trait PetriNetRules extends AnyRef
The PetriNetRules class is used to define firing rules for the PetriNet class.
It supports both constant flow and linear flow models of token (integer valued)
and fluid (real valued) flow. Typically, in the constant flow model, a base
flow vector is used for the threshold (require at least this number of tokens/amount
of fluid) and the flow (move this number this number of tokens/amount of fluid
over the arc). It is also possible to set the flow below the threshold.
In the the linear flow model, a base flow vector can be augmented by additional
flow that is a function of the residual left after the base is taken and the
time it takes to fire the transition. The total flow may not exceed the the
number/amount at the place. Additional flow models are under development.
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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
- 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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- 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
- 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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