def add_entries(client, database, key_makers, random_seed): molecule_db = stk.MoleculeMongoDb( mongo_client=client, database=database, molecule_collection='molecules', position_matrix_collection='position_matrices', jsonizer=stk.MoleculeJsonizer(key_makers=key_makers, ), ) num_atoms_db = stk.ValueMongoDb( mongo_client=client, collection='numAtoms', database=database, key_makers=key_makers, ) num_bonds_db = stk.ValueMongoDb( mongo_client=client, collection='numBonds', database=database, key_makers=key_makers, ) add_value = True for molecule in get_molecules(200, 5): molecule_db.put(molecule) num_bonds_db.put(molecule, molecule.get_num_bonds()) if add_value: num_atoms_db.put(molecule, molecule.get_num_atoms()) add_value ^= 1
def add_constructed_molecules( client, database, key_makers, ): constructed_molecule_db = stk.ConstructedMoleculeMongoDb( mongo_client=client, database=database, molecule_collection='molecules', position_matrix_collection='position_matrices', jsonizer=stk.ConstructedMoleculeJsonizer(key_makers=key_makers, ), ) num_atoms_db = stk.ValueMongoDb( mongo_client=client, collection='numAtoms', database=database, key_makers=key_makers, ) for bb1, bb2 in zip( get_molecules(200, 5), get_molecules(200, 5), ): molecule = stk.ConstructedMolecule(topology_graph=stk.polymer.Linear( building_blocks=(bb1, bb2), repeating_unit='AB', num_repeating_units=1, ), ) constructed_molecule_db.put(molecule) num_atoms_db.put(molecule, molecule.get_num_atoms()) num_atoms_db.put(bb1, bb1.get_num_atoms())
def name_db(mongo_client): """ A :class:`.ValueDatabase` for holding the names of molecules. """ return stk.ValueMongoDb( mongo_client=mongo_client, database='_stk_pytest_database', collection='name', key_makers=(stk.Smiles(), ), indices=(stk.Smiles().get_key_name(), ), )
def test_get_caching(mongo_client): collection = '_test_get_caching' database_name = '_test_get_caching' mongo_client.drop_database(database_name) database = stk.ValueMongoDb( mongo_client=mongo_client, collection=collection, database=database_name, ) molecule = stk.BuildingBlock('CCC') database.put(molecule, 43) database.get(molecule) database.get(molecule) cache_info = database._get.cache_info() assert cache_info.hits == 1 assert cache_info.misses == 1
def test_update_1(): """ Test that existing entries are updated. """ collection = '_test_update_1' database_name = '_test_update_1' client = pymongo.MongoClient() client.drop_database(database_name) database = stk.ValueMongoDb( mongo_client=client, collection=collection, database=database_name, put_lru_cache_size=0, get_lru_cache_size=0, ) molecule = stk.BuildingBlock('CCC') database.put(molecule, 12) assert_database_state( state1=get_database_state(database), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), v=12, ): 1, }), ) database.put(molecule, 43) assert_database_state( state1=get_database_state(database), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), v=43, ): 1, }), )
def test_put_caching(): collection = '_test_put_caching' database_name = '_test_put_caching' client = pymongo.MongoClient() client.drop_database(database_name) database = stk.ValueMongoDb( mongo_client=client, collection=collection, database=database_name, ) molecule = stk.BuildingBlock('CCC') database.put(molecule, 43) database.put(molecule, 43) cache_info = database._put.cache_info() assert cache_info.hits == 1 assert cache_info.misses == 1 database.put(molecule, 40) cache_info = database._put.cache_info() assert cache_info.hits == 1 assert cache_info.misses == 2
