Object

smfsb

Types

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object Types

Object containing basic types used throughout the library.

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Type Members

  1. trait CsvRow[T] extends AnyRef

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    Type class for vectors that can be rendered to a CSV string (and a Breeze DenseVector[Double]), extended by State

  2. implicit class CsvRowSyntax[T] extends AnyRef

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    Syntax for CsvRow

  3. trait DataSet[D] extends AnyRef

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    Data set type class, for ABC methods

  4. type DoubleState = DenseVector[Double]

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    Alias for a Breeze DenseVector[Double]

  5. type HazardVec = DenseVector[Double]

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    Type for a SPN hazard vector

  6. type IntState = DenseVector[Int]

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    Alias for a Breeze DenseVector[Int]

  7. type LogLik = Double

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    Type representing log-likelihoods - just an alias for Double.

    Type representing log-likelihoods - just an alias for Double. All likelihoods in this library are on a log scale. There should be no raw likelihoods passed into or out of any user-facing function.

  8. case class MarkedSpn[S](species: List[String], m: S, pre: DenseMatrix[Int], post: DenseMatrix[Int], h: (S, Time) ⇒ HazardVec)(implicit evidence$2: State[S]) extends Spn[S] with Product with Serializable

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    Case class for SPNs that include an initial marking

  9. trait Observation[O] extends CsvRow[O]

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    Observation type class, with implementations for Ints and Doubles

  10. sealed trait Spn[S] extends AnyRef

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    Main trait for stochastic Petri nets (SPNs)

  11. trait State[S] extends CsvRow[S]

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    State type class, with implementations for Breeze DenseVector Ints and Doubles

  12. trait Thinnable[F[_]] extends AnyRef

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    A type class for things which can be "thinned", with an implementation for Stream.

    A type class for things which can be "thinned", with an implementation for Stream. Useful for MCMC algorithms.

  13. implicit class ThinnableSyntax[T, F[T]] extends AnyRef

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    Provision of the .thin syntax for Thinnable things

  14. type Time = Double

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    Type representing time, but just an alias for Double

  15. type Ts[S] = List[(Time, S)]

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    The main time series class, for representing output from simulation functions, and for observed time course data

  16. case class UnmarkedSpn[S](species: List[String], pre: DenseMatrix[Int], post: DenseMatrix[Int], h: (S, Time) ⇒ HazardVec)(implicit evidence$1: State[S]) extends Spn[S] with Product with Serializable

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    Case class for SPNs without an initial marking

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. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. implicit val dvdObs: Observation[DoubleState]

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    Evidence that DoubleState belongs to the Observation type class

  7. implicit val dvdState: State[DoubleState]

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    Evidence that DoubleState belongs to the State type class

  8. implicit val dviObs: Observation[IntState]

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    Evidence that IntState belongs to the Observation type class

  9. implicit val dviState: State[IntState]

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    Evidence that IntState belongs to the State type class

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

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  11. def equals(arg0: Any): Boolean

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  12. def finalize(): Unit

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

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. implicit val streamThinnable: Thinnable[Stream]

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    A Thinnable instance for Stream

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

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  21. def toString(): String

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  22. implicit val tsdsDs: DataSet[Ts[DoubleState]]

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    Evidence that Ts[DoubleState] is a DataSet

  23. implicit val tsisDs: DataSet[Ts[IntState]]

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    Evidence that Ts[IntState] is a DataSet

  24. final def wait(): Unit

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

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

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