def find_schemas(self, fitness, num_schemas):
"""Find the given number of unique schemas using a genetic algorithm
Arguments:
- fitness - A callable object (ie. function) which will evaluate
the fitness of a motif.
- num_schemas - The number of unique schemas with good fitness
that we want to generate.
"""
start_population = \
Organism.function_population(self.motif_generator.random_motif,
self.initial_population,
fitness)
finisher = SimpleFinisher(num_schemas, self.min_generations)
# set up the evolver and do the evolution
evolver = GenerationEvolver(start_population, self.selector)
evolved_pop = evolver.evolve(finisher.is_finished)
# convert the evolved population into a PatternRepository
schema_info = {}
for org in evolved_pop:
# convert the Genome from a MutableSeq to a Seq so that
# the schemas are just strings (and not array("c")s)
seq_genome = org.genome.toseq()
schema_info[str(seq_genome)] = org.fitness
return PatternRepository(schema_info)
def find_schemas(self, fitness, num_schemas):
"""Find the given number of unique schemas using a genetic algorithm
Arguments:
o fitness - A callable object (ie. function) which will evaluate
the fitness of a motif.
o num_schemas - The number of unique schemas with good fitness
that we want to generate.
"""
start_population = \
Organism.function_population(self.motif_generator.random_motif,
self.initial_population,
fitness)
finisher = SimpleFinisher(num_schemas, self.min_generations)
# set up the evolver and do the evolution
evolver = GenerationEvolver(start_population, self.selector)
evolved_pop = evolver.evolve(finisher.is_finished)
# convert the evolved population into a PatternRepository
schema_info = {}
for org in evolved_pop:
# convert the Genome from a MutableSeq to a Seq so that
# the schemas are just strings (and not array("c")s)
seq_genome = org.genome.toseq()
schema_info[str(seq_genome)] = org.fitness
return PatternRepository(schema_info)
def test_function_population(self):
"""Create a population using a function to generate genomes.
"""
num_orgs = 10
new_pop = Organism.function_population(genome_generator,
num_orgs, fitness_calculator)
self.assertEqual(len(new_pop), num_orgs, "Expected %s organisms, "
"got %s" % (num_orgs, len(new_pop)))
for org in new_pop:
self.assertIsInstance(org, Organism.Organism,
"Expected to get an organism, got %r" % org)
exp_fit = fitness_calculator(org.genome)
self.assertEqual(org.fitness, exp_fit, "Expected fitness of %s, "
"got %s" % (org.fitness, exp_fit))
def test_function_population(self):
"""Create a population using a function to generate genomes.
"""
num_orgs = 10
new_pop = Organism.function_population(genome_generator, num_orgs,
fitness_calculator)
assert len(new_pop) == num_orgs, "Expected %s organisms, got %s" \
% (num_orgs, len(new_pops))
for org in new_pop:
assert isinstance(org, Organism.Organism), \
"Expected to get an organism, got %r" % org
exp_fit = fitness_calculator(org.genome)
assert org.fitness == exp_fit, \
"Expected fitness of %s, got %s" % (org.fitness, exp_fit)
def test_function_population(self):
"""Create a population using a function to generate genomes.
"""
num_orgs = 10
new_pop = Organism.function_population(genome_generator,
num_orgs, fitness_calculator)
assert len(new_pop) == num_orgs, "Expected %s organisms, got %s" \
% (num_orgs, len(new_pops))
for org in new_pop:
assert isinstance(org, Organism.Organism), \
"Expected to get an organism, got %r" % org
exp_fit = fitness_calculator(org.genome)
assert org.fitness == exp_fit, \
"Expected fitness of %s, got %s" % (org.fitness, exp_fit)
def test_function_population(self):
"""Create a population using a function to generate genomes.
"""
num_orgs = 10
new_pop = Organism.function_population(genome_generator, num_orgs,
fitness_calculator)
self.assertEqual(
len(new_pop), num_orgs, "Expected %s organisms, "
"got %s" % (num_orgs, len(new_pop)))
for org in new_pop:
self.assertIsInstance(org, Organism.Organism,
"Expected to get an organism, got %r" % org)
exp_fit = fitness_calculator(org.genome)
self.assertEqual(
org.fitness, exp_fit, "Expected fitness of %s, "
"got %s" % (org.fitness, exp_fit))
