Python Population.population方法代码示例

# 需要导入模块: from population import Population [as 别名]
# 或者: from population.Population import population [as 别名]
def run(pop,
        surveyList, 
        nostdout=False, 
        allsurveyfile=False,
        scint=False):
    """ Run the surveys and detect the pulsars."""

    # print the population
    if not nostdout:
        print "Running doSurvey on population..."
        print pop

    # loop over the surveys we want to run on the pop file
    surveyPops = []
    for surv in surveyList:
        s = Survey(surv)
        s.discoveries = 0
        if not nostdout:
            print "\nRunning survey {0}".format(surv)

        # create a new population object to store discovered pulsars in 
        survpop = Population()
        # HERE SHOULD INCLUDE THE PROPERTIES OF THE ORIGINAL POPULATION
        
        # counters 
        nsmear = 0
        nout = 0
        ntf = 0
        ndet = 0
        # loop over the pulsars in the population list
        for psr in pop.population:
            # pulsar could be dead (evolve!) - continue if so
            if psr.dead:
                continue

            # is the pulsar over the detection threshold?
            snr = s.SNRcalc(psr, pop)

            # add scintillation, if required
            # modifying S/N rather than flux is sensible because then
            # a pulsar can have same flux but change S/N in repeated surveys
            if scint:
                snr = s.scint(psr, snr)

            if snr > s.SNRlimit:
                ndet += 1
                psr.snr = snr
                survpop.population.append(psr)
                
                # check if the pulsar has been detected in other 
                # surveys
                if not psr.detected:
                    # if not, set to detected and increment
                    # number of discoveries by the survey
                    psr.detected = True
                    s.discoveries += 1

            elif snr == -1.0:
                nsmear += 1
            elif snr == -2.0:
                nout += 1
            else:
                ntf += 1

        # report the results
        if not nostdout:
            print "Number detected by survey {0} = {1}".format(surv,ndet)
            print "Of which are discoveries = {0}".format(s.discoveries)
            print "Number too faint = {0}".format(ntf)
            print "Number smeared = {0}".format(nsmear)
            print "Number out = {0}".format(nout)
            print "\n"

        d = Detections(ndet=ndet, 
                       ntf=ntf, 
                       nsmear=nsmear, 
                       nout=nout,
                       ndisc=s.discoveries)
        surveyPops.append([surv,survpop,d])

    if allsurveyfile:
        allsurvpop = Population()
        allsurvpop.population = [psr for psr in pop.population if psr.detected]
        surveyPops.append([None, allsurvpop, None])

    return surveyPops

# 需要导入模块: from population import Population [as 别名]
# 或者: from population.Population import population [as 别名]
        print("Gen: {}\tPopulation: {}\tFitnesses: {}\tAverage Fitness: {}"
              .format(current_generation, ga.population, ga.fitnesses, avg))

        # Selection at random for mating
        lowest_fitness_index = ga.fitnesses.index(min(ga.fitnesses))
        del ga.population[lowest_fitness_index]
        del ga.fitnesses[lowest_fitness_index]

        # Crossover/Repr
        parents = ga.random_mate_select(ga.population)
        children = ga.reproduce(parents[0], parents[1])

        parents2 = ga.random_mate_select(ga.population)
        children = children + ga.reproduce(parents2[0], parents2[1])

        # Mutation with small independent probability
        for child in children:
            if random.random() < ga.p_mutation:
                children[children.index(child)] = ga.mutate(child)

        ga.population = children
        ga.fitnesses.clear()
        current_generation += 1

        if current_generation == ga.max_generations:
            print("\nGlobal Optimum: ")
            print("Individual: {}\tFitness: {}\tGeneration: {}\n"
                .format(ga.global_optimum[0], ga.global_optimum[1], ga.global_optimum[2]))

            num_gens = input("How many more generations would you like to run? (0 to stop)\n")
            ga.max_generations += int(num_gens)