###################################################################### # GA Program #4: Simulates an initial population of 200 organisms to # reach the goal of having all 4s for their genome ###################################################################### import sys, os sys.path.append(os.path.join(os.path.dirname(os.getcwd()), 'src')) import genetic as g g.population_data['maximum_generation'] = 1000 g.population_data['chromosome'] = [0] * 200 pop = g.population_constructor(g.population_data) g.population_simulate(pop, 100, 'never', 'pop', 0.1, 'result.txt')
import genetic as g
pdata = \
{
'nucleotide_list' : [1, 2, 3, 4],
'chromosome_length' : 200,
'chromosome_type' : 'defined',
'chromosome' : [1] * 200,
'background_mutation' : 0.0001,
'genome_size' : 1,
'population_size' : 200,
'fitness_function' : 'default',
'mutation_scheme' : 'default',
'additional_mutation_rate' : 0.01,
'mutation_type' : 'point',
'goal' : 4,
'maximum_generation' : 5000,
'prepopulation_control' : 'default',
'mating' : 'default',
'postpopulation_control' : 'default',
'generation_events' : 'default',
'report' : 'default'
}
for chromosome_length in range(200, 1600, 100):
pdata['chromosome'] = [0] * chromosome_length
pop = g.population_constructor(pdata)
g.population_simulate(pop, 100, 'never', 'pop', 0.1,
str(chromosome_length) + 'result.txt')
import genetic as g
pdata = \
{
'nucleotide_list' : [1, 2, 3, 4],
'chromosome_length' : 200,
'chromosome_type' : 'defined',
'chromosome' : [1] * 200,
'background_mutation' : 0.0001,
'genome_size' : 1,
'population_size' : 200,
'fitness_function' : 'default',
'mutation_scheme' : 'default',
'additional_mutation_rate' : 0.01,
'mutation_type' : 'point',
'goal' : 4,
'maximum_generation' : 5000,
'prepopulation_control' : 'default',
'mating' : 'default',
'postpopulation_control' : 'default',
'generation_events' : 'default',
'report' : 'default'
}
for chromosome_length in range(200, 1600, 100):
pdata['chromosome'] = [0] * chromosome_length
pop = g.population_constructor(pdata)
g.population_simulate(pop, 100, 'never', 'pop', 0.1,
str(chromosome_length)+'result.txt')
###################################################################### # GA Program #4: Simulates an initial population of 200 organisms to # reach the goal of having all 4s for their genome ###################################################################### import sys, os sys.path.append(os.path.join(os.path.dirname(os.getcwd()), 'copads')) import genetic as g g.population_data['maximum_generation'] = 1000 g.population_data['chromosome'] = [0] * 200 pop = g.population_constructor(g.population_data) g.population_simulate(pop, 100, 'never', 'pop', 0.1, 'result.txt')
