)
mstats.register("min", np.min)
mstats.register("max", np.max)
cxpb = 0.7
mutpb = 0.3
ngen = 100
params = ['best_of_each_specie', 2, 'yes']
neat_cx = True
neat_alg = True
neat_pelit = 0.5
neat_h = 0.15
problem = "EnergyCooling"
pop, log = eaneatGP.neat_GP(pop, toolbox, cxpb, mutpb, ngen, neat_alg, neat_cx, neat_h, neat_pelit, n_corr, p, params, problem, stats=mstats, halloffame=hof, verbose=True)
#pop, log = algorithms.eaSimple(pop, toolbox, cxpb, mutpb, ngen, problem, p, n_corr,stats=mstats, halloffame=hof, verbose=True)
return pop, log, hof
def run(number, problem):
n = 1
while n <= number:
main(n, problem)
n += 1
if __name__ == "__main__":
n = 1
while n < 6:
#cProfile.run('print main(n, 93); print')
main(n, 9)
n += 1