def _get_case_data(mongo_client): """ Get a :class:`.CaseData` instance. Parameters ---------- mongo_client : :class:`pymongo.MongoClient` The mongo client the database should connect to. """ # The basic idea here is that the _counter.get_count method will # return a different "fitness value" each time it is called. # When the test runs fitness_calculator.get_fitness_value(), if # caching is working, the same number as before will be returned. # However, if caching is not working, a different number will be # returned as the fitness value. db = stk.ValueMongoDb( mongo_client=mongo_client, collection='test_caching', database='_stk_pytest_database', ) fitness_calculator = stk.PropertyVector( property_functions=(_counter.get_count, ), input_database=db, output_database=db, ) molecule = stk.BuildingBlock('BrCCBr') fitness_value = fitness_calculator.get_fitness_value(molecule) return CaseData( fitness_calculator=fitness_calculator, molecule=molecule, fitness_value=fitness_value, )
import pytest import stk import pymongo from ..case_data import CaseData @pytest.fixture( params=( CaseData( database=stk.ValueMongoDb( mongo_client=pymongo.MongoClient(), collection='values', database='_stk_test_database_for_testing', put_lru_cache_size=0, get_lru_cache_size=0, ), molecule=stk.BuildingBlock('BrCCBr'), value=12, ), CaseData( database=stk.ValueMongoDb( mongo_client=pymongo.MongoClient(), collection='values', database='_stk_test_database_for_testing', put_lru_cache_size=128, get_lru_cache_size=128, ), molecule=stk.BuildingBlock('BrCCBr'), value=12, ),
def test_update_2(mongo_client): """ Test that existing entries are updated. In this test, you first create two separate entries, using different molecule keys. You then update both at the same time, with a database which uses both molecule keys. """ collection = '_test_update_2' database_name = '_test_update_2' mongo_client.drop_database(database_name) database1 = stk.ValueMongoDb( mongo_client=mongo_client, collection=collection, database=database_name, put_lru_cache_size=0, get_lru_cache_size=0, key_makers=( stk.InchiKey(), ), ) database2 = stk.ValueMongoDb( mongo_client=mongo_client, collection=collection, database=database_name, put_lru_cache_size=0, get_lru_cache_size=0, key_makers=( stk.Smiles(), ), ) database3 = stk.ValueMongoDb( mongo_client=mongo_client, collection=collection, database=database_name, put_lru_cache_size=0, get_lru_cache_size=0, key_makers=( stk.InchiKey(), stk.Smiles(), ), ) molecule = stk.BuildingBlock('CCC') database1.put(molecule, 12) assert_database_state( state1=get_database_state(database1), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), v=12, ): 1, }), ) # Should add another entry, as a different key maker is used. database2.put(molecule, 32) assert_database_state( state1=get_database_state(database1), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), v=12, ): 1, DatabaseEntry( SMILES=stk.Smiles().get_key(molecule), v=32, ): 1, }), ) # Should update both entries as both key makers are used. database3.put(molecule, 56) assert_database_state( state1=get_database_state(database1), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), SMILES=stk.Smiles().get_key(molecule), v=56, ): 2, }), )
def test_update_3(mongo_client): """ Test that existing entries are updated. In this test, you first create one entry with two keys. Then update the entry with databases, each using 1 different key. No duplicate entries should be made in the database this way. """ collection = '_test_update_3' database_name = '_test_update_3' mongo_client.drop_database(database_name) database1 = stk.ValueMongoDb( mongo_client=mongo_client, collection=collection, database=database_name, put_lru_cache_size=0, get_lru_cache_size=0, key_makers=( stk.InchiKey(), stk.Smiles(), ), ) database2 = stk.ValueMongoDb( mongo_client=mongo_client, collection=collection, database=database_name, put_lru_cache_size=0, get_lru_cache_size=0, key_makers=( stk.InchiKey(), ), ) database3 = stk.ValueMongoDb( mongo_client=mongo_client, collection=collection, database=database_name, put_lru_cache_size=0, get_lru_cache_size=0, key_makers=( stk.Smiles(), ), ) molecule = stk.BuildingBlock('CCC') database1.put(molecule, 12) assert_database_state( state1=get_database_state(database1), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), SMILES=stk.Smiles().get_key(molecule), v=12, ): 1 }), ) # Should update the entry. database2.put(molecule, 32) assert_database_state( state1=get_database_state(database1), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), SMILES=stk.Smiles().get_key(molecule), v=32, ): 1, }), ) # Should also update the entry. database3.put(molecule, 62) assert_database_state( state1=get_database_state(database1), state2=DatabaseState({ DatabaseEntry( InChIKey=stk.InchiKey().get_key(molecule), SMILES=stk.Smiles().get_key(molecule), v=62, ): 1, }), )
import pytest import stk from ..case_data import CaseData from ...utilities import MockMongoClient @pytest.fixture( params=( CaseData( database=stk.ValueMongoDb( mongo_client=MockMongoClient(), collection='values', lru_cache_size=0, ), molecule=stk.BuildingBlock('BrCCBr'), value=12, ), CaseData( database=stk.ValueMongoDb( mongo_client=MockMongoClient(), collection='values', lru_cache_size=128, ), molecule=stk.BuildingBlock('BrCCBr'), value=12, ), ), ) def mongo_db(request): return request.param
The value to put into the database. """ get_database: abc.Callable[[pymongo.MongoClient], stk.ValueMongoDb] molecule: stk.Molecule value: object @pytest.fixture( params=( lambda: CaseDataData( get_database=lambda mongo_client: stk.ValueMongoDb( mongo_client=mongo_client, collection='values', database='_stk_test_database_for_testing', put_lru_cache_size=0, get_lru_cache_size=0, ), molecule=stk.BuildingBlock('BrCCBr'), value=12, ), lambda: CaseDataData( get_database=lambda mongo_client: stk.ValueMongoDb( mongo_client=mongo_client, collection='values', database='_stk_test_database_for_testing', put_lru_cache_size=128, get_lru_cache_size=128, ), molecule=stk.BuildingBlock('BrCCBr'),
def main(): username = input('Username: '******'mongodb+srv://{username}:{password}@stk-vis-example.x4bkl.' 'mongodb.net/stk?retryWrites=true&w=majority') database = 'stk' client.drop_database(database) constructed_db = stk.ConstructedMoleculeMongoDb(client, database) atoms_db = stk.ValueMongoDb(client, 'Num Atoms') bonds_db = stk.ValueMongoDb(client, 'Num Bonds') energy_db = stk.ValueMongoDb(client, 'UFF Energy') macrocycle = uff( stk.ConstructedMolecule(topology_graph=stk.macrocycle.Macrocycle( building_blocks=( stk.BuildingBlock( smiles='BrCCBr', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='BrNNBr', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='BrOOBr', functional_groups=[stk.BromoFactory()], ), ), repeating_unit='ABC', num_repeating_units=2, ), )) atoms_db.put(macrocycle, macrocycle.get_num_atoms()) bonds_db.put(macrocycle, macrocycle.get_num_bonds()) energy_db.put(macrocycle, uff_energy(macrocycle)) constructed_db.put(macrocycle) polymer = uff( stk.ConstructedMolecule(topology_graph=stk.polymer.Linear( building_blocks=( stk.BuildingBlock( smiles='BrCCBr', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='BrNNBr', functional_groups=[stk.BromoFactory()], ), ), repeating_unit='AB', num_repeating_units=4, ), )) atoms_db.put(polymer, polymer.get_num_atoms()) bonds_db.put(polymer, polymer.get_num_bonds()) energy_db.put(polymer, uff_energy(polymer)) constructed_db.put(polymer) rotaxane = uff( stk.ConstructedMolecule(topology_graph=stk.rotaxane.NRotaxane( axle=stk.BuildingBlock.init_from_molecule(polymer), cycles=(stk.BuildingBlock( smiles=('C1=CC2=CC3=CC=C(N3)C=C4C=CC(=N4)' 'C=C5C=CC(=N5)C=C1N2'), ), ), repeating_unit='A', num_repeating_units=1, ), )) atoms_db.put(rotaxane, rotaxane.get_num_atoms()) bonds_db.put(rotaxane, rotaxane.get_num_bonds()) energy_db.put(rotaxane, uff_energy(rotaxane)) constructed_db.put(rotaxane) kagome = uff( stk.ConstructedMolecule(topology_graph=stk.cof.Honeycomb( building_blocks=( stk.BuildingBlock('BrC=CBr', [stk.BromoFactory()]), stk.BuildingBlock( smiles='Brc1cc(Br)cc(Br)c1', functional_groups=[stk.BromoFactory()], ), ), lattice_size=(2, 2, 1)), )) atoms_db.put(kagome, kagome.get_num_atoms()) bonds_db.put(kagome, kagome.get_num_bonds()) energy_db.put(kagome, uff_energy(kagome)) constructed_db.put(kagome) cc3 = stk.ConstructedMolecule(topology_graph=stk.cage.FourPlusSix( building_blocks=( stk.BuildingBlock( smiles='NC1CCCCC1N', functional_groups=[stk.PrimaryAminoFactory()], ), stk.BuildingBlock( smiles='O=Cc1cc(C=O)cc(C=O)c1', functional_groups=[stk.AldehydeFactory()], ), ), ), ) cc3 = uff(cc3) atoms_db.put(cc3, cc3.get_num_atoms()) bonds_db.put(cc3, cc3.get_num_bonds()) energy_db.put(cc3, uff_energy(cc3)) constructed_db.put(cc3)
def main(): parser = argparse.ArgumentParser() parser.add_argument('--mongodb_uri', help='The MongoDB URI for the database to connect to.', default='mongodb://localhost:27017/') args = parser.parse_args() logging.basicConfig(level=logging.INFO) # Use a random seed to get reproducible results. random_seed = 4 generator = np.random.RandomState(random_seed) logger.info('Making building blocks.') # Load the building block databases. fluoros = tuple( get_building_blocks( path=pathlib.Path(__file__).parent / 'fluoros.txt', functional_group_factory=stk.FluoroFactory(), )) bromos = tuple( get_building_blocks( path=pathlib.Path(__file__).parent / 'bromos.txt', functional_group_factory=stk.BromoFactory(), )) initial_population = tuple(get_initial_population(fluoros, bromos)) # Write the initial population. for i, record in enumerate(initial_population): write(record.get_molecule(), f'initial_{i}.mol') client = pymongo.MongoClient(args.mongodb_uri) db = stk.ConstructedMoleculeMongoDb(client) fitness_db = stk.ValueMongoDb(client, 'fitness_values') # Plot selections. generation_selector = stk.Best( num_batches=25, duplicate_molecules=False, ) stk.SelectionPlotter('generation_selection', generation_selector) mutation_selector = stk.Roulette( num_batches=5, random_seed=generator.randint(0, 1000), ) stk.SelectionPlotter('mutation_selection', mutation_selector) crossover_selector = stk.Roulette( num_batches=3, batch_size=2, random_seed=generator.randint(0, 1000), ) stk.SelectionPlotter('crossover_selection', crossover_selector) fitness_calculator = stk.PropertyVector( property_functions=( get_num_rotatable_bonds, get_complexity, get_num_bad_rings, ), input_database=fitness_db, output_database=fitness_db, ) fitness_normalizer = stk.NormalizerSequence( fitness_normalizers=( # Prevent division by 0 error in DivideByMean, by ensuring # a value of each property to be at least 1. stk.Add((1, 1, 1)), stk.DivideByMean(), # Obviously, because all coefficients are equal, the # Multiply normalizer does not need to be here. However, # it's here to show that you can easily change the relative # importance of each component of the fitness value, by # changing the values of the coefficients. stk.Multiply((1, 1, 1)), stk.Sum(), stk.Power(-1), ), ) ea = stk.EvolutionaryAlgorithm( num_processes=1, initial_population=initial_population, fitness_calculator=fitness_calculator, mutator=stk.RandomMutator( mutators=( stk.RandomBuildingBlock( building_blocks=fluoros, is_replaceable=is_fluoro, random_seed=generator.randint(0, 1000), ), stk.SimilarBuildingBlock( building_blocks=fluoros, is_replaceable=is_fluoro, random_seed=generator.randint(0, 1000), ), stk.RandomBuildingBlock( building_blocks=bromos, is_replaceable=is_bromo, random_seed=generator.randint(0, 1000), ), stk.SimilarBuildingBlock( building_blocks=bromos, is_replaceable=is_bromo, random_seed=generator.randint(0, 