PyGen/run_sim.py at master · SavinaRoja/PyGen · GitHub

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#! /usr/bin/python

import argparse
import sys
import os.path

from Flower import Flower #Code for a flower, in Flower.py
from random import randint #A rmethod for creating random integers

def run_sim(pop_size, max_fit, selection, runs = 1, output = sys.stdout, style = 'verbose'):
    for run in range(runs):
        population = [] #Create a list to hold the elements of the population
        for i in range(pop_size): #Fill the list with flowers
            population.append(Flower())

        generation = 0
        maxreached = False
        while not maxreached:
            #Sort the population by individual fitness
            population.sort(reverse = True, key = lambda Flower: Flower.fitness)

            mostfit = population[:int(pop_size / selection)]
            if style == 'verbose':
                output.write('GENERATION {0} - Top Fitness: {1}\n'.format(generation,
                                                                          mostfit[0].fitness))
            elif style == 'csv':
                pass

            if mostfit[0].fitness >= max_fit: #Check for threshold fitness
                maxreached = True #Escape the while loop conditions to end the program
                if style == 'verbose':
                    output.write('Maximum Fitness Achieved!\n')
                elif style == 'csv':
                    output.write(str(generation))
                    output.write(',')


            if not maxreached:
                population = [] #Empty the population list to start over
                for i in range(pop_size): #Re-populate from the most fit flowers
                    #Randomly pick two parents from the most fit population
                    firstparent = mostfit[randint(0,len(mostfit)-1)]
                    secondparent = mostfit[randint(0,len(mostfit)-1)]

                    #Mate the two parents to create a child flower for the next generation
                    population.append(firstparent.mate(secondparent))

                generation += 1 #Increase the generation counter by one

        if not run % 1000 and run != 0:
            output.write('\n')

def main():
    '''do stuff'''
    parser = argparse.ArgumentParser(description = 'PyGen Parser')
    parser.add_argument('-b', '--batch', action ='store', type = int, default = 0,
                        help = 'Run a number of iterations of the simulation')
    parser.add_argument('-p', '--popsize', action ='store', type = int, default = 64,
                        help = 'Set the population size')
    parser.add_argument('-f', '--fitness', action ='store', type = int, default = 32,
                        help = 'Set the fitness goal')
    parser.add_argument('-s', '--selection', action = 'store', type = float, default = 2,
                        help = 'Set the population size divisor for selection')
    parser.add_argument('-o', '--output', action = 'store',
                        help = 'Choose filename for CSV output. Or enter "stdout"')
    style_group = parser.add_mutually_exclusive_group()
    style_group.add_argument('-v', '--verbose', const = 'verbose', action = 'store_const', default = False,
                        help = 'Overrides output to be verbose, ie. information from each generation')
    style_group.add_argument('-c', '--csv', const = 'csv', action = 'store_const', default = False,
                        help = 'Overrides output to csv format, ie. information after each run')
    args = parser.parse_args()

    batchruns = args.batch #Number of runs to use for batch mode
    popsize = args.popsize #The size of the flower population
    maxfit = args.fitness #Set the fitness threshold
    selection = args.selection #Selection stringency factor

    if not args.output:
        if batchruns:
            args.output = 'batch_output.csv'
        else:
            args.output = 'stdout'

    if args.output == 'stdout':
        if args.csv:
            outstyle = args.csv
        else:
            outstyle = 'verbose'
        if not batchruns:
            batchruns = 1
        run_sim(popsize, maxfit, selection, output = sys.stdout, runs = batchruns, style = outstyle)

    else:
        if args.verbose:
            outstyle = args.verbose
        else:
            outstyle = 'csv'
        outstring = args.output
        if not os.path.splitext(args.output)[1] == '.csv':
            outstring += '.csv'
        if not batchruns:
            batchruns = 1
        with open(outstring, 'w') as outfile:
            run_sim(popsize, maxfit, selection, output = outfile, runs = batchruns, style = outstyle)

if __name__ == '__main__':
    main()