gistfile1.py

# imports
import BBP
import numpy
import random
import time
import wx
from math import pi, sqrt, log10
from deap import base
from deap import creator
from deap import tools
from deap import algorithms
from scoop import futures
 
# GA Configuration
creator.create("FitnessMin", base.Fitness, weights=(-1.0,))
creator.create("Individual", list, fitness=creator.FitnessMin)
toolbox = base.Toolbox()
 
# Attribute generator
FLT_M1_min, FLT_M1_max = 0.0, 1.0
FLT_M2_min, FLT_M2_max = 0.0, 1.0
FLT_M3_min, FLT_M3_max = 0.0, 1.0
N_CYCLES = 1
toolbox.register("attr_M1", random.uniform, FLT_M1_min, FLT_M1_max)
toolbox.register("attr_M2", random.uniform, FLT_M2_min, FLT_M2_max)
toolbox.register("attr_M3", random.uniform, FLT_M3_min, FLT_M3_max)
 
# Structure initializers
toolbox.register("individual", tools.initCycle, creator.Individual,(toolbox.attr_M1,
toolbox.attr_M2,toolbox.attr_M3), n = N_CYCLES)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)
 
# Fitness function
def evaluate(individual, am, bm):
        M1 = individual[0]
        M2 = individual[1]
        M3 = individual[2]
        
        # BBP Function
        a, b = BBP.bbp(M1, M2, M3)
        error_a = abs(20*log10(a)-20*log10(am))
        error_b = abs(20*log10(b)-20*log10(bm))
        # Evaluation of the result
        evaluation = sqrt(error_a) + sqrt(error_b)
        return evaluation,

# Operator registering
toolbox.register("mate", tools.cxTwoPoints)
toolbox.register("mutate", tools.mutGaussian,mu=0.0, sigma=0.2, indpb=0.2)
toolbox.register("select", tools.selTournament, tournsize=4)
# Parallelization
toolbox.register("map", futures.map)

# vars
class file_vars:
        def __init__(self):
                self.loop = []
                self.a = []
                self.b = []

def load_files():
        path = './file/file'
        content = [line.rstrip('\n') for line in open(path)]
        for line in content:
                word = line.split()
                if word[0]=='loop': file_vars.loop.append(float(word[2]))
                if word[0]=='a': file_vars.a.append(float(word[2]))
                if word[0]=='b': file_vars.b.append(float(word[2]))

def main(am, bm):
        # Initialization the basic random number generator.
        random.seed(64)
        # Initials
        CXPB, MUTPB, NGEN, MU = 0.5, 0.2, 1, 4
        # Generation of population
        pop = toolbox.population(n = MU)
        toolbox.register("evaluate", evaluate, am=am, bm=bm)
        hof = tools.HallOfFame(1)
        stats = tools.Statistics(lambda ind: ind.fitness.values)
        stats.register("avg", numpy.mean)
        stats.register("std", numpy.std)
        stats.register("min", min)
        stats.register("max", max)
        algorithms.eaSimple(pop, toolbox, CXPB, MUTPB, NGEN, stats=stats,
        halloffame=hof, verbose=True)
        return pop, stats, hof

if __name__ == "__main__":
        start_time = time.time()
        ea_result = futures.map(
            main,
            file_vars.a
            file_vars.b
        )

        for pop, stats, hof in ea_result:
            print("Best individual is %s" % hof)
            results.append(hof[0])
                
        print time.time() - start_time, "seconds"