Welcome to LEAP: Library for Evolutionary Algorithms in Python’s documentation!

Contents:

• Quickstart Guide
  • Using LEAP
    • Simple Example
    • Genetic Algorithm Example
    • More Examples
  • Documentation
  • Installing from Source
    • Run the Test Suite
  • Acknowledgements
  • Citing LEAP
• LEAP Concepts
  • Core Classes
  • Operator Pipeline
  • Detailed Explanations
    • Individuals
    • Decoders
    • Representations
    • Problems
    • Operators
    • Contexts
    • Probes
    • Parsimony
    • Visualizations
• Prebuilt Algorithms
  • ea_solve()
    • Example
  • generational_ea()
    • Example
• Building New Algorithms
  • Deciding on a suitable representation
    • Decoders for binary representations
    • Impact on representation on choice of pipeline operators
    • LEAP supports three numeric representations
    • Support for exotic representations
  • Defining a Problem subclass
  • Possibly defining or choosing a special Individual subclass
  • Putting all that together
    • Evolutionary algorithm examples
• Distributed LEAP
  • Synchronous fitness evaluations
    • Components
    • Example
    • Separate Examples
  • Asynchronous fitness evaluations
    • Example
    • DistributedIndividual
    • Separate Examples
• Multiobjective Optimization
  • Using generalized_nsga_2
    • Example
  • Creating a tailored NSGA-II
    • Example
  • Representing multiple fitnesses
  • Asynchronous steady-state multiobjective optimization
  • References
• Cookbook
  • Enforcing problem bounds constraints
    • Bounds for initialization
    • Enforcing bounds during mutation
• Common Problems
  • min() returns the worst individual for minimization problems
  • Missing pipeline operator arguments
• Roadmap
• API
  • Subpackages
    • leap_ec.binary_rep package
    • leap_ec.contrib package
    • leap_ec.distrib package
    • leap_ec.executable_rep package
    • leap_ec.int_rep package
    • leap_ec.landscape_features package
    • leap_ec.multiobjective package
    • leap_ec.real_rep package
    • leap_ec.segmented_rep package
  • Submodules
  • leap_ec.algorithm module
    • generational_ea()
    • multi_population_ea()
    • random_search()
    • stop_at_generation()
  • leap_ec.data module
  • leap_ec.decoder module
    • Decoder
    • IdentityDecoder
  • leap_ec.global_vars module
  • leap_ec.individual module
    • Individual
    • RobustIndividual
    • WholeEvaluatedIndividual
  • leap_ec.ops module
    • CooperativeEvaluate
    • Crossover
    • NAryCrossover
    • Operator
    • UniformCrossover
    • clone()
    • compute_expected_probability()
    • compute_population_values()
    • concat_combine()
    • const_evaluate()
    • cyclic_selection()
    • elitist_survival()
    • evaluate()
    • grouped_evaluate()
    • insertion_selection()
    • iteriter_op()
    • iterlist_op()
    • listiter_op()
    • listlist_op()
    • migrate()
    • migration_metric()
    • naive_cyclic_selection()
    • pool()
    • proportional_selection()
    • random_bernoulli_vector()
    • random_selection()
    • sus_selection()
    • tournament_selection()
    • truncation_selection()
  • leap_ec.parsimony module
    • koza_parsimony()
    • lexical_parsimony()
  • leap_ec.probe module
    • AttributesCSVProbe
    • BestSoFarIterProbe
    • BestSoFarProbe
    • CartesianPhenotypePlotProbe
    • FitnessPlotProbe
    • FitnessStatsCSVProbe
    • HeatMapPhenotypeProbe
    • HistPhenotypePlotProbe
    • PopulationMetricsPlotProbe
    • SumPhenotypePlotProbe
    • best_of_gen()
    • num_fixated_metric()
    • pairwise_squared_distance_metric()
    • print_individual()
    • print_population()
    • print_probe()
    • sum_of_variances_metric()
  • leap_ec.problem module
    • AlternatingProblem
    • AverageFitnessProblem
    • ConstantProblem
    • CooperativeProblem
    • ExternalProcessProblem
    • FitnessOffsetProblem
    • FunctionProblem
    • Problem
    • ScalarProblem
    • concat_combine()
  • leap_ec.representation module
    • Representation
  • leap_ec.simple module
    • ea_solve()
  • leap_ec.statistical_helpers module
    • collect_distribution()
    • equals_gaussian()
    • equals_uniform()
    • stochastic_chisquare()
    • stochastic_equals()
  • leap_ec.util module
    • birth_brander()
    • get_step()
    • inc_births()
    • inc_generation()
    • is_flat()
    • is_iterable()
    • is_sequence()
    • print_list()
    • wrap_curry()
  • Module contents
    • leap_logger_name
• References

Indices and tables

• Index

• Module Index

• Search Page