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 cle1d(n: Spn[DoubleState], d: DoubleState, dt: Double = 0.01): (Seq[DoubleState], Time, Time) => Seq[DoubleState]

   The 1d spatial CLE algorithm

   The 1d spatial CLE algorithm

   n

   A Spn[DoubleState] model for simulation

   d

   A vector of diffusion coefficients - one for each species

   dt

   Time step of the simulation algorithm

   returns

   A function with type signature (x0: GenSeq[DoubleState], t0: Time, deltat: Time) => GenSeq[DoubleState] which will simulate the state of the system at time t0+deltat given initial state x0 and initial time t0

6.  def cle2d(n: Spn[DoubleState], d: DoubleState, dt: Double = 0.01): (PMatrix[DoubleState], Time, Time) => PMatrix[DoubleState]

   The 2d spatial CLE algorithm

   The 2d spatial CLE algorithm

   n

   A Spn[DoubleState] model for simulation

   d

   A vector of diffusion coefficients - one for each species

   dt

   Time step of the simulation algorithm

   returns

   A function with type signature (x0: PMatrix[DoubleState], t0: Time, deltat: Time) => PMatrix[DoubleState] which will simulate the state of the system at time t0+deltat given initial state x0 and initial time t0

7.  def clone(): AnyRef

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   @throws(classOf[java.lang.CloneNotSupportedException]) @native()

8.  final def eq(arg0: AnyRef): Boolean

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9.  def equals(arg0: AnyRef): Boolean

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10.  def euler1d(n: Spn[DoubleState], d: DoubleState, dt: Double = 0.01): (Seq[DoubleState], Time, Time) => Seq[DoubleState]

    The 1d spatial Euler algorithm

    The 1d spatial Euler algorithm

    n

    A Spn[DoubleState] model for simulation

    d

    A vector of diffusion coefficients - one for each species

    dt

    Time step of the simulation algorithm

    returns

    A function with type signature (x0: GenSeq[DoubleState], t0: Time, deltat: Time) => GenSeq[DoubleState] which will simulate the state of the system at time t0+deltat given initial state x0 and initial time t0

11.  def euler2d(n: Spn[DoubleState], d: DoubleState, dt: Double = 0.01): (PMatrix[DoubleState], Time, Time) => PMatrix[DoubleState]

    The 2d spatial Euler algorithm

    The 2d spatial Euler algorithm

    n

    A Spn[DoubleState] model for simulation

    d

    A vector of diffusion coefficients - one for each species

    dt

    Time step of the simulation algorithm

    returns

    A function with type signature (x0: PMatrix[DoubleState], t0: Time, deltat: Time) => PMatrix[DoubleState] which will simulate the state of the system at time t0+deltat given initial state x0 and initial time t0

12.  def finalize(): Unit

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

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    @native()

14.  def gillespie1d(n: Spn[IntState], d: DoubleState, minH: Double = 1e-20, maxH: Double = 1e6): (Seq[IntState], Time, Time) => Seq[IntState]

    The 1d spatial Gillespie algorithm

    The 1d spatial Gillespie algorithm

    n

    A Spn[IntState] model for simulation

    d

    A vector of diffusion coefficients - one for each species

    minH

    Threshold for treating hazard as zero

    maxH

    Threshold for terminating simulation early

    returns

    A function with type signature (x0: GenSeq[IntState], t0: Time, deltat: Time) => GenSeq[IntState] which will simulate the state of the system at time t0+deltat given initial state x0 and initial time t0

15.  def gillespie2d(n: Spn[IntState], d: DoubleState, minH: Double = 1e-20, maxH: Double = 1e6): (PMatrix[IntState], Time, Time) => PMatrix[IntState]

    The 2d spatial Gillespie algorithm

    The 2d spatial Gillespie algorithm

    n

    A Spn[IntState] model for simulation

    d

    A vector of diffusion coefficients - one for each species

    minH

    Threshold for treating hazard as zero

    maxH

    Threshold for terminating simulation early

    returns

    A function with type signature (x0: PMatrix[IntState], t0: Time, deltat: Time) => PMatrix[IntState] which will simulate the state of the system at time t0+deltat given initial state x0 and initial time t0

16.  def hashCode(): Int

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17.  final def isInstanceOf[T0]: Boolean

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18.  final def ne(arg0: AnyRef): Boolean

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19.  final def notify(): Unit

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    @native()

20.  final def notifyAll(): Unit

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    @native()

21.  def plotTs1d[S](ts: Ts[Seq[S]])(implicit arg0: State[S]): Unit

    Plot the output of a 1d time series simulation.

    Plot the output of a 1d time series simulation. Called solely for the side-effect of rendering a plot on the console.

    ts

    Output from a 1d spatial time series simulation

22.  final def synchronized[T0](arg0: => T0): T0

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23.  def toString(): String

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24.  final def wait(): Unit

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    @throws(classOf[java.lang.InterruptedException])

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

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    @throws(classOf[java.lang.InterruptedException])

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

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    @throws(classOf[java.lang.InterruptedException]) @native()