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fr.iscpif.mgo.algorithm

noisypse

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object noisypse extends Imports

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  1. case class Genome(values: Array[Double], operator: Maybe[Int]) extends Product with Serializable

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  2. case class Individual(genome: Genome, historyAge: Long, phenotypeHistory: Array[Array[Double]], age: Long, mapped: Boolean = false, foundedIsland: Boolean = false) extends Product with Serializable

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  3. case class NoisyPSE(lambda: Int, phenotype: (Random, Vector[Double]) ⇒ Vector[Double], pattern: (Vector[Double]) ⇒ Vector[Int], aggregation: (Vector[Vector[Double]]) ⇒ Vector[Double], genomeSize: Int, historySize: Int = 100, cloneProbability: Double = 0.2, operatorExploration: Double = 0.1) extends Product with Serializable

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  4. case class OpenMOLE(pattern: (Vector[Double]) ⇒ Vector[Int], aggregation: (Vector[Vector[Double]]) ⇒ Vector[Double], genomeSize: Int, historySize: Int, cloneProbability: Double, operatorExploration: Double) extends Product with Serializable

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Value Members

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

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. object Genome extends Serializable

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  5. object Individual extends Serializable

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  6. object NoisyPSE extends Serializable

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  7. object OpenMOLE extends Serializable

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  8. final def asInstanceOf[T0]: T0

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  9. def boundedGrid(lowBound: Vector[Double], highBound: Vector[Double], definition: Vector[Int])(value: Vector[Double]): Vector[Int]

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  10. def breeding(lambda: Int, aggregation: (Vector[Vector[Double]]) ⇒ Vector[Double], pattern: (Vector[Double]) ⇒ Vector[Int], cloneProbability: Double, operatorExploration: Double): Breeding[[β]IndexedStateT[IO, mgo.EvolutionData[Map[Vector[Int], Int]], mgo.EvolutionData[Map[Vector[Int], Int]], β], Individual, Genome]

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  11. def buildGenome(values: Vector[Double], operator: Maybe[Int]): Genome

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  12. def buildIndividual(genome: Genome, phenotype: Vector[Double]): Individual

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  13. def clone(): AnyRef

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  14. def elitism(pattern: (Vector[Double]) ⇒ Vector[Int], aggregation: (Vector[Vector[Double]]) ⇒ Vector[Double], historySize: Int): Elitism[[β]IndexedStateT[IO, mgo.EvolutionData[Map[Vector[Int], Int]], mgo.EvolutionData[Map[Vector[Int], Int]], β], Individual]

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  15. final def eq(arg0: AnyRef): Boolean

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  16. def equals(arg0: Any): Boolean

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  17. def expression(phenotype: (Random, Vector[Double]) ⇒ Vector[Double]): Expression[(Random, Genome), Individual]

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  18. def finalize(): Unit

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  19. def genomeProfile[G](values: (G) ⇒ Vector[Double], x: Int, nX: Int): Niche[G, Int]

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  20. final def getClass(): Class[_]

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  21. def grid(gridSize: Seq[Double])(value: Vector[Double]): Vector[Int]

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  22. def hashCode(): Int

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  23. implicit def hitMapper: HitMapper[[β]IndexedStateT[IO, mgo.EvolutionData[Map[Vector[Int], Int]], mgo.EvolutionData[Map[Vector[Int], Int]], β], Vector[Int]]

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  24. def initialGenomes(mu: Int, genomeSize: Int): mgo.EvolutionState[HitMap, Vector[Genome]]

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  25. def irregularGrid(axes: Vector[Vector[Double]])(values: Vector[Double]): Vector[Int]

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  26. final def isInstanceOf[T0]: Boolean

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  27. def mapGenomePlotter[G](x: Int, nX: Int, y: Int, nY: Int)(implicit values: Lens[G, Seq[Double]]): Niche[G, (Int, Int)]

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

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  29. final def notify(): Unit

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  30. final def notifyAll(): Unit

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  31. final def synchronized[T0](arg0: ⇒ T0): T0

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  32. def toString(): String

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  33. def vectorPhenotype: PLens[Individual, Individual, Vector[Vector[Double]], Vector[Vector[Double]]]

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  34. def vectorValues: PLens[Genome, Genome, Vector[Double], Vector[Double]]

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  35. final def wait(): Unit

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  36. final def wait(arg0: Long, arg1: Int): Unit

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  37. final def wait(arg0: Long): Unit

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