FixedCost

abstract def distanceDecay: Double

Decaying effect of distance on interaction

abstract def economicMultiplier: Double

Factor adjusting the values of production and consumption

abstract def fixedCost: Double

Cost of a transaction

abstract def maxStep: Int

Number of simulation steps

abstract def populationToWealthExponent: Double

Exponent of the scaling law to convert population into wealth

abstract def sizeEffectOnDemand: Double

Exponent of the scaling law between demand and population

abstract def sizeEffectOnSupply: Double

Exponent of the scaling law between supply and population

abstract def wealthToPopulationExponent: Double

Exponent of the scaling law to convert wealth into population

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def bonuses(transacted: Transacted): Seq[Double]

Stub for bonuses injection.

def clone(): AnyRef

def demand(population: Double): Double

Demand of a city from its population

def ended(state: State): Boolean

Stop criterion on a maximum number of state

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def exchangeBalances(cities: Seq[City], network: FullNetwork, supplies: Seq[Double], demands: Seq[Double]): Seq[Double]

Valued balance of the cities resulting from exchanges.

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

def initialCities: Seq[City]

Create the initial state of the cities

def initialState: State

Initial state of the model

def interactionPotential(mass1: Double, mass2: Double, distance: Double): Double

Compute the interaction potential as a gravity model.

def interactionPotentialMatrix(supplies: Seq[Double], demands: Seq[Double], network: FullNetwork): DenseMatrix

Filter the interaction potential matrix

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

def nextState(state: State): State

The next state of the model

final def notify(): Unit

final def notifyAll(): Unit

def populationToWealth(population: Double): Double

Estimate the wealth of a city from its population

def rescaleWealth(wealth: Seq[Double], population: Seq[Double]): Seq[Double]

Center the wealth distribution on the population distribution

def states: Iterator[Try[State]]

Iterate through the states of the model

def supply(population: Double): Double

Supply of a city from its population

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

def totalFixedCosts(t: Transacted): Seq[Double]

Cost implied by the number of transactions

def transactions(cities: Seq[City], network: FullNetwork, supplies: Seq[Double], demands: Seq[Double]): DenseMatrix

Match cities according to their interaction potential and compute the transacted quantity

def updatedPopulation(city: City, updatedWealth: Double): Double

The updated population of a city from its updated wealth

def updatedWealths(state: State): Seq[Double]

The updated wealth of the cities as a result of economic processes:

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

def wealthToPopulation(wealth: Double): Double

Convert a quantity of wealth into a quantity of population