1000), ), ), random_seed=generator.randint(0, 1000), ), crosser=stk.GeneticRecombination(get_gene=get_functional_group_type, ), generation_selector=generation_selector, mutation_selector=mutation_selector, crossover_selector=crossover_selector, fitness_normalizer=fitness_normalizer, ) logger.info('Starting EA.') generations = [] for generation in ea.get_generations(50): for record in generation.get_molecule_records(): db.put(record.get_molecule()) generations.append(generation) # Write the final population. for i, record in enumerate(generation.get_molecule_records()): write(record.get_molecule(), f'final_{i}.mol') logger.info('Making fitness plot.') # Normalize the fitness values across the entire EA before # plotting the fitness values. generations = tuple( normalize_generations( fitness_calculator=fitness_calculator, fitness_normalizer=fitness_normalizer, generations=generations, )) fitness_progress = stk.ProgressPlotter( generations=generations, get_property=lambda record: record.get_fitness_value(), y_label='Fitness Value', ) fitness_progress.write('fitness_progress.png') fitness_progress.get_plot_data().to_csv('fitness_progress.csv') logger.info('Making rotatable bonds plot.') rotatable_bonds_progress = stk.ProgressPlotter( generations=generations, get_property=lambda record: get_num_rotatable_bonds(record. get_molecule()), y_label='Number of Rotatable Bonds', ) rotatable_bonds_progress.write('rotatable_bonds_progress.png')
def add_mixed_entries( client, database, key_makers, ): constructed_molecule_db = stk.ConstructedMoleculeMongoDb( mongo_client=client, database=database, molecule_collection='molecules', position_matrix_collection='position_matrices', jsonizer=stk.ConstructedMoleculeJsonizer(key_makers=key_makers, ), ) num_atoms_db = stk.ValueMongoDb( mongo_client=client, collection='numAtoms', database=database, key_makers=key_makers, ) num_bonds_db = stk.ValueMongoDb( mongo_client=client, collection='numBonds', database=database, key_makers=key_makers, ) cage1 = stk.ConstructedMolecule(topology_graph=stk.cage.FourPlusSix( building_blocks=( stk.BuildingBlock( smiles='BrC1C(Br)CCCC1', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='Brc1cc(Br)cc(Br)c1', functional_groups=[stk.BromoFactory()], ), ), ), ) constructed_molecule_db.put(cage1) num_atoms_db.put(cage1, cage1.get_num_atoms()) cage2 = stk.ConstructedMolecule(topology_graph=stk.cage.TwentyPlusThirty( building_blocks=( stk.BuildingBlock( smiles='BrC1C(Br)CCCC1', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='Brc1cc(Br)cc(Br)c1', functional_groups=[stk.BromoFactory()], ), ), ), ) constructed_molecule_db.put(cage2) num_atoms_db.put(cage2, cage2.get_num_atoms()) macrocycle = stk.ConstructedMolecule( topology_graph=stk.macrocycle.Macrocycle( building_blocks=( stk.BuildingBlock( smiles='BrCCBr', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='BrNNBr', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='BrOOBr', functional_groups=[stk.BromoFactory()], ), ), repeating_unit='ABC', num_repeating_units=2, ), ) num_atoms_db.put(macrocycle, macrocycle.get_num_atoms()) polymer = stk.ConstructedMolecule(topology_graph=stk.polymer.Linear( building_blocks=( stk.BuildingBlock( smiles='BrCCBr', functional_groups=[stk.BromoFactory()], ), stk.BuildingBlock( smiles='BrNNBr', functional_groups=[stk.BromoFactory()], ), ), repeating_unit='AB', num_repeating_units=4, ), ) rotaxane = stk.ConstructedMolecule(topology_graph=stk.rotaxane.NRotaxane( axle=stk.BuildingBlock.init_from_molecule(polymer), cycles=(stk.BuildingBlock.init_from_molecule(macrocycle), ), repeating_unit='A', num_repeating_units=1, ), ) constructed_molecule_db.put(polymer) constructed_molecule_db.put(macrocycle) constructed_molecule_db.put(rotaxane) num_bonds_db.put(rotaxane, rotaxane.get_num_bonds())