def generate_children(self, number_of_children, number_of_mutations, info, lookup, magnets, ref_trajectories, real_bfield=None):
# first age, as we are now creating children
self.age_bcell()
children = []
# Generate the IDfiled for the parent, as we need to calculate it fully here.
original_bfield = None
original_fitness = None
if real_bfield == None:
original_bfield, original_fitness = fg.calculate_cached_trajectory_fitness(info, lookup, magnets, self.genome, ref_trajectories)
fitness_error = abs(self.fitness - original_fitness)
logging.debug("Estimated fitness to real fitness error %2.10e"%(fitness_error))
else :
original_bfield = real_bfield
original_fitness = fg.calculate_trajectory_fitness_from_array(original_bfield, info, ref_trajectories)
fitness_error = abs(self.fitness - original_fitness)
logging.debug("Using real bfield")
original_magnets = fg.generate_per_magnet_array(info, self.maglist, magnets)
maglist = copy.deepcopy(self.maglist)
mutation_list = self.create_mutant(number_of_mutations)
maglist.mutate_from_list(mutation_list)
new_magnets = fg.generate_per_magnet_array(info, maglist, magnets)
update = fg.compare_magnet_arrays(original_magnets, new_magnets, lookup)
updated_bfield = np.array(original_bfield)
for beam in update.keys() :
if update[beam].size != 0:
updated_bfield = updated_bfield - update[beam]
self.fitness = fg.calculate_trajectory_fitness_from_array(updated_bfield, info, ref_trajectories)
for i in range(number_of_children):
maglist = copy.deepcopy(self.maglist)
mutation_list = self.create_mutant(number_of_mutations)
maglist.mutate_from_list(mutation_list)
new_magnets = fg.generate_per_magnet_array(info, maglist, magnets)
update = fg.compare_magnet_arrays(original_magnets, new_magnets, lookup)
child = ID_Shim_BCell()
child.mutations = number_of_mutations
child.genome = mutation_list
child.maglist = self.maglist
updated_bfield = np.array(original_bfield)
for beam in update.keys() :
if update[beam].size != 0:
updated_bfield = updated_bfield - update[beam]
child.fitness = fg.calculate_trajectory_fitness_from_array(updated_bfield, info, ref_trajectories)
children.append(child)
logging.debug("Child created with fitness : %2.10e" % (child.fitness))
return children
def generate_children(self,
number_of_children,
number_of_mutations,
info,
lookup,
magnets,
ref_trajectories,
real_bfield=None):
# first age, as we are now creating children
self.age_bcell()
children = []
# Generate the IDfiled for the parent, as we need to calculate it fully here.
original_bfield = None
if real_bfield == None:
original_bfield, calculated_fitness = fg.calculate_cached_trajectory_fitness(
info, lookup, magnets, self.genome, ref_trajectories)
fitness_error = abs(self.fitness - calculated_fitness)
logging.debug("Estimated fitness to real fitness error %2.10e" %
(fitness_error))
self.fitness = calculated_fitness
else:
original_bfield = real_bfield
logging.debug("Using real bfield")
original_magnets = fg.generate_per_magnet_array(
info, self.genome, magnets)
for i in range(number_of_children):
maglist = copy.deepcopy(self.genome)
available_magnets = {
key: range(len(magnets.magnet_sets[key]))
for key in magnets.magnet_sets.keys()
}
maglist.mutate(number_of_mutations, available_magnets)
new_magnets = fg.generate_per_magnet_array(info, maglist, magnets)
update = fg.compare_magnet_arrays(original_magnets, new_magnets,
lookup)
child = ID_BCell()
child.mutations = number_of_mutations
child.genome = maglist
updated_bfield = np.array(original_bfield)
for beam in update.keys():
if update[beam].size != 0:
updated_bfield = updated_bfield - update[beam]
child.fitness = fg.calculate_trajectory_fitness_from_array(
updated_bfield, info, ref_trajectories)
#child.create(info, lookup, magnets, maglist, ref_total_id_field)
children.append(child)
