PetriNet

scalation.simulation.activity.PetriNet
class PetriNet(colors: Array[Color], placeI: Array[PlaceI], placeD: Array[PlaceD], transition: Array[Transition]) extends PetriNetRules

The PetriNet class provides a simulation engine for Hybrid Colored Petri Nets. Reference: "Discrete-event simulation of fluid stochastic Petri Nets"

Value parameters

colors

array of colors for tokens/fluids

placeD

array of continuous places

placeI

array of discrete places

transition

array of timed transitions

Attributes

Graph
Supertypes
class Object
trait Matchable
class Any

Members list

Value members

Constructors

def this(colors: Array[Color], placeI: Array[PlaceI], transition: Array[Transition])

Construct a discrete Petri net (tokens, but no fluids).

Construct a discrete Petri net (tokens, but no fluids).

Value parameters

colors

array of colors for tokens

placeI

array of discrete places

transition

array of timed transitions

Attributes

def this(colors: Array[Color], placeD: Array[PlaceD], transition: Array[Transition])

Construct a continuous Petri net (fluids, but no tokens).

Construct a continuous Petri net (fluids, but no tokens).

Value parameters

colors

array of colors for fluids

placeD

array of continuous places

transition

array of timed transitions

Attributes

Concrete methods

def clock: Double

Get the current time.

Get the current time.

Attributes

def getCommandQueue: ConcurrentLinkedQueue[AnimateCommand]

Get the animation command queue.

Get the animation command queue.

Attributes

def initAnimation(gColors: Array[Color], timeDilationFactor: Double): Unit

Initialize the animation by drawing the Petri net components onto the animation drawing panel using animation commands.

Initialize the animation by drawing the Petri net components onto the animation drawing panel using animation commands.

Value parameters

gColors

the colors for nodes and edges in the graph i.e., discrete-places, continuous-places, transitions and arcs

timeDilationFactor

time dilation is used to speed up/slow down animation

Attributes

def simulate(tStart: Double, tStop: Double): Unit

Simulate the execution of the Petri Net.

Simulate the execution of the Petri Net.

Value parameters

tStart

the starting time for the simulation

tStop

the stopping time for the simulation

Attributes

override def toString: String

Convert the Petri net to the string representation.

Convert the Petri net to the string representation.

Attributes

Definition Classes
Any

Inherited methods

def calcFiringDelay(v: Variate, w_t: VectorD, t: VectorI, w_f: VectorD, f: VectorD): Double

Function to compute the delay in firing a transition. The base time is given by a random variate. This is adjusted by weight vectors multiplying the number of aggregate tokens and the aggregate amount of fluids summed over all input places: delay = v + w_t * t + w_f * f.

Function to compute the delay in firing a transition. The base time is given by a random variate. This is adjusted by weight vectors multiplying the number of aggregate tokens and the aggregate amount of fluids summed over all input places: delay = v + w_t * t + w_f * f.

Value parameters

f

the aggregate fluid level vector (summed over all input places)

t

the aggregate token vector (summed over all input places)

v

the random variate used to compute base firing time

w_f

the weight for the fluid vector

w_t

the weight for the token vector

Attributes

Inherited from:
PetriNetRules
def fluidFlow(f: VectorD, derv: Array[Derivative], t0: Double, d: Double): VectorD

Compute the amount of fluid to flow over an arc according to the system of first-order Ordinary Differential Equation 'ODE's: "integral 'derv' from t0 to t". Supports ODE base flow models.

Compute the amount of fluid to flow over an arc according to the system of first-order Ordinary Differential Equation 'ODE's: "integral 'derv' from t0 to t". Supports ODE base flow models.

Value parameters

d

the time delay

derv

the array of derivative functions

f

the fluid vector (amount of fluid per color)

t0

the current time

Attributes

Inherited from:
PetriNetRules
def fluidFlow(f: VectorD, b: VectorD, r: VectorD, d: Double): VectorD

Compute the amount of fluid to flow over an arc according to the vector expression: b + r * (f-b) * d. If r is 0, returns b. Supports linear (w.r.t. time delay) and constant (d == 0) flow models.

Compute the amount of fluid to flow over an arc according to the vector expression: b + r * (f-b) * d. If r is 0, returns b. Supports linear (w.r.t. time delay) and constant (d == 0) flow models.

Value parameters

b

the constant vector for base fluid flow

d

the time delay

f

the fluid vector (amount of fluid per color)

r

the rate vector (amounts of fluids per unit time)

Attributes

Inherited from:
PetriNetRules
def thresholdD(f: VectorD, b: VectorD): Boolean

Return whether the vector inequality is true: f >= b. The firing threshold should be checked for every incoming arc. If all return true, the transition should fire.

Return whether the vector inequality is true: f >= b. The firing threshold should be checked for every incoming arc. If all return true, the transition should fire.

Value parameters

b

The base constant vector

f

The fluid vector (amount of fluid per color)

Attributes

Inherited from:
PetriNetRules
def thresholdI(t: VectorI, b: VectorI): Boolean

Return whether the vector inequality is true: t >= b. The firing threshold should be checked for every incoming arc. If all return true, the transition should fire.

Return whether the vector inequality is true: t >= b. The firing threshold should be checked for every incoming arc. If all return true, the transition should fire.

Value parameters

b

the base constant vector

t

the token vector (number of tokens per color)

Attributes

Inherited from:
PetriNetRules
def tokenFlow(t: VectorI, b: VectorI, r: VectorI, d: Double): VectorI

Compute the number of tokens to flow over an arc according to the vector expression: b + r * (t-b) * d. If d is 0, returns b. Supports linear (w.r.t. time delay) and constant (d == 0) flow models.

Compute the number of tokens to flow over an arc according to the vector expression: b + r * (t-b) * d. If d is 0, returns b. Supports linear (w.r.t. time delay) and constant (d == 0) flow models.

Value parameters

b

the constant vector for base token flow

d

the time delay

r

the rate vector (number of tokens per unit time)

t

the token vector (number of tokens per color)

Attributes

Inherited from:
PetriNetRules