Spatial

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): (GenSeq[DoubleState], Time, Time) ⇒ GenSeq[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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8. final def eq(arg0: AnyRef): Boolean

   

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9. def equals(arg0: Any): Boolean

   

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10. def euler1d(n: Spn[DoubleState], d: DoubleState, dt: Double = 0.01): (GenSeq[DoubleState], Time, Time) ⇒ GenSeq[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[_]

    

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14. def gillespie1d(n: Spn[IntState], d: DoubleState, minH: Double = 1e-20, maxH: Double = 1e6): (GenSeq[IntState], Time, Time) ⇒ GenSeq[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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20. final def notifyAll(): Unit

    

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21. def plotTs1d[S](ts: Ts[GenSeq[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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25. final def wait(arg0: Long, arg1: Int): Unit

    

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

    

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