Spatial

object Spatial

All functions and utilities relating to spatial simulation

class Object
trait Matchable
class Any

Value members

Concrete methods

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

The 1d spatial CLE algorithm

The 1d spatial CLE algorithm

Value Params
d

A vector of diffusion coefficients - one for each species

dt

Time step of the simulation algorithm

n

A Spn[DoubleState] model for simulation

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

The 2d spatial CLE algorithm

The 2d spatial CLE algorithm

Value Params
d

A vector of diffusion coefficients - one for each species

dt

Time step of the simulation algorithm

n

A Spn[DoubleState] model for simulation

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

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

The 1d spatial Euler algorithm

The 1d spatial Euler algorithm

Value Params
d

A vector of diffusion coefficients - one for each species

dt

Time step of the simulation algorithm

n

A Spn[DoubleState] model for simulation

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

The 2d spatial Euler algorithm

The 2d spatial Euler algorithm

Value Params
d

A vector of diffusion coefficients - one for each species

dt

Time step of the simulation algorithm

n

A Spn[DoubleState] model for simulation

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

def gillespie1d(n: Spn[IntState], d: DoubleState, minH: Double, maxH: Double): (Seq[IntState], Time, Time) => Seq[IntState]

The 1d spatial Gillespie algorithm

The 1d spatial Gillespie algorithm

Value Params
d

A vector of diffusion coefficients - one for each species

maxH

Threshold for terminating simulation early

minH

Threshold for treating hazard as zero

n

A Spn[IntState] model for simulation

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

def gillespie2d(n: Spn[IntState], d: DoubleState, minH: Double, maxH: Double): (PMatrix[IntState], Time, Time) => PMatrix[IntState]

The 2d spatial Gillespie algorithm

The 2d spatial Gillespie algorithm

Value Params
d

A vector of diffusion coefficients - one for each species

maxH

Threshold for terminating simulation early

minH

Threshold for treating hazard as zero

n

A Spn[IntState] model for simulation

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

def plotTs1d[S](ts: Ts[Seq[S]])(implicit evidence$1: State[S]): Unit

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

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

Value Params
ts

Output from a 1d spatial time series simulation