import random

import string

Target=Hello,world!

def calc_ fitness(source, target):

 fitval = 0

 for i in range(0, len(source)):

 fitval += (ord(target[i]) - ord(source[i])) ** 2

 return(fitval)

def mutate(parent1, parent2):

child_dna = parent1['dna'][:]

# Mix both DNAs

start = random.randint(0, len(parent2['dna']) - 1)

stop = random.randint(0, len(parent2['dna']) - 1)

if start > stop:

stop, start = start, stop

child_dna[start:stop] = parent2['dna'][start:stop]

# Mutate one position

charpos = random.randint(0, len(child_dna) - 1)

child_dna[charpos] = chr(ord(child_dna[charpos]) + random.randint(-1,1))

child_fitness = calc_fitness(child_dna, target)

return({'dna': child_dna, 'fitness': child_fitness})

GENSIZE = 20

genepool = []

for i in range(0, GENSIZE):

dna = [random.choice(string.printable[:-5]) for j in range(0, len(target))]

fitness = calc_fitness(dna, target)

candidate = {'dna': dna, 'fitness': fitness }

genepool.append(candidate)

def mutate(parent1, parent2):

child_dna = parent1['dna'][:]

# Mix both DNAs

start = random.randint(0, len(parent2['dna']) - 1)

stop = random.randint(0, len(parent2['dna']) - 1)

if start > stop:

stop, start = start, stop

child_dna[start:stop] = parent2['dna'][start:stop]

def random_parent(genepool):

 wRndNr = random.random() * random.random() * (GENSIZE - 1)

 wRndNr = int(wRndNr)

 return(genepool[wRndNr])

def dump_genepool(generation,genepool);

for candidate in genepool:

print %6i%6i %15s%( generation,candidate[fitness],

.join(candidate[dna])

)

Print

GENSIZE = 20

genepool = []

for i in range(0, GENSIZE):

 dna = [random.choice(string.printable[:-5]) for j in range(0, len(target))]

 fitness = calc_fitness(dna, target)

 candidate = {'dna': dna, 'fitness': fitness }

 genepool.append(candidate)

generation = 0

while True:

 generation +=1

 genepool.sort(key=lambda candidate: candidate['fitness'])

 dump_genepool(generation,genepool)

 if genepool[0]['fitness'] == 0:

 # Target reached

 break

 parent1 = random_parent(genepool)

 parent2 = random_parent(genepool)

 child = mutate(parent1, parent2)

 if child['fitness'] < genepool[-1]['fitness']:

 genepool[-1] = child

this is a pyton program I want to some one to change it in matlab program and the quation says

Your program must include at least 3 user-defined function (fitness.m, get_parent.m and mutate.m).

The user can enter any user defined string as the evolutionary target up to 30 characters max.

The program should randomly generate the first generation of parents from which to breed.

The program should print out every 100^th iteration and the best-fit individual along with its fitness in the command window.