npl.optimization.genetic_algoritm package

Submodules

npl.optimization.genetic_algoritm.ConvexHull module

npl.optimization.genetic_algoritm.ConvexHull.locate_convex_hull(start_population, unsuccessful_gens_for_convergence, energy_calculator, local_env_calculator, local_feature_classifier)[source]

npl.optimization.genetic_algoritm.CutAndSpliceOperator module

class npl.optimization.genetic_algoritm.CutAndSpliceOperator.CutAndSpliceOperator(max_radius, recompute_neighbor_list=True, normal_dir=None)[source]

Bases: object

cut_and_splice(p1, p2, fixed_stoichiometry=True)[source]

npl.optimization.genetic_algoritm.ExchangeOperator module

class npl.optimization.genetic_algoritm.ExchangeOperator.ExchangeOperator(p)[source]

Bases: object

random_exchange(particle, n_exchanges=None)[source]

npl.optimization.genetic_algoritm.LocalOptimizationOperator module

class npl.optimization.genetic_algoritm.LocalOptimizationOperator.LocalOptimizationOperator(energy_calculator, environment_energies)[source]

Bases: object

local_optimization(particle)[source]

npl.optimization.genetic_algoritm.MutationOperator module

class npl.optimization.genetic_algoritm.MutationOperator.MutationOperator(p, symbols)[source]

Bases: object

draw_from_geometric_distribution()[source]
random_mutation(particle, n_mutations=None, symbols=None)[source]

npl.optimization.genetic_algoritm.NichedPopulation module

class npl.optimization.genetic_algoritm.NichedPopulation.NichedPopulation(niche_symbol, n_atoms)[source]

Bases: Population

add_offspring(particle)[source]
compute_fitness(particle)[source]
gaussian_tournament(n_individuals, tournament_size, mean=None)[source]
get_as_list()[source]
get_convex_hull()[source]
get_niche(particle)[source]
random_selection(n_individuals)[source]
tournament_selection(n_individuals, tournament_size)[source]
class npl.optimization.genetic_algoritm.NichedPopulation.Population[source]

Bases: object

add_offspring(particle)[source]
compute_fitness(particle)[source]
gaussian_tournament(n_individuals, tournament_size, mean=None)[source]
random_selection(n_individuals)[source]
tournament_selection(n_individuals, tournament_size)[source]

npl.optimization.genetic_algoritm.SingleParticleGA module

npl.optimization.genetic_algoritm.SingleParticleGA.compute_fitness(particle, min_energy, max_energy, energy_key)[source]
npl.optimization.genetic_algoritm.SingleParticleGA.run_single_particle_ga(start_population, unsuccessful_gens_for_convergence, energy_calculator, local_env_calculator, local_feature_classifier, environment_energies)[source]

Module contents