class ArcD extends PetriNetRules with Identifiable
The ArcD class represents an arc connecting continuous place with a
transition. If incoming is true the arc is from the place to transition,
otherwise it is from the transition to the place (outgoing).
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- new ArcD(place: PlaceD, transition: Transition, incoming: Boolean, minFluids: VectorD, rates: VectorD = null, derv: Array[Derivative] = null, testArc: Boolean = false, scaleFactor: Double = 1.0)
- place
the continuous place at one end of the arc
- transition
the transition the other end of the arc
- incoming
whether the arc goes into a transition
- minFluids
minimum amount of fluid to transport over the arc
- rates
the rate vector for the linear flow model
- derv
the array of derivative functions for ODE's
- testArc
whether the arc is a test arc meaning the tokens/fluids stay
- scaleFactor
the scale factor for the firing delay
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- final def !=(arg0: Any): Boolean
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- def _fluidFlow(fluids: VectorD, time: Double, firingDelay: Double): VectorD
Compute the amount of fluid of each color to flow over 'this' arc.
Compute the amount of fluid of each color to flow over 'this' arc.
- fluids
the amount of fluid available
- time
the current time
- firingDelay
the time it takes for the transition to fire
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- def calcFiringDelay(v: Variate, w_t: VectorD, t: VectorI, w_f: VectorD, f: VectorD): Double
Function to compute the delay in firing a transition.
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.
- v
the random variate used to compute base firing time
- w_t
the weight for the token vector
- t
the aggregate token vector (summed over all input places)
- w_f
the weight for the fluid vector
- f
the aggregate fluid level vector (summed over all input places)
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- 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".
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.
- f
the fluid vector (amount of fluid per color)
- derv
the array of derivative functions
- t0
the current time
- d
the time delay
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- def fluidFlow(f: VectorD, b: VectorD, r: VectorD = null, d: Double = 0): VectorD
Compute the amount of fluid to flow over an arc according to the vector expression: b + r * (f-b) * d.
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.
- f
the fluid vector (amount of fluid per color)
- b
the constant vector for base fluid flow
- r
the rate vector (amounts of fluids per unit time)
- d
the time delay
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- val minFluids: VectorD
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- val place: PlaceD
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- def thresholdD(f: VectorD, b: VectorD): Boolean
Return whether the vector inequality is true: f >= b.
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.
- f
The fluid vector (amount of fluid per color)
- b
The base constant vector
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- def thresholdI(t: VectorI, b: VectorI): Boolean
Return whether the vector inequality is true: t >= b.
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.
- t
the token vector (number of tokens per color)
- b
the base constant vector
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- def tokenFlow(t: VectorI, b: VectorI, r: VectorI = null, d: Double = 0): VectorI
Compute the number of tokens to flow over an arc according to the vector expression: b + r * (t-b) * d.
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.
- t
the token vector (number of tokens per color)
- b
the constant vector for base token flow
- r
the rate vector (number of tokens per unit time)
- d
the time delay
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- val transition: Transition
- final def wait(arg0: Long, arg1: Int): Unit
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