fr.geocites.marius.model

Marius

trait Marius extends AnyRef

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  1. case class Transacted(cities: Seq[City], supplies: Seq[Double], demands: Seq[Double], transacted: DenseMatrix) extends Product with Serializable

    Technical data structure to memoize the matrix computation

    Technical data structure to memoize the matrix computation

    cities

    the cities

    supplies

    the supplies of the city

    demands

    the demands of the city

    transacted

    the transaction matrix

Abstract Value Members

  1. abstract def distanceDecay: Double

    Decaying effect of distance on interaction

  2. abstract def economicMultiplier: Double

    Factor adjusting the values of production and consumption

  3. abstract def maxStep: Int

    Number of simulation steps

  4. abstract def populationToWealthExponent: Double

    Exponent of the scaling law to convert population into wealth

  5. abstract def sizeEffectOnDemand: Double

    Exponent of the scaling law between demand and population

  6. abstract def sizeEffectOnSupply: Double

    Exponent of the scaling law between supply and population

  7. abstract def wealthToPopulationExponent: Double

    Exponent of the scaling law to convert wealth into population

Concrete Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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

    Stub for bonuses injection.

    Stub for bonuses injection. No bonuses are modeled in this version.

    transacted

    information on all transactions between cities

    returns

    a sequence of bonuses indexed by city index

  6. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )
  7. def demand(population: Double): Double

    Demand of a city from its population

    Demand of a city from its population

    population

    the population the city

    returns

    the demand

  8. def ended(state: State): Boolean

    Stop criterion on a maximum number of state

    Stop criterion on a maximum number of state

    state

    a state of the model

    returns

    true if the simulation is finished

  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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

    Valued balance of the cities resulting from exchanges.

    Valued balance of the cities resulting from exchanges.

    cities

    the cities

    network

    the network of cities

    supplies

    the supplies of the cities indexed by city index

    demands

    the demands of the cities indexed by city index

    returns

    the exchange balance of the cities indexed by city index

  12. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]

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  14. def hashCode(): Int

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  15. def initialCities: Seq[City]

    Create the initial state of the cities

  16. def initialState: State

    Initial state of the model

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

    Compute the interaction potential as a gravity model.

    Compute the interaction potential as a gravity model.

    mass1

    mass of the 1st city

    mass2

    mass of the 2nd city

    distance

    distance between the cities

    returns

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

    Compute the interaction potential matrix of the whole network of city.

    Compute the interaction potential matrix of the whole network of city.

    supplies

    masses of the cities of origin

    demands

    masses of the cities of destination

    network

    the interaction network

    returns

    the interaction potential matrix as an adjacency matrix

  19. final def isInstanceOf[T0]: Boolean

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  20. final def ne(arg0: AnyRef): Boolean

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  21. def nextState(state: State): State

    The next state of the model

    The next state of the model

    state

    the current state

    returns

    the subsequent state

  22. final def notify(): Unit

    Definition Classes
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  23. final def notifyAll(): Unit

    Definition Classes
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  24. def populationToWealth(population: Double): Double

    Estimate the wealth of a city from its population

    Estimate the wealth of a city from its population

    population

    population of the city

    returns

    the estimated wealth

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

    Center the wealth distribution on the population distribution

    Center the wealth distribution on the population distribution

    wealth

    the wealth distribution

    population

    the population distribution

    returns

    the centered wealth distribution

  26. def states: Iterator[Try[State]]

    Iterate through the states of the model

  27. def supply(population: Double): Double

    Supply of a city from its population

    Supply of a city from its population

    population

    the population the city

    returns

    the supply

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

    Definition Classes
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  29. def toString(): String

    Definition Classes
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  30. def totalFixedCosts(transacted: Transacted): Seq[Double]

    Stub for fixed costs injection.

    Stub for fixed costs injection. No fixed cost are modeled in this version.

    transacted

    information on all transactions between cities

    returns

    a sequence of fixed costs indexed by city index

  31. 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

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

    cities

    the cities

    network

    the network of cities

    supplies

    the supplies of the cities indexed by city index

    demands

    the demands of the cities indexed by city index

    returns

    the

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

    The updated population of a city from its updated wealth

    The updated population of a city from its updated wealth

    city

    the city to update

    updatedWealth

    the updated wealth

    returns

    the updated population

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

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

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

    • supply,
    • demand,
    • exchange balance.
    state

    the current state of the model

    returns

  34. final def wait(): Unit

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    @throws( ... )
  35. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  36. final def wait(arg0: Long): Unit

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    @throws( ... )
  37. def wealthToPopulation(wealth: Double): Double

    Convert a quantity of wealth into a quantity of population

    Convert a quantity of wealth into a quantity of population

    wealth

    the stock of wealth

    returns

    the matching population

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