fr.iscpif.mgo.test

RastriginVector

trait RastriginVector extends problem.GAProblem with ModelFamilyGenome with fitness.MGFitness

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Inherited
  1. RastriginVector
  2. MGFitness
  3. ModelFamilyGenome
  4. Sigma
  5. ModelId
  6. GAProblem
  7. MG
  8. Scaling
  9. GAScaling
  10. GA
  11. RandomGenome
  12. Problem
  13. Evolution
  14. Elitism
  15. Breeding
  16. Archive
  17. Lambda
  18. Modifier
  19. A
  20. IndividualFilter
  21. Termination
  22. MF
  23. F
  24. P
  25. G
  26. AnyRef
  27. Any
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Type Members

  1. abstract type A

    Definition Classes
    ArchiveA
  2. case class EvolutionState(population: Population[Evolution.G, Evolution.P, Evolution.F, Evolution.MF], archive: Evolution.A, generation: Int, terminationState: Evolution.STATE, terminated: Boolean) extends Product with Serializable

    Represent a state of the evolution algorithm

    Represent a state of the evolution algorithm

    Definition Classes
    Evolution
  3. type F = Seq[Double]

    Definition Classes
    MGFitnessF
  4. type G = Genome

    Definition Classes
    ModelFamilyGenomeG
  5. abstract type MF

    the type of the meta-fitness

    the type of the meta-fitness

    Definition Classes
    MF
  6. type P = Double

    Definition Classes
    RastriginVectorP
  7. abstract type STATE

    Type of the state maintained to study the evolution of the algorithm

    Type of the state maintained to study the evolution of the algorithm

    Definition Classes
    Termination

Abstract Value Members

  1. abstract def breed(individuals: Seq[Individual[G, P, F]], a: A, size: Int)(implicit aprng: Random): Seq[G]

    Definition Classes
    Breeding
  2. abstract def combine(a1: A, a2: A): A

    Definition Classes
    Archive
  3. abstract def diff(original: A, modified: A): A

    Definition Classes
    Archive
  4. abstract def elitism(oldGeneration: Seq[Individual[G, P, F]], newGeneration: Seq[Individual[G, P, F]], archive: A)(implicit aprng: Random): Seq[Individual[G, P, F]]

    Definition Classes
    Elitism
  5. abstract def initialArchive: A

    Definition Classes
    Archive
  6. abstract def initialState: STATE

    Compute the initial state

    Compute the initial state

    returns

    the initial state

    Definition Classes
    Termination
  7. abstract def lambda: Int

    the size of the offspring

    the size of the offspring

    Definition Classes
    Lambda
  8. abstract def modelMasks: Range

  9. abstract def modify(individuals: Seq[Individual[G, P, F]], archive: A): Population[G, P, F, MF]

    Generate a population from a set of indiviuals

    Generate a population from a set of indiviuals

    individuals

    a set of individual

    returns

    the population with the meta-fitness for each individual

    Definition Classes
    Modifier
  10. abstract def terminated(population: ⇒ Population[G, P, F, MF], terminationState: STATE): (Boolean, STATE)

    Test if the algorithm has converged.

    Test if the algorithm has converged.

    population

    the current population

    terminationState

    the actual termination state

    returns

    a boolean which is equal to true if a terminal state has been detected and the new termination state

    Definition Classes
    Termination
  11. abstract def toArchive(individuals: Seq[Individual[G, P, F]]): A

    Definition Classes
    Archive

Concrete Value Members

  1. final def !=(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  4. def archive(a: A, individuals: Seq[Individual[G, P, F]]): A

    Definition Classes
    Archive
  5. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  6. lazy val bestFitness: IndexedSeq[Int]

  7. def buildRNG(seed: Long): Random

    Definition Classes
    Evolution
  8. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  10. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  11. def evaluate(phenotype: P, rng: Random): F

    Evaluate a phenotype

    Evaluate a phenotype

    phenotype

    the phenotype to evaluate

    returns

    the phenotype

    Definition Classes
    RastriginVectorProblem
  12. def evolve(implicit rng: Random): Iterator[EvolutionState]

    Definition Classes
    ScalingProblem
  13. def evolve(expression: (G, Random) ⇒ P, evaluation: (P, Random) ⇒ F)(implicit prng: Random): Iterator[EvolutionState]

    Run the evolutionary algorithm

    Run the evolutionary algorithm

    expression

    the genome expression

    evaluation

    the fitness evaluator

    returns

    an iterator over the states of the evolution

    Definition Classes
    Evolution
  14. def evolve(individuals: Seq[Individual[G, P, F]], a: A, expression: (G, Random) ⇒ P, evaluation: (P, Random) ⇒ F)(implicit aprng: Random): Iterator[EvolutionState]

    Run the evolutionary algorithm

    Run the evolutionary algorithm

    individuals

    the initial individuals

    expression

    the genome expression

    evaluation

    the fitness evaluator

    returns

    an iterator over the states of the evolution

    Definition Classes
    Evolution
  15. def express(g: G, rng: Random): Double

    Definition Classes
    RastriginVectorProblem
  16. def filter(individuals: Seq[Individual[G, P, F]]): Seq[Individual[G, P, F]]

    Filter the individuals

    Filter the individuals

    individuals

    the set of evaluated individuals

    returns

    the filtrated individuals

    Definition Classes
    IndividualFilter
  17. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  18. def fitness: SimpleLens[Seq[Double], F]

    Definition Classes
    MGFitnessMG
  19. def genome: SimpleLens[G, Seq[Double]]

    The entire genome with potentially additional information

    The entire genome with potentially additional information

    Definition Classes
    ModelFamilyGenomeGA
  20. lazy val genomeSize: Int

    Size of the value part of the genome

    Size of the value part of the genome

    Definition Classes
    RastriginVectorModelFamilyGenomeGAProblemGA
  21. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  22. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  23. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  24. lazy val masks: Seq[Seq[Boolean]]

  25. lazy val max: Seq[Double]

    Maximum scaled value in the correct order

    Maximum scaled value in the correct order

    Definition Classes
    RastriginVectorScaling
  26. lazy val min: Seq[Double]

    minimum scaled value in the correct order

    minimum scaled value in the correct order

    Definition Classes
    RastriginVectorScaling
  27. def modelId: Lens[G, G, Int, Int]

    Definition Classes
    ModelFamilyGenomeModelId
  28. def models: Int

    Definition Classes
    RastriginVectorModelFamilyGenome
  29. lazy val nbTrue: Seq[Int]

  30. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  31. final def notify(): Unit

    Definition Classes
    AnyRef
  32. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  33. def randomGenome(implicit rng: Random): Genome

    Definition Classes
    ModelFamilyGenomeGARandomGenome
  34. def scale(i: Individual[G, P, F]): Individual[G, P, F]

    Definition Classes
    Scaling
  35. def scale[MF](i: PopulationElement[G, P, F, MF]): PopulationElement[G, P, F, MF]

    Scale a population element genome from [0.0, 1.0] to the correct scale

    Scale a population element genome from [0.0, 1.0] to the correct scale

    i

    the population element to scale

    returns

    the scaled population element

    Definition Classes
    Scaling
  36. def scale(g: G): G

    Scale the genome from [0.0, 1.0] to the correct scale for the fitness evaluation

    Scale the genome from [0.0, 1.0] to the correct scale for the fitness evaluation

    g

    the genome to scale

    returns

    the scaled genome

    Definition Classes
    Scaling
  37. def scale(x: Seq[Double]): Seq[Double]

    Scale a vector according to the minimun and maximum

    Scale a vector according to the minimun and maximum

    x

    the vector to scale

    returns

    the scaled vector

    Definition Classes
    ScalingGAScaling
  38. def sigma: Lens[G, G, Seq[Double], Seq[Double]]

    Definition Classes
    ModelFamilyGenomeSigma
  39. def step(individuals: Seq[Individual[G, P, F]], archive: A, expression: (G, Random) ⇒ P, evaluation: (P, Random) ⇒ F)(implicit rng: Random): (Seq[Individual[G, P, F]], A)

    Evolve one step

    Evolve one step

    individuals

    the current population

    archive

    the current archive

    expression

    expression of the genome

    evaluation

    the fitness evaluator

    returns

    a new population of evaluated solutions

    Definition Classes
    Evolution
  40. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  41. def toPopulation(individuals: Seq[Individual[G, P, F]], a: A): Population[G, P, F, MF]

    Generate a population from a set of indiviuals that is filtered in a first time

    Generate a population from a set of indiviuals that is filtered in a first time

    individuals

    a set of individual

    returns

    the filtred population with the meta-fitness for each individual

    Definition Classes
    Modifier
  42. def toString(): String

    Definition Classes
    AnyRef → Any
  43. def values: Lens[G, G, Seq[Double], Seq[Double]]

    The value part of the genome actually used for the optimisation

    The value part of the genome actually used for the optimisation

    Definition Classes
    ModelFamilyGenomeGA
  44. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  45. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  46. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from fitness.MGFitness

Inherited from ModelFamilyGenome

Inherited from genome.Sigma

Inherited from ModelId

Inherited from problem.GAProblem

Inherited from fitness.MG

Inherited from problem.Scaling

Inherited from GAScaling

Inherited from genome.GA

Inherited from RandomGenome

Inherited from problem.Problem

Inherited from Evolution

Inherited from elitism.Elitism

Inherited from breed.Breeding

Inherited from archive.Archive

Inherited from Lambda

Inherited from modifier.Modifier

Inherited from archive.A

Inherited from modifier.IndividualFilter

Inherited from termination.Termination

Inherited from modifier.MF

Inherited from fitness.F

Inherited from phenotype.P

Inherited from genome.G

Inherited from AnyRef

Inherited from Any

Ungrouped