def __init__(self, config):
super().__init__(config=config, config_fields=[
'memory_min_size', 'memory_max_size',
'neuron_inter_mincount', 'neuron_inter_maxcount',
'neuron_edges_mincount', 'neuron_edges_maxcount',
'mutator',
])
self.neuron_types = NeuronType.xano()
def __init__(self, config):
super().__init__(config=config,
config_fields=[
'memory_min_size',
'memory_max_size',
'neuron_inter_mincount',
'neuron_inter_maxcount',
'neuron_edges_mincount',
'neuron_edges_maxcount',
'mutator',
])
self.neuron_types = NeuronType.xano()
def mutate(self, nb_intermediate_neuron:int, nb_total_neuron:int,
neuron_types:iter, edges:iter):
"""Return the data received in input, modified according to
mutation settings.
nb_intermediate_neuron: integer equal to number of intermediate neuron.
nb_total_neuron: integer equal to total number of neuron.
neuron_types: iterable of NeuronType.
edges: iterable of 2-tuple describing links between neurons.
"""
MUTATION_RATE = self.mutation_rate
mutation = lambda: random() <= MUTATION_RATE
mutate_nb_neuron = mutation(), mutation()
mutate_neuron_type = mutation(), mutation()
mutate_edges = mutation(), mutation()
del mutation
if any(mutate_nb_neuron):
add, rmv = mutate_nb_neuron
neuron_types = list(neuron_types) # allow modifications
if add:
nb_total_neuron += 1
nb_intermediate_neuron += 1
neuron_types.append(random_choice(NeuronType.xano()))
if commons.log_level() >= logging.INFO:
LOGGER.info('Mutator ' + str(self)
+ ' add new neuron of type '
+ neuron_types[-1].name + '.')
if rmv and nb_intermediate_neuron > 0:
nb_total_neuron -= 1
nb_intermediate_neuron -= 1
target_idx = randrange(0, len(neuron_types))
if commons.log_level() >= logging.INFO:
LOGGER.info('Mutator ' + str(self)
+ ' remove neuron ' + str(target_idx) + ' ('
+ neuron_types[target_idx].name + ').')
del neuron_types[target_idx]
if any(mutate_neuron_type):
modify, swap = mutate_neuron_type
neuron_types = list(neuron_types) # allow modifications
if modify: # modify just one type
target_idx = randrange(0, len(neuron_types))
new_type = random_choice(NeuronType.xano())
if commons.log_level() >= logging.INFO:
LOGGER.info('Mutator ' + str(self) + ' modify type of '
+ str(target_idx) + ' from '
+ neuron_types[target_idx].name + ' to '
+ new_type.name + '.'
)
neuron_types[target_idx] = new_type
if swap: # swap two types in the list
target1_idx = randrange(0, len(neuron_types))
target2_idx = randrange(0, len(neuron_types))
neuron_types[target1_idx], neuron_types[target2_idx] = (
neuron_types[target2_idx], neuron_types[target1_idx]
)
if commons.log_level() >= logging.INFO:
LOGGER.info('Mutator ' + str(self) + ' swaps '
+ str(target1_idx) + ' ('
+ neuron_types[target2_idx].name + ') and '
+ str(target1_idx) + ' ('
+ neuron_types[target2_idx].name + ').'
)
if any(mutate_edges):
add, rmv = mutate_edges
edges = list(edges) # allow modifications
if add: # add one new edge
target1_idx = randrange(1, nb_total_neuron + 1)
target2_idx = randrange(1, nb_total_neuron + 1)
edges.append((target1_idx, target2_idx))
if commons.log_level() >= logging.INFO:
LOGGER.info('Mutator ' + str(self) + ' get an edge '
+ str((target1_idx, target2_idx)) + '.')
if rmv: # remove one existing edge
idx = randrange(0, len(edges))
if commons.log_level() >= logging.INFO:
LOGGER.info('Mutator ' + str(self) + ' lose its edge '
+ str(edges[idx]) + '.')
neuron_types = tuple(neuron_types)
edges = tuple(edges)
return nb_intermediate_neuron, neuron_types, edges