*************** ECsPy Reference *************** This chapter provides a complete reference to all of the functionality included in ECsPy. ======================== Evolutionary Computation ======================== .. autoclass:: ecspy.ec.EvolutionExit :members: .. autoclass:: ecspy.ec.Bounder :members: .. autoclass:: ecspy.ec.Individual :members: .. autoclass:: ecspy.ec.EvolutionaryComputation :members: .. autoclass:: ecspy.ec.DEA :members: .. autoclass:: ecspy.ec.EDA :members: .. autoclass:: ecspy.ec.ES :members: .. autoclass:: ecspy.ec.GA :members: .. autoclass:: ecspy.ec.SA :members: --------- Functions --------- An evolutionary computation is composed of many parts: - an archiver -- stores solutions separate from the population (e.g., in a multiobjective EC) - an evaluator -- measures the fitness of candidate solutions; problem-dependent - a generator -- creates new candidate solutions; problem-dependent - a migrator -- moves individuals to other populations (in the case of distributed ECs) - observers -- view the progress of an EC in operation; may be a list of observers - a replacer -- determines the survivors of a generation - a selector -- determines the parents of a generation - terminators -- determine whether the evolution should stop; may be a list of terminators - variators -- modify candidate solutions; may be a list of variators Each of these parts may be specified to create custom ECs to suit particular problems. ^^^^^^^^^ Archivers ^^^^^^^^^ .. automodule:: ecspy.archivers :members: ^^^^^^^^^^ Evaluators ^^^^^^^^^^ .. automodule:: ecspy.evaluators :members: ^^^^^^^^^^ Generators ^^^^^^^^^^ Generator functions are problem-specific. They are used to create the initial set of candidate solutions needed by the evolutionary computation. All generator functions have the following arguments: - *random* -- the random number generator object - *args* -- a dictionary of keyword arguments ^^^^^^^^^ Migrators ^^^^^^^^^ .. automodule:: ecspy.migrators :members: ^^^^^^^^^ Observers ^^^^^^^^^ .. automodule:: ecspy.observers :members: ^^^^^^^^^ Replacers ^^^^^^^^^ .. automodule:: ecspy.replacers :members: ^^^^^^^^^ Selectors ^^^^^^^^^ .. automodule:: ecspy.selectors :members: ^^^^^^^^^^ Teminators ^^^^^^^^^^ .. automodule:: ecspy.terminators :members: ^^^^^^^^^ Variators ^^^^^^^^^ .. automodule:: ecspy.variators :members: =========================== Particle Swarm Optimization =========================== .. automodule:: ecspy.swarm :members: ---------- Topologies ---------- Additionally, particle swarms make use of topologies, which determine the logical relationships among particles in the swarm (i.e., which ones belong to the same "neighborhood"). .. automodule:: ecspy.topologies :members: ======================================== Evolutionary Multiobjective Optimization ======================================== .. automodule:: ecspy.emo :members: ======== Analysis ======== .. automodule:: ecspy.analysis :members: ================== Benchmark Problems ================== .. autoclass:: ecspy.benchmarks.Benchmark :members: .. autoclass:: ecspy.benchmarks.Binary :members: --------------------------- Single-Objective Benchmarks --------------------------- .. autoclass:: ecspy.benchmarks.Ackley :members: .. autoclass:: ecspy.benchmarks.Griewank :members: .. autoclass:: ecspy.benchmarks.Rastrigin :members: .. autoclass:: ecspy.benchmarks.Rosenbrock :members: .. autoclass:: ecspy.benchmarks.Schwefel :members: .. autoclass:: ecspy.benchmarks.Sphere :members: -------------------------- Multi-Objective Benchmarks -------------------------- .. autoclass:: ecspy.benchmarks.Kursawe :members: .. autoclass:: ecspy.benchmarks.DTLZ1 :members: .. autoclass:: ecspy.benchmarks.DTLZ2 :members: .. autoclass:: ecspy.benchmarks.DTLZ3 :members: .. autoclass:: ecspy.benchmarks.DTLZ4 :members: .. autoclass:: ecspy.benchmarks.DTLZ5 :members: .. autoclass:: ecspy.benchmarks.DTLZ6 :members: .. autoclass:: ecspy.benchmarks.DTLZ7 :members: ===================== Contributed Utilities ===================== .. automodule:: ecspy.contrib.utils :members: