pychemia.searcher package

Routines related to stochastic optimization techniques

Subpackages

• pychemia.searcher.tests package
  • Submodules
  • pychemia.searcher.tests.test_searcher module

Submodules

pychemia.searcher.annealing module

class pychemia.searcher.annealing.SimulatedAnnealing(population, params, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

set_params(params)

pychemia.searcher.ant module

class pychemia.searcher.ant.AntColony(population, params, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

set_params(params)

pychemia.searcher.bee module

class pychemia.searcher.bee.BeeAlgorithm(population, params=None, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

create_foragers(scout, n)

get_params()

process_scouts(scouts, selection)

run_one()

set_params(params)

Set all the parameters required by the bee algorithm, Check right values for all the parameters

Parameters:params –

pychemia.searcher.firefly module

class pychemia.searcher.firefly.FireFly(population, params=None, generation_size=32, stabilization_limit=10, target_value=None)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

set_params(params)

pychemia.searcher.genetic module

class pychemia.searcher.genetic.GeneticAlgorithm(population, params=None, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

set_params(params)

pychemia.searcher.grey module

class pychemia.searcher.grey.GreyWolf(population, params=None, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

set_params(params)

pychemia.searcher.harmony module

class pychemia.searcher.harmony.HarmonySearch(population, params=None, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

Run one cycle for the Harmony Search Method

set_params(params)

Set the parameters for the Harmony Search algorithm There are 4 parameters

Parameters:params –

pychemia.searcher.mhm module

class pychemia.searcher.mhm.MinimaHoppingMethod(population, params, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

class MinimaHopping

get_params()

run_one()

set_params(params)

pychemia.searcher.searcher module

class pychemia.searcher.searcher.Searcher(population, generation_size=32, stabilization_limit=10, target_value=None, searcher_id=None)

Bases: object

actives_in_generation

advance(father, son, change)

clean()

correct_extras(changedb=False)

enforce_generation_size()

get_all_generations(generation_number=None)

get_generation(generation_number=None)

Return all the elements tagged as belonging to a given generation

Parameters:generation_number – Number of generation to get Returns:(list) Identifiers of all candidates for a given generation number Return type:list

get_params()

pass_to_new_generation(entry_id, reason=None)

print_status(level='DEBUG')

recover(changedb=False)

replace_by_changed(entry_id_old, reason=None)

replace_by_other(entry_id_old, entry_id_new, reason=None)

replace_by_random(entry_id_old, reason=None)

replace_failed()

run()

Execute the total number of cycles

Returns:

run_one()

save_generations()

save_info()

searcher_name

set_generation(entry_id, value)

set_params(params)

to_dict

update_generation()

update_lineages()

write_change(entry_id, change)

pychemia.searcher.swarm module

class pychemia.searcher.swarm.ParticleSwarm(population, params=None, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

set_params(params)

pychemia.searcher.swarm2 module

class pychemia.searcher.swarm2.ParticleSwarm(population, params=None, generation_size=32, stabilization_limit=10)

Bases: pychemia.searcher.searcher.Searcher

get_params()

run_one()

set_params(params)