logging.debug("Child created with fitness : %f" % (child.fitness))
return children
def create(self, info, lookup, magnets, maglist, ref_trajectories, number_of_changes, original_bfield):
self.maglist = maglist
self.changes = number_of_changes
self.create_genome(number_of_changes)
maglist = copy.deepcopy(self.maglist)
maglist.mutate_from_list(self.genome)
new_magnets = fg.generate_per_magnet_array(info, maglist, magnets)
original_magnets = fg.generate_per_magnet_array(info, self.maglist, magnets)
update = fg.compare_magnet_arrays(original_magnets, new_magnets, lookup)
updated_bfield = np.array(original_bfield)
for beam in update.keys() :
if update[beam].size != 0:
updated_bfield = updated_bfield - update[beam]
self.fitness = fg.calculate_trajectory_fitness_from_array(updated_bfield, info, ref_trajectories)
def create(self, info, lookup, magnets, maglist, ref_trajectories,
number_of_changes, original_bfield):
self.maglist = maglist
self.changes = number_of_changes
self.create_genome(number_of_changes)
maglist = copy.deepcopy(self.maglist)
maglist.mutate_from_list(self.genome)
new_magnets = fg.generate_per_magnet_array(info, maglist, magnets)
original_magnets = fg.generate_per_magnet_array(
info, self.maglist, magnets)
update = fg.compare_magnet_arrays(original_magnets, new_magnets,
lookup)
updated_bfield = np.array(original_bfield)
for beam in update.keys():
if update[beam].size != 0:
updated_bfield = updated_bfield - update[beam]
self.fitness = fg.calculate_trajectory_fitness_from_array(
updated_bfield, info, ref_trajectories)
def generate_children(self,
number_of_children,
number_of_mutations,
info,
lookup,
magnets,
ref_trajectories,
real_bfield=None):
# first age, as we are now creating children
self.age_bcell()
children = []
# Generate the IDfiled for the parent, as we need to calculate it fully here.
original_bfield = None
original_fitness = None
if real_bfield is None:
original_bfield, original_fitness = fg.calculate_cached_trajectory_fitness(
info, lookup, magnets, self.genome, ref_trajectories)
fitness_error = abs(self.fitness - original_fitness)
logging.debug("Estimated fitness to real fitness error %2.10e" %
(fitness_error))
else:
original_bfield = real_bfield
original_fitness = fg.calculate_trajectory_fitness_from_array(
original_bfield, info, ref_trajectories)
fitness_error = abs(self.fitness - original_fitness)
logging.debug("Using real bfield")
original_magnets = fg.generate_per_magnet_array(
info, self.maglist, magnets)
available = magnets.availability()
maglist = copy.deepcopy(self.maglist)
mutation_list = self.create_mutant(number_of_mutations, available)
maglist.mutate_from_list(mutation_list)
new_magnets = fg.generate_per_magnet_array(info, maglist, magnets)
update = fg.compare_magnet_arrays(original_magnets, new_magnets,
lookup)
updated_bfield = np.array(original_bfield)
for beam in update.keys():
if update[beam].size != 0:
updated_bfield = updated_bfield - update[beam]
self.fitness = fg.calculate_trajectory_fitness_from_array(
updated_bfield, info, ref_trajectories)
for i in range(number_of_children):
maglist = copy.deepcopy(self.maglist)
mutation_list = self.create_mutant(number_of_mutations, available)
maglist.mutate_from_list(mutation_list)
new_magnets = fg.generate_per_magnet_array(info, maglist, magnets)
update = fg.compare_magnet_arrays(original_magnets, new_magnets,
lookup)
child = ID_Shim_BCell()
child.mutations = number_of_mutations
child.genome = mutation_list
child.maglist = self.maglist
updated_bfield = np.array(original_bfield)
for beam in update.keys():
if update[beam].size != 0:
updated_bfield = updated_bfield - update[beam]
child.fitness = fg.calculate_trajectory_fitness_from_array(
updated_bfield, info, ref_trajectories)
children.append(child)
logging.debug("Child created with fitness : %2.10e" %
(child.fitness))
